1_python_perceptron.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import numpy.random as nr\n",
    "import matplotlib.pyplot as pl\n",
    "%matplotlib inline\n",
    "\n",
    "# This notebook is based on an excellent tutorial by Kostis Gourgoulias (http://kgourgou.me/)\n",
    "\n",
    "# Specify size of plot\n",
    "pl.rcParams['figure.figsize'] = (12.0, 10.0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Playing around with the linear perceptron algorithm \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The linear perceptron algorithm can be used to classify data points according to pre-selected features they have. The idea is to find a curve (or hyperplane) that separates points with different features. Once we have the curve, we can use it to decide if future points are of feature A or B based on where they are with respect to the curve (above or below it). \n",
    "\n",
    "Now, let generate a collection of points and then paint them according to a line. If the points are above the line, they are blue, if they are below, green. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7f5d96b7e050>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA9wAAANDCAYAAABfYBeLAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\npA4w4ZYkSZIkqQNMuCVJkiRJ6oD/D1+vwetXm6x7AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5d98c09110>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Generate some points\n",
    "N = 100\n",
    "xn = nr.rand(N,2)\n",
    "\n",
    "x = np.linspace(0,1)\n",
    "\n",
    "# Pick a line \n",
    "#a, b = nr.rand(), nr.rand()\n",
    "a, b = 0.8, 0.2\n",
    "f = lambda x : a*x + b\n",
    "\n",
    "fig = pl.figure()\n",
    "figa = pl.gca()\n",
    "\n",
    "pl.plot(xn[:,0],xn[:,1],'bo')\n",
    "pl.plot(x,f(x),'r')\n",
    "\n",
    "# Linearly separate the points by the line\n",
    "yn = np.zeros([N,1])\n",
    "\n",
    "for i in xrange(N):\n",
    "    if(f(xn[i,0])>xn[i,1]):\n",
    "        # Point is below line\n",
    "        yn[i] = 1\n",
    "        pl.plot(xn[i,0],xn[i,1],'go')\n",
    "    else:\n",
    "        # Point is above line\n",
    "        yn[i] = -1\n",
    "        \n",
    "        \n",
    "pl.legend(['Above','Separator','Below'],loc=0)\n",
    "pl.title('Selected points with their separating line.')\n",
    "#figa.axes.get_xaxis().set_visible(False)\n",
    "#figa.axes.get_yaxis().set_visible(False)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The curve naturally separates the space into two regions, one of green points and one of blue points. Thus, if I am given a new point, I can assign it a color based on where it is with respect to the curve. It is really that simple.\n",
    "\n",
    "What is not so simple is to find the curve given the points. However, if the points are linearly separable, i.e. if a line exists that does the job, then I can just move a line around until I get it to the correct position. This is what the linear perceptron algorithm is doing."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "30 0.879833009026 0.8233558434 0.0 [ 1.]\n",
      "19 0.174161776555 0.597111911245 1.0 [-1.]\n",
      "97 0.045875351594 0.423093427763 1.0 [-1.]\n",
      "97 0.045875351594 0.423093427763 -1.0 [-1.]\n",
      "21 0.840331401342 0.629225436542 -1.0 [ 1.]\n"
     ]
    }
   ],
   "source": [
    "def perceptron(xn, yn, max_iter=1000, w=np.zeros(3)):\n",
    "    '''\n",
    "        A very simple implementation of the perceptron algorithm for two dimensional data.\n",
    "        \n",
    "        Given points (x,y) with x in R^{2} and y in {-1,1}, the perceptron learning algorithm searches for the best\n",
    "        line that separates the data points according to the difference classes defined in y. \n",
    "        \n",
    "        Input: \n",
    "            xn : Data points, an Nx2 vector. \n",
    "            yn : Classification of the previous data points, an Nx1 vector. \n",
    "            max_iter : Maximum number of iterations (optional).\n",
    "            w  : Initial vector of parameters (optional).\n",
    "            \n",
    "        Output: \n",
    "            w : Parameters of the best line, y = ax+b, that linearly separates the data. \n",
    "        \n",
    "        Note:\n",
    "            Convergence will be slower than expected, since this implementation picks points\n",
    "            to update without a specific plan (randomly). This is enough for a demonstration, not \n",
    "            so good for actual work. \n",
    "'''\n",
    "    \n",
    "    N = xn.shape[0]\n",
    "    \n",
    "    # Separating curve\n",
    "    f = lambda x: np.sign(w[0]+w[1]*x[0]+w[2]*x[1])\n",
    "\n",
    "    for _ in xrange(max_iter):\n",
    "        i = nr.randint(N) # try a random sample from the dataset\n",
    "        print i, xn[i,0], xn[i,1], f(xn[i,:]), yn[i]\n",
    "        if(yn[i] != f(xn[i,:])): # If not classified correctly, adjust the line to account for that point.\n",
    "            w[0] = w[0] + yn[i] # the first weight is effectively the bias\n",
    "            w[1] = w[1] + yn[i] * xn[i,0]\n",
    "            w[2] = w[2] + yn[i] * xn[i,1]\n",
    "            \n",
    "                \n",
    "                \n",
    "            \n",
    "    return w\n",
    "\n",
    "w = perceptron(xn, yn, max_iter=5)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that we have an implementation, let's see how close it gets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "91 0.0890732533084 0.00244232163674 1.0 [ 1.]\n",
      "41 0.81173758157 0.668956447099 -1.0 [ 1.]\n",
      "81 0.381810773963 0.0490773641201 1.0 [ 1.]\n",
      "53 0.548329869102 0.0624212455486 1.0 [ 1.]\n",
      "77 0.496264957964 0.845378385805 -1.0 [-1.]\n",
      "57 0.293664761481 0.729828763353 -1.0 [-1.]\n",
      "56 0.353738600475 0.00756391261736 1.0 [ 1.]\n",
      "86 0.196119994596 0.0285439625255 1.0 [ 1.]\n",
      "1 0.892296748113 0.177735339239 1.0 [ 1.]\n",
      "92 0.779426089377 0.893706883543 1.0 [-1.]\n",
      "5 0.919137310532 0.405530139276 1.0 [ 1.]\n",
      "11 0.239075832595 0.37766247145 -1.0 [ 1.]\n",
      "48 0.371056092459 0.163945871083 1.0 [ 1.]\n",
      "26 0.120163718153 0.761187461488 -1.0 [-1.]\n",
      "25 0.952509705642 0.0608161332277 1.0 [ 1.]\n",
      "82 0.535520226808 0.534943007047 1.0 [ 1.]\n",
      "81 0.381810773963 0.0490773641201 1.0 [ 1.]\n",
      "89 0.576238788847 0.30669210164 1.0 [ 1.]\n",
      "22 0.999495269627 0.373928049906 1.0 [ 1.]\n",
      "96 0.271118145609 0.402583553886 1.0 [ 1.]\n",
      "98 0.953279166254 0.0164775745715 1.0 [ 1.]\n",
      "40 0.390781201264 0.693559596939 -1.0 [-1.]\n",
      "27 0.281856192374 0.30011411922 1.0 [ 1.]\n",
      "77 0.496264957964 0.845378385805 -1.0 [-1.]\n",
      "21 0.840331401342 0.629225436542 1.0 [ 1.]\n",
      "77 0.496264957964 0.845378385805 -1.0 [-1.]\n",
      "88 0.18145704597 0.453838269468 -1.0 [-1.]\n",
      "82 0.535520226808 0.534943007047 1.0 [ 1.]\n",
      "62 0.554190410985 0.732632567499 -1.0 [-1.]\n",
      "29 0.990887462299 0.940005389776 -1.0 [ 1.]\n",
      "18 0.232510784476 0.0380953109131 1.0 [ 1.]\n",
      "16 0.88702319713 0.0768101145928 1.0 [ 1.]\n",
      "67 0.8570472191 0.386760791026 1.0 [ 1.]\n",
      "59 0.694236822751 0.960496982481 1.0 [-1.]\n",
      "89 0.576238788847 0.30669210164 1.0 [ 1.]\n",
      "58 0.843473715833 0.142090447691 1.0 [ 1.]\n",
      "53 0.548329869102 0.0624212455486 1.0 [ 1.]\n",
      "75 0.683534546985 0.0629488637525 1.0 [ 1.]\n",
      "25 0.952509705642 0.0608161332277 1.0 [ 1.]\n",
      "86 0.196119994596 0.0285439625255 1.0 [ 1.]\n",
      "61 0.0648544437806 0.82881802564 -1.0 [-1.]\n",
      "45 0.513588266283 0.519593913864 1.0 [ 1.]\n",
      "36 0.135587591581 0.611580384356 -1.0 [-1.]\n",
      "18 0.232510784476 0.0380953109131 1.0 [ 1.]\n",
      "17 0.616746606008 0.691849572172 1.0 [ 1.]\n",
      "81 0.381810773963 0.0490773641201 1.0 [ 1.]\n",
      "19 0.174161776555 0.597111911245 -1.0 [-1.]\n",
