rbm_imonad.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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      "X 500 Y 2055\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch: 1 err: 0.032999 ksteps: 50\n",
      "[0.8728007 0.5209726 1.       ]\n",
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      "[0.9063804  0.83182514 1.        ]\n",
      "[0.9063804  0.83182514 1.        ]\n",
      "[0.06294502 0.48037153 1.        ]\n",
      "[0.06294502 0.48037153 1.        ]\n",
      "[0.76934135 0.40921712 1.        ]\n",
      "[0.76934135 0.40921712 1.        ]\n",
      "[0.93662584 0.5503505  1.        ]\n",
      "[0.93662584 0.5503505  1.        ]\n",
      "[0.43320626 0.6767758  1.        ]\n",
      "[0.43320626 0.6767758  1.        ]\n",
      "[0.7623564  0.37933066 1.        ]\n",
      "[0.7623564  0.37933066 1.        ]\n",
      "[0.40954039 0.6407464  1.        ]\n",
      "[0.40954039 0.6407464  1.        ]\n",
      "[0.334351   0.65552264 1.        ]\n",
      "[0.334351   0.65552264 1.        ]\n",
      "[0.07603859 0.18778512 1.        ]\n",
      "[0.07603859 0.18778512 1.        ]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.53399485 0.32138944 1.        ]\n",
      "[0.53399485 0.32138944 1.        ]\n",
      "[0.3340918  0.64470094 1.        ]\n",
      "[0.3340918  0.64470094 1.        ]\n",
      "[0.75174874 0.37181374 1.        ]\n",
      "[0.75174874 0.37181374 1.        ]\n",
      "[0.9188657 0.5929782 1.       ]\n",
      "[0.9188657 0.5929782 1.       ]\n",
      "[0.8595262  0.41054162 1.        ]\n",
      "[0.8595262  0.41054162 1.        ]\n",
      "[0.874201  0.7435325 1.       ]\n",
      "[0.874201  0.7435325 1.       ]\n",
      "[0.3768695 0.6660423 1.       ]\n",
      "[0.3768695 0.6660423 1.       ]\n",
      "[0.926943   0.74515015 1.        ]\n",
      "[0.926943   0.74515015 1.        ]\n",
      "[0.29809955 0.62278897 1.        ]\n",
      "[0.29809955 0.62278897 1.        ]\n",
      "[0.47467148 0.63591313 1.        ]\n",
      "[0.47467148 0.63591313 1.        ]\n",
      "[0.70363694 0.32946697 1.        ]\n",
      "[0.70363694 0.32946697 1.        ]\n",
      "[0.8128631  0.42654365 1.        ]\n",
      "[0.8128631  0.42654365 1.        ]\n",
      "[0.16922505 0.59642136 1.        ]\n",
      "[0.16922505 0.59642136 1.        ]\n",
      "[0.17541173 0.5969224  1.        ]\n",
      "[0.17541173 0.5969224  1.        ]\n",
      "[0.12122424 0.51913    1.        ]\n",
      "[0.12122424 0.51913    1.        ]\n",
      "[0.14202712 0.5608266  1.        ]\n",
      "[0.14202712 0.5608266  1.        ]\n",
      "[0.2830834  0.68284607 1.        ]\n",
      "[0.2830834  0.68284607 1.        ]\n",
      "[0.11608178 0.16345522 1.        ]\n",
      "[0.11608178 0.16345522 1.        ]\n",
      "[0.89729154 0.8085056  1.        ]\n",
      "[0.89729154 0.8085056  1.        ]\n",
      "[0.87971425 0.5991245  1.        ]\n",
      "[0.87971425 0.5991245  1.        ]\n",
      "[0.40711313 0.42800778 1.        ]\n",
      "[0.40711313 0.42800778 1.        ]\n",
      "[0.49361095 0.30789527 1.        ]\n",
      "[0.49361095 0.30789527 1.        ]\n",
      "[0.5049371 0.3717762 1.       ]\n",
      "[0.5049371 0.3717762 1.       ]\n",
      "[0.87757623 0.5165852  1.        ]\n",
      "[0.87757623 0.5165852  1.        ]\n",
      "[0.90346813 0.9056007  1.        ]\n",
      "[0.90346813 0.9056007  1.        ]\n",
      "[0.90627265 0.59465754 1.        ]\n",
      "[0.90627265 0.59465754 1.        ]\n",
      "[0.10952549 0.33889806 1.        ]\n",
