From d6e419e7d10ff445eb260198dd8e313231083b34 Mon Sep 17 00:00:00 2001 From: Bertrand Benjamin Date: Fri, 14 May 2021 10:52:14 +0200 Subject: [PATCH] =?UTF-8?q?Feat:=20lancement=20de=20l'activit=C3=A9=20prog?= =?UTF-8?q?rammation=20sur=20les=20co=C3=BBts?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- TST/12_Fonction_inverse/1E_couts.html | 15007 +++++++++++++++++++++++ TST/12_Fonction_inverse/1E_couts.ipynb | 554 + TST/12_Fonction_inverse/index.rst | 6 +- 3 files changed, 15566 insertions(+), 1 deletion(-) create mode 100644 TST/12_Fonction_inverse/1E_couts.html create mode 100644 TST/12_Fonction_inverse/1E_couts.ipynb diff --git a/TST/12_Fonction_inverse/1E_couts.html b/TST/12_Fonction_inverse/1E_couts.html new file mode 100644 index 0000000..50d1218 --- /dev/null +++ b/TST/12_Fonction_inverse/1E_couts.html @@ -0,0 +1,15007 @@ + + + + + +1E_couts + + + + + + + + + + + + + + + + + + + + + + + +
+
+
+
+
+
+ + +
+
+
+ + +
+
+
+ + +
+ + +
+
+
+ + +
+ + +
+
+
+
+
+
+
+
+
+ + +
+
+
+ + +
+
+
+ + +
+
+
+
+
+
+
+
+
+ + +
+
+
+ + +
+
+
+ + +
+
+
+
+
+
+
+
+
+ + +
+
+
+ + + + +
+
+
+ + + + +
+
+
+ + + + +
+
+
+ + + + +
+
+
+ + + + +
+
+
+ + +
+ + + + +
+
+
+ + +
+
+
+ + +
+
+
+ + + + +
+ + +
+ + + + + + + + + diff --git a/TST/12_Fonction_inverse/1E_couts.ipynb b/TST/12_Fonction_inverse/1E_couts.ipynb new file mode 100644 index 0000000..1919e78 --- /dev/null +++ b/TST/12_Fonction_inverse/1E_couts.ipynb @@ -0,0 +1,554 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Coûts d'une entreprises\n", + "\n", + "Dans ce TP, on propose d'étudier les coûts d'une entreprises. Nous commencerons pas étudier les coûts \"classiques\" puis le coût moyen et enfin les coûts marginal.\n", + "\n", + "Des aides sont disponibles à la fin de ce TP." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Coût total\n", + "\n", + "L'étude des coûts totaux d'une entreprise a mené à la formule suivante où $q$ décrit la quantité produite (entre 0 et 500):\n", + "$$ Coût(q) = 0.3q^3 + 1.25q^2 + 7,5q + 900$$" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "1. En vous inspirant de l'annexe sur les fonctions, programmer la fonction coût." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "2. Calculer les coûts pour 0, 5 et 10 objets" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "3. On souhaite calculer tous les coûts possibles. Pour cela, inspirer vous de l'annexe sur les boucles et les listes pour calculer les coûts pour les quantités allant de 0 à 500." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "quantites = list(range(0, 11))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "4. En vous inspirant de l'annexe sur les graphiques, tracer le graphique qui permet de visualiser l'évolution de ces coûts." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "5. Décrire l'évolution des coûts pour cette entreprise." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Étude du coût moyen\n", + "\n", + "Le coût moyen est le coût pour une unité produite. Plus ce coût moyen est faible plus le coût unitaire d'une unité est faible. Ce coût se calcule à partir du coût total avec la formule suivante\n", + "$$ C_m(q) = \\frac{C(q)}{q}$$\n", + "Dans la suite, on reprend la formule du coût de la partie précédente." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "1. Programmer la fonction qui permet de calculer le coût moyen." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "2. Calculer les coûts moyennes quand les quantités varient de 1 à 500." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "3. Tracer le graphique représentant les coûts moyens" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "4. Décrire la courbe représentative des coûts marginaux. Quelle quantité doit ont produire pour que le coût d'un objet soit le plus faible?" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Coût marginal\n", + "\n", + "Le coût marginal est le coût supplémentaire si l'on décide de produire une unité de plus. Il se calcule à partir du coût total avec la formule suivante:\n", + "$$ C_M(q) = C(q+1) - C(q)$$" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "1. Programmer la fonction qui permet de calculer le coût marginal.\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "2. Calculer le coût marginal pour les quantités allant de 1 à 499." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "3. Tracer le graphique représentant les coûts marginaux." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "4. Décrire la courbe des coûts marginaux. Que peut-on dire du coût de production si l'on chercher à augmenter la production." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Annexe" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Programmer des fonctions\n", + "\n", + "Les fonctions mathématiques peuvent aisement se programmer avec des fonctions de programmation. Seul la syntaxe change.\n", + "\n", + "Si l'on souhaite programmer la fonction\n", + "\n", + "$$ f(x) = \\frac{x + 1}{3x - 1} $$\n", + "On écrira" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "def f(x):\n", + " return (x+1)/(3*x-1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Quelques éléments sont à noter:\n", + "\n", + "- Il y a deux points à la fin de la première ligne\n", + "- Le mot clé `return` est indenté\n", + "- Toutes les opérations sont écrites avec les parenthèses appropriées.\n", + "\n", + "On pourra ensuite utiliser cette fonction pour calculer des images de nombres. Dans ce cas, la syntaxe est la même qu'en math." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1.0\n", + "0.3377926421404682\n" + ] + } + ], + "source": [ + "print(f(1))\n", + "print(f(100))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Boucles et listes\n", + "\n", + "En programmation, il existe plusieurs types de variables. Vous connaissez par exemples les `integer` qui sont des nombres entiers, les `string` qui sont les chaines de caractères. Il existe aussi les listes qui permettent de stocker plusieurs valeurs dans une seule variable." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[1, 5, 'a', 10]\n" + ] + } + ], + "source": [ + "liste = [1, 5, 'a', 10]\n", + "print(liste)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "On peut accéder à des valeurs particulières avec des crochets" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1\n", + "a\n" + ] + } + ], + "source": [ + "print(liste[0])\n", + "print(liste[2])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "On peut ajouter des éléments à une liste" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[1, 5, 'a', 10, 100]\n" + ] + } + ], + "source": [ + "liste.append(100)\n", + "print(liste)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Les listes marchent particulièrement bien avec les boucles. On peut alors faire des actions sur chacune des valeurs de la liste." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "5\n", + "25\n", + "aaaaa\n", + "50\n", + "500\n" + ] + } + ], + "source": [ + "for valeur in liste:\n", + " print(valeur * 5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Quand on fait des calculs sur des listes, il est utile garder les résultats dans une deuxième liste" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "deuxieme_liste = [] # On crée une liste vide\n", + "for valeur in liste:\n", + " deuxieme_liste.append(valeur*5)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[5, 25, 'aaaaa', 50, 500]\n" + ] + } + ], + "source": [ + "print(deuxieme_liste)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Tracer une graphique\n", + "\n", + "On peut tracer des graphiques à partir de deux listes:\n", + "\n", + "- la liste des abcisses (les x)\n", + "- la liste des ordonnées (les y)\n", + "\n", + "avant de pouvoir tracer ce graphique, il faut s'assurer d'avoir importer la biliothèque qui permet de les réaliser. Il faut donc valider (une seule fois) les lignes suivantes" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "On calcule ou on entre les abscisses et les ordonnées" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "abscisses = [0, 1, 2, 3, 4]\n", + "ordonnees = [2, 4, 5, 0, 1]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Et on peut tracer le