      "12 0.987358760495 0.695492327125 1.0 [ 1.]\n",
      "54 0.923614619505 0.907369666747 -1.0 [ 1.]\n",
      "17 0.616746606008 0.691849572172 1.0 [ 1.]\n",
      "19 0.174161776555 0.597111911245 1.0 [-1.]\n",
      "40 0.390781201264 0.693559596939 -1.0 [-1.]\n",
      "21 0.840331401342 0.629225436542 1.0 [ 1.]\n",
      "3 0.489900278109 0.0361629135948 1.0 [ 1.]\n",
      "57 0.293664761481 0.729828763353 -1.0 [-1.]\n",
      "71 0.736917167 0.0831379698757 1.0 [ 1.]\n",
      "65 0.724016071598 0.868408371425 1.0 [-1.]\n",
      "2 0.272429858097 0.0996488660833 1.0 [ 1.]\n",
      "40 0.390781201264 0.693559596939 -1.0 [-1.]\n",
      "47 0.765856295185 0.973839204595 -1.0 [-1.]\n",
      "62 0.554190410985 0.732632567499 -1.0 [-1.]\n",
      "31 0.353749480424 0.222712938048 1.0 [ 1.]\n",
      "84 0.511960485424 0.492128947069 -1.0 [ 1.]\n",
      "0 0.112686349571 0.595819718002 -1.0 [-1.]\n",
      "13 0.734323610514 0.59395724502 1.0 [ 1.]\n",
      "69 0.686860222636 0.567885278963 1.0 [ 1.]\n",
      "43 0.930071803683 0.668773150417 1.0 [ 1.]\n",
      "65 0.724016071598 0.868408371425 -1.0 [-1.]\n",
      "1 0.892296748113 0.177735339239 1.0 [ 1.]\n",
      "67 0.8570472191 0.386760791026 1.0 [ 1.]\n",
      "30 0.879833009026 0.8233558434 1.0 [ 1.]\n",
      "13 0.734323610514 0.59395724502 1.0 [ 1.]\n",
      "95 0.00496862368636 0.979399577186 -1.0 [-1.]\n",
      "70 0.647294095653 0.79905420063 -1.0 [-1.]\n",
      "37 0.115846816632 0.656502340474 -1.0 [-1.]\n",
      "88 0.18145704597 0.453838269468 -1.0 [-1.]\n",
      "96 0.271118145609 0.402583553886 1.0 [ 1.]\n",
      "83 0.143100616452 0.47401273593 -1.0 [-1.]\n",
      "36 0.135587591581 0.611580384356 -1.0 [-1.]\n",
      "84 0.511960485424 0.492128947069 1.0 [ 1.]\n",
      "35 0.511014542106 0.656675802281 1.0 [-1.]\n",
      "22 0.999495269627 0.373928049906 1.0 [ 1.]\n",
      "27 0.281856192374 0.30011411922 1.0 [ 1.]\n",
      "41 0.81173758157 0.668956447099 -1.0 [ 1.]\n",
      "48 0.371056092459 0.163945871083 1.0 [ 1.]\n",
      "23 0.513922567866 0.152461236624 1.0 [ 1.]\n",
      "51 0.163476432452 0.201643499134 1.0 [ 1.]\n",
      "95 0.00496862368636 0.979399577186 -1.0 [-1.]\n",
      "5 0.919137310532 0.405530139276 1.0 [ 1.]\n",
      "35 0.511014542106 0.656675802281 1.0 [-1.]\n",
      "71 0.736917167 0.0831379698757 1.0 [ 1.]\n",
      "86 0.196119994596 0.0285439625255 1.0 [ 1.]\n",
      "41 0.81173758157 0.668956447099 -1.0 [ 1.]\n",
      "85 0.93641898673 0.192563260228 1.0 [ 1.]\n",
      "10 0.184646086615 0.258210259342 1.0 [ 1.]\n",
      "81 0.381810773963 0.0490773641201 1.0 [ 1.]\n",
      "2 0.272429858097 0.0996488660833 1.0 [ 1.]\n",
      "47 0.765856295185 0.973839204595 -1.0 [-1.]\n",
      "92 0.779426089377 0.893706883543 1.0 [-1.]\n",
      "12 0.987358760495 0.695492327125 1.0 [ 1.]\n",
      "54 0.923614619505 0.907369666747 -1.0 [ 1.]\n",
      "83 0.143100616452 0.47401273593 -1.0 [-1.]\n",
      "7 0.0652883845189 0.186617724961 1.0 [ 1.]\n",
      "55 0.0247822099079 0.791406591631 -1.0 [-1.]\n",
      "54 0.923614619505 0.907369666747 1.0 [ 1.]\n",
      "48 0.371056092459 0.163945871083 1.0 [ 1.]\n",
      "66 0.452572628372 0.622648553801 1.0 [-1.]\n",
      "12 0.987358760495 0.695492327125 1.0 [ 1.]\n",
      "92 0.779426089377 0.893706883543 -1.0 [-1.]\n",
      "58 0.843473715833 0.142090447691 1.0 [ 1.]\n",
      "45 0.513588266283 0.519593913864 -1.0 [ 1.]\n",
      "35 0.511014542106 0.656675802281 1.0 [-1.]\n",
      "79 0.597297307701 0.823493915838 -1.0 [-1.]\n",
      "41 0.81173758157 0.668956447099 1.0 [ 1.]\n",
      "84 0.511960485424 0.492128947069 -1.0 [ 1.]\n",
      "6 0.67151033146 0.7554830267 1.0 [-1.]\n",
      "32 0.469096656183 0.552402853665 -1.0 [ 1.]\n",
      "59 0.694236822751 0.960496982481 -1.0 [-1.]\n",
      "24 0.967621042854 0.346893379289 1.0 [ 1.]\n",
      "50 0.991234656298 0.976972742406 1.0 [ 1.]\n",
      "86 0.196119994596 0.0285439625255 1.0 [ 1.]\n",
      "20 0.329549870376 0.969372894276 -1.0 [-1.]\n",
      "60 0.683969845028 0.409171762867 1.0 [ 1.]\n",
      "11 0.239075832595 0.37766247145 1.0 [ 1.]\n",
      "30 0.879833009026 0.8233558434 1.0 [ 1.]\n",
      "79 0.597297307701 0.823493915838 -1.0 [-1.]\n",
      "51 0.163476432452 0.201643499134 1.0 [ 1.]\n",
      "92 0.779426089377 0.893706883543 -1.0 [-1.]\n",
      "29 0.990887462299 0.940005389776 1.0 [ 1.]\n",
      "18 0.232510784476 0.0380953109131 1.0 [ 1.]\n",
      "22 0.999495269627 0.373928049906 1.0 [ 1.]\n",
      "60 0.683969845028 0.409171762867 1.0 [ 1.]\n",
      "68 0.354333276088 0.930061890577 -1.0 [-1.]\n",
      "31 0.353749480424 0.222712938048 1.0 [ 1.]\n",
      "12 0.987358760495 0.695492327125 1.0 [ 1.]\n",
      "13 0.734323610514 0.59395724502 1.0 [ 1.]\n",
      "32 0.469096656183 0.552402853665 1.0 [ 1.]\n",
      "79 0.597297307701 0.823493915838 -1.0 [-1.]\n",
      "82 0.535520226808 0.534943007047 1.0 [ 1.]\n",
      "16 0.88702319713 0.0768101145928 1.0 [ 1.]\n",
      "11 0.239075832595 0.37766247145 1.0 [ 1.]\n",
      "57 0.293664761481 0.729828763353 -1.0 [-1.]\n",
      "36 0.135587591581 0.611580384356 -1.0 [-1.]\n",
      "35 0.511014542106 0.656675802281 1.0 [-1.]\n",
      "39 0.831000884785 0.913121763713 -1.0 [-1.]\n",
      "90 0.306303132227 0.508438341563 -1.0 [-1.]\n",
      "74 0.866475955985 0.6472912176 1.0 [ 1.]\n",
      "51 0.163476432452 0.201643499134 1.0 [ 1.]\n",
      "21 0.840331401342 0.629225436542 1.0 [ 1.]\n",
      "53 0.548329869102 0.0624212455486 1.0 [ 1.]\n",
      "15 0.56293522383 0.541372509145 -1.0 [ 1.]\n",
      "63 0.575638390701 0.934658331896 -1.0 [-1.]\n",
      "17 0.616746606008 0.691849572172 1.0 [ 1.]\n",
      "29 0.990887462299 0.940005389776 1.0 [ 1.]\n",
      "51 0.163476432452 0.201643499134 1.0 [ 1.]\n",
      "53 0.548329869102 0.0624212455486 1.0 [ 1.]\n",
      "7 0.0652883845189 0.186617724961 1.0 [ 1.]\n",
      "56 0.353738600475 0.00756391261736 1.0 [ 1.]\n",
      "64 0.0697482249646 0.239849688301 1.0 [ 1.]\n",
      "69 0.686860222636 0.567885278963 1.0 [ 1.]\n",
      "57 0.293664761481 0.729828763353 -1.0 [-1.]\n",
      "20 0.329549870376 0.969372894276 -1.0 [-1.]\n",
      "24 0.967621042854 0.346893379289 1.0 [ 1.]\n",
      "1 0.892296748113 0.177735339239 1.0 [ 1.]\n",
      "81 0.381810773963 0.0490773641201 1.0 [ 1.]\n",
      "26 0.120163718153 0.761187461488 -1.0 [-1.]\n",
      "80 0.848160387085 0.581767032246 1.0 [ 1.]\n",
      "32 0.469096656183 0.552402853665 1.0 [ 1.]\n",
      "24 0.967621042854 0.346893379289 1.0 [ 1.]\n",
      "14 0.45751773429 0.168761153349 1.0 [ 1.]\n",
      "0 0.112686349571 0.595819718002 -1.0 [-1.]\n",
      "80 0.848160387085 0.581767032246 1.0 [ 1.]\n",
      "44 0.67030153368 0.434654882032 1.0 [ 1.]\n",
      "26 0.120163718153 0.761187461488 -1.0 [-1.]\n",
      "22 0.999495269627 0.373928049906 1.0 [ 1.]\n",
      "92 0.779426089377 0.893706883543 -1.0 [-1.]\n",
      "31 0.353749480424 0.222712938048 1.0 [ 1.]\n",
      "72 0.642924042961 0.274031947171 1.0 [ 1.]\n",
      "34 0.771153929748 0.790737142338 1.0 [ 1.]\n",
      "71 0.736917167 0.0831379698757 1.0 [ 1.]\n",
      "96 0.271118145609 0.402583553886 1.0 [ 1.]\n",
      "35 0.511014542106 0.656675802281 -1.0 [-1.]\n",
      "60 0.683969845028 0.409171762867 1.0 [ 1.]\n",
      "31 0.353749480424 0.222712938048 1.0 [ 1.]\n",
      "9 0.173135674059 0.293647642084 1.0 [ 1.]\n",
      "18 0.232510784476 0.0380953109131 1.0 [ 1.]\n",
      "55 0.0247822099079 0.791406591631 -1.0 [-1.]\n",
      "62 0.554190410985 0.732632567499 -1.0 [-1.]\n",
      "30 0.879833009026 0.8233558434 1.0 [ 1.]\n",
      "17 0.616746606008 0.691849572172 1.0 [ 1.]\n",
      "30 0.879833009026 0.8233558434 1.0 [ 1.]\n",
      "84 0.511960485424 0.492128947069 1.0 [ 1.]\n",
      "6 0.67151033146 0.7554830267 1.0 [-1.]\n",
      "59 0.694236822751 0.960496982481 -1.0 [-1.]\n",
      "39 0.831000884785 0.913121763713 -1.0 [-1.]\n",
      "32 0.469096656183 0.552402853665 -1.0 [ 1.]\n",
      "57 0.293664761481 0.729828763353 -1.0 [-1.]\n",
