27_RF_Feature_Extraction_Rewrite_KSTest_Final_Class3.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Filter analysis of Convolutional Layers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook investigates features were learned by filters in the convolutional layers in a conv. network. Especially we are interested in the features learned by filters that show a higher average activity for inputs of a certain class. In this case the network was trained on 128 electrode EEG data to discriminate between 4 classes (right hand, left hand, rest, right foot).\n",
    "\n",
    "To find the fiters of interest the data it was trained on (1720 trials / 430 per class) was run through the network and the average activity over all units in a filter over all inputs for a certain class was recorded. The mean activity of the filters regarding a single class was then compared with the average activity for the remaining classes to find the on average most active filters for a certain class.\n",
    "\n",
    "The 200 trials that invoked the highest response in a unit of a filter (top 46% of class trials) were determined and the signal window that was responsible for activity in that unit (receptive field of the unit on the total input) was recorded. Several features are then extracted from those windows and their distribution is compared to a baseline of (randomly) sampled control inputs also belonging to one of the 4 classes.\n",
    "\n",
    "The deeper the layer in the convolutional network, the bigger the receptive field of its units and more complex characteristic features are expected.\n",
    "\n",
    "<b>In this notebook class 3 (right foot) is compared to the other classes</b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "cl = 3\n",
    "max_baseline_inputs = 5000 # Number of signal windows used for baseline\n",
    "wins_per_input = 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using gpu device 0: GeForce GTX TITAN Black (CNMeM is disabled, cuDNN 5005)\n",
      "/home/hartmank/braindecode/vienv/local/lib/python2.7/site-packages/sklearn/cross_validation.py:44: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. Also note that the interface of the new CV iterators are different from that of this module. This module will be removed in 0.20.\n",
      "  \"This module will be removed in 0.20.\", DeprecationWarning)\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import scipy\n",
    "import random\n",
    "\n",
    "import logging\n",
    "log = logging.getLogger()\n",
    "log.setLevel(\"DEBUG\")\n",
    "from braindecode.scripts.train_experiments import setup_logging\n",
    "setup_logging()\n",
    "\n",
    "import sys\n",
    "sys.path.append(\"/home/hartmank/braindecode/convvisual\")\n",
    "\n",
    "from braindecode.veganlasagne.layer_util import print_layers\n",
    "\n",
    "import os\n",
    "from numpy.random import RandomState\n",
    "\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import receptive_field\n",
    "import analysis\n",
    "import utils"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "modelpath = '/home/hartmank/braindecode/data/models/'\n",
    "modelname = 'paper/ours/cnt/deep4/car/22'\n",
    "savepath  = '/home/hartmank/data/convvisual/RF_data/'\n",
    "RF_save = receptive_field.ReceptiveFieldInputsIO()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "rng = RandomState(98787)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Plotting functions\n",
    "def cut_input_data(RF_data,filt,separated_channels=True,use_class_start_samples=False):\n",
    "    reshape_channels = n_chans\n",
    "    if separated_channels:\n",
    "        reshape_channels = 1\n",
    "    \n",
    "    max_units_in_filters = np.asarray(RF_data.results[cl].max_units_in_filters)\n",
    "    filt_input_indeces = max_units_in_filters[:,1]==filt\n",
    "    max_units_in_filters = max_units_in_filters[filt_input_indeces]\n",
    "    \n",
    "    X_RF_cropped = utils.get_cropped_RF(RF_data.results[cl].RF_X[filt_input_indeces].squeeze(),([0],reshape_channels,-1))\n",
    "    window_indeces = np.unique(max_units_in_filters[:,2])\n",
    "    \n",
    "    classes = RF_data.classes\n",
    "    neg_classes = np.delete(classes,cl)\n",
    "    inputs_baseline = np.array([])\n",
    "    for c in neg_classes:\n",
    "        inputs_baseline = np.vstack([inputs_baseline,RF_data.results[c].inputs]) if inputs_baseline.size else RF_data.results[c].inputs\n",
    "        \n",
    "    print inputs_baseline.shape\n",
    "    if use_class_start_samples:\n",
    "        X_baseline = utils.cut_ind_windows(inputs_baseline,X_RF_cropped.shape[2],window_indeces,wins_per_input=wins_per_input).squeeze()\n",
    "    else:\n",
    "        X_baseline = utils.cut_rand_windows(inputs_baseline,X_RF_cropped.shape[2],wins_per_input).squeeze()\n",
    "    \n",
    "    if separated_channels:\n",
    "        X_baseline = X_baseline.reshape((-1,X_RF_cropped.shape[1],X_RF_cropped.shape[2]))\n",
    "    print X_baseline.shape\n",
    "    indx = rng.permutation(len(X_baseline))[:max_baseline_inputs]\n",
    "    X_baseline = X_baseline[indx]\n",
    "    \n",
    "    return X_RF_cropped,X_baseline \n",
    "    \n",
    "\n",
    "def plot_max_filters(RF_data):\n",
    "    print 'Max filters: ',RF_data.results[cl].max_filters\n",
    "    plt.figure()\n",
    "    sns.heatmap(np.reshape(RF_data.results[cl].filters_means,(-1,1)).T,\n",
    "                linewidths=.5)\n",
    "    plt.xlabel('Filter #')\n",
    "    plt.ylabel('Activation Diff')\n",
    "    plt.title('Mean activation for feature maps over all inputs')\n",
    "    plt.show()\n",
    "    \n",
    "    \n",
    "def print_features(score,p,labels,indeces):\n",
    "    for idx in indeces:\n",
    "        print 'Score %f  p %f  : %s'%(score[idx],p[idx],labels[idx])\n",
    "        \n",
    "        \n",
    "def plot_RF_starts(RF_data,win_size):\n",
    "    plt.figure()\n",
    "    max_units_in_filters = np.asarray(RF_data.results[cl].max_units_in_filters)\n",
    "    max_units_in_filters = max_units_in_filters[max_units_in_filters[:,1]==filt]\n",
    "    sns.distplot(max_units_in_filters[:,2],bins=np.arange(0,RF_data.results[cl].inputs.shape[2],20),kde=False)\n",