      "[0.10952549 0.33889806 1.        ]\n",
      "[0.8480889  0.43216118 1.        ]\n",
      "[0.8480889  0.43216118 1.        ]\n",
      "[0.8778047  0.42477652 1.        ]\n",
      "[0.8778047  0.42477652 1.        ]\n",
      "[0.33236268 0.67439145 1.        ]\n",
      "[0.33236268 0.67439145 1.        ]\n",
      "[0.47649887 0.3697464  1.        ]\n",
      "[0.47649887 0.3697464  1.        ]\n",
      "[0.10687476 0.19018042 1.        ]\n",
      "[0.10687476 0.19018042 1.        ]\n",
      "[0.87851506 0.8073077  1.        ]\n",
      "[0.87851506 0.8073077  1.        ]\n",
      "[0.08891282 0.42392108 1.        ]\n",
      "[0.08891282 0.42392108 1.        ]\n",
      "[0.7621773  0.35704663 1.        ]\n",
      "[0.7621773  0.35704663 1.        ]\n",
      "[0.12119471 0.21907467 1.        ]\n",
      "[0.12119471 0.21907467 1.        ]\n",
      "[0.77189773 0.44206896 1.        ]\n",
      "[0.77189773 0.44206896 1.        ]\n",
      "[0.7603717  0.36940703 1.        ]\n",
      "[0.7603717  0.36940703 1.        ]\n",
      "[0.3404948  0.36750576 1.        ]\n",
      "[0.3404948  0.36750576 1.        ]\n",
      "[0.19584268 0.63841206 1.        ]\n",
      "[0.19584268 0.63841206 1.        ]\n",
      "[0.92114806 0.66374207 1.        ]\n",
      "[0.92114806 0.66374207 1.        ]\n",
      "[0.11642437 0.24172987 1.        ]\n",
      "[0.11642437 0.24172987 1.        ]\n",
      "[0.5417737 0.6527815 1.       ]\n",
      "[0.5417737 0.6527815 1.       ]\n",
      "[0.26895487 0.6880078  1.        ]\n",
      "[0.26895487 0.6880078  1.        ]\n",
      "[0.60031575 0.30869392 1.        ]\n",
      "[0.60031575 0.30869392 1.        ]\n",
      "[0.13574982 0.16298704 1.        ]\n",
      "[0.13574982 0.16298704 1.        ]\n",
      "[0.35992306 0.6432467  1.        ]\n",
      "[0.35992306 0.6432467  1.        ]\n",
      "[0.7415553  0.32240877 1.        ]\n",
      "[0.7415553  0.32240877 1.        ]\n",
      "[0.7129233  0.33772138 1.        ]\n",
      "[0.7129233  0.33772138 1.        ]\n",
      "[0.72210336 0.3193142  1.        ]\n",
      "[0.72210336 0.3193142  1.        ]\n",
      "[0.9446209  0.67085266 1.        ]\n",
      "[0.9446209  0.67085266 1.        ]\n",
      "[0.5303187  0.67058074 1.        ]\n",
      "[0.5303187  0.67058074 1.        ]\n",
      "[0.07207727 0.1912037  1.        ]\n",
      "[0.07207727 0.1912037  1.        ]\n",
      "[0.104058   0.27427128 1.        ]\n",
      "[0.104058   0.27427128 1.        ]\n",
      "[0.08070468 0.24996898 1.        ]\n",
      "[0.08070468 0.24996898 1.        ]\n",
      "[0.50171024 0.689927   1.        ]\n",
      "[0.50171024 0.689927   1.        ]\n",
      "[0.35434777 0.6681898  1.        ]\n",
      "[0.35434777 0.6681898  1.        ]\n",
      "[0.55015403 0.61316997 1.        ]"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-16-1d9858c9c414>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m    180\u001b[0m     \u001b[0mseed\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m12345\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    181\u001b[0m     \u001b[0mrbm\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mRBM\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m8\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 182\u001b[1;33m     \u001b[0mrbm\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlearn\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m4000\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    183\u001b[0m     \u001b[0mkkk\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    