      "48 0.371056092459 0.163945871083 1.0 [ 1.]\n",
      "25 0.952509705642 0.0608161332277 1.0 [ 1.]\n",
      "89 0.576238788847 0.30669210164 1.0 [ 1.]\n",
      "52 0.521511147846 0.474250194048 1.0 [ 1.]\n",
      "83 0.143100616452 0.47401273593 -1.0 [-1.]\n",
      "80 0.848160387085 0.581767032246 1.0 [ 1.]\n",
      "26 0.120163718153 0.761187461488 -1.0 [-1.]\n",
      "98 0.953279166254 0.0164775745715 1.0 [ 1.]\n",
      "7 0.0652883845189 0.186617724961 1.0 [ 1.]\n",
      "9 0.173135674059 0.293647642084 1.0 [ 1.]\n",
      "6 0.67151033146 0.7554830267 -1.0 [-1.]\n",
      "41 0.81173758157 0.668956447099 1.0 [ 1.]\n",
      "57 0.293664761481 0.729828763353 -1.0 [-1.]\n",
      "30 0.879833009026 0.8233558434 1.0 [ 1.]\n",
      "71 0.736917167 0.0831379698757 1.0 [ 1.]\n",
      "38 0.571551605706 0.624716789126 1.0 [ 1.]\n",
      "97 0.045875351594 0.423093427763 -1.0 [-1.]\n",
      "51 0.163476432452 0.201643499134 1.0 [ 1.]\n",
      "66 0.452572628372 0.622648553801 -1.0 [-1.]\n",
      "96 0.271118145609 0.402583553886 1.0 [ 1.]\n",
      "28 0.0806789269102 0.0659012909087 1.0 [ 1.]\n",
      "0 0.112686349571 0.595819718002 -1.0 [-1.]\n",
      "28 0.0806789269102 0.0659012909087 1.0 [ 1.]\n",
      "3 0.489900278109 0.0361629135948 1.0 [ 1.]\n",
      "34 0.771153929748 0.790737142338 1.0 [ 1.]\n",
      "60 0.683969845028 0.409171762867 1.0 [ 1.]\n",
      "37 0.115846816632 0.656502340474 -1.0 [-1.]\n",
      "74 0.866475955985 0.6472912176 1.0 [ 1.]\n",
      "51 0.163476432452 0.201643499134 1.0 [ 1.]\n",
      "8 0.8265617107 0.852185434141 1.0 [ 1.]\n",
      "76 0.768955390969 0.903366052993 -1.0 [-1.]\n",
      "50 0.991234656298 0.976972742406 -1.0 [ 1.]\n",
      "10 0.184646086615 0.258210259342 1.0 [ 1.]\n",
      "68 0.354333276088 0.930061890577 -1.0 [-1.]\n",
      "1 0.892296748113 0.177735339239 1.0 [ 1.]\n",
      "82 0.535520226808 0.534943007047 1.0 [ 1.]\n",
      "26 0.120163718153 0.761187461488 -1.0 [-1.]\n",
      "35 0.511014542106 0.656675802281 1.0 [-1.]\n",
      "99 0.746488035775 0.171535146624 1.0 [ 1.]\n",
      "31 0.353749480424 0.222712938048 1.0 [ 1.]\n",
      "49 0.0107333010178 0.855353886455 -1.0 [-1.]\n",
      "91 0.0890732533084 0.00244232163674 1.0 [ 1.]\n",
      "52 0.521511147846 0.474250194048 1.0 [ 1.]\n",
      "31 0.353749480424 0.222712938048 1.0 [ 1.]\n",
      "8 0.8265617107 0.852185434141 1.0 [ 1.]\n",
      "92 0.779426089377 0.893706883543 1.0 [-1.]\n",
      "79 0.597297307701 0.823493915838 -1.0 [-1.]\n",
      "38 0.571551605706 0.624716789126 -1.0 [ 1.]\n",
      "83 0.143100616452 0.47401273593 -1.0 [-1.]\n",
      "79 0.597297307701 0.823493915838 -1.0 [-1.]\n",
      "80 0.848160387085 0.581767032246 1.0 [ 1.]\n",
      "11 0.239075832595 0.37766247145 1.0 [ 1.]\n",
      "60 0.683969845028 0.409171762867 1.0 [ 1.]\n",
      "9 0.173135674059 0.293647642084 1.0 [ 1.]\n",
      "60 0.683969845028 0.409171762867 1.0 [ 1.]\n",
      "74 0.866475955985 0.6472912176 1.0 [ 1.]\n",
      "53 0.548329869102 0.0624212455486 1.0 [ 1.]\n",
      "82 0.535520226808 0.534943007047 1.0 [ 1.]\n",
      "19 0.174161776555 0.597111911245 -1.0 [-1.]\n",
      "97 0.045875351594 0.423093427763 -1.0 [-1.]\n",
      "91 0.0890732533084 0.00244232163674 1.0 [ 1.]\n",
      "88 0.18145704597 0.453838269468 -1.0 [-1.]\n",
      "87 0.944976803419 0.443707231164 1.0 [ 1.]\n",
      "99 0.746488035775 0.171535146624 1.0 [ 1.]\n",
      "74 0.866475955985 0.6472912176 1.0 [ 1.]\n",
      "71 0.736917167 0.0831379698757 1.0 [ 1.]\n",
      "5 0.919137310532 0.405530139276 1.0 [ 1.]\n",
      "12 0.987358760495 0.695492327125 1.0 [ 1.]\n",
      "46 0.605808326697 0.870041821958 -1.0 [-1.]\n",
      "88 0.18145704597 0.453838269468 -1.0 [-1.]\n",
      "80 0.848160387085 0.581767032246 1.0 [ 1.]\n",
      "54 0.923614619505 0.907369666747 1.0 [ 1.]\n",
      "36 0.135587591581 0.611580384356 -1.0 [-1.]\n",
      "27 0.281856192374 0.30011411922 1.0 [ 1.]\n",
      "36 0.135587591581 0.611580384356 -1.0 [-1.]\n",
      "28 0.0806789269102 0.0659012909087 1.0 [ 1.]\n",
      "60 0.683969845028 0.409171762867 1.0 [ 1.]\n",
      "33 0.794230305109 0.591895838 1.0 [ 1.]\n",
      "46 0.605808326697 0.870041821958 -1.0 [-1.]\n",
      "55 0.0247822099079 0.791406591631 -1.0 [-1.]\n",
      "77 0.496264957964 0.845378385805 -1.0 [-1.]\n",
      "8 0.8265617107 0.852185434141 1.0 [ 1.]\n",
      "22 0.999495269627 0.373928049906 1.0 [ 1.]\n",
      "36 0.135587591581 0.611580384356 -1.0 [-1.]\n",
      "77 0.496264957964 0.845378385805 -1.0 [-1.]\n",
      "92 0.779426089377 0.893706883543 -1.0 [-1.]\n",
      "52 0.521511147846 0.474250194048 1.0 [ 1.]\n",
      "46 0.605808326697 0.870041821958 -1.0 [-1.]\n",
      "53 0.548329869102 0.0624212455486 1.0 [ 1.]\n",
      "72 0.642924042961 0.274031947171 1.0 [ 1.]\n",
      "53 0.548329869102 0.0624212455486 1.0 [ 1.]\n",
      "38 0.571551605706 0.624716789126 1.0 [ 1.]\n",
      "21 0.840331401342 0.629225436542 1.0 [ 1.]\n",
      "80 0.848160387085 0.581767032246 1.0 [ 1.]\n",
      "52 0.521511147846 0.474250194048 1.0 [ 1.]\n",
      "45 0.513588266283 0.519593913864 1.0 [ 1.]\n",
      "89 0.576238788847 0.30669210164 1.0 [ 1.]\n",
      "73 0.290734591188 0.424810284665 1.0 [ 1.]\n",
      "64 0.0697482249646 0.239849688301 1.0 [ 1.]\n",
      "10 0.184646086615 0.258210259342 1.0 [ 1.]\n",
      "17 0.616746606008 0.691849572172 1.0 [ 1.]\n",
      "55 0.0247822099079 0.791406591631 -1.0 [-1.]\n",
      "53 0.548329869102 0.0624212455486 1.0 [ 1.]\n",
      "72 0.642924042961 0.274031947171 1.0 [ 1.]\n",
      "50 0.991234656298 0.976972742406 1.0 [ 1.]\n",
      "68 0.354333276088 0.930061890577 -1.0 [-1.]\n",
      "78 0.776495471284 0.404143870584 1.0 [ 1.]\n",
      "73 0.290734591188 0.424810284665 1.0 [ 1.]\n",
      "80 0.848160387085 0.581767032246 1.0 [ 1.]\n",
      "62 0.554190410985 0.732632567499 -1.0 [-1.]\n",
      "36 0.135587591581 0.611580384356 -1.0 [-1.]\n",
      "7 0.0652883845189 0.186617724961 1.0 [ 1.]\n",
      "29 0.990887462299 0.940005389776 1.0 [ 1.]\n",
      "15 0.56293522383 0.541372509145 1.0 [ 1.]\n",
      "3 0.489900278109 0.0361629135948 1.0 [ 1.]\n",
      "35 0.511014542106 0.656675802281 -1.0 [-1.]\n",
      "42 0.764365085549 0.571570338649 1.0 [ 1.]\n",
      "38 0.571551605706 0.624716789126 1.0 [ 1.]\n",
      "23 0.513922567866 0.152461236624 1.0 [ 1.]\n",
      "52 0.521511147846 0.474250194048 1.0 [ 1.]\n",
      "53 0.548329869102 0.0624212455486 1.0 [ 1.]\n",
      "25 0.952509705642 0.0608161332277 1.0 [ 1.]\n",
      "34 0.771153929748 0.790737142338 1.0 [ 1.]\n",
      "62 0.554190410985 0.732632567499 -1.0 [-1.]\n",
      "57 0.293664761481 0.729828763353 -1.0 [-1.]\n",
      "6 0.67151033146 0.7554830267 1.0 [-1.]\n",
      "50 0.991234656298 0.976972742406 -1.0 [ 1.]\n",
      "37 0.115846816632 0.656502340474 -1.0 [-1.]\n",
      "39 0.831000884785 0.913121763713 1.0 [-1.]\n",
      "70 0.647294095653 0.79905420063 -1.0 [-1.]\n",
      "40 0.390781201264 0.693559596939 -1.0 [-1.]\n",
      "38 0.571551605706 0.624716789126 -1.0 [ 1.]\n",
      "67 0.8570472191 0.386760791026 1.0 [ 1.]\n",
      "90 0.306303132227 0.508438341563 -1.0 [-1.]\n",
      "13 0.734323610514 0.59395724502 1.0 [ 1.]\n",
      "58 0.843473715833 0.142090447691 1.0 [ 1.]\n",
      "16 0.88702319713 0.0768101145928 1.0 [ 1.]\n",
      "80 0.848160387085 0.581767032246 1.0 [ 1.]\n",
      "85 0.93641898673 0.192563260228 1.0 [ 1.]\n",
      "23 0.513922567866 0.152461236624 1.0 [ 1.]\n",
      "62 0.554190410985 0.732632567499 -1.0 [-1.]\n",
      "48 0.371056092459 0.163945871083 1.0 [ 1.]\n",
      "13 0.734323610514 0.59395724502 1.0 [ 1.]\n",
      "23 0.513922567866 0.152461236624 1.0 [ 1.]\n",
      "90 0.306303132227 0.508438341563 -1.0 [-1.]\n",
      "14 0.45751773429 0.168761153349 1.0 [ 1.]\n",
      "77 0.496264957964 0.845378385805 -1.0 [-1.]\n",
      "89 0.576238788847 0.30669210164 1.0 [ 1.]\n",
      "71 0.736917167 0.0831379698757 1.0 [ 1.]\n",
      "3 0.489900278109 0.0361629135948 1.0 [ 1.]\n",
