{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "# How to use [ParseEyetrackerFile](https://linescanning.readthedocs.io/en/latest/classes/dataset.html#linescanning.dataset.ParseEyetrackerFile)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook illustrates how to read in the output from the `EyeLink`-software, as implemented with [exptools](https://github.com/Gilles86/exptools2/tree/show_pupil)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "221207-14:58:37,988 nipype.utils WARNING:\n",
      "\t A newer version (1.8.4) of nipy/nipype is available. You are using 1.8.2\n"
     ]
    }
   ],
   "source": [
    "# imports\n",
    "from linescanning import (\n",
    "    dataset, \n",
    "    plotting, \n",
    "    fitting\n",
    "    )\n",
    "\n",
    "import os\n",
    "opj = os.path.join\n",
    "opd = os.path.dirname"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Whenever you run an experiment with [exptools](https://github.com/Gilles86/exptools2/tree/show_pupil), you'll get an `edf`-file. This file can be read in with [hedfpy](https://github.com/gjheij/hedfpy), which is wrapped into the [ParseEyetrackerFile](https://linescanning.readthedocs.io/en/latest/classes/dataset.html#linescanning.dataset.ParseEyetrackerFile)-class within the `linescanning`-toolbox. I have provided an example dataset `eye.edf`. This is from a recent 3D-EPI acquisition with a TR of 1.1s, and 270 volumes (this is necessary to extract the correct time period of the eyetracking)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# define an edf file\n",
    "edf_file = opj(opd(opd(dataset.__file__)), 'examples', 'eye.edf')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The hard part is actually *getting* the eyetracking data, processing is not that difficult really. We can just plop everything in the class and check it's read-outs, but first let's try to understand what happens under the hood.\n",
    "\n",
    "From [hedfpy](https://github.com/gjheij/hedfpy):\n",
    "\n",
    "\"*For full parsing of the edf file data, hedfpy assumes a specific trial-based experimental format that is communicated to the eye tracker. Specifically, it looks for explicitly formatted messages by means of regular expressions. These messages detail the start and end of trial phases, trials, button press events, sound events and the stimulus parameters for a given trial which are all stored in tabular format in the HDF5 file. The parsing of these messages can be turned off for basic functionality.*\". This `hdf5`-file is stored in the directory in which `edf_file` lives. It will also store other outputs - such as basic quality assessments - in that folder.\n",
    "\n",
    "The way the line-scanning toolbox is reading in data is as follows:\n",
    "\n",
    "- Either use specific classes as stand-alone (e.g., [ParseEyetrackerFile](https://linescanning.readthedocs.io/en/latest/classes/dataset.html#linescanning.dataset.ParseEyetrackerFile), or [ParseExpToolsFile](https://linescanning.readthedocs.io/en/latest/classes/dataset.html#linescanning.dataset.ParseExpToolsFile))\n",
    "- Combine eyetracker and exptools file (in case of psychophysical experiments) with [ParseExpToolsFile](https://linescanning.readthedocs.io/en/latest/classes/dataset.html#linescanning.dataset.ParseExpToolsFile)\n",
    "- Combine eyetracker, exptools, and functional files with [ParseFuncFile](https://linescanning.readthedocs.io/en/latest/classes/dataset.html#linescanning.dataset.ParseFuncFile) or the [dataset](https://linescanning.readthedocs.io/en/latest/classes/dataset.html#linescanning.dataset.Dataset)-class\n",
    "\n",
    "In any case, it's best to use `use_bids=True`, as this will read subject/session/run-specific information from the file itself. If you've done the same for your functional files, every dataframe that comes out of this lines up index-wise, which is great (and which is why it's default!). Because our `edf-file` is called `eye.edf`, I'll turn off `use_bids`.\n",
    "\n",
    "Let's see how that looks:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Stand-alone usage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I was able to import hedfpy\n",
      "\n",
      "EYETRACKER\n",
      "22-12-07_14-58-39 - INFO - EDFOperator - started with eye.edf\n",
      "22-12-07_14-58-39 - INFO - EDF2ASCOperator - <hedfpy.CommandLineOperator.EDF2ASCOperator object at 0x7f1e2c01d760> initialized with file eye.edf\n",
      "22-12-07_14-58-39 - DEBUG - EDF2ASCOperator - <hedfpy.CommandLineOperator.EDF2ASCOperator object at 0x7f1e2c01d760>executing command \n",
      "edf2asc -t -ftime -y -z -v -s -miss 0.0001 -vel \"/data1/projects/MicroFunc/Jurjen/programs/packages/linescanning/examples/eye.edf\"; mv \"/data1/projects/MicroFunc/Jurjen/programs/packages/linescanning/examples/eye.asc\" \"/data1/projects/MicroFunc/Jurjen/programs/packages/linescanning/examples/eye.gaz\"; edf2asc -t -ftime -y -z -v -e \"/data1/projects/MicroFunc/Jurjen/programs/packages/linescanning/examples/eye.edf\"; mv \"/data1/projects/MicroFunc/Jurjen/programs/packages/linescanning/examples/eye.asc\" \"/data1/projects/MicroFunc/Jurjen/programs/packages/linescanning/examples/eye.msg\"\n",
      "22-12-07_14-58-42 - INFO - EDFOperator - reading trials from eye.msg\n",
      "22-12-07_14-58-42 - INFO - EDFOperator - no parameter information in edf file\n",
      "22-12-07_14-58-42 - INFO - EDFOperator - reading key_events from eye.msg\n",
      "22-12-07_14-58-43 - INFO - EDFOperator - reading key_events from eye.msg\n",
      "22-12-07_14-58-43 - INFO - EDFOperator - reading key_events from eye.msg\n",
      "22-12-07_14-58-43 - INFO - EDFOperator - reading eyelink events from eye.msg\n",
      "22-12-07_14-58-43 - INFO - EDFOperator - reading sounds from eye.msg\n",
      "22-12-07_14-58-43 - INFO - EDFOperator - cleaning gaze information from /data1/projects/MicroFunc/Jurjen/programs/packages/linescanning/examples/eye.gaz\n",
