decodeState_recall.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import itertools\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import sklearn\n",
    "import brainiak\n",
    "import nilearn as nl\n",
    "from nilearn import image, plotting, input_data\n",
    "\n",
    "from scipy.spatial import distance\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "pd.options.display.max_rows = 200"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# load dataframes with timing and order information"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "      <th>62</th>\n",
       "      <td>33</td>\n",
       "      <td>vid1b_q</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>1b</td>\n",
       "      <td>6</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>10</td>\n",
       "      <td>vid1b_q</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>1b</td>\n",
       "      <td>6</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>6</td>\n",
       "      <td>vid1b_q</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>1b</td>\n",
       "      <td>6</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>38</td>\n",
       "      <td>vid1b_q</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>1b</td>\n",
       "      <td>6</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>4</td>\n",
       "      <td>vid1b_q</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>1b</td>\n",
       "      <td>6</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>32</td>\n",
       "      <td>vid1b_q</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>1b</td>\n",
       "      <td>6</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>18</td>\n",
       "      <td>vid1b_q</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>1b</td>\n",
       "      <td>6</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>31</td>\n",
       "      <td>vid1b_q</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>1b</td>\n",
       "      <td>6</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>17</td>\n",
       "      <td>vid1b_q</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>1b</td>\n",
       "      <td>6</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>23</td>\n",
       "      <td>vid1b_q</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>1b</td>\n",
       "      <td>6</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>37</td>\n",
       "      <td>vid1b_q</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>1b</td>\n",
       "      <td>6</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>28</td>\n",
       "      <td>vid1b_q</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>1b</td>\n",
       "      <td>6</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>40</td>\n",
       "      <td>vid1b_q</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>1b</td>\n",
       "      <td>6</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>12</td>\n",
       "      <td>vid1b_q</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>1b</td>\n",
       "      <td>6</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>24</td>\n",
       "      <td>vid1b_q</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>1b</td>\n",
       "      <td>6</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>44</td>\n",
       "      <td>vid1b_q</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>1b</td>\n",
       "      <td>6</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>8</td>\n",
       "      <td>vid1b_q</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>1b</td>\n",
       "      <td>6</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>7</td>\n",
       "      <td>vid1b_q</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>1b</td>\n",
       "      <td>6</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>29</td>\n",
       "      <td>vid1b_q</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>1b</td>\n",
       "      <td>6</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>26</td>\n",
       "      <td>vid1b_q</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>1b</td>\n",
       "      <td>6</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>27</td>\n",
       "      <td>vid1b_q</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>1b</td>\n",
       "      <td>6</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>25</td>\n",
       "      <td>vid1b_q</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>1b</td>\n",
       "      <td>6</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>36</td>\n",
       "      <td>vid1b_q</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>1b</td>\n",
       "      <td>6</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>3</td>\n",
       "      <td>vid1b_q</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>1b</td>\n",
       "      <td>6</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>6</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2b</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>12</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2a</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>35</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2a</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>41</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2a</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>31</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2b</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>44</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2a</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>27</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2a</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>33</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2b</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>34</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2a</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>5</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2b</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>7</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2a</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>38</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2b</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>26</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2b</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>28</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2b</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>3</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2b</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>32</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2a</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>19</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2b</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>4</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2a</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>17</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2b</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>40</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2a</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>15</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2a</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>25</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2a</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>13</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2b</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>18</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2b</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>42</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2a</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>10</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2b</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>8</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2b</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>36</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2b</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>9</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2b</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>11</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2b</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>22</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2b</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>43</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2a</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>37</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2a</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>23</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2a</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>24</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2a</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>14</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2a</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>30</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2a</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>39</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2b</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>29</td>\n",
       "      <td>vid2_q</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>2b</td>\n",
