heritability.ipynb

{
 "worksheets": [
  {
   "cells": [
    {
     "metadata": {},
     "cell_type": "code",
     "input": "import numpy as np\nimport scipy as sp\nimport pandas as pd\nimport statsmodels as sm\nimport seaborn as sn\nimport matplotlib.pyplot as plt",
     "prompt_number": 95,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "ls -lrt",
     "prompt_number": 119,
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "total 3920\r\n-rw-r--r--@ 1 chris  staff   21768 Jan 27 16:05 main.fls\r\n-rw-r--r--@ 1 chris  staff   53156 Jan 27 16:05 main.dvi\r\n-rw-r--r--@ 1 chris  staff   20698 Jan 27 16:06 main.fdb_latexmk\r\n-rw-r--r--@ 1 chris  staff     491 Jan 27 16:09 main.toc\r\n-rw-r--r--@ 1 chris  staff     397 Jan 27 16:09 main.snm\r\n-rw-r--r--@ 1 chris  staff   43804 Jan 27 16:09 main.pdf\r\n-rw-r--r--@ 1 chris  staff     448 Jan 27 16:09 main.out\r\n-rw-r--r--@ 1 chris  staff    1956 Jan 27 16:09 main.nav\r\n-rw-r--r--@ 1 chris  staff   39036 Jan 27 16:09 main.log\r\n-rw-r--r--@ 1 chris  staff    4939 Jan 27 16:09 main.aux\r\n-rw-rw-r--@ 1 chris  staff     181 Jan 27 16:32 session2.tex\r\n-rw-rw-r--@ 1 chris  staff     166 Jan 27 16:33 session3.tex\r\n-rw-r--r--@ 1 chris  staff    6012 Jan 27 16:35 beamercolorthemesolarized.sty\r\n-rw-r--r--@ 1 chris  staff     266 Jan 27 16:40 session1.fls\r\n-rw-r--r--@ 1 chris  staff     266 Jan 27 16:40 session2.fls\r\n-rw-r--r--@ 1 chris  staff     972 Jan 27 16:40 session3.log\r\n-rw-r--r--@ 1 chris  staff     266 Jan 27 16:40 session3.fls\r\n-rw-r--r--@ 1 chris  staff     584 Jan 27 16:40 session3.fdb_latexmk\r\n-rw-r--r--@ 1 chris  staff     964 Jan 27 16:40 session2.log\r\n-rw-r--r--@ 1 chris  staff     584 Jan 27 16:40 session2.fdb_latexmk\r\n-rw-r--r--@ 1 chris  staff   33736 Jan 27 16:40 slides.dvi\r\n-rw-r--r--@ 1 chris  staff  181123 Jan 27 20:31 slides.key\r\n-rw-r--r--@ 1 chris  staff    7377 Feb  1 11:13 session1.log\r\n-rw-r--r--@ 1 chris  staff     845 Feb  1 11:13 session1.fdb_latexmk\r\n-rw-r--r--@ 1 chris  staff  437566 Feb  1 11:47 sork.pdf\r\n-rw-rw-r--@ 1 chris  staff     105 Feb  1 12:46 references.tex\r\n-rw-r--r--@ 1 chris  staff     662 Feb  1 23:09 *.aux\r\n-rw-r--r--@ 1 chris  staff      80 Feb  4 02:35 makefile\r\n-rw-r--r--@ 1 chris  staff      21 Feb  4 02:37 missfont.log\r\n-rw-rw-r--@ 1 chris  staff     133 Feb  4 03:10 README.md\r\n-rw-rw-r--@ 1 chris  staff     140 Feb  4 09:34 scratch.tex\r\n-rw-rw-r--@ 1 chris  staff    2662 Feb  6 11:32 refs.bib\r\n-rw-r--r--@ 1 chris  staff  131423 Feb  6 12:02 salvo_fig1.pdf\r\n-rw-r--r--@ 1 chris  staff    1072 Feb  6 12:09 slides.blg\r\n-rw-r--r--@ 1 chris  staff    1132 Feb  6 12:09 slides.bbl\r\n-rw-rw-r--@ 1 chris  staff    4829 Feb  6 12:14 session1.tex\r\n-rw-rw-r--@ 1 chris  staff    1230 Feb  6 12:21 slides.tex\r\n-rw-r--r--@ 1 chris  