184\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m<ipython-input-16-1d9858c9c414>\u001b[0m in \u001b[0;36mlearn\u001b[1;34m(self, epochmax)\u001b[0m\n\u001b[0;32m    109\u001b[0m                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mSvis0\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdat\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mpoint\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    110\u001b[0m                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mSvis\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mSvis0\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 111\u001b[1;33m                 \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mSvis0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    112\u001b[0m                 \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mSvis\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    113\u001b[0m                 \u001b[1;31m# positive phase\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\envs\\myenv\\lib\\site-packages\\ipykernel\\iostream.py\u001b[0m in \u001b[0;36mwrite\u001b[1;34m(self, string)\u001b[0m\n\u001b[0;32m    398\u001b[0m             \u001b[0mis_child\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_is_master_process\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    399\u001b[0m             \u001b[1;31m# only touch the buffer in the IO thread to avoid races\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 400\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpub_thread\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mschedule\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;32mlambda\u001b[0m \u001b[1;33m:\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_buffer\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwrite\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mstring\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    401\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mis_child\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    402\u001b[0m                 \u001b[1;31m# newlines imply flush in subprocesses\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\envs\\myenv\\lib\\site-packages\\ipykernel\\iostream.py\u001b[0m in \u001b[0;36mschedule\u001b[1;34m(self, f)\u001b[0m\n\u001b[0;32m    201\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_events\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    202\u001b[0m             \u001b[1;31m# wake event thread (message content is ignored)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 203\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_event_pipe\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34mb''\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    204\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    205\u001b[0m             \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\envs\\myenv\\lib\\site-packages\\zmq\\sugar\\socket.py\u001b[0m in \u001b[0;36msend\u001b[1;34m(self, data, flags, copy, track, routing_id, group)\u001b[0m\n\u001b[0;32m    393\u001b[0m                                  copy_threshold=self.copy_threshold)\n\u001b[0;32m    394\u001b[0m             \u001b[0mdata\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mgroup\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgroup\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 