    "    plt.xlim([1,RF_data.results[cl].inputs.shape[2]-win_size])\n",
    "    plt.xlabel('Sample #')\n",
    "    plt.ylabel('Number of receptive fields starting at sample')\n",
    "    plt.title('Starting of the RF windows in complete input signal')\n",
    "    plt.show()\n",
    "    \n",
    "    \n",
    "def plot_channels(RF_data,sensor_names):\n",
    "    max_units_in_filters = np.asarray(RF_data.results[cl].max_units_in_filters)\n",
    "    max_units_in_filters = max_units_in_filters[max_units_in_filters[:,1]==filt]\n",
    "    chan_counts = np.bincount(max_units_in_filters[:,3])\n",
    "    max_chan = chan_counts.argmax()\n",
    "    max_name = sensor_names[max_chan]\n",
    "    plt.figure(figsize=(10, 10))\n",
    "    sns.distplot(max_units_in_filters[:,3],bins=np.arange(n_chans),kde=False)\n",
    "    plt.xlim([0,n_chans])\n",
    "    plt.ylabel('Number of times signal window originated in channel')\n",
    "    plt.xlabel('Channel')\n",
    "    plt.title('Channels that provided maximized input %s: %d'%(max_name,chan_counts[max_chan]))\n",
    "    plt.xticks(range(1,len(sensor_names)+1),sensor_names,rotation=90,fontsize=5)\n",
    "    plt.show()\n",
    "        \n",
    "        \n",
    "def plot_channel_avg(X_RF_cropped,channel,title=''):\n",
    "    plt.figure()\n",
    "    sns.tsplot(data=X_RF_cropped[:,channel],err_style=\"unit_points\")\n",
    "    m = X_RF_cropped[:,channel].mean(axis=0)\n",
    "    s = X_RF_cropped[:,channel].std(axis=0)\n",
    "    plt.fill_between(np.arange(X_RF_cropped.shape[2]),m-s,m+s,color='r',zorder=100,alpha=0.3) \n",
    "    plt.plot(np.arange(X_RF_cropped.shape[2]),m,color='r',zorder=101) \n",
    "    plt.xlabel('Sample # (250Hz)')\n",
    "    plt.ylabel('Amplitude')\n",
    "    plt.title(title)\n",
    "    plt.show()\n",
    "    \n",
    "\n",
    "def plot_channel_avg_comparison(X1,X2,channel):\n",
    "    plt.figure()\n",
    "    #sns.tsplot(data=X_RF_cropped[:,channel],err_style=\"unit_traces\")\n",
    "    sns.tsplot(data=X1[:,channel],err_style=\"unit_traces\")\n",
    "    sns.tsplot(data=X2[:,channel],err_style=\"unit_traces\")\n",
    "    plt.show()\n",
    "    \n",
    "    \n",
    "def plot_dist_comparison(features,features_base,idx):\n",
    "    sns.distplot(features[:,idx],label='Input')\n",
    "    sns.distplot(features_base[:,idx],label='Baseline')\n",
    "    plt.legend()\n",
    "    plt.xlabel(labels[idx])\n",
    "    plt.show()\n",
    "    \n",
    "    \n",
    "def subplots_4_features(features,features_base,indeces):\n",
    "    plt.figure()\n",
    "    plt.subplot(221)\n",
    "    plot_dist_comparison(features,features_base,indeces[0])\n",
    "    plt.subplot(222)\n",
    "    plot_dist_comparison(features,features_base,indeces[1])\n",
    "    plt.subplot(223)\n",
    "    plot_dist_comparison(features,features_base,indeces[2])\n",
    "    plt.subplot(224)\n",
    "    plot_dist_comparison(features,features_base,indeces[3])\n",
    "    \n",
    "    \n",
    "def plot_phaselocks(phaselocks,sensor_names):\n",
    "    plt.figure(figsize=(30, 30))\n",
    "    sns.heatmap(phaselocks,xticklabels=sensor_names,yticklabels=sensor_names)\n",
    "    plt.plot([0, len(sensor_names)],[len(sensor_names), 0])\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Layer 03"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Analysis of filters in Layer 03"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "filename = 'Layer03_nUnits200_nFilters05_filterdiff_traindata.data'\n",
    "RF_data_03 = RF_save.load(os.path.join(savepath,modelname,filename))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Filter activation\n",
    "Mean activation for each filter in the Layer over all units and inputs of a specific class minus the mean activitaction for the remaining classes.\n",
    "\n",
    "Activation matrix of size $Filters \\times Units \\times Inputs \\xrightarrow[]{average} Filters$\n",
    "\n",
    "Max filters are the filters with the highest difference of average activation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Max filters:  [13 20 22  2 18]\n"
     ]
    },
    {
     "data": {
      "image/png": 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3euV5teNKP9cry6/v3Kxdu1YvvfSSJk+erKpVqxb49ddDBhcAAMDOo4A3hbmT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\niIiISFZY4BIRERGRrPwf/1twT0gt208AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84a3ad6f90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_max_filters(RF_data_03)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>Filter to look at</b> (index in Max filters)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "filt = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1342, 128, 1000, 1)\n",
      "(515328, 1, 10)\n",
      "(200, 1, 5) (200, 1) (200, 1, 1) (200, 1)\n",
      "(5000, 1, 5) (5000, 1) (5000, 1, 1) (5000, 1)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "utils.py:92: VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n",
      "  tmp = inputs[i,:,ind_start[i,j]:ind_end[i,j]]\n"
     ]
    }
   ],
   "source": [
    "n_chans = RF_data_03.results[cl].n_chans\n",
    "sampling_rate = RF_data_03.results[cl].sampling_rate\n",
    "sensor_names = RF_data_03.results[cl].sensor_names\n",
    "\n",
    "X_RF_cropped,X_baseline = cut_input_data(RF_data_03,filt,separated_channels=True)\n",
    "frequencies = scipy.fftpack.fftfreq(X_baseline.shape[2], 1./sampling_rate)\n",
    "frequencies = frequencies[:frequencies.shape[0]/2].astype(str)\n",
    "\n",
    "sensor_names_one_chan = ['N/A' for entry in sensor_names]\n",
    "feat_mean_diff,feat_p,index_labels,features_class,features_base = utils.extract_features_and_diff(X_RF_cropped,X_baseline,sampling_rate)\n",
    "sort_mean_diff = feat_mean_diff.argsort()[::-1]\n",
    "labels = utils.make_labels_from_index_labels(index_labels.tolist(),\n",
    "                                    {'FFT':[sensor_names_one_chan,frequencies],\n",
    "                                    'FFTc':[sensor_names_one_chan,frequencies],\n",
    "                                    'Phase':[sensor_names_one_chan,frequencies[1:]],\n",