      "22-12-07_14-58-47 - INFO - EDFOperator - identifying recording blocks from /data1/projects/MicroFunc/Jurjen/programs/packages/linescanning/examples/eye.gaz\n",
      "22-12-07_14-58-47 - INFO - EDFOperator - 1 raw blocks discovered\n",
      "22-12-07_14-58-47 - INFO - EDFOperator - 373457.000000 raw block duration, threshold 30000.000000\n",
      "22-12-07_14-58-47 - INFO - EDFOperator - 1 correct duration blocks discovered\n",
      "22-12-07_14-58-49 - INFO - EDFOperator - found data from block 0 of shape (373457, 6)\n",
      "22-12-07_14-58-50 - INFO - HDFEyeOperator - Adding message data from eye.edf to group  run_1 to /data1/projects/MicroFunc/Jurjen/programs/packages/linescanning/examples/eye.h5\n",
      "22-12-07_14-58-50 - INFO - HDFEyeOperator - Adding gaze data from eye.edf to group  run_1 to /data1/projects/MicroFunc/Jurjen/programs/packages/linescanning/examples/eye.h5\n",
      "22-12-07_14-58-50 - INFO - EyeSignalOperator - Interpolating blinks using interpolate_blinks\n",
      "22-12-07_14-58-50 - INFO - EyeSignalOperator - Band-pass filtering of pupil signals, hp = 0.010, lp = 6.000\n",
      "22-12-07_14-58-50 - INFO - EyeSignalOperator - Regressing blinks, saccades and gaze position of pupil signals\n",
      "[(373457,), (373457,)]\n",
      "22-12-07_14-58-50 - INFO - EyeSignalOperator - Nuisance GLM Results, pearsons R (p) is 0.225 (0.0000)\n",
      "22-12-07_14-58-50 - INFO - EyeSignalOperator - Nuisance GLM Results, blink beta 305.27923542121846\n",
      "22-12-07_14-58-50 - INFO - EyeSignalOperator - Nuisance GLM Results, saccade beta -44.34956672331177\n",
      "22-12-07_14-58-53 - WARNING - EyeSignalOperator - time_frequency_decomposition_pupil:\n",
      "                                    requested minimal_frequency 0.00250 smaller than\n",
      "                                    data allows (0.00268). \n",
      "22-12-07_14-58-53 - INFO - EyeSignalOperator - Time_frequency_decomposition_pupil, with filterbank [0.1        0.06305834 0.03976354 0.02507422 0.01581139 0.0099704\n",
      " 0.00628717 0.00396458 0.0025    ]\n",
      "22-12-07_14-58-53 - INFO - HDFEyeOperator - Performed T-F analysis of type lp_butterworth\n",
      "22-12-07_14-58-53 - INFO - HDFEyeOperator - Saved T-F analysis 0.10000\n",
      "22-12-07_14-58-53 - INFO - HDFEyeOperator - Saved T-F analysis 0.06306\n",
      "22-12-07_14-58-53 - INFO - HDFEyeOperator - Saved T-F analysis 0.03976\n",
      "22-12-07_14-58-53 - INFO - HDFEyeOperator - Saved T-F analysis 0.02507\n",
      "22-12-07_14-58-53 - INFO - HDFEyeOperator - Saved T-F analysis 0.01581\n",
      "22-12-07_14-58-53 - INFO - HDFEyeOperator - Saved T-F analysis 0.00997\n",
      "22-12-07_14-58-53 - INFO - HDFEyeOperator - Saved T-F analysis 0.00629\n",
      "22-12-07_14-58-53 - INFO - HDFEyeOperator - Saved T-F analysis 0.00396\n",
      "22-12-07_14-58-53 - INFO - HDFEyeOperator - Saved T-F analysis 0.00250\n",
      "Preprocessing /data1/projects/MicroFunc/Jurjen/programs/packages/linescanning/examples/eye.edf\n",
      " Alias:        run_1\n",
      " Sample rate:  1000\n",
      " Start time:   3566804.0\n",
      " Stop time:    3863804.0\n",
      " Duration:     297.0s [297000 samples]\n",
      " Fetching:     ['pupil', 'pupil_int', 'gaze_x_int', 'gaze_y_int', 'gaze_x', 'gaze_y']\n",
      " Start time exp =  107.72\n",
      " Found 26 blinks [0.09 blinks per second]\n",
      " Found 579 saccades\n",
      "Done\n"
     ]
    }
   ],
   "source": [
    "nr_vols = 270\n",
    "TR = 1.1\n",
    "\n",
    "eye_ = dataset.ParseEyetrackerFile(\n",
    "    edf_file,\n",
    "    use_bids=False,\n",
    "    verbose=True,\n",
    "    nr_vols=270,\n",
    "    TR=TR\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ideally, this does not return an error. If so, we can inspect some of the parameters it extracted from the file (see the list after `Fetching` above)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>onset</th>\n",
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       "      <th>subject</th>\n",
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       "      <th>blink</th>\n",
       "      <td>3.298</td>\n",
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       "    <tr>\n",
       "      <th>blink</th>\n",
       "      <td>11.899</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>blink</th>\n",
       "      <td>17.987</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>blink</th>\n",
       "      <td>31.194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>blink</th>\n",
       "      <td>43.787</td>\n",
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      ],
      "text/plain": [
       "                         onset\n",
       "subject run event_type        \n",
       "1       1   blink        3.298\n",
       "            blink       11.899\n",
       "            blink       17.987\n",
       "            blink       31.194\n",
       "            blink       43.787"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# we get a dataframe for blink onsets\n",
    "eye_.df_blinks.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>pupil</th>\n",
       "      <th>pupil_int</th>\n",
       "      <th>gaze_x_int</th>\n",
       "      <th>gaze_y_int</th>\n",
       "      <th>gaze_x</th>\n",
       "      <th>gaze_y</th>\n",
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       "    <tr>\n",
       "      <th>subject</th>\n",
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       "      <th>0.000</th>\n",
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       "      <td>542.000000</td>\n",
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       "      <th>0.001</th>\n",
       "      <td>3627.0</td>\n",
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       "      <td>871.200012</td>\n",
       "      <td>511.899994</td>\n",
       "      <td>871.200012</td>\n",
       "      <td>511.899994</td>\n",
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       "    <tr>\n",
       "      <th>0.002</th>\n",
