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jminas/why_no_float?

Created November 1, 2013 17:58
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why_no_float?
{
"metadata": {
"name": ""
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "code",
"collapsed": false,
"input": [
"from scipy.io import loadmat\n",
"import pandas as pd\n",
"import numpy as np\n",
"import glob\n",
"from __future__ import division\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"\n",
"import os\n",
"from scipy import stats as st\n",
"from scipy.stats import norm"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 4
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df = pd.read_csv('/home/jminas/Documents/iauhsrfuoiaherou.csv')\n",
"df"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>subject</th>\n",
" <th>session</th>\n",
" <th>Trial</th>\n",
" <th>Trial_type</th>\n",
" <th>Reaction_Time</th>\n",
" <th>Fixation_1_onset</th>\n",
" <th>Instruction_onset</th>\n",
" <th>Stimulus_onset</th>\n",
" <th>Fixation_2_onset</th>\n",
" <th>Probe_onset</th>\n",
" <th>Accuracy</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0 </th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 1</td>\n",
" <td> DRY_cr</td>\n",
" <td> 1.489786</td>\n",
" <td> 0.021435</td>\n",
" <td> 4.036645</td>\n",
" <td> 9.051471</td>\n",
" <td> 10.067761</td>\n",
" <td> 14.083652</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1 </th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 2</td>\n",
" <td> 2R_h</td>\n",
" <td> 0.845029</td>\n",
" <td> 16.132993</td>\n",
" <td> 20.148242</td>\n",
" <td> 23.163798</td>\n",
" <td> 24.179877</td>\n",
" <td> 26.196046</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2 </th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 3</td>\n",
" <td> 4RY_h</td>\n",
" <td> 0.677303</td>\n",
" <td> 28.228318</td>\n",
" <td> 31.244003</td>\n",
" <td> 35.259397</td>\n",
" <td> 36.276368</td>\n",
" <td> 38.292193</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3 </th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 4</td>\n",
" <td> DRY_h</td>\n",
" <td> 1.043895</td>\n",
" <td> 40.324901</td>\n",
" <td> 44.339741</td>\n",
" <td> 47.355573</td>\n",
" <td> 48.371992</td>\n",
" <td> 52.387347</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4 </th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 5</td>\n",
" <td> 4RY_cr</td>\n",
" <td> 0.699229</td>\n",
" <td> 54.420396</td>\n",
" <td> 57.435494</td>\n",
" <td> 62.450462</td>\n",
" <td> 63.466978</td>\n",
" <td> 66.482994</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5 </th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 6</td>\n",
" <td> 2R_cr</td>\n",
" <td> 1.456915</td>\n",
" <td> 68.498710</td>\n",
" <td> 72.514199</td>\n",
" <td> 76.529787</td>\n",
" <td> 77.546002</td>\n",
" <td> 79.561724</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6 </th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 7</td>\n",
" <td> 4RY_h</td>\n",
" <td> 1.679115</td>\n",
" <td> 81.594548</td>\n",
" <td> 84.609550</td>\n",
" <td> 87.625640</td>\n",
" <td> 88.642109</td>\n",
" <td> 91.657912</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7 </th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 8</td>\n",
" <td> 2R_h</td>\n",
" <td> 1.136683</td>\n",
" <td> 93.690656</td>\n",
" <td> 96.706504</td>\n",
" <td> 100.721243</td>\n",
" <td> 101.738023</td>\n",
" <td> 103.753741</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8 </th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 9</td>\n",
" <td> DRY_cr</td>\n",
" <td> 0.824417</td>\n",
" <td> 105.786785</td>\n",
" <td> 108.802024</td>\n",
" <td> 111.818192</td>\n",
" <td> 112.834354</td>\n",
" <td> 116.848395</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9 </th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 10</td>\n",
" <td> 2R_h</td>\n",
" <td> 0.704208</td>\n",
" <td> 118.881506</td>\n",
" <td> 122.896604</td>\n",
" <td> 127.911487</td>\n",
" <td> 128.927985</td>\n",
" <td> 131.943303</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 11</td>\n",
" <td> DRY_h</td>\n",
" <td> 0.926933</td>\n",
" <td> 133.976202</td>\n",
" <td> 137.991489</td>\n",
" <td> 142.006898</td>\n",
" <td> 143.023162</td>\n",
" <td> 147.038233</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 12</td>\n",
" <td> 4RY_h</td>\n",
" <td> 1.485780</td>\n",
" <td> 149.070537</td>\n",
" <td> 153.086369</td>\n",
" <td> 157.101826</td>\n",
" <td> 158.118047</td>\n",
" <td> 162.133466</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 13</td>\n",
" <td> 4RY_fa</td>\n",
" <td> 0.630968</td>\n",
" <td> 164.165568</td>\n",
" <td> 168.180818</td>\n",
" <td> 172.196856</td>\n",
" <td> 173.213236</td>\n",
" <td> 177.228316</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 14</td>\n",
" <td> DRY_h</td>\n",
" <td> 0.941841</td>\n",
" <td> 179.260733</td>\n",
" <td> 182.276938</td>\n",
" <td> 186.292037</td>\n",
" <td> 187.307867</td>\n",
" <td> 189.324796</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 15</td>\n",
" <td> 2R_cr</td>\n",
" <td> 1.246130</td>\n",
" <td> 191.357181</td>\n",
" <td> 194.372404</td>\n",
" <td> 199.388100</td>\n",
" <td> 200.403776</td>\n",
" <td> 202.419958</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 16</td>\n",
" <td> DRY_h</td>\n",
" <td> 0.959472</td>\n",
" <td> 204.452442</td>\n",
" <td> 207.468442</td>\n",
" <td> 212.483215</td>\n",
" <td> 213.499562</td>\n",
" <td> 216.515158</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 17</td>\n",
" <td> 4RY_m</td>\n",
" <td> 1.158538</td>\n",
" <td> 218.530888</td>\n",
" <td> 222.546423</td>\n",
" <td> 225.562261</td>\n",
" <td> 226.578278</td>\n",
" <td> 230.593605</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 18</td>\n",
" <td> 2R_cr</td>\n",
" <td> 0.734570</td>\n",
" <td> 232.626864</td>\n",
" <td> 235.642123</td>\n",
" <td> 238.657791</td>\n",
" <td> 239.673886</td>\n",
" <td> 243.689393</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 19</td>\n",
" <td> 2R_cr</td>\n",
" <td> 0.917417</td>\n",
" <td> 245.721808</td>\n",
" <td> 249.737869</td>\n",
" <td> 253.752572</td>\n",
" <td> 254.769201</td>\n",
" <td> 258.784617</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 20</td>\n",
" <td> 4RY_cr</td>\n",
" <td> 1.143319</td>\n",
" <td> 260.817394</td>\n",
" <td> 264.832724</td>\n",
" <td> 269.847572</td>\n",
" <td> 270.863655</td>\n",
" <td> 272.880078</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 21</td>\n",
" <td> DRY_cr</td>\n",
" <td> 0.753987</td>\n",
" <td> 274.895999</td>\n",
" <td> 278.911357</td>\n",
" <td> 282.926934</td>\n",
" <td> 283.943261</td>\n",
" <td> 285.958878</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 22</td>\n",
" <td> 2R_h</td>\n",
" <td> 0.632535</td>\n",
" <td> 287.975207</td>\n",
" <td> 290.990134</td>\n",
" <td> 296.005395</td>\n",
" <td> 297.021128</td>\n",
" <td> 300.037251</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 23</td>\n",
" <td> DRY_cr</td>\n",
" <td> 1.265268</td>\n",
" <td> 302.069337</td>\n",
" <td> 305.085451</td>\n",
" <td> 310.100264</td>\n",
" <td> 311.116528</td>\n",
" <td> 313.132531</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 24</td>\n",
" <td> 4RY_cr</td>\n",
" <td> 1.312230</td>\n",
" <td> 315.148799</td>\n",
" <td> 318.164500</td>\n",
" <td> 322.179484</td>\n",
" <td> 323.196205</td>\n",
" <td> 325.212088</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 25</td>\n",
" <td> 2R_cr</td>\n",
" <td> 0.752770</td>\n",
" <td> 327.227452</td>\n",
" <td> 330.243708</td>\n",
" <td> 333.259146</td>\n",
" <td> 334.275457</td>\n",
" <td> 337.291333</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 26</td>\n",
" <td> 4RY_fa</td>\n",
" <td> 1.375301</td>\n",
" <td> 339.307095</td>\n",
" <td> 342.322564</td>\n",
" <td> 347.337944</td>\n",
" <td> 348.354172</td>\n",
" <td> 351.369260</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 27</td>\n",
" <td> DRY_cr</td>\n",
" <td> 0.585002</td>\n",
" <td> 353.385888</td>\n",
" <td> 356.401332</td>\n",