    "                                    'Phasec':[sensor_names_one_chan,frequencies[1:]],\n",
    "                                    'Mean':[sensor_names_one_chan],\n",
    "                                    'Meanc':[sensor_names_one_chan],\n",
    "                                    'Bandpower':[sensor_names_one_chan]})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(200, 1, 10)\n"
     ]
    }
   ],
   "source": [
    "print X_RF_cropped.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Receptive field starting sample\n",
    "Sample at which the receptive field started in the original input.  \n",
    "The original input window has a length of 4 seconds containing 1000 samples (250 Hz).  \n",
    "Interesting to see if the maximizing signal windows for that filter are evenly distributed over the whole trial or e.g. accumulate in the middle of the trial."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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RERERWQQGUyIiIiKyCAymRERERGQRGEyJiIiIyCIwmBIRERGRRWAwJSIiIiKL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\nFAAAAI5AMAUAAIAj/D9rZLoNgmYWLwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84a3a04ed0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_RF_starts(RF_data_03,X_baseline.shape[2])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Channels of the Receptive Field\n",
    "In Layer 03 the receptive field is still channel specific. Therefore it could be interesting to see from which channel the most maximizing signal windows originate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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atWununXrqlChQhmRDQAAAACcmt2FavHixfL395erq903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\n5vf+ThUAAAAA3EyKHKgWLVpUnH0AAAAAgMexfNt0AAAAALj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s97915coV08+5ke3bt9+w\nnt/TyZMntXbtWmM72rp1q+lp8HeonJg2bZoGDhwoSVq9erXatm0rSdq4caOioqI0Z84c/fe//1Xr\n1q3VqlUrTZ06VYMHD5Ykbd68WTt37jQO3KKjoyVJBw8e1J49e5Q/yzt16qR33nlHf/vb3xQQEFBg\n+klJSdq6datat26t999/Xw899JCaN28uSWrXrp0GDx6sli1batasWYqOji5wkPjFF1+oXbt28vLy\n0pEjR/Sf//xHDzzwgD755BNFRUXpT3/6kyRpzpw5OnjwoCTJZrNp0qRJTudDYa/X2Xj+9re/6Zln\nntHDDz9cYJyffvqpypcvr88//1ylS5dWvXr11K1bN7399ts6cOCAGjVqpJ07d6pixYr6v//7P5ct\nm08//VSS5HA49N1336lly5bq3LmzPvzwQ1WrVk3Lly+Xl5eXGjRooF69eumjjz7Svn37VLt2bSUn\nJ6tq1arq16+f02UpSa+88oruuusu2Ww22Ww2DRgwwFgHHnzwQeM1dOnSxfjZ2XNcVb9Rr5MnT5bd\nbtepU6dUrlw5BQUF6ZVXXlGXLl3UokULdevWTeXLl/e4ZTZx4kTl5OQoOztb1apV0/HjxzV69Gi9\n8847Onr0qMLCwpSenq7w8HD17t270GVZ2DJzts6PHz9e6enp19WdDe+qurNena0T11qzZo3i4+P1\nwgsvqF69etc9vnfvXlWoUEELFy5Udna2unXrpjvvvLPQfdRvx9+6dWtJN953/fTTT9q+fbs6deqk\nkJAQffvtt2rTpo3Tfdr+/ftVrlw5LVy4UFlZWerSpYvCw8P11VdfaevWrYqKitL69esVERGhbt26\nOR2/JMXHx2vr1q3Gso+Liyt0vlmZz67Yjm/Up7P3DkmaOHGiAgICVK1aNQUHB2vDhg2KjY3Vq6++\nqrp162r79u164okn9OWXX2r69Ok6duyY8VyHw6E5c+Zo/PjxkqR+/fpp1KhRqly5subNm6e+fftq\n6NChqlu3rlJTU/Xaa69pwoQJeu2119SrVy9VqFBBDodD+/fvV+3atTVp0iTFxsaqbNmyqlChggIC\nAvTDDz9o4sSJhb4/mZ3Xzra9YcOGGa+rKNuqs7rZ5zjr01k/o0eP1t13360DBw6oevXqSklJ0YgR\nI/Tss8+qTp06at++verWretxy1iSxowZo0qVKikpKUlt2rTRli1bFBsbq8mTJ6tUqVIqX768Tpw4\nIbvdbuk46rfy9zmFbftm9vvfffedPvvsMzkcDgUGBqpHjx5q2LChoqOjb7jf/Pbbb1WxYkUtXrxY\nvr6++stf/qLWrVtr2bJl2rx5sx599FGtXr1aderU0fPPPy9J6tatmyIjIxUdHa1//vOfio6OVkJC\ngjHOL7/8Uo899pgiIyP1xRdf6Pbbb9d7770nSWrdurXatWvndB+YlJSkjz76SDk5OQoKClLXrl1V\nu3Ztp6+3sLrkfBt0tm7ni4uL02uvvSZJmj9/vp577jl5e3sbry1/mPPnz6thw4bq2rVrgeeYeV+8\ndt5J0pIlSzRjxgxJ0pNPPqnY2Fjde++9xvvQkCFD9Oijj+qHH35QTEyM3nzzTWO6ReVjauib2PPP\nP6+wsDBJV1eGn376yTgA/Oyzz7R161YNHjxYu3btUlRUlM6dO6e4uDh99NFH2rRpU4HkvXLlSvXr\n1082m63ANGbOnKmnnnqqQP3QoUOaM2eOypYtq7Zt26pixYqSpAULFqhXr14aOXKkpk2bpvHjxxsH\nK23bttX58+f11ltvGeNp0aKFmjVrJj8/PyUnJ2vTpk2Ki4vT4sWL1aFDB73xxht64403NHfuXOMN\nKzMzU5MnTy7SfCjs9d5oPJJUr149hYWFGTvqu+++W61bt9bBgwd18OBBTZ06VZKMnXpaWpqmTZum\nV199VW+99ZbGjh3r0mWzfft2Va1aVc2aNVNoaKjuvPNOSdIvv/yitLQ0TZ8+XZI0YcIESVc/oXnj\njTcUGxurMWPGaObMmYUuy/zXnL+DvFb9+vUL7JCK8py6devqhRdeKPLwzuo36tXb21tDhw7VjBkz\n1L9/f2NeN27cWD179tTixYv1yy+/KDAwUDExMR6zzEJDQ9WvXz9NmDBBzz//vGbNmiVJysjIMHq7\ndnhn80cqfJk5W+dDQkIUExNT5OFdVXfW643WofyQKl1dNl999ZVq1aqlgwcPavny5brvvvtUs2ZN\n1alTR9LV/VleXp569eqloKAgTZw4UePGjXO6j7rR+PMDVf6+a/r06caBzKJFi/Tss89q6tSpGjRo\nkLZv3642bdo43actWbJEpUuXVteuXRUQEKApU6Zo0qRJ2rdvn0aOHKmYmBjFxcUZ64az8UvSnj17\nFBsb+4e3Y2fDO1sGhT3nRvUb9ensvSNfXl6ennjiCUkyDi7KlCmjPn36yMfHR4888oh27twpSRo0\naFCBg6dDhw4ZP4eHh2vhwoVq0qSJcZa4TJkyevbZZ3Xw4EG9+eabxrLs06ePtm/frr///e9auHCh\ncRDs5+cnf39/PfXUU5J+/fS3sPcns/Pa2bZXo0YNvfjii0Ue3lnd7HOc9emsn4CAAP3tb3/TtGnT\n1KtXL73++uuSpIiICA0ePFgrVqzQkiVLlJeXZ+y/PGEZ54+rb9++GjVqlNq1a2cc/DocDvXv398Y\nLv8DDcnccZSzfU5h276Z/f6///1vzZo1S7NmzdKLL76okSNHqmHDhrr99ttvuN/cuXOn8vLyNHHi\nRNlsNsXGxqp169ZKTEzU5MmT9dJLL2nOnDl64403jGlERUWpbdu2GjFihNHTnDlzVL9+fd11111K\nS0szzuLt2bNH+/bt07Rp0yRJb7zxhtq1a+d0H7h06VKNGjVKfn5+yszMVGxsrDGvnW1nVo5Zfrtu\nd+3a1XjPzj8OyPfTTz9p5MiRio6OLrAu+vj4KC4uTt9++61WrlxZYPxm3hfnzZunDh06GOvtpUuX\njMcefPBB/fvf/y5whjUoKEitW7dW/fr1NWnSJONKFzMIVP/fAw88UOBNKf+AUZIaNmyobt26acKE\nCcap6vPnz+vw4cPq0aOHFixYYJwSPXr0qCpUqKDs7GyVLl3aGIfdble9evXUsGHDAvUyZcpo0KBB\nOnLkiJYtW6aUlBRNmDBBPj4+qlOnjp577jmVKVNG/v7+xnOqVaumTp066cCBAxo9erQkacWKFXr/\n/ff18MMP64cffjB2cjabTVWrVpXNZtNtt90mH5+rizx/Wh9++KFKlSolSercubPT+eDs9TobT76m\nTZuqadOmSk1NVXJysiTpP//5j3x8fHTy5EldvHhRp06dknT1oPfw4cMaNWqUjh07posXLxrjaN++\n/XU95eTk3HDZ5I/nt72OGTNG33//vbZt26bbbrtNTZo0kSSVLl1ahw8f1ttvv218siJJKSkpmjdv\nnlJSUvT5558blyw4W5ZDhw7V2bNntWfPHqM+adIkDR06VFlZWRowYIAxj/I/WSnsOWfPnlVSUtIN\n686G/23dWa9eXl4aPXq0GjZsqMTERJUtW9Z4LCwszFh/zp8/X+gyu3jx4g2Xmau2pwkTJmjNmjXa\nunVrgWUWEhKiffv2XbfMzp07p1dffVW33XabRo4cKS8vL2OZvf322ypXrpxOnz4tb2/v312W+cvM\nz8+vwKdhztb5t956S4mJiZo4caIxrgEDBjgd3lV1Z+uXs3Vo48aN6tq1qzEPAgMDJV39hLZDhw7a\nvn27tmzZYgSqCxcuqHTp0ipXrpx8fHyMSyKc7aOcjX/79u2y2Wzq1KmTPvjgAyOIe3l56a677tLQ\noUM1efJk443P2T7N29tblSpVUqlSpZSbm2ss45MnT2r16tU6ceKEduzYYayjzsafkJCgvLw8bdy4\n0ZhvkZGRprdjZ8Pnr0d/dDt+4oknbtins/cOSTp8+LC8vb2VkpKi//73v8b2HR4ersTERPXq1Us/\n/vijypUrJ0mKiYlRlSpVjO312rPTAQEBevnllxUfH6+vv/5a0dHRuuuuu5SYmKh69erpscceMw7O\noqKi1LBhQ82fP7/AJVytWrXSqlWr9PzzzxsBUHL+/mR2Xjvb9oYOHaojR44oOTm5SMM7q0sy9ZyU\nlBSny/dG/UhX97tt27bV//3f/xnzVpKCg4O1fv16dezYscAB7r59+5SYmKj27dvrxIkTxjIuX768\n5s+fr2eeeabAMn7ttdeUkpKiRx99VH5+fsYyPnPmjAICAtS3b199+eWXxjIuV66cMZ5rl3GdOnV0\n5swZ/fOf/zTOyuUv45EjR2rDhg2qXLmysYylq2Grbt26GjBggKKjo1W9enXjtb3++usKCwtTRkaG\n7rjjDknmj6Oc7XOcbfuF7fezs7OvW+8yMzOVkJCgnJwcHT9+3Hifk26839y/f7/8/PyUkZGhrKws\n47L6/PfO4cOH6+zZs8Zlm5J0//33Kzw8XKNGjdLbb78tSXr//fe1ZMkSXb58WbVr1zbOovn4+Oji\nxYuKj4+Xw+EwLm13tg/MycnR2bNnddtttyktLc0IGYVtZ1aOWX67bnfv3l3NmjWTr6+vypYtqylT\nphivt3r16uratavefffdApeWZmdnKzk5WX/605+0ceNGbdq0SZLz911n9VatWkmSKlWqJOnXM2wJ\nCQkqW7aswsPDZbfb9dFHHyk6OlqRkZFasGCBIiIiVL9+fb355pvG8XVRccmfE5cvXzYupdi/f79q\n1aolh8Ohjz/+WN26dTMuK8rfcA8fPqwaNWoYn4hfKzo6+oanDuPi4oxLWX5r586dCg4OVs2aNbV7\n925lZGSoRYsWio+PV6dOnQqcur7W559/rt27d2vEiBGSpA0bNmjDhg169NFHtXj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6NPnz7Nv3AWBCVUCmOqB8lS2mmuOC0J0dhbcnUlY5ny24Q4GXnacACWNJix3LG3CB2iMZAMfUzS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\nhBIqgiAIgiAIgiAIE/l/8i7eP3EQbAYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84532d4250>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_channels(RF_data_03,sensor_names)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Most differentiating Features\n",
    "Features that are most distinct between the maximizing signal windows and baseline windows of the same size that were randomly sampled from inputs of the 3 other classes, but <b>starting at the same time samples during the trials</b> as the maximizing windows. This is done to get a better baseline for filters that appear to be time specific.\n",
    "\n",
    "There are no channel specific features in L03, because the features are extracted for the one channel in the receptive field.\n",
    "\n",
    "<b>Score is calculated by</b> the Kolmogorov–Smirnov test\n",
    "https://en.wikipedia.org/wiki/Kolmogorov%E2%80%93Smirnov_test  \n",
    "<b>0</b>: Complete overlap of distributions <b>1</b>: No overlap\n",
    "\n",
    "Labels show type of feature and corresponding Hz or Channel name  \n",
    "<b>FFT</b>: Frequency Amplitude in Channel  \n",
    "<b>FFTc</b>: Change of Frequency Amplitude in Channel between first and second half of input window  \n",
    "<b>Phase</b>: Phase of frequency in Channel  \n",
    "<b>Phasec</b>: Change of Phase  \n",
    "<b>Mean</b>: Mean of signal amplitude over complete RF  \n",
    "<b>Meanc</b>: Change of mean from first to second half of input window  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Score 0.997800  p 0.000000  : Bandpower N/A\n",
      "Score 0.981000  p 0.000000  : FFT N/A 75.0\n",
      "Score 0.979000  p 0.000000  : FFT N/A 50.0\n",
      "Score 0.970800  p 0.000000  : FFT N/A 100.0\n",
      "Score 0.857400  p 0.000000  : FFT N/A 25.0\n",
      "Score 0.689800  p 0.000000  : FFTc N/A 25.0\n",
      "Score 0.661800  p 0.000000  : Meanc N/A\n",
      "Score 0.580200  p 0.000000  : Phase N/A 75.0\n",
      "Score 0.542000  p 0.000000  : Phase N/A 25.0\n",
      "Score 0.455400  p 0.000000  : Phase N/A 100.0\n",
      "Score 0.431400  p 0.000000  : Phase N/A 50.0\n",
      "Score 0.202200  p 0.000000  : Phasec N/A 25.0\n",
      "Score 0.147800  p 0.000384  : FFT N/A 0.0\n",
      "Score 0.147400  p 0.000402  : Mean N/A\n",
      "Score 0.137600  p 0.001202  : FFTc N/A 0.0\n"
     ]
    }
   ],
   "source": [
    "print_features(feat_mean_diff,feat_p,labels,sort_mean_diff[:20])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Feature distributions\n",
    "Distributions of the 5 highest scoring features for maximizing and baseline signal windows.\n",
    "Blue shows the maximizing and green the baseline windows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(200, 15) (5000, 15)\n"
     ]
    },
    {
     "data": {
      "image/png": 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1ZrdbqIoEd23fqUqtosbmOyG/KXvfvfzyi7z66jzAsxtonz7pzJv3Ol26dOWxxx7nX/96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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84a3a046d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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FbNq0qce2O3bsYMmSJcybN4+77rqL0tLSTu+/9tpr3HLLLcyZM4elS5eyb9++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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f846364f050>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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q91BZ1YDZOHALSgfLc+8rUT2xmTNnUllZidPpjIQMDh48yNSpUzt4oTNnzuTw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\naBmGYSSGAy3DMIzEcKBlGIaRmP8B0pHH1BHWi9QAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f8447e18e50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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oLQEZrT6GeEvfBzvR/v6Fg5CE1mazUV9f36msoaEBSZJITEzsU93JkycDkJSU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\nSHgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f8442a02990>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print features_class.shape,features_base.shape\n",
    "subplots_4_features(features_class,features_base,sort_mean_diff[:4])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>Plots to investigate a specific feature</b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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qsMBmsCKajmEoPoI6EydeEdHcw8BKRNN2vDuIH75wCAP+OADAZTfif39mOS48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wt7bYCvXr2KpqYmuLq6asV//PFHLFq0CH5+fjhy5Aja2tp6nOfx48eIjo6Gu7s7ZDIZxo4diwUL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\nSkRERER67X8HyywpJcfn3AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84a3a6d510>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_dist_comparison(features_class,features_base,sort_mean_diff[5])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Average signal window\n",
    "Average of the 20 maximizing signal windows and baseline windows.  \n",
    "The red curve is the average with 1 std confidence interval. Blue dots are the original values at that time sample."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[['Bandpower', [0]] ['FFT', [0, 3]] ['FFT', [0, 2]] ['FFT', [0, 4]]\n",
      " ['FFT', [0, 1]] ['FFTc', [0, 1]] ['Meanc', [0]] ['Phase', [0, 2]]\n",
      " ['Phase', [0, 0]] ['Phase', [0, 3]]]\n"
     ]
    }
   ],
   "source": [
