{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MNE-Python version: 0.19.0.\n"
     ]
    }
   ],
   "source": [
    "# set paths\n",
    "import sys\n",
    "\n",
    "# figures within notebook\n",
    "%matplotlib inline\n",
    "\n",
    "# to keep copy of raw data\n",
    "from copy import deepcopy\n",
    "\n",
    "# for plotting\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "# import numpy package\n",
    "import numpy as np\n",
    "\n",
    "# import MNE-Python tools\n",
    "import mne\n",
    "\n",
    "# check MNE-Python version\n",
    "print('MNE-Python version: %s.' % mne.__version__)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Read raw sample data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "# define raw audio-visual sample data filename and parameters for evoked analysis\n",
    "raw_fname_av = '../data/MEG_sample/sample/sample_audvis_filt-0-40_raw.fif'\n",
    "\n",
    "# parameters for evoked analysis\n",
    "event_ids = {'AudL': 1, 'AudR': 2, 'VisL': 3, 'VisR': 4}\n",
    "tmin = -0.2\n",
    "tmax = 0.5\n",
    "baseline=(None, 0)\n",
    "reject=dict(eeg=80e-6, eog=150e-6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Opening raw data file ../data/MEG_sample/sample/sample_audvis_filt-0-40_raw.fif...\n",
      "    Read a total of 4 projection items:\n",
      "        PCA-v1 (1 x 102)  idle\n",
      "        PCA-v2 (1 x 102)  idle\n",
      "        PCA-v3 (1 x 102)  idle\n",
      "        Average EEG reference (1 x 60)  idle\n",
      "    Range : 6450 ... 48149 =     42.956 ...   320.665 secs\n",
      "Ready.\n",
      "Current compensation grade : 0\n",
      "Reading 0 ... 41699  =      0.000 ...   277.709 secs...\n",
      "319 events found\n",
      "Event IDs: [ 1  2  3  4  5 32]\n"
     ]
    }
   ],
   "source": [
    "raw_av = mne.io.read_raw_fif(raw_fname_av, preload=True)\n",
    "events_av = mne.find_events(raw_av)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "288 matching events found\n",
      "Applying baseline correction (mode: mean)\n",
      "Not setting metadata\n",
      "Created an SSP operator (subspace dimension = 4)\n",
      "4 projection items activated\n"
     ]
    }
   ],
   "source": [
    "# create epochs around event triggers\n",
    "epochs_av = mne.Epochs(raw_av, events_av, event_id=event_ids, tmin=tmin, tmax=tmax, baseline=baseline, reject=reject)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Epochs  |   288 events (good & bad), -0.199795 - 0.499488 sec, baseline [None, 0], ~3.7 MB, data not loaded,\n",
       " 'Auditory': 145\n",
       " 'Visual': 143>"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# combine some conditions to make it simpler\n",
    "mne.epochs.combine_event_ids(epochs_av, ['AudL', 'AudR'], {'Auditory': 12}, copy=False)\n",
    "mne.epochs.combine_event_ids(epochs_av, ['VisL', 'VisR'], {'Visual': 34}, copy=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Average epochs (again)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001']\n",
      "    Rejecting  epoch based on EEG : ['EEG 008', 'EEG 009']\n",
      "    Rejecting  epoch based on EEG : ['EEG 008']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007', 'EEG 008']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EOG : ['EOG 061']\n",
      "    Rejecting  epoch based on EOG : ['EOG 061']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 025']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 008']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007', 'EEG 008']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 003']\n",
      "    Rejecting  epoch based on EOG : ['EOG 061']\n",
      "    Rejecting  epoch based on EEG : ['EEG 016']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n"
     ]
    }
   ],
   "source": [
    "# average epochs and get Evoked datasets\n",
    "evokeds = [epochs_av[cond].average() for cond in ['Auditory', 'Visual']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 460.8x360 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot time courses\n",
    "fig = evokeds[0].plot(spatial_colors=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Time-frequency analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "# define somatosensory dataset\n",
    "raw_fname_som = '../data/MEG_somato/somato/sef_raw_sss.fif'\n",
    "event_id, tmin, tmax = 1, -1., 3.\n",
    "baseline = (None, 0)\n",
    "reject = dict(grad=4000e-13, eog=350e-6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Opening raw data file ../data/MEG_somato/somato/sef_raw_sss.fif...\n",
      "    Range : 237600 ... 506999 =    791.189 ...  1688.266 secs\n",
      "Ready.\n",
      "Current compensation grade : 0\n",
      "111 events found\n",
      "Event IDs: [1]\n"
     ]
    }
   ],
   "source": [
    "# Read raw data\n",
    "raw_som = mne.io.Raw(raw_fname_som)\n",
    "# get events from raw data\n",
    "events_som = mne.find_events(raw_som, stim_channel='STI 014')\n",
    "# Let's only look at gradiometers because it's quicker\n",
    "picks = mne.pick_types(raw_som.info, meg='grad', eeg=False, eog=True, stim=False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "111 matching events found\n",
      "Applying baseline correction (mode: mean)\n",
      "Not setting metadata\n",
      "0 projection items activated\n"
     ]
    }
   ],
   "source": [
    "epochs_som = mne.Epochs(raw_som, events_som, event_id, tmin, tmax,\n",
    "                    picks=picks, baseline=baseline, reject=reject)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Parameters for wavelet decomposition\n",
    "freqs = np.arange(6, 30, 3)  # define frequencies of interest\n",
    "n_cycles = freqs / 2.  # different number of cycle per frequency"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading data for 111 events and 1202 original time points ...\n",
      "    Rejecting  epoch based on EOG : ['EOG 061']\n",
      "    Rejecting  epoch based on EOG : ['EOG 061']\n",
      "    Rejecting  epoch based on EOG : ['EOG 061']\n",
      "3 bad epochs dropped\n"
     ]
    }
   ],
   "source": [
    "power, itc = mne.time_frequency.tfr_morlet(epochs_som, freqs=freqs, n_cycles=n_cycles, use_fft=True,\n",
    "                        return_itc=True, decim=3, n_jobs=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Applying baseline correction (mode: logratio)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = power.plot_topo(baseline=(-0.5, 0), mode='logratio', title='Average power')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Applying baseline correction (mode: logratio)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = power.plot([82], baseline=(-0.5, 0), mode='logratio')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Applying baseline correction (mode: logratio)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 144x144 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Applying baseline correction (mode: logratio)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 144x144 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot alpha and beta ranges\n",
    "fig = power.plot_topomap(ch_type='grad', tmin=0.5, tmax=1.5, fmin=8, fmax=12,\n",
    "                   baseline=(-0.5, 0), mode='logratio',\n",
    "                   title='Alpha', vmax=0.45)\n",
    "fig = power.plot_topomap(ch_type='grad', tmin=0.5, tmax=1.5, fmin=13, fmax=25,\n",
    "                   baseline=(-0.5, 0), mode='logratio',\n",
    "                   title='Beta', vmax=0.45)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Phase-locking"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reading inverse operator decomposition from ../data/MEG_sample/sample/sample_audvis-meg-oct-6-meg-inv.fif...\n",
      "    Reading inverse operator info...\n",
      "    [done]\n",
      "    Reading inverse operator decomposition...\n",
      "    [done]\n",
      "    305 x 305 full covariance (kind = 1) found.\n",
      "    Read a total of 4 projection items:\n",
      "        PCA-v1 (1 x 102) active\n",
      "        PCA-v2 (1 x 102) active\n",
      "        PCA-v3 (1 x 102) active\n",
      "        Average EEG reference (1 x 60) active\n",
      "    Noise covariance matrix read.\n",
      "    22494 x 22494 diagonal covariance (kind = 2) found.\n",
      "    Source covariance matrix read.\n",
      "    22494 x 22494 diagonal covariance (kind = 6) found.\n",
      "    Orientation priors read.\n",
      "    22494 x 22494 diagonal covariance (kind = 5) found.\n",
      "    Depth priors read.\n",
      "    Did not find the desired covariance matrix (kind = 3)\n",
      "    Reading a source space...\n",
      "    Computing patch statistics...\n",
      "    Patch information added...\n",
      "    Distance information added...\n",
      "    [done]\n",
      "    Reading a source space...\n",
      "    Computing patch statistics...\n",
      "    Patch information added...\n",
      "    Distance information added...\n",
      "    [done]\n",
      "    2 source spaces read\n",
      "    Read a total of 4 projection items:\n",
      "        PCA-v1 (1 x 102) active\n",
      "        PCA-v2 (1 x 102) active\n",
      "        PCA-v3 (1 x 102) active\n",
      "        Average EEG reference (1 x 60) active\n",
      "    Source spaces transformed to the inverse solution coordinate frame\n"
     ]
    }
   ],
   "source": [
    "# Read region-of-interest (\"label\")\n",
    "fname_label = '../data/MEG_sample/sample/labels/Aud-rh.label'\n",
    "label = mne.read_label(fname_label)\n",
    "# Filename for inverse operator\n",
    "fname_inv = '../data/MEG_sample/sample/sample_audvis-meg-oct-6-meg-inv.fif'\n",
    "inverse_operator = mne.minimum_norm.read_inverse_operator(fname_inv)\n",
    "\n",
    "reject = dict(grad=4000e-13, mag=4e-12, eog=150e-6)\n",
    "frequencies = np.arange(7, 30, 2)  # define frequencies of interest\n",
    "n_cycles = frequencies / 3.  # different number of cycle per frequency"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Opening raw data file ../data/MEG_sample/sample/sample_audvis_filt-0-40_raw.fif...\n",
      "    Read a total of 4 projection items:\n",
      "        PCA-v1 (1 x 102)  idle\n",
      "        PCA-v2 (1 x 102)  idle\n",
      "        PCA-v3 (1 x 102)  idle\n",
      "        Average EEG reference (1 x 60)  idle\n",
      "    Range : 6450 ... 48149 =     42.956 ...   320.665 secs\n",
      "Ready.\n",
      "Current compensation grade : 0\n",
      "Reading 0 ... 41699  =      0.000 ...   277.709 secs...\n",
      "319 events found\n",
      "Event IDs: [ 1  2  3  4  5 32]\n",
      "288 matching events found\n",
      "Applying baseline correction (mode: mean)\n",
      "Not setting metadata\n",
      "Created an SSP operator (subspace dimension = 4)\n",
      "4 projection items activated\n"
     ]
    }
   ],
   "source": [
    "# Read raw data again\n",
