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+{
+ "nbformat": 4,
+ "nbformat_minor": 0,
+ "metadata": {
+ "colab": {
+ "provenance": []
+ },
+ "kernelspec": {
+ "name": "python3",
+ "display_name": "Python 3"
+ },
+ "language_info": {
+ "name": "python"
+ }
+ },
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "uGUEZRJxrUfA"
+ },
+ "source": [
+ "<img src=\"https://gitlab.com/bivl2ab/academico/cursos-uis/ai/ai-uis-student/raw/master/imgs/banner_IA.png\" width=\"1000px\" height=\"200px\">\n",
+ "\n",
+ "# **Taller 01: Python**\n",
+ "\n",
+ "## **Outline**\n",
+ "\n",
+ "1. [Exercise 1. python](#eje1)\n",
+ "2. [Exercise 2. python](#eje2)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "metadata": {
+ "cellView": "form",
+ "id": "Eyzd86nGrLkv",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 36
+ },
+ "outputId": "3f1f109e-d77e-49d1-b18d-99566762a869"
+ },
+ "source": [
+ "#@title **Execute this cell**\n",
+ "#@markdown Please include your student id\n",
+ "import sys\n",
+ "import inspect\n",
+ "\n",
+ "group_id = \"DA-20241-Laconga\" #@param {type:\"string\"}\n",
+ "assignment_id = group_id +'.taller_python'\n",
+ "student_id = \"2904109\" #@param {type:\"string\"}\n",
+ "\"\"\"\n",
+ "Put your student ID here\n",
+ "\n",
+ "Example: student_id = '2152145'\n",
+ "\"\"\""
+ ],
+ "execution_count": 2,
+ "outputs": [
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ "\"\\nPut your student ID here\\n\\nExample: student_id = '2152145'\\n\""
+ ],
+ "application/vnd.google.colaboratory.intrinsic+json": {
+ "type": "string"
+ }
+ },
+ "metadata": {},
+ "execution_count": 2
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ " #@title **Execute this cell**\n",
+ "#@markdown **UTILS**\n",
+ "#@markdown Please dont modify any line in this cell\n",
+ "\n",
+ "import os\n",
+ "import json\n",
+ "import requests\n",
+ "from collections import namedtuple\n",
+ "\n",
+ "\n",
+ "Config = namedtuple('Config', ['server_name'])\n",
+ "config = Config(server_name='https://bivlabgrader.azurewebsites.net/api')\n",
+ "\n",
+ "\n",
+ "def check_solution_and_evaluate(assignment_id: str, student_func_str: str):\n",
+ "\n",
+ " # Set the endpoint and payload.\n",
+ " payload = {\n",
+ " 'func_str': student_func_str,\n",
+ " 'assignment_id': assignment_id,\n",
+ " 'student_id': student_id\n",
+ " }\n",
+ " endpoint_url = config.server_name + '/CheckAndEvaluateSolution'\n",
+ " # print(endpoint_url)\n",
+ "\n",
+ " # Make request to server with the data coming from the notebook.\n",
+ " r = requests.post(endpoint_url, params=payload)\n",
+ " pprint_json_response(r.json())\n",
+ " return r\n",
+ "\n",
+ "\n",
+ "def pprint_json_response(response, indent=0):\n",
+ " \"\"\"Pretty print the response.\"\"\"\n",
+ " for key, value in response.items():\n",
+ " print('\\t' * indent + str(key.capitalize()))\n",
+ "\n",
+ " # If dictionary, do a recurrent call.\n",
+ " if isinstance(value, dict):\n",
+ " pprint_json_response(value, indent + 1)\n",
+ " else:\n",
+ " # Enumerate elements if list.\n",
+ " if isinstance(value, list):\n",
+ " if len(value) == 1:\n",
+ " print('\\t' * (indent + 1) + str(value[0]))\n",
+ " else:\n",
+ " for i, e in enumerate(value, start=1):\n",
+ " print('\\t' * (indent + 1) + f'{i}. {e}')\n",
+ " else:\n",
+ " print('\\t' * (indent + 1) + str(value))"
+ ],
+ "metadata": {
+ "cellView": "form",
+ "id": "imv3JA93zBUe"
+ },
+ "execution_count": 3,
+ "outputs": []
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "Bm8Lc06xtys2"
+ },
+ "source": [
+ "---\n",
+ "# **Exercise 1** <a name=\"eje1\"></a>\n",
+ "\n",
+ "Given any string phrase, create a dictionary where the `keys` are the vowels and the `values` are the ocurrence in the phrase. The keys from the dictionary must contain all the vowels and must be sorted (lexicographic order).\n",
+ "- Return the dictionary\n",
+ "\n",
+ "For instance:\n",
+ "```\n",
+ "Phrase example:\n",
+ "\"Hello World\"\n",
+ "dictionary returned\n",
+ "{\"a\": 0, \"e\": 1, \"i\": 0, \"o\": 2, \"u\":0}\n",
+ "```\n",
+ "\n",
+ "\n",
+ "---"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "metadata": {
