From 3f7e5f54a375c896e68a938932f926093c169051 Mon Sep 17 00:00:00 2001 From: Jose Miguel Ladino Mendez <ladinoj@jupyterMiLAB> Date: Thu, 18 Feb 2021 23:28:44 -0500 Subject: [PATCH] Entrega de tarea clase05 desde jupyterhub --- .gitignore | 1 + Entrega.html | 20313 ++++++++++++++++++++++++++++++++++++++++++++++++ Entrega.ipynb | 4328 +++++++++++ README.md | 56 + 4 files changed, 24698 insertions(+) create mode 100644 .gitignore create mode 100644 Entrega.html create mode 100644 Entrega.ipynb diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..87620ac --- /dev/null +++ b/.gitignore @@ -0,0 +1 @@ +.ipynb_checkpoints/ diff --git a/Entrega.html b/Entrega.html new file mode 100644 index 0000000..61c7c05 --- /dev/null +++ b/Entrega.html @@ -0,0 +1,20313 @@ +<!DOCTYPE html> +<html> +<head><meta charset="utf-8" /> +<meta name="viewport" content="width=device-width, initial-scale=1.0"> + +<title>Entrega</title><script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script> + + + + +<style type="text/css"> + pre { line-height: 125%; margin: 0; } +td.linenos pre { color: #000000; background-color: #f0f0f0; padding-left: 5px; padding-right: 5px; } +span.linenos { color: #000000; background-color: #f0f0f0; padding-left: 5px; padding-right: 5px; } +td.linenos pre.special { color: #000000; background-color: #ffffc0; padding-left: 5px; padding-right: 5px; } +span.linenos.special { color: #000000; background-color: #ffffc0; padding-left: 5px; padding-right: 5px; } +.highlight .hll { background-color: var(--jp-cell-editor-active-background) } +.highlight { background: var(--jp-cell-editor-background); color: var(--jp-mirror-editor-variable-color) } +.highlight .c { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment */ +.highlight .err { color: var(--jp-mirror-editor-error-color) } /* Error */ +.highlight .k { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword */ +.highlight .o { color: var(--jp-mirror-editor-operator-color); font-weight: bold } /* Operator */ +.highlight .p { color: var(--jp-mirror-editor-punctuation-color) } /* Punctuation */ +.highlight .ch { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Hashbang */ +.highlight .cm { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Multiline */ +.highlight .cp { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Preproc */ +.highlight .cpf { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.PreprocFile */ +.highlight .c1 { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Single */ +.highlight .cs { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Special */ +.highlight .kc { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Constant */ +.highlight .kd { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Declaration */ +.highlight .kn { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Namespace */ +.highlight .kp { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Pseudo */ +.highlight .kr { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Reserved */ +.highlight .kt { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Type */ +.highlight .m { color: var(--jp-mirror-editor-number-color) } /* Literal.Number */ +.highlight .s { color: var(--jp-mirror-editor-string-color) } /* Literal.String */ +.highlight .ow { color: var(--jp-mirror-editor-operator-color); font-weight: bold } /* Operator.Word */ +.highlight .w { color: var(--jp-mirror-editor-variable-color) } /* Text.Whitespace */ +.highlight .mb { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Bin */ +.highlight .mf { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Float */ +.highlight .mh { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Hex */ +.highlight .mi { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Integer */ +.highlight .mo { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Oct */ +.highlight .sa { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Affix */ +.highlight .sb { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Backtick */ +.highlight .sc { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Char */ +.highlight .dl { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Delimiter */ +.highlight .sd { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Doc */ +.highlight .s2 { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Double */ +.highlight .se { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Escape */ +.highlight .sh { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Heredoc */ +.highlight .si { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Interpol */ +.highlight .sx { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Other */ +.highlight .sr { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Regex */ +.highlight .s1 { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Single */ +.highlight .ss { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Symbol */ +.highlight .il { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Integer.Long */ + </style> + + + +<style type="text/css"> +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/* + * Mozilla scrollbar styling + */ + +/* use standard opaque scrollbars for most nodes */ +[data-jp-theme-scrollbars='true'] { + scrollbar-color: rgb(var(--jp-scrollbar-thumb-color)) + var(--jp-scrollbar-background-color); +} + +/* for code nodes, use a transparent style of scrollbar. These selectors + * will match lower in the tree, and so will override the above */ +[data-jp-theme-scrollbars='true'] .CodeMirror-hscrollbar, +[data-jp-theme-scrollbars='true'] .CodeMirror-vscrollbar { + scrollbar-color: rgba(var(--jp-scrollbar-thumb-color), 0.5) transparent; +} + +/* + * Webkit scrollbar styling + */ + +/* use standard opaque scrollbars for most nodes */ + +[data-jp-theme-scrollbars='true'] ::-webkit-scrollbar, +[data-jp-theme-scrollbars='true'] ::-webkit-scrollbar-corner { + background: var(--jp-scrollbar-background-color); +} + +[data-jp-theme-scrollbars='true'] ::-webkit-scrollbar-thumb { + background: rgb(var(--jp-scrollbar-thumb-color)); + border: var(--jp-scrollbar-thumb-margin) solid transparent; + background-clip: content-box; + border-radius: var(--jp-scrollbar-thumb-radius); +} + +[data-jp-theme-scrollbars='true'] ::-webkit-scrollbar-track:horizontal { + border-left: var(--jp-scrollbar-endpad) solid + var(--jp-scrollbar-background-color); + border-right: var(--jp-scrollbar-endpad) solid + var(--jp-scrollbar-background-color); +} + +[data-jp-theme-scrollbars='true'] ::-webkit-scrollbar-track:vertical { + border-top: var(--jp-scrollbar-endpad) solid + var(--jp-scrollbar-background-color); + border-bottom: var(--jp-scrollbar-endpad) solid + var(--jp-scrollbar-background-color); +} + +/* for code nodes, use a transparent style of scrollbar */ + +[data-jp-theme-scrollbars='true'] .CodeMirror-hscrollbar::-webkit-scrollbar, +[data-jp-theme-scrollbars='true'] .CodeMirror-vscrollbar::-webkit-scrollbar, +[data-jp-theme-scrollbars='true'] + .CodeMirror-hscrollbar::-webkit-scrollbar-corner, +[data-jp-theme-scrollbars='true'] + .CodeMirror-vscrollbar::-webkit-scrollbar-corner { + background-color: transparent; +} + +[data-jp-theme-scrollbars='true'] + .CodeMirror-hscrollbar::-webkit-scrollbar-thumb, +[data-jp-theme-scrollbars='true'] + .CodeMirror-vscrollbar::-webkit-scrollbar-thumb { + background: rgba(var(--jp-scrollbar-thumb-color), 0.5); + border: var(--jp-scrollbar-thumb-margin) solid transparent; + background-clip: content-box; + border-radius: var(--jp-scrollbar-thumb-radius); +} + +[data-jp-theme-scrollbars='true'] + .CodeMirror-hscrollbar::-webkit-scrollbar-track:horizontal { + border-left: var(--jp-scrollbar-endpad) solid transparent; + border-right: var(--jp-scrollbar-endpad) solid transparent; +} + +[data-jp-theme-scrollbars='true'] + .CodeMirror-vscrollbar::-webkit-scrollbar-track:vertical { + border-top: var(--jp-scrollbar-endpad) solid transparent; + border-bottom: var(--jp-scrollbar-endpad) solid transparent; +} + +/* + * Phosphor + */ + +.lm-ScrollBar[data-orientation='horizontal'] { + min-height: 16px; + max-height: 16px; + min-width: 45px; + border-top: 1px solid #a0a0a0; +} + +.lm-ScrollBar[data-orientation='vertical'] { + min-width: 16px; + max-width: 16px; + min-height: 45px; + border-left: 1px solid #a0a0a0; +} + +.lm-ScrollBar-button { + background-color: #f0f0f0; + background-position: center center; + min-height: 15px; + max-height: 15px; + min-width: 15px; + max-width: 15px; +} + +.lm-ScrollBar-button:hover { + background-color: #dadada; +} + +.lm-ScrollBar-button.lm-mod-active { + background-color: #cdcdcd; +} + +.lm-ScrollBar-track { + background: #f0f0f0; +} + +.lm-ScrollBar-thumb { + background: #cdcdcd; +} + +.lm-ScrollBar-thumb:hover { + background: #bababa; +} + +.lm-ScrollBar-thumb.lm-mod-active { + background: #a0a0a0; +} + +.lm-ScrollBar[data-orientation='horizontal'] .lm-ScrollBar-thumb { + height: 100%; + min-width: 15px; + border-left: 1px solid #a0a0a0; + border-right: 1px solid #a0a0a0; +} + +.lm-ScrollBar[data-orientation='vertical'] .lm-ScrollBar-thumb { + width: 100%; + min-height: 15px; + border-top: 1px solid #a0a0a0; + border-bottom: 1px solid #a0a0a0; +} + +.lm-ScrollBar[data-orientation='horizontal'] + .lm-ScrollBar-button[data-action='decrement'] { + background-image: var(--jp-icon-caret-left); + background-size: 17px; +} + +.lm-ScrollBar[data-orientation='horizontal'] + .lm-ScrollBar-button[data-action='increment'] { + background-image: var(--jp-icon-caret-right); + background-size: 17px; +} + +.lm-ScrollBar[data-orientation='vertical'] + .lm-ScrollBar-button[data-action='decrement'] { + background-image: var(--jp-icon-caret-up); + background-size: 17px; +} + +.lm-ScrollBar[data-orientation='vertical'] + .lm-ScrollBar-button[data-action='increment'] { + background-image: var(--jp-icon-caret-down); + background-size: 17px; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Copyright (c) 2014-2017, PhosphorJS Contributors +| +| Distributed under the terms of the BSD 3-Clause License. +| +| The full license is in the file LICENSE, distributed with this software. +|----------------------------------------------------------------------------*/ + + +/* <DEPRECATED> */ .p-Widget, /* </DEPRECATED> */ +.lm-Widget { + box-sizing: border-box; + position: relative; + overflow: hidden; + cursor: default; +} + + +/* <DEPRECATED> */ .p-Widget.p-mod-hidden, /* </DEPRECATED> */ +.lm-Widget.lm-mod-hidden { + display: none !important; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Copyright (c) 2014-2017, PhosphorJS Contributors +| +| Distributed under the terms of the BSD 3-Clause License. +| +| The full license is in the file LICENSE, distributed with this software. +|----------------------------------------------------------------------------*/ + + +/* <DEPRECATED> */ .p-CommandPalette, /* </DEPRECATED> */ +.lm-CommandPalette { + display: flex; + flex-direction: column; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; +} + + +/* <DEPRECATED> */ .p-CommandPalette-search, /* </DEPRECATED> */ +.lm-CommandPalette-search { + flex: 0 0 auto; +} + + +/* <DEPRECATED> */ .p-CommandPalette-content, /* </DEPRECATED> */ +.lm-CommandPalette-content { + flex: 1 1 auto; + margin: 0; + padding: 0; + min-height: 0; + overflow: auto; + list-style-type: none; +} + + +/* <DEPRECATED> */ .p-CommandPalette-header, /* </DEPRECATED> */ +.lm-CommandPalette-header { + overflow: hidden; + white-space: nowrap; + text-overflow: ellipsis; +} + + +/* <DEPRECATED> */ .p-CommandPalette-item, /* </DEPRECATED> */ +.lm-CommandPalette-item { + display: flex; + flex-direction: row; +} + + +/* <DEPRECATED> */ .p-CommandPalette-itemIcon, /* </DEPRECATED> */ +.lm-CommandPalette-itemIcon { + flex: 0 0 auto; +} + + +/* <DEPRECATED> */ .p-CommandPalette-itemContent, /* </DEPRECATED> */ +.lm-CommandPalette-itemContent { + flex: 1 1 auto; + overflow: hidden; +} + + +/* <DEPRECATED> */ .p-CommandPalette-itemShortcut, /* </DEPRECATED> */ +.lm-CommandPalette-itemShortcut { + flex: 0 0 auto; +} + + +/* <DEPRECATED> */ .p-CommandPalette-itemLabel, /* </DEPRECATED> */ +.lm-CommandPalette-itemLabel { + overflow: hidden; + white-space: nowrap; + text-overflow: ellipsis; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Copyright (c) 2014-2017, PhosphorJS Contributors +| +| Distributed under the terms of the BSD 3-Clause License. +| +| The full license is in the file LICENSE, distributed with this software. +|----------------------------------------------------------------------------*/ + + +/* <DEPRECATED> */ .p-DockPanel, /* </DEPRECATED> */ +.lm-DockPanel { + z-index: 0; +} + + +/* <DEPRECATED> */ .p-DockPanel-widget, /* </DEPRECATED> */ +.lm-DockPanel-widget { + z-index: 0; +} + + +/* <DEPRECATED> */ .p-DockPanel-tabBar, /* </DEPRECATED> */ +.lm-DockPanel-tabBar { + z-index: 1; +} + + +/* <DEPRECATED> */ .p-DockPanel-handle, /* </DEPRECATED> */ +.lm-DockPanel-handle { + z-index: 2; +} + + +/* <DEPRECATED> */ .p-DockPanel-handle.p-mod-hidden, /* </DEPRECATED> */ +.lm-DockPanel-handle.lm-mod-hidden { + display: none !important; +} + + +/* <DEPRECATED> */ .p-DockPanel-handle:after, /* </DEPRECATED> */ +.lm-DockPanel-handle:after { + position: absolute; + top: 0; + left: 0; + width: 100%; + height: 100%; + content: ''; +} + + +/* <DEPRECATED> */ +.p-DockPanel-handle[data-orientation='horizontal'], +/* </DEPRECATED> */ +.lm-DockPanel-handle[data-orientation='horizontal'] { + cursor: ew-resize; +} + + +/* <DEPRECATED> */ +.p-DockPanel-handle[data-orientation='vertical'], +/* </DEPRECATED> */ +.lm-DockPanel-handle[data-orientation='vertical'] { + cursor: ns-resize; +} + + +/* <DEPRECATED> */ +.p-DockPanel-handle[data-orientation='horizontal']:after, +/* </DEPRECATED> */ +.lm-DockPanel-handle[data-orientation='horizontal']:after { + left: 50%; + min-width: 8px; + transform: translateX(-50%); +} + + +/* <DEPRECATED> */ +.p-DockPanel-handle[data-orientation='vertical']:after, +/* </DEPRECATED> */ +.lm-DockPanel-handle[data-orientation='vertical']:after { + top: 50%; + min-height: 8px; + transform: translateY(-50%); +} + + +/* <DEPRECATED> */ .p-DockPanel-overlay, /* </DEPRECATED> */ +.lm-DockPanel-overlay { + z-index: 3; + box-sizing: border-box; + pointer-events: none; +} + + +/* <DEPRECATED> */ .p-DockPanel-overlay.p-mod-hidden, /* </DEPRECATED> */ +.lm-DockPanel-overlay.lm-mod-hidden { + display: none !important; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Copyright (c) 2014-2017, PhosphorJS Contributors +| +| Distributed under the terms of the BSD 3-Clause License. +| +| The full license is in the file LICENSE, distributed with this software. +|----------------------------------------------------------------------------*/ + + +/* <DEPRECATED> */ .p-Menu, /* </DEPRECATED> */ +.lm-Menu { + z-index: 10000; + position: absolute; + white-space: nowrap; + overflow-x: hidden; + overflow-y: auto; + outline: none; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; +} + + +/* <DEPRECATED> */ .p-Menu-content, /* </DEPRECATED> */ +.lm-Menu-content { + margin: 0; + padding: 0; + display: table; + list-style-type: none; +} + + +/* <DEPRECATED> */ .p-Menu-item, /* </DEPRECATED> */ +.lm-Menu-item { + display: table-row; +} + + +/* <DEPRECATED> */ +.p-Menu-item.p-mod-hidden, +.p-Menu-item.p-mod-collapsed, +/* </DEPRECATED> */ +.lm-Menu-item.lm-mod-hidden, +.lm-Menu-item.lm-mod-collapsed { + display: none !important; +} + + +/* <DEPRECATED> */ +.p-Menu-itemIcon, +.p-Menu-itemSubmenuIcon, +/* </DEPRECATED> */ +.lm-Menu-itemIcon, +.lm-Menu-itemSubmenuIcon { + display: table-cell; + text-align: center; +} + + +/* <DEPRECATED> */ .p-Menu-itemLabel, /* </DEPRECATED> */ +.lm-Menu-itemLabel { + display: table-cell; + text-align: left; +} + + +/* <DEPRECATED> */ .p-Menu-itemShortcut, /* </DEPRECATED> */ +.lm-Menu-itemShortcut { + display: table-cell; + text-align: right; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Copyright (c) 2014-2017, PhosphorJS Contributors +| +| Distributed under the terms of the BSD 3-Clause License. +| +| The full license is in the file LICENSE, distributed with this software. +|----------------------------------------------------------------------------*/ + + +/* <DEPRECATED> */ .p-MenuBar, /* </DEPRECATED> */ +.lm-MenuBar { + outline: none; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; +} + + +/* <DEPRECATED> */ .p-MenuBar-content, /* </DEPRECATED> */ +.lm-MenuBar-content { + margin: 0; + padding: 0; + display: flex; + flex-direction: row; + list-style-type: none; +} + + +/* <DEPRECATED> */ .p--MenuBar-item, /* </DEPRECATED> */ +.lm-MenuBar-item { + box-sizing: border-box; +} + + +/* <DEPRECATED> */ +.p-MenuBar-itemIcon, +.p-MenuBar-itemLabel, +/* </DEPRECATED> */ +.lm-MenuBar-itemIcon, +.lm-MenuBar-itemLabel { + display: inline-block; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Copyright (c) 2014-2017, PhosphorJS Contributors +| +| Distributed under the terms of the BSD 3-Clause License. +| +| The full license is in the file LICENSE, distributed with this software. +|----------------------------------------------------------------------------*/ + + +/* <DEPRECATED> */ .p-ScrollBar, /* </DEPRECATED> */ +.lm-ScrollBar { + display: flex; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; +} + + +/* <DEPRECATED> */ +.p-ScrollBar[data-orientation='horizontal'], +/* </DEPRECATED> */ +.lm-ScrollBar[data-orientation='horizontal'] { + flex-direction: row; +} + + +/* <DEPRECATED> */ +.p-ScrollBar[data-orientation='vertical'], +/* </DEPRECATED> */ +.lm-ScrollBar[data-orientation='vertical'] { + flex-direction: column; +} + + +/* <DEPRECATED> */ .p-ScrollBar-button, /* </DEPRECATED> */ +.lm-ScrollBar-button { + box-sizing: border-box; + flex: 0 0 auto; +} + + +/* <DEPRECATED> */ .p-ScrollBar-track, /* </DEPRECATED> */ +.lm-ScrollBar-track { + box-sizing: border-box; + position: relative; + overflow: hidden; + flex: 1 1 auto; +} + + +/* <DEPRECATED> */ .p-ScrollBar-thumb, /* </DEPRECATED> */ +.lm-ScrollBar-thumb { + box-sizing: border-box; + position: absolute; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Copyright (c) 2014-2017, PhosphorJS Contributors +| +| Distributed under the terms of the BSD 3-Clause License. +| +| The full license is in the file LICENSE, distributed with this software. +|----------------------------------------------------------------------------*/ + + +/* <DEPRECATED> */ .p-SplitPanel-child, /* </DEPRECATED> */ +.lm-SplitPanel-child { + z-index: 0; +} + + +/* <DEPRECATED> */ .p-SplitPanel-handle, /* </DEPRECATED> */ +.lm-SplitPanel-handle { + z-index: 1; +} + + +/* <DEPRECATED> */ .p-SplitPanel-handle.p-mod-hidden, /* </DEPRECATED> */ +.lm-SplitPanel-handle.lm-mod-hidden { + display: none !important; +} + + +/* <DEPRECATED> */ .p-SplitPanel-handle:after, /* </DEPRECATED> */ +.lm-SplitPanel-handle:after { + position: absolute; + top: 0; + left: 0; + width: 100%; + height: 100%; + content: ''; +} + + +/* <DEPRECATED> */ +.p-SplitPanel[data-orientation='horizontal'] > .p-SplitPanel-handle, +/* </DEPRECATED> */ +.lm-SplitPanel[data-orientation='horizontal'] > .lm-SplitPanel-handle { + cursor: ew-resize; +} + + +/* <DEPRECATED> */ +.p-SplitPanel[data-orientation='vertical'] > .p-SplitPanel-handle, +/* </DEPRECATED> */ +.lm-SplitPanel[data-orientation='vertical'] > .lm-SplitPanel-handle { + cursor: ns-resize; +} + + +/* <DEPRECATED> */ +.p-SplitPanel[data-orientation='horizontal'] > .p-SplitPanel-handle:after, +/* </DEPRECATED> */ +.lm-SplitPanel[data-orientation='horizontal'] > .lm-SplitPanel-handle:after { + left: 50%; + min-width: 8px; + transform: translateX(-50%); +} + + +/* <DEPRECATED> */ +.p-SplitPanel[data-orientation='vertical'] > .p-SplitPanel-handle:after, +/* </DEPRECATED> */ +.lm-SplitPanel[data-orientation='vertical'] > .lm-SplitPanel-handle:after { + top: 50%; + min-height: 8px; + transform: translateY(-50%); +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Copyright (c) 2014-2017, PhosphorJS Contributors +| +| Distributed under the terms of the BSD 3-Clause License. +| +| The full license is in the file LICENSE, distributed with this software. +|----------------------------------------------------------------------------*/ + + +/* <DEPRECATED> */ .p-TabBar, /* </DEPRECATED> */ +.lm-TabBar { + display: flex; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; +} + + +/* <DEPRECATED> */ .p-TabBar[data-orientation='horizontal'], /* </DEPRECATED> */ +.lm-TabBar[data-orientation='horizontal'] { + flex-direction: row; +} + + +/* <DEPRECATED> */ .p-TabBar[data-orientation='vertical'], /* </DEPRECATED> */ +.lm-TabBar[data-orientation='vertical'] { + flex-direction: column; +} + + +/* <DEPRECATED> */ .p-TabBar-content, /* </DEPRECATED> */ +.lm-TabBar-content { + margin: 0; + padding: 0; + display: flex; + flex: 1 1 auto; + list-style-type: none; +} + + +/* <DEPRECATED> */ +.p-TabBar[data-orientation='horizontal'] > .p-TabBar-content, +/* </DEPRECATED> */ +.lm-TabBar[data-orientation='horizontal'] > .lm-TabBar-content { + flex-direction: row; +} + + +/* <DEPRECATED> */ +.p-TabBar[data-orientation='vertical'] > .p-TabBar-content, +/* </DEPRECATED> */ +.lm-TabBar[data-orientation='vertical'] > .lm-TabBar-content { + flex-direction: column; +} + + +/* <DEPRECATED> */ .p-TabBar-tab, /* </DEPRECATED> */ +.lm-TabBar-tab { + display: flex; + flex-direction: row; + box-sizing: border-box; + overflow: hidden; +} + + +/* <DEPRECATED> */ +.p-TabBar-tabIcon, +.p-TabBar-tabCloseIcon, +/* </DEPRECATED> */ +.lm-TabBar-tabIcon, +.lm-TabBar-tabCloseIcon { + flex: 0 0 auto; +} + + +/* <DEPRECATED> */ .p-TabBar-tabLabel, /* </DEPRECATED> */ +.lm-TabBar-tabLabel { + flex: 1 1 auto; + overflow: hidden; + white-space: nowrap; +} + + +/* <DEPRECATED> */ .p-TabBar-tab.p-mod-hidden, /* </DEPRECATED> */ +.lm-TabBar-tab.lm-mod-hidden { + display: none !important; +} + + +/* <DEPRECATED> */ .p-TabBar.p-mod-dragging .p-TabBar-tab, /* </DEPRECATED> */ +.lm-TabBar.lm-mod-dragging .lm-TabBar-tab { + position: relative; +} + + +/* <DEPRECATED> */ +.p-TabBar.p-mod-dragging[data-orientation='horizontal'] .p-TabBar-tab, +/* </DEPRECATED> */ +.lm-TabBar.lm-mod-dragging[data-orientation='horizontal'] .lm-TabBar-tab { + left: 0; + transition: left 150ms ease; +} + + +/* <DEPRECATED> */ +.p-TabBar.p-mod-dragging[data-orientation='vertical'] .p-TabBar-tab, +/* </DEPRECATED> */ +.lm-TabBar.lm-mod-dragging[data-orientation='vertical'] .lm-TabBar-tab { + top: 0; + transition: top 150ms ease; +} + + +/* <DEPRECATED> */ +.p-TabBar.p-mod-dragging .p-TabBar-tab.p-mod-dragging +/* </DEPRECATED> */ +.lm-TabBar.lm-mod-dragging .lm-TabBar-tab.lm-mod-dragging { + transition: none; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Copyright (c) 2014-2017, PhosphorJS Contributors +| +| Distributed under the terms of the BSD 3-Clause License. +| +| The full license is in the file LICENSE, distributed with this software. +|----------------------------------------------------------------------------*/ + + +/* <DEPRECATED> */ .p-TabPanel-tabBar, /* </DEPRECATED> */ +.lm-TabPanel-tabBar { + z-index: 1; +} + + +/* <DEPRECATED> */ .p-TabPanel-stackedPanel, /* </DEPRECATED> */ +.lm-TabPanel-stackedPanel { + z-index: 0; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Copyright (c) 2014-2017, PhosphorJS Contributors +| +| Distributed under the terms of the BSD 3-Clause License. +| +| The full license is in the file LICENSE, distributed with this software. +|----------------------------------------------------------------------------*/ + +@charset "UTF-8"; +/*! + +Copyright 2015-present Palantir Technologies, Inc. All rights reserved. +Licensed under the Apache License, Version 2.0. + +*/ +html{ + -webkit-box-sizing:border-box; + box-sizing:border-box; } + +*, +*::before, +*::after{ + -webkit-box-sizing:inherit; + box-sizing:inherit; } + +body{ + text-transform:none; + line-height:1.28581; + letter-spacing:0; + font-size:14px; + font-weight:400; + color:#182026; + font-family:-apple-system, "BlinkMacSystemFont", "Segoe UI", "Roboto", "Oxygen", "Ubuntu", "Cantarell", "Open Sans", "Helvetica Neue", "Icons16", sans-serif; } + +p{ + margin-top:0; + margin-bottom:10px; } + +small{ + font-size:12px; } + +strong{ + font-weight:600; } + +::-moz-selection{ + background:rgba(125, 188, 255, 0.6); } + +::selection{ + background:rgba(125, 188, 255, 0.6); } +.bp3-heading{ + color:#182026; + font-weight:600; + margin:0 0 10px; + padding:0; } + .bp3-dark .bp3-heading{ + color:#f5f8fa; } + +h1.bp3-heading, .bp3-running-text h1{ + line-height:40px; + font-size:36px; } + +h2.bp3-heading, .bp3-running-text h2{ + line-height:32px; + font-size:28px; } + +h3.bp3-heading, .bp3-running-text h3{ + line-height:25px; + font-size:22px; } + +h4.bp3-heading, .bp3-running-text h4{ + line-height:21px; + font-size:18px; } + +h5.bp3-heading, .bp3-running-text h5{ + line-height:19px; + font-size:16px; } + +h6.bp3-heading, .bp3-running-text h6{ + line-height:16px; + font-size:14px; } +.bp3-ui-text{ + text-transform:none; + line-height:1.28581; + letter-spacing:0; + font-size:14px; + font-weight:400; } + +.bp3-monospace-text{ + text-transform:none; + font-family:monospace; } + +.bp3-text-muted{ + color:#5c7080; } + .bp3-dark .bp3-text-muted{ + color:#a7b6c2; } + +.bp3-text-disabled{ + color:rgba(92, 112, 128, 0.6); } + .bp3-dark .bp3-text-disabled{ + color:rgba(167, 182, 194, 0.6); } + +.bp3-text-overflow-ellipsis{ + overflow:hidden; + text-overflow:ellipsis; + white-space:nowrap; + word-wrap:normal; } +.bp3-running-text{ + line-height:1.5; + font-size:14px; } + .bp3-running-text h1{ + color:#182026; + font-weight:600; + margin-top:40px; + margin-bottom:20px; } + .bp3-dark .bp3-running-text h1{ + color:#f5f8fa; } + .bp3-running-text h2{ + color:#182026; + font-weight:600; + margin-top:40px; + margin-bottom:20px; } + .bp3-dark .bp3-running-text h2{ + color:#f5f8fa; } + .bp3-running-text h3{ + color:#182026; + font-weight:600; + margin-top:40px; + margin-bottom:20px; } + .bp3-dark .bp3-running-text h3{ + color:#f5f8fa; } + .bp3-running-text h4{ + color:#182026; + font-weight:600; + margin-top:40px; + margin-bottom:20px; } + .bp3-dark .bp3-running-text h4{ + color:#f5f8fa; } + .bp3-running-text h5{ + color:#182026; + font-weight:600; + margin-top:40px; + margin-bottom:20px; } + .bp3-dark .bp3-running-text h5{ + color:#f5f8fa; } + .bp3-running-text h6{ + color:#182026; + font-weight:600; + margin-top:40px; + margin-bottom:20px; } + .bp3-dark .bp3-running-text h6{ + color:#f5f8fa; } + .bp3-running-text hr{ + margin:20px 0; + border:none; + border-bottom:1px solid rgba(16, 22, 26, 0.15); } + .bp3-dark .bp3-running-text hr{ + border-color:rgba(255, 255, 255, 0.15); } + .bp3-running-text p{ + margin:0 0 10px; + padding:0; } + +.bp3-text-large{ + font-size:16px; } + +.bp3-text-small{ + font-size:12px; } +a{ + text-decoration:none; + color:#106ba3; } + a:hover{ + cursor:pointer; + text-decoration:underline; + color:#106ba3; } + a .bp3-icon, a .bp3-icon-standard, a .bp3-icon-large{ + color:inherit; } + a code, + .bp3-dark a code{ + color:inherit; } + .bp3-dark a, + .bp3-dark a:hover{ + color:#48aff0; } + .bp3-dark a .bp3-icon, .bp3-dark a .bp3-icon-standard, .bp3-dark a .bp3-icon-large, + .bp3-dark a:hover .bp3-icon, + .bp3-dark a:hover .bp3-icon-standard, + .bp3-dark a:hover .bp3-icon-large{ + color:inherit; } +.bp3-running-text code, .bp3-code{ + text-transform:none; + font-family:monospace; + border-radius:3px; + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2); + background:rgba(255, 255, 255, 0.7); + padding:2px 5px; + color:#5c7080; + font-size:smaller; } + .bp3-dark .bp3-running-text code, .bp3-running-text .bp3-dark code, .bp3-dark .bp3-code{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4); + background:rgba(16, 22, 26, 0.3); + color:#a7b6c2; } + .bp3-running-text a > code, a > .bp3-code{ + color:#137cbd; } + .bp3-dark .bp3-running-text a > code, .bp3-running-text .bp3-dark a > code, .bp3-dark a > .bp3-code{ + color:inherit; } + +.bp3-running-text pre, .bp3-code-block{ + text-transform:none; + font-family:monospace; + display:block; + margin:10px 0; + border-radius:3px; + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.15); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.15); + background:rgba(255, 255, 255, 0.7); + padding:13px 15px 12px; + line-height:1.4; + color:#182026; + font-size:13px; + word-break:break-all; + word-wrap:break-word; } + .bp3-dark .bp3-running-text pre, .bp3-running-text .bp3-dark pre, .bp3-dark .bp3-code-block{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4); + background:rgba(16, 22, 26, 0.3); + color:#f5f8fa; } + .bp3-running-text pre > code, .bp3-code-block > code{ + -webkit-box-shadow:none; + box-shadow:none; + background:none; + padding:0; + color:inherit; + font-size:inherit; } + +.bp3-running-text kbd, .bp3-key{ + display:-webkit-inline-box; + display:-ms-inline-flexbox; + display:inline-flex; + -webkit-box-align:center; + -ms-flex-align:center; + align-items:center; + -webkit-box-pack:center; + -ms-flex-pack:center; + justify-content:center; + border-radius:3px; + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 0 0 rgba(16, 22, 26, 0), 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 0 0 rgba(16, 22, 26, 0), 0 1px 1px rgba(16, 22, 26, 0.2); + background:#ffffff; + min-width:24px; + height:24px; + padding:3px 6px; + vertical-align:middle; + line-height:24px; + color:#5c7080; + font-family:inherit; + font-size:12px; } + .bp3-running-text kbd .bp3-icon, .bp3-key .bp3-icon, .bp3-running-text kbd .bp3-icon-standard, .bp3-key .bp3-icon-standard, .bp3-running-text kbd .bp3-icon-large, .bp3-key .bp3-icon-large{ + margin-right:5px; } + .bp3-dark .bp3-running-text kbd, .bp3-running-text .bp3-dark kbd, .bp3-dark .bp3-key{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 0 0 rgba(16, 22, 26, 0), 0 1px 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 0 0 rgba(16, 22, 26, 0), 0 1px 1px rgba(16, 22, 26, 0.4); + background:#394b59; + color:#a7b6c2; } +.bp3-running-text blockquote, .bp3-blockquote{ + margin:0 0 10px; + border-left:solid 4px rgba(167, 182, 194, 0.5); + padding:0 20px; } + .bp3-dark .bp3-running-text blockquote, .bp3-running-text .bp3-dark blockquote, .bp3-dark .bp3-blockquote{ + border-color:rgba(115, 134, 148, 0.5); } +.bp3-running-text ul, +.bp3-running-text ol, .bp3-list{ + margin:10px 0; + padding-left:30px; } + .bp3-running-text ul li:not(:last-child), .bp3-running-text ol li:not(:last-child), .bp3-list li:not(:last-child){ + margin-bottom:5px; } + .bp3-running-text ul ol, .bp3-running-text ol ol, .bp3-list ol, + .bp3-running-text ul ul, + .bp3-running-text ol ul, + .bp3-list ul{ + margin-top:5px; } + +.bp3-list-unstyled{ + margin:0; + padding:0; + list-style:none; } + .bp3-list-unstyled li{ + padding:0; } +.bp3-rtl{ + text-align:right; } + +.bp3-dark{ + color:#f5f8fa; } + +:focus{ + outline:rgba(19, 124, 189, 0.6) auto 2px; + outline-offset:2px; + -moz-outline-radius:6px; } + +.bp3-focus-disabled :focus{ + outline:none !important; } + .bp3-focus-disabled :focus ~ .bp3-control-indicator{ + outline:none !important; } + +.bp3-alert{ + max-width:400px; + padding:20px; } + +.bp3-alert-body{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; } + .bp3-alert-body .bp3-icon{ + margin-top:0; + margin-right:20px; + font-size:40px; } + +.bp3-alert-footer{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; + -webkit-box-orient:horizontal; + -webkit-box-direction:reverse; + -ms-flex-direction:row-reverse; + flex-direction:row-reverse; + margin-top:10px; } + .bp3-alert-footer .bp3-button{ + margin-left:10px; } +.bp3-breadcrumbs{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; + -ms-flex-wrap:wrap; + flex-wrap:wrap; + -webkit-box-align:center; + -ms-flex-align:center; + align-items:center; + margin:0; + cursor:default; + height:30px; + padding:0; + list-style:none; } + .bp3-breadcrumbs > li{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; + -webkit-box-align:center; + -ms-flex-align:center; + align-items:center; } + .bp3-breadcrumbs > li::after{ + display:block; + margin:0 5px; + background:url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16'%3e%3cpath fill-rule='evenodd' clip-rule='evenodd' d='M10.71 7.29l-4-4a1.003 1.003 0 0 0-1.42 1.42L8.59 8 5.3 11.29c-.19.18-.3.43-.3.71a1.003 1.003 0 0 0 1.71.71l4-4c.18-.18.29-.43.29-.71 0-.28-.11-.53-.29-.71z' fill='%235C7080'/%3e%3c/svg%3e"); + width:16px; + height:16px; + content:""; } + .bp3-breadcrumbs > li:last-of-type::after{ + display:none; } + +.bp3-breadcrumb, +.bp3-breadcrumb-current, +.bp3-breadcrumbs-collapsed{ + display:-webkit-inline-box; + display:-ms-inline-flexbox; + display:inline-flex; + -webkit-box-align:center; + -ms-flex-align:center; + align-items:center; + font-size:16px; } + +.bp3-breadcrumb, +.bp3-breadcrumbs-collapsed{ + color:#5c7080; } + +.bp3-breadcrumb:hover{ + text-decoration:none; } + +.bp3-breadcrumb.bp3-disabled{ + cursor:not-allowed; + color:rgba(92, 112, 128, 0.6); } + +.bp3-breadcrumb .bp3-icon{ + margin-right:5px; } + +.bp3-breadcrumb-current{ + color:inherit; + font-weight:600; } + .bp3-breadcrumb-current .bp3-input{ + vertical-align:baseline; + font-size:inherit; + font-weight:inherit; } + +.bp3-breadcrumbs-collapsed{ + margin-right:2px; + border:none; + border-radius:3px; + background:#ced9e0; + cursor:pointer; + padding:1px 5px; + vertical-align:text-bottom; } + .bp3-breadcrumbs-collapsed::before{ + display:block; + background:url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16'%3e%3cg fill='%235C7080'%3e%3ccircle cx='2' cy='8.03' r='2'/%3e%3ccircle cx='14' cy='8.03' r='2'/%3e%3ccircle cx='8' cy='8.03' r='2'/%3e%3c/g%3e%3c/svg%3e") center no-repeat; + width:16px; + height:16px; + content:""; } + .bp3-breadcrumbs-collapsed:hover{ + background:#bfccd6; + text-decoration:none; + color:#182026; } + +.bp3-dark .bp3-breadcrumb, +.bp3-dark .bp3-breadcrumbs-collapsed{ + color:#a7b6c2; } + +.bp3-dark .bp3-breadcrumbs > li::after{ + color:#a7b6c2; } + +.bp3-dark .bp3-breadcrumb.bp3-disabled{ + color:rgba(167, 182, 194, 0.6); } + +.bp3-dark .bp3-breadcrumb-current{ + color:#f5f8fa; } + +.bp3-dark .bp3-breadcrumbs-collapsed{ + background:rgba(16, 22, 26, 0.4); } + .bp3-dark .bp3-breadcrumbs-collapsed:hover{ + background:rgba(16, 22, 26, 0.6); + color:#f5f8fa; } +.bp3-button{ + display:-webkit-inline-box; + display:-ms-inline-flexbox; + display:inline-flex; + -webkit-box-orient:horizontal; + -webkit-box-direction:normal; + -ms-flex-direction:row; + flex-direction:row; + -webkit-box-align:center; + -ms-flex-align:center; + align-items:center; + -webkit-box-pack:center; + -ms-flex-pack:center; + justify-content:center; + border:none; + border-radius:3px; + cursor:pointer; + padding:5px 10px; + vertical-align:middle; + text-align:left; + font-size:14px; + min-width:30px; + min-height:30px; } + .bp3-button > *{ + -webkit-box-flex:0; + -ms-flex-positive:0; + flex-grow:0; + -ms-flex-negative:0; + flex-shrink:0; } + .bp3-button > .bp3-fill{ + -webkit-box-flex:1; + -ms-flex-positive:1; + flex-grow:1; + -ms-flex-negative:1; + flex-shrink:1; } + .bp3-button::before, + .bp3-button > *{ + margin-right:7px; } + .bp3-button:empty::before, + .bp3-button > :last-child{ + margin-right:0; } + .bp3-button:empty{ + padding:0 !important; } + .bp3-button:disabled, .bp3-button.bp3-disabled{ + cursor:not-allowed; } + .bp3-button.bp3-fill{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; + width:100%; } + .bp3-button.bp3-align-right, + .bp3-align-right .bp3-button{ + text-align:right; } + .bp3-button.bp3-align-left, + .bp3-align-left .bp3-button{ + text-align:left; } + .bp3-button:not([class*="bp3-intent-"]){ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 -1px 0 rgba(16, 22, 26, 0.1); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 -1px 0 rgba(16, 22, 26, 0.1); + background-color:#f5f8fa; + background-image:-webkit-gradient(linear, left top, left bottom, from(rgba(255, 255, 255, 0.8)), to(rgba(255, 255, 255, 0))); + background-image:linear-gradient(to bottom, rgba(255, 255, 255, 0.8), rgba(255, 255, 255, 0)); + color:#182026; } + .bp3-button:not([class*="bp3-intent-"]):hover{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 -1px 0 rgba(16, 22, 26, 0.1); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 -1px 0 rgba(16, 22, 26, 0.1); + background-clip:padding-box; + background-color:#ebf1f5; } + .bp3-button:not([class*="bp3-intent-"]):active, .bp3-button:not([class*="bp3-intent-"]).bp3-active{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 1px 2px rgba(16, 22, 26, 0.2); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 1px 2px rgba(16, 22, 26, 0.2); + background-color:#d8e1e8; + background-image:none; } + .bp3-button:not([class*="bp3-intent-"]):disabled, .bp3-button:not([class*="bp3-intent-"]).bp3-disabled{ + outline:none; + -webkit-box-shadow:none; + box-shadow:none; + background-color:rgba(206, 217, 224, 0.5); + background-image:none; + cursor:not-allowed; + color:rgba(92, 112, 128, 0.6); } + .bp3-button:not([class*="bp3-intent-"]):disabled.bp3-active, .bp3-button:not([class*="bp3-intent-"]):disabled.bp3-active:hover, .bp3-button:not([class*="bp3-intent-"]).bp3-disabled.bp3-active, .bp3-button:not([class*="bp3-intent-"]).bp3-disabled.bp3-active:hover{ + background:rgba(206, 217, 224, 0.7); } + .bp3-button.bp3-intent-primary{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 -1px 0 rgba(16, 22, 26, 0.2); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 -1px 0 rgba(16, 22, 26, 0.2); + background-color:#137cbd; + background-image:-webkit-gradient(linear, left top, left bottom, from(rgba(255, 255, 255, 0.1)), to(rgba(255, 255, 255, 0))); + background-image:linear-gradient(to bottom, rgba(255, 255, 255, 0.1), rgba(255, 255, 255, 0)); + color:#ffffff; } + .bp3-button.bp3-intent-primary:hover, .bp3-button.bp3-intent-primary:active, .bp3-button.bp3-intent-primary.bp3-active{ + color:#ffffff; } + .bp3-button.bp3-intent-primary:hover{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 -1px 0 rgba(16, 22, 26, 0.2); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 -1px 0 rgba(16, 22, 26, 0.2); + background-color:#106ba3; } + .bp3-button.bp3-intent-primary:active, .bp3-button.bp3-intent-primary.bp3-active{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 1px 2px rgba(16, 22, 26, 0.2); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 1px 2px rgba(16, 22, 26, 0.2); + background-color:#0e5a8a; + background-image:none; } + .bp3-button.bp3-intent-primary:disabled, .bp3-button.bp3-intent-primary.bp3-disabled{ + border-color:transparent; + -webkit-box-shadow:none; + box-shadow:none; + background-color:rgba(19, 124, 189, 0.5); + background-image:none; + color:rgba(255, 255, 255, 0.6); } + .bp3-button.bp3-intent-success{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 -1px 0 rgba(16, 22, 26, 0.2); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 -1px 0 rgba(16, 22, 26, 0.2); + background-color:#0f9960; + background-image:-webkit-gradient(linear, left top, left bottom, from(rgba(255, 255, 255, 0.1)), to(rgba(255, 255, 255, 0))); + background-image:linear-gradient(to bottom, rgba(255, 255, 255, 0.1), rgba(255, 255, 255, 0)); + color:#ffffff; } + .bp3-button.bp3-intent-success:hover, .bp3-button.bp3-intent-success:active, .bp3-button.bp3-intent-success.bp3-active{ + color:#ffffff; } + .bp3-button.bp3-intent-success:hover{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 -1px 0 rgba(16, 22, 26, 0.2); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 -1px 0 rgba(16, 22, 26, 0.2); + background-color:#0d8050; } + .bp3-button.bp3-intent-success:active, .bp3-button.bp3-intent-success.bp3-active{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 1px 2px rgba(16, 22, 26, 0.2); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 1px 2px rgba(16, 22, 26, 0.2); + background-color:#0a6640; + background-image:none; } + .bp3-button.bp3-intent-success:disabled, .bp3-button.bp3-intent-success.bp3-disabled{ + border-color:transparent; + -webkit-box-shadow:none; + box-shadow:none; + background-color:rgba(15, 153, 96, 0.5); + background-image:none; + color:rgba(255, 255, 255, 0.6); } + .bp3-button.bp3-intent-warning{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 -1px 0 rgba(16, 22, 26, 0.2); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 -1px 0 rgba(16, 22, 26, 0.2); + background-color:#d9822b; + background-image:-webkit-gradient(linear, left top, left bottom, from(rgba(255, 255, 255, 0.1)), to(rgba(255, 255, 255, 0))); + background-image:linear-gradient(to bottom, rgba(255, 255, 255, 0.1), rgba(255, 255, 255, 0)); + color:#ffffff; } + .bp3-button.bp3-intent-warning:hover, .bp3-button.bp3-intent-warning:active, .bp3-button.bp3-intent-warning.bp3-active{ + color:#ffffff; } + .bp3-button.bp3-intent-warning:hover{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 -1px 0 rgba(16, 22, 26, 0.2); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 -1px 0 rgba(16, 22, 26, 0.2); + background-color:#bf7326; } + .bp3-button.bp3-intent-warning:active, .bp3-button.bp3-intent-warning.bp3-active{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 1px 2px rgba(16, 22, 26, 0.2); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 1px 2px rgba(16, 22, 26, 0.2); + background-color:#a66321; + background-image:none; } + .bp3-button.bp3-intent-warning:disabled, .bp3-button.bp3-intent-warning.bp3-disabled{ + border-color:transparent; + -webkit-box-shadow:none; + box-shadow:none; + background-color:rgba(217, 130, 43, 0.5); + background-image:none; + color:rgba(255, 255, 255, 0.6); } + .bp3-button.bp3-intent-danger{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 -1px 0 rgba(16, 22, 26, 0.2); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 -1px 0 rgba(16, 22, 26, 0.2); + background-color:#db3737; + background-image:-webkit-gradient(linear, left top, left bottom, from(rgba(255, 255, 255, 0.1)), to(rgba(255, 255, 255, 0))); + background-image:linear-gradient(to bottom, rgba(255, 255, 255, 0.1), rgba(255, 255, 255, 0)); + color:#ffffff; } + .bp3-button.bp3-intent-danger:hover, .bp3-button.bp3-intent-danger:active, .bp3-button.bp3-intent-danger.bp3-active{ + color:#ffffff; } + .bp3-button.bp3-intent-danger:hover{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 -1px 0 rgba(16, 22, 26, 0.2); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 -1px 0 rgba(16, 22, 26, 0.2); + background-color:#c23030; } + .bp3-button.bp3-intent-danger:active, .bp3-button.bp3-intent-danger.bp3-active{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 1px 2px rgba(16, 22, 26, 0.2); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 1px 2px rgba(16, 22, 26, 0.2); + background-color:#a82a2a; + background-image:none; } + .bp3-button.bp3-intent-danger:disabled, .bp3-button.bp3-intent-danger.bp3-disabled{ + border-color:transparent; + -webkit-box-shadow:none; + box-shadow:none; + background-color:rgba(219, 55, 55, 0.5); + background-image:none; + color:rgba(255, 255, 255, 0.6); } + .bp3-button[class*="bp3-intent-"] .bp3-button-spinner .bp3-spinner-head{ + stroke:#ffffff; } + .bp3-button.bp3-large, + .bp3-large .bp3-button{ + min-width:40px; + min-height:40px; + padding:5px 15px; + font-size:16px; } + .bp3-button.bp3-large::before, + .bp3-button.bp3-large > *, + .bp3-large .bp3-button::before, + .bp3-large .bp3-button > *{ + margin-right:10px; } + .bp3-button.bp3-large:empty::before, + .bp3-button.bp3-large > :last-child, + .bp3-large .bp3-button:empty::before, + .bp3-large .bp3-button > :last-child{ + margin-right:0; } + .bp3-button.bp3-small, + .bp3-small .bp3-button{ + min-width:24px; + min-height:24px; + padding:0 7px; } + .bp3-button.bp3-loading{ + position:relative; } + .bp3-button.bp3-loading[class*="bp3-icon-"]::before{ + visibility:hidden; } + .bp3-button.bp3-loading .bp3-button-spinner{ + position:absolute; + margin:0; } + .bp3-button.bp3-loading > :not(.bp3-button-spinner){ + visibility:hidden; } + .bp3-button[class*="bp3-icon-"]::before{ + line-height:1; + font-family:"Icons16", sans-serif; + font-size:16px; + font-weight:400; + font-style:normal; + -moz-osx-font-smoothing:grayscale; + -webkit-font-smoothing:antialiased; + color:#5c7080; } + .bp3-button .bp3-icon, .bp3-button .bp3-icon-standard, .bp3-button .bp3-icon-large{ + color:#5c7080; } + .bp3-button .bp3-icon.bp3-align-right, .bp3-button .bp3-icon-standard.bp3-align-right, .bp3-button .bp3-icon-large.bp3-align-right{ + margin-left:7px; } + .bp3-button .bp3-icon:first-child:last-child, + .bp3-button .bp3-spinner + .bp3-icon:last-child{ + margin:0 -7px; } + .bp3-dark .bp3-button:not([class*="bp3-intent-"]){ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + background-color:#394b59; + background-image:-webkit-gradient(linear, left top, left bottom, from(rgba(255, 255, 255, 0.05)), to(rgba(255, 255, 255, 0))); + background-image:linear-gradient(to bottom, rgba(255, 255, 255, 0.05), rgba(255, 255, 255, 0)); + color:#f5f8fa; } + .bp3-dark .bp3-button:not([class*="bp3-intent-"]):hover, .bp3-dark .bp3-button:not([class*="bp3-intent-"]):active, .bp3-dark .bp3-button:not([class*="bp3-intent-"]).bp3-active{ + color:#f5f8fa; } + .bp3-dark .bp3-button:not([class*="bp3-intent-"]):hover{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + background-color:#30404d; } + .bp3-dark .bp3-button:not([class*="bp3-intent-"]):active, .bp3-dark .bp3-button:not([class*="bp3-intent-"]).bp3-active{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.6), inset 0 1px 2px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.6), inset 0 1px 2px rgba(16, 22, 26, 0.2); + background-color:#202b33; + background-image:none; } + .bp3-dark .bp3-button:not([class*="bp3-intent-"]):disabled, .bp3-dark .bp3-button:not([class*="bp3-intent-"]).bp3-disabled{ + -webkit-box-shadow:none; + box-shadow:none; + background-color:rgba(57, 75, 89, 0.5); + background-image:none; + color:rgba(167, 182, 194, 0.6); } + .bp3-dark .bp3-button:not([class*="bp3-intent-"]):disabled.bp3-active, .bp3-dark .bp3-button:not([class*="bp3-intent-"]).bp3-disabled.bp3-active{ + background:rgba(57, 75, 89, 0.7); } + .bp3-dark .bp3-button:not([class*="bp3-intent-"]) .bp3-button-spinner .bp3-spinner-head{ + background:rgba(16, 22, 26, 0.5); + stroke:#8a9ba8; } + .bp3-dark .bp3-button:not([class*="bp3-intent-"])[class*="bp3-icon-"]::before{ + color:#a7b6c2; } + .bp3-dark .bp3-button:not([class*="bp3-intent-"]) .bp3-icon, .bp3-dark .bp3-button:not([class*="bp3-intent-"]) .bp3-icon-standard, .bp3-dark .bp3-button:not([class*="bp3-intent-"]) .bp3-icon-large{ + color:#a7b6c2; } + .bp3-dark .bp3-button[class*="bp3-intent-"]{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); } + .bp3-dark .bp3-button[class*="bp3-intent-"]:hover{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); } + .bp3-dark .bp3-button[class*="bp3-intent-"]:active, .bp3-dark .bp3-button[class*="bp3-intent-"].bp3-active{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 1px 2px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 1px 2px rgba(16, 22, 26, 0.2); } + .bp3-dark .bp3-button[class*="bp3-intent-"]:disabled, .bp3-dark .bp3-button[class*="bp3-intent-"].bp3-disabled{ + -webkit-box-shadow:none; + box-shadow:none; + background-image:none; + color:rgba(255, 255, 255, 0.3); } + .bp3-dark .bp3-button[class*="bp3-intent-"] .bp3-button-spinner .bp3-spinner-head{ + stroke:#8a9ba8; } + .bp3-button:disabled::before, + .bp3-button:disabled .bp3-icon, .bp3-button:disabled .bp3-icon-standard, .bp3-button:disabled .bp3-icon-large, .bp3-button.bp3-disabled::before, + .bp3-button.bp3-disabled .bp3-icon, .bp3-button.bp3-disabled .bp3-icon-standard, .bp3-button.bp3-disabled .bp3-icon-large, .bp3-button[class*="bp3-intent-"]::before, + .bp3-button[class*="bp3-intent-"] .bp3-icon, .bp3-button[class*="bp3-intent-"] .bp3-icon-standard, .bp3-button[class*="bp3-intent-"] .bp3-icon-large{ + color:inherit !important; } + .bp3-button.bp3-minimal{ + -webkit-box-shadow:none; + box-shadow:none; + background:none; } + .bp3-button.bp3-minimal:hover{ + -webkit-box-shadow:none; + box-shadow:none; + background:rgba(167, 182, 194, 0.3); + text-decoration:none; + color:#182026; } + .bp3-button.bp3-minimal:active, .bp3-button.bp3-minimal.bp3-active{ + -webkit-box-shadow:none; + box-shadow:none; + background:rgba(115, 134, 148, 0.3); + color:#182026; } + .bp3-button.bp3-minimal:disabled, .bp3-button.bp3-minimal:disabled:hover, .bp3-button.bp3-minimal.bp3-disabled, .bp3-button.bp3-minimal.bp3-disabled:hover{ + background:none; + cursor:not-allowed; + color:rgba(92, 112, 128, 0.6); } + .bp3-button.bp3-minimal:disabled.bp3-active, .bp3-button.bp3-minimal:disabled:hover.bp3-active, .bp3-button.bp3-minimal.bp3-disabled.bp3-active, .bp3-button.bp3-minimal.bp3-disabled:hover.bp3-active{ + background:rgba(115, 134, 148, 0.3); } + .bp3-dark .bp3-button.bp3-minimal{ + -webkit-box-shadow:none; + box-shadow:none; + background:none; + color:inherit; } + .bp3-dark .bp3-button.bp3-minimal:hover, .bp3-dark .bp3-button.bp3-minimal:active, .bp3-dark .bp3-button.bp3-minimal.bp3-active{ + -webkit-box-shadow:none; + box-shadow:none; + background:none; } + .bp3-dark .bp3-button.bp3-minimal:hover{ + background:rgba(138, 155, 168, 0.15); } + .bp3-dark .bp3-button.bp3-minimal:active, .bp3-dark .bp3-button.bp3-minimal.bp3-active{ + background:rgba(138, 155, 168, 0.3); + color:#f5f8fa; } + .bp3-dark .bp3-button.bp3-minimal:disabled, .bp3-dark .bp3-button.bp3-minimal:disabled:hover, .bp3-dark .bp3-button.bp3-minimal.bp3-disabled, .bp3-dark .bp3-button.bp3-minimal.bp3-disabled:hover{ + background:none; + cursor:not-allowed; + color:rgba(167, 182, 194, 0.6); } + .bp3-dark .bp3-button.bp3-minimal:disabled.bp3-active, .bp3-dark .bp3-button.bp3-minimal:disabled:hover.bp3-active, .bp3-dark .bp3-button.bp3-minimal.bp3-disabled.bp3-active, .bp3-dark .bp3-button.bp3-minimal.bp3-disabled:hover.bp3-active{ + background:rgba(138, 155, 168, 0.3); } + .bp3-button.bp3-minimal.bp3-intent-primary{ + color:#106ba3; } + .bp3-button.bp3-minimal.bp3-intent-primary:hover, .bp3-button.bp3-minimal.bp3-intent-primary:active, .bp3-button.bp3-minimal.bp3-intent-primary.bp3-active{ + -webkit-box-shadow:none; + box-shadow:none; + background:none; + color:#106ba3; } + .bp3-button.bp3-minimal.bp3-intent-primary:hover{ + background:rgba(19, 124, 189, 0.15); + color:#106ba3; } + .bp3-button.bp3-minimal.bp3-intent-primary:active, .bp3-button.bp3-minimal.bp3-intent-primary.bp3-active{ + background:rgba(19, 124, 189, 0.3); + color:#106ba3; } + .bp3-button.bp3-minimal.bp3-intent-primary:disabled, .bp3-button.bp3-minimal.bp3-intent-primary.bp3-disabled{ + background:none; + color:rgba(16, 107, 163, 0.5); } + .bp3-button.bp3-minimal.bp3-intent-primary:disabled.bp3-active, .bp3-button.bp3-minimal.bp3-intent-primary.bp3-disabled.bp3-active{ + background:rgba(19, 124, 189, 0.3); } + .bp3-button.bp3-minimal.bp3-intent-primary .bp3-button-spinner .bp3-spinner-head{ + stroke:#106ba3; } + .bp3-dark .bp3-button.bp3-minimal.bp3-intent-primary{ + color:#48aff0; } + .bp3-dark .bp3-button.bp3-minimal.bp3-intent-primary:hover{ + background:rgba(19, 124, 189, 0.2); + color:#48aff0; } + .bp3-dark .bp3-button.bp3-minimal.bp3-intent-primary:active, .bp3-dark .bp3-button.bp3-minimal.bp3-intent-primary.bp3-active{ + background:rgba(19, 124, 189, 0.3); + color:#48aff0; } + .bp3-dark .bp3-button.bp3-minimal.bp3-intent-primary:disabled, .bp3-dark .bp3-button.bp3-minimal.bp3-intent-primary.bp3-disabled{ + background:none; + color:rgba(72, 175, 240, 0.5); } + .bp3-dark .bp3-button.bp3-minimal.bp3-intent-primary:disabled.bp3-active, .bp3-dark .bp3-button.bp3-minimal.bp3-intent-primary.bp3-disabled.bp3-active{ + background:rgba(19, 124, 189, 0.3); } + .bp3-button.bp3-minimal.bp3-intent-success{ + color:#0d8050; } + .bp3-button.bp3-minimal.bp3-intent-success:hover, .bp3-button.bp3-minimal.bp3-intent-success:active, .bp3-button.bp3-minimal.bp3-intent-success.bp3-active{ + -webkit-box-shadow:none; + box-shadow:none; + background:none; + color:#0d8050; } + .bp3-button.bp3-minimal.bp3-intent-success:hover{ + background:rgba(15, 153, 96, 0.15); + color:#0d8050; } + .bp3-button.bp3-minimal.bp3-intent-success:active, .bp3-button.bp3-minimal.bp3-intent-success.bp3-active{ + background:rgba(15, 153, 96, 0.3); + color:#0d8050; } + .bp3-button.bp3-minimal.bp3-intent-success:disabled, .bp3-button.bp3-minimal.bp3-intent-success.bp3-disabled{ + background:none; + color:rgba(13, 128, 80, 0.5); } + .bp3-button.bp3-minimal.bp3-intent-success:disabled.bp3-active, .bp3-button.bp3-minimal.bp3-intent-success.bp3-disabled.bp3-active{ + background:rgba(15, 153, 96, 0.3); } + .bp3-button.bp3-minimal.bp3-intent-success .bp3-button-spinner .bp3-spinner-head{ + stroke:#0d8050; } + .bp3-dark .bp3-button.bp3-minimal.bp3-intent-success{ + color:#3dcc91; } + .bp3-dark .bp3-button.bp3-minimal.bp3-intent-success:hover{ + background:rgba(15, 153, 96, 0.2); + color:#3dcc91; } + .bp3-dark .bp3-button.bp3-minimal.bp3-intent-success:active, .bp3-dark .bp3-button.bp3-minimal.bp3-intent-success.bp3-active{ + background:rgba(15, 153, 96, 0.3); + color:#3dcc91; } + .bp3-dark .bp3-button.bp3-minimal.bp3-intent-success:disabled, .bp3-dark .bp3-button.bp3-minimal.bp3-intent-success.bp3-disabled{ + background:none; + color:rgba(61, 204, 145, 0.5); } + .bp3-dark .bp3-button.bp3-minimal.bp3-intent-success:disabled.bp3-active, .bp3-dark .bp3-button.bp3-minimal.bp3-intent-success.bp3-disabled.bp3-active{ + background:rgba(15, 153, 96, 0.3); } + .bp3-button.bp3-minimal.bp3-intent-warning{ + color:#bf7326; } + .bp3-button.bp3-minimal.bp3-intent-warning:hover, .bp3-button.bp3-minimal.bp3-intent-warning:active, .bp3-button.bp3-minimal.bp3-intent-warning.bp3-active{ + -webkit-box-shadow:none; + box-shadow:none; + background:none; + color:#bf7326; } + .bp3-button.bp3-minimal.bp3-intent-warning:hover{ + background:rgba(217, 130, 43, 0.15); + color:#bf7326; } + .bp3-button.bp3-minimal.bp3-intent-warning:active, .bp3-button.bp3-minimal.bp3-intent-warning.bp3-active{ + background:rgba(217, 130, 43, 0.3); + color:#bf7326; } + .bp3-button.bp3-minimal.bp3-intent-warning:disabled, .bp3-button.bp3-minimal.bp3-intent-warning.bp3-disabled{ + background:none; + color:rgba(191, 115, 38, 0.5); } + .bp3-button.bp3-minimal.bp3-intent-warning:disabled.bp3-active, .bp3-button.bp3-minimal.bp3-intent-warning.bp3-disabled.bp3-active{ + background:rgba(217, 130, 43, 0.3); } + .bp3-button.bp3-minimal.bp3-intent-warning .bp3-button-spinner .bp3-spinner-head{ + stroke:#bf7326; } + .bp3-dark .bp3-button.bp3-minimal.bp3-intent-warning{ + color:#ffb366; } + .bp3-dark .bp3-button.bp3-minimal.bp3-intent-warning:hover{ + background:rgba(217, 130, 43, 0.2); + color:#ffb366; } + .bp3-dark .bp3-button.bp3-minimal.bp3-intent-warning:active, .bp3-dark .bp3-button.bp3-minimal.bp3-intent-warning.bp3-active{ + background:rgba(217, 130, 43, 0.3); + color:#ffb366; } + .bp3-dark .bp3-button.bp3-minimal.bp3-intent-warning:disabled, .bp3-dark .bp3-button.bp3-minimal.bp3-intent-warning.bp3-disabled{ + background:none; + color:rgba(255, 179, 102, 0.5); } + .bp3-dark .bp3-button.bp3-minimal.bp3-intent-warning:disabled.bp3-active, .bp3-dark .bp3-button.bp3-minimal.bp3-intent-warning.bp3-disabled.bp3-active{ + background:rgba(217, 130, 43, 0.3); } + .bp3-button.bp3-minimal.bp3-intent-danger{ + color:#c23030; } + .bp3-button.bp3-minimal.bp3-intent-danger:hover, .bp3-button.bp3-minimal.bp3-intent-danger:active, .bp3-button.bp3-minimal.bp3-intent-danger.bp3-active{ + -webkit-box-shadow:none; + box-shadow:none; + background:none; + color:#c23030; } + .bp3-button.bp3-minimal.bp3-intent-danger:hover{ + background:rgba(219, 55, 55, 0.15); + color:#c23030; } + .bp3-button.bp3-minimal.bp3-intent-danger:active, .bp3-button.bp3-minimal.bp3-intent-danger.bp3-active{ + background:rgba(219, 55, 55, 0.3); + color:#c23030; } + .bp3-button.bp3-minimal.bp3-intent-danger:disabled, .bp3-button.bp3-minimal.bp3-intent-danger.bp3-disabled{ + background:none; + color:rgba(194, 48, 48, 0.5); } + .bp3-button.bp3-minimal.bp3-intent-danger:disabled.bp3-active, .bp3-button.bp3-minimal.bp3-intent-danger.bp3-disabled.bp3-active{ + background:rgba(219, 55, 55, 0.3); } + .bp3-button.bp3-minimal.bp3-intent-danger .bp3-button-spinner .bp3-spinner-head{ + stroke:#c23030; } + .bp3-dark .bp3-button.bp3-minimal.bp3-intent-danger{ + color:#ff7373; } + .bp3-dark .bp3-button.bp3-minimal.bp3-intent-danger:hover{ + background:rgba(219, 55, 55, 0.2); + color:#ff7373; } + .bp3-dark .bp3-button.bp3-minimal.bp3-intent-danger:active, .bp3-dark .bp3-button.bp3-minimal.bp3-intent-danger.bp3-active{ + background:rgba(219, 55, 55, 0.3); + color:#ff7373; } + .bp3-dark .bp3-button.bp3-minimal.bp3-intent-danger:disabled, .bp3-dark .bp3-button.bp3-minimal.bp3-intent-danger.bp3-disabled{ + background:none; + color:rgba(255, 115, 115, 0.5); } + .bp3-dark .bp3-button.bp3-minimal.bp3-intent-danger:disabled.bp3-active, .bp3-dark .bp3-button.bp3-minimal.bp3-intent-danger.bp3-disabled.bp3-active{ + background:rgba(219, 55, 55, 0.3); } + +a.bp3-button{ + text-align:center; + text-decoration:none; + -webkit-transition:none; + transition:none; } + a.bp3-button, a.bp3-button:hover, a.bp3-button:active{ + color:#182026; } + a.bp3-button.bp3-disabled{ + color:rgba(92, 112, 128, 0.6); } + +.bp3-button-text{ + -webkit-box-flex:0; + -ms-flex:0 1 auto; + flex:0 1 auto; } + +.bp3-button.bp3-align-left .bp3-button-text, .bp3-button.bp3-align-right .bp3-button-text, +.bp3-button-group.bp3-align-left .bp3-button-text, +.bp3-button-group.bp3-align-right .bp3-button-text{ + -webkit-box-flex:1; + -ms-flex:1 1 auto; + flex:1 1 auto; } +.bp3-button-group{ + display:-webkit-inline-box; + display:-ms-inline-flexbox; + display:inline-flex; } + .bp3-button-group .bp3-button{ + -webkit-box-flex:0; + -ms-flex:0 0 auto; + flex:0 0 auto; + position:relative; + z-index:4; } + .bp3-button-group .bp3-button:focus{ + z-index:5; } + .bp3-button-group .bp3-button:hover{ + z-index:6; } + .bp3-button-group .bp3-button:active, .bp3-button-group .bp3-button.bp3-active{ + z-index:7; } + .bp3-button-group .bp3-button:disabled, .bp3-button-group .bp3-button.bp3-disabled{ + z-index:3; } + .bp3-button-group .bp3-button[class*="bp3-intent-"]{ + z-index:9; } + .bp3-button-group .bp3-button[class*="bp3-intent-"]:focus{ + z-index:10; } + .bp3-button-group .bp3-button[class*="bp3-intent-"]:hover{ + z-index:11; } + .bp3-button-group .bp3-button[class*="bp3-intent-"]:active, .bp3-button-group .bp3-button[class*="bp3-intent-"].bp3-active{ + z-index:12; } + .bp3-button-group .bp3-button[class*="bp3-intent-"]:disabled, .bp3-button-group .bp3-button[class*="bp3-intent-"].bp3-disabled{ + z-index:8; } + .bp3-button-group:not(.bp3-minimal) > .bp3-popover-wrapper:not(:first-child) .bp3-button, + .bp3-button-group:not(.bp3-minimal) > .bp3-button:not(:first-child){ + border-top-left-radius:0; + border-bottom-left-radius:0; } + .bp3-button-group:not(.bp3-minimal) > .bp3-popover-wrapper:not(:last-child) .bp3-button, + .bp3-button-group:not(.bp3-minimal) > .bp3-button:not(:last-child){ + margin-right:-1px; + border-top-right-radius:0; + border-bottom-right-radius:0; } + .bp3-button-group.bp3-minimal .bp3-button{ + -webkit-box-shadow:none; + box-shadow:none; + background:none; } + .bp3-button-group.bp3-minimal .bp3-button:hover{ + -webkit-box-shadow:none; + box-shadow:none; + background:rgba(167, 182, 194, 0.3); + text-decoration:none; + color:#182026; } + .bp3-button-group.bp3-minimal .bp3-button:active, .bp3-button-group.bp3-minimal .bp3-button.bp3-active{ + -webkit-box-shadow:none; + box-shadow:none; + background:rgba(115, 134, 148, 0.3); + color:#182026; } + .bp3-button-group.bp3-minimal .bp3-button:disabled, .bp3-button-group.bp3-minimal .bp3-button:disabled:hover, .bp3-button-group.bp3-minimal .bp3-button.bp3-disabled, .bp3-button-group.bp3-minimal .bp3-button.bp3-disabled:hover{ + background:none; + cursor:not-allowed; + color:rgba(92, 112, 128, 0.6); } + .bp3-button-group.bp3-minimal .bp3-button:disabled.bp3-active, .bp3-button-group.bp3-minimal .bp3-button:disabled:hover.bp3-active, .bp3-button-group.bp3-minimal .bp3-button.bp3-disabled.bp3-active, .bp3-button-group.bp3-minimal .bp3-button.bp3-disabled:hover.bp3-active{ + background:rgba(115, 134, 148, 0.3); } + .bp3-dark .bp3-button-group.bp3-minimal .bp3-button{ + -webkit-box-shadow:none; + box-shadow:none; + background:none; + color:inherit; } + .bp3-dark .bp3-button-group.bp3-minimal .bp3-button:hover, .bp3-dark .bp3-button-group.bp3-minimal .bp3-button:active, .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-active{ + -webkit-box-shadow:none; + box-shadow:none; + background:none; } + .bp3-dark .bp3-button-group.bp3-minimal .bp3-button:hover{ + background:rgba(138, 155, 168, 0.15); } + .bp3-dark .bp3-button-group.bp3-minimal .bp3-button:active, .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-active{ + background:rgba(138, 155, 168, 0.3); + color:#f5f8fa; } + .bp3-dark .bp3-button-group.bp3-minimal .bp3-button:disabled, .bp3-dark .bp3-button-group.bp3-minimal .bp3-button:disabled:hover, .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-disabled, .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-disabled:hover{ + background:none; + cursor:not-allowed; + color:rgba(167, 182, 194, 0.6); } + .bp3-dark .bp3-button-group.bp3-minimal .bp3-button:disabled.bp3-active, .bp3-dark .bp3-button-group.bp3-minimal .bp3-button:disabled:hover.bp3-active, .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-disabled.bp3-active, .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-disabled:hover.bp3-active{ + background:rgba(138, 155, 168, 0.3); } + .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-primary{ + color:#106ba3; } + .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-primary:hover, .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-primary:active, .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-primary.bp3-active{ + -webkit-box-shadow:none; + box-shadow:none; + background:none; + color:#106ba3; } + .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-primary:hover{ + background:rgba(19, 124, 189, 0.15); + color:#106ba3; } + .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-primary:active, .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-primary.bp3-active{ + background:rgba(19, 124, 189, 0.3); + color:#106ba3; } + .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-primary:disabled, .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-primary.bp3-disabled{ + background:none; + color:rgba(16, 107, 163, 0.5); } + .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-primary:disabled.bp3-active, .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-primary.bp3-disabled.bp3-active{ + background:rgba(19, 124, 189, 0.3); } + .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-primary .bp3-button-spinner .bp3-spinner-head{ + stroke:#106ba3; } + .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-primary{ + color:#48aff0; } + .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-primary:hover{ + background:rgba(19, 124, 189, 0.2); + color:#48aff0; } + .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-primary:active, .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-primary.bp3-active{ + background:rgba(19, 124, 189, 0.3); + color:#48aff0; } + .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-primary:disabled, .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-primary.bp3-disabled{ + background:none; + color:rgba(72, 175, 240, 0.5); } + .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-primary:disabled.bp3-active, .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-primary.bp3-disabled.bp3-active{ + background:rgba(19, 124, 189, 0.3); } + .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-success{ + color:#0d8050; } + .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-success:hover, .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-success:active, .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-success.bp3-active{ + -webkit-box-shadow:none; + box-shadow:none; + background:none; + color:#0d8050; } + .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-success:hover{ + background:rgba(15, 153, 96, 0.15); + color:#0d8050; } + .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-success:active, .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-success.bp3-active{ + background:rgba(15, 153, 96, 0.3); + color:#0d8050; } + .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-success:disabled, .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-success.bp3-disabled{ + background:none; + color:rgba(13, 128, 80, 0.5); } + .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-success:disabled.bp3-active, .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-success.bp3-disabled.bp3-active{ + background:rgba(15, 153, 96, 0.3); } + .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-success .bp3-button-spinner .bp3-spinner-head{ + stroke:#0d8050; } + .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-success{ + color:#3dcc91; } + .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-success:hover{ + background:rgba(15, 153, 96, 0.2); + color:#3dcc91; } + .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-success:active, .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-success.bp3-active{ + background:rgba(15, 153, 96, 0.3); + color:#3dcc91; } + .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-success:disabled, .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-success.bp3-disabled{ + background:none; + color:rgba(61, 204, 145, 0.5); } + .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-success:disabled.bp3-active, .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-success.bp3-disabled.bp3-active{ + background:rgba(15, 153, 96, 0.3); } + .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-warning{ + color:#bf7326; } + .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-warning:hover, .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-warning:active, .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-warning.bp3-active{ + -webkit-box-shadow:none; + box-shadow:none; + background:none; + color:#bf7326; } + .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-warning:hover{ + background:rgba(217, 130, 43, 0.15); + color:#bf7326; } + .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-warning:active, .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-warning.bp3-active{ + background:rgba(217, 130, 43, 0.3); + color:#bf7326; } + .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-warning:disabled, .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-warning.bp3-disabled{ + background:none; + color:rgba(191, 115, 38, 0.5); } + .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-warning:disabled.bp3-active, .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-warning.bp3-disabled.bp3-active{ + background:rgba(217, 130, 43, 0.3); } + .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-warning .bp3-button-spinner .bp3-spinner-head{ + stroke:#bf7326; } + .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-warning{ + color:#ffb366; } + .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-warning:hover{ + background:rgba(217, 130, 43, 0.2); + color:#ffb366; } + .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-warning:active, .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-warning.bp3-active{ + background:rgba(217, 130, 43, 0.3); + color:#ffb366; } + .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-warning:disabled, .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-warning.bp3-disabled{ + background:none; + color:rgba(255, 179, 102, 0.5); } + .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-warning:disabled.bp3-active, .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-warning.bp3-disabled.bp3-active{ + background:rgba(217, 130, 43, 0.3); } + .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-danger{ + color:#c23030; } + .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-danger:hover, .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-danger:active, .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-danger.bp3-active{ + -webkit-box-shadow:none; + box-shadow:none; + background:none; + color:#c23030; } + .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-danger:hover{ + background:rgba(219, 55, 55, 0.15); + color:#c23030; } + .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-danger:active, .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-danger.bp3-active{ + background:rgba(219, 55, 55, 0.3); + color:#c23030; } + .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-danger:disabled, .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-danger.bp3-disabled{ + background:none; + color:rgba(194, 48, 48, 0.5); } + .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-danger:disabled.bp3-active, .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-danger.bp3-disabled.bp3-active{ + background:rgba(219, 55, 55, 0.3); } + .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-danger .bp3-button-spinner .bp3-spinner-head{ + stroke:#c23030; } + .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-danger{ + color:#ff7373; } + .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-danger:hover{ + background:rgba(219, 55, 55, 0.2); + color:#ff7373; } + .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-danger:active, .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-danger.bp3-active{ + background:rgba(219, 55, 55, 0.3); + color:#ff7373; } + .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-danger:disabled, .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-danger.bp3-disabled{ + background:none; + color:rgba(255, 115, 115, 0.5); } + .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-danger:disabled.bp3-active, .bp3-dark .bp3-button-group.bp3-minimal .bp3-button.bp3-intent-danger.bp3-disabled.bp3-active{ + background:rgba(219, 55, 55, 0.3); } + .bp3-button-group .bp3-popover-wrapper, + .bp3-button-group .bp3-popover-target{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; + -webkit-box-flex:1; + -ms-flex:1 1 auto; + flex:1 1 auto; } + .bp3-button-group.bp3-fill{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; + width:100%; } + .bp3-button-group .bp3-button.bp3-fill, + .bp3-button-group.bp3-fill .bp3-button:not(.bp3-fixed){ + -webkit-box-flex:1; + -ms-flex:1 1 auto; + flex:1 1 auto; } + .bp3-button-group.bp3-vertical{ + -webkit-box-orient:vertical; + -webkit-box-direction:normal; + -ms-flex-direction:column; + flex-direction:column; + -webkit-box-align:stretch; + -ms-flex-align:stretch; + align-items:stretch; + vertical-align:top; } + .bp3-button-group.bp3-vertical.bp3-fill{ + width:unset; + height:100%; } + .bp3-button-group.bp3-vertical .bp3-button{ + margin-right:0 !important; + width:100%; } + .bp3-button-group.bp3-vertical:not(.bp3-minimal) > .bp3-popover-wrapper:first-child .bp3-button, + .bp3-button-group.bp3-vertical:not(.bp3-minimal) > .bp3-button:first-child{ + border-radius:3px 3px 0 0; } + .bp3-button-group.bp3-vertical:not(.bp3-minimal) > .bp3-popover-wrapper:last-child .bp3-button, + .bp3-button-group.bp3-vertical:not(.bp3-minimal) > .bp3-button:last-child{ + border-radius:0 0 3px 3px; } + .bp3-button-group.bp3-vertical:not(.bp3-minimal) > .bp3-popover-wrapper:not(:last-child) .bp3-button, + .bp3-button-group.bp3-vertical:not(.bp3-minimal) > .bp3-button:not(:last-child){ + margin-bottom:-1px; } + .bp3-button-group.bp3-align-left .bp3-button{ + text-align:left; } + .bp3-dark .bp3-button-group:not(.bp3-minimal) > .bp3-popover-wrapper:not(:last-child) .bp3-button, + .bp3-dark .bp3-button-group:not(.bp3-minimal) > .bp3-button:not(:last-child){ + margin-right:1px; } + .bp3-dark .bp3-button-group.bp3-vertical > .bp3-popover-wrapper:not(:last-child) .bp3-button, + .bp3-dark .bp3-button-group.bp3-vertical > .bp3-button:not(:last-child){ + margin-bottom:1px; } +.bp3-callout{ + line-height:1.5; + font-size:14px; + position:relative; + border-radius:3px; + background-color:rgba(138, 155, 168, 0.15); + width:100%; + padding:10px 12px 9px; } + .bp3-callout[class*="bp3-icon-"]{ + padding-left:40px; } + .bp3-callout[class*="bp3-icon-"]::before{ + line-height:1; + font-family:"Icons20", sans-serif; + font-size:20px; + font-weight:400; + font-style:normal; + -moz-osx-font-smoothing:grayscale; + -webkit-font-smoothing:antialiased; + position:absolute; + top:10px; + left:10px; + color:#5c7080; } + .bp3-callout.bp3-callout-icon{ + padding-left:40px; } + .bp3-callout.bp3-callout-icon > .bp3-icon:first-child{ + position:absolute; + top:10px; + left:10px; + color:#5c7080; } + .bp3-callout .bp3-heading{ + margin-top:0; + margin-bottom:5px; + line-height:20px; } + .bp3-callout .bp3-heading:last-child{ + margin-bottom:0; } + .bp3-dark .bp3-callout{ + background-color:rgba(138, 155, 168, 0.2); } + .bp3-dark .bp3-callout[class*="bp3-icon-"]::before{ + color:#a7b6c2; } + .bp3-callout.bp3-intent-primary{ + background-color:rgba(19, 124, 189, 0.15); } + .bp3-callout.bp3-intent-primary[class*="bp3-icon-"]::before, + .bp3-callout.bp3-intent-primary > .bp3-icon:first-child, + .bp3-callout.bp3-intent-primary .bp3-heading{ + color:#106ba3; } + .bp3-dark .bp3-callout.bp3-intent-primary{ + background-color:rgba(19, 124, 189, 0.25); } + .bp3-dark .bp3-callout.bp3-intent-primary[class*="bp3-icon-"]::before, + .bp3-dark .bp3-callout.bp3-intent-primary > .bp3-icon:first-child, + .bp3-dark .bp3-callout.bp3-intent-primary .bp3-heading{ + color:#48aff0; } + .bp3-callout.bp3-intent-success{ + background-color:rgba(15, 153, 96, 0.15); } + .bp3-callout.bp3-intent-success[class*="bp3-icon-"]::before, + .bp3-callout.bp3-intent-success > .bp3-icon:first-child, + .bp3-callout.bp3-intent-success .bp3-heading{ + color:#0d8050; } + .bp3-dark .bp3-callout.bp3-intent-success{ + background-color:rgba(15, 153, 96, 0.25); } + .bp3-dark .bp3-callout.bp3-intent-success[class*="bp3-icon-"]::before, + .bp3-dark .bp3-callout.bp3-intent-success > .bp3-icon:first-child, + .bp3-dark .bp3-callout.bp3-intent-success .bp3-heading{ + color:#3dcc91; } + .bp3-callout.bp3-intent-warning{ + background-color:rgba(217, 130, 43, 0.15); } + .bp3-callout.bp3-intent-warning[class*="bp3-icon-"]::before, + .bp3-callout.bp3-intent-warning > .bp3-icon:first-child, + .bp3-callout.bp3-intent-warning .bp3-heading{ + color:#bf7326; } + .bp3-dark .bp3-callout.bp3-intent-warning{ + background-color:rgba(217, 130, 43, 0.25); } + .bp3-dark .bp3-callout.bp3-intent-warning[class*="bp3-icon-"]::before, + .bp3-dark .bp3-callout.bp3-intent-warning > .bp3-icon:first-child, + .bp3-dark .bp3-callout.bp3-intent-warning .bp3-heading{ + color:#ffb366; } + .bp3-callout.bp3-intent-danger{ + background-color:rgba(219, 55, 55, 0.15); } + .bp3-callout.bp3-intent-danger[class*="bp3-icon-"]::before, + .bp3-callout.bp3-intent-danger > .bp3-icon:first-child, + .bp3-callout.bp3-intent-danger .bp3-heading{ + color:#c23030; } + .bp3-dark .bp3-callout.bp3-intent-danger{ + background-color:rgba(219, 55, 55, 0.25); } + .bp3-dark .bp3-callout.bp3-intent-danger[class*="bp3-icon-"]::before, + .bp3-dark .bp3-callout.bp3-intent-danger > .bp3-icon:first-child, + .bp3-dark .bp3-callout.bp3-intent-danger .bp3-heading{ + color:#ff7373; } + .bp3-running-text .bp3-callout{ + margin:20px 0; } +.bp3-card{ + border-radius:3px; + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.15), 0 0 0 rgba(16, 22, 26, 0), 0 0 0 rgba(16, 22, 26, 0); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.15), 0 0 0 rgba(16, 22, 26, 0), 0 0 0 rgba(16, 22, 26, 0); + background-color:#ffffff; + padding:20px; + -webkit-transition:-webkit-transform 200ms cubic-bezier(0.4, 1, 0.75, 0.9), -webkit-box-shadow 200ms cubic-bezier(0.4, 1, 0.75, 0.9); + transition:-webkit-transform 200ms cubic-bezier(0.4, 1, 0.75, 0.9), -webkit-box-shadow 200ms cubic-bezier(0.4, 1, 0.75, 0.9); + transition:transform 200ms cubic-bezier(0.4, 1, 0.75, 0.9), box-shadow 200ms cubic-bezier(0.4, 1, 0.75, 0.9); + transition:transform 200ms cubic-bezier(0.4, 1, 0.75, 0.9), box-shadow 200ms cubic-bezier(0.4, 1, 0.75, 0.9), -webkit-transform 200ms cubic-bezier(0.4, 1, 0.75, 0.9), -webkit-box-shadow 200ms cubic-bezier(0.4, 1, 0.75, 0.9); } + .bp3-card.bp3-dark, + .bp3-dark .bp3-card{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4), 0 0 0 rgba(16, 22, 26, 0), 0 0 0 rgba(16, 22, 26, 0); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4), 0 0 0 rgba(16, 22, 26, 0), 0 0 0 rgba(16, 22, 26, 0); + background-color:#30404d; } + +.bp3-elevation-0{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.15), 0 0 0 rgba(16, 22, 26, 0), 0 0 0 rgba(16, 22, 26, 0); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.15), 0 0 0 rgba(16, 22, 26, 0), 0 0 0 rgba(16, 22, 26, 0); } + .bp3-elevation-0.bp3-dark, + .bp3-dark .bp3-elevation-0{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4), 0 0 0 rgba(16, 22, 26, 0), 0 0 0 rgba(16, 22, 26, 0); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4), 0 0 0 rgba(16, 22, 26, 0), 0 0 0 rgba(16, 22, 26, 0); } + +.bp3-elevation-1{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 0 0 rgba(16, 22, 26, 0), 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 0 0 rgba(16, 22, 26, 0), 0 1px 1px rgba(16, 22, 26, 0.2); } + .bp3-elevation-1.bp3-dark, + .bp3-dark .bp3-elevation-1{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 0 0 rgba(16, 22, 26, 0), 0 1px 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 0 0 rgba(16, 22, 26, 0), 0 1px 1px rgba(16, 22, 26, 0.4); } + +.bp3-elevation-2{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 1px 1px rgba(16, 22, 26, 0.2), 0 2px 6px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 1px 1px rgba(16, 22, 26, 0.2), 0 2px 6px rgba(16, 22, 26, 0.2); } + .bp3-elevation-2.bp3-dark, + .bp3-dark .bp3-elevation-2{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 1px 1px rgba(16, 22, 26, 0.4), 0 2px 6px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 1px 1px rgba(16, 22, 26, 0.4), 0 2px 6px rgba(16, 22, 26, 0.4); } + +.bp3-elevation-3{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 2px 4px rgba(16, 22, 26, 0.2), 0 8px 24px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 2px 4px rgba(16, 22, 26, 0.2), 0 8px 24px rgba(16, 22, 26, 0.2); } + .bp3-elevation-3.bp3-dark, + .bp3-dark .bp3-elevation-3{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 2px 4px rgba(16, 22, 26, 0.4), 0 8px 24px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 2px 4px rgba(16, 22, 26, 0.4), 0 8px 24px rgba(16, 22, 26, 0.4); } + +.bp3-elevation-4{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 4px 8px rgba(16, 22, 26, 0.2), 0 18px 46px 6px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 4px 8px rgba(16, 22, 26, 0.2), 0 18px 46px 6px rgba(16, 22, 26, 0.2); } + .bp3-elevation-4.bp3-dark, + .bp3-dark .bp3-elevation-4{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 4px 8px rgba(16, 22, 26, 0.4), 0 18px 46px 6px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 4px 8px rgba(16, 22, 26, 0.4), 0 18px 46px 6px rgba(16, 22, 26, 0.4); } + +.bp3-card.bp3-interactive:hover{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 2px 4px rgba(16, 22, 26, 0.2), 0 8px 24px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 2px 4px rgba(16, 22, 26, 0.2), 0 8px 24px rgba(16, 22, 26, 0.2); + cursor:pointer; } + .bp3-card.bp3-interactive:hover.bp3-dark, + .bp3-dark .bp3-card.bp3-interactive:hover{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 2px 4px rgba(16, 22, 26, 0.4), 0 8px 24px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 2px 4px rgba(16, 22, 26, 0.4), 0 8px 24px rgba(16, 22, 26, 0.4); } + +.bp3-card.bp3-interactive:active{ + opacity:0.9; + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 0 0 rgba(16, 22, 26, 0), 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 0 0 rgba(16, 22, 26, 0), 0 1px 1px rgba(16, 22, 26, 0.2); + -webkit-transition-duration:0; + transition-duration:0; } + .bp3-card.bp3-interactive:active.bp3-dark, + .bp3-dark .bp3-card.bp3-interactive:active{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 0 0 rgba(16, 22, 26, 0), 0 1px 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 0 0 rgba(16, 22, 26, 0), 0 1px 1px rgba(16, 22, 26, 0.4); } + +.bp3-collapse{ + height:0; + overflow-y:hidden; + -webkit-transition:height 200ms cubic-bezier(0.4, 1, 0.75, 0.9); + transition:height 200ms cubic-bezier(0.4, 1, 0.75, 0.9); } + .bp3-collapse .bp3-collapse-body{ + -webkit-transition:-webkit-transform 200ms cubic-bezier(0.4, 1, 0.75, 0.9); + transition:-webkit-transform 200ms cubic-bezier(0.4, 1, 0.75, 0.9); + transition:transform 200ms cubic-bezier(0.4, 1, 0.75, 0.9); + transition:transform 200ms cubic-bezier(0.4, 1, 0.75, 0.9), -webkit-transform 200ms cubic-bezier(0.4, 1, 0.75, 0.9); } + .bp3-collapse .bp3-collapse-body[aria-hidden="true"]{ + display:none; } + +.bp3-context-menu .bp3-popover-target{ + display:block; } + +.bp3-context-menu-popover-target{ + position:fixed; } + +.bp3-divider{ + margin:5px; + border-right:1px solid rgba(16, 22, 26, 0.15); + border-bottom:1px solid rgba(16, 22, 26, 0.15); } + .bp3-dark .bp3-divider{ + border-color:rgba(16, 22, 26, 0.4); } +.bp3-dialog-container{ + opacity:1; + -webkit-transform:scale(1); + transform:scale(1); + display:-webkit-box; + display:-ms-flexbox; + display:flex; + -webkit-box-align:center; + -ms-flex-align:center; + align-items:center; + -webkit-box-pack:center; + -ms-flex-pack:center; + justify-content:center; + width:100%; + min-height:100%; + pointer-events:none; + -webkit-user-select:none; + -moz-user-select:none; + -ms-user-select:none; + user-select:none; } + .bp3-dialog-container.bp3-overlay-enter > .bp3-dialog, .bp3-dialog-container.bp3-overlay-appear > .bp3-dialog{ + opacity:0; + -webkit-transform:scale(0.5); + transform:scale(0.5); } + .bp3-dialog-container.bp3-overlay-enter-active > .bp3-dialog, .bp3-dialog-container.bp3-overlay-appear-active > .bp3-dialog{ + opacity:1; + -webkit-transform:scale(1); + transform:scale(1); + -webkit-transition-property:opacity, -webkit-transform; + transition-property:opacity, -webkit-transform; + transition-property:opacity, transform; + transition-property:opacity, transform, -webkit-transform; + -webkit-transition-duration:300ms; + transition-duration:300ms; + -webkit-transition-timing-function:cubic-bezier(0.54, 1.12, 0.38, 1.11); + transition-timing-function:cubic-bezier(0.54, 1.12, 0.38, 1.11); + -webkit-transition-delay:0; + transition-delay:0; } + .bp3-dialog-container.bp3-overlay-exit > .bp3-dialog{ + opacity:1; + -webkit-transform:scale(1); + transform:scale(1); } + .bp3-dialog-container.bp3-overlay-exit-active > .bp3-dialog{ + opacity:0; + -webkit-transform:scale(0.5); + transform:scale(0.5); + -webkit-transition-property:opacity, -webkit-transform; + transition-property:opacity, -webkit-transform; + transition-property:opacity, transform; + transition-property:opacity, transform, -webkit-transform; + -webkit-transition-duration:300ms; + transition-duration:300ms; + -webkit-transition-timing-function:cubic-bezier(0.54, 1.12, 0.38, 1.11); + transition-timing-function:cubic-bezier(0.54, 1.12, 0.38, 1.11); + -webkit-transition-delay:0; + transition-delay:0; } + +.bp3-dialog{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; + -webkit-box-orient:vertical; + -webkit-box-direction:normal; + -ms-flex-direction:column; + flex-direction:column; + margin:30px 0; + border-radius:6px; + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 4px 8px rgba(16, 22, 26, 0.2), 0 18px 46px 6px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 4px 8px rgba(16, 22, 26, 0.2), 0 18px 46px 6px rgba(16, 22, 26, 0.2); + background:#ebf1f5; + width:500px; + padding-bottom:20px; + pointer-events:all; + -webkit-user-select:text; + -moz-user-select:text; + -ms-user-select:text; + user-select:text; } + .bp3-dialog:focus{ + outline:0; } + .bp3-dialog.bp3-dark, + .bp3-dark .bp3-dialog{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 4px 8px rgba(16, 22, 26, 0.4), 0 18px 46px 6px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 4px 8px rgba(16, 22, 26, 0.4), 0 18px 46px 6px rgba(16, 22, 26, 0.4); + background:#293742; + color:#f5f8fa; } + +.bp3-dialog-header{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; + -webkit-box-flex:0; + -ms-flex:0 0 auto; + flex:0 0 auto; + -webkit-box-align:center; + -ms-flex-align:center; + align-items:center; + border-radius:6px 6px 0 0; + -webkit-box-shadow:0 1px 0 rgba(16, 22, 26, 0.15); + box-shadow:0 1px 0 rgba(16, 22, 26, 0.15); + background:#ffffff; + min-height:40px; + padding-right:5px; + padding-left:20px; } + .bp3-dialog-header .bp3-icon-large, + .bp3-dialog-header .bp3-icon{ + -webkit-box-flex:0; + -ms-flex:0 0 auto; + flex:0 0 auto; + margin-right:10px; + color:#5c7080; } + .bp3-dialog-header .bp3-heading{ + overflow:hidden; + text-overflow:ellipsis; + white-space:nowrap; + word-wrap:normal; + -webkit-box-flex:1; + -ms-flex:1 1 auto; + flex:1 1 auto; + margin:0; + line-height:inherit; } + .bp3-dialog-header .bp3-heading:last-child{ + margin-right:20px; } + .bp3-dark .bp3-dialog-header{ + -webkit-box-shadow:0 1px 0 rgba(16, 22, 26, 0.4); + box-shadow:0 1px 0 rgba(16, 22, 26, 0.4); + background:#30404d; } + .bp3-dark .bp3-dialog-header .bp3-icon-large, + .bp3-dark .bp3-dialog-header .bp3-icon{ + color:#a7b6c2; } + +.bp3-dialog-body{ + -webkit-box-flex:1; + -ms-flex:1 1 auto; + flex:1 1 auto; + margin:20px; + line-height:18px; } + +.bp3-dialog-footer{ + -webkit-box-flex:0; + -ms-flex:0 0 auto; + flex:0 0 auto; + margin:0 20px; } + +.bp3-dialog-footer-actions{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; + -webkit-box-pack:end; + -ms-flex-pack:end; + justify-content:flex-end; } + .bp3-dialog-footer-actions .bp3-button{ + margin-left:10px; } +.bp3-drawer{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; + -webkit-box-orient:vertical; + -webkit-box-direction:normal; + -ms-flex-direction:column; + flex-direction:column; + margin:0; + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 4px 8px rgba(16, 22, 26, 0.2), 0 18px 46px 6px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 4px 8px rgba(16, 22, 26, 0.2), 0 18px 46px 6px rgba(16, 22, 26, 0.2); + background:#ffffff; + padding:0; } + .bp3-drawer:focus{ + outline:0; } + .bp3-drawer.bp3-position-top{ + top:0; + right:0; + left:0; + height:50%; } + .bp3-drawer.bp3-position-top.bp3-overlay-enter, .bp3-drawer.bp3-position-top.bp3-overlay-appear{ + -webkit-transform:translateY(-100%); + transform:translateY(-100%); } + .bp3-drawer.bp3-position-top.bp3-overlay-enter-active, .bp3-drawer.bp3-position-top.bp3-overlay-appear-active{ + -webkit-transform:translateY(0); + transform:translateY(0); + -webkit-transition-property:-webkit-transform; + transition-property:-webkit-transform; + transition-property:transform; + transition-property:transform, -webkit-transform; + -webkit-transition-duration:200ms; + transition-duration:200ms; + -webkit-transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + -webkit-transition-delay:0; + transition-delay:0; } + .bp3-drawer.bp3-position-top.bp3-overlay-exit{ + -webkit-transform:translateY(0); + transform:translateY(0); } + .bp3-drawer.bp3-position-top.bp3-overlay-exit-active{ + -webkit-transform:translateY(-100%); + transform:translateY(-100%); + -webkit-transition-property:-webkit-transform; + transition-property:-webkit-transform; + transition-property:transform; + transition-property:transform, -webkit-transform; + -webkit-transition-duration:100ms; + transition-duration:100ms; + -webkit-transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + -webkit-transition-delay:0; + transition-delay:0; } + .bp3-drawer.bp3-position-bottom{ + right:0; + bottom:0; + left:0; + height:50%; } + .bp3-drawer.bp3-position-bottom.bp3-overlay-enter, .bp3-drawer.bp3-position-bottom.bp3-overlay-appear{ + -webkit-transform:translateY(100%); + transform:translateY(100%); } + .bp3-drawer.bp3-position-bottom.bp3-overlay-enter-active, .bp3-drawer.bp3-position-bottom.bp3-overlay-appear-active{ + -webkit-transform:translateY(0); + transform:translateY(0); + -webkit-transition-property:-webkit-transform; + transition-property:-webkit-transform; + transition-property:transform; + transition-property:transform, -webkit-transform; + -webkit-transition-duration:200ms; + transition-duration:200ms; + -webkit-transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + -webkit-transition-delay:0; + transition-delay:0; } + .bp3-drawer.bp3-position-bottom.bp3-overlay-exit{ + -webkit-transform:translateY(0); + transform:translateY(0); } + .bp3-drawer.bp3-position-bottom.bp3-overlay-exit-active{ + -webkit-transform:translateY(100%); + transform:translateY(100%); + -webkit-transition-property:-webkit-transform; + transition-property:-webkit-transform; + transition-property:transform; + transition-property:transform, -webkit-transform; + -webkit-transition-duration:100ms; + transition-duration:100ms; + -webkit-transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + -webkit-transition-delay:0; + transition-delay:0; } + .bp3-drawer.bp3-position-left{ + top:0; + bottom:0; + left:0; + width:50%; } + .bp3-drawer.bp3-position-left.bp3-overlay-enter, .bp3-drawer.bp3-position-left.bp3-overlay-appear{ + -webkit-transform:translateX(-100%); + transform:translateX(-100%); } + .bp3-drawer.bp3-position-left.bp3-overlay-enter-active, .bp3-drawer.bp3-position-left.bp3-overlay-appear-active{ + -webkit-transform:translateX(0); + transform:translateX(0); + -webkit-transition-property:-webkit-transform; + transition-property:-webkit-transform; + transition-property:transform; + transition-property:transform, -webkit-transform; + -webkit-transition-duration:200ms; + transition-duration:200ms; + -webkit-transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + -webkit-transition-delay:0; + transition-delay:0; } + .bp3-drawer.bp3-position-left.bp3-overlay-exit{ + -webkit-transform:translateX(0); + transform:translateX(0); } + .bp3-drawer.bp3-position-left.bp3-overlay-exit-active{ + -webkit-transform:translateX(-100%); + transform:translateX(-100%); + -webkit-transition-property:-webkit-transform; + transition-property:-webkit-transform; + transition-property:transform; + transition-property:transform, -webkit-transform; + -webkit-transition-duration:100ms; + transition-duration:100ms; + -webkit-transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + -webkit-transition-delay:0; + transition-delay:0; } + .bp3-drawer.bp3-position-right{ + top:0; + right:0; + bottom:0; + width:50%; } + .bp3-drawer.bp3-position-right.bp3-overlay-enter, .bp3-drawer.bp3-position-right.bp3-overlay-appear{ + -webkit-transform:translateX(100%); + transform:translateX(100%); } + .bp3-drawer.bp3-position-right.bp3-overlay-enter-active, .bp3-drawer.bp3-position-right.bp3-overlay-appear-active{ + -webkit-transform:translateX(0); + transform:translateX(0); + -webkit-transition-property:-webkit-transform; + transition-property:-webkit-transform; + transition-property:transform; + transition-property:transform, -webkit-transform; + -webkit-transition-duration:200ms; + transition-duration:200ms; + -webkit-transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + -webkit-transition-delay:0; + transition-delay:0; } + .bp3-drawer.bp3-position-right.bp3-overlay-exit{ + -webkit-transform:translateX(0); + transform:translateX(0); } + .bp3-drawer.bp3-position-right.bp3-overlay-exit-active{ + -webkit-transform:translateX(100%); + transform:translateX(100%); + -webkit-transition-property:-webkit-transform; + transition-property:-webkit-transform; + transition-property:transform; + transition-property:transform, -webkit-transform; + -webkit-transition-duration:100ms; + transition-duration:100ms; + -webkit-transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + -webkit-transition-delay:0; + transition-delay:0; } + .bp3-drawer:not(.bp3-position-top):not(.bp3-position-bottom):not(.bp3-position-left):not( + .bp3-position-right):not(.bp3-vertical){ + top:0; + right:0; + bottom:0; + width:50%; } + .bp3-drawer:not(.bp3-position-top):not(.bp3-position-bottom):not(.bp3-position-left):not( + .bp3-position-right):not(.bp3-vertical).bp3-overlay-enter, .bp3-drawer:not(.bp3-position-top):not(.bp3-position-bottom):not(.bp3-position-left):not( + .bp3-position-right):not(.bp3-vertical).bp3-overlay-appear{ + -webkit-transform:translateX(100%); + transform:translateX(100%); } + .bp3-drawer:not(.bp3-position-top):not(.bp3-position-bottom):not(.bp3-position-left):not( + .bp3-position-right):not(.bp3-vertical).bp3-overlay-enter-active, .bp3-drawer:not(.bp3-position-top):not(.bp3-position-bottom):not(.bp3-position-left):not( + .bp3-position-right):not(.bp3-vertical).bp3-overlay-appear-active{ + -webkit-transform:translateX(0); + transform:translateX(0); + -webkit-transition-property:-webkit-transform; + transition-property:-webkit-transform; + transition-property:transform; + transition-property:transform, -webkit-transform; + -webkit-transition-duration:200ms; + transition-duration:200ms; + -webkit-transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + -webkit-transition-delay:0; + transition-delay:0; } + .bp3-drawer:not(.bp3-position-top):not(.bp3-position-bottom):not(.bp3-position-left):not( + .bp3-position-right):not(.bp3-vertical).bp3-overlay-exit{ + -webkit-transform:translateX(0); + transform:translateX(0); } + .bp3-drawer:not(.bp3-position-top):not(.bp3-position-bottom):not(.bp3-position-left):not( + .bp3-position-right):not(.bp3-vertical).bp3-overlay-exit-active{ + -webkit-transform:translateX(100%); + transform:translateX(100%); + -webkit-transition-property:-webkit-transform; + transition-property:-webkit-transform; + transition-property:transform; + transition-property:transform, -webkit-transform; + -webkit-transition-duration:100ms; + transition-duration:100ms; + -webkit-transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + -webkit-transition-delay:0; + transition-delay:0; } + .bp3-drawer:not(.bp3-position-top):not(.bp3-position-bottom):not(.bp3-position-left):not( + .bp3-position-right).bp3-vertical{ + right:0; + bottom:0; + left:0; + height:50%; } + .bp3-drawer:not(.bp3-position-top):not(.bp3-position-bottom):not(.bp3-position-left):not( + .bp3-position-right).bp3-vertical.bp3-overlay-enter, .bp3-drawer:not(.bp3-position-top):not(.bp3-position-bottom):not(.bp3-position-left):not( + .bp3-position-right).bp3-vertical.bp3-overlay-appear{ + -webkit-transform:translateY(100%); + transform:translateY(100%); } + .bp3-drawer:not(.bp3-position-top):not(.bp3-position-bottom):not(.bp3-position-left):not( + .bp3-position-right).bp3-vertical.bp3-overlay-enter-active, .bp3-drawer:not(.bp3-position-top):not(.bp3-position-bottom):not(.bp3-position-left):not( + .bp3-position-right).bp3-vertical.bp3-overlay-appear-active{ + -webkit-transform:translateY(0); + transform:translateY(0); + -webkit-transition-property:-webkit-transform; + transition-property:-webkit-transform; + transition-property:transform; + transition-property:transform, -webkit-transform; + -webkit-transition-duration:200ms; + transition-duration:200ms; + -webkit-transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + -webkit-transition-delay:0; + transition-delay:0; } + .bp3-drawer:not(.bp3-position-top):not(.bp3-position-bottom):not(.bp3-position-left):not( + .bp3-position-right).bp3-vertical.bp3-overlay-exit{ + -webkit-transform:translateY(0); + transform:translateY(0); } + .bp3-drawer:not(.bp3-position-top):not(.bp3-position-bottom):not(.bp3-position-left):not( + .bp3-position-right).bp3-vertical.bp3-overlay-exit-active{ + -webkit-transform:translateY(100%); + transform:translateY(100%); + -webkit-transition-property:-webkit-transform; + transition-property:-webkit-transform; + transition-property:transform; + transition-property:transform, -webkit-transform; + -webkit-transition-duration:100ms; + transition-duration:100ms; + -webkit-transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + -webkit-transition-delay:0; + transition-delay:0; } + .bp3-drawer.bp3-dark, + .bp3-dark .bp3-drawer{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 4px 8px rgba(16, 22, 26, 0.4), 0 18px 46px 6px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 4px 8px rgba(16, 22, 26, 0.4), 0 18px 46px 6px rgba(16, 22, 26, 0.4); + background:#30404d; + color:#f5f8fa; } + +.bp3-drawer-header{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; + -webkit-box-flex:0; + -ms-flex:0 0 auto; + flex:0 0 auto; + -webkit-box-align:center; + -ms-flex-align:center; + align-items:center; + position:relative; + border-radius:0; + -webkit-box-shadow:0 1px 0 rgba(16, 22, 26, 0.15); + box-shadow:0 1px 0 rgba(16, 22, 26, 0.15); + min-height:40px; + padding:5px; + padding-left:20px; } + .bp3-drawer-header .bp3-icon-large, + .bp3-drawer-header .bp3-icon{ + -webkit-box-flex:0; + -ms-flex:0 0 auto; + flex:0 0 auto; + margin-right:10px; + color:#5c7080; } + .bp3-drawer-header .bp3-heading{ + overflow:hidden; + text-overflow:ellipsis; + white-space:nowrap; + word-wrap:normal; + -webkit-box-flex:1; + -ms-flex:1 1 auto; + flex:1 1 auto; + margin:0; + line-height:inherit; } + .bp3-drawer-header .bp3-heading:last-child{ + margin-right:20px; } + .bp3-dark .bp3-drawer-header{ + -webkit-box-shadow:0 1px 0 rgba(16, 22, 26, 0.4); + box-shadow:0 1px 0 rgba(16, 22, 26, 0.4); } + .bp3-dark .bp3-drawer-header .bp3-icon-large, + .bp3-dark .bp3-drawer-header .bp3-icon{ + color:#a7b6c2; } + +.bp3-drawer-body{ + -webkit-box-flex:1; + -ms-flex:1 1 auto; + flex:1 1 auto; + overflow:auto; + line-height:18px; } + +.bp3-drawer-footer{ + -webkit-box-flex:0; + -ms-flex:0 0 auto; + flex:0 0 auto; + position:relative; + -webkit-box-shadow:inset 0 1px 0 rgba(16, 22, 26, 0.15); + box-shadow:inset 0 1px 0 rgba(16, 22, 26, 0.15); + padding:10px 20px; } + .bp3-dark .bp3-drawer-footer{ + -webkit-box-shadow:inset 0 1px 0 rgba(16, 22, 26, 0.4); + box-shadow:inset 0 1px 0 rgba(16, 22, 26, 0.4); } +.bp3-editable-text{ + display:inline-block; + position:relative; + cursor:text; + max-width:100%; + vertical-align:top; + white-space:nowrap; } + .bp3-editable-text::before{ + position:absolute; + top:-3px; + right:-3px; + bottom:-3px; + left:-3px; + border-radius:3px; + content:""; + -webkit-transition:background-color 100ms cubic-bezier(0.4, 1, 0.75, 0.9), -webkit-box-shadow 100ms cubic-bezier(0.4, 1, 0.75, 0.9); + transition:background-color 100ms cubic-bezier(0.4, 1, 0.75, 0.9), -webkit-box-shadow 100ms cubic-bezier(0.4, 1, 0.75, 0.9); + transition:background-color 100ms cubic-bezier(0.4, 1, 0.75, 0.9), box-shadow 100ms cubic-bezier(0.4, 1, 0.75, 0.9); + transition:background-color 100ms cubic-bezier(0.4, 1, 0.75, 0.9), box-shadow 100ms cubic-bezier(0.4, 1, 0.75, 0.9), -webkit-box-shadow 100ms cubic-bezier(0.4, 1, 0.75, 0.9); } + .bp3-editable-text:hover::before{ + -webkit-box-shadow:0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), inset 0 0 0 1px rgba(16, 22, 26, 0.15); + box-shadow:0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), inset 0 0 0 1px rgba(16, 22, 26, 0.15); } + .bp3-editable-text.bp3-editable-text-editing::before{ + -webkit-box-shadow:0 0 0 1px #137cbd, 0 0 0 3px rgba(19, 124, 189, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px #137cbd, 0 0 0 3px rgba(19, 124, 189, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); + background-color:#ffffff; } + .bp3-editable-text.bp3-disabled::before{ + -webkit-box-shadow:none; + box-shadow:none; } + .bp3-editable-text.bp3-intent-primary .bp3-editable-text-input, + .bp3-editable-text.bp3-intent-primary .bp3-editable-text-content{ + color:#137cbd; } + .bp3-editable-text.bp3-intent-primary:hover::before{ + -webkit-box-shadow:0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), inset 0 0 0 1px rgba(19, 124, 189, 0.4); + box-shadow:0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), inset 0 0 0 1px rgba(19, 124, 189, 0.4); } + .bp3-editable-text.bp3-intent-primary.bp3-editable-text-editing::before{ + -webkit-box-shadow:0 0 0 1px #137cbd, 0 0 0 3px rgba(19, 124, 189, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px #137cbd, 0 0 0 3px rgba(19, 124, 189, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); } + .bp3-editable-text.bp3-intent-success .bp3-editable-text-input, + .bp3-editable-text.bp3-intent-success .bp3-editable-text-content{ + color:#0f9960; } + .bp3-editable-text.bp3-intent-success:hover::before{ + -webkit-box-shadow:0 0 0 0 rgba(15, 153, 96, 0), 0 0 0 0 rgba(15, 153, 96, 0), inset 0 0 0 1px rgba(15, 153, 96, 0.4); + box-shadow:0 0 0 0 rgba(15, 153, 96, 0), 0 0 0 0 rgba(15, 153, 96, 0), inset 0 0 0 1px rgba(15, 153, 96, 0.4); } + .bp3-editable-text.bp3-intent-success.bp3-editable-text-editing::before{ + -webkit-box-shadow:0 0 0 1px #0f9960, 0 0 0 3px rgba(15, 153, 96, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px #0f9960, 0 0 0 3px rgba(15, 153, 96, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); } + .bp3-editable-text.bp3-intent-warning .bp3-editable-text-input, + .bp3-editable-text.bp3-intent-warning .bp3-editable-text-content{ + color:#d9822b; } + .bp3-editable-text.bp3-intent-warning:hover::before{ + -webkit-box-shadow:0 0 0 0 rgba(217, 130, 43, 0), 0 0 0 0 rgba(217, 130, 43, 0), inset 0 0 0 1px rgba(217, 130, 43, 0.4); + box-shadow:0 0 0 0 rgba(217, 130, 43, 0), 0 0 0 0 rgba(217, 130, 43, 0), inset 0 0 0 1px rgba(217, 130, 43, 0.4); } + .bp3-editable-text.bp3-intent-warning.bp3-editable-text-editing::before{ + -webkit-box-shadow:0 0 0 1px #d9822b, 0 0 0 3px rgba(217, 130, 43, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px #d9822b, 0 0 0 3px rgba(217, 130, 43, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); } + .bp3-editable-text.bp3-intent-danger .bp3-editable-text-input, + .bp3-editable-text.bp3-intent-danger .bp3-editable-text-content{ + color:#db3737; } + .bp3-editable-text.bp3-intent-danger:hover::before{ + -webkit-box-shadow:0 0 0 0 rgba(219, 55, 55, 0), 0 0 0 0 rgba(219, 55, 55, 0), inset 0 0 0 1px rgba(219, 55, 55, 0.4); + box-shadow:0 0 0 0 rgba(219, 55, 55, 0), 0 0 0 0 rgba(219, 55, 55, 0), inset 0 0 0 1px rgba(219, 55, 55, 0.4); } + .bp3-editable-text.bp3-intent-danger.bp3-editable-text-editing::before{ + -webkit-box-shadow:0 0 0 1px #db3737, 0 0 0 3px rgba(219, 55, 55, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px #db3737, 0 0 0 3px rgba(219, 55, 55, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); } + .bp3-dark .bp3-editable-text:hover::before{ + -webkit-box-shadow:0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), inset 0 0 0 1px rgba(255, 255, 255, 0.15); + box-shadow:0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), inset 0 0 0 1px rgba(255, 255, 255, 0.15); } + .bp3-dark .bp3-editable-text.bp3-editable-text-editing::before{ + -webkit-box-shadow:0 0 0 1px #137cbd, 0 0 0 3px rgba(19, 124, 189, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px #137cbd, 0 0 0 3px rgba(19, 124, 189, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); + background-color:rgba(16, 22, 26, 0.3); } + .bp3-dark .bp3-editable-text.bp3-disabled::before{ + -webkit-box-shadow:none; + box-shadow:none; } + .bp3-dark .bp3-editable-text.bp3-intent-primary .bp3-editable-text-content{ + color:#48aff0; } + .bp3-dark .bp3-editable-text.bp3-intent-primary:hover::before{ + -webkit-box-shadow:0 0 0 0 rgba(72, 175, 240, 0), 0 0 0 0 rgba(72, 175, 240, 0), inset 0 0 0 1px rgba(72, 175, 240, 0.4); + box-shadow:0 0 0 0 rgba(72, 175, 240, 0), 0 0 0 0 rgba(72, 175, 240, 0), inset 0 0 0 1px rgba(72, 175, 240, 0.4); } + .bp3-dark .bp3-editable-text.bp3-intent-primary.bp3-editable-text-editing::before{ + -webkit-box-shadow:0 0 0 1px #48aff0, 0 0 0 3px rgba(72, 175, 240, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px #48aff0, 0 0 0 3px rgba(72, 175, 240, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); } + .bp3-dark .bp3-editable-text.bp3-intent-success .bp3-editable-text-content{ + color:#3dcc91; } + .bp3-dark .bp3-editable-text.bp3-intent-success:hover::before{ + -webkit-box-shadow:0 0 0 0 rgba(61, 204, 145, 0), 0 0 0 0 rgba(61, 204, 145, 0), inset 0 0 0 1px rgba(61, 204, 145, 0.4); + box-shadow:0 0 0 0 rgba(61, 204, 145, 0), 0 0 0 0 rgba(61, 204, 145, 0), inset 0 0 0 1px rgba(61, 204, 145, 0.4); } + .bp3-dark .bp3-editable-text.bp3-intent-success.bp3-editable-text-editing::before{ + -webkit-box-shadow:0 0 0 1px #3dcc91, 0 0 0 3px rgba(61, 204, 145, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px #3dcc91, 0 0 0 3px rgba(61, 204, 145, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); } + .bp3-dark .bp3-editable-text.bp3-intent-warning .bp3-editable-text-content{ + color:#ffb366; } + .bp3-dark .bp3-editable-text.bp3-intent-warning:hover::before{ + -webkit-box-shadow:0 0 0 0 rgba(255, 179, 102, 0), 0 0 0 0 rgba(255, 179, 102, 0), inset 0 0 0 1px rgba(255, 179, 102, 0.4); + box-shadow:0 0 0 0 rgba(255, 179, 102, 0), 0 0 0 0 rgba(255, 179, 102, 0), inset 0 0 0 1px rgba(255, 179, 102, 0.4); } + .bp3-dark .bp3-editable-text.bp3-intent-warning.bp3-editable-text-editing::before{ + -webkit-box-shadow:0 0 0 1px #ffb366, 0 0 0 3px rgba(255, 179, 102, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px #ffb366, 0 0 0 3px rgba(255, 179, 102, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); } + .bp3-dark .bp3-editable-text.bp3-intent-danger .bp3-editable-text-content{ + color:#ff7373; } + .bp3-dark .bp3-editable-text.bp3-intent-danger:hover::before{ + -webkit-box-shadow:0 0 0 0 rgba(255, 115, 115, 0), 0 0 0 0 rgba(255, 115, 115, 0), inset 0 0 0 1px rgba(255, 115, 115, 0.4); + box-shadow:0 0 0 0 rgba(255, 115, 115, 0), 0 0 0 0 rgba(255, 115, 115, 0), inset 0 0 0 1px rgba(255, 115, 115, 0.4); } + .bp3-dark .bp3-editable-text.bp3-intent-danger.bp3-editable-text-editing::before{ + -webkit-box-shadow:0 0 0 1px #ff7373, 0 0 0 3px rgba(255, 115, 115, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px #ff7373, 0 0 0 3px rgba(255, 115, 115, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); } + +.bp3-editable-text-input, +.bp3-editable-text-content{ + display:inherit; + position:relative; + min-width:inherit; + max-width:inherit; + vertical-align:top; + text-transform:inherit; + letter-spacing:inherit; + color:inherit; + font:inherit; + resize:none; } + +.bp3-editable-text-input{ + border:none; + -webkit-box-shadow:none; + box-shadow:none; + background:none; + width:100%; + padding:0; + white-space:pre-wrap; } + .bp3-editable-text-input::-webkit-input-placeholder{ + opacity:1; + color:rgba(92, 112, 128, 0.6); } + .bp3-editable-text-input::-moz-placeholder{ + opacity:1; + color:rgba(92, 112, 128, 0.6); } + .bp3-editable-text-input:-ms-input-placeholder{ + opacity:1; + color:rgba(92, 112, 128, 0.6); } + .bp3-editable-text-input::-ms-input-placeholder{ + opacity:1; + color:rgba(92, 112, 128, 0.6); } + .bp3-editable-text-input::placeholder{ + opacity:1; + color:rgba(92, 112, 128, 0.6); } + .bp3-editable-text-input:focus{ + outline:none; } + .bp3-editable-text-input::-ms-clear{ + display:none; } + +.bp3-editable-text-content{ + overflow:hidden; + padding-right:2px; + text-overflow:ellipsis; + white-space:pre; } + .bp3-editable-text-editing > .bp3-editable-text-content{ + position:absolute; + left:0; + visibility:hidden; } + .bp3-editable-text-placeholder > .bp3-editable-text-content{ + color:rgba(92, 112, 128, 0.6); } + .bp3-dark .bp3-editable-text-placeholder > .bp3-editable-text-content{ + color:rgba(167, 182, 194, 0.6); } + +.bp3-editable-text.bp3-multiline{ + display:block; } + .bp3-editable-text.bp3-multiline .bp3-editable-text-content{ + overflow:auto; + white-space:pre-wrap; + word-wrap:break-word; } +.bp3-control-group{ + -webkit-transform:translateZ(0); + transform:translateZ(0); + display:-webkit-box; + display:-ms-flexbox; + display:flex; + -webkit-box-orient:horizontal; + -webkit-box-direction:normal; + -ms-flex-direction:row; + flex-direction:row; + -webkit-box-align:stretch; + -ms-flex-align:stretch; + align-items:stretch; } + .bp3-control-group > *{ + -webkit-box-flex:0; + -ms-flex-positive:0; + flex-grow:0; + -ms-flex-negative:0; + flex-shrink:0; } + .bp3-control-group > .bp3-fill{ + -webkit-box-flex:1; + -ms-flex-positive:1; + flex-grow:1; + -ms-flex-negative:1; + flex-shrink:1; } + .bp3-control-group .bp3-button, + .bp3-control-group .bp3-html-select, + .bp3-control-group .bp3-input, + .bp3-control-group .bp3-select{ + position:relative; } + .bp3-control-group .bp3-input{ + z-index:2; + border-radius:inherit; } + .bp3-control-group .bp3-input:focus{ + z-index:14; + border-radius:3px; } + .bp3-control-group .bp3-input[class*="bp3-intent"]{ + z-index:13; } + .bp3-control-group .bp3-input[class*="bp3-intent"]:focus{ + z-index:15; } + .bp3-control-group .bp3-input[readonly], .bp3-control-group .bp3-input:disabled, .bp3-control-group .bp3-input.bp3-disabled{ + z-index:1; } + .bp3-control-group .bp3-input-group[class*="bp3-intent"] .bp3-input{ + z-index:13; } + .bp3-control-group .bp3-input-group[class*="bp3-intent"] .bp3-input:focus{ + z-index:15; } + .bp3-control-group .bp3-button, + .bp3-control-group .bp3-html-select select, + .bp3-control-group .bp3-select select{ + -webkit-transform:translateZ(0); + transform:translateZ(0); + z-index:4; + border-radius:inherit; } + .bp3-control-group .bp3-button:focus, + .bp3-control-group .bp3-html-select select:focus, + .bp3-control-group .bp3-select select:focus{ + z-index:5; } + .bp3-control-group .bp3-button:hover, + .bp3-control-group .bp3-html-select select:hover, + .bp3-control-group .bp3-select select:hover{ + z-index:6; } + .bp3-control-group .bp3-button:active, + .bp3-control-group .bp3-html-select select:active, + .bp3-control-group .bp3-select select:active{ + z-index:7; } + .bp3-control-group .bp3-button[readonly], .bp3-control-group .bp3-button:disabled, .bp3-control-group .bp3-button.bp3-disabled, + .bp3-control-group .bp3-html-select select[readonly], + .bp3-control-group .bp3-html-select select:disabled, + .bp3-control-group .bp3-html-select select.bp3-disabled, + .bp3-control-group .bp3-select select[readonly], + .bp3-control-group .bp3-select select:disabled, + .bp3-control-group .bp3-select select.bp3-disabled{ + z-index:3; } + .bp3-control-group .bp3-button[class*="bp3-intent"], + .bp3-control-group .bp3-html-select select[class*="bp3-intent"], + .bp3-control-group .bp3-select select[class*="bp3-intent"]{ + z-index:9; } + .bp3-control-group .bp3-button[class*="bp3-intent"]:focus, + .bp3-control-group .bp3-html-select select[class*="bp3-intent"]:focus, + .bp3-control-group .bp3-select select[class*="bp3-intent"]:focus{ + z-index:10; } + .bp3-control-group .bp3-button[class*="bp3-intent"]:hover, + .bp3-control-group .bp3-html-select select[class*="bp3-intent"]:hover, + .bp3-control-group .bp3-select select[class*="bp3-intent"]:hover{ + z-index:11; } + .bp3-control-group .bp3-button[class*="bp3-intent"]:active, + .bp3-control-group .bp3-html-select select[class*="bp3-intent"]:active, + .bp3-control-group .bp3-select select[class*="bp3-intent"]:active{ + z-index:12; } + .bp3-control-group .bp3-button[class*="bp3-intent"][readonly], .bp3-control-group .bp3-button[class*="bp3-intent"]:disabled, .bp3-control-group .bp3-button[class*="bp3-intent"].bp3-disabled, + .bp3-control-group .bp3-html-select select[class*="bp3-intent"][readonly], + .bp3-control-group .bp3-html-select select[class*="bp3-intent"]:disabled, + .bp3-control-group .bp3-html-select select[class*="bp3-intent"].bp3-disabled, + .bp3-control-group .bp3-select select[class*="bp3-intent"][readonly], + .bp3-control-group .bp3-select select[class*="bp3-intent"]:disabled, + .bp3-control-group .bp3-select select[class*="bp3-intent"].bp3-disabled{ + z-index:8; } + .bp3-control-group .bp3-input-group > .bp3-icon, + .bp3-control-group .bp3-input-group > .bp3-button, + .bp3-control-group .bp3-input-group > .bp3-input-action{ + z-index:16; } + .bp3-control-group .bp3-select::after, + .bp3-control-group .bp3-html-select::after, + .bp3-control-group .bp3-select > .bp3-icon, + .bp3-control-group .bp3-html-select > .bp3-icon{ + z-index:17; } + .bp3-control-group:not(.bp3-vertical) > *{ + margin-right:-1px; } + .bp3-dark .bp3-control-group:not(.bp3-vertical) > *{ + margin-right:0; } + .bp3-dark .bp3-control-group:not(.bp3-vertical) > .bp3-button + .bp3-button{ + margin-left:1px; } + .bp3-control-group .bp3-popover-wrapper, + .bp3-control-group .bp3-popover-target{ + border-radius:inherit; } + .bp3-control-group > :first-child{ + border-radius:3px 0 0 3px; } + .bp3-control-group > :last-child{ + margin-right:0; + border-radius:0 3px 3px 0; } + .bp3-control-group > :only-child{ + margin-right:0; + border-radius:3px; } + .bp3-control-group .bp3-input-group .bp3-button{ + border-radius:3px; } + .bp3-control-group > .bp3-fill{ + -webkit-box-flex:1; + -ms-flex:1 1 auto; + flex:1 1 auto; } + .bp3-control-group.bp3-fill > *:not(.bp3-fixed){ + -webkit-box-flex:1; + -ms-flex:1 1 auto; + flex:1 1 auto; } + .bp3-control-group.bp3-vertical{ + -webkit-box-orient:vertical; + -webkit-box-direction:normal; + -ms-flex-direction:column; + flex-direction:column; } + .bp3-control-group.bp3-vertical > *{ + margin-top:-1px; } + .bp3-control-group.bp3-vertical > :first-child{ + margin-top:0; + border-radius:3px 3px 0 0; } + .bp3-control-group.bp3-vertical > :last-child{ + border-radius:0 0 3px 3px; } +.bp3-control{ + display:block; + position:relative; + margin-bottom:10px; + cursor:pointer; + text-transform:none; } + .bp3-control input:checked ~ .bp3-control-indicator{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 -1px 0 rgba(16, 22, 26, 0.2); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 -1px 0 rgba(16, 22, 26, 0.2); + background-color:#137cbd; + background-image:-webkit-gradient(linear, left top, left bottom, from(rgba(255, 255, 255, 0.1)), to(rgba(255, 255, 255, 0))); + background-image:linear-gradient(to bottom, rgba(255, 255, 255, 0.1), rgba(255, 255, 255, 0)); + color:#ffffff; } + .bp3-control:hover input:checked ~ .bp3-control-indicator{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 -1px 0 rgba(16, 22, 26, 0.2); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 -1px 0 rgba(16, 22, 26, 0.2); + background-color:#106ba3; } + .bp3-control input:not(:disabled):active:checked ~ .bp3-control-indicator{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 1px 2px rgba(16, 22, 26, 0.2); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 1px 2px rgba(16, 22, 26, 0.2); + background:#0e5a8a; } + .bp3-control input:disabled:checked ~ .bp3-control-indicator{ + -webkit-box-shadow:none; + box-shadow:none; + background:rgba(19, 124, 189, 0.5); } + .bp3-dark .bp3-control input:checked ~ .bp3-control-indicator{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); } + .bp3-dark .bp3-control:hover input:checked ~ .bp3-control-indicator{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + background-color:#106ba3; } + .bp3-dark .bp3-control input:not(:disabled):active:checked ~ .bp3-control-indicator{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 1px 2px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 1px 2px rgba(16, 22, 26, 0.2); + background-color:#0e5a8a; } + .bp3-dark .bp3-control input:disabled:checked ~ .bp3-control-indicator{ + -webkit-box-shadow:none; + box-shadow:none; + background:rgba(14, 90, 138, 0.5); } + .bp3-control:not(.bp3-align-right){ + padding-left:26px; } + .bp3-control:not(.bp3-align-right) .bp3-control-indicator{ + margin-left:-26px; } + .bp3-control.bp3-align-right{ + padding-right:26px; } + .bp3-control.bp3-align-right .bp3-control-indicator{ + margin-right:-26px; } + .bp3-control.bp3-disabled{ + cursor:not-allowed; + color:rgba(92, 112, 128, 0.6); } + .bp3-control.bp3-inline{ + display:inline-block; + margin-right:20px; } + .bp3-control input{ + position:absolute; + top:0; + left:0; + opacity:0; + z-index:-1; } + .bp3-control .bp3-control-indicator{ + display:inline-block; + position:relative; + margin-top:-3px; + margin-right:10px; + border:none; + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 -1px 0 rgba(16, 22, 26, 0.1); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 -1px 0 rgba(16, 22, 26, 0.1); + background-clip:padding-box; + background-color:#f5f8fa; + background-image:-webkit-gradient(linear, left top, left bottom, from(rgba(255, 255, 255, 0.8)), to(rgba(255, 255, 255, 0))); + background-image:linear-gradient(to bottom, rgba(255, 255, 255, 0.8), rgba(255, 255, 255, 0)); + cursor:pointer; + width:1em; + height:1em; + vertical-align:middle; + font-size:16px; + -webkit-user-select:none; + -moz-user-select:none; + -ms-user-select:none; + user-select:none; } + .bp3-control .bp3-control-indicator::before{ + display:block; + width:1em; + height:1em; + content:""; } + .bp3-control:hover .bp3-control-indicator{ + background-color:#ebf1f5; } + .bp3-control input:not(:disabled):active ~ .bp3-control-indicator{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 1px 2px rgba(16, 22, 26, 0.2); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 1px 2px rgba(16, 22, 26, 0.2); + background:#d8e1e8; } + .bp3-control input:disabled ~ .bp3-control-indicator{ + -webkit-box-shadow:none; + box-shadow:none; + background:rgba(206, 217, 224, 0.5); + cursor:not-allowed; } + .bp3-control input:focus ~ .bp3-control-indicator{ + outline:rgba(19, 124, 189, 0.6) auto 2px; + outline-offset:2px; + -moz-outline-radius:6px; } + .bp3-control.bp3-align-right .bp3-control-indicator{ + float:right; + margin-top:1px; + margin-left:10px; } + .bp3-control.bp3-large{ + font-size:16px; } + .bp3-control.bp3-large:not(.bp3-align-right){ + padding-left:30px; } + .bp3-control.bp3-large:not(.bp3-align-right) .bp3-control-indicator{ + margin-left:-30px; } + .bp3-control.bp3-large.bp3-align-right{ + padding-right:30px; } + .bp3-control.bp3-large.bp3-align-right .bp3-control-indicator{ + margin-right:-30px; } + .bp3-control.bp3-large .bp3-control-indicator{ + font-size:20px; } + .bp3-control.bp3-large.bp3-align-right .bp3-control-indicator{ + margin-top:0; } + .bp3-control.bp3-checkbox input:indeterminate ~ .bp3-control-indicator{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 -1px 0 rgba(16, 22, 26, 0.2); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 -1px 0 rgba(16, 22, 26, 0.2); + background-color:#137cbd; + background-image:-webkit-gradient(linear, left top, left bottom, from(rgba(255, 255, 255, 0.1)), to(rgba(255, 255, 255, 0))); + background-image:linear-gradient(to bottom, rgba(255, 255, 255, 0.1), rgba(255, 255, 255, 0)); + color:#ffffff; } + .bp3-control.bp3-checkbox:hover input:indeterminate ~ .bp3-control-indicator{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 -1px 0 rgba(16, 22, 26, 0.2); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 -1px 0 rgba(16, 22, 26, 0.2); + background-color:#106ba3; } + .bp3-control.bp3-checkbox input:not(:disabled):active:indeterminate ~ .bp3-control-indicator{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 1px 2px rgba(16, 22, 26, 0.2); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 1px 2px rgba(16, 22, 26, 0.2); + background:#0e5a8a; } + .bp3-control.bp3-checkbox input:disabled:indeterminate ~ .bp3-control-indicator{ + -webkit-box-shadow:none; + box-shadow:none; + background:rgba(19, 124, 189, 0.5); } + .bp3-dark .bp3-control.bp3-checkbox input:indeterminate ~ .bp3-control-indicator{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); } + .bp3-dark .bp3-control.bp3-checkbox:hover input:indeterminate ~ .bp3-control-indicator{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + background-color:#106ba3; } + .bp3-dark .bp3-control.bp3-checkbox input:not(:disabled):active:indeterminate ~ .bp3-control-indicator{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 1px 2px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4), inset 0 1px 2px rgba(16, 22, 26, 0.2); + background-color:#0e5a8a; } + .bp3-dark .bp3-control.bp3-checkbox input:disabled:indeterminate ~ .bp3-control-indicator{ + -webkit-box-shadow:none; + box-shadow:none; + background:rgba(14, 90, 138, 0.5); } + .bp3-control.bp3-checkbox .bp3-control-indicator{ + border-radius:3px; } + .bp3-control.bp3-checkbox input:checked ~ .bp3-control-indicator::before{ + background-image:url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16'%3e%3cpath fill-rule='evenodd' clip-rule='evenodd' d='M12 5c-.28 0-.53.11-.71.29L7 9.59l-2.29-2.3a1.003 1.003 0 0 0-1.42 1.42l3 3c.18.18.43.29.71.29s.53-.11.71-.29l5-5A1.003 1.003 0 0 0 12 5z' fill='white'/%3e%3c/svg%3e"); } + .bp3-control.bp3-checkbox input:indeterminate ~ .bp3-control-indicator::before{ + background-image:url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16'%3e%3cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 7H5c-.55 0-1 .45-1 1s.45 1 1 1h6c.55 0 1-.45 1-1s-.45-1-1-1z' fill='white'/%3e%3c/svg%3e"); } + .bp3-control.bp3-radio .bp3-control-indicator{ + border-radius:50%; } + .bp3-control.bp3-radio input:checked ~ .bp3-control-indicator::before{ + background-image:radial-gradient(#ffffff, #ffffff 28%, transparent 32%); } + .bp3-control.bp3-radio input:checked:disabled ~ .bp3-control-indicator::before{ + opacity:0.5; } + .bp3-control.bp3-radio input:focus ~ .bp3-control-indicator{ + -moz-outline-radius:16px; } + .bp3-control.bp3-switch input ~ .bp3-control-indicator{ + background:rgba(167, 182, 194, 0.5); } + .bp3-control.bp3-switch:hover input ~ .bp3-control-indicator{ + background:rgba(115, 134, 148, 0.5); } + .bp3-control.bp3-switch input:not(:disabled):active ~ .bp3-control-indicator{ + background:rgba(92, 112, 128, 0.5); } + .bp3-control.bp3-switch input:disabled ~ .bp3-control-indicator{ + background:rgba(206, 217, 224, 0.5); } + .bp3-control.bp3-switch input:disabled ~ .bp3-control-indicator::before{ + background:rgba(255, 255, 255, 0.8); } + .bp3-control.bp3-switch input:checked ~ .bp3-control-indicator{ + background:#137cbd; } + .bp3-control.bp3-switch:hover input:checked ~ .bp3-control-indicator{ + background:#106ba3; } + .bp3-control.bp3-switch input:checked:not(:disabled):active ~ .bp3-control-indicator{ + background:#0e5a8a; } + .bp3-control.bp3-switch input:checked:disabled ~ .bp3-control-indicator{ + background:rgba(19, 124, 189, 0.5); } + .bp3-control.bp3-switch input:checked:disabled ~ .bp3-control-indicator::before{ + background:rgba(255, 255, 255, 0.8); } + .bp3-control.bp3-switch:not(.bp3-align-right){ + padding-left:38px; } + .bp3-control.bp3-switch:not(.bp3-align-right) .bp3-control-indicator{ + margin-left:-38px; } + .bp3-control.bp3-switch.bp3-align-right{ + padding-right:38px; } + .bp3-control.bp3-switch.bp3-align-right .bp3-control-indicator{ + margin-right:-38px; } + .bp3-control.bp3-switch .bp3-control-indicator{ + border:none; + border-radius:1.75em; + -webkit-box-shadow:none !important; + box-shadow:none !important; + width:auto; + min-width:1.75em; + -webkit-transition:background-color 100ms cubic-bezier(0.4, 1, 0.75, 0.9); + transition:background-color 100ms cubic-bezier(0.4, 1, 0.75, 0.9); } + .bp3-control.bp3-switch .bp3-control-indicator::before{ + position:absolute; + left:0; + margin:2px; + border-radius:50%; + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 1px 1px rgba(16, 22, 26, 0.2); + background:#ffffff; + width:calc(1em - 4px); + height:calc(1em - 4px); + -webkit-transition:left 100ms cubic-bezier(0.4, 1, 0.75, 0.9); + transition:left 100ms cubic-bezier(0.4, 1, 0.75, 0.9); } + .bp3-control.bp3-switch input:checked ~ .bp3-control-indicator::before{ + left:calc(100% - 1em); } + .bp3-control.bp3-switch.bp3-large:not(.bp3-align-right){ + padding-left:45px; } + .bp3-control.bp3-switch.bp3-large:not(.bp3-align-right) .bp3-control-indicator{ + margin-left:-45px; } + .bp3-control.bp3-switch.bp3-large.bp3-align-right{ + padding-right:45px; } + .bp3-control.bp3-switch.bp3-large.bp3-align-right .bp3-control-indicator{ + margin-right:-45px; } + .bp3-dark .bp3-control.bp3-switch input ~ .bp3-control-indicator{ + background:rgba(16, 22, 26, 0.5); } + .bp3-dark .bp3-control.bp3-switch:hover input ~ .bp3-control-indicator{ + background:rgba(16, 22, 26, 0.7); } + .bp3-dark .bp3-control.bp3-switch input:not(:disabled):active ~ .bp3-control-indicator{ + background:rgba(16, 22, 26, 0.9); } + .bp3-dark .bp3-control.bp3-switch input:disabled ~ .bp3-control-indicator{ + background:rgba(57, 75, 89, 0.5); } + .bp3-dark .bp3-control.bp3-switch input:disabled ~ .bp3-control-indicator::before{ + background:rgba(16, 22, 26, 0.4); } + .bp3-dark .bp3-control.bp3-switch input:checked ~ .bp3-control-indicator{ + background:#137cbd; } + .bp3-dark .bp3-control.bp3-switch:hover input:checked ~ .bp3-control-indicator{ + background:#106ba3; } + .bp3-dark .bp3-control.bp3-switch input:checked:not(:disabled):active ~ .bp3-control-indicator{ + background:#0e5a8a; } + .bp3-dark .bp3-control.bp3-switch input:checked:disabled ~ .bp3-control-indicator{ + background:rgba(14, 90, 138, 0.5); } + .bp3-dark .bp3-control.bp3-switch input:checked:disabled ~ .bp3-control-indicator::before{ + background:rgba(16, 22, 26, 0.4); } + .bp3-dark .bp3-control.bp3-switch .bp3-control-indicator::before{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + background:#394b59; } + .bp3-dark .bp3-control.bp3-switch input:checked ~ .bp3-control-indicator::before{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4); } + .bp3-control.bp3-switch .bp3-switch-inner-text{ + text-align:center; + font-size:0.7em; } + .bp3-control.bp3-switch .bp3-control-indicator-child:first-child{ + visibility:hidden; + margin-right:1.2em; + margin-left:0.5em; + line-height:0; } + .bp3-control.bp3-switch .bp3-control-indicator-child:last-child{ + visibility:visible; + margin-right:0.5em; + margin-left:1.2em; + line-height:1em; } + .bp3-control.bp3-switch input:checked ~ .bp3-control-indicator .bp3-control-indicator-child:first-child{ + visibility:visible; + line-height:1em; } + .bp3-control.bp3-switch input:checked ~ .bp3-control-indicator .bp3-control-indicator-child:last-child{ + visibility:hidden; + line-height:0; } + .bp3-dark .bp3-control{ + color:#f5f8fa; } + .bp3-dark .bp3-control.bp3-disabled{ + color:rgba(167, 182, 194, 0.6); } + .bp3-dark .bp3-control .bp3-control-indicator{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + background-color:#394b59; + background-image:-webkit-gradient(linear, left top, left bottom, from(rgba(255, 255, 255, 0.05)), to(rgba(255, 255, 255, 0))); + background-image:linear-gradient(to bottom, rgba(255, 255, 255, 0.05), rgba(255, 255, 255, 0)); } + .bp3-dark .bp3-control:hover .bp3-control-indicator{ + background-color:#30404d; } + .bp3-dark .bp3-control input:not(:disabled):active ~ .bp3-control-indicator{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.6), inset 0 1px 2px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.6), inset 0 1px 2px rgba(16, 22, 26, 0.2); + background:#202b33; } + .bp3-dark .bp3-control input:disabled ~ .bp3-control-indicator{ + -webkit-box-shadow:none; + box-shadow:none; + background:rgba(57, 75, 89, 0.5); + cursor:not-allowed; } + .bp3-dark .bp3-control.bp3-checkbox input:disabled:checked ~ .bp3-control-indicator, .bp3-dark .bp3-control.bp3-checkbox input:disabled:indeterminate ~ .bp3-control-indicator{ + color:rgba(167, 182, 194, 0.6); } +.bp3-file-input{ + display:inline-block; + position:relative; + cursor:pointer; + height:30px; } + .bp3-file-input input{ + opacity:0; + margin:0; + min-width:200px; } + .bp3-file-input input:disabled + .bp3-file-upload-input, + .bp3-file-input input.bp3-disabled + .bp3-file-upload-input{ + -webkit-box-shadow:none; + box-shadow:none; + background:rgba(206, 217, 224, 0.5); + cursor:not-allowed; + color:rgba(92, 112, 128, 0.6); + resize:none; } + .bp3-file-input input:disabled + .bp3-file-upload-input::after, + .bp3-file-input input.bp3-disabled + .bp3-file-upload-input::after{ + outline:none; + -webkit-box-shadow:none; + box-shadow:none; + background-color:rgba(206, 217, 224, 0.5); + background-image:none; + cursor:not-allowed; + color:rgba(92, 112, 128, 0.6); } + .bp3-file-input input:disabled + .bp3-file-upload-input::after.bp3-active, .bp3-file-input input:disabled + .bp3-file-upload-input::after.bp3-active:hover, + .bp3-file-input input.bp3-disabled + .bp3-file-upload-input::after.bp3-active, + .bp3-file-input input.bp3-disabled + .bp3-file-upload-input::after.bp3-active:hover{ + background:rgba(206, 217, 224, 0.7); } + .bp3-dark .bp3-file-input input:disabled + .bp3-file-upload-input, .bp3-dark + .bp3-file-input input.bp3-disabled + .bp3-file-upload-input{ + -webkit-box-shadow:none; + box-shadow:none; + background:rgba(57, 75, 89, 0.5); + color:rgba(167, 182, 194, 0.6); } + .bp3-dark .bp3-file-input input:disabled + .bp3-file-upload-input::after, .bp3-dark + .bp3-file-input input.bp3-disabled + .bp3-file-upload-input::after{ + -webkit-box-shadow:none; + box-shadow:none; + background-color:rgba(57, 75, 89, 0.5); + background-image:none; + color:rgba(167, 182, 194, 0.6); } + .bp3-dark .bp3-file-input input:disabled + .bp3-file-upload-input::after.bp3-active, .bp3-dark + .bp3-file-input input.bp3-disabled + .bp3-file-upload-input::after.bp3-active{ + background:rgba(57, 75, 89, 0.7); } + .bp3-file-input.bp3-file-input-has-selection .bp3-file-upload-input{ + color:#182026; } + .bp3-dark .bp3-file-input.bp3-file-input-has-selection .bp3-file-upload-input{ + color:#f5f8fa; } + .bp3-file-input.bp3-fill{ + width:100%; } + .bp3-file-input.bp3-large, + .bp3-large .bp3-file-input{ + height:40px; } + .bp3-file-input .bp3-file-upload-input-custom-text::after{ + content:attr(bp3-button-text); } + +.bp3-file-upload-input{ + outline:none; + border:none; + border-radius:3px; + -webkit-box-shadow:0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), inset 0 0 0 1px rgba(16, 22, 26, 0.15), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), inset 0 0 0 1px rgba(16, 22, 26, 0.15), inset 0 1px 1px rgba(16, 22, 26, 0.2); + background:#ffffff; + height:30px; + padding:0 10px; + vertical-align:middle; + line-height:30px; + color:#182026; + font-size:14px; + font-weight:400; + -webkit-transition:-webkit-box-shadow 100ms cubic-bezier(0.4, 1, 0.75, 0.9); + transition:-webkit-box-shadow 100ms cubic-bezier(0.4, 1, 0.75, 0.9); + transition:box-shadow 100ms cubic-bezier(0.4, 1, 0.75, 0.9); + transition:box-shadow 100ms cubic-bezier(0.4, 1, 0.75, 0.9), -webkit-box-shadow 100ms cubic-bezier(0.4, 1, 0.75, 0.9); + -webkit-appearance:none; + -moz-appearance:none; + appearance:none; + overflow:hidden; + text-overflow:ellipsis; + white-space:nowrap; + word-wrap:normal; + position:absolute; + top:0; + right:0; + left:0; + padding-right:80px; + color:rgba(92, 112, 128, 0.6); + -webkit-user-select:none; + -moz-user-select:none; + -ms-user-select:none; + user-select:none; } + .bp3-file-upload-input::-webkit-input-placeholder{ + opacity:1; + color:rgba(92, 112, 128, 0.6); } + .bp3-file-upload-input::-moz-placeholder{ + opacity:1; + color:rgba(92, 112, 128, 0.6); } + .bp3-file-upload-input:-ms-input-placeholder{ + opacity:1; + color:rgba(92, 112, 128, 0.6); } + .bp3-file-upload-input::-ms-input-placeholder{ + opacity:1; + color:rgba(92, 112, 128, 0.6); } + .bp3-file-upload-input::placeholder{ + opacity:1; + color:rgba(92, 112, 128, 0.6); } + .bp3-file-upload-input:focus, .bp3-file-upload-input.bp3-active{ + -webkit-box-shadow:0 0 0 1px #137cbd, 0 0 0 3px rgba(19, 124, 189, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px #137cbd, 0 0 0 3px rgba(19, 124, 189, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); } + .bp3-file-upload-input[type="search"], .bp3-file-upload-input.bp3-round{ + border-radius:30px; + -webkit-box-sizing:border-box; + box-sizing:border-box; + padding-left:10px; } + .bp3-file-upload-input[readonly]{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.15); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.15); } + .bp3-file-upload-input:disabled, .bp3-file-upload-input.bp3-disabled{ + -webkit-box-shadow:none; + box-shadow:none; + background:rgba(206, 217, 224, 0.5); + cursor:not-allowed; + color:rgba(92, 112, 128, 0.6); + resize:none; } + .bp3-file-upload-input::after{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 -1px 0 rgba(16, 22, 26, 0.1); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 -1px 0 rgba(16, 22, 26, 0.1); + background-color:#f5f8fa; + background-image:-webkit-gradient(linear, left top, left bottom, from(rgba(255, 255, 255, 0.8)), to(rgba(255, 255, 255, 0))); + background-image:linear-gradient(to bottom, rgba(255, 255, 255, 0.8), rgba(255, 255, 255, 0)); + color:#182026; + min-width:24px; + min-height:24px; + overflow:hidden; + text-overflow:ellipsis; + white-space:nowrap; + word-wrap:normal; + position:absolute; + top:0; + right:0; + margin:3px; + border-radius:3px; + width:70px; + text-align:center; + line-height:24px; + content:"Browse"; } + .bp3-file-upload-input::after:hover{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 -1px 0 rgba(16, 22, 26, 0.1); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 -1px 0 rgba(16, 22, 26, 0.1); + background-clip:padding-box; + background-color:#ebf1f5; } + .bp3-file-upload-input::after:active, .bp3-file-upload-input::after.bp3-active{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 1px 2px rgba(16, 22, 26, 0.2); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 1px 2px rgba(16, 22, 26, 0.2); + background-color:#d8e1e8; + background-image:none; } + .bp3-file-upload-input::after:disabled, .bp3-file-upload-input::after.bp3-disabled{ + outline:none; + -webkit-box-shadow:none; + box-shadow:none; + background-color:rgba(206, 217, 224, 0.5); + background-image:none; + cursor:not-allowed; + color:rgba(92, 112, 128, 0.6); } + .bp3-file-upload-input::after:disabled.bp3-active, .bp3-file-upload-input::after:disabled.bp3-active:hover, .bp3-file-upload-input::after.bp3-disabled.bp3-active, .bp3-file-upload-input::after.bp3-disabled.bp3-active:hover{ + background:rgba(206, 217, 224, 0.7); } + .bp3-file-upload-input:hover::after{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 -1px 0 rgba(16, 22, 26, 0.1); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 -1px 0 rgba(16, 22, 26, 0.1); + background-clip:padding-box; + background-color:#ebf1f5; } + .bp3-file-upload-input:active::after{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 1px 2px rgba(16, 22, 26, 0.2); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 1px 2px rgba(16, 22, 26, 0.2); + background-color:#d8e1e8; + background-image:none; } + .bp3-large .bp3-file-upload-input{ + height:40px; + line-height:40px; + font-size:16px; + padding-right:95px; } + .bp3-large .bp3-file-upload-input[type="search"], .bp3-large .bp3-file-upload-input.bp3-round{ + padding:0 15px; } + .bp3-large .bp3-file-upload-input::after{ + min-width:30px; + min-height:30px; + margin:5px; + width:85px; + line-height:30px; } + .bp3-dark .bp3-file-upload-input{ + -webkit-box-shadow:0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); + background:rgba(16, 22, 26, 0.3); + color:#f5f8fa; + color:rgba(167, 182, 194, 0.6); } + .bp3-dark .bp3-file-upload-input::-webkit-input-placeholder{ + color:rgba(167, 182, 194, 0.6); } + .bp3-dark .bp3-file-upload-input::-moz-placeholder{ + color:rgba(167, 182, 194, 0.6); } + .bp3-dark .bp3-file-upload-input:-ms-input-placeholder{ + color:rgba(167, 182, 194, 0.6); } + .bp3-dark .bp3-file-upload-input::-ms-input-placeholder{ + color:rgba(167, 182, 194, 0.6); } + .bp3-dark .bp3-file-upload-input::placeholder{ + color:rgba(167, 182, 194, 0.6); } + .bp3-dark .bp3-file-upload-input:focus{ + -webkit-box-shadow:0 0 0 1px #137cbd, 0 0 0 1px #137cbd, 0 0 0 3px rgba(19, 124, 189, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px #137cbd, 0 0 0 1px #137cbd, 0 0 0 3px rgba(19, 124, 189, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); } + .bp3-dark .bp3-file-upload-input[readonly]{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4); } + .bp3-dark .bp3-file-upload-input:disabled, .bp3-dark .bp3-file-upload-input.bp3-disabled{ + -webkit-box-shadow:none; + box-shadow:none; + background:rgba(57, 75, 89, 0.5); + color:rgba(167, 182, 194, 0.6); } + .bp3-dark .bp3-file-upload-input::after{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + background-color:#394b59; + background-image:-webkit-gradient(linear, left top, left bottom, from(rgba(255, 255, 255, 0.05)), to(rgba(255, 255, 255, 0))); + background-image:linear-gradient(to bottom, rgba(255, 255, 255, 0.05), rgba(255, 255, 255, 0)); + color:#f5f8fa; } + .bp3-dark .bp3-file-upload-input::after:hover, .bp3-dark .bp3-file-upload-input::after:active, .bp3-dark .bp3-file-upload-input::after.bp3-active{ + color:#f5f8fa; } + .bp3-dark .bp3-file-upload-input::after:hover{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + background-color:#30404d; } + .bp3-dark .bp3-file-upload-input::after:active, .bp3-dark .bp3-file-upload-input::after.bp3-active{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.6), inset 0 1px 2px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.6), inset 0 1px 2px rgba(16, 22, 26, 0.2); + background-color:#202b33; + background-image:none; } + .bp3-dark .bp3-file-upload-input::after:disabled, .bp3-dark .bp3-file-upload-input::after.bp3-disabled{ + -webkit-box-shadow:none; + box-shadow:none; + background-color:rgba(57, 75, 89, 0.5); + background-image:none; + color:rgba(167, 182, 194, 0.6); } + .bp3-dark .bp3-file-upload-input::after:disabled.bp3-active, .bp3-dark .bp3-file-upload-input::after.bp3-disabled.bp3-active{ + background:rgba(57, 75, 89, 0.7); } + .bp3-dark .bp3-file-upload-input::after .bp3-button-spinner .bp3-spinner-head{ + background:rgba(16, 22, 26, 0.5); + stroke:#8a9ba8; } + .bp3-dark .bp3-file-upload-input:hover::after{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + background-color:#30404d; } + .bp3-dark .bp3-file-upload-input:active::after{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.6), inset 0 1px 2px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.6), inset 0 1px 2px rgba(16, 22, 26, 0.2); + background-color:#202b33; + background-image:none; } + +.bp3-file-upload-input::after{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 -1px 0 rgba(16, 22, 26, 0.1); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 -1px 0 rgba(16, 22, 26, 0.1); } +.bp3-form-group{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; + -webkit-box-orient:vertical; + -webkit-box-direction:normal; + -ms-flex-direction:column; + flex-direction:column; + margin:0 0 15px; } + .bp3-form-group label.bp3-label{ + margin-bottom:5px; } + .bp3-form-group .bp3-control{ + margin-top:7px; } + .bp3-form-group .bp3-form-helper-text{ + margin-top:5px; + color:#5c7080; + font-size:12px; } + .bp3-form-group.bp3-intent-primary .bp3-form-helper-text{ + color:#106ba3; } + .bp3-form-group.bp3-intent-success .bp3-form-helper-text{ + color:#0d8050; } + .bp3-form-group.bp3-intent-warning .bp3-form-helper-text{ + color:#bf7326; } + .bp3-form-group.bp3-intent-danger .bp3-form-helper-text{ + color:#c23030; } + .bp3-form-group.bp3-inline{ + -webkit-box-orient:horizontal; + -webkit-box-direction:normal; + -ms-flex-direction:row; + flex-direction:row; + -webkit-box-align:start; + -ms-flex-align:start; + align-items:flex-start; } + .bp3-form-group.bp3-inline.bp3-large label.bp3-label{ + margin:0 10px 0 0; + line-height:40px; } + .bp3-form-group.bp3-inline label.bp3-label{ + margin:0 10px 0 0; + line-height:30px; } + .bp3-form-group.bp3-disabled .bp3-label, + .bp3-form-group.bp3-disabled .bp3-text-muted, + .bp3-form-group.bp3-disabled .bp3-form-helper-text{ + color:rgba(92, 112, 128, 0.6) !important; } + .bp3-dark .bp3-form-group.bp3-intent-primary .bp3-form-helper-text{ + color:#48aff0; } + .bp3-dark .bp3-form-group.bp3-intent-success .bp3-form-helper-text{ + color:#3dcc91; } + .bp3-dark .bp3-form-group.bp3-intent-warning .bp3-form-helper-text{ + color:#ffb366; } + .bp3-dark .bp3-form-group.bp3-intent-danger .bp3-form-helper-text{ + color:#ff7373; } + .bp3-dark .bp3-form-group .bp3-form-helper-text{ + color:#a7b6c2; } + .bp3-dark .bp3-form-group.bp3-disabled .bp3-label, + .bp3-dark .bp3-form-group.bp3-disabled .bp3-text-muted, + .bp3-dark .bp3-form-group.bp3-disabled .bp3-form-helper-text{ + color:rgba(167, 182, 194, 0.6) !important; } +.bp3-input-group{ + display:block; + position:relative; } + .bp3-input-group .bp3-input{ + position:relative; + width:100%; } + .bp3-input-group .bp3-input:not(:first-child){ + padding-left:30px; } + .bp3-input-group .bp3-input:not(:last-child){ + padding-right:30px; } + .bp3-input-group .bp3-input-action, + .bp3-input-group > .bp3-button, + .bp3-input-group > .bp3-icon{ + position:absolute; + top:0; } + .bp3-input-group .bp3-input-action:first-child, + .bp3-input-group > .bp3-button:first-child, + .bp3-input-group > .bp3-icon:first-child{ + left:0; } + .bp3-input-group .bp3-input-action:last-child, + .bp3-input-group > .bp3-button:last-child, + .bp3-input-group > .bp3-icon:last-child{ + right:0; } + .bp3-input-group .bp3-button{ + min-width:24px; + min-height:24px; + margin:3px; + padding:0 7px; } + .bp3-input-group .bp3-button:empty{ + padding:0; } + .bp3-input-group > .bp3-icon{ + z-index:1; + color:#5c7080; } + .bp3-input-group > .bp3-icon:empty{ + line-height:1; + font-family:"Icons16", sans-serif; + font-size:16px; + font-weight:400; + font-style:normal; + -moz-osx-font-smoothing:grayscale; + -webkit-font-smoothing:antialiased; } + .bp3-input-group > .bp3-icon, + .bp3-input-group .bp3-input-action > .bp3-spinner{ + margin:7px; } + .bp3-input-group .bp3-tag{ + margin:5px; } + .bp3-input-group .bp3-input:not(:focus) + .bp3-button.bp3-minimal:not(:hover):not(:focus), + .bp3-input-group .bp3-input:not(:focus) + .bp3-input-action .bp3-button.bp3-minimal:not(:hover):not(:focus){ + color:#5c7080; } + .bp3-dark .bp3-input-group .bp3-input:not(:focus) + .bp3-button.bp3-minimal:not(:hover):not(:focus), .bp3-dark + .bp3-input-group .bp3-input:not(:focus) + .bp3-input-action .bp3-button.bp3-minimal:not(:hover):not(:focus){ + color:#a7b6c2; } + .bp3-input-group .bp3-input:not(:focus) + .bp3-button.bp3-minimal:not(:hover):not(:focus) .bp3-icon, .bp3-input-group .bp3-input:not(:focus) + .bp3-button.bp3-minimal:not(:hover):not(:focus) .bp3-icon-standard, .bp3-input-group .bp3-input:not(:focus) + .bp3-button.bp3-minimal:not(:hover):not(:focus) .bp3-icon-large, + .bp3-input-group .bp3-input:not(:focus) + .bp3-input-action .bp3-button.bp3-minimal:not(:hover):not(:focus) .bp3-icon, + .bp3-input-group .bp3-input:not(:focus) + .bp3-input-action .bp3-button.bp3-minimal:not(:hover):not(:focus) .bp3-icon-standard, + .bp3-input-group .bp3-input:not(:focus) + .bp3-input-action .bp3-button.bp3-minimal:not(:hover):not(:focus) .bp3-icon-large{ + color:#5c7080; } + .bp3-input-group .bp3-input:not(:focus) + .bp3-button.bp3-minimal:disabled, + .bp3-input-group .bp3-input:not(:focus) + .bp3-input-action .bp3-button.bp3-minimal:disabled{ + color:rgba(92, 112, 128, 0.6) !important; } + .bp3-input-group .bp3-input:not(:focus) + .bp3-button.bp3-minimal:disabled .bp3-icon, .bp3-input-group .bp3-input:not(:focus) + .bp3-button.bp3-minimal:disabled .bp3-icon-standard, .bp3-input-group .bp3-input:not(:focus) + .bp3-button.bp3-minimal:disabled .bp3-icon-large, + .bp3-input-group .bp3-input:not(:focus) + .bp3-input-action .bp3-button.bp3-minimal:disabled .bp3-icon, + .bp3-input-group .bp3-input:not(:focus) + .bp3-input-action .bp3-button.bp3-minimal:disabled .bp3-icon-standard, + .bp3-input-group .bp3-input:not(:focus) + .bp3-input-action .bp3-button.bp3-minimal:disabled .bp3-icon-large{ + color:rgba(92, 112, 128, 0.6) !important; } + .bp3-input-group.bp3-disabled{ + cursor:not-allowed; } + .bp3-input-group.bp3-disabled .bp3-icon{ + color:rgba(92, 112, 128, 0.6); } + .bp3-input-group.bp3-large .bp3-button{ + min-width:30px; + min-height:30px; + margin:5px; } + .bp3-input-group.bp3-large > .bp3-icon, + .bp3-input-group.bp3-large .bp3-input-action > .bp3-spinner{ + margin:12px; } + .bp3-input-group.bp3-large .bp3-input{ + height:40px; + line-height:40px; + font-size:16px; } + .bp3-input-group.bp3-large .bp3-input[type="search"], .bp3-input-group.bp3-large .bp3-input.bp3-round{ + padding:0 15px; } + .bp3-input-group.bp3-large .bp3-input:not(:first-child){ + padding-left:40px; } + .bp3-input-group.bp3-large .bp3-input:not(:last-child){ + padding-right:40px; } + .bp3-input-group.bp3-small .bp3-button{ + min-width:20px; + min-height:20px; + margin:2px; } + .bp3-input-group.bp3-small .bp3-tag{ + min-width:20px; + min-height:20px; + margin:2px; } + .bp3-input-group.bp3-small > .bp3-icon, + .bp3-input-group.bp3-small .bp3-input-action > .bp3-spinner{ + margin:4px; } + .bp3-input-group.bp3-small .bp3-input{ + height:24px; + padding-right:8px; + padding-left:8px; + line-height:24px; + font-size:12px; } + .bp3-input-group.bp3-small .bp3-input[type="search"], .bp3-input-group.bp3-small .bp3-input.bp3-round{ + padding:0 12px; } + .bp3-input-group.bp3-small .bp3-input:not(:first-child){ + padding-left:24px; } + .bp3-input-group.bp3-small .bp3-input:not(:last-child){ + padding-right:24px; } + .bp3-input-group.bp3-fill{ + -webkit-box-flex:1; + -ms-flex:1 1 auto; + flex:1 1 auto; + width:100%; } + .bp3-input-group.bp3-round .bp3-button, + .bp3-input-group.bp3-round .bp3-input, + .bp3-input-group.bp3-round .bp3-tag{ + border-radius:30px; } + .bp3-dark .bp3-input-group .bp3-icon{ + color:#a7b6c2; } + .bp3-dark .bp3-input-group.bp3-disabled .bp3-icon{ + color:rgba(167, 182, 194, 0.6); } + .bp3-input-group.bp3-intent-primary .bp3-input{ + -webkit-box-shadow:0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), inset 0 0 0 1px #137cbd, inset 0 0 0 1px rgba(16, 22, 26, 0.15), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), inset 0 0 0 1px #137cbd, inset 0 0 0 1px rgba(16, 22, 26, 0.15), inset 0 1px 1px rgba(16, 22, 26, 0.2); } + .bp3-input-group.bp3-intent-primary .bp3-input:focus{ + -webkit-box-shadow:0 0 0 1px #137cbd, 0 0 0 3px rgba(19, 124, 189, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px #137cbd, 0 0 0 3px rgba(19, 124, 189, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); } + .bp3-input-group.bp3-intent-primary .bp3-input[readonly]{ + -webkit-box-shadow:inset 0 0 0 1px #137cbd; + box-shadow:inset 0 0 0 1px #137cbd; } + .bp3-input-group.bp3-intent-primary .bp3-input:disabled, .bp3-input-group.bp3-intent-primary .bp3-input.bp3-disabled{ + -webkit-box-shadow:none; + box-shadow:none; } + .bp3-input-group.bp3-intent-primary > .bp3-icon{ + color:#106ba3; } + .bp3-dark .bp3-input-group.bp3-intent-primary > .bp3-icon{ + color:#48aff0; } + .bp3-input-group.bp3-intent-success .bp3-input{ + -webkit-box-shadow:0 0 0 0 rgba(15, 153, 96, 0), 0 0 0 0 rgba(15, 153, 96, 0), inset 0 0 0 1px #0f9960, inset 0 0 0 1px rgba(16, 22, 26, 0.15), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 0 rgba(15, 153, 96, 0), 0 0 0 0 rgba(15, 153, 96, 0), inset 0 0 0 1px #0f9960, inset 0 0 0 1px rgba(16, 22, 26, 0.15), inset 0 1px 1px rgba(16, 22, 26, 0.2); } + .bp3-input-group.bp3-intent-success .bp3-input:focus{ + -webkit-box-shadow:0 0 0 1px #0f9960, 0 0 0 3px rgba(15, 153, 96, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px #0f9960, 0 0 0 3px rgba(15, 153, 96, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); } + .bp3-input-group.bp3-intent-success .bp3-input[readonly]{ + -webkit-box-shadow:inset 0 0 0 1px #0f9960; + box-shadow:inset 0 0 0 1px #0f9960; } + .bp3-input-group.bp3-intent-success .bp3-input:disabled, .bp3-input-group.bp3-intent-success .bp3-input.bp3-disabled{ + -webkit-box-shadow:none; + box-shadow:none; } + .bp3-input-group.bp3-intent-success > .bp3-icon{ + color:#0d8050; } + .bp3-dark .bp3-input-group.bp3-intent-success > .bp3-icon{ + color:#3dcc91; } + .bp3-input-group.bp3-intent-warning .bp3-input{ + -webkit-box-shadow:0 0 0 0 rgba(217, 130, 43, 0), 0 0 0 0 rgba(217, 130, 43, 0), inset 0 0 0 1px #d9822b, inset 0 0 0 1px rgba(16, 22, 26, 0.15), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 0 rgba(217, 130, 43, 0), 0 0 0 0 rgba(217, 130, 43, 0), inset 0 0 0 1px #d9822b, inset 0 0 0 1px rgba(16, 22, 26, 0.15), inset 0 1px 1px rgba(16, 22, 26, 0.2); } + .bp3-input-group.bp3-intent-warning .bp3-input:focus{ + -webkit-box-shadow:0 0 0 1px #d9822b, 0 0 0 3px rgba(217, 130, 43, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px #d9822b, 0 0 0 3px rgba(217, 130, 43, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); } + .bp3-input-group.bp3-intent-warning .bp3-input[readonly]{ + -webkit-box-shadow:inset 0 0 0 1px #d9822b; + box-shadow:inset 0 0 0 1px #d9822b; } + .bp3-input-group.bp3-intent-warning .bp3-input:disabled, .bp3-input-group.bp3-intent-warning .bp3-input.bp3-disabled{ + -webkit-box-shadow:none; + box-shadow:none; } + .bp3-input-group.bp3-intent-warning > .bp3-icon{ + color:#bf7326; } + .bp3-dark .bp3-input-group.bp3-intent-warning > .bp3-icon{ + color:#ffb366; } + .bp3-input-group.bp3-intent-danger .bp3-input{ + -webkit-box-shadow:0 0 0 0 rgba(219, 55, 55, 0), 0 0 0 0 rgba(219, 55, 55, 0), inset 0 0 0 1px #db3737, inset 0 0 0 1px rgba(16, 22, 26, 0.15), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 0 rgba(219, 55, 55, 0), 0 0 0 0 rgba(219, 55, 55, 0), inset 0 0 0 1px #db3737, inset 0 0 0 1px rgba(16, 22, 26, 0.15), inset 0 1px 1px rgba(16, 22, 26, 0.2); } + .bp3-input-group.bp3-intent-danger .bp3-input:focus{ + -webkit-box-shadow:0 0 0 1px #db3737, 0 0 0 3px rgba(219, 55, 55, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px #db3737, 0 0 0 3px rgba(219, 55, 55, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); } + .bp3-input-group.bp3-intent-danger .bp3-input[readonly]{ + -webkit-box-shadow:inset 0 0 0 1px #db3737; + box-shadow:inset 0 0 0 1px #db3737; } + .bp3-input-group.bp3-intent-danger .bp3-input:disabled, .bp3-input-group.bp3-intent-danger .bp3-input.bp3-disabled{ + -webkit-box-shadow:none; + box-shadow:none; } + .bp3-input-group.bp3-intent-danger > .bp3-icon{ + color:#c23030; } + .bp3-dark .bp3-input-group.bp3-intent-danger > .bp3-icon{ + color:#ff7373; } +.bp3-input{ + outline:none; + border:none; + border-radius:3px; + -webkit-box-shadow:0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), inset 0 0 0 1px rgba(16, 22, 26, 0.15), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), inset 0 0 0 1px rgba(16, 22, 26, 0.15), inset 0 1px 1px rgba(16, 22, 26, 0.2); + background:#ffffff; + height:30px; + padding:0 10px; + vertical-align:middle; + line-height:30px; + color:#182026; + font-size:14px; + font-weight:400; + -webkit-transition:-webkit-box-shadow 100ms cubic-bezier(0.4, 1, 0.75, 0.9); + transition:-webkit-box-shadow 100ms cubic-bezier(0.4, 1, 0.75, 0.9); + transition:box-shadow 100ms cubic-bezier(0.4, 1, 0.75, 0.9); + transition:box-shadow 100ms cubic-bezier(0.4, 1, 0.75, 0.9), -webkit-box-shadow 100ms cubic-bezier(0.4, 1, 0.75, 0.9); + -webkit-appearance:none; + -moz-appearance:none; + appearance:none; } + .bp3-input::-webkit-input-placeholder{ + opacity:1; + color:rgba(92, 112, 128, 0.6); } + .bp3-input::-moz-placeholder{ + opacity:1; + color:rgba(92, 112, 128, 0.6); } + .bp3-input:-ms-input-placeholder{ + opacity:1; + color:rgba(92, 112, 128, 0.6); } + .bp3-input::-ms-input-placeholder{ + opacity:1; + color:rgba(92, 112, 128, 0.6); } + .bp3-input::placeholder{ + opacity:1; + color:rgba(92, 112, 128, 0.6); } + .bp3-input:focus, .bp3-input.bp3-active{ + -webkit-box-shadow:0 0 0 1px #137cbd, 0 0 0 3px rgba(19, 124, 189, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px #137cbd, 0 0 0 3px rgba(19, 124, 189, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); } + .bp3-input[type="search"], .bp3-input.bp3-round{ + border-radius:30px; + -webkit-box-sizing:border-box; + box-sizing:border-box; + padding-left:10px; } + .bp3-input[readonly]{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.15); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.15); } + .bp3-input:disabled, .bp3-input.bp3-disabled{ + -webkit-box-shadow:none; + box-shadow:none; + background:rgba(206, 217, 224, 0.5); + cursor:not-allowed; + color:rgba(92, 112, 128, 0.6); + resize:none; } + .bp3-input.bp3-large{ + height:40px; + line-height:40px; + font-size:16px; } + .bp3-input.bp3-large[type="search"], .bp3-input.bp3-large.bp3-round{ + padding:0 15px; } + .bp3-input.bp3-small{ + height:24px; + padding-right:8px; + padding-left:8px; + line-height:24px; + font-size:12px; } + .bp3-input.bp3-small[type="search"], .bp3-input.bp3-small.bp3-round{ + padding:0 12px; } + .bp3-input.bp3-fill{ + -webkit-box-flex:1; + -ms-flex:1 1 auto; + flex:1 1 auto; + width:100%; } + .bp3-dark .bp3-input{ + -webkit-box-shadow:0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); + background:rgba(16, 22, 26, 0.3); + color:#f5f8fa; } + .bp3-dark .bp3-input::-webkit-input-placeholder{ + color:rgba(167, 182, 194, 0.6); } + .bp3-dark .bp3-input::-moz-placeholder{ + color:rgba(167, 182, 194, 0.6); } + .bp3-dark .bp3-input:-ms-input-placeholder{ + color:rgba(167, 182, 194, 0.6); } + .bp3-dark .bp3-input::-ms-input-placeholder{ + color:rgba(167, 182, 194, 0.6); } + .bp3-dark .bp3-input::placeholder{ + color:rgba(167, 182, 194, 0.6); } + .bp3-dark .bp3-input:focus{ + -webkit-box-shadow:0 0 0 1px #137cbd, 0 0 0 1px #137cbd, 0 0 0 3px rgba(19, 124, 189, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px #137cbd, 0 0 0 1px #137cbd, 0 0 0 3px rgba(19, 124, 189, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); } + .bp3-dark .bp3-input[readonly]{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4); } + .bp3-dark .bp3-input:disabled, .bp3-dark .bp3-input.bp3-disabled{ + -webkit-box-shadow:none; + box-shadow:none; + background:rgba(57, 75, 89, 0.5); + color:rgba(167, 182, 194, 0.6); } + .bp3-input.bp3-intent-primary{ + -webkit-box-shadow:0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), inset 0 0 0 1px #137cbd, inset 0 0 0 1px rgba(16, 22, 26, 0.15), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), inset 0 0 0 1px #137cbd, inset 0 0 0 1px rgba(16, 22, 26, 0.15), inset 0 1px 1px rgba(16, 22, 26, 0.2); } + .bp3-input.bp3-intent-primary:focus{ + -webkit-box-shadow:0 0 0 1px #137cbd, 0 0 0 3px rgba(19, 124, 189, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px #137cbd, 0 0 0 3px rgba(19, 124, 189, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); } + .bp3-input.bp3-intent-primary[readonly]{ + -webkit-box-shadow:inset 0 0 0 1px #137cbd; + box-shadow:inset 0 0 0 1px #137cbd; } + .bp3-input.bp3-intent-primary:disabled, .bp3-input.bp3-intent-primary.bp3-disabled{ + -webkit-box-shadow:none; + box-shadow:none; } + .bp3-dark .bp3-input.bp3-intent-primary{ + -webkit-box-shadow:0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), inset 0 0 0 1px #137cbd, inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), inset 0 0 0 1px #137cbd, inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); } + .bp3-dark .bp3-input.bp3-intent-primary:focus{ + -webkit-box-shadow:0 0 0 1px #137cbd, 0 0 0 1px #137cbd, 0 0 0 3px rgba(19, 124, 189, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px #137cbd, 0 0 0 1px #137cbd, 0 0 0 3px rgba(19, 124, 189, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); } + .bp3-dark .bp3-input.bp3-intent-primary[readonly]{ + -webkit-box-shadow:inset 0 0 0 1px #137cbd; + box-shadow:inset 0 0 0 1px #137cbd; } + .bp3-dark .bp3-input.bp3-intent-primary:disabled, .bp3-dark .bp3-input.bp3-intent-primary.bp3-disabled{ + -webkit-box-shadow:none; + box-shadow:none; } + .bp3-input.bp3-intent-success{ + -webkit-box-shadow:0 0 0 0 rgba(15, 153, 96, 0), 0 0 0 0 rgba(15, 153, 96, 0), inset 0 0 0 1px #0f9960, inset 0 0 0 1px rgba(16, 22, 26, 0.15), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 0 rgba(15, 153, 96, 0), 0 0 0 0 rgba(15, 153, 96, 0), inset 0 0 0 1px #0f9960, inset 0 0 0 1px rgba(16, 22, 26, 0.15), inset 0 1px 1px rgba(16, 22, 26, 0.2); } + .bp3-input.bp3-intent-success:focus{ + -webkit-box-shadow:0 0 0 1px #0f9960, 0 0 0 3px rgba(15, 153, 96, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px #0f9960, 0 0 0 3px rgba(15, 153, 96, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); } + .bp3-input.bp3-intent-success[readonly]{ + -webkit-box-shadow:inset 0 0 0 1px #0f9960; + box-shadow:inset 0 0 0 1px #0f9960; } + .bp3-input.bp3-intent-success:disabled, .bp3-input.bp3-intent-success.bp3-disabled{ + -webkit-box-shadow:none; + box-shadow:none; } + .bp3-dark .bp3-input.bp3-intent-success{ + -webkit-box-shadow:0 0 0 0 rgba(15, 153, 96, 0), 0 0 0 0 rgba(15, 153, 96, 0), 0 0 0 0 rgba(15, 153, 96, 0), inset 0 0 0 1px #0f9960, inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 0 rgba(15, 153, 96, 0), 0 0 0 0 rgba(15, 153, 96, 0), 0 0 0 0 rgba(15, 153, 96, 0), inset 0 0 0 1px #0f9960, inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); } + .bp3-dark .bp3-input.bp3-intent-success:focus{ + -webkit-box-shadow:0 0 0 1px #0f9960, 0 0 0 1px #0f9960, 0 0 0 3px rgba(15, 153, 96, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px #0f9960, 0 0 0 1px #0f9960, 0 0 0 3px rgba(15, 153, 96, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); } + .bp3-dark .bp3-input.bp3-intent-success[readonly]{ + -webkit-box-shadow:inset 0 0 0 1px #0f9960; + box-shadow:inset 0 0 0 1px #0f9960; } + .bp3-dark .bp3-input.bp3-intent-success:disabled, .bp3-dark .bp3-input.bp3-intent-success.bp3-disabled{ + -webkit-box-shadow:none; + box-shadow:none; } + .bp3-input.bp3-intent-warning{ + -webkit-box-shadow:0 0 0 0 rgba(217, 130, 43, 0), 0 0 0 0 rgba(217, 130, 43, 0), inset 0 0 0 1px #d9822b, inset 0 0 0 1px rgba(16, 22, 26, 0.15), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 0 rgba(217, 130, 43, 0), 0 0 0 0 rgba(217, 130, 43, 0), inset 0 0 0 1px #d9822b, inset 0 0 0 1px rgba(16, 22, 26, 0.15), inset 0 1px 1px rgba(16, 22, 26, 0.2); } + .bp3-input.bp3-intent-warning:focus{ + -webkit-box-shadow:0 0 0 1px #d9822b, 0 0 0 3px rgba(217, 130, 43, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px #d9822b, 0 0 0 3px rgba(217, 130, 43, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); } + .bp3-input.bp3-intent-warning[readonly]{ + -webkit-box-shadow:inset 0 0 0 1px #d9822b; + box-shadow:inset 0 0 0 1px #d9822b; } + .bp3-input.bp3-intent-warning:disabled, .bp3-input.bp3-intent-warning.bp3-disabled{ + -webkit-box-shadow:none; + box-shadow:none; } + .bp3-dark .bp3-input.bp3-intent-warning{ + -webkit-box-shadow:0 0 0 0 rgba(217, 130, 43, 0), 0 0 0 0 rgba(217, 130, 43, 0), 0 0 0 0 rgba(217, 130, 43, 0), inset 0 0 0 1px #d9822b, inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 0 rgba(217, 130, 43, 0), 0 0 0 0 rgba(217, 130, 43, 0), 0 0 0 0 rgba(217, 130, 43, 0), inset 0 0 0 1px #d9822b, inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); } + .bp3-dark .bp3-input.bp3-intent-warning:focus{ + -webkit-box-shadow:0 0 0 1px #d9822b, 0 0 0 1px #d9822b, 0 0 0 3px rgba(217, 130, 43, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px #d9822b, 0 0 0 1px #d9822b, 0 0 0 3px rgba(217, 130, 43, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); } + .bp3-dark .bp3-input.bp3-intent-warning[readonly]{ + -webkit-box-shadow:inset 0 0 0 1px #d9822b; + box-shadow:inset 0 0 0 1px #d9822b; } + .bp3-dark .bp3-input.bp3-intent-warning:disabled, .bp3-dark .bp3-input.bp3-intent-warning.bp3-disabled{ + -webkit-box-shadow:none; + box-shadow:none; } + .bp3-input.bp3-intent-danger{ + -webkit-box-shadow:0 0 0 0 rgba(219, 55, 55, 0), 0 0 0 0 rgba(219, 55, 55, 0), inset 0 0 0 1px #db3737, inset 0 0 0 1px rgba(16, 22, 26, 0.15), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 0 rgba(219, 55, 55, 0), 0 0 0 0 rgba(219, 55, 55, 0), inset 0 0 0 1px #db3737, inset 0 0 0 1px rgba(16, 22, 26, 0.15), inset 0 1px 1px rgba(16, 22, 26, 0.2); } + .bp3-input.bp3-intent-danger:focus{ + -webkit-box-shadow:0 0 0 1px #db3737, 0 0 0 3px rgba(219, 55, 55, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px #db3737, 0 0 0 3px rgba(219, 55, 55, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); } + .bp3-input.bp3-intent-danger[readonly]{ + -webkit-box-shadow:inset 0 0 0 1px #db3737; + box-shadow:inset 0 0 0 1px #db3737; } + .bp3-input.bp3-intent-danger:disabled, .bp3-input.bp3-intent-danger.bp3-disabled{ + -webkit-box-shadow:none; + box-shadow:none; } + .bp3-dark .bp3-input.bp3-intent-danger{ + -webkit-box-shadow:0 0 0 0 rgba(219, 55, 55, 0), 0 0 0 0 rgba(219, 55, 55, 0), 0 0 0 0 rgba(219, 55, 55, 0), inset 0 0 0 1px #db3737, inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 0 rgba(219, 55, 55, 0), 0 0 0 0 rgba(219, 55, 55, 0), 0 0 0 0 rgba(219, 55, 55, 0), inset 0 0 0 1px #db3737, inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); } + .bp3-dark .bp3-input.bp3-intent-danger:focus{ + -webkit-box-shadow:0 0 0 1px #db3737, 0 0 0 1px #db3737, 0 0 0 3px rgba(219, 55, 55, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px #db3737, 0 0 0 1px #db3737, 0 0 0 3px rgba(219, 55, 55, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); } + .bp3-dark .bp3-input.bp3-intent-danger[readonly]{ + -webkit-box-shadow:inset 0 0 0 1px #db3737; + box-shadow:inset 0 0 0 1px #db3737; } + .bp3-dark .bp3-input.bp3-intent-danger:disabled, .bp3-dark .bp3-input.bp3-intent-danger.bp3-disabled{ + -webkit-box-shadow:none; + box-shadow:none; } + .bp3-input::-ms-clear{ + display:none; } +textarea.bp3-input{ + max-width:100%; + padding:10px; } + textarea.bp3-input, textarea.bp3-input.bp3-large, textarea.bp3-input.bp3-small{ + height:auto; + line-height:inherit; } + textarea.bp3-input.bp3-small{ + padding:8px; } + .bp3-dark textarea.bp3-input{ + -webkit-box-shadow:0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), 0 0 0 0 rgba(19, 124, 189, 0), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); + background:rgba(16, 22, 26, 0.3); + color:#f5f8fa; } + .bp3-dark textarea.bp3-input::-webkit-input-placeholder{ + color:rgba(167, 182, 194, 0.6); } + .bp3-dark textarea.bp3-input::-moz-placeholder{ + color:rgba(167, 182, 194, 0.6); } + .bp3-dark textarea.bp3-input:-ms-input-placeholder{ + color:rgba(167, 182, 194, 0.6); } + .bp3-dark textarea.bp3-input::-ms-input-placeholder{ + color:rgba(167, 182, 194, 0.6); } + .bp3-dark textarea.bp3-input::placeholder{ + color:rgba(167, 182, 194, 0.6); } + .bp3-dark textarea.bp3-input:focus{ + -webkit-box-shadow:0 0 0 1px #137cbd, 0 0 0 1px #137cbd, 0 0 0 3px rgba(19, 124, 189, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px #137cbd, 0 0 0 1px #137cbd, 0 0 0 3px rgba(19, 124, 189, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); } + .bp3-dark textarea.bp3-input[readonly]{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.4); } + .bp3-dark textarea.bp3-input:disabled, .bp3-dark textarea.bp3-input.bp3-disabled{ + -webkit-box-shadow:none; + box-shadow:none; + background:rgba(57, 75, 89, 0.5); + color:rgba(167, 182, 194, 0.6); } +label.bp3-label{ + display:block; + margin-top:0; + margin-bottom:15px; } + label.bp3-label .bp3-html-select, + label.bp3-label .bp3-input, + label.bp3-label .bp3-select, + label.bp3-label .bp3-slider, + label.bp3-label .bp3-popover-wrapper{ + display:block; + margin-top:5px; + text-transform:none; } + label.bp3-label .bp3-button-group{ + margin-top:5px; } + label.bp3-label .bp3-select select, + label.bp3-label .bp3-html-select select{ + width:100%; + vertical-align:top; + font-weight:400; } + label.bp3-label.bp3-disabled, + label.bp3-label.bp3-disabled .bp3-text-muted{ + color:rgba(92, 112, 128, 0.6); } + label.bp3-label.bp3-inline{ + line-height:30px; } + label.bp3-label.bp3-inline .bp3-html-select, + label.bp3-label.bp3-inline .bp3-input, + label.bp3-label.bp3-inline .bp3-input-group, + label.bp3-label.bp3-inline .bp3-select, + label.bp3-label.bp3-inline .bp3-popover-wrapper{ + display:inline-block; + margin:0 0 0 5px; + vertical-align:top; } + label.bp3-label.bp3-inline .bp3-button-group{ + margin:0 0 0 5px; } + label.bp3-label.bp3-inline .bp3-input-group .bp3-input{ + margin-left:0; } + label.bp3-label.bp3-inline.bp3-large{ + line-height:40px; } + label.bp3-label:not(.bp3-inline) .bp3-popover-target{ + display:block; } + .bp3-dark label.bp3-label{ + color:#f5f8fa; } + .bp3-dark label.bp3-label.bp3-disabled, + .bp3-dark label.bp3-label.bp3-disabled .bp3-text-muted{ + color:rgba(167, 182, 194, 0.6); } +.bp3-numeric-input .bp3-button-group.bp3-vertical > .bp3-button{ + -webkit-box-flex:1; + -ms-flex:1 1 14px; + flex:1 1 14px; + width:30px; + min-height:0; + padding:0; } + .bp3-numeric-input .bp3-button-group.bp3-vertical > .bp3-button:first-child{ + border-radius:0 3px 0 0; } + .bp3-numeric-input .bp3-button-group.bp3-vertical > .bp3-button:last-child{ + border-radius:0 0 3px 0; } + +.bp3-numeric-input .bp3-button-group.bp3-vertical:first-child > .bp3-button:first-child{ + border-radius:3px 0 0 0; } + +.bp3-numeric-input .bp3-button-group.bp3-vertical:first-child > .bp3-button:last-child{ + border-radius:0 0 0 3px; } + +.bp3-numeric-input.bp3-large .bp3-button-group.bp3-vertical > .bp3-button{ + width:40px; } + +form{ + display:block; } +.bp3-html-select select, +.bp3-select select{ + display:-webkit-inline-box; + display:-ms-inline-flexbox; + display:inline-flex; + -webkit-box-orient:horizontal; + -webkit-box-direction:normal; + -ms-flex-direction:row; + flex-direction:row; + -webkit-box-align:center; + -ms-flex-align:center; + align-items:center; + -webkit-box-pack:center; + -ms-flex-pack:center; + justify-content:center; + border:none; + border-radius:3px; + cursor:pointer; + padding:5px 10px; + vertical-align:middle; + text-align:left; + font-size:14px; + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 -1px 0 rgba(16, 22, 26, 0.1); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 -1px 0 rgba(16, 22, 26, 0.1); + background-color:#f5f8fa; + background-image:-webkit-gradient(linear, left top, left bottom, from(rgba(255, 255, 255, 0.8)), to(rgba(255, 255, 255, 0))); + background-image:linear-gradient(to bottom, rgba(255, 255, 255, 0.8), rgba(255, 255, 255, 0)); + color:#182026; + border-radius:3px; + width:100%; + height:30px; + padding:0 25px 0 10px; + -moz-appearance:none; + -webkit-appearance:none; } + .bp3-html-select select > *, .bp3-select select > *{ + -webkit-box-flex:0; + -ms-flex-positive:0; + flex-grow:0; + -ms-flex-negative:0; + flex-shrink:0; } + .bp3-html-select select > .bp3-fill, .bp3-select select > .bp3-fill{ + -webkit-box-flex:1; + -ms-flex-positive:1; + flex-grow:1; + -ms-flex-negative:1; + flex-shrink:1; } + .bp3-html-select select::before, + .bp3-select select::before, .bp3-html-select select > *, .bp3-select select > *{ + margin-right:7px; } + .bp3-html-select select:empty::before, + .bp3-select select:empty::before, + .bp3-html-select select > :last-child, + .bp3-select select > :last-child{ + margin-right:0; } + .bp3-html-select select:hover, + .bp3-select select:hover{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 -1px 0 rgba(16, 22, 26, 0.1); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 -1px 0 rgba(16, 22, 26, 0.1); + background-clip:padding-box; + background-color:#ebf1f5; } + .bp3-html-select select:active, + .bp3-select select:active, .bp3-html-select select.bp3-active, + .bp3-select select.bp3-active{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 1px 2px rgba(16, 22, 26, 0.2); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 1px 2px rgba(16, 22, 26, 0.2); + background-color:#d8e1e8; + background-image:none; } + .bp3-html-select select:disabled, + .bp3-select select:disabled, .bp3-html-select select.bp3-disabled, + .bp3-select select.bp3-disabled{ + outline:none; + -webkit-box-shadow:none; + box-shadow:none; + background-color:rgba(206, 217, 224, 0.5); + background-image:none; + cursor:not-allowed; + color:rgba(92, 112, 128, 0.6); } + .bp3-html-select select:disabled.bp3-active, + .bp3-select select:disabled.bp3-active, .bp3-html-select select:disabled.bp3-active:hover, + .bp3-select select:disabled.bp3-active:hover, .bp3-html-select select.bp3-disabled.bp3-active, + .bp3-select select.bp3-disabled.bp3-active, .bp3-html-select select.bp3-disabled.bp3-active:hover, + .bp3-select select.bp3-disabled.bp3-active:hover{ + background:rgba(206, 217, 224, 0.7); } + +.bp3-html-select.bp3-minimal select, +.bp3-select.bp3-minimal select{ + -webkit-box-shadow:none; + box-shadow:none; + background:none; } + .bp3-html-select.bp3-minimal select:hover, + .bp3-select.bp3-minimal select:hover{ + -webkit-box-shadow:none; + box-shadow:none; + background:rgba(167, 182, 194, 0.3); + text-decoration:none; + color:#182026; } + .bp3-html-select.bp3-minimal select:active, + .bp3-select.bp3-minimal select:active, .bp3-html-select.bp3-minimal select.bp3-active, + .bp3-select.bp3-minimal select.bp3-active{ + -webkit-box-shadow:none; + box-shadow:none; + background:rgba(115, 134, 148, 0.3); + color:#182026; } + .bp3-html-select.bp3-minimal select:disabled, + .bp3-select.bp3-minimal select:disabled, .bp3-html-select.bp3-minimal select:disabled:hover, + .bp3-select.bp3-minimal select:disabled:hover, .bp3-html-select.bp3-minimal select.bp3-disabled, + .bp3-select.bp3-minimal select.bp3-disabled, .bp3-html-select.bp3-minimal select.bp3-disabled:hover, + .bp3-select.bp3-minimal select.bp3-disabled:hover{ + background:none; + cursor:not-allowed; + color:rgba(92, 112, 128, 0.6); } + .bp3-html-select.bp3-minimal select:disabled.bp3-active, + .bp3-select.bp3-minimal select:disabled.bp3-active, .bp3-html-select.bp3-minimal select:disabled:hover.bp3-active, + .bp3-select.bp3-minimal select:disabled:hover.bp3-active, .bp3-html-select.bp3-minimal select.bp3-disabled.bp3-active, + .bp3-select.bp3-minimal select.bp3-disabled.bp3-active, .bp3-html-select.bp3-minimal select.bp3-disabled:hover.bp3-active, + .bp3-select.bp3-minimal select.bp3-disabled:hover.bp3-active{ + background:rgba(115, 134, 148, 0.3); } + .bp3-dark .bp3-html-select.bp3-minimal select, .bp3-html-select.bp3-minimal .bp3-dark select, + .bp3-dark .bp3-select.bp3-minimal select, .bp3-select.bp3-minimal .bp3-dark select{ + -webkit-box-shadow:none; + box-shadow:none; + background:none; + color:inherit; } + .bp3-dark .bp3-html-select.bp3-minimal select:hover, .bp3-html-select.bp3-minimal .bp3-dark select:hover, + .bp3-dark .bp3-select.bp3-minimal select:hover, .bp3-select.bp3-minimal .bp3-dark select:hover, .bp3-dark .bp3-html-select.bp3-minimal select:active, .bp3-html-select.bp3-minimal .bp3-dark select:active, + .bp3-dark .bp3-select.bp3-minimal select:active, .bp3-select.bp3-minimal .bp3-dark select:active, .bp3-dark .bp3-html-select.bp3-minimal select.bp3-active, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-active, + .bp3-dark .bp3-select.bp3-minimal select.bp3-active, .bp3-select.bp3-minimal .bp3-dark select.bp3-active{ + -webkit-box-shadow:none; + box-shadow:none; + background:none; } + .bp3-dark .bp3-html-select.bp3-minimal select:hover, .bp3-html-select.bp3-minimal .bp3-dark select:hover, + .bp3-dark .bp3-select.bp3-minimal select:hover, .bp3-select.bp3-minimal .bp3-dark select:hover{ + background:rgba(138, 155, 168, 0.15); } + .bp3-dark .bp3-html-select.bp3-minimal select:active, .bp3-html-select.bp3-minimal .bp3-dark select:active, + .bp3-dark .bp3-select.bp3-minimal select:active, .bp3-select.bp3-minimal .bp3-dark select:active, .bp3-dark .bp3-html-select.bp3-minimal select.bp3-active, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-active, + .bp3-dark .bp3-select.bp3-minimal select.bp3-active, .bp3-select.bp3-minimal .bp3-dark select.bp3-active{ + background:rgba(138, 155, 168, 0.3); + color:#f5f8fa; } + .bp3-dark .bp3-html-select.bp3-minimal select:disabled, .bp3-html-select.bp3-minimal .bp3-dark select:disabled, + .bp3-dark .bp3-select.bp3-minimal select:disabled, .bp3-select.bp3-minimal .bp3-dark select:disabled, .bp3-dark .bp3-html-select.bp3-minimal select:disabled:hover, .bp3-html-select.bp3-minimal .bp3-dark select:disabled:hover, + .bp3-dark .bp3-select.bp3-minimal select:disabled:hover, .bp3-select.bp3-minimal .bp3-dark select:disabled:hover, .bp3-dark .bp3-html-select.bp3-minimal select.bp3-disabled, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-disabled, + .bp3-dark .bp3-select.bp3-minimal select.bp3-disabled, .bp3-select.bp3-minimal .bp3-dark select.bp3-disabled, .bp3-dark .bp3-html-select.bp3-minimal select.bp3-disabled:hover, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-disabled:hover, + .bp3-dark .bp3-select.bp3-minimal select.bp3-disabled:hover, .bp3-select.bp3-minimal .bp3-dark select.bp3-disabled:hover{ + background:none; + cursor:not-allowed; + color:rgba(167, 182, 194, 0.6); } + .bp3-dark .bp3-html-select.bp3-minimal select:disabled.bp3-active, .bp3-html-select.bp3-minimal .bp3-dark select:disabled.bp3-active, + .bp3-dark .bp3-select.bp3-minimal select:disabled.bp3-active, .bp3-select.bp3-minimal .bp3-dark select:disabled.bp3-active, .bp3-dark .bp3-html-select.bp3-minimal select:disabled:hover.bp3-active, .bp3-html-select.bp3-minimal .bp3-dark select:disabled:hover.bp3-active, + .bp3-dark .bp3-select.bp3-minimal select:disabled:hover.bp3-active, .bp3-select.bp3-minimal .bp3-dark select:disabled:hover.bp3-active, .bp3-dark .bp3-html-select.bp3-minimal select.bp3-disabled.bp3-active, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-disabled.bp3-active, + .bp3-dark .bp3-select.bp3-minimal select.bp3-disabled.bp3-active, .bp3-select.bp3-minimal .bp3-dark select.bp3-disabled.bp3-active, .bp3-dark .bp3-html-select.bp3-minimal select.bp3-disabled:hover.bp3-active, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-disabled:hover.bp3-active, + .bp3-dark .bp3-select.bp3-minimal select.bp3-disabled:hover.bp3-active, .bp3-select.bp3-minimal .bp3-dark select.bp3-disabled:hover.bp3-active{ + background:rgba(138, 155, 168, 0.3); } + .bp3-html-select.bp3-minimal select.bp3-intent-primary, + .bp3-select.bp3-minimal select.bp3-intent-primary{ + color:#106ba3; } + .bp3-html-select.bp3-minimal select.bp3-intent-primary:hover, + .bp3-select.bp3-minimal select.bp3-intent-primary:hover, .bp3-html-select.bp3-minimal select.bp3-intent-primary:active, + .bp3-select.bp3-minimal select.bp3-intent-primary:active, .bp3-html-select.bp3-minimal select.bp3-intent-primary.bp3-active, + .bp3-select.bp3-minimal select.bp3-intent-primary.bp3-active{ + -webkit-box-shadow:none; + box-shadow:none; + background:none; + color:#106ba3; } + .bp3-html-select.bp3-minimal select.bp3-intent-primary:hover, + .bp3-select.bp3-minimal select.bp3-intent-primary:hover{ + background:rgba(19, 124, 189, 0.15); + color:#106ba3; } + .bp3-html-select.bp3-minimal select.bp3-intent-primary:active, + .bp3-select.bp3-minimal select.bp3-intent-primary:active, .bp3-html-select.bp3-minimal select.bp3-intent-primary.bp3-active, + .bp3-select.bp3-minimal select.bp3-intent-primary.bp3-active{ + background:rgba(19, 124, 189, 0.3); + color:#106ba3; } + .bp3-html-select.bp3-minimal select.bp3-intent-primary:disabled, + .bp3-select.bp3-minimal select.bp3-intent-primary:disabled, .bp3-html-select.bp3-minimal select.bp3-intent-primary.bp3-disabled, + .bp3-select.bp3-minimal select.bp3-intent-primary.bp3-disabled{ + background:none; + color:rgba(16, 107, 163, 0.5); } + .bp3-html-select.bp3-minimal select.bp3-intent-primary:disabled.bp3-active, + .bp3-select.bp3-minimal select.bp3-intent-primary:disabled.bp3-active, .bp3-html-select.bp3-minimal select.bp3-intent-primary.bp3-disabled.bp3-active, + .bp3-select.bp3-minimal select.bp3-intent-primary.bp3-disabled.bp3-active{ + background:rgba(19, 124, 189, 0.3); } + .bp3-html-select.bp3-minimal select.bp3-intent-primary .bp3-button-spinner .bp3-spinner-head, .bp3-select.bp3-minimal select.bp3-intent-primary .bp3-button-spinner .bp3-spinner-head{ + stroke:#106ba3; } + .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-primary, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-primary, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-primary, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-primary{ + color:#48aff0; } + .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-primary:hover, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-primary:hover, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-primary:hover, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-primary:hover{ + background:rgba(19, 124, 189, 0.2); + color:#48aff0; } + .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-primary:active, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-primary:active, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-primary:active, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-primary:active, .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-primary.bp3-active, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-primary.bp3-active, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-primary.bp3-active, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-primary.bp3-active{ + background:rgba(19, 124, 189, 0.3); + color:#48aff0; } + .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-primary:disabled, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-primary:disabled, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-primary:disabled, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-primary:disabled, .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-primary.bp3-disabled, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-primary.bp3-disabled, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-primary.bp3-disabled, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-primary.bp3-disabled{ + background:none; + color:rgba(72, 175, 240, 0.5); } + .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-primary:disabled.bp3-active, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-primary:disabled.bp3-active, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-primary:disabled.bp3-active, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-primary:disabled.bp3-active, .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-primary.bp3-disabled.bp3-active, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-primary.bp3-disabled.bp3-active, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-primary.bp3-disabled.bp3-active, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-primary.bp3-disabled.bp3-active{ + background:rgba(19, 124, 189, 0.3); } + .bp3-html-select.bp3-minimal select.bp3-intent-success, + .bp3-select.bp3-minimal select.bp3-intent-success{ + color:#0d8050; } + .bp3-html-select.bp3-minimal select.bp3-intent-success:hover, + .bp3-select.bp3-minimal select.bp3-intent-success:hover, .bp3-html-select.bp3-minimal select.bp3-intent-success:active, + .bp3-select.bp3-minimal select.bp3-intent-success:active, .bp3-html-select.bp3-minimal select.bp3-intent-success.bp3-active, + .bp3-select.bp3-minimal select.bp3-intent-success.bp3-active{ + -webkit-box-shadow:none; + box-shadow:none; + background:none; + color:#0d8050; } + .bp3-html-select.bp3-minimal select.bp3-intent-success:hover, + .bp3-select.bp3-minimal select.bp3-intent-success:hover{ + background:rgba(15, 153, 96, 0.15); + color:#0d8050; } + .bp3-html-select.bp3-minimal select.bp3-intent-success:active, + .bp3-select.bp3-minimal select.bp3-intent-success:active, .bp3-html-select.bp3-minimal select.bp3-intent-success.bp3-active, + .bp3-select.bp3-minimal select.bp3-intent-success.bp3-active{ + background:rgba(15, 153, 96, 0.3); + color:#0d8050; } + .bp3-html-select.bp3-minimal select.bp3-intent-success:disabled, + .bp3-select.bp3-minimal select.bp3-intent-success:disabled, .bp3-html-select.bp3-minimal select.bp3-intent-success.bp3-disabled, + .bp3-select.bp3-minimal select.bp3-intent-success.bp3-disabled{ + background:none; + color:rgba(13, 128, 80, 0.5); } + .bp3-html-select.bp3-minimal select.bp3-intent-success:disabled.bp3-active, + .bp3-select.bp3-minimal select.bp3-intent-success:disabled.bp3-active, .bp3-html-select.bp3-minimal select.bp3-intent-success.bp3-disabled.bp3-active, + .bp3-select.bp3-minimal select.bp3-intent-success.bp3-disabled.bp3-active{ + background:rgba(15, 153, 96, 0.3); } + .bp3-html-select.bp3-minimal select.bp3-intent-success .bp3-button-spinner .bp3-spinner-head, .bp3-select.bp3-minimal select.bp3-intent-success .bp3-button-spinner .bp3-spinner-head{ + stroke:#0d8050; } + .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-success, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-success, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-success, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-success{ + color:#3dcc91; } + .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-success:hover, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-success:hover, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-success:hover, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-success:hover{ + background:rgba(15, 153, 96, 0.2); + color:#3dcc91; } + .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-success:active, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-success:active, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-success:active, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-success:active, .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-success.bp3-active, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-success.bp3-active, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-success.bp3-active, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-success.bp3-active{ + background:rgba(15, 153, 96, 0.3); + color:#3dcc91; } + .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-success:disabled, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-success:disabled, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-success:disabled, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-success:disabled, .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-success.bp3-disabled, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-success.bp3-disabled, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-success.bp3-disabled, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-success.bp3-disabled{ + background:none; + color:rgba(61, 204, 145, 0.5); } + .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-success:disabled.bp3-active, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-success:disabled.bp3-active, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-success:disabled.bp3-active, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-success:disabled.bp3-active, .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-success.bp3-disabled.bp3-active, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-success.bp3-disabled.bp3-active, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-success.bp3-disabled.bp3-active, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-success.bp3-disabled.bp3-active{ + background:rgba(15, 153, 96, 0.3); } + .bp3-html-select.bp3-minimal select.bp3-intent-warning, + .bp3-select.bp3-minimal select.bp3-intent-warning{ + color:#bf7326; } + .bp3-html-select.bp3-minimal select.bp3-intent-warning:hover, + .bp3-select.bp3-minimal select.bp3-intent-warning:hover, .bp3-html-select.bp3-minimal select.bp3-intent-warning:active, + .bp3-select.bp3-minimal select.bp3-intent-warning:active, .bp3-html-select.bp3-minimal select.bp3-intent-warning.bp3-active, + .bp3-select.bp3-minimal select.bp3-intent-warning.bp3-active{ + -webkit-box-shadow:none; + box-shadow:none; + background:none; + color:#bf7326; } + .bp3-html-select.bp3-minimal select.bp3-intent-warning:hover, + .bp3-select.bp3-minimal select.bp3-intent-warning:hover{ + background:rgba(217, 130, 43, 0.15); + color:#bf7326; } + .bp3-html-select.bp3-minimal select.bp3-intent-warning:active, + .bp3-select.bp3-minimal select.bp3-intent-warning:active, .bp3-html-select.bp3-minimal select.bp3-intent-warning.bp3-active, + .bp3-select.bp3-minimal select.bp3-intent-warning.bp3-active{ + background:rgba(217, 130, 43, 0.3); + color:#bf7326; } + .bp3-html-select.bp3-minimal select.bp3-intent-warning:disabled, + .bp3-select.bp3-minimal select.bp3-intent-warning:disabled, .bp3-html-select.bp3-minimal select.bp3-intent-warning.bp3-disabled, + .bp3-select.bp3-minimal select.bp3-intent-warning.bp3-disabled{ + background:none; + color:rgba(191, 115, 38, 0.5); } + .bp3-html-select.bp3-minimal select.bp3-intent-warning:disabled.bp3-active, + .bp3-select.bp3-minimal select.bp3-intent-warning:disabled.bp3-active, .bp3-html-select.bp3-minimal select.bp3-intent-warning.bp3-disabled.bp3-active, + .bp3-select.bp3-minimal select.bp3-intent-warning.bp3-disabled.bp3-active{ + background:rgba(217, 130, 43, 0.3); } + .bp3-html-select.bp3-minimal select.bp3-intent-warning .bp3-button-spinner .bp3-spinner-head, .bp3-select.bp3-minimal select.bp3-intent-warning .bp3-button-spinner .bp3-spinner-head{ + stroke:#bf7326; } + .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-warning, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-warning, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-warning, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-warning{ + color:#ffb366; } + .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-warning:hover, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-warning:hover, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-warning:hover, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-warning:hover{ + background:rgba(217, 130, 43, 0.2); + color:#ffb366; } + .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-warning:active, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-warning:active, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-warning:active, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-warning:active, .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-warning.bp3-active, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-warning.bp3-active, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-warning.bp3-active, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-warning.bp3-active{ + background:rgba(217, 130, 43, 0.3); + color:#ffb366; } + .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-warning:disabled, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-warning:disabled, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-warning:disabled, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-warning:disabled, .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-warning.bp3-disabled, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-warning.bp3-disabled, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-warning.bp3-disabled, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-warning.bp3-disabled{ + background:none; + color:rgba(255, 179, 102, 0.5); } + .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-warning:disabled.bp3-active, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-warning:disabled.bp3-active, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-warning:disabled.bp3-active, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-warning:disabled.bp3-active, .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-warning.bp3-disabled.bp3-active, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-warning.bp3-disabled.bp3-active, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-warning.bp3-disabled.bp3-active, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-warning.bp3-disabled.bp3-active{ + background:rgba(217, 130, 43, 0.3); } + .bp3-html-select.bp3-minimal select.bp3-intent-danger, + .bp3-select.bp3-minimal select.bp3-intent-danger{ + color:#c23030; } + .bp3-html-select.bp3-minimal select.bp3-intent-danger:hover, + .bp3-select.bp3-minimal select.bp3-intent-danger:hover, .bp3-html-select.bp3-minimal select.bp3-intent-danger:active, + .bp3-select.bp3-minimal select.bp3-intent-danger:active, .bp3-html-select.bp3-minimal select.bp3-intent-danger.bp3-active, + .bp3-select.bp3-minimal select.bp3-intent-danger.bp3-active{ + -webkit-box-shadow:none; + box-shadow:none; + background:none; + color:#c23030; } + .bp3-html-select.bp3-minimal select.bp3-intent-danger:hover, + .bp3-select.bp3-minimal select.bp3-intent-danger:hover{ + background:rgba(219, 55, 55, 0.15); + color:#c23030; } + .bp3-html-select.bp3-minimal select.bp3-intent-danger:active, + .bp3-select.bp3-minimal select.bp3-intent-danger:active, .bp3-html-select.bp3-minimal select.bp3-intent-danger.bp3-active, + .bp3-select.bp3-minimal select.bp3-intent-danger.bp3-active{ + background:rgba(219, 55, 55, 0.3); + color:#c23030; } + .bp3-html-select.bp3-minimal select.bp3-intent-danger:disabled, + .bp3-select.bp3-minimal select.bp3-intent-danger:disabled, .bp3-html-select.bp3-minimal select.bp3-intent-danger.bp3-disabled, + .bp3-select.bp3-minimal select.bp3-intent-danger.bp3-disabled{ + background:none; + color:rgba(194, 48, 48, 0.5); } + .bp3-html-select.bp3-minimal select.bp3-intent-danger:disabled.bp3-active, + .bp3-select.bp3-minimal select.bp3-intent-danger:disabled.bp3-active, .bp3-html-select.bp3-minimal select.bp3-intent-danger.bp3-disabled.bp3-active, + .bp3-select.bp3-minimal select.bp3-intent-danger.bp3-disabled.bp3-active{ + background:rgba(219, 55, 55, 0.3); } + .bp3-html-select.bp3-minimal select.bp3-intent-danger .bp3-button-spinner .bp3-spinner-head, .bp3-select.bp3-minimal select.bp3-intent-danger .bp3-button-spinner .bp3-spinner-head{ + stroke:#c23030; } + .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-danger, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-danger, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-danger, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-danger{ + color:#ff7373; } + .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-danger:hover, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-danger:hover, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-danger:hover, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-danger:hover{ + background:rgba(219, 55, 55, 0.2); + color:#ff7373; } + .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-danger:active, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-danger:active, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-danger:active, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-danger:active, .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-danger.bp3-active, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-danger.bp3-active, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-danger.bp3-active, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-danger.bp3-active{ + background:rgba(219, 55, 55, 0.3); + color:#ff7373; } + .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-danger:disabled, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-danger:disabled, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-danger:disabled, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-danger:disabled, .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-danger.bp3-disabled, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-danger.bp3-disabled, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-danger.bp3-disabled, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-danger.bp3-disabled{ + background:none; + color:rgba(255, 115, 115, 0.5); } + .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-danger:disabled.bp3-active, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-danger:disabled.bp3-active, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-danger:disabled.bp3-active, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-danger:disabled.bp3-active, .bp3-dark .bp3-html-select.bp3-minimal select.bp3-intent-danger.bp3-disabled.bp3-active, .bp3-html-select.bp3-minimal .bp3-dark select.bp3-intent-danger.bp3-disabled.bp3-active, + .bp3-dark .bp3-select.bp3-minimal select.bp3-intent-danger.bp3-disabled.bp3-active, .bp3-select.bp3-minimal .bp3-dark select.bp3-intent-danger.bp3-disabled.bp3-active{ + background:rgba(219, 55, 55, 0.3); } + +.bp3-html-select.bp3-large select, +.bp3-select.bp3-large select{ + height:40px; + padding-right:35px; + font-size:16px; } + +.bp3-dark .bp3-html-select select, .bp3-dark .bp3-select select{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + background-color:#394b59; + background-image:-webkit-gradient(linear, left top, left bottom, from(rgba(255, 255, 255, 0.05)), to(rgba(255, 255, 255, 0))); + background-image:linear-gradient(to bottom, rgba(255, 255, 255, 0.05), rgba(255, 255, 255, 0)); + color:#f5f8fa; } + .bp3-dark .bp3-html-select select:hover, .bp3-dark .bp3-select select:hover, .bp3-dark .bp3-html-select select:active, .bp3-dark .bp3-select select:active, .bp3-dark .bp3-html-select select.bp3-active, .bp3-dark .bp3-select select.bp3-active{ + color:#f5f8fa; } + .bp3-dark .bp3-html-select select:hover, .bp3-dark .bp3-select select:hover{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + background-color:#30404d; } + .bp3-dark .bp3-html-select select:active, .bp3-dark .bp3-select select:active, .bp3-dark .bp3-html-select select.bp3-active, .bp3-dark .bp3-select select.bp3-active{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.6), inset 0 1px 2px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.6), inset 0 1px 2px rgba(16, 22, 26, 0.2); + background-color:#202b33; + background-image:none; } + .bp3-dark .bp3-html-select select:disabled, .bp3-dark .bp3-select select:disabled, .bp3-dark .bp3-html-select select.bp3-disabled, .bp3-dark .bp3-select select.bp3-disabled{ + -webkit-box-shadow:none; + box-shadow:none; + background-color:rgba(57, 75, 89, 0.5); + background-image:none; + color:rgba(167, 182, 194, 0.6); } + .bp3-dark .bp3-html-select select:disabled.bp3-active, .bp3-dark .bp3-select select:disabled.bp3-active, .bp3-dark .bp3-html-select select.bp3-disabled.bp3-active, .bp3-dark .bp3-select select.bp3-disabled.bp3-active{ + background:rgba(57, 75, 89, 0.7); } + .bp3-dark .bp3-html-select select .bp3-button-spinner .bp3-spinner-head, .bp3-dark .bp3-select select .bp3-button-spinner .bp3-spinner-head{ + background:rgba(16, 22, 26, 0.5); + stroke:#8a9ba8; } + +.bp3-html-select select:disabled, +.bp3-select select:disabled{ + -webkit-box-shadow:none; + box-shadow:none; + background-color:rgba(206, 217, 224, 0.5); + cursor:not-allowed; + color:rgba(92, 112, 128, 0.6); } + +.bp3-html-select .bp3-icon, +.bp3-select .bp3-icon, .bp3-select::after{ + position:absolute; + top:7px; + right:7px; + color:#5c7080; + pointer-events:none; } + .bp3-html-select .bp3-disabled.bp3-icon, + .bp3-select .bp3-disabled.bp3-icon, .bp3-disabled.bp3-select::after{ + color:rgba(92, 112, 128, 0.6); } +.bp3-html-select, +.bp3-select{ + display:inline-block; + position:relative; + vertical-align:middle; + letter-spacing:normal; } + .bp3-html-select select::-ms-expand, + .bp3-select select::-ms-expand{ + display:none; } + .bp3-html-select .bp3-icon, + .bp3-select .bp3-icon{ + color:#5c7080; } + .bp3-html-select .bp3-icon:hover, + .bp3-select .bp3-icon:hover{ + color:#182026; } + .bp3-dark .bp3-html-select .bp3-icon, .bp3-dark + .bp3-select .bp3-icon{ + color:#a7b6c2; } + .bp3-dark .bp3-html-select .bp3-icon:hover, .bp3-dark + .bp3-select .bp3-icon:hover{ + color:#f5f8fa; } + .bp3-html-select.bp3-large::after, + .bp3-html-select.bp3-large .bp3-icon, + .bp3-select.bp3-large::after, + .bp3-select.bp3-large .bp3-icon{ + top:12px; + right:12px; } + .bp3-html-select.bp3-fill, + .bp3-html-select.bp3-fill select, + .bp3-select.bp3-fill, + .bp3-select.bp3-fill select{ + width:100%; } + .bp3-dark .bp3-html-select option, .bp3-dark + .bp3-select option{ + background-color:#30404d; + color:#f5f8fa; } + .bp3-dark .bp3-html-select::after, .bp3-dark + .bp3-select::after{ + color:#a7b6c2; } + +.bp3-select::after{ + line-height:1; + font-family:"Icons16", sans-serif; + font-size:16px; + font-weight:400; + font-style:normal; + -moz-osx-font-smoothing:grayscale; + -webkit-font-smoothing:antialiased; + content:""; } +.bp3-running-text table, table.bp3-html-table{ + border-spacing:0; + font-size:14px; } + .bp3-running-text table th, table.bp3-html-table th, + .bp3-running-text table td, + table.bp3-html-table td{ + padding:11px; + vertical-align:top; + text-align:left; } + .bp3-running-text table th, table.bp3-html-table th{ + color:#182026; + font-weight:600; } + + .bp3-running-text table td, + table.bp3-html-table td{ + color:#182026; } + .bp3-running-text table tbody tr:first-child th, table.bp3-html-table tbody tr:first-child th, + .bp3-running-text table tbody tr:first-child td, + table.bp3-html-table tbody tr:first-child td{ + -webkit-box-shadow:inset 0 1px 0 0 rgba(16, 22, 26, 0.15); + box-shadow:inset 0 1px 0 0 rgba(16, 22, 26, 0.15); } + .bp3-dark .bp3-running-text table th, .bp3-running-text .bp3-dark table th, .bp3-dark table.bp3-html-table th{ + color:#f5f8fa; } + .bp3-dark .bp3-running-text table td, .bp3-running-text .bp3-dark table td, .bp3-dark table.bp3-html-table td{ + color:#f5f8fa; } + .bp3-dark .bp3-running-text table tbody tr:first-child th, .bp3-running-text .bp3-dark table tbody tr:first-child th, .bp3-dark table.bp3-html-table tbody tr:first-child th, + .bp3-dark .bp3-running-text table tbody tr:first-child td, + .bp3-running-text .bp3-dark table tbody tr:first-child td, + .bp3-dark table.bp3-html-table tbody tr:first-child td{ + -webkit-box-shadow:inset 0 1px 0 0 rgba(255, 255, 255, 0.15); + box-shadow:inset 0 1px 0 0 rgba(255, 255, 255, 0.15); } + +table.bp3-html-table.bp3-html-table-condensed th, +table.bp3-html-table.bp3-html-table-condensed td, table.bp3-html-table.bp3-small th, +table.bp3-html-table.bp3-small td{ + padding-top:6px; + padding-bottom:6px; } + +table.bp3-html-table.bp3-html-table-striped tbody tr:nth-child(odd) td{ + background:rgba(191, 204, 214, 0.15); } + +table.bp3-html-table.bp3-html-table-bordered th:not(:first-child){ + -webkit-box-shadow:inset 1px 0 0 0 rgba(16, 22, 26, 0.15); + box-shadow:inset 1px 0 0 0 rgba(16, 22, 26, 0.15); } + +table.bp3-html-table.bp3-html-table-bordered tbody tr td{ + -webkit-box-shadow:inset 0 1px 0 0 rgba(16, 22, 26, 0.15); + box-shadow:inset 0 1px 0 0 rgba(16, 22, 26, 0.15); } + table.bp3-html-table.bp3-html-table-bordered tbody tr td:not(:first-child){ + -webkit-box-shadow:inset 1px 1px 0 0 rgba(16, 22, 26, 0.15); + box-shadow:inset 1px 1px 0 0 rgba(16, 22, 26, 0.15); } + +table.bp3-html-table.bp3-html-table-bordered.bp3-html-table-striped tbody tr:not(:first-child) td{ + -webkit-box-shadow:none; + box-shadow:none; } + table.bp3-html-table.bp3-html-table-bordered.bp3-html-table-striped tbody tr:not(:first-child) td:not(:first-child){ + -webkit-box-shadow:inset 1px 0 0 0 rgba(16, 22, 26, 0.15); + box-shadow:inset 1px 0 0 0 rgba(16, 22, 26, 0.15); } + +table.bp3-html-table.bp3-interactive tbody tr:hover td{ + background-color:rgba(191, 204, 214, 0.3); + cursor:pointer; } + +table.bp3-html-table.bp3-interactive tbody tr:active td{ + background-color:rgba(191, 204, 214, 0.4); } + +.bp3-dark table.bp3-html-table.bp3-html-table-striped tbody tr:nth-child(odd) td{ + background:rgba(92, 112, 128, 0.15); } + +.bp3-dark table.bp3-html-table.bp3-html-table-bordered th:not(:first-child){ + -webkit-box-shadow:inset 1px 0 0 0 rgba(255, 255, 255, 0.15); + box-shadow:inset 1px 0 0 0 rgba(255, 255, 255, 0.15); } + +.bp3-dark table.bp3-html-table.bp3-html-table-bordered tbody tr td{ + -webkit-box-shadow:inset 0 1px 0 0 rgba(255, 255, 255, 0.15); + box-shadow:inset 0 1px 0 0 rgba(255, 255, 255, 0.15); } + .bp3-dark table.bp3-html-table.bp3-html-table-bordered tbody tr td:not(:first-child){ + -webkit-box-shadow:inset 1px 1px 0 0 rgba(255, 255, 255, 0.15); + box-shadow:inset 1px 1px 0 0 rgba(255, 255, 255, 0.15); } + +.bp3-dark table.bp3-html-table.bp3-html-table-bordered.bp3-html-table-striped tbody tr:not(:first-child) td{ + -webkit-box-shadow:inset 1px 0 0 0 rgba(255, 255, 255, 0.15); + box-shadow:inset 1px 0 0 0 rgba(255, 255, 255, 0.15); } + .bp3-dark table.bp3-html-table.bp3-html-table-bordered.bp3-html-table-striped tbody tr:not(:first-child) td:first-child{ + -webkit-box-shadow:none; + box-shadow:none; } + +.bp3-dark table.bp3-html-table.bp3-interactive tbody tr:hover td{ + background-color:rgba(92, 112, 128, 0.3); + cursor:pointer; } + +.bp3-dark table.bp3-html-table.bp3-interactive tbody tr:active td{ + background-color:rgba(92, 112, 128, 0.4); } + +.bp3-key-combo{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; + -webkit-box-orient:horizontal; + -webkit-box-direction:normal; + -ms-flex-direction:row; + flex-direction:row; + -webkit-box-align:center; + -ms-flex-align:center; + align-items:center; } + .bp3-key-combo > *{ + -webkit-box-flex:0; + -ms-flex-positive:0; + flex-grow:0; + -ms-flex-negative:0; + flex-shrink:0; } + .bp3-key-combo > .bp3-fill{ + -webkit-box-flex:1; + -ms-flex-positive:1; + flex-grow:1; + -ms-flex-negative:1; + flex-shrink:1; } + .bp3-key-combo::before, + .bp3-key-combo > *{ + margin-right:5px; } + .bp3-key-combo:empty::before, + .bp3-key-combo > :last-child{ + margin-right:0; } + +.bp3-hotkey-dialog{ + top:40px; + padding-bottom:0; } + .bp3-hotkey-dialog .bp3-dialog-body{ + margin:0; + padding:0; } + .bp3-hotkey-dialog .bp3-hotkey-label{ + -webkit-box-flex:1; + -ms-flex-positive:1; + flex-grow:1; } + +.bp3-hotkey-column{ + margin:auto; + max-height:80vh; + overflow-y:auto; + padding:30px; } + .bp3-hotkey-column .bp3-heading{ + margin-bottom:20px; } + .bp3-hotkey-column .bp3-heading:not(:first-child){ + margin-top:40px; } + +.bp3-hotkey{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; + -webkit-box-align:center; + -ms-flex-align:center; + align-items:center; + -webkit-box-pack:justify; + -ms-flex-pack:justify; + justify-content:space-between; + margin-right:0; + margin-left:0; } + .bp3-hotkey:not(:last-child){ + margin-bottom:10px; } +.bp3-icon{ + display:inline-block; + -webkit-box-flex:0; + -ms-flex:0 0 auto; + flex:0 0 auto; + vertical-align:text-bottom; } + .bp3-icon:not(:empty)::before{ + content:"" !important; + content:unset !important; } + .bp3-icon > svg{ + display:block; } + .bp3-icon > svg:not([fill]){ + fill:currentColor; } + +.bp3-icon.bp3-intent-primary, .bp3-icon-standard.bp3-intent-primary, .bp3-icon-large.bp3-intent-primary{ + color:#106ba3; } + .bp3-dark .bp3-icon.bp3-intent-primary, .bp3-dark .bp3-icon-standard.bp3-intent-primary, .bp3-dark .bp3-icon-large.bp3-intent-primary{ + color:#48aff0; } + +.bp3-icon.bp3-intent-success, .bp3-icon-standard.bp3-intent-success, .bp3-icon-large.bp3-intent-success{ + color:#0d8050; } + .bp3-dark .bp3-icon.bp3-intent-success, .bp3-dark .bp3-icon-standard.bp3-intent-success, .bp3-dark .bp3-icon-large.bp3-intent-success{ + color:#3dcc91; } + +.bp3-icon.bp3-intent-warning, .bp3-icon-standard.bp3-intent-warning, .bp3-icon-large.bp3-intent-warning{ + color:#bf7326; } + .bp3-dark .bp3-icon.bp3-intent-warning, .bp3-dark .bp3-icon-standard.bp3-intent-warning, .bp3-dark .bp3-icon-large.bp3-intent-warning{ + color:#ffb366; } + +.bp3-icon.bp3-intent-danger, .bp3-icon-standard.bp3-intent-danger, .bp3-icon-large.bp3-intent-danger{ + color:#c23030; } + .bp3-dark .bp3-icon.bp3-intent-danger, .bp3-dark .bp3-icon-standard.bp3-intent-danger, .bp3-dark .bp3-icon-large.bp3-intent-danger{ + color:#ff7373; } + +span.bp3-icon-standard{ + line-height:1; + font-family:"Icons16", sans-serif; + font-size:16px; + font-weight:400; + font-style:normal; + -moz-osx-font-smoothing:grayscale; + -webkit-font-smoothing:antialiased; + display:inline-block; } + +span.bp3-icon-large{ + line-height:1; + font-family:"Icons20", sans-serif; + font-size:20px; + font-weight:400; + font-style:normal; + -moz-osx-font-smoothing:grayscale; + -webkit-font-smoothing:antialiased; + display:inline-block; } + +span.bp3-icon:empty{ + line-height:1; + font-family:"Icons20"; + font-size:inherit; + font-weight:400; + font-style:normal; } + span.bp3-icon:empty::before{ + -moz-osx-font-smoothing:grayscale; + -webkit-font-smoothing:antialiased; } + +.bp3-icon-add::before{ + content:""; } + +.bp3-icon-add-column-left::before{ + content:""; } + +.bp3-icon-add-column-right::before{ + content:""; } + +.bp3-icon-add-row-bottom::before{ + content:""; } + +.bp3-icon-add-row-top::before{ + content:"î›·"; } + +.bp3-icon-add-to-artifact::before{ + content:""; } + +.bp3-icon-add-to-folder::before{ + content:"î›’"; 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} + +.bp3-icon-mobile-phone::before{ + content:""; } + +.bp3-icon-mobile-video::before{ + content:""; } + +.bp3-icon-moon::before{ + content:"î”"; } + +.bp3-icon-more::before{ + content:""; } + +.bp3-icon-mountain::before{ + content:"îž±"; } + +.bp3-icon-move::before{ + content:"îš“"; } + +.bp3-icon-mugshot::before{ + content:"î››"; } + +.bp3-icon-multi-select::before{ + content:""; } + +.bp3-icon-music::before{ + content:""; } + +.bp3-icon-new-drawing::before{ + content:""; } + +.bp3-icon-new-grid-item::before{ + content:"î‡"; } + +.bp3-icon-new-layer::before{ + content:""; } + +.bp3-icon-new-layers::before{ + content:""; } + +.bp3-icon-new-link::before{ + content:""; } + +.bp3-icon-new-object::before{ + content:"î™"; } + +.bp3-icon-new-person::before{ + content:""; } + +.bp3-icon-new-prescription::before{ + content:"îž‹"; } + +.bp3-icon-new-text-box::before{ + content:"î™›"; } + +.bp3-icon-ninja::before{ + content:""; } + +.bp3-icon-not-equal-to::before{ + content:"îŸ "; } + +.bp3-icon-notifications::before{ + content:""; } + +.bp3-icon-notifications-updated::before{ + content:""; } + +.bp3-icon-numbered-list::before{ + content:"î†"; } + +.bp3-icon-numerical::before{ + content:"î–"; } + +.bp3-icon-office::before{ + content:"îš›"; } + +.bp3-icon-offline::before{ + content:""; } + +.bp3-icon-oil-field::before{ + content:""; } + +.bp3-icon-one-column::before{ + content:""; } + +.bp3-icon-outdated::before{ + content:""; } + +.bp3-icon-page-layout::before{ + content:"î™ "; } + +.bp3-icon-panel-stats::before{ + content:"î·"; } + +.bp3-icon-panel-table::before{ + content:"î¸"; } + +.bp3-icon-paperclip::before{ + content:""; } + +.bp3-icon-paragraph::before{ + content:"î¬"; } + +.bp3-icon-path::before{ + content:"î“"; } + +.bp3-icon-path-search::before{ + content:""; } + +.bp3-icon-pause::before{ + content:"îš©"; } + +.bp3-icon-people::before{ + content:""; } + +.bp3-icon-percentage::before{ + content:"îª"; } + +.bp3-icon-person::before{ + content:""; } + +.bp3-icon-phone::before{ + content:"☎"; } + +.bp3-icon-pie-chart::before{ + content:"îš„"; } + +.bp3-icon-pin::before{ + content:""; } + +.bp3-icon-pivot::before{ + content:"î›±"; } + +.bp3-icon-pivot-table::before{ + content:""; } + +.bp3-icon-play::before{ + content:"îš«"; } + +.bp3-icon-plus::before{ + content:"+"; } + +.bp3-icon-polygon-filter::before{ + content:""; } + +.bp3-icon-power::before{ + content:"î›™"; } + +.bp3-icon-predictive-analysis::before{ + content:""; } + +.bp3-icon-prescription::before{ + content:""; } + +.bp3-icon-presentation::before{ + content:""; } + +.bp3-icon-print::before{ + content:"⎙"; } + +.bp3-icon-projects::before{ + content:""; } + +.bp3-icon-properties::before{ + content:""; } + +.bp3-icon-property::before{ + content:""; } + +.bp3-icon-publish-function::before{ + content:"î’"; } + +.bp3-icon-pulse::before{ + content:""; } + +.bp3-icon-random::before{ + content:""; } + +.bp3-icon-record::before{ + content:"îš®"; } + +.bp3-icon-redo::before{ + content:""; } + +.bp3-icon-refresh::before{ + content:""; } + +.bp3-icon-regression-chart::before{ + content:"î˜"; } + +.bp3-icon-remove::before{ + content:""; } + +.bp3-icon-remove-column::before{ + content:"î•"; } + +.bp3-icon-remove-column-left::before{ + content:""; } + +.bp3-icon-remove-column-right::before{ + content:""; } + +.bp3-icon-remove-row-bottom::before{ + content:""; } + +.bp3-icon-remove-row-top::before{ + content:"î›»"; } + +.bp3-icon-repeat::before{ + content:"îš’"; } + +.bp3-icon-reset::before{ + content:""; } + +.bp3-icon-resolve::before{ + content:""; } + +.bp3-icon-rig::before{ + content:"î€"; } + +.bp3-icon-right-join::before{ + content:""; } + +.bp3-icon-ring::before{ + content:""; } + +.bp3-icon-rotate-document::before{ + content:""; } + +.bp3-icon-rotate-page::before{ + content:""; } + +.bp3-icon-satellite::before{ + content:"î«"; } + +.bp3-icon-saved::before{ + content:"îš¶"; } + +.bp3-icon-scatter-plot::before{ + content:""; } + +.bp3-icon-search::before{ + content:""; } + +.bp3-icon-search-around::before{ + content:""; } + +.bp3-icon-search-template::before{ + content:""; } + +.bp3-icon-search-text::before{ + content:""; } + +.bp3-icon-segmented-control::before{ + content:""; } + +.bp3-icon-select::before{ + content:""; } + +.bp3-icon-selection::before{ + content:"⦿"; } + +.bp3-icon-send-to::before{ + content:"î™®"; } + +.bp3-icon-send-to-graph::before{ + content:""; } + +.bp3-icon-send-to-map::before{ + content:""; } + +.bp3-icon-series-add::before{ + content:"îž–"; } + +.bp3-icon-series-configuration::before{ + content:"îžš"; } + +.bp3-icon-series-derived::before{ + content:"îž™"; } + +.bp3-icon-series-filtered::before{ + content:""; } + +.bp3-icon-series-search::before{ + content:"îž—"; } + +.bp3-icon-settings::before{ + content:""; } + +.bp3-icon-share::before{ + content:""; } + +.bp3-icon-shield::before{ + content:"îž²"; } + +.bp3-icon-shop::before{ + content:""; } + +.bp3-icon-shopping-cart::before{ + content:"î›"; } + +.bp3-icon-signal-search::before{ + content:""; } + +.bp3-icon-sim-card::before{ + content:""; } + +.bp3-icon-slash::before{ + content:"î©"; } + +.bp3-icon-small-cross::before{ + content:"î›—"; } + +.bp3-icon-small-minus::before{ + content:""; } + +.bp3-icon-small-plus::before{ + content:"îœ"; } + +.bp3-icon-small-tick::before{ + content:""; } + +.bp3-icon-snowflake::before{ + content:"îž¶"; } + +.bp3-icon-social-media::before{ + content:"î™±"; } + +.bp3-icon-sort::before{ + content:"î™"; } + +.bp3-icon-sort-alphabetical::before{ + content:"î™"; } + +.bp3-icon-sort-alphabetical-desc::before{ + content:""; } + +.bp3-icon-sort-asc::before{ + content:""; } + +.bp3-icon-sort-desc::before{ + content:"î›–"; } + +.bp3-icon-sort-numerical::before{ + content:""; } + +.bp3-icon-sort-numerical-desc::before{ + content:""; } + +.bp3-icon-split-columns::before{ + content:"î"; } + +.bp3-icon-square::before{ + content:""; } + +.bp3-icon-stacked-chart::before{ + content:"î›§"; } + +.bp3-icon-star::before{ + content:"★"; } + +.bp3-icon-star-empty::before{ + content:"☆"; } + +.bp3-icon-step-backward::before{ + content:"îš§"; } + +.bp3-icon-step-chart::before{ + content:"îœ"; } + +.bp3-icon-step-forward::before{ + content:"îš"; } + +.bp3-icon-stop::before{ + content:""; } + +.bp3-icon-stopwatch::before{ + content:"î¤"; } + +.bp3-icon-strikethrough::before{ + content:""; } + +.bp3-icon-style::before{ + content:"î˜"; } + +.bp3-icon-swap-horizontal::before{ + content:"î…"; } + +.bp3-icon-swap-vertical::before{ + content:"î„"; } + +.bp3-icon-symbol-circle::before{ + content:""; } + +.bp3-icon-symbol-cross::before{ + content:""; } + +.bp3-icon-symbol-diamond::before{ + content:""; } + +.bp3-icon-symbol-square::before{ + content:""; } + +.bp3-icon-symbol-triangle-down::before{ + content:""; } + +.bp3-icon-symbol-triangle-up::before{ + content:""; } + +.bp3-icon-tag::before{ + content:""; } + +.bp3-icon-take-action::before{ + content:""; } + +.bp3-icon-taxi::before{ + content:"îžž"; } + +.bp3-icon-text-highlight::before{ + content:"î›"; } + +.bp3-icon-th::before{ + content:"î™§"; } + +.bp3-icon-th-derived::before{ + content:""; } + +.bp3-icon-th-disconnect::before{ + content:""; } + +.bp3-icon-th-filtered::before{ + content:""; } + +.bp3-icon-th-list::before{ + content:""; } + +.bp3-icon-thumbs-down::before{ + content:"îš¾"; } + +.bp3-icon-thumbs-up::before{ + content:"îš½"; } + +.bp3-icon-tick::before{ + content:"✓"; } + +.bp3-icon-tick-circle::before{ + content:"î¹"; } + +.bp3-icon-time::before{ + content:"â²"; } + +.bp3-icon-timeline-area-chart::before{ + content:"î›"; } + +.bp3-icon-timeline-bar-chart::before{ + content:"î˜ "; } + +.bp3-icon-timeline-events::before{ + content:""; } + +.bp3-icon-timeline-line-chart::before{ + content:""; } + +.bp3-icon-tint::before{ + content:"îš²"; } + +.bp3-icon-torch::before{ + content:"î™·"; } + +.bp3-icon-tractor::before{ + content:""; } + +.bp3-icon-train::before{ + content:""; } + +.bp3-icon-translate::before{ + content:"î™"; } + +.bp3-icon-trash::before{ + content:""; } + +.bp3-icon-tree::before{ + content:"îž·"; } + +.bp3-icon-trending-down::before{ + content:""; } + +.bp3-icon-trending-up::before{ + content:""; } + +.bp3-icon-truck::before{ + content:""; } + +.bp3-icon-two-columns::before{ + content:"î™—"; } + +.bp3-icon-unarchive::before{ + content:""; } + +.bp3-icon-underline::before{ + content:"âŽ"; } + +.bp3-icon-undo::before{ + content:"⎌"; } + +.bp3-icon-ungroup-objects::before{ + content:""; } + +.bp3-icon-unknown-vehicle::before{ + content:""; } + +.bp3-icon-unlock::before{ + content:""; } + +.bp3-icon-unpin::before{ + content:"î™"; } + +.bp3-icon-unresolve::before{ + content:""; } + +.bp3-icon-updated::before{ + content:"îž§"; } + +.bp3-icon-upload::before{ + content:"îš"; } + +.bp3-icon-user::before{ + content:""; } + +.bp3-icon-variable::before{ + content:""; } + +.bp3-icon-vertical-bar-chart-asc::before{ + content:"î›"; } + +.bp3-icon-vertical-bar-chart-desc::before{ + content:""; } + +.bp3-icon-vertical-distribution::before{ + content:""; } + +.bp3-icon-video::before{ + content:"îš "; } + +.bp3-icon-volume-down::before{ + content:""; } + +.bp3-icon-volume-off::before{ + content:""; } + +.bp3-icon-volume-up::before{ + content:""; } + +.bp3-icon-walk::before{ + content:"îž"; } + +.bp3-icon-warning-sign::before{ + content:""; } + +.bp3-icon-waterfall-chart::before{ + content:""; } + +.bp3-icon-widget::before{ + content:""; } + +.bp3-icon-widget-button::before{ + content:"îž"; } + +.bp3-icon-widget-footer::before{ + content:"îž’"; } + +.bp3-icon-widget-header::before{ + content:"îž‘"; } + +.bp3-icon-wrench::before{ + content:""; } + +.bp3-icon-zoom-in::before{ + content:"î™"; } + +.bp3-icon-zoom-out::before{ + content:""; } + +.bp3-icon-zoom-to-fit::before{ + content:"î™»"; } +.bp3-submenu > .bp3-popover-wrapper{ + display:block; } + +.bp3-submenu .bp3-popover-target{ + display:block; } + +.bp3-submenu.bp3-popover{ + -webkit-box-shadow:none; + box-shadow:none; + padding:0 5px; } + .bp3-submenu.bp3-popover > .bp3-popover-content{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 2px 4px rgba(16, 22, 26, 0.2), 0 8px 24px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 2px 4px rgba(16, 22, 26, 0.2), 0 8px 24px rgba(16, 22, 26, 0.2); } + .bp3-dark .bp3-submenu.bp3-popover, .bp3-submenu.bp3-popover.bp3-dark{ + -webkit-box-shadow:none; + box-shadow:none; } + .bp3-dark .bp3-submenu.bp3-popover > .bp3-popover-content, .bp3-submenu.bp3-popover.bp3-dark > .bp3-popover-content{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 2px 4px rgba(16, 22, 26, 0.4), 0 8px 24px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 2px 4px rgba(16, 22, 26, 0.4), 0 8px 24px rgba(16, 22, 26, 0.4); } +.bp3-menu{ + margin:0; + border-radius:3px; + background:#ffffff; + min-width:180px; + padding:5px; + list-style:none; + text-align:left; + color:#182026; } + +.bp3-menu-divider{ + display:block; + margin:5px; + border-top:1px solid rgba(16, 22, 26, 0.15); } + .bp3-dark .bp3-menu-divider{ + border-top-color:rgba(255, 255, 255, 0.15); } + +.bp3-menu-item{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; + -webkit-box-orient:horizontal; + -webkit-box-direction:normal; + -ms-flex-direction:row; + flex-direction:row; + -webkit-box-align:start; + -ms-flex-align:start; + align-items:flex-start; + border-radius:2px; + padding:5px 7px; + text-decoration:none; + line-height:20px; + color:inherit; + -webkit-user-select:none; + -moz-user-select:none; + -ms-user-select:none; + user-select:none; } + .bp3-menu-item > *{ + -webkit-box-flex:0; + -ms-flex-positive:0; + flex-grow:0; + -ms-flex-negative:0; + flex-shrink:0; } + .bp3-menu-item > .bp3-fill{ + -webkit-box-flex:1; + -ms-flex-positive:1; + flex-grow:1; + -ms-flex-negative:1; + flex-shrink:1; } + .bp3-menu-item::before, + .bp3-menu-item > *{ + margin-right:7px; } + .bp3-menu-item:empty::before, + .bp3-menu-item > :last-child{ + margin-right:0; } + .bp3-menu-item > .bp3-fill{ + word-break:break-word; } + .bp3-menu-item:hover, .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-menu-item{ + background-color:rgba(167, 182, 194, 0.3); + cursor:pointer; + text-decoration:none; } + .bp3-menu-item.bp3-disabled{ + background-color:inherit; + cursor:not-allowed; + color:rgba(92, 112, 128, 0.6); } + .bp3-dark .bp3-menu-item{ + color:inherit; } + .bp3-dark .bp3-menu-item:hover, .bp3-dark .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-menu-item, .bp3-submenu .bp3-dark .bp3-popover-target.bp3-popover-open > .bp3-menu-item{ + background-color:rgba(138, 155, 168, 0.15); + color:inherit; } + .bp3-dark .bp3-menu-item.bp3-disabled{ + background-color:inherit; + color:rgba(167, 182, 194, 0.6); } + .bp3-menu-item.bp3-intent-primary{ + color:#106ba3; } + .bp3-menu-item.bp3-intent-primary .bp3-icon{ + color:inherit; } + .bp3-menu-item.bp3-intent-primary::before, .bp3-menu-item.bp3-intent-primary::after, + .bp3-menu-item.bp3-intent-primary .bp3-menu-item-label{ + color:#106ba3; } + .bp3-menu-item.bp3-intent-primary:hover, .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-primary.bp3-menu-item, .bp3-menu-item.bp3-intent-primary.bp3-active{ + background-color:#137cbd; } + .bp3-menu-item.bp3-intent-primary:active{ + background-color:#106ba3; } + .bp3-menu-item.bp3-intent-primary:hover, .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-primary.bp3-menu-item, .bp3-menu-item.bp3-intent-primary:hover::before, .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-primary.bp3-menu-item::before, .bp3-menu-item.bp3-intent-primary:hover::after, .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-primary.bp3-menu-item::after, + .bp3-menu-item.bp3-intent-primary:hover .bp3-menu-item-label, + .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-primary.bp3-menu-item .bp3-menu-item-label, .bp3-menu-item.bp3-intent-primary:active, .bp3-menu-item.bp3-intent-primary:active::before, .bp3-menu-item.bp3-intent-primary:active::after, + .bp3-menu-item.bp3-intent-primary:active .bp3-menu-item-label, .bp3-menu-item.bp3-intent-primary.bp3-active, .bp3-menu-item.bp3-intent-primary.bp3-active::before, .bp3-menu-item.bp3-intent-primary.bp3-active::after, + .bp3-menu-item.bp3-intent-primary.bp3-active .bp3-menu-item-label{ + color:#ffffff; } + .bp3-menu-item.bp3-intent-success{ + color:#0d8050; } + .bp3-menu-item.bp3-intent-success .bp3-icon{ + color:inherit; } + .bp3-menu-item.bp3-intent-success::before, .bp3-menu-item.bp3-intent-success::after, + .bp3-menu-item.bp3-intent-success .bp3-menu-item-label{ + color:#0d8050; } + .bp3-menu-item.bp3-intent-success:hover, .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-success.bp3-menu-item, .bp3-menu-item.bp3-intent-success.bp3-active{ + background-color:#0f9960; } + .bp3-menu-item.bp3-intent-success:active{ + background-color:#0d8050; } + .bp3-menu-item.bp3-intent-success:hover, .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-success.bp3-menu-item, .bp3-menu-item.bp3-intent-success:hover::before, .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-success.bp3-menu-item::before, .bp3-menu-item.bp3-intent-success:hover::after, .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-success.bp3-menu-item::after, + .bp3-menu-item.bp3-intent-success:hover .bp3-menu-item-label, + .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-success.bp3-menu-item .bp3-menu-item-label, .bp3-menu-item.bp3-intent-success:active, .bp3-menu-item.bp3-intent-success:active::before, .bp3-menu-item.bp3-intent-success:active::after, + .bp3-menu-item.bp3-intent-success:active .bp3-menu-item-label, .bp3-menu-item.bp3-intent-success.bp3-active, .bp3-menu-item.bp3-intent-success.bp3-active::before, .bp3-menu-item.bp3-intent-success.bp3-active::after, + .bp3-menu-item.bp3-intent-success.bp3-active .bp3-menu-item-label{ + color:#ffffff; } + .bp3-menu-item.bp3-intent-warning{ + color:#bf7326; } + .bp3-menu-item.bp3-intent-warning .bp3-icon{ + color:inherit; } + .bp3-menu-item.bp3-intent-warning::before, .bp3-menu-item.bp3-intent-warning::after, + .bp3-menu-item.bp3-intent-warning .bp3-menu-item-label{ + color:#bf7326; } + .bp3-menu-item.bp3-intent-warning:hover, .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-warning.bp3-menu-item, .bp3-menu-item.bp3-intent-warning.bp3-active{ + background-color:#d9822b; } + .bp3-menu-item.bp3-intent-warning:active{ + background-color:#bf7326; } + .bp3-menu-item.bp3-intent-warning:hover, .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-warning.bp3-menu-item, .bp3-menu-item.bp3-intent-warning:hover::before, .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-warning.bp3-menu-item::before, .bp3-menu-item.bp3-intent-warning:hover::after, .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-warning.bp3-menu-item::after, + .bp3-menu-item.bp3-intent-warning:hover .bp3-menu-item-label, + .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-warning.bp3-menu-item .bp3-menu-item-label, .bp3-menu-item.bp3-intent-warning:active, .bp3-menu-item.bp3-intent-warning:active::before, .bp3-menu-item.bp3-intent-warning:active::after, + .bp3-menu-item.bp3-intent-warning:active .bp3-menu-item-label, .bp3-menu-item.bp3-intent-warning.bp3-active, .bp3-menu-item.bp3-intent-warning.bp3-active::before, .bp3-menu-item.bp3-intent-warning.bp3-active::after, + .bp3-menu-item.bp3-intent-warning.bp3-active .bp3-menu-item-label{ + color:#ffffff; } + .bp3-menu-item.bp3-intent-danger{ + color:#c23030; } + .bp3-menu-item.bp3-intent-danger .bp3-icon{ + color:inherit; } + .bp3-menu-item.bp3-intent-danger::before, .bp3-menu-item.bp3-intent-danger::after, + .bp3-menu-item.bp3-intent-danger .bp3-menu-item-label{ + color:#c23030; } + .bp3-menu-item.bp3-intent-danger:hover, .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-danger.bp3-menu-item, .bp3-menu-item.bp3-intent-danger.bp3-active{ + background-color:#db3737; } + .bp3-menu-item.bp3-intent-danger:active{ + background-color:#c23030; } + .bp3-menu-item.bp3-intent-danger:hover, .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-danger.bp3-menu-item, .bp3-menu-item.bp3-intent-danger:hover::before, .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-danger.bp3-menu-item::before, .bp3-menu-item.bp3-intent-danger:hover::after, .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-danger.bp3-menu-item::after, + .bp3-menu-item.bp3-intent-danger:hover .bp3-menu-item-label, + .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-danger.bp3-menu-item .bp3-menu-item-label, .bp3-menu-item.bp3-intent-danger:active, .bp3-menu-item.bp3-intent-danger:active::before, .bp3-menu-item.bp3-intent-danger:active::after, + .bp3-menu-item.bp3-intent-danger:active .bp3-menu-item-label, .bp3-menu-item.bp3-intent-danger.bp3-active, .bp3-menu-item.bp3-intent-danger.bp3-active::before, .bp3-menu-item.bp3-intent-danger.bp3-active::after, + .bp3-menu-item.bp3-intent-danger.bp3-active .bp3-menu-item-label{ + color:#ffffff; } + .bp3-menu-item::before{ + line-height:1; + font-family:"Icons16", sans-serif; + font-size:16px; + font-weight:400; + font-style:normal; + -moz-osx-font-smoothing:grayscale; + -webkit-font-smoothing:antialiased; + margin-right:7px; } + .bp3-menu-item::before, + .bp3-menu-item > .bp3-icon{ + margin-top:2px; + color:#5c7080; } + .bp3-menu-item .bp3-menu-item-label{ + color:#5c7080; } + .bp3-menu-item:hover, .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-menu-item{ + color:inherit; } + .bp3-menu-item.bp3-active, .bp3-menu-item:active{ + background-color:rgba(115, 134, 148, 0.3); } + .bp3-menu-item.bp3-disabled{ + outline:none !important; + background-color:inherit !important; + cursor:not-allowed !important; + color:rgba(92, 112, 128, 0.6) !important; } + .bp3-menu-item.bp3-disabled::before, + .bp3-menu-item.bp3-disabled > .bp3-icon, + .bp3-menu-item.bp3-disabled .bp3-menu-item-label{ + color:rgba(92, 112, 128, 0.6) !important; } + .bp3-large .bp3-menu-item{ + padding:9px 7px; + line-height:22px; + font-size:16px; } + .bp3-large .bp3-menu-item .bp3-icon{ + margin-top:3px; } + .bp3-large .bp3-menu-item::before{ + line-height:1; + font-family:"Icons20", sans-serif; + font-size:20px; + font-weight:400; + font-style:normal; + -moz-osx-font-smoothing:grayscale; + -webkit-font-smoothing:antialiased; + margin-top:1px; + margin-right:10px; } + +button.bp3-menu-item{ + border:none; + background:none; + width:100%; + text-align:left; } +.bp3-menu-header{ + display:block; + margin:5px; + border-top:1px solid rgba(16, 22, 26, 0.15); + cursor:default; + padding-left:2px; } + .bp3-dark .bp3-menu-header{ + border-top-color:rgba(255, 255, 255, 0.15); } + .bp3-menu-header:first-of-type{ + border-top:none; } + .bp3-menu-header > h6{ + color:#182026; + font-weight:600; + overflow:hidden; + text-overflow:ellipsis; + white-space:nowrap; + word-wrap:normal; + margin:0; + padding:10px 7px 0 1px; + line-height:17px; } + .bp3-dark .bp3-menu-header > h6{ + color:#f5f8fa; } + .bp3-menu-header:first-of-type > h6{ + padding-top:0; } + .bp3-large .bp3-menu-header > h6{ + padding-top:15px; + padding-bottom:5px; + font-size:18px; } + .bp3-large .bp3-menu-header:first-of-type > h6{ + padding-top:0; } + +.bp3-dark .bp3-menu{ + background:#30404d; + color:#f5f8fa; } + +.bp3-dark .bp3-menu-item.bp3-intent-primary{ + color:#48aff0; } + .bp3-dark .bp3-menu-item.bp3-intent-primary .bp3-icon{ + color:inherit; } + .bp3-dark .bp3-menu-item.bp3-intent-primary::before, .bp3-dark .bp3-menu-item.bp3-intent-primary::after, + .bp3-dark .bp3-menu-item.bp3-intent-primary .bp3-menu-item-label{ + color:#48aff0; } + .bp3-dark .bp3-menu-item.bp3-intent-primary:hover, .bp3-dark .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-primary.bp3-menu-item, .bp3-submenu .bp3-dark .bp3-popover-target.bp3-popover-open > .bp3-intent-primary.bp3-menu-item, .bp3-dark .bp3-menu-item.bp3-intent-primary.bp3-active{ + background-color:#137cbd; } + .bp3-dark .bp3-menu-item.bp3-intent-primary:active{ + background-color:#106ba3; } + .bp3-dark .bp3-menu-item.bp3-intent-primary:hover, .bp3-dark .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-primary.bp3-menu-item, .bp3-submenu .bp3-dark .bp3-popover-target.bp3-popover-open > .bp3-intent-primary.bp3-menu-item, .bp3-dark .bp3-menu-item.bp3-intent-primary:hover::before, .bp3-dark .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-primary.bp3-menu-item::before, .bp3-submenu .bp3-dark .bp3-popover-target.bp3-popover-open > .bp3-intent-primary.bp3-menu-item::before, .bp3-dark .bp3-menu-item.bp3-intent-primary:hover::after, .bp3-dark .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-primary.bp3-menu-item::after, .bp3-submenu .bp3-dark .bp3-popover-target.bp3-popover-open > .bp3-intent-primary.bp3-menu-item::after, + .bp3-dark .bp3-menu-item.bp3-intent-primary:hover .bp3-menu-item-label, + .bp3-dark .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-primary.bp3-menu-item .bp3-menu-item-label, + .bp3-submenu .bp3-dark .bp3-popover-target.bp3-popover-open > .bp3-intent-primary.bp3-menu-item .bp3-menu-item-label, .bp3-dark .bp3-menu-item.bp3-intent-primary:active, .bp3-dark .bp3-menu-item.bp3-intent-primary:active::before, .bp3-dark .bp3-menu-item.bp3-intent-primary:active::after, + .bp3-dark .bp3-menu-item.bp3-intent-primary:active .bp3-menu-item-label, .bp3-dark .bp3-menu-item.bp3-intent-primary.bp3-active, .bp3-dark .bp3-menu-item.bp3-intent-primary.bp3-active::before, .bp3-dark .bp3-menu-item.bp3-intent-primary.bp3-active::after, + .bp3-dark .bp3-menu-item.bp3-intent-primary.bp3-active .bp3-menu-item-label{ + color:#ffffff; } + +.bp3-dark .bp3-menu-item.bp3-intent-success{ + color:#3dcc91; } + .bp3-dark .bp3-menu-item.bp3-intent-success .bp3-icon{ + color:inherit; } + .bp3-dark .bp3-menu-item.bp3-intent-success::before, .bp3-dark .bp3-menu-item.bp3-intent-success::after, + .bp3-dark .bp3-menu-item.bp3-intent-success .bp3-menu-item-label{ + color:#3dcc91; } + .bp3-dark .bp3-menu-item.bp3-intent-success:hover, .bp3-dark .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-success.bp3-menu-item, .bp3-submenu .bp3-dark .bp3-popover-target.bp3-popover-open > .bp3-intent-success.bp3-menu-item, .bp3-dark .bp3-menu-item.bp3-intent-success.bp3-active{ + background-color:#0f9960; } + .bp3-dark .bp3-menu-item.bp3-intent-success:active{ + background-color:#0d8050; } + .bp3-dark .bp3-menu-item.bp3-intent-success:hover, .bp3-dark .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-success.bp3-menu-item, .bp3-submenu .bp3-dark .bp3-popover-target.bp3-popover-open > .bp3-intent-success.bp3-menu-item, .bp3-dark .bp3-menu-item.bp3-intent-success:hover::before, .bp3-dark .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-success.bp3-menu-item::before, .bp3-submenu .bp3-dark .bp3-popover-target.bp3-popover-open > .bp3-intent-success.bp3-menu-item::before, .bp3-dark .bp3-menu-item.bp3-intent-success:hover::after, .bp3-dark .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-success.bp3-menu-item::after, .bp3-submenu .bp3-dark .bp3-popover-target.bp3-popover-open > .bp3-intent-success.bp3-menu-item::after, + .bp3-dark .bp3-menu-item.bp3-intent-success:hover .bp3-menu-item-label, + .bp3-dark .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-success.bp3-menu-item .bp3-menu-item-label, + .bp3-submenu .bp3-dark .bp3-popover-target.bp3-popover-open > .bp3-intent-success.bp3-menu-item .bp3-menu-item-label, .bp3-dark .bp3-menu-item.bp3-intent-success:active, .bp3-dark .bp3-menu-item.bp3-intent-success:active::before, .bp3-dark .bp3-menu-item.bp3-intent-success:active::after, + .bp3-dark .bp3-menu-item.bp3-intent-success:active .bp3-menu-item-label, .bp3-dark .bp3-menu-item.bp3-intent-success.bp3-active, .bp3-dark .bp3-menu-item.bp3-intent-success.bp3-active::before, .bp3-dark .bp3-menu-item.bp3-intent-success.bp3-active::after, + .bp3-dark .bp3-menu-item.bp3-intent-success.bp3-active .bp3-menu-item-label{ + color:#ffffff; } + +.bp3-dark .bp3-menu-item.bp3-intent-warning{ + color:#ffb366; } + .bp3-dark .bp3-menu-item.bp3-intent-warning .bp3-icon{ + color:inherit; } + .bp3-dark .bp3-menu-item.bp3-intent-warning::before, .bp3-dark .bp3-menu-item.bp3-intent-warning::after, + .bp3-dark .bp3-menu-item.bp3-intent-warning .bp3-menu-item-label{ + color:#ffb366; } + .bp3-dark .bp3-menu-item.bp3-intent-warning:hover, .bp3-dark .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-warning.bp3-menu-item, .bp3-submenu .bp3-dark .bp3-popover-target.bp3-popover-open > .bp3-intent-warning.bp3-menu-item, .bp3-dark .bp3-menu-item.bp3-intent-warning.bp3-active{ + background-color:#d9822b; } + .bp3-dark .bp3-menu-item.bp3-intent-warning:active{ + background-color:#bf7326; } + .bp3-dark .bp3-menu-item.bp3-intent-warning:hover, .bp3-dark .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-warning.bp3-menu-item, .bp3-submenu .bp3-dark .bp3-popover-target.bp3-popover-open > .bp3-intent-warning.bp3-menu-item, .bp3-dark .bp3-menu-item.bp3-intent-warning:hover::before, .bp3-dark .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-warning.bp3-menu-item::before, .bp3-submenu .bp3-dark .bp3-popover-target.bp3-popover-open > .bp3-intent-warning.bp3-menu-item::before, .bp3-dark .bp3-menu-item.bp3-intent-warning:hover::after, .bp3-dark .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-warning.bp3-menu-item::after, .bp3-submenu .bp3-dark .bp3-popover-target.bp3-popover-open > .bp3-intent-warning.bp3-menu-item::after, + .bp3-dark .bp3-menu-item.bp3-intent-warning:hover .bp3-menu-item-label, + .bp3-dark .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-warning.bp3-menu-item .bp3-menu-item-label, + .bp3-submenu .bp3-dark .bp3-popover-target.bp3-popover-open > .bp3-intent-warning.bp3-menu-item .bp3-menu-item-label, .bp3-dark .bp3-menu-item.bp3-intent-warning:active, .bp3-dark .bp3-menu-item.bp3-intent-warning:active::before, .bp3-dark .bp3-menu-item.bp3-intent-warning:active::after, + .bp3-dark .bp3-menu-item.bp3-intent-warning:active .bp3-menu-item-label, .bp3-dark .bp3-menu-item.bp3-intent-warning.bp3-active, .bp3-dark .bp3-menu-item.bp3-intent-warning.bp3-active::before, .bp3-dark .bp3-menu-item.bp3-intent-warning.bp3-active::after, + .bp3-dark .bp3-menu-item.bp3-intent-warning.bp3-active .bp3-menu-item-label{ + color:#ffffff; } + +.bp3-dark .bp3-menu-item.bp3-intent-danger{ + color:#ff7373; } + .bp3-dark .bp3-menu-item.bp3-intent-danger .bp3-icon{ + color:inherit; } + .bp3-dark .bp3-menu-item.bp3-intent-danger::before, .bp3-dark .bp3-menu-item.bp3-intent-danger::after, + .bp3-dark .bp3-menu-item.bp3-intent-danger .bp3-menu-item-label{ + color:#ff7373; } + .bp3-dark .bp3-menu-item.bp3-intent-danger:hover, .bp3-dark .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-danger.bp3-menu-item, .bp3-submenu .bp3-dark .bp3-popover-target.bp3-popover-open > .bp3-intent-danger.bp3-menu-item, .bp3-dark .bp3-menu-item.bp3-intent-danger.bp3-active{ + background-color:#db3737; } + .bp3-dark .bp3-menu-item.bp3-intent-danger:active{ + background-color:#c23030; } + .bp3-dark .bp3-menu-item.bp3-intent-danger:hover, .bp3-dark .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-danger.bp3-menu-item, .bp3-submenu .bp3-dark .bp3-popover-target.bp3-popover-open > .bp3-intent-danger.bp3-menu-item, .bp3-dark .bp3-menu-item.bp3-intent-danger:hover::before, .bp3-dark .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-danger.bp3-menu-item::before, .bp3-submenu .bp3-dark .bp3-popover-target.bp3-popover-open > .bp3-intent-danger.bp3-menu-item::before, .bp3-dark .bp3-menu-item.bp3-intent-danger:hover::after, .bp3-dark .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-danger.bp3-menu-item::after, .bp3-submenu .bp3-dark .bp3-popover-target.bp3-popover-open > .bp3-intent-danger.bp3-menu-item::after, + .bp3-dark .bp3-menu-item.bp3-intent-danger:hover .bp3-menu-item-label, + .bp3-dark .bp3-submenu .bp3-popover-target.bp3-popover-open > .bp3-intent-danger.bp3-menu-item .bp3-menu-item-label, + .bp3-submenu .bp3-dark .bp3-popover-target.bp3-popover-open > .bp3-intent-danger.bp3-menu-item .bp3-menu-item-label, .bp3-dark .bp3-menu-item.bp3-intent-danger:active, .bp3-dark .bp3-menu-item.bp3-intent-danger:active::before, .bp3-dark .bp3-menu-item.bp3-intent-danger:active::after, + .bp3-dark .bp3-menu-item.bp3-intent-danger:active .bp3-menu-item-label, .bp3-dark .bp3-menu-item.bp3-intent-danger.bp3-active, .bp3-dark .bp3-menu-item.bp3-intent-danger.bp3-active::before, .bp3-dark .bp3-menu-item.bp3-intent-danger.bp3-active::after, + .bp3-dark .bp3-menu-item.bp3-intent-danger.bp3-active .bp3-menu-item-label{ + color:#ffffff; } + +.bp3-dark .bp3-menu-item::before, +.bp3-dark .bp3-menu-item > .bp3-icon{ + color:#a7b6c2; } + +.bp3-dark .bp3-menu-item .bp3-menu-item-label{ + color:#a7b6c2; } + +.bp3-dark .bp3-menu-item.bp3-active, .bp3-dark .bp3-menu-item:active{ + background-color:rgba(138, 155, 168, 0.3); } + +.bp3-dark .bp3-menu-item.bp3-disabled{ + color:rgba(167, 182, 194, 0.6) !important; } + .bp3-dark .bp3-menu-item.bp3-disabled::before, + .bp3-dark .bp3-menu-item.bp3-disabled > .bp3-icon, + .bp3-dark .bp3-menu-item.bp3-disabled .bp3-menu-item-label{ + color:rgba(167, 182, 194, 0.6) !important; } + +.bp3-dark .bp3-menu-divider, +.bp3-dark .bp3-menu-header{ + border-color:rgba(255, 255, 255, 0.15); } + +.bp3-dark .bp3-menu-header > h6{ + color:#f5f8fa; } + +.bp3-label .bp3-menu{ + margin-top:5px; } +.bp3-navbar{ + position:relative; + z-index:10; + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 0 0 rgba(16, 22, 26, 0), 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 0 0 rgba(16, 22, 26, 0), 0 1px 1px rgba(16, 22, 26, 0.2); + background-color:#ffffff; + width:100%; + height:50px; + padding:0 15px; } + .bp3-navbar.bp3-dark, + .bp3-dark .bp3-navbar{ + background-color:#394b59; } + .bp3-navbar.bp3-dark{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), 0 0 0 rgba(16, 22, 26, 0), 0 1px 1px rgba(16, 22, 26, 0.4); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), 0 0 0 rgba(16, 22, 26, 0), 0 1px 1px rgba(16, 22, 26, 0.4); } + .bp3-dark .bp3-navbar{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 0 0 rgba(16, 22, 26, 0), 0 1px 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 0 0 rgba(16, 22, 26, 0), 0 1px 1px rgba(16, 22, 26, 0.4); } + .bp3-navbar.bp3-fixed-top{ + position:fixed; + top:0; + right:0; + left:0; } + +.bp3-navbar-heading{ + margin-right:15px; + font-size:16px; } + +.bp3-navbar-group{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; + -webkit-box-align:center; + -ms-flex-align:center; + align-items:center; + height:50px; } + .bp3-navbar-group.bp3-align-left{ + float:left; } + .bp3-navbar-group.bp3-align-right{ + float:right; } + +.bp3-navbar-divider{ + margin:0 10px; + border-left:1px solid rgba(16, 22, 26, 0.15); + height:20px; } + .bp3-dark .bp3-navbar-divider{ + border-left-color:rgba(255, 255, 255, 0.15); } +.bp3-non-ideal-state{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; + -webkit-box-orient:vertical; + -webkit-box-direction:normal; + -ms-flex-direction:column; + flex-direction:column; + -webkit-box-align:center; + -ms-flex-align:center; + align-items:center; + -webkit-box-pack:center; + -ms-flex-pack:center; + justify-content:center; + width:100%; + height:100%; + text-align:center; } + .bp3-non-ideal-state > *{ + -webkit-box-flex:0; + -ms-flex-positive:0; + flex-grow:0; + -ms-flex-negative:0; + flex-shrink:0; } + .bp3-non-ideal-state > .bp3-fill{ + -webkit-box-flex:1; + -ms-flex-positive:1; + flex-grow:1; + -ms-flex-negative:1; + flex-shrink:1; } + .bp3-non-ideal-state::before, + .bp3-non-ideal-state > *{ + margin-bottom:20px; } + .bp3-non-ideal-state:empty::before, + .bp3-non-ideal-state > :last-child{ + margin-bottom:0; } + .bp3-non-ideal-state > *{ + max-width:400px; } + +.bp3-non-ideal-state-visual{ + color:rgba(92, 112, 128, 0.6); + font-size:60px; } + .bp3-dark .bp3-non-ideal-state-visual{ + color:rgba(167, 182, 194, 0.6); } + +.bp3-overflow-list{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; + -ms-flex-wrap:nowrap; + flex-wrap:nowrap; + min-width:0; } + +.bp3-overflow-list-spacer{ + -ms-flex-negative:1; + flex-shrink:1; + width:1px; } + +body.bp3-overlay-open{ + overflow:hidden; } + +.bp3-overlay{ + position:static; + top:0; + right:0; + bottom:0; + left:0; + z-index:20; } + .bp3-overlay:not(.bp3-overlay-open){ + pointer-events:none; } + .bp3-overlay.bp3-overlay-container{ + position:fixed; + overflow:hidden; } + .bp3-overlay.bp3-overlay-container.bp3-overlay-inline{ + position:absolute; } + .bp3-overlay.bp3-overlay-scroll-container{ + position:fixed; + overflow:auto; } + .bp3-overlay.bp3-overlay-scroll-container.bp3-overlay-inline{ + position:absolute; } + .bp3-overlay.bp3-overlay-inline{ + display:inline; + overflow:visible; } + +.bp3-overlay-content{ + position:fixed; + z-index:20; } + .bp3-overlay-inline .bp3-overlay-content, + .bp3-overlay-scroll-container .bp3-overlay-content{ + position:absolute; } + +.bp3-overlay-backdrop{ + position:fixed; + top:0; + right:0; + bottom:0; + left:0; + opacity:1; + z-index:20; + background-color:rgba(16, 22, 26, 0.7); + overflow:auto; + -webkit-user-select:none; + -moz-user-select:none; + -ms-user-select:none; + user-select:none; } + .bp3-overlay-backdrop.bp3-overlay-enter, .bp3-overlay-backdrop.bp3-overlay-appear{ + opacity:0; } + .bp3-overlay-backdrop.bp3-overlay-enter-active, .bp3-overlay-backdrop.bp3-overlay-appear-active{ + opacity:1; + -webkit-transition-property:opacity; + transition-property:opacity; + -webkit-transition-duration:200ms; + transition-duration:200ms; + -webkit-transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + -webkit-transition-delay:0; + transition-delay:0; } + .bp3-overlay-backdrop.bp3-overlay-exit{ + opacity:1; } + .bp3-overlay-backdrop.bp3-overlay-exit-active{ + opacity:0; + -webkit-transition-property:opacity; + transition-property:opacity; + -webkit-transition-duration:200ms; + transition-duration:200ms; + -webkit-transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + -webkit-transition-delay:0; + transition-delay:0; } + .bp3-overlay-backdrop:focus{ + outline:none; } + .bp3-overlay-inline .bp3-overlay-backdrop{ + position:absolute; } +.bp3-panel-stack{ + position:relative; + overflow:hidden; } + +.bp3-panel-stack-header{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; + -ms-flex-negative:0; + flex-shrink:0; + -webkit-box-align:center; + -ms-flex-align:center; + align-items:center; + z-index:1; + -webkit-box-shadow:0 1px rgba(16, 22, 26, 0.15); + box-shadow:0 1px rgba(16, 22, 26, 0.15); + height:30px; } + .bp3-dark .bp3-panel-stack-header{ + -webkit-box-shadow:0 1px rgba(255, 255, 255, 0.15); + box-shadow:0 1px rgba(255, 255, 255, 0.15); } + .bp3-panel-stack-header > span{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; + -webkit-box-flex:1; + -ms-flex:1; + flex:1; + -webkit-box-align:stretch; + -ms-flex-align:stretch; + align-items:stretch; } + .bp3-panel-stack-header .bp3-heading{ + margin:0 5px; } + +.bp3-button.bp3-panel-stack-header-back{ + margin-left:5px; + padding-left:0; + white-space:nowrap; } + .bp3-button.bp3-panel-stack-header-back .bp3-icon{ + margin:0 2px; } + +.bp3-panel-stack-view{ + position:absolute; + top:0; + right:0; + bottom:0; + left:0; + display:-webkit-box; + display:-ms-flexbox; + display:flex; + -webkit-box-orient:vertical; + -webkit-box-direction:normal; + -ms-flex-direction:column; + flex-direction:column; + margin-right:-1px; + border-right:1px solid rgba(16, 22, 26, 0.15); + background-color:#ffffff; + overflow-y:auto; } + .bp3-dark .bp3-panel-stack-view{ + background-color:#30404d; } + +.bp3-panel-stack-push .bp3-panel-stack-enter, .bp3-panel-stack-push .bp3-panel-stack-appear{ + -webkit-transform:translateX(100%); + transform:translateX(100%); + opacity:0; } + +.bp3-panel-stack-push .bp3-panel-stack-enter-active, .bp3-panel-stack-push .bp3-panel-stack-appear-active{ + -webkit-transform:translate(0%); + transform:translate(0%); + opacity:1; + -webkit-transition-property:opacity, -webkit-transform; + transition-property:opacity, -webkit-transform; + transition-property:transform, opacity; + transition-property:transform, opacity, -webkit-transform; + -webkit-transition-duration:400ms; + transition-duration:400ms; + -webkit-transition-timing-function:ease; + transition-timing-function:ease; + -webkit-transition-delay:0; + transition-delay:0; } + +.bp3-panel-stack-push .bp3-panel-stack-exit{ + -webkit-transform:translate(0%); + transform:translate(0%); + opacity:1; } + +.bp3-panel-stack-push .bp3-panel-stack-exit-active{ + -webkit-transform:translateX(-50%); + transform:translateX(-50%); + opacity:0; + -webkit-transition-property:opacity, -webkit-transform; + transition-property:opacity, -webkit-transform; + transition-property:transform, opacity; + transition-property:transform, opacity, -webkit-transform; + -webkit-transition-duration:400ms; + transition-duration:400ms; + -webkit-transition-timing-function:ease; + transition-timing-function:ease; + -webkit-transition-delay:0; + transition-delay:0; } + +.bp3-panel-stack-pop .bp3-panel-stack-enter, .bp3-panel-stack-pop .bp3-panel-stack-appear{ + -webkit-transform:translateX(-50%); + transform:translateX(-50%); + opacity:0; } + +.bp3-panel-stack-pop .bp3-panel-stack-enter-active, .bp3-panel-stack-pop .bp3-panel-stack-appear-active{ + -webkit-transform:translate(0%); + transform:translate(0%); + opacity:1; + -webkit-transition-property:opacity, -webkit-transform; + transition-property:opacity, -webkit-transform; + transition-property:transform, opacity; + transition-property:transform, opacity, -webkit-transform; + -webkit-transition-duration:400ms; + transition-duration:400ms; + -webkit-transition-timing-function:ease; + transition-timing-function:ease; + -webkit-transition-delay:0; + transition-delay:0; } + +.bp3-panel-stack-pop .bp3-panel-stack-exit{ + -webkit-transform:translate(0%); + transform:translate(0%); + opacity:1; } + +.bp3-panel-stack-pop .bp3-panel-stack-exit-active{ + -webkit-transform:translateX(100%); + transform:translateX(100%); + opacity:0; + -webkit-transition-property:opacity, -webkit-transform; + transition-property:opacity, -webkit-transform; + transition-property:transform, opacity; + transition-property:transform, opacity, -webkit-transform; + -webkit-transition-duration:400ms; + transition-duration:400ms; + -webkit-transition-timing-function:ease; + transition-timing-function:ease; + -webkit-transition-delay:0; + transition-delay:0; } +.bp3-popover{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 2px 4px rgba(16, 22, 26, 0.2), 0 8px 24px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 2px 4px rgba(16, 22, 26, 0.2), 0 8px 24px rgba(16, 22, 26, 0.2); + -webkit-transform:scale(1); + transform:scale(1); + display:inline-block; + z-index:20; + border-radius:3px; } + .bp3-popover .bp3-popover-arrow{ + position:absolute; + width:30px; + height:30px; } + .bp3-popover .bp3-popover-arrow::before{ + margin:5px; + width:20px; + height:20px; } + .bp3-tether-element-attached-bottom.bp3-tether-target-attached-top > .bp3-popover{ + margin-top:-17px; + margin-bottom:17px; } + .bp3-tether-element-attached-bottom.bp3-tether-target-attached-top > .bp3-popover > .bp3-popover-arrow{ + bottom:-11px; } + .bp3-tether-element-attached-bottom.bp3-tether-target-attached-top > .bp3-popover > .bp3-popover-arrow svg{ + -webkit-transform:rotate(-90deg); + transform:rotate(-90deg); } + .bp3-tether-element-attached-left.bp3-tether-target-attached-right > .bp3-popover{ + margin-left:17px; } + .bp3-tether-element-attached-left.bp3-tether-target-attached-right > .bp3-popover > .bp3-popover-arrow{ + left:-11px; } + .bp3-tether-element-attached-left.bp3-tether-target-attached-right > .bp3-popover > .bp3-popover-arrow svg{ + -webkit-transform:rotate(0); + transform:rotate(0); } + .bp3-tether-element-attached-top.bp3-tether-target-attached-bottom > .bp3-popover{ + margin-top:17px; } + .bp3-tether-element-attached-top.bp3-tether-target-attached-bottom > .bp3-popover > .bp3-popover-arrow{ + top:-11px; } + .bp3-tether-element-attached-top.bp3-tether-target-attached-bottom > .bp3-popover > .bp3-popover-arrow svg{ + -webkit-transform:rotate(90deg); + transform:rotate(90deg); } + .bp3-tether-element-attached-right.bp3-tether-target-attached-left > .bp3-popover{ + margin-right:17px; + margin-left:-17px; } + .bp3-tether-element-attached-right.bp3-tether-target-attached-left > .bp3-popover > .bp3-popover-arrow{ + right:-11px; } + .bp3-tether-element-attached-right.bp3-tether-target-attached-left > .bp3-popover > .bp3-popover-arrow svg{ + -webkit-transform:rotate(180deg); + transform:rotate(180deg); } + .bp3-tether-element-attached-middle > .bp3-popover > .bp3-popover-arrow{ + top:50%; + -webkit-transform:translateY(-50%); + transform:translateY(-50%); } + .bp3-tether-element-attached-center > .bp3-popover > .bp3-popover-arrow{ + right:50%; + -webkit-transform:translateX(50%); + transform:translateX(50%); } + .bp3-tether-element-attached-top.bp3-tether-target-attached-top > .bp3-popover > .bp3-popover-arrow{ + top:-0.3934px; } + .bp3-tether-element-attached-right.bp3-tether-target-attached-right > .bp3-popover > .bp3-popover-arrow{ + right:-0.3934px; } + .bp3-tether-element-attached-left.bp3-tether-target-attached-left > .bp3-popover > .bp3-popover-arrow{ + left:-0.3934px; } + .bp3-tether-element-attached-bottom.bp3-tether-target-attached-bottom > .bp3-popover > .bp3-popover-arrow{ + bottom:-0.3934px; } + .bp3-tether-element-attached-top.bp3-tether-element-attached-left > .bp3-popover{ + -webkit-transform-origin:top left; + transform-origin:top left; } + .bp3-tether-element-attached-top.bp3-tether-element-attached-center > .bp3-popover{ + -webkit-transform-origin:top center; + transform-origin:top center; } + .bp3-tether-element-attached-top.bp3-tether-element-attached-right > .bp3-popover{ + -webkit-transform-origin:top right; + transform-origin:top right; } + .bp3-tether-element-attached-middle.bp3-tether-element-attached-left > .bp3-popover{ + -webkit-transform-origin:center left; + transform-origin:center left; } + .bp3-tether-element-attached-middle.bp3-tether-element-attached-center > .bp3-popover{ + -webkit-transform-origin:center center; + transform-origin:center center; } + .bp3-tether-element-attached-middle.bp3-tether-element-attached-right > .bp3-popover{ + -webkit-transform-origin:center right; + transform-origin:center right; } + .bp3-tether-element-attached-bottom.bp3-tether-element-attached-left > .bp3-popover{ + -webkit-transform-origin:bottom left; + transform-origin:bottom left; } + .bp3-tether-element-attached-bottom.bp3-tether-element-attached-center > .bp3-popover{ + -webkit-transform-origin:bottom center; + transform-origin:bottom center; } + .bp3-tether-element-attached-bottom.bp3-tether-element-attached-right > .bp3-popover{ + -webkit-transform-origin:bottom right; + transform-origin:bottom right; } + .bp3-popover .bp3-popover-content{ + background:#ffffff; + color:inherit; } + .bp3-popover .bp3-popover-arrow::before{ + -webkit-box-shadow:1px 1px 6px rgba(16, 22, 26, 0.2); + box-shadow:1px 1px 6px rgba(16, 22, 26, 0.2); } + .bp3-popover .bp3-popover-arrow-border{ + fill:#10161a; + fill-opacity:0.1; } + .bp3-popover .bp3-popover-arrow-fill{ + fill:#ffffff; } + .bp3-popover-enter > .bp3-popover, .bp3-popover-appear > .bp3-popover{ + -webkit-transform:scale(0.3); + transform:scale(0.3); } + .bp3-popover-enter-active > .bp3-popover, .bp3-popover-appear-active > .bp3-popover{ + -webkit-transform:scale(1); + transform:scale(1); + -webkit-transition-property:-webkit-transform; + transition-property:-webkit-transform; + transition-property:transform; + transition-property:transform, -webkit-transform; + -webkit-transition-duration:300ms; + transition-duration:300ms; + -webkit-transition-timing-function:cubic-bezier(0.54, 1.12, 0.38, 1.11); + transition-timing-function:cubic-bezier(0.54, 1.12, 0.38, 1.11); + -webkit-transition-delay:0; + transition-delay:0; } + .bp3-popover-exit > .bp3-popover{ + -webkit-transform:scale(1); + transform:scale(1); } + .bp3-popover-exit-active > .bp3-popover{ + -webkit-transform:scale(0.3); + transform:scale(0.3); + -webkit-transition-property:-webkit-transform; + transition-property:-webkit-transform; + transition-property:transform; + transition-property:transform, -webkit-transform; + -webkit-transition-duration:300ms; + transition-duration:300ms; + -webkit-transition-timing-function:cubic-bezier(0.54, 1.12, 0.38, 1.11); + transition-timing-function:cubic-bezier(0.54, 1.12, 0.38, 1.11); + -webkit-transition-delay:0; + transition-delay:0; } + .bp3-popover .bp3-popover-content{ + position:relative; + border-radius:3px; } + .bp3-popover.bp3-popover-content-sizing .bp3-popover-content{ + max-width:350px; + padding:20px; } + .bp3-popover-target + .bp3-overlay .bp3-popover.bp3-popover-content-sizing{ + width:350px; } + .bp3-popover.bp3-minimal{ + margin:0 !important; } + .bp3-popover.bp3-minimal .bp3-popover-arrow{ + display:none; } + .bp3-popover.bp3-minimal.bp3-popover{ + -webkit-transform:scale(1); + transform:scale(1); } + .bp3-popover-enter > .bp3-popover.bp3-minimal.bp3-popover, .bp3-popover-appear > .bp3-popover.bp3-minimal.bp3-popover{ + -webkit-transform:scale(1); + transform:scale(1); } + .bp3-popover-enter-active > .bp3-popover.bp3-minimal.bp3-popover, .bp3-popover-appear-active > .bp3-popover.bp3-minimal.bp3-popover{ + -webkit-transform:scale(1); + transform:scale(1); + -webkit-transition-property:-webkit-transform; + transition-property:-webkit-transform; + transition-property:transform; + transition-property:transform, -webkit-transform; + -webkit-transition-duration:100ms; + transition-duration:100ms; + -webkit-transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + -webkit-transition-delay:0; + transition-delay:0; } + .bp3-popover-exit > .bp3-popover.bp3-minimal.bp3-popover{ + -webkit-transform:scale(1); + transform:scale(1); } + .bp3-popover-exit-active > .bp3-popover.bp3-minimal.bp3-popover{ + -webkit-transform:scale(1); + transform:scale(1); + -webkit-transition-property:-webkit-transform; + transition-property:-webkit-transform; + transition-property:transform; + transition-property:transform, -webkit-transform; + -webkit-transition-duration:100ms; + transition-duration:100ms; + -webkit-transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + -webkit-transition-delay:0; + transition-delay:0; } + .bp3-popover.bp3-dark, + .bp3-dark .bp3-popover{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 2px 4px rgba(16, 22, 26, 0.4), 0 8px 24px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 2px 4px rgba(16, 22, 26, 0.4), 0 8px 24px rgba(16, 22, 26, 0.4); } + .bp3-popover.bp3-dark .bp3-popover-content, + .bp3-dark .bp3-popover .bp3-popover-content{ + background:#30404d; + color:inherit; } + .bp3-popover.bp3-dark .bp3-popover-arrow::before, + .bp3-dark .bp3-popover .bp3-popover-arrow::before{ + -webkit-box-shadow:1px 1px 6px rgba(16, 22, 26, 0.4); + box-shadow:1px 1px 6px rgba(16, 22, 26, 0.4); } + .bp3-popover.bp3-dark .bp3-popover-arrow-border, + .bp3-dark .bp3-popover .bp3-popover-arrow-border{ + fill:#10161a; + fill-opacity:0.2; } + .bp3-popover.bp3-dark .bp3-popover-arrow-fill, + .bp3-dark .bp3-popover .bp3-popover-arrow-fill{ + fill:#30404d; } + +.bp3-popover-arrow::before{ + display:block; + position:absolute; + -webkit-transform:rotate(45deg); + transform:rotate(45deg); + border-radius:2px; + content:""; } + +.bp3-tether-pinned .bp3-popover-arrow{ + display:none; } + +.bp3-popover-backdrop{ + background:rgba(255, 255, 255, 0); } + +.bp3-transition-container{ + opacity:1; + display:-webkit-box; + display:-ms-flexbox; + display:flex; + z-index:20; } + .bp3-transition-container.bp3-popover-enter, .bp3-transition-container.bp3-popover-appear{ + opacity:0; } + .bp3-transition-container.bp3-popover-enter-active, .bp3-transition-container.bp3-popover-appear-active{ + opacity:1; + -webkit-transition-property:opacity; + transition-property:opacity; + -webkit-transition-duration:100ms; + transition-duration:100ms; + -webkit-transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + -webkit-transition-delay:0; + transition-delay:0; } + .bp3-transition-container.bp3-popover-exit{ + opacity:1; } + .bp3-transition-container.bp3-popover-exit-active{ + opacity:0; + -webkit-transition-property:opacity; + transition-property:opacity; + -webkit-transition-duration:100ms; + transition-duration:100ms; + -webkit-transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + -webkit-transition-delay:0; + transition-delay:0; } + .bp3-transition-container:focus{ + outline:none; } + .bp3-transition-container.bp3-popover-leave .bp3-popover-content{ + pointer-events:none; } + .bp3-transition-container[data-x-out-of-boundaries]{ + display:none; } + +span.bp3-popover-target{ + display:inline-block; } + +.bp3-popover-wrapper.bp3-fill{ + width:100%; } + +.bp3-portal{ + position:absolute; + top:0; + right:0; + left:0; } +@-webkit-keyframes linear-progress-bar-stripes{ + from{ + background-position:0 0; } + to{ + background-position:30px 0; } } +@keyframes linear-progress-bar-stripes{ + from{ + background-position:0 0; } + to{ + background-position:30px 0; } } + +.bp3-progress-bar{ + display:block; + position:relative; + border-radius:40px; + background:rgba(92, 112, 128, 0.2); + width:100%; + height:8px; + overflow:hidden; } + .bp3-progress-bar .bp3-progress-meter{ + position:absolute; + border-radius:40px; + background:linear-gradient(-45deg, rgba(255, 255, 255, 0.2) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.2) 50%, rgba(255, 255, 255, 0.2) 75%, transparent 75%); + background-color:rgba(92, 112, 128, 0.8); + background-size:30px 30px; + width:100%; + height:100%; + -webkit-transition:width 200ms cubic-bezier(0.4, 1, 0.75, 0.9); + transition:width 200ms cubic-bezier(0.4, 1, 0.75, 0.9); } + .bp3-progress-bar:not(.bp3-no-animation):not(.bp3-no-stripes) .bp3-progress-meter{ + animation:linear-progress-bar-stripes 300ms linear infinite reverse; } + .bp3-progress-bar.bp3-no-stripes .bp3-progress-meter{ + background-image:none; } + +.bp3-dark .bp3-progress-bar{ + background:rgba(16, 22, 26, 0.5); } + .bp3-dark .bp3-progress-bar .bp3-progress-meter{ + background-color:#8a9ba8; } + +.bp3-progress-bar.bp3-intent-primary .bp3-progress-meter{ + background-color:#137cbd; } + +.bp3-progress-bar.bp3-intent-success .bp3-progress-meter{ + background-color:#0f9960; } + +.bp3-progress-bar.bp3-intent-warning .bp3-progress-meter{ + background-color:#d9822b; } + +.bp3-progress-bar.bp3-intent-danger .bp3-progress-meter{ + background-color:#db3737; } +@-webkit-keyframes skeleton-glow{ + from{ + border-color:rgba(206, 217, 224, 0.2); + background:rgba(206, 217, 224, 0.2); } + to{ + border-color:rgba(92, 112, 128, 0.2); + background:rgba(92, 112, 128, 0.2); } } +@keyframes skeleton-glow{ + from{ + border-color:rgba(206, 217, 224, 0.2); + background:rgba(206, 217, 224, 0.2); } + to{ + border-color:rgba(92, 112, 128, 0.2); + background:rgba(92, 112, 128, 0.2); } } +.bp3-skeleton{ + border-color:rgba(206, 217, 224, 0.2) !important; + border-radius:2px; + -webkit-box-shadow:none !important; + box-shadow:none !important; + background:rgba(206, 217, 224, 0.2); + background-clip:padding-box !important; + cursor:default; + color:transparent !important; + -webkit-animation:1000ms linear infinite alternate skeleton-glow; + animation:1000ms linear infinite alternate skeleton-glow; + pointer-events:none; + -webkit-user-select:none; + -moz-user-select:none; + -ms-user-select:none; + user-select:none; } + .bp3-skeleton::before, .bp3-skeleton::after, + .bp3-skeleton *{ + visibility:hidden !important; } +.bp3-slider{ + width:100%; + min-width:150px; + height:40px; + position:relative; + outline:none; + cursor:default; + -webkit-user-select:none; + -moz-user-select:none; + -ms-user-select:none; + user-select:none; } + .bp3-slider:hover{ + cursor:pointer; } + .bp3-slider:active{ + cursor:-webkit-grabbing; + cursor:grabbing; } + .bp3-slider.bp3-disabled{ + opacity:0.5; + cursor:not-allowed; } + .bp3-slider.bp3-slider-unlabeled{ + height:16px; } + +.bp3-slider-track, +.bp3-slider-progress{ + top:5px; + right:0; + left:0; + height:6px; + position:absolute; } + +.bp3-slider-track{ + border-radius:3px; + overflow:hidden; } + +.bp3-slider-progress{ + background:rgba(92, 112, 128, 0.2); } + .bp3-dark .bp3-slider-progress{ + background:rgba(16, 22, 26, 0.5); } + .bp3-slider-progress.bp3-intent-primary{ + background-color:#137cbd; } + .bp3-slider-progress.bp3-intent-success{ + background-color:#0f9960; } + .bp3-slider-progress.bp3-intent-warning{ + background-color:#d9822b; } + .bp3-slider-progress.bp3-intent-danger{ + background-color:#db3737; } + +.bp3-slider-handle{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 -1px 0 rgba(16, 22, 26, 0.1); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 -1px 0 rgba(16, 22, 26, 0.1); + background-color:#f5f8fa; + background-image:-webkit-gradient(linear, left top, left bottom, from(rgba(255, 255, 255, 0.8)), to(rgba(255, 255, 255, 0))); + background-image:linear-gradient(to bottom, rgba(255, 255, 255, 0.8), rgba(255, 255, 255, 0)); + color:#182026; + position:absolute; + top:0; + left:0; + border-radius:3px; + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 1px 1px rgba(16, 22, 26, 0.2); + cursor:pointer; + width:16px; + height:16px; } + .bp3-slider-handle:hover{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 -1px 0 rgba(16, 22, 26, 0.1); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 -1px 0 rgba(16, 22, 26, 0.1); + background-clip:padding-box; + background-color:#ebf1f5; } + .bp3-slider-handle:active, .bp3-slider-handle.bp3-active{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 1px 2px rgba(16, 22, 26, 0.2); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 1px 2px rgba(16, 22, 26, 0.2); + background-color:#d8e1e8; + background-image:none; } + .bp3-slider-handle:disabled, .bp3-slider-handle.bp3-disabled{ + outline:none; + -webkit-box-shadow:none; + box-shadow:none; + background-color:rgba(206, 217, 224, 0.5); + background-image:none; + cursor:not-allowed; + color:rgba(92, 112, 128, 0.6); } + .bp3-slider-handle:disabled.bp3-active, .bp3-slider-handle:disabled.bp3-active:hover, .bp3-slider-handle.bp3-disabled.bp3-active, .bp3-slider-handle.bp3-disabled.bp3-active:hover{ + background:rgba(206, 217, 224, 0.7); } + .bp3-slider-handle:focus{ + z-index:1; } + .bp3-slider-handle:hover{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 -1px 0 rgba(16, 22, 26, 0.1); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 -1px 0 rgba(16, 22, 26, 0.1); + background-clip:padding-box; + background-color:#ebf1f5; + z-index:2; + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 1px 1px rgba(16, 22, 26, 0.2); + cursor:-webkit-grab; + cursor:grab; } + .bp3-slider-handle.bp3-active{ + -webkit-box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 1px 2px rgba(16, 22, 26, 0.2); + box-shadow:inset 0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 1px 2px rgba(16, 22, 26, 0.2); + background-color:#d8e1e8; + background-image:none; + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 1px 1px rgba(16, 22, 26, 0.1); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), inset 0 1px 1px rgba(16, 22, 26, 0.1); + cursor:-webkit-grabbing; + cursor:grabbing; } + .bp3-disabled .bp3-slider-handle{ + -webkit-box-shadow:none; + box-shadow:none; + background:#bfccd6; + pointer-events:none; } + .bp3-dark .bp3-slider-handle{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + background-color:#394b59; + background-image:-webkit-gradient(linear, left top, left bottom, from(rgba(255, 255, 255, 0.05)), to(rgba(255, 255, 255, 0))); + background-image:linear-gradient(to bottom, rgba(255, 255, 255, 0.05), rgba(255, 255, 255, 0)); + color:#f5f8fa; } + .bp3-dark .bp3-slider-handle:hover, .bp3-dark .bp3-slider-handle:active, .bp3-dark .bp3-slider-handle.bp3-active{ + color:#f5f8fa; } + .bp3-dark .bp3-slider-handle:hover{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.4); + background-color:#30404d; } + .bp3-dark .bp3-slider-handle:active, .bp3-dark .bp3-slider-handle.bp3-active{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.6), inset 0 1px 2px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.6), inset 0 1px 2px rgba(16, 22, 26, 0.2); + background-color:#202b33; + background-image:none; } + .bp3-dark .bp3-slider-handle:disabled, .bp3-dark .bp3-slider-handle.bp3-disabled{ + -webkit-box-shadow:none; + box-shadow:none; + background-color:rgba(57, 75, 89, 0.5); + background-image:none; + color:rgba(167, 182, 194, 0.6); } + .bp3-dark .bp3-slider-handle:disabled.bp3-active, .bp3-dark .bp3-slider-handle.bp3-disabled.bp3-active{ + background:rgba(57, 75, 89, 0.7); } + .bp3-dark .bp3-slider-handle .bp3-button-spinner .bp3-spinner-head{ + background:rgba(16, 22, 26, 0.5); + stroke:#8a9ba8; } + .bp3-dark .bp3-slider-handle, .bp3-dark .bp3-slider-handle:hover{ + background-color:#394b59; } + .bp3-dark .bp3-slider-handle.bp3-active{ + background-color:#293742; } + .bp3-dark .bp3-disabled .bp3-slider-handle{ + border-color:#5c7080; + -webkit-box-shadow:none; + box-shadow:none; + background:#5c7080; } + .bp3-slider-handle .bp3-slider-label{ + margin-left:8px; + border-radius:3px; + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 2px 4px rgba(16, 22, 26, 0.2), 0 8px 24px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 2px 4px rgba(16, 22, 26, 0.2), 0 8px 24px rgba(16, 22, 26, 0.2); + background:#394b59; + color:#f5f8fa; } + .bp3-dark .bp3-slider-handle .bp3-slider-label{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 2px 4px rgba(16, 22, 26, 0.4), 0 8px 24px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 2px 4px rgba(16, 22, 26, 0.4), 0 8px 24px rgba(16, 22, 26, 0.4); + background:#e1e8ed; + color:#394b59; } + .bp3-disabled .bp3-slider-handle .bp3-slider-label{ + -webkit-box-shadow:none; + box-shadow:none; } + .bp3-slider-handle.bp3-start, .bp3-slider-handle.bp3-end{ + width:8px; } + .bp3-slider-handle.bp3-start{ + border-top-right-radius:0; + border-bottom-right-radius:0; } + .bp3-slider-handle.bp3-end{ + margin-left:8px; + border-top-left-radius:0; + border-bottom-left-radius:0; } + .bp3-slider-handle.bp3-end .bp3-slider-label{ + margin-left:0; } + +.bp3-slider-label{ + -webkit-transform:translate(-50%, 20px); + transform:translate(-50%, 20px); + display:inline-block; + position:absolute; + padding:2px 5px; + vertical-align:top; + line-height:1; + font-size:12px; } + +.bp3-slider.bp3-vertical{ + width:40px; + min-width:40px; + height:150px; } + .bp3-slider.bp3-vertical .bp3-slider-track, + .bp3-slider.bp3-vertical .bp3-slider-progress{ + top:0; + bottom:0; + left:5px; + width:6px; + height:auto; } + .bp3-slider.bp3-vertical .bp3-slider-progress{ + top:auto; } + .bp3-slider.bp3-vertical .bp3-slider-label{ + -webkit-transform:translate(20px, 50%); + transform:translate(20px, 50%); } + .bp3-slider.bp3-vertical .bp3-slider-handle{ + top:auto; } + .bp3-slider.bp3-vertical .bp3-slider-handle .bp3-slider-label{ + margin-top:-8px; + margin-left:0; } + .bp3-slider.bp3-vertical .bp3-slider-handle.bp3-end, .bp3-slider.bp3-vertical .bp3-slider-handle.bp3-start{ + margin-left:0; + width:16px; + height:8px; } + .bp3-slider.bp3-vertical .bp3-slider-handle.bp3-start{ + border-top-left-radius:0; + border-bottom-right-radius:3px; } + .bp3-slider.bp3-vertical .bp3-slider-handle.bp3-start .bp3-slider-label{ + -webkit-transform:translate(20px); + transform:translate(20px); } + .bp3-slider.bp3-vertical .bp3-slider-handle.bp3-end{ + margin-bottom:8px; + border-top-left-radius:3px; + border-bottom-left-radius:0; + border-bottom-right-radius:0; } + +@-webkit-keyframes pt-spinner-animation{ + from{ + -webkit-transform:rotate(0deg); + transform:rotate(0deg); } + to{ + -webkit-transform:rotate(360deg); + transform:rotate(360deg); } } + +@keyframes pt-spinner-animation{ + from{ + -webkit-transform:rotate(0deg); + transform:rotate(0deg); } + to{ + -webkit-transform:rotate(360deg); + transform:rotate(360deg); } } + +.bp3-spinner{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; + -webkit-box-align:center; + -ms-flex-align:center; + align-items:center; + -webkit-box-pack:center; + -ms-flex-pack:center; + justify-content:center; + overflow:visible; + vertical-align:middle; } + .bp3-spinner svg{ + display:block; } + .bp3-spinner path{ + fill-opacity:0; } + .bp3-spinner .bp3-spinner-head{ + -webkit-transform-origin:center; + transform-origin:center; + -webkit-transition:stroke-dashoffset 200ms cubic-bezier(0.4, 1, 0.75, 0.9); + transition:stroke-dashoffset 200ms cubic-bezier(0.4, 1, 0.75, 0.9); + stroke:rgba(92, 112, 128, 0.8); + stroke-linecap:round; } + .bp3-spinner .bp3-spinner-track{ + stroke:rgba(92, 112, 128, 0.2); } + +.bp3-spinner-animation{ + -webkit-animation:pt-spinner-animation 500ms linear infinite; + animation:pt-spinner-animation 500ms linear infinite; } + .bp3-no-spin > .bp3-spinner-animation{ + -webkit-animation:none; + animation:none; } + +.bp3-dark .bp3-spinner .bp3-spinner-head{ + stroke:#8a9ba8; } + +.bp3-dark .bp3-spinner .bp3-spinner-track{ + stroke:rgba(16, 22, 26, 0.5); } + +.bp3-spinner.bp3-intent-primary .bp3-spinner-head{ + stroke:#137cbd; } + +.bp3-spinner.bp3-intent-success .bp3-spinner-head{ + stroke:#0f9960; } + +.bp3-spinner.bp3-intent-warning .bp3-spinner-head{ + stroke:#d9822b; } + +.bp3-spinner.bp3-intent-danger .bp3-spinner-head{ + stroke:#db3737; } +.bp3-tabs.bp3-vertical{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; } + .bp3-tabs.bp3-vertical > .bp3-tab-list{ + -webkit-box-orient:vertical; + -webkit-box-direction:normal; + -ms-flex-direction:column; + flex-direction:column; + -webkit-box-align:start; + -ms-flex-align:start; + align-items:flex-start; } + .bp3-tabs.bp3-vertical > .bp3-tab-list .bp3-tab{ + border-radius:3px; + width:100%; + padding:0 10px; } + .bp3-tabs.bp3-vertical > .bp3-tab-list .bp3-tab[aria-selected="true"]{ + -webkit-box-shadow:none; + box-shadow:none; + background-color:rgba(19, 124, 189, 0.2); } + .bp3-tabs.bp3-vertical > .bp3-tab-list .bp3-tab-indicator-wrapper .bp3-tab-indicator{ + top:0; + right:0; + bottom:0; + left:0; + border-radius:3px; + background-color:rgba(19, 124, 189, 0.2); + height:auto; } + .bp3-tabs.bp3-vertical > .bp3-tab-panel{ + margin-top:0; + padding-left:20px; } + +.bp3-tab-list{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; + -webkit-box-flex:0; + -ms-flex:0 0 auto; + flex:0 0 auto; + -webkit-box-align:end; + -ms-flex-align:end; + align-items:flex-end; + position:relative; + margin:0; + border:none; + padding:0; + list-style:none; } + .bp3-tab-list > *:not(:last-child){ + margin-right:20px; } + +.bp3-tab{ + overflow:hidden; + text-overflow:ellipsis; + white-space:nowrap; + word-wrap:normal; + -webkit-box-flex:0; + -ms-flex:0 0 auto; + flex:0 0 auto; + position:relative; + cursor:pointer; + max-width:100%; + vertical-align:top; + line-height:30px; + color:#182026; + font-size:14px; } + .bp3-tab a{ + display:block; + text-decoration:none; + color:inherit; } + .bp3-tab-indicator-wrapper ~ .bp3-tab{ + -webkit-box-shadow:none !important; + box-shadow:none !important; + background-color:transparent !important; } + .bp3-tab[aria-disabled="true"]{ + cursor:not-allowed; + color:rgba(92, 112, 128, 0.6); } + .bp3-tab[aria-selected="true"]{ + border-radius:0; + -webkit-box-shadow:inset 0 -3px 0 #106ba3; + box-shadow:inset 0 -3px 0 #106ba3; } + .bp3-tab[aria-selected="true"], .bp3-tab:not([aria-disabled="true"]):hover{ + color:#106ba3; } + .bp3-tab:focus{ + -moz-outline-radius:0; } + .bp3-large > .bp3-tab{ + line-height:40px; + font-size:16px; } + +.bp3-tab-panel{ + margin-top:20px; } + .bp3-tab-panel[aria-hidden="true"]{ + display:none; } + +.bp3-tab-indicator-wrapper{ + position:absolute; + top:0; + left:0; + -webkit-transform:translateX(0), translateY(0); + transform:translateX(0), translateY(0); + -webkit-transition:height, width, -webkit-transform; + transition:height, width, -webkit-transform; + transition:height, transform, width; + transition:height, transform, width, -webkit-transform; + -webkit-transition-duration:200ms; + transition-duration:200ms; + -webkit-transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + pointer-events:none; } + .bp3-tab-indicator-wrapper .bp3-tab-indicator{ + position:absolute; + right:0; + bottom:0; + left:0; + background-color:#106ba3; + height:3px; } + .bp3-tab-indicator-wrapper.bp3-no-animation{ + -webkit-transition:none; + transition:none; } + +.bp3-dark .bp3-tab{ + color:#f5f8fa; } + .bp3-dark .bp3-tab[aria-disabled="true"]{ + color:rgba(167, 182, 194, 0.6); } + .bp3-dark .bp3-tab[aria-selected="true"]{ + -webkit-box-shadow:inset 0 -3px 0 #48aff0; + box-shadow:inset 0 -3px 0 #48aff0; } + .bp3-dark .bp3-tab[aria-selected="true"], .bp3-dark .bp3-tab:not([aria-disabled="true"]):hover{ + color:#48aff0; } + +.bp3-dark .bp3-tab-indicator{ + background-color:#48aff0; } + +.bp3-flex-expander{ + -webkit-box-flex:1; + -ms-flex:1 1; + flex:1 1; } +.bp3-tag{ + display:-webkit-inline-box; + display:-ms-inline-flexbox; + display:inline-flex; + -webkit-box-orient:horizontal; + -webkit-box-direction:normal; + -ms-flex-direction:row; + flex-direction:row; + -webkit-box-align:center; + -ms-flex-align:center; + align-items:center; + position:relative; + border:none; + border-radius:3px; + -webkit-box-shadow:none; + box-shadow:none; + background-color:#5c7080; + min-width:20px; + max-width:100%; + min-height:20px; + padding:2px 6px; + line-height:16px; + color:#f5f8fa; + font-size:12px; } + .bp3-tag.bp3-interactive{ + cursor:pointer; } + .bp3-tag.bp3-interactive:hover{ + background-color:rgba(92, 112, 128, 0.85); } + .bp3-tag.bp3-interactive.bp3-active, .bp3-tag.bp3-interactive:active{ + background-color:rgba(92, 112, 128, 0.7); } + .bp3-tag > *{ + -webkit-box-flex:0; + -ms-flex-positive:0; + flex-grow:0; + -ms-flex-negative:0; + flex-shrink:0; } + .bp3-tag > .bp3-fill{ + -webkit-box-flex:1; + -ms-flex-positive:1; + flex-grow:1; + -ms-flex-negative:1; + flex-shrink:1; } + .bp3-tag::before, + .bp3-tag > *{ + margin-right:4px; } + .bp3-tag:empty::before, + .bp3-tag > :last-child{ + margin-right:0; } + .bp3-tag:focus{ + outline:rgba(19, 124, 189, 0.6) auto 2px; + outline-offset:0; + -moz-outline-radius:6px; } + .bp3-tag.bp3-round{ + border-radius:30px; + padding-right:8px; + padding-left:8px; } + .bp3-dark .bp3-tag{ + background-color:#bfccd6; + color:#182026; } + .bp3-dark .bp3-tag.bp3-interactive{ + cursor:pointer; } + .bp3-dark .bp3-tag.bp3-interactive:hover{ + background-color:rgba(191, 204, 214, 0.85); } + .bp3-dark .bp3-tag.bp3-interactive.bp3-active, .bp3-dark .bp3-tag.bp3-interactive:active{ + background-color:rgba(191, 204, 214, 0.7); } + .bp3-dark .bp3-tag > .bp3-icon, .bp3-dark .bp3-tag .bp3-icon-standard, .bp3-dark .bp3-tag .bp3-icon-large{ + fill:currentColor; } + .bp3-tag > .bp3-icon, .bp3-tag .bp3-icon-standard, .bp3-tag .bp3-icon-large{ + fill:#ffffff; } + .bp3-tag.bp3-large, + .bp3-large .bp3-tag{ + min-width:30px; + min-height:30px; + padding:0 10px; + line-height:20px; + font-size:14px; } + .bp3-tag.bp3-large::before, + .bp3-tag.bp3-large > *, + .bp3-large .bp3-tag::before, + .bp3-large .bp3-tag > *{ + margin-right:7px; } + .bp3-tag.bp3-large:empty::before, + .bp3-tag.bp3-large > :last-child, + .bp3-large .bp3-tag:empty::before, + .bp3-large .bp3-tag > :last-child{ + margin-right:0; } + .bp3-tag.bp3-large.bp3-round, + .bp3-large .bp3-tag.bp3-round{ + padding-right:12px; + padding-left:12px; } + .bp3-tag.bp3-intent-primary{ + background:#137cbd; + color:#ffffff; } + .bp3-tag.bp3-intent-primary.bp3-interactive{ + cursor:pointer; } + .bp3-tag.bp3-intent-primary.bp3-interactive:hover{ + background-color:rgba(19, 124, 189, 0.85); } + .bp3-tag.bp3-intent-primary.bp3-interactive.bp3-active, .bp3-tag.bp3-intent-primary.bp3-interactive:active{ + background-color:rgba(19, 124, 189, 0.7); } + .bp3-tag.bp3-intent-success{ + background:#0f9960; + color:#ffffff; } + .bp3-tag.bp3-intent-success.bp3-interactive{ + cursor:pointer; } + .bp3-tag.bp3-intent-success.bp3-interactive:hover{ + background-color:rgba(15, 153, 96, 0.85); } + .bp3-tag.bp3-intent-success.bp3-interactive.bp3-active, .bp3-tag.bp3-intent-success.bp3-interactive:active{ + background-color:rgba(15, 153, 96, 0.7); } + .bp3-tag.bp3-intent-warning{ + background:#d9822b; + color:#ffffff; } + .bp3-tag.bp3-intent-warning.bp3-interactive{ + cursor:pointer; } + .bp3-tag.bp3-intent-warning.bp3-interactive:hover{ + background-color:rgba(217, 130, 43, 0.85); } + .bp3-tag.bp3-intent-warning.bp3-interactive.bp3-active, .bp3-tag.bp3-intent-warning.bp3-interactive:active{ + background-color:rgba(217, 130, 43, 0.7); } + .bp3-tag.bp3-intent-danger{ + background:#db3737; + color:#ffffff; } + .bp3-tag.bp3-intent-danger.bp3-interactive{ + cursor:pointer; } + .bp3-tag.bp3-intent-danger.bp3-interactive:hover{ + background-color:rgba(219, 55, 55, 0.85); } + .bp3-tag.bp3-intent-danger.bp3-interactive.bp3-active, .bp3-tag.bp3-intent-danger.bp3-interactive:active{ + background-color:rgba(219, 55, 55, 0.7); } + .bp3-tag.bp3-fill{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; + width:100%; } + .bp3-tag.bp3-minimal > .bp3-icon, .bp3-tag.bp3-minimal .bp3-icon-standard, .bp3-tag.bp3-minimal .bp3-icon-large{ + fill:#5c7080; } + .bp3-tag.bp3-minimal:not([class*="bp3-intent-"]){ + background-color:rgba(138, 155, 168, 0.2); + color:#182026; } + .bp3-tag.bp3-minimal:not([class*="bp3-intent-"]).bp3-interactive{ + cursor:pointer; } + .bp3-tag.bp3-minimal:not([class*="bp3-intent-"]).bp3-interactive:hover{ + background-color:rgba(92, 112, 128, 0.3); } + .bp3-tag.bp3-minimal:not([class*="bp3-intent-"]).bp3-interactive.bp3-active, .bp3-tag.bp3-minimal:not([class*="bp3-intent-"]).bp3-interactive:active{ + background-color:rgba(92, 112, 128, 0.4); } + .bp3-dark .bp3-tag.bp3-minimal:not([class*="bp3-intent-"]){ + color:#f5f8fa; } + .bp3-dark .bp3-tag.bp3-minimal:not([class*="bp3-intent-"]).bp3-interactive{ + cursor:pointer; } + .bp3-dark .bp3-tag.bp3-minimal:not([class*="bp3-intent-"]).bp3-interactive:hover{ + background-color:rgba(191, 204, 214, 0.3); } + .bp3-dark .bp3-tag.bp3-minimal:not([class*="bp3-intent-"]).bp3-interactive.bp3-active, .bp3-dark .bp3-tag.bp3-minimal:not([class*="bp3-intent-"]).bp3-interactive:active{ + background-color:rgba(191, 204, 214, 0.4); } + .bp3-dark .bp3-tag.bp3-minimal:not([class*="bp3-intent-"]) > .bp3-icon, .bp3-dark .bp3-tag.bp3-minimal:not([class*="bp3-intent-"]) .bp3-icon-standard, .bp3-dark .bp3-tag.bp3-minimal:not([class*="bp3-intent-"]) .bp3-icon-large{ + fill:#a7b6c2; } + .bp3-tag.bp3-minimal.bp3-intent-primary{ + background-color:rgba(19, 124, 189, 0.15); + color:#106ba3; } + .bp3-tag.bp3-minimal.bp3-intent-primary.bp3-interactive{ + cursor:pointer; } + .bp3-tag.bp3-minimal.bp3-intent-primary.bp3-interactive:hover{ + background-color:rgba(19, 124, 189, 0.25); } + .bp3-tag.bp3-minimal.bp3-intent-primary.bp3-interactive.bp3-active, .bp3-tag.bp3-minimal.bp3-intent-primary.bp3-interactive:active{ + background-color:rgba(19, 124, 189, 0.35); } + .bp3-tag.bp3-minimal.bp3-intent-primary > .bp3-icon, .bp3-tag.bp3-minimal.bp3-intent-primary .bp3-icon-standard, .bp3-tag.bp3-minimal.bp3-intent-primary .bp3-icon-large{ + fill:#137cbd; } + .bp3-dark .bp3-tag.bp3-minimal.bp3-intent-primary{ + background-color:rgba(19, 124, 189, 0.25); + color:#48aff0; } + .bp3-dark .bp3-tag.bp3-minimal.bp3-intent-primary.bp3-interactive{ + cursor:pointer; } + .bp3-dark .bp3-tag.bp3-minimal.bp3-intent-primary.bp3-interactive:hover{ + background-color:rgba(19, 124, 189, 0.35); } + .bp3-dark .bp3-tag.bp3-minimal.bp3-intent-primary.bp3-interactive.bp3-active, .bp3-dark .bp3-tag.bp3-minimal.bp3-intent-primary.bp3-interactive:active{ + background-color:rgba(19, 124, 189, 0.45); } + .bp3-tag.bp3-minimal.bp3-intent-success{ + background-color:rgba(15, 153, 96, 0.15); + color:#0d8050; } + .bp3-tag.bp3-minimal.bp3-intent-success.bp3-interactive{ + cursor:pointer; } + .bp3-tag.bp3-minimal.bp3-intent-success.bp3-interactive:hover{ + background-color:rgba(15, 153, 96, 0.25); } + .bp3-tag.bp3-minimal.bp3-intent-success.bp3-interactive.bp3-active, .bp3-tag.bp3-minimal.bp3-intent-success.bp3-interactive:active{ + background-color:rgba(15, 153, 96, 0.35); } + .bp3-tag.bp3-minimal.bp3-intent-success > .bp3-icon, .bp3-tag.bp3-minimal.bp3-intent-success .bp3-icon-standard, .bp3-tag.bp3-minimal.bp3-intent-success .bp3-icon-large{ + fill:#0f9960; } + .bp3-dark .bp3-tag.bp3-minimal.bp3-intent-success{ + background-color:rgba(15, 153, 96, 0.25); + color:#3dcc91; } + .bp3-dark .bp3-tag.bp3-minimal.bp3-intent-success.bp3-interactive{ + cursor:pointer; } + .bp3-dark .bp3-tag.bp3-minimal.bp3-intent-success.bp3-interactive:hover{ + background-color:rgba(15, 153, 96, 0.35); } + .bp3-dark .bp3-tag.bp3-minimal.bp3-intent-success.bp3-interactive.bp3-active, .bp3-dark .bp3-tag.bp3-minimal.bp3-intent-success.bp3-interactive:active{ + background-color:rgba(15, 153, 96, 0.45); } + .bp3-tag.bp3-minimal.bp3-intent-warning{ + background-color:rgba(217, 130, 43, 0.15); + color:#bf7326; } + .bp3-tag.bp3-minimal.bp3-intent-warning.bp3-interactive{ + cursor:pointer; } + .bp3-tag.bp3-minimal.bp3-intent-warning.bp3-interactive:hover{ + background-color:rgba(217, 130, 43, 0.25); } + .bp3-tag.bp3-minimal.bp3-intent-warning.bp3-interactive.bp3-active, .bp3-tag.bp3-minimal.bp3-intent-warning.bp3-interactive:active{ + background-color:rgba(217, 130, 43, 0.35); } + .bp3-tag.bp3-minimal.bp3-intent-warning > .bp3-icon, .bp3-tag.bp3-minimal.bp3-intent-warning .bp3-icon-standard, .bp3-tag.bp3-minimal.bp3-intent-warning .bp3-icon-large{ + fill:#d9822b; } + .bp3-dark .bp3-tag.bp3-minimal.bp3-intent-warning{ + background-color:rgba(217, 130, 43, 0.25); + color:#ffb366; } + .bp3-dark .bp3-tag.bp3-minimal.bp3-intent-warning.bp3-interactive{ + cursor:pointer; } + .bp3-dark .bp3-tag.bp3-minimal.bp3-intent-warning.bp3-interactive:hover{ + background-color:rgba(217, 130, 43, 0.35); } + .bp3-dark .bp3-tag.bp3-minimal.bp3-intent-warning.bp3-interactive.bp3-active, .bp3-dark .bp3-tag.bp3-minimal.bp3-intent-warning.bp3-interactive:active{ + background-color:rgba(217, 130, 43, 0.45); } + .bp3-tag.bp3-minimal.bp3-intent-danger{ + background-color:rgba(219, 55, 55, 0.15); + color:#c23030; } + .bp3-tag.bp3-minimal.bp3-intent-danger.bp3-interactive{ + cursor:pointer; } + .bp3-tag.bp3-minimal.bp3-intent-danger.bp3-interactive:hover{ + background-color:rgba(219, 55, 55, 0.25); } + .bp3-tag.bp3-minimal.bp3-intent-danger.bp3-interactive.bp3-active, .bp3-tag.bp3-minimal.bp3-intent-danger.bp3-interactive:active{ + background-color:rgba(219, 55, 55, 0.35); } + .bp3-tag.bp3-minimal.bp3-intent-danger > .bp3-icon, .bp3-tag.bp3-minimal.bp3-intent-danger .bp3-icon-standard, .bp3-tag.bp3-minimal.bp3-intent-danger .bp3-icon-large{ + fill:#db3737; } + .bp3-dark .bp3-tag.bp3-minimal.bp3-intent-danger{ + background-color:rgba(219, 55, 55, 0.25); + color:#ff7373; } + .bp3-dark .bp3-tag.bp3-minimal.bp3-intent-danger.bp3-interactive{ + cursor:pointer; } + .bp3-dark .bp3-tag.bp3-minimal.bp3-intent-danger.bp3-interactive:hover{ + background-color:rgba(219, 55, 55, 0.35); } + .bp3-dark .bp3-tag.bp3-minimal.bp3-intent-danger.bp3-interactive.bp3-active, .bp3-dark .bp3-tag.bp3-minimal.bp3-intent-danger.bp3-interactive:active{ + background-color:rgba(219, 55, 55, 0.45); } + +.bp3-tag-remove{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; + opacity:0.5; + margin-top:-2px; + margin-right:-6px !important; + margin-bottom:-2px; + border:none; + background:none; + cursor:pointer; + padding:2px; + padding-left:0; + color:inherit; } + .bp3-tag-remove:hover{ + opacity:0.8; + background:none; + text-decoration:none; } + .bp3-tag-remove:active{ + opacity:1; } + .bp3-tag-remove:empty::before{ + line-height:1; + font-family:"Icons16", sans-serif; + font-size:16px; + font-weight:400; + font-style:normal; + -moz-osx-font-smoothing:grayscale; + -webkit-font-smoothing:antialiased; + content:"î›—"; } + .bp3-large .bp3-tag-remove{ + margin-right:-10px !important; + padding:5px; + padding-left:0; } + .bp3-large .bp3-tag-remove:empty::before{ + line-height:1; + font-family:"Icons20", sans-serif; + font-size:20px; + font-weight:400; + font-style:normal; } +.bp3-tag-input{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; + -webkit-box-orient:horizontal; + -webkit-box-direction:normal; + -ms-flex-direction:row; + flex-direction:row; + -webkit-box-align:start; + -ms-flex-align:start; + align-items:flex-start; + cursor:text; + height:auto; + min-height:30px; + padding-right:0; + padding-left:5px; + line-height:inherit; } + .bp3-tag-input > *{ + -webkit-box-flex:0; + -ms-flex-positive:0; + flex-grow:0; + -ms-flex-negative:0; + flex-shrink:0; } + .bp3-tag-input > .bp3-tag-input-values{ + -webkit-box-flex:1; + -ms-flex-positive:1; + flex-grow:1; + -ms-flex-negative:1; + flex-shrink:1; } + .bp3-tag-input .bp3-tag-input-icon{ + margin-top:7px; + margin-right:7px; + margin-left:2px; + color:#5c7080; } + .bp3-tag-input .bp3-tag-input-values{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; + -webkit-box-orient:horizontal; + -webkit-box-direction:normal; + -ms-flex-direction:row; + flex-direction:row; + -ms-flex-wrap:wrap; + flex-wrap:wrap; + -webkit-box-align:center; + -ms-flex-align:center; + align-items:center; + -ms-flex-item-align:stretch; + align-self:stretch; + margin-top:5px; + margin-right:7px; + min-width:0; } + .bp3-tag-input .bp3-tag-input-values > *{ + -webkit-box-flex:0; + -ms-flex-positive:0; + flex-grow:0; + -ms-flex-negative:0; + flex-shrink:0; } + .bp3-tag-input .bp3-tag-input-values > .bp3-fill{ + -webkit-box-flex:1; + -ms-flex-positive:1; + flex-grow:1; + -ms-flex-negative:1; + flex-shrink:1; } + .bp3-tag-input .bp3-tag-input-values::before, + .bp3-tag-input .bp3-tag-input-values > *{ + margin-right:5px; } + .bp3-tag-input .bp3-tag-input-values:empty::before, + .bp3-tag-input .bp3-tag-input-values > :last-child{ + margin-right:0; } + .bp3-tag-input .bp3-tag-input-values:first-child .bp3-input-ghost:first-child{ + padding-left:5px; } + .bp3-tag-input .bp3-tag-input-values > *{ + margin-bottom:5px; } + .bp3-tag-input .bp3-tag{ + overflow-wrap:break-word; } + .bp3-tag-input .bp3-tag.bp3-active{ + outline:rgba(19, 124, 189, 0.6) auto 2px; + outline-offset:0; + -moz-outline-radius:6px; } + .bp3-tag-input .bp3-input-ghost{ + -webkit-box-flex:1; + -ms-flex:1 1 auto; + flex:1 1 auto; + width:80px; + line-height:20px; } + .bp3-tag-input .bp3-input-ghost:disabled, .bp3-tag-input .bp3-input-ghost.bp3-disabled{ + cursor:not-allowed; } + .bp3-tag-input .bp3-button, + .bp3-tag-input .bp3-spinner{ + margin:3px; + margin-left:0; } + .bp3-tag-input .bp3-button{ + min-width:24px; + min-height:24px; + padding:0 7px; } + .bp3-tag-input.bp3-large{ + height:auto; + min-height:40px; } + .bp3-tag-input.bp3-large::before, + .bp3-tag-input.bp3-large > *{ + margin-right:10px; } + .bp3-tag-input.bp3-large:empty::before, + .bp3-tag-input.bp3-large > :last-child{ + margin-right:0; } + .bp3-tag-input.bp3-large .bp3-tag-input-icon{ + margin-top:10px; + margin-left:5px; } + .bp3-tag-input.bp3-large .bp3-input-ghost{ + line-height:30px; } + .bp3-tag-input.bp3-large .bp3-button{ + min-width:30px; + min-height:30px; + padding:5px 10px; + margin:5px; + margin-left:0; } + .bp3-tag-input.bp3-large .bp3-spinner{ + margin:8px; + margin-left:0; } + .bp3-tag-input.bp3-active{ + -webkit-box-shadow:0 0 0 1px #137cbd, 0 0 0 3px rgba(19, 124, 189, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px #137cbd, 0 0 0 3px rgba(19, 124, 189, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); + background-color:#ffffff; } + .bp3-tag-input.bp3-active.bp3-intent-primary{ + -webkit-box-shadow:0 0 0 1px #106ba3, 0 0 0 3px rgba(16, 107, 163, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px #106ba3, 0 0 0 3px rgba(16, 107, 163, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); } + .bp3-tag-input.bp3-active.bp3-intent-success{ + -webkit-box-shadow:0 0 0 1px #0d8050, 0 0 0 3px rgba(13, 128, 80, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px #0d8050, 0 0 0 3px rgba(13, 128, 80, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); } + .bp3-tag-input.bp3-active.bp3-intent-warning{ + -webkit-box-shadow:0 0 0 1px #bf7326, 0 0 0 3px rgba(191, 115, 38, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px #bf7326, 0 0 0 3px rgba(191, 115, 38, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); } + .bp3-tag-input.bp3-active.bp3-intent-danger{ + -webkit-box-shadow:0 0 0 1px #c23030, 0 0 0 3px rgba(194, 48, 48, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px #c23030, 0 0 0 3px rgba(194, 48, 48, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.2); } + .bp3-dark .bp3-tag-input .bp3-tag-input-icon, .bp3-tag-input.bp3-dark .bp3-tag-input-icon{ + color:#a7b6c2; } + .bp3-dark .bp3-tag-input .bp3-input-ghost, .bp3-tag-input.bp3-dark .bp3-input-ghost{ + color:#f5f8fa; } + .bp3-dark .bp3-tag-input .bp3-input-ghost::-webkit-input-placeholder, .bp3-tag-input.bp3-dark .bp3-input-ghost::-webkit-input-placeholder{ + color:rgba(167, 182, 194, 0.6); } + .bp3-dark .bp3-tag-input .bp3-input-ghost::-moz-placeholder, .bp3-tag-input.bp3-dark .bp3-input-ghost::-moz-placeholder{ + color:rgba(167, 182, 194, 0.6); } + .bp3-dark .bp3-tag-input .bp3-input-ghost:-ms-input-placeholder, .bp3-tag-input.bp3-dark .bp3-input-ghost:-ms-input-placeholder{ + color:rgba(167, 182, 194, 0.6); } + .bp3-dark .bp3-tag-input .bp3-input-ghost::-ms-input-placeholder, .bp3-tag-input.bp3-dark .bp3-input-ghost::-ms-input-placeholder{ + color:rgba(167, 182, 194, 0.6); } + .bp3-dark .bp3-tag-input .bp3-input-ghost::placeholder, .bp3-tag-input.bp3-dark .bp3-input-ghost::placeholder{ + color:rgba(167, 182, 194, 0.6); } + .bp3-dark .bp3-tag-input.bp3-active, .bp3-tag-input.bp3-dark.bp3-active{ + -webkit-box-shadow:0 0 0 1px #137cbd, 0 0 0 1px #137cbd, 0 0 0 3px rgba(19, 124, 189, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px #137cbd, 0 0 0 1px #137cbd, 0 0 0 3px rgba(19, 124, 189, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); + background-color:rgba(16, 22, 26, 0.3); } + .bp3-dark .bp3-tag-input.bp3-active.bp3-intent-primary, .bp3-tag-input.bp3-dark.bp3-active.bp3-intent-primary{ + -webkit-box-shadow:0 0 0 1px #106ba3, 0 0 0 3px rgba(16, 107, 163, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px #106ba3, 0 0 0 3px rgba(16, 107, 163, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); } + .bp3-dark .bp3-tag-input.bp3-active.bp3-intent-success, .bp3-tag-input.bp3-dark.bp3-active.bp3-intent-success{ + -webkit-box-shadow:0 0 0 1px #0d8050, 0 0 0 3px rgba(13, 128, 80, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px #0d8050, 0 0 0 3px rgba(13, 128, 80, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); } + .bp3-dark .bp3-tag-input.bp3-active.bp3-intent-warning, .bp3-tag-input.bp3-dark.bp3-active.bp3-intent-warning{ + -webkit-box-shadow:0 0 0 1px #bf7326, 0 0 0 3px rgba(191, 115, 38, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px #bf7326, 0 0 0 3px rgba(191, 115, 38, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); } + .bp3-dark .bp3-tag-input.bp3-active.bp3-intent-danger, .bp3-tag-input.bp3-dark.bp3-active.bp3-intent-danger{ + -webkit-box-shadow:0 0 0 1px #c23030, 0 0 0 3px rgba(194, 48, 48, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px #c23030, 0 0 0 3px rgba(194, 48, 48, 0.3), inset 0 0 0 1px rgba(16, 22, 26, 0.3), inset 0 1px 1px rgba(16, 22, 26, 0.4); } + +.bp3-input-ghost{ + border:none; + -webkit-box-shadow:none; + box-shadow:none; + background:none; + padding:0; } + .bp3-input-ghost::-webkit-input-placeholder{ + opacity:1; + color:rgba(92, 112, 128, 0.6); } + .bp3-input-ghost::-moz-placeholder{ + opacity:1; + color:rgba(92, 112, 128, 0.6); } + .bp3-input-ghost:-ms-input-placeholder{ + opacity:1; + color:rgba(92, 112, 128, 0.6); } + .bp3-input-ghost::-ms-input-placeholder{ + opacity:1; + color:rgba(92, 112, 128, 0.6); } + .bp3-input-ghost::placeholder{ + opacity:1; + color:rgba(92, 112, 128, 0.6); } + .bp3-input-ghost:focus{ + outline:none !important; } +.bp3-toast{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; + -webkit-box-align:start; + -ms-flex-align:start; + align-items:flex-start; + position:relative !important; + margin:20px 0 0; + border-radius:3px; + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 2px 4px rgba(16, 22, 26, 0.2), 0 8px 24px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 2px 4px rgba(16, 22, 26, 0.2), 0 8px 24px rgba(16, 22, 26, 0.2); + background-color:#ffffff; + min-width:300px; + max-width:500px; + pointer-events:all; } + .bp3-toast.bp3-toast-enter, .bp3-toast.bp3-toast-appear{ + -webkit-transform:translateY(-40px); + transform:translateY(-40px); } + .bp3-toast.bp3-toast-enter-active, .bp3-toast.bp3-toast-appear-active{ + -webkit-transform:translateY(0); + transform:translateY(0); + -webkit-transition-property:-webkit-transform; + transition-property:-webkit-transform; + transition-property:transform; + transition-property:transform, -webkit-transform; + -webkit-transition-duration:300ms; + transition-duration:300ms; + -webkit-transition-timing-function:cubic-bezier(0.54, 1.12, 0.38, 1.11); + transition-timing-function:cubic-bezier(0.54, 1.12, 0.38, 1.11); + -webkit-transition-delay:0; + transition-delay:0; } + .bp3-toast.bp3-toast-enter ~ .bp3-toast, .bp3-toast.bp3-toast-appear ~ .bp3-toast{ + -webkit-transform:translateY(-40px); + transform:translateY(-40px); } + .bp3-toast.bp3-toast-enter-active ~ .bp3-toast, .bp3-toast.bp3-toast-appear-active ~ .bp3-toast{ + -webkit-transform:translateY(0); + transform:translateY(0); + -webkit-transition-property:-webkit-transform; + transition-property:-webkit-transform; + transition-property:transform; + transition-property:transform, -webkit-transform; + -webkit-transition-duration:300ms; + transition-duration:300ms; + -webkit-transition-timing-function:cubic-bezier(0.54, 1.12, 0.38, 1.11); + transition-timing-function:cubic-bezier(0.54, 1.12, 0.38, 1.11); + -webkit-transition-delay:0; + transition-delay:0; } + .bp3-toast.bp3-toast-exit{ + opacity:1; + -webkit-filter:blur(0); + filter:blur(0); } + .bp3-toast.bp3-toast-exit-active{ + opacity:0; + -webkit-filter:blur(10px); + filter:blur(10px); + -webkit-transition-property:opacity, -webkit-filter; + transition-property:opacity, -webkit-filter; + transition-property:opacity, filter; + transition-property:opacity, filter, -webkit-filter; + -webkit-transition-duration:300ms; + transition-duration:300ms; + -webkit-transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + -webkit-transition-delay:0; + transition-delay:0; } + .bp3-toast.bp3-toast-exit ~ .bp3-toast{ + -webkit-transform:translateY(0); + transform:translateY(0); } + .bp3-toast.bp3-toast-exit-active ~ .bp3-toast{ + -webkit-transform:translateY(-40px); + transform:translateY(-40px); + -webkit-transition-property:-webkit-transform; + transition-property:-webkit-transform; + transition-property:transform; + transition-property:transform, -webkit-transform; + -webkit-transition-duration:100ms; + transition-duration:100ms; + -webkit-transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + -webkit-transition-delay:50ms; + transition-delay:50ms; } + .bp3-toast .bp3-button-group{ + -webkit-box-flex:0; + -ms-flex:0 0 auto; + flex:0 0 auto; + padding:5px; + padding-left:0; } + .bp3-toast > .bp3-icon{ + margin:12px; + margin-right:0; + color:#5c7080; } + .bp3-toast.bp3-dark, + .bp3-dark .bp3-toast{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 2px 4px rgba(16, 22, 26, 0.4), 0 8px 24px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 2px 4px rgba(16, 22, 26, 0.4), 0 8px 24px rgba(16, 22, 26, 0.4); + background-color:#394b59; } + .bp3-toast.bp3-dark > .bp3-icon, + .bp3-dark .bp3-toast > .bp3-icon{ + color:#a7b6c2; } + .bp3-toast[class*="bp3-intent-"] a{ + color:rgba(255, 255, 255, 0.7); } + .bp3-toast[class*="bp3-intent-"] a:hover{ + color:#ffffff; } + .bp3-toast[class*="bp3-intent-"] > .bp3-icon{ + color:#ffffff; } + .bp3-toast[class*="bp3-intent-"] .bp3-button, .bp3-toast[class*="bp3-intent-"] .bp3-button::before, + .bp3-toast[class*="bp3-intent-"] .bp3-button .bp3-icon, .bp3-toast[class*="bp3-intent-"] .bp3-button:active{ + color:rgba(255, 