    "raw_av = mne.io.read_raw_fif(raw_fname_av, preload=True)\n",
    "events_av = mne.find_events(raw_av)\n",
    "reject=dict(eeg=80e-6, eog=300e-6)\n",
    "event_id = 1\n",
    "# Compute epochs\n",
    "epochs = mne.Epochs(raw_av, events_av, event_id=event_ids, tmin=tmin, tmax=tmax, baseline=baseline, reject=reject)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Subtracting Evoked from Epochs\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007', 'EEG 015', 'EEG 051']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007', 'EEG 015', 'EEG 051']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007', 'EEG 015', 'EEG 051']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007', 'EEG 015', 'EEG 051']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007', 'EEG 051']\n",
      "    Rejecting  epoch based on EEG : ['EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 025']\n",
      "    Rejecting  epoch based on EEG : ['EEG 025']\n",
      "    Rejecting  epoch based on EEG : ['EEG 025']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007', 'EEG 025']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007', 'EEG 025']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007', 'EEG 025']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 003', 'EEG 006', 'EEG 007', 'EEG 008', 'EEG 009']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007', 'EEG 008', 'EEG 009']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007', 'EEG 008', 'EEG 009']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 005', 'EEG 007', 'EEG 008', 'EEG 009', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 005', 'EEG 007', 'EEG 008', 'EEG 009', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 005', 'EEG 007', 'EEG 008', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 005', 'EEG 007', 'EEG 008', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 005', 'EEG 007', 'EEG 008', 'EEG 015', 'EEG 025']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 005', 'EEG 007', 'EEG 008', 'EEG 015', 'EEG 025']\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 008', 'EEG 015', 'EEG 025']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 008']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 007', 'EEG 008']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 007', 'EEG 008']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 008', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 002', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 004']\n",
      "    Rejecting  epoch based on EEG : ['EEG 004']\n",
      "    Rejecting  epoch based on EEG : ['EEG 004']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 016']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 016']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 016']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 016']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 016']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 010']\n",
      "    Rejecting  epoch based on EEG : ['EEG 010']\n",
      "    Rejecting  epoch based on EEG : ['EEG 010']\n",
      "    Rejecting  epoch based on EEG : ['EEG 010']\n",
      "    Rejecting  epoch based on EEG : ['EEG 010']\n",
      "    Rejecting  epoch based on EEG : ['EEG 010']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    The following channels are not included in the subtraction: STI 003, STI 006, STI 004, STI 005, STI 015, EOG 061, STI 014, STI 016, STI 002, STI 001\n",
      "[done]\n"
     ]
    }
   ],
   "source": [
    "# subtract the evoked response in order to exclude evoked activity\n",
    "epochs_induced = epochs.copy().subtract_evoked()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading data for 288 events and 601 original time points ...\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007', 'EEG 015', 'EEG 051']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007', 'EEG 015', 'EEG 051']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007', 'EEG 015', 'EEG 051']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007', 'EEG 015', 'EEG 051']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007', 'EEG 051']\n",
      "    Rejecting  epoch based on EEG : ['EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 025']\n",
      "    Rejecting  epoch based on EEG : ['EEG 025']\n",
      "    Rejecting  epoch based on EEG : ['EEG 025']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007', 'EEG 025']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007', 'EEG 025']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007', 'EEG 025']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 003', 'EEG 006', 'EEG 007', 'EEG 008', 'EEG 009']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007', 'EEG 008', 'EEG 009']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007', 'EEG 008', 'EEG 009']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 005', 'EEG 007', 'EEG 008', 'EEG 009', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 005', 'EEG 007', 'EEG 008', 'EEG 009', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 005', 'EEG 007', 'EEG 008', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 005', 'EEG 007', 'EEG 008', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 005', 'EEG 007', 'EEG 008', 'EEG 015', 'EEG 025']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 005', 'EEG 007', 'EEG 008', 'EEG 015', 'EEG 025']\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 008', 'EEG 015', 'EEG 025']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 008']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 007', 'EEG 008']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 007', 'EEG 008']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 008', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 002', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 004']\n",
      "    Rejecting  epoch based on EEG : ['EEG 004']\n",
      "    Rejecting  epoch based on EEG : ['EEG 004']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 016']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 016']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 016']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 016']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 016']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 010']\n",
      "    Rejecting  epoch based on EEG : ['EEG 010']\n",
      "    Rejecting  epoch based on EEG : ['EEG 010']\n",
      "    Rejecting  epoch based on EEG : ['EEG 010']\n",
      "    Rejecting  epoch based on EEG : ['EEG 010']\n",
      "    Rejecting  epoch based on EEG : ['EEG 010']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "179 bad epochs dropped\n",
      "Preparing the inverse operator for use...\n",
      "    Scaled noise and source covariance from nave = 1 to nave = 1\n",
      "    Created the regularized inverter\n",
      "    Created an SSP operator (subspace dimension = 3)\n",
      "    Created the whitener using a noise covariance matrix with rank 302 (3 small eigenvalues omitted)\n",
      "    Computing noise-normalization factors (dSPM)...\n",
      "[done]\n",
      "Picked 305 channels from the data\n",
      "Computing inverse...\n",
      "    Eigenleads need to be weighted ...\n",
      "Reducing data rank 81 -> 81\n",
      "Computing source power ...\n",
      "Applying baseline correction (mode: percent)\n",
      "Loading data for 288 events and 601 original time points ...\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007']\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007', 'EEG 015', 'EEG 051']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007', 'EEG 015', 'EEG 051']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007', 'EEG 015', 'EEG 051']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007', 'EEG 015', 'EEG 051']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007', 'EEG 051']\n",
      "    Rejecting  epoch based on EEG : ['EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 025']\n",
      "    Rejecting  epoch based on EEG : ['EEG 025']\n",
      "    Rejecting  epoch based on EEG : ['EEG 025']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007', 'EEG 025']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007', 'EEG 025']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007', 'EEG 025']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 003', 'EEG 006', 'EEG 007', 'EEG 008', 'EEG 009']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007', 'EEG 008', 'EEG 009']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007', 'EEG 008', 'EEG 009']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 005', 'EEG 007', 'EEG 008', 'EEG 009', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 005', 'EEG 007', 'EEG 008', 'EEG 009', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 005', 'EEG 007', 'EEG 008', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 008', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 005', 'EEG 007', 'EEG 008', 'EEG 015', 'EEG 025']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 005', 'EEG 007', 'EEG 008', 'EEG 015', 'EEG 025']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007', 'EEG 008', 'EEG 015', 'EEG 025']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 008']\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 007', 'EEG 008']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 007', 'EEG 008']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 008', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 004']\n",
      "    Rejecting  epoch based on EEG : ['EEG 004']\n",
      "    Rejecting  epoch based on EEG : ['EEG 004']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 016']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 016']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 016']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 016']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 016']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 010']\n",
      "    Rejecting  epoch based on EEG : ['EEG 010']\n",
      "    Rejecting  epoch based on EEG : ['EEG 010']\n",
      "    Rejecting  epoch based on EEG : ['EEG 010']\n",
      "    Rejecting  epoch based on EEG : ['EEG 010']\n",
      "    Rejecting  epoch based on EEG : ['EEG 010']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "179 bad epochs dropped\n",
      "Preparing the inverse operator for use...\n",
      "    Scaled noise and source covariance from nave = 1 to nave = 1\n",
      "    Created the regularized inverter\n",
      "    Created an SSP operator (subspace dimension = 3)\n",
      "    Created the whitener using a noise covariance matrix with rank 302 (3 small eigenvalues omitted)\n",
      "    Computing noise-normalization factors (dSPM)...\n",
      "[done]\n",
      "Picked 305 channels from the data\n",
      "Computing inverse...\n",
      "    Eigenleads need to be weighted ...\n",
