1re Spé - Formule de conjugaison.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# On détaille ici un programme python affichant les points expérimentaux des mesures 1/OA' = f(1/OA) (en grandeurs algébriques).\n",
    "### Dans cet exercice il faudra :\n",
    "###     1. Compléter les listes OA' et OA avec les valeurs expérimentales en valeurs algébriques.\n",
    "###     2. Ajuster la valeur du coefficient directeur \"a\" et de l'ordonnée à l'origine \"b\" pour faire correspondre au mieux le modèle aux points expérimentaux."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Chaque partie de code est précédée d'un titre.\n",
    "### Certaines parties de code sont à modifier par vous, cela est indiqué par la mention $\\color {red} {\"A\\: VOUS\\: DE\\: JOUER\\,!\"}$ dans le titre de la partie."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ETAPE 0 : Initialisation des bibliothèques python nécessaires"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import math"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.close() # On ferme les fenêtres graphiques éventuellement ouvertes."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ETAPE 1 : On entre les coordonnées des valeurs expérimentales."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### $\\color {red} {\"A\\: VOUS\\: DE\\: JOUER\\,!\"}$ \n",
    "### En valeurs algébriques et en cm, compléter les listes OA' et OA ci-dessous avec les valeurs OA' et OA expérimentales, les valeurs sont séparées par une virgule."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "OA_prime_cm = np.array([]) #Liste contenant les valeurs de OA' en cm\n",
    "OA_cm = np.array([]) #Liste contenant les valeurs de OA en cm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ETAPE 2 : Conversion des données en mètre"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### $\\color {red} {\"A\\: VOUS\\: DE\\: JOUER\\,!\"}$ \n",
    "### Ecrire la valeur du facteur de conversion pour passer de centimètre à mètre."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "ename": "UFuncTypeError",
     "evalue": "ufunc 'multiply' did not contain a loop with signature matching types (dtype('<U32'), dtype('<U32')) -> dtype('<U32')",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mUFuncTypeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-4-e68f2403c8ce>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mOA_prime_m\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mOA_prime_cm\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0;34m\"A modifier\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mOA_m\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mOA_cm\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0;34m\"A modifier\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mUFuncTypeError\u001b[0m: ufunc 'multiply' did not contain a loop with signature matching types (dtype('<U32'), dtype('<U32')) -> dtype('<U32')"
     ]
    }
   ],
   "source": [
    "OA_prime_m = OA_prime_cm * \"A modifier\"\n",
    "OA_m = OA_cm * \"A modifier\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ETAPE 3: On modélise la répartition des points par une droite affine de la forme y = ax + b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'OA_m' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-5-bea249e0a716>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0mb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m5\u001b[0m \u001b[0;31m#Valeur de l'ordonnée à l'origine de la droite modèle\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mpas\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mmax\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0mOA_m\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0mmin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0mOA_m\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0;36m100\u001b[0m \u001b[0;31m#pas générant les abscisses du mmodèle\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0mabs_debut\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0mOA_m\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0;36m100\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mpas\u001b[0m \u001b[0;31m#Abscisse de début du graphique\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'OA_m' is not defined"
     ]
    }
   ],
   "source": [
    "a = 0.8 #Valeur du coefficient directeur de la droite modèle\n",
    "b = 5 #Valeur de l'ordonnée à l'origine de la droite modèle\n",
    "\n",
    "pas = (max(1/OA_m)-min(1/OA_m))/100 #pas générant les abscisses du mmodèle\n",
    "\n",
    "abs_debut = min(1/OA_m) - 100 * pas #Abscisse de début du graphique\n",
    "\n",
    "abs_fin = 0 + 100 * pas #Abscisse de fin du graphique\n",
    "\n",
    "X_modele = np.arange(abs_debut, abs_fin, pas) #On génère les abscisses du modèle\n",
    "                                                        # 10 x pas permet d'obtenir une droite qui dépasse à droite\n",
    "for i in X_modele:\n",
    "    Y_modele = a * X_modele + b #On génère les ordonnées du modèle"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ETAPE 4 : On trace le graphique contenant les points expérimentaux et le modèle"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### $\\color {red} {\"A\\: VOUS\\: DE\\: JOUER\\,!\"}$ \n",
    "### Si nécessaire, modifier les valeurs de \"a\" et de \"b\", dans l'étape 4, pour que le modèle s'ajuste au mieux à la répartition des points expérimentaux."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'abs_debut' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-6-a379acdd80e4>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mylabel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"A modifier\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msize\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m18\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m#Affiche le titre des ordonnées\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mxlabel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"A modifier\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msize\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m18\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m#Affiche le titre des abscisses\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mxlim\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mabs_debut\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mabs_fin\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m#Définit le début et la fin des abscisses.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      7\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'equal'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m#Les axes sont orthonormés\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      8\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0mOA_m\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m1\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0mOA_prime_m\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'o'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolor\u001b[0m \u001b[0;34m=\u001b[0m\u001b[0;34m'red'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabel\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'Points issus de la mesure'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m#Affiche les points expérimentaux\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'abs_debut' is not defined"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,8)) #Définit la taille de l'affichage du graphique\n",
    "plt.grid() # Affiche une grille sur le graphique\n",
    "plt.title(\"A modifier\", size=22) #Définit le titre du graphique\n",
    "plt.ylabel(\"A modifier\", size=18) #Affiche le titre des ordonnées\n",
    "plt.xlabel(\"A modifier\", size=18) #Affiche le titre des abscisses\n",
    "plt.xlim(abs_debut, abs_fin) #Définit le début et la fin des abscisses.\n",
    "plt.axis('equal') #Les axes sont orthonormés\n",
    "plt.plot(1/OA_m, 1 / OA_prime_m, 'o', color ='red', label = 'Points issus de la mesure') #Affiche les points expérimentaux\n",
    "plt.plot(X_modele, Y_modele, color = 'b', label = 'Modèle') #Affiche le modèle mathématique, ici une droite affine\n",
    "plt.legend(fontsize=18)# Affiche la légende\n",
    "plt.text(0,6,\"y = \" + str(a) + \"*\" + \"x\" + \" + \" + str(b), size=22, color='b', bbox=dict(boxstyle=\"round\", ec=(\"k\"), fc=(\"w\"))) #Affiche l'équation de la droite dans un encadré\n",
    "plt.show() #Affiche le graphique"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "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": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}