      "67 0.8570472191 0.386760791026 1.0 [ 1.]\n",
      "2 0.272429858097 0.0996488660833 1.0 [ 1.]\n",
      "48 0.371056092459 0.163945871083 1.0 [ 1.]\n",
      "80 0.848160387085 0.581767032246 1.0 [ 1.]\n",
      "10 0.184646086615 0.258210259342 1.0 [ 1.]\n",
      "9 0.173135674059 0.293647642084 1.0 [ 1.]\n",
      "4 0.294849676429 0.477137560987 1.0 [-1.]\n",
      "96 0.271118145609 0.402583553886 -1.0 [ 1.]\n",
      "4 0.294849676429 0.477137560987 -1.0 [-1.]\n",
      "13 0.734323610514 0.59395724502 1.0 [ 1.]\n",
      "5 0.919137310532 0.405530139276 1.0 [ 1.]\n",
      "86 0.196119994596 0.0285439625255 1.0 [ 1.]\n",
      "55 0.0247822099079 0.791406591631 -1.0 [-1.]\n",
      "8 0.8265617107 0.852185434141 1.0 [ 1.]\n",
      "20 0.329549870376 0.969372894276 -1.0 [-1.]\n",
      "26 0.120163718153 0.761187461488 -1.0 [-1.]\n",
      "20 0.329549870376 0.969372894276 -1.0 [-1.]\n",
      "52 0.521511147846 0.474250194048 1.0 [ 1.]\n",
      "62 0.554190410985 0.732632567499 -1.0 [-1.]\n",
      "51 0.163476432452 0.201643499134 1.0 [ 1.]\n",
      "23 0.513922567866 0.152461236624 1.0 [ 1.]\n",
      "81 0.381810773963 0.0490773641201 1.0 [ 1.]\n",
      "53 0.548329869102 0.0624212455486 1.0 [ 1.]\n",
      "26 0.120163718153 0.761187461488 -1.0 [-1.]\n",
      "33 0.794230305109 0.591895838 1.0 [ 1.]\n",
      "49 0.0107333010178 0.855353886455 -1.0 [-1.]\n",
      "55 0.0247822099079 0.791406591631 -1.0 [-1.]\n",
      "14 0.45751773429 0.168761153349 1.0 [ 1.]\n",
      "31 0.353749480424 0.222712938048 1.0 [ 1.]\n",
      "57 0.293664761481 0.729828763353 -1.0 [-1.]\n",
      "65 0.724016071598 0.868408371425 -1.0 [-1.]\n",
      "37 0.115846816632 0.656502340474 -1.0 [-1.]\n",
      "30 0.879833009026 0.8233558434 1.0 [ 1.]\n",
      "14 0.45751773429 0.168761153349 1.0 [ 1.]\n",
      "87 0.944976803419 0.443707231164 1.0 [ 1.]\n",
      "31 0.353749480424 0.222712938048 1.0 [ 1.]\n",
      "9 0.173135674059 0.293647642084 1.0 [ 1.]\n",
      "52 0.521511147846 0.474250194048 1.0 [ 1.]\n",
      "68 0.354333276088 0.930061890577 -1.0 [-1.]\n",
      "20 0.329549870376 0.969372894276 -1.0 [-1.]\n",
      "28 0.0806789269102 0.0659012909087 1.0 [ 1.]\n",
      "54 0.923614619505 0.907369666747 1.0 [ 1.]\n",
      "97 0.045875351594 0.423093427763 -1.0 [-1.]\n",
      "47 0.765856295185 0.973839204595 -1.0 [-1.]\n",
      "75 0.683534546985 0.0629488637525 1.0 [ 1.]\n",
      "64 0.0697482249646 0.239849688301 1.0 [ 1.]\n",
      "72 0.642924042961 0.274031947171 1.0 [ 1.]\n",
      "16 0.88702319713 0.0768101145928 1.0 [ 1.]\n",
      "89 0.576238788847 0.30669210164 1.0 [ 1.]\n",
      "51 0.163476432452 0.201643499134 1.0 [ 1.]\n",
      "89 0.576238788847 0.30669210164 1.0 [ 1.]\n",
      "2 0.272429858097 0.0996488660833 1.0 [ 1.]\n",
      "69 0.686860222636 0.567885278963 1.0 [ 1.]\n",
      "22 0.999495269627 0.373928049906 1.0 [ 1.]\n",
      "7 0.0652883845189 0.186617724961 1.0 [ 1.]\n",
      "88 0.18145704597 0.453838269468 -1.0 [-1.]\n",
      "81 0.381810773963 0.0490773641201 1.0 [ 1.]\n",
      "63 0.575638390701 0.934658331896 -1.0 [-1.]\n",
      "13 0.734323610514 0.59395724502 1.0 [ 1.]\n",
      "23 0.513922567866 0.152461236624 1.0 [ 1.]\n",
      "9 0.173135674059 0.293647642084 1.0 [ 1.]\n",
      "39 0.831000884785 0.913121763713 -1.0 [-1.]\n",
      "79 0.597297307701 0.823493915838 -1.0 [-1.]\n",
      "19 0.174161776555 0.597111911245 -1.0 [-1.]\n",
      "57 0.293664761481 0.729828763353 -1.0 [-1.]\n",
      "89 0.576238788847 0.30669210164 1.0 [ 1.]\n",
      "17 0.616746606008 0.691849572172 1.0 [ 1.]\n",
      "30 0.879833009026 0.8233558434 1.0 [ 1.]\n",
      "94 0.461860723844 0.457741457449 1.0 [ 1.]\n",
      "0 0.112686349571 0.595819718002 -1.0 [-1.]\n",
      "1 0.892296748113 0.177735339239 1.0 [ 1.]\n",
      "97 0.045875351594 0.423093427763 -1.0 [-1.]\n",
      "62 0.554190410985 0.732632567499 -1.0 [-1.]\n",
      "12 0.987358760495 0.695492327125 1.0 [ 1.]\n",
      "80 0.848160387085 0.581767032246 1.0 [ 1.]\n",
      "8 0.8265617107 0.852185434141 1.0 [ 1.]\n",
      "1 0.892296748113 0.177735339239 1.0 [ 1.]\n",
      "36 0.135587591581 0.611580384356 -1.0 [-1.]\n",
      "9 0.173135674059 0.293647642084 1.0 [ 1.]\n",
      "16 0.88702319713 0.0768101145928 1.0 [ 1.]\n",
      "92 0.779426089377 0.893706883543 -1.0 [-1.]\n",
      "78 0.776495471284 0.404143870584 1.0 [ 1.]\n",
      "85 0.93641898673 0.192563260228 1.0 [ 1.]\n",
      "28 0.0806789269102 0.0659012909087 1.0 [ 1.]\n",
      "99 0.746488035775 0.171535146624 1.0 [ 1.]\n",
      "66 0.452572628372 0.622648553801 -1.0 [-1.]\n",
      "87 0.944976803419 0.443707231164 1.0 [ 1.]\n",
      "47 0.765856295185 0.973839204595 -1.0 [-1.]\n",
      "28 0.0806789269102 0.0659012909087 1.0 [ 1.]\n",
      "44 0.67030153368 0.434654882032 1.0 [ 1.]\n",
      "62 0.554190410985 0.732632567499 -1.0 [-1.]\n",
      "10 0.184646086615 0.258210259342 1.0 [ 1.]\n",
      "7 0.0652883845189 0.186617724961 1.0 [ 1.]\n",
      "91 0.0890732533084 0.00244232163674 1.0 [ 1.]\n",
      "38 0.571551605706 0.624716789126 1.0 [ 1.]\n",
      "49 0.0107333010178 0.855353886455 -1.0 [-1.]\n",
      "14 0.45751773429 0.168761153349 1.0 [ 1.]\n",
      "50 0.991234656298 0.976972742406 1.0 [ 1.]\n",
      "88 0.18145704597 0.453838269468 -1.0 [-1.]\n",
      "71 0.736917167 0.0831379698757 1.0 [ 1.]\n",
      "78 0.776495471284 0.404143870584 1.0 [ 1.]\n",
      "47 0.765856295185 0.973839204595 -1.0 [-1.]\n",
      "78 0.776495471284 0.404143870584 1.0 [ 1.]\n",
      "82 0.535520226808 0.534943007047 1.0 [ 1.]\n",
      "75 0.683534546985 0.0629488637525 1.0 [ 1.]\n",
      "41 0.81173758157 0.668956447099 1.0 [ 1.]\n",
      "71 0.736917167 0.0831379698757 1.0 [ 1.]\n",
      "19 0.174161776555 0.597111911245 -1.0 [-1.]\n",
      "33 0.794230305109 0.591895838 1.0 [ 1.]\n",
      "95 0.00496862368636 0.979399577186 -1.0 [-1.]\n",
      "80 0.848160387085 0.581767032246 1.0 [ 1.]\n",
      "53 0.548329869102 0.0624212455486 1.0 [ 1.]\n",
      "87 0.944976803419 0.443707231164 1.0 [ 1.]\n",
      "80 0.848160387085 0.581767032246 1.0 [ 1.]\n",
      "68 0.354333276088 0.930061890577 -1.0 [-1.]\n",
      "25 0.952509705642 0.0608161332277 1.0 [ 1.]\n",
      "88 0.18145704597 0.453838269468 -1.0 [-1.]\n",
      "52 0.521511147846 0.474250194048 1.0 [ 1.]\n",
      "97 0.045875351594 0.423093427763 -1.0 [-1.]\n",
      "45 0.513588266283 0.519593913864 1.0 [ 1.]\n",
      "23 0.513922567866 0.152461236624 1.0 [ 1.]\n",
      "42 0.764365085549 0.571570338649 1.0 [ 1.]\n",
      "1 0.892296748113 0.177735339239 1.0 [ 1.]\n",
      "46 0.605808326697 0.870041821958 -1.0 [-1.]\n",
      "1 0.892296748113 0.177735339239 1.0 [ 1.]\n",
      "25 0.952509705642 0.0608161332277 1.0 [ 1.]\n",
      "72 0.642924042961 0.274031947171 1.0 [ 1.]\n",
      "19 0.174161776555 0.597111911245 -1.0 [-1.]\n",
      "4 0.294849676429 0.477137560987 -1.0 [-1.]\n",
      "84 0.511960485424 0.492128947069 1.0 [ 1.]\n",
      "5 0.919137310532 0.405530139276 1.0 [ 1.]\n",
      "45 0.513588266283 0.519593913864 1.0 [ 1.]\n",
      "26 0.120163718153 0.761187461488 -1.0 [-1.]\n",
      "39 0.831000884785 0.913121763713 -1.0 [-1.]\n",
      "91 0.0890732533084 0.00244232163674 1.0 [ 1.]\n",
      "6 0.67151033146 0.7554830267 1.0 [-1.]\n",
      "6 0.67151033146 0.7554830267 -1.0 [-1.]\n",
      "38 0.571551605706 0.624716789126 -1.0 [ 1.]\n",
      "68 0.354333276088 0.930061890577 -1.0 [-1.]\n",
      "81 0.381810773963 0.0490773641201 1.0 [ 1.]\n",
      "40 0.390781201264 0.693559596939 -1.0 [-1.]\n",
      "54 0.923614619505 0.907369666747 1.0 [ 1.]\n",
      "37 0.115846816632 0.656502340474 -1.0 [-1.]\n",
      "64 0.0697482249646 0.239849688301 1.0 [ 1.]\n",
      "50 0.991234656298 0.976972742406 -1.0 [ 1.]\n",
      "6 0.67151033146 0.7554830267 1.0 [-1.]\n",
      "66 0.452572628372 0.622648553801 -1.0 [-1.]\n",
      "43 0.930071803683 0.668773150417 1.0 [ 1.]\n",
      "87 0.944976803419 0.443707231164 1.0 [ 1.]\n",
      "55 0.0247822099079 0.791406591631 -1.0 [-1.]\n",