255, 255, 0.7) !important; } + .bp3-toast[class*="bp3-intent-"] .bp3-button:focus{ + outline-color:rgba(255, 255, 255, 0.5); } + .bp3-toast[class*="bp3-intent-"] .bp3-button:hover{ + background-color:rgba(255, 255, 255, 0.15) !important; + color:#ffffff !important; } + .bp3-toast[class*="bp3-intent-"] .bp3-button:active{ + background-color:rgba(255, 255, 255, 0.3) !important; + color:#ffffff !important; } + .bp3-toast[class*="bp3-intent-"] .bp3-button::after{ + background:rgba(255, 255, 255, 0.3) !important; } + .bp3-toast.bp3-intent-primary{ + background-color:#137cbd; + color:#ffffff; } + .bp3-toast.bp3-intent-success{ + background-color:#0f9960; + color:#ffffff; } + .bp3-toast.bp3-intent-warning{ + background-color:#d9822b; + color:#ffffff; } + .bp3-toast.bp3-intent-danger{ + background-color:#db3737; + color:#ffffff; } + +.bp3-toast-message{ + -webkit-box-flex:1; + -ms-flex:1 1 auto; + flex:1 1 auto; + padding:11px; + word-break:break-word; } + +.bp3-toast-container{ + display:-webkit-box !important; + display:-ms-flexbox !important; + display:flex !important; + -webkit-box-orient:vertical; + -webkit-box-direction:normal; + -ms-flex-direction:column; + flex-direction:column; + -webkit-box-align:center; + -ms-flex-align:center; + align-items:center; + position:fixed; + right:0; + left:0; + z-index:40; + overflow:hidden; + padding:0 20px 20px; + pointer-events:none; } + .bp3-toast-container.bp3-toast-container-top{ + top:0; + bottom:auto; } + .bp3-toast-container.bp3-toast-container-bottom{ + -webkit-box-orient:vertical; + -webkit-box-direction:reverse; + -ms-flex-direction:column-reverse; + flex-direction:column-reverse; + top:auto; + bottom:0; } + .bp3-toast-container.bp3-toast-container-left{ + -webkit-box-align:start; + -ms-flex-align:start; + align-items:flex-start; } + .bp3-toast-container.bp3-toast-container-right{ + -webkit-box-align:end; + -ms-flex-align:end; + align-items:flex-end; } + +.bp3-toast-container-bottom .bp3-toast.bp3-toast-enter:not(.bp3-toast-enter-active), +.bp3-toast-container-bottom .bp3-toast.bp3-toast-enter:not(.bp3-toast-enter-active) ~ .bp3-toast, .bp3-toast-container-bottom .bp3-toast.bp3-toast-appear:not(.bp3-toast-appear-active), +.bp3-toast-container-bottom .bp3-toast.bp3-toast-appear:not(.bp3-toast-appear-active) ~ .bp3-toast, +.bp3-toast-container-bottom .bp3-toast.bp3-toast-leave-active ~ .bp3-toast{ + -webkit-transform:translateY(60px); + transform:translateY(60px); } +.bp3-tooltip{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 2px 4px rgba(16, 22, 26, 0.2), 0 8px 24px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 2px 4px rgba(16, 22, 26, 0.2), 0 8px 24px rgba(16, 22, 26, 0.2); + -webkit-transform:scale(1); + transform:scale(1); } + .bp3-tooltip .bp3-popover-arrow{ + position:absolute; + width:22px; + height:22px; } + .bp3-tooltip .bp3-popover-arrow::before{ + margin:4px; + width:14px; + height:14px; } + .bp3-tether-element-attached-bottom.bp3-tether-target-attached-top > .bp3-tooltip{ + margin-top:-11px; + margin-bottom:11px; } + .bp3-tether-element-attached-bottom.bp3-tether-target-attached-top > .bp3-tooltip > .bp3-popover-arrow{ + bottom:-8px; } + .bp3-tether-element-attached-bottom.bp3-tether-target-attached-top > .bp3-tooltip > .bp3-popover-arrow svg{ + -webkit-transform:rotate(-90deg); + transform:rotate(-90deg); } + .bp3-tether-element-attached-left.bp3-tether-target-attached-right > .bp3-tooltip{ + margin-left:11px; } + .bp3-tether-element-attached-left.bp3-tether-target-attached-right > .bp3-tooltip > .bp3-popover-arrow{ + left:-8px; } + .bp3-tether-element-attached-left.bp3-tether-target-attached-right > .bp3-tooltip > .bp3-popover-arrow svg{ + -webkit-transform:rotate(0); + transform:rotate(0); } + .bp3-tether-element-attached-top.bp3-tether-target-attached-bottom > .bp3-tooltip{ + margin-top:11px; } + .bp3-tether-element-attached-top.bp3-tether-target-attached-bottom > .bp3-tooltip > .bp3-popover-arrow{ + top:-8px; } + .bp3-tether-element-attached-top.bp3-tether-target-attached-bottom > .bp3-tooltip > .bp3-popover-arrow svg{ + -webkit-transform:rotate(90deg); + transform:rotate(90deg); } + .bp3-tether-element-attached-right.bp3-tether-target-attached-left > .bp3-tooltip{ + margin-right:11px; + margin-left:-11px; } + .bp3-tether-element-attached-right.bp3-tether-target-attached-left > .bp3-tooltip > .bp3-popover-arrow{ + right:-8px; } + .bp3-tether-element-attached-right.bp3-tether-target-attached-left > .bp3-tooltip > .bp3-popover-arrow svg{ + -webkit-transform:rotate(180deg); + transform:rotate(180deg); } + .bp3-tether-element-attached-middle > .bp3-tooltip > .bp3-popover-arrow{ + top:50%; + -webkit-transform:translateY(-50%); + transform:translateY(-50%); } + .bp3-tether-element-attached-center > .bp3-tooltip > .bp3-popover-arrow{ + right:50%; + -webkit-transform:translateX(50%); + transform:translateX(50%); } + .bp3-tether-element-attached-top.bp3-tether-target-attached-top > .bp3-tooltip > .bp3-popover-arrow{ + top:-0.22183px; } + .bp3-tether-element-attached-right.bp3-tether-target-attached-right > .bp3-tooltip > .bp3-popover-arrow{ + right:-0.22183px; } + .bp3-tether-element-attached-left.bp3-tether-target-attached-left > .bp3-tooltip > .bp3-popover-arrow{ + left:-0.22183px; } + .bp3-tether-element-attached-bottom.bp3-tether-target-attached-bottom > .bp3-tooltip > .bp3-popover-arrow{ + bottom:-0.22183px; } + .bp3-tether-element-attached-top.bp3-tether-element-attached-left > .bp3-tooltip{ + -webkit-transform-origin:top left; + transform-origin:top left; } + .bp3-tether-element-attached-top.bp3-tether-element-attached-center > .bp3-tooltip{ + -webkit-transform-origin:top center; + transform-origin:top center; } + .bp3-tether-element-attached-top.bp3-tether-element-attached-right > .bp3-tooltip{ + -webkit-transform-origin:top right; + transform-origin:top right; } + .bp3-tether-element-attached-middle.bp3-tether-element-attached-left > .bp3-tooltip{ + -webkit-transform-origin:center left; + transform-origin:center left; } + .bp3-tether-element-attached-middle.bp3-tether-element-attached-center > .bp3-tooltip{ + -webkit-transform-origin:center center; + transform-origin:center center; } + .bp3-tether-element-attached-middle.bp3-tether-element-attached-right > .bp3-tooltip{ + -webkit-transform-origin:center right; + transform-origin:center right; } + .bp3-tether-element-attached-bottom.bp3-tether-element-attached-left > .bp3-tooltip{ + -webkit-transform-origin:bottom left; + transform-origin:bottom left; } + .bp3-tether-element-attached-bottom.bp3-tether-element-attached-center > .bp3-tooltip{ + -webkit-transform-origin:bottom center; + transform-origin:bottom center; } + .bp3-tether-element-attached-bottom.bp3-tether-element-attached-right > .bp3-tooltip{ + -webkit-transform-origin:bottom right; + transform-origin:bottom right; } + .bp3-tooltip .bp3-popover-content{ + background:#394b59; + color:#f5f8fa; } + .bp3-tooltip .bp3-popover-arrow::before{ + -webkit-box-shadow:1px 1px 6px rgba(16, 22, 26, 0.2); + box-shadow:1px 1px 6px rgba(16, 22, 26, 0.2); } + .bp3-tooltip .bp3-popover-arrow-border{ + fill:#10161a; + fill-opacity:0.1; } + .bp3-tooltip .bp3-popover-arrow-fill{ + fill:#394b59; } + .bp3-popover-enter > .bp3-tooltip, .bp3-popover-appear > .bp3-tooltip{ + -webkit-transform:scale(0.8); + transform:scale(0.8); } + .bp3-popover-enter-active > .bp3-tooltip, .bp3-popover-appear-active > .bp3-tooltip{ + -webkit-transform:scale(1); + transform:scale(1); + -webkit-transition-property:-webkit-transform; + transition-property:-webkit-transform; + transition-property:transform; + transition-property:transform, -webkit-transform; + -webkit-transition-duration:100ms; + transition-duration:100ms; + -webkit-transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + -webkit-transition-delay:0; + transition-delay:0; } + .bp3-popover-exit > .bp3-tooltip{ + -webkit-transform:scale(1); + transform:scale(1); } + .bp3-popover-exit-active > .bp3-tooltip{ + -webkit-transform:scale(0.8); + transform:scale(0.8); + -webkit-transition-property:-webkit-transform; + transition-property:-webkit-transform; + transition-property:transform; + transition-property:transform, -webkit-transform; + -webkit-transition-duration:100ms; + transition-duration:100ms; + -webkit-transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + -webkit-transition-delay:0; + transition-delay:0; } + .bp3-tooltip .bp3-popover-content{ + padding:10px 12px; } + .bp3-tooltip.bp3-dark, + .bp3-dark .bp3-tooltip{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 2px 4px rgba(16, 22, 26, 0.4), 0 8px 24px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 2px 4px rgba(16, 22, 26, 0.4), 0 8px 24px rgba(16, 22, 26, 0.4); } + .bp3-tooltip.bp3-dark .bp3-popover-content, + .bp3-dark .bp3-tooltip .bp3-popover-content{ + background:#e1e8ed; + color:#394b59; } + .bp3-tooltip.bp3-dark .bp3-popover-arrow::before, + .bp3-dark .bp3-tooltip .bp3-popover-arrow::before{ + -webkit-box-shadow:1px 1px 6px rgba(16, 22, 26, 0.4); + box-shadow:1px 1px 6px rgba(16, 22, 26, 0.4); } + .bp3-tooltip.bp3-dark .bp3-popover-arrow-border, + .bp3-dark .bp3-tooltip .bp3-popover-arrow-border{ + fill:#10161a; + fill-opacity:0.2; } + .bp3-tooltip.bp3-dark .bp3-popover-arrow-fill, + .bp3-dark .bp3-tooltip .bp3-popover-arrow-fill{ + fill:#e1e8ed; } + .bp3-tooltip.bp3-intent-primary .bp3-popover-content{ + background:#137cbd; + color:#ffffff; } + .bp3-tooltip.bp3-intent-primary .bp3-popover-arrow-fill{ + fill:#137cbd; } + .bp3-tooltip.bp3-intent-success .bp3-popover-content{ + background:#0f9960; + color:#ffffff; } + .bp3-tooltip.bp3-intent-success .bp3-popover-arrow-fill{ + fill:#0f9960; } + .bp3-tooltip.bp3-intent-warning .bp3-popover-content{ + background:#d9822b; + color:#ffffff; } + .bp3-tooltip.bp3-intent-warning .bp3-popover-arrow-fill{ + fill:#d9822b; } + .bp3-tooltip.bp3-intent-danger .bp3-popover-content{ + background:#db3737; + color:#ffffff; } + .bp3-tooltip.bp3-intent-danger .bp3-popover-arrow-fill{ + fill:#db3737; } + +.bp3-tooltip-indicator{ + border-bottom:dotted 1px; + cursor:help; } +.bp3-tree .bp3-icon, .bp3-tree .bp3-icon-standard, .bp3-tree .bp3-icon-large{ + color:#5c7080; } + .bp3-tree .bp3-icon.bp3-intent-primary, .bp3-tree .bp3-icon-standard.bp3-intent-primary, .bp3-tree .bp3-icon-large.bp3-intent-primary{ + color:#137cbd; } + .bp3-tree .bp3-icon.bp3-intent-success, .bp3-tree .bp3-icon-standard.bp3-intent-success, .bp3-tree .bp3-icon-large.bp3-intent-success{ + color:#0f9960; } + .bp3-tree .bp3-icon.bp3-intent-warning, .bp3-tree .bp3-icon-standard.bp3-intent-warning, .bp3-tree .bp3-icon-large.bp3-intent-warning{ + color:#d9822b; } + .bp3-tree .bp3-icon.bp3-intent-danger, .bp3-tree .bp3-icon-standard.bp3-intent-danger, .bp3-tree .bp3-icon-large.bp3-intent-danger{ + color:#db3737; } + +.bp3-tree-node-list{ + margin:0; + padding-left:0; + list-style:none; } + +.bp3-tree-root{ + position:relative; + background-color:transparent; + cursor:default; + padding-left:0; } + +.bp3-tree-node-content-0{ + padding-left:0px; } + +.bp3-tree-node-content-1{ + padding-left:23px; } + +.bp3-tree-node-content-2{ + padding-left:46px; } + +.bp3-tree-node-content-3{ + padding-left:69px; } + +.bp3-tree-node-content-4{ + padding-left:92px; } + +.bp3-tree-node-content-5{ + padding-left:115px; } + +.bp3-tree-node-content-6{ + padding-left:138px; } + +.bp3-tree-node-content-7{ + padding-left:161px; } + +.bp3-tree-node-content-8{ + padding-left:184px; } + +.bp3-tree-node-content-9{ + padding-left:207px; } + +.bp3-tree-node-content-10{ + padding-left:230px; } + +.bp3-tree-node-content-11{ + padding-left:253px; } + +.bp3-tree-node-content-12{ + padding-left:276px; } + +.bp3-tree-node-content-13{ + padding-left:299px; } + +.bp3-tree-node-content-14{ + padding-left:322px; } + +.bp3-tree-node-content-15{ + padding-left:345px; } + +.bp3-tree-node-content-16{ + padding-left:368px; } + +.bp3-tree-node-content-17{ + padding-left:391px; } + +.bp3-tree-node-content-18{ + padding-left:414px; } + +.bp3-tree-node-content-19{ + padding-left:437px; } + +.bp3-tree-node-content-20{ + padding-left:460px; } + +.bp3-tree-node-content{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; + -webkit-box-align:center; + -ms-flex-align:center; + align-items:center; + width:100%; + height:30px; + padding-right:5px; } + .bp3-tree-node-content:hover{ + background-color:rgba(191, 204, 214, 0.4); } + +.bp3-tree-node-caret, +.bp3-tree-node-caret-none{ + min-width:30px; } + +.bp3-tree-node-caret{ + color:#5c7080; + -webkit-transform:rotate(0deg); + transform:rotate(0deg); + cursor:pointer; + padding:7px; + -webkit-transition:-webkit-transform 200ms cubic-bezier(0.4, 1, 0.75, 0.9); + transition:-webkit-transform 200ms cubic-bezier(0.4, 1, 0.75, 0.9); + transition:transform 200ms cubic-bezier(0.4, 1, 0.75, 0.9); + transition:transform 200ms cubic-bezier(0.4, 1, 0.75, 0.9), -webkit-transform 200ms cubic-bezier(0.4, 1, 0.75, 0.9); } + .bp3-tree-node-caret:hover{ + color:#182026; } + .bp3-dark .bp3-tree-node-caret{ + color:#a7b6c2; } + .bp3-dark .bp3-tree-node-caret:hover{ + color:#f5f8fa; } + .bp3-tree-node-caret.bp3-tree-node-caret-open{ + -webkit-transform:rotate(90deg); + transform:rotate(90deg); } + .bp3-tree-node-caret.bp3-icon-standard::before{ + content:"îš•"; } + +.bp3-tree-node-icon{ + position:relative; + margin-right:7px; } + +.bp3-tree-node-label{ + overflow:hidden; + text-overflow:ellipsis; + white-space:nowrap; + word-wrap:normal; + -webkit-box-flex:1; + -ms-flex:1 1 auto; + flex:1 1 auto; + position:relative; + -webkit-user-select:none; + -moz-user-select:none; + -ms-user-select:none; + user-select:none; } + .bp3-tree-node-label span{ + display:inline; } + +.bp3-tree-node-secondary-label{ + padding:0 5px; + -webkit-user-select:none; + -moz-user-select:none; + -ms-user-select:none; + user-select:none; } + .bp3-tree-node-secondary-label .bp3-popover-wrapper, + .bp3-tree-node-secondary-label .bp3-popover-target{ + display:-webkit-box; + display:-ms-flexbox; + display:flex; + -webkit-box-align:center; + -ms-flex-align:center; + align-items:center; } + +.bp3-tree-node.bp3-disabled .bp3-tree-node-content{ + background-color:inherit; + cursor:not-allowed; + color:rgba(92, 112, 128, 0.6); } + +.bp3-tree-node.bp3-disabled .bp3-tree-node-caret, +.bp3-tree-node.bp3-disabled .bp3-tree-node-icon{ + cursor:not-allowed; + color:rgba(92, 112, 128, 0.6); } + +.bp3-tree-node.bp3-tree-node-selected > .bp3-tree-node-content{ + background-color:#137cbd; } + .bp3-tree-node.bp3-tree-node-selected > .bp3-tree-node-content, + .bp3-tree-node.bp3-tree-node-selected > .bp3-tree-node-content .bp3-icon, .bp3-tree-node.bp3-tree-node-selected > .bp3-tree-node-content .bp3-icon-standard, .bp3-tree-node.bp3-tree-node-selected > .bp3-tree-node-content .bp3-icon-large{ + color:#ffffff; } + .bp3-tree-node.bp3-tree-node-selected > .bp3-tree-node-content .bp3-tree-node-caret::before{ + color:rgba(255, 255, 255, 0.7); } + .bp3-tree-node.bp3-tree-node-selected > .bp3-tree-node-content .bp3-tree-node-caret:hover::before{ + color:#ffffff; } + +.bp3-dark .bp3-tree-node-content:hover{ + background-color:rgba(92, 112, 128, 0.3); } + +.bp3-dark .bp3-tree .bp3-icon, .bp3-dark .bp3-tree .bp3-icon-standard, .bp3-dark .bp3-tree .bp3-icon-large{ + color:#a7b6c2; } + .bp3-dark .bp3-tree .bp3-icon.bp3-intent-primary, .bp3-dark .bp3-tree .bp3-icon-standard.bp3-intent-primary, .bp3-dark .bp3-tree .bp3-icon-large.bp3-intent-primary{ + color:#137cbd; } + .bp3-dark .bp3-tree .bp3-icon.bp3-intent-success, .bp3-dark .bp3-tree .bp3-icon-standard.bp3-intent-success, .bp3-dark .bp3-tree .bp3-icon-large.bp3-intent-success{ + color:#0f9960; } + .bp3-dark .bp3-tree .bp3-icon.bp3-intent-warning, .bp3-dark .bp3-tree .bp3-icon-standard.bp3-intent-warning, .bp3-dark .bp3-tree .bp3-icon-large.bp3-intent-warning{ + color:#d9822b; } + .bp3-dark .bp3-tree .bp3-icon.bp3-intent-danger, .bp3-dark .bp3-tree .bp3-icon-standard.bp3-intent-danger, .bp3-dark .bp3-tree .bp3-icon-large.bp3-intent-danger{ + color:#db3737; } + +.bp3-dark .bp3-tree-node.bp3-tree-node-selected > .bp3-tree-node-content{ + background-color:#137cbd; } +/*! + +Copyright 2017-present Palantir Technologies, Inc. All rights reserved. +Licensed under the Apache License, Version 2.0. + +*/ +.bp3-omnibar{ + -webkit-filter:blur(0); + filter:blur(0); + opacity:1; + top:20vh; + left:calc(50% - 250px); + z-index:21; + border-radius:3px; + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 4px 8px rgba(16, 22, 26, 0.2), 0 18px 46px 6px rgba(16, 22, 26, 0.2); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.1), 0 4px 8px rgba(16, 22, 26, 0.2), 0 18px 46px 6px rgba(16, 22, 26, 0.2); + background-color:#ffffff; + width:500px; } + .bp3-omnibar.bp3-overlay-enter, .bp3-omnibar.bp3-overlay-appear{ + -webkit-filter:blur(20px); + filter:blur(20px); + opacity:0.2; } + .bp3-omnibar.bp3-overlay-enter-active, .bp3-omnibar.bp3-overlay-appear-active{ + -webkit-filter:blur(0); + filter:blur(0); + opacity:1; + -webkit-transition-property:opacity, -webkit-filter; + transition-property:opacity, -webkit-filter; + transition-property:filter, opacity; + transition-property:filter, opacity, -webkit-filter; + -webkit-transition-duration:200ms; + transition-duration:200ms; + -webkit-transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + -webkit-transition-delay:0; + transition-delay:0; } + .bp3-omnibar.bp3-overlay-exit{ + -webkit-filter:blur(0); + filter:blur(0); + opacity:1; } + .bp3-omnibar.bp3-overlay-exit-active{ + -webkit-filter:blur(20px); + filter:blur(20px); + opacity:0.2; + -webkit-transition-property:opacity, -webkit-filter; + transition-property:opacity, -webkit-filter; + transition-property:filter, opacity; + transition-property:filter, opacity, -webkit-filter; + -webkit-transition-duration:200ms; + transition-duration:200ms; + -webkit-transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + transition-timing-function:cubic-bezier(0.4, 1, 0.75, 0.9); + -webkit-transition-delay:0; + transition-delay:0; } + .bp3-omnibar .bp3-input{ + border-radius:0; + background-color:transparent; } + .bp3-omnibar .bp3-input, .bp3-omnibar .bp3-input:focus{ + -webkit-box-shadow:none; + box-shadow:none; } + .bp3-omnibar .bp3-menu{ + border-radius:0; + -webkit-box-shadow:inset 0 1px 0 rgba(16, 22, 26, 0.15); + box-shadow:inset 0 1px 0 rgba(16, 22, 26, 0.15); + background-color:transparent; + max-height:calc(60vh - 40px); + overflow:auto; } + .bp3-omnibar .bp3-menu:empty{ + display:none; } + .bp3-dark .bp3-omnibar, .bp3-omnibar.bp3-dark{ + -webkit-box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 4px 8px rgba(16, 22, 26, 0.4), 0 18px 46px 6px rgba(16, 22, 26, 0.4); + box-shadow:0 0 0 1px rgba(16, 22, 26, 0.2), 0 4px 8px rgba(16, 22, 26, 0.4), 0 18px 46px 6px rgba(16, 22, 26, 0.4); + background-color:#30404d; } + +.bp3-omnibar-overlay .bp3-overlay-backdrop{ + background-color:rgba(16, 22, 26, 0.2); } + +.bp3-select-popover .bp3-popover-content{ + padding:5px; } + +.bp3-select-popover .bp3-input-group{ + margin-bottom:0; } + +.bp3-select-popover .bp3-menu{ + max-width:400px; + max-height:300px; + overflow:auto; + padding:0; } + .bp3-select-popover .bp3-menu:not(:first-child){ + padding-top:5px; } + +.bp3-multi-select{ + min-width:150px; } + +.bp3-multi-select-popover .bp3-menu{ + max-width:400px; + max-height:300px; + overflow:auto; } + +.bp3-select-popover .bp3-popover-content{ + padding:5px; } + +.bp3-select-popover .bp3-input-group{ + margin-bottom:0; } + +.bp3-select-popover .bp3-menu{ + max-width:400px; + max-height:300px; + overflow:auto; + padding:0; } + .bp3-select-popover .bp3-menu:not(:first-child){ + padding-top:5px; } +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/* This file was auto-generated by ensureUiComponents() in @jupyterlab/buildutils */ + +/** + * (DEPRECATED) Support for consuming icons as CSS background images + */ + +/* Icons urls */ + +:root { + --jp-icon-add: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTE5IDEzaC02djZoLTJ2LTZINXYtMmg2VjVoMnY2aDZ2MnoiLz4KICA8L2c+Cjwvc3ZnPgo=); + --jp-icon-bug: url(data:image/svg+xml;base64,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); + --jp-icon-build: url(data:image/svg+xml;base64,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); + --jp-icon-caret-down-empty-thin: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIwIDIwIj4KCTxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSIgc2hhcGUtcmVuZGVyaW5nPSJnZW9tZXRyaWNQcmVjaXNpb24iPgoJCTxwb2x5Z29uIGNsYXNzPSJzdDEiIHBvaW50cz0iOS45LDEzLjYgMy42LDcuNCA0LjQsNi42IDkuOSwxMi4yIDE1LjQsNi43IDE2LjEsNy40ICIvPgoJPC9nPgo8L3N2Zz4K); + --jp-icon-caret-down-empty: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiIHNoYXBlLXJlbmRlcmluZz0iZ2VvbWV0cmljUHJlY2lzaW9uIj4KICAgIDxwYXRoIGQ9Ik01LjIsNS45TDksOS43bDMuOC0zLjhsMS4yLDEuMmwtNC45LDVsLTQuOS01TDUuMiw1Ljl6Ii8+CiAgPC9nPgo8L3N2Zz4K); + --jp-icon-caret-down: 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+ --jp-icon-spreadsheet: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIyIDIyIj4KICA8cGF0aCBjbGFzcz0ianAtaWNvbi1jb250cmFzdDEganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjNENBRjUwIiBkPSJNMi4yIDIuMnYxNy42aDE3LjZWMi4ySDIuMnptMTUuNCA3LjdoLTUuNVY0LjRoNS41djUuNXpNOS45IDQuNHY1LjVINC40VjQuNGg1LjV6bS01LjUgNy43aDUuNXY1LjVINC40di01LjV6bTcuNyA1LjV2LTUuNWg1LjV2NS41aC01LjV6Ii8+Cjwvc3ZnPgo=); + --jp-icon-stop: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTAgMGgyNHYyNEgweiIgZmlsbD0ibm9uZSIvPgogICAgICAgIDxwYXRoIGQ9Ik02IDZoMTJ2MTJINnoiLz4KICAgIDwvZz4KPC9zdmc+Cg==); + --jp-icon-tab: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTIxIDNIM2MtMS4xIDAtMiAuOS0yIDJ2MTRjMCAxLjEuOSAyIDIgMmgxOGMxLjEgMCAyLS45IDItMlY1YzAtMS4xLS45LTItMi0yem0wIDE2SDNWNWgxMHY0aDh2MTB6Ii8+CiAgPC9nPgo8L3N2Zz4K); + --jp-icon-terminal: url(data:image/svg+xml;base64,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); + --jp-icon-text-editor: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8cGF0aCBjbGFzcz0ianAtaWNvbjMganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjNjE2MTYxIiBkPSJNMTUgMTVIM3YyaDEydi0yem0wLThIM3YyaDEyVjd6TTMgMTNoMTh2LTJIM3Yyem0wIDhoMTh2LTJIM3Yyek0zIDN2MmgxOFYzSDN6Ii8+Cjwvc3ZnPgo=); + --jp-icon-trusted: url(data:image/svg+xml;base64,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); + --jp-icon-undo: url(data:image/svg+xml;base64,PHN2ZyB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIxNiIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTEyLjUgOGMtMi42NSAwLTUuMDUuOTktNi45IDIuNkwyIDd2OWg5bC0zLjYyLTMuNjJjMS4zOS0xLjE2IDMuMTYtMS44OCA1LjEyLTEuODggMy41NCAwIDYuNTUgMi4zMSA3LjYgNS41bDIuMzctLjc4QzIxLjA4IDExLjAzIDE3LjE1IDggMTIuNSA4eiIvPgogIDwvZz4KPC9zdmc+Cg==); + --jp-icon-vega: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIyIDIyIj4KICA8ZyBjbGFzcz0ianAtaWNvbjEganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjMjEyMTIxIj4KICAgIDxwYXRoIGQ9Ik0xMC42IDUuNGwyLjItMy4ySDIuMnY3LjNsNC02LjZ6Ii8+CiAgICA8cGF0aCBkPSJNMTUuOCAyLjJsLTQuNCA2LjZMNyA2LjNsLTQuOCA4djUuNWgxNy42VjIuMmgtNHptLTcgMTUuNEg1LjV2LTQuNGgzLjN2NC40em00LjQgMEg5LjhWOS44aDMuNHY3Ljh6bTQuNCAwaC0zLjRWNi41aDMuNHYxMS4xeiIvPgogIDwvZz4KPC9zdmc+Cg==); + --jp-icon-yaml: url(data:image/svg+xml;base64,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); +} + +/* Icon CSS class declarations */ + +.jp-AddIcon { + background-image: var(--jp-icon-add); +} +.jp-BugIcon { + background-image: var(--jp-icon-bug); +} +.jp-BuildIcon { + background-image: var(--jp-icon-build); +} +.jp-CaretDownEmptyIcon { + background-image: var(--jp-icon-caret-down-empty); +} +.jp-CaretDownEmptyThinIcon { + background-image: var(--jp-icon-caret-down-empty-thin); +} +.jp-CaretDownIcon { + background-image: var(--jp-icon-caret-down); +} +.jp-CaretLeftIcon { + background-image: var(--jp-icon-caret-left); +} +.jp-CaretRightIcon { + background-image: var(--jp-icon-caret-right); +} +.jp-CaretUpEmptyThinIcon { + background-image: var(--jp-icon-caret-up-empty-thin); +} +.jp-CaretUpIcon { + background-image: var(--jp-icon-caret-up); +} +.jp-CaseSensitiveIcon { + background-image: var(--jp-icon-case-sensitive); +} +.jp-CheckIcon { + background-image: var(--jp-icon-check); +} +.jp-CircleEmptyIcon { + background-image: var(--jp-icon-circle-empty); +} +.jp-CircleIcon { + background-image: var(--jp-icon-circle); +} +.jp-ClearIcon { + background-image: var(--jp-icon-clear); +} +.jp-CloseIcon { + background-image: var(--jp-icon-close); +} +.jp-ConsoleIcon { + background-image: var(--jp-icon-console); +} +.jp-CopyIcon { + background-image: var(--jp-icon-copy); +} +.jp-CutIcon { + background-image: var(--jp-icon-cut); +} +.jp-DownloadIcon { + background-image: var(--jp-icon-download); +} +.jp-EditIcon { + background-image: var(--jp-icon-edit); +} +.jp-EllipsesIcon { + background-image: var(--jp-icon-ellipses); +} +.jp-ExtensionIcon { + background-image: var(--jp-icon-extension); +} +.jp-FastForwardIcon { + background-image: var(--jp-icon-fast-forward); +} +.jp-FileIcon { + background-image: var(--jp-icon-file); +} +.jp-FileUploadIcon { + background-image: var(--jp-icon-file-upload); +} +.jp-FilterListIcon { + background-image: var(--jp-icon-filter-list); +} +.jp-FolderIcon { + background-image: var(--jp-icon-folder); +} +.jp-Html5Icon { + background-image: var(--jp-icon-html5); +} +.jp-ImageIcon { + background-image: var(--jp-icon-image); +} +.jp-InspectorIcon { + background-image: var(--jp-icon-inspector); +} +.jp-JsonIcon { + background-image: var(--jp-icon-json); +} +.jp-JupyterFaviconIcon { + background-image: var(--jp-icon-jupyter-favicon); +} +.jp-JupyterIcon { + background-image: var(--jp-icon-jupyter); +} +.jp-JupyterlabWordmarkIcon { + background-image: var(--jp-icon-jupyterlab-wordmark); +} +.jp-KernelIcon { + background-image: var(--jp-icon-kernel); +} +.jp-KeyboardIcon { + background-image: var(--jp-icon-keyboard); +} +.jp-LauncherIcon { + background-image: var(--jp-icon-launcher); +} +.jp-LineFormIcon { + background-image: var(--jp-icon-line-form); +} +.jp-LinkIcon { + background-image: var(--jp-icon-link); +} +.jp-ListIcon { + background-image: var(--jp-icon-list); +} +.jp-ListingsInfoIcon { + background-image: var(--jp-icon-listings-info); +} +.jp-MarkdownIcon { + background-image: var(--jp-icon-markdown); +} +.jp-NewFolderIcon { + background-image: var(--jp-icon-new-folder); +} +.jp-NotTrustedIcon { + background-image: var(--jp-icon-not-trusted); +} +.jp-NotebookIcon { + background-image: var(--jp-icon-notebook); +} +.jp-PaletteIcon { + background-image: var(--jp-icon-palette); +} +.jp-PasteIcon { + background-image: var(--jp-icon-paste); +} +.jp-PythonIcon { + background-image: var(--jp-icon-python); +} +.jp-RKernelIcon { + background-image: var(--jp-icon-r-kernel); +} +.jp-ReactIcon { + background-image: var(--jp-icon-react); +} +.jp-RefreshIcon { + background-image: var(--jp-icon-refresh); +} +.jp-RegexIcon { + background-image: var(--jp-icon-regex); +} +.jp-RunIcon { + background-image: var(--jp-icon-run); +} +.jp-RunningIcon { + background-image: var(--jp-icon-running); +} +.jp-SaveIcon { + background-image: var(--jp-icon-save); +} +.jp-SearchIcon { + background-image: var(--jp-icon-search); +} +.jp-SettingsIcon { + background-image: var(--jp-icon-settings); +} +.jp-SpreadsheetIcon { + background-image: var(--jp-icon-spreadsheet); +} +.jp-StopIcon { + background-image: var(--jp-icon-stop); +} +.jp-TabIcon { + background-image: var(--jp-icon-tab); +} +.jp-TerminalIcon { + background-image: var(--jp-icon-terminal); +} +.jp-TextEditorIcon { + background-image: var(--jp-icon-text-editor); +} +.jp-TrustedIcon { + background-image: var(--jp-icon-trusted); +} +.jp-UndoIcon { + background-image: var(--jp-icon-undo); +} +.jp-VegaIcon { + background-image: var(--jp-icon-vega); +} +.jp-YamlIcon { + background-image: var(--jp-icon-yaml); +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/** + * (DEPRECATED) Support for consuming icons as CSS background images + */ + +:root { + --jp-icon-search-white: url(data:image/svg+xml;base64,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); +} + +.jp-Icon, +.jp-MaterialIcon { + background-position: center; + background-repeat: no-repeat; + background-size: 16px; + min-width: 16px; + min-height: 16px; +} + +.jp-Icon-cover { + background-position: center; + background-repeat: no-repeat; + background-size: cover; +} + +/** + * (DEPRECATED) Support for specific CSS icon sizes + */ + +.jp-Icon-16 { + background-size: 16px; + min-width: 16px; + min-height: 16px; +} + +.jp-Icon-18 { + background-size: 18px; + min-width: 18px; + min-height: 18px; +} + +.jp-Icon-20 { + background-size: 20px; + min-width: 20px; + min-height: 20px; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/** + * Support for icons as inline SVG HTMLElements + */ + +/* recolor the primary elements of an icon */ +.jp-icon0[fill] { + fill: var(--jp-inverse-layout-color0); +} +.jp-icon1[fill] { + fill: var(--jp-inverse-layout-color1); +} +.jp-icon2[fill] { + fill: var(--jp-inverse-layout-color2); +} +.jp-icon3[fill] { + fill: var(--jp-inverse-layout-color3); +} +.jp-icon4[fill] { + fill: var(--jp-inverse-layout-color4); +} + +.jp-icon0[stroke] { + stroke: var(--jp-inverse-layout-color0); +} +.jp-icon1[stroke] { + stroke: var(--jp-inverse-layout-color1); +} +.jp-icon2[stroke] { + stroke: var(--jp-inverse-layout-color2); +} +.jp-icon3[stroke] { + stroke: var(--jp-inverse-layout-color3); +} +.jp-icon4[stroke] { + stroke: var(--jp-inverse-layout-color4); +} +/* recolor the accent elements of an icon */ +.jp-icon-accent0[fill] { + fill: var(--jp-layout-color0); +} +.jp-icon-accent1[fill] { + fill: var(--jp-layout-color1); +} +.jp-icon-accent2[fill] { + fill: var(--jp-layout-color2); +} +.jp-icon-accent3[fill] { + fill: var(--jp-layout-color3); +} +.jp-icon-accent4[fill] { + fill: var(--jp-layout-color4); +} + +.jp-icon-accent0[stroke] { + stroke: var(--jp-layout-color0); +} +.jp-icon-accent1[stroke] { + stroke: var(--jp-layout-color1); +} +.jp-icon-accent2[stroke] { + stroke: var(--jp-layout-color2); +} +.jp-icon-accent3[stroke] { + stroke: var(--jp-layout-color3); +} +.jp-icon-accent4[stroke] { + stroke: var(--jp-layout-color4); +} +/* set the color of an icon to transparent */ +.jp-icon-none[fill] { + fill: none; +} + +.jp-icon-none[stroke] { + stroke: none; +} +/* brand icon colors. Same for light and dark */ +.jp-icon-brand0[fill] { + fill: var(--jp-brand-color0); +} +.jp-icon-brand1[fill] { + fill: var(--jp-brand-color1); +} +.jp-icon-brand2[fill] { + fill: var(--jp-brand-color2); +} +.jp-icon-brand3[fill] { + fill: var(--jp-brand-color3); +} +.jp-icon-brand4[fill] { + fill: var(--jp-brand-color4); +} + +.jp-icon-brand0[stroke] { + stroke: var(--jp-brand-color0); +} +.jp-icon-brand1[stroke] { + stroke: var(--jp-brand-color1); +} +.jp-icon-brand2[stroke] { + stroke: var(--jp-brand-color2); +} +.jp-icon-brand3[stroke] { + stroke: var(--jp-brand-color3); +} +.jp-icon-brand4[stroke] { + stroke: var(--jp-brand-color4); +} +/* warn icon colors. Same for light and dark */ +.jp-icon-warn0[fill] { + fill: var(--jp-warn-color0); +} +.jp-icon-warn1[fill] { + fill: var(--jp-warn-color1); +} +.jp-icon-warn2[fill] { + fill: var(--jp-warn-color2); +} +.jp-icon-warn3[fill] { + fill: var(--jp-warn-color3); +} + +.jp-icon-warn0[stroke] { + stroke: var(--jp-warn-color0); +} +.jp-icon-warn1[stroke] { + stroke: var(--jp-warn-color1); +} +.jp-icon-warn2[stroke] { + stroke: var(--jp-warn-color2); +} +.jp-icon-warn3[stroke] { + stroke: var(--jp-warn-color3); +} +/* icon colors that contrast well with each other and most backgrounds */ +.jp-icon-contrast0[fill] { + fill: var(--jp-icon-contrast-color0); +} +.jp-icon-contrast1[fill] { + fill: var(--jp-icon-contrast-color1); +} +.jp-icon-contrast2[fill] { + fill: var(--jp-icon-contrast-color2); +} +.jp-icon-contrast3[fill] { + fill: var(--jp-icon-contrast-color3); +} + +.jp-icon-contrast0[stroke] { + stroke: var(--jp-icon-contrast-color0); +} +.jp-icon-contrast1[stroke] { + stroke: var(--jp-icon-contrast-color1); +} +.jp-icon-contrast2[stroke] { + stroke: var(--jp-icon-contrast-color2); +} +.jp-icon-contrast3[stroke] { + stroke: var(--jp-icon-contrast-color3); +} + +/* CSS for icons in selected items in the settings editor */ +#setting-editor .jp-PluginList .jp-mod-selected .jp-icon-selectable[fill] { + fill: #fff; +} +#setting-editor + .jp-PluginList + .jp-mod-selected + .jp-icon-selectable-inverse[fill] { + fill: var(--jp-brand-color1); +} + +/* CSS for icons in selected filebrowser listing items */ +.jp-DirListing-item.jp-mod-selected .jp-icon-selectable[fill] { + fill: #fff; +} +.jp-DirListing-item.jp-mod-selected .jp-icon-selectable-inverse[fill] { + fill: var(--jp-brand-color1); +} + +/* CSS for icons in selected tabs in the sidebar tab manager */ +#tab-manager .lm-TabBar-tab.jp-mod-active .jp-icon-selectable[fill] { + fill: #fff; +} + +#tab-manager .lm-TabBar-tab.jp-mod-active .jp-icon-selectable-inverse[fill] { + fill: var(--jp-brand-color1); +} +#tab-manager + .lm-TabBar-tab.jp-mod-active + .jp-icon-hover + :hover + .jp-icon-selectable[fill] { + fill: var(--jp-brand-color1); +} + +#tab-manager + .lm-TabBar-tab.jp-mod-active + .jp-icon-hover + :hover + .jp-icon-selectable-inverse[fill] { + fill: #fff; +} + +/** + * TODO: come up with non css-hack solution for showing the busy icon on top + * of the close icon + * CSS for complex behavior of close icon of tabs in the sidebar tab manager + */ +#tab-manager + .lm-TabBar-tab.jp-mod-dirty + > .lm-TabBar-tabCloseIcon + > :not(:hover) + > .jp-icon3[fill] { + fill: none; +} +#tab-manager + .lm-TabBar-tab.jp-mod-dirty + > .lm-TabBar-tabCloseIcon + > :not(:hover) + > .jp-icon-busy[fill] { + fill: var(--jp-inverse-layout-color3); +} + +#tab-manager + .lm-TabBar-tab.jp-mod-dirty.jp-mod-active + > .lm-TabBar-tabCloseIcon + > :not(:hover) + > .jp-icon-busy[fill] { + fill: #fff; +} + +/** +* TODO: come up with non css-hack solution for showing the busy icon on top +* of the close icon +* CSS for complex behavior of close icon of tabs in the main area tabbar +*/ +.lm-DockPanel-tabBar + .lm-TabBar-tab.lm-mod-closable.jp-mod-dirty + > .lm-TabBar-tabCloseIcon + > :not(:hover) + > .jp-icon3[fill] { + fill: none; +} +.lm-DockPanel-tabBar + .lm-TabBar-tab.lm-mod-closable.jp-mod-dirty + > .lm-TabBar-tabCloseIcon + > :not(:hover) + > .jp-icon-busy[fill] { + fill: var(--jp-inverse-layout-color3); +} + +/* CSS for icons in status bar */ +#jp-main-statusbar .jp-mod-selected .jp-icon-selectable[fill] { + fill: #fff; +} + +#jp-main-statusbar .jp-mod-selected .jp-icon-selectable-inverse[fill] { + fill: var(--jp-brand-color1); +} +/* special handling for splash icon CSS. While the theme CSS reloads during + splash, the splash icon can loose theming. To prevent that, we set a + default for its color variable */ +:root { + --jp-warn-color0: var(--md-orange-700); +} + +/* not sure what to do with this one, used in filebrowser listing */ +.jp-DragIcon { + margin-right: 4px; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/** + * Support for alt colors for icons as inline SVG HTMLElements + */ + +/* alt recolor the primary elements of an icon */ +.jp-icon-alt .jp-icon0[fill] { + fill: var(--jp-layout-color0); +} +.jp-icon-alt .jp-icon1[fill] { + fill: var(--jp-layout-color1); +} +.jp-icon-alt .jp-icon2[fill] { + fill: var(--jp-layout-color2); +} +.jp-icon-alt .jp-icon3[fill] { + fill: var(--jp-layout-color3); +} +.jp-icon-alt .jp-icon4[fill] { + fill: var(--jp-layout-color4); +} + +.jp-icon-alt .jp-icon0[stroke] { + stroke: var(--jp-layout-color0); +} +.jp-icon-alt .jp-icon1[stroke] { + stroke: var(--jp-layout-color1); +} +.jp-icon-alt .jp-icon2[stroke] { + stroke: var(--jp-layout-color2); +} +.jp-icon-alt .jp-icon3[stroke] { + stroke: var(--jp-layout-color3); +} +.jp-icon-alt .jp-icon4[stroke] { + stroke: var(--jp-layout-color4); +} + +/* alt recolor the accent elements of an icon */ +.jp-icon-alt .jp-icon-accent0[fill] { + fill: var(--jp-inverse-layout-color0); +} +.jp-icon-alt .jp-icon-accent1[fill] { + fill: var(--jp-inverse-layout-color1); +} +.jp-icon-alt .jp-icon-accent2[fill] { + fill: var(--jp-inverse-layout-color2); +} +.jp-icon-alt .jp-icon-accent3[fill] { + fill: var(--jp-inverse-layout-color3); +} +.jp-icon-alt .jp-icon-accent4[fill] { + fill: var(--jp-inverse-layout-color4); +} + +.jp-icon-alt .jp-icon-accent0[stroke] { + stroke: var(--jp-inverse-layout-color0); +} +.jp-icon-alt .jp-icon-accent1[stroke] { + stroke: var(--jp-inverse-layout-color1); +} +.jp-icon-alt .jp-icon-accent2[stroke] { + stroke: var(--jp-inverse-layout-color2); +} +.jp-icon-alt .jp-icon-accent3[stroke] { + stroke: var(--jp-inverse-layout-color3); +} +.jp-icon-alt .jp-icon-accent4[stroke] { + stroke: var(--jp-inverse-layout-color4); +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +.jp-icon-hoverShow:not(:hover) svg { + display: none !important; +} + +/** + * Support for hover colors for icons as inline SVG HTMLElements + */ + +/** + * regular colors + */ + +/* recolor the primary elements of an icon */ +.jp-icon-hover :hover .jp-icon0-hover[fill] { + fill: var(--jp-inverse-layout-color0); +} +.jp-icon-hover :hover .jp-icon1-hover[fill] { + fill: var(--jp-inverse-layout-color1); +} +.jp-icon-hover :hover .jp-icon2-hover[fill] { + fill: var(--jp-inverse-layout-color2); +} +.jp-icon-hover :hover .jp-icon3-hover[fill] { + fill: var(--jp-inverse-layout-color3); +} +.jp-icon-hover :hover .jp-icon4-hover[fill] { + fill: var(--jp-inverse-layout-color4); +} + +.jp-icon-hover :hover .jp-icon0-hover[stroke] { + stroke: var(--jp-inverse-layout-color0); +} +.jp-icon-hover :hover .jp-icon1-hover[stroke] { + stroke: var(--jp-inverse-layout-color1); +} +.jp-icon-hover :hover .jp-icon2-hover[stroke] { + stroke: var(--jp-inverse-layout-color2); +} +.jp-icon-hover :hover .jp-icon3-hover[stroke] { + stroke: var(--jp-inverse-layout-color3); +} +.jp-icon-hover :hover .jp-icon4-hover[stroke] { + stroke: var(--jp-inverse-layout-color4); +} + +/* recolor the accent elements of an icon */ +.jp-icon-hover :hover .jp-icon-accent0-hover[fill] { + fill: var(--jp-layout-color0); +} +.jp-icon-hover :hover .jp-icon-accent1-hover[fill] { + fill: var(--jp-layout-color1); +} +.jp-icon-hover :hover .jp-icon-accent2-hover[fill] { + fill: var(--jp-layout-color2); +} +.jp-icon-hover :hover .jp-icon-accent3-hover[fill] { + fill: var(--jp-layout-color3); +} +.jp-icon-hover :hover .jp-icon-accent4-hover[fill] { + fill: var(--jp-layout-color4); +} + +.jp-icon-hover :hover .jp-icon-accent0-hover[stroke] { + stroke: var(--jp-layout-color0); +} +.jp-icon-hover :hover .jp-icon-accent1-hover[stroke] { + stroke: var(--jp-layout-color1); +} +.jp-icon-hover :hover .jp-icon-accent2-hover[stroke] { + stroke: var(--jp-layout-color2); +} +.jp-icon-hover :hover .jp-icon-accent3-hover[stroke] { + stroke: var(--jp-layout-color3); +} +.jp-icon-hover :hover .jp-icon-accent4-hover[stroke] { + stroke: var(--jp-layout-color4); +} + +/* set the color of an icon to transparent */ +.jp-icon-hover :hover .jp-icon-none-hover[fill] { + fill: none; +} + +.jp-icon-hover :hover .jp-icon-none-hover[stroke] { + stroke: none; +} + +/** + * inverse colors + */ + +/* inverse recolor the primary elements of an icon */ +.jp-icon-hover.jp-icon-alt :hover .jp-icon0-hover[fill] { + fill: var(--jp-layout-color0); +} +.jp-icon-hover.jp-icon-alt :hover .jp-icon1-hover[fill] { + fill: var(--jp-layout-color1); +} +.jp-icon-hover.jp-icon-alt :hover .jp-icon2-hover[fill] { + fill: var(--jp-layout-color2); +} +.jp-icon-hover.jp-icon-alt :hover .jp-icon3-hover[fill] { + fill: var(--jp-layout-color3); +} +.jp-icon-hover.jp-icon-alt :hover .jp-icon4-hover[fill] { + fill: var(--jp-layout-color4); +} + +.jp-icon-hover.jp-icon-alt :hover .jp-icon0-hover[stroke] { + stroke: var(--jp-layout-color0); +} +.jp-icon-hover.jp-icon-alt :hover .jp-icon1-hover[stroke] { + stroke: var(--jp-layout-color1); +} +.jp-icon-hover.jp-icon-alt :hover .jp-icon2-hover[stroke] { + stroke: var(--jp-layout-color2); +} +.jp-icon-hover.jp-icon-alt :hover .jp-icon3-hover[stroke] { + stroke: var(--jp-layout-color3); +} +.jp-icon-hover.jp-icon-alt :hover .jp-icon4-hover[stroke] { + stroke: var(--jp-layout-color4); +} + +/* inverse recolor the accent elements of an icon */ +.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent0-hover[fill] { + fill: var(--jp-inverse-layout-color0); +} +.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent1-hover[fill] { + fill: var(--jp-inverse-layout-color1); +} +.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent2-hover[fill] { + fill: var(--jp-inverse-layout-color2); +} +.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent3-hover[fill] { + fill: var(--jp-inverse-layout-color3); +} +.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent4-hover[fill] { + fill: var(--jp-inverse-layout-color4); +} + +.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent0-hover[stroke] { + stroke: var(--jp-inverse-layout-color0); +} +.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent1-hover[stroke] { + stroke: var(--jp-inverse-layout-color1); +} +.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent2-hover[stroke] { + stroke: var(--jp-inverse-layout-color2); +} +.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent3-hover[stroke] { + stroke: var(--jp-inverse-layout-color3); +} +.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent4-hover[stroke] { + stroke: var(--jp-inverse-layout-color4); +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/* Sibling imports */ + +/* Override Blueprint's _reset.scss styles */ +html { + box-sizing: unset; +} + +*, +*::before, +*::after { + box-sizing: unset; +} + +body { + color: unset; + font-family: var(--jp-ui-font-family); +} + +p { + margin-top: unset; + margin-bottom: unset; +} + +small { + font-size: unset; +} + +strong { + font-weight: unset; +} + +/* Override Blueprint's _typography.scss styles */ +a { + text-decoration: unset; + color: unset; +} +a:hover { + text-decoration: unset; + color: unset; +} + +/* Override Blueprint's _accessibility.scss styles */ +:focus { + outline: unset; + outline-offset: unset; + -moz-outline-radius: unset; +} + +/* Styles for ui-components */ +.jp-Button { + border-radius: var(--jp-border-radius); + padding: 0px 12px; + font-size: var(--jp-ui-font-size1); +} + +/* Use our own theme for hover styles */ +button.jp-Button.bp3-button.bp3-minimal:hover { + background-color: var(--jp-layout-color2); +} +.jp-Button.minimal { + color: unset !important; +} + +.jp-Button.jp-ToolbarButtonComponent { + text-transform: none; +} + +.jp-InputGroup input { + box-sizing: border-box; + border-radius: 0; + background-color: transparent; + color: var(--jp-ui-font-color0); + box-shadow: inset 0 0 0 var(--jp-border-width) var(--jp-input-border-color); +} + +.jp-InputGroup input:focus { + box-shadow: inset 0 0 0 var(--jp-border-width) + var(--jp-input-active-box-shadow-color), + inset 0 0 0 3px var(--jp-input-active-box-shadow-color); +} + +.jp-InputGroup input::placeholder, +input::placeholder { + color: var(--jp-ui-font-color3); +} + +.jp-BPIcon { + display: inline-block; + vertical-align: middle; + margin: auto; +} + +/* Stop blueprint futzing with our icon fills */ +.bp3-icon.jp-BPIcon > svg:not([fill]) { + fill: var(--jp-inverse-layout-color3); +} + +.jp-InputGroupAction { + padding: 6px; +} + +.jp-HTMLSelect.jp-DefaultStyle select { + background-color: initial; + border: none; + border-radius: 0; + box-shadow: none; + color: var(--jp-ui-font-color0); + display: block; + font-size: var(--jp-ui-font-size1); + height: 24px; + line-height: 14px; + padding: 0 25px 0 10px; + text-align: left; + -moz-appearance: none; + -webkit-appearance: none; +} + +/* Use our own theme for hover and option styles */ +.jp-HTMLSelect.jp-DefaultStyle select:hover, +.jp-HTMLSelect.jp-DefaultStyle select > option { + background-color: var(--jp-layout-color2); + color: var(--jp-ui-font-color0); +} +select { + box-sizing: border-box; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/* This file was auto-generated by ensurePackage() in @jupyterlab/buildutils */ + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +.jp-Collapse { + display: flex; + flex-direction: column; + align-items: stretch; + border-top: 1px solid var(--jp-border-color2); + border-bottom: 1px solid var(--jp-border-color2); +} + +.jp-Collapse-header { + padding: 1px 12px; + color: var(--jp-ui-font-color1); + background-color: var(--jp-layout-color1); + font-size: var(--jp-ui-font-size2); +} + +.jp-Collapse-header:hover { + background-color: var(--jp-layout-color2); +} + +.jp-Collapse-contents { + padding: 0px 12px 0px 12px; + background-color: var(--jp-layout-color1); + color: var(--jp-ui-font-color1); + overflow: auto; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/*----------------------------------------------------------------------------- +| Variables +|----------------------------------------------------------------------------*/ + +:root { + --jp-private-commandpalette-search-height: 28px; +} + +/*----------------------------------------------------------------------------- +| Overall styles +|----------------------------------------------------------------------------*/ + +.lm-CommandPalette { + padding-bottom: 0px; + color: var(--jp-ui-font-color1); + background: var(--jp-layout-color1); + /* This is needed so that all font sizing of children done in ems is + * relative to this base size */ + font-size: var(--jp-ui-font-size1); +} + +/*----------------------------------------------------------------------------- +| Search +|----------------------------------------------------------------------------*/ + +.lm-CommandPalette-search { + padding: 4px; + background-color: var(--jp-layout-color1); + z-index: 2; +} + +.lm-CommandPalette-wrapper { + overflow: overlay; + padding: 0px 9px; + background-color: var(--jp-input-active-background); + height: 30px; + box-shadow: inset 0 0 0 var(--jp-border-width) var(--jp-input-border-color); +} + +.lm-CommandPalette.lm-mod-focused .lm-CommandPalette-wrapper { + box-shadow: inset 0 0 0 1px var(--jp-input-active-box-shadow-color), + inset 0 0 0 3px var(--jp-input-active-box-shadow-color); +} + +.lm-CommandPalette-wrapper::after { + content: ' '; + color: white; + background-color: var(--jp-brand-color1); + position: absolute; + top: 4px; + right: 4px; + height: 30px; + width: 10px; + padding: 0px 10px; + background-image: var(--jp-icon-search-white); + background-size: 20px; + background-repeat: no-repeat; + background-position: center; +} + +.lm-CommandPalette-input { + background: transparent; + width: calc(100% - 18px); + float: left; + border: none; + outline: none; + font-size: var(--jp-ui-font-size1); + color: var(--jp-ui-font-color0); + line-height: var(--jp-private-commandpalette-search-height); +} + +.lm-CommandPalette-input::-webkit-input-placeholder, +.lm-CommandPalette-input::-moz-placeholder, +.lm-CommandPalette-input:-ms-input-placeholder { + color: var(--jp-ui-font-color3); + font-size: var(--jp-ui-font-size1); +} + +/*----------------------------------------------------------------------------- +| Results +|----------------------------------------------------------------------------*/ + +.lm-CommandPalette-header:first-child { + margin-top: 0px; +} + +.lm-CommandPalette-header { + border-bottom: solid var(--jp-border-width) var(--jp-border-color2); + color: var(--jp-ui-font-color1); + cursor: pointer; + display: flex; + font-size: var(--jp-ui-font-size0); + font-weight: 600; + letter-spacing: 1px; + margin-top: 8px; + padding: 8px 0 8px 12px; + text-transform: uppercase; +} + +.lm-CommandPalette-header.lm-mod-active { + background: var(--jp-layout-color2); +} + +.lm-CommandPalette-header > mark { + background-color: transparent; + font-weight: bold; + color: var(--jp-ui-font-color1); +} + +.lm-CommandPalette-item { + padding: 4px 12px 4px 4px; + color: var(--jp-ui-font-color1); + font-size: var(--jp-ui-font-size1); + font-weight: 400; + display: flex; +} + +.lm-CommandPalette-item.lm-mod-disabled { + color: var(--jp-ui-font-color3); +} + +.lm-CommandPalette-item.lm-mod-active { + background: var(--jp-layout-color3); +} + +.lm-CommandPalette-item.lm-mod-active:hover:not(.lm-mod-disabled) { + background: var(--jp-layout-color4); +} + +.lm-CommandPalette-item:hover:not(.lm-mod-active):not(.lm-mod-disabled) { + background: var(--jp-layout-color2); +} + +.lm-CommandPalette-itemContent { + overflow: hidden; +} + +.lm-CommandPalette-itemLabel > mark { + color: var(--jp-ui-font-color0); + background-color: transparent; + font-weight: bold; +} + +.lm-CommandPalette-item.lm-mod-disabled mark { + color: var(--jp-ui-font-color3); +} + +.lm-CommandPalette-item .lm-CommandPalette-itemIcon { + margin: 0 4px 0 0; + position: relative; + width: 16px; + top: 2px; + flex: 0 0 auto; +} + +.lm-CommandPalette-item.lm-mod-disabled .lm-CommandPalette-itemIcon { + opacity: 0.4; +} + +.lm-CommandPalette-item .lm-CommandPalette-itemShortcut { + flex: 0 0 auto; +} + +.lm-CommandPalette-itemCaption { + display: none; +} + +.lm-CommandPalette-content { + background-color: var(--jp-layout-color1); +} + +.lm-CommandPalette-content:empty:after { + content: 'No results'; + margin: auto; + margin-top: 20px; + width: 100px; + display: block; + font-size: var(--jp-ui-font-size2); + font-family: var(--jp-ui-font-family); + font-weight: lighter; +} + +.lm-CommandPalette-emptyMessage { + text-align: center; + margin-top: 24px; + line-height: 1.32; + padding: 0px 8px; + color: var(--jp-content-font-color3); +} + +/*----------------------------------------------------------------------------- +| Copyright (c) 2014-2017, Jupyter Development Team. +| +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +.jp-Dialog { + position: absolute; + z-index: 10000; + display: flex; + flex-direction: column; + align-items: center; + justify-content: center; + top: 0px; + left: 0px; + margin: 0; + padding: 0; + width: 100%; + height: 100%; + background: var(--jp-dialog-background); +} + +.jp-Dialog-content { + display: flex; + flex-direction: column; + margin-left: auto; + margin-right: auto; + background: var(--jp-layout-color1); + padding: 24px; + padding-bottom: 12px; + min-width: 300px; + min-height: 150px; + max-width: 1000px; + max-height: 500px; + box-sizing: border-box; + box-shadow: var(--jp-elevation-z20); + word-wrap: break-word; + border-radius: var(--jp-border-radius); + /* This is needed so that all font sizing of children done in ems is + * relative to this base size */ + font-size: var(--jp-ui-font-size1); + color: var(--jp-ui-font-color1); +} + +.jp-Dialog-button { + overflow: visible; +} + +button.jp-Dialog-button:focus { + outline: 1px solid var(--jp-brand-color1); + outline-offset: 4px; + -moz-outline-radius: 0px; +} + +button.jp-Dialog-button:focus::-moz-focus-inner { + border: 0; +} + +.jp-Dialog-header { + flex: 0 0 auto; + padding-bottom: 12px; + font-size: var(--jp-ui-font-size3); + font-weight: 400; + color: var(--jp-ui-font-color0); +} + +.jp-Dialog-body { + display: flex; + flex-direction: column; + flex: 1 1 auto; + font-size: var(--jp-ui-font-size1); + background: var(--jp-layout-color1); + overflow: auto; +} + +.jp-Dialog-footer { + display: flex; + flex-direction: row; + justify-content: flex-end; + flex: 0 0 auto; + margin-left: -12px; + margin-right: -12px; + padding: 12px; +} + +.jp-Dialog-title { + overflow: hidden; + white-space: nowrap; + text-overflow: ellipsis; +} + +.jp-Dialog-body > .jp-select-wrapper { + width: 100%; +} + +.jp-Dialog-body > button { + padding: 0px 16px; +} + +.jp-Dialog-body > label { + line-height: 1.4; + color: var(--jp-ui-font-color0); +} + +.jp-Dialog-button.jp-mod-styled:not(:last-child) { + margin-right: 12px; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) 2014-2016, Jupyter Development Team. +| +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +.jp-HoverBox { + position: fixed; +} + +.jp-HoverBox.jp-mod-outofview { + display: none; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +.jp-IFrame { + width: 100%; + height: 100%; +} + +.jp-IFrame > iframe { + border: none; +} + +/* +When drag events occur, `p-mod-override-cursor` is added to the body. +Because iframes steal all cursor events, the following two rules are necessary +to suppress pointer events while resize drags are occurring. There may be a +better solution to this problem. +*/ +body.lm-mod-override-cursor .jp-IFrame { + position: relative; +} + +body.lm-mod-override-cursor .jp-IFrame:before { + content: ''; + position: absolute; + top: 0; + left: 0; + right: 0; + bottom: 0; + background: transparent; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) 2014-2016, Jupyter Development Team. +| +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +.jp-MainAreaWidget > :focus { + outline: none; +} + +/** + * google-material-color v1.2.6 + * https://github.com/danlevan/google-material-color + */ +:root { + --md-red-50: #ffebee; + --md-red-100: #ffcdd2; + --md-red-200: #ef9a9a; + --md-red-300: #e57373; + --md-red-400: #ef5350; + --md-red-500: #f44336; + --md-red-600: #e53935; + --md-red-700: #d32f2f; + --md-red-800: #c62828; + --md-red-900: #b71c1c; + --md-red-A100: #ff8a80; + --md-red-A200: #ff5252; + --md-red-A400: #ff1744; + --md-red-A700: #d50000; + + --md-pink-50: #fce4ec; + --md-pink-100: #f8bbd0; + --md-pink-200: #f48fb1; + --md-pink-300: #f06292; + --md-pink-400: #ec407a; + --md-pink-500: #e91e63; + --md-pink-600: #d81b60; + --md-pink-700: #c2185b; + --md-pink-800: #ad1457; + --md-pink-900: #880e4f; + --md-pink-A100: #ff80ab; + --md-pink-A200: #ff4081; + --md-pink-A400: #f50057; + --md-pink-A700: #c51162; + + --md-purple-50: #f3e5f5; + --md-purple-100: #e1bee7; + --md-purple-200: #ce93d8; + --md-purple-300: #ba68c8; + --md-purple-400: #ab47bc; + --md-purple-500: #9c27b0; + --md-purple-600: #8e24aa; + --md-purple-700: #7b1fa2; + --md-purple-800: #6a1b9a; + --md-purple-900: #4a148c; + --md-purple-A100: #ea80fc; + --md-purple-A200: #e040fb; + --md-purple-A400: #d500f9; + --md-purple-A700: #aa00ff; + + --md-deep-purple-50: #ede7f6; + --md-deep-purple-100: #d1c4e9; + --md-deep-purple-200: #b39ddb; + --md-deep-purple-300: #9575cd; + --md-deep-purple-400: #7e57c2; + --md-deep-purple-500: #673ab7; + --md-deep-purple-600: #5e35b1; + --md-deep-purple-700: #512da8; + --md-deep-purple-800: #4527a0; + --md-deep-purple-900: #311b92; + --md-deep-purple-A100: #b388ff; + --md-deep-purple-A200: #7c4dff; + --md-deep-purple-A400: #651fff; + --md-deep-purple-A700: #6200ea; + + --md-indigo-50: #e8eaf6; + --md-indigo-100: #c5cae9; + --md-indigo-200: #9fa8da; + --md-indigo-300: #7986cb; + --md-indigo-400: #5c6bc0; + --md-indigo-500: #3f51b5; + --md-indigo-600: #3949ab; + --md-indigo-700: #303f9f; + --md-indigo-800: #283593; + --md-indigo-900: #1a237e; + --md-indigo-A100: #8c9eff; + --md-indigo-A200: #536dfe; + --md-indigo-A400: #3d5afe; + --md-indigo-A700: #304ffe; + + --md-blue-50: #e3f2fd; + --md-blue-100: #bbdefb; + --md-blue-200: #90caf9; + --md-blue-300: #64b5f6; + --md-blue-400: #42a5f5; + --md-blue-500: #2196f3; + --md-blue-600: #1e88e5; + --md-blue-700: #1976d2; + --md-blue-800: #1565c0; + --md-blue-900: #0d47a1; + --md-blue-A100: #82b1ff; + --md-blue-A200: #448aff; + --md-blue-A400: #2979ff; + --md-blue-A700: #2962ff; + + --md-light-blue-50: #e1f5fe; + --md-light-blue-100: #b3e5fc; + --md-light-blue-200: #81d4fa; + --md-light-blue-300: #4fc3f7; + --md-light-blue-400: #29b6f6; + --md-light-blue-500: #03a9f4; + --md-light-blue-600: #039be5; + --md-light-blue-700: #0288d1; + --md-light-blue-800: #0277bd; + --md-light-blue-900: #01579b; + --md-light-blue-A100: #80d8ff; + --md-light-blue-A200: #40c4ff; + --md-light-blue-A400: #00b0ff; + --md-light-blue-A700: #0091ea; + + --md-cyan-50: #e0f7fa; + --md-cyan-100: #b2ebf2; + --md-cyan-200: #80deea; + --md-cyan-300: #4dd0e1; + --md-cyan-400: #26c6da; + --md-cyan-500: #00bcd4; + --md-cyan-600: #00acc1; + --md-cyan-700: #0097a7; + --md-cyan-800: #00838f; + --md-cyan-900: #006064; + --md-cyan-A100: #84ffff; + --md-cyan-A200: #18ffff; + --md-cyan-A400: #00e5ff; + --md-cyan-A700: #00b8d4; + + --md-teal-50: #e0f2f1; + --md-teal-100: #b2dfdb; + --md-teal-200: #80cbc4; + --md-teal-300: #4db6ac; + --md-teal-400: #26a69a; + --md-teal-500: #009688; + --md-teal-600: #00897b; + --md-teal-700: #00796b; + --md-teal-800: #00695c; + --md-teal-900: #004d40; + --md-teal-A100: #a7ffeb; + --md-teal-A200: #64ffda; + --md-teal-A400: #1de9b6; + --md-teal-A700: #00bfa5; + + --md-green-50: #e8f5e9; + --md-green-100: #c8e6c9; + --md-green-200: #a5d6a7; + --md-green-300: #81c784; + --md-green-400: #66bb6a; + --md-green-500: #4caf50; + --md-green-600: #43a047; + --md-green-700: #388e3c; + --md-green-800: #2e7d32; + --md-green-900: #1b5e20; + --md-green-A100: #b9f6ca; + --md-green-A200: #69f0ae; + --md-green-A400: #00e676; + --md-green-A700: #00c853; + + --md-light-green-50: #f1f8e9; + --md-light-green-100: #dcedc8; + --md-light-green-200: #c5e1a5; + --md-light-green-300: #aed581; + --md-light-green-400: #9ccc65; + --md-light-green-500: #8bc34a; + --md-light-green-600: #7cb342; + --md-light-green-700: #689f38; + --md-light-green-800: #558b2f; + --md-light-green-900: #33691e; + --md-light-green-A100: #ccff90; + --md-light-green-A200: #b2ff59; + --md-light-green-A400: #76ff03; + --md-light-green-A700: #64dd17; + + --md-lime-50: #f9fbe7; + --md-lime-100: #f0f4c3; + --md-lime-200: #e6ee9c; + --md-lime-300: #dce775; + --md-lime-400: #d4e157; + --md-lime-500: #cddc39; + --md-lime-600: #c0ca33; + --md-lime-700: #afb42b; + --md-lime-800: #9e9d24; + --md-lime-900: #827717; + --md-lime-A100: #f4ff81; + --md-lime-A200: #eeff41; + --md-lime-A400: #c6ff00; + --md-lime-A700: #aeea00; + + --md-yellow-50: #fffde7; + --md-yellow-100: #fff9c4; + --md-yellow-200: #fff59d; + --md-yellow-300: #fff176; + --md-yellow-400: #ffee58; + --md-yellow-500: #ffeb3b; + --md-yellow-600: #fdd835; + --md-yellow-700: #fbc02d; + --md-yellow-800: #f9a825; + --md-yellow-900: #f57f17; + --md-yellow-A100: #ffff8d; + --md-yellow-A200: #ffff00; + --md-yellow-A400: #ffea00; + --md-yellow-A700: #ffd600; + + --md-amber-50: #fff8e1; + --md-amber-100: #ffecb3; + --md-amber-200: #ffe082; + --md-amber-300: #ffd54f; + --md-amber-400: #ffca28; + --md-amber-500: #ffc107; + --md-amber-600: #ffb300; + --md-amber-700: #ffa000; + --md-amber-800: #ff8f00; + --md-amber-900: #ff6f00; + --md-amber-A100: #ffe57f; + --md-amber-A200: #ffd740; + --md-amber-A400: #ffc400; + --md-amber-A700: #ffab00; + + --md-orange-50: #fff3e0; + --md-orange-100: #ffe0b2; + --md-orange-200: #ffcc80; + --md-orange-300: #ffb74d; + --md-orange-400: #ffa726; + --md-orange-500: #ff9800; + --md-orange-600: #fb8c00; + --md-orange-700: #f57c00; + --md-orange-800: #ef6c00; + --md-orange-900: #e65100; + --md-orange-A100: #ffd180; + --md-orange-A200: #ffab40; + --md-orange-A400: #ff9100; + --md-orange-A700: #ff6d00; + + --md-deep-orange-50: #fbe9e7; + --md-deep-orange-100: #ffccbc; + --md-deep-orange-200: #ffab91; + --md-deep-orange-300: #ff8a65; + --md-deep-orange-400: #ff7043; + --md-deep-orange-500: #ff5722; + --md-deep-orange-600: #f4511e; + --md-deep-orange-700: #e64a19; + --md-deep-orange-800: #d84315; + --md-deep-orange-900: #bf360c; + --md-deep-orange-A100: #ff9e80; + --md-deep-orange-A200: #ff6e40; + --md-deep-orange-A400: #ff3d00; + --md-deep-orange-A700: #dd2c00; + + --md-brown-50: #efebe9; + --md-brown-100: #d7ccc8; + --md-brown-200: #bcaaa4; + --md-brown-300: #a1887f; + --md-brown-400: #8d6e63; + --md-brown-500: #795548; + --md-brown-600: #6d4c41; + --md-brown-700: #5d4037; + --md-brown-800: #4e342e; + --md-brown-900: #3e2723; + + --md-grey-50: #fafafa; + --md-grey-100: #f5f5f5; + --md-grey-200: #eeeeee; + --md-grey-300: #e0e0e0; + --md-grey-400: #bdbdbd; + --md-grey-500: #9e9e9e; + --md-grey-600: #757575; + --md-grey-700: #616161; + --md-grey-800: #424242; + --md-grey-900: #212121; + + --md-blue-grey-50: #eceff1; + --md-blue-grey-100: #cfd8dc; + --md-blue-grey-200: #b0bec5; + --md-blue-grey-300: #90a4ae; + --md-blue-grey-400: #78909c; + --md-blue-grey-500: #607d8b; + --md-blue-grey-600: #546e7a; + --md-blue-grey-700: #455a64; + --md-blue-grey-800: #37474f; + --md-blue-grey-900: #263238; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) 2017, Jupyter Development Team. +| +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +.jp-Spinner { + position: absolute; + display: flex; + justify-content: center; + align-items: center; + z-index: 10; + left: 0; + top: 0; + width: 100%; + height: 100%; + background: var(--jp-layout-color0); + outline: none; +} + +.jp-SpinnerContent { + font-size: 10px; + margin: 50px auto; + text-indent: -9999em; + width: 3em; + height: 3em; + border-radius: 50%; + background: var(--jp-brand-color3); + background: linear-gradient( + to right, + #f37626 10%, + rgba(255, 255, 255, 0) 42% + ); + position: relative; + animation: load3 1s infinite linear, fadeIn 1s; +} + +.jp-SpinnerContent:before { + width: 50%; + height: 50%; + background: #f37626; + border-radius: 100% 0 0 0; + position: absolute; + top: 0; + left: 0; + content: ''; +} + +.jp-SpinnerContent:after { + background: var(--jp-layout-color0); + width: 75%; + height: 75%; + border-radius: 50%; + content: ''; + margin: auto; + position: absolute; + top: 0; + left: 0; + bottom: 0; + right: 0; +} + +@keyframes fadeIn { + 0% { + opacity: 0; + } + 100% { + opacity: 1; + } +} + +@keyframes load3 { + 0% { + transform: rotate(0deg); + } + 100% { + transform: rotate(360deg); + } +} + +/*----------------------------------------------------------------------------- +| Copyright (c) 2014-2017, Jupyter Development Team. +| +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +button.jp-mod-styled { + font-size: var(--jp-ui-font-size1); + color: var(--jp-ui-font-color0); + border: none; + box-sizing: border-box; + text-align: center; + line-height: 32px; + height: 32px; + padding: 0px 12px; + letter-spacing: 0.8px; + outline: none; + appearance: none; + -webkit-appearance: none; + -moz-appearance: none; +} + +input.jp-mod-styled { + background: var(--jp-input-background); + height: 28px; + box-sizing: border-box; + border: var(--jp-border-width) solid var(--jp-border-color1); + padding-left: 7px; + padding-right: 7px; + font-size: var(--jp-ui-font-size2); + color: var(--jp-ui-font-color0); + outline: none; + appearance: none; + -webkit-appearance: none; + -moz-appearance: none; +} + +input.jp-mod-styled:focus { + border: var(--jp-border-width) solid var(--md-blue-500); + box-shadow: inset 0 0 4px var(--md-blue-300); +} + +.jp-select-wrapper { + display: flex; + position: relative; + flex-direction: column; + padding: 1px; + background-color: var(--jp-layout-color1); + height: 28px; + box-sizing: border-box; + margin-bottom: 12px; +} + +.jp-select-wrapper.jp-mod-focused select.jp-mod-styled { + border: var(--jp-border-width) solid var(--jp-input-active-border-color); + box-shadow: var(--jp-input-box-shadow); + background-color: var(--jp-input-active-background); +} + +select.jp-mod-styled:hover { + background-color: var(--jp-layout-color1); + cursor: pointer; + color: var(--jp-ui-font-color0); + background-color: var(--jp-input-hover-background); + box-shadow: inset 0 0px 1px rgba(0, 0, 0, 0.5); +} + +select.jp-mod-styled { + flex: 1 1 auto; + height: 32px; + width: 100%; + font-size: var(--jp-ui-font-size2); + background: var(--jp-input-background); + color: var(--jp-ui-font-color0); + padding: 0 25px 0 8px; + border: var(--jp-border-width) solid var(--jp-input-border-color); + border-radius: 0px; + outline: none; + appearance: none; + -webkit-appearance: none; + -moz-appearance: none; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) 2014-2016, Jupyter Development Team. +| +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +:root { + --jp-private-toolbar-height: calc( + 28px + var(--jp-border-width) + ); /* leave 28px for content */ +} + +.jp-Toolbar { + color: var(--jp-ui-font-color1); + flex: 0 0 auto; + display: flex; + flex-direction: row; + border-bottom: var(--jp-border-width) solid var(--jp-toolbar-border-color); + box-shadow: var(--jp-toolbar-box-shadow); + background: var(--jp-toolbar-background); + min-height: var(--jp-toolbar-micro-height); + padding: 2px; + z-index: 1; +} + +/* Toolbar items */ + +.jp-Toolbar > .jp-Toolbar-item.jp-Toolbar-spacer { + flex-grow: 1; + flex-shrink: 1; +} + +.jp-Toolbar-item.jp-Toolbar-kernelStatus { + display: inline-block; + width: 32px; + background-repeat: no-repeat; + background-position: center; + background-size: 16px; +} + +.jp-Toolbar > .jp-Toolbar-item { + flex: 0 0 auto; + display: flex; + padding-left: 1px; + padding-right: 1px; + font-size: var(--jp-ui-font-size1); + line-height: var(--jp-private-toolbar-height); + height: 100%; +} + +/* Toolbar buttons */ + +/* This is the div we use to wrap the react component into a Widget */ +div.jp-ToolbarButton { + color: transparent; + border: none; + box-sizing: border-box; + outline: none; + appearance: none; + -webkit-appearance: none; + -moz-appearance: none; + padding: 0px; + margin: 0px; +} + +button.jp-ToolbarButtonComponent { + background: var(--jp-layout-color1); + border: none; + box-sizing: border-box; + outline: none; + appearance: none; + -webkit-appearance: none; + -moz-appearance: none; + padding: 0px 6px; + margin: 0px; + height: 24px; + border-radius: var(--jp-border-radius); + display: flex; + align-items: center; + text-align: center; + font-size: 14px; + min-width: unset; + min-height: unset; +} + +button.jp-ToolbarButtonComponent:disabled { + opacity: 0.4; +} + +button.jp-ToolbarButtonComponent span { + padding: 0px; + flex: 0 0 auto; +} + +button.jp-ToolbarButtonComponent .jp-ToolbarButtonComponent-label { + font-size: var(--jp-ui-font-size1); + line-height: 100%; + padding-left: 2px; + color: var(--jp-ui-font-color1); +} + +/*----------------------------------------------------------------------------- +| Copyright (c) 2014-2017, Jupyter Development Team. +| +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/* This file was auto-generated by ensurePackage() in @jupyterlab/buildutils */ + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Copyright (c) 2014-2017, PhosphorJS Contributors +| +| Distributed under the terms of the BSD 3-Clause License. +| +| The full license is in the file LICENSE, distributed with this software. +|----------------------------------------------------------------------------*/ + + +/* <DEPRECATED> */ body.p-mod-override-cursor *, /* </DEPRECATED> */ +body.lm-mod-override-cursor * { + cursor: inherit !important; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) 2014-2016, Jupyter Development Team. +| +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +.jp-JSONEditor { + display: flex; + flex-direction: column; + width: 100%; +} + +.jp-JSONEditor-host { + flex: 1 1 auto; + border: var(--jp-border-width) solid var(--jp-input-border-color); + border-radius: 0px; + background: var(--jp-layout-color0); + min-height: 50px; + padding: 1px; +} + +.jp-JSONEditor.jp-mod-error .jp-JSONEditor-host { + border-color: red; + outline-color: red; +} + +.jp-JSONEditor-header { + display: flex; + flex: 1 0 auto; + padding: 0 0 0 12px; +} + +.jp-JSONEditor-header label { + flex: 0 0 auto; +} + +.jp-JSONEditor-commitButton { + height: 16px; + width: 16px; + background-size: 18px; + background-repeat: no-repeat; + background-position: center; +} + +.jp-JSONEditor-host.jp-mod-focused { + background-color: var(--jp-input-active-background); + border: 1px solid var(--jp-input-active-border-color); + box-shadow: var(--jp-input-box-shadow); +} + +.jp-Editor.jp-mod-dropTarget { + border: var(--jp-border-width) solid var(--jp-input-active-border-color); + box-shadow: var(--jp-input-box-shadow); +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/* This file was auto-generated by ensurePackage() in @jupyterlab/buildutils */ + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/* BASICS */ + +.CodeMirror { + /* Set height, width, borders, and global font properties here */ + font-family: monospace; + height: 300px; + color: black; + direction: ltr; +} + +/* PADDING */ + +.CodeMirror-lines { + padding: 4px 0; /* Vertical padding around content */ +} +.CodeMirror pre.CodeMirror-line, +.CodeMirror pre.CodeMirror-line-like { + padding: 0 4px; /* Horizontal padding of content */ +} + +.CodeMirror-scrollbar-filler, .CodeMirror-gutter-filler { + background-color: white; /* The little square between H and V scrollbars */ +} + +/* GUTTER */ + +.CodeMirror-gutters { + border-right: 1px solid #ddd; + background-color: #f7f7f7; + white-space: nowrap; +} +.CodeMirror-linenumbers {} +.CodeMirror-linenumber { + padding: 0 3px 0 5px; + min-width: 20px; + text-align: right; + color: #999; + white-space: nowrap; +} + +.CodeMirror-guttermarker { color: black; } +.CodeMirror-guttermarker-subtle { color: #999; } + +/* CURSOR */ + +.CodeMirror-cursor { + border-left: 1px solid black; + border-right: none; + width: 0; +} +/* Shown when moving in bi-directional text */ +.CodeMirror div.CodeMirror-secondarycursor { + border-left: 1px solid silver; +} +.cm-fat-cursor .CodeMirror-cursor { + width: auto; + border: 0 !important; + background: #7e7; +} +.cm-fat-cursor div.CodeMirror-cursors { + z-index: 1; +} +.cm-fat-cursor-mark { + background-color: rgba(20, 255, 20, 0.5); + -webkit-animation: blink 1.06s steps(1) infinite; + -moz-animation: blink 1.06s steps(1) infinite; + animation: blink 1.06s steps(1) infinite; +} +.cm-animate-fat-cursor { + width: auto; + border: 0; + -webkit-animation: blink 1.06s steps(1) infinite; + -moz-animation: blink 1.06s steps(1) infinite; + animation: blink 1.06s steps(1) infinite; + background-color: #7e7; +} +@-moz-keyframes blink { + 0% {} + 50% { background-color: transparent; } + 100% {} +} +@-webkit-keyframes blink { + 0% {} + 50% { background-color: transparent; } + 100% {} +} +@keyframes blink { + 0% {} + 50% { background-color: transparent; } + 100% {} +} + +/* Can style cursor different in overwrite (non-insert) mode */ +.CodeMirror-overwrite .CodeMirror-cursor {} + +.cm-tab { display: inline-block; text-decoration: inherit; } + +.CodeMirror-rulers { + position: absolute; + left: 0; right: 0; top: -50px; bottom: 0; + overflow: hidden; +} +.CodeMirror-ruler { + border-left: 1px solid #ccc; + top: 0; bottom: 0; + position: absolute; +} + +/* DEFAULT THEME */ + +.cm-s-default .cm-header {color: blue;} +.cm-s-default .cm-quote {color: #090;} +.cm-negative {color: #d44;} +.cm-positive {color: #292;} +.cm-header, .cm-strong {font-weight: bold;} +.cm-em {font-style: italic;} +.cm-link {text-decoration: underline;} +.cm-strikethrough {text-decoration: line-through;} + +.cm-s-default .cm-keyword {color: #708;} +.cm-s-default .cm-atom {color: #219;} +.cm-s-default .cm-number {color: #164;} +.cm-s-default .cm-def {color: #00f;} +.cm-s-default .cm-variable, +.cm-s-default .cm-punctuation, +.cm-s-default .cm-property, +.cm-s-default .cm-operator {} +.cm-s-default .cm-variable-2 {color: #05a;} +.cm-s-default .cm-variable-3, .cm-s-default .cm-type {color: #085;} +.cm-s-default .cm-comment {color: #a50;} +.cm-s-default .cm-string {color: #a11;} +.cm-s-default .cm-string-2 {color: #f50;} +.cm-s-default .cm-meta {color: #555;} +.cm-s-default .cm-qualifier {color: #555;} +.cm-s-default .cm-builtin {color: #30a;} +.cm-s-default .cm-bracket {color: #997;} +.cm-s-default .cm-tag {color: #170;} +.cm-s-default .cm-attribute {color: #00c;} +.cm-s-default .cm-hr {color: #999;} +.cm-s-default .cm-link {color: #00c;} + +.cm-s-default .cm-error {color: #f00;} +.cm-invalidchar {color: #f00;} + +.CodeMirror-composing { border-bottom: 2px solid; } + +/* Default styles for common addons */ + +div.CodeMirror span.CodeMirror-matchingbracket {color: #0b0;} +div.CodeMirror span.CodeMirror-nonmatchingbracket {color: #a22;} +.CodeMirror-matchingtag { background: rgba(255, 150, 0, .3); } +.CodeMirror-activeline-background {background: #e8f2ff;} + +/* STOP */ + +/* The rest of this file contains styles related to the mechanics of + the editor. You probably shouldn't touch them. */ + +.CodeMirror { + position: relative; + overflow: hidden; + background: white; +} + +.CodeMirror-scroll { + overflow: scroll !important; /* Things will break if this is overridden */ + /* 30px is the magic margin used to hide the element's real scrollbars */ + /* See overflow: hidden in .CodeMirror */ + margin-bottom: -30px; margin-right: -30px; + padding-bottom: 30px; + height: 100%; + outline: none; /* Prevent dragging from highlighting the element */ + position: relative; +} +.CodeMirror-sizer { + position: relative; + border-right: 30px solid transparent; +} + +/* The fake, visible scrollbars. Used to force redraw during scrolling + before actual scrolling happens, thus preventing shaking and + flickering artifacts. */ +.CodeMirror-vscrollbar, .CodeMirror-hscrollbar, .CodeMirror-scrollbar-filler, .CodeMirror-gutter-filler { + position: absolute; + z-index: 6; + display: none; +} +.CodeMirror-vscrollbar { + right: 0; top: 0; + overflow-x: hidden; + overflow-y: scroll; +} +.CodeMirror-hscrollbar { + bottom: 0; left: 0; + overflow-y: hidden; + overflow-x: scroll; +} +.CodeMirror-scrollbar-filler { + right: 0; bottom: 0; +} +.CodeMirror-gutter-filler { + left: 0; bottom: 0; +} + +.CodeMirror-gutters { + position: absolute; left: 0; top: 0; + min-height: 100%; + z-index: 3; +} +.CodeMirror-gutter { + white-space: normal; + height: 100%; + display: inline-block; + vertical-align: top; + margin-bottom: -30px; +} +.CodeMirror-gutter-wrapper { + position: absolute; + z-index: 4; + background: none !important; + border: none !important; +} +.CodeMirror-gutter-background { + position: absolute; + top: 0; bottom: 0; + z-index: 4; +} +.CodeMirror-gutter-elt { + position: absolute; + cursor: default; + z-index: 4; +} +.CodeMirror-gutter-wrapper ::selection { background-color: transparent } +.CodeMirror-gutter-wrapper ::-moz-selection { background-color: transparent } + +.CodeMirror-lines { + cursor: text; + min-height: 1px; /* prevents collapsing before first draw */ +} +.CodeMirror pre.CodeMirror-line, +.CodeMirror pre.CodeMirror-line-like { + /* Reset some styles that the rest of the page might have set */ + -moz-border-radius: 0; -webkit-border-radius: 0; border-radius: 0; + border-width: 0; + background: transparent; + font-family: inherit; + font-size: inherit; + margin: 0; + white-space: pre; + word-wrap: normal; + line-height: inherit; + color: inherit; + z-index: 2; + position: relative; + overflow: visible; + -webkit-tap-highlight-color: transparent; + -webkit-font-variant-ligatures: contextual; + font-variant-ligatures: contextual; +} +.CodeMirror-wrap pre.CodeMirror-line, +.CodeMirror-wrap pre.CodeMirror-line-like { + word-wrap: break-word; + white-space: pre-wrap; + word-break: normal; +} + +.CodeMirror-linebackground { + position: absolute; + left: 0; right: 0; top: 0; bottom: 0; + z-index: 0; +} + +.CodeMirror-linewidget { + position: relative; + z-index: 2; + padding: 0.1px; /* Force widget margins to stay inside of the container */ +} + +.CodeMirror-widget {} + +.CodeMirror-rtl pre { direction: rtl; } + +.CodeMirror-code { + outline: none; +} + +/* Force content-box sizing for the elements where we expect it */ +.CodeMirror-scroll, +.CodeMirror-sizer, +.CodeMirror-gutter, +.CodeMirror-gutters, +.CodeMirror-linenumber { + -moz-box-sizing: content-box; + box-sizing: content-box; +} + +.CodeMirror-measure { + position: absolute; + width: 100%; + height: 0; + overflow: hidden; + visibility: hidden; +} + +.CodeMirror-cursor { + position: absolute; + pointer-events: none; +} +.CodeMirror-measure pre { position: static; } + +div.CodeMirror-cursors { + visibility: hidden; + position: relative; + z-index: 3; +} +div.CodeMirror-dragcursors { + visibility: visible; +} + +.CodeMirror-focused div.CodeMirror-cursors { + visibility: visible; +} + +.CodeMirror-selected { background: #d9d9d9; } +.CodeMirror-focused .CodeMirror-selected { background: #d7d4f0; } +.CodeMirror-crosshair { cursor: crosshair; } +.CodeMirror-line::selection, .CodeMirror-line > span::selection, .CodeMirror-line > span > span::selection { background: #d7d4f0; } +.CodeMirror-line::-moz-selection, .CodeMirror-line > span::-moz-selection, .CodeMirror-line > span > span::-moz-selection { background: #d7d4f0; } + +.cm-searching { + background-color: #ffa; + background-color: rgba(255, 255, 0, .4); +} + +/* Used to force a border model for a node */ +.cm-force-border { padding-right: .1px; } + +@media print { + /* Hide the cursor when printing */ + .CodeMirror div.CodeMirror-cursors { + visibility: hidden; + } +} + +/* See issue #2901 */ +.cm-tab-wrap-hack:after { content: ''; } + +/* Help users use markselection to safely style text background */ +span.CodeMirror-selectedtext { background: none; } + +.CodeMirror-dialog { + position: absolute; + left: 0; right: 0; + background: inherit; + z-index: 15; + padding: .1em .8em; + overflow: hidden; + color: inherit; +} + +.CodeMirror-dialog-top { + border-bottom: 1px solid #eee; + top: 0; +} + +.CodeMirror-dialog-bottom { + border-top: 1px solid #eee; + bottom: 0; +} + +.CodeMirror-dialog input { + border: none; + outline: none; + background: transparent; + width: 20em; + color: inherit; + font-family: monospace; +} + +.CodeMirror-dialog button { + font-size: 70%; +} + +.CodeMirror-foldmarker { + color: blue; + text-shadow: #b9f 1px 1px 2px, #b9f -1px -1px 2px, #b9f 1px -1px 2px, #b9f -1px 1px 2px; + font-family: arial; + line-height: .3; + cursor: pointer; +} +.CodeMirror-foldgutter { + width: .7em; +} +.CodeMirror-foldgutter-open, +.CodeMirror-foldgutter-folded { + cursor: pointer; +} +.CodeMirror-foldgutter-open:after { + content: "\25BE"; +} +.CodeMirror-foldgutter-folded:after { + content: "\25B8"; +} + +/* + Name: material + Author: Mattia Astorino (http://github.com/equinusocio) + Website: https://material-theme.site/ +*/ + +.cm-s-material.CodeMirror { + background-color: #263238; + color: #EEFFFF; +} + +.cm-s-material .CodeMirror-gutters { + background: #263238; + color: #546E7A; + border: none; +} + +.cm-s-material .CodeMirror-guttermarker, +.cm-s-material .CodeMirror-guttermarker-subtle, +.cm-s-material .CodeMirror-linenumber { + color: #546E7A; +} + +.cm-s-material .CodeMirror-cursor { + border-left: 1px solid #FFCC00; +} + +.cm-s-material div.CodeMirror-selected { + background: rgba(128, 203, 196, 0.2); +} + +.cm-s-material.CodeMirror-focused div.CodeMirror-selected { + background: rgba(128, 203, 196, 0.2); +} + +.cm-s-material .CodeMirror-line::selection, +.cm-s-material .CodeMirror-line>span::selection, +.cm-s-material .CodeMirror-line>span>span::selection { + background: rgba(128, 203, 196, 0.2); +} + +.cm-s-material .CodeMirror-line::-moz-selection, +.cm-s-material .CodeMirror-line>span::-moz-selection, +.cm-s-material .CodeMirror-line>span>span::-moz-selection { + background: rgba(128, 203, 196, 0.2); +} + +.cm-s-material .CodeMirror-activeline-background { + background: rgba(0, 0, 0, 0.5); +} + +.cm-s-material .cm-keyword { + color: #C792EA; +} + +.cm-s-material .cm-operator { + color: #89DDFF; +} + +.cm-s-material .cm-variable-2 { + color: #EEFFFF; +} + +.cm-s-material .cm-variable-3, +.cm-s-material .cm-type { + color: #f07178; +} + +.cm-s-material .cm-builtin { + color: #FFCB6B; +} + +.cm-s-material .cm-atom { + color: #F78C6C; +} + +.cm-s-material .cm-number { + color: #FF5370; +} + +.cm-s-material .cm-def { + color: #82AAFF; +} + +.cm-s-material .cm-string { + color: #C3E88D; +} + +.cm-s-material .cm-string-2 { + color: #f07178; +} + +.cm-s-material .cm-comment { + color: #546E7A; +} + +.cm-s-material .cm-variable { + color: #f07178; +} + +.cm-s-material .cm-tag { + color: #FF5370; +} + +.cm-s-material .cm-meta { + color: #FFCB6B; +} + +.cm-s-material .cm-attribute { + color: #C792EA; +} + +.cm-s-material .cm-property { + color: #C792EA; +} + +.cm-s-material .cm-qualifier { + color: #DECB6B; +} + +.cm-s-material .cm-variable-3, +.cm-s-material .cm-type { + color: #DECB6B; +} + + +.cm-s-material .cm-error { + color: rgba(255, 255, 255, 1.0); + background-color: #FF5370; +} + +.cm-s-material .CodeMirror-matchingbracket { + text-decoration: underline; + color: white !important; +} +/** + * " + * Using Zenburn color palette from the Emacs Zenburn Theme + * https://github.com/bbatsov/zenburn-emacs/blob/master/zenburn-theme.el + * + * Also using parts of https://github.com/xavi/coderay-lighttable-theme + * " + * From: https://github.com/wisenomad/zenburn-lighttable-theme/blob/master/zenburn.css + */ + +.cm-s-zenburn .CodeMirror-gutters { background: #3f3f3f !important; } +.cm-s-zenburn .CodeMirror-foldgutter-open, .CodeMirror-foldgutter-folded { color: #999; } +.cm-s-zenburn .CodeMirror-cursor { border-left: 1px solid white; } +.cm-s-zenburn { background-color: #3f3f3f; color: #dcdccc; } +.cm-s-zenburn span.cm-builtin { color: #dcdccc; font-weight: bold; } +.cm-s-zenburn span.cm-comment { color: #7f9f7f; } +.cm-s-zenburn span.cm-keyword { color: #f0dfaf; font-weight: bold; } +.cm-s-zenburn span.cm-atom { color: #bfebbf; } +.cm-s-zenburn span.cm-def { color: #dcdccc; } +.cm-s-zenburn span.cm-variable { color: #dfaf8f; } +.cm-s-zenburn span.cm-variable-2 { color: #dcdccc; } +.cm-s-zenburn span.cm-string { color: #cc9393; } +.cm-s-zenburn span.cm-string-2 { color: #cc9393; } +.cm-s-zenburn span.cm-number { color: #dcdccc; } +.cm-s-zenburn span.cm-tag { color: #93e0e3; } +.cm-s-zenburn span.cm-property { color: #dfaf8f; } +.cm-s-zenburn span.cm-attribute { color: #dfaf8f; } +.cm-s-zenburn span.cm-qualifier { color: #7cb8bb; } +.cm-s-zenburn span.cm-meta { color: #f0dfaf; } +.cm-s-zenburn span.cm-header { color: #f0efd0; } +.cm-s-zenburn span.cm-operator { color: #f0efd0; } +.cm-s-zenburn span.CodeMirror-matchingbracket { box-sizing: border-box; background: transparent; border-bottom: 1px solid; } +.cm-s-zenburn span.CodeMirror-nonmatchingbracket { border-bottom: 1px solid; background: none; } +.cm-s-zenburn .CodeMirror-activeline { background: #000000; } +.cm-s-zenburn .CodeMirror-activeline-background { background: #000000; } +.cm-s-zenburn div.CodeMirror-selected { background: #545454; } +.cm-s-zenburn .CodeMirror-focused div.CodeMirror-selected { background: #4f4f4f; } + +.cm-s-abcdef.CodeMirror { background: #0f0f0f; color: #defdef; } +.cm-s-abcdef div.CodeMirror-selected { background: #515151; } +.cm-s-abcdef .CodeMirror-line::selection, .cm-s-abcdef .CodeMirror-line > span::selection, .cm-s-abcdef .CodeMirror-line > span > span::selection { background: rgba(56, 56, 56, 0.99); } +.cm-s-abcdef .CodeMirror-line::-moz-selection, .cm-s-abcdef .CodeMirror-line > span::-moz-selection, .cm-s-abcdef .CodeMirror-line > span > span::-moz-selection { background: rgba(56, 56, 56, 0.99); } +.cm-s-abcdef .CodeMirror-gutters { background: #555; border-right: 2px solid #314151; } +.cm-s-abcdef .CodeMirror-guttermarker { color: #222; } +.cm-s-abcdef .CodeMirror-guttermarker-subtle { color: azure; } +.cm-s-abcdef .CodeMirror-linenumber { color: #FFFFFF; } +.cm-s-abcdef .CodeMirror-cursor { border-left: 1px solid #00FF00; } + +.cm-s-abcdef span.cm-keyword { color: darkgoldenrod; font-weight: bold; } +.cm-s-abcdef span.cm-atom { color: #77F; } +.cm-s-abcdef span.cm-number { color: violet; } +.cm-s-abcdef span.cm-def { color: #fffabc; } +.cm-s-abcdef span.cm-variable { color: #abcdef; } +.cm-s-abcdef span.cm-variable-2 { color: #cacbcc; } +.cm-s-abcdef span.cm-variable-3, .cm-s-abcdef span.cm-type { color: #def; } +.cm-s-abcdef span.cm-property { color: #fedcba; } +.cm-s-abcdef span.cm-operator { color: #ff0; } +.cm-s-abcdef span.cm-comment { color: #7a7b7c; font-style: italic;} +.cm-s-abcdef span.cm-string { color: #2b4; } +.cm-s-abcdef span.cm-meta { color: #C9F; } +.cm-s-abcdef span.cm-qualifier { color: #FFF700; } +.cm-s-abcdef span.cm-builtin { color: #30aabc; } +.cm-s-abcdef span.cm-bracket { color: #8a8a8a; } +.cm-s-abcdef span.cm-tag { color: #FFDD44; } +.cm-s-abcdef span.cm-attribute { color: #DDFF00; } +.cm-s-abcdef span.cm-error { color: #FF0000; } +.cm-s-abcdef span.cm-header { color: aquamarine; font-weight: bold; } +.cm-s-abcdef span.cm-link { color: blueviolet; } + +.cm-s-abcdef .CodeMirror-activeline-background { background: #314151; } + +/* + + Name: Base16 Default Light + Author: Chris Kempson (http://chriskempson.com) + + CodeMirror template by Jan T. Sott (https://github.com/idleberg/base16-codemirror) + Original Base16 color scheme by Chris Kempson (https://github.com/chriskempson/base16) + +*/ + +.cm-s-base16-light.CodeMirror { background: #f5f5f5; color: #202020; } +.cm-s-base16-light div.CodeMirror-selected { background: #e0e0e0; } +.cm-s-base16-light .CodeMirror-line::selection, .cm-s-base16-light .CodeMirror-line > span::selection, .cm-s-base16-light .CodeMirror-line > span > span::selection { background: #e0e0e0; } +.cm-s-base16-light .CodeMirror-line::-moz-selection, .cm-s-base16-light .CodeMirror-line > span::-moz-selection, .cm-s-base16-light .CodeMirror-line > span > span::-moz-selection { background: #e0e0e0; } +.cm-s-base16-light .CodeMirror-gutters { background: #f5f5f5; border-right: 0px; } +.cm-s-base16-light .CodeMirror-guttermarker { color: #ac4142; } +.cm-s-base16-light .CodeMirror-guttermarker-subtle { color: #b0b0b0; } +.cm-s-base16-light .CodeMirror-linenumber { color: #b0b0b0; } +.cm-s-base16-light .CodeMirror-cursor { border-left: 1px solid #505050; } + +.cm-s-base16-light span.cm-comment { color: #8f5536; } +.cm-s-base16-light span.cm-atom { color: #aa759f; } +.cm-s-base16-light span.cm-number { color: #aa759f; } + +.cm-s-base16-light span.cm-property, .cm-s-base16-light span.cm-attribute { color: #90a959; } +.cm-s-base16-light span.cm-keyword { color: #ac4142; } +.cm-s-base16-light span.cm-string { color: #f4bf75; } + +.cm-s-base16-light span.cm-variable { color: #90a959; } +.cm-s-base16-light span.cm-variable-2 { color: #6a9fb5; } +.cm-s-base16-light span.cm-def { color: #d28445; } +.cm-s-base16-light span.cm-bracket { color: #202020; } +.cm-s-base16-light span.cm-tag { color: #ac4142; } +.cm-s-base16-light span.cm-link { color: #aa759f; } +.cm-s-base16-light span.cm-error { background: #ac4142; color: #505050; } + +.cm-s-base16-light .CodeMirror-activeline-background { background: #DDDCDC; } +.cm-s-base16-light .CodeMirror-matchingbracket { color: #f5f5f5 !important; background-color: #6A9FB5 !important} + +/* + + Name: Base16 Default Dark + Author: Chris Kempson (http://chriskempson.com) + + CodeMirror template by Jan T. Sott (https://github.com/idleberg/base16-codemirror) + Original Base16 color scheme by Chris Kempson (https://github.com/chriskempson/base16) + +*/ + +.cm-s-base16-dark.CodeMirror { background: #151515; color: #e0e0e0; } +.cm-s-base16-dark div.CodeMirror-selected { background: #303030; } +.cm-s-base16-dark .CodeMirror-line::selection, .cm-s-base16-dark .CodeMirror-line > span::selection, .cm-s-base16-dark .CodeMirror-line > span > span::selection { background: rgba(48, 48, 48, .99); } +.cm-s-base16-dark .CodeMirror-line::-moz-selection, .cm-s-base16-dark .CodeMirror-line > span::-moz-selection, .cm-s-base16-dark .CodeMirror-line > span > span::-moz-selection { background: rgba(48, 48, 48, .99); } +.cm-s-base16-dark .CodeMirror-gutters { background: #151515; border-right: 0px; } +.cm-s-base16-dark .CodeMirror-guttermarker { color: #ac4142; } +.cm-s-base16-dark .CodeMirror-guttermarker-subtle { color: #505050; } +.cm-s-base16-dark .CodeMirror-linenumber { color: #505050; } +.cm-s-base16-dark .CodeMirror-cursor { border-left: 1px solid #b0b0b0; } + +.cm-s-base16-dark span.cm-comment { color: #8f5536; } +.cm-s-base16-dark span.cm-atom { color: #aa759f; } +.cm-s-base16-dark span.cm-number { color: #aa759f; } + +.cm-s-base16-dark span.cm-property, .cm-s-base16-dark span.cm-attribute { color: #90a959; } +.cm-s-base16-dark span.cm-keyword { color: #ac4142; } +.cm-s-base16-dark span.cm-string { color: #f4bf75; } + +.cm-s-base16-dark span.cm-variable { color: #90a959; } +.cm-s-base16-dark span.cm-variable-2 { color: #6a9fb5; } +.cm-s-base16-dark span.cm-def { color: #d28445; } +.cm-s-base16-dark span.cm-bracket { color: #e0e0e0; } +.cm-s-base16-dark span.cm-tag { color: #ac4142; } +.cm-s-base16-dark span.cm-link { color: #aa759f; } +.cm-s-base16-dark span.cm-error { background: #ac4142; color: #b0b0b0; } + +.cm-s-base16-dark .CodeMirror-activeline-background { background: #202020; } +.cm-s-base16-dark .CodeMirror-matchingbracket { text-decoration: underline; color: white !important; } + +/* + + Name: dracula + Author: Michael Kaminsky (http://github.com/mkaminsky11) + + Original dracula color scheme by Zeno Rocha (https://github.com/zenorocha/dracula-theme) + +*/ + + +.cm-s-dracula.CodeMirror, .cm-s-dracula .CodeMirror-gutters { + background-color: #282a36 !important; + color: #f8f8f2 !important; + border: none; +} +.cm-s-dracula .CodeMirror-gutters { color: #282a36; } +.cm-s-dracula .CodeMirror-cursor { border-left: solid thin #f8f8f0; } +.cm-s-dracula .CodeMirror-linenumber { color: #6D8A88; } +.cm-s-dracula .CodeMirror-selected { background: rgba(255, 255, 255, 0.10); } +.cm-s-dracula .CodeMirror-line::selection, .cm-s-dracula .CodeMirror-line > span::selection, .cm-s-dracula .CodeMirror-line > span > span::selection { background: rgba(255, 255, 255, 0.10); } +.cm-s-dracula .CodeMirror-line::-moz-selection, .cm-s-dracula .CodeMirror-line > span::-moz-selection, .cm-s-dracula .CodeMirror-line > span > span::-moz-selection { background: rgba(255, 255, 255, 0.10); } +.cm-s-dracula span.cm-comment { color: #6272a4; } +.cm-s-dracula span.cm-string, .cm-s-dracula span.cm-string-2 { color: #f1fa8c; } +.cm-s-dracula span.cm-number { color: #bd93f9; } +.cm-s-dracula span.cm-variable { color: #50fa7b; } +.cm-s-dracula span.cm-variable-2 { color: white; } +.cm-s-dracula span.cm-def { color: #50fa7b; } +.cm-s-dracula span.cm-operator { color: #ff79c6; } +.cm-s-dracula span.cm-keyword { color: #ff79c6; } +.cm-s-dracula span.cm-atom { color: #bd93f9; } +.cm-s-dracula span.cm-meta { color: #f8f8f2; } +.cm-s-dracula span.cm-tag { color: #ff79c6; } +.cm-s-dracula span.cm-attribute { color: #50fa7b; } +.cm-s-dracula span.cm-qualifier { color: #50fa7b; } +.cm-s-dracula span.cm-property { color: #66d9ef; } +.cm-s-dracula span.cm-builtin { color: #50fa7b; } +.cm-s-dracula span.cm-variable-3, .cm-s-dracula span.cm-type { color: #ffb86c; } + +.cm-s-dracula .CodeMirror-activeline-background { background: rgba(255,255,255,0.1); } +.cm-s-dracula .CodeMirror-matchingbracket { text-decoration: underline; color: white !important; } + +/* + + Name: Hopscotch + Author: Jan T. Sott + + CodeMirror template by Jan T. Sott (https://github.com/idleberg/base16-codemirror) + Original Base16 color scheme by Chris Kempson (https://github.com/chriskempson/base16) + +*/ + +.cm-s-hopscotch.CodeMirror {background: #322931; color: #d5d3d5;} +.cm-s-hopscotch div.CodeMirror-selected {background: #433b42 !important;} +.cm-s-hopscotch .CodeMirror-gutters {background: #322931; border-right: 0px;} +.cm-s-hopscotch .CodeMirror-linenumber {color: #797379;} +.cm-s-hopscotch .CodeMirror-cursor {border-left: 1px solid #989498 !important;} + +.cm-s-hopscotch span.cm-comment {color: #b33508;} +.cm-s-hopscotch span.cm-atom {color: #c85e7c;} +.cm-s-hopscotch span.cm-number {color: #c85e7c;} + +.cm-s-hopscotch span.cm-property, .cm-s-hopscotch span.cm-attribute {color: #8fc13e;} +.cm-s-hopscotch span.cm-keyword {color: #dd464c;} +.cm-s-hopscotch span.cm-string {color: #fdcc59;} + +.cm-s-hopscotch span.cm-variable {color: #8fc13e;} +.cm-s-hopscotch span.cm-variable-2 {color: #1290bf;} +.cm-s-hopscotch span.cm-def {color: #fd8b19;} +.cm-s-hopscotch span.cm-error {background: #dd464c; color: #989498;} +.cm-s-hopscotch span.cm-bracket {color: #d5d3d5;} +.cm-s-hopscotch span.cm-tag {color: #dd464c;} +.cm-s-hopscotch span.cm-link {color: #c85e7c;} + +.cm-s-hopscotch .CodeMirror-matchingbracket { text-decoration: underline; color: white !important;} +.cm-s-hopscotch .CodeMirror-activeline-background { background: #302020; } + +/****************************************************************/ +/* Based on mbonaci's Brackets mbo theme */ +/* https://github.com/mbonaci/global/blob/master/Mbo.tmTheme */ +/* Create your own: http://tmtheme-editor.herokuapp.com */ +/****************************************************************/ + +.cm-s-mbo.CodeMirror { background: #2c2c2c; color: #ffffec; } +.cm-s-mbo div.CodeMirror-selected { background: #716C62; } +.cm-s-mbo .CodeMirror-line::selection, .cm-s-mbo .CodeMirror-line > span::selection, .cm-s-mbo .CodeMirror-line > span > span::selection { background: rgba(113, 108, 98, .99); } +.cm-s-mbo .CodeMirror-line::-moz-selection, .cm-s-mbo .CodeMirror-line > span::-moz-selection, .cm-s-mbo .CodeMirror-line > span > span::-moz-selection { background: rgba(113, 108, 98, .99); } +.cm-s-mbo .CodeMirror-gutters { background: #4e4e4e; border-right: 0px; } +.cm-s-mbo .CodeMirror-guttermarker { color: white; } +.cm-s-mbo .CodeMirror-guttermarker-subtle { color: grey; } +.cm-s-mbo .CodeMirror-linenumber { color: #dadada; } +.cm-s-mbo .CodeMirror-cursor { border-left: 1px solid #ffffec; } + +.cm-s-mbo span.cm-comment { color: #95958a; } +.cm-s-mbo span.cm-atom { color: #00a8c6; } +.cm-s-mbo span.cm-number { color: #00a8c6; } + +.cm-s-mbo span.cm-property, .cm-s-mbo span.cm-attribute { color: #9ddfe9; } +.cm-s-mbo span.cm-keyword { color: #ffb928; } +.cm-s-mbo span.cm-string { color: #ffcf6c; } +.cm-s-mbo span.cm-string.cm-property { color: #ffffec; } + +.cm-s-mbo span.cm-variable { color: #ffffec; } +.cm-s-mbo span.cm-variable-2 { color: #00a8c6; } +.cm-s-mbo span.cm-def { color: #ffffec; } +.cm-s-mbo span.cm-bracket { color: #fffffc; font-weight: bold; } +.cm-s-mbo span.cm-tag { color: #9ddfe9; } +.cm-s-mbo span.cm-link { color: #f54b07; } +.cm-s-mbo span.cm-error { border-bottom: #636363; color: #ffffec; } +.cm-s-mbo span.cm-qualifier { color: #ffffec; } + +.cm-s-mbo .CodeMirror-activeline-background { background: #494b41; } +.cm-s-mbo .CodeMirror-matchingbracket { color: #ffb928 !important; } +.cm-s-mbo .CodeMirror-matchingtag { background: rgba(255, 255, 255, .37); } + +/* + MDN-LIKE Theme - Mozilla + Ported to CodeMirror by Peter Kroon <plakroon@gmail.com> + Report bugs/issues here: https://github.com/codemirror/CodeMirror/issues + GitHub: @peterkroon + + The mdn-like theme is inspired on the displayed code examples at: https://developer.mozilla.org/en-US/docs/Web/CSS/animation + +*/ +.cm-s-mdn-like.CodeMirror { color: #999; background-color: #fff; } +.cm-s-mdn-like div.CodeMirror-selected { background: #cfc; } +.cm-s-mdn-like .CodeMirror-line::selection, .cm-s-mdn-like .CodeMirror-line > span::selection, .cm-s-mdn-like .CodeMirror-line > span > span::selection { background: #cfc; } +.cm-s-mdn-like .CodeMirror-line::-moz-selection, .cm-s-mdn-like .CodeMirror-line > span::-moz-selection, .cm-s-mdn-like .CodeMirror-line > span > span::-moz-selection { background: #cfc; } + +.cm-s-mdn-like .CodeMirror-gutters { background: #f8f8f8; border-left: 6px solid rgba(0,83,159,0.65); color: #333; } +.cm-s-mdn-like .CodeMirror-linenumber { color: #aaa; padding-left: 8px; } +.cm-s-mdn-like .CodeMirror-cursor { border-left: 2px solid #222; } + +.cm-s-mdn-like .cm-keyword { color: #6262FF; } +.cm-s-mdn-like .cm-atom { color: #F90; } +.cm-s-mdn-like .cm-number { color: #ca7841; } +.cm-s-mdn-like .cm-def { color: #8DA6CE; } +.cm-s-mdn-like span.cm-variable-2, .cm-s-mdn-like span.cm-tag { color: #690; } +.cm-s-mdn-like span.cm-variable-3, .cm-s-mdn-like span.cm-def, .cm-s-mdn-like span.cm-type { color: #07a; } + +.cm-s-mdn-like .cm-variable { color: #07a; } +.cm-s-mdn-like .cm-property { color: #905; } +.cm-s-mdn-like .cm-qualifier { color: #690; } + +.cm-s-mdn-like .cm-operator { color: #cda869; } +.cm-s-mdn-like .cm-comment { color:#777; font-weight:normal; } +.cm-s-mdn-like .cm-string { color:#07a; font-style:italic; } +.cm-s-mdn-like .cm-string-2 { color:#bd6b18; } /*?*/ +.cm-s-mdn-like .cm-meta { color: #000; } /*?*/ +.cm-s-mdn-like .cm-builtin { color: #9B7536; } /*?*/ +.cm-s-mdn-like .cm-tag { color: #997643; } +.cm-s-mdn-like .cm-attribute { color: #d6bb6d; } /*?*/ +.cm-s-mdn-like .cm-header { color: #FF6400; } +.cm-s-mdn-like .cm-hr { color: #AEAEAE; } +.cm-s-mdn-like .cm-link { color:#ad9361; font-style:italic; text-decoration:none; } +.cm-s-mdn-like .cm-error { border-bottom: 1px solid red; } + +div.cm-s-mdn-like .CodeMirror-activeline-background { background: #efefff; } +div.cm-s-mdn-like span.CodeMirror-matchingbracket { outline:1px solid grey; color: inherit; } + +.cm-s-mdn-like.CodeMirror { background-image: url(data:image/png;base64,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); } + +/* + + Name: seti + Author: Michael Kaminsky (http://github.com/mkaminsky11) + + Original seti color scheme by Jesse Weed (https://github.com/jesseweed/seti-syntax) + +*/ + + +.cm-s-seti.CodeMirror { + background-color: #151718 !important; + color: #CFD2D1 !important; + border: none; +} +.cm-s-seti .CodeMirror-gutters { + color: #404b53; + background-color: #0E1112; + border: none; +} +.cm-s-seti .CodeMirror-cursor { border-left: solid thin #f8f8f0; } +.cm-s-seti .CodeMirror-linenumber { color: #6D8A88; } +.cm-s-seti.CodeMirror-focused div.CodeMirror-selected { background: rgba(255, 255, 255, 0.10); } +.cm-s-seti .CodeMirror-line::selection, .cm-s-seti .CodeMirror-line > span::selection, .cm-s-seti .CodeMirror-line > span > span::selection { background: rgba(255, 255, 255, 0.10); } +.cm-s-seti .CodeMirror-line::-moz-selection, .cm-s-seti .CodeMirror-line > span::-moz-selection, .cm-s-seti .CodeMirror-line > span > span::-moz-selection { background: rgba(255, 255, 255, 0.10); } +.cm-s-seti span.cm-comment { color: #41535b; } +.cm-s-seti span.cm-string, .cm-s-seti span.cm-string-2 { color: #55b5db; } +.cm-s-seti span.cm-number { color: #cd3f45; } +.cm-s-seti span.cm-variable { color: #55b5db; } +.cm-s-seti span.cm-variable-2 { color: #a074c4; } +.cm-s-seti span.cm-def { color: #55b5db; } +.cm-s-seti span.cm-keyword { color: #ff79c6; } +.cm-s-seti span.cm-operator { color: #9fca56; } +.cm-s-seti span.cm-keyword { color: #e6cd69; } +.cm-s-seti span.cm-atom { color: #cd3f45; } +.cm-s-seti span.cm-meta { color: #55b5db; } +.cm-s-seti span.cm-tag { color: #55b5db; } +.cm-s-seti span.cm-attribute { color: #9fca56; } +.cm-s-seti span.cm-qualifier { color: #9fca56; } +.cm-s-seti span.cm-property { color: #a074c4; } +.cm-s-seti span.cm-variable-3, .cm-s-seti span.cm-type { color: #9fca56; } +.cm-s-seti span.cm-builtin { color: #9fca56; } +.cm-s-seti .CodeMirror-activeline-background { background: #101213; } +.cm-s-seti .CodeMirror-matchingbracket { text-decoration: underline; color: white !important; } + +/* +Solarized theme for code-mirror +http://ethanschoonover.com/solarized +*/ + +/* +Solarized color palette +http://ethanschoonover.com/solarized/img/solarized-palette.png +*/ + +.solarized.base03 { color: #002b36; } +.solarized.base02 { color: #073642; } +.solarized.base01 { color: #586e75; } +.solarized.base00 { color: #657b83; } +.solarized.base0 { color: #839496; } +.solarized.base1 { color: #93a1a1; } +.solarized.base2 { color: #eee8d5; } +.solarized.base3 { color: #fdf6e3; } +.solarized.solar-yellow { color: #b58900; } +.solarized.solar-orange { color: #cb4b16; } +.solarized.solar-red { color: #dc322f; } +.solarized.solar-magenta { color: #d33682; } +.solarized.solar-violet { color: #6c71c4; } +.solarized.solar-blue { color: #268bd2; } +.solarized.solar-cyan { color: #2aa198; } +.solarized.solar-green { color: #859900; } + +/* Color scheme for code-mirror */ + +.cm-s-solarized { + line-height: 1.45em; + color-profile: sRGB; + rendering-intent: auto; +} +.cm-s-solarized.cm-s-dark { + color: #839496; + background-color: #002b36; + text-shadow: #002b36 0 1px; +} +.cm-s-solarized.cm-s-light { + background-color: #fdf6e3; + color: #657b83; + text-shadow: #eee8d5 0 1px; +} + +.cm-s-solarized .CodeMirror-widget { + text-shadow: none; +} + +.cm-s-solarized .cm-header { color: #586e75; } +.cm-s-solarized .cm-quote { color: #93a1a1; } + +.cm-s-solarized .cm-keyword { color: #cb4b16; } +.cm-s-solarized .cm-atom { color: #d33682; } +.cm-s-solarized .cm-number { color: #d33682; } +.cm-s-solarized .cm-def { color: #2aa198; } + +.cm-s-solarized .cm-variable { color: #839496; } +.cm-s-solarized .cm-variable-2 { color: #b58900; } +.cm-s-solarized .cm-variable-3, .cm-s-solarized .cm-type { color: #6c71c4; } + +.cm-s-solarized .cm-property { color: #2aa198; } +.cm-s-solarized .cm-operator { color: #6c71c4; } + +.cm-s-solarized .cm-comment { color: #586e75; font-style:italic; } + +.cm-s-solarized .cm-string { color: #859900; } +.cm-s-solarized .cm-string-2 { color: #b58900; } + +.cm-s-solarized .cm-meta { color: #859900; } +.cm-s-solarized .cm-qualifier { color: #b58900; } +.cm-s-solarized .cm-builtin { color: #d33682; } +.cm-s-solarized .cm-bracket { color: #cb4b16; } +.cm-s-solarized .CodeMirror-matchingbracket { color: #859900; } +.cm-s-solarized .CodeMirror-nonmatchingbracket { color: #dc322f; } +.cm-s-solarized .cm-tag { color: #93a1a1; } +.cm-s-solarized .cm-attribute { color: #2aa198; } +.cm-s-solarized .cm-hr { + color: transparent; + border-top: 1px solid #586e75; + display: block; +} +.cm-s-solarized .cm-link { color: #93a1a1; cursor: pointer; } +.cm-s-solarized .cm-special { color: #6c71c4; } +.cm-s-solarized .cm-em { + color: #999; + text-decoration: underline; + text-decoration-style: dotted; +} +.cm-s-solarized .cm-error, +.cm-s-solarized .cm-invalidchar { + color: #586e75; + border-bottom: 1px dotted #dc322f; +} + +.cm-s-solarized.cm-s-dark div.CodeMirror-selected { background: #073642; } +.cm-s-solarized.cm-s-dark.CodeMirror ::selection { background: rgba(7, 54, 66, 0.99); } +.cm-s-solarized.cm-s-dark .CodeMirror-line::-moz-selection, .cm-s-dark .CodeMirror-line > span::-moz-selection, .cm-s-dark .CodeMirror-line > span > span::-moz-selection { background: rgba(7, 54, 66, 0.99); } + +.cm-s-solarized.cm-s-light div.CodeMirror-selected { background: #eee8d5; } +.cm-s-solarized.cm-s-light .CodeMirror-line::selection, .cm-s-light .CodeMirror-line > span::selection, .cm-s-light .CodeMirror-line > span > span::selection { background: #eee8d5; } +.cm-s-solarized.cm-s-light .CodeMirror-line::-moz-selection, .cm-s-ligh .CodeMirror-line > span::-moz-selection, .cm-s-ligh .CodeMirror-line > span > span::-moz-selection { background: #eee8d5; } + +/* Editor styling */ + + + +/* Little shadow on the view-port of the buffer view */ +.cm-s-solarized.CodeMirror { + -moz-box-shadow: inset 7px 0 12px -6px #000; + -webkit-box-shadow: inset 7px 0 12px -6px #000; + box-shadow: inset 7px 0 12px -6px #000; +} + +/* Remove gutter border */ +.cm-s-solarized .CodeMirror-gutters { + border-right: 0; +} + +/* Gutter colors and line number styling based of color scheme (dark / light) */ + +/* Dark */ +.cm-s-solarized.cm-s-dark .CodeMirror-gutters { + background-color: #073642; +} + +.cm-s-solarized.cm-s-dark .CodeMirror-linenumber { + color: #586e75; + text-shadow: #021014 0 -1px; +} + +/* Light */ +.cm-s-solarized.cm-s-light .CodeMirror-gutters { + background-color: #eee8d5; +} + +.cm-s-solarized.cm-s-light .CodeMirror-linenumber { + color: #839496; +} + +/* Common */ +.cm-s-solarized .CodeMirror-linenumber { + padding: 0 5px; +} +.cm-s-solarized .CodeMirror-guttermarker-subtle { color: #586e75; } +.cm-s-solarized.cm-s-dark .CodeMirror-guttermarker { color: #ddd; } +.cm-s-solarized.cm-s-light .CodeMirror-guttermarker { color: #cb4b16; } + +.cm-s-solarized .CodeMirror-gutter .CodeMirror-gutter-text { + color: #586e75; +} + +/* Cursor */ +.cm-s-solarized .CodeMirror-cursor { border-left: 1px solid #819090; } + +/* Fat cursor */ +.cm-s-solarized.cm-s-light.cm-fat-cursor .CodeMirror-cursor { background: #77ee77; } +.cm-s-solarized.cm-s-light .cm-animate-fat-cursor { background-color: #77ee77; } +.cm-s-solarized.cm-s-dark.cm-fat-cursor .CodeMirror-cursor { background: #586e75; } +.cm-s-solarized.cm-s-dark .cm-animate-fat-cursor { background-color: #586e75; } + +/* Active line */ +.cm-s-solarized.cm-s-dark .CodeMirror-activeline-background { + background: rgba(255, 255, 255, 0.06); +} +.cm-s-solarized.cm-s-light .CodeMirror-activeline-background { + background: rgba(0, 0, 0, 0.06); +} + +.cm-s-the-matrix.CodeMirror { background: #000000; color: #00FF00; } +.cm-s-the-matrix div.CodeMirror-selected { background: #2D2D2D; } +.cm-s-the-matrix .CodeMirror-line::selection, .cm-s-the-matrix .CodeMirror-line > span::selection, .cm-s-the-matrix .CodeMirror-line > span > span::selection { background: rgba(45, 45, 45, 0.99); } +.cm-s-the-matrix .CodeMirror-line::-moz-selection, .cm-s-the-matrix .CodeMirror-line > span::-moz-selection, .cm-s-the-matrix .CodeMirror-line > span > span::-moz-selection { background: rgba(45, 45, 45, 0.99); } +.cm-s-the-matrix .CodeMirror-gutters { background: #060; border-right: 2px solid #00FF00; } +.cm-s-the-matrix .CodeMirror-guttermarker { color: #0f0; } +.cm-s-the-matrix .CodeMirror-guttermarker-subtle { color: white; } +.cm-s-the-matrix .CodeMirror-linenumber { color: #FFFFFF; } +.cm-s-the-matrix .CodeMirror-cursor { border-left: 1px solid #00FF00; } + +.cm-s-the-matrix span.cm-keyword { color: #008803; font-weight: bold; } +.cm-s-the-matrix span.cm-atom { color: #3FF; } +.cm-s-the-matrix span.cm-number { color: #FFB94F; } +.cm-s-the-matrix span.cm-def { color: #99C; } +.cm-s-the-matrix span.cm-variable { color: #F6C; } +.cm-s-the-matrix span.cm-variable-2 { color: #C6F; } +.cm-s-the-matrix span.cm-variable-3, .cm-s-the-matrix span.cm-type { color: #96F; } +.cm-s-the-matrix span.cm-property { color: #62FFA0; } +.cm-s-the-matrix span.cm-operator { color: #999; } +.cm-s-the-matrix span.cm-comment { color: #CCCCCC; } +.cm-s-the-matrix span.cm-string { color: #39C; } +.cm-s-the-matrix span.cm-meta { color: #C9F; } +.cm-s-the-matrix span.cm-qualifier { color: #FFF700; } +.cm-s-the-matrix span.cm-builtin { color: #30a; } +.cm-s-the-matrix span.cm-bracket { color: #cc7; } +.cm-s-the-matrix span.cm-tag { color: #FFBD40; } +.cm-s-the-matrix span.cm-attribute { color: #FFF700; } +.cm-s-the-matrix span.cm-error { color: #FF0000; } + +.cm-s-the-matrix .CodeMirror-activeline-background { background: #040; } + +/* +Copyright (C) 2011 by MarkLogic Corporation +Author: Mike Brevoort <mike@brevoort.com> + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in +all copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN +THE SOFTWARE. +*/ +.cm-s-xq-light span.cm-keyword { line-height: 1em; font-weight: bold; color: #5A5CAD; } +.cm-s-xq-light span.cm-atom { color: #6C8CD5; } +.cm-s-xq-light span.cm-number { color: #164; } +.cm-s-xq-light span.cm-def { text-decoration:underline; } +.cm-s-xq-light span.cm-variable { color: black; } +.cm-s-xq-light span.cm-variable-2 { color:black; } +.cm-s-xq-light span.cm-variable-3, .cm-s-xq-light span.cm-type { color: black; } +.cm-s-xq-light span.cm-property {} +.cm-s-xq-light span.cm-operator {} +.cm-s-xq-light span.cm-comment { color: #0080FF; font-style: italic; } +.cm-s-xq-light span.cm-string { color: red; } +.cm-s-xq-light span.cm-meta { color: yellow; } +.cm-s-xq-light span.cm-qualifier { color: grey; } +.cm-s-xq-light span.cm-builtin { color: #7EA656; } +.cm-s-xq-light span.cm-bracket { color: #cc7; } +.cm-s-xq-light span.cm-tag { color: #3F7F7F; } +.cm-s-xq-light span.cm-attribute { color: #7F007F; } +.cm-s-xq-light span.cm-error { color: #f00; } + +.cm-s-xq-light .CodeMirror-activeline-background { background: #e8f2ff; } +.cm-s-xq-light .CodeMirror-matchingbracket { outline:1px solid grey;color:black !important;background:yellow; } + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +.CodeMirror { + line-height: var(--jp-code-line-height); + font-size: var(--jp-code-font-size); + font-family: var(--jp-code-font-family); + border: 0; + border-radius: 0; + height: auto; + /* Changed to auto to autogrow */ +} + +.CodeMirror pre { + padding: 0 var(--jp-code-padding); +} + +.jp-CodeMirrorEditor[data-type='inline'] .CodeMirror-dialog { + background-color: var(--jp-layout-color0); + color: var(--jp-content-font-color1); +} + +/* This causes https://github.com/jupyter/jupyterlab/issues/522 */ +/* May not cause it not because we changed it! */ +.CodeMirror-lines { + padding: var(--jp-code-padding) 0; +} + +.CodeMirror-linenumber { + padding: 0 8px; +} + +.jp-CodeMirrorEditor-static { + margin: var(--jp-code-padding); +} + +.jp-CodeMirrorEditor, +.jp-CodeMirrorEditor-static { + cursor: text; +} + +.jp-CodeMirrorEditor[data-type='inline'] .CodeMirror-cursor { + border-left: var(--jp-code-cursor-width0) solid var(--jp-editor-cursor-color); +} + +/* When zoomed out 67% and 33% on a screen of 1440 width x 900 height */ +@media screen and (min-width: 2138px) and (max-width: 4319px) { + .jp-CodeMirrorEditor[data-type='inline'] .CodeMirror-cursor { + border-left: var(--jp-code-cursor-width1) solid + var(--jp-editor-cursor-color); + } +} + +/* When zoomed out less than 33% */ +@media screen and (min-width: 4320px) { + .jp-CodeMirrorEditor[data-type='inline'] .CodeMirror-cursor { + border-left: var(--jp-code-cursor-width2) solid + var(--jp-editor-cursor-color); + } +} + +.CodeMirror.jp-mod-readOnly .CodeMirror-cursor { + display: none; +} + +.CodeMirror-gutters { + border-right: 1px solid var(--jp-border-color2); + background-color: var(--jp-layout-color0); +} + +.jp-CollaboratorCursor { + border-left: 5px solid transparent; + border-right: 5px solid transparent; + border-top: none; + border-bottom: 3px solid; + background-clip: content-box; + margin-left: -5px; + margin-right: -5px; +} + +.CodeMirror-selectedtext.cm-searching { + background-color: var(--jp-search-selected-match-background-color) !important; + color: var(--jp-search-selected-match-color) !important; +} + +.cm-searching { + background-color: var( + --jp-search-unselected-match-background-color + ) !important; + color: var(--jp-search-unselected-match-color) !important; +} + +.CodeMirror-focused .CodeMirror-selected { + background-color: var(--jp-editor-selected-focused-background); +} + +.CodeMirror-selected { + background-color: var(--jp-editor-selected-background); +} + +.jp-CollaboratorCursor-hover { + position: absolute; + z-index: 1; + transform: translateX(-50%); + color: white; + border-radius: 3px; + padding-left: 4px; + padding-right: 4px; + padding-top: 1px; + padding-bottom: 1px; + text-align: center; + font-size: var(--jp-ui-font-size1); + white-space: nowrap; +} + +.jp-CodeMirror-ruler { + border-left: 1px dashed var(--jp-border-color2); +} + +/** + * Here is our jupyter theme for CodeMirror syntax highlighting + * This is used in our marked.js syntax highlighting and CodeMirror itself + * The string "jupyter" is set in ../codemirror/widget.DEFAULT_CODEMIRROR_THEME + * This came from the classic notebook, which came form highlight.js/GitHub + */ + +/** + * CodeMirror themes are handling the background/color in this way. This works + * fine for CodeMirror editors outside the notebook, but the notebook styles + * these things differently. + */ +.CodeMirror.cm-s-jupyter { + background: var(--jp-layout-color0); + color: var(--jp-content-font-color1); +} + +/* In the notebook, we want this styling to be handled by its container */ +.jp-CodeConsole .CodeMirror.cm-s-jupyter, +.jp-Notebook .CodeMirror.cm-s-jupyter { + background: transparent; +} + +.cm-s-jupyter .CodeMirror-cursor { + border-left: var(--jp-code-cursor-width0) solid var(--jp-editor-cursor-color); +} +.cm-s-jupyter span.cm-keyword { + color: var(--jp-mirror-editor-keyword-color); + font-weight: bold; +} +.cm-s-jupyter span.cm-atom { + color: var(--jp-mirror-editor-atom-color); +} +.cm-s-jupyter span.cm-number { + color: var(--jp-mirror-editor-number-color); +} +.cm-s-jupyter span.cm-def { + color: var(--jp-mirror-editor-def-color); +} +.cm-s-jupyter span.cm-variable { + color: var(--jp-mirror-editor-variable-color); +} +.cm-s-jupyter span.cm-variable-2 { + color: var(--jp-mirror-editor-variable-2-color); +} +.cm-s-jupyter span.cm-variable-3 { + color: var(--jp-mirror-editor-variable-3-color); +} +.cm-s-jupyter span.cm-punctuation { + color: var(--jp-mirror-editor-punctuation-color); +} +.cm-s-jupyter span.cm-property { + color: var(--jp-mirror-editor-property-color); +} +.cm-s-jupyter span.cm-operator { + color: var(--jp-mirror-editor-operator-color); + font-weight: bold; +} +.cm-s-jupyter span.cm-comment { + color: var(--jp-mirror-editor-comment-color); + font-style: italic; +} +.cm-s-jupyter span.cm-string { + color: var(--jp-mirror-editor-string-color); +} +.cm-s-jupyter span.cm-string-2 { + color: var(--jp-mirror-editor-string-2-color); +} +.cm-s-jupyter span.cm-meta { + color: var(--jp-mirror-editor-meta-color); +} +.cm-s-jupyter span.cm-qualifier { + color: var(--jp-mirror-editor-qualifier-color); +} +.cm-s-jupyter span.cm-builtin { + color: var(--jp-mirror-editor-builtin-color); +} +.cm-s-jupyter span.cm-bracket { + color: var(--jp-mirror-editor-bracket-color); +} +.cm-s-jupyter span.cm-tag { + color: var(--jp-mirror-editor-tag-color); +} +.cm-s-jupyter span.cm-attribute { + color: var(--jp-mirror-editor-attribute-color); +} +.cm-s-jupyter span.cm-header { + color: var(--jp-mirror-editor-header-color); +} +.cm-s-jupyter span.cm-quote { + color: var(--jp-mirror-editor-quote-color); +} +.cm-s-jupyter span.cm-link { + color: var(--jp-mirror-editor-link-color); +} +.cm-s-jupyter span.cm-error { + color: var(--jp-mirror-editor-error-color); +} +.cm-s-jupyter span.cm-hr { + color: #999; +} + +.cm-s-jupyter span.cm-tab { + background: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADAAAAAMCAYAAAAkuj5RAAAAAXNSR0IArs4c6QAAAGFJREFUSMft1LsRQFAQheHPowAKoACx3IgEKtaEHujDjORSgWTH/ZOdnZOcM/sgk/kFFWY0qV8foQwS4MKBCS3qR6ixBJvElOobYAtivseIE120FaowJPN75GMu8j/LfMwNjh4HUpwg4LUAAAAASUVORK5CYII=); + background-position: right; + background-repeat: no-repeat; +} + +.cm-s-jupyter .CodeMirror-activeline-background, +.cm-s-jupyter .CodeMirror-gutter { + background-color: var(--jp-layout-color2); +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/* This file was auto-generated by ensurePackage() in @jupyterlab/buildutils */ + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/*----------------------------------------------------------------------------- +| RenderedText +|----------------------------------------------------------------------------*/ + +.jp-RenderedText { + text-align: left; + padding-left: var(--jp-code-padding); + line-height: var(--jp-code-line-height); + font-family: var(--jp-code-font-family); +} + +.jp-RenderedText pre, +.jp-RenderedJavaScript pre, +.jp-RenderedHTMLCommon pre { + color: var(--jp-content-font-color1); + font-size: var(--jp-code-font-size); + border: none; + margin: 0px; + padding: 0px; + line-height: normal; +} + +.jp-RenderedText pre a:link { + text-decoration: none; + color: var(--jp-content-link-color); +} +.jp-RenderedText pre a:hover { + text-decoration: underline; + color: var(--jp-content-link-color); +} +.jp-RenderedText pre a:visited { + text-decoration: none; + color: var(--jp-content-link-color); +} + +/* console foregrounds and backgrounds */ +.jp-RenderedText pre .ansi-black-fg { + color: #3e424d; +} +.jp-RenderedText pre .ansi-red-fg { + color: #e75c58; +} +.jp-RenderedText pre .ansi-green-fg { + color: #00a250; +} +.jp-RenderedText pre .ansi-yellow-fg { + color: #ddb62b; +} +.jp-RenderedText pre .ansi-blue-fg { + color: #208ffb; +} +.jp-RenderedText pre .ansi-magenta-fg { + color: #d160c4; +} +.jp-RenderedText pre .ansi-cyan-fg { + color: #60c6c8; +} +.jp-RenderedText pre .ansi-white-fg { + color: #c5c1b4; +} + +.jp-RenderedText pre .ansi-black-bg { + background-color: #3e424d; +} +.jp-RenderedText pre .ansi-red-bg { + background-color: #e75c58; +} +.jp-RenderedText pre .ansi-green-bg { + background-color: #00a250; +} +.jp-RenderedText pre .ansi-yellow-bg { + background-color: #ddb62b; +} +.jp-RenderedText pre .ansi-blue-bg { + background-color: #208ffb; +} +.jp-RenderedText pre .ansi-magenta-bg { + background-color: #d160c4; +} +.jp-RenderedText pre .ansi-cyan-bg { + background-color: #60c6c8; +} +.jp-RenderedText pre .ansi-white-bg { + background-color: #c5c1b4; +} + +.jp-RenderedText pre .ansi-black-intense-fg { + color: #282c36; +} +.jp-RenderedText pre .ansi-red-intense-fg { + color: #b22b31; +} +.jp-RenderedText pre .ansi-green-intense-fg { + color: #007427; +} +.jp-RenderedText pre .ansi-yellow-intense-fg { + color: #b27d12; 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+} +.jp-RenderedText pre .ansi-default-inverse-bg { + background-color: var(--jp-inverse-layout-color0); +} + +.jp-RenderedText pre .ansi-bold { + font-weight: bold; +} +.jp-RenderedText pre .ansi-underline { + text-decoration: underline; +} + +.jp-RenderedText[data-mime-type='application/vnd.jupyter.stderr'] { + background: var(--jp-rendermime-error-background); + padding-top: var(--jp-code-padding); +} + +/*----------------------------------------------------------------------------- +| RenderedLatex +|----------------------------------------------------------------------------*/ + +.jp-RenderedLatex { + color: var(--jp-content-font-color1); + font-size: var(--jp-content-font-size1); + line-height: var(--jp-content-line-height); +} + +/* Left-justify outputs.*/ +.jp-OutputArea-output.jp-RenderedLatex { + padding: var(--jp-code-padding); + text-align: left; +} + +/*----------------------------------------------------------------------------- +| RenderedHTML +|----------------------------------------------------------------------------*/ + +.jp-RenderedHTMLCommon { + color: var(--jp-content-font-color1); + font-family: var(--jp-content-font-family); + font-size: var(--jp-content-font-size1); + line-height: var(--jp-content-line-height); + /* Give a bit more R padding on Markdown text to keep line lengths reasonable */ + padding-right: 20px; +} + +.jp-RenderedHTMLCommon em { + font-style: italic; +} + +.jp-RenderedHTMLCommon strong { + font-weight: bold; +} + +.jp-RenderedHTMLCommon u { + text-decoration: underline; +} + +.jp-RenderedHTMLCommon a:link { + text-decoration: none; + color: var(--jp-content-link-color); +} + +.jp-RenderedHTMLCommon a:hover { + text-decoration: underline; + color: var(--jp-content-link-color); +} + +.jp-RenderedHTMLCommon a:visited { + text-decoration: none; + color: var(--jp-content-link-color); +} + +/* Headings */ + +.jp-RenderedHTMLCommon h1, +.jp-RenderedHTMLCommon h2, +.jp-RenderedHTMLCommon h3, +.jp-RenderedHTMLCommon h4, +.jp-RenderedHTMLCommon h5, +.jp-RenderedHTMLCommon h6 { + line-height: var(--jp-content-heading-line-height); + font-weight: var(--jp-content-heading-font-weight); + font-style: normal; + margin: var(--jp-content-heading-margin-top) 0 + var(--jp-content-heading-margin-bottom) 0; +} + +.jp-RenderedHTMLCommon h1:first-child, +.jp-RenderedHTMLCommon h2:first-child, +.jp-RenderedHTMLCommon h3:first-child, +.jp-RenderedHTMLCommon h4:first-child, +.jp-RenderedHTMLCommon h5:first-child, +.jp-RenderedHTMLCommon h6:first-child { + margin-top: calc(0.5 * var(--jp-content-heading-margin-top)); +} + +.jp-RenderedHTMLCommon h1:last-child, +.jp-RenderedHTMLCommon h2:last-child, +.jp-RenderedHTMLCommon h3:last-child, +.jp-RenderedHTMLCommon h4:last-child, +.jp-RenderedHTMLCommon h5:last-child, +.jp-RenderedHTMLCommon h6:last-child { + margin-bottom: calc(0.5 * var(--jp-content-heading-margin-bottom)); +} + +.jp-RenderedHTMLCommon h1 { + font-size: var(--jp-content-font-size5); +} + +.jp-RenderedHTMLCommon h2 { + font-size: var(--jp-content-font-size4); +} + +.jp-RenderedHTMLCommon h3 { + font-size: var(--jp-content-font-size3); +} + +.jp-RenderedHTMLCommon h4 { + font-size: var(--jp-content-font-size2); +} + +.jp-RenderedHTMLCommon h5 { + font-size: var(--jp-content-font-size1); +} + +.jp-RenderedHTMLCommon h6 { + font-size: var(--jp-content-font-size0); +} + +/* Lists */ + +.jp-RenderedHTMLCommon ul:not(.list-inline), +.jp-RenderedHTMLCommon ol:not(.list-inline) { + padding-left: 2em; +} + +.jp-RenderedHTMLCommon ul { + list-style: disc; +} + +.jp-RenderedHTMLCommon ul ul { + list-style: square; +} + +.jp-RenderedHTMLCommon ul ul ul { + list-style: circle; +} + +.jp-RenderedHTMLCommon ol { + list-style: decimal; +} + +.jp-RenderedHTMLCommon ol ol { + list-style: upper-alpha; +} + +.jp-RenderedHTMLCommon ol ol ol { + list-style: lower-alpha; +} + +.jp-RenderedHTMLCommon ol ol ol ol { + list-style: lower-roman; +} + +.jp-RenderedHTMLCommon ol ol ol ol ol { + list-style: decimal; +} + +.jp-RenderedHTMLCommon ol, +.jp-RenderedHTMLCommon ul { + margin-bottom: 1em; +} + +.jp-RenderedHTMLCommon ul ul, +.jp-RenderedHTMLCommon ul ol, +.jp-RenderedHTMLCommon ol ul, +.jp-RenderedHTMLCommon ol ol { + margin-bottom: 0em; +} + +.jp-RenderedHTMLCommon hr { + color: var(--jp-border-color2); + background-color: var(--jp-border-color1); + margin-top: 1em; + margin-bottom: 1em; +} + +.jp-RenderedHTMLCommon > pre { + margin: 1.5em 2em; +} + +.jp-RenderedHTMLCommon pre, +.jp-RenderedHTMLCommon code { + border: 0; + background-color: var(--jp-layout-color0); + color: var(--jp-content-font-color1); + font-family: var(--jp-code-font-family); + font-size: inherit; + line-height: var(--jp-code-line-height); + padding: 0; + white-space: pre-wrap; +} + +.jp-RenderedHTMLCommon :not(pre) > code { + background-color: var(--jp-layout-color2); + padding: 1px 5px; +} + +/* Tables */ + +.jp-RenderedHTMLCommon table { + border-collapse: collapse; + border-spacing: 0; + border: none; + color: var(--jp-ui-font-color1); + font-size: 12px; + table-layout: fixed; + margin-left: auto; + margin-right: auto; +} + +.jp-RenderedHTMLCommon thead { + border-bottom: var(--jp-border-width) solid var(--jp-border-color1); + vertical-align: bottom; +} + +.jp-RenderedHTMLCommon td, +.jp-RenderedHTMLCommon th, +.jp-RenderedHTMLCommon tr { + vertical-align: middle; + padding: 0.5em 0.5em; + line-height: normal; + white-space: normal; + max-width: none; + border: none; +} + +.jp-RenderedMarkdown.jp-RenderedHTMLCommon td, +.jp-RenderedMarkdown.jp-RenderedHTMLCommon th { + max-width: none; +} + +:not(.jp-RenderedMarkdown).jp-RenderedHTMLCommon td, +:not(.jp-RenderedMarkdown).jp-RenderedHTMLCommon th, +:not(.jp-RenderedMarkdown).jp-RenderedHTMLCommon tr { + text-align: right; +} + +.jp-RenderedHTMLCommon th { + font-weight: bold; +} + +.jp-RenderedHTMLCommon tbody tr:nth-child(odd) { + background: var(--jp-layout-color0); +} + +.jp-RenderedHTMLCommon tbody tr:nth-child(even) { + background: var(--jp-rendermime-table-row-background); +} + +.jp-RenderedHTMLCommon tbody tr:hover { + background: var(--jp-rendermime-table-row-hover-background); +} + +.jp-RenderedHTMLCommon table { + margin-bottom: 1em; +} + +.jp-RenderedHTMLCommon p { + text-align: left; + margin: 0px; +} + +.jp-RenderedHTMLCommon p { + margin-bottom: 1em; +} + +.jp-RenderedHTMLCommon img { + -moz-force-broken-image-icon: 1; +} + +/* Restrict to direct children as other images could be nested in other content. */ +.jp-RenderedHTMLCommon > img { + display: block; + margin-left: 0; + margin-right: 0; + margin-bottom: 1em; +} + +/* Change color behind transparent images if they need it... */ +[data-jp-theme-light='false'] .jp-RenderedImage img.jp-needs-light-background { + background-color: var(--jp-inverse-layout-color1); +} +[data-jp-theme-light='true'] .jp-RenderedImage img.jp-needs-dark-background { + background-color: var(--jp-inverse-layout-color1); +} +/* ...or leave it untouched if they don't */ +[data-jp-theme-light='false'] .jp-RenderedImage img.jp-needs-dark-background { +} +[data-jp-theme-light='true'] .jp-RenderedImage img.jp-needs-light-background { +} + +.jp-RenderedHTMLCommon img, +.jp-RenderedImage img, +.jp-RenderedHTMLCommon svg, +.jp-RenderedSVG svg { + max-width: 100%; + height: auto; +} + +.jp-RenderedHTMLCommon img.jp-mod-unconfined, +.jp-RenderedImage img.jp-mod-unconfined, +.jp-RenderedHTMLCommon svg.jp-mod-unconfined, +.jp-RenderedSVG svg.jp-mod-unconfined { + max-width: none; +} + +.jp-RenderedHTMLCommon .alert { + padding: var(--jp-notebook-padding); + border: var(--jp-border-width) solid transparent; + border-radius: var(--jp-border-radius); + margin-bottom: 1em; +} + +.jp-RenderedHTMLCommon .alert-info { + color: var(--jp-info-color0); + background-color: var(--jp-info-color3); + border-color: var(--jp-info-color2); +} +.jp-RenderedHTMLCommon .alert-info hr { + border-color: var(--jp-info-color3); +} +.jp-RenderedHTMLCommon .alert-info > p:last-child, +.jp-RenderedHTMLCommon .alert-info > ul:last-child { + margin-bottom: 0; +} + +.jp-RenderedHTMLCommon .alert-warning { + color: var(--jp-warn-color0); + background-color: var(--jp-warn-color3); + border-color: var(--jp-warn-color2); +} +.jp-RenderedHTMLCommon .alert-warning hr { + border-color: var(--jp-warn-color3); +} +.jp-RenderedHTMLCommon .alert-warning > p:last-child, +.jp-RenderedHTMLCommon .alert-warning > ul:last-child { + margin-bottom: 0; +} + +.jp-RenderedHTMLCommon .alert-success { + color: var(--jp-success-color0); + background-color: var(--jp-success-color3); + border-color: var(--jp-success-color2); +} +.jp-RenderedHTMLCommon .alert-success hr { + border-color: var(--jp-success-color3); +} +.jp-RenderedHTMLCommon .alert-success > p:last-child, +.jp-RenderedHTMLCommon .alert-success > ul:last-child { + margin-bottom: 0; +} + +.jp-RenderedHTMLCommon .alert-danger { + color: var(--jp-error-color0); + background-color: var(--jp-error-color3); + border-color: var(--jp-error-color2); +} +.jp-RenderedHTMLCommon .alert-danger hr { + border-color: var(--jp-error-color3); +} +.jp-RenderedHTMLCommon .alert-danger > p:last-child, +.jp-RenderedHTMLCommon .alert-danger > ul:last-child { + margin-bottom: 0; +} + +.jp-RenderedHTMLCommon blockquote { + margin: 1em 2em; + padding: 0 1em; + border-left: 5px solid var(--jp-border-color2); +} + +a.jp-InternalAnchorLink { + visibility: hidden; + margin-left: 8px; + color: var(--md-blue-800); +} + +h1:hover .jp-InternalAnchorLink, +h2:hover .jp-InternalAnchorLink, +h3:hover .jp-InternalAnchorLink, +h4:hover .jp-InternalAnchorLink, +h5:hover .jp-InternalAnchorLink, +h6:hover .jp-InternalAnchorLink { + visibility: visible; +} + +.jp-RenderedHTMLCommon kbd { + background-color: var(--jp-rendermime-table-row-background); + border: 1px solid var(--jp-border-color0); + border-bottom-color: var(--jp-border-color2); + border-radius: 3px; + box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25); + display: inline-block; + font-size: 0.8em; + line-height: 1em; + padding: 0.2em 0.5em; +} + +/* Most direct children of .jp-RenderedHTMLCommon have a margin-bottom of 1.0. + * At the bottom of cells this is a bit too much as there is also spacing + * between cells. Going all the way to 0 gets too tight between markdown and + * code cells. + */ +.jp-RenderedHTMLCommon > *:last-child { + margin-bottom: 0.5em; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/* This file was auto-generated by ensurePackage() in @jupyterlab/buildutils */ + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +.jp-MimeDocument { + outline: none; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/* This file was auto-generated by ensurePackage() in @jupyterlab/buildutils */ + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/*----------------------------------------------------------------------------- +| Variables +|----------------------------------------------------------------------------*/ + +:root { + --jp-private-filebrowser-button-height: 28px; + --jp-private-filebrowser-button-width: 48px; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +.jp-FileBrowser { + display: flex; + flex-direction: column; + color: var(--jp-ui-font-color1); + background: var(--jp-layout-color1); + /* This is needed so that all font sizing of children done in ems is + * relative to this base size */ + font-size: var(--jp-ui-font-size1); +} + +.jp-FileBrowser-toolbar.jp-Toolbar { + border-bottom: none; + height: auto; + margin: var(--jp-toolbar-header-margin); + box-shadow: none; +} + +.jp-BreadCrumbs { + flex: 0 0 auto; + margin: 4px 12px; +} + +.jp-BreadCrumbs-item { + margin: 0px 2px; + padding: 0px 2px; + border-radius: var(--jp-border-radius); + cursor: pointer; +} + +.jp-BreadCrumbs-item:hover { + background-color: var(--jp-layout-color2); +} + +.jp-BreadCrumbs-item:first-child { + margin-left: 0px; +} + +.jp-BreadCrumbs-item.jp-mod-dropTarget { + background-color: var(--jp-brand-color2); + opacity: 0.7; +} + +/*----------------------------------------------------------------------------- +| Buttons +|----------------------------------------------------------------------------*/ + +.jp-FileBrowser-toolbar.jp-Toolbar { + padding: 0px; +} + +.jp-FileBrowser-toolbar.jp-Toolbar { + justify-content: space-evenly; +} + +.jp-FileBrowser-toolbar.jp-Toolbar .jp-Toolbar-item { + flex: 1; +} + +.jp-FileBrowser-toolbar.jp-Toolbar .jp-ToolbarButtonComponent { + width: 100%; +} + +/*----------------------------------------------------------------------------- +| DirListing +|----------------------------------------------------------------------------*/ + +.jp-DirListing { + flex: 1 1 auto; + display: flex; + flex-direction: column; + outline: 0; +} + +.jp-DirListing-header { + flex: 0 0 auto; + display: flex; + flex-direction: row; + overflow: hidden; + border-top: var(--jp-border-width) solid var(--jp-border-color2); + border-bottom: var(--jp-border-width) solid var(--jp-border-color1); + box-shadow: var(--jp-toolbar-box-shadow); + z-index: 2; +} + +.jp-DirListing-headerItem { + padding: 4px 12px 2px 12px; + font-weight: 500; +} + +.jp-DirListing-headerItem:hover { + background: var(--jp-layout-color2); +} + +.jp-DirListing-headerItem.jp-id-name { + flex: 1 0 84px; +} + +.jp-DirListing-headerItem.jp-id-modified { + flex: 0 0 112px; + border-left: var(--jp-border-width) solid var(--jp-border-color2); + text-align: right; +} + +.jp-DirListing-narrow .jp-id-modified, +.jp-DirListing-narrow .jp-DirListing-itemModified { + display: none; +} + +.jp-DirListing-headerItem.jp-mod-selected { + font-weight: 600; +} + +/* increase specificity to override bundled default */ +.jp-DirListing-content { + flex: 1 1 auto; + margin: 0; + padding: 0; + list-style-type: none; + overflow: auto; + background-color: var(--jp-layout-color1); +} + +/* Style the directory listing content when a user drops a file to upload */ +.jp-DirListing.jp-mod-native-drop .jp-DirListing-content { + outline: 5px dashed rgba(128, 128, 128, 0.5); + outline-offset: -10px; + cursor: copy; +} + +.jp-DirListing-item { + display: flex; + flex-direction: row; + padding: 4px 12px; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; +} + +.jp-DirListing-item.jp-mod-selected { + color: white; + background: var(--jp-brand-color1); +} + +.jp-DirListing-item.jp-mod-dropTarget { + background: var(--jp-brand-color3); +} + +.jp-DirListing-item:hover:not(.jp-mod-selected) { + background: var(--jp-layout-color2); +} + +.jp-DirListing-itemIcon { + flex: 0 0 20px; + margin-right: 4px; +} + +.jp-DirListing-itemText { + flex: 1 0 64px; + white-space: nowrap; + overflow: hidden; + text-overflow: ellipsis; + user-select: none; +} + +.jp-DirListing-itemModified { + flex: 0 0 125px; + text-align: right; +} + +.jp-DirListing-editor { + flex: 1 0 64px; + outline: none; + border: none; +} + +.jp-DirListing-item.jp-mod-running .jp-DirListing-itemIcon:before { + color: limegreen; + content: '\25CF'; + font-size: 8px; + position: absolute; + left: -8px; +} + +.jp-DirListing-item.lm-mod-drag-image, +.jp-DirListing-item.jp-mod-selected.lm-mod-drag-image { + font-size: var(--jp-ui-font-size1); + padding-left: 4px; + margin-left: 4px; + width: 160px; + background-color: var(--jp-ui-inverse-font-color2); + box-shadow: var(--jp-elevation-z2); + border-radius: 0px; + color: var(--jp-ui-font-color1); + transform: translateX(-40%) translateY(-58%); +} + +.jp-DirListing-deadSpace { + flex: 1 1 auto; + margin: 0; + padding: 0; + list-style-type: none; + overflow: auto; + background-color: var(--jp-layout-color1); +} + +.jp-Document { + min-width: 120px; + min-height: 120px; + outline: none; +} + +.jp-FileDialog.jp-mod-conflict input { + color: red; +} + +.jp-FileDialog .jp-new-name-title { + margin-top: 12px; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/* This file was auto-generated by ensurePackage() in @jupyterlab/buildutils */ + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/*----------------------------------------------------------------------------- +| Private CSS variables +|----------------------------------------------------------------------------*/ + +:root { +} + +/*----------------------------------------------------------------------------- +| Main OutputArea +| OutputArea has a list of Outputs +|----------------------------------------------------------------------------*/ + +.jp-OutputArea { + overflow-y: auto; +} + +.jp-OutputArea-child { + display: flex; + flex-direction: row; +} + +.jp-OutputPrompt { + flex: 0 0 var(--jp-cell-prompt-width); + color: var(--jp-cell-outprompt-font-color); + font-family: var(--jp-cell-prompt-font-family); + padding: var(--jp-code-padding); + letter-spacing: var(--jp-cell-prompt-letter-spacing); + line-height: var(--jp-code-line-height); + font-size: var(--jp-code-font-size); + border: var(--jp-border-width) solid transparent; + opacity: var(--jp-cell-prompt-opacity); + /* Right align prompt text, don't wrap to handle large prompt numbers */ + text-align: right; + white-space: nowrap; + overflow: hidden; + text-overflow: ellipsis; + /* Disable text selection */ + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; +} + +.jp-OutputArea-output { + height: auto; + overflow: auto; + user-select: text; + -moz-user-select: text; + -webkit-user-select: text; + -ms-user-select: text; +} + +.jp-OutputArea-child .jp-OutputArea-output { + flex-grow: 1; + flex-shrink: 1; +} + +/** + * Isolated output. + */ +.jp-OutputArea-output.jp-mod-isolated { + width: 100%; + display: block; +} + +/* +When drag events occur, `p-mod-override-cursor` is added to the body. +Because iframes steal all cursor events, the following two rules are necessary +to suppress pointer events while resize drags are occurring. There may be a +better solution to this problem. +*/ +body.lm-mod-override-cursor .jp-OutputArea-output.jp-mod-isolated { + position: relative; +} + +body.lm-mod-override-cursor .jp-OutputArea-output.jp-mod-isolated:before { + content: ''; + position: absolute; + top: 0; + left: 0; + right: 0; + bottom: 0; + background: transparent; +} + +/* pre */ + +.jp-OutputArea-output pre { + border: none; + margin: 0px; + padding: 0px; + overflow-x: auto; + overflow-y: auto; + word-break: break-all; + word-wrap: break-word; + white-space: pre-wrap; +} + +/* tables */ + +.jp-OutputArea-output.jp-RenderedHTMLCommon table { + margin-left: 0; + margin-right: 0; +} + +/* description lists */ + +.jp-OutputArea-output dl, +.jp-OutputArea-output dt, +.jp-OutputArea-output dd { + display: block; +} + +.jp-OutputArea-output dl { + width: 100%; + overflow: hidden; + padding: 0; + margin: 0; +} + +.jp-OutputArea-output dt { + font-weight: bold; + float: left; + width: 20%; + padding: 0; + margin: 0; +} + +.jp-OutputArea-output dd { + float: left; + width: 80%; + padding: 0; + margin: 0; +} + +/* Hide the gutter in case of + * - nested output areas (e.g. in the case of output widgets) + * - mirrored output areas + */ +.jp-OutputArea .jp-OutputArea .jp-OutputArea-prompt { + display: none; +} + +/*----------------------------------------------------------------------------- +| executeResult is added to any Output-result for the display of the object +| returned by a cell +|----------------------------------------------------------------------------*/ + +.jp-OutputArea-output.jp-OutputArea-executeResult { + margin-left: 0px; + flex: 1 1 auto; +} + +.jp-OutputArea-executeResult.jp-RenderedText { + padding-top: var(--jp-code-padding); +} + +/*----------------------------------------------------------------------------- +| The Stdin output +|----------------------------------------------------------------------------*/ + +.jp-OutputArea-stdin { + line-height: var(--jp-code-line-height); + padding-top: var(--jp-code-padding); + display: flex; +} + +.jp-Stdin-prompt { + color: var(--jp-content-font-color0); + padding-right: var(--jp-code-padding); + vertical-align: baseline; + flex: 0 0 auto; +} + +.jp-Stdin-input { + font-family: var(--jp-code-font-family); + font-size: inherit; + color: inherit; + background-color: inherit; + width: 42%; + min-width: 200px; + /* make sure input baseline aligns with prompt */ + vertical-align: baseline; + /* padding + margin = 0.5em between prompt and cursor */ + padding: 0em 0.25em; + margin: 0em 0.25em; + flex: 0 0 70%; +} + +.jp-Stdin-input:focus { + box-shadow: none; +} + +/*----------------------------------------------------------------------------- +| Output Area View +|----------------------------------------------------------------------------*/ + +.jp-LinkedOutputView .jp-OutputArea { + height: 100%; + display: block; +} + +.jp-LinkedOutputView .jp-OutputArea-output:only-child { + height: 100%; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/* This file was auto-generated by ensurePackage() in @jupyterlab/buildutils */ + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +.jp-Collapser { + flex: 0 0 var(--jp-cell-collapser-width); + padding: 0px; + margin: 0px; + border: none; + outline: none; + background: transparent; + border-radius: var(--jp-border-radius); + opacity: 1; +} + +.jp-Collapser-child { + display: block; + width: 100%; + box-sizing: border-box; + /* height: 100% doesn't work because the height of its parent is computed from content */ + position: absolute; + top: 0px; + bottom: 0px; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/*----------------------------------------------------------------------------- +| Header/Footer +|----------------------------------------------------------------------------*/ + +/* Hidden by zero height by default */ +.jp-CellHeader, +.jp-CellFooter { + height: 0px; + width: 100%; + padding: 0px; + margin: 0px; + border: none; + outline: none; + background: transparent; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/*----------------------------------------------------------------------------- +| Input +|----------------------------------------------------------------------------*/ + +/* All input areas */ +.jp-InputArea { + display: flex; + flex-direction: row; +} + +.jp-InputArea-editor { + flex: 1 1 auto; +} + +.jp-InputArea-editor { + /* This is the non-active, default styling */ + border: var(--jp-border-width) solid var(--jp-cell-editor-border-color); + border-radius: 0px; + background: var(--jp-cell-editor-background); +} + +.jp-InputPrompt { + flex: 0 0 var(--jp-cell-prompt-width); + color: var(--jp-cell-inprompt-font-color); + font-family: var(--jp-cell-prompt-font-family); + padding: var(--jp-code-padding); + letter-spacing: var(--jp-cell-prompt-letter-spacing); + opacity: var(--jp-cell-prompt-opacity); + line-height: var(--jp-code-line-height); + font-size: var(--jp-code-font-size); + border: var(--jp-border-width) solid transparent; + opacity: var(--jp-cell-prompt-opacity); + /* Right align prompt text, don't wrap to handle large prompt numbers */ + text-align: right; + white-space: nowrap; + overflow: hidden; + text-overflow: ellipsis; + /* Disable text selection */ + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/*----------------------------------------------------------------------------- +| Placeholder +|----------------------------------------------------------------------------*/ + +.jp-Placeholder { + display: flex; + flex-direction: row; + flex: 1 1 auto; +} + +.jp-Placeholder-prompt { + box-sizing: border-box; +} + +.jp-Placeholder-content { + flex: 1 1 auto; + border: none; + background: transparent; + height: 20px; + box-sizing: border-box; +} + +.jp-Placeholder-content .jp-MoreHorizIcon { + width: 32px; + height: 16px; + border: 1px solid transparent; + border-radius: var(--jp-border-radius); +} + +.jp-Placeholder-content .jp-MoreHorizIcon:hover { + border: 1px solid var(--jp-border-color1); + box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.25); + background-color: var(--jp-layout-color0); +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/*----------------------------------------------------------------------------- +| Private CSS variables +|----------------------------------------------------------------------------*/ + +:root { + --jp-private-cell-scrolling-output-offset: 5px; +} + +/*----------------------------------------------------------------------------- +| Cell +|----------------------------------------------------------------------------*/ + +.jp-Cell { + padding: var(--jp-cell-padding); + margin: 0px; + border: none; + outline: none; + background: transparent; +} + +/*----------------------------------------------------------------------------- +| Common input/output +|----------------------------------------------------------------------------*/ + +.jp-Cell-inputWrapper, +.jp-Cell-outputWrapper { + display: flex; + flex-direction: row; + padding: 0px; + margin: 0px; + /* Added to reveal the box-shadow on the input and output collapsers. */ + overflow: visible; +} + +/* Only input/output areas inside cells */ +.jp-Cell-inputArea, +.jp-Cell-outputArea { + flex: 1 1 auto; +} + +/*----------------------------------------------------------------------------- +| Collapser +|----------------------------------------------------------------------------*/ + +/* Make the output collapser disappear when there is not output, but do so + * in a manner that leaves it in the layout and preserves its width. + */ +.jp-Cell.jp-mod-noOutputs .jp-Cell-outputCollapser { + border: none !important; + background: transparent !important; +} + +.jp-Cell:not(.jp-mod-noOutputs) .jp-Cell-outputCollapser { + min-height: var(--jp-cell-collapser-min-height); +} + +/*----------------------------------------------------------------------------- +| Output +|----------------------------------------------------------------------------*/ + +/* Put a space between input and output when there IS output */ +.jp-Cell:not(.jp-mod-noOutputs) .jp-Cell-outputWrapper { + margin-top: 5px; +} + +/* Text output with the Out[] prompt needs a top padding to match the + * alignment of the Out[] prompt itself. + */ +.jp-OutputArea-executeResult .jp-RenderedText.jp-OutputArea-output { + padding-top: var(--jp-code-padding); +} + +.jp-CodeCell.jp-mod-outputsScrolled .jp-Cell-outputArea { + overflow-y: auto; + max-height: 200px; + box-shadow: inset 0 0 6px 2px rgba(0, 0, 0, 0.3); + margin-left: var(--jp-private-cell-scrolling-output-offset); +} + +.jp-CodeCell.jp-mod-outputsScrolled .jp-OutputArea-prompt { + flex: 0 0 + calc( + var(--jp-cell-prompt-width) - + var(--jp-private-cell-scrolling-output-offset) + ); +} + +/*----------------------------------------------------------------------------- +| CodeCell +|----------------------------------------------------------------------------*/ + +/*----------------------------------------------------------------------------- +| MarkdownCell +|----------------------------------------------------------------------------*/ + +.jp-MarkdownOutput { + flex: 1 1 auto; + margin-top: 0; + margin-bottom: 0; + padding-left: var(--jp-code-padding); +} + +.jp-MarkdownOutput.jp-RenderedHTMLCommon { + overflow: auto; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/* This file was auto-generated by ensurePackage() in @jupyterlab/buildutils */ + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/*----------------------------------------------------------------------------- +| Variables +|----------------------------------------------------------------------------*/ + +/*----------------------------------------------------------------------------- + +/*----------------------------------------------------------------------------- +| Styles +|----------------------------------------------------------------------------*/ + +.jp-NotebookPanel-toolbar { + padding: 2px; +} + +.jp-Toolbar-item.jp-Notebook-toolbarCellType .jp-select-wrapper.jp-mod-focused { + border: none; + box-shadow: none; +} + +.jp-Notebook-toolbarCellTypeDropdown select { + height: 24px; + font-size: var(--jp-ui-font-size1); + line-height: 14px; + border-radius: 0; + display: block; +} + +.jp-Notebook-toolbarCellTypeDropdown span { + top: 5px !important; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/*----------------------------------------------------------------------------- +| Private CSS variables +|----------------------------------------------------------------------------*/ + +:root { + --jp-private-notebook-dragImage-width: 304px; + --jp-private-notebook-dragImage-height: 36px; + --jp-private-notebook-selected-color: var(--md-blue-400); + --jp-private-notebook-active-color: var(--md-green-400); +} + +/*----------------------------------------------------------------------------- +| Imports +|----------------------------------------------------------------------------*/ + +/*----------------------------------------------------------------------------- +| Notebook +|----------------------------------------------------------------------------*/ + +.jp-NotebookPanel { + display: block; + height: 100%; +} + +.jp-NotebookPanel.jp-Document { + min-width: 240px; + min-height: 120px; +} + +.jp-Notebook { + padding: var(--jp-notebook-padding); + outline: none; + overflow: auto; + background: var(--jp-layout-color0); +} + +.jp-Notebook.jp-mod-scrollPastEnd::after { + display: block; + content: ''; + min-height: var(--jp-notebook-scroll-padding); +} + +.jp-Notebook .jp-Cell { + overflow: visible; +} + +.jp-Notebook .jp-Cell .jp-InputPrompt { + cursor: move; +} + +/*----------------------------------------------------------------------------- +| Notebook state related styling +| +| The notebook and cells each have states, here are the possibilities: +| +| - Notebook +| - Command +| - Edit +| - Cell +| - None +| - Active (only one can be active) +| - Selected (the cells actions are applied to) +| - Multiselected (when multiple selected, the cursor) +| - No outputs +|----------------------------------------------------------------------------*/ + +/* Command or edit modes */ + +.jp-Notebook .jp-Cell:not(.jp-mod-active) .jp-InputPrompt { + opacity: var(--jp-cell-prompt-not-active-opacity); + color: var(--jp-cell-prompt-not-active-font-color); +} + +.jp-Notebook .jp-Cell:not(.jp-mod-active) .jp-OutputPrompt { + opacity: var(--jp-cell-prompt-not-active-opacity); + color: var(--jp-cell-prompt-not-active-font-color); +} + +/* cell is active */ +.jp-Notebook .jp-Cell.jp-mod-active .jp-Collapser { + background: var(--jp-brand-color1); +} + +/* collapser is hovered */ +.jp-Notebook .jp-Cell .jp-Collapser:hover { + box-shadow: var(--jp-elevation-z2); + background: var(--jp-brand-color1); + opacity: var(--jp-cell-collapser-not-active-hover-opacity); +} + +/* cell is active and collapser is hovered */ +.jp-Notebook .jp-Cell.jp-mod-active .jp-Collapser:hover { + background: var(--jp-brand-color0); + opacity: 1; +} + +/* Command mode */ + +.jp-Notebook.jp-mod-commandMode .jp-Cell.jp-mod-selected { + background: var(--jp-notebook-multiselected-color); +} + +.jp-Notebook.jp-mod-commandMode + .jp-Cell.jp-mod-active.jp-mod-selected:not(.jp-mod-multiSelected) { + background: transparent; +} + +/* Edit mode */ + +.jp-Notebook.jp-mod-editMode .jp-Cell.jp-mod-active .jp-InputArea-editor { + border: var(--jp-border-width) solid var(--jp-cell-editor-active-border-color); + box-shadow: var(--jp-input-box-shadow); + background-color: var(--jp-cell-editor-active-background); +} + +/*----------------------------------------------------------------------------- +| Notebook drag and drop +|----------------------------------------------------------------------------*/ + +.jp-Notebook-cell.jp-mod-dropSource { + opacity: 0.5; +} + +.jp-Notebook-cell.jp-mod-dropTarget, +.jp-Notebook.jp-mod-commandMode + .jp-Notebook-cell.jp-mod-active.jp-mod-selected.jp-mod-dropTarget { + border-top-color: var(--jp-private-notebook-selected-color); + border-top-style: solid; + border-top-width: 2px; +} + +.jp-dragImage { + display: flex; + flex-direction: row; + width: var(--jp-private-notebook-dragImage-width); + height: var(--jp-private-notebook-dragImage-height); + border: var(--jp-border-width) solid var(--jp-cell-editor-border-color); + background: var(--jp-cell-editor-background); + overflow: visible; +} + +.jp-dragImage-singlePrompt { + box-shadow: 2px 2px 4px 0px rgba(0, 0, 0, 0.12); +} + +.jp-dragImage .jp-dragImage-content { + flex: 1 1 auto; + z-index: 2; + font-size: var(--jp-code-font-size); + font-family: var(--jp-code-font-family); + line-height: var(--jp-code-line-height); + padding: var(--jp-code-padding); + border: var(--jp-border-width) solid var(--jp-cell-editor-border-color); + background: var(--jp-cell-editor-background-color); + color: var(--jp-content-font-color3); + text-align: left; + margin: 4px 4px 4px 0px; +} + +.jp-dragImage .jp-dragImage-prompt { + flex: 0 0 auto; + min-width: 36px; + color: var(--jp-cell-inprompt-font-color); + padding: var(--jp-code-padding); + padding-left: 12px; + font-family: var(--jp-cell-prompt-font-family); + letter-spacing: var(--jp-cell-prompt-letter-spacing); + line-height: 1.9; + font-size: var(--jp-code-font-size); + border: var(--jp-border-width) solid transparent; +} + +.jp-dragImage-multipleBack { + z-index: -1; + position: absolute; + height: 32px; + width: 300px; + top: 8px; + left: 8px; + background: var(--jp-layout-color2); + border: var(--jp-border-width) solid var(--jp-input-border-color); + box-shadow: 2px 2px 4px 0px rgba(0, 0, 0, 0.12); +} + +/*----------------------------------------------------------------------------- +| Cell toolbar +|----------------------------------------------------------------------------*/ + +.jp-NotebookTools { + display: block; + min-width: var(--jp-sidebar-min-width); + color: var(--jp-ui-font-color1); + background: var(--jp-layout-color1); + /* This is needed so that all font sizing of children done in ems is + * relative to this base size */ + font-size: var(--jp-ui-font-size1); + overflow: auto; +} + +.jp-NotebookTools-tool { + padding: 0px 12px 0 12px; +} + +.jp-ActiveCellTool { + padding: 12px; + background-color: var(--jp-layout-color1); + border-top: none !important; +} + +.jp-ActiveCellTool .jp-InputArea-prompt { + flex: 0 0 auto; + padding-left: 0px; +} + +.jp-ActiveCellTool .jp-InputArea-editor { + flex: 1 1 auto; + background: var(--jp-cell-editor-background); + border-color: var(--jp-cell-editor-border-color); +} + +.jp-ActiveCellTool .jp-InputArea-editor .CodeMirror { + background: transparent; +} + +.jp-MetadataEditorTool { + flex-direction: column; + padding: 12px 0px 12px 0px; +} + +.jp-RankedPanel > :not(:first-child) { + margin-top: 12px; +} + +.jp-KeySelector select.jp-mod-styled { + font-size: var(--jp-ui-font-size1); + color: var(--jp-ui-font-color0); + border: var(--jp-border-width) solid var(--jp-border-color1); +} + +.jp-KeySelector label, +.jp-MetadataEditorTool label { + line-height: 1.4; +} + +/*----------------------------------------------------------------------------- +| Presentation Mode (.jp-mod-presentationMode) +|----------------------------------------------------------------------------*/ + +.jp-mod-presentationMode .jp-Notebook { + --jp-content-font-size1: var(--jp-content-presentation-font-size1); + --jp-code-font-size: var(--jp-code-presentation-font-size); +} + +.jp-mod-presentationMode .jp-Notebook .jp-Cell .jp-InputPrompt, +.jp-mod-presentationMode .jp-Notebook .jp-Cell .jp-OutputPrompt { + flex: 0 0 110px; +} + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/* This file was auto-generated by ensurePackage() in @jupyterlab/buildutils */ + +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +</style> + + <style type="text/css"> +/*----------------------------------------------------------------------------- +| Copyright (c) Jupyter Development Team. +| Distributed under the terms of the Modified BSD License. +|----------------------------------------------------------------------------*/ + +/* +The following CSS variables define the main, public API for styling JupyterLab. +These variables should be used by all plugins wherever possible. In other +words, plugins should not define custom colors, sizes, etc unless absolutely +necessary. This enables users to change the visual theme of JupyterLab +by changing these variables. + +Many variables appear in an ordered sequence (0,1,2,3). These sequences +are designed to work well together, so for example, `--jp-border-color1` should +be used with `--jp-layout-color1`. The numbers have the following meanings: + +* 0: super-primary, reserved for special emphasis +* 1: primary, most important under normal situations +* 2: secondary, next most important under normal situations +* 3: tertiary, next most important under normal situations + +Throughout JupyterLab, we are mostly following principles from Google's +Material Design when selecting colors. We are not, however, following +all of MD as it is not optimized for dense, information rich UIs. +*/ + +:root { + /* Elevation + * + * We style box-shadows using Material Design's idea of elevation. These particular numbers are taken from here: + * + * https://github.com/material-components/material-components-web + * https://material-components-web.appspot.com/elevation.html + */ + + --jp-shadow-base-lightness: 0; + --jp-shadow-umbra-color: rgba( + var(--jp-shadow-base-lightness), + var(--jp-shadow-base-lightness), + var(--jp-shadow-base-lightness), + 0.2 + ); + --jp-shadow-penumbra-color: rgba( + var(--jp-shadow-base-lightness), + var(--jp-shadow-base-lightness), + var(--jp-shadow-base-lightness), + 0.14 + ); + --jp-shadow-ambient-color: rgba( + var(--jp-shadow-base-lightness), + var(--jp-shadow-base-lightness), + var(--jp-shadow-base-lightness), + 0.12 + ); + --jp-elevation-z0: none; + --jp-elevation-z1: 0px 2px 1px -1px var(--jp-shadow-umbra-color), + 0px 1px 1px 0px var(--jp-shadow-penumbra-color), + 0px 1px 3px 0px var(--jp-shadow-ambient-color); + --jp-elevation-z2: 0px 3px 1px -2px var(--jp-shadow-umbra-color), + 0px 2px 2px 0px var(--jp-shadow-penumbra-color), + 0px 1px 5px 0px var(--jp-shadow-ambient-color); + --jp-elevation-z4: 0px 2px 4px -1px var(--jp-shadow-umbra-color), + 0px 4px 5px 0px var(--jp-shadow-penumbra-color), + 0px 1px 10px 0px var(--jp-shadow-ambient-color); + --jp-elevation-z6: 0px 3px 5px -1px var(--jp-shadow-umbra-color), + 0px 6px 10px 0px var(--jp-shadow-penumbra-color), + 0px 1px 18px 0px var(--jp-shadow-ambient-color); + --jp-elevation-z8: 0px 5px 5px -3px var(--jp-shadow-umbra-color), + 0px 8px 10px 1px var(--jp-shadow-penumbra-color), + 0px 3px 14px 2px var(--jp-shadow-ambient-color); + --jp-elevation-z12: 0px 7px 8px -4px var(--jp-shadow-umbra-color), + 0px 12px 17px 2px var(--jp-shadow-penumbra-color), + 0px 5px 22px 4px var(--jp-shadow-ambient-color); + --jp-elevation-z16: 0px 8px 10px -5px var(--jp-shadow-umbra-color), + 0px 16px 24px 2px var(--jp-shadow-penumbra-color), + 0px 6px 30px 5px var(--jp-shadow-ambient-color); + --jp-elevation-z20: 0px 10px 13px -6px var(--jp-shadow-umbra-color), + 0px 20px 31px 3px var(--jp-shadow-penumbra-color), + 0px 8px 38px 7px var(--jp-shadow-ambient-color); + --jp-elevation-z24: 0px 11px 15px -7px var(--jp-shadow-umbra-color), + 0px 24px 38px 3px var(--jp-shadow-penumbra-color), + 0px 9px 46px 8px var(--jp-shadow-ambient-color); + + /* Borders + * + * The following variables, specify the visual styling of borders in JupyterLab. + */ + + --jp-border-width: 1px; + --jp-border-color0: var(--md-grey-400); + --jp-border-color1: var(--md-grey-400); + --jp-border-color2: var(--md-grey-300); + --jp-border-color3: var(--md-grey-200); + --jp-border-radius: 2px; + + /* UI Fonts + * + * The UI font CSS variables are used for the typography all of the JupyterLab + * user interface elements that are not directly user generated content. + * + * The font sizing here is done assuming that the body font size of --jp-ui-font-size1 + * is applied to a parent element. When children elements, such as headings, are sized + * in em all things will be computed relative to that body size. + */ + + --jp-ui-font-scale-factor: 1.2; + --jp-ui-font-size0: 0.83333em; + --jp-ui-font-size1: 13px; /* Base font size */ + --jp-ui-font-size2: 1.2em; + --jp-ui-font-size3: 1.44em; + + --jp-ui-font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Helvetica, + Arial, sans-serif, 'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol'; + + /* + * Use these font colors against the corresponding main layout colors. + * In a light theme, these go from dark to light. + */ + + /* Defaults use Material Design specification */ + --jp-ui-font-color0: rgba(0, 0, 0, 1); + --jp-ui-font-color1: rgba(0, 0, 0, 0.87); + --jp-ui-font-color2: rgba(0, 0, 0, 0.54); + --jp-ui-font-color3: rgba(0, 0, 0, 0.38); + + /* + * Use these against the brand/accent/warn/error colors. + * These will typically go from light to darker, in both a dark and light theme. + */ + + --jp-ui-inverse-font-color0: rgba(255, 255, 255, 1); + --jp-ui-inverse-font-color1: rgba(255, 255, 255, 1); + --jp-ui-inverse-font-color2: rgba(255, 255, 255, 0.7); + --jp-ui-inverse-font-color3: rgba(255, 255, 255, 0.5); + + /* Content Fonts + * + * Content font variables are used for typography of user generated content. + * + * The font sizing here is done assuming that the body font size of --jp-content-font-size1 + * is applied to a parent element. When children elements, such as headings, are sized + * in em all things will be computed relative to that body size. + */ + + --jp-content-line-height: 1.6; + --jp-content-font-scale-factor: 1.2; + --jp-content-font-size0: 0.83333em; + --jp-content-font-size1: 14px; /* Base font size */ + --jp-content-font-size2: 1.2em; + --jp-content-font-size3: 1.44em; + --jp-content-font-size4: 1.728em; + --jp-content-font-size5: 2.0736em; + + /* This gives a magnification of about 125% in presentation mode over normal. */ + --jp-content-presentation-font-size1: 17px; + + --jp-content-heading-line-height: 1; + --jp-content-heading-margin-top: 1.2em; + --jp-content-heading-margin-bottom: 0.8em; + --jp-content-heading-font-weight: 500; + + /* Defaults use Material Design specification */ + --jp-content-font-color0: rgba(0, 0, 0, 1); + --jp-content-font-color1: rgba(0, 0, 0, 0.87); + --jp-content-font-color2: rgba(0, 0, 0, 0.54); + --jp-content-font-color3: rgba(0, 0, 0, 0.38); + + --jp-content-link-color: var(--md-blue-700); + + --jp-content-font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', + Helvetica, Arial, sans-serif, 'Apple Color Emoji', 'Segoe UI Emoji', + 'Segoe UI Symbol'; + + /* + * Code Fonts + * + * Code font variables are used for typography of code and other monospaces content. + */ + + --jp-code-font-size: 13px; + --jp-code-line-height: 1.3077; /* 17px for 13px base */ + --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ + --jp-code-font-family-default: Menlo, Consolas, 'DejaVu Sans Mono', monospace; + --jp-code-font-family: var(--jp-code-font-family-default); + + /* This gives a magnification of about 125% in presentation mode over normal. */ + --jp-code-presentation-font-size: 16px; + + /* may need to tweak cursor width if you change font size */ + --jp-code-cursor-width0: 1.4px; + --jp-code-cursor-width1: 2px; + --jp-code-cursor-width2: 4px; + + /* Layout + * + * The following are the main layout colors use in JupyterLab. In a light + * theme these would go from light to dark. + */ + + --jp-layout-color0: white; + --jp-layout-color1: white; + --jp-layout-color2: var(--md-grey-200); + --jp-layout-color3: var(--md-grey-400); + --jp-layout-color4: var(--md-grey-600); + + /* Inverse Layout + * + * The following are the inverse layout colors use in JupyterLab. In a light + * theme these would go from dark to light. + */ + + --jp-inverse-layout-color0: #111111; + --jp-inverse-layout-color1: var(--md-grey-900); + --jp-inverse-layout-color2: var(--md-grey-800); + --jp-inverse-layout-color3: var(--md-grey-700); + --jp-inverse-layout-color4: var(--md-grey-600); + + /* Brand/accent */ + + --jp-brand-color0: var(--md-blue-700); + --jp-brand-color1: var(--md-blue-500); + --jp-brand-color2: var(--md-blue-300); + --jp-brand-color3: var(--md-blue-100); + --jp-brand-color4: var(--md-blue-50); + + --jp-accent-color0: var(--md-green-700); + --jp-accent-color1: var(--md-green-500); + --jp-accent-color2: var(--md-green-300); + --jp-accent-color3: var(--md-green-100); + + /* State colors (warn, error, success, info) */ + + --jp-warn-color0: var(--md-orange-700); + --jp-warn-color1: var(--md-orange-500); + --jp-warn-color2: var(--md-orange-300); + --jp-warn-color3: var(--md-orange-100); + + --jp-error-color0: var(--md-red-700); + --jp-error-color1: var(--md-red-500); + --jp-error-color2: var(--md-red-300); + --jp-error-color3: var(--md-red-100); + + --jp-success-color0: var(--md-green-700); + --jp-success-color1: var(--md-green-500); + --jp-success-color2: var(--md-green-300); + --jp-success-color3: var(--md-green-100); + + --jp-info-color0: var(--md-cyan-700); + --jp-info-color1: var(--md-cyan-500); + --jp-info-color2: var(--md-cyan-300); + --jp-info-color3: var(--md-cyan-100); + + /* Cell specific styles */ + + --jp-cell-padding: 5px; + + --jp-cell-collapser-width: 8px; + --jp-cell-collapser-min-height: 20px; + --jp-cell-collapser-not-active-hover-opacity: 0.6; + + --jp-cell-editor-background: var(--md-grey-100); + --jp-cell-editor-border-color: var(--md-grey-300); + --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); + --jp-cell-editor-active-background: var(--jp-layout-color0); + --jp-cell-editor-active-border-color: var(--jp-brand-color1); + + --jp-cell-prompt-width: 64px; + --jp-cell-prompt-font-family: 'Source Code Pro', monospace; + --jp-cell-prompt-letter-spacing: 0px; + --jp-cell-prompt-opacity: 1; + --jp-cell-prompt-not-active-opacity: 0.5; + --jp-cell-prompt-not-active-font-color: var(--md-grey-700); + /* A custom blend of MD grey and blue 600 + * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ + --jp-cell-inprompt-font-color: #307fc1; + /* A custom blend of MD grey and orange 600 + * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ + --jp-cell-outprompt-font-color: #bf5b3d; + + /* Notebook specific styles */ + + --jp-notebook-padding: 10px; + --jp-notebook-select-background: var(--jp-layout-color1); + --jp-notebook-multiselected-color: var(--md-blue-50); + + /* The scroll padding is calculated to fill enough space at the bottom of the + notebook to show one single-line cell (with appropriate padding) at the top + when the notebook is scrolled all the way to the bottom. We also subtract one + pixel so that no scrollbar appears if we have just one single-line cell in the + notebook. This padding is to enable a 'scroll past end' feature in a notebook. + */ + --jp-notebook-scroll-padding: calc( + 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - + var(--jp-code-padding) - var(--jp-cell-padding) - 1px + ); + + /* Rendermime styles */ + + --jp-rendermime-error-background: #fdd; + --jp-rendermime-table-row-background: var(--md-grey-100); + --jp-rendermime-table-row-hover-background: var(--md-light-blue-50); + + /* Dialog specific styles */ + + --jp-dialog-background: rgba(0, 0, 0, 0.25); + + /* Console specific styles */ + + --jp-console-padding: 10px; + + /* Toolbar specific styles */ + + --jp-toolbar-border-color: var(--jp-border-color1); + --jp-toolbar-micro-height: 8px; + --jp-toolbar-background: var(--jp-layout-color1); + --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.24); + --jp-toolbar-header-margin: 4px 4px 0px 4px; + --jp-toolbar-active-background: var(--md-grey-300); + + /* Input field styles */ + + --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); + --jp-input-active-background: var(--jp-layout-color1); + --jp-input-hover-background: var(--jp-layout-color1); + --jp-input-background: var(--md-grey-100); + --jp-input-border-color: var(--jp-border-color1); + --jp-input-active-border-color: var(--jp-brand-color1); + --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); + + /* General editor styles */ + + --jp-editor-selected-background: #d9d9d9; + --jp-editor-selected-focused-background: #d7d4f0; + --jp-editor-cursor-color: var(--jp-ui-font-color0); + + /* Code mirror specific styles */ + + --jp-mirror-editor-keyword-color: #008000; + --jp-mirror-editor-atom-color: #88f; + --jp-mirror-editor-number-color: #080; + --jp-mirror-editor-def-color: #00f; + --jp-mirror-editor-variable-color: var(--md-grey-900); + --jp-mirror-editor-variable-2-color: #05a; + --jp-mirror-editor-variable-3-color: #085; + --jp-mirror-editor-punctuation-color: #05a; + --jp-mirror-editor-property-color: #05a; + --jp-mirror-editor-operator-color: #aa22ff; + --jp-mirror-editor-comment-color: #408080; + --jp-mirror-editor-string-color: #ba2121; + --jp-mirror-editor-string-2-color: #708; + --jp-mirror-editor-meta-color: #aa22ff; + --jp-mirror-editor-qualifier-color: #555; + --jp-mirror-editor-builtin-color: #008000; + --jp-mirror-editor-bracket-color: #997; + --jp-mirror-editor-tag-color: #170; + --jp-mirror-editor-attribute-color: #00c; + --jp-mirror-editor-header-color: blue; + --jp-mirror-editor-quote-color: #090; + --jp-mirror-editor-link-color: #00c; + --jp-mirror-editor-error-color: #f00; + --jp-mirror-editor-hr-color: #999; + + /* Vega extension styles */ + + --jp-vega-background: white; + + /* Sidebar-related styles */ + + --jp-sidebar-min-width: 180px; + + /* Search-related styles */ + + --jp-search-toggle-off-opacity: 0.5; + --jp-search-toggle-hover-opacity: 0.8; + --jp-search-toggle-on-opacity: 1; + --jp-search-selected-match-background-color: rgb(245, 200, 0); + --jp-search-selected-match-color: black; + --jp-search-unselected-match-background-color: var( + --jp-inverse-layout-color0 + ); + --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); + + /* Icon colors that work well with light or dark backgrounds */ + --jp-icon-contrast-color0: var(--md-purple-600); + --jp-icon-contrast-color1: var(--md-green-600); + --jp-icon-contrast-color2: var(--md-pink-600); + --jp-icon-contrast-color3: var(--md-blue-600); +} +</style> + +<style type="text/css"> +a.anchor-link { + display: none; +} +.highlight { + margin: 0.4em; +} + +/* Input area styling */ +.jp-InputArea { + overflow: hidden; +} + +.jp-InputArea-editor { + overflow: hidden; +} + +@media print { + body { + margin: 0; + } +} +</style> + + + +<!