" <td> 361.416550</td>\n",
" <td> 362.432631</td>\n",
" <td> 365.448624</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 28</td>\n",
" <td> 2R_h</td>\n",
" <td> 0.933963</td>\n",
" <td> 367.481352</td>\n",
" <td> 371.496540</td>\n",
" <td> 374.511728</td>\n",
" <td> 375.528433</td>\n",
" <td> 379.543135</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 29</td>\n",
" <td> DRY_cr</td>\n",
" <td> 0.648839</td>\n",
" <td> 381.575908</td>\n",
" <td> 385.591399</td>\n",
" <td> 388.607429</td>\n",
" <td> 389.623640</td>\n",
" <td> 392.639220</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 30</td>\n",
" <td> 4RY_h</td>\n",
" <td> 0.632727</td>\n",
" <td> 394.671399</td>\n",
" <td> 398.687306</td>\n",
" <td> 401.702806</td>\n",
" <td> 402.719377</td>\n",
" <td> 405.734857</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 1</td>\n",
" <td> 4RY_cr</td>\n",
" <td> 0.876987</td>\n",
" <td> 0.017930</td>\n",
" <td> 3.033248</td>\n",
" <td> 8.048419</td>\n",
" <td> 9.064541</td>\n",
" <td> 11.080478</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>31</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 2</td>\n",
" <td> DRY_h</td>\n",
" <td> 1.058671</td>\n",
" <td> 13.112584</td>\n",
" <td> 17.128793</td>\n",
" <td> 22.143722</td>\n",
" <td> 23.159750</td>\n",
" <td> 25.175848</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 3</td>\n",
" <td> 2R_h</td>\n",
" <td> 0.690472</td>\n",
" <td> 27.191645</td>\n",
" <td> 31.207420</td>\n",
" <td> 36.222278</td>\n",
" <td> 37.238754</td>\n",
" <td> 40.254106</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>33</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 4</td>\n",
" <td> DRY_h</td>\n",
" <td> 1.054261</td>\n",
" <td> 42.286474</td>\n",
" <td> 46.302070</td>\n",
" <td> 50.317478</td>\n",
" <td> 51.333701</td>\n",
" <td> 53.349959</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>34</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 5</td>\n",
" <td> 4RY_cr</td>\n",
" <td> 0.949158</td>\n",
" <td> 55.381924</td>\n",
" <td> 58.398029</td>\n",
" <td> 63.413443</td>\n",
" <td> 64.429355</td>\n",
" <td> 68.444981</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>35</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 6</td>\n",
" <td> 2R_cr</td>\n",
" <td> 1.208110</td>\n",
" <td> 70.461176</td>\n",
" <td> 74.475980</td>\n",
" <td> 78.491689</td>\n",
" <td> 79.507906</td>\n",
" <td> 81.523854</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>36</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 7</td>\n",
" <td> 4RY_cr</td>\n",
" <td> 1.081796</td>\n",
" <td> 83.539104</td>\n",
" <td> 86.555483</td>\n",
" <td> 89.570998</td>\n",
" <td> 90.587037</td>\n",
" <td> 92.603296</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>37</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 8</td>\n",
" <td> DRY_h</td>\n",
" <td> 0.943692</td>\n",
" <td> 94.618724</td>\n",
" <td> 98.634084</td>\n",
" <td> 103.649740</td>\n",
" <td> 104.665850</td>\n",
" <td> 107.681615</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>38</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 9</td>\n",
" <td> 2R_cr</td>\n",
" <td> 0.981080</td>\n",
" <td> 109.697773</td>\n",
" <td> 113.712432</td>\n",
" <td> 118.727934</td>\n",
" <td> 119.743847</td>\n",
" <td> 121.759635</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>39</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 10</td>\n",
" <td> DRY_h</td>\n",
" <td> 0.829796</td>\n",
" <td> 123.792629</td>\n",
" <td> 127.807833</td>\n",
" <td> 130.823750</td>\n",
" <td> 131.839862</td>\n",
" <td> 135.855530</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>40</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 11</td>\n",
" <td> 4RY_h</td>\n",
" <td> 1.500785</td>\n",
" <td> 137.871400</td>\n",
" <td> 141.886942</td>\n",
" <td> 145.901719</td>\n",
" <td> 146.918400</td>\n",
" <td> 150.933949</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>41</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 12</td>\n",
" <td> 2R_h</td>\n",
" <td> 1.536864</td>\n",
" <td> 152.966742</td>\n",
" <td> 156.981719</td>\n",
" <td> 160.997330</td>\n",
" <td> 162.013391</td>\n",
" <td> 166.028706</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>42</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 13</td>\n",
" <td> 2R_h</td>\n",
" <td> 1.136647</td>\n",
" <td> 168.044810</td>\n",
" <td> 172.059831</td>\n",
" <td> 175.075749</td>\n",
" <td> 176.091904</td>\n",
" <td> 179.108012</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>43</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 14</td>\n",
" <td> 4RY_nr</td>\n",
" <td> NaN</td>\n",
" <td> 181.140096</td>\n",
" <td> 185.155370</td>\n",
" <td> 189.170549</td>\n",
" <td> 190.186896</td>\n",
" <td> 193.202615</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>44</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 15</td>\n",
" <td> DRY_cr</td>\n",
" <td> 1.272600</td>\n",
" <td> 195.235196</td>\n",
" <td> 199.250353</td>\n",
" <td> 202.266476</td>\n",
" <td> 203.282883</td>\n",
" <td> 206.298382</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 16</td>\n",
" <td> 4RY_cr</td>\n",
" <td> 1.062302</td>\n",
" <td> 208.330772</td>\n",
" <td> 212.345805</td>\n",
" <td> 217.361376</td>\n",
" <td> 218.377696</td>\n",
" <td> 222.393067</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>46</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 17</td>\n",
" <td> 2R_cr</td>\n",
" <td> 1.677504</td>\n",
" <td> 224.408427</td>\n",
" <td> 227.424595</td>\n",
" <td> 232.439443</td>\n",
" <td> 233.455782</td>\n",
" <td> 237.471219</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>47</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 18</td>\n",
" <td> DRY_h</td>\n",
" <td> 0.888521</td>\n",
" <td> 239.504001</td>\n",
" <td> 242.519436</td>\n",
" <td> 245.535181</td>\n",
" <td> 246.551823</td>\n",
" <td> 250.566942</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>48</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 19</td>\n",
" <td> 4RY_cr</td>\n",
" <td> 1.225967</td>\n",
" <td> 252.599545</td>\n",
" <td> 255.615103</td>\n",
" <td> 259.630436</td>\n",
" <td> 260.646930</td>\n",
" <td> 262.662711</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>49</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 20</td>\n",
" <td> 2R_h</td>\n",
" <td> 1.376171</td>\n",
" <td> 264.695435</td>\n",
" <td> 267.710971</td>\n",
" <td> 271.726119</td>\n",
" <td> 272.742591</td>\n",
" <td> 275.758338</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 21</td>\n",
" <td> DRY_fa</td>\n",
" <td> 1.112251</td>\n",
" <td> 277.774158</td>\n",
" <td> 280.789343</td>\n",
" <td> 284.804923</td>\n",
" <td> 285.821602</td>\n",
" <td> 289.836585</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>51</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 22</td>\n",
" <td> DRY_cr</td>\n",
" <td> 1.179686</td>\n",
" <td> 291.853218</td>\n",
" <td> 294.868666</td>\n",
" <td> 298.883516</td>\n",
" <td> 299.900073</td>\n",
" <td> 301.916316</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>52</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 23</td>\n",
" <td> 2R_cr</td>\n",
" <td> 1.167593</td>\n",
" <td> 303.948465</td>\n",
" <td> 306.964286</td>\n",
" <td> 310.980121</td>\n",
" <td> 311.995762</td>\n",
" <td> 316.010835</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>53</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 24</td>\n",
" <td> 4RY_cr</td>\n",
" <td> 0.822557</td>\n",
" <td> 318.044026</td>\n",
" <td> 322.058843</td>\n",
" <td> 325.074434</td>\n",
" <td> 326.090955</td>\n",
" <td> 329.106882</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>54</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 25</td>\n",
" <td> 2R_h</td>\n",
" <td> 1.509566</td>\n",
" <td> 331.139326</td>\n",
" <td> 334.155217</td>\n",
" <td> 337.171061</td>\n",
" <td> 338.186869</td>\n",
" <td> 340.203432</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>55</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 26</td>\n",