       "      <td>11</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>7</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3b</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>39</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3a</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>8</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3a</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>25</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3b</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>15</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3b</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>14</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3b</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>17</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3a</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>5</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3a</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>4</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3b</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>36</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3a</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>11</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3a</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>27</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3b</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>33</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3a</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>37</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3b</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>10</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3a</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>23</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3b</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>3</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3a</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>40</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3b</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>29</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3a</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>31</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3a</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>35</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3b</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>41</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3b</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>12</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3b</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>19</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3a</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>32</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3b</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>42</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3b</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>38</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3a</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>26</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3a</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>6</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3a</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>9</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3a</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>44</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3b</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>18</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3a</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>30</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3b</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>13</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3a</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>28</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3a</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>22</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3a</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>34</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3b</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>24</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3b</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>43</td>\n",
       "      <td>vid3_q</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>3b</td>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>14</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4a</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>44</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4a</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>37</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4a</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>42</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4a</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>13</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4b</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>15</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4a</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>41</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4a</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>26</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4b</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>10</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4b</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>34</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4a</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>23</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4a</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>27</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4a</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>3</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4b</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>11</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4b</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>39</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4b</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>8</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4b</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>29</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4b</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>22</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4b</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>43</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4a</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>30</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4a</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>9</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4b</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>35</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4a</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>24</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4a</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>33</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4b</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>19</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4b</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>12</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4a</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>38</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4b</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>36</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4b</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>6</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4b</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>18</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4b</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>40</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4a</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>7</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4a</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>28</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4b</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>32</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4a</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>31</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4b</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>5</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4b</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>17</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4b</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>4</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4a</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>25</td>\n",
       "      <td>vid4_q</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4a</td>\n",
       "      <td>16</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>5</td>\n",
       "      <td>vid5_q</td>\n",
       "      <td>0</td>\n",
       "      <td>83</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>13</td>\n",
       "      <td>vid5_q</td>\n",
       "      <td>0</td>\n",
       "      <td>83</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>12</td>\n",
       "      <td>vid5_q</td>\n",
       "      <td>0</td>\n",
       "      <td>83</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>35</td>\n",
       "      <td>vid5_q</td>\n",
       "      <td>0</td>\n",
       "      <td>83</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>11</td>\n",
       "      <td>vid5_q</td>\n",
       "      <td>0</td>\n",
       "      <td>83</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    sub_num  vid_str  wed_num  onset_TR state  len_TRs  offset_TR\n",
       "60       25  vid1a_q        0        12    1b       17         29\n",
       "60       29  vid1a_q        0        12    1b       17         29\n",
       "60        6  vid1a_q        0        12    1b       17         29\n",
       "60       10  vid1a_q        0        12    1b       17         29\n",
       "60       36  vid1a_q        0        12    1b       17         29\n",
       "60       38  vid1a_q        0        12    1b       17         29\n",
       "60        8  vid1a_q        0        12    1b       17         29\n",
       "60       23  vid1a_q        0        12    1b       17         29\n",
       "60       28  vid1a_q        0        12    1b       17         29\n",
       "60       12  vid1a_q        0        12    1b       17         29\n",
       "60        4  vid1a_q        0        12    1b       17         29\n",
       "60       22  vid1a_q        0        12    1b       17         29\n",
       "60       32  vid1a_q        0        12    1b       17         29\n",
       "60       18  vid1a_q        0        12    1b       17         29\n",
       "60       43  vid1a_q        0        12    1b       17         29\n",
       "60       13  vid1a_q        0        12    1b       17         29\n",
       "60       31  vid1a_q        0        12    1b       17         29\n",
       "60       19  vid1a_q        0        12    1b       17         29\n",
       "60       11  vid1a_q        0        12    1b       17         29\n",
       "60       17  vid1a_q        0        12    1b       17         29\n",
       "60       41  vid1a_q        0        12    1b       17         29\n",
       "60       37  vid1a_q        0        12    1b       17         29\n",
       "60       44  vid1a_q        0        12    1b       17         29\n",
       "60        9  vid1a_q        0        12    1b       17         29\n",
       "60       27  vid1a_q        0        12    1b       17         29\n",
       "60        3  vid1a_q        0        12    1b       17         29\n",
       "60       35  vid1a_q        0        12    1b       17         29\n",
       "60       15  vid1a_q        0        12    1b       17         29\n",
       "60        5  vid1a_q        0        12    1b       17         29\n",
       "60       33  vid1a_q        0        12    1b       17         29\n",
       "60       30  vid1a_q        0        12    1b       17         29\n",
       "60       39  vid1a_q        0        12    1b       17         29\n",
       "60        7  vid1a_q        0        13    1b       17         30\n",