-- Load mathjax --> + <script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.7/latest.js?config=TeX-MML-AM_CHTML-full,Safe"> </script> + <!-- MathJax configuration --> + <script type="text/x-mathjax-config"> + init_mathjax = function() { + if (window.MathJax) { + // MathJax loaded + MathJax.Hub.Config({ + TeX: { + equationNumbers: { + autoNumber: "AMS", + useLabelIds: true + } + }, + tex2jax: { + inlineMath: [ ['$','$'], ["\\(","\\)"] ], + displayMath: [ ['$$','$$'], ["\\[","\\]"] ], + processEscapes: true, + processEnvironments: true + }, + displayAlign: 'center', + CommonHTML: { + linebreaks: { + automatic: true + } + }, + "HTML-CSS": { + linebreaks: { + automatic: true + } + } + }); + + MathJax.Hub.Queue(["Typeset", MathJax.Hub]); + } + } + init_mathjax(); + </script> + <!-- End of mathjax configuration --></head> +<body class="jp-Notebook" data-jp-theme-light="true" data-jp-theme-name="JupyterLab Light"> + +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<h1 id="José-Miguel-Ladino-Méndez---Maestría-en-Ciencias-Astronomía---UNAL">José Miguel Ladino Méndez - Maestría en Ciencias Astronomía - UNAL<a class="anchor-link" href="#José-Miguel-Ladino-Méndez---Maestría-en-Ciencias-Astronomía---UNAL">¶</a></h1><h1 id="LACoNGA-Physics---Ciencia-de-Datos---Tarea-Clase-05">LACoNGA Physics - Ciencia de Datos - Tarea-Clase-05<a class="anchor-link" href="#LACoNGA-Physics---Ciencia-de-Datos---Tarea-Clase-05">¶</a></h1> +</div> +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<h2 id="Ejercicios-para-practicar-numpy-y-optimización-con-scipy">Ejercicios para practicar numpy y optimización con scipy<a class="anchor-link" href="#Ejercicios-para-practicar-numpy-y-optimización-con-scipy">¶</a></h2><h2 id="Resolución-espacial">Resolución espacial<a class="anchor-link" href="#Resolución-espacial">¶</a></h2><ul> +<li>En observaciones astronómicas e imágenes en general, llamamos resolución espacial +a la distancia angular minima a la que pueden estar dos fuentes puntuales de luz +y aun poder ser reconocidas como objetos individuales. +En el caso de la astronomÃa, este efecto tiene que ver con la dispersión de la +luz al atravezar la atmósfera, la cual hace que una estrella, que deberÃa +en principio aparecer como una fuente puntual (pues las estrellas están muy +lejos), aparezca en cambio como una mancha. AsÃ, si dos estrellas están +demasiado cerca sus manchas se superpondrán hasta el punto en que sea imposible +distinguirlas como fuentes individuales. +Para modelar este efecto, tÃpicamente consideramos la acción de la atmósfera +como la convolución de la imagen "perfecta" (como se verÃa desde el espacio) +con un kernel gaussiano. El ancho de esa función gaussiana 2D caracteriza +las condiciones de observación, varÃa con las condiciones climáticas y para +cada sitio de la Tierra. +La resolución espacial normalmente se toma como el FWHM +de la gaussiana caracteristica registrada durante una observación. Es decir, +si dos estrellas están a una distancia aparente en el cielo menor que el +FWHM del efecto atmosférico, la luz de ambas fuentes se mezclará después de +la convolución hasta el punto de impedir reconocerlas de modo individual. +Además, la atmósfera puede interactuar de maneras distintas con la luz de +distintas longitudes de onda, de manera que el ancho de la gaussiana puede +ser distinto para observaciones con diferentes filtros. +El objetivo de esta tarea es medir de forma aproximada la resolución +espacial en una noche de observación en Zapatoca, Santander (Colombia), a partir +de una foto del cielo estrellado.</li> +</ul> +<ul> +<li>El objetivo de esta tarea es medir de forma aproximada la resolución +espacial en una noche de observación en Zapatoca, Santander (Colombia), a partir +de una foto del cielo estrellado. +## Ejercicio:</li> +<li>Leer la imagen almacenada en la carpeta data como un array de numpy. Ese +array estará compuesto de 3 matrices, una tras otra, correspondiente a los +canales R,G,B.</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [99]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span> <span class="c1">#librerÃa util para manejar los array y funciones matemáticas</span> +<span class="kn">from</span> <span class="nn">PIL</span> <span class="kn">import</span> <span class="n">Image</span> <span class="c1">#Módulo para abrir imagen.</span> + +<span class="n">imagen</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="s1">'data/zapatocaImage.jpeg'</span><span class="p">))</span> <span class="c1">#volviendo imagen en array</span> +<span class="c1">#print(imagen)</span> +</pre></div> + + </div> +</div> +</div> +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>Combinar los 3 array para generar una versión blanco y negro de la imagen, +en la cual ella consiste de una sola matriz 2D. Puede usar su intuición y prueba +y error para combinar las 3 imágenes, explicando el procedimiento elegido. Esto +será más interesante que usar un comando desconocido de una biblioteca sofisticada +que haga las cosas como una caja negra (queremos practicar numpy).</li> +</ul> + +</div> +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>Algunas maneras que se encontrarón para combinar los array RGB son:</li> +</ul> + +</div> +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<p><strong>1)</strong> Tomando el promedio aritmético para cada pixel</p> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [899]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Escalagrises2</span> <span class="o">=</span> <span class="n">imagen</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span> <span class="c1">#Toma el promedio aritmético para cada pixel (R+G+B/3)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">Escalagrises2</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> <span class="c1">#muestra imagen en escala de grises</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +<span class="nb">print</span><span class="p">(</span><span class="n">Escalagrises2</span><span class="o">.</span><span class="n">ndim</span><span class="p">)</span> <span class="c1">#dim del array</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + +<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain"> +<pre>2 +</pre> +</div> +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<p><strong>2)</strong> Usando la formula lineal estandar de Luma de brillo en una imagen [1]</p> +<ul> +<li>[1] : <a href="https://en.wikipedia.org/wiki/Grayscale">https://en.wikipedia.org/wiki/Grayscale</a></li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [438]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Escalagrises3</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">empty_like</span><span class="p">(</span><span class="n">imagen</span><span class="p">)</span> <span class="c1">#array del mismo shape</span> +<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">3</span><span class="p">):</span> + <span class="n">Escalagrises3</span><span class="p">[:,:,</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.299</span><span class="o">*</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="mf">0.587</span><span class="o">*</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">1</span><span class="p">]</span><span class="o">+</span><span class="mf">0.114</span><span class="o">*</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">2</span><span class="p">]</span> <span class="c1">#aplicando formula Luma a cada pixel</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">Escalagrises3</span><span class="p">[:,:,</span><span class="mi">0</span><span class="p">],</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +<span class="nb">print</span><span class="p">(</span><span class="n">Escalagrises3</span><span class="p">[:,:,</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">ndim</span><span class="p">)</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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DqdIp1OI5fLOTQ+Go2Qy+XcPa1WC+PxGNVqFaVSybXj/Pwc7XYb29vb2N3dRTab9aJK4IYxieh9DE3FoYzIwW+3267dFrWoMOXz+cR7VEEQOVna8z4WdR3ZxuFw6Nrqc+us0lbXXY2yKtJ1wmMNHifUGCNWQ8Bn7SQgi89V1mLjv4qcLaJaLBZOYOm9qSItFouYTCYJmgPLGKcaBe17GIZuopb0Zh/v3LmDVCqF58+fJwwK21gsFl17GAbhhCFXyBJQTCaTlXdQkatiLJVKGI1GK16R0kbHXK9x7sIqbFVY1vPRsfEBHQ2J6DNRFCWMBPnG1sEJb+oS5UG9z1fUk9I+W57QelgvwZuCMw2tkb4+oOPzhhPteuWv/wKKKgUgaWFtHud4PMZkMnGKvlgsuue4us2iKFVEOuGhxqLZbCIMQ6eIaUVPT0/RbrdRq9XcykzG6MbjMS4vL1Gv15FKpVxb6HJR8VhmZn947zoG5qcyviJSG0sko/oQlIYClD4Wkdj3a/1ULKpEyIh0rZXu6mWwH6pkbSzQLkKxQqvt4af1MGyd1oACSCgzRaPaV42x6phZ2ufzeVc/DZXymbZbwxU2BU371el0nGegCprtV1nRMAs9MkV5bLd6UeyfhgmotC19lfd00lgVTiaTwbe//W386Ec/Qr/fx3vvvYenT586Y6ZI1Rpu6xHZNqrC1+dU8el33qehS8tPWoeVIeUP69HxOumu9+t9urBOU3PZNxom9Win0+lK+2y5VYrbuqd0DUkIm50wmUzQ6XTQaDSQTqdRKBTQbrcxHo8TebKqOKmcVEA4EHxXNpvF1taWQ9bMCkilUuj3+85gBMFNjLrdbqPf7+Pi4gL7+/sJY6ACr30FVvfqsMKiz7Ntmidr44FRFGE4HCYUkG9i1Bb1btg+vlPRP4CEi6190XdZYVeDoF6CjqtlVhtK0NxuzQuPouWkXaVSQbPZdM9SoWiIRRUGERGLtl1DdltbW2i1WgCWIQ96HjbkQ9SsfKwKsF6vo91ur0X+Sje+v9vtolKpeF1uojZFfjbso79Z0KDjZsMLOq4ajrLtVKVGWjx//twZlCdPniTGzfKMlQuOZ7lcTiQX6Ps13GbpYeumt2G9YP5O+ll9YEEeeU29E18ITtvkMy46NtzXR1E5PaZ1HgDLrVHclpE1j5eTMNx7RC38aDTCy5cvHVIYj8crzMEB4KfOTCsiyuVyyOfzjhF5vd1u4+joyClwm89Lw5DP591Se40768BQkdlFLesEWZVTEAQJS89nmQ2ijM1YOpE3i8+SKxJhn9lWRZ+qVIgebEjKIhvWp2MG3LigdNctElJFT49Gi8YjSX8uZGKf1GDS2KhCUwVmlTpjwKlUCp1Ox91fqVScgs7lco7fLHrUcWg0Gmi322i1Wgk3OooiN9E5HA4TGyipciAQ0T6pkrI8ZsdajbxFyNbz87noNq7MeyeTiRtH0gIAXr586erX1EdgiUgtT2udqpRtBlUURS67SOeuwjDE22+/jcvLS5e6qf2j90GDTJpZQGMBHouCEIvabcxa++HzKjgOfLfm6c9mM8cDr9IJwC3JKlHCKGMpw3ES0KZsUQnmcrnErLoiLBZ9FkjGqpjDTKTAz8vLS+fqaXK85mxyQiGdTmN/f98pf30/lYAVLItmfQiEio31ad/oQVgUZwWZTOuL2WnsOZVKoVKprAiNNZaqMBSd22JjpLz/nXfewebmZiKlzzebz2ta3zrjQ2Nv3Wr1JGx/fKlsbBPHl5uYRVGEs7MzFwpiSEHRlaI59r3dbrv9bVjoXs9mMzepvs5dpzBzTOjJxXGcWLpvlYcW5RtFqwC8Bk3pYflPf+M1jfvbdmj8HAB2d3e9e/OwPipb/Y3tnkwmK3sFZbNZNBoNlEolB2Rs+7TtFiXTe7Ngw9c29XSUX9XzsjJO2beGM5/Pu4y4VCqVSAt9Xbk1iFutGcMPFERdru6baGo2m4k8X2vxfLFOJRaJzcnO2WyGbrcLYKmkZrOZizFqXbS2zBkmeuIqUF88TRWidfl4r/bN5j2TWXxurnoRuVwuEf4BluEGLjyyNNR26uSf3UUOWCoOH3NZwVAXVpVAEAR4+vTpSh1EZxqrtUbdKgarXOw7VUn73FUqG0Xk/H1jY8OFSHzIymaS2LFW78x6ADaOyfxsKieL1jQGXy6X3bJoKhkbktKihksNGtukWReqEMk7ypOWl/UaPxUNk99LpRIqlQouLi7QbDYT3oVtN/+3E81q2NQQzedz/OAHP8BsNnPgRPtuZUrb6gM4/Fy3NS/rBZL54LbwmgJOPkedwUlj9T4pe68Kl9waxa2CFgTLWI8qbM4Mr0OVnIwkcrOxq1cJsFo97pORy+VcXjDdQNalig24GTwKUhiGuHPnDq6urhLxP1Vs2gcfQwJwqY6tVmslk0TrIDOoEqMLrzTViSxFhlriOE7EaoleqNiApRCOx2PHaKqYlK6KprWvUZTMrNGiSMe6q1qfCrkKmNJBU+iUD2gALR04ruQdZt9ofWybpptqsUZD/1clopNRwE1++mKxQKFQcCjflji+2adZFYM1dFaR6DJy/c3OVyjYULnRcdS++cZQjSd/0zCnhjMt6laAZvuiIMx+Z+iuVCq5EKHdatjGnVm3ReCkKXUCx1mBgV5jn23hb+ppW09H0wYZ7qT+8xkDN25rf/k9LuoiLhYLp4i5lwhzmBkXtDnEQHJg18VnVYijKHICQiGnxeb7q9WqWxZNNKRxahWu670FcO/ePTcJxaKDoPFoq5AVqdKF9ilGNQZWSOw7VfB8YQcb5yXt+Bu9ENan+2roe3iNEyxBsFwUoocm8D6NJ2ohauJ+yTbjggqFqFxDEOQRjp0qKp+XEoahG4vpdJrIlNC+6XOlUgm9Xs/1RffasPF5VWzWqPF+joHNwlGvka62PbxD6/bFi/VdVkGzWLRsDQDbwffaFE/rFZF/LUjRLBrfJ58n7TS5QOlmEb/OgwA3i7DIy2yDzWZZF5tmvdbo6pja8dH367305FgUeSu9LQiwoMVXbkWMm4XKRzMF7Kq0QqGwIpDA+pVNOpHhY8ggCFCv11GtVhGGy2WuVAi64ZEvxsdMhnK5jFqthnq9jihaZrvoBjT6PrZJhdTGZskwXBik4REb8rHPKS1UESt9+Rtpxeft7/zj5BiLCoumOFHA6fZrloN9TplUC40G0ZmNGasnoBOUwFJoud2tImxrwNRDUc9ODbE+b2mkHhIXpZDPVKiJ8HzG1aJe5SurxLkhGg2iFt+8AOvUQl5SOisf2f5aT8GOlYYadDyUjgqi2Dfdx4XtqFarjraZTMahZj6jxkk9cEtTK6NadDU0f+duh8q3/F1XN6rBU4Vr9QHbYOdT1hUaKiunPkNsy61A3IoyOfDMhVbrS0umsS9lcg5oHCdzwdUN4wQAlyxz0U06ncZ4PEa73XZMyBnwSqWCdrudyI0tFovY3t528d5KpYJMJoNyuZxYms6i6WsWjalyUqtvFZ1mZ2jakEX2FGad1NJUJmUsjalpOywSV2TEbUA1T1kFi+lyilYVhbCd1g1XZUKPisbbhkIs8mSxfWOxCIeeFsNCVnHpuzKZjOszJ2b1j3VrnJnvtFu/KjhRQ6TPx3Gc2G6WtOYqO2tEldeo/Oyy/ThezdJQBGuN3FcJA6hna5W7pqMSfFjQQb7j4jkADhXb8VYZmM9vTnciXS3ypadIha38zLkb6xVoP/kuHSeVI+vNKz/aeL22ScdJaaF0VT2wrtw6xA3cKHIyPhmY31VoFIkBcAtj9B4qTWaeVCoVbGxsoF6vo1aruQwB3TEvim5WZWleOHDDFFtbW9jd3cXu7i4qlQo2NzdRLBZX9oygZeV5ldpXfrdCbpGKnUCq1WoJJKlMq+EFACsplJzN5ntqtVriOC+7Jwu/s22qsG282CoAFq5C1f5oUdRIeml9fCczduyzttgMHhUIdX81Z1b5SenFMArr1bGg0KqnQd7RiS1th22Xvpfv2Nvbc2PChT0c21Kp5OijG25pfVoU6bLd1mjaZ3Q+wd5v72Of2H4FJ74YscbP+Rs3viKwIJjSNrJNpIuu0mQ/rTHSop6evof/Kx+owVFwAyxBH2Xc0oTfbQaX/mb1nPUSXhcmAW4J4mbRgWTskh3Tpa0WFenztLJ6CCcAlzIYRcsl9dxbRBfJ6CG7mh5omTqOY3Q6HfT7fdTr9YTA6eBQMZAJGH9TBWWRjc1UUDeW/YjjGBcXF+4ei16B1RVcrCuVSqFaraLdbrvl0jpBogsCWBRNhGHo0LANr/gEhgjF7qXscyfVc6LHoAg1n8+jUCgklmOrS2ldfEVtzJtWo6RoWZUX6aQKiAqewmjDIHwfx4BZA9YjpDJTz0eNHdv06aefJupRepGPLEK2bvs6w678tLm5ifF47Paw0ec0nq1gQmmu9Mzn8y50ZGlJ/rDeidLuVaFFa5DIsxwbnezl52QycXMW+l7lVRbS2V7XZ1mYEcTIAHnEV7eN0QOrHrCOpY7Zq8qtUtxAcmmzMjaLEskybhwnt4nkfTzxfTqdotfruSR9npZDy0lkrUn+JC5DE2RMAIl9lBUVK8pQN9wiRd6re0bYCRDeZ1GA0otMvrGxgXa7nXD7rUVfLBYu7LO1tYXxeIx+v+/ope/1uZDKYNbdtvewXVRg+juLr69sp/aV7r/dZ4XPb21tIZ/P4/j42Ambbl+ripZjqvFNGzLg/4r6+Az/L5VKzrtjsahKr6syUkSqfMxPTuqu8y7YF1/miaJQnhavdSuteeAG+0mwocpZw2RahzV+bG8Yrqb0qkwqMvYpZdJkNpslNviyY8O2qbfh82T1N1WeLBbZ837Kr7bPhhMVNKi8Ux+R17jOQ9/h4xFfP3zlVoVKFBHo/xYx0A3RJH4KIAlGAlN4mQlB9NLr9XB5eYnT01N0u123jH2xWCTQFWOhvM53cUJyPB5jPB7j6OjILdThCiidVNQsDUWqqvgBuF0JgyBInE9oXUsaFlWivV7P3asIXeOPZKJUKuVOfmF7rBJj8XkAbL/2Se9TAVWBs0aXY8Xx5NYFDD3YkATrVrQCLDdxarfb2NraWkF4mimi6JVGnW3woR1rpPS3g4ODBPomveM4RqFQcOcequAz3Kf0YR81JEFUx/baXG2bq6ztUr5h6p1FnOwb0+bYP9JGF/aoR8d68vk8Dg8PVzwW8pPdoVC9Dd5P2igwY566zglZo2/5jHVYI6rvUyVrwxu+vXus4VLDqu9UeeAnaagTsaSnGgDdAlb5W73YdeW1ijsIgv9bEATnQRD8WK5tBkHwd4MgeHz9Wb++HgRB8B8HQfB5EAQ/CoLgD76ufpZ1DV2HxLh1onZYBwO42WBmOp1iOBy6cIumknW7XfR6PfR6PZdrCsBllLAeTV1Lp9Mol8sIggBXV1f48ssvcXJy4sIORHuqlMnEuv+Kurfa/3VuLbAqePqcZtuou6oK1LqfnOTh81ZwrSAorYMgcPtBh2HoYvjWRVeUapW5NUg83kmVoRoKrU+R83Q6xWg0cgun7ByD5Qu+W3O3NQynfGeVC9vx7NmzRBuJVum+0xBpCE376+NdVYSkt+61USwWsbu760VkbBc9KKJWpYPynB7CoO9WGiktfTzpM0C8bo28/q4yYelvU+a06DyUVcD8zU7CKt11fG16pBof/rEvNJbFYtEdjKz1cqx4rw2bKELXcdcDmH0e7rryVRD3/x3AnzbX/gqAvx/H8SMAf//6fwD4MwAeXf99F8Bf/wr1A7gJGyg61N/UraIipWLWg071WR0sKnAKk56GA8CtRIvj2E2G6oQO05R0dpwobzAYoFwuI51O48WLF3jx4oVz4XRQLRKkAdHfdJGRL2XOGjifd0I6pVIplzlTr9fdEnPuOc7PdW5goVBIoFVFzGRARSv27ECfoFO5q7JQl9saC59g+YyZNYysWz+LxWJipSzRkXV5+cnvNGh8ThWZKo8guIlJz2Yz9Ho9945cLufSz1QwiYhtaiPrU2XHsBp3DLRG1H5XmbB1x3EyrGgni7VfvhDfZDLB0dFR4p009uvynW2/SGfSlLRpNpuJtqqHocqe71oXLrK09r1b+0SZtLRLpVJuQnQ4HLpMJNLMZkxpnRYoadH9fuxvFoSu9O+Vvy5f/g8BNM3lPwfgl66//xKAf12u/814Wb4HoBYEwf7r3sGGWqWkrqK91yIgElKVNQfVbt6jrrcqGRtzU1SQzWZRKpVcnne/30ez2USv13Ppas1mE/1+fwUVW4Wkv/Pkb6ugFJFaplchpWKwyIf0ODg4cKEH7hVON3w4HGIwGLh7ldmjaHkeI59ju0lTGlqdTFXlxvbZMM1gMHDHaNliwwHsh7qlvmwUVRoacmAh/wyHQ2xubq6gXrZP32eNj44f7yHtld+s4uWnntytWSnZbDaRqeI7QUUV9Hg8dnMrVj6sDCk/6HWVExYbLtCUN1W+akiUvpZWOg7kG/7GPUX4Z8Ob9tP3TgArB4PruPgUtvXy1INmUc+A7SJAsWEhNfxKYzUqOoYWHFja2+dfpbz/WScnd+M4Prn+fgpg9/r7HQAv5L6j62snMCUIgu9iicr1GgC/S8bii1kpMuJz1mKyED1RYekAKpPFcezuAeAOW2AoRCd1Op0OCoUCarWaSwtkYZ10o7Uf8bVba9tqPQeth99t30kPm2f68uXLRAxTwzga89e8Vi26fa3SVl3uVCqFt99+G48fP060lfTh+3mNed5sP/9msxnK5XLCmFjUrLTRXHZ1Q9lO3YGR5fT0dAWdWsBQLpcTm0hx3kF3AmTb7aIYbYcqHF5nnzjZao3MOuWiIIL91wlAFhuiswt2gGS4zqLCKIqwsbGR2JHQekEqX6/zPmxMn7nzKqvKtzrWVsHpNYbHFDQwrKRe1zpQobKUyWQSh18QBPhy4S2/2BCIXlcQwvRBPeVdPUUbR39dnPt3PDkZL2t/dSTd/9wvxnH8h+I4/kMWGSjqscwAYAVhhGG4sjMgf9d6SRwSxBJLlZeiKCrCXq/nmI4xb8ZlOUlZrVYTG+rzfTpTr0Kpk5a+MBGFR5EwLT1zXYWmjhY0QHYFJ/PZtU7fBGWtVnOMx3Y9evTIhTrUEMVxjKurK+TzeZRKJXe/ombSUz0DPmsnshg3Pzg4SJypSEVkDbV9h66AVPSlvKQ00/qpoLlSEYDLPlK+VG/HjimFlffrd/6vSJ39VkFW+vF3HWsLNngPADfRq3KifK+f+gzHhjnor1MgdoLY3qcelPZflaPSgLLGEJ4CBu2fhh00phyLN6l0YgqsfZa/c06FNKX88E/TPHWMdRyUr8jTylfW67Cev835tp6lLf+sivssuA6BXH+eX19/CeCu3Hd4fe21hQOoSlXdBX6SkXTyII7jxJ4V6lry06Kgdf+rcmQh+uLOeuqiss08Kefi4iKxV4Z1oXTCQ62/RTBUCvyun5zwUgOihcoYSLqx/NQzNrXfulRc9yahgej1em7FqXoVURTh8vJyhW6bm5srxkHHmjQJw9AtcuFBFYvFwu1fzfFJp9Oo1WorhgxYMjoPvtAJQhUI5QMiQuvVUHEBN3tH93o9DIfDFUVseZcCyQOs9R5fKMeGQ+wkoN6rvKIoUsMz6rpr3rwif6t42HbdJ3s0GiWUvipviyx1DFkfv6unx3YTEVu+1X7pQjtfaqL99KFp2z/diljBEJ9TY6+Lp7R9OjY+r1jfx7r1GEH1MnSBkR0f1QPryj+r4v41AL9w/f0XAPyqXP+3gmX5wwA68U1IZW3xMRKVHGOAPtTNwVXmtWhC9x/QOlQYNAyg1pu/KyNZpMT7eC4lFaAWzdRgfyzj6L28xnuBG8FWFGYtNulE2rAO6wozHZArwNQTYV1ELkTAW1tbuLy8dDnButES72PdwM1ZiLrnhI6TMq0icQorx+Du3buJiSmLqGz4iHTSNlGR6r2KitRDU1prOpeOg4/P1DjwSDvlb5vBoHWocmRdShfNpLLFzo+waNxV0aJ9tyJ6KgyfQlWPRpWojqu2W40OlaumyXJMNeSmnz70uW7c9U+9AAIR0k71gC/Ob8eRfWAYzyZPWG9J+0B5tEZH9RU9I20D2+ebcNXy2hh3EAT/BYA/AWArCIIjAP87AH8VwK8EQfCXADwD8Oevb//bAP4sgM8BDAH8xdfVr0TwMYcyk1pX/sZBVmVMBafW2rrJWgeQ3F+A16yg6Pu0nURpjA9qHq0qWYs0tS3KqOo62s12fMjHMq/GJH1ZEyps1rqHYYgPPvgAH3/8sUPK4/EYw+FwJdSk6MoqFs4JsA7NNFDD6EPDFJDpdIqnT58m6KKToTpmi8UCw+EwgZzUqKrQs73kK5/H4lOG3JdGlb3SwfKUKhKd6LIeVhRFzogOBoPEGAE3rjtpo2mtpB3pYRWRtscqSNtWlS0WhuTi+GbilP1QvgKwgqItSrZyzf5oUa/EKkqVcxtWss9qiIZ0VmVojbWiXpVF3qvv9Xm5Noyj/bL6h7/5TrtRYPqqEvgY9Pe6hGEYMy5smSGOl4cCFItFl8FBRQkkmdGiN9/gqLK1SsQSzaIRFjJcFEVuDw4y/uHhIR4+fOiuWyZg0X42Gg10u93E6jC2jSlg9t12m0wrnGrwNDtA065UCWtohWjZKjAaEq2Dh0ew/aSFombfmFqBCoJgZbtbPT9RQwZqCCqVCjqdjhsnXQqtgsw6qfh0zBQl2VPDfTzEZ9To2E33+W6fEle+0rbpmGSzWbegJAgClMtlN6mrf/peNZJKZx1bHQMFAspfvMbJRcqGRdWqkDR0obS391jjq2E9VW70NJS3+btVwGoQ1dPiu/V+XU1ri+2Ljj/pzHbpmbiWdqrY2R6tg3Ji11rwd77zs88+w2g08qaW3JqVk8pEav2IoHieIAlDweO9dgJBQxo+a6coQBGRjX9ZxlFrXq/Xcf/+fezv77vsgouLCwyHQ/R6PRwfH7vsE+0nkIzD6QGyyvhAcpN8MqBO0ClS1T8aQruQRhmdtGTdZJrhcJgIDzFswOwKbp2az+cxn89RKpUcGuN2AdZ7UoFXOqgLqqe62LglaQYkN9HialF1P1VhK3JjH3m/jjVpo0pK+UaNvU8obV2KqPlnDZiNI6vS1L1mwjBEt9tdSbvT+2lEVenyXaSptk95xSoffqrStn1jm30hGRtuUb7TYu+xmU3KQ2qMLEpn2I88QoOmMs+wqS/cxKJ0tWFIGmMbdrQeqPIH20O6Ub7UuCq/raOLr9wKxR0EN7FY6zL4YmXMjNABtCjACpDWYZWyVSaWWRX9MnaVTi+PHOKGTVywU61WcXV1hRcvXrhDZi1it4jaGh7rJrE9ZEZVpMpkqlj4Di7j53NWuNS9VnSmCEYRHUsqlcLW1hb++B//406phOFyb2WdONaxBG52VguCm1WXOl/B9yo/KE8oileDawWMW7Eq/dgHjevTAPE3G25QPlBX2kdv9fQUoQOrJ6SzLzZ+zHYozZRn2eZKpeJop31SVGuLVdSsi8bOjr3d68WmqlJufUbNB5z4pztRUp42NjZWQIW2W8NabNvGxoYDDJpix//1cG+rDNUb5jiQX2q1mlvzoLKpYMmG/tYV1q3vonxQvqhPFES9rtwKxQ3cWCNrtWwskYiPp4FY1EGG4W6AfM6iBf2zE0JAEnnoxBTvm8/nmE6n+NGPfoROp4NUarl/OAAcHR25STzmUWusmQLD+u2yaP3NTnqwn1warkWZXRWhMimVpg09aF/VgOokEutn+GaxWLhd7Ehz3SbAuqtBELjnguDmxHrrEfE3Ow4+xEgh1rYrurZhAnpwOoFswxf6qQrZvsMXitI269yMIm4dS6ugFIGp18H9O8IwxHvvvYednZ3EONJb0XfqXIAFJTaMZI0jAHe4CK9pH8NwmTJK+mkd+r/Pm/EhfM1A0aL0VxCmefY6Xkpfjj0npjnubIt631G0nJ+qVCorKbSs356OpADQ8qe2SWmihYbP99zrUPetUdxqyZUQltG10N0FVq3yOqZUAqvrqQytbVJkwGtU2rrcHlguX764uMB4PEar1cLZ2Rk2NjYSilOzPHx9U1RsDQnvtfFXpZ8qUWuQFD2zHtZJIdXtA6gUNS+d7yL9ZrOZ+32xWO48qPmqpKn2i3RX5cK+A8tTwHmf3quIHIBbgcf3KcKyysNm5GhRhGsPqPWNEz0+9lkzAyiMpI/G7DUDRBWYjjeRnFWURLZxHOP8/BxnZ2cryMynHDgOmiHDPel9cXilT7PZ9CpjjsH9+/fd2Cpi9ylm6z2pQudOiPl8fgVZk3/V2NDrttlaOn4WTavnACTPh+V99JrJR+RP8o3dZtj2mSBMaWLHhPVaI8h+qrH28aqj66t+/L0q2Ww2rtfrbnGLr8PAzVmNqpy1/Ywzr4un6eDr74qu1HXh8WV0u/v9fmJ/gTi+mQC01jUMQzQaDXzjG99wTKVhFipJDcWwnXZgbdHBZ38onJZxbYiG74jj5Q52RBdEExp6oFIkSlVh4viUSiV0u11ks9nEjnbqmezu7uL8/HwFcXLvdNsfInqrfPVZGiedmVeDw3Hgp8bRFdlpqiHpGEXLzZx032udOFXDpO/md0tvbROVTjabTRxwrUZUDZxFoeQ5NVA+Q24LjYbNiGD9NjwTBEFCiemYqjLOZrPY3t7G8+fP3XWdmLbxXF/4hO3Qd7Aeu8BMDZsqYqW3pSNpowrf6hjdP12BzqtQs4Y3dIyt4dJ2qpFWes9mM5dRxHNMnzx5gul06kWtt2I/7jheZo7wL51O4/j4ODFry7get18lcmSuMxdwUKBVMPUEGJ9S16Ix1Ewmg2KxmLDOVGIcKDKCWuA4jt0qwmaziUql4hDfyckJdnZ23Dl7VhhID/2uHoONz7PQHeTCmUqlglwu5xbGWCGxiN5O2thsBWCpaHl6ThwvT0HnTnQ8cor1huEy/7vZbOLs7GxFWVoB4W8219uuqmQJgsBlh+iYBkGQCJGQR6x3xqLKXT+54Ib3q5JUT0LrUQSn7dH7yCPaZ95jFUoY3qSeqRH4qkhbx1KVpeUp36ctPv6koX7x4sWKkcpms4lzHpU29I6VppZ3fIqQ10hDBXk+pe0LlVkPXa8rUGB79bv1ACz4s3rF5tgTQPA7y3Q6Rb/fx2g0cgBIw0C+cmsUN5VjtVpFpVLBfL7cNF8POeXxZTx4AIDb9U9jTUEQYGtryy2/7na77llNsdLJLO57oDPPVIQqTJlMBnfu3MHLl8sFoVTiRGREGdPpFKenp2i329jb20MQBO6UkTt37gBICoNND1IUpgpWQz2qyHVnviAIEqfaWFTDYtPt+F2FWN+xWCzP1vy5n/s5fPbZZ84DId3q9brbC4SZQMrQZFyiOO6yZtEmP4vFIvr9/kpfWafGK/V5nS+g8uP7bTqYxqd9iNeXj2u9JhpLDcVwlWezudyfLZfLrbjaANxRbDrZZXmZ/VEAwfbznT4hV6Wm46657lQU7LsqM/VOqCiVTxXpW0XLOSi7j4vSUfex4XcdA6vQOR5xHK+cqERjqGOlh1aTHkEQuLHQMJZP6fqKtsMCASur/N0XL2dh9hb7zhWevpBdon2v/PX3qATBMsOAA355eemIQ3dN453rXFMKZBAEbpUfCT2ZTBKrmTTuHARBApWRWabTqdsKlsiABkXdWMu4ZFYK2tnZGaJouU3q1taWQ1dWMFmUaW02wrrv7HehUHCHOVB4FNVorNgqa3XnOHGo7SEduTEWURXRJk+nUUVNgeTzOsNP48m9z+32vFydaV1R7YMWvU+FHLgRbOtZWKRplYHWTYUaRTcbHKnh0DbV63V3kILyripTAgbtk46HenXqSShP6HedR+B48hp5l+1RT0vb7cto0mJdfmAVbSowYht0xeurvD2LZjXEpPcASUSrfWU/mTFDb5D1qdJmfVa5qneVy+USRlP7a0MuOnbWYPJ+8iL/KANRFCUWuq3zfoBboriBZQrOYDBAr9dzKFoJqspOmRNIuqW6j4cKPq9raEMtrrrAluB6YjyRszUgNrcauDEk/X7fHbwQRZHb/Y4bOVGo1f1b59L6YuKquFlUOPmcVd58XhlFkZfWSQZtt9v4h//wHyZQA1GbPWpL3Vp9vwpnGIaJ3QK1T1aRKQ34XWPUSh96HZzU0z7wu6JqTauzfVADqrRTRaSFi2d08yIKPveuUA9J+02eVx609+rudda4W6VCXrCTZTRCOndBHrRIlAYvjpfzIrr4zXqCKpsKYNSrUg+K7bUGR3lT+zwej5FKpZxR1HkIi4B9YTY7/sqbOrb2fpU5G8pR2nPeSIGd9tUu1FK9wfDIq7wolluhuKMowtHRkQtlqNLJZrPY2NjAcDhMCLgythK0VColGF03drErnahYlFHZHkVs+h6r1NcNOF21yWSCYrHoNq6Zz+d49uwZ7t+/j42NjQQdrNLwoWpfDJWf6qIqnXyhBB9C0j99HkguMOl2u8jn89je3nYxbhaiIFV0yvzaVp+Q+hCeohcbVrErSOkFMJyhCl0FQZE/DyDmdRoiPqfI26fsbKGnpkXpTeSmvKmfapxJFwUKyguqiCyfvmqxifZR61H+o/uufzqhyjYfHh66QxW0HyzkNxvOsPHtcrkMYBkSpQFRHlGZLJVKiZCmyobPq1T+UXn1tdmOrQUQHA/tFw2/bv2rMmTDdARwPBQDgPNedTfKdeVWpAPG8fLUdBuQJ6NS6am76nNxSSBrGcnEVikBSUbVEIpV0ipUrJsIXhPqWSeNENvKSc7pdOpO0tF2LxYLZ5gUIdp4rVWqto1EYBR0ehp8ngyhCtm6ZSpM7DO/M/amx7T58l7VHSQ9FeXY9ymNtagH4BMu9kHpqOOptGM9yj8AnDLScefSft5rERi/WwWgSCmTybhFIuw3BVvHi8/R2NPo8B7th6JfbbPep/M0OjlnY6u27T7a2zHRBTssFiywP2yv9SAsP/OP2+mWSqXEYRvkV/Uazs/P0el0EuEYvVfboqtIidRVX3CyXdvGNvu8KvKDrz+8pmmNKodBsAxn0mtIpVLOM6N32O/33TqQdeVWIG4ytY1nkbjcTtUqNRZlkl6vt0Jk/s4BpIFQZubga9jAh6b4G5mOy7+JlukSU2EtFsu9PzY2NhwiLJfLLqtE26h9ogK2gq1tUCbRe3UVndLIhyBUwerRWj43mIXj8/Lly7UCqzTKZDJuPxNF/ByDarXqxiSXyzn317ZBETX5QVM32T8aUhU+nWyySlgzCHjdIjY12D5wwc9isejCcHEco1KpuDkB3mOfJw35XkX0NCLKr5YvFahEUZQQep/nowqT31+1hwfH1fIBFdHl5eXKvarw9FlFvsovVkEqT2i91hO2YUwFInyvHuTByT+VGZvcoGEOvs96C9pmLTrG2gb+xolI0o96geEVBQk2FKPl1ihurjrUlXU6yKoglCg+hecLIwA3aYc8kovXdNBUyK27QwRsrWoURS5bRd1ctpnMdefOHWSzWXfYAhlMGVER5rqwiW7+YxUB6QPcCLI9bZoTj/xdhZhMqvsXs/80bhb9+TwZizSYrkivg22J4xi1Ws2hXk4kWaVKutKL4R9XDFpkylRBtpOxZTXQGte1fMJiwxG+mCjfzfZohsjx8bEzLjpWNEIbGxs4Oztz9dkNimybbKjIh96phLXtyiPkfd0TWkNO5D1ts89DorGncVEPU+O4amTZVsoIaaegaTAYuBCcyjn1guZiU7naDCA7fsyk8eWVq+FUVK9t5LM65ppmyaL6hO2tVqtu/x+ryKkHMpkMer3eyiZn68qtWICTy+XiP/gH/yCAJYq7urpySrZarbocR6sgLGF5zSJTVU4WqfI3GxrxISMNb4ThzUkzVB4+AWcsrlQq4Vvf+pY7gNciGBVGMpnWx0ImVAHnjDTrVDdYFbTWwWKVFBU35xqULtZDUKHSxT++fnHHQTKmzdjQou2zXpHSiQub6Koze0XfT8NFOuRyOfT7/ZXQAX8PwzBxjJUWnQjVGDWFlJlJtg/6jJZ1Ocas06JQWyf5nv3L5/MrCk8VM8dMx69arSYONValqHn0mlm1vb2N09NTr0eo424zXnTBFJ9RRacIme3UOujVWrpY1G49KlXW1hvQ91C2SC/W7+MFC1IAeMNTNiGCzzJ8xlz38XiMq6srd2ZtKpVCp9PBfD73BrpvRYybcdLLy0sXtwrDEOVyGQcHB25DJbrc/OTeAkBygkKZ0yptIEloElSVncYuSUTrzsZx7BRRNpt1J4iz7el0GgcHB3jvvfewsbHh0vPYLl+sVdvGwbXCrmiAaFa3KdVYmgq8hkmUPhpfVqYmGtN6+LxtL2nj6w/v10VTumOhvtOiQvVafAJeKBQSefY+HgBuvDh1U31emiovoiCOUyqVwubmZoImXPwVhstsAh7rxjaQHzQMSJoQQeqOiOpp+MJc1vvRe6lglccVVCg/09BoWEzHRXnGF760E6/aJ6W77bOme6pcsn71oJVualBt3+072Xd9v1XaVg8ovZQHWMe68JHW4TPM/N8HVoDlds6sX+VOt8VYV26F4gbgjvziieRRFLkVREQT7BTzu7e2trC7u7uCYK1F5XfGolX5AqvxNWVyXlfURkEGbpaqMu5qlWW/38dsNsPdu3ddLMsiKI2/WrdaPQC9h4aMbaHgav0WTVulqwpOw0+cDLaIiX3XYlG4KkC9pjT10Z7ttXFc0kORNN+pGS1sl8Yi1ZARRelqPu0zkDx0gsqN1xaLBZrNpluha+nLFFZtD0NavF9DU+r6Wy/BGjTrvVhgwr4PBoMEfTTtVUOD6oXYnGZd3KbhAuBmsYiuxrW8pAaB121YiTyrfde28TtRL++n/Oo+PHwn79NxtMqUXrO+l99rtZrbf8bn7SiPqbFIpVJOtvk+GiGVOY639o3rO0hrG656VbkVijuKIrRaLQwGAycA7EAmk8He3p5zxzkgmjfMQaClsgSzCMcKgA/JqHIh8iqVSomj1FSRq8CwrmaziadPn7pjzX7yk58kzlHkfVoWi4Vb0ahMTeOkg0pjQYSiykIzXTRDYV2/+a6tra2EolA6akyS18ikNh6v8X+LkjjmKljaJl6v1WrOYNv2q5Br+3Q8bN1UABre0WKVG3BjOPgcAYAacPZX91uO4+WkOtuuykCRpY8HfApNx0KVFBWFVXIWYSuS03kJu1UBMxv0/Rwr8p2iUV/xoWCdkKYhpLLSsfcZMcoEFZ7ygtLRByws+FGe4DNBEGBnZ8eFHG1ftC4tfJYbdlm6+FaN2kIZzeVy7sxUrsZ9VbkVihtYdmwymbiVQxww5uRyUo87wukWosViEaVSCZubmyv7Ayuy04wPYHUJuCIY6/IVi0UX85vNZoml+CpQVJh8lvEtLn2+vLx0cSy63TQ+ynR0tckMGqPUZf8UBP5xwNUtVCXlC2Xoe1ut1kqf+CzfwT1lLIq39LBxZH7nboIahrBn79FbmUwmCSRrkbtVYvouywNaoijC9vb2SjjIhqG0jzq2qjhU0av3pwZEvSvyCZ9Xg8T6rZK2qJuG0u5Gp0DFZmqpAuZ77XPK++toR/ramLKlkbbXepCqqLUOpacCI3qX2iY1ECrnPq9Q5UnfSyPy+eefO0OrfGnlRftIo/7pp5+upKHyPp8hUcOla0hqtRrq9ToKhQKKxeIrUfdrFXcQBHeDIPjvgiD4aRAEPwmC4N+9vr4ZBMHfDYLg8fVn/fp6EATBfxwEwedBEPwoCII/+Lp3XD+3wkTT6RQnJyeI4xiHh4dO0MrlcgJBlEolbG9vI5/Po1qtJpCUEt4KnFp6Mgu3Ma3X69ja2kKxWHQZCRQGLdY11QwHjSEyZnznzh133S6QoEJj4cnQqhgUxQLr96rg/5qiyOuq/IIgSBykq20ibeyG9Gps9P3K7PYvDEPU6/UEkmPb+F4Ni/CaGiJdBGSRvCpJO7baBvY9nU7j8vIykf2gikLfoTyi/VflYg290l/r5e98xl7TP7bLjofyHFGy8iPbpehUwz40xgqQSDu7NS5lgiEoy29UqpoLbQvlmTLg2wfEhq2sIVWFbQ2L0srWrSiY58G+SiES5OhiOJ9nEcex896t8eWnz/Dp+KoBJ5Db2NjA9va22xpjXfkqiHsO4H8Vx/EHAP4wgH87CIIPAPwVAH8/juNHAP7+9f8A8GcAPLr++y6Av/66F6gisZM54/EYzWYTw+EQp6enuLi4QKfTcUJ4dXXlwix2lh5YVXSWMdRycsByuRy2trZQLpeRzWbdxCIA57pblwu42aGPjEXjks1mnSGo1WrY3Nx0/WUbomiZf6vXlMEUIfgUiCIs6y6TJpaRKHxEtIr8FbHadDndOtciGOAGBTKOyueYn60772lRr4j/W7SpgqLv5D1WEetvrEPTBLW/Fi3qYiUrmPpe/mn7qLyVltpPRWXaF63LKm9LC/7O9E57iIXWx+/sY6FQWOmTjVvznfqptOCzXGxmiw1V2RCO0kOL/q8yoMqd/VfFp++ztEun0/jmN7+Z0A22nXyWMmUPabbABIDb0Y9F88z1/Zyotv331c17fTLi2rnOSq59IAh+FcBfu/77E3EcnwRBsA/gH8Rx/F4QBP/p9ff/4vr+T3nfujrDMIwLhYJbhksGtcxN5aOTc9zDG0gKmioAteRWcXOQaakZDikUCg71R9Fyg6g7d+6g1Wo5xaPvjuNlPjL3cS6VSigUCm6zIW6zyslXKj9uYGNRK/NowzB0Oc4s/F0nTH2xZO2r7T9zfVUQ7XPKXBb1a6qgxrP5uyIlq0DJ2KzD7gqnfVL0a5GWoi1FjbYtvF4sFl1ITtGUolRNtaQ3R6Cg6F3Txfi/GjttO8ebxsymG1raKq1Y2B6llZEhL40Ye9d6dIzUGNvQAMdIlSfrtmjUhkFsuzjuOkHHsY7j2O3Nrnxo61D58PFAOp3Gzs4OXrx4sYJ4gyBwW0/oLo2FQgEfffQRvve97yXGzY4D22qX2bNfyoP6LOvUBU56nZ6Krg5n2uTjx48xHA692vu3tQAnCIK3AHwTwH8PYFeU8SmA3evvdwC8kMeOrq+tVdzXdSfcS2VcixQZ++YueGRqCodlClVcmnWggmgZjwakUCggl8uhXq+j2WxiNpvhwYMHKJfL+OKLL9Dtdt0ET7/fRxAs91x4//33Ua/X3Sx4Pp93m0vRylIB6l4ZKny0/BQ+vc42q/LU1YM+ZKSfVrGRhqoA+TsV7LpTv4MgcJuEkQmtoQBulCRPPNFx0fp9XoHWpwKshcZX26j10KPxjbvyjQouN7dXpWONDMfI9lP5l8+RR0lrVaA6vnxOvR0NVbHouFuFofTztduGjkhbyojyqfIL79W2an+AZay/VCq5HSOBGzRq+xEEgeMJH99aBc1+ad94z8XFRYIntM/cdI50I8D7+OOP3TXlST6vfde5iY2NDbcmQAv7aNts+wTA6TH2h3N6+l5f+cqKOwiCMoD/F4D/RRzHXWOZ4yAIflvQPQiC72IZSnEMYLd31N+sQClKUhRAS6joWyfJVEBUGcRx7GZ2s9ksLi8vEYbLxQb1eh0AcHJy4pTzvXv38ODBA5ycnOD4+BhxvIx59Xo9vPPOO9jd3U2gObv3gLZBt6HU/cK1nypkFCyd8AJWQ0QstVrNrdyyBsoiF30PEQHREBWEIhzed3l5ucL0VDxKZyoaKxAUZpsOyOd07K0wEKWwb3o2oHoVpJmG4qwrbuvnSTUWEbM9qqx0DPR9+psiVGuEVUlrn62Ctx6R7tdBBaoGT0NDFpGrV8D/F4uFO4XFx0+6EEbHl/dQcfV6vcQ42bCLyrVuVaFgS/tqwYAqf9bJ5eu6kIb3WjBCQNTpdAAg4UXZ9ygdSFsuXFJlbjN8lMZRFK0s0orjGP1+H+Px2KFvemSv2iTsK2WVBEGQwVJp/+dxHP/X15fPgmWIBNef59fXXwK4K48fXl9LlDiOfzGO4z8Ux/Efco1ZI5wcSEVINoyig5jL5VzcyRJfFZUOZi6Xw/b2Nj744APk83nUajU0Gg1Uq1U8e/YMT58+dYzcarXw9OlTzOdzNxNcqVTc5lF60rn2yYeIqPAZ36VS5j02M0Npw71FuDkPkJzg1L4C6/PVfQLBMp1OMRwOV1ZFEiVZ1KsxXTUEinTZJo3t2Ykr1qsLirSdvjREdUH1fVq3KkC+R0MEcRxjZ2cHqdTy8Oe7d++6yW69j/3i3IiN3+p3H+pScMG6rUIiQme7NCQGwKW3sj4qKl1EpB6WbZ+VIw23kCc1G4njzu0QeK8P/UZRlBgbG5pThafGTsGOKlof/X3omP/rARfWS9EUYuVPXrPJDdYL0Hi08mYQ3CzKUtqS/mEYurUp4/EYvV6PqyPdGgPOV7wKbQNfLaskAPA3AHwcx/H/SX76NQC/cP39FwD8qlz/t4Jl+cMAOvEr4tskjk+ZWCtpQxx6nz6nJ6DrJB+VuWXoKIrcjmS9Xs/tn033fzgcot1uYzqdOmEbjUb4+OOPcXl5iXw+71ZO7u/vO4Ru0a1lICB5rBRn/vkskERV2hfGbK2Lrlua8r2KfFR4VCCsG0paWmHX+QCuhtQMk4ODg4TSTKVuDtZVRQTAoXl+1/Q8KnYel8aicX01CFQiNma9TkFphgrHgDTgQR7D4RBPnjxJjIlOBrP+dHp52g3fb/lWx1GVHGlBoOHzNFjYR9avueQa3lBesh4PeSWXyyVAhcoWx5e8ptsIAFgxmDq/pDS0m3opeNAxIa2oLH2eBttuPVFLJ0s79VxsyE3vUUCo95B/eS2OY4eKrWdF2uj4sq2k0WKxQL/fR6fTcTsA8vwBIvXZbOYWHb6qvHZyMgiCPwbg1wH8FgBS5n+LZZz7VwDcA/AMwJ+P47h5rej/GoA/DWAI4C/Gcfz9V70jlUrFJIgOgrqOaoGtVfYhWQAu35gbGzHor0qbjJrP5xMuTrlcxt27d9FqtTCdTtHtdt0glEol5HI5DIdDp1S4JeuHH37olBfba9tqFYuNkbHvuVzOIWlet7nfNmRirTzpZV16ZWwVSqXt9dgklABPq1Gm13u494W6waRxLpdDu91O0EERmypsuooPHz7EZDLB0dFRok26N4wqJ2YBKaqynoTShW3XSTh9VullUZB6UjRKUbQ8aLhQKLhJTV1Q5lMu/G2xWKDRaCROEtJ5G9JaPQYqHBuSskCB7+WeMetOs9dPDWmocmN7NL6tPOmr1xptOyaUTe0bf7cGTPtoFaUFR+vGbT6fJ2RJ79H+WGBoQaL2S8NOaqBIE2bIEShyri6bzWI4HGI0GjleIeBat1fJrdhkKrzOKrEKDVgVDiDpNtrrZGIguXufLuXlM7T0RIRkHCLWer2Ozc1NFAoFnJycYLFYHs+1sbGBw8NDNJtNpFIpt0gkDEPs7e3hrbfeci60L06lB6my3WQey/iqZCxTsm+vSnEql8tuRap9nobBuoI6Bj466/sBuEwJ9oW/qUuvRiyOYzQaDcxmM7fl6WKxQC6Xc8iDikgzCIBlKIhIX5EvTx7hu3WCkn3Q3FyL3qyAAjcZRgoYqMTIq6rI2Fflv2w2687NpKFIpZKHWytdiVRZnyJajrWGOvR5i0b5PkWE+XzeyYKmD9LAFgoFB0Js/FvrYf1WKWroQNuhCnYdkLC0ZJ9UMWu9upLaNweh9FXDo7zN+lgXjzgMgsDRSduvbbDtJy1tnwlCoihCs9lEOp12GU79ft/xWafTcdklYRhyXup3nlXyu13UxQRWY8GqvBQtWaRN5qYy1fqsUWCKkC4zZ3ysUCigVCo55Xd8fIwoinB6eor5fI579+6hWCwiDJdLVoMgcJ8WXWmxg873KtMqwlJkBtwgb2V2GhxV4rTkavWZRqnZMHYMNPyi7dExsG1nuzRcYX+P45tUJ0XlwE1IazabufxZHxJ6++238dlnn61kEGWzWRe20Xiq5QsVMB8643usQVTjqopSFZqi21Qq5ZBtKpVKZNLYzAqL/Eul0srxV8pPqhBIT3opViGxDvIL+Zxt1AVjcRy7Vb3aR9s/FlWENqTAMeV99jlrJFk/x13vVY9D22HTHFWu1WBrGzVryeoXzfQiPcPwZg941mtpzOt28pm8xE/1ogkuut2u0xtqmH/HMe7fi0Iis3MWRavSojVUZQAkCcTfNc7GgVMmKJVKTvFygKPo5iQK7vxHA6DbUo5GI3z++ed4/vw5MpkMKpUK6vW6O0H69PTUZZKk02lUKhXXVnVTrVvKYmPRKlwAEkrNIiEWnbgirebz5VmcXGzE+mikfMKkyiUIgpXVaZPJxE3QkbHXIXRFIBQA1k0FVKlUVtBjHC8ncT/++GOHrHWsdQJVUbLOCWjcXw2l9tHHZyqkij59Hh/7ooZFvQhOKJKOKqQc38FgsOKmq5LQfitaZn912we2Sz0NFjtJZ9+l/MbfddKdfbVypjysJ8XbokbU8jL7YvepsTJhFSPvUyP9KsXK3zlGOoFN+vKkGtJHT+exsfMgCBzwsDJNZJ/L5Ry44OI+6h3btnXlViFudSmsK6sDRaWju6Ep4fjJevL5vLOoVMLz+fK09uFwmGBqKucwXE7+cbHNfD5HNptFoVBw6TvpdBonJyeYzWb45je/iUwmg+PjYxwfHwNYZmTcv38fABKHFwCreyrwf0VIKjhsnxosnzCwLl9RmujewVF0c3itMqRtIxm50Wig2Ww6ZepDt2yrXaihfVDlpEpoOBy6tC4iQ/6mRk/7qSEMvkP3WNGQD8ef/bV5xeVyGYVCweUEqxImzTTub8NhRGyqmBSZkx5UFKS1Kk2lGdulnpDlD/ZNjTf3SFc+0Ri5jrU1YupZUAnpyS1E6hYs+LwxRalqBPkOpZXWYxGz0kTv0TbxuvZFaap8rchaQ6mkXRgut5LVXHQgeXizTsqyvcqjNlVQJ9uJ5skX3LJaPaV15VbEuFOplItxc0CtoCvxuZRclQaLdenjeBlPpfvZ6/US8WUVClrXMAyxu7uLRqPhJnO4cfxwOESn03Epg+1227k6rKNYLOIP/IE/kMg2oQJiCIcIM5/Pr8QUfWPiU4SvEhxf3JvFxt/0HVqHjXVb4dBwhkV4th47eWZjpyqYKqzWTWeuuw858XkqRUWFNj+e7VAFwVKtVhGGIVqtVkKxq/Lmszo3Yd1u7Ru/q6Kwk6E+9MY+ajhFC2mlSp4KIpVKnmTkkxPtiyo8331Eo5qiqHXr+LPNFnwRPFlPWo0pC2mo9Of7tc/aVhuGIY01R3sdwPABnnUAydJd+VWBgvbT9o+ptlEUOY8xjmM3/3EdTrzdMW47kRCGoVv4YYV3sVgkNlX3ueTADTH7/T52d3dRrVbdxvJ2yTKwnKzTZdGz2QylUgm1Ws1NQA6HQ7cTYT6fR6fTcc9Mp1OXnVIoFFCpVJxrTMGme0xhtbEzlnUehDKKLrxRJV4sFhNbQ3Lyg0Xda4totCgKs8aEtE+n064vOuFkEaa+37rl2j/r0isCVAWm4QiNJ+7t7SEMQ5yenrp3kP6LxcKhUEXNGvYA4BZkUNHqBKkqcvVatM2qxFkHcLNwRT06ZhaQjuo5KL2sUmFb+JwdN46/D3lmMhnn0Vjlo/VTBjW8o+/WuoHkxKyOsf5ujZTKtp0M1pQ7Fr6DfKsLbbQtLL4tAhRIWD7lePomjm3xeScAEpPgFgTp2Gaz2cSRelzcZydufeXWKG5VUGEYupNtfFkPjOPp/hBkCnU3SaTJZILj42Mn1Da0EsexOzuPoZRut4t6ve4mlh4+fIjRaIRSqYR0Oo1qtYqzszMUi0Vsbm6i1+shn8+7nQu3trYAwBkYZplwt8Fms5nID9b2+gRJmZ/f1XNgPJDWW8u6dCW+wxowRbNESUyx29rackfLsVhBtEynCo3KWRGUekkUQhVeRWUa6lFDxrAIV+AxZqhIyhoZy3+2LeQrG0JQ5KwKGrjJyeYB1zZkokqCtNBQCesoFAqJFFTLs9oWKzs6ttpG/V3Rqk4iKh9GUeTkj4jR8qS2S1G/0pg01zHVbBdet5ONPoOl7dQJXVuCIEgcp6eGX5Wt8glpYUETi09WtB7SY523aw0f+55KLRftzedztFotb+jIllujuIGbVKJyuewOz2T6l25DSYHIZDJoNBqYTqcJRciihGIWBWNQ1rWfTCYol8u4d+8e2u22Ywzu0cvtZHlmIRnq7t272NnZQavVckqdbWbdijzq9Tp+5md+Br/+67/u8svZVhsyUESqwktBImPauCGFJAhuTrAGkKAbN8/iuyzS4zM0Bjzw1J7Abt+vTGmzCqwLrkZEhVQ3tFfasd+z2WxloQ6/c28R9TKYQ05Dp1sM2HxmVSj6TvaRqY86Njp+DKdZwWOdmiWkCy2oFINgOWleqVRcbNWGBPSdSmurQLUfqkjtfUDSQHKjNH3POg+QStgqcfVOVKHrffb9HEsbxtMwhBpRGkiVC83Y0ecIQHzomm223rC9V2VTf7Oehw+p27HQ63G8XNjDo/FoMGm4feVWxLjDMIx1dV02m0W5XMb29jaAm7BAq9VyS0QBoF6v4/DwEBcXFy5Vj6k7JEYcJ5eNq2tkGYkzvkzjYpiE+3Pv7u6i3W67/O1Op4N3330XjUbDIXadQNIYH4Wfce/BYIDRaJRAhJbReA1IIlmfK6XMUi6XAcChPj5PA0QX2ipMW4/GaRm20t9V8dv4t6JqzV5QA0Nh0rp8wmffRX7wuftar/UKJpNJAl3ZdD+bDqZjY5WMr23sl6ZqWoQGJD0gX+yTKaXqUfF+O546dja+r21jscoPuFn8YlGk0kY/15V1vyuvWWXu48F1ffbVy7G3/GHbo3Vo333ZJ+oZqaFV3UH9omsHtD/UOypDtqj3pqCEGS7XGVS3O8atgsMTZohCUqkUrq6u0O12HcE4afjixQt0Op0EWmFwX60ukFyYwaLfNS4cBAEmkwmurq4QhiEuLy/xW7/1WwkF/fDhQzfRooJNxaKuKlcccp8Cja+S8ajolCGB5Gb8Fg3yd90Zb93mPvrdomCmParBUMVGpe0TCu0Lf1OjZV1xKh1tB4vGB7WflsakF8dbN0RKp5cHVjx79iwRXmFb9ZOGRT053q/91b7x06JxvtvS1houPq8hEkWD9DB1rHRRjw096FwE/6eHauVADakqJPVQtD92HkQ/7VhbflYe0YlG9kVBk2bX8L2M/3IbB2to+XwY3uRaa1uVf5SfrLGzxkPRvvKfyiC9WYuuWT91mfbHp7ytPDLk+boDH26N4rYojkoZSCKUIAjcSRbT6RRXV1euDmZvBEHg3OMoutm8iYxjFcu6duiCDo2fU2i2t7ddW9YhVQ4i0bUPdahw2Z3FrALX+imEdrWdPkvmpmJgHTZVTJdlq/JZx3gWtfm8GO2XGjIKJN+rE2CKgNg3NSYcX9bFU4Isoj06OlpBz0pD8o+OubZflXYQBDg4OHDpo6q07KSYVUIqxApOrJJTwWXc1oYLNAymS/6VJmybnhxk26cokvTSYvmIRXcF9PGmGhMbhmI9voU6SifSLggCfPDBB2g2mzg6OlrJRFHDEEVRYh9/X9hGJyNV+Wo7WMirWnyel6WRyhyzZ8iDvNcaDRaGMEkzXcvgK7dGcSvCYWcVmQE3Atbv9xOHD3AAGLflwG1sbKBYLAJYMnK73XYxWRJJB9+6Q6yHbaAhiKIId+7cwdbWlvuNiIWCqcaGCsgyhCIVftrMDP1dMwisN2GNiqIT7Q8zXmiUVKlaQWIIRJWIj4Ff1xaL/DKZTCIFkuPNLQJUiSmj+4SNcUmLKm0/bPt1ubf2Qa9ruKXZbLrYNunLcdV20uCrkrVhFt7nAw86BhpztePJZ7XfpA9XaVpUrvTTcVJDaNG1XuffOsCjilyNngIJ/sY+2Hx0/fz0009X5NGOmfYNuNmEzG5Ja+VM+8r2WbCkBmzd+zSnXe9R75X9UdCo9NGxsHyyrtwKxb1uQCgEcRyjWCy6RTd0iRRJcECY4xuGy8yUvb29xF4anPiczWa4uLhAvV7HYrFwm78osYnat7a23H65URRhf38f9+/fd0LLtjKzwSdkKtiaW2rdIWUOYDmglUolcWiERbOvEhZVIGwDFxX5nqOysntj2L5Y47Ku7cr8bC8nd/kuKhk1pFof67LhBio1DTPxXl4rl8vo9/serlsWeku6QEqVRxAswzFcqKVCrgcDAzeGRpWq0pf3sG8WpSo6U77SvtlChcB37+zsuM2KSGNV/BxjG3Zgf1ThsA827ZLts8CC462pmpqrbkMHDAnQIGqbUqmUd5LXZ4SVF1Qe2A+ulVDUrQpUZUQncH0hH1+xYRUdPzvRSS/Nho7I/6xn3fF+LLdCcSuRfCiEaJOxYSvQ9l6W8/NzVKtVlMtlpFIpl4/daDRwdnaGhw8fYmtrC1988YULs9BSc6vOw8NDFItFNJtNbG5uYnt72y3Q8Lk9KrBWYfMaUade40DbLIcgCFy839ZvmVR/03ZRSPRwU1UYOglHWtsQiZ1EZKHCsAbIIgor4LatHHsaDaJWXwiG9fN/jSdaxa/L46MoSoRISAMaDhZ6IKSDTT1UIQyCm8OUff2z3o/Sxue18LoKPNupgq60Vc9Ad/5Tb48AyHp1LGyjLyPKGngNYbEujoOGJkkrNfRq+BeLRWLuRHPALTjgmKjHYnkHwMoaDdLJGj7lVx8i1/77+FWz3FTBW09Tj6qzBtHnjdj3riu3MqvEljiOEydyWILyOVWUQbDMTjk4OHDbsgbBcoXjo0eP3GHAXNLa6/UwHA5xdnaGOI6xv7+Pd955B2EYulRBLsbg6j3uOcD0NO7XYY8zUkFTJMLBU2SkaFGtvyIa1qXf+X8qlcLm5qZbrq0C4GsTiyIyPsf/Ga/jc1YRqVBpnA5Yxup4Uohtq3WdOYY+pKOKmUKgKMuGK7hdgSIqVbhar6/wHXalqF3IpH1RAVclbF106/7Tc9OTdhTRWoOhbUylUi5F1ccb+tyr+m29KUXH/G4VnP5uw2oqm/b92i9VfHxHKpXChx9+iB//+McJo2lROWmgz1q94KOJBRo0bNYosL6NjQ202+2ELOVyucQByTqm/F8XVVmQR6VOWvF39W5+67d+C/1+//ZmlVAhKvNY5cz9tNlJ3+ArMgjD0IU29EQLrmzkiRNhGGJnZwe7u7sIggDtdhulUsnFyoge+J7Ly0u8ePECX//61wHApaWxTqJbbbtNLWMbif58xlOf8xklRdvADXpbLBbuGDFe98UmVRhYJwCXr83imxDVMWBdRDkMObBOKm2LIlQ5WCXj8xroOlt3l642acq66PJrXVTGPuHnu7UdbCfRr91Zjp9UvlQyvvHie0g7S089cktXZKZSKZRKJfR6PdRqNberoo6r0lfRsNLVen+qVH1K1GeA+C470Uf6sQ++0JqGEHSCXEMoOl6fffaZ8y50RSX3CtJ61DhaevtQsUXfbBsVqXoSXBzDjDaGgezOmtYjYx2qA9g21mNTgZUXX1duheIuFAo4ODjAaDRyJ85Y9KIxOHWrgNU8U6KQRqPhzlssFovupPVms4nz83PEcYytrS28//77LtOh0WgkLDAHYDAY4PT0FKenp3j06JFrFw+gtULPwbIupbq9HHwNZVBYiXJVwBXxKaMCqyEO3sNndWGDFvaDfdbsEhvz86EG+y6LyMiI6iqqIbFCrqjKhgiITNVwkK6+CSJVQto2DR3QKCuCZKop66ZnRbdeeY1joqEla3isl6GKj31XT4I8ww2JuCcPdw20tNWMCpu/rlkcOq4ahwaWCDKTybhl1z5DayeLbbiN43n37l28fPkScXyzQEtlwxp/nTtgXXqws7Zds2U07GWBH9/FtmtIx77TyhL7xnJxcZEwjKzb5mhrGMvHfzbV1OdNWS9lXbkV27ouFgvU63VUq1W3OY5Fz1R0VpiA5MwsALcbYKPRwMHBAfb39/H1r38d7777rtucilbz+fPnuLi4wGQycYMym80wnU7dfaPRCF988QUeP37s2kUlwpCHbtFJJi8UConJMy2qxAEktpRMpVKJiQq+gwbJIm0qWE7ysKghswgbSMbdq9Wq6/tsNnNCYd1efa/Wo+3U/vE7r+sOc2F4MyGpykIFTBnYjjPrUxTFZxaLRQIBa9tUGdGIkI40mCpwABIT4tw9UOkZRVFislpRFt/pU4a6YpL3sV4CGa6wVEUL3MxNqHFU2lBOeJ/S0iqZyWSyslWCFio79XZYj2ZQAcDV1ZV7l/U+1UDa9mjfOI4EUHy3ptRasMTx86Xzab2WN60BVfoBwLe//W132IoabLZR9ZDKlEXTFpDYtmt5VQ43cEti3NlsNt7Z2QEAt0DFZwn1OwXfun86cJubm/ja176GRqPhniWqHI1GOD8/dzvAfetb30osYun3+zg6OsL+/j4eP37shId7UTx69AjvvfdeIkND461sk+ZPW2ZRi6/IiM/qwAdB4Laz1QkoZURVslT+1uqrMqRxoYGKosgdGsHftejkJpDcGIzFGg51/dUlVuXFWKD9XRV+Pp/HaDRK0HWxWKBarWI0GiV2ivRl99CjIXLnvATvsZNfGhrg70T1VIa69azyALDMXtKYNdutKFKNkxo8RfXK5z6jrNe0jYq+fceUKQK0161ysgZHXX0df1U+QRDg7bffxpMnT7zbrVpFrjJhU151PPh+G5qwv/ve9Tplbv/n/dxjX71Pq58syLBI2ucx2/YoL6ZSKXzve9+73THuIFgePVUul3F2doYoihJ5mD7lo66WorTDw0PkcjmcnZ0lZpjVJaSC5qq7fr/v9pemi3p0dISzszMX8yaDFQoFt4+KIhSLbilwZHB1U3mfPqOoZXNzMxGnZn+pLFQB+LbCBG5m/qMocoxHweCzVO6qrKi0qfzs8WtcxaZCpkpYDZENYaghU9Skk7IWpbNtnHzjikLyg9KN8W5V9nZ3SdJEDx22/cjlciiXy+h2uyvbAwBYWQzC55VHyZs2dKH90rFgH5S/rddpQwp8hjQgOtV0U6vUWJ8qbav0XhVC4P3aH32HyhlDfTo3oMraAhabYqhKm/ewPfocja6dN9D5GTWOVuFqse9Ww2fv1bHgpncWXdtYtg3RaD3KC6/L435tqCQIgnwQBP+/IAh+GATBT4Ig+D9cX38QBMF/HwTB50EQ/JdBEGSvr+eu///8+ve3XveOKIpw9+5d3Lt3D/fu3UOtVnMC6nNlVOBJ0ChaHsB5584dAMD29jYODw9xdnaGq6urxJ4CvJ9IEwCePXuGp0+f4urqCp9++qk7IIHMn81m3TaMGrtmnZYRLIpQRW77ohMhYbjcBxpYVe4aQqISpHUmIud17nfBe4Gb+Cuv7+7uJtx7FZDJZIIoWu40yC1tNe7NuqgAFdmkUim3ZNcKgioIxlVVCWpR2rGdNtVrNBq5MaLgcKx1MyoacTXk7Isu5grD0BnnDz/8MDHONm9fi45LHC/DHPSQ9P6dnR0XVmNh+MvG/tPp5clJPFiWNGFb2WcbOrMK17ZVXfp1SFFDS3xGZU9BgK7c5T2TycQd8af01vr4jFXmyi/8jeBJ26h9Yb+Vly0iJx9pv9k2lQtd1KX6Qt9tEbpNCU2lUokTpoDVAzl8eoPt9YVXtXwVxD0B8KfiOO4HQZAB8I+CIPh/A/hfAvgP4zj+5SAI/hMAfwnAX7/+bMVx/E4QBD8P4D8A8Bde9YIwXC6DLpVK7hzHxWKBTqeTcMeUeNYyc/e+4+NjXFxcYG9vD5VKBd1uF59++imCIHBbrrbbbXeALmPePLH98vISqVTK7bE9Ho9RqVScguIGThsbGwmkrzEvnQlXoVCm8iEcdRs1fEBGUCSmIRidJKGCJ2rX+KDd5pQnzWgbarWa22lRBSWbzbpwEdtvDz0GbhiafVcErsxJBav16So6K5C6uELrZdHjujQbx4Z3NBuhVColMlLoXXB+48WLFwmeU8+DY0ljoqE6ttMe2xVFkRsT9ZjoxWjf+DvTWPVdSuc4vtkGl7xgPTGLhtWTYbvYdht/1lCXAgP1Yvip/VRDaEM9ijT1OY3ZqyIHkp4en1WFqjLAZ22YSueQ+D4FDXzfuhCgpaP1TlQncfytUWVRWqmHZMHLuvJaxR0vKcWlZ5nrvxjAnwLwP7m+/ksA/vdYKu4/d/0dAP4rAH8tCIIgtn6GFCoU3eaSilWLRQD8zGQyeOutt9But9Htdp0yYrig3++j3W7j4uLCCS6FiogNgEszUtdPGZQH7fL0d+sNKBNypt/n3voYQpUklSJww8xkSt/kDH/TrIuNjQ00m82VdyqjMzdVEUCn00mgEJ2w1f0nbDgrl8ut5MKyb75+r/tfjZoaNEXkatAYHrF04v1UZCq4FDJdURkEgRszph1qni7prGOmz6rxViXIdFKGZ3i/CrqPXovFwp1tqC44DbqNnRK8cGyt0WNRRWHjsDa2bA2A0tvnzaksrDO4pJ+VAQ0taH1WySq9Vebs6k6CH22jGhPruVHWLc9ZlK9Km+mMFkSwPt0OA7jZZoG8wsU5GjZSI/2q8pVi3EEQpAD8BoB3APxfADwB0I7jmKN6BODO9fc7AF5cd24eBEEHQAPApanzuwC+C8ClPL148QKLxQJXV1eOOSyDK1ORgGEYJmLaHMTj42PMZjMcHh46gVQGUKWlBA/D0J12nU6nUSwWsbGxgc3NTVSrVefiK4EVKao7q+1VZhM6JGLMdNNs9gWzTtQ9ja/DDZyYA26U2ueff77iAltDaAVB0QyFX5e+K420juDaNeZmUVq3VcSs08YNSQdue9vtdjGfzxOnYgPJzaEYStDMBhVmpleq8CkS0rZpvaSj0l+Rpo5fo9FAp9NJpAqqslVB9/GBjSer18T5B1VG2j+rPBVoqOK0IUdVpKogLH/avs7nc+d56u8EKHyHHratsqZeo1XeOhbaByo9NaIqUz5vnDwWX4cwLBrn6lAFGUozKwvWa2OpVqsYDAYrazEs7dUzYImiyK2oVO/W9mdd+UqKO47jBYCPgiCoAfhbAN7/Ks+9ps5fBPCLAJBOp+Mf/vCHCWRBIbGuiTI/Y6mlUgnAEvUx1HF2dobJZIKHDx+iWCxid3cXV1dXOD09dW2wjMNrREpBsDz44P79+9jY2EChUHA5vtYqW4ZXt84Kjb7PDpRO5mj71P0n8tF0PTKqtkHDKIrk9FPbzpicunjKeHEcu9WmNBbqNhM18L0a9lFUQmRLIeP9mUwGBwcH+PDDD/H3/t7fc1kkSsPZbIZ6ve48A12VqWOqCJTv9WX9XPNfgu+UVopw2RelCZWU4W3XNxokCzhoHKmcONHN+9XQWv63/VQe8aFP9SD1fzuHop+qTPhMECQPf2Cf1Jj4QBVXGuu9drxURrQuRexKXwVK+gwNuIIhlRvgZotiC2yUR5RmvrTOKIqcR6v3qqdP/WWRu/XorQH6Kor7t5XHHcdxG8B/B+CPAKgFQUDFfwjg5fX3lwDuXhMzDWADwBVeUeL45oBMuvnvvvsu6vX6irvDTjIOXa/XcXBw4GKwHDAyLzcR4mSZCimJlclk3O596nrG8TLmu7e35+Lj2g7ex2c4+HZHQy6FLxaLKJVKLp1M+8+BnU6nLpZowxg0VnEcu5M/FEUr+mG7bBqiThiy6Gy+ZRwb71N0YRlbhUX75surVaFUI3xxcYF//I//sQu76G59VGq69wNdTdKffdHQifZdBYnPWTqqguQEtebqcj/4QqGA8/PzBKrT51k3jVK1WnUpmHx/FEWJvVJ0jFk0BGTBgIIZCwrUODBUk81mEwaTxojjp3xJ5K/KxY6h8j7bwVAk26lrFCyI0b7xGj+tArNK2vKzjhvrVOBHmhCUsX/6G9/xqlCFvktpTvmzxoK8aI2jDbdRr7GeV5WvklWyfY20EQRBAcC/CuBjLBX4v3F92y8A+NXr7792/T+uf/9vYzviq+9wHd/Y2MDh4SEqlQoqlUpCCQLJvGWGMYbDIXq9Hvr9vjvOrNFooFAooFqtOoYlstNwQ6VSwebmJnZ3d1EoFNx5f9y5TPdb5qCrklbmIvE5WcUBIhMPh0OMx+OVMBCfpdDoKeaaimgVoo2NKxL0xR41bODzNojg+cf7qXjJkJpvqqlYLNpWPsN32uwaRUr9fh+9Xg9nZ2dOmdnQQDqddu7pbDZDoVBwyoiZSNw3JpvNYn9/3z2rmTbaZlXaGrNU2mqdd+/exc/93M+5bX2tQVCExcJJyMVikZjQVbfe8gSVmkWqquh0It22geOnz1kkzdCipieSBhxrHUs1OPwex7Fb9KZ9sIBA+/AqL0L52ip7FjWIqiD1fgIm8iplgXzC/zmGapwJ5rSdrCeXyyX4V0GItlOfUXmkIvehagVMrypfJVSyD+CXgmWcOwTwK3Ec/zdBEPwUwC8HQfDvA/gBgL9xff/fAPCfBUHwOYAmgJ9/3QtU2QRBgFqthkKhgFar5Q7iVWTFTBAA6Ha7iKIIo9EI6XQa+/v7KJfLGA6HuH//PhqNBqJoOZvPxTOMnd69exfVatUN2MXFhYu/np2dIZ/Pe4mqRWOmijw1e0GfrdfriU2vrLtnXacguAmLqNFSZKDt0sMkgNWDgul56JJ+KibLXHqepI1PqutN5EIGtvF/GzqwiNIqOTUQKmy6o2KxWESr1UIULbfZ5epXVVzcfIn1M1ZpaazuKxWAxkU1dzyXy+Gtt97Cd77zHZyenuL8/HwlVKTjQV7kWNh38rrygEVxFlHbtjNfnW23brhe4/MaeuO7mCWk9/rGSMEAr9s1DXq/hor4PIvyCD+V99d5FDQYuqBF32/j7jaOzP4pT6nnZo239kflxIIUn3diaUl50TkV0jCKlscEvg5xf5Wskh8B+Kbn+hcAftZzfQzg33xdvb5CoRqPxy52vb+/j9FohNPTU+TzeVxcXDih5gpCDt5bb72FQqGAdruNvb09PHjwAADcopJKpeIIWiwW8cEHHzirvVgssLu7CwBotVoulzefzztEpxOGwA1D2pgpCwVK0TmPFaMHYBWHjYnx1HJlXutC6m/qIRChKmMyFMN+aB5zEASoVCqYTqcOFXJXRvaBHodVgKr4+K4wDFGr1bC1tYVWq4V2u71ygIHtA7A8gPnZs2cJ4bHxXqaHAcDR0ZHzEFT5sm+NRgOtVsuFNDSkYhdoKeqiwdjY2HAraGezGT755BNcXV3h6OhoJTxkld7Ozo7rixbrxmuMVY0y+05FpSGJOI7dASGkoc2KUkPJ6wooNBbLsbGo3KfI7bhZsKG/qXzo7xwHu0BHvSF9r4IH1q8yZMMXmh6p7bEGgL8pD5OfLPLV8ebvWofKxTojzHu1DYPBAJeXl8hms87bf1W5FUveM5lMXCqVHBrkoNVqNWxvb7tT3Pv9vtulC7jZY4MxNGZ/lEolvPXWW46wp6enbuOq8/Nzh76/853vYGdnJ7FIgm67nn2oMSlFG+pGqhdgU5ekn4mBV4blvTZ0okxuXVHew9/JbNxKlc/q5vh0H+1ybC16nYqM6Fvj51QSVCB0+YlQaYB3dnYQxzGurq4SmRIUUGZQsE/FYjExmUXjqulUqnAZblBDQgPD8AjnP4rFokPr7KtFzPTKFFnpeGh4hHMzqoSt4mN8d3d3F0dHR4nxsuhUx4DvUtr7lCjpZ/PgGQbQyVXlXbbNrr5V5UKe13rT6XRiMzLeZ5WWrcvyNz81ds+iIQrem06nsb29jdPTU29M3CJl61nZ+mxR2VYjpKm9vmfVC+Xz6o3a1cPaBnq23W4XrVYLxWLRZWc9fvz4dh8WrCiYmQ29Xg/n5+c4OztznbMEIlMFwXKhQq/XQ6/Xw927d9Fut91sfavVQr/fdyev1Go1dLtdDAYDJ4TcA0QVjyJrRWkqRIp8rBJlUaa2v1sGo7Ii06jLxP/VYGgdANwudsDNIhhFYGEYuli2bwzYPsuAfA8/2U62mZPA1iDN53Ocnp6iUqlgZ2cHx8fHCeSnipP94zJ1pQv7VKlUXLYJBYArC7m9bhAEbjENQwhMAWMevs1h135ZL4lZAizz+TxxXqcKJf9niqsqkU6nk0C/Gie1oRp9lx3rILjJp9Z71JBpbFdp5fPWLL9qPbZf/F+BhFVmivx9IQPNGLNzHUoH62XOZjOcnJwkZNDypcqThmGoQJWWvG7Rvq2XRSdx9fxNa6TUA1Da2dDLaDRy6054dmqv18N4PF5ZdWnLrdgdUN0butbM32U4RAVJrVW73U4spIjjGJ1OB0+fPsXTp09xdnaGk5MTlyZItBaGoduukWEXy/wsVNoqWGrx1c1mzIyDrC6Vvl+Zn/FbTpDokluLkHzvVgabTqcrC0d0plq9CFp3i0JYpxoO9TqsG6uTULxOtMdrg8EA5+fnTqDI8LZ+xpT1WQ0V6NYFpMdkMnGMz+dJS76PPDSZTPDFF18gim6yKnwGkkKnHoUiOj5PmthJdCJxHUPupc2x1z3f6Wk8ePBgpS0ca6UtDYcqJ+WN7e1tfPDBB24uQ5WIxlC1Pcqzyg82+0KNKhG4esHqmakiVfTOtnOMVPZ8SlvDIGrslWcV9ChiZz95H+nKNGIdb6W5erusg/U0Gg0XQuW9/FPUzl0F1TPjmI/HY1xcXDgQwRXa5XLZbS+9rtwaxH1wcIBarYbLy0vM53MMBgMn/DoYZFAqI0UetGKpVMplcOjEIRfV0H1+/vw5PvzwQ9RqtZX0MbaLDM3tTlVxWXTEQsVkY3LKnLpoJpPJoFKpoNVquZV2ihx1AcA6tKNK2WfkFF2wjslkspJpwj7rqi7WaQ9A9aEVO64sGkunISsWiw79Kx3tXAIRbBiGbp9mRTx2Bacqma2tLXQ6HUdPVajrFIRuN8D3czw55uyDKhS+37fiVz05jqeeC0lPhZPWdrdCVWqqoG1ohPdeXFy4c1Tt+FiFyzHZ2dnBycmJdyzJA2yn8oE1UNbYWH7ld54FyXguFbIFJtYbVP5SQ6Bt8AEr/T8IgoTesCESDQP5jMT5+XnimgIX9mcymWAymaDVaiGOY5RKJTf+w+HQLQjkWDCLjnNr2u6VsVj7y+9hCYLlUuujoyOnTGip1N0H4GKQtExAMm86lUqh1+uh2Ww6Ja4TUZoaOJlM8P3vfx+dTgdxHKPdbrsJKOBGKOx+wywW8ZKpbdqhxj+tkgKW1rjdbidmyGnNrbum/1tUSBSjio5WnAZQc3OpGCxamc/nK6jdusRBECQ2iVLGDcOb/Hk1FCoINBy+3Q1t2AlYTkYycyGKopV71LBvbGzgj/7RP4owXG7YpZNuVMxcocl3cqzo8SiaZRvv3bvnJs1JS9sn3UuE8w1xvDzsmoBBAYIueppMJri8vHRjqyl6LOqaa8jQolDSyCJ1YLkxlyp71sPFaVZZqWGynpQPcVo+1aJ8YiecLXiygIJGSwGVGk7NFdf2Kfggrzx8+NBtKWDDdWwni28MKMe+5ziWBBWj0QgnJyc4OjpCu93G2dkZLi4uMBgMEl52oVBw0QYrb7bcCsQNrJ48rhvXq1WN4xj1et2FVI6OjhK7wenZe1S6RBRbW1uoVCq4urpyyPbp06dotVrY3d3FfD7H3bt33fM2BKDuuQqLuntUnNbyExHbTBLLOCwUOrXIGttWlKFtY18bjQaOj4/dXtVs22QySSgmGkbWz7ba9iwWC3faPNPuNLzEPttUSPVKtO22fn2PhmV8E2fqOmuclM+Px2M8efLEvY+TPVbJKYLU7BvOdVChk16ff/55wvPhGGgKpE4ShmHoJoF5Uvyr9t9hnzTcYJWxhgDIRzrfwt+ojG3aHxWjKlxguV5AT7/RYnmYxYY1bNH22LZxrJSPdCztM+vqVK9MJ/9VVsIwTJxZG4YhXrx44Yw/6U16af02ZEpZUb60/eeZAqyXacWTyQTdbhfpdNrNy8Rx7A40Jw9xgdaryq1Q3Kr0GOJQN0utGrNPuDvf/v6+O+7s8vJyJTTBgazVam6CSgUpDEP0ej3MZjN861vfcnnQQHJDHzKpxgNZtw6cZmGo9bdo3VeHnQzS4rumTKzGKooih57K5bJbFs74L1G1KjC20aI4/WRmjho0LmdmP8l8dKeVfmqsrPDaQoWaz+exubmJly9fJvrsQyRsG0MF2WzWpTcyXKLv17kTKjTt+6uMhqIweojD4TCRakn0FQQBLi8vE4advEk62W0BNBxEAVe6kxeVx2xoQvuk11WJ87PX6yWeU7mzSlTnKKzSUpr4wjg2HKnP0lDautWbsmOu/MNJaxuSAZJ7qAdBsPI/67dAzYZi2AfVLQokOME4Go0wnU6dwajVas6g53I5p7Poueq2teoFryu3IlQShmFis/84jl0opFqtroQZLi8v8cknn+DFixfIZDJuJ0GduKISKRQKKBQKuHv3riPw9vY2crmcO1SBrn06ncbu7q7bc9vuGcKB0vAEhZGDZkMhyrAUUgqHpg2yHqtIgJtDDVTh2WX12m8i3ziOnUDa3xRF8X3Ww6ByKpVKbrk2AOfe1et1RNHNToaKUthWXTijyoT1kO6WH9iu2WyWmFhWRMRPG1Ji9tD29nZibxnNINJ2qFFWN5x1ak4tx8iHuu0knt7P8dF95rVYJadyQMWuPGXRKGnjM2ZqlK1SsjRQ2mvdync6DgooGDojPTT0sS6kp+0EkpPv61CnKltNGtC61Ehqny2d9VPrUUVujZ/yuLaJ76S88H7yWxiGbuW0hoPplVnj8CrUfSsQt4YMgmA54cjlxJ1Ox90DwGWQMD6aSqXQ6XQcGlRLyA3qmau9vb2NjY0NZ+l4cvx4PHbKWidaiPo0DZAKQFEQ262TkYqELALg4PP9vlil5uRy4QiZ2udOstDgsPC9mg6l7qoifUWa6iGQBmq4gGWmiKI6/U4DoROQFi0qrTTz5lW5y7rPBGlhDRcVdKFQQK1WcymlKpR8P+8lOtJURuaTM697XejGZgv4xp3tYw60CqkqCRaNxzMvX8dT+6wypIUoXhGs8lgcxwkv1Bpza4Qsv1haTiYTFIvFxF7sHGvrbVmeU35V48V7eI0esZ2gVeOiYEnbp8bLZ/BtWIrtUcNr+dXSgdla5OPhcOh4hrxFfVOr1RL01rpeV26F4gbgkHEYhu6ggzAM3faL1o0AlnHxp0+fJhgUSC7D1eXAP/MzP4NCoYDT01O3OIRuTLVadRN5QHIQbbzMujAcTBVaq0CBZLaJ5gbbkIu+i8y3vb2NZrOZiNlbd1JRpF2MQWNjMypYiJKoLNge4OYAYaUtr6uhsa4mjSIFTU+7IS34Ht3bmHu1EMFY+lCRMtZI5cv+kbbPnz/Hl19+ubI3OsMkXNBBHtnc3MTp6alL2xuPxyiXyyuCpIrFhvIUsWrsWfsGIMErqnRVSTC/154vavlO28R+6unwvray0Iholgzbq8pIFa9VtPqpR8XpGPtCfXrdts0aEW2/ndz3eQgKTriXC5/TCWTKlz6n360HpOBNx8HSJJ1eHuwyn89dBsl8PsfW1pZ7HzeuA5ILoaxs+sqtUdycQOIxWcpQ1n1XZUVGtR3ls9yVbW9vz20itbOzg2w2i5cvXzoleOfOHdRqtQRitxZaUa8iHWA19U2tvbpBRLQ2TkjkBiSRDpXXYDBIrObTfrId1tVSxGNPQ9c+KJ017s5ClMO2kxbaBkXp6qqqN8Lx0pN44jhGoVBYyWJhvcznV1rzs1wuYzabOSNPBUxFw35Qib3zzjv45JNP3LuiKEKr1UK9Xke5XMZHH32EdruNTz75BF988YULw1n+UrTmUxpqQNWw2Ulbjq/yG/trvSI1eJrlxHGz6Ys63hZ56nuVX+z48T5VTCoHQHKiXsfG1qnXeJ0Gwlc0vGBBFIsCIPaZbVQDZw0/Q3Sj0WjF2/F5ND5gpGFU9aJVhuv1OubzuTtpaTaboVQqYTAYoFwuu8wrn8FYZ+hYboXijuPYTT7pTmlcs6/Ln4HV1YaAP7+zUqngG9/4Bg4ODhI7w3Ff7e3tbZclwYR3DqQiTJ9raq/rAPgQLe+xzKj/2zgjmTKO48Q+yPo8LTWf4Z/tg+Ycq4JX11X7o+EYbspFRtd2UyGxfbwex7FDuoq8GG6gAlC6KcKjQuDGOzrGNmzGaxrWCoJlSmS5XMY3v/lN/Pqv/zouLi7cdU4ajsdj9Pt9XF1d4fLyEjs7O26FI4+2s0ZJx1+9JHXZFaGxfRaVaQiONOJufUoLH5+xbGxsYLFYLkTzGVS2Vw2G8inbag2AAiRfXFhRqi8bSemhvK/lVVlMSlP+b4t6wjaUqPX5TrknMCQ/qqfMtlpQpnKqY+HzdukJcjdBou+Liws3B8PwLOuiJ+gLUdlyKxQ3cGPBdEtUIm/ryqwLFTB3mW75Rx99hLfeemvlpHIyAScoiYiA5Cb/LNYq02LP53OXuXB5eZlgFnWrVFFyMBnPZb8197tSqSCKooSy1rawDcxKUGSfSqXcjnRUTJbZFAUDN1uLauzVKlTG462A2bgl3VJOwPCdqtSVLnEcu4VRilyI8tku9lkVgG0Lx4jvv7q6QhRF+M3f/M0EEuc7SHvSmZtgqaDr4iflCau8FEhY78fn5ehY+JQ7x5LP6xirQtPj6bQONaA+pUdFQ+W5ubnpFoDZUJlFzZQnBVjKB7b4lDbbd3h4iFar5fhVPVQFPkoj8gGLXevBop6BNfq8poha6cHnrbevhsiG+8i31otQkDQej936AYbitA4Ctdcp71uxyVQYhjH3wKagkHk4U81Jyuv7Aayi3o2NDWxvbwMADg4O8Pbbbzs3yg4gcDOIurUjkLSkFmErMtZBpLHQpdH8zVcv22JRGXCTxcCUJWYraDiB1nldn9RVVwVgGVwNjAqNMqWiCk666ORwuVx2i5hsXNN6KlyOTnTJmLT1QjhRSAWjfbQZHL69V4DVDBDWrW6tjhP7SaNRKpUckiU/Ko18CtGOufZdEboaM3sP20he4rsKhYKbhNextYrCZwxYDz0J6zGwDYqY9X9tv46VeiBKD6UR36F7qiiQAZIG0hc+sWiX42onCJUufK+VfTUK2g8rn0obq6D1GsGirdMnlzS0xWIRcRx7dwGMomU8/vvf/z663a6XyW5FOiDRsgo1sFRg9+/fd0F8EoLLQhWJAEvXuVAo4Gd/9mfx6NEjt/pQ3VHWMZ1OcXx8nBAyi+BZdNB0MOyiFZ34s4jMPqtMZ/fGZqxfFZ8qG11WrS71OndTs0FsdgXfry66VUgq5IoGaBR5yLJO2IRh6BYSsL58Po+trS189NFHqNfr7hl6PUo7NTDWFaXS1hRQNU6kL8NFrEtT1OwCCn4SrXNZstZJGip9bCqoHWP97uM19e60f2pwea8u17cT2xwPeikKHpjpUCgUVuZv9N127O12qz5lrnMX1jiyXqu0WTfHQY8SI39Z5K7vsDxF2bbvtjyj12wYx46ZVdDW+GrISOvkuFk9wVKr1bCxseGWtdt3cWxetU8JcEsUdxguJ5aoCMh4e3t7iOPlUnTGpev1Oj744AMcHBw4l0NDGdlsFuVy2eVI6kATxfT7ffzGb/wGut0ugGQOps/dUyFQFGERkbrqVui0LoviNStmsVi4PcaVwXQbU929DrhRHsyIUVRHIwckJ2mobBSJaZu1KILgc69idtajJ1iznmKxiPfee8/lhTPcw/eyv5rTz/dRqGm4iLyBG+Nn260G0iJANeb8n98ZorFIm88wQ0Yno/RYMKWjFUzryQXBzcIlVaaWr+jhVCoVPHz4MHFoNduoXpU+a9c5kH58B+mqvGMVu0XjNhRoQwfWmJK/eS2KIm8ev9KHfKnpf+yPzdqxY2hDG9oWYDXuv67oWLE9FnWTjxTp809XbHJOSGVNdYTllXXlVsS4oyhKoAlg6TrxdJFsNou9vT2HJu7cuePStcIwdLO0d+7cwfvvv++QHAeUzDscDvH9738frVYLDx8+xHvvvZdQjqrg1Q1VhKpKmZkwGoPlO7VOPYmdcW1lTIssg+AmVqYTMMqoinqstdb6NMWLvysKUVSu38lkVKpRFK2sirRuNpB0nfm8Ku6zszP8nb/zd9zyb3XjtR72UQ2qGme7tavuqMjDIqig7H0Mxdj8chaeCWpXtmq7yIscF9IFgDellLTndfUWOU5hGKLRaGB3dxc//elPVwyRGhwfSrMhN6XtupPKyY+LxQLD4dDxo8/YKLrUsVJPTkEU+0Za+UJvTNW1nhaNmb7PgpUwDN2qXVWmNKjqoet11kX62FCKGi8f/XVcrAHW6+pl2ZCW9exJo2w2m5h0X1duheJWC0/3KQxDJ5xcLhoEy1PXKbxbW1tot9uYzWbI5XL46KOP3KY+eqhBFEV4/vw5fvKTn6DVaiGbzeLk5AR7e3suJq6Kwioktk0HgkznG1x+KsrX563bBSRn4bkogqglipbLZBuNhtvxTRmTbedkqV0AwWJdfnVLaSB1gYsyMgXch/St8VEaUqCowPv9vpuIUrqqweC4sT7dAZJtZ39Yjw1n+UITfFZT6oCbkBfbrGEafV4nxRTdUilpSMqmdOp4qFdi3zMcDtFsNhOGVusNw2WmDU/f0dx0i4q1WJooANB+W6Ws9NUx8o2BjrUqYt6nhoWKWcdcvQRF0b5x19CKjpHyneUp8obSZB26Ja1sGMsqdSpkmzKqxhNYPUNSDSHrpU5RcLWufGXFHSzPnPw+gJdxHP9rQRA8APDLABoAfgPA/yyO42kQBDkAfxPAt7A83f0vxHH85SsbkV6eFZlKpfD8+XMnrDs7OwCABw8eOARar9fRarWc8I3HYxQKBURRhB//+Mf4xje+gSiK3H4B3GyIBylwNWUqtcyN3t3ddZNtJCiLTwgUFaty5v+KRlUIyNiW8VWh8D3co2M0Gjn3WK1zGIaJXeVsaIaKVJkjl8ut9FFRkaLrnZ0dt2eMRVH6B9xsKq9xwEajgfF47LbmZZs1f51FFb/Pk4jjOHG48mKxcMv4aRSt8tO+6f+sk5PIFu0rMtPxANavIuR4qbtPhcLnLRK2qI110SscDAZuTBgO4oIhpZGPV+3/lBPS2IYtlJd9iNMqeusZaVGPEIA7tUjHQkMJVK66r4/yg4IZpSPbbzPLrEfKkIRmijHdTtv0Ko9Vx1kNrxoyBUgcL+sl+HhUr2mbvkq45LeDuP9dLE93r17//x8A+A/jOP7lIAj+EwB/CcBfv/5sxXH8ThAEP3993194VcXMt/7kk0+cm7mzs4N79+6h0Wi4paHAze5rw+EQZ2dnidjg8fExLi8vMRqN3Pr/KIqwubnpVslxsUapVHIbVVlic/tXFXaNB9prPuuo7p+iNGUq/WShsNhJKG75ycFVxmXRrBybdaHpedoX9XTIjN1u16FrzWbR9D72R5UuGU5T1EhXRXWWTqroLK2UtqpQaIx8fdG2sb+KcPWUdY435xnYBit8qmyUZqQ7+6JekI6n3r+uqIJQo0qFpLTRT4uKWdQL0PkYNdaWftpf7bdF4nZMdCz53Z4SRJ5Ug6A59T6PlG3TUAvDdpq2adEzgYLKbBwn55Ms4lVetOhcx0Y9HKWnelJAMgzqMzrWU1T6art95StNTgZBcAjgfwjg/3r9fwDgTwH4r65v+SUA//r19z93/T+uf/9XgteYjyBYhgdyuZw7pHcwGOCLL77AkydPcHJyksgeYI7udDpFsVh0gzQYDHB8fIxms+mWtBNJEsWWy2XU63U0Gg00Go0EMVmU+GQa3dhchVuVnh1sFmUEy5QULlVQFFSu9LSz1FSo/E4kobvf1ev1lVQpm/4Wx3FiMxxFQD4Fy0+LvqzHwbi/dWPp7SidVdFp3apI9T1ctMD4pgo649wWjanStsjZKkH1JHi/TpofHh46g6/eiI6d9kfpAsDtjW69OB1LO2ZqwKkc7Cpai1Ct56JGV2mqnpovHKjK3/aFPKMKVmlIAMJCXuP9lNkwvMmiWAdkrAfD/jIuzPbrhmdarCG1iQhKD6s0rfHRMKM1XEqX1ylfy3t2PF9Vviri/j8D+N8AqFz/3wDQjuOYgcIjAHeuv98B8AIA4jieB0HQub7/8lUvyGQybntDMku/30c+n8fjx48RBIFLC+x2u25FHdHSaDRyQX3uSJfP59HtdpHNZnHnzh3EcYzNzU3s7e25TdQ5ccgTXyzCsFZRB1rjjyzW1dH/7Sy4TlgoUgzDm9NmVIgUuSnC9TE19yVnKIPuthVq7gtiBZ6LeBQRKbJQ9KZuPOlkD1IIgiCxB4lFeeyjIi+91yJxi3D0YAXNRGB7qPxsXb7sH84VaPsZnnrw4AG++OILjMdjlxGjz2q4RftGxMhxJJ2ZM64n0KsnZ1GfKkOLkll08tuHiH2ej63HGl0dRxpnZnVpW5UvVbmmUinniWkYj+/REIa2yca/tViEH0WRC6u9KuyjITK9l2PD+shLGt5UT0SNpX5az0jbq96ffcbOoVjjo+W1ijsIgn8NwHkcx78RBMGfeN39X7UEQfBdAN8F4I7s2dzcRK/Xc7PbXNlIAWEqH9EzN2zhRjwcCBoBMs2jR49c+hlPmBgMBgBukJVVCFrsAKjytUxi43JWuJQZdTKHxe4VYgWJRkYZTNtjQwVkWD0cAIDLnSbC1vYDNwtlbByR7+T9Nmav6FSXFbO/pLm6mnYBlPBIYk9q4Ca3OIqixJatWr/Ni1daavvsftwcewII7n7Itk2nU3z/+993/OhTJirYtvBdvgUmnMPRkIZVYuyfbiCmvOELlfB9uVwuMbms9Nd7rVJn//UQ7+fPn7stI3K5nDu31GaWqHG1K1D5XgIvy+d27GxRw6/vUhlkfWqwdAzUaAPJtQCUJ2v87fv1fh+61nezWJlRo2hpsK58FcT9HQD/oyAI/iyAPJYx7v8IQC0IgvQ16j4E8PL6/pcA7gI4CoIgDWADy0nKRInj+BcB/CIA7OzsxMDyfEAi693dXQBwp7Fr2tDGxgZ2dnYQRcsDAzj5ks1mUSwWUS6XUSqVMB6PcefOHTx69MjFRKMowvn5uYub63mFFu35io1VWotrXdbrvq4Iitbvy2Pl9VQqhXfeeQcff/xxQuHxvD5VWmy/onkNHSgTcx8OdUUpZGEYupWqNHBWGfFdPsQKLJG87rFOOkRRlHD7AThvR/thc9nV/eSYadsYLrNKwHomNCbZbNa9w7rLi8XCnVTC64VCwW3BoErKemfrDPfW1ha63a57ThcCWWWlE8VKbwULOmb6bq1HlTHr8z0HJEMtLLPZDBcXF6hUKq5uHsrBE9eLxSLu3r2b8MCU3zWsowpb4+w+xK7jp/1f97sqb9sPy3/qsShN1CDa8KVV3FqvVc6qQyyKZwiQfEta2LkgpZWvvFZxx3H87wH4965f/CcA/K/jOP6fBkHw/wTwb2CZWfILAH71+pFfu/7/H1///t/Gr8L812U0GmE4HKLdbuP+/fvY3Nx0HdNDNcNwObHIODhDIvP53KX3lctl9Pt9bGxsJLZ0ZKoVV2kqcX2fdoDV/bNxKRubA242m7GWXRUo/1fGY5YMkfCzZ88S8ccgCFbS46hkKKDMQ2Z76f7r0VrT6TQRiyOdODlLJan9t0KhSMMaJu2fzYjQcAFPIuJ1Wy8LUZuGE9h/pY81MMzQ0fZxox8+71MSFChmL2l71PBq5oaOCeuiAeYeHzSsPpTLBVN2Zaz2kwZW+8mxs8rAem++MBu3Ud7e3kYYLtMN2WYaxcVigWaziVar5d5RLpedt6zIVN/DcbLpjxbtKzCw426Vvi98Qh6L49g72amT6Dqpb5Uri27e5qMZ26nAwipeGi4NrfAeVdb2HVr3uvI7yeP+ywB+OQiCfx/ADwD8jevrfwPAfxYEwecAmgB+/nUVDYdD/Pqv/7pDVY8ePVo27lrYy+XyirVNpZbLeBnPPjg4QLVaRTabRSqVwu7urlNORGZHR0fo9Xp49OiRQ5xAMkb3qpgacMM0KlCq5HXwfHmoPgWlQqxZHLyH8Xy2UdGeokQqCRa17KocWFTRWMQGIJE+yN0ViWpVoauSZz8tzZRxSWcVJCIc682oQVNh1Eki9o+0Ue+Dhp4bSVkUrkJm6aLvIo0tPbWNiuxItziOkcvlcHFxkVDAOrGtbWG4RMdWt8HVdxKdq5JnLj5Ro8bWLd+yf4vFAqVSydX17NkzTKdT5zHxOz0EbpS0u7vrDk5QGbBjbidA+W41lHrNhmr4O99j0a+t1/cO9SyUl9blwatCVbr5UL62VcfdGib9Tf/35Xi/rvy2FHccx/8AwD+4/v4FgJ/13DMG8G/+durlIZqbm5v4+te/7jIHrJXivhbcwS0IbvK9VZg5kIPBwC1m+Oyzz9DpdHB4eIh2u41arZYQGGAVeZl+uXuAZOyZMUBrMfk7lZOuJLQDboWfdWhKla6mVCVGg7eOsdT11hAKsBpvpTHTe4Cl0GxsbKDX6zkFzfevOwBXhUTp5aORdQ35v6Js3svYu54xaMdSjRyPPovj5OHRin6UnqzTKglFjWowCTAs3amEGIenogCQiK9b5WK9Bh2HMAzdAi3gJswUhqFTsjbWrcbRhp0WiwX29/fR7/fR6XQQhqELCXExCE8qL5VKCMObA5DPzs4AwIUlmX3F/H0mGNRqNRSLxRVla3mGnqGOH/uWzWZXtm6wIMqm//lAEos1Xhbdrks6sAbHLkrTd1EnaPqpBTX2vQocX1VuxcrJfD6P73znO6hWq24z/FKplBAAChiVhlWSOlhxHLvVZVEU4eTkBKenp9jc3EShUHD3AavuPT+tS+dz3/hubtWq27D6JuJUmahSYz1ar2UmIloqNNtmRZzWMOgiDnU7LXOWSqXEtqa6adF8Pkez2VwxjtZQWGRj0aeiWxUEn6KK49gdfcbsGN3Ck66xKm4r/PqnY0FFZ5WnCiH7QdBgkZS6w9adtghcDbgvfKHjbPPlOe76P+d03nnnHfz4xz9OhGr0U+mq9FckzHt4AlUul8PW1pZbpUtlfHZ25kJGTMnt9/uoVCpoNpsIwxD379/HZDJBu912yJzbFFu+tehaQ5NhuFw0d3JygnK5jEaj4SZY2WY16Oyv1qnGk32046tjox6N3mdlXcdPaWgBBr1Sgk3lM95jvQvbvnXlVijuQqGAVCqF4+NjdDodvPvuu27bQ3WzFBVZhQcsCdFut3F5eYlOp4PpdOr2ZKaLVyqVsLe352KOvhVsGuLQAfFNeOh9KpQ23mjdaouyfP/rUmwbE2Nsnxs56Z4iPJJN3UF1z1R5acyeCJbtUI9HESaViwoET5PXtgM3yJL00LkKVXa2TQBcSIb/282tfIbBCjb760N7qmjVoKmC5bVGo4F2u51oP+nKMbfhNdZBI2knjH0eFuvRNquBUh4dDAb4+OOPEzzK33wxbms4+En03u12UavVnOFmOi2PD9R5AQIJehz8/uTJEwdk0uk0er0ems0misUier0e4jh2YRm2h/xq2zUYDDCdTh1gIOLXiUNLK+s9WYWtgEX5TmloDa/PM7L6hzykBoC/2UVGeo9GFnzvXFduheKeTqf47LPPAMClFllkyaKMrtZxsVieAvKbv/mbiONl+ttoNHKZJtPpFLu7uy4WToWgCJlCpogSWEVFxWLRbfkJYAUF2piiFjuJaY2CRcq8phNgFE6e09lqtRLPax4vrxE1kknt4RJ6L+lMJaNogRNnFnVyGTqL3qNtsCjPMrLSTQ9v0OXfep8dL/aT46vxbt09kTymz2gGjM3PVhpbb4xFDTU3Qzs6OlqLEklfjgvHWw22Kg01lPzfrh58VRjMKr1UKoVut4tWq4WNjQ3UajWMRiNMJhO3p8xsNkOr1UrsxkfQw9zryWSSCGNwoVuxWMTV1ZXL/KJXuru7i42NDdc/3R2SNOJRfdVqFcPhEKPRCOfn527yfDKZuCPn1OvyeTDWuOtvFvipZ8P+qMzZdlrgZQFAFEWJXUg5hqq0dWzYDh1rX7kVins8HmM8HiOXy2F7exubm5srAmET9Hu9njvgNZPJoNVq4Qc/+IGbIc/n86jX6wCWgvCtb30LOzs7bkc/FTKtl7HoKLrZ8cwqV2ZBUOgU7eqqMh/qse+zhskynjIN20IG4IIjVYJ8hshCXTfrSShqYZ99ueVMhaOi0P5YV1M3DrIhDNJUzxPk+9U9ZTu1LkW1pJN+sh2K5LRuZmswu4Tt4/j4TkmysWz2Q7cW4Lup0HidsXUKoIYo2Ac1YrZ/thwcHODq6sqlgPrcap+iVnopSGE7xuOx85Q01NBut91cgs6P8L00ADSS+XweGxsbaLfbSKeXh0RXq1W3MRpDJ+l0GvV6PUE760lNJhN88cUXLsmA2VDPnz9fkb1SqZRA2Ko4bcw7lUolVvT6FK/KmM0IU3pqeIzjRtopP6ox8YVHVQZ9nsK6cisU93w+R7vdxs/8zM/g8PAwsdwZWE0X4iKdSqWCfr+PVquFn/70pzg5OUEqlXKLbVKpFAqFAr72ta9ha2srsRmQoj/gBtWqIlKh1SwADVmwLp0wUeG0qMmHCqxiZ9vYJl3IogKuzGIVsipPVfr6HiI7FWq19syJ9u3/rXTjJ9/F93MMaNC0PaSDHtrKdqni1d0Olb7aD20DEZzSmjzG2DD7qTSx6X76u/KE7bMaTWukdZMt+6wqSR1b9Y4UHXP/GPUM4zh2e4DrXttW6NeNHZVfKpXCeDx2q4y5OVShUEC1WsXx8bHzRrhkn2NKXslms3jrrbcwm81cmDKKIhQKBadc2+22237CbnxlZZ1x4TBcrings2EYusU/m5ubAIDz83OUSiWX1ODjaSpilVkNYSoatmOtYQ1tp9JxnYdt71UDo0pff1ssFm4V97pyKxQ30RXjWXqwL5CM+3KzpFQqhcvLS5yfn+OTTz5xqy0p6MwxffjwIRqNhhMsdbGt8rX/KwIksfm/ZikAqwqb1/hJhUVGsQqJRWf/2U4AKyEKRQa2qPK36IKCqxvp0zjQs9H6+T/rtAcI6DtV4VpERsa3DMslyupC6vOsj8JNBKixYhUm38IVpS0/qeDVEKtC9HlCRNQEAD6XXFMb1cPR8JUaE22P9YhYbxRFifkD7XcQ3GQt2JCBGgYFFprvPBwOUSwWcXp6itFolAjBbW9vO55WwEEjl0qlkM/nkc/nUa1W3ZYA8/kcL168wGw2Q6FQwNXVFXq9XiLMYZWSyh8X4n3++ec4OztzbSiXy27Cs16vu9ALt3ZuNBorE5Q2Zq1K3cqQjqkaZNJcx1mVtQWWlvesh6+GSvvPuieTCVqt1oqMabk1inuxWODjjz9GoVDA4eFhwrXkxvgA8OTJE1QqFQwGA3z22Wc4PT11xOCE3d7eHt566y1sbm6iUqmsENuGFnRgfbFmCjyV1rpYp8ZTfSEJMoaGOyjsVJ4WLVC4iXgs4tR3kWb85D7WRDCMy1ulpKtH7WSJHSfWRUWiAsLj5BRds267iZA1pBat2ncGQYBisegm0hgSIT3UY1JEqPFjO2GqfbaTeCxqGBgW07Gz92oddPEtgvYJrd6jdVnEruEACjnvUY+SPGa9Q95HPisWizg5OUEURdjY2HCAYjQa4eLiwtWvE+E60dput7Gzs4ODg4NEuPPp06cYDAZIp9NuawJmn3S7XbTbbSev3POE/aExrdVqGI/HaDabyGazru5Op4Pnz59jd3cXi8UCtVrNbTTFvuuY2vHSyXv1YsnHOuakN422Rdx8XvladYxV+urx6/u0LVwAd+sV92Kx3GM5n8/j+fPn7pzJ2WyG09NTXFxcoFar4fnz527BzZdffunOjFRF12g08J3vfCeRvkUloQtH1MJZJGTdJRZFir5QC5/lJwmvLhZ/t/t46CotvU+RvGUyvtcXPgCQiOdqvI57cyuSovFUZUqlo+69xiOtQWKfFWEow6sA6R7efE4VkqIVKh/mD7PfOj6KeKwStuEDi8jC8GZTL7ZZ20P62pxy/q7tpgGjR+PjL5+3or/bogqYRevl+9WjUENllYqOBVcdFwoFHBwcoNfruaX53GoCgANA3M2P/J/JZNDr9dBqtVAul/GTn/zE8UMul8PLly/dGo3t7W1Mp1Nks1mHwLnfCbAMgZ6enqJSqaDRaGBjYyPhlZK+i8UCV1dXuLi4QLVadUccXl5eYnt72yU4WDqRlnbyntetd2r5hrygXp2NbStf+vQI5Uz5VcESvfHXlVuhuAG48+6GwyH+0T/6R+7ABIZOmOS/t7fnZrpV6RAVkJmsZaRbDiRzdpW4Oth2gKi0bKjCZjlYIaTStjFLfb9VQtofPbBWUapFC/yuaME3iQjALQjRZ1j4v3UjlanZDy4IYlG3WhWvHuKgnhSVshpY9kvbZ9PEyOjWxdVDJ3if0tIKHOdAuHEX20RDY11a6y7bQqXAexnWWxeT136o4OoYsk6N27M+3Y9cPS1F7TrurJfxfk4icv0BF9pEUYRarebCIhwHNVw0DuVy2W0Al8/nEUURXrx4gW63i729PdTrdbTbbfR6PRc/Z7YIQxvMTDk5OXHAYDqd4uLiwmVkMJ13MplgZ2cHtVoNl5fLDUefPHmCfD6PUqmU8CaUr1RWFEXbMIfSeJ03pXF08qXeqzLN7xaF67gof83nc2fI1hly4BYpbhJ1MBjg6uoKL168ALDMD6ablslksL+/j+l0mtjLJI5jl2XCzalIGJ/l5HUbX7aGwKIcRaUax/QJsdYZBIHLlGFoB0hu1crB1cHSbWYtqlamsBafdSoC0/aQuXm//q5oQJlOx0gzaUgP9sfnNSjK09S4VCqFvb09nJ6eOg/JzgOMx+MV5KvxbY2pW8/Geg+cR+E9tVoN3W43gfyV3kpP9oN1275aHlssltueEl3yHZxQVwNv4/RWMahS0IlmxprVkNtQIGmuyvby8hIXFxfY2dlxKXb5fN4tsEmn025BDWnKuQ4qXo5Vv9/H5uYmNjc3MZvN0Gw2cXFxgfl8jvPzc2xsbLgJ0KurK6f8M5kMut0uMpmMm7xknJyeMSdeqbS5MnM4HGJ7exuHh4crqzq5WtEHhOw1G3LkeFB+1NPVT9/YW6Bo67UgSMeNz9HwLRaLRPjSV26N4uaAagiBcat+v4/pdIqvf/3r2Nvbc9a/VCphMpmg0+mgUqngww8/xLvvvpuol3WRgW38Sq2xztgrKtLB0I2bbNHUIWutLy8vE0ZBGcS6aapEbBaMWnertBX9s27Skc+SvkSjFt1rv1hvOp1GtVp1J4UTPZO5NFVOlYeGQXgfr9OVPz09BZDcipXeCbNNrGHwGUrGsqMoeYivtkM35qJnZmlPGmqGkY6tKm22zSIq1jWZTBKn1bPffA+/WwWgikAVShRFCS/H8pL19kj78XjswgfcyG04HOLy8hLj8diFJfv9/sqe6cDN4ioeJsITptif6XSKy8tLh+RLpZJD2XEco1arodfrYWNjw6XjMYbbbrfR7/eRSqXQarXc+HMFNRcAaRhssVjg9PQUW1tbLpuEB6qQLkpTa1zVAFulbr0UW3yKXGWF79HvysPsv0XlDNcxI+dVaBu4RYpbiaWz3vV6HXfv3nU75DEMcufOHVSrVVxeXmKxWOD999/Hu+++u4I4rOtuEY6ialWkwI3rb9tpXVsiUIs0gZtB1AwGFkXa/J/v1fexHqWRz42zcVmWdDqNjz76CI8fP8bFxcWKIomiyB3ga5EracBcew0FaOxUJ+40BKDoXsMPijhU8RFhWeVmvQA7Hur6chJT6a3PsZ9cVav95jMaptEwlSpKNfxWcXIPEbafikr3LSF9dbx8aFHvUw9PkaHlE+XRs7MzhOFys61er4dOp+M8DQCJ09251S9RNscwjmN0u12X8cExZwjz9PQUYRgmMkw6nQ42NjZc+87Pz3F4eIhUarnPTD6fB7Dc/K1cLqPT6bjJOfKIzhUwnFIul7G3t4dPP/3U0eSdd95xoM56Pz5ZUhCgsrIOefMZ3ZZV5ZT3qTeq42TDrMo3/L/T6TivhAdsrCu3RnEDSbedHbpz546bNOHhwalUCpVKxW0Wde/ePWxtba3EagH/iR6+6+rGKMryCYUqe8ZWfcxi66SC4HMqsNZ90nAAi3WpfeESq9DjeBkv/Pjjj52LrooQgIvvKgrX36m47cpL7acyIguFm8/YvmiYhe2gm8y4uK7IU4SioQFN5wOQSJ2zyEbbrGEJjY3btirt1dDSa+A7KLQ6b6BxUB0fX1jDGieL/CxCU1Bix91mkzCrg/yazWaxubnpYsn0nkgH9aYGg4G7zonLVCqFcrns9g+hwiUCr1arWCyWW8HWajWk02lcXV3h6dOnbtdBHsLArSn4Pho5Im1VnKyfnkGv10MqlcLFxQVyuRzG4zFSqZTzwpnMUC6XE3xpU2WDIEgcsEI6V6tVJzc6lqSVVeK6iZxF8qxXiz7PTfQY5/59EeNmJzlZMZvNcHBwgOFwiB/96EfIZDIYj8c4Pz/HbDbD1dUVrq6u8M4776BcLicEUOuzytzGQa0gAUmUQ6bRkIlVHCrUPtdXQwU2bqmxYhs20XfpBJ/+5lOYhUIhsaBE92xR5cT0MSpFNUAqMGRQH2og7WymBOOauuiB46oGUOOnrIvoivQJgiCxtSkL07rUveUYMJ6ttPYpQkX91ttiP/ibIm+9d53B5m9E35Y3FdnTU+AWvlqPVfLq3VheYL2qxKrVKqIoQqlUwmKxcAttuB+QKl9OMhaLRXfaPACnTEkLjXUDcGGQVquVOKFpNpvh/Pzc3cs8bvJlv993/Vf6WF5kfTQkz549c+MUBAHOz88xHA6dB8BQUBzHKBQKeP/99x3C16L16zYWpCVPQVJ+tyl9vpg3P+135VEde2C53Uej0XDGxip5LbdGcTMOy43Zt7a2cOfOHTx79szNfD958sQF8e1xW+ykzhwDNwqm0+mgVCqtxAiVOIp4+L+1soqkfDFFVVIMj6hrpvFoIh8VSt6j6XK6j4YVZvaBil8NCO/VnFZ1udXwKNrW+3xomQpH0SKv83lmEHQ6HafsWD9/o1CowbIuLJUFMxh0q1Er0IpQ+L+dE1Ajo4LErCZNXeTkqPKCzSBQgVbkz3ppXNRAalhHQ0S6Hap6E+QBhpGIzkgXy+uMQ7NfW1tbGAwGWCwWbs/6MAzx7NkzTCYTNBoNF7fmohadV5hMJs7jCsPlnAlDa4zjc9yKxaILhWj40MqKTvCz3WpobazZGikfiCCNSUeG9iaTCY6Pj7G9ve0OLPbVqfKk9VkjzfdrVopVsqqUrZ5hPRbIcZKY+u3WI+50Ou32HKlUKvj617/uJq54KCsZmPGfTCaDjY0NN5ts4038S6VS+OEPf4jRaIRvfetbK8rVV5Rx1hXrBrEu3VOFA6sDpBOYZN51YQAguWpTEYhVsmyzhm7YTst8ykyWeakQuEKQbSY9+Q7frLe+h5kAfEZRFcdFFbX2mW1Wlx+A25uF9/E0HzuhbL0ai8h5jyoVut4aclFvge2yyEqNl6bn8Xddearv1vGg4lN+4+SpjimARI4vhR24WVlreVo31uI75vM5Op2OWyl5dXXljFYul0tslKZpsETkk8nExcLZPxonhj50LoSyQDqwPo6d5Vc1fkT69tATncxm3zqdDlKplJuoZMw8jmM8f/4c4/EY77333kqYj58q92o4eU29SjWobLfylYax+LvlF5V3u7hPIwO+cisUN4V2Pp9ja2vLrbQaDAYoFosOcV5cXDiFzb0KdDZZlQQJ0mw28ezZM7ePAg/BVSKpMreoT9tolYwiWa1HBUoZQ4uuRGNRxaenmtgwhA6+nURR900ZRT0RRT8W7WrYQhE0sKrIbKYF35tKpRKKnWPLtnCTfkVTNM6sSzf6Yt/4brZD0aYiYqWTby8PnwDpmClNSF81Avy0PEMPYp3B17qsZ6deE9up7eN1rmwk/dTTJBjQRWbclIpeyuPHj9Fut91+90TGrIthDI6B0pMInlkmDP8w1l+r1TCfz9Hr9VaUMo056yZg0awclRUFQ6lUCjs7O+j1em4BELOgWBef4YSpTgxb+VG6chx8Y0OPibntTHGcz+duEzsaAdJex94CBeU568XqmK+Lh2u5FYp7sVjmgx4cHODu3bvOmt+/fx/Pnz93gl4sFvHo0SNUKhV0Oh23HaWiHApzv9/H8fExRqMRvvOd77iJLzsJZZW2ElgZyLqjVqmo0EdR5EIgZGobgiBj6eCxXsY6OfA2Nm2NAdEZ49oamrAupTKxoioAiSXl9h7GQXk/ER6RiGaAWFroUnhgdZWoje+rYtXJST3Sy6IgK/T6brtcW0NAdsx9bq96LWG4un0AEZOGWVRR8X+muOkY6J41aqAssOB1ngdp+8z7uJGWz0MDlpOUnCxkJgfDCfV6HcPhEN1uN0Ejjq+GN8gD3LqVKJj3M5TAeQ2VAZunrsbT8ioB0nA4RC6Xw2g0cptfcX5DjWUmk0G/33deDOmwWCzPnCV9bFhUvTLlB017vLi4wPHxMYbDIbLZrItH12o11Ov1FQOhPK3v4qfOHTF7xgcafeVWKG4A2NzcxNtvv43JZILJZOIOJuV2kIvFAh9++CFKpRK63a47fZpKQCepXr58iadPn6LT6aBcLuODDz5wp3sAyYkctYgq9BZF6sSnWmcfIuQzei/RgLqsWlS4qGRsGMMqNwqRMoSGI7T9KjTAqpufyWRQrVa9+04Dyf21uQkRd6wjHXUCV109IkbrGakxZDtYVEHzN4to9HfSg+EF0oUuPNtgDZ/SSkNIqliUlnEcu42xlJdoJGxsFriZFCdwsApF+0CF6DvpiTz2qsUZ6ilY5JbNZvHo0SNMJhOcnp4ilUrh7bffBgC8ePECm5ubODw8xGeffeYWDSnv0GCMRiPn2lM2R6MR6vW6y/cmD7PNapx0LHQuwhptfmeYpFQqAUAi5q6nA2UyGbfgiXTX59vtNo6Pj50u2N7edp7daDRCv993ht7yy3g8dsv3KQ8c/8vLS9y5cwebm5uJVFjlaZ9MqaFQpf1VyldS3EEQfAmgB2ABYB7H8R8KgmATwH8J4C0AXwL483Ect4Jli/8jAH8WwBDA/zyO43/6mvqRyWTw+PFjxHGMg4MDnJ+fuwEKgsDNiL948QIXFxeo1+vI5/Not9sIggC9Xg9HR0fI5/Po9/sJZENiWMIo0rMuoX73udVkStZrXXLdG4QDo+ECqxzUjdSihsQicIsM9ZqdgNM+KHOp4lksFtjd3cXJyYlrt06SUBn0+330+/2EArZoQ91kLtmm8uZSaxsWsLF4uqoa4+VvROJ2QYMaEtJNvRfWQcG9uLhITCJZg63vDIIAhUIB/X5/xejbcfV5RkSy2jblKXX51xUbO7XjrzFZ/lHBzWYzdLtdB2iOj4/damSuogSAe/fuYTgcuiXojFkvFsudAxluZKiCR95xq2Uq0bOzs5WdAJWfrfenPKb8ybZzrOl9c1GRjrnOF7Au0nSxWODp06fIZrMolUooFArOY2BbGU4F4A5gYdKEbpnBCVga0pcvX2IymWB/f38FBNrxpD6w/KHtfV357SDuPxnH8aX8/1cA/P04jv9qEAR/5fr/vwzgzwB4dP33bQB//fpzbYmiCK1WC8PhEDs7OxiNRuh0OhgOhwkX9eXLly5diQz1+eefI4oiNJtNTCYTl/zP+NvDhw/d0WhAcv8ORbAs3NFNERYFTQeCg6eIgYgKSCp8q9TUgKgBoFIFkqegWATiQyaq2Hidk7g8nUZj1DYswTHo9XqJ+Lreb+PH1pWna6ztSqfTibipMrGGV+I4doKosWsKnCo4696yWBSs4Rm2i20litIxtghf6+N7Nc+X9NGVbkTe2i9FrOQTVVzsQxguszL6/X7C0PpitPzNLuPX+oIgcGmBHIdOp4OTkxPUajWUy2VcXFy4MZ/P5+74slKphFKp5PiC4z+ZTFw/qMjv37+Ply9fYjQaOSXL92koTmnEMVEeowHl2PEa+ZYrMVOplEt1pPKMosglLrDwPXq4NUMSNGYnJyfutJ1CoYAoitwGWN1u19H/6urKgTMi+8lkglqtBmCp5Dc2NlYmh5XfyTOqTyy/qcf0qvI7CZX8OQB/4vr7L2F5+vtfvr7+N+Ml93wvCIJaEAT7cRyfrKsojpd7jRQKBWxtbblN0zOZjNsEiDFtTkyk02lcXFw4a0/mJZMXCgU8evQIDx8+TCgDH5pWgqnSYttsmAJI7jdNBKExZhUeH4LSa+oq8p3rwiksGqLRCR6+k2jZphXZGJrSg8xvQzI+46YegmUyRU9arOfDMeY15pUzh1W3ubW0UKZnf5XeljbAzYQwx6fT6bh2+caMSkXHRu/XMIcqI80wYtEFMTxA9+rqyoVdSGOm2dELpYJiZgW9OvaPaNPGerW+8/Nzp6w5uTgcDlEoFFwYiQtkqMSKxaIDUOwz88e5rD2fz7u9Rg4PD/Hxxx8jlUo5paa0Uhpopgrprh6i9XyUT/mpylhl1IYi9B71xFjP9va2C/swFY8prAxvAsvwDMM9k8nEzfmMx2O8/fbbyGazK7v66ToDi/6tTlCaKD+tK19VcccA/r9BEMQA/tM4jn8RwK4o41MAu9ff7wB4Ic8eXV9LKO4gCL4L4LvX3zGfz7G/v+8aXCwWEUWRyy5RZfLWW2/h8vISrVbLdZKTBGSiUqnkGFUtHAeEBwergmZdlknspzKJujxAEinzGYs0HFEFYev7ravF53V3NkVpfP5VgqBMqNcBJDwYvk/rs2EBKix6GHaCkPfpe0kzRaIsqvQ4PmoQNHbO//W7GmxVErZOzeJhuxQB6cHEjEkzvKX8p2OrvEEvjOPE+ClpxHfWajW8++67+N73vpc4SMJ6Uer5cYy0LcCNchgOh+5QhEKh4Og8mUycx3V0dOR4s1gsYm9vD4PBAI1GA7PZzK0SBID9/X2Mx2O3apDZGowHE4FzH6FareYWfhEwKF+qDGisn+Nnt4SwfK60VoVsY8o2lKTP06hyjIDlPizlchlBEKDT6bgdB4EbtK88xPro0Xc6HTx79gxbW1vY3t5eyVhT469oWvnMhuq+SvmqivuPxXH8MgiCHQB/NwiCT/THOI7ja6X+lcu18v/F68bHYbjMu+SmQ5wk4J7SRAYHBweoVCo4OjrC3t4eyuUyptMpKpWK28OgXC479Hj9LifYURTh4uICqVRqRXGTqDrwOkOvsWV1waloVMGwLiIQZiEQYeo+EPpOVXjW+uqsvp3oVKXic7PWhRTYFjUYiuYsStaQCYUwm826E8G1zWoslU4AEnm5RC/sxzolrb/rpKKiNA2RsH96sgmVsT1ggbyi422zWCj8ivStYtFx5H2kF4X64uIisZmQNdZqxHWvc463GkjWOxqN3KG8X/va15zCuLq6wnw+x+bmpgvBkEaFQgGDwQCnp6d46623sL297TYSy+fz2NzcdCFIZs3YrWqjKHJL4guFgksu4Hs0HGIRpXrByrNaP2VDc8k17KXjQOWo48DfSWce7JDJZNyE7HQ6xZ07dzCdTl1Kp46p9bQ1Jz0IAlxdXSGVSrmdEPWd5FtF/SobLBaRv658JcUdx/HL68/zIAj+FoCfBXAWXIdAgiDYB3B+fftLAHfl8cPra2tLEARoNBoIwxD9ft+5LNxfgfsM7OzsYH9/H6enp/joo49QKpVcvKtUKrl9u2ezmdsB7d69e46Y8/nc7fF99+7dhButBCPBbdxQLaYqUe2HKioWKppYQjEs9l06QacuI9OZeECyjfv6XETWq223xzPps/RcrMKmILEuzd2lMvYhBkXN7IMqXEX3OpGsKN56QEon/q7vs+iVfaYS9t3jQzz6XjVARKsM41iPROvRvquyZRzYegk2Lqzvp9HgYrVWq4VcLofd3V08fvzY8TXT/XZ2dpDNZlGr1dyE22w2Q6/Xc+mZz549w+XlJfL5PN566y3XFiLmbrfrvBCmrLE/bGc2m3VJAdyWVMNL+ml5QpWtepZKa1/aoFXYykvKm6xLQQFpz9N42u02FouFQ9qj0SjBVyof9BT0QGgq7MlkgmfPniGOY5cmyf3GlXdtuEQRvAI3a5xtea3iDoKgBCCM47h3/f1/AOD/CODXAPwCgL96/fmr14/8GoB/JwiCX8ZyUrITvyK+DcDNbB8dHbnOZTIZfPjhhyiXy074uCcJEXUYhi63stFoOEvabrdxdnaGg4MD59oxhtdut90m7tatsrFiZSASH1jN/1ZFyMJYMRWWr/DdPneJiI/u6LNnz3B6eorhcIg/+Sf/pDsolQxkFYjP5SITq1FhuIAxSVXmunJPlSmfUfdPF7io++pz/6w3oe6jhnTUdVYaqUHV7xovVzfaLvax7dL36zUWFbrFYpFIPVWXXo2F1qXvoOBbFG69OOYJc1Ls3r17+OyzzwAsd/ObTCYYjUbodrvo9XqJkMbl5aU7g5FHAc7nczQaDef+c16oUCi4vbTDMMTx8bHby2Q4HGJrayuRRWQ9J4YiW62WC+eoMvahSqJnnZew3qoNd9h5Gp9McpMm7uFun+W9PLOSKYBBsNw8S+chbIYPZURBDGVvOp3iwYMHLn05nU6j2+1iMBigXq+7bTyU/0gLnpfJOb7JZILNzU2X+riufBXEvQvgb113Og3g/xHH8d8JguCfAPiVIAj+EoBnAP789f1/G8tUwM+xTAf8i697AZcKT6dTZ7XJ3O122+27y8Hq9Xp48uQJNjc38fLlS7dZzb179/DkyRO8ePEC6XTabQd7dXWFnZ0dvHz50hHw5cuXKBaLqFarCUKq4KqCtkpeQwYsPrfPZrEAWGFQy4Sc8X78+DEuLy9xdnbm6h6Px2i1WigWi24mXNukbdR2AcmVjlahqvCoItIVjGy77tqnyEjDFEoDdQ+tsuR3In0qFi3r3EtLNwoblTwnfPguq0gtcvO9Sz85hprFoajQhjOsgdfxUSWxvb2Nq6srZDIZPHz4EJ9//jmAJQojQvzxj3/s6uW+6RyLi4sLlznCyczZbIbnz59jf38fm5ubbjn63t4ehsMh+v2+S9/b3NxEp9PBYDBw48CQwYMHD7C1tYXj42M3UWnj0xpaIo+oIiYCtp6JHQf9rp6n/V35nXIYBOtTRzmm3FeehkYXUXHc+MfxVJ5Tj1rb0u/38fLlS7dnPecABoMBer0eHjx4gI2NjZW+EpTR8NIz7Ha7qNfrXvDF8lrFHcfxFwC+4bl+BeBf8VyPAfzbr6tXy3Q6xenpKabTKYrFImazGba2ttDr9RyTbWxsOGS+WCxX0T1+/NgxUxQt05YKhQI6nQ4ajQaGw6E7m5KncjAFKp1O48GDB/ja176WQD3WlVOEZgVQ7+F1DiwRKxUZC+tPpVKJmXG6emS8s7MzPHv2DMPhEOVyGa1WC3t7e7i4uMAnn3yCo6MjzGYz/LE/9sfcSlNtlx42qv3RPF/Sni6vnUCxzwPA6ekpMpkMdnd3VzJC+A49bIKZEUo30ktzu+v1Oi4vLxPhF6WvxijXoWEqRKvIgeRqPZuqp/WtQ/N8l46j8oaOvd6r7avX6y474d69ezg5OXETizSOn3zyiVuyrifcWEPXbrcRRcv5mhcvXrhToejq1+t1nJyc4NmzZ1gsFtjY2HBIlAutuLEW5ymePXuGcrns8pn39vbQ7/ddlgkXtpB/iW5ptHmY79nZWWJs2Tc756GhKvbLypQaREXyGiJhYRKDVbbax3w+j1arlchY8iF9+6nyr/fRcLTbbXQ6HbfnDXmOhyPwzE6tMwxDlMtlNyFMz3AwGDg+WVduxcpJnr6Ry+Vccj+w7Pjh4SE+/fRTvHz5Eg8ePHAdLZVKOD8/d4zDwVTU8P3vf9+5eIztcWFPKpVCPp/HO++8k9hvQBXDuhiaxqmD4CZtSxV7GN5sV6puPpDcLlYtOH/nqtHhcIj5fO6W+8bxcm8J7pJXLpddvFXRDBUmGZYLF/T9WmhcqMBVATFfF4DbTvPBgwfOK1qH8tk/Km3W5Svz+dwdlWVj3aS3omZVinyXVcIa2uG7Nf7p86TUaOm4WIEFbsJFbBvbDCxdceZjEzlxW116FZ999plrn54rqhNsDGtx8phpmGdnZ/j4448TKZl6dibRcrFYxOnpKZ4/f467d++6NMAvv/wSURRhf38f9Xodm5ubODg4wA9/+EMX157NZjg6OkrwE1E1M6e4qZV6Idvb2xiPx7i6unL8Ta+H/Mg6NXasabgWsXOsbVjEKlD+xpN6aBBpKLhknt489YT1Bi0Ps15fyqIWbRd1CfccXyxuDtFgrDwMQ7dbIXPg2VbyybpyKxQ3FR0nVJrNJgaDAUajEY6Pj90EAuN6Z2dnKBQKK4RShMWl8qpQeN4fGRGAW5HV6XSwvb2dCIFY11bdblVoNp5nkZoWn5KzFp5tymazTvECwOXlJQqFAvb29vDFF1/g29/+thNqXfxCBU/hV4XD96mC1HZbJRhFkTuX8LPPPsN0OnWnb3P7STIbx8OmgqmBsjRl0bGjkVRh0fpUUVojpKiMhd9Zly/EBdzssKeCbN/Juhn/39vbQ6vVQjqdxuHhIb788kun4OI4dmEuhgJtCEXbrzRgOKTZbOLFixduj+xms+mEnEpwb2/PKfFqterQX6FQcHVdXV0ldrILgsBtBhWGoZucowdGRExDHgSBkznNwU6n0w4sAUuDWavV3B4oaojYR8oSDRNDImybDVsq3yr9FH0rT9jMEypRyqzuqcJ3Ku3tO3TcfWEY4Gbls4bUmCLIzLeXL186DzoMQ7cjKj0BghyGtRT02HIrFHcmk8GjR4+cu8ZFANwshgT8/PPP8eWXXyKVSjklrvFX7tgVRZE70oyE5Iw9UQJjbp1OB19++aWb7LMrEBU1aPxL3XYVPs3j1FQuYHVSjgpK0Tjdrn6/j/v376Pf7+PFixduD4Z6vY5+v4+HDx8m9hYnU9o4tq4E1ZCQRTxsmzJgFEU4OjrCD37wA6fUDg8P3QRMEATOA1CXmHRgO7TvvgkrFVq9X5UlhZ0KU9E5++BD2Gqk1BX3vZ+pgmyn8k+1WkUqlUK/38f+/r4DBkSa4/EYjx8/BgA30WvHQt+t7jdpYz2bTCaDzz//3IUqCoUCLi4uEATLDau2trYAwC3h5qKZMAzd8noq1rOzMywWC7df9mQyQavVQrfbxf7+vlOy3KdjPB4nVt5qzFm9F4YG9vf3HT15YIE13KSvKmwbk7Z8w+++cIYCEzXOHCfldaYB7uzs4IsvvsB4PHa8xFWjOjfBokZcQ2w6ZppaSt2yWCxXlVYqFZycnDhl3Ov1cH5+jlQq5VaGM6xZLpdRqVRc1gvDwL5yKxQ3Z9GfPHmCbreLdDrtOkVLDywFolwuYzAYJJauMsY2Ho/RbrcB3ExupNNpF9/iBA6wVNCnp6e4vLxEtVrFo0ePACTPjmOKji/UoZ98DrhhVu7wp0UVh938KIoit8R2e3vbZQRwv4hGo+E2wx+Px27PctsWG5OjYCk60TYzp5n/kwFnsxkGgwF+8pOfJE5a73a7aLfb2N3dRafTQbFYdCmYikLU8CkCsrSislfFS/SmOdcazuFzikoo0D5lzfcx7mpDVORBhgG2t7fRbDZRLpdRr9dxfHzsvJ7pdIrnz5+7uieTSeIQXPZfw2bsu07a8vgu3sP6FouFW+3IHSRLpRI2NjZcXUEQYGdnB+l0Gufn5xgMBiiVSrh//35i0Y72X59loeLjSTFUIHTx2V/+pgZosVi4jBLGcjOZDC4uLhJjpN4TkwFOT08dILNhKgIM5Wmf0dP+2fkNLkDStD0CQQUEd+7ccXu3aDyZ/MGTaDhvQOSu+egsbCuN7GQywfn5OYrFIk5OTrBYLLC5uemA1GKxQK/XQxAEzsjev38f9XrdZZm8qtwKxT0ajfCjH/0osZQXuImt8RTqKIqws7PjFMlnn32WsJRcNNButxMWmKlVw+EQo9HIbV1J4vP0HXXV1a1VpMxiY6hqEOgWa9EQS7PZxMXFBXZ2dlCr1Rxi++EPf4h6vY633nrLuai7u7soFArY2NjAYDBw6JvbW2q4AbiZ0beun42r0zhxb4ooWm5ET8T0/PlzfPnll2i1WojjGPv7+6hUKphOpzg+PsZgMEChUMC3v/1td1wUBVVXm5GeNsTBokpWJyZJKyo87R9pqYKp3hHj44re+V4qIQoYUdD+/r6b4efeHZPJxAEBjqEqEX4nL5F3+X7yBLM9ALhtHIhot7a2cHJyktgciZNVi8UClUoFu7u7aDQabvXiycmJQ8YMm/AkGwBuJSPncSg/HBvSjwkAutJTQRNTcHXPbvaNi+PIU5xYBpI5yaQ555lyuZwDYjo/oJO9NBz0vC0KVn4KgsAZQfVYrGfJeprNphs/ei/q1es8ShRF2Nrawnw+d2daEglr25U/mRWXSqUwGAxwfHyMIAjcviiVSgXFYtF5NXr4RbPZdOcPMLVyXbkVipvIBUgm6BcKBdy9e9flk47HY3dfPp93EzLAEsF87Wtfw8bGBn7rt37LpVLRxaZVI7OpMNfrdYf4VOCBG8XCyRk+a2OvREsWySmimM1mePHiBT7//HMUCgXUajUX4uj3+zg/P3d5pblcDqenpygUCnj77bfdpNP+/j6ePn2Kp0+f4uHDh44J2G66f4o4GWLQfUgY1+x2u044f/zjHyMMQ3zjG99Aq9XC6empQx5c7qyTpURY1WrVCamuBFUaWs+A96gLzeKLXfM6Bda3otIqdEXq29vbTgHt7e3h5cuXznsB4HaHA27CTmr82A+N15I3NK5JL0rPDFR3ej6fJ477Oj09TaB+3ru5uenGrdlsYn9/H1tbW06onz175niRe4bM58uN/qfTKcrlMmq1mpsYY/bK3t4eSqUSnj9/7uZByK+ZTAaNRgPPnz93ipoKinxNHt/Z2XH54ABcloaG3+yqTyp49pUHpmj9Gq7j2GodRP5xHDv5t6EzBQgaMtRVnKPRCIPBAPl8PgHC2Ec+y03tKF/MteZvyg8Mu2gywOXl5QoAvHv3ruPNJ0+eOD3FMwQAJI5Y85VbobiBmwEi8k2n024LyXQ67U55Z1yOxCGDNRoNtx8uEWSz2XT3MDRRrVbdidIkOK0kUS6QTEOymSS+QuKzrJsA49l+i8UC//Sf/lPk83m8//77zp27urpCv993bnK5XMZiscDBwYGL39Mt1Xeo98BcXnXNdUEQP5vNJr788kuUy2W0222cnJwk0BBpcHBwgEKhgGfPniGfz7u8+16vh9PTU9y5c8fRkUVj6hofZXaMTq6psFu3mIXhLqI5RTw2NHHv3j1cXV251XztdtulWEVR5Fa4acaBtoPfFdVxTDXMQyWgz7Cd5XLZKW/uI0JFq6fXaO4zsFRoPAUqn8/j4uICV1dX+PTTT93eO6Q9T4M6PDxEKpVyxog7BqZSKYcwwzB02wzwOSpd9oH7UevBzHpYrk4adrvdxOQ0jTNppoaPcqTG2s7J2A251AhoeEv/bzQabgGSGge2k5kp+XzenTc7GAxQqVRQKpXcQcWqgO0c19nZmTNA0+kUR0dHrg+qr9hX33yKGpJUKuVWfHM3VM6VAHDGzK6FsOVWKG7tWBiGbuOX+XyOJ0+eOKsXx7E7K4+uBoUql8vh5OTE7XDG7TdpZcfjccL90om6druNx48f46233nLWVcMKNkzCtmoMzioaDnS320WlUnHCxFAJADdRMxwOHSKk26s75J2dnWE6nbrc32fPnuGP/JE/4lCwzqRzQyFf0X7MZjOcnZ2h2Wzi+fPnePr0qTslmwqKOfX9fh8XFxduX2YaTa7wYm43FbiGa5QeOtPPa9pWjYuyvTppy1AaT7wvlUool8s4Pz93J6IwFY07tzEPWVGyrlDkGLCtXFPAvqirr96YReLa5mw2i52dHbz99tsIggBPnjzBy5cvXRaHokTWrxNc5XIZ6XQ6ETNuNpt4+vSpy0QgXWjEB4MBarWaO+GcG//TwOdyORweHqLf7+PLL79EOp1Go9FAvV7H06dP0e123XuoWNWT01BGFEVuawpmPZGu6hVpfJ19VYVKuhMwqUxZ1OwzoDzU2IY52NZ6ve7Cf1xtzclWgjGdQ1FPXHlSw0TsK/lX9QF5SnWGelM0InwXTx0ajUaJdOJKpbKSDmnLrVDcwI0bWqvV8PDhQwBwbgYT63u9XuL0aBVGTgAQWRBFE8Xp0Vvq3qRSKZyfnyOdTmN3d9chwnUxWQq4JaoqGWAZ53vy5AnOzs6wt7eHarWKwWCATz/91MWD+Y7Ly0vU63UXsuFeK7rXcqPRwIsXL3B+fu52bhsOh6hWq96UPw1NsD+kD40KkfmTJ0+cschms3j58iWeP3/uUHez2XTGjgdXAMud1a6urtDtdnF4eJgQIN6jsX+ln84pEHVRUVCYoihCpVLBeDxGoVBwG1nRCxkOh27C9vz83L2XSkSFUkNWQFIg+X8cL9cBNJtN1Go1d6oL3XOGQqw3RbeWx4oVCgXcuXMHH330kes/F2cQbLD/5AHdKheAAxCNRsMZ7o8//tiNEZdEz+dzHB8fu7qr1aob10Kh4BbJ0OiSHtzVLwgCd4SZIkYLRkgfhkAIKsj3aoxJK+W9ILg5hILjoZ4OjZHWR35VA8fnoihyi4joSWjGShAE7rDg4XCIly9fuklLAM6T50IX0pUnOylf+IoNhQLJs1UZp4/j2PEFjTHj6wxp5XI5J1u6WvZVXv6tUtzZbNYtKCmVSmg0Gjg5OUG5XMbBwQEymQy+/PJLNznAjuXzeWxsbLjVkXSheLQZJ4JIUFpp1kH3FYBbdalMp+jBruxj4UDOZjMMh0McHR3hpz/9qZuYGgwG6Ha7Lj6min4ymbhJx/39fTfTzUmg7e1tbGxsIJvNuh3bLi8vXQoYsPQ4bOzdh3qJbLi45/Dw0G0RQCV5enrqEEAqlXLzAsDNhHE6nXbxuHw+jw8//NApJCB5rqQaWCsIpC1pkk6n3SrZbrfrFk1QSUdRhLOzM1cfP4nCFSHrGPJd1ktShUPFxaPzODmo+0xwIlQzejgZpudjcpc8yytUKr6Te/gOPtNutxP0pBFXQ6coOJfLJerl1siFQsEplP39fZTLZRwdHaHVauH4+DixYMh6lwxZqDFmOIay4xtXpTH7x6wOpaEaUDX27IMicOvlULHTIPhi3XwPaUFjw1ASaaeGTUM1rM/G3tUb532kM7NQCCK5fzfTNRl+4bYENPw8gFlXVK8rt0Jxc1C2traQzWbR7XbRbDbdTPGDBw9QrVbx5MkTF07QuBtXJ1EhEyFqSh73GqbrrBM777//Pu7du+f+Z3uoZJn2pAOlbWch8nvy5AmOjo4wnU6Ry+XcvhA255TPLxYLd/DxixcvHIPMZjO3jJiIKJvNugUx9Cy4KEdDR3aCkPG68Xjs8nY5F8C9mOfzOXK5nDvCSmP2nOQiQ3OVHpFir9dzKWt8vxad3FW0YjNCdNc94Ob8TdZpFTINsC7k4AQfY8i+0Av/Zx0nJyeoVqtoNpsuXMWcbV+IROuZz+duI316MvRYcrkczs7OEimsOi6+NgHLTJXnz5+j2WwmUtLIt2w7J7UYpy0Wi06hdbtd7O7u4urqCvV63YXScrmcC6twnx/SSBWx9VL0d6J6GzK0bdRQgaWhonv1tpi2q4ZZ+Viv6zayvklttmE4HLpMH8aYeZhFq9VyISXylvbdZiitM1RqDIj+mSWiYGk8HmNvb8+F/waDgXtGVyO/qtwKxQ0sB6TX67kDaDlZl06ncXZ2hhcvXrhVaLyfqCIIlrPVHDTGwEejEUqlEqrVqhMsTnRmMhm3TWy1WsXl5aWbAH3w4AEmkwm+/PJL7O/vO1dMXTwqUaIttv/s7Mwp7TAMUalUcH5+7uKsKrjWjeRkEFF6Pp/HdDrFs2fPAMDFx/WdV1dX7hBlO9mnZbFYuNQkbhrUbrdddghn+ykAuh96KpVCtVp1E4PMvnj33Xdd5gnT03zCSaWgfWcYS8MbABJhHxviUIRM5KmuMQ258o6ukGX/ACTc9E6ng4uLC/T7fYfueR4jBff/396bxkiaZddh50UukZFr5FaZlbV3d3X3zHRDPUPCGsIEYZiiLBKGRj8EQQMDGssE5odpmSYMGCQMWPA/GTAsjwCD0NiyTBoCJZsmTYIQRcijAfiHM8OZlmZ6uqurK2vrXCKXyC1yqdwiPv+IOC9PnHxfVDU5w8psxAMCEfEtb7nvvnvPu++++1RZqP2R+dTr9WjSo52dApECUhEkky5w0i/96OgIH3/8cTT/sO6cNarJr7e3t20bNzdtcAa2tLQUBene3l4MGcETcAYGBuKagM9OlJcciWt/8FkKYlXaauJQXtRyuBjK3757VWe5XMvh+1TM5Aei5SzL4phSRD04ONi2jra+vg6guSjIMazCWdG38qSab1gXhtJQhE4/f95vNBoxdjpBD/uXa2HKL3npQghuDjif7rDxRN/O+Bys1FicvpF49FyoVqtYXl6OeTJe7vT0NKrVavS5bDSaftNbW1sxT92c4gslfpbdvXv3UK1W446zg4OD6FfOQc16u4CjjZJ2skKhEKdYCwsL8ZnT09PoBsUdjHw+tRJdKBSwtraGH/zgB9E+XS6XYzwUnlxCNMApHxd2yMT097116xa2t7dRq9Xw4YcfRsY8PW1GlKMiBRBnL4qY3ROG00k181Ag8x1fuPL2sV99YLtZRAcVhQEX5YiwOcD39vZw7do1ZFnTY4k2ap9tuWmKgpVKgDMVClugHWl60pnCtWvXUK/Xo8mEm2I4TsgTQHss8v7+/jg2OOPkDGtrawvPnj2LU3K32btZhO302Rv7VV3+yHs6Tlz4qJLWPmVANhXYilxpG04llq8CV0GWmusYzrZarcazaYF232+2kbzl7XDTHz/sfzVlHR8fY3x8PLrMPnr0KM4SeIg10f/MzAyq1WrbYnleuhCCGzi/G5EdkWVZ3MarxONihp7qATRNIlmWxU0Ru7u7bSYKarWTk5N4+DDdb4rFIjY2NjA/P4++vj7cuXMnLgKpINCFto2NjTjdXFhYwOHhIW7evBm9RXiCiNp7VfizzY5aOHWjEODzFOj8T7u3Ci+tb71ej3Y1+mNzMHOaTWGVZVkcQPv7+21Bemh35LoAkR53zS0uLuLOnTtxoYUzHqJWCjSdkis93Z6pyQc4BxPpqV4WRPjqz+5IkAgsy5qLkZyucuOL9snR0RHee++9GMdGEbuaebTvVEFr9LxUm1SBa6yKmzdvIoTmrjq6BtIVkKCCtGK9QggYGRnB9PR09Num2aher8cwyBRWulipqFKTzjaUfs5jKszcnKACkHmosFOe57NUwEpL8r8qFS2HirS3t3k8HE2qDK6lAlHNpfyvaxTKrynziI4JtpEfzpz4Dk2KVMCcURNAUFGrV1lqd6amCyG4tQGKvHTAK7MMDAzglVdeaYuwRv9tHvSpbkI82HRnZ6fNQ4AdSc8EAPjoo49iZ6utjYLi+PgYCwsLMYj92tpajEdAE8z09HT0xV5YWIhtANIxNZSZiTiI1BQBUZDzf09PD+bm5mKscraXUy91MWs0mmFFWf/d3d24eq0mBgr6LMsiPTkboBKZmJhApVJBo9GIC4nb29vR/ZEbixwl6+YJZXrSQwUf39V3FIm5TXZsbAzb29vn7qtgU1eunp7myUm7u7vY2NhoU/4cbFxLmJubQ39/fwzNyb7UTU155in3ZWa/uRBU00SWZZiZmYlusADa7O4qJCnM1e5NUwNNWD09PdFDaXJysm07te545ZjwevF9XeNQZeECxvtVr2s9eY3moNPT08j3riQpA5SOakvXxA13Y2NjKBaL0buEeSm/sRxXXMpDyku8x7zIDzTFZlnWtgP8+Pg4uihzp6bOSLhISXmh6yAX3lSi2k07BTg7e5JO9mSuhYWFc6vHFGxEHq+99loUYgxRSW1GZqAfLB3iQ2gu8HBRUPNvNBrY3d3FBx98gIODg3hGXa1WazM1MAqYanQqEu00ZTplSJp/+N7o6GhsK1FhX18frl+/jp2dHbz77ruYnJzEjRs3sLe3hwcPHmBiYgI3btyIgdk5IGjf9EUlCm4VbjwVnQtj3A5Nc0qWNX25q9Uqtre3sbTUPKHu1q1b2NjYwPT0dAyE5HZP7WMKDk4xfXCSbqSn0o2DQ9GY2oU1f+bBmQI9R7iuwkGYZRnGxsaisr927Vo8iBdANIFp/bTvGo0zn3VNvM/B6vf4rbtgucNwbW0Ny8vLMVwq8/GIgzQDkBfJb/SUIVhRWvOb+fJDtM0Pn6HS1WspWrtCU4HtJhnSTWeD7HfdKMRxzn52PmZ7yPdsryJnR/HaBkX2PktUOnNWNzQ0hNPTZpx/2rIfPXqEer0eg6/xwOajo6Pocgggji0qE9/M1CldGMGtA5KdCiAONCUy7ak6TWk0zvw6Geh/ZmYGWZbh/v37EUVzyqJas1QqYXh4GMvLy7EujMTG3ZicCTx8+BBPnjyJsQSIFLRTHz582CaYFWX4FJLtB84H6ucWZLoLcZfYyMgIxsbGoq+xDoJqtYpqtRqR2Pr6evTTpj2STMkyKLBZB+alrmUA4mIpd6DSzQpoopcnT57E/smyLCo+tie1Q7ETTXSmozRSG3aj0YxgeP369XgakCI0HdxU1Ovr68iyLB5MTRu3mlwODg5iH/PIuM9+9rPxEIKRkZG2OrJuek3PpvQ28ZvrIWpjdb7mYhr9gjkLoY+28h9BCZPODmhyo2JTIcZnOSN0RK2zYIInfV/bqKYh3XSVEpRZdratXnlCXe90bKhQdeHvilLjv/B55T9/Xv/n1VfrMDQ0hHK5jP7+/hhOl6fX1Go1lEol3Lp1C7u7u9HLiAuWnC0pf2s5vlbl6UIIbmVW/gfap1Z+P6WRSIC+vj5sbW3hO9/5TvSpJXoZHx/H6elpXHjjwOb0hkxHm6cKooODg7gKrUJNGcGRpA5CdXHS5zXplJkbOegJs7Ozg2KxiPHx8RiL4rXXXou+p6wfF8W2trbw4MGDaBPf2dmJm3wYPEnrz6BCXBeg7ZfnEjJy47Vr1zA5OYn3338f9+7dw5UrV6I3Rm9vLyqVSqwj295oNNoWjh2R6myEfawLTEoXRXTb29tYXl6O7lVEOKkF26OjI1QqlRhxkfXlNBloP8WbfcwZFcObKkKn2UPrrYjUFRMFG+kCoM0bgnk4jxeLRUxOTmJ5eRkHBwdx8ZuCi/mTV5mfmtkoELVeilb147MaH5N8x5WNXue7aifnfeV1N5toPsoHyjeu1MkPbnpkSs0ulZ9cnqi3kr7PNDIyEl19CWjUG45HlXEWcXrajJGjedGs60pKgWteuhCCGzgvxFwru8bL0+K0OZZKJSwuLkbUOjY2hp2dHaytrcUByDyy7OzUDC4ezM7O4vXXX29THCsrK6hUKm1bdpnUjqgM46YRXdDitw98Co69vT08fvwYvb292NzcbBMI3Np+7dq1KCzm5+extLSEYrGIp0+f4tmzZygWiygWi9H+W6vV2nxF9XSZoaGhGP1Mo5yNjIyg0TiL5cLzCemR4zsQueBFLxNe16Bgipi8zxmjRhcLtf856GifZgjNO3futE3zHW1vbGxgfX09HtDK/uECKn39yQ/0OKFnA90GT05OUKlUMDc3F3lGUSlnAnpkG78pFCmAiOqdv4Gzk2G4AM5AWORVReoqrFkHrYsKXKU368IyU2sTrjS1r105pcakj2XySMo+nRJazEP70xW9gwDdIOWKJaUwtB4sg7RgP2h7GC9peHg4rqHx6ETOgui5QzNJuVyOMWKWlpbiBjuGKNC6+WzAU2exfka4cgjht0MIH4YQ7oUQfiqEMBFC+NchhAet7/HWsyGE8I9CCPMhhB+EEL7wgmXECntH63Um1eAqgBuNRoy0R5RHhLK/v4+tra22WMBZlmFraysuttHL5OTkBNVqFQcHB1hYWIinyTuByaTsKLcHanvyEKUyu6IBLkytr69HpmWMESJ/oMloe3t7EUUXi8WIzIhAdaVcF0oVvZ6eNsNXDg8P4/bt2zg5OcGdO3ciSnv77bfRaDTiRp5CoRA9cSgIGaifDK3xodXDQ5GMT3nr9Xqb+xdppGsgXIXv7+/HjRs3sLm5GRfa3EQFNE0fDx8+jM8xPoTGXxkZGcHw8DCyLGvbLUrf34ODg6j0qABpm0zxckqokZZE+fRq8V15rP/R0VHs77W1tTibGh0djbNH2k2J3BUkqNmCqFX/sxzWh+9ofzC5MHHeJS/q1J/9Sd5WepDXU7MARdQ61pVOCoJcOQJnZhpvs9eP9ebmHG23AjS1dRNJb21tRUB4eHiI1dXVuFZ2eHiI+fl5bG1tIYQQ4wLNz8/HAFcqt1Q2uDLx9EKCG8DXAPyrLMveRPPg4HsAfhXAN7IsuwvgG63/APDzAO62Pl8F8OsvWEbbVM0Rgk4JVfv6lJLMTuFMNPPxxx/HI9AAxPMaAUTm4SAmOnv48CHW19fx4MGDuPGFqEZd0sjo3rEpJaT+qnxW26904LZvMk+WNRfNTk5OcPPmTbzxxhtR2Tx9+hS7u7uYnJzExsZGrMvm5mbbmYZq1uGuLiJ8RtC7e/cusqy5oLWxsRGR+/r6eoyudnh4iMPDwxiEvlgsxvje6+vr8YgtlkVhy5TyOOCnXq+3xU3WviWS5gaGiYkJXLt2Da+//npc+wDQJsSAs3NN6QNNZcs60WuDZaaCCT179izGoFhdXY3eCvxWe6/+Vq8o5RNtn9qlledp4uNmHApqKhLSg2Y4bupwMKPlMVqeI2PShXVWIelI0FGvjkvOePis26R1oVkFuvI+k8oElu/v8bf2u7qlOsLW5/mbdFS7uCbNR+l5cnISD7PQXd00ZZIfgSYAW11dbfOjJwDQlDIPn+ON3DtnFR4D8DMA/kmLcMdZlm0D+BKA32g99hsA/kbr95cA/GbWTN8CUA4hXO1Uhk+pSEz9OPFTyJb31e4YQoguOUoQokUXoPRioTvgu+++G+2hKV/XEEJcLGTYVW9PljUXobg1v6+vLy5MMNHUonWp1WoRRTIO89zcHCYmJvDqq6/GHZ306Dg+Po5hY9k+RfsqQDjQ3cwBAAsLC3H2QPc/HnXFWNHcKak+uEzFYhFzc3PRfU7NI9pmenUoKuKGIo2D4f2eZRmWlpZim7Msi/77KysrbYOSvuqLi4uxTYqg2N/0mGEUOV1EovLXrcncXbmxsRHNU0TmKpwpSJgcjKiZgs+qjZZCmsfZhRDi4ihDyPLIPu469O3iKpR7enripindccp7SmsFSjp2lKcUpKhAVHClm2AU/aZMNz4jVb5UvnXFpOUTDacOSGCeOo5pKqPSU1qpEmKgKI5VKlWgOaMjf9H1jxsHuemn0WhgYmICt2/fjhvVuGCpYzBlc/f0IjbuOwDWAfzTEMJfAvA9AL8MYCbLskrrmRUAM63f1wAsyPuLrWsVuYYQwlfRRORt2pRMpLY61z4+/fSkUz9uIeV7nLbVarW2/LW84+PjGCOCC12MdcwFEhKWsY11wU/bxHYNDg5GO7siBSb3Xx0cHMTIyAhWVlbiBoypqal4sAJnC8+ePcN7770Xbe/026UpgQtwrJOiWi6ycaddqVTC8fExtra2oq3/+vXrGBgYwHvvvReV1Pb2doxnwryJrm/evImRkRHMzc1FhMVoezwph5EPue365OQkLooy3gnzBdrdBznwPvOZz8TNUnfv3o0uiZVKBa+++mqb8KzVavG4LDWjsK/Zl6SVCjMOZnoQ6IaolZWVGCZ4dXU1BicjfyjgSCVVTD5bo6Lt6WnG52bsa4INCiXurp2ZmUGhUMDy8nIslwuztPcqj29ubraNB+VZFfYpftZndMz6FD/lUaL5pBbgVBHwGTc5KS/n0VRnqap4NK+enp6oGGluolkROA8oqfAdCDFPPahka2urLR/S4yd+4ifw5S9/Gb/yK7/SVh+nq9Pb04sI7l4AXwDw97Is+3YI4Ws4M4uwYlkIobM13VKWZV8H8HUAKBQKmU+JVZgD5wWh3+PCGjdNkCE57VMNzTJcy/EUEYZ7pImAge1pB9dNCHS508Hk9SwUzk7eYVwJrz8PV+B2fD3woVAoxNjX6+vreOedd+Ki4NOnT7GyshJtrYoo1Z6q00YdHBQynAkwbO7y8jJmZmYwNzeHk5MTTE9Px/pws83Y2Fh0JaTwnZ6extraWhws3LzDPtne3sbi4mLbdvidnZ14NNvIyAgAtKEc7Tf+5mG69PGfmJjAa6+9htnZ2XhqDFf+j4+P4+Is6aJJET7pp5tOuMGJsW5WVlZQLpej6QVoCn26hgFn9nwKpzwhpeYGN2VR+dCTh4qEtlW6tTYajWjGIm/RJEc/cC5mc1zQ7KfjISXI1cSREpRqHvFFVkfnpIcja/7nmovSJzWrJn9oHBF9nu1227byPlE2gc7o6GgMvMVAdKQLP84zzE+BHJPTjOWvr6/jD//wD9sOYE7R9UchuBcBLGZZ9u3W/99GU3CvhhCuZllWCU1TyFrr/hKAG/L+9da13KSV9I5SYuuz+k10qDvnmBdwpjk51VGhTqYiwzASILepT01N4e7du1hZWYmnX+iUK8vaj3cCzlCols/FMG0X8yCq48Dkdl0GrRkYGMDVq1djbANuO+fCowoiLp719DRP2tCj2hxF6fONRuOcX+nBwQHef//9NqXA8hiukv7fzHdhYaFNgVUqFTx8+DDm/dFHH2F7ezvGKKeA3dzcxOTkJOr1ZsQ0mlmYD/2q6/WzsxA5w9nZ2YkBwrgphaFpp6amYhharmEor9FOzH7SHXoMKcv28GSbk5OTOOM5PW2G8bx37x5OT09x+/btWG91XaMQUbOJ84LPNNg/jCszOjqKsbExbG5uRoVB04ceRuBg5fj4ON7nNdbDzRGuKNVkoONR26BjVgGXzpZ9Vq1JzRep314e0L5GomOYfajPqrmD5anL5+DgYJxh80xMBWmqYNkG/c88UzseXbZ997vfxXvvvdcW5yg1a/lzm0qyLFsJISyEEN7Isuw+gJ8F8EHr8xUA/6D1/XutV34fwH8RQvjnAP4ygJ3szKSSV0YSWfO/E8I1VKPRiNt4dVWbiYNCTRSOLIi01IbGgcRY0L4Y6vmk/FWdUb3uigD6+/vj1m2eAE3BzVNoGo0G/uRP/gQhBNy9excbGxttTExaEmn6QqgOCNKGjELbOK9xkZe2O+ZFuxynmiyH8U1o6z84OMD9+/ejT/je3l48VHZgYCDGjeFRUuVyOa4lsL9YN4YR5U6zJ0+exC3En/vc57C6uoqVlRX09vbiC1/4Ap49e4a9vb1YPpW2uj+y/TzpRzelZFnTbs4ZXJZl0XOHdNjb24sHF2xtbcXrhcLZbj+aoYgAfSbpNm3lJaYrV67g0aNHMcYFgUq5XMbR0RF2dnZiaIUsy+L6A/uNJxvNzMxgaWmpDS2SR9V9zoWJ1teVvzoNOE/7u6kxoLypQtf5VBFsSvirs4CXoetdQLud/OTkJIZ/ILBSm7PbxlWw+rj3NqYEOMePXtN3mE9qhqbpRf24/x6AfxZC6AfwCMDfRXNh8/8KIfwigKcA/lbr2X8J4BcAzAM4aD3bMaUYRDtIiZ5C3/qeMiN/0+/Vpz+aH9/36dXJyQnu378fY3LQ28CnkY7ymTjVdTMKkVWxWIxT8VKphJGRkbizj+9RafAUaMZffvfdd5PTOCJxpYvSVGmTms4BiEKZ9KBft3pblEqlaNJR+zEjDi4vL6NWq8XQAwsLC+jr64teK/Qx58aoLMvw4YcfYnp6GuVyOfYPTzBRVEgvi9HR0Xgs2NHREYaHh7G5uYlarYbFxcVIH9KbuyNVEXH37MrKCkII0UOGoXU506BbV09PD9bX1+OMg7OA4+NjrK2txWPoqtUq7ty5E4WwIleP1aJIkyYDKvS5uTncunULAHD16lVUKhVUq1XcuHEDpVIJ9+/fPxdigedt6iIzlYjyA/tfffvVNq08nhLmvOZTfi3HecxnzSok9Z1U0rqo/TvLzjY2eVk6o6EJiTNcdVHlRjVNLlxdIXEWxs00DtqU1qwP+0jRPNv8I0PcrUL/HYCfTNz62cSzGYBfepF8PeVV1pki5WWinaPPUIvzed3xpvaxFEOdnp5icXERhUIhLuTxvk9vWKZ2BBmaq/0cFCE0bfJHR0eYmpqKg46ufGoDp5mCZ2YWCoWIqNRM4VM3ZWhtk9ZRByrpwEVCABFZ86gsLuiyXScnJ1hfXz83e+EC3sOHDwEgHozBmClcQ6CddXNzE6Ojo/G0edaHx5Q1Gs1wBvRdZ9jZubm56AHDchuNRvTX5kBUJKcxMDi9rdVq0SuGnhoclNyUo8H6C4VCtNuTl3p7e+PJ65///OdxeHiIJ0+eYGZmJiohnWLrbxXaFEycznPW9/bbb2N5eRlPnz6NexFqtRquXbsWvX6AM9s6w8LSw4HrC8rrLiCUZ1T4ue09hXg5DlILiSk02gmAqUJTftOxl1IU6n+uY0LrQhMo+57PacxvbYOvhSmfk6/oBuizGKdDih4++3CZkpcuzM5JJnaIem8oAVLTTf7mfUfq7kCv79K+TIHOBUpH4fv7+5ieno7xTPJmAs5MFH4sn+9xAwsjhxWLRTx+/LgtUiEFMz1E6IOs02ifmeggI4MqDX27NXB2OlChUIjHvmVZFk0gg4ODcUOMbvDQeCAqhFZWVqLf+8DAAKrValz0PDk5weLiYmwv3fWuXbuGwcHBuLi4v7+PR48eYXZ2FlnWtLfv7OzEQy9u376NSqWCnZ2dGBOEQo6HOxCxko66YKVxSXxqTNrwUAsVEqSDz8y4eYORFavVahT4TvPULMeRGHC2QYrmpJmZGTx9+jTubAUQDxAeGxvDxsbGubankJ+a1nyxUJE2cIZwVSi6oGXdPa+UYHbQpWPdk/Ku8zXp5ApAhaKWq/UjrzC+OQWwmglTbdA6sF7c/6F0SFkC3N6vz6WEuyN/TxdGcDuhFAVqo1Mdr4JcNZYyBYWNDky1L/J6yv7EjuRmGO3EFKLVa27D4zs8+ovIjYuRii5YLu3MzJ9CU7dLe0criiMdVMDqYo3Sjd4HDGDF45gY4pa/VYmSdmRkjUFN32cu9GRZho8//vjcgKhWq3j99dcRQsDq6ioKhQLm5+fjppfe3uZZlDy1hW0MIcRt36enp9EmzTK5YYnIGEAMacDNRfS8oCmoWCzG2QVnD76grSFdqdCmp6ej7b9SqcSAZ0pjR6w+K1LeOj09O0CAZiGevUoT24MHD1CtVttCC9AXnhE0dRwp/yqi9dgxTCosfZz52PVZn44LHbtqXkyhfLqIkrfJVzoufGyqUFXaat56XwEd6ZDa1ZsaWykaqEJLzUiUfvzvfKDvXgrBrYJDp2RuV1Mbnk6d+K2NZ8M9gA/QPiVxbal50gOFrnc0IegipJbrWjXFyKx7lmXJg4NVsCoCUyHJgUkPGEWMurOT+bFNWj8u0HB7//Xr11GpVOImm/Hx8SjEKYjpvaAxxTktz7IMw8PDEd2yThxw7BOafDRWCNtJX+y7d+/Gmc3u7i5mZ2cxNTWFSqWClZUV9PX1YWVlJXpUUCEo3dhGmqGIXjm70o0P7KORkRFUq1VMTk5GP2eg6TP+wx/+MLaL5q+JiYnoMlgul+OxYA8ePMDx8TGmpqaimYcLti6wXYExKS/zvePjY1y9ejUep0ez2ePHj+Pxdkp7DXerMwT2m/IH+dfHnIMlr5//VsWUGgOp8jwPjkl3YVW6edIxrcmfTQFC5pnyAvL6Oer28eXjPQUsXVF7G1hOp3QhBDdTaprjKCXVMWROEkSZzweHDmwiJi2TZfHEZn3eUVNevZ2RFSmwrm5m0Hc5SH3LrioLAPF8PD+nTwep15e/mT+3B9NdsV5vxhFWn3ZO/xuNRkSv3BCinhhcAFRUpfQnstXTPzRuTKVSQblcxsTEBBYWFuIByDs7OxgaGoo7T3W9QX2HqUS48KdTbS4kEi1T4XHhml44wNmhrxTS4+PjKBaLMSQwZxt0saOb5pMnT+ICbKHQPG3p/v37GBkZiWFwtU/8dwq5sv6Hh4f46KOPcHh4iDfffDMi7Fu3bqG3tzeeGcr6KNBR/nH7uvKpmiadnzU/FzbO3/6Olk8+0HxIa6+DzlA9/zxFomhek+ZBX3uaHek+SZ5kv3vZ/u1o+XlIOXVf+UCf0R21qXRhBLdr9pRWSk1BVDApUzph+UkhihRK1ih//u2LC520qgtmXbH3hRNFwm6r1zLUO4bfqoycPi68mT/LGh4ebqMzlVYIIS7U9fb2xlC4FFi0gRNZ66YCRbk6YLkA6TSkYKUvd29vb0TAjLBGDxvvcypCDnQOSO0vpfvp6WmML0JlBCAK9s3NzXj81Pj4eDzxiLsUh4aGMDg4GO3uIQRcuXIluisCiGE9syyLm4rU9KH9ozZb7XP1L+caB71E2J6enh5cuXIFb731VoyHrifCp8ZRiveVn5yfU4jXEW4n/nf/ZgqllI+0J6WB1k/rovsmtE4pIEj+HR0djbuYOfMlz/rM29vvM2te85SiicuwPIUwODgYzaOp9KJBpn6sSQUr/3scBV7XBrq5Qu2ofMa1nHcuialowt9xIeHTmU6a0dtJweGDV4Wyhz7Nmway/bqwoonIUAWn0pKxFrgVnedrcgs/37ty5UpcoKSZRE8tZ93UcyOFmBqNRlx8JerXPiwWi6hWq/jggw9iDHJGODw9PY1rDIz7Qt935sG6UBgzeh+FrfKJHqILIM4CgObOUA7mSqUST0qneWF0dBRDQ0PRc2VwcBCTk5Nx9vHs2TNsbm7GWCzsG12ASwkqzoAozFUhDw0N4fr166jX63GRutFoxHUR2te3trbawIvykQOF5wld/dZ3lNdYD43xwUQkq3yufOs8qzMkH998PyUTaBpMKQAfN4VCMziXAgINe8CxpEDP/6t8UgXlSD81K8hD58yTHko6blLpQiBuZSyg/TRwZRjVaoqc3XbIlBLQ+i5/6/subPLy4P887ZlC3b444mjYFyUVlQM4NzC0TCY+o0pFBRqv9fT0xA0wDElJ5t/c3Izok7GnaVOnQHR6KAJRhaLlZVkWzTvejhACrl69ivX1dSwtLWF4eDjGPD49bQahZwjUEM6mtFxUVLSqdWA7C4VC9GzhdV3wBRBj2gwMDETUykVk7hQtl8vRz5sLj1wHqNVq0f+9XC5jcHAwHvQwPT2Nk5MTjI+PR9qlhLfym4MEmmqWl5djYKlqtdq2wF0qldDf3x9nNc7HKVOI9p8qjNQak76TAkZ81sdvyiToHmLkE5oo+Yz2ZQrpax1c2PsY5bN6ALkKZR0/zItt8QV9mhO9/7TdOr617uRhpRWVe95CsaYLIbiV+Mogjgx02s2khPfB4I33zvWVXT6jDKnM6s+qQE4hYs2PvxX5+GKGM1ve/9Q10ibVJuDMdUrfGRoawiuvvILvfOc78ZQORTBXr16NG08oiHXgpxQmB723iaYFZ2gu/hYKzQh4uhDKAdTf34/BwUFcuXIlbnyhoK7Vam1oh4Hp1d6/vb3dtpkIOFt45iERdIEketQ6EkkDiMfo7e3tReV2eHiIo6MjzM7OxnCeMzMzqNfr+O53vwsA8UAMLlIeHx/HGQ7LUoWbEnzDw8MYHx+P53hubGygWq1GDxaadhgUS/cE6DmXjqq1T9R8kQJG3q/63wGHCmYVqM67Ota8zNTaldZR3+Vvn/HpvdRsw0EW604+ZrlqlmMsG9bH89XfrCddUCm0OQNjX/OemztT6UIIbuD84oLfU4HnjAXkbwzQ94Hzq8Ka+L5qW2WAFAJRZeBKwwWbM7GjEEdIzCelsLx9OkgAnPvPdun3xsZGPExAUcXx8THK5TLK5TLu3bsXyybaVTTvU2a959ProaGhuKXd+4YbStQ8wPpvbW1hZmYGw8PDqFaryLIsCqjd3d3omsdDnsfHx1GpVGLgrL29vYigSav9/f0opDmQOGAcCbIve3p6oq2diDaEpjvi8fExZmZmYgRH+qvT93xtbQ0TExN46623oqvenTt3omeI8naj0WhzIyQdh4eH8c4776Cvrw/Dw8M4ODhArVaL/cgDIgYHB9sQasqjxAWW8m0qnorypwtBJt9f4LNZBz16nyYwPSHdBa0qVOdthlml2cMVoY43n2HrGAbaF7yZP81zvb29ceeytt9pwfc1JgzrVygUYix8dZdlG1MyzNOFEdzA+UUANkgJ7RqY7+k9dflxdKHa18smw6TsZepdoougnr/WXQejts+nln5dnwfSi0apfFJl6HUKVjLT3t5eDEvKZ7n9nmdcqpDVcguFAubm5tpQnW+i0LZNTExgeno6hodlm3TDkwa8Usav1+v4/ve/H9F3X18ftre30dvbi6mpqRiNkEL8M5/5TJwl0M6tA5T9MjExgdPTZmxtHv6rNnhXiPV6vS3Ur9Ky0WhgbW0NpVIJq6ur2N/fj1EUeUzVO++8gxCaIT+fPHkSD1PWszmVjopCWZ/Jyck2Qc44LZwJcDZCZUCe9pCkvp7Dj5sDtB+VD31Men+TJnkzwBSS18U4R9J5ycGb9pU/kwf2UnnxP+uv8XkYBsHpkxqTCjgVSXuIAlWKeQu1mi6M4E5pLJ9S8bkUuk4RTzs+T+DxWiq5ZnaUkkIS2hYVcsr0qYGhZaTar4g7j9l84OksQ2mgi6P6bAhnG3C8TH+2p6cnut5R0A0ODsbwtFr3er2O1dVVVKvVpO96im40n3BxkX1JZKY7IHlYK7evf+tb3zoXrEppT3fAoaGhmP/Vq1dx5coVvPvuu227Vx1d6q5a0rtYLOKNN96IKP/x48cYHh6ObmfFYhGvvvoqJicnsbe3h6WlpbgNfnl5GVevXo2eETotV6SvfambgUZGRnD79m0cHh6iUqmgVqtFl86jo6O4zT3FR85nLjx09qPPuiksNaYAxHUIV5iqELVODlBS482FsM74NO6+ywbnMc0zZQ7VhVwfs+RPKkTtLx+3yifsSwY1o/spgDZ+f56yAi6Q4PbO987ibyWyT6n5nl9zAczvvGsp7anMp0iC9/S/1oPle5natpQg1rxTg4Lva/t8QHSir9NKB5Fe09mFHvDaaDSi7zCf545Kp1kIIdq3tc78VoXDj68FqClG29jT04NyuYxarRYjKu7u7iLL2rdSq+Cjb/rq6mq0RZfL5WijptsjbaX6rqImPYZudXUVfX19ePPNN+NmoUqlgr6+Prz99tuYm5uLiHJiYgJTU1NtJ/ikzIOkC+lADxXSlrOUQqEQTwBihMaNjY02pep94msrLhCVZtpvbnpwu7RvHPMy2CamFKDxurIsR80u+JXn2fc+xn1W4IpKETuVqXuq0cxGjyadzZAGPqtRwU7gwaS2c9IkTxkyXQjBnULR2mhthKJXJwqvMU8XkkoQzTcPrTuiduZSRvI6aR6u0TuV+bxpkgt0p5G3OaW5vXxNrvC8TG2HKwp1pdI6Utj6u54vv0ulUvSS4HUiGy5ecmFoc3MzHqVG5UCvEC4GufACzmz5PKnk/fffx8HBQdspRj74SA+i7CxrujTybNCZmRmcnp5icnIynrhDpdVonB2i8eqrr6JWq2F+fj66XnqfkUZ+j990C3z//ffx6NEj1Ov16NpGOqkyTAneFHDQPvJxkhpnGr/bUac+p8pYlXBKqTgfKljS5O/7GNQ6ed4p+zuBgC5MUsienp5GPiIv04MnNUNz4EHgo+sreUolNS49XQjBDbQLuZSW4jMpoaOCP8UMmh9wXhCnnu+EdFNuRPo/tfijg1+ZScvTaZ8zXio/1pffPsXy9/js7Oxs9JF2ocnfamd1JUZBnFK0fi8l7P2eozh6lHAgcXDoVJKLUPV6HXNzc3GRp16vR+TPo6h0wYdxrBlhj4Nqa2srRnrjIFSzjtOdJhMiL/pQf/Ob38TQ0BBWV1cxNDQUY5+Mj4/j6OgIS0tLePr0KWZmZrC5uYnh4eGI0JQe2nc+TlShViqVtgBe7IdUgDbNw1PqfkpQ6zPOcynTov4mT6We53WOEZ3l5I1Fb19K2Kfa6GBH89fxzJ3DExMT8RhADdWwt7eHUqmE4eHhKLwVpNAnW/c8kD+1zmqOYh3yZA/ThRHcatsD8t3ogM5mFU2O6pwYnYiTQtnOcHn5acyDVD55TMj2OdLTd5xGLlDzGFbz3NzcPDe9I7pzwZCiIa/rwOY7vvKv+bmtXwdlCoGxnTzxXZGXTssfP34cXetoCsmyLC7Ysa4DAwPRH3tkZCSeebm7uxsRuC/Gsq4qXH3BkMqB7oxra2uYnZ3FzMwMtre38eabb0b/7Q8++ADVahWPHz9uO2BiYmKird98AdzRW09PDyYmJnDjxo24Y5OLtN6HGqvHEbAKMeadt8bB1AkN6qxExwOTmnsU+SqtdXagvKNlq+DjNZqNlNeVFvq+LjqrANc8gLMNcYxF42GMFWS4THAA523X51XRpmaIni6M4E6hyk6C1rW5TsF4P0/YpQS9I0MvR/+7MNXn/HkVyFofHzD6X/NxplPhqZ2t36lytAwym+aZUhC8poPQkYL3jwtzRzYuJJzp+T6ZXBUEEUypVGo7IZ7bwElrxlGh/ZH07+3tjTFJZmdnsbKyErfp017sdKPQUyGg02DWdX19PW4eaTTOTp354he/GD08VldXUalUMDQ0hK2tLczOzmJoaAgPHz6MhySrOUD51vmPNOGhCq7MNLJeCmikELTm7X2r/JIapw4itCwdk4pIHe063+UBJq83n9Ot79pHLshVEbrrJ7/1lJydnZ02d9PDw8MIUFQxOIgialclyXpqaAigPUStA5hUujBb3oE0EZTQaj/VTnGB5YiIg8un98yf+aWIpUzo5WjSQa1mA0cXLqB1gDBvChJOrXjd28X2pBiaZboi0EHnA41CR+nCenl/MDmKVhrwWmowppLTWtEIBXSWNU0gvjVckQ990zUeNYUpz7KsVCpx2zvPsmQ9GadZ+0fRqIdjIF+Uy+U44Gu1GqrVKvb397G4uIjl5WW89957ODg4wN7eXjy6rV6vo1qtJt0uU4hQ+7Kvrw9vvPEGxsfH22z67BfWK8WzqX7kR1F3asy58tA6uTDWMlygk656XRWil8FdhVoPX7TUslM8nQISvKcyRmUHY9usrq627UNgZEifAecBKSYqGLaF7/rMo1O6EIg7b2CrIO60kMGkDJZKLsS0c1yQsVzNz9G91z010DzvTm3XMlP19borItP/eULcUa8jXx1sLtxTm2b024WAKpTUgnKqbt5O/mdwJi4SVavVNiWm5bEsN9kwXvbGxgb6+/tjLPNisYjR0dFzhy6zbU5/RXJah0aj6WVTKpViu7loWSwWsbi4iMePH7ehcSojPdBY+yglEByFv/XWW9jZ2Ym7N+lZ437Mzj/aVyl07WY3Bzh5Qkb5yGebOgvw9StvJ9/T7eA+c9XyFMmn2ull5I15lq+IW/MtFovRY2VgYCAeZ6ftdZOa0lRReAqkvGh6ruAOIbwB4F/IpVcA/HcAfrN1/TaAJwD+VpZlW6HZiq+hee7kAYD/NMuyd59TRmQ2HcQupPwd3lOm9md0YOszqc53QeNCxgVaStikbHwpReEM6oLCn9P7zvRaX00phMHrilo8NkJK0aiHgtaXwiZlG1b0ovVWAQucj0PsQoFnJWZZe8xkR2tE3qyfHjJRKpUwNjaGra0tTE5OolwuY29vLx4QwZPmyYc6sHUNQLf9q9AGmkJmaGgoxgG/f/8+QmjurOThB0TG09PT+MxnPoN6vY6xsbEk2FAecGHQaDTiAQ9EovReSfVfqr+cZ7Q8b6P2fWpXrif2lZadGk+8TvSpgcr0GReEfo80cgTMb6Wh05L5DA4OolAoxLUOrY+Oub6+vnjqEssgb6gLqcfqUf7W/HSLvivFvPRcU0mWZfezLHsny7J3APwEmsL4dwH8KoBvZFl2F8A3Wv8B4OcB3G19vgrg159bC6TPm0xNI/KQoqPbPAGrAtDLTqFVzZP1SA0OF4wphKlCmM+x/JTdz5nVp3Gq6fmulkX6uT1Z7cj+jtbJlYYrIr2uiEjb5uUrfZROrnT5v1gsYmRkJAab0qh/nr+bZ3jt9PQU+/v7ePDgQVzVn5+fx8HBAQ4PD7G8vIz+/v64e1Lz0JmF84s+y8GnEQ339vZQq9XiCeyMyc1NGABw9+5d3Lx5M+btPOJjgPcODw/xx3/8x/jd3/3dKGj0o88rb6irm/al0k/NXZ6P1jGVfBz4N/kvpTB8luB1dR5S+jiPuyzQxV5XzHqdSJqK39tGZc+Qvqy/+m6rmYmL5f39/XGNhtvdqQB1P4DSo1P6pDbunwXwMMuypwC+BOA3Wtd/A8DfaP3+EoDfzJrpWwDKIYSrnTIl4bxDU7biPOGcYiZ9Rt/1e/6ua3XWJSWsmdSUk0Ip/k5KqTgjufBlOdomb7sKWKeV0lXr5oJP26319/b7Mykl4KYFfS6FwHhfp5wMY8q6fhJbINEolWOhUIhnYDJIFH2vaTtX+zlt2sBZvG51lQwhRJRNxMc4FhyYJycnePjwIQ4PDzEyMoIrV65gdnY2uiT6+k2Kj70fGb+8WCxicnIyLnRSQHjYUU/Ka0B7WFLlC9LQ80kpY347z2j+2h43pWgfKx1Ic9ZDeSPPJMT3tF1KYwdG7CfOwEqlUttz2i4CAV4jqKACZ78zEFWh0NwgNTo6Gg/8ppLggrnunFUey0uf1Mb9twH8Vuv3TJZlldbvFQAzrd/XACzIO4utaxW5hhDCV9FE5LHCJJQLWyZFHD7tSQk9/d0qM+apglGFYErQktCdBLy0K5d4KYbVfFJIQe+74tHf/NY81Oam76Tsmno/hWr4HvuB91MIxwVzpym5l6dtpRBkHVxga51Sijg14BTJNhqNuJlmeXm57XDmPGTnIKNer2NwcBA7OzvIsiweGMxp8+joKOr1ejw7s1wuY25uDnfv3o0LXSkeVfr69RACRkdHcfPmTayvr6O3tzdudadZiSYjF4K+VqRlpRYb/RmlhYIJdTf0OisvqIDuBAJSCsSRsz6fNxZTSsTrpXlzY9fJyUlb9D6vl+6sBNBmlqPvNu3kAOJh3H19fW1HIBJ966EkL2IqeWHBHULoB/DXAfya38uyLAshfCLrepZlXwfwdQDo6enJnDApxlFh53YippTPqpWrbWoTKr4YyXupDSX+33/rIMizTafqmRq4KoRSZaUQmj7nKMhp4UpCZzpa/9T7Wr9ObfAy9R77Uhei9L7GcVAk6+sDqQVsn0VwgPG70Whu5uHGGw5cFWRqDqKrIQcoANRqtTj1pe2T9uRisYixsTEsLi5GJTQ+Po6lpSV89NFHmJ2dxc/8zM+co5ULUqd3f38/3nnnHezu7uJP//RPUalU2s7RdKWrfKsASEEEFZkLTUWqjpKZhybvb1dA+l/HnwILzcMVSgrYecgEfTfPBOHjjs/y4O5isRjjtmveKTBEOih/hhAiPx0cHER/e/IGZQt3CSsgSq15aPokppKfB/BulmWrrf+roWUCaX2vta4vAbgh711vXctNTmxlXtd23slqi3Om1JTSsq75NY8UUkkxpP5PaXgXinovVS8ykL+XJ8S1zl5GSqg603lSRk+10evsQkLbkVefVDv50UWplLBI5ZOH1pQfNDldPVCQxrhQugBnMTCYuDuTvKrxW05OTrC+vh69Yra2trCysoIPP/wQ+/v7qNVq+Oijj1CpVM7Z0PMQpNKeR3BNTEzgypUrbUL6eQg0NUbyeDqvTqn3XaimELEDipT5S3nebfV58kLlgPJ+Sm544jX2Lw+DHhwcbONXd+Hr7e2N6xbedq7FaF1orqMX0cnJSduRf53qqOmTCO4v48xMAgC/D+Arrd9fAfB7cv3vhGb6IoCd7MykkpvyBrqjnlSn8Fm9p9c9Xz7nWi31rjO4l5NaaFEU4vXwOqRSJ+bk/RQq8QVCz5MDxKe1Xp5vd/f6aj+k1h6cxqn+0jql6OVl60KRL9KmeIYDjMiGSoHPq51UyyJKIhpS+z8/PFHn9PQ0+mQfHR2hUCigXC7jc5/7XIwMmGUZFhcXo3LY39/HwkLTkvjTP/3TmJmZweLiIoD0ApvSMk/R3r17F+Pj45ienj6HhvmM2r3zeNHbrPc9T6W192dKcWi+Xjcfo47g8/qJferm0tRMpZNCY5ksl/sAeDC0ttfL9PHkQvzo6Cgetk0eoOmM99QxwWmSl15IcIcQhgD8HIDfkcv/AMDPhRAeAPgrrf8A8C8BPAIwD+B/BfCfv0D+bYRxxk0hs9gAGcT6nCNvZTDvaJbtC0SOJrW+Xo62Q1OKgVzop1CNM4nWLc8WSUbKo69qdBX0Pnj0mgpCbU/qHRXEpI3XMzW4fcClhIaHomWZnbx3VGh3Mhl4v6ibl/cl3QoLhUK0J+s9ACiXy5iamorIjeFGx8fHY1yTjY0NNBoNbGxstB2erLRxNOrIlG3ljKRUKqFUKmFgYCD2FxdNnwd0tF/YHu1z8oDzWArRpvpRx3NKQSm/02XRx5y3W3lBlbiOLb+uYw04H2qWgphCt1arneMBLjoqfYjUuQlKzSbuMebOAN62H5mNO8uyfQCTdm0DTS8TfzYD8Esvkq8mJaiGhmTyaUQKbbXKT/7PYyR2XGoBjfVRRNgpaZ2c6VIM7u+m0GueANF8VABpm9V2qXmnaJVScF5eCgnqIp0rFFe4ndYeeJ3PqAJI0SJFG1emjBnug5XlpJReHjpje4aGhuLi0vj4eNx6T1vm7u4ulpaWMDAwAOAsGNXBwQFef/31uHC5trYWIxouLy9jf38fIyMj2Nvbi7ZxFT5KV/3faDTicW63b99Go9GMS720tIQQmqeFMxqd9pkrLW+n2vVTSJe8omPD7ynfpdajVMjm8YXygQM3DWfgM3MKUj5LmeLAIwWAUm3mN/tSN0tRmA8MDJzblMN2ZtnZmoi7a6b4OjXuNV2ILe9AuyBNCZTUYNLrjiRS9zw//a3fmjqhYh8Mavv0+ip6StkL9bkUuvC8UkjD6ZNnO2SeeUgrJaBT7fEyvC5a95Ti02ecLnkIS5MvPPKaIx3mrQNf3QTpWZKaFXj+tVoN29vbODk5wdbWVjSZqLtapVLB5uZm3F5PFPbo0SOsra3h6OgIOzs7mJ+fx+7uLpaXl3Hv3j0cHBzE0+GdHi5ElR7b29s4PT3F9PQ0xsfHsb29HdvGqbgKSBUY2ncef9z5wfvB33dU726Eep/vuTufo3H17PC1LJ/1KdpnGQ6GWA9/j3nqQRnKZ+ofz/owDwpkms7c1KjvpDaqvQive7oQW96BdIjHFKLqlFz4u0B3tA6cFx4pLawM58ghb8U67xllWmfq1BQyhYj4cfuit0/boYskL2J/zxtwXlZe37hS8J2XWlZeHbS9qedcubBvOqGpVBtPT0/jFng9F9AVdKFQaDssQhUEPTpI63q93nbE1ezsLEJoHltWLBbjOZn0IX/69CmGhobi9StXrsRZTKdZEBXF2toaFhcXo3sZ60gPGH5UePv46LTO0ImeKeCTxx8uEEkvN2W6AnFhq2U4T+mMQYGFKx1tt/KN1s9prWPPlQjXOVL1TMkep4e/0yldGMGthHEtD5x3S+pEgJRgYRmeVDvrO6mFyxQS6TRD8Kmio3UVwpq/Cx5vkzMC3/F2+zVXRCllxHo78+UNckc4SoMU2tG8fPpKevkgylNGyiM6NU8xv19zAbK3txd/a1kqREgbJkWUVE7Hx8cYHx/H8PBw24GyJycnKJVK6O3txejoKIaGhvD++++jUGgeHEu7Nw8WfuWVV+KJQ6yHojzW4/j4GPv7+3j27BneffddjI+Pt8XlVlop3zlf5NFXUS7rkLcArjTJ4zmlv65RONBR84n3sfKt9q++l9f/2hZVZD6evL55C558TpU2lW2qban1hhRQuhSCWzvREVOqk5jyGC5FBEcFKcGu9fFnXfB6ItOkPDZSyFDzUltcpw5LMZUrAgDnhE2qvanrzriabye04oMxpWR06s9nVAh0KieFBN1mn2c/d/qkBLjylqJAbYMft6XTYd+ZyYHMHXhjY2N49OgRtre3Y0zw1dXVGOf52bNn8aT4ycnJGLR/eHg40oTb/Wk7Zz/TVMNDjFdXV+PiqvJgpxltyt6dElh5Slyv+UY1XutkRnQB7H3i9XCl4gAoNYaUX/Lq7nVQWuUJWU9Oo5Qs0ZQCYS+SLoTgVgHgBHIG5PNue3YkwqSEc0RGRKPv6++UKSKF2PKEgCct25VTiqG0HNf4SgelV0rgppRbakBq0vddSLpQ1vZ5XVNC3M0QrpgdkWg/qeBP5a31dGTlA1VRkc+OuJHLUZ7WT/10mUej0YwS2N/fj7GxMQwODmJqagrb29vxAIulpSVsbm7GxVPGE+dBDIVCAd/73vfw9ttvxxNyAGBtbS0eLMz29/T0xNN0ent74+kqKc8OF4pssz6bQpZKMwdUpIf2XQqoOP+lBJajbG2jR/5zHkmVmef2qvRxftTnnR8VaOlMxJPLII/prkn5k/yTGuueLoTg1pQnEP0ZZ4IUk+Z1gP9OMXleXYDzi2IpDZ9Cdvyfh1JTgj8lrDshH0dPbrdzpvUyfPCyvrznx0+p8FMk5MonZRN0VKt1zFuo1PxV2KbMO/6u9psOlE7veVu0Tbr7Uj2huMi1vb2Ng4MDrK2toVAoYGRkBDs7O/E/435zA8+zZ8+wubmJcrkcT9JRRL2wzVfgxgAAENhJREFUsICxsTGUSqXYr9w2r/R0YeZ9rf2l/ce6+zVHuCpoWIaajXxRkN/OW0pvlqf2efaTtkXb4ODHBV4eQMgDM6k+Vlo6PZ9nO88DL5ov+4w8RCF/KQS3EiOPSfgccP7YodTgyhuMeULC3+0keB0x+DualMG9brzP71QeKbpoPZjcZp4aII5KU3bxPDrmPeNugFpOXr/oYPd6qzJVheGIj8+kFLTaGHWwqSLjPdZBFYt6MHg7SFutl9OY14+Pj3F4eIj+/v54diFNIqzz4eFh2wJio9HA6OgoXn31VWxvb2NnZwf7+/sAgGq1GjeHMIJdrVbD4uIi9vf3o3ucos0Uv2mfe9ucvxT1Kt1T+ev4cn5NCVHnCTen+LN6ar0+zzrSPOXAzhWN/vZ2Ku+lxmPq2dS4dwWn11O2+SzLzsVj75QuhOB2FKjfqalbysDP5LZyvqPJzQjObK5p9Rmviz6j1xzFu/BMCSJfOFIhoe1LlU0mTtmDHREoYk0hA2838yVtdXrtbdB3/TvVn50URaoN2m5fjPKByee9f7V/vC91GpxCeyke0TycTwqF5vbmoaEh9PT0YGRkJCJsepWoICwWi9jb28OHH36I7e3tGEaUEQ0fPnyI9fV1jI2N4erVq1hZWWmLH61CzcOSev+kxpzTTmmiyU1bqoSVb5iPKkftAwpiNRmk3mcefC9Vju4M1XHga2d5oEYXVr2vU2PETZ8ulJmHt1uVkdZTj87rZHIFLojgBvIRXZ5ASBHUtZUuInkePk3W8lIoK1Un5pUXOdA7O08oaptdYOm9Tpo9j0YpWmlZ/HaTgb+rQjuvPK1TyjPAg0hpm1KKLsXAXge3xesAd2Htg0XLdwGm5Wmdnc/8+ZRiPjk5wcTEBEqlEmZnZ7Gzs4Ojo6O4OYgIv1gsYmhoqA3Nzs/PY2ZmBlnW3Mn3/e9/H7u7u3Fjzfb2No6Pj+MuTSoFF1yse6d1iDylnzcr8mdVcKcEj4+blELWfDsJS18Tc6WRUiLeZ3o/pXS9nmpeU57IM52qjGE/K6+kDppwpZmXLozg9ulq6n5KW7qN1ZGRrzw7EwLtU6M8+692uPokK9rQ5EJP89L28Lr+dq2fSiltnydEU89S4bhwddSv9UkpNH6nrivdUmiqE501H7djuw01pXBSJpyUK1ueknNaUpjqtm+NSeHvlkqlGCb2ypUr6OnpwYMHD9qm+8ViMSLsEJpxvW/duoWhoSEUCgVUKhVsb28DONvkQZPI3t4eKpUKSqUSyuUyVlZW2ngrj1+UHql687oLMae5z8DyzI0ucFPgTP878PI1GhWy3j5vl5fjgML50GVJihau1FPgyAV7SpkpkFEa6/9O6cIIbuC8cNbGKsF0WuICP09LAp0XLPmdp8n1Webl9VHh5PmkBkxK4KrW1ZQnDPnfGVTzdAbRweSoI2Wzc0Th5VA5en3zFm/ylBHvO61U+aoQd/rxw0Ueb3OqbT5Afbef8loe36SUjdqtq9UqKpXKOUEWQogHH/T398ezKWlO2dzcRJY1beVTU1PY3NyM9vFGoxnnZHZ2FsPDw3ETkNfRv1MmolR/+BhQcKP9oXn4OEkJOc07tSiq9UrNzFLleFv4np904+PX+TKVND99Nw+okL6cRbl8SZXlY+V5ZhLgAglun/4C51eivaNSWlGvpxgsJaBSjObE1cHr7/k5eT6IVSj4NN0Fj95zJtU2Kc1UgOYJxVS9O7VJkasrH29HSnCl0Ese4u2UHKWkynRaEQ1TGOiWbx10KfSXQuq+WOXgIKXoGBSLNCwWi3FHJtDcrcmocTyRfmNjA4ODg9ja2sLp6Sn6+/sxOzuLo6MjXL9+HSsrK3F3Xn9/P+r1OtbX11EqldDf358UUs+bQWkfpISagx9eS/Wz92dKASqNtD6+lyFP6fvY1f8uB7Qc7Sc1oXYafy5rlJ4KKHUMcXw6AFAaqTxTGZWqf14Kzxs4fxGpp6cnY2Q1oJ2YuhiWmsYwOXPqIPaO0zw0nzxGzhPoXoY/q891Qq16TZ9NLUQ6A3jyweeM0IkOqfY9D511ep91dLe/FPJ1BZuiiU+38xY6lW+0Hn6PQpr5q0Lyurpic4WSZyrIsrPDjnURUgMN6VFpAGLAqnq9jqmpKYyOjuLw8DAGkwKA69evo9FotMXypsBQ98CUguFzwPmNSdr2TuPCbf7aZkfEbgtW2qsw1E/eWHdg4eV7X2iZ/py2N0ULf87HMP+ndoumQJmPQ9805kqwdbhCUopfmCBTwHkESoGdp4Fd2zEP7WxFe0x5tvTUNe88ZzDmp3m8iDDUNjqjp9BQ6nm97sxB2uhilNaf+ajyUfoqPZlv6hxDfy5P8Lsy9Xd5PSW08+inz3l9fDt9ajD6QFeQoOF0lQ+1nSoYPX/tR5pNhoeH2w6J9f4jSud5ktoGBt0fHh7G7OwsRkdHce3aNVy7di22b2hoCGNjYxGNp/rNlVuqr5y2fj21SKf8lVoYDOEszC7bw/w8TrjSzvtKP8qbXp4iX5cfTgM+mwJX2tf+vgJKPucKgt8+K0iNIc3neenCmEqA9GBNaaOU8HAUoO8omtFOVKI7g7jA7FTnlLBm/lofvZ4yazyvzJT2doXE5xzlKlP54PI2KyLLM1OlFJzXP7UQnKJXnrJL5al9qfX1haAUfd2rJaUElCeA8x4oKYXtNuDU4KNpROOIaNv6+/vjdYaJZT148EKhUMDw8DBu3LiBSqWCw8NDNBqNaB9nZDsqiIODg6gQVLhqe1KCRvs0T3F6PuQZnUF4HqQvg3A5sHCvC9LW+d6RuvaNlqk8ou3VmY8mLgCnAEhqfCvNVPmnyvfvTvTMK0vThULcmnT66NOyFOP7IqY/p8TQ33kM7b99atyJuJ0EHJBvvvE8UgIuVRfNl+12JK+//TglZ9SUeUDrzMU/R0o6qPic1yNFF+8bzSeVbx6t/ZryT6FQiCfbaNv0fdqmAbQhQrZd25uil/Ybf2t99/b24m5LXuc0W9F2o9GI6JpeJLSPr66uYnd3F5OTkzg6OsLa2loMS1uv1+MGH0WQOgbUvqu09jHGZz3sqtJWx53SyenKuugMJfVM3rsOMJTuzhfP4wftY/Jman3NAUcKhCkIVF5X8ODPaz4+680bH6l0KRB3oVBoO6G70/POWH5f33VU5tdSgo3X8swtvJ6KrcD6dUIGKY2dUjraJpZJ1OcnlSjTe/7KmJ2URQr1pBSj5p2y1adMX6k+0/9qwtCkg1r7ws0krItObbUeKd5QNK0CW5We9lEKjatngU61UyiX/O0IlIfWFgrNKII9PT148uQJpqamADS9V3i4rR6N5QpG6ePxVaiU9D/pkmfK8zxTQCYFAJQflKb8r+sOOs6U5krvlEBne/ic5tFJSLs88Hf0t7cpJX88b82Tv33nbmr9J5UujODOQ1TasW5n1N8qHLyDeF3va+ok1F3Ipa55OanO0/oy5QmvvAGRQkVaX5+u+fsq3PMQrz+bUhyOJvIGry6QaZt9APLZVL86vb1/mKcKmNR7rLPn5QGAfKDxGR6WwOm07kz0wet18Lq6cisUCm2BtHp7e3F6ehrRc09PDwYHBzEwMICrV69ic3MTOzs72N3djYJahTGj8an5IUVH7RO2I0+paj+xDJ9paP/4tZQydR5NCVxf9PX/qXHtC9Ne77z1D1XWmr9GN1TPKOUpTUrrlN1a5ZUGMuO9FxHcF8ZUwgo7QVO2KKCdODpo+duneJp04cKnN27/1PcdiaXqwv/uGujPAu3ug77Dk8+m3tN7pJkiSC6uKSMrAvfkzO8IObV2kFKAWs+UEPZ25CG3POWYJ4BSz6riyUP0Os11BanvKULTvPRMS6Wltlv7w+kZQoiLifTlJsqu1+solUooFosx1smNGzeiPTvLsmgS0Y/yhNY3tVahtFT+0DHhoCUlWHx8OMDw+rni0v7QftZnSUPNX4ViCgGT3nrNAZ7ykI9pLZP5qwlXaeK0SNHGZVaqDlrfTulCuAOGEHYB3H/Z9fgxpSkA1ZddiR9T+jS3Dfh0t6/btoufbmVZNp26cVFMJfezLPvJl12JH0cKIXy327bLmT7N7eu27XKnC2Mq6aZu6qZu6qYXS13B3U3d1E3ddMnSRRHcX3/ZFfgxpm7bLm/6NLev27ZLnC7E4mQ3dVM3dVM3vXi6KIi7m7qpm7qpm14wdQV3N3VTN3XTJUsvXXCHEP5aCOF+CGE+hPCrL7s+nzSFEG6EEL4ZQvgghPB+COGXW9cnQgj/OoTwoPU93roeQgj/qNXeH4QQvvByW/D8FELoCSH82xDCH7T+3wkhfLvVhn8RQuhvXS+2/s+37t9+qRV/TgohlEMIvx1C+DCEcC+E8FOfln4LIfxKix9/GEL4rRDCwGXttxDC/x5CWAsh/FCufeJ+CiF8pfX8gxDCV15GW35U6aUK7hBCD4D/BcDPA/gsgC+HED77Muv0Z0inAP7rLMs+C+CLAH6p1YZfBfCNLMvuAvhG6z/QbOvd1uerAH79L77Knzj9MoB78v9/APAPsyx7DcAWgF9sXf9FAFut6/+w9dxFTl8D8K+yLHsTwF9Cs42Xvt9CCNcA/JcAfjLLsrcA9AD427i8/fZ/APhrdu0T9VMIYQLA3wfwlwH8ewD+PoX9pUypbal/UR8APwXgj+T/rwH4tZdZpx9Bm34PwM+huRP0auvaVTQ3GQHAPwbwZXk+PncRPwCuozkw/kMAfwAgoLkrrdf7EMAfAfip1u/e1nPhZbchp11jAB57/T4N/QbgGoAFABOtfvgDAP/RZe43ALcB/PDP2k8AvgzgH8v1tucu2+dlm0rIYEyLrWuXMrWmmJ8H8G0AM1mWVVq3VgDMtH5ftjb/zwD+GwAM5DAJYDvLstPWf61/bFvr/k7r+YuY7gBYB/BPW2ag/y2EMIRPQb9lWbYE4H8E8DGACpr98D18OvqN6ZP206XpvxdJL1twf2pSCGEYwP8D4L/Ksqym97Kmir90fpchhP8YwFqWZd972XX5MaReAF8A8OtZln0ewD7OptsALnW/jQP4EprKaQ7AEM6bGj416bL2058nvWzBvQTghvy/3rp2qVIIoQ9Nof3Psiz7ndbl1RDC1db9qwDWWtcvU5v/fQB/PYTwBMA/R9Nc8jUA5RAC49xo/WPbWvfHAGz8RVb4E6RFAItZln279f+30RTkn4Z++ysAHmdZtp5l2QmA30GzLz8N/cb0SfvpMvXfc9PLFtx/CuBua7W7H80FlN9/yXX6RCk0YzD+EwD3siz7n+TW7wPgyvVX0LR98/rfaa1+fxHAjkz5LlTKsuzXsiy7nmXZbTT75t9kWfafAPgmgL/Zeszbxjb/zdbzFxIJZVm2AmAhhPBG69LPAvgAn4J+Q9NE8sUQwmCLP9m2S99vkj5pP/0RgL8aQhhvzUj+auva5Uwv28gO4BcAfATgIYD/9mXX589Q/59Gc5r2AwD/rvX5BTRthN8A8ADA/wdgovV8QNOT5iGA99Bc+X/p7XiBdv4HAP6g9fsVAN8BMA/g/wZQbF0faP2fb91/5WXX+zltegfAd1t99/8CGP+09BuA/x7AhwB+COD/BFC8rP0G4LfQtNWfoDlT+sU/Sz8B+M9abZwH8Hdfdrv+PJ/ulvdu6qZu6qZLll62qaSbuqmbuqmbPmHqCu5u6qZu6qZLlrqCu5u6qZu66ZKlruDupm7qpm66ZKkruLupm7qpmy5Z6grubuqmbuqmS5a6grubuqmbuumSpf8fMTAh/ETPKjMAAAAASUVORK5CYII= +" +> +</div> + +</div> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + +<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain"> +<pre>2 +</pre> +</div> +</div> + +</div> + +</div> + +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [462]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">trim</span><span class="p">(</span><span class="n">array</span><span class="p">,</span> <span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">width</span><span class="p">,</span> <span class="n">height</span><span class="p">):</span> <span class="c1">#función para recortar </span> + <span class="k">return</span> <span class="n">array</span><span class="p">[</span><span class="n">y</span><span class="p">:</span><span class="n">y</span> <span class="o">+</span> <span class="n">height</span><span class="p">,</span> <span class="n">x</span><span class="p">:</span><span class="n">x</span><span class="o">+</span><span class="n">width</span><span class="p">]</span> + +<span class="c1"># Calcula el error entre el valor z dado por la imagen y el determinado por el modelo teniendo en cuenta la incertidumbre</span> + +<span class="k">def</span> <span class="nf">error</span><span class="p">(</span><span class="n">xdatatuple</span><span class="p">,</span><span class="n">a</span><span class="p">,</span><span class="n">b</span><span class="p">,</span> <span class="n">x0</span><span class="p">,</span><span class="n">y0</span><span class="p">,</span><span class="n">c</span><span class="p">,</span><span class="n">z</span><span class="p">,</span><span class="n">inc</span><span class="p">):</span> + <span class="n">model</span> <span class="o">=</span> <span class="n">gauss2d</span><span class="p">(</span><span class="n">xdatatuple</span><span class="p">,</span><span class="n">a</span><span class="p">,</span><span class="n">b</span><span class="p">,</span> <span class="n">x0</span><span class="p">,</span><span class="n">y0</span><span class="p">,</span><span class="n">c</span><span class="p">)</span> + <span class="n">errors</span> <span class="o">=</span> <span class="p">(</span><span class="n">model</span> <span class="o">-</span> <span class="n">z</span><span class="p">)</span><span class="o">/</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="nb">abs</span><span class="p">(</span><span class="n">inc</span><span class="p">))</span> + <span class="k">return</span> <span class="n">errors</span> +</pre></div> + + </div> +</div> +</div> +</div> + +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [303]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">scipy.optimize</span> <span class="kn">import</span> <span class="n">curve_fit</span> <span class="c1">#función del módelo de mÃnimos cuadrados general no lineal para ajustar</span> + + +<span class="k">def</span> <span class="nf">gauss2d</span><span class="p">(</span><span class="n">xdatatuple</span><span class="p">,</span><span class="n">a</span><span class="p">,</span><span class="n">b</span><span class="p">,</span> <span class="n">x0</span><span class="p">,</span><span class="n">y0</span><span class="p">,</span><span class="n">c</span><span class="p">):</span> <span class="c1">#modelo gaussiano 2d a inplementar con constante aditiva ("el cielo vacio brilla")</span> + <span class="p">(</span><span class="n">x</span><span class="p">,</span><span class="n">y</span><span class="p">)</span><span class="o">=</span><span class="n">xdatatuple</span> + <span class="n">z</span> <span class="o">=</span> <span class="n">a</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="o">-</span><span class="p">((</span><span class="n">x</span><span class="o">-</span><span class="n">x0</span><span class="p">)</span><span class="o">**</span><span class="mi">2</span><span class="o">+</span><span class="p">(</span><span class="n">y</span><span class="o">-</span><span class="n">y0</span><span class="p">)</span><span class="o">**</span><span class="mi">2</span><span class="p">)</span><span class="o">/</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">c</span><span class="p">))</span><span class="o">+</span><span class="n">b</span> + <span class="k">return</span> <span class="n">z</span><span class="o">.</span><span class="n">ravel</span><span class="p">()</span> +<span class="n">FWHM</span><span class="o">=</span><span class="p">[]</span> <span class="c1">#lista para los primeros valores de FWHM a blanco y negro</span> +</pre></div> + + </div> +</div> +</div> +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>Tomando el modelo de gaussiana 2d de tal manera que se tomarán a sigma_x=sigma_y=sigma [2]</li> +</ul> + +</div> +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<p>[2] : <a href="http://campar.in.tum.de/Chair/HaukeHeibelGaussianDerivatives">http://campar.in.tum.de/Chair/HaukeHeibelGaussianDerivatives</a></p> + +</div> +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 1 (blanco y negro)</li> +<li>Todos los tratamientos de las estrellas son iguales de tal manera que solo se comentará el procedimiento en la siguiente celda</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [304]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorte1</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">Escalagrises3</span><span class="p">[:,:,</span><span class="mi">0</span><span class="p">],</span> <span class="mi">210</span><span class="p">,</span> <span class="mi">237</span><span class="p">,</span> <span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">)</span> <span class="c1">#Recorte de la estrella individual</span> +<span class="n">x1</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">15</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span> +<span class="n">y1</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">15</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span> +<span class="n">y1</span><span class="p">,</span><span class="n">x1</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">meshgrid</span><span class="p">(</span><span class="n">x1</span><span class="p">,</span><span class="n">y1</span><span class="p">)</span> <span class="c1">#creando tupla xy</span> +<span class="n">xdata1</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">vstack</span><span class="p">((</span><span class="n">x1</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span><span class="n">y1</span><span class="o">.</span><span class="n">ravel</span><span class="p">()))</span> <span class="c1">#util para leer rejilla simetrica (2,225) en curve_fit</span> +<span class="c1">#aplicación de curve_fit para hallar constantes, p0 es una sugerencia a los parametros, util para el ajuste</span> +<span class="n">popt1</span><span class="p">,</span> <span class="n">pcov1</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata1</span><span class="p">,</span> <span class="n">recorte1</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrella1</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata1</span><span class="p">,</span> <span class="n">popt1</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt1</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt1</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt1</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt1</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> <span class="c1">#aplicacion gaussiana con los parametros hallados</span> +<span class="n">FWHM1</span><span class="o">=</span><span class="n">FWHM</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">popt1</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> <span class="c1">#valor de FWHM de la gaussiana obtenida </span> +<span class="c1">#parametros para graficar, tamaño, barra de colores, titulos y color.</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 1 fotografÃa"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorte1</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 1 a partir de la gaussiana"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrella1</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li><p>Repita este procedimiento para varias estrellas y presente alguna estadÃstica +sobre las medidas de la FWHM de las distintas gaussianas: histograma, media, mediana, +desviación estándar</p> +</li> +<li><p>Al repetir el procedimiento en cada estrella a blanco y negro y cada una de las BandasRGB se modifican los parametros de cada recorte, rejilla, color y sugerencias p0</p> +</li> +</ul> + +</div> +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 2 (blanco y negro)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [305]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">x2</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">35</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span> +<span class="n">y2</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">35</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span> +<span class="n">y2</span><span class="p">,</span><span class="n">x2</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">meshgrid</span><span class="p">(</span><span class="n">x2</span><span class="p">,</span><span class="n">y2</span><span class="p">)</span> +<span class="n">recorte2</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">Escalagrises3</span><span class="p">[:,:,</span><span class="mi">0</span><span class="p">],</span> <span class="mi">645</span><span class="p">,</span> <span class="mi">535</span><span class="p">,</span> <span class="mi">35</span><span class="p">,</span> <span class="mi">35</span><span class="p">)</span> +<span class="n">xdata2</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">vstack</span><span class="p">((</span><span class="n">x2</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span><span class="n">y2</span><span class="o">.</span><span class="n">ravel</span><span class="p">()))</span> +<span class="n">popt2</span><span class="p">,</span> <span class="n">pcov2</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata2</span><span class="p">,</span> <span class="n">recorte2</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrella2</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata2</span><span class="p">,</span> <span class="n">popt2</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt2</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt2</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt2</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt2</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHM2</span><span class="o">=</span><span class="n">FWHM</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">popt2</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 2 fotografÃa"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorte2</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 2 a partir de la gaussiana"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrella2</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">35</span><span class="p">,</span> <span class="mi">35</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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hgR6yWtl7huGgAAYBhiJ+DotZjk7GFJZw78fUY9DQCAieDMGTqG2AlAajHJ2RclnWP7Oao+WN4o6cezGWZmZrRmzZo527JiEk899VRj2549exrbxlFoYjHLPHjwYGNbtv4rV64sWmamtChEVmSkdNs89NBDjW0nnXRSY9tZZ53V2JYVStmyZUtjW2lxiwMHDqTtxx9/fGPb/v37i5abvU8rVqxobJuZmSl6vX379s05neAY08I9YuigBcdOAI4uxclZRBy0/U5Jf6GqHOxVEXHvyHoGAMAQJGfoEmInAMMs6p6ziLhR0o0j6gsAAECvETsByIy9IAgAAOPCmTMAQJ+QnAEAOovkDADQJyRnAIDOIjkDAPQJyRkAoJOo1ggA6JtOJGdZifasBH3Wli2ztC0rTy/lJcwzWcn0TNafxazHqGVl5rPS/dkwAtk6ZPOV7mvTkPWndIiFbL6mNoJjAACA0ehEcgYAwFz4cgAA0CckZwCAziI5AwD0CckZAKCzSM4AAH1CcgYA6CySMwBAnzRXPwAAAAAATAxnzgAAnUQpfQBA37QmOctKmGel5Pfv3z/RvmQl2ktL3g97zaycfKlxlMsvLTW/Zs2axrZsu2Tv/aFDhxrbDhw4MK9+HSl7f7PXW4xs/TPZe1G63ca1jsBiTDo5s32mpE9KOlVSSFofER8daL9M0m9IOjkitrj6sP2opNdK2i3ppyLirol2GsC8TXo4oa7gi7DJaU1yBgDAQk0hYDgo6bKIuMv28ZLutH1zRNxXJ26vkvSPA89/jaRz6p/vk/Tx+jcAAM/APWcAgM6avbRxlD9DXm/T7JmviNgp6X5J6+rmj0h6j6ozarMulvTJqNwmaY3t00e+IQAAvUByBgBAAdtnS3qRpNttXyzp4Yj40hFPWyfpoYG/N+rbyRwAAE/DZY0AgM4a02WNa23fMfD3+ohYP/gE26skfUbSu1Vd6vh+VZc0AgBQjOQMANBJY6zWuCUizm9qtL1MVWL2qYi43vZ3S3qOpC/VxQTOkHSX7QskPSzpzIHZz6inAQDwDCRnAIDOmkK1Rku6UtL9EXFF3YevSDpl4DkPSDq/rtZ4g6R32r5WVSGQ7RGxaaKdBgB0xsSTs6YS36Wl5EtLnpaWKM/mG7bMrK/ZvDMzM8M7NiGl5fIzxx13XGPbvn37Gtv27t3b2JYFbFkp/dL3YdhwB9l2W8wQDJNEeWFAkvQySW+W9BXbd9fT3h8RNzY8/0ZVZfQ3qCql/9ax9xBA8TFrHMe6SR8/21T2vk196YpuRIUAAMxh0gf+iPi8pDTSioizBx6HpEvH3C0AQE+QnAEAOotvZQEAfUJyBgDoLJIzAECfkJwBADppjNUaAQCYCgahBgAAAIAW4MwZAKCzOHMGAOiT1pTSz2QlzFesWDHyfoyjXLxUXjK9tOx/ZlzrWCLry/79+xvbSoOyQ4cONbZl23oxJe+z8v2ZrD+l72HpfE19OXjwYNHygFEgOQP6bRwl8buyzEzpZ182X9aW9XNcn8NH6+f7opKzeqDNnZIOSToYEeePolMAAMzH0XrwRncROwHIjOLM2csjYssIlgMAwIKQnKGjiJ0AzImCIAAAAADQAotNzkLSTbbvtH3JKDoEAMB8zJbSH/UPMGbETgAaLfayxh+IiIdtnyLpZttfjYhbB59Qf/BcUj9e5MsBAPBtJFPooAXFTgCOLos6cxYRD9e/N0v6rKQL5njO+og4PyLOH0fVQQDA0YszZ+iahcZOk+4fgOkqPnNm+zhJSyJiZ/34VZJ+KZsnItIy5k2WLVvW2JaV0h9Hie+sDPliks/srGI2lECpcSyzNKgZ1zZtku0Xpe/DsLPCWSn90nL5bfmygzPimCaSKXRJSezUd8OOIaXl68fRlh13x1Fmv1Rpufws5hjHMhejz5/9i7ms8VRJn613uKWS/iAi/nwkvQIAAOgfYicAqeLkLCK+IemFI+wLAAAL0udvT9E/xE4AhhnFOGcAAEwc94gBAPqG5AwA0FkkZwCAPiE5AwB0FskZAKBP2lHuDQAAAACOchM9cxYRjWXMS0uXZmXRs/KdWVtW7n8x5VCzUuzZOmbDBbRJ6bbJvvnOtss4hgPIXm8xpetLS+mXKt33x7X+wLhw5gxov8WUmS+ND7vSVmocpe1LY+PScvnj+vzu+nGByxoBAJ3V9YMwAACDSM4AAJ1EtUYAQN9wnRIAAAAAtABnzgAAncWZMwBAn5CcAQA6i+QMANAnJGcAgM4iOQMA9MnEk7OmcpulB9isRHlpSdDMYkqllpaFX7Zs2fCOjVBpydfS+bLhEJYubd5FsyEGsvc+22fGsV8Me82sTHC2/qXlcEtRSh9tRHIGtENpufxhpfRLY6fStuy4m7WVDpc0jmGIslgma8visXHMNyxWGUcs04VjBtEWAAAAALQAlzUCADqJUvoAgL4hOQMAdBbJGQCgT0jOAACdRXIGAOgTkjMAQGeRnAEA+oSCIAAAAADQApw5AwB0FmfOAAB9MtHkbMmSJTruuOPmbNuxY0fjfKtWrWpsy8ZPyMacKB0jK5ONfyFJK1eubGw75phjGtuOPfbYxrbScS4ypWODLF++vLEtG6tt3759jW3Z2BnZ+7R3797Gtqyf+/fvb2wrHVNPkk466aSieUvHDslk82XvRVPbOMYhAeaDao3AZI1jLLNhY2iWjkmWxR1ZWxYjZK+XzVc6VlumdNyxrC2Lc7L4KFu/cYwtK/V7DDQuawQAdNZsgjbKn4ztM23fYvs+2/faflc9/ddtf9X2l21/1vaagXneZ3uD7a/ZfvV4twgAoMtIzgAAnTXp5EzSQUmXRcS5kl4i6VLb50q6WdJ3RcT3SPp7Se+TpLrtjZJeIOkiSb9ru+yrcgBA75GcAQAwTxGxKSLuqh/vlHS/pHURcVNEzF4vdJukM+rHF0u6NiL2RcQ3JW2QdMGk+w0A6AYKggAAOmtM9wistX3HwN/rI2L9kU+yfbakF0m6/Yimn5b0h/XjdaqStVkb62kAADwDyRkAoLPGlJxtiYjzsyfYXiXpM5LeHRE7Bqb/oqpLHz81jo4BAPqN5AwA0EnTqtZoe5mqxOxTEXH9wPSfkvQ6Sa+Mb3fsYUlnDsx+Rj0NAIBnGJqc2b5K1cFmc0R8Vz3tRFWXbJwt6QFJb4iIrcOWFRGNJTxLS4KWln0fVva+SVYONiujKuUl8bNS+sOW22RYedom2XbLys9m2ybb3tnrZaVSs/KsmWyZpYHesFK42f6dvU9Z2ziC0pKSvll5XaBvXH3QXSnp/oi4YmD6RZLeI+mHImL3wCw3SPoD21dIerakcyR9YYJdxhSMMnaatOxYXjrfYkrJl5avz4ZMytqyeKy0rTQGymRxRXZczobMyYYhKm3L9othcVxpnDOOOG+S5hO9X62qwtSg90r6XEScI+lz9d8AAEzUFKo1vkzSmyW9wvbd9c9rJX1M0vGSbq6n/V7dv3slXSfpPkl/LunSiCgf3AddcbWInQAUGHr6KCJurW96HnSxpAvrx9dI+u+SfmGUHQMAYJhJfwsaEZ+XNNdXwTcm83xI0ofG1im0DrETgFKl95ydGhGb6sePSjp1RP0BAGDeunCJClAjdgIw1KILgkRE2G48Otq+RNIl9ePFvhwAAN9CcoYuWkjsBODoUjoI9WO2T5ek+vfmpidGxPqIOD8izic5AwAAR6mi2GlivQPQCqXJ2Q2S3lI/foukPxlNdwAAmJ9xFAPhTBzGiNgJwFDzKaX/aVU3sK61vVHS5ZI+LOk622+T9KCkN8znxWw3lhPNSolmB8vSEuWZ0pLwWZl5qbx0a9af7DVLy8ged9xxRa+XvYfZe7Fr167Gtqzk6549e4peL5PNl637sHKw2X46DqUljUuGmOCMOKaJZAptNMrYqU2yz/txldIvjXOy4YtWrlzZ2LZq1aqituz1sn6WltLPhpnKSts/9dRTjW27d+9ubMvmK90vhn1+Z+3Z+mfzlcYskzzWzKda45saml454r4AALAgJGdoI2InAKUWXRAEAIBpITkDAPRJ6T1nAAAAAIAR4swZAKCzOHMGAOgTkjMAQCdRXREA0DckZwCAziI5AwD0yUSTsyVLljSWGs1KYmZK5ystl5+Vgx1WLj3r6+HDhxvbsjL7WTnY1atXN7adcMIJjW1ZKf2sjGxpqdjNmxvH4UzL5Wcl+Ldt29bYlpXlzZaZlZgdVro/K7Wf7TfZfpG1ZbK+lv5fANNCcgYsXGnp83GUyx92bFm+fHljWxYDZbFMFh+tWbOmse1Zz3pWY9vxxx/f2Jb1M4tJss+3LK7I4pUdO3Y0tm3fvr2xrbTkf2ZYHFMaA2VtiyntPykUBAEAAACAFuCrcABAZ7Xlm04AAEaB5AwA0EkUBAEA9A3JGQCgs0jOAAB9wj1nAAAAANACnDkDAHQWZ84AAH0y8eSsqdRqVoa99OCblcvMLKZcfqZ0PbKSr1mp2LVr1za2nXzyyY1tWZn9rC9Zqdhsm2bLzMrBPvbYY41tWcnXrC+lpVmzfi7mNcexL0769YBxIjkDJmccZfazUvJSHh9mcUdW2j6Lc7LY6aSTTmpsKy2znw0VkNm7d29jWzYs0NatW0felyyuyIaRGjYcVtaexSTZ/pYdM0rzhlEfhzhzBgDoLJIzAECfkJwBADqJao0AgL6hIAgAAAAAtABnzgAAncWZMwBAn5CcAQA6i+QMANAnJGcAgM4iOQMA9MlEk7OI0J49exrbmmQlOpcubV6FrDxrVn41W2ZWZvOYY45pbBvWnpWKzcrlZ+VZTz311Ma2s846q7HttNNOa2w78cQTG9uyEqxZ2+OPP17Uduyxxza2Ze9habn4AwcONLbt37+/sW1YfzKlpWJLy+Vn8wFtRHIGjNY4yuVnw9sMOz5m8cM4SulnQw1lcVVWgj8bMiiLDbPPt6Z4WpK2b9/e2JbFm5ksBspK3mfx0bDYqfQ1s9iptFz+JFEQBAAAAABagMsaAQCdRCl9AEDfkJwBADqL5AwA0CckZwCAziI5AwD0CckZAKCzSM4AAH1CQRAAAAAAaIGhZ85sXyXpdZI2R8R31dM+IOntkmbrnL8/Im4ctqzDhw9r3759c3eksCR+acnwrC0rs5mVIB1WDjYriZ+VhV+1alVjW1a6NSuJf+aZZxa1ZaX0s/cpk5W0zcrPZu9hVn61aR+U8tK0u3fvLlqmlL+/w0rJlsjWP5Nt0yZdKEuL/uLMGdpolLFTm0yjlH4Wd2Vl6LPYac2aNY1tJ510UmPbKaec0tiWxVxZnJMNB5DFuFm8ksWb2fuUlaffu3dvUV+eeuqpxrZsmIRhr1ka45eW2Z/ksWY+kdjVki6aY/pHIuK8+qdTHy4AgO6brdY46h9gBK4WsROAAkOTs4i4VdKTE+gLAAALMunkzPaZtm+xfZ/te22/q55+ou2bbX+9/n1CPd22f9v2Bttftv3iCWwWTBmxE4BSi7nn7J31geaq2YMQAAA9d1DSZRFxrqSXSLrU9rmS3ivpcxFxjqTP1X9L0msknVP/XCLp45PvMlqE2AlAqjQ5+7ik50k6T9ImSb/Z9ETbl9i+w/YdXC4CABilSZ85i4hNEXFX/XinpPslrZN0saRr6qddI+n19eOLJX0yKrdJWmP79DFsCrRfUew0ob4BaImiUvoR8djsY9ufkPSnyXPXS1ovSTMzM2RnAICRmeaXfrbPlvQiSbdLOjUiNtVNj0o6tX68TtJDA7NtrKdtEo4qpbGTbWIn4ChSlJzZPn3gIPQjku4ZXZcAAJifMSVna484Y7G+Dpa/xfYqSZ+R9O6I2DFY5SsigoAaRyJ2AjAf8yml/2lJF6o6WG2UdLmkC22fJykkPSDpHfN9wZIDaVZGdceOHY1tWXnWrDxpVvI1K885rBxs6XABWTnY448/vrEtKxVb2pa9F6VKhwrI3vutW7cWvV5W0jYr+TqsHGxWujXbF7N9Jit5my0za8uUlNkHxmmM1RW3RMT5TY22l6lKzD4VEdfXkx+bDb7ryxY319MfljQ4PskZ9TT02Khjp8I+tKZtXLFTVko/O55npeZLy+yffPLJRfNlQ+1kn2+7du1qbMu2dzZ8z86dOxvbxhE7DXvvS+Px0v20LYYmZxHxpjkmXzmGvgAA0GqujuxXSro/Iq4YaLpB0lskfbj+/ScD099p+1pJ3ydp+8DZE/QUsROAUkWXNQIA0AZTuOfsZZLeLOkrtu+up71fVVJ2ne23SXpQ0hvqthslvVbSBkm7Jb11or0FAHQKyRkAoLMmnZxFxOclNV0X88o5nh+SLh1rpwAAvUFyBgDoLIZoAQD0CckZAKCzSM4AAH1C+TUAAAAAaIHWnDnLSmJmJcOz8p1ZefqsbVhpzyZZP6W8JGhW1jUrfZ7Nl5Whz0q+Zts0U1pqvXT9TjnllMa2rMz+E0880diWlbTNtsvu3bsb26S8dG0m2xez8rR79+4ter3s/6Jp/+5CWVr00xhL6QNYoHGU2Zfy2Kn0GJkdz7O20qGNVq9e3diWxTnZ51u2Xfbt21f0elkMlA2lVBpTZ+sg5fvGpEvpl85XcoxqTXIGAMBCkZwBAPqE5AwA0FkkZwCAPiE5AwB0FskZAKBPKAgCAAAAAC3AmTMAQGdx5gwA0CckZwCATqJaIwCgbyaanNluLMWZlTwdtswmWZnNcRzQh5UEzUrtZ+XkszKk2fqXzpcpLV2aGbbdmmRlXbN1H0fJ12HDL5SWgy1ty9bxwIEDjW3ZPnro0KE5pxMcY5rY/4D2W8yQK+Mo0Z/Nlx3rS+OAxZSTL5mvtG0c8chiytofrUP1cOYMANBZJGcAgD6hIAgAAAAAtABnzgAAncWZMwBAn5CcAQA6i+QMANAnJGcAgE6iWiMAoG+45wwAAAAAWmCiZ86WLFmiY489trGtyVNPPdXYlpVTL9VUMlzKS5Bm80l5ufysvHkme819+/Y1tu3fv7+xLetntv7j+AY760vp0ATZts62S7ath6373r17i14zW27ptsnasv/Dpu3GmQtME/sf0H6lx7LFzFsyNIxUHiNkMVfWVhpXlcZ4WVvpNsvasvdo2Od31j6OtrbgskYAQGd14UALAMB8kZwBADqL5AwA0CckZwCAziI5AwD0CQVBAAAAAKAFOHMGAOgkSukDAPqG5AwA0FkkZwCAPpl4Kf2m0vdZ6dKsbeXKlUV9yUp7ZuXEF1MStHQdd+zYUdT2+OOPN7atWbOmsW358uWNbatXr25sW7q0bHfKSrdu3769se3JJ59sbHviiSca23bu3NnYlpW837NnT2PbsKEQslK5mdLytJls+Illy5Y1tjWt465du4r6AYwCyRkwWqX/U6Ul74e9XhYjlJaMz47nWYyQxVzHHXdcY1sWA2RxR7ZtsmGmstgpW7/seL579+7GtqysfxYfZe+ttLghjEZtkuX5h95zZvtM27fYvs/2vbbfVU8/0fbNtr9e/z5hpD0DAGCI2UsbR/kDLBaxE4BS8ykIclDSZRFxrqSXSLrU9rmS3ivpcxFxjqTP1X8DAAAc7YidABQZmpxFxKaIuKt+vFPS/ZLWSbpY0jX1066R9Pox9REAgDlx5gxtROwEoNSCbhKyfbakF0m6XdKpEbGpbnpU0qkN81wi6RKp/J4kAACORDKFLlhs7ATg6DLvbMn2KkmfkfTuiNhh+1ttERG25zxCRsR6Sesl6ZhjjuEoCgAYGZIztNkoYqem5wDop3klZ7aXqfpw+VREXF9Pfsz26RGxyfbpkjaPq5MAAMyF5AxtRewEoMTQ5MzV1zxXSro/Iq4YaLpB0lskfbj+/SfDlnX48OHGcptZmdWsvPew12uSle/MSumXziflJUGzEqVZudSsZPzmzc2f+Vk59UxWmnbVqlWNbdl7mJX837p1a2Pbgw8+2Nj26KOPNrZlZWRLS9dn80n5+mdDF5SWJs4uIc7e+2OPPbaxrUk2pAEAHI1GGTuVKv3iYvDs3kKWmR2TSuMxqbxcfhY7ZSXxt23b1tiWHSOzGDArNZ8NCZVt7yxuzGKnLVu2NLZl6z7pMvtSeUy2mKEb2mA+Z85eJunNkr5i++562vtVfbBcZ/ttkh6U9Iax9BAAgAZdONDiqETsBKDI0OQsIj4vqelrlFeOtjsAAMwfyRnaiNgJQCnKJwIAOolqjQCAvpnPINQAAKBm+yrbm23fMzDtPNu32b7b9h22L6in2/Zv295g+8u2Xzy9ngMA2o7kDADQWVMahPpqSRcdMe3XJH0wIs6T9J/qvyXpNZLOqX8ukfTxUaw3AKCfuKwRANBZ07isMSJurQcWftpkSavrx8+S9Ej9+GJJn4yqo7fZXjNbSn0yvQUAdMnEk7NhJVPnsnr16sa2rAxnaZnNTFb2fFg59ayc6MzMTGPb3r17G9uy8qWPPPJIY1u23bZv397Ytnbt2sa24447rrEtKyWfrcNjjz3W2JaVy8/K82fldbOyvIsJArN1zMrTZv8v2f6UtWWy/bBJ6f8SMApjSs7W2r5j4O/19aDAmXdL+gvbv6HqqpTvr6evk/TQwPM21tNIztBK2f9UaVsWHw2LC7N4Zc+ePY1t2bE1KxmfxXlZufysn9kQPtnwNtk2zdY9GyogG4Ipa8u2WRZXZTFsFnNJ+b6R7VPj2IcniTNnAIDOGtPBdEtEnL/AeX5W0r+PiM/YfoOqMa7+xei7BgDoM+45AwBg8d4i6fr68f8r6YL68cOSzhx43hn1NAAAnoHkDADQSeMoBrKIM3GPSPqh+vErJH29fnyDpP+1rtr4Eknbud8MANCEyxoBAJ01jXsEbH9a0oWq7k3bKOlySW+X9FHbSyXtVVWZUZJulPRaSRsk7Zb01ol3GADQGSRnAIDOmlK1xjc1NP2zOZ4bki4db48AAH1BcgYA6Ky2VNcCAGAUJpqczczM6MQTT5yzLSvRuXRpczezkuHDSts3yUqlZmU/bafLzcqsZuuRlYPNXjMrQZqVWc1K8J9wwgmNbatWrWpsy7ZpVoo92y+ykq/ZNsu2dVbuNisVm23PYf3JyuFmsu2W7ftZWf9sH21qKxkeAwDQPdmXIaXDF2XHHSk/ZmfHs2wInyyuzJQeW7OhhrLS/dn2zuLR0mEEnnzyyaL5stgpi3EWU0q/dH/rwhd6nDkDAHRWFw60AADMF8kZAKCTFlldEQCA1iE5AwB0FskZAKBPSM4AAJ1FcgYA6BMGoQYAAACAFuDMGQCgszhzBgDok4kmZ8uXL9e6devmbMvKlGdlVDNZCc6stHvpfMNK92fLzebdsmVL0TKz8rQrVqxobMtKvmblSbP3aWZmprGttARrVtZ17969jW2lwxZk5fKHldLPyvZm5X6ztiwoLd1Ps/2pabsRHGOa2P+AhSv9vyktpV963JHKY4vsOJgNQ5StR1b6PYtlVq5c2dhWWtY/i/Gysv6lcc727duLljmuUvrZPjWO/XuSxxrOnAEAOolqjQCAvuGeMwAAAABoAc6cAQA6izNnAIA+ITkDAHQWyRkAoE9IzgAAnUVyBgDoE5IzAEBnkZwBAPpkosnZ/v379cgjjyx4vqyMalYONStDnpVYzWRlPbOSrlJenjVbbraOWfnSrMzq8uXLG9uyEqxZmdXS7Z2tQ7bNMqUl+LPtkpXCHTbcQ1bav3S+rARtVmK2dJsec8wxc04vXTcAQLeUlhrPjklZjCPl8UPp8Sc7DpaWqM9K6WfDFw2LHZuUDH0j5fFRtn7ZkFfZMrP3KNvWUnksk7V14Qu9oRmK7TNt32L7Ptv32n5XPf0Dth+2fXf989rxdxcAgMpsKf1R/wCLRewEoNR8zpwdlHRZRNxl+3hJd9q+uW77SET8xvi6BwBAM5IptBSxE4AiQ5OziNgkaVP9eKft+yWtG3fHAAAYhuQMbUTsBKDUgm68sn22pBdJur2e9E7bX7Z9le0TGua5xPYdtu/Irh0FAGChuKwRbbfY2GlS/QTQDvNOzmyvkvQZSe+OiB2SPi7peZLOU/Xt0G/ONV9ErI+I8yPi/NKbHgEAALpmFLHTpPoKoB3mVa3R9jJVHy6fiojrJSkiHhto/4SkPx1LDwEAaMCZLrQVsROAEkOTM1c1Tq+UdH9EXDEw/fT6mmpJ+hFJ9wxb1qFDh7R169Y527Kyn6Vl7zPjOKAPu2wzKxmarePSpc1vU1a+NCuzmvU1a8teL+tnViq3tPxuJisHm5Wgz96jrC9tKydfWi4f6BIuQ0RbjTJ2mrTS/6nS485iYqdMth6lQxtlx/os7sjio3EM7ZS1ZTFQFouXtpXGXFJ5Kf3SIR/acjyZz5mzl0l6s6Sv2L67nvZ+SW+yfZ6kkPSApHeMoX8AADRqy8EUOAKxE4Ai86nW+HlJc532uHH03QEAYP5IztBGxE4ASo3+ekEAAAAAwILNqyAIAABtxJkzAECfkJwBADqJgiAAgL4hOQMAdBbJGQCgT7jnDAAAAABaYKJnzg4ePKgnnnhizrZsnIeVK1c2tmXjZ2VKx+PI+pmN5SBJMzMzRa9ZKvtGORsDI+tn1lY6Vkc2/kfWz0w23siOHTsa20rXYdeuXWn76tWrG9vaNCZZyVkIzlxgmtj/gPYrHXNMKo8DSsdQzcbeysbzyuKjcYxzVjpWW9aWrfs45hs2xl3W3oXxykpxWSMAoLO6fhAGAGAQyRkAoLNIzgAAfUJyBgDoJKo1AgD6hoIgAAAsgO2rbG+2fc8R03/O9ldt32v71wamv8/2Bttfs/3qyfcYANAVnDkDAHTWlM6cXS3pY5I+OTvB9sslXSzphRGxz/Yp9fRzJb1R0gskPVvSX9p+fkTkd8IDAI5KnDkDAHTW7KWNo/yZx2veKunJIyb/rKQPR8S++jmb6+kXS7o2IvZFxDclbZB0wei2AACgTyZ+5mxY2cxJyQ7ApeX5h8lKjWYlUbP+ZOsxrLR/k9KSr6VtmWwdsmWWlsnNZO/DsFLApeXys/my975027SprD8wHy265+z5kn7Q9ock7ZX08xHxRUnrJN028LyN9TSgc8bx/7aY405Wpj1bbnYcLI0fSmOg0pizdHiC0nUfR9uw934xQzCULLMtuKwRANBZYzrQrrV9x8Df6yNi/ZB5lko6UdJLJH2vpOtsP3ccnQMA9BfJGQAAT7clIs5f4DwbJV0fVbb4BduHJa2V9LCkMweed0Y9DQCAZ+CeMwBAJ43jfrNFnIn7Y0kvlyTbz5e0XNIWSTdIeqPtFbafI+kcSV9Y/NoDAPqIM2cAgM6axv0Dtj8t6UJVlz9ulHS5pKskXVWX198v6S31WbR7bV8n6T5JByVdSqVGAEATkjMAQGdNIzmLiDc1NP1kw/M/JOlD4+sRAKAvSM4AAJ3VhcpbAADM10STM9s65phj5mwrLTOazVdanj5TWhJeyvtTWva01MzMTGNbto6lZfaz18vs27evaJnZ+1s6NEHWNmz9snK/2ftbWia4tMTsYvZvAMDRa1xflJQOKTOOUvPjKJc/jlL6pes+jrbFlMMv3ae6/qUdZ84AAJ3V9YMwAACDSM4AAJ20yOqKAAC0DskZAKCzSM4AAH1CcgYA6CySMwBAn3D3PwAAAAC0AGfOAACdxZkzAECfDE3ObB8j6VZJK+rn/1FEXG77OZKulXSSpDslvTki9mfLWrJkiVasWLHgTo6jvPdiyqKXysqzlpYoLR1KIJOVy8/ev2XLljW2Zdu7ZJ8YtszSkv/Ze5TtF8PW4cCBA41tpe9TqVEPI1G6PGAUSM7QRqOMnfpgMf+n2bylQ+Nk85UOwzSOtkxpKf2utA3T58/++WQ9+yS9IiJeKOk8SRfZfomkX5X0kYj4DklbJb1tbL0EAOAIs9UaR/0DjACxE4AiQ5OzqOyq/1xW/4SkV0j6o3r6NZJeP44OAgAAdAmxE4BS87pe0PaM7bslbZZ0s6R/kLQtIg7WT9koaV3DvJfYvsP2HZO+fAsA0G+cOUNbjSp2mkhnAbTGvAqCRMQhSefZXiPps5K+c74vEBHrJa2XpGXLlnHUAwCMDMkU2mpUsZNtdnLgKLKgao0Rsc32LZJeKmmN7aX1N0BnSHp4HB0EAKAJyRnajtgJwEIMvazR9sn1tz6yvVLSD0u6X9Itkn60ftpbJP3JmPoIAMCcuKwRbUTsBKDUfM6cnS7pGtszqpK56yLiT23fJ+la2/+XpL+TdOWwBUVEY6nyrLx51paVKD948GBj2zgMK/lf2tesTHt2H19pGdlM1s/SZS5fvryxbe/evUWvl7WVltIv3daLmbf0Ps3S4SfGMWwFAByFRhY79d2w42dpufzS1yyNZSY93zjWvXS+Sfel74YmZxHxZUkvmmP6NyRdMI5OAQAwDGe60FbETgBKLeieMwAA2oTkDADQJyRnAIDOIjkDAPQJyRkAoLNIzgAAfcLd/wAAAADQApw5AwB0FmfOAAB9MtHk7PDhw9qzZ8+cbcuWLWucLyu1npV2Ly2LnrVlfRlW9ry0rytXrixaZibra+mwBqVtS5c274bZfpEpLQk/ruEXsvc3M45S+qXbpqncb2kZYGCxqNYI9N+k/8dLy+z34bNoHOvQh+0yaZw5AwB0Fgd+AECfkJwBADqL5AwA0CcUBAEAAACAFuDMGQCgszhzBgDoE5IzAEBnkZwBAPqE5AwA0ElUawQA9M1Ek7OlS5fqhBNOmLMtO8CWlsRfsWJFY1tpifas1PqwICHrz8zMTGPbrl27GttKS61nr5dtm6zsffY+HThwoLFt27ZtjW3Z+u3fv7/o9bJllgZ6iyknn223bH8rfe8z2fvbtM8QHAMA2oZj08KxzdqBM2cAgM4imAAA9AnJGQCgs0jOAAB9QnIGAOgskjMAQJ+QnAEAOovkDADQJwxCDQAAAAAtQHIGAOik2VL6o/4ZxvZVtjfbvmeOtstsh+219d+2/du2N9j+su0Xj2FTAAB6YqKXNR46dKixLHx2QMzKiZcqLUO+mL4sWdKcC2fl67O+lq5H1pfMOMq3b9++vbEt2y/GsV0yWZn5YQFdVi4/K8NfOuTDOC71aloHLivDNE1p/7ta0sckfXJwou0zJb1K0j8OTH6NpHPqn++T9PH6N4CO4XiHSeDMGQCgs6Zx5iwibpX05BxNH5H0HkmDC7lY0iejcpukNbZPH8W6AwD6h4IgAIDOGtM32Wtt3zHw9/qIWJ/NYPtiSQ9HxJeOOBu+TtJDA39vrKdtGlVnAQD9QXIGAMDTbYmI8+f7ZNvHSnq/qksaAQAoRnIGAOisltwD8jxJz5E0e9bsDEl32b5A0sOSzhx47hn1NAAAnoHkDADQSfO9R2wC/fiKpFNm/7b9gKTzI2KL7RskvdP2taoKgWyPCC5pBADMieQMANBZ00jObH9a0oWq7k3bKOnyiLiy4ek3SnqtpA2Sdkt660Q6CQDopIkmZ4cPH96yc+fOB+s/10raMs7X27t370KePvb+LAB9mRt9mdu0+3LWFF8bR7lpJGcR8aYh7WcPPA5Jl467T+i1LZImFjstQJv6IrWrP/RlbvTl2xpjp4kmZxFx8uxj23cs5IbrcWtTf+jL3OjL3NrUFwDAaLU1dmpTX6R29Ye+zI2+zA+XNQIAOqsN95wBADAqJGcAgM4iOQMA9Mk0k7N0QM8paFN/6Mvc6Mvc2tQXYGLaUq0RmKA2fd63qS9Su/pDX+ZGX+bBHNgAAF20fPnyOO2000a+3IceeujOtt6LAADoNy5rBAB0Fl8wAgD6hOQMANBZJGcAgD5ZMo0XtX2R7a/Z3mD7vdPow0BfHrD9Fdt3275jCq9/le3Ntu8ZmHai7Zttf73+fcIU+/IB2w/X2+du26+dUF/OtH2L7fts32v7XfX0iW+bpC8T3za2j7H9BdtfqvvywXr6c2zfXv9P/aHt5ePuC9AGs/edjfIHaCNip2+9dmvipqQ/04gPWhM3DekPsdMQE0/ObM9I+h1Jr5F0rqQ32T530v04wssj4rwp3WNwtaSLjpj2Xkmfi4hzJH2u/ntafZGkj9Tb57yIuHFCfTko6bKIOFfSSyRdWu8n09g2TX2RJr9t9kl6RUS8UNJ5ki6y/RJJv1r35TskbZX0tgn0BZg6kjMcDYidnuZqtSduauqPNPn4oE1xU9YfidgpNY0zZxdI2hAR34iI/ZKulXTxFPrRChFxq6Qnj5h8saRr6sfXSHr9FPsyFRGxKSLuqh/vlHS/pHWawrZJ+jJxUdlV/7ms/glJr5D0R/X0ie0zAICJIHaqtSluSvozcW2Km4b0Z+K6FjtNIzlbJ+mhgb83akpvVi0k3WT7TtuXTLEfg06NiE3140clnTrNzkh6p+0v16fuJ3apwCzbZ0t6kaTbNeVtc0RfpClsG9sztu+WtFnSzZL+QdK2iDhYP2Xa/1PARIzjrBlnztBSxE65tsVN0hRjpzbFTXP0RyJ2Sk3lnrOW+YGIeLGqSwUutf3Pp92hQVFFCtOMFj4u6XmqTgNvkvSbk3xx26skfUbSuyNix2DbpLfNHH2ZyraJiEMRcZ6kM1R9m/qdk3hdoI1IzoCpaG3s1IK4SZpi7NSmuKmhP8ROQ0wjOXtY0pkDf59RT5uKiHi4/r1Z0mdVvWHT9pjt0yWp/r15Wh2JiMfqHfqwpE9ogtvH9jJV/9Cfiojr68lT2TZz9WWa26Z+/W2SbpH0UklrbM9WX53q/xQwSSRnOEoQO+VaEzdJ04sP2hQ3NfWH2Gm4aSRnX5R0Tl0hZbmkN0q6YQr9kO3jbB8/+1jSqyTdk881ETdIekv9+C2S/mRaHZn9h679iCa0fWxb0pWS7o+IKwaaJr5tmvoyjW1j+2Tba+rHKyX9sKrruG+R9KP106a6zwCTRHKGowSxU641cZM0tfigNXFT1h9ip+E8jQNRXTbztyTNSLoqIj408U5U/Xiuqm98pGrMtz+YdF9sf1rShZLWSnpM0uWS/ljSdZL+iaQHJb0hIsZ+s2lDXy5Udeo5JD0g6R0D1y6Psy8/IOlvJH1F0uF68vtVXa880W2T9OVNmvC2sf09qm5anVH15cp1EfFL9b58raQTJf2dpJ+MiH3j7AswbcuWLYsTThj97QqPP/74nTGd6r1AI2Knb71+a+KmpD8XavLxQWvipiH9IXYaYirJGQAAi7Vs2bJYs2bNyJe7ZcsWkjMAwFQsHf4UAADah8sQAQB9Q3IGAOgskjMAQJ+QnAEAOovkDADQJ4xzBgAAAAAtwJkzAEBnceYMANAnJGcAgM4iOQMA9AnJGQCgk6jWCADoG+45AwAAAIAW4MwZAKCzOHMGAOgTkjMAQGeRnAEA+oTkDADQWSRnAIA+ITkDAHQWyRkAoE8oCAIAAAAALcCZMwBAJ1FKHwDQNyRnAIDOIjkDAPQJyRkAoLNIzgAAfUJyBgDoLJIzAECfUBAEAAAAAFqA5AwA0FmzRUFG+TOM7atsb7Z9z8C0X7f9Vdtftv1Z22sG2t5ne4Ptr9l+9Xi2BACgD0jOAACdNI7EbJ6XSV4t6aIjpt0s6bsi4nsk/b2k90mS7XMlvVHSC+p5ftf2zKi2AQCgX0jOAACdNY3kLCJulfTkEdNuioiD9Z+3STqjfnyxpGsjYl9EfFPSBkkXjG4LAAD6hIIgAIDOamlBkJ+W9If143WqkrVZG+tpAAA8A8kZAABPt9b2HQN/r4+I9fOZ0fYvSjoo6VNj6RkAoNdIzgAAnTWmM2dbIuL8hc5k+6ckvU7SK+PbHXtY0pkDTzujngYAwDNwzxkAoLOmVBDkGWxfJOk9kv5VROweaLpB0httr7D9HEnnSPrColccANBLnDkDAHTVX0haO4blbskabX9a0oWqLn/cKOlyVdUZV0i62bYk3RYRPxMR99q+TtJ9qi53vDQiDo2hzwCAHnBLb6YGAAAAgKMKlzUCAAAAQAuQnAEAAABAC5CcAQAAAEALkJwBAAAAQAuQnAEAAABAC5CcAQAAAEALkJwBAAAAQAuQnAEAAABAC/z/jRVXeCerfbkAAAAASUVORK5CYII= +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 3 (blanco y negro)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [306]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorte3</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">Escalagrises3</span><span class="p">[:,:,</span><span class="mi">0</span><span class="p">],</span> <span class="mi">560</span><span class="p">,</span> <span class="mi">320</span><span class="p">,</span> <span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">)</span> +<span class="n">x3</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">15</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span> +<span class="n">y3</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">15</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span> +<span class="n">y3</span><span class="p">,</span><span class="n">x3</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">meshgrid</span><span class="p">(</span><span class="n">x3</span><span class="p">,</span><span class="n">y3</span><span class="p">)</span> +<span class="n">xdata3</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">vstack</span><span class="p">((</span><span class="n">x3</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span><span class="n">y3</span><span class="o">.</span><span class="n">ravel</span><span class="p">()))</span> +<span class="n">popt3</span><span class="p">,</span> <span class="n">pcov3</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata3</span><span class="p">,</span> <span class="n">recorte3</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrella3</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata3</span><span class="p">,</span> <span class="n">popt3</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt3</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt3</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt3</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt3</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHM3</span><span class="o">=</span><span class="n">FWHM</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">popt3</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 3 fotografÃa"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorte3</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 3 a partir de la gaussiana"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrella3</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 4 (blanco y negro)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [307]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorte4</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">Escalagrises3</span><span class="p">[:,:,</span><span class="mi">0</span><span class="p">],</span> <span class="mi">442</span><span class="p">,</span> <span class="mi">370</span><span class="p">,</span> <span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">)</span> +<span class="n">x4</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">15</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span> +<span class="n">y4</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">15</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span> +<span class="n">y4</span><span class="p">,</span><span class="n">x4</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">meshgrid</span><span class="p">(</span><span class="n">x4</span><span class="p">,</span><span class="n">y4</span><span class="p">)</span> +<span class="n">xdata4</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">vstack</span><span class="p">((</span><span class="n">x4</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span><span class="n">y4</span><span class="o">.