staff     493 Feb  6 12:21 slides.toc\r\n-rw-r--r--@ 1 chris  staff   31972 Feb  6 12:21 slides.synctex.gz\r\n-rw-r--r--@ 1 chris  staff     160 Feb  6 12:21 slides.snm\r\n-rw-r--r--@ 1 chris  staff  626400 Feb  6 12:21 slides.pdf\r\n-rw-r--r--@ 1 chris  staff     571 Feb  6 12:21 slides.out\r\n-rw-r--r--@ 1 chris  staff    3037 Feb  6 12:21 slides.nav\r\n-rw-r--r--@ 1 chris  staff   57099 Feb  6 12:21 slides.log\r\n-rw-r--r--@ 1 chris  staff   28126 Feb  6 12:21 slides.fls\r\n-rw-r--r--@ 1 chris  staff    1896 Feb  6 12:21 slides.aux\r\n-rw-r--r--@ 1 chris  staff    1317 Feb  6 12:21 session3.aux\r\n-rw-r--r--@ 1 chris  staff    1345 Feb  6 12:21 session2.aux\r\n-rw-r--r--@ 1 chris  staff    3425 Feb  6 12:21 session1.aux\r\n-rw-r--r--@ 1 chris  staff     956 Feb  6 12:21 scratch.aux\r\n-rw-r--r--@ 1 chris  staff    1323 Feb  6 12:21 references.aux\r\n-rw-r--r--@ 1 chris  staff   49014 Feb  6 12:25 slides.fdb_latexmk\r\n-rw-------@ 1 chris  staff   52925 Feb  6 13:07 heritability.ipynb\r\n"
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "%matplotlib inline",
     "prompt_number": 96,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "loc = 50\nscale = 2",
     "prompt_number": 97,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "parent_heights = sp.random.normal(loc=loc, scale=scale, size=500)",
     "prompt_number": 98,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "plt.hist(parent_heights)\nplt.show()",
     "prompt_number": 99,
     "outputs": [
      {
       "output_type": "display_data",
       "metadata": {},
       "png": 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vPerYqwUi4jvAWO3pfwMfAnYDk8AhYHOn9j+j9/+hOm4/BpyhC8buzG2fmW+pLe+KsTvL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\nRU5ErkJggg==\n",
       "text": "<matplotlib.figure.Figure at 0x11ce00610>"
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "h2 = 0.8",
     "prompt_number": 107,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "offspring_heights = []\nfor p in parent_heights:\n    r = sp.random.random()\n    if r < h2:\n        if sp.random.random() > 0.5:\n            offspring_heights.append(p + p*sp.random.uniform(0, 0.1))\n        else:\n            offspring_heights.append(p - p*sp.random.uniform(0, 0.1))\n    else:\n        offspring_heights.append(sp.random.normal(scale=scale, loc=loc))",
     "prompt_number": 108,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "plt.hist(offspring_heights)\nplt.show()",
     "prompt_number": 109,
     "outputs": [
      {
       "output_type": "display_data",
       "metadata": {},
       "png": 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LjaSuazQmnu6ZdtXrtY6f20vtvMG0U+Yn91i5HtiSUhoE9gDb2ngNSVIPlCrziHgYuKR1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\nc0nKgGUuSRn4f3AYXQjVBICGAAAAAElFTkSuQmCC\n",
