fix

parent e2bbc063
......@@ -27,16 +27,13 @@
"hidePrompt": true
},
"source": [
"My computer tells me that $\\pi$ is approximatively"
"My computer tells me that $\\pi$ is *approximatively*"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"hideCode": true,
"hidePrompt": true
},
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
......@@ -58,34 +55,21 @@
"hidePrompt": true
},
"source": [
"## Buffon's needle"
"## Buffon's needle\n",
"Applying the method of [Buffon's needle](https://en.wikipedia.org/wiki/Buffon%27s_needle_problem), we get the __approximation__"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"hideCode": true,
"hidePrompt": true
},
"outputs": [
{
"data": {
"text/plain": [
"3.128911138923655"
]
},
"execution_count": 6,
"execution_count": null,
"metadata": {},
"output_type": "execute_result"
}
],
"outputs": [],
"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",
"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)"
]
},
......@@ -96,17 +80,8 @@
"hidePrompt": true
},
"source": [
"## Using a surface fraction argument"
]
},
{
"cell_type": "markdown",
"metadata": {
"hideCode": true,
"hidePrompt": true
},
"source": [
"A method that is easier to understand and does not make the use of the sin function is based on the fact that if $X ~ U(0,1)$ and $Y ~ U(0,1)$, then $P[{x}^{2}+{y}^{2} = \\pi/4]$ (see [\"Monte Carlo method\" on wikipedia](https://en.wikipedia.org/wiki/Monte_Carlo_method). The following code uses this approach:"
"## Using a surface fraction argument\n",
"A method that is easier to understand and does not make use of the $\\sin$ function is based on the fact that if $X\\sim U(0,1)$ and $Y\\sim U(0,1)$, then $P[X^2+Y^2\\leq 1] = \\pi/4$ (see [\"Monte Carlo method\" on Wikipedia](https://en.wikipedia.org/wiki/Monte_Carlo_method)). The following code uses this approach:"
]
},
{
......@@ -131,16 +106,18 @@
}
],
"source": [
"%matplotlib inline\n",
"%matplotlib inline \n",
"import matplotlib.pyplot as plt\n",
"\n",
"np.random.seed(seed =42)\n",
"np.random.seed(seed=42)\n",
"N = 1000\n",
"x=np.random.uniform(size=N, low=0, high=1)\n",
"y=np.random.uniform(size=N, low=0, high=1)\n",
"accept=(x*x+y*y)<=1\n",
"reject=np.logical_not(accept)\n",
"fig, ax=plt.subplots(1)\n",
"x = np.random.uniform(size=N, low=0, high=1)\n",
"y = np.random.uniform(size=N, low=0, high=1)\n",
"\n",
"accept = (x*x+y*y) <= 1\n",
"reject = np.logical_not(accept)\n",
"\n",
"fig, ax = plt.subplots(1)\n",
"ax.scatter(x[accept], y[accept], c='b', alpha=0.2, edgecolor=None)\n",
"ax.scatter(x[reject], y[reject], c='r', alpha=0.2, edgecolor=None)\n",
"ax.set_aspect('equal')"
......
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