</span><span class="n">ravel</span><span class="p">()))</span> +<span class="n">popt4</span><span class="p">,</span> <span class="n">pcov4</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata4</span><span class="p">,</span> <span class="n">recorte4</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrella4</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata4</span><span class="p">,</span> <span class="n">popt4</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt4</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt4</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt4</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt4</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHM4</span><span class="o">=</span><span class="n">FWHM</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">popt4</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 4 fotografÃa"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorte4</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 4 a partir de la gaussiana"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrella4</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 5 (blanco y negro)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [308]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorte5</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">Escalagrises3</span><span class="p">[:,:,</span><span class="mi">0</span><span class="p">],</span> <span class="mi">320</span><span class="p">,</span> <span class="mi">455</span><span class="p">,</span> <span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">)</span> +<span class="n">x5</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">15</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span> +<span class="n">y5</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">15</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span> +<span class="n">y5</span><span class="p">,</span><span class="n">x5</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">meshgrid</span><span class="p">(</span><span class="n">x5</span><span class="p">,</span><span class="n">y5</span><span class="p">)</span> +<span class="n">xdata5</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">vstack</span><span class="p">((</span><span class="n">x5</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span><span class="n">y5</span><span class="o">.</span><span class="n">ravel</span><span class="p">()))</span> +<span class="n">popt5</span><span class="p">,</span> <span class="n">pcov5</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata5</span><span class="p">,</span> <span class="n">recorte5</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrella5</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata5</span><span class="p">,</span> <span class="n">popt5</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt5</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt5</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt5</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt5</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHM5</span><span class="o">=</span><span class="n">FWHM</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">popt5</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 5 fotografÃa"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorte5</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 5 a partir de la gaussiana"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrella5</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 6 (blanco y negro)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [309]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorte6</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">Escalagrises3</span><span class="p">[:,:,</span><span class="mi">0</span><span class="p">],</span> <span class="mi">535</span><span class="p">,</span> <span class="mi">335</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span> +<span class="n">x6</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">10</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span> +<span class="n">y6</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">10</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span> +<span class="n">y6</span><span class="p">,</span><span class="n">x6</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">meshgrid</span><span class="p">(</span><span class="n">x6</span><span class="p">,</span><span class="n">y6</span><span class="p">)</span> +<span class="n">xdata6</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">vstack</span><span class="p">((</span><span class="n">x6</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span><span class="n">y6</span><span class="o">.</span><span class="n">ravel</span><span class="p">()))</span> +<span class="n">popt6</span><span class="p">,</span> <span class="n">pcov6</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata6</span><span class="p">,</span> <span class="n">recorte6</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrella6</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata6</span><span class="p">,</span> <span class="n">popt6</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt6</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt6</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt6</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt6</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHM6</span><span class="o">=</span><span class="n">FWHM</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">popt6</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 6 fotografÃa"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorte6</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 6 a partir de la gaussiana"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrella6</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 7 (blanco y negro)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [310]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorte7</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">Escalagrises3</span><span class="p">[:,:,</span><span class="mi">0</span><span class="p">],</span> <span class="mi">540</span><span class="p">,</span> <span class="mi">345</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span> +<span class="n">x7</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">10</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span> +<span class="n">y7</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">10</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span> +<span class="n">y7</span><span class="p">,</span><span class="n">x7</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">meshgrid</span><span class="p">(</span><span class="n">x7</span><span class="p">,</span><span class="n">y7</span><span class="p">)</span> +<span class="n">xdata7</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">vstack</span><span class="p">((</span><span class="n">x7</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span><span class="n">y7</span><span class="o">.</span><span class="n">ravel</span><span class="p">()))</span> +<span class="n">popt7</span><span class="p">,</span> <span class="n">pcov7</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata7</span><span class="p">,</span> <span class="n">recorte7</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrella7</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata7</span><span class="p">,</span> <span class="n">popt7</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt7</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt7</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt7</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt7</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHM7</span><span class="o">=</span><span class="n">FWHM</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">popt7</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 7 fotografÃa"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorte7</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 7 a partir de la gaussiana"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrella7</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 8 (blanco y negro)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [311]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorte8</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">Escalagrises3</span><span class="p">[:,:,</span><span class="mi">0</span><span class="p">],</span> <span class="mi">620</span><span class="p">,</span> <span class="mi">306</span><span class="p">,</span> <span class="mi">20</span><span class="p">,</span> <span class="mi">20</span><span class="p">)</span> +<span class="n">x8</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">20</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span> +<span class="n">y8</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">20</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span> +<span class="n">y8</span><span class="p">,</span><span class="n">x8</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">meshgrid</span><span class="p">(</span><span class="n">x8</span><span class="p">,</span><span class="n">y8</span><span class="p">)</span> +<span class="n">xdata8</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">vstack</span><span class="p">((</span><span class="n">x8</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span><span class="n">y8</span><span class="o">.</span><span class="n">ravel</span><span class="p">()))</span> +<span class="n">popt8</span><span class="p">,</span> <span class="n">pcov8</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata8</span><span class="p">,</span> <span class="n">recorte8</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrella8</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata8</span><span class="p">,</span> <span class="n">popt8</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt8</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt8</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt8</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt8</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHM8</span><span class="o">=</span><span class="n">FWHM</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">popt8</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 8 fotografÃa"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorte8</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 8 a partir de la gaussiana"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrella8</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">20</span><span class="p">,</span> <span class="mi">20</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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7dvX1F8J0XlE5/4xKL40tfgjh07iuIBli+fybU/W3bt2lW8fakuczACNwK8NTNvqS6Se3NEXJ+Zd1XF3UuA77bFnwucVt1eAHycmV0TS5LUXA9MtrCrYa6IOCcivhkRmyLiHZM8vigirqoevykiTummPUmSOjHbF/LOzK3jI2iZuZvWhWXXVA//MfB2WiNz49YBl2fLjcCKiFhd65OgvmDuJKlbHRdwETEI/Cmtbw1PBy6IiNMnhL0O2JGZT6f1gfWBTtuTJKlTPSjgVkbExrbb+qnarhLw5wE3RcQ6YEtm3jYhbA3wYNvvm/lhwaeGMHeSVIduDqE8E9iUmfcBRMSnaH2DeFdbzDrgfdX9vwU+FhGRnk0uSZpFPfjY2Z6ZZxwpKCKWAZ8B3kLrsMp30Tp8UkcncydJXevmEMqZfFv4g5jq6us7gbITeSRJmociYohW8XZFZn4WeBpwKnBbRNwPnAzcEhEnAluAtW2rn1wtU7OYO0nqWt9MYlIdfrK+uj/HvZEkNcVcXEagmlXyEuDuzPxw1Y9vACe0xdwPnFHNQnkN8KZqROYFwM7M3Dqrnda80p43STq6dFPAzeTbwvGYzRGxADgW+P5kG8vMDcAGgMHBQQ8TkCTVZg6OPvsp4FXANyLi1mrZuzLz2inir6V1CYFNtC4j8Jqe91BzobbcqT1v8jIC0tGlmwLu68BpEXEqrTeb84FfmRBzDXAh8FXgFcA/ewy3JGm2zfZHT2Z+BZj2cJLMPKXtfgJv7HG3NPfMnSR1reMCLjNHIuJNwHXAIHBpZt4ZEb8HbMzMa2gdPvJXEbEJeJTWG5UkSdJRx9xJUh26OgeuOhTk2gnL3tN2/wDwn7ppQ5KkbjmAoX5h7iSpW30zicls6/VEKZ1sf/HixUXxQ0NDRfF79+4tigcYGxsril+woOwlNTg4WBQPcODAgeJ1SpUme4sWLSqK37NnT1E8wHe+852i+NLntvT1BGV/i9LXklQnCzhJUlMctQWcJOnoMBezUEqS1CsWcJKkxrOAkyQ1RTcX8pYkSZIkzSJH4CRJjecInCSpKSzgJEmNZwEnSWoKCzhJUuNZwEmSmsICTpLUaM5CKUlqEicxkSRJkqR5whE4SVLjOQInSWoKCzhJUuNZwEmSmsICTpLUeBZwkqSmsICTJDWeBZwkqSn6soCbjRnDSrcfEUXxS5cuLYrvZJ2xsbGi+KGhoaJ4gJGRkeJ1em1wcLAo/glPeEJxG8PDw8XrlFi8eHHxOocOHeppfOnrCfrz9SFJOjqU5mb9tn2YnS+X/AKrefqygJMkqS5eRkCS1CQWcJKkxrOAkyQ1hQWcJKnxLOAkSU3hhbwlSZIkaZ5wBE6S1HiOwEmSmsICTpLUeBZwkqSmsICTJDWas1BKkprEAk6S1HgWcJKkpuh4EpOIWBsRX46IuyLizoh48yQxZ0XEzoi4tbq9p7vuSpIkzU/mTpLq0M0I3Ajw1sy8JSKWAzdHxPWZedeEuH/LzJd20Y4kSV1xBE59wtxJUtc6LuAycyuwtbq/OyLuBtYAE9+EJEmaUxZw6gfmTpLqUMs5cBFxCvA84KZJHv6JiLgNeAh4W2beWUeb/W7ZsmXF6yxcuLAovjQhGR0dLYoHGBwcLIov7dPY2FhRPMCiRYuK4kv3AWB4eLgo/uDBg0XxCxaU/+sNDQ0Vxc9GwrpkyZIZxx44cKCHPZGmZwGnftP03CkiehoPMDBQdibQbPSp1GzkTaVtdPJ+6Xvs7Oq6gIuIZcBngLdk5q4JD98CPCUz90TEecDngNOm2M56YH11v9tuSZIEOAul+k8duVN73iTp6NLxJCYAETFE6w3oisz87MTHM3NXZu6p7l8LDEXEysm2lZkbMvOMzDyjmz5JkiT1q7pyJ/Mm6ejV8QhctIbJLgHuzswPTxFzIvBIZmZEnEmrYPx+p21KktQJR+DUD8ydJNWhm0Mofwp4FfCNiLi1WvYu4MkAmfkJ4BXAGyJiBNgPnJ9+ikqSZtlsf/RExFrgcmAVkMCGzPxIRHwI+AVgGPg28JrMfKxa553A64BR4Lcz87pZ7bRmg7mTpK51MwvlV4BpT1bLzI8BH+u0DUmS6jAH+e+k08UD1wPvzMyRiPgA8E7gdyLidOB84NnAScA/RcQzMrN89in1LXMnSXXo6hw4SZLmg/GJTOq6zaC9rZl5S3V/N3A3sCYzv5iZI1XYjcDJ1f11wKcy82BmfgfYBJxZ+xMhSZr3LOAkSSq3MiI2tt2mnA1wmuniXwt8vrq/Bniw7bHN1TJJkg5Ty3XgJEnqVz26jMD2mcz+N9V08RHxblqHWV5Rd8ckSc1mASdJary5mANiquniI+Ii4KXA2W2TU2wB1ratfnK1TJKkw3gIpSSp8Wb7HLippouPiHOAtwMvy8x9batcA5wfEYsi4lRaF27+Wq1PgiSpERyBkyQ13hyMwE01XfxHgUXA9a0ajxsz8/WZeWdEfBq4i9ahlW90BkpJ0mT6soCLCKoPthlZsKB8NwYHB4vXKbF48eLidUr7tGjRoqL4pUuXFsUDHDx4sCh+eHi4KH50tDw/GRgoGzjev39/cRulr6nS56k0Hsr/3iX/Q9BZgrtkyZIZx5a+NqT5bJrp4q+dZp2LgYt71impC6WfvaXxneRlQ0NDRfGln+2l+wDln6WledChQ4eK4gFGRkaOHNRmbGysuI3Sdby0YXf6soCTJKlOJguSpKawgJMkNVqPZqGUJGlOWMBJkhrPAk6S1BTOQilJkiRJ84QjcJKkxnMETpLUFBZwkqTGs4CTJDWFBZwkqfEs4CRJTWEBJ0lqNGehlCQ1iZOYSJIkSdI84QicJKnxHIGTJDWFBZwkqfEs4CRJTWEBJ0lqPAs4SVJT9G0Bt2DBzLs2ODhYvP2IKIofGCg7XXDRokVF8VC+H0uWLOlpPMDw8HBR/O7du4viDx48WBQP5c/TY489VtzGscceWxRf2qddu3YVxXfSRqkDBw70dJ2xsbHi7Ut1sYCTfqg0B4LyPGjhwoVF8YsXLy6Kh/K8prSNkly0U6Wfvfv37y9uY9++fUXxneRmpUpzAt/DD+ckJpIkSZI0T/TtCJwkSXXwMgKSpCbpuoCLiPuB3cAoMJKZZ0x4PICPAOcB+4CLMvOWbtuVJGmmLODUL8ybJHWrrhG4F2Xm9ikeOxc4rbq9APh49VOSpFlhAac+Y94kqWOzcQjlOuDybH163hgRKyJidWZunYW2JUmygNN8Yt4kaVp1TGKSwBcj4uaIWD/J42uAB9t+31wtO0xErI+IjRGx0Q9aSZLUULXnTT3qp6Q+VccI3E9n5paIOAG4PiLuycwbSjeSmRuADQCDg4NWcJKk2vjFoPpI7XlTRPgCl44iXY/AZeaW6uc24GrgzAkhW4C1bb+fXC2TJKnnxmehrPMmdcq8SVK3uirgImJpRCwfvw+8BLhjQtg1wKuj5YXATo/jliTNJgs49QPzJkl16PYQylXA1a0Zb1kA/HVmfiEiXg+QmZ8ArqU1Fe4mWtPhvqbLNiVJkuYj8yZJXeuqgMvM+4DnTLL8E233E3hjN+1IktQNR83UD8ybJNVhNi4j0HPVN1lFFi5cWBS/aNGiovihoaGieIBTTjmlKH758uVF8U94whOK4gH27t1bFP/973+/p/EABw4cKIovfZ4ADh48WBQ/PDxcFN/J66P0dV76ml2woPztYGRkpHgdaS5YwKnpSj4jBgbKz6Ap/dw65phjiuKPO+64oniAJz7xiUXxxx9/fFH84sWLi+IBxsbGiuJ37txZFL99+1SXD5zajh07iuJ37dpV3EZpblb6nux7+OEaUcBJkjQdP/wlSU1hASdJajQnHpEkNUkdF/KWJEmSJM0CR+AkSY3nCJwkqSks4CRJjWcBJ0lqCgs4SVLjWcBJkprCc+AkSY03PpFJXbcjiYi1EfHliLgrIu6MiDdXy4+PiOsj4t7q53HV8oiIj0bEpoi4PSKe3+OnRJI0T1nASZJUvxHgrZl5OvBC4I0RcTrwDuBLmXka8KXqd4BzgdOq23rg47PfZUnSfGABJ0lqtLpH32YyApeZWzPzlur+buBuYA2wDvhkFfZJ4OXV/XXA5dlyI7AiIlbX/FRIkhrAc+AkSY3Xg3PgVkbExrbfN2TmhskCI+IU4HnATcCqzNxaPfQwsKq6vwZ4sG21zdWyrUiS1MYCTpLUeD0o4LZn5hlHCoqIZcBngLdk5q6IaO9TRoSzq0iSivRlARcRtH/IHcmSJUuK21i0aFFR/IIFZU/VmjVriuIBVq1adeSgNk972tOK4levLj8aZ9++fUXx9913X1H8N7/5zaJ4gMcee6wofmxsrLiNkZGRoviBgbKjkUdHR4viO+Gse9IPzcX/Q0QM0SrersjMz1aLH4mI1Zm5tTpEclu1fAuwtm31k6tl0oyU5E2Dg4PF21+4cGFR/PLly4viTzzxxKJ4gFNPPbUo/slPfnJR/IoVK4riAYaHh4viH3744aL473znO0XxnSjNgaA8rynNzUpe3+OanAd5DpwkSTWLVrZxCXB3Zn647aFrgAur+xcCf9e2/NXVbJQvBHa2HWopSdIP9OUInCRJdZnpxCM1+yngVcA3IuLWatm7gPcDn46I1wEPAK+sHrsWOA/YBOwDXjOrvZUkzRsWcJKkxpvtAi4zvwJMdczP2ZPEJ/DGnnZKktQIFnCSpMZr8rkQkqSji+fASZIkSdI84QicJKnxHIGTJDWFBZwkqfEs4CRJTWEBJ0lqtDmahVKSpJ6wgJMkNZ4FnCSpKTqexCQinhkRt7bddkXEWybEnBURO9ti3tN1jyVJkuYhcydJdeh4BC4zvwk8FyAiBoEtwNWThP5bZr6003YkSeqWI3DqB+ZOkupQ1yGUZwPfzswHatqeJEm1sYBTHzJ3ktSRugq484Erp3jsJyLiNuAh4G2ZeedkQRGxHlgPMDAwwNDQ0IwbX7x4cVlvgWXLlhXFL1hQ9lQ96UlPKooHeNrTnlYUf/bZZxfFr169uigeYHh4uCj+tttuK4rft29fUTyU9+nAgQPFbRw6dKgofu/evcVtlBodHS2KL01Yx8bGiuI7XUeaCxZw6kNd5U7teVP1+4wbHhwcLOspsGjRoqL4FStWFMWvWbOmKB7gWc96VlH8s5/97KL4E044oSgeynOOb3/728VtlCrNUfbs2VPcxv79+4viS/Ms843DdV3ARcRC4GXAOyd5+BbgKZm5JyLOAz4HnDbZdjJzA7ABYGhoyE9aSVItnIVS/aaO3Kk9b4oIX+DSUaTjSUzanAvckpmPTHwgM3dl5p7q/rXAUESsrKFNSZKk+crcSVLH6jiE8gKmOAQgIk4EHsnMjIgzaRWM36+hTUmSZswROPUZcydJHeuqgIuIpcB/BH6jbdnrATLzE8ArgDdExAiwHzg//RSVJM0yP3rUL8ydJHWrqwIuM/cCT5yw7BNt9z8GfKybNiRJ6pb5r/qFuZOkbtU1C6UkSX3LAk6S1BR1TGIiSZIkSZoFjsBJkhrNywhIkprEAk6S1HgWcJKkprCAkyQ1ngWcJKkpPAdOkiRJkuaJvhyBiwiOOeaYGccvWFC+G4sXLy6KX7ZsWVH8scceWxQPsHbt2qL4008/vSi+dB+g/Fvrffv2FcXfddddRfEADz74YFH8okWLitvYv39/UfzAQNl3IaOjo0XxAGNjY0Xxpf8XpdvvdB1pLjgCJ/1Q6WcWwNDQUFH80qVLi+JXrlxZFA/wlKc8pSj+R37kR4riTzrppKJ4KM8fIqIoftu2bUXxUJ43lebIAIODg0XxpftdGg/Nft/vywJOkqQ6NfmDXJJ0dLGAkyQ1mrNQSpKaxAJOktR4FnCSpKZwEhNJkiRJmiccgZMkNZ4jcJKkprCAkyQ1ngWcJKkpLOAkSY1nASdJagoLOElSozkLpSSpSZzERJIkSZLmCQs4SVLjjY/C1XU7koi4NCK2RcQdbcueGxE3RsStEbExIs6slkdEfDQiNkXE7RHx/B4+FZKkec4CTpLUeLNdwAGXAedMWPZB4Hcz87nAe6rfAc4FTqtu64GP17HPkqRm6ttz4EZHR2cc28m5DWNjY8XrlHjCE55QvM7SpUuL4hcvXlzcRqmIKIov7VPpPgOsWLGiKH7Hjh3FbZQqfZ4GBsq/Oyl9zfb6NQ69/z+V6jLbr7/MvCEiTpm4GBj/cDgWeKi6vw64PFudvDEiVkTE6szcOju9VROUfg6VKv3cKu3PggXlKemiRYuK4pcsWVIUv2zZsqJ4KH+ejjnmmKL4hQsXFsUDDA4OFsV3kqP0+vWnw/VtASdJUl16UMCtjIiNbb9vyMwNR1jnLcB1EfGHtI6A+clq+Rrgwba4zdUyCzhJ0uNYwEmSVG57Zp5RuM4bgP+cmZ+JiFcClwAvrr9rkqQm8xw4SVKj1X3+WxejeRcCn63u/w1wZnV/C7C2Le7kapkkSY8zowJuitm0jo+I6yPi3urncVOse2EVc29EXFhXxyVJmqk+KeAeAn62uv8fgHur+9cAr65mo3whsNPz3+Y38yZJvTTTEbjLePxsWu8AvpSZpwFfqn4/TEQcD7wXeAGtbxrfO9UbliRJvTIHlxG4Evgq8MyI2BwRrwN+HfijiLgN+ANaM04CXAvcB2wC/hz4zV48B5pVl2HeJKlHZnQO3BSzaa0DzqrufxL4F+B3JsT8HHB9Zj4KEBHX03pDu7Kz7kqSVG4OZqG8YIqH/o9JYhN4Y297pNlk3iSpl7qZxGRV2yEeDwOrJomZamatx4mI9VTfRpZOdypJktTnepY3STq61DILZWZmRHT19WY1/fIGgIULF3rBKElSbbwOofpJ3XlTt9uSNL90MwvlIxGxGqD6uW2SGGfWkiTNqT6ahVJHN/MmSbXopoC7htaUyFQ//26SmOuAl0TEcdVJuC+plkmSNGss4NQHzJsk1WKmlxGYbDat9wP/MSLupXUh0vdXsWdExF8AVCfh/j7w9er2e+Mn5kqSJDWReZOkXprpLJRTzaZ19iSxG4Ffa/v9UuDSjnonSVINHDXTbDJvktRLtUxiUrexsTH2798/4/hjjjmmuI3h4eGi+D179vR0+wA7duwoit+6tew6r6tWTTbh1fRGRkaK4rdv314Uv3v37qJ4KJ+l9NChQ8VtlO73bCSHAwNlRzyXxo+NjRXFg0mx5g9fq2q6ktd4J/8Po6OjRfGln72leRbAo4+WDU4+/PDDxW2UOnDgQFH8tm2TnQo5tZ07dxbFA+zbt68ovjQHgs5yiBK+hx+uLws4SZLq5Ie/JKkpLOAkSY3mxCOSpCbpZhZKSZIkSdIscgROktR4jsBJkprCAk6S1HgWcJKkprCAkyQ1ngWcJKkpLOAkSY1nASdJagonMZEkSZKkecIROElSo3kZAUlSk1jASZIazwJOktQUFnCSpMazgJMkNUVfFnCZyejo6Izjh4eHi9soXWdwcLAo/r777iuKBxgaGiqKX7JkSVH8KaecUhQPsHfv3qL4u+66qyi+k+dp27ZtRfEHDhwobuPgwYNF8SWv19kSEXPdBalvWMCp6Upe4518ZpV+Lu7evbso/pFHHimKB7j33nuL1ymxcuXK4nVKn6cHHnigKP673/1uUTzAjh07iuL3799f3MbIyEhR/NjYWHEb+iEnMZEkSZKkeaIvR+AkSaqTI3CSpKawgJMkNZqzUEqSmsQCTpLUeBZwkqSm8Bw4SZIkSZonHIGTJDWeI3CSpKawgJMkNZ4FnCSpKSzgJEmNZwEnSWqKI54DFxGXRsS2iLijbdmHIuKeiLg9Iq6OiBVTrHt/RHwjIm6NiI019luSpBkZn4Wyzps0HXMnSb00k0lMLgPOmbDseuBHM/PHgG8B75xm/Rdl5nMz84zOuihJkjSvXIa5k6QeOWIBl5k3AI9OWPbFzBypfr0ROLkHfZMkqRaOwGk2mTtJ6qU6LiPwWuDzUzyWwBcj4uaIWF9DW5IkFbOAU58xd5LUsa4mMYmIdwMjwBVThPx0Zm6JiBOA6yPinupbqcm2tR5YDzAwMMDg4OCM+3Ho0KGyjgOjo6NF8RFRFL9ly5aieICFCxcWxe/bt68o/lvf+lZRPMCePXuK4h9++OGi+IceeqgoHmD37t1F8QcPHixuo/T1URrfiZL/CWj9H5WYjX2Q5spsF10RcSnwUmBbZv5o2/LfAt4IjAL/mJlvr5a/E3hdtfy3M/O6We2wZk1duVN73gRlr/GxsbGyTlP+Wbpz586i+M2bNxfFd2LHjh1F8cuXLy9uozQn3b59e1F8J3lTaRt79+4tbmNkZOTIQW1K35P94uxwHRdwEXERrQ+ns3OKZzUzt1Q/t0XE1cCZwKQFXGZuADYALFiwwL+SJKk2c/DhfxnwMeDy8QUR8SJgHfCczDxYJehExOnA+cCzgZOAf4qIZ2Sm36o0TJ25U3veFBHmTdJRpKNDKCPiHODtwMsyc9JhoIhYGhHLx+8DLwHumCxWkqQmmewcKOANwPsz82AVs61avg74VGYezMzvAJtoJe1qEHMnSXWZyWUErgS+CjwzIjZHxOtofau4nNbQ/q0R8Ykq9qSIuLZadRXwlYi4DfgarUNFvtCTvZAkaQo9uozAyojY2HabyblKzwB+JiJuioh/jYgfr5avAR5si9tcLdM8Ze4kqZeOeAhlZl4wyeJLpoh9CDivun8f8JyueidJUg16cAjl9g6meF8AHA+8EPhx4NMR8dS6O6a5Z+4kqZe6msREkqT5oE9OgN8MfLY69+lrETEGrAS2AGvb4k6ulkmS9Dh1XEZAkqS+1ieXEfgc8CKAiHgGsBDYDlwDnB8RiyLiVOA0WofPSZL0OI7ASZJUs+ocqLNonSu3GXgvcClwaUTcAQwDF1ajcXdGxKeBu2hNL/9GZ6CUJE3FAk6S1HizfQjlFOdAAfzqFPEXAxf3rkeSpKawgJMkNVqXhz1KktRXLOAkSY1nASdJagonMZEkSZKkeaIvR+AGBgZYtmzZjOMHBweL2zh06FBR/KOPPloUf8wxxxTFAzzwwANF8Tt27CiKj4iieICRkZGi+AMHDhTF7927tygeYM+ePUXxjz32WHEbo6Nl8weUvp5K46F8BKH0793J/9HixYtnHFv6WpLq5Aicmq7kNV76GQfln1uln9WdGB4eLor/3ve+VxS/aNGioniAsbGxovjS52nXrl1F8Z2sU5rLQflnfOnzpMP1ZQEnSVKdLOAkSU1hASdJajwLOElSU1jASZIazVkoJUlN4iQmkiRJkjRPOAInSWo8R+AkSU1hASdJajwLOElSU1jASZIazwJOktQUFnCSpMazgJMkNYWTmEiSJEnSPOEInCSp0byMgCSpSSzgJEmNZwEnSWqKvizgRkdH2blz54zjFywo343Fixf3NH7Xrl1F8VCeYIyMjBTFDwyUHzE7PDxcFD82NtbT7QMcPHiwKH5wcLC4jVKl+10aD63/i17q5PUhzRcWcNIPdfL/UJpzHDhwoCi+k8/F0nzgscceK4rvJH8ofW4PHTpUFF+6z52sU9onKP/7+Z7cnb4s4CRJqpPJgiSpKfzKXZIkSZLmiSMWcBFxaURsi4g72pa9LyK2RMSt1e28KdY9JyK+GRGbIuIddXZckqSZGJ/EpM6bNB1zJ0m9NJMRuMuAcyZZ/seZ+dzqdu3EByNiEPhT4FzgdOCCiDi9m85KktQJCzjNssswd5LUI0cs4DLzBuDRDrZ9JrApM+/LzGHgU8C6DrYjSVJXLOA0m8ydJPVSN+fAvSkibq8OEzhuksfXAA+2/b65WjapiFgfERsjYqMfjpIkqYFqy53a86ZedFRS/+q0gPs48DTgucBW4I+67UhmbsjMMzLzjIjodnOSJP2AI3DqA7XmTu15Uw19kzSPdHQZgcx8ZPx+RPw58A+ThG0B1rb9fnK1TJKkWWXRpblm7iSpLh2NwEXE6rZffxG4Y5KwrwOnRcSpEbEQOB+4ppP2JEnqlLNQqh+YO0mqyxFH4CLiSuAsYGVEbAbeC5wVEc8FErgf+I0q9iTgLzLzvMwciYg3AdcBg8ClmXlnL3ZCkqTpWHRpNpk7SeqlIxZwmXnBJIsvmSL2IeC8tt+vBR43Ta4kSVJTmTtJ6qWOzoGTJGk+cQROktQUfVnAZSaHDh2acfzBgweL2xgdHS2KHxsbK4qfjT7t27evuI1eGxwcLIofGRkpbuPAgQNF8aV96mSd0r/dwED56ae9TkBLX+PSfGIBJ/1QJ/8PpZ8RJXlcJ9vvpI3Sz97Z+Kwu3e/SfKOTdWbj9aHu9GUBJ0lSnSzgJElNYQEnSWo0Z46UJDVJpxfyliRJU4iISyNiW0Q8bqr4iHhrRGRErKx+j4j4aERsiojbI+L5s99jSdJ8YQEnSWq8ObgO3GXAORMXRsRa4CXAd9sWnwucVt3WAx/veoclSY1lASdJarzZLuAy8wbg0Uke+mPg7bSuBTZuHXB5ttwIrJhw0WdJkn7Ac+AkSY3Xg3PgVkbExrbfN2TmhulWiIh1wJbMvC0i2h9aAzzY9vvmatnWujorSWoOCzhJUuP1oIDbnplnzDQ4IpYA76J1+KQkSR2zgJMkqfeeBpwKjI++nQzcEhFnAluAtW2xJ1fLJEl6HAs4SVKj9cNlBDLzG8AJ479HxP3AGZm5PSKuAd4UEZ8CXgDszEwPn5QkTcoCTpLUeLNdwEXElcBZtM6V2wy8NzMvmSL8WuA8YBOwD3jNrHRSkjQvWcBJkhpvtgu4zLzgCI+f0nY/gTf2uk+SpGboywJuYGCAhQsXzjj+0KFDxW0cOHCgp/FLly4tigcYHR0tih8eHu7p9gEmzJR2RENDQ0XxnfSpNBHrJHEbGxsrXqfflO7DwED5VUVK/n5zfQibjm6+/qTu9Pp/aGRkpHid0hyiNKcpjYfeP0+dbH828ibNLq8DJ0mSJEnzRF+OwEmSVCe/UZYkNYUFnCSp0fphFkpJkupiASdJajwLOElSU3gOnCRJkiTNE47ASZIazxE4SVJTWMBJkhrPAk6S1BQWcJKkxrOAkyQ1xRELuIi4FHgpsC0zf7RadhXwzCpkBfBYZj53knXvB3YDo8BIZp5RS68lSZohZ6HUbDN3ktRLMxmBuwz4GHD5+ILM/OXx+xHxR8DOadZ/UWZu77SDkiRJ88xlmDtJ6pEjFnCZeUNEnDLZYxERwCuB/1BzvyRJqo0jcJpN5k6Seqnbc+B+BngkM++d4vEEvhgRCfxZZm6YakMRsR5YX90v6sTQ0FBRfCeGh4eL4jvpU+l+l/apNB5gcHCwKL40SRobGyuKBzh06FDP2yjdj9HR0Z7GQ/l+zEafBga8EonmBws49ZFacqf2vKkfzcb/XGkbpXnWbPC9SZ3otoC7ALhymsd/OjO3RMQJwPURcU9m3jBZYPUGtQFgwYIFvpolSbUxSVIfqSV3as+bqmJP0lGi46/PI2IB8EvAVVPFZOaW6uc24GrgzE7bkySpU+MTmdR1kzph7iSpDt0c//Ri4J7M3DzZgxGxNCKWj98HXgLc0UV7kiRJ85m5k6SuHbGAi4grga8Cz4yIzRHxuuqh85lwCEBEnBQR11a/rgK+EhG3AV8D/jEzv1Bf1yVJOrK6R98cgdORmDtJ6qWZzEJ5wRTLL5pk2UPAedX9+4DndNk/SZK6ZtGl2WTuJKmXup3ERJKkvmcBJ0lqCgs4SVLjWcBJkprCizhJkiRJ0jzhCJwkqfEcgZMkNYUFnCSp0Zw5UpLUJBZwkqTGs4CTJDWF58BJkiRJ0jzRlyNwY2NjHDhwYMbxixcvLm5j0aJFRfELFpQ9VWNjY0XxUP4NcclzBHDo0KGieIDBwcHidXpteHi4KH5oaKi4jdK/Xyd/714bGCj7fqaTfShZxxEQzSVff5J8H1BT9GUBJ0lSnUzcJElNYQEnSWo8CzhJUlNYwEmSGs1ZKCVJTeIkJpIkSZI0TzgCJ0lqPEfgJElN4QicJKnxxg+jrOt2JBFxaURsi4g72pZ9KCLuiYjbI+LqiFjR9tg7I2JTRHwzIn6uN8+CJKkJLOAkSY032wUccBlwzoRl1wM/mpk/BnwLeCdARJwOnA88u1rnf0ZE/13DRZLUFyzgJEmNN9sFXGbeADw6YdkXM3Ok+vVG4OTq/jrgU5l5MDO/A2wCzqxv7yVJTWIBJ0lSuZURsbHttr5w/dcCn6/urwEebHtsc7VMkqTHcRITSVKj9egyAtsz84xOVoyIdwMjwBX1dkmSdDSwgJMkNV6/zEIZERcBLwXOzh92aguwti3s5GqZJEmP05cFXGZuP3jw4AOTPLQS2D5x4cGDB3vfqSnabnC7HbW9b9++OWt7Kvv375+ztudJu7PV9lN6vH1pSv1QwEXEOcDbgZ/NzPY3y2uAv46IDwMnAacBX5uDLmr+2g5MljeBn2m23dx2j4a2J82d+rWAe9JkyyNiY6eHrHRrrto+Gvf5aG37aNxnabbMdgEXEVcCZ9E6V24z8F5as04uAq6PCIAbM/P1mXlnRHwauIvWoZVvzMzRWe2w5rWp8ibwM822m9vu0dx2XxZwkiTNZ5l5wSSLL5km/mLg4t71SJLUFBZwkqTG64dDKCVJqsN8K+A2HIVtH437fLS2fTTus9RzPZqFUpov/Eyz7aa2e9S2HX6oSZKabOHChblq1apat7l58+abPW9UkjQXvJC3JEmSJM0T8+0QSkmSinm0iSSpKfpuBC4izomIb0bEpoh4xySPL4qIq6rHb4qIU2pqd21EfDki7oqIOyPizZPEnBUROyPi1ur2njrarrZ9f0R8o9ruxkkej4j4aLXft0fE82tq95lt+3NrROyKiLdMiKltvyPi0ojYFhF3tC07PiKuj4h7q5/HTbHuhVXMvRFxYU1tfygi7qme06sjYsUU60779+mg3fdFxJa25/S8Kdad9v+hw7avamv3/oi4dYp1O95nqd+MnwdX103qJ+ZO5k69yJ3mKm+apm1zp3F1f6h1+YE4CHwbeCqwELgNOH1CzG8Cn6junw9cVVPbq4HnV/eXA9+apO2zgH/o0b7fD6yc5vHzgM8DAbwQuKlHz//DwFN6td/AvweeD9zRtuyDwDuq++8APjDJescD91U/j6vuH1dD2y8BFlT3PzBZ2zP5+3TQ7vuAt83g7zHt/0MnbU94/I+A99S9z9689dNtaGgoV69eXesN2DjX++XNW6a5k7lT73Knucqbpmnb3Km69dsI3JnApsy8LzOHgU8B6ybErAM+Wd3/W+DsiNYVUbuRmVsz85bq/m7gbmBNt9ut0Trg8my5EVgREatrbuNs4NuZ+UDN2/2BzLwBeHTC4va/6SeBl0+y6s8B12fmo5m5A7geOKfbtjPzi5k5Uv16I3ByyTY7bXeGZvL/0HHb1f/NK4ErO+ibNG/04sNT6iPmTlMzd+oid5qrvGmqtmfoqMid+q2AWwM82Pb7Zh7/RvCDmOoFtBN4Yp2dqA4teB5w0yQP/0RE3BYRn4+IZ9fYbAJfjIibI2L9JI/P5Lnp1vlM/YLs1X4DrMrMrdX9h4HJpoubjf1/La1v6iZzpL9PJ95UHYJw6RSHPvR6n38GeCQz753i8V7ssySpXuZO5k5zlTvNdt4E5k6Ak5g8TkQsAz4DvCUzd014+BZaQ+R7quNuPwecVlPTP52ZWyLiBOD6iLin+gZgVkTEQuBlwDsnebiX+32YzMyImPWvtyPi3cAIcMUUIXX/fT4O/D6tf/TfpzUc/9outteJC5j+G6Q5fU1KdXLUTOodc6ejL3eag7wJzJ1+oN9G4LYAa9t+P7laNmlMRCwAjgW+X0fjETFE6w3oisz87MTHM3NXZu6p7l8LDEXEyjrazswt1c9twNW0hoDbzeS56ca5wC2Z+cgkfevZflceGT+kofq5bZKYnu1/RFwEvBT4v3KKLG8Gf58imflIZo5m5hjw51Nsr5f7vAD4JeCqafpY6z5Lc8lDKNVg5k7mTrOaO81F3lRty9yp0m8F3NeB0yLi1OpbjfOBaybEXAOMz6LzCuCfp3rxlKiOab0EuDszPzxFzInjx4xHxJm0nr+u3wAjYmlELB+/T+sE0TsmhF0DvDpaXgjsbBs6r8OU3yj0ar/btP9NLwT+bpKY64CXRMRx1ZD5S6plXYmIc4C3Ay/LzH1TxMzk71Pabvsx+L84xfZm8v/QqRcD92Tm5in6V/s+S3PJAk4NZu5k7jRrudNc5U3VtsydxtX9oVbDh+J5tGYx+jbw7mrZ79F6oQAsBv4G2AR8DXhqTe3+NK0h2duBW6vbecDrgddXMW8C7qQ1o82NwE/W1PZTq23eVm1/fL/b2w7gT6vn5RvAGTU+50tpvakc27asJ/tN641uK3CI1nHJr6N1HP6XgHuBfwKOr2LPAP6ibd3XVn/3TcBramp7E61jpcf/5uOzdJ0EXDvd36fLdv+q+jveTuuNZfXEdqf6f+i27Wr5ZeN/37bY2vbZm7d+ui1YsCBXrlxZ6w1nofTWR7fJPiswdwJzJ+gid5qi3Z7nTdO0be5U3aJqUJKkRhoaGsoVK1bUus3t27ffnJln1LpRSZJmwElMJEmN1vZNqSRJ854FnCSp8SzgJElNYQEnSWo8CzhJUlNYwEmSGs8CTpLUFP12GQFJkiRJ0hQcgZMkNZ4jcJKkprCAkyQ1mrNQSpKaxAJOktR4FnCSpKbwHDhJkiRJmiccgZMkNZ4jcJKkprCAkyQ1ngWcJKkpLOAkSY1nASdJagoLOElSozkLpSSpSZzERJIkSZLmCUfgJEmN5wicJKkpLOAkSY1nASdJagoPoZQkNd74eXB13Y4kIi6NiG0RcUfbsuMj4vqIuLf6eVy1PCLioxGxKSJuj4jn9/CpkCTNcxZwkqTGm+0CDrgMOGfCsncAX8rM04AvVb8DnAucVt3WAx+vZaclSY1kASdJUs0y8wbg0QmL1wGfrO5/Enh52/LLs+VGYEVErJ6VjkqS5h3PgZMkNVofXUZgVWZure4/DKyq7q8BHmyL21wt24okSRNYwEmSGq8HBdzKiNjY9vuGzNxQ0J+MiL6oKiVJ84sFnCSp8XpQwG3PzDMK13kkIlZn5tbqEMlt1fItwNq2uJOrZZIkPY7nwEmSGm8OJjGZzDXAhdX9C4G/a1v+6mo2yhcCO9sOtZQk6TCOwEmSVLOIuBI4i9ahlpuB9wLvBz4dEa8DHgBeWYVfC5wHbAL2Aa+Z9Q5LkuaN6JMTuyVJ6omI+AKwsubNbs/MiZcJkCSp5yzgJEmSJGme8Bw4SZIkSZonLOAkSZIkaZ6wgJMkSZKkecICTpIkSZLmCQs4SZIkSZonLOAkSZIkaZ6wgJMkSZKkeeL/B9BDyBuizaGZAAAAAElFTkSuQmCC +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 9 (blanco y negro)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [312]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorte9</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">Escalagrises3</span><span class="p">[:,:,</span><span class="mi">0</span><span class="p">],</span> <span class="mi">545</span><span class="p">,</span> <span class="mi">360</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span> +<span class="n">x9</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">10</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span> +<span class="n">y9</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">10</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span> +<span class="n">y9</span><span class="p">,</span><span class="n">x9</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">meshgrid</span><span class="p">(</span><span class="n">x9</span><span class="p">,</span><span class="n">y9</span><span class="p">)</span> +<span class="n">xdata9</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">vstack</span><span class="p">((</span><span class="n">x9</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span><span class="n">y9</span><span class="o">.</span><span class="n">ravel</span><span class="p">()))</span> +<span class="n">popt9</span><span class="p">,</span> <span class="n">pcov9</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata9</span><span class="p">,</span> <span class="n">recorte9</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrella9</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata9</span><span class="p">,</span> <span class="n">popt9</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt9</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt9</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt9</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt9</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHM9</span><span class="o">=</span><span class="n">FWHM</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">popt9</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 9 fotografÃa"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorte9</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 9 a partir de la gaussiana"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrella9</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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pKkYePuAauqbVV1TfN8B3ADsLpZ/UfAecBwQWcAH6qBK4Gjkhy7pG+CpoptJ0lzWTCAJVkG/DGDq3snAS9PclLbFZMkaUYLAWxVko1Dj7PnOnaSE4CnAVclOQPYWlVfmbXZamDz0Ost/CSw6SHGtpOk+YwyBPFkYFNVfRsgycUMrvRd32bFJEma0cIkHNurav1CGyU5HPgo8EYGwxLfzGD4oTQf206S5jRKANvXVb29xrU3Vw/nvIIoSdL+mNQsiElWMAhfF1XVpUl+BjgR+EoSgDXANUlOBrYCa4d2X9Ms00PTgm0n203SQ9eSzYJYVRuqav0oVxQlSeqyDBLWB4AbquodAFX1tap6VFWdUFUnMGhUP72qbgUuA361mQ3xFODOqto2qfqr+2w3SQ9do/SAeVVPkjRRE+gBezbwSuBrSb7cLHtzVV0+x/aXAy8GNgH3AGe1XkN1mW0nSXMaJYB9EViX5EQGvzzOBH651VpJkjRk3AGsqj4HZIFtThh6XsA5LVdL08O2k6Q5LRjAqmpXktcCVwDLgAur6rrWayZJUmMS94BJ+8u2k6T5jPRFzM2Qi7mGXUiS1CoDmKaNbSdJc1mySTgkSZIkSfMbqQdMkqRJmdQ09JIktcEAJknqPAOYJKkvDGCSpM4zgEmS+sJ7wCRJkiRpTOwBkyR1nj1gkqS+aCWAJWHlypVtFP1ju3btarX8I488stXyYTwNihUrVrRa/n333ddq+QAHH3xw68do+30CWL683esdybzfGdv58qX5GMAkjePvUNvtgcMOO6zV8gEOOeSQ1o/Rdjsc4O677261/HG0Yffs2bPP5faASZI6zVkQJUl9YgCTJHWeAUyS1BdOwiFJkiRJY2IPmCSp8+wBkyT1hQFMktR5BjBJUl8YwCRJnWcAkyT1hQFMktRpzoIoSeoTJ+GQJEmSpDGxB0yS1Hn2gEmS+sIAJknqPAOYJKkvDGCSpM4zgEmS+sIAJknqPAOYJKkvnIRDkiRJksbEHjBJUqc5Db0kqU8MYJKkzjOASZL6wgAmSeo8A5gkqS+8B0ySJEmSxsQeMElS59kDJknqCwOYJKnzDGCSpL4wgEmSOs1ZECVJfWIAkyR1ngFMktQXTsIhSZIkSWNiD5gkqfPsAZMk9UUrASwJBx98cBtF/9j999/favlHH310q+UDHHnkka0fo23r1q1r/Rgnn3xy68e48847Wz/Gxo0bWy3/5ptvbrV8G8CaJD9/kpYvb7/f4BGPeESr5T/hCU9otXyAE044ofVj/PCHP2z9GNdee22r5W/durXV8gHuvffefS63B0yS1HkGMElSX3gPmCSp02ZmQVzKx0KSrE3y6STXJ7kuyRua5X+Y5OtJvprkY0mOGtrn/CSbktyY5EXtvSOSpGlmAJMkaW+7gHOr6iTgFOCcJCcBnwCeVFVPBr4BnA/QrDsTeCJwKvDeJMsmUnNJUqcZwCRJnTfuHrCq2lZV1zTPdwA3AKur6uNVtavZ7EpgTfP8DODiqrqvqr4DbALav4FVkjR1vAdMktR5LdwDtirJ8Mw4G6pqw742THIC8DTgqlmrfh34q+b5agaBbMaWZpkkSQ9iAJMkdV4LAWx7Va1faKMkhwMfBd5YVXcNLf9dBsMUL1rqikmS+s0AJknqvEnMgphkBYPwdVFVXTq0/NeA04EX1E8qthVYO7T7mmaZJEkP4j1gkiTNkiTAB4AbquodQ8tPBc4DXlJV9wztchlwZpKVSU4E1gFfGGedJUnTwR4wSVKnjTpxxhJ7NvBK4GtJvtwsezPwbmAl8IlBRuPKqnpNVV2X5BLgegZDE8+pqt3jrrQkqfsWDGBJ1gIfAo4BisGNyu9qu2KSJM0YdwCrqs8B2ceqy+fZ563AW1urlKaGbSdJ8xmlB2zmu1CuSXIEcHWST1TV9S3XTZIkYDL3gEkHwLaTpDktGMCqahuwrXm+I8kNDKbW9ZeIJGksDGCaJradJM1nUZNwzPNdKJIkSZrFtpOk2UaehGOu70IZWn82cHbzfMkqKEmSPWCaRvO1nYbbTZIeWkYKYHN9F8qwqtoAbABYtmyZfyklSUtiQrMgSgdkobbTcLspiR9w6SFklFkQ9/ldKJIkjYsBTNPEtpOk+YxyD9jMd6E8P8mXm8eLW66XJEnStLLtJGlOo8yCONd3oUiSNBb2gGma2HaSNJ+RJ+GQJGlSDGCSpL4wgEmSOs8AJknqCwOYJKnTnAVRktQni/oiZkmSJEnS/rMHTJLUefaASZL6wgAmSeo8A5gkqS+mNoAddFC7oyd3797davkA99xzT+vHOOaYY1ot/7TTTmu1fICzzjqr9WN84xvfaP0YO3bsaLX8zZs3t1r+4HtFpckwgEndNo6/EQcffHDrx1izZk2r5Z9++umtlg/wwhe+sPVjfOtb32r9GH/xF3/Ravl33nlnq+UD3HvvvftcPrUBTJL00GEAkyT1hZNwSJIkSdKY2AMmSeo0p6GXJPWJAUyS1HkGMElSXxjAJEmdZwCTJPWFAUyS1HkGMElSXzgJhyRJkiSNiT1gkqTOswdMktQXBjBJUqc5C6IkqU8MYJKkzjOASZL6wnvAJEmSJGlM7AGTJHWePWCSpL4wgEmSOs8AJknqCwOYJKnTnIRDktQnBjBJUucZwCRJfeEkHJIkSZI0JvaASZI6zx4wSVJfGMAkSZ1nAJMk9YUBTJLUeQYwSVJfeA+YJKnTZmZBXMrHQpKsTfLpJNcnuS7JG5rlj0jyiSTfbP49ulmeJO9OsinJV5M8veW3RZI0pQxgkiTtbRdwblWdBJwCnJPkJOBNwD9U1TrgH5rXAKcB65rH2cD7xl9lSdI0MIBJkjpv3D1gVbWtqq5pnu8AbgBWA2cAf95s9ufAS5vnZwAfqoErgaOSHLvEb4MkqQe8B0yS1Hkt3AO2KsnGodcbqmrDvjZMcgLwNOAq4Jiq2tasuhU4pnm+Gtg8tNuWZtk2JEkaYgCTJHVeCwFse1WtX2ijJIcDHwXeWFV3JRmuUyVxdhBJ0qK0FsB2797dVtEALF/ebnbcuXNnq+UDPPDAA60f49BDD221/DVr1rRaPsAhhxzS+jEe+chHtn6Mgw5yxK+0vyYxC2KSFQzC10VVdWmz+HtJjq2qbc0Qw9ua5VuBtUO7r2mWSVoi4/g7evjhh7da/vHHH99q+QBPfvKTWz/GihUrWj/GT/3UT7Va/jjOYS62CCVJmiWDrq4PADdU1TuGVl0GvKp5/irgfwwt/9VmNsRTgDuHhipKkvRjDkGUJHXaqBNnLLFnA68Evpbky82yNwNvAy5J8hvATcDLmnWXAy8GNgH3AGeNtbaSpKlhAJMkdd64A1hVfQ7IHKtfsI/tCzin1UpJknrBACZJ6rxJ3AMmSVIbvAdMkiRJksbEHjBJUufZAyZJ6gsDmCSp8wxgkqS+MIBJkjptQrMgSpLUCgOYJKnzDGCSpL4YeRKOJMuSfCnJ37ZZIUmSpD6w7SRpXxbTA/YG4Abg4S3VRZKkfbIHTFPKtpOkvYzUA5ZkDfCLwPvbrY4kSXubuQ9sqR5S22w7SZrLqD1g7wTOA46Ya4MkZwNnN88PuGKSJM0wNGkKvZN52k7D7SZJDy0L9oAlOR24raqunm+7qtpQVeurar0BTJK0VJa698swp7aN0nYabjeNsWqSOmCUIYjPBl6S5LvAxcDzk/xlq7WSJEmaXradJM1pwQBWVedX1ZqqOgE4E/hUVb2i9ZpJktSwB0zTxLaTpPn4PWCSpM4zNEmS+mJRAayq/hH4x1ZqIknSHAxgmla2nSTNZg+YJKnzDGCSpL4Y6XvAJEmSJEkHzh4wSVKnOXGGJKlPDGCSpM4zgEmS+sIAJknqPAOYJKkvWglgVcWePXvaKPrHduzY0Wr5K1asaLV8gCStH2P58nYz9ubNm1stH+Caa65p/Rg33nhj68e45ZZbWi2/7c/sOD6vkiTNZdeuXa0fY/v27a2W/8UvfrHV8mE8bdhxtP9uuummVsvfuXNnq+XPxx4wSVLn2QMmSeoLA5gkqfMMYJKkvjCASZI6zVkQJUl9YgCTJHWeAUyS1Bd+EbMkSZIkjYk9YJKkzrMHTJLUFwYwSVLnGcAkSX1hAJMkdZ4BTJLUFwYwSVKnOQuiJKlPnIRDkiRJksbEHjBJUufZAyZJ6gsDmCSp8wxgkqS+MIBJkjrPACZJ6gvvAZMkdd7MRBxL9VhIkguT3Jbk2qFlT01yZZIvJ9mY5ORmeZK8O8mmJF9N8vQW3wpJ0pQzgEmStLc/A06dtewPgN+rqqcC/7l5DXAasK55nA28bzxVlCRNI4cgSpI6bRLT0FfVZ5OcMHsx8PDm+ZHALc3zM4AP1aCSVyY5KsmxVbVtPLWVJE0TA5gkqfNaCGCrkmwcer2hqjYssM8bgSuSvJ3BCJJnNctXA5uHttvSLDOASZL2YgCTJHVeCwFse1WtX+Q+vwX8dlV9NMnLgA8AP7/UFZMk9Zv3gEmSOm/ck3DM4VXApc3z/w6c3DzfCqwd2m5Ns0ySpL0YwCRJGs0twL9qnj8f+Gbz/DLgV5vZEE8B7vT+L0nSXByCKEnqvHFPwpHkw8BzGdwrtgW4AHg18K4ky4GdDGY8BLgceDGwCbgHOGuslZUkTRUDmCSp0yY0C+LL51j1L/axbQHntFsjSVJfGMAkSZ037gAmSVJbvAdMkiRJksaklR6wJBx0ULvZ7vbbb2+1/COOOKLV8gGOPvro1o9xxx13tFr+5z73uVbLB7jxxhtbP8ZNN93U+jG2bNnSavmHH354q+W3/X9amo89YFK3jeP/6P3339/6MbZubXcC08svv7zV8gGuueaa1o/xox/9qPVj3Hzzza2Wf/fdd7da/nwcgihJ6jwDmCSpLwxgkqTOM4BJkvrCACZJ6rRJzIIoSVJbvKlDkiRJksbEHjBJUufZAyZJ6gsDmCSp8wxgkqS+MIBJkjrPACZJ6gsDmCSp8wxgkqS+cBIOSZIkSRqTkQJYkqOSfCTJ15PckOSZbVdMkiT4yTT0S/mQ2mbbSdJcRh2C+C7g76vq3yY5GDisxTpJkvQghiZNIdtOkvZpwQCW5Ejg54BfA6iq+4H7262WJEk/YQDTNLHtJGk+owxBPBG4Hfhgki8leX+Sh83eKMnZSTYm2egfSknSUnIIoqbMgm2n4XbTZKooaVJGCWDLgacD76uqpwF3A2+avVFVbaiq9VW1PskSV1OSJGlqLNh2Gm43TaKCkiZnlAC2BdhSVVc1rz/C4JeKJEljYQ+YpoxtJ0lzWjCAVdWtwOYkj28WvQC4vtVaSZLUcBZETRvbTpLmM+osiK8DLmpm8fk2cFZ7VZIk6cEMTZpCtp0k7dNIAayqvgw4RlmSJGkEtp0kzWXUHjBJkibGHjBJUl8YwCRJnWcAkyT1hQFMktR5BjBJUl8YwCRJnebMhZKkPhnle8AkSZIkSUvAHjBJUufZAyZJ6otWAlhVsXv37jaK/rGdO3e2Wv7DH/7wVssHWLFiRevHuP3221st/3vf+16r5QOsXLmy9WPcddddrR9j2bJlrZZ/zDHHtFp+klbLl+ZjAJPUdtsS2m8PtN1+Bbj55ptbP8aePXtaP8Z9993Xavm7du1qtfz52AMmSeo8A5gkqS8MYJKkzjOASZL6wkk4JEmSJGlM7AGTJHWa09BLkvrEACZJ6jwDmCSpLwxgkqTOM4BJkvrCe8AkSZ03MwxxqR4LSXJhktuSXDtr+euSfD3JdUn+YGj5+Uk2JbkxyYtaeAskST1hD5gkSXv7M+A9wIdmFiR5HnAG8JSqui/Jo5rlJwFnAk8EjgM+meRxVdX+lxZJkqaOPWCSpM4bdw9YVX0W+MGsxb8FvK2q7mu2ua1ZfgZwcVXdV1XfATYBJy/d2UuS+sQAJknqtKUOX00AW5Vk49Dj7BGq8jjgOUmuSvKZJM9olq8GNg9tt6VZJknSXhyCKEnqvBYm4dheVesXuc9y4BHAKcAzgEuSPGapKyZJ6jd7wCRJGs0W4NIa+AKwB1gFbAXWDm23plkmSdJeDGCSpM4b9z1gc/hr4HkASR4HHAxsBy4DzkyyMsmJwDrgCwd+1pKkPnIIoiSp88b9PWBJPgw8l8G9YluAC4ALgQubqenvB15Vg4pdl+QS4HpgF3COMyBKkuZiAJMkddoB9lrt7zFfPseqV8yx/VuBt7ZXI0lSXxjAJEmdN+4AJklSW7wHTJIkSZLGxB4wSVLn2QMmSeoLA5gkqfMMYJKkvjCASZI6zwAmSeoLA5gkqdMmMQuiJEltcRIOSZIkSRoTe8AkSZ1nD5gkqS8MYJKkzjOASZL6orUAtmfPnraKBuCxj31sq+UfdthhrZYPcNttt7V+jPvuu6/V8g8//PBWywe4++67Wz/G/fff3/ox2v5M3X777a2W/8ADD7RavjQfA5ikcdi9e3er5e/cubPV8sd1jHHo8+99e8AkSZ3X5z/EkqSHFifhkCRJkqQxsQdMktRpTkMvSeoTA5gkqfMMYJKkvjCASZI6zwAmSeoL7wGTJEmSpDGxB0yS1Hn2gEmS+sIAJknqPAOYJKkvRhqCmOS3k1yX5NokH05ySNsVkyQJfjIL4lI+pLbZdpI0lwUDWJLVwOuB9VX1JGAZcGbbFZMkaYYBTNPEtpOk+Yw6Ccdy4NAky4HDgFvaq5IkSdLUs+0kaZ8WDGBVtRV4O3AzsA24s6o+Pnu7JGcn2Zhko1cXJUlLyR4wTZNR2k7D7aZJ1FHS5IwyBPFo4AzgROA44GFJXjF7u6raUFXrq2p9kqWvqSTpIcsApmkySttpuN00iTpKmpxRhiD+PPCdqrq9qh4ALgWe1W61JEn6CQOYpoxtJ0lzGmUa+puBU5IcBtwLvACwu1ySNBaGJk0h206S5jTKPWBXAR8BrgG+1uyzoeV6SZIkTSXbTpLmM9IXMVfVBcAFLddFkqR9sgdM08a2k6S5jBTAJEmaJAOYJKkvDGCSpM4zgEmS+sIAJknqPAOYJKkvRpmGXpIkSZK0BOwBkyR1mtPQS5L6xAAmSeo8A5gkqS9aCWAHHXQQD3vYw9oo+seWL283O+7atavV8gF27tw59cfYvXt3q+UDPPDAA60fY+XKla0f45577mm1/IMOandE8Z49e1otX5qPAUxSH/i7TOA9YJKkKTAzDHGpHgtJcmGS25Jcu4915yapJKua10ny7iSbknw1ydNbeAskST1hAJMkaW9/Bpw6e2GStcAvADcPLT4NWNc8zgbeN4b6SZKmlAFMktR54+4Bq6rPAj/Yx6o/As4Dhgs5A/hQDVwJHJXk2KU4b0lS/zgJhySp01qaBXFVko1DrzdU1Yb5dkhyBrC1qr6SZHjVamDz0OstzbJtS1VZSVJ/GMAkSZ3XQgDbXlXrR904yWHAmxkMP5Qkab8ZwCRJWthPAycCM71fa4BrkpwMbAXWDm27plkmSdJeDGCSpM6b9NTNVfU14FEzr5N8F1hfVduTXAa8NsnFwM8Cd1aVww8lSftkAJMkdd64A1iSDwPPZXCv2Bbggqr6wBybXw68GNgE3AOcNZZKSpKmkgFMktR54w5gVfXyBdafMPS8gHParpMkqR8MYJKkTmtpFkRJkibC7wGTJEmSpDGxB0yS1Hn2gEmS+sIAJknqPAOYJKkvDGCSpM4zgEmS+sIAJknqPAOYJKkvnIRDkiRJksbEHjBJUqc5Db0kqU8MYJKkzjOASZL6wgAmSeo8A5gkqS8MYJKkzjOASZL6wkk4JEmSJGlM7AGTJHWePWCSpL4wgEmSOs1ZECVJfWIAkyR1ngFMktQXrQSw3bt3b7/jjjtuWsQuq4DtiznGHXfcsbhKtW/R59BBiz6HnTt3tlSVA7Lo87j33ntbqsp+6+Ln6fhJV0CSemo7sJh2E3Tz78RieQ7d0IdzgG6exz7bTq0EsKp65GK2T7Kxqta3UZdx8Ry6ow/n0YdzkJaSPWDqs8W2m6Affyc8h27owznAdJ2HQxAlSZ1nAJMk9YUBTJLUeQYwSVJfdCWAbZh0BZaA59AdfTiPPpyDtCScBVHapz78nfAcuqEP5wBTdB7xj5okqcsOPvjgevSjH72kZW7evPnqablXQJLUL13pAZMkaU5eLJQk9YUBTJLUeQYwSVJfHDTJgyc5NcmNSTYledMk67K/kqxN8ukk1ye5LskbJl2n/ZVkWZIvJfnbSddlfyQ5KslHknw9yQ1JnjnpOi1Wkt9uPkfXJvlwkkMmXSepC2buA1uqhzStbDt1x7S3m8C206RMLIAlWQb8MXAacBLw8iQnTao+B2AXcG5VnQScApwzpecB8AbghklX4gC8C/j7qnoC8BSm7FySrAZeD6yvqicBy4AzJ1srqRsMYJJtpw6a9nYT2HaaiEn2gJ0MbKqqb1fV/cDFwBkTrM9+qaptVXVN83wHgw/u6snWavGSrAF+EXj/pOuyP5IcCfwc8AGAqrq/qn440Urtn+XAoUmWA4cBt0y4PpKk7rDt1BHT3m4C206TNMkAthrYPPR6C1P2n2+2JCcATwOumnBV9sc7gfOAPROux/46Ebgd+GAzHOD9SR426UotRlVtBd4O3AxsA+6sqo9PtlbS5C1175c9YJpitp26451Md7sJbDtNzETvAeuTJIcDHwXeWFV3Tbo+i5HkdOC2qrp60nU5AMuBpwPvq6qnAXcDUzU2PsnRDK5knggcBzwsySsmWyupGwxgUv9Ma9upJ+0msO00MZMMYFuBtUOv1zTLpk6SFQx+gVxUVZdOuj774dnAS5J8l8Fwhucn+cvJVmnRtgBbqmrmCtpHGPxSmSY/D3ynqm6vqgeAS4FnTbhOUicYwCTAtlNX9KHdBLadJmaSAeyLwLokJyY5mMENc5dNsD77JUkYjJ29oareMen67I+qOr+q1lTVCQx+Dp+qqs5fPRhWVbcCm5M8vln0AuD6CVZpf9wMnJLksOZz9QKm7GZYqS0GMAmw7dQJfWg3gW2nSZrY94BV1a4krwWuYDBjyYVVdd2k6nMAng28Evhaki83y95cVZdPrkoPWa8DLmr+KH0bOGvC9VmUqroqyUeAaxjMEPUlYMNkayVJ6grbTmqBbacJiFcCJUldtmLFijrqqKOWtMzt27dfXVXrl7RQSZJGMLEeMEmSRuGwQUlSnxjAJEmdZwCTJPWF09BLkjRLkguT3Jbk2qFlf5jk60m+muRjSY4aWnd+kk1JbkzyoolUWpI0FQxgkqTOm8AsiH8GnDpr2SeAJ1XVk4FvAOcDJDmJwUxoT2z2eW+SZUt17pKkfjGASZI6b9wBrKo+C/xg1rKPV9Wu5uWVDL6DCQZfAnpxVd1XVd8BNgEnL93ZS5L6xHvAJEmd18I9YKuSbBx6vaGqFjN18a8Df9U8X80gkM3Y0iyTJGkvBjBJUqe1NAvi9v2dhj7J7zL4vpmLlrZKkqSHAgOYJEkjSvJrwOnAC+onqXArsHZoszXNMkmS9uI9YJKkzpvAJBx7SXIqcB7wkqq6Z2jVZcCZSVYmORFYB3zhgE9aktRL9oBJkjpv3N8DluTDwHMZ3Cu2BbiAwayHK4FPJAG4sqpeU1XXJbkEuJ7B0MRzqmr3WCssSZoa8cstJUldtmzZsjr00EOXtMy777776v29B0ySpANhD5gkqfO8WChJ6gvvAZMkSZKkMbEHTJLUaS1NQy9J0kQYwCRJnWcAkyT1hQFMktR5BjBJUl8YwCRJnWcAkyT1hZNwSJIkSdKY2AMmSeo8e8AkSX1hAJMkdZqzIEqS+sQAJknqPAOYJKkvvAdMkiRJksbEHjBJUufZAyZJ6gsDmCSp8wxgkqS+MIBJkjrPACZJ6gsDmCSp664AVi1xmduXuDxJkkYSrypKkiRJ0ng4C6IkSZIkjYkBTJIkSZLGxAAmSZIkSWNiAJMkSZKkMTGASZIkSdKY/P9Qcmc3XpXyGgAAAABJRU5ErkJggg== +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 10 (blanco y negro)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [313]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorte10</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">Escalagrises3</span><span class="p">[:,:,</span><span class="mi">0</span><span class="p">],</span> <span class="mi">615</span><span class="p">,</span> <span class="mi">394</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span> +<span class="n">x10</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">10</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span> +<span class="n">y10</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">10</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span> +<span class="n">y10</span><span class="p">,</span><span class="n">x10</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">meshgrid</span><span class="p">(</span><span class="n">x10</span><span class="p">,</span><span class="n">y10</span><span class="p">)</span> +<span class="n">xdata10</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">vstack</span><span class="p">((</span><span class="n">x10</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span><span class="n">y10</span><span class="o">.</span><span class="n">ravel</span><span class="p">()))</span> +<span class="n">popt10</span><span class="p">,</span> <span class="n">pcov10</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata10</span><span class="p">,</span> <span class="n">recorte10</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrella10</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata10</span><span class="p">,</span> <span class="n">popt10</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt10</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt10</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt10</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt10</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHM10</span><span class="o">=</span><span class="n">FWHM</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">popt10</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 10 fotografÃa"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorte10</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 10 a partir de la gaussiana"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrella10</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Histograma (blanco y negro)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [447]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">FWHM</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">FWHM</span><span class="p">)</span> +<span class="n">sigmaBN</span> <span class="o">=</span> <span class="n">FWHM</span><span class="o">.</span><span class="n">std</span><span class="p">()</span> +<span class="n">mediaBN</span> <span class="o">=</span> <span class="n">FWHM</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> +<span class="n">medianaBN</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">median</span><span class="p">(</span><span class="n">FWHM</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Datos de FWHM de las estrellas a blanco y negro :"</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Desviación :"</span><span class="p">,</span> <span class="n">sigmaBN</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Media :"</span><span class="p">,</span> <span class="n">mediaBN</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Mediana :"</span><span class="p">,</span> <span class="n">medianaBN</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">FWHM</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">'FHWM'</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">'# de estrellas'</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + +<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain"> +<pre>Datos de FWHM de las estrellas a blanco y negro : +Desviación : 2.506520397288835 +Media : 4.2231882458162096 +Mediana : 3.1419657079162633 +</pre> +</div> +</div> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img src="data:image/png;base64,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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>Repita el mismo ejercicio sobre cada una de las bandas R,G,B separadamente +y comente si observa diferencias en los resultados</li> +</ul> + +</div> +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<h2 id="Para-la-banda-R">Para la banda R<a class="anchor-link" href="#Para-la-banda-R">¶</a></h2><ul> +<li>## Estrella 1 (Rojo)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [353]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">FWHMR</span><span class="o">=</span><span class="p">[]</span> +</pre></div> + + </div> +</div> +</div> +</div> + +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [354]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteR1</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">0</span><span class="p">],</span> <span class="mi">210</span><span class="p">,</span> <span class="mi">237</span><span class="p">,</span> <span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">)</span> +<span class="n">poptR1</span><span class="p">,</span> <span class="n">pcovR1</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata1</span><span class="p">,</span> <span class="n">recorteR1</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaR1</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata1</span><span class="p">,</span> <span class="n">poptR1</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR1</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR1</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR1</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR1</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMR1</span><span class="o">=</span><span class="n">FWHMR</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptR1</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 1 fotografÃa (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteR1</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 1 a partir de la gaussiana (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaR1</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 2 (Rojo)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [355]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteR2</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">0</span><span class="p">],</span> <span class="mi">645</span><span class="p">,</span> <span class="mi">535</span><span class="p">,</span> <span class="mi">35</span><span class="p">,</span> <span class="mi">35</span><span class="p">)</span> +<span class="n">poptR2</span><span class="p">,</span> <span class="n">pcovR2</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata2</span><span class="p">,</span> <span class="n">recorteR2</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaR2</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata2</span><span class="p">,</span> <span class="n">poptR2</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR2</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR2</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR2</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR2</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMR2</span><span class="o">=</span><span class="n">FWHMR</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptR2</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 2 fotografÃa (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteR2</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 2 a partir de la gaussiana (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaR2</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">35</span><span class="p">,</span> <span class="mi">35</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 3 (Rojo)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [356]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteR3</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">0</span><span class="p">],</span> <span class="mi">560</span><span class="p">,</span> <span class="mi">320</span><span class="p">,</span> <span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">)</span> +<span class="n">poptR3</span><span class="p">,</span> <span class="n">pcovR3</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata3</span><span class="p">,</span> <span class="n">recorteR3</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaR3</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata3</span><span class="p">,</span> <span class="n">poptR3</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR3</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR3</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR3</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR3</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMR3</span><span class="o">=</span><span class="n">FWHMR</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptR3</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 3 fotografÃa (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteR3</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 3 a partir de la gaussiana (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaR3</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 4 (Rojo)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [357]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteR4</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">0</span><span class="p">],</span> <span class="mi">442</span><span class="p">,</span> <span class="mi">370</span><span class="p">,</span> <span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">)</span> +<span class="n">poptR4</span><span class="p">,</span> <span class="n">pcovR4</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata4</span><span class="p">,</span> <span class="n">recorteR4</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaR4</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata4</span><span class="p">,</span> <span class="n">poptR4</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR4</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR4</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR4</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR4</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMR4</span><span class="o">=</span><span class="n">FWHMR</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptR4</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 4 fotografÃa (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteR4</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 4 a partir de la gaussiana (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaR4</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 5 (Rojo)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [358]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteR5</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">0</span><span class="p">],</span> <span class="mi">320</span><span class="p">,</span> <span class="mi">455</span><span class="p">,</span> <span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">)</span> +<span class="n">poptR5</span><span class="p">,</span> <span class="n">pcovR5</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata5</span><span class="p">,</span> <span class="n">recorteR5</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaR5</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata5</span><span class="p">,</span> <span class="n">poptR5</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR5</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR5</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR5</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR5</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMR5</span><span class="o">=</span><span class="n">FWHMR</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptR5</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 5 fotografÃa (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteR5</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 5 a partir de la gaussiana (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaR5</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt 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pfzdpc5OwfsWmVD7po5VdkwvceVFQwXj7LudGVHDh5VVrUfquwI0sghk42cpey8tKsk3aPsKMJx0vNDL0+T9Ov8cR7YZP3b89/PV3a040lJDyv7gGjk75X9469WdqRoLBfsHsvzJEmLlF1DpD4re3ntdVc2rGJl7fFI+raybu/lyk7evbbVwCJiSNJfKftnXaXsROH6L7uxxj5y+7cpew3+ISJ+oWx8+EXKnvddlM9MWuA4ZUfw7pZ0tbKjbWfV3f8uZWPJgb5Fjx7GsU0pH/mwpM/m8XxaWcEymofybT+o7Jz4D0bEne1sq0F+MyZ5znOssu/RFXls9ZOBtPWcR8Qdys6fv0ZZEf9SjX7w/rP5fu9RVuxcqDzvaratiLhcWd51q6QbJP2obrsDyg4GPyjpEWVFQq1gGe39WG+sr3G9seaH39DGcw5IG2aZf1LS9coe+6n5fV+SNEXZaKdrJf2s1cBaeO1Tclsp+197VNIHNEreXeBdykafPSjpEmXn6f5CkvKi8U2Szmm2c8dGlyEDiuVHHh5T1nV9T4/DkSTZ/i9lY7a/3+tYyuDs0gnrJb0oIu5vsu5bJB0ZEY0SBaDydhqcEB+fMrPj2/3IU6tuiIj5Hd8wANk+WNJ3ImJOk1U3ebY/JOmIiGhpYrt+YvvXkj4S+UXT+53tF0v6vaSJ0aQ4s32csiG0JzbbLheNREN5sXCFsiGbX5B0mzZMYtJzETGWYQP9YC9lR38earZiRPxQ0g+7HhHQQ1Z/DksBsGlydqmEFyvrtdtV2blnjabf72sRcVDztfrKXpLua1bkSVJENLoExgvwHYnRLFDWZfygsg+cI1p5A6LzbL9d2fTWH8/HrwMQQzcB9JVJyoYtrlZ2MfgfaMPll9CnbP8vZackndTxbZO3AwCqaN7gxPjk1Jkd3+7CJ4cYugkAqDyGbgIAKoseOAAAijF0EwAAAAD6TKk9erO23irmzU2YZOnZZ9KDSB2qOnlKegxOrK/Xr2u+TjNRdImUMRjswFsn9fV8rgOnqk2anNh+s/QY1q9Pa5/aozEwmNT83vuXaWjVKvpV0BO88dDvZs3aOubttFOvwwDQQffef7+GhrqfO5Va6M2bO0fXX3Zp2+1j+V3JMURicTAwb8/kGLTZ5mntH1+ZHEKsfTqpvWdskx7Dst+ntX9o1CsMtMRz/ySt/ezdkmPQU4+ntR9IPHAwdUZS85e95g1p+wfaZJU/dNP2XGXX5dxO2YWFF0XEl+vuP0HZLMXbRMRQfq3PLyu75tHTko6JiBvLjRpVNm+nnbT46it7HQaADpr/5weXsh/O0QMAVNZA+X166ySdEBE32p4u6Qbbl0fEHXkR+AZJ9Ueh3qhs1uJdlV1g+etq7eLWAAAk4Rw9AABaFBEraj1yEbFa0hJJs/O7vyjpRGU9fTULJH07MtdKmplfKwsAgK6iRw8AUEnu3nXvZtleXPf3oohY9ML9e56k/SRdZ3uBpOURcUs2WvN5syU9UPf3snzZio5HDQBAnaRCz/ahys49GJT0zYg4vSNRAQDQgi4NSxlqdh0929MkXSTpeGXDOT+hbNgmMCpyJwBlafs70vagpK8pO/9gD0nvsr1HpwIDAKAZd+HWdJ/2RGVF3rkRcbGkXSTtLOkW2/dKmiPpRtvbS1ouaW5d8zn5MmyCyJ0AlCnlYOgBkpZGxN0R8ayk85WdiwAAQNdls26647dR95mNyzxT0pKIOEOSIuK2iNg2IuZFxDxlwzP3j4iHJF0q6ShnDpT0eEQwbHPTRe4EoDQphV6j8w42Ynuh7cW2F69ctSphdwAA9NxBko6U9FrbN+e3N42y/k8k3S1pqaT/kPThEmLE+DX23GmI3AlAe7o+GUt+AvsiSZq/796JVysHAGCDsi+uEBFXN9tt3qtX+z0kHdvlsNBnNsqd9t+P3AlAW1IKPc47AAD0VOlX0QPSkDsBKE3K0M3rJe1qe2fbkyQdoexcBAAAStGLyViABOROAErTdo9eRKyz/RFJP1c2RfBZEXF7xyIDAKAJN5k8BRhPyJ0AlCnpHL2I+ImyE80BAADQBLkTgLJ0fTIWAAC6gaGWAAA0Vm6h9+wziuV3td08rr8yOQS/+q3J20g2PJzW/IHfJYcwMG/PtA1EByYBm7pFUnPvuk96DOvXJzWPVenn0Hvy1MQNJP4bP7smrX0n3gtAm1JONAcAoJ/RowcAqCxO0QMAoBiFHgCgsszgTQAACjHqBQAAAAD6DD16AIBKYjIWAAAao9ADAFQWhR4AAMUo9AAAlTVApQcAQCHO0QMAAACAPkOPHgCgosysmwAANEChBwCoJCZjAQCgMQo9AEA1mQumAwDQCIUeAKCyqPMAACjGZCwAAAAA0Gfo0QMAVNYAfXoAABSi0AMAVBKTsQAA0BiFHgCgspiMBQCAYhR6AIDKos4DAKBYuYVeDCvWrmm7uV92cHII3nK7pPbxxFB6DNO2Sms/ZVpyDBoYBzX+4GBa+4HE9p3YRidiSLV+XVr7wXHwXgAAAEBHkeEBACrL9OkBAFCIQg8AUEmWNECdBwBAIQo9AEBlUecBAFCMQg8AUFkUegAAFBtot6HtubZ/ZfsO27fb/mgnAwMAAOgn5E4AypTSo7dO0gkRcaPt6ZJusH15RNzRodgAABgVk7GgYsidAJSm7UIvIlZIWpH/vtr2EkmzJfFhBQAoBRdMR5WQOwEoU0fO0bM9T9J+kq7rxPYAAGjGSjj/AOgxcicA3Zb8HWl7mqSLJB0fEU8U3L/Q9mLbi1c+9oK7AQAANiljyp2GVpUfIIC+kFTo2Z6o7IPq3Ii4uGidiFgUEfMjYv42M7dI2R0AABtxF25AN405d5q1dbkBAugbbQ/dtG1JZ0paEhFndC4kAABaY07SQ4WQOwEoU0qP3kGSjpT0Wts357c3dSguAACaokcPFUPuBKA0KbNuXi2+EwEAPUJhhqohdwJQJiYsAwAAAIA+05HLKwAAUDqbc/QAAGig3EJvOKS1a9pvv+3cDsQwnNZ+9aPpMUxNnH104qTkEOLJR5Lae/LU5BiSDQwmb8KDif8Ckfh+khTr1yW190Bix3zq/0REWnsgwQB1HtB1kfo534HvyuTvqk4cFErMOzgwhbLRowcAqCxT6QEAUIhCDwBQSVZnDtIDANCPmIwFAAAAAPoMPXoAgGoyPXoAADRCoQcAqCwmNwAAoBiFHgCgsqjzAAAoRqEHAKgsevQAACjGZCwAAAAA0Gfo0QMAVBKXVwAAoDEKPQBANVkaoNIDAKAQhR4AoLKo8wAAKMY5egCAirLszt9G3aM91/avbN9h+3bbH82X/4vtO23favsS2zPr2pxse6nt39n+i+4+JwAAZCj0AABo3TpJJ0TEHpIOlHSs7T0kXS5pr4jYW9LvJZ0sSfl9R0jaU9Khkv7N9mBPIgcAbFIo9AAAlWRJHuj8bTQRsSIibsx/Xy1piaTZEXFZRKzLV7tW0pz89wWSzo+ItRFxj6Slkg7owtMBAMBGOEcPAFBN7tp19GbZXlz396KIWPSC3dvzJO0n6boRd71P0nfz32crK/xqluXLAADoKgo9AEBldWkylqGImD/6fj1N0kWSjo+IJ+qWf1LZ8M5zuxIZAAAtKrfQGxyUt9iq7eYx9GB6DFOfaL5Olw3fdVPaBoYeSg9i28QDyltukx7D4MS09hMmpcfQbJxWMzGcHsOaJ9NCmJj2PDj5eYzE9kC12J6orMg7NyIurlt+jKTDJB0SEbV/jOWS5tY1n5MvA0qx4a2Y4Lm1ae2feiw5hFj9aFJ7T52WHIOmtZ/DSlJMmpIcggc46wqt490CAKisHsy6aUlnSloSEWfULT9U0omS3hoRT9c1uVTSEbYn295Z0q6SftPxJwIAgBEYugkAqKweXEfvIElHSrrN9s35sk9I+oqkyZIuz4vFayPigxFxu+0LJN2hbEjnsRGxvvSoAQCbHAo9AEAlWdJAyZVeRFyd73qkn4zS5jRJp3UtKAAAClDoAQCqyT3p0QMAoBKSz9GzPWj7Jts/6kRAAAAA/YzcCUAZOtGj91FlF4zdogPbAgCgZV26jh7QbeROALouqUfP9hxJb5b0zc6EAwBA6+zO34BuIncCUJbUHr0vKZtOenp6KAAAtM6iMEMlfUnkTgBK0HaPnu3DJD0cETc0WW+h7cW2F6989PF2dwcAwMZseaDzN6Bb2sqdhlaVFB2AfpMydPMgSW+1fa+k8yW91vZ3Rq4UEYsiYn5EzN9myxkJuwMAAKi0sedOs7YuO0YAfaLtQi8iTo6IORExT9IRkn4ZEe/pWGQAADTBOXqoEnInAGXiOnoAgMoq+4LpAABURUcKvYi4UtKVndgWAACtYDIWVBm5E4Buo0cPAFBZXEcPAIBiSdfRAwAAAACMP+X26E2YKG+9Q9vN457bk0OIdc+mbeB3tybHsOyL/5XUfpvdtkmOYfLCv0lqH5OnJMfgqdPSNpD6WkrSQNqxjhgeTo9h/XNp7SdOSo8BqCImTwGaG16fvo0nhtJC+PF/Joew9oqrk9pP2nu35BgGDn9fUnvPTo9BA5PTt4FNBkM3AQCVxdBNAACKUegBACqLOg8AgGKcowcAAAAAfYYePQBAJWWXV6BLDwCAIhR6AIBqsmTGpQAAUIhCDwBQUaZHDwCABij0AADVNUChBwBAEQa9AAAAAECfoUcPAFBdDN0EAKAQhR4AoJrMrJsAADRCoQcAqC7O0QMAoBCFHgCgoszQTQAAGmAyFgAAAADoM/ToAQAqyZbM0E0AAApR6AEAqouhmwAAFKLQAwBUFj16AAAUK73Qi+Hh9htPm5EewKMrk5qvueSnySF8/rYHk9q/c8WTyTG86qg1aRtYkx6Dpm+Z1v65Z5NDiNQNDAwmx6CpWyQ194SJafufODmtvTnVFz1Ejx4wuvXrkjcxvOKepPZDZ12aHMMpix9Ian/0/70vOYYD9to3qb23m5ccQ0yYlBYDn5mbFDI0AAAAAOgzDN0EAFSTzXX0AABogEIPAFBZDEMCAKAYhR4AoLro0QMAoFDSOXq2Z9q+0PadtpfYfnmnAgMAAOg35E4AypLao/dlST+LiMNtT5I0tQMxAQDQnMWsm6gicicApWi70LM9Q9KrJB0jSRHxrKT0+e4BAGgRV/dAlZA7AShTylfkzpJWSvqW7Ztsf9P25h2KCwCA5uzO34DuIXcCUJqUQm+CpP0lfT0i9pP0lKSTRq5ke6HtxbYXr1z1aMLuAACoY8sDnb8BXTT23GloVdkxAugTKYXeMknLIuK6/O8LlX14bSQiFkXE/IiYv83WWybsDgAAoNLGnjvN2rrUAAH0j7YLvYh4SNIDtnfPFx0i6Y6ORAUAQCsYuokKIXcCUKbUWTePk3RuPmvU3ZLemx4SAAAtYqglqofcCUApkgq9iLhZ0vzOhAIAQOuyDjgKPVQLuROAsqT26AEA0Dv06AEAUIgrEAEAAABAnym3R294WFq7pu3mnrpFcgix/J6k9gOTet8JutcuM9M3Mmv7tPYDg+kxpG5jeH16DM8lXqd28pTkEDxxctoGJm7W2/YMnUPPMHkK0FQH/kec+F03bccZyTEcOH1lUvsdtk3/vta0xDyUzyuUrPdVCwAAbeIcPQAAilHoAQCqyeIcPQAAGqDQAwBUFj16AAAUYzIWAAAAAOgzFHoAgOoacOdvo7A91/avbN9h+3bbH82Xb2X7ctt35T+3zJfb9ldsL7V9q+39S3hWAACg0AMAVJTdndvo1kk6ISL2kHSgpGNt7yHpJElXRMSukq7I/5akN0raNb8tlPT1bjwVAACMxDl6AIDKcsmTsUTECkkr8t9X214iabakBZIOzlc7R9KVkj6eL/92RISka23PtL1Dvh0AALqGHj0AADY2y/biutvCopVsz5O0n6TrJG1XV7w9JGm7/PfZkh6oa7YsXwYAQFfRowcAqK7uzLo5FBHzR9+tp0m6SNLxEfFE/eyfERG2oxuBAQDQKgo9AEA19eg6erYnKivyzo2Ii/PFf6wNybS9g6SH8+XLJc2taz4nXwYAQFcxdBMAUFm2O35rsj9LOlPSkog4o+6uSyUdnf9+tKQf1C0/Kp9980BJj3N+HgCgDPToAQAqqvnlELrgIElHSrrN9s35sk9IOl3SBbbfL+k+Se/I7/uJpDdJWirpaUnvLTVaAMAmi0IPAIAWRcTVygaNFjmkYP2QdGxXgwIAoACFHgCgurozGQsAAJVHoQcAqCaLQg8AgAYo9AAA1UWhBwBAoXILvYEBecrmpe5ypJg+I6n95L88LDmGLzy7Lqn9lL85uvlKTQzM3T15G6li7dNpGxhenx7EwGD6NlJNmJTWftLkpOaetFna/s3kvegVSwO8/4BRDaanet5+56T2mx334eQY3vOaG5Lae27aY5CkgZcckLaBCWnf15KazgwM1OMbEgAAAAD6DEM3AQDVxdFtAAAKUegBAKqJyVgAAGiIQg8AUF0UegAAFEo6R8/2x2zfbvu3ts+znTirAwAArconY+n0DegicicAZWn7G832bEl/J2l+ROwlaVDSEZ0KDAAAoJ+QOwEoU+rQzQmSpth+TtJUSQ+mhwQAQIsYuonqIXcCUIq2e/QiYrmkL0i6X9IKSY9HxGWdCgwAgFHVJmPp9A3oEnInAGVKGbq5paQFknaWtKOkzW2/p2C9hbYX21688pFH248UAICRKPRQIW3lTkOryg4TQJ9IOev8dZLuiYiVEfGcpIslvWLkShGxKCLmR8T8bbbaMmF3AADUYzIWVM7Yc6dZW5ceJID+kPKNdr+kA21PtW1Jh0ha0pmwAAAA+g65E4DStD0ZS0RcZ/tCSTdKWifpJkmLOhUYAABNMdQSFULuBKBMSbNuRsQpkk7pUCwAALSuNhkLUCHkTgDKknp5BQAAeodCDwCAQpx1DgAAAAB9ptwevWfXanjZXW03H9j5pekxbD4jrf2OOyWHMOWEj6VtYGAwOYZYvy5tA0924FIZgxOTmnvzLdJjmLhZWnt34FhJDKe1f+aptN0nttf659LaA22yLDNLJjAqdyJnSMydBvZ7TXIM2usFk5OOzWAHUt7JU3sfAzAGvOMAANXF0E0AAApR6AEAqonJWAAAaIhCDwBQXRR6AAAU4uQGAAAAAOgz9OgBACrKEpOxAABQiEIPAFBdDN0EAKAQhR4AoJqYjAUAgIYo9AAA1UWhBwBAIU5uAAAAAIA+Q48eAKCimIwFAIBGKPQAANXF0E0AAApR6AEAqonJWAAAaIhCDwBQUQzdBACgEb4hAQAAAKDP0KMHAKguhm4CAFCIQg8AUF0UegAAFCq30Ju0mQbm7t5++8lTkkPwrB3TNpDavhMeH0rehBPPa4lpWybHkMzjYORxJ84P8mBa+4i09sPDae1Foo0eYTIWoBQeTEsXY7Np6UFM3jytfQc+K8znDSpmHGTKAAAAAIBOYugmAKCimHUTAIBGKPQAANXFUCoAAApR6AEAqotCDwCAQk3HvNg+y/bDtn9bt2wr25fbviv/OQ5m5gAAbFKsbFKmTt+AROROAMaDVr7RzpZ06IhlJ0m6IiJ2lXRF/jcAAADInQCMA00LvYi4StIjIxYvkHRO/vs5kt7W2bAAAGjG0kAXbkAicicA40G75+htFxEr8t8fkrRdoxVtL5S0UJJ2mr1Dm7sDAKAAQy1RHe3lTnPnlhAagH6U/A0ZESGp4RWbI2JRRMyPiPnbbLVV6u4AANjA7vwN6LIx5U6zti4xMgD9pN0evT/a3iEiVtjeQdLDnQwKAICmzHX0UCnkTgBK1e435KWSjs5/P1rSDzoTDgAAQF8idwJQqlYur3CepGsk7W57me33Szpd0utt3yXpdfnfAACUi6GbGIfInQCMB02HbkbEuxrcdUiHYwEAYGyYjAXjELkTgPGAb0gAQHX1oEevwcWw97V9re2bbS+2fUC+3La/Ynup7Vtt79/FZwMAgOdR6AEAqqk2GUunb82drRdeDPufJZ0aEftK+nT+tyS9UdKu+W2hpK934qEDANBMu7NutseWJm7Wfvu1azoXS5s8dUb6RobXJTWP1Y8mhxDDw0ntPdiBt86ESWntI+0xdGQbnTifJ/V5SLXu2bT2nNOETUxEXGV73sjFkrbIf58h6cH89wWSvp1Pp3+t7Zm1mRfLiRboPXfie4LvGmDMyi30AADopO4kf7NsL677e1FELGrS5nhJP7f9BWWjZV6RL58t6YG69Zblyyj0AABdRaEHAKiu7kzGMhQR88fY5kOSPhYRF9l+h6Qzlc2sCABAT3COHgCgmmxpoAu39hwt6eL89+9JOiD/fbmkuXXrzcmXAQDQVRR6AACke1DSq/PfXyvprvz3SyUdlc++eaCkxzk/DwBQBoZuAgCqqwfX0csvhn2wsnP5lkk6RdIHJH3Z9gRJzyibYVOSfiLpTZKWSnpa0ntLDxgAsEmi0AMAVFcPZuIb5WLY/6Ng3ZB0bHcjAgDghSj0AAAV5Z706AEAUAUUegCAarJSJk8BAKCvcSgUAAAAAPoMPXoAgOrqwTl6AABUAYUeAKC6OEcPAIBCFHoAgGpy0gXOAQDoaxR6AIDqokcPAIBCfEMCAAAAQJ+hRw8AUF1MxgIAQCEKPQBARXHBdAAAGim30LOlwcH22z/zTHoIEyYmb6PnZsxK3oQ3m5a2gZTXsVPWrknfRgyntZ8wKT0GElWgPVwwHQCAhujRAwBUFwdKAAAoxDckAAAAAPQZevQAANXFZCwAABSi0AMAVJSlAQamAABQpOk3pO2zbD9s+7d1y/7F9p22b7V9ie2ZXY0SAICRrKxHr9M3IBG5E4DxoJVDoWdLOnTEsssl7RURe0v6vaSTOxwXAABAVZ0tcicAPda00IuIqyQ9MmLZZRGxLv/zWklzuhAbAACj80Dnb0AicicA40EnvtHeJ+mnje60vdD2YtuLV656pNFqAACMUReGbTJ0E+VoPXcaWlViWAD6SVKhZ/uTktZJOrfROhGxKCLmR8T8bbbeKmV3AABsbGCg8zegi8acO83aurzgAPSVtmfdtH2MpMMkHRIR0bGIAABoRW0yFqAiyJ0AlKmtQs/2oZJOlPTqiHi6syEBAAD0F3InAGVrWujZPk/SwZJm2V4m6RRlM0VNlnS5s6Op10bEB7sYJwAAI5jJUzAukTsBGA+aFnoR8a6CxWd2IRYAAMaGoZsYh8idAIwHbZ+jBwBAz9GjBwBAIQo9AEA12dIAPXoAABQpt9AbGJQ3n9l2845MTzWY+JDXr2u+TjPDadvwFh2YannS1LT2655NjyF1GzGcHEIkvp7jIsVMfD+Jid8AAAD6Dj16AIDqYugmAACFKPQAANXFZCwAABSi0AMAVBSXVwAAoBEKPQBAZZkePQAACnEoFAAAAAD6DD16AIBqshi6CQBAAxR6AICK4hw9AAAaodADAFQXF0wHAKAQhR4AoLro0QMAoBDfkAAAAADQZ+jRAwBUk8UF0wEAaIBCDwBQUUzGAgBAIxR6AIDqokcPAIBCHAoFAAAAgD5Djx4AoLoYugkAQCEKPQBANdlcRw8AgAZKLvRCsX5d+83XrE4PYeqMtPbr1yeHEM88ldTek6Ykx6Bnn05rv3ZNegwTJqa1j+H0GMaD4YT/CUla91xa+5T/SUmKSGsPpKBHDwCAQvToAQCqi8lYAAAoxKFQAAAAAOgz9OgBACqK6+gBANBI029I22fZftj2bwvuO8F22J7VnfAAABiF3fkbkIjcCcB40Mqh0LMlHTpyoe25kt4g6f4OxwQAQHNW1qPX6RuQ7myROwHosabfaBFxlaRHCu76oqQTJTHlHgCgBywNDHT+BiQidwIwHrT1jWZ7gaTlEXFLh+MBAGBcazQsz/Zxtu+0fbvtf65bfrLtpbZ/Z/svyo8Y4wG5E4CyjXkyFttTJX1C2dCDVtZfKGmhJO00d85YdwcAQEPuzTl1Z0v6qqRv18XxGkkLJO0TEWttb5sv30PSEZL2lLSjpF/Y3i0i0i/KispIy53mdjEyAP2snR69XSTtLOkW2/dKmiPpRtvbF60cEYsiYn5EzN9m1tbtRwoAwEg9OEevwbC8D0k6PSLW5us8nC9fIOn8iFgbEfdIWirpgM49AagIcicApRtzj15E3CZp29rf+QfW/IgY6mBcAACMzurWLJmzbC+u+3tRRCxq0mY3Sa+0fZqkZyT9fURcL2m2pGvr1luWL8MmhNwJQC80LfRsnyfpYGVffMsknRIRZ3Y7MAAARte16+gNRcT8MbaZIGkrSQdKepmkC2y/uOORoRLInQCMB00LvYh4V5P753UsGgAAqmmZpIsjIiT9xvawpFmSlkuqP8lqTr4MfYzcCcB4wDzSAIDqGj8XTP++pNdkIXk3SZMkDUm6VNIRtifb3lnSrpJ+k/7AAQAY3ZjP0QMAYNzowXXvioblSTpL0ln5JReelXR03rt3u+0LJN0haZ2kY5lxEwBQBgo9AEA1pfXAtW2UYXnvabD+aZJO615EAAC8UKmF3g033TI0sMWs+0ZZZZayoS69RAzjI4Ze758YWo/hRWUFAgCbmhtuunnIm88kdxr/MfR6/8RQrRhKyZ1KLfQiYpvR7re9uI2ZzjqKGMZHDL3ePzGMrxiAhroz6yYwbpA7VSOGXu+fGIihCEM3AQDV1YOhmwAAVAGFHgCgwij0AAAoMt4KvUW9DkDEUNPrGHq9f4kYasZDDECB3kzGAowz4+Ezmhh6v3+JGGqIIeds9mcAAKpl/t57xfU/vqDj2x3Yac8bxsO5FQAApBhvPXoAALSOHj0AAApR6AEAKoxCDwCAIuNmXmrbh9r+ne2ltk/qwf7n2v6V7Tts3277o2XHkMcxaPsm2z/q0f5n2r7Q9p22l9h+eQ9i+Fj+GvzW9nm2Nythn2fZftj2b+uWbWX7ctt35T+37EEM/5K/FrfavsT2zLJjqLvvBNthe1Y3YwBaZm24aHonb0AFkDdtFAu5E7kTuVOBcVHo2R6U9DVJb5S0h6R32d6j5DDWSTohIvaQdKCkY3sQgyR9VNKSHuy35suSfhYRfyppn7JjsT1b0t9Jmh8Re0kalHRECbs+W9KhI5adJOmKiNhV0hX532XHcLmkvSJib0m/l3RyD2KQ7bmS3iDp/i7vHxgbd+EGjHPkTS9A7kTuVI/cKTcuCj1JB0haGhF3R8Szks6XtKDMACJiRUTcmP++Wtk/6ewyY7A9R9KbJX2zzP3W7X+GpFdJOlOSIuLZiHisB6FMkDTF9gRJUyU92O0dRsRVkh4ZsXiBpHPy38+R9LayY4iIyyJiXf7ntZLmlB1D7ouSTpTE7E0A0HvkTTlyp+eRO21YRu6UGy+F3mxJD9T9vUw9+LCosT1P0n6Srit5119S9oYYLnm/NTtLWinpW/kQiG/a3rzMACJiuaQvKDv6sULS4xFxWZkx1NkuIlbkvz8kabsexVHzPkk/LXunthdIWh4Rt5S9b6A5uvSwSSJv2uBLIncid2psk86dxkuhN27YnibpIknHR8QTJe73MEkPR8QNZe2zwARJ+0v6ekTsJ+kpdb/LfSP5WO4Fyj44d5S0ue33lBlDkciuQ9KzIzK2P6lsmMy5Je93qqRPSPp0mfsFWtOF8/M4Rw8Yk17lTfm+yZ1E7tQIudP4KfSWS5pb9/ecfFmpbE9U9mF1bkRcXPLuD5L0Vtv3KhuC8Vrb3yk5hmWSlkVE7Yjchco+vMr0Okn3RMTKiHhO0sWSXlFyDDV/tL2DJOU/H+5FELaPkXSYpHdH+Re+3EXZF8ct+XtzjqQbbW9fchxAMQo9bJrImzLkThlypxHInTLjpdC7XtKutne2PUnZCaSXlhmAbSsbX70kIs4oc9+SFBEnR8SciJin7PH/MiJKPRoTEQ9JesD27vmiQyTdUWYMyoYdHGh7av6aHKLenWB9qaSj89+PlvSDsgOwfaiyISlvjYiny95/RNwWEdtGxLz8vblM0v75ewUYBxi6iU3SJp83SeROdcid6pA7bTAuCr38hMmPSPq5sjfmBRFxe8lhHCTpSGVHg27Ob28qOYbx4DhJ59q+VdK+kj5X5s7zI2IXSrpR0m3K3qOLur1f2+dJukbS7raX2X6/pNMlvd72XcqOlp3egxi+Kmm6pMvz9+S/9yAGAMA4Qt407pA7kTuNy9zJ5fdmAgCQbv4+L43rL+v8weKB7Xe5ISLmd3zDAACUaEKvAwAAoH0MtQQAoAiFHgCgmpg8BQCAhsbFOXoAAAAAgM6hRw8AUF306AEAUIhCDwBQYRR6AAAUodADAFSW6dEDAKAQhR4AoLoo9AAAKMRkLAAAAADQZ+jRAwBUlMU5egAAFKPQAwBUF0M3AQAoRKEHAKgmi0IPAIAGKPQAABVGoQcAQBEmYwEAAACAPkOPHgCguhi6CQBAIQo9AEB1UecBAFCIQg8AUFFcXgEAgEYo9AAA1cXQTQAACjEZCwAAAAD0GXr0AADVxHX0AABoiEIPAFBhFHoAABSh0AMAVBc9egAAFOIcPQAAAADoM/ToAQAqyvToAQDQAIUeAKDCKPQAAChCoQcAqC569AAAKOSI6HUMAACMme2fSZrVhU0PRcShXdguAAClodADAAAAgD7DrJsAAAAA0Gco9AAAAACgz1DoAQAAAECfodADAAAAgD5DoQcAAAAAfeb/AxOXusrspVSXAAAAAElFTkSuQmCC +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 6 (Rojo)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [359]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteR6</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">0</span><span class="p">],</span> <span class="mi">535</span><span class="p">,</span> <span class="mi">335</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span> +<span class="n">poptR6</span><span class="p">,</span> <span class="n">pcovR6</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata6</span><span class="p">,</span> <span class="n">recorteR6</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaR6</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata6</span><span class="p">,</span> <span class="n">poptR6</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR6</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR6</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR6</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR6</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMR6</span><span class="o">=</span><span class="n">FWHMR</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptR6</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 6 fotografÃa (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteR6</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 6 a partir de la gaussiana (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaR6</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 7 (Rojo)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [360]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteR7</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">0</span><span class="p">],</span> <span class="mi">540</span><span class="p">,</span> <span class="mi">345</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span> +<span class="n">poptR7</span><span class="p">,</span> <span class="n">pcovR7</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata7</span><span class="p">,</span> <span class="n">recorteR7</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaR7</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata7</span><span class="p">,</span> <span class="n">poptR7</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR7</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR7</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR7</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR7</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMR7</span><span class="o">=</span><span class="n">FWHMR</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptR7</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 7 fotografÃa (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteR7</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 7 a partir de la gaussiana (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaR7</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 8 (Rojo)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [361]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteR8</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">0</span><span class="p">],</span> <span class="mi">620</span><span class="p">,</span> <span class="mi">306</span><span class="p">,</span> <span class="mi">20</span><span class="p">,</span> <span class="mi">20</span><span class="p">)</span> +<span class="n">poptR8</span><span class="p">,</span> <span class="n">pcovR8</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata8</span><span class="p">,</span> <span class="n">recorteR8</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaR8</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata8</span><span class="p">,</span> <span class="n">poptR8</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR8</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR8</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR8</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR8</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMR8</span><span class="o">=</span><span class="n">FWHMR</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptR8</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 8 fotografÃa (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteR8</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 8 a partir de la gaussiana (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaR8</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">20</span><span class="p">,</span> <span class="mi">20</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 9 (Rojo)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [362]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteR9</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">0</span><span class="p">],</span> <span class="mi">545</span><span class="p">,</span> <span class="mi">360</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span> +<span class="n">poptR9</span><span class="p">,</span> <span class="n">pcovR9</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata9</span><span class="p">,</span> <span class="n">recorteR9</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaR9</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata9</span><span class="p">,</span> <span class="n">poptR9</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR9</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR9</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR9</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR9</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMR9</span><span class="o">=</span><span class="n">FWHMR</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptR9</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 9 fotografÃa (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteR9</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 9 a partir de la gaussiana (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaR9</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 10 (Rojo)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [363]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteR10</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">0</span><span class="p">],</span> <span class="mi">615</span><span class="p">,</span> <span class="mi">394</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span> +<span class="n">poptR10</span><span class="p">,</span> <span class="n">pcovR10</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata10</span><span class="p">,</span> <span class="n">recorteR10</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaR10</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata10</span><span class="p">,</span> <span class="n">poptR10</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR10</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR10</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR10</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR10</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMR10</span><span class="o">=</span><span class="n">FWHMR</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptR10</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 10 fotografÃa (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteR10</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 10 a partir de la gaussiana (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaR10</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Histograma (Banda Rojo)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [446]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">FWHMR</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">FWHMR</span><span class="p">)</span> +<span class="n">sigmaR</span> <span class="o">=</span> <span class="n">FWHMR</span><span class="o">.</span><span class="n">std</span><span class="p">()</span> +<span class="n">mediaR</span> <span class="o">=</span> <span class="n">FWHMR</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> +<span class="n">medianaR</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">median</span><span class="p">(</span><span class="n">FWHMR</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Datos de FWHM de las estrellas para la Banda rojo :"</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Desviación :"</span><span class="p">,</span> <span class="n">sigmaR</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Media :"</span><span class="p">,</span> <span class="n">mediaR</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Mediana :"</span><span class="p">,</span> <span class="n">medianaR</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">FWHMR</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">'FHWM'</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">'# de estrellas'</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + +<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain"> +<pre>Datos de FWHM de las estrellas para la Banda rojo : +Desviación : 2.329889939974896 +Media : 4.021186556528661 +Mediana : 2.9192045463592478 +</pre> +</div> +</div> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAXgAAAEGCAYAAABvtY4XAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAAsTAAALEwEAmpwYAAARkElEQVR4nO3de5BkZX3G8e8juxFFECMTSoHNeiuUWAXqFuGmUVCDgpBYxmDUUopyEyUJJpaKVkoqlz/QMlasijHiDRMRRYSIN5R4iQqILogKAmrMekV38QYCisAvf/RZ6V13Z3qm58zpffl+qrq6+3TPOQ9Tsw+n3z7nPakqJEntucfQASRJ/bDgJalRFrwkNcqCl6RGWfCS1KhVQwcYt9dee9XatWuHjiFJO43LL7/8hqqa295rM1Xwa9euZcOGDUPHkKSdRpJv7eg1h2gkqVEWvCQ1yoKXpEZZ8JLUKAtekhplwUtSo3o9TDLJRuAm4A7g9qpa1+f2JEl3WYnj4J9QVTeswHYkSWMcopGkRvW9B1/Ax5IU8KaqOmPbNyRZD6wHWLNmzZI3tPbUDy35Z6ex8fRjBtmuJC2k7z34I6rq0cBTgJOTPG7bN1TVGVW1rqrWzc1tdzoFSdIS9FrwVfW97n4TcD5wcJ/bkyTdpbeCT7Jbkt23PAaeDFzV1/YkSVvrcwx+b+D8JFu2866qurDH7UmSxvRW8FX1TeDAvtYvSZqfh0lKUqMseElqlAUvSY2y4CWpURa8JDXKgpekRlnwktQoC16SGmXBS1KjLHhJapQFL0mNsuAlqVEWvCQ1yoKXpEZZ8JLUKAtekhplwUtSoyx4SWqUBS9JjbLgJalRFrwkNcqCl6RGWfCS1CgLXpIaZcFLUqMseElqlAUvSY2y4CWpURa8JDXKgpekRlnwktQoC16SGtV7wSfZJckXk3yw721Jku6yEnvwpwDXrMB2JEljei34JPsCxwBv6XM7kqTf1Pce/L8ALwPu3NEbkqxPsiHJhs2bN/ccR5LuPnor+CTHApuq6vL53ldVZ1TVuqpaNzc311ccSbrb6XMP/nDguCQbgXcDRyZ5Z4/bkySN6a3gq+oVVbVvVa0FTgA+UVXP6Wt7kqSteRy8JDVq1UpspKo+BXxqJbYlSRpxD16SGmXBS1KjLHhJapQFL0mNsuAlqVEWvCQ1yoKXpEZZ8JLUKAtekhplwUtSoyx4SWqUBS9JjbLgJalRFrwkNcqCl6RGWfCS1CgLXpIaZcFLUqMseElq1IIFn+Q1SfZIsjrJx5NsTvKclQgnSVq6Sfbgn1xVNwLHAhuBhwIv7TOUJGl6kxT8qu7+GOC9VfWzHvNIkpbJqoXfwgeTXAvcCrwwyRzwi35jSZKmteAefFWdChwGrKuqXwE3A8f3HUySNJ1J9uABHgg8McmuY8v+o4c8kqRlsmDBJzkNeDxwAPBh4CnAZ7HgJWmmTfIl6zOAo4AfVNWJwIHAfXtNJUma2iQFf2tV3QncnmQPYBOwX7+xJEnTmmQMfkOSPYE3A5cDPwcu7TOUJGl6CxZ8Vb2oe/jvSS4E9qiqL/cbS5I0rR0WfJJHz/daVV3RTyRJ0nKYbw/+n+d5rYAjlzmLJGkZ7bDgq+oJ06y4O2b+08A9u+2cW1WnTbNOSdLk5huiefp8P1hV5y2w7l8CR1bVz5OsBj6b5CNV9bkl5JQkLdJ8QzRPm+e1AuYt+KoqRkfcAKzubrWodJKkJZtviObEaVeeZBdGh1Y+FHhDVV027TolSZOZ5IIfeyd5a5KPdM8PSHLSJCuvqjuq6iBgX+DgJI/czvrXJ9mQZMPmzZsXGV+StCOTnMl6JvBRRhOOAXwNePFiNlJVPwU+CRy9ndfOqKp1VbVubm5uMauVJM1jkoLfq6rOAe4EqKrbgTsW+qEkc90ZsCS5F/Ak4NqlR5UkLcYkUxXcnOT+dF+QJjkEmOSqTg8A3tGNw98DOKeqPrjkpJKkRZmk4P8WuAB4SJKLgTlGM0zOq5vO4FHTxZMkLdW8Bd/tff9Bd9sfCHBdd2UnSdIMm3cMvqruAJ5VVbdX1dVVdZXlLkk7h0mGaC5O8q/AexhdjxUAJxuTpNk2ScEf1N3/w9gyJxuTpBk3ScGfVFXfHF+Q5ME95ZEkLZNJjoM/dzvL3rvcQSRJy2u+2SQfDvwecN9tZpbcA9i172CSpOnMN0SzP3AssCdbzyx5E/CCHjNJkpbBfLNJvh94f5JDq8qLbEvSTmaSMfg/TrJHktVJPp5kc5Ln9J5MkjSVSQr+yVV1I6Phmo2M5nZ/aZ+hJEnTm6TgV3f3xwDvrapJJhqTJA1skuPgP5DkWuBW4IVJ5oBf9BtLkjStBffgq+pU4DBgXTcPzS3A8X0HkyRNZ5JL9t0beBHwxm7RA4F1fYaSJE1vkjH4twO3MdqLB/ge8E+9JZIkLYtJCv4hVfUa4FcAVXULo3nhJUkzbJKCv627puqWS/Y9BPhlr6kkSVOb5Cia04ALgf2SnAUcDjy/z1CSpOktWPBVdVGSK4BDGA3NnFJVN/SeTJI0lUn24KmqHwEf6jmLJGkZTTIGL0naCVnwktSoiQo+yRFJTuwezyV5UL+xJEnTmuRM1tOAlwOv6BatBt7ZZyhJ0vQmmg8eOA64GaCqvg/s3mcoSdL0JjrRqaqKu0502q3fSJKk5TBJwZ+T5E3AnkleAPw38OZ+Y0mSpjXJiU6vTfIk4EZGF+J+VVVd1HsySdJUJj3R6SLAUpekncgOCz7JTXTj7ttTVXv0kkiStCx2WPBVtTtAkn8Ergf+k9FcNM8GHrAi6SRJSzbJl6zHVdW/VdVNVXVjVb0RL9knSTNvkoK/Ocmzk+yS5B5Jnk13TPx8kuyX5JNJvprk6iSnTB9XkjSpSQr+z4BnAj/sbn/SLVvI7cBLquoARlMNn5zkgKUGlSQtziSHSW5kCUMyVXU9o7F7quqmJNcA+wBfXey6JEmLN9FhktNKshZ4FHDZdl5bD6wHWLNmzUrEWVZrTx1umvyNpx8z2LYlzb7epwtOch/gfcCLq+rGbV+vqjOqal1VrZubm+s7jiTdbfRa8ElWMyr3s6rqvD63JUna2iTTBf/d2ON7TrriJAHeClxTVa9bWjxJ0lLtsOCTvDzJocAzxhZfuoh1Hw48FzgyyZXd7alLzClJWqT5vmS9ltEhkQ9O8pnu+f2T7F9V1y204qr6LKMzXyVJA5hviOanwCuBbwCPB17fLT81ySX9xpIkTWu+Pfg/BF4FPAR4HfBl4OaqOnElgkmSprPDPfiqemVVHQVsZDTR2C7AXJLPJvnACuWTJC3RJCc6fbSqNgAbkrywqo5IslffwSRJ01nwMMmqetnY0+d3y27oK5AkaXks6kSnqvpSX0EkScur96kKJEnDsOAlqVEWvCQ1yoKXpEZZ8JLUKAtekhplwUtSoyx4SWqUBS9JjbLgJalRFrwkNcqCl6RGWfCS1CgLXpIaZcFLUqMseElqlAUvSY2y4CWpURa8JDXKgpekRlnwktQoC16SGmXBS1KjLHhJapQFL0mNsuAlqVG9FXyStyXZlOSqvrYhSdqxPvfgzwSO7nH9kqR59FbwVfVp4Md9rV+SNL9VQwdIsh5YD7BmzZqB02gSa0/90NARVtzG048ZOoJWwFB/2339fQ3+JWtVnVFV66pq3dzc3NBxJKkZgxe8JKkfFrwkNarPwyTPBi4F9k/y3SQn9bUtSdJv6u1L1qp6Vl/rliQtzCEaSWqUBS9JjbLgJalRFrwkNcqCl6RGWfCS1CgLXpIaZcFLUqMseElqlAUvSY2y4CWpURa8JDXKgpekRlnwktQoC16SGmXBS1KjLHhJapQFL0mNsuAlqVEWvCQ1yoKXpEZZ8JLUKAtekhplwUtSoyx4SWqUBS9JjbLgJalRFrwkNcqCl6RGWfCS1CgLXpIaZcFLUqMseElqVK8Fn+ToJNcl+UaSU/vcliRpa70VfJJdgDcATwEOAJ6V5IC+tidJ2lqfe/AHA9+oqm9W1W3Au4Hje9yeJGnMqh7XvQ/wnbHn3wV+f9s3JVkPrO+e/jzJdfOscy/ghmVLuHwGyZVXz/uyv6vJLZhpgd91X3bK39UAZjETLCLXlH9fv7ujF/os+IlU1RnAGZO8N8mGqlrXc6RFm8Vcs5gJZjPXLGaC2cxlpsnNQq4+h2i+B+w39nzfbpkkaQX0WfBfAB6W5EFJfgs4Abigx+1Jksb0NkRTVbcn+Uvgo8AuwNuq6uopVzvRUM4AZjHXLGaC2cw1i5lgNnOZaXKD50pVDZ1BktQDz2SVpEZZ8JLUqJ2i4JPsl+STSb6a5Ookp8xApl2TfD7Jl7pMfz90pnFJdknyxSQfHDoLQJKNSb6S5MokG4bOs0WSPZOcm+TaJNckOXTgPPt3v6MttxuTvHjITF2uv+n+zq9KcnaSXYfOBJDklC7T1UP+npK8LcmmJFeNLfvtJBcl+Xp3f7+VzrVTFDxwO/CSqjoAOAQ4eQamPfglcGRVHQgcBByd5JBhI23lFOCaoUNs4wlVddDQxwZv4/XAhVX1cOBABv6dVdV13e/oIOAxwC3A+UNmSrIP8NfAuqp6JKODJk4YMhNAkkcCL2B01vyBwLFJHjpQnDOBo7dZdirw8ap6GPDx7vmK2ikKvqqur6orusc3MfpHuM/Amaqqft49Xd3dZuIb6yT7AscAbxk6yyxLcl/gccBbAarqtqr66aChtnYU8L9V9a2hgzA64u5eSVYB9wa+P3AegEcAl1XVLVV1O/A/wNOHCFJVnwZ+vM3i44F3dI/fAfzRSmaCnaTgxyVZCzwKuGzgKFuGQa4ENgEXVdXgmTr/ArwMuHPgHOMK+FiSy7vpKWbBg4DNwNu74ay3JNlt6FBjTgDOHjpEVX0PeC3wbeB64GdV9bFhUwFwFfDYJPdPcm/gqWx9cuXQ9q6q67vHPwD2XukAO1XBJ7kP8D7gxVV149B5quqO7qP0vsDB3UfGQSU5FthUVZcPnWUbR1TVoxnNLnpykscNHYjRXumjgTdW1aOAmxngY/T2dCcHHge8dway3I/R3uiDgAcCuyV5zrCpoKquAV4NfAy4ELgSuGPITDtSo+PRV/wT/k5T8ElWMyr3s6rqvKHzjOs+1n+S3xyDG8LhwHFJNjKawfPIJO8cNtKv9wKpqk2MxpQPHjYRMJoA77tjn7zOZVT4s+ApwBVV9cOhgwBPBP6vqjZX1a+A84DDBs4EQFW9taoeU1WPA34CfG3oTGN+mOQBAN39ppUOsFMUfJIwGie9pqpeN3QegCRzSfbsHt8LeBJw7aChgKp6RVXtW1VrGX3E/0RVDbq3lWS3JLtveQw8mdHH60FV1Q+A7yTZv1t0FPDVASONexYzMDzT+TZwSJJ7d/8Wj2JGvsBP8jvd/RpG4+/vGjbRVi4Antc9fh7w/pUOMPhskhM6HHgu8JVuzBvglVX14eEi8QDgHd2FTe4BnFNVM3FI4gzaGzh/1A2sAt5VVRcOG+nX/go4qxsS+SZw4sB5tvxP8EnAnw+dBaCqLktyLnAFoyPavsgMnIbfeV+S+wO/Ak4e6kvyJGcDjwf2SvJd4DTgdOCcJCcB3wKeueK5nKpAktq0UwzRSJIWz4KXpEZZ8JLUKAtekhplwUtSoyx43W0kuWObmRrXJnn8tjNuJjkzyTOSHJ/kv8aWvyLJN8aePy3JBd3jjUk+s816rhyfXVBaaRa87k5u3TJTY3fbuMD7L2E0e+kWhwI3bjm5htHZnJeMvb57kv0AkjxiuUJLS2XBSztQVZsZFfqWKWj3YTRdxpbT9A8DLh77kXOAP+0ez9KZqLqbsuB1d3KvseGZ8TnWHzs+dMNokq8tLgYO66Yz+Drwue75KkZzkH9h7L3v467pap8GfKCv/xBpEjvLVAXScri1m/1zW5+pqmO3PEly5thrlzDaU98FuBT4PPAqRlNWX1tVvxh774+AnyQ5gdFcLbcsa3ppkdyDl+Z3MaOCPwy4tLvgzK6M5h25ZDvvfw/wBhye0Qyw4KX5XcNoDvQjGE2yBaN5x/+CrcfftzgfeA3w0ZUIJ83Hgpfm0V2o4TLgR91c6DAaqnkw29mDr6qbqurVVXXbCsaUtsvZJCWpUe7BS1KjLHhJapQFL0mNsuAlqVEWvCQ1yoKXpEZZ8JLUqP8HD2Ny9kXnBRAAAAAASUVORK5CYII= +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<h2 id="Para-la-banda-G">Para la banda G<a class="anchor-link" href="#Para-la-banda-G">¶</a></h2><ul> +<li>## Estrella 1 (Verde)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [411]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">FWHMG</span><span class="o">=</span><span class="p">[]</span> +</pre></div> + + </div> +</div> +</div> +</div> + +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [412]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteG1</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">1</span><span class="p">],</span> <span class="mi">210</span><span class="p">,</span> <span class="mi">237</span><span class="p">,</span> <span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">)</span> +<span class="n">poptG1</span><span class="p">,</span> <span class="n">pcovG1</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata1</span><span class="p">,</span> <span class="n">recorteG1</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaG1</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata1</span><span class="p">,</span> <span class="n">poptG1</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG1</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG1</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG1</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG1</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMG1</span><span class="o">=</span><span class="n">FWHMG</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptG1</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 1 fotografÃa (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteG1</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 1 a partir de la gaussiana (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaG1</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 2 (Verde)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [413]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteG2</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">1</span><span class="p">],</span> <span class="mi">645</span><span class="p">,</span> <span class="mi">535</span><span class="p">,</span> <span class="mi">35</span><span class="p">,</span> <span class="mi">35</span><span class="p">)</span> +<span class="n">poptG2</span><span class="p">,</span> <span class="n">pcovG2</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata2</span><span class="p">,</span> <span class="n">recorteG2</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaG2</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata2</span><span class="p">,</span> <span class="n">poptG2</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG2</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG2</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG2</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG2</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMG2</span><span class="o">=</span><span class="n">FWHMG</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptG2</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 2 fotografÃa (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteG2</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 2 a partir de la gaussiana (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaG2</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">35</span><span class="p">,</span> <span class="mi">35</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 3 (Verde)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [414]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteG3</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">1</span><span class="p">],</span> <span class="mi">560</span><span class="p">,</span> <span class="mi">320</span><span class="p">,</span> <span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">)</span> +<span class="n">poptG3</span><span class="p">,</span> <span class="n">pcovG3</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata3</span><span class="p">,</span> <span class="n">recorteG3</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaG3</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata3</span><span class="p">,</span> <span class="n">poptG3</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG3</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG3</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG3</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG3</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMG3</span><span class="o">=</span><span class="n">FWHMG</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptG3</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 3 fotografÃa (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteG3</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 3 a partir de la gaussiana (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaG3</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 4 (Verde)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [415]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteG4</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">1</span><span class="p">],</span> <span class="mi">442</span><span class="p">,</span> <span class="mi">370</span><span class="p">,</span> <span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">)</span> +<span class="n">poptG4</span><span class="p">,</span> <span class="n">pcovG4</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata4</span><span class="p">,</span> <span class="n">recorteG4</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaG4</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata4</span><span class="p">,</span> <span class="n">poptG4</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG4</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG4</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG4</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG4</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMG4</span><span class="o">=</span><span class="n">FWHMG</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptG4</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 4 fotografÃa (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteG4</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 4 a partir de la gaussiana (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaG4</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 5 (Verde)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [416]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteG5</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">1</span><span class="p">],</span> <span class="mi">320</span><span class="p">,</span> <span class="mi">455</span><span class="p">,</span> <span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">)</span> +<span class="n">poptG5</span><span class="p">,</span> <span class="n">pcovG5</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata5</span><span class="p">,</span> <span class="n">recorteG5</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaG5</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata5</span><span class="p">,</span> <span class="n">poptG5</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG5</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG5</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG5</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG5</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMG5</span><span class="o">=</span><span class="n">FWHMG</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptG5</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 5 fotografÃa (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteG5</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 5 a partir de la gaussiana (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaG5</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div 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/VoPjJb0rqIeN72oSoOttZzTtr+H6gYtjZyPeLJbmus/GayLpN0rO3fTznPJ7V1Ttzoa76divd3bWr3XhW9dOOp/U2fr6LIK7utWyW9Jr13O6o4fUdp3V1tL0nF9gYVn4Ph9NhEn8dajbzHtW1L5YfpQPi/auIcb4GkY7R1jvecigl+dlZxrmRZ9d77RnLbC1W8d0cozScRxSybV0n6rO0dXEwYtI/tMZ9nRGxWMULs7NSjub9q5nGQ9H1JL3MxMc3UdDvEW86rlErkeL1Q+I3MGjly+05afoikG2yPjA3+SGy5NsnZKsbfPuEXz4gz4m9Tu6tcnEO2TMVJmPWcI+mVKobT/UDFmzie2SqOLDwuabWKD/WbImL0EMvxnK+ii/k6SferOCH0w9ILvUznSvp5ep6H11n/rnT/EhVHQ56W9KiKL4zx/DcVXwTrVRQw35pg3dEm8zpJ0lIV16CrzcpeNfK+qxiGsVZbCqGvq+giX63iZOBlZQOLYtKVP1Yx8cpjKk48rv3xm2zsUvGaPylpVUT8omb5/1BxtGuZiyEF/6riKNZ4zlHxvO5X8YXywvTH6UvjWBXj2O9X0aP4VaVz+mzPUDHe/EIBvaKvBTegMdtSPvLnkj6Z4vmEigJmIo+kbT+sIjH+QETc28i2xslvJiXlPKeo6NVak2KrnVykodc8Iu6W9FlJ16so6n9PEx/M/2Ta7/0qfv8vU8q76m0rIq5WkXfdLukmFYXBiD5J/1XF671ORUEwUsBM9HmsNdn3uNZk88N/1NaT4ElbZrF/WtIvVDz3c9JjX5A0U0Wes0zFaTKllHjvG8ltL1cxIdM1qeAb8R5tmZTmcRXv70ST83xIxZDUR1RMDPO1mrjXq5gc5jgV7+sjkv6PpOmS5GLSn/0lfXeiQB1bXRYNKKQewSdUdHXf3+FwJEm2v6lizPd3Ox1LFdn+sIohG6d3OhagGTwwI7RkUfM3fP4vb4qIxc3fMLDtsX2UpG9ExII6q27zbH9Q0nERUWqivF5i++eSPpTOj8Mk2f6sivMLvzTRelzUEi+w/VZJ16gY4vkZSXdoy6QoHRcRkxlmgFEiYrwpm4FqYmgmgApLvTQvUdGrt6+Kc9dGX5ZgmxARR9RfC+OJiNPKrMegFtRaoqL7+GEVX0DHBV3CALoZk7sAqK5pKoY5rldxcfrvqbimMtAS9PjhBRHxn7X1hSUBoLvR4wd0tYi4VlvPXIkkzQg50eQvQFNR+AEAqotxKwAAlMJPJgAAAAD0uLb2+A0MzI0999qz/orjGIqhJkSRd8pav/NfMmeeRLI5NmfHkKvP+ccMcp/H5uH812FKX9772YzPw/CYl8+ZjLzPdF/m8Z+HHnxIg4OPMd4O7Wcx1BM9b2BgIPZa1HjuBKD7PPjAQxocHGz7D1hbC78999pT1y27tuH2j28YzI4ht9iYM23n7Bim9E3Nav/M0PrsGHLnbJk5ZbvsGJ7a+HhW+ycy20vSvBm7ZrXfYdpO2TE8v/nZrPa57+X0/hlZ7V9z+FFZ7YEs1H3ocXst2lM/v+FnnQ4DQBMdcdjvd2S/nOMHAKiuPio/AADK4Bw/AAAAAOhx9PgBAKqLc/wAACglq8fP9jG2f2l7he2PNSsoAADqasXF26kj0WLkTgA6peEeP9v9kv5e0hskrZL0C9tXRsTdzQoOAIDxWW5Bj1/edEnA+MidAHRSTo/foZJWRMRvImKjpEskLWlOWAAA1Ge76bc6+1to+ye277Z9l+2PpOV/Y/te27fb/o7tOTVtzki9O7+0/cbWviLocuROADomp/CbL2llzd+r0rKt2D7Z9nLbywcHH8vYHQAAHTck6bSI2F/S4ZJOsb2/pKslHRgRB0n6laQzJCk9dpykAyQdI+lLqdcH26ZJ505r1+ZfygoApDbM6hkRSyNicUQsHhiY2+rdAQC2IXbzbxOJiDURcXO6v17SPZLmR8RVETGUVlsmaUG6v0TSJRGxISLul7RCRa8PMK7a3GnevIFOhwOgR+TM6rla0sKavxekZQAAtJwl9bXgHL/NZfdvL5L0Ckk3jHrofZK+le7PV1EIjhizhwfbDHInAB2TU/j9QtK+tvdW8aV1nKQ/bUpUAADUY7VkchdJA7aX1/y9NCKWbrVre3tJl0s6NSKeqln+cRXDQS9qRWCoPHInAB3TcOEXEUO2PyTpx5L6JZ0fEXc1LTIAAOpoUeE3GBGLJ9jnVBVF30URcUXN8pMkHSvp6IgYmRyUHh68gNwJQCdlXcA9In4o6YdNigUAgK7motI8T9I9EfG5muXHSDpd0pER8WxNkyslfdP25yTtIWlfSTe2MWR0GXInAJ2SVfgBANA5rbmOXx1HSDpB0h22b03LzpT0RUnTJV2dYloWER+IiLtsXyrpbhVDQE+JiLKnEQIA0DRtLfyGYkjrNqxtuP2vn1qRHcN+c343q30zLuy7OfM3/9HnHsmOYfdZC+qvNIHNL0xe17ipfdOy2u8yc7fsGJw5se0zQ+uzY+jLjKEvc2b4TcObstoHl7tGB7W77ouIn6mYV2a0cXtwIuJcSee2LCgAAEqgxw8AUElWy87xAwCg51D4AQCqqXWzegIA0HNafgF3AAAAAEBn0eMHAKgsj3m6HQAAGI3CDwBQWQz1BACgHAo/AEBlUfcBAFAO5/gBAAAAQI+jxw8AUEmW1UeXHwAApVD4AQAqi3P8AAAoh8IPAFBNXMcPAIDSKPwAAJVF3QcAQDlM7gIAAAAAPY4ePwBAJVkM9QQAoCwKPwBAZVH4AQBQDoUfAKCiTOEHAEBJFH4AgGpiVk8AAEpra+EXEdo4vLHh9nvPfkl2DDP7t8tq//SmJ7NjmN4/M6v9lL6p2TEMx3BW+z7nzwsUiqz2Vn7Cl/s8mhFDruHYnNW+z/1NigQAgBeLyPu97xYcaELV0eMHAKgs8jAAAMqh8AMAVBKzegIAUB6FHwCgsij8AAAoh8IPAFBZfRR+AACU0vDMFrYX2v6J7btt32X7I80MDAAAoJeQOwHopJwevyFJp0XEzbZnS7rJ9tURcXeTYgMAYHxmchdUDrkTgI5puPCLiDWS1qT7623fI2m+JL68AAAtZy7gjoohdwLQSU05x8/2IkmvkHRDM7YHAEAZ3XAtTaAR5E4A2i37Kty2t5d0uaRTI+KpMR4/2fZy28vXPbYud3cAAACVNpncae3awfYHCKAnZRV+tqeq+OK6KCKuGGudiFgaEYsjYvHOc3fO2R0AAFux3fQb0EqTzZ3mzRtob4AAelbDQz1d/DqeJ+meiPhc80ICAKAcCjVUCbkTgE7K6fE7QtIJkl5n+9Z0e3OT4gIAoC67+TeghcidAHRMzqyeP5M4qx4A0BlFocbPEKqD3AlAJ2VP7gIAAAAA6G5NuZwDAADtx2QsAACU1dbCb1jD2rB5Q8PtZ8/YITuGzTGU1f7Zzc9mx2DndbQOx3B2DE9teiKr/Yz+mdkx5Op3/se3GdvINRSbOrr/3OugRZPiABpB4QdMLCL/W3pYeXnH5uG83EuShmNzVvvc3EvKzxn63Z8dA995yNH5rBcAgAaRAwEAUA6FHwCgsjj6DQBAOUzuAgAAAAA9jh4/AEAlcTkHAADKo/ADAFQWhR8AAOVQ+AEAKou6DwCAcij8AAAVxXX8AAAoi8ldAAAAAKDH0eMHAKgsevwAACiHwg8AUEnM6gkAQHkUfgCAyqLuAwCgHAo/AEBl0eMHAEA5TO4CAEBJthfa/ontu23fZfsjafnOtq+2fV/6/05puW1/0fYK27fbfmVnnwEAYFtF4QcAqK7iRL/m3iY2JOm0iNhf0uGSTrG9v6SPSbomIvaVdE36W5LeJGnfdDtZ0pdb8TIAAFAPhR8AoKKK6/g1+zaRiFgTETen++sl3SNpvqQlki5Mq10o6e3p/hJJX4/CMklzbO/eghcDAIAJcY4fAKCaSnXQtXD39iJJr5B0g6RdI2JNeugRSbum+/MlraxptiotWyMAANqorYVfn/o0vX96w+0Hn1+bHUPO/iVp0/Cm7BhWPv1gVvsnNjyRHcNOM3bKaj976g7ZMcyeOjt7G7lyc8ZoQgwReVsZjs1Z7d3XDa8C0FUGbC+v+XtpRCytXcH29pIul3RqRDxV21MYEWGbfxjoCsMazt7G85ufy2r/2POPZsewbsNjWe1nTZmVHcOuM/M667ebkp/39Gem7kyItW2jxw8AUElWy5KYwYhYPO5+7akqir6LIuKKtPi3tnePiDVpKOdIprta0sKa5gvSMgAA2opz/AAAldXuc/xcrHCepHsi4nM1D10p6cR0/0RJ36tZ/p40u+fhkp6sGRIKAEDb0OMHAKisDgxbOkLSCZLusH1rWnampE9LutT2+yU9KOmd6bEfSnqzpBWSnpX03rZGCwBAQuEHAKisdtd9EfEzjX968NFjrB+STmlpUAAAlJA91NN2v+1bbH+/GQEBAAD0MnInAJ3QjB6/j6i4jlH+NI8AAJRV4pw8oEuROwFou6weP9sLJL1F0lebEw4AAOWMzOrZzsldgFzkTgA6JbfH7wuSTpfU+QuyAQC2ORRqqKAviNwJQAc03ONn+1hJj0bETXXWO9n2ctvL1z22rtHdAQDwIvT4oUoayZ3Wrh1sU3QAel3OUM8jJL3N9gOSLpH0OtvfGL1SRCyNiMURsXjnuTtn7A4AAKDSJp07zZs30O4YAfSohgu/iDgjIhZExCJJx0n6t4h4d9MiAwBgIi4u59DsG9Aq5E4AOonr+AEAKouhmQAAlNOUwi8irpV0bTO2BQBAGRbn5KG6yJ0AtBs9fgCAyqLwAwCgnKzr+AEAAAAAul9be/z63KfZU3douP1TG1dmx/Dc0LNZ7R96Oj+Gz/7797La7z13p+wY3n3AG7PaT3H+R2da37Ss9lMz20vScBd0eoeGO7z/6Oj+gRx0+KHXRUgRjX9PDw1vyo7hkWdXZ7X/7q9/kB3Dj351V1b739llXnYMJxxwbFb7A3Y6KDuGWVO2z2pv8aW5Let81gsAQCPMUE8AAMqi8AMAVBeFHwAApXCOHwAAAAD0OHr8AACVxVBPAADKofADAFSSJfVR9wEAUAqFHwCgoriAOwAAZVH4AQCqyVIfhR8AAKUwuQsAAAAA9Dh6/AAAlWQxuQsAAGVR+AEAKothKwAAlEPhBwCoLM7xAwCgHAo/AEAlMdQTAIDyGCUDAAAAAD2OHj8AQEWZoZ4AAJRE4QcAqCYz1BMAgLIo/AAAlWRxvgIAAGW1tfALhTYNb2q4/dS+qdkxPL7hiaz23773p9kx/PsF/y+r/YNHvTQ7hj/a78is9s8OPZcdw47T5mS13xybs2PI3UZfE9JOZ26jry+vx6MZzwHoFIZ6YlsQiobbDsVQ9v5XP7Mqq/23fnFjdgx3XHFzVvubXr5rdgy/t8uirPYv3eFl2THM7J+VtwHzm78t490HAAAAgB7HUE8AQGVxjh8AAOVQ+AEAKsliqCcAAGVR+AEAKouyDwCAcrLO8bM9x/Zltu+1fY/tVzUrMAAAgF5D7gSgU3J7/P5W0r9ExDtsT5OUOdUQAABlcQF3VBK5E4COaLjws72jpNdIOkmSImKjpI3NCQsAgInZnOOHaiF3AtBJOUM995a0VtLXbN9i+6u2t2tSXAAA1GW76TeghcidAHRMTuE3RdIrJX05Il4h6RlJHxu9ku2TbS+3vXzd4LqM3QEAsLU+u+k3oIUmnTsNDg62O0YAPSqn8FslaVVE3JD+vkzFl9lWImJpRCyOiMU7D+ycsTsAAIBKm3TuNDAw0NYAAfSuhgu/iHhE0krb+6VFR0u6uylRAQBQh1t0A1qF3AlAJ+XO6vlhSRelWal+I+m9+SEBAFAOQzNRQeROADoiq/CLiFslLW5OKAAATAbn5KF6yJ0AdEpujx8AAB1hi1k4AQAoKWdyFwAAAABABbS1xy8itHHzhobbT+ufnh3DxuEuuE5qf94R6r0W7Z4dwuxps7PaT+ufmh1DNxypH47NWe37nH/spN/9HW3vzOdgpsNABzHUE5hYM/6FTM/Mv2bv0IRLFe4+K6v53Dl5eY8kbT81L4Zm5AxADoZ6AgAqi7IPAIByOPQAAKgkqzMXcLd9vu1Hbd9Zs+zltpfZvjVdePvQtNy2v2h7he3bbb/omm0AALQDhR8AoLI6UfhJukDSMaOW/bWkcyLi5ZI+kf6WpDdJ2jfdTpb05WY8bwAAJovCDwCASYiI6yStG71Y0g7p/o6SHk73l0j6ehSWSZpjO/9EbQAAJolz/AAAFeVWTRI1YHt5zd9LI2JpnTanSvqx7c+oOKj66rR8vqSVNeutSsvWNClWAABKofADAFSS1bJhK4MRMdkLbH9Q0kcj4nLb75R0nqTXNz80AAAaw1BPAEA1pQu4N/vWoBMlXZHuf1vSoen+akkLa9ZbkJYBANBWFH4AAOR7WNKR6f7rJN2X7l8p6T1pds/DJT0ZEQzzBAC0HUM9AQCV1YkLuNu+WNJRKs4FXCXpLEl/JulvbU+R9LyKGTwl6YeS3ixphaRnJb237QEDACAKPwBARY1cx6/dIuJd4zz0H8ZYNySd0tqIAACoj8IPAFBZLZrVEwCAnkPhBwCoKKtPFH4AAJTB5C4AAAAA0OPo8QMAVBZDPQEAKIfCDwBQSXZnJncBAKCKKPwAAJVlzvEDAKCUthZ+tjWtf3rD7fuG809JnOL+rPZvfelh2TE8+YENWe1POPDI+ivVsdus3bLa92e+jpLU1wWnmBYzrWdoQs45pW9qVvvc9yI3cSbxRicx1BPbgpzv2Sl907L3v9f2i7Laf+iwY7JjOGzPBVnt99whL++RpMW7vDKr/fT+mdkx2J3PnVBdfHoAAAAAoMcx1BMAUEmWOccPAICSKPwAAJVlBq4AAFAKhR8AoLLo8QMAoJysQ6W2P2r7Ltt32r7Y9oxmBQYAQD22m34DWoncCUCnNFz42Z4v6S8kLY6IAyX1SzquWYEBAAD0EnInAJ2UO9RziqSZtjdJmiXp4fyQAACoz+k/oGLInQB0RMM9fhGxWtJnJD0kaY2kJyPiqmYFBgDAhFyc49fsG9Aq5E4AOilnqOdOkpZI2lvSHpK2s/3uMdY72fZy28vXDa5rPFIAAEbhHD9USSO50+DgYLvDBNCjciZ3eb2k+yNibURsknSFpFePXikilkbE4ohYvPPAzhm7AwBgC0vqa8F/QAtNOncaGBhoe5AAelPOL9xDkg63PcvFIdKjJd3TnLAAAAB6DrkTgI5peHKXiLjB9mWSbpY0JOkWSUubFRgAABNjaCaqhdwJQCdlzeoZEWdJOqtJsQAAMCkUfqgacicAnZJ7OQcAADqmj8s5AABQCmexAwAAAECPa2uP33AMa/2mpxpuv8uM3bJjmL/dgqz2c2fMzY7hr488KKt9My5YPHd63ixhQzGUHUOf8447TPHU7Bim9OX9E3ATjp1sznwth4Y3ZceQY1jDHd0/tl0WQz3R++y8z/mUJqR6O2XmDEft8drsGA7Z5ZCs9tP7pmfHsN3U2R2PITd3wraNoZ4AgGpKF3AHAAD1UfgBACrKTRkBAQDAtoDCDwBQSRbDngAAKItfTAAAAADocfT4AQAqi8ldAAAoh8IPAFBZnOMHAEA5FH4AgIoys3oCAFAShR8AoJIsevwAACiLyV0AAAAAoMfR4wcAqCyGegIAUA6FHwCgmiyZ6/gBAFAKhR8AoKLMOX4AAJRE4QcAqCSLoZ4AAJTFGBkAAAAA6HH0+AEAKsv0+AEAUAqFHwCgsvo4xw8AgFLaWvhN8RTNnT6v4fZT+6Zlx7D91Nkdbd8Mzw09m72N3KPk0zw9O4Zc3XCkvxkR9Dnvn2FoOLN9HibXQKdY3fE9AHSzvibMfJubf+0wdU52DNtP3SGrvZtwdlPua8nvJTqNc/wAAAAAoMcx1BMAUFHmOn4AAJRE4QcAqCzO8QMAoBwKPwBAJdmc4wcAQFl1x8jYPt/2o7bvrFm2s+2rbd+X/r9Ta8MEAODF3IL/gFzkTgC6UZmTIy6QdMyoZR+TdE1E7CvpmvQ3AAA9b6ykPi3/sO17bd9l+69rlp9he4XtX9p+Y/sjRgdcIHInAF2mbuEXEddJWjdq8RJJF6b7F0p6e3PDAgCgHstu/q2ECzQqqbf9WhW/jQdHxAGSPpOW7y/pOEkHpDZfst3fxBcBXYjcCUA3anQ6tF0jYk26/4ikXcdb0fbJtpfbXv7Y4GMN7g4AgBfrk5t+q2ecpP6Dkj4dERvSOo+m5UskXRIRGyLifkkrJB3avFcAFdJQ7rR27WB7ogPQ87LnwY6I0ATXgI6IpRGxOCIWzx2Ym7s7AAAkjVzAva/pN0kDI0l3up1cIpyXSfoD2zfY/qntQ9Ly+ZJW1qy3Ki3DNmwyudO8eQNtjAxAL2t0Vs/f2t49ItbY3l3So3VbAADQVC2bjGUwIhZPss0USTtLOlzSIZIutf2SpkeGKiN3AtBRjfb4XSnpxHT/REnfa044AABU0ipJV0ThRknDkgYkrZa0sGa9BWkZtj3kTgA6qszlHC6WdL2k/Wyvsv1+SZ+W9Abb90l6ffobAIC26tDkLmP5rqTXppheJmmapEEVyf5xtqfb3lvSvpJuzH/m6GbkTgC6Ud2hnhHxrnEeOrrJsQAAMCmduO5eSuqPUnEu4CpJZ0k6X9L56RIPGyWdmM7jusv2pZLuljQk6ZSI2Nz2oNFW5E4AulGj5/gBANBxGT10DZsgqX/3OOufK+nc1kUEAEB9FH4AgEqyVOryCwAAoN2Fn60pfY3vctPwxiYG05jp/TOytzEcw1ntN/j57BiKEUiN6+/LvhKI+p338Rtuwmip3NfBTXkdMq/lnNl+M6POAAAT6HPmb11ue0mZv5QARI8fAKCq8iZjAQBgm0LhBwCoLDd8VSIAALYtFH4AgMqixw8AgHI4VAoAAAAAPY4ePwBAJVmduY4fAABVROEHAKgoq4+hngAAlELhBwCoLHr8AAAoh8IPAFBZTO4CAEA5TO4CAAAAAD2OHj8AQCUVk7tw/BIAgDIo/AAAFWWGegIAUBKFHwCgsvqY3AUAgFIo/AAA1WQmdwEAoCxOjgAAAACAHkePHwCgkorJXejxAwCgDAo/AEBlMdQTAIBy2lr4WVJfxujSjbExO4Y+V39064z+mdnbmNY/Pav9FE/NjiHX5hjK3kYo8trHcHYMNsdfgMaYyzkAAFASGScAoLL66PEDAKAUDpUCAAAAQI+jxw8AUElM7gIAQHkUfgCAymJyFwAAyqk71NP2+bYftX1nzbK/sX2v7dttf8f2nJZGCQDAi7gl/wG5yJ0AdKMy5/hdIOmYUcuulnRgRBwk6VeSzmhyXAAAAFV1gcidAHSZuoVfRFwnad2oZVdFvDCX/jJJC1oQGwAAE7Ld9BuQi9wJQDdqxjl+75P0rfEetH2ypJMlacFCvuMAAM2Re21YoINK504L91zYrpgA9LisX0zbH5c0JOmi8daJiKURsTgiFg/Mm5uzOwAAtjA9fqieyeZO8+YNtC84AD2t4R4/2ydJOlbS0RERTYsIAIBSmIwF1ULuBKCTGir8bB8j6XRJR0bEs80NCQAAoLeQOwHotLqFn+2LJR0lacD2KklnqZiJarqkq9OwmGUR8YEWxgkAwIswNBPdiNwJQDeqW/hFxLvGWHxeC2IBAGBSGOqJbkTuBKAbNWNWTwAA2s6i8AMAoCwKPwBAdTHUEwCAUtpa+PW5TzOmzGp8A0P1V6kfQ39W++HYnB3DsIaz2s+asn12DFP7pmW1D+VPRjY0vKnjMWS/n56aHUOu3M9TRF57AAAAdD96/AAAFcXlHAAAKIvCDwBQWczqCQBAORR+AIDKoscPAIByKPwAAJVF4QcAQDl9nQ4AAAAAANBa9PgBACrJ4hw/AADKovADAFQUs3oCAFAWhR8AoLIo/AAAKIfCDwBQTWaoJwAAZTG5CwAAAAD0OAo/AEBluQX/1d2nfb7tR23fOcZjp9kO2wPpb9v+ou0Vtm+3/coWvAwAANRF4QcAqKSRWT2bfSvhAknHvCgee6GkP5T0UM3iN0naN91OlvTl3OcNAEAjKPwAABXViv6++oVfRFwnad0YD31e0umSombZEklfj8IySXNs796MZw8AwGRQ+AEAkMn2EkmrI+K2UQ/Nl7Sy5u9VaRkAAG3FrJ4AgMpq0eUcBmwvr/l7aUQsHTcGe5akM1UM8wQAoCtR+AEAKqtFl3MYjIjFk1h/H0l7S7otxbNA0s22D5W0WtLCmnUXpGUAALRVWwu/CGk4hhtuv2H4+ewYZvTPymo/rMbjH7FpeGNW+6l90zoew+bYnB1Dn/NGGkdE/ZUqIPcztXl4qKP77413AVXVDRdwj4g7JO0y8rftByQtjohB21dK+pDtSyQdJunJiFjTmUgBANsyzvEDAFSS1bHLOVws6XpJ+9leZfv9E6z+Q0m/kbRC0lck/XkTnjoAAJPGUE8AACYhIt5V5/FFNfdD0imtjgkAgHoo/AAAFVX6unsAAGzz6g71tH2+7Udt3znGY6fZDtsDrQkPAICJuAU3IA+5E4BuVOYcvwskHTN6oe2FKqaufqjJMQEAUJ+LWT2bfQOa4AKROwHoMnULv4i4TtK6MR76vKTTxaR+AIAO6cTkLkA95E4AulFDs3raXiJpdUTc1uR4AAAAeg65E4BOm/TkLrZnSTpTxVCFMuufLOlkSVq458I6awMAUB49dKgCcicA3aCRHr99JO0t6bZ0kdoFkm62vdtYK0fE0ohYHBGLBwY4jxkA0BxW88/v4xw/tEjDudO8eeROAJpj0j1+EXGHpF1G/k5fYIsjYrCJcQEAUBc9fqgCcicA3aDM5RwulnS9pP1sr7L9/taHBQBAfUzugm5E7gSgG9Xt8YuId9V5fFHTogEAAKg4cicA3WjSQz0BAOgWnJMHAEA5FH4AgMpiaCYAAOVQ+AEAKmlkVk8AAFBfWwu/W26+ZXC7qbMfnGCVAUmdnuGKGLojhk7vnxjKx7BXuwIBgG3NzTfdMjhzynbkTt0fQ6f3TwzViqEjuVNbC7+ImDfR47aXR8TidsVDDN0bQ6f3TwzdFQMwHoZ6oteRO1Ujhk7vnxiIoQyGegIAKozCDwCAMij8AACVRdkHAEA53Vb4Le10ACKGEZ2OodP7l4hhRDfEAIyJyV2ArviOJobO718ihhHEMA5HRKdjAABg0g5+5UHx45//oOnb3X3Wnjd147kZAADk6LYePwAAJoEePwAAyqDwAwBUFmUfAADl9HU6gBG2j7H9S9srbH+sA/tfaPsntu+2fZftj7Q7hhRHv+1bbH+/Q/ufY/sy2/favsf2qzoQw0fTe3Cn7Yttz2jDPs+3/ajtO2uW7Wz7atv3pf/v1IEY/ia9F7fb/o7tOe2Ooeax02yH7YFWxgCU5xbdgO5H3rRVLORO5E7kTiV0ReFnu1/S30t6k6T9Jb3L9v5tDmNI0mkRsb+kwyWd0oEYJOkjku7pwH5H/K2kf4mI35F0cLtjsT1f0l9IWhwRB0rql3RcG3Z9gaRjRi37mKRrImJfSdekv9sdw9WSDoyIgyT9StIZHYhBthdK+kNJD7V4/0BpdjG5S7NvQLcjb3oRcidyp1rkTuPoisJP0qGSVkTEbyJio6RLJC1pZwARsSYibk7316v4Rzu/nTHYXiDpLZK+2s791ux/R0mvkXSeJEXExoh4ogOhTJE00/YUSbMkPdzqHUbEdZLWjVq8RNKF6f6Fkt7e7hgi4qqIGEp/LpO0oN0xJJ+XdLokZoMCgM4jb0rInV5A7rRlGbnTOLql8JsvaWXN36vUgS+PEbYXSXqFpBvavOsvqPiADLd5vyP2lrRW0tfSkImv2t6unQFExGpJn1FxdGSNpCcj4qp2xlBj14hYk+4/ImnXDsUx4n2SftTundpeIml1RNzW7n0DAMZE3rTFF0TuRO40PnKnGt1S+HUN29tLulzSqRHxVBv3e6ykRyPipnbtcwxTJL1S0pcj4hWSnlHru+i3ksaCL1HxRbqHpO1sv7udMYwliuuedOyIje2PqxhWc1Gb9ztL0pmSPtHO/QJluQX/ASivU3lT2je5k8idxkPu9GLdUvitlrSw5u8FaVlb2Z6q4svrooi4os27P0LS22w/oGLIxutsf6PNMayStCoiRo7YXabiy6ydXi/p/ohYGxGbJF0h6dVtjmHEb23vLknp/492IgjbJ0k6VtLx0f4Lb+6j4ofktvTZXCDpZtu7tTkOYEwUfthGkTcVyJ0K5E6jkDuNrVsKv19I2tf23ranqTgh9cp2BuDijP7zJN0TEZ9r574lKSLOiIgFEbFIxfP/t4ho69GaiHhE0krb+6VFR0u6u50xqBimcLjtWek9OVqdO2H7SkknpvsnSvpeuwOwfYyKISxvi4hn273/iLgjInaJiEXps7lK0ivTZwUA0BnbfN4kkTvVIHeqQe40vq4o/NIJmB+S9GMVH9RLI+KuNodxhKQTVBwtujXd3tzmGLrBhyVdZPt2SS+X9Kl27jwdMbtM0s2S7lDxGV3a6v3avljS9ZL2s73K9vslfVrSG2zfp+Jo2qc7EMPfSZot6er0mfyHDsQAAOgi5E1dh9yJ3KkSuZPb3/sJAEC+l/+Hg+Oaf2/+/AUDM3a7KSIWN33DAAB0UFf0+AEAAAAAWmdKpwMAAKAxTMYCAEBZ9PgBAAAAQI+jxw8AUGH0+AEAUAaFHwCgkizKPgAAyqLwAwBUVnHJKgAAUA+FHwCgwij8AAAog8ldAAAAAKDH0eMHAKgs+vsAACiHwg8AUGGUfgAAlEHhBwCoKDO5CwAAJXGOHwAAAAD0OAo/AAAAAOhxDPUEAFRScQF3hnoCAFAGhR8AoMIo/AAAKIOhngCAynILbnX3aZ9v+1Hbd9Ys+xvb99q+3fZ3bM+peewM2yts/9L2G3OfMwAAjaDwAwBUlu2m30q4QNIxo5ZdLenAiDhI0q8knZHi21/ScZIOSG2+ZLu/Wc8fAICyKPwAAJiEiLhO0rpRy66KiKH05zJJC9L9JZIuiYgNEXG/pBWSDm1bsAAAJBR+AICKasVAz6acM/g+ST9K9+dLWlnz2Kq0DACAtmJyFwBAZbVoapcB28tr/l4aEUtLxWN/XNKQpItaEhkAAA2i8AMAVFhLSr/BiFg86UjskyQdK+noiIi0eLWkhTWrLUjLAABoK4Z6AgCQyfYxkk6X9LaIeLbmoSslHWd7uu29Je0r6cZOxAgA2LbR4wcAqCar7Cyczd2tfbGko1QMCV0l6SwVs3hOl3R1imlZRHwgIu6yfamku1UMAT0lIja3PWgAwDaPwg8AgEmIiHeNsfi8CdY/V9K5rYsIAID6KPwAAJVUzMHZ/h4/AACqyFvOPwcAoDps/4ukgRZsejAiRl+gHQCASqPwAwAAAIAex6yeAAAAANDjKPwAAAAAoMdR+AEAAABAj6PwAwAAAIAeR+EHAAAAAD3u/wO4bIDtdRuCegAAAABJRU5ErkJggg== +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 6 (Verde)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [417]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteG6</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">1</span><span class="p">],</span> <span class="mi">535</span><span class="p">,</span> <span class="mi">335</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span> +<span class="n">poptG6</span><span class="p">,</span> <span class="n">pcovG6</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata6</span><span class="p">,</span> <span class="n">recorteG6</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaG6</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata6</span><span class="p">,</span> <span class="n">poptG6</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG6</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG6</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG6</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG6</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMG6</span><span class="o">=</span><span class="n">FWHMG</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptG6</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 6 fotografÃa (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteG6</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 6 a partir de la gaussiana (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaG6</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 7 (Verde)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [418]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteG7</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">1</span><span class="p">],</span> <span class="mi">540</span><span class="p">,</span> <span class="mi">345</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span> +<span class="n">poptG7</span><span class="p">,</span> <span class="n">pcovG7</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata7</span><span class="p">,</span> <span class="n">recorteG7</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaG7</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata7</span><span class="p">,</span> <span class="n">poptG7</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG7</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG7</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG7</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG7</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMG7</span><span class="o">=</span><span class="n">FWHMG</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptG7</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 7 fotografÃa (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteG7</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 7 a partir de la gaussiana (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaG7</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 8 (Verde)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [419]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteG8</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">1</span><span class="p">],</span> <span class="mi">620</span><span class="p">,</span> <span class="mi">306</span><span class="p">,</span> <span class="mi">20</span><span class="p">,</span> <span class="mi">20</span><span class="p">)</span> +<span class="n">poptG8</span><span class="p">,</span> <span class="n">pcovG8</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata8</span><span class="p">,</span> <span class="n">recorteG8</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaG8</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata8</span><span class="p">,</span> <span class="n">poptG8</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG8</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG8</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG8</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG8</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMG8</span><span class="o">=</span><span class="n">FWHMG</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptG8</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 8 fotografÃa (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteG8</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 8 a partir de la gaussiana (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaG8</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">20</span><span class="p">,</span> <span class="mi">20</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 9 (Verde)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [420]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteG9</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">1</span><span class="p">],</span> <span class="mi">545</span><span class="p">,</span> <span class="mi">360</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span> +<span class="n">poptG9</span><span class="p">,</span> <span class="n">pcovG9</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata9</span><span class="p">,</span> <span class="n">recorteG9</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaG9</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata9</span><span class="p">,</span> <span class="n">poptG9</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG9</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG9</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG9</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG9</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMG9</span><span class="o">=</span><span class="n">FWHMG</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptG9</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 9 fotografÃa (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteG9</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 9 a partir de la gaussiana (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaG9</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 10 (Verde)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [421]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteG10</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">1</span><span class="p">],</span> <span class="mi">615</span><span class="p">,</span> <span class="mi">394</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span> +<span class="n">poptG10</span><span class="p">,</span> <span class="n">pcovG10</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata10</span><span class="p">,</span> <span class="n">recorteG10</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaG10</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata10</span><span class="p">,</span> <span class="n">poptG10</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG10</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG10</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG10</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG10</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMG10</span><span class="o">=</span><span class="n">FWHMG</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptG10</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 10 fotografÃa (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteG10</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 10 a partir de la gaussiana (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaG10</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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gBNtpjEaSzXCUqtGY/Ox8J7Wmz7ke9EPnmyg6Rb2yxr9Os1+n4zrdYZ81iv9H7cOOr9mBkRL1Nrxyu1gu2f35ORbr3NXptmx/XGOrUq635J2zSs/8gJ49xi+KFIY4+fo3Ri/Mj82MUR8WKlxOO3SvHcJiq+xyPPnWiM2CrO25B/dzcoJUxS6mJ6oaT5EbG9pC+0U7dsvDivSnz7NUkH2X62UqvtSHflFZK+NupztG1EfKxx98aqV/5cNNZzhaS/HlXejIj4WcM6LeO8vkr4bP+VNw5cvUvpBRvO9/+kNBZtPF+QdEp+Y+V0nbdFbWx6ptJZsHuc+ub+fYt6buXU33lI0lSnQbQjZ2bOlPQK23/h1Kf6w5IuGNUK11Rugv6ZpH/KZe4t6S3aOJPlnyQtcJ7xp431z5V0otMA4blKH/TxbKv0mq/O+/kmpTMg7ZimdBBZLWm97UO0MVFr5iqlM1pjdonKX7I9tHEW05mS7pX053zm6m1jPbeJcyW90/Y824/WplPcTrTuymfTzlPqh39TRCzJD/2npCfbPiJ/Tray/Sxv7GM+2s+VWhXemdd9tTbtYvBFScfms162va3ToOaZUhrALemZSuMGgf7V5Ulb8kH3y5KWRcQnJSl3JXpsRCyIiAVK3Tb3jYjblIKQI/P38ABJ90TEqtpeD/TcJIxJZiodj1bncj6gzVsHR3uZ7ec6jVv7iKQrcmxSpaxNYpyKGuOeeUrjKEdcJek+p4l1ZjhN5raX7Wc1L2oTM5XG2t3tNPHOyeOs+3OlJObtTpPhLdKmx/VWZV0j6fD8vm4y54DtF9h+Wn5/71Xq4jns1Cq8KL/HDyt9foa1uSrvy4iJxoiXStrXY4wBzb+li5TGyC5rqN+dEfGQ7f2U5jxo13jv/YTj20hDhy5X6lZ6aT4OSCnGfoXtl+bP0HTbz/fYk/h8V9Ketl/t1FL6Tm3a6+sLud575rptb/uRYUD5N2AHbTrWcTOlJnwjs1KO3L6Vlz9LaQzFn5UOru+K1MdaSn3fz3Bq8jysSZmS9Jn8vEts36f04uzfRn0+JGlfpbMc31VqvRnPF5W+rK9T6rP+oHL3vkh9po9V+pG9XenDO3pikfG8TmmilVuVBv2eHGnCFClN6CFJd9he2sb6H1YKWG6U9H2lBOXhsTYcEddL+helH6s/KQ24/Wk7lc4Hj3cqfeHuUvqSXjjO+muVBjSPnkjmsyOfC6WzK/8QafYxKQ2Mfb1SV5QvSjpH7fuiUjeIayUtVcN7PNG6NzhDqSl+pJl/pKyXKI0JuFWp68H/U0ooN5Nfh1dLOlqpGf+1o+q2RGnCmc/mui3P6454haTLIuLWNuoLlGuow7fWDlT63X6hUzefa2yPd6b/IqXJIpYr/Z5M5HcdZSMmSS5WmnL+90rd4R5S6y6U31BKWO5UOvk4ckyvUlazGGeiPpS3d6PSWPxHLu0UaUzaoUpj52+UtEZp3oPt2yj300pDTdYovY9jTs3fcFx/i1I3vDcqnQweib9alfV/lXob3JX35xsNjz1eKZa7VylJ+lHexyFJf6sUd9ypNO6t2UnxKu/LyH5NKEaMiD9J+oHS5DyNvpO/U/cqjV88KjaON/wbSR/O35cPKMVl7Rrvva8a3zaL81bkfTpJKYFcoXRSpumRJyLWKM3j8DFJdyjN9PzThse/pRQnnu3Uxfc3SuP+Rrxe0hmRxsmOyZt2IcZkZvttkg6PiKqDvzvKaUajn0jaJ9ofsI0Gtq+U9JaI+E2v6wJU5dnTQ4sWdLbQ0353dUQsbL0igCqcLs+0MiL+odd1KV0+Vn8hIr7S67p0k9MM5WdI2i9ISCbMacjRtZKeF/ka2GPhopSTmNN0s09QOqOxm1K/8Xan/q1dpNnHmg4qRnsiop2zxUDZ2r92HgAUz/ZfKl2SYI3SxG17awIX7B4UuWWtnS6zaCK36rUVJ5PwTW7TlC5dsKtSt4KzJX2ulxUCgKbI9wAMjt2VuiNuq9QV/DWM+UWdSPgmsYi4Se1PugIAvUMLH9BXIuLoXtehVHlW4M1mBgbqQsIHAChfqVOMAQBQOA6hAAAAADCgamnhmz17duyyYOfWK26B4Wh2+ZDOcRcGjERb1xAtfxt168Z70Q11vxdDmtJ6pS1w8003a82aNYPxZqC/WHTpxEDrRtwEoPuWXv3LNRExp9f1qCXh22XBzvrplZfXUfQjHt7wUK3lD23RdT3bU3fSKknrhtfWvo26bTU0rddV6Ii1w+NeImWLbTt1Zq3lP3f/59VaPjAu8j0MsG7ETQC6b8bUbW/qdR0kxvABAPrBEBkfAABVMIYPAAAAAAYULXwAgPIxhg8AgEpI+AAAZbMYwwcAQEUkfACAwlnucAtf/89fDABAe0j4AADFI+EDAKAaJm0BAAAAgAHVVsJn+2Dbv7O93Pb76q4UAACN7M7egLoROwEoRcsunbanSPo3SS+WtFLSL2xfGBHX1105AAAsaajDWdqGjpYGbIrYCUBJ2mnh20/S8oi4ISLWSjpb0qJ6qwUAQOY0hq+TN6BmxE4AitFOwjdX0oqG+yvzsk3YPsb2EttLVq9e06n6AQBAwod+0zJ2Im4C0C0dm7QlIhZHxMKIWDhnzuxOFQsAADBwiJsAdEs7l2W4RdL8hvvz8jIAALqAVjn0HWInAMVop4XvF5J2s72r7WmSDpd0Yb3VAgBgI2bpRJ8hdgJQjJYtfBGx3vbbJV0saYqk0yLiutprBgCA0iydtPChnxA7AShJO106FREXSbqo5roAALA5k/Ch/xA7AShFxyZtAQAAAACUpa0WPgAAesmihQ8AgCpI+AAAxaNLJwAA1ZDwAQCKR74HAEA1jOEDAAAAgAFFCx8AoGiWNUQTHwAAlfRtwmfX2zg55Cm1li9JwzFc+zbqForat/Hwhodq30Y3xgcN1dyg/tCGB2otf1j9/3lF/2IMH4BB0I3YLwYgvpS6EetPno6OfZvwAQAmCa7DBwBAZSR8AIDike8BAFDN5GnLBAAAAIBJhhY+AEDRLLp0AgBQFQkfAKB4JHwAAFRDl04AQOEsu7O3llu059v+oe3rbV9n+115+T/b/q3tX9n+lu1ZDc850fZy27+z/dL6Xg8AANpHwgcAKFuepbObCZ+k9ZKOj4g9JB0g6Tjbe0i6VNJeEbG3pN9LOlGS8mOHS9pT0sGSPmd34fo+AAC0QMIHAMAoEbEqIpbm/++TtEzS3Ii4JCLW59WukDQv/79I0tkR8XBE3ChpuaT9ul1vAABGYwwfAKB4NQzhm217ScP9xRGxuPm2vUDSPpKuHPXQmyWdk/+fq5QAjliZlwEA0FMkfACAotU0S+eaiFjYctv2dpLOl/TuiLi3Yfn7lbp9ntnpigEA0EkkfACA4vVilk7bWykle2dGxAUNy4+WdKikgyIi8uJbJM1vePq8vAwAgJ5iDB8AoHhDdkdvrThlmF+WtCwiPtmw/GBJJ0h6ZUQ80PCUCyUdbntr27tK2k3SVR19EQAAqIAWPgAANnegpCMk/dr2NXnZSZJOlbS1pEtzq+MVEXFsRFxn+1xJ1yt19TwuIjZ0v9oAAGyKhA8AUDbXMmnLuCLi8rTlzVw0znNOkXRKbZUCAKACEj4AQNGstq+dBwAARiHhAwAUz00b2wAAQCtM2gIAAAAAA4oWPgBA8ejSCQBANSR8AIDikfABAFANCR8AoHjkewAAVEPCBwAomk0LHwAAVTFpCwAAAAAMKFr4AACF4zp8AABUVUvCNxzDenjDQ3UU3TUburCNiOHat1H3tavuX39freVL0so/r6h9GzOmzqh9GwtmPrHW8h9Yf3+t5Q9HN74VQHMkfAC6YcPw+lrLf3DDA7WWL0l/Xndv7duY4im1b2PbrWbWWv7WU+qP/UpBCx8AoHjkewAAVEPCBwAoHi18AABUw6QtAAAAADCgaOEDABSNyzIAAFAdCR8AoHgkfAAAVEPCBwAoHvkeAADVkPABAArHdfgAAKiKSVsAAAAAYEDRwgcAKB4tfAAAVNOyhc/2fNs/tH297etsv6sbFQMAQNo4S2cnb0CdiJ0AlKSdFr71ko6PiKW2Z0q62valEXF9zXUDAEASk7ag7xA7AShGy4QvIlZJWpX/v8/2MklzJfGjBQDoClrl0E+InQCUZEKTttheIGkfSVfWUhsAAIABQuwEoNfaTvhsbyfpfEnvjoh7mzx+jO0ltpfcseaOTtYRADDZpYF8nbsBXTBe7NQYN61evaY3FQQwKbSV8NneSukH68yIuKDZOhGxOCIWRsTCx8x+TCfrCACY1Do7YQvdQ9ENrWKnxrhpzpzZ3a8ggEmj5Rg+pyPjlyUti4hP1l8lAAAa0CiHPkPsBKAk7bTwHSjpCEkvtH1Nvr2s5noBAAD0K2InAMVoZ5bOyyVxbhUA0BMWs3SivxA7AShJO9fhAwCgp0j4AACohoQPAFA8Ej4AAKoh4QMAFI98DwCAaiZ04XUAAAAAQP+ghQ8AUDaunQcAQGUkfACAojFLJwAA1dWW8EUM11W0JGnq0LRay187/FCt5UvSuuF1XdjG2lrLv+pPV9ZaviSdetVFtW9j5ozptW/jvfsfXmv5u2y3oNbypai5fGBs3U74bM+X9FVJj1P68C+OiM/Y3kHSOZIWSPqjpMMi4q58oe3PSHqZpAckHR0RS7taaWDADdccW0rSgxseqLX8pWt+UWv5kvTN332/9m3MnFZvHC5Jr939FbWW/+Tt96i1/JIwhg8AUDznbp2durVhvaTjI2IPSQdIOs72HpLeJ+m/I2I3Sf+d70vSIZJ2y7djJH2+068BAABVkPABADBKRKwaaaGLiPskLZM0V9IiSWfk1c6Q9Kr8/yJJX43kCkmzbO/Y3VoDALA5xvABAMrm3l6WwfYCSftIulLS4yJiVX7oNqUun1JKBlc0PG1lXrZKAAD0EAkfAKB4NYzhm217ScP9xRGxuMl2t5N0vqR3R8S9jfWIiLDN4FYAQNFI+AAARbNquSzDmohYOO527a2Ukr0zI+KCvPhPtneMiFW5y+btefktkuY3PH1eXgYAQE8xhg8AULxuT9qSZ938sqRlEfHJhoculHRU/v8oSf/RsPxIJwdIuqeh6ycAAD1DCx8AAJs7UNIRkn5t+5q87CRJH5N0ru23SLpJ0mH5sYuULsmwXOmyDG/qam0BABgDCR8AoHjdnrQlIi5XuuZ7Mwc1WT8kHVdrpQAAqICEDwBQNnf/wusAAAwKEj4AQPlI+AAAqIRJWwAAAABgQNHCBwAoHl06AQCohoQPAFA0Sxoi3wMAoBISPgBA4Wq58DoAAJMCCR8AoGyWhkj4AACohElbAAAAAGBA0cIHACiaxaQtAABURcIHACge3VEAAKiGhA8AUDzG8AEAUA0JHwCgaHTpBACgOnrJAAAAAMCAooUPAFA406UTAICKSPgAAGUzXToBAKiKhA8AUDSL8QcAAFRVS8JnWVOG6s0lp9Zc/gPr19daviSt3fBQ7dt4YMMDtZZ/5apf1Vq+JF3+tctr34YeM732Tbxwl6fUWv4uT1pQa/lAL9GlE0DEcO3buHft3bWWf9ayS2otX5JO//i3at9GN+KmRx//qFrL33nPBbWWXxJOmgIAAADAgKJLJwCgeIzhAwCgGhI+AEDRLLp0AgBQFQkfAKB4pHsAAFTDGD4AAAAAGFC08AEACseF1wEAqIqEDwBQNJsxfAAAVEXCBwAoHrN0AgBQTdsJn+0pkpZIuiUiDq2vSgAAbIoWPvQjYicAJZjIpC3vkrSsrooAAAAMGGInAD3XVsJne56kl0v6Ur3VAQBgU67hBtSN2AlAKdrt0vlpSSdImllfVQAAaI4unehDnxaxE4ACtGzhs32opNsj4uoW6x1je4ntJWvWrOlYBQEAk126LEMnb0Cd2omdGuOm1auJmwDUp50unQdKeqXtP0o6W9ILbX999EoRsTgiFkbEwtmzZ3e4mgCAycpOs3R28gbUrGXs1Bg3zZlD3ASgPi0Tvog4MSLmRcQCSYdL+kFEvLH2mgEAAPQhYicAJeE6fACA4tENEwCAaiaU8EXEZZIuq6UmAACMgXQP/YrYCUCv0cIHACiaRQsfAABVTeTC6wAA9ES3Z+m0fZrt223/pmHZM2xfYfuaPLvifnm5bZ9qe7ntX9net8aXAgCACSHhAwBgc6dLOnjUso9L+lBEPEPSB/J9STpE0m75doykz3enigAAtEaXTgBA4bp/KYWI+LHtBaMXS3pU/n97Sbfm/xdJ+mpEhKQrbM+yvWNErOpObQEAGBsJHwCgaFYt3VFm217ScH9xRCxu8Zx3S7rY9idylZ6Tl8+VtKJhvZV5GQkfAKDnSPgAAGXLF17vsDURsXCCz3mbpPdExPm2D5P0ZUkv6nTFAADopFoSvlBoOIbrKHrjNiJqLX9DrK+1fEkaVr2vkSRtPbR17duo3br6Xyfdu7b2Tey43Zxay6+/yxuzJGLSO0rSu/L/35T0pfz/LZLmN6w3Ly8D0GeGXO/0FtOmTKm1fEnSNl1oz+nCNqZNqXcbnkRxDZO2AACK1+1ZOsdwq6S/zP+/UNL/5P8vlHRknq3zAEn3MH4PAFAKunQCAIrWi+vw2T5L0vOVxvqtlHSypLdK+oztqZIeUpqRU5IukvQyScslPSDpTV2tLAAA4yDhAwAUrwezdL5ujIee2WTdkHRcvTUCAKAaEj4AQOGsoUk01gIAgE5iDB8AAAAADCha+AAAxet2l04AAAYFCR8AoGh29ydtAQBgUJDwAQCKN5mulwQAQCeR8AEAikeXTgAAqmHSFgAAAAAYULTwAQCKZpkxfAAAVETCBwAonumQAgBAJSR8AIDi0cIHAEA1JHwAgOIxaQsAANXQRwYAAAAABhQtfACAojn/AQCAiSPhAwCUzYzhAwCgKhI+AEDxGMMHAEA1JHwAgKJZ0hBDzgEAqIQjKAAAAAAMKFr4AACFM106AQCoiIQPAFA8Ej4AAKoh4QMAFG+IyzIAAFAJY/gAAAAAYEDV0sIXCq0bXltH0QNl+pRtat/GkOvN6V+0y4G1li9Jq//+gdq3scOMGbVvY5eZO9da/tZT6t0HLnyNXrHo0glAcs0xjSTN3Gr7Wst/w1MPrbV8SdrhfdvWvo3ttqo/bnrJzi+otfzpNcdNJaFLJwCgbFx4HQCAykj4AACFMy3MAABURMIHACiaVX/3dAAABhVHUAAAAAAYULTwAQCKx6QtAABUQ8IHACgeY/gAAKiGhA8AUDgzSycAABWR8AEAimbRwgcAQFVtTdpie5bt82z/1vYy28+uu2IAAAD9itgJQCnabeH7jKTvRcRrbE+TtE2NdQIAYBN06UQfInYCUISWCZ/t7SU9T9LRkhQRayWtrbdaAABklsx1+NBHiJ0AlKSdI+iuklZL+ortX9r+ku1ta64XAACZO/4H1IzYCUAx2kn4pkraV9LnI2IfSfdLet/olWwfY3uJ7SV3rL6jw9UEAExWVurS2clby23ap9m+3fZvRi1/Rx6TdZ3tjzcsP9H2ctu/s/3Szr8K6DMtY6fGuGn16jW9qCOASaKdhG+lpJURcWW+f57Sj9gmImJxRCyMiIWPmfOYTtYRAIBuO13SwY0LbL9A0iJJT4+IPSV9Ii/fQ9LhkvbMz/mc7SldrS1K0zJ2aoyb5syZ3fUKApg8WiZ8EXGbpBW2d8+LDpJ0fa21AgCgge2O3lqJiB9LunPU4rdJ+lhEPJzXuT0vXyTp7Ih4OCJulLRc0n6d23v0G2InACVpd5bOd0g6M88ydYOkN9VXJQAANjVUxri7J0v6C9unSHpI0t9FxC8kzZV0RcN6K/MyTG7ETgCK0FbCFxHXSFpYb1UAANicpbZa5SZotu0lDfcXR8TiFs+ZKmkHSQdIepakc20/odMVw2AgdgJQinZb+AAAGCRrImKiwfhKSRdEREi6yvawpNmSbpE0v2G9eXkZAAA9x4WNAACFs+yhjt4q+rakF0iS7SdLmiZpjaQLJR1ue2vbu0raTdJVW77fAABsOVr4AADF6/YYPttnSXq+UtfPlZJOlnSapNPypRrWSjoqt/ZdZ/tcpUk51ks6LiI2dLXCAACMgYQPAFA0u5YxfOOKiNeN8dAbx1j/FEmn1FcjAACqIeEDABTPZczSCQBA32EMHwAAAAAMKFr4AACFa+9i6QAAYHO1JHxDmqIZU7eto+hHrB9eV2v5WzCLW9uGuzCmf6jm/XjKrKfWWr4kvXXv7WrfxrQp02rfxk7bzKu1/Kmu9/wNATd6qZALrwPoobpjGkmaPmVGreXvtcPetZYvSU981JNq30Y33osZU7aptfxpU6bXWn5JaOEDABQtXXidEQgAAFRBwgcAKJyZtAUAgIo4ZQoAAAAAA4oWPgBA8RhDCgBANSR8AIDi0aUTAIBqSPgAAMWjhQ8AgGpI+AAARbO4LAMAAFUxaQsAAAAADCha+AAAZbPp0gkAQEUkfACA4pkOKQAAVELCBwAoHi18AABUwylTAAAAABhQtPABAIpmcR0+AACqIuEDABTOGqJLJwAAlZDwAQCKRwsfAADVkPABAIrHpC0AAFTDpC0AAAAAMKBo4QMAFC1N2sL5SQAAqiDhAwAUznTpBACgIhI+AEDxhpi0BQCASkj4AABlM5O2AABQFYMiAAAAAGBA0cIHAChamrSFFj4AAKog4QMAFI8unQAAVFNLwmdLUzyljqIfsV7rai1/2tC0WsuXpPXD62vfxnAM11r+9Knb1Fq+JD1p+91r30bU/DpJ9bdQbFXzZ5YWFvSOuSwDgK6YMlRvW8h01x83bT1lRu3b6Iahmn/3J9OJRFr4AADFG5pEB2YAADqJU6YAAAAAMKBo4QMAFI1JWwAAqI6EDwBQvMk01gIAgE4i4QMAFM608AEAUBFj+AAAAABgQJHwAQCKZ7ujtza2d5rt223/psljx9sO27Pzfds+1fZy27+yvW8NLwEAAJWQ8AEAimal6zF18q8Np0s6eLO62PMlvUTSzQ2LD5G0W74dI+nzW7rPAAB0SltHPdvvsX2d7d/YPsv29LorBgCAJMndb+GLiB9LurPJQ5+SdIKkaFi2SNJXI7lC0izbO3Zi19G/iJ0AlKJlwmd7rqR3SloYEXtJmiLp8LorBgBA4o7/SZpte0nD7ZiWtbAXSbolIq4d9dBcSSsa7q/MyzBJETsBKEm7s3ROlTTD9jpJ20i6tb4qAQBQuzURsbDdlW1vI+kkpe6cQDuInQAUoWULX0TcIukTSuMVVkm6JyIuGb2e7WNGzpSuXr2m8zUFAExa3e7S2cQTJe0q6Vrbf5Q0T9JS24+XdIuk+Q3rzsvLMEm1EzsRNwHolna6dD5aaXzCrpJ2krSt7TeOXi8iFkfEwohYOGfO7M7XFAAwadXQpXNCIuLXEfHYiFgQEQuUum3uGxG3SbpQ0pF5ts4DlIL7VR19AdBX2omdiJsAdEs7k7a8SNKNEbE6ItZJukDSc+qtFgAAidX9hM/2WZJ+Lml32yttv2Wc1S+SdIOk5ZK+KOlvOrDb6G/ETgCK0c4YvpslHZDHLzwo6SBJS2qtFQAAjap1w6wsIl7X4vEFDf+HpOPqrhP6CrETgGK0M4bvSknnSVoq6df5OYtrrhcAAEBfInYCUJK2ZumMiJMlnVxzXQAAaKLauDugl4idAJSi3csyAADQMxVn1gQAYNIj4QMAFI8WPgAAqiHhAwAUj4QPAIBq2rksAwAAAACgD9HCBwAomsUYPgAAqiLhAwAUjlk6AQCoqpaELyK0fnh9HUV3zbSh6V3YRu2b0EMbHqi1/HXDa2stX+rO2J0hT6l9G6GotXy77g8UATd6h4QPwCAYqv1YDWyOFj4AQNlMl04AAKriNAMAAAAADCha+AAAxaNLJwAA1ZDwAQCKxiydAABUR8IHACgcs3QCAFAVY/gAAAAAYEDRwgcAKB4tfAAAVEPCBwAoHmP4AACohoQPAFA8WvgAAKiGhA8AUDSLhA8AgKqYtAUAAAAABhQtfACAwpkxfAAAVETCBwDoAyR8AABUQcIHACibmaUTAICqSPgAAMVj0hYAAKph0hYAAAAAGFC08AEAikcLHwAA1ZDwAQCKZmbpBACgMhI+AEDxaOEDAKAaEj4AQPFI+AAAqIZJWwAAAABgQNHCBwAoHmP4AACohoQPAFA8unQCAFANCR8AoGjM0gkAQHW1JHy/XHrNmpnTtr9pAk+ZLWlNHXXpIvahHIOwHyXuwy69rgAADKKlV/9yzYyp204kbpLKPE5MFPtQhkHYB6nM/Sgidqol4YuIORNZ3/aSiFhYR126hX0oxyDsxyDsA9BJ3e7Safs0SYdKuj0i9srL/lnSKyStlfQHSW+KiLvzYydKeoukDZLeGREXd7XC6GsTjZukwThOsA9lGIR9kAZnP+rALJ0AgD7gDt9aOl3SwaOWXSppr4jYW9LvJZ0oSbb3kHS4pD3zcz5ne0ql3QQAoMNI+AAAxet2uhcRP5Z056hll0TE+nz3Cknz8v+LJJ0dEQ9HxI2Slkvar9KOAgDQYaVM2rK41xXoAPahHIOwH4OwD0DHFDhpy5slnZP/n6uUAI5YmZcBdRqE4wT7UIZB2AdpcPaj44pI+CKi798g9qEcg7Afg7APQOFm217ScH9xu9872++XtF7SmbXUDGjDIBwn2IcyDMI+SIOzH3UoIuEDAGB8HW/hW1NlcL/to5UmczkoIiIvvkXS/IbV5uVlAAD0HGP4AADF6/qULc3qYB8s6QRJr4yIBxoeulDS4ba3tr2rpN0kXVVxMwAAdFRPEz7bB9v+ne3ltt/Xy7pUZXu+7R/avt72dbbf1es6VWV7iu1f2v7PXtelCtuzbJ9n+7e2l9l+dq/rNFG235M/R7+xfZbt6b2uE9B7nU73Wqd8ts+S9HNJu9teafstkj4raaakS21fY/sLkhQR10k6V9L1kr4n6biI2NCJPQdGI3YqR7/HTRKx02ThjT1SurzhNGX17yW9WGmA+y8kvS4iru9JhSqyvaOkHSNiqe2Zkq6W9Kp+2w9Jsv23khZKelREHNrr+kyU7TMk/SQivmR7mqRtRq6R1Q9sz5V0uaQ9IuJB2+dKuigiTu9tzYDeesYznx6X/PS/Olrm42bMvZrrNaHfEDuVpd/jJonYabLoZQvffpKWR8QNEbFW0tlKU1v3lYhYFRFL8//3SVqmPpydzfY8SS+X9KVe16UK29tLep6kL0tSRKztpx+sBlMlzbA9VdI2km7tcX0AAOUgdipEv8dNErHTZNLLhG+upBUN9/t+GmvbCyTtI+nKHlelik8rjU0Z7nE9qtpV0mpJX8ndK75ke9teV2oiIuIWSZ+QdLOkVZLuiYhLelsrAEBBiJ3K8Wn1d9wkETtNGkza0iG2t5N0vqR3R8S9va7PRNg+VNLtEXF1r+uyBaZK2lfS5yNiH0n3S+qrsQ22H610pnZXSTtJ2tb2G3tbK6AM7vAfgN7r19hpQOImidhp0uhlwjcw01jb3krpB+vMiLig1/Wp4EBJr7T9R6XuIS+0/fXeVmnCVkpaGREjZwjPU/oR6ycvknRjRKyOiHWSLpD0nB7XCSgCCR8gidipFIMQN0nETpNGLxO+X0jazfaueZDo4UpTW/cV21bq+7wsIj7Z6/pUEREnRsS8iFig9D78ICL66uxIRNwmaYXt3fOig5RmzOsnN0s6wPY2+XN1kNK4BgAAJGKnIgxC3CQRO00mPbvwekSst/12SRdLmiLptDy1db85UNIRkn5t+5q87KSIuKh3VZq03iHpzHwQvEHSm3pcnwmJiCttnydpqaT1kn4paXFvawUAKAWxE2pA7DQJ9OyyDAAAtOMZz3x6/PfPOjsGf/b0x3NZBgDApMCkLQAAAAAwoHrWpRMAgPYw0QoAAFXRwgcAAAAAA4oWPgBAH6CFDwCAKkj4AABFs0j3AACoioQPAFC8dHklAAAwUSR8AIA+QMIHAEAVTNoCAAAAAAOKFj4AQPFo3wMAoBoSPgBAHyDlAwCgChI+AEDhzKQtAABUxBg+AAAAABhQJHwAAAAAMKDo0gkAKFq68DpdOgEAqIKEDwDQB0j4AACogoQPAFA80j0AAKoh4QMAFI9ZOgEAqIZJWwAAAABgQNHCBwAonEWnTgAAqiHhAwAUj3QPAIBqSPgAAH2AlA8AgCoYwwcAAAAAA4oWPgBA2cwsnQAAVEULHwAAAAAMKFr4AABFS3N00sIHAEAVjohe1wEAgDHZ/p6k2R0udk1EHNzhMgEAKA4JHwAAAAAMKMbwAQAAAMCAIuEDAAAAgAFFwgcAAAAAA4qEDwAAAAAGFAkfAAAAAAyo/w8LTJHuPffQMgAAAABJRU5ErkJggg== +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Histograma (Banda Verde)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [445]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">FWHMG</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">FWHMG</span><span class="p">)</span> +<span class="n">sigmaG</span> <span class="o">=</span> <span class="n">FWHMG</span><span class="o">.</span><span class="n">std</span><span class="p">()</span> +<span class="n">mediaG</span> <span class="o">=</span> <span class="n">FWHMG</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> +<span class="n">medianaG</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">median</span><span class="p">(</span><span class="n">FWHMG</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Datos de FWHM de las estrellas para la Banda verde :"</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Desviación :"</span><span class="p">,</span> <span class="n">sigmaG</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Media :"</span><span class="p">,</span> <span class="n">mediaG</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Mediana :"</span><span class="p">,</span> <span class="n">medianaG</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">FWHMG</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">'FHWM'</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">'# de estrellas'</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + +<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain"> +<pre>Datos de FWHM de las estrellas para la Banda verde : +Desviación : 2.525571326812283 +Media : 4.24280156594701 +Mediana : 3.1827269210351594 +</pre> +</div> +</div> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img src="data:image/png;base64,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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<h2 id="Para-la-banda-B">Para la banda B<a class="anchor-link" href="#Para-la-banda-B">¶</a></h2><ul> +<li>## Estrella 1 (Azul)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [426]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">FWHMB</span><span class="o">=</span><span class="p">[]</span> +</pre></div> + + </div> +</div> +</div> +</div> + +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [427]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteB1</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">2</span><span class="p">],</span> <span class="mi">210</span><span class="p">,</span> <span class="mi">237</span><span class="p">,</span> <span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">)</span> +<span class="n">poptB1</span><span class="p">,</span> <span class="n">pcovB1</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata1</span><span class="p">,</span> <span class="n">recorteB1</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaB1</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata1</span><span class="p">,</span> <span class="n">poptB1</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB1</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB1</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB1</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB1</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMB1</span><span class="o">=</span><span class="n">FWHMB</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptB1</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 1 fotografÃa (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteB1</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 1 a partir de la gaussiana (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaB1</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 2 (Azul)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [428]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteB2</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">2</span><span class="p">],</span> <span class="mi">645</span><span class="p">,</span> <span class="mi">535</span><span class="p">,</span> <span class="mi">35</span><span class="p">,</span> <span class="mi">35</span><span class="p">)</span> +<span class="n">poptB2</span><span class="p">,</span> <span class="n">pcovB2</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata2</span><span class="p">,</span> <span class="n">recorteB2</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaB2</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata2</span><span class="p">,</span> <span class="n">poptB2</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB2</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB2</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB2</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB2</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMB2</span><span class="o">=</span><span class="n">FWHMB</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptB2</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 2 fotografÃa (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteB2</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 2 a partir de la gaussiana (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaB2</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">35</span><span class="p">,</span> <span class="mi">35</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 3 (Azul)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [429]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteB3</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">2</span><span class="p">],</span> <span class="mi">560</span><span class="p">,</span> <span class="mi">320</span><span class="p">,</span> <span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">)</span> +<span class="n">poptB3</span><span class="p">,</span> <span class="n">pcovB3</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata3</span><span class="p">,</span> <span class="n">recorteB3</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaB3</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata3</span><span class="p">,</span> <span class="n">poptB3</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB3</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB3</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB3</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB3</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMB3</span><span class="o">=</span><span class="n">FWHMB</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptB3</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 3 fotografÃa (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteB3</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 3 a partir de la gaussiana (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaB3</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 4 (Azul)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [430]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteB4</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">2</span><span class="p">],</span> <span class="mi">442</span><span class="p">,</span> <span class="mi">370</span><span class="p">,</span> <span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">)</span> +<span class="n">poptB4</span><span class="p">,</span> <span class="n">pcovB4</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata4</span><span class="p">,</span> <span class="n">recorteB4</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaB4</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata4</span><span class="p">,</span> <span class="n">poptB4</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB4</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB4</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB4</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB4</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMB4</span><span class="o">=</span><span class="n">FWHMB</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptB4</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 4 fotografÃa (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteB4</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 4 a partir de la gaussiana (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaB4</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 5 (Azul)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [431]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteB5</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">2</span><span class="p">],</span> <span class="mi">320</span><span class="p">,</span> <span class="mi">455</span><span class="p">,</span> <span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">)</span> +<span class="n">poptB5</span><span class="p">,</span> <span class="n">pcovB5</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata5</span><span class="p">,</span> <span class="n">recorteB5</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaB5</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata5</span><span class="p">,</span> <span class="n">poptB5</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB5</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB5</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB5</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB5</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMB5</span><span class="o">=</span><span class="n">FWHMB</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptB5</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 5 fotografÃa (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteB5</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 5 a partir de la gaussiana (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaB5</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 6 (Azul)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [432]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteB6</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">2</span><span class="p">],</span> <span class="mi">535</span><span class="p">,</span> <span class="mi">335</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span> +<span class="n">poptB6</span><span class="p">,</span> <span class="n">pcovB6</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata6</span><span class="p">,</span> <span class="n">recorteB6</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaB6</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata6</span><span class="p">,</span> <span class="n">poptB6</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB6</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB6</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB6</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB6</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMB6</span><span class="o">=</span><span class="n">FWHMB</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptB6</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 6 fotografÃa (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteB6</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 6 a partir de la gaussiana (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaB6</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 7 (Azul)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [433]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteB7</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">2</span><span class="p">],</span> <span class="mi">540</span><span class="p">,</span> <span class="mi">345</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span> +<span class="n">poptB7</span><span class="p">,</span> <span class="n">pcovB7</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata7</span><span class="p">,</span> <span class="n">recorteB7</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaB7</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata7</span><span class="p">,</span> <span class="n">poptB7</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB7</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB7</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB7</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB7</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMB7</span><span class="o">=</span><span class="n">FWHMB</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptB7</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 7 fotografÃa (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteB7</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 7 a partir de la gaussiana (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaB7</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 8 (Azul)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [434]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteB8</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">2</span><span class="p">],</span> <span class="mi">620</span><span class="p">,</span> <span class="mi">306</span><span class="p">,</span> <span class="mi">20</span><span class="p">,</span> <span class="mi">20</span><span class="p">)</span> +<span class="n">poptB8</span><span class="p">,</span> <span class="n">pcovB8</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata8</span><span class="p">,</span> <span class="n">recorteB8</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaB8</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata8</span><span class="p">,</span> <span class="n">poptB8</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB8</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB8</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB8</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB8</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMB8</span><span class="o">=</span><span class="n">FWHMB</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptB8</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 8 fotografÃa (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteB8</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 8 a partir de la gaussiana (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaB8</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">20</span><span class="p">,</span> <span class="mi">20</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 9 (Azul)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [435]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteB9</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">2</span><span class="p">],</span> <span class="mi">545</span><span class="p">,</span> <span class="mi">360</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span> +<span class="n">poptB9</span><span class="p">,</span> <span class="n">pcovB9</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata9</span><span class="p">,</span> <span class="n">recorteB9</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaB9</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata9</span><span class="p">,</span> <span class="n">poptB9</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB9</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB9</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB9</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB9</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMB9</span><span class="o">=</span><span class="n">FWHMB</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptB9</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 9 fotografÃa (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteB9</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 9 a partir de la gaussiana (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaB9</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 10 (Azul)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [436]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">recorteB10</span> <span class="o">=</span> <span class="n">trim</span><span class="p">(</span><span class="n">imagen</span><span class="p">[:,:,</span><span class="mi">2</span><span class="p">],</span> <span class="mi">615</span><span class="p">,</span> <span class="mi">394</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span> +<span class="n">poptB10</span><span class="p">,</span> <span class="n">pcovB10</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata10</span><span class="p">,</span> <span class="n">recorteB10</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span> +<span class="n">estrellaB10</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata10</span><span class="p">,</span> <span class="n">poptB10</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB10</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB10</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB10</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB10</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMB10</span><span class="o">=</span><span class="n">FWHMB</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptB10</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 10 fotografÃa (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteB10</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 10 a partir de la gaussiana (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaB10</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Histograma (Banda Azul)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [444]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">FWHMB</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">FWHMB</span><span class="p">)</span> +<span class="n">sigmaB</span> <span class="o">=</span> <span class="n">FWHMB</span><span class="o">.</span><span class="n">std</span><span class="p">()</span> +<span class="n">mediaB</span> <span class="o">=</span> <span class="n">FWHMB</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> +<span class="n">medianaB</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">median</span><span class="p">(</span><span class="n">FWHMB</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Datos de FWHM de las estrellas para la Banda azul :"</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Desviación :"</span><span class="p">,</span> <span class="n">sigmaB</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Media :"</span><span class="p">,</span> <span class="n">mediaB</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Mediana :"</span><span class="p">,</span> <span class="n">medianaB</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">FWHMB</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">'FHWM'</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">'# de estrellas'</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + +<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain"> +<pre>Datos de FWHM de las estrellas para la Banda azul : +Desviación : 2.699911640184987 +Media : 4.508060549859931 +Mediana : 3.4823388160938347 +</pre> +</div> +</div> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img src="data:image/png;base64,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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<h1 id="Para-quienes-ya-"dominaron"-el-ejercicio-inicial">Para quienes ya "dominaron" el ejercicio inicial<a class="anchor-link" href="#Para-quienes-ya-"dominaron"-el-ejercicio-inicial">¶</a></h1><ul> +<li>Como ejercicio final, repita los ajustes realizados inicialmente, esta vez teniendo +en cuenta la incertidumbre de los datos, para ver si surge algún cambio en los resultados. +Encuentre una forma de programar sus rutinas de modo que sean fácilmente reutilizables; +con una buena implementación, este nuevo ajuste debe ser cuestión de un par de minutos +con pocos o ningún paso manual.</li> +</ul> +<h1 id="Repitiendo-todos-los-análisis-ahora-con-incertidumbre-:">Repitiendo todos los análisis ahora con incertidumbre :<a class="anchor-link" href="#Repitiendo-todos-los-análisis-ahora-con-incertidumbre-:">¶</a></h1><ul> +<li>Se añade la incertidumbre al fit mediante el valor de sigma, incluyendo el array dado por la aplicacion de la funcion error ya definida al inicio, para cada pixel, repitiendo todos los calculos para las 10 estrellas BN y cada una de sus bandas R,G y B.