{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# toy_notebook_fr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# March 28, 2019"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**1. A propos du calcul de π**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**1.1. En demandant à la lib maths**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mon ordianteur m'indique que π vaut *approxiamtivement*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.141592653589793\n"
     ]
    }
   ],
   "source": [
    " from math import *\n",
    " print(pi)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3.141592653589793"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**1.2.En utilisant la méthode des aiguilles de Buffon**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "invalid syntax (<ipython-input-10-8125d01a75d0>, line 1)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-10-8125d01a75d0>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m    Mais calculé avec la **méthode** des http://aiguillesdeBuffon.com , on obtiendrait comme **approximation** :\u001b[0m\n\u001b[0m               ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
     ]
    }
   ],
   "source": [
    "Mais calculé avec la **méthode** des http://aiguillesdeBuffon.com , on obtiendrait comme **approximation** :"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "import numpy as np\n",
    " np.random.seed(seed=42)\n",
    " N = 10000\n",
    " x = np.random.uniform(size=N, low=0, high=1)\n",
    " theta = np.random.uniform(size=N, low=0, high=pi/2)\n",
    " 2/(sum((x+np.sin(theta))>1)/N)\n",
    "    "
   ]
  },
  {
   "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"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
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