MyfirtsTestJupiter

module2/exo1/montestutojupiter.ipynb

+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# mes tests codes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "a =  10\n",
+    "b = 2.5\n",
+    "print(a)\n",
+    "print(b)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "c= a+b\n",
+    "print(c)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "20\n"
+     ]
+    }
+   ],
+   "source": [
+    "x = 20\n",
+    "print(x)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Exemple de completion "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "mu, sigma= 100,15\n",
+    "nu,gamma = 200, 30"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "y = np.random.normal(loc=mu, scale=sigma, size = 10000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([  27.,  216.,  809., 1909., 2759., 2441., 1296.,  438.,   93.,\n",
+       "          12.]),\n",
+       " array([ 48.92891808,  59.68693403,  70.44494998,  81.20296593,\n",
+       "         91.96098187, 102.71899782, 113.47701377, 124.23502972,\n",
+       "        134.99304567, 145.75106161, 156.50907756]),\n",
+       " <a list of 10 Patch objects>)"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYEAAAD8CAYAAACRkhiPAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvIxREBQAAEHlJREFUeJzt3X+s3XV9x/Hna612+INY1sKwbXY7U5cVkqF0HZvZorJIlcXiHyYlm3QZSw3BRRf3o2gy3R9NqvNHQjJY6mCUzUEaxdEE2ERiZkwQvDCkLbWh2gqXdvQ6s8m2hFl874/zJR7Lub2/7+Hez/ORnJzveX8/3/P9vHPbvu73e77n21QVkqQ2/cywJyBJGh5DQJIaZghIUsMMAUlqmCEgSQ0zBCSpYYaAJDXMEJCkhhkCktSw5cOewGRWrVpVIyMjw56GJC0qjzzyyPeravVk4172ITAyMsLo6OiwpyFJi0qS701lnKeDJKlhhoAkNcwQkKSGGQKS1DBDQJIaZghIUsMMAUlqmCEgSQ0zBCSpYS/7bwxLkxnZec9Q9nt895VD2a80lzwSkKSGGQKS1DBDQJIaZghIUsMMAUlqmCEgSQ0zBCSpYYaAJDXMEJCkhhkCktQwQ0CSGmYISFLDDAFJapghIEkNmzQEkqxL8tUkh5McSvLBrv7xJM8keax7vKtvmxuSHE1yJMkVffVLkxzo1t2YJPPTliRpKqby/wmcBj5cVY8meS3wSJL7u3WfrapP9Q9OshHYBlwEvB74SpI3VtULwM3ADuAbwL3AFuC+uWlFkjRdkx4JVNXJqnq0W34OOAysOcsmW4E7q+r5qjoGHAU2J7kQOLeqHqyqAm4Hrpp1B5KkGZvWZwJJRoA3AQ91pQ8keTzJrUlWdrU1wNN9m411tTXd8pl1SdKQTDkEkrwG+CLwoar6Ib1TO28ALgFOAp9+ceiAzess9UH72pFkNMno+Pj4VKcoSZqmKYVAklfQC4DPV9VdAFX1bFW9UFU/Bj4HbO6GjwHr+jZfC5zo6msH1F+iqvZU1aaq2rR69erp9CNJmoapXB0U4BbgcFV9pq9+Yd+w9wAHu+X9wLYkK5KsBzYAD1fVSeC5JJd173kNcPcc9SFJmoGpXB30FuB9wIEkj3W1jwBXJ7mE3imd