From 9ec3a4c0651ac9f69212c2d25835e6956610359d Mon Sep 17 00:00:00 2001
From: b4be7b445b878ad4e31ba006a9f5a959
 <b4be7b445b878ad4e31ba006a9f5a959@app-learninglab.inria.fr>
Date: Mon, 23 Mar 2020 02:16:53 +0000
Subject: [PATCH] DONE somepart of ittttttttttttttt!!!

---
 module2/exo1/toy_notebook_fr.ipynb | 50 +++++++++++++++++++++++-------
 1 file changed, 38 insertions(+), 12 deletions(-)

diff --git a/module2/exo1/toy_notebook_fr.ipynb b/module2/exo1/toy_notebook_fr.ipynb
index b34edd3..56e4aee 100644
--- a/module2/exo1/toy_notebook_fr.ipynb
+++ b/module2/exo1/toy_notebook_fr.ipynb
@@ -14,40 +14,66 @@
     "<h4 style=\"text-align: center;\"> March 28, 2019 </h4>"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 1. A propos du calcul de $\\pi$\n",
+    "\n",
+    "### 1.1. En demandant à la lib maths \n",
+    "Mon ordinateur m'indique que $\\pi$ vaut *approximativement*\n"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "1\n"
+      "3.141592653589793\n"
      ]
     }
    ],
    "source": [
-    "x=1\n",
-    "print(x)"
+    "from math import *\n",
+    "print(pi)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 1.2. En utilisant la méthode des aiguilles de Buffon \n",
+    "\n",
+    "Mais calculé avec la **méthode** des [aiguilles de Buffon](http://fr.wikipedia.org/wiki/Aiguille_de_Buffon), on obtiendrait comme **approximation** :\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[1] 1\n"
-     ]
+     "data": {
+      "text/plain": [
+       "3.128911138923655"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
-    "x=1\n",
-    "print(x)"
+    "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"
    ]
   },
   {
-- 
2.18.1