" <td> 4RY_h</td>\n",
" <td> 1.077532</td>\n",
" <td> 342.235866</td>\n",
" <td> 345.251381</td>\n",
" <td> 348.267380</td>\n",
" <td> 349.283514</td>\n",
" <td> 352.299301</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>56</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 27</td>\n",
" <td> DRY_cr</td>\n",
" <td> 0.736435</td>\n",
" <td> 354.331714</td>\n",
" <td> 357.347522</td>\n",
" <td> 360.363077</td>\n",
" <td> 361.379055</td>\n",
" <td> 364.395067</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>57</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 28</td>\n",
" <td> DRY_fa</td>\n",
" <td> 1.955766</td>\n",
" <td> 366.427073</td>\n",
" <td> 369.443377</td>\n",
" <td> 374.458267</td>\n",
" <td> 375.474592</td>\n",
" <td> 377.490900</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>58</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 29</td>\n",
" <td> 4RY_h</td>\n",
" <td> 1.017861</td>\n",
" <td> 379.506862</td>\n",
" <td> 383.522149</td>\n",
" <td> 388.536939</td>\n",
" <td> 389.553382</td>\n",
" <td> 393.568753</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>59</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 30</td>\n",
" <td> 2R_cr</td>\n",
" <td> 0.872621</td>\n",
" <td> 395.601404</td>\n",
" <td> 398.616716</td>\n",
" <td> 401.632723</td>\n",
" <td> 402.648591</td>\n",
" <td> 405.664458</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 6,
"text": [
" subject session Trial Trial_type Reaction_Time Fixation_1_onset \\\n",
"0 2016 2 1 DRY_cr 1.489786 0.021435 \n",
"1 2016 2 2 2R_h 0.845029 16.132993 \n",
"2 2016 2 3 4RY_h 0.677303 28.228318 \n",
"3 2016 2 4 DRY_h 1.043895 40.324901 \n",
"4 2016 2 5 4RY_cr 0.699229 54.420396 \n",
"5 2016 2 6 2R_cr 1.456915 68.498710 \n",
"6 2016 2 7 4RY_h 1.679115 81.594548 \n",
"7 2016 2 8 2R_h 1.136683 93.690656 \n",
"8 2016 2 9 DRY_cr 0.824417 105.786785 \n",
"9 2016 2 10 2R_h 0.704208 118.881506 \n",
"10 2016 2 11 DRY_h 0.926933 133.976202 \n",
"11 2016 2 12 4RY_h 1.485780 149.070537 \n",
"12 2016 2 13 4RY_fa 0.630968 164.165568 \n",
"13 2016 2 14 DRY_h 0.941841 179.260733 \n",
"14 2016 2 15 2R_cr 1.246130 191.357181 \n",
"15 2016 2 16 DRY_h 0.959472 204.452442 \n",
"16 2016 2 17 4RY_m 1.158538 218.530888 \n",
"17 2016 2 18 2R_cr 0.734570 232.626864 \n",
"18 2016 2 19 2R_cr 0.917417 245.721808 \n",
"19 2016 2 20 4RY_cr 1.143319 260.817394 \n",
"20 2016 2 21 DRY_cr 0.753987 274.895999 \n",
"21 2016 2 22 2R_h 0.632535 287.975207 \n",
"22 2016 2 23 DRY_cr 1.265268 302.069337 \n",
"23 2016 2 24 4RY_cr 1.312230 315.148799 \n",
"24 2016 2 25 2R_cr 0.752770 327.227452 \n",
"25 2016 2 26 4RY_fa 1.375301 339.307095 \n",
"26 2016 2 27 DRY_cr 0.585002 353.385888 \n",
"27 2016 2 28 2R_h 0.933963 367.481352 \n",
"28 2016 2 29 DRY_cr 0.648839 381.575908 \n",
"29 2016 2 30 4RY_h 0.632727 394.671399 \n",
"30 2016 2 1 4RY_cr 0.876987 0.017930 \n",
"31 2016 2 2 DRY_h 1.058671 13.112584 \n",
"32 2016 2 3 2R_h 0.690472 27.191645 \n",
"33 2016 2 4 DRY_h 1.054261 42.286474 \n",
"34 2016 2 5 4RY_cr 0.949158 55.381924 \n",
"35 2016 2 6 2R_cr 1.208110 70.461176 \n",
"36 2016 2 7 4RY_cr 1.081796 83.539104 \n",
"37 2016 2 8 DRY_h 0.943692 94.618724 \n",
"38 2016 2 9 2R_cr 0.981080 109.697773 \n",
"39 2016 2 10 DRY_h 0.829796 123.792629 \n",
"40 2016 2 11 4RY_h 1.500785 137.871400 \n",
"41 2016 2 12 2R_h 1.536864 152.966742 \n",
"42 2016 2 13 2R_h 1.136647 168.044810 \n",
"43 2016 2 14 4RY_nr NaN 181.140096 \n",
"44 2016 2 15 DRY_cr 1.272600 195.235196 \n",
"45 2016 2 16 4RY_cr 1.062302 208.330772 \n",
"46 2016 2 17 2R_cr 1.677504 224.408427 \n",
"47 2016 2 18 DRY_h 0.888521 239.504001 \n",
"48 2016 2 19 4RY_cr 1.225967 252.599545 \n",
"49 2016 2 20 2R_h 1.376171 264.695435 \n",
"50 2016 2 21 DRY_fa 1.112251 277.774158 \n",
"51 2016 2 22 DRY_cr 1.179686 291.853218 \n",
"52 2016 2 23 2R_cr 1.167593 303.948465 \n",
"53 2016 2 24 4RY_cr 0.822557 318.044026 \n",
"54 2016 2 25 2R_h 1.509566 331.139326 \n",
"55 2016 2 26 4RY_h 1.077532 342.235866 \n",
"56 2016 2 27 DRY_cr 0.736435 354.331714 \n",
"57 2016 2 28 DRY_fa 1.955766 366.427073 \n",
"58 2016 2 29 4RY_h 1.017861 379.506862 \n",
"59 2016 2 30 2R_cr 0.872621 395.601404 \n",
"\n",
" Instruction_onset Stimulus_onset Fixation_2_onset Probe_onset Accuracy \n",
"0 4.036645 9.051471 10.067761 14.083652 1 \n",
"1 20.148242 23.163798 24.179877 26.196046 1 \n",
"2 31.244003 35.259397 36.276368 38.292193 1 \n",
"3 44.339741 47.355573 48.371992 52.387347 1 \n",
"4 57.435494 62.450462 63.466978 66.482994 1 \n",
"5 72.514199 76.529787 77.546002 79.561724 1 \n",
"6 84.609550 87.625640 88.642109 91.657912 1 \n",
"7 96.706504 100.721243 101.738023 103.753741 1 \n",
"8 108.802024 111.818192 112.834354 116.848395 1 \n",
"9 122.896604 127.911487 128.927985 131.943303 1 \n",
"10 137.991489 142.006898 143.023162 147.038233 1 \n",
"11 153.086369 157.101826 158.118047 162.133466 1 \n",
"12 168.180818 172.196856 173.213236 177.228316 0 \n",
"13 182.276938 186.292037 187.307867 189.324796 1 \n",
"14 194.372404 199.388100 200.403776 202.419958 1 \n",
"15 207.468442 212.483215 213.499562 216.515158 1 \n",
"16 222.546423 225.562261 226.578278 230.593605 0 \n",
"17 235.642123 238.657791 239.673886 243.689393 1 \n",
"18 249.737869 253.752572 254.769201 258.784617 1 \n",
"19 264.832724 269.847572 270.863655 272.880078 1 \n",
"20 278.911357 282.926934 283.943261 285.958878 1 \n",
"21 290.990134 296.005395 297.021128 300.037251 1 \n",
"22 305.085451 310.100264 311.116528 313.132531 1 \n",
"23 318.164500 322.179484 323.196205 325.212088 1 \n",
"24 330.243708 333.259146 334.275457 337.291333 1 \n",
"25 342.322564 347.337944 348.354172 351.369260 0 \n",
"26 356.401332 361.416550 362.432631 365.448624 1 \n",
"27 371.496540 374.511728 375.528433 379.543135 1 \n",
"28 385.591399 388.607429 389.623640 392.639220 1 \n",
"29 398.687306 401.702806 402.719377 405.734857 1 \n",
"30 3.033248 8.048419 9.064541 11.080478 1 \n",
"31 17.128793 22.143722 23.159750 25.175848 1 \n",
"32 31.207420 36.222278 37.238754 40.254106 1 \n",
"33 46.302070 50.317478 51.333701 53.349959 1 \n",
"34 58.398029 63.413443 64.429355 68.444981 1 \n",
"35 74.475980 78.491689 79.507906 81.523854 1 \n",
"36 86.555483 89.570998 90.587037 92.603296 1 \n",
"37 98.634084 103.649740 104.665850 107.681615 1 \n",
"38 113.712432 118.727934 119.743847 121.759635 1 \n",
"39 127.807833 130.823750 131.839862 135.855530 1 \n",
"40 141.886942 145.901719 146.918400 150.933949 1 \n",
"41 156.981719 160.997330 162.013391 166.028706 1 \n",
"42 172.059831 175.075749 176.091904 179.108012 1 \n",
"43 185.155370 189.170549 190.186896 193.202615 0 \n",
"44 199.250353 202.266476 203.282883 206.298382 1 \n",
"45 212.345805 217.361376 218.377696 222.393067 1 \n",
"46 227.424595 232.439443 233.455782 237.471219 1 \n",
"47 242.519436 245.535181 246.551823 250.566942 1 \n",
"48 255.615103 259.630436 260.646930 262.662711 1 \n",
"49 267.710971 271.726119 272.742591 275.758338 1 \n",
"50 280.789343 284.804923 285.821602 289.836585 0 \n",
"51 294.868666 298.883516 299.900073 301.916316 1 \n",
"52 306.964286 310.980121 311.995762 316.010835 1 \n",
"53 322.058843 325.074434 326.090955 329.106882 1 \n",
"54 334.155217 337.171061 338.186869 340.203432 1 \n",
"55 345.251381 348.267380 349.283514 352.299301 1 \n",
"56 357.347522 360.363077 361.379055 364.395067 1 \n",
"57 369.443377 374.458267 375.474592 377.490900 0 \n",
"58 383.522149 388.536939 389.553382 393.568753 1 \n",
"59 398.616716 401.632723 402.648591 405.664458 1 "
]
}
],
"prompt_number": 6
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"i want to subtract \"probe_onset\" , (index 0) from \"fixation_onset\" (index 1)"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"d = {'one' : [1., 2., 3., 4.],'two' : [4., 3., 2., 1.], 'three' : [ 1., 1., 1., 1.]}\n",
"d = pd.DataFrame(d)\n",
"d"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>one</th>\n",
" <th>three</th>\n",
" <th>two</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> 4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td> 2</td>\n",
