{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Analysis of pupil data\n",
    "======================\n",
    "\n",
    "There are many valid approaches to the analysis of pupillometry data, but the optimal approach will depend on the type of experiment being run and the research question in mind. [Kelbsch et al. (2019)](https://www.frontiersin.org/articles/10.3389/fneur.2019.00129/full) provide an informative view on standards in pupillometry, and there are [some](https://github.com/samhforbes/PupillometryR) [great](https://github.com/beOn/cili) [examples](https://github.com/ihrke/pypillometry) of community-developed packages for streamlining pupillometry data analysis. Whilst it is always worth exploring the wider options that are available, *PyPlr* includes a set of pandas-reliant (you won't regret [learning pandas!](https://bitbucket.org/hrojas/learn-pandas/src/master/)) scripting tools for implementing a standard data processing pipeline that is optimised to work with some of the idiosynchrasies of Pupil Labs data. So far we have found these tools to be adequate for analysing our own data, but we welcome suggestions for improvements. \n",
    "\n",
    "See [here](https://github.com/pupil-labs/pupil-tutorials/blob/master/01_load_exported_data_and_visualize_pupillometry.ipynb) for a general introduction to analysing Pupil Labs pupillometry data. What follows is a typical *PyPlr* analysis pipeline with tools from `pyplr.utils` and `pyplr.preproc`.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Export with Pupil Player\n",
    "------------------------\n",
    "\n",
    "The first step in our pipeline is to export the data using [Pupil Player](https://docs.pupil-labs.com/core/software/pupil-player/), making sure the required plugins (e.g., Annotation Player plugin) are enabled. Currently this must be done individually for each recording. Below is printed the file structure of a typical recording after export (more info on recording format [here](https://docs.pupil-labs.com/developer/core/recording-format/#recording-format))."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "JTM/\n",
      "    .DS_Store\n",
      "    annotation.pldata\n",
      "    annotation_player.pldata\n",
      "    annotation_player_timestamps.npy\n",
      "    annotation_timestamps.npy\n",
      "    blinks.pldata\n",
      "    blinks_timestamps.npy\n",
      "    eye1.intrinsics\n",
      "    eye1.mp4\n",
      "    eye1_lookup.npy\n",
      "    eye1_timestamps.npy\n",
      "    fixations.pldata\n",
      "    fixations_timestamps.npy\n",
      "    gaze.pldata\n",
      "    gaze_timestamps.npy\n",
      "    info.player.json\n",
      "    notify.pldata\n",
      "    notify_timestamps.npy\n",
      "    pupil.pldata\n",
      "    pupil_timestamps.npy\n",
      "    surface_definitions_v01\n",
      "    user_info.csv\n",
      "    world.intrinsics\n",
      "    world.mp4\n",
      "    world_lookup.npy\n",
      "    world_timestamps.npy\n",
      "    analysis/\n",
      "        plr_extraction.png\n",
      "        plr_metrics.csv\n",
      "        plr_overall_metrics.png\n",
      "        processed.csv\n",
      "        pupil_processing.png\n",
      "    exports/\n",
      "        000/\n",
      "            annotations.csv\n",
      "            export_info.csv\n",
      "            gaze_positions.csv\n",
      "            pupil_gaze_positions_info.txt\n",
      "            pupil_positions.csv\n",
      "            world.mp4\n",
      "            world_timestamps.csv\n",
      "            world_timestamps.npy\n",
      "    pyplr_analysis/\n",
      "    offline_data/\n",
      "        tokens/\n",
      "            gaze_positions_consumer_Vis_Polyline.token\n",
      "            gaze_positions_producer_GazeFromRecording.token\n",
      "            pupil_positions_consumer_Pupil_From_Recording.token\n",
      "            pupil_positions_consumer_System_Timelines.token\n",
      "            pupil_positions_producer_Pupil_From_Recording.token\n"
     ]
    }
   ],