48D7AarqUJJ9wBP0riy6vrsyCOA64DbgHHpXBXllkCQN0aQhUFVfZ/D5/HvPss0uYNeA+ihw8XQmKEmaP1M5EpA0wMjOe4a27+O7rxzavrW0eNsISWqYISBJDTMEJKlhhoAkNcwQkKSGGQKS1DBDQJIaZghIUsMMAUlqmCEgSQ0zBCSpYYaAJDXMEJCkhhkCktQwQ0CSGmYISFLDDAFJapghIEkNMwQkqWGGgCQ1zBCQpIYZApLUMENAkhpmCEhSwwwBSWqYISBJDTMEJKlhhoAkNWzSEEiyLslXkxxOcijJB7v6eUnuT/Jk97yyb5sbkhxNciTJFX31S5Mc6NbdmCTz05YkaSqmciRwGvhwVf0ycBlwfZKNwE7ggaraADzQvaZbtw24CNgC3JRkWfdeNwM7gA3dY8sc9iJJmqZJQ6CqTlbVo93yc8BhYA2wFdjbDdsLXNUtbwXurKrnq+oYcBTYnORC4NyqerCqCri9bxtJ0hBM6zOBJCPAm4CHgAuq6iT0ggI4vxu2Bni6b7OxrramWz6zLkkakimHQJLXAF8EPlRVPzzb0AG1Okt90L52JBlNMjo+Pj7VKUqSpmlKIZDkFfQC4PNVdVdXfrY7xUP3fKqrjwHr+jZfC5zo6msH1F+iqvZU1aaq2rR69eqp9iJJmqapXB0U4BbgcFV9pm/VfmB7t7wduLuvvi3JiiTr6X0A/HB3yui5JJd173lN3zaSpCFYPoUxbwHeBxxI8lhX+wiwG9iX5FrgKeC9AFV1KMk+4Al6VxZdX1UvdNtdB9wGnAPc1z0kSUMyaQhU1dcZfD4f4PIJttkF7BpQHwUuns4EJUnzx28MS1LDDAFJathUPhOQJjWy855hT0HSDHgkIEkNMwQkqWGGgCQ1zBCQpIYZApLUMENAkhpmCEhSwwwBSWqYISBJDTMEJKlhhoAkNcwQkKSGGQKS1DBDQJIaZghIUsMMAUlqmCEgSQ0zBCSpYYaAJDXMEJCkhhkCktQwQ0CSGmYISFLDDAFJapghIEkNMwQkqWGThkCSW5OcSnKwr/bxJM8keax7vKtv3Q1JjiY5kuSKvvqlSQ50625MkrlvR5I0HVM5ErgN2DKg/tmquqR73AuQZCOwDbio2+amJMu68TcDO4AN3WPQe0qSFtCkIVBVXwN+MMX32wrcWVXPV9Ux4CiwOcmFwLlV9WBVFXA7cNVMJy1Jmhuz+UzgA0ke704Xrexqa4Cn+8aMdbU13fKZ9YGS7EgymmR0fHx8FlOUJJ3NTEPgZuANwCXASeDTXX3Qef46S32gqtpTVZuqatPq1atnOEVJ0mRmFAJV9WxVvVBVPwY+B2zuVo0B6/qGrgVOdPW1A+qSpCGaUQh05/hf9B7gxSuH9gPbkqxIsp7eB8APV9VJ4Lkkl3VXBV0D3D2LeUuS5sDyyQYkuQN4K7AqyRjwMeCtSS6hd0rnOPB+gKo6lGQf8ARwGri+ql7o3uo6elcanQPc1z0kSUM0aQhU1dUDyrecZfwuYNeA+ihw8bRmJ0maV35jWJIaZghIUsMMAUlqmCEgSQ0zBCSpYYaAJDXMEJCkhhkCktQwQ0CSGmYISFLDJr1thKSXn5Gd9wxlv8d3XzmU/Wr+eCQgSQ0zBCSpYYaAJDXMEJCkhhkCktQwQ0CSGmYISFLDDAFJapghIEkNMwQkqWGGgCQ1zBCQpIYZApLUMENAkhpmCEhSwwwBSWqYISBJDZs0BJLcmuRUkoN9tfOS3J/kye55Zd+6G5IcTXIkyRV99UuTHOjW3Zgkc9+OJGk6pnIkcBuw5YzaTuCBqtoAPNC9JslGYBtwUbfNTUmWddvcDOwANnSPM99TkrTAJg2Bqvoa8IMzyluBvd3yXuCqvvqdVfV8VR0DjgKbk1wInFtVD1ZVAbf3bSNJGpKZfiZwQVWdBOiez+/qa4Cn+8aNdbU13fKZdUnSEM31B8ODzvPXWeqD3yTZkWQ0yej4+PicTU6S9NNmGgLPdqd46J5PdfUxYF3fuLXAia6+dkB9oKraU1WbqmrT6tWrZzhFSdJkZhoC+4Ht3fJ24O6++rYkK5Ksp/cB8MPdKaPnklzWXRV0Td82kqQhWT7ZgCR3AG8FViUZAz4G7Ab2JbkWeAp4L0BVHUqyD3gCOA1cX1UvdG91Hb0rjc4B7usekqQhmjQEqurqCVZdPsH4XcCuAfVR4OJpzU6SNK/8xrAkNcwQkKSGGQKS1DBDQJIaZghIUsMMAUlqmCEgSQ0zBCSpYYaAJDVs0m8Ma3EZ2XnPsKcgaRHxSECSGmYISFLDDAFJapghIEkNMwQkqWGGgCQ1zBCQpIYZApLUMENAkhpmCEhSwwwBSWqYISBJDTMEJKlhhoAkNcwQkKSGGQKS1DBDQJIaZghIUsMMAUlq2KxCIMnxJAeSPJZktKudl+T+JE92zyv7xt+Q5GiSI0mumO3kJUmzMxdHAm+rqkuqalP3eifwQFVtAB7oXpNkI7ANuAjYAtyUZNkc7F+SNEPzcTpoK7C3W94LXNVXv7Oqnq+qY8BRYPM87F+SNEWzDYECvpzkkSQ7utoFVXUSoHs+v6uvAZ7u23asq71Ekh1JRpOMjo+Pz3KKkqSJLJ/l9m+pqhNJzgfuT/Lts4zNgFoNGlhVe4A9AJs2bRo4RpI0e7M6EqiqE93zKeBL9E7vPJvkQoDu+VQ3fAxY17f5WuDEbPYvSZqdGYdAklcnee2Ly8A7gIPAfmB7N2w7cHe3vB/YlmRFkvXABuDhme5fkjR7szkddAHwpSQvvs8/VtU/J/kmsC/JtcBTwHsBqupQkn3AE8Bp4PqqemFWs5ckzcqMQ6Cqvgv8yoD6fwCXT7DNLmDXTPcpabhGdt4zlP0e333lUPbbAr8xLEkNMwQkqWGGgCQ1zBCQpIYZApLUMENAkhpmCEhSwwwBSWqYISBJDTMEJKlhhoAkNcwQkKSGGQKS1DBDQJIaZghIUsMMAUlq2Gz/o3kNMKz/eEOSpssjAUlqmCEgSQ0zBCSpYYaAJDXMEJCkhhkCktQwQ0CSGmYISFLD/LKYpJe9YX4B8/juK4e274XgkYAkNcwQkKSGLXgIJNmS5EiSo0l2LvT+JUk/saAhkGQZ8NfAO4GNwNVJNi7kHCRJP7HQHwxvBo5W1XcBktwJbAWemI+deTdPSTq7hQ6BNcDTfa/HgF9b4DlI0pQN65fJhboqaaFDIANq9ZJByQ5gR/fyv5McmddZzY9VwPeHPYl5ttR7XOr9gT2+bOUTUx46UX+/MJWNFzoExoB1fa/XAifOHFRVe4A9CzWp+ZBktKo2DXse82mp97jU+wN7XApm299CXx30TWBDkvVJXglsA/Yv8BwkSZ0FPRKoqtNJPgD8C7AMuLWqDi3kHCRJP7Hgt42oqnuBexd6v0OwqE9nTdFS73Gp9wf2uBTMqr9UveRzWUlSI7xthCQ1zBCYI0lel+QLSb6d5HCSX09yXpL7kzzZPa8c9jxnKskfJzmU5GCSO5L87GLvL8mtSU4lOdhXm7CnJDd0tzs5kuSK4cx6eibo8a+6P6ePJ/lSktf1rVtUPQ7qr2/dnySpJKv6aouqP5i4xyR/1PVxKMkn++rT67GqfMzBA9gL/GG3/ErgdcAngZ1dbSfwiWHPc4a9rQGOAed0r/cBv7/Y+wN+C3gzcLCvNrAnerc5+RawAlgPfAdYNuweZtjjO4Dl3fInFnOPg/rr6uvoXYDyPWDVYu3vLD/DtwFfAVZ0r8+faY8eCcyBJOfS+0HdAlBV/1dV/0nvlhh7u2F7gauGM8M5sRw4J8ly4FX0vt+xqPurqq8BPzijPFFPW4E7q+r5qjoGHKV3G5SXtUE9VtWXq+p09/Ib9L6vA4uwxwl+hgCfBf6Mn/4y6qLrDybs8Tpgd1U934051dWn3aMhMDd+ERgH/i7JvyX52ySvBi6oqpMA3fP5w5zkTFXVM8CngKeAk8B/VdWXWSL9nWGingbd8mTNAs9tPvwBcF+3vCR6TPJu4Jmq+tYZq5ZEf503Ar+Z5KEk/5rkV7v6tHs0BObGcnqHazdX1ZuA/6F3KmFJ6M6Lb6V3ePl64NVJfm+4s1pwU7rlyWKS5KPAaeDzL5YGDFtUPSZ5FfBR4C8GrR5QW1T99VkOrAQuA/4U2JckzKBHQ2BujAFjVfVQ9/oL9ELh2SQXAnTPpybY/uXut4FjVTVeVT8C7gJ+g6XTX7+JeprSLU8WiyTbgd8Bfre6k8ksjR7fQO+XlW8lOU6vh0eT/DxLo78XjQF3Vc/DwI/p3UNo2j0aAnOgqv4deDrJL3Wly+ndHns/sL2rbQfuHsL05sJTwGVJXtX9tnE5cJil01+/iXraD2xLsiLJemAD8PAQ5jdrSbYAfw68u6r+t2/Vou+xqg5U1flVNVJVI/T+UXxz93d00ffX55+AtwMkeSO9i1G+z0x6HPYn30vlAVwCjAKPdz+glcDPAQ8AT3bP5w17nrPo7y+BbwMHgb+nd/XBou4PuIPeZxw/ovePxbVn64neaYbvAEeAdw57/rPo8Si988aPdY+/Waw9DurvjPXH6a4OWoz9neVn+ErgH7q/j48Cb59pj35jWJIa5ukgSWqYISBJDTMEJKlhhoAkNcwQkKSGGQKS1DBDQJIaZghIUsP+HxCL5FKB/6LYAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.hist(y)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "nu, gamma = 200, 30 \n",