graphique" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWoAAAD4CAYAAADFAawfAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAAsTAAALEwEAmpwYAAAl6klEQVR4nO3deXhU9b3H8fcv+0pYkhBIBsISQPZlArgLCkVRXAluKCpqa6t1ab23vbe1tva5vbdqtWrdkKooCrivFRQUN0LCDmICYUvYErYsQPbf/SNBKYJMIDNnls/refJ06JzM+XjI+XByzpnvGGstIiLiv8KcDiAiIj9ORS0i4udU1CIifk5FLSLi51TUIiJ+LsIbL5qcnGwzMzO98dIiIkFpyZIlu6y1KUd7zitFnZmZSX5+vjdeWkQkKBljNh/rOZ36EBHxcypqERE/p6IWEfFzKmoRET+nohYR8XMe3fVhjNkEVAINQL211u3NUCIi8r2W3J43ylq7y2tJRETkqHTqQ0JCQ6Plg1XbWbZlr9NRRFrM0yNqC8w1xljgaWvtM0cuYIy5BbgFoEuXLq2XUOQkWGv5aM0OHp5XSOHOKjLaxbLw16MICzNORxPxmKdH1GdYa4cC5wM/N8acdeQC1tpnrLVua607JeWo74IU8RlrLZ8WlDLh8S/56UtLqW+0XDuyCyV7D/L1ht1OxxNpEY+OqK21W5v/t9QY8yYwHFjozWAiJyp3w24enFtA3qa9ZLSL5a9XDOTSIenUN1reWb6NWXnFnN4z2emYIh47blEbY+KBMGttZfPjscAfvZ5MpIVWFO/jwbkFfL5uF6mJ0fzp4n5Myu5CVETTL44R4XDJkHRezSum/EAdSXGRDicW8YwnR9QdgTeNMYeWn2mt/ZdXU4m0QMGOSh6aW8Dcb3bSLi6S317Qh8kjM4mNCv/BsjluFy9+vZm3V2zlulMzfR9W5AQct6ittRuAQT7IItIim3bt528fF/LOim0kREVw13m9uPGMTBJjjn2k3D89ib6d2jA7v1hFLQHDK2NORbxp276D/P2TdcxZUkJkuOHWs3pw61ndaRcf5dH3T8p2cd87a1izrZx+nZO8nFbk5KmoJWCUVdbwxIL1zMzdAsDkkV25bVQPUhNjWvQ6Fw/uzJ8/WMvsvGLuv1hFLf5PRS1+b9+BWp5euIHnv9xEbUMjVwzN4PZze5LRLu6EXq9tXBQ/6ZfGW8u38ZsLTiEm8ofnskX8iYpa/FZVTT3Tv9jIsws3UFVbz0UDO3PneVl0T0k46dee5Hbx7optzP1mJxMGdW6FtCLeo6IWv1Nd18CMrzfz5GdF7Nlfy5i+HblnbC/6pLVptXWc1qMD6W1jmZNfrKIWv6eiFr9RW9/IrPxiHp+/jp0VNZyZlcw9Y3sz2NW21dcVFmaY6M7g0U/WUbL3wAmfRhHxBQ1lEsc1NFpeW1LCuQ9/yu/eWo2rXRyv3jKSGTeN8EpJH3LFsAwAXltS4rV1iLQGHVGLYxobLR+u3sHD8wooKttP//Q2/PGG/pzTK4XmN1h5VUa7OM7omcyc/BLuGJ2lQU3it1TU4nPWWhYUlPLQ3ELWbKugZ2oCT14zlHH903xS0Ieb6HZxxyvL+KpoN2dkaf6H+CcVtfjUV0W7eGhuIUs276VL+zgezhnExYPTCXfoaHZs344kxUYyK79YRS1+S0UtPrFsy14enFvAl+t3k9Ymhj9f2p8ct4vIcGcvk8REhnPJ4M68klfMvgO1tI3z7N2NIr6kohavWru9gofmFvDx2lI6xEfx3+NP4dqRXf3qTSY52S5e+Hozby/fxvWnZTodR+QHVNTiFUVlVfxtXiHvrdxOYkwEvxrbixtO70Z8tP/9yPXrnES/zk2DmlTU4o/8b6+RgFay9wCPfryO15eWEBMZzs9H9eCWM3v4/eznSdkufv/2GlZvLad/uuZ/iH9RUUurKK2obhqYtHgLxhimnNaN20b1IDkh2uloHrl4UDoPvL+W2fnFKmrxOypqOSl799fy1GdFvPD1JuobLBPdLm4f3ZPObWOdjtYiSXGRjOuXxlvLtvJbDWoSP6OilhNSWV3Hc19sZNrnG9lfW88lg9O587wsunaIdzraCZuU7eKdFdv4aM0OLh6c7nQcke+oqKVFDtY28OLXm3jqsyL2HqhjXL807h7bi14dE52OdtJO7d6BjHaxzMkvUVGLX1FRi0dq6huYlVfMY/PXU1ZZw9m9UvjV2N4MyAie87lhYYaJw1z87eNCivccwNVeg5rEP2gok/yo+oZGZucVM/rBz/j922volhzP7FtP5YUbhwdVSR9yhTsDYzSoSfyLjqjlqBobLe+v2s7f5hWyYdd+BmYk8T+XDeDMrGSfz+PwpfS2sZzRM5nXlpRwx7lZjr21XeRwKmr5N9ZaPllbykPzClm7vYLeHRN5evIwxvbtGNQFfbgct4vbX1nGV0W7ODMrxek4Iipq+d6X63fx148KWF68j8wOcTx65WAuHNg55I4qx/brSNu4SGblFauoxS+oqIUlm/fy4EcFfL1hN52TYvjLZQO4fFiG4wOTnBIdEc4lg9OZmbtFg5rEL6ioQ9iabeU8NLeQ+d+WkpwQxX0X9eWq4V30Zg+aTn88/9Um3lq2lSmnd3M6joQ4FXUIWl/aNDDp/VXbSYqN5N5xvZlyWiZxUfpxOKRv5zYMSE9iVn4J15+WGTLn58U/ac8MIcV7DvDIx+t4c1kJsZHh3DG6Jzed2Z2kWP8emOSUHHcGv3t7DWu2VWj+hzhKRR0CdlZU89j8dczKKybMGG46oxs/PbsHHQJkYJJTJgxuGtQ0K0+DmsRZKuogtmd/LU9+up4Xv95MQ6PlyuEufjEqi7SkGKejBYSk2EjG9U/j7eVb+a/xGtQkzlFRB6GK6jqmLdzAc19s5GBdA5cOyeDO87L0lugTMMnt4u3lGtQkzlJRB5EDtfU8/9Umnv5sA+UH6xg/oBN3jcmiZ2rgD0xyysjuHXC1j2V2frGKWhzjcVEbY8KBfGCrtfZC70WSlqqpb