" <td> 1</td>\n",
" <td> 3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td> 3</td>\n",
" <td> 1</td>\n",
" <td> 2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td> 4</td>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 26,
"text": [
" one three two\n",
"0 1 1 4\n",
"1 2 1 3\n",
"2 3 1 2\n",
"3 4 1 1"
]
}
],
"prompt_number": 26
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"d['diff'] = 0\n",
"for ii in range(d.shape[0] - 1):\n",
" d['diff'][ii] = d['two'][ii] - d['one'][ii + 1]\n",
"d"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>one</th>\n",
" <th>three</th>\n",
" <th>two</th>\n",
" <th>diff</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> 4</td>\n",
" <td> 2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td> 2</td>\n",
" <td> 1</td>\n",
" <td> 3</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td> 3</td>\n",
" <td> 1</td>\n",
" <td> 2</td>\n",
" <td>-2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td> 4</td>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 31,
"text": [
" one three two diff\n",
"0 1 1 4 2\n",
"1 2 1 3 0\n",
"2 3 1 2 -2\n",
"3 4 1 1 0"
]
}
],
"prompt_number": 31
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"d['diff2'] = 0\n",
"for ii in range(d.shape[0] - 1):\n",
" d['diff2'][ii] = d['one'][ii] - d['two'][ii + 1]\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
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" <th></th>\n",
" <th>one</th>\n",
" <th>three</th>\n",
" <th>two</th>\n",
" <th>diff</th>\n",
" <th>diff2</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td> 1</td>\n",
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" <td> 4</td>\n",
" <td> 2</td>\n",
" <td>-2</td>\n",
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" <tr>\n",
" <th>1</th>\n",
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" <td> 1</td>\n",
" <td> 3</td>\n",
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" <tr>\n",
" <th>2</th>\n",
" <td> 3</td>\n",
" <td> 1</td>\n",
" <td> 2</td>\n",
" <td>-2</td>\n",
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" <th>3</th>\n",
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" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 32,
"text": [
" one three two diff diff2\n",
"0 1 1 4 2 -2\n",
"1 2 1 3 0 0\n",
"2 3 1 2 -2 2\n",
"3 4 1 1 0 0"
]
}
],
"prompt_number": 32
},
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"THIS IS WHAT HAPPENS ---> NO FLOAT????"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df['probe_onset'] = df.apply(lambda row: (row['Probe_onset']),axis = 1)\n",
"df['probe_duration'] = 0\n",
"for ii in range(df.shape[0]-1):\n",
" df['probe_duration'][ii] = df['Instruction_onset'][ii+1] - df['probe_onset'][ii]\n",
"df"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>subject</th>\n",
" <th>session</th>\n",
" <th>Trial</th>\n",
" <th>Trial_type</th>\n",
" <th>Reaction_Time</th>\n",
" <th>Fixation_1_onset</th>\n",
" <th>Instruction_onset</th>\n",
" <th>Stimulus_onset</th>\n",
" <th>Fixation_2_onset</th>\n",
" <th>Probe_onset</th>\n",
" <th>Accuracy</th>\n",
" <th>probe_onset</th>\n",
" <th>probe_duration</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0 </th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 1</td>\n",
" <td> DRY_cr</td>\n",
" <td> 1.489786</td>\n",
" <td> 0.021435</td>\n",
" <td> 4.036645</td>\n",
" <td> 9.051471</td>\n",
" <td> 10.067761</td>\n",
" <td> 14.083652</td>\n",
" <td> 1</td>\n",
" <td> 14.083652</td>\n",
" <td> 6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1 </th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 2</td>\n",
" <td> 2R_h</td>\n",
" <td> 0.845029</td>\n",
" <td> 16.132993</td>\n",
" <td> 20.148242</td>\n",
" <td> 23.163798</td>\n",
" <td> 24.179877</td>\n",
" <td> 26.196046</td>\n",
" <td> 1</td>\n",
" <td> 26.196046</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2 </th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 3</td>\n",
" <td> 4RY_h</td>\n",
" <td> 0.677303</td>\n",
" <td> 28.228318</td>\n",
" <td> 31.244003</td>\n",
" <td> 35.259397</td>\n",
" <td> 36.276368</td>\n",
" <td> 38.292193</td>\n",
" <td> 1</td>\n",
" <td> 38.292193</td>\n",
" <td> 6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3 </th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 4</td>\n",
" <td> DRY_h</td>\n",
" <td> 1.043895</td>\n",
" <td> 40.324901</td>\n",
" <td> 44.339741</td>\n",
" <td> 47.355573</td>\n",
" <td> 48.371992</td>\n",
" <td> 52.387347</td>\n",
" <td> 1</td>\n",
" <td> 52.387347</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4 </th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 5</td>\n",
" <td> 4RY_cr</td>\n",
" <td> 0.699229</td>\n",
" <td> 54.420396</td>\n",
" <td> 57.435494</td>\n",
" <td> 62.450462</td>\n",
" <td> 63.466978</td>\n",
" <td> 66.482994</td>\n",
" <td> 1</td>\n",
" <td> 66.482994</td>\n",
" <td> 6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5 </th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 6</td>\n",
" <td> 2R_cr</td>\n",
" <td> 1.456915</td>\n",
" <td> 68.498710</td>\n",
" <td> 72.514199</td>\n",
" <td> 76.529787</td>\n",
" <td> 77.546002</td>\n",
" <td> 79.561724</td>\n",
" <td> 1</td>\n",
" <td> 79.561724</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6 </th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 7</td>\n",
" <td> 4RY_h</td>\n",
" <td> 1.679115</td>\n",
" <td> 81.594548</td>\n",
" <td> 84.609550</td>\n",
" <td> 87.625640</td>\n",
" <td> 88.642109</td>\n",
" <td> 91.657912</td>\n",
" <td> 1</td>\n",
" <td> 91.657912</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7 </th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 8</td>\n",
" <td> 2R_h</td>\n",
" <td> 1.136683</td>\n",
" <td> 93.690656</td>\n",
" <td> 96.706504</td>\n",
" <td> 100.721243</td>\n",
" <td> 101.738023</td>\n",
" <td> 103.753741</td>\n",
" <td> 1</td>\n",
" <td> 103.753741</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8 </th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 9</td>\n",
" <td> DRY_cr</td>\n",
" <td> 0.824417</td>\n",
" <td> 105.786785</td>\n",
" <td> 108.802024</td>\n",
" <td> 111.818192</td>\n",
" <td> 112.834354</td>\n",
" <td> 116.848395</td>\n",
" <td> 1</td>\n",
" <td> 116.848395</td>\n",
" <td> 6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9 </th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 10</td>\n",
" <td> 2R_h</td>\n",
" <td> 0.704208</td>\n",
" <td> 118.881506</td>\n",
" <td> 122.896604</td>\n",
" <td> 127.911487</td>\n",
" <td> 128.927985</td>\n",
" <td> 131.943303</td>\n",
" <td> 1</td>\n",
" <td> 131.943303</td>\n",
" <td> 6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 11</td>\n",
" <td> DRY_h</td>\n",
" <td> 0.926933</td>\n",
" <td> 133.976202</td>\n",
" <td> 137.991489</td>\n",
" <td> 142.006898</td>\n",
" <td> 143.023162</td>\n",
" <td> 147.038233</td>\n",
" <td> 1</td>\n",
" <td> 147.038233</td>\n",
" <td> 6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 12</td>\n",
" <td> 4RY_h</td>\n",
" <td> 1.485780</td>\n",
" <td> 149.070537</td>\n",
" <td> 153.086369</td>\n",
" <td> 157.101826</td>\n",
" <td> 158.118047</td>\n",
" <td> 162.133466</td>\n",
" <td> 1</td>\n",
" <td> 162.133466</td>\n",
" <td> 6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 13</td>\n",
" <td> 4RY_fa</td>\n",
" <td> 0.630968</td>\n",
" <td> 164.165568</td>\n",
" <td> 168.180818</td>\n",
" <td> 172.196856</td>\n",
" <td> 173.213236</td>\n",
" <td> 177.228316</td>\n",
" <td> 0</td>\n",
" <td> 177.228316</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 14</td>\n",
" <td> DRY_h</td>\n",
" <td> 0.941841</td>\n",
" <td> 179.260733</td>\n",
" <td> 182.276938</td>\n",
" <td> 186.292037</td>\n",
" <td> 187.307867</td>\n",
" <td> 189.324796</td>\n",
" <td> 1</td>\n",
" <td> 189.324796</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 15</td>\n",
" <td> 2R_cr</td>\n",
" <td> 1.246130</td>\n",
" <td> 191.357181</td>\n",
" <td> 194.372404</td>\n",
" <td> 199.388100</td>\n",
" <td> 200.403776</td>\n",
" <td> 202.419958</td>\n",
" <td> 1</td>\n",