       "text": "<matplotlib.figure.Figure at 0x11ce0b7d0>"
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "reg = sp.stats.linregress(parent_heights, \n                          offspring_heights)\nprint reg\nslope, intercept, r_value, p_value, std_err = reg",
     "prompt_number": 110,
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "(0.84671228358383677, 7.714965372193241, 0.5042741991270504, 1.3106705905507895e-33, 0.064973865557779134)\n"
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "plt.scatter(parent_heights, offspring_heights)\nplt.xlabel(\"Parent height (cm)\")\nplt.ylabel(\"Offpring height (cm)\")\nplt.title(\"y=%.5fx + %.5f ($r^2$ = %.2f, $p$ = %.5f)\" % (slope, \n                                                         intercept, \n                                                         r_value**2,\n                                                         p_value))\nplt.plot(parent_heights,parent_heights*slope+intercept, 'r-')\nplt.show()",
     "prompt_number": 111,
     "outputs": [
      {
       "output_type": "display_data",
       "metadata": {},
       "png": 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r+SsqthoVRrcSqFmUjDIJrccc7GE8Xu+9JCcn4/F4GDr0S1Ti2iZD\nnjfZtes2IinQtIGppA1MxbPqpRA5Ls+7lyQO4SOVQB/oEiCbyso7HAdou9I+TF1dX4qKJrhWiKHn\nOQxspLZ2IOXlr0Q8ZvXqJior76CoaEJM1wrG5/M5ft463yExuFEGJ0kp95gvpJT/B3xLSvl54sTS\ndFVi+SG6jUs/9dRQm3h6+rdsx5rhpOFmqAG5egE/IzNzHwUFFzvKtXjxu20eoEzOOmsjasCfhJkD\nYDafqa6+HVWh9GeGPM7lICCgBJzYv6+R/fsaGT58sMPWkbhfnVkL9bVlNWfWYhoDZLN48Z6wzy9e\nK8dIKxKd75AY3CiDPwshXhBCZAshcoQQLwBvCiGygS8SLJ+mixHrDzFa9rHP52PYsNPweOZiKpjU\n1Hk89NC1tmOdZvjWQSacXPn5o0hPn4/dbHOn7dhwM9Dc3BGkppYA56MKzAUU4IoVv2b06HrUT+iQ\nUaE1ySLjV8CDqJLRs+3Hj3yW22df4agEDp/4rVYlYFJQcJEtSU71U4gczGdX2m3vEaCeXzFQQMAp\nfgOzZj0dYYXWfqIplWjfK03suClhPd34uw61VtyE8hmMQX1DNEcY1rBOcyCFtsX1B5zRPgYMuI1z\nzz2OsrKb8Pt7t0su63tTp55CUdE61Nd9EtDIH/+4mdra97n33nyuu+5PjpEpVVXbjYbtW4EBQDU5\nOX/liSdm4PF4WL9+Eo8/Hlyh1YdK2jdjQBcDrwB/J4u7WU8JbAuVveHldfgzzw17X8uXT7A0kbma\nyZNfjFgd1BqV5PH04oUXAi1MY6kmqp7f2RQVme/4gOVUVt5BZWVoJE9HVy7VIabxI1LV0hOllHuF\nEKcQiCQyabGajhKMjiaKI/GUs71JRuGiQm6/fYJj28u2RqrYj22gd+8nOHxYZTp7PPfj8/0KlU4T\nkMEscBeQT2XrDhhQQ23tXPr37x/yLEMjmlT2bwvTwsq2/9PPISl60IeZpb1jx0cMHz6YiRPPdd1e\nsqrqz7zyyrvA1wwbNpjk5KNa+w1HOs4cZHNzR1gyvkOT2IIjeRoaGpgzpxTAscpqOKzP083n3d7v\nnxNulEs3+q3Hre3lEtSnvhXnvIL0WC6k6Xl0ZJJRe5r5WFtIPvXUGj755NlWmX2+IpQ5x5z6+oyG\nMmoQXLhwPl7vDZglKurrs8nKms+WLVMIhI8GrmOdRbfwjbAyWc1A0Qh0S+sLqBl5Tc0Sli+fELUE\nhwrbvRb1Uy7jT3/6iKam2wBP2Ph8pzh+lWhXY/RuDl+x1eczK8reAeBYZdUNbj7veH//jvT8hbA+\nAylltvHvICllevBfx4mo6anEGhXSXjvx6tVNfPLJxJD3Bwz4pyFDI6mpj1FZeQezZ+cwefI6Jk8+\nEXgcqwPW6705rFO0oOAiWuij+go7kMQdjMx4IiZbu+qW1mCTYdu2KVEds4FoqEAUVFPTj1Dzu/DO\nXSd7fVXVdgoLx7BgwfSIn1k8Q4872i8Q77Dp7oabTmfHoeLYTgeuNP5/q5TyMzcXEEK8A5iRR/8E\nfg+UorJ4/grM6MQieJp2kJs7gvvvD3ThSk2dR27u5ChH