{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# La loi d’Ohm (version élève, polyfit et sans fonction)\n",
    "\n",
    "\n",
    "Mathilde, élève de 2nde, souhaite tracer la caractéristique d’un dipôle ohmique, c’est-à-dire la courbe donnant les valeurs de la tension aux bornes du dipôle ohmique en fonction des valeurs de l’intensité du courant qui le traverse.\n"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {
    "raw_mimetype": "text/restructuredtext"
   },
   "source": [
    ":download:`Télécharger le pdf <./loi_ohm_eleve_polyfit_sans_fonction.pdf>`\n",
    "\n",
    ":download:`Télécharger le notebook <./loi_ohm_eleve_polyfit_sans_fonction-download.ipynb>`\n",
    "\n",
    ":download:`Lancer le notebook sur binder (lent) <https://mybinder.org/v2/gl/pyspc%2Fpyspc/master?filepath=07-activites%2F02-seconde%2Floi_d_ohm%2Floi_ohm_eleve_polyfit_sans_fonction.ipynb>`"
   ]
  },
  {
   "attachments": {
    "circuit.png": {
     "image/png": "iVBORw0KGgoAAAANSUhEUgAABJQAAAH+CAYAAADK/VTeAAAAAXNSR0IArs4c6QAAAARnQU1BAACx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\n"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Elle a schématisé le circuit de son expérience :\n",
    "\n",
    "![circuit.png](attachment:circuit.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Dans la cellule ci-dessous, indiquer la signification des symboles X et Y et le nom des bornes 1, 2, 3, 4."
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "X :         1 :             2 :\n",
    "Y :         3 :             4 :\n"
   ]
  },
  {
   "attachments": {
    "tableau.png": {
     "image/png": "iVBORw0KGgoAAAANSUhEUgAABIUAAABnCAYAAACej/I3AAAAAXNSR0IArs4c6QAAAARnQU1BAACx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\nTkSuQmCC\n"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mathilde relève les mesures expérimentales suivantes : \n",
    "\n",
    "![tableau.png](attachment:tableau.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2. Aider Mathilde à coder la deuxième ligne du tableau de valeurs dans la cellule vide ci-dessous en vous aidant du code de la première ligne (attention les valeurs de l'intensité y ont été converties en ampère)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# array signifie tableau en anglais\n",
    "I=np.array([0,25e-3,50e-3,75e-3,100e-3,125e-3])\n",
    "print (I)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3. Mathilde veut maintenant afficher la caractéristique « intensité-tension » du dipôle ohmique en respectant les consignes suivantes :\n",
    "\n",
    "    - axe des abscisses (horizontal) : Intensité I (mA)\n",
    "    - axe des ordonnées (vertical) : Tension U(V)\n",
    "    - points expérimentaux : croix + de couleur rouge \n",
    "    - Titre: \"Caractéristique Intensité-Tension d’un dipôle ohmique\"\n",
    "\n",
    "Les cellules ci-dessous contiennent chacune une ligne du code nécessaire à l'affichage de la caractéristique. \n",
    "Exécuter chaque cellule au fur et à mesure afin de comprendre leur utilité. Noter si besoin des commentaires dans les cellules laissées vides à cet effet."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig = plt.figure(figsize=(12,10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.plot(I,U)"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "commentaire : "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.plot(I,U,'r+')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.plot(I,U,'r+')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "commentaire : "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.plot(I,U,'r+',label='U=f(I)')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "commentaire : "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.xlabel(\"intensité I (A)\")"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "commentaire : "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.ylabel(\"tension U (V)\")"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "commentaire : "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.grid()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "commentaire : "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.title(\"Caractéristique Intensité-Tension \"\n",
    "          \"d’un dipôle ohmique\")"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "commentaire : "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4. Exécutez maintenant le programme en entier! "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "I=np.array([0,25e-3,50e-3,75e-3,100e-3,125e-3]) \n",
    "U=np.array([0,1.7,3.4,5.1,6.8,8.5])\n",
    "fig = plt.figure(figsize=(12,10))\n",
    "plt.plot(I,U,'r+',label='U=f(I)')\n",
    "plt.legend()\n",
    "plt.xlabel(\"intensité I (A)\")\n",
    "plt.ylabel(\"tension U (V)\")\n",
    "plt.grid()\n",
    "plt.title(\"Caractéristique Intensité-Tension d’un \"\n",
    "          \"dipôle ohmique\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "5. Il s'agit maintenant de modéliser la courbe obtenue."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "   5.1. Quelle est la forme de la courbe obtenue?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "5.2. Quelle est l'équation mathématique d'une telle courbe?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "5.3. Exécutez le programme ci-dessous permettant de modéliser la courbe obtenue par une droite."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "coeff=np.polyfit(I, U,1)\n",
    "print ('{0:.1f}'.format(coeff[0]), \n",
    "       '{0:.1f}'.format(coeff[1]))\n",
    "Umodel = coeff[0]*I+coeff[1]\n",
    "print('U={0:.1f}'.format(coeff[0]),'x I')\n",
    "print('Les valeurs de la tension modélisée sont',Umodel)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "5.3.1. Que représente coeff [0] ?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "5.3.2. Que représente coeff[1] ?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "5.4. Affichez la droite modélisée grâce au programme ci-dessous."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig = plt.figure(figsize=(12,10))\n",
    "plt.plot(I,U,'r+',label='U=f(I)')\n",
    "plt.plot(I,Umodel,'b',label='modèle linéaire')\n",
    "plt.legend()\n",
    "plt.xlabel(\"intensité I (A)\")\n",
    "plt.ylabel(\"tension U (V)\")\n",
    "plt.grid()\n",
    "plt.title(\"Caractéristique Intensité-Tension \"\n",
    "          \"d’un dipôle ohmique\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "5.4.1. La tension U et l’intensité I sont-elles proportionnelles ? Pourquoi ?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "5.4.2. Que remarquez-vous à propos de la valeur du coefficient directeur de la droite?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "5.4.3. En déduire une formule appelée loi d'Ohm entre la tension U, l’intensité I et la résistance électrique R du \n",
    "dipôle ohmique."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "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": "3.6.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}