2Bm7haeWFDErqoaRvdJ5e4xvXRetRUcGtT08DwNahLntOQdDb8E1noriLRcXUMjry7ewqi/fsr9735Dz9R4Xv/ZqUyfkq2SbkWXD2sa1DRHg5rEIR4VtTEmAxgPTPNuHPHU3v21XPLEl/znG6tIbRPDy1NH8MrNIxnWtb3T0YJOettYzsxK4bX8YhoardNxJAR5ekT9CHAv0HisBYwxtxhj8o0x+WVlZa2RTY6h/GAd101fzLrSKp64eihv3nYap/cM7ql2TstxZ7CtvJov1+9yOoqEoOMWtTHmQqDUWrvkx5az1j5jrXVba90pKRpk4y37a+q54Z+L+XZHBU9fO4zxAzupoH1gTN/mQU35xU5HkRDkyRH16cAEY8wm4FVgtDHmJa+mkqOqrmvgphfyWFFSzt+vHMKoPqlORwoZhwY1zVuzk737a52OIyHmuEVtrf2NtTbDWpsJXAnMt9Ze6/Vk8m9q6hu4ZcYScjfu4eGcQZw/oJPTkULOpGwXtQ2NvLV8q9NRJMSE5hzLAFPX0MgvZi5jYWEZ/3vZQN3P65BTOrVhYEYSs/KKsVYXFcV3WlTU1tpPdQ+1bzU0Wu6atZx53+zk/gn9yMl2OR0ppE10u/h2RyWrt1Y4HUVCiI6o/Vhjo+Xe11by3srt/Ob8Plx/WqbTkULehEGdiY4IY1b+FqejSAhRUfspay2/e3s1ry8t4a7zenHr2T2cjiQ0DWo6v38aby/fRnVdg9NxJESoqP2QtZYH3l/Ly7lb+OnZPbjj3J5OR5LD5GS7qKyu51+rdzgdRUKEitoPPTS3kOe+2MiU0zL5j3G9dZ+0nxnZ7ftBTSK+oKL2M4/PX8fjC9Zz1XAX913UVyXth8LCDDnDXHxVtJstuw84HUdCgIraj0z7fAMPzi3k0iHpPHDJAJW0Hzs0qOm1JTqqFu9TUfuJGYs288D7a7lgQBp/vWIg4WEqaX/WuW0sZ2WlMGdJiQY1idepqP3Aa0tK+N1bqzm3TyqPTBpCRLj+WgJBjtvF9vJqvtCgJvEyNYLD3l2xjXtfW8GZWck8cc1QoiL0VxIozuubSru4SGbn6fSHeJdawUEfrdnBnbOW485szzOT3frw1AATHRHOpUMymPvNDvZoUJN4kYraIZ8WlHL7zGUMSE9i+pRsYqNU0oEoJzuDugbLW8s0qEm8R0XtgK+KdnHrjCX0TE3ghRuGkxCtzxgOVH3S2jAoI4nZ+RrUJN6jovaxJZv3MPWFfLq0j+OlqSNIiot0OpKcpEODmlZtLXc6igQpFbUPrSopZ8r0PDq2ieHlm0fQPj7K6UjSCiYMbh7UpIuK4iUqah9Zu72CydNzSYqL5OWpI0hNjHE6krSSNjGRXDCgE+8s38bBWg1qktanovaB9aVVTH4ul5iIcGZOHUnntrFOR5JWluN2UVlTz7/WbHc6igQhFbWXbd69n2umLQIML988gi4d4pyOJF4wolt7urSPY3ZeidNRJAipqL1o676DXP1sLrX1jbw8dQQ9UhKcjiReEhZmyHFn8PWG3Wzevd/pOBJkVNReUlpRzTXPLqKiuo4ZN42gd1qi05HEyy4flkGYaRoJINKaVNResLuqhmum5VJaWcPzNwynf3qS05HEBzolxXJWrxRe06AmaWUq6lZWfqCOa59bzJY9B5g+JZthXds5HUl86NCgpoXrypyOIkFERd2KKqvruO6fiykqreLZ69yM7N7B6UjiY+ed0pH28VHM0ae/SCtSUbeSA7X13Ph8Hmu2lvOPa4ZyVq8UpyOJA6Iiwrh0SDrzvtnJ7qoap+NIkFBRt4LqugZufjGfJZv38siVgzmvb0enI4mDctyupkFNy7c5HUWChIr6JNXWN3Lby0v5qmg3f71iEBcO7Ox0JHFY77REBrnaMjtPg5qkdaioT0J9QyO/fHUZ878t5c+XDODyYRlORxI/kePOoGBnJStLNKhJTp6K+gQ1NFrumbOCD1fv4HcX9uXqEV2cjiR+5KJBnYmJDGOWLipKK1BRn4DGRst/vbmKt5dv49c/6c1NZ3RzOpL4mTYxkVzQvxPvalCTtAIVdQtZa7n/3TW8mlfMHaN78vNRPZ2OJH4qJ7tpUNOHqzWoSU6OiroFrLX85cNveeHrzdx8ZjfuGtPL6Ujix0Z0a0/XDnHM1ukPOUnHLWpjTIwxZrExZoUxZo0x5n5fBPNHj36yjqcXbmDyyK789oJTMMY4HUn8mDGGHLeLRRv2aFCTnBRPjqhrgNHW2kHAYGCcMWakV1P5oac+K+KRj9cxcVgG90/op5IWj1w+tGlQ05x8DWqSE3fcorZNqpr/GNn8FVI3hz7/5Ub+8uG3TBjUmb9cPpCwMJW0eCYtKYazNahJTpJH56iNMeHGmOVAKTDPWpt7lGVuMcbkG2Pyy8qCZyDNq4u38Id3v+En/TryUM4gwlXS0kKTsl3sqKhmYWHw7BfiWx4VtbW2wVo7GMgAhhtj+h9lmWestW5rrTslJTjmXLy5rITfvLmKc3qn8PerhhAZrmuv0nKj+3SkQ3yULirKCWtR81hr9wELgHFeSeNHPli1nXtmr+DU7h146tphREeEOx1JAtShQU0fr9WgJjkxntz1kWKMadv8OBYYA3zr5VyO+mTtTu54ZRlDu7Tj2evcxESqpOXk5GQ3DWp6c9lWp6NIAPLkiLoTsMAYsxLIo+kc9XvejeWcz9eV8bOXltK3cxum35BNfHSE05EkCPTqmMhgV1tm52tQk7ScJ3d9rLTWDrHWDrTW9rfW/tEXwZyQu2E3N7+YT/eUeF68cThtYiKdjiRBJMftonBnFSs0qElaSFfHmi3bspcbn88jvW0sL00dQdu4KKcjSZC5aFCnpkFNebqoKC2jogZWby3n+umLSU6MZubNI0lOiHY6kgShxJhILhjQiXdXaFCTtEzIF3Xhzkqum76YxJhIXp46go5tYpyOJEFskttFVU09H6zSoCbxXEgX9cZd+7lmWi4RYYaXp44go12c05EkyA3v1p5MDWqSFgrZoi7ec4Crn11EY6Nl5s0jyEyOdzqShABjDBPdLnI37mHTLg1qEs+EZFHvKK/m6mmLOFDbwIybRtAzNdHpSBJCDg1q0lG1eCrkirqssoarpy1i7/46XrxxOH07t3E6koSYtKQYzumdyutLS6hvaHQ6jgSAkCrqvftruXZaLtv3VfPPG7IZ5GrrdCQJUTluFzsrali4ToOa5PhCpqjLD9YxeXouG3fv57nr3WRntnc6koSw0X1SmwY15WlOtRxfSBR1VU09N/xzMQU7Knn62mGc1jPZ6UgS4qIiwrhsaNOgpl0a1CTHEfRFfbC2gakv5LGipJzHrhrKqD6pTkcSAZpOf9Q3Wt7SoCY5jqAu6pr6Bm59aQm5G/fwcM4gxvVPczqSyHeyOiYypEtbZuVpUJP8uKAt6rqGRn4xcxkLC8v438sHcvHgdKcjifxAjtvFutIqlhfvczqK+LGgLOqGRsuds5Yz75ud/OnifuS4XU5HEjmqCwd2IjYyXPdUy48KuqJubLT8+rUVvL9yO/91wSlMPjXT6Ugix/T9oKbtHKitdzqO+KmgKmprLf/99mreWLqVu8f04uazujsdSeS4JmUfGtS0w+ko4qeCpqittfzpvbXMzN3Cbef04PbRPZ2OJOKR7Mx2dEuO1+kPOaagKeoH5xYw/cuN3HB6Jr/+SW+MMU5HEvFI06CmDBZv3MNGDWqSowiKon58/jqeWFDEVcO78PsL+6qkJeBcMTSD8DCjo2o5qoAv6mmfb+DBuYVcNiSdP1/SXyUtASm1TQzn9Erh9SUa1CQ/FNBFPWPRZh54fy3jB3Ti/64YSFiYSloCV062i9LKGj4r1KAm+XcBW9Rz8ov53VurOe+UVB65cjAR4QH7nyICNA1qSk6I0ukP+YGAbLd3VmzjP15fyZlZyTx+9VAiVdISBCLDw7hsaAafrC2lrFKDmuR7AddwH63ZwV2zlpOd2Z5nJruJiQx3OpJIq8lxZ2hQk/xAQBX1pwWl/GLmUgZmJPHclGxio1TSElx6piYytEtbZuVrUJN8L2CK+quiXdw6Ywm9Oiby/A3DSYiOcDqSiFfkuF2sL61imQY1SbOAKOr8TXuY+kI+mR3imXHTCJJiI52OJOI1Fw7q3DSoKU8XFaWJ3xf1ypJ93PDPPNLaxDBj6nDax0c5HUnEqxKiIxg/sBPvrtimQU0C+HlRr91eweTnFtM2PpKXbx5BamKM05FEfGJStov9tQ28v3K701HED/htUa8vreLaabnERYUzc+pIOiXFOh1JxGfcXdvRXYOapJlfFvXm3fu5ZtoijDG8PHUErvZxTkcS8ammQU0u8jbtZUNZldNxxGHHLWpjjMsYs8AY840xZo0x5pfeDLR130GufjaX2vpGXp46gu4pCd5cnYjfunxoevOgphKno4jDPDmirgfusdb2BUYCPzfG9PVGmJ0V1Vz97CIqquuYcdMIeqclemM1IgEhtU0Mo3qn8PpSDWoKdcctamvtdmvt0ubHlcBaoNU/Kbb8QB3XTMtlV2UNL9w4nP7pSa29CpGAk+N2UVZZw6cFGtQUylp0jtoYkwkMAXKP8twtxph8Y0x+WVnLf6gSYyI4o2cyz03JZmiXdi3+fpFgNKpPKskJ0bqoGOI8LmpjTALwOnCntbbiyOettc9Ya93WWndKSkrLg4QZ/jChHyO7d2jx94oEq8jwMC4fms78bzWoKZR5VNTGmEiaSvpla+0b3o0kIoeb6HZR32h5c5kuKoYqT+76MMBzwFpr7cPejyQih+uZmsCwru2YladBTaHKkyPq04HJwGhjzPLmrwu8nEtEDpPjzqCobD9Lt+xzOoo4wJO7Pr6w1hpr7UBr7eDmrw98EU5Emowf2Jm4KA1qClV++c5EEfl3CdERjB/QifdWbmN/jQY1hRoVtUiA+G5Q0yoNago1KmqRADGsazu6p8Tr9EcIUlGLBAhjDDluF/mb91KkQU0hRUUtEkAu+25Qk46qQ4mKWiSApCbGMKp3Kq8v2UqdBjWFDBW1SICZlO1iV5UGNYUSFbVIgDmnd4oGNYUYFbVIgIkMD+PyYU2Dmkorq52OIz6gohYJQBOHuWhotLy5dKvTUcQHVNQiAahnagLuru2Yla9BTaFARS0SoHLcLjaU7Wfplr1ORxEvU1GLBKjxAzsRHxXOLL1TMeipqEUCVHx0BBcO7Mx7K7dTpUFNQU1FLRLAcrIzOFDbwAcrNagpmKmoRQLY0C7t6JESzyzdUx3UVNQiAezQoKYlm/eyvlSDmoKVilokwF02NIPwMMMcHVUHLRW1SIBLSYxmdJ9UXl+qQU3BSkUtEgQmuZsGNS34ttTpKOIFKmqRIHBO7xRSEqOZnV/idBTxAhW1SBCICA/j8qEZLCgopbRCg5qCjYpaJEhMdGfQ0Gh5Y5kGNQUbFbVIkOiRkkB2Zjtm52lQU7BRUYsEkYluFxt27WfJZg1qCiYqapEgMn6ABjUFIxW1SBCJj47gokGdeX+VBjUFExW1SJCZ6HZxoLaB91duczqKtBIVtUiQGdqlLT1TE3T6I4ioqEWCTNOgpgyWbtnH+tJKp+NIKzhuURtjphtjSo0xq30RSERO3qVDMogIM3qnYpDw5Ij6eWCcl3OISCs6NKjpjaUlGtQUBI5b1NbahcAeH2QRkVY0KdvFrqpa5mtQk09s2rWfd1Z45wJuRGu9kDHmFuAWgC5durTWy4rICTq7VwqpidHMyS/mJ/3SnI4TtLbuO8hjn6xjzpIS2sREMLZvR2Iiw1t1Ha1W1NbaZ4BnANxut96/KuKwiPAwLh+WwTMLN1BaUU1qmxinIwWVssoanliwnpm5WwCYPLIrt43q0eolDa1Y1CLifyYOy+DJT4t4felWfnZOD6fjBIV9B2p5euEGnv9yE7UNjUwclsHt52aR3jbWa+tUUYsEse4pCQzPbM+c/GJ+enZ3jDFORwpYVTX1TP9iI88u3EBVbT0XDezMXWN60S053uvrPm5RG2NeAc4Bko0xJcB91trnvB1MRFpHTraLX81ZQd6mvQzv1t7pOAGnuq6BGV9v5snPitizv5axfTty99he9Elr47MMxy1qa+1VvggiIt5xwYA0/vDOGmbnF6uoW6C2vpFZ+cU8Pn8dOytqODMrmXvG9mawq63Ps+jUh0iQi4uK4KJBnXhr2Tbuu6gviTGRTkfyaw2NljeXbeWRjwsp2XsQd9d2PHrlEEZ27+BYJhW1SAiY6HbxyuJi3l+5nSuH6/bZo2lstHy4egcPzyugqGw//dPb8KdL+nNOrxTHz+2rqEVCwBBXW7JSE5iVX6yiPoK1lgUFpTz4USHfbK8gKzWBJ68Zyrj+aY4X9CEqapEQ0DSoycWfP1jLup2VZHVMdDqSX/iqaBcPflTA0i376NI+jodzBnHx4HTCw/yjoA/R9DyREHHp0PTmQU0af7psy16umbaIq5/NZdu+av58aX8+uedsLhua4XclDTqiFgkZyQnRnHtKKm8s3cq94/oQGR56x2nfbKvg4XkFfLy2lA7xUfz3+FO4dmRXr7ybsDWpqEVCyKRsFx+t2ckna0sZ1z905n8UlVXxt3mFvLdyO4kxEfxqbC9uOL0b8dGBUYGBkVJEWsVZWd8PagqFoi7ec4C/f7KO15eWEBMZzs9H9eCWM3uQFBdYtyiqqEVCSER4GFcMy+Cpz4rYWVFNxyAd1FRaUc3jC9bzyuItGGOYclo3bhvVg+SEaKejnRAVtUiImeh28Y9Pi3htSQk/H9XT6Titau/+Wp76rIgXvt5EfYNlotvFHef2pFOS9wYm+YKKWiTEdEuOZ3i3pkFNt53Tw2/uFT4ZldV1TPt8I899sZH9tfVcOjidX56XRdcO3h+Y5AsqapEQNMnt4p45K1i8cQ8jHHxr9Mk6WNvAC19v4qnPith3oI5x/dK4e2wvegXZfeIqapEQdP6ANO57Zw2z80sCsqhr6ht4dXExjy9YT1llDWf3SuFXY3szICPJ6WheoaIWCUFNg5o689ayrfxhQuAMaqpvaOSNpVt59JN1bN13kOHd2vOPa4aSnRncUwFV1CIhKsedwSuLt/Deyu1c5efzPxobLe+t2s4j8wrZsGs/gzKS+J/LBnBmVnJQnGM/HhW1SIga7GpLr44JzMor9tuittby8dpSHppbwLc7KundMZGnJw9jbN+OIVHQh6ioRULUoUFND7y/lsKdlX51Ac5ay5frd/Pg3AKWF+8js0Mcj145mAsHdvbLWRzeFnpv9heR71w6pHlQU57/DGpasnkPVz27iGufy6W0opq/XDaAeXef7ZdT7XxFR9QiIaxDQjTnndKRN5c1DWqKinDu2G311nIemlvAgoIykhOiue+ivlw9ogvREf49MMkXVNQiIW5Stot/rdnB/G93Mq5/J5+vf31pJQ/PK+SDVTtIio3k3nG9mXJaJnFRqqdDtCVEQtyZWcl0bBPN7PwSnxb1lt0HeOSTQt5atpXYyHDuGN2Tm87sTlJsYNwq6EsqapEQd2hQ05OfFrGjvJq0JO8OatpRXs1j89cxK6+Y8DDDTWd046dn96BDgA5M8gUVtYgwcZiLJxYU8fpS7w1q2l1Vw5OfFjFj0WYareXK4S5uH50VtBP8WpOKWkTITI5nRLf2zPbCoKbyg3VM+3wD07/YyMG6Bi4dksGd52Xhah/XausIdipqEQGaLirePXsFuRv3MLIV5n8cqK3nn19u4pmFGyg/WMf4AZ24a0wWPVP9537tQKGiFhEAzu/fifveXsPs/OKTKurqugZm5m7hH5+uZ1dVLaP7pHL3mF70Tw/OgUm+oKIWEQBio8K5aHBn3lhawh8m9KNNCwc11TU08tqSEv7+yTq2l1dzavcOPD25N8O6tvNS4tChohaR7+S4XczM3cJ7K7Zz9QjP5n80NFreXbGNRz4uZNPuAwx2teXBiYM4vWeyl9OGDhW1iHxnUEYSvTsmMiu/+LhFba3lozU7eXheAYU7q+iTlsi069yce0pqSA1M8gUVtYh8xxjDRHcGD7y/loIdlfRO++GFP2stC9ft4qG5BawsKad7cjyPXTWE8QM6ERaiszi8TUOZROTfXDoknchww+z8Hw5qWrxxD5OeXsT10xezu6qW/7tiIHPvOouLBnVWSXuRR0fUxphxwKNAODDNWvsXr6YSEcccPqjpP5oHNa0s2ceDcwtZWFhGSmI0f7y4H5OyXRqY5CPHLWpjTDjwBDAGKAHyjDHvWGu/8XY4EXFGTraLD1fvYNoXG1hRvI+P1uykbVwkvzm/D9edmklslAralzw5oh4OrLfWbgAwxrwKXAyoqEWC1FlZKaS1ieH//lVAQnQEd56XxU1ndAuYz1YMNp4UdTpw+MmqEmDEkQsZY24BbgHo0sU/P9ZHRDwTHmb40yX9WbOtnOtPzaRdfJTTkUJaq931Ya19BngGwO1229Z6XRFxxpi+HRnTt6PTMQTP7vrYCrgO+3NG8/8nIiI+4ElR5wFZxphuxpgo4ErgHe/GEhGRQ4576sNaW2+M+QXwEU2350231q7xejIREQE8PEdtrf0A+MDLWURE5Cj0zkQRET+nohYR8XMqahERP6eiFhHxc8ba1n9vijGmDNh8gt+eDOxqxTitRblaRrlaRrlaJhhzdbXWphztCa8U9ckwxuRba91O5ziScrWMcrWMcrVMqOXSqQ8RET+nohYR8XP+WNTPOB3gGJSrZZSrZZSrZUIql9+doxYRkX/nj0fUIiJyGBW1iIifc6yojTHjjDEFxpj1xpj/PMrz0caYWc3P5xpjMv0k1xRjTJkxZnnz11QfZJpujCk1xqw+xvPGGPP35swrjTFDvZ3Jw1znGGPKD9tWv/dRLpcxZoEx5htjzBpjzC+PsozPt5mHuXy+zYwxMcaYxcaYFc257j/KMj7fHz3M5fP98bB1hxtjlhlj3jvKc627vay1Pv+iaVxqEdAdiAJWAH2PWOY24Knmx1cCs/wk1xTgcR9vr7OAocDqYzx/AfAhYICRQK6f5DoHeM+Bn69OwNDmx4lA4VH+Hn2+zTzM5fNt1rwNEpofRwK5wMgjlnFif/Qkl8/3x8PWfTcw82h/X629vZw6ov7uA3OttbXAoQ/MPdzFwAvNj18DzjXGGD/I5XPW2oXAnh9Z5GLgRdtkEdDWGNPJD3I5wlq73Vq7tPlxJbCWps/+PJzPt5mHuXyueRtUNf8xsvnryLsMfL4/epjLEcaYDGA8MO0Yi7Tq9nKqqI/2gblH/sB+t4y1th4oBzr4QS6Ay5t/XX7NGOM6yvO+5mluJ5za/Kvrh8aYfr5eefOvnENoOho7nKPb7EdygQPbrPnX+OVAKTDPWnvM7eXD/dGTXODM/vgIcC/QeIznW3V76WJiy70LZFprBwLz+P5fTfmhpTTNLxgEPAa85cuVG2MSgNeBO621Fb5c9485Ti5Htpm1tsFaO5imz0Qdbozp74v1Ho8HuXy+PxpjLgRKrbVLvL2uQ5wqak8+MPe7ZYwxEUASsNvpXNba3dbamuY/TgOGeTmTJ/zyA4ittRWHfnW1TZ8SFGmMSfbFuo0xkTSV4cvW2jeOsogj2+x4uZzcZs3r3AcsAMYd8ZQT++Nxczm0P54OTDDGbKLp9OhoY8xLRyzTqtvLqaL25ANz3wGub358BTDfNp+ZdzLXEecxJ9B0ntFp7wDXNd/JMBIot9ZudzqUMSbt0Hk5Y8xwmn7evL5zN6/zOWCttfbhYyzm823mSS4ntpkxJsUY07b5cSwwBvj2iMV8vj96ksuJ/dFa+xtrbYa1NpOmjphvrb32iMVadXt59JmJrc0e4wNzjTF/BPKtte/Q9AM9wxiznqYLVlf6Sa47jDETgPrmXFO8ncsY8wpNdwMkG2NKgPtourCCtfYpmj7P8gJgPXAAuMHbmTzMdQXwM2NMPXAQuNIH/9hC0xHPZGBV8/lNgN8CXQ7L5sQ28ySXE9usE/CCMSacpn8YZltr33N6f/Qwl8/3x2Px5vbSW8hFRPycLiaKiPg5FbWIiJ9TUYuI+DkVtYiIn1NRi4j4ORW1iIifU1GLiPi5/wdlf7ZQczP7fgAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(abscisses, ordonnees)" + ] + }, + { + "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": "3.9.4" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/TST/12_Fonction_inverse/index.rst b/TST/12_Fonction_inverse/index.rst index 7801091..bf967cd 100644 --- a/TST/12_Fonction_inverse/index.rst +++ b/TST/12_Fonction_inverse/index.rst @@ -2,7 +2,7 @@ Fonction inverse ################ :date: 2021-05-06 -:modified: 2021-05-06 +:modified: 2021-05-14 :authors: Benjamin Bertrand :tags: Fonctions inverse :category: TST @@ -13,6 +13,10 @@ Fonction inverse Activité avec le tableur pour calcul un coût puis un coût unitaire. Les graphiques seront tracés pour approcher les notions de limites. +`Activité de programmation sur les études de coûts (version Mybinder) `_ +`Activité de programmation sur les études de coûts (version ipython) <./1E_couts.ipynb>`_ +`Activité de programmation sur les études de coûts (version html) <./1E_couts.html>`_ + Bilan: nécessité d'étudier la fonction 1/x pour l'étude du coût unitaire Étape 2: Bastonage sur des exercices types.