2Zfi5owTEtO608QeIhnIdPZ4ipk+PZN+\n/VayY8dHtrpEtbWFjBu3ivT0JrzeKBf44gvSTvu246aXGUcuK4EFwDTq6vpRXr6KadPc9URYvHgP\nKqK782nLCs1tV7lY0Z3V4oubaKJFwA6UB60J+D9UcHVUhBAeUI1yjL9rgfnAnVLKUShfxGWRzqHp\nugQcrJuATTQ23hhSqz+Y4JDByZPXkZ8/KubZn+m4XrRoNYsWrYkY2eLzBUw/1ub2/foV4PP9iuLi\nyaxe3eQYwpmcnMyGDTNsEUnW2XC/Rx9S4aEOiqB+x3t8vGcfZXkjUGGoMzHLcbsNb1XJdLeg+hkE\nEupGjlzquIqyRkaNHXsmKSkPEIikmscxx7yFio4KvxKLtmKLNGMPLRe+iJqaz2NK+nNLvENMj/T8\nBTfRROlSyj8IIaZLKX3Ab4QQ/+vy/GcB/YQQG4xrFQHDpJTm2msdKiqpKlbBNZHpuCgLs2kMqB+R\nnYaGBm67bQm7d+8jLy+D5OS+7bbzBmy7P0dlA6vViJONN7DvTQT6D5vN7Z/AzAGorc1n3Lg1ZGaG\nzjQ9Hg9btkxxrBd0tIN8Vn+AB1iwYDrvvrsUr3cs9vDWTTHcd0CJ5eS82xrRZEX1g3ihtW7SwoV3\n0dRUhNnhDW7ktttepl+/Ta334eQvqKjYyrhxKYwbt8ooYRG7fybQuW6Are1nbW0hs2aVkJl5Rsj3\nsi2RafHsrNYev1RPwI0y8AshjjVfCCEGo9babvgSeFBKucQ4bn3Q9i+AY0MP07SHjnKERVumNzQ0\ncM45pcaABDt3lnDqqfXAhHZd117p1LSjOysWu3noeOBBcnKaGTbsu8yd+zKmIlGK4uiwg4E56ESq\nHBrOKewc3upmUR78jHuRmbnPURH4fD6ysp601WbyekcSrKz79evXWqspuBpsvKJzrAO0Obhbqaw8\nk8rKS23fS+UkX8GWLQXGPp3jvD2i23a2tLRE/BsyZMglQ4YM+cuQIUPqhwwZ8vKQIUP2DRkyZFy0\n44xj+wwZMsRjeb19yJAhfsvry4YMGfJ4lPNoYmThwtUtcKgFWoy/5paFC1cn5FoHDx5sWbhwdcvC\nhatbDh48aNuWn//7EDngnpbBg+cZ/29uGT16Schx0QjcX/T7VPs2tsASY99DLYMHz2t5+OHlIcc+\n9lhl+IsGdgz9c/mcRo9eEtN9m8/2scdWtTz2WKXjM7bfZ1XQPX0e8qw/++wzQw71LM4//+nWcz/2\n2Kq4f2+C7xsWtcDBkPN35Hf2CCLqGG39i7oykFKuF0K8DYwAegPXSSk/dalrfgGcCcwQQnwbFYu3\nUQgxWkq5BRiLypWPSDeJ6e0ycjY1hdpkm5p87N/flBA5J0wYZVzDT1NTINu1udkp8zWZwsKTLfX0\nx4ccF03G7OwRhjknn4DpR61MsrPzbMdmZ48gPb3YNmP+8MNZvPFGSch5fb7DtmN7ef/JgIyzHWX4\nYm4xx9xzp9rf5fMsLx9vWXWE3rddFudZerhj1Gc+BqtzPD19IWvWTGLz5k00NfnIzx/PokWbjdm3\nyoN4/fXevP56trH/fFRuRLLtvOE+C7emSPO+VVjqTVhbeJrnj/Sd7Wp0pd96JNLSUqLvZMFNCevj\ngHzUGru1r4GU8t5oJxdCHAU8C5xqvDUbVf5xEaoh7PvAtCjRRDrpLEYiJezEImd7/Q4BM9Ec4515\n/PjHx7By5f+ELU1RXv4K7723m6FDB1FQcFHUpCi//xCQFLE886JFa2x2a9U9bCWrVzc5PqNjr8yl\nz2uvOl53/6690K8fEP4zN++jrk4CkJEhonY4C37WTm0zo5WrDrTtfJX09G1s2DAjJDnOnki3BqVA\nYu+C1haTUqTvpc/no6Cghi1bro567c6mK/3WI5GItpdbgU9Rhdxbd5ZS/jbsQfFFK4M2EG4gdytn\nvOzHpgPZ6/03p5ySxk9+8kPHQd6eWKXs+CNHqsQqoF1KKdwgFHxeN01krDg9y8B9JGP2RYYyMjKa\nWbHiStcD67hxqSEKLFrNfjefuf1ZhGYTh2vxGUxbewpEmmCkpCTz+ONrol67s+lqv/VwJEIZvCel\nHNouqdqHVgYxEG023xkNRNwoFnW9owjug1xcvIrVqxuNyKFXSU+vbZ3xRrqe257JQNiqoQBJRoRU\nevp8NmyYhMfjMVYkfjyeXrzxhmT48NNbZ/6LFq2mqOifqEVwaD9np+fn3Pc4/MolVoIHWaB1VVVT\n87mtZpHbaySiwUxX+Q1FoxvJGbdyFCZ/FUIMl1LuaKNMmg6iq6bTt6dswI4dHxphoSuAArzeS1vL\nQbiZZVufge16LS2kneAcyHaIZPpSidWE4vXezJgxRZx44neNrF5Q/oqbqKxcRnX1csrLc+KWIJac\n3CcuYY7honTMZ1FQENou0w064avnETa+TQjhFUJ4gQuAOiHEx+Z7Qoh/dpyIGrfEM52+oxNw8vNH\nkZHxL6ylnkeMWMzhw37gMWAibspBRHsGfV7ZoJLEHBRBw8oaHpz3En350vHcu3b1DynvoEo7XENd\nXRoTJ/4er/d7QAYqUd9M9nqO4cN3t2biBiddqXt/BpVuU0VGxqLW1YvZca2iYmubSkZXVGy1OIxD\nm/u4KfngVOJb9xToeURaGVzQYVJouhzxTMBxM4v0eDysWHGl4UCez/e+dxLr1rVQXX2XsUcZKkrG\nbCQTW43+SKagB0tWQFIS+T/OIP/HGLLmo5Llbzb2eh5wajIDKgLHy86dC4