       "60       14  vid1a_q        0        13    1b       17         30\n",
       "60       42  vid1a_q        0        13    1b       17         30\n",
       "60       40  vid1a_q        0        13    1b       17         30\n",
       "60       24  vid1a_q        0        13    1b       17         30\n",
       "60       26  vid1a_q        0        13    1b       17         30\n",
       "60       34  vid1a_q        0        13    1b       17         30\n",
       "62       22  vid1b_q        0        29    1b        6         35\n",
       "62       39  vid1b_q        0        29    1b        6         35\n",
       "62       30  vid1b_q        0        29    1b        6         35\n",
       "62        9  vid1b_q        0        29    1b        6         35\n",
       "62       11  vid1b_q        0        29    1b        6         35\n",
       "62       43  vid1b_q        0        29    1b        6         35\n",
       "62       19  vid1b_q        0        29    1b        6         35\n",
       "62       14  vid1b_q        0        29    1b        6         35\n",
       "62       42  vid1b_q        0        29    1b        6         35\n",
       "62       35  vid1b_q        0        29    1b        6         35\n",
       "62        5  vid1b_q        0        29    1b        6         35\n",
       "62       34  vid1b_q        0        29    1b        6         35\n",
       "62       15  vid1b_q        0        29    1b        6         35\n",
       "62       41  vid1b_q        0        29    1b        6         35\n",
       "62       13  vid1b_q        0        29    1b        6         35\n",
       "62       33  vid1b_q        0        29    1b        6         35\n",
       "62       10  vid1b_q        0        29    1b        6         35\n",
       "62        6  vid1b_q        0        29    1b        6         35\n",
       "62       38  vid1b_q        0        29    1b        6         35\n",
       "62        4  vid1b_q        0        29    1b        6         35\n",
       "62       32  vid1b_q        0        29    1b        6         35\n",
       "62       18  vid1b_q        0        29    1b        6         35\n",
       "62       31  vid1b_q        0        29    1b        6         35\n",
       "62       17  vid1b_q        0        29    1b        6         35\n",
       "62       23  vid1b_q        0        29    1b        6         35\n",
       "62       37  vid1b_q        0        29    1b        6         35\n",
       "62       28  vid1b_q        0        29    1b        6         35\n",
       "62       40  vid1b_q        0        29    1b        6         35\n",
       "62       12  vid1b_q        0        29    1b        6         35\n",
       "62       24  vid1b_q        0        29    1b        6         35\n",
       "62       44  vid1b_q        0        29    1b        6         35\n",
       "62        8  vid1b_q        0        29    1b        6         35\n",
       "62        7  vid1b_q        0        29    1b        6         35\n",
       "62       29  vid1b_q        0        29    1b        6         35\n",
       "62       26  vid1b_q        0        29    1b        6         35\n",
       "62       27  vid1b_q        0        29    1b        6         35\n",
       "62       25  vid1b_q        0        29    1b        6         35\n",
       "62       36  vid1b_q        0        29    1b        6         35\n",
       "62        3  vid1b_q        0        29    1b        6         35\n",
       "64        6   vid2_q        0        35    2b       11         46\n",
       "64       12   vid2_q        0        35    2a       11         46\n",
       "64       35   vid2_q        0        35    2a       11         46\n",
       "64       41   vid2_q        0        35    2a       11         46\n",
       "64       31   vid2_q        0        35    2b       11         46\n",
       "64       44   vid2_q        0        35    2a       11         46\n",
       "64       27   vid2_q        0        35    2a       11         46\n",
       "64       33   vid2_q        0        35    2b       11         46\n",
       "64       34   vid2_q        0        35    2a       11         46\n",
       "64        5   vid2_q        0        35    2b       11         46\n",
       "64        7   vid2_q        0        35    2a       11         46\n",
       "64       38   vid2_q        0        35    2b       11         46\n",
       "64       26   vid2_q        0        35    2b       11         46\n",
       "64       28   vid2_q        0        35    2b       11         46\n",
       "64        3   vid2_q        0        35    2b       11         46\n",
       "64       32   vid2_q        0        35    2a       11         46\n",
       "64       19   vid2_q        0        35    2b       11         46\n",
       "64        4   vid2_q        0        35    2a       11         46\n",
       "64       17   vid2_q        0        35    2b       11         46\n",
       "64       40   vid2_q        0        35    2a       11         46\n",
       "64       15   vid2_q        0        35    2a       11         46\n",
       "64       25   vid2_q        0        35    2a       11         46\n",
       "64       13   vid2_q        0        35    2b       11         46\n",
       "64       18   vid2_q        0        35    2b       11         46\n",
       "64       42   vid2_q        0        35    2a       11         46\n",
       "64       10   vid2_q        0        35    2b       11         46\n",
       "64        8   vid2_q        0        35    2b       11         46\n",
       "64       36   vid2_q        0        35    2b       11         46\n",
       "64        9   vid2_q        0        35    2b       11         46\n",
       "64       11   vid2_q        0        35    2b       11         46\n",
       "64       22   vid2_q        0        35    2b       11         46\n",
       "64       43   vid2_q        0        35    2a       11         46\n",
       "64       37   vid2_q        0        35    2a       11         46\n",
       "64       23   vid2_q        0        35    2a       11         46\n",
       "64       24   vid2_q        0        35    2a       11         46\n",
       "64       14   vid2_q        0        35    2a       11         46\n",
       "64       30   vid2_q        0        35    2a       11         46\n",
       "64       39   vid2_q        0        35    2b       11         46\n",
       "64       29   vid2_q        0        35    2b       11         46\n",
       "66        7   vid3_q        0        49    3b       15         64\n",
       "66       39   vid3_q        0        49    3a       15         64\n",
       "66        8   vid3_q        0        49    3a       15         64\n",
       "66       25   vid3_q        0        49    3b       15         64\n",
       "66       15   vid3_q        0        49    3b       15         64\n",
       "66       14   vid3_q        0        49    3b       15         64\n",
       "66       17   vid3_q        0        49    3a       15         64\n",
       "66        5   vid3_q        0        49    3a       15         64\n",
       "66        4   vid3_q        0        49    3b       15         64\n",
       "66       36   vid3_q        0        49    3a       15         64\n",
       "66       11   vid3_q        0        49    3a       15         64\n",
       "66       27   vid3_q        0        49    3b       15         64\n",
       "66       33   vid3_q        0        49    3a       15         64\n",
       "66       37   vid3_q        0        49    3b       15         64\n",
       "66       10   vid3_q        0        49    3a       15         64\n",
       "66       23   vid3_q        0        49    3b       15         64\n",
       "66        3   vid3_q        0        49    3a       15         64\n",
       "66       40   vid3_q        0        49    3b       15         64\n",
       "66       29   vid3_q        0        49    3a       15         64\n",
       "66       31   vid3_q        0        49    3a       15         64\n",
       "66       35   vid3_q        0        49    3b       15         64\n",
       "66       41   vid3_q        0        49    3b       15         64\n",
       "66       12   vid3_q        0        49    3b       15         64\n",
       "66       19   vid3_q        0        49    3a       15         64\n",
       "66       32   vid3_q        0        49    3b       15         64\n",
       "66       42   vid3_q        0        49    3b       15         64\n",
       "66       38   vid3_q        0        49    3a       15         64\n",
       "66       26   vid3_q        0        49    3a       15         64\n",
       "66        6   vid3_q        0        49    3a       15         64\n",
       "66        9   vid3_q        0        49    3a       15         64\n",
       "66       44   vid3_q        0        49    3b       15         64\n",
       "66       18   vid3_q        0        49    3a       15         64\n",
       "66       30   vid3_q        0        49    3b       15         64\n",
       "66       13   vid3_q        0        49    3a       15         64\n",
       "66       28   vid3_q        0        49    3a       15         64\n",
       "66       22   vid3_q        0        49    3a       15         64\n",
       "66       34   vid3_q        0        49    3b       15         64\n",
       "66       24   vid3_q        0        49    3b       15         64\n",
       "66       43   vid3_q        0        49    3b       15         64\n",
       "68       14   vid4_q        0        67    4a       16         83\n",
       "68       44   vid4_q        0        67    4a       16         83\n",
       "68       37   vid4_q        0        67    4a       16         83\n",
       "68       42   vid4_q        0        67    4a       16         83\n",
       "68       13   vid4_q        0        67    4b       16         83\n",
       "68       15   vid4_q        0        67    4a       16         83\n",
       "68       41   vid4_q        0        67    4a       16         83\n",
       "68       26   vid4_q        0        67    4b       16         83\n",
       "68       10   vid4_q        0        67    4b       16         83\n",
       "68       34   vid4_q        0        67    4a       16         83\n",
       "68       23   vid4_q        0        67    4a       16         83\n",
       "68       27   vid4_q        0        67    4a       16         83\n",
       "68        3   vid4_q        0        67    4b       16         83\n",
       "68       11   vid4_q        0        67    4b       16         83\n",
       "68       39   vid4_q        0        67    4b       16         83\n",
       "68        8   vid4_q        0        67    4b       16         83\n",
       "68       29   vid4_q        0        67    4b       16         83\n",
       "68       22   vid4_q        0        67    4b       16         83\n",