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       "      <td>519.900024</td>\n",
       "      <td>866.500000</td>\n",
       "      <td>519.900024</td>\n",
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       "    <tr>\n",
       "      <th>0.003</th>\n",
       "      <td>3630.0</td>\n",
       "      <td>3630.0</td>\n",
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       "      <td>538.099976</td>\n",
       "      <td>865.400024</td>\n",
       "      <td>538.099976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.004</th>\n",
       "      <td>3686.0</td>\n",
       "      <td>3686.0</td>\n",
       "      <td>856.900024</td>\n",
       "      <td>517.700012</td>\n",
       "      <td>856.900024</td>\n",
       "      <td>517.700012</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    pupil  pupil_int  gaze_x_int  gaze_y_int      gaze_x  \\\n",
       "subject run t                                                              \n",
       "1       1   0.000  3634.0     3634.0  864.299988  542.000000  864.299988   \n",
       "            0.001  3627.0     3627.0  871.200012  511.899994  871.200012   \n",
       "            0.002  3679.0     3679.0  866.500000  519.900024  866.500000   \n",
       "            0.003  3630.0     3630.0  865.400024  538.099976  865.400024   \n",
       "            0.004  3686.0     3686.0  856.900024  517.700012  856.900024   \n",
       "\n",
       "                       gaze_y  \n",
       "subject run t                  \n",
       "1       1   0.000  542.000000  \n",
       "            0.001  511.899994  \n",
       "            0.002  519.900024  \n",
       "            0.003  538.099976  \n",
       "            0.004  517.700012  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# and gaze/pupil size both in eyetracking time (@sample rate)\n",
    "eye_.df_space_eye.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
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       "      <td>559.765381</td>\n",
       "      <td>-1.320480</td>\n",
       "      <td>2.184196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.1</th>\n",
       "      <td>2884.0</td>\n",
       "      <td>2557.087891</td>\n",
       "      <td>2.614754</td>\n",
       "      <td>-8.982216</td>\n",
       "      <td>2884.0</td>\n",
       "      <td>2551.462402</td>\n",
       "      <td>2.615150</td>\n",
       "      <td>-9.311279</td>\n",
       "      <td>923.000000</td>\n",
       "      <td>920.140625</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.742149</td>\n",
       "      <td>1.095352</td>\n",
       "      <td>923.000000</td>\n",
       "      <td>920.086853</td>\n",
       "      <td>-0.949356</td>\n",
       "      <td>-1.461578</td>\n",
       "      <td>534.200012</td>\n",
       "      <td>551.961243</td>\n",
       "      <td>-2.741142</td>\n",
       "      <td>0.762779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.2</th>\n",
       "      <td>3193.0</td>\n",
       "      <td>2866.520752</td>\n",
       "      <td>13.682709</td>\n",
       "      <td>2.101234</td>\n",
       "      <td>3193.0</td>\n",
       "      <td>2860.913330</td>\n",
       "      <td>13.684769</td>\n",
       "      <td>1.774490</td>\n",
       "      <td>932.799988</td>\n",
       "      <td>929.968384</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.323082</td>\n",
       "      <td>1.512039</td>\n",
       "      <td>932.799988</td>\n",
       "      <td>929.914856</td>\n",
       "      <td>0.101898</td>\n",
       "      <td>-0.407318</td>\n",
       "      <td>536.500000</td>\n",
       "      <td>554.252808</td>\n",
       "      <td>-2.322235</td>\n",
       "      <td>1.180161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.3</th>\n",
       "      <td>3087.0</td>\n",
       "      <td>2761.168213</td>\n",
       "      <td>9.885933</td>\n",
       "      <td>-1.672340</td>\n",
       "      <td>3087.0</td>\n",
       "      <td>2755.588135</td>\n",
       "      <td>9.887421</td>\n",
       "      <td>-1.998680</td>\n",
       "      <td>915.599976</td>\n",
       "      <td>912.809998</td>\n",
       "      <td>...</td>\n",
       "      <td>0.555717</td>\n",
       "      <td>4.387268</td>\n",
       "      <td>915.599976</td>\n",
       "      <td>912.756775</td>\n",
       "      <td>-1.743164</td>\n",
       "      <td>-2.247887</td>\n",
       "      <td>552.299988</td>\n",
       "      <td>570.040222</td>\n",
       "      <td>0.555519</td>\n",
       "      <td>4.055618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.4</th>\n",
       "      <td>2697.0</td>\n",
       "      <td>2372.028076</td>\n",
       "      <td>-4.083328</td>\n",
       "      <td>-15.610802</td>\n",
       "      <td>2697.0</td>\n",
       "      <td>2366.484131</td>\n",
       "      <td>-4.083939</td>\n",
       "      <td>-15.937943</td>\n",
       "      <td>947.599976</td>\n",
       "      <td>944.865417</td>\n",
       "      <td>...</td>\n",
       "      <td>-5.001472</td>\n",
       "      <td>-1.174690</td>\n",
       "      <td>947.599976</td>\n",
       "      <td>944.812622</td>\n",
       "      <td>1.689514</td>\n",
       "      <td>1.190781</td>\n",
       "      <td>521.799988</td>\n",
       "      <td>539.523315</td>\n",
       "      <td>-4.999634</td>\n",
       "      <td>-1.502617</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  pupil     pupil_hp  pupil_psc  pupil_hp_psc  pupil_int  \\\n",
       "subject run t                                                              \n",
       "1       1   0.0  3634.0  3306.871094  29.478714     17.873978     3634.0   \n",
       "            1.1  2884.0  2557.087891   2.614754     -8.982216     2884.0   \n",
       "            2.2  3193.0  2866.520752  13.682709      2.101234     3193.0   \n",
       "            3.3  3087.0  2761.168213   9.885933     -1.672340     3087.0   \n",
       "            4.4  2697.0  2372.028076  -4.083328    -15.610802     2697.0   \n",
       "\n",
       "                 pupil_int_hp  pupil_int_psc  pupil_int_hp_psc  gaze_x_int  \\\n",