zXjwLXo2zyHwCnsH//\nXoqKfgk4r9iSknpj5gMkJS0JnDkBq73Fi9+N6Jy33VmE6x/RMfk9kKg+gy6A9hm4xE3Z3/bI2Z7o\noliaqq9Zs52NG9+x1Qky7e7Kp/AcxcVHM23aOMfjrc+ghb5hZfp4zz5HXwaoGfWBA19QVvY3vN6f\nABdy6qmPsXv3QKDQOMNzqHJdvwfuDZL1QeBWlPKqIlLZ50j2d6cy2nl577FgwXTX5aezsyv48MNZ\nxtYFwGTmzXvdlTNahYPaP4dENZ/vCr8hN3QjOePuM9B0ExKZTt/eGaqbWaT9Gl857PEBalC6kuTk\nTQ7bA8/gO6eEVwJmpnBF6cYQX4ZZQM6UdcqUS42BdRMHDpzC3Ll5qPIOfiCVs866g5NPPo41a4Kv\n8kPUauJK0tO34fVehMqYBlUbKFbM1pMFVFZmhy0N7fQ5XXvtidxxxz2oVpnTgWX4/U6FNJzOoYeI\nIwV3OfGabkOiyv621x8RrrVk+GtkYfUfpKbOA36J6m9c4ey/+OIL0gamOoaINl86no/37OPBeS9R\nWrqRhoYGS/G6AMEF5Kx2+3XrmlC1kH4GXMr5539OTc1v+clPfmCTVSmBLOAa8vIWUF19LampC1AO\n6TGkpj5Gbu6I1mtE8s8Etq3H2noylvLT77yzB7VyuQyV93kNof2qwp3D/jkcacXbjiTclLCejMov\nML89XwMHgQ+klH9NoGyaHkLbVhUe4Ery8lRRs9zcyVRVORdY+8bTT3DM3Xc6nqV+x3t8fcqpIS02\n779/AY2NNxHsFwhXQK6iYit1ddbOr34mTjwej8dDcnIfYJxxru+jag95UIPnGaxb9780Ns7BXIE0\nNs6mqipgaom2ohs3LoUDBzayc2f0ktdO9OoV2kLUzCWIjv1zONKKtx1JuFkD5gA/Qhk+k1DGz/8D\njhZCvCilnJ9A+TRdhGhO4Eg+AbehpaHXqLDZxoP3j+QUDi4aZ5dho2VwHoIqnhtaQM56TyrTGQKF\n3w61mqqU3C9SW/tLVEe0XgRm0XmuVlBOZjS7AhtHamqgd0S4UE6nz2nhwuns3u0+DDTa56DpmbhR\nBt9ClZ1uABBC3AOsBn4CvI2aDml6OJFmr8Ez/5UrnyEnZ0BriYhYr7FmjVlLx3kW6lYJ2AfzcNFH\nY1FmnUB9o/z8vJB7GjlyCRkZz1BXN611v8LCa2hq8luezSb8/qPx+5exc+cuhg8/3XhWoQN0bu5Y\nW7lmCM2yDjb5NDbeGHWG7vQ59e/fPyZf0pFeyvlIxU0G8t+BM6SUXxmvk4G/SCl/KIR4V0rpXMkr\nfuhoojiSCDlDI16exywpkZmp+ucGGqpHz3QNJ2MsK4HgwTwj4xk+/bSRXbtuNWR8HLjd2LbIprw8\nHk+YrOBVQEtrU/pbbskNKRrnpETGjzdzGlQNpUCD+YBsSUm9W5PZzKimcPWJzLwDa12m3NwRrY2F\nQjKsj+DvZiLoRnLGPZpoJfCqEGIZqmrpBKBSCHEN8O/YRdT0bDYT6DHgo7Z2IHPmlFJWVhi2vWWw\nicnaaD7p0085fqhzfP9/nl5Cy+WhPY0h1DRVVzeNnJz72bXLNAnNANZGDdO002KUiFBN6TduLKe8\nfLyDSeznqCJwH7Bt22ls25YE5NoG+UCPhc1Gf+NA+QrTjBZuRRHa2Mf0gaiCgB2Red5xzZM0HUXU\naCIp5a9RQdNDgEHAA1LKu4C/o4ysmiMIp6ggezSMOVM2QyGzqay8w9beEmg9R0NDg60NptkW8RuP\nzSdtYKqjIuiLjySauW7DJ46RSYE2l2sNORQZGWeQmfkpKhqoH5mZ+1oVQfB9OUX4QJLNbLNly9Uh\n/gA1W38R5Ve4FWgEPgQOB0UAmc9nDOHKVzhl+VZVbTdk2EpA6W61+EAS38g9uHWp21aWbiLKNJ2H\n2yBiL2qFkAQghBhlaV2pOUKIFBVk2phV8bMlbNt2IoFQSPts13qOhQvvsvUaeLP2evjG9Y7XV0Xj\nAiaTysoz2bu30jYLDsh4h7FfGXAlmZkVFBTkUVBAiC083H0F283dDbBJqGqlppzXoJTSZpQSUspz\n4UJrjwUzfNPut4Cu2XmrLbWmumrdLE2AqCsDIcSTqG/zvcBc46+jyldr4kx7ZmeRcg3MQWvatHEs\nXz6BnJx3Q473+/0h51CtGaGFJFrCxL7v39fIx3v22WbqZiy/VYaGhgbGj7/Hdn4z1j+4hII1D8Nu\nttlIbe1Ali5dh8fjsTl3c3NH2GQYPfr5EAd5+JBNf2uMvmqDaXW1BcI3o9X5CaxYzicQ/38+qamB\nWkhdMRcgnnWzNInBzcpgDCCklAcTLYwmsXRUn1mPx0NGhqC6OjDbVaUbgrNeW2jBOcTx4M+v5osF\nT9nOuWxZHrNmlVBZeSbWWH4wG+kspqnppJBzZWae4eIefZiVUQEeeGAuEybs5brr/mSbzZaVjW31\nfcycOSnEgZyfP4qnnnrIcFSb972XnJxDPPHEzFY5CgouYvVq5/DNSI3hPR4PZWVjmTNnAYcPH2bY\nsAr69TvayMPomOgfXbG0Z+JGGfwTnancI7BXsIytlDTENggEErHMshGqhER+/ije+ePveHHnXMfj\n/v3K63zrovP4Iky0xvDhg3n33Vq83gtQDeKVDL/61eM0NZ0CXEU4k4sTPp8Pv/8Q/frdxoEDT2A+\nG5/vHq6++iaj+FzgeZnJYmrA3myEwAYGbI/Hw7RpgygqqkH5CgRwJeedtylkUHcK34xmTvH