395\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0msuper\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mSocket\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mflags\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mflags\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mcopy\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtrack\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mtrack\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    396\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    397\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0msend_multipart\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmsg_parts\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mflags\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtrack\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mzmq/backend/cython/socket.pyx\u001b[0m in \u001b[0;36mzmq.backend.cython.socket.Socket.send\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mzmq/backend/cython/socket.pyx\u001b[0m in \u001b[0;36mzmq.backend.cython.socket.Socket.send\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mzmq/backend/cython/socket.pyx\u001b[0m in \u001b[0;36mzmq.backend.cython.socket._send_copy\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\envs\\myenv\\lib\\site-packages\\zmq\\backend\\cython\\checkrc.pxd\u001b[0m in \u001b[0;36mzmq.backend.cython.checkrc._check_rc\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "\"\"\"\n",
    "Continuous Restricted Boltzmann Machine\n",
    "14/09/2008 - v. 0.1 by http://imonad.com\n",
    "\"\"\"\n",
    "\n",
    "from numpy import *\n",
    "from numpy.random import *\n",
    "import pylab as p\n",
    "from scipy import stats, mgrid, c_, reshape, random, rot90\n",
    "\n",
    "# import psyco\n",
    "# psyco.full()\n",
    "\n",
    "\n",
    "class RBM:\n",
    "    def __init__(self, nvis, nhid):\n",
    "        self.sig = 0.2\n",
    "        self.epsW = 0.5\n",
    "        self.epsA  = 0.5\n",
    "        self.nvis = nvis\n",
    "        self.nhid = nhid\n",
    "        self.Ndat = 500\n",
    "        self.cost = 0.00001\n",
    "        self.moment = 0.90\n",
    "        self.Svis0 = zeros( nvis+1, dtype=float32)\n",
    "        self.Svis0[-1] = 1.0\n",
    "        self.Svis = zeros( nvis+1, dtype=float32)\n",
    "        self.Svis[-1] = 1.0\n",
    "        self.Shid = zeros( nhid+1, dtype=float32)\n",
    "        self.W  = standard_normal((nvis+1, nhid+1))/10\n",
    "        self.dW = standard_normal((nvis+1, nhid+1))/1000\n",
    "        self.Avis  =  0.1*ones( nvis+1, dtype=float32)\n",
    "        self.Ahid  =  ones( nhid+1, dtype=float32)\n",
    "        self.dA = zeros( nvis+1, dtype=float32)\n",
    "        self.dat = self.genData()\n",
    "\n",
    "    def genData(self):\n",
    "        c1 = 0.5\n",
    "        r1 = 0.4\n",
    "        r2 = 0.3\n",
    "        # generate enough data to filter\n",
    "        N = 20* self.Ndat\n",
    "        X = array(random_sample(N))\n",
    "        Y = array(random_sample(N))\n",
    "        X1 = X[(X-c1)*(X-c1) + (Y-c1)*(Y-c1) < r1*r1]\n",
    "        Y1 = Y[(X-c1)*(X-c1) + (Y-c1)*(Y-c1) < r1*r1]\n",
    "        X2 = X1[(X1-c1)*(X1-c1) + (Y1-c1)*(Y1-c1) > r2*r2]\n",
    "        Y2 = Y1[(X1-c1)*(X1-c1) + (Y1-c1)*(Y1-c1) > r2*r2]\n",
    "        X3 = X2[ abs(X2-Y2)>0.05 ]\n",
    "        Y3 = Y2[ abs(X2-Y2)>0.05 ]\n",
    "        #X3 = X2[ X2-Y2>0.15 ]\n",
    "        #Y3 = Y2[ X2-Y2>0.15]\n",
    "        X4=zeros( self.Ndat, dtype=float32)\n",
    "        Y4=zeros( self.Ndat, dtype=float32)\n",
    "        for i in range(self.Ndat):\n",
    "            if (X3[i]-Y3[i]) >0.05:\n",
    "                X4[i] = X3[i] + 0.08\n",
    "                Y4[i] = Y3[i] + 0.18\n",
    "            else:\n",