    "print index_labels[sort_mean_diff[:10]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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DkpISPPnkk7jllluC98nMzMSqVavwzDPP4Hvf+x7cbjeGDRuGZ555JuyqRL9+/VBYWIgj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\nIhJ2lASLiIiISNj5f9ExvuO/t0vsAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f8447ea23d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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fj4ceemjEzRCIiCaTCdEm+B//+AeWL1+OK6+8MmfdCy+8gFNOOQVHHHEEvvjFL2Lt2rVZ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\nsBxCMAAAACyHEAwAAADL+X93NXryLyfwAAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f8442721b10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_channel_avg(X_RF_cropped,0,'Maximizing input windows')\n",
    "plot_channel_avg(X_baseline,0,'Baseline input windows')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Layer 04"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Analysis of filters in Layer 04"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "del RF_data_03"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "filename = 'Layer04_nUnits200_nFilters05_filterdiff_traindata.data'\n",
    "RF_data_04 = RF_save.load(os.path.join(savepath,modelname,filename))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Filter activation\n",
    "Mean activation for each filter in the Layer over all units and inputs of a specific class minus the mean activitaction for the remaining classes.\n",
    "\n",
    "Activation matrix of size $Filters \\times Units \\times Inputs \\xrightarrow[]{average} Filters$\n",
    "\n",
    "Max filters are the filters with the highest difference of average activation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Max filters:  [10  4 22 11 19]\n"
     ]
    },
    {
     "data": {
      "image/png": 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RRAIAALj48Ik1ljGdDQAAANuoRAIAALg4WFhjGSMFAAAA26hEAgAAuPiwsMYy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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f842c833cd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_max_filters(RF_data_04)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>Filter to look at</b> (index in Max filters)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "filt = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1342, 128, 1000, 1)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/hartmank/braindecode/convvisual/utils.py:92: VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n",
      "  tmp = inputs[i,:,ind_start[i,j]:ind_end[i,j]]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(4026, 128, 10)\n",
      "(200, 128, 5) (200, 128) (200, 128, 1) (200, 128)\n",
      "(4026, 128, 5) (4026, 128) (4026, 128, 1) (4026, 128)\n"
     ]
    }
   ],
   "source": [
    "n_chans = RF_data_04.results[cl].n_chans\n",
    "sampling_rate = RF_data_04.results[cl].sampling_rate\n",
    "sensor_names = RF_data_04.results[cl].sensor_names\n",
    "\n",
    "X_RF_cropped,X_baseline = cut_input_data(RF_data_04,filt,separated_channels=False)\n",
    "frequencies = scipy.fftpack.fftfreq(X_baseline.shape[2], 1./sampling_rate)\n",
    "frequencies = frequencies[:frequencies.shape[0]/2].astype(str)\n",
    "\n",
    "feat_mean_diff,feat_p,index_labels,features_class,features_base = utils.extract_features_and_diff(X_RF_cropped,X_baseline,sampling_rate)\n",
    "sort_mean_diff = feat_mean_diff.argsort()[::-1]\n",
    "labels = utils.make_labels_from_index_labels(index_labels.tolist(),\n",
    "                                    {'FFT':[sensor_names,frequencies],\n",
    "                                    'FFTc':[sensor_names,frequencies],\n",
    "                                    'Phase':[sensor_names,frequencies[1:]],\n",
    "                                    'Phasec':[sensor_names,frequencies[1:]],\n",
    "                                    'Mean':[sensor_names],\n",
    "                                    'Meanc':[sensor_names],\n",
    "                                    'Bandpower':[sensor_names]})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Receptive field starting sample\n",
    "Sample at which the receptive field started in the original input.  \n",
    "The original input window has a length of 4 seconds containing 1000 samples (250 Hz).  \n",
    "Interesting to see if the maximizing signal windows for that filter are evenly distributed over the whole trial or e.g. accumulate in the middle of the trial."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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dcZdBREREpRDPwRIRERFRqcDgSkRERESlAoMrEREREZUKDK5EREREVCowuBIR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\nPFhrq31NTZ3iPbLdXpJqa/1q5UnQoUOH/++qsJ0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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f8427563090>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_RF_starts(RF_data_04,X_baseline.shape[2])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Phase locking of channels\n",
    "Phase locking of channel pairs. Phase locking is computed for class signals and baseline signals. The plot shows the difference PL_class-PL_baseline. The Phase locking value is averaged over the complete windows. So an average Phase locking for all inputs and time steps is computed.\n",
    "http://www.ncbi.nlm.nih.gov/pubmed/10619414\n",
    "\n",
    "The Phase Lock Values are computed for the band 8-15 Hz"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/hartmank/braindecode/vienv/local/lib/python2.7/site-packages/seaborn/matrix.py:143: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
      "  if xticklabels == []:\n",
      "/home/hartmank/braindecode/vienv/local/lib/python2.7/site-packages/seaborn/matrix.py:151: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
      "  if yticklabels == []:\n"
     ]
    },
    {
     "data": {
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77rrr3BNPPOH+8pe/uHfffbfKfN+PvfLKK11xcXGF6UVFRdW2Gzt37lzh/R06dKgw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\n8ikWrBARERERERERERERERERERGRT/0fzjamINpRfVgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f8447ff7a90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "phaselock_class = analysis.phase_locking_value(X_RF_cropped, sampling_rate, 100, [8, 15])\n",
