basic-convolution-notebook

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   "cells": [
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Une simple exploration avec notebook"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Bonjour \u00e0 tous et bienvenue sur votre premier notebook!\n",
      "\n",
      "Un document notebook est compos\u00e9 d'une suite de cellules.\n",
      "Chaque cellule poss\u00e8de un type pr\u00e9cis. Le titre juste au-dessus est une cellule _'heading 1'_ tandis que celle-ci est de type _'markdown'_.\n",
      "Mais en g\u00e9n\u00e9ral, on utilise des cellules _'code'_ qui sont les seules \u00e0 \u00eatre interpr\u00e9t\u00e9es par Python.\n",
      "\n",
      "PS : Pour \u00eatre tout \u00e0 fait exact, la page que vous \u00eates en train de visualiser est probablement la repr\u00e9sentation html du document que vous pourrez retrouver sur [github](https://gist.github.com/BertrandDechoux/8817646)."
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Votre premi\u00e8re fonction magique"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "IPython rajoute un ensemble de racourcis appel\u00e9s _'magic functions'_ qui vont simplifieront la vie.\n",
      "Commen\u00e7ons tout d'abord par charger _numpy_ et _matplotlib_. L'argument _inline_ est pr\u00e9cis\u00e9 afin que les graphiques g\u00e9n\u00e9r\u00e9s par _matplotlib_ soient integr\u00e9s directement dans ce document. En une seule ligne, votre environnement est pr\u00eat."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%pylab inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Populating the interactive namespace from numpy and matplotlib\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "/Users/dechouxb/anaconda/envs/py3k/lib/python3.3/site-packages/matplotlib/mathtext.py:46: UserWarning: Due to a bug in pyparsing <= 2.0.0 on Python 3.x, packrat parsing has been disabled.  Mathtext rendering will be much slower as a result.  Install pyparsing 2.0.0 or later to improve performance.\n",
        "  warn(\"Due to a bug in pyparsing <= 2.0.0 on Python 3.x, packrat parsing \"\n"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Description du probl\u00e8me"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Supposons que nous soyons mandat\u00e9s pour v\u00e9rifier la capacit\u00e9 d'un porte-carte rigide. Comment feriez vous? Cela semble relativement simple. Il suffit de faire l'addition de l'\u00e9paisseur de chaque carte pour connaitre l'\u00e9paisseur minimum de ce porte-carte afin de garantir un nombre donn\u00e9 de cartes.\n",
      "\n",
      "Si on suppose que l'on poss\u00e8de une carte avec une \u00e9paisseur de 800 microm\u00e8tres et un autre carte avec une \u00e9paisseur de 1200 microm\u00e8tres, alors pour contenir ces 2 cartes, il faut au minimum 2000 microm\u00e8tres.\n",
      "\n",
      "On peut le visualiser comme montr\u00e9 ci-dessous. La compr\u00e9hension du code n'est pas requise, seul le graphique n\u00e9cessite une attention."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def drawRequiredWidth(cardWidths):\n",
      "    assert len(cardWidths) > 0\n",
      "    figsize(20,4)\n",
      "    colors = 'rgbcmykw'\n",
      "    bins = arange(200)\n",
      "\n",
      "    requiredWidth = None\n",
      "        \n",
      "    for (n,cardWidth) in enumerate(cardWidths):\n",
      "        hist = histogram(cardWidth / 10, density=True, bins=bins)\n",
      "        y = hist[0][0:199]\n",
      "        requiredWidth = y if requiredWidth is None else convolve(requiredWidth,y)\n",
      "        bar(hist[1][0:199] * 10,y,\n",
      "            alpha=0.5, color=colors[n],\n",
      "            label='Epaisseur carte n\u00b0 ' + str(n + 1),\n",
      "            linewidth=0, width=10, align='center')\n",
      "    \n",
      "    bar(arange(len(requiredWidth)) * 10, requiredWidth, alpha=0.5, label='Epaisseur n\u00e9cessaire',\n",
      "        linewidth=0, width=10, align='center')\n",
      "    \n",
      "    title('Epaisseur minimum n\u00e9cessaire du porte-carte rigide')\n",
      "    ylabel('Probablilit\u00e9')\n",
      "    xlabel('Epaisseur en microm\u00e8tres (1000 millim\u00e8tres)')\n",
      "    legend()\n",
      "    grid()\n",
      "    \n",
      "    return requiredWidth\n",
      "\n",
      "card1Width = 800\n",
      "card2Width = 1200\n",
      "result = drawRequiredWidth([card1Width,card2Width])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