      "50 0.991234656298 0.976972742406 1.0 [ 1.]\n",
      "94 0.461860723844 0.457741457449 1.0 [ 1.]\n",
      "98 0.953279166254 0.0164775745715 1.0 [ 1.]\n",
      "16 0.88702319713 0.0768101145928 1.0 [ 1.]\n",
      "66 0.452572628372 0.622648553801 -1.0 [-1.]\n",
      "80 0.848160387085 0.581767032246 1.0 [ 1.]\n",
      "94 0.461860723844 0.457741457449 1.0 [ 1.]\n",
      "95 0.00496862368636 0.979399577186 -1.0 [-1.]\n",
      "55 0.0247822099079 0.791406591631 -1.0 [-1.]\n",
      "28 0.0806789269102 0.0659012909087 1.0 [ 1.]\n",
      "32 0.469096656183 0.552402853665 1.0 [ 1.]\n",
      "41 0.81173758157 0.668956447099 1.0 [ 1.]\n",
      "28 0.0806789269102 0.0659012909087 1.0 [ 1.]\n",
      "41 0.81173758157 0.668956447099 1.0 [ 1.]\n",
      "28 0.0806789269102 0.0659012909087 1.0 [ 1.]\n",
      "89 0.576238788847 0.30669210164 1.0 [ 1.]\n",
      "79 0.597297307701 0.823493915838 -1.0 [-1.]\n",
      "95 0.00496862368636 0.979399577186 -1.0 [-1.]\n",
      "25 0.952509705642 0.0608161332277 1.0 [ 1.]\n",
      "9 0.173135674059 0.293647642084 1.0 [ 1.]\n",
      "70 0.647294095653 0.79905420063 -1.0 [-1.]\n",
      "84 0.511960485424 0.492128947069 1.0 [ 1.]\n",
      "13 0.734323610514 0.59395724502 1.0 [ 1.]\n",
      "0 0.112686349571 0.595819718002 -1.0 [-1.]\n",
      "21 0.840331401342 0.629225436542 1.0 [ 1.]\n",
      "1 0.892296748113 0.177735339239 1.0 [ 1.]\n",
      "63 0.575638390701 0.934658331896 -1.0 [-1.]\n",
      "49 0.0107333010178 0.855353886455 -1.0 [-1.]\n",
      "18 0.232510784476 0.0380953109131 1.0 [ 1.]\n",
      "64 0.0697482249646 0.239849688301 1.0 [ 1.]\n",
      "51 0.163476432452 0.201643499134 1.0 [ 1.]\n",
      "10 0.184646086615 0.258210259342 1.0 [ 1.]\n",
      "92 0.779426089377 0.893706883543 -1.0 [-1.]\n",
      "79 0.597297307701 0.823493915838 -1.0 [-1.]\n",
      "87 0.944976803419 0.443707231164 1.0 [ 1.]\n",
      "26 0.120163718153 0.761187461488 -1.0 [-1.]\n",
      "66 0.452572628372 0.622648553801 -1.0 [-1.]\n",
      "92 0.779426089377 0.893706883543 -1.0 [-1.]\n",
      "71 0.736917167 0.0831379698757 1.0 [ 1.]\n",
      "50 0.991234656298 0.976972742406 1.0 [ 1.]\n",
      "17 0.616746606008 0.691849572172 1.0 [ 1.]\n",
      "41 0.81173758157 0.668956447099 1.0 [ 1.]\n",
      "17 0.616746606008 0.691849572172 1.0 [ 1.]\n",
      "90 0.306303132227 0.508438341563 -1.0 [-1.]\n",
      "88 0.18145704597 0.453838269468 -1.0 [-1.]\n",
      "25 0.952509705642 0.0608161332277 1.0 [ 1.]\n",
      "82 0.535520226808 0.534943007047 1.0 [ 1.]\n",
      "20 0.329549870376 0.969372894276 -1.0 [-1.]\n",
      "51 0.163476432452 0.201643499134 1.0 [ 1.]\n",
      "2 0.272429858097 0.0996488660833 1.0 [ 1.]\n",
      "29 0.990887462299 0.940005389776 1.0 [ 1.]\n",
      "60 0.683969845028 0.409171762867 1.0 [ 1.]\n",
      "18 0.232510784476 0.0380953109131 1.0 [ 1.]\n",
      "6 0.67151033146 0.7554830267 1.0 [-1.]\n",
      "57 0.293664761481 0.729828763353 -1.0 [-1.]\n",
      "57 0.293664761481 0.729828763353 -1.0 [-1.]\n",
      "54 0.923614619505 0.907369666747 -1.0 [ 1.]\n",
      "59 0.694236822751 0.960496982481 -1.0 [-1.]\n",
      "92 0.779426089377 0.893706883543 1.0 [-1.]\n",
      "65 0.724016071598 0.868408371425 -1.0 [-1.]\n",
      "1 0.892296748113 0.177735339239 1.0 [ 1.]\n",
      "59 0.694236822751 0.960496982481 -1.0 [-1.]\n",
      "2 0.272429858097 0.0996488660833 1.0 [ 1.]\n",
      "81 0.381810773963 0.0490773641201 1.0 [ 1.]\n",
      "37 0.115846816632 0.656502340474 -1.0 [-1.]\n",
      "48 0.371056092459 0.163945871083 1.0 [ 1.]\n",
      "93 0.370136828682 0.918092060306 -1.0 [-1.]\n",
      "60 0.683969845028 0.409171762867 1.0 [ 1.]\n",
      "91 0.0890732533084 0.00244232163674 1.0 [ 1.]\n",
      "61 0.0648544437806 0.82881802564 -1.0 [-1.]\n",
      "42 0.764365085549 0.571570338649 1.0 [ 1.]\n",
      "72 0.642924042961 0.274031947171 1.0 [ 1.]\n",
      "42 0.764365085549 0.571570338649 1.0 [ 1.]\n",
      "56 0.353738600475 0.00756391261736 1.0 [ 1.]\n",
      "33 0.794230305109 0.591895838 1.0 [ 1.]\n",
      "10 0.184646086615 0.258210259342 -1.0 [ 1.]\n",
      "99 0.746488035775 0.171535146624 1.0 [ 1.]\n",
      "11 0.239075832595 0.37766247145 1.0 [ 1.]\n",
      "33 0.794230305109 0.591895838 1.0 [ 1.]\n",
      "21 0.840331401342 0.629225436542 1.0 [ 1.]\n",
      "13 0.734323610514 0.59395724502 1.0 [ 1.]\n",
      "30 0.879833009026 0.8233558434 1.0 [ 1.]\n",
      "65 0.724016071598 0.868408371425 -1.0 [-1.]\n",
      "78 0.776495471284 0.404143870584 1.0 [ 1.]\n",
      "32 0.469096656183 0.552402853665 1.0 [ 1.]\n",
      "81 0.381810773963 0.0490773641201 1.0 [ 1.]\n",
      "85 0.93641898673 0.192563260228 1.0 [ 1.]\n",
      "34 0.771153929748 0.790737142338 -1.0 [ 1.]\n",
      "79 0.597297307701 0.823493915838 1.0 [-1.]\n",
      "55 0.0247822099079 0.791406591631 -1.0 [-1.]\n",
      "71 0.736917167 0.0831379698757 1.0 [ 1.]\n",
      "22 0.999495269627 0.373928049906 1.0 [ 1.]\n",
      "4 0.294849676429 0.477137560987 -1.0 [-1.]\n",
      "91 0.0890732533084 0.00244232163674 1.0 [ 1.]\n",
      "53 0.548329869102 0.0624212455486 1.0 [ 1.]\n",
      "46 0.605808326697 0.870041821958 -1.0 [-1.]\n",
      "59 0.694236822751 0.960496982481 -1.0 [-1.]\n",
      "49 0.0107333010178 0.855353886455 -1.0 [-1.]\n",
      "56 0.353738600475 0.00756391261736 1.0 [ 1.]\n",
      "29 0.990887462299 0.940005389776 1.0 [ 1.]\n",
      "28 0.0806789269102 0.0659012909087 1.0 [ 1.]\n",
      "42 0.764365085549 0.571570338649 1.0 [ 1.]\n",
      "72 0.642924042961 0.274031947171 1.0 [ 1.]\n",
      "38 0.571551605706 0.624716789126 1.0 [ 1.]\n",
      "70 0.647294095653 0.79905420063 -1.0 [-1.]\n",
      "5 0.919137310532 0.405530139276 1.0 [ 1.]\n",
      "79 0.597297307701 0.823493915838 -1.0 [-1.]\n",
      "14 0.45751773429 0.168761153349 1.0 [ 1.]\n",
      "22 0.999495269627 0.373928049906 1.0 [ 1.]\n",
      "56 0.353738600475 0.00756391261736 1.0 [ 1.]\n",
      "40 0.390781201264 0.693559596939 -1.0 [-1.]\n",
      "38 0.571551605706 0.624716789126 1.0 [ 1.]\n",
      "84 0.511960485424 0.492128947069 1.0 [ 1.]\n",
      "82 0.535520226808 0.534943007047 1.0 [ 1.]\n",
      "69 0.686860222636 0.567885278963 1.0 [ 1.]\n",
      "99 0.746488035775 0.171535146624 1.0 [ 1.]\n",
      "69 0.686860222636 0.567885278963 1.0 [ 1.]\n",
      "63 0.575638390701 0.934658331896 -1.0 [-1.]\n",
      "83 0.143100616452 0.47401273593 -1.0 [-1.]\n",
      "50 0.991234656298 0.976972742406 -1.0 [ 1.]\n",
      "95 0.00496862368636 0.979399577186 -1.0 [-1.]\n",
      "97 0.045875351594 0.423093427763 1.0 [-1.]\n",
      "72 0.642924042961 0.274031947171 1.0 [ 1.]\n",
      "19 0.174161776555 0.597111911245 -1.0 [-1.]\n",
      "56 0.353738600475 0.00756391261736 1.0 [ 1.]\n",
      "68 0.354333276088 0.930061890577 -1.0 [-1.]\n",
      "2 0.272429858097 0.0996488660833 1.0 [ 1.]\n",
      "42 0.764365085549 0.571570338649 1.0 [ 1.]\n",
      "90 0.306303132227 0.508438341563 1.0 [-1.]\n",
      "24 0.967621042854 0.346893379289 1.0 [ 1.]\n",
      "43 0.930071803683 0.668773150417 1.0 [ 1.]\n",
      "80 0.848160387085 0.581767032246 1.0 [ 1.]\n",
      "17 0.616746606008 0.691849572172 -1.0 [ 1.]\n",
      "1 0.892296748113 0.177735339239 1.0 [ 1.]\n",
      "39 0.831000884785 0.913121763713 1.0 [-1.]\n",
      "45 0.513588266283 0.519593913864 -1.0 [ 1.]\n",
      "91 0.0890732533084 0.00244232163674 1.0 [ 1.]\n",
      "8 0.8265617107 0.852185434141 1.0 [ 1.]\n",
      "89 0.576238788847 0.30669210164 1.0 [ 1.]\n",
      "14 0.45751773429 0.168761153349 1.0 [ 1.]\n",
      "97 0.045875351594 0.423093427763 -1.0 [-1.]\n",
      "52 0.521511147846 0.474250194048 1.0 [ 1.]\n",
      "34 0.771153929748 0.790737142338 1.0 [ 1.]\n",
      "12 0.987358760495 0.695492327125 1.0 [ 1.]\n",
      "94 0.461860723844 0.457741457449 1.0 [ 1.]\n",
      "65 0.724016071598 0.868408371425 1.0 [-1.]\n",
      "8 0.8265617107 0.852185434141 -1.0 [ 1.]\n",
      "24 0.967621042854 0.346893379289 1.0 [ 1.]\n",
      "14 0.45751773429 0.168761153349 1.0 [ 1.]\n",