      "Reducing data rank 81 -> 81\n",
      "Computing source power ...\n",
      "Applying baseline correction (mode: percent)\n"
     ]
    }
   ],
   "source": [
    "# compute power and phase-locking within label\n",
    "power, phase_lock = mne.minimum_norm.source_induced_power(epochs, inverse_operator,\n",
    "        frequencies, label, baseline=(-0.3, 0), baseline_mode='percent',\n",
    "        n_cycles=n_cycles)\n",
    "\n",
    "# Same for induced activity\n",
    "power_ind, phase_lock_ind = mne.minimum_norm.source_induced_power(epochs_induced, inverse_operator,\n",
    "        frequencies, label, baseline=(-0.3, 0), baseline_mode='percent',\n",
    "        n_cycles=n_cycles)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "# average power across epochs\n",
    "power_avg = np.mean(power, axis=0)\n",
    "power_ind_avg = np.mean(power_ind, axis=0)\n",
    "phase_lock_avg = np.mean(phase_lock, axis=0)\n",
    "phase_lock_ind_avg = np.mean(phase_lock_ind, axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Power Evoked+Induced')"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "times = epochs_av.times\n",
    "fig = plt.imshow(20 * power_avg,\n",
    "               extent=[times[0], times[-1], frequencies[0], frequencies[-1]],\n",
    "               aspect='auto', origin='lower', vmin=0., vmax=30.)\n",
    "plt.title('Power Evoked+Induced')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Phase-locking Evoked+Induced')"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.imshow(phase_lock_avg,\n",
    "               extent=[times[0], times[-1], frequencies[0], frequencies[-1]],\n",
    "               aspect='auto', origin='lower', vmin=0., vmax=.7)\n",
    "plt.title('Phase-locking Evoked+Induced')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Power Induced')"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.imshow(20 * power_ind_avg,\n",
    "               extent=[times[0], times[-1], frequencies[0], frequencies[-1]],\n",
    "               aspect='auto', origin='lower', vmin=0., vmax=30.)\n",
    "plt.title('Power Induced')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Phase-locking Induced')"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.imshow(phase_lock_ind_avg,\n",
    "               extent=[times[0], times[-1], frequencies[0], frequencies[-1]],\n",
    "               aspect='auto', origin='lower', vmin=0., vmax=.7)\n",
    "plt.title('Phase-locking Induced')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Source Estimation on single trials"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Read new label\n",
    "fname_label = '../data/MEG_sample/sample/labels/Aud-lh.label'\n",
    "label = mne.read_label(fname_label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "72 matching events found\n",
      "Applying baseline correction (mode: mean)\n",
      "Not setting metadata\n",
      "Created an SSP operator (subspace dimension = 4)\n",
      "4 projection items activated\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007', 'EEG 015', 'EEG 051']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007', 'EEG 015', 'EEG 051']\n",
      "    Rejecting  epoch based on EEG : ['EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 025']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 003', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007', 'EEG 008', 'EEG 009']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 005', 'EEG 007', 'EEG 008', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 005', 'EEG 007', 'EEG 008', 'EEG 015', 'EEG 025']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 007', 'EEG 008']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 005', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 015']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 016']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 004', 'EEG 006', 'EEG 007', 'EEG 016']\n",
      "    Rejecting  epoch based on EEG : ['EEG 010']\n",
      "    Rejecting  epoch based on EEG : ['EEG 001', 'EEG 002', 'EEG 003', 'EEG 007']\n"
     ]
    }
   ],
   "source": [
    "# Compute epochs again\n",
    "epochs = mne.Epochs(raw_av, events_av, event_id=[1], tmin=tmin, tmax=tmax, baseline=baseline, reject=reject)\n",
    "# create evoked data again\n",
    "evoked = epochs.average()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Preparing the inverse operator for use...\n",
      "    Scaled noise and source covariance from nave = 1 to nave = 29\n",
      "    Created the regularized inverter\n",
      "    Created an SSP operator (subspace dimension = 3)\n",
      "    Created the whitener using a noise covariance matrix with rank 302 (3 small eigenvalues omitted)\n",
      "Applying inverse operator to \"1\"...\n",
      "    Picked 305 channels from the data\n",
      "    Computing inverse...\n",
      "    Eigenleads need to be weighted ...\n",
      "    Computing residual...\n",
      "    Explained  41.8% variance\n",
      "[done]\n"
     ]
    }
   ],
   "source": [
    "# Apply inverse operator to EVOKED data\n",
    "lambda2 = 0.1 # regularisation parameter\n",
    "stc_evoked = mne.minimum_norm.apply_inverse(evoked, inverse_operator, lambda2=lambda2, method='MNE',\n",
    "                           pick_ori=\"normal\")\n",
    "# get source time-courses within ROI/label\n",
    "stc_evoked_label = stc_evoked.in_label(label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Apply inverse operator to EPOCHS\n",
    "lambda2 = 1.  # regularisation parameter\n",
    "stcs = mne.minimum_norm.apply_inverse_epochs(epochs, inverse_operator, lambda2=lambda2, method='dSPM', label=label,\n",
    "                            pick_ori=\"normal\", nave=evoked.nave, verbose=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Source time courses for one epoch for all vertices in label.')"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot time courses for one epoch in label\n",
    "plt.plot(stcs[0].times, stcs[0].data.T)\n",
    "plt.title('Source time courses for one epoch for all vertices in label.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f5cffb53b10>]"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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FZKmILO3o6BiJ03rsAI6T/WzEPSH38BjLjGjUilIqBLwJfCLPvr8qpU5QSp0wderUkTytx3aQnjQLwEgauzAnHh4eO8pIRK1MFZEJ7ucy4BygekeP6zG6ZCfNAiNpDpDSw8Njd2ckolZmAP8SET/6xfCEUuqFETiuxyji5Ap5wtqFOfHw8NhRRiJqZTXwwRHIi8dORGX7OjFTnpB7eIxlvJGdeyiOUiilBdxM2YOk9vDw2J3xhHwPRdmA0vHjluGF/Xt4jGU8Id9DUQpURsidQVJ7eHjsznhCvofiOCDosEPbkl2cGw8Pjx3BE/I9FB1+aAIK2+vr9PAY03hCvoeilIAofH6FY3vVwMNjLOM9wXsoSoGg8AcUjuPHcbzIFQ+PsYon5HsoygERRVGJQnwV3nJvHh5jGE/I91DSrpWyKkF84zE9IffwGLN4Qr6HohSIQPk4H+IbTzIe39VZ8vDw2E48Id9TUdq1UjkhgIifaLe3ALOHx1jFE/I9FKUEESipKAIgEfFWCfLwGKt4Qr6nokB8QnGpFvJU3JuT3MNjrOIJ+R6KQkCgpEwLuZHw5iT38BireEK+p+J2dhaXlwBgJDyL3MNjrOIJ+R6KQhAflKSF3FslyMNjzOIJ+Z6KEkSE0got5GbSm3DFw2Os4gn5Hovg80FJRSngLS7h4TGW8YR8D0QpBQiIUFZZBoBpeELu4TFW8YR8D0S5CwL5fEJJeQlKOd7iEh792Laui3CnN1BsLLDDiy97jD2Uoygy4sza+B6+udNBCZbpCblHb57/0yp8fuFbfzlrV2fFYxB22CIXkX1F5A0R2SAi60Tk+yORMY/RQzU28dk53+SMZ+6DCy/kwrm/wPYsco8clNtsc2xvPdexwEi4VizgBqXUEcDJwHdE5MgROK7HaPHgPxkfbsl8PWDbe0zesm4XZshjd8MT8LHFDgu5UqpFKbXc/RwBNgAzd/S4HqNH4NZf9Nt21OJndkFOPHZXvCimscWIdnaKyCzgg8C7efZ9U0SWisjSjo6OkTytxwgwsWPrrs6Cx26E1/k9thgxIReRSmAO8AOlVLjvfqXUX5VSJyilTpg6depIndZjhChNRHZ1Fjx2I6yccFTb8kR9d2dEhFxEitAi/ohS6qmROKbHzsVne0P0PbJYZlbIjYQ36nd3ZySiVgR4ANiglLp7x7PkMaoY+SfHUuINKfDIkutasS2v43N3ZySe3o8AXwLOFpGV7t8FI3Bcj9GgszPvZr9jQ8Ib/OGhyR3p69iea2V3Z4cHBCml3gFkBPLisTMI9+u+yNLdDTO9gKP3G+HwGqqqjkTEP+Tf9LbIPSHf3fHa03saqVThfcHgzsuHx04hHq/jvaWXsmnzHcP6Xe/OTs+1srvjCfmehifkexS2rddibWt7fli/szzXypjCE/I9jeQAiyx3d++8fHjsFBylO7cNI3/fSCG8zs6xhSfkexoDWOTKE/L3HY49QAtsAHKF3PF85Ls9npDvaQwg5I434vZ9h+MM0AIb8Hc5FrnnWtnt8YR8T2Mgi7yraydmxGNn4DjbZ5HnTprleK6V3R5PyPc0BrLIu4bnR/XY/egJr6K7e0Hmu729FnmOkO+s8EOlFFvq/kg0WrNTzvd+whPyPY0BhDzS8PpOzIjHaLB06WWsWHkVth0HevvI03OMD4XcSJWd5VpxnAR1dfewbPnnd8r53k94Qr6nMUDUigq278SMeIwmweBioLdrRamhz5nSa2TnMFwryWQzyWTzkNPnkn752HZ0u36/J+MJ+Z7GABZ5UWRgy6up+d9s3frXkc7RmMJxTJTafTv/9Px1YFp6BG9uZ6fj5J9nJx9WKpt2OK6VBQs/yoKFHx1y+lzSQq6UNxf6cPGEfE9jACEPDCLk1dU/ZXPtnSOdo92SSGRdXsvy7XdOZNmyz+yCHA0VfQ8zrhUnxWYOwcGHUkMXcjNlZFwxZmrnzIxp295cP9uLJ+R7GgNZ5NGhNaEtKzbk00UiG9i67e9DTr+92HaSlau+TixWOyLHW/Lexf0sS9tOYFkResIrRuQco0FafG1LuycaUvAL+Q1/59rhWeSGBWgBNxLDj3zZHqvatoderzx64wn5+wClFGvebCQWGsIDN6BFbsEQOsTiiboh5+29pZexefMdOM7ozmkdCi2hq+sNNm68dUSPa1lZf204snZEjz3SaJePtsg3197JihVXEXajT+bLx4Yl5GbKBGVmPw+TVGr4/S2W24rwGD6ekL8P6NgW4a3HN/LWvzcOnniAzk6fA0TyrxRkOVkLq75n6MvCpZvztj26KxCJT/uGHTWyboBc94pppke+7p6PTV+Ltju4gFAylPk+LIvctFBuWVrbJeQtgyfqg+MJ+Xaze9ZIj2HR2aitRr9/CLMJDzRpFhScb6U6nB31uSU2wFS4Lm3tL2EY2WOZ5uC/2RF8bief44yskPfqLHRD+YYzHezOJLf1kKYjkn25D0fIbdMCLJRyMM3ht6aG437L/MYT8u3GE/I+NDY+MuYiM7qb9UNTOal08MSDCXmBGRC74tnBQt2pgcPDUqk21q69jrXrvpfZZlmjK+QK7UIYTodewWPluJfsHHGxHd0ZJ7vpakqW1b/VE8uJAXeGUTa26YByANv1lw+P4YQ6Zs45BoQ8kWhk69b7hxWTvzPYPWvkLqRm48/ZXHvnbh1i1hczpd0etjmEPA9TyC0rgmmGiRnZ4fshY+AHzjR73FO15RxnlIXctTbVCPjicy3X3EgKJ/N51z02htHFhuqb80Z4mFZPv21Jsi93wzbc8MnBRUgPAnJA7Roh31khiI5jsGbtdUMeTar14S4i0XWjnLPh4Ql5AcbSMOH07HS5c0gXZJiulXcWnMZbb3+QZI6bpMcYOEwsPaDD7yvLbDNHWcjT4jscq7PwsbJl1Nsi3zmulWi0ppdbKpf6rffR3Pw4zS3/6bcvldR+6UBgQmZbkuw9CMdbeePNw2lsenjQPOgh+jbgYJvDF9XtEWIzxx0z0i6yQsTjdbS3v8S7Sy5gW8M/B03vk2IAwuHVo521YeEJeQ65lkoisW1UztHR8V8i0eoRPabtRiaYxo5b5Kq798RZaVE2jayP3MyxBpPJln7XY5q6g83nz1qDo22RpwV8JATAcVL8kD9yH9/NuFMg1yIfXd5dcgFL3rs4775AoAoAI6e1kyaZaiFJCX+VbxNkot6WY5F3RTcD0Nb23KB5UI7Kula2Q8i3p9M5lSPkaoQ7rQuR27LZtOl24vGBI7LS5R+LDSGwYCfiCXkOuT5GK08zdSRYveYaliy5cESPOVSL3DA6SfbUD5hGhfJbgoHY8uwXM/vALVp8br/rMU3tnvH7siKSSg5trvPmlv/QHVw0pLS5tCR0niLm9s32l+b1eQezes23aJGZvC1nZR70jo5X6e5+BxhdkUkbE4WiPooC4wHtYulLKtnCRv+JvG59iL/xbaC3kEcMXafTYjQQjgMKB6Xs7Zo0a/ss8mzrZzgdszuCaYV6fe/qmj9wetdI2d553kcLT8hzyF1FJZ+/cUcZrcqZtsgHE/JVq68lERzYZZQr5Ln9BKXJtWCAJKEimk3juBZr7rWlK3s6JBBg47vz6Ox8g2XLv1Cw/0Epmw0bfsSKFV8cMI+5JBINRKM1dLl+e2uHy1gRzhnwY1pxotEaVq/5VmYgkOMYo9bZNdi0s2lLN2X0nzs+mWzCCUwHYBOH6nQ5Qt6T1OIf8A9ByG0QtEW+Pa4Vwx7+fTByXSs7ySLvTvQ2MPJ1GOdiuEbKznrRDJUREXIR+YeItIvI7j1iYhCyccJgmSMv5MNdbmuopC1yMzWw5RSPb0bMgQVIhbMWSm6lLrVb8EdBTKhKhkn2mREvmcxakGkhJ0ewo6E21qz9NqHQu3nD5ACisU39tjlOisbGRwpaeAsXncm7Sy7A57pUfOx4Z6dJIPN5XTROtJ8rTG1XZ95QsAaZMCrt3unbYlRKEQyvIVJ8CABxyjH800jk+siTuv75/GUMhnIUvoAPlLNd85FHreELnWVk3W/OdrwItofmWO+WzWBCntaIkeiLGUlGyiJ/EPjECB1rl5E7d/NodM7ls6JGgnTTdzBfpm3H8Q0i5PRkhTztIkkjMUEMKFFJInbvcyWTTZnPljv4J1eUisoCGTEu9LBEI+vdT9lquXXrX6nZ+HNaW58ZMNviDif3jYDAxinPfA4lzLz5HbXWVYGXXGa/W0f73pvu6FauNX/NfdET9Abx0WyV9hLyiOsSG4qvXynw+QTEGfI0trmtlNh2CLltZq/dHEL0UTiyliXvXbJdMetpUm45PjfxrxQVTczU2a6u+f3KGLLlvr0LdowWIyLkSqm3gDG/4GPuzclYlSOIsR3DlodCenHcdBhiIZSyBxfyUNbS61uRA13aIi9RKXosfS4Rbb3mCnnaf2hZEVIU085e+Ep9WSEvMMrTcK0dny+Qsy3o5mXg+2H1NOrfOtsfNpoWogQVmW3RWDRvC2K48erRaA2trYU7GZWysazIoBZ52mfft3W3PNRBSCb12va8cRldTKFoaw+BDSEMSgCwBpjTpK39JRKJBpQjiA9EVK9FJgYit5USt4bvGjGNBFdFHuZl6wKMAXzQW+r+SEfHf9m48VYikbVEhjB1QkvLHBoa/tVvu2H2EKccu+RgioomYFlRDKOTlau+yrr1N/RKa9upTKf9+9K1MhRE5JsislRElnbspmtDpoXc7y8flSiLUXOt2OnOzsFFzGcMxyLvLZ5/mfodfjXhZxSTIuwKebrjLJFszObHLUfLDHMv3+N6uRcrq80FLfJMR5JjZUQ1Heqn6H1tSine7s45juv799nD8+fadiLzglHKIkY5PYzL7I9Zdt4Xz3Af5HeXXMC69dcX3L9p82+Y/9ZxGKnss5HKE5mSda1EWLX6msz2pOuK8NdH8W/WdXdx6WnUycH4q6MEtsVIoUPnCk1O5TgWa9dex8JFZ1IS7+H8zX/mpIY5ONbQyjRXyO1BQlT7/1axNVFK0aJunqi5NHM9+dLV1d3D6jXXYKT08+QfxFWklGL9hpvYuOm2fvtSRpCEKqMy4Mfvr8S2o5nQ40SioVdaI6dF/b60yIeCUuqvSqkTlFInTJ06dWeddlikH87i4qmj4iPPfTnkNkNNM7Tdk/FDjkWeHLw5OphFbgc7MuGEacFdkjiJdzmFefucxeqy4yjGzAh5jb0Pt3Mr6yNZccg0/60w6zkagGbJxjbncx8sXXYFW7feyx38jAf5aubc6VGUykm7ZWJs2PATFnW1cMWq7EyHcV+Yn3MHW2X/QcsgjdmV4Pvzb+HJ1XcD+v5/U2Zzm/w6kyZhZV0rISbwF75PB1O32yIr5OtvaXkKgJSRbbW9s+DUfi//XPdfZ+d/M5+Ttr73RTU9FNVG+NrGaHpHJk3aIrcLuCLS/t+yRpPPPnot+7+6jBNfeYpz59w6+PgD+oR+Boe3/uv6DT9kafveAEjKKWiR5z5DaVflQPcikjS57pG3Cacqgf6rJKnNq6kIRfDZNoFAJZaVFfLi4im90ho592aPFfKxgOOkeJmLeFpdOipRK7mWaG5FWLrssyxY+NFBY1gLkbbIjeTAoWJvcjbKHPiWJzrbM+GE6fzeU34Tf5QfZhOVW9grP0h39wKecS5ggxzN3K4wPT0rM9fWzSQMx2AK+mFr9E/P/LyvRe44Fj09y1HAWjmO1+T8THhdOsIlbRU3N/+b5pYnaG24n2ObO1CAAjYxlVo5lEcCXx5yREndS8v4j3yeG7pOd8/VXxCSYlLfZfPzhT9mZepYFsrp/Jabt1vIC/tzdZ77ut+MPu6tQv7tuJEEJ3vd36pTjLeCSE4kU1KlXSta5G072aus0i+NfZ4LU5bMCua+W1fAX/4y0GUBYNpZIVfxoU+SZtspWlufoTE6U/+23I9RwKJPpVozn7MRU4VF9ZkVTbywNsLzdee55+ptRATMMI7p44hH/kXAX4ltRYkn9KRwfV+6Kbe1VFqy957rWhkLOE6Kh+VqZqdOHxXXSq6vNS1mhtFFPK4HamzvaNJENCsOke78sxsqpfibfAfTLBk4j+EiVnUcCcCWVWt7xSH7ulP42hKEKnUsc139X7DRro8m9st0SMhgOTYAACAASURBVAYtH9fJ33iCL1CFLsfOwOTsOfoIedJ1y4TIWu2boj290vZ18yTaW/n4c/fwG37GNTyIoB8sk6IhRZTYdpLFAR0bX4YWgpTVXxBSPpizbm+aontT3aYjQhKUDelBVkrR3v5K3vueJ7U+n9FOF5NJZqzn3sJj2gnMsqOZNvNqLIpwHItodCMdtVuRePa6TRSTrG7EilBxyO2UTHuWhF3uXnsMy4ry5vyjqKv/U+Y3addB1eY8wnjTTYNeb9I2SFFMnLLMlAlDIe3qiVhuWKStMJL5X3j5Wq757sXq1deyadOvQfREcq+bH2cRp2bEOI0voHAsH5W1NYh/HJYVyZRD39ZQentNZyWWvX2LWo8WIxV++BiwCDhMRBpF5Gsjcdx8KGWzofrmER8dCb3f7BEzlbEGU45DbIh+woGwrDCzuZp/8bXMwx0Or8rsTyQGnh7WMm1ef3B9P7FORGIo1zp55OeLey2cm0YpAwybYmPgB6wqFaM5OoNtLdto7DL4mjyS2Ve0oovild1sih4E6IqdjopokFnE4trVsdXUzdgNHJ2JY04Fsi+QvmIWT9QD0E7Wal8X1eUTNWO8yMVsWfcuwdZmxO0I9XXph2qtHEdMqoi7Q6cNit35YYJ0h6upa6nDyeM3X/reZ1gzTYc7TnW09R82+5eN4Q9Q6tP5TbKPPjfOkMLPenqWsWbtd6it/d/stReczjc9OjfI9+Sv/ATt7ulbVtviYX6XuJRzmi/iVn6JaXbx7pLzaUtVMzF4I76SFvClaPRFmZyMETCa8AWiFE9aRI89jke5ikazIuN/b219NnutrnCNq8kj5IP0PXR3L6A7uJh7+T7fkIfpdAY2GHJJl2XUdKOFbLBSMerr7yUcXtMrbdb1lJ3ps69FHg6voaPzNbY1PEAwlh7xK/yFH5Ay9HW/E4zwSHMXieJSrpk5m1uu+CqXd3yaTsuXEey+UWbpzv+WaBWJ1NCEXClFMPjuqE+yNVJRK59XSs1QShUppfZRSj0wEsfNRzRWS3Pz46xY84MRP3YqJ2SqmRkZS+ETSzdy0NtrCv1syFhWhFfkIl6VC6hPpMPIsi6ceB4hjwaT9HRoka5f3UX14lYWztncK43fX4xysg/8igX/4s35x/ZKY9gpipd3UZpHrHIpsS22hA/gl7N/ycrKfXrvdKMX2qNTWMypxFKhjMXezN50RHXnUKOtLfZJdBFzI0BSRcXZcrD7WuTayupgr8y2xXX6WP+OHc6j8mXe5DCe//1vMs1df7ybtPgBtMgMAEyKefudE1mw8Aw+tXQ5p1T3sOq1l3qdTynF4rif5fFiJjdcQ5Hb+grlKZsEZTiWzl88qZv+Nv4hWeSd3Yt5jC+yIZpt3fUV5u7uBSxffiXdThXvcDqG2/Jol+kkKemXvt6cwBr5IABb5JCsINsh/KqLkr1eoeLA3/Ptw37EwZEu/HZWjOZa5/OiXMJb6pSM6yoQqMzsz1ighbxzA4jRipVXsXXjD3lPTgagQcbnTdfV/U6/6BHD0s9C0tR1SdkQT3RRu+V/WbHyy73SpvuuRPws4lSulDk0pnq3wJKprNVe16ont5KkTTEGpnvdn15Zyw01DTSUzAKgbeJkwk4R79jHkkjol4Vjx3stiGJZEUynhKRVgjlEi7y19RlWLPs84XnfA3v0FlcZc66VmrCuuNuMkZ+4qD2nr6aLybzd0YTlKM6N3s596isD/jYcXk1d/cB+xFROnGx6KHl6Lo+S4mm9/H9p/vWThTz8Mz1kPZ+lDaDwoZzssWvXLMO2oyilaGj4F6/PO4i4GackNLRIgrrQwRwf35/6kikU14f4/mv6ARf3Oa63D+BPcgMP2peRoJyKVBgHH+utvfQ5HR0GV0GUhBuTnZRsbHZfCyo9MdXEfa8DYILqZpWpCHYvJ2zrKhoPVJDoCWWFzQwzc8IR2WtGuz1M9GjSqG1TI9pFVLet97w5hhXjDvkFDbF2fCpOJKF9++GcF3mxSlFlWMStChKWFpiemK4gCcr7uQ5WhuO9o2iAjT3beEE+xbXhq7LX2keY12+4iWBoMXc6P+Be+T6tOVFFi/lIPyEPpsp7fW9OxN3r1hawr6QZX5F+GVzWaTPezva7iOufNwlkXp4Bf1bITTPE3daN+AtENqlIz5DnIDKc/MdYufLLbNx0Wy8LNej6w+MpN/rEUUSS+fuLLCtCMzOJWmW8o84AYHOi9zz8ue6oxi79TEnMQiyVGR9SpFJ8U/2Z9iptAGA6lMxrYU39IRhGB47Sx8ydNM20wiStCvyxKmSI4aepVBszGgyWv70Jc2n/8MeRYswJeWtUV0DbP26QlL2x7QStbc8PmKbdzFaICONxNlzII7VvchKLqCIyYPPovaWfYsuWuwec/jac0xkUcf2xth1HKWiKH4pjp1BKZZYUc/o8DOnwQvH1WUBCCcrpQcQd4ZnQvmalLGq36CZ6JBWkZBC3SpqqeIwZH36JbWXl+Gpi3O+kuG9JtkKnLG1dV3MUSco4sFO7KOrVfth2jLCj9ycpJe5a5LkDUyz3OtNWbfphSfqnI8DZvMbG0iN5beU1YGrLJxUoJRrspisW5l6uI15aTs3e2Zf5VmbpdG4LoZH98FlBfFYnzX3uSVOzOwq1z4rz3Ynsi66cOJW2j0SqiqCpJ6Bqt/TjkpQyTDs7SZfjWFy0dB1fWLmeXNri/QeU9BXm8vIDdVrXrdSe0xn9N/kO3SktvmveeJX61Ssw3HDMvUOuQeNao6ZK143sS7IotB8zE1nrVNxzhxmfGYmbO+9KyIjRFDqwX57TdGx4nIWLzqKj4zVAt2y2xPX5lnIiqzguk9ZQ+aXFxodBUa9QvqRrkdvuS1tsRdzQ4xKKi3v3rUQi67iRe7h4QR0/3fCQm4/ehkFuGYcS7jEtBfOCLG/Q9+1U3uEM3qCRfQHwhQzEUlRvPBBI0Ryd7uYpt38jTOeiK5m6+tM4Rk487QC0RPxs7voA8zmZpfWjM38TjEEh74jpiukP5G+6FaK6+mbWrfvBgL71aI4bMIKu4E5kaWZbj7tSipNKYYfyD1ApuIBsy2oSsaxQRNxmvJGK8EbDafxo3hWsbptAa+szvPfeJXR0vEaotfe8311d+ve+PisBKSWgDA48Zi0Tp5djJ8e72018Pi2qsVSQYntogzTGxaLUlc4gqLKdj8d1mxzbXMMHm6oxDS2AHexFglLGJXoYlwzSzExMM0TMca1iqkiJFtZcIY+aSZqaHuWNN4/ANIPYdgyfr5Qey6FK4EMsAaCaI+m2taXZ7XaWvtrh5x05kxemfxF/WTZ/3aJDxWJUoIB6ZwaTm7/HxNb/YVufwSnVW7Qv32frloaltJA0d2TjtktSccbFbWLJybSZrssnZ773iKXn9V606GxWrPgid/D/+AdfzLzslbLpzJm33XKH/fcV8rIyLSS2u7/F1uU1o1iXYVPKwrYsXr3vj8z51c9IuS+fb72ip1yNutdmuv6QD2+I8M87tvDIbbVs2PQbgk41H6hRTA6Z+N1z9zAhMymX35+18FtTDpN78i8sAmC01KCAltanWbduHQ+uXcWp727gyYZqfi8/5i75WTZtAWn5OXfyQ/7E681ZV2XMSlDPATi2W69tRUKF++VvQ/XNdHbP5+ioNhxO79T9S/E+LVXLilCasDl+VYjSVO/yrunUD/n+aIs/yCRmxrdy2htvZtLErYk0btBCbhjZ3xtGmFTbMQA48QlD8nu3tBskLLeTuW10xpHAGBRy0+2ssBnaGxEgHjaoWVCEcnyZZteaNWuoqekdJZK7mkqPo0WiIsdKDxpR3uqOsOkrV7Px5FPynis9am7Lig5CHdFstMX9H+X8txdk0oWSCdauXcuChfPYGNKdhw1Bm6bmxwE9wCYZywnnchSLV70OQLgzwV+unUftinY93Sg+FDZGIk7ZuCKspG6tOI6REfKoEaJ4iKPtquIRtrI/YVMfx+fYTJjzE56dfQNPP/xD7v3f2ylNJUlJKaaUUGSkmBptp4l9Ma0QMTfMLT2VKvQW8piVpLFpNgDdwUXYdhy/v5zWUA8S6mZiSwclKsFmjqHbjT8P+rWQG3Ft1TQEZnCU//B+ebclQIpS6uzJbt5jtGGy/q15PPo/N6CUosl9oEqMVrdsEyil6GzV4jEh3MPn7pnD1359K4cv20JnXI97kBwhD1smkchakqlmQj3vsTfN+HCIuHUomWwmonKu2W2ZFHrR2+6j2OFoA+LT03XZdZoWbVuyfSKGFBGo6WGt0vHyEXcNVlPZTOsy+OvdmzihJs4xWxJ89fEVLPzOBh69Yx1zf7iRa5+bo/POuMysf44yCbY0sfaN12gzFeOjhcMGq5tMvs5sGs0SnnzySd5cNw+xI9y3ZX2/tCb9lx1sShrUy4F0yVQWtlVnXH+xUC1/d65B0iNIbYdEZjqHbP9CIlFPiPEcH9mgy9SdJjnSZy4Yy45yWG2UiT0Wx9hbYaof/5RawKE9oe/PJNH1KMREqowwIV/WxVQbPoepHbqORBJZgy2eyJaNGZvcLzoqkdjG6jXf7hWlFOwMYbkt1CJz9FZAGnNCrtI+rujQZwR499laWpafR8/WkzODHubMmcNjjz1GdzhbUWLplVAcRXS1tvAqVryT2b8m1MpnVtVyz3FHIzPyi2Ldlnt4fd5BvHz/Kp74zVzeevskjJiuFAGlGG+6g0tiUTZv3ozfb2G5Fmw4YdPTo1sAfl9prxV/jKTFNL/Oe8tmXQlXvLotZ/i0jRGPUz7Oj5XQFrnjmJmJ8GOp0DAs8hjr+QAk9bGvfXcOE2qzU8uesHk9l/0324FYbKSYHG6nmb0xjFBGtHuYQJFpcvKqZUxpDhGjnHXOUcTMROYFEwwupiHp4x/OVWzp6KQsFaf55VlMjzfTzFQioh+wiE+/VLoc7VqI+8qIlLquFaU4d9Fb3P6nO/nKs0/wsH0VC51sM7/HF+flv9xNy6Ya4j0hgikTHAMHt4XkxInGe4glLKZ1tvPKt77IT+b+k6tWvMg9d/6UK5a8CuiBKqVzm5CYRdC0iMb6h4s2ucIaj9cTJeu2aGUG9cwi1LO8V/p0f4HtWtpd6Hp3QLl+GXaZ0LghPQRd0RmdSKA+yrOTTgel2LReL3BgYnPee2ECBTx7JZbip48/zcfmv0nQmZBZi9RIdfDig59j7n330G76qYwVniJgcVslSSlnTvwoADp8dUxp+jbxPCNQzTzS0pKziHMxcWKxTWzcdBtGyy30xHRZFSkLsRWGOxDMMEL0rGjGcRxEitnKgUwxdKtBXIs40mcKAcuKUBnRL4KUXQwVWymf+jeKp75Kl+tPL3bDVUNMpCoVprN4Ar6APk5bTxlm7OcEN59BMJoV8kQsZwqP2JR+fT2ba39LR8dcOjtfz2yzxcB0W5WJAiGVI8GYE/JSdxHgveoHDz9cE4nz9bV1tDdo8Yy1fADDDOIoxSSnkiqnjCWN2Vn7Yu7gidK3WljRMRMsIVKU9be0xHWP95VH/p2mnymU2V8Ym1ueAED8JpMOfwGwaN/2Xmb/BPdFFDFNysrK8PsswoauxJ3JrD9QfEVYOYN7UnELx+od0uXYCtt2EMfiMHM1HVsWs63mGczEJIzIVAwzyRvqVL7OQ3QneyjzNTIUxiWirOEY/AmDX839Mze99VC/NCev0VO6TjG62SfZxvhQkKSU05kIkXD91FWdCRZedQnPXP91XrrqajY8dhq/9t9GNJnKdJpFI+uZl9ibV5yPsqF8PGWpFOcVn8ck0yTE+MwEVmHG4fMJPW6nqU2A7hL94F354tPMvvn7fP3px/nNPXdw8d2L8NnZF3SyOGs5dTc1EPcVcVjdSk5fGWZ8VOGzo3R2dxI3TT73ynPMauldTl9d3HvCLl93ilDSyDuAqyWm62d70zIiOUP9b5NfcbP8rtdoTOgfA92Jtv73d1+6HUnF248+iPgcpMghGB0HOPhKG5FgikjKwB91+NGf5nPj4/07y/vyyK3Xc8wLq+no1nUy2LOS5SedQHDaRDrsIsYNIORGTD8LdbbuzO62dZRVd0q/EP22xUnrlnHXf+8Eq7e12tk5j+rmlzPflWVgGJ20Mw3DKiUU1c/AzGQH2IokpaTsIhJmhNNWn8fdL9yBiA9b+ZjitnLLnRRldpKw3dv6t6wIPW5rskyZ+Iu0v71o/GpCSS15RRg4+OhhHGWJCMHiCVSVaWEORvVLtXPdxXQFcxYQT2S1wI5N6ifk6XsZz+kQtuwEKeWuKmRZVMdGZ3GSofsndhNKkkEoAau0/zuoOpbg2bYQNx0wHRHhug3bqI4m+JDra7YSE+iKd/DV9zbwgHESAHPXhbi/qp2rZ04hYjr61ZZSOAhtzsGUkX3QOhJdnKveIlmhK04k1E3VlL2oq/8Tc/gMT8lneURdDoAvkKJyb20tBVvWkw7kq3Q79iKmTVFRET6/RcTQVmdXIuuKcByjl0Weilsou7eQW4YNr8/j649cSnE8geMT1n6/lgX+E2hf9RkiJ4X4u/FJElJKbVctE/d6ekhlfNvce/lwahNX/PelgmnOWLoYgDmrruewVD3fjV0NwKZwN3G3A+nmv/+Rfdv0i9KnFNc/+HceuuAKEuMcLNHWSTRWg1l0Zua4e5l+yvY6hulWK5uYmPEtR6iitLScSEA/oFGpYGtRPRNa/sn3HlvcK2+ffu1FXj17L5a6ru1UcbYcuxoa+Mgzz3LLU9ml0hYdVUnXXmvoVG18YnX/Mjqou4kKK0ks4A6OshVtPVuIVdT2SxtLddDYsIzVb80mdPiV0Ce4Kj3fSZqMGDgKSdl0lmqLfO0N38V/zY9pjVpMBD7w1U0kQwGeiZVSNGkBpdNehNDlBKUU587JnLtmWb+8FOKJe25g7kFHEzgKelQ5j/q+DJ+CT9ovMS1WeHIynzvgqMXW9TTtl08SoNgw+Nf//ICzluqW28cP3wsu+jEUFYEIq1Z/gxo+BnIwAP6ONloSQe4ybmHF4iv4xrineIiz2MeOU2creswqvvvmXZxw4KNQvI7XQm/wIWbx8sYPcT0vZvI0PdVJtI+QN6Z8TFJ+EBhPjIDP7WQUk3BK35BiZZDoqeDbr8zmmNrlWDMCdE2YRg+lhJP6HonfIBTOTjXgGFnNGdfaf1BYemBbNLohs81ykqD0i2Fz5Xi+uaSG1rOOY6QZUxZ5zLIpducstkvSTa9Ouru17/nTK2r5/dY2Wg1tzXSbFsUWOEY6mmMi9ZE26tqzN0fmxfjF5mYeau4iZgvT21uZFukkYFv8bdvVBHPmCEmm2rmMJzPf69tr6QmvoK7uHp6SzwLQ0n0odxs/RQIpUDCp22BidTZaZkKyhyJl0GZYbAsF8fst4pbrirCyFpxtx3sNt49H4jhWbxGw2rsouvxiiuNuJ6ijOPK+rUza5w2izccQ6uoi4EaytMRSlA4286FLmWUMKOIAFYk4KMVh8XoAjnBjyDe0NxGnnCLT5IrXXuz1m2LL4rjqdaRsvRbkVjmRLruYUM6qPvtG9MMxMWkRlXEkpZxKJ4wSP3NPOY+ugLZYL311LjfeeB3VVz7L/i29m/ZFtsUF76zk2mfaufidIKak2DjrCF742Kcx3lvFx56e0yv9KeuiHP6Va4iEl3Lu0vxz3hwbzrbcJGHRGt5EZ+cbhCrOpItsS8oMvk7Nppswjqxgoe90KpKuhesoilZ0sSp0VK+h36Zl0MM4ApvClLzVRldqIr72BJvLx1PlhAlaAWYccjg+v0PpZJOkWULROB0uWaKW05ko4+Tq4S8DMPMl/Ry1OjMy23pUKRMjhTs7qyKNjDM3EZSJfIuHmBZ1X9JmiI8vmp8RcYDp1e3wzbPhvtMy1xvJcTXFlI/ZDVv5fIuuZ1dHn+fk1D/4yvIX+fq7T7Ox/iAc5WdlSM+/cogcwLKFl3N16DUujr6dPY/RSVfctYTjcV544QXWJsdR7E5rPE7ilIi2yMUfJeqK8eSeTk66fhs/++s9XPL62zz18I188a3nIQAxUz9nvoBBNJKdKkK5o6IFG8MYh231tq7T/WHptVMx4ny47R1MV8gDw5zQbTiMKYv8RxsbOdPn48s8zjUl93Mhep6SRKKes8/aSKcbVbIlnmJcwE9ZZ4wrV9YC0ymq6MSMT8SKdfGtN9+CgJ5fo8wN5auNJbnij09z74s39jpnqqyY9bdMovuEcopSdYwjzH71SYqUzcbi1XS0/TaTttyO88W1CzmnuIYnS35OQ880PrFpM5BdcWZSRyelkxO0Jy221S7n6IMt4u7Q6ZCZM7GUnehlkXd2dqLs3kI+pXYZ0mcyo0BCMTm0hU58BNtCBHzawuuwK6kYypqeQ6QyEeesbYtoik9kZkM7B5TV4VcWG8wizKISTql+L+/vpga7SaFjmX/Kj9mbBg62N2UG6u2T0i+bKansS2dGqoVNZeNYfMjxAHxkxXv84a5b8A0QNXDFc9nzv738aT5355PY/gBl/3kq7+8qWzt46jtz+m1Pc37zRq4pmsL3y2y6kqUY/hK2sQ8/iV/HOHqwNiQ5ILmZM05s5SCmc6P8EYAPhA0Wl+o4Zn97kieil3LTJUZmxr6/xM/g1bqvEdiqhTXZWURZ/WJePn0lRcEqEuVH8lqrjy+iY+QNswhfqRZbn6+LgCjKt2N5u6Nf2UbbjQfS5ctODNXONCZEFhf8zaSuNylpqYZ9H2IaXRRTBBTjTwY54fU8A+b+tQBmjSNUO5e/cy11HJTZFfUXE4wFOaVFR6BUbGnjsX/pz+cAy+sP5/OXHYnyaUGOpML864ibOD8agw7Y6MzkUF8T0+PtNFbogVrz589n6dKltJ5UTiW6D6CSKNBBhV1GzJ/AMKM4jsNeS3uYtrX3S+tLrz/L7078AuOCPRxe8wqB41fRkJwG6Bby+Jokp/7nGiaF6lFT/MROSWFc9l18AQsnrDATYfDp2HHbdmh69iaqwjrcEsDvTrFsK4Vf+ncG7whjSsjPnFhJXcksnE6blys/zs/QPdkAiZwwofqEQVXAz9UvPUksVI0a/w1KJ9VhxqYQ6DQpb9vIY8fEcMShyjqGA7f8hOmLr+DsFxf2O2dJwuCQe7o5+erfc/bxy2ECHLJNW1kr99lMVXY1Mw6LaZ/hdKOLyKQ6amuOBt+CXscraoxRengSn/hQST8iVibsKmmVoJSeHqLh7TmMk1ngRjt0dYRw7GLEZ6LcztHSVP75YGZsrCOWWkrryin4jh0PPgjZJUwebArbYfLYvdejlhtgwQWygt/KL7nrym/qsmjcnPc346NhUuJjC7qJ3Sz7srfSVrA4Doe0N/C7ibOxzSOAIzm2Zh23PnoXWyoP4D/nXkTz1L2Yc8M3h5XPjy6v59J5c5lz7oWM29J/FaKhcO57zxHwTeSR92YTLa1g+bcOpeUEbS2GZTylDVG2BMazrW0FsQm/yDxZB29rx+hsZN2kAwDw+xWOk8oI+cup4yjdlBPr3WPgL9+C+AyIv060eCoTfEVEjApe3nYOhgn+ijjiBPD5w5QaOxYJ0S7TMp/bmM74SOE5hsrdFaimuyNAk26HZLG5miPDS/P/yFRsXPk6b0z+EgCTVCdBJpEoKiMWLWN6shN8ULy4t3V7fF01d6/5A//cp5gaIGEnoQherqzgro4ulvoP51DVxMymRmonayE33eH4LfEqykR/torDKLE5Pj6Vt6u2caF6nbh5Jb6W/gMKS02DT619g5tf+huVqQS8CQ2fHAefBScR5sN/Xkh50O2wbLOo+spPeGzlf5j+iU6qzONwAvoaksk2/vjwL/m/DedwSdEMLmt/nEm1ETrH78vNk++j5/DvMWnGkQXLeXsYU0Je9sxsqvc+hOLlXcSnOHBBdt/ly5ZzeUMl11en+MOUCLObu/h4j35olZOgdOJWIg0nkuy0cRyTh/bS7o5Dy2qIBGKc/nT/Dr00lc0GpT0WdQ3TyJnXibLYpl7fD3XdDAC+4ijn+lbRo8r5z4RTWFx8En/bdDsXr3iDA0MtvHHOKSjbhy0+0uaoYRaxqvNI7lv9Ne478BaofgK4Gkcsejotjl30AjOa1tI54XCWH/c5igs8xEc9tYqjWEX4rencd99v6Z42ns888iZXzRnaqLwhs8TIBpkp+Pzs57nl0h9ChWLSlvyLaEwJdhP0F7GNozLbIlRxxaKn+dPNer7oy4FE8csccUkbVz/zb0pNg5NZzRdefjbvMYfCV559gjnnXkhlZPsGZUxv3wrP30bafj3xx2v55T++zpQZ3XQWaZ9x2czH8ce3YpYeTbJyL377u9v40ova57561qFcdfEtOBN83L21k+v2DtLVuQiMw3qdR+IWvrIujtwoHFsf5gONf+fDK0OUPZpi3Ykn8v8SD/DptRuw/AHuu2QS6w8t7AoZDNv00V2UtciDMplxkcLhhxXulLgHxbUbzZdy2L8rRcuk1oy12Y+kwurYgkx0OHXDi9z+2N2kojNoOngyD15+MdPppiNUxdSa/i+QC5e/w+JP7kcNlbQHenfCPnf4x7l4/QJmpDrAcWic9zfqV63nZv9DXBvMzvseLNHC++Gww9tVUOILEkl1UNydP7+/eOG+XtNY7Pt8mMgzz1BSamdF3MVn2hxuRgkBkaKVvMxFlBjC2cXPs6Y5iqkCXPrMU5y6Nu362sppHUuoO/XyPVvI9z/iaNq6dbRKKl6M4zh0rr+AqpkrMRPNfGdlJVviG1m5pYzNVX7OzSwYEKdknPZbJdssxhvwtRc6OLQhybojTLacFuCY5QP7GSfFe5hW1E5nYhKgLZKKWBPBCWWUus24D0Q3ZtKX+VOcwRpetE/mlaqTiDVOgP+L8glzAZ94awGfee5F6g84mFlzN3NV5fPMPuWTKMPH/63+Brbt5wl1EZ8sbSVhNRMdv5kzZ7/LBxa+AsB+W1dx/Kp/D1pe4yKtvHbll/j9lV/n+aGOmQAAIABJREFUqjn5VwePVFZSFR14VZqhIqbi2idnc9fnvklJS/65KKYGu2liJhvcecoBgolJ3HbXH3qlKzMcvvXk7BHJF8BewS5QiqrQyCxk5VPwkZfW8osjP8V1Jdezz+J6JqxZw/Onl7BufJgPrVuVEXGAY+o3cuWKl3l8n/P4fUOU8xN/o3bLfwlYtwPl+Eq3UTRxCWbXZbx097Mc2Nb/JX3zm//I+WbzP7NbeOXEl/ulSzPvoOP4SP1qSgpM7ZBqr6B75mQqgy8xre2/1B72OyrDhUPkLlrUQ7TMz4ZLqqHW4pHf1TIxOojfN6nY55VVtHz7QzkbQxy3GqZt6mLGCe0U/7NAK8CBuOuC6Ax0IsBeQZM5nWcg9RYt/snsbXVyaesb7LNtDl/0VVGExdWdr2QOES7r5oB2H59aOJ/2ceOJHzqOxOZXKe3KH4qbby6i6Pevo/TLn82b3r9yH5xPbiFuO8yJTyVRdB77meuYVBHisgXzOG1t73BTFhu0+idxQMEC2z7GlJCXrH2eG2cvINpTSvNeU4ldfSKdaz9FcPNZXDhrLq82t2Eriw9vmcXHmrOzCuIkKKrUFuJeqxo5+9kFFLs37IJ3e/j+w4J/kOWsJsfDiOXQ3TMR2m2IK6wZFt+Qhzlf6SW8Tg2txGiC4ojJwWym0kiwhMMJWZO5ct7zkFN39mtqZb8mHS52G/dz23/v5919j6Z66v7sG2rDngUH7bOZ/TcuprI1xgH19dtdbtc/8veC+6IVFUMS8js/Aj9aMGgyvvfIP5h77Ee4qPrtvPuPq1nHOxzGZg6hIhkmVjqOs95awsSekZ82OJf9W5po/djxI3rMY1ZvggMVt/zpD0zu1pb+Z+f7eeDiV7nhsf6F9anqN5h9wUUAmKqYOZEAE+3biAZ+SvmsexEc7v/zkrwiXohPvLeu4L668XG2He3wlVX595uhcj5Us55n7vo9pabi9Q9/m0PqB56B83PzumGe7heaOGBKjdWg2P/5/POmnLBmA3QWjrdwEpDwuUPscTh/cYhb/9FEmVHD5TxPdFoFJWfEaZmkWxWTJIIJvFDZQVNRJSfFk/TUmTz5f42UGIqbSBCu6uJNtTdHdw49DHBSaxssejfvvuPefJUPXfMSxUWz+ejyf3DNnAf5cHAb3TOXM21FHqPBhKM7YtB/LNsOMXaEvLGRQ677ozs1ElADicub4fg7mGpP4JCuj/Oa0sOWZy5+CJSi2LQoMwwqEjUUBRwmdW3hnKfnE+hjoRQPYZXwSfEe4pafkx/YAvO01fLBubVU3Rfm5XEXc0X1Sxz5+9XQoo99IXMB+B13UTtjHw5qGTyG+6SGtZzU4LYMtqS3jvzaobkkygdfUR34/+ydd5xdVdX3v/vU2+/MnV4zmclMeu+kAEkgoRMQQTSgCAgKYuNRVHhsr+WxY9dHUBEQFRXFAtKlhmAooSSkt8lMMn3u3HbO2e8f+8zcOyUQIai8r+vzmc/MnHvOuafs/dur/NZaPH+ETZ0Mz+Wuj7zzsJ9P2rmNJT97nodPXsUFf76FZxtnsurxsUH/310C6SzcMkBJZ14rLUq6Y4I4wISDezH9gPyBQ0/QpWvgghF7BsPzOPvBTo7b2jrmsa9FHqrfwq44hwXypj+0ceY9Xx8K/q5cf/hA52sV9/lXycFuPXwAXkt5TN/QT8zIEE+6XHPz8GcTaUsS+WWSdXfsg3dYYAm2d+o8P0vyRDjKPXqYH103PCYS68sx4/ZHaXjpyDty2dkc3PPwYT9/6m0nj9pW0X54y6/3vseILlt+xN9/RCKl/Kf/zJ07V/5Dsm2blPX1UqpCmqN+MmVNsu386+XPzzxL3rRqifzO6avklpqKYfv0lVkya9iHPcer/aQMU/5m1dJR27+68h3y05dc9ZrP+6/+eWHixCPa77gL//XX+v/Cz29Wr5AV922U99zbKC/55iT5uXdUyXuWJGTaEEf1e3bGkfYnkPw38ncT//X3/Z+f/E/7u97zj+FfgQAbxsJUoT7758q8efPkhg2HiXKPlF274JhjYP9r72n5Hzm8bJw5k9nPHEZl8+Xb8+Hri2Hb9f+ki/p/XK5+/zpq+x/iiht3ob9B02/GZfDcYJ8OCet/BPP/M4X+LcRZuQTjFTT8VxIhxFNSynkjt//7JwRVV8O8Udf9HzlKIo+Az3rjbNj7j1UN/qfIYSqlHjXZVAZvP+von/fL19/EVTe8cSD+/jUFIA4g4KYZb8x3/Uf+cTHufQQ+8QnYOjZF97XIvz+QmybcdhuccMK/+kreFNKRKObR61uOeH/d9fjF0tljftZtw1Vr4O/VkDXg5cTRusqjI9vXHUm47bXJF5fAoovhlhlw+Slv2Ne8IfJ47eht/44L8f/X8vnPw3e/e9RO9+8P5ACBAO5vbidpvfqu/z+L1GDbpVM5puPViycNim2Z/HRBDQcLGs9sKgPzWii+Bq5XnbuY7dXwtbEr9/5L5OBUm58t1egtGBOOgH7z8McMyjMVcM1K+Fv92J93BuCaVZD0S9t8f75yVfwr5C8TYE9Z4NV39KXPgqcrR2+/b/yRPZv/yD9RLrroqJ3qzQHkwL1tj3HWW//VV/HvIekaHTmGR0RMMymzVbTcG3dkrfDMRIKdkV4mXqFM8ktPhfmXglNw+EWBGu7I3MKNC01WvwN+WtAO1AN+PBvua3jt91ModzYrK6BQfjITJr8P/u4D1LPlcPzyDJ/Z18GCS+Dn0+G3k2D1Opj2XthRNPq8g/KJFTDrcvjiMth2GIX+yRoYWU77uUpFwfxnyo2z4KR3wFlXjFan20Ow7F2jj/mfJZAroIlE/IHSE4QVF75RVwp/bIZ3nfH6zrEnduRW36EjI1sdkVxyGnxgNTw47uidE2BnhcXFb3sve8rqRn2Wmzsbpk0b46jXJkeFfiiEWAN8E1Xr7X+llF88GuctlL+3/p2/V736foWS1aD6w3D1higfvX94xtojdWpiLtsNV4/IzH+xFCZ0gnn0SpMACpCK03BGQRnr/7MMJh6Ct7x4+ONGyjMzqphd3I61KZ+8kLI1gqtsilB87OcbEkzfdfBwpwDgxaog4clT6OGvdIXgW4tG77NY6lxZ53Fy5fuY0d3E3RNe4u4J8M61UJKEpAVpExq6YMMPoeR1Vum8+HRoiypted5+2FgFG6oBAfMuBcODnM4Q0G4ug3VnDz/HhPfDlIOwOw5rX4Tv/hFCDvxuIny94B7X14xNzfvWgrGv7cezj4xLD5A04Yzz1LW//wn4zANHdlyh3N+gfm8JpvnNgjBnrc8n63xrITw8DiLXwJXrobJfAdFvJ8NVzkpO0x9jBhq2V0+z1ka76ODJWrh+Abx//T9+La8kx10ID44H3YXv3QmBV8gROhSE0jHGSNJUgLq5FD57HyzaCxMOk7S6ah3c2wjPfwemvErTnV9NUVbND/4AxhgxCVfA7ZOhKwTfXAylSVizFbqKTL7wcITpL4++iExAYKdfOcDx8QvKuX1pnL54DUXBOXzlhj3DPv/rCY2MJi2+dnndQC6E0IHvACcAe4EnhRC/l1KObhvyOuSp1qc4FIatxYd/wYOyqQy+vES9xJQFHzu2j1+0wP/+Hqa3wQMN8La3QGcI/jBJaRO/vxViWegKwJUnwXUPwvLXkNH+bDm8VAo1fdAehgX71N9/aIEProHuAJQnwdHU9w/K9AMwvR0erQMJfO+PajD32NBQkFW+q8zifStmctL+Slb3/YSlu1xaI3DOOR4fjbqc5gP5TxdarNwHJxXEUzoD8LtJ0BaBAxG4e3acJ5afRP9jPx91H9d4IZYKyWoMnrF1yME55ctoTx1kV0ZVhOsI5/ffWQwLLoH/fgCW7IGmgnf07fnK3O8MQn2PWiQfqYebfsuwRggbqhSIA2ysVj+FIjXIHYEN6WmwyS8h8tPZcPMMiGShe4QW99AYGti2YvjjYUIML5fCxafB/45o/XrZKQpYHA2ufELd009nqdgCwGePU6yfXV+HxIiE14wOx70TVm2Hz96f394aUaAMMJAZ4CNrK9kQSTK9XV33D/xEyaStrItCqdR6iGp1lHmtPGdnOdc+nS29z3CX/nc+txxmtsGxr5D3c8lpcGcLtIXh8w/Auo0K8P42Dt4+ojbW4nfD477C6epw63R419PD9+kIQsBRi+iXlqp5+JYXQJfKzfXLqSoYu8e3pAYX5mAW9n5t+DN7uA7C408D8QfOPQfuvAXGjai68JtJao5/f17eOjl1C6wdo4XBIIgPyqEw/HwmQI7lyRzTR5Tmufm4OPedFkU8G6dl12bWbXCo6h9+vitPgtZYO+xvh/2f4Gu10DQPLveJejfNgE+Wr2e756JrR6eJ/OumHwohFgOfklKu9v+/BkBK+YXDHfMP0Q+BXd27aPl2C1k3yycfHD7gR8plp8AP5jHKNAZAgu6pATdSIhmY2g5bStSLPXYH/PY2pUFndPjhXLh3vPp83n741p8hPkbRube+BX41wmLS3bG/80hFd9VADDhw1ySdkvoGRFsLW70/E0tDr63ud5LUeIEwAsFKXO4TSYpSStsxPEiZw59LTIbYdep9JP54DJLh5sfu9HjqbAXYDy1OcF/0QiZv2spdAx08WbyXtV3dfPvgKVRoHWzRf4Mnhh8fycCcVtgVh12HcWF8489wlZ8w5wo4+e1w94TX/pxei/z1p7BqR/7/C86EmwrKRc+TGpPQqTVP5IuOKss7oQOuWK8W3G8vgG0lHJEs3g33/gyCfs+FH8+GiwfdERIufxIueEYt9p9cAU/V5I8tDcQ5lD6yOjEflB9kbuw23t7bz6+jYT5dWsLEVDGbDzzCJv891fTAhc9APK2Co6e8DLW98Itp8JOxY98ID75wL1z1OAyYcPWJcMOIZNlIBv7nr3DMHniiBj6+cviCPySSUXO0RhSz2FvJvdxBl1Bp0HYOPvg4NHfA36vgL3NqeLvxbu7t+hmPJHYSycC7Nqqxdv94+NnM0ecFWLYTHvrJ8G17YtB8JWQOEzsQHnzgcTj3ebWo/ffx8PQIr4DuwjufVhbg3U1w14Sxvx+UBRt0YK/fbvh35/6OMyb9Y/6ow9EPjwaQvwVYI6W82P9/HbBQSnnFiP0uBS4FqK+vn7tr1yunAg+KlJJTbz2VP72s6hYHs/CVu+G8TSoSf/Hp6gW7+dpTR03K+mFGG2wvhh0jfXcSgjmlDXz6figdUJrfDbPHvo4VoXHcN3Bk9/x65E7CdHkW67QjK6a0cc0fmP2X04ZtK0PwiwPvZ0XFjQDcu7yUlSu2cevXz+KPMsgzJc8ypbeC8vaVFGtZ7hE38ph4Dfcm1QI1oVOZvy8dYfboK0mxhLWY3CBeva1dHA0n4/GRR5UFccdEuH0KIOB4qfOdBe9j8vqfALAl8FW6nc+xyNk1Kj5RIUv5Qc9SZsfv4S+Uc3//qdwV3UK/cS/Skyz0FrJePEFOOkxph5NeVgrBn5uHxyKOhkRllA/yQQKJn3JNZxe3R8J8qqyE7678Ls//+t1c3vPaqj8eDVmSXclm8xkOidH+kHg4znuTp2DJZs7kT7xcVsSXA93s6t9Fe7cqrxGUQS7iIur3dNHq7OYbjaO52EWRIir0aiZ217JHbGOH1864vggLiDL3oS28x++/cXcjnPE25Rb8V8nl8y7nu6f8Y8yVwwH50fCRH0b3HbFByh8CPwSlkR/pyduT7bx4MO9ATlnwvlPVzxsp04OLeY7HuDdymB0EWBGbl6wM575KEDZuxFnT8y4uMx7greKBo32pw+RUkqAdeW/A9b2jPWA1aLzYN53W2lOZ2ZQvtiXTLnW5evaF9nNGj0aH3koHCebKstcG5ALuLCj+d5k0OUGW8BFTssMd3Qfy1eRiafIZQvTg8BOZw3uVhf36+Ewu7NnIp48f/dk5mEw69jr6Nv2BzsQAe3r7iOpT+IpzgI/IzBCYJ/QoT6TWkXn0MXacO4tU7xwWWBkez76Tmoa9zG6bT+NAPRqt/I3tvFAOL5T/w7d2xDKf+QgEZtl06HyIRdPX8dWJK1lWu4ylV77I3659O0nrdu4Qzquf7AjkXPtY7p//ZZw9PyG483vsE/mpbegG1SXVSCdMcd8lrM5lWJibz/etrzJQUHioNtFCUczC6m8EYPvEAIlID6f8rYyDVQmulA+zE8mDXIWFBdkD1GbjLO1o4OGSnUPniYfj1JTUUDNQx2wWcrI2ns5MGGvfZmaX7+P0kyy+ujiL5cLz5QwhV2n2as41XuQ72p1H5Zkcidz9jrtZ1bjqqJ3vaLBW9gKFYdla4KjlkFVEKnju8uf4yOKPoIl/DskmIOLUidM4XtqH3ac0Vsp35tRyx9yp3FJVyWcaS3mLuW7MfSuMClx04oRYJo+yCvY65fHO0dG+GgQrNnyF0IFdtJWrZ/C73/6WLZnZ2J7NXw48x/nOE0MNbBdQzzgnOuo8hbI4+ApUEmAmIb5LgOO8WayQS7DkkVPuKq0ivl99LD8iiKcXMQmdr3H4dzcoxwSmcrscTX/QgDpRjwiX8Pfjv8DW8SE2NTWxYcpJzDqmmvd4l3BWoIi6sjpWhxdRZ95A7byX+d+i0+mimAnmfqQboe/FLzArqe77DKMJMRbVaIQcK3W012gk12lTOIZjALhsxY/goruoOeHznNhwIgBC1zlhi+R3hDgkI7xVxik/gmsqlJSMckJoCZXFlTRVNzHfrEZoJvGqM9lLlAsrJjC3ZgEtNS201LQQMcZjdl9CkRHBNdKUuNVcKxcTDUYJWkHqI4vRD3wWZ9clDPbF08MDBLPFVOYGaOlqYSI6qzEUiAOaX/Du9LYpzNHfQUmshHEV46grbUIIgeUaCDx0XZKxoiQbJiM0i8/LUl4uhecrGALx9zoLCbvHskAkmCvnjnHHR19mRY/lhKYTEEexucTRQMYngWYhxHghhAWcB/z+KJx3SMJWmC+f+GXeOemdWMbrI5OXxEpo5JtEvabD7mPmltOTKeH3hDjdHv1yhRAkogkSuuTA/mmUTwhRl1vAhJ7FxMPxUfs3aU2kDYdDoogP8+9Fhn+2azRdpgZByfRe5oTyzuOtz+WjXLavTUl/Nmi6zje7zuEdsphTZII/yiA7ZYTpxiQS0QTXB0r47cDhNcCgNLjKmsxeqlnvnk1ZroxzvfdRmTuN0txpXJ5bx0YZZpnXyCXS5E8yyPdkgIulSWn2v/jqtPEsjquo7kFLUfWuwqZfRtkmI1yVewsj/SGrKyLszBVzFia7ZYQaMdjFHa4uj9M7pwgn65LNZkAIau0wJ0xeiewJU6FV8wVHJx6OU5GaxGe4ikfLFjD/gHJb2KbDMu1ZmsR+QkJRNJqMABeUTT2sMlIhK7hOXssDhPkFr86tW9M3ha95ZVwhTd6areW46DV8qP14dB8Mk+1tUL8IRgTTdk6bzFNMowSNj3sTaSOKlDG+JN/BBjmWMzsvl0qTAIIaMYHSeClBK0gYl+J+l0SP+p4bDrSzfP+5eIfOpTizmP5tV+MmW4hrgw2abeblShlXMY6m6ibqzKnghjFyeTPFNNMI1yLSP5keT0Uic77zwHTTLCk9HQANwRxvIsW5izE6L8E11NwzPRMhJU0pdU1eMMyW2Ew6jUs4L3QOkWAx4UCYaYlqVolKTtY3EKvYz0pnDNrWGyCzqo9+htnrBnIppQNcAdwFvAj8Ukp5+Nqar0Omtx5Hc00zy8NXkaj+Gro/4G3T5l4Z4jovrxWaMkBxZHiUzdRNyuJleE4xddoHOFaOBl0hdcY7xxAeyBHBpcFtoLmmeWgBEUJQV1ZHSA/xxMPr2L9vCo88/Db2vryEmp4WTu17F4aWn4iJaIK6XC3l/UWgSaIcy8LABIyCCWYZFp9kBmXHPMTZZaeO7Nd7VGSpHqDIPXHU9pc6t4zaVikNdk1tpCuYN7RS2Qxlop0LxK/YFaigI2bh+cNnwDZI08RNuNyJwxph8kDfPNY9N4Hf7qviylSOCjRm66O15Gap8RXjeEoDJfyY83jc2outVVIlirCd9xB23oPnNTELnS/LUn5IkKVEuAyLHxGkyp1DXE9j+23sukJ5TT6MoBENUzZQb+T9J5WazgX1Ce7ujtN36veplgYPWJWcm/kYfUQ5uypGRfgQ+9uSpJKKBZTqOEB5WTEDXSqy2ZLL8dyO3dREigHBejmTqgFF92wLlfPxSd/mG94zWKgFzNSznF1ZzMTaiTRVNbFQGAXXqXM6p6N5Br/pOpONvOVV3+dZkVmcQ5RvEeR0FnNsr4Vn559v/wHVp7Jj7x72PP8sruuSy6kF+A+s4lN8gP6cchBLIMV4EtRTLw/vbW1CYye1lGTy86Yj2cjbH3uQc57cxrz095if/h7GQIxc90KakovAUAtosVTMAM0Nsj+YpwXVZNT7WiDyjUhMM4PwTLychSc1fuOt5oecD0CF3klHNp/wNiV3kFznMpzeWRi+hmtKE0/ohAvmd6uuKEST0xOoHrea8ZXjWWYEMTXBpeZfiDVvo7EzS6Xz2tOXz5AG9itY3JqmMS7eyMQDR9+3dlR45FLKPwGv3K33KEi6qRPRIYimajDnHs87Y9dhdB9gRfphVmRfJiEbSSZmcHzHr/hI+geE679K1g6xJ51E13RKYiVoXoK6hENL6AAn7V3CDdomLpWlJLVnsAiRzb2fx+wCwk2uFNu0FZhnUqQtm2+kZrDpmbWk7S7sbIy++BaEriMQLG47jRfnWBxyf4Hsm0+8ZDNVj0XAaiSgPchD7kLKzTiTyy1+vC9Fmi4ur6mhbGuEq/QfMj92iMZMDbcFdCag04Dgz1mX1u7XFyhd5Uj2lkL3iBhoMjfan76f6fyRlQAs4yZc18A1TGbILcQDHdxZ9W5qa29l+d/Ws5tq1hfFuLWrlMHS+0/MLeLAX2IY0sVMQ3skTpg089OzeNZ+BNdTROO3SoNfEOSOiI5hDOfl2eQ1+G6Ulj1d7CApA3zPW825+iOM4xCn6Y9zyvp95AyBh8ahwGhttltGmB8+ni91t1EkdlBbFaEtYDDgpfjWLSanBufSkt3IVY2/w94ryPiNvQ90DNB1cC/hKnD/dDM3P/hbYhPLEZ42pAJdct7l/Pp/f8CerI3ub0uLIPtrA6Q2l5FF+fotIwVmF7quE9SDXCPnYcpn2IWkXEziOarRPIs9zlsxWU+VsGiVo5scAPzam8J+UcJWr4Za/RBJXQVyHCM/nbtbFTD+9CPvQ0qPbOMUMvYgz04BXmevgDJwpY4UGulsJU3mVnYfxuLfyKmkmYzt5q8r59lg9eJYvRxKzwdggbOdgD6OGZHtPNBTA0iKPYeiQ7MxnAhOyXaUG8WlPhNieXeQTDxHbxBskUbTPIRn4EgJnsezZr6bTjJTz87+rQgtjtDLmOF04wV1vIogcZGkGzBdk4bcHvqybyFmPIYhHTqFUsQ81yJrT8FKb6I257CKv6FLh4e0EpA2U7sSHCh79eYjxdFytNorsdq+S4Vdxcb9yiL8hnccN