       "subject run t                                                                \n",
       "1       1   0.0   3301.236572      29.483154         17.548630  864.299988   \n",
       "            1.1   2551.462402       2.615150         -9.311279  923.000000   \n",
       "            2.2   2860.913330      13.684769          1.774490  932.799988   \n",
       "            3.3   2755.588135       9.887421         -1.998680  915.599976   \n",
       "            4.4   2366.484131      -4.083939        -15.937943  947.599976   \n",
       "\n",
       "                 gaze_x_int_hp  ...  gaze_y_int_psc  gaze_y_int_hp_psc  \\\n",
       "subject run t                   ...                                      \n",
       "1       1   0.0     861.426758  ...       -1.320969           2.517723   \n",
       "            1.1     920.140625  ...       -2.742149           1.095352   \n",
       "            2.2     929.968384  ...       -2.323082           1.512039   \n",
       "            3.3     912.809998  ...        0.555717           4.387268   \n",
       "            4.4     944.865417  ...       -5.001472          -1.174690   \n",
       "\n",
       "                     gaze_x   gaze_x_hp  gaze_x_psc  gaze_x_hp_psc  \\\n",
       "subject run t                                                        \n",
       "1       1   0.0  864.299988  861.372864   -7.246170      -7.759895   \n",
       "            1.1  923.000000  920.086853   -0.949356      -1.461578   \n",
       "            2.2  932.799988  929.914856    0.101898      -0.407318   \n",
       "            3.3  915.599976  912.756775   -1.743164      -2.247887   \n",
       "            4.4  947.599976  944.812622    1.689514       1.190781   \n",
       "\n",
       "                     gaze_y   gaze_y_hp  gaze_y_psc  gaze_y_hp_psc  \n",
       "subject run t                                                       \n",
       "1       1   0.0  542.000000  559.765381   -1.320480       2.184196  \n",
       "            1.1  534.200012  551.961243   -2.741142       0.762779  \n",
       "            2.2  536.500000  554.252808   -2.322235       1.180161  \n",
       "            3.3  552.299988  570.040222    0.555519       4.055618  \n",
       "            4.4  521.799988  539.523315   -4.999634      -1.502617  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# or resampled to the TR (useful for deconvolution of eyeblinks) > also has high-pass/percent signal changed versions. This takes too long for the data @sample_rate\n",
    "eye_.df_space_func.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "    .dataframe tbody tr th {\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>expanded_start_time</th>\n",
       "      <th>expanded_end_time</th>\n",
       "      <th>expanded_duration</th>\n",
       "      <th>expanded_start_point</th>\n",
       "      <th>expanded_end_point</th>\n",
       "      <th>expanded_vector</th>\n",
       "      <th>expanded_amplitude</th>\n",
       "      <th>peak_velocity</th>\n",
       "      <th>raw_start_time</th>\n",
       "      <th>raw_end_time</th>\n",
       "      <th>raw_duration</th>\n",
       "      <th>raw_start_point</th>\n",
       "      <th>raw_end_point</th>\n",
       "      <th>raw_vector</th>\n",
       "      <th>raw_amplitude</th>\n",
       "      <th>start_timestamp</th>\n",
       "      <th>end_timestamp</th>\n",
       "      <th>onset</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>subject</th>\n",
       "      <th>run</th>\n",
       "      <th>event_type</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">1</th>\n",
       "      <th>saccade</th>\n",
       "      <td>272</td>\n",
       "      <td>292</td>\n",
       "      <td>20</td>\n",
       "      <td>[866.0, 540.1]</td>\n",
       "      <td>[904.1, 492.6]</td>\n",
       "      <td>[38.099976, -47.49997]</td>\n",
       "      <td>0.728021</td>\n",
       "      <td>62.434765</td>\n",
       "      <td>274</td>\n",
       "      <td>289</td>\n",
       "      <td>15</td>\n",
       "      <td>[909.8, 526.3]</td>\n",
       "      <td>[864.8, 542.4]</td>\n",
       "      <td>[45.0, -16.100037]</td>\n",
       "      <td>0.673154</td>\n",
       "      <td>3567076.0</td>\n",
       "      <td>3567096.0</td>\n",
       "      <td>0.272</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>saccade</th>\n",
       "      <td>405</td>\n",
       "      <td>426</td>\n",
       "      <td>21</td>\n",
       "      <td>[889.8, 519.4]</td>\n",
       "      <td>[914.7, 530.3]</td>\n",
       "      <td>[24.900024, 10.899963]</td>\n",
       "      <td>0.442447</td>\n",
       "      <td>37.022831</td>\n",
       "      <td>411</td>\n",
       "      <td>423</td>\n",
       "      <td>12</td>\n",
       "      <td>[922.6, 524.0]</td>\n",
       "      <td>[893.9, 527.1]</td>\n",
       "      <td>[28.699951, -3.0999756]</td>\n",
       "      <td>0.349249</td>\n",
       "      <td>3567209.0</td>\n",
       "      <td>3567230.0</td>\n",
       "      <td>0.405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>saccade</th>\n",
       "      <td>1483</td>\n",
       "      <td>1505</td>\n",
       "      <td>22</td>\n",
       "      <td>[919.1, 574.0]</td>\n",
       "      <td>[937.5, 546.8]</td>\n",
       "      <td>[18.400024, -27.200012]</td>\n",
       "      <td>0.639112</td>\n",
       "      <td>53.668053</td>\n",
       "      <td>1489</td>\n",
       "      <td>1501</td>\n",
       "      <td>12</td>\n",
       "      <td>[935.3, 514.5]</td>\n",
       "      <td>[913.3, 575.0]</td>\n",
       "      <td>[22.0, -60.5]</td>\n",
       "      <td>0.500670</td>\n",
       "      <td>3568287.0</td>\n",
       "      <td>3568309.0</td>\n",
       "      <td>1.483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>saccade</th>\n",
       "      <td>1852</td>\n",
       "      <td>1866</td>\n",
       "      <td>14</td>\n",
       "      <td>[924.8, 538.7]</td>\n",
