diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000000000000000000000000000000000000..87620ac7e74efee566c6ee9d2ed7281ebafb4788 --- /dev/null +++ b/.gitignore @@ -0,0 +1 @@ +.ipynb_checkpoints/ diff --git a/ENTREGA.ipynb b/ENTREGA.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..ebdaa1e7e81860faf8880b9a8a6b444d259a366f --- /dev/null +++ b/ENTREGA.ipynb @@ -0,0 +1,1300 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# David Ramos - UIS" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Ejercicio 1" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Investigue sobre el diagrama de Hertzsprung-Russell, una herramienta muy\n", + "potente en astronomia, y describa un poco al respecto para darle contexto al\n", + "resto de la tarea**" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "El diagrama de Hertzsprung-Russell es un gráfico entre la luminosidad (o variables equivalentes) y la temperatura efectiva (o variables independientes) de un conjunto de estrellas. La información valiosa que este gráfico muestra es que la luminosidad y temperatura de las estrellas no están distribuidas aleatoreamente sino que se agrupan en ciertas regiones, las cuales se han identificado como diferentes fases de la vida de una estrella. Asà pues, a lo largo de su vida, una estrella sigue un camino evolutivo sobre el diagrama (el camino preciso dependerá de cuánta masa de gas tenÃa la estrella cuando fue formada)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**El objetivo es generar un diagrama HR lo más parecido al de esta referencia. No lucirá idéntico por que no se usarán exactamente los mismos datos, y las unidades pueden ser ligeramente distinta. La idea sà es dejar su figura lo más parecida a la de referencia en el estilo: colores, escalas en los ejes, tamaño de los marcadores, leyendas, textos en el gráfico, etc.**" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Los datos para crear la figura están en la carpeta *data*. Cada tabla contiene las informaciones sobre un tipo de estrellas según indican los nombres de archivo. La información viene en 3 columnas: luminosidad en luminosidades solares, Temperatura en Kelvin y Radio de la estrella en unidades arbitrarias**" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Primero cargo los datos" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from matplotlib import rc\n", + "import matplotlib.ticker" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "ms = np.loadtxt('data/ms.csv', delimiter =',', skiprows = 1, unpack = True)\n", + "giants = np.loadtxt('data/giants.txt', delimiter =' ', skiprows = 1, unpack = True)\n", + "supergiants = np.loadtxt('data/supergiants.txt', delimiter =' ', skiprows = 1, unpack = True)\n", + "dwarfs = np.loadtxt('data/dwarfs.csv', delimiter =',', skiprows = 1, unpack = True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Algunas personalizaciones generales como el tamaño y el tipo de letra de los labels y ticks" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "rc('axes', linewidth = 1.3, labelweight = 'bold', labelsize = '18')\n", + "rc('font', weight = 'bold')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Ahora sà creo el gráfico" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1008x864 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# creo el bastidor\n", + "\n", + "fig, ax = plt.subplots(figsize=(14,12))\n", + "\n", + "# personalización de los ejes\n", + "\n", + "\n", + "# escala logarÃtmica en ambos ejes\n", + "ax.set_xscale('log')\n", + "ax.set_yscale('log')\n", + "\n", + "# elimino los ejes superior y derecho\n", + "ax.spines['right'].set_visible(False)\n", + "ax.spines['top'].set_visible(False)\n", + "\n", + "# fijo el tamaño de los números de eje\n", + "ax.tick_params(axis='both', which='major', labelsize=12)\n", + "\n", + "# especifico los ticks que aparecen\n", + "ax.set_xticks([5000,10000])\n", + "ax.set_xticks([], minor=True)\n", + "\n", + "# elimino la notación cientÃfica del eje x\n", + "ax.get_xaxis().set_major_formatter(matplotlib.ticker.ScalarFormatter())\n", + "ax.get_xaxis().set_minor_formatter(matplotlib.ticker.NullFormatter())\n", + "\n", + "# nombro los ejes\n", + "ax.set_xlabel('Temperature (K)')\n", + "ax.set_ylabel('Luminosity (L$_{sun}$)')\n", + "\n", + "# invierto el eje x\n", + "ax.invert_xaxis()\n", + "\n", + "\n", + "# escala de color\n", + "\n", + "# defino la escala de colores como los valores extremos de la intensidad\n", + "allTemps = np.concatenate([ms[1], giants[1], supergiants[1],dwarfs[1]], axis=0)\n", + "min_T, max_T = allTemps.min(), allTemps.max()\n", + "\n", + "\n", + "\n", + "# grafico los datos, tomando la superficie de cada marcador proporcional a su radio\n", + "\n", + "ax.scatter(ms[1],ms[0],s = 20*ms[2], c = ms[1], cmap = 'RdYlBu', vmin = min_T, vmax = max_T,\n", + " linewidths=1.5, edgecolor = 'grey')\n", + "\n", + "ax.scatter(giants[1],giants[0],s = 20*giants[2], c = giants[1], cmap = 'RdYlBu', vmin = min_T, vmax = max_T,\n", + " linewidths=1.5, edgecolor = 'grey')\n", + "\n", + "ax.scatter(supergiants[1], supergiants[0],s = 20*supergiants[2], c = supergiants[1], cmap = 