4mdPC+2E7A0SkpKCQVCDJJKdDTmukfuNjxSedNkdgL0hLK4qRomB1RyT9Y0CesJQv5qu0tWcmvRxXzIvo0UCU7adizfT+aoLaulqqSK3O6Pkdx2NWEjTVRLsleW00AP53sTeIwwN3nllLnDqwtls6povRCC3xzs5oa2Q9S4zYTTZejZFuxUOWammEhvnjcX0CPEQjEi8R4MTyeWKQfHxhQKrDQvhNQ0ZjodRHUDIQQpUcUiHqVG302D0IiFYpToJj9oO4TV+k1Ks//1up5dqVVKLHxkr7unMOQhJZmMAoA4fTxR0cKyY6aDEBgT9jGz8jGyts4+8pSTjKURE4pcm/ZMykUPYZFhSjFMqJ5AdUk1d8og7/Xm8Sd5HJ7WR8ga3lhCKwia5bDJSp2QyJDC5r70ci5LfxqAd+qq7rvpSNJ6gL2hGPtEGff5vmJQQB63epknNNZgkCxXE8nUB0iLTnZ4TQQ8h5mHDpDBJmOp59TZnSbXo7RsM91HqjdFR6oCKxfmp+0/4gvpz/KbL36aDr+LfZtUfV+SPWosPJzby0KepoXt1EW3k/PyAb5nvXmcjMnlWNS5SkPTnQi6a6NJwbuMhjHfTbUUhBlPH2Guyb2bO91FvChVkNDRC4D8UBsd+/YgpYeQsgDE89LRp/bX8Wg41MR9nZ9k4iv4beOU4qETyY1duOVM6znOMp8nIz0qenRyAy7S18jjwsV0oggEAjD9SLThqEVI83z/t/T8/03q4qvQRN7dE+qvw0tOIaeVYMffjRk+DTKVaMviOC0xijXVkKOkeyp9eyK81GcT4UQme8PdeucOFHF2Xz8X9vYSIIfj67NSmhzf0URT0XD+ZYUUfNX5CJ+s+whF077N6qr/wp52C0bZqRiNn+PETJ5CGPeK+erBd3Nj1wdYEVtMKKCeuxACIQSekOxPjN0G8fXImwrIa8VaBnZewYxYKzHZw7ZgI/3uAH2GelhbvFrIQiqrTMZ2WUyJm08z87KlIE0iWpqo1s8eWYYmJJM0lflTKnqJMVwLWjvt95wUjHLKXpMGx2FROkOobTEuEDUGEGgUdU3HyubdOLbmd80OHGB8dwJDxJGeSVhTC1DUVYM3rQn6/Q4ocVdlp7i6IO5rrB2BBOeFPgsYhN3l/CQ6dp+/ifGJNNc0U11SPWaCgSahbdpcZmhHVm0tWOijzeikU+p6A3o/eyPjiSVUrvy+6iAvtUSx9SyZAt+/a2houpqQmQIC/eymnZiGSSKa4BRMaugiJnO0bz4VwxlOyrcK3sPkHf3skQrsMtiYussu4uSkSbO2b2i/LixMy+EesYSd5CtHdRPBzOncyUruFfPpj6iJu/TQJjZGunhRTqSHKKG0R7s3TnW/Bjr7sgQ7W6nbm6K8sh8pDLqcBGYuRr9XSn+uiM59ezD8fpWdvp/d8xtmj09uYzYvcD53ICx3GJc3r0pOAAAgAElEQVRrYKj7J2SzlRQdmk20pxmBhu3BUhr5sBwdT1nrTOdJMYssNvOsA3zRvQDfgCBXAOTJnkPc9qmPIYTG5Oapo84D0OOM41C2im6niqSjSOsNrxBkTqDcDuHc2O6HIi1NTB8gh41mJumy4LRJdzN7wvO0mAUc+BzkNAWusZQaS8JTbiEpBJ5jkkoWMeBKBPkFKNQ/DitbhGaobC8hBD2ygk84n+Wr+qeIaGqh1DwTT1PvP3cgy15X/a3jULe/iiuencWnDnVS46h5lvGdmZ5nEvAMzqpZS/myJ2lZ+jeeDc3lV3NrOUbOxM442Ikl6CWrkWYJ58hbyIbmMK0tH8hPeyZPddzNfdZDRLNjP8ucNral9XrkTQXknicZF8kQAGwvx7bAeO5oOY+fV57Kk9o0fslyxICDSLvUFHkckMUk3MJ8YXW7EZEiKpIckGpAtmgqfTYkMnw/8NFh37l/52KmvnQ2s/ZfDsCO9Cy0XETNycjYJNSAlvdV1nSEMEJqgIXcLJ/km9RnFCilhcZzqMpNwdxkXr55OtqGtYQ8NeM1LcIjTQuHzvXwrLMpW3w/5fpcIhJiBPg8ARKBOmzTJhFNMLl+MrHQcI3pjNxKjo1sotI6fGPdQrELgLzxKUi+oPoyhcI96CKOZQ7PgLE1BcK/tCbx1Az13cLPh864eXAxTMGkbIzvHlAaSYXoprVzLa67gO5Dw/2GNjlu8a7jAa6i4cCT7PaBPEUAU5cMoHFQKCvgYLHFVnsidwZmYutpctIkVcBa6ZZhzM440jN4uqDpc71zgLiWxNEkD6Ke8353qAcVPf29BLJ99G5vZEXZdsoSLiDQc2riGq7AtAPMO/k0NM8hpwmQGq6jfLOentdus6aGlIKpHWvItK3BLrA4ujMtmE4UTarxZLk6XW4xX8bm69KmSQaoklW8bd9Cxvd+ksGeO1O0XayyXibgUwmllv++/p4DpHp7WBAsInr/8LoC7+cGqg5Oo7TsLdzW+V1ac5OHPqt1x2YfRWVwiDUSzh7ej6y5Fo600a0ky45t5KzSO7ii8QcIL78oyQKGUzSprGnNU2PO0TRa11/EcxvPYkdy6xCDR5Mewp+/mpHPyuk0yqjLtlPpbiLgL8A5PUNVcz5w2dc9AUO6nJjYQYrh6cJpL4RjqOceqlZzMZxpRwgDieDQppMp+a8Qe+Z/Gy2txvnL0QhCepz8Uhsb7uojMJBmI1N4QTZzSDbgmho7q5JYI5IEJibHsWbDTI6ffPRoh4PypgLyK1c2s67xCTzHpFfkB8PTsYnc6a0iaiUx2gcQEhY22LTJYoqHtXVTo6I0B1EtTY8fpS8lD3ARlEtg8KiOvkb698+mw23kkdyV/LX7Q6Rc9UKt4rHZBUE9D/DRbohUKo0/6ZWhS4+QP6h/WBSj05+UMVlEst/hnt3b2JpVwaCEDCETNjKgUx1upYguNLOIaOxz9BHjCbeJa6RFhuFmc21ZLbfIIP8jbVZqV3Jiv8rNih5h8kOhRr7Jnc5OqQa4HsgSjJYSCuVbx7o5QUhLoUmXrCboLvKDwrokkFgFNXmXS84QLPZqWZZSLqYIKXpcNSlT2Qjv5wZmdCp2jI5LKNNPQ+Agi6a/NATkhnCxhFqc26VaNA6647lr1xfp6JtP6/OLyUmLNHltyMEkIdIUyRR9spjejji44IUkzdndeFqOvzOd73kXcH86TyHtOLiZXuq4k1W8TCN1ZQ5CehhZBdSGJyitH0dRRRVazg/meSZkFNC3nJmPa6QDGh3PzeHEjkmc3z8cLDsywxlUpmPT6lYjEHwAmz+11fDnXxVzXMcSTCfvaqglH/QTI5oGO5l+dNej5LEn6ZkyPMgck/04boKtZWo+dDp5V9re3NiFnMoKiARGbnRyhZGNkWhfSFHHbFxpoRkZ4kX5Bd9zrIK/o5zdsYqoE0Y4aqxpPjslFOwg2aYszwPVs4YAyiTHojMb/ZvNf3+mL0G6TQWyL2hazoKihTR2zCTVn4c23Qtw8sBOpk9bhtDU83M8pdX/uP1m9pjqfZWUq3Edzig3n0QgM30IKTACaayUUsh6TYtKWvH2qnMdyOzjDlbzS3EqGiGqlxWxpeVDIIdnOxfnojTkLqKpZSZHW95UQA7g5fbiZgJc4XwLXSpNRMdDIKg0O4caHK9ojnCI+LBobmZJBZkl5dT3JbBFjh7ykyJVYMamsNGAtLRgiEMiaE+cTo4ot+aeBKC4bGzNJFxg4oZ7bGL1ihmiF03BwSKSU0BwWyzKLyrVwmF56lpcqVGzZwnz+qewSKoJnllWwXWLvkyR378zbQRolQkm+ZZE2gdyzz+vJjTOlgGuxiZk1uI5Ngc3nUHPc2N3Ah8pgQIQfA6VsTOVzeRMQX1FFVsezVddSncECGhpIk4SUVA4RdMtkDPY237V0DbXELgyby283Bgi6y+mobKpJOihzvcfumi0pRR4TEvsZqGfuBSSaWxfA/1c9q10yzAvpWbi6ANkNRfPteggQV/Buz0j8CJCQJ3Tg4bLzi1LaG9rJBkJUe+2IX2TvF0kwMvfe+vuR+kV6h1vLDqDHdoE4nYnms/s0D3BuBlziJdXIH1GiO7ahFM6IxOmX7y/nr7Wd5PqGD90/O+7Psbe7BT6veEprQEZZ6BgMY0fSGO5HhsmTEHz8qA8TcuTw4QzIpPVgHozQFtFGbumNgBQSRs2GdrDyg1Y1xIHAftoHDpsyowECW9EkRtgvpcH+0IrCyDaPZGizpnono3u2UhpohkZgnbe5SDdQiAPs2TXGXzvxS+pSw12IdwgUyfezfjKJ9BM5euuSGro/oM0pcPcNQ2E4hKhFSouAbT+8znu2OdYPuubXH/sd7DdEP1dGeywwbTlymXUP+k97DBVBnN7Zi9t2eu5sf3HADwfLMFzBZZ/vaFsHsi9TA/bauqxzQxWRztxqdgCDd5uNu/Yw5/2/ohDZl4RFFJHtwfIhKfgasPjDUH3jaMev6mAfKCnm6KBl/AckwkHsnwWFQB0fbCdGMhrQDPKIrg+xesbbQcZv/M0ZNhARkyCAyaaZwxp5AB/8eZzozyBP7CSe1H1SjNYGORdM8WVCoRealSNUxvGjw3kcTL0v/xxBvZcytk1l2LHVcBMlkzDkQHC2dHBIs3NT1DbifDZPVcwIT1As3yJs569F1N30AeZHIZgh6d8i2lh4fiT3suobVLqnCH+D1/JnYNmekjPpOOFU9G7j6x1t13glshi08ROzuFPZE2NWDrNn7/zNXbcXcO+R8txcxoBLU3M6UXTJamOBrq3LaOocbDEXX6ISSHQ/EDZRm8Ce+ryE9KIqRhBzLeO+ojyP4EL+fmeOexNF9Foqca7L/Sfiu2/kw1yEu/NfoxnczV0lT41dC4VvBL8jLOGgp5GLoKTsljNQ/TkSti8dQlPs5zyqnKk5mJKFykEeoErTliQRC0m7V6U/ZQTKM7TfsJl1Sw661zKxzehp32etBNEOgZudrjWmszln2m8cwZrvL/x/ASN9X3nU5gcrekQEVXMIc/bz6ZMLl71UZ6aMgWBwEhmiYVaiVpdzEymCO7ajHAHlRrHP4+GlZE8cPwK2nvqAckl/IKr+T7PVCj30fKJpYRiBh2ZPJA7OZelmeFtkXTN5hjyRc4dXC5sP5357YqlIqThhzCH7gKhORhGnv7n5vILpJuNsCXj8XC/etZ2fC/StTAdFeTWLQXkZsYbZC9i+EpbIGQjxHDT0gqa6HoITbOxQvlFpqg8xLHnT6SkJkxfJsa2jQcpqgzy+9CL3NHpMuCp+StEDs/RMK04wmrE7ldAXpfr4C8zZ3DpNZ9XMRtTI4CyJicc2ov0JH25ToqL8vEOIQ2EmeTj8r+py45wF7om533u6Gvj8CYD8s59e9F0iefYtD11IStaLsGWKdblfgLAqooHOH/Sr7l20Zdp25yhpijAdlHJyoEUfbnGoSDW0sBNIKGvwCXRJaN8R5yO1z2bInp5kIX8QZyAUVAMKlqiBuPyF5UZ21CnQEk3hz/GiJMlO7EeOWMG98+vRLeV1m0EajgUjmBmh/PXg67N76otCKoKRLauNKZQLs2n+ATv3vhDAJqyKuGkStvPFqkCOD16Efi+VS+jNLtk5HxeMsfzbXctASMNUsMKGgS80cyFkRLwbMJkSJAHrKjvbsqaGqmDSqvo2RGja+ty3HQYS8+xtEIDTbDr3k9w4KkLCJWNXQM46JgsTn+L87KfxHPyE1K31aBvYO/QtvZYA4+7U9g8UIEZ8tiRmsOLyVOJiHxgND7I2xWj0yG3M46HWEh5bwXFHXPYkatlR0V+0qW9KJmAsnKinpqgegGzRLMgKxQAd/b24Xoe2X3576kIRtENg2AkSsBQ12GH1PPJ9av72VsVwNEFU4/PFy013BDTGxbw7Wmreai0oEIXEIpYeFYRzUa+Jsp1Uy9iX6QMxw/ShlsHGFfyOP0Bg1jOxBjoGwLyCAoEM2aEDTMKQUOg42HgcXCX8tEmqiLESoJIN6/QuNkwswZOoEQ/Edu0iQRi1EaWUGzk35VtZzivYw31SeVy07yRLGYdhIdl5QkAzkCBmyUbgQIFyYq3gtTY98jn6N5+DpqZr3Nr+FPL9PcPRkePYSuY90Ubpobmo38opt5FpDhAf1eagd4sReVhMDRkQRxLkzquq+E5gljlWYik4MPy81zTewu7i2N4us6Ulm8QKp7EAh4DoHb7Rvorx5GNJZg8Zz7Ctxw0z0QYKaayiXnZSr6/7VoW9Cl3leXpFBW/cobza5U3FZAf3L0HN1OJmwmj6wFqKtZwA+/g7O4/cS6/JxfLsbL+IRpie7j3L7s5vSHKealr+VLuPLYZ+VJyVuVLGDJHXXwfadQA7ZYRQJCyo6RLMtzPMWylYUwgH5REdZiZK+pY++Hpw7ZHclnc2jC5SICL1k73B6ZHx64gz7WU4mSH+yyDXgDNBS2+nD3TV9HmqoHcnlORftefA7GeFDfLs2kytrLeU9p1Bg3XZ7wII0lp/Bs0JKqZmlVc2KDPz7aC+hGlvYe8MAn7IMWh9iHtLorimmvRGg5uV9cktGKMwGran7uG8gjMLHJxUnnNLtNXMfT3Pq+I5ydG/PMLWikhg0WmJ/9ONKEGuE2ONdzPWudObr/yOIKxOLuTcYQGB90JeBgcm877hqvcsYewKKjmGBb96CKD5x7LoWcuH8ryNHCGzN+4f6+edYiXHlmNzOrUZNW2RisPqpkdec1TphW45LIu7/zY5wgMVNJco8Az26eAfHNzhAeXlDBnzXAtN3zRF/Dwa6sXbo/bOJ7O0zWTeQSVVfyC2YBbESA3pDAYSEfDtSAnA9iBBnRPfTa46O4JK3/vDKFcUs2ZJL849HVSXpS+/XP87woTKx0OjLlkKYZrE2cVzTXNNFTWEzAroUAJtoI5brTvp9QpxcjGsLThi7b0bBAuwYKEstzACOtVz1E/VW0LRvLHpw5ORxYsDKapHpDhc9fNwOjUF8vObxNCYAfV/4NAbocMsimHVG+WUNRUBpBWQEmUATxPw8m6hCJBck6cOTxF2GznYFDdeHXtaVQ0zeYcbuUb8jLs9hThojoyNY3MX7oKnTyQDxonuyq2snHfvTDkdtPR9TemRMebCsg3P7GDQ89fzUDbfEKxMKZZzJzZtzCx7FpqZYIuPa9Z3FVygIP7dtMXCvI993TwB8Q4uZ0dE8IY0uW6hV/G8P2jPYSRUjBghGgLNAydRy8oLhQpygPh2g/PQQjB0rc2U9EwnMUR9l+cg4mtaQghMYI97NucIdXRSFqO9J0FOSYYxIraRIXDwdIObtvxJXp8/qtTKvGERS6lBmZc7+EBbxZ/c6fx6+KVeNmZZDsXkz10HF2WQRHdCN/UHwRyO2hgvULtmKFr8cKMm/cwlXM2DKXgD2p5Xs1Mkt1+soRQz0I6ETwyGD1tpJN5RkimO0//+5m7gAMVan/D968Wu4JMd36ie47Ng4sTbHQrWMTTTJA7aamIctqiFjr9nmvS77Zc4sAxXi/T9VbCh+nAHJYDQ3+HRBLNVouRQCNxcAHF6QADhHD61Zgp9rW4/tg2DrrleO1xQv57mhh/hqrKSprH1aMPMYoEmaR6z7f89+Pc+qmnifa2UNNQDgKy/cPNar1gbLYsVIucRAWACyUUt3BzHn2xGja2Xc1v3UvYtXwyuanFOP6tCmHgOho7ykrZljkGPXYSUVv5tcMiieEvSsX9PZwl7+ITXE9310l0OA1DPv+K2TdjGEFipXlfvKZLMj21GJ4Obn678KzC0AF2RPDRT3yMlaespbhzFs3zh7s6pBcAzUMr0Hq93AhigOZw8mUzuPhry7AC+ZML3cErcMNYfraq7bOgTGv0+zYDw8HRtNX/eSA3SffnSPXnCMYsPvShDyHECCB3dZych2FquL7LJam1IXVBpPMnAJSPbyTTblHGQdJdNkWNU7j22mtJJIrRfcVBeBa7i5Qban/oAJ2lMUyfgitH1xI8avKmAnI7nAcHy395xcULia14F9FP34NWUG3ok4u+xszmrxIO+WaaIfhS4hE+7n1W/TsiSaBbhjGEi+cEkKm89mBoeRPQLvC/VTcf3kSKZNQx0q+r0dLyKeqP+woAXduOA+BXW/8P6w6qEo4aGhFPEI0G+NExq4hNWkguluBAuQp2uqUSaZTi+EGyEr2TAQKsy32cPZEpCE0j03YGXraCdjtCsdtPZ05dQ0mgw79284g08qAXRtNcNM3D82MPuRKNTRMjWPEJpPv7KaqsQoiCwI2WItj0aywzgm6phaNQ2w4aeVNZugHW9duc32+T7s43zcylNRxTw5rkWxCmx7aN7Wx+shYI89fsLHJ+gat+t4zZbpa55l6cw+SvREU+U9QNZ9AC+QxW3bMho66/f596j8WR4XVGnt2zlA67Eg0XM9jHJZdcwupVqxgMfofiFumkg5SS/q68qycUNQnF9CHXSv7+1HHTj69lxQV5ul/WB/ITzp/ItGklxMpCODmP+soahLS5qWotBA0wNRyfzrjgzPNomL+CznbVUUILgem7DXXhDnHwS0LKPdYaybvynmpSc8iO70fTApTV5dkogbCNTM3BQCC9QuC1yAXzcytQbGBZFpMWVvOWj85j2dqThj98LzCGq2v4izJNF93UsEMmekHrHqE5eE4BkIeUJWcYajwb9miN1hyxbTDQPEwjT7tITxKKWcRiMfSCBUEWaOSGpUFALbRduy2W7niMyRllkdVUVvHy78fRenMVbtogVlY2pGGH5GCyn8kCv1prTk/jBUIY/iAd0Ed0FTmK8qYC8vpp+axLwxoj8WXEpK4KtxMOKs1MGhqlmaewfA2u1PcBp3z/Whqb8lAnbi6AVjCQAkae1hWMqoEx/fgx2pQXiJVSGkqt7++tq13HmtMfJV4eJOu7HLbO/AZBPzqf1AY4tLefytIQGxZPIVIfJ13TSE9QTbJss8QMTyenq8lVbuQzw86aOxHNN22lBp6mE8120qUp/6RIKndHrCSAgfmqFfhCXmSIYVDnF7HsHydpqwgQCNaR7u+jdvI0TrrymqFjhOYRLB3AzYYIFqnn6qTz4BHU88/QcwJMLo0QBtJdBUCeUe+lP+rXy8DlLz/YRDaloekJ/rqnkWd7lLug261SJizgGCm0AhZF2HcDTStg+AXs/GIcqX6acKIXz1Euhb5ABOGaxMvyriCAfp8BdAG3M2CbaLpOrKwMxCCQ27iOR++h4ZPTCpkUlYeGaeT9+6ez/vcqWFs+Loru5/J/pbkc3Z/cdbPLOPaKmeiWhpvzqIupeMdAwTgfBPJgNEFRcSX9rdPR7V7qTm5n0GJXQK4shaim3CwPFq0YOkfKz2HQ7T6E0Cgbpx5UrCyIHTIY6MliSJAFGjlekGwofx3Vk9T1C01QMT7muzLyYKxcK2pMLl3yGPPn3jP02SAjxSiwRDQz/35ySQ03nXf3xMrV9eb8WMUgaIuCyW6N0MgHrYzBfQsVsME5bBTGtWQQ19XJZT0MS6e4ejzP3zSBvY9WEiiq5sa1PwWgvCSBdDX2ptU1lVTnx0w4oK6nJbYdq1U9i/O6T8CsGEdFSs3Fotzo2k5HS95UQJ5O5rXokeYUQHdqdFv0WNDvwySA/sfB55HWGgpkd/nMib2yjIZoK54TxE3ngzRa2GX8mmuZedZDhGIW6z63mGVvbeaVRGbCfEp+jM+Y1w9tG/TdSX+R0IwMLT4Xfmr/JLIph9kn1FMbsJhUribxlIp84kNF9dvJ6Gr/gJ7XAGeNq81bIv7grhrYxbQ+RU0b2K8mcbQ0qOpUv4p7JSgjQ6btOm7nSm4kWKT84qHQeNL9/QQiUaRXoNH46dZOOoYdGUAICBj5NOeAnn9vnmNjhwyKKsOkO9UiYwUNfBo2ybB6r5sGVuevqVRSkW2nW1cTp9ctR/hA7hoDCM8m0b6ABf1J5rf8mbPWLiYcyN9nKKLhpNQkKp5wH6FYXuPsNYLobpBgYjiQA6zibzSwj15TAYEVCDKkkfvaXuvW7mHHhKIW8bIITqrIv1+TvQ+/n82Pq8W3UHt8e00Fa4K3oRnpIbaFYWp4rsTz2T2ZAs1x0J/uOi62GcZJFRGueJFIkclg5oMlMkOulTADPDq5nDItH1AdXGB0W7GDIsU2x5w1gVPfNwM75GckCzkMyIUMkCmYb+OmDefBC01gBY0R29SYtO1yYvF83oEwFJDrBQXUGhouGPrbcyReQS2S+kY1pzsD6rfpL2yF4D3Sbz77BLVvokZp84VAPvjeCoHczRZz4L6v0L6zF8PUaGhuJjdggicorW6mNFjqf2cQaViYjlJMKsrzOLFq8XRsMhz/ntOILFestwAmtcevZv7APD6/6/3MSr4xjBU4SkWz/lmyeG0Tm556EKdz/ChzCuC0lT9h8/ZH6e/48NC2psrdbByYjVsVwiaDZ4TBZShw1FZuszE5nUk8y4nV7Wx9dhVOOorARWoO8YopGLHfECtTFMJCn+LhxM2GaeZlTDm8+mLhgNKMDDWaxa1bvsShjM7zQGmtGngLpk6moey9vJx6ivQ2tX9VtI6c72e1fA23yO5G14NomgsY4GtstX27MbuTrD99FeGHXP+61eSwpE2Ww5t4IS+K56SBXm7eNpNZa06npaWBbKaNaGgOTjZDIBwhmy4ofeBa6FoGNx3DCndh2jrp/jz7o7DysOfYmLZOvDxEV6ua1NFEgFzatyqE4MXGKI8++e6hY8qmp9DMJOlkBCTkZBjNL2Pg6VlMJ4TuBdCdCC9vuJb6VDF1gbxWFynK4GYUMNpFe6EjNIydorsBQpXjgOFFOytp54mSMnKFbiQfyMNxte3pe4Y31Q3GTIJREycTRUpwUsPHwPDAnM68ExcROGnckJY+yICSuQogi2M4RFM5+oJhlbkpwMl56EYINxNFt/soCkWotqJ0DYSZV7GBHX0KOEUwzYa2Eyht3wl+Rmu2vwKQzFv0I/8aBLNPVMA3OD61oEAU1ODUZAA3ABdxGxGSaNbwjlLqWJNsqoC6qR/G8tP99+bkx2AoWsFQCwO/JsmgTJg8Dv4MyZRa6Y0xNPKRWDBuWgmXfeu4oWdpB/M+/EEgFyJ/jJvJM5kMS6emKk+1LKkp6LcHBIMR0n2dSN2goiRPMW04/gKuWe6AbtBcei25Z5M0nXcpfYbNgBlh2kA1z1r7eKPkTaWR92cddFtxPM0xXCtF0XIWzjyTRQv/irBUynV1oBVnajEyYSMAK6S4r62VeY3A0S1OHn8PQaMEpOIAJw7Op6R9EaVlijlQWXn6K19cwbh1s35yjzuiol8oP6A0I41npChyo3iOTaTYHjY4y8vLqQnmNZ94sBJX+GV7fY18Vtlz6HoIY9C1omuclb0Vc0ABvWNaBPzyrrES39x8FY08JKNDGnlnNkR7n6Cq8kzGjXsPmQHltghEIuTSeS1bOjaeY+I5QayQg2nrpPoKaHyGxrY/foGOF9cgHRvTNigfl+fSF1WEyGXyzIWt9lRyOZMVF0waep6G7RI3CxKOClK+B90svW4F2YEytj7ZjxnKT7K65gWMX3Ez0doNGIE+wvEYoiCHQHcDhCvyEzbcNx4zU8zexiwvFVey76HP84dvPY2UkuMvvEw9T39B79hX0HkXBRSBiAWeQXnJ23Czw1khIy3J8Y0XUTUuHyQeHNcDnWoB+Kh5HdahD+Tv1VRAjgzhOUF0u4+q4jjhsjJivRMIBiroQlkftpnC3vkCrS9vHjo+11+GFdApSSxgpAwCuYgI9IJ4kyZtYrVnU89+EvRg6KMzOwuVFABhjA3kg0lj4aKCTNEC7Vj4QfT5p9Zy8deWEYmFWb58ORdccMGw51MoY1nnhZTgsVwrsqDcrFdgfRiWRqI8b53VFtBVAYpKlbUc1CKU2SNSpf1EwECgmjkLfkagrJTp0RDCz2fRzTeur9ybCsh3dwxgBBSQjxX0GJRwuJHKmgsBKOXg0PYZ079HdaUq6u7p+VvXfSqSoauX5KTjaNJE8yyCEdWvsrwsb+qPJed+YgFLz2lm9gn1Q0Duealh+1jDNPI0mp+enPGgpmV0h+LiQH6wa5rFoUoV/KwMH+Rj87/O2ybdjq4H0f1AkIbHWv12HD+wdmZNObXj1aQepE5avHLAM+jFcX33T3lDEwe2bhkqwZnu7wNMtmwI0rYzn83muRZuRl2rHfJGmbpCBMglSzn43Nl4TgAzoFPTkg8W22HD1+bU5B8MlLb2X4jQHNxsGCkqEAVJNoPgXfh3xst/bhbUm6luXkhJwwFqjvkBuh4iHIujFRT50p0gweI888jKFFPUNR231qGsrAOZC7H7+U6+e/n97Hph8JxFrHxnPmg5KIapE/RrITz8wxXsf+LiYZ+PBTqFMgg06+9Q5W81M4Um8wqBYSofuuP7kQ27D10PEDAtHGyMYDOzjWcJMUBleA9u2qDQ8M4NFI9ygwzKoNu9LdwAACAASURBVKJhxHS0AtqtLgPES2finfApek+7jkhk4qhjZ59Yz6xVeRaSpo8NLdIvplY2Lr9wFsa7BrM2A+Hg0PWsWLGChoYGgKFr95z89RVaOWNJuLgg2W5wDnoFQF5QzdEwdSLxOKnq8fRPmMG4xPB5GS1TwB7VX7kj1tB3Gzr3FafYp3Wwv/qNY628qVwrmw/0YcdaSQK51Cv3HCyLV9DKcCC37Aoq7AB7Ruzb2tpCXek+YvG3Al24BYG6VN+RVSorrY1QWhtBSsmCM2p58KGrR+0zyG/V/297Zx4l113d+c99a629t9RqtVotWbJasixbi7G829iAsQ0yY0NIWGzGARxgZoDJIXicIclMPIRwkskJJId4Qs6BM2wJA2OIIYPNzuQY48HGKza2vMmbJMtqLb1V1fvNH++9qlfVtXZ1VVe5f59z+nR116tXt1699333d3/33p+jEEORs30Pt39zH2eWibunU6GnFjQDivcTpAmzud9fvccwYvnMGkN5GIZi1xvexdS29fzH0yaYP2WMY4dniQUNvmqlIKa8PrxsjMMPX0Fq1ZvZf/df8bOvfIF1p+1ADAMxhzj4tAIKC+h62cI+nYTv1RQRaUXqzQ9huyYDo0lE/Ilj0zSCUI1/omemB8HI4plPYjgnyM0nmT38geJdKhNRCiWSj5fPRN6H2AAEvcDN5ABm4EW67mri6XhRJaKZi2MnIgUigbefnTGRXPEE1XOP+jFx0zKY3LsGyzZRnuJ7ny+EZeKpwOvzIHOiOPbulMmDjpLoLS7jHhz7KO989i4+f/DTGLkpHOcmshkvmBD0MN0TmEYcMyhIkqFJLjn4Wa7K/pD9sYR/U5doGmCyog1hYY0z7GAdy+GpOIbMYCqblJvAOO8jlG9gC6eeNUL/6mQ+1CQlQn7xe3M8/uvPMrX/Wo4DdkR8i88X/3G50ClAMujlMz+bY2yynwO/fqWoIKgcvcOReH8Qtpk+XtCP3HxkdBDYku31b+yDvcXff2rAz2hLra9/cYjU5n6+e+8v2LLm7NobL5KuEvLHXjrGaX3PcgQ4enCm6rapuP9FJCnkE7tO+WXaZ2Z66Hn0YhIXj0GQzbJ2Sx/PPXqU8W2DZV9TCRHBsmJYVg8bJj5U9FzoDZhB/PDljbexac9HWbtrVdn1+wzD4rxzf4rnzQevKx7S5jAxDBsriDtKIITjG68gebrvvTsxi6GxFF6Q/1xLyPu8VcwemeHlh/046OjWy7j7tq9z921fp2d4NSILX69yLirIHHHi5dLBCuGFXMZ/XkT4vb+9BBHhnu88SS7joXImYubITg9gx48gQbl29mThOxAjg8p74wqQvPDOe5EKxcQI/oJVgNuDZQUjBmc1TvB6Y3YWLxbDJo5hCBdmHuK+E9fm9zf7igsUJpyjmEHJ4abd/gUdS9rMBc5FvEp3skoCFZJIF4T8hr+4gFjSZrh3O//zX/1Vg0zbYPZEhl/ebgAeZuwYtt2Hta4f7n4C8+I/wHjwMxj4lbjZOZPBtRs4GVk/pFxRDcBpF6wl0ePw5MgxrP3PcOLktSSSX8b2YqTqWGLRiMTFjZLCl1XrDV6cepCTz1yz4DhYdvXQSJRoLccVH9jB0w+8TN/q6hXLIkI8bTM3HZ10L3jHuciKR2GYZ9++fdx77724bvH5nuzzPfTkaP0rCZ3dm+RHwCq3db1WukrIT18bxzH8fipb9o5U3da2C0OiG9VfM8Lz2PY38qJYjCBnvaVo2Ds83sPVH9m1aFsvuvDeBf8Lh4pB+2qUmSG5e2G2RJRYrNDAKG0XC3ko3HbgkYt4xOPjJBIbKcUwwmWwqodWer0hTjxX8LtWbdjF84/cAcCxQy9h2JsWvMbLOnmv3LBOFHlbACpXbHc+FhvcvMLhci4bxzJPkJ1ejZ30C49Me5rpQ4WlwQY27OflJ/yhfZinn4+XRyoCv/ulDMaww6lzJ8AwsKzAI4+N+AUvQOrFw6zdey0njvtCMLn9XB75caRb47QFLAx5+XYV33jXbStc2OF8RDlqhVaiHnks6Z8vGzadCv8Km/o2YdkmT91fGA3F+p/GtvuxgjYQOWXhBiJ13LVwYqdw5Ydv5h9v+UXBhgo3k/RAjB2XrOOlZ36DJVkyc7s59vIOBmLPkbJqF5OFNzeA3mTxMehJ+6nD8fg4r+AV2VB6LAEsq4JHHgmT2I6Zv5HW4l1/ei7KWxjaECODimTJhGGenTt3snPnzgXbT553IdPHpjj9tQuXTazE4KDviAwNDdXYcvF0VYz8DdsGMJ0ZrrrpqXxXs0pEK+ku4MecKvsxjDimWf7uHR9cVXSR1fKcFkOyzz8JS9ZQqJtUyQSSEaScWUF6n4FibO07q67OXcsj780NMDc1AWSxHAPbXcXF734vPcPBBRNpWBSmgHk5Jz8vgDWF7RafVl62OJ4YnfSFyHE56X+nmekB7IRfyGTYs3kPfOL1f8zgmoJ3nlS+m+nMLRRbwWDw0F42x/wbt1JBgyZ3JD9h9jt/9BcMxcaxAnvNc24o2sfE9kuL8uGjREWrlFiFPvVAPjulEuXOOxHhh2/7IV984xeLwgj9m76PYWaxrHTenlzG41ebR3l0U5LnT0wi9lu4+9tPFu2v1rkdtx1syUJOIR7YZEk7dQh5xIsu9bJdd5hLX/sEqSA/PjNXyHCJJW12X76ebecXnJZKHnlpzni92K5ZNDew54oJ+tfOI2Zx18jwXKxE76oRLrnuvQytW1/3e2/fvp3rr7+eHTt21N54kXSVkGez/gSbbdeeaBARBgcvYmjIX3vSMFxEBMNYOLx5xzveweTkZNGkSbnZ8WbpGaxdWVmNZIkIhNWVTjBZK3hYdvWig2rVnTHPwgmyBlL9Fn2rE0wdmmH3lfs4++q3Fb0nFARLZd18CbaYrywQCi9T3iMPWT3h2/zUnb9PZqaXzHQaK3EEEQcjspanac+Q7iuMNm6Qr9F/eHd+wYFStmyZY/P7/bmKZMIPNQ0PvS4/UZ6b98jM5/IjiFJxjiVW5/PPS6k0mRdy3SfPLargXLOpl/6R2k3LRIRLr9/K2/7TWUX/H4oPkXbShQlJ22DVzq8GrzHysd0ffPERDg5u4sBonLkp/+Z76OniZfRqCrnjYEsG8RR4CosMcbP24D0aWjGt8jezs67cgGkbjE0Wbr4iwt6rT2F4XeE8qSTkIsLuy9fzxvefXvb5ejn7zRu59P0eEum5ctn1W9m8Z+kXRhYRJiYmqjpYzdJVoZVMxh9u20598akzz/gHDhz4EocPf39B68somzf7E41FHvki7/zVSA80J+SjQxfznedex+ahXYwf/lQ+XGDnhVwVjURK2XPlBF/9aWUxWZVJYbsmmdkcqzesIpvJMT3le7QDo2E1a0HIe4biHDs8i5eJEXf8YagTNxeEVkpbuoYhg5BUZLh87JnXAML6TZex+7z/zHceuoPjQUNEw5nGtdKAL0wDTGEFCy0MjgkvH/CHzq+7YRupPpfRzQWxWL/+9xgdfRux2CizR/zXP3HvIY6+NJ3v32GWjHgO7x9i6sndZY9VJaEpfKYYp+wa5u5v72fPFRNsO380P09Ri8m95ePyUJiQTPa5RHUhjO0+99hRRoe34Kx9iNxc+fOtlpDHLNsvKsr5Qm6TIVZaNl2G6I2wkpD3rU5w42cuLv96Oxo3r3x89159SsXnGsG2ehHDr7i10yfYUuW4dzpNeeQi8lYReUhEPBHZs1RGVWI+EHLHLh+3LIcb82PpoTdfDafFoZVKaV/1cv7gAG8489O8acyv1AuFvNcqzGRZFUJHAK+5agNnX7owdSxky8xI/nP3DMaIJW1mTvhCvnZyG3uveTsbdp4DwK7L1+c9zvGxm+hJXorlemzddkve487Hvkv6r5d65ADv+fPzAZCjfnhjbOM5OM4AQ6uCeQrxMKw53Hj5G1VyoCA067cPFYk4+JWE4XxDGEp54EcHePm5k/nPXCrOLzy4ML0wv78KedJRnJjFdZ88j9MuWIuI1Ayr1ENY3FIaAojaHgvWsDWCBlmUeILVUncBEqaDIxnwFOR8j9ypw5ssFvLGr59o9kq10NVSYdv9SBCWtJ3WecvtoFmP/EHg3wB/twS21CQTtGa17fpnjNOp8GIsbrVpmilyueJijqh4tyK0AnDlB3eQ6nf41WOLe/1FA2mmpoJy7iATY4348eScMqt65CJCf7xys6+NsyPkgvzh9GAMT6l8haYYBue97Z385GuPcejZFznn6lNQSmEYwv5fTnH42RP0j6RwnSFiST+jKBxq5+aTIDlQYe+Lhd5aosdheDzNwaf9G26+gCm4uRrWLIZh4pTM/P/O0Ac5svM97D/+esA/P6p5c7Dwuw2FrVQ8jr7of46r/t0ZjG7q4xe3P8m93/OX7VsKUV4MoUeeHoixefMfYhq+152dL5zfKuOfAz0DWzkC+Uk+wxA8T9XOnLEcv19LTiHKj5G7Ru3PW3Rzk0zlDSsQ/d5qjXiWAtvuy4dWynVV7CaaEnKl1CNAS2M/UTIZPzWwESF3XX+45DiFGeMLzv85huGSy83kq66gOO5ZKzd1sUycHtixSCEHf8IOYM0aPyVta8Ivbx7bcBDTrN4HpsetlAkMI/OD2P0mc9NZEr0O87NZsvNe0BUu6IQ4my00LhLBTVocfta/IaaC0FEYOw9PC28+gWHN4WV8T7GcRw7QvybBoWeOY7tmfj4hzHkWyQHGghz1fut5nDM289wv4vn3NCqVhwdUErJSIfc8xeTeEdafNrjAbqkj1NAKwknEeNpmfN178v9fv32QPVdOcM/tT6GC3PfsrD9iC2/GluPn69cSctewsFUGCbJfbDK4dXzeomMija8Ub9UZWlkqLCudF/IKkaCuoW0xchF5H/A+gPHxhc2t6mE+cwQRK++J1vm+nHXWbUUrv4eiXm0/tWavl5NYbJSLLrwvn1e+MXWC33/959jAfkzzdVVf2xsrP3nnusPYEuPS67bxL3/3ACMbevMCMHsyQyov5LmiPGQ7ZuXL8ddN+jfY0hi4l41jxqbY96EzePhnL+YLo0oZWBN4kkOxvCjkb6iiMAwn7zQkBgsrCdlr9mA6fiqQ6Zg1HYvS0MLRF4OOfGXEI/pZy3XcbDfzQa66W3KMTcvg7Ddt5L47n2X++CAHf/QRzGBiO4zN549pjaIk2xTfIw+qJ20ydTlr0W1S6YUpsLWItpZth0dumsm8kJdLgewmagq5iNwJlEvavlkpdVu9b6SUuhW4FWDPnj2LqlXNZF7x41oNjgB60uVXBq9GO4Q8ldq26NdGb0KWm2Dr3H0AVUMrUNkjj8WGwTQZ29LP7/6lvyZpWKE4cyJDqt8Xhfm5XNFcQij2u9+4njOCEu28kEe+J8OcZ2zLIGNbKhdYrds6wMM/e56t5xXS0PKhFcNm6+Qt9Pf0Mrl3hNTmf4I7gm0Sa7Hsp/xjUYcAlG4zHVTvlovLFheuLP/wOxxtRCeIo7gxk+cfHgAWjlrDgpiwOVslbBEc5vMtxcNuio3Q03tq7Y1KKAqttCFGLmJEhHz5v9tmqCnkSqnL2mFIPUxuuYXcppO1N1wCanktzXLxRQ8UdWBrhpTlBNFhKubJh1QS8oTbB06xlxdWKE4fKwyTo6EVKHiIm3avzhcdFQp+Cvsqzdctx6r1PbzrT88t+l94U9h+/hZWr/aLkS69fhtP7N/MPWf04qoEp0fS7+q5x4sIhiV4WcUZr13Hxp1+bnO5cEmRkHeAR77r8vU4CYtTzypfSObELU5OlQ9rmEGfluHx6iNaWwRbRVpGL0LIa6VnVrIvpF03zUKMvHVVl+2gq9IP/fL36t5Et1BLcBvalxFZxNis3ma3kpCnnD7MkrTBsIru9s/+inXbBrjqQ2cwP5sj0bPQGxxYU/g8YYx8/fZBHvm/LwSGNT75BTA2OcA1f7Cb1RPFdvf27OSpXptUyhf3ML5q1Bm7fvct5/LC41M1KwPbMQHeCE7MYtfrKxejVMuMeutNezh5dK6mtysiOCrS5ncRQm7WmKcoRzRG3g6PHChkrbjNpQYvN00JuYi8BfgMMAzcLiL3KaWqtwnscF5/w2l+m9AuQgIhN80EItUvgP5Y+dTNlJPGjBefzGF4SSl45qEjvPD4VBAjL1xw+z58JkcPzhR5YLGkzTv+ZC/pwRi/vutZVM6qyyMvh2EIIxsWxvUHBs5l44aPsHbt24FC6lq9nmCy162rvLvVtQVLTaWJZBF/DmJwtD5HyIpkecW9xkuRFzROa/A17ZpMlqC9hePWXmegk2k2a+WbwDeXyJaOYHOFIWsnY0hByGuxsX8jvVYPU9lotZ/BeO9GrJLwemmK3eEDx5mfy+JEvNSxyQHGJhe+T9jIyLCy5HIWGIsT8koYhsuGDYWmZOFQ3Kgjv7sWg2uTvPycH8KLeuSlnQk7kVSFuR3TNhqaW7KkUEJvSuOOTaK38Tmm5ZiDkOC8dNylGyEvB90d4dcAFBrX1yHkIsJvrdmH7fnVcQYWfZs+xqATw00vnCiNCuORF6YXZK3UwrTCyaRcjS2bI4xfNzskf+9fXcg1HyvUtkWFPLkIcWo3lSbpGz0uVmQNzsV4x5VuKFXfMzjW0fL9VhN65JbTVVHmBXS39RoAxAiFvHrGSsh4fA1rvM+g5qY5LZHm3tFVxGb+kXR6YXLSWz++B+XBT7/2GIefPY6XUw2FGAwrbFbV2nBVOFFWK4e8Fk7Myi+k4f9d+KyVwhadROlNNtHjMH1sHi/XWKJY1COvFa4r+/pFzCeYpsFvf+Ls/LKE7WBk9BKOPT3btph8q+hu6zUA+UZg9U6gOoa/vqdBjPAUcL0ZBoYWxoyHxtIMj6fpH0nw0lN+OKaRDnShkIerGLWKUDgWky1RSjQEYRetsdn5ucZD60r62oSNzRrcj1nkkbfvBjYwmmxrdtDgGr/jZnSN2W6k810MTU0sy8/oMI36Jmxsy0JZ/ho5KmiOHsvNMjhYuWK2f00yrwalTbGqkV+GzmqtRx5qbD09UBqh1Atfu6U/v4BvJ7JucoDf+sOzeHH/MX785UfzYZFGeweZEpH+BrzVvVdvLGoX0On0DfvOz9Sh6gvVdDpayF8F2JbfP0VRn9cbeuQ+oZBP09dTOTYZVl1CYx65GSyYbNqtvbjD0MFSeORR0iWth6/+yMLFBjqNobE0A6MpUAo3afO9v3+o4V4iRiRrxTTr/753Xz7R0PssN2sn+0kPxNj1hvr7i3ciWshfBdhBD3LPq294GLMcVCB4KnCzY7kZenoqN9Tqjwh5Q1Wvoafc4snOsNIx7IvSLOe85RR6huJdEU4ph2EI2y8a4/nf+GuMNjKKAigKiy+ik2G34MYt3v3fzq29YYejhfxVgGX5Qq5UfULu2nbeIzeDoXcsO0u6p7IIRkvCB0brm1QFyM75r3NTszW2bI7+kSTXffLcJWut0O0eWkjY+bDRlXWizQ7NLs/oWAnob+hVgG0HoRWvvgq8mGXnp7mN4Pp2c7PEE5VLt6OeaSPtC7KzfjzZTbZWyIF8PxhNgXAkdebrGmtUlzMKwt/qdhWa5tHf0KuAMO3QU/W1DnVNJz9xqYJhc3r+OJZdvZfnlR/YUbTWYj1kZ/19uunG25pqmifR4/DBz7224ddlImt02rHOz59f6WghfxUQdkKMxaovSB3i2ra/+guQjZnYap5ktnYzsokdja8Cnp33hTyW7u70rpXGrBPnt7d8nYneZzjmvGm5zdHUQAv5q4B4fIzTt/8N/f1769reMe28R55xTQa9V0C1pqRg97UP8vj/ewWrczP2NGWYdWNcsf4nANzrdXf5+kpAC/mrhFWrLq9727hV8MinYyYDHEHlWpOZMDhxkpPGFzEM7dV1E3OxgnhbjhbyTkdXdq5AbNvJLxpw0jHp42Wyc625pxviu+JL1Xtd0x6iQm4mKy8PqOkMtJCvQGKWTXbCL+We6bVJGVPkMq2JfVj5HHc92dlNzMUKKaZWqn1NrDSLQwv5CiRmO3ir47x92zTTcZME08xnW5OZ4Ni+CGSzx1uyf01rmIsXerbEbR1a6XS0kK9AXNv3vqdtB0+EBCeZ91rTWN+2/f4t2eyJluxf0xqybqSS165/sXPN8qCFfAUSs11EeRwLBD3BNLNea4ppwmKlXE4LeTdhmYU5k7Q7vIyWaOpBC/kKxLLjmOQ4avkXa4KTzEj9ZfeNYOvQSlcSswrFYW4DTbM0y4MW8hWImA4mOY4FF2uC6RYKue+R69BKd5G0XJ5lnG9wLa6hZaLT0XnkKxDDdjE5ytG8kJ/kgFe5F3kzWFYPyeRmNmz49y3Zv6Y1JC2Xj8t/B+CGNi2ErFk8TQm5iHwaeBMwDzwBvEcpdXQpDNO0DsNyMcgxZflx8eyDAxw3WpNiJmKw9+x/acm+Na0jZcUBf7EFd4l7vGuWnma/oTuA7UqpHcBjwE3Nm6RpNWI6WOQ4afqTnc7sHPOOboykKZC2C1lMTpf2ZF9JNCXkSqnvKaXC3ql3AWPNm6RpNablYFFoYmVMz5KzdZRNUyARaY7j6tBKx7OUY6Z/C3y30pMi8j4RuUdE7jl06NASvq2mUUQs7CIhn0G5uquVpoAdmeCM6cnOjqemGyYidwIjZZ66WSl1W7DNzUAW+FKl/SilbgVuBdizZ0+ji3prlpCokIvKYcxkyCZbk7Wi6U7iES88rmPkHU9NIVdKXVbteRG5DrgKuFQppQW6C/CF3O994jIP8wYxHVrRROiNrNOZ0kLe8TSbtXI58AfARUqp6aUxSdNqoh65wzzZnEVKx0E1EXojN/ZuXYB6JdHsrfazQBq4Q0TuE5HPLYFNmhYjIvnJToc5Mp5ddOFqNFGPXNP5NHX1KqU2LZUhmvZiqwyI75HP49Cv0w81EbSQdxc6+LVCsVXBI8+KzXBctyrVFNBC3l1oIV+hhELuMkdGXMZ79eIBmgJayLsLLeQrlFDIbebJGg6nDg4ts0WaTiKmM1W6Cj3DtUKx8h75PEqZ9A/1LbNFmk7jYxtGOLtX1xd0A1rIVyi2V0g/VFi4SbvGKzQrjY9OlKsD1HQievy0QrGCFjmumiFnORh6KK3RdC366l2pKL/Io0+9Qs7S3rhG081oIV+hHJNeAHpyU+Qs3TBLo+lmtJCvUKbEn9zs8bSQazTdjhbyFcr6zFMArM0eIGdrIddouhmdtbJCedPxb3NB6gcMZA9zv6urOjWabkZ75CsUQ8EaXkB5ApY+DTSabkZfwSsUpfyvPjmdAVMPzDSabkYL+QpFKb+XhpEF09F9NTSabkYL+Qol9MjJgatDKxpNV6Ov4BWL74V7nkHS1QVBGk03o4V8xeILuVIGPXp1II2mq9FCvmLxxdtTJn2x2DLbotFomkEL+UpFAiH3hJHe4WU2RqPRNIMW8hWKGL6QK8+gr3fVMluj0WiaQQv5CkUMf4JTKYN4UodWNJpupikhF5H/KiL3i8h9IvI9ERldKsM0rSUUcs8zSGgh12i6mmY98k8rpXYopc