       "      <td>[939.2, 534.7]</td>\n",
       "      <td>[14.400024, -4.0]</td>\n",
       "      <td>0.351644</td>\n",
       "      <td>32.373600</td>\n",
       "      <td>1854</td>\n",
       "      <td>1863</td>\n",
       "      <td>9</td>\n",
       "      <td>[939.4, 516.7]</td>\n",
       "      <td>[927.9, 550.9]</td>\n",
       "      <td>[11.5, -34.200012]</td>\n",
       "      <td>0.259657</td>\n",
       "      <td>3568656.0</td>\n",
       "      <td>3568670.0</td>\n",
       "      <td>1.852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>saccade</th>\n",
       "      <td>3685</td>\n",
       "      <td>3707</td>\n",
       "      <td>22</td>\n",
       "      <td>[931.3, 548.1]</td>\n",
       "      <td>[950.9, 519.6]</td>\n",
       "      <td>[19.600037, -28.5]</td>\n",
       "      <td>0.604658</td>\n",
       "      <td>56.158707</td>\n",
       "      <td>3691</td>\n",
       "      <td>3702</td>\n",
       "      <td>11</td>\n",
       "      <td>[942.1, 521.8]</td>\n",
       "      <td>[932.5, 530.0]</td>\n",
       "      <td>[9.599976, -8.200012]</td>\n",
       "      <td>0.462714</td>\n",
       "      <td>3570489.0</td>\n",
       "      <td>3570511.0</td>\n",
       "      <td>3.685</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        expanded_start_time  expanded_end_time  \\\n",
       "subject run event_type                                           \n",
       "1       1   saccade                     272                292   \n",
       "            saccade                     405                426   \n",
       "            saccade                    1483               1505   \n",
       "            saccade                    1852               1866   \n",
       "            saccade                    3685               3707   \n",
       "\n",
       "                        expanded_duration expanded_start_point  \\\n",
       "subject run event_type                                           \n",
       "1       1   saccade                    20       [866.0, 540.1]   \n",
       "            saccade                    21       [889.8, 519.4]   \n",
       "            saccade                    22       [919.1, 574.0]   \n",
       "            saccade                    14       [924.8, 538.7]   \n",
       "            saccade                    22       [931.3, 548.1]   \n",
       "\n",
       "                       expanded_end_point          expanded_vector  \\\n",
       "subject run event_type                                               \n",
       "1       1   saccade        [904.1, 492.6]   [38.099976, -47.49997]   \n",
       "            saccade        [914.7, 530.3]   [24.900024, 10.899963]   \n",
       "            saccade        [937.5, 546.8]  [18.400024, -27.200012]   \n",
       "            saccade        [939.2, 534.7]        [14.400024, -4.0]   \n",
       "            saccade        [950.9, 519.6]       [19.600037, -28.5]   \n",
       "\n",
       "                        expanded_amplitude  peak_velocity  raw_start_time  \\\n",
       "subject run event_type                                                      \n",
       "1       1   saccade               0.728021      62.434765             274   \n",
       "            saccade               0.442447      37.022831             411   \n",
       "            saccade               0.639112      53.668053            1489   \n",
       "            saccade               0.351644      32.373600            1854   \n",
       "            saccade               0.604658      56.158707            3691   \n",
       "\n",
       "                        raw_end_time  raw_duration raw_start_point  \\\n",
       "subject run event_type                                               \n",
       "1       1   saccade              289            15  [909.8, 526.3]   \n",
       "            saccade              423            12  [922.6, 524.0]   \n",
       "            saccade             1501            12  [935.3, 514.5]   \n",
       "            saccade             1863             9  [939.4, 516.7]   \n",
       "            saccade             3702            11  [942.1, 521.8]   \n",
       "\n",
       "                         raw_end_point               raw_vector  \\\n",
       "subject run event_type                                            \n",
       "1       1   saccade     [864.8, 542.4]       [45.0, -16.100037]   \n",
       "            saccade     [893.9, 527.1]  [28.699951, -3.0999756]   \n",
       "            saccade     [913.3, 575.0]            [22.0, -60.5]   \n",
       "            saccade     [927.9, 550.9]       [11.5, -34.200012]   \n",
       "            saccade     [932.5, 530.0]    [9.599976, -8.200012]   \n",
       "\n",
       "                        raw_amplitude  start_timestamp  end_timestamp  onset  \n",
       "subject run event_type                                                        \n",
       "1       1   saccade          0.673154        3567076.0      3567096.0  0.272  \n",
       "            saccade          0.349249        3567209.0      3567230.0  0.405  \n",
       "            saccade          0.500670        3568287.0      3568309.0  1.483  \n",
       "            saccade          0.259657        3568656.0      3568670.0  1.852  \n",
       "            saccade          0.462714        3570489.0      3570511.0  3.685  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# and saccades\n",
    "eye_.df_saccades.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's plot some stuff, like gaze. Ideally, we'd like this to be as stable as possible, meaning the subject was fixating properly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<linescanning.plotting.LazyPlot at 0x7f1e1858a3d0>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1728x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# gaze x/y\n",
    "df_gaze = eye_.df_space_func.copy()\n",
    "input_l = [df_gaze[f\"gaze_{i}_int\"].values for i in [\"x\",\"y\"]]\n",
    "avg = [float(input_l[i].mean()) for i in range(len(input_l))]\n",