       "68       43   vid4_q        0        67    4a       16         83\n",
       "68       30   vid4_q        0        67    4a       16         83\n",
       "68        9   vid4_q        0        67    4b       16         83\n",
       "68       35   vid4_q        0        67    4a       16         83\n",
       "68       24   vid4_q        0        67    4a       16         83\n",
       "68       33   vid4_q        0        67    4b       16         83\n",
       "68       19   vid4_q        0        67    4b       16         83\n",
       "68       12   vid4_q        0        67    4a       16         83\n",
       "68       38   vid4_q        0        67    4b       16         83\n",
       "68       36   vid4_q        0        67    4b       16         83\n",
       "68        6   vid4_q        0        67    4b       16         83\n",
       "68       18   vid4_q        0        67    4b       16         83\n",
       "68       40   vid4_q        0        67    4a       16         83\n",
       "68        7   vid4_q        0        67    4a       16         83\n",
       "68       28   vid4_q        0        67    4b       16         83\n",
       "68       32   vid4_q        0        67    4a       16         83\n",
       "68       31   vid4_q        0        67    4b       16         83\n",
       "68        5   vid4_q        0        67    4b       16         83\n",
       "68       17   vid4_q        0        67    4b       16         83\n",
       "68        4   vid4_q        0        67    4a       16         83\n",
       "68       25   vid4_q        0        67    4a       16         83\n",
       "70        5   vid5_q        0        83     5        7         90\n",
       "70       13   vid5_q        0        83     5        7         90\n",
       "70       12   vid5_q        0        83     5        7         90\n",
       "70       35   vid5_q        0        83     5        7         90\n",
       "70       11   vid5_q        0        83     5        7         90"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "view_df = pd.read_csv('deriv/view_df.csv',index_col=0)\n",
    "view_df.iloc[:200]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "recall_df = pd.read_csv('deriv/recall_df.csv',index_col=0)\n",
    "# recall_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# form training and testing datasets"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### classifier training "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "sub_num,layer_num = 33,3\n",
    "def get_training_info(sub_num,layer_num):\n",
    "  # find df rows corresponding to sub/layer\n",
    "  layer_bool = view_df.state.str[0]==str(layer_num)\n",
    "  sub_layer_view_df = view_df[(view_df.sub_num == sub_num) & layer_bool]\n",
    "  # extract TRs and labels \n",
    "  TR_L = []\n",
    "  ytarget_L = []\n",
    "  for idx,row in sub_layer_view_df.iterrows():\n",
    "    TRs = np.arange(row.onset_TR,row.offset_TR)\n",
    "    TR_L.extend(TRs)\n",
    "    ytarget_L.extend(np.repeat(row.state[1]=='a',len(TRs)))\n",
    "  return np.array(TR_L),np.array(ytarget_L)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"\"\" \n",
    "build testing dataset\n",
    "\"\"\" \n",
    "\n",
    "## dict mapping (layer,state):recall_transcript_code\n",
    "recall_label_D = {\n",
    "  (2,'a'):3,\n",
    "  (2,'b'):4,\n",
    "  (3,'a'):5,\n",
    "  (3,'b'):6,\n",
    "  (4,'a'):7,\n",
    "  (4,'b'):8\n",
    "}\n",
    "\n",
    "def get_test_info(sub_num,layer_num):\n",
    "  \"\"\" \n",
    "  build testing dataset\n",
    "  find TRs during recall when sub is recalling given state+layer\n",
    "  along with labels for these recall TRs when recalling layer\n",
    "  \"\"\"\n",
    "  ytarget = []\n",
    "  XTRs = []\n",
    "  sub_recall_df = recall_df[recall_df.sub_num==sub_num]\n",
    "  for state_id in ['a','b']:\n",
    "    # from layer+state get transcript_code\n",
    "    recall_code = recall_label_D[(layer_num,state_id)]\n",
    "    # find TRs where sub talks about layer+state\n",
    "    TRs_state = sub_recall_df[sub_recall_df.recall==recall_code].TR.values\n",
    "    XTRs.extend(TRs_state)\n",
    "    ytarget.extend(np.repeat(state_id,len(TRs_state)))\n",
    "  return XTRs,np.array(ytarget)=='a'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# train-test loop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_sub_roi(sub_num,roi_name,task):\n",
    "  fpath = \"sub-%i_task-%s_roi-%s.npy\" %(sub_num,task,roi_name)\n",
    "  return np.load('data/fmri/masked/'+fpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "ROI_NAME_L = [\n",
    "  'SnPM_filtered_FDR',\n",
    "  'rglasser_AT_net',\n",
    "  'rglasser_MP_net',\n",
    "  'rglasser_MTN_net',\n",
    "  'rglasser_PM_net',\n",
    "  'rhippocampusAAL', \n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "r SnPM_filtered_FDR sub 0 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 0 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 0 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 1 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 1 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 1 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 2 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 2 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 2 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 3 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 3 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 3 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 4 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 4 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 4 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 5 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 5 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 5 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 6 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 6 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 6 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 7 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 7 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 7 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 8 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 8 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 8 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 9 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 9 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 9 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 10 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 10 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 10 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 11 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 11 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 11 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 12 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 12 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 12 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 13 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 13 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 13 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 14 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 14 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 14 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 15 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 15 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 15 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 16 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 16 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 16 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 17 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 17 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 17 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 18 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 18 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 18 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 19 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 19 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 19 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 20 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 20 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 20 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 21 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 21 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 21 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 22 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 22 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 22 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 23 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 23 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 23 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 24 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 24 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 24 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 25 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 25 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 25 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 26 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 26 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 26 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 27 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 27 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 27 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 28 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 28 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 28 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 29 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 29 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 29 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 30 layer 2\n",
      "r SnPM_filtered_FDR sub 30 layer 3\n",
      "r SnPM_filtered_FDR sub 30 layer 4\n",
      "r SnPM_filtered_FDR sub 31 layer 2\n",
      "r SnPM_filtered_FDR sub 31 layer 3\n",
      "no recall data. sub 31 layer 3\n",
      "r SnPM_filtered_FDR sub 31 layer 4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "//anaconda3/envs/brain/lib/python3.6/site-packages/ipykernel_launcher.py:31: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "r SnPM_filtered_FDR sub 32 layer 2\n",
      "r SnPM_filtered_FDR sub 32 layer 3\n",
      "r SnPM_filtered_FDR sub 32 layer 4\n",
      "r SnPM_filtered_FDR sub 33 layer 2\n",
      "r SnPM_filtered_FDR sub 33 layer 3\n",
      "r SnPM_filtered_FDR sub 33 layer 4\n",
      "r SnPM_filtered_FDR sub 34 layer 2\n",
      "r SnPM_filtered_FDR sub 34 layer 3\n",
      "r SnPM_filtered_FDR sub 34 layer 4\n",
      "r SnPM_filtered_FDR sub 35 layer 2\n",