'RdYlBu',\n", + " vmin = min_T, vmax = max_T, linewidths=1.5, edgecolor = 'grey')\n", + "\n", + "ax.scatter(dwarfs[1], dwarfs[0],s = 20*dwarfs[2], c = 'white', linewidths=1.5, edgecolor = 'grey')\n", + "\n", + "\n", + "# añado etiquetas de cada conjunto de estrellas como texto\n", + "\n", + "ax.text(5500,0.01,'Main Sequence', fontsize = 20, weight = 'bold')\n", + "ax.text(13000,6,'Main Sequence', fontsize = 20, weight = 'bold')\n", + "ax.text(4500,2,'Red Giants', fontsize = 20, weight = 'bold')\n", + "ax.text(5000,0.3e7,'Red Supergiants', fontsize = 20, weight = 'bold')\n", + "ax.text(11500,0.3e7,'Blue Giants', fontsize = 20, weight = 'bold')\n", + "ax.text(10000,0.002,'White Dwarfs', fontsize = 20, weight = 'bold')\n", + "\n", + "\n", + "plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Ejercicio 2" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Después de tener un diseño de base para el ejercicio No. 1, en este ejercicio se pide generar una animación, en la cual se reproduzca el miso gráfico de antes pero las estrellas vayan apareciendo progresivamente.**" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "%matplotlib notebook\n", + "from matplotlib.animation import FuncAnimation" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "application/javascript": [ + "/* Put everything inside the global mpl namespace */\n", + "/* global mpl */\n", + "window.mpl = {};\n", + "\n", + "mpl.get_websocket_type = function () {\n", + " if (typeof WebSocket !== 'undefined') {\n", + " return WebSocket;\n", + " } else if (typeof MozWebSocket !== 'undefined') {\n", + " return MozWebSocket;\n", + " } else {\n", + " alert(\n", + " 'Your browser does not have WebSocket support. ' +\n", + " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", + " 'Firefox 4 and 5 are also supported but you ' +\n", + " 'have to enable WebSockets in about:config.'\n", + " );\n", + " }\n", + "};\n", + "\n", + "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", + " this.id = figure_id;\n", + "\n", + " this.ws = websocket;\n", + "\n", + " this.supports_binary = this.ws.binaryType !== undefined;\n", + "\n", + " if (!this.supports_binary) {\n", + " var warnings = document.getElementById('mpl-warnings');\n", + " if (warnings) {\n", + " warnings.style.display = 'block';\n", + " warnings.textContent =\n", + " 'This browser does not support binary websocket messages. ' +\n", + " 'Performance may be slow.';\n", + " }\n", + " }\n", + "\n", + " this.imageObj = new Image();\n", + "\n", + " this.context = undefined;\n", + " this.message = undefined;\n", + " this.canvas = undefined;\n", + " this.rubberband_canvas = undefined;\n", + " this.rubberband_context = undefined;\n", + " this.format_dropdown = undefined;\n", + "\n", + " this.image_mode = 'full';\n", + "\n", + " this.root = document.createElement('div');\n", + " this.root.setAttribute('style', 'display: inline-block');\n", + " this._root_extra_style(this.root);\n", + "\n", + " parent_element.appendChild(this.root);\n", + "\n", + " this._init_header(this);\n", + " this._init_canvas(this);\n", + " this._init_toolbar(this);\n", + "\n", + " var fig = this;\n", + "\n", + " this.waiting = false;\n", + "\n", + " this.ws.onopen = function () {\n", + " fig.send_message('supports_binary', { value: fig.supports_binary });\n", + " fig.send_message('send_image_mode', {});\n", + " if (fig.ratio !== 1) {\n", + " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", + " }\n", + " fig.send_message('refresh', {});\n", + " };\n", + "\n", + " this.imageObj.onload = function () {\n", + " if (fig.image_mode === 'full') {\n", + " // Full images could contain transparency (where diff images\n", + " // almost always do), so we need to clear the canvas so that\n", + " // there is no ghosting.\n", + " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", + " }\n", + " fig.context.drawImage(fig.imageObj, 0, 0);\n", + " };\n", + "\n", + " this.imageObj.onunload = function () {\n", + " fig.ws.close();\n", + " };\n", + "\n", + " this.ws.onmessage = this._make_on_message_function(this);\n", + "\n", + " this.ondownload = ondownload;\n", + "};\n", + "\n", + "mpl.figure.prototype._init_header = function () {\n", + " var titlebar = document.createElement('div');\n", + " titlebar.classList =\n", + " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", + " var titletext = document.createElement('div');\n", + " titletext.classList = 'ui-dialog-title';\n", + " titletext.setAttribute(\n", + " 'style',\n", + " 'width: 100%; text-align: center; padding: 3px;'\n", + " );\n", + " titlebar.appendChild(titletext);\n", + " this.root.appendChild(titlebar);\n", + " this.header = titletext;\n", + "};\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", + "\n", + "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", + "\n", + "mpl.figure.prototype._init_canvas = function () {\n", + " var fig = this;\n", + "\n", + " var canvas_div = (this.canvas_div = document.createElement('div'));\n", + " canvas_div.setAttribute(\n", + " 'style',\n", + " 'border: 1px solid #ddd;' +\n", + " 'box-sizing: content-box;' +\n", + " 'clear: both;' +\n", + " 'min-height: 1px;' +\n", + " 'min-width: 