</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [816]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Lsitas de valores de FWHM teniendo en cuenta las incertidumbres</span> +<span class="n">FWHM_I</span><span class="o">=</span><span class="p">[]</span> +<span class="n">FWHMR_I</span><span class="o">=</span><span class="p">[]</span> +<span class="n">FWHMG_I</span><span class="o">=</span><span class="p">[]</span> +<span class="n">FWHMB_I</span><span class="o">=</span><span class="p">[]</span> +</pre></div> + + </div> +</div> +</div> +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 1 con incertidumbre (blanco y negro)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [817]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_BN1</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata1</span><span class="p">,</span> <span class="n">popt1</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt1</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt1</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt1</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt1</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorte1</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">popt1Err</span><span class="p">,</span> <span class="n">pcov1Err</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata1</span><span class="p">,</span> <span class="n">recorte1</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">3</span><span class="p">,</span><span class="mi">3</span><span class="p">,</span><span class="mi">3</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">Err_BN1</span><span class="p">)</span> +<span class="n">estrella1Err</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata1</span><span class="p">,</span> <span class="n">popt1Err</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt1Err</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt1Err</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt1Err</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt1Err</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHM1Err</span><span class="o">=</span><span class="n">FWHM_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">popt1Err</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 1 fotografÃa"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorte1</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 1 a partir de la gaussiana con incertidumbre"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrella1Err</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [818]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">FWHMBI</span><span class="o">=</span><span class="p">[]</span> +<span class="c1">#recorteB10 = trim(imagen[:,:,2], 615, 394, 10, 10)</span> +<span class="n">E</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata10</span><span class="p">,</span> <span class="n">poptB10</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB10</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB10</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB10</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB10</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteB10</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptB10I</span><span class="p">,</span> <span class="n">pcovB10I</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata10</span><span class="p">,</span> <span class="n">recorteB10I</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">2</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">E</span><span class="p">)</span> +<span class="n">estrellaB10I</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata10</span><span class="p">,</span> <span class="n">poptB10I</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB10I</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB10I</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB10I</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB10I</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMB10I</span><span class="o">=</span><span class="n">FWHMBI</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptB10I</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 10 fotografÃa (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteB10</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 10 a partir de la gaussiana (Banda Azul) con incertidumbre"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaB10I</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +<span class="nb">print</span><span class="p">(</span><span class="n">FWHMBI</span><span class="p">)</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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iAcM6MEvp52Ju3wbj+9eJy6dS5l2/W/4w7U/Um079uH067pOp92wBntlvN3wDXAH89673XAniN/LzZA088x0s1NmnqT7j5sF+Jlt7Mdq9OuhXwBrdXhtt0x4upFln3z8SbJzMCEl4xZ1uztNfvvuSw2z7zHQNr+uGDW/ti7qh41xnKfT2ulfGC3T2a6kc+1bS4FDky2+dKO1mmxsn7MPMfPrkX3pVV1BK2b8NF0LYNV9fGq+lXa4EjfoMU521jiPp557/bGTovFP1uqtU5voXULhpYongIcXFX70q6TnET8s711P7577awu/jltZPpMd/R3Ap+uqhNH3jeTAE0q/rmQ1iV6tktoSdSo0bi4L/PV50LgBmDDyHdrn6oavUXi9n7fF/ouwwLfkyW6bVpX/NHlXTLy9+wTUtv9WzL1CWyS/5FbLti/krZRtnZ//4B2LedC/gF4efeFJO0+o8eMsei9aWdjr05yIK0P+0L13CXtuog1wLq0wQNmzhCeBDw67f5Re9Fug/KBWa2kc+q6WfwX8H+7Mu9J65YwM1LvD4BDux+IceZ/D/CitIERDqT9QC1kL9o2v7xbz6fSzsSNY1fawf9yYHOSR3JL4jmXL9LOrM7XukySn6cNYjDT3WdvWlL4o+4M6u+MWTdo2+I5SQ5Kclu2HZ59e+t+PK1r871HHv8/8Kgkt08bAOqXgSd0XSpGnQU8Pm0AgqNYoHtU9xm7H23wLGn1sAV2qu2Ex+q9adewXd6V86fcuvV2tkcl+YW06z5fBpzaHbOXUtY2x/4lGo0HDqJdhzzji8C1aQNt7dEdn+6e5P5zF7WNvWktNlelXX/4kgXm/QItKXtW2qCRx7BtV9XFyjqL7nKdtAGUbh7LIslDk9yj27/X0LoUb01rtT+m28c30D4/s4/LM8ve3v0yY3tjp08C980811CnOYZ2jfm5I/W7oqp+kna95ePHrBssvO/HrntX32Np17Hfe+TxbFpcs47W7Xsv4Lmj763W5f9i4Ind5+tpzJ3wzSzrQNpJn1PnmeWNwMuSHN5tr3umXef6UeAuabfIWpd2m58jgH+Zb1kT8ibgqUkeljZI3YFJfraqLqVdkvY3SfbpXrtzkoW6xv8AOCizBlIa8R7gKWn3Et6Tub8nv5nWo+FnaHnBjnppkl27Ez1H08Z/mcuSfkum6Sg+e5Syf+6m3x84LcmPaGeantv1n4bWx/ttaU3Sx85RJsCru/d9Ism1tA/+A8eoz0uB+9LOtn0E+MAi87+B9iP7ONq1LdfTWuXo+pM/g3ZwvIz2ozN7oKGFPI428NIltMEOXlJtACW45QPzwyRnjjH/n9MGeLoA+Ddal9Yb5ltwVZ0D/A3tIPMDWl/2/xyn0t1B/zm0L9aVtB/XUxaY/0bahe2zB5a6eQRfWpegP642iiS0i9YfT+vi9QbaaG3jegOte9FXgDMZ2cfbU/ckR9LO7r2ua4WYeZxCay1+XPe4E+1s+8xn/MVdEc+lXYtxFW3ggw8uUOdHA5+pqksWmEeaPrbATguP1c3HgY/RWme/C/yExbv9vZMWWF5BOxE5c6xbSllzHfu310u75V1AC6hvvkVdtWs6j6YlIxcAm2gJwr5jlPsq2iU/m2j78WPzzdgd93+TFlBfRdsm/8ItccliZf0JLem5slufd4689tO0GOcaWtL32W4d19AG/LmEti9+mblPfi9lv8ys13bFTlX1A+DfaYN1jfpw9526hpYIHl+3XK/7u8Cfd9+XP6XFK+NaaN9vT90fQ/sOvX00/qHds3UdbXCjx9Gudb5y5HdjZpCn36addPohbRC1/1qgzo8H3lbtGvK5vJK2DT5B215vAvaodh3s0bTW/B/SWtWPrqpNCyxrh1XVF+kGAKX9Pn2WW1qCn0xrKDmH9tl9H603wHz+ndZw8/0kt6p3FxO/qpvvvO7/UX9LG5DuB7TrkE9ix3y/q/clXVnPqKpvzDXjUn9Lsu1lBdK2kvwOcFxVLXXQi4lKG+ToP4D71PgDVew0kpwGPL2qvr7SdZEmZc2+B9duD/r9iZb5k4/9/hlVtXHxOaX+pd1m7qKqmn0JiWbpjnP/UFVvWem6LKckR9CSiweUwfs20i7r+grwS9UGPdIqN9U3v9XkpQ2DfifambXDaWekxh2Svnddl5I5B1MQVNU4LRLSlIndfqWdVNd18pu0lpkn0G5FMm+r7WrVtXyO00V7p9O1uhob7kRMYDXbrrTRzg6jddc5Gfj7layQJNntV9pp3ZXW9XMv2gCIj+2uE5S0kzKB1Taq6ruMPwiTJPUv2AKrVa2qnrLSdRiqbmTaExedUdJOwwRWkjRwdiGWJEmNEYEkSZIkaSr00gK7YcOGuuMhh/ZR9M229jwAW5Z8n/Px1Vj3Gd8xW/texDKMg7dmGU6zLMd4fn3vi13W9vuZ/d53v8OmTZu8EFErw2tgtYpt2LChDuk5bpK0/M4884xNVbXfStdjteklgb3jIYfyn6d+qY+ib3bdjVt6LX/tMgRLW5Yha7q+5+20HInfbrv0n8Fu7T3Th+tvmus+6JOz397z3b96Mn7pQQ9YfCapL3Yh1ip2yCGH8p+nnb7S1ZA0YXvsku+udB1WIyMCSdLwJZN9LLq4HJzk00nOSXJ2kud20/86yTeSfDXJPydZP/KeFyU5L8k3kzyiv40hSdLOywRWkqRb2ww8v6qOAI4EnpnkCOCTwN2r6p7AfwMvAuheOw64G3AU8PdJ1q5IzSVJWsVMYCVJw5ZuFOJJPhZRVZdW1Znd82uBc4EDq+oTVbW5m+1U4KDu+THAyVV1Q1VdAJwH2O9ekqQJ8zY6kqThm/y4BBuSjF50eGJ3v8k5Fp1DgfsAp8166WnAu7vnB9IS2hkXddMkSdIEmcBKkgYvk09gN1XVxjGWexvg/cDzquqakel/ROtmfNKkKyZJkuZnAitJGrTQSwK7+HKTXWjJ60lV9YGR6U8BjgYeVnXzWOwXAwePvP2gbpokSZogr4GVJGmWtIz5TcC5VfXKkelHAS8AfqOqrht5yynAcUl2S3IYcDjwxeWssyRJO4OxEtgkR3W3BTgvyQv7rpQkSTdLD4/FPRh4EvArSc7qHo8CXgvsDXyym/YPAFV1NvAe4BzgY8Azq6rfG3Fr0IydJKkfi3Yh7m4D8DrgV2mDUnwpySlVdU7flZMkCbLsXYir6vPMnep+dIH3vBx4eW+V0tQwdpKk/ozTAvsA4LyqOr+qbgROpt0uQJKkZZFkog+pZ8ZOktSTcRLYA4ELR/6e89YASU5IcnqS0zdtunxS9ZMkyQRW02bR2Gk0brrcuEmSxjaxQZyq6sSq2lhVGzds2G9SxUqSJK06o3HTfsZNkjS2cW6j460BJEkrylZTTRljJ0nqyTgtsF8CDk9yWJJdgeNotwuQJKl/KzMKsbQjjJ0kqSeLtsBW1eYkzwI+DqwF3tzdLkCSpN5lBUYhlnaEsZMk9WecLsRU1UdZ4NYBkiT1yQRW08bYSZL6MbFBnCRJkiRJ6tNYLbCSJK0kW2AlSRKYwEqSpoAJrCRJAhNYSdLQOXKwJEnqeA2sJEmSJGkq2AIrSRo8uxBLkiToMYGt6qvkZs0qCGa2bu15I9H/fti8DOtw4/Wbe1/Gcnyc1q3pdyE/vmFLr+VvWYZ9Lc3F+8BKWi7Vc+C0HMfS1XK4Xttz3NRz8eqRLbCSpMEzgZUkSWACK0maBuavkiQJB3GSJEmSJE0JW2AlScMWuxBLkqTGBFaSNHgmsJIkCUxgJUlTwARWkiSBCawkaeC8jY4kSZrhIE6SJEmSpKlgC6wkafhsgJUkSZjASpKGzlGIJUlSxwRWkjR4JrCSJAlMYCVJU8AEVpIkgYM4SZIkSZKmhC2wkqThswFWkiRhAitJmgJ2IZYkSWACK0kauCQmsJIkCfAaWEmSJEnSlLAFVpI0eLbASpIksAVWkjQFZroRT+oxxvIOTvLpJOckOTvJc7vpt0vyySTf6v6/bTc9SV6T5LwkX01y3543iSRJOyUTWEnS8GXCj8VtBp5fVUcARwLPTHIE8ELgU1V1OPCp7m+ARwKHd48TgNfvyOpKkqS5mcBKkgZvuVtgq+rSqjqze34tcC5wIHAM8LZutrcBj+meHwO8vZpTgfVJ7jDhzSBJ0k7PBFaSpAUkORS4D3AasH9VXdq99H1g/+75gcCFI2+7qJsmSZImyEGcJEnDll4GcdqQ5PSRv0+sqhNvtejkNsD7gedV1TWj9aiqSlKTrpgkSZpfLwns1iquv3FLH0Xfou8BKZchJNmytf+FVPW7jOtu2Nxr+QCXXHN978vYZU3/nRHueLs9ey3/pp/0uy+29vxZkuYToIdBiDdV1cYFl5vsQkteT6qqD3STf5DkDlV1addF+LJu+sXAwSNvP6ibJmlC+o5pAG7cvLXX8q+5vv+46errbup9GcsxMPz6vXbttfx9drcdb1rZhViSNHCTvf51zFGIA7wJOLeqXjny0inA8d3z44EPjUx/cjca8ZHA1SNdjSVJ0oR46kGSNHgrcBvYBwNPAr6W5Kxu2ouBvwTek+TpwHeBY7vXPgo8CjgPuA546rLWVpKknYQJrCRJs1TV55n/YpWHzTF/Ac/stVKSJMkEVpI0fD0M4iRJkqaQCawkadiyIl2IJUnSAJnASpIGLcCaNWawkiTJBFaSNAVsgZUkSeBtdCRJkiRJU8IWWEnS4DmIkyRJgjFaYJMcnOTTSc5JcnaS5y5HxSRJAm4exGmSD6lPxk6S1J9xWmA3A8+vqjOT7A2ckeSTVXVOz3WTJIlgC6ymjrGTJPVk0QS2qi4FLu2eX5vkXOBAwB9hSdIyiAmspoqxkyT1Z7sGcUpyKHAf4LReaiNJkrSKGDtJ0mSNncAmuQ3wfuB5VXXNHK+fkOT0JKf/cNOmSdZRkrST8xpYTaOFYqfRuOnyTZevTAUlaQqNlcAm2YX2A3xSVX1grnmq6sSq2lhVG2+/YcMk6yhJ2sklmehD6ttisdNo3LTfhv2Wv4KSNKUWvQY27Uj/JuDcqnpl/1WSJGmEraaaMsZOktSfcVpgHww8CfiVJGd1j0f1XC9JkqRpZewkST0ZZxTiz9PuYiBJ0rLzNjqaNsZOktSfce4DK0nSijJ/lSRJYAIrSZoCtsBKkiQwgZUkTQHzV0mSBNtxH1hJkiRJklaSLbCSpGGLXYglSVJjAitJGrQ2CvFK10KSJA1Bbwns1qq+igZg3Zp+ez9fd9OWXssH+MmN/S/jxs1bey3/9Euu6LV8gBM/853el7Hrrv2fy3nWQw7rtfx77L9vr+X3/JWWFhBbYCWxZWv/B6Jrrt/ca/lfvLD/uOldZ1zS+zL2WIa46cn3O6DX8u9+QL9xk/pjC6wkafDMXyVJEjiIkyRJkiRpStgCK0kaPLsQS5IkMIGVJA1d7EIsSZIaE1hJ0qC1UYjNYCVJkgmsJGkKmMBKkiRwECdJkiRJ0pSwBVaSNHg2wEqSJDCBlSRNAbsQS5IkMIGVJA2doxBLkqSO18BKkiRJkqaCCawkadBCSCb7WHSZyZuTXJbk6yPT7p3k1CRnJTk9yQO66UnymiTnJflqkvv2uDkkSdqpmcBKkgYvmexjDG8Fjpo17a+Al1bVvYE/7f4GeCRwePc4AXj9BFZZkiTNwWtgJUmDt2aZL4Ktqs8lOXT2ZGCf7vm+wCXd82OAt1dVAacmWZ/kDlV16fLUVpKknYcJrCRp8HrIXzckOX3k7xOr6sRF3vM84ONJXkHrwfSgbvqBwIUj813UTTOBlSRpwkxgJUk7o01VtXE73/M7wO9V1fuTHAu8CXj45KsmSZLm4zWwkqRBa9etLu8gTvM4HvhA9/y9wAO65xcDB4/Md1A3TZIkTZgJrCRp8NZkso8lugT45e75rwDf6p6fAjy5G434SOBqr3+VJKkfdiGWJA3eDrSaLnV57wIeQrtW9iLgJcBvA69Osg74CW3EYYCPAo8CzgOuA566rJWVJGknYgIrSRq8Zc5fqarHzfPS/eaYt4Bn9lsjSZIEdiGWJEmSJE0JW2AlSYMWICxzE6wkSRokE1hJ0uDtwMBLkiRpFTGBlSQN247d+kaSJK0ivSSwIeyytt/La9et7TeY2bxla6/lA9y4uf9l/PiGzb2W/7nzr+61fIAz3/uh3pfBbW7f+yLudehtey3/Hvvv22v50koyf5W0ZWv1voyrr7up1/JPOv2SXssH+NfXvqX3ZbDX+t4Xse/zn9Br+Yfebq9ey1d/HMRJkiRJkjQV7EIsSRq0AGtsgpUkSZjASpKmgPmrJEkCE1hJ0hRwECdJkgReAytJkiRJmhK2wEqSBi2xC7EkSWpMYCVJg+cgTpIkCUxgJUlTwPRVkiTBdiSwSdYCpwMXV9XR/VVJkqRtOYiTppGxkyRN3vYM4vRc4Ny+KiJJkrTKGDtJ0oSNlcAmOQj4deCN/VZHkqRtBViTyT6kvhk7SVI/xu1C/CrgBcDe/VVFkqQ5JHYh1jR6FcZOkjRxi7bAJjkauKyqzlhkvhOSnJ7k9E2bLp9YBSVJmrmVzqQeUp/GiZ1G46bLjZskaWzjdCF+MPAbSb4DnAz8SpJ3zJ6pqk6sqo1VtXHDhv0mXE1J0s4sXSvspB5SzxaNnUbjpv2MmyRpbIsmsFX1oqo6qKoOBY4D/r2qnth7zSRJkqaQsZMk9cf7wEqSBm1mECdJkqTtSmCr6jPAZ3qpiSRJ87Dbr6aVsZMkTZYtsJKkwTN9lSRJYAIrSRq4BNbYAitJkhhvFGJJkiRJklacLbCSpMGzAVaSJIEJrCRpCjiIkyRJAhNYSdIUMH+VJEnQUwJbFFu2Vh9F32xNzzcFvGlLv/UH2Fr9L2PXdf1e5rx5GbYTN93Q/zKu3dT7Iu6wz669lt93gG/+IElaScvRE6PvRey+69p+FwCw577LsIz1vS9i93X97gx79kwvW2AlSYMW4ijEkiQJMIGVJA1d7EIsSZIaE1hJ0uDZ1UuSJIH3gZUkTYE1E34sJsmbk1yW5Ouzpj87yTeSnJ3kr0amvyjJeUm+meQRO7a2kiRpPrbASpJ0a28FXgu8fWZCkocCxwD3qqobkvxUN/0I4DjgbsABwL8luUtVbVn2WkuStMrZAitJGrTQuhBP8rGYqvoccMWsyb8D/GVV3dDNc1k3/Rjg5Kq6oaouAM4DHjCxDSBJkm5mAitJGrw1mexjie4C/GKS05J8Nsn9u+kHAheOzHdRN02SJE2YXYglSYPXw62/NyQ5feTvE6vqxEXesw64HXAkcH/gPUnuNPGaSZKkeZnASpIGLellFOJNVbVxO99zEfCBqirgi0m2AhuAi4GDR+Y7qJsmSZImzC7EkiSN54PAQwGS3AXYFdgEnAIcl2S3JIcBhwNfXKlKSpK0mtkCK0kavB66EC8oybuAh9C6Gl8EvAR4M/Dm7tY6NwLHd62xZyd5D3AOsBl4piMQS5LUDxNYSdLgTb4H8cKq6nHzvPTEeeZ/OfDy/mokSZLABFaSNHAB1ix3BitJkgbJBFaSNHgO2CBJksCYQJIkSZI0JWyBlSQNnj2IJUkSmMBKkgYuidfASpIkwARWkjQFzF8lSRKYwEqSpsBy3wdWkiQNk4M4SZIkSZKmgi2wkqRB8z6wkiRphgmsJGnwzF8lSRKYwEqShi5eAytJkhqvgZUkSZIkTYXeWmC3VPVVdLeArb0Wvxxn+/fcrf8G8LU9r8dj77F/vwsAbvy9p/e+jH333LX3Zdzrp/bptfzd1vV7Pir24dQKCn7+pJ3dcsRm6/fqNx54yv0O7LV8gPW//4Tel7HHLv23gf3mz/YbY+69ux1Rp5V7TpI0aG0Qp5WuhSRJGgITWEnS4JnASpIkMIGVJE0Bu7BLkiRwECdJkiRJ0pSwBVaSNGheAytJkmaYwEqShi1gD2JJkgQmsJKkKbDGDFaSJGECK0kaOLsQS5KkGWMN4pRkfZL3JflGknOT/HzfFZMkSZpWxk6S1I9xW2BfDXysqh6bZFdgzx7rJEnSNuxBrClk7CRJPVg0gU2yL/BLwFMAqupG4MZ+qyVJ0oywBjNYTQ9jJ0nqzzhdiA8DLgfekuTLSd6YZK+e6yVJEtCugU0m+5B6ZuwkST0ZJ4FdB9wXeH1V3Qf4MfDC2TMlOSHJ6UlO/+GmTROupiRpp5U2iNMkH1LPFo2dRuOmyzddvhJ1lKSpNE4CexFwUVWd1v39PtqP8jaq6sSq2lhVG2+/YcMk6yhJkjRNFo2dRuOm/Tbst+wVlKRptWgCW1XfBy5Mctdu0sOAc3qtlSRJI9YkE31IfTJ2kqT+jDsK8bOBk7pR9M4HntpflSRJusXMNbDSlDF2kqQejJXAVtVZwMZ+qyJJ0txsNdW0MXaSpH6Mcw2sJEmSJEkrbtwuxJIkrRgbYCVJEpjASpIGLthdSJIkNcYEkqRhCySZ6GPRRSZvTnJZkq/P8drzk1SSDd3fSfKaJOcl+WqSW91qTpIkTYYJrCRp8DLhxxjeChx1q3okBwO/BnxvZPIjgcO7xwnA67dn3SRJ0vhMYCVJmqWqPgdcMcdLfwu8AKiRaccAb6/mVGB9kjssQzUlSdrpeA2sJGnQwjBuo5PkGODiqvrKrG7IBwIXjvx9UTft0mWsniRJO4VeEtg1CXvuuraPom92w+atvZY/zjVSO6qqFp9pR/W8Hne63V69lg/wtPsf1Psydl3T7+cVYP99duu1/HVr++1QMYD8QTuxHj5+G5KcPvL3iVV14rzLT/YEXkzrPixpBaxd0/+BaJ/d+23buceB+/ZaPsBht+8/NluOOHnvnvfFXrv1H/upH7bASpIGr4dYaVNVbdyO+e8MHAbMtL4eBJyZ5AHAxcDBI/Me1E2TJEkTZgIrSRq48UYO7lNVfQ34qZm/k3wH2FhVm5KcAjwrycnAA4Grq8ruw5Ik9cBBnCRJmiXJu4AvAHdNclGSpy8w+0eB84HzgDcAv7sMVZQkaadkC6wkadDC8p9trarHLfL6oSPPC3hm33WSJEkmsJKkKbDSXYglSdIwmMBKkgbP9FWSJIEJrCRp6GILrCRJahzESZIkSZI0FWyBlSQN2koM4iRJkobJBFaSNHh2IZYkSWACK0maAqavkiQJ7JUlSZIkSZoStsBKkgbPHsSSJAlMYCVJA9cGcTKDlSRJJrCSpClgC6wkSQITWEnS4IXYAitJknAQJ0mSJEnSlLAFVpI0eHYhliRJYAIrSRo4B3GSJEkzTGAlScMWW2AlSVJjAitJGjwTWEmSBA7iJEmSJEmaErbASpIGz9voSJIkMIGVJA1cgDXmr5IkiZ4S2ADr1vbbO/mmLdVr+XvttrbX8gFuuGlr78vYvLXf7bTHrv1vp8Nuf5vel1HV73Zqy+i3/N3W9fud8xpErSRbYCVlGQ5E63oOa/bZY5d+FwDsvfvqaJ9a0/P+XuOZ0am1Oj7hkqRVzRMokiQJHMRJkiRJkjQlbIGVJA2eXYglSRKYwEqSBs5BnCRJ0gwTWEnSwMUWWEmSBHgNrCRJkiRpStgCK0katjgKsSRJakxgJUmDZ/4qSZJgzC7ESX4vydlJvp7kXUl277tikiTBzCBOmehD6puxkyT1Y9EENsmBwHOAjVV1d2AtcFzfFZMkaUYm/JD6ZOwkSf0ZdxCndcAeSdYBewKX9FclSZKkqWfsJEk9WDSBraqLgVcA3wMuBa6uqk/Mni/JCUlOT3L65Zsun3xNJUk7L5tgNUXGiZ2MmyRpacbpQnxb4BjgMOAAYK8kT5w9X1WdWFUbq2rjfhv2m3xNJUk7rUz436LLS96c5LIkXx+Z9tdJvpHkq0n+Ocn6kddelOS8JN9M8oh+toKmxTixk3GTJC3NOF2IHw5cUFWXV9VNwAeAB/VbLUmSbpFM9jGGtwJHzZr2SeDuVXVP4L+BF7W65Qja9Y13697z90nWTmjVNZ2MnSSpJ+MksN8DjkyyZ5IADwPO7bdakiTdYrl7EFfV54ArZk37RFVt7v48FTioe34McHJV3VBVFwDnAQ9Y0opqtTB2kqSejHMN7GnA+4Azga917zmx53pJktSnDTPXH3aPE7bz/U8D/rV7fiBw4chrF3XTtJMydpKk/qwbZ6aqegnwkp7rIknS3CY/8NKmqtq4lDcm+SNgM3DSZKuk1cTYSZL6MVYCK0nSSmndfocxdHCSpwBHAw+rquomXwwcPDLbQd00SZI0YePeB1aSpJUx4QGcxhzE6dbVSI4CXgD8RlVdN/LSKcBxSXZLchhwOPDFHV1tSZJ0a7bASpIGb7nbX5O8C3gI7VrZi2hdQV8E7AZ8so3Lw6lV9YyqOjvJe4BzaF2Ln1lVW5a5ypIk7RRMYCVJmqWqHjfH5DctMP/LgZf3VyNJkgQmsJKkaTCMS2AlSdIKM4GVJA1cBjOIkyRJWlm9JLAFbN6ytY+il83uu6xdFcu49iebey3/+hv7v8xrOcLWtWv7H89sy9ZafKYdsGZNv1vKBEIraakDL0nS9kjPPzZrl+W3zB9MrW62wEqSBi0YjkmSpMbb6EiSJEmSpoItsJKk4bMJVpIkYQIrSZoCXoMtSZLABFaSNAUcxEmSJIHXwEqSJEmSpoQtsJKkwbMBVpIkgQmsJGnovI+OJEnqmMBKkgbPQZwkSRKYwEqSBi44iJMkSWocxEmSJEmSNBVsgZUkDZ4NsJIkCUxgJUnTwAxWkiRhAitJmgIO4iRJksAEVpI0BRzESZIkgYM4SZIkSZKmhC2wkqTBswFWkiSBCawkaRqYwUqSJExgJUkDFxzESZIkNSawkqRhi4M4SZKkxkGcJEmSJElTwRZYSdLg2QArSZLABFaSNA3MYCVJEiawkqTBi4M4SZIkoKcE9stnnrFp793Xfnc73rIB2NRHXZaR6zAcq2E9hrgOh6x0BSRpNTrzzDM27bFLtidugmEeJ7aX6zAMq2EdYJjrYezUg14S2Krab3vmT3J6VW3soy7LxXUYjtWwHqthHaRJchRirWbbGzfB6jhOuA7DsBrWAVbPemhxdiGWJA1a8BJYSZLUmMBKkobPDFaSJDGcBPbEla7ABLgOw7Ea1mM1rIM0MQ7iJN3KajhOuA7DsBrWAVbPemgRqaqVroMkSfO6573vVx/+1H9NtMxDN+x+xkLXSiV5M3A0cFlV3b2bdjvg3cChwHeAY6vqyiQBXg08CrgOeEpVnTnRCkuSJADWrHQFJElaTDLZxxjeChw1a9oLgU9V1eHAp7q/AR4JHN49TgBeP4l1liRJt2YCK0kavEz4sZiq+hxwxazJxwBv656/DXjMyPS3V3MqsD7JHbZ7JSVJ0qJWNIFNclSSbyY5L8kLF3/H8CQ5OMmnk5yT5Owkz13pOi1VkrVJvpzkX1a6LkuRZH2S9yX5RpJzk/z8StdpeyX5ve5z9PUk70qy+0rXSVpxE2593YFb8uxfVZd2z78P7N89PxC4cGS+i7pp0sQZOw3HtMdNYOyk6bRiCWyStcDraF2vjgAel+SIlarPDtgMPL+qjgCOBJ45pesB8Fzg3JWuxA54NfCxqvpZ4F5M2bokORB4DrCxu+ZuLXDcytZKGoqJt8FuSHL6yOOE7alNtQEkHERCy8rYaXCmPW4CYydNoZVsgX0AcF5VnV9VNwIn07phTZWqunRmsI6qupb2xZ+6M+9JDgJ+HXjjStdlKZLsC/wS8CaAqrqxqq5a0UotzTpgjyTrgD2BS1a4PtJqtamqNo48xhm98gczXYO7/y/rpl8MHDwy30HdNGnSjJ0GYtrjJjB20vRayQR21XW5SnIocB/gtBWuylK8CngBsHWF67FUhwGXA2/puvO8McleK12p7VFVFwOvAL4HXApcXVWfWNlaSSsvDKYL8SnA8d3z44EPjUx/cpojad/dS+cqQNpBxk7D8SqmO24CYydNKQdxmpAktwHeDzyvqq5Z6fpsjyQzt4o4Y6XrsgPWAfcFXl9V9wF+zC0jhE6FJLelnUk/DDgA2CvJE1e2VtIwLPcgTkneBXwBuGuSi5I8HfhL4FeTfAt4ePc3wEeB84HzgDcAv7uDqyvtFKY1dlolcRMYO2lKrVvBZa+aLldJdqH9AJ9UVR9Y6foswYOB30jyKGB3YJ8k76iqafoBuAi4qKpmzuC+jyn7EaYFxBdU1eUAST4APAh4x4rWShqAHWg1XZKqetw8Lz1sjnkLeGa/NZIAY6ehWA1xExg7aUqtZAvsl4DDkxyWZFfaBdenrGB9lqS7gf2bgHOr6pUrXZ+lqKoXVdVBVXUobT/8+7T9CFfV94ELk9y1m/Qw4JwVrNJSfA84Msme3efqYUzZYApSXzLhf9KUMnYagNUQN4Gxk6bXirXAVtXmJM8CPk4bMezNVXX2StVnBzwYeBLwtSRnddNeXFUfXbkq7bSeDZzUHdTPB566wvXZLlV1WpL3AWfSRmj8MjDOwDKSpJ2AsZN6YOykqZPW80mSpGG6133uVx//7KkTLfMO++56RlVtnGihkiSpdyt5DawkSWOx068kSQITWEnSwO3grW8kSdIq4m10JEmSJElTwRZYSdLgOXKwJEkCE1hJ0jQwf5UkSZjASpKmgPmrJEkCE1hJ0hRwECdJkgQO4iRJkiRJmhK2wEqSBi4O4iRJkgATWEnSwAW7EEuSpMYuxJIkSZKkqWALrCRp8GyBlSRJYAusJEmSJGlK2AIrSRo8B3GSJElgAitJGrrYhViSJDUmsJKkQUv3kCRJMoGVJA2fGawkScJBnCRJkiRJU8IWWEnS4DmIkyRJAhNYSdIUcBAnSZIEJrCSpClg/ipJksBrYCVJkiRJU8IWWEnS8NkEK0mSMIGVJE0BB3GSJElgAitJGrjgIE6SJKlJVa10HSRJmleSjwEbJlzspqo6asJlSpKknpnASpIkSZKmgqMQS5IkSZKmggmsJEmSJGkqmMBKkiRJkqaCCawkSZIkaSqYwEqSJEmSpsL/A3vI8Vku0yc9AAAAAElFTkSuQmCC +" +> +</div> + +</div> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + +<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain"> +<pre>[3.041995114502331] +</pre> +</div> +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 2 con incertidumbre (blanco y negro)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [819]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_BN2</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata2</span><span class="p">,</span> <span class="n">popt2</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt2</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt2</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt2</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt2</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorte2</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">popt2E</span><span class="p">,</span> <span class="n">pcov2E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata2</span><span class="p">,</span> <span class="n">recorte2</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span> <span class="n">sigma</span><span class="o">=</span><span class="n">Err_BN2</span><span class="p">)</span> +<span class="n">estrella2E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata2</span><span class="p">,</span> <span class="n">popt2E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt2E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt2E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt2E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt2E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHM2E</span><span class="o">=</span><span class="n">FWHM_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">popt2E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 2 fotografÃa"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorte2</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 2 a partir de la gaussiana con incertidumbre"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrella2E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">35</span><span class="p">,</span> <span class="mi">35</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 3 con incertidumbre (blanco y negro)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [820]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_BN3</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata3</span><span class="p">,</span> <span class="n">popt3</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt3</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt3</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt3</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt3</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorte3</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">popt3E</span><span class="p">,</span> <span class="n">pcov3E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata3</span><span class="p">,</span> <span class="n">recorte3</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">2</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">Err_BN3</span><span class="p">)</span> +<span class="n">estrella3E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata3</span><span class="p">,</span> <span class="n">popt3E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt3E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt3E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt3E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt3E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHM3E</span><span class="o">=</span><span class="n">FWHM_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">popt3E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 3 fotografÃa"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorte3</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 3 a partir de la gaussiana con incertidumbre"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrella3E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 4 con incertidumbre (blanco y negro)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [821]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_BN4</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata4</span><span class="p">,</span> <span class="n">popt4</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt4</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt4</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt4</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt4</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorte4</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">popt4E</span><span class="p">,</span> <span class="n">pcov4E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata4</span><span class="p">,</span> <span class="n">recorte4</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">3</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">Err_BN4</span><span class="p">)</span> +<span class="n">estrella4E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata4</span><span class="p">,</span> <span class="n">popt4E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt4E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt4E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt4E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt4E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHM4E</span><span class="o">=</span><span class="n">FWHM_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">popt4E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 4 fotografÃa"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorte4</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 4 a partir de la gaussiana con incertidumbre"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrella4E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 5 con incertidumbre (blanco y negro)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [822]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_BN5</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata5</span><span class="p">,</span> <span class="n">popt5</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt5</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt5</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt5</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt5</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorte5</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">popt5E</span><span class="p">,</span> <span class="n">pcov5E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata5</span><span class="p">,</span> <span class="n">recorte5</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">3</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span> <span class="n">sigma</span><span class="o">=</span><span class="n">Err_BN5</span><span class="p">)</span> +<span class="n">estrella5E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata5</span><span class="p">,</span> <span class="n">popt5E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt5E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt5E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt5E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt5E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHM5E</span><span class="o">=</span><span class="n">FWHM_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">popt5E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 5 fotografÃa"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorte5</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 5 a partir de la gaussiana con incertidumbre"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrella5E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 6 con incertidumbre (blanco y negro)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [823]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_BN6</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata6</span><span class="p">,</span> <span class="n">popt6</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt6</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt6</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt6</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt6</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorte6</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">popt6E</span><span class="p">,</span> <span class="n">pcov6E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata6</span><span class="p">,</span> <span class="n">recorte6</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">3</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">Err_BN6</span><span class="p">)</span> +<span class="n">estrella6E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata6</span><span class="p">,</span> <span class="n">popt6E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt6E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt6E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt6E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt6E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHM6E</span><span class="o">=</span><span class="n">FWHM_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">popt6E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 6 fotografÃa"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorte6</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 6 a partir de la gaussiana con incertidumbre"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrella6E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 7 con incertidumbre (blanco y negro)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [824]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_BN7</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata7</span><span class="p">,</span> <span class="n">popt7</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt7</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt7</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt7</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt7</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorte7</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">popt7E</span><span class="p">,</span> <span class="n">pcov7E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata7</span><span class="p">,</span> <span class="n">recorte7</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">Err_BN7</span><span class="p">)</span> +<span class="n">estrella7E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata7</span><span class="p">,</span> <span class="n">popt7E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt7E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt7E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt7E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt7E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHM7E</span><span class="o">=</span><span class="n">FWHM_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">popt7E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 7 fotografÃa"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorte7</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 7 a partir de la gaussiana con incertidumbre"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrella7E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 8 con incertidumbre (blanco y negro)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [825]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_BN8</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata8</span><span class="p">,</span> <span class="n">popt8</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt8</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt8</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt8</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt8</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorte8</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">popt8E</span><span class="p">,</span> <span class="n">pcov8E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata8</span><span class="p">,</span> <span class="n">recorte8</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">Err_BN8</span><span class="p">)</span> +<span class="n">estrella8E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata8</span><span class="p">,</span> <span class="n">popt8E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt8E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt8E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt8E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt8E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHM8E</span><span class="o">=</span><span class="n">FWHM_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">popt8E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 8 fotografÃa"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorte8</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 8 a partir de la gaussiana con incertidumbre"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrella8E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">20</span><span class="p">,</span> <span class="mi">20</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 9 con incertidumbre (blanco y negro)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [826]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_BN9</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata9</span><span class="p">,</span> <span class="n">popt9</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt9</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt9</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt9</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt9</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorte9</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">popt9E</span><span class="p">,</span> <span class="n">pcov9E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata9</span><span class="p">,</span> <span class="n">recorte9</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">12</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span> <span class="n">sigma</span><span class="o">=</span><span class="n">Err_BN9</span><span class="p">)</span> +<span class="n">estrella9E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata9</span><span class="p">,</span> <span class="n">popt9E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt9E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt9E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt9E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt9E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHM9E</span><span class="o">=</span><span class="n">FWHM_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">popt9E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 9 fotografÃa"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorte9</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 9 a partir de la gaussiana con incertidumbre"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrella9E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 10 con incertidumbre (blanco y negro)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [827]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_BN10</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata10</span><span class="p">,</span> <span class="n">popt10</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt10</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt10</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt10</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt10</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorte10</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">popt10E</span><span class="p">,</span> <span class="n">pcov10E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata10</span><span class="p">,</span> <span class="n">recorte10</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">2</span><span class="p">,</span><span class="mi">13</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span> <span class="n">sigma</span><span class="o">=</span><span class="n">Err_BN10</span><span class="p">)</span> +<span class="n">estrella10E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata10</span><span class="p">,</span> <span class="n">popt10E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">popt10E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">popt10E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">popt10E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">popt10E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHM10E</span><span class="o">=</span><span class="n">FWHM_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">popt10E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 10 fotografÃa"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorte10</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 10 a partir de la gaussiana con incertidumbre"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrella10E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'gray'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Histograma con incertidumbres (blanco y negro)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [828]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">FWHM_I</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">FWHM_I</span><span class="p">)</span> +<span class="n">sigmaBN_I</span> <span class="o">=</span> <span class="n">FWHM_I</span><span class="o">.</span><span class="n">std</span><span class="p">()</span> +<span class="n">mediaBN_I</span> <span class="o">=</span> <span class="n">FWHM_I</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> +<span class="n">medianaBN_I</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">median</span><span class="p">(</span><span class="n">FWHM_I</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Datos de FWHM con incertidumbres de las estrellas a blanco y negro :"</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Desviación :"</span><span class="p">,</span> <span class="n">sigmaBN_I</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Media :"</span><span class="p">,</span> <span class="n">mediaBN_I</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Mediana :"</span><span class="p">,</span> <span class="n">medianaBN_I</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">FWHM_I</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">'FHWM'</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">'# de estrellas'</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + +<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain"> +<pre>Datos de FWHM con incertidumbres de las estrellas a blanco y negro : +Desviación : 2.5072119906676873 +Media : 4.216826728193483 +Mediana : 3.1229418738608983 +</pre> +</div> +</div> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img src="data:image/png;base64,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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 1 con incertidumbre (Banda Rojo)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [829]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_R1</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata1</span><span class="p">,</span> <span class="n">poptR1</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR1</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR1</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR1</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR1</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteR1</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptR1E</span><span class="p">,</span> <span class="n">pcovR1E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata1</span><span class="p">,</span> <span class="n">recorteR1</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">2</span><span class="p">,</span><span class="mi">3</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">Err_R1</span><span class="p">)</span> +<span class="n">estrellaR1E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata1</span><span class="p">,</span> <span class="n">poptR1E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR1E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR1E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR1E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR1E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMR1E</span><span class="o">=</span><span class="n">FWHMR_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptR1E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 1 fotografÃa (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteR1</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 1 a partir de la gaussiana con incertidumbre (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaR1E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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tyGpsc0P+6OCXqO/ppSBye75WWf3MKy5zT83/ib3sqyhmoe28xI8yxrjKfhfNRvsVLT3cZtvllEjPg4OadmqD9QOu9tn8/Hl2r4bTOgPDIopmbLelIpMeif/nmNC46I30bEfKVmjz+SdGEevioiToiIP1O6Nel/2T5wiNjGso/7jebYW6x07+VQRiwLtMliSTM99D3AiyV9atBxMS0iGpvkDj7umh2HW+cyar/GMtjgfTxJqSa2xODv4RpJyxuGNcY7pu9BdoukXYdrURLJbZL+nzbcU1rymzXgO62B21FK5eZLJM2JiK0kfb2VZUdqHfMRSS/xhubKrR6XD0ia43zPesO0jb/dL5Z0c7M4eiaptf233tB5z6NKB0T/VYE/afgfi35fl/Sp/uYEtrd1akffzHSl5gMrc5Ix4uNrbE9xus+zT9Jk25s2qfFrdL6ko23vk3/oPy3pukhNYqSNP+dI0/9E+eDMX7bjlO7LqOyzDjHv00qPoZmpDc1xh3OpRmgS4fSInLdpQ2/L05Xui3hYabt+XOnKUit+nef9QN4/f6V0b8BYYx/sNElvtP1SpRPqm2wf6HSfwQlKzXaG+nE8X9I/52NxlqSPK12x6/caSb/IPzbAhERHURPDBD1HT5f0uKQnbL9IUivPWvwXp9Y/eyrdH9p/L+xYltXKdhvJTyTtafuvcjngAxpYDvi6pJNyrLK9le2/bWG5U5Vu/3lY0tpcAzW4o55GF0r6oO2dchL1kVEs6+b8GfbJ++2U/hG2p9p+u+2tcjPUx5WPOaeOjl6QE/mVSrX+jTVJ/cayXxrnbfXY+7GkHWwf79QBz3TbL8/jmpUFKhepR9qfKl182jp/L/ov6H9T0ntzrZ9tb+7UAdFQNZL9hj1WI+I+SQslfTLvs1cpV1hkv1dqWfemXG76Z6VjosQ7bO9he5rSPbcXxfCPFxrr90ARsUSpRcCwj+XMx9WrNLA8O9ay9oWS3tXw2QaXV6cr1cA/Y3t/SX/f6oIjYrWkzysdf1Lrx+V1SrXJJ+bj6LVK+/eChmleo3S8jWgiJrX9vaf1v36Yh79M0nW2n1C6CvHBiPhjHneKpHOcmg68dZjlnp7nu8zpXshrlW6gb+aTSh0brFQ6QVzcZPpvKiVIRyjdZP20hm6DvpGI+C+ltv8/ULoa83ylxK7fKWr4nCNNHxHLJf2tUscAjyj1IrxQKcGq6rM2Ok3p3tHlStv2Z02mP1fSobY3axi2Y/9+V2q6MFOpTb+UOgX4mdKP332SnlGLzV/yF/WvlG60X6F032vjZxtt7IOX/3D+PB+PiN8pXXX7Ul7e4UqdJ6weYtb/o7RPbpF0q6Qb8rB+b1f6sQUmLGpqa6eXztEfVioUrsrzDddZU6NfKhVyr1BqgnhZwbJOUfPtNqyGcsCpSuWA3ZRqjPrH/1DS/yfpAqdmkLcp3WfZbLmrlBLkC5UuYPy90r4bzjeV7pO9RamTn0uVLjSva7asSJ1S/qtSJ0t3q6GfjexISffm+N+rDWWG3fI8Tyhd2P5qRFw5RGxj2S/9Wj728ud8o1KZ4MH8WV6XRzcrC7TLkUo1mHcp9Q1yfI51oVLnXl9W2ieLlDsqGsG/KyVAj7mh1+8Gf6/0fV6hlIid2z8it8z7J6UngixVqrkdfLvcaH1HqRXdg0pPu/jAcBOO9XvQ4Bva+DfkxPz7+KTSsf9tbejMasxl7Ug9t5+m1CHaIm3oGK3fP0n61/wb+nHllgujcJaknW0frhaPy1y+PVxpmy2X9FVJ74yIuyTJ6f7tPZRaUozIsfF978BGnJoFLJH09mF+2DvO9qclPRQRp3U7lk5x6kL+HZE6Shhpur2VOmp4xUjTAXW286TJ8ZHNZlS+3Pc9+cj1ETGv+ZRANZw6aLxH0pQYpidUJLk29usR0dJjU4DxzKml5I2SDsw14BOe09NXvpWb9zeb9vOS/hARX202ba0feoz2sv2XSs0CnlZq3mANfEROV0XEyd2OoZNsb6t0n8i9zaaN1GsdCS0mNGtiNjcCsEFukfU6pRqr7ZVq6n444kxATeRbxPbodhwdtpfSRbymIuKEVhdKUouRvELppvGpku5Q6rVyNI8KQEVsv0zS5ZK+FOmxAABEc2GgB1ipyeX3lC6y/0Qb7tsDUCO2T1fqfG20zxpuvmyaHwMA6mjupCnxsWkzKl/usU8sp/kxAAA1Qk0tAKC2qKkFAADcjgQAAAAAqK2O1tTO2mZmzJ0zu/mEw6miqfT64R4z1UF9rT52dhiu4FpE6XaIoR7XNuqFFM4/QapoSvdnX+H868v25b1Llmr5ikcnyM5A3XDgYaKbNWubmLvzzt0OA0CF7r3/fi1f/ginsAp1NKmdO2e2fnvFpWNfwOpnimOIp1cVL6OUNxvp+dMt2GRaeRBPPlY0ezz7VHkMpRcpPDF+C7zpFmUL2LTweHimbF++7NC/KVs/MEYWzY8x8c3deWctvOaqbocBoELzXvXabocw4XBPLQCgtvqoqwUAoOdxTy0AAAAAoLaoqQUA1JJN82MAAFBYU2v7YNu/s73I9kerCgoAgFb0teEFtBNlJwCo3pjP37YnSfqKpEMk7SHpCNt7VBUYAADNuA0voF0oOwFAe5Q0P95f0qKI+KMk2b5A0nxJd1QRGAAAI0m9H5OGolYoOwFAG5S0tNpJ0uKG90vysAFsH2t7oe2FDz+yomB1AAAAtTb6stPyRzoWHADUVdtvH4qIBRExLyLmbbvNzHavDgDQQ2h+jIloQNlp1jbdDgcAxr2S5sdLJc1peD87DwMAoCNIQlEzlJ0AoA1Kamp/K2k327vanirpbZIuqSYsAACao6YWNUPZCQDaYMxJbUSslfQ+ST+XdKekCyPi9qoCAwCgGduVv5qsb47tK23fYft22x8cNP4E22F7Vn5v22fkx7fcYnu/Nm4OjHOUnQCgPUqaHysiLpV0aUWxAAAw3q2VdEJE3GB7uqTrbV8eEXfYniPpIEn3N0x/iKTd8uvlkr6W/6JHUXYCgOrxnHkAQC21o+lxs+bHEbEsIm7I/69Sqm3r7732i5JOlBQNs8yXdG4k10qaYXuHsX9qAAAwWFFN7aitW6tY+fDY51/9bHkM69eWzT9lk/IY1jxTvoxC8cyTZQtYU8G+KLXp5uXL6JtUvoziGAqvLZlrU+hd3Tz6bc+VtK+k62zPl7Q0Im4e1IR5uEe4LOtUnAAATHSdTWoBAKhQk1tgx2qW7YUN7xdExIKB6/UWkn4g6XilJsknKzU9BgAAHUZSCwCoLbenv+LlETFv2HXaU5QS2vMi4mLbL5G0q6T+WtrZkm6wvb94hAsAAG1Hu0UAAFrklLWeKenOiPiCJEXErRGxXUTMjYi5Sk2M94uIB5Ue1/LO3AvyAZJWRgRNjwEAqBA1tQCAWurSc2VfKelISbfavikPOzn3aDuUSyUdKmmRpKckHd32CAEA6DEktQCA2up0UhsR1zRbba6t7f8/JB3X5rAAAOhpJLUAgNrq60JVLQAAGF+4pxYAAAAAUFvU1AIAasrt6v0YAADUCEktAKCWutRRFAAAGGdIagEA9WTJZLUAAPQ8kloAQG2R0wIAADqKAgAAAADUFjW1AIDa6qOuFgCAnkdSCwCoJTqKAgAAEkktAKDG6CgKAACQ1AIAaoucFgAAdDapXb9Oeurxsc+/6ebFIXjL55UtoK+8b6144rGy+e+7ozgGb7JZWQzr15XHsNkWZQvom1Qew6TCr0CsL45B6wuXsa5wX0yfWTZ/6TYEAAAAClAaBQDUlqmrBQCg55HUAgBqyZL6yGkBAOh5JLUAgNoipwUAACS1AIDaIqkFAABj7vXI9hzbV9q+w/bttj9YZWAAAAATCWUnAGiPkpratZJOiIgbbE+XdL3tyyOivGteAABaQEdRqBnKTgDQBmNOaiNimaRl+f9Vtu+UtJMkfpgBAB1hclrUCGUnAGiPSu6ptT1X0r6SrqtieQAANGMV3EMDdBllJwCoTnF5wPYWkn4g6fiIeHyI8cfaXmh74cOPrixdHQAAQK2Nquy0/JHOBwgANVOU1NqeovSjfF5EXDzUNBGxICLmRcS8bbfeqmR1AAAM4Da8gHYaddlp1jadDRAAamjMzY9tW9KZku6MiC9UFxIAAK0xN9WiRig7AUB7lNTUvlLSkZJeb/um/Dq0orgAAGiKmlrUDGUnAGiDkt6PrxHnfwBAl5CEom4oOwFAe9BxJAAAAACgtip5pA8AAB1nc08tAADocFLbN0nadPOOrnKweGqjnvNHZ/268iDWrS2a3VvOLA4hHl9RFsN2c4pj8OQpZQvYdHpxDFr9dPkyCsXa1WULKPwMXl/YK3kV3wlgjPrIaQF0SKxfX7aASs6XUTa7K2ik2TepLAQuRqINqKkFANSWyWoBAOh5JLUAgFqyJC74AwAAOooCAAAAANQWNbUAgHoyNbUAAICkFgBQY3Q4AgAASGoBALVFTgsAAEhqAQC1RU0tAACgoygAAAAAQG1RUwsAqCUe6QMAACSSWgBAXVnqI6sFAKDnkdQCAGqLnBYAAJDUAgBqynQUBQAA6CgKAAAAAFBf1NQCAGrJksylWQAAeh5JLQCgnsxzagEAAEktAKDGyGkBAEDvJbXr15XNv25teQzPPlUYQ+FnkKS+SUWzx903FocQhZ/DO8wtjkGbbFY0ezyxsjyGwmPS280pW3+sL5sf6CG250g6V9L2kkLSgog43fZnJR0uabWkP0g6OiIey/OcJOkYSeskfSAift6N2IFeFqXlP0l65smyGJ54tIIYysqQ3mKr8hg2n1E0e0zZtDgE93HvCQbiiAAA1Jbtyl9NrJV0QkTsIekAScfZ3kPS5ZL2ioi9Jf1e0kk5vj0kvU3SnpIOlvRV22VXFQEAwAAktQCA2rKrf40kIpZFxA35/1WS7pS0U0RcFhH9TXmulTQ7/z9f0gUR8WxE3CNpkaT927EtAADoVb3X/BgAMCFYUl8Xb6q1PVfSvpKuGzTq3ZK+l//fSSnJ7bckDwMAABUhqQUA1FMLNatjNMv2wob3CyJiwYBV21tI+oGk4yPi8YbhH1NqonxeWyIDAAAbKU5q871BCyUtjYjDykMCAKCrlkfEvOFG2p6ilNCeFxEXNwx/l6TDJB0YEZEHL5XU2Jvb7DwMPYyyEwBUq4p7aj+odE8RAAAd1emOopwmOFPSnRHxhYbhB0s6UdKbI6Kxe9JLJL3N9ia2d5W0m6TfVL4hUDeUnQCgQkVJre3Zkt4k6VvVhAMAQOs63VGUpFdKOlLS623flF+HSvqypOmSLs/Dvi5JEXG7pAsl3SHpZ5KOi4gKni2CuqLsBADVK21+fJrSlenp5aEAANA6q2331A4rIq7Jqx7s0hHm+ZSkT7UtKNTNaaLsBACVGnNNre3DJD0UEdc3me5Y2wttL3x4RQUPnQYAQJJsua/6F9AuYyo7LX+kQ9EBQH2VND9+paQ3275X0gVKTbG+O3iiiFgQEfMiYt62M7cuWB0AAECtjb7sNGubTscIALUz5qQ2Ik6KiNkRMVfS2yT9IiLeUVlkAAA00YV7aoExo+wEAO3Bc2oBALXVRxYKAEDPqySpjYirJF1VxbIAAGhFNzqKAqpC2QkAqkNNLQCgtpo9VxYAAEx8Rc+pBQAAAACgm+pVUxtRvozVz5bNv7Zwfknx1BNlC1i3pjgGPbGyaPZnvnFmcQjPPlgWw5Z/sVdxDD7osLIFTJ5aHIOefbps/hnblc0/ZZOy+av4XgJjQcdOQM+I0nPN6sJzraT1991eNH9c+v0KYlhcNP+k/V9WHIPf8Ddl82+zU3EM6issu2DCqVdSCwBAA5ofAwAAkloAQG2R0wIAAO6pBQAAAADUFjW1AIBaSo/0oaoWAIBeR1ILAKgnS6a9EQAAPY+kFgBQU6amFgAAkNQCAGqsj6QWAIBeR8MtAAAAAEBtUVMLAKgvmh8DANDzSGoBAPVkej8GAAAktQCAOuOeWgAAeh5JLQCgpkzzYwAAQEdRAAAAAID6oqYWAFBLtmSaHwMA0PNIagEA9UXzYwAAeh5JLQCgtqipBQAAnU9q+yaNfd51a8vXv75wGWtWl8ew+pmy+ddWEMMf7iqa/Xv/9fviEH6zqmw7vP/BJ4tjeNErXl00v+e+uDiGWPVo2QImFXynJEXx9yoK5wcKUFML9IZYXzb/M0+Vx/DbXxbNfs2XflYcwuWPlpV9jrvh/uIYtt/1hUXze6tti2OIyVPLYuDcMeHQURQAAAAAoLZofgwAqCeb59QCAACSWgBAfdGEDAAAkNQCAOqLmloAAHpe0T21tmfYvsj2XbbvtP2KqgIDAACYaCg7AUD1SmtqT5f0s4j4G9tTJU2rICYAAJqz6P0YdUTZCQAqNuak1vZWkv5C0rskKSJWS6rgWTMAALTG9OGPGqHsBADtUVIc2FXSw5K+bftG29+yvXlFcQEA0Jxd/QtoH8pOANAGJUntZEn7SfpaROwr6UlJHx08ke1jbS+0vfDhFY8WrA4AgAa23Ff9C2ij0Zedlj/S6RgBoHZKktolkpZExHX5/UVKP9QDRMSCiJgXEfO2nbl1weoAAABqbfRlp1nbdDRAAKijMSe1EfGgpMW2d8+DDpR0RyVRAQDQCpofo0YoOwFAe5T2fvx+Sefl3vv+KOno8pAAAGgRzYVRP5SdAKBiRUltRNwkaV41oQAA0LpUsUpSi3qh7AQA1SutqQUAoHuoqQUAoOfxhD8AAAAAQG3Vq6a2imZmUzYpm39NBc9InzSpbP615SEoomj2Z9aXzV+FZ59dX76Qwu1QvC8lafKUotm9adkjDmPNs0XzF29DYMzo2AlAqyo4VxWWAZ9aV15ueWTtuqL5n3mmbH5J0vrCZVBuQBvUK6kFAKAB99QCAACSWgBAPVncUwsAAEhqAQD1RU0tAACgoygAAFpke47tK23fYft22x/Mw2favtz23fnv1nm4bZ9he5HtW2zv191PAADAxENSCwCorz5X/xrZWkknRMQekg6QdJztPSR9VNIVEbGbpCvye0k6RNJu+XWspK+1YzMAANDLSGoBAPVkt+c1gohYFhE35P9XSbpT0k6S5ks6J092jqS35P/nSzo3kmslzbC9Qxu2BgAAPYt7agEAteUudhRle66kfSVdJ2n7iFiWRz0oafv8/06SFjfMtiQPWyYAAFAJkloAAAaaZXthw/sFEbGgcQLbW0j6gaTjI+Lxxg6rIiJs8yBGAAA6hKQWAFBf7en9eHlEzBt+lZ6ilNCeFxEX58F/sr1DRCzLzYsfysOXSprTMPvsPAwAAFSEe2oBAPXU/5zaDnYU5VQle6akOyPiCw2jLpF0VP7/KEn/2TD8nbkX5AMkrWxopgwAACpATS0AoLa68JzaV0o6UtKttm/Kw06WdKqkC20fI+k+SW/N4y6VdKikRZKeknR0R6MFAKAHkNQCAGqqpUfwVCoirkkrHtKBQ0wfko5ra1AAAPQ4mh8DAAAAAGqLmloAQH11vvkxAAAYZ0hqAQD1ZJHUAgAAkloAQI2R1AIA0PM6m9TaUt+kjq6yclOmli9j6qZl87uCW6F336to9iNfNbc4hIfuW1k0/5xX7locgzabVjR7PPVEcQjeZLOyBUwpPJ7WrS2bn6QCXWOpj64hgN5QeK6ZWniulaT/8aqi2Q96173FIbz6rsVF82/2uv2LY/DcPcsWMLm8LN2Fnu8xzlEaAAAAAADUFs2PAQD1xdV6AAB6HkktAKCe6CgKAACIpBYAUGcktQAA9Lyie2ptf8j27bZvs32+7cIeawAAaFXuKKrqF9BGlJ0AoHpjPnvb3knSByTNi4i9JE2S9LaqAgMAAJhIKDsBQHuUNj+eLGkz22skTZP0QHlIAAC0iObHqB/KTgBQsTHX1EbEUkmfk3S/pGWSVkbEZVUFBgDAiPo7iqr6BbQJZScAaI+S5sdbS5ovaVdJO0ra3PY7hpjuWNsLbS98+JFHxx4pAACDkdSiRsZUdlr+SKfDBIDaKekR4w2S7omIhyNijaSLJf354IkiYkFEzIuIedtus3XB6gAAaERHUaid0ZedZm3T8SABoG5Kzt73SzrA9jTblnSgpDurCQsAAGDCoewEAG0w5o6iIuI62xdJukHSWkk3SlpQVWAAADRFc2HUCGUnAGiPot6PI+ITkj5RUSwAALSuv6MooEYoOwFA9Uof6QMAQPeQ1AIA0PPoEQMAAAAAUFsdrqm1PKlglSXzViQqWEZxvcLk1eVBzNiuaPZpH/iH4hDmPrikbAHb7lAcg7acWTS7N9msPIZJk8rmj/VFsxd9J9MSCucHxsayTG/FQE8o/a7HJtOKY+h7wb5lMbynvNwy7anHi+b31tsXx+CtZpUtYPLU4hiAwbqfJQIAMFY0PwYAoOeR1AIA6omOogAAgEhqAQB1RlILAEDP42YkAAAAAEBtUVMLAKgpS3QUBQBAzyOpBQDUF82PAQDoeSS1AIB6oqMoAAAgkloAQJ2R1AIA0PO4GQkAAAAAUFvU1AIAaoqOogAAAEktAKDOaH4MAEDPI6kFANQTHUUBAACR1AIAaovmxwAAgI6iAAAAAAA1Rk0tAKC+aH4MAEDPI6kFANQXSS0AAD2vXkmtu99a2lM2KV5GrF9XQSSFppZ9Dr9oXnEIMXP7shi22Ko4Bq0r3BfTty6PoVA8+1TR/J66aVkA5BToFjqKAtAiTyov8sa0Lcti2GRacQyOKFtAFf0Q9JVtS9MXAtqAowoAAAAAUFv1qqkFAOA59H4MAABIagEAdUbzYwAAeh5JLQCgvkhqAQDoeU3bbdk+y/ZDtm9rGDbT9uW2785/u99bDgCgt1ipA8GqX0Ahyk4A0FmtnL3PlnTwoGEflXRFROwm6Yr8HgAAAJSdAKCjmia1EXG1pBWDBs+XdE7+/xxJb6k2LAAAmrHU14ZXs7UOXQu3j+1rbd9ke6Ht/fNw2z7D9iLbt9jer40bBOMEZScA6KyxtrPaPiKW5f8flDTsA0dtH5tP8AsfXjH49x0AgALdaX58tjauhfuMpE9GxD6SPp7fS9IhknbLr2Mlfa2Kj41aGlvZafkjnYkOAGqs+OahiAhJwz4JOiIWRMS8iJi37cyZpasDAGADu/pXE8PUwoWkLfP/W0l6IP8/X9K5kVwraYbtHSr69KipUZWdZm3TwcgAoJ7G2vvxn2zvEBHL8sn5oSqDAgCgKbftObWzbC9seL8gIhY0med4ST+3/TmlC8Z/nofvJGlxw3RL8rBlQq+h7AQAbTLW0sAlko7K/x8l6T+rCQcAgK5b3l9Lll/NElpJ+kdJH4qIOZI+JOnM9oaIGqLsBABt0sojfc6X9GtJu9teYvsYSadKeqPtuyW9Ib8HAKCzutD8eBhHSbo4//99Sfvn/5dKmtMw3ew8DBMYZScA6KymzY8j4ohhRh1YcSwAAIzO+Hmu7AOSXiPpKkmvl3R3Hn6JpPfZvkDSyyWtbOgsCBMUZScA6Kyx3lMLAED3jb1mtWCVPl/Sa5XuvV0i6ROS3iPpdNuTJT2j1NOxJF0q6VBJiyQ9JenojgcMAMAER1ILAKin9nUUNaIRauH+xxDThqTj2hsRAAC9rfNJbUlTsamblq9/7eqi2ePxx8pjmLpJ0eyeNaf5RE0N+ySB1qxfXxyBZ29WGMPa4hhi7ZriZdRe6b4sPJQAAKgD900qW0Dp/ACGRU0tAKC+utD8GAAAjC8ktQCA+ho/HUUBAIAuIakFANSTLfVRUwsAQK/jEjcAAAAAoLaoqQUA1BfNjwEA6HkktQCA+qKjKAAAeh5JLQCgpkxNLQAAIKkFANSURUdRAACAjqIAAAAAAPVFTS0AoL64pxYAgJ5HUgsAqC/uqQUAoOeR1AIA6snmnloAAEBSCwCoMWpqAQDoeZQGAAAAAAC1RU0tAKC+6CgKAICeR1ILAKgp0/wYAAB0OKmdPEWeucOYZ4+nV5XHsHZ10ezeYkZ5DH2FhbB1a8pjKBXryxdRuC9K9+W4MXlqd9dfwb4EusKioygAAEBNLQCgxqipBQCg51EaAAAAAADUFjW1AID6oqMoAAB6HkktAKCmXN5HAQAAqL2mpQHbZ9l+yPZtDcM+a/su27fY/qHtGW2NEgCAwaxUU1v1CyhE2QkAOquVS9xnSzp40LDLJe0VEXtL+r2kkyqOCwAAoK7OFmUnAOiYpkltRFwtacWgYZdFxNr89lpJs9sQGwAAI3Nf9S+gEGUnAOisKs7e75b00+FG2j7W9kLbCx9e/kgFqwMAQJLa0PSY5sfoDMpOAFChoqTW9sckrZV03nDTRMSCiJgXEfO2nbVNyeoAABior6/6F9BGlJ0AoHpj7v3Y9rskHSbpwIiIyiICAKAV/R1FATVB2QkA2mNMSa3tgyWdKOk1EfFUtSEBAABMLJSdAKB9mia1ts+X9FpJs2wvkfQJpR77NpF0udNV8msj4r1tjBMAgEFMx04Ylyg7AUBnNU1qI+KIIQaf2YZYAAAYHZofYxyi7AQAnTXme2oBAOg6amoBAOh5JLUAgHqypT5qagEA6HWdTWrXr1M8vWrs8z/5WHEI8UTZMjx9ZnEMctlmj5XLy0PYsvBzrFvbfJpmMRQ+OiP6JhXHoPXryuafPLU4BE8q/BqW1lStL92XdOAJAACA7qGmFgBQXzQ/BgCg55HUAgDqi46iAADoeSS1AICa4pE+AACApBYAUGOmphYAgJ7HJW4AAAAAQG1RUwsAqCeL5scAAICkFgBQV9xTCwAASGoBAHXWxz21AAD0OpJaAEB9UVMLAEDPozQAAAAAAKgtkloAQD1Zkl39q9lq7bNsP2T7tkHD32/7Ltu32/5Mw/CTbC+y/Tvbf1n9hgAAoLfR/BgAUFNd6yjqbElflnTuc5HYr5M0X9JLI+JZ29vl4XtIepukPSXtKOm/bL8wItZ1PGoAACYoamoBAPXVhZraiLha0opBg/9R0qkR8Wye5qE8fL6kCyLi2Yi4R9IiSftXtwEAAABJLQAAA82yvbDhdWwL87xQ0qttX2f7l7ZflofvJGlxw3RL8jAAAFARmh8DAOqrPc2Pl0fEvFHOM1nSTEkHSHqZpAtt/1nlkQEAgI2Q1AIA6skeT8+pXSLp4ogISb+xvV7SLElLJc1pmG52HgYAACrS2aTWfdKUTcc+/9Rp5SFML7yqv9kWxTEUbQNJjvXlMayvYBnd1jepeBGePKUwhgq+Qn2Fx2RpDGtKj4Vxk1SgF42f59T+SNLrJF1p+4WSpkpaLukSSf9h+wtKHUXtJuk33QoSAICJiJpaAEB9tdCxU/Wr9PmSXqt07+0SSZ+QdJaks/JjflZLOirX2t5u+0JJd0haK+k4ej4GAKBaJLUAAIxCRBwxzKh3DDP9pyR9qn0RAQDQ20hqAQA11bXn1AIAgHGkaWnA9lm2H8pNqgaPO8F22J7VnvAAABhBF55TCzRD2QkAOquVS9xnSzp48EDbcyQdJOn+imMCAKA5K9XUVv0Cyp0tyk4A0DFNz94RcbWkFUOM+qKkEyVF1UEBANCcU+/hVb+AQpSdAKCzxnT2tj1f0tKIuLnieAAAACYcyk4A0D6j7ijK9jRJJys1n2ll+mMlHStJO8+ZPdrVAQAwLHMPLGqgrOw0p42RAcDEMJaa2udL2lXSzbbvlTRb0g22nzfUxBGxICLmRcS8bbfZZuyRAgAwGPfUoh7GXnaaRdkJAJoZdU1tRNwqabv+9/nHeV5ELK8wLgAARmbRWzFqgbITALRXK4/0OV/SryXtbnuJ7WPaHxYAAM2YmlqMS5SdAKCzmtbURsQRTcbPrSwaAACAmqPsBACdNermxwAAjBs0PwYAoOeR1AIA6ovnygIA0PNIagEA9WRTUwsAADqb1F5/083L+7ba9r4RJpklqds9ARLD+Iih2+snhtZj2KVTgQBAr7n+xpuWe/MZlJ3GfwzdXj8x1CsGyk4V62hSGxHbjjTe9sKImNepeIhh/MbQ7fUTw/iKARgWvRVjgqPsVI8Yur1+YiCGXkfzYwBAfdH8GACAnkdSCwCoMZJaAAB63XhLahd0OwARQ79ux9Dt9UvE0G88xAAMgY6iAI2P32hi6P76JWLoRww9yBHR7RgAABi1eXvvFb/9yYWVL7dv5z2v514oAADqY7zV1AIA0DpqagEA6HkktQCAGiOpBQCg142bZyHYPtj272wvsv3RLqx/ju0rbd9h+3bbH+x0DDmOSbZvtP3jLq1/hu2LbN9l+07br+hCDB/K++A22+fb3rQD6zzL9kO2b2sYNtP25bbvzn+37kIMn8374hbbP7Q9o9MxNIw7wXbYntXOGICWWammtuoXUAOUmwbEQtmJshNlpx43LpJa25MkfUXSIZL2kHSE7T06HMZaSSdExB6SDpB0XBdikKQPSrqzC+vtd7qkn0XEiyS9tNOx2N5J0gckzYuIvSRNkvS2Dqz6bEkHDxr2UUlXRMRukq7I7zsdw+WS9oqIvSX9XtJJXYhBtudIOkjS/W1ePzA6bsMLGOcoN22EshNlp0aUnXrQuEhqJe0vaVFE/DEiVku6QNL8TgYQEcsi4ob8/yqlH6SdOhmD7dmS3iTpW51cb8P6t5L0F5LOlKSIWB0Rj3UhlMmSNrM9WdI0SQ+0e4URcbWkFYMGz5d0Tv7/HElv6XQMEXFZRKzNb6+VNLvTMWRflHSiJHqWA4Duo9yUUXZ6DmWnDcMoO/Wg8ZLU7iRpccP7JerCD2M/23Ml7Svpug6v+jSlg399h9fbb1dJD0v6dm7G8y3bm3cygIhYKulzSle1lklaGRGXdTKGBttHxLL8/4OStu9SHP3eLemnnV6p7fmSlkbEzZ1eN9AcVbXoSZSbNjhNlJ0oOw2PslOPGC9J7bhhewtJP5B0fEQ83sH1HibpoYi4vlPrHMJkSftJ+lpE7CvpSbW/2cgA+d6L+UoniR0lbW77HZ2MYSiRnn3VtStttj+m1NTrvA6vd5qkkyV9vJPrBVrThvtpuacWGJVulZvyuik7ibLTcCg79ZbxktQulTSn4f3sPKyjbE9R+mE+LyIu7vDqXynpzbbvVWpG9Hrb3+1wDEskLYmI/iutFyn9UHfSGyTdExEPR8QaSRdL+vMOx9DvT7Z3kKT896FuBGH7XZIOk/T26PyDpZ+vdJK8OR+bsyXdYPt5HY4DGBpJLXoT5aaEslNC2WkQyk69Z7wktb+VtJvtXW1PVbq5/ZJOBmDbSvdD3BkRX+jkuiUpIk6KiNkRMVfp8/8iIjp6lS0iHpS02PbuedCBku7oZAxKTWcOsD0t75MD1b3OHy6RdFT+/yhJ/9npAGwfrNSs6s0R8VSn1x8Rt0bEdhExNx+bSyTtl48VYByg+TF6Us+XmyTKTg0oOzWg7NSbxkVSm2/mfp+knyt9CS+MiNs7HMYrJR2pdJXvpvw6tMMxjAfvl3Se7Vsk7SPp051ceb7SeZGkGyTdqnSMLmj3em2fL+nXkna3vcT2MZJOlfRG23crXQU9tQsxfFnSdEmX52Py612IAQAwjlBuGncoO1F2ouzUZe58jTwAAOXmvfQl8dvLqq8E6Hve86+PiHmVLxgAALTF5G4HAADA2NFcGACAXkdSCwCoJzp2AgAAGif31AIAAAAAMBbU1AIA6ouaWgAAeh5JLQCgxkhqAQDodSS1AIDaMjW1AAD0PJJaAEB9kdQCANDz6CgKAAAAAFBb1NQCAGrK4p5aAABAUgsAqC+aHwMA0PNIagEA9WSR1AIAAJJaAECdkdQCANDr6CgKAAAAAFBbJLUAgPqyq381XaXPsv2Q7duGGHeC7bA9K7+37TNsL7J9i+392rAVAADoaSS1AID6chtezZ0t6eCNQrHnSDpI0v0Ngw+RtFt+HSvpa6P5eAAAoDmSWgBATbUjo22e1UbE1ZJWDDHqi5JOlBQNw+ZLOjeSayXNsL3DKD8oAAAYAR1FAQDqa5z0fmx7vqSlEXGzB8a0k6TFDe+X5GHLOhgeAAATGkktAAADzbK9sOH9gohYMNzEtqdJOlmp6TEAAOgwkloAQD217zm1yyNi3iimf76kXSX119LOlnSD7f0lLZU0p2Ha2XkYAACoCPfUAgBqrDs9RTWKiFsjYruImBsRc5WaGO8XEQ9KukTSO3MvyAdIWhkRND0GAKBCJLUAgPrqziN9zpf0a0m7215i+5gRJr9U0h8lLZL0TUn/VMXHBgAAG9D8GACAUYiII5qMn9vwf0g6rt0xAQDQy0hqAQA11VrNKgAAmNhIagEANUZSCwBAryOpBQDUFzW1AAD0PKfbfQAAqBfbP5M0qw2LXh4RB7dhuQAAoA1IagEAAAAAtcUjfQAAAAAAtUVSCwAAAACoLZJaAAAAAEBtkdQCAAAAAGqLpBYAAAAAUFv/Pym0lkvMXDm3AAAAAElFTkSuQmCC +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 2 con incertidumbre (Banda Rojo)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [830]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_R2</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata2</span><span class="p">,</span> <span class="n">poptR2</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR2</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR2</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR2</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR2</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteR2</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptR2E</span><span class="p">,</span> <span class="n">pcovR2E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata2</span><span class="p">,</span> <span class="n">recorteR2</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">Err_R2</span><span class="p">)</span> +<span class="n">estrellaR2E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata2</span><span class="p">,</span> <span class="n">poptR2E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR2E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR2E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR2E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR2E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMR2E</span><span class="o">=</span><span class="n">FWHMR_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptR2E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 2 fotografÃa (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteR2</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 2 a partir de la gaussiana con incertidumbre (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaR2E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">35</span><span class="p">,</span> <span class="mi">35</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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5f0Ry3HfLuqc1gqezzC9sttX193M9wp6RUqH5sj8jE5zzNc12Q/Vs9/l6turM+pp/+eqhanz7rqujzlQDfTPC+TyxjL62Vncu1tUFVpnUq7MsGDcWSr+yN5mIZH8h4Re+t/l9f52R4RO6ZY5vGSLpy4LupzsmFSnmZyrZ6oqvLWOk7MXaWZC+5v+X+fpG3x6GBEE2OwtB6TyZ/DUR15bjr9HExVhpWqxoyVEXGUqu7Fr3fdXX6aZc0przE99jP8sKryvup1d/IdtaZe/4WqyrKjLduafB0u1GO/g09Ude3snjRv6/FaIWlXm3zMy8rslCLivoh4Y0ScqOrXtz91PipiTHp/j6SXT7r5LomqK2fmt+t1Pa2uZP20VH4oq+5+8SlVFceZDt5zr6oP08S6jlLVlaCUx2z+LWrpglB3J5n8HOjkYzSjfZ3kQlW/3jy7Xnaia1Rp+ZslPbm0sojYpeoXu1fW+f8+VYWkV6v6BXGlqg/IdPK3RdK6li41UvULYad5b83nP6pqof79etLkc2JVX/5TncMj5q3zdG/LsutUdTOZVQgGYK5yD7oY0814sObpvfoDkr4p6dR63Rdl665taPm/9bt9OuuafEymI1tmS2t+Wu5LE+5R1WLaesyXRkQaHq4+hp9Qdf9bW9+Xr1H52BxRLpmUp3brelhVi+LE/I9rXXFEfCUizlbVPfNTqlpOFRG7I+LCiHiiqkeR/pvtF02Rt07O8YSZXHv3qOq6OZW0TNAj90ha7amf8b1H0jsnXRfLIqK16+3k667ddbiqLqtOaC2LTT7HC1R1952NyZ/DQ5K2tUxrze9MPgd3VFl08QefiLhTVWvvRFSKjsuaeuxneJmq8v6Ejq7fqMYMeI+k/Xq0W/JU1+GYjvwhYWK+1a66zrfO2/pd/R8kfb1dPoamMmv7x/3og9I7VF2A4/X7+1X+cpjwvyW90/XD3LaPc9U/vp0Vqrox7Kov2mIYGtujqp5T3SfpnLpVbiY+JukNtk+vv9h/W9KX6g+E9Nj9zOb/G0lPs/2qunXyfFVdSjLT3tfCsvtUhZNZLentbea/RtWzClNyNarka/To6MkrVH2YHpC00Pb/UtU9bDr+tV72l22P2v5RVc+idJr3yf5Q0ottP0PVDfSHbL+ovh4ulHRAVbfmyT4m6dfra3GNqm4krfHWfkDSP0TEgRnmB2gMBoCaX+bpvXqFqsdf9tj+Xkn/dRr5+Z91S8xTVD0DN/Gsayfrms5xy/yNpKfY/tG6PPDLOrI88L8lva3Oq2wfY/vHp7HeRZIWq7ovj7kaVGjyADytrpT0Ztvr6srT/5jBur5e78PprsbKuHgiwfYi2z9l+5ioois8pPqaczWA0Sl1BX6Xqlb+qc53J+elddnplp3+WtIJti9wNeDTCj8aFqpdmaDrImKLqgrXn7oaoGjU9kQl64OSfsH2s105yvYPTaq8TFa8ViPiLkk3SHpHfc6ep0crepL0b6p61P1Q/Rn9dVXXxGz8tO3T6srfb0j6qyiHlZn25yAiDqp69jkrx66X9DIdWY7ttKz5V5J+2PbzXI3B8hs6sg44m+tXkt4l6S31Z+tjkn7F1WBdy1XVLT4+qVeAIuIeVWXb37G9xNXgYOfqseXYv2238flYmZ0YBW3i9cl6+rMkfcn2HlWD+7w5Ir5Tp10s6XJXXQNeXVjvH9XLfdb2blUDC00nrtw7VA1UsEvVDeGqZN7/pGqAgJeoulgn9uH7kmUeERF/r+qZy0+o+hXmSaoqdBMuVst+ZvNHxDZJP67qWZ0HVT0rcIOqilU39nWyP5S0VNUvXterGtwg82FJr3DVzWvCiRPHTFVXhdWSfqpO+0y9zn+r0/Zrmt1b6i+dH1X13Mh2ST+hI/dtpnmfvP4H6v35XxHxLVW/yv5xvb5XqhoM4eAUi/6WqnNys6pntr5aT5vwU6q+XIF5i5bZxhqme/WvqhqYZbeqAn5pEKZW/6iq9eZzkn4/Ij47i3VdrPbHrailPPAuVeWBUyX9c0v6JyX9rqQrXHVR/IaqgZrarXe3qorxlap+uPhJVeeu5IOqBge7WdXgPdeo+qH5cLt1RTXo5G+oqkB8W9IRIxurGhjnzjr/v6BHyw6n1svsUfXD9p9GxHVT5K2T8zJh2tdevZ8vVlU2uK/elxfUye3KBL3yOlUtlt9U9RzuBXVeb1A1aNf7VZ2TO1SVozK/o6pCvtMto3i3+ElVn+ftqipzH55IqHvk/aKqSB+bVbXUTjnA0gz8uarec/epimLxy6UZO/gc/JmqY9fqJ1rKsV9R9Tl7R532h+qwrBkRt6pqlPqoqvL+Dh15bGZz/UrVdbtD1fm+TNVx+4Kk76oqb/9SYbnXqnqO9l5Jn5T09rpuorpi/Aq1PC5YMvGwLpByNRT9Jkk/Vfgi7zvbvy1pa0T84aDz0i+uhoD/6Yj4Qpv5ni7pzyLiOdl8QJM9fsHCeOvSlV1f7y8+/OCNEbGx/ZxAd9k+WVUBcHRySwaOVLe+/u+IeHzbmYE5yPY/q4ry8bVB56UfbD9RVaPSaLSpgNr+JUkbIuIt7dbb6CDF6C3bL5X0JVXdGv67qv7z16cL9VFEXDToPPST7eNUPf9xZ7t5I+JmVcOrAwDQeHVPrBeoap1dq6pl7pPpQsAcFhHPbT/XvPJUSXe1q8hKUkT88XRXOh+7GaN7nqNq1LyJ7q6vioh9+SLoBdvPUtWd6I8j4u5B5weYK+hmDAwNq+pyuUNVN+PbVT0XCmCOs/3fVIVdm3JE8Fmtm27GAIAmOnnBaPzaspVdX+95e7bRzRgAgAagmzEAoLFoSQUAYHhRmQUANBZ1WQAAhtesKrO2X6ZqGPwFkv5PRLwrm3/NscfGySdtmDoxK5FkPaHHS+Ge2nCnRaBOM9pG1t07y2u2XNqFPEtLtpcetk6P6Tzo6t5uF0YWDGCjpcU6Pd5TL3fnPZu1bfsO6hQAMA0zLjutOTZOPumkvuQNQH/ceffd2rbtQcpOXdBxZdb2Akl/oire1SZJX7F9dUTcVlrm5JM26Cv/+PdTJ44kY1EdTkan37c7yWSyzgVJ5SJbLksbbzOK/nhW8Uxirmd5HTuUpE0VmnQiL8n2snPR6bHJtI033wDt9mHZMf3d5uHkR550ueQaLiz3rFf8WHkZoIcsuhmjWTorO52kG774+T7lEEA/bHze8wedhXljNqMZnynpjoj4TkQclHSFpLO7ky0AANobkbv+AnqIshMAdNFsKrPrJN3T8n5TPe0Its+zfYPtGx548MFZbA4AgEe5B2F5aOlFj8287LSNshMAlPQ8zmxEXBIRGyNi43HHHtvrzQEAhshID17AoB1RdlpD2QkASmZz394sqXU0p/X1NAAAADwWZScA6KLZjGb8FUmn2n6Cqi/i10j6yXSJ8cPSnh1Tp2WDDi05qpy2aGk5rRcDC2XrHGlzOJ0s69FyWjbIU7bNLDvZAFDZQFbJoFKRrTMxsvbk8jof2lZMG//218or3benmOT1p5TTVq4trzOzcFGeng1Uli27MLkuskGeDu1PlkvOb5aX0SVTT+904C+gC+gVjIaZedkJAFDUcWU2IsZsv0nSZ1QNL39ZRNzatZwBAJCoRjOmOovmoOwEAN01qzizEXGNpGu6lBcAAGaEqiyahrITAHQP/QMBAAAAAI0zq5ZZAAAGiZZZAACGF5VZAEBjUZkFAGB4UZkFADSWGQAKAICh1YzKbBbyJQvpkz0SnK2z05A+WUibdrJtdrreTvexwxA7nYq9u8qJSSggjSZhZMaTkE2ji5PMZOGTZvGIebZsp2kLku1FcmyydXYUJojKBAbD4uoDAGCYMQAUAAAAAKBxmtEyCwDAFPhFFgCA4UVlFgDQWDwyCwDA8KIyCwBoLPPULAAAQ4seWgCARnKPXuk27Q22r7N9m+1bbb95UvqFtsP2mvq9bb/P9h22b7b9zG7sOwAAoGUWAICZGJN0YUR81fYKSTfavjYibrO9QdJLJN3dMv/LJZ1av54t6QP1XwAAMEtzpzLbaTiYkQ53wcn2snAwWeiWw4c7y0u79fY5VE6nnIZJKovdO8qJ4+Vj6sXl8DuRhO3xoiXTytdj85KESFrQo49Sp2GiOg2/syCJ91PaRx5axAD1++qLiC2SttT/77Z9u6R1km6T9F5Jb5H06ZZFzpb04YgISdfbXmn7hHo9AABgFuZOZRYAgBka6U1tdo3tG1reXxIRl0yeyfbJks6Q9CXbZ0vaHBFf95E/8KyTdE/L+031NCqzAADMEpVZAEBDuVcDQG2LiI3plu3lkj4h6QJVXY8vUtXFGAAA9AmVWQBAI01nwKaebNceVVWR/UhEXGX7aZKeIGmiVXa9pK/aPlPSZkkbWhZfX08DAACzxGjGAABMk6va6qWSbo+I90hSRNwSEcdHxMkRcbKqrsTPjIj7JF0t6fX1qMZnSdrF87IAAHQHLbMAgGbyQMYfe66k10m6xfZN9bSLIuKawvzXSHqFpDsk7ZX0hp7nEACAIUFlFgDQWAMYzfiL7TZbt85O/B+Szu9xtgAAGEr9r8yWwrdk4WfGDpXTOg1d0qks/E67vGT7mC3b733MQuy4w0vmcBLW5uHt5bSlK8ppy1cWkzyShJjJQtOkoZeSfXASzqmdLOTPXFI8NtHXbACtRgby1CyA+ar6/QmTmTB8mKN4ZhYAAAAA0Dh0MwYANNKgRjMGAABzA5VZAEBj0fMNAIDhRWUWANBY1GUBABheVGYBAI1lqrMAAAwtBoACAAAAADRO/1tmXag/L0yykoUuObR/5tuS2oSfSdKy8CztdBqCZTbbLMn2MdPpzx/Z8V64uJjkhaPl5VxeLtXh+Y2DybWWhV2S5NEkHFB2frP1Zsc0zUy2/8lypdA8hDHAgFjSCA2zAKbQcYidju9pc+le2P0vxk73jpA+6LVZVWZt3ylpt6oi8FhEbOxGpgAAmA6KSWgayk4A0D3daJl9QURs68J6AACYESqzaCjKTgDQBQwABQBoLAaAAgBgeM12AKiQ9FnbN9o+b6oZbJ9n+wbbNzywffssNwcAANBoMys7bXuwz9kDgOaYbcvs8yJis+3jJV1r+5sR8YXWGSLiEkmXSNLGZzxtLj0dDwBoOMYWQQPNrOz0zDMoOwFAwaxaZiNic/13q6RPSjqzG5kCAKAdq7qJdfsF9BJlJwDono5bZm0fJWkkInbX/79E0m+0WUhasGDmGxtLwpOMHSynLch2L0nLSjPZOrO8tJOEYImxQ52vt59GOji3UnpNRBryJg+HU+LsHJbCz0jSoQPltMNZTBtJWWiebJuZDhfruLRe2kVC82CAaJhFk3RUdhpyvQmxk6T1e3s9kXwzZt1ZsrROD0uSRtgedMNsuhmvlfTJ+kJcKOmjEfF3XckVAADTQGEIDUPZCQC6qOPKbER8R9IzupgXAACAeYuyEwB0F6F5AACNRbssAADDi8osAKCRLCqzAAAMMyqzAIBmsnlmFgCAIUYUAgAAAABA4/S3ZdYj0uiSqdOysDZZ6JIszIqTuvpIltZh6JZ2Do8lq03Wu29359vsp3bhaUqycE3ZOjs8LrHy+HLieLK9LK2dhUlonjT8UIey6zv7XGTXdy/yCczSCA2zQKN1HHqnWjhJS+5Zc2m5XkjD73RYNs4e6siWyw5ZsrV26JWDCXQzBgA0lqnNAgAwtKjMAgAaycobIAAAwPxGZRYA0EymMgsAwDBjACgAAAAAQOPQMgsAaCwGAQEAYHhRmQUANBZ1WQAAhlf/K7OlIcGzocIzWciTbJ1ZOJjMeIchT9Qm/E4WmqjDkDeRrTPTaYidTkPXjJbPoQ+V9yEe2l5e50j5/Hrx0iQvi8tpmXb7vnA0WTYZnH68HM4pvd46/TylCM2DuYeWWWDuS8PvtA1b0+Gy2X05DUPXYYi+7F7ei7A9vQi/k5Sd8rA9yXJpeaRNWSXZx+ya4r4wXGiZBQA0EqMZAwAw3BgACgAAAADQOLTMAgCaydIITbMAAAwtKrMAgMaiLgsAwPCiMgsAaCgz0AcAAEOMyiwAoJGsHg3cDQAAGoFiAAAAAACgcfrbMjt+WNq7a+q0ZceUl+s0nubhJEZnFoN1QXJYOo3dJclJehw6UE57uHDMpDTObhpPNRGH95UT9+0pp+1K4r7uTZZbtryclyRNR68uJvnoY8vLJcfFybmPLP5aEg9XkrT/4Ty9ZCT7iCZx69pcix1tr3Tc6OaJQTHxBIG5ovNYsm3irI73IiZsVj5M0rLlsjJnkpfI9i+RlSnTeLELkrj3Wfk3TUvOYRq7tpxU6SyWLjFohwvdjAEAjUW5BACA4UVlFgDQWPzKDgDA8KIyCwBoLOqyAAAMLwaAAgAAAAA0Di2zAIBGsqQRmmYBABhaVGYBAM1kuhkDADDM2lZmbV8m6YclbY2Ip9bTVkv6uKSTJd0p6dURsaPt1uxy6I9OhwOPzoY0T4dQ78U6JcXucuia2JOE38nCvhxOhnvPwg9lsu1l+dyfhPTJ1pkNn58tl+3fgb3ltAXlYeLTAAHZOtuF5lmehJ7KhuV3h9ditlin1zcwBzEAFOairpad5oXk7touNE0vQuyMlcMhKguVuD8pBxwol4Hi0P7yckk5LhMLyyF2vGhxecElRyXLJSEdR5N1ZuWKLBRQO1lYn+ya4r4wVKbzzOyHJL1s0rS3SvpcRJwq6XP1ewAA5jXbG2xfZ/s227fafnM9/fdsf9P2zbY/aXtlyzJvs32H7W/ZfunAMo9++pAoOwFAz7WtzEbEFyRNblI8W9Ll9f+XS3pVd7MFAEB7dvdfbYxJujAiTpN0lqTzbZ8m6VpJT42Ip0v6N0lvq/Ln0yS9RtJTVFVu/tR21tyAeYCyEwD0R6ejGa+NiC31//dJWtul/AAAMC1W/yuzEbElIr5a/79b0u2S1kXEZyNiol/j9ZLW1/+fLemKiDgQEd+VdIekM3twODD3UXYCgC6b9QBQERG2ix3XbZ8n6TxJOmn9utluDgCAii2P9OTZqDW2b2h5f0lEXPLYzftkSWdI+tKkpJ9V9WykJK1TVbmdsKmehiE2o7LThg19yxcANE2nldn7bZ8QEVtsnyBpa2nGugBwiSRtPP3p6fg6AADMRI/G+dgWERvz7Xq5pE9IuiAiHmqZ/muquiJ/pCc5Q5N1VnZ65hmUnQCgoNNuxldLOqf+/xxJn+5OdgAAmNtsj6qqyH4kIq5qmf4zqkaw/amImKiAbJbU2rS2vp6G4UPZCQC6bDqheT4m6fmqul1tkvR2Se+SdKXtcyXdJenV09paRHkY9SysjZM6d5amPFROUTZMfDL8eBxMhl6XFHv3lBOzkDeZXoS82Z3kJUmLvVnomkPFJK99XHm5LKTN6KJyXhaW05yE5tHe3eW05HhGm9A8fR8kPhsmP0trE15q6vXRaIDBGelzCAZXsYAulXR7RLynZfrLJL1F0g9EROuX4dWSPmr7PZJOlHSqpC/3McsYgK6WneaQyL7vO05rF5onC7FTLlsoKZNFFmpvz87ycruTSEpZ+WHfw+W0LIRQJgm/E0vL4XfSclWWdtTKYpIXJyF9ZqPj7/dy3SArsRDqrZnaVmYj4rWFpBd1OS8AAEzbxABQffZcSa+TdIvtm+ppF0l6n6TFkq6tC0TXR8QvRMSttq+UdJuqX1jPj4jOAkuiMSg7AUB/zHoAKAAABqXfv6RHxBc1dWeLa5Jl3inpnT3LFAAAQ4rKLACgmaYXFxYAAMxTnQ4ABQAAAADAwNAyCwBoLAbsAABgeFGZBQA0FnVZAACGV38rszEulYZDH0mykg3bvnC0s7ws6HDXs9AlI0nIF0nKQsJkaVmonCwkTBYKaOf2YlLsSZbblYXtKQ9LP36gPHz+yOHywJ5eva+8vQ6PZ4wlxywJ6aNsuWQfpDx0j7NrMQ091aGuh+0hNA8GoxrNmNosMDd0GH4nCyMo5eWuQwfKm9xfLsvErm3lde54oJz24P3ltF3lsD2x+6HycgeTskX2/bZkSXmx5UeXl1t1bDEpjj2+vM4khFAcs6a8XBacsN3393hSBhrJ1psG4Mm3icahZRYA0Ezuze89AACgGSgGAAAAAAAah5ZZAEBDmW7GAAAMMSqzAIDmyp6bAgAA8xqVWQBAc9EyCwDA0OKZWQAAAABA4/Q5NI8U41MPz+4s7EmnYXSyoeA7NdJ5/d9J6J7IwvrsKofR0f5y6JrYtbO83LbysPTj28rbO3hfOTTP4T3lIfLHD5WHdF96sDws/8LjykPd61A53E/aVrNseTltNAnNk4UCaheWKQs9kF1T2TXc6TCuDP+K+cKE5gG6LSILsdNhWqHsJykPvSNJY+V7fRzcX057KCk7PXhfOW3LpvI679tcXu6Bckif8Z3l0Dzj+8r7l1mwfHE5cfWqctpxO4tJPpiEOkrOb1a+nVXZKUvPyjKR3RfK+5EG9OFeM2fRzRgA0Fw8MwsAwNCiMgsAaCjzzCwAAEOMyiwAoJFsybTMAgAwtHh4DgAAAADQOLTMAgCai27GAAAMLSqzAIDGopsxAADDq7+V2ZERefGyQk6SkCiZZMh2JeF+suHcO7Zvd5oce8phbXSgHGKn4/A7d99dXuV37i+mPXh3eZ3bt5eP255D5fAzY+PlAc/XbSuv83Hry6F5liWhedLh1desLSeuOKacloX0aTe8/IG9xaRQ4TMhyZ2GpUqHrO9BuB9gUGiZBfqo07A9yX0nC9sjpWU57S2HvNFDD5bTtm4pJsW995TT7krKVXeVQx4+/MCeYtq+feWyU3ZLPuqo0WLasrXl8ubik5PySBZ+JymPxGgSJmjx0mSd5X2QJI0nZaCs3BXJgeOWMe/QMgsAaCab0DwAAAwxmmEAAAAAAI1DyywAoLFMN2MAAIYWlVkAQHPRzRgAgKFFZRYA0EwWA0ABADDEqMwCABqLAbgBABhebSuzti+T9MOStkbEU+tpF0t6o6QH6tkuiohr2m7NlhYlw3eXZOF3OjVeHgo9TTt0oJgUe8tDr0uSstA8u8tpsffh8nLbtxeTDtz1QDFt07fKQ8jfuaM8bPt9B8eKaTvHysPrjyXDvW9NQuycsrs8JP+pC8otMstGk+HeRzos/Y4m4aOyNOVhmXwoCSGVrNPZUPhZSJ8sDEJ2aKg1AMC0dLXs1BRZ+J00NE+5XCFJkZQB03LXQzvLyz24tbzc5s3FpH3fLoc13HJP+T6/bVe57LjncPnYZP1Ojl5YDk2zdnf5mB2XbG/JoqQsc1QSnvCYleW05Una0qPKaZI0npRz0rJMVnpKS1Z5fjAnTad0+iFJL5ti+nsj4vT6NX++jAEAzWF3/wXM3odE2QkAeq5ty2xEfMH2yX3ICwAA02fLDACFOYiyEwD0x2z6Db7J9s22L7O9qms5AgBgumiZRbNQdgKALuq0MvsBSU+SdLqkLZL+oDSj7fNs32D7hgceLD/fCQAAMI91Vnba9mCfsgcAzdNRZTYi7o+IwxExLumDks5M5r0kIjZGxMbjjl3daT4BAHisEXf/BfRAx2WnNcf2L5MA0DAdheaxfUJEbKnf/oikb3QvSwAAtFf1CqbyiWag7AQA3Ted0Dwfk/R8SWtsb5L0dknPt326qvGt75T089Pami0tLAz7PVYOT6KD+8tpy1ZMa9OPyUoS1iQOlEPTpGF7sn2QpCQEi7Lh5fcn+7+nvNyhHeWQPtsfKg8Tv+1QeZj8+w+V93//eDbcedk395WHkF+QFFRX3vNQMW39uvIQ+QtWJWFysqHnZ2Nf+Tylg8QvKA+9HyPltLR4n4ZISJYr9ePo7LQD3UFLKuagrpadeiCScHnqRVoWRiVLk/KyVVZeS0IeaseOYtLB+8vLPXhf+V5+745yWW1LEoJw68FyuWph8vV2/KJyEX58W/lcLFlSLjuMHlt+HHDBmp3FNO/ZXUyLlfuKae1Cbzorc2eFj+xaxLwzndGMXzvF5Et7kBcAAGaAAZswN1F2AoD+mM1oxgAAAAAADERHz8wCADAX8MwsAADDi8osAKCZLJ6ZBQBgiFGZBQA0Fi2zAAAMLyqzAIDmomUWAIChNXcqs1lYlwVJNrNhvZPh3ONQOTSNsrRMKezQhGSI8dhVHibey5YV0w7vLQ8Ff+/mZAj5g+XjtjkZJj4Lv5OljSXDpC9JCqObDpTDBB39QDn00Ipb7y2mrV5RPp6xohzqycuTYf6XLC2nSdLhZHj5bNEsnNOBZLj7FauSvJSPaSRpLn5dMAQ+ACCThVFpF5qns3Jeeo/cWw7pM7arnLbrofL2to+V75/f3Z+F5invfxaa52BySJeNlMd3PXZ3eR+Ofqh8zBYkx0wHk3Lz4eT8paF31HkoqE7XmV2n9AKas+ZOZRYAgJkwoXkAABhmVGYBAI1luhkDADC0qMwCAJqLllkAAIZWuVM9AABz2URonm6/sk3aG2xfZ/s227fafnM9fbXta21/u/67qp5u2++zfYftm20/s/cHBgCA4UBlFgCA6RuTdGFEnCbpLEnn2z5N0lslfS4iTpX0ufq9JL1c0qn16zxJH+h/lgEAmJ+ozAIAGst211+ZiNgSEV+t/98t6XZJ6ySdLenyerbLJb2q/v9sSR+OyvWSVto+oQeHAgCAodPfZ2YjysN3HyqHmEmNJ0O6Z2kjCzrb3mwk23QyjHocSoY1zzaXdJc7nAxNnoXY2XO4fEz3HC4vF8lw57uTkdnHklHS1yfhbg4mQ91HMny+sxA6mf1JCABJWpBcb1nIpiTNY9lQ+OV9zEJdOQuRUFqOZxYxMO27Bfd06/bJks6Q9CVJayNiS510n6S19f/rJN3TstimetoWAWgvuy9loV2ykI9J+TDGymmHkzLQoQ7LVQeS/TsY5e+3fck+ZHkZS/Yvkv1Ly9RZ2Slbrl14nU7D72CoMAAUAKC5evNjyhrbN7S8vyQiLjlys14u6ROSLoiIh1pbdCMibFMKAwCgx6jMAgBwpG0RsbGUaHtUVUX2IxFxVT35ftsnRMSWuhvx1nr6ZkkbWhZfX08DAACzxDOzAIBmsqqW2W6/sk1WTbCXSro9It7TknS1pHPq/8+R9OmW6a+vRzU+S9Kulu7IAABgFmiZBQA0V/+f2X6upNdJusX2TfW0iyS9S9KVts+VdJekV9dp10h6haQ7JO2V9Ia+5hYAgHmMyiwAoKEsJYPn9UJEfLHa8JReNMX8Ien8nmYKAIAhRWUWANBcjKYNAMDQ6m9ldvywtH/P1GnZ0OtLlpfTxg7OLk9TGenssHh0UZoeWXiWJUvLaUloHi8q53V0YbnFYnGHrRmdht/pVDacfS94yZLOFszOrSQtLV/DXpyc+yyE1MLFSX6SazhLyz6HC0vXN5UJAEBmFveJrEyW3iOT5UZHy6tcXF5u8aLy9pbsL5erjllQTksiCaaRx7J1Lk0WXJLs38ji8nHJjll6rLPyUbsfI3vxYyU/gM47tMwCAJppYgAoAAAwlKjMAgCai8osAABDi8osAKCh+j8AFAAAmDuozAIAmouWWQAAhhY/aQMAAAAAGoeWWQBAMzEAFAAAQ62/ldkYVxzYO2WSFyUhURYmw4Ef2t9RVpw8ZxVZiJ1ylJx8iHhJykKwJKF5nA1rvnJlMWnN2qOKacdv31dMe/ziw8W0PYfLY8jvTsL2ZJwM2f+kJeVLdO2i8nVx9PHlfffRR5czk537o5IQUe3O/Xj5mKayc98uHFBJEs4qDpSvCx0qLDeexBUAeo3KLDA3ZJ/FNK1NJ8Es7EtWdly6rJx2VLmMMLq6fK9ftWp3Me34feUC4ngSunD1aPkeujA5bCuTMsBxSflo5cpyOWfhys6OWRpeMg0jmJTvpfza6PR6S7fH/aSJ2nYztr3B9nW2b7N9q+0319NX277W9rfrv6t6n10AACbUA0B1+wXMEmUnAOiP6dy1xyRdGBGnSTpL0vm2T5P0Vkmfi4hTJX2ufg8AQP/Y3X8Bs0fZCQD6oG1lNiK2RMRX6/93S7pd0jpJZ0u6vJ7tckmv6lEeAQAAGoOyEwD0x4yembV9sqQzJH1J0tqI2FIn3SdpbWGZ8ySdJ0knnfi4jjMKAMARGAAKDTDrstOGDX3IJQA007QfDrK9XNInJF0QEQ+1pkVESFM/3R4Rl0TExojYeNzqlbPJKwAAR6KbMeawrpSd1hzbh5wCQDNNq2XW9qiqL+OPRMRV9eT7bZ8QEVtsnyBpa68yCQDAZJbTkemBQaLsBAC917Yya9uSLpV0e0S8pyXpaknnSHpX/ffTbbfmEXlxYdjvrEByuMOwJmkhp5yW/S7fWfCZWhaaZ8Ux5bT9SbiUNWuKSUtPOb6YdsrecngW3fVQMSkbJv6uA2PFtD1J2J6nH1UeJn794nLaU09ZWUxbesqUPbcqxyTHOlMKTSPl51aS9u4pJkWyrLOQP9nn4nD5XJTCY0lS7OigXJWE+gF6jpZUzEFdLTv1gJPPTV7O6UH4nTah7TxaDu0SS5JwMUm5yqtXF9MWnrCzmHbM7nJ5bP14+cgtfbAcRnLvofK9PPt2W5GELjzuuHK5YulJ5Zb+kePLZUqvKh8zLU+OdRIiyVnoTSm/NtKQTtwXhsl0WmafK+l1km6xfVM97SJVX8RX2j5X0l2SXt2THAIAADQLZScA6IO2ldmI+KLKP3G8qLvZAQBgmhgACnMUZScA6I8ZjWYMAMCcQmUWAIChRWUWANBQbjM2AgAAmM8oBQAAAAAAGoeWWQBAc9HNGACAodXfyqwtLZj5JuPhneVVjpZDt6TDdmf5SJabVdieZcvLaQc6C83j0fKw5iMnrS+mrV5cXu4Z63cW006+88Fi2s5d5RAt+/aVQ8WsWFE+hyc8cVUxbelTTy6m6YQTiknZMUtlIZLaOX5dMclHJ8Pdl0JZSXIWDmh0SXm58lL5NVpCN08MCgNAAXNI8lnM7hML8tA8WlC+Z3vZ0cW0yO6tax5XTttfDqOzJMolvTVLy2WZY+4vhzw8uP9QMW0kOaSjy8v3+UVry2XKhRvKoQt94onlDR5bDveoFeWymrLwScm5lZRfN1kZP70vcM+Yb2iZBQA0F5VZAACGFpVZAEBDMQAUAADDjFIAAAAAAKBxaJkFADQX3YwBABhaVGYBAM3EAFAAAAw1KrMAgIbimVkAAIZZfyuzhw4qtt49ZZKPTYYDHyuHfNGi8tDkWXiSXmjbPpCEUoksJEqWdlx5eHmvSML9rN9QTFry8J5i2uKtW4tpx+/aVUyLsXJoHmctK+vL4YW8/qTyctkxO3y4nDaepC1JQuEsT461JK88rpx2VLJsOvR8h6EOlpSPjbOQVQsLYQdK04F+oGUW6KPk85Z9FrP71Uib0DzJPcZLk7AvRx9bTIqkXOkYL68zCe23aHn53rroxHJonmUHDpTzkh3TpUmZZOXK8jrXlMsjOr4c1lDHZuXNZHtJiEEtbBeaJ7k20rA93BeGCT9pAwAAAAAah27GAIDm4hd4AACGFpVZAEAzMQAUAABDjcosAKChGAAKAIBhRmUWANBctMwCADC0+EkbAAAAANA4/W2Z3b9X8a2bpk57VnkI9XRY78xIp7/YJ4dlPBmyPQtrIkkLFydpSXiT49eV0/aUw+GkYWay8DSHkiHrjyoPPR/bHywvd+hQOW3V6nJektBDWp0ML58dzwP7ymnJvqfhfpYmaW3WGwf3J8uVh+zXSPl6S0MLJMul1/Bo4frNQi4AvUbLLNBVWTiYyJdMkrJQcm3KTtn9bDwJwbhiVTk7yTojCweThALyqjXl5faUQ/M4K3dk0nCBR5fTjikfF60s74OPSdKWryyvs1R2kNqf+zRsU/bd31kIqTQUEuYsuhkDAJrJ4scUAACGGJVZAEBDeRY9cAAAQNPxkzYAAAAAoHFomQUANBfdjAEAGFpUZgEAzcWAHQAADC0qswCAZrKlEVpmAQAYVv2tzC5ZJp36tKnTsuG3szAr2ZDt+x8up2UhdjoUWRgVSdq3u5w2lgzNvjgZfj0LF5MN956F9NmfhK5JzpOXrygvl4UJWpmE5slCCD1wXzktCSGkY5NwP1nYnmzfjy6HlpIkjSbXcLbeLCxV9rnIZIX/rMtm6frOPoNAr9EyC8wRnYVDycOvSFowWk4bLQcLSr8ZVib3uuR+HUuTcs7KpIyXlS3GxsppmaxcsSQpOywr74OXlUP6OFlOi5IQSQuT89c2NE9ynvghE7W2V4LtDbavs32b7Vttv7mefrHtzbZvql+v6H12AQAYLNuX2d5q+xst0063fX19P7zB9pn1dNt+n+07bN9s+5mDyzn6hbITAPTHdFpmxyRdGBFftb1C0o22r63T3hsRv9+77AEAkBjMAFAfkvR+SR9umfZuSe+IiL+tKyjvlvR8SS+XdGr9erakD9R/Mb9RdgKAPmhbmY2ILZK21P/vtn27pHW9zhgAAG0NoJtxRHzB9smTJ0ua6KN3jKR76//PlvThiAhJ19teafuE+t6KeYqyEwD0x4x+0q5v3mdI+lI96U11t6nLbK8qLHNe3eXqhgd2JM9pAgAwExMDQHX7Ja2ZuG/Vr/OmkZsLJP2e7Xsk/b6kt9XT10m6p2W+TaJSM1RmXXba9mC/sgoAjTPtyqzt5ZI+IemCiHhIVVepJ0k6XdWvj38w1XIRcUlEbIyIjcetOmb2OQYAYILd/Ze0beK+Vb8umUZO/qukX4mIDZJ+RdKlvdxtNENXyk5r2gwwCABDbFqVWdujqr6MPxIRV0lSRNwfEYcjYlzSByWd2btsAgAwp50j6ar6/7/Uo/fEzZI2tMy3vp6GeY6yEwD0XttnZm1b1S/Mt0fEe1qmtz7z8yOSvjHV8kdubVQjx22YOi0b1juV1Mez8DvufjgRtwlRElmInSR0jbMQLMmQ9jGSDAWfyYbJX5G0rmehgLLQPO2G5e9EErLIS5OwPdk5SnjpUWl6jB3qaL0d6zT8DtA0c+d6vlfSD0j6vKQXSvp2Pf1qVd1Kr1A18NMunped/7padppDnDyjXg6SI83wqbZJiyZlhCxsTxoOqJwfZ+FistA8afidJHRjFoIwk4W8ycqNSTknLW+maR2G32lX/ku/3zsLBZVdw2im6Yxm/FxJr5N0i+2b6mkXSXqt7dNVfX/dKenne5A/AACmZksj/S+Y2P6YqpGK19jeJOntkt4o6Y9sL5S0X9LEc7bXSHqFpDsk7ZX0hr5nGINA2QkA+mA6oxl/UVP//HFN97MDAMAMDKBlNiJeW0j6j1PMG5LO722OMNdQdgKA/phOyywAAHMTXcYAABhac+ZhIwAAAAAApouWWQBAQ3kuDQAFAAD6jMosAKCZrIEMAAUAAOYGKrMAgObimVkAAIZWfyuzIwul5aumTstitGYxuLLlFiTdz9rEhC3KYtdmsbQkafGyYlJaHMtitC4ox+hyFoN2NIkXlsVhHUtiyXZq755yWodxX7M4szr62M7Wme37aJs4yQf3l9N6EWe3U5102aQyAQBDr2cxaDt9kiC7N2X3upFyWS6Nw7ooKQdkZc6sXJnuQxZHNylXJPuXlSk7jhebpbUrc2TpxJJFjZZZAEBz8cwsAABDi8osAKCZbJ6ZBQBgiFGZBQA0Fy2zAAAMLSqzAIDm4tkoAACGFj9pAwAAAAAah5ZZAEBDmW7GAAAMsf5WZu3y0N6Hx8rLjR9I0joMsZMNMd5p2J42vHC0vEmVw/bowN7u52XxynLieHIuDiXhaZIQQpGFF0rC77jT0DwJj3RW+I1sSP526+w0/E623vQ6zYazz0IS0GUTDWJxzQJN1/ZRgeye1eF60/tgcr8eT9KSMp4iCU6Uxy0qyw5bun+dlg86DLGTlo/anHvC72AaaJkFADQXLbMAAAwtKrMAgObi13kAAIYWP2kDAAAAABqHllkAQEO5/fPqAABg3qIyCwBoJotuxgAADDEqswCA5mIAKAAAhlZ/K7MxLh3YV04rycLvZMtlhZwsFFC2zk6XkxTZfiRDnvuoY9L1diLNS2akcP4kaawcQsmHk9A8mcVJyKJDWcimLExQdq0l+czSZhE+qdNQQen13WkBf7zTGAHAIJiWWaABsjAqkYWtqRZOErP7YIehebKyXBaeJt2PLDRPh/fd9Lhk+97hcUmX60FeRPgdTA8/aQMAAAAAGoduxgCA5mIAKAAAhhaVWQBAMzEAFAAAQ43KLACgocwAUAAADDFKAQAAAACAxqFlFgDQXHQzBgBgaLWtzNpeIukLkhbX8/9VRLzd9hMkXSHpWEk3SnpdRBxMVzY+Lh3sPITJ1BnssHE5GzTkcIdha9rwguRwZ/npdB+T5dJwMFn4oWS5OJgMWZ+E0Yl9e4ppaTF1pHw803VmQ+uPLi6nJeGF4uD+8nKSnIUY6vTcdzrwTZsQUkVjhY93p+sDuoFuxpiDulp2mudmE34lD2qTrTdZMstPp2F0Ol2uUx2H0UlX2vV1EnoH3TCdUsABSS+MiGdIOl3Sy2yfJel3Jb03Ik6RtEPSuT3LJQAAk9nSSA9ewOxRdgKAPmhbmY3KRDPXaP0KSS+U9Ff19MslvaoXGQQAoMgj3X8Bs0TZCQD6Y1p3bdsLbN8kaaukayX9u6SdETHRH3WTpHWFZc+zfYPtGx7Yvr0LWQYAAJjbulZ22vZgX/ILAE00rcpsRByOiNMlrZd0pqTvne4GIuKSiNgYERuPW726s1wCADAVu/svoAu6VnZac2yvsggAjTej0YwjYqft6yQ9R9JK2wvrXxjXS9rciwwCADA14sxi7qPsBAC907YUYPs42yvr/5dKerGk2yVdJ+m/1LOdI+nTPcojAABTst31FzBblJ0AoD+m0zJ7gqTLbS9QVfm9MiL+2vZtkq6w/VuSvibp0rZrssvhVLLwHqWQIJK0cFE5LQtdkoR16Vi7ECXZNrOwPYeSsC+dtkqMJ3lN9iOy5bKQN9m+P5Q8S52d3/FyqBwdSq6Zxcly2T5k2i2Xnd8mhN+RytdMv0MOABMsWmYxV3Wv7ISiTn986klIn05XOZcQYgcN1LZGFxE3SzpjiunfUfUMCAAAAGqUnQCgP3rQPAkAQD/wzCwAAMOMyiwAoLlG6N4GAMCwojILAGguWmYBABhaVGYBAM1kERcWAIAhxk/aAAAAAIDG6W/LrC0tXjp12tih4mJxsByaxlnIkywcTPacVSR1/Gx7WdgaKQ8zs6Ac2iUe2tbROp2Fdcm65mVhXbJwOAf2ltOyUDn795WzcqCclsrymfDC0SQ1S2sju24ynXah7DTUVYchm4DBYAAoADPXm5A+zUeIHTQR3YwBAM1F4QsAgKFFZRYA0Fy0zAIAMLSozAIAmskmNA8AAEOMn7QBAJgB25fZ3mr7G5Om/5Ltb9q+1fa7W6a/zfYdtr9l+6X9zzEAAPMTLbMAgOYaTDfjD0l6v6QPP5IN+wWSzpb0jIg4YPv4evppkl4j6SmSTpT097afHBGdjVIHAAAeQcssAKC57O6/2oiIL0jaPmnyf5X0rog4UM+ztZ5+tqQrIuJARHxX0h2SzuzeAQAAYHj1t2V2/LC0Z8eMF0vD72S/yh8qh/RJw5NkOs1Lu/zsHyuv9pjjy8t1+rzY4aRRIMtnFrpl6Ypiko/q8HeT0SSc0eJl5e2NLi4v12nIokyvwtZk+UnPfTnUUxqyarx8HepwIY3RZDEwPQvNs8b2DS3vL4mIS9os82RJ32f7nZL2S/rViPiKpHWSrm+Zb1M9DUDDELoGmHvoZgwAwJG2RcTGGS6zUNJqSWdJepakK20/ses5AwAAj6AyCwBorrnTUrJJ0lUREZK+bHtc0hpJmyVtaJlvfT0NAADMEs/MAgCayaq6GXf71ZlPSXqBJNl+sqRFkrZJulrSa2wvtv0ESadK+vKs9x0AANAyCwBoKufPwPdqq/bHJD1f1bO1myS9XdJlki6rw/UclHRO3Up7q+0rJd0maUzS+YxkDABAd1CZBQA01iAGZImI1xaSfrow/zslvbN3OQIAYDjRzRgAAAAA0Dj9bZkdWSAtPbqQlvy63ovQC52uMwvNMxu9CS/Rde60S1+yf16TRKno9LgMoOthx7JwR+MdhpDqheK1P2cG4MEwash3JwAA6D66GQMAmsmaS6MZAwCAPqMyCwBoKNMyCwDAEKMyCwBoLlpmAQAYWvykDQAAAABoHFpmAQDN1aTB3gAAQFdRmQUANJNNN2MAAIZYXyuzN379lm0ja0++q367RtK2fm6/jbmUH/IyNfIytUHn5fED3DaGHQNAYZ678Ws3bfNRK+di2Wku5UWaW/khL1MjL4+i7NQlfa3MRsRxE//bviEiNvZz+5m5lB/yMjXyMrW5lBeg72iZxTw3V8tOcykv0tzKD3mZGnlBL/CTNgAAAACgcXhmFgDQYLTMAgAwrAZZmb1kgNueylzKD3mZGnmZ2lzKC9BHDACFoTOXvu/nUl6kuZUf8jI18oKuc0QMOg8AAMzYxqc/Nb5yzV92fb0jG067kWepAACY+3hmFgAAAADQODwzCwBoMLoZAwAwrAbSMmv7Zba/ZfsO228dRB5a8nKn7Vts32T7hgFs/zLbW21/o2XaatvX2v52/XfVAPNyse3N9fG5yfYr+pSXDbavs32b7Vttv7me3vdjk+Sl78fG9hLbX7b99Tov76inP8H2l+rP1MdtL+p1XoCBs6pnZrv9AuYgyk6PbHvOlJuS/AyifDBnyk1t8kPZCV3V98qs7QWS/kTSyyWdJum1tk/rdz4meUFEnD6gZ6Q+JOllk6a9VdLnIuJUSZ+r3w8qL5L03vr4nB4R1/QpL2OSLoyI0ySdJen8+joZxLEp5UXq/7E5IOmFEfEMSadLepntsyT9bp2XUyTtkHRuH/ICDJ578ALmGMpOR/iQ5k65qZQfqf/lg7lUbsryI1F2QhcNomX2TEl3RMR3IuKgpCsknT2AfMwJEfEFSdsnTT5b0uX1/5dLetUA8zIQEbElIr5a/79b0u2S1mkAxybJS99FZU/9drR+haQXSvqrenrfrhlg8KjNYihQdqrNpXJTkp++m0vlpjb56TvKTvPbICqz6yTd0/J+kwZ0cddC0mdt32j7vAHmo9XaiNhS/3+fpLWDzIykN9m+ue5K07euOxNsnyzpDElf0oCPzaS8SAM4NrYX2L5J0lZJ10r6d0k7I2KsnmXQnykAQHdRdsrNtXKTNMCy01wqN02RH4myE7qI0Yyl50XEM1V13Tnf9vcPOkOtooqdNMj4SR+Q9CRV3TK2SPqDfm7c9nJJn5B0QUQ81JrW72MzRV4Gcmwi4nBEnC5pvapf67+3H9sF5p4ePC/LM7PAdMzZstMcKDdJAyw7zaVyUyE/lJ3QVYOozG6WtKHl/fp62kBExOb671ZJn1R1gQ/a/bZPkKT679ZBZSQi7q+/AMYlfVB9PD62R1V9AX4kIq6qJw/k2EyVl0Eem3r7OyVdJ+k5klbanhidfKCfKaCvqMxiOFB2ys2ZcpM0uPLBXCo3lfJD2QndNojK7FcknVqPILZI0mskXT2AfMj2UbZXTPwv6SWSvpEv1RdXSzqn/v8cSZ8eVEYmvgBrP6I+HR/blnSppNsj4j0tSX0/NqW8DOLY2D7O9sr6/6WSXqzqOZTrJP2XeraBXjNAf/HMLIYCZafcnCk3SQMrH8yZclOWH8pO6La+x5mNiDHbb5L0GUkLJF0WEbf2Ox+1tZI+WX3etFDSRyPi7/qZAdsfk/R8SWtsb5L0dknvknSl7XMl3SXp1QPMy/Ntn66qW8qdkn6+H3mR9FxJr5N0S/2MgyRdpMEcm1JeXjuAY3OCpMvrkS1HJF0ZEX9t+zZJV9j+LUlfU3UDAeY/WlIxBCg7PWoulZuS/Ayi7DSXyk1Zfig7oatcdZ8HAKBZNj7jafGVz3b/h/SRxz3pxgGFagMAADPQ95ZZAAC6h5ZZAACGFZVZAEAzMWATAABDjcosAKC5qMwCADC0qMwCABqMyiwAAMNqEKF5AAAAAACYFVpmAQCNZboZAwAwtKjMAgCai8osAABDi8osAKChLJ6ZBQBgePHMLAAAAACgcWiZBQA0F92MAQAYWlRmAQDNZFGZBQBgiFGZBQA0GJVZAACGFZVZAEBz0TILAMDQYgAoAAAAAEDj0DILAGguGmYBABhaVGYBAA1FnFkAAIYZlVkAQHPxzCwAAEOLyiwAoJkIzQMAwFBjACgAAAAAQONQmQUANJh78GqzRfsy21ttf2OKtAtth+019Xvbfp/tO2zfbPuZs9xhAABQozILAGguu/uv9j4k6WWPzYo3SHqJpLtbJr9c0qn16zxJH5j1PgMAAElUZgEAjdWDiuw0KrMR8QVJ26dIeq+kt0iKlmlnS/pwVK6XtNL2Cd3YewAAhh2VWQBAg/Wkm/Ea2ze0vM5rmwv7bEmbI+Lrk5LWSbqn5f2mehoAAJglRjMGAOBI2yJi43Rntr1M0kWquhgDAIA+oTILAGikG79202e8fNWaHqx62wznf5KkJ0j6uqtuyuslfdX2mZI2S9rQMu/6ehoAAJglKrMAgEaKiMcMwjQIEXGLpOMn3tu+U9LGiNhm+2pJb7J9haRnS9oVEVsGk1MAAOYXnpkFAGAGbH9M0r9K+h7bm2yfm8x+jaTvSLpD0gcl/WIfsggAwFBwRLSfCwAAAACAOYSWWQAAAABA41CZBQAAAAA0DpVZAAAAAEDjUJkFAAAAADQOlVkAAAAAQONQmQUAAAAANA6VWQAAAABA4/x/m1H+VXOfsq8AAAAASUVORK5CYII= +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 3 con incertidumbre (Banda Rojo)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [831]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_R3</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata3</span><span class="p">,</span> <span class="n">poptR3</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR3</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR3</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR3</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR3</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteR3</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptR3E</span><span class="p">,</span> <span class="n">pcovR3E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata3</span><span class="p">,</span> <span class="n">recorteR3</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">8</span><span class="p">,</span><span class="mi">9</span><span class="p">,</span><span class="mi">4</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">Err_R3</span><span class="p">)</span> +<span class="n">estrellaR3E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata3</span><span class="p">,</span> <span class="n">poptR3E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR3E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR3E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR3E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR3E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMR3E</span><span class="o">=</span><span class="n">FWHMR_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptR3E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 3 fotografÃa (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteR3</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 3 a partir de la gaussiana con incertidumbre (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaR3E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 4 con incertidumbre (Banda Rojo)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [832]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_R4</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata4</span><span class="p">,</span> <span class="n">poptR4</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR4</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR4</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR4</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR4</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteR4</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptR4E</span><span class="p">,</span> <span class="n">pcovR4E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata4</span><span class="p">,</span> <span class="n">recorteR4</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span> <span class="n">sigma</span><span class="o">=</span><span class="n">Err_R4</span><span class="p">)</span> +<span class="n">estrellaR4E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata4</span><span class="p">,</span> <span class="n">poptR4E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR4E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR4E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR4E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR4E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMR4E</span><span class="o">=</span><span class="n">FWHMR_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptR4E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 4 fotografÃa (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteR4</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 4 a partir de la gaussiana con incertidumbre (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaR4E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img src="data:image/png;base64,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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 5 con incertidumbre (Banda Rojo)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [833]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_R5</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata5</span><span class="p">,</span> <span class="n">poptR5</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR5</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR5</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR5</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR5</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteR5</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptR5E</span><span class="p">,</span> <span class="n">pcovR5E</span><span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata5</span><span class="p">,</span> <span class="n">recorteR5</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">3</span><span class="p">,</span><span class="mi">3</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span> <span class="n">sigma</span><span class="o">=</span><span class="n">Err_R5</span><span class="p">)</span> +<span class="n">estrellaR5E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata5</span><span class="p">,</span> <span class="n">poptR5E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR5E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR5E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR5E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR5E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMR5E</span><span class="o">=</span><span class="n">FWHMR_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptR5E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 5 fotografÃa (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteR5</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 5 a partir de la gaussiana con incertidumbre (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaR5E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img src="data:image/png;base64,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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 6 con incertidumbre (Banda Rojo)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [834]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_R6</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata6</span><span class="p">,</span> <span class="n">poptR6</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR6</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR6</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR6</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR6</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteR6</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptR6E</span><span class="p">,</span> <span class="n">pcovR6E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata6</span><span class="p">,</span> <span class="n">recorteR6</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">2</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">Err_R6</span><span class="p">)</span> +<span class="n">estrellaR6E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata6</span><span class="p">,</span> <span class="n">poptR6E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR6E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR6E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR6E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR6E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMR6E</span><span class="o">=</span><span class="n">FWHMR_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptR6E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 6 fotografÃa (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteR6</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 6 a partir de la gaussiana con incertidumbre (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaR6E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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aQumOP5RE7ruTmYeovU8cap65WufFTzbi/HeG5V+tFIkmxvqdQFoFMZx1t+jSpdB3I3kPb7NNvLNpl1bXeU0tWYF+XPtro0dfr81UqVxDFFxL1KV+Bel8v/EqXK0BuVrgjOVfohdFO+NZIWVLrCSOmK31TLXi3nj5RanI/Pk9q/Eysd5Mf6Dkctm8t0a+WzC5S6h2zUow2AUrnHXYNz9+D5tpdVXoeNnbdnSzpL0pERcZ/SSXmeUve8v5J0RtsxA12YpufqEyX9StLOOe1jx0m7ZVHl7+qxvZu0JlNv6OYza6rlqZyXWlYqtYBWt/nmETHuY9dyN9GzlM5/2+Xz8rnqvG1G1UvayjRRWvcrtRC2lv+9asIR8fOIOFipW+V3lFpCFRHrIuKoiHi60i1E/9v2fmOUbSrfcctk9r2VSl0uxzJunaAmKyXN89j34K6U9PG2/WKLiKh2mW3f7ybaD7fOddWWal2s/TueodRNd2O0/w4f1egB16rlnczvYEUqojte2MkXw76nXI/VRtQ19eTf8BZK9f2WKe2/EfFYRHxG0kN6ojvxWPvheo2+YNBabp5Tl/fqstVj9bMl/WKicky7oNX2n/iJG5bvVtrRNuT3v1Xng0DLv0j6uPNN1ba3deq/PpE5St0P7s07Z8fHu+SrV9+SdLTtObm8h0n6bhf5SKnv/Dtt754P4J+QdGne8aUnr+d4y/+npOfafkNubTxcqStIT9a1w2cfVHpMyzylQS7Gc67SvQRjyhXKQ/TEaMVzlH40d0iaafvvlO576cbP8mc/YHuW7T9UuldkqmVvd4KkV9l+vtKJ8rW297M9S+kg9bBSd+R2p0n6m7wvzlfq/lF9XtnLJP0wIh6eZHmAoVHDQExrI2JJ5bW0Pc/82zxL0qkRcXaevErS2ZFcpnR+ma90Aq5WfBaq84XExpum5+o5Sret/M7270v6yy7K87e5ZWU3pXvUWveiTiWtbrbbeP5T0m62/zDXBz6g0fWBf5F0TC6rbG9l+0+6SHcTSZsqnZfXOw3u0z4QTtUZko6wvSAHSX89ibR+kddhd6exLI5rzbC9ie03294q0tMM7lPe55wGEnpmDtTvVWq136Anm8r3Uv1st3Wn70ra3vaRTgMvzbH9ojxvojpBz0XEGqXA6ktOAwXNst0Kpr4i6T22X+RkS9uvbQtS2nXcVyPiZknLJH0sf2d/oCcCOil10d8s5zFL6X7ejR2I8i1OYxZsodRV/Mzo/LiWrn8HEfGI0r3J49VjFyqNg1Ctx061rnmmpINs/4HTGCl/r9Gx3sbsv5L0KaXj4WZK++EHnQbNmq0UW3yrrZVfEbFSqW77SdubOQ3SdaieXI/93kSZD3PQ2hp1rPX6dp7+QkmX2v6d0iA7R0TEDXnecZL+1alJ/40d0v1c/tz5ttcpDfDzog7LVn1MacCAe5UO/GePv7jep3TwulUpWPqm0o3sE4qI/1K6J/Ispasqz1AK3FqOU2U9x1s+ItZK+hOle2nuVOrLv0wpgOrVuladIGlzpStYlygNMjCeUyQdaHvzyrQdWt+7UheDeZLenOedl9P8nzzvIXXZLSUfXP5Q6b6OuyT9qUav22TL3p7+HXl9/i4irle6yvrPOb3XKQ1K8MgYH/1Hpe/kaknXSLoiT2t5s9JBFJi2+j0QU668niRpeb7C3PIdpYEnWgOqbaL0Gz5H0iG5grmT0j06l/V0IwynJp2rP6Q0QMo6pYp8p8GQqn6k1BrzA0nHR8T5G5HWcZp4u3VUqQ98Sqk+sLOk/67M/7ak/yPpdKeuhb9UGjBponTXKQXAZyhdoPgzpe+uk68oDdJ1tdIgOucqXVB+bKK0Ig3++PdKgcKvJY0aSVhpgJqbcvnfoyfqDjvnz/xO6Xv+UkRcOEbZpvK9tHS97+X1fJVS3eC2vC6vyLMnqhPU5a1KLZC/UrpP9shc1mVKg2d9Qek7WaFUjxrPJ5UC73tcGTW74s+Ufs93KQVtp7Rm5B5271V6ssZqpZbXMQc6moR/U+oNd5vSUyM+0GnBKfwOvqy07ar+tFKP/bnS7+xjed4JmmJdMyKuVWp8+qZSff9ujd42G7P/Smm/vVvp+z5Zabv9WNKNSvXt93f43JuU7nO9VdK3JX00xybKAfCBqtzm10nrZlpAUhrCWmkHf3OHA3bf2f6EpNsj4oRBl6VfnIZWf0tE/HiC5Z4n6csRsfd4ywHD7GkzZsZfbz63p2m+7/47L4+IJZ3m56v7P1GqFLZaXI5VqtierDQ4xiOSPhQRrccgfERpBMr1St2JJ7xyjGZyuk/6Rkmz2lsmMFpuTf2XiNhxwoWBAtn+b6Wnalw56LL0g+2nKzUezYoJAk3b75e0KCKOnijdoX7IL3rD6XmClyp1R/grpf7tl4z7oT6KiGMHXYZ+sr2t0v0ZN020bERcrTRsOTBtWf3vFhQRF6vzvT5v6fCZjys9FgzAFOWeVa9Qam3dTqml7dvjfggoWETsM/FS08pzJN08UcAqSRHxz90mOszdg9E7eyuNUtfqpvqGiHhw/I+gDk4jkf5a0j9HxC2DLg9QigE8pxXAYFipq+TdSt2DlyvdtwmgcLb/t9LjzMYcgXuj0qZ7MACgZItnzIqPbDG3p2ke9ru143YPBgAA5aB7MACgeLSOAgDQXHQPBgAAAAAUq5aW1vnzto7FC3eoI+knuOZ4O8Z6PFePrX+0/jxGZtSb/oya05ekDZ0elTVkRmru2DBS72/ipltWau2dd9HehYFgx8N0Nn/+NrH4aU8bdDEA9NjlV161NiK2HXQ5poNaatGLF+6gy845rY6kH+fNZteafjz0u1rTlyTd/dv689h8vGc7bzzP2brW9CUpHriv9jz6wVvOrTeDzev9Tbxw3/1rTR/oxKJ7MKa3xU97mpZdfNGgiwGgx7zl3JsHXYbpgntaAQDFG6GtFQCAxuKeVgAAAABAsWhpBQAUzTxbFQCARiNoBQAUj25BAAA0F0ErAKB4NLQCANBcBK0AgKKl0YMJWwEAaCp6XAEAAAAAitVV0Gp7f9vX215h+8N1FwoAgCr3+AXUjboTAPTOhEGr7RmSvijpAEm7SnqT7V3rLhgAAC0ErRgm1J0AoLe6aWndU9KKiLghIh6RdLqkg+stFgAATyBoxZCh7gQAPdRN0LpA0srK+1V52ii2D7O9zPayO+68u1flAwBAtnv6Amo2Yd1pVL1p7Z19LRwADJueDcQUEUsjYklELNl2m617lSwAAMC0M6reNH+bQRcHAIrWzSNvVktaVHm/ME8DAKB2dOnFEKLuBAA91E1L688l7Wx7J9ubSDpE0jn1FgsAgCeM9PgF1Iy6EwD00IQtrRGx3vb7JJ0naYakkyPi2tpLBgBAxm2oGCbUnQCgt7rpHqyIOFfSuTWXBQCAMZkOwhgy1J0AoHfoJQUAAAAAKFZXLa0AAAwKAzEBANBsBK0AgOIRtAIA0FwErQCA4o0QtQIA0Fjc0woAAAAAKBYtrQCAwpnRgwEAaLB6glaPyJvNriXplrjn9lrT74vNtqw/j002rTf92FBv+pI8e+va89CGx+rPo+YHTca9d9Savh5bX2/6QAcMxARAkiKi/kzqPtc99mi96Uv9ebD1zE1qz8IjM2rPA8ODllYAQNncnzoYAAAoE0ErAKB4xKwAADQXAzEBAAAAAIpFSysAoHgjtLUCANBYBK0AgKIxEBMAAM1G0AoAKB4DMQEA0Fzc0woAKJ57/JowP3uR7QttX2f7WttHtM0/ynbYnp/f2/bnba+wfbXtF2z8WgMAAImWVgAAxrJe0lERcYXtOZIut31BRFxne5GkV0u6pbL8AZJ2zq8XSTox/w8AADYSLa0AgOK5x/8mEhFrIuKK/Pc6ScslLcizPyvpaElR+cjBkk6J5BJJc21v39ONAABAQ9HSCgAomiWN9P6e1vm2l1XeL42IpWPmby+WtIekS20fLGl1RPzCo2+0XSBpZeX9qjxtTU9LDQBAAxG0AgCKV8M4TGsjYsmE+dqzJZ0l6UilLsPHKnUNBgAAfULQCgAo3iAGD7Y9SylgPTUizrb9XEk7SWq1si6UdIXtPSWtlrSo8vGFeRoAANhI3NMKAEAbp6j0JEnLI+IzkhQR10TEUyNicUQsVuoC/IKIuE3SOZLelkcR3kvSvRFB12AAAHqAllYAQPG6GTypx/aR9FZJ19i+Kk87NiLO7bD8uZIOlLRC0gOS3ll7CQEAaAiCVgBA8dznmDUiLtYEvZJza2vr75B0eM3FAgCgkQhaAQBFs7iXBQCAJqMeAAAAAAAoFi2tAIDiDWL0YAAAUAaCVgBA8dzvm1oBAEAxCFoBAMUjZAUAoLkIWgEARbMIWgEAaDIGYgIAAAAAFIuWVgBA2WzuaQUAoMGGNmj1nK1rTT8efqDW9FMmUX8Wv7m61vQ3/PD7taYvSdp889qz8L6vrT2PkZ2eU28Gj62vN/0+7K9AJyPErADWP1J7FnHn6nrT/9WyWtOXJG0xu/YsRnZZUnseMWderel7xtCGQY3EtwUAKJ6JWgEAaCyCVgBA0SyJ3sEAADQXAzEBAAAAAIpFSysAoGympRUAgCYjaAUAFI/RgwEAaC6CVgBA8YhZAQBoLoJWAEDxaGkFAKC5GIgJAAAAAFAsWloBAEXjkTcAADTbhC2tthfZvtD2dbavtX1EPwoGAIAkydKI3dMXUCfqTgDQW920tK6XdFREXGF7jqTLbV8QEdfVXDYAACTR0oqhQ90JAHpowqA1ItZIWpP/Xmd7uaQFkjjwAgD6wAzEhKFC3QkAemtSAzHZXixpD0mX1lIaAACAaYS6EwBsvK4HYrI9W9JZko6MiPvGmH+YpMMk6WkLduhZAQEAzWZJZqx7DKHx6k6j6k2LFg2gdAAwPLqqBtiepXTQPTUizh5rmYhYGhFLImLJttvM62UZAQBN5vSc1l6+gLpNVHcaVW+av03/CwgAQ2TCllans/tJkpZHxGfqLxIAAKMRZ2KYUHcCgN7qpqV1H0lvlbSv7avy68CaywUAADCsqDsBQA91M3rwxUq3FAEAMBB06cUwoe4EAL3V9UBMAAAMCjErAADNRdAKACiaJY0QtQIA0FgErQCAspmWVgAAmown3wEAAAAAikVLKwCgeAzEBABAcxG0AgCKR8wKAEBz1Re0xobakpYkPfZorcnH3b+tNX1J8qzNas8j/vvCWtP/pxPOqzV9SVq8af3XVv5426fWnoee8fxak/dmW9aavka4mwCDYRG0AqWLDTXX+yTpwXW1Z7HhO1+rNf2ffursWtOXpAXbbF57Hov/6eja8xjZ67X1ZjCDtrthQi0UAFA2Wx7p7WviLL3I9oW2r7N9re0j8vT/a/tXtq+2/W3bcyufOcb2CtvX235NfRsEAIBmIWgFAODJ1ks6KiJ2lbSXpMNt7yrpAknPiYjnSfofScdIUp53iKTdJO0v6Uu2Zwyk5AAATDMErQCA4tm9fU0kItZExBX573WSlktaEBHnR8T6vNglkhbmvw+WdHpEPBwRN0paIWnPXm8HAACaiM7cAIDijQzwplbbiyXtIenStlnvkvSt/PcCpSC2ZVWeBgAANhJBKwCgaDUNxDTf9rLK+6URsfRJeduzJZ0l6ciIuK8y/SNKXYhP7XnJAADAKAStAIDi1fCc1rURsWSCPGcpBaynRsTZlenvkHSQpP0iIvLk1ZIWVT6+ME8DAAAbiXtaAQBo4xQlnyRpeUR8pjJ9f0lHS3p9RDxQ+cg5kg6xvantnSTtLOmyfpYZAIDpipZWAEDZuhw8qcf2kfRWSdfYvipPO1bS5yVtKumC3Pp7SUS8JyKutX2GpOuUug0fHhGP9b3UAABMQwStAIDi1dA9eFwRcbHS7bTtzh3nMx+X9PHaCgUAQEMRtAIAijfAwYMBAMCAcU8rAAAAAKBYtLQCAIqWHnlDUysAAE1F0AoAKJsl0y8IAIDGImgFABTOtLQCANBgBK0AgPKNELQCANBUdLgCAAAAABSLllYAQPnoHgwAQGMRtAIAymZGDwYAoMkIWgEA5eOeVgAAGougFQBQONM9GACABmMgJgAAAABAsWhpBQAUzZZM92AAABqLoBUAUD66BwMA0FgErQCA4tHSCgBAcw1t0Bp3/bbeDFb8st70JcU229Wex/obVtaa/o0PPVpr+v3K448efqj2PBRRb/qzNq03fXMLPAaIllYAjz5cfx6/+U2tyX/zjntrTV+S9nqo/u20+NZ665eSpA3ra00+6q6XoaeohQIAAAAAijW0La0AgIaweU4rAAANRtAKACie6R4MAEBjEbQCAMpHSysAAI3FPa0AAAAAgGLR0goAKJvF6MEAADQYQSsAoHg8cQkAgOYiaAUAlI+WVgAAGqvroNX2DEnLJK2OiIPqKxIAABW2zEBMGELUnQCgNybT4eoIScvrKggAAMA0Q90JAHqgq6DV9kJJr5X01XqLAwDAGOzevoCaUXcCgN7ptnvwCZKOljSnvqIAANAB3YMxfE4QdScA6IkJW1ptHyTp9oi4fILlDrO9zPayO+68q2cFBAA0W2ocdU9fQJ26qTuNqjetvbOPpQOA4dNN9+B9JL3e9k2STpe0r+1vtC8UEUsjYklELNl2m3k9LiYAoNFG3NsXUK8J606j6k3ztxlEGQFgaEwYtEbEMRGxMCIWSzpE0g8j4i21lwwAAGAIUXcCgN7iOa0AgMIxeBIAAE02qaA1Ii6SdFEtJQEAoAPuQ8Wwou4EABuPllYAQNks7kMFAKDBunpOKwAAg9Tv0YNtL7J9oe3rbF9r+4g8fZ7tC2z/Ov+/dZ5u25+3vcL21bZfUPMmAQCgMQhaAQB4svWSjoqIXSXtJelw27tK+rCkH0TEzpJ+kN9L0gGSds6vwySd2P8iAwAwPRG0AgDK1+dH3kTEmoi4Iv+9TtJySQskHSzpX/Ni/yrpDfnvgyWdEsklkuba3r7HWwEAgEbinlYAQNk82NGDbS+WtIekSyVtFxFr8qzbJG2X/14gaWXlY6vytDUCAAAbhaAVAFA8934gpvm2l1XeL42IpU/K154t6SxJR0bEfdX7YSMibEevCwYAAEarL2h1vT2PPW+7iRfaCH2phcSG2rOY+dzfrzX9V2/9y1rTl6RdnrJF7Xn42c+rPY+47856M9is5u204bF60wf6a21ELBlvAduzlALWUyPi7Dz5t7a3j4g1ufvv7Xn6akmLKh9fmKcBzdCP3hCbz649C7/6wFrT/6c199SaviRtuv3c2vPQHi+uP4+Zm9aaPI9SGy7c0woAKF+ri3CvXhNmZ0s6SdLyiPhMZdY5kt6e/367pP+oTH9bHkV4L0n3VroRAwCAjUD3YABA2QbznNZ9JL1V0jW2r8rTjpX0KUln2D5U0s2S3pjnnSvpQEkrJD0g6Z19LS0AANMYQSsAoHj97sYVERcrhctj2W+M5UPS4bUWCgCAhiJoBQAUrrvH1AAAgOmJe1oBAAAAAMWipRUAUD5GeQQAoLEIWgEAZbMIWgEAaDCCVgBA+QhaAQBoLIJWAEDhLI0wBAMAAE1FLQAAAAAAUCxaWgEA5aN7MAAAjUXQCgAoGwMxAQDQaAStAIDyEbQCANBYBK0AgMIxEBMAAE1GLQAAAAAAUCxaWgEA5aN7MAAAjUXQCgAoGwMxAQDQaAStAIDyEbQCANBYBK0AgMIxEBMAAE1GLQAAAAAAUCxaWgEA5aN7MAAAjUXQCgAoGwMxAQDQaAStAIDyEbQCANBY3NMKAAAAAChWPS2trn+kR89fVGv62unZ9aYvyXO2rj+PRc+qNf2Dt92u1vQlSQt3qj2Lkd32rj2P+O3N9WbwyEP1pv/Y+nrTBzqwLDN6MFA096E3RGw2u/Y8RvY+qNb0N9/tRbWmL0metWnteWjOvPrzmLlJ/XlgaNA9GABQProHAwDQWAStAICyMRATAACNRtAKACgfQSsAAI3FTUIAAAAAgGLR0goAKFz9g/sBAIByEbQCAMpH92AAABqLoBUAUDYGYgIAoNEIWgEA5SNoBQCgsbq6Scj2XNtn2v6V7eW29667YAAAAMOKuhMA9E63La2fk/T9iPhj25tI2qLGMgEAUMFATBhK1J0AoEcmDFptbyXppZLeIUkR8YikR+otFgAAFXQPxhCh7gQAvdXNpeudJN0h6Wu2r7T9Vdtb1lwuAACS1kBMvXwB9aLuBAA91E3QOlPSCySdGBF7SLpf0ofbF7J9mO1ltpfdceedPS4mAKC5cvfgXr6Aek1YdxpVb1pLvQkAxtPNmXuVpFURcWl+f6bSgXiUiFgaEUsiYsm222zTyzICANBXtk+2fbvtX1am7W77EttX5WBjzzzdtj9ve4Xtq20/6RyJxpmw7jSq3jSfehMAjGfCoDUibpO00vaz8qT9JF1Xa6kAAKjqf/fgr0vav23apyV9LCJ2l/R3+b0kHSBp5/w6TNKJvVhlDC/qTgDQW92OHvx+Safm0e9ukPTO+ooEAECbPt+HGhE/tr24fbKkp+S/t5J0a/77YEmnRERIuiQ/6mT7iFjTn9KiUNSdAKBHugpaI+IqSUvqLQoAAGNoDcTUW/NtL6u8XxoRSyf4zJGSzrN9vFJPpRfn6QskrawstypPI2htMOpOANA73ba0AgAwnayNiMkGFH8p6YMRcZbtN0o6SdIre180AABQRdAKACicSxnx9+2Sjsh//7ukr+a/V0taVFluYZ4GAAB6oIhaAAAA4yrjOa23SnpZ/ntfSb/Of58j6W15FOG9JN3L/awAAPQOLa0AgPL1eSAm26dJernSva+rJH1U0rslfc72TEkPKY0ULEnnSjpQ0gpJD4gBdwAA6CmCVgBA2SzJ/e0YFBFv6jDrf42xbEg6vN4SAQDQXHQPBgAAAAAUi5ZWAEDhLI30t3swAAAoR41Ba70VjHjo/lrT91MXTbzQxuaxyea156FN683Dr+7Ug66HRmbUn8esTWrPwvO2qzX9ePjBWtMvZPRWNFWfuwcDKI/7UB+ILbeqNX1vMafW9PumD8dk93ksA5SNllYAQPmovAAA0FgErQCAsrmY57QCAIABoBYAAAAAACgWLa0AgPLRPRgAgMYiaAUAlI+BmAAAaCyCVgBA+WhpBQCgsQhaAQBlYyAmAAAajVoAAAAAAKBYtLQCAMpH92AAABqLoBUAUD4GYgIAoLEIWgEAZbOlEVpaAQBoKi5dAwAAAACKRUsrAKB8dA8GAKCxCFoBAOVjICYAABqLoBUAUDjT0goAQIMRtAIAymYxEBMAAA3GpWsAAAAAQLFoaQUAlI97WgEAaCyCVgBA+binFQCAxiJoBQCUzeaeVgAAGoygFQBQPlpaAQBoLGoBAAAAAIBi0dIKACgfAzEBANBYBK0AgMKZ7sEAADRYfUFrzYNmbPjlxbWm720X1pq+JGnmrPrzuP+eWpOP+++rNX1J0sMP1p/H3G1rz8JPmV9v+jPW1Zq+RmbUmz7QicVATAD6wnX36jDnUmAqaGkFAJSPllYAABqLWgAAAAAAoFi0tAIAysdATAAANBZBKwCgcJZG6BgEAEBTEbQCAMpm0dIKAECDcekaAAAAAFAsglYAQPk80tvXRNnZJ9u+3fYv26a/3/avbF9r+9OV6cfYXmH7etuvqWELAADQWHQPBgAUzoPoHvx1SV+QdMrjpbBfIelgSc+PiIdtPzVP31XSIZJ2k7SDpP+yvUtEPNbvQgMAMB111dJq+4P5qvIvbZ9me7O6CwYAwONGRnr7mkBE/FjSXW2T/1LSpyLi4bzM7Xn6wZJOj4iHI+JGSSsk7dm7lccwou4EAL0z4Znb9gJJH5C0JCKeI2mG0hVlAADq1xqIqZcvab7tZZXXYV2UZBdJL7F9qe0f2X5hnr5A0srKcqvyNDQUdScA6K1uuwfPlLS57UclbSHp1vqKBABA7dZGxJJJfmampHmS9pL0Qkln2H56z0uG6YK6EwD0yIQtrRGxWtLxkm6RtEbSvRFxfvtytg9rXbG+4872HlUAAEyV+z4QUwerJJ0dyWWSNkiaL2m1pEWV5RbmaWiobupOo+pNa+8cRDEBYGh00z14a6X7dXZSGmBiS9tvaV8uIpZGxJKIWLLtNvN6X1IAQHP1vnvwVHxH0itScbyLpE0krZV0jqRDbG9qeydJO0u6bONXGsOqm7rTqHrT/G0GUUwAGBrdXG5+paQbI+KOiHhU0tmSXlxvsQAAqOj/I29Ok/QzSc+yvcr2oZJOlvT0/Bic0yW9Pbe6XivpDEnXSfq+pMMZObjxqDsBQA91c0/rLZL2sr2FpAcl7SdpWa2lAgCgxZZG+vvIm4h4U4dZT+pplJf/uKSP11ciDBnqTgDQQ93c03qppDMlXSHpmvyZpTWXCwAAYChRdwKA3upq9OCI+Kikj9ZcFgAAxjb1wZOAgaDuBAC90+0jbwAAGJypD54EAACGHEErAKBwpqUVAIAGI2gFABTPtLQCANBYXLoGAAAAABSLllYAQNksugcDANBgBK0AgMJxTysAAE1WX9C6YUNtSUuSVt5Qa/JRa+rZppvXnoVnzqo9j9qNzKg9C8/atPY8+rEewLQ1wj2tAAA0FS2tAIDy0dIKAEBjUQsAAAAAABSLllYAQNksiUfeAADQWAStAIDCMRATAABNRtAKACgfLa0AADQWl64BAAAAAMWipRUAUD66BwMA0FgErQCAstk8pxUAgAYjaAUAlI+WVgAAGougFQBQPgZiAgCgsbh0DQAAAAAoFi2tAIDC8ZxWAACajKAVAFA+ugcDANBYBK0AgLJZtLQCANBgBK0AgMJZGiFoBQCgqagFAAAAAACKRUsrAKB45p5WAAAai6AVAFA+7mkFAKCxCFoBAGWzGD0YAIAGI2gFABSO57QCANBk1AIAAAAAAMWipRUAUD66BwMA0FgErQCA8vGcVgAAGougFQBQNpuWVgAAGqyWoPXyX1yzdmS7nW6exEfmS1pbR1n6iHUox3RYjxLXYcdBFwAApqPLr7xqrbecO5l6k1TmeWKyWIcyTId1kMpcD+pOPVJL0BoR205medvLImJJHWXpF9ahHNNhPabDOgA91efRg22fLOkgSbdHxHPa5h0l6XhJ20bEWtuW9DlJB0p6QNI7IuKKvhYYQ22y9SZpepwnWIcyTId1kKbPemBs3CQEAChfq4twr14T+7qk/Z9cDC+S9GpJt1QmHyBp5/w6TNKJG72+AADgcQStAIAh4B6/xhcRP5Z01xizPivpaElRmXawpFMiuUTSXNvbT3oVAQDAmEoZiGnpoAvQA6xDOabDekyHdQB6pIyBmGwfLGl1RPzCo8uzQNLKyvtVedqaPhYPzTMdzhOsQxmmwzpI02c9MIYigtaIGPqdjHUox3RYj+mwDkDh5tteVnm/dLzfne0tJB2r1DUYGLjpcJ5gHcowHdZBmj7rgbEVEbQCADCu3re0rp3kgB3PkLSTpFYr60JJV9jeU9JqSYsqyy7M0wAAQA9wTysAYAj0957WdhFxTUQ8NSIWR8RipS7AL4iI2ySdI+ltTvaSdG9E0DUYAIAeGWjQant/29fbXmH7w4Msy1TZXmT7QtvX2b7W9hGDLtNU2Z5h+0rb3x10WabC9lzbZ9r+le3ltvcedJkmy/YH8370S9un2d5s0GUCBs7q++jBtk+T9DNJz7K9yvah4yx+rqQbJK2Q9BVJ7+3BWgNjou5UjmGvN0nUnTA8BtY92PYMSV+U9CqlK9Y/t31ORFw3qDJN0XpJR0XEFbbnSLrc9gVDuB6SdISk5ZKeMuiCTNHnJH0/Iv7Y9iaSthh0gSbD9gJJH5C0a0Q8aPsMSYcoPXoDaLY+j8MUEW+aYP7iyt8h6fC6ywRQdyrOsNebJOpOGBKDbGndU9KKiLghIh6RdLrSYwOGSkSsaT1EPiLWKR28Fgy2VJNne6Gk10r66qDLMhW2t5L0UkknSVJEPBIR9wy0UFMzU9LmtmcqnThuHXB5AADloO5UiGGvN0nUnTBcBhm0dnpEwNCyvVjSHpIuHXBRpuIEpWcPbhhwOaZqJ0l3SPpa7qrzVdtbDrpQkxERqyUdL+kWpUdl3BsR5w+2VEApBntPK1AI6k7lOEHDXW+SqDthiDAQU4/Yni3pLElHRsR9gy7PZNg+SNLtEXH5oMuyEWZKeoGkEyNiD0n3Sxqqe31sb610xXwnSTtI2tL2WwZbKqAEPb6ftYBnvgIY3rrTNKk3SdSdMEQGGbROm0cE2J6ldNA9NSLOHnR5pmAfSa+3fZNSV6N9bX9jsEWatFWSVkVE60rtmUoH4mHySkk3RsQdEfGopLMlvXjAZQLKQNAKSNSdSjEd6k0SdScMkUEGrT+XtLPtnfKN34coPTZgqDg9sO8kScsj4jODLs9URMQxEbEwDyxyiKQfRsRQXaXKj51YaftZedJ+koZtQIdbJO1le4u8X+2ndJ8PALoHAxJ1pyJMh3qTRN0Jw2VgowdHxHrb75N0nqQZkk6OiGsHVZ6NsI+kt0q6xvZVedqxEXHu4IrUWO+XdGo+kd8g6Z0DLs+kRMSlts+UdIXSyIpXSlo62FIBAEpB3Qk1oO6EoeA0Uj8AAGVa8vznxs/P/4+epjnye8+4PCKW9DRRAABQi4G1tAIA0D269AIA0FQErQCAsjF4EgAAjcYjbwAAAAAAxaKlFQBQPlpaAQBoLIJWAMAQIGgFAKCpCFoBAMUzLa0AADQWQSsAoHwErQAANBYDMQEAAAAAikVLKwCgcBb3tAIA0FwErQCA8tE9GACAxiJoBQCUzSJoBQCgwQhaAQBDgKAVAICmYiAmAAAAAECxaGkFAJSP7sEAADQWQSsAoHzErAAANBZBKwCgcDzyBgCAJiNoBQCUj+7BAAA0FgMxAQAAAACKRUsrAKBsPKcVAIBGI2gFAAwBglYAAJqKoBUAUD5aWgEAaCzuaQUAAAAAFIuWVgBA4UxLKwAADUbQCgAYAgStAAA0FUErAKB8tLQCANBYjohBlwEAgI5sf1/S/B4nuzYi9u9xmgAAoAYErQAAAACAYjF6MAAAAACgWAStAAAAAIBiEbQCAAAAAIpF0AoAAAAAKBZBKwAAAACgWP8fx3Owk4VmHvMAAAAASUVORK5CYII= +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 7 con incertidumbre (Banda Rojo)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [835]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_R7</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata7</span><span class="p">,</span> <span class="n">poptR7</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR7</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR7</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR7</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR7</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteR7</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptR7E</span><span class="p">,</span> <span class="n">pcovR7E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata7</span><span class="p">,</span> <span class="n">recorteR7</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">2</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">Err_R7</span><span class="p">)</span> +<span class="n">estrellaR7E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata7</span><span class="p">,</span> <span class="n">poptR7E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR7E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR7E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR7E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR7E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMR7E</span><span class="o">=</span><span class="n">FWHMR_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptR7E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 7 fotografÃa (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteR7</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 7 a partir de la gaussiana con incertidumbre (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaR7E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 8 con incertidumbre (Banda Rojo)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [836]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_R8</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata8</span><span class="p">,</span> <span class="n">poptR8</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR8</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR8</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR8</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR8</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteR8</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptR8E</span><span class="p">,</span> <span class="n">pcovR8E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata8</span><span class="p">,</span> <span class="n">recorteR8</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">Err_R8</span><span class="p">)</span> +<span class="n">estrellaR8E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata8</span><span class="p">,</span> <span class="n">poptR8E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR8E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR8E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR8E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR8E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMR8E</span><span class="o">=</span><span class="n">FWHMR_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptR8E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 8 fotografÃa (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteR8</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 8 a partir de la gaussiana con incertidumbre (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaR8E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">20</span><span class="p">,</span> <span class="mi">20</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 9 con incertidumbre (Banda Rojo)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [837]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_R9</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata9</span><span class="p">,</span> <span class="n">poptR9</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR9</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR9</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR9</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR9</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteR9</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptR9E</span><span class="p">,</span> <span class="n">pcovR9E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata9</span><span class="p">,</span> <span class="n">recorteR9</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">4</span><span class="p">,</span><span class="mi">7</span><span class="p">,</span><span class="mi">3</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">Err_R9</span><span class="p">)</span> +<span class="n">estrellaR9E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata9</span><span class="p">,</span> <span class="n">poptR9E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR9E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR9E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR9E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR9E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMR9E</span><span class="o">=</span><span class="n">FWHMR_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptR9E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 9 fotografÃa (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteR9</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 9 a partir de la gaussiana con incertidumbre (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaR9E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 10 con incertidumbre (Banda Rojo)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [838]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_R10</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata10</span><span class="p">,</span> <span class="n">poptR10</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR10</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR10</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR10</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR10</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteR10</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptR10E</span><span class="p">,</span> <span class="n">pcovR10E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata10</span><span class="p">,</span> <span class="n">recorteR10</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">2</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">Err_R10</span><span class="p">)</span> +<span class="n">estrellaR10E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata10</span><span class="p">,</span> <span class="n">poptR10E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptR10E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptR10E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptR10E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptR10E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMR10E</span><span class="o">=</span><span class="n">FWHMR_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptR10E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 10 fotografÃa (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteR10</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 10 a partir de la gaussiana con incertidumbre (Banda Rojo)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaR10E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Reds'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Histograma con incertidumbres (Banda Rojo)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [839]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">FWHMR_I</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">FWHMR_I</span><span class="p">)</span> +<span class="n">sigmaR_I</span> <span class="o">=</span> <span class="n">FWHMR_I</span><span class="o">.</span><span class="n">std</span><span class="p">()</span> +<span class="n">mediaR_I</span> <span class="o">=</span> <span class="n">FWHMR_I</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> +<span class="n">medianaR_I</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">median</span><span class="p">(</span><span class="n">FWHMR_I</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Datos de FWHM con incertidumbres de las estrellas para la Banda rojo :"</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Desviación :"</span><span class="p">,</span> <span class="n">sigmaR_I</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Media :"</span><span class="p">,</span> <span class="n">mediaR_I</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Mediana :"</span><span class="p">,</span> <span class="n">medianaR_I</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">FWHMR_I</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">'FHWM'</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">'# de estrellas'</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + +<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain"> +<pre>Datos de FWHM con incertidumbres de las estrellas para la Banda rojo : +Desviación : 2.344334810725805 +Media : 4.008532518694751 +Mediana : 2.9196546806439647 +</pre> +</div> +</div> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img src="data:image/png;base64,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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 1 con incertidumbre (Banda Verde)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [840]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_G1</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata1</span><span class="p">,</span> <span class="n">poptG1</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG1</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG1</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG1</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG1</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteG1</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptG1E</span><span class="p">,</span> <span class="n">pcovG1E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata1</span><span class="p">,</span> <span class="n">recorteG1</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">12</span><span class="p">,</span><span class="mi">4</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">Err_G1</span><span class="p">)</span> +<span class="n">estrellaG1E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata1</span><span class="p">,</span> <span class="n">poptG1E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG1E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG1E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG1E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG1E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMG1E</span><span class="o">=</span><span class="n">FWHMG_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptG1E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 1 fotografÃa (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteG1</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 1 a partir de la gaussiana con incertidumbre (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaG1E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 2 con incertidumbre (Banda Verde)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [841]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_G2</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata2</span><span class="p">,</span> <span class="n">poptG2</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG2</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG2</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG2</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG2</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteG2</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptG2E</span><span class="p">,</span> <span class="n">pcovG2E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata2</span><span class="p">,</span> <span class="n">recorteG2</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">Err_G2</span><span class="p">)</span> +<span class="n">estrellaG2E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata2</span><span class="p">,</span> <span class="n">poptG2E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG2E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG2E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG2E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG2E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMG2E</span><span class="o">=</span><span class="n">FWHMG_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptG2E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 2 fotografÃa (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteG2</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 2 a partir de la gaussiana con incertidumbre (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaG2E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">35</span><span class="p">,</span> <span class="mi">35</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img src="data:image/png;base64,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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 3 con incertidumbre (Banda Verde)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [842]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_G3</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata3</span><span class="p">,</span> <span class="n">poptG3</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG3</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG3</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG3</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG3</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteG3</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptG3E</span><span class="p">,</span> <span class="n">pcovG3E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata3</span><span class="p">,</span> <span class="n">recorteG3</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">4</span><span class="p">,</span><span class="mi">4</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">Err_G3</span><span class="p">)</span> +<span class="n">estrellaG3E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata3</span><span class="p">,</span> <span class="n">poptG3E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG3E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG3E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG3E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG3E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMG3E</span><span class="o">=</span><span class="n">FWHMG_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptG3E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 3 fotografÃa (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteG3</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 3 a partir de la gaussiana con incertidumbre (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaG3E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 4 con incertidumbre (Banda Verde)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [843]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_G4</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata4</span><span class="p">,</span> <span class="n">poptG4</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG4</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG4</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG4</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG4</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteG4</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptG4E</span><span class="p">,</span> <span class="n">pcovG4E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata4</span><span class="p">,</span> <span class="n">recorteG4</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">3</span><span class="p">,</span><span class="mi">5</span><span class="p">,</span><span class="mi">4</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span> <span class="n">sigma</span><span class="o">=</span><span class="n">Err_G4</span><span class="p">)</span> +<span class="n">estrellaG4E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata4</span><span class="p">,</span> <span class="n">poptG4E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG4E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG4E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG4E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG4E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMG4E</span><span class="o">=</span><span class="n">FWHMG_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptG4E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 4 fotografÃa (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteG4</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 4 a partir de la gaussiana con incertidumbre (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaG4E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 5 con incertidumbre (Banda Verde)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [844]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_G5</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata5</span><span class="p">,</span> <span class="n">poptG5</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG5</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG5</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG5</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG5</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteG5</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptG5E</span><span class="p">,</span> <span class="n">pcovG5E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata5</span><span class="p">,</span> <span class="n">recorteG5</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">2</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">Err_G5</span><span class="p">)</span> +<span class="n">estrellaG5E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata5</span><span class="p">,</span> <span class="n">poptG5E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG5E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG5E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG5E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG5E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMG5E</span><span class="o">=</span><span class="n">FWHMG_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptG5E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 5 fotografÃa (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteG5</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 5 a partir de la gaussiana con incertidumbre (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaG5E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 6 con incertidumbre (Banda Verde)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [845]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_G6</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata6</span><span class="p">,</span> <span class="n">poptG6</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG6</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG6</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG6</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG6</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteG6</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptG6E</span><span class="p">,</span> <span class="n">pcovG6E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata6</span><span class="p">,</span> <span class="n">recorteG6</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">2</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">Err_G6</span><span class="p">)</span> +<span class="n">estrellaG6E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata6</span><span class="p">,</span> <span class="n">poptG6E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG6E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG6E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG6E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG6E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMG6E</span><span class="o">=</span><span class="n">FWHMG_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptG6E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 6 fotografÃa (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteG6</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 6 a partir de la gaussiana con incertidumbre (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaG6E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 7 con incertidumbre (Banda Verde)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [846]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_G7</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata7</span><span class="p">,</span> <span class="n">poptG7</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG7</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG7</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG7</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG7</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteG7</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptG7E</span><span class="p">,</span> <span class="n">pcovG7E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata7</span><span class="p">,</span> <span class="n">recorteG7</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">2</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">Err_G7</span><span class="p">)</span> +<span class="n">estrellaG7E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata7</span><span class="p">,</span> <span class="n">poptG7E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG7E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG7E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG7E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG7E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMG7E</span><span class="o">=</span><span class="n">FWHMG_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptG7E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 7 fotografÃa (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteG7</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 7 a partir de la gaussiana con incertidumbre (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaG7E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 8 con incertidumbre (Banda Verde)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [847]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_G8</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata8</span><span class="p">,</span> <span class="n">poptG8</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG8</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG8</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG8</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG8</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteG8</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptG8E</span><span class="p">,</span> <span class="n">pcovG8E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata8</span><span class="p">,</span> <span class="n">recorteG8</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">3</span><span class="p">,</span><span class="mi">3</span><span class="p">,</span><span class="mi">3</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">Err_G8</span><span class="p">)</span> +<span class="n">estrellaG8E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata8</span><span class="p">,</span> <span class="n">poptG8E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG8E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG8E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG8E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG8E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMG8E</span><span class="o">=</span><span class="n">FWHMG_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptG8E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 8 fotografÃa (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteG8</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 8 a partir de la gaussiana con incertidumbre (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaG8E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">20</span><span class="p">,</span> <span class="mi">20</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 9 con incertidumbre (Banda Verde)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [848]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_G9</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata9</span><span class="p">,</span> <span class="n">poptG9</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG9</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG9</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG9</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG9</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteG9</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptG9E</span><span class="p">,</span> <span class="n">pcovG9E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata9</span><span class="p">,</span> <span class="n">recorteG9</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">5</span><span class="p">,</span><span class="mi">6</span><span class="p">,</span><span class="mi">6</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">Err_G9</span><span class="p">)</span> +<span class="n">estrellaG9E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata9</span><span class="p">,</span> <span class="n">poptG9E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG9E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG9E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG9E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG9E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMG9E</span><span class="o">=</span><span class="n">FWHMG_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptG9E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 9 fotografÃa (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteG9</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 9 a partir de la gaussiana con incertidumbre (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaG9E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 10 con incertidumbre (Banda Verde)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [849]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_G10</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata10</span><span class="p">,</span> <span class="n">poptG10</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG10</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG10</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG10</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG10</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteG10</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptG10E</span><span class="p">,</span> <span class="n">pcovG10E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata10</span><span class="p">,</span> <span class="n">recorteG10</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">Err_G10</span><span class="p">)</span> +<span class="n">estrellaG10E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata10</span><span class="p">,</span> <span class="n">poptG10E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptG10E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptG10E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptG10E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptG10E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMG10E</span><span class="o">=</span><span class="n">FWHMG_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptG10E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 10 fotografÃa (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteG10</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 10 a partir de la gaussiana con incertidumbre (Banda Verde)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaG10E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Greens'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Histograma con incertidumbres (Banda Verde)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [850]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">FWHMG_I</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">FWHMG_I</span> <span class="p">)</span> +<span class="n">sigmaG_I</span> <span class="o">=</span> <span class="n">FWHMG_I</span> <span class="o">.</span><span class="n">std</span><span class="p">()</span> +<span class="n">mediaG_I</span> <span class="o">=</span> <span class="n">FWHMG_I</span> <span class="o">.</span><span class="n">mean</span><span class="p">()</span> +<span class="n">medianaG_I</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">median</span><span class="p">(</span><span class="n">FWHMG_I</span> <span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Datos de FWHM con incertidumbres de las estrellas para la Banda verde :"</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Desviación :"</span><span class="p">,</span> <span class="n">sigmaG_I</span> <span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Media :"</span><span class="p">,</span> <span class="n">mediaG_I</span> <span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Mediana :"</span><span class="p">,</span> <span class="n">medianaG_I</span> <span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">FWHMG_I</span> <span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">'FHWM'</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">'# de estrellas'</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + +<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain"> +<pre>Datos de FWHM con incertidumbres de las estrellas para la Banda verde : +Desviación : 2.525343798913612 +Media : 4.246485293065105 +Mediana : 3.173731685005169 +</pre> +</div> +</div> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img src="data:image/png;base64,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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 1 con incertidumbre (Banda Azul)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [851]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_B1</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata1</span><span class="p">,</span> <span class="n">poptB1</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB1</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB1</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB1</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB1</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteB1</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptB1E</span><span class="p">,</span> <span class="n">pcovB1E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata1</span><span class="p">,</span> <span class="n">recorteB1</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">3</span><span class="p">,</span><span class="mi">3</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">Err_B1</span><span class="p">)</span> +<span class="n">estrellaB1E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata1</span><span class="p">,</span> <span class="n">poptB1E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB1E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB1E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB1E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB1E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMB1E</span><span class="o">=</span><span class="n">FWHMB_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptB1E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 1 fotografÃa (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteB1</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 1 a partir de la gaussiana con incertidumbre (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaB1E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 2 con incertidumbre (Banda Azul)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [852]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_B2</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata2</span><span class="p">,</span> <span class="n">poptB2</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB2</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB2</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB2</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB2</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteB2</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptB2E</span><span class="p">,</span> <span class="n">pcovB2E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata2</span><span class="p">,</span> <span class="n">recorteB2</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">4</span><span class="p">,</span><span class="mi">4</span><span class="p">,</span><span class="mi">4</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span> <span class="n">sigma</span><span class="o">=</span> <span class="n">Err_B2</span><span class="p">)</span> +<span class="n">estrellaB2E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata2</span><span class="p">,</span> <span class="n">poptB2E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB2E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB2E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB2E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB2E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMB2E</span><span class="o">=</span><span class="n">FWHMB_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptB2E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 2 fotografÃa (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteB2</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 2 a partir de la gaussiana con incertidumbre (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaB2E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">35</span><span class="p">,</span> <span class="mi">35</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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dfNWr5smcXigc7HnyjpDzv2+U5Vr2Ep9niA7efY/qqrKbO7VA2cS/vmkH4s7PMy17XQf6gff5Oraaw/Vt//v1Wdcf+cq6nLryk8j6W8LgtjjMPqZZdz7B2v6gfwxRwS06njuKndFYeedX+gD0vwQN8jYk/952F1f3bWPy4sdKKkV3f+aFU/vrNPyzlWHyHp7jg0T8xNpQcX3N7x915JO+LB5FLzsVbnPln4PpzWoa9N0/fBYjGsVJ3k2BwRG1VNL36J6+nyS4w1Fz3G9ND38P2q4n3V617uZ9T87EJFxK2qpksvPEv+pvo5/lqynm42aQkx7Nh8a0fEbRHxqxHxCFVTHv7EeVbEhb+83SzpOQu+fNfVL2Lmd+t1/et6kPWftOBak06upl98QtXAsXjtSMH3Vb2Z5te1UdVUglIfs8dvV8cUBNvWoVMSpIfuo2U91wVereoXwh+tl52fGlVa/mpJjymtLKpfyD+kakqJXF0f+xuqftk9MiI2S7pnif3bLunYeh/MO6FJ3+vg53RJP1l/aNymamrH420/vn7MY1UNwk+PiM4PyvtVTeWZ1+2C+3+lKkHYvd2eINBK/ZhizDTjoVql39XvUpXI5OR63a/L1l07vuPvE1R9Xy91XYtNg+0mW2Z7Z3/q78LO/t2saopu5z5fHxF/n22w3ocXq8paenT9vXyJyvvmkLhkQZ+6reuQ708vSFgTEV+LiOermp75CVVntVSf+Xx1RPyAqkuRft32sxbpW5PXeN5yjr2bJf1Aoe2QmE6HHjf9crOkLV78Gt+bJb1pwXGxISI6p5wuPO66HYdH1rHqvM5YbOFrPKnqzOtKLHwfHpS0o+O+zv4u531wfdVFF3/wqc+Q/rXqOFbLj5M7LXwPb1AV789b8vFr+8dVTZN+bUcc+6OSfsEPXtv8YlWzSX4+Dk3y2iSO/aduT25sBrO2/6MfvFD6blUH4Pwp9ttV/nCY925Jb3I9XcD2Nlfz47vZpGq6wD31QVssQ2N7WtV1qnslnRURc6XHFlwo6Zdtn1p/sP+upMvqN4T00OeZPf6vJP1r2y+oD86Xq/tBt+TnWlh2r6Rdri6wf32Xx1+ifCrvYZJerAezJ29Sdb3DnZKmbP8PVdfVLMU/1Mv+mu1p2y9UdS1Kk76/QNVZglNUTf84VdWb9W9V/QJ3uKRPqpomt3B63VWSnuaq7toRqqaFZ35S1QchsHpxZnZVWaXf1Zsk3SvpPts/KGkptRN/uz4T8zhV18DNX+vaZF1L2W+Zv1I1jfCFdTzwazo0Hni3qsD2cZJk+wjb/3EJ612j6nKfOyXNuJqRtDABT6eLJL3S9rH14Ok3l7Guf6qfw6mucmWcO99ge43tX7R9RB1436v6mHOVwOjR9QD+HlXf34u93k1el85llxo7fVrSMbZf5Srh0yY/WBbqQkn/vT7mt0r6H6rO8vZNVBln/1rVj05H1jHS/CDrPZLOsf2jrmy0/e9cXfdbUjxWI+ImSZdLekP9mv2EHhzoSdXlZevqbUyrul54paUP/5PtU+rB3xslfTTKZYKW/D6IiAOqrn3O4tjjJD1bh8axy4mTO31U0vNs/4SrPDBv1KFjwOUcv2dJulSHxrE/JGm9pOe4mm78R6pm39y5YNmrJL2w/mx7tKprtzNLimNX47f2fBa0+dvH6/v/jaTLbM/PQ39lRHy3bjtX0gWupgacXljvH9bLfc72blWJhZZSV+4NqhIV3KPqC+FjyWN/XNX1ED+t6mCdfw5LuuYjIv5G1Tz4i1X9CvMoVQO6eeeq43lmj6+nwP5HVRf636XqoL1c1fUOvXiuC71d1Rthh6p9+5kuj3+/pOe6OtM574FMwKqmg2xRdQ2JVF3k/xlVH3Y3SdqnJU5vqT90XqiqHNBOSS/Soc9tOX0/S9U1Dd+rz0DcFhG3qbqI/xdVDZIfqypxxX0dz0cRcamqgOZqVQkQPt2l62foockMgNWFM7NtNU7f1f9NVV6E3aoC/FISpk5fUnX25vOS/iAiPreCdZ2r7vutqCMeeLOqeOBkSX/X0f5xSb8v6cOupih+U9V1lN3Wu1vVwPgiVT9c/IKq167kPaqug71aVfKeS1T90DzbbV1RJZ18o6oBxHfUkU+jdqakG+v+n6MHY4eT62XuU/XD9p9ExBcW6VuT12Xeko+9+nn+lKpB3G31c3lG3fw7quK0qyV9Q9KV9X39dqaqM5bfUpWE61V1Xy9XlbTrnapek+tVxVGZ31M1IN/ljizeHX5B1ft5p6rB3PvnG+oZef9FVaWPW1WdBVw0wdIyfEBV1YnbVFWxKE6ZbfA++FMdek2zJL2oI+77mqr32RvqtrdreXFyZ9+uUXVS6kOq4v27dei+WdLxW/8QdLqkP+qMYaOqIPIBVTHu81Ul2PpKx2fj/ID0bZIOqPrR4gLVU5UL2zpG1djjE92en+Oh17EDD+HqQu5bJP1i4YN84Gz/rqQ7IuLtw+7LqHFVjPvMiFh24AK0xcQRx8faH//1nq9332d+/YqIOK37I4HecpWA8V8kTS+4vhEL1Gdf3x0RSyoDBIwa23+nqsrH14fdl1Fj+y2SboiIP+n22FYXKUZ/2f4ZVRmB96qa9mIdWupmqCLidcPuw6iKiL/U8rP8AS1jpgUDY6KeifUMVWdnj1Z1Zu7j6ULACIuIp3R/1HiKiFcv9bFEAcj8mKqseTtUTWlZSWZdAOg9phkD48KqplzerWqa8XWqrgsFMMY4M4uiiDhXSywaDwADZ3FmFqtKnYCRX1QWUZeE+TfD7geA0cJgFgDQUkwzBgBgnBEFAAAAAABaZ0VnZm0/W1Ua/ElJ/yci3pw9fuvWrXHiiScteztZvuW5JBuzm87USRbL1tg1L3QfEkdHstJBJ6pueqnZOCTUnpwY7Kyxpvs0O55Kbv7eTbprxw6mxWE4uMYVLTOo2AnA6Lrpphu1g9ipJxoPZm1PSvpjVfWubpH0NdufiohrS8uceOJJ+rvLLl/2tubmygH23oOl2sXSRBLkZGMLN1wu6aYkKSuDlA0+stXOzJZrtc8mHcr62nTfjPNgtluJq8PWDXZGf/baZ12dbXAgPutpSynhCPQJ04zRIoOMnQCMrqf8KNXfemUlUcCTJF0fEd+NiAOSPqyqUC4AAINBNmO0C7ETAPTQSgazx0q6uePft9T3AQAA4KGInQCgh/o+99H22ZLOlqTjTzih35sDAIwLk80YqxOxEwAszUqigFslHd/x7+Pq+w4REedFxGkRcdq2rdtWsDkAABYY8DRj28fb/oLta21fY/uV9f3n2r7V9lX17bkdy7zW9vW2v237Z/q8RzDaiJ0AoIdWcmb2a5JOtv1IVR/EL5b0C9kCsxG6f9/M4o1J/LB2qjzmztq6JWRqIltntyRAmYkk69LBJMlTtly6vaQtS7g1kyYWavb8t25aW2zbvfdgsW3H7gPFtmyfHb5+uti2Ye1ksS0zNZH/LrT/YLk/WabjqclyW5bkaWa23JYleWrSl8ZZw4EeyJLS9cmMpFdHxJW2N0m6wvalddvbIuIPFvTvFFXfj4+T9AhJf2P7MRFRzl6I1WzZsRMAoKzxYDYiZmy/QtJnVaWXf29EXNOzngEAkLAGP5iNiO2Sttd/77Z9nfJrHp8v6cMRsV/Sv9i+XlUSoH/oe2cxcoidAKC3VnTNbERcIumSHvUFAIDWsH2SpCdIukzSUyS9wvZLJF2u6uzt3aoGul/tWIyEP2OO2AkAeofMGQCAdnKfbtJW25d33M5+yKbtwyRdLOlVEXGvpHdJepSkU1WduX1LP54yAAB4UN+zGQMA0B/u1zTjHRFRrGhve1rVQPaDEfExSYqI2zva3yPp0/U/l5TwBwAALB9nZgEArWW757cu27Ok8yVdFxFv7bj/mI6H/Zykb9Z/f0rSi22vrZP+nCzpH3u6EwAAGFOcmQUAtNYQshk/RdKZkr5h+6r6vtdJOsP2qZJC0o2SXiZJEXGN7YskXasqE/LLyWQMAEBvrOrBbMOqNWn5naxszYoqASXlUrJtpqtstrm+lDTK7D1Qjuuy8jNZWaLJKLdly2X7ZfAxcy4L4tNKQeUqQZpM1lkq2zNq+wXop4j4ihYvJldM6BMRb5L0pr51CkDPrKTM4mo2hB8OgSVZ1YNZAMDqRoAFAMD4YjALAGinB7MPAwCAMcRgFgDQSu5fNmMAANACDGYBAK3FYBYAgPFFaR4AAAAAQOtwZhYA0FqcmQUAYHyNzmA2yYSelWcplQtZiabld5qW0JGkuSQVfPb8m2+v56tsHFTev3+m2JZlyM9e+wmXJx00PWay13dysj8BddPXKetNut/SfcqgAaOHwSwwvvpRRmfQlXmabm7wn3y93zF8fqMXRmcwCwDAcpDNGACAscY1swAAAACA1uHMLACgtZimBgDA+GIwCwBoJerMAgAw3hjMAgBai8EsAADji8EsAKC9GMsCADC2Bj+YLQUeScbvmaxUTsNM4bNNF0wWy8rrdFk0fR6zA04Tn+lH3Lh/Zq7YNj1ZzlG2ZqrclvVzKik/k6X5z14Hd6mhk1YDSus9pasdqG7HNwAAvda0/E4fwry+lAJqqh89yWa6ZE89C3GyyTPd9iczb7AUnJkFALSTCXYAABhnDGYBAK3FYBYAgPHFYBYA0FoMZgEAGF8MZgEArURpHgAAxls5gw4AAAAAACOKM7MAgPbixCwAAGNroINZy5ooTAmbS5KMzyVlT2aStN5Zyu9salq/Zq1lzyMzM9v7+ixNp+b1Y9c03C15uZtEdlxkZaBmkto8s106s266PAkiPS7SfPfpJotK78FufYnCYiNUqQDjhmzGQCuspKRNtmjTtWb9abq9xiWEGi3VPB5L4980bi6vM3sOTnra/Tk02zt8L4yXFQ1mbd8oabekWUkzEXFaLzoFAMBSELSgbYidAKB3enFm9hkRsaMH6wEAYFkYzKKliJ0AoAdIAAUAAAAAaJ2VDmZD0udsX2H77F50CACAJXMfbkB/ETsBQI+sdJrxT0TErbYfJulS29+KiC93PqD+oD5bko47/oQVbg4AgAcxzRgttKzY6fgTiJ0AoGRFZ2Yj4tb6/3dI+rikJy3ymPMi4rSIOG3r1m0r2RwAAA+w3Zcb0E/LjZ22ETsBQFHjM7O2N0qaiIjd9d8/LemN3ZYrVzApBxCzSWruAzPlsjUTSbmUyS6JxIstWWryFZQoyaqzzDatXZPq/Tqzki/5cuW2PA1+o82l+zpb51zSOJeU7ZEkJaV5siWzbU40nA+ZlcHKXkNK8ADAyjSNndqgcWmaLos1LYfT9Pu8aWmebJ19CLlySXiQxVxpNcB0ndmSWfnBLnFMw0WbluZEO61kmvHRkj5eHxRTkj4UEZ/pSa8AAFgCAhO0DLETAPRQ48FsRHxX0uN72BcAAJaFwSzahNgJAHqrF3VmAQAYDsayAACMLQazAIDW4swsAADja6V1ZgEAAAAAGDjOzAIA2smcmQUAYJwNdDBrS5OFnOCRlDbJsp1n5XfyFOPl1qalYrrJqrdkacRnupV9GRHRcO9kr9NclEsvzTUsWbRuzWSxLXsdss1lx4xUPu6rjebLNtIwhX6T0gJNX3dgpazulR0A9E4/yu90W2PT7+UsRkhL7TUsldi0n02/QbOPvrT8TvKhmcUq2WftZBZzJOuc6PLss9asPCFle8YL04wBAC1l2b2/pVu0j7f9BdvX2r7G9ivr+/+37W/Zvtr2x21vru8/yfZe21fVt3f3f78AADAemGYMAGitIfyQPiPp1RFxpe1Nkq6wfamkSyW9NiJmbP++pNdK+s16mRsi4tSB9xQAgFWOM7MAACxRRGyPiCvrv3dLuk7SsRHxuYiYqR/2VUnHDauPAACMCwazAIDWGvQ04wXbPknSEyRdtqDpVyT9dce/H2n767a/ZPupK37SAABAEtOMAQBt5b5NM95q+/KOf58XEecdsmn7MEkXS3pVRNzbcf9vqZqK/MH6ru2SToiIu2w/UdInbD+ucxkAANAMg1kAQCtZeabMFdgREacVt2tPqxrIfjAiPtZx/y9Jep6kZ0WdMjMi9kvaX/99he0bJD1G0uUL1wsAAJZnZAazTX9dn2qcRrzZBvN07l1SjDdNL9+HVPiZpttrqmmpmINJyaIsvp2azcoyNT0u8vbsOM1292zSmPW1aXjfuGwPMCSDTgDlah7y+ZKui4i3dtz/bEm/IeknI2JPx/3bJO2MiFnbPyDpZEnfHWyvgf7LviKy749uXy39KKOTtc00XC5ry8oE9aU0TxJzZGV0stI8U5PlKxMjuWixXAxRii6f32lMkuw5yvaMl5EZzAIA0AJPkXSmpG/Yvqq+73WS3iFpraRL66DnqxFxjqSnSXqj7YOS5iSdExE7B95rAABWIQazAIDWGvSv5RHxFS1+UuSSwuMvVjUlGQAA9BiDWQBAO/UvARQAAGgBBrMAgFayuI4JAIBxxmAWANBSy6sLCwAAVpck/xgAAAAAAKOJM7MAgNbixCwAAONroIPZ2bnQ/ftnF21bv6ZciSqr+zSd1L3KanQenJ1Llis2pX2ZyRaUtO/g4s9dkg7MlPuTTaPL+pPVYc22lz7HrO5pUtcrqwe2fqr82jetbZrVQ8tkx+GGpG06K9wm6a77DhTbsjpqU8l6s+Miq2ub1eBdM1Xeb9PTi7c1rc0L9ALTjIHeymKA7Cu5ab3Ubt/zTWvCZjHZTBIDZrFTGjs2rUHbcMdl3+VN44osdlqTdDRbLt1e9iSkdP5oFnOm9WuT/c3XSTtxZhYA0E5kMwYAYKxxzSwAAAAAoHU4MwsAaCVK8wAAMN4YzAIAWouxLAAA44vBLACgtTgzCwDA+GIwCwBoLcayAACMr66DWdvvlfQ8SXdExA/V922R9BFJJ0m6UdLpEXF393WVU4mnKcaTxiwteyaropOmUE/asnI3krT/YJYKvtw2mT3/hink7z0wU15uLinbk+Q0n3I5n1gWcB7InnuyYFZ6aUNS7ieLffP08s3S7neTlSWIhvnls0oHc1kJpexpFBobVk8CgFWrl7FTP/Sj/E62zqZla6Q8zmtagjBr29+wjGLWl/2z5XU2jWOzsjZrJpISO0kJvqxtJmlbO11syuOYZJ1dJYs626VZQJq+FOVGZggN11KOovdJevaC+14j6fMRcbKkz9f/BgBgcFwFEb2+AT3wPhE7AUDfdR3MRsSXJe1ccPfzJV1Q/32BpBf0tlsAAOSqbMa9vwErRewEAIPR9JrZoyNie/33bZKO7lF/AABYIs6kolWInQCgx1YwWb0S1UUSxYnkts+2fbnty+/asWOlmwMA4AGcmUUbLSd2unPHnQPsGQC0S9PB7O22j5Gk+v93lB4YEedFxGkRcdpRW7c23BwAAECrNYqdtm3dNrAOAkDbNB3MfkrSWfXfZ0n6ZG+6AwDA0pEACi1C7AQAPbaU0jwXSnq6pK22b5H0eklvlnSR7ZdKuknS6UvZWES59EeWmTwLLRpn2E5k6eWzMiorSS+/LynbMz1ZfpJ7khTy9xw4UGzbsbfctmtfkkI+ST2fVLVJA8SjNpQPw+zXlrVJ+Z2NU+V1bport2XH00xSQmjtdLkvUl56qh+yQ3EieWdkpacG/iSAbpgWjBHVy9hplOTxUXm5rK1b7JSWvElioKwc4r5kuT0Hym33HjhYbLv/YLnk4Z6ZrDRPuZ/ZrlmTBF3rG8ZHRyQ1dtYncU5azmk6DQ7LbeoW/5dbs9I8WQzEj5nt1HUwGxFnFJqe1eO+AACwZFU2Y4IPjB5iJwAYjKbZjAEAGDoGswAAjK8VZzMGAAAAAGDQODMLAGgtTswCADC+GMwCAFqLacYAAIwvBrMAgHYimzEAAGNtoIPZiHI69KzqR5a2fXqqfNlvt3TvJRNJdDSbpvRutLl6m+W23QfK6d537S+X2Ll19/5i2/fuLrftvL+8zvv2lfvS1LFb1hfb1iWv7/ok3ftRG8uH9tYNa4ptWXr5I9aVU9Z3k5XuyV777JjKzkg1LUuVlY8q7dFovDUAQL9kZXTSUioNt5eVLszKvmXfO5J0cKZcuuZA0rY3K7Gzv1xi56595RhoZ1LW8M77y+u8Nyl5uC95DpksPjp8XTnmyOKjPTPl+OiodWuLbU2PmSzertrLz3Eiqb+TrTbbZvo8GjYye6j/ODMLAGglywQKAACMMQazAIDWYiwLAMD4YjALAGitbtPUAADA6sVgFgDQWoxlAQAYX+UrqwEAAAAAGFGcmQUAtJJNpkgAAMbZwAezpcztB2bLaa0nG8YqWer5TJZePtOtFFD2NLJFb9uzr9h2155yKvh/vnNvse3GO+4rtt1x155i276kNM/sbDm9fBZv3n7UhmLbhqQczpZN5TTxW5O2mS3NXt/sOWxSXrZnTZJCP1txdkxNNXxjEPxjNclKWwFYvqykTxarZKHTbNI4k8R/knQwiS32HSy33ZeUNdyxt1yeMCtrePOuctudu8tle+7ZU27bl5QQyqxbUy6/c/j6ckyyLYmPjt9c3p/Za5jlLsg+oye7fIBPJO1ZaZ5suewYnqDETitxZhYA0FoEGAAAjC8GswCA1mIsCwDA+CIBFAAAS2T7eNtfsH2t7Wtsv7K+f4vtS21/p/7/kfX9tv0O29fbvtr2jwz3GQAAsHowmAUAtJIluQ//dTEj6dURcYqkJ0t6ue1TJL1G0ucj4mRJn6//LUnPkXRyfTtb0rv6sCsAABhLDGYBAK014d7fMhGxPSKurP/eLek6ScdKer6kC+qHXSDpBfXfz5f0/qh8VdJm28f0fk8AADB+uGYWANBO9lATQNk+SdITJF0m6eiI2F433Sbp6PrvYyXd3LHYLfV92wUAAFZkoINZW5oulCjJwpEsWDk4k6URL69z/8FyKvQsbXdWKmVF6eVny/3Jyu987+5ymvjv3r673Hbj3cW2HbeV2/bsLpft0Wy5n5nbt2wutm3avKnYtnnz+mLbI44+rFFfsnI3G6fKb5cp55McNq4tp9DPZOnus/IJ2Xum6XLAKOrTIbvV9uUd/z4vIs47dLs+TNLFkl4VEfd2vnciIuykbgTQUnnZnnJbGjt1KWt4IInzslhu1/5yOZzb7i/HTjcmcdXNO+4vtt2xq1wO8Z57yuvcv79cQijb32vXlmOSI45YV2y7LymxeDB5LbL4YO1kOQbK2tZMlV9bSZqaLW9zOonX5pLnkc6+yWKnbLGkDf3HmVkAAA61IyJOKzXanlY1kP1gRHysvvt228dExPZ6GvEd9f23Sjq+Y/Hj6vsAAMAKcc0sAKCVrGr2Qq9v6Tar0xPnS7ouIt7a0fQpSWfVf58l6ZMd97+kzmr8ZEn3dExHBgAAK8CZWQBAaw1hZvxTJJ0p6Ru2r6rve52kN0u6yPZLJd0k6fS67RJJz5V0vaQ9kn55oL0FAGAVYzALAGitQV/nHRFfUfkSqWct8viQ9PK+dgoAgDHFNGMAAAAAQOtwZhYA0Er2UKYZAwCAEdF1MGv7vZKeJ+mOiPih+r5zJf2qpDvrh70uIi7pvq5yKu0sjXZW0iZL1pGtMzOTbC9LEZ/1U5J2HyinQ98zU2678/5yyZs77i2ne//+bfcV27Z/745i28Gb/7nYpvt3ldsyyet0/11HlNs2H1Ns239cuW0ySdm+drpcJufwdeW2o9aXX4f1U3npney4mUzzxGfKEyuy7swkb4tC5axqucJTSCoHAH3XLWETMAy9jJ0yWemWdLmm28vaksYsHstiLkk6mJQ93JOW5il/Z9+2u9y2/e5yiZ3vZ6V57ii33XdPuW3f3n3FtszadWuLbfffv7HYNjNT3mdZPLJxTTlA2JzETpvWTBfb1s7kE0TXJEFJVu5pbqLcFpGVLiz3pelXTek9SujUO0uZZvw+Sc9e5P63RcSp9W1FH8YAADThPtyAHnifiJ0AoO+6npmNiC/bPmkAfQEAYFkGnQAKWApiJwAYjJUkgHqF7attv9f2kT3rEQAAwOpE7AQAPdR0MPsuSY+SdKqk7ZLeUnqg7bNtX2778rt27Gi4OQAADmVJE+79DeiTRrHTnTvuLD0MAMZeo8FsRNweEbMRMSfpPZKelDz2vIg4LSJOO2rr1qb9BADgULbchxvQD01jp21btw2ukwDQMo0Gs7Y708j+nKRv9qY7AAAs3Xx5nl7egH4gdgKA3ltKaZ4LJT1d0lbbt0h6vaSn2z5VVWbpGyW9bCkbi2hWxmMmScu+YW15PJ5uqpyZPJX1P0sTLkkH58rp5+8/WC7Ns+O+cgr5HbvLKd137dpT7ss9u4ptjcvvZLIdl21vtrxf7t1QTj2/cdP68nKb15Xb9pUPjPuTEgBHrs1f+6w0z9Rk+RieTNLLZ21zSer5LFbPDuEJEsljBHEmFaOol7FTU03LpqXLZeV3kgWz75ZuVRSz0j17kzIz9+7vfVy1c2e5bM+uHfcU2+6/e1exTXvuLbcl+3T/+sOLbTNJTDmZxBzr15fL6Gw5rFwKaNem8uuwZV257fA1+Yuflt9peEz1I5LpR0kfLN1Sshmfscjd5/ehLwAAAK1H7AQAg9F1MAsAwCiaTwAFAADGE4NZAEBrMc0YAIDxxWAWANBaDGUBABhfDGYBAK1kSxOcmQUAYGw1Ks0DAAAAAMAwjcyZ2bQkSJLh42BStidL6d20LTPZJRNJlrr7vgPl1OXZmYc9+8rp1++5q5wmXjtvKbeNkn33FZtm7yw/h7s3lsvvbN5cLtuz+6hyuv779pdfowMb8lpP2TE1Ndlsuaxk1ZqG7+ystAITOjGKODELLF80rNuTVu3JyqFkZXu6xFzZ9+CBuaSc3oFySZ89SdmePXvKccD995XL9ty/+/5im+65s9y2Z1e5LXOw3Jc902uKbesPK8dAe/aU2+7bX94vew+W9/WBpCxlHnN0KbHTtPZUIj++y63kbhiukRnMAgCwXAQRAACMLwazAIDWYiwLAMD44ppZAAAAAEDrcGYWANBKlslmDADAGGMwCwBoJzPNGACAccZgFgDQWiSAAgBgfA10MBuSDs4unqK7YTWcNFX2oNNodyvpM5v2p7xct9TlJRMTySXRSTr71kjS0s8VjrNusuMiazvQcHvdZMfU5ESzsj1Tk+XnkR1qk8lywLCQ+AHord4XPOlS8mQF602+6vLSdlnbTPn7fHYmiZ1myqVrsnhFB/eX2zJTyToPlNtmDpbLEqXPPdnZWZnMLIbtFvvnMX6+bJN1UoKwnYgDAAAAAACtwzRjAEArWUwzBgBgnDGYBQC01gRjWQAAxhaDWQBAazGYBQBgfDGYBQC0ks00YwAAxhkJoAAAAAAArTPYM7NRLhmSpe5eOz1ZbJtrWtMnMZGWZylvL1tOkiaT9rWT5d8VJpN5dFm5lOk108W2vWvWF9sap4kftInycTGR7M+pqfI+WzNVXm5tstxUl7mO0w1f32y12fE2ka4zKc2TbK/0HDkxhmFimjHQW/14S2XrXMn2smWz79bsO3sqiQMmp8pxh6bKMZem1jRry2TLTZfbsueQPvck3kxCnDxW6fLi5+US82UxPphmDABoLQIaAADGF4NZAEArWd1nxAAAgNWLwSwAoLVI/AAAwPgiDgAAAAAAtA5nZgEArTWMWca23yvpeZLuiIgfqu/7iKTH1g/ZLGlXRJxq+yRJ10n6dt321Yg4Z7A9BgBgdWIwCwBoJdvDumb2fZLeKen983dExIvm/7b9Fkn3dDz+hog4dVCdAwBgXHQdzNo+XtUX9tGSQtJ5EfGHtrdI+oikkyTdKOn0iLg7W1dE6ODs3KJtTVOo729YmidLB57FRlma8Ow5SNJ0VkYnyWt+1Mbyy3TUpnXFts1HbSq23bv1hGKb9u4ut83Nltv6YcMR5bZt5edw+JGHF9s2biynrN+8vryvNyYlotZOJun6Vb1xeq3pOkvvQUmaTd5Ppba58uqAvhvGWDYivlyfcX0IV18Sp0t65kA7hZHSy9ipT/0rtkVSKjEtsdOwsdt7OIutsrKGG6aTtrXl7/r168sldjZsXFtuO2xDsW3PgYcV2xqX5llfjnPWb9pYbNuwsRw3Zs99Y7LPsn29ZqLc1u3HyDxWb/bhn5b7abgchmsp18zOSHp1RJwi6cmSXm77FEmvkfT5iDhZ0ufrfwMAMDAT7v1thZ4q6faI+E7HfY+0/XXbX7L91BVvAW1A7AQAA9B1MBsR2yPiyvrv3aqu/TlW0vMlXVA/7AJJL+hTHwEAGKStti/vuJ29jGXPkHRhx7+3SzohIp4g6dclfch2+ZQKVgViJwAYjGVdM1tPq3qCpMskHR0R2+um21RNpQEAYCD6WGd2R0ScttyFbE9JeqGkJ87fFxH7Je2v/77C9g2SHiPp8h71FSOO2AkA+mfJpXlsHybpYkmvioh7O9uiusBi0YssbJ89/+v2zp07VtRZAAA62b2/rcC/lfStiLjlwf55m+3J+u8fkHSypO+uaCtojV7ETnfuuHMAPQWAdlrSYNb2tKoP4w9GxMfqu2+3fUzdfoykOxZbNiLOi4jTIuK0LVu29qLPAABIfbhedinXzNq+UNI/SHqs7Vtsv7RuerEOnWIsSU+TdLXtqyR9VNI5EbGzZ/sAI6tXsdO2rdsG02EAaKGlZDO2pPMlXRcRb+1o+pSksyS9uf7/J/vSQwAARkhEnFG4/5cWue9iVQMajBFiJwAYjKVcM/sUSWdK+kb9y7IkvU7VB/FF9S/SN6kqRZCyXSxBk03tytLEd9teSfbre3YN1oTLfelWmmf9ZJLWfKpc8mZLUi7mqE3lNPHbtpVTs993b/mX3p0HH11s0z23l9v27ym3ZSV9thxbbjv8qGLT1mPKZ/of9rDycz8ySa0/lZRPyo6nrHyUJB2YKdevyY6biaQ/2ftiLimxk5XmyfopLf4azjZ8fwK94LSYAjA0PYudmsrjqmbLZW+3LHZKvsq6xk5TSfmddVPlsnhHrEtip43lEjQ7k7hqz5b1xbaZ7Hs+6ef+vYcV2zJr1pVL+hx2RHmdRx1VLiGUxZRbNpT32RFJnLo+ee5ZzCV1iY/SY7Hc1o9vDKr2DFfXwWxEfEXl1/5Zve0OAABLUyWAGnYvgIcidgKAwVhWNmMAAEYJg1kAAMYXg1kAQGtl0/8BAMDqtuTSPAAAAAAAjArOzAIAWolrZgEAGG8MZgEA7WSySAIAMM4GPpidaPAz+p4D5bIuWcr2bEtZuu8sVfhcZG3JBiVNJ+vNUpevmy4/x81JOvRjjiqXp5lNyrNk6d537yqX9Jk5OFNsU7Jv1q4vp4LftLmcXn7r1nJ6+W1bym2b1pfTy08nx0WWQX7K+Yz9tVPl9uy4KJWykvLjdDrZXqZJlR3GEhimrBwIsNpl14w3LWuYbi/tS7kti/2yOE6SpifL8crGqXIMdMSa8nf9wzeV45Xd+5PyO7NJecbkeWzYUI6r9u8v9yV7DdeuTZ77EUnZxiPL8dHDs7ZNSWmeZF9vnC73M4txpG6leZq1ZcdpP75OSu9Rvrl6hzOzAIBWYpoxAADjjQRQAAAAAIDW4cwsAKC1mGUMAMD4YjALAGgpa4IrjwAAGFsMZgEArWRxZhYAgHHGYBYA0E4mARQAAONsoIPZuQjtKaQg35CkGM9K3mRxTJMyQJI0MZeUZ0nWOdulNk+Wfn7tZLk0zxHJvnn4pnLK+n0z5fTy66aT7W1aV2y7Z3e5VM7+/eUSSpksnf2mTeV09ps3llPPb9lUbjtsbfm5H7WxvK+z9PLrktJKkrQ2Ka+0Jimj0zQtfVZGyMn2snI/U4W+ZH0EAIye7FM7i2SyUkDZV0H2fVX6bpmXlW/Jvls3ry3HD/s2luOVg1n5naSvG5NYbdfhB4pt+w82i52y2OGIjeXnvi2Jj47bXG57eLLclqSkY1ZeMnsOUh43Z69FXn6nWcxCpDO6ODMLAGgt6swCADC+GMwCAFqJa2YBABhvDGYBAK3FmVkAAMZXPlkdAAAAAIARxJlZAEBrcWIWAIDxxWAWANBKFtOLAAAYZwMdzM7MhXbet3h68iw993RWZySRpXvPyuhkJX3csGyPlKetn0pOL2xdX06HnmSQ18HkOU4m28vOdGTPce+BxcsudXPEhnJK98PWTRfbNq5LyuisKZfK2by+vNzmZHtZmv8NyfakvLxUdizOJC9wnnq+3JaW9Ele31J5BM6MYWjcvMwCgMWl5XeSwj1JeJTGY3NdYrwsPpydK3/3Zt+7D4tyCcIsPtqwptyXozYkpXn2luO4fTN5WceSdVPlfh6RxEdZCcJtSTyWld85bE1SujApBTndrTRPctxkbWkcn2yP75N24swsAKC1CD0AABhfzNACAAAAALQOZ2YBAK1kUZoHAIBxxmAWANBaDGUBABhfDGYBAK3FiVkAAMYXg1kAQEuZ7JMAAIyxgQ5mpyesbYcvnp58qlD2Q5LWJGnbs9TrB2bmim3NEqHnKeK7L5uUA0pL5SSpyTcmaeKTNOqP3Fwuo7Nvtrzf7kvK7+xP0stHlNuOSErlZHt7cqLceniSJn7L2nKK/JkoP/esfFK342nj2rx0T0lWKidry46ZLPSfSt5rs8lrCAAYLfkPPcnnebOmNI6J5Mt8KvIfpOaSuGsu+V7K+pptcTqJLTZMlWOLI9cdLLbtm5ktth3Iaiwmsu/r9VPlmGPTdPk5bFqTlENM4qr1SXnCtdPN4nspf45Z+Z08pi5vLy/bk7Xxo+owdR2Z2T7e9hdsX2v7GtuvrO8/1/attq+qb8/tf3cBAKhY1ZdYr2/AShE7AcBgLOXM7IykV0fElbY3SbrC9qV129si4g/61z0AAMr4RRwjitgJAAag62A2IrZL2l7/vdv2dZKO7XfHAADohqEsRhGxEwAMxrJmVNk+SdITJF1W3/UK21fbfq/tIwvLnG37ctuX79y5Y2W9BQBgnqszs72+Ab200tjpzh13DqqrANA6Sx7M2j5M0sWSXhUR90p6l6RHSTpV1a+Pb1lsuYg4LyJOi4jTtmzZuvIeAwAAtEAvYqdtW7cNqrsA0DpLymZse1rVh/EHI+JjkhQRt3e0v0fSp/vSQwAAFjGfAAoYRcROANB/XQezruZcnS/puoh4a8f9x9TXhEjSz0n6Zrd1TUxYG9cuvsnphuV3sqzeWbLzrFRMU0mWcEl5+SGpXBImW++G6XI69Cy9/FSy0rVJSaMNSbr3rHRL1jaZTOvL2rL9kqWlX5uk+V/ncls2/XBdknp+GJqW3wHahmnBGEW9jJ1GSfZ+m0iirqz6TlZmTpLKxWKU1/xJZJvMviOz+OGI2XJPDyQlD7OSgJms/My6yXIMtCYrhZk8v7TETrZc0pbHxXmsmr2GWRvfGavPUj4FniLpTEnPXJBK/n/Z/obtqyU9Q9J/7WdHAQBYyH24dd1mda3jHba/2XFfseSK7dfavt72t23/zIqfNNqA2AkABmAp2Yy/osW/3y/pfXcAABh575P0TknvX3D/Q0qu2D5F0oslPU7SIyT9je3HRMTsIDqK4SB2AoDBGK25kQAALIPd+1s3EfFlSTuX2MXnS/pwROyPiH+RdL2kJzV+wgAA4AEMZgEArVQlgHLPbyuwWMmVYyXd3PGYW0S9UQAAeoLBLACgtfp0ZnbrfI3P+nb2ErqypJIrAACgd5ZUmgcAgNFjeWVnUkt2RMRpy1kgKblyq6TjOx56XH0fAABYIc7MAgCwQraP6fhnZ8mVT0l6se21th8p6WRJ/zjo/gEAsBoN9Mzs5IR1+PrFN5nVkt1/sJz0MasWm9WunWmYRzLfXv7bwFxaSyypfZrUks36MzVZbl07V97ezHRSLzZ5oQ7ONauVtj+pv5bV0c1ky61fU27L6rZlstdIkmaS/datPvEgjVBXgCUZRslA2xdKerqq6ci3SHq9pKfbPlXVx/KNkl4mSRFxje2LJF0raUbSy8lkjGHLa20mkUUWdDSsC7+i0ypJDdOsP1lt26z26ZqppF7sbLPYaS6ynVqWvYbp80vappP9mcXU2T7LlutWY3girTPb7MM/WypbJfVpRxfTjAEArTSfAGrQIuKMRe4+P3n8myS9qX89AgBgPDGYBQC00xJL6QAAgNWJwSwAoLUYzAIAML5IAAUAAAAAaB3OzAIAWqtPpXkAAEALMJgFALSSNVrZwAEAwGANfDBbTqXdLDV5836U27IyQSuRpSfP+hPT5dngWbr3bHuZbJ1Z6vlQUkIoST2/KelLlrY9S8uepXNfk6Sez1KvZ6/RVJd93Y/U+5lsv6UVErgAES3DmVlgcJpW9MmW65qRvOEFcdn3WfaVPTWRlNjJSj6m5XfK28vio0zTeKVp2Z5suaZtWawmSZPJc0yPqYbLoZ04MwsAaC0CEwAAxhcJoAAAAAAArcOZWQBAazHNGACA8cVgFgDQSiSAAgBgvDGYBQC0lDkzCwDAGOOaWQAAAABA6wz0zGyEdGBmbvG2bLku6yxJ03Ync9PmsvIzDVOoV/1J0qEn6d6ztOZNZeV3shTyBwuvX7Vcs3VmsvJCTV/7pvszS/W+gsOicRmd7HhqmuG1aQkhYChMNmOg17LvliwGalp+Z65LacasPEsmqbAju3wuZ7JhfDTdNAZq+r3bsDRPWtawYdzctITOSuLbfpTfaVoOEcPFNGMAQGsRegAAML4YzAIAWqlKAMVwFgCAccVgFgDQWgxlAQAYXySAAgAAAAC0DmdmAQDtxalZAADGFoNZAEBrUWcWAIDx1XUwa3udpC9LWls//qMR8Xrbj5T0YUlHSbpC0pkRcSBbVyh0cLZc2mWQsvAnSxWele3pJstAnqUDXzNZng2epXvP8qLMJM8jK8+SPYem5X5mkmMiey2ybPZZXzJNU71329pU8ho2PRabprRvegSX9jfVfDBM5H/CKOpl7DRKBl22R8q/s5Kv1rx8X9IWSWez+Ciy55Ftr9yUSvdaFm8mizWNgZou160UTl6eMF208TbRPku5Zna/pGdGxOMlnSrp2bafLOn3Jb0tIh4t6W5JL+1bLwEAWIT7cAN6gNgJAAag62A2KvfV/5yubyHpmZI+Wt9/gaQX9KODAAAAbULsBACDsaRsxrYnbV8l6Q5Jl0q6QdKuiJipH3KLpGP70kMAAEo4NYsRRewEAP23pMFsRMxGxKmSjpP0JEk/uNQN2D7b9uW2L79rx45mvQQAYIFq7Nn7/4Be6FXsdOeOO/vVRQBovWXVmY2IXZK+IOnHJG22PZ9A6jhJtxaWOS8iTouI047aunUlfQUA4EGukoD0+gb00kpjp21btw2mowDQQl0Hs7a32d5c/71e0k9Juk7VB/PP1w87S9In+9RHAAAWxSxjjCJiJwAYjKXUmT1G0gW2J1UNfi+KiE/bvlbSh23/jqSvSzp/KRucKJUTyUq3JGVWphqWJ0kjlmR700ke+CwtfTfF/aI8bXv29LNU6ZosN80l1ZPmsjz4Ki+YpcHfe6DcuKYPlZCzqj3Tk81eh25HYVZGp2nJpkzTQzEvrUCYDwBL1NPYqQ36UbanWjjdaKMFJ9O+lteYlRHKnuOgK9jlJW2SMjrpcg370nB7/domVp+uQ4WIuFrSExa5/7uqrgEBAGA4iFkwgoidAGAw+nDeCwCAQSBhEwAA44zBLACgtZhNBgDA+GIwCwBoJRI2AQAw3pZVmgcAAAAAgFHAmVkAQHtxahYAgLE10MHshK21U4ufDJ6ZLScuPzhbLvkyMVE+uZyVPElLl6TVZ5LU610u3srKs2Rp4u/bP1Nsy8rvRJIMvlky++blh9KU9UnbbFZHJzHXsJ9ZiaSVyF77TNPrAbOn37T8zkpKTwH9QgIoYPStrFRK01imYam9NHZMllwFF/A3fZ36UdKnWrb9+xT9x5lZAEBrEesAADC+uGYWAIBlsP1e23fY/mbHff/b9rdsX23747Y31/efZHuv7avq27uH1nEAAFYZBrMAgNZyH25L8D5Jz15w36WSfigifljSP0t6bUfbDRFxan07Z5lPEQAAFDCYBQC0Uz9GsksYzUbElyXtXHDf5yJiPsHBVyUdt5KnBgAAumMwCwBoLffhvx74FUl/3fHvR9r+uu0v2X5qLzYAAABIAAUAaCmrbwmgttq+vOPf50XEeUvqk/1bkmYkfbC+a7ukEyLiLttPlPQJ24+LiHt722UAAMbPQAezcxHac2B20bYs23lWLiWLY7JyPzNJyZesHExWYqVbUJX1Z/9cufxQqZyRlJfmycwmO3z/wXJf0tcp6cvkVLltw9ryYZhVtMlei6nJ8j5LU/k3Lj3U5QFJX7PnmB37TV/7bKnsuCgdomSTxSq0IyJOW+5Ctn9J0vMkPSvqD5OI2C9pf/33FbZvkPQYSZeX1gPgQU1LxmXfTXkc0KwvmUEXtuvH13I/vuspvYNe4MwsAKC1RiUUsv1sSb8h6ScjYk/H/dsk7YyIWds/IOlkSd8dUjcBAFhVGMwCANprCKNZ2xdKerqq6ci3SHq9quzFayVdWp9t+Gqdufhpkt5o+6CkOUnnRMTORVcMAACWhcEsAKC1epSwaVki4oxF7j6/8NiLJV3c3x4BADCeGMwCAFqLS64AABhflOYBAAAAALQOZ2YBAK3FiVkAAMbXQAeztrVuenLRtqw8SX86U26amkxKzKxgTluWmv3gbLkcTlIpSNEw4ftcttJE06efpbpfv2bxY0LKA9WmJZuayvZYt/2SHd/ZerMyUbPJkis5Tkuy/Q0MDYclMLb6U9ql94V0VsPHFGV0MKo4MwsAaCVrOAmgAADAaGAwCwBoJ5MACgCAcUYCKAAAAABA63BmFgDQWpyYBQBgfDGYBQC0F6NZAADGFoNZAEBLmQRQAACMsYEOZq+68oodR6yfvKn+51ZJOwa5/S5GqT/0ZXH0ZXHD7suJQ9w2AKxqV155xY710x7F2GmU+iKNVn/oy+Loy4OInXpkoIPZiNg2/7ftyyPitEFuPzNK/aEvi6MvixulvgCDRjZjrHajGjuNUl+k0eoPfVkcfUE/MM0YANBKFpfMAgAwzhjMAgDai9EsAABja5iD2fOGuO3FjFJ/6Mvi6MviRqkvwECRAApjZpQ+70epL9Jo9Ye+LI6+oOccEcPuAwAAy/bDpz4x/vLzf9/z9Z60dd0VXEsFAMDoY5oxAKC1SAAFAMD4mhjGRm0/2/a3bV9v+zXD6ENHX260/Q3bV9m+fAjbf6/tO2x/s+O+LbYvtf2d+v9HDrEv59q+td4/V9l+7oD6crztL9i+1vY1tl9Z3z/wfZP0ZeD7xvY62/9o+5/qvryhvv+Rti+r31Mfsb2m330BRoH7cANGEbHTA9sembgp6c8w4oORiZu69IfYCT018MGs7UlJfyzpOZJOkXSG7VMG3Y8FnhERpw5pWtn7JD17wX2vkfT5iDhZ0ufrfw+rL5L0tnr/nBoRlwyoLzOSXh0Rp0h6sqSX18fJMPZNqS/S4PfNfknPjIjHSzpV0rNtP1nS79d9ebSkuyW9dAB9AYbL1ZnZXt+AUUPsdIj3aXTiplJ/pMHHB6MUN2X9kYid0EPDODP7JEnXR8R3I+KApA9Lev4Q+jESIuLLknYuuPv5ki6o/75A0guG2JehiIjtEXFl/fduSddJOlZD2DdJXwYuKvfV/5yubyHpmZI+Wt8/sGMGGD7OzWIsEDvVRiluSvozcKMUN3Xpz8ARO61uwxjMHivp5o5/36IhHdy1kPQ521fYPnuI/eh0dERsr/++TdLRw+yMpFfYvrqeSjOwqTvzbJ8k6QmSLtOQ982CvkhD2De2J21fJekOSZdKukHSroiYqR8y7PcUAKC3iJ1yoxY3SUOMnUYpblqkPxKxE3poKNfMjpifiIgfUTV15+W2nzbsDnWKKt30MFNOv0vSo1RNy9gu6S2D3LjtwyRdLOlVEXFvZ9ug980ifRnKvomI2Yg4VdJxqn6t/8FBbBcYNRbTjIEhGdnYaQTiJmmIsdMoxU2F/hA7oaeGMZi9VdLxHf8+rr5vKCLi1vr/d0j6uKoDfNhut32MJNX/v2NYHYmI2+sPgDlJ79EA94/taVUfgB+MiI/Vdw9l3yzWl2Hum3r7uyR9QdKPSdpsez47+VDfU8AgMckYY4LYKTcycZM0vPhglOKmUn+IndBrwxjMfk3SyXUGsTWSXizpU0Poh2xvtL1p/m9JPy3pm/lSA/EpSWfVf58l6ZPD6sj8B2Dt5zSg/WPbks6XdF1EvLWjaeD7ptSXYewb29tsb67/Xi/pp1Rdh/IFST9fP2yoxwwwSJyZxZggdsqNTNwkDS0+GJm4KesPsRN6beB1ZiNixvYrJH1W0qSk90bENYPuR+1oSR+v3m+akvShiPjMIDtg+0JJT5e01fYtkl4v6c2SLrL9Ukk3STp9iH15uu1TVU1LuVHSywbRF0lPkXSmpG/U1zhI0us0nH1T6ssZQ9g3x0i6oM5sOSHpooj4tO1rJX3Y9u9I+rqqLxBg1TPnUjEGiJ0eNEpxU9KfYcROoxQ3Zf0hdkJPuZo+DwBAuzz+CU+Mz37xqz1f7zGb11wxpFJtAABgGQZ+ZhYAgJ7hxCwAAGOLwSwAoLUYywIAML4YzAIAWomETQAAjDfqzAIAAAAAWoczswCA1iKbMQAA44vBLACgvRjLAgAwthjMAgBai7EsAADji8EsAKC1SAAFAMD4IgEUAAAAAKB1ODMLAGgpkwAKAIAxxplZAEArWQ/Wmu3lret27ffavsP2Nzvu22L7Utvfqf9/ZH2/bb/D9vW2r7b9I33bIQAAjBkGswAALM/7JD17wX2vkfT5iDhZ0ufrf0vScySdXN/OlvSuAfURAIBVj8EsAKC1hnFmNiK+LGnngrufL+mC+u8LJL2g4/73R+WrkjbbPqYnTx4AgDHHYBYAgJU7OiK213/fJuno+u9jJd3c8bhb6vsAAMAKkQAKANBafUoAtdX25R3/Pi8izlvqwhERtqMP/QIAAB0YzAIA2mmJ04Ib2BERpy1zmdttHxMR2+tpxHfU998q6fiOxx1X3wcAAFaIacYAgFZyn24NfUrSWfXfZ0n6ZMf9L6mzGj9Z0j0d05EBAMAKcGYWANBeQygza/tCSU9XNR35Fkmvl/RmSRfZfqmkmySdXj/8EknPlXS9pD2SfnngHQYAYJViMAsAwDJExBmFpmct8tiQ9PL+9ggAgPHEYBYA0Fp9SgAFAABagMEsAKC1+pQACgAAtACDWQBAazGWBQBgfJHNGAAAAADQOpyZBQC0F6dmAQAYWwxmAQCtRQIoAADGF4NZAEArWSSAAgBgnLkqgQcAQLvY/oykrX1Y9Y6IeHYf1gsAAHqIwSwAAAAAoHXIZgwAAAAAaB0GswAAAACA1mEwCwAAAABoHQazAAAAAIDWYTALAAAAAGid/x9NixA4dFxXfwAAAABJRU5ErkJggg== +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 3 con incertidumbre (Banda Azul)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [853]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_B3</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata3</span><span class="p">,</span> <span class="n">poptB3</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB3</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB3</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB3</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB3</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteB3</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptB3E</span><span class="p">,</span> <span class="n">pcovB3E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata3</span><span class="p">,</span> <span class="n">recorteB3</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">4</span><span class="p">,</span><span class="mi">4</span><span class="p">,</span><span class="mi">5</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">Err_B3</span><span class="p">)</span> +<span class="n">estrellaB3E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata3</span><span class="p">,</span> <span class="n">poptB3E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB3E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB3E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB3E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB3E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMB3E</span><span class="o">=</span><span class="n">FWHMB_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptB3E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 3 fotografÃa (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteB3</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 3 a partir de la gaussiana con incertidumbre (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaB3E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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Jukk+oPWuX562OazL66i6QHY/g4MXePNfMY/lB3/wlJ/fHM4FK1XKv+PRn5dzhTwz+bZv8ORsthpdTIMScitlTqXvw25+7yDeaao+5j2vRv+DGlfF953ZP9jqr1LlRErFHqLj2ylfyM/BrfM856JrK1Gshhu+ZXOyLui4h3RsQuSl0ePuvxR0UceeRtlaRDR/z4bpY/xPF8NK/rebnIeqtGnGsygRnK/eUbcK/SH5MkyfaWSl0JxopxvPnXqq4Lgm1reJcEadP3qMhrPUnpCOEBedla16ixlr9Z0nPHWllEPKxUJL4ux/8SpSTpSEnbRcQcSQ83GN9aSfPye1CzazOx2948x/DS/KVxn1LXjhfYfkGeZw+lIvzIiKj/onxMqStPzUQn3P+Z0gBhj0z0AoFKakUXY7oZd9Q0/a3+nNJAJovyuk9tYN3159/uqvR73ei6RusGO5HxlllbH0/+LayPb5VSF93693zziPjv8Tbo1N30G0qjlu6Uf5ev0NjvzbC8ZERME61r2O+nRwxYExG/ioglSt0zv6XUqqXc8nlSRPyJ0qlI/2D74FFia+YzrpnMvrdK0p+M8dywnE7D95tWWSVpe49+ju8qSWeM2C+2iIj6Lqcj97uJ9sPtcq5aU5+LjfyMe5VaXosY+Xe4UVJ/3bT6eCfzd7AyhegxD/jkFtLvKeexmnyeXG/k3/AWSvl+TcP7r+0XK3WTPqUujz1A0pv9zLnNRyn1JnljDB/ktZk89qaJXlzXFLO2/9rPnCj9oNIOWGti/4PG/nKo+bykM5y7C9ie68aG4t9aqbvAw3mnHfMyNLb/NB9Z3Nz2TNtvVdpZxzxBfISLJB1ne5/8xf5RSdflPwhp09c53vz/Kel5to/IO+cJmnina/i1jrHsE5IecjrB/rQJ5r9C43fl3UrSUXpm9OStlc53WC9phu1/UjqvphG/yMu+J38ub1A6F6WZ2I9QaiXYU6n7xz5Kf6w/VToCt42kbyt1kxvZve5GSX/pdN21bZW6hY/npUpfhMD0RcvstDJNf6u3lvSIpD/a/lNJjVw78UO5JWYvpXPgaue6NrOuRt638fynUjfCN+R84D0ang98Ximx3UuSbG9r+68bWO8spdN91ksacOqRNHIAnnqXSDrR9rxcPL1/Euu6Kb+GfZzGyji99oTtWbbfYnvbnHg/orzPOQ1g9JxcwD+s9Ps9WnfyZj6X+mUbzZ2+K2ln2+91GvBpa9sH5OcukvR/8j7fJ+mflFp5WybSiLPfUzrotF3+e6gVWf8h6V22D3Cype3XOp33O5Yx99WIuFvpvPQP58/sL/RMoSel08s2y9uYqXS+cNFLH77V9p65+PuIpEtj7MsENfx3EBEblM59Hi+PnS/pEA3PYyeTJ9e7VNLhtv/CaRyYj2h4DTiZ/fdYSVdpeB67t6TNJR3q1N34U0q9b9aPWPZGSW/I323PUTp3ezwN5bHT8Ve7Ngpa7fbNPP2Fkq6zXeuHfmJE/D4/d7qk8526Bhw5xno/kZe70vajSgMLHTDGvPU+rDRQwcNKPwiXjTOvcyzrlL6QT1S6dM2KcZZ5WkT8l1I/+G8oHYV5tlJBV3O66l7nePPnLrB/rXSi//1KO+1ypfMdynitI52t9IfQr/Tefn+C+S+QdJhTS2fN0yMBK3UH2V7pHBIpneT/faUvu7slPakGu7fkL503KF0O6AFJb9Lw1zaZ2I9VOqfhntwCcV9E3Kd0Ev9blIrkPZQGrvhj3etRRFyllNDcrDQAwncnCP1obTqYATC90DJbVd30W/2PSuMiPKqU4I81CFO9nyi13lwt6WMRcWWBdZ2uid+3MdXlA2cq5QOLJP287vlvSvp/ki526qJ4q9J5lBOt91GlwvgSpQMXb1b67MbyH0rnwd6sNHjPFUoHmgcnWlekQSc/olRA/E5142lkx0i6K8f/Lj2TOyzKy/xR6cD2ZyPiR6PE1sznUtPwvpdf56uUirj78mt5eX76/yrlaTdLukXSijyt1Y5RarH8tdLfxHtzrMuVBu36tNJnslIpjxrPvygV5A+5bhTvOm9W+nt+QKmYu6D2RO6R97+UrvSxRqkVcNQBlibhy0pXnbhP6SoWY3aZbeLv4Asafk6zJL2pLu/7ldLf2Yfzc2drcnlyfWy3KTVKfVUp339Qw9+bhvbffCDoSEmfqs9hI11B5MtKOe4SpQG2flb3/V4rSM+StEHpoMX5yl2Vx9jWzkq1x7cmen2OTc9jBzbhdCL3aklvGeOLvO1sf1TSuog4u9OxTDVOF+M+JiImnbgAVdGz7YKY/eJ/KH29T37/H66PiMUTzwmUy2kAxjslzRxxfiNGyK2vn4+Ihi4DBEw1tn+udJWPGzody1Rj+98l/U9EfHaieSt9kWK0lu3XKI0I/IRStxdr+KVuOioiTu10DFNVRHxHkx/lD6gY0y0Y6BK5J9bLlVpnd1JqmfvmuAsBU1hEHDTxXN0pIk5qdF6yAIznRUqj5vUrdWkpMrIuAJSPbsZAt7BSl8sHlboZ36F0XiiALkbLLMYUEadrgovGA0DHWLTMYlrJAzByRGUU+ZIwL+x0HACmFopZAEBF0c0YAIBuRhYAAAAAAKictrbM7rBDX8zftflB58o4lckFe+8MMfpzaabCqWlFP84ydoei+1RvT7E3sujy99x9l/r7+6fAp4muNBW+SIAW6uvri912W9jpMACU6G5yp9K0tZidv+tuuvInzQ+GO6Ng0i1JM3qLrePJjaNdK3tyBgaLraNo8SFJg0OdLaAkqafgOsr4Bij4NuiJDWNdO7txGwaK7Q9bblbsz3j7LWcWWv6gAzmFCR1EN2NMc7vttlA/v255p8MAUKKDDuDqb2XhnFkAQHXRMgsAQNfikDYAAAAAoHJomQUAVJMZzRgAgG5WKAuwfYjt39heafsDZQUFAEBD7PJvQAuROwFAeZouZm33SvqMpEMl7SnpaNt7lhUYAAATsV36bYLtLbD9I9u3277N9ol5+r/Z/rXtm21/0/acumVOyYXLb2y/prXvCKYycicAKFeRltn9Ja2MiN9HxAZJF0taUk5YAACMz2p/MStpQNJJEbGnpAMlnZCLkask7R0Rz5f0W0mnKMW3p6SjJO0l6RBJn80FDboTuRMAlKhIMTtP0qq6x6vztGFsL7W93PbyB+7vL7A5AAA6KyLWRsSKfP9RSXdImhcRV0bEQJ7tWknz8/0lki6OiKci4k5JK5UKGnSnSedO6/vXty04AKialo+cERHLImJxRCzefoe+Vm8OANAt3KJbo5u3F0raV9J1I556h6Tv5fsNFS9AvfrcaW7f3E6HAwBTVpHRjNdIWlD3eH6eBgBAGzTULbgZfbaX1z1eFhHLhm3Z3krSNyS9NyIeqZv+QaWuyBe2IjBUHrkTAJSoSDH7K0mLbO+u9EV8lKQ3lxIVAAANaFEx2x8Ri8fZ5kylQvbCiLisbvrbJR0u6eCIiDyZ4gX1yJ0AoERNF7MRMWD73ZJ+IKlX0rkRcVtpkQEAMIEWFbPjbc+SzpF0R0R8vG76IZJOlvTSiHi8bpHLJX3V9scl7SJpkaRftjFkTCHkTgBQriIts4qIKyRdUVIsAABMdQdJOkbSLbZvzNNOlfRJSbMlXZUL7Gsj4l0RcZvtSyTdrtT9+ISIGGx/2JgqyJ0AoDyFilkAADqp3S2zEfEzjT5M1JjFSUScIemMlgUFAECXamsxO6PH2naLmU0v/9iTAxPPNIEnNw4VWn5gKCaeaQK9PcWSr+IRSCqYAM7sLT4Q9swZLR9Me0IbB4vtDz0FP0up+Oc5WHCffHxDsUaioShljwQmb5KjDwMAgOmFllkAQCW5daMZAwCACqCYBQBUFsUsAADdq/P9PAEAAAAAmCRaZgEAlUXLLAAA3YtiFgBQWRSzAAB0L4pZAEA1MZoxAABdjXNmAQAAAACVQ8ssAKCy6GYMAED3opgFAFQS15kFAKC7UcwCACqLYhYAgO5FMQsAqC5qWQAAuhYDQAEAAAAAKoeWWQBANZluxgAAdDOKWQBAZVHMAgDQvShmAQCVRTELAED3opgFAFQSl+YBAKC7tbWYHQrpqY2Dza+ghJwlIgotPzRUbHlJ2lhwHWXkbjN6iq1k4+BQ8SCKvo7iH4UGC+4PZaTRM3uLraW34GdZdF8ww8kCAACgA2iZBQBUF8dSAADoWhSzAIBqYjRjAAC6GsUsAKCyKGYBAOheFLMAgMqimAUAoHv1NLug7QW2f2T7dtu32T6xzMAAAACmE3InAChXkZbZAUknRcQK21tLut72VRFxe0mxAQAwPhpmUS3kTgBQoqaL2YhYK2ltvv+o7TskzZPEFzIAoC3oZowqIXcCgHKVcs6s7YWS9pV0XRnrAwBgIrYpZlFZ5E4AUFzT58zW2N5K0jckvTciHhnl+aW2l9tefn//+qKbAwAAqLTJ5E7ryZ0AYEyFilnbM5W+jC+MiMtGmycilkXE4ohYvEPf3CKbAwBgmFrrbJk3oJUmmzvNJXcCgDE13c3Y6Rf/HEl3RMTHywsJAIDGUHyiSsidAKBcRVpmD5J0jKRX2L4x3w4rKS4AACbmFtyA1iF3AoASFRnN+GfiZx8A0EHtbpm1vUDSBZJ2khSSlkXEJ2xvL+lrkhZKukvSkRHxYG6J+4SkwyQ9LuntEbGirUFjyiB3AoByFR4ACgCALlK7Tuiekg6UdILtPSV9QNLVEbFI0tX5sSQdKmlRvi2V9Ln2hwwAwPREMQsAqCa3fwCoiFhba1mNiEcl1a4TukTS+Xm28yUdke8vkXRBJNdKmmN75xa8GwAAdJ1SrjPbqFBow8BQOze5iQ2DUWj5iGLLS9LM3mI9jHp7ivdQ6im4jic3Fv8cZxbc+waGin8WRXsoFv0sk2LHlIrGULibJh3m0CFW8b/hQtsffp3QnSJibX7qPqVuyFIqdFfVLbY6T1srAA0bKvibP1RC/lb097KM/A3AcG0tZgEAKE/LLqXTZ3t53eNlEbFs2JZHXCe0Po6ICNvFM2cAADAuilkAQGW1qGW2PyIWj73NUa8T+gfbO0fE2tyNeF2evkbSgrrF5+dpAACgIM6ZBQCgQeNcJ/RyScfm+8dK+nbd9Lc5OVDSw3XdkQEAQAG0zAIAKqvdl+bRM9cJvcX2jXnaqZLOlHSJ7eMl3S3pyPzcFUqX5VmpdGme49oaLQAA0xjFLACgmtz+AaAmuE7owaPMH5JOaGlQAAB0KYpZAEAlWcVHZgcAANVFMQsAqKxOXpoHAAB0FgNAAQAAAAAqh5ZZAEBldWAAKAAAMEVQzAIAqqkDA0ABAICpg2IWAFBJFi2zAAB0M4pZAEBFmWIWAIAuxgBQAAAAAIDKoWUWAFBZNMwCANC9KGYBAJVFN2MAALoXxSwAoJoYzRgAgK7W1mLWtmbP7G16+Y0DQ4VjGBgsto6ZvcVPM37wsY2Flr/3kScKxzB3y9mFlt9h62LLS9LsGcXey15H4RiKGuwpHkOo2D45NFQshqc2DhZaPqLznwMAYOoqmntJ0gN/3FBo+fWPFltekrbZvFjavOM2JeROBfJoYDqiZRYAUElcmgcAgO5GMQsAqCxqWQAAuhfFLACgsmiZBQCge1HMAgAqi1oWAIDuVXg0I9u9tm+w/d0yAgIAAJjOyJ0AoBxltMyeKOkOSduUsC4AABpjuhmjssidAKAEhVpmbc+X9FpJXywnHAAAGpNGMy7/BrQSuRMAlKdoy+zZkk6WtHXxUAAAmAzTMosqOlvkTgBQiqZbZm0fLmldRFw/wXxLbS+3vfz+9eub3RwAAJugZRZV0kzutL6f3AkAxlKkm/FBkl5v+y5JF0t6he2vjJwpIpZFxOKIWLzD3LkFNgcAAFBpk86d5vaROwHAWJouZiPilIiYHxELJR0l6YcR8dbSIgMAYAK2S78BrULuBADl4jqzAIBqolswAABdrZRiNiJ+LOnHZawLAIBGpNGMqWZRTeROAFAcLbMAgMqimAUAoHsVus4sAAAAAACd0NaW2aGh0KNPbGx6+Z6e4kfgt5xd7CVHROEYzrthdaHlP3PezwvH8JpDX1Bo+U+94XmFYxgYLPZebhgcKhxDb8FWnd4S9skZJayjiJm9xY5pWbSMoXNomAVar2ju89hTg4VjuOy2ewstf+aXVxSO4bWv3KPQ8h86eFHhGHbcpthvdhm5NDCV0M0YAFBZdDMGAKB7UcwCAKqJ0YwBAOhqnDMLAMAk2D7X9jrbt9ZN28f2tbZvtL3c9v55um1/0vZK2zfb3q9zkQMAML1QzAIAKsmy7PJvDThP0iEjpv2rpA9HxD6S/ik/lqRDJS3Kt6WSPlfGawcAABSzAIAKs8u/TSQirpH0wMjJkrbJ97eVVButZomkCyK5VtIc2zuX8+oBAOhunDMLAKisntacNNtne3nd42URsWyCZd4r6Qe2P6Z0oPjFefo8Savq5ludp60tKVYAALoWxSwAoLJaNABUf0QsnuQyfyfpfRHxDdtHSjpH0ivLDw0AANTQzRgAgOKOlXRZvv91Sfvn+2skLaibb36eBgAACqKYBQBUUjrHtSMDQI3mXkkvzfdfIel3+f7lkt6WRzU+UNLDEUEXYwAASkA3YwBAZfV04Dqzti+S9DKlc2tXSzpN0jslfcL2DElPKo1cLElXSDpM0kpJj0s6ru0BAwAwTVHMAgAqq0BLatMi4ugxnvrzUeYNSSe0NiIAALoTxSwAoLI6UMsCAIApgnNmAQAAAACVQ8ssAKCSLMmiaRYAgG5FMQsAqKxODAAFAACmBopZAEA1FbuUDgAAqLi2FrODQ6E/PjXY9PJbze4tHMOMGcUSnyghcVr78JPFVvD7GwrHsGrtnxRafiiicAyPbWh+X5CkjQNDhWOYPbPYaeNb9BbfJ2fNKBbDUMGPYkZvsX2aWgKdxP4HTH0DRX+oJN3+h8cLLf/w8h8Xj+E5cwstv6GEvAXAcAwABQAAAACoHLoZAwAqyZJ6aJoFAKBrUcwCACqLWhYAgO5FMQsAqCwGgAIAoHsVOmfW9hzbl9r+te07bL+orMAAAACmG3InAChP0ZbZT0j6fkS80fYsSVuUEBMAABOy6WaMSiJ3AoCSNF3M2t5W0l9KerskRcQGSRvKCQsAgIkxABSqhNwJAMpVpJvx7pLWS/qS7Rtsf9H2liXFBQDAhNyCG9BC5E4AUKIixewMSftJ+lxE7CvpMUkfGDmT7aW2l9te/uD9/QU2BwDAcLZLvwEtNOncaX3/+nbHCACVUaSYXS1pdURclx9fqvQFPUxELIuIxRGxeLsd+gpsDgAAoNImnTvN7Zvb1gABoEqaLmYj4j5Jq2zvkScdLOn2UqICAGACltTj8m9Aq5A7AUC5io5m/PeSLsyj8f1e0nHFQwIAoAF0C0Y1kTsBQEkKFbMRcaOkxeWEAgDA5FDLomrInQCgPEVbZgEA6BhaZgEA6F5FBoACAAAAAKAj2toyO7O3RzttM7vp5Z/YOFg4hgcf21ho+R22mlU4hqUv3LXQ8ve/85jCMbz2+TsWWj6icAia2VusRWVoqHiLTNE1lNEqNDRU7M3cODhUaPmBgn9WQ2XsDEATagNAAWitor91W87qLRzD0sULCi3/7I+/r3AMf/6sbQstv92WMwvHQGcUYDi6GQMAKotuxgAAdC+KWQBAZVHKAgDQvShmAQCVZEs9tMwCANC1GAAKAAAAAFA5tMwCACqLhlkAALoXxSwAoLIYAAoAgO5FMQsAqCxqWQAAuhfnzAIAMAm2z7W9zvatI6b/ve1f277N9r/WTT/F9krbv7H9mvZHDADA9ETLLACgkix3ajTj8yR9WtIFT8div1zSEkkviIinbO+Yp+8p6ShJe0naRdJ/2X5uRAy2PWoAAKYZWmYBANXk1M247NtEIuIaSQ+MmPx3ks6MiKfyPOvy9CWSLo6IpyLiTkkrJe1f2nsAAEAXo5gFAFSW7dJvTXqupJfYvs72T2y/ME+fJ2lV3Xyr8zQAAFAQ3YwBAJXVoiOyfbaX1z1eFhHLJlhmhqTtJR0o6YWSLrH9J60JDwAASBSzAACM1B8Riye5zGpJl0VESPql7SFJfZLWSFpQN9/8PA0AABREN2MAQCVZU6qb8bckvVwppudKmiWpX9Llko6yPdv27pIWSfpl4RcPAABomQUAVFdPBwYztn2RpJcpdUdeLek0SedKOjdfrmeDpGNzK+1tti+RdLukAUknMJIxAADloJgFAFRWJ4rZiDh6jKfeOsb8Z0g6o3URAQDQndpazA5F6LGnBppefuNgFI6hp2Dmc/8fNxSOYadtZhda/qwj9i4cw+azegstv/XmxXedNQ88UWj5Gb3Fe8lvtVmx1zFzYKhwDEX1Fr3OZkcu0wkUly6lww4MTHWzZxb/vV70rK0KLb9b3xaFY5hZMO+YNaP4+8B3HjAc58wCAAAAACqHbsYAgMrqRDdjAAAwNVDMAgAqix53AAB0L4pZAEAlWVIP1SwAAF2r0Dmztt9n+zbbt9q+yPZmZQUGAMBEelpwA1qJ3AkAytP077bteZLeI2lxROwtqVfSUWUFBgAAMJ2QOwFAuYp2M54haXPbGyVtIene4iEBANAYehmjgsidAKAkTbfMRsQaSR+TdI+ktZIejogrywoMAIDx2FZPC25Aq5A7AUC5inQz3k7SEkm7S9pF0pa23zrKfEttL7e9/P7+9c1HCgDACHb5N6BVmsmd1pM7AcCYiox18UpJd0bE+ojYKOkySS8eOVNELIuIxRGxeIe+uQU2BwDAcD0u/wa00KRzp7nkTgAwpiLF7D2SDrS9hW1LOljSHeWEBQAAMO2QOwFAiZoeACoirrN9qaQVkgYk3SBpWVmBAQAwHq4zi6ohdwKAchUazTgiTpN0WkmxAAAwKdSyqBpyJwAoT9FL8wAA0Bmc4woAQFcrcs4sAAAAAAAd0faW2d4ih9FL6E82s/AaihsYHOp0CIXPM9s4UPw1zNlyVqHlC+1L2WYzih3PmT2z+PGggcEotHyxpYuzaBpD57D/AVOfS8jfZs/s7ejyAKYmuhkDACopDQDV6SgAAECnUMwCACqLYhYAgO5FMQsAqKwyui8CAIBqYgAoAAAAAEDl0DILAKgkzpkFAKC7UcwCAKrJpQxyDwAAKopiFgBQWUUvMwYAAKqLYhYAUEl0MwYAoLsxABQAAAAAoHJomQUAVBa9jAEA6F4UswCAirJ6RDULAEC3opgFAFSSRcssAADdjGIWAFBNZgAoAAC6GQNAAQAwCbbPtb3O9q2jPHeS7bDdlx/b9idtr7R9s+392h8xAADTE8UsAKCyeuzSbw04T9IhIyfaXiDp1ZLuqZt8qKRF+bZU0ucKv2gAACCJYhYAUFG1c2bLvk0kIq6R9MAoT50l6WRJUTdtiaQLIrlW0hzbOxd/9QAAoK3nzNpSb4ETnGaWcHLUxoGhQss/VXB5SYqYeJ7xzJ5Z/BhEg60PYxoYLP4+bL1Z50/Zntlb7H0osj/XDBXcHzqOcxbRQUW/y8pie4mkNRFxk4fHNE/SqrrHq/O0tW0MDwCAaanz1QQAAFNLn+3ldY+XRcSysWa2vYWkU5W6GAMAgDahmAUAVFaLGmb7I2LxJOZ/tqTdJdVaZedLWmF7f0lrJC2om3d+ngYAAAqimAUAVJI1NQZ+iIhbJO1Ye2z7LkmLI6Lf9uWS3m37YkkHSHo4IuhiDABACShmAQDVZMkdOGfW9kWSXqbUHXm1pNMi4pwxZr9C0mGSVkp6XNJxbQkSAIAuMGExa/tcSYdLWhcRe+dp20v6mqSFku6SdGREPNi6MAEA2FQnhn+KiKMneH5h3f2QdEKrY8LUQu4EAO3RSA+t87Tp9fQ+IOnqiFgk6er8GAAAAOROANAWExazY1xPb4mk8/P98yUdUW5YAACMz0qX5in7BhRF7gQA7dHs2Bk71Q1gcZ+kncaa0fZS28ttL7+/v7/JzQEAsCm34Aa0SFO50/r+9e2JDgAqqPBAkPl8oBjn+WURsTgiFu/Q11d0cwAAPM0u/wa02mRyp7l9c9sYGQBUS7OjGf/B9s4Rsdb2zpLWlRkUAAATc0dGMwaaRO4EACVrtmX2cknH5vvHSvp2OeEAAABMS+ROAFCyCYvZfD29X0jaw/Zq28dLOlPSq2z/TtIr82MAANrGSj9iZd+AosidAKA9JuxmPM719A4uORYAACaFbsaYisidAKA9mj1nFgCAjqOUBQCge1HMAgCqybTMAgDQzdpezPb0NJ94DA2NOYp9wzYMFlvHw49vLBzDjN5iZ2XNnFH8rK6CIZRiYHCo0PIl7A4qeoZcGTEU3a9n9BZL5nsKFgOUEgAAAOgEWmYBAJVUGwAKAAB0J4pZAEBl0c0YAIDuRTELAKgsSlkAALoXPbQAAAAAAJVDyywAoLLoZQwAQPeimAUAVFIaAIpqFgCAbkUxCwCoLFpmAQDoXhSzAICKskzLLAAAXYsBoAAAAAAAlUPLLACgsuhmDABA96KYBQBUEgNAAQDQ3ShmAQDVZFpmAQDoZhSzAIDKopgFAKB7MQAUAAAAAKByaJkFAFQWl+YBAKB7UcwCACrJknqoZQEA6FptLWYjpIHBaOcmNzEwOFRo+aHOhl+a3oInmm0s4US1wYJvZhkfxdAU+ECLxlD4o+BkA1QYLbMAAHQvWmYBAJXFAFAAAHQv2mQAAAAAAJVDMQsAqCy34N+E27TPtb3O9q110/7N9q9t32z7m7bn1D13iu2Vtn9j+zWteScAAOg+FLMAgEqqDQBV9q0B50k6ZMS0qyTtHRHPl/RbSadIku09JR0laa+8zGdt95bzDgAA0N0mLGYnewQaAID2aEW77MTVbERcI+mBEdOujIiB/PBaSfPz/SWSLo6IpyLiTkkrJe1f3nuAqYjcCQDao5GW2fPU4BFoAACmgT7by+tuSye5/DskfS/fnydpVd1zq/M0TG/nidwJAFpuwtGMI+Ia2wtHTLuy7uG1kt5YclwAAIzPLRvNuD8iFjezoO0PShqQdGG5IaFKyJ0AoD3KOGe2/gj0JmwvrR3dfuD+/hI2BwBA4hbcmo7FfrukwyW9JSJqF5BeI2lB3Wzz8zR0t4Zzp/X969sYFgBUS6FitpEj0BGxLCIWR8Ti7XfoK7I5AACelgaAcum3pmKxD5F0sqTXR8TjdU9dLuko27Nt7y5pkaRfFn3tqK7J5k5z++a2LzgAqJgJuxmPpe4I9MF1R6ABAGib1vQynmCb9kWSXqZ0bu1qSacpnf84W9JVTgXxtRHxroi4zfYlkm5XKmBOiIjBDoSNKYDcCQDK1VQxW3cE+qUjjkADADCtRcTRo0w+Z5z5z5B0RusiQhWQOwFA+Rq5NM9Fkn4haQ/bq20fL+nTkrZWOgJ9o+3PtzhOAAA2NZVOmgUycicAaI9GRjOe1BFoAADapZHrwgLtRu4EAO3R9DmzAAB0WosuzQMAACqAYhYAUFnUsgAAdK+2FrMR0oaBoaaXnzWj+GVxN5/VW2j5Gb3FY+gtmH3NKrqCEszoKR7D7IKf52AJA0H2FmzWKaNVaKjgOoq+DYNDxVbAeJwAAADoBFpmAQDV1fljewAAoEMoZgEAlZQGH6aaBQCgW1HMAgCqyQwABQBAN6OYBQBUFrUsAADdq/hoRgAAAAAAtBktswCA6qJpFgCArkUxCwCoKDMAFAAAXYxiFgBQWQwABQBA96KYBQBUkkUvYwAAuhkDQAEAAAAAKoeWWQBAddE0CwBA16KYBQBUFgNAAQDQvShmAQCVxQBQAAB0L86ZBQAAAABUDi2zAIDKomEWAIDuRTELAKgmrs0DAEBXa2sx29MjzZ7ZfM/mMnKWGb3FelZvNrPzmdPA4FDhdQxFFFp+1oziPdR7eoq9ly72EiRJvQVjKMNQCa+jytsHimAAKAAAuhctswCASrIYAAoAgG7GAFAAAAAAgMqhZRYAUFk0zAIA0L0mbJm1fa7tdbZvHeW5k2yH7b7WhAcAwDjcghtQELkTALRHI92Mz5N0yMiJthdIerWke0qOCQCAhrgF/4ASnCdyJwBouQmL2Yi4RtIDozx1lqSTJTEWKgCgI+zyb0BR5E4A0B5NDQBle4mkNRFxU8nxAAAATDvkTgBQvkkPAGV7C0mnKnWTaWT+pZKWStL8BbtOdnMAAIyJhlRUQZHcacGu5E4AMJZmWmafLWl3STfZvkvSfEkrbD9rtJkjYllELI6IxTv0MdYBAKBEHRgAarTBfWxvb/sq27/L/2+Xp9v2J22vtH2z7f3KeeGomKZzp7l9c9sYJgBUy6SL2Yi4JSJ2jIiFEbFQ0mpJ+0XEfaVHBwDAGFLt2ZEBoM7TpoP7fEDS1RGxSNLV+bEkHSppUb4tlfS5Ml47qoXcCQBao5FL81wk6ReS9rC92vbxrQ8LAIAJtGDwp0YGgBpjcJ8lks7P98+XdETd9AsiuVbSHNs7l/L6MWWROwFAe0x4zmxEHD3B8wtLiwYAgM7rs7287vGyiFg2wTI7RcTafP8+STvl+/Mkraqbb3WetlaYtsidAKA9Jj0AFAAAU0WLBoDqj4jFzS4cEWGbS68AANBiTV2aBwCAKaEDA0CN4Q+17sP5/3V5+hpJC+rmm5+nAQCAgihmAQAV1Yrhn5quZi+XdGy+f6ykb9dNf1se1fhASQ/XdUcGAAAFtLWb8U03rOjfaZtZd48zS5+k/nbFQwxTOoZOb58YGo9ht3YFAkwFeXCflymdW7ta0mmSzpR0SR7o525JR+bZr5B0mKSVkh6XdFzbA0alrVhxff/mM03uNPVj6PT2iaFaMZA7laStxWxEjHuxNNvLi5ynVAZimBoxdHr7xDC1YgDG0sjow2UbZ3Cfg0eZNySd0NqIMJ2RO1Ujhk5vnxiIoVsxABQAoJKKneIKAACqjmIWAFBdVLMAAHStqVbMTnQdv3YghqTTMXR6+xIx1EyFGIBRFRiwCZgupsJ3NDF0fvsSMdQQQxdxOp0HAIBqef4+fx7fufq/S1/vwr7NrudcJwAApr6p1jILAEDDOjEAFAAAmBooZgEAlUUtCwBA9+rpdAA1tg+x/RvbK21/oAPbX2D7R7Zvt32b7RPbHUOOo9f2Dba/26Htz7F9qe1f277D9os6EMP78mdwq+2LbG/Whm2ea3ud7Vvrpm1v+yrbv8v/b9eBGP4tfxY32/6m7TntjqHuuZNsh+2+VsYANMypZbbsG1AF5E3DYiF3Incid+pSU6KYtd0r6TOSDpW0p6Sjbe/Z5jAGJJ0UEXtKOlDSCR2IQZJOlHRHB7Zb8wlJ34+IP5X0gnbHYnuepPdIWhwRe0vqlXRUGzZ9nqRDRkz7gKSrI2KRpKvz43bHcJWkvSPi+ZJ+K+mUDsQg2wskvVrSPS3ePjBJbsENmNrImzZB7kTuVI/cqYtMiWJW0v6SVkbE7yNig6SLJS1pZwARsTYiVuT7jyp9Ec1rZwy250t6raQvtnO7ddvfVtJfSjpHkiJiQ0Q81IFQZkja3PYMSVtIurfVG4yIayQ9MGLyEknn5/vnSzqi3TFExJURMZAfXitpfrtjyM6SdLIkRowDgM4jb8rInZ5G7vTMNHKnLjJVitl5klbVPV6tDnwh1theKGlfSde1edNnK+30Q23ebs3uktZL+lLurvNF21u2M4CIWCPpY0pHsdZKejgirmxnDHV2ioi1+f59knbqUBw175D0vXZv1PYSSWsi4qZ2bxsYj0U3Y3Qt8qZnnC1yJ3KnsZE7TXNTpZidMmxvJekbkt4bEY+0cbuHS1oXEde3a5ujmCFpP0mfi4h9JT2m1ncPGSafW7FE6cdhF0lb2n5rO2MYTaRrWHXsyJrtDyp16bqwzdvdQtKpkv6pndsFGkUnY6CzOpU35W2TO4ncaSzkTt1hqhSzayQtqHs8P09rK9szlb6QL4yIy9q8+YMkvd72XUrdhV5h+yttjmG1pNURUTuyeqnSF3Q7vVLSnRGxPiI2SrpM0ovbHEPNH2zvLEn5/3WdCML22yUdLukt0f4LQz9b6cfxprxvzpe0wvaz2hwHMCpaZtGlyJsScqeE3GkEcqfuMVWK2V9JWmR7d9uzlE5av7ydAdi20vkOd0TEx9u5bUmKiFMiYn5ELFR6/T+MiLYeVYuI+yStsr1HnnSwpNvbGYNSF5kDbW+RP5OD1blBHS6XdGy+f6ykb7c7ANuHKHWfen1EPN7u7UfELRGxY0QszPvmakn75X0F6Di34B9QAV2fN0nkTnXIneqQO3WXKVHM5pO03y3pB0p/fJdExG1tDuMgSccoHdW7Md8Oa3MMU8HfS7rQ9s2S9pH00XZuPB/ZvFTSCkm3KO2jy1q9XdsXSfqFpD1sr7Z9vKQzJb3K9u+Ujnqe2YEYPi1pa0lX5X3y8x2IAQAwhZA3TTnkTuRO5E4d4va3vAMAUNwL9v3z+MFPri19vTtvO+v6iFhc+ooBAECpZnQ6AAAAmkWnYAAAuhfFLACgkhiwCQCA7jYlzpkFAAAAAGAyaJkFAFQWow8DANC9KGYBANVFLQsAQNeimAUAVBa1LAAA3YtiFgBQWQwABQBA92IAKAAAAABA5dAyCwCoKDMAFAAAXYxiFgBQSRbdjAEA6GZ0MwYAAAAAVA4tswCAyqJlFgCA7kXLLAAAAACgcmiZBQBUFgNAAQDQvWiZBQBUk1M347JvE27Wfp/t22zfavsi25vZ3t32dbZX2v6a7VmtfwMAAOhuFLMAgEpyi27jbtOeJ+k9khZHxN6SeiUdJen/STorIp4j6UFJx5f1OgEAwOgoZgEA1dXuajaZIWlz2zMkbSFpraRXSLo0P3++pCMKvjIAADABilkAABoUEWskfUzSPUpF7MOSrpf0UEQM5NlWS5rXmQgBAOgeFLMAgMpyC/5J6rO9vO629Ont2dtJWiJpd0m7SNpS0iEdefEAAHQ5RjMGAFRWi64z2x8Ri8d47pWS7oyI9Wn7vkzSQZLm2J6RW2fnS1rTksgAAMDTaJkFAFRWB06ZvUfSgba3sG1JB0u6XdKPJL0xz3OspG+X8PIAAMA4KGYBAGhQRFynNNDTCkm3KP2OLpP0fkn/YHulpB0kndOxIAEA6BJ0MwYAVFdruhmPKyJOk3TaiMm/l7R/+6MBAKB7UcwCACrLnahmAQDAlEAxCwCoJKtlA0ABAIAKcER0OgYAACbN9vcl9bVg1f0RweV2AACY4ihmAQAAAACVw2jGAAAAAIDKoZgFAAAAAFQOxSwAAAAAoHIoZgEAAAAAlUMxCwAAAAConP8PEquVTNW/sFIAAAAASUVORK5CYII= +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 4 con incertidumbre (Banda Azul)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [854]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_B4</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata4</span><span class="p">,</span> <span class="n">poptB4</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB4</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB4</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB4</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB4</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteB4</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptB4E</span><span class="p">,</span> <span class="n">pcovB4E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata4</span><span class="p">,</span> <span class="n">recorteB4</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">2</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">Err_B4</span><span class="p">)</span> +<span class="n">estrellaB4E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata4</span><span class="p">,</span> <span class="n">poptB4E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB4E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB4E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB4E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB4E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMB4E</span><span class="o">=</span><span class="n">FWHMB_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptB4E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 4 fotografÃa (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteB4</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 4 a partir de la gaussiana con incertidumbre (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaB4E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 5 con incertidumbre (Banda Azul)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [855]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_B5</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata5</span><span class="p">,</span> <span class="n">poptB5</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB5</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB5</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB5</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB5</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteB5</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptB5E</span><span class="p">,</span> <span class="n">pcovB5E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata5</span><span class="p">,</span> <span class="n">recorteB5</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">2</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span> <span class="n">sigma</span><span class="o">=</span><span class="n">Err_B5</span><span class="p">)</span> +<span class="n">estrellaB5E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata5</span><span class="p">,</span> <span class="n">poptB5E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB5E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB5E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB5E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB5E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMB5E</span><span class="o">=</span><span class="n">FWHMB_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptB5E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 5 fotografÃa (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteB5</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 5 a partir de la gaussiana con incertidumbre (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaB5E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 6 con incertidumbre (Banda Azul)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [856]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_B6</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata6</span><span class="p">,</span> <span class="n">poptB6</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB6</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB6</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB6</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB6</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteB6</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptB6E</span><span class="p">,</span> <span class="n">pcovB6E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata6</span><span class="p">,</span> <span class="n">recorteB6</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span> <span class="n">sigma</span><span class="o">=</span><span class="n">Err_B6</span><span class="p">)</span> +<span class="n">estrellaB6E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata6</span><span class="p">,</span> <span class="n">poptB6E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB6E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB6E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB6E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB6E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMB6E</span><span class="o">=</span><span class="n">FWHMB_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptB6E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 6 fotografÃa (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteB6</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 6 a partir de la gaussiana con incertidumbre (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaB6E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 7 con incertidumbre (Banda Azul)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [857]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_B7</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata7</span><span class="p">,</span> <span class="n">poptB7</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB7</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB7</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB7</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB7</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteB7</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptB7E</span><span class="p">,</span> <span class="n">pcovB7E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata7</span><span class="p">,</span> <span class="n">recorteB7</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">3</span><span class="p">,</span><span class="mi">3</span><span class="p">,</span><span class="mi">3</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">Err_B7</span><span class="p">)</span> +<span class="n">estrellaB7E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata7</span><span class="p">,</span> <span class="n">poptB7E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB7E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB7E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB7E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB7E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMB7E</span><span class="o">=</span><span class="n">FWHMB_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptB7E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 7 fotografÃa (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteB7</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 7 a partir de la gaussiana con incertidumbre (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaB7E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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NPg9poHr5d0YkQsUKoxOM6p6ZVsz1VqznlrZf6DlZqCzVeqefhsJ3fBZDNJr9WfVRpQZH5O++Sx0lYq3A/aTel63W5awzVfHctoy9xezU++Flbzt0ypaW11n28ZEb8YbYVOzUTPUxoldOd8Xb5QI++bIeWSljyNldaQ66dbBo6JiF9FxKFKzSq/o1RLpVyTeWJE/JlSF6J/sH3gMHmbyHc8aDzH3jJJfzbCZ0PKdBp63NRlmaQdPXwf3GWSPthyXGwVEdWmoq3H3VjH4Q65rDqoWhZr/Y6nKtWkbo7W3+E6Sasq06r5Hc/vYGnKoke8sZNrPL+vXI7V+MvJVa2/4a2UyvuD2j5+bT9T6Xp2UqUc+3RJb/CmvseHK7UOeU0MHWx1IuXY/x1r4yZd0Gr7td7UYflupQNtsGr8jxr5JDDoc5I+6FzNb3snp/brY9lWqZr/3nxwtvN4l/+T8/jjNuatOkvS0bb3zifwD0m6IjYNDtG6naPN/1+Snmz7lfkgPE5jH1wT2dbqsmsk3ePU0f19Y8x/oUZvgruNpMO1abTibZUKmyslTbP9z0r9XtrxP3nZt9uebvtVSn1FJpL3Vyrd9V+g1Gxjb6Uf5U+V7qhtJ+k/lZq3tTaLu1rSc5wet7C9UnPu0TxX6YQHTF5drmmNiNsjNx3MTbSWaNOd9E8o3RyrFmQOlfTVSC5XujO+S0f3wSQySa/V20q6T9L9tv9cUjvPHnxvrlnZS6mP2mBf1Imk1c5+G81/KTX/e1UuD7xdQ8sDn1MqwO4lSba3t/3aNtKdodRNZ6Wk9U4tjFoHwqk6R9LxtmfnIOld40jrf/M27O00lsUpgx/YnmH7jba3zwXs+5SPOaeBhJ6QA/V7la7fG/VoE/leqsu2e+x9T9Iutk9wGnhpW9tPz5+dJemf8jE/IOmflWptaxNphNfvK91c2iGXkQaDqS9IOtb2051sbftlTv1yRzLisRoRt0haLOn9+Tt7ljYFdFLqFrZFXsd0pf68m/tIwTfZXpCDvA9IOjdGfvxO27+DiHhYqW/yaOXYOZIO0tBy7HjKyVXnSjrE9rOcxmn5gIbGeuM5fo+SdImGlmOfJGlLSQc7NRP+D6XWNCtblr1a0qvyue0JSn2rR9NWObafg9bBUccGX9/O058m6Qrbg+3Ej4+IG/Nnp0j6ilOV/mEjpPvJvNzFtlcrDfDz9BHmrXq/0oAB9yqd+M9vY5mjlNrRj+tuaUT8t1I79fOU7qo8XilwG3SKKts52vy56eprlTrc/0np4Fys1B9hJBPZ1kGnKh3wq5T27Q/GmP+rkl6a73QPemTkXaVmHDsq9fGQUmf7Hyid1G6R9JDabJaSTy6vUnrMzl2SXqeh2zaevB+l1Ofg1lyjcEdE3KHUmf6NSsHwnkoDSNxf2R5FxCVKBZdrlAYi+N4YWX+9Hj2oADC59HAgJqf+//soXVsOVepG0HpXeLaGnmuWq41mkw3QpGv1PyqNW7BaqSA/0mBIVT9Rqo35oaSPRcTFm5HWKRp7v42oUh74iFJ5YL6kn1c+/7ak/yfpbKemhb9RamEwVrqrlQLgc5SC/zcofXcj+YJSP9VrlAbRuVDphvKGsdKKNPjjB5QChd+rMt5FdoSkm3P+j9WmssP8vMz9SjewPxMRw92kmMj3MqjtYy9v54uUgrU78rY8P3/8r0rltGskXSvpqjytbkco1UD+VmkwrBNyXhcrDZ71KaXvZKlSOWo0H1YKvO9xZdTsijco/Z7vUgravjr4QW5h93dKT9ZYoVSrN+xAR+PwNaWnPNyh9NSIEZu6TuB38HkN7XMsSa+rlPt+pfQ7e3/+7FSNr5xczdt1SpVP31Aq79+tofumreM33/A5TNJ/VMuwkZ7Y8TWlc+KhSgNd/axyfh8MPD8h6WGlmxNfUW5iPMK6dlGKPb4z1vZ5nPESJjmnDtXLJb1xhBN219n+kKQ7I+LUXuelNE4PrT4iIsZdQAH6xZTt58bMZ/5DR9N86Af/cIuGNv9aFBGLWufLrTl+otRv5wdKtW0vjoh7bd8saWFErLL9PaWBPn6Wl/uhpHflAh0wRL4RcpOk6S39D9Ei16Z+LiLGHPAJKJHtnys9VePXvc5LaWz/u6Q/RMRnxpq3rx/yi86w/RKlEXjXKDVXsYY+QqanIuLkXuehVBHxXY1/VD2gz7itJr3jtCoiFo42Q256dp6kMyPifNtPlrSH0rMwpdTv7irb+ynd8a/2i5qjkccZADCC3LLq+Uq1rTsr1bR9e9SFgIJFxAFjz9VMEXFiu/P2c/NgdM4zlEapW6XUFGVzRrIFgM7rcvPg3LftdElLIuLjkhQR10bEYyNiXkTMU2qVsm9u+n+BUn91295f0r25HxiA8bFSU8m7lZoHL1HqtwmgwahphSLiFLXxcHUA6AmrjprWsRyg1A/pWttX52knR3ru4XAuVHqUxlKlRxAcXXsO0bfyQIjj61zdEJEetfK0XucDQFkIWgEAhaulefCoct/UUYOKXNs6+HcoDYABAAA6jObBAAAAAIBi1VLT+pjHDMTc3RnkbSzuQsugjTWPDr1xY/2jT6/bUP86Htow0uO4+sc2M+ptOLFi2a26+65VNGdDb4zzMTVAPxkYGIjdd5/X62wA6LCrrrpyVUTs1Ot8TAa1lHLn7r67LvlJvYPPuuYCzJQulI+mdKEQtnb9cM/G7pz71qyrNX1J+uO9oz0ytjOW3HVf7euYWnO7hgN2q/ec+OqXPKvW9IFRdb9PK9A1u+8+Tz+/gqcjAZPNltN9S6/zMFnQpxUAUD5qWgEAaCxuXQMAAAAAikVNKwCgbO7+6MEAAKAcBK0AgPLRPBgAgMYiaAUAFK/uwfcAAEC5CFoBAEWzCFoBAGgyOgkBAAAAAIrVVtBq+yDbN9heavvddWcKAIBHuIYXUDPKTgDQOWM2D7Y9VdKnJb1I0nJJv7J9QURcX3fmAACQTPNg9BXKTgDQWe3UtO4naWlE3BgRD0s6W9Kh9WYLAIBNbHf0BdSMshMAdFA7QetsScsq75fnaUPYPsb2YtuL/7RqVafyBwAAQSv6zZhlp2q5aeWqlV3NHAD0m44NxBQRiyJiYUQsfMzAQKeSBQAAmHSq5aadBnbqdXYAoGjtPPJmhaS5lfdz8jQAALqC2lH0GcpOANBB7dS0/krSfNt72J4h6XBJF9SbLQAAMkYPRv+h7AQAHTRmTWtErLf9NkkXSZoq6YyIuK72nAEAIMmMHow+Q9kJADqrnebBiogLJV1Yc14AABgWQSv6DWUnAOicjg3EBAAAAABAp7VV0woAQC9R0woAQHMRtAIAikfQCgBAcxG0AgDKxoi/AAA0Gn1aAQAAAADFoqYVAFA8mgcDANBctQStU2xtMX1qHUlvWseUegswD63bUGv6knT/2vW1r2OrGfV+D5PF/B22qX0dA1vPrDX9bbeo9x7U1Jp/c8BIeE4rAADNRk0rAKB4BK0AADQXQSsAoHzErAAANBYDMQEAAAAAikVNKwCgbKZ5MAAATUbQCgAoHkErAADNRdAKACgeQSsAAM1F0AoAKBqPvAEAoNkYiAkAgBa259r+se3rbV9n+/g8/d9s/9b2Nba/bXtWZZmTbC+1fYPtl/Qs8wAATDIErQCA8rnDr7Gtl3RiRCyQtL+k42wvkHSJpCdFxFMk/U7SSZKUPztc0l6SDpL0GdtTN3OrAQCACFoBAKXLowd38jWWiLg9Iq7Kf6+WtETS7Ii4OCLW59kulzQn/32opLMjYm1E3CRpqaT9Or4vAABoIPq0AgCK18s+rbbnSdpH0hUtH/2VpG/mv2crBbGDludpAABgMxG0AgCKV0PQOmB7ceX9oohYNMx6t5F0nqQTIuK+yvT3KDUhPrPTGQMAAEMRtAIAmmhVRCwcbQbb05UC1jMj4vzK9DdLOkTSgRERefIKSXMri8/J0wAAwGaiTysAoHxdHojJqWr3dElLIuLjlekHSXqnpFdExIOVRS6QdLjtmbb3kDRf0i8nvL0AAOAR1LQCAIrXgz6tB0g6QtK1tq/O006WdJqkmZIuyXm6PCKOjYjrbJ8j6XqlZsPHRcSGbmcaAIDJiKAVAFC0dkf87aSI+JmGr5O9cJRlPijpg7VlCgCAhqJ5MAAAAACgWNS0AgCK18tH3gAAgN4iaAUAFI+gFQCA5iJoBQCUj5gVAIDGImgFABSPmlYAAJqLgZgAAAAAAMWiphUAUDZT0woAQJPVErRa0vRp/V2Ju3bdxtrXsXrN+trXsebhep9t//D6+vfTdlvWf29lyxlTa1/HrK2m15r+A2vr/a4jak0eGJElEbMCmAyiCxfTyXK9rvu8z83Q/kJNKwCgcKZwAQBAgxG0AgCKR8wKAEBz9XcbXgAAAADApEZNKwCgeDQPBgCguQhaAQBlM82DAQBoMoJWAEDRLGnKFKJWAACaiqAVAFA8aloBAGguBmICAAAAABSLmlYAQPEYiAkAgOYas6bV9lzbP7Z9ve3rbB/fjYwBACDpkYGYOvkC6kTZCQA6q52a1vWSToyIq2xvK+lK25dExPU15w0AAFnUtKLvUHYCgA4aM2iNiNsl3Z7/Xm17iaTZkjjxAgC6wASt6CuUnQCgs8Y1EJPteZL2kXRFLbkBAACYRCg7AcDmaztotb2NpPMknRAR9w3z+TG2F9tevHLVyk7mEQDQcPRpRT8arexEuQkA2tdW0Gp7utJJ98yIOH+4eSJiUUQsjIiFOw3s1Mk8AgAaznZHX0Ddxio7UW4CgPaN2afV6ep+uqQlEfHx+rMEAEAFtaPoM5SdAKCz2qlpPUDSEZJeYPvq/HppzfkCAADoV5SdAKCD2hk9+GdKTxwAAKDreOQN+g1lJwDorHae0woAQE8RswIA0FwErQCA4lHTCgBAcxG0AgCKR8wKAEBztf2cVgAAAAAAuo2aVgBA2UzzYAAAmoygFQBQtDR6cK9zAQAAeqWWoDUkRUQdST9iw8Z60++GbhTC7rxvba3pbz2z/vse06fWv6OmT62/pXzdNUV1/yZC/f+bQ78yNa0AuqLua+m6DRtrTV+S1q2vfx3dMH1avWWzbpT90DnUtAIAikfMCgBAc3GLAQCAFrbn2v6x7ettX2f7+Dx9R9uX2P59/n+HPN22T7O91PY1tvft7RYAADB5ELQCAIpnu6OvNqyXdGJELJC0v6TjbC+Q9G5JP4yI+ZJ+mN9L0sGS5ufXMZI+2+l9AABAUxG0AgDK5tQ8uJOvsUTE7RFxVf57taQlkmZLOlTSV/JsX5H0yvz3oZK+GsnlkmbZ3qWzOwIAgGaiTysAoGhp9OCOd2odsL248n5RRCwadv32PEn7SLpC0s4RcXv+6A5JO+e/Z0taVllseZ52uwAAwGYhaAUAFK+GoHVVRCxsY73bSDpP0gkRcV81HxERthlWGwCAmtE8GACAYdierhSwnhkR5+fJfxxs9pv/vzNPXyFpbmXxOXkaAADYTAStAIDidbtPq1OV6umSlkTExysfXSDpqPz3UZL+szL9yDyK8P6S7q00IwYAAJuB5sEAgOLV0Dx4LAdIOkLStbavztNOlvQRSefYfoukWyQdlj+7UNJLJS2V9KCko7uaWwAAJjGCVgBA2dqsHe2kiPhZWvOwDhxm/pB0XK2ZAgCgoWgeDAAAAAAoFjWtAICiWe5F82AAAFAIglYAQPGIWQEAaC6CVgBA8aYQtQIA0FgErQCA4hGzAgDQXAzEBAAAAAAoFjWtAICi2T15TisAACgEQSsAoHhTiFkBAGgsglYAQPGoaQUAoLkIWgEAxSNmBQCguRiICQAAAABQLGpaAQBFsySLqlYAAJqKoBUAUDwGYgIAoLkIWgEAZbMZiAkAgAarLWjdGHWlnETN6U/twm39GdPq71L80IYNtaa/fk3NX4SkOx5cU/s6NtZ9QEnac8ftak1/q5lTa02/C7sIGBExK4CNdRcuJT20rt5y06rVD9eaviTdce9Dta+jG+WmXbbfotb0d9p2Zq3po7MYiAkAAAAAUCyaBwMAimZJU6hqBQCgsQhaAQDFI2YFAKC5CFoBAMVjICYAAJqLPq0AAAAAgGJR0woAKJpN82AAAJqMoBUAUDwGYgIAoLkIWgEAxSNkBQCgudoOWm1PlbRY0oqIOKS+LAEAMBQDMaEfUXYCgM4Yz0BMx0taUldGAAAAJhnKTgDQAW0FrbbnSHqZpC/Wmx0AAIaypCnu7AuoG2UnAOicdpsHnyrpnZK2rS8rAAAMw6Z5MPrRqaLsBAAdMWZNq+1DJN0ZEVeOMd8xthfbXrxq1cqOZRAAgMHH3nTqBdSpnbJTtdy0knITAIyqnebBB0h6he2bJZ0t6QW2v946U0QsioiFEbFwYGCnDmcTANBkzrWtnXoBNRuz7FQtN+1EuQkARjVm0BoRJ0XEnIiYJ+lwST+KiDfVnjMAAIA+RNkJADqL57QCAIo2OBATAABopnEFrRFxqaRLa8kJAAAjoEkv+hVlJwDYfNS0AgCKR8gKAEBztfWcVgAAesWWptgdfY29Tp9h+07bv6lM29v25bavzqO+7pen2/Zptpfavsb2vjXuDgAAGoegFQCAR/uypINapn1U0vsjYm9J/5zfS9LBkubn1zGSPtudLAIA0AwErQCA4nX7Oa0RcZmku1onS9ou/729pNvy34dK+mokl0uaZXuXzmw5AACgTysAoHg1DMQ0YHtx5f2iiFg0xjInSLrI9seUbvo+M0+fLWlZZb7ledrtHcorAACNRtAKACheDYMHr4qIheNc5m8lvSMizrN9mKTTJb2w4zkDAABD1Ba0RkRdSaf0a029O7rxCIeH1m+oNf1frbi71vQl6ZuX3lj7Oh64f23t63j1i55Ya/qvW/C4WtPfsHEy/OqAzXKUpOPz39+S9MX89wpJcyvzzcnTAHRQN65D9z64rtb0L7t5Za3pS9KiH95U+zo2bNhY+zqOev4etab/sj3rLTehs+jTCgAomtXZkYPbGT14BLdJem7++wWSfp//vkDSkXkU4f0l3RsRNA0GAKBDaB4MAChbm4MndXSV9lmSnqfU93W5pPdJequkT9qeJukhpZGCJelCSS+VtFTSg5KO7m5uAQCY3AhaAQDF60Z3iqqIeP0IH/3lMPOGpOPqzREAAM1F0AoAKB59WQAAaC7KAQAAAACAYlHTCgAomtX95sEAAKAcBK0AgOJNIWYFAKCxCFoBAMUjaAUAoLkIWgEARbNpHgwAQJMxEBMAAAAAoFjUtAIAikfzYAAAmougFQBQPFoHAwDQXAStAICiWdIUolYAABqLoBUAUDwGYAAAoLkoBwAAAAAAikVNKwCgeLQOBgCguQhaAQBFs02fVgAAGoygFQBQPGJWAACai6AVAFA8ntMKAEBzMRATAAAAAKBY1LQCAIrGc1oBAGg2glYAQPGIWQEAaC6CVgBA2UyfVgAAmow+rQAAAACAYtVW0+qa23Jt3LCx1vTX1Zy+JD28vv51bD9jRq3p/2Hlg7WmL0k3//wXta+jG5bvO6fW9LeYMbXW9Ov+TQOjsTj+gJJFRO3r2NCFdTywdkOt6f/whrtqTV+SfvOdC2pfh9Y/XPsq/vtxR9Wa/nN2e0yt6aOzaB4MAChaGoip17kAAAC9QtAKACgeQSsAAM1F0AoAKB7N0wEAaC4GYgIAAAAAFIuaVgBA0ejTCgBAsxG0AgDKZonWwQAANBdBKwCgeFOIWgEAaCyCVgBA0WgeDABAs7U1EJPtWbbPtf1b20tsP6PujAEAAPQryk4A0Dnt1rR+UtIPIuI1tmdI2qrGPAEAMAStg9GHKDsBQIeMGbTa3l7ScyS9WZIi4mFJD9ebLQAABllTRNSK/kHZCQA6q53mwXtIWinpS7Z/bfuLtreuOV8AAEhKfVrtzr7GXKd9hu07bf+mZfrf5+ae19n+aGX6SbaX2r7B9ks6vhPQbyg7AUAHtRO0TpO0r6TPRsQ+kh6Q9O7WmWwfY3ux7cWrVq3scDYBAI3lNBBTJ19t+LKkg4Zkw36+pEMlPTUi9pL0sTx9gaTDJe2Vl/mM7amd2wHoQ2OWnarlppWUmwBgVO0ErcslLY+IK/L7c5VOxENExKKIWBgRCwcGdupkHgEA6KqIuEzSXS2T/1bSRyJibZ7nzjz9UElnR8TaiLhJ0lJJ+3UtsyjRmGWnarlpJ8pNADCqMYPWiLhD0jLbe+ZJB0q6vtZcAQBQMcXu6GuCnijp2bavsP0T20/L02dLWlaZb3mehoai7AQAndXu6MF/L+nMPPrdjZKOri9LAABsMtintcMGbC+uvF8UEYvGWGaapB0l7S/paZLOsf1nHc8ZJgvKTgDQIW0FrRFxtaSF9WYFAIDhbUbt6EhWRcR4r2vLJZ0fESHpl7Y3ShqQtELS3Mp8c/I0NBhlJwDonHb6tAIAAOk7kp4vSbafKGmGpFWSLpB0uO2ZtveQNF/SL3uVSQAAJpt2mwcDANAzNTQPHmN9PkvS85SaES+X9D5JZ0g6Iz8G52FJR+Va1+tsn6PUZ3G9pOMiYkN3cwwAwORF0AoAKJrV/WZBEfH6ET560wjzf1DSB+vLEQAAzUXQCgAomyV3u6oVAAAUg6AVAFA8QlYAAJqLgZgAAAAAAMWiphUAUDSrlkfeAACAPlFb0Dql5vLF+o1Rb/ob6k1fkraeObX2ddxd8xcxsN3MWtPvmtV/qn0VM6bX27DhgbXra01/Y9T/mwBGQsgKlK0b/c67cfNq+tR617HbY7aqNX1JmrnnvrWvY8P6+gdI321g61rTnzGNBqf9hJpWAEDxqGgFAKC5CFoBAIUzowcDANBg1IsDAAAAAIpFTSsAoGgWd1gBAGgyglYAQPFoHgwAQHMRtAIAikfICgBAcxG0AgDKZmpaAQBoMroJAQAAAACKRU0rAKBoDMQEAECzEbQCAIpH82AAAJqLoBUAUDxCVgAAmosWVwAAAACAYlHTCgAoHq2DAQBoLoJWAEDR0kBMRK0AADQVQSsAoHjUtAIA0FwErQCAwlmmphUAgMZiICYAAAAAQLGoaQUAFI/mwQAANBdBKwCgaAzEBABAsxG0AgDKZmpaAQBoMoJWAEDxCFoBAGguBmICAAAAABSLmlYAQPF45A0AAM1F0AoAKJolTSFmBQCgsfo2aK27f9NkKSDtPGuLWtN/zV/sXGv6krT6ba+tfR333L+29nW8Ye9dak1/x61n1Jr+tMnyo0BfoqYVwNQuXIdmbTW91vRf3YVy067HPLP2dayP2lehA2bvWGv6O25Tb7kJndW3QSsAoDkYiAkAgOZiICYAAAAAQLGoaQUAFI/mwQAANBc1rQCAog0OxNTJ15jrtM+wfaft3wzz2Ym2w/ZAfm/bp9leavsa2/t2fCcAANBgBK0AgMK54//a8GVJBz0qJ/ZcSS+WdGtl8sGS5ufXMZI+u9mbDAAAHkHQCgBAi4i4TNJdw3z0CUnvlFQdO/NQSV+N5HJJs2zXO1w4AAANQp9WAEDZXMbowbYPlbQiIv7XQzM0W9KyyvvledrtXcweAACTFkErAKB4NcSsA7YXV94viohFI67f3krSyUpNgwEAQBe1FbTafoekv1ZqDnWtpKMj4qE6MwYAgDQ4EFPHw9ZVEbFwHPM/XtIekgZrWedIusr2fpJWSJpbmXdOnoYGo+wEAJ0zZp9W27MlvV3Swoh4kqSpkg6vO2MAAAxyh1/jFRHXRsRjI2JeRMxTagK8b0TcIekCSUfmUYT3l3RvRNA0uMEoOwFAZ7U7ENM0SVvaniZpK0m31ZclAAB6y/ZZkv5H0p62l9t+yyizXyjpRklLJX1B0t91IYsoH2UnAOiQMZsHR8QK2x9TGt5/jaSLI+Li1vlsH6M01L/m7rZbp/MJAGiyLg/EFBGvH+PzeZW/Q9JxdecJ/aOdshPlJgBoXzvNg3dQGs5/D0m7Stra9pta54uIRRGxMCIWDgzs1PmcAgAaqwfPaQUmrJ2yU7XctBPlJgAYVTvNg18o6aaIWBkR6ySdL+mZ9WYLAIBN7M6+gJpRdgKADmonaL1V0v62t3IaMvFASUvqzRYAAJv0eiAmYJwoOwFAB40ZtEbEFZLOlXSV0pDtUySN+Cw7AACAJqPsBACd1dZzWiPifZLeV3NeAAAYHtWj6DOUnQCgc9oKWgEA6JXUpJeoFQCApiJoBQCUjcGTAABoNIJWAEDxiFkBAGiudkYPBgAAAACgJ6hpBQCUj6pWAAAai6AVAFA4MxATAAANVkvQakmuedSMqTWnP23q5Gg5vcX0evfT3B23rDV9STrxWXvUvo616zfWvo4Z0+o9pqZNrfe7JmRALzEQE4ApXTgPbLNFvfU5ezx261rTl6Sdt9+i9nV0w5Yzptaa/lY1p4/OoqYVAFA0i5smAAA02eSoTgQAAAAATErUtAIAykdVKwAAjUXQCgAoHgMxAQDQXAStAIDiMRATAADNRZ9WAAAAAECxqGkFABSPilYAAJqLoBUAUDaeeQMAQKMRtAIAisdATAAANBdBKwCgaBYDMQEA0GQMxAQAAAAAKBY1rQCA4lHRCgBAcxG0AgDKR9QKAEBjEbQCAIrHQEwAADQXQSsAoHgMxAQAQHMxEBMAAAAAoFjUtAIAikdFKwAAzUXQCgAoH1ErAACNRdAKACiaxUBMAAA0GUErAKBsZiAmAACajIGYAAAAAADFImgFABTPHX6NuT77DNt32v5NZdq/2f6t7Wtsf9v2rMpnJ9leavsG2y/Z7A0GAACPIGgFAJSv21Gr9GVJB7VMu0TSkyLiKZJ+J+kkSbK9QNLhkvbKy3zG9tSJbCYAAHg0glYAQOHc8X9jiYjLJN3VMu3iiFif314uaU7++1BJZ0fE2oi4SdJSSft1bvsBAGi2WgZiuuqqK1dtOd23jGORAUmr6shLF7EN5ZgM21HiNuze6wwABfkrSd/Mf89WCmIHLc/TgLZMoNwklXmdGC+2oQyTYRukMreDslOH1BK0RsRO45nf9uKIWFhHXrqFbSjHZNiOybANQCfVMHrwgO3FlfeLImJRe3nxeyStl3Rmx3OFRhpvuUmaHNcJtqEMk2EbpMmzHRgej7wBABSt/W6o47JqIoUb22+WdIikAyMi8uQVkuZWZpuTpwEAgA6gTysAoHzdH4jp0VmwD5L0TkmviIgHKx9dIOlw2zNt7yFpvqRfTmwtAACgVSk1rW01ySoc21COybAdk2EbgI5pZ/Ckjq7PPkvS85SaES+X9D6l0YJnSrrEqb3y5RFxbERcZ/scSdcrNRs+LiI2dDXDaKLJcJ1gG8owGbZBmjzbgWF4U+smAADK85S9/zK++8NfdDTNeQNbXEnfJwAA+kMpNa0AAIyohoGYAABAnyBoBQAUj5gVAIDm6ulATLYPsn2D7aW2393LvEyU7bm2f2z7etvX2T6+13maKNtTbf/a9vd6nZeJsD3L9rm2f2t7ie1n9DpP42X7Hfk4+o3ts2xv0es8AT3nVNPayRfQryg7laPfy00SZSf0j54FrbanSvq0pIMlLZD0etsLepWfzbBe0okRsUDS/pKO69PtkKTjJS3pdSY2wycl/SAi/lzSU9Vn22J7tqS3S1oYEU+SNFXS4b3NFVCKAoYPBnqMslNx+r3cJFF2Qp/oZU3rfpKWRsSNEfGwpLMlHdrD/ExIRNweEVflv1cr/dhn9zZX42d7jqSXSfpir/MyEba3l/QcSadLUkQ8HBH39DRTEzNN0pa2p0naStJtPc4PAKAclJ0K0e/lJomyE/pLL4PW2ZKWVd4vV5+dsFrZnidpH0lX9DgrE3Gq0vMHN/Y4HxO1h6SVkr6Um+p80fbWvc7UeETECkkfk3SrpNsl3RsRF/c2V0DvWTQPBjLKTuU4Vf1dbpIoO6GP9LRP62RiextJ50k6ISLu63V+xsP2IZLujIgre52XzTBN0r6SPhsR+0h6QFJf9fWxvYPSHfM9JO0qaWvbb+ptroAy0DgYmHz6tew0ScpNEmUn9JFeBq0rJM2tvJ+Tp/Ud29OVTrpnRsT5vc7PBBwg6RW2b1ZqavQC21/vbZbGbbmk5RExeKf2XKUTcT95oaSbImJlRKyTdL6kZ/Y4T0ARqGkFJFF2KsVkKDdJlJ3QR3oZtP5K0nzbe9ieodRp+oIe5mdCbFupL8CSiPh4r/MzERFxUkTMiYh5St/DjyKir+5SRcQdkpbZ3jNPOlDS9T3M0kTcKml/21vl4+pA9dmACEBd3OF/QJ+i7FSAyVBukig7ob/07DmtEbHe9tskXaQ00tcZEXFdr/KzGQ6QdISka21fnaedHBEX9i5LjfX3ks7MF/IbJR3d4/yMS0RcYftcSVcpjaz4a0mLepsrAEApKDuhBpSd0BccEb3OAwAAI3rqPn8ZF/3k8o6mucv2M66MiIUdTRQAANSiZzWtAAC0iwa9AAA0F0ErAKBoDJ4EAECz8cgbAAAAAECxqGkFABSPEX8BAGguglYAQPmIWQEAaCyCVgBA8YhZAQBoLoJWAEDxGIgJAIDmYiAmAAAAAECxqGkFABTODMQEAECDEbQCAIpm0TwYAIAmo3kwAAAAAKBY1LQCAIpHTSsAAM1FTSsAAAAAoFjUtAIAisdATAAANBdBKwCgbKZ5MAAATUbQCgAomvMLAAA0E0ErAKB8RK0AADQWAzEBAAAAAIpFTSsAoHgMxAQAQHMRtAIAisdATAAANBdBKwCgeMSsAAA0F31aAQAAAADFoqYVAFA+qloBAGgsglYAQPEYiAkAgOYiaAUAFM1iICYAAJrMEdHrPAAAMCLbP5A00OFkV0XEQR1OEwAA1ICgFQAAAABQLEYPBgAAAAAUi6AVAAAAAFAsglYAAAAAQLEIWgEAAAAAxSJoBQAAAAAU6/8Dz/D4/h8UhQ0AAAAASUVORK5CYII= +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 8 con incertidumbre (Banda Azul)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [858]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_B8</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata8</span><span class="p">,</span> <span class="n">poptB8</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB8</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB8</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB8</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB8</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteB8</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptB8E</span><span class="p">,</span> <span class="n">pcovB8E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata8</span><span class="p">,</span> <span class="n">recorteB8</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span> <span class="n">sigma</span><span class="o">=</span><span class="n">Err_B8</span><span class="p">)</span> +<span class="n">estrellaB8E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata8</span><span class="p">,</span> <span class="n">poptB8E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB8E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB8E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB8E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB8E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMB8E</span><span class="o">=</span><span class="n">FWHMB_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptB8E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 8 fotografÃa (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteB8</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 8 a partir de la gaussiana con incertidumbre (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaB8E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">20</span><span class="p">,</span> <span class="mi">20</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 9 con incertidumbre (Banda Azul)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [859]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_B9</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata9</span><span class="p">,</span> <span class="n">poptB9</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB9</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB9</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB9</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB9</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteB9</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptB9E</span><span class="p">,</span> <span class="n">pcovB9E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata9</span><span class="p">,</span> <span class="n">recorteB9</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">Err_B9</span><span class="p">)</span> +<span class="n">estrellaB9E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata9</span><span class="p">,</span> <span class="n">poptB9E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB9E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB9E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB9E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB9E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMB9E</span><span class="o">=</span><span class="n">FWHMB_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptB9E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 9 fotografÃa (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteB9</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 9 a partir de la gaussiana con incertidumbre (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaB9E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Estrella 10 con incertidumbre (Banda Azul)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [860]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Err_B10</span><span class="o">=</span><span class="n">error</span><span class="p">(</span><span class="n">xdata10</span><span class="p">,</span> <span class="n">poptB10</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB10</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB10</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB10</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB10</span><span class="p">[</span><span class="mi">4</span><span class="p">],</span> <span class="n">recorteB10</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">inc</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> +<span class="n">poptB10E</span><span class="p">,</span> <span class="n">pcovB10E</span> <span class="o">=</span> <span class="n">curve_fit</span><span class="p">(</span><span class="n">gauss2d</span><span class="p">,</span> <span class="n">xdata10</span><span class="p">,</span> <span class="n">recorteB10</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">p0</span><span class="o">=</span><span class="p">[</span><span class="mi">3</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">sigma</span><span class="o">=</span><span class="n">Err_B10</span><span class="p">)</span> +<span class="n">estrellaB10E</span><span class="o">=</span><span class="n">gauss2d</span><span class="p">(</span><span class="n">xdata10</span><span class="p">,</span> <span class="n">poptB10E</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">poptB10E</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="n">poptB10E</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">poptB10E</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">poptB10E</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> +<span class="n">FWHMB10E</span><span class="o">=</span><span class="n">FWHMB_I</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">poptB10E</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> +<span class="n">fig</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">15</span><span class="p">))</span> +<span class="n">pos</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.35</span><span class="p">,</span><span class="mf">0.02</span><span class="p">,</span><span class="mf">0.3</span><span class="p">])</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">131</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 10 fotografÃa (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">recorteB10</span><span class="p">,</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">133</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Estrella 10 a partir de la gaussiana con incertidumbre (Banda Azul)"</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">estrellaB10E</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">),</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'Blues'</span><span class="p">))</span> +<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">cax</span><span class="o">=</span><span class="n">pos</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img 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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Histograma con incertidumbres (Banda Azul)</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [861]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="n">FWHMB_I</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">FWHMB_I</span><span class="p">)</span> +<span class="n">sigmaB_I</span> <span class="o">=</span> <span class="n">FWHMB_I</span><span class="o">.</span><span class="n">std</span><span class="p">()</span> +<span class="n">mediaB_I</span> <span class="o">=</span> <span class="n">FWHMB_I</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> +<span class="n">medianaB_I</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">median</span><span class="p">(</span><span class="n">FWHMB_I</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Datos de FWHM con incertidumbres de las estrellas para la Banda azul :"</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Desviación :"</span><span class="p">,</span> <span class="n">sigmaB_I</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Media :"</span><span class="p">,</span> <span class="n">mediaB_I</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="s2">"Mediana :"</span><span class="p">,</span> <span class="n">medianaB_I</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">FWHMB_I</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">'FHWM'</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">'# de estrellas'</span><span class="p">)</span> +<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + +<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain"> +<pre>Datos de FWHM con incertidumbres de las estrellas para la Banda azul : +Desviación : 2.6951116878528705 +Media : 4.515986827150282 +Mediana : 3.49839915953825 +</pre> +</div> +</div> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + + + +<div class="jp-RenderedImage jp-OutputArea-output "> +<img src="data:image/png;base64,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 +" +> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li>## Resumen de resultados:</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [897]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span> +<span class="c1"># -- crear un data frame con esa información</span> +<span class="c1"># -- crear un array con todas las cantidades calculadas anteriormente para el FWHM</span> +<span class="n">datos</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([[</span><span class="n">sigmaBN</span><span class="p">,</span><span class="n">mediaBN</span><span class="p">,</span><span class="n">medianaBN</span><span class="p">],</span> + <span class="p">[</span><span class="n">sigmaR</span><span class="p">,</span><span class="n">mediaR</span><span class="p">,</span><span class="n">medianaR</span><span class="p">],</span> + <span class="p">[</span><span class="n">sigmaG</span><span class="p">,</span><span class="n">mediaG</span><span class="p">,</span><span class="n">medianaG</span><span class="p">],</span> + <span class="p">[</span><span class="n">sigmaB</span><span class="p">,</span><span class="n">mediaB</span><span class="p">,</span><span class="n">medianaB</span><span class="p">],</span> + <span class="p">[</span><span class="n">sigmaBN_I</span><span class="p">,</span><span class="n">mediaBN_I</span><span class="p">,</span><span class="n">medianaBN_I</span><span class="p">],</span> + <span class="p">[</span><span class="n">sigmaR_I</span><span class="p">,</span><span class="n">mediaR_I</span><span class="p">,</span><span class="n">medianaR_I</span><span class="p">],</span> + <span class="p">[</span><span class="n">sigmaG_I</span><span class="p">,</span><span class="n">mediaG_I</span><span class="p">,</span><span class="n">medianaG_I</span><span class="p">],</span> + <span class="p">[</span><span class="n">sigmaB_I</span><span class="p">,</span><span class="n">mediaB_I</span><span class="p">,</span><span class="n">medianaB_I</span><span class="p">]])</span> + +<span class="nb">print</span><span class="p">(</span><span class="s1">'</span><span class="se">\033</span><span class="s1">[1m'</span> <span class="o">+</span> <span class="s1">'Los valores estadÃsticos obtenidos para el Full Width at Half Maximum (FHWM) son:'</span> <span class="p">)</span> +<span class="n">FWHM_tabla</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">datos</span><span class="p">,</span> + <span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s1">'D-E'</span><span class="p">,</span><span class="s1">'Media'</span><span class="p">,</span><span class="s1">'Mediana'</span><span class="p">],</span> + <span class="n">index</span><span class="o">=</span><span class="p">[</span><span class="s1">'Blanco/Negro'</span><span class="p">,</span><span class="s1">'Blanco/Negro con incertidumbre'</span><span class="p">,</span> + <span class="s1">'B-Rojo'</span><span class="p">,</span><span class="s1">'B-Rojo con incertidumbre'</span><span class="p">,</span> + <span class="s1">'B-Verde'</span><span class="p">,</span><span class="s1">'B-Verde con incertidumbre'</span><span class="p">,</span> + <span class="s1">'B-Azul'</span><span class="p">,</span><span class="s1">'B-Azul con incertidumbre'</span><span class="p">])</span> +<span class="n">FWHM_tabla</span> +</pre></div> + + </div> +</div> +</div> +</div> + +<div class="jp-Cell-outputWrapper"> + + +<div class="jp-OutputArea jp-Cell-outputArea"> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> + + +<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain"> +<pre><span class="ansi-bold">Los valores estadÃsticos obtenidos para el Full Width at Half Maximum (FHWM) son: +</span></pre> +</div> +</div> + +<div class="jp-OutputArea-child"> + + + <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[897]:</div> + + + +<div class="jp-RenderedHTMLCommon jp-RenderedHTML jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/html"> +<div> +<style scoped> + .dataframe tbody tr th:only-of-type { + vertical-align: middle; + } + + .dataframe tbody tr th { + vertical-align: top; + } + + .dataframe thead th { + text-align: right; + } +</style> +<table border="1" class="dataframe"> + <thead> + <tr style="text-align: right;"> + <th></th> + <th>D-E</th> + <th>Media</th> + <th>Mediana</th> + </tr> + </thead> + <tbody> + <tr> + <th>Blanco/Negro</th> + <td>2.506520</td> + <td>4.223188</td> + <td>3.141966</td> + </tr> + <tr> + <th>Blanco/Negro con incertidumbre</th> + <td>2.329890</td> + <td>4.021187</td> + <td>2.919205</td> + </tr> + <tr> + <th>B-Rojo</th> + <td>2.525571</td> + <td>4.242802</td> + <td>3.182727</td> + </tr> + <tr> + <th>B-Rojo con incertidumbre</th> + <td>2.699912</td> + <td>4.508061</td> + <td>3.482339</td> + </tr> + <tr> + <th>B-Verde</th> + <td>2.507212</td> + <td>4.216827</td> + <td>3.122942</td> + </tr> + <tr> + <th>B-Verde con incertidumbre</th> + <td>2.344335</td> + <td>4.008533</td> + <td>2.919655</td> + </tr> + <tr> + <th>B-Azul</th> + <td>2.525344</td> + <td>4.246485</td> + <td>3.173732</td> + </tr> + <tr> + <th>B-Azul con incertidumbre</th> + <td>2.695112</td> + <td>4.515987</td> + <td>3.498399</td> + </tr> + </tbody> +</table> +</div> +</div> + +</div> + +</div> + +</div> + +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li># Comentarios y conclusiones:</li> +</ul> + +</div> +</div> +<div class="jp-Cell-inputWrapper"><div class="jp-InputPrompt jp-InputArea-prompt"> +</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown"> +<ul> +<li><p>#### Fue posible implementar la función curve_fit para modelar la gaussiana sin mayores inconvenientes, sin embargo, la determinación de los parámetros sugeridos p0 fue totalmente aleatoria de tal manera que presentaba bastantes inconvenientes para algunos valores, y variaciones en los resultados bastante notables en el ingreso de diferentes enteros, como por ejemplo tomando x0=0 o y0=0 , el valor sugerido en p0 para la constante aditiva b de la gaussiana fue la que más cambio en los diferentes 8 resultados estadÃsticos del cálculo del FHWM, la segunda constante en más variar fue la multiplicativa de amplitud a.</p> +</li> +<li><p>#### Los resultados obtenidos para los análisis a blanco y negro se tomarón de la función lÃneal de Luma, como recomendación de algunos sitios web [1]. No se automatizó el plot de cada imagen ni la aplicación del modelo para cada una de las estrellas por que se estaban presentando errores de acumulación de datos en los arrays y listas, decidà hacerlo para cada una de tal manera que pudisese aprovechar esto y modificar algunos detalles para cada estrella, cómo: tamaño rejilla, titulos, añadidura de incertidumbres al fit y cambio en los p0 para cada uno de los tratamientos.</p> +</li> +<li><p>#### Al comparar los resultados obtenidos sin incertidumbres para los valores estadÃsticos del FHWM se observa que los canales rojo y azul tienen tanto mayor desviación como mayor FWHM que el canal verde y los resultados para los recortes blanco y negro, por lo que estos dos ultimos son los más considerables para modelar.</p> +</li> +<li><p>#### Al aplicar el módelo a todos los procedimientos, pero teniendo en cuenta la incertidumbre, los valores de p0 se hicieron mucho más variados que en los realizados sin incertidumbre. Razón por la cual es probable que justifique el hecho de que las desviaciones para los resultados de los valores estadÃsticos obtenidos del FHWM sean mayores en los casos de la bandas rojo y azul. El valor de la constante aditiva b de la gaussiana en la mayorÃa de los casos sin incertidumbre era cercano a 0 mientras que con incertidumbre tomaba siempre el mayor valor que todas las otras constantes, en especial en los casos de las bandas rojo y azul. Por lo que una vez más se presentan mejores resultados para el análisis a blanco y negro y para la banda verde.</p> +</li> +<li><p>#### Los valores obtenidos para el FWHM no varian significativamente con o sin incertidumbre, en la mayorÃa de todos los resultados el FWHM estaba entre 2 y 4, a excepsión de curiosamente la estrella más luminosa de la fotografÃa, la estrella 2, la cual presentaba FWHM alrededor de 11, como FWHM es el ancho de la gaussiana en su punto medio, podrÃa decirse que la estrella 2 es la más "desenfocada" de la fotografÃa por ser el objeto (o varios) de mayor tamaño.</p> +</li> +</ul> + +</div> +</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs "> +<div class="jp-Cell-inputWrapper"> +<div class="jp-InputArea jp-Cell-inputArea"> +<div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div> +<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> + <div class="CodeMirror cm-s-jupyter"> +<div class=" highlight hl-ipython3"><pre><span></span> +</pre></div> + + </div> +</div> +</div> +</div> + +</div> +</body> + + + + + + + +</html> diff --git a/Entrega.ipynb b/Entrega.ipynb new file mode 100644 index 0000000..9ae1c93 --- /dev/null +++ b/Entrega.ipynb @@ -0,0 +1,4328 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# José Miguel Ladino Méndez - MaestrÃa en Ciencias AstronomÃa - UNAL\n", + "# LACoNGA Physics - Ciencia de Datos - Tarea-Clase-05" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Ejercicios para practicar numpy y optimización con scipy\n", + "## Resolución espacial\n", + "* En observaciones astronómicas e imágenes en general, llamamos resolución espacial\n", + "a la distancia angular minima a la que pueden estar dos fuentes puntuales de luz\n", + "y aun poder ser reconocidas como objetos individuales.\n", + "En el caso de la astronomÃa, este efecto tiene que ver con la dispersión de la\n", + "luz al atravezar la atmósfera, la cual hace que una estrella, que deberÃa\n", + "en principio aparecer como una fuente puntual (pues las estrellas están muy\n", + "lejos), aparezca en cambio como una mancha. AsÃ, si dos estrellas están\n", + "demasiado cerca sus manchas se superpondrán hasta el punto en que sea imposible\n", + "distinguirlas como fuentes individuales.\n", + "Para modelar este efecto, tÃpicamente consideramos la acción de la atmósfera\n", + "como la convolución de la imagen \"perfecta\" (como se verÃa desde el espacio)\n", + "con un kernel gaussiano. El ancho de esa función gaussiana 2D caracteriza\n", + "las condiciones de observación, varÃa con las condiciones climáticas y para\n", + "cada sitio de la Tierra.\n", + "La resolución espacial normalmente se toma como el FWHM\n", + "de la gaussiana caracteristica registrada durante una observación. Es decir,\n", + "si dos estrellas están a una distancia aparente en el cielo menor que el\n", + "FWHM del efecto atmosférico, la luz de ambas fuentes se mezclará después de\n", + "la convolución hasta el punto de impedir reconocerlas de modo individual.\n", + "Además, la atmósfera puede interactuar de maneras distintas con la luz de\n", + "distintas longitudes de onda, de manera que el ancho de la gaussiana puede\n", + "ser distinto para observaciones con diferentes filtros.\n", + "El objetivo de esta tarea es medir de forma aproximada la resolución\n", + "espacial en una noche de observación en Zapatoca, Santander (Colombia), a partir\n", + "de una foto del cielo estrellado.\n", + "\n", + "\n", + "* El objetivo de esta tarea es medir de forma aproximada la resolución\n", + "espacial en una noche de observación en Zapatoca, Santander (Colombia), a partir\n", + "de una foto del cielo estrellado.\n", + "## Ejercicio:\n", + "* Leer la imagen almacenada en la carpeta data como un array de numpy. Ese\n", + "array estará compuesto de 3 matrices, una tras otra, correspondiente a los\n", + "canales R,G,B." + ] + }, + { + "cell_type": "code", + "execution_count": 99, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np #librerÃa util para manejar los array y funciones matemáticas\n", + "from PIL import Image #Módulo para abrir imagen.\n", + "\n", + "imagen = np.array(Image.open('data/zapatocaImage.jpeg')) #volviendo imagen en array\n", + "#print(imagen)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* Combinar los 3 array para generar una versión blanco y negro de la imagen,\n", + "en la cual ella consiste de una sola matriz 2D. Puede usar su intuición y prueba\n", + "y error para combinar las 3 imágenes, explicando el procedimiento elegido. Esto\n", + "será más interesante que usar un comando desconocido de una biblioteca sofisticada\n", + "que haga las cosas como una caja negra (queremos practicar numpy)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* Algunas maneras que se encontrarón para combinar los array RGB son:" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**1)** Tomando el promedio aritmético para cada pixel" + ] + }, + { + "cell_type": "code", + "execution_count": 899, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2\n" + ] + } + ], + "source": [ + "Escalagrises2 = imagen.mean(axis=2) #Toma el promedio aritmético para cada pixel (R+G+B/3)\n", + "plt.imshow(Escalagrises2, plt.get_cmap('gray')) #muestra imagen en escala de grises\n", + "plt.show()\n", + "print(Escalagrises2.ndim) #dim del array" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**2)** Usando la formula lineal estandar de Luma de brillo en una imagen [1]\n", + "* [1] : https://en.wikipedia.org/wiki/Grayscale" + ] + }, + { + "cell_type": "code", + "execution_count": 438, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2\n" + ] + } + ], + "source": [ + "Escalagrises3 = np.empty_like(imagen) #array del mismo shape\n", + "for i in range(3):\n", + " Escalagrises3[:,:,i] = 0.299*imagen[:,:,0] + 0.587*imagen[:,:,1]+0.114*imagen[:,:,2] #aplicando formula Luma a cada pixel\n", + "plt.imshow(Escalagrises3[:,:,0], plt.get_cmap('gray'))\n", + "plt.show()\n", + "print(Escalagrises3[:,:,0].ndim)" + ] + }, + { + "cell_type": "code", + "execution_count": 462, + "metadata": {}, + "outputs": [], + "source": [ + "def trim(array, x, y, width, height): #función para recortar \n", + " return array[y:y + height, x:x+width]\n", + "\n", + "# Calcula el error entre el valor z dado por la imagen y el determinado por el modelo teniendo en cuenta la incertidumbre\n", + "\n", + "def error(xdatatuple,a,b, x0,y0,c,z,inc): \n", + " model = gauss2d(xdatatuple,a,b, x0,y0,c)\n", + " errors = (model - z)/np.sqrt(abs(inc))\n", + " return errors\n" + ] + }, + { + "cell_type": "code", + "execution_count": 303, + "metadata": {}, + "outputs": [], + "source": [ + "from scipy.optimize import curve_fit #función del módelo de mÃnimos cuadrados general no lineal para ajustar\n", + "\n", + "\n", + "def gauss2d(xdatatuple,a,b, x0,y0,c): #modelo gaussiano 2d a inplementar con constante aditiva (\"el cielo vacio brilla\")\n", + " (x,y)=xdatatuple\n", + " z = a*np.exp(-((x-x0)**2+(y-y0)**2)/(2*c))+b\n", + " return z.ravel()\n", + "FWHM=[] #lista para los primeros valores de FWHM a blanco y negro" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* Tomando el modelo de gaussiana 2d de tal manera que se tomarán a sigma_x=sigma_y=sigma [2]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[2] : http://campar.in.tum.de/Chair/HaukeHeibelGaussianDerivatives" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 1 (blanco y negro)\n", + "* Todos los tratamientos de las estrellas son iguales de tal manera que solo se comentará el procedimiento en la siguiente celda" + ] + }, + { + "cell_type": "code", + "execution_count": 304, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorte1 = trim(Escalagrises3[:,:,0], 210, 237, 15, 15) #Recorte de la estrella individual\n", + "x1=np.arange(0,15,1)\n", + "y1=np.arange(0,15,1)\n", + "y1,x1 = np.meshgrid(x1,y1) #creando tupla xy\n", + "xdata1 = np.vstack((x1.ravel(),y1.ravel())) #util para leer rejilla simetrica (2,225) en curve_fit\n", + "#aplicación de curve_fit para hallar constantes, p0 es una sugerencia a los parametros, util para el ajuste\n", + "popt1, pcov1 = curve_fit(gauss2d, xdata1, recorte1.ravel(), p0=[1,0,1,1,1]) \n", + "estrella1=gauss2d(xdata1, popt1[0], popt1[1],popt1[2], popt1[3], popt1[4]) #aplicacion gaussiana con los parametros hallados\n", + "FWHM1=FWHM.append(2*np.sqrt(2*np.log(2))*np.sqrt(popt1[4])) #valor de FWHM de la gaussiana obtenida \n", + "#parametros para graficar, tamaño, barra de colores, titulos y color.\n", + "fig=plt.figure(figsize=(15, 15)) \n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 1 fotografÃa\")\n", + "plt.imshow(recorte1, plt.get_cmap('gray'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 1 a partir de la gaussiana\")\n", + "plt.imshow(estrella1.reshape(15, 15), plt.get_cmap('gray'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* Repita este procedimiento para varias estrellas y presente alguna estadÃstica\n", + "sobre las medidas de la FWHM de las distintas gaussianas: histograma, media, mediana,\n", + "desviación estándar\n", + "\n", + "* Al repetir el procedimiento en cada estrella a blanco y negro y cada una de las BandasRGB se modifican los parametros de cada recorte, rejilla, color y sugerencias p0" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 2 (blanco y negro)" + ] + }, + { + "cell_type": "code", + "execution_count": 305, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "x2=np.arange(0,35,1)\n", + "y2=np.arange(0,35,1)\n", + "y2,x2 = np.meshgrid(x2,y2)\n", + "recorte2 = trim(Escalagrises3[:,:,0], 645, 535, 35, 35)\n", + "xdata2 = np.vstack((x2.ravel(),y2.ravel()))\n", + "popt2, pcov2 = curve_fit(gauss2d, xdata2, recorte2.ravel(), p0=[1,0,1,1,1])\n", + "estrella2=gauss2d(xdata2, popt2[0], popt2[1],popt2[2], popt2[3], popt2[4])\n", + "FWHM2=FWHM.append(2*np.sqrt(2*np.log(2))*np.sqrt(popt2[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 2 fotografÃa\")\n", + "plt.imshow(recorte2, plt.get_cmap('gray'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 2 a partir de la gaussiana\")\n", + "plt.imshow(estrella2.reshape(35, 35), plt.get_cmap('gray'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 3 (blanco y negro)" + ] + }, + { + "cell_type": "code", + "execution_count": 306, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorte3 = trim(Escalagrises3[:,:,0], 560, 320, 15, 15)\n", + "x3=np.arange(0,15,1)\n", + "y3=np.arange(0,15,1)\n", + "y3,x3 = np.meshgrid(x3,y3)\n", + "xdata3 = np.vstack((x3.ravel(),y3.ravel()))\n", + "popt3, pcov3 = curve_fit(gauss2d, xdata3, recorte3.ravel(), p0=[1,0,1,1,1])\n", + "estrella3=gauss2d(xdata3, popt3[0], popt3[1],popt3[2], popt3[3], popt3[4])\n", + "FWHM3=FWHM.append(2*np.sqrt(2*np.log(2))*np.sqrt(popt3[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 3 fotografÃa\")\n", + "plt.imshow(recorte3, plt.get_cmap('gray'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 3 a partir de la gaussiana\")\n", + "plt.imshow(estrella3.reshape(15, 15), plt.get_cmap('gray'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 4 (blanco y negro)" + ] + }, + { + "cell_type": "code", + "execution_count": 307, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorte4 = trim(Escalagrises3[:,:,0], 442, 370, 15, 15)\n", + "x4=np.arange(0,15,1)\n", + "y4=np.arange(0,15,1)\n", + "y4,x4 = np.meshgrid(x4,y4)\n", + "xdata4 = np.vstack((x4.ravel(),y4.ravel()))\n", + "popt4, pcov4 = curve_fit(gauss2d, xdata4, recorte4.ravel(), p0=[1,0,1,1,1])\n", + "estrella4=gauss2d(xdata4, popt4[0], popt4[1],popt4[2], popt4[3], popt4[4])\n", + "FWHM4=FWHM.append(2*np.sqrt(2*np.log(2))*np.sqrt(popt4[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 4 fotografÃa\")\n", + "plt.imshow(recorte4, plt.get_cmap('gray'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 4 a partir de la gaussiana\")\n", + "plt.imshow(estrella4.reshape(15, 15), plt.get_cmap('gray'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 5 (blanco y negro)" + ] + }, + { + "cell_type": "code", + "execution_count": 308, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorte5 = trim(Escalagrises3[:,:,0], 320, 455, 15, 15)\n", + "x5=np.arange(0,15,1)\n", + "y5=np.arange(0,15,1)\n", + "y5,x5 = np.meshgrid(x5,y5)\n", + "xdata5 = np.vstack((x5.ravel(),y5.ravel()))\n", + "popt5, pcov5 = curve_fit(gauss2d, xdata5, recorte5.ravel(), p0=[1,1,1,1,1])\n", + "estrella5=gauss2d(xdata5, popt5[0], popt5[1],popt5[2], popt5[3], popt5[4])\n", + "FWHM5=FWHM.append(2*np.sqrt(2*np.log(2))*np.sqrt(popt5[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 5 fotografÃa\")\n", + "plt.imshow(recorte5, plt.get_cmap('gray'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 5 a partir de la gaussiana\")\n", + "plt.imshow(estrella5.reshape(15, 15), plt.get_cmap('gray'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 6 (blanco y negro)" + ] + }, + { + "cell_type": "code", + "execution_count": 309, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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guKDTgA/VwJXA/kkOHutJ0Eyx7SRpIUsGsCQrgT9j8O3eMcCLkxzTdsUkSZoz6QA2LMkRwNOAq5KcBtxUVV+dt9qhwMahx5t4ILBpD2PbSdJiRhmCeAKwoaq+A5DkIgbf9F3XZsUkSZrTwiQcByRZP/R4XVWtm79Skn2BjwGvYTAs8Q0Mhh9Ki7HtJGlBowSwXX2r95Bx7UnOBM4EWLly5VgqJ0lSS7Mgbqmq4xdbIclqBuHrwqq6NMnPAUcCX00CsBa4JskJwE3AYUObr22Wac+0ZNtpuN0kac8ytlkQq2pdVR1fVcevWOHkipKk2ZVBwjofuL6q3g5QVV+vqsdX1RFVdQSDRvVxVfVD4HLgN5rZEE8E7qiqzdOqv7pvuN007bpImqxResD8Vk+SNFVT+B2wZwIvBb6e5CvNsjdU1ScXWP+TwKnABuAe4IzWa6gus+0kaUGjBLB/AI5KciSDD4/TgV9rtVaSJA2ZdACrqi8CWWKdI4buF3BWy9XS7LDtJGlBSwawqtqe5JXAp4CVwAVVdW3rNZMkqTGFHjBpt9l2krSYkX6IuRlysdCwC0mSWmUA06yx7SRpIc6WIUmSJEkTMlIPmCRJ09LSNPSSJE2FAUyS1HkGMElSXxjAJEmdZwCTJPWF14BJkiRJ0oTYAyZJ6jx7wCRJfdFKANu5cyf33ntvG0X/xOMe97hWy5+ESTQoVqxot5Nz9erVrZYPtP5egskcx8qVK1st/+CDD261/M2bN7davrQYA5ikZNHfRh+LVava7ZuYRHtjEp+X999/f+v72LFjR+v7mBZ7wCRJneYsiJKkPjGASZI6zwAmSeoLJ+GQJEmSpAmxB0yS1Hn2gEmS+sIAJknqPAOYJKkvDGCSpM4zgEmS+sIAJknqNGdBlCT1iZNwSJIkSdKE2AMmSeo8e8AkSX1hAJMkdZ4BTJLUFwYwSVLnGcAkSX1hAJMkdZ4BTJLUF07CIUmSJEkTYg+YJKnTnIZektQnBjBJUucZwCRJfWEAkyR1ngFMktQXXgMmSZIkSRNiD5gkqfPsAZMk9YUBTJLUeQYwSVJfGMAkSZ3mLIiSpD4xgEmSOs8AJknqCyfhkCRJkqQJsQdMktR59oBJkvpiZgPY1q1bWy3/kY98ZKvlA+zcubP1fTzhCU9otfwnP/nJrZYPsGPHjtb38dWvfrX1fWzcuLHV8pO0Wr40TQYwSXvttVfr+zj44INbLf/II49stXyAbdu2tb6PDRs2tL6PLVu2tFr+9u3bWy1/MQ5BlCR13txEHOO6LSXJYUk+l+S6JNcmObtZ/idJvpnka0kuS7L/0DbnJtmQ5IYkz2/vbEiSZpkBTJLUaeMOXyP2pm0HzqmqY4ATgbOSHAN8GnhSVT0Z+BZwLkDz3OnAscDJwHuSrGzhdEiSZpwBTJKkeapqc1Vd09zfClwPHFpVV1TV3LiVK4G1zf3TgIuq6r6q+i6wAThh0vWWJHXfzF4DJknac0zzGrAkRwBPA66a99RvAR9t7h/KIJDN2dQskyTpQQxgkqTOayGAHZBk/dDjdVW1bv5KSfYFPga8pqruHFr+hwyGKV447opJkvrNACZJ6rwWAtiWqjp+sRWSrGYQvi6sqkuHlv8m8ALgpHqgYjcBhw1tvrZZJknSg3gNmCSp86YwC2KA84Hrq+rtQ8tPBl4HvLCq7hna5HLg9CR7JzkSOAr48lhPgiSpF+wBkyTpoZ4JvBT4epKvNMveALwL2Bv4dPPbe1dW1Suq6tokFwPXMRiaeFZVtf8jhpKkmWMAkyR12jKmjh/nPr8I7OrXzT+5yDZvBt7cWqUkSb2w5BDEhX6MUpKkSZnC74BJu822k6TFjNIDNvdjlNck2Q+4Osmnq+q6lusmSRIw3Wnopd1g20nSgpYMYFW1Gdjc3N+a5HoGv23ih4gkaSIMYJoltp0kLWZZsyAu8mOUkiRJmse2k6T5Rp6EY6Efoxx6/kzgTIAVK5zdXpI0PvaAaRYt1nYabjdJ2rOMFMAW+jHKYVW1DlgHsGrVKv9SSpLGwokzNIuWajsNt5uS+AaX9iBLBrCFfoxSkqRJMYBplth2krSYUcYKzv0Y5XOTfKW5ndpyvSRJkmaVbSdJCxplFsSFfoxSkqSJsAdMs8S2k6TFjDwJhyRJ02IAkyT1hQFMktR5BjBJUl8YwCRJneYsiJKkPvEHuyRJkiRpQuwBkyR1nj1gkqS+MIBJkjrPACZJ6otWAlgSVqxod3Tj6tWrWy3/0Y9+dKvlA2zbtq31fRx77LGtlv/7v//7rZYPcOedd7a+jz/6oz9qfR833nhjq+W3/X7auXNnq+VLizGASd3WdrsPYM2aNa3v4znPeU6r5Z9xxhmtlg9wyy23tL6P973vfa3v4+///u9bLf+uu+5qtXxY+G+XPWCSpM4zgEmS+sJJOCRJkiRpQuwBkyR1mtPQS5L6xAAmSeo8A5gkqS8MYJKkzjOASZL6wgAmSeo8A5gkqS+chEOSJEmSJsQeMElS59kDJknqCwOYJKnTnAVRktQnBjBJUucZwCRJfeE1YJIkSZI0IfaASZI6zx4wSVJfGMAkSZ1nAJMk9YUBTJLUaU7CIUnqEwOYJKnzDGCSpL5wEg5JkiRJmhB7wCRJnWcPmCSpL+wBkyR13tx1YOO6LSXJYUk+l+S6JNcmObtZ/tgkn07y7ebfxzTLk+RdSTYk+VqS41o+JZKkGWUAkyR13qQDGLAdOKeqjgFOBM5KcgzweuBvquoo4G+axwCnAEc1tzOB9477HEiS+sEAJknqtHGHr1ECWFVtrqprmvtbgeuBQ4HTgL9sVvtL4EXN/dOAD9XAlcD+SQ4e86mQJPWAAUySpEUkOQJ4GnAVcGBVbW6e+iFwYHP/UGDj0GabmmWSJD2Ik3BIkjqvhUk4DkiyfujxuqpaN3+lJPsCHwNeU1V3JhmuUyVxdhBJ0rIYwCRJnddCANtSVccvtkKS1QzC14VVdWmz+H8nObiqNjdDDG9ult8EHDa0+dpmmSRJD+IQRElS501hFsQA5wPXV9Xbh566HHhZc/9lwH8fWv4bzWyIJwJ3DA1VlCTpJ2a2B2zNmjWtln/IIYe0Wj7A1q1bW9/HQQcd1Gr5hx9+eKvlA9x3332t72OvvfZqfR9t27ZtW6vl+ztMmqYpvP+eCbwU+HqSrzTL3gC8Fbg4yW8D3wN+tXnuk8CpwAbgHuCMidZW2gPsvffere+j7XbNs571rFbLB9i8uf3vfi677LLW97Fq1czGlCX198gkSdpNVfVFIAs8fdIu1i/grFYrJUnqBQOYJKnTlvHbXZIkdZ4BTJLUeQYwSVJfGMAkSZ1nAJMk9YWzIEqSJEnShNgDJknqPHvAJEl9YQCTJHWeAUyS1BcGMElSpzkLoiSpT0YOYElWAuuBm6rqBe1VSZKkBzOAaRbZdpK0K8uZhONs4Pq2KiJJktQztp0kPcRIASzJWuCXgQ+0Wx1Jkh5qbhjiuG5S22w7SVrIqEMQ3wG8DtivvapIkrRrhibNoHdg20nSLizZA5bkBcDNVXX1EuudmWR9kvU7d+4cWwUlSbIHTLNklLbTcLtpglWT1AGj9IA9E3hhklOBRwBrkny4ql4yvFJVrQPWAaxevdq/bpKksTA0aQYt2XYabjcl8Q0u7UGW7AGrqnOram1VHQGcDnx2fviSJEnSgG0nSYvxd8AkSZ1nD5gkqS+WFcCq6m+Bv22lJpIkLcAAplll20nSfPaASZI6zwAmSeoLA5gkqfMMYJKkvhjph5glSZIkSQ+fPWCSpE5zGnpJUp8YwCRJnWcAkyT1hQFMktR5BjBJUl+0EsCqip07d7ZR9E/ceeedrZa/YkU/Lo+78cYbWy3/mmuuabV8gI0bN7a+j+9///ut72PNmjWtlt/2e/auu+5qtXxJ0uyaxJckd999d+v7WL9+favlv//972+1fIA77rij9X3ccMMNre/jvvvua7X8aX6xZw+YJKnz7AGTJPWFAUyS1HkGMElSXxjAJEmd5iyIkqQ+MYBJkjrPACZJ6ot+zDQhSZIkSTPAHjBJUufZAyZJ6gsDmCSp8wxgkqS+MIBJkjrPACZJ6gsDmCSp05wFUZLUJ07CIUmSJEkTYgCTJHXeXC/YuG5LSXJBkpuTfGNo2VOTXJnkK0nWJzmhWZ4k70qyIcnXkhzX4qmQJM04A5gkqfMmHcCAvwBOnrfsj4E3VdVTgf/cPAY4BTiquZ0JvHccxyxJ6ievAZMkdd6krwGrqi8kOWL+YmBNc//RwA+a+6cBH6pBJa9Msn+Sg6tq82RqK0maJQYwSVLndWQSjtcAn0ryNgYjSH6hWX4osHFovU3NMgOYJOkhHIIoSdoTHdBcxzV3O3OEbX4PeG1VHQa8Fji/3SpKkvrIHjBJUqe1NA39lqo6fpnbvAw4u7n/34APNPdvAg4bWm9ts0ySpIewB0yS1HlTmIRjV34A/Mvm/nOBbzf3Lwd+o5kN8UTgDq//kiQtxB4wSVLnTfoasCQfAZ7NYKjiJuA84OXAO5OsAu5lMOMhwCeBU4ENwD3AGROtrCRpphjAJEmdN4VZEF+8wFP/xy7WLeCsdmskSeoLhyBKkiRJ0oTYAyZJ6ryOTEMvSdLDZgCTJHVaS7MgSpI0FQYwSVLnGcAkSX3hNWCSJEmSNCGt9YC1/W3lpk2bWi3/p37qp1otH+Dee+9tfR9btmxptfzbb7+91fIBbrnlltb38a1vfav1fTz+8Y9vtfx999231fJXrPD7Gk2PPWBSt03i/+jWrVtb38eVV17ZavkbNmxotXyA7du3t76Pm2++ufV9TKKdPC0OQZQkdZ4BTJLUFwYwSVLnGcAkSX1hAJMkdZqzIEqS+sSLOiRJkiRpQuwBkyR1nj1gkqS+MIBJkjrPACZJ6gsDmCSp8wxgkqS+MIBJkjrPACZJ6ouRJuFIsn+SS5J8M8n1SZ7RdsUkSZJmlW0nSQsZtQfsncBfV9W/S7IX8KgW6yRJ0k84Db1mlG0nSbu0ZABL8mjgF4HfBKiq+4H7262WJEkPMIBplth2krSYUYYgHgn8CPhgkn9M8oEk+7RcL0mSfmKuF2xcN6lltp0kLWiUALYKOA54b1U9DbgbeP38lZKcmWR9kvX+cZMkjZMBTDNmybbTcLtpGhWUND2jBLBNwKaquqp5fAmDD5UHqap1VXV8VR2fZJx1lCRJmiVLtp2G200Tr52kqVoygFXVD4GNSZ7YLDoJuK7VWkmSNMQeMM0S206SFjPqLIivAi5sZvH5DnBGe1WSJOkBhibNKNtOknZppABWVV8B7CKXJE2FAUyzxraTpIWM9EPMkiRJkqSHb9QhiJIkTY09YJKkvjCASZI6zwAmSeoLA5gkqfMMYJKkvjCASZI6zVkQJUl94iQckiRJkjQh9oBJkjrPHjBJUl+0FsB27tzZVtEA7LPPPq2Wf9ttt7VaPsC2bdta38e9997bavl33nlnq+UD7Nixo/V9TOK1mMS5alPb/6elxRjAJG3fvr31fdx6662tln/77be3Wv6kTKJt1ufPfXvAJEmd1+c/xJKkPYsBTJLUeQYwSVJfOAmHJEnzJLkgyc1JvjFv+auSfDPJtUn+eGj5uUk2JLkhyfMnX2NJ0qywB0yS1GlTmob+L4B3Ax+aW5DkOcBpwFOq6r4kj2+WHwOcDhwLHAJ8JsnRVdX+RRKSpJljD5gkqfPmQti4biPs7wvA/Kvxfw94a1Xd16xzc7P8NOCiqrqvqr4LbABOGN/RS5L6xAAmSeq8SQewBRwNPCvJVUk+n+TpzfJDgY1D621qlkmS9BAOQZQkdV4LQxAPSLJ+6PG6qlq3xDargMcCJwJPBy5O8tPjrpgkqd8MYJKkPdGWqjp+mdtsAi6tQRr8cpKdwAHATcBhQ+utbZZJkvQQDkGUJHVeR4Yg/hXwHIAkRwN7AVuAy4HTk+yd5EjgKODLD/+oJUl9ZA+YJKnTpjELYpKPAM9mMFRxE3AecAFwQTM1/f3Ay5resGuTXAxcB2wHznIGREnSQgxgkqTOm3QAq6oXL/DUSxZY/83Am9urkSSpLxyCKEmSJEkTYg+YJKnzpvBDzJIktcIAJknqPAOYJKkvDGCSpE6bxiQckiS1xQAmSeo8A5gkqS+chEOSJEmSJsQeMElS59kDJknqCwOYJKnzDGCSpL4wgEmSOs8AJknqCwOYJKnTnAVRktQnTsIhSZIkSRNiD5gkqfPsAZMk9YUBTJLUeQYwSVJfzGwA+9mf/dlWy7/99ttbLR9g586dre9jzZo1rZa/zz77tFo+wOrVq1vfx9133936Pm699dZWy2/7PE3i/SotxAAmaRLa/lvn31LBDAcwSdKewwAmSeoLJ+GQJEmSpAmxB0yS1GlOQy9J6hMDmCSp8wxgkqS+MIBJkjrPACZJ6guvAZMkSZKkCbEHTJLUefaASZL6wgAmSeo8A5gkqS9GGoKY5LVJrk3yjSQfSfKItismSRI8MAviOG9S22w7SVrIkgEsyaHAq4Hjq+pJwErg9LYrJknSHAOYZoltJ0mLGXUSjlXAI5OsAh4F/KC9KkmSJM08206SdmnJAFZVNwFvA74PbAbuqKor5q+X5Mwk65Os37lz5/hrKknaY9kDplkySttpuN00jTpKmp5RhiA+BjgNOBI4BNgnyUvmr1dV66rq+Ko6fsUKZ7eXJI2PAUyzZJS203C7aRp1lDQ9oySlXwK+W1U/qqptwKXAL7RbLUmSHmAA04yx7SRpQaNMQ/994MQkjwJ+DJwE2F0uSZoIQ5NmkG0nSQsa5Rqwq4BLgGuArzfbrGu5XpIkSTPJtpOkxYz0Q8xVdR5wXst1kSRpl+wB06yx7SRpISMFMEmSpskAJknqCwOYJKnzDGCSpL5wvnhJUudNehbEJBckuTnJN3bx3DlJKskBzeMkeVeSDUm+luS4Fk6BJKknDGCSJD3UXwAnz1+Y5DDgeQxmuZtzCnBUczsTeO8E6idJmlEGMElSp42792uUHrCq+gJw6y6e+lPgdcBwIacBH6qBK4H9kxw8jmOXJPWP14BJkjqvC9eAJTkNuKmqvppk+KlDgY1Djzc1yzZPsHqSpBnRWgBbuXJlW0UDcOCBB7Za/iTceuuuvlwdrx07drRa/s6dO1stH9o/BoBt27a1vo+2j2Pvvfdutfx5DU5poloIYAckGf5h3HVVteDvNDU/qPsGBsMPJUnabfaASZI6r4UAtqWqjl/G+j8DHAnM9X6tBa5JcgJwE3DY0Lprm2WSJD2E14BJkrSEqvp6VT2+qo6oqiMYDDM8rqp+CFwO/EYzG+KJwB1V5fBDSdIu2QMmSeq8SV8DluQjwLMZDFXcBJxXVecvsPongVOBDcA9wBkTqaQkaSYZwCRJnTbqzIVj3ueLl3j+iKH7BZzVdp0kSf1gAJMkdV4XZkGUJGkcvAZMkiRJkibEHjBJUufZAyZJ6gsDmCSp8wxgkqS+MIBJkjrPACZJ6gsDmCSp06YxC6IkSW1xEg5JkiRJmhB7wCRJnWcPmCSpLwxgkqTOM4BJkvrCACZJ6jwDmCSpLwxgkqTOM4BJkvrCSTgkSZIkaULsAZMkdZrT0EuS+sQAJknqPAOYJKkvDGCSpM4zgEmS+sIAJknqPAOYJKkvnIRDkiRJkibEHjBJUufZAyZJ6gsDmCSp05wFUZLUJwYwSVLnGcAkSX3RSgDbsWPHlltvvfV7y9jkAGDLcvbxiU98YnmVat+yj6GD+nAM0I/jWPYx3HHHHS1V5ScOb3sHkrSH2gIsp90Ee+jfug7yGLqji8exy7ZTKwGsqh63nPWTrK+q49uoy6R4DN3Rh+PowzFI42QPmPpsue0m6MffCY+hG/pwDDBbx+EQRElS5xnAJEl9YQCTJHWeAUyS1BddCWDrpl2BMfAYuqMPx9GHY5DGwlkQpV3qw98Jj6Eb+nAMMEPHEf+oSZK6bK+99qqDDjporGVu3Ljx6lm5VkCS1C9d6QGTJGlBflkoSeoLA5gkqfMMYJKkvlgxzZ0nOTnJDUk2JHn9NOuyu5IcluRzSa5Lcm2Ss6ddp92VZGWSf0zy8WnXZXck2T/JJUm+meT6JM+Ydp2WK8lrm/fRN5J8JMkjpl0nqQvmrgMb102aVbadumPW201g22laphbAkqwE/gw4BTgGeHGSY6ZVn4dhO3BOVR0DnAicNaPHAXA2cP20K/EwvBP466r658BTmLFjSXIo8Grg+Kp6ErASOH26tZK6wQAm2XbqoFlvN4Ftp6mYZg/YCcCGqvpOVd0PXAScNsX67Jaq2lxV1zT3tzJ44x463VotX5K1wC8DH5h2XXZHkkcDvwicD1BV91fV7VOt1O5ZBTwyySrgUcAPplwfSVJ32HbqiFlvN4Ftp2maZgA7FNg49HgTM/afb74kRwBPA66aclV2xzuA1wE7p1yP3XUk8CPgg81wgA8k2WfalVqOqroJeBvwfWAzcEdVXTHdWknTN+7eL3vANMNsO3XHO5jtdhPYdpqaqV4D1idJ9gU+Brymqu6cdn2WI8kLgJur6upp1+VhWAUcB7y3qp4G3A3M1Nj4JI9h8E3mkcAhwD5JXjLdWkndYACT+mdW2049aTeBbaepmWYAuwk4bOjx2mbZzEmymsEHyIVVdem067Mbngm8MMmNDIYzPDfJh6dbpWXbBGyqqrlv0C5h8KEyS34J+G5V/aiqtgGXAr8w5TpJnTDpAJbkgiQ3J/nG0LI/aS5U/1qSy5LsP/Tcuc2kCDckeX47Z0Gy7dQRfWg3gW2nqZlmAPsH4KgkRybZi8EFc5dPsT67JUkYjJ29vqrePu367I6qOreq1lbVEQxeh89WVee/PRhWVT8ENiZ5YrPoJOC6KVZpd3wfODHJo5r31UnM2MWwUlum0AP2F8DJ85Z9GnhSVT0Z+BZwLkAzecDpwLHNNu9pJkuQxs22Uwf0od0Etp2maWoBrKq2A68EPsXgRF1cVddOqz4PwzOBlzL49uMrze3UaVdqD/Uq4MIkXwOeCrxlutVZnuYbqEuAa4CvM/j/uW6qlZL2UFX1BeDWecuuaP52AVzJoPcBBsNfLqqq+6rqu8AGBpMlSGNl20ktsO00BXEsvCSpy1avXl3777//WMvcsmXL1VV1/GLrNJMDfLwGUxvPf+5/AB+tqg8neTdwZVV9uHnufOB/VtUlY620JKkXVk27ApIkLaaliTMOSLJ+6PG6qhrpW9Mkf8jgd4wuHHelJEn9ZwCTJHVeCwFsy1I9YLuS5DeBFwAn1QOV6s3ECJKk9jkNvSRJI0hyMoPf/XlhVd0z9NTlwOlJ9k5yJHAU8OVp1FGS1H32gEmSOm/S1ysn+QjwbAZDFTcB5zGY9XBv4NODyba4sqpeUVXXJrmYwexh24GzqmrHRCssSZoZTsIhSeq0VatW1X777TfWMm+//fYlJ+GQJKkN9oBJkjrPLwslSX1hAJMkdVpLsyBKkjQVTsIhSZIkSRNiD5gkqfPsAZMk9YUBTJLUeQYwSVJfGMAkSZ1nAJMk9YUBTJLUeQYwSVJfOAmHJEmSJE2IPWCSpE5zGnpJUp8YwCRJnWcAkyT1hQFMktR5BjBJUl8YwCRJnWcAkyT1hZNwSJIkSdKE2AMmSeo8e8AkSX1hAJMkdZqzIEqS+sQAJknqPAOYJKkvvAZMkiRJkibEHjBJUufZAyZJ6gsDmCSp8wxgkqS+MIBJkjrPACZJ6gsDmCSp6z4FHDDmMreMuTxJkkYSv1WUJEmSpMlwFkRJkiRJmhADmCRJkiRNiAFMkiRJkibEACZJkiRJE2IAkyRJkqQJ+f8BxMyApRGFzQIAAAAASUVORK5CYII=\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorte6 = trim(Escalagrises3[:,:,0], 535, 335, 10, 10)\n", + "x6=np.arange(0,10,1)\n", + "y6=np.arange(0,10,1)\n", + "y6,x6 = np.meshgrid(x6,y6)\n", + "xdata6 = np.vstack((x6.ravel(),y6.ravel()))\n", + "popt6, pcov6 = curve_fit(gauss2d, xdata6, recorte6.ravel(), p0=[1,0,1,1,1])\n", + "estrella6=gauss2d(xdata6, popt6[0], popt6[1],popt6[2], popt6[3], popt6[4])\n", + "FWHM6=FWHM.append(2*np.sqrt(2*np.log(2))*np.sqrt(popt6[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 6 fotografÃa\")\n", + "plt.imshow(recorte6, plt.get_cmap('gray'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 6 a partir de la gaussiana\")\n", + "plt.imshow(estrella6.reshape(10, 10), plt.get_cmap('gray'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 7 (blanco y negro)" + ] + }, + { + "cell_type": "code", + "execution_count": 310, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorte7 = trim(Escalagrises3[:,:,0], 540, 345, 10, 10)\n", + "x7=np.arange(0,10,1)\n", + "y7=np.arange(0,10,1)\n", + "y7,x7 = np.meshgrid(x7,y7)\n", + "xdata7 = np.vstack((x7.ravel(),y7.ravel()))\n", + "popt7, pcov7 = curve_fit(gauss2d, xdata7, recorte7.ravel(), p0=[1,0,1,1,1])\n", + "estrella7=gauss2d(xdata7, popt7[0], popt7[1],popt7[2], popt7[3], popt7[4])\n", + "FWHM7=FWHM.append(2*np.sqrt(2*np.log(2))*np.sqrt(popt7[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 7 fotografÃa\")\n", + "plt.imshow(recorte7, plt.get_cmap('gray'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 7 a partir de la gaussiana\")\n", + "plt.imshow(estrella7.reshape(10, 10), plt.get_cmap('gray'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 8 (blanco y negro)" + ] + }, + { + "cell_type": "code", + "execution_count": 311, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorte8 = trim(Escalagrises3[:,:,0], 620, 306, 20, 20)\n", + "x8=np.arange(0,20,1)\n", + "y8=np.arange(0,20,1)\n", + "y8,x8 = np.meshgrid(x8,y8)\n", + "xdata8 = np.vstack((x8.ravel(),y8.ravel()))\n", + "popt8, pcov8 = curve_fit(gauss2d, xdata8, recorte8.ravel(), p0=[1,0,1,1,1])\n", + "estrella8=gauss2d(xdata8, popt8[0], popt8[1],popt8[2], popt8[3], popt8[4])\n", + "FWHM8=FWHM.append(2*np.sqrt(2*np.log(2))*np.sqrt(popt8[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 8 fotografÃa\")\n", + "plt.imshow(recorte8, plt.get_cmap('gray'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 8 a partir de la gaussiana\")\n", + "plt.imshow(estrella8.reshape(20, 20), plt.get_cmap('gray'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 9 (blanco y negro)" + ] + }, + { + "cell_type": "code", + "execution_count": 312, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorte9 = trim(Escalagrises3[:,:,0], 545, 360, 10, 10)\n", + "x9=np.arange(0,10,1)\n", + "y9=np.arange(0,10,1)\n", + "y9,x9 = np.meshgrid(x9,y9)\n", + "xdata9 = np.vstack((x9.ravel(),y9.ravel()))\n", + "popt9, pcov9 = curve_fit(gauss2d, xdata9, recorte9.ravel(), p0=[1,0,1,1,1])\n", + "estrella9=gauss2d(xdata9, popt9[0], popt9[1],popt9[2], popt9[3], popt9[4])\n", + "FWHM9=FWHM.append(2*np.sqrt(2*np.log(2))*np.sqrt(popt9[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 9 fotografÃa\")\n", + "plt.imshow(recorte9, plt.get_cmap('gray'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 9 a partir de la gaussiana\")\n", + "plt.imshow(estrella9.reshape(10, 10), plt.get_cmap('gray'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 10 (blanco y negro)" + ] + }, + { + "cell_type": "code", + "execution_count": 313, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorte10 = trim(Escalagrises3[:,:,0], 615, 394, 10, 10)\n", + "x10=np.arange(0,10,1)\n", + "y10=np.arange(0,10,1)\n", + "y10,x10 = np.meshgrid(x10,y10)\n", + "xdata10 = np.vstack((x10.ravel(),y10.ravel()))\n", + "popt10, pcov10 = curve_fit(gauss2d, xdata10, recorte10.ravel(), p0=[1,0,1,1,1])\n", + "estrella10=gauss2d(xdata10, popt10[0], popt10[1],popt10[2], popt10[3], popt10[4])\n", + "FWHM10=FWHM.append(2*np.sqrt(2*np.log(2))*np.sqrt(popt10[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 10 fotografÃa\")\n", + "plt.imshow(recorte10, plt.get_cmap('gray'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 10 a partir de la gaussiana\")\n", + "plt.imshow(estrella10.reshape(10, 10), plt.get_cmap('gray'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Histograma (blanco y negro)" + ] + }, + { + "cell_type": "code", + "execution_count": 447, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Datos de FWHM de las estrellas a blanco y negro :\n", + "Desviación : 2.506520397288835\n", + "Media : 4.2231882458162096\n", + "Mediana : 3.1419657079162633\n" + ] + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "FWHM = np.array(FWHM)\n", + "sigmaBN = FWHM.std()\n", + "mediaBN = FWHM.mean()\n", + "medianaBN = np.median(FWHM)\n", + "print(\"Datos de FWHM de las estrellas a blanco y negro :\")\n", + "print(\"Desviación :\", sigmaBN)\n", + "print(\"Media :\", mediaBN)\n", + "print(\"Mediana :\", medianaBN)\n", + "plt.hist(FWHM)\n", + "plt.xlabel('FHWM')\n", + "plt.ylabel('# de estrellas')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* Repita el mismo ejercicio sobre cada una de las bandas R,G,B separadamente\n", + "y comente si observa diferencias en los resultados" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Para la banda R\n", + "* ## Estrella 1 (Rojo)" + ] + }, + { + "cell_type": "code", + "execution_count": 353, + "metadata": {}, + "outputs": [], + "source": [ + "FWHMR=[]" + ] + }, + { + "cell_type": "code", + "execution_count": 354, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteR1 = trim(imagen[:,:,0], 210, 237, 15, 15)\n", + "poptR1, pcovR1 = curve_fit(gauss2d, xdata1, recorteR1.ravel(), p0=[1,1,1,1,1])\n", + "estrellaR1=gauss2d(xdata1, poptR1[0], poptR1[1],poptR1[2], poptR1[3], poptR1[4])\n", + "FWHMR1=FWHMR.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptR1[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 1 fotografÃa (Banda Rojo)\")\n", + "plt.imshow(recorteR1, plt.get_cmap('Reds'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 1 a partir de la gaussiana (Banda Rojo)\")\n", + "plt.imshow(estrellaR1.reshape(15, 15), plt.get_cmap('Reds'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 2 (Rojo)" + ] + }, + { + "cell_type": "code", + "execution_count": 355, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteR2 = trim(imagen[:,:,0], 645, 535, 35, 35)\n", + "poptR2, pcovR2 = curve_fit(gauss2d, xdata2, recorteR2.ravel(), p0=[1,0,1,1,1])\n", + "estrellaR2=gauss2d(xdata2, poptR2[0], poptR2[1],poptR2[2], poptR2[3], poptR2[4])\n", + "FWHMR2=FWHMR.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptR2[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 2 fotografÃa (Banda Rojo)\")\n", + "plt.imshow(recorteR2, plt.get_cmap('Reds'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 2 a partir de la gaussiana (Banda Rojo)\")\n", + "plt.imshow(estrellaR2.reshape(35, 35), plt.get_cmap('Reds'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 3 (Rojo)" + ] + }, + { + "cell_type": "code", + "execution_count": 356, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteR3 = trim(imagen[:,:,0], 560, 320, 15, 15)\n", + "poptR3, pcovR3 = curve_fit(gauss2d, xdata3, recorteR3.ravel(), p0=[1,1,1,1,1])\n", + "estrellaR3=gauss2d(xdata3, poptR3[0], poptR3[1],poptR3[2], poptR3[3], poptR3[4])\n", + "FWHMR3=FWHMR.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptR3[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 3 fotografÃa (Banda Rojo)\")\n", + "plt.imshow(recorteR3, plt.get_cmap('Reds'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 3 a partir de la gaussiana (Banda Rojo)\")\n", + "plt.imshow(estrellaR3.reshape(15, 15), plt.get_cmap('Reds'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 4 (Rojo)" + ] + }, + { + "cell_type": "code", + "execution_count": 357, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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77g3yCUmX5l3hb22y3c/n7a51dg3YzcqG3LXySWXD9LYoKxiubrZiZNdaPVJ7KPvQPhkRm9vYjyRdrOy6tBskPaDsLMIH8m0/pWzM8k/y13lSi/VX5D9foexsxxOS1iv7A9HMf1X2H3+bsi+E8QxBbfs45ZYpu4dIfVb28tr7rmxYxYba65H0NWXd3muVXbx7c7uBRcRGSX+g7D/rJmUXCv8kIfbR279L2Xvw3yLiX5V9wX5T2XE/SvnMpA18QNkZvPsl3ajsbNvFdc+fqWwsOTCw6NFDH9uX8pE/lvSpPJ6PKStYxvKIsqLiYWXXxP9RRNRm9hzXtprkN+OS5zznKPseXZfHVj8ZSEfHPCLuUXb9/E3KivgXa+/8YbRP5ft9QFmxc5XyvKvVtiLiOmV5152SbpX0vbrtDik7GfywpM3KioRawTLW57HeeN/jeuPND/9ee885IO2ZZf4JST9T9to/mT/3OUlTlY12ulnSv7QbWBvvfUpuK2X/1x6T9F6NkXc3cKay0WcPS/qWsut0/1WS8qLxDZIubbVzx163IQMay888PK6s6/qBHocjSbL9f5WN2f52r2Mpg7NbJ+yS9LyIeKjFum+S9M6IaJYoAJW3YMLE+NOpswrf7vuf3HRrRCwufMMAZPsUSV+PiHktVt3n2X6fpDMioq2J7QaJ7Z9Ien/kN00fdLaPlPRLSZOiRXFm+wPKhtCe32q73DQSTeXFwg+VDdn8K0l3ac8kJj0XEeMZNjAIjlF29ueRVitGxHclfbfrEQE9ZA3msBQA+yZnt0o4Ulmv3SJl1541m35/oEXEya3XGijHSPp1qyJPkiKi2S0wnoPvSIxlibIu44eV/cE5o50PIIpn+/cl/VjZVLs7eh0P0C8YuglggExWNmxxm7KbwX9He26/hAFl+78ouyTpw4Vvm7wdAFBFCydMio9Mm1X4dpc+sZGhmwCAymPoJgCgsuiBAwCgMYZuAgAAAMCAKbVHb3jOnFi4YH7rFZsqYJhp8iYKiMGpp6ALOIW9e6T1Ot2OIfVYFjHsePeuxA0UcByGJiSGkBjDUNr5ngcfWq2NmzbTr4Ke4IOHQTc8PCcWLljQ6zAAFOjBhx7Sxo2buv4VVmqht3DBfP3s+ms730A0un/jOO1O3EYRMUxIPOxDBbxt2zaltXcBncGJxzJ2jnVLvzZtfyKtfWqRJsnTZqRtYPLUtPZT0tq/9Hd+N23/QIcshm5i8C1csEDLb7y+12FAEvNaFMPJHR7Vt/i3TillP1yjBwCorCH69AAAaIhr9AAAAABgwNCjBwCoJHPfOwAAmkrq0bN9mu1f2F5lu/Cb/AEAMJahLjyAbiJ3AlCWjr/TbE+Q9DeSXi/paEln2j66qMAAAGjFXXgA3ULuBKBMKUM3T5S0KiLulyTbV0haIumeIgIDAGAs2ayblGaoFHInAKVJGaUyV9Lqut/X5Mv2Ynup7eW2l2/YlDilPwAAQHWNP3faSO4EoDNdvxwhIpZFxOKIWHzQnDnd3h0AYB/C0E0Mor1yp2FyJwCdSRm6uVbS/Lrf5+XLAAAoBYUZKobcCUBpUnr0fiZpke0jbE+WdIaka4oJCwCA1sru0bM93/aPbd9je4XtD456/jzbYXs4/922v5DPsHin7RMKeeGoKnInAKXpuEcvIkZsv1/SDyRNkHRxRKwoLDIAAFpw+ZOxjEg6LyJusz1D0q22r4uIe2zPl/Q6SQ/Vrf96SYvyx8skfSn/F/sgcicAZUq6YXpEfF/S9wuKBQCAvhYR6ySty3/eZnulssk07pH015LOl/SduiZLJH0tIkLSzbZn2T4s3w72QeROAMrCvWEBAJXUjWGbef/gcG3Gw/yxtOH+7YWSjpd0i+0lktZGxB2jVmtrlkUAAIqW1KM3brY8aUqpuxwtRnambWBkR3oQqdsYeTI5hNi+LW0DEycnx+DEbRTyWUp9HUUMG5u0X1r7KVPT2qd+FnbvTmsPJOjS2cqNEbF4rBVs7y/pm5LOVTac80JlwzYB9KEo5Lsq0pr3QwyFSMt9YqiAv9xO20YPhv33RLmFHgAABerFd7XtScqKvMsi4mrbL5Z0hKQ78uRhnqTbbJ8oZlkEAPQIhR4AoLJc8g0WnFVyX5G0MiIukqSIuEvSwXXrPChpcURstH2NpPfbvkLZJCxbuD4PAFAGCj0AANp3sqR3SrrL9u35sgvzCTYa+b6kN0haJekpSe/peoQAAIhCDwBQUe3c965oEXFjq91GxMK6n0PSOV0OCwCA56DQAwBU1r5xOT0AAONHoQcAqKwhKj0AABriPnoAAAAAMGDo0QMAVJRLn3UTAICqoNADAFRSLyZjAQCgKij0AADV5N7cMB0AgCqg0AMAVBZ1HgAAjTEZCwAAAAAMGHr0AACVNUSfHgAADVHoAQAqiclYAABojkIPAFBZTMYCAEBjFHoAgMqizgMAoLFyC70IxcjOztvvHkmPYWRHWvtdu9Jj2LE9qXk881RyCLH2V8nbSI5h2syk9p45OzkGT52e1D7p81yT+H56x9S0/Q9NSGsPAMAYIqKIjaS174cccqSAGJJfRwGnxyYmlg8TJqXHkLiNSMx9PFSN+Szp0QMAVJbp0wMAoCEKPQBAJVnSEHUeAAANUegBACqLOg8AgMYo9AAAlUWhBwBAYx1fSWh7vu0f277H9grbHywyMAAAgEFC7gSgTCk9eiOSzouI22zPkHSr7esi4p6CYgMAYExMxoKKIXcCUJqOC72IWCdpXf7zNtsrJc2VxB8rAEApuGE6qoTcCUCZCrlGz/ZCScdLuqWI7QEA0IqVcP0B0GPkTgC6Lfk70vb+kr4p6dyI2Nrg+aW2l9tevmHTptTdAQAAVNq4cqeN5E4AOpNU6NmepOwP1WURcXWjdSJiWUQsjojFB82Zk7I7AAD24i48gG4ad+40TO4EoDMdD920bUlfkbQyIi4qLiQAANpjLtJDhZA7AShTSo/eyZLeKenVtm/PH28oKC4AAFqiRw8VQ+4EoDQps27eKL4TAQA9QmGGqiF3AlAmJiwDAAAAgAFTyO0VAAAonc01egAANFFuobd7l/TEYx03j6e2pMewa1da+ylT02MY2ZHUPLZuTo/hsQ1p7bc8nh7D7rT3Ig4+LDmEmDk7eRvJUj9T+01Pau6D56ftH+ihIeo8oP9FpG9j18609ju2p8ewfVtS83hsfXIIsf2JtA0MTUiOwTMOTGs/s4CZZKfun9Z+4pSk5lGRk4z06AEAKstUegAANEShBwCoJEuqyElVAABKx2QsAAAAADBg6NEDAFST6dEDAKAZCj0AQGUx6yYAAI1R6AEAKos6DwCAxij0AACVRY8eAACNMRkLAAAAAAwYevQAAJXE7RUAAGiOQg8AUE2Whqj0AABoiEIPAFBZ1HkAADRGoQcAqCgzGQsAAE0wGQsAAAAADBgKPQBAJVmSh4p/jLlPe77tH9u+x/YK2x/Ml/+l7Xtt32n7W7Zn1bW5wPYq27+w/bvdPCYAANRQ6AEAqsnZffSKfrQwIum8iDha0kmSzrF9tKTrJB0TES+R9EtJF0hS/twZkl4k6TRJf2t7QpeOCAAAz6LQAwBUll38YywRsS4ibst/3iZppaS5EXFtRIzkq90saV7+8xJJV0TEMxHxgKRVkk7sxrEAAKBeyZOxhBS7O2++c0dxoXTIQ+m1cTyzPW0DWzYmx6ChtBPKsfHR9Bgefjit/YGrk0PwwqPSNjD/yPQYps9Maz/n8LQAdo20XmdMkdgeqCbbCyUdL+mWUU/9oaRv5D/PVVb41azJlwGVEZH4d373rvQgdj6d1Dy2bU4OIR5ckbaBXya2lxTrE/OvSZOSY9CCI5Kax6IXJ4cwdHhi/jY9MZ9PrgfKyZ2YdRMAUFldmnVz2Pbyut+XRcSyUfvdX9I3JZ0bEVvrln9E2fDOy7oRGAAA7aLQAwBUVpfurrAxIhY336cnKSvyLouIq+uWnyXpdEmnxp4ukLWS5tc1n5cvAwCgq7hGDwBQSZY0ZBf+GHOfWRfiVyStjIiL6pafJul8Sb8XEU/VNblG0hm2p9g+QtIiST8t+lgAADAaPXoAgGpqY/KULjhZ0jsl3WX79nzZhZK+IGmKpOvy4aQ3R8QfRcQK21dKukfZkM5zIqKAC5YAABhbcqGXTxO9XNLaiDg9PSQAAPpTRNyorDNxtO+P0ebTkj7dtaBQOeROAMpQRI/eB5VNL502dSAAAOPUpclYgG4jdwLQdUnX6NmeJ+mNkr5cTDgAALSv7PvoAanInQCUJbVH73PKLj6fkR4KAADtsyjMUEmfE7kTgBJ03KNn+3RJ6yPi1hbrLbW93PbyDZse63R3AADszZaHin8A3dJR7rRxU0nRARg0KUM3T5b0e7YflHSFpFfb/vrolSJiWUQsjojFB805MGF3AAAAlTb+3Gl4TtkxAhgQHRd6EXFBRMyLiIWSzpD0o4h4R2GRAQDQAtfooUrInQCUifvoAQAqq9UNzgEA2FcVUuhFxPWSri9iWwAAtIPJWFBl5E4Auo0ePQBAZXEfPQAAGku6jx4AAAAAoP+U26PnIWnSfp03nzE7PYahCYntC6iNd21Ma7/p0eQQ4rafJbXfev2dyTGs+NXjSe0PmjklOYYFx/0iqf3kk45LjkHHnpjWfvoBSc2d+pmOSGsPdIrJU4BypP6d370rPYYdTyc1j4fvTw4hbr0pqf32H/00OYaHf7U5qf1++6Wn/of+u18ltZ84MpIcQ0yfmdTek6emBTBhUlr7klInhm4CACqLoZsAADRGoQcAqCzqPAAAGuMaPQAAAAAYMPToAQAqKbu9Al16AAA0QqEHAKgmZ3N8AQCA56LQAwBUlOnRAwCgCQo9AEB1DVHoAQDQCINeAAAAAGDA0KMHAKguhm4CANAQhR4AoJrMrJsAADRDoQcAqC6u0QMAoCEKPQBARZmhmwAANMFkLAAAAAAwYOjRAwBUki2ZoZsAADREoQcAqC6GbgIA0BCFHgCgsujRAwCgsfILvZQv5UlT0vc/siOpeWzZnBxCrF+dtoFtW5NjeObeXye1/96KR5Nj+H9bn07bwPrkEHT2trTPw/FHzU0PYlPisTw48TM5azitPdBL9OgBJYi05rt3pUewIzVnWJscw667701qf9utDyfHcPO27UntD5yYPj3HKc+kvZ9Hzv9lcgw66jeTmvvAQ9P2H1PT2peEyVgAAAAAYMAwdBMAUE0299EDAKAJCj0AQGWZoZsAADREoQcAqC569AAAaCjpGj3bs2xfZfte2yttv7yowAAAAAYNuROAsqT26H1e0r9ExFtsT5Y0rYCYAABozWLWTVQRuROAUnRc6Nk+QNIrJZ0lSRGxQ1LaXPUAAIyDmTsaFULuBKBMKV+RR0jaIOmrtn9u+8u2pxcUFwAArdnFP4DuIXcCUJqUQm+ipBMkfSkijpf0pKQPj17J9lLby20v37Ap/WbjAABIkmx5qPgH0EXjz502bio7RgADIqXQWyNpTUTckv9+lbI/XnuJiGURsTgiFh80Z3bC7gAAACpt/LnT8JxSAwQwODou9CLiEUmrbb8gX3SqpHsKiQoAgHYwdBMVQu4EoEyps25+QNJl+axR90t6T3pIAAC0iaGWqB5yJwClSCr0IuJ2SYuLCQUAgPZlHXAUeqgWcicAZUnt0QMAoHfo0QMAoCHuQAQAAAAAA6ZaPXojBdxTdNfO3sewe1da+6EJySEMTU576ycOyHCpJ3btTtvAU0+lB7Fta1Lz2LIxbf/7H5DWPiKtPdCx8idPsT1f0tckHSIpJC2LiM/bni3pG5IWSnpQ0lsj4jFnY0s/L+kNkp6SdFZE3FZq0EDPFfA9sWskrf2OZ5JDGNm6Pan9YyOJ+Z+kB55Oy2Mfn5ieQ56wNTEXLiJ32pn4fkZi/pec+5STO9GjBwCoLNuFP1oYkXReRBwt6SRJ59g+Wtm90H4YEYsk/VB77o32ekmL8sdSSV/qxnEAAGA0Cj0AQDVZ2TV6RT/GEBHraj1yEbFN0kpJcyUtkXRpvtqlkt6c/7xE0tcic7OkWbYPK/5gAACwt2oN3QQAoE6XZt0ctr287vdlEbGswb4XSjpe0i2SDomIdflTjygb2illReDqumZr8mXrBABAF1HoAQCwt40RMeb097b3l/RNSedGxNb6gjMiwjYXrwIAeopCDwBQXT24vYLtScqKvMsi4up88aO2D4uIdfnQzPX58rWS5tc1n5cvAwCgq7hGDwBQTXZ3HmPu0pb0FUkrI+KiuqeukfTu/Od3S/pO3fJ3OXOSpC11QzwBAOgaevQAAJXl8nv0Tpb0Tkl32b49X3ahpM9KutL22ZJ+Lemt+XPfV3ZrhVXKbq/wnlKjBQDssyj0AABoU0TcqGy+z0ZObbB+SDqnq0EBANAAhR4AoLpKvmE6AABVQaEHAKim2n30AADAc1DoAQAqq0v30QMAoPIo9AAAFWV69AAAaILbKwAAAADAgKFHDwBQXQzdBACgIQo9AEA1WRR6AAA0QaEHAKguCj0AABqqVqEXkb6JkZ0FBJJoytS09tOnJ4cwac7+Se0XTpmcHMMN2p68jVRHHJp4LIeH04OYMCGt/fYn0trv3JHWvoD/l0BnLA1xqTnQ95z+/9ST0vKOmHFAcgxT5s5Oan/E/g8nx3DK7t1J7acV8Ddz3tw+yJ2mzUxrPyGxBEo+yVjOSUq+IQEAAABgwFSrRw8AgHoM3QQAoCEKPQBANTEZCwAATVHoAQCqi0IPAICGkq7Rs/0h2yts3237ctv7FRUYAABjyydjKfoBdBG5E4CydPyNZnuupD+RtDgijpE0QdIZRQUGAAAwSMidAJQpdejmRElTbe+UNE1S+ryxAAC0i6GbqB5yJwCl6LhHLyLWSvorSQ9JWidpS0RcW1RgAACMqTYZS9EPoEvInQCUKWXo5oGSlkg6QtLhkqbbfkeD9ZbaXm57+YZNmzuPFACA0Sj0UCEd5U4bN5UdJoABkXLV+WskPRARGyJip6SrJb1i9EoRsSwiFkfE4oPmzE7YHQAA9ZiMBZUz/txpeE7pQQIYDCnfaA9JOsn2NNuWdKqklcWEBQAAMHDInQCUpuPJWCLiFttXSbpN0oikn0taVlRgAAC0xFBLVAi5E4AyJc26GREfl/TxgmIBAKB9tclYgAohdwJQltTbKwAA0DsUegAANMRV5wAAAAAwYMrv0XNCbTlxUvruE9tHcgSSps1Maz9ze3oM8+YlNT/ulVuTQ5hzR9o9YmfOmJwcw0Gnn5jU3i86NjkGzTggrf3MxNlsJyUeR3pU0COWZWbJBEqQ+Hd+aEJ6CJOnprU/bGFyCD7uhKT2R+8cSY5h4X2PJrUfmpqeS099yVFJ7f3CY5Jj8OxD0jaQWlOk1DMlYugmAKC6ONEAAEBDFHoAgGpiMhYAAJqi0AMAVBeFHgAADVVjgCkAAAAAoG306AEAKsoSk7EAANAQhR4AoLoYugkAQEMUegCAamIyFgAAmqLQAwBUF4UeAAANcXEDAAAAAAwYevQAABXFZCwAADRDoQcAqC6GbgIA0BCFHgCgmpiMBQCApij0AAAVxdBNAACa4RsSAAAAAAYMPXoAgOpi6CYAAA1R6AEAqotCDwCAhkou9Cw5YbTopCnpIQylvWQXkVTMnJ3UPNIjkBe9MKn9lMPnJ8dw1Mkbk9p70qTkGLRwUVr7OYcmh+AZB6a1nzknLYChCYntGQGOHmEyFqAcqf/PUr9nJGnyfmkhHJyet+w+9uVpMQwfnBzD/i/bkLaBCQXkTofNS2rueb+RHIJnJOY+ExNritTPdEnfXWRoAACMg+2Lba+3fXfdsuNs32z7dtvLbZ+YL7ftL9heZftO2yf0LnIAwL6EQg8AUFH5rJtFP1q7RNJpo5b9haRPRsRxkj6W/y5Jr5e0KH8slfSlIl45AACtUOgBAKrLLv7RQkTcIGnz6MWSZuY/HyDp4fznJZK+FpmbJc2yfVhBrx4AgKaYjAUAUF39c43euZJ+YPuvlJ1EfUW+fK6k1XXrrcmXrSs1OgDAPqdlj16TaxFm277O9n35v2mzSQAAMF5WNsFX0Q9pOL/OrvZY2kY075P0oYiYL+lDkr7SxVeOPkfuBKAftDN08xI991qED0v6YUQskvTD/HcAAAbBxohYXPdY1kabd0u6Ov/5HyWdmP+8VlL9dH/z8mUYbJeI3AlAj7Us9Jpci7BE0qX5z5dKenOxYQEA0IqloS48OvOwpFflP79a0n35z9dIelc+++ZJkrZEBMM2Bxy5E4B+0Ok1eofUfVE9IumQZivmQ16WStKCeXM73B0AAA2k3Ju1013al0s6RdkQzzWSPi7pvZI+b3uipKeVf+9J+r6kN0haJekpSe8pPWD0i85yp/np938DsG9KnowlIsJ203t450NelknS4uOOLeJe3wAAZHowGUtEnNnkqX/XYN2QdE53I0LVjCt3OuF4cicAHem00HvU9mERsS6fJnp9kUEBANCS3e5974B+QO4EoFSdfkNeo+zCc+X/fqeYcAAAAAYSuROAUrVze4XLJd0k6QW219g+W9JnJb3W9n2SXpP/DgBAuXpww3SgFXInAP2g5dDNMa5FOLXgWAAAGJ8eTMYCtELuBKAfJE/GAgBAz9ADBwBAQxR6AIBqYjIWAACaKrnQCyl2l7vL0Tq/GW5m0n7JIXj6AYkxTE6OIXbtTNvAhEnJMTg1hie2JMeQrIDjoKn7p7WfMj2t/e6RtPaiRwUABpkTe85jaEJ6EBOnpLWfNjM5hKF5i5Lax/DhyTHo6SfT2hfwXnhqYt6xX2LeI0mTE/PxiYn5W0VGk9CjBwCorop82QIAUDYKPQBAdTEZCwAADVHoAQCqyU4fjg8AwIDiVCgAAAAADBh69AAA1cXQTQAAGqLQAwBUF5OxAADQEIUeAKCiTI8eAABNUOgBAKrJYjIWAACa4FQoAAAAAAwYevQAANXFNXoAADREoQcAqC6u0QMAoCEKPQBANXHDdAAAmqLQAwBUFz16AAA0xDckAAAAAAwYevQAANXFZCwAADREoQcAqChumA4AQDPVKvRGdhawjR1p7ScUcMgmTkpq7qEJ6TEcMJzWfsrU9Bh270prv9/05BBix9NJ7V3EcUi1M+01FPKZBnqBG6YDleACet4jNfeZtF9yDBpK+74sJGeYMTt9G6lS34vEPLiQGBJPEhbxmS4DGR4AoLro0QMAoCG+IQEAAABgwNCjBwCorooMnwEAoGwUegCAirI0xMAUAAAaafkNafti2+tt31237C9t32v7Ttvfsj2rq1ECADCalfXoFf0AEpE7AegH7ZwKvUTSaaOWXSfpmIh4iaRfSrqg4LgAAACq6hKROwHosZaFXkTcIGnzqGXXRsRI/uvNkuZ1ITYAAMbmoeIfQCJyJwD9oIhvtD+U9M/NnrS91PZy28s3bNrcbDUAAMapC8M2GbqJcrSfO23cVGJYAAZJUqFn+yOSRiRd1mydiFgWEYsjYvFBc/rgJo8AgMExNFT8A+iicedOw3PKCw7AQOl41k3bZ0k6XdKpERGFRQQAQDtqk7EAFUHuBKBMHRV6tk+TdL6kV0XEU8WGBAAAMFjInQCUrWWhZ/tySadIGra9RtLHlc0UNUXSdc7Opt4cEX/UxTgBABjFTJ6CvkTuBKAftCz0IuLMBou/0oVYAAAYH4Zuog+ROwHoBx1fowcAQM/RowcAQEMUegCAarKlIXr0AABopPxCL3Z33nbH9vTd73wmqb0nTUmOQZOnprWfWMDbNmlyUvNCjsPQhLT2++2fHEJyipjyea5tIvEzGVvT7rHkAw5Kag8AQLc58dYnEQWcFEoeQTApPYZ+mKw1ech8Ee9F2ja8jwz7p0cPAFBdDN0EAKAhCj0AQHXtI2dlAQAYL06FAgAqKr+9QtGPVnu1L7a93vbdo5Z/wPa9tlfY/ou65RfYXmX7F7Z/twsHAgCA56BHDwBQWT26zuISSV+U9LW6OH5H0hJJx0bEM7YPzpcfLekMSS+SdLikf7X9/IjYVXrUAIB9Cj16AACMQ0TcIGnzqMXvk/TZiHgmX2d9vnyJpCsi4pmIeEDSKkknlhYsAGCfRaEHAKgmqydDN5t4vqTftn2L7X+z/dJ8+VxJq+vWW5MvAwCgqxi6CQCoKHdr1s1h28vrfl8WEctatJkoabakkyS9VNKVto/sRnAAALSDQg8AUF3duWH6xohYPM42ayRdHREh6ae2d0salrRW0vy69eblywAA6CqGbgIAqqt/hm5+W9LvSJLt50uaLGmjpGsknWF7iu0jJC2S9NP0Fw4AwNjo0QMAYBxsXy7pFGVDPNdI+rikiyVdnN9yYYekd+e9eytsXynpHkkjks5hxk0AQBko9AAA1WT15IbpEXFmk6fe0WT9T0v6dPciAgDguSj0AAAV1bXJWAAAqDwKPQBAdfXmhukAAPQ9ToUCAAAAwIChRw8AUF0M3QQAoCEKPQBANdnduo8eAACVV36hl3L2tYAzt540JW0Dk6cmx6CJk9K3kcgzD+p1CNKECWnt++FMfuxO3oRTt7E70tpPSfxMDyW+j0CKfvg7AKDvuYjrefvgmuDsri29VcixRCno0QMAVBcJBwAADXEqFAAAAAAGDD16AICK4j56AAA00/Ib0vbFttfbvrvBc+fZDtvD3QkPAIAx2MU/gETkTgD6QTunQi+RdNrohbbnS3qdpIcKjgkAgNasrEev6AeQ7hKROwHosZbfaBFxg6TNDZ76a0nnS+r99D8AgH2QpaGh4h9AInInAP2go28020skrY2IOwqOBwAAYOCQOwEo27gnY7E9TdKFyoYetLP+UklLJWnBvLnj3R0AAE1xPydUQVLuNH9+FyMDMMg66dE7StIRku6w/aCkeZJus31oo5UjYllELI6IxQfNmd15pAAAjMY1eqiGznOn4TklhglgkIy7Ry8i7pJ0cO33/A/W4ojYWGBcAACMzWKWTFQCuROAXmjn9gqXS7pJ0gtsr7F9dvfDAgCgFdOjh75E7gSgH7Ts0YuIM1s8v7CwaAAAACqO3AlAPxj30E0AAPoGQzcBAGiIQg8AUF3c9w4AgIYo9AAA1WTTowcAQBOlFnq33nHXxqHh+b8eY5VhSb2egYoY+iOGXu+fGNqP4XllBQIA+5pbf377Rk+fRe7U/zH0ev/EUK0YSsmdSi30IuKgsZ63vTwiFpcVDzH0bwy93j8x9FcMQFPMkokBR+5UjRh6vX9iIIZGGLoJAKguhm4CANAQhR4AoMIo9AAAaKTfCr1lvQ5AxFDT6xh6vX+JGGr6IQagASZjAdQff6OJoff7l4ihhhhyjohexwAAwLgtfskx8bN/urLw7Q4teNGt/XBtBQAAKfqtRw8AgPbRowcAQEMUegCACqPQAwCgkb6Zl9r2abZ/YXuV7Q/3YP/zbf/Y9j22V9j+YNkx5HFMsP1z29/r0f5n2b7K9r22V9p+eQ9i+FD+Htxt+3Lb+5Wwz4ttr7d9d92y2bavs31f/u+BPYjhL/P34k7b37I9q+wY6p47z3bYHu5mDEDbrD03TS/yAVQAedNesZA7kTuROzXQF4We7QmS/kbS6yUdLelM20eXHMaIpPMi4mhJJ0k6pwcxSNIHJa3swX5rPi/pXyLihZKOLTsW23Ml/YmkxRFxjKQJks4oYdeXSDpt1LIPS/phRCyS9MP897JjuE7SMRHxEkm/lHRBD2KQ7fmSXifpoS7vHxgfd+EB9DnypucgdyJ3qkfulOuLQk/SiZJWRcT9EbFD0hWSlpQZQESsi4jb8p+3KftPOrfMGGzPk/RGSV8uc791+z9A0islfUWSImJHRDzeg1AmSppqe6KkaZIe7vYOI+IGSZtHLV4i6dL850slvbnsGCLi2ogYyX+9WdK8smPI/bWk8yUxexMA9B55U47c6VnkTnuWkTvl+qXQmytpdd3va9SDPxY1thdKOl7SLSXv+nPKPhC7S95vzRGSNkj6aj4E4su2p5cZQESslfRXys5+rJO0JSKuLTOGOodExLr850ckHdKjOGr+UNI/l71T20skrY2IO8reN9AaXXrYJ5E37fE5kTuROzW3T+dO/VLo9Q3b+0v6pqRzI2Jrifs9XdL6iLi1rH02MFHSCZK+FBHHS3pS3e9y30s+lnuJsj+ch0uabvsdZcbQSGT3IenZGRnbH1E2TOaykvc7TdKFkj5W5n6B9nTh+jyu0QPGpVd5U75vcieROzVD7tQ/hd5aSfPrfp+XLyuV7UnK/lhdFhFXl7z7kyX9nu0HlQ3BeLXtr5ccwxpJayKidkbuKmV/vMr0GkkPRMSGiNgp6WpJryg5hppHbR8mSfm/63sRhO2zJJ0u6e1R/o0vj1L2xXFH/tmcJ+k224eWHAfQGIUe9k3kTRlypwy50yjkTpl+KfR+JmmR7SNsT1Z2Aek1ZQZg28rGV6+MiIvK3LckRcQFETEvIhYqe/0/iohSz8ZExCOSVtt+Qb7oVEn3lBmDsmEHJ9melr8np6p3F1hfI+nd+c/vlvSdsgOwfZqyISm/FxFPlb3/iLgrIg6OiIX5Z3ONpBPyzwrQBxi6iX3SPp83SeROdcid6pA77dEXhV5+weT7Jf1A2QfzyohYUXIYJ0t6p7KzQbfnjzeUHEM/+ICky2zfKek4SZ8pc+f5GbGrJN0m6S5ln9Fl3d6v7csl3STpBbbX2D5b0mclvdb2fcrOln22BzF8UdIMSdfln8m/60EMAIA+Qt7Ud8idyJ36Mndy+b2ZAACkW3zsi+Nn1xZ/snjo0KNujYjFhW8YAIASTex1AAAAdI6hlgAANEKhBwCoJiZPAQCgqb64Rg8AAAAAUBx69AAA1UWPHgAADVHoAQAqjEIPAIBGGLoJAKgs24U/2tjnxbbX2767wXPn2Q7bw/nvtv0F26ts32m77BspAwD2URR6AIDqqk3IUuSjtUsknfbcUDxf0uuU3by45vWSFuWPpZK+lPyaAQBoA4UeAADjEBE3SNrc4Km/lnS+pPob1C6R9LXI3Cxplu3DSggTALCPo9ADAFSUu/TQsO3ldY+lLSOxl0haGxF3jHpqrqTVdb+vyZcBANBVTMYCAKiu7sy6uTEiFrcfgqdJulDZsE0AAPoChR4AoJqsfrm9wlGSjpB0Rz6ZyzxJt9k+UdJaSfPr1p2XLwMAoKsYugkAqLCuDN0cl4i4KyIOjoiFEbFQ2fDMEyLiEUnXSHpXPvvmSZK2RMS6jl8uAABtotADAGAcbF8u6SZJL7C9xvbZY6z+fUn3S1ol6R8k/XEJIQIAwNBNAECF9WDoZkSc2eL5hXU/h6Rzuh0TAACjUegBAKqrLy7RAwCg/1DoAQAqqrNr6gAA2BdQ6AEAqqs/Zt0EAKDvMBkLAAAAAAwYevQAANXUP/fRAwCg71DoAQAqjEIPAIBGKPQAANVFjx4AAA1xjR4AAAAADBh69AAAFWV69AAAaIJCDwBQYRR6AAA0QqEHAKguevQAAGjIEdHrGAAAGDfb/yJpuAub3hgRp3VhuwAAlIZCDwAAAAAGDLNuAgAAAMCAodADAAAAgAFDoQcAAAAAA4ZCDwAAAAAGDIUeAAAAAAyY/w9x9lmMGZpxfQAAAABJRU5ErkJggg==\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteR4 = trim(imagen[:,:,0], 442, 370, 15, 15)\n", + "poptR4, pcovR4 = curve_fit(gauss2d, xdata4, recorteR4.ravel(), p0=[1,0,1,1,1])\n", + "estrellaR4=gauss2d(xdata4, poptR4[0], poptR4[1],poptR4[2], poptR4[3], poptR4[4])\n", + "FWHMR4=FWHMR.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptR4[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 4 fotografÃa (Banda Rojo)\")\n", + "plt.imshow(recorteR4, plt.get_cmap('Reds'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 4 a partir de la gaussiana (Banda Rojo)\")\n", + "plt.imshow(estrellaR4.reshape(15, 15), plt.get_cmap('Reds'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 5 (Rojo)" + ] + }, + { + "cell_type": "code", + "execution_count": 358, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteR5 = trim(imagen[:,:,0], 320, 455, 15, 15)\n", + "poptR5, pcovR5 = curve_fit(gauss2d, xdata5, recorteR5.ravel(), p0=[1,1,1,1,1])\n", + "estrellaR5=gauss2d(xdata5, poptR5[0], poptR5[1],poptR5[2], poptR5[3], poptR5[4])\n", + "FWHMR5=FWHMR.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptR5[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 5 fotografÃa (Banda Rojo)\")\n", + "plt.imshow(recorteR5, plt.get_cmap('Reds'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 5 a partir de la gaussiana (Banda Rojo)\")\n", + "plt.imshow(estrellaR5.reshape(15, 15), plt.get_cmap('Reds'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 6 (Rojo)" + ] + }, + { + "cell_type": "code", + "execution_count": 359, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteR6 = trim(imagen[:,:,0], 535, 335, 10, 10)\n", + "poptR6, pcovR6 = curve_fit(gauss2d, xdata6, recorteR6.ravel(), p0=[1,0,1,1,1])\n", + "estrellaR6=gauss2d(xdata6, poptR6[0], poptR6[1],poptR6[2], poptR6[3], poptR6[4])\n", + "FWHMR6=FWHMR.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptR6[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 6 fotografÃa (Banda Rojo)\")\n", + "plt.imshow(recorteR6, plt.get_cmap('Reds'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 6 a partir de la gaussiana (Banda Rojo)\")\n", + "plt.imshow(estrellaR6.reshape(10, 10), plt.get_cmap('Reds'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 7 (Rojo)" + ] + }, + { + "cell_type": "code", + "execution_count": 360, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteR7 = trim(imagen[:,:,0], 540, 345, 10, 10)\n", + "poptR7, pcovR7 = curve_fit(gauss2d, xdata7, recorteR7.ravel(), p0=[1,2,1,1,1])\n", + "estrellaR7=gauss2d(xdata7, poptR7[0], poptR7[1],poptR7[2], poptR7[3], poptR7[4])\n", + "FWHMR7=FWHMR.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptR7[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 7 fotografÃa (Banda Rojo)\")\n", + "plt.imshow(recorteR7, plt.get_cmap('Reds'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 7 a partir de la gaussiana (Banda Rojo)\")\n", + "plt.imshow(estrellaR7.reshape(10, 10), plt.get_cmap('Reds'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 8 (Rojo)" + ] + }, + { + "cell_type": "code", + "execution_count": 361, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteR8 = trim(imagen[:,:,0], 620, 306, 20, 20)\n", + "poptR8, pcovR8 = curve_fit(gauss2d, xdata8, recorteR8.ravel(), p0=[1,0,1,1,1])\n", + "estrellaR8=gauss2d(xdata8, poptR8[0], poptR8[1],poptR8[2], poptR8[3], poptR8[4])\n", + "FWHMR8=FWHMR.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptR8[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 8 fotografÃa (Banda Rojo)\")\n", + "plt.imshow(recorteR8, plt.get_cmap('Reds'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 8 a partir de la gaussiana (Banda Rojo)\")\n", + "plt.imshow(estrellaR8.reshape(20, 20), plt.get_cmap('Reds'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 9 (Rojo)" + ] + }, + { + "cell_type": "code", + "execution_count": 362, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteR9 = trim(imagen[:,:,0], 545, 360, 10, 10)\n", + "poptR9, pcovR9 = curve_fit(gauss2d, xdata9, recorteR9.ravel(), p0=[1,0,1,1,1])\n", + "estrellaR9=gauss2d(xdata9, poptR9[0], poptR9[1],poptR9[2], poptR9[3], poptR9[4])\n", + "FWHMR9=FWHMR.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptR9[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 9 fotografÃa (Banda Rojo)\")\n", + "plt.imshow(recorteR9, plt.get_cmap('Reds'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 9 a partir de la gaussiana (Banda Rojo)\")\n", + "plt.imshow(estrellaR9.reshape(10, 10), plt.get_cmap('Reds'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 10 (Rojo)" + ] + }, + { + "cell_type": "code", + "execution_count": 363, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteR10 = trim(imagen[:,:,0], 615, 394, 10, 10)\n", + "poptR10, pcovR10 = curve_fit(gauss2d, xdata10, recorteR10.ravel(), p0=[1,0,1,1,1])\n", + "estrellaR10=gauss2d(xdata10, poptR10[0], poptR10[1],poptR10[2], poptR10[3], poptR10[4])\n", + "FWHMR10=FWHMR.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptR10[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 10 fotografÃa (Banda Rojo)\")\n", + "plt.imshow(recorteR10, plt.get_cmap('Reds'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 10 a partir de la gaussiana (Banda Rojo)\")\n", + "plt.imshow(estrellaR10.reshape(10, 10), plt.get_cmap('Reds'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Histograma (Banda Rojo)" + ] + }, + { + "cell_type": "code", + "execution_count": 446, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Datos de FWHM de las estrellas para la Banda rojo :\n", + "Desviación : 2.329889939974896\n", + "Media : 4.021186556528661\n", + "Mediana : 2.9192045463592478\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "FWHMR = np.array(FWHMR)\n", + "sigmaR = FWHMR.std()\n", + "mediaR = FWHMR.mean()\n", + "medianaR = np.median(FWHMR)\n", + "print(\"Datos de FWHM de las estrellas para la Banda rojo :\")\n", + "print(\"Desviación :\", sigmaR)\n", + "print(\"Media :\", mediaR)\n", + "print(\"Mediana :\", medianaR)\n", + "plt.hist(FWHMR)\n", + "plt.xlabel('FHWM')\n", + "plt.ylabel('# de estrellas')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Para la banda G\n", + "* ## Estrella 1 (Verde)" + ] + }, + { + "cell_type": "code", + "execution_count": 411, + "metadata": {}, + "outputs": [], + "source": [ + "FWHMG=[]" + ] + }, + { + "cell_type": "code", + "execution_count": 412, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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tlvQWZSf3F+TLi9bzJnrvm/reRMSzyoZOvUdZC+AVEbFJ2Yn/5yQdUPcZ2imyCWxeLD5RbNq2nvfAqM/krIg4pm6dVyrrFjqhSZn82f5DvzQJxxPKDu5I/vhRSb/RYBNflnRerXnf9hxn/b8bmSXpGUkbbc9Vg8sa2J7qrDvggKQptqdP0Po12uWS3mf74PwPxCcl3ZI3zUvbvs6J1v+WpN+yfVze+nWqsrMsbXutY5R9TtKTzgatn9Ng/es0QZO77R2UNXvXZhedpWzs23plx/UvlfWXL+JHedmP5O/P7ytrrWs1dilL/t6irG//JXXLm/2cXZnHNc/ZxDEvnq2LiLXKuoP8re0dnU0QsK/t+uP2RmV95IHJgwlf0OMmaZ1klqSnJD1j+zclFZmG/3866z1zgLLxa7Wxeq1sq8hxm8i3lF3+6Pfzes9HtHW958uSzspjlbMJ1f6wwHanKRtmsl7SFttHKxvjOJ4rJZ1me66zSUX+oolt3Zm/hoPz9+3c2hO2p9l+l+2d8q6NTyn/zNk+1tkkRFZ2YnxYL30e67XyvtSXbaaO2Kiet6uk/09b1/NeUNaDbabyFsGCGr33rdRvL5H0R8paWy+RpIgYUdYt87POL7+Qv89vH3cr2efhLGeTC85TNt635lZJTzubIGZG3vp5oLPxkDWF6nlVT/7+xVtfU+eafPmrJd1i+xllk3mclveNlbIvxyV5k+nx42z3c3m5G5z1NV6mbKBxI59QNmB3o7IP19UN1v+KskTiREkfz++fNGGJXER8R9L/VHYmZK2ywaH1/X7PVd3rnGj9yAal/qGkv1H2Rdpf2aDaF9r4WutdIGmGsrMiy5Q1g0/kUknHOJ8hKbdn7X1X1iy+i7J+1pJ0fb7NX+TPPa+CXUbyszW/r+zyEo8r+zLXv7ZmY1eeYP+npO2Vfa5qmv2cfUXZa7tT2eDm0cf8Pcp+LO5VVsG4Slm//poTlV8rEZg0BjpwA1rTT3WSP1fW+vJ0Xm68SVfq/UBZd8PvSvp0RNyQsK1z1fi4jauu3nO+snrPQkn/Uff8NZL+j6QrnHX9+6myiVkabfdpZcnElcp+h/9YW//uj/YVZSdu75J0h7IkaIuk4Ubbimwyvb+S9B1lY+FGjyU9SdKDefwf1Et1pIV5mWeUnfD+YkTcNEZsrbwvNc1+9pYqu0Zd/dm319bV81YoS4JrydClyup3a5TVeeon/JtQo/e+hdilbAjQRkmrI+LHdcv/Qtlnfln+PnxHW88/MdonlL2uB5R9Lv5vXdzDyibYOTh/foOyKwHsJEn5CYBjVOASE45tx3iizzkbsLpa0rvG+YPQdbY/KWldRFxQdixVZPsdkk6KiKZ/JIFe5aHpocUL2r/hi35+e0QsarwigEacTSz3gKSp0cT1bftR3rr35YgodFmJycT2/5N0ZUR8s+xYqsj2hyXNj4gzG63LhS8hScqboW9Rdqbvvyvr31z4TEqnRcTZZcdQZRHxL8qmCAYmD7ppAqiwvEfTm5S18uyubCjJNRMWmqQi4o/LjqHKIuLviq5LBxfUvFbZgNsNygbUHhfNTakMAN3HhC8AqsvKuvo9oazb5wptfR04oO1o+YMkKSLOVfsu/goA3UHLH9DT8nHvfFHHkM8U+eqGKwJtRPIHAKgu+q8AAFAYP5sAAAAA0Ae62vI3NDQUe+29V+MVxxFjXoak2W2UP7upE3PugTZ0cxqJtGPZjuOYOtHsZOlD4sT304lHYiTxvVz1q1V6bMNjk+XtQJVYdPvEpDc0NBR7L2i97gSg9/zqwYe0YcOGUn7Aupr87bX3XvrhLTe3XH7zyKbkGNqxjVTTBrZLKz+YVl6SntvybFL54TbM1jwcw0nlByZJ+jdlYFpS+WmJ5Z8feT6p/JGvm+j6tUCHTY4/A8C49l6wl/7jltGXcANQZa9/ze+Utm/G/AEAqmuA7A8AgKIY8wcAAAAAfYCWPwBAdTHmDwCAwpJa/mwfZfvntlfa/li7ggIAoKFOXOCdXBIdRt0JQJlabvmzPSjp7yW9VdJqST+2fW1E3Nuu4AAAGJ+TZ8sdS/lzQmOyou4EoGwpLX+HSVoZEfdHxCZJV0ha3J6wAABozHbbb0AHUXcCUKqU5G+upFV1j1fny7Zie4nt22zftmHDhoTdAQAAVFrTdaf166k7AWifjs/2GRFLI2JRRCwaGhrq9O4AAH3Ebv8NKFt93WnOHOpOANonZbbPNZLm1z2ely8DAKDjLGmgA9nacNu3CLyIuhOAUqW0/P1Y0kLb+9ieJukESde2JywAABowY/5QOdSdAJSq5Za/iNhi+0OSrpc0KOmiiLinbZEBANAAyRqqhLoTgLIlXeQ9Iq6TdF2bYgEAAJjUqDsBKFNS8gcAQHnopgkAQDO6mvyNaFjPbnmm5fLDsSU5hoi0y/fa6ROkbkl9HW2YjWDLyKak8iMaSY4h+b0YmJocQy9Irby24zMJVBW5HwAAxdHyBwCoJIsxfwAANIPkDwBQTSb5AwCgGfQXAwCgINvzbd9k+17b99g+LV/+Kds/s32X7Wtsz64rc5btlbZ/bvvtpQUPAOh7JH8AgMpyB/41sEXSGRGxv6TDJZ1qe39JN0o6MCJeJekXks6SpPy5EyQdIOkoSV+0PdihwwEAwIRI/gAAldXti7xHxNqIWJ7ff1rSCklzI+KGiBdn81omaV5+f7GkKyLihYh4QNJKSYd15GAAANAAY/4AAJXVoSF/Q7Zvq3u8NCKWbrtvL5B0iKRbRj31fklfz+/PVZYM1qzOlwEA0HUkfwAAbG1DRCyaaAXbO0j6hqTTI+KpuuUfV9Y19LLOhggAQPNI/gAAlWRZAyXM9ml7qrLE77KIuLpu+XslHSvpyHjpQqZrJM2vKz4vXwYAQNcx5g8AUFndHvPnbIULJa2IiM/ULT9K0pmS3hkRz9YVuVbSCba3s72PpIWSbm37gQAAoABa/gAA1VTOdf5eL+kkSXfb/km+7GxJn5e0naQb85iWRcQHI+Ie21dKuldZd9BTI2K420EDACCR/AEAKqzbuV9E/FAa83oQ101Q5jxJ53UsKAAACqLbJwAAAAD0AVr+AACVZJXS7RMAgMoi+QMAVBbJHwAAxZH8AQAqqvHsnAAA4CUkfwCAaipntk8AACqrq8lfRGjzyKaWy09xerjTp85MKj/Qhjlynh95Pqn8k5seS45hysDUpPIjMZIeQxvez1QDHkwqH4rGKzXaRqRtI/W9mDm4fVL5dnwnAADodam/122pMyRuw2NOVtzdbXDSrlzl174BAGgRdQgAAIoj+QMAVBKzfQIA0BySPwBAZZH8AQBQHMkfAKCyBkj+AAAorOWZGmzPt32T7Xtt32P7tHYGBgAAMJlQdwJQtpSWvy2SzoiI5bZnSbrd9o0RcW+bYgMAYHxmwhdUDnUnAKVqOfmLiLWS1ub3n7a9QtJcSfwBAwB0nLnIOyqGuhOAsrVlzJ/tBZIOkXRLO7YHAEAR7bhmFVAG6k4AypB8dWbbO0j6hqTTI+KpMZ5fYvs227c9tuHx1N0BAABUWjN1p/XrN3Q/QACTVlLyZ3uqsj9el0XE1WOtExFLI2JRRCzadWiXlN0BALAV222/AZ3UbN1pzpyh7gYIYFJruduns1/ICyWtiIjPtC8kAACKIVlDlVB3AlC2lJa/10s6SdKbbf8kvx3TprgAAGjIbv8N6CDqTgBKlTLb5w8lRtoDAMqRJWv8DKE6qDsBKFvyhC8AAAAAgN7Xlks9AADQfUzQAgBAM7qe/KVck2lEkbz/F4afTyofMZIew8gLSeU3j2xOjuHR5x5JKj9jyszkGKY47eO307TZyTEMx3BS+akD05JjGPRg2gYSP5JbEivPkRoAkIDkD+gPEWl1wGhDHXJLYv1rS6TX30YS66EDqXUOSVMHpiaVH2xD+jFgOi+2ipY/AEBlkfsBAFAcyR8AoLJo+QMAoDjaTAEAAACgD9DyBwCoJC71AABAc0j+AACVRfIHAEBxJH8AgMoi9wMAoDiSPwBARXGdPwAAmsGELwAAAADQB2j5AwBUFi1/AAAUR/IHAKgkZvsEAKA5JH8AgMoi9wMAoDiSPwBAZdHyBwBAcUz4AgAAAAB9gJY/AEB10fIHAEBhJH8AgIriOn8AADSD5A8AUE2m4Q8AgGZ0PflLOUs7oPJ/5Uc0kr6NGE4qv3lkc3IMA04b7rnmmdXJMWwa2ZRU/mUzX5Ycw4wpM5PKT3H6V2j64PSk8jtM3TGp/CDngAAAPS4USeU3jbyQHMMzmzcmlX/k2bVtiOGZpPKzt5udHMPuM/ZIKr/9lFnJMUwZmJpUPrUeXGXU+gAAlWQx2ycAAM3o37QXAFB5ttt+a7C/+bZvsn2v7Xtsn5Yv38X2jbbvy//fOV9u25+3vdL2XbYP7cJhAQBgTCR/AIDK6nbyJ2mLpDMiYn9Jh0s61fb+kj4m6bsRsVDSd/PHknS0pIX5bYmkL3XiOAAAUATJHwCgsuz23yYSEWsjYnl+/2lJKyTNlbRY0iX5apdIOi6/v1jSpZFZJmm27bQBMwAAtCg5+bM9aPsO2//ajoAAACjZkO3b6m5LxlrJ9gJJh0i6RdLuEVGbzeERSbvn9+dKWlVXbHW+DH2MuhOAsrRjwpfTlJ35TJtyEACAZhTrptmKDRGxaOJdewdJ35B0ekQ8VR9HRITttKkJMdlRdwJQiqSWP9vzJP2epK+2JxwAAIqpzfbZ5TF/sj1VWeJ3WURcnS9+tNadM/9/Xb58jaT5dcXn5cvQp6g7AShTarfPCySdKbXh4ncAADSphNk+LelCSSsi4jN1T10r6eT8/smS/rlu+XvyWT8Pl7Sxrnso+tMFou4EoCQtJ3+2j5W0LiJub7Dektq4icc3PN7q7gAA2EYJLX+vl3SSpDfb/kl+O0bS+ZLeavs+SW/JH0vSdZLul7RS0lck/VlHDgQqoZW60/r1G7oUHYB+kDLm7/WS3pn/6E2XtKPtf4yId9evFBFLJS2VpIMOfRVjIAAAlRURP1TW43QsR46xfkg6taNBoUqarjv99qJDqTsBaJuWW/4i4qyImBcRCySdIOl7o/94AQDQMR24zENn5o8BMtSdAJStHbN9AgBQig7N9gkAwKTUluQvIr4v6fvt2BYAAEVYHbvUA9Bx1J0AlIGWPwBAZZH8AQBQXOqlHgAAAAAAFdDVlj/LGkjIN+3yc9WRSL8sz+aRzUnlN428kBzDU5ueSir/1bu+lRzDmic2JpV/88sXJsfwtr3fmFR+1tQdkmN4fvi5pPLTB2ekBZD4tQoxER3KQ8Mf0PuySW/TjMRwUvnntvw6OYa7H7srqfzV992UHMPKx9Mum3bYnnOTY3jHvm9NKr/fTq9MjmHQg2kb6IGcoix0+wQAVJPp9gkAQDNI/gAA1UXyBwBAYf3b5gkAAAAAfYSWPwBAZdHtEwCA4kj+AACVZEkD5H4AABRG8gcAqCgu8g4AQDNI/gAA1WRpgOQPAIDCmPAFAAAAAPoALX8AgEqymPAFAIBmkPwBACqL7isAABRH8gcAqCzG/AEAUBzJHwCgkuj2CQBAc+gxAwAAAAB9gJY/AEBFmW6fAAA0geQPAFBNptsnAADNIPkDAFSSxdgFAACa0d3kz5Jd7k91xEhaeUVyDJtHNpdaXpJWPbM6qfw1Ny5LjmH43seSyj9+zMbkGF6zx0FJ5XfZbufkGLbEllLLD8ZgUvk2fCWAltHtE+h97ag7DcdwUvmNm55MjmHZ2juSyn/9Oz9KjuHpe9cllb//tfsmx7Bg9tyk8nvtsHdyDNOnzEwqPxBpn8kq9zrhpCkAAAAA9AG6fQIAKqvKZ18BAOg2kj8AQCVZdPsEAKAZJH8AgMoi9QMAoLikMX+2Z9u+yvbPbK+w/dp2BQYAADDZUHcCUKbUlr/PSfp2RPyB7WmS0qbeAQCgMC7yjkqi7gSgNC0nf7Z3kvS7kt4rSRGxSdKm9oQFAMDEbMb8oVqoOwEoW0q3z30krZf0Ndt32P6q7e3bFBcAAA3ZbvsN6CDqTgBKlZL8TZF0qKQvRcQhkn4t6WOjV7K9xPZttm97bH3aRb0BAKg3YLf9BnRQ03Wn9es3dDtGAJNYSvK3WtLqiLglf3yVsj9oW4mIpRGxKCIW7Tpn14TdAQAAVFrTdac5c4a6GiCAya3l5C8iHpG0yvZ++aIjJd3blqgAAGjAHboBnULdCUDZUmf7/LCky/LZqu6X9L70kAAAKIZumqgg6k4ASpOU/EXETyQtak8oAAA0gzF6qB7qTgDKlNryBwBAKWwxOycAAE1ImfAFAAAAAFARXW75s+zW882IkTbGUp5eOFM9kngsh7cMpwcRacU3b96SHELqcWiHgYTvhCQNejCp/EjiG5H4NgJJ6PYJoIh2/N5vGkmrdzz/wubkGPRsWgybNqXHsCXxOLTjvaDu0Tpa/gAAlVXGbJ+2L7K9zvZP65YdbHuZ7Z/k12c7LF9u25+3vdL2Xba3mdYfAIBuIfkDAFSSVdpF3i+WdNSoZX8j6RMRcbCkv8wfS9LRkhbmtyWSvtSGlw4AQEuY8AUAUFlldPuMiJttLxi9WNKO+f2dJD2c318s6dKICEnLbM+2vUdErO1OtAAAvITkDwCAdKdLut72p5X1qnldvnyupFV1663Ol5H8AQC6jm6fAICKsuz23yQN5eP2arclBYL5U0kfjYj5kj4q6cJOvnIAAFpByx8AoJKsjp3B3BARzV6E+2RJp+X3/0nSV/P7ayTNr1tvXr4MAICuo+UPAFBN+UXeO9Dy14qHJb0xv/9mSffl96+V9J581s/DJW1kvB8AoCy0/AEA0ATbl0s6Qln30NWSzpH0AUmfsz1F0vPKZvaUpOskHSNppaRnJb2v6wEDAJAj+QMAVFZJs32eOM5Tvz3GuiHp1M5GBABAMSR/AIBKql3nDwAAFEPyBwCorIQxegAA9B2SPwBARVkDIvkDAKAoZvsEAAAAgD5Ayx8AoLLo9gkAQHEkfwCASrKZ8AUAgGaQ/AEAKsuM+QMAoLCuJ39JP9Quf4jiQKTHMNVT08oPpJWXpL1n7ZVU/qgjX50cw5oDHksqf9jCBckxTBuYllT+hZEXkmNIfT8HEr8XqRNmUPVGmej2CfS+dpykSf2t23HaTskxLNr9wKTyRx/xaHIMD/3mhqTyB+8zPzmG39z5FUnlZ0yZmRzDANOWtIwjBwAAAAB9gG6fAIBKssyYPwAAmkDyBwCoLNOBBQCAwkj+AACVRcsfAADFJZ0ytf1R2/fY/qnty21Pb1dgAAA0YrvtN6CTqDsBKFPLyZ/tuZI+ImlRRBwoaVDSCe0KDAAAYDKh7gSgbKndPqdImmF7s6SZkh5ODwkAgMac/wMqhroTgNK03PIXEWskfVrSQ5LWStoYETe0KzAAACbkbMxfu29Ap1B3AlC2lG6fO0taLGkfSXtK2t72u8dYb4nt22zf9tj6tIt6AwBQjzF/qJJW6k7r16dd1BsA6qVM+PIWSQ9ExPqI2CzpakmvG71SRCyNiEURsWjXObsm7A4AgJdY0kAH/gEd1HTdac6coa4HCWDySvmVe0jS4bZnOjtVeqSkFe0JCwAAYNKh7gSgVC1P+BIRt9i+StJySVsk3SFpabsCAwBgYnTTRLVQdwJQtqTZPiPiHEnntCkWAACaQvKHqqHuBKBMqZd6AACgNANc6gEAgMIY2Q4AAAAAfaDrLX+haLlsOy7maw8mlR/0SHIMUwbSDvt2g9OTY9hj5p5J5T/y24uTY3j0uXVJ5Yemp8+AtvP0nZPKTx2YmhxD6vsZ0fp3SpI8kHgOiIYXlMSi2ydQBe34ng4orf62/ZRZyTEcMnRIUvldF+2SHMNTm55KKj80I73utNcOeyeVnz44MzmGAafVXfr5t4NunwCAasov8g4AAIoh+QMAVJTb0iMEAIB+QfIHAKgkK73rDwAA/YRfTQAAAADoA7T8AQAqq58H7QMA0CySPwBAZTHmDwCA4kj+AAAVZWb7BACgCSR/AIBKsmj5AwCgGUz4AgAAAAB9gJY/AEBl0e0TAIDiSP4AANVkyVznDwCAwkj+AAAVZcb8AQDQBJI/AEAlWXT7BACgGfSXAQAAAIA+QMsfAKCyTMsfAACFkfwBACprgDF/AAAU1nfJX+rkAO2YWW7Ag0nlpzj9bUs9W/7ynRYmxzA0Yyip/IzBGckxKPE47DBlh+QQpg1ul1Q+FEnlUz+PovKNkljltPzZvkjSsZLWRcSBdcs/LOlUScOSvhURZ+bLz5J0Sr78IxFxfdeDBipuIHGkUupvrSTtOn23pPKzpu2UHMNIDCeVH2xDHXLaQNqxnDIwNTmGAWZ6blnfJX8AACS6WNIXJF1aW2D7TZIWSzooIl6wvVu+fH9JJ0g6QNKekr5j+xURiTU4AABaQPIHAKgol3Kdv4i42faCUYv/VNL5EfFCvs66fPliSVfkyx+wvVLSYZJ+1K14AQCooc0UAFBZA3Lbby16haQ32L7F9g9svzpfPlfSqrr1VufLAADoOlr+AACVZHdszN+Q7dvqHi+NiKUNykyRtIukwyW9WtKVtn+jE8EBANCqhsnfWAPbbe8i6euSFkh6UNLxEfFE58IEAGBbqZN4jWNDRCxqssxqSVdHREi61faIpCFJayTNr1tvXr4Mkxh1JwC9qki3z4slHTVq2cckfTciFkr6bv4YAIB+9U1Jb5Ik26+QNE3SBknXSjrB9na295G0UNKtZQWJrrlY1J0A9KCGyV9E3Czp8VGLF0u6JL9/iaTj2hsWAACNWHb7bw33al+ubMKW/Wyvtn2KpIsk/Ybtn0q6QtLJkblH0pWS7pX0bUmnMtPn5EfdCUCvanXM3+4RsTa//4ik3cdb0fYSSUskad78eS3uDgCAbZVxkfeIOHGcp949zvrnSTqvcxGhIlqqO83fa/54qwFA05Jn+8zHN4x7lemIWBoRiyJi0a5zdk3dHQAAkmoXeR9o+w3otGbqTnPmDHUxMgCTXau/co/a3kOS8v/XNVgfAIA2c0f+AR1C3QlA6VpN/q6VdHJ+/2RJ/9yecAAAACYl6k4ASlfkUg+XSzpC2XWPVks6R9L5yq5hdIqkX0k6vpNBAgAwlg5d5w9IQt0JQK9qmPxNMLD9yDbHAgBAU+imiV5E3QlAr2p1tk8AAEpHyx8AAMWR/AEAKskq51IPAABUVZeTv1DESMulBwemJkcwnHht3c0jm5JjGPRgUvmdt0uf9nkk8TikvI81s6bumFR+ROkxpGpHl7OBxKnlB532NY7xZxsHAKAnpLbyD0T6ZVymDkxLKj+lDfVYReJvdht6S6TWfVLrPUhDyx8AoJpsun0CANAEkj8AQGW55SsWAQDQf0j+AACVRcsfAADFccoUAAAAAPoALX8AgEqyuM4fAADNIPkDAFSUNUC3TwAACiP5AwBUFi1/AAAUR/IHAKgsJnwBAKA4JnwBAAAAgD5Ayx8AoJKyCV84hwkAQFEkfwCAijLdPgEAaALJHwCgsgaY8AUAgMJI/gAA1WQmfAEAoBkMlgAAAACAPkDLHwCgkrIJX2j5AwCgKJI/AEBl0e0TAIDiupr8DXpQO0zdseXyW0a2JMcwEiNJ5acNTk+OYSCxt+2I0l6DJNnl9/idkhjDcKR/HlLfi3Ycx9RtpL6G9OMYieWBVplLPQAopB0ninqip0EPhIBqo+UPAFBZA7T8AQBQGKdMAQAAAKAP0PIHAKgkJnwBAKA5JH8AgMpiwhcAAIpr2O3T9kW219n+ad2yT9n+me27bF9je3ZHowQAYBvuyD8gFXUnAL2qyJi/iyUdNWrZjZIOjIhXSfqFpLPaHBcAAEBVXSzqTgB6UMPkLyJulvT4qGU3RLw4P/wySfM6EBsAABOy3fYbkIq6E4Be1Y4xf++X9PXxnrS9RNISSZq/1/w27A4AgGzCl9TrXAIloe4EoBRJv5q2Py5pi6TLxlsnIpZGxKKIWDRnzlDK7gAAeIlp+UP1UHcCUKaWW/5sv1fSsZKOjIhoW0QAABTCBC2oFupOAMrWUvJn+yhJZ0p6Y0Q8296QAAAAJhfqTgB6QcPkz/blko6QNGR7taRzlM1QtZ2kG/MuMssi4oMdjBMAgG3QTRO9iLoTgF7VMPmLiBPHWHxhB2IBAKApdPtEL6LuBKBXtWO2TwAAus4i+QMAoBkkfwCA6qLbJwAAhXU1+RuJ0KbhF1ou/9xw+vjoTcPPJ5WfOXVWcgypY1Q2b2n9GNZsNzgjqXy0ocIVSpvobLANH98BDyaWT7/GWOp1ylJfw/DwlsYrAXiR7YuUzdi4LiIOHPXcGZI+LWlORGxw9gf/c5KOkfSspPdGxPJuxwwAgJR4nT8AAMrjjvwr4GJJR20TjT1f0tskPVS3+GhJC/PbEklfSn7ZAAC0iOQPAFBZZVzkPSJulvT4GE99VtlU/vXdGhZLujQyyyTNtr1HO147AADNYswfAKCyemXCF9uLJa2JiDtHJZBzJa2qe7w6X7a2i+EBACCJ5A8AUGEdSv6GbN9W93hpRCwdNwZ7pqSzlXX5BACgZ5H8AQCwtQ0RsaiJ9feVtI+kWqvfPEnLbR8maY2k+XXrzsuXAQDQdSR/AIBKstJnT26HiLhb0m61x7YflLQon+3zWkkfsn2FpNdI2hgRdPkEAJSCCV8AABVVzmyfti+X9CNJ+9lebfuUCVa/TtL9klZK+oqkP2vHKwcAoBW0/AEAKquMCV8i4sQGzy+oux+STu10TAAAFEHyBwCoJvdGt08AAKqCbp8AAAAA0Ado+QMAVFavXOcPAIAqIPkDAFRSr8z2CQBAVZD8AQAqqtjsnAAAIMOYPwAAAADoA7T8AQAqi5Y/AACKI/kDAFQWY/4AACiuq8mfZU0ZmNpy+akxLTmGgcSzxNsNTE+OYcpA+Tl3dt3h1g04vcdwagweGEyOIbXVoB3HwYm9r9sRA1BVtPwBAFBc+VkIAAAtsEj+AABoBk0GAAAAANAHaPkDAFSUGfMHAEATGrb82b7I9jrbPx3juTNsh+2hzoQHAMBE3IEbkIa6E4BeVaTb58WSjhq90PZ8SW+T9FCbYwIAoDFns322+wa0wcWi7gSgBzVM/iLiZkmPj/HUZyWdKSltykYAAFrkDvwDUlF3AtCrWprwxfZiSWsi4s42xwMAADDpUHcC0AuanvDF9kxJZyvrtlBk/SWSlkjS/L3mN7s7AADGRUsdqoC6E4Be0UrL376S9pF0p+0HJc2TtNz2y8ZaOSKWRsSiiFg0NMTYZgBAe1jtH+/HmD90SMt1pzlzqDsBaJ+mW/4i4m5Ju9Ue53/EFkXEhjbGBQBAQ7T8oQqoOwHoFUUu9XC5pB9J2s/2atundD4sAAAaY8IX9CLqTgB6VcOWv4g4scHzC9oWDQAAQMVRdwLQq5ru9gkAQK9gjB4AAMWR/AEAKotumgAAFEfyBwCopNpsnwAAoJiuJn93LL9jw/ZTZ/1qglWGJJU98xUx9EYMZe+fGIrHsHe3AgGAfrP89js2zJiyPXWn3o+h7P0TQ7ViKK3u1NXkLyLmTPS87dsiYlG34iGG3o2h7P0TQ2/FAIyHbp+Y7Kg7VSOGsvdPDMRQFN0+AQAVRvIHAEBRJH8AgMoi9QMAoLheS/6Wlh2AiKGm7BjK3r9EDDW9EAMwJiZ8AXribzQxlL9/iRhqiGECjoiyYwAAoGkHHfqquP4/vtX27e4xc6/be3WsBgAAKXqt5Q8AgCbQ8gcAQFEkfwCAyiL1AwCguIGyA6ixfZTtn9teaftjJex/vu2bbN9r+x7bp3U7hjyOQdt32P7XkvY/2/ZVtn9me4Xt15YQw0fz9+Cnti+3Pb0L+7zI9jrbP61btovtG23fl/+/cwkxfCp/L+6yfY3t2d2Ooe65M2yH7aFOxgAU5w7dgN5HvWmrWKg7UXei7lRQTyR/tgcl/b2koyXtL+lE2/t3OYwtks6IiP0lHS7p1BJikKTTJK0oYb81n5P07Yj4TUkHdTsW23MlfUTSoog4UNKgpBO6sOuLJR01atnHJH03IhZK+m7+uNsx3CjpwIh4laRfSDqrhBhke76kt0l6qMP7Bwqzswlf2n0Deh31pm1Qd6LuVI+60wR6IvmTdJiklRFxf0RsknSFpMXdDCAi1kbE8vz+08q+uHO7GYPteZJ+T9JXu7nfuv3vJOl3JV0oSRGxKSKeLCGUKZJm2J4iaaakhzu9w4i4WdLjoxYvlnRJfv8SScd1O4aIuCEituQPl0ma1+0Ycp+VdKYkZogCgPJRb8pRd3oRdaeXllF3mkCvJH9zJa2qe7xaJfwBqbG9QNIhkm7p8q4vUPYhGenyfmv2kbRe0tfy7hNftb19NwOIiDWSPq3sLMlaSRsj4oZuxlBn94hYm99/RNLuJcVR835J/9btndpeLGlNRNzZ7X0DAMZEveklF4i6E3Wn8VF3GqVXkr+eYXsHSd+QdHpEPNXF/R4raV1E3N6tfY5hiqRDJX0pIg6R9Gt1vrl+K3nf8MXK/pjuKWl72+/uZgxjieyaKKWdubH9cWVdbC7r8n5nSjpb0l92c79AUe7APwDFlVVvyvdN3UnUncZD3WlsvZL8rZE0v+7xvHxZV9mequwP2GURcXWXd/96Se+0/aCy7htvtv2PXY5htaTVEVE7c3eVsj9o3fQWSQ9ExPqI2Czpakmv63IMNY/a3kOS8v/XlRGE7fdKOlbSu6L7F+bcV9mPyZ35Z3OepOW2X9blOIAxkfyhT1FvylB3ylB3GoW60/h6Jfn7saSFtvexPU3ZINVruxmAs1H+F0paERGf6ea+JSkizoqIeRGxQNnr/15EdPWsTUQ8ImmV7f3yRUdKurebMSjrsnC47Zn5e3KkyhvEfa2kk/P7J0v6524HYPsoZd1Z3hkRz3Z7/xFxd0TsFhEL8s/makmH5p8VAEA5+r7eJFF3qkPdqQ51p4n1RPKXD8r8kKTrlX1Yr4yIe7ocxuslnaTsrNFP8tsxXY6hF3xY0mW275J0sKRPdnPn+ZmzqyQtl3S3ss/o0k7v1/blkn4kaT/bq22fIul8SW+1fZ+ys2rnlxDDFyTNknRj/pn8cgkxAAB6CPWmnkPdibpTZepO7n5LKAAA6Q7+7YPiu//Z/jkNhqa/7PaIWDTe87YvUtadaF0+rbpsf0rSOyRtkvRLSe+rzfhn+yxJp0galvSRiLi+7UEDAFBAT7T8AQBQIRer4HWl8uuenSDpgLzMF/NrtAEA0HUkfwCAiurEdC+NJ3xp8rpSiyVdEREvRMQDklYqu0YbAABdR/IHAEB71V9XqqeuxwYA6G9Tyg4AAIDWdeTSDEO2b6t7vDQiCk2eUNZ1pQAAKILkDwBQSVaHUj9pw0QTvoyn7rpSR9ZdV6onrscGAIBEt08AQIXZbvutxTjGu67UtZJOsL2d7X0kLZR0a/ILBwCgBbT8AQAqrENtfxPtMbum0xHKuoeulnSOstk9t1N2XSlJWhYRH4yIe2xfqeyiz1sknRoRw10PGgAAkfwBANCUiDhxjMUXTrD+eZLO61xEAAAUQ/IHAKis7rf7AQBQXSR/AIAKI/0DAKAokj8AQEW1PkELAAD9iNk+AQAAAKAPkPwBAAAAQB+g2ycAoJKyi7zT7RMAgKJI/gAAFUbyBwBAUSR/AIDKIvUDAKA4kj8AQGUx2ycAAMUx4QsAAAAA9AFa/gAAFWXR8RMAgOJI/gAAlUXqBwBAcSR/AIAKI/0DAKAoxvwBAAAAQB+g5Q8AUE1mtk8AAJpByx8AAAAA9AFa/gAAlZTN9UnLHwAARTkiyo4BAICm2f62pKEObHpDRBzVge0CAFAqkj8AAAAA6AOM+QMAAACAPkDyBwAAAAB9gOQPAAAAAPoAyR8AAAAA9AGSPwAAAADoA/8/KL3g4i5MKzQAAAAASUVORK5CYII=\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteG1 = trim(imagen[:,:,1], 210, 237, 15, 15)\n", + "poptG1, pcovG1 = curve_fit(gauss2d, xdata1, recorteG1.ravel(), p0=[1,1,1,1,1])\n", + "estrellaG1=gauss2d(xdata1, poptG1[0], poptG1[1],poptG1[2], poptG1[3], poptG1[4])\n", + "FWHMG1=FWHMG.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptG1[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 1 fotografÃa (Banda Verde)\")\n", + "plt.imshow(recorteG1, plt.get_cmap('Greens'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 1 a partir de la gaussiana (Banda Verde)\")\n", + "plt.imshow(estrellaG1.reshape(15, 15), plt.get_cmap('Greens'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 2 (Verde)" + ] + }, + { + "cell_type": "code", + "execution_count": 413, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteG2 = trim(imagen[:,:,1], 645, 535, 35, 35)\n", + "poptG2, pcovG2 = curve_fit(gauss2d, xdata2, recorteG2.ravel(), p0=[1,0,1,1,1])\n", + "estrellaG2=gauss2d(xdata2, poptG2[0], poptG2[1],poptG2[2], poptG2[3], poptG2[4])\n", + "FWHMG2=FWHMG.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptG2[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 2 fotografÃa (Banda Verde)\")\n", + "plt.imshow(recorteG2, plt.get_cmap('Greens'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 2 a partir de la gaussiana (Banda Verde)\")\n", + "plt.imshow(estrellaG2.reshape(35, 35), plt.get_cmap('Greens'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 3 (Verde)" + ] + }, + { + "cell_type": "code", + "execution_count": 414, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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/0E76ZWALTUvpfWhaXxkyvqU++5G+N1V1J82lU8+l6fL59qq6m+bE//eAhw4cQ/epZgCbHxRfLDbuWc/70rxj8tCqetrAMj9O0y10Uftk8pfk3+SHg3B8k2bnzravvwb8yBKr+BPgtWkv4ExyZIYb8vhQmm4ftyc5lkVua5Dkx9ozOgcl2S/Js2kSiY8NsR1o+p6/IMlJ7R+I3wMur6ovt/Pnv8/Flv9b4CeSPKNt/TqD5izLWN7rAmW/B3wrzUXrr1pi+ffQXOuwV0kOoenbPTe66KE03QVuA9Yn+R2a/vLD+ERb9jfaz+WXaFrrlhs7NMnfz9P07T9vYPqox9lFbVwb0wwc84OzdVW1neaakv+R5N5pBgh4UJLB/fZzNF1ZpH2HA75oldtH6ySH0lx28Z0kPwYMMwz/f0nTe+ahNNevzV2rt5x1DbPfFvO3NLc/+qW23vMb7Fnv+RPgrDZW0gyo9m+GWO/+wAE09Y9dSZ5Kc4nGQi4CzkxybJpBRX5rhHVd3b6Hk9KMafDquRlJ9k/yK0nuU80o69+mPeaSPD3NIEShOTG+mx8ej4OW87kMlh2ljrhUPe8Imq6Ug/W8u2h6sB1M2yI4pKU+++XUb88D/i1Na+t5AFU1S3P7hTekvf1C+zk/ZcG1NMfDWWkGF9xIc73vnE8Cd6QZIOagtvXzYWmuh5wzVD2v78nfX2fPe+q8q53+KODyJN+hGczjzKr6Yjvv1cB5bZPpMxdY75vach9IcgfNQCKPGSKe19BcsHs7zcF18SLLpo3lVpov9pk0t0K4aojtUFUfBP4LzZmQ7TRn504bWOTVDLzPxZav5qLUf0PTB//rNNfAXUHzxRrHe53vjcBBNGdFLqNpBl/M+cDT0o6Q1Dpm7nOnaRY/HPiVdt7723X+Uzvv+wzZZaQ9W/NLNP3Nv0HzZR58b6PGTptg/wNwL5rjas6ox9mf0ry3q2kubp6/z59L82NxHU0F4x0014bMeRbtvRKlfcbMCjyk5VlLdZL/RNP6cgfNb9NCg64M+hhNd8MPAX9YVR/osK5Xs/R+W9BAved1NPWeE2iuyZ+b/y7gvwNvT9P177M010Eutd47aJKJi2h+h3+ZPX/35/tTmhO31wCfokmCdtFct7XouqoZTO93gQ8CXwD2GPmTphXqy238v8YP60gntGW+Q3PC+4+r6iN7iW05n8ucUeuIW2nuUTd49u1xA/W862mOy7lk6Hya+t3NNHWewQH/FrXUZ7+M2KG5BOh2muvz/nFg+m/RHPOXtZ/DB2l6jy3kNTTv60s0x8X/Hoh7N80AOye183fQ3AngPgDtCYCnMcQtJrLnpU3SD0YU2gb8ygJ/ECYuye8Bt1bVG6cdSx8l+QXgOVU18o+ktFplw4HFluPHv+JzPn9lVW1eekFJS0lyPE1ldb8a4f62a1HbuvcnVXXckgvvY5L8BXBRVb172rH0UZKXAJuq6uVLLeuNLwVA2wx9OU2Xxv9McxZw6DMpK62qXjntGPqsqv6aZohgad9hN01JPdb2aHoiTSvPUTSXkrxr0UL7qKr65WnH0GdV9T+HXdYOLprzOJoLbnfQXFD7jGruUydJq5cDvkjqr9B09fsmTbfP69nzPnDS2NnyJwCq6tUscfNXSVp1bPmTVrX2une/qHvRjhT5qCUXlMbI5E+S1F/2X5EkaWj+bEqSJEnSGjDRlr8jNhxemx6waekFFzKGTgPpmO/Wsu4zes+1dJEx7Iiu72Ic/TdWxziz3aKYrb3dGmfECDqOuLtuZl238ulW/itfvpEdO3bYpUeTF+z2qX3ehg0b6rjjH7D0gpJ6Y5p1p4kmf5sesIkP/P3y7zHdtZIKsN/M/p3K76ydnWOgc2W/+8e2u3Z3Kj8zhkbjron0OBLx6pi8fX939zFx7t692O0Ul3bo/vfpVn6/buUf/5if7lRe6sTcT/u4445/AH9/+fxbuEnqs2nWnbzmT5LUXzNmf5IkDctr/iRJGlKSTUk+kuS6JNcmOXPe/JclqSQb2tdJ8uYkNyS5JsnJ04lckiRb/iRJfTb5a/52AS+rqquSHApcmeTSqrouySbgycCNA8s/FTihfTwGeGv7vyRJE9ep5S/JqUk+357RfMW4gpIkaUkrcYP3JXLJqtpeVVe1z++guSnzse3sNwAvZ8+RpLYA51fjMuCwJEd3eNfqOetOkqZp2clfknXAH9Gc1TwReFaSE8cVmCRJiwvJ+B/AhiRXDDxO3+vWk+OBRwKXJ9kC3FxVV89b7FjgpoHX2/hhsqg1xrqTpGnr0u3z0cANVfVFgCRvpznDed04ApMkaSlZgW6fBTuqavMS2z0EeCfwUpquoK+k6fIpLca6k6Sp6tLtc6izmUlOnzt7+vUdX++wOUmSpi/JfjSJ3wVVdTHwIOCBwNVJvgxsBK5Kcn/gZmDwBrcb22lam0auO912246JBSdp37fio31W1daq2lxVm4/YcMRKb06StIYk438svr0EOBu4vqpeD1BVn6mq+1XV8VV1PE2F/uSqugW4BHhuO+rnY4Hbq2r7Su4T9d9g3enIIzdMOxxJ+5Au3T49mylJmpoAMyvQ7XP34rMfDzwH+EyST7fTXllV71lg+fcATwNuAO4EXjCWINVX1p0kTVWX5O8fgROSPJDmD9dpwC+PJSpJkpaSlbnmbzFV9XcsMSZo2/o397yAM1Y4LPWHdSdJU7Xs5K+qdiX5deD9wDrgnKq6dmyRSZK0hEknf1IX1p0kTVunm7y33VwW6uoiSZKkAdadJE1Tp+RPkqTpiS1/kiSNYKLJ30zWca/9Dl12+bt2f79zDDtrZ+d1dDWTdZ3KN5eQdJPFL1lZ0rqZ7ofOTMfBZmeZ7RzD7tldncqv6/hZQvf3sWu22zHd9Xs1W90/B2m5zP0kSRqeLX+SpF4KXvMnSdIoTP4kSf00hdE+JUnqsxW/ybskSZIkafps+ZMk9VbX65clSVpLTP4kSb1lt09JkoZn8idJ6i1zP0mShuc1f5IkSZK0BtjyJ0nqpRBmbPqTJGloJn+SpN7ymj9JkoZn8idJ6ifv8ydJ0khM/iRJvWXuJ0nS8BzwRZIkSZLWAFv+JEm9FOz2KUnSKEz+JEm9ZfInSdLwTP4kST0Vkz9JkkZg8idJ6idH+5QkaSQTTf6KWXbO3r3s8qH7j3zVbLfyVOcYdtauTuXHUdmZybpO5XfPdnsPAJVu4w3trt3dY+h4PIzjmNx/Zv9O5bt+lus6lh/HPpAkSdLKs+VPktRbNvxJkjQ8kz9JUi852qckSaMx+ZMk9ZbJnyRJwzP5kyT11ozJnyRJQ1v2iBtJNiX5SJLrklyb5MxxBiZJkrQvse4kadq6tPztAl5WVVclORS4MsmlVXXdmGKTJGlhccAX9Y51J0lTtezkr6q2A9vb53ckuR44FvAPmCRpxcWbvKtnrDtJmraxXPOX5HjgkcDl41ifJEnD8D6T6ivrTpKmodtdtoEkhwDvBF5aVd/ey/zTk1yR5IodO77edXOSJE3NQtdsJfmDJJ9Lck2SdyU5bKDMWUluSPL5JE+ZWvBaNUapO912247JByhpn9Up+UuyH80frwuq6uK9LVNVW6tqc1Vt3rDhiC6bkyRpD0nG/ljC3DVbJwKPBc5IciJwKfCwqno48E/AWW18JwKnAQ8FTgX+OMm6Fdod6oFR605HHrlhsgFK2qd1Ge0zwNnA9VX1+vGFJEnScCad/FXV9qq6qn1+B3A9cGxVfaCqdrWLXQZsbJ9vAd5eVXdV1ZeAG4BHr8jO0Kpn3UnStHVp+Xs88BzgSUk+3T6eNqa4JElaUjL+x/DbXvCarRcC722fHwvcNDBvWztNa5N1J0lT1WW0z78Dr7SXJE1Hk6ytyM/QhiRXDLzeWlVb99z23q/ZSvLbNF1DL1iJwNRv1p0kTdtYRvuUJGkfsqOqNi80c6FrtpI8H3g6cEpVVTv5ZmDTQPGN7TRJkiau82ifkiRNx/iv91uqJXGha7aSnAq8HPjFqrpzoMglwGlJDkjyQOAE4JNj3xWSJA1hoi1/RbF7dtfSCy5gZgwDpO2u3Z3KF7X0QktYn267fRz7YSbd8v67dn+/cwwHrDuwU/lxfBZdrZvp/hXav2P5rseTPZDUZ1O4yfvcNVufSfLpdtorgTcDBwCXtjFdVlW/VlXXJrmI5ibeu4Azqjr+EElr0A8b05dZfgx1hq73FZ3C3yvpHuz2KUnqrUnXpRa5Zus9i5R5LfDaFQtKkqQhmfxJknrLM+mSJA3Pa/4kSZIkaQ2w5U+S1EsreKsHSZL2SSZ/kqTeMvmTJGl4Jn+SpN4y95MkaXgmf5Kknlr6vnySJOmHHPBFkiRJktYAW/4kSb1ly58kScMz+ZMk9ZKjfUqSNBqTP0lSb5n7SZI0PJM/SVJv2fInSdLwHPBFkiRJktYAW/4kSf1ly58kSUMz+ZMk9ZT3+ZMkaRQmf5KkfooNf5IkjWKiyd8MMxyw7sBll985u7NzDLO1u1P59TP7dY7hO7u+3an8tu/c1DmG+x10VKfyhx1weOcYuhwLAJm9u3MMXY+HmarOMVS6rWOW2U7ld3bcj0X3fSBJ2nfNVrffKYA7d32nU/lv3vX1zjHce//7dCp/yPp7d45h3YztNurGI0iS1EvB0T4lSRqFyZ8kqbdM/iRJGp7JnySpt0z+JEkansmfJKm3zP0kSRpe55u8J1mX5FNJ/mYcAUmSJO3LrDtJmpZxtPydCVwPdB/CSJKkYcX7/Km3rDtJmopOLX9JNgL/EnjbeMKRJGk4c6N9jvshrSTrTpKmqWvL3xuBlwOHdg9FkqTRmKyph96IdSdJU7Lslr8kTwduraorl1ju9CRXJLlix47uN9iUJGmOLX/qk+XUnW67bceEopO0FnTp9vl44BeTfBl4O/CkJH8+f6Gq2lpVm6tq84YNR3TYnCRJUq+NXHc68sgNk45R0j5s2clfVZ1VVRur6njgNODDVfXssUUmSdJi0tzqYdwPaaVYd5I0bd7nT5LUW3bTlCRpeGNJ/qrqo8BHx7EuSZKGEbxGT/1l3UnSNNjyJ0nqLZM/SZKG1+k+f5IkrSVJNiX5SJLrklyb5Mx2+uFJLk3yhfb/+7bTk+TNSW5Ick2Sk6f7DiRJa9lEW/521yzf3fWdZZdfn+7hHrj+4E7lq6pzDOddf2Gn8q+54B2dY3jWqT/dqfwbn/A7nWPYNburY/mdnWMoun2e4zgm181MtwF+Jp4DUn9NoeFvF/CyqroqyaHAlUkuBZ4PfKiqXpfkFcArgN8Cngqc0D4eA7y1/V9aM+6evavzOj5w0/s6lf+dv/qLzjE852d/qlP5//DwX+0cwyG5d6fy9paQtT5JUj9l8vf5q6rtVXVV+/wO4HrgWGALcF672HnAM9rnW4Dzq3EZcFiSo1dgb0iStCSv+ZMk9dfKnMXekOSKgddbq2rrPTed44FHApcDR1XV9nbWLcBR7fNjgZsGim1rp21HkqQJM/mTJGlPO6pq82ILJDkEeCfw0qr69mCLYVVVku7XCEiSNGYmf5Kk3prG9StJ9qNJ/C6oqovbyV9LcnRVbW+7dd7aTr8Z2DRQfGM7TZKkifOaP0lSLwWYyfgfi26zyTbPBq6vqtcPzLoEeF77/HnAXw1Mf2476udjgdsHuodKkjRRtvxJknpqKjd5fzzwHOAzST7dTnsl8DrgoiQvAr4CPLOd9x7gacANwJ3ACyYarSRJA0z+JEn9FJiZcPJXVX/XbHmvTtnL8gWcsaJBSZI0JLt9SpIkSdIaYMufJKmXgjcsliRpFCZ/kqTesvuKJEnDM/mTJPXWpK/5kySpz0z+JEm9ZLdPSZJGY48ZSZIkSVoDbPmTJPVU7PYpSdIITP4kSf0Uu31KkjQKkz9JUi8Fr12QJGkUE03+ilm+v/vOZZc/eP0hnWNYT7ezxDMz6zrHcPMd3+hUfvbabuUBvnDSbd1iqNnOMdy1+3udyt89e1fnGGbS7fNct6778bCuYwzT3n46fqekLuz2Ka1+s7W78zqu3XFDp/L//P7rOsfwsePv36n86Q/b2TkGqStPmkqSJEnSGmC3T0lSb3nNnyRJwzP5kyT1UrDbpyRJozD5kyT1lqmfJEnD63TNX5LDkrwjyeeSXJ/kceMKTJIkaV9j3UnSNHVt+XsT8L6q+tdJ9gcOHkNMkiQNwZu8q5esO0mammUnf0nuA/ws8HyAqrobuHs8YUmStLjEa/7UL9adJE1bl26fDwRuA/4syaeSvC3JvcYUlyRJS0oy9oe0gqw7SZqqLsnfeuBk4K1V9Ujgu8Ar5i+U5PQkVyS54hs7ut+cXJKkOTPJ2B/SChq57nTbbTsmHaOkfViX5G8bsK2qLm9fv4PmD9oeqmprVW2uqs2Hbzi8w+YkSZJ6beS605FHbphogJL2bctO/qrqFuCmJA9pJ50CXDeWqCRJWkJW6CGtFOtOkqat62ifLwEuaEer+iLwgu4hSZI0HLtpqoesO0mamk7JX1V9Gtg8nlAkSRqF1+ipf6w7SZqmri1/kiRNRYKjc0qSNIIuA75IkiRJknpioi1/67OeIw6437LL37X7+51juGPntzqVP2z/IzrH8MKH/VKn8l8/887OMTztR3+yU/miOsewbqbb4TdTuzrHkI7DO3QtDzBbsx3L7+5Ufne6lZ8dw7EgLZfdPqXVb/+ZAzqv45d/7F91Kr/xjUd1juGkDT/RqfzB6w/pHIO9HdSV3T4lSb1lNUiSpOGZ/EmSeinY8idJ0ihM/iRJvWXyJ0nS8BzwRZKkESQ5J8mtST47MO2kJJcl+XSSK5I8up2eJG9OckOSa5KcPL3IJUlrncmfJKmnQjL+xxDOBU6dN+33gddU1UnA77SvAZ4KnNA+TgfeOo53LknScpj8SZJ6KTQ/YuN+LKWqPg58Y/5k4N7t8/sAX22fbwHOr8ZlwGFJjh71vUqSNA5e8ydJ6qfVdZP3lwLvT/KHNDnkT7XTjwVuGlhuWztt+0SjkyQJW/4kSZpvQ3vd3tzj9CHK/HvgN6tqE/CbwNkrG6IkSaOz5U+S1FsrNNrnjqraPGKZ5wFnts//Enhb+/xmYNPAchvbaZIkTZwtf5KkXpq7z9+4H8v0VeDn2udPAr7QPr8EeG476udjgduryi6fkqSpsOVPktRb07jmL8mFwBNouoduA14FvBh4U5L1wPdpRvYEeA/wNOAG4E7gBRMPWJKklsmfJKmnwgyTT/6q6lkLzPrJvSxbwBkrG5EkScOx26ckSZIkrQG2/EmSemsV3epBkqRVz+RPktRLyYqN9ilJ0j7J5E+S1FuZwjV/kiT11USTv1lm+d7uO5ddfvfsrs4xzGRdp/Lf3vmtzjEce69NSy+0iDc+8RWdYzhg3UGdyh+07uDOMdx8542dys+M4ZLVe+13SKfy62a7HU/jkHTbD10rz1a9NU12+5RWv/Uz+3Vex3GHPKhT+V8+4bjOMazrWIdcF9tcNH0O+CJJkiRJa4CnICRJvRQ63ZRdkqQ1x+RPktRbsQOLJElDM/mTJPWWLX+SJA2v0ynTJL+Z5Nokn01yYZIDxxWYJElLSTL2h7SSrDtJmqZlJ39JjgV+A9hcVQ8D1gGnjSswSZKkfYl1J0nT1rXb53rgoCQ7gYOBr3YPSZKkpaX9J/WMdSdJU7Pslr+quhn4Q+BGYDtwe1V9YFyBSZK0qDTX/I37Ia0U606Spq1Lt8/7AluABwLHAPdK8uy9LHd6kiuSXPH1276+/EglSZrHa/7UJ8upO912245JhylpH9ZlwJefB75UVbdV1U7gYuCn5i9UVVuranNVbT7iyCM6bE6SpB8KMLMC/6QVNHLd6cgjN0w8SEn7ri6/cjcCj01ycJpTpacA148nLEmSpH2OdSdJU7XsAV+q6vIk7wCuAnYBnwK2jiswSZIWZzdN9Yt1J0nT1mm0z6p6FfCqMcUiSdJITP7UN9adJE1T11s9SJI0NTPe6kGSpKF5ZbskSZIkrQG9avlbP7Nf53V0viHwGLoYVc12XkdXSbe8f+fszs4x3Hf/bqO/ztJ9P+43s3+38ul+TO6u3Z3K2+1Na1Xw+JfWivUz3aqs6/tV5ZVWjN8ESVI/tTd5lyRJwzH5kyT1VLr35pAkaQ0x+ZMk9VKAmY5d2CVJWkv81ZQkSZKkNcCWP0lSbzngiyRJwzP5kyT1ltf8SZI0PJM/SVJPxdE+JUkagcmfJKmXgi1/kiSNwgFfJEmSJGkNMPmTJPXWTDL2x1KSnJPk1iSfnTf9JUk+l+TaJL8/MP2sJDck+XySp6zAbpAkaSh2+5Qk9VMg07nP37nAW4DzfxBK8kRgC/CIqroryf3a6ScCpwEPBY4BPpjkwVW1e+JRS5LWPFv+JEk9lRX5t5Sq+jjwjXmT/z3wuqq6q13m1nb6FuDtVXVXVX0JuAF49Pj2gSRJwzP5kyT1UphOt88FPBj4mSSXJ/lYkke1048FbhpYbls7TZKkibPbpyRJe9qQ5IqB11urausSZdYDhwOPBR4FXJTkR1YqQEmSlsPkT5LUW1mZ+/ztqKrNI5bZBlxcVQV8MskssAG4Gdg0sNzGdpokSRNnt09JUm/NkLE/lundwBMBkjwY2B/YAVwCnJbkgCQPBE4APtn9nUuSNLoJt/yFdVn+JmfGMKrb7o4DrO2e3dU5hq5nqveb2b9zDF3tmt3ZeR0HrjuoU/munyXAuqzrVH6mY3mAojqvo4vuoyV6k21NR1ixlr/Ft5tcCDyBpnvoNuBVwDnAOe3tH+4Gnte2Al6b5CLgOmAXcIYjfUqSpsVun5IkjaCqnrXArGcvsPxrgdeuXESSJA3H5E+S1FOZ1n3+JEnqJZM/SVJvdbhGT5KkNcfkT5LUS8l0rvmTJKmvluwvk+ScJLe2F7HPTTs8yaVJvtD+f9+VDVOSpHvKCvyTurLuJGm1GuZiiXOBU+dNewXwoao6AfhQ+1qSJEnWnSStUksmf1X1ceAb8yZvAc5rn58HPGO8YUmStJSQjP8hdWXdSdJqtdxr/o6qqu3t81uAoxZaMMnpwOkAGzdtXObmJEm6Jwd8UY8sq+606QGbJhCapLWi8xjZ7U1sF7xLdVVtrarNVbX5iCOP6Lo5SZKAuZu8z4z9Ia20UepORx65YYKRSdrXLfdX7mtJjgZo/791fCFJkjSMlRjuxZZErRjrTpKmbrnJ3yXA89rnzwP+ajzhSJIk7ZOsO0mauiWv+UtyIfAEYEOSbcCrgNcBFyV5EfAV4JkrGaQkSXvjAC1ajaw7SVqtlkz+qupZC8w6ZcyxSJI0ErtpajWy7iRptVruaJ+SJE2dLX+SJA3P5E+S1EvBWz1IkjSKXiV/szXbeR07Z+/uVP72u7/ZOYb9Z/bvVP7e+9+3cwzrM/2Pfnft7lR+V+3sHMMs3Y6p9QuP1D18DB2P63VZN9XydruTJEnqh+lnAJIkLUdit09JkkZg8idJ6q0s+45FkiStPSZ/kqTesuVPkqThecpUkiRJktYAW/4kSb0UHHBIkqRRmPxJknoqzNjtU5KkoZn8SZJ6y5Y/SZKGZ/InSeotB3yRJGl4DvgiSZIkSWuALX+SpF5qBnzxHKYkScMy+ZMk9VTs9ilJ0ghM/iRJvTXjgC+SJA3N5E+S1E9xwBdJkkbhxRKSJEmStAbY8idJ6qVmwBdb/iRJGpYtf5Kk3koy9scQ2zwnya1JPruXeS9LUkk2tK+T5M1JbkhyTZKTV2A3SJI0lIm2/FUVO2fvXnb5mXTPVXfN7uxUfvfs7s4xVKrzOrrqerZ8HGfbZ6vbvpyt2c4xzHQ8/7GbMRwPHd9H12ueZqrr8Tj941lrVaZ1q4dzgbcA5+8RTbIJeDJw48DkpwIntI/HAG9t/5ckaeJs+ZMk9dZMMvbHUqrq48A39jLrDcDL2fOMyBbg/GpcBhyW5OhxvHdJkkZl8idJ0p42JLli4HH6UgWSbAFurqqr5806Frhp4PW2dpokSRPngC+SpF5awQFfdlTV5qHjSA4GXknT5VOSpFXL5E+S1Fur5D5/DwIeCFzdxrMRuCrJo4GbgU0Dy25sp0mSNHFLdvvc26hmSf4gyefakcveleSwFY1SkqR7yIr8G1VVfaaq7ldVx1fV8TRdO0+uqluAS4DntqN+Pha4vaq2j3U3aNWx7iRptRrmmr9zgVPnTbsUeFhVPRz4J+CsMcclSdKqlORC4BPAQ5JsS/KiRRZ/D/BF4AbgT4H/MIEQNX3nYt1J0iq0ZLfPqvp4kuPnTfvAwMvLgH895rgkSVrSNLp9VtWzlph//MDzAs5Y6Zi0ulh3krRajeOavxcC/2ehme0oaacDbNzkAGeSpPEI3e/VKU3J0HWnTQ/YtNBikjSyTr+aSX4b2AVcsNAyVbW1qjZX1ebDNxzRZXOSJP1Qmpa/cT+klTRq3enIIzdMLjhJ+7xlt/wleT7wdOCUtluLJEkTtLwBWqRpse4kadqWlfwlORV4OfBzVXXneEOSJEnat1h3krQaLJn8taOaPQHYkGQb8CqaEaoOAC5tu8hcVlW/toJxSpJ0D3bT1Gpk3UnSajXMaJ97G9Xs7BWIRZKkkdjtU6uRdSdJq9U4RvuUJGnigsmfJEmjMPmTJPWX3T4lSRrahJO/YnftWnbpsF/nCPafOaBT+cMP7D7k8n7p9j66lge6V5jGUOFan46HX3WPoes9wsZxvdFuug341nXAuFl2d9t+p9KSJEmaFFv+JEk95a0eJEkahcmfJKm3HO1TkqThmfxJknrLlj9JkoZn8idJ6i2TP0mShtdttAtJkiRJUi/Y8idJ6qXgNX+SJI3C5E+S1FOO9ilJ0ihM/iRJvWXyJ0nS8Ez+JEn9FLt9SpI0Cgd8kSRJkqQ1wJY/SVJv2e1TkqThmfxJknrJ0T4lSRqNyZ8kqacc7VOSpFF4zZ8kSZIkrQG2/EmSesuWP0mShmfyJ0nqLa/5kyRpeBNP/mayrkPZ7r1U16XbW17XIf5VpapT8f2yX/cYOlba1tH9s5jp2vN5DBXP2ZrtvI5O26fr9rsdS1IXtvxJkjQ8W/4kSb0UTP4kSRqFA75IkiRJ0hpgy58kqafiNX+SJI1gyZa/JOckuTXJZ/cy72VJKsmGlQlPkqTFZAUeS2xxL7+LSf4gyeeSXJPkXUkOG5h3VpIbknw+yVO6v2etdtadJK1Ww3T7PBc4df7EJJuAJwM3jjkmSZKWlma0z3E/hnAu9/xdvBR4WFU9HPgn4CyAJCcCpwEPbcv8cbKvjBymRZyLdSdJq9CSyV9VfRz4xl5mvQF4OQ71J0makqzAv6Xs7Xexqj5QVbval5cBG9vnW4C3V9VdVfUl4Abg0ePbA1qNrDtJWq2WNeBLki3AzVV19ZjjkSSp714IvLd9fixw08C8be00rTHWnSStBiMP+JLkYOCVNN0Whln+dOB0gGM3+XsnSRqfFbrVw4YkVwy83lpVW4eKJ/ltYBdwwUoEpn7qUnfa9IBNKxiZpLVmOaN9Pgh4IHB1e23ERuCqJI+uqlvmL9z+YG4FeMTJD7ebgyRpLLJyo33uqKrNI8eTPB94OnBKVc393t0MDNbeN7bTtLYsu+70k5tPtu4kaWxGTv6q6jPA/eZeJ/kysLmqdowxLkmSlrRabvKe5FSaa7l+rqruHJh1CfAXSV4PHAOcAHxyCiFqiqw7SVothrnVw4XAJ4CHJNmW5EUrH5YkSUubxoAvC/wuvgU4FLg0yaeT/AlAVV0LXARcB7wPOKOqdq/U/tDqYN1J0mq1ZMtfVT1rifnHjy0aSZJWuQV+F89eZPnXAq9duYi02lh3krRaLeeaP0mSVoUVuuZPkqR9ksmfJKm3Vss1f5Ik9YHJnySpl1ZwtE9JkvZJE03+rvnUZ3YcffCmryyyyAZg2iNfGcPqiGHa2zeG4WM4blKBSNJac9WVn9px0Pp7WXda/TFMe/vG0K8YplZ3mmjyV1VHLjY/yRXLubfSOBnD6ohh2ts3htUVg7QQu31qX2fdqR8xTHv7xmAMw7LbpySpx0z+JEkalsmfJKm3TP0kSRreakv+tk47AIxhzrRjmPb2wRjmrIYYpL1ywBdpVfyNNobpbx+MYY4xLCJVNe0YJEka2SNOfni9/+//duzrPfrgB1y5Wq/VkCSpi9XW8idJ0ghs+ZMkaVgmf5Kk3jL1kyRpeDPTDmBOklOTfD7JDUleMYXtb0rykSTXJbk2yZmTjqGNY12STyX5mylt/7Ak70jyuSTXJ3ncFGL4zfYz+GySC5McOIFtnpPk1iSfHZh2eJJLk3yh/f++U4jhD9rP4pok70py2KRjGJj3siSVZMNKxiANLyv0kFY/6017xGLdybqTdachrYrkL8k64I+ApwInAs9KcuKEw9gFvKyqTgQeC5wxhRgAzgSun8J257wJeF9V/RjwiEnHkuRY4DeAzVX1MGAdcNoENn0ucOq8aa8APlRVJwAfal9POoZLgYdV1cOBfwLOmkIMJNkEPBm4cYW3Lw0taQZ8GfdDWu2sN92DdSfrToOsOy1iVSR/wKOBG6rqi1V1N/B2YMskA6iq7VV1Vfv8Dpov7rGTjCHJRuBfAm+b5HYHtn8f4GeBswGq6u6q+tYUQlkPHJRkPXAw8NWV3mBVfRz4xrzJW4Dz2ufnAc+YdAxV9YGq2tW+vAzYOOkYWm8AXg44QpQkTZ/1ppZ1px+w7vTDadadFrFakr9jgZsGXm9jCn9A5iQ5HngkcPmEN/1GmoNkdsLbnfNA4Dbgz9ruE29Lcq9JBlBVNwN/SHOWZDtwe1V9YJIxDDiqqra3z28BjppSHHNeCLx30htNsgW4uaqunvS2JUl7Zb3ph96IdSfrTguz7jTPakn+Vo0khwDvBF5aVd+e4HafDtxaVVdOapt7sR44GXhrVT0S+C4r31y/h7Zv+BaaP6bHAPdK8uxJxrA31dwTZWpnbpL8Nk0XmwsmvN2DgVcCvzPJ7UrDygr8kzS8adWb2m1bd8K600KsO+3dakn+bgY2Dbze2E6bqCT70fwBu6CqLp7w5h8P/GKSL9N033hSkj+fcAzbgG1VNXfm7h00f9Am6eeBL1XVbVW1E7gY+KkJxzDna0mOBmj/v3UaQSR5PvB04Fdq8jfmfBDNj8nV7bG5Ebgqyf0nHIe0VyZ/WqOsNzWsOzWsO81j3WlhqyX5+0fghCQPTLI/zUWql0wygDRX+Z8NXF9Vr5/ktgGq6qyq2lhVx9O8/w9X1UTP2lTVLcBNSR7STjoFuG6SMdB0WXhskoPbz+QUpncR9yXA89rnzwP+atIBJDmVpjvLL1bVnZPeflV9pqruV1XHt8fmNuDk9liRJE3Hmq83gXWnAdadBlh3WtyqSP7aizJ/HXg/zcF6UVVdO+EwHg88h+as0afbx9MmHMNq8BLggiTXACcBvzfJjbdnzt4BXAV8huYY3brS201yIfAJ4CFJtiV5EfA64F8k+QLNWbXXTSGGtwCHApe2x+SfTCEGSdIqYr1p1bHuZN2pN3WnTL4lVJKk7k76yUfUh/5h/GMabDjw/ldW1eaxr1iSpClbFS1/kiRJkqSVtX7aAUiStDwO0CJJ0ihs+ZMkSZKkNcCWP0lSj9nyJ0nSsEz+JEm9FEz9JEkahcmfJKm3mltaSZKkYZj8SZJ6zORPkqRhOeCLJEmSJK0BtvxJknrLdj9JkoZn8idJ6jHTP0mShmW3T0lST4Vk/I8lt5qck+TWJJ8dmHZ4kkuTfKH9/77t9CR5c5IbklyT5OQV3CGSJC3K5E+SpNGcC5w6b9orgA9V1QnAh9rXAE8FTmgfpwNvnVCMkiTdg8mfJEkjqKqPA9+YN3kLcF77/DzgGQPTz6/GZcBhSY6eSKCSJM3jNX+SpF5qbvK+Itf8bUhyxcDrrVW1dYkyR1XV9vb5LcBR7fNjgZsGltvWTtuOJEkTZvInSeqxFUn+dlTV5uUWrqpKUuMMSJKkcbDbpySpt7ICj2X62lx3zvb/W9vpNwObBpbb2E6TJGniTP4kSb01jdE+F3AJ8Lz2+fOAvxqY/tx21M/HArcPdA+VJGmi7PYpSdIIklwIPIHm2sBtwKuA1wEXJXkR8BXgme3i7wGeBtwA3Am8YOIBS5LUMvmTJPVUx46ay1RVz1pg1il7WbaAM1Y2IkmShmPyJ0nqrcmnfpIk9ZfJnySpx0z/JEkalgO+SJIkSdIaYMufJKmfQpfROSVJWnNs+ZMkSZKkNcCWP0lSLzVjfdryJ0nSsNKMQi1JUr8keR+wYQVWvaOqTl2B9UqSNFUmf5IkSZK0BnjNnyRJkiStASZ/kiRJkrQGmPxJkiRJ0hpg8idJkiRJa4DJnyRJkiStAf8/J81g+5XTujcAAAAASUVORK5CYII=\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteG3 = trim(imagen[:,:,1], 560, 320, 15, 15)\n", + "poptG3, pcovG3 = curve_fit(gauss2d, xdata3, recorteG3.ravel(), p0=[1,1,1,1,1])\n", + "estrellaG3=gauss2d(xdata3, poptG3[0], poptG3[1],poptG3[2], poptG3[3], poptG3[4])\n", + "FWHMG3=FWHMG.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptG3[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 3 fotografÃa (Banda Verde)\")\n", + "plt.imshow(recorteG3, plt.get_cmap('Greens'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 3 a partir de la gaussiana (Banda Verde)\")\n", + "plt.imshow(estrellaG3.reshape(15, 15), plt.get_cmap('Greens'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 4 (Verde)" + ] + }, + { + "cell_type": "code", + "execution_count": 415, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteG4 = trim(imagen[:,:,1], 442, 370, 15, 15)\n", + "poptG4, pcovG4 = curve_fit(gauss2d, xdata4, recorteG4.ravel(), p0=[1,0,1,1,1])\n", + "estrellaG4=gauss2d(xdata4, poptG4[0], poptG4[1],poptG4[2], poptG4[3], poptG4[4])\n", + "FWHMG4=FWHMG.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptG4[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 4 fotografÃa (Banda Verde)\")\n", + "plt.imshow(recorteG4, plt.get_cmap('Greens'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 4 a partir de la gaussiana (Banda Verde)\")\n", + "plt.imshow(estrellaG4.reshape(15, 15), plt.get_cmap('Greens'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 5 (Verde)" + ] + }, + { + "cell_type": "code", + "execution_count": 416, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteG5 = trim(imagen[:,:,1], 320, 455, 15, 15)\n", + "poptG5, pcovG5 = curve_fit(gauss2d, xdata5, recorteG5.ravel(), p0=[1,1,1,1,1])\n", + "estrellaG5=gauss2d(xdata5, poptG5[0], poptG5[1],poptG5[2], poptG5[3], poptG5[4])\n", + "FWHMG5=FWHMG.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptG5[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 5 fotografÃa (Banda Verde)\")\n", + "plt.imshow(recorteG5, plt.get_cmap('Greens'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 5 a partir de la gaussiana (Banda Verde)\")\n", + "plt.imshow(estrellaG5.reshape(15, 15), plt.get_cmap('Greens'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 6 (Verde)" + ] + }, + { + "cell_type": "code", + "execution_count": 417, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteG6 = trim(imagen[:,:,1], 535, 335, 10, 10)\n", + "poptG6, pcovG6 = curve_fit(gauss2d, xdata6, recorteG6.ravel(), p0=[1,0,1,1,1])\n", + "estrellaG6=gauss2d(xdata6, poptG6[0], poptG6[1],poptG6[2], poptG6[3], poptG6[4])\n", + "FWHMG6=FWHMG.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptG6[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 6 fotografÃa (Banda Verde)\")\n", + "plt.imshow(recorteG6, plt.get_cmap('Greens'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 6 a partir de la gaussiana (Banda Verde)\")\n", + "plt.imshow(estrellaG6.reshape(10, 10), plt.get_cmap('Greens'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 7 (Verde)" + ] + }, + { + "cell_type": "code", + "execution_count": 418, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteG7 = trim(imagen[:,:,1], 540, 345, 10, 10)\n", + "poptG7, pcovG7 = curve_fit(gauss2d, xdata7, recorteG7.ravel(), p0=[1,2,1,1,1])\n", + "estrellaG7=gauss2d(xdata7, poptG7[0], poptG7[1],poptG7[2], poptG7[3], poptG7[4])\n", + "FWHMG7=FWHMG.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptG7[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 7 fotografÃa (Banda Verde)\")\n", + "plt.imshow(recorteG7, plt.get_cmap('Greens'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 7 a partir de la gaussiana (Banda Verde)\")\n", + "plt.imshow(estrellaG7.reshape(10, 10), plt.get_cmap('Greens'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 8 (Verde)" + ] + }, + { + "cell_type": "code", + "execution_count": 419, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteG8 = trim(imagen[:,:,1], 620, 306, 20, 20)\n", + "poptG8, pcovG8 = curve_fit(gauss2d, xdata8, recorteG8.ravel(), p0=[1,1,1,1,1])\n", + "estrellaG8=gauss2d(xdata8, poptG8[0], poptG8[1],poptG8[2], poptG8[3], poptG8[4])\n", + "FWHMG8=FWHMG.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptG8[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 8 fotografÃa (Banda Verde)\")\n", + "plt.imshow(recorteG8, plt.get_cmap('Greens'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 8 a partir de la gaussiana (Banda Verde)\")\n", + "plt.imshow(estrellaG8.reshape(20, 20), plt.get_cmap('Greens'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 9 (Verde)" + ] + }, + { + "cell_type": "code", + "execution_count": 420, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteG9 = trim(imagen[:,:,1], 545, 360, 10, 10)\n", + "poptG9, pcovG9 = curve_fit(gauss2d, xdata9, recorteG9.ravel(), p0=[1,0,2,1,1])\n", + "estrellaG9=gauss2d(xdata9, poptG9[0], poptG9[1],poptG9[2], poptG9[3], poptG9[4])\n", + "FWHMG9=FWHMG.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptG9[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 9 fotografÃa (Banda Verde)\")\n", + "plt.imshow(recorteG9, plt.get_cmap('Greens'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 9 a partir de la gaussiana (Banda Verde)\")\n", + "plt.imshow(estrellaG9.reshape(10, 10), plt.get_cmap('Greens'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 10 (Verde)" + ] + }, + { + "cell_type": "code", + "execution_count": 421, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteG10 = trim(imagen[:,:,1], 615, 394, 10, 10)\n", + "poptG10, pcovG10 = curve_fit(gauss2d, xdata10, recorteG10.ravel(), p0=[1,0,1,1,1])\n", + "estrellaG10=gauss2d(xdata10, poptG10[0], poptG10[1],poptG10[2], poptG10[3], poptG10[4])\n", + "FWHMG10=FWHMG.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptG10[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 10 fotografÃa (Banda Verde)\")\n", + "plt.imshow(recorteG10, plt.get_cmap('Greens'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 10 a partir de la gaussiana (Banda Verde)\")\n", + "plt.imshow(estrellaG10.reshape(10, 10), plt.get_cmap('Greens'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Histograma (Banda Verde)" + ] + }, + { + "cell_type": "code", + "execution_count": 445, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Datos de FWHM de las estrellas para la Banda verde :\n", + "Desviación : 2.525571326812283\n", + "Media : 4.24280156594701\n", + "Mediana : 3.1827269210351594\n" + ] + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "FWHMG = np.array(FWHMG)\n", + "sigmaG = FWHMG.std()\n", + "mediaG = FWHMG.mean()\n", + "medianaG = np.median(FWHMG)\n", + "print(\"Datos de FWHM de las estrellas para la Banda verde :\")\n", + "print(\"Desviación :\", sigmaG)\n", + "print(\"Media :\", mediaG)\n", + "print(\"Mediana :\", medianaG)\n", + "plt.hist(FWHMG)\n", + "plt.xlabel('FHWM')\n", + "plt.ylabel('# de estrellas')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Para la banda B\n", + "* ## Estrella 1 (Azul)" + ] + }, + { + "cell_type": "code", + "execution_count": 426, + "metadata": {}, + "outputs": [], + "source": [ + "FWHMB=[]" + ] + }, + { + "cell_type": "code", + "execution_count": 427, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteB1 = trim(imagen[:,:,2], 210, 237, 15, 15)\n", + "poptB1, pcovB1 = curve_fit(gauss2d, xdata1, recorteB1.ravel(), p0=[1,0,1,1,1])\n", + "estrellaB1=gauss2d(xdata1, poptB1[0], poptB1[1],poptB1[2], poptB1[3], poptB1[4])\n", + "FWHMB1=FWHMB.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptB1[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 1 fotografÃa (Banda Azul)\")\n", + "plt.imshow(recorteB1, plt.get_cmap('Blues'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 1 a partir de la gaussiana (Banda Azul)\")\n", + "plt.imshow(estrellaB1.reshape(15, 15), plt.get_cmap('Blues'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 2 (Azul)" + ] + }, + { + "cell_type": "code", + "execution_count": 428, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteB2 = trim(imagen[:,:,2], 645, 535, 35, 35)\n", + "poptB2, pcovB2 = curve_fit(gauss2d, xdata2, recorteB2.ravel(), p0=[1,0,1,1,1])\n", + "estrellaB2=gauss2d(xdata2, poptB2[0], poptB2[1],poptB2[2], poptB2[3], poptB2[4])\n", + "FWHMB2=FWHMB.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptB2[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 2 fotografÃa (Banda Azul)\")\n", + "plt.imshow(recorteB2, plt.get_cmap('Blues'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 2 a partir de la gaussiana (Banda Azul)\")\n", + "plt.imshow(estrellaB2.reshape(35, 35), plt.get_cmap('Blues'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 3 (Azul)" + ] + }, + { + "cell_type": "code", + "execution_count": 429, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteB3 = trim(imagen[:,:,2], 560, 320, 15, 15)\n", + "poptB3, pcovB3 = curve_fit(gauss2d, xdata3, recorteB3.ravel(), p0=[1,1,1,1,1])\n", + "estrellaB3=gauss2d(xdata3, poptB3[0], poptB3[1],poptB3[2], poptB3[3], poptB3[4])\n", + "FWHMB3=FWHMB.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptB3[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 3 fotografÃa (Banda Azul)\")\n", + "plt.imshow(recorteB3, plt.get_cmap('Blues'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 3 a partir de la gaussiana (Banda Azul)\")\n", + "plt.imshow(estrellaB3.reshape(15, 15), plt.get_cmap('Blues'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 4 (Azul)" + ] + }, + { + "cell_type": "code", + "execution_count": 430, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteB4 = trim(imagen[:,:,2], 442, 370, 15, 15)\n", + "poptB4, pcovB4 = curve_fit(gauss2d, xdata4, recorteB4.ravel(), p0=[1,0,1,1,1])\n", + "estrellaB4=gauss2d(xdata4, poptB4[0], poptB4[1],poptB4[2], poptB4[3], poptB4[4])\n", + "FWHMB4=FWHMB.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptB4[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 4 fotografÃa (Banda Azul)\")\n", + "plt.imshow(recorteB4, plt.get_cmap('Blues'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 4 a partir de la gaussiana (Banda Azul)\")\n", + "plt.imshow(estrellaB4.reshape(15, 15), plt.get_cmap('Blues'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 5 (Azul)" + ] + }, + { + "cell_type": "code", + "execution_count": 431, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteB5 = trim(imagen[:,:,2], 320, 455, 15, 15)\n", + "poptB5, pcovB5 = curve_fit(gauss2d, xdata5, recorteB5.ravel(), p0=[1,0,1,1,1])\n", + "estrellaB5=gauss2d(xdata5, poptB5[0], poptB5[1],poptB5[2], poptB5[3], poptB5[4])\n", + "FWHMB5=FWHMB.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptB5[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 5 fotografÃa (Banda Azul)\")\n", + "plt.imshow(recorteB5, plt.get_cmap('Blues'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 5 a partir de la gaussiana (Banda Azul)\")\n", + "plt.imshow(estrellaB5.reshape(15, 15), plt.get_cmap('Blues'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 6 (Azul)" + ] + }, + { + "cell_type": "code", + "execution_count": 432, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteB6 = trim(imagen[:,:,2], 535, 335, 10, 10)\n", + "poptB6, pcovB6 = curve_fit(gauss2d, xdata6, recorteB6.ravel(), p0=[1,0,1,1,1])\n", + "estrellaB6=gauss2d(xdata6, poptB6[0], poptB6[1],poptB6[2], poptB6[3], poptB6[4])\n", + "FWHMB6=FWHMB.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptB6[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 6 fotografÃa (Banda Azul)\")\n", + "plt.imshow(recorteB6, plt.get_cmap('Blues'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 6 a partir de la gaussiana (Banda Azul)\")\n", + "plt.imshow(estrellaB6.reshape(10, 10), plt.get_cmap('Blues'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 7 (Azul)" + ] + }, + { + "cell_type": "code", + "execution_count": 433, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteB7 = trim(imagen[:,:,2], 540, 345, 10, 10)\n", + "poptB7, pcovB7 = curve_fit(gauss2d, xdata7, recorteB7.ravel(), p0=[1,0,1,1,1])\n", + "estrellaB7=gauss2d(xdata7, poptB7[0], poptB7[1],poptB7[2], poptB7[3], poptB7[4])\n", + "FWHMB7=FWHMB.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptB7[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 7 fotografÃa (Banda Azul)\")\n", + "plt.imshow(recorteB7, plt.get_cmap('Blues'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 7 a partir de la gaussiana (Banda Azul)\")\n", + "plt.imshow(estrellaB7.reshape(10, 10), plt.get_cmap('Blues'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 8 (Azul)" + ] + }, + { + "cell_type": "code", + "execution_count": 434, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteB8 = trim(imagen[:,:,2], 620, 306, 20, 20)\n", + "poptB8, pcovB8 = curve_fit(gauss2d, xdata8, recorteB8.ravel(), p0=[1,1,1,1,1])\n", + "estrellaB8=gauss2d(xdata8, poptB8[0], poptB8[1],poptB8[2], poptB8[3], poptB8[4])\n", + "FWHMB8=FWHMB.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptB8[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 8 fotografÃa (Banda Azul)\")\n", + "plt.imshow(recorteB8, plt.get_cmap('Blues'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 8 a partir de la gaussiana (Banda Azul)\")\n", + "plt.imshow(estrellaB8.reshape(20, 20), plt.get_cmap('Blues'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 9 (Azul)" + ] + }, + { + "cell_type": "code", + "execution_count": 435, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteB9 = trim(imagen[:,:,2], 545, 360, 10, 10)\n", + "poptB9, pcovB9 = curve_fit(gauss2d, xdata9, recorteB9.ravel(), p0=[1,1,1,1,1])\n", + "estrellaB9=gauss2d(xdata9, poptB9[0], poptB9[1],poptB9[2], poptB9[3], poptB9[4])\n", + "FWHMB9=FWHMB.