{ "cells": [ { "cell_type": "markdown", "source": [ "# Les graphiques\n", "\n", "Python a plusieurs modules pour les graphiques. Nous pourrions passer des heures sur ces modules. Nous ne présentons qu'une introduction...\n", "\n", "\n", "Le module le plus commun est `pyplot`, qui lui est dans `matplotlib`. " ], "metadata": {} }, { "cell_type": "code", "execution_count": 3, "source": [ "from matplotlib import pyplot as plt" ], "outputs": [], "metadata": {} }, { "cell_type": "markdown", "source": [ "Pour faire un bon graphique, on débute par l'encapsuler dans la recette suivante avec les ouvertures `figure()` et `show()`:" ], "metadata": {} }, { "cell_type": "code", "execution_count": 4, "source": [ "plt.figure()\n", "# graph ici\n", "plt.show()" ], "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
" ] }, "metadata": {} } ], "metadata": {} }, { "cell_type": "markdown", "source": [ "Ensuite on va utiliser l'un des types de graphiques de pyplot, `plot()`. Pour une liste complète consulter cette [galerie](https://matplotlib.org/stable/gallery/index.html) sur le site de Matplotlib." ], "metadata": {} }, { "cell_type": "code", "execution_count": 5, "source": [ "import numpy as np \n", "\n", "xs = np.linspace(1,100,1000)\n", "ys = np.log(xs)\n", "\n", "plt.figure()\n", "plt.plot(xs,ys)\n", "plt.show()" ], "outputs": [ { "output_type": "display_data", "data": { "image/png": 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dx26ex92X5TsdSUQCkIr6AlW2dHPHU1up9/Ty/+4s5pq5GU5HEpEApaK+AOWNndzxw6109Q3yk3tXsCQ3yelIIhLAVNTnaV+Nh7ueHrkm1U/vW8mcLN2BRUR8K8TpAP5k5/FWbtuwhfDQEJW0iEwazajHaU9VG3c9tY3k2Aieu2c5Ocm68p2ITA4V9Tjsq/Fw51PbSIgOZ+O9K5iqW2WJyCTS0scYDtV3cOdTW4mOCFVJi4gjVNTnUNHcxZd+uJWQEMPzX9Vyh4g4Q0V9Fs2dfdz19Db6h4Z5/qvLKUiLdTqSiAQpFfUZ9PQP8ZVnt1PX3stTdy9jVkac05FEJIjpYOJpBoeG+fONJeypauMHdyxlaZ5OZhERZ2lGfZrHX9nHm2UNPHbzPK6bl+l0HBERFfWpNm47zo+3VLD+ygLuWpnvdBwREUBFPWr7sRb+4eVSVs9K4xvripyOIyIySkUN1Lb38LXnSpiWOIX/e9tiQnU9aRFxkaA/mNg/OMzXniuhp3+QjfcuJyE63OlIIiJ/IuiL+ruv72d3ZRv/9aUlzNQ2PBFxoaBe+nh7fwP/88ej3LEilxsWZDkdR0TkjIK2qOvae3no57spyozj72+c63QcEZGzCsqiHh62/NVPd9HTP8T3b19CVHio05FERM4qKNeof7zlGFuONPOdzy5gRrqu4SEi7hZ0M+pjTV1857UDXDU7jVuLc5yOIyIypqAq6uFhy8Mv7iYs1PAvtyzEGO2XFhH3C6qi/tHmY3x4rJVvfnIemQlRTscRERmXoCnquvZe/v13B1g9K43PLpnmdBwRkXELmqL+1qv7GBi2PP6peVryEBG/EhRF/d6hJl