      "r SnPM_filtered_FDR sub 35 layer 3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "//anaconda3/envs/brain/lib/python3.6/site-packages/ipykernel_launcher.py:31: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "no recall data. sub 35 layer 3\n",
      "r SnPM_filtered_FDR sub 35 layer 4\n",
      "r SnPM_filtered_FDR sub 36 layer 2\n",
      "r SnPM_filtered_FDR sub 36 layer 3\n",
      "r SnPM_filtered_FDR sub 36 layer 4\n",
      "r SnPM_filtered_FDR sub 37 layer 2\n",
      "r SnPM_filtered_FDR sub 37 layer 3\n",
      "r SnPM_filtered_FDR sub 37 layer 4\n",
      "r SnPM_filtered_FDR sub 38 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 38 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 38 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 39 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 39 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 39 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 40 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 40 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 40 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 41 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 41 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 41 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 42 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 42 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 42 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 43 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 43 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 43 layer 4\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 44 layer 2\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 44 layer 3\n",
      "err loading roi data\n",
      "r SnPM_filtered_FDR sub 44 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 0 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 0 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 0 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 1 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 1 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 1 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 2 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 2 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 2 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 3 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 3 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 3 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 4 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 4 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 4 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 5 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 5 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 5 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 6 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 6 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 6 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 7 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 7 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 7 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 8 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 8 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 8 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 9 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 9 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 9 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 10 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 10 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 10 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 11 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 11 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 11 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 12 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 12 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 12 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 13 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 13 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 13 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 14 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 14 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 14 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 15 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 15 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 15 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 16 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 16 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 16 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 17 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 17 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 17 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 18 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 18 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 18 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 19 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 19 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 19 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 20 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 20 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 20 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 21 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 21 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 21 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 22 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 22 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 22 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 23 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 23 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 23 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 24 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 24 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 24 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 25 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 25 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 25 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 26 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 26 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 26 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 27 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 27 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 27 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 28 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 28 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 28 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 29 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 29 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 29 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 30 layer 2\n",
      "r rglasser_AT_net sub 30 layer 3\n",
      "r rglasser_AT_net sub 30 layer 4\n",
      "r rglasser_AT_net sub 31 layer 2\n",
      "r rglasser_AT_net sub 31 layer 3\n",
      "no recall data. sub 31 layer 3\n",
      "r rglasser_AT_net sub 31 layer 4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "//anaconda3/envs/brain/lib/python3.6/site-packages/ipykernel_launcher.py:31: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "r rglasser_AT_net sub 32 layer 2\n",
      "r rglasser_AT_net sub 32 layer 3\n",
      "r rglasser_AT_net sub 32 layer 4\n",
      "r rglasser_AT_net sub 33 layer 2\n",
      "r rglasser_AT_net sub 33 layer 3\n",
      "r rglasser_AT_net sub 33 layer 4\n",
      "r rglasser_AT_net sub 34 layer 2\n",
      "r rglasser_AT_net sub 34 layer 3\n",
      "r rglasser_AT_net sub 34 layer 4\n",
      "r rglasser_AT_net sub 35 layer 2\n",
      "r rglasser_AT_net sub 35 layer 3\n",
      "no recall data. sub 35 layer 3\n",
      "r rglasser_AT_net sub 35 layer 4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "//anaconda3/envs/brain/lib/python3.6/site-packages/ipykernel_launcher.py:31: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "r rglasser_AT_net sub 36 layer 2\n",
      "r rglasser_AT_net sub 36 layer 3\n",
      "r rglasser_AT_net sub 36 layer 4\n",
      "r rglasser_AT_net sub 37 layer 2\n",
      "r rglasser_AT_net sub 37 layer 3\n",
      "r rglasser_AT_net sub 37 layer 4\n",
      "r rglasser_AT_net sub 38 layer 2\n",
      "r rglasser_AT_net sub 38 layer 3\n",
      "no recall data. sub 38 layer 3\n",
      "r rglasser_AT_net sub 38 layer 4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "//anaconda3/envs/brain/lib/python3.6/site-packages/ipykernel_launcher.py:31: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "r rglasser_AT_net sub 39 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 39 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 39 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 40 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 40 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 40 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 41 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 41 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 41 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 42 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 42 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 42 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 43 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 43 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 43 layer 4\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 44 layer 2\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 44 layer 3\n",
      "err loading roi data\n",