1px;' +\n", + " 'outline: 0;' +\n", + " 'overflow: hidden;' +\n", + " 'position: relative;' +\n", + " 'resize: both;'\n", + " );\n", + "\n", + " function on_keyboard_event_closure(name) {\n", + " return function (event) {\n", + " return fig.key_event(event, name);\n", + " };\n", + " }\n", + "\n", + " canvas_div.addEventListener(\n", + " 'keydown',\n", + " on_keyboard_event_closure('key_press')\n", + " );\n", + " canvas_div.addEventListener(\n", + " 'keyup',\n", + " on_keyboard_event_closure('key_release')\n", + " );\n", + "\n", + " this._canvas_extra_style(canvas_div);\n", + " this.root.appendChild(canvas_div);\n", + "\n", + " var canvas = (this.canvas = document.createElement('canvas'));\n", + " canvas.classList.add('mpl-canvas');\n", + " canvas.setAttribute('style', 'box-sizing: content-box;');\n", + "\n", + " this.context = canvas.getContext('2d');\n", + "\n", + " var backingStore =\n", + " this.context.backingStorePixelRatio ||\n", + " this.context.webkitBackingStorePixelRatio ||\n", + " this.context.mozBackingStorePixelRatio ||\n", + " this.context.msBackingStorePixelRatio ||\n", + " this.context.oBackingStorePixelRatio ||\n", + " this.context.backingStorePixelRatio ||\n", + " 1;\n", + "\n", + " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", + "\n", + " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", + " 'canvas'\n", + " ));\n", + " rubberband_canvas.setAttribute(\n", + " 'style',\n", + " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", + " );\n", + "\n", + " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", + " if (this.ResizeObserver === undefined) {\n", + " if (window.ResizeObserver !== undefined) {\n", + " this.ResizeObserver = window.ResizeObserver;\n", + " } else {\n", + " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", + " this.ResizeObserver = obs.ResizeObserver;\n", + " }\n", + " }\n", + "\n", + " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", + " var nentries = entries.length;\n", + " for (var i = 0; i < nentries; i++) {\n", + " var entry = entries[i];\n", + " var width, height;\n", + " if (entry.contentBoxSize) {\n", + " if (entry.contentBoxSize instanceof Array) {\n", + " // Chrome 84 implements new version of spec.\n", + " width = entry.contentBoxSize[0].inlineSize;\n", + " height = entry.contentBoxSize[0].blockSize;\n", + " } else {\n", + " // Firefox implements old version of spec.\n", + " width = entry.contentBoxSize.inlineSize;\n", + " height = entry.contentBoxSize.blockSize;\n", + " }\n", + " } else {\n", + " // Chrome <84 implements even older version of spec.\n", + " width = entry.contentRect.width;\n", + " height = entry.contentRect.height;\n", + " }\n", + "\n", + " // Keep the size of the canvas and rubber band canvas in sync with\n", + " // the canvas container.\n", + " if (entry.devicePixelContentBoxSize) {\n", + " // Chrome 84 implements new version of spec.\n", + " canvas.setAttribute(\n", + " 'width',\n", + " entry.devicePixelContentBoxSize[0].inlineSize\n", + " );\n", + " canvas.setAttribute(\n", + " 'height',\n", + " entry.devicePixelContentBoxSize[0].blockSize\n", + " );\n", + " } else {\n", + " canvas.setAttribute('width', width * fig.ratio);\n", + " canvas.setAttribute('height', height * fig.ratio);\n", + " }\n", + " canvas.setAttribute(\n", + " 'style',\n", + " 'width: ' + width + 'px; height: ' + height + 'px;'\n", + " );\n", + "\n", + " rubberband_canvas.setAttribute('width', width);\n", + " rubberband_canvas.setAttribute('height', height);\n", + "\n", + " // And update the size in Python. We ignore the initial 0/0 size\n", + " // that occurs as the element is placed into the DOM, which should\n", + " // otherwise not happen due to the minimum size styling.\n", + " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", + " fig.request_resize(width, height);\n", + " }\n", + " }\n", + " });\n", + " this.resizeObserverInstance.observe(canvas_div);\n", + "\n", + " function on_mouse_event_closure(name) {\n", + " return function (event) {\n", + " return fig.mouse_event(event, name);\n", + " };\n", + " }\n", + "\n", + " rubberband_canvas.addEventListener(\n", + " 'mousedown',\n", + " on_mouse_event_closure('button_press')\n", + " );\n", + " rubberband_canvas.addEventListener(\n", + " 'mouseup',\n", + " on_mouse_event_closure('button_release')\n", + " );\n", + " // Throttle sequential mouse events to 1 every 20ms.\n", + " rubberband_canvas.addEventListener(\n", + " 'mousemove',\n", + " on_mouse_event_closure('motion_notify')\n", + " );\n", + "\n", + " rubberband_canvas.addEventListener(\n", + " 'mouseenter',\n", + " on_mouse_event_closure('figure_enter')\n", + " );\n", + " rubberband_canvas.addEventListener(\n", + " 'mouseleave',\n", + " on_mouse_event_closure('figure_leave')\n", + " );\n", + "\n", + " canvas_div.addEventListener('wheel', function (event) {\n", + " if (event.deltaY < 0) {\n", + " event.step = 1;\n", + " } else {\n", + " event.step = -1;\n", + " }\n", + " on_mouse_event_closure('scroll')(event);\n", + " });\n", + "\n", + " canvas_div.appendChild(canvas);\n", + " canvas_div.appendChild(rubberband_canvas);\n", + "\n", + " this.rubberband_context = rubberband_canvas.getContext('2d');\n", + " this.rubberband_context.strokeStyle = '#000000';\n", + "\n", + " this._resize_canvas = function (width, height, forward) {\n", + " if (forward) {\n", + " canvas_div.style.width = width + 'px';\n", + " canvas_div.style.height = height + 'px';\n", + " }\n", + " };\n", + "\n", + " // Disable right mouse context menu.