" <td> 202.419958</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 16</td>\n",
" <td> DRY_h</td>\n",
" <td> 0.959472</td>\n",
" <td> 204.452442</td>\n",
" <td> 207.468442</td>\n",
" <td> 212.483215</td>\n",
" <td> 213.499562</td>\n",
" <td> 216.515158</td>\n",
" <td> 1</td>\n",
" <td> 216.515158</td>\n",
" <td> 6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 17</td>\n",
" <td> 4RY_m</td>\n",
" <td> 1.158538</td>\n",
" <td> 218.530888</td>\n",
" <td> 222.546423</td>\n",
" <td> 225.562261</td>\n",
" <td> 226.578278</td>\n",
" <td> 230.593605</td>\n",
" <td> 0</td>\n",
" <td> 230.593605</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 18</td>\n",
" <td> 2R_cr</td>\n",
" <td> 0.734570</td>\n",
" <td> 232.626864</td>\n",
" <td> 235.642123</td>\n",
" <td> 238.657791</td>\n",
" <td> 239.673886</td>\n",
" <td> 243.689393</td>\n",
" <td> 1</td>\n",
" <td> 243.689393</td>\n",
" <td> 6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 19</td>\n",
" <td> 2R_cr</td>\n",
" <td> 0.917417</td>\n",
" <td> 245.721808</td>\n",
" <td> 249.737869</td>\n",
" <td> 253.752572</td>\n",
" <td> 254.769201</td>\n",
" <td> 258.784617</td>\n",
" <td> 1</td>\n",
" <td> 258.784617</td>\n",
" <td> 6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 20</td>\n",
" <td> 4RY_cr</td>\n",
" <td> 1.143319</td>\n",
" <td> 260.817394</td>\n",
" <td> 264.832724</td>\n",
" <td> 269.847572</td>\n",
" <td> 270.863655</td>\n",
" <td> 272.880078</td>\n",
" <td> 1</td>\n",
" <td> 272.880078</td>\n",
" <td> 6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 21</td>\n",
" <td> DRY_cr</td>\n",
" <td> 0.753987</td>\n",
" <td> 274.895999</td>\n",
" <td> 278.911357</td>\n",
" <td> 282.926934</td>\n",
" <td> 283.943261</td>\n",
" <td> 285.958878</td>\n",
" <td> 1</td>\n",
" <td> 285.958878</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 22</td>\n",
" <td> 2R_h</td>\n",
" <td> 0.632535</td>\n",
" <td> 287.975207</td>\n",
" <td> 290.990134</td>\n",
" <td> 296.005395</td>\n",
" <td> 297.021128</td>\n",
" <td> 300.037251</td>\n",
" <td> 1</td>\n",
" <td> 300.037251</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 23</td>\n",
" <td> DRY_cr</td>\n",
" <td> 1.265268</td>\n",
" <td> 302.069337</td>\n",
" <td> 305.085451</td>\n",
" <td> 310.100264</td>\n",
" <td> 311.116528</td>\n",
" <td> 313.132531</td>\n",
" <td> 1</td>\n",
" <td> 313.132531</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 24</td>\n",
" <td> 4RY_cr</td>\n",
" <td> 1.312230</td>\n",
" <td> 315.148799</td>\n",
" <td> 318.164500</td>\n",
" <td> 322.179484</td>\n",
" <td> 323.196205</td>\n",
" <td> 325.212088</td>\n",
" <td> 1</td>\n",
" <td> 325.212088</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 25</td>\n",
" <td> 2R_cr</td>\n",
" <td> 0.752770</td>\n",
" <td> 327.227452</td>\n",
" <td> 330.243708</td>\n",
" <td> 333.259146</td>\n",
" <td> 334.275457</td>\n",
" <td> 337.291333</td>\n",
" <td> 1</td>\n",
" <td> 337.291333</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 26</td>\n",
" <td> 4RY_fa</td>\n",
" <td> 1.375301</td>\n",
" <td> 339.307095</td>\n",
" <td> 342.322564</td>\n",
" <td> 347.337944</td>\n",
" <td> 348.354172</td>\n",
" <td> 351.369260</td>\n",
" <td> 0</td>\n",
" <td> 351.369260</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 27</td>\n",
" <td> DRY_cr</td>\n",
" <td> 0.585002</td>\n",
" <td> 353.385888</td>\n",
" <td> 356.401332</td>\n",
" <td> 361.416550</td>\n",
" <td> 362.432631</td>\n",
" <td> 365.448624</td>\n",
" <td> 1</td>\n",
" <td> 365.448624</td>\n",
" <td> 6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 28</td>\n",
" <td> 2R_h</td>\n",
" <td> 0.933963</td>\n",
" <td> 367.481352</td>\n",
" <td> 371.496540</td>\n",
" <td> 374.511728</td>\n",
" <td> 375.528433</td>\n",
" <td> 379.543135</td>\n",
" <td> 1</td>\n",
" <td> 379.543135</td>\n",
" <td> 6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 29</td>\n",
" <td> DRY_cr</td>\n",
" <td> 0.648839</td>\n",
" <td> 381.575908</td>\n",
" <td> 385.591399</td>\n",
" <td> 388.607429</td>\n",
" <td> 389.623640</td>\n",
" <td> 392.639220</td>\n",
" <td> 1</td>\n",
" <td> 392.639220</td>\n",
" <td> 6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 30</td>\n",
" <td> 4RY_h</td>\n",
" <td> 0.632727</td>\n",
" <td> 394.671399</td>\n",
" <td> 398.687306</td>\n",
" <td> 401.702806</td>\n",
" <td> 402.719377</td>\n",
" <td> 405.734857</td>\n",
" <td> 1</td>\n",
" <td> 405.734857</td>\n",
" <td>-402</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 1</td>\n",
" <td> 4RY_cr</td>\n",
" <td> 0.876987</td>\n",
" <td> 0.017930</td>\n",
" <td> 3.033248</td>\n",
" <td> 8.048419</td>\n",
" <td> 9.064541</td>\n",
" <td> 11.080478</td>\n",
" <td> 1</td>\n",
" <td> 11.080478</td>\n",
" <td> 6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>31</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 2</td>\n",
" <td> DRY_h</td>\n",
" <td> 1.058671</td>\n",
" <td> 13.112584</td>\n",
" <td> 17.128793</td>\n",
" <td> 22.143722</td>\n",
" <td> 23.159750</td>\n",
" <td> 25.175848</td>\n",
" <td> 1</td>\n",
" <td> 25.175848</td>\n",
" <td> 6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 3</td>\n",
" <td> 2R_h</td>\n",
" <td> 0.690472</td>\n",
" <td> 27.191645</td>\n",
" <td> 31.207420</td>\n",
" <td> 36.222278</td>\n",
" <td> 37.238754</td>\n",
" <td> 40.254106</td>\n",
" <td> 1</td>\n",
" <td> 40.254106</td>\n",
" <td> 6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>33</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 4</td>\n",
" <td> DRY_h</td>\n",
" <td> 1.054261</td>\n",
" <td> 42.286474</td>\n",
" <td> 46.302070</td>\n",
" <td> 50.317478</td>\n",
" <td> 51.333701</td>\n",
" <td> 53.349959</td>\n",
" <td> 1</td>\n",
" <td> 53.349959</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>34</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 5</td>\n",
" <td> 4RY_cr</td>\n",
" <td> 0.949158</td>\n",
" <td> 55.381924</td>\n",
" <td> 58.398029</td>\n",
" <td> 63.413443</td>\n",
" <td> 64.429355</td>\n",
" <td> 68.444981</td>\n",
" <td> 1</td>\n",
" <td> 68.444981</td>\n",
" <td> 6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>35</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 6</td>\n",
" <td> 2R_cr</td>\n",
" <td> 1.208110</td>\n",
" <td> 70.461176</td>\n",
" <td> 74.475980</td>\n",
" <td> 78.491689</td>\n",
" <td> 79.507906</td>\n",
" <td> 81.523854</td>\n",
" <td> 1</td>\n",
" <td> 81.523854</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>36</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 7</td>\n",
" <td> 4RY_cr</td>\n",
" <td> 1.081796</td>\n",
" <td> 83.539104</td>\n",
" <td> 86.555483</td>\n",
" <td> 89.570998</td>\n",
" <td> 90.587037</td>\n",
" <td> 92.603296</td>\n",
" <td> 1</td>\n",
" <td> 92.603296</td>\n",
" <td> 6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>37</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 8</td>\n",
" <td> DRY_h</td>\n",
" <td> 0.943692</td>\n",
" <td> 94.618724</td>\n",
" <td> 98.634084</td>\n",
" <td> 103.649740</td>\n",
" <td> 104.665850</td>\n",
" <td> 107.681615</td>\n",
" <td> 1</td>\n",
" <td> 107.681615</td>\n",
" <td> 6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>38</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 9</td>\n",
" <td> 2R_cr</td>\n",
" <td> 0.981080</td>\n",
" <td> 109.697773</td>\n",
" <td> 113.712432</td>\n",
" <td> 118.727934</td>\n",
" <td> 119.743847</td>\n",
" <td> 121.759635</td>\n",
" <td> 1</td>\n",
" <td> 121.759635</td>\n",
" <td> 6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>39</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 10</td>\n",
" <td> DRY_h</td>\n",
" <td> 0.829796</td>\n",
" <td> 123.792629</td>\n",
" <td> 127.807833</td>\n",
" <td> 130.823750</td>\n",
" <td> 131.839862</td>\n",
" <td> 135.855530</td>\n",
" <td> 1</td>\n",
" <td> 135.855530</td>\n",
" <td> 6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>40</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 11</td>\n",
" <td> 4RY_h</td>\n",
" <td> 1.500785</td>\n",
" <td> 137.871400</td>\n",
" <td> 141.886942</td>\n",