    "                X4[i] = X3[i] - 0.08\n",
    "                Y4[i] = Y3[i] - 0.18\n",
    "        print(\"X\", size(X3[0:self.Ndat]), \"Y\", size(Y3))\n",
    "#         print(vstack((X4[0:self.Ndat],Y4[0:self.Ndat]))[0])\n",
    "        return(vstack((X4[0:self.Ndat],Y4[0:self.Ndat])))\n",
    "\n",
    "    # Sigmoidal Function\n",
    "    def sigFun(self, X, A):\n",
    "        lo = 0.0\n",
    "        hi = 1.0\n",
    "        return(lo + (hi-lo)/(1.0 + exp(-A*X)))\n",
    "\n",
    "    # visible=0, hidden=1\n",
    "    def activ(self, who):\n",
    "        if(who==0):\n",
    "            self.Svis = dot(self.W, self.Shid) + self.sig*standard_normal(self.nvis+1)         \n",
    "            self.Svis = self.sigFun(self.Svis, self.Avis)\n",
    "            self.Svis[-1] = 1.0 # bias\n",
    "        if(who==1):\n",
    "            self.Shid = dot(self.Svis, self.W) + self.sig*standard_normal(self.nhid+1)\n",
    "            self.Shid = self.sigFun(self.Shid, self.Ahid)\n",
    "            self.Shid[-1] = 1.0 # bias\n",
    "\n",
    "    def wview(self):\n",
    "        import pylab as p\n",
    "        p.plot(range(size(self.W[2])),self.W[2], 'bo')\n",
    "        p.show()\n",
    "\n",
    "    def learn(self, epochmax):\n",
    "        Err = zeros( epochmax, dtype=float32)\n",
    "        E = zeros( epochmax, dtype=float32)\n",
    "        self.stat = zeros( epochmax, dtype=float32)\n",
    "        self.stat2 = zeros( epochmax, dtype=float32)\n",
    "        ksteps = 1\n",
    "        \n",
    "        for epoch in range(1,epochmax):\n",
    "            wpos = zeros( (self.nvis+1, self.nhid+1), dtype=float32)\n",
    "            wneg = zeros( (self.nvis+1, self.nhid+1), dtype=float32)\n",
    "            apos = zeros( self.nhid+1, dtype=float32)\n",
    "            aneg = zeros( self.nhid+1, dtype=float32)\n",
    "                \n",
    "            if(epoch>0):\n",
    "                ksteps=50\n",
    "            if(epoch>1000):\n",
    "                ksteps=(epoch-epoch%100)/100+40\n",
    "            self.ksteps = ksteps\n",
    "            \n",
    "            for point in range(self.Ndat):\n",
    "                #print(self.dat[:][point])\n",
    "                self.Svis0[0:2] = self.dat[:,point]\n",
    "                self.Svis = self.Svis0\n",
    "                # positive phase\n",
    "                self.activ(1)\n",
    "                wpos = wpos + outer(self.Svis, self.Shid)\n",
    "                apos = apos + self.Shid*self.Shid\n",
    "                # negative phase\n",
    "                self.activ(0)\n",
    "                self.activ(1)\n",
    "                \n",
    "                \n",
    "                for recstep in range(ksteps): \n",
    "                    self.activ(0)\n",
    "                    self.activ(1)\n",
    "\n",
    "                tmp = outer(self.Svis, self.Shid)\n",
    "                wneg = wneg + tmp\n",
    "                aneg = aneg + self.Shid*self.Shid\n",
    "                \n",
    "                \n",
    "                delta = self.Svis0[0:2]-self.Svis[0:2]\n",
    "                # statistics\n",
    "                Err[epoch] = Err[epoch] + sum(delta*delta)\n",
    "                E[epoch] =E[epoch] -sum( dot(self.W.T, tmp) )\n",
    "                \n",
    "\n",
    "            \n",
    "            self.dW = self.dW*self.moment + self.epsW * ((wpos-wneg)/size(self.dat) - self.cost*self.W)\n",
    "            self.W = self.W + self.dW\n",
    "            self.Ahid = self.Ahid + self.epsA*(apos-aneg)/(size(self.dat)*self.Ahid*self.Ahid)\n",
