{
 "cells": [
  {
   "cell_type": "code",
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   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "module 'book_format' has no attribute 'load_style'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-1-088e253ce17b>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      7\u001b[0m \u001b[1;31m# consistant with that look and feel.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      8\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mbook_format\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 9\u001b[1;33m \u001b[0mbook_format\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mload_style\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdirectory\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'..'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m: module 'book_format' has no attribute 'load_style'"
     ]
    }
   ],
   "source": [
    "from __future__ import division, print_function\n",
    "%matplotlib inline\n",
    "import sys\n",
    "sys.path.insert(0,'..') # allow us to format the book\n",
    "sys.path.insert(0,'../code') \n",
    "# use same formatting as rest of book so that the plots are\n",
    "# consistant with that look and feel.\n",
    "import book_format\n",
    "book_format.load_style(directory='..')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "ename": "ModuleNotFoundError",
     "evalue": "No module named 'gif_animate'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-2-5ca8afccfac5>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpyplot\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[1;32mfrom\u001b[0m \u001b[0mgif_animate\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0manimate\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      4\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mstats\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mgaussian\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpylab\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mpylab\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mModuleNotFoundError\u001b[0m: No module named 'gif_animate'"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from gif_animate import animate\n",
    "from stats import gaussian\n",
    "import matplotlib.pylab as pylab\n",
    "from matplotlib import animation\n",
    "import matplotlib\n",
    "\n",
    "def plt_g (mu, variance):\n",
    "    xs = np.arange(2,8,0.05)\n",
    "    ys = [gaussian (x, mu, variance) for x in xs]\n",
    "    plt.plot (xs, ys)\n",
    "    plt.ylim((0,1))\n",
    "\n",
    "\n",
    "mu = 2\n",
    "sigma = 0.6\n",
    "def ganimate(frame):\n",
    "    global mu, sigma\n",
    "    if frame < 25:\n",
    "        mu += .2\n",
    "    elif frame == 25:\n",
    "        mu = 5\n",
    "    elif frame < 37:\n",
    "        sigma -= 0.05\n",
    "    else:\n",
    "        sigma += 0.05\n",
    "\n",
    "    plt.cla()\n",
    "    plt_g(mu,sigma)\n",
    "\n",
    "animate('04_gaussian_animate.gif', ganimate, \n",
    "        frames=80, interval=50, figsize=(6,4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src='04_gaussian_animate.gif'>"
   ]
  }
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