5fEYk\nkjKD7d//LMuWje1Qc1JbQk9jVSDaQd3xuFEGnwHvCyHeJOCNa5FSTkmcWJquiN034AdSqKjY6vhj\nDSRiFQLqxz/9/+0g5ZQreNHh3Ps//RySkjgKHGfG9kFyAgMG3MfMmaczZYoaiHbv/g9wF2rgvhpY\ny0knvcSyZY+EHUgaGhrIynoSrzcTCN/lLJhoA3ZBwcWsXl1Jbe0trffuNPA5DeBO9vhZs8zcglHt\n6vnujwMAACAASURBVA0RT2JVPrEoEO1f6BzczPjXA/cAG4Atlj9NNyM/fxSjR5fTHtuyaUdfvbqR\noqIrHKNJzFnduHGpFBevpIW+vFl7PSnPLgo53/59jSpHICmp9dhLLnkhJFKlvHyzzeZcX/8bysoC\ntYXy8jKtUgKXMm1aVsQBJyvrBcOJeylwMnA/1lpIzz9/c0hEUW7uCGbNepra2hNQPgZl//7Vr55M\nUK1/H5WVvZg9+ygmTlzumDwXaznvzsJt3SztX+gcwq4MhBAnSin3An/CXpsILL2QNd0Hj8fD+vWT\nePzx8LMzN8vzSLNT66yuhT6Ocnx93HHUf7DLcZuTKau8fCWLF+9EpbgE8HpHMmvW02RmnsGECSNZ\nurSEPXtUuYbhw59hypSrwj6LioqteL23EIj6+QWwkrPOuonTTvsWJSWFIZm7ubljbSYaKMcsYVFd\n3cy///1HcnNPbE1ea8tsPTd3BE8++Wt27/4mkA78A1DXq6srY+zYZkaOXNLaqhKeo7q6mYICX9jc\njZkz21bTSHNkEclMtAQVLL2F0MG/BTgtUUJpEkek5b3b5bmKpV+L+vpchHWBufz5zSo8lNDw0MbH\nn6b5qthTU3bs+Aivtwg1+F5tvLsAuJ7KyiQqKy/kvvseoqnpRFSdIejVK/b5Snr6Tmpqfhti27fm\nRliVoGmOgv8CN/PWW8/y1ltKYTnZ+qMpWZ/PR0FBNbt3fw+VQ7AWpQgCYao7d5YwfvzpbNtmJs9d\nTV1dL5upKPhzXLMmNDmuK6Md1J1DWGUgpTSnE7+SUq7uIHk0nYgbe7TP56Om5nPgCuOdMjIymrlm\ncDppA1O5NeSssODe55g0PTfq9ZUz18/pp/+Gjz46B+hDRsYnDB8+mMpKD2oWbvYSOBVVFO5qYDNN\nTcNQ5h4l+/bthxxltzZ9sQ446emPsGHDjDYMmB8AN6GsqYGVRrjVEoRXsqoy6smW+wj9eQ4fPtgI\nXw3cqxlRZT2P9XNUyXEd71doK7o2UufgxoE8D1WYTqOhomKrpQ8wlLKFyXXP4xQhmkSzqkNUeEnU\n8wY7iFVE0FUkJf2RiRPPtYRh/oz09EcYOvRLqqtvx2yDGdv5Q8NE8/OnxBwRk5o6j8bGG1ErozrM\ntpXBuHX6qhXXB8arLNSqKxAZNXLkUgoKAiuPjpo5d0ZkT1dMtuvpuFEG/xBCLEV9263RRM8lTixN\nZ5CfP4pVqwL26JEjl5KfP8Fx33AJYqDaSVZUbGUeNa5ndcEDphoAN7Ft2xSqqmqCZopKvv37zWil\n80lJeZimpv1YB87c3OzWqCS/3x8yIFt7CrgheMY6bdqveOqptezY8SFnnfU91q8PPLtYB+jAimu2\n8Y7KnB4x4iCXXlrBzp27GT58sKMcwc84N3cE998fKHd97LEPkpt7DVZiaUPqNrLHPKdyaLeQnNxH\nh4V2I9wog3rU1Gdk0PtaGfRAWloOY9rd1f/t3D77CqPWp52/ZGZx8ssrADVXj/eszoxiqqjY2hrO\nanfuTmXFijfYsaOE4cMHM3Fitq0yaHr6XQQ7oN3Q0NDAnDmlAK1OZfPe+vdPYdq0bKapqtZMmeJz\nHKDd2MDtKy4fcDxDh85myZJbjcQ3VRxv8eL5bNgwySYHhJbrbmychZnj8fnnM6mq2hTWp7Bqlaqs\n6jR4u13VBJ9TKbNxVFa+qMNCuwlRlYGUstAoW30mqjHte1LKrxMumabDCXTzMit9Krv7LyaM5Pjv\nnux4zDn8mXcYzry8mtY28W0heFViNps3VyfhZqjWQWnatHGtA3PA2asqg3q9wxg0KJAZ7Gbm3tDQ\nwPDhZTQ2qmiezZtL2LFjMv3793fcP5xpI7h2E6SGzc+w9jp+771scnLm4/X+EvMz8XpvJivrbrZs\nuTVsP4mA4jPNVpF9Ctu2TTEc0pe2OaY/3Mqus/IgNLHjpjbRz4DdwDNAKcpsNCLiQZoewTm8ze2z\nr3BUBOePfIokmnmH4XGphePxeIy6/+tQUTQDgFcZP/5Yx0Yv7mLPrZVB82hpOUxx8SrXsf9z5pQa\nM+yNqO5oN7auEtpyfyo/o4miogmtORQNDQ2Ulm7E7z/EyJFLCO517PXeDLxqO5fXO5Ly8ldaa0wt\nXbrWyHvYCBzG672T9PT5RKqhFMpROD3XSP2ZNT0LN2aiR4FLpZTvAgghhgNPA8MTKZim4zHNGRfX\nfsK93Ou4j9lE5gWfs0mkPagSFvYomeTkmjadK7QyKOzePZvk5PCz1GA7+uHDfgI9AwDKjPfCH2tt\nOOPG5JKVdbcho2pyk5PzLtXVdkf0gAGbqa8fa7x6HhjH4sXPGnkSPjyeh4DfGNtLgWMZOvQgU6eu\nJDm5T0gNpWCzlVqFXY0TbiN7nM95pQ4L7Ua4UQY+UxEASCl3CCFi6qCj6R58e8RZvLk3tF/RwWuv\n44vfP2R7LxHRHpFs67HGnpuVQYuK3F3byQx18cWDqK4OJMDBNQwbtizCsdaGM+7KKKhSGIEGPMXF\nK9m/336