4E/hn4xBLYpGkDkuwBIP3KSQZX6WXeNJpupikhV0odi/yZBFRz5mjahTu+HoD7x7eR7k0tszUajaYZmk4gFpFbgHcDU8AlVbZ7H/A+gPHx8WbfVtMkPY7BFPDLiR2IyHKbo9FomqCmRy4id4rIg2V+9gEopW5WSq0DvgR8qNJ+lFK3KqX2KKX2DA/rdLflJiH+4stzuMtsiUajaZaaHrlS6rI69/Vl4Hbgj5qySNMevFkAHE8LuUbT7TSbtbI58uebgV83Z46mXeS8GQBu2nrKMlui0WiapdkY+Z+JyBbAA54GbmzeJE078Lw5AHqd5DJbotFomqUpIVdKXbNUhmjai5fzQyuGGV9mSzQaTbPoys6VivhfvamFXKPpenT/0hXK1q1/xnPPfZnenp3LbYpGo2kSLeQrlJg7wikbP7rcZmg0miVAh1Y0Go2my9FCrtFoNF2OFnKNRqPpcrSQazQaTZejhVyj0Wi6HC3kGo1G0+VoIddoNJouRwu5RqPRdDmiVPsX9RGRQ/hNthbDEHB4Cc1ZKrRdjaHtapxOtU3b1RjN2LVeKbVgQYdlEfJmEJF7lFJ7ltuOUrRdjaHtapxOtU3b1RitsEuHVjQajabL0UKu0Wg0XU43Cvmty21ABbRdjaHtapxOtU3b1RhLblfXxcg1Go1GU0w3euQajUajiaCFXKPRaLqcjhdyEXmriDwkIp6IVEzZEZHLReRREXlcRD7eBrsGROQOEflN8Lu/wnY5Ebkv+PlWC+2p+vlFxBWRrwXP/1xEJlplS4N2XS8ihyLH6HfbZNc/iMhBEXmwwvMiIn8d2H2/iOzqELsuFpGpyPH6RBtsWiciPxSRR4Jr8T+U2abtx6tOu9p+vIL3jYnI3SLyq8C2PymzzdJdk0qpjv4BtgJbgB8BeypsYwJPABsBB/gVsK3Fdv058PHg8ceBT1XY7kQbjlHNzw98APhc8PjtwNc6xK7rgc8uw3l1IbALeLDC81cA3wUE2Av8vEPsuhj45zYfqzXAruBxGniszPfY9uNVp11tP17B+wqQCh7bwM+BvSXbLNk12fEeuVLqEaXUozU2ew3wuFJqv1JqHvgqsK/Fpu0DvhA8/gJwdYvfrxr1fP6ovV8HLhUR6QC7lgWl1E+AI1U22Qd8UfncBfSJyJoOsKvtKKVeUEr9Mnh8HHgEWFuyWduPV512LQvBcTgR/GkHP6WZJUt2TXa8kNfJWuDZyN8HaP0Xulop9QL4JxSwqsJ2MRG5R0TuEpFWiX09nz+/jVIqC0wBgy2ypxG7AK4JhuNfF5F1LbapXpbjnKqXc4Ih+3dF5LR2vnEw/N+J72FGWdbjVcUuWKbjJSKmiNwHHATuUEpVPGbNXpMdsfiyiNwJjJR56mal1G317KLM/5rOq6xmVwO7GVdKPS8iG4EfiMgDSqknmrWtopI9mQAAAlRJREFUhHo+f0uOUQ3qec9vA19RSs2JyI34HsprW2xXPSzH8aqHX+L32zghIlcA/xvY3I43FpEU8L+ADyuljpU+XeYlbTleNexatuOllMoBZ4pIH/BNEdmulIrOfSzZMesIIVdKXdbkLg4AUU9uDHi+yX1WtUtEXhKRNUqpF4Ih5MEK+3g++L1fRH6E7zUstZDX8/nDbQ6IiAX00vohfE27lFIvR/78H8CnWmxTvbTknGqWqFAppb4jIn8rIkNKqZY2hxIRG18sv6SU+kaZTZbleNWya7mOV4kNR4Nr/3IgKuRLdk2+WkIrvwA2i8gGEXHwJw5aliES8C3guuDxdcCCkYOI9IuIGzweAs4DHm6BLfV8/qi91wI/UMEsSwupaVdJHPXN+HHOTuBbwLuDbIy9wFQYSltORGQkjKOKyGvwr+GXq7+q6fcU4PPAI0qpv6ywWduPVz12LcfxCt5rOPDEEZE4cBnw65LNlu6abPdsbqM/wFvw71xzwEvA/wn+Pwp8J7LdFfiz1k/gh2Rabdcg8H3gN8HvgeD/e4C/Dx6fCzyAn63xAHBDC+1Z8PmB/wK8OXgcA/4JeBy4G9jYpu+vll2fBB4KjtEPgck22fUV4AUgE5xfNwA3AjcGzwvwN4HdD1AhY2oZ7PpQ5HjdBZzbBpvOxx/y3w/cF/xcsdzHq0672n68gvfdAdwb2PYg8Ing/y25JnWJvkaj0XQ5r5bQikaj0axYtJBrNBpNl6OFXKPRaLocLeQajUbT5Wgh12g0mi5HC7lGo9F0OVrINRqNpsv5/0vseK8xiljVAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot evoked source time-courses for all vertices within label\n",
    "plt.plot(stc_evoked_label.times, stc_evoked_label.data.T)\n",
    "plt.title('Evoked source time-courses for all vertices within label')\n",
    "# Note: change in \"sign\" even within label\n",
    "\n",
    "# plot mean across vertices (taking into account the sign)\n",
    "stc_evoked_mean = np.mean(stc_evoked_label.data, axis=0)\n",
    "plt.plot(stc_evoked_label.times, stc_evoked_mean, 'g', linewidth=5)\n",
    "\n",
    "# plot mean across vertices (take absolute values first)\n",
    "stc_evoked_abs = np.mean(np.abs(stc_evoked_label.data), axis=0)\n",
    "plt.plot(stc_evoked_label.times, stc_evoked_abs, 'r', linewidth=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Functional Connectivity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [],
   "source": [
    "subjects_dir = '../data/sample_subjects'\n",
    "fmin = 8.\n",
    "fmax = 13.\n",
    "sfreq = raw_av.info['sfreq']  # the sampling frequency\n",
    "con_methods = ['pli', 'wpli2_debiased']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Apply inverse operator to EPOCHS\n",
    "lambda2 = 1.  # regularisation parameter\n",
    "stcs = mne.minimum_norm.apply_inverse_epochs(epochs, inverse_operator, lambda2=lambda2, method='dSPM', \n",
    "                            pick_ori=\"normal\", nave=evoked.nave, verbose=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reading labels from parcellation...\n",
      "   read 34 labels from ../data/sample_subjects/sample/label/lh.aparc.annot\n",
      "   read 34 labels from ../data/sample_subjects/sample/label/rh.aparc.annot\n"
     ]
    }
   ],
   "source": [
    "# Get labels for FreeSurfer 'aparc' cortical parcellation with 34 labels/hemi\n",
    "labels = mne.read_labels_from_annot('sample', parc='aparc',\n",
    "                                    subjects_dir=subjects_dir)\n",
    "label_colors = [label.color for label in labels]\n",
    "\n",
    "# Average the source estimates within each label using sign-flips to reduce\n",
    "# signal cancellations, also here we return a generator\n",
    "src = inverse_operator['src']\n",
    "label_ts = mne.extract_label_time_course(stcs, labels, src, mode='mean_flip',\n",
    "                                         return_generator=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Connectivity computation...\n",
      "Extracting time courses for 68 labels (mode: mean_flip)\n",
      "only using indices for lower-triangular matrix\n",
      "    computing connectivity for 2278 connections\n",
      "    using t=0.000s..3.996s for estimation (601 points)\n",
      "    frequencies: 8.2Hz..13.0Hz (20 points)\n",
      "    connectivity scores will be averaged for each band\n",
      "    Using multitaper spectrum estimation with 7 DPSS windows\n",
      "    the following metrics will be computed: PLI, Debiased WPLI Square\n",
      "    computing connectivity for epoch 1\n",
      "Extracting time courses for 68 labels (mode: mean_flip)\n",
      "    computing connectivity for epoch 2\n",
      "Extracting time courses for 68 labels (mode: mean_flip)\n",
      "    computing connectivity for epoch 3\n",
      "Extracting time courses for 68 labels (mode: mean_flip)\n",
      "    computing connectivity for epoch 4\n",
      "Extracting time courses for 68 labels (mode: mean_flip)\n",
      "    computing connectivity for epoch 5\n",
      "Extracting time courses for 68 labels (mode: mean_flip)\n",
      "    computing connectivity for epoch 6\n",
      "Extracting time courses for 68 labels (mode: mean_flip)\n",
      "    computing connectivity for epoch 7\n",
      "Extracting time courses for 68 labels (mode: mean_flip)\n",
      "    computing connectivity for epoch 8\n",
      "Extracting time courses for 68 labels (mode: mean_flip)\n",
      "    computing connectivity for epoch 9\n",
      "Extracting time courses for 68 labels (mode: mean_flip)\n",
      "    computing connectivity for epoch 10\n",
      "Extracting time courses for 68 labels (mode: mean_flip)\n",
      "    computing connectivity for epoch 11\n",
      "Extracting time courses for 68 labels (mode: mean_flip)\n",
      "    computing connectivity for epoch 12\n",
      "Extracting time courses for 68 labels (mode: mean_flip)\n",
      "    computing connectivity for epoch 13\n",
      "Extracting time courses for 68 labels (mode: mean_flip)\n",
      "    computing connectivity for epoch 14\n",
      "Extracting time courses for 68 labels (mode: mean_flip)\n",
      "    computing connectivity for epoch 15\n",
      "Extracting time courses for 68 labels (mode: mean_flip)\n",
      "    computing connectivity for epoch 16\n",
      "Extracting time courses for 68 labels (mode: mean_flip)\n",
      "    computing connectivity for epoch 17\n",
      "Extracting time courses for 68 labels (mode: mean_flip)\n",
      "    computing connectivity for epoch 18\n",
      "Extracting time courses for 68 labels (mode: mean_flip)\n",
      "    computing connectivity for epoch 19\n",
      "Extracting time courses for 68 labels (mode: mean_flip)\n",
      "    computing connectivity for epoch 20\n",
      "Extracting time courses for 68 labels (mode: mean_flip)\n",
      "    computing connectivity for epoch 21\n",
      "Extracting time courses for 68 labels (mode: mean_flip)\n",
      "    computing connectivity for epoch 22\n",
      "Extracting time courses for 68 labels (mode: mean_flip)\n",
      "    computing connectivity for epoch 23\n",
      "Extracting time courses for 68 labels (mode: mean_flip)\n",
      "    computing connectivity for epoch 24\n",
      "Extracting time courses for 68 labels (mode: mean_flip)\n",
      "    computing connectivity for epoch 25\n",
      "Extracting time courses for 68 labels (mode: mean_flip)\n",
      "    computing connectivity for epoch 26\n",
      "Extracting time courses for 68 labels (mode: mean_flip)\n",
      "    computing connectivity for epoch 27\n",
      "Extracting time courses for 68 labels (mode: mean_flip)\n",
      "    computing connectivity for epoch 28\n",
      "Extracting time courses for 68 labels (mode: mean_flip)\n",
      "    computing connectivity for epoch 29\n",
      "    assembling connectivity matrix (filling the upper triangular region of the matrix)\n",
      "[Connectivity computation done]\n"
     ]
    }
   ],
   "source": [
    "con, freqs, times, n_epochs, n_tapers = mne.connectivity.spectral_connectivity(label_ts,\n",
    "        method=con_methods, mode='multitaper', sfreq=sfreq, fmin=fmin,\n",
    "        fmax=fmax, faverage=True, mt_adaptive=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [],
   "source": [
    "# con is a 3D array, get the connectivity for the first (and only) freq. band\n",
    "# for each method\n",
    "con_res = dict()\n",
    "for method, c in zip(con_methods, con):\n",
    "    con_res[method] = c[:,:, 0]\n",
    "\n",
    "# First, we reorder the labels based on their location in the left hemi\n",
    "label_names = [label.name for label in labels]\n",
    "\n",
    "lh_labels = [name for name in label_names if name.endswith('lh')]\n",
    "\n",
    "# Get the y-location of the label\n",
    "label_ypos = list()\n",
    "for name in lh_labels:\n",
    "    idx = label_names.index(name)\n",
    "    ypos = np.mean(labels[idx].pos[:, 1])\n",
    "    label_ypos.append(ypos)\n",
    "\n",
    "# Reorder the labels based on their location\n",
    "lh_labels = [label for (ypos, label) in sorted(zip(label_ypos, lh_labels))]\n",
    "\n",
    "# For the right hemi\n",
    "rh_labels = [label[:-2] + 'rh' for label in lh_labels]\n",
    "\n",
    "# Save the plot order and create a circular layout\n",
    "node_order = list()\n",
    "node_order.extend(lh_labels[::-1])  # reverse the order\n",
    "node_order.extend(rh_labels)\n",
    "\n",
    "node_angles = mne.viz.circular_layout(label_names, node_order, start_pos=90,\n",
    "                              group_boundaries=[0, len(label_names) / 2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(<Figure size 576x576 with 2 Axes>,\n",
       " <matplotlib.axes._subplots.PolarAxesSubplot at 0x7f5cffbd2390>)"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mne.viz.plot_connectivity_circle(con_res['pli'], label_names, n_lines=300,\n",
    "                         node_angles=node_angles, node_colors=label_colors,\n",
    "                         title='All-to-All Connectivity left-Auditory '\n",
    "                               'Condition (PLI)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