   "source": [
    "from pyplr import utils\n",
    "\n",
    "# Pupil Labs recording directory\n",
    "rec_dir = '/Users/jtm/OneDrive - Nexus365/protocols/pipr_protocol/JTM'\n",
    "utils.print_file_structure(rec_dir)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load exported data\n",
    "------------------\n",
    "\n",
    "Now we can set up some constants and use `pyplr.utils` to get things moving. `new_subject(...)` returns a dictionary with the root directory, recording id, data directory and a newly made output directory for the analysis results. Then, passing the data directory to `load_pupil(...)`, we load the specified columns from the *pupil_positions.csv* exported data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "************************************************************\n",
      "*************************** JTM ****************************\n",
      "************************************************************\n",
      "Loaded 48552 samples\n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>eye_id</th>\n",
       "      <th>confidence</th>\n",
       "      <th>diameter</th>\n",
       "      <th>method</th>\n",
       "      <th>diameter_3d</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pupil_timestamp</th>\n",
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       "<p>48552 rows × 5 columns</p>\n",
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      "text/plain": [
       "                 eye_id  confidence   diameter  method  diameter_3d\n",
       "pupil_timestamp                                                    \n",
       "85838.895658          1    0.977211  50.102968  3d c++     6.105771\n",
       "85838.903656          1    0.997867  50.037086  3d c++     6.099682\n",
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       "...                 ...         ...        ...     ...          ...\n",
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       "86246.746889          1    0.969337  57.176728  3d c++     7.027931\n",
       "86246.758588          1    0.956524  56.838490  3d c++     6.988390\n",
       "86246.762987          1    0.927155  56.933094  3d c++     7.000156\n",
       "\n",
       "[48552 rows x 5 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Columns to load\n",
    "use_cols = ['confidence',\n",
    "            'method',\n",
    "            'pupil_timestamp',\n",
    "            'eye_id',\n",
    "            'diameter_3d',\n",
    "            'diameter']\n",
    "\n",
    "# Get a handle on a subject\n",
    "s = utils.new_subject(\n",
    "    rec_dir, export='000', out_dir_nm='pyplr_analysis')\n",
    "\n",
    "# Load pupil data\n",
    "samples = utils.load_pupil(\n",
    "    s['data_dir'], eye_id='best', cols=use_cols)\n",
    "samples"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Preprocessing\n",
    "-------------\n",
    "\n",
    "Preprocessing pupillometry data is relatively straight-forward and typically involves dealing with signal loss due to eye blinks and smoothing out any high frequency noise. There are [sophisticated algorithms](https://osf.io/jyz43/) for detecting blinks in a pupil time course, but Pupil Player has its own [Blink Detection](https://docs.pupil-labs.com/core/software/pupil-capture/#blink-detection) plugin that detects blinks based on rapid changes in the [confidence metric](https://docs.pupil-labs.com/core/terminology/#confidence). Whilst you can export these blink events and use the timestamps to index and mask the pupil timecourse, we find that it is effective simply to mask the pupil data with thresholds on the first derivative and confidence metric, and then to follow up with linear interpolation and smoothing."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x1008 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pyplr import graphing\n",
    "from pyplr import preproc\n",
    "\n",
    "# Sampling frequency\n",
    "SAMPLE_RATE = 120\n",
    "\n",
    "# Pupil columns to analyse\n",
    "pupil_cols = ['diameter_3d', 'diameter']\n",