      "r rglasser_AT_net sub 44 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 0 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 0 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 0 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 1 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 1 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 1 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 2 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 2 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 2 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 3 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 3 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 3 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 4 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 4 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 4 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 5 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 5 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 5 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 6 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 6 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 6 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 7 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 7 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 7 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 8 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 8 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 8 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 9 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 9 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 9 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 10 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 10 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 10 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 11 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 11 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 11 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 12 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 12 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 12 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 13 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 13 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 13 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 14 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 14 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 14 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 15 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 15 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 15 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 16 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 16 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 16 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 17 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 17 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 17 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 18 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 18 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 18 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 19 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 19 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 19 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 20 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 20 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 20 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 21 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 21 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 21 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 22 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 22 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 22 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 23 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 23 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 23 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 24 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 24 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 24 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 25 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 25 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 25 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 26 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 26 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 26 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 27 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 27 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 27 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 28 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 28 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 28 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 29 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 29 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 29 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 30 layer 2\n",
      "r rglasser_MP_net sub 30 layer 3\n",
      "r rglasser_MP_net sub 30 layer 4\n",
      "r rglasser_MP_net sub 31 layer 2\n",
      "r rglasser_MP_net sub 31 layer 3\n",
      "no recall data. sub 31 layer 3\n",
      "r rglasser_MP_net sub 31 layer 4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "//anaconda3/envs/brain/lib/python3.6/site-packages/ipykernel_launcher.py:31: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "r rglasser_MP_net sub 32 layer 2\n",
      "r rglasser_MP_net sub 32 layer 3\n",
      "r rglasser_MP_net sub 32 layer 4\n",
      "r rglasser_MP_net sub 33 layer 2\n",
      "r rglasser_MP_net sub 33 layer 3\n",
      "r rglasser_MP_net sub 33 layer 4\n",
      "r rglasser_MP_net sub 34 layer 2\n",
      "r rglasser_MP_net sub 34 layer 3\n",
      "r rglasser_MP_net sub 34 layer 4\n",
      "r rglasser_MP_net sub 35 layer 2\n",
      "r rglasser_MP_net sub 35 layer 3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "//anaconda3/envs/brain/lib/python3.6/site-packages/ipykernel_launcher.py:31: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "no recall data. sub 35 layer 3\n",
      "r rglasser_MP_net sub 35 layer 4\n",
      "r rglasser_MP_net sub 36 layer 2\n",
      "r rglasser_MP_net sub 36 layer 3\n",
      "r rglasser_MP_net sub 36 layer 4\n",
      "r rglasser_MP_net sub 37 layer 2\n",
      "r rglasser_MP_net sub 37 layer 3\n",
      "r rglasser_MP_net sub 37 layer 4\n",
      "r rglasser_MP_net sub 38 layer 2\n",
      "r rglasser_MP_net sub 38 layer 3\n",
      "no recall data. sub 38 layer 3\n",
      "r rglasser_MP_net sub 38 layer 4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "//anaconda3/envs/brain/lib/python3.6/site-packages/ipykernel_launcher.py:31: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "r rglasser_MP_net sub 39 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 39 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 39 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 40 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 40 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 40 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 41 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 41 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 41 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 42 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 42 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 42 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 43 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 43 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 43 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 44 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 44 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MP_net sub 44 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 0 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 0 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 0 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 1 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 1 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 1 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 2 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 2 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 2 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 3 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 3 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 3 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 4 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 4 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 4 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 5 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 5 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 5 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 6 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 6 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 6 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 7 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 7 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 7 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 8 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 8 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 8 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 9 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 9 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 9 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 10 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 10 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 10 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 11 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 11 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 11 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 12 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 12 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 12 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 13 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 13 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 13 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 14 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 14 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 14 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 15 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 15 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 15 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 16 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 16 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 16 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 17 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 17 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 17 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 18 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 18 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 18 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 19 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 19 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 19 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 20 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 20 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 20 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 21 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 21 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 21 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 22 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 22 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 22 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 23 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 23 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 23 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 24 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 24 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 24 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 25 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 25 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 25 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 26 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 26 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 26 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 27 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 27 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 27 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 28 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 28 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 28 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 29 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 29 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 29 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 30 layer 2\n",