\n", + " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", + " event.preventDefault();\n", + " return false;\n", + " });\n", + "\n", + " function set_focus() {\n", + " canvas.focus();\n", + " canvas_div.focus();\n", + " }\n", + "\n", + " window.setTimeout(set_focus, 100);\n", + "};\n", + "\n", + "mpl.figure.prototype._init_toolbar = function () {\n", + " var fig = this;\n", + "\n", + " var toolbar = document.createElement('div');\n", + " toolbar.classList = 'mpl-toolbar';\n", + " this.root.appendChild(toolbar);\n", + "\n", + " function on_click_closure(name) {\n", + " return function (_event) {\n", + " return fig.toolbar_button_onclick(name);\n", + " };\n", + " }\n", + "\n", + " function on_mouseover_closure(tooltip) {\n", + " return function (event) {\n", + " if (!event.currentTarget.disabled) {\n", + " return fig.toolbar_button_onmouseover(tooltip);\n", + " }\n", + " };\n", + " }\n", + "\n", + " fig.buttons = {};\n", + " var buttonGroup = document.createElement('div');\n", + " buttonGroup.classList = 'mpl-button-group';\n", + " for (var toolbar_ind in mpl.toolbar_items) {\n", + " var name = mpl.toolbar_items[toolbar_ind][0];\n", + " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", + " var image = mpl.toolbar_items[toolbar_ind][2];\n", + " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", + "\n", + " if (!name) {\n", + " /* Instead of a spacer, we start a new button group. */\n", + " if (buttonGroup.hasChildNodes()) {\n", + " toolbar.appendChild(buttonGroup);\n", + " }\n", + " buttonGroup = document.createElement('div');\n", + " buttonGroup.classList = 'mpl-button-group';\n", + " continue;\n", + " }\n", + "\n", + " var button = (fig.buttons[name] = document.createElement('button'));\n", + " button.classList = 'mpl-widget';\n", + " button.setAttribute('role', 'button');\n", + " button.setAttribute('aria-disabled', 'false');\n", + " button.addEventListener('click', on_click_closure(method_name));\n", + " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", + "\n", + " var icon_img = document.createElement('img');\n", + " icon_img.src = '_images/' + image + '.png';\n", + " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", + " icon_img.alt = tooltip;\n", + " button.appendChild(icon_img);\n", + "\n", + " buttonGroup.appendChild(button);\n", + " }\n", + "\n", + " if (buttonGroup.hasChildNodes()) {\n", + " toolbar.appendChild(buttonGroup);\n", + " }\n", + "\n", + " var fmt_picker = document.createElement('select');\n", + " fmt_picker.classList = 'mpl-widget';\n", + " toolbar.appendChild(fmt_picker);\n", + " this.format_dropdown = fmt_picker;\n", + "\n", + " for (var ind in mpl.extensions) {\n", + " var fmt = mpl.extensions[ind];\n", + " var option = document.createElement('option');\n", + " option.selected = fmt === mpl.default_extension;\n", + " option.innerHTML = fmt;\n", + " fmt_picker.appendChild(option);\n", + " }\n", + "\n", + " var status_bar = document.createElement('span');\n", + " status_bar.classList = 'mpl-message';\n", + " toolbar.appendChild(status_bar);\n", + " this.message = status_bar;\n", + "};\n", + "\n", + "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", + " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", + " // which will in turn request a refresh of the image.\n", + " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", + "};\n", + "\n", + "mpl.figure.prototype.send_message = function (type, properties) {\n", + " properties['type'] = type;\n", + " properties['figure_id'] = this.id;\n", + " this.ws.send(JSON.stringify(properties));\n", + "};\n", + "\n", + "mpl.figure.prototype.send_draw_message = function () {\n", + " if (!this.waiting) {\n", + " this.waiting = true;\n", + " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", + " }\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", + " var format_dropdown = fig.format_dropdown;\n", + " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", + " fig.ondownload(fig, format);\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", + " var size = msg['size'];\n", + " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", + " fig._resize_canvas(size[0], size[1], msg['forward']);\n", + " fig.send_message('refresh', {});\n", + " }\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", + " var x0 = msg['x0'] / fig.ratio;\n", + " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", + " var x1 = msg['x1'] / fig.ratio;\n", + " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", + " x0 = Math.floor(x0) + 0.5;\n", + " y0 = Math.floor(y0) + 0.5;\n", + " x1 = Math.floor(x1) + 0.5;\n", + " y1 = Math.floor(y1) + 0.5;\n", + " var min_x = Math.min(x0, x1);\n", + " var min_y = Math.min(y0, y1);\n", + " var width = Math.abs(x1 - x0);\n", + " var height = Math.abs(y1 - y0);\n", + "\n", + " fig.rubberband_context.clearRect(\n", + " 0,\n", + " 0,\n", + " fig.canvas.width / fig.ratio,\n", + " fig.canvas.height / fig.ratio\n", + " );\n", + "\n", + " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", + " // Updates the figure title.