    "std = [float(input_l[i].std()) for i in range(len(input_l))]\n",
    "plotting.LazyPlot(\n",
    "    input_l,\n",
    "    line_width=2,\n",
    "    figsize=(24,5),\n",
    "    color=[\"#1B9E77\",\"#D95F02\"],\n",
    "    labels=[f\"gaze {i} (M={round(avg[ix],2)}; SD={round(std[ix],2)}px)\" for ix,i in enumerate([\"x\",\"y\"])],\n",
    "    x_label=\"volumes (TR-space)\",\n",
    "    y_label=\"position (pixels)\",\n",
    "    add_hline={\"pos\": avg},\n",
    "    title=\"gaze position during run (raw pixels)\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<linescanning.plotting.LazyPlot at 0x7f1e11ab8e80>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1728x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# gaze x/y percent signal changed\n",
    "input_l = [df_gaze[f\"gaze_{i}_int_psc\"].values for i in [\"x\",\"y\"]]\n",
    "avg = [float(input_l[i].mean()) for i in range(len(input_l))]\n",
    "std = [float(input_l[i].std()) for i in range(len(input_l))]\n",
    "plotting.LazyPlot(\n",
    "    input_l,\n",
    "    line_width=2,\n",
    "    figsize=(24,5),\n",
    "    color=[\"#1B9E77\",\"#D95F02\"],\n",
    "    labels=[f\"gaze {i} (M={round(avg[ix],2)}; SD={round(std[ix],2)}px)\" for ix,i in enumerate([\"x\",\"y\"])],\n",
    "    x_label=\"volumes (TR-space)\",\n",
    "    y_label=\"position (%change pixels)\",\n",
    "    add_hline=0,\n",
    "    title=\"gaze position during run (percent change)\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<linescanning.plotting.LazyPlot at 0x7f1e184c8eb0>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1728x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1728x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# pupil size\n",
    "data = df_gaze[\"pupil_int_hp\"].values\n",
    "avg = data.mean()\n",
    "\n",
    "# raw-ish values\n",
    "plotting.LazyPlot(\n",
    "    data,\n",
    "    line_width=2,\n",
    "    figsize=(24,5),\n",
    "    color=\"r\",\n",
    "    x_label=\"volumes (TR-space)\",\n",
    "    y_label=\"pupil size (pixels)\",\n",
    "    title=\"pupil size during run (high-pass filtered)\",\n",
    "    add_hline={\"pos\": avg}\n",
    ")\n",
    "\n",
    "# percent change\n",
    "data = df_gaze[\"pupil_int_hp_psc\"].values\n",
    "plotting.LazyPlot(\n",
    "    data,\n",
    "    line_width=2,\n",
    "    figsize=(24,5),\n",
    "    color=\"r\",\n",
    "    x_label=\"volumes (TR-space)\",\n",
    "    y_label=\"pupil size (pixels)\",\n",
    "    title=\"pupil size during run (high-pass filtered percent change)\",\n",
    "    add_hline=0\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also try to deconvolve the pupil response using the `eye_.df_blinks`-dataframe as onsets, and the pupil size as input data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Selected 'fourier'-basis sets\n",
      "Adding event 'blink' to model\n",
      "Fitting with 'ols' minimization\n",
      "Done\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# deconvolve pupil response\n",
    "interval = [0,7]\n",
    "nd_pupil = fitting.NideconvFitter(\n",
    "    df_gaze[\"pupil_int_hp_psc\"],\n",
    "    eye_.df_blinks,\n",
    "    basis_sets='fourier',\n",
    "    n_regressors=4,\n",
    "    TR=eye_.TR,\n",
    "    interval=interval,\n",
    "    add_intercept=True,\n",
    "    verbose=True)\n",
    "\n",
    "nd_pupil.plot_average_per_event(\n",
    "    figsize=(5,5),\n",
    "    x_label=\"time (s)\",\n",
    "    y_label=\"Magnitude (%)\",\n",
    "    title=\"pupil response\",\n",
    "    line_width=2,\n",
    "    font_size=16,\n",
    "    label_size=14,\n",
    "    color=\"r\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Use as part of [ParseExpToolsFile](https://linescanning.readthedocs.io/en/latest/classes/dataset.html#linescanning.dataset.ParseExpToolsFile) or [ParseFuncFile](https://linescanning.readthedocs.io/en/latest/classes/dataset.html#linescanning.dataset.ParseFuncFile)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also add the `edf`-files into classes that can read in the `tsv`-files from [exptools](https://github.com/Gilles86/exptools2/tree/show_pupil), or that can read in functional files. In case of the latter, we need to realize the inheritance structure from the code.\n",
    "\n",
    "[Dataset](https://linescanning.readthedocs.io/en/latest/classes/dataset.html#) << [ParseFuncFile](https://linescanning.readthedocs.io/en/latest/classes/dataset.html#linescanning.dataset.ParseFuncFile) << [ParseExpToolsFile](https://linescanning.readthedocs.io/en/latest/classes/dataset.html#linescanning.dataset.ParseExpToolsFile) << [ParseEyetrackerFile](https://linescanning.readthedocs.io/en/latest/classes/dataset.html#linescanning.dataset.ParseEyetrackerFile).\n",
    "\n",
    "So if we pass the edf-files and tsv-files to [ParseFuncFile](https://linescanning.readthedocs.io/en/latest/classes/dataset.html#linescanning.dataset.ParseFuncFile), they'll all trickle down where they need to go and you have everything in one dataframe. That would look something like this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I was able to import hedfpy\n",
      "\n",
      "EYETRACKER\n",
      "Preprocessing /data1/projects/MicroFunc/Jurjen/programs/packages/linescanning/examples/eye.edf\n",
      " Alias:        run_1\n",
      " Sample rate:  1000\n",
      " Start time:   3566804.0\n",
      " Stop time:    3863804.0\n",
      " Duration:     297.0s [297000 samples]\n",
      " Fetching:     ['pupil', 'pupil_int', 'gaze_x_int', 'gaze_y_int', 'gaze_x', 'gaze_y']\n",
      " Start time exp =  107.72\n",
      " Found 26 blinks [0.09 blinks per second]\n",
      " Found 579 saccades\n",
      "Done\n",
      "\n",
      "EXPTOOLS\n",
      "Preprocessing /data1/projects/MicroFunc/Jurjen/programs/packages/linescanning/examples/eye.tsv\n",
      " 1st 't' @107.72s\n",
      " Cutting 107.72s from onsets\n"
     ]
    }
   ],
   "source": [
    "tsv_file = opj(opd(edf_file), \"eye.tsv\")\n",