      "25 0.952509705642 0.0608161332277 1.0 [ 1.]\n",
      "5 0.919137310532 0.405530139276 1.0 [ 1.]\n",
      "54 0.923614619505 0.907369666747 1.0 [ 1.]\n",
      "75 0.683534546985 0.0629488637525 1.0 [ 1.]\n",
      "84 0.511960485424 0.492128947069 1.0 [ 1.]\n",
      "22 0.999495269627 0.373928049906 1.0 [ 1.]\n",
      "73 0.290734591188 0.424810284665 1.0 [ 1.]\n",
      "44 0.67030153368 0.434654882032 1.0 [ 1.]\n",
      "42 0.764365085549 0.571570338649 1.0 [ 1.]\n",
      "87 0.944976803419 0.443707231164 1.0 [ 1.]\n",
      "29 0.990887462299 0.940005389776 1.0 [ 1.]\n",
      "69 0.686860222636 0.567885278963 1.0 [ 1.]\n",
      "4 0.294849676429 0.477137560987 1.0 [-1.]\n",
      "11 0.239075832595 0.37766247145 -1.0 [ 1.]\n",
      "48 0.371056092459 0.163945871083 1.0 [ 1.]\n",
      "32 0.469096656183 0.552402853665 1.0 [ 1.]\n",
      "86 0.196119994596 0.0285439625255 1.0 [ 1.]\n",
      "12 0.987358760495 0.695492327125 1.0 [ 1.]\n",
      "51 0.163476432452 0.201643499134 1.0 [ 1.]\n",
      "48 0.371056092459 0.163945871083 1.0 [ 1.]\n",
      "72 0.642924042961 0.274031947171 1.0 [ 1.]\n",
      "51 0.163476432452 0.201643499134 1.0 [ 1.]\n",
      "86 0.196119994596 0.0285439625255 1.0 [ 1.]\n",
      "12 0.987358760495 0.695492327125 1.0 [ 1.]\n",
      "51 0.163476432452 0.201643499134 1.0 [ 1.]\n",
      "82 0.535520226808 0.534943007047 1.0 [ 1.]\n",
      "69 0.686860222636 0.567885278963 1.0 [ 1.]\n",
      "22 0.999495269627 0.373928049906 1.0 [ 1.]\n",
      "78 0.776495471284 0.404143870584 1.0 [ 1.]\n",
      "70 0.647294095653 0.79905420063 1.0 [-1.]\n",
      "47 0.765856295185 0.973839204595 -1.0 [-1.]\n",
      "78 0.776495471284 0.404143870584 1.0 [ 1.]\n",
      "97 0.045875351594 0.423093427763 -1.0 [-1.]\n",
      "19 0.174161776555 0.597111911245 -1.0 [-1.]\n",
      "71 0.736917167 0.0831379698757 1.0 [ 1.]\n",
      "63 0.575638390701 0.934658331896 -1.0 [-1.]\n",
      "99 0.746488035775 0.171535146624 1.0 [ 1.]\n",
      "56 0.353738600475 0.00756391261736 1.0 [ 1.]\n",
      "25 0.952509705642 0.0608161332277 1.0 [ 1.]\n",
      "58 0.843473715833 0.142090447691 1.0 [ 1.]\n",
      "34 0.771153929748 0.790737142338 -1.0 [ 1.]\n",
      "73 0.290734591188 0.424810284665 1.0 [ 1.]\n",
      "89 0.576238788847 0.30669210164 1.0 [ 1.]\n",
      "90 0.306303132227 0.508438341563 1.0 [-1.]\n",
      "81 0.381810773963 0.0490773641201 1.0 [ 1.]\n",
      "78 0.776495471284 0.404143870584 1.0 [ 1.]\n",
      "31 0.353749480424 0.222712938048 1.0 [ 1.]\n",
      "60 0.683969845028 0.409171762867 1.0 [ 1.]\n",
      "16 0.88702319713 0.0768101145928 1.0 [ 1.]\n",
      "10 0.184646086615 0.258210259342 1.0 [ 1.]\n",
      "14 0.45751773429 0.168761153349 1.0 [ 1.]\n",
      "46 0.605808326697 0.870041821958 -1.0 [-1.]\n",
      "33 0.794230305109 0.591895838 1.0 [ 1.]\n",
      "58 0.843473715833 0.142090447691 1.0 [ 1.]\n",
      "56 0.353738600475 0.00756391261736 1.0 [ 1.]\n",
      "80 0.848160387085 0.581767032246 1.0 [ 1.]\n",
      "72 0.642924042961 0.274031947171 1.0 [ 1.]\n",
      "51 0.163476432452 0.201643499134 1.0 [ 1.]\n",
      "95 0.00496862368636 0.979399577186 -1.0 [-1.]\n",
      "78 0.776495471284 0.404143870584 1.0 [ 1.]\n",
      "91 0.0890732533084 0.00244232163674 1.0 [ 1.]\n",
      "19 0.174161776555 0.597111911245 -1.0 [-1.]\n",
      "25 0.952509705642 0.0608161332277 1.0 [ 1.]\n",
      "21 0.840331401342 0.629225436542 1.0 [ 1.]\n",
      "56 0.353738600475 0.00756391261736 1.0 [ 1.]\n",
      "78 0.776495471284 0.404143870584 1.0 [ 1.]\n",
      "80 0.848160387085 0.581767032246 1.0 [ 1.]\n",
      "22 0.999495269627 0.373928049906 1.0 [ 1.]\n",
      "48 0.371056092459 0.163945871083 1.0 [ 1.]\n",
      "13 0.734323610514 0.59395724502 1.0 [ 1.]\n",
      "53 0.548329869102 0.0624212455486 1.0 [ 1.]\n",
      "52 0.521511147846 0.474250194048 1.0 [ 1.]\n",
      "55 0.0247822099079 0.791406591631 -1.0 [-1.]\n",
      "63 0.575638390701 0.934658331896 -1.0 [-1.]\n",
      "65 0.724016071598 0.868408371425 -1.0 [-1.]\n",
      "57 0.293664761481 0.729828763353 -1.0 [-1.]\n",
      "97 0.045875351594 0.423093427763 -1.0 [-1.]\n",
      "23 0.513922567866 0.152461236624 1.0 [ 1.]\n",
      "97 0.045875351594 0.423093427763 -1.0 [-1.]\n",
      "50 0.991234656298 0.976972742406 -1.0 [ 1.]\n",
      "8 0.8265617107 0.852185434141 1.0 [ 1.]\n",
      "53 0.548329869102 0.0624212455486 1.0 [ 1.]\n",
      "92 0.779426089377 0.893706883543 1.0 [-1.]\n",
      "11 0.239075832595 0.37766247145 -1.0 [ 1.]\n",
      "49 0.0107333010178 0.855353886455 -1.0 [-1.]\n",
      "83 0.143100616452 0.47401273593 -1.0 [-1.]\n",
      "57 0.293664761481 0.729828763353 -1.0 [-1.]\n",
      "97 0.045875351594 0.423093427763 -1.0 [-1.]\n",
      "94 0.461860723844 0.457741457449 1.0 [ 1.]\n",
      "41 0.81173758157 0.668956447099 1.0 [ 1.]\n",
      "17 0.616746606008 0.691849572172 1.0 [ 1.]\n",
      "24 0.967621042854 0.346893379289 1.0 [ 1.]\n",
      "55 0.0247822099079 0.791406591631 -1.0 [-1.]\n",
      "77 0.496264957964 0.845378385805 -1.0 [-1.]\n",
      "25 0.952509705642 0.0608161332277 1.0 [ 1.]\n",
      "25 0.952509705642 0.0608161332277 1.0 [ 1.]\n",
      "8 0.8265617107 0.852185434141 1.0 [ 1.]\n",
      "38 0.571551605706 0.624716789126 1.0 [ 1.]\n",
      "23 0.513922567866 0.152461236624 1.0 [ 1.]\n",
      "79 0.597297307701 0.823493915838 -1.0 [-1.]\n",
      "30 0.879833009026 0.8233558434 1.0 [ 1.]\n",
      "78 0.776495471284 0.404143870584 1.0 [ 1.]\n",
      "66 0.452572628372 0.622648553801 1.0 [-1.]\n",
      "23 0.513922567866 0.152461236624 1.0 [ 1.]\n",
      "51 0.163476432452 0.201643499134 1.0 [ 1.]\n",
      "33 0.794230305109 0.591895838 1.0 [ 1.]\n",
      "49 0.0107333010178 0.855353886455 -1.0 [-1.]\n",
      "13 0.734323610514 0.59395724502 1.0 [ 1.]\n",
      "3 0.489900278109 0.0361629135948 1.0 [ 1.]\n",
      "60 0.683969845028 0.409171762867 1.0 [ 1.]\n",
      "71 0.736917167 0.0831379698757 1.0 [ 1.]\n",
      "77 0.496264957964 0.845378385805 -1.0 [-1.]\n",
      "51 0.163476432452 0.201643499134 1.0 [ 1.]\n",
      "53 0.548329869102 0.0624212455486 1.0 [ 1.]\n",
      "76 0.768955390969 0.903366052993 -1.0 [-1.]\n",
      "82 0.535520226808 0.534943007047 -1.0 [ 1.]\n",
      "2 0.272429858097 0.0996488660833 1.0 [ 1.]\n",
      "38 0.571551605706 0.624716789126 1.0 [ 1.]\n",
      "22 0.999495269627 0.373928049906 1.0 [ 1.]\n",
      "0 0.112686349571 0.595819718002 -1.0 [-1.]\n",
      "17 0.616746606008 0.691849572172 1.0 [ 1.]\n",
      "71 0.736917167 0.0831379698757 1.0 [ 1.]\n",
      "56 0.353738600475 0.00756391261736 1.0 [ 1.]\n",
      "22 0.999495269627 0.373928049906 1.0 [ 1.]\n",
      "31 0.353749480424 0.222712938048 1.0 [ 1.]\n",
      "18 0.232510784476 0.0380953109131 1.0 [ 1.]\n",
      "21 0.840331401342 0.629225436542 1.0 [ 1.]\n",
      "92 0.779426089377 0.893706883543 1.0 [-1.]\n",
      "17 0.616746606008 0.691849572172 -1.0 [ 1.]\n",
      "64 0.0697482249646 0.239849688301 1.0 [ 1.]\n",
      "62 0.554190410985 0.732632567499 -1.0 [-1.]\n",
      "59 0.694236822751 0.960496982481 -1.0 [-1.]\n",
      "52 0.521511147846 0.474250194048 1.0 [ 1.]\n",
      "40 0.390781201264 0.693559596939 -1.0 [-1.]\n",
      "11 0.239075832595 0.37766247145 1.0 [ 1.]\n",
      "79 0.597297307701 0.823493915838 -1.0 [-1.]\n",
      "6 0.67151033146 0.7554830267 1.0 [-1.]\n",
      "18 0.232510784476 0.0380953109131 1.0 [ 1.]\n",
      "46 0.605808326697 0.870041821958 -1.0 [-1.]\n",
      "12 0.987358760495 0.695492327125 1.0 [ 1.]\n",
      "75 0.683534546985 0.0629488637525 1.0 [ 1.]\n",
      "27 0.281856192374 0.30011411922 1.0 [ 1.]\n",
      "99 0.746488035775 0.171535146624 1.0 [ 1.]\n",
      "12 0.987358760495 0.695492327125 1.0 [ 1.]\n",
      "76 0.768955390969 0.903366052993 -1.0 [-1.]\n",
      "73 0.290734591188 0.424810284665 -1.0 [ 1.]\n",
      "84 0.511960485424 0.492128947069 1.0 [ 1.]\n",
      "32 0.469096656183 0.552402853665 1.0 [ 1.]\n",
      "29 0.990887462299 0.940005389776 1.0 [ 1.]\n",
      "59 0.694236822751 0.960496982481 -1.0 [-1.]\n",