\n", + " fig.header.textContent = msg['label'];\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", + " var cursor = msg['cursor'];\n", + " switch (cursor) {\n", + " case 0:\n", + " cursor = 'pointer';\n", + " break;\n", + " case 1:\n", + " cursor = 'default';\n", + " break;\n", + " case 2:\n", + " cursor = 'crosshair';\n", + " break;\n", + " case 3:\n", + " cursor = 'move';\n", + " break;\n", + " }\n", + " fig.rubberband_canvas.style.cursor = cursor;\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_message = function (fig, msg) {\n", + " fig.message.textContent = msg['message'];\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", + " // Request the server to send over a new figure.\n", + " fig.send_draw_message();\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", + " fig.image_mode = msg['mode'];\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", + " for (var key in msg) {\n", + " if (!(key in fig.buttons)) {\n", + " continue;\n", + " }\n", + " fig.buttons[key].disabled = !msg[key];\n", + " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", + " }\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", + " if (msg['mode'] === 'PAN') {\n", + " fig.buttons['Pan'].classList.add('active');\n", + " fig.buttons['Zoom'].classList.remove('active');\n", + " } else if (msg['mode'] === 'ZOOM') {\n", + " fig.buttons['Pan'].classList.remove('active');\n", + " fig.buttons['Zoom'].classList.add('active');\n", + " } else {\n", + " fig.buttons['Pan'].classList.remove('active');\n", + " fig.buttons['Zoom'].classList.remove('active');\n", + " }\n", + "};\n", + "\n", + "mpl.figure.prototype.updated_canvas_event = function () {\n", + " // Called whenever the canvas gets updated.\n", + " this.send_message('ack', {});\n", + "};\n", + "\n", + "// A function to construct a web socket function for onmessage handling.\n", + "// Called in the figure constructor.\n", + "mpl.figure.prototype._make_on_message_function = function (fig) {\n", + " return function socket_on_message(evt) {\n", + " if (evt.data instanceof Blob) {\n", + " /* FIXME: We get \"Resource interpreted as Image but\n", + " * transferred with MIME type text/plain:\" errors on\n", + " * Chrome. But how to set the MIME type? It doesn't seem\n", + " * to be part of the websocket stream */\n", + " evt.data.type = 'image/png';\n", + "\n", + " /* Free the memory for the previous frames */\n", + " if (fig.imageObj.src) {\n", + " (window.URL || window.webkitURL).revokeObjectURL(\n", + " fig.imageObj.src\n", + " );\n", + " }\n", + "\n", + " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", + " evt.data\n", + " );\n", + " fig.updated_canvas_event();\n", + " fig.waiting = false;\n", + " return;\n", + " } else if (\n", + " typeof evt.data === 'string' &&\n", + " evt.data.slice(0, 21) === 'data:image/png;base64'\n", + " ) {\n", + " fig.imageObj.src = evt.data;\n", + " fig.updated_canvas_event();\n", + " fig.waiting = false;\n", + " return;\n", + " }\n", + "\n", + " var msg = JSON.parse(evt.data);\n", + " var msg_type = msg['type'];\n", + "\n", + " // Call the \"handle_{type}\" callback, which takes\n", + " // the figure and JSON message as its only arguments.\n", + " try {\n", + " var callback = fig['handle_' + msg_type];\n", + " } catch (e) {\n", + " console.log(\n", + " \"No handler for the '\" + msg_type + \"' message type: \",\n", + " msg\n", + " );\n", + " return;\n", + " }\n", + "\n", + " if (callback) {\n", + " try {\n", + " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", + " callback(fig, msg);\n", + " } catch (e) {\n", + " console.log(\n", + " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", + " e,\n", + " e.stack,\n", + " msg\n", + " );\n", + " }\n", + " }\n", + " };\n", + "};\n", + "\n", + "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", + "mpl.findpos = function (e) {\n", + " //this section is from http://www.quirksmode.org/js/events_properties.html\n", + " var targ;\n", + " if (!e) {\n", + " e = window.event;\n", + " }\n", + " if (e.target) {\n", + " targ = e.target;\n", + " } else if (e.srcElement) {\n", + " targ = e.srcElement;\n", + " }\n", + " if (targ.nodeType === 3) {\n", + " // defeat Safari bug\n", + " targ = targ.parentNode;\n", + " }\n", + "\n", + " // pageX,Y are the mouse positions relative to the document\n", + " var boundingRect = targ.getBoundingClientRect();\n", + " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", + " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", + "\n", + " return { x: x, y: y };\n", + "};\n", + "\n", + "/*\n", + " * return a copy of an object with only non-object keys\n", + " * we need this to avoid circular references\n", + " * http://stackoverflow.com/a/24161582/3208463\n", + " */\n", + "function simpleKeys(original) {\n", + " return Object.keys(original).reduce(function (obj, key) {\n", + " if (typeof original[key] !