+    "z = np.random.normal(loc=nu, scale =gamma, size = 15000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([   5.,   85.,  641., 2220., 4211., 4446., 2490.,  756.,  133.,\n",
+       "          13.]),\n",
+       " array([ 76.52685301, 100.86580289, 125.20475276, 149.54370263,\n",
+       "        173.8826525 , 198.22160238, 222.56055225, 246.89950212,\n",
+       "        271.23845199, 295.57740187, 319.91635174]),\n",
+       " <a list of 10 Patch objects>)"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.hist(z)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# calcul et affichage de cosinus et sinus "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7f9e2401deb8>]"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "xx = np.linspace(0,2*np.pi,30)\n",
+    "alpha = np.cos(xx)\n",
+    "beta =  np.sin(x)\n",
+    "plt.figure\n",
+    "plt.plot(alpha)\n",
+    "plt.figure\n",
+    "plt.plot(beta)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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1dz73ObNGx/Pk1+fpUQMqIIkIP1k2ldpmOw+/VURcRDArFo21OpZP0nL3AvmHa/nms7mMTYrizyvOICpMvy0qcNlswoNXz6C+1c59r+wiPjKUK+akWx3L5+ixdRbbV9XIij9/RkJ0KM/eOp/4yFCrIyllueAgG4/dMIcF4xL53gv5vLu70upIPkfL3UK1ze3c+pet2ET4261nkhIbbnUkpbxGeEgQf7w5h6lpMax6bhu7j9YP/CB1gpa7ReydXdz+t22U1bay5qZ5ZCZGWR1JKa8THRbMUzd1T1V+45lcqhvbrI7kM7TcLWCM4d71BXy8v4ZfXj2DeZl6IWulTic1Lpw/3pRDVUMbK/+aR1uHvovVGVruFnhmSwnPfXqIleeN56q5GVbHUcrrzRodz2++Movcg8f5yT936rngnaCHZXjY+0VV/OzVXVycncIPL51sdRylfMaXZo5ib0Ujv3t7LxNHRvOt88ZbHcmrabl7UHFlA6ue28aklBgeuW62nlZAqUG668KJFFc18svXdzM+OZqLslOsjuS1dFrGQ2qb27n1mVzCgm08dXOOHsuu1BDYbMJD18xiRnocd639XI+g6YeWuwcYY/je8/mU1bbwhxvnkTFCr3uq1FBFhAbxx5u6B0jf/ts2Gtv0om990XL3gKc+OMDbuyv5ybKpemSMUi6QEhvOYzfMoaSmif9ct0N3sPZBy93N8g4e58HXd7NkWio3L8yyOo5SfuPMcYl89+JJrM8vY+3WwwM/IMBoubtRbXM7dz63jbT4cB68ZqaevlQpF/v24gmcMzGJe9cXsKtM599703J3E2MM338hn6rGNlZ/dS5xESFWR1LK79hswsPXzSY+IoRVz+n8e29a7m7ypw8P8FZh9zz7zIx4q+Mo5beSosN41DH//pN/6vx7Dy13N9h26Di/3Kjz7Ep5ylmO+feXvyjjHzr/Dmi5u1xDq507n/tc59mV8rDe8+97KxqsjmM5LXcX+/