7ZU8v/uaqQvJQYp+OIiJyXgC/qvsEh/uHlUvJSovna6kKn44iInLeA30f97OZjHGnq4kdfXqYTW0TEL405ozbG5Bhj3jbGlBlj9hpjHpiMYBOhrbuf7//+MFfNTuOq2elOxxERuSDjmVEPAg9Za0uMMXHADmPMG9bafT7OdtGefPswHX2DPHK9bgQgIv5rzBm1tbbWWlvi/XsHUAa4fn9bZUs3z26u4HNLsinKjHc6jojIBTuvg4nGmHxgMbD1DK+tN8ZsN8Zsb2xsnKB4F+6JNw5iDDx47Syno4iIXJRxF7UxJhb4BfCX1lrP6a9bazdYa4uttcVpaWkTmfG8HWns5OVd1dx9WT5ZCVMczSIicrHGVdTGmHBGSvp5a+1Lvo108Z58u5yIsBDuvaLA6SgiIhdtPLs+DPAUUGatfcL3kS7O8eZufrWrmtsvzSMtLtLpOCIiF208M+pVwJ3AGmPMLu/HDT7OdcH++53DhIYY7lut2bSIBIYxt+dZa98D/OLiGLXtPby4o4ovXppLRryujicigSGgTiF/dnMFQ8OW9VdqNi0igSNgirq7f5CN246zbn4m2UnRTscREZkwAVPUL5VU094zwFdWTXc6iojIhAqIoh4etjzz/lEWZiewNC/J6TgiIhMqIIr6vcNNlDd28ZVV03VTABEJOAFR1C98eJzkmAiuX5DpdBQRkQnn90Xd3NnHG/vq+cziaUSG6XrTIhJ4/L6of7mzmoEhyxeW5TgdRUTEJ/y6qK21/PTDSi7JSWRWRpzTcUREfMKvi3pnZRuHGjo1mxaRgObXRf3LkmqiwkO4aWGW01FERHzGb4t6cGiY35bWsrYog7iocKfjiIj4jN8W9dajLTR19ms2LSIBz2+L+te7a4iJCOXqIt1dXEQCm18W9cDQMK/treMTczOICtfeaREJbH5Z1JvLm2nrHuCmhVOdjiIi4nN+WdRvldUzJTyUK2amOh1FRMTn/K6orbW8VdbA5TNTtewhIkHB74r6QH0H1W09rNVBRBEJEn5X1G+VNQCwRkUtIkHCD4u6noXZCaTr5rUiEiT8qqhbuvrZWdnG1bM1mxaR4OFXRb2lvBlrYfXsNKejiIhMGr8q6vfLm4iNDGPhtASno4iITBq/Kuot5c0sn55MWKhfxRYRuSh+03g1bT0cbepiZWGK01FERCaV3xT15vJmAFbN0NmIIhJc/Kaot5Q3kxwTwWzdcktEgozfFPWOihaW5iUREmKcjiIiMqn8oqibO/s41tzN0rwkp6OIiEw6vyjqncfbAFiSq6IWkeDjF0W943grYSGGhdnaPy0iwccvirqkopV5U+N1WVMRCUquL+rBoWH2VLWzWMseIhKkxixqY8zTxpgGY0zpZAQ63YH6DnoGhlicm+jEtxcRcdx4ZtQ/Atb5OMdZ7a3xALBA1/cQkSA1ZlFba98FWiYhyxntq/EQHRFKXkqMUxFERBw1YWvUxpj1xpjtxpjtjY2NE/Vl2VfroSgzjlCd6CIiQWrCitpau8FaW2ytLU5Lm5jrRVtrKavxMHdq/IR8PRERf+TqXR9VrT109A0yb6rWp0UkeLm6qE8cSJybpRm1iASv8WzP2whsAWYbY6qMMff4PtaIfbUeQgzMztQV80QkeIWN9QZr7RcnI8iZlNV6KEiL1RmJIhLUXL30Ud7QyayMWKdjiIg4yrVF3T84TEVLN4VpKmoRCW6uLerjLV0MDVsVtYgEPdcW9eGGLgAVtYgEPdcWdXljJwAFaTp1XESCm6uLOishipjIMTemiIgENBcXdZeWPUREcHFRH2nsZHqqlj1ERFxZ1O3dA3T0DpKbHO10FBERx7myqCtbuwHISZ7icBIREee5sqirvEWdnaQZtYiIK4u6sqUHgBwVtYiIS4u6tZu4qDASosOdjiIi4jh3FnVLt2bTIiJerizqqtYespN0IFFEBFxY1NZaqlp7yNHWPBERwIVF3dTZT8/AkGbUIiJerivquvZeAKYmqqhFRMCFRV3vGSnqzPgoh5OIiLiD64q6zlvUGSpqERHAhUXd4OklxEBqbITTUUREXMF1RV3n6SU1NpKwUNdFExFxhOvasN7TR2aClj1ERE5wYVH3kh6nohYROcGVRZ2ZEOl0DBER13BVUfcNDtHaPaAZtYjIKVxV1C1d/QCkxmpGLSJygquKurlzpKiTY7Q1T0TkBFcV9YkZdYr2UIuIjHJlUWtGLSJykquKuvnEjFpFLSIyylVF3dLVR2iIIT5Kt+ASETnBZUXdT1J0BCEhxukoIiKu4aqibu7s17KHiMhpxlXUxph1xpgDxpjDxphHfBWmpatfBxJFRE4zZlEbY0KBJ4HrgbnAF40xc30RpqWrn2RtzRMR+RPjmVFfChy21h6x1vYDLwCf8kWY5q5+kqNV1CIipxpPUU8DKk95XOV97k8YY9YbY7YbY7Y3NjaedxBrLWuK0lmcm3jenysiEsjCxvGeM23BsB97wtoNwAaA4uLij70+5jcxhv/4wiXn+2kiIgFvPDPqKiDnlMfZQI1v4oiIyOnGU9QfAjONMdONMRHAbcAm38YSEZETxlz6sNYOGmO+DrwOhAJPW2v3+jyZiIgA41ujxlr7G+A3Ps4iIiJn4KozE0VE5ONU1CIiLqeiFhFxORW1iIjLGWvP+9yUsb+oMY1AxXl8SirQNOFB3C0YxwzBOe5gHDME57gvZsx51tq0M73gk6I+X8aY7dbaYqdzTKZgHDME57iDccwQnOP21Zi19CEi4nIqahERl3NLUW9wOoADgnHMEJzjDsYxQ3CO2ydjdsUatYiInJ1bZtQiInIWKmoREZdztKgn66a5TjPG5Bhj3jbGlBlj9hpjHvA+n2yMecMYc8j7Z5LTWSeaMSbUGLPTGPOK93EwjDnRGPOiMWa/92e+MtDHbYz5K+/vdqkxZqMxJioQx2yMedoY02CMKT3lubOO0xjzqLffDhhjrrvQ7+tYUU/mTXNdYBB4yFo7B1gB/Jl3rI8Ab1lrZwJveR8HmgeAslMeB8OY/xN4zVpbBCxiZPwBO25jzDTgL4Bia+18Ri6HfBuBOeYfAetOe+6M4/T+G78NmOf9nP/y9t75s9Y68gGsBF4/5fGjwKNO5Znksb8MXAMcALK8z2UBB5zONsHjzPb+4q4BXvE+F+hjjgeO4j1Qf8rzATtuTt5XNZmRSye/AlwbqGMG8oHSsX62p3caI9f0X3kh39PJpY9x3TQ30Bhj8oHFwFYgw1pbC+D9M93BaL7wPeBvgOFTngv0MRcAjcAz3iWfHxpjYgjgcVtrq4F/A44DtUC7tfZ3BPCYT3O2cU5YxzlZ1OO6aW4gMcbEAr8A/tJa63E6jy8ZY24CGqy1O5zOMsnCgCXAf1trFwNdBMb/8p+Vd032U8B0YCoQY4y5w9lUrjBhHedkUQfVTXONMeGMlPTz1tqXvE/XG2OyvK9nAQ1O5fOBVcDNxphjwAvAGmPMcwT2mGHk97rKWrvV+/hFRoo7kMf9CeCotbbRWjsAvARcRmCP+VRnG+eEdZyTRR00N801xhjgKaDMWvvEKS9tAu72/v1uRtauA4K19lFrbba1Np+Rn+3vrbV3EMBjBrDW1gGVxpjZ3qfWAvsI7HEfB1YYY6K9v+trGTmAGshjPtXZxrkJuM0YE2mMmQ7MBLZd0HdweFH+BuAgUA78ndMHCXw4zssZ+V+ePcAu78cNQAojB9sOef9Mdjqrj8Z/FScPJgb8mIFLgO3en/evgKRAHzfwGLAfKAX+F4gMxDEDGxlZhx9gZMZ8z7nGCfydt98OANdf6PfVKeQiIi6nMxNFRFxORS0i4nIqahERl1NRi4i4nIpaRMTlVNQiIi6nohYRcbn/D9cvi2R6qBSbAAAAAElFTkSuQmCC", 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" ] }, "metadata": { "needs_background": "light" } } ], "metadata": {} }, { "cell_type": "markdown", "source": [ "On peut maintenant changer les titres d'axes, les légendes, etc. Voici un exemple complet:" ], "metadata": {} }, { "cell_type": "code", "execution_count": 6, "source": [ "plt.figure()\n", "plt.plot(xs,ys,label='$y = \\log x$')\n", "plt.xlabel('$x$')\n", "plt.ylabel('$y$')\n", "plt.title('Figure 1: Fabulous function')\n", "plt.legend()\n", "plt.show()" ], "outputs": [ { "output_type": "display_data", "data": { "image/png": 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", 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