{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# A propos du calcul de $ \\pi $" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## En demandant à la lib maths" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Mon ordinateur m’indique que $\\pi$ vaut *approximativement*" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "3.141592653589793\n" ] } ], "source": [ "from math import *\n", "print(pi)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## En utilisant la méthode des aiguilles de Buffon" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Mais calculé avec la **méthode** des [aiguilles de Buffon](https://fr.wikipedia.org/wiki/Aiguille_de_Buffon), on obtiendrait comme **approximation** :" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "3.128911138923655" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "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": "markdown", "metadata": {}, "source": [ "## Avec un argument \"fréquentiel\" de surface" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Sinon, une méthode plus simple à comprendre et ne faisant pas intervenir d’appel à la fonction\n", "sinus se base sur le fait que si $X ∼ U(0, 1)$ et $Y ∼ U(0, 1)$ alors $P[X^2 + Y^2 ≤ 1] = \\pi/4$ (voir\n", "[méthode de Monte Carlo sur Wikipedia](https://fr.wikipedia.org/wiki/M%C3%A9thode_de_Monte-Carlo)). Le code suivant illustre ce fait :" ] }, { "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": "3.6.4" } }, "nbformat": 4, "nbformat_minor": 2 }