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptB9[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 9 fotografÃa (Banda Azul)\")\n", + "plt.imshow(recorteB9, plt.get_cmap('Blues'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 9 a partir de la gaussiana (Banda Azul)\")\n", + "plt.imshow(estrellaB9.reshape(10, 10), plt.get_cmap('Blues'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 10 (Azul)" + ] + }, + { + "cell_type": "code", + "execution_count": 436, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "recorteB10 = trim(imagen[:,:,2], 615, 394, 10, 10)\n", + "poptB10, pcovB10 = curve_fit(gauss2d, xdata10, recorteB10.ravel(), p0=[1,0,1,1,1])\n", + "estrellaB10=gauss2d(xdata10, poptB10[0], poptB10[1],poptB10[2], poptB10[3], poptB10[4])\n", + "FWHMB10=FWHMB.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptB10[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 10 fotografÃa (Banda Azul)\")\n", + "plt.imshow(recorteB10, plt.get_cmap('Blues'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 10 a partir de la gaussiana (Banda Azul)\")\n", + "plt.imshow(estrellaB10.reshape(10, 10), plt.get_cmap('Blues'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Histograma (Banda Azul)" + ] + }, + { + "cell_type": "code", + "execution_count": 444, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Datos de FWHM de las estrellas para la Banda azul :\n", + "Desviación : 2.699911640184987\n", + "Media : 4.508060549859931\n", + "Mediana : 3.4823388160938347\n" + ] + }, + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAEGCAYAAABo25JHAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAAsTAAALEwEAmpwYAAAVS0lEQVR4nO3de7SldX3f8ffHYSKoXFo4NTgXR4VFSlwCehYBtC2FkKLgTJtgC1UjlGRWjVZsbQzYLlihXV1oU01SjHQEAioLQbwNFyVTJEtARQccEBiMs+w0DKIMg3KTi4Pf/rGfaTaHfc7ZM2eevYfzvF9r7TXP5bef5/uwDudzntvvl6pCktRdLxp3AZKk8TIIJKnjDAJJ6jiDQJI6ziCQpI7bbdwFbK/99tuvli1bNu4yJOkF5bbbbnuoqiYGrXvBBcGyZctYu3btuMuQpBeUJP93unVeGpKkjjMIJKnjDAJJ6jiDQJI6ziCQpI4zCCSp41oPgiQLknw3yTUD1r04yRVJNiS5NcmytuuRJD3XKM4IzgDWT7PudOCnVXUA8DHgwyOoR5LUp9UgSLIYOAG4cJomK4BLm+mrgGOTpM2aJEnP1fabxX8KfBDYc5r1i4D7AKpqa5JHgH2Bh/obJVkJrARYunTpDhez7Mxrd/i7c7XxvBPGtm9JmklrZwRJTgQerKrb5rqtqlpVVZNVNTkxMbCrDEnSDmrz0tAbgeVJNgKfBY5J8pkpbe4HlgAk2Q3YG9jSYk2SpClaC4KqOquqFlfVMuBk4GtV9Y4pzVYD72qmT2raOIiyJI3QyHsfTXIusLaqVgMXAZ9OsgF4mF5gSJJGaCRBUFV/Dfx1M3123/KngLeNogZJ0mC+WSxJHWcQSFLHGQSS1HEGgSR1nEEgSR1nEEhSxxkEktRxBoEkdZxBIEkdZxBIUscZBJLUcQaBJHWcQSBJHWcQSFLHGQSS1HEGgSR1XJuD1++e5NtJ7khyd5I/HtDm1CSbk6xrPr/XVj2SpMHaHKHsaeCYqno8yULg5iRfqapvTWl3RVW9t8U6JEkzaC0ImkHoH29mFzYfB6aXpF1Mq/cIkixIsg54EFhTVbcOaPY7Se5MclWSJW3WI0l6vlaDoKqerapDgcXA4UleO6XJ1cCyqnodsAa4dNB2kqxMsjbJ2s2bN7dZsiR1zkieGqqqnwE3AsdPWb6lqp5uZi8E3jDN91dV1WRVTU5MTLRaqyR1TZtPDU0k2aeZ3gM4Drh3Spv9+2aXA+vbqkeSNFibTw3tD1yaZAG9wLmyqq5Jci6wtqpWA+9LshzYCjwMnNpiPZKkAdp8auhO4LABy8/umz4LOKutGiRJs/PNYknqOINAkjrOIJCkjjMIJKnjDAJJ6jiDQJI6ziCQpI4zCCSp4wwCSeo4g0CSOs4gkKSOMwgkqeMMAknqOINAkjrOIJCkjjMIJKnjDAJJ6rg2xyzePcm3k9yR5O4kfzygzYuTXJFkQ5Jbkyxrqx5J0mBtnhE8DRxTVYcAhwLHJzliSpvTgZ9W1QHAx4APt1iPJGmA1oKgeh5vZhc2n5rSbAVwaTN9FXBskrRVkyTp+VobvB4gyQLgNuAA4ONVdeuUJouA+wCqamuSR4B9gYembGclsBJg6dKlbZbcmmVnXjuW/W4874Sx7FfSC0erN4ur6tmqOhRYDBye5LU7uJ1VVTVZVZMTExM7tUZJ6rqRPDVUVT8DbgSOn7LqfmAJQJLdgL2BLaOoSZLU0+ZTQxNJ9mmm9wCOA+6d0mw18K5m+iTga1U19T6CJKlFbd4j2B+4tLlP8CLgyqq6Jsm5wNqqWg1cBHw6yQbgYeDkFuuRJA3QWhBU1Z3AYQOWn903/RTwtrZqkCTNzjeLJanjDAJJ6jiDQJI6ziCQpI4zCCSp4wwCSeo4g0CSOs4gkKSOMwgkqeNmDYIkH0myV5KFSW5IsjnJO0ZRnCSpfcOcEfxWVT0KnAhspDe2wB+2WZQkaXSGCYJt/RGdAHyuqh5psR5J0ogN0+ncNUnuBZ4E3p1kAniq3bIkSaMy6xlBVZ0JHAVMVtUvgCfojTUsSZoHhu2G+hXAbybZvW/Zp1qoR5I0YrMGQZJzgKOBg4HrgDcDN2MQSNK8MMzN4pOAY4EfV9VpwCH0xhaWJM0DwwTBk1X1S2Brkr2AB2kGnJ9JkiVJbkxyT5K7k5wxoM3RSR5Jsq75nD1oW5Kk9gxzj2BtMwj9J4HbgMeBbw7xva3AB6rq9iR7ArclWVNV90xpd1NVnbg9RUuSdp5Zg6Cq/qCZvCDJV4G9mvGIZ/veA8ADzfRjSdYDi4CpQSBJGqNpgyDJ62daV1W3D7uTJMvoDWR/64DVRya5A/gR8B+r6u4B318JrARYunTpsLuVJA1hpjOC/zHDugKOGWYHSV4GfB54f9NVRb/bgVdW1eNJ3gJ8CTjweTurWgWsApicnKxh9itJGs60QVBV/3SuG0+ykF4IXFZVXxiwj0f7pq9L8hdJ9quqh+a6b0nScGa6NPTbM31x0C/2Kd8PcBGwvqo+Ok2bXwV+UlWV5HB6TzFtmbVqSdJOM9OlobfOsK6AGYMAeCPwTuB7SdY1yz4ELAWoqgvovaPw7iRb6fVldHJVeelHkkZopktDp81lw1V1M5BZ2pwPnD+X/UiS5maYgWlenuSiJF9p5g9Ocnr7pUmSRmGYN4svAa6n1/EcwN8A72+pHknSiA0TBPtV1ZXALwGqaivwbKtVSZJGZpggeCLJvvRuEJPkCMBRyiRpnhimr6H/AKwGXpPkFmCC3tM+kqR5YMYgSLIA+CfN5yB6TwF9vxmpTJI0D8x4aaiqngVOqaqtVXV3Vd1lCEjS/DLMpaFbkpwPXEFvvGIAtqfTOUnSrmuYIDi0+ffcvmVDdzonSdq1DRMEp1fVD/sXJHl1S/VIkkZsmMdHrxqw7HM7uxBJ0njM1PvorwG/Duw9pSfSvYDd2y5MkjQaM10aOgg4EdiH5/ZE+hjw+y3WJEkaoZl6H/0y8OUkR1bVMIPVS5JegIa5R/AvkuyVZGGSG5JsTvKO1iuTJI3EMEHwW82QkicCG4EDgD9ssyhJ0ugMEwQLm39PAD5XVXY4J0nzyDBBcHWSe4E3ADckmQCemu1LSZYkuTHJPUnuTnLGgDZJ8udJNiS5M8nrt/8QJElzMWsQVNWZwFHAZNPP0M+BFUNseyvwgao6GDgCeE+Sg6e0eTNwYPNZCXxiO2qXJO0EwwxV+RLgD/i7X9KvACZn+15VPbCtP6KqegxYDyya0mwF8Knq+RawT5L9t6N+SdIcDXNp6C+BZ+idFQDcD/zX7dlJkmXAYcCtU1YtAu7rm9/E88OCJCuTrE2ydvPmzduza0nSLIYJgtdU1UeAXwBU1c/pjUswlCQvAz4PvL95+mi7VdWqqpqsqsmJiYkd2YQkaRrDBMEzSfbg74aqfA3w9DAbT7KQXghcVlVfGNDkfmBJ3/ziZpkkaUSGCYJzgK8CS5JcBtwAfHC2LyUJcBGwvqo+Ok2z1cDvNk8PHQE8UlUPDFe6JGlnmLUb6qpak+R2ek/+BDijqh4aYttvBN4JfC/JumbZh4ClzXYvAK4D3gJsoPc00mnbewCSpLkZZjwCqmoLcO32bLiqbmaWewlVVcB7tme7kqSda5hLQ5KkecwgkKSOGyoIkrwpyWnN9ESSV7VbliRpVIZ5s/gc4I+As5pFC4HPtFmUJGl0hhqPAFgOPAFQVT8C9myzKEnS6Az1QlnzdM+2F8pe2m5JkqRRGiYIrkzyv+h1CPf7wP8GPtluWZKkURnmhbI/SXIc8Ci9Ae3Prqo1rVcmSRqJYV8oWwP4y1+S5qFpgyDJYzT3BQapqr1aqUiSNFLTBkFV7QmQ5L8ADwCfptdlxNsBB4+RpHlimJvFy6vqL6rqsap6tKo+wXBDVUqSXgCGCYInkrw9yYIkL0rydpp3CiRJL3zDBMG/Bv4l8JPm87ZmmSRpHhjm8dGNeClIkuYtex+VpI4zCCSp41oLgiQXJ3kwyV3TrD86ySNJ1jWfs9uqRZI0vWG6of7PfdMv3o5tXwIcP0ubm6rq0OZz7nZsW5K0k0wbBEn+KMmRwEl9i7857Iar6uvAw3OoTZI0AjOdEdxL71HRVye5KckngX2THLQT939kkjuSfCXJr0/XKMnKJGuTrN28efNO3L0kaaYg+BnwIWADcDTwZ83yM5N8Yyfs+3bglVV1CPA/gS9N17CqVlXVZFVNTkxM7IRdS5K2mSkI/hlwLfAa4KPAbwBPVNVpVXXUXHfcdFfxeDN9HbAwyX5z3a4kaftMGwRV9aGqOhbYSK/DuQXARJKbk1w91x0n+dUkaaYPb2rZMtftSpK2zzDjEVxfVWuBtUneXVVvGuYv9ySX07uktF+STcA59Aa+p6ouoHcT+t1JtgJPAic3Q2JKkkZomC4mPtg3e2qz7KEhvnfKLOvPB86fbTuSpHZt1wtlVXVHW4VIksbDLiYkqeMMAknqOINAkjrOIJCkjjMIJKnjDAJJ6jiDQJI6ziCQpI4zCCSp4wwCSeo4g0CSOs4gkKSOMwgkqeMMAknqOINAkjrOIJCkjmstCJJcnOTBJHdNsz5J/jzJhiR3Jnl9W7VIkqbX5hnBJcDxM6x/M3Bg81kJfKLFWiRJ02gtCKrq68DDMzRZAXyqer4F7JNk/7bqkSQNNuvg9S1aBNzXN7+pWfbA1IZJVtI7a2Dp0qUjKW6+WHbmtWPb98bzThjLfrt4zBqd+fjz9YK4WVxVq6pqsqomJyYmxl2OJM0r4wyC+4ElffOLm2WSpBEaZxCsBn63eXroCOCRqnreZSFJUrtau0eQ5HLgaGC/JJuAc4CFAFV1AXAd8BZgA/Bz4LS2apEkTa+1IKiqU2ZZX8B72tq/JGk4L4ibxZKk9hgEktRxBoEkdZxBIEkdZxBIUscZBJLUcQaBJHWcQSBJHWcQSFLHGQSS1HEGgSR1nEEgSR1nEEhSxxkEktRxBoEkdZxBIEkdZxBIUse1GgRJjk/y/SQbkpw5YP2pSTYnWdd8fq/NeiRJz9fmmMULgI8DxwGbgO8kWV1V90xpekVVvbetOiRJM2vzjOBwYENV/bCqngE+C6xocX+SpB3QZhAsAu7rm9/ULJvqd5LcmeSqJEsGbSjJyiRrk6zdvHlzG7VKUmeN+2bx1cCyqnodsAa4dFCjqlpVVZNVNTkxMTHSAiVpvmszCO4H+v/CX9ws+/+qaktVPd3MXgi8ocV6JEkDtBkE3wEOTPKqJL8CnAys7m+QZP++2eXA+hbrkSQN0NpTQ1W1Ncl7geuBBcDFVXV3knOBtVW1GnhfkuXAVuBh4NS26pEkDdZaEABU1XXAdVOWnd03fRZwVps1SJJmNu6bxZKkMTMIJKnjDAJJ6jiDQJI6ziCQpI4zCCSp4wwCSeo4g0CSOs4gkKSOMwgkqeMMAknqOINAkjrOIJCkjjMIJKnjDAJJ6jiDQJI6ziCQpI5rNQiSHJ/k+0k2JDlzwPoXJ7miWX9rkmVt1iNJer7WgiDJAuDjwJuBg4FTkhw8pdnpwE+r6gDgY8CH26pHkjRYm2cEhwMbquqHVfUM8FlgxZQ2K4BLm+mrgGOTpMWaJElTtDl4/SLgvr75TcBvTNemqrYmeQTYF3iov1GSlcDKZvbxJN+fZp/7Tf1uh+xyx57Rnt/tEsc/4mPeZpc49jHp1LFP+fna3mN/5XQr2gyCnaaqVgGrZmuXZG1VTY6gpF1Ol48dun38HrvHPldtXhq6H1jSN7+4WTawTZLdgL2BLS3WJEmaos0g+A5wYJJXJfkV4GRg9ZQ2q4F3NdMnAV+rqmqxJknSFK1dGmqu+b8XuB5YAFxcVXcnORdYW1WrgYuATyfZADxMLyzmYtbLR/NYl48dun38Hns37bRjj3+AS1K3+WaxJHWcQSBJHTcvgiDJkiQ3Jrknyd1Jzhh3TaOWZEGS7ya5Zty1jFKSfZJcleTeJOuTHDnumkYlyb9vft7vSnJ5kt3HXVObklyc5MEkd/Ut+/tJ1iT5QfPv3xtnjW2Z5tj/e/Nzf2eSLybZZ0e3Py+CANgKfKCqDgaOAN4zoDuL+e4MYP24ixiDPwO+WlW/BhxCR/4bJFkEvA+YrKrX0nsgY64PW+zqLgGOn7LsTOCGqjoQuKGZn48u4fnHvgZ4bVW9Dvgb4Kwd3fi8CIKqeqCqbm+mH6P3y2DReKsanSSLgROAC8ddyygl2Rv4x/SePqOqnqmqn421qNHaDdijeQfnJcCPxlxPq6rq6/SeLuzX303NpcA/H2VNozLo2Kvqr6pqazP7LXrvau2QeREE/ZoeTA8Dbh1zKaP0p8AHgV+OuY5RexWwGfjL5rLYhUleOu6iRqGq7gf+BPhb4AHgkar6q/FWNRYvr6oHmukfAy8fZzFj9G+Ar+zol+dVECR5GfB54P1V9ei46xmFJCcCD1bVbeOuZQx2A14PfKKqDgOeYP5eGniO5lr4Cnph+ArgpUneMd6qxqt5GbVzz8Mn+U/0Lo9ftqPbmDdBkGQhvRC4rKq+MO56RuiNwPIkG+n18HpMks+Mt6SR2QRsqqptZ39X0QuGLvhN4P9U1eaq+gXwBeCoMdc0Dj9Jsj9A8++DY65npJKcCpwIvH0uvTLMiyBouq6+CFhfVR8ddz2jVFVnVdXiqlpG72bh16qqE38ZVtWPgfuSHNQsOha4Z4wljdLfAkckeUnz838sHblRPkV/NzXvAr48xlpGKsnx9C4JL6+qn89lW/MiCOj9VfxOen8Nr2s+bxl3URqJfwdcluRO4FDgv423nNFozoKuAm4Hvkfv/+V53d1CksuBbwIHJdmU5HTgPOC4JD+gd5Z03jhrbMs0x34+sCewpvmdd8EOb98uJiSp2+bLGYEkaQcZBJLUcQaBJHWcQSBJHWcQSFLHGQTSFEme7XsMeV2SZUmOntqza5JLkpyUZEWSL/UtP6sZdW/b/FuTrG6mNya5acp21vX3KimNmkEgPd+TVXVo32fjLO2/Qa/X222OBB5N8g+a+aOaNtvsmWQJQJJ/uLOKlnaUQSDNUVVtpveL/4Bm0SJ63Z1s6/LhKOCWvq9cCfyrZvoU4PJR1ClNxyCQnm+PvstCX+xb/o/6LxkBy/vW3QIc1XR38QN63QIf1XQRfQjwnb62nwd+u5l+K3B1WwciDWO3cRcg7YKerKpDByy/qapO3DaT5JK+dd+g95f/AnpdAXwbOJtel+j3VtVTfW23AD9NcjK9/oHm1E+MNFeeEUg7xy30guAo4JvNAEm7A0fz3PsD21wBfBwvC2kXYBBIO8d6euMCvAn4brNsHfBvee79gW2+CHwEuH4UxUkzMQiknaDpC/5WYEszPgD0LhG9mgFnBFX1WFV9uKqeGWGZ0kD2PipJHecZgSR1nEEgSR1nEEhSxxkEktRxBoEkdZxBIEkdZxBIUsf9P1tu9QzAdBq2AAAAAElFTkSuQmCC\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "FWHMB = np.array(FWHMB)\n", + "sigmaB = FWHMB.std()\n", + "mediaB = FWHMB.mean()\n", + "medianaB = np.median(FWHMB)\n", + "print(\"Datos de FWHM de las estrellas para la Banda azul :\")\n", + "print(\"Desviación :\", sigmaB)\n", + "print(\"Media :\", mediaB)\n", + "print(\"Mediana :\", medianaB)\n", + "plt.hist(FWHMB)\n", + "plt.xlabel('FHWM')\n", + "plt.ylabel('# de estrellas')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Para quienes ya \"dominaron\" el ejercicio inicial\n", + "\n", + "* Como ejercicio final, repita los ajustes realizados inicialmente, esta vez teniendo\n", + "en cuenta la incertidumbre de los datos, para ver si surge algún cambio en los resultados.\n", + "Encuentre una forma de programar sus rutinas de modo que sean fácilmente reutilizables;\n", + "con una buena implementación, este nuevo ajuste debe ser cuestión de un par de minutos\n", + "con pocos o ningún paso manual.\n", + "\n", + "# Repitiendo todos los análisis ahora con incertidumbre :\n", + "\n", + "* Se añade la incertidumbre al fit mediante el valor de sigma, incluyendo el array dado por la aplicacion de la funcion error ya definida al inicio, para cada pixel, repitiendo todos los calculos para las 10 estrellas BN y cada una de sus bandas R,G y B." + ] + }, + { + "cell_type": "code", + "execution_count": 816, + "metadata": {}, + "outputs": [], + "source": [ + "# Lsitas de valores de FWHM teniendo en cuenta las incertidumbres\n", + "FWHM_I=[]\n", + "FWHMR_I=[]\n", + "FWHMG_I=[]\n", + "FWHMB_I=[]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 1 con incertidumbre (blanco y negro)" + ] + }, + { + "cell_type": "code", + "execution_count": 817, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_BN1=error(xdata1, popt1[0], popt1[1],popt1[2], popt1[3], popt1[4], recorte1.ravel(), inc=1)\n", + "popt1Err, pcov1Err = curve_fit(gauss2d, xdata1, recorte1.ravel(), p0=[3,3,3,1,1],sigma=Err_BN1)\n", + "estrella1Err=gauss2d(xdata1, popt1Err[0], popt1Err[1],popt1Err[2], popt1Err[3], popt1Err[4])\n", + "FWHM1Err=FWHM_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(popt1Err[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 1 fotografÃa\")\n", + "plt.imshow(recorte1, plt.get_cmap('gray'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 1 a partir de la gaussiana con incertidumbre\")\n", + "plt.imshow(estrella1Err.reshape(15, 15), plt.get_cmap('gray'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 818, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[3.041995114502331]\n" + ] + } + ], + "source": [ + "FWHMBI=[]\n", + "#recorteB10 = trim(imagen[:,:,2], 615, 394, 10, 10)\n", + "E=error(xdata10, poptB10[0], poptB10[1],poptB10[2], poptB10[3], poptB10[4], recorteB10.ravel(), inc=1)\n", + "poptB10I, pcovB10I = curve_fit(gauss2d, xdata10, recorteB10I.ravel(), p0=[2,2,2,2,1],sigma=E)\n", + "estrellaB10I=gauss2d(xdata10, poptB10I[0], poptB10I[1],poptB10I[2], poptB10I[3], poptB10I[4])\n", + "FWHMB10I=FWHMBI.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptB10I[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 10 fotografÃa (Banda Azul)\")\n", + "plt.imshow(recorteB10, plt.get_cmap('Blues'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 10 a partir de la gaussiana (Banda Azul) con incertidumbre\")\n", + "plt.imshow(estrellaB10I.reshape(10, 10), plt.get_cmap('Blues'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()\n", + "print(FWHMBI)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 2 con incertidumbre (blanco y negro)" + ] + }, + { + "cell_type": "code", + "execution_count": 819, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_BN2=error(xdata2, popt2[0], popt2[1],popt2[2], popt2[3], popt2[4], recorte2.ravel(), inc=1)\n", + "popt2E, pcov2E = curve_fit(gauss2d, xdata2, recorte2.ravel(), p0=[1,0,1,1,1], sigma=Err_BN2)\n", + "estrella2E=gauss2d(xdata2, popt2E[0], popt2E[1],popt2E[2], popt2E[3], popt2E[4])\n", + "FWHM2E=FWHM_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(popt2E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 2 fotografÃa\")\n", + "plt.imshow(recorte2, plt.get_cmap('gray'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 2 a partir de la gaussiana con incertidumbre\")\n", + "plt.imshow(estrella2E.reshape(35, 35), plt.get_cmap('gray'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 3 con incertidumbre (blanco y negro)" + ] + }, + { + "cell_type": "code", + "execution_count": 820, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_BN3=error(xdata3, popt3[0], popt3[1],popt3[2], popt3[3], popt3[4], recorte3.ravel(), inc=1)\n", + "popt3E, pcov3E = curve_fit(gauss2d, xdata3, recorte3.ravel(), p0=[2,2,1,1,1],sigma=Err_BN3)\n", + "estrella3E=gauss2d(xdata3, popt3E[0], popt3E[1],popt3E[2], popt3E[3], popt3E[4])\n", + "FWHM3E=FWHM_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(popt3E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 3 fotografÃa\")\n", + "plt.imshow(recorte3, plt.get_cmap('gray'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 3 a partir de la gaussiana con incertidumbre\")\n", + "plt.imshow(estrella3E.reshape(15, 15), plt.get_cmap('gray'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 4 con incertidumbre (blanco y negro)" + ] + }, + { + "cell_type": "code", + "execution_count": 821, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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6TcUELA09Koqqx1QMj3y1ni3Wxns9Npvqc9xs0rlTRDwq6Q0qZtx9QkUB3Lhe8EMqetV+KukmFc/XxVOIY8rKAvVNkn5BxYSFG1T0sCsirpH03yVdUQ6pvUfSmDOtli7UGP/jUcyX8TsqJmF8otzP1U33P6DiNfJPKq5Pnej65sn4GxWTGf1UxZDf8b4vdcr/B+akiOmi7HF8SsXQiIc6HA6Amr385S+P66+/vvLtHnnkkbdFxLKJ1wRmHtunSvpGRCyeYNUZz/YHJJ0eEUx8hyzRo4is2X6T7QPK4RiflXS3pIc7GxWAdqFHEUC3sH2U7VNcfF/di1T0ql0zUTugW004LTDQ5VaoGJpqSatVfHJHpgfMEPy7A+gic1R8dcQxKkY4XaHi+56BLFEoImsR8XuSfq/TcQDoDApFoL0i4gcaObMnShHxiMaf7AbICoUiACBbFIoAANSDaxQBAAAAACO0tUfRdoz8Dsr26/T+q1DFJ+i9vb0djyH1uajiuezpSfuspIrjkLqN4eH9fV1Se/cfEfn/YyE7TD6DmcA2L3JgGsohd2p3oai5c+e2c5fPkVoYpLaX0hP7oaGh5BgOOeSQjseQeiyreC3Nmzcvqf3g4GByDPv27Utqv2vXrqT2AwMDSe337t2b1B5IQaEIAEA9uEYRAJAtCkUAAOrBNYoAAAAAgBHoUQQAZIseRQAA6pHUo2h7ue37ba+z/dGqggIAYDIaE9pU+QPUidwJQC5a7lG03SvpLyS9VtIGST+yfW1ErKkqOAAAxkJhh9yQOwHISUqP4kmS1kXETyNin6QrJK2oJiwAACZGjyIyQ+4EIBspheIiSeub/t5QLhvB9krbq22v5gQMAABmsCnnTm2LDABGqX0ym4hYJWmVJPX09FApAgAqwweQmI6acyfbvMgBdERKobhR0pKmvxeXywAAaAsKRWSG3AlANlKGnv5I0nG2j7E9R9Lpkq6tJiwAACbGNYrIDLkTgGy03KMYEYO2Pyjpu5J6JV0cEfdWFhkAAOOgsENuyJ0A5CTpGsWIuE7SdRXFAgAAMK2ROwHIRe2T2QAAUBd6FAEAqEdbC8WI0N69e9u5y+eYO3duUvuenpTLOguzZ89Oan/ggQcmx5B6HIaGhpJjGBgYSGq/Z8+e5Bj6+/uTt9HpGFKPw4IFC5Lad8MxxMxFoQigXWx3tH1V20iV+r5bxfs27/3tQY8iACBbJAsAANSDQhEAkC0KRQAA6pE+jhIAAAAAMK3QowgAyBJfjwEAQH0oFAEA2aJQBACgHgw9BQBkq9GrWOXPeGwvsf1922ts32v77HL5n9u+z/Zdtq+x3dfU5jzb62zfb/u36j0iAABUg0IRAIDJG5R0TkQcL+lkSWfZPl7SDZJeGhG/JOkBSedJUnnf6ZJeImm5pK/Y7u1I5AAATAGFIgAgW+3uUYyITRFxe3l7h6S1khZFxPURMViudoukxeXtFZKuiIj+iHhI0jpJJ9VyMAAAqBDXKAIAslXTNYoLba9u+ntVRKwavZLtpZJOkHTrqLveK+mb5e1FKgrHhg3lMgAAuhqFIgAgSzXOerotIpaNt4LtBZK+JenDEbG9afnHVAxPvayOwAAAaBcKRQBAtjox66nt2SqKxMsi4uqm5WdKeqOk0+LZwDZKWtLUfHG5DACArsY1igAATJJtS7pI0tqI+FzT8uWSzpX05ojY3dTkWkmn255r+xhJx0n6YTtjBgCgFfQoAgCy1YEexVMkvUvS3bbvKJedL+lLkuZKuqGoJXVLRLw/Iu61faWkNSqGpJ4VEUPtDhoAgKmiUAQAZKvdhWJE3CTJ+7nrunHafErSp2oLCgCAGlAoAgCy1YlrFAEAmAkoFAEAWapx1lMAAGa8thaKtjVrVuu7nD17dnIMVWwj1fz585Paz507NzmGvr6+5G2k2rNnT0fbS9LQUNqlQr29vckxpD6f8+bNS2qfmmiX12MBAFCb1HNNT0/6/I0pOWwV7aVqHkeqwcHBjraX0vO34eHh5BhmAnoUAQDZokcRAIB6UCgCALJFoQgAQD0oFAEA2aJQBACgHhSKAIBsUSgCAFCPlq+Itb3E9vdtr7F9r+2zqwwMAABgOiF3ApCTlB7FQUnnRMTttg+SdJvtGyJiTUWxAQAwJr4eAxkidwKQjZYLxYjYJGlTeXuH7bWSFknizQ4A0BYUisgJuROAnFRyjaLtpZJOkHRrFdsDAGAyKBSRK3InAN0uuVC0vUDStyR9OCK27+f+lZJWpu4HAABgOiB3ApCDpELR9mwVb3SXRcTV+1snIlZJWiVJPT09fPQLAKgMPYrIzVRzJ9u8yAF0RMuFom1LukjS2oj4XHUhAQAwORSKyAm5E4CctPz1GJJOkfQuSa+xfUf584aK4gIAYFyNWU+r/gFqRO4EIBsps57eJMkVxgIAwJRQ2CEn5E4AcpLSowgAAAAAmIYq+XoMAAA6gR5FAADq0dZCsbe3V319fS23P/DAA6sLpkWDg4PJ2+jt7U1qX8VxmD9/flL7BQsWJMfQ05PWob19+3NmFJ+yPXv2JLUfGhpKjiHV3r17k9o/+eSTSe1J1NFJvP6A7lfM4ZMmNWeYO3ducgyp+VcV+du8efOS2lfxnrl79+6k9jt37ux4DAMDA0nth4eHk9rngh5FAEC2KBQBAKgHhSIAIEvMUgoAQH2YzAYAAAAAMAI9igCAbNGjCABAPSgUAQDZolAEAKAeFIoAgGxRKAIAUA8KRQBAtigUAQCoB5PZAAAAAABGoEcRAJAlvh4DAID6UCgCALJFoQgAQD0oFAEA2aJQBACgHhSKAIBsUSgCAFAPJrMBAAAAAIxAjyIAIFv0KAIAUA8KRQBAlpj1FACA+lAoAgCyRaEIAEA92l4o2m65bW9vb4WRtGbfvn3J25g3b15S+wULFiTHMDw8nNS+r68vOYZDDz00qf3u3buTY3j88ceT2m/bti05hieffDKp/VNPPZXUftYsPi8CANQnJfdrmDNnTlL7gw46KDmGo446Kqn94sWLk2M47LDDktoPDAwkx7Bly5ak9hs2bOh4DLt27Upqn3occ/mQkwwRAJCtXE62AADkhkIRAJAtCkUAAOpBoQgAyBaFIgAA9aBQBABkiVlPAQCoT0/qBmz32v6x7e9UERAAAN3K9hLb37e9xva9ts8ulx9m+wbbD5a/Dy2X2/aXbK+zfZftEzv7CNANyJ0A5CC5UJR0tqS1FWwHAIApafQqVvkzgUFJ50TE8ZJOlnSW7eMlfVTS9yLiOEnfK/+WpNdLOq78WSnpq3UcB2SH3AlA10sqFG0vlvTbkr5WTTgAAExeuwvFiNgUEbeXt3eoSPYXSVoh6dJytUslvaW8vULS16Nwi6Q+22lz7CNr5E4AcpF6jeIXJJ0rKf3LaQAAmKKarlFcaHt109+rImLV6JVsL5V0gqRbJR0REZvKuzZLOqK8vUjS+qZmG8plm4SZ6gsidwKQgZYLRdtvlLQlIm6zfeo4661UMdxGPT1VjHQFAKBQU6G4LSKWjbeC7QWSviXpwxGxvfkLxSMibDPLDp6jldwJADolpXI7RdKbbT8s6QpJr7H9jdErRcSqiFgWEcsoFAEAubM9W0WReFlEXF0ufrwxpLT8vaVcvlHSkqbmi8tlmJmmnDu1O0AAaGi5couI8yJicUQslXS6pH+OiHdWFhkAAOOo4/rEiXooXXQdXiRpbUR8rumuayWdUd4+Q9LfNS1/dzn76cmSnm4aoooZhtwJQE74HkUAQLY68D2Kp0h6l6S7bd9RLjtf0mckXWn7fZIekfS28r7rJL1B0jpJuyW9p63RAgDQokoKxYj4gaQfVLEtAAAmq92FYkTcJMlj3H3aftYPSWfVGhSyRO4EoNvRowgAyFYHehQBAJgRmF0GAAAAADBCW3sUh4eHtXfv3nbu8jmGhoaS2g8PDyfHcPDBBye17+vrS47hyCOPTGr/4he/ODmGY445Jqn9rl27kmN48MEHk9qvW7cuOYaHH344qf3AwEBS+9TXdPPXAgDtRo8iUL/U9/kqZr2fO3duUvvDDz88OYYXvvCFSe1/+Zd/OTmGpUuXJrXv7+9PjmHt2rVJ7Xt7e5NjSK0n9u3bl9Q+tZ5Ibd8uDD0FAGRpMrOUAgCA1lAoAgCyRaEIAEA9uEYRAAAAADACPYoAgGzRowgAQD0oFAEA2aJQBACgHhSKAIAsMZkNAAD1oVAEAGSLQhEAgHowmQ0AAAAAYAR6FAEA2aJHEQCAelAoAgCyRaEIAEA9KBQBANmiUAQAoB4UigCALDHrKQAA9WEyGwAAAADACPQoAgCyRY8iAAD1oFAEAGSLQhEAgHpQKAIAskWhCABAPdpeKA4PD7fctr+/P3n/c+bMSWp/0EEHJcdw8MEHJ7WfPXt2cgxHH310UvtTTjklOYZXvepVSe2reD1cffXVSe23bt2aHEPqa+qAAw5Iar9z586k9kAnUSgC3a+nJ31KjNT87dBDD02O4dhjj01qf9JJJyXH8LKXvSyp/e7du5NjSH0uNm/enBzDY489ltT+qaeeSmpvO6l9LpjMBgAAAAAwAkNPAQBZ4usxAACoD4UiACBbFIoAANSDQhEAkC0KRQAA6pF0jaLtPttX2b7P9lrbv1ZVYAAAANMNuROAXKT2KH5R0j9GxFttz5GUNv0iAABTQI8iMkTuBCALLReKtg+R9OuSzpSkiNgnaV81YQEAMDEKReSE3AlATlKGnh4jaaukv7b9Y9tfs31gRXEBADCuxqynVf8ANSJ3ApCNlEJxlqQTJX01Ik6QtEvSR0evZHul7dW2V3MCBgBUiUIRmZly7tTuAAGgIaVQ3CBpQ0TcWv59lYo3vxEiYlVELIuIZbYTdgcAAJC1KedObY0OAJq0XChGxGZJ622/qFx0mqQ1lUQFAMAk0KOInJA7AchJ6qynH5J0WTlr108lvSc9JAAAJofCDhkidwKQhaRCMSLukMSwCABAR1AoIjfkTgBykdqjCABARzBUFACA+qRMZgMAAAAAmIay6lGcM2dO8jZmz56d1H7WrPRD1tOTVp8PDw8nxzAwMJDUfmhoKDmGVKnHUZLmz5+f1L6K1+QBBxyQ1H7BggVJ7ffu3ZvUntmM0Un0KALdr4rzROo5PzX/k9LP1319fckxHH744UntU/MeSTr44IOT2s+bNy85ht7e3qT25C6Tk1WhCABAMwpFAADqQaEIAMgWhSIAAPWgUAQAZItCEQCAejCZDQAAAABgBApFAECWGl+PUfXPRGxfbHuL7Xualr3C9i2277C92vZJ5XLb/pLtdbbvsn1ijYcEAIDKUCgCALLViUJR0iWSlo9a9meSPhkRr5D0ifJvSXq9pOPKn5WSvlrF4wYAoG5cowgAyFYnrlGMiBttLx29WFJjzvhDJD1W3l4h6etRBHqL7T7bR0XEpvZECwBAaygUAQBI92FJ37X9WRWjdV5ZLl8kaX3TehvKZRSKAICuxtBTAEC2ahp6urC8zrDxs3ISoXxA0kciYomkj0i6qM7HDQBA3ehRBABkq6ahp9siYtkU25wh6ezy9t9K+lp5e6OkJU3rLS6XAQDQ1ehRBABkqVOzno7hMUmvLm+/RtKD5e1rJb27nP30ZElPc30iACAH9CgCALLViclsbF8u6VQVQ1Q3SLpA0u9L+qLtWZL2qpjhVJKuk/QGSesk7Zb0nrYHDABACygUAQCYgoh4+xh3/fJ+1g1JZ9UbEQAA1aNQBABkqxM9igAAzAQUigCAbFEoAgBQDwpFAEC2KBQBAKhH2wvFnp7WJ1q1nbz/3t7e5G2kGhwcTGo/MDCQHMPu3buT2j/++OPJMWzevDmpfRXHYdOmtMkHd+zYkRxD6uth3rx5Se1T/yeq+L8EWpE4SymANqni/zT1XJma90jS1q1bk9o/9NBDyTGknvP37NmTHMP69euT2j/11FPJMfT39ye1Hx4eTmo/U849fD0GAAAAAGAEhp4CALI1Uz7VBQCg3SgUAQDZolAEAKAeFIoAgGxRKAIAUI+kaxRtf8T2vbbvsX257bQrbAEAmILGhDZV/gB1IncCkIuWC0XbiyT9kaRlEfFSSb2STq8qMAAAgOmE3AlATlKHns6SNN/2gKQDJD2WHhIAABOjBxCZIncCkIWWexQjYqOkz0p6VNImSU9HxPVVBQYAwEQYeoqckDsByEnK0NNDJa2QdIykoyUdaPud+1lvpe3VtldzAgYAVIlCETlpJXdqd4wA0JAymc1vSnooIrZGxICkqyW9cvRKEbEqIpZFxDLbCbsDAGAkCkVkZsq5U9sjBIBSSqH4qKSTbR/gogI8TdLaasICAACYdsidAGSj5clsIuJW21dJul3SoKQfS1pVVWAAAEyEHkDkhNwJQE6SZj2NiAskXVBRLAAATBpDRZEjcicAuUj9egwAADqGQhEAgHqkXKMIAAAAAJiG2t6jODw83HLboaGh5P339/cnbyPVnj17ktrPmpX+tG3bti2p/Y9//OPkGLZv357UPvU4StKPfvSjpPbr169PjiH1cezevTupfer/FT066CRef0D9Uv/PUnK/htT87Wc/+1lyDA888EBS+97e3uQYHnrooaT2+/btS47hJz/5SVL7Rx55JDmG1BxyYGAgqf1MOfcw9BQAkK2ZcrIGAKDdKBQBANmiUAQAoB4UigCALDHrKQAA9WEyGwAAAADACPQoAgCyRY8iAAD1oFAEAGSLQhEAgHpQKAIAskWhCABAPSgUAQDZolAEAKAeTGYDAAAAABiBHkUAQJb4egwAAOpDoQgAyBaFIgAA9aBQBABki0IRAIB6UCgCALJFoQgAQD2YzAYAAAAAMAI9igCAbNGjCABAPSgUAQBZYtZTAADq0/ZCcXh4uOW2/f39yfvv7e1Nal9FUpIaQxW2bNmS1P7JJ59MjuH+++9Paj80NJQcw9atW5Pa79ixIzmGvXv3djSG1Nc0iTo6idcf0P1Scr+G1Bywirxl3bp1Se23b9+eHMOaNWuS2leRO6Uey9QcVErPfQYGBpLaz5RzD9coAgAAAABGYOgpACBbM+VTXQAA2o1CEQCQLQpFAADqwdBTAEC2GhPaVPkzEdsX295i+55Ryz9k+z7b99r+s6bl59leZ/t+279Vw2EAAKByExaK+zsh2j7M9g22Hyx/H1pvmAAAjFRHkTjJHspLJC1vXmD7NyStkPTyiHiJpM+Wy4+XdLqkl5RtvmK78zOaoVbkTgCmg8n0KF6iUSdESR+V9L2IOE7S98q/AQCY9iLiRklPjFr8AUmfiYj+cp3GtH4rJF0REf0R8ZCkdZJOaluw6JRLRO4EIHMTFopjnBBXSLq0vH2ppLdUGxYAABPrUI/i/rxQ0qts32r7X2z/Srl8kaT1TettKJdhGiN3AjAdtDqZzRERsam8vVnSEWOtaHulpJXl7RZ3BwDAc9U0mc1C26ub/l4VEasmaDNL0mGSTpb0K5KutP2COoJDtlrKnQCgU5JnPY2IsD3mmbo8ua6SpN7eXqanAwBUpqZCcVtELJtimw2Sro4ioB/aHpa0UNJGSUua1ltcLsMMNpXcabz1AKBOrc56+rjtoySp/L1lgvUBAKhcFw09/bak35Ak2y+UNEfSNknXSjrd9lzbx0g6TtIP0x85MkTuBCArrRaK10o6o7x9hqS/qyYcAAC6m+3LJd0s6UW2N9h+n6SLJb2gnOXyCklnROFeSVdKWiPpHyWdFRFDnYodHUXuBCArEw49LU+Ip6q4ZmODpAskfUbF9Rfvk/SIpLfVGSQAAKMl9gCm7PftY9z1zjHW/5SkT9UXEboNuROA6WDCQnGcE+JpFccCAMCUdKJQBCZC7gRgOkiezAYAgE6hUAQAoB4UigCAbFEoAgBQjxlXKKYmFfv27UuOobe3N6n90FD6PAjdcBzmzp2b1H7+/PnJMaSqIknt7+9Par979+6k9qnPA4k6AGA8w8PDydsYHBxMar9r166Ox7Bjx47kGGbPnp3Uvhvylj179iTHkJqHpubSMyX3mXGFIgBg+pgpJ2sAANqNQhEAkKVOzXoKAMBMQKEIAMgWhSIAAPXo6XQAAAAAAIDuQo8iACBb9CgCAFAPCkUAQLYoFAEAqAeFIgAgS0xmAwBAfSgUAQDZolAEAKAeTGYDAAAAABiBHkUAQLboUQQAoB4UigCAbFEoAgBQDwpFAEC2KBQBAKgHhSIAIEvMegoAQH2YzAYAAAAAMAI9igCAbNGjCABAPSgUAQDZolAEAKAebS8Ue3paH+06e/bs5P2nbmNoaCg5hoGBgY7HkPI8SOmPQZL27t2b1L6/vz85hjlz5iS137dvX3IMqebPn5/Ufnh4uKJIgPajUARmhtRzVRV5S2r+VUXeYjt5G6lSn4sq8tjUGDh3TA49igCAbHGyBwCgHkxmAwAAAAAYgR5FAECW+HoMAADqQ6EIAMgWhSIAAPWYcOip7Yttb7F9T9OyP7d9n+27bF9ju6/WKAEA2I9Gr2KVP0AqcicA08FkrlG8RNLyUctukPTSiPglSQ9IOq/iuAAAAHJ1icidAGRuwkIxIm6U9MSoZddHxGD55y2SFtcQGwAA46JHEd2I3AnAdFDFNYrvlfTNse60vVLSyvJ2BbsDAKBAYYdMTTp3AoBOSSoUbX9M0qCky8ZaJyJWSVolSb29vZzRAQCVoAcQOZpq7mSbFzmAjmi5ULR9pqQ3SjotOFMDADqA0w9yQu4EICctFYq2l0s6V9KrI2J3tSEBAABML+ROAHIzYaFo+3JJp0paaHuDpAtUzNQ1V9IN5XWHt0TE+2uMEwCA56BTBt2I3AnAdDBhoRgRb9/P4otqiAUAgCmhUEQ3IncCMB1UMespAAAdQaEIAEA9KBQBAFli1lMAAOrT9kKxp6en5bbz589P3n9vb29S+6GhoeQY9uzZk9R+cHBw4pUmMHfu3KT2AwMDyTGkPo7U4yilvR6lar4bdM6cOUntDz744KT227dvT2rP96MCALrd8PBw8jZSP5iqIofshnNu6nHgA7580KMIAMgWCQcAAPWgUAQAZItCEQCAelAoAgCyRaEIAEA90i7QAgCggxoT2lT5MxHbF9veYvue/dx3ju2wvbD827a/ZHud7btsn1jDYQAAoHIUigAATM0lkpaPXmh7iaTXSXq0afHrJR1X/qyU9NU2xAcAQDIKRQBAluroTZxMj2JE3Cjpif3c9XlJ50pq3sgKSV+Pwi2S+mwfVcXjBwCgTlyjCADIVrdco2h7haSNEXHnqOnrF0la3/T3hnLZpjaGBwDAlFEoAgCyVVOhuND26qa/V0XEqrFWtn2ApPNVDDsFAGBaoFAEAGSrpkJxW0Qsm8L6x0o6RlKjN3GxpNttnyRpo6QlTesuLpcBANDVuEYRAIAEEXF3RPx8RCyNiKUqhpeeGBGbJV0r6d3l7KcnS3o6Ihh2CgDoevQoAgCy1YlrFG1fLulUFUNUN0i6ICIuGmP16yS9QdI6SbslvactQQIAkIhCEQCQpcnOUlrDft8+wf1Lm26HpLPqjgkAgKpRKAIAstUts54CADDdcI0iAAAAAGAEehQBANmiRxEAgHpQKAIAskWhCABAPdpeKA4PD3ekbVX27NmTvI2BgYEKIkmzY8eOToegoaGhpPbd8Hro6Ukfvb13796k9uX3tnVs/6nPI5CCQhFAu3TD+003xICZgx5FAECWOjXrKQAAMwGT2QAAAAAARqBHEQCQLXoUAQCox4Q9irYvtr3F9j37ue8c22F7YT3hAQAwtsbw0yp/gFTkTgCmg8kMPb1E0vLRC20vkfQ6SY9WHBMAAJNCoYgudYnInQBkbsJCMSJulPTEfu76vKRzJXFWBQB0BIUiuhG5E4DpoKXJbGyvkLQxIu6sOB4AAIBph9wJQG6mPJmN7QMkna9i6MRk1l8paWV5e6q7AwBgv+gBRC5ScicA6JRWZj09VtIxku4sC7/Fkm63fVJEbB69ckSskrRKknp7ezmjAwAqQ6GITLScO9nmRQ6gI6ZcKEbE3ZJ+vvG37YclLYuIbRXGBQDAhCgUkQNyJwA5mszXY1wu6WZJL7K9wfb76g8LAICJMZkNuhG5E4DpYMIexYh4+wT3L60sGgAAgMyROwGYDlq5RhEAgK5ADyAAAPWgUAQAZImhogAA1IdCEQCQLQpFAADq0dZCcXh4eNvOnTsfGWeVhZLGnAFs586d1Qc1xRjahBg6v39imHwMz29XIAAwA22T1HLu1CbE0Pn9E0NeMWSRO7W1UIyInxvvfturI2JZu+Ihhu6NodP7J4buigEYCz2KmO7InfKIodP7JwZiqANDTwEA2aJQBACgHhSKAIBsUSgCAFCPbisUV3U6ABFDQ6dj6PT+JWJo6IYYgOdg1lNAUne8RxND5/cvEUMDMVTEnGQBADmaM2dOHHnkkZVvd/369bdNh2tLAABI0W09igAATBofdgIAUA8KRQBAtigUAQCoR0+nA2iwvdz2/bbX2f5oB/a/xPb3ba+xfa/ts9sdQxlHr+0f2/5Oh/bfZ/sq2/fZXmv71zoQw0fK5+Ae25fbnteGfV5se4vte5qWHWb7BtsPlr8P7UAMf14+F3fZvsZ2X7tjaLrvHNthe2GdMQBT0bhOscofIAfkTSNiIXcidyJ3qkFXFIq2eyX9haTXSzpe0tttH9/mMAYlnRMRx0s6WdJZHYhBks6WtLYD+234oqR/jIhflPTydsdie5GkP5K0LCJeKqlX0ult2PUlkpaPWvZRSd+LiOMkfa/8u90x3CDppRHxS5IekHReB2KQ7SWSXifp0Zr3D0wJhSJmIvKm5yB3IndqRu5Uka4oFCWdJGldRPw0IvZJukLSinYGEBGbIuL28vYOFf/ki9oZg+3Fkn5b0tfaud+m/R8i6dclXSRJEbEvIp7qQCizJM23PUvSAZIeq3uHEXGjpCdGLV4h6dLy9qWS3tLuGCLi+ogYLP+8RdLidsdQ+rykcyWRRQNA55E3lcidnkHu9OwycqeKdEuhuEjS+qa/N6gDbzYNtpdKOkHSrW3e9RdUvKCG27zfhmMkbZX01+UQjq/ZPrCdAUTERkmfVfHpyyZJT0fE9e2MockREbGpvL1Z0hEdiqPhvZL+od07tb1C0saIuLPd+wbGU0dvIj2KyAR507O+IHIncqexkTsl6JZCsWvYXiDpW5I+HBHb27jfN0raEhG3tWuf+zFL0omSvhoRJ0japfqHDIxQjmVfoeKN92hJB9p+Zztj2J8osseOZZC2P6ZimM9lbd7vAZLOl/SJdu4XmCwKRaCzOpU3lfsmdxK501jIndJ1S6G4UdKSpr8Xl8vayvZsFW92l0XE1W3e/SmS3mz7YRVDSF5j+xttjmGDpA0R0fhE8CoVb37t9JuSHoqIrRExIOlqSa9scwwNj9s+SpLK31s6EYTtMyW9UdI7ov1Z7LEqTjx3lq/NxZJut139l9cBLaBQxAxF3lQgdyqQO41C7lSNbikUfyTpONvH2J6j4gLca9sZgG2rGF++NiI+1859S1JEnBcRiyNiqYrH/88R0dZPgyJis6T1tl9ULjpN0pp2xqBi2MTJtg8on5PT1LkL1K+VdEZ5+wxJf9fuAGwvVzGk5s0Rsbvd+4+IuyPi5yNiafna3CDpxPK1AnQchSJmqBmfN0nkTk3InZqQO1WnKwrFKC44/aCk76p4YV8ZEfe2OYxTJL1LxadRd5Q/b2hzDN3gQ5Ius32XpFdI+nQ7d15+IneVpNsl3a3iNbqq7v3avlzSzZJeZHuD7fdJ+oyk19p+UMWndZ/pQAxflnSQpBvK1+RfdiAGAEAXIW/qOuRO5E7TMncyn54CAHI0e/bs6Ovrq3y727Ztuy0illW+YQAAMjKr0wEAANAKhooCAFAfCkUAQLYoFAEAqEdXXKMIAAAAAOge9CgCALJFjyIAAPWgRxEAkK1OfD2G7Yttb7F9T9OyP7d9n+27bF9ju6/pvvNsr7N9v+3fqudIAABQLQpFAEC2OvQ9ipdIWj5q2Q2SXhoRvyTpAUnnSZLt41V8v9tLyjZfsd1b1eMHAKAuFIoAgCzVUSROplCMiBslPTFq2fXld9tJ0i2SFpe3V0i6IiL6I+IhSesknVTdUQAAoB4UigAAjLTQ9uqmn5VTbP9eSf9Q3l4kaX3TfRvKZQAAdDUmswEAZKumyWy2RcSyVhra/pikQUmXVRsSAADtRaEIAMhWN816avtMSW+UdFo8G9hGSUuaVltcLgMAoKsx9BQAkK0OTWbzHLaXSzpX0psjYnfTXddKOt32XNvHSDpO0g+THzgAADWjRxEAkK1O9CjavlzSqSquZdwg6QIVs5zOlXSDbUm6JSLeHxH32r5S0hoVQ1LPioihtgcNAMAUuZuG7QAAMFm9vb0xb968yre7e/fu21q9RhEAgOmCHkUAQJZShooCAIDxUSgCALJFoQgAQD0oFAEA2aJQBACgHhSKAIBsUSgCAFAPvh4DAAAAADACPYoAgGzRowgAQD0oFAEAWWLWUwAA6kOhCADIFoUiAAD14BpFAAAAAMAI9CgCALJFjyIAAPWgUAQAZItCEQCAelAoAgCyRaEIAEA9KBQBALn6rqSFNWx3Ww3bBAAgK+bTWAAAAABAM2Y9BQAAAACMQKEIAAAAABiBQhEAAAAAMAKFIgAAAABgBApFAAAAAMAI/x+Q+fnqZg8ongAAAABJRU5ErkJggg==\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_BN4=error(xdata4, popt4[0], popt4[1],popt4[2], popt4[3], popt4[4], recorte4.ravel(), inc=1)\n", + "popt4E, pcov4E = curve_fit(gauss2d, xdata4, recorte4.ravel(), p0=[3,2,2,1,1],sigma=Err_BN4)\n", + "estrella4E=gauss2d(xdata4, popt4E[0], popt4E[1],popt4E[2], popt4E[3], popt4E[4])\n", + "FWHM4E=FWHM_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(popt4E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 4 fotografÃa\")\n", + "plt.imshow(recorte4, plt.get_cmap('gray'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 4 a partir de la gaussiana con incertidumbre\")\n", + "plt.imshow(estrella4E.reshape(15, 15), plt.get_cmap('gray'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 5 con incertidumbre (blanco y negro)" + ] + }, + { + "cell_type": "code", + "execution_count": 822, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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9hutOEfGwpDdKOr2M9TY9c73gh1W0qt0v6QYVn9cFE4hjwsoE9c2SXqBiwMK1KrrxKiKulPR/JF3qokvtXZJGHWm1dI5G+Y5HMV7G76sYhPHxcj1X1L3+CxX7yPdVXJ863vXNjfgXFYMZ3a+iy+9fjzHvhL8H5qCIyaJscdysomvEAx0OB0DFjjjiiLj22tbfQ3zu3Lm3RMSi8ecE9jy2XyPp6xExf5xZ93i2PyjppIhg4DtkiRZFZM32m23vVXbH+KykOyU92NmoALQLLYoAuoXtg8ouv1Nc3C7kdBUjVwJZGndYYKDLLVHRNdWSVqg4c0dND9hD8HUH0EWmqbh1xKEqejhdquJ+z0CWSBSRtYj4I0l/1Ok4AHQGiSLQXhHxIw0d2ROliHhIYw92A2SFRBEAkC0SRQAAqsE1igAAAACAIdraomg7ht6DcmKmTZvWwmia09/fn7yM1DPgU6d2viF49+7dycvo7e1NKt/T05Mcw8DAQFL5vr6+5Bha8T5SDA6OdLulxpUDgDT/xQaaxOAz2BPYZicHJqEc6k7tThQ1Y8aMpsvPmzcvOYbUSvm6deuSY9i1a6zb/I1vzpw5yTGkbofNmzcnxzB37tyk8vvvv39yDBs2bEgq34r9Yd99900qn3LyRZK2bt2aVD412QZSkCgCAFCNzjdNAQDQJBJFAACqwTWKAAAAAIAhaFEEAGSLFkUAAKqR1KJoe7Hte22vtv2xVgUFAEAjagPatPIBVIm6E4BcNN2iaLtH0j9Kep2ktZJ+ZvuqiLi7VcEBADAaEjvkhroTgJyktCgeLWl1RNwfEX2SLpW0pDVhAQAwPloUkRnqTgCykZIozpO0pu7/teW0IWwvtb3C9oqEdQEAAOSOuhOAbFQ+mE1ELJO0TJKmTJnCqVoAQMvQAojJqL7uZJudHEBHpCSK6yQtqPt/fjkNAIC2IFFEZqg7AchGStfTn0k6zPahtqdJOknSVa0JCwCA8XGNIjJD3QlANppuUYyIAdsfknSNpB5JF0TEypZFBgDAGEjskBvqTgByknSNYkRcLenqFsUCAAAwqVF3ApCLygezAQCgKrQoAgBQjbYmitOmTdO8ec8aBbphhx12WHIMq1atSio/ZUrKZZ2F3t7epPIp27DmgQceSCo/dWr6rrNz586k8uvWdf76/wMOOCB5GX19fUnld+/enVR+5syZSeW3bduWVB5IQaIIAEA1aFEEAGSLRBEAgGqkN48BANAh7R711PYC2z+0fbftlbZPK6f/ne17bN9h+0rbs+vKnGl7te17bf9etVsEAIDWIFEEAKBxA5JOj4jDJR0j6VTbh0taLuklEfHbkn4h6UxJKl87SdKLJS2W9CXbPR2JHACACSBRBABkqYrWxPFaFCNifUTcWj5/UtIqSfMi4tqIGChnu0nFjdQlaYmkSyNiV0Q8IGm1pKMr2SAAALQQ1ygCALLVyWsUbS+UdKSkm4e99D5J3yifz1ORONasLacBANDVSBQBANmqKFGcY3tF3f/LImJZ/Qy295b0LUkfiYitddM/rqJ76sVVBAYAQLuQKAIAMNSmiFg02ou2e1UkiRdHxBV100+RdIKk4+KZDHadpAV1xeeX0wAA6GpcowgAyFYHRj21pPMlrYqIz9VNXyzpDElviYin6opcJekk29NtHyrpMEk/bfmGAACgxWhRBABkqwPXKB4r6d2S7rR9WzntLElflDRd0vIil9RNEfGBiFhp+zJJd6voknpqROxud9AAAEwUiSIAIEuNtABWsM4bJHmEl64eo8ynJH2qsqAAAKgAiSIAIFudHPUUAIDJjGsUAQAAAABD0KIIAMgWLYoAAFSDRBEAkC0SRQAAqkGiCADIFokiAADVIFEEAGSpE6OeAgCwp2hromhbU6c2v8r7778/OYbNmzcnlT/ggAOSY3jyySeTyvf19SXHMGVK2jhGu3d3/jZgg4ODHV9GK2JI1dPTk1S+G94DAABjKe9P2lGcmMKehhZFAEC2qLgBAFANEkUAQLZIFAEAqAaJIgAgWySKAABUg0QRAJAtEkUAAKrR9IgmthfY/qHtu22vtH1aKwMDAACYTKg7AchJSovigKTTI+JW2/tIusX28oi4u0WxAQAwKm6PgQxRdwKQjaYTxYhYL2l9+fxJ26skzZPEjx0AoC1IFJET6k4ActKSaxRtL5R0pKSbW7E8AAAaQaKIXFF3AtDtkhNF23tL+pakj0TE1hFeXyppqSRNncrYOQAAYM82kboTAHRKUuZmu1fFD93FEXHFSPNExDJJyyRp5syZnPoFALQMLYrIzUTrTrbZyQF0RNOJom1LOl/Sqoj4XOtCAgCgMSSKyAl1JwA5afr2GJKOlfRuSa+1fVv5eGOL4gIAYEy1UU9b/QAqRN0JQDZSRj29QZJbGAsAABNCYoecUHcCkJOUFkUAAAAAwCTEMKQAgGzRoggAQDXamija1owZM5ou/9hjjyXH0Nvbm1R+r732So5hYGAgeRmp9t9//6TyO3bsSI5hypS0Bu3+/v7kGFqxjFSp+2Sq3bt3J5UvxmYAOoNEEaheT09PUvlWHOdSYxgcHEyOIbXOkHq8lfjNQ3vRoggAyBaVJgAAqkGiCADIEqOUAgBQHQazAQAAAAAMQYsiACBbtCgCAFANEkUAQLZIFAEAqAaJIgAgWySKAABUg0QRAJAtEkUAAKrBYDYAAAAAgCFoUQQAZInbYwAAUB0SRQBAtkgUAQCoBokiACBbJIoAAFSDRBEAkC0SRQAAqsFgNgAAAACAIWhRBABkixZFAACqQaIIAMgSo54CAFAdEkUAQLZIFAEAqEZbE8WI0M6dO5su/5znPCc5hv7+/qTyU6emb7KFCxcmld9nn32SY3jiiSeSym/evDk5hpR9oVUGBweTyk+Zkn6Zb+o+ZTup/MDAQFJ5AED36unpSV7G3nvvnVR+7ty5yTHst99+SeWfeuqp5Bg2bNiQVD617iWl12OBiaBFEQCQLVoUAQCoBokiACBbJIoAAFSDRBEAkC0SRQAAqkGiCADIEqOeAgBQneSROGz32P657e+1IiAAAIDJjLoTgBy0okXxNEmrJP1aC5YFAEDDaFFEpqg7Aeh6SS2KtudLepOkr7QmHAAAGlfrftrKx1hsL7D9Q9t3215p+7Ry+v62l9u+r/y7Xzndtr9oe7XtO2wf1YbNgi5G3QlALlK7nn5e0hmS0m5GBwBAE9qdKEoakHR6RBwu6RhJp9o+XNLHJF0XEYdJuq78X5LeIOmw8rFU0nlVbAdk5fOi7gQgA00nirZPkLQxIm4ZZ76ltlfYXsGNvQEArdTuRDEi1kfEreXzJ1V0H5wnaYmki8rZLpJ0Yvl8iaSvReEmSbNtH1TBpkAGmqk7tSk0AHiWlBbFYyW9xfaDki6V9FrbXx8+U0Qsi4hFEbFo6lQGWQUATA62F0o6UtLNkg6MiPXlSxskHVg+nydpTV2xteU07JkmXHdqd4AAUNN0ohgRZ0bE/IhYKOkkST+IiHe1LDIAAMZQRWti2aI4p9aaUz6WDl+37b0lfUvSRyJi67C4QhKj7OBZqDsByAlNfACAbFU06ummsVpybPeqSBIvjogrysmP2j4oItaXXUs3ltPXSVpQV3x+OQ0AgK6WfB9FSYqIH0XECa1YFgAAjerAqKeWdL6kVRHxubqXrpJ0cvn8ZEnfqZv+nnL002Mkbanrooo9GHUnAN2OFkUAQLYqalEcy7GS3i3pTtu3ldPOkvQZSZfZfr+khyS9vXztaklvlLRa0lOS3tvWaAEAaBKJIgAADYqIGyR5lJePG2H+kHRqpUEBAFCBtiaKu3fv1pYtW5ouP3v27OQYZs2alVR+3rz0were+ta3JpVfvz6919Ly5cuTyvf39yfHkHq7lN7e3o7H0ApFT7bOmTIlrQd6p+PHnq0DLYpA26X8zk6fPj15/QsWLBh/pjG89rWvTY7hyCOPTCq/du3a5BhS60533HFHcgxbt24df6YxDA5y+040jhZFAECWGrmmEAAANIdEEQCQLRJFAACq0ZJRTwEAAAAAkwctigCAbNGiCABANUgUAQDZIlEEAKAaJIoAgCwxmA0AANUhUQQAZItEEQCAajCYDQAAAABgCFoUAQDZokURAIBqkCgCALJFoggAQDVIFAEA2SJRBACgGiSKAIAsMeopAADVYTAbAAAAAMAQtCgCALJFiyIAANUgUQQAZItEEQCAapAoAgCyRaIIAEA12poo2tb06dObLt/X15ccw/77759U/lWvelVyDCeddFJS+RtvvDE5hh//+MdJ5WfMmJEcw+bNm5PKT52avvtOmzYtqfzAwEByDLt3704qPzg4mFS+v78/qTwVdXQS+x/2BLabLpt6nJOkefPmJZU//vjjk2N485vfnFT+zjvvTI7hwQcfTCr/y1/+MjmGbdu2JZVPrTNgz8JgNgAAAACAIeh6CgDIErfHAACgOiSKAIBskSgCAFANEkUAQLZIFAEAqEbSNYq2Z9u+3PY9tlfZfkWrAgMAAJhsqDsByEVqi+IXJP17RLzN9jRJe7UgJgAAGkKLIjJE3QlAFppOFG3vK+l3JJ0iSRHRJyn9/hUAADSIRBE5oe4EICcpXU8PlfSYpK/a/rntr9ie1aK4AAAYU23U01Y/gApRdwKQjZREcaqkoySdFxFHStou6WPDZ7K91PYK2ytSbywOAEA9EkVkZsJ1p3YHCAA1KYniWklrI+Lm8v/LVfz4DRERyyJiUUQs6unpSVgdAABA1iZcd2prdABQp+lEMSI2SFpj+0XlpOMk3d2SqAAAaAAtisgJdScAOUkd9fTDki4uR+26X9J700MCAKAxJHbIEHUnAFlIShQj4jZJdIsAAHQEiSJyQ90JQC5SWxQBAOgIuooCAFCdlMFsAAAAAACTUFtbFG1r+vTpTZfv60u/J21vb29S+VacvU5dxgMPPJAcw/bt25PKDwwMJMfQDbdLSR2JtxXbIXW/7u/v72j5wcHBpPJACloUsSdI2c9b8R1JPU5t2bIlOYZf/epXSeU3b96cHMPOnTuTyrei3sNvHtqJrqcAgGxRaQIAoBokigCAbJEoAgBQDRJFAEC2SBQBAKgGg9kAAAAAAIagRREAkCVujwEAQHVIFAEA2SJRBACgGiSKAIBskSgCAFANrlEEAAAAAAxBiyIAIFu0KAIAUA0SRQBAtkgUAQCoBokiACBLjHoKAEB1SBQBANkiUQQAoBoMZgMAwATYvsD2Rtt31U17qe2bbN9me4Xto8vptv1F26tt32H7qM5FDgBA40gUAQDZqnU/beWjARdKWjxs2t9K+mREvFTSJ8r/JekNkg4rH0slndeK9w0AQNXoegoAyFYnup5GxPW2Fw6fLOnXyuf7SnqkfL5E0teiCPQm27NtHxQR69sTLQAAzSFRBABkq6JEcY7tFXX/L4uIZeOU+Yika2x/VkVvnVeW0+dJWlM339pyGokiAKCrtTVRjAjt2rWr6fK7d+9OjiF1GT/72c+SYzj//POTyl933XXJMWzYsCGp/MDAQHIMKPT39yeVT/lOSVJfX19SeQYTQadUOOrppohYNMEyH5T00Yj4lu23Szpf0vGtDw2YmJ07dyYv46GHHkoq/93vfjc5hnvvvTep/MaNG5NjWLlyZVL57du3J8fAMRftxDWKAACkO1nSFeXzb0o6uny+TtKCuvnml9MAAOhqJIoAgGx1aDCbkTwi6dXl89dKuq98fpWk95Sjnx4jaQvXJwIAcsA1igCAbHWiG5btSyS9RsW1jGslnS3pjyV9wfZUSTtVjHAqSVdLeqOk1ZKekvTetgcMAEATSBQBANnq0Kin7xjlpf8ywrwh6dRqIwIAoPWSup7a/qjtlbbvsn2J7RmtCgwAgPF0UddToCHUnQDkoulE0fY8SX8maVFEvERSj6STWhUYAADAZELdCUBOUrueTpU003a/pL30zA2GAQCoFC2AyBR1JwBZaLpFMSLWSfqspIdV3Dh4S0Rc26rAAAAYD11PkRPqTgByktL1dD9JSyQdKulgSbNsv2uE+ZbaXmF7RerN7gEAqEeiiJw0U3dqd4wAUJMymM3xkh6IiMciol/FjYZfOXymiFgWEYsiYlFPT0/C6gAAGIpEEZmZcN2p7RECQCklUXxY0jG297JtScdJWtWasAAAACYd6k4AstH0YDYRcbPtyyXdKmlA0s8lLWtVYAAAjIcWQOSEuhOAnCSNehoRZ0s6u0WxAADQMLqKIkfUnQDkIvX2GAAAdAyJIgAA1Ui5RhEAAAAAMAm1tUWxp6dHs2fPbrr8mjVrkmN45JG0+9pu3rw5OYZVq9KuWx8YGEiO4YknnkgqP3369OQYBgcHk8rv2rUrOYbUZaS+B0maOjXta9jb25scQ4pWfCeAZtGiiD1Byn7e39+fvP4NGzYklb/hhhuSY7j11luTyrdiO6TWnXbs2JEcQyvqHUCj6HoKAMgWiSIAANUgUQQAZItEEQCAapAoAgCyxKinAABUh8FsAAAAAABD0KIIAMgWLYoAAFSDRBEAkC0SRQAAqkGiCADIFokiAADVIFEEAGSLRBEAgGowmA0AAAAAYAhaFAEAWeL2GAAAVIdEEQCQLRJFAACqQaIIAMgWiSIAANUgUQQAZItEEQCAajCYDQAAAABgCFoUAQDZokURAIBqkCgCALLEqKcAAFSnrYniwMCAHn300abL79ixIzmGrVu3drR8K8ycOTN5GYODg0nlW/FZpEp9D90Sw8DAQFL5KVPSepCnlgc6iUQRGFsrjlOpx/y+vr7kGFKPVa34rdi9e3dS+W6otwATQQ0RAAAAADAEXU8BANmiRREAgGqQKAIAskWiCABANUgUAQDZIlEEAKAa416jaPsC2xtt31U3bX/by23fV/7dr9owAQAYqjbqaasfQCrqTgAmg0YGs7lQ0uJh0z4m6bqIOEzSdeX/AAAAoO4EYBIYN1GMiOslPT5s8hJJF5XPL5J0YmvDAgBgfLQoohtRdwIwGTR7jeKBEbG+fL5B0oGjzWh7qaSlktTT09Pk6gAAeDYSO2SkqboTAHRK8mA2ERG2Rz1SR8QyScskadq0aRzRAQAtQ6KIHE2k7jTWfABQpWYTxUdtHxQR620fJGljK4MCAKARJIrICHUnAFlpZDCbkVwl6eTy+cmSvtOacAAAACYl6k4AsjJui6LtSyS9RtIc22slnS3pM5Ius/1+SQ9JenuVQQIAMByDz6BbUXcCMBmMmyhGxDtGeem4FscCAMCEkCiiG1F3AjAZJA9mAwBAp5AoAgBQDRJFAEC2SBQBAKhGWxPFwcFB7dq1q+nyM2fObGE0zdm2bVvyMmwnlZ82bVpyDFOmNDuOUaGvry85hv7+/qTyrbgvZ+pnMTg4mBxD6nZI1dvbm1SeijoATG6pv/MDAwMtigRAO9GiCADIFicqAACoRlqzEgAAHVIb9bTVj/HYvsD2Rtt3DZv+Ydv32F5p+2/rpp9pe7Xte23/XgWbAgCAlqNFEQCQrQ61KF4o6VxJX6tNsP27kpZIOiIidtk+oJx+uKSTJL1Y0sGSvm/7hRGxu+1RAwAwAbQoAgAwARFxvaTHh03+oKTPRMSucp6N5fQlki6NiF0R8YCk1ZKObluwAAA0iUQRAJCtirqezrG9ou6xtIFQXijpVbZvtv1j2y8rp8+TtKZuvrXlNAAAuhpdTwEA2aqo6+mmiFg0wTJTJe0v6RhJL5N0me3ntTwyAADahEQRAJClRgefaZO1kq6IIqCf2h6UNEfSOkkL6uabX04DAKCr0fUUAJCtTox6OopvS/pdSbL9QknTJG2SdJWkk2xPt32opMMk/TT9nQMAUC1aFAEAmADbl0h6jYprGddKOlvSBZIuKG+Z0Sfp5LJ1caXtyyTdLWlA0qmMeAoAyAGJIgAgW53oehoR7xjlpXeNMv+nJH2quogAAGg9EkUAQLa66BpFAAAmFRJFAEC2SBQBAKgGiSIAIEtdNuopAACTCqOeAgAAAACGoEURAJAtWhQBAKgGiSIAIFskigAAVKOtiWJEaGBgoOnys2bNSo5h9+78b1+1Y8eO5GVs3749qXxfX19yDKlasT9MmZLW+7q/vz85hsHBweRlAHsqEkUAAKpBiyIAIFskigAAVIPBbAAAAAAAQ9CiCADIErfHAACgOuO2KNq+wPZG23fVTfs72/fYvsP2lbZnVxolAAAjqCWLrXwAqag7AZgMGul6eqGkxcOmLZf0koj4bUm/kHRmi+MCAGBcJIroUheKuhOAzI2bKEbE9ZIeHzbt2oioDV96k6T5FcQGAACQHepOACaDVlyj+D5J32jBcgAAmBBaAJEp6k4Aul5Somj745IGJF08xjxLJS0tn6esDgCAIUgUkZuJ1p0AoFOaThRtnyLpBEnHxRhH6ohYJmmZJPX09HBEBwC0BNcUIjfN1J1ss5MD6IimEkXbiyWdIenVEfFUa0MCAKAxJIrIBXUnALlp5PYYl0i6UdKLbK+1/X5J50raR9Jy27fZ/nLFcQIAAGSBuhOAyWDcFsWIeMcIk8+vIBYAACaEFkV0I+pOACaDVox6CgBAR5AoAgBQDRJFAEC2SBQBAKgGiSIAIEuMegoAQHXamigODg5q69at7Vzls/T39yeV7+npSY5h+vTpSeUff/zx5Bh27NiRVL4btsOUKeOOxTSuqVPzP1eS+h5asR0BAAAwueRfSwYA7LFoUQQAoBokigCAbJEoAgBQDRJFAEC2SBQBAKgGiSIAIFskigAAVINRLAAAAAAAQ9CiCADIErfHAACgOiSKAIBskSgCAFANEkUAQLZIFAEAqAaJIgAgWySKAABUg8FsAAAAAABD0KIIAMgWLYoAAFSDRBEAkCVGPQUAoDokigCAbJEoAgBQDa5RBAAAAAAMQYsiACBbtCgCAFANEkUAQLZIFAEAqEbbE0XbTZedNWtW8vq3bNmSVH7q1PRNNnPmzKTyO3bs6HgM06dPT45hYGAgqfyUKZOj53TqPtXb29vR9ad8p4FUJIoAAFSDFkUAQJYY9RQAgOpMjiYZAAAAAEDL0KIIAMgWLYoAAFRj3BZF2xfY3mj7rhFeO9122J5TTXgAAIyu1v20lQ8gFXUnAJNBI11PL5S0ePhE2wskvV7Swy2OCQCAhpAooktdKOpOADI3bqIYEddLenyEl/5e0hmSOKoCADqiE4niRFqLXPii7dW277B9VAWbAV2GuhOAyaCpwWxsL5G0LiJub3E8AAB0uwvVeGvRGyQdVj6WSjqvDfGhC1F3ApCbCQ9mY3svSWepOBg2Mv9SFQdHAABaplNdRSPietsLR3ip1lr0nbppSyR9LYpAb7I92/ZBEbG+DaGiS1B3ApCjZloUny/pUEm3235Q0nxJt9qeO9LMEbEsIhZFxKLmwwQA4Nm65RrFMVqL5klaU/f/2nIa9izUnQBkZ8ItihFxp6QDav+XP3iLImJTC+MCAGBcFbUozrG9ou7/ZRGxbLSZJ9pahD0PdScAORo3UbR9iaTXqDhwrpV0dkScX3VgAACMp6JEcdMEW3LqW4ukZ1qLjpa0TtKCunnnl9MwiVF3AjAZjJsoRsQ7xnl9YcuiAQAgM2O1Ftm+StKHbF8q6eWStnB94uRH3QnAZDDhrqcAAHSLTgxmM8HWoqslvVHSaklPSXpvW4IEACARiSIAIEsdHPW04daicrTTU6uOCQCAViNRBABkqxOJIgAAe4J2J4qbIuKhMV6fI2nUEcDWr2/LZR1jxvDUU08lr2Dz5s1JMbTJmDHs2LGjo+uXpG3btnU8hjYYN4Yu+CwOqToAANiDbZLUdN2pTYih8+snhrxiyKLu1NZEMSKeM9brtld0+p5BxNAdMXR6/cTQXTEAo6FFEZMddac8Yuj0+omBGKpA11MAQLZIFAEAqAaJIgAgWySKAABUo9sSxWWdDkDEUNPpGDq9fokYarohBuBZOjXqKdBluuE3mhg6v36JGGqIoUXMQRYAkKNp06bF3LlzW77cNWvW3DIZri0BACBFt7UoAgDQME52AgBQDRJFAEC2SBQBAKjGlE4HUGN7se17ba+2/bEOrH+B7R/avtv2StuntTuGMo4e2z+3/b0OrX+27ctt32N7le1XdCCGj5afwV22L7E9ow3rvMD2Rtt31U3b3/Zy2/eVf/frQAx/V34Wd9i+0vbsdsdQ99rptsP2nCpjACaidp1iKx9ADqg3DYmFuhN1J+pOFeiKRNF2j6R/lPQGSYdLeoftw9scxoCk0yPicEnHSDq1AzFI0mmSVnVgvTVfkPTvEfEbko5odyy250n6M0mLIuIlknokndSGVV8oafGwaR+TdF1EHCbpuvL/dsewXNJLIuK3Jf1C0pkdiEG2F0h6vaSHK14/MCEkitgTUW96FupO1J3qUXdqka5IFCUdLWl1RNwfEX2SLpW0pJ0BRMT6iLi1fP6kii/5vHbGYHu+pDdJ+ko711u3/n0l/Y6k8yUpIvoiYnMHQpkqaabtqZL2kvRI1SuMiOslPT5s8hJJF5XPL5J0YrtjiIhrI2Kg/PcmSfPbHUPp7yWdIYlaNAB0HvWmEnWnp1F3emYadacW6ZZEcZ6kNXX/r1UHfmxqbC+UdKSkm9u86s+r2KEG27zemkMlPSbpq2UXjq/YntXOACJinaTPqjj7sl7Sloi4tp0x1DkwItaXzzdIOrBDcdS8T9K/tXultpdIWhcRt7d73cBYqmhNpEURmaDe9IzPi7oTdafRUXdK0C2JYtewvbekb0n6SERsbeN6T5C0MSJuadc6RzBV0lGSzouIIyVtV/VdBoYo+7IvUfHDe7CkWbbf1c4YRhJF7bFjNUjbH1fRzefiNq93L0lnSfpEO9cLNIpEEeisTtWbynVTdxJ1p9FQd0rXLYniOkkL6v6fX05rK9u9Kn7sLo6IK9q8+mMlvcX2gyq6kLzW9tfbHMNaSWsjonZG8HIVP37tdLykByLisYjol3SFpFe2OYaaR20fJEnl342dCML2KZJOkPTOaH8t9vkqDjy3l/vmfEm32m79zeuAJpAoYg9FvalA3alA3WkY6k6t0S2J4s8kHWb7UNvTVFyAe1U7A7BtFf3LV0XE59q5bkmKiDMjYn5ELFTx/n8QEW09GxQRGyStsf2ictJxku5uZwwquk0cY3uv8jM5Tp27QP0qSSeXz0+W9J12B2B7sYouNW+JiKfavf6IuDMiDoiIheW+uVbSUeW+AnQciSL2UHt8vUmi7lSHulMd6k6t0xWJYhQXnH5I0jUqduzLImJlm8M4VtK7VZyNuq18vLHNMXSDD0u62PYdkl4q6dPtXHl5Ru5ySbdKulPFPrqs6vXavkTSjZJeZHut7fdL+oyk19m+T8XZus90IIZzJe0jaXm5T365AzEAALoI9aauQ92JutOkrDuZs6cAgBz19vbG7NmzW77cTZs23RIRi1q+YAAAMjK10wEAANAMuooCAFAdEkUAQLZIFAEAqEZXXKMIAAAAAOgetCgCALJFiyIAANUgUQQAZItEEQCAapAoAgCyRaIIAEA1SBQBAFli1FMAAKrDYDYAAAAAgCFoUQQAZIsWRQAAqkGiCADIFokiAADVIFEEAGSLRBEAgGqQKAIAskWiCABANRjMBgAAAAAwBC2KAIAscXsMAACqQ6IIAMgWiSIAANUgUQQAZItEEQCAapAoAgCyRaIIAEA1GMwGAAAAADAELYoAgGzRoggAQDVIFAEAWWLUUwAAqkOiCADIFokiAADV4BpFAAAAAMAQtCgCALJFiyIAANUgUQQAZItEEQCAapAoAgCyRaIIAEA1SBQBALm6RtKcCpa7qYJlAgCQFXM2FgAAAABQj1FPAQAAAABDkCgCAAAAAIYgUQQAAAAADEGiCAAAAAAYgkQRAAAAADDE/wcL7cyLuZQQKwAAAABJRU5ErkJggg==\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_BN5=error(xdata5, popt5[0], popt5[1],popt5[2], popt5[3], popt5[4], recorte5.ravel(), inc=1)\n", + "popt5E, pcov5E = curve_fit(gauss2d, xdata5, recorte5.ravel(), p0=[3,2,2,1,1], sigma=Err_BN5)\n", + "estrella5E=gauss2d(xdata5, popt5E[0], popt5E[1],popt5E[2], popt5E[3], popt5E[4])\n", + "FWHM5E=FWHM_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(popt5E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 5 fotografÃa\")\n", + "plt.imshow(recorte5, plt.get_cmap('gray'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 5 a partir de la gaussiana con incertidumbre\")\n", + "plt.imshow(estrella5E.reshape(15, 15), plt.get_cmap('gray'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 6 con incertidumbre (blanco y negro)" + ] + }, + { + "cell_type": "code", + "execution_count": 823, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_BN6=error(xdata6, popt6[0], popt6[1],popt6[2], popt6[3], popt6[4], recorte6.ravel(), inc=1)\n", + "popt6E, pcov6E = curve_fit(gauss2d, xdata6, recorte6.ravel(), p0=[3,2,2,1,1],sigma=Err_BN6)\n", + "estrella6E=gauss2d(xdata6, popt6E[0], popt6E[1],popt6E[2], popt6E[3], popt6E[4])\n", + "FWHM6E=FWHM_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(popt6E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 6 fotografÃa\")\n", + "plt.imshow(recorte6, plt.get_cmap('gray'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 6 a partir de la gaussiana con incertidumbre\")\n", + "plt.imshow(estrella6E.reshape(10, 10), plt.get_cmap('gray'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 7 con incertidumbre (blanco y negro)" + ] + }, + { + "cell_type": "code", + "execution_count": 824, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_BN7=error(xdata7, popt7[0], popt7[1],popt7[2], popt7[3], popt7[4], recorte7.ravel(), inc=1)\n", + "popt7E, pcov7E = curve_fit(gauss2d, xdata7, recorte7.ravel(), p0=[2,1,1,1,1],sigma=Err_BN7)\n", + "estrella7E=gauss2d(xdata7, popt7E[0], popt7E[1],popt7E[2], popt7E[3], popt7E[4])\n", + "FWHM7E=FWHM_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(popt7E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 7 fotografÃa\")\n", + "plt.imshow(recorte7, plt.get_cmap('gray'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 7 a partir de la gaussiana con incertidumbre\")\n", + "plt.imshow(estrella7E.reshape(10, 10), plt.get_cmap('gray'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 8 con incertidumbre (blanco y negro)" + ] + }, + { + "cell_type": "code", + "execution_count": 825, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_BN8=error(xdata8, popt8[0], popt8[1],popt8[2], popt8[3], popt8[4], recorte8.ravel(), inc=1)\n", + "popt8E, pcov8E = curve_fit(gauss2d, xdata8, recorte8.ravel(), p0=[1,0,1,1,1],sigma=Err_BN8)\n", + "estrella8E=gauss2d(xdata8, popt8E[0], popt8E[1],popt8E[2], popt8E[3], popt8E[4])\n", + "FWHM8E=FWHM_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(popt8E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 8 fotografÃa\")\n", + "plt.imshow(recorte8, plt.get_cmap('gray'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 8 a partir de la gaussiana con incertidumbre\")\n", + "plt.imshow(estrella8E.reshape(20, 20), plt.get_cmap('gray'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 9 con incertidumbre (blanco y negro)" + ] + }, + { + "cell_type": "code", + "execution_count": 826, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_BN9=error(xdata9, popt9[0], popt9[1],popt9[2], popt9[3], popt9[4], recorte9.ravel(), inc=1)\n", + "popt9E, pcov9E = curve_fit(gauss2d, xdata9, recorte9.ravel(), p0=[1,12,0,1,1], sigma=Err_BN9)\n", + "estrella9E=gauss2d(xdata9, popt9E[0], popt9E[1],popt9E[2], popt9E[3], popt9E[4])\n", + "FWHM9E=FWHM_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(popt9E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 9 fotografÃa\")\n", + "plt.imshow(recorte9, plt.get_cmap('gray'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 9 a partir de la gaussiana con incertidumbre\")\n", + "plt.imshow(estrella9E.reshape(10, 10), plt.get_cmap('gray'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 10 con incertidumbre (blanco y negro)" + ] + }, + { + "cell_type": "code", + "execution_count": 827, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_BN10=error(xdata10, popt10[0], popt10[1],popt10[2], popt10[3], popt10[4], recorte10.ravel(), inc=1)\n", + "popt10E, pcov10E = curve_fit(gauss2d, xdata10, recorte10.ravel(), p0=[2,13,2,1,1], sigma=Err_BN10)\n", + "estrella10E=gauss2d(xdata10, popt10E[0], popt10E[1],popt10E[2], popt10E[3], popt10E[4])\n", + "FWHM10E=FWHM_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(popt10E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 10 fotografÃa\")\n", + "plt.imshow(recorte10, plt.get_cmap('gray'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 10 a partir de la gaussiana con incertidumbre\")\n", + "plt.imshow(estrella10E.reshape(10, 10), plt.get_cmap('gray'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Histograma con incertidumbres (blanco y negro)" + ] + }, + { + "cell_type": "code", + "execution_count": 828, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Datos de FWHM con incertidumbres de las estrellas a blanco y negro :\n", + "Desviación : 2.5072119906676873\n", + "Media : 4.216826728193483\n", + "Mediana : 3.1229418738608983\n" + ] + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "FWHM_I = np.array(FWHM_I)\n", + "sigmaBN_I = FWHM_I.std()\n", + "mediaBN_I = FWHM_I.mean()\n", + "medianaBN_I = np.median(FWHM_I)\n", + "print(\"Datos de FWHM con incertidumbres de las estrellas a blanco y negro :\")\n", + "print(\"Desviación :\", sigmaBN_I)\n", + "print(\"Media :\", mediaBN_I)\n", + "print(\"Mediana :\", medianaBN_I)\n", + "plt.hist(FWHM_I)\n", + "plt.xlabel('FHWM')\n", + "plt.ylabel('# de estrellas')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 1 con incertidumbre (Banda Rojo)" + ] + }, + { + "cell_type": "code", + "execution_count": 829, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_R1=error(xdata1, poptR1[0], poptR1[1],poptR1[2], poptR1[3], poptR1[4], recorteR1.ravel(), inc=1)\n", + "poptR1E, pcovR1E = curve_fit(gauss2d, xdata1, recorteR1.ravel(), p0=[2,3,2,1,1],sigma=Err_R1)\n", + "estrellaR1E=gauss2d(xdata1, poptR1E[0], poptR1E[1],poptR1E[2], poptR1E[3], poptR1E[4])\n", + "FWHMR1E=FWHMR_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptR1E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 1 fotografÃa (Banda Rojo)\")\n", + "plt.imshow(recorteR1, plt.get_cmap('Reds'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 1 a partir de la gaussiana con incertidumbre (Banda Rojo)\")\n", + "plt.imshow(estrellaR1E.reshape(15, 15), plt.get_cmap('Reds'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 2 con incertidumbre (Banda Rojo)" + ] + }, + { + "cell_type": "code", + "execution_count": 830, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_R2=error(xdata2, poptR2[0], poptR2[1],poptR2[2], poptR2[3], poptR2[4], recorteR2.ravel(), inc=1)\n", + "poptR2E, pcovR2E = curve_fit(gauss2d, xdata2, recorteR2.ravel(), p0=[1,0,1,1,1],sigma=Err_R2)\n", + "estrellaR2E=gauss2d(xdata2, poptR2E[0], poptR2E[1],poptR2E[2], poptR2E[3], poptR2E[4])\n", + "FWHMR2E=FWHMR_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptR2E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 2 fotografÃa (Banda Rojo)\")\n", + "plt.imshow(recorteR2, plt.get_cmap('Reds'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 2 a partir de la gaussiana con incertidumbre (Banda Rojo)\")\n", + "plt.imshow(estrellaR2E.reshape(35, 35), plt.get_cmap('Reds'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 3 con incertidumbre (Banda Rojo)" + ] + }, + { + "cell_type": "code", + "execution_count": 831, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_R3=error(xdata3, poptR3[0], poptR3[1],poptR3[2], poptR3[3], poptR3[4], recorteR3.ravel(), inc=1)\n", + "poptR3E, pcovR3E = curve_fit(gauss2d, xdata3, recorteR3.ravel(), p0=[8,9,4,1,1],sigma=Err_R3)\n", + "estrellaR3E=gauss2d(xdata3, poptR3E[0], poptR3E[1],poptR3E[2], poptR3E[3], poptR3E[4])\n", + "FWHMR3E=FWHMR_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptR3E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 3 fotografÃa (Banda Rojo)\")\n", + "plt.imshow(recorteR3, plt.get_cmap('Reds'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 3 a partir de la gaussiana con incertidumbre (Banda Rojo)\")\n", + "plt.imshow(estrellaR3E.reshape(15, 15), plt.get_cmap('Reds'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 4 con incertidumbre (Banda Rojo)" + ] + }, + { + "cell_type": "code", + "execution_count": 832, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_R4=error(xdata4, poptR4[0], poptR4[1],poptR4[2], poptR4[3], poptR4[4], recorteR4.ravel(), inc=1)\n", + "poptR4E, pcovR4E = curve_fit(gauss2d, xdata4, recorteR4.ravel(), p0=[1,0,1,1,1], sigma=Err_R4)\n", + "estrellaR4E=gauss2d(xdata4, poptR4E[0], poptR4E[1],poptR4E[2], poptR4E[3], poptR4E[4])\n", + "FWHMR4E=FWHMR_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptR4E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 4 fotografÃa (Banda Rojo)\")\n", + "plt.imshow(recorteR4, plt.get_cmap('Reds'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 4 a partir de la gaussiana con incertidumbre (Banda Rojo)\")\n", + "plt.imshow(estrellaR4E.reshape(15, 15), plt.get_cmap('Reds'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 5 con incertidumbre (Banda Rojo)" + ] + }, + { + "cell_type": "code", + "execution_count": 833, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_R5=error(xdata5, poptR5[0], poptR5[1],poptR5[2], poptR5[3], poptR5[4], recorteR5.ravel(), inc=1)\n", + "poptR5E, pcovR5E= curve_fit(gauss2d, xdata5, recorteR5.ravel(), p0=[3,3,1,1,1], sigma=Err_R5)\n", + "estrellaR5E=gauss2d(xdata5, poptR5E[0], poptR5E[1],poptR5E[2], poptR5E[3], poptR5E[4])\n", + "FWHMR5E=FWHMR_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptR5E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 5 fotografÃa (Banda Rojo)\")\n", + "plt.imshow(recorteR5, plt.get_cmap('Reds'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 5 a partir de la gaussiana con incertidumbre (Banda Rojo)\")\n", + "plt.imshow(estrellaR5E.reshape(15, 15), plt.get_cmap('Reds'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 6 con incertidumbre (Banda Rojo)" + ] + }, + { + "cell_type": "code", + "execution_count": 834, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_R6=error(xdata6, poptR6[0], poptR6[1],poptR6[2], poptR6[3], poptR6[4], recorteR6.ravel(), inc=1)\n", + "poptR6E, pcovR6E = curve_fit(gauss2d, xdata6, recorteR6.ravel(), p0=[2,2,1,1,1],sigma=Err_R6)\n", + "estrellaR6E=gauss2d(xdata6, poptR6E[0], poptR6E[1],poptR6E[2], poptR6E[3], poptR6E[4])\n", + "FWHMR6E=FWHMR_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptR6E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 6 fotografÃa (Banda Rojo)\")\n", + "plt.imshow(recorteR6, plt.get_cmap('Reds'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 6 a partir de la gaussiana con incertidumbre (Banda Rojo)\")\n", + "plt.imshow(estrellaR6E.reshape(10, 10), plt.get_cmap('Reds'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 7 con incertidumbre (Banda Rojo)" + ] + }, + { + "cell_type": "code", + "execution_count": 835, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_R7=error(xdata7, poptR7[0], poptR7[1],poptR7[2], poptR7[3], poptR7[4], recorteR7.ravel(), inc=1)\n", + "poptR7E, pcovR7E = curve_fit(gauss2d, xdata7, recorteR7.ravel(), p0=[2,2,1,1,1],sigma=Err_R7)\n", + "estrellaR7E=gauss2d(xdata7, poptR7E[0], poptR7E[1],poptR7E[2], poptR7E[3], poptR7E[4])\n", + "FWHMR7E=FWHMR_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptR7E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 7 fotografÃa (Banda Rojo)\")\n", + "plt.imshow(recorteR7, plt.get_cmap('Reds'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 7 a partir de la gaussiana con incertidumbre (Banda Rojo)\")\n", + "plt.imshow(estrellaR7E.reshape(10, 10), plt.get_cmap('Reds'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 8 con incertidumbre (Banda Rojo)" + ] + }, + { + "cell_type": "code", + "execution_count": 836, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_R8=error(xdata8, poptR8[0], poptR8[1],poptR8[2], poptR8[3], poptR8[4], recorteR8.ravel(), inc=1)\n", + "poptR8E, pcovR8E = curve_fit(gauss2d, xdata8, recorteR8.ravel(), p0=[1,0,1,1,1],sigma=Err_R8)\n", + "estrellaR8E=gauss2d(xdata8, poptR8E[0], poptR8E[1],poptR8E[2], poptR8E[3], poptR8E[4])\n", + "FWHMR8E=FWHMR_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptR8E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 8 fotografÃa (Banda Rojo)\")\n", + "plt.imshow(recorteR8, plt.get_cmap('Reds'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 8 a partir de la gaussiana con incertidumbre (Banda Rojo)\")\n", + "plt.imshow(estrellaR8E.reshape(20, 20), plt.get_cmap('Reds'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 9 con incertidumbre (Banda Rojo)" + ] + }, + { + "cell_type": "code", + "execution_count": 837, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_R9=error(xdata9, poptR9[0], poptR9[1],poptR9[2], poptR9[3], poptR9[4], recorteR9.ravel(), inc=1)\n", + "poptR9E, pcovR9E = curve_fit(gauss2d, xdata9, recorteR9.ravel(), p0=[4,7,3,1,1],sigma=Err_R9)\n", + "estrellaR9E=gauss2d(xdata9, poptR9E[0], poptR9E[1],poptR9E[2], poptR9E[3], poptR9E[4])\n", + "FWHMR9E=FWHMR_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptR9E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 9 fotografÃa (Banda Rojo)\")\n", + "plt.imshow(recorteR9, plt.get_cmap('Reds'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 9 a partir de la gaussiana con incertidumbre (Banda Rojo)\")\n", + "plt.imshow(estrellaR9E.reshape(10, 10), plt.get_cmap('Reds'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 10 con incertidumbre (Banda Rojo)" + ] + }, + { + "cell_type": "code", + "execution_count": 838, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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5rzE+exFw12w/BucA2uBquP32LrX8xbTuXbM2z7POW8tMG6PzDlrL5z7dgf1VxtgXaQO0P0Jrjbx799kTFvnsl1m4qxbdVcB/o3VpmJ0l8O20q5EHd9/TK8epW+ditt/+A+5A3UfreS3w68AzkzyEdsVttnVidF3zHYMXzVluvmV/hJFubtK0y4S7D9uFePXtaOfqtLFkL6O13NylO0dctcS6bz3fJJmdmPCiMcuau7/mPp/PUssseA6kfR/nzfk+9qqqJ42x3pfSAt8f7b6T2W7k8+2bi4H9koy+N1qnpcq6Dth9ZPnZuyHQtVi9uqoOoXUTPoKuN1pVfaqqfprWxfFrtDhnOyv8jmc/u9zY6XzmjF/sjBMT9GGh+pwP3AhsGjku9q6q+40ss9xjdbHjEBb5jlfoLmldZEfXd9HI87kXU5bz/2CpOPZmWq/Ig2g9AFYcawKX0bpyLxTHrvj4rdZj8cXAW9Nua3kRsDnd3C0j61oyju329T4sM46d+gQ2yf/IbQP2v0c7sGavAHyXNqZwMX8BvK77MSHtPqNHjrHqvWhXY69Ksh9tHMBi9dy5u5oyA+yUNnnA7BXC44CfTbsH1x602+R8dE4r6byqdev5D+APuzIfSOvaMTtT73eBA2cPqjGW/zDwirSJEfaj/bguZg/aPr+s287n0q4ijmMX2sn/MmBr2v1LF5ue/ou0K6sLtS6T5Mdog99nu/vsBVwNXNtdQf31MesGbV+8KMn+aeMJRqf1Xm7dt9N1x3knrWvHLd26Xpdkr+5Y/F/cfrZlaD9c90m7lcNOSX6p295/GFnmkbQuMdK64SRO020HPFfvRQseL+vK+X1u33o715OS/HjauM/X0nrtnL/CsrY796/QaDywP21c26wvAtekTbS1W9okQ/dPm2V1KXvRWm+uTBvD+apFlv0CraX9hd0570i272a7VFmnA0d13+t2c1kk+akkD+i+36tpF5K3pbXaH9l9xzfSjp9t3N5KvpdZy42d3gm8NsnBaR6YNs51nJigD8cCz03ymLQJ1vZL8sNVdTGti+sfJ9m7e+/eSRbr1v1dYP/MmUhpxIeB5yQ5JMnuzP8d/0Jaa/wP0WLaO+rVSXbpkrwjgL9ZYLnl/j84gUW6uOe2OVKup40TXnGs2cWWHwX+oNs3hzAyjp07dvxSVZ+mJaNHAyfTWn5f1v1fexStG/vcsa3QxrE/N8mDuwT99cDJ1YbP0f1O35XtxwHfzjQlsLOz7s4+/rZ7/aHAyUmupXXLfHHXBx1aP/n3pjXrP2WeMgHe2n3uxCTX0HbYj45Rn1cDh9KuVnyCdpAs5h20A/KptLEt19P1He/65D+PdnK8lHZQzZ1oaDFPpTXnX0Sb7OBV1SZQgtv+012e5LQxln8NbYKn84B/ok0KceNCK66qs2jjNb9A+xF6APDv41S6O+m/iPbj9D3awPiPL7L8TbTJAeZOLPWns8cFrUvQ71abRRLawP+n0bp4vYM249243kHrXnQGcBoj3/Fy676At9AClgfSAoPraD9Yn6cNpn/X3A9UG/NyBO2q8+W0q2dHVNUWgO5H89pqt9OR1g1bYKeG5+rmU8Anaa2z36bNfbBU18m/pgXnV9AmnJk9162krPnO/cv16m5959GSkltvUdcFx0fQxkSeR+tJ9E5aF8SlvIU25GcL7Xv85EILduf9X6AlJVfS9sk/cFtcslRZv0drKfxetz1/PfLePWgxztW0Lumf7bZxhnYR+SLad/FI5r/4vZLvZXa7lhs7vYkWb5zY1fdYYLelYoK+dDHGc2njW6+i7bvZVrVn0RKvs2j7/XhaS/ZC/oXW6HBJktvVu4vn3tItd07376g30yZT+y5tjOdx3DGXdPW+qCvreVX1tfkWXO7/g6o6jXYxbe5v1xndb+P3aEnmf6829vyOxpovpHUnvoQWP7975L0VH78j/h+3DQ/5WdrErVtotxd71nz7rcs3fo/Wsnwx7f/n6JjhpwHv7cbHLijbDyuQtpfk14Gjqmqlk15MVJK7Af8GPKTGn6hiqqWNFXtGVT16jGU/AhxbbSC/tC4csGGn+u3dNk60zBded/mpVeX9kjUIabeZu6Cqfnet6zJ0SU4G/qKq3r3kwtLAJHkc8Pyq+vm1rstqSfI+4Jyqes0Sy+1KazT6yWoTgC1oqm8grMlLm8L9B2lXBQ+mXdUbd0r63lWbRXLeyRTWsfvRruwtqap+see6SKsuTFd3IUmT03U//TqtZefptNu5LNhqKw1ZVZ1Ia0nfIaRNWnZf4NNLLdu1uo4V45vAaq5daDPGHUTrrvNBWlcArYEkH6NdSPgfa1wVaU3Z7VfaYd2X1oVyD9owmyd3Yy0lDd8lwKm0LsMTYxdiSdKgHbhh5/qd3TdOtMyjr91iF2JJkqaQLbCSpMGzBVaSJIHDiiRJkiRJU6KXFthN++xTBx6weekF74ia75Zck7ROLvf3vp9WwcyGpZeZBn1/F3fodn9L+9Z3zmfL5Zevk/8YmjYeeFrPNm3apw484IC1roakCTv1P0/fUlV3W+t6rDe9JLAHHrCZL32m5wm2bur5Diob1knv6hu+32/5q5Fc7j72fZWH7YZr+y1/1917Lf6hjxrr3tnSxAW7EGt9O/CAAzjl859Z62pImrDssfHba12H9WidZGmSpPVsxjZYSZKEY2AlSZIkSVPCFlhJ0qAldiGWJEmNLbCSpMGbmfBjKUk2J/nXJGclOTPJi+e8/9IklWRT9zxJ3pbknCRfTnLoHd9qSZI0ly2wkqTBW4MG2K3AS6vqtCR7Aacm+XRVnZVkM/A44Dsjyz8ROLh7/Cjw9u5fSZI0QbbASpIGrc1CnIk+llJVF1fVad3f1wBnA/t1b78ZeBlQIx85EnhfNScBG5Pcc5L7QZIkmcBKkrSoJAcCDwFOTnIkcGFVnTFnsf2A80eeX8BtCa8kSZqQsRLYJE9I8vVubM/L+66UJEmjMuEHsCnJKSOPo+ddb7In8BHgJbRuxa8Efr+HTdQ6Y+wkSf1Ycgxskg3AnwE/Tbui/KUkH6+qs/qunCRJ0MsY2C1Vddii60x2piWvx1XVR5M8ADgIOCOtG/L+wGlJHgZcCGwe+fj+3WvaARk7SVJ/xmmBfRhwTlWdW1U3AR+kjfWRJGlV9NACu/j6WoZ6LHB2Vb0JoKq+UlU/UFUHVtWBtMTk0Kq6BPg48KxuNuLDgauq6uJJbLumkrGTJPVknAR2rHE9SY6e7Yp12eWXT6p+kiSRZKKPMTwCeCbw6CSnd48nLbL8CcC5wDnAO4Dn3+GN1jRbMnbaLm7aYtwkSeOa2G10quoY4BiAwx7y4FpicUmSBquqPs8SjbVdK+zs3wW8oOdqaR3ZLm469CHGTZI0pnESWMf1SJLWzLjdfqUBMXaSpJ6M04X4S8DBSQ5KsgtwFG2sjyRJq2Jmwg+pZ8ZOktSTJVtgq2prkhcCnwI2AO+qqjN7r5kkSZ3xhq1Kw2DsJEn9GWsMbFWdQJugQpKkVRc7EWvKGDtJUj/sSSVJkiRJmgoTm4VYkqQ+OImTJEmaZQIrSRo8E1hJkgQmsJKkKTBjBitJknAMrCRJkiRpStgCK0kauDgLsSRJAvpKYANs6Dk3Ts+Nxzvt2m/5AFtv7H8dMxt6Ln8VGvFvuLb/dazGTSZ3uVO/5V93Vb/lb7ul3/KlBTiJk6T1orZtW42V9L+O1dBzrJ/ViGHVC1tgJUnDltW5xiRJkobPBFaSNHjmr5IkCZzESZIkSZI0JWyBlSQN3oxtsJIkCRNYSdLAOYmTJEmaZQIrSRo8J3GSJElgAitJmgLmr5IkCZzESZIkSZI0JWyBlSQNXmyDlSRJmMBKkgYuwIz5qyRJwgRWkjQFzF8lSRKYwEqSpoAJrCRJAidxkiRJkiRNCVtgJUmD5yROkiQJTGAlSVMg5q+SJAkTWEnSwAXHu0iSpMaYQJIkSZI0FWyBlSQNnj2IJUkSmMBKkqZAHAQrSZIwgZUkTQHTV0mSBCawkqSBCyawkiSpcRInSZIkSdJUsAVWkjRsiWNgJUkS0FcCu20bfP/qXoq+Vd/BzNab+i1/tey0c6/F1zVX9Fo+QJ33ld7XwZ039b6Kmfs+rNfy63uX9Fo+W2/ut3xpETPmr5JWQd2ytd8VXH9tv+UDdd2Vva+j9zgcyJ4bey2/7rRnr+WrP7bASpIGL2awkiQJE1hJ0sCFVbnYL0mSpoCTOEmSJEmSpoItsJKkYYstsJIkqTGBlSQNnrMQS5IksAuxJGkKJJN9LL2+bE7yr0nOSnJmkhd3r/+/JF9L8uUkf5tk48hnXpHknCRfT/L43naGJEk7MBNYSdLgpbsX7KQeY9gKvLSqDgEOB16Q5BDg08D9q+qBwH8Br+jqdwhwFHA/4AnAnyfZ0MOukCRph2YCK0nSHFV1cVWd1v19DXA2sF9VnVhVszeKPAnYv/v7SOCDVXVjVZ0HnAP0e/NnSZJ2QI6BlSQNWk+30dmU5JSR58dU1THzrj85EHgIcPKct34Z+FD39360hHbWBd1rkiRpgpZMYJNsBt4H3B0o2kn+rX1XTJIkAAIzk89gt1TVYUuuOtkT+Ajwkqq6euT136F1Mz5u0hXT9DN2kqT+jNMCOzsO6LQkewGnJvl0VZ3Vc90kSQLW5jY6SXamJa/HVdVHR15/DnAE8Jiqqu7lC4HNIx/fv3tNOyZjJ0nqyZJjYBcaB9R3xSRJaiY7gdM4kzilLXQscHZVvWnk9ScALwN+rqq+P/KRjwNHJdk1yUHAwcAXJ7obNDWMnSSpP8saA7vIOCBJktaTRwDPBL6S5PTutVcCbwN2BT7dJcInVdXzqurMJB8GzqK1vr2gqm5Z/WpraIydJGmyxk5gFxoHNPL+0cDRAAfsv+/EKihJ2rEFyCrPmV9Vn+9WPdcJi3zmdcDrequUps5isdN2cdPmzfN8WpI0n7FCgoXGAY2qqmOq6rCqOuxu++wzyTpKknZkWZP7wEp3yFKx03Zx0ybjJkka1zizEM87DkiSpNVizqlpYuwkSf0ZpwV2dhzQo5Oc3j2e1HO9JEmSppWxkyT1ZMkW2EXGAUmStCrs9qtpYuwkSf1Z1izEkiStBfNXSZIEJrCSpIELMGMGK0mSMIGVJA1dbIGVJEnNKt9ZT5IkSZKklbEFVpI0eE7iJEmSwARWkjQFzF8lSRL0lcBWwbZtvRR9q9327Lf8m67vt3yArTf3v46bb+y1+Prnj/RaPsCFf/Kh3tex95137X0de73mFb2Wnztv6rV8quf/09ICggmsJKi+Y0uA66/ttfhtp5zYa/kAt/zt8b2vY2bXnXtfR5789F7Ln7n/j/davvpjC6wkadgSMmMGK0mSnMRJkiRJkjQlbIGVJA2eXYglSRKYwEqSpsCMGawkScIEVpI0cE7iJEmSZpnASpIGz/vASpIkcBInSZIkSdKUsAVWkjRssQuxJElqTGAlSYNnF2JJkgQmsJKkKWD+KkmSwDGwkiRJkqQpYQusJGnQ2m10bIKVJEkmsJKkoQvE/kKSJAkTWEnS4MUWWEmSBJjASpKmwYwJrCRJchInSZIkSdKUsAVWkjR8diGWJEmYwEqShi7OQixJkhoTWEnS8DkGVpIkYQIrSRq82IVYkiQBTuIkSZIkSZoStsBKkgYtgdiFWJIkYQIrSZoGdiGWJEmYwEqSpoAtsJIkCfpKYDMDu+zaS9G3rmLnfsuv667qtXyAuvH7va+D71/da/HbvvTFXssHeP2XL+p9HTuvQuvOm0/6bK/l5/G/2Gv50pqyBVZSbet/Fdde0Wv5W4//cK/lA7z43Sf1vo59dtrQ+zpeveee/a7g3g/qt3z1xkmcJEmSJElTwS7EkqRhS7wPrCRJAkxgJUlTIHYhliRJ2IVYkjQNZjLZxxKSbE7yr0nOSnJmkhd3r981yaeTfKP79y7d60nytiTnJPlykkN73iOSJO2QTGAlSbq9rcBLq+oQ4HDgBUkOAV4O/HNVHQz8c/cc4InAwd3jaODtq19lSZLWPxNYSdKwhTYOdpKPJVTVxVV1Wvf3NcDZwH7AkcB7u8XeC/x89/eRwPuqOQnYmOSek90RkiTJMbCSpMHLGl5uTXIg8BDgZODuVXVx99YlwN27v/cDzh/52AXdaxcjSZImxgRWkjR8k5/EaVOSU0aeH1NVx9x+tdkT+Ajwkqq6enQyqaqqJDXpikmSpIWNncAm2QCcAlxYVUf0VyVJkkYkZPK30dlSVYctvtrsTEtej6uqj3YvfzfJPavq4q6L8KXd6xcCm0c+vn/3mnZgxk6SNHnL6ZT1YtoYIEmS1rW0ptZjgbOr6k0jb30ceHb397OBvxt5/VndbMSHA1eNdDXWjsvYSZImbKwENsn+wM8A7+y3OpIkzWOVJ3ECHgE8E3h0ktO7x5OAPwJ+Osk3gMd2zwFOAM4FzgHeATx/4vtAU8XYSZL6MW4X4rcALwP26q8qkiQtYPJdiBdVVZ+nzX88n8fMs3wBL+i1Upo2b8HYSZImbskW2CRHAJdW1alLLHd0klOSnHLZ5ZdPrIKSpB1bazTNRB9Sn8aJnbaLm7YYN0nSuMbpQvwI4OeSfAv4IK071fvnLlRVx1TVYVV12N322WfC1ZQk7dBmMtmH1K8lY6ft4qZNxk2SNK4lE9iqekVV7V9VBwJHAf9SVc/ovWaSJElTyNhJkvrjfWAlSQM39sRLkiRpnVtWAltVnwE+00tNJElagONWNa2MnSRpsmyBlSQNW3DcqiRJAkxgJUlTwBZYSZIE481CLEmSJEnSmrMFVpI0fHYhliRJmMBKkoYuzkIsSZIaE1hJ0uDFFlhJkkRvCWzB1pv7KXp2DVW9ls/NN/RbPkBt630V2XNj7+tYD27u+3gCcs/9e15B30PaTSAkSetcz+fSmV36bzvaY6b/KW723mkVptHZsKHf8u3ZM7VsgZUkDZ+BhiRJwgRWkjR03gdWkiR1TGAlSYPnfWAlSRKYwEqSBi+2wEqSJABWYQS2JEmSJEl3nC2wkqThswuxJEnCBFaSNHTBBFaSJAEmsJKkaWACK0mSMIGVJA1eYMYpGyRJkpM4SZIkSZKmhC2wkqThswuxJEnCBFaSNHRO4iRJkjomsJKk4TOBlSRJmMBKkgbPSZwkSVJjRCBJkiRJmgq2wEqShs8uxJIkCRNYSdLQOYmTJEnqmMBKkobPBFaSJGECK0kaPCdxkiRJjRGBJEmSJGkq2AIrSRo+uxBLkiRMYCVJQ+ckTpIkqWMCK0kaPhNYSZKEY2AlSZIkSVOinxbYKrhlay9F3+rG6/otfxVk1937X8nOu/Za/MxjHtdr+QBvOO+y3texyz029r4O9t3cb/l737Xf8jds6Ld8aQEhxFmIJaX/34HsubHX8mee/LReywf4v3usQny5yy69ryI/8+R+V7DbXv2Wr97YhViSNHx2IZYkSZjASpKGzkmcJElSxwRWkjR8JrCSJAkncZIk6XaSvCvJpUm+OvLag5OclOT0JKckeVj3epK8Lck5Sb6c5NC1q7kkSeubCawkaeACMzOTfSztPcAT5rz2BuDVVfVg4Pe75wBPBA7uHkcDb5/EVkuSpNszgZUkDV8y2ccSqupzwBVzXwb27v6+M3BR9/eRwPuqOQnYmOSeE9pySZI0wjGwkqRh62cSp01JThl5fkxVHbPEZ14CfCrJG2kXgB/evb4fcP7Ichd0r108obpKkqSOCawkafgmn8BuqarDlvmZXwd+s6o+kuQpwLHAYyddMUmStLCxuhAn2Zjk+CRfS3J2kh/ru2KSJA3Ms4GPdn//DfCw7u8Lgc0jy+3fvaYdmLGTJPVj3DGwbwU+WVU/DDwIOLu/KkmSNGpNJnGaz0XAI7u/Hw18o/v748CzutmIDweuqiq7D8vYSZJ6sGQX4iR3Bn4SeA5AVd0E3NRvtSRJGrHK94FN8gHgUbSxshcArwJ+DXhrkp2AG2gzDgOcADwJOAf4PvDcVa2sBsfYSZL6M84Y2IOAy4B3J3kQcCrw4qq6rteaSZIEfU3itKiqeuoCb/23eZYt4AX91khTxthJknoyTj+qnYBDgbdX1UOA64CXz10oydHdjd1PuezyuXcekCRppQbThVga15Kx03Zx05bL16KOkjSVxjmLXwBcUFUnd8+Pp/0ob6eqjqmqw6rqsLvtc9dJ1lGSJGmaLBk7bRc3bdpn1SsoSdNqyQS2qi4Bzk9y3+6lxwBn9VorSZJGJZN9SD0ydpKk/ox7H9jfAI5LsgtwLk5QIUlaTSadmj7GTpLUg7ES2Ko6HVjuDd8lSbrj1mASJ+mOMnaSpH44k4UkSZIkaSqM24VYkqQ1EmcOliRJgAmsJGka2IVYkiRhAitJmgYmsJIkCRNYSdLQBYhdiCVJkpM4SZIkSZKmhC2wkqSBC8zYhViSJPWVwM7MwG579lL0rbbd0m/5q2HrTf2vY+ddey0+h/5kr+UD7PGSvXpfB7v3fLwCMwcf2u8Kalu/5duFU2vJ40/a4WUVZiOvO/UbD8w8+JG9lg/AfXqON2B15iXYfe9+y991937LV29sgZUkDZ+TOEmSJExgJUlDF+8DK0mSGiMCSZIkSdJUsAVWkjR8diGWJEmYwEqSpoGTOEmSJExgJUnTwBZYSZKECawkaeicxEmSJHWMCCRJkiRJU8EWWEnS8NmFWJIkYQIrSZoGTuIkSZIwgZUkDV0CM7bASpIkx8BKkiRJkqaELbCSpOGzC7EkScIEVpI0DZzESZIkYQIrSRq82AIrSZIAE1hJ0tAFJ3GSJEmAkzhJkiRJkqaELbCSpOFzDKwkScIEVpI0DRwDK0mSMIGVJA1d4hhYSZIEmMBKkqaBLbCSJAkncZIkSZIkTQlbYCVJw+ckTpIkCRNYSdLgxS7EkiQJ6CuBTWCnXXop+lY33dBv+bvt1W/5AFtv7n8dN9/Ya/HZ/c69lg+QBz+q93WsCzvv2m/5MyYQWiPBSZwkrYps6Ldtp3bbu9fyAbjTnv2vYzX0fOEy9uyZWrbASpKGzxZYSZKEkzhJknQ7Sd6V5NIkX53z+m8k+VqSM5O8YeT1VyQ5J8nXkzx+9WssSdKOwRZYSdLwrX5Xr/cAfwq877Yq5KeAI4EHVdWNSX6ge/0Q4CjgfsC+wD8luU9V3bLalZYkab0zgZUkDVxWfQx2VX0uyYFzXv514I+q6sZumUu7148EPti9fl6Sc4CHAV9YrfpKkrSjsAuxJGnYQmuBneRjZe4D/ESSk5N8NslDu9f3A84fWe6C7jVJkjRhtsBKknZEm5KcMvL8mKo6ZonP7ATcFTgceCjw4SQ/2FcFJUnS7ZnASpKGb/KzEG+pqsOW+ZkLgI9WVQFfTLIN2ARcCGweWW7/7jVJkjRhdiGWJA3chLsPr7wL8ceAnwJIch9gF2AL8HHgqCS7JjkIOBj44h3fbkmSNNdYLbBJfhP4VaCArwDPraob+qyYJEm3WuVJnJJ8AHgUravxBcCrgHcB7+purXMT8OyuNfbMJB8GzgK2Ai9wBmIZO0lSP5ZMYJPsB7wIOKSqru9O0kfRbjEgSVK/ZidxWkVV9dQF3nrGAsu/DnhdfzXSNDF2kqT+jHtJeydgtyQ7AbsDF/VXJUmSpKln7CRJPVgyga2qC4E3At8BLgauqqoT5y6X5OgkpyQ55bItl0++ppKkHVTaJE6TfEg9Gid2Mm6SpJVZ8iye5C60m7QfBOwL7JHkdl2oquqYqjqsqg6726Z9Jl9TSdKOaxiTOEljGSd2Mm6SpJUZ5zL0Y4HzquqyqroZ+Cjw8H6rJUnSCFtgNV2MnSSpJ+PMQvwd4PAkuwPXA48BTln8I5IkTUgCM7aaaqoYO0lST8YZA3sycDxwGm0a+BngmJ7rJUmSNJWMnSSpP2PdB7aqXkW7B54kSavPbr+aMsZOktSPsRJYSZLWlBMvSZIkTGAlSYMXW2AlSRJgAitJmgKxBVaSJDHebXQkSZIkSVpztsBKkoYt2IVYkiQBJrCSpMFzDKwkSWr6SWC3Fdx0Qy9F32rrTf2Wf6c9+y1/tXz/6n7Lv/G6fssH2GmX/tcxs6H/dVT1W/5qbIO0VmYcAytp+q3KeP4YD2h9swVWkjR8tsBKkiScxEmSJEmSNCVsgZUkDVsAb6MjSZIwgZUkDZ6TOEmSpMYEVpI0fLbASpIkHAMrSZIkSZoStsBKkobPLsSSJAkTWEnS0CXeB1aSJAEmsJKkaWALrCRJwgRWkjQNnMRJkiThJE6SJEmSpClhC6wkaeC8D6wkSWpMYCVJw2cXYkmShAmsJGnogi2wkiQJMIGVJA1eYMYEVpIkOYmTJEmSJGlK2AIrSRq8OAZWkiRhAitJmgaOgZUkSZjASpKGLjgLsSRJAkxgJUmD531gJUlSY0QgSZIkSZoKtsBKkobPLsSSJAkTWEnSNPA+sJIkCRNYSdLQJbbASpIkoKcE9tQzvrxlZp/9vr2Mj2wCtvRRl1XkNgzHetiOIW7Dvda6ApK0Hp36n6dvyR4blxM3wTDPE8vlNgzDetgGGOZ2GDv1oJcEtqrutpzlk5xSVYf1UZfV4jYMx3rYjvWwDdJEOQux1rHlxk2wPs4TbsMwrIdtgPWzHVqaEYEkafhmuxFP6rHk6vKuJJcm+eo87700SSXZ1D1PkrclOSfJl5Mc2sMekCRJmMBKkqZCJvxY0nuAJ9yuFslm4HHAd0ZefiJwcPc4Gnj78rZNkiSNaygJ7DFrXYEJcBuGYz1sx3rYBmlCJtz6OkYLbFV9DrhinrfeDLwMqJHXjgTeV81JwMYk95zElkuLWA/nCbdhGNbDNsD62Q4tYRAJbFVN/QHnNgzHetiO9bAN0nqT5Ejgwqo6Y85b+wHnjzy/oHtN6s16OE+4DcOwHrYB1s92aGneRkeSNHyTv43OpiSnjDw/ZrHgJ8nuwCtp3YclSdIaMYGVJE2BiSewW5Y5W+W9gYOAM9KS6f2B05I8DLgQ2Dyy7P7da5IkacLWtAtxkick+Xo3c+PL17IuK5Vkc5J/TXJWkjOTvHit67RSSTYk+c8k/7DWdVmJJBuTHJ/ka0nOTvJja12n5Urym91x9NUkH0hyp7Wuk7TmwqqPgZ2rqr5SVT9QVQdW1YG0bsKHVtUlwMeBZ3WzER8OXFVVF09yF0izjJ2GY9rjJjB20nRaswQ2yQbgz2izNx4CPDXJIWtVnztgK/DSqjoEOBx4wZRuB8CLgbPXuhJ3wFuBT1bVDwMPYsq2Jcl+wIuAw6rq/sAG4Ki1rZU0EKs8CXGSDwBfAO6b5IIkv7LI4icA5wLnAO8Anr/czZPGYew0ONMeN4Gxk6bQWrbAPgw4p6rOraqbgA/SZnKcKlV1cVWd1v19De0//tRN3pFkf+BngHeudV1WIsmdgZ8EjgWoqpuq6so1rdTK7ATslmQnYHfgojWuj7RDqqqnVtU9q2rnqtq/qo6d8/6BVbWl+7uq6gVVde+qekBVnTJ/qdIdZuw0ENMeN4Gxk6bXWiaw627WxiQHAg8BTl7jqqzEW2i3hti2xvVYqYOAy4B3d9153plkj7Wu1HJU1YXAG2n3l7yY1g3xxLWtlTQUq34fWGmIjJ2G4y1Md9wExk6aUoO4jc56kGRP4CPAS6rq6rWuz3IkOQK4tKpOXeu63AE7AYcCb6+qhwDXAVM1NijJXWhX0g8C9gX2SPKMta2VNASrfx9YSf2b1thpncRNYOykKbWWCey6mbUxyc60H+Djquqja12fFXgE8HNJvkXrjvToJO9f2yot2wXABVU1ewX3eNqP8jR5LHBeVV1WVTcDHwUevsZ1kobBBFYCY6ehWA9xExg7aUqtZQL7JeDgJAcl2YU24Prja1ifFUm7n8KxwNlV9aa1rs9KVNUrujFeB9K+h3+pqqm6etXNBHp+kvt2Lz0GOGsNq7QS3wEOT7J7d1w9himbTEHqj12IJYydBmE9xE1g7KTptWb3ga2qrUleCHyKNmPYu6rqzLWqzx3wCOCZwFeSnN699sqqOmHtqrTD+g3guO6kfi7w3DWuz7JU1clJjgdOo83Q+J/AMWtbK0nSUBg7qQfGTpo6qaq1roMkSQs67EEPqC+d+HcTLXPmHvc+taoOm2ihkiSpd2vWAitJ0vjs9itJkkxgJUlD58RLkiSp4210JEmSJElTwRZYSdLw2QIrSZIwgZUkTQUTWEmSZAIrSZoCsQVWkiRhAitJmgYmsJIkCSdxkiRJkiRNCVtgJUkDFxwDK0mSwARWkjQN7EIsSZIwgZUkDV0wgZUkSYAJrCRpKpjASpIkJ3GSJEmSJE0JW2AlScNnF2JJkoQJrCRpGpi/SpIkTGAlSYPnbXQkSVJjAitJGj67EEuSJJzESZIkSZI0JWyBlSQNm/eBlSRJHRNYSdIUMIGVJEkmsJKkaWALrCRJwjGwkiRJkqQpYQusJGngYgusJEkCTGAlSVPBBFaSJJnASpKmgS2wkiQJSFWtdR0kSVpQkk8CmyZc7JaqesKEy5QkST0zgZUkSZIkTQVnIZYkSZIkTQUTWEmSJEnSVDCBlSRJkiRNBRNYSZIkSdJUMIGVJEmSJE2F/w9NAQihRM8aFAAAAABJRU5ErkJggg==\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_R10=error(xdata10, poptR10[0], poptR10[1],poptR10[2], poptR10[3], poptR10[4], recorteR10.ravel(), inc=1)\n", + "poptR10E, pcovR10E = curve_fit(gauss2d, xdata10, recorteR10.ravel(), p0=[2,2,1,1,1],sigma=Err_R10)\n", + "estrellaR10E=gauss2d(xdata10, poptR10E[0], poptR10E[1],poptR10E[2], poptR10E[3], poptR10E[4])\n", + "FWHMR10E=FWHMR_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptR10E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 10 fotografÃa (Banda Rojo)\")\n", + "plt.imshow(recorteR10, plt.get_cmap('Reds'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 10 a partir de la gaussiana con incertidumbre (Banda Rojo)\")\n", + "plt.imshow(estrellaR10E.reshape(10, 10), plt.get_cmap('Reds'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Histograma con incertidumbres (Banda Rojo)" + ] + }, + { + "cell_type": "code", + "execution_count": 839, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Datos de FWHM con incertidumbres de las estrellas para la Banda rojo :\n", + "Desviación : 2.344334810725805\n", + "Media : 4.008532518694751\n", + "Mediana : 2.9196546806439647\n" + ] + }, + { + "data": { + "image/png": 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NOpRWtD8FzkvydeBQ4G8nG2f6DP/CuRC4HvgvBt0xFZfjT1qS84FrgIOT3JHkDOAc4PlJvsHgr59zJpLNpQokqU0r8QhektSBBS9JjbLgJalRFrwkNcqCl6RGWfDabSR5aM6ptTckWZfkmB1X2kxybpKXJjk5yb/O2X5Wktvn3H9xkkuGtzcn+dIO+7lh7gqD0nKz4LU7eaCqDp3ztXme53+ZwYql2xwB3JvkV4f3jxw+Z5u9khwIkOTXlyq0tFgWvLQLVbWFQaE/dbhpfwZLZGy7RP9I4Oo5P3IB8IfD26cC5y9HTmlXLHjtTh4zZ3rm4jnbf2vu1A1w0pzHrgaOHC5l8A3gK8P7qxmsHf/VOc/9BPCS4e0XA5/q6z9E6mL1pANIy+iBqjp0J9u/VFUnbruT5Nw5j32ZwZH6KgaXo/8H8BYGy1TfWlU/nfPc7wP/l+QUBuu0/GRJ00sL5BG8NNrVDAr+SOCa4YfM7AEcw/bz79t8DHg3Ts9oCljw0mi3MFj//Gjga8NtNwB/zPbz79tcDLwNuHw5wkmjWPDSCMMPa7gW+P5wHXQYTNU8hZ0cwVfVfVX11qp6cBljSjvlapKS1CiP4CWpURa8JDXKgpekRlnwktQoC16SGmXBS1KjLHhJatT/A6zaxXqA9dpDAAAAAElFTkSuQmCC\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "FWHMR_I = np.array(FWHMR_I)\n", + "sigmaR_I = FWHMR_I.std()\n", + "mediaR_I = FWHMR_I.mean()\n", + "medianaR_I = np.median(FWHMR_I)\n", + "print(\"Datos de FWHM con incertidumbres de las estrellas para la Banda rojo :\")\n", + "print(\"Desviación :\", sigmaR_I)\n", + "print(\"Media :\", mediaR_I)\n", + "print(\"Mediana :\", medianaR_I)\n", + "plt.hist(FWHMR_I)\n", + "plt.xlabel('FHWM')\n", + "plt.ylabel('# de estrellas')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 1 con incertidumbre (Banda Verde)" + ] + }, + { + "cell_type": "code", + "execution_count": 840, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_G1=error(xdata1, poptG1[0], poptG1[1],poptG1[2], poptG1[3], poptG1[4], recorteG1.ravel(), inc=1)\n", + "poptG1E, pcovG1E = curve_fit(gauss2d, xdata1, recorteG1.ravel(), p0=[1,12,4,1,1],sigma=Err_G1)\n", + "estrellaG1E=gauss2d(xdata1, poptG1E[0], poptG1E[1],poptG1E[2], poptG1E[3], poptG1E[4])\n", + "FWHMG1E=FWHMG_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptG1E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 1 fotografÃa (Banda Verde)\")\n", + "plt.imshow(recorteG1, plt.get_cmap('Greens'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 1 a partir de la gaussiana con incertidumbre (Banda Verde)\")\n", + "plt.imshow(estrellaG1E.reshape(15, 15), plt.get_cmap('Greens'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 2 con incertidumbre (Banda Verde)" + ] + }, + { + "cell_type": "code", + "execution_count": 841, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_G2=error(xdata2, poptG2[0], poptG2[1],poptG2[2], poptG2[3], poptG2[4], recorteG2.ravel(), inc=1)\n", + "poptG2E, pcovG2E = curve_fit(gauss2d, xdata2, recorteG2.ravel(), p0=[1,0,1,1,1],sigma=Err_G2)\n", + "estrellaG2E=gauss2d(xdata2, poptG2E[0], poptG2E[1],poptG2E[2], poptG2E[3], poptG2E[4])\n", + "FWHMG2E=FWHMG_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptG2E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 2 fotografÃa (Banda Verde)\")\n", + "plt.imshow(recorteG2, plt.get_cmap('Greens'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 2 a partir de la gaussiana con incertidumbre (Banda Verde)\")\n", + "plt.imshow(estrellaG2E.reshape(35, 35), plt.get_cmap('Greens'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 3 con incertidumbre (Banda Verde)" + ] + }, + { + "cell_type": "code", + "execution_count": 842, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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xLTn+P1OqML1d6eziTEmPNxnfKklzCt1vpHT2sNXYpdQycbTSProqImpfts0cZ8X9vkobXuNVjGu50tmzgcK6to6I3QvLvETprO4To8QKVAvdkittE/29Pkdp0JMFed1nNLHu+u/2B8axrvp90ozRymzwW5N/D4vxLVdqUS3u880jdV9sKHdP/YbSiKfb59/mK9V432xQN6mLaax1/UGpxbG2fLFyrIj4VUQsUqqEf0upZVUR8WREnBIRL1C6fOl/2z5whNha+YxrxnPsLZf0ggbzNqjXacPjplOWS5rlka8RXi7pw3XHxYyIKHbVrT/uxjoOt8n11Zpivaf+M+5XSp7KqP87XKvUQFFTjHc8fwfLUohueAIoIu5Vag1+S57USn2zpv5veIZSnb9mXMdvRNyn1O36SKUuybXGpGbqnsV9tlqpNX60uuyP6/bplhFRvP3PSyTdPMp73zSTW9t/6eGLrh9V2rFD+fXv1fiLouYLkj7sfGG47dlubtj/rZS6PDyeD+CGt71xumD6YNub255q+0ilA/fHTWxHSv3632F7z/wl/xFJ1+c/Dmnj9zna8v8l6aW2D8utlydow7Mkpd5rg7LPSHrM6WL9M8dY/kql6xxGZHtLpX75tdGZt1L641ktaYrt9yt1o2jGL3LZ9+TP5W1Kra2txi6l5Pb1StcPXVCYPt7j7NIc11yn62bWn1GONILc1ZL+zfbWToOs7Gq7uN9eo/TFCWw6GFCq0jbR3+utlC6Zecr2n0ga876Mkv5PbqnZXekautq1sq2sq5n9Npr/Urp13NtyneA92rBO8AVJp+dY5TSgzF82sd5pkjZTruA6DVJUP6BP0aWSTrI9JydT/zSOdd2c38OeTuNtnFWbYXua7b+x/bxId3B4QvmYcxoQ6YU5oX9cqRfAkDbWyudSLNts/ek7knawfbLTAFJb2d43z7tY0j/nY35AqStqR+4BW5PrGt9VOgm1Tf57qCVdX5L0Ltv7OtnC9pudrhtupOGxmhOqpZI+kD+zV2k48ZOk3yr1unuz7alKXWc3G2FV43Gk7d1yMvhBSZdF49sSNf13EBHPKV07PVpddq6kg7RhXXa89c2ayyQdavtVTmPJfFAb5nytHL8XSDpRqYv1Rfl9NVP3XC/vy8uVBpaa4XQt7TGFRb4j6UVOg2FNzY9X2H5JYZkx67JVT25rI6zVHt/M018h6XrbTykNFnRSRNyT550l6QKn5u76EbhqPp3LXW37SaWBivZtsGzRB5QGPXhc6cfh8lGWdY7lIaUv55OUbpVzYxPbUUR8X9L/UTpzuUrpDPLhhUXOUuF9jrZ8RKyR9JdK1/k8rHSdwVKlszHteK/1zpa0udLZsOuUBkoYzYWSDrG9eWHajrXPXalLwyylrgtSGjDge0pffPcpXbjeVFeY/AX0NqXrBB5R6v9ffG/jjb12Nu7nStc8XFGYNd7j7EtK7+1mSTdq431+tIYHI3hU6cuteKuKI7Tx4AlAtfV14IFOmEy/1/+oNNDLk0rf240GdSr6sVLrzrWSPhERV5dY11kae781VKgTfFSpTrBAabyI2vxvSvr/JV3i1KXxN0rXIY+13ieVEuVLlX6j/lob/ibW+5JSxfkWpcGArlQ6+Tw41roiDWT5QaWE4m5JG4ycrNT6dG+O/10arj8syGWeUjrZ/fmI+OEIsbXyudQ0fezl9/kGpaTuwfxeXptnf0iprnaLpFuV6gUfGkccrTpKqUXzTqW/iZNzrEuVTuJ/VukzWaZUlxrNvyol6I+5MEp4wV8r/T0/opTcXVibkXvtvVvpbiIrlVpyRxywaRz+XWmMmAeV7pTxnkYLtvB38EWlfVf0V4W67K+U/s4+kOedrXHWNwux3abUUPU1pTr/o9pw37Ry/H5Dqa59bU5qa8aqe9Y7Uan79INK+/orhbifVDpJdbhSL4QHlfZxbRTwHZRylG+NFqhjg0sLAclp2PsVkv6mwZd619n+iKSHIuLsXsdSRU43Dz8qIsZd0QEmKg9MDy2a3/4Vn3fXDRGxcOwFgXJsz5f0O0lTYxz3Pp+McuvsFyJi5zEXBiYg2z9TupPITb2OpYps/5vS9b6fH225St9EGe1j+01Ktzd4RqmLjLXhrXV6KiLO6HUMVRYR/ynpP3sdB9BWdCMGNlm5t9ZrlVpvt1dqufvmqIWACSwi9h97KTQSEac0sxwdsFDzSqUR+dYodX85LNJ9WgFg4urygFK259n+oe3bnUb3Palu/im2I18DV7t/4WdsL7N9i5u/Dycw2Vmpi+ajSt2S71C6rhQAGqLlFpKkiDhLY9zAHgAmnO633K6TdEpE3JgHSrnB9jURcbvteUrXC91fWP5gpev4FihdO3aOmrsmFJNAHpOB7gcjiHQLmlf0Og4A1ULLLQCguro8oFRErKoNJJQHv7hDw/c1/JTSbciKg1ksknRhJNcp3adwtME2AABAi0huAQDY0IDtpYXH4pEWyoMB7aU02u8iSSsjov7+e3O04WjtKzScDAMAgDbqarfkbQdmxbyd5o29YCNt6Ljjkvl8tHSv9I3XUobbsCPKvot29KGaGON0l4tiKEa6/d04Iyg5Ynl/X3+58i5X/r5779eaNWvoVofuszrVLXnNWKMlO91f+xtKt8FYJ+kMjX7PTqAlAwMDsfP8nXodBoA2ou7UOV1NbuftNE9X/2zU++6OqmwlXJKm9k0rVX5trC0dg0onM+U/tsGG96RuTl8bGv3Lnihox4mGKJmc/nGw/Jhbzw2OdjvhsW017Xnlyk8tV37/fV9VqjxQSg+qBranKiW2F0XE5bZfKmkXSTc7JdtzJd1oex+l+y8Wz+rOzdOApuw8fyf97Pr627QCqDLqTp3DgFIAgOrq625265S9nivpjoj4pCRFxK2Stissc6+khRGxxvYVkk60fYnSQFKPR8SqrgYNAMAkQXILAEDz9pd0lKRbbf86TzsjIq5ssPyVkg6RtEzS05Le0fEIAQCYpEhuAQDV1eVbAUXETzVGZ+iImF94HpJO6HBYAABAJUdLtn2Q7bvyzelPa1dQAACMyR16AB1E3QkAOqflllvb/ZI+J+kNSrc2+JXtKyLi9nYFBwBAY5Y70HI7MUZyx6aIuhMAdFaZltt9JC2LiHsi4jlJlyjdrB4AgK6w3fYH0EHUnQCgg8okt03dmN72YttLbS99eM3DJTYHAABQaeOuO61evaZrwQFA1ZW/WekYImJJRCyMiIXbDmzb6c0BACYRu/0PoNeKdafZswd6HQ4AVEaZ0ZK5MT0AoGcsqa8D2ehg29cIrEfdCQA6qEzL7a8kLbC9i+1pkg6XdEV7wgIAYAzmmltUDnUnAOiglltuI2Kd7RMlXSWpX9J5EXFb2yIDAGAMJKOoEupOANBZZbolKyKulHRlm2IBAADYpFF3AoDOKZXcAgDQO3QjBgAAw7qa3Pa5X1tM3arl8s8O/rF0DGtjbel1lNXn/lLlI6J0DFa5CmF/X/lDp6/kYN1DGiodw+DQulLl+0t+llL597FuqNwxXfbvaijKfw5Aq8htAQBADS23AIBKsrjmFgAADCO5BQBUk0luAQDAsHL9QgEAAAAAmABouQUAVFbZ8QMAAMCmg+QWAFBZdEsGAAA1JLcAgMoitwUAADVccwsAAAAAqDxabgEAlWRZfTTdAgCAjOQWAFBZXHMLAABqSG4BANXEfW4BAEAByS0AoLLIbQEAQA0DSgEAAAAAKo+WWwBAJVl0SwYAAMNIbgEAlUVyCwAAakhuAQAVZZJbAACwHsktAKCaGC0ZAAAUdDW5DQ1p7dBzLZe3yldiIobKlVeUjmFtrCtVvh2VuT73lyo/OFTuPUhSuNx4ZoMxWD6GksdDO47JaX3TSpUv+1n2lyzfjn0AAAAAlEXLLQCgsmi4BQAANSS3AIBKYrRkAABQxH1uAQCVZbvtjzG2N8/2D23fbvs22yfl6R+3faftW2x/0/bMQpnTbS+zfZftN3V2jwAAMHmR3AIAKqvPbvtjDOsknRIRu0naT9IJtneTdI2kPSLiZZJ+K+l0ScrzDpe0u6SDJH3eLnmhOwAAGFHLyW2js9cAAGyqImJVRNyYnz8p6Q5JcyLi6oj1owVeJ2lufr5I0iUR8WxE/E7SMkn7dDtuTAzUnQCgs8pcc1s7e32j7a0k3WD7moi4vU2xAQDQmHs7oJTt+ZL2knR93azjJH09P5+jlOzWrMjTMDlRdwKADmo5uY2IVZJW5edP2r5D6QebL2gAQMdZY18j26IB20sLr5dExJINtm1vKekbkk6OiCcK09+nlMBc1InAUG3UnQCgs9oyWvIoZ68BAOiYDt1neU1ELGy4TXuqUmJ7UURcXph+rKRDJR0YEbWboq+UNK9QfG6ehkmOuhMAtF/pAaUanb0uzF9se6ntpWvWPFx2cwAA9IxTU/G5ku6IiE8Wph8k6VRJb42IpwtFrpB0uO3NbO8iaYGkX3YzZkw846k7rV69pvsBAkBFlUpuG529LoqIJRGxMCIWDgxsW2ZzAABsoNu3ApK0v6SjJL3O9q/z4xBJn5W0laRr8rQvSFJE3CbpUqVup9+TdEJEDHZsh2DCG2/dafbsge4GCAAV1nK35EZnrwEA6JYOXXPbUET8VBqxL/SVo5T5sKQPdywoVAZ1JwDorDItt43OXgMA0BV2+x9AB1F3AoAOKjNacqOz1wAAdFxKRvkZQnVQdwKAzio9oBQAAAAAAL3WllsBAQDQfR27zy0AAKigria3odDg0LqWy/e5v3QMgyUHqQzF2AuNYYrL7fZ27Ic+l2u0f3bwj6Vj2Kx/eqny7fgsyurvK/8nNK1k+bLHEz3kUGUkt8DkMHzr6BbLt6HOUPa+2nxfAZ1Hyy0AoLKoKwIAgBqSWwBAZdESAgAAahhQCgAAAABQebTcAgAqiVsBAQCAIpJbAEBlkdwCAIAaklsAQGWR2wIAgBqSWwBARXGfWwAAMIwBpQAAAAAAlUfLLQCgsmi5BQAANSS3AIBKYrRkAABQRHILAKgsclsAAFBDcgsAqCxabgEAQA0DSgEAAAAAKo+WWwBAddFyCwAAMpJbAEBFcZ9bAAAwjOQWAFBNpuEWAAAM62py26c+bdY/veXya4fWlo5hKAZLlZ/SN7V0DE+te6JU+RVPLS8dw3abb1+q/MzNZpWOocyxIEkeeq50DGWPh76I0jGEy61jSEOlyq8tuR9D5fcBAGDTNRTlfqck6el1T5Uq//Czq0vH8Lxp25Qqv9WUrUvH0N9HuxQwGv5CAACVZDFaMgAAGEZyCwCoLJJbAABQQ3ILAKgsklsAAFBDcgsAqCxyWwAAUNNXdgW2+23fZPs77QgIAABgU0bdCQA6ox0ttydJukNS+SHgAABolrnPLSqLuhMAdECpllvbcyW9WdKX2xMOAADNqY2W3O4H0EnUnQCgc8q23J4t6VRJW5UPBQCA8SEZRQWdLepOANARLbfc2j5U0kMRccMYyy22vdT20jVrHm51cwAAbISWW1RJK3Wn1avXdCk6AKi+Mt2S95f0Vtv3SrpE0utsf7V+oYhYEhELI2LhwMC2JTYHAEBv2Z5n+4e2b7d9m+2T8vRZtq+xfXf+f5s83bY/Y3uZ7Vts793bd4AeG3fdafbsgW7HCACV1XJyGxGnR8TciJgv6XBJP4iII9sWGQAAo3G6FVC7H2NYJ+mUiNhN0n6STrC9m6TTJF0bEQskXZtfS9LBkhbkx2JJ53RgT6AiqDsBQGeVvhUQAAC90u1uyRGxKiJuzM+fVBrxdo6kRZIuyItdIOmw/HyRpAsjuU7STNs7dGBXAAAw6bXjVkCKiB9J+lE71gUAQDOsjl0jO2B7aeH1kohYstH27fmS9pJ0vaTtI2JVnvWgpO3z8zmSlheKrcjTVgmTGnUnAGi/tiS3AAD0QoeS2zURsXCM7W4p6RuSTo6IJ4pxRETYjk4EBgAAGqNbMgAA42B7qlJie1FEXJ4n/77W3Tj//1CevlLSvELxuXkaAABos6623A7GkP6w7qmWy09x+XCnT5lRqnxE+ZPxF9xxcanyH7jostIxHHHQq0qVP/uA95eOYd3QupLl15aOIVTu82zHMdnf19sOFH3mHBeqq9t37nFqoj1X0h0R8cnCrCskHSPpo/n/bxemn2j7Ekn7Snq80H0ZmBSeG3q29DquvP87pcq/77KLSsdw3IGvLlX+xJe/q3QMW3rrUuW53Rk2dXRLBgBUk3tSUdtf0lGSbrX96zztDKWk9lLbx0u6T9Lb87wrJR0iaZmkpyW9o6vRAgAwiZDcAgCqq8vJbUT8VFKjjR44wvIh6YSOBgUAACRxzS0AAAAAYBNAyy0AoLK4fgwAANSQ3AIAKsmS+shtAQBARnILAKgo03ILAADWI7kFAFSTpT6SWwAAkDGgFAAAAACg8mi5BQBUksWAUgAAYBjJLQCgsuh+BAAAakhuAQCVxTW3AACghuQWAFBJdEsGAABF9OgCAAAAAFQeLbcAgIoy3ZIBAMB6JLcAgGoy3ZIBAMAwklsAQCVZXFsDAACGdTW5DQ3pj4NPt1x+xpQtS8cwReXO8vf19ZeOYeWTj5QqP3RbufKSdPeeq8vFEEOlY3h28JlS5Z8berZ0DH0u93n295c/HvpLxtDr7bvk3xRQBt2SgYlvKAZLr+Ouh+8tVX7FD+8uHcPPX7xTqfJ//9J1pWMAMDpOegMAAAAAKo9uyQCAyuKaWwAAUENyCwCoJItuyQAAYBjJLQCgskhtAQBATalrbm3PtH2Z7Ttt32H7le0KDAAAYFND3QkAOqdsy+2nJX0vIv7C9jRJM9oQEwAATTDdklFF1J0AoENaTm5tP0/SqyUdK0kR8Zyk59oTFgAAo7O55hbVQt0JADqrTLfkXSStlvQV2zfZ/rLtLdoUFwAAY7Ld9gfQQdSdAKCDyiS3UyTtLemciNhL0h8knVa/kO3FtpfaXvrImkdKbA4AgA312W1/AB007rrT6tVruh0jAFRWmeR2haQVEXF9fn2Z0hf2BiJiSUQsjIiFswZmldgcAABApY277jR79kBXAwSAKms5uY2IByUtt/3iPOlASbe3JSoAAMbgDj2ATqHuBACdVXa05H+QdFEe7e8eSe8oHxIAAM2hGzEqiLoTAHRIqeQ2In4taWF7QgEAYDy4RhbVQ90JADqnbMstAAA9YYvRjQEAwHplBpQCAAAAAGBC6GrL7RRP0babbddy+WcH/1g6hifXPlaq/Mxp25aO4bg93laq/MMnPV06hkNe+L9KlQ9F6Rj6+8odfn2xrnQMLjl8TNnykjQUQyXLD5YqP+hy5YfacCwArepFt2Tb50k6VNJDEbFHnranpC9Imi5pnaR3R8QvnZqWPy3pEElPSzo2Im7setBAD03rm156HUe+5C9Lld/1/84rHcNLt929VPnNp5S/pTG9VYDR0XILAKisHo2WfL6kg+qmfUzSByJiT0nvz68l6WBJC/JjsaRzxvcOAQBAs7jmFgBQSVZvWm4j4ie259dPlrR1fv48SQ/k54skXRgRIek62zNt7xARq7oTLQAAkwfJLQCgsibQaMknS7rK9ieUekX9aZ4+R9LywnIr8jSSWwAA2oxuyQAAbGjA9tLCY3ETZf5e0nsjYp6k90o6t7MhAgCAerTcAgAqyp0aXGVNRIz3PqTHSDopP/8PSV/Oz1dKKo5kMzdPAwAAbUbLLQCgkqz0I9buR4sekPSa/Px1ku7Oz6+QdLST/SQ9zvW2AAB0Bi23AIBqcm9ui2H7YkkHKHVfXiHpTEnvlPRp21Mk/VFpZGRJulLpNkDLlG4F9I6uBwwAwCRBcgsAwDhExBENZm10A/E8SvIJnY0IAABIJLcAgAqbQKMlAwCAHiO5BQBUUq/ucwsAACYmklsAQGX14ppbAAAwMZHcAgAqyuoTyS0AAEi4FRAAAAAAoPJouQUAVBbdkgEAQA3JLQCgkmwGlAIAAMNIbgEAlWWuuQUAAFlXk9shDemZwadbLj84tK50DH3uL1X+ibWPlY5hzhbzSpU/+7WnlY5hs/7NS5XfvH9G6RhWPn1/qfJ9bbhkfIupW5Yq3z9U7nhqB7vcfiibHJBaoJfolgxMfFP6ylc3d9pil1Lld3xBubqXJPW73PvoL1kHBTA2BpQCAAAAAFQe3ZIBAJVkmWtuAQDAeiS3AIDKMh2QAABARnILAKgsWm4BAEBNqVPett9r+zbbv7F9se3p7QoMAICx2G77A+gk6k4A0DktJ7e250h6j6SFEbGHpH5Jh7crMAAAgE0JdScA6Kyy3ZKnSNrc9lpJMyQ9UD4kAADG5vwPqBjqTgDQIS233EbESkmfkHS/pFWSHo+Iq9sVGAAAo3K65rbdD6BTqDsBQGeV6Za8jaRFknaRtKOkLWwfOcJyi20vtb304dUPtx4pAAB1uOYWVdJK3Wn16jXdDhMAKqvMgFKvl/S7iFgdEWslXS7pT+sXioglEbEwIhZuO3vbEpsDAGCYJfV14B/QQeOuO82ePdD1IAGgqsr8it8vaT/bM5xOdR8o6Y72hAUAALDJoe4EAB3U8oBSEXG97csk3ShpnaSbJC1pV2AAAIyObsSoFupOANBZpUZLjogzJZ3ZplgAABgXkltUDXUnAOicsrcCAgCgZ/q4FRAAAMgYOQMAAAAAUHmVarmd0je19Dpc9ix/G7rARQyVXkdZdrnzGmuH1paOYZtp5UbPHlL5/Ti1b1q58i5/TA7GYKnydMvEZGVx/AOTRX9fuSprf7WqvABaxF86AKCaLPWR3AIAgIzkFgBQUS7fGwcAAGwySG4BAJVkSX0lL7EAAACbDmoFAAAAAIDKo+UWAFBZDCgFAABqSG4BAJXFNbcAAKCGbskAgIqy+tz+x5hbtc+z/ZDt39RN/wfbd9q+zfbHCtNPt73M9l2239SBHQEAAETLLQCgoqyetdyeL+mzki5cH4v9WkmLJL08Ip61vV2evpukwyXtLmlHSd+3/aKIkje4BgAAG6HlFgCAcYiIn0h6pG7y30v6aEQ8m5d5KE9fJOmSiHg2In4naZmkfboWLAAAkwjJLQCgsjrULXnA9tLCY3ETobxI0p/Zvt72j22/Ik+fI2l5YbkVeRoAAGgzuiUDAKrJkjtzn9s1EbFwnGWmSJolaT9Jr5B0qe0XtD0yAADQEMktAKCiPJFGS14h6fKICEm/tD0kaUDSSknzCsvNzdMAAECb0S0ZAFBJVse6JbfiW5JeK0m2XyRpmqQ1kq6QdLjtzWzvImmBpF+WfvMAAGAjtNwCADAOti+WdIDStbkrJJ0p6TxJ5+XbAz0n6Zjcinub7Usl3S5pnaQTGCkZAIDOILkFAFSWW29pbVlEHNFg1pENlv+wpA93LiIAACCR3AIAKqxv4lxzCwAAeqzLya3V79Y32deGUTEHS/YGGxxaVzqGsi0NU/umlY6hrHVDa0uvY3r/5qXKl/0sJanf/aXK95UsL0mhKL2OMsqPNktygd6wetNyCwAAJiYGlAIAAAAAVB7dkgEAFeVO3ecWAABUEMktAKCyuOYWAADUkNwCACrJ5ppbAAAwbMz+XLbPs/1Qvndfbdos29fYvjv/v01nwwQAYGPuwD+gLOpOANAbzVysdL6kg+qmnSbp2ohYIOna/BoAAADUnQCgJ8ZMbiPiJ5IeqZu8SNIF+fkFkg5rb1gAAIzFstv/AMqi7gQAvdHqNbfbR8Sq/PxBSds3WtD2YkmLJWnuvLktbg4AgI0xoBQqpKW607yd5nUhNADYNJS+h0JEhKQYZf6SiFgYEQu3nb1t2c0BACBJsiS7r+0PoNPGU3eaPXugi5EBQLW1+iv+e9s7SFL+/6H2hQQAQDM6MZwULcHoGOpOANBhrSa3V0g6Jj8/RtK32xMOAADAJom6EwB02JjX3Nq+WNIBkgZsr5B0pqSPSrrU9vGS7pP09k4GCQDASBgAChMRdScA6I0xk9uIOKLBrAPbHAsAAONCN2JMRNSdAKA3Wh0tGQCAnqPlFgAA1JDcAgAqyeJWQAAAYFilktuhGCq9jrVDz5Uq//hzj5aOYVrftFLlt562TekYprj3H/1gDJYqvy7Wlo5hSOWOqSmN7+TQfAwlj+t+9/e0PN1CAQAAMBH0PsMBAKAVNt2SAQDAeiS3AIDKcst3tAMAAJsaklsAQGXRcgsAAGo45Q0AAAAAqDxabgEAlWQxoBkAABhGcgsAqCirj27JAAAgI7kFAFQWLbcAAKCG5BYAUFkMKAUAAGoYUAoAAAAAUHm03AIAKikNKMU5WgAAkJDcAgAqynRLBgAA65HcAgAqq48BpQAAQEZ/LgBANTkNKNXux5ibtc+z/ZDt34ww7xTbYXsgv7btz9heZvsW23t3YE8AAACR3AIAMF7nSzqofqLteZLeKOn+wuSDJS3Ij8WSzulCfAAATEoktwCASkoDSrX/31gi4ieSHhlh1qcknSopCtMWSbowkuskzbS9QxvePgAAqMM1twCAypooA0rZXiRpZUTcXBfTHEnLC69X5GmruhgeAACTQleT24jQ2qHnWi7f5/INzeuG1pYqPzg0WDqGcIy9UIc10zrRyfKSNBTl9uVQDJWOoa9k54VBteF4KPk+ylbu+6Ls8dj74xmTlTt1K6AB20sLr5dExJKGUdgzJJ2h1CUZAAD0CC23AIDK6utMy+2aiFg4juV3lbSLpFqr7VxJN9reR9JKSfMKy87N0wAAQJtxzS0AACVExK0RsV1EzI+I+Updj/eOiAclXSHp6Dxq8n6SHo8IuiQDANABJLcAgErq1YBSti+W9AtJL7a9wvbxoyx+paR7JC2T9CVJ727DWwcAACOgWzIAoLJ6MaBURBwxxvz5hech6YROxwQAAJpouR3pZvW2P277znxD+m/antnRKAEA2Egn2m0nxujLqDbqTgDQG810Sz5fG9+s/hpJe0TEyyT9VtLpbY4LAACgqs4XdScA6Loxk9uRblYfEVdHxLr88jql0R8BAOgq221/AGVRdwKA3mjHNbfHSfp6o5m2F0taLElz581pw+YAAEgDSpW9VzXQI03XnebtNK/RYgCAOqVqBbbfJ2mdpIsaLRMRSyJiYUQsnDWwbZnNAQAwzLTconrGW3eaPXuge8EBQMW13HJr+1hJh0o6MI8GCQBAFzEAFKqFuhMAdFZLya3tgySdKuk1EfF0e0MCAADYtFB3AoDOGzO5zTerP0DSgO0Vks5UGuFvM0nX5C5c10XEuzoYJwAAG6EbMSYi6k4A0BtjJrcNblZ/bgdiAQBgXOiWjImIuhMA9EY7RksGAKDrLJJbAAAwjOQWAFBddEsGAABZl5Pb0OD6+5ePnzW1dATT+jYrVX7W9PJD8k91ufdRtryk8hXCNlQop7jk4RflYyh7j8x2XO83qHIDZpYdcHNIg+W2X6o0AAAA0B603AIAKopbAQEAgGEktwCAymK0ZAAAUENyCwCoLFpuAQBADcktAKCySG4BAEBNudF0AAAAAACYAGi5BQBUksU1twAAYBjJLQCgohgtGQAADCO5BQBUFsktAACoIbkFAFST6ZYMAACGMaAUAAAAAKDyaLkFAFQW3ZIBAEANyS0AoJIYLRkAABSR3AIAKorRkgEAwDCuuQUAAAAAVB4ttwCAyqLlFgAA1JDcAgAqi2tuAQBATdeT2z73lyhbvhd1v8u95f4S8U8oEaWKT/XU8jGUrJT2q/xn0Ve2Z34bKtZDMVR6HaW2r7LbL3csAWXQcgsAAGpouQUAVJJFcgsAAIYxoBQAAAAAoPJIbgEAFWXZ7X+MuVX7PNsP2f5NYdrHbd9p+xbb37Q9szDvdNvLbN9l+02d2RcAAGDM5HakH/HCvFNsh+2BzoQHAMBo3IHHmM6XdFDdtGsk7RERL5P0W0mnS5Lt3SQdLmn3XObz9qYyeAMaoe4EAL3RTMvt+dr4R1y250l6o6T72xwTAABjs3rSchsRP5H0SN20qyNiXX55naS5+fkiSZdExLMR8TtJyyTt076dgAnqfFF3AoCuGzO5HelHPPuUpFPFUKkAgB5xB/5JGrC9tPBYPM6wjpP03fx8jqTlhXkr8jRswqg7AUBvtDRasu1FklZGxM3cYxAAsIlZExELWylo+32S1km6qL0hoeqoOwFA5407ubU9Q9IZSt1qmll+saTFkjRnHierAQDtM5FuBWT7WEmHSjowYv3NxFdKmldYbG6ehkmkTN1p3k7zxlgaAFDTymjJu0raRdLNtu9V+qG+0fbzR1o4IpZExMKIWLjtwKzWIwUAoMA9Gi15xFjsg5S6m741Ip4uzLpC0uG2N7O9i6QFkn5Z+s2jalquO82ezbhTANCscbfcRsStkrarvc5f0gsjYk0b4wIAYEy9aLm1fbGkA5SuzV0h6Uyl0ZE3k3RNTpCvi4h3RcRtti+VdLtSd+UTImKw60Gjp6g7AUB3jJncjvQjHhHndjowAADG0ovkNiKOGGFyw9/FiPiwpA93LiJMNNSdAKA3xkxuG/yIF+fPb1s0AAAAFUfdCQB6o6XRkgEAmAgYdRYAANSQ3AIAKmsijZYMAAB6i+QWAFBJtdGSAQAApC4nt7fcdOuaHWbMu2+URQYk9XrkQGKYGDH0evvE0HwMO3crEACYbG684aY1m0/ZgrrTxI+h19snhmrFQN2pQ7qa3EbE7NHm214aEQu7FQ8xTNwYer19YphYMQCN0C0ZmzrqTtWIodfbJwZiQEK3ZABAhZHcAgCAhOQWAFBZpLYAAKBmoiW3S3odgIihptcx9Hr7EjHUTIQYgBExoBQwIb6jiaH325eIoYYYJjFHRK9jAABg3F6+98viqp/9V9vXu8OMnW7gWikAAKpnorXcAgAwDrTcAgCAhOQWAFBZpLYAAKCmr9cB1Ng+yPZdtpfZPq0H259n+4e2b7d9m+2Tuh1DjqPf9k22v9Oj7c+0fZntO23fYfuVPYjhvfkz+I3ti21P78I2z7P9kO3fFKbNsn2N7bvz/9v0IIaP58/iFtvftD2z2zEU5p1iO2wPdDIGoHnu0AOY+Kg3bRALdSfqTtSdIGmCJLe2+yV9TtLBknaTdITt3bocxjpJp0TEbpL2k3RCD2KQpJMk3dGD7dZ8WtL3IuJPJL2827HYniPpPZIWRsQekvolHd6FTZ8v6aC6aadJujYiFki6Nr/udgzXSNojIl4m6beSTu9BDLI9T9IbJd3f4e0DTbPTgFLtfgATHfWmjVB3ou5URN1pEpsQya2kfSQti4h7IuI5SZdIWtTNACJiVUTcmJ8/qfTFNKebMdieK+nNkr7cze0Wtv88Sa+WdK4kRcRzEfFYD0KZImlz21MkzZD0QKc3GBE/kfRI3eRFki7Izy+QdFi3Y4iIqyNiXX55naS53Y4h+5SkUyUxAh0A9B71poy603rUnYanUXeaxCZKcjtH0vLC6xXqwRdkje35kvaSdH2XN3220h/BUJe3W7OLpNWSvpK793zZ9hbdDCAiVkr6hNJZrlWSHo+Iq7sZQ8H2EbEqP39Q0vY9iqPmOEnf7fZGbS+StDIibu72tgEAI6LeNOxsUXei7tQYdadJZqIktxOG7S0lfUPSyRHxRBe3e6ikhyLihm5tcwRTJO0t6ZyI2EvSH9T57iQbyNdmLFL6sdhR0ha2j+xmDCOJdM+snp15s/0+pS5gF3V5uzMknSHp/d3cLtAsd+AfgOb1qt6Ut03dSdSdGqHuNDlNlOR2paR5hddz87Susj1V6Qv6ooi4vMub31/SW23fq9S96HW2v9rlGFZIWhERtTOvlyl9YXfT6yX9LiJWR8RaSZdL+tMux1Dze9s7SFL+/6FeBGH7WEmHSvqb6P6NqXdV+rG8OR+bcyXdaPv5XY4DGBHJLSYp6k0JdaeEulMd6k6T10RJbn8laYHtXWxPU7oI/opuBuA0isi5ku6IiE92c9uSFBGnR8TciJiv9P5/EBFdPesWEQ9KWm77xXnSgZJu72YMSl1q9rM9I38mB6p3g0RcIemY/PwYSd/udgC2D1LqbvXWiHi629uPiFsjYruImJ+PzRWS9s7HCgCgNyZ9vUmi7lRA3amAutPkNiGS23zR94mSrlL6Y7w0Im7rchj7SzpK6azfr/PjkC7HMBH8g6SLbN8iaU9JH+nmxvOZz8sk3SjpVqVjdEmnt2v7Ykm/kPRi2ytsHy/po5LeYPtupbOiH+1BDJ+VtJWka/Ix+YUexAAAmECoN0041J2oO1F3miDc/ZZ6AADK2/N/vTyu/Xn7x0wZmP78GyJiYdtXDAAAOmpCtNwCAAAAAFDGlF4HAABAaxgACgAADKPlFgAAAABQebTcAgAqjJZbAACQkNwCACrJIrUFAADDSG4BAJWVbukIAABAcgsAqDSSWwAAkDCgFAAAAACg8mi5BQBUFu22AACghpZbAECFuQOPMbZon2f7Idu/KUybZfsa23fn/7fJ0237M7aX2b7F9t5teuMAAKAOyS0AoKIsu/2PJpwv6aC6aadJujYiFki6Nr+WpIMlLciPxZLOactbBwAAGyG5BQBgHCLiJ5IeqZu8SNIF+fkFkg4rTL8wkuskzbS9Q1cCBQBgkiG5BQCgvO0jYlV+/qCk7fPzOZKWF5ZbkacBAIA2Y0ApAEAlpStkOzKk1IDtpYXXSyJiSbOFIyJsRwfiAgAAoyC5BQBUWEeS2zURsXCcZX5ve4eIWJW7HT+Up6+UNK+w3Nw8DQAAtBndkgEAldX9sZIbukLSMfn5MZK+XZh+dB41eT9Jjxe6LwMAgDai5RYAUFlNjm7c7m1eLOkApe7LKySdKemjki61fbyk+yS9PS9+paRDJC2T9LSkd3Q9YAAAJgmSWwAAxiEijmgw68ARlg1JJ3Q2IgAAIJHcAgAqq2RHYgAAsEkhuQUAVBapLQAAqCG5BQBUGOktAABIGC0ZAAAAAFB5tNwCAKrJvRktGQAATEy03AIAAAAAKo+WWwBAJaWxkmm5BQAAidMt+AAAqBbb35M00IFVr4mIgzqwXgAA0EEktwAAAACAyuOaWwAAAABA5ZHcAgAAAAAqj+QWAAAAAFB5JLcAAAAAgMojuQUAAAAAVN7/A2LcJMCK5D2uAAAAAElFTkSuQmCC\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_G3=error(xdata3, poptG3[0], poptG3[1],poptG3[2], poptG3[3], poptG3[4], recorteG3.ravel(), inc=1)\n", + "poptG3E, pcovG3E = curve_fit(gauss2d, xdata3, recorteG3.ravel(), p0=[4,4,2,1,1],sigma=Err_G3)\n", + "estrellaG3E=gauss2d(xdata3, poptG3E[0], poptG3E[1],poptG3E[2], poptG3E[3], poptG3E[4])\n", + "FWHMG3E=FWHMG_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptG3E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 3 fotografÃa (Banda Verde)\")\n", + "plt.imshow(recorteG3, plt.get_cmap('Greens'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 3 a partir de la gaussiana con incertidumbre (Banda Verde)\")\n", + "plt.imshow(estrellaG3E.reshape(15, 15), plt.get_cmap('Greens'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 4 con incertidumbre (Banda Verde)" + ] + }, + { + "cell_type": "code", + "execution_count": 843, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_G4=error(xdata4, poptG4[0], poptG4[1],poptG4[2], poptG4[3], poptG4[4], recorteG4.ravel(), inc=1)\n", + "poptG4E, pcovG4E = curve_fit(gauss2d, xdata4, recorteG4.ravel(), p0=[3,5,4,1,1], sigma=Err_G4)\n", + "estrellaG4E=gauss2d(xdata4, poptG4E[0], poptG4E[1],poptG4E[2], poptG4E[3], poptG4E[4])\n", + "FWHMG4E=FWHMG_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptG4E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 4 fotografÃa (Banda Verde)\")\n", + "plt.imshow(recorteG4, plt.get_cmap('Greens'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 4 a partir de la gaussiana con incertidumbre (Banda Verde)\")\n", + "plt.imshow(estrellaG4E.reshape(15, 15), plt.get_cmap('Greens'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 5 con incertidumbre (Banda Verde)" + ] + }, + { + "cell_type": "code", + "execution_count": 844, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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K87GMtVzzOXCetq0PtLTPcxfbz0l6q9JdHxZIulWj75tt6iVNMY23rieVEoaGvasrjojvRMTvK1Wa78zrmszxONnPuGoydafVSl1kmw0qtRI21+nGO+5LrZa0n0ceGGi1pD9vOi7mRsSPKstM9PiU0ue/qKkrdbXOs81nbHubz7hFzfWr+yqvS757bpF04Cj7TZHcKumHGr6etOQ7aqy6ojT54/cHSj9WLM9xXJinT6TeWd1v6zTy913DaqWW2+r6doqIcyvLjFuPnbbJre0/tt34UnxEaecO5dcPKF2jMJbPSvpQ/gKV7YX5eoLxzFfqfvVY7jv+l2PEuJ/TvWBn2Z5j+y+Vfjn54QS2I6VrGd7ldHH2zhq+JnezUreRIW37Psda/jJJr7T9IqfrHD6g8f+I5kt6XNKv86+ek7kVz4T3U/YtpesaRmR7D6Wuvo3RmecrXV/xkNKX399OIrZvSjrU9h/lL6K3a9sT42Rjl9IXwWuUukFdKEkRMaR0Qv248+15nIZdP37UtaTuamfb3i0f32+rzLte0hNOAx7MdWq9PszpeuSGY5S6DgHTAwNK1do0PVfPl/RwRPzG9hFKP7aO54N5/S+RdILS9YWtrGukc/9kXSbpBKeBjGYp3davWl9sdZ/vpPT5rs/l3qDU2jqa6vlukVIiO9F13STpd/Nnt6tSV0nlZfeyvTxXsDcoHQdDed5Yx2NVK59xtexE604XSXqZ7VfbnmF7D9vPjYgtSvvnQ7bn58/i/1Nq3euk65USlHNt75T/HhpjknxW6fM6VFJjwKsxb1upsf/Gf6zUAPN22zNt/5GkIyrzb1aqqz03tyh+oLW3tI0zbS92GhjqvZK+MsayE/47iDT+yqqm+LeRj4UXa9t67GTrmg2XKg3edEj+cer9TfMndfzm1vMvKt2KZ4HSdbbSxOqd1fXcozQ2TuP77sUabpSS0vH7StvH53XNsX1s5W9SmkA9djokt43ReBuPK/L0F0i6zvavlX6deEcM35/sA0oXQj9q+9WjrPeTudyVtp+QdK1S3/LxfFDS85W6fn5TqUvqaOYr/YL3iNKvbcuUfgVq7g48mvOVLrS/Ruki9N8oJzu5tfBDkn6Y3+dR4yx/W35+idIX168lPaj0xT+av1D6g3hCKUkb60ug2WT2k5SugTnZ3qbm+cLG567UHWS9hpO9Lyp1dVgr6Xalz29CIg309MdKgz09pHR9QbUSM9nYpbTPH1O6luQ/K9P/SukL71qnbif/pnQt9Gg+qPS+7lYa9GLrsPL5ZHeC0oATdyv9svt5pZZr5S//SQ/dDkxpfR14oBN2pHP1WyT9TY7nfUoVzbHcn9d9n1Iy86aIuLOVdY1y7p+UXB84U6l1Z12ObU1lkZb2eUTcLun/KiUtDyhd8zjWj/l/k7d7t9K58TLlOsl464qIq5TqJLcoDV7zL5X19iklgvcptUYdo+EEc6zjsWqyn3HVhOtOEXGv0nn73TnWmzQ8mM7blFov71JqWfuyUj2vY3I945VKA2Deq/T5vCbPu0Ip+bkk12duVbrTxVg+oFH+xnMPtz9Surb24bydyyvzf650jPyb0qjf24yc3KIvK9Wt7lLqMTjWPVUn+3fw/2v7UYfPyt+HT+btfiEvJ7VW15QkRcS3la6j/Z5SHfN7TYu0cvx+UamV9SuRB4kdr945ij9R2k8PKyXdX6zEvVqpdfgcpTr9aqWkvjEK+Ask/TrSLYFG5W27sgOJU8vuo0rdZu7ucTiSJNtflnRpRPxTr2OpI9tvU+qCclavYwHawQvnhpYf0P4Vn3fnDREx5n30gHawfazSYCqLx1l0h2f7zUqDMo3aiwuYqpxuifkTpUGo1vU6njqy/TVJ50XEt8ZartY3UUZ72X6l0ojKlvRRST/V8EBMPRcRk+n2gyYRMdotDQAAmFKcbuvzDKXW2YOUWi8/NWYhYIrKrZ3b3XoLExcRE7oVFB2wULVcqZvOfUonkpOCpn0AUxkDSgHT1SylLppPKHWr/LqkT/c0IgBTHi232Coi/lTpPnIAUA8MAIUai4irte2IwMjy4DNjDTgFANshuQUA1Bf9jwAAQEZyCwCoJ4uWWwAAsFVXk9uBgT1iv/2b7yM8cZtjcxuiKLuEtH/k+y9Pigsv6toSW4pjKNXn8uaS0vexZah8P8zoK/s823E8DI14C73JKDum+wqbvu69514NDj5EhgEAHTAwMBD7H9B63QnA1HPPr+7V4OAgdacO6Gpyu9/+++maa69uufwjGwaLYyhNqBbM2r04hhl9M4vKP7n5ieIYSseJmjtjp+IYHt/4SFH5RwvLS9LCOXsVld9l1m7FMfxmy1NF5Us/y9n9c4rK/+5RxxaVB4pQNcA0t/8B++mH17XjFp4Apoqjj3xxr0OYtuiWDACorz6yWwAAkJDcAgDqi2tuAQBAxjiTAIB66sQ9bsfJlW0vsf1927fbvs32O/L0j9i+0/Yttq+wvaBS5mzbq2z/zPbx7Xr7AABgW0XJre1l+WS9yvZ72hUUAABT1GZJ746IQyQdJelM24dIukrSYRFxuKSfSzpbkvK8kyQdKmmZpE/b7u9J5JgSqDsBQOe0nNzmk/M/SHq5pEMkvTafxAEA6ALLbv9jLBGxLiJuzM+fkHSHpEURcWXE1iH9r5W0OD9fLumSiNgQEXdLWiXpiI7sDkx51J0AoLNKWm6PkLQqIu6KiI2SLlE6iQMA0BUdSm4HbK+sPM4YZdsHSHqepOuaZr1R0rfz80WSVlfmrcnTsGOi7gQAHVQyoNRIJ+wjmxfKlYIzJGnJfksKNgcAwLY6NJ7UYEQsHXu73lnS1yS9MyIer0x/r1LX5Ys6EhnqjroTAHRQxweUiogVEbE0IpYODOzR6c0BANBRtmcqJbYXRcTllemnSTpB0skxfAPqtZKq2cniPA0YVbXutHDhQK/DAYDaKEluOWEDAHrGkvrstj/G3Gbqt3yepDsi4mOV6csknSXpVRHxVKXINySdZHu27QMlHSTp+nbvC9QGdScA6KCSbsn/KemgfLJeqzQa5J+0JSoAAMZjjTsAVAccLekUST+1fVOedo6kv5M0W9JVOaZrI+JNEXGb7Usl3a7UXfnMiNjS7aAxZVB3AoAOajm5jYjNtt8q6TuS+iWdHxG3tS0yAADG0e3kNiJ+oJHvhvutMcp8SNKHOhYUaoO6EwB0VknLrSLiWxrjhA4AQOeMf+seYKqh7gQAndPxAaUAAAAAAOi0opbbydocm/XwhvUtl//l46uKYzh4wW8VlY/xFxnXlsLLrR58+v7iGPaZt7io/JbYXBzDzL5ZReX3nLt3cQwu/H3nyc1PFMfQVxhDn/uLym8a2lRUPtryVwG0hoZbAADQ0NXkFgCAdrF6MqAUAACYokhuAQD11JvRkgEAwBRFcgsAqC2POHAxAADYETGgFAAAAACg9mi5BQDUFt2SAQBAA8ktAKC2yG0BAEADyS0AoJYsq4/sFgAAZCS3AIDaolsyAABoYEApAAAAAEDt0XILAKgn7nMLAAAqSG4BALVFbgsAABpIbgEAtWTRcgsAAIZxzS0AAAAAoPZouQUA1BYttwAAoIHkFgBQUya5BQAAW5HcAgDqidGSAQBARVeT24jQxqGNLZc/cP4zimOY279TUflfb3qsOIbZ/XOLys/om1kcw1AMFZXvc/nl2qEoKm+VV2pL30c7Yig1FFuKyve5v02RAN1HbgtMfRFl5/upgh/TgKmPAaUAAAAAALVHt2QAQC1xKyAAAFBFcgsAqC2SWwAA0EByCwCorT6SWwAAkLV8za3tJba/b/t227fZfkc7AwMAYExOA0q1+wF0CnUnAOiskpbbzZLeHRE32p4v6QbbV0XE7W2KDQAAYDqh7gQAHdRychsR6ySty8+fsH2HpEWS+IIGAHScZa65Ra1QdwKAzmrLNbe2D5D0PEnXtWN9AABMxFS41zTQCupOANB+xcmt7Z0lfU3SOyPi8RHmnyHpDEnad8k+pZsDAGArWm5RR5OpOy3Zb0mXowOA+mp5QClJsj1T6cv5ooi4fKRlImJFRCyNiKW777F7yeYAANiG7bY/gE6abN1p4cKB7gYIADVWMlqyJZ0n6Y6I+Fj7QgIAAJh+qDsBQGeVtNweLekUSS+1fVN+vKJNcQEAMC5uBYSaoe4EAB1UMlryDyRG8gAA9EZKRjkNoT6oOwFAZ7VltGQAALqPa2QBAMAwklsAQG2R3AIAgIauJrdDGtKGLRtaLj9/zi7FMWyJzUXln9ryVHEMdtEg1RqKoeIYHt/0aFH5Of1zi2Mo1e/yw7cd6yi1OTb1dPul9wmNNsUBAJiatsSWnpaXpKGhsvpbad1LkmYU1hn63F8cAz/oAWPrfc0eAIAWUc8DAAANJLcAgNqiFQMAADSQ3AIAaonRkgEAQFX5BQgAAAAAAPQYLbcAgNqi5RYAADSQ3AIAaovcFgAANJDcAgBqyrTcAgCArUhuAQC1RXILAAAaGFAKAAAAAFB7tNwCAGqJWwEBAIAqWm4BALWVEtz2PsbenpfY/r7t223fZvsdefrutq+y/Yv8/255um3/ne1Vtm+x/fzO7xUAAHZMJLcAgNqy3fbHODZLendEHCLpKEln2j5E0nskfTciDpL03fxakl4u6aD8OEPSZzqxHwAAAMktAKDOutx0GxHrIuLG/PwJSXdIWiRpuaQL82IXSjoxP18u6YuRXCtpge19OrAnAADY4ZHcAgCwrQHbKyuPM0ZayPYBkp4n6TpJe0XEujzrfkl75eeLJK2uFFuTpwEAgDZjQCkAQE117D63gxGxdMwt2ztL+pqkd0bE49U4IiJsRycCAwAAoyO5BQDU0wQGgOrIZu2ZSontRRFxeZ78gO19ImJd7nb8YJ6+VtKSSvHFeRoAAGizria3ferT7P7ZLZcf/M364hhKti9Jm4Y2Fcew+tf3FJV/dMOjxTHsNme3ovLzZ+5SHMP8mfOL11GqtF7cjqaZiLK1DMWWovLumwp7AZg8q/u3AnLa4HmS7oiIj1VmfUPSqZLOzf9/vTL9rbYvkXSkpMcq3ZeBjttSeI6QpA1bni4q/1Ab6m8Pb3ioqPy8GfOKY9hz7t5F5XeaUV7v6S+sunP7NEx3tNwCAGqrBxW1oyWdIumntm/K085RSmovtX26pHskvTrP+5akV0haJekpSW/oarQAAOxASG4BAJigiPiBRu/0cdwIy4ekMzsaFAAAkERyCwCoMbrYAQCABpJbAEBtkdsCAICG4uTWdr+klZLWRsQJ5SEBADAB7titgICOou4EAJ3R14Z1vEPSHW1YDwAAwI6AuhMAdEBRcmt7saQ/lPT59oQDAMDENG4F1O4H0EnUnQCgc0q7JX9C0lmSen/DUgDADodkFDX0CVF3AoCOaLnl1vYJkh6MiBvGWe4M2yttr3z4oYdb3RwAANuh5RZ10krdaf36wS5FBwD1V9It+WhJr7L9K0mXSHqp7S81LxQRKyJiaUQs3X2P3Qs2BwBAhdNoye1+AB006brTwoUD3Y4RAGqr5eQ2Is6OiMURcYCkkyR9LyJe17bIAAAAphHqTgDQWdznFgBQW3QjBgAADW1JbiPiaklXt2NdAABMhMU1sqgv6k4A0H603AIAaovkFgAANJDcAgBqi9wWAAA0dDW57XOf5s/cpeXyj29cXRzD05ufKip/76/LY/i/P/p6UfkD99itOIbXHXp8UfkZLj90ZvXNKio/s7C8JA1Ngd93QkM93n70dPsAgNFFSBGtf09vHtpUHMMDT68rKv/1X36zOIZv/vzWovIHDexRHMOph72yqPyhux1eHMO8GTsXlbf4RRDTW+9r9gAAtMJ0SwYAAMNIbgEA9UVyCwAAMpJbAEBt0XILAAAaSG4BALVkSX3ktgAAIOvrdQAAAAAAAJSi5RYAUFOmWzIAANiK5BYAUE+W+khuAQBARnILAKgliwGlAADAMK65BQAAAADUHi23AIDa4hdaAADQQHILAKgtrrkFAAANJLcAgFrimlsAAFBFcgsAqCnTcgsAALbiciUAAAAAQO3RcgsAqCfTLRkAAAwjuQUA1JJF9yMAADCsq8ltKLRpaFPL5Wf2zSyO4ZENjxaV/+qd/14cw48u+I+i8vcc+6ziGP7bwccUlX9q89PFMew6a0FR+S2xpTiG0nX0taFq7cJ19PWVtVy14z0AvcI1t9gRhKLlsltic/H21z65tqj8JSuvK47h5stuKCp//eELi2P47T33Lyr/rF2eXRzD3P55ZSsw53xMb7TcAgBqi27JAACggZ9vAAAAAAC1R8stAKCWLLolAwCAYSS3AIDaIrUFAAANRd2SbS+wfZntO23fYfuF7QoMAICxWX1u/wPoJOpOANA5pS23n5T0rxHx323PklQ4hBsAABNj0y0ZtUTdCQA6pOXk1vaukn5X0mmSFBEbJW1sT1gAAADTC3UnAOiskm7JB0paL+kLtn9i+/O2d2peyPYZtlfaXvnw4MMFmwMAYFu22/4AOmjSdafBwcHuRwkANVWS3M6Q9HxJn4mI50l6UtJ7mheKiBURsTQilu4+sHvB5gAA2BbX3KJmJl13GhgY6HaMAFBbJcntGklrIuK6/PoypS9sAAA6zh16AB1E3QkAOqjl5DYi7pe02vbBedJxkm5vS1QAAADTDHUnAOis0tGS3ybpojza312S3lAeEgAAE0M3YtQQdScA6JCi5DYibpK0tD2hAAAwGVwji/qh7gQAnVPacgsAQE/YYnRjAACwFcktAKC2aLkFAAANXU1uI0Ibt2xoufys/tnFMWwcmgL3Su8vq4ztf8A+xSHMnzW/qPys/pnFMUyFFpeh2FJUvs8lA44n/e7vaXkXvgczvix2MLbPl3SCpAcj4rA87bmSPitpjqTNkt4SEdc7fdF9UtIrJD0l6bSIuLEngWMHVf4dPaew/jV/l+1u5Tt5+8wrKr7Hgl2KQ9h5VlkM7agzABgbf2UAgNrq0a2ALpC0rGnahyV9MCKeK+l9+bUkvVzSQflxhqTPTO4dAgCAiaJbMgCglqzedEuOiGtsH9A8WVKjaWhXSffl58slfTEiQtK1thfY3ici1nUnWgAAdhwktwCA2upQcjtge2Xl9YqIWDFOmXdK+o7tjyr1inpRnr5I0urKcmvyNJJbAADajOQWAFBT7tS1+4MRMdlbtbxZ0rsi4mu2Xy3pPEkva39oAABgNFxzCwBAuVMlXZ6ff1XSEfn5WklLKsstztMAAECbkdwCAGrJSiexdj9adJ+kY/Lzl0r6RX7+DUmvd3KUpMe43hYAgM6gWzIAoJ7cm1uK2b5Y0rFK1+aukfR+SX8m6ZO2Z0j6jdLIyJL0LaXbAK1SuhXQG7oeMAAAOwiSWwBAbfVotOTXjjLrd0ZYNiSd2dmIAACARHILAKipXt0KCAAATE1ccwsAAAAAqD1abgEAtdWLa24BAMDURHILAKgpq08ktwAAICG5BQDUFi23AACggeQWAFBLNgNKAQCAYQwoBQAAAACoPVpuAQC1Za65BQAAWVeTW9ua1T+75fJ9Q+UNzTPcX1T+lc86sjiGx960oaj8KYcdUxzD3vP2LirfX7gfJalvCnQciIiyFbShXj2jb2ZR+dLPojQ5ILlAL3HNLXYEJd+zpecYSdpv5/2Lyr/1iJcXx3DkksVF5RfN37M4hiP2XFpUfnb/3OIY7N7XnYCpjJZbAEAtWeaaWwAAsBU//wAAAAAAao+WWwBAbZnfaAEAQEZyCwCoLbolAwCAhqKfvG2/y/Zttm+1fbHtOe0KDACA8dhu+wPoJOpOANA5LSe3thdJerukpRFxmKR+SSe1KzAAAMbiDv0DOoW6EwB0VunFSjMkzbU9Q9I8SfeVhwQAADBtUXcCgA5pObmNiLWSPirpXknrJD0WEVc2L2f7DNsrba98ePDh1iMFAKDK6Zrbdj+ATmml7jQ4ONjtMAGgtkq6Je8mabmkAyXtK2kn269rXi4iVkTE0ohYuvvA7q1HCgBAE665RZ20UncaGBjodpgAUFsl3ZJfJunuiFgfEZskXS7pRe0JCwCAsVlSXwf+AR1E3QkAOqjkVkD3SjrK9jxJT0s6TtLKtkQFAMC4aGlF7VB3AoAOKrnm9jpJl0m6UdJP87pWtCkuAACAaYW6EwB0VknLrSLi/ZLe36ZYAACYFFpuUTfUnQCgc4qSWwAAeqmP+9ICAICM5BYAUEsWLbcAAGBYV5PboRjSE5seb7n8nnP2Lo5h0U6Li8rvMWeP4hg+fMzhReXdhpaKPWaX3Vpgc2wujqHPZaOSzvDM4hhm9JX9CbgNI6tuKdyXm4c2FcdQYkhDPd0+dmD5PrfAdGaX/Ygzow1VvV1nld3K8Zh9ji2OYenCpUXlZ/XNKo5hp5nzi8rP7ptdHENp3QmY7vgLAQAAAADUHt2SAQA15bb0ZAEAANMDyS0AoJYsuugBAIBhJLcAgNpiQCkAANDAT94AAAAAgNqj5RYAUFtccwsAABpIbgEANWVuBQQAALYiuQUA1JJFyy0AABhGcgsAqC1abgEAQAMDSgEAAAAAao+WWwBAPVky97kFAAAZyS0AoKbMNbcAAGArklsAQC1ZXHMLAACGkdwCAGrLJLcAACDjYiUAAAAAQO3RcgsAqK0+rrkFAABZV5PbGZ6hPWYvbLn8zL5ZxTHsPHN+T8u3w9ObnypeR2lXvlmeXRxDqanQHbEdEfS57M8wNFRYvgwD+qBXrKnxPQBMZX1tGFG8tP41Y2Z5dXPnmbsUrqH8u6J0X7bjswAwNlpuAQA1ZW4FBAAAtiK5BQDUFt2SAQBAAz95AwAAAABqj5ZbAEAt2VxzCwAAho3bcmv7fNsP2r61Mm1321fZ/kX+f7fOhgkAwPbcgX/jbnOE82Ke/jbbd9q+zfaHK9PPtr3K9s9sH9+B3YAphroTAPTGRLolXyBpWdO090j6bkQcJOm7+TUAAF1k2e1/TMAFajov2v49ScslPSciDpX00Tz9EEknSTo0l/m07f427gRMTReIuhMAdN24yW1EXCPp4abJyyVdmJ9fKOnE9oYFAMDUNMp58c2Szo2IDXmZB/P05ZIuiYgNEXG3pFWSjuhasOgJ6k4A0ButDii1V0Ssy8/vl7TXaAvaPsP2StsrHxp8qMXNAQCwvT657Q9JA43zVn6cMYFQni3pJbavs/3vtl+Qpy+StLqy3Jo8DTuelupO69cPdic6AJgGigeUioiwHWPMXyFphSQ99/nPGXU5AAAmw1Kn7nM7GBFLJ1lmhqTdJR0l6QWSLrX9jLZHhmlhMnWn31n6fOpOADBBrdYKHrC9jyTl/x8cZ3kAANqsE8NJtTz68hpJl0dyvaQhSQOS1kpaUllucZ6GHQ91JwDosFaT229IOjU/P1XS19sTDgAAE9ejAaVG8k+Sfi/H9GxJsyQNKp0vT7I92/aBkg6SdH35O0cNUXcCgA4bt1uy7YslHat0DdIaSe+XdK5Sl6vTJd0j6dWdDBIAgKlilPPi+ZLOz7d+2Sjp1IgISbfZvlTS7ZI2SzozIrb0JnJ0C3UnAOiNcZPbiHjtKLOOa3MsAABMSkE34paNcV583SjLf0jShzoXEaYa6k4A0BvFA0oBANArBd2IAQDANENyCwCoJUuNW/cAAAB0Obm1NaOv9U1uGtrYxmBaM7t/TvE6hmKoqPwG/6Y4hnQpWOv6+8pvv9HvssNvqA2XrZXuB7dlP/SXraCw/BYu/0NdlQ0ABWCC+kpvudWZW3YBwHb4tgEAAAAA1B7dkgEAtWV+owUAABnJLQCgtuiWDAAAGkhuAQC1ZPXmVkAAAGBqIrkFANSU1UfLLQAAyLhYCQAAAABQe7TcAgBqi27JAACggeQWAFBbDCgFAAAaSG4BALWUBpTi6hoAAJBQKwAAAAAA1B4ttwCAmjLdkgEAwFYktwCA2upjQCkAAJCR3AIA6skMKAUAAIaR3AIAaikNKEVyCwAAEgaUAgAAAADUHi23AIDaolsyAABo6Gpya0l9BY3FG2NjcQx9rn9j9Zz+ucXrmNU/u6j8DM8sjqHUlthcvI5QlJWPoeIYbH5jAlpj7nMLAAC2olYNAKitPlpuAQBARnILAKglBpQCAABV9OcCAAAAANQeLbcAgNpiQCkAANAwbsut7fNtP2j71sq0j9i+0/Yttq+wvaCjUQIAsB135B9QiroTAPTGRLolXyBpWdO0qyQdFhGHS/q5pLPbHBcAAOOy3fYH0AYXiLoTAHTduMltRFwj6eGmaVdGbL0Py7WSFncgNgAARtW4vVy7/wGlqDsBQG+04yz+RknfHm2m7TNsr7S9cnD9Q23YHAAAQK1NuO60fv1gF8MCgHorSm5tv1fSZkkXjbZMRKyIiKURsXRg4R4lmwMAYJjploz6mWzdaeHCge4FBwA11/JoybZPk3SCpOMiItoWEQAAE8IAUKgX6k4A0FktJbe2l0k6S9IxEfFUe0MCAGBiaGlFXVB3AoDOm8itgC6W9GNJB9teY/t0SZ+SNF/SVbZvsv3ZDscJAMB2uBUQpiLqTgDQG+O23EbEa0eYfF4HYgEAAKg96k4A0BstX3MLAEAvWaKlFQAAbEVyCwCoL665BQAAWVeT2z73ac6Mea2vYPP4i4wfQ39R+aHYUhzDkIaKys+bsXNxDDP7ZhWVD5UP8rh5aFPPYyj+PD2zOIZSpcdTRFl5oHe4RhYAAAwrus8tAAAAAABTAd2SAQC1xa2AAABAA8ktAKC26JYMAAAaSG4BALVFcgsAABpIbgEAtWTRLRkAAAxjQCkAAAAAQO3RcgsAqCluBQQAAIaR3AIAaovkFgAANJDcAgDqyVxzCwAAhpHcAgBqi5ZbAADQwIBSAABMgu3zbT9o+9YR5r3bdtgeyK9t++9sr7J9i+3ndz9iAAB2DCS3AIBaatwKqN2PCbhA0rLt4rGXSPoDSfdWJr9c0kH5cYakz5S+bwAAMDKSWwBATbkj/8YTEddIeniEWR+XdJakqExbLumLkVwraYHtfdrx7gEAwLa45hYAUFsduuZ2wPbKyusVEbFizDjs5ZLWRsTNTa2/iyStrrxek6eta1ewAAAgIbkFANRWh0ZLHoyIpZOIYZ6kc5S6JAMAgB4huQUAoMwzJR0oqdFqu1jSjbaPkLRW0pLKsovzNAAA0GZdTW4jpKEYarn8hqHfFMcwp39eUfkhtR5/w6ahjUXlZ/bN6nkMW2JLcQx9LrvkOyLGX6gGSo+pLUObe7r96fEpoK6mwq2AIuKnkvZsvLb9K0lLI2LQ9jckvdX2JZKOlPRYRNAlGQCADmBAKQBALVmdGVJq3O3aF0v6saSDba+xffoYi39L0l2SVkn6nKS3tOGtAwCAEdAtGQBQUxO+dU9bRcRrx5l/QOV5SDqz0zEBAABabgEAAAAA08C4ya3t820/aPvWEea923bYHuhMeAAAjMUdeABlqDsBQG9MpOX2AknLmifaXqJ024N72xwTAADjc7oVULsfQBtcIOpOANB14ya3EXGNpIdHmPVxSWeJwVIBAD3SiwGlgPFQdwKA3mhpQCnbyyWtjYib+ZUbANArJKOoC+pOANB5k05ubc+TdI5St5qJLH+GpDMkacl+S8ZZGgAAYHqh7gQA3dHKaMnPlHSgpJvzjeoXS7rR9t4jLRwRKyJiaUQsHRhg7AQAQHtY7b/elhY1dEjLdaeFC6k7AcBETbrlNiJ+KmnPxuv8Jb00IgbbGBcAAOOiWzLqgLoTAHTHRG4FdLGkH0s62PYa26d3PiwAAMbHgFKYiqg7AUBvjNtyGxGvHWf+AW2LBgCASaAbMaYi6k4A0ButXHMLAAAAAMCU0tKtgAAAmAroRgwAABpIbgEAtdQYLRkAAEDqcnL7kxt/MrjTzPn3jLHIgKRejxxIDFMjhl5vnxgmHsP+3QoEaEbLLaa7G2/4yeDcGTtRd5r6MfR6+8RQrxioO3VIV5PbiFg41nzbKyNiabfiIYapG0Ovt08MUysGYHQkt5jeqDvVI4Zeb58YiAEJA0oBAAAAAGqPa24BALVFuy0AAGiYasntil4HIGJo6HUMvd6+RAwNUyEGYEQMKAVMie9oYuj99iViaCCGHZgjotcxAAAwac95/uHxnR9+q+3r3Wfekhu4VgoAgPrhmlsAAAAAQO1NtW7JAABMGJ2SAQBAw5RpubW9zPbPbK+y/Z4ebH+J7e/bvt32bbbf0e0Ychz9tn9i+196tP0Fti+zfaftO2y/sAcxvCt/Brfavtj2nC5s83zbD9q+tTJtd9tX2f5F/n+3HsTwkfxZ3GL7CtsLuh1DZd67bYftgU7GAEycO/QApj7qTdvEQt2JuhN1J0iaIsmt7X5J/yDp5ZIOkfRa24d0OYzNkt4dEYdIOkrSmT2IQZLeIemOHmy34ZOS/jUi/ouk53Q7FtuLJL1d0tKIOExSv6STurDpCyQta5r2HknfjYiDJH03v+52DFdJOiwiDpf0c0ln9yAG2V4i6Q8k3dvh7QMTZqcBpdr9AKY66k3boe5E3amKutMObEokt5KOkLQqIu6KiI2SLpG0vJsBRMS6iLgxP39C6YtpUTdjsL1Y0h9K+nw3t1vZ/q6SflfSeZIUERsj4tEehDJD0lzbMyTNk3RfpzcYEddIerhp8nJJF+bnF0o6sdsxRMSVEbE5v7xW0uJux5B9XNJZkhiBDgB6j3pTRt1pK+pOw9OoO+3Apkpyu0jS6srrNerBF2SD7QMkPU/SdV3e9CeU/giGurzdhgMlrZf0hdy95/O2d+pmABGxVtJHlX7lWifpsYi4spsxVOwVEevy8/sl7dWjOBreKOnb3d6o7eWS1kbEzd3eNgBgRNSbhn1C1J2oO42OutMOZqokt1OG7Z0lfU3SOyPi8S5u9wRJD0bEDd3a5ghmSHq+pM9ExPMkPanOdyfZRr42Y7nSyWJfSTvZfl03YxhJpHtm9eyXN9vvVeoCdlGXtztP0jmS3tfN7QIT5Q78AzBxvao35W1TdxJ1p9FQd9oxTZXkdq2kJZXXi/O0rrI9U+kL+qKIuLzLmz9a0qts/0qpe9FLbX+pyzGskbQmIhq/vF6m9IXdTS+TdHdErI+ITZIul/SiLsfQ8IDtfSQp//9gL4KwfZqkEySdHN2/MfUzlU6WN+djc7GkG23v3eU4gBGR3GIHRb0poe6UUHdqQt1pxzVVktv/lHSQ7QNtz1K6CP4b3QzAaRSR8yTdEREf6+a2JSkizo6IxRFxgNL7/15EdPVXt4i4X9Jq2wfnScdJur2bMSh1qTnK9rz8mRyn3g0S8Q1Jp+bnp0r6ercDsL1MqbvVqyLiqW5vPyJ+GhF7RsQB+dhcI+n5+VgBAPTGDl9vkqg7VVB3qqDutGObEsltvuj7rZK+o/THeGlE3NblMI6WdIrSr3435ccruhzDVPA2SRfZvkXScyX9bTc3nn/5vEzSjZJ+qnSMruj0dm1fLOnHkg62vcb26ZLOlfT7tn+h9KvouT2I4VOS5ku6Kh+Tn+1BDMCUxWjJ2BFRb5pyqDtRd6LuNEW4+y31AACUe+7vPCe++6P2j5kyMGfvGyJiadtXDAAAOmpKtNwCAAAAAFBiRq8DAACgNQwABQAAhpHcAgBqjOQWAAAkJLcAgFqySG0BAMAwrrkFAAAAANQeLbcAgNri1j0AAKCB5BYAUGMktwAAICG5BQDUFqktAABo4JpbAAAAAEDt0XILAKgx2m4BAEBCcgsAqCkzoBQAANiKbskAAAAAgNqj5RYAUEuWZLolAwCAjJZbAAAAAEDt0XILAKgxWm4BAEBCcgsAqC1SWwAA0EC3ZABAbdlu+2MC2zzf9oO2b61M+4jtO23fYvsK2wsq8862vcr2z2wf35k9AQAASG4BADXlDj3GdYGkZU3TrpJ0WEQcLunnks6WJNuHSDpJ0qG5zKdt97fwZgEAwDhIbgEAmISIuEbSw03TroyIzfnltZIW5+fLJV0SERsi4m5JqyQd0bVgAQDYgZDcAgBqq0PttgO2V1YeZ0wyrDdK+nZ+vkjS6sq8NXkaAABoMwaUAgDUWEeGlBqMiKWtFLT9XkmbJV3U3pAAAMB4SG4BAPVkTWgAqG6xfZqkEyQdFxGRJ6+VtKSy2OI8DQAAtBndkgEAKGR7maSzJL0qIp6qzPqGpJNsz7Z9oKSDJF3fixgBAJjuaLkFAGASbF8s6Vila3PXSHq/0ujIsyVdlVuTr42IN0XEbbYvlXS7UnflMyNiS28iBwBgevNwzykAAOrD9r9KGujAqgcjovlWPwAAYIojuQUAAAAA1B7X3AIAAAAAao/kFgAAAABQeyS3AAAAAIDaI7kFAAAAANQeyS0AAAAAoPZIbgEAAAAAtff/AF2WOB1X8PuXAAAAAElFTkSuQmCC\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_G5=error(xdata5, poptG5[0], poptG5[1],poptG5[2], poptG5[3], poptG5[4], recorteG5.ravel(), inc=1)\n", + "poptG5E, pcovG5E = curve_fit(gauss2d, xdata5, recorteG5.ravel(), p0=[2,2,2,1,1],sigma=Err_G5)\n", + "estrellaG5E=gauss2d(xdata5, poptG5E[0], poptG5E[1],poptG5E[2], poptG5E[3], poptG5E[4])\n", + "FWHMG5E=FWHMG_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptG5E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 5 fotografÃa (Banda Verde)\")\n", + "plt.imshow(recorteG5, plt.get_cmap('Greens'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 5 a partir de la gaussiana con incertidumbre (Banda Verde)\")\n", + "plt.imshow(estrellaG5E.reshape(15, 15), plt.get_cmap('Greens'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 6 con incertidumbre (Banda Verde)" + ] + }, + { + "cell_type": "code", + "execution_count": 845, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_G6=error(xdata6, poptG6[0], poptG6[1],poptG6[2], poptG6[3], poptG6[4], recorteG6.ravel(), inc=1)\n", + "poptG6E, pcovG6E = curve_fit(gauss2d, xdata6, recorteG6.ravel(), p0=[2,2,2,1,1],sigma=Err_G6)\n", + "estrellaG6E=gauss2d(xdata6, poptG6E[0], poptG6E[1],poptG6E[2], poptG6E[3], poptG6E[4])\n", + "FWHMG6E=FWHMG_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptG6E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 6 fotografÃa (Banda Verde)\")\n", + "plt.imshow(recorteG6, plt.get_cmap('Greens'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 6 a partir de la gaussiana con incertidumbre (Banda Verde)\")\n", + "plt.imshow(estrellaG6E.reshape(10, 10), plt.get_cmap('Greens'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 7 con incertidumbre (Banda Verde)" + ] + }, + { + "cell_type": "code", + "execution_count": 846, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_G7=error(xdata7, poptG7[0], poptG7[1],poptG7[2], poptG7[3], poptG7[4], recorteG7.ravel(), inc=1)\n", + "poptG7E, pcovG7E = curve_fit(gauss2d, xdata7, recorteG7.ravel(), p0=[2,2,1,1,1],sigma=Err_G7)\n", + "estrellaG7E=gauss2d(xdata7, poptG7E[0], poptG7E[1],poptG7E[2], poptG7E[3], poptG7E[4])\n", + "FWHMG7E=FWHMG_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptG7E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 7 fotografÃa (Banda Verde)\")\n", + "plt.imshow(recorteG7, plt.get_cmap('Greens'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 7 a partir de la gaussiana con incertidumbre (Banda Verde)\")\n", + "plt.imshow(estrellaG7E.reshape(10, 10), plt.get_cmap('Greens'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 8 con incertidumbre (Banda Verde)" + ] + }, + { + "cell_type": "code", + "execution_count": 847, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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0YbkXeGbT+h8fkTszH67f7kjdwpCZDzXEPr7fSvOemT+m2jevqa9Cvoq6izTVcfbJhjzeTXXcNn6Hjd/D3k2fG6/qL6v3wxUN6/tKPb3RTlQ/uNLcFziAVv+bN+fpknU3aP5N37tgXc3n6XZMtkyrskDjeWZf4KTxfV7v95XjeZ5MRDwvIr4RVVfP+6haXifaN83nuq3yXLiuZm+gupD8/ai6Qr+inv55qjLEOVF1zf5otBiUs83vpfGJHw9TlS1Ky00rgVuzanFrtlV5rn6/gK2P/ZZ5aMNdTWmOLztC9TfwwxbL7Av8etNx8UKqC1TjSo7VZVTbM1F5px13Nrx/BCAzm6c17pPH08rMB6nKY3u3ms80/g6YuDx7Xv37uANVj4XXRsQboe3jZqLve6u/pbpse9f454h4WlTdru+o1/1nTP639HngJXWPzFcDP8xqILB9qXo9rm/YJ39H1ao7rnEfTvUd7ws8r2kf/zZVo9W4Kcuz86Uy3FJm3pGZv5uZe1N1Y/hMTD4yZTZ9vg04sukEviS3HcCp2Z/V63pWVl1wXsPEHe9+ChjNzDMzc0tWXSbOAY6aavtqt1MdLEDVtYLqj3E8j83bNFn8emB5PW3cyqblm9d3EtXVyOfV2zreta2d0uRvUXUHeylVd5z9plj2GqqTV0uZ+QjVlb1DI2Ikqns9Pge8FVhaV5ivbTNv64HdYutBr/aZRt6hus/iWKruZj/KzCvq6bcBb2w6zrbLqivK45vXlLfG76UxXxupftyf0bCuXbIajKHKYNWVaRGTdDmX5hy7Sc9JA3qeLln3uObf9NsL1tW8T5o/tzJZTKuyQON55jbgw037fPvMbL69p5UvABdQtbbtApzMxPtmPVt35Wwuj0y2roeoLgwDj3c3fvyicGbelFWX8j2AvwD+OSJ2yMzNmfmBzDyAqjfAK2gaLKjWyXc8rqTcdBuwT7QeaGir8hxP9Gi7s0Vst2yk6tL6lBbzbqNqGW48LnbIzI80xJQcqz+h2p6JyjvjjRWN965O+ZSVKTyeVt1wsTtP/C3C1vmdzt/BmiqJmKjhisy8harn4PjTP6ZT3t6q3BjV/b5LG+Z/lmogqv3rdb9nsvVm5q1UXdxfQ1WuPaOedRtVy/BIwz7ZOTMbx1do3IdTfce3Af/TtI93zMzGxyn9DHD1JNs+vyvDEfHr8cTN5fdQfQFj9ec7aTFoRJOTgQ/XlSoiYllU93dOZSeqLmH31Qf6H04S+4Nq1fFbUQ2G8CSqbgHXtJEOVPe5/FJEHF5fvTyJ6kAcr0g1b+dk8d+muqL+1ohYUG/rIW1s6yNUj+vZHXhfm/keX/YxqqtT21OdXCZzIdV9YS1FdZ/GsVRXxu6i6gaSVH9sRDUAxDPbyVj9h3458IGo7qd+IU/8IHWSd4AvUv2Rf4CtR9w7GXh31ANwRTX4wK9Psp7zgOMj4oD6B+3xfV639H8O+ERE7FGvb3lEvLxh+RcD/5WZj7WRZ2lucACtOWlAz9Ml6x73h1ENkLMSeBvViK2drqud/TaZb1MVUH8/qnukf5WtywKfA95Ut8xGROwQ1WBWrVq6mu0E3J2Zj0bEIVQXlidyHvC6iPiZ+lzX/Dirydb1A2BJna+FVN06H7+XMyJeExHL6nPmvfXksYh4SUQ8q64830/VhXOMbXXyvTQu22656TtUFZmP1Pt5SUS8oJ53NvAHUQ32uSNVOeTcCVqRu6LeX6cBH4+IvaPqJff8uvz1j8AvR8TL6+lLIuKwmGRwMCY5VrN6FNiXqAZZ2j6q+0SPa5j/E6qGnNfU6b2e1pX0EkdFxAujum/+Q8ClmTlRa3bHfweZuYlqzIHJyrQrqO45v66eNJ3y9j8Dr2jYtg+ydR1xJ6rj/cGI+Glgymf3UpVj30rV5fuservWU40B8bGI2Ln+vXxKRLTczqm+Y6r75Z8W1eBfC+vXc2Pre99fTHXRYELzpTI8Pmri+Ov8evpzgcsi4kGqq4dvyyeeXfZ+4Iyomt2bRyYb98l6ua9FxANUAzM9r438fIBqEIz7qAYT+NJEgZl5P9VN6H9AVRC4iqr1sq0Hf2fmjVRXZv6G6ordL1MNnLGpDvlz4E/q7XzHZPH1Mr9K1X3o3jru36kqfRP5a2C7el2XUnUla9eZVN0h1lENEHDp5OH8G/DTUXXLaHRv/R3fSXV/zSuzcj3wMaoT+51U94t8syB/v0X1fd9N9aPT+Kzg0ryPd0v5ItWV7rMapp9PdWX6nKi6p1xLNVDaROv5MtV+/y+qq4v/1RTyR/X0S+v1/SdbD5b121QFSGlwDHX5pW6bT+fpttfd4F+pBmy8ql7m1Gmsa6vzfhvxW2koCxxPdf77zcZ0M/Ny4HepBu+5h+p8c3ybq38L8MH6u3ovTwxc1SofXwY+BXyjTmP8PDteJplwXVk9vvEtwN9TnacfAhoHKzoCuK4+7j5JdS/tI1Qti/9MVTG4gWq03+bH30Bn38u4v6bNclNdWfhlqntof1xvw2/Ws0+r83Yx8COqFtvfK8hHp94BfA/4LtXx8RfAUF1pXE3VqvgTqla9P2TyX9RPAq+OanTkT7WY/1aqrr53UPX8+4em+b9bp3EX1eju32J6vkBV3rubapCw10wUOM2/A6i6Dx/bNO03x38jqfbvN6mONZhGeTszr6N67OgXqC6u3MPWfw/voCrzPkBVyT+3eR0tfJGq5fzrdSV43Gt5YuCve6j+nvbadvHHTfgdZ+YDVANwHU3VQn8H1fG2GCCqAXEPoBrwb0KRW93yIZWJiMuoBn1o/gGaFRFxAnBAZr59tvMyF0U17P/fZebzZzsvUrfEyJJk9X7dXelpN16Rmau6u1JpWxGRVN0T18x2XvpZ3Rp0LbC4l62f0kyJ6jFTb83qflsVioiPUd2v/JnJ4mbygfQaAHVXhhuprjz9NtXjAEpae3sqM0+Z7TzMZZl5DVXruTQ47NosDaSI+BWqW6S2p2oR+jcrwhoUmfmCqaM0kcw8qZ04O3up1NOpbkS/l+p+4lc3dX+QpP7jAFrSIHoj1WN9fkg1pkk79zJK0uNsGVaRuuXV1ldJc4stw5qjMtODdwKZecRs50HS3GZlWJI0+OwHJUmSmlg8kCRJkiTNO33ZMrx0ZGnus2/zs9NnV+mY28NRfp2hdGTvLM5VufIUSpco7/01VHgNZ6zlIwAnV/pdDBV2wezkmxvL0aL4KNxPnRyzJfv2tltv466Nd9vdTzMvsJu0BtrIyEjuu98+s50NSV125RX/tzEzl812PgZZX1aG99l3Jd/49td7m0hhZWessPqy/YIdiuIBNo9tmjqowehY4YCJHRQGx7KsIjlaOIjjcAwXxQMsHt6uKP6x0UeK09g8trkofvHQ4qL4TiroD2y+ryh+yfD2RfGdHLOPFuzbX3yBt3ZpFlkX1gDbd799+OZll8x2NiR12XYLdrh1tvMw6PqyMixJUlcNWRuWJElbm9Y9wxFxRETcGBFrIuJdLeYvjohz6/mXRcR+00lPkqS5ICJWRsQ3IuL6iLguIt7WNP+kiMiIGKk/R0R8qj5fXhMRB89OztVrlp0kqX90XBmOiGHgb4EjgQOAYyLigKawNwD3ZOZTgU9QPRBdkqSZFdHd19S2ACdl5gHAocCJ4+fIiFgJvAz4cUP8kcD+9esE4LPd3Hz1B8tOktRfptMyfAiwJjNvzsxNwDnA6qaY1cAZ9ft/Bg6PcBQTSdIMih68ppCZ6zPzyvr9A8ANwPJ69ieAd7L1WHqrgTOzcimwa0Ts1ekmq29ZdpKkPjKdyvBy4LaGz2t54kS/TUxmbgHuA5a2WllEnBARl0fE5Rs33jWNbEmS1CiI6O6rKPWqm+tzgMsiYjWwLjOvbgpr55yqua9rZafGctNPfrKxR9mVpMHWN88ZzsxTMnNVZq4aGWlZX5YkqSM9qAyPjFdE6tcJE6S7I/BF4O1UXaffA7x3prZbg6ux3LRs2chsZ0eS5qTpjCa9Dmh8GPCKelqrmLURsQDYBbDZV5I0123MzFWTBUTEQqqK8FmZ+aWIeBbwZODqukK9ArgyIg6hvXOq5j7LTpLUR6bTMvxdYP+IeHJELAKOBi5oirkAOK5+/2rgvzILH/ArSdI0zfT4WfU9nqcCN2TmxwEy83uZuUdm7peZ+1F1kT04M++gOl++th5V+lDgvsxc36v9oVlj2UmS+kjHLcOZuSUi3gp8FRgGTsvM6yLig8DlmXkBVUHg8xGxBrib6kdfkqQZE8BQl8cfGp065AXAscD3IuKqetp7MvPCCeIvBI4C1gAPA6+bdibVdyw7SVJ/mU43aeqT+oVN097b8P5R4Nenk0avjNF/F1lHx7YUxW/JsviFsagoHmConWFTG2zOseI0SmVxGuWF4PLt3lwUv3hoSVE8wMjiPYviR7ON4npjfOHxBzAcJT8hDoaqWRIUD3o1XZl5CVMc9HXr8Pj7BE7scbbUB+Zy2UmSBs20KsOSJM0FPplGkiQ165vRpCVJkiRJmim2DEuSBlz5s4ElSdLgszIsSRp41oUlSVIzK8OSpIEWeM+wJEnalpVhSdJgm4XRpCVJUv9zAC1JkiRJ0rxjy7AkaeCFz7mWJElNrAxLkgae3aQlSVIzK8OSpIFnXViSJDXznmFJkiRJ0rxjy7AkaaAFwZBNw5IkqUnfVoZ7PdjJUOH6x8ii+E2jjxXFAzw2Vr5MiQU5Vr5QYQGydL92YqxwOx4bfaQ4jQVR+KeRZcfH5rFNZesHhoaXFMUPx3BxGqUWRPudS2bi2JAm4j3DUn/LwvNoR2kUluVmwkwM7ufvnzSxvq0MS5LUFT5nWJIktWBlWJI08KwLS5KkZg6gJUmSJEmad2wZliQNtMBu0pIkaVtWhiVJA8/KsCRJamZlWJI04MLKsCRJ2oaVYUnSYHM0aUmS1IIDaEmSJEmS5p2OK8MRsTIivhER10fEdRHxthYxh0XEfRFxVf167/SyK0lSuYjuvqROWHaSpP4ynW7SW4CTMvPKiNgJuCIiLsrM65vi/jczXzGNdCRJ6pijSauPWHaSpD7ScWU4M9cD6+v3D0TEDcByoPkHXZKkWWVlWP3AspMk9ZeuDKAVEfsBzwEuazH7+RFxNXA78I7MvK4bafa7x0YfKV5mNLf0ICdP2JzlveKHOlim17YU7qdO9uuiocVF8cNDZX9KYzlWFA/l2z0cw8VplNo0tqnt2DGyhzmRJjdkZVh9ZtDLTpllv/nZwTkiC8+lHaRQvESpoPC3qYPfssiyZYrzhBccNXdNuzIcETsCXwTenpn3N82+Etg3Mx+MiKOAfwH2n2A9JwAnAKzcZ8V0syVJktSXulF22rrctLK3GZakATWtZr+IWEj1Y35WZn6peX5m3p+ZD9bvLwQWRsRIq3Vl5imZuSozVy0dWTqdbEmS9IQuD55lA4imo1tlp8Zy07JlLYtWkqQpdNwyHFV/iFOBGzLz4xPEPAm4MzMzIg6hqnzf1WmakiSVCsIufOoLlp0kqb9Mp5v0C4Bjge9FxFX1tPcA+wBk5snAq4E3R8QW4BHg6Cy9iUSSpGnq5B44qQcsO0lSH5nOaNKXwOSli8z8NPDpTtOQJEkaFJadJKm/9N9QwZIkdVlEdPXVRnorI+IbEXF9RFwXEW+rp/9lRHw/Iq6JiPMjYteGZd4dEWsi4saIeHnv9oYkSQIrw5KkeWCmK8PAFuCkzDwAOBQ4MSIOAC4CnpmZzwZ+ALy7zt8BwNHAM4AjgM9EzMDz0SRJmsesDEuSBt5Mjyadmesz88r6/QPADcDyzPxa5uMPDb8UGH+W4GrgnMx8LDN/BKwBDun2fpAkSU+Y9nOGJUnqZ1UFdvYG0IqI/YDnAJc1zXo9cG79fjlV5Xjc2nqaJEnqESvDkiSVG4mIyxs+n5KZpzQHRcSOVM+UfXtm3t8w/Y+pulKf1fOcSpKklqwMS5IGXE+eM7wxM1dNmmrEQqqK8FmZ+aWG6ccDrwAOb3hkzjpgZcPiK+ppkiSpR/q2Mpy0/0i9sRwrX38Hy5R4bOzR4mVGc7QoftPopuI0Si0cWlgYv6gofijKb1vfwuai+IVDi4vTGKPs+Cgd5WZBlP/pbXn8NsM2zcBjKTePtX8M+phMzaaZ7iYdVYKnAjdk5scbph8BvBN4cWY+3LDIBcAXIuLjwN7A/sB3ZjDLmkc6+T0uKZdVaZSdR0cLz7sAY4XlptL4mThvDRWOk9dJuWm4sMzRSRqFh8es3roiNerbyrAkSd0yC+WuFwDHAt+LiKvqae8BPgUsBi6qC4OXZuabMvO6iDgPuJ6q+/SJmYUld0mSVMTKsCRp4M10K0RmXgK0SvTCSZb5MPDhnmVKkiRtxUcrSZIkSZLmHVuGJUkDbbYfrSRJkvqTlWFJ0sCzMixJkppZGZYkDTzrwpIkqZmVYUnSgOvJc4YlSdIc5wBakiRJkqR5x5ZhSdLAs2VYkiQ1szIsSRpojiYtSZJasTIsSRp41oUlSVIzK8OSpIFny7AkSWrWl5XhBMZyrP34gtgn0siexj82+lhRPMBojhbFP7zlocL4h4viARYMlR0iOy/cpSh+0dCiongo/y52XLhzcRoPbX6gKH67BdsXxS8e3q4oHsqP87EoGx9v4dDConiAhQXfhZURSeoPpedRKD8HbcktRfGbxzYVxXeyzCOF5aDNubkoHmCocGzaJcNLiuI7KT+UlrUWdFAeGIrhsgUKD0HLEOqVvqwMS5LUVRakJElSEyvDkqQB53OGJUnStqZdGY6IW4AHgFFgS2auapofwCeBo4CHgeMz88rppitJUlvChmH1D8tNktQ/utUy/JLM3DjBvCOB/evX84DP1v9LkiTNR5abJKkPzEQ36dXAmZmZwKURsWtE7JWZ62cgbUnSPBc4+IrmFMtNkjRDyoa8ay2Br0XEFRFxQov5y4HbGj6vradJkjQjIqKrL2kaLDdJUp/oRsvwCzNzXUTsAVwUEd/PzItLV1KfEE4AWLFyRReyJUlSxQqs+kjXy00r91nZ7TxK0rww7ZbhzFxX/78BOB84pClkHdD4K72inta8nlMyc1Vmrlq6bOl0syVJ0uMiuvuSOtWLctOyZSO9yq4kDbRpVYYjYoeI2Gn8PfAy4NqmsAuA10blUOA+73uRJEnzjeUmSeov0+0mvSdwft39bAHwhcz8SkS8CSAzTwYupHo8wBqqRwS8bpppSpLUPu/zVf+w3CRJfWRaleHMvBk4sMX0kxveJ3DidNKRJKlTjiatfmG5SZL6y0w8WqnnkixeZjS3FMVvGSuLf3jLQ0XxALc+8OOi+Ps23VcUv/GRe4riAXZbsnNR/B7bLSuKX1YYD7BkeLui+KC8ELxkQVkaC2JhUfxYjhXFQ/lxPja2uSw+R4viAYZiuHgZaTZYGdYgy4SqDt1mfEflprJzxKaxx4riH9x8f1E8wF2PTvSo5tY2FsY/tPnhoniABUNl58XdFu9eFN9JuWm3RWVpLClOARYMlf3GDkXZnZqdlOWkdgxEZViSpMlYGZYkSc268ZxhSZIkSZLmFFuGJUmDzcchSZKkFqwMS5IGnt2kJUlSMyvDkqSBFvhoJUmStC0rw5KkgWdlWJIkNXMALUmSJEnSvGNlWJI08CK6+5o6vVgZEd+IiOsj4rqIeFs9ffeIuCgibqr/362eHhHxqYhYExHXRMTBvd0jkiTJyrAkabBF1U26m682bAFOyswDgEOBEyPiAOBdwNczc3/g6/VngCOB/evXCcBnu70bJEnS1qwMS5IG3ww3DWfm+sy8sn7/AHADsBxYDZxRh50BvKp+vxo4MyuXArtGxF5d3guSJKmBlWFJksqNRMTlDa8TJgqMiP2A5wCXAXtm5vp61h3AnvX75cBtDYutradJkqQe6dPRpJPMsbajN409VpzCptGyZcYK8gNw6wM/LooH+OF9txTFX33nj4ri19x1d1E8wG7bb1cUf/CTVhTF/+yezy6KB1i6ZPei+KHF5dd8FuWiovgxyo6P4Q6uQwVlo+FGDBenUWqoIE+O5avZ1IPRpDdm5qo20t0R+CLw9sy8vzEfmZkRkd3OmOanpP1DqaSMNW5Lbi6Kf2TLQ0Xxdzy8fuqgJjfcc2NR/PUbf1gUf8eDDxbFA2y3cGFR/P67l3UAecbSpxfFA/zUzmXxSxcvK05jqLDMUfqbnFn+U+lTBNSOPq0MS5LUHQEMzUKZKCIWUlWEz8rML9WT74yIvTJzfd0NekM9fR2wsmHxFfU0SZLUI3aTliQNuO4OntVOa0NUQacCN2TmxxtmXQAcV78/DvjXhumvrUeVPhS4r6E7tSRJ6gFbhiVJgy1gaOa7y70AOBb4XkRcVU97D/AR4LyIeANwK/Ab9bwLgaOANcDDwOtmNLeSJM1DVoYlSeqyzLyEiW+VP7xFfAIn9jRTkiRpK1aGJUkDLXAgFUmStC0rw5KkgecAGZIkqZmVYUnSwJuFe4YlSVKfszIsSRpodpOWJEmt2HNMkiRJkjTvdFwZjoinR8RVDa/7I+LtTTGHRcR9DTHvnXaOJUkqEgxFd19SJyw7SVJ/6bibdGbeCBwEEBHDwDrg/Bah/5uZr+g0HUmSpiXsJq3+YNlJkvpLt+4ZPhz4YWbe2qX1SZLUFYH3BKkvWXaSpFnWrcrw0cDZE8x7fkRcDdwOvCMzr2sVFBEnACcArFi5nLEcbTvxR7c8UpZb4OHRh4viS/IDcPtD64viAa684+ai+K9866qi+A133l0UDzC8eGFR/LpnlaWxy+KdiuIBFi9dXBS/3YLtitNYNLSoKH7x0JKyBDpopBqO4aL4MbIofqiDTEVYxdDcYNdm9aFplZ0ay00r91lZlPBYjpXlFNgytqUo/v5N9xXF3/JA+TWBS267tij+uzfdUhS/YcM9RfEA221XVkb54VPK0yi1y6Kdi+J3WlheNltYWG4azrIyTSflJqkd0y7JRsQi4JXAP7WYfSWwb2YeCPwN8C8TrSczT8nMVZm5aunI0ulmS5IkqS91o+zUWG4aGRnpWV4laZB1o1nnSODKzLyzeUZm3p+ZD9bvLwQWRoS/2JKkGRURXX1J02TZSZL6QDe6SR/DBN18IuJJwJ2ZmRFxCFXl+64upClJUlsCu0mr71h2kqQ+MK3KcETsAPwi8MaGaW8CyMyTgVcDb46ILcAjwNGZWXYjoyRJ02RVWP3CspMk9Y9pVYYz8yFgadO0kxvefxr49HTSkCRJGhSWnSSpf3RrNGlJkvpU2E1akiRtw8qwJGmgRXjPsCRJ2paVYUnSwHMEaEmS1MzKsCRp4NkyLEmSmnXjOcOSJEmSJM0ptgxLkgZa4KOVJEnStvqyMpwkm8Y2tR0/mqPFaTw2+mhR/EObHy6Kv/Ohu4viAW68Y0NR/Iar15Ul8ODmsnhgtLAEuWaH7Yrif/jU28sSAJ6665OL4kuOpXGbx8r21Rhlj4Bc2EnRvLCb51BhGtFBnsqWsTqi2WM3aQ26LDgPlcSOG80tRfEPbXmoKH7dA3cWxQNcv75smRt+8OOi+NFb7iuKB2DnRUXhpb9NP1q6dOqgJj+z+z1F8U/afq/iNLZbsGNRfOkx2Mkx20m5RvNPX1aGJUnqHh+tJEmStmVlWJI00CIcTVqSJG3LAbQkSZIkSfOOLcOSpIFnN2lJktTMyrAkaeBZFZYkSc2sDEuSBlpgy7AkSdqWlWFJ0sCzMixJkpo5gJYkSZIkad6xMixJGnBBRHdfU6YYcVpEbIiIaxumHRQRl0bEVRFxeUQcUk+PiPhURKyJiGsi4uAe7gxJklSzMixJGmhBdbLr5qsNpwNHNE37KPCBzDwIeG/9GeBIYP/6dQLw2bItlCRJnfCeYUnSYAvaas3tpsy8OCL2a54M7Fy/3wW4vX6/GjgzMxO4NCJ2jYi9MnP9zORWkqT5qW8rw0PRfqN1SezjyxQ2iidjRfH3PHp/UTzAo488VrbAY6PFaRTLsvBHHi3bhnsffbQsAeC+TfcVxe+x/bLiNLJ0wwvjx4rXD0OlD4fJsjSyg7pCyd+ewxdJvB34akT8FVUD88/V05cDtzXEra2nWRlW3yg9L45lWblp09jmoniAzZu2FMWPPrypLIGHytYPQOGFt0cfK9vuhzeX76ctY2XlxSwsP9QLlS8j9QG7SUuSBt5QRFdfwEh93+/464Q2svFm4A8ycyXwB8CpvdxmSZI0ub5tGZYkqRt69JzhjZm5qnCZ44C31e//Cfj7+v06YGVD3Ip6miRJ6iFbhiVJA2+mR5OewO3Ai+v3vwDcVL+/AHhtPar0ocB93i8sSVLvtVUZnuAREbtHxEURcVP9/24TLHtcHXNTRBzXrYxLktSeYKjLrylTjDgb+Dbw9IhYGxFvAH4X+FhEXA38GdXI0QAXAjcDa4DPAW/pxV7QzLHcJElzQ7stw6ez7SMi3gV8PTP3B75ef95KROwOvA94HnAI8L6JfvwlSRoUmXlMZu6VmQszc0VmnpqZl2Tmz2bmgZn5vMy8oo7NzDwxM5+Smc/KzMtnO/+attOx3CRJfa+tynBmXgzc3TR5NXBG/f4M4FUtFn05cFFm3p2Z9wAXse3JQZKknuqTbtKaJyw3SdLcMJ0BtPZsuKfpDmDPFjETPS5iG/VInCcALF/ZMkSSpGIRPRlASyrVs3LTyn1WtgqRJE2hKwNoZfVAsmk9YCwzT8nMVZm5aunI7t3IliRJAESX/0nT0e1y08jISJdyJknzy3Qqw3dGxF4A9f8bWsT4uAhJ0qyzm7T6gOUmSeoz06kMX0D1zETq//+1RcxXgZdFxG71ABAvq6dJkiTNJ5abJKnPtPtopVaPiPgI8IsRcRPw0vozEbEqIv4eIDPvBj4EfLd+fbCeJknSjAiCoejuS5qM5SZJmhvaGkArM4+ZYNbhLWIvB36n4fNpwGkd5U6SpC6I7gyRIbXFcpMkzQ3TGU26ZyKCBUML244fjuHiNBYMlW36Dgt2KIrffuGSoniAXXbdqWyB/Qrj1z5YFg+wuGzf7jlS9jjEZdtvXxQPMJqjRfELo/1jadyC6MM/jSwba2WscGyWoU6GcrGBTHOErbnS9AwVlrUWDy8uil+6ZJeieICR3Xcuit9j76VF8RuGy383Fm5Xtt177LFrUfxeOxaW/YAdFpaVtUrLyEAHYyn4m6z+0IclfkmSustBryRJUjP7jUmSJEmS5h1bhiVJA81nA0uSpFasDEuSBlt4z7AkSdqWlWFJ0sDznmFJktTMyrAkaaAFMOQQGZIkqYmlA0mSJEnSvGPLsCRpwIXdpCVJ0jasDEuSBp6VYUmS1MzKsCRp4A35aCVJktTEe4YlSZIkSfNO37YMl4z8uXBoUfH6Fw8vKYpPsij+WcueVhQPsGVsS1H8pudvLopfe9uGoniAHbYv20/P2n+fovgD9yjfT0/afs+i+EXDi4vTWFJ4fJSPVFt2PAGMFS9RmkZ5y1lm+2mUb7HUHYHdpDX4ouA3fCjK20IWRFmRcceFOxXF77PTiqJ4gJ9bsbEovvR54xvvub8oHmDR4rIy6TP3KivTHDDylKJ4gJElI0XxS4a3K05jKIaL4kt/k0uOb6lE31aGJUnqiigvBEuSpMFnZViSNODCVgVJkrQNK8OSpIEWdNYtVJIkDTZLB5IkSZKkeceWYUnSwHMALUmS1MzKsCRp4HnPsCRJamZlWJI04MLRpCVJ0jasDEuSBlpgy7AkSdrWlANoRcRpEbEhIq5tmPaXEfH9iLgmIs6PiF0nWPaWiPheRFwVEZd3Md+SJEl9ybKTJM0N7YwmfTpwRNO0i4BnZuazgR8A755k+Zdk5kGZuaqzLEqSND1DEV19SVM4HctOktT3pqwMZ+bFwN1N076WmVvqj5cCK3qQN0mSpi8gYqirrymTbNEyWE//vbp18LqI+GjD9HdHxJqIuDEiXt6DvaAZZNlJkuaGbjxn+PXAlyeYl8DXIuKKiDihC2lJklQouv6vDafT1DIYES8BVgMHZuYzgL+qpx8AHA08o17mMxEx3MUdoP5j2UmS+sC0BtCKiD8GtgBnTRDywsxcFxF7ABdFxPfrq6Wt1nUCcALAipXLGWOs7XwMd1BmKF1mLNvPD8CTd96vKB5gdGy0KH63JTsXxd+x391TBzXZvTCNfXfZqyh+v532K4oH2GnhjkXxS4aXFKcxVHpMzUC3ySw8BpMsS6CDbejG1TSp1wJmvGtzZl4cEfs1TX4z8JHMfKyO2VBPXw2cU0//UUSsAQ4Bvj1T+dXM6VbZqbHctHKflUV5GOrg13vB0MKi+J0X7lIUv3LHsm0AiL3K/q732nFZUfw9j95fFA+weHhRUfxeO+5RFL/fTvsWxQMsXTJSFL9oaHFxGqXlagc1VL/ouCwbEccDrwB+OzNblrozc139/wbgfKqTe0uZeUpmrsrMVUuXLe00W5IkzYSRiLi84dVOC97TgJ+PiMsi4n8i4rn19OXAbQ1xa+tpGjDdLDs1lptGRsoqO5KkSkctwxFxBPBO4MWZ+fAEMTsAQ5n5QP3+ZcAHO86pJEkdiu63DG/sYHCjBcDuwKHAc4HzIuKnup0x9SfLTpLUf9p5tNLZVF21nh4RayPiDcCngZ2ouu9cFREn17F7R8SF9aJ7ApdExNXAd4D/yMyv9GQrJEmaxBDR1VeH1gJfysp3gDFgBFgHNPYRXVFP0xxl2UmS5oYpW4Yz85gWk0+dIPZ24Kj6/c3AgdPKnSRJ0xT0pGW4E/8CvAT4RkQ8DVgEbAQuAL4QER8H9gb2p6oIaY6y7CRJc8O0BtCSJEnbqlsGD6O6t3gt8D7gNOC0+nFLm4Dj6vtGr4uI84DrqQZWOjEzy0ZUlCRJxawMS5IGXLT1bOBumqBlEOA1E8R/GPhw73IkSZKaWRmWJA28adznK0mSBpSVYUnSQIvom3uGJUlSH7EyLEkaeGHLsCRJajKzN1FJkiRJktQHbBmWJA24sJu0JEnaRl9WhjOTLWOb244fy7HiNBYPLy6MX1YU/+DmB4viAZ626/5F8ct33LsovpP9NBxlh8iSBWX7dfsFOxTFA+y4YMei+B0W7lScxlBhp4nhGC5bf2E8QAyVFearJ7YUxFMWDzBW9PSX8vVL3eIAWhp0RbcCdDC6+oLCIuOi4SVF8SNL9iiKB1hcmMae2+1ZFP/Y2GNF8VBeHigtB+28cOeieIDtCtNYOLSoOI3Sck3prSte0FSv9GVlWJKkbgmY8UcrSZKk/mdlWJI04MIBtCRJ0ja8VC5JkiRJmndsGZYkDTzvN5MkSc2sDEuSBp7dpCVJUjMrw5KkgWfLsCRJamZlWJI00AIfrSRJkrblAFqSJEmSpHnHlmFJ0mCLsJu0JEnahpVhSdLACztCSZKkJlaGJUkDz5ZhSZLUrC8rwxFDLB7eru34sRwtTmPL2Oai+M1jm4rid160S1E8wHAMF8UvGl5UFD+WY0XxUJ6nBUMLi+IXDZVtA8Ci4cVF8Z1sd+lYO+WPbSkvmA9lb1u2kuzp+iVJvRFReMGng5/7odIySuH5fSjKz3GlZY6dCstm2Un5odCCKCuKDxduc0dpFH7XUF4O8gKl+kVfVoYlSeqWwOcMS5KkbVkZliQNuGDIVghJktRkyj4pEXFaRGyIiGsbpr0/ItZFxFX166gJlj0iIm6MiDUR8a5uZlySpHZFl/9Jk7HsJElzQzs3aJwOHNFi+icy86D6dWHzzIgYBv4WOBI4ADgmIg6YTmYlSepE1I9X6tZLmsLpWHaSpL43ZWU4My8G7u5g3YcAazLz5szcBJwDrO5gPZIkSXOGZSdJmhumMzztWyPimror0G4t5i8Hbmv4vLaeJknSjKkG0Brq6kvqkGUnSeojnZ7RPws8BTgIWA98bLoZiYgTIuLyiLj8rp/cNd3VSZJU624XabtJq0NdLTs1lpt+8pONXcieJM0/HVWGM/POzBzN6gFsn6Pq1tNsHbCy4fOKetpE6zwlM1dl5qqly5Z2ki1JklrqbruwlWGV63bZqbHctGzZSPczLEnzQEeV4YjYq+HjrwDXtgj7LrB/RDw5IhYBRwMXdJKeJEkdCwfQ0uyz7CRJ/WfK5wxHxNnAYcBIRKwF3gccFhEHAQncAryxjt0b+PvMPCozt0TEW4GvAsPAaZl5XS82QpIkqV9YdpKkuWHKynBmHtNi8qkTxN4OHNXw+UJgm0cHSJI0U6oBtGzN1cyx7CRJc4NDYkqSBt5Md5OuRwveEBHbdIWNiJMiIiNipP4cEfGpiFhTjzR8cA92gSRJajJly/BsCGA4htuOXxDlmzEUZdcBSu8RG+4gT7GwLI0lw0vK1j8D97mN5mhR/IJYWJzGwsJlxhgrTmMsy5YZKr6ulIXxkFG+TIlOWs7SxjbNCTEbj0M6Hfg0cOZWOYlYCbwM+HHD5COB/evX86hGHX7ejORS81JH5YHCU9BQQTkOYGEH56Dh4cI0Cs/tMyEKy6Pl5Y3y77uT8kBpuVrqFx65kqSBNxTR1ddUMvNi4O4Wsz4BvJOtqxargTOzcimwa9NgS5IkqQesDEuSNAMiYjWwLjOvbpq1HLit4fPaepokSeqhvuwmLUlSt/RoAK2RiLi84fMpmXnKhHmI2B54D1UXaUmS1AesDEuSBl4PxkzYmJmrCuKfAjwZuLrOywrgyog4BFgHrGyIXVFPkyRJPWRlWJI04GLWH62Umd8D9hj/HBG3AKsyc2NEXAC8NSLOoRo4677MXD87OZUkaf7wnmFJkrosIs4Gvg08PSLWRsQbJgm/ELgZWAN8DnjLDGRRkqR5z5ZhSdLAm4lHyzXKzGOmmL9fw/sETux1niRJ0tasDEuSBlrQ2bM5JUnSYLMyLEkabDHzLcOSJKn/WRmWJA242R9AS5Ik9R/7jUmSJEmS5p2+bBlOYDS3tB0/FMPFaSyIhWXxw2Xxm8YeK4qH8u1YOFTW0hHRybWPLIoezrGi+I5aa0q7O2Z5GkMD0Io0Ey1hZWnM/X2quctu0tL0FP8NlRUfiA7KclHYpjNcvAmFG9GB/jtX+3up+aUvK8OSJHWT3aQlSVIzK8OSpIEWWBmWJEnbsjIsSRp8dvuTJElNHEBLkiRJkjTv2DIsSRpwPlpJkiRty8qwJGngOTqqJElqZmVYkjTwbBmWJEnNrAxLkgaelWFJktRsyspwRJwGvALYkJnPrKedCzy9DtkVuDczD2qx7C3AA8AosCUzV3Ul15IkSX3KspMkzQ3ttAyfDnwaOHN8Qmb+5vj7iPgYcN8ky78kMzd2mkFJkqYj8J5hzbjTsewkSX1vyspwZl4cEfu1mhdV6eI3gF/ocr4kSeoSR5PWzLLsJElzw3TvGf554M7MvGmC+Ql8LSIS+LvMPGWa6bU0lqPlCxWWixZE2a7KHCtLoAPDQ2V5Gi7cBijfji1sKYof6qCAOhzDRfGdFIJLl4koe2R3aTyU52mogzR6yaqIZpOVYfWRvig79dpM9MYo/bvOzJ6ufybYy0XqrulWho8Bzp5k/gszc11E7AFcFBHfz8yLWwVGxAnACQArVq6YZrYkSaqFBUj1la6UnRrLTSv3WdmbnErSgOu46SgiFgC/Cpw7UUxmrqv/3wCcDxwySewpmbkqM1ctXba002xJkiT1pW6WnRrLTcuWjfQiu5I08KbTj/KlwPczc22rmRGxQ0TsNP4eeBlw7TTSkySpI9Hlf1KHLDtJUh+ZsjIcEWcD3waeHhFrI+IN9ayjaermExF7R8SF9cc9gUsi4mrgO8B/ZOZXupd1SZKmNj6adDdf0mQsO0nS3NDOaNLHTDD9+BbTbgeOqt/fDBw4zfxJkjRNtuZqZll2kqS5ob+Gm5UkSZIkaQZMdzRpSZL6ni3DkiSpmZVhSdLA8z5fSZLUzMqwJGng2TIsSZKaWRmWJA20wMqwJEnalgNoSZIkSZLmHVuGJUkDzmcDS5KkbfVlZTgIFsTCtuO35ObiNEbHthTFj8VYWQIdFLyGCxvqF0TZ1zcUw0Xx0MF2F4Z3Yrhwu2G0OI2h0i6VfVjQTrIo3m6kGmwe39J850UxSc3sJi1JGmxRFYK7+ZoyyYjTImJDRFzbMO0vI+L7EXFNRJwfEbs2zHt3RKyJiBsj4uW92RGSJKmRlWFJ0sCLLv9rw+nAEU3TLgKemZnPBn4AvBsgIg4AjgaeUS/zmYgOuvJIkqQiVoYlSeqyzLwYuLtp2tcyc/wenUuBFfX71cA5mflYZv4IWAMcMmOZlSRpnurLe4YlSeqmHtwTPxIRlzd8PiUzTylY/vXAufX75VSV43Fr62mSJKmHrAxLkgZa9GY06Y2Zuaqj/ET8MbAFOKu7WZIkSSWsDEuSBl6/jJYeEccDrwAOz8zxId/XASsbwlbU0yRJUg95z7AkaeDNwgBa2+Yh4gjgncArM/PhhlkXAEdHxOKIeDKwP/CdaW+0JEmalC3DkiR1WUScDRxGdW/xWuB9VKNHLwYuqrttX5qZb8rM6yLiPOB6qu7TJ2Zm+QPSJUlSESvDkqSB14N7hieVmce0mHzqJPEfBj7cuxxJkqRmVoYlSQOvX+4ZliRJ/cPKsCRpoPVoNGlJkjTH9WVl+Korr9q4y+Ldb20xawTYONP5meW05+M2z9e0B32b9+3x+iVpXrryiv/buN2CHVqVm8BzmmkPbrrzIW3LTj3Wl5XhzFzWanpEXN7pcx2na7bSno/bPF/Tno/bLM0Uu0lrkE1UbgLPaaY9uOnO57TVPX1ZGZYkqbusDEuSpK1ZGZYkDTyrwpIkqdlcqwyfMg/Tno/bPF/Tno/bLM0IB9DSPOY5zbQHNd35nLa6JDJztvMgSVLPHHjws/Or3/yPrq5zr+33ucJ7xSRJmtvmWsuwJEkdsGVYkiRtzcqwJGngWRWWJEnNhmY7A80i4oiIuDEi1kTEu1rMXxwR59bzL4uI/bqU7sqI+EZEXB8R10XE21rEHBYR90XEVfXrvd1Iu173LRHxvXq9l7eYHxHxqXq7r4mIg7uU7tMbtueqiLg/It7eFNO17Y6I0yJiQ0Rc2zBt94i4KCJuqv/fbYJlj6tjboqI47qU9l9GxPfrfXp+ROw6wbKTfj8dpPv+iFjXsE+PmmDZSf8eOkz73IZ0b4mIqyZYtuNtlvpL9OAl9Q/LTpadelF2mq1y0yRpW3ZS92Vm37yAYeCHwE8Bi4CrgQOaYt4CnFy/Pxo4t0tp7wUcXL/fCfhBi7QPA/69R9t+CzAyyfyjgC9TlcIOBS7r0f6/A9i3V9sNvAg4GLi2YdpHgXfV798F/EWL5XYHbq7/361+v1sX0n4ZsKB+/xet0m7n++kg3fcD72jj+5j076GTtJvmfwx4b7e32ZevfnodePCz885H1nX1BVw+29vly1emZSfLTr0rO81WuWmStC07+er6q99ahg8B1mTmzZm5CTgHWN0Usxo4o37/z8DhEdMfJjQz12fmlfX7B4AbgOXTXW8XrQbOzMqlwK4RsVeX0zgc+GFm3trl9T4uMy8G7m6a3PidngG8qsWiLwcuysy7M/Me4CLgiOmmnZlfy8wt9cdLgRUl6+w03Ta18/fQcdr1381vAGd3kDdJUn+w7DQxy07TKDvNVrlporTbZNlJRfqtMrwcuK3h81q2/VF9PKb+Y7wPWNrNTNTdh54DXNZi9vMj4uqI+HJEPKOLySbwtYi4IiJOaDG/nX0zXUcz8R93r7YbYM/MXF+/vwPYs0XMTGz/66muILcy1ffTibfW3YxOm6B7U6+3+eeBOzPzpgnm92KbJUndZdnJstNslZ1mutwElp3UZf1WGZ51EbEj8EXg7Zl5f9PsK6m6wRwI/A3wL11M+oWZeTBwJHBiRLyoi+ueUkQsAl4J/FOL2b3c7q1kZlL9kMyoiPhjYAtw1gQh3f5+Pgs8BTgIWE/V5WamHcPkVzZn9ZiUuim6/E/SEyw7zb+y0yyUm8Cyk3qg3yrD64CVDZ9X1NNaxkTEAmAX4K5uJB4RC6l+zM/KzC81z8/M+zPzwfr9hcDCiBjpRtqZua7+fwNwPlU3j0bt7JvpOBK4MjPvbJG3nm137c7xbkv1/xtaxPRs+yPieOAVwG/XJ5RttPH9FMnMOzNzNDPHgM9NsL5ebvMC4FeBcyfJY1e3WZpNVoY1wCw7WXaa0bLTbJSb6nVZdlLX9Vtl+LvA/hHx5Ppq29HABU0xFwDjo+G9Gvivif4QS9T3AJwK3JCZH58g5knj99hExCFU+2/aJ5OI2CEidhp/TzU4wbVNYRcAr43KocB9Dd1jumHCK1292u4Gjd/pccC/toj5KvCyiNit7hbzsnratETEEcA7gVdm5sMTxLTz/ZSm23jP0q9MsL52/h469VLg+5m5doL8dX2bJUk9YdnJstOMlZ1mq9xUr8uyk7qur54znJlbIuKtVH+ow8BpmXldRHyQauTOC6h+dD8fEWuobm4/ukvJvwA4FvhePDFc+nuAfeq8nUx1AnlzRGwBHgGO7sbJhOo+j/Pr38wFwBcy8ysR8aaGtC+kGhVxDfAw8LoupAs8/gf7i8AbG6Y1pt217Y6Is6lGWByJiLXA+4CPAOdFxBuAW6kGJiAiVgFvyszfycy7I+JDVD9yAB/MzKKBFSZI+93AYuCiev9fmplvioi9gb/PzKOY4PuZZrqHRcRBVN2abqHe943pTvT3MN1tzsxTaXGPUze3WZI0Myw7WXaiR2Wn2So3TZK2ZSd1XXTn90iSpP500M8emF//1te6us6RJU+6IjNXdXWlkiRpRvVbN2lJkiRJknqur7pJS5LUfQ56JUmStmXLsCRJkiRp3rFlWJI0D9gyLEmStmZlWJI00AKrwpIkaVtWhiVJA69+1IUkSdLjrAxLkuYBK8OSJGlrDqAlSZIkSZp3bBmWJA0824UlSVIzK8OSpHnA6rAkSdqa3aQlSQMuiOjua8oUI06LiA0RcW3DtN0j4qKIuKn+f7d6ekTEpyJiTURcExEH93BnSJKkmpVhSZK673TgiKZp7wK+npn7A1+vPwMcCexfv04APjtDeZQkaV6zMixJUpdl5sXA3U2TVwNn1O/PAF7VMP3MrFwK7BoRe81IRiVJmse8Z1iSNNACiP64Z3jPzFxfv78D2LN+vxy4rSFubT1tPZIkqWesDEuS5oGuV4ZHIuLyhs+nZOYp7S6cmRkR2e1MSZKk9lkZliQNvB60C2/MzFWFy9wZEXtl5vq6G/SGevo6YGVD3Ip6miRJ6iHvGZYkDbyZHk16AhcAx9XvjwP+tWH6a+tRpQ8F7mvoTi1JknrElmFJkrosIs4GDqPqTr0WeB/wEeC8iHgDcCvwG3X4hcBRwBrgYeB1M55hSZLmISvDkqQBF/Sko/QkMvOYCWYd3iI2gRN7myNJktTMyrAkaeD1xVjSkiSpr1gZliTNA1aHJUnS1hxAS5IkSZI079gyLEkabMF0RoCWJEkDypZhSZIkSdK8Y8uwJGmgVWNJ2zIsSZK2FtUTHSRJGkwR8RVgpMur3ZiZR3R5nZIkaQZZGZYkSZIkzTveMyxJkiRJmnesDEuSJEmS5h0rw5IkSZKkecfKsCRJkiRp3rEyLEmSJEmad/5/lh6UEr+3aT0AAAAASUVORK5CYII=\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_G8=error(xdata8, poptG8[0], poptG8[1],poptG8[2], poptG8[3], poptG8[4], recorteG8.ravel(), inc=1)\n", + "poptG8E, pcovG8E = curve_fit(gauss2d, xdata8, recorteG8.ravel(), p0=[3,3,3,1,1],sigma=Err_G8)\n", + "estrellaG8E=gauss2d(xdata8, poptG8E[0], poptG8E[1],poptG8E[2], poptG8E[3], poptG8E[4])\n", + "FWHMG8E=FWHMG_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptG8E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 8 fotografÃa (Banda Verde)\")\n", + "plt.imshow(recorteG8, plt.get_cmap('Greens'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 8 a partir de la gaussiana con incertidumbre (Banda Verde)\")\n", + "plt.imshow(estrellaG8E.reshape(20, 20), plt.get_cmap('Greens'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 9 con incertidumbre (Banda Verde)" + ] + }, + { + "cell_type": "code", + "execution_count": 848, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_G9=error(xdata9, poptG9[0], poptG9[1],poptG9[2], poptG9[3], poptG9[4], recorteG9.ravel(), inc=1)\n", + "poptG9E, pcovG9E = curve_fit(gauss2d, xdata9, recorteG9.ravel(), p0=[5,6,6,1,1],sigma=Err_G9)\n", + "estrellaG9E=gauss2d(xdata9, poptG9E[0], poptG9E[1],poptG9E[2], poptG9E[3], poptG9E[4])\n", + "FWHMG9E=FWHMG_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptG9E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 9 fotografÃa (Banda Verde)\")\n", + "plt.imshow(recorteG9, plt.get_cmap('Greens'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 9 a partir de la gaussiana con incertidumbre (Banda Verde)\")\n", + "plt.imshow(estrellaG9E.reshape(10, 10), plt.get_cmap('Greens'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 10 con incertidumbre (Banda Verde)" + ] + }, + { + "cell_type": "code", + "execution_count": 849, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_G10=error(xdata10, poptG10[0], poptG10[1],poptG10[2], poptG10[3], poptG10[4], recorteG10.ravel(), inc=1)\n", + "poptG10E, pcovG10E = curve_fit(gauss2d, xdata10, recorteG10.ravel(), p0=[1,1,1,1,1],sigma=Err_G10)\n", + "estrellaG10E=gauss2d(xdata10, poptG10E[0], poptG10E[1],poptG10E[2], poptG10E[3], poptG10E[4])\n", + "FWHMG10E=FWHMG_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptG10E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 10 fotografÃa (Banda Verde)\")\n", + "plt.imshow(recorteG10, plt.get_cmap('Greens'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 10 a partir de la gaussiana con incertidumbre (Banda Verde)\")\n", + "plt.imshow(estrellaG10E.reshape(10, 10), plt.get_cmap('Greens'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Histograma con incertidumbres (Banda Verde)" + ] + }, + { + "cell_type": "code", + "execution_count": 850, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Datos de FWHM con incertidumbres de las estrellas para la Banda verde :\n", + "Desviación : 2.525343798913612\n", + "Media : 4.246485293065105\n", + "Mediana : 3.173731685005169\n" + ] + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "FWHMG_I = np.array(FWHMG_I )\n", + "sigmaG_I = FWHMG_I .std()\n", + "mediaG_I = FWHMG_I .mean()\n", + "medianaG_I = np.median(FWHMG_I )\n", + "print(\"Datos de FWHM con incertidumbres de las estrellas para la Banda verde :\")\n", + "print(\"Desviación :\", sigmaG_I )\n", + "print(\"Media :\", mediaG_I )\n", + "print(\"Mediana :\", medianaG_I )\n", + "plt.hist(FWHMG_I )\n", + "plt.xlabel('FHWM')\n", + "plt.ylabel('# de estrellas')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 1 con incertidumbre (Banda Azul)" + ] + }, + { + "cell_type": "code", + "execution_count": 851, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_B1=error(xdata1, poptB1[0], poptB1[1],poptB1[2], poptB1[3], poptB1[4], recorteB1.ravel(), inc=1)\n", + "poptB1E, pcovB1E = curve_fit(gauss2d, xdata1, recorteB1.ravel(), p0=[3,3,2,1,1],sigma=Err_B1)\n", + "estrellaB1E=gauss2d(xdata1, poptB1E[0], poptB1E[1],poptB1E[2], poptB1E[3], poptB1E[4])\n", + "FWHMB1E=FWHMB_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptB1E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 1 fotografÃa (Banda Azul)\")\n", + "plt.imshow(recorteB1, plt.get_cmap('Blues'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 1 a partir de la gaussiana con incertidumbre (Banda Azul)\")\n", + "plt.imshow(estrellaB1E.reshape(15, 15), plt.get_cmap('Blues'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 2 con incertidumbre (Banda Azul)" + ] + }, + { + "cell_type": "code", + "execution_count": 852, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_B2=error(xdata2, poptB2[0], poptB2[1],poptB2[2], poptB2[3], poptB2[4], recorteB2.ravel(), inc=1)\n", + "poptB2E, pcovB2E = curve_fit(gauss2d, xdata2, recorteB2.ravel(), p0=[4,4,4,1,1], sigma= Err_B2)\n", + "estrellaB2E=gauss2d(xdata2, poptB2E[0], poptB2E[1],poptB2E[2], poptB2E[3], poptB2E[4])\n", + "FWHMB2E=FWHMB_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptB2E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 2 fotografÃa (Banda Azul)\")\n", + "plt.imshow(recorteB2, plt.get_cmap('Blues'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 2 a partir de la gaussiana con incertidumbre (Banda Azul)\")\n", + "plt.imshow(estrellaB2E.reshape(35, 35), plt.get_cmap('Blues'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 3 con incertidumbre (Banda Azul)" + ] + }, + { + "cell_type": "code", + "execution_count": 853, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_B3=error(xdata3, poptB3[0], poptB3[1],poptB3[2], poptB3[3], poptB3[4], recorteB3.ravel(), inc=1)\n", + "poptB3E, pcovB3E = curve_fit(gauss2d, xdata3, recorteB3.ravel(), p0=[4,4,5,1,1],sigma=Err_B3)\n", + "estrellaB3E=gauss2d(xdata3, poptB3E[0], poptB3E[1],poptB3E[2], poptB3E[3], poptB3E[4])\n", + "FWHMB3E=FWHMB_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptB3E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 3 fotografÃa (Banda Azul)\")\n", + "plt.imshow(recorteB3, plt.get_cmap('Blues'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 3 a partir de la gaussiana con incertidumbre (Banda Azul)\")\n", + "plt.imshow(estrellaB3E.reshape(15, 15), plt.get_cmap('Blues'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 4 con incertidumbre (Banda Azul)" + ] + }, + { + "cell_type": "code", + "execution_count": 854, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_B4=error(xdata4, poptB4[0], poptB4[1],poptB4[2], poptB4[3], poptB4[4], recorteB4.ravel(), inc=1)\n", + "poptB4E, pcovB4E = curve_fit(gauss2d, xdata4, recorteB4.ravel(), p0=[2,2,2,1,1],sigma=Err_B4)\n", + "estrellaB4E=gauss2d(xdata4, poptB4E[0], poptB4E[1],poptB4E[2], poptB4E[3], poptB4E[4])\n", + "FWHMB4E=FWHMB_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptB4E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 4 fotografÃa (Banda Azul)\")\n", + "plt.imshow(recorteB4, plt.get_cmap('Blues'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 4 a partir de la gaussiana con incertidumbre (Banda Azul)\")\n", + "plt.imshow(estrellaB4E.reshape(15, 15), plt.get_cmap('Blues'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 5 con incertidumbre (Banda Azul)" + ] + }, + { + "cell_type": "code", + "execution_count": 855, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_B5=error(xdata5, poptB5[0], poptB5[1],poptB5[2], poptB5[3], poptB5[4], recorteB5.ravel(), inc=1)\n", + "poptB5E, pcovB5E = curve_fit(gauss2d, xdata5, recorteB5.ravel(), p0=[2,0,1,1,1], sigma=Err_B5)\n", + "estrellaB5E=gauss2d(xdata5, poptB5E[0], poptB5E[1],poptB5E[2], poptB5E[3], poptB5E[4])\n", + "FWHMB5E=FWHMB_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptB5E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 5 fotografÃa (Banda Azul)\")\n", + "plt.imshow(recorteB5, plt.get_cmap('Blues'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 5 a partir de la gaussiana con incertidumbre (Banda Azul)\")\n", + "plt.imshow(estrellaB5E.reshape(15, 15), plt.get_cmap('Blues'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 6 con incertidumbre (Banda Azul)" + ] + }, + { + "cell_type": "code", + "execution_count": 856, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_B6=error(xdata6, poptB6[0], poptB6[1],poptB6[2], poptB6[3], poptB6[4], recorteB6.ravel(), inc=1)\n", + "poptB6E, pcovB6E = curve_fit(gauss2d, xdata6, recorteB6.ravel(), p0=[2,1,1,1,1], sigma=Err_B6)\n", + "estrellaB6E=gauss2d(xdata6, poptB6E[0], poptB6E[1],poptB6E[2], poptB6E[3], poptB6E[4])\n", + "FWHMB6E=FWHMB_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptB6E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 6 fotografÃa (Banda Azul)\")\n", + "plt.imshow(recorteB6, plt.get_cmap('Blues'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 6 a partir de la gaussiana con incertidumbre (Banda Azul)\")\n", + "plt.imshow(estrellaB6E.reshape(10, 10), plt.get_cmap('Blues'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 7 con incertidumbre (Banda Azul)" + ] + }, + { + "cell_type": "code", + "execution_count": 857, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_B7=error(xdata7, poptB7[0], poptB7[1],poptB7[2], poptB7[3], poptB7[4], recorteB7.ravel(), inc=1)\n", + "poptB7E, pcovB7E = curve_fit(gauss2d, xdata7, recorteB7.ravel(), p0=[3,3,3,1,1],sigma=Err_B7)\n", + "estrellaB7E=gauss2d(xdata7, poptB7E[0], poptB7E[1],poptB7E[2], poptB7E[3], poptB7E[4])\n", + "FWHMB7E=FWHMB_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptB7E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 7 fotografÃa (Banda Azul)\")\n", + "plt.imshow(recorteB7, plt.get_cmap('Blues'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 7 a partir de la gaussiana con incertidumbre (Banda Azul)\")\n", + "plt.imshow(estrellaB7E.reshape(10, 10), plt.get_cmap('Blues'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 8 con incertidumbre (Banda Azul)" + ] + }, + { + "cell_type": "code", + "execution_count": 858, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_B8=error(xdata8, poptB8[0], poptB8[1],poptB8[2], poptB8[3], poptB8[4], recorteB8.ravel(), inc=1)\n", + "poptB8E, pcovB8E = curve_fit(gauss2d, xdata8, recorteB8.ravel(), p0=[1,1,1,1,1], sigma=Err_B8)\n", + "estrellaB8E=gauss2d(xdata8, poptB8E[0], poptB8E[1],poptB8E[2], poptB8E[3], poptB8E[4])\n", + "FWHMB8E=FWHMB_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptB8E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 8 fotografÃa (Banda Azul)\")\n", + "plt.imshow(recorteB8, plt.get_cmap('Blues'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 8 a partir de la gaussiana con incertidumbre (Banda Azul)\")\n", + "plt.imshow(estrellaB8E.reshape(20, 20), plt.get_cmap('Blues'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 9 con incertidumbre (Banda Azul)" + ] + }, + { + "cell_type": "code", + "execution_count": 859, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_B9=error(xdata9, poptB9[0], poptB9[1],poptB9[2], poptB9[3], poptB9[4], recorteB9.ravel(), inc=1)\n", + "poptB9E, pcovB9E = curve_fit(gauss2d, xdata9, recorteB9.ravel(), p0=[1,1,1,1,1],sigma=Err_B9)\n", + "estrellaB9E=gauss2d(xdata9, poptB9E[0], poptB9E[1],poptB9E[2], poptB9E[3], poptB9E[4])\n", + "FWHMB9E=FWHMB_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptB9E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 9 fotografÃa (Banda Azul)\")\n", + "plt.imshow(recorteB9, plt.get_cmap('Blues'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 9 a partir de la gaussiana con incertidumbre (Banda Azul)\")\n", + "plt.imshow(estrellaB9E.reshape(10, 10), plt.get_cmap('Blues'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Estrella 10 con incertidumbre (Banda Azul)" + ] + }, + { + "cell_type": "code", + "execution_count": 860, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x1080 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Err_B10=error(xdata10, poptB10[0], poptB10[1],poptB10[2], poptB10[3], poptB10[4], recorteB10.ravel(), inc=1)\n", + "poptB10E, pcovB10E = curve_fit(gauss2d, xdata10, recorteB10.ravel(), p0=[3,2,2,1,1],sigma=Err_B10)\n", + "estrellaB10E=gauss2d(xdata10, poptB10E[0], poptB10E[1],poptB10E[2], poptB10E[3], poptB10E[4])\n", + "FWHMB10E=FWHMB_I.append(2*np.sqrt(2*np.log(2))*np.sqrt(poptB10E[4]))\n", + "fig=plt.figure(figsize=(15, 15))\n", + "pos = fig.add_axes([0.5,0.35,0.02,0.3])\n", + "plt.subplot(131)\n", + "plt.title(\"Estrella 10 fotografÃa (Banda Azul)\")\n", + "plt.imshow(recorteB10, plt.get_cmap('Blues'))\n", + "plt.subplot(133)\n", + "plt.title(\"Estrella 10 a partir de la gaussiana con incertidumbre (Banda Azul)\")\n", + "plt.imshow(estrellaB10E.reshape(10, 10), plt.get_cmap('Blues'))\n", + "plt.colorbar(cax=pos)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Histograma con incertidumbres (Banda Azul)" + ] + }, + { + "cell_type": "code", + "execution_count": 861, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Datos de FWHM con incertidumbres de las estrellas para la Banda azul :\n", + "Desviación : 2.6951116878528705\n", + "Media : 4.515986827150282\n", + "Mediana : 3.49839915953825\n" + ] + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "FWHMB_I = np.array(FWHMB_I)\n", + "sigmaB_I = FWHMB_I.std()\n", + "mediaB_I = FWHMB_I.mean()\n", + "medianaB_I = np.median(FWHMB_I)\n", + "print(\"Datos de FWHM con incertidumbres de las estrellas para la Banda azul :\")\n", + "print(\"Desviación :\", sigmaB_I)\n", + "print(\"Media :\", mediaB_I)\n", + "print(\"Mediana :\", medianaB_I)\n", + "plt.hist(FWHMB_I)\n", + "plt.xlabel('FHWM')\n", + "plt.ylabel('# de estrellas')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* ## Resumen de resultados:" + ] + }, + { + "cell_type": "code", + "execution_count": 897, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1mLos valores estadÃsticos obtenidos para el Full Width at Half Maximum (FHWM) son:\n" + ] + }, + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>D-E</th>\n", + " <th>Media</th>\n", + " <th>Mediana</th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>Blanco/Negro</th>\n", + " <td>2.506520</td>\n", + " <td>4.223188</td>\n", + " <td>3.141966</td>\n", + " </tr>\n", + " <tr>\n", + " <th>Blanco/Negro con incertidumbre</th>\n", + " <td>2.329890</td>\n", + " <td>4.021187</td>\n", + " <td>2.919205</td>\n", + " </tr>\n", + " <tr>\n", + " <th>B-Rojo</th>\n", + " <td>2.525571</td>\n", + " <td>4.242802</td>\n", + " <td>3.182727</td>\n", + " </tr>\n", + " <tr>\n", + " <th>B-Rojo con incertidumbre</th>\n", + " <td>2.699912</td>\n", + " <td>4.508061</td>\n", + " <td>3.482339</td>\n", + " </tr>\n", + " <tr>\n", + " <th>B-Verde</th>\n", + " <td>2.507212</td>\n", + " <td>4.216827</td>\n", + " <td>3.122942</td>\n", + " </tr>\n", + " <tr>\n", + " <th>B-Verde con incertidumbre</th>\n", + " <td>2.344335</td>\n", + " <td>4.008533</td>\n", + " <td>2.919655</td>\n", + " </tr>\n", + " <tr>\n", + " <th>B-Azul</th>\n", + " <td>2.525344</td>\n", + " <td>4.246485</td>\n", + " <td>3.173732</td>\n", + " </tr>\n", + " <tr>\n", + " <th>B-Azul con incertidumbre</th>\n", + " <td>2.695112</td>\n", + " <td>4.515987</td>\n", + " <td>3.498399</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "</div>" + ], + "text/plain": [ + " D-E Media Mediana\n", + "Blanco/Negro 2.506520 4.223188 3.141966\n", + "Blanco/Negro con incertidumbre 2.329890 4.021187 2.919205\n", + "B-Rojo 2.525571 4.242802 3.182727\n", + "B-Rojo con incertidumbre 2.699912 4.508061 3.482339\n", + "B-Verde 2.507212 4.216827 3.122942\n", + "B-Verde con incertidumbre 2.344335 4.008533 2.919655\n", + "B-Azul 2.525344 4.246485 3.173732\n", + "B-Azul con incertidumbre 2.695112 4.515987 3.498399" + ] + }, + "execution_count": 897, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import pandas as pd\n", + "# -- crear un data frame con esa información\n", + "# -- crear un array con todas las cantidades calculadas anteriormente para el FWHM\n", + "datos = np.array([[sigmaBN,mediaBN,medianaBN],\n", + " [sigmaR,mediaR,medianaR],\n", + " [sigmaG,mediaG,medianaG],\n", + " [sigmaB,mediaB,medianaB],\n", + " [sigmaBN_I,mediaBN_I,medianaBN_I],\n", + " [sigmaR_I,mediaR_I,medianaR_I],\n", + " [sigmaG_I,mediaG_I,medianaG_I],\n", + " [sigmaB_I,mediaB_I,medianaB_I]])\n", + "\n", + "print('\\033[1m' + 'Los valores estadÃsticos obtenidos para el Full Width at Half Maximum (FHWM) son:' )\n", + "FWHM_tabla = pd.DataFrame(datos,\n", + " columns=['D-E','Media','Mediana'], \n", + " index=['Blanco/Negro','Blanco/Negro con incertidumbre',\n", + " 'B-Rojo','B-Rojo con incertidumbre',\n", + " 'B-Verde','B-Verde con incertidumbre',\n", + " 'B-Azul','B-Azul con incertidumbre'])\n", + "FWHM_tabla" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* # Comentarios y conclusiones:" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* #### Fue posible implementar la función curve_fit para modelar la gaussiana sin mayores inconvenientes, sin embargo, la determinación de los parámetros sugeridos p0 fue totalmente aleatoria de tal manera que presentaba bastantes inconvenientes para algunos valores, y variaciones en los resultados bastante notables en el ingreso de diferentes enteros, como por ejemplo tomando x0=0 o y0=0 , el valor sugerido en p0 para la constante aditiva b de la gaussiana fue la que más cambio en los diferentes 8 resultados estadÃsticos del cálculo del FHWM, la segunda constante en más variar fue la multiplicativa de amplitud a. \n", + "\n", + "* #### Los resultados obtenidos para los análisis a blanco y negro se tomarón de la función lÃneal de Luma, como recomendación de algunos sitios web [1]. No se automatizó el plot de cada imagen ni la aplicación del modelo para cada una de las estrellas por que se estaban presentando errores de acumulación de datos en los arrays y listas, decidà hacerlo para cada una de tal manera que pudisese aprovechar esto y modificar algunos detalles para cada estrella, cómo: tamaño rejilla, titulos, añadidura de incertidumbres al fit y cambio en los p0 para cada uno de los tratamientos. \n", + "\n", + "* #### Al comparar los resultados obtenidos sin incertidumbres para los valores estadÃsticos del FHWM se observa que los canales rojo y azul tienen tanto mayor desviación como mayor FWHM que el canal verde y los resultados para los recortes blanco y negro, por lo que estos dos ultimos son los más considerables para modelar.\n", + "\n", + "* #### Al aplicar el módelo a todos los procedimientos, pero teniendo en cuenta la incertidumbre, los valores de p0 se hicieron mucho más variados que en los realizados sin incertidumbre. Razón por la cual es probable que justifique el hecho de que las desviaciones para los resultados de los valores estadÃsticos obtenidos del FHWM sean mayores en los casos de la bandas rojo y azul. El valor de la constante aditiva b de la gaussiana en la mayorÃa de los casos sin incertidumbre era cercano a 0 mientras que con incertidumbre tomaba siempre el mayor valor que todas las otras constantes, en especial en los casos de las bandas rojo y azul. Por lo que una vez más se presentan mejores resultados para el análisis a blanco y negro y para la banda verde.\n", + "\n", + "* #### Los valores obtenidos para el FWHM no varian significativamente con o sin incertidumbre, en la mayorÃa de todos los resultados el FWHM estaba entre 2 y 4, a excepsión de curiosamente la estrella más luminosa de la fotografÃa, la estrella 2, la cual presentaba FWHM alrededor de 11, como FWHM es el ancho de la gaussiana en su punto medio, podrÃa decirse que la estrella 2 es la más \"desenfocada\" de la fotografÃa por ser el objeto (o varios) de mayor tamaño. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/README.md b/README.md index 4faac69..3bf36c7 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,61 @@ # Ejercicios para practicar numpy y optimización con scipy +**NUEVO PLAZO DE ENTREGA: Feb/18 a la media noche COL/PER/ECU - 1:00 a.m del 19/02 VEN** + + +# ADICIONES - FEB/17 + +## Para quienes tengan dificultad en comprender el ajuste sobre la región 2D + +Pueden empezar resolviendo un problema más sencillo, de nuevo en 1 dimensión +asà como en el ejemplo de la clase. En este caso, después de recortar el cuadradito +de una estrella, vamos a tomar solo los pixeles de la lÃnea que pasa por la mitad +de la estrella, es decir tenemos un vector de valores de intensidad luminosa. +Si los grafican, deben obtener algo similar a esto: + + +La idea entonces es ajustar una función gaussiana común y corriente, agregando una +constante aditiva. Cuando dominen este problema (y escriban su solución para entregar) +pueden retomar el problema original a ver si lo entienden mejor. + +La diferencia será +que ya no tendrán una función de una variable, si no de dos. Es decir: + +* En el problema +simplificado tenemos $y=y(x)$. 'x' es nuestra variable independiente y representa las +distintas posiciones a lo largo de la linea 1D, mientras 'y', que representa las +intensidades luminosas en cada posición, es nuestra variable dependiente, los datos +a los cuales deseamos ajustar el modelo + +* En el problema planteado originalmente se desea ajustar una función de 2 variables: +$z=z(x,y)$. 'x','y' son las variables independientes, y juntas representan todas las +posiciones sobre el cuadrito 2D del recorte de la estrella; deberán usar meshgrid +para obtener todas las combinaciones (fila, columna) de los pixeles en la imagen. +Por su parte, 'z', que es la variable dependiente, es el brillo de cada pixel, y +corresponde a los valores que vienen almacenados en la propia imagen. Esos valores +de 'z' son nuestros datos, a los cuales queremos ajustar el modelo de gaussiana 2D, +algo del estilo: zmodel = gauss2D(x,y) + +Una vez logren ajustar una de esas gausianas 1D, la idea es repetir en varias estrellas +y sacar una estadÃstica sobre el ancho de ellas. + + +## Para quienes ya dominaron el ejercicio inicial + +Olvidé comentar sobre la incertidumbre, que obviamente existe siempre que tomamos +cualquier medida. En el caso de las imágenes, el conteo de fotones es un proceso que +sigue la estadÃstica de Poisson, y si el flujo luminoso es grande (llegan muchos fotones) +esto acaba derivando en una estadÃstica gaussiana. En ese caso podemos modelar la +incertidumbre como la raÃz cuadrada del flujo observado. + +Como ejercicio final, repita los ajustes realizados inicialmente, esta vez teniendo +en cuenta la incertidumbre de los datos, para ver si surge algún cambio en los resultados. +Encuentre una forma de programar sus rutinas de modo que sean fácilmente reutilizables; +con una buena implementación, este nuevo ajuste debe ser cuestión de un par de minutos +con pocos o ningún paso manual. + + + ## Resolución espacial En observaciones astronómicas e imágenes en general, llamamos resolución espacial -- GitLab