fzzwzk5ycu40Kr1eQnv47i5LbiM/3G4uMk4F1VFcXGXWL1PWtyiC4rEhV1Re89dZ6ADIy\nPiE//8qQZxntsw4tVXK0UYtK+wu6C26UwZtCiIWo1cBh4H+Af5qmIinl9gTKp0k0LS2knXCs46aG\nlTX4zx/dYaJE6oHcltjz0Mqg4RWI06z9xBNLQvbr16+f7bXP5zPKU5yJvctbIHtarXhCcxsGDXqY\nXbt+FXSFJMf73LLlVmPVsgm/P5qSs5p8arj99lDHuTnAqyimlZj+haSkJZFOHBEdDtq9caMMhqIy\njh8Net/8pVwQV4k0HUJSU2NYp/B//r6blv7f7GCJFB6Ph+nTsx17zCayOJodH7Cew4f9ttIPpjIx\nTUIeTy9eeOFTtm0zy1Pcgz3XwMfixXsMc05obsOBA99m7txlBJf5Dr7P0LagWJSc6mVghpFGMvk4\nEZw3sm3bFO3wPUKJVJuoXEpZAJRLKds+XdB0Lf7yF9KGDXPcZFYO7QnEmigVMEPlozKbJ1NdnU1G\nxjMUF68yfABqVREwJ60FAgOpKh0xH7gZIMicE5rboHIgxhBc5jv4PqJ1YTN7Gfj9fqqrm6mr60XA\n2avt9Rp3JLW0ONdwEULsRpVx/A2qNrCNDkw6a3GaJXY10tJSHGezXQXPs4tJmXNLyPv+YefQsP5P\nnSBReNr7LIMHULMRfTSFYJp8Kiut9YAOMW+efQCfPTvH2L4GNZgH9s3JuZ+MjDNITk7G7/dTVDQh\n7LkCoatqVp+aOi8kdNV+PXWOuXOX8ctfOpf3cFKCkZ5n4FkVGs+qtNPyArr6b8ikG8kZ08wukplo\nOjAROAZnU5BOOusGHJt/OX1efSXk/c+fq+DQJZeqwSNMV62uQFtKIbitsRR8Xo/HQ2bmGVRWupXO\nXi4iM7PU1s3M5/NF9FlUVW23JIcdorHxe8yZU9ra8Swcv/99LZMm/dQx36HjTGmankYkZXC7lPJC\nIcRdUsr7OkwiTfs5fJi0b4Wx+e/axf5+xwHuSg20tS5NPOrZJKrJSaTzRotasm/vRUZGMzk5ATOS\nm25mdjwopaISzSorL2PvXrs8JSX3UV9vho4+T3PzA8yZs4A//OGmdj0Hq5zaR6CJZCbyor6hU4CF\nqH4GZl+DFimlcyB6/NFmoghYB92fjx/Gyd93riy+/1//gT59bHI6mSCsZoz2mFvacpyJKWM0+aJf\nv9C4finPPHMBd99dweHDfg4f/po1a36MKgbncbzvSIrM3J6S4iE7e0SblVNAzoEox7PzfU6d+iDV\n1edgLRmel1fiWhl0I7OGljOOxNNMNAHVxBaUAkiy/F/TBTAHk3/X/pS3Gclxsz+zbff/aBgNG15r\n8/nb2mIxXq0ZnTp41daq7maRVhvBM/KxYy/g3HOX0dh4E/YkskeBaUC/kOMjyWpub++gYMqp/BTh\nG9A89NA0XnvN7lsoKSls83U1Gici9TN4B3hHCPGWlHJdB8qkccmfi5/izdq5Ie9//sflHPpZ9LLR\nXbGJiM/n4+mnt/Lf/zby8sv/wWqTT0kpobLyJiorPVFNRtYB/frrHzXqC23EmgcAs4B7yMg4OSTR\nypQl0aWbPR4PCxZMZ+/e8J9D//792bFjMnPmqGhus2CeRhNPIuYZCCFGA7cKISqMt7YD90kpdUPS\nTsSz5BlSfn0b+Zb3PmUgP+bPzJy3k8KfuZuBR7Npt1VZtPU4u3lpLSqG4TBmQ5umpu8BKUA8G8Fn\nMHZsk6MpKN7+inDKxY1voX///nHzEWg0TkTyGVyI6jN4P/A60AfIBIqA/5FSdlQ8ovYZAHz1Fcfc\nfhPf+KM9iKu2/w+4qOENDtLPVVhgrHJ2pAM5WtimKmJ3WetrN/4DsIZw3ojKITCTvJ7HLO9grQIa\nKovz9WJ5lu31o7SHbmTj1nLGkXj6DOYC2da6RCiz0TaUsfX82MXTxErSZ//l2CsuI/m9nbb3D8y6\nlS/vvJuTm5v5bcVmIDFhgW2NNGl/hEpol6+WlsPU1alyzBkZi/D7B1BaujFE2Tgpolmzvs3DD0/j\nwIHvAjOBsajWncvweu+komJTwiJqGhoamDjx9+zceRLwJdBfl3bWdDkiKYPUIEUAgJTybSHEcQmU\nSQP0lh9w3PmhlcIbn3mW5txArZmeFBYYOWxT3bPZE6CmpreR0GU34QTPwFeufIakpN5GyYUCVFXP\nvqg4iD8Bzq054uVPCaxKFhjvzANmEOy01mg6m0jK4GghxFFSyq+sbwohjgJ6J1asI5c+G9ZxbMFV\nIe9/tvl1vhp6VsRjO6NXbTwJLVR3Zcg9FBaOobR0o62ejioIp5RGbe371NYGMojr6k7CHrapqnpa\nzU3p6XeTn3+royztTcZSPRGsGc23Aw+SmZnW6c56jcZKJGWwEVWMrvVXYiiCR1EGXU28aGmh36MP\ncfTv7bl9X50+mIaX19OSlhb1FIlK0OpoIhWqi8Tixe8adYDc1F60M3Xq2Y7PKXrBuJSYrwVw1lmf\nsGzZdd3us9H0bCJ1OpsDDBNC/EMIUSGEWAn8AzgN5UTWtJfmZlKnFJB2wrE2ReC7/Ar2/+s/fPbm\n264UAQTH9rvtBNY9Ce6+lZ7+CF5vEeres1C+BrVtxIiPjQ5i6vWgQQ9z6qnvYe3cVVBwEaAGe7N7\nmM/ns13TVLazZ+e0dikL3seJkpJCUlNLWq+XmjqPFSt+rRWBpssRKc/gCyOiaDTwY5Rx9REp5Rsd\nJVxPpdene+mfPYbee3bZ3