      "99 0.746488035775 0.171535146624 1.0 [ 1.]\n",
      "15 0.56293522383 0.541372509145 1.0 [ 1.]\n",
      "75 0.683534546985 0.0629488637525 1.0 [ 1.]\n",
      "93 0.370136828682 0.918092060306 -1.0 [-1.]\n",
      "67 0.8570472191 0.386760791026 1.0 [ 1.]\n",
      "5 0.919137310532 0.405530139276 1.0 [ 1.]\n",
      "59 0.694236822751 0.960496982481 -1.0 [-1.]\n",
      "1 0.892296748113 0.177735339239 1.0 [ 1.]\n",
      "95 0.00496862368636 0.979399577186 -1.0 [-1.]\n",
      "81 0.381810773963 0.0490773641201 1.0 [ 1.]\n",
      "77 0.496264957964 0.845378385805 -1.0 [-1.]\n",
      "79 0.597297307701 0.823493915838 -1.0 [-1.]\n",
      "8 0.8265617107 0.852185434141 1.0 [ 1.]\n",
      "96 0.271118145609 0.402583553886 1.0 [ 1.]\n",
      "59 0.694236822751 0.960496982481 -1.0 [-1.]\n",
      "57 0.293664761481 0.729828763353 -1.0 [-1.]\n",
      "12 0.987358760495 0.695492327125 1.0 [ 1.]\n",
      "72 0.642924042961 0.274031947171 1.0 [ 1.]\n",
      "35 0.511014542106 0.656675802281 -1.0 [-1.]\n",
      "74 0.866475955985 0.6472912176 1.0 [ 1.]\n",
      "12 0.987358760495 0.695492327125 1.0 [ 1.]\n",
      "70 0.647294095653 0.79905420063 -1.0 [-1.]\n",
      "94 0.461860723844 0.457741457449 1.0 [ 1.]\n",
      "30 0.879833009026 0.8233558434 1.0 [ 1.]\n",
      "46 0.605808326697 0.870041821958 -1.0 [-1.]\n",
      "32 0.469096656183 0.552402853665 1.0 [ 1.]\n",
      "1 0.892296748113 0.177735339239 1.0 [ 1.]\n",
      "73 0.290734591188 0.424810284665 1.0 [ 1.]\n",
      "57 0.293664761481 0.729828763353 -1.0 [-1.]\n",
      "68 0.354333276088 0.930061890577 -1.0 [-1.]\n",
      "15 0.56293522383 0.541372509145 1.0 [ 1.]\n",
      "72 0.642924042961 0.274031947171 1.0 [ 1.]\n",
      "81 0.381810773963 0.0490773641201 1.0 [ 1.]\n",
      "68 0.354333276088 0.930061890577 -1.0 [-1.]\n",
      "76 0.768955390969 0.903366052993 -1.0 [-1.]\n",
      "72 0.642924042961 0.274031947171 1.0 [ 1.]\n",
      "69 0.686860222636 0.567885278963 1.0 [ 1.]\n",
      "28 0.0806789269102 0.0659012909087 1.0 [ 1.]\n",
      "54 0.923614619505 0.907369666747 1.0 [ 1.]\n",
      "51 0.163476432452 0.201643499134 1.0 [ 1.]\n",
      "35 0.511014542106 0.656675802281 -1.0 [-1.]\n",
      "57 0.293664761481 0.729828763353 -1.0 [-1.]\n",
      "12 0.987358760495 0.695492327125 1.0 [ 1.]\n",
      "37 0.115846816632 0.656502340474 -1.0 [-1.]\n",
      "51 0.163476432452 0.201643499134 1.0 [ 1.]\n",
      "73 0.290734591188 0.424810284665 1.0 [ 1.]\n",
      "58 0.843473715833 0.142090447691 1.0 [ 1.]\n",
      "2 0.272429858097 0.0996488660833 1.0 [ 1.]\n",
      "84 0.511960485424 0.492128947069 1.0 [ 1.]\n",
      "48 0.371056092459 0.163945871083 1.0 [ 1.]\n",
      "93 0.370136828682 0.918092060306 -1.0 [-1.]\n",
      "4 0.294849676429 0.477137560987 -1.0 [-1.]\n",
      "52 0.521511147846 0.474250194048 1.0 [ 1.]\n",
      "56 0.353738600475 0.00756391261736 1.0 [ 1.]\n",
      "65 0.724016071598 0.868408371425 -1.0 [-1.]\n",
      "7 0.0652883845189 0.186617724961 1.0 [ 1.]\n",
      "96 0.271118145609 0.402583553886 1.0 [ 1.]\n",
      "53 0.548329869102 0.0624212455486 1.0 [ 1.]\n",
      "88 0.18145704597 0.453838269468 -1.0 [-1.]\n",
      "17 0.616746606008 0.691849572172 1.0 [ 1.]\n",
      "34 0.771153929748 0.790737142338 1.0 [ 1.]\n",
      "2 0.272429858097 0.0996488660833 1.0 [ 1.]\n",
      "43 0.930071803683 0.668773150417 1.0 [ 1.]\n",
      "91 0.0890732533084 0.00244232163674 1.0 [ 1.]\n",
      "99 0.746488035775 0.171535146624 1.0 [ 1.]\n",
      "38 0.571551605706 0.624716789126 1.0 [ 1.]\n",
      "46 0.605808326697 0.870041821958 -1.0 [-1.]\n",
      "16 0.88702319713 0.0768101145928 1.0 [ 1.]\n",
      "25 0.952509705642 0.0608161332277 1.0 [ 1.]\n",
      "77 0.496264957964 0.845378385805 -1.0 [-1.]\n",
      "91 0.0890732533084 0.00244232163674 1.0 [ 1.]\n",
      "8 0.8265617107 0.852185434141 1.0 [ 1.]\n",
      "77 0.496264957964 0.845378385805 -1.0 [-1.]\n",
      "1 0.892296748113 0.177735339239 1.0 [ 1.]\n",
      "28 0.0806789269102 0.0659012909087 1.0 [ 1.]\n",
      "85 0.93641898673 0.192563260228 1.0 [ 1.]\n",
      "77 0.496264957964 0.845378385805 -1.0 [-1.]\n",
      "35 0.511014542106 0.656675802281 -1.0 [-1.]\n",
      "15 0.56293522383 0.541372509145 1.0 [ 1.]\n",
      "8 0.8265617107 0.852185434141 1.0 [ 1.]\n",
      "89 0.576238788847 0.30669210164 1.0 [ 1.]\n",
      "36 0.135587591581 0.611580384356 -1.0 [-1.]\n",
      "68 0.354333276088 0.930061890577 -1.0 [-1.]\n",
      "42 0.764365085549 0.571570338649 1.0 [ 1.]\n",
      "76 0.768955390969 0.903366052993 -1.0 [-1.]\n",
      "86 0.196119994596 0.0285439625255 1.0 [ 1.]\n",
      "56 0.353738600475 0.00756391261736 1.0 [ 1.]\n",
      "98 0.953279166254 0.0164775745715 1.0 [ 1.]\n",
      "80 0.848160387085 0.581767032246 1.0 [ 1.]\n",
      "78 0.776495471284 0.404143870584 1.0 [ 1.]\n",
      "75 0.683534546985 0.0629488637525 1.0 [ 1.]\n",
      "49 0.0107333010178 0.855353886455 -1.0 [-1.]\n",
      "26 0.120163718153 0.761187461488 -1.0 [-1.]\n",
      "9 0.173135674059 0.293647642084 1.0 [ 1.]\n",
      "75 0.683534546985 0.0629488637525 1.0 [ 1.]\n",
      "68 0.354333276088 0.930061890577 -1.0 [-1.]\n",
      "28 0.0806789269102 0.0659012909087 1.0 [ 1.]\n",
      "19 0.174161776555 0.597111911245 -1.0 [-1.]\n",
      "51 0.163476432452 0.201643499134 1.0 [ 1.]\n",
      "77 0.496264957964 0.845378385805 -1.0 [-1.]\n",
      "49 0.0107333010178 0.855353886455 -1.0 [-1.]\n",
      "19 0.174161776555 0.597111911245 -1.0 [-1.]\n",
      "4 0.294849676429 0.477137560987 -1.0 [-1.]\n",
      "56 0.353738600475 0.00756391261736 1.0 [ 1.]\n",
      "28 0.0806789269102 0.0659012909087 1.0 [ 1.]\n",
      "13 0.734323610514 0.59395724502 1.0 [ 1.]\n",
      "31 0.353749480424 0.222712938048 1.0 [ 1.]\n",
      "90 0.306303132227 0.508438341563 -1.0 [-1.]\n",
      "20 0.329549870376 0.969372894276 -1.0 [-1.]\n",
      "92 0.779426089377 0.893706883543 -1.0 [-1.]\n",
      "65 0.724016071598 0.868408371425 -1.0 [-1.]\n",
      "77 0.496264957964 0.845378385805 -1.0 [-1.]\n",
      "35 0.511014542106 0.656675802281 -1.0 [-1.]\n",
      "51 0.163476432452 0.201643499134 1.0 [ 1.]\n",
      "73 0.290734591188 0.424810284665 1.0 [ 1.]\n",
      "50 0.991234656298 0.976972742406 1.0 [ 1.]\n",
      "75 0.683534546985 0.0629488637525 1.0 [ 1.]\n",
      "84 0.511960485424 0.492128947069 1.0 [ 1.]\n",
      "12 0.987358760495 0.695492327125 1.0 [ 1.]\n",
      "34 0.771153929748 0.790737142338 1.0 [ 1.]\n",
      "28 0.0806789269102 0.0659012909087 1.0 [ 1.]\n",
      "65 0.724016071598 0.868408371425 -1.0 [-1.]\n",
      "78 0.776495471284 0.404143870584 1.0 [ 1.]\n",
      "66 0.452572628372 0.622648553801 -1.0 [-1.]\n",
      "31 0.353749480424 0.222712938048 1.0 [ 1.]\n",
      "21 0.840331401342 0.629225436542 1.0 [ 1.]\n",
      "9 0.173135674059 0.293647642084 1.0 [ 1.]\n",
      "4 0.294849676429 0.477137560987 -1.0 [-1.]\n",
      "73 0.290734591188 0.424810284665 1.0 [ 1.]\n",
      "25 0.952509705642 0.0608161332277 1.0 [ 1.]\n",
      "53 0.548329869102 0.0624212455486 1.0 [ 1.]\n",
      "45 0.513588266283 0.519593913864 1.0 [ 1.]\n",
      "38 0.571551605706 0.624716789126 1.0 [ 1.]\n",
      "17 0.616746606008 0.691849572172 1.0 [ 1.]\n",
      "15 0.56293522383 0.541372509145 1.0 [ 1.]\n",
      "98 0.953279166254 0.0164775745715 1.0 [ 1.]\n",
      "55 0.0247822099079 0.791406591631 -1.0 [-1.]\n",
      "73 0.290734591188 0.424810284665 1.0 [ 1.]\n",
      "46 0.605808326697 0.870041821958 -1.0 [-1.]\n",
      "49 0.0107333010178 0.855353886455 -1.0 [-1.]\n",
      "43 0.930071803683 0.668773150417 1.0 [ 1.]\n",
      "97 0.045875351594 0.423093427763 -1.0 [-1.]\n",
      "0 0.112686349571 0.595819718002 -1.0 [-1.]\n",
      "97 0.045875351594 0.423093427763 -1.0 [-1.]\n",
      "8 0.8265617107 0.852185434141 1.0 [ 1.]\n",
      "3 0.489900278109 0.0361629135948 1.0 [ 1.]\n",
      "79 0.597297307701 0.823493915838 -1.0 [-1.]\n",
      "46 0.605808326697 0.870041821958 -1.0 [-1.]\n",
      "73 0.290734591188 0.424810284665 1.0 [ 1.]\n",