    "exp_ = dataset.ParseExpToolsFile(\n",
    "    tsv_file, \n",
    "    edfs=edf_file,\n",
    "    use_bids=False, \n",
    "    verbose=True, \n",
    "    TR=eye_.TR, \n",
    "    nr_vols=eye_.nr_vols,\n",
    "    phase_onset=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can see that we pass the `edf_file` with the `edfs=`-flag. This will trigger the initialization of [ParseEyetrackerFile](https://linescanning.readthedocs.io/en/latest/classes/dataset.html#linescanning.dataset.ParseEyetrackerFile), resulting in the same output that we saw before. Because we now also have `tsv_file`, we have some extra output on the preprocessing of that file. We do have, however, our usual output:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>onset</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>subject</th>\n",
       "      <th>run</th>\n",
       "      <th>event_type</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">1</th>\n",
       "      <th>blink</th>\n",
       "      <td>3.298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>blink</th>\n",
       "      <td>11.899</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>blink</th>\n",
       "      <td>17.987</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>blink</th>\n",
       "      <td>31.194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>blink</th>\n",
       "      <td>43.787</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         onset\n",
       "subject run event_type        \n",
       "1       1   blink        3.298\n",
       "            blink       11.899\n",
       "            blink       17.987\n",
       "            blink       31.194\n",
       "            blink       43.787"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "exp_.df_blinks.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>pupil</th>\n",
       "      <th>pupil_hp</th>\n",
       "      <th>pupil_psc</th>\n",
       "      <th>pupil_hp_psc</th>\n",
       "      <th>pupil_int</th>\n",
       "      <th>pupil_int_hp</th>\n",
       "      <th>pupil_int_psc</th>\n",
       "      <th>pupil_int_hp_psc</th>\n",
       "      <th>gaze_x_int</th>\n",
       "      <th>gaze_x_int_hp</th>\n",
       "      <th>...</th>\n",
       "      <th>gaze_y_int_psc</th>\n",
       "      <th>gaze_y_int_hp_psc</th>\n",
       "      <th>gaze_x</th>\n",
       "      <th>gaze_x_hp</th>\n",
       "      <th>gaze_x_psc</th>\n",
       "      <th>gaze_x_hp_psc</th>\n",
       "      <th>gaze_y</th>\n",
       "      <th>gaze_y_hp</th>\n",
       "      <th>gaze_y_psc</th>\n",
       "      <th>gaze_y_hp_psc</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>subject</th>\n",
       "      <th>run</th>\n",
       "      <th>t</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">1</th>\n",
       "      <th>0.0</th>\n",
       "      <td>3634.0</td>\n",
       "      <td>3306.871094</td>\n",
       "      <td>29.478714</td>\n",
       "      <td>17.873978</td>\n",
       "      <td>3634.0</td>\n",
       "      <td>3301.236572</td>\n",
       "      <td>29.483154</td>\n",
       "      <td>17.548630</td>\n",
       "      <td>864.299988</td>\n",
       "      <td>861.426758</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.320969</td>\n",
       "      <td>2.517723</td>\n",
       "      <td>864.299988</td>\n",
       "      <td>861.372864</td>\n",
       "      <td>-7.246170</td>\n",
       "      <td>-7.759895</td>\n",
       "      <td>542.000000</td>\n",
       "      <td>559.765381</td>\n",
       "      <td>-1.320480</td>\n",
       "      <td>2.184196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.1</th>\n",
       "      <td>2884.0</td>\n",
       "      <td>2557.087891</td>\n",
       "      <td>2.614754</td>\n",
       "      <td>-8.982216</td>\n",
       "      <td>2884.0</td>\n",
       "      <td>2551.462402</td>\n",
       "      <td>2.615150</td>\n",
       "      <td>-9.311279</td>\n",
       "      <td>923.000000</td>\n",
       "      <td>920.140625</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.742149</td>\n",
       "      <td>1.095352</td>\n",
       "      <td>923.000000</td>\n",
       "      <td>920.086853</td>\n",
       "      <td>-0.949356</td>\n",
       "      <td>-1.461578</td>\n",
       "      <td>534.200012</td>\n",
       "      <td>551.961243</td>\n",
       "      <td>-2.741142</td>\n",
       "      <td>0.762779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.2</th>\n",
       "      <td>3193.0</td>\n",
       "      <td>2866.520752</td>\n",
       "      <td>13.682709</td>\n",
       "      <td>2.101234</td>\n",
       "      <td>3193.0</td>\n",
       "      <td>2860.913330</td>\n",
       "      <td>13.684769</td>\n",
       "      <td>1.774490</td>\n",
       "      <td>932.799988</td>\n",
       "      <td>929.968384</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.323082</td>\n",
       "      <td>1.512039</td>\n",
       "      <td>932.799988</td>\n",
       "      <td>929.914856</td>\n",
       "      <td>0.101898</td>\n",
       "      <td>-0.407318</td>\n",
       "      <td>536.500000</td>\n",
       "      <td>554.252808</td>\n",
       "      <td>-2.322235</td>\n",
       "      <td>1.180161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.3</th>\n",
       "      <td>3087.0</td>\n",
       "      <td>2761.168213</td>\n",
       "      <td>9.885933</td>\n",
       "      <td>-1.672340</td>\n",
       "      <td>3087.0</td>\n",
       "      <td>2755.588135</td>\n",
       "      <td>9.887421</td>\n",
       "      <td>-1.998680</td>\n",
       "      <td>915.599976</td>\n",
       "      <td>912.809998</td>\n",
       "      <td>...</td>\n",
       "      <td>0.555717</td>\n",
       "      <td>4.387268</td>\n",
       "      <td>915.599976</td>\n",
       "      <td>912.756775</td>\n",
       "      <td>-1.743164</td>\n",
       "      <td>-2.247887</td>\n",
       "      <td>552.299988</td>\n",
       "      <td>570.040222</td>\n",
       "      <td>0.555519</td>\n",