mrhZTXtfC76+foPLtSHmSzCb/9ymyiwoL5/gv5dHR2WR3JUlruLvTunkr+kXuYb503nrljRlgdR6mAkxwTxv3Lp5NfWscfNu+3Oo6ltNxdpK7Zzj0vbWdSSjR360V9lbLMZTPTuGxmGo+8VRTQpyfQcneRn75aQHVjO7+5drZe3Fopi92/fDpxESF87/l87AE6PaPl7gKbdlWwbtsR7lg8nhkZcVbHUSrgJUSF8vMrZlBQVs/qd4utjmMJLfdhOt7Uzo/X7WBKagyrLtDpGKW8xZLpqVwxexSPv1PMziN1VsfxOC33Ybp3fQG1ze385iuzCA3WzamUN7nv8mkkRIXy/RfyA+7yfNpGw7BpVwXr88v4zoUTmTZKp2OU8jbxkaE8cNUMdh9tYPW7+6yO41Fa7kPU0t7JfesLmJQSze2L9XJfSnmrC6emcPmsUTz5/j5KqpusjuMxWu5DtPrdYo7UtnD/8umEBOlmVMqb/eSyqYQG2bjvlYKAOfeMttIQ7K9qZM3m/Vw5J50zxyVaHUcpNYCU2HDuvmgi7+2p4o2CCqvjeISW+yAZY7h3fQFhwTZ+vGyK1XGUUk5asTCLKakx/OyVAprb/f/UwE6Vu4gsEZE9IlIsIvecZpnFIvKFiBSIyPuujek9Nuw4ygd7q/neJZMYGRNudRyllJOCg2z8bPl0yupaeewd/z/2fcByF5EgYDWwFMgGbhCR7JOWiQeeAC43xkwDrnVDVss1tXVw/6u7yE6L5etnZVodRyk1SPPHJnDV3HSe+mA/xZWNVsdxK2dG7vOBYmPMfmNMO7AWWH7SMl8F1hljDgEYYypdG9M7PPr2Xo7Wt3L/FdMJ1p2oSvmkHy+dSnhIEPeu3+nXO1edaah0oPfZ70sdt/U2CRghIu+JSJ6I3NTXE4nIbSKSKyK5VVVVQ0tskeLKBv704QG+kpPBvEw946NSvio5JowfXDqZj4preG1HudVx3MaZcu/rahMn/7oLBuYBlwGXAv8lIpNOeZAxa4wxOcaYnOTk5EGHtdIvN+4hIiSIHy3RnahK+bqvnZnJlNQYfvX6Hto7/PPEYs6UeykwutfXGUBZH8u8boxpMsZUA5uBWa6JaL2tJcd4q7CClYvHkxgdZnUcpdQwBdmEe5ZO4dCxZp779KDVcdzCmXLfCkwUkbEiEgpcD6w/aZmXgXNEJFhEIoEzgULXRrWGMYYHNhQyMiaMWxZlWR1HKeUi501KZsG4RB59p5iGVrvVcVxuwHI3xnQAq4A36C7s540xBSKyUkRWOpYpBF4HtgOfAU8ZY3a6L7bnvLmrgm2Harn7oklEhgZbHUcp5SIi3aP3Y03t/NEPr9okVu0tzsnJMbm5uZas21kdnV1c+shmDPDm3efqETJK+aE7ntvGO4WVvP/DxT7x3hURyTPG5Ay0nLZVP17IK2VfVRM/vHSKFrtSfuoHl0zG3tnF797aa3UUl9LGOo2W9k4e3lTE3DHxXDotxeo4Sik3yUqK4qtnjmHt1sPsr/KfNzZpuZ/G0x8doLKhjR8vm4pIX0eDKqX8xZ0XTCQ82MZDb+6xOorLaLn3oa7FzpPv7+OiqSM5IyvB6jhKKTdLjgnjm+eOY8OOo+wo9Y9L8mm59+GvH5fQ0NrB3Red8j4spZSfuvXsscSGB/vNBbW13E/S1NbBnz48wAVTRjI9XS+dp1SgiAkPYcXCLF4vOEpRRYPVcYZNy/0kf//sEMeb7dxx/gSroyilPOyWRWOJDA3iCT8YvWu599Jq72TN5v0sGJeoJwdTKgCNiArl62dlsj6/jIM1vn29VS33Xl7IK6WyoY1VF+ioXalA9Y2zxxIcZOP37+2zOsqwaLk72Du7ePK9fcwZE8/C8XpdVKUC1cjYcK7LGc1L20opq22xOs6Qabk7vPxFGUdqW1h1/gQ9rl2pAPet88ZhDKzx4XPOaLkDnV2GJ94rZmpaLBdMGWl1HKWUxTJGRHLlnHTWbj1EVUOb1XGGRMsd2LSrgv1VTdxx/ngdtSulALh98XjaOrp4ZkuJ1VGGRMsd+MuWA6THR7BkWqrVUZRSXmJccjQXTknh758dotXeaXWcQQv4ct99tJ5P9h/j62dl6pkflVL/ZsXCLGqa2nltu+9dazXg2+yZLQcJC7Zx/RmjB15YKRVQFk1IZMLIaJ75uASrrn0xVAFd7nXNdv71+RGumJ3OiKhQq+MopbyMiHDzgky2l9bx+eFaq+MMSkCX+/O5h2mxd3LzwiyroyilvNRVczOICQv2uR2rAVvunV2GZz4uYX5WAtmjYq2Oo5TyUlFhwVybM5rXtpdTWd9qdRynBWy5v7O7ktLjLTpqV0oN6KYFmXQaw/98esjqKE4L2HJ/ZksJaXHhXKKX0FNKDSArKYrFk5J57rNDtHd0WR3HKQFZ7vuqGvmwuJqvn5VJiB7+qJRyws0Ls6hqaOP1gqNWR3FKQDbbi3mlBNmEa3MyrI6ilPIR505MJj0+ghdyD1sdxSkBV+6dXYZ120pZPCmZkTHhVsdRSvkIm024el4GHxZXU17n/WeLDLhy/7C4mor6Nq6ep6N2pdTgXD03HWNg3bYjVkcZUMCV+4t5pcRFhHDhVD37o1JqcDITo5iflcBLeaVe/47VgCr3uhY7bxYcZfnsUYQFB1kdRynlg66Zl8H+6iavf8dqQJX7a9vLaevo4hqdklFKDdGymWlEhATxYl6p1VH6FVDl/mLeYSalRDMjPc7qKEopHxUdFszS6am8kl/m1acCDphy31fVyLZDtVw9N0MvyKGUGpar52XQ0NrBm7sqrI5yWk6Vu4gsEZE9IlIsIvf0s9wZItIpIte4LqJrrNtWik3gyjnpVkdRSvm4BeMSGRUX7tVTMwOWu4gEAauBpUA2cIOIZJ9muQeBN1wdcriMMbz8RRlnT0xmZKwe266UGh6bTbhybjof7q2iptE7r7HqzMh9PlBsjNlvjGkH1gLL+1juTuAloNKF+VyioKye0uMtXDZDL6OnlHKNpdPT6DLd12D2Rs6UezrQ+/22pY7bThCRdOBK4EnXRXOdjTvLCbIJF2druSulXGPaqFhGJ0Swcad3nmvGmXLva+/jyUfvPwL8yBjT765jEblNRHJFJLeqqsrZjMNijGHjzqOcOTaBBL3aklLKRUSEpdPT2LKvmroWu9VxTuFMuZcCvS8wmgGUnbRMDrBWREqAa4AnROSKk5/IGLPGGJNjjMlJTk4eYuTB2VvZyP6qJpbOSPPI+pRSgWPp9FTsnYa3C71vasaZct8KTBSRsSISClwPrO+9gDFmrDEmyxiTBbwIfNsY8y+Xpx2CjTuOIgKX6nnblVIuNisjnrS4cK+cmhmw3I0xHcAquo+CKQSeN8YUiMhKEVnp7oDDtXFnOTmZI/QMkEopl7PZhEunpfJ+URWNbR1Wx/k3Th3nbozZYIyZZIwZb4z5f47bnjTGnLID1RizwhjzoquDDsWB6iZ2H21gyXSdklFKucfS6am0d3Tx7m7vOlDQr9+hunFnOQBLputRMkop98jJSiApOpTXvWxqxq/L/Y2dR5mVEUd6fITVUZRSfirIJlwyLZV391R61blm/LbcqxvbyC+t4+Js3ZGqlHKvi7NTaG7v5LMDx6yOcoLflvsHe7uPoz93kmcOuVRKBa6zxiYSGmzj/SLPvH/HGX5b7puLqkmICmX6KD29r1LKvSJCg5iflcBmLXf36uoyfLC3irMnJGGz6el9lVLud+6kJPZWNlJW6x0Xz/bLct9VXk91Y7tOySilPKanb3qmhK3ml+W+uWe+fWKSxUmUUoFickoMKbFhbC6qtjoK4K/lXlTFlNQYPXe7UspjRIRzJybzYXE1nV0nn1vR8/yu3JvaOsg7eJzzdEpGKeVh505Kpq7FTn5prdVR/K/cP95Xg73T6Hy7Usrjzp6QhAhecdSM35X7B3uriAgJIidrhNVRlFIBZkRUKDMz4rXc3eHTA8eYlzmCsOAgq6MopQLQgnGJ7DhSZ/mpCPyq3Otb7eypaNBRu1LKMmdkjcDeacg/bO28u1+V++eHajEGcjITrI6ilApQ8zK7B5e5B49bmsOvyj235Bg2gdlj4q2OopQKUPGRoUwYGU1uibUnEfOzcj9O9qhYosOCrY6ilApgZ2SNIO/gcbosPN7db8rd3tnF54eP65SMUspy8zITqG/tYG9lo2UZ/Kbcd5XV02rv0p2pSinLnZHVM+9u3dSM35R7z84LHbkrpaw2JiGSpOgw8kqs26nqP+VecoyMERGkxun5ZJRS1hIRzsgawVYduQ+PMYa8g8fJydQpGaWUd5iXOYLDx1qorG+1ZP1+Ue5VDW1UNrQxa7QeAqmU8g6zHX20s6zOkvX7RbkXlNUDME0vqaeU8hJT0mIRgYIj9Zas3y/KfVd598abkhZjcRKllOoWHRZMVmLUiX7yNP8o97J6xiREEhseYnUUpZQ6ITstVst9OHaV15OdFmt1DKWU+jfZo2I5WNNMQ6vd4+v2+XJvbOugpKaJ7FFa7kop79Iz6Nx9tMHj6/b5ct9ztB5j0JG7