" <td> 145.901719</td>\n",
" <td> 146.918400</td>\n",
" <td> 150.933949</td>\n",
" <td> 1</td>\n",
" <td> 150.933949</td>\n",
" <td> 6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>41</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 12</td>\n",
" <td> 2R_h</td>\n",
" <td> 1.536864</td>\n",
" <td> 152.966742</td>\n",
" <td> 156.981719</td>\n",
" <td> 160.997330</td>\n",
" <td> 162.013391</td>\n",
" <td> 166.028706</td>\n",
" <td> 1</td>\n",
" <td> 166.028706</td>\n",
" <td> 6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>42</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 13</td>\n",
" <td> 2R_h</td>\n",
" <td> 1.136647</td>\n",
" <td> 168.044810</td>\n",
" <td> 172.059831</td>\n",
" <td> 175.075749</td>\n",
" <td> 176.091904</td>\n",
" <td> 179.108012</td>\n",
" <td> 1</td>\n",
" <td> 179.108012</td>\n",
" <td> 6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>43</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 14</td>\n",
" <td> 4RY_nr</td>\n",
" <td> NaN</td>\n",
" <td> 181.140096</td>\n",
" <td> 185.155370</td>\n",
" <td> 189.170549</td>\n",
" <td> 190.186896</td>\n",
" <td> 193.202615</td>\n",
" <td> 0</td>\n",
" <td> 193.202615</td>\n",
" <td> 6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>44</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 15</td>\n",
" <td> DRY_cr</td>\n",
" <td> 1.272600</td>\n",
" <td> 195.235196</td>\n",
" <td> 199.250353</td>\n",
" <td> 202.266476</td>\n",
" <td> 203.282883</td>\n",
" <td> 206.298382</td>\n",
" <td> 1</td>\n",
" <td> 206.298382</td>\n",
" <td> 6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 16</td>\n",
" <td> 4RY_cr</td>\n",
" <td> 1.062302</td>\n",
" <td> 208.330772</td>\n",
" <td> 212.345805</td>\n",
" <td> 217.361376</td>\n",
" <td> 218.377696</td>\n",
" <td> 222.393067</td>\n",
" <td> 1</td>\n",
" <td> 222.393067</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>46</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 17</td>\n",
" <td> 2R_cr</td>\n",
" <td> 1.677504</td>\n",
" <td> 224.408427</td>\n",
" <td> 227.424595</td>\n",
" <td> 232.439443</td>\n",
" <td> 233.455782</td>\n",
" <td> 237.471219</td>\n",
" <td> 1</td>\n",
" <td> 237.471219</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>47</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 18</td>\n",
" <td> DRY_h</td>\n",
" <td> 0.888521</td>\n",
" <td> 239.504001</td>\n",
" <td> 242.519436</td>\n",
" <td> 245.535181</td>\n",
" <td> 246.551823</td>\n",
" <td> 250.566942</td>\n",
" <td> 1</td>\n",
" <td> 250.566942</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>48</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 19</td>\n",
" <td> 4RY_cr</td>\n",
" <td> 1.225967</td>\n",
" <td> 252.599545</td>\n",
" <td> 255.615103</td>\n",
" <td> 259.630436</td>\n",
" <td> 260.646930</td>\n",
" <td> 262.662711</td>\n",
" <td> 1</td>\n",
" <td> 262.662711</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>49</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 20</td>\n",
" <td> 2R_h</td>\n",
" <td> 1.376171</td>\n",
" <td> 264.695435</td>\n",
" <td> 267.710971</td>\n",
" <td> 271.726119</td>\n",
" <td> 272.742591</td>\n",
" <td> 275.758338</td>\n",
" <td> 1</td>\n",
" <td> 275.758338</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 21</td>\n",
" <td> DRY_fa</td>\n",
" <td> 1.112251</td>\n",
" <td> 277.774158</td>\n",
" <td> 280.789343</td>\n",
" <td> 284.804923</td>\n",
" <td> 285.821602</td>\n",
" <td> 289.836585</td>\n",
" <td> 0</td>\n",
" <td> 289.836585</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>51</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 22</td>\n",
" <td> DRY_cr</td>\n",
" <td> 1.179686</td>\n",
" <td> 291.853218</td>\n",
" <td> 294.868666</td>\n",
" <td> 298.883516</td>\n",
" <td> 299.900073</td>\n",
" <td> 301.916316</td>\n",
" <td> 1</td>\n",
" <td> 301.916316</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>52</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 23</td>\n",
" <td> 2R_cr</td>\n",
" <td> 1.167593</td>\n",
" <td> 303.948465</td>\n",
" <td> 306.964286</td>\n",
" <td> 310.980121</td>\n",
" <td> 311.995762</td>\n",
" <td> 316.010835</td>\n",
" <td> 1</td>\n",
" <td> 316.010835</td>\n",
" <td> 6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>53</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 24</td>\n",
" <td> 4RY_cr</td>\n",
" <td> 0.822557</td>\n",
" <td> 318.044026</td>\n",
" <td> 322.058843</td>\n",
" <td> 325.074434</td>\n",
" <td> 326.090955</td>\n",
" <td> 329.106882</td>\n",
" <td> 1</td>\n",
" <td> 329.106882</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>54</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 25</td>\n",
" <td> 2R_h</td>\n",
" <td> 1.509566</td>\n",
" <td> 331.139326</td>\n",
" <td> 334.155217</td>\n",
" <td> 337.171061</td>\n",
" <td> 338.186869</td>\n",
" <td> 340.203432</td>\n",
" <td> 1</td>\n",
" <td> 340.203432</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>55</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 26</td>\n",
" <td> 4RY_h</td>\n",
" <td> 1.077532</td>\n",
" <td> 342.235866</td>\n",
" <td> 345.251381</td>\n",
" <td> 348.267380</td>\n",
" <td> 349.283514</td>\n",
" <td> 352.299301</td>\n",
" <td> 1</td>\n",
" <td> 352.299301</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>56</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 27</td>\n",
" <td> DRY_cr</td>\n",
" <td> 0.736435</td>\n",
" <td> 354.331714</td>\n",
" <td> 357.347522</td>\n",
" <td> 360.363077</td>\n",
" <td> 361.379055</td>\n",
" <td> 364.395067</td>\n",
" <td> 1</td>\n",
" <td> 364.395067</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>57</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 28</td>\n",
" <td> DRY_fa</td>\n",
" <td> 1.955766</td>\n",
" <td> 366.427073</td>\n",
" <td> 369.443377</td>\n",
" <td> 374.458267</td>\n",
" <td> 375.474592</td>\n",
" <td> 377.490900</td>\n",
" <td> 0</td>\n",
" <td> 377.490900</td>\n",
" <td> 6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>58</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 29</td>\n",
" <td> 4RY_h</td>\n",
" <td> 1.017861</td>\n",
" <td> 379.506862</td>\n",
" <td> 383.522149</td>\n",
" <td> 388.536939</td>\n",
" <td> 389.553382</td>\n",
" <td> 393.568753</td>\n",
" <td> 1</td>\n",
" <td> 393.568753</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>59</th>\n",
" <td> 2016</td>\n",
" <td> 2</td>\n",
" <td> 30</td>\n",
" <td> 2R_cr</td>\n",
" <td> 0.872621</td>\n",
" <td> 395.601404</td>\n",
" <td> 398.616716</td>\n",
" <td> 401.632723</td>\n",
" <td> 402.648591</td>\n",
" <td> 405.664458</td>\n",
" <td> 1</td>\n",
" <td> 405.664458</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 50,
"text": [
" subject session Trial Trial_type Reaction_Time Fixation_1_onset \\\n",
"0 2016 2 1 DRY_cr 1.489786 0.021435 \n",
"1 2016 2 2 2R_h 0.845029 16.132993 \n",
"2 2016 2 3 4RY_h 0.677303 28.228318 \n",
"3 2016 2 4 DRY_h 1.043895 40.324901 \n",
"4 2016 2 5 4RY_cr 0.699229 54.420396 \n",
"5 2016 2 6 2R_cr 1.456915 68.498710 \n",
"6 2016 2 7 4RY_h 1.679115 81.594548 \n",
"7 2016 2 8 2R_h 1.136683 93.690656 \n",
"8 2016 2 9 DRY_cr 0.824417 105.786785 \n",
"9 2016 2 10 2R_h 0.704208 118.881506 \n",
"10 2016 2 11 DRY_h 0.926933 133.976202 \n",
"11 2016 2 12 4RY_h 1.485780 149.070537 \n",
"12 2016 2 13 4RY_fa 0.630968 164.165568 \n",
"13 2016 2 14 DRY_h 0.941841 179.260733 \n",
"14 2016 2 15 2R_cr 1.246130 191.357181 \n",
"15 2016 2 16 DRY_h 0.959472 204.452442 \n",
"16 2016 2 17 4RY_m 1.158538 218.530888 \n",
"17 2016 2 18 2R_cr 0.734570 232.626864 \n",
"18 2016 2 19 2R_cr 0.917417 245.721808 \n",
"19 2016 2 20 4RY_cr 1.143319 260.817394 \n",
"20 2016 2 21 DRY_cr 0.753987 274.895999 \n",
"21 2016 2 22 2R_h 0.632535 287.975207 \n",
"22 2016 2 23 DRY_cr 1.265268 302.069337 \n",
"23 2016 2 24 4RY_cr 1.312230 315.148799 \n",
"24 2016 2 25 2R_cr 0.752770 327.227452 \n",
"25 2016 2 26 4RY_fa 1.375301 339.307095 \n",
"26 2016 2 27 DRY_cr 0.585002 353.385888 \n",
"27 2016 2 28 2R_h 0.933963 367.481352 \n",
"28 2016 2 29 DRY_cr 0.648839 381.575908 \n",