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kB3sZkFTswURycG0hqZgrJAfzhYjaOxaYiIiIiIiIiB5CCoWi3TaMpo6Ht8hR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\nERERUdOMFph27drVZJPvMWPGtElARC3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       "text": [
        "<matplotlib.figure.Figure at 0x1037f9450>"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Bien sur, s'il y a une incertitude concernant l'\u00e9paisseur d'une des deux cartes, alors cette incertitude doit \u00eatre gard\u00e9e pour le r\u00e9sultat final."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "card1Width = random.normal(800, 20, 1000)\n",
      "card2Width = 1000\n",
      "result = drawRequiredWidth([card1Width,card2Width])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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AAAAAAFR5FJgAB1iLDyvRgwlW4d4HK5F/sAq5BwC3hgITAAAAAAAAbgk9mACg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\nJe9LtjoE1FDc+2Al8g9WIfd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       "text": [
        "<matplotlib.figure.Figure at 0x10634fad0>"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Et en pratique, cette incertitude va exister pour les deux cartes."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "card2Width = random.normal(1000, 20, 1000)\n",
      "result = drawRequiredWidth([card1Width,card2Width])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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MPSKi+mHhiYiIiIiIiIhkCoWiyTaqpuaHt9oRVajvrXK81Y7qiLfaEREREbU8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\nq+6JeDWpz75ERERERERERNQ0GC083bt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       "text": [
        "<matplotlib.figure.Figure at 0x10a85ca90>"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Techniquement, on vient de faire la somme de plusieurs variables al\u00e9atoires en utilisant une convolution et on pourrait d\u00e9rouler les maths pour compl\u00e9ter l'explication. Mais une image vaut mille mots et, plus g\u00e9n\u00e9ralement, les graphiques sont un bon moyen de vulgarisation.\n",
      "\n",
      "Suite \u00e0 cette tr\u00e8s courte mod\u00e9lisation du probl\u00e8me, nous recevons plus d'information sur la mission.\n",
      "\n",
      "Apr\u00e8s \u00e9tude du march\u00e9, il s'av\u00e8re que les cartes ont toutes tendance \u00e0 avoir la m\u00eame \u00e9paisseur. Mais que deux types de cartes se distinguent tout de m\u00eame : les cartes bancaires et les autres. En effet, les cartes bancaires poss\u00e8dent g\u00e9n\u00e9ralement un imprim\u00e9 en relief et sont donc plus \u00e9paisse. La seconde remarque est qu'\u00e0 priori les clients potentiels seraient interess\u00e9s par un porte-carte pouvant contenir une carte de type bancaire plus quatres autres non bancaires.\n",
      "\n",
      "Quelles sont les contraintes sur l'\u00e9paisseur du porte-carte?\n",
      "Voici la r\u00e9ponse :\n",
      "\n"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "creditCard = random.normal(1200, 60, 1000)\n",
      "otherCard = random.normal(800, 40, 1000)\n",
      "result = drawRequiredWidth([creditCard,otherCard,otherCard,otherCard,otherCard])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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EREQkkslk/Xahanr4cKodERERERERkRnwMyv1d5xqR0REREREREREDy0Wnoj6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\nvb0VFhamr776yrzPz89PK1euNMdJSUkaO3asJCk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       "text": [
        "<matplotlib.figure.Figure at 0x106d2cb10>"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Et l'on peut d\u00e9sormais s'int\u00e9resser de plus pr\u00e8s au r\u00e9sultat."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "bar(arange(len(result)) * 10, result, linewidth=0, width=10, align='center')\n",
      "print('plus probable avec prise en compte des variations d\\'\u00e9paisseur : ', result.argmax() * 10)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "plus probable avec prise en compte des variations d'\u00e9paisseur :  4380\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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p7OxMkrS1tWVsbCzHjh2reu2p13R2dubxxx+/GGPjCuIXKLW4HOulWjgkOLqY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\nRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x106dd4250>"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Il faudra discuter ensuite discuter avec le d\u00e9cideur final du risque \u00e0 prendre. On pourrait choisir par exemple de prendre l'\u00e9paisseur telle que 99% des cas sont couverts. Mais ceci est un autre sujet, qui ne sera pas discut\u00e9 dans cette analyse."
     ]
    }
   ],
   "metadata": {}
  }
 ]
}