Usrr9Aw6d5V5fmrG58v9xJEy6VruSinvMjImjMSoUAosOBzS58t9V1k9IyJDSI3Vd6YqpbyLiJA9ypqdqk6Vu4gsEZE9IlIsIvf0cf/XRGS742OLiMxyfdS+7SqvJ3tULCLiqVUqpZTTstNiKTraiL2zy6PrHbDcRSQIWA0sBbKBG0Qk+6TFDgDnGWNmAvcDa1wdtC/GGPZWNDIpRY9vV0p5p8mpMbR3dnGwptmj63Vm5D4fKDbG7DfGtANrgeW9FzDGbDHG9Jz+7BMgw7Ux+1ZR30aLvZNxSVGeWJ1SSg1alqOfSqqbPLpeZ8o9HTjc6+tSx22ncyuwsa87ROQ2EckVkdyqqirnU57GAcfGytJyV0p5qbGJjnKv8b5y72syu89rR4nI+XSX+4/6ut8Ys8YYk2OMyUlOTnY+5Wn0bKysRC13pZR3GhEVSnxkyInBqKc4c7HRUmB0r68zgLKTFxKRmcBTwFJjTI1r4vXvQHUToUE2RsVHeGJ1Sik1JFmJUR4vd2dG7luBiSIyVkRCgeuB9b0XEJExwDrgRmNMketj9u1AdRNjEiMJsumRMkop7zXJ2QvBAAAJcUlEQVQ2Kcr75tyNMR3AKuANoBB43hhTICIrRWSlY7H/BhKBJ0TkCxHJdVviXkqqmxir8+1KKS+XlRhFWV0rrfZOj63TmWkZjDEbgA0n3fZkr8+/AXzDtdH619VlOHismfOnjPTkapVSatCykiIBOFjTzORUzxy67bPvUC2ra6G9o0t3piqlvN64pGgAj867+2y5/+9hkJEWJ1FKqf719JSWuxMOHet+t5eO3JVS3i4mPITEqFAOHdNyH1BFXSs26T7rmlJKebvUuHAq6ts8tj6fLfej9a0kRYcRHOSz/wWlVABJjQ3naF2rx9bns81YUd9Gip7mVynlI0bGhlPZoOU+oIr6Vi13pZTPSIkNo7qxnfYOz5z618fLXefblVK+oeeCQlWNnpl398lyb+vo5HizXUfuSimf0dNXFfWemZrxyXKvdOxx1kvrKaV8xUjHTEOFh3aq+mS59/zmG6nTMkopH5GqI/eB9RwrmhqnI3ellG8YERlKSJBQ0aBz7qd11PGbLyVGy10p5RtsNmFkTLhOy/Sntrkdm0BcRIjVUZRSymkJUaEcb273yLp8stzrW+zEhIdg04t0KKV8SGxEMPWtHR5Zl2+We2sHMeFOnYpeKaW8RkxYCPUtdo+syyfLvaHVTmy4TskopXxLbEQwDTpyP736lg5iI3TkrpTyLbHhIdS36sj9tOp15K6U8kGxESE0t3di73T/+WV8s9xb7MTqkTJKKR8T69hX6ImpGd8sd92hqpTyQTGOGQdP7FT1uXLv7DI0tnXotIxSyuf0zDjoyL0PjY6NotMySilf0zMt44mdqj5X7g1t3RslOizI4iRKKTU40Trnfnr2TgNAaLDPRVdKBbhQxzWf9WiZPnQ4NkqwzeeiK6UCXLCj3Du6tNxP0TNyDwnS88oopXxLsON8WD095k4+WO46cldK+aYQnZY5vZ4/Z0J0zl0p5WN6Zhw6dOR+qhPTMnq6X6WUjwn2tpG7iCwRkT0iUiwi9/Rxv4jIo477t4vIXNdH7dbzG69nIymllK84MXLv8oKRu4gEAauBpUA2cIOIZJ+02FJgouPjNuD3Ls55gt0xLROsO1SVUj6mZ19hh5eM3OcDxcaY/caYdmAtsPykZZYDz5punwDxIpLm4qwA2Du6N0qojtyVUj6mZ+Te7iVz7unA4V5flzpuG+wyLtHz54yO3JVSvkZECLaJ14zc+2rRk3/tOLMMInKbiOSKSG5VVZUz+U6REhvGshmpenFspZRPumxmGpNSYty+HmfOm1sKjO71dQZQNoRlMMasAdYA5OTkDOnvknmZCczLTBjKQ5VSynK/u36OR9bjzMh9KzBRRMaKSChwPbD+pGXWAzc5jpo5C6gzxpS7OKtSSiknDThyN8Z0iMgq4A0gCHjaGFMgIisd9z8JbACWAcVAM3CL+yIrpZQaiFOXMzLGbKC7wHvf9mSvzw1wh2ujKaWUGio9nlAppfyQlrtSSvkhLXellPJDWu5KKeWHtNyVUsoPSfeBLhasWKQKODjEhycB1S6M4yremgu8N5vmGhzNNTj+mCvTGJM80EKWlftwiEiuMSbH6hwn89Zc4L3ZNNfgaK7BCeRcOi2jlFJ+SMtdKaX8kK+W+xqrA5yGt+YC782muQZHcw1OwObyyTl3pZRS/fPVkbtSSql+eG25i8i1IlIgIl0ictq9yqe7eLeIJIjIJhHZ6/h3hItyDfi8IjJZRL7o9VEvInc77rtPRI70um+Zp3I5lisRkR2OdecO9vHuyCUio0XkXREpdHzP7+p1n0u313Au9j7QY92c62uOPNtFZIuIzOp1X5/fUw/lWiwidb2+P//t7GPdnOsHvTLtFJFOEUlw3OfO7fW0iFSKyM7T3O+515cxxis/gKnAZOA9IOc0ywQB+4BxQCiQD2Q77vsVcI/j83uAB12Ua1DP68h4lO5jUwHuA77vhu3lVC6gBEga7v/LlbmANGCu4/MYoKjX99Fl26u/10uvZZYBG+m+uthZwKfOPtbNuRYCIxyfL+3J1d/31EO5FgOvDuWx7sx10vJfBt5x9/ZyPPe5wFxg52nu99jry2tH7saYQmPMngEW6+/i3cuBZxyfPwNc4aJog33eC4F9xpihvmHLWcP9/1q2vYwx5caYbY7PG4BC3HMN3uFc7N2Zx7otlzFmizHmuOPLT+i+2pm7Def/bOn2OskNwN9dtO5+GWM2A8f6WcRjry+vLXcn9Xdh7hTjuBqU49+RLlrnYJ/3ek59Ya1y/En2tKumPwaRywBvikieiNw2hMe7KxcAIpIFzAE+7XWzq7bXcC727s6LwA/2uW+le/TX43TfU0/lWiAi+SKyUUSmDfKx7syFiEQCS4CXet3sru3lDI+9vpy6WIe7iMhbQGofd/3EGPOyM0/Rx23DPvynv1yDfJ5Q4HLgx71u/j1wP9057wd+A/yHB3MtMsaUichIYJOI7HaMNobMhdsrmu4fwruNMfWOm4e8vfpaRR+3OXuxd7e81gZY56kLipxPd7mf3etml39PB5FrG91Tjo2O/SH/AiY6+Vh35urxZeAjY0zv0bS7tpczPPb6srTcjTEXDfMp+rswd4WIpBljyh1/9lS6IpeIDOZ5lwLbjDEVvZ77xOci8kfgVU/mMsaUOf6tFJF/0v3n4GYs3l4iEkJ3sf+PMWZdr+ce8vbqw3Au9h7qxGPdmQsRmQk8BSw1xtT03N7P99TtuXr9EsYYs0FEnhCRJGce685cvZzyl7Mbt5czPPb68vVpmf4u3r0euNnx+c2AM38JOGMwz3vKXJ+j4HpcCfS5V90duUQkSkRiej4HLum1fsu2l4gI8Ceg0Bjz25Puc+X2Gs7F3p15rNtyicgYYB1wozGmqNft/X1PPZEr1fH9Q0Tm090pNc481p25HHnigPPo9Zpz8/ZyhudeX+7YY+yKD7p/kEuBNqACeMNx+yhgQ6/lltF9dMU+uqdzem5PBN4G9jr+TXBRrj6ft49ckXS/yONOevxfgR3Adsc3L81TuejeE5/v+Cjwlu1F9xSDcWyTLxwfy9yxvfp6vQArgZWOzwVY7bh/B72O1Drda81F22mgXE8Bx3ttn9yBvqceyrXKsd58unf0LvSG7eX4egWw9qTHuXt7/R0oB+x099etVr2+9B2qSinlh3x9WkYppVQftNyVUsoPabkrpZQf0nJXSik/pOWulFJ+SMtdKaX8kJa7Ukr5IS13pZTyQ/8fTvAebIw3goIAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from pylab import *\n",
+    "yy = linspace(0,pi,60)\n",
+    "delta1 = cos(yy)\n",
+    "delta2 = sin(yy)\n",
+    "figure\n",
+    "plot(delta1, delta2)\n",
+    "show()\n",
+    "figure\n",
+    "plot(delta1)\n",
+    "show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from pylab import *\n",
+    "x = array([0,1,1,0,0])\n",
+    "y = array([0,0,1,1,0])\n",
+    "t = array([0,0,2,2,0])\n",
+    "z = array([0,2,2,0,0])\n",
+    "figure\n",
+    "plot(x,y)\n",
+    "axis(\"off\")\n",
+    "show()\n",
+    "figure\n",
+    "plot(t,z)\n",
+    "axis(\"off\")\n",
+    "show()"
+   ]
+  },
+  {
+   "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": 4
+}