    "phaselock_base = analysis.phase_locking_value(X_baseline, sampling_rate, 100, [8, 15])\n",
    "plot_phaselocks(phaselock_class-phaselock_base,sensor_names)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Most differentiating Features\n",
    "Features that are most distinct between the maximizing signal windows and baseline windows of the same size that were randomly sampled from inputs of the 3 other classes, but <b>starting at the same time samples during the trials</b> as the maximizing windows. This is done to get a better baseline for filters that appear to be time specific.\n",
    "\n",
    "<b>Score is calculated by</b> the Kolmogorov–Smirnov test\n",
    "https://en.wikipedia.org/wiki/Kolmogorov%E2%80%93Smirnov_test  \n",
    "<b>0</b>: Complete overlap of distributions <b>1</b>: No overlap\n",
    "\n",
    "Labels show type of feature and corresponding Hz or Channel name  \n",
    "<b>FFT</b>: Frequency Amplitude in Channel  \n",
    "<b>FFTc</b>: Change of Frequency Amplitude in Channel between first and second half of input window  \n",
    "<b>Phase</b>: Phase of frequency in Channel  \n",
    "<b>Phasec</b>: Change of Phase  \n",
    "<b>Mean</b>: Mean of signal amplitude over complete RF  \n",
    "<b>Meanc</b>: Change of mean from first to second half of input window  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Score 0.529121  p 0.000000  : Mean Cz\n",
      "Score 0.517956  p 0.000000  : Mean CCP1h\n",
      "Score 0.464640  p 0.000000  : Mean FCC2h\n",
      "Score 0.462047  p 0.000000  : Mean CP4\n",
      "Score 0.454352  p 0.000000  : Phase FCC2h 75.0\n",
      "Score 0.453743  p 0.000000  : Mean FC2\n",
      "Score 0.449985  p 0.000000  : Mean FCC1h\n",
      "Score 0.439918  p 0.000000  : FFT Cz 75.0\n",
      "Score 0.432350  p 0.000000  : FFT Cz 0.0\n",
      "Score 0.424913  p 0.000000  : Phase FC2 75.0\n",
      "Score 0.424545  p 0.000000  : Phase Cz 75.0\n",
      "Score 0.415132  p 0.000000  : FFT CCP1h 75.0\n",
      "Score 0.413460  p 0.000000  : FFT CCP1h 0.0\n",
      "Score 0.411371  p 0.000000  : Phase FCC1h 75.0\n",
      "Score 0.410156  p 0.000000  : Mean CCP2h\n",
      "Score 0.404426  p 0.000000  : Phase CCP1h 75.0\n",
      "Score 0.400219  p 0.000000  : Meanc Fp1\n",
      "Score 0.399419  p 0.000000  : Phase Fp1 25.0\n",
      "Score 0.389461  p 0.000000  : FFT CCP2h 75.0\n",
      "Score 0.385323  p 0.000000  : Phase CCP2h 75.0\n"
     ]
    }
   ],
   "source": [
    "print_features(feat_mean_diff,feat_p,labels,sort_mean_diff[:20])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Feature distributions\n",
    "Distributions of the 5 highest scoring features for maximizing and baseline signal windows.\n",
    "Blue shows the maximizing and green the baseline windows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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JhysLFxPz5fbfCJOQMGIizPBNEf3IMjjTPHS50+l2G/H5kp+DwKHY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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f842768ac90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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9tG5flEAkSkAJArkN7Upi01kxSJp/WfhpZzZp56PdunUry5Yto66ujp6eHj75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\neZlMtJIkSV4mE60kSZKX/T+Rc/jJ3pTlDAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f8466922490>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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I8+fPx2Kx9JOtqalJ7CpQFIXa2lpuv/12fD4fO3fu5L777mPGjBkAuN1u3G43\nc+fOTWkA0zXX/ETnuZ8MY4/FVBRF5b0m7QCCLEH+TDtxpf8Cl6qqdMY1f2yWxUnYDKEQNDYbWNL1\nBVbiKpKsogxU7nqEVFQVKT6ITBfddQb0mHUmQvEwjf7WtHxek+Fzn26600FKDoiCggKKi4vZuXMn\nPp+PU6dOUVFRwR133AFAaWkphw8fBrRU4k899RRvv/02oVCIxx9/HJPJxMqVK7Hb7bz99ts89NBD\ntLe3097ezre+9S0KCgq46qqr0j9KwSVN/QVtsSkv24bJMHDsAhUVv6LJucxO5s3R5C60GVAGMMzp\nontB7EK4dcx0CCY/KXt6d+3aRXNzM8uXL+euu+7illtuoaysDIC6ujoCAW3WsGLFCrZu3cqWLVso\nKSnh0KFD7NmzB6NR82U9/vjjAHzyk5/k4x//OPF4nJ/85CfpGpdgmhCKKHg6NVdBfs7gPtCwFCCO\nNiNymTIThjYak2m5MHYzpW5D2xIShnY6k/JiWG5uLnv27BnwvWPHjvUpr1u3jnXr1g0om5eXxw9+\n8INU1QsEfWhp7/GNzs6xDirnlzsSf7vMTqxWHbKsoigSdefi5OWmP4oXgNPYtcUr5scX9WM3jH5B\nTDD1ELEOBFOaFq9maG1mPQ6bcVA5v04ztDpJh91gR6+XyM7Urj17Pt5nR0w6yTT1bHEUkbymL8LQ\nCqYsiqomZrSzc2xDbjHsntFmmhyJPbEzsrRrOztVvO1jY2gdxl6GVsSmnbYIQyuYstS3BonENAM5\newj/LIBf1rZ2uUyZiboZrh63Q31DfAx6CEadAbNsAhDZFqYxwtAKpiwn67VDChIwK3tw/2xYCRKR\ntZiw3ae1AIxGFYddC/hS3zg2hhYgQ6f9CIgZ7fRFGFrBlOVUo2Zos51mjINs6wJoj/es+Pee0QJk\nZ0UBaGpWGKv98PauZI0N/qYx8wULJjfC0AqmJLG4wplmbV9sbtbgs1kAb+xC4u/ei1MAOS5tRhuP\ng7djbMImdhtafzRAZ9Q3JjoEkxuRnFEwJTnd2EG0yz+bN5yh7ZrRmjERCvSklQkE/JgMYXQ6O/G4\nRPMFsNsC+HyaMUxXCMUMXU+0uwZfE46s9GfeFUxuhKEVTEm6Y89KEsx0DX0W3RvXZrRKUOZUQ3ui\n/sIFHzq9Dps9Rke7gRaPEaO1E79kJRwK4pSjZDgdgzWbNHZ9zw9Bo7+ZRVkfGHWbgqmFMLSCKck7\nZ7Vwmy5hocFrAAAgAElEQVSbHsMQ4QfjaoyOuJZGxqRYsVh6dieYTFZ0RplsnURHO0SjFnQGW49M\nJJqWvuolPZkGJ95ou9h5ME0RPlrBlCMaU3i3XpuZ5jgHP6QA0BF3o3YdvdXHBpbNdPW4CAIBc5p6\n2ZdE+nGx82BaIgytYMpxqr6daFckpxmOoRewut0GAIaYaUAZq03FYNCMbcA/9oZW7DyYfghDK5hy\nHOvyz+pkCZd9GEMb0xbC9HEDOnVgT5kkgTNTM9xjPaMNxkK4Q94x0SGYvAhDK5hyHDuj+VznzbSi\n1w2d2aN7RmuO2oeUc2Zqs8xIxEC4f9zwUZNnmZn4+7yvIf0KBJOalA1tfX095eXllJSUsGrVKnbs\n2DGo7P79+yktLWXZsmWsX7+empqaAeVeeuklFi1axOuvv55qdwSTGEVRaG1tTemlKEOfGohE45yq\n1+IWvH/W0MduVVVN7KG1xIaW7Z7RArR70j//yDFlY5C1GbUwtNOPlHcdbN68maKiIqqqqmhra+Pe\ne+8lJyeHu+++u49cVVUVu3fvZu/evSxcuJB9+/ZRXl7Oiy++iNnc83gWDAb593//d6zWofdCCqYe\nbreb5w+9g93uHF4Y8PnaueHaReTk5Awq806dm2jXEa75s+y0uDsHb0/xEkOLZ2CJ2okSG1TWYgWd\nLkY8rqfdK5GRXJeTRifJzLbNoq7zHOc7haGdbqT0011dXc2JEyfYtm0bNpuNefPmsWHDBiorK/vJ\nVlZWsnbtWoqKijAajWzatAlJkqiqquoj98Mf/pCPfOQj/XKOCS4N7HYnjsyspF7JGOTqd9sA0Osk\nLps5+I+zoijUd5zqqfBKQy5CSRJYLdphBq93bDxqczJmAXCus35M2hdMXlK6o2pra8nPz8du7/F3\nFRYWcvr0afz+vrnrjx49SmFhYaIsSRIFBQVUV1cn6o4fP87TTz/N1q1bxUqsICmqT2mLW/NnO4fc\nP+vr8HImWAuATtXT5K8jEgkNKg9gsQQBCIckIuHhszoni6IouN1tZEraD4kn7OVs07lh3SSCS4eU\nXAderxeHo+9Jme4kjV6vF5vNNqSs0+nE6+1Zcf3mN7/Jli1bEm2MhOmWa36y5LlPRr9eLyHLEjo5\nOaMlyxJ6vYR+EAMaU1SOd+04KHifa8j2ZVkiZtIOHNj0DiSrDkmSkHrJSjJ96qzWHkPs6zSQ6ZKQ\ndRKyTk7EsJUlCamrDuh6v6c8UF3A7+evba9iyOo5wfbHUy9yu/kz5OTMSOqzma733GS530fLqE+G\ndc9Ehwq6fLEsaK4FVVW59dZbR6V/uuaan+g898noj8UCWCxGrNaB969eTCRsJDPThss18MLVm+80\nE+vyz5YUzSbToQ7afjikJxTT8tdlGDIJGQIY9DJGY88tbzTokPX6RJ3NqqLXx4nFdPh9Rsx5Jixm\nEzZrz0EHk8mAzqBP1FnMxj7lgeosZiP2DCu5c3I56O5a8LWpQ451MKbrPTfR9/toScnQZmVl4fF4\n+tS1t7cjSVI/H+tgsgsWLMDj8fCDH/yAvXv3jrDbPUy3XPOTJc99Mvq9Xj/BYASjKbn9UsFgBK/X\nj14/sO/11epGAMxGHblOE15P26DtXwi2Jk6EmbHhi3aCTiES6VkQi0Tj6CBRF43FsVpDdHTYaPfK\nhMJhDKEw/kAEWZKwWAyEw1GkeBx/QFtkC4Yi6HqVB6rrLkfCCg5jBh2RTloD3iHHejHT9Z6bLPf7\naEnJ0C5evJiGhga8Xm/icf/IkSPMnz8fi8XST7ampoY1a9YAmp+qtraW2267jQMHDuD1etmwYUNi\nltvR0cF9993HzTffzD//8z8n3afpmmt+ovPcJ6M/FlNRFJV4kum8FUUlFlMHbbfbP7voMheoQ7fv\nVXpi0FrJALURVVVRe8mqCn3qVIWEoQ2HdQSDMja7ihJXoOsRUlFVpHhXHaDEVSS5pzxQXe+yy+Sk\nI9JJe7RzyLEOxnS95yb6fh8tKTkgCgoKKC4uZufOnfh8Pk6dOkVFRQV33HEHAKWlpRw+fBiAsrIy\nnnrqKd5++21CoRCPP/44JpOJ6667jk996lO89NJL/O53v+Opp57iqaeeYubMmXz729/mS1/6UvpH\nKZjyeH1hzl/QFlwXvz9rWPkOtWt3AgYMUnKuC+jrp233pf+UWGZX4HF/PEBUSU/QGsHkJ2Uf7a5d\nu3jwwQdZvnw5drudsrIyysrKAKirqyMQ0PxiK1asYOvWrWzZsgW3201RURF79uzBaNT8Vrm5uX3a\n1el0uFwuMjJErE5Bf2pOuxN/L748e1j5DjR5q+xIav2gG4MxhtGoEolIdPhMMMTe25Hg6kqlo6LS\nEmplFrPS2r5gcpKyoc3NzWXPnj0Dvnfs2LE+5XXr1rFu3bqk2n3ppZdS7YpgGlHbdew2x2lmVraV\neHxwd4SiKglDa5NT++HujntwoUXXNaNNb0aE3ql0GoMtLElr64LJioh1IJj0KIpK9Xua4fzggpnD\nzlA74m0oaMkWrSkaWuiJexAKGwilcT8tgFlvwqrX1jMago1pbVsweRGGVjDpOXneiy+o+TOvuTJv\nWHlPvCXxt1VOPUNC77gHbm/684hlmzUf8zm/OIo7XRCGVjDpefOEFhjGaJC5auHwG/zdMS24tl41\nYJSTXwjrxmwBg0Eztm5v+pOQ5Fg0Q3sh3EowFkx7+4LJhzC0gkmNqqr8rcvQFs/Pxmwc3vB5ugyt\nWU3tMEA3kgR2h7YINjaGVlvMU4Ez7efS3r5g8iEMrWBSc7bZR1uHdiDhQwtnDiOt5QhLZL1VRx4R\nLsOhuSoCQR1+f3r3b7pMTmQ03+97HXVpbVswORGGVjCpefOE5m/VyRIf/MDg4RO7aY/3OhE2whkt\nQEZGz7aupub0GlqdrMOh1xbpTrcLQzsdEIZWMGmJKwoHq7WssQWXubCZh1+Y6vbPwugMrcmsYNBr\nxrahKT7idgbDZdD2057pOIuiTt0TT4LkEIZWMGmpPuXG06m5DT62ZHZS13T7Zy3Y0Y0iZpIkQWaG\ndkqssSn9hjCzy9AGYyGa/C3DSAumOsLQCiYtf3pLC5DttBmTchsAuLu2djkZ/vTYcDi7DK3Pr9LR\nmWY/rb4nyPlp4ae95BGGVjApafUGqT6lxStYsWQ2+iTigsbUKB1x7WCDQ0qfoQVoaEyv+8CsM+E0\ndPtpz6a1bcHkQxhawaTk2UN1qGiP8CuTdhu0oG2aAifJzYCHwmyMYzFrBrYxzYZWURRm6rU+nnSf\nSioxpWDqIgytYNJR19TJgbe0U1PXFuaS7UwuipYn3rMQ5mD4CF/JkO3qWhBrjKc13ZKvw0fIrx1W\naA27ee74C7jd7mGuEkxVhKEVTCpUVeWXL55ABUwGHbded8Ww1yiKQofXTXNA2/xvw0mw04eSBsOY\nnantpw2GVNye9M5qZ1h7Zt1hU3qjhAkmFykb2vr6esrLyykpKWHVqlXs2LFjUNn9+/dTWlrKsmXL\nWL9+PTU1NYn32tvbeeCBB/jwhz/MNddcw5133smRI0dGNgrBJYGqqjz7WhMnz7cDsPojl+HKGP4I\nra/Dy7G212lTtSAtOkXPCfdbRMKBUfcpy9VjAM+eS68xtEtW9JK2M8IdbU9r24LJRcqGdvPmzeTl\n5VFVVUVFRQUvvPACFRUV/eSqqqrYvXs3jz76KAcPHmTlypWUl5cTCmkLDF//+tfx+/0899xzvPzy\ny1x55ZV8/vOfJx5P/55FweQnFleoOevnQLV23HbeTDs3LJuX9PVGu4WopG0Fc5iyMNtGvoe2Nyaj\nSpZLO8VVdy69gbolSUrEPfBEvcNIC6YyKRna6upqTpw4wbZt27DZbMybN48NGzZQWVnZT7ayspK1\na9dSVFSE0Whk06ZNSJJEVVUVAJ/61Kd48MEHcTgcGI1GbrnlFjweD21tbekZmWDSEldU3B0hzrf4\nOH7Wy6u1zTxx4D3ebdR8lvk5Nrau++CQ6cQvJiz1zF5TjUE7HPmzdQDUN0RJd9qqGV1xD9pjnURE\nxoVLlpR2dNfW1pKfn4/dbk/UFRYWcvr0afx+f59040ePHuWmm25KlCVJoqCggOrqam688UZWr16d\neM/tdlNRUcHVV1/NzJnDn2cXTD1UVaWxLcDR024ueIKD5hF7X66VL932QRy9ssomQ6iXobXIdvz4\nR9Xf3uTP0lFdEyMWA2+7npzs9FnbGdYcaNMyLtQHGpktMi5ckqRkaL1eLw5H3/ie3UkavV5vH0M7\nkKzT6cTr7fuIVFpaSl1dHVdffTWPPfZYSp0XTA3CkTh/OdJAQ+vAPlOrSU+Ww8S8bD03f3QeTnvq\noQ3DkmZYTZIVnZTeiFu5M2X0eojFoNVjJCc7NPxFSZJtdiEjoaBS5z/PMpamrW3B5GHUd2T3lpdk\n8jINtD3mj3/8Ix6Phx//+MfccccdPP3005hMyX/RdElsZE833Tqnm+5U9ev1EqGowp9eO4vXp6Xe\nNht1LJibSa7LQobNiMWow2jQHs3bvW4MBhn9IC6Di3Xr9RKyrN133TNamy4DSZaQZO2elLreR5L6\nlqGfTO+yJEnIOu1lMOqYlafj3Pk4bR4Dsi6M3NWHbhm51+dxcd1QMkaDkSyLi9agm3OB80mPfTyZ\nrrrTqTclQ5uVlYXH4+lT197ejiRJuFyupGQXLFjQr12Xy8X27dv5zW9+w4EDB7jhhhuS7lM6cq6P\nlOmqO1n9Hb4ODta20xnUVusXz8/mw0WzMOp1A8pHwkYyM224XEMvZHXrjsUCWCxGYmqUSEybZWYY\nMjEa9RgNOmS9HmNX/Fq9QYdBLyfKQD+Z3uV4VI9ZZ8JiNmGzGrn8MoVz5wN0+vWAVgdgMRvRGfSJ\n8kB1w8nMduR2GdoGHE4zOnngz6f32CeC6ao7HaRkaBcvXkxDQwNerzfhMjhy5Ajz58/HYrH0k62p\nqWHNmjWAttextraW22+/Hb/fz2c+8xl2797NokWLgJ4ZsV6f2iS7oyNIPN0rFMOg08k4HJZppzsV\n/aqqsufp4wkje9WCHJbMzyYWiRGLDLxNKhiM4PX60esHjiN7sW6v108wGMGj9gRlMalWIpEYkWgc\nHRDp0hWLxkGnJMpAP5ne5Ug0hi4WxhAK4w9EyMvtmQmfa1CZPVeboQdDEXTxOP5ApGccF9UNJ+My\napOUcDxC9bl3ucwxZ9ixjyfTVXdv/aMlJatWUFBAcXExO3fuZPv27TQ3N1NRUcHGjRsBzd/68MMP\ns3TpUsrKyrj//vtZvXo1CxcuZO/evZhMJlauXInRaGT+/Pl897vf5ZFHHsHhcPDjH/8Yo9HI0qWp\n+ajicYVYbGKOLk5X3cnof+nN8xx5T9sbOj/fQdH7s1FUYIhDBIqiEoupw46rW3cspqIoKl61Z6eK\nRbKjKiqqohl7tXvRTVX7lqGfTO+yqqoo8e6XQkaGhNMp096u0HxBj9L1pVfiKpKsJsoD1Q0nk23q\neRo80fYe+dbBjxxP13tuou/30ZKyA2LXrl00NzezfPly7rrrLm655RbKysoAqKurIxDQfGUrVqxg\n69atbNmyhZKSEg4dOsSePXswGrXHp0cffZSZM2dy4403snz5ct58801++tOfJmbKgqmLpzPMbw+c\nAiDDoqOkMHdM9XWo2tFVk2RBL6U/mSJoT1zvf5/WdpvbQGyIdOepYtKZsOm0WbwIBH5pkvJiWG5u\nLnv27BnwvWPHjvUpr1u3jnXr1g0o63Q6+c53vpOqesEU4Dd/epdwJI4EfOiKjKQib42GDjRDO5LU\n4qlw+WVG/vZ2mLgi0dikMDd/cF9qqrgMTvzxAO8JQ3tJImIdCNLKiXNeDtVowV2uWZRFpm1sZpjd\nxNU4frQtg1bZPoz06Jg9S49epz2+njuf3hOMmXptK6Qn7MUbFsdxLzWEoRWkDVVV+e2fNJeBzayn\n9Oq8MdfZiQe1KzTiWM9odTqJnCzt9Na58+mN5tWdcQHgjIhPe8khDK0gbdScdvNuvTYbu+nD78Nm\nTn+q7ovpoGchzCo7hpBMDzOytJ0D/oBKmzt9izMZOhsmWVu/EJlxLz2EoRWkBVVVefIvpwFw2Ix8\nfGn+uOjt6NpxYFCNY7YQ1psZ2VEkSZvJnq5Ln/tAkiTyrdrxW5Fx4dJDGFpBWqh+r43TjR0A3HTt\nZZgM6VsoGor2roUw0ygy3g6EqqoEg0ECgQA+nw+fr5POTh/RiA+XQ4sSdvpMFL/fTyAQSIsbYW7X\ntq6zneeJKSI+7aXE2D/bCaYFv/+r9rjrtBu57qrkUs+MlqgSTSyEmdWBDzmMlHAoSFNTO44Q+CUr\nkiRhNOipb+5E1huAWfj8Eu81RNHpveTlz+oTbClVFEUhE83HHFNiHD1/jDnWWWRlZSHLYj401RGG\nVjBqTpzz8m5XsO5PLpuHYZAjtummKXghsRBmTvOMFsBgMGGyWLBYbEiyhNGox2S2YrTEaHOrqKpE\nJJqN0zr62aevw0dTyAddH93LjYeYGXexasF15OSMPv+ZYGIRP5WCUfPsIW02azXpWfnB8ZnNAjQE\nmxJ/p3tGOxQ6nYIzUzPwnT77UIfdUsKZ4STDqM2K/XIQW8bYblcTjB/C0ApGxfkWH0e60oKv+tAc\nLKbxe0jqNrQW7OjG+eFsxkxtx0E0aiASSS55ZDLkmLWMC21BkajxUkIYWsGo+MOr2gq5QS/ziQ/1\nD4YylnQbWifZ46oXIHuGgixrU1mfL33byrpT2/hjAcJKZBhpwVRBGFrBiHF3hHjtmHYKbHnRLBy2\n1LIijIZIPMKFkDaTdkjjb2j1esjqyrTg8ztQ0rSlNsvckybdG+1IT6OCCUcYWsGIef71c8QVFUmC\nG66ZO666z/saEgthDrKGkR4bZuZ2RedS9DS3DCOcJJkmBzpJ+1q2x4ShvVQQhlYwIvzBKAfebgDg\nQwtmkOsav8UogLqO84m/HRPgOgDIzFKRZe3Qwpmzw2cYSQZZknGZutJDiRntJUPKhra+vp7y8nJK\nSkpYtWoVO3bsGFR2//79lJaWsmzZMtavX09NTU3ivXA4zLe//W1WrlzJNddcw8aNGzl58uTIRiEY\nd1568zzhiGZkSksuG3f9Zzs1Q2slA4M0fi6L3sgyODJ8ANQ3QiiUnu0H2V1+2vZYR1rjKQgmjpQN\n7ebNm8nLy6OqqoqKigpeeOEFKioq+slVVVWxe/duHn30UQ4ePMjKlSspLy8nFNJSjjz66KMcPnyY\nyspK/vznPzNr1iz+8R//cdQDEow94Wic518/B8CieZm8f/bYxxjojaIovOt+DwBr1EFnhwdlggyS\nI6Ozq08Sp06n5zRXtlkLBB5VY7gj3mGkBVOBlAxtdXU1J06cYNu2bdhsNubNm8eGDRuorKzsJ1tZ\nWcnatWspKirCaDSyadMmJEmiqqoKgIyMDLZv305ubi5ms5m77rqLs2fPcuHChfSMTDBmVL1+lg6/\ntiJ+47UTMJttPpswQEo8zgn3W0TCA2fYHWtMpigmYxCA4ydjaZmBZvdaEKsPNI66PcHEk5Khra2t\nJT8/v89Rw8LCQk6fPo3f7+8je/ToUQoLCxNlSZIoKCiguroagC996Utcc801ifcbGhowmUw4nU4E\nk5e4ovDEn94FYN5MO1dePv4LUXW+Hv9spnkGZlv6T4WlQkaGZvS97SoXWke//cBmsGLUae6Q88LQ\nXhKktMvb6/XicPR9TOxOPeP1erH1uuEHknU6nXi9/R+F2tvbefjhh9m4cWMi1Y1gcnKoppmmNm32\n+KlrL0sqzXyyKIqC29026Pt6vUQsFuB4m2bo9egwYSHCxO43tdk68XrziMUl3jkR4/JZo2tPkiSy\nzS4a/c3UB4WhvRQY9XGa7kelZL5wAz1WtbS0cO+993LllVeOyEc73XLNT6RuRVX534NnAMjLsvLh\nxXnI8uD/73q9hCxL6IaQ6U3A38HBt1uYkRsd8H1ZljGZ9JxoPw8y6GMmYmoUSdbuP6mXnn51kjSs\nTO+yJElIUk9Z7rq/5YvakWTQ6VTedxm8+x6cPhNnbq6MQSchd/0fyTqp69Xzf3Zx3cXlHEsWjf5m\nmoLNICvodNpXdbrdcxOpO516UzK0WVlZeDyePnXt7e1IkoTL5UpKdsGCBYny2bNnufvuu1m1ahXf\n+MY3RjQ7mq655idC98EjDTS0ai6iv79+AdnZQ5/Fj8UCWCxGrFZTUu1bLEbsGTZmzR58ShhTovg6\ntQA2dtmJQadDMeiQ9XqMxp7b2XhRnd6gw6CXh5TpXTYYdBiMOgwXtavXy/2uQdJRuMDAu+/FiCvQ\n0mpj0QIFm1V7OrOYjegM+kR5oLqLy/muXKpbjxFT43RKXmY4NF/4dLvnJoPudJCSoV28eDENDQ14\nvd6Ey+DIkSPMnz8fi8XST7ampoY1a9YA2mNhbW0tt912GwAej4eNGzdy22238YUvfGHEA5huueYn\nSreiqvziD1ryzWyHkctccPLkmSGvcbvbCATCGE3hpHQEgxF0eggEBpaXZRkPjYmDCsaYhWg8TiQa\nRwdEIj2r/hfXxaJx0ClDyvQuR6NxopE40ViMSCSGLEnoDTpiMQWJWJ9rYrE4ZnOUvFwdTc0K753V\nM29uJ/6A5tIIhiLo4vFEeaC6i8s2qSctz1vnjpOjnznt7rmJ1t1b/2hJydAWFBRQXFzMzp072b59\nO83NzVRUVLBx40YASktLefjhh1m6dCllZWXcf//9rF69moULF7J3715MJhPXXXcdADt37mTJkiWj\nMrIwfXPNj7fuN95p4VyLtmd0TpbEy0caUJShV9ibGs5id2aT4UxuwUxVVeKK9hoYhZZofZewhFGx\noMigKtq1aq/r+tWp6rAyvcuqqqKqPWWl6wlSUVXkAa5R4iqLFuhpao4QDOtobtEzK7/r5FhcRZJV\nlF6G4uK6i8tGyYBVZyEQD3LKc4aPz/soML3uucmiOx2k7KPdtWsXDz74IMuXL8dut1NWVkZZWRkA\ndXV1BALaQsmKFSvYunUrW7Zswe12U1RUxJ49exKLXU888QQ6nY7nn38eSZJQVRVJknjooYf4zGc+\nk8YhCkaLoqo8dVBLU+OyGyi4PAeLJWMIg6jR2eEZ8v2R0BzWdhyYVQvyJDvY+L55OqwWiUBQ5cx5\nEx+8anTtufROAvEgp0UK8ilPyoY2NzeXPXv2DPjesWPH+pTXrVvHunXrBpStra1NVbVggnjjnRbq\nL2i+2es/lMsErUugqiotYW1Ga1EnX6xWWZYoWKjnzbeiuL0G3B6FLNfIP6xMg5P6cBOtITcd4U5c\nTOw2NsHImVxTAsGkIxZXePLP2imsGZlmli2YmAAuAN54KxFV899OJkOrqip+vx+fz8ec2WFkSXvE\nfbs6iM/nIxDw98o9pr26/cxD4eqVgvw9Maud0ohUNoIhOVjdSLNHO/m0ZsX70enSt282VZojPdlh\nraoDhfRloR0NkUiYk+fayHBoC2QWq4rfn8WZs5CR3YH3gg+dXodf0gLvhENBnHKUDOfQR5e7U5CH\nlQinvGf4OCVjPhbB2CBmtIJBiUTjPN21b3bODBslhbkT2p/GaFcCSLLHPaPCcBhNWm4xi8VGdpa2\nTqGqEp62DEwmayL3mMViw2RObhW7dwry97xiRjuVmVx3q2Dc0U5jDZw25U9vt+Dp1B7VP3HVDNxt\nbXR0uElbkqwUiKsxWrt2HORI45eXbCSYjFFstiB+v4XGepnL5kqMNF3lXOts3vPVUddxjlhcpCCf\nqghDO81xu908f+gd7Pa+MSYiUYXn39IMcHaGHk+7j1eO+mlpOsvMvFkYzRkDNZd2FEXB1+GlVW0g\n3uUqsATshHWTO81LVnYHfr+FWEyio9NOttk//EUDMNeaD0BUiXHGe55seUY6uykYJ4TrQIDd7sSR\nmdXndbpVIRbXZq7XXDkbpysbR2YWVtv4hkT0dXg51vY678WOAiAj09R2bsKidSWL1RrCZtMWxbzt\nzhE9BCiKgq1X4sfDdUdQ0pUzRzCuCEMr6EdnIMLxs9oe2Mty7czInNjjjxa7nZBemxE6DdlYJjha\nVzJIEuTP68mU29mZegYKX4ePN8+9hV2nXXuw7vUhg+4IJi/C0Ar6cfj4BRRVMxZXLZj4R9UYUYKq\ndiot0zAxaWtGQs4MBZNJm8q62xwjmtXaMmzMtGv/B564yLgwVRGGVtCHZk+AumbNqC2a5xrXzLaD\n4Zd6cmc5p5ChlWWYPVfzK4dCJtq9I9sal2edqbURj9AcFIHxpyLC0AoSqKrKm+9oX2SjQaZ4/uQw\nan5Zi9ZlkExY5MnvNuhN3iwlkcDx/NmR7T3oNrQAJztPp6VfgvFFGFpBgtONHbS2azndiudnYzKO\ndFNS+oirMXySFiw+Uz8jrYHGxwOdDjKd2ozc65Hxdabef5PeRFZXHrGTHcLQTkWEoRUAEI0pHD7e\nCoDDamDhPNcwV4wPrTSgdh1pzdLPHEZ6cpLp7EDqGsO5Ec5qZ9m1wyJ1vvNE4pN7a5ugP8LQCgCo\nOe0mENY2xF+9aGbSWRHGmmZVOxGlx4hdzpzg3owMnU4h06X5vdsuSISCqX/tZtk0QxtT45z0ilnt\nVEMYWgH+UJya09rhhFnZVvJnTA4/aFyN0YJ2Gsw1Bd0GvcnK6kCSVECiscE8rPzF5Fiz0UvabPgd\n94k0904w1qRsaOvr6ykvL6ekpIRVq1axY8eOQWX3799PaWkpy5YtY/369dTU1PR5v66ujrVr17J8\n+fLUey5IGzVnfcQVFUmCZQUzJ41Ba4rWEUfLH+bSTU23QTcGQ5zcWZr7wN1qJBhK7VCmTpKZadEW\nJ2uFoZ1ypGxoN2/eTF5eHlVVVVRUVPDCCy9QUVHRT66qqordu3fz6KOPcvDgQVauXEl5eTmhkLbY\ncujQIe68807mzp076kEIRs67DT4a3JrPb9E8F5n25PJ7jQfnIycB0Kn6Kes26M2cefHErPZ8s3NY\n+VagIvkAACAASURBVIvJteQA0ORvxhPqn01aMHlJydBWV1dz4sQJtm3bhs1mY968eWzYsIHKysp+\nspWVlaxdu5aioiKMRiObNm1CkiSqqqoALVHjvn37EqltBONPLK7w1Cvao7nJoGPJFZNjOxdATI3S\nENF8kXbFNWlm2aPBbIbcPG1W2+K24Q+kNs/Js/QcHjncciStfROMLSn9T9fW1pKfn4/d3hN0ubCw\nkNOnT+P39w2acfToUQoLCxNlSZIoKCiguroagE9+8pNcfvnlo+m7YJS8+MZ5mr1adK6lC3O0jK6T\nhLPh48TQZtoOdeKCjaebOZf1zGrfPZPa0eYMg425XWETDzW+IU6JTSFSchR5vV4cjr5BRbqz4Xq9\nXmy9zqAPJOt0OvF60/vIM91yzadLt7sjxNOJPGB6Fs7NTGrWKMtyr3+HDnAiSRI6WUp6B0O3vCzB\nu+G3AbCTiVWyI8kSclf/ZElC6nrJEkiydq3US0+/uu5rhpDpXdba7yn3033RNVo/+rdzcdlihZyZ\nES40m2hsMeLxqmRn65B1Uter5/+1d123/g/NKOZcXSMN/iYago1c5piT1Gc7Gi6F+320+kfLqMMk\ndv+qJvMlHYtf4Omaa360un/ydC2hSBwJKCnIwmZLbiXcZNJuGbPZMKysxWJEpzdgtSbn9+2W79C1\n0B7X9vR+wLSYeDSG0dhzq+r1MrJej86gQ9bpUAw6ZL2+j4zxojq9QYdBLw8p07tsMOgwGHUYLmq3\nW3fvayJ6TXagdgYqX/a+AG0XjCiKxOG3Y6xZbcFiNqIz6LFZe448X1wXDsBH5y3lmfNVRONR3mz9\nGx+8bGFSn206mMr3+0STkqHNysrC4+mb2bS9vR1JknC5XEnJLliwYIRdHZjplms+HbrfOtnKwSMN\nAHzkymysBggEwkldGw7HsOoNhELRYUP2BYMRdPrk2w4GI0iywkn1TQAMGDG5M/AYL2CMxJAlCb1B\nRyymIBFDkUCOa5kgdEAk0hMY++K6WDQOOmVImd7laDRONBInGosRGUB372uiMU12oHYGKiNFyZ/Z\nwbkmJ3Vno5x4N4ASiqCLx/EHeg4jBHvVyZKEoii01LdR4LiCI55j/Pn0q9w09wZMhrFdwJzq93s6\n9I+WlAzt4sWLaWhowOv1JlwGR44cYf78+Vgsln6yNTU1rFmzBtBia9bW1nLbbbeNutO9ma655keq\nOxSJse8P7wDgtBu54UN5/O1Ey7Cpw7vpNq6Kogx7jaqqxBU16bZVVcXta6LZfBYksMddvNtWjc2V\ngV1xoHQ9xSmqiqyqqKqKooKqaNeqvfT0q+uSH0qmd1lVVVS1p9xP90XXaP3o386AZVVl9swOmtsy\niERl/vpqmA9dqSLJKkovY6LEe9XpZDrbOzngfQWTUzOswXiIv5x6leuuGJ/tkVPxfp8spOSAKCgo\noLi4mJ07d+Lz+Th16hQVFRXccccdAJSWlnL48GEAysrKeOqpp3j77bcJhUI8/vjjmEymfrsMhEN/\nfHniwHu0dWhb7O74xAIskyCeQW8u2M5Blxcq3/Z+zFMg9uxI0OtUFrxfS3rpbVc535ic68aWYef9\nuZdj1WsTm9faDovv0BQgZR/trl27ePDBB1m+fDl2u52ysjLKysoA7QBCIKBFvl+xYgVbt25ly5Yt\nuN1uioqK2LNnD0aj5m/auHEjr7/+ujYziscpLi5GkiR+9rOfcfXVV///9u48ruoqf/z463MXuCyK\noIIrhTmCywXKFcVUKvJbqKmVWtpDHcUWWzSdtHJpnZbJ+ZY1zbfJR+Ujm0YtC2es+Tm5NI0tjgYi\naLggyipcuMBduOv5/XHl5hVM0HsR7TwfDx4+Pp9z7ud9jp/PffPhs5zjxy7++hSdKqa0oqrJ+nKj\ng3/tqwfgmq5aHPUl/Lekljqzlo6dLv+d/QbFgiHkzJtg6miCVVf2dbkL6dnNTlllBwzVbo6dDKV7\nt7oLfwjPDbm+nfpwoCqPInMxh2uO0D/Kv5fkJP9qdaKNiYnhnXfeabbs0KFDPsvTp09n+vTpzdZd\nt25da0NLLVRaXolN6/smlcPpZlf+CQCCNCqGDozFrtVgV2uorS8j8PeuL+xU0E8IRYBQ6KHtc7mb\nE3CKAinDtPz9SxtOl4q8glDirhMturHcL/I6DhsKsAsHWce+JCHyN1fFs8ZXKznWwa/Evp8qqbd4\nXmcdkhBNqK59zctpdFZSqfGczUa4u6BTtX7qlytRdFc1A/t79kWlIYhjha4WfU6r0tA39FoATtYX\nk1N5MFBNlPxAJtpfgeJKEwWnPM8v944O57qebTvBYksctO4BBRShoou7++VuTpsanKwlROdJsHu+\nt1Nb27KbPr1DetJJ69mXW4//E5e7ZUlaansy0V7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