      "37 0.115846816632 0.656502340474 -1.0 [-1.]\n",
      "73 0.290734591188 0.424810284665 1.0 [ 1.]\n",
      "82 0.535520226808 0.534943007047 1.0 [ 1.]\n",
      "72 0.642924042961 0.274031947171 1.0 [ 1.]\n",
      "8 0.8265617107 0.852185434141 1.0 [ 1.]\n",
      "91 0.0890732533084 0.00244232163674 1.0 [ 1.]\n",
      "42 0.764365085549 0.571570338649 1.0 [ 1.]\n",
      "51 0.163476432452 0.201643499134 1.0 [ 1.]\n",
      "67 0.8570472191 0.386760791026 1.0 [ 1.]\n",
      "50 0.991234656298 0.976972742406 1.0 [ 1.]\n",
      "24 0.967621042854 0.346893379289 1.0 [ 1.]\n",
      "31 0.353749480424 0.222712938048 1.0 [ 1.]\n",
      "90 0.306303132227 0.508438341563 -1.0 [-1.]\n",
      "47 0.765856295185 0.973839204595 -1.0 [-1.]\n",
      "71 0.736917167 0.0831379698757 1.0 [ 1.]\n",
      "24 0.967621042854 0.346893379289 1.0 [ 1.]\n",
      "94 0.461860723844 0.457741457449 1.0 [ 1.]\n",
      "62 0.554190410985 0.732632567499 -1.0 [-1.]\n",
      "85 0.93641898673 0.192563260228 1.0 [ 1.]\n",
      "23 0.513922567866 0.152461236624 1.0 [ 1.]\n",
      "7 0.0652883845189 0.186617724961 1.0 [ 1.]\n",
      "73 0.290734591188 0.424810284665 1.0 [ 1.]\n",
      "68 0.354333276088 0.930061890577 -1.0 [-1.]\n",
      "47 0.765856295185 0.973839204595 -1.0 [-1.]\n",
      "90 0.306303132227 0.508438341563 -1.0 [-1.]\n",
      "59 0.694236822751 0.960496982481 -1.0 [-1.]\n",
      "7 0.0652883845189 0.186617724961 1.0 [ 1.]\n",
      "37 0.115846816632 0.656502340474 -1.0 [-1.]\n",
      "3 0.489900278109 0.0361629135948 1.0 [ 1.]\n",
      "78 0.776495471284 0.404143870584 1.0 [ 1.]\n",
      "63 0.575638390701 0.934658331896 -1.0 [-1.]\n",
      "5 0.919137310532 0.405530139276 1.0 [ 1.]\n",
      "20 0.329549870376 0.969372894276 -1.0 [-1.]\n",
      "20 0.329549870376 0.969372894276 -1.0 [-1.]\n",
      "82 0.535520226808 0.534943007047 1.0 [ 1.]\n",
      "26 0.120163718153 0.761187461488 -1.0 [-1.]\n",
      "10 0.184646086615 0.258210259342 1.0 [ 1.]\n",
      "93 0.370136828682 0.918092060306 -1.0 [-1.]\n",
      "10 0.184646086615 0.258210259342 1.0 [ 1.]\n",
      "37 0.115846816632 0.656502340474 -1.0 [-1.]\n",
      "94 0.461860723844 0.457741457449 1.0 [ 1.]\n",
      "88 0.18145704597 0.453838269468 -1.0 [-1.]\n",
      "11 0.239075832595 0.37766247145 1.0 [ 1.]\n",
      "9 0.173135674059 0.293647642084 1.0 [ 1.]\n",
      "38 0.571551605706 0.624716789126 1.0 [ 1.]\n",
      "89 0.576238788847 0.30669210164 1.0 [ 1.]\n",
      "24 0.967621042854 0.346893379289 1.0 [ 1.]\n",
      "95 0.00496862368636 0.979399577186 -1.0 [-1.]\n",
      "20 0.329549870376 0.969372894276 -1.0 [-1.]\n",
      "10 0.184646086615 0.258210259342 1.0 [ 1.]\n",
      "97 0.045875351594 0.423093427763 -1.0 [-1.]\n",
      "12 0.987358760495 0.695492327125 1.0 [ 1.]\n",
      "74 0.866475955985 0.6472912176 1.0 [ 1.]\n",
      "11 0.239075832595 0.37766247145 1.0 [ 1.]\n",
      "12 0.987358760495 0.695492327125 1.0 [ 1.]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7f5d968e8090>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA+gAAANDCAYAAAA+eDXJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSZJSwIIuSZIkSVIK/D/Vw982yLbx9wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5d964fc6d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "w = perceptron(xn, yn)\n",
    "\n",
    "# Using weights w to compute a,b for a line y=a*x+b\n",
    "bnew = -w[0]/w[2];\n",
    "anew = -w[1]/w[2];\n",
    "y = lambda x: anew * x + bnew;\n",
    "\n",
    "# Computing the colors for the points\n",
    "sep_color = (yn+1)/2.0;\n",
    "\n",
    "pl.figure();\n",
    "figa = pl.gca()\n",
    "\n",
    "pl.scatter(xn[:,0],xn[:,1],c=sep_color, s=30)\n",
    "pl.plot(x,y(x),'b--',label='Line from perceptron implementation.')\n",
    "pl.plot(x,f(x),'r',label='Original line.')\n",
    "pl.legend()\n",
    "\n",
    "pl.title('Comparison between the linear separator and the perceptron approximation.')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Not bad, right? The algorithm should have managed to converge to a good approximation of the separating line. If it didn't, try running the last piece of code again. Remember that this implementation updates randomly picked points, so in some cases convergence will be worse.\n",
    "\n",
    "Also, note that the line that separates the points is not unique, given the dataset we have available. Would it be so if we had all of the possible information? My guess is that this depends on the data. \n",
    "\n",
    "In any case, it can be proven that this process works every time, given a sufficient number of steps. This assumes that the data is linearly separable, a fact that is quite powerful on its own. We may be good at finding patterns in $\\mathbb{R}^2$ but what about $\\mathbb{R}^d$? Is there a way to show that a collection of points can be separated by \"inserting\" planes between them? We take a look at that next."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# What if the dataset is not linearly separable?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If the data is not separable by a line, then, in most cases, this process will not work perfectly. Some points will be classified correctly and some will not. Then, we can think about two more questions. \n",
    "\n",
    "1. How much will it cost us if we missclassify a point? Is the cost an extra spam e-mail in our inbox or is it a patient not getting the correct medicine?\n",
    "2. If we don't want to take the risk with a line, which is the best curve to use instead?\n",
    "\n",
    "We are not going to answer those here. Instead, I will just show you an example where the classification can fail, if the points are not separable by a line. Then, if you download this notebook, you can try with other curves and see what happens. \n",
    "\n",
    "Remember that, in our case, given a point $x=(x_1,x_2)$, classification is done according to $\\text{sign}(f(x_1)-x_2)$, which can either be -1 or 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA7YAAAMvCAYAAADmk0wTAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6b1231d3d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Change this function to select points with respect to a different curve.\n",
    "f = lambda x: x**2;\n",
    "\n",
    "x = np.linspace(0,1);\n",
    "\n",
    "# Generate some data points to play with.\n",
    "N = 100\n",
    "xn = nr.rand(N,2)\n",
    "\n",
    "fig = pl.figure()\n",
    "figa = pl.gca();\n",
    "\n",
    "# Plot classifier \n",
    "pl.plot(x,f(x),'r')\n",
    "\n",
    "# Classify based on f(x)\n",
    "yn = np.sign(f(xn[:,0])-xn[:,1])\n",
    "\n",
    "colors = (yn+1)/2.0;\n",
    "\n",
    "pl.scatter(xn[:,0],xn[:,1],c=colors,s=30);\n",
    "pl.title('Classification based on f(x)')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this example, we can see that $x^2$ colours some points as black and others as white. Let us find a linear separator now."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f6b106f0f10>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA+gAAANDCAYAAAA+eDXJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6b12acaed0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Try percepton with that data.\n",
    "w = perceptron(xn, yn, max_iter=1000)\n",
    "\n",
    "# Re-scale the weights to construct a new representation\n",
    "bnew = -w[0]/w[2];\n",
    "anew = -w[1]/w[2];\n",
    "y = lambda x: anew * x + bnew;\n",
    "\n",
    "figa = pl.gca()\n",
    "pl.scatter(xn[:,0],xn[:,1],c=colors,s=50);\n",
    "pl.title('Classification based on f(x)')\n",
    "\n",
    "pl.plot(x,f(x),'r',label='Separating curve.')\n",
    "pl.plot(x,y(x),'b--',label = 'Curve from perceptron algorithm.')\n",
    "\n",
    "pl.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this case, our classifier cannot get all the cases right (white points should be above the blue line, black points below). This situation will probably become worse as we add more and more points. "
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}