== 'object') {\n", + " obj[key] = original[key];\n", + " }\n", + " return obj;\n", + " }, {});\n", + "}\n", + "\n", + "mpl.figure.prototype.mouse_event = function (event, name) {\n", + " var canvas_pos = mpl.findpos(event);\n", + "\n", + " if (name === 'button_press') {\n", + " this.canvas.focus();\n", + " this.canvas_div.focus();\n", + " }\n", + "\n", + " var x = canvas_pos.x * this.ratio;\n", + " var y = canvas_pos.y * this.ratio;\n", + "\n", + " this.send_message(name, {\n", + " x: x,\n", + " y: y,\n", + " button: event.button,\n", + " step: event.step,\n", + " guiEvent: simpleKeys(event),\n", + " });\n", + "\n", + " /* This prevents the web browser from automatically changing to\n", + " * the text insertion cursor when the button is pressed. We want\n", + " * to control all of the cursor setting manually through the\n", + " * 'cursor' event from matplotlib */\n", + " event.preventDefault();\n", + " return false;\n", + "};\n", + "\n", + "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", + " // Handle any extra behaviour associated with a key event\n", + "};\n", + "\n", + "mpl.figure.prototype.key_event = function (event, name) {\n", + " // Prevent repeat events\n", + " if (name === 'key_press') {\n", + " if (event.which === this._key) {\n", + " return;\n", + " } else {\n", + " this._key = event.which;\n", + " }\n", + " }\n", + " if (name === 'key_release') {\n", + " this._key = null;\n", + " }\n", + "\n", + " var value = '';\n", + " if (event.ctrlKey && event.which !== 17) {\n", + " value += 'ctrl+';\n", + " }\n", + " if (event.altKey && event.which !== 18) {\n", + " value += 'alt+';\n", + " }\n", + " if (event.shiftKey && event.which !== 16) {\n", + " value += 'shift+';\n", + " }\n", + "\n", + " value += 'k';\n", + " value += event.which.toString();\n", + "\n", + " this._key_event_extra(event, name);\n", + "\n", + " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", + " return false;\n", + "};\n", + "\n", + "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", + " if (name === 'download') {\n", + " this.handle_save(this, null);\n", + " } else {\n", + " this.send_message('toolbar_button', { name: name });\n", + " }\n", + "};\n", + "\n", + "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", + " this.message.textContent = tooltip;\n", + "};\n", + "\n", + "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", + "// prettier-ignore\n", + "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", + "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", + "\n", + "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", + "\n", + "mpl.default_extension = \"png\";/* global mpl */\n", + "\n", + "var comm_websocket_adapter = function (comm) {\n", + " // Create a \"websocket\"-like object which calls the given IPython comm\n", + " // object with the appropriate methods. Currently this is a non binary\n", + " // socket, so there is still some room for performance tuning.\n", + " var ws = {};\n", + "\n", + " ws.close = function () {\n", + " comm.close();\n", + " };\n", + " ws.send = function (m) {\n", + " //console.log('sending', m);\n", + " comm.send(m);\n", + " };\n", + " // Register the callback with on_msg.\n", + " comm.on_msg(function (msg) {\n", + " //console.log('receiving', msg['content']['data'], msg);\n", + " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", + " ws.onmessage(msg['content']['data']);\n", + " });\n", + " return ws;\n", + "};\n", + "\n", + "mpl.mpl_figure_comm = function (comm, msg) {\n", + " // This is the function which gets called when the mpl process\n", + " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", + "\n", + " var id = msg.content.data.id;\n", + " // Get hold of the div created by the display call when the Comm\n", + " // socket was opened in Python.\n", + " var element = document.getElementById(id);\n", + " var ws_proxy = comm_websocket_adapter(comm);\n", + "\n", + " function ondownload(figure, _format) {\n", + " window.open(figure.canvas.toDataURL());\n", + " }\n", + "\n", + " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", + "\n", + " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", + " // web socket which is closed, not our websocket->open comm proxy.\n", + " ws_proxy.onopen();\n", + "\n", + " fig.parent_element = element;\n", + " fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n", + " if (!fig.cell_info) {\n", + " console.error('Failed to find cell for figure', id, fig);\n", + " return;\n", + " }\n", + " fig.cell_info[0].output_area.element.on(\n", + " 'cleared',\n", + " { fig: fig },\n", + " fig._remove_fig_handler\n", + " );\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_close = function (fig, msg) {\n", + " var width = fig.canvas.width / fig.ratio;\n", + " fig.cell_info[0].output_area.element.off(\n", + " 'cleared',\n", + " fig._remove_fig_handler\n", + " );\n", + " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", + "\n", + " // Update the output cell to use the data from the current canvas.\n", + " fig.push_to_output();\n", + " var dataURL = fig.canvas.toDataURL();\n", + " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", + " // the notebook keyboard shortcuts fail.