"29 2016 2 30 4RY_h 0.632727 394.671399 \n",
"30 2016 2 1 4RY_cr 0.876987 0.017930 \n",
"31 2016 2 2 DRY_h 1.058671 13.112584 \n",
"32 2016 2 3 2R_h 0.690472 27.191645 \n",
"33 2016 2 4 DRY_h 1.054261 42.286474 \n",
"34 2016 2 5 4RY_cr 0.949158 55.381924 \n",
"35 2016 2 6 2R_cr 1.208110 70.461176 \n",
"36 2016 2 7 4RY_cr 1.081796 83.539104 \n",
"37 2016 2 8 DRY_h 0.943692 94.618724 \n",
"38 2016 2 9 2R_cr 0.981080 109.697773 \n",
"39 2016 2 10 DRY_h 0.829796 123.792629 \n",
"40 2016 2 11 4RY_h 1.500785 137.871400 \n",
"41 2016 2 12 2R_h 1.536864 152.966742 \n",
"42 2016 2 13 2R_h 1.136647 168.044810 \n",
"43 2016 2 14 4RY_nr NaN 181.140096 \n",
"44 2016 2 15 DRY_cr 1.272600 195.235196 \n",
"45 2016 2 16 4RY_cr 1.062302 208.330772 \n",
"46 2016 2 17 2R_cr 1.677504 224.408427 \n",
"47 2016 2 18 DRY_h 0.888521 239.504001 \n",
"48 2016 2 19 4RY_cr 1.225967 252.599545 \n",
"49 2016 2 20 2R_h 1.376171 264.695435 \n",
"50 2016 2 21 DRY_fa 1.112251 277.774158 \n",
"51 2016 2 22 DRY_cr 1.179686 291.853218 \n",
"52 2016 2 23 2R_cr 1.167593 303.948465 \n",
"53 2016 2 24 4RY_cr 0.822557 318.044026 \n",
"54 2016 2 25 2R_h 1.509566 331.139326 \n",
"55 2016 2 26 4RY_h 1.077532 342.235866 \n",
"56 2016 2 27 DRY_cr 0.736435 354.331714 \n",
"57 2016 2 28 DRY_fa 1.955766 366.427073 \n",
"58 2016 2 29 4RY_h 1.017861 379.506862 \n",
"59 2016 2 30 2R_cr 0.872621 395.601404 \n",
"\n",
" Instruction_onset Stimulus_onset Fixation_2_onset Probe_onset \\\n",
"0 4.036645 9.051471 10.067761 14.083652 \n",
"1 20.148242 23.163798 24.179877 26.196046 \n",
"2 31.244003 35.259397 36.276368 38.292193 \n",
"3 44.339741 47.355573 48.371992 52.387347 \n",
"4 57.435494 62.450462 63.466978 66.482994 \n",
"5 72.514199 76.529787 77.546002 79.561724 \n",
"6 84.609550 87.625640 88.642109 91.657912 \n",
"7 96.706504 100.721243 101.738023 103.753741 \n",
"8 108.802024 111.818192 112.834354 116.848395 \n",
"9 122.896604 127.911487 128.927985 131.943303 \n",
"10 137.991489 142.006898 143.023162 147.038233 \n",
"11 153.086369 157.101826 158.118047 162.133466 \n",
"12 168.180818 172.196856 173.213236 177.228316 \n",
"13 182.276938 186.292037 187.307867 189.324796 \n",
"14 194.372404 199.388100 200.403776 202.419958 \n",
"15 207.468442 212.483215 213.499562 216.515158 \n",
"16 222.546423 225.562261 226.578278 230.593605 \n",
"17 235.642123 238.657791 239.673886 243.689393 \n",
"18 249.737869 253.752572 254.769201 258.784617 \n",
"19 264.832724 269.847572 270.863655 272.880078 \n",
"20 278.911357 282.926934 283.943261 285.958878 \n",
"21 290.990134 296.005395 297.021128 300.037251 \n",
"22 305.085451 310.100264 311.116528 313.132531 \n",
"23 318.164500 322.179484 323.196205 325.212088 \n",
"24 330.243708 333.259146 334.275457 337.291333 \n",
"25 342.322564 347.337944 348.354172 351.369260 \n",
"26 356.401332 361.416550 362.432631 365.448624 \n",
"27 371.496540 374.511728 375.528433 379.543135 \n",
"28 385.591399 388.607429 389.623640 392.639220 \n",
"29 398.687306 401.702806 402.719377 405.734857 \n",
"30 3.033248 8.048419 9.064541 11.080478 \n",
"31 17.128793 22.143722 23.159750 25.175848 \n",
"32 31.207420 36.222278 37.238754 40.254106 \n",
"33 46.302070 50.317478 51.333701 53.349959 \n",
"34 58.398029 63.413443 64.429355 68.444981 \n",
"35 74.475980 78.491689 79.507906 81.523854 \n",
"36 86.555483 89.570998 90.587037 92.603296 \n",
"37 98.634084 103.649740 104.665850 107.681615 \n",
"38 113.712432 118.727934 119.743847 121.759635 \n",
"39 127.807833 130.823750 131.839862 135.855530 \n",
"40 141.886942 145.901719 146.918400 150.933949 \n",
"41 156.981719 160.997330 162.013391 166.028706 \n",
"42 172.059831 175.075749 176.091904 179.108012 \n",
"43 185.155370 189.170549 190.186896 193.202615 \n",
"44 199.250353 202.266476 203.282883 206.298382 \n",
"45 212.345805 217.361376 218.377696 222.393067 \n",
"46 227.424595 232.439443 233.455782 237.471219 \n",
"47 242.519436 245.535181 246.551823 250.566942 \n",
"48 255.615103 259.630436 260.646930 262.662711 \n",
"49 267.710971 271.726119 272.742591 275.758338 \n",
"50 280.789343 284.804923 285.821602 289.836585 \n",
"51 294.868666 298.883516 299.900073 301.916316 \n",
"52 306.964286 310.980121 311.995762 316.010835 \n",
"53 322.058843 325.074434 326.090955 329.106882 \n",
"54 334.155217 337.171061 338.186869 340.203432 \n",
"55 345.251381 348.267380 349.283514 352.299301 \n",
"56 357.347522 360.363077 361.379055 364.395067 \n",
"57 369.443377 374.458267 375.474592 377.490900 \n",
"58 383.522149 388.536939 389.553382 393.568753 \n",
"59 398.616716 401.632723 402.648591 405.664458 \n",
"\n",
" Accuracy probe_onset probe_duration \n",
"0 1 14.083652 6 \n",
"1 1 26.196046 5 \n",
"2 1 38.292193 6 \n",
"3 1 52.387347 5 \n",
"4 1 66.482994 6 \n",
"5 1 79.561724 5 \n",
"6 1 91.657912 5 \n",
"7 1 103.753741 5 \n",
"8 1 116.848395 6 \n",
"9 1 131.943303 6 \n",
"10 1 147.038233 6 \n",
"11 1 162.133466 6 \n",
"12 0 177.228316 5 \n",
"13 1 189.324796 5 \n",
"14 1 202.419958 5 \n",
"15 1 216.515158 6 \n",
"16 0 230.593605 5 \n",
"17 1 243.689393 6 \n",
"18 1 258.784617 6 \n",
"19 1 272.880078 6 \n",
"20 1 285.958878 5 \n",
"21 1 300.037251 5 \n",
"22 1 313.132531 5 \n",
"23 1 325.212088 5 \n",
"24 1 337.291333 5 \n",
"25 0 351.369260 5 \n",
"26 1 365.448624 6 \n",
"27 1 379.543135 6 \n",
"28 1 392.639220 6 \n",
"29 1 405.734857 -402 \n",
"30 1 11.080478 6 \n",
"31 1 25.175848 6 \n",
"32 1 40.254106 6 \n",
"33 1 53.349959 5 \n",
"34 1 68.444981 6 \n",
"35 1 81.523854 5 \n",
"36 1 92.603296 6 \n",
"37 1 107.681615 6 \n",
"38 1 121.759635 6 \n",
"39 1 135.855530 6 \n",
"40 1 150.933949 6 \n",
"41 1 166.028706 6 \n",
"42 1 179.108012 6 \n",
"43 0 193.202615 6 \n",
"44 1 206.298382 6 \n",
"45 1 222.393067 5 \n",
"46 1 237.471219 5 \n",
"47 1 250.566942 5 \n",
"48 1 262.662711 5 \n",
"49 1 275.758338 5 \n",
"50 0 289.836585 5 \n",
"51 1 301.916316 5 \n",
"52 1 316.010835 6 \n",
"53 1 329.106882 5 \n",
"54 1 340.203432 5 \n",
"55 1 352.299301 5 \n",
"56 1 364.395067 5 \n",
"57 0 377.490900 6 \n",
"58 1 393.568753 5 \n",
"59 1 405.664458 0 "
]
}
],
"prompt_number": 50
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"d['duration'] = d.apply(lambda row: (row['two']- (row['one']) ,axis = 1)"
],
"language": "python",
"metadata": {},
"outputs": []
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def subjectinfo(subject_id):\n",
" import os\n",
" import nipype.algorithms.modelgen as model\n",
" import nipype.algorithms.rapidart as ra\n",
" import nipype.interfaces.freesurfer as fs\n",
" import nipype.interfaces.ants as ants\n",
" import nipype.interfaces.fsl as fsl\n",
" import nipype.interfaces.io as nio\n",
" import nipype.interfaces.matlab as mlab\n",
" import nipype.interfaces.spm as spm\n",
" import nipype.interfaces.utility as util\n",
" import nipype.pipeline.engine as pe\n",
" import numpy as np\n",
" from nipype.interfaces.base import Bunch\n",
" import time\n",
" from copy import deepcopy\n",
" import scipy.signal\n",
" import scipy.special as sp\n",
" from glob import glob\n",
" import sys\n",
" import math\n",
" from scipy.io import loadmat\n",
" paradigm = 'wmfilt'\n",
" subj_data_file = os.path.abspath('/gablab/p/LAP/data/behav/lap_data.csv')\n",
" subj_data = np.genfromtxt(subj_data_file,names=True,dtype=None,delimiter=\",\",comments='##')\n",
" data_dir = os.path.abspath('/gablab/p/LAP/data/')\n",
" onsets_dir = os.path.join(data_dir, 'onsets',paradigm)\n",
" subj = subj_data[subj_data['Subject_ID'] == int(subject_id[-4:])]\n",
" output = []\n",
" #onsets_temp = os.path.join(onsets_dir,\n",
" # '{0}_*onsets*.mat'.format(subject_id[-4:]))\n",
" onsets_temp = os.path.join(onsets_dir,'%s_*onsets*_mcnab2.mat'%(subject_id))\n",
" def get_onsets(onset_file):\n",
" from scipy.io.matlab import loadmat\n",
" import numpy as np\n",
" paradigm = 'wmfilt'\n",
" subj_data_file = os.path.abspath('/gablab/p/LAP/data/behav/lap_data.csv')\n",
" subj_data = np.genfromtxt(subj_data_file,names=True,dtype=None,delimiter=',',comments='##')\n",
" data_dir = os.path.abspath('/gablab/p/LAP/data/')\n",
" onsets_dir = os.path.join(data_dir, 'onsets',paradigm)\n",