v/invs5OOPGzhGqGxFswvH7T6GoyBxcPcCVqOqh3+Oyy46noOBii7ln\nKkCI+Sfaysopka60dBMTJoyKaJ7TOQKa7kLENbWUsgV4zfjTtJOj/vI238wKrfn3+Ysvceii9jmB\nu2ICWVswk86UzyBylrG1fIS1IBy8BNz0/9u79/Co6juP429wA1MtYGXx9rjbpg/mV12vSOGJl6KC\nsjXeFeGhhIuCN/qI1VaoWKu7Zb0VrFoXrJeCuGsEJRQQBWQRyi6E4rbqevlqa3T71KIsdzCBCLN/\n/M6EmcnJMBNmMifJ5/U8eTJzZubMNzM553vO7/x+3x/QmZKShaEX2dPvt3TUdDbNcxojIG1BpmYi\nyZOuc6vodWT3lEQQ79qVzf/1Bhs/337QiQD2Hy0/+ODCrCd8b22ZmmESjw8dWs1NN12YU1NM4m+f\nMmUepaV347uMds7r5O1hE8OPHj2wQzXPSfuW+9W2HDnnjgTewHccPwxYBHwQPDzdzOYUOoai2LeP\nw+79CYdOfyxlccMZ32Zb1UvEe+S/qSDK3UyzOYI+mJpGsViMceMqqKwcSFWVnyDmQD2A6uvrmT37\nNdav/yOnnvr1lFnN+vV7itWrN7BmzbuNTTsq9SztWUGTgXOuBHgCP9KmE3AGMNXMphXyfYtq5056\njBxGl9WpR4d1o6/zk8ofEv1euYXootrSHf2aNe/mFEO2CbG+vp4hQ+ZQU9MVmER1NfTrN4MpU+bR\n0NDA1KmfsW6dn9Np+fIHGiedSV93e2meEyn0mcFD+PLXPw7u9wGcc+4y4EPgVjPbWeAYWkdtLT1P\n70PnbVtTFu/4+SPUjxzT6uEcTBmJ1uqimr6jT9+xwrNUV9/Khg3P520eg8Rn0tCwh5qa44CLSCSo\ndetu4OqrF7J+/Yfs2HFX4/Lt2+9g4sTwktGaHEbai4JdM3DOjQY2mtnSpMXrgB+a2QDgI/wM4m1a\nyepV9DqyO3zzmymJYMuCJWz8fHvREkFLukFC4bqopre5J3b0ybEldqzDhk3DDwwbAXRjzZphTJgw\no9lrDdmor6/nmmteavxMfvWr2iCOg5c4Gxk9+kIlAmm74vF4QX7KyspWlpWVvV5WVrairKxsS1lZ\n2dqysrKjkh4/says7LUs1hVNv/xlPA6pP0cdFY9/8kmxI4tPn74oDnuSQtsdnz59UcFfeyB1dXXx\nYcPui8P8ONQ1u/7UGOri8GRwf098wICn43V1dTm/96OPVjf5u+CmYN2747A73rv3/fEtW7bEp06d\nE4/Fbo7Dtjjsjvfo8bP4li1b8vIZiLSinPbZBWsmCo7+AXDOrcDXI57vnLvFzH6Hv6C8Ppt1RaZC\nYDOVQ3cPvICuC+azcddev6DI8e7Y0fToeceOejZu3EGvXt348583Mnv2ctav/5C+fXtTWTmo8Yi2\noqIf5eWpbeAVFVfk7Tvo0+d4qqr2N80kx5ZoxonFOiddzH2V5DkIVq4cwWOP5V7gbcWKt/FlKZIN\nxA+fGQ+cz4gRR3PRRXOCM6PL6dnznznrLD+5TEPDIU0+gzZUvVJx5lFbijMXrdm1NI5PCA8HyaEc\nXx478jpt2czhA8+h17FHpCSCXbf+kI2fbWP78y/BodEpPBbWDTLRxTLRXDJ58lVUV09i8uRdDBky\np0lTTaG6qDYXW3LT1i23XEw8vpcpU+ZxxRVv5+V9+/btTfLIZHgWnxyGAI9TWvomJSVdU5rINm26\ni7PPPlWDxKRDKHjXUgAzSx5pdXZrvGc+HPL+exzxnf5Nlm9/cia7L7uyCBFlJ9NFzZkzl6cUeYOR\n1NQspqpqVePRdqG7qF58cXeOPvqB4KzExzZz5tKU3kY1NeO46qqFB5wFLFuVlYNYsGAONTWLgXeA\n64HlwaPnMHbsaZSUlDS/ApF2rlWSQVvTXPnozctXs/fkU4oQUe6iNubA9+lfHhSUmwzE2LDh11RW\nZn5dIrHNnj2vsVkr03s014MqFosxd+41VFWt4osvjmPq1Bn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       "text": "<matplotlib.figure.Figure at 0x11cdcb350>"
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "S = 0.6",
     "prompt_number": 112,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "markdown",
     "source": "$V_A = h^2S$"
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "V_A = slope*S\nV_A",
     "prompt_number": 113,
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 113,
       "metadata": {},
       "text": "0.50802737015030208"
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    }
   ],
   "metadata": {}
  }
 ],
 "metadata": {
  "name": "",
  "signature": "sha256:b8c444c132e1da090265380c3348714373edf4df144d9e9315c4f87534363b62",
  "gist_id": "d08dd9e61bd736b6e0d5"
 }
}