    "\n",
    "            Err[epoch] = Err[epoch]/(self.nvis*size(self.dat))\n",
    "            E[epoch] = E[epoch]/size(self.dat)\n",
    "            if (epoch%100==0) or (epoch==epochmax) or (epoch==1):\n",
    "                print(\"epoch:\", epoch, \"err:\", round_(Err[epoch], 6), \"ksteps:\", ksteps)\n",
    "            self.stat[epoch] = self.W[0,0]\n",
    "            self.stat2[epoch] = self.Ahid[0]\n",
    "        self.Err = Err\n",
    "        self.E   = E\n",
    "        \n",
    "\n",
    "    def reconstruct(self, Npoint, Nsteps):\n",
    "        X = array(random_sample(Npoint))\n",
    "        Y = array(random_sample(Npoint))\n",
    "        datnew = vstack((X, Y))\n",
    "        self.datout = zeros( (2,Npoint), dtype=float32)\n",
    "        for point in range(Npoint):\n",
    "            self.Svis[0:2] = datnew[:,point]\n",
    "            for recstep in range(Nsteps): \n",
    "                self.activ(1)\n",
    "                self.activ(0)\n",
    "        \n",
    "            self.datout[:,point] = self.Svis[0:2]\n",
    "            \n",
    "    def contour(self, p, dat):\n",
    "        X, Y = mgrid[0.0:1.0:100j, 0.0:1.0:100j]\n",
    "        positions = c_[X.ravel(), Y.ravel()]\n",
    "        val           = c_[dat[0,:], dat[1,:]]\n",
    "        kernel = stats.kde.gaussian_kde(val.T)\n",
    "        Z = reshape(kernel(positions.T).T, X.T.shape)\n",
    "        p.imshow(     rot90(Z) , cmap=p.cm.YlGnBu, extent=[0, 1, 0, 1])\n",
    "        p.plot(dat[0,:], dat[1,:], 'r.')\n",
    "        p.axis([0.0, 1.0, 0.0, 1.0])\n",
    "    \n",
    "\n",
    "        \n",
    "\n",
    "if __name__ == \"__main__\":\n",
    "    \n",
    "    seed(12345)\n",
    "    rbm = RBM(2,8)\n",
    "    rbm.learn(4000)\n",
    "    kkk=0\n",
    "    \n",
    "    p.figure(1)\n",
    "    p.plot(range(size(rbm.E)),rbm.E, 'b+')\n",
    "\n",
    "    p.figure(2)\n",
    "    p.plot(range(size(rbm.Err)),rbm.Err, 'r.')\n",
    "\n",
    "    p.figure(3)\n",
    "    if kkk==1:\n",
    "        p.plot(rbm.dat[0,:],rbm.dat[1,:], 'bo')\n",
    "        p.axis([0.0, 1.0, 0.0, 1.0])\n",
    "    else:\n",
    "        rbm.contour(p, rbm.dat)\n",
    "        p.savefig(\"dat.png\",dpi=100)\n",
    "\n",
    "\n",
    "    rbm.reconstruct(rbm.Ndat, 1)\n",
    "    p.figure(4)\n",
    "    if kkk==1:\n",
    "        p.plot(rbm.datout[0,:],rbm.datout[1,:], 'b.')\n",
    "        p.axis([0.0, 1.0, 0.0, 1.0])\n",
    "    else:\n",
    "        rbm.contour(p, rbm.datout) \n",
    "    \n",
    "    rbm.reconstruct(rbm.Ndat, 20)\n",
    "    p.figure(5)\n",
    "    if kkk==1:\n",
    "        p.plot(rbm.datout[0,:],rbm.datout[1,:], 'b.')\n",
    "        p.axis([0.0, 1.0, 0.0, 1.0])\n",
    "    else:\n",
    "        rbm.contour(p, rbm.datout)\n",
    "    \n",
    "    \n",
    "    rbm.reconstruct(rbm.Ndat, rbm.ksteps)\n",
    "    p.figure(6)\n",
    "    if kkk==1:\n",
    "        p.plot(rbm.datout[0,:],rbm.datout[1,:], 'b.')\n",
    "        p.axis([0.0, 1.0, 0.0, 1.0])\n",
    "    else:\n",
    "        rbm.contour(p, rbm.datout)\n",
    "        p.savefig(\"reconstruct.png\",dpi=100)\n",
    "\n",
    "    p.figure(7)\n",
    "    p.plot(range(size(rbm.stat)), rbm.stat, \"b.\")\n",
    "\n",
    "    p.figure(8)\n",
    "    p.plot(range(size(rbm.stat2)), rbm.stat2, \"b.\")\n",
    "\n",
    "    print(around(rbm.W,5))\n",
    "    print(rbm.Ahid)\n",
    "\n",
    "    p.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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