      "r rglasser_MTN_net sub 30 layer 3\n",
      "r rglasser_MTN_net sub 30 layer 4\n",
      "r rglasser_MTN_net sub 31 layer 2\n",
      "r rglasser_MTN_net sub 31 layer 3\n",
      "no recall data. sub 31 layer 3\n",
      "r rglasser_MTN_net sub 31 layer 4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "//anaconda3/envs/brain/lib/python3.6/site-packages/ipykernel_launcher.py:31: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "r rglasser_MTN_net sub 32 layer 2\n",
      "r rglasser_MTN_net sub 32 layer 3\n",
      "r rglasser_MTN_net sub 32 layer 4\n",
      "r rglasser_MTN_net sub 33 layer 2\n",
      "r rglasser_MTN_net sub 33 layer 3\n",
      "r rglasser_MTN_net sub 33 layer 4\n",
      "r rglasser_MTN_net sub 34 layer 2\n",
      "r rglasser_MTN_net sub 34 layer 3\n",
      "r rglasser_MTN_net sub 34 layer 4\n",
      "r rglasser_MTN_net sub 35 layer 2\n",
      "r rglasser_MTN_net sub 35 layer 3\n",
      "no recall data. sub 35 layer 3\n",
      "r rglasser_MTN_net sub 35 layer 4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "//anaconda3/envs/brain/lib/python3.6/site-packages/ipykernel_launcher.py:31: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "r rglasser_MTN_net sub 36 layer 2\n",
      "r rglasser_MTN_net sub 36 layer 3\n",
      "r rglasser_MTN_net sub 36 layer 4\n",
      "r rglasser_MTN_net sub 37 layer 2\n",
      "r rglasser_MTN_net sub 37 layer 3\n",
      "r rglasser_MTN_net sub 37 layer 4\n",
      "r rglasser_MTN_net sub 38 layer 2\n",
      "r rglasser_MTN_net sub 38 layer 3\n",
      "no recall data. sub 38 layer 3\n",
      "r rglasser_MTN_net sub 38 layer 4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "//anaconda3/envs/brain/lib/python3.6/site-packages/ipykernel_launcher.py:31: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "r rglasser_MTN_net sub 39 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 39 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 39 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 40 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 40 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 40 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 41 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 41 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 41 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 42 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 42 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 42 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 43 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 43 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 43 layer 4\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 44 layer 2\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 44 layer 3\n",
      "err loading roi data\n",
      "r rglasser_MTN_net sub 44 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 0 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 0 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 0 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 1 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 1 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 1 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 2 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 2 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 2 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 3 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 3 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 3 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 4 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 4 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 4 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 5 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 5 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 5 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 6 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 6 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 6 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 7 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 7 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 7 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 8 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 8 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 8 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 9 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 9 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 9 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 10 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 10 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 10 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 11 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 11 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 11 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 12 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 12 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 12 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 13 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 13 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 13 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 14 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 14 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 14 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 15 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 15 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 15 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 16 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 16 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 16 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 17 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 17 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 17 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 18 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 18 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 18 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 19 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 19 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 19 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 20 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 20 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 20 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 21 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 21 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 21 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 22 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 22 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 22 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 23 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 23 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 23 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 24 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 24 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 24 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 25 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 25 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 25 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 26 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 26 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 26 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 27 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 27 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 27 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 28 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 28 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 28 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 29 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 29 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 29 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 30 layer 2\n",
      "r rglasser_PM_net sub 30 layer 3\n",
      "r rglasser_PM_net sub 30 layer 4\n",
      "r rglasser_PM_net sub 31 layer 2\n",
      "r rglasser_PM_net sub 31 layer 3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "//anaconda3/envs/brain/lib/python3.6/site-packages/ipykernel_launcher.py:31: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "no recall data. sub 31 layer 3\n",
      "r rglasser_PM_net sub 31 layer 4\n",
      "r rglasser_PM_net sub 32 layer 2\n",
      "r rglasser_PM_net sub 32 layer 3\n",
      "r rglasser_PM_net sub 32 layer 4\n",
      "r rglasser_PM_net sub 33 layer 2\n",
      "r rglasser_PM_net sub 33 layer 3\n",
      "r rglasser_PM_net sub 33 layer 4\n",
      "r rglasser_PM_net sub 34 layer 2\n",
      "r rglasser_PM_net sub 34 layer 3\n",
      "r rglasser_PM_net sub 34 layer 4\n",
      "r rglasser_PM_net sub 35 layer 2\n",
      "r rglasser_PM_net sub 35 layer 3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "//anaconda3/envs/brain/lib/python3.6/site-packages/ipykernel_launcher.py:31: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "no recall data. sub 35 layer 3\n",
      "r rglasser_PM_net sub 35 layer 4\n",
      "r rglasser_PM_net sub 36 layer 2\n",
      "r rglasser_PM_net sub 36 layer 3\n",
      "r rglasser_PM_net sub 36 layer 4\n",
      "r rglasser_PM_net sub 37 layer 2\n",
      "r rglasser_PM_net sub 37 layer 3\n",
      "r rglasser_PM_net sub 37 layer 4\n",
      "r rglasser_PM_net sub 38 layer 2\n",
      "r rglasser_PM_net sub 38 layer 3\n",
      "no recall data. sub 38 layer 3\n",