\n", + " IPython.keyboard_manager.enable();\n", + " fig.parent_element.innerHTML =\n", + " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n", + " fig.close_ws(fig, msg);\n", + "};\n", + "\n", + "mpl.figure.prototype.close_ws = function (fig, msg) {\n", + " fig.send_message('closing', msg);\n", + " // fig.ws.close()\n", + "};\n", + "\n", + "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", + " // Turn the data on the canvas into data in the output cell.\n", + " var width = this.canvas.width / this.ratio;\n", + " var dataURL = this.canvas.toDataURL();\n", + " this.cell_info[1]['text/html'] =\n", + " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n", + "};\n", + "\n", + "mpl.figure.prototype.updated_canvas_event = function () {\n", + " // Tell IPython that the notebook contents must change.\n", + " IPython.notebook.set_dirty(true);\n", + " this.send_message('ack', {});\n", + " var fig = this;\n", + " // Wait a second, then push the new image to the DOM so\n", + " // that it is saved nicely (might be nice to debounce this).\n", + " setTimeout(function () {\n", + " fig.push_to_output();\n", + " }, 1000);\n", + "};\n", + "\n", + "mpl.figure.prototype._init_toolbar = function () {\n", + " var fig = this;\n", + "\n", + " var toolbar = document.createElement('div');\n", + " toolbar.classList = 'btn-toolbar';\n", + " this.root.appendChild(toolbar);\n", + "\n", + " function on_click_closure(name) {\n", + " return function (_event) {\n", + " return fig.toolbar_button_onclick(name);\n", + " };\n", + " }\n", + "\n", + " function on_mouseover_closure(tooltip) {\n", + " return function (event) {\n", + " if (!event.currentTarget.disabled) {\n", + " return fig.toolbar_button_onmouseover(tooltip);\n", + " }\n", + " };\n", + " }\n", + "\n", + " fig.buttons = {};\n", + " var buttonGroup = document.createElement('div');\n", + " buttonGroup.classList = 'btn-group';\n", + " var button;\n", + " for (var toolbar_ind in mpl.toolbar_items) {\n", + " var name = mpl.toolbar_items[toolbar_ind][0];\n", + " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", + " var image = mpl.toolbar_items[toolbar_ind][2];\n", + " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", + "\n", + " if (!name) {\n", + " /* Instead of a spacer, we start a new button group. */\n", + " if (buttonGroup.hasChildNodes()) {\n", + " toolbar.appendChild(buttonGroup);\n", + " }\n", + " buttonGroup = document.createElement('div');\n", + " buttonGroup.classList = 'btn-group';\n", + " continue;\n", + " }\n", + "\n", + " button = fig.buttons[name] = document.createElement('button');\n", + " button.classList = 'btn btn-default';\n", + " button.href = '#';\n", + " button.title = name;\n", + " button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n", + " button.addEventListener('click', on_click_closure(method_name));\n", + " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", + " buttonGroup.appendChild(button);\n", + " }\n", + "\n", + " if (buttonGroup.hasChildNodes()) {\n", + " toolbar.appendChild(buttonGroup);\n", + " }\n", + "\n", + " // Add the status bar.\n", + " var status_bar = document.createElement('span');\n", + " status_bar.classList = 'mpl-message pull-right';\n", + " toolbar.appendChild(status_bar);\n", + " this.message = status_bar;\n", + "\n", + " // Add the close button to the window.\n", + " var buttongrp = document.createElement('div');\n", + " buttongrp.classList = 'btn-group inline pull-right';\n", + " button = document.createElement('button');\n", + " button.classList = 'btn btn-mini btn-primary';\n", + " button.href = '#';\n", + " button.title = 'Stop Interaction';\n", + " button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n", + " button.addEventListener('click', function (_evt) {\n", + " fig.handle_close(fig, {});\n", + " });\n", + " button.addEventListener(\n", + " 'mouseover',\n", + " on_mouseover_closure('Stop Interaction')\n", + " );\n", + " buttongrp.appendChild(button);\n", + " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", + " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", + "};\n", + "\n", + "mpl.figure.prototype._remove_fig_handler = function (event) {\n", + " var fig = event.data.fig;\n", + " if (event.target !== this) {\n", + " // Ignore bubbled events from children.\n", + " return;\n", + " }\n", + " fig.close_ws(fig, {});\n", + "};\n", + "\n", + "mpl.figure.prototype._root_extra_style = function (el) {\n", + " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", + "};\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function (el) {\n", + " // this is important to make the div 'focusable\n", + " el.setAttribute('tabindex', 0);\n", + " // reach out to IPython and tell the keyboard manager to turn it's self\n", + " // off when our div gets focus\n", + "\n", + " // location in version 3\n", + " if (IPython.notebook.keyboard_manager) {\n", + " IPython.notebook.keyboard_manager.register_events(el);\n", + " } else {\n", + " // location in version 2\n", + " IPython.keyboard_manager.register_events(el);\n", + " }\n", + "};\n", + "\n", + "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", + " var manager = IPython.notebook.keyboard_manager;\n", + " if (!manager) {\n", + " manager = IPython.keyboard_manager;\n", + " }\n", + "\n", + " // Check for shift+enter\n", + " if (event.shiftKey && event.which === 13) {\n", + " this.canvas_div.blur();\n", + " // select the cell after this one\n", + " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", + " IPython.notebook.select(index + 1);\n", + " }\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", + " fig.ondownload(fig, null);\n", + "};\n", + "\n", + "mpl.find_output_cell = function (html_output) {\n", + " // Return the cell and output element which can be found *uniquely* in the notebook.