{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import arviz as az\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%config InlineBackend.figure_format = 'retina'\n",
    "az.style.use('arviz-darkgrid')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Code 9.1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "d = {'A':[0, 0, 10, 0, 0], \n",
    "     'B':[0, 1, 8, 1, 0], \n",
    "     'C':[0, 2, 6, 2, 0], \n",
    "     'D':[1, 2, 4, 2, 1], \n",
    "     'E':[2, 2, 2, 2, 2]}\n",
    "p = pd.DataFrame(data=d)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Code 9.2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "p_norm = p/p.sum(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Code 9.3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "A   -0.000000\n",
       "B    0.639032\n",
       "C    0.950271\n",
       "D    1.470808\n",
       "E    1.609438\n",
       "dtype: float64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def entropy(x):\n",
    "    y = []\n",
    "    for i in x:\n",
    "        if i == 0:\n",
    "            y.append(0)\n",
    "        else: \n",
    "            y.append(i*np.log(i))\n",
    "    h = -sum(y)\n",
    "    return h\n",
    "H = p_norm.apply(entropy, axis=0)\n",
    "H"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Code 9.4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 431,
       "width": 644
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ways = [1, 90, 1260, 37800, 113400]\n",
    "logwayspp = np.log(ways)/10\n",
    "plt.plot(logwayspp, H, 'o')\n",
    "plt.plot([0.0, max(logwayspp)], [0.0, max(H)], '--k')\n",
    "plt.ylabel('entropy', fontsize=14)\n",
    "plt.xlabel('log(ways) per pebble');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Code 9.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1.0, 0.9999999999999999, 1.0, 1.0]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Build list of the candidate distributions.\n",
    "p = [[1/4, 1/4, 1/4, 1/4],\n",
    "     [2/6, 1/6, 1/6, 2/6],\n",
    "     [1/6, 2/6, 2/6, 1/6],\n",
    "     [1/8, 4/8, 2/8, 1/8]]\n",
    "\n",
    "# Compute expected value of each. The sum of the multiplied entries is just a dot product.\n",
    "p_ev = [np.dot(i, [0, 1, 1, 2]) for i in p]\n",
    "p_ev"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Code 9.6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1.3862943611198906,\n",
       " 1.3296613488547582,\n",
       " 1.3296613488547582,\n",
       " 1.2130075659799042]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Compute entropy of each distribution\n",
    "p_ent = [entropy(i) for i in p]\n",
    "p_ent"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Code 9.7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0.09000000000000002,\n",
       " 0.21000000000000002,\n",
       " 0.21000000000000002,\n",
       " 0.48999999999999994]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p = 0.7\n",
    "A = [(1-p)**2, p*(1-p), (1-p)*p, p**2]\n",
    "A"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Code 9.8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.221728604109787"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "-np.sum(A*np.log(A))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Code 9.9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def sim_p(G=1.4):\n",
    "    x123 = np.random.uniform(size=3)\n",
    "    x4 = (G * np.sum(x123) - x123[1] - x123[2]) / (2 - G)\n",
    "    x1234 = np.concatenate((x123, [x4]))\n",
    "    z = np.sum(x1234)\n",
    "    p = x1234 / z\n",
    "    return - np.sum(p * np.log(p)), p"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Code 9.10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "H = []\n",
    "p = np.zeros((10**5, 4))\n",
    "for rep in range(10**5):\n",
    "    h, p_ = sim_p()\n",
    "    H.append(h)\n",
    "    p[rep] = p_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 720x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 431,
       "width": 620
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "az.plot_kde(H)\n",
    "plt.xlabel('Entropy')\n",
    "plt.ylabel('Density');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Code 9.12"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.2217270587669808"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.max(H)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Code 9.13"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.09035691, 0.20978912, 0.20949706, 0.49035691])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p[np.argmax(H)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This notebook was created using:\n",
      "Python 3.7.3\n",
      "IPython 7.5.0\n",
      "ArviZ 0.4.1\n",
      "NumPy 1.16.4\n",
      "Matplotlib 3.1.0\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import platform\n",
    "import sys\n",
    "\n",
    "import IPython\n",
    "import matplotlib\n",
    "import scipy\n",
    "\n",
    "print(\"\"\"This notebook was created using:\\nPython {}\\nIPython {}\\nArviZ {}\\nNumPy {}\\nMatplotlib {}\\n\"\"\".format(sys.version[:5], IPython.__version__, az.__version__, np.__version__, matplotlib.__version__))"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "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": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}