      "r rglasser_PM_net sub 38 layer 4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "//anaconda3/envs/brain/lib/python3.6/site-packages/ipykernel_launcher.py:31: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "r rglasser_PM_net sub 39 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 39 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 39 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 40 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 40 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 40 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 41 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 41 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 41 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 42 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 42 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 42 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 43 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 43 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 43 layer 4\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 44 layer 2\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 44 layer 3\n",
      "err loading roi data\n",
      "r rglasser_PM_net sub 44 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 0 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 0 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 0 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 1 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 1 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 1 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 2 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 2 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 2 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 3 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 3 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 3 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 4 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 4 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 4 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 5 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 5 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 5 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 6 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 6 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 6 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 7 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 7 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 7 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 8 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 8 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 8 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 9 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 9 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 9 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 10 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 10 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 10 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 11 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 11 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 11 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 12 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 12 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 12 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 13 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 13 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 13 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 14 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 14 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 14 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 15 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 15 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 15 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 16 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 16 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 16 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 17 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 17 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 17 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 18 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 18 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 18 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 19 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 19 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 19 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 20 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 20 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 20 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 21 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 21 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 21 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 22 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 22 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 22 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 23 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 23 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 23 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 24 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 24 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 24 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 25 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 25 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 25 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 26 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 26 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 26 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 27 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 27 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 27 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 28 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 28 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 28 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 29 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 29 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 29 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 30 layer 2\n",
      "r rhippocampusAAL sub 30 layer 3\n",
      "r rhippocampusAAL sub 30 layer 4\n",
      "r rhippocampusAAL sub 31 layer 2\n",
      "r rhippocampusAAL sub 31 layer 3\n",
      "no recall data. sub 31 layer 3\n",
      "r rhippocampusAAL sub 31 layer 4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "//anaconda3/envs/brain/lib/python3.6/site-packages/ipykernel_launcher.py:31: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "r rhippocampusAAL sub 32 layer 2\n",
      "r rhippocampusAAL sub 32 layer 3\n",
      "r rhippocampusAAL sub 32 layer 4\n",
      "r rhippocampusAAL sub 33 layer 2\n",
      "r rhippocampusAAL sub 33 layer 3\n",
      "r rhippocampusAAL sub 33 layer 4\n",
      "r rhippocampusAAL sub 34 layer 2\n",
      "r rhippocampusAAL sub 34 layer 3\n",
      "r rhippocampusAAL sub 34 layer 4\n",
      "r rhippocampusAAL sub 35 layer 2\n",
      "r rhippocampusAAL sub 35 layer 3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "//anaconda3/envs/brain/lib/python3.6/site-packages/ipykernel_launcher.py:31: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "no recall data. sub 35 layer 3\n",
      "r rhippocampusAAL sub 35 layer 4\n",
      "r rhippocampusAAL sub 36 layer 2\n",
      "r rhippocampusAAL sub 36 layer 3\n",
      "r rhippocampusAAL sub 36 layer 4\n",
      "r rhippocampusAAL sub 37 layer 2\n",
      "r rhippocampusAAL sub 37 layer 3\n",
      "r rhippocampusAAL sub 37 layer 4\n",
      "r rhippocampusAAL sub 38 layer 2\n",
      "r rhippocampusAAL sub 38 layer 3\n",
      "no recall data. sub 38 layer 3\n",
      "r rhippocampusAAL sub 38 layer 4\n",
      "r rhippocampusAAL sub 39 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 39 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 39 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 40 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 40 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 40 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 41 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 41 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 41 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 42 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 42 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 42 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 43 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 43 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 43 layer 4\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 44 layer 2\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 44 layer 3\n",
      "err loading roi data\n",
      "r rhippocampusAAL sub 44 layer 4\n",
      "err loading roi data\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "//anaconda3/envs/brain/lib/python3.6/site-packages/ipykernel_launcher.py:31: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n"
     ]
    }
   ],
   "source": [
    "\"\"\" \n",
    "train and test classifier\n",
    "\"\"\"\n",
    "\n",
    "L = []\n",
    "for roi_name,sub_num,layer_num in itertools.product(ROI_NAME_L,np.arange(45),range(2,5)):\n",
    "  print('r',roi_name,'sub',sub_num,'layer',layer_num)\n",
    "  # load fmri data; \n",
    "  try: # check that fmri files exist\n",
    "    sub_roi_view = load_sub_roi(sub_num,roi_name,'videos')\n",
    "    sub_roi_recall = load_sub_roi(sub_num,roi_name,'recall2')\n",
    "    assert len(sub_roi_view)\n",
    "    assert len(sub_roi_recall)\n",
    "  except:\n",
    "    print('err loading roi data')\n",
    "    continue\n",
    "  ## build train/test datasets\n",
    "  try:\n",
    "    train_TRs,Ytrain = get_training_info(sub_num,layer_num)\n",
    "    test_TRs,Ytest = get_test_info(sub_num,layer_num)\n",
    "    Xtrain = sub_roi_view[train_TRs,:] \n",
    "    Xtest = sub_roi_recall[test_TRs,:]\n",
    "  except:\n",
    "    print('err finding info to build classifier dataset')\n",
    "    continue\n",
    "  # check if recall data exists\n",
    "  if not len(Xtest): \n",
    "    print('no recall data. sub',sub_num,'layer',layer_num)\n",
    "    continue\n",
    "  ## normalize\n",
    "  scaler = StandardScaler()\n",
    "  Xtrain = scaler.fit_transform(Xtrain)\n",
    "  Xtest = scaler.transform(Xtest)\n",
    "  ## fit classifier\n",
    "  clf = sklearn.linear_model.LogisticRegression(solver='liblinear',C=1.00)\n",
    "  clf.fit(Xtrain,Ytrain)\n",
    "  # eval classifier\n",
    "  yhat = clf.predict_proba(Xtrain)\n",
    "  score = clf.score(Xtest,Ytest)\n",
    "  ## record data\n",
    "  D = {}\n",
    "  D['sub_num']=sub_num\n",
    "  D['roi']=roi_name\n",
    "  D['layer']=layer_num\n",
    "  D['num_test_samples']=len(Ytest)\n",
    "  D['score']=score  \n",
    "  L.append(D)\n",
    "\n",
    "## \n",
    "results = pd.DataFrame(L)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "Nsubs = len(results.sub_num.unique())\n",
    "results.to_csv('data/analyses/decodeState_trainView_testRecall-N%i.csv'%Nsubs)\n"
   ]
  }
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