" mat = loadmat(onset_file, struct_as_record=False)\n",
" names = []\n",
" onsets = []\n",
" durations = []\n",
" for idx,name in enumerate(np.squeeze(mat['names'])):\n",
" names.append(str(name[0]))\n",
" onset_vec = np.squeeze(mat['onsets'][0][idx])\n",
" duration_vec = np.squeeze(mat['durations'][0][idx])\n",
" try:\n",
" onsets.append([item for item in onset_vec])\n",
" except TypeError:\n",
" onsets.append([onset_vec])\n",
" try:\n",
" durations.append([item for item in duration_vec])\n",
" except TypeError:\n",
" durations.append([duration_vec])\n",
" return (names,onsets,durations)\n",
" print onsets_temp\n",
" for idx,onset_file in enumerate(sorted(glob(onsets_temp))):\n",
" run = idx+1\n",
" print onset_file\n",
" (names,onsets,durations) = get_onsets(onset_file)\n",
" lengthTR = 2.0 #seconds\n",
" regressor_names = []\n",
" regressors = []\n",
" numTRs = 267\n",
" num_polynomials = int(numTRs*lengthTR/150) + 1\n",
" x = np.linspace(-1,1,numTRs)\n",
" for p in range(1,num_polynomials+1):\n",
" regressor_names.append(\"Poly%s\"%str(p))\n",
" regressors.append(list(sp.legendre(p)(x)))\n",
" output.insert(idx,\n",
" Bunch(conditions=names,\n",
" onsets=deepcopy(onsets),\n",
" durations=durations,\n",
" amplitudes=None,\n",
" tmod=None,\n",
" pmod=None,\n",
" regressor_names=regressor_names,\n",
" regressors=regressors))\n",
" return output"
],
"language": "python",
"metadata": {},
"outputs": []
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from nipype.interfaces.base import Bunch\n",
"import numpy as np \n",
"import os\n",
"info = []\n",
"if not isinstance(run_event_files[0],list):\n",
" run_event_files = [run_event_files] \n",
"\n",
"for i, event_files in enumerate(run_event_files):\n",
" runinfo = Bunch(conditions=[], onsets=[], durations=[], amplitudes=[],tmod=None, pmod=None, regressor_names=None, regressors=None)\n",
" for event_file in event_files:\n",
" _, name = os.path.split(event_file)\n",
" if '.run' in name:\n",
" name, _ = name.split('.run%03d'%(i+1))\n",
" elif '.txt' in name:\n",
" name, _ = name.split('.txt')\n",
" runinfo.conditions.append(name)\n",
" event_info = np.loadtxt(event_file)\n",
" runinfo.onsets.append(event_info[:, 0].tolist())\n",
" if event_info.shape[1] > 1:\n",
" runinfo.durations.append(event_info[:, 1].tolist())\n",
" else:\n",
" runinfo.durations.append([0])\n",
" if event_info.shape[1] > 2:\n",
" runinfo.amplitudes.append(event_info[:, 2].tolist())\n",
" else:\n",
" delattr(runinfo, 'amplitudes')\n",
" info.append(runinfo)\n",
"return info\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"ename": "ImportError",
"evalue": "No module named nipype.interfaces.base",
"output_type": "pyerr",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mImportError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m<ipython-input-47-397d4422aebe>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[1;32mfrom\u001b[0m \u001b[0mnipype\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minterfaces\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mbase\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mBunch\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 2\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 3\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mos\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 4\u001b[0m \u001b[0minfo\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 5\u001b[0m \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrun_event_files\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mlist\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;31mImportError\u001b[0m: No module named nipype.interfaces.base"
]
}
],
"prompt_number": 47
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def subjectinfo(subject_id):\n",
" import scipy.signal\n",
" import scipy.special as sp\n",
" import numpy as np\n",
" import math\n",
" from nipype.interfaces.base import Bunch\n",
" from copy import deepcopy\n",
" output = []\n",
" names = ['English','Mandarin','MAL']\n",
" if int(subject_id.split(\"_\")[1]) >= 2000:\n",
" numruns = [2,3]\n",
" else:\n",
" numruns = [0,1]\n",
" trialDur = [[3.0],[3.0],[3.0]] #seconds\n",
" onset = [[[21.09, 24.14, 27.14, 30.14, 33.14, 36.14, 96.22, 99.21, 102.22, 105.22, 108.22, 111.22, 171.32, 174.33, 177.33, 180.34, 183.35, 186.36, 246.47, 249.47, 252.49, 255.51, 258.52, 261.54, 321.61, 324.63, 327.64, 330.65, 333.65, 336.65],\n",
" [60.16, 63.20, 66.20, 69.21, 72.21, 75.21, 135.23, 138.28, 141.28, 144.28, 147.28, 150.30, 210.34, 213.39, 216.41, 219.43, 222.44, 225.46, 285.52, 288.58, 291.60, 294.60, 297.60, 300.60, 357.66, 360.68, 363.68, 366.68, 369.68, 372.68],\n",
" [1.51, 4.59, 7.58, 10.59, 13.60, 16.62, 40.59, 43.65, 46.66, 49.68, 52.68, 55.70, 115.69, 118.76, 121.77, 124.78, 127.78, 130.78, 190.84, 193.88, 196.89, 199.88, 202.88, 205.89, 266.00, 269.04, 272.04, 275.04, 278.04, 281.05]],\n",
" [[18.07, 21.09, 24.10, 27.11, 30.10, 33.10, 112.64, 115.70, 118.72, 121.74, 124.75, 127.75, 207.42, 210.42, 213.43, 216.44, 219.45, 222.47, 282.57, 285.58, 288.60, 291.61, 294.63, 297.63, 357.62, 360.69, 363.70, 366.70, 369.70, 372.70],\n",
" [57.12, 60.16, 63.16, 66.16, 69.16, 72.16, 93.17, 96.17, 99.18, 102.18, 105.18, 108.18, 132.21, 135.26, 138.26, 141.26, 144.26, 147.28, 171.29, 174.34, 177.35, 180.36, 183.37, 186.39, 246.44, 249.50, 252.52, 255.53, 258.55, 261.57],\n",
" [37.56, 40.60, 43.60, 46.61, 49.62, 52.64, 151.75, 154.82, 157.81, 160.83, 163.83, 166.83, 226.94, 229.99, 232.99, 235.99, 238.99, 241.99, 302.09, 305.13, 308.13, 311.13, 314.13, 317.14, 338.14, 341.15, 344.15, 347.15, 350.15, 353.15]],\n",
" [[60.17, 63.23, 66.24, 69.25, 72.25, 75.24, 115.87, 118.87, 121.87, 124.89, 127.90, 130.92, 154.90, 157.95, 160.97, 163.98, 167.00, 170.00, 246.58, 249.63, 252.65, 255.65, 258.65, 261.67, 302.20, 305.25, 308.25, 311.24, 314.26, 317.28],\n",
" [1.51, 4.59, 7.60, 10.61, 13.61, 16.61, 40.63, 43.67, 46.68, 49.68, 52.68, 55.70, 191.01, 194.03, 197.04, 200.06, 203.06, 206.06, 227.07, 230.08, 233.10, 236.12, 239.13, 242.13, 338.31, 341.31, 344.32, 347.31, 350.32, 353.31],\n",
" [21.07, 24.13, 27.14, 30.17, 33.16, 36.17, 79.72, 82.78, 85.79, 88.81, 91.83, 94.84, 135.39, 138.44, 141.44, 144.44, 147.44, 150.44, 282.69, 285.69, 288.70, 291.70, 294.72, 297.73, 357.76, 360.82, 363.84, 366.85, 369.86, 372.86]],\n",
" [[1.52, 4.58, 7.58, 10.59, 13.58, 16.60, 112.72, 115.77, 118.77, 121.79, 124.80, 127.82, 168.34, 171.34, 174.34, 177.34, 180.34, 183.34, 226.90, 229.96, 232.98, 235.98, 238.98, 241.98, 338.12, 341.16, 344.16, 347.17, 350.17, 353.17],\n",
" [57.16, 60.18, 63.18, 66.20, 69.20, 72.20, 93.20, 96.22, 99.23, 102.25, 105.26, 108.26, 132.28, 135.32, 138.33, 141.33, 144.33, 147.33, 187.80, 190.86, 193.88, 196.89, 199.90, 202.90, 246.44, 249.48, 252.48, 255.49, 258.50, 261.52],\n",
" [21.07, 24.14, 27.15, 30.15, 33.15, 36.16, 207.36, 210.40, 213.40, 216.40, 219.41, 222.43, 282.53, 285.52, 288.53, 291.54, 294.57, 297.56, 318.58, 321.59, 324.61, 327.62, 330.64, 333.66, 357.63, 360.69, 363.71, 366.72, 369.72, 372.73]]]\n",
" lengthTR = 2.0 #seconds\n",
" for r in numruns:\n",
" regressor_names = []\n",
" regressors = []\n",
" if subject_id == \"LAP_1016\" and r == 0:\n",
" numTRs = 190\n",
" elif subject_id == \"LAP_1013\" and r == 0:\n",
" numTRs = 195\n",
" elif subject_id == \"LAP_1013\" and r == 1:\n",
" numTRs = 193\n",
" else:\n",
" numTRs = 191\n",
" num_polynomials = int(numTRs*lengthTR/150) + 1\n",
" x = np.linspace(-1,1,numTRs)\n",
" for p in range(1,num_polynomials+1):\n",
" regressor_names.append(\"Poly%s\"%str(p))\n",
" regressors.append(list(sp.legendre(p)(x)))\n",
" output.insert(r,\n",
" Bunch(conditions=names,\n",
" onsets=deepcopy(onset[r]),\n",
" durations=trialDur,\n",
" amplitudes=None,\n",
" tmod=None,\n",
" pmod=None,\n",
" regressor_names=regressor_names,\n",
" regressors=regressors))\n",
" return output"
],
"language": "python",
"metadata": {},
"outputs": []
}
],
"metadata": {}
}
]
}
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