       "      <td>4.055618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.4</th>\n",
       "      <td>2697.0</td>\n",
       "      <td>2372.028076</td>\n",
       "      <td>-4.083328</td>\n",
       "      <td>-15.610802</td>\n",
       "      <td>2697.0</td>\n",
       "      <td>2366.484131</td>\n",
       "      <td>-4.083939</td>\n",
       "      <td>-15.937943</td>\n",
       "      <td>947.599976</td>\n",
       "      <td>944.865417</td>\n",
       "      <td>...</td>\n",
       "      <td>-5.001472</td>\n",
       "      <td>-1.174690</td>\n",
       "      <td>947.599976</td>\n",
       "      <td>944.812622</td>\n",
       "      <td>1.689514</td>\n",
       "      <td>1.190781</td>\n",
       "      <td>521.799988</td>\n",
       "      <td>539.523315</td>\n",
       "      <td>-4.999634</td>\n",
       "      <td>-1.502617</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  pupil     pupil_hp  pupil_psc  pupil_hp_psc  pupil_int  \\\n",
       "subject run t                                                              \n",
       "1       1   0.0  3634.0  3306.871094  29.478714     17.873978     3634.0   \n",
       "            1.1  2884.0  2557.087891   2.614754     -8.982216     2884.0   \n",
       "            2.2  3193.0  2866.520752  13.682709      2.101234     3193.0   \n",
       "            3.3  3087.0  2761.168213   9.885933     -1.672340     3087.0   \n",
       "            4.4  2697.0  2372.028076  -4.083328    -15.610802     2697.0   \n",
       "\n",
       "                 pupil_int_hp  pupil_int_psc  pupil_int_hp_psc  gaze_x_int  \\\n",
       "subject run t                                                                \n",
       "1       1   0.0   3301.236572      29.483154         17.548630  864.299988   \n",
       "            1.1   2551.462402       2.615150         -9.311279  923.000000   \n",
       "            2.2   2860.913330      13.684769          1.774490  932.799988   \n",
       "            3.3   2755.588135       9.887421         -1.998680  915.599976   \n",
       "            4.4   2366.484131      -4.083939        -15.937943  947.599976   \n",
       "\n",
       "                 gaze_x_int_hp  ...  gaze_y_int_psc  gaze_y_int_hp_psc  \\\n",
       "subject run t                   ...                                      \n",
       "1       1   0.0     861.426758  ...       -1.320969           2.517723   \n",
       "            1.1     920.140625  ...       -2.742149           1.095352   \n",
       "            2.2     929.968384  ...       -2.323082           1.512039   \n",
       "            3.3     912.809998  ...        0.555717           4.387268   \n",
       "            4.4     944.865417  ...       -5.001472          -1.174690   \n",
       "\n",
       "                     gaze_x   gaze_x_hp  gaze_x_psc  gaze_x_hp_psc  \\\n",
       "subject run t                                                        \n",
       "1       1   0.0  864.299988  861.372864   -7.246170      -7.759895   \n",
       "            1.1  923.000000  920.086853   -0.949356      -1.461578   \n",
       "            2.2  932.799988  929.914856    0.101898      -0.407318   \n",
       "            3.3  915.599976  912.756775   -1.743164      -2.247887   \n",
       "            4.4  947.599976  944.812622    1.689514       1.190781   \n",
       "\n",
       "                     gaze_y   gaze_y_hp  gaze_y_psc  gaze_y_hp_psc  \n",
       "subject run t                                                       \n",
       "1       1   0.0  542.000000  559.765381   -1.320480       2.184196  \n",
       "            1.1  534.200012  551.961243   -2.741142       0.762779  \n",
       "            2.2  536.500000  554.252808   -2.322235       1.180161  \n",
       "            3.3  552.299988  570.040222    0.555519       4.055618  \n",
       "            4.4  521.799988  539.523315   -4.999634      -1.502617  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "exp_.df_space_func.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As well as the output from [ParseExpToolsFile](https://linescanning.readthedocs.io/en/latest/classes/dataset.html#linescanning.dataset.ParseExpToolsFile):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>onset</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>subject</th>\n",
       "      <th>run</th>\n",
       "      <th>event_type</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">1</th>\n",
       "      <th>baseline</th>\n",
       "      <td>0.002889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>horizontal</th>\n",
       "      <td>20.011666</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>horizontal</th>\n",
       "      <td>20.261721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>horizontal</th>\n",
       "      <td>20.511702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>horizontal</th>\n",
       "      <td>20.761743</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            onset\n",
       "subject run event_type           \n",
       "1       1   baseline     0.002889\n",
       "            horizontal  20.011666\n",
       "            horizontal  20.261721\n",
       "            horizontal  20.511702\n",
       "            horizontal  20.761743"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "exp_.get_onset_df(index=True).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Similarly, we can do this with the [ParseFuncFile](https://linescanning.readthedocs.io/en/latest/classes/dataset.html#linescanning.dataset.ParseFuncFile) or [Dataset](https://linescanning.readthedocs.io/en/latest/classes/dataset.html#) class:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "obj_ = dataset.Dataset(\n",
    "    \"some_funcfile.nii.gz\",\n",
    "    edf_file=edf_file,\n",
    "    tsv_file=tsv_file,\n",
    "    TR=eye_.TR,\n",
    "    nr_vols=eye_.nr_vols,\n",
    "    ...\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  }
 ],
 "metadata": {
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