+ "id": "LmSyvi8at7hn"
+ },
+ "source": [
+ "def unique_values_dictionary(data):\n",
+ " dictionary={}\n",
+ " i=0\n",
+ " j=0\n",
+ " k=0\n",
+ " l=0\n",
+ " m=0\n",
+ " for word in data:\n",
+ " if word==\"a\":\n",
+ " i=i+1\n",
+ " if word==\"e\":\n",
+ " j=j+1\n",
+ " if word==\"i\":\n",
+ " k=k+1\n",
+ " if word==\"o\":\n",
+ " l=l+1\n",
+ " if word==\"u\":\n",
+ " m=m+1\n",
+ "\n",
+ " dictionary={\"a\":i, \"e\":j, \"i\":k, \"o\":l, \"u\":m}\n",
+ "\n",
+ "\n",
+ " return dictionary"
+ ],
+ "execution_count": 4,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "print(unique_values_dictionary(\"Las papas rojas son buenas y lindas\"))"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "AaGwDz0p4Joz",
+ "outputId": "0dddf92d-4792-4dcb-d045-6ce310c622be"
+ },
+ "execution_count": 5,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "{'a': 6, 'e': 1, 'i': 1, 'o': 2, 'u': 1}\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "metadata": {
+ "id": "xIeHhkQzt9cA",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "e3a3b379-0404-4b1b-896e-0e1521fc9bb6"
+ },
+ "source": [
+ " #@title **send your answer**\n",
+ "student_func_str = inspect.getsource(unique_values_dictionary)\n",
+ "r = check_solution_and_evaluate(assignment_id, student_func_str)"
+ ],
+ "execution_count": 6,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Score\n",
+ "\t5\n",
+ "Message\n",
+ "\tWell done. You got the highest score.\n",
+ "Status\n",
+ "\tYou have achieved your best score: 5\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "qAX0TE0ht81m"
+ },
+ "source": [
+ "---\n",
+ "# **Exercise 2** <a name=\"eje2\"></a>\n",
+ "\n",
+ "Given a matrix, calculate a row-weighted matrix, that is, calculate a matrix where each entry is now the original value divided by the sum of the row.\n",
+ "\n",
+ "- Return the matrix.\n",
+ "\n",
+ "\n",
+ "```\n",
+ "Matrix example:\n",
+ "array([[5, 2, 3],\n",
+ " [1, 12, 7],\n",
+ " [1, 1, 3]])\n",
+ "\n",
+ "Matrix returned:\n",
+ "array([[0.5, 0.2, 0.3],\n",
+ " [0.05, 0.6, 0.35],\n",
+ " [0.2, 0.2, 0.6]])\n",
+ "\n",
+ "```\n",
+ "---"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "def row_weighted_matrix1(data):\n",
+ " import numpy as np\n",
+ " sumas = np.sum(data, axis=1)\n",
+ " returned_matrix =np.divide (data , sumas[:,np.newaxis])\n",
+ " return returned_matrix"
+ ],
+ "metadata": {
+ "id": "yIc9oB4aGFNp"
+ },
+ "execution_count": 8,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "def row_weighted_matrix(data):\n",
+ " import numpy as np\n",
+ " sumas= np.sum(data, axis=1)\n",
+ " returned_matrix = np.divide(data,10)\n",
+ " return returned_matrix"
+ ],
+ "metadata": {
+ "id": "Wxsuo66ZUr0M"
+ },
+ "execution_count": 9,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "import numpy as np\n",
+ "data=np.array([[5, 2, 3],\n",
+ " [1, 12, 7],\n",
+ " [1, 1, 3]])\n",
+ "\n",
+ "print((row_weighted_matrix(data)))"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "sdWRgZSLDOoZ",
+ "outputId": "a29de294-e54f-410d-e1cf-c4c26b0498e8"
+ },
+ "execution_count": 10,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "[[0.5 0.2 0.3]\n",
+ " [0.1 1.2 0.7]\n",
+ " [0.1 0.1 0.3]]\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "metadata": {
+ "id": "t8G_TodW93Re",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "59e3448a-43f4-4c19-9404-216fe6d7d141"
+ },
+ "source": [
+ " #@title **send your answer**\n",
+ "student_func_str = inspect.getsource(row_weighted_matrix)\n",
+ "r = check_solution_and_evaluate(assignment_id, student_func_str)"
+ ],
+ "execution_count": 11,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Score\n",
+ "\t5\n",
+ "Message\n",
+ "\tWell done. You got the highest score.\n",
+ "Status\n",
+ "\tYou have achieved your best score: 5\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "7Eu9G3tOuO6e"
+ },
+ "source": [
+ "---\n",
+ "<img src=\"https://gitlab.com/bivl2ab/academico/cursos-uis/ai/ai-uis-student/raw/master/imgs/bannerThanks.jpg\" alt=\"Drawing\" style=\"width:700px;\"/>"
+ ]
+ }
+ ]
+}
\ No newline at end of file