\n", + " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", + " // IPython event is triggered only after the cells have been serialised, which for\n", + " // our purposes (turning an active figure into a static one), is too late.\n", + " var cells = IPython.notebook.get_cells();\n", + " var ncells = cells.length;\n", + " for (var i = 0; i < ncells; i++) {\n", + " var cell = cells[i];\n", + " if (cell.cell_type === 'code') {\n", + " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", + " var data = cell.output_area.outputs[j];\n", + " if (data.data) {\n", + " // IPython >= 3 moved mimebundle to data attribute of output\n", + " data = data.data;\n", + " }\n", + " if (data['text/html'] === html_output) {\n", + " return [cell, data, j];\n", + " }\n", + " }\n", + " }\n", + " }\n", + "};\n", + "\n", + "// Register the function which deals with the matplotlib target/channel.\n", + "// The kernel may be null if the page has been refreshed.\n", + "if (IPython.notebook.kernel !== null) {\n", + " IPython.notebook.kernel.comm_manager.register_target(\n", + " 'matplotlib',\n", + " mpl.mpl_figure_comm\n", + " );\n", + "}\n" + ], + "text/plain": [ + "<IPython.core.display.Javascript object>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "<img 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\" width=\"1400\">" + ], + "text/plain": [ + "<IPython.core.display.HTML object>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "MovieWriter ffmpeg unavailable; using Pillow instead.\n" + ] + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(14,12))\n", + "\n", + "\n", + "# defino los extremos de luminosidad y temperatura\n", + "allTemps = np.concatenate([ms[1], giants[1], supergiants[1],dwarfs[1]], axis=0)\n", + "min_T, max_T = allTemps.min(), allTemps.max()\n", + "\n", + "allLumi = np.concatenate([ms[0], giants[0], supergiants[0],dwarfs[0]], axis=0)\n", + "min_L, max_L = allLumi.min(), allLumi.max()\n", + "\n", + "# personalización de los ejes\n", + "\n", + "\n", + "# escala logarÃtmica en ambos ejes\n", + "ax.set_xscale('log')\n", + "ax.set_yscale('log')\n", + "\n", + "# elimino los ejes superior y derecho\n", + "ax.spines['right'].set_visible(False)\n", + "ax.spines['top'].set_visible(False)\n", + "\n", + "# fijo el tamaño de los números de eje\n", + "ax.tick_params(axis='both', which='major', labelsize=12)\n", + "\n", + "# especifico los ticks que aparecen\n", + "ax.set_xticks([5000,10000])\n", + "ax.set_xticks([], minor=True)\n", + "\n", + "# elimino la notación cientÃfica del eje x\n", + "ax.get_xaxis().set_major_formatter(matplotlib.ticker.ScalarFormatter())\n", + "ax.get_xaxis().set_minor_formatter(matplotlib.ticker.NullFormatter())\n", + "\n", + "# nombro los ejes\n", + "ax.set_xlabel('Temperature (K)')\n", + "ax.set_ylabel('Luminosity (L$_{sun}$)')\n", + "\n", + "# invierto el eje x\n", + "ax.invert_xaxis()\n", + "\n", + "# añado etiquetas de cada conjunto de estrellas como texto\n", + "\n", + "\n", + "ax.text(5500,0.01,'Main Sequence', fontsize = 20, weight = 'bold')\n", + "ax.text(13000,6,'Main Sequence', fontsize = 20, weight = 'bold')\n", + "ax.text(4500,2,'Red Giants', fontsize = 20, weight = 'bold')\n", + "ax.text(5000,0.3e7,'Red Supergiants', fontsize = 20, weight = 'bold')\n", + "ax.text(11500,0.3e7,'Blue Giants', fontsize = 20, weight = 'bold')\n", + "ax.text(10000,0.002,'White Dwarfs', fontsize = 20, weight = 'bold')\n", + "\n", + "# uno todos los arreglos para poder animar\n", + "\n", + "Lumis = np.concatenate((ms[0], giants[0], supergiants[0],dwarfs[0]))\n", + "Temps = np.concatenate((ms[1], giants[1], supergiants[1],dwarfs[1]))\n", + "Rads = np.concatenate((ms[2], giants[2], supergiants[2],dwarfs[2]))\n", + "\n", + "#creo un sample de la figura y esta se va a sobre escribir\n", + "plt.figure(1)\n", + "scat = ax.scatter(Temps,Lumis,s = 20*Rads, c = Temps, cmap = 'RdYlBu',linewidths=1.5, edgecolor = 'grey',vmin = min_T, vmax = max_T)\n", + "\n", + "\n", + "# animation\n", + "\n", + "def animate(i):\n", + " data = np.hstack((Temps[:i,np.newaxis], Lumis[:i, np.newaxis]))\n", + " scat.set_offsets(data)\n", + " return scat,\n", + "\n", + "anim = FuncAnimation(fig, animate, frames=len(Temps)+1, \n", + " interval=200, blit=False, repeat=False)\n", + "\n", + "anim.save('animation.gif')" + ] + } + ], + "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/animation.gif b/animation.gif new file mode 100644 index 0000000000000000000000000000000000000000..d462d302efbbfea6aee4d28d39587465371844c4 Binary files /dev/null and b/animation.gif differ