    "\n",
    "# Make figure for processing\n",
    "f, axs = graphing.pupil_preprocessing(nrows=5, subject='Example')\n",
    "\n",
    "# Plot the raw data\n",
    "samples[pupil_cols].plot(title='Raw', ax=axs[0], legend=True)\n",
    "axs[0].legend(loc='center right', labels=['mm', 'pixels'])\n",
    "\n",
    "# Mask first derivative\n",
    "samples = preproc.mask_pupil_first_derivative(\n",
    "    samples, threshold=3.0, mask_cols=pupil_cols)\n",
    "samples[pupil_cols].plot(\n",
    "    title='Masked 1st deriv (3*SD)', ax=axs[1], legend=False)\n",
    "\n",
    "# Mask confidence\n",
    "samples = preproc.mask_pupil_confidence(\n",
    "    samples, threshold=0.8, mask_cols=pupil_cols)\n",
    "samples[pupil_cols].plot(\n",
    "    title='Masked confidence (<0.8)', ax=axs[2], legend=False)\n",
    "\n",
    "# Interpolate\n",
    "samples = preproc.interpolate_pupil(\n",
    "    samples, interp_cols=pupil_cols)\n",
    "samples[pupil_cols].plot(\n",
    "    title='Linear interpolation', ax=axs[3], legend=False)\n",
    "\n",
    "# Smooth  \n",
    "samples = preproc.butterworth_series(\n",
    "    samples, fields=pupil_cols, filt_order=3, \n",
    "    cutoff_freq=4/(SAMPLE_RATE/2))\n",
    "samples[pupil_cols].plot(\n",
    "    title='3rd order Butterworth filter with 4 Hz cut-off', \n",
    "    ax=axs[4], legend=False);\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Extraction\n",
    "----------\n",
    "\n",
    "Having cleaned the timecourse we need to extract the events of interest. This requires the annotation events sent during the recording, which have the timestamps needed for extraction. These can be loaded with `utlis.load_annotations(...)`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loaded 6 events\n"
     ]
    },
    {
     "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>index</th>\n",
       "      <th>label</th>\n",
       "      <th>duration</th>\n",
       "      <th>color</th>\n",
       "      <th>creation_time</th>\n",
       "      <th>creator</th>\n",
       "      <th>protocol</th>\n",
       "      <th>pulse_duration</th>\n",
       "      <th>pulse_spec</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>timestamp</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>85854.348667</th>\n",
       "      <td>1835</td>\n",
       "      <td>LIGHT_ON</td>\n",
       "      <td>NaN</td>\n",
       "      <td>red</td>\n",
       "      <td>2020-11-10 09:39:10.888989</td>\n",
       "      <td>jtm</td>\n",
       "      <td>pulse</td>\n",
       "      <td>1000</td>\n",
       "      <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 1979]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85919.820362</th>\n",
       "      <td>9629</td>\n",
       "      <td>LIGHT_ON</td>\n",
       "      <td>NaN</td>\n",
       "      <td>blue</td>\n",
       "      <td>2020-11-10 09:39:10.882007</td>\n",
       "      <td>jtm</td>\n",
       "      <td>pulse</td>\n",
       "      <td>1000</td>\n",
       "      <td>[0, 0, 0, 2500, 0, 0, 0, 0, 0, 0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85985.280630</th>\n",
       "      <td>17422</td>\n",
       "      <td>LIGHT_ON</td>\n",
       "      <td>NaN</td>\n",
       "      <td>blue</td>\n",
       "      <td>2020-11-10 09:39:10.882007</td>\n",
       "      <td>jtm</td>\n",
       "      <td>pulse</td>\n",
       "      <td>1000</td>\n",
       "      <td>[0, 0, 0, 2500, 0, 0, 0, 0, 0, 0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86050.768628</th>\n",
       "      <td>25217</td>\n",
       "      <td>LIGHT_ON</td>\n",
       "      <td>NaN</td>\n",
       "      <td>red</td>\n",
       "      <td>2020-11-10 09:39:10.888989</td>\n",
       "      <td>jtm</td>\n",
       "      <td>pulse</td>\n",
       "      <td>1000</td>\n",
       "      <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 1979]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86116.228025</th>\n",
       "      <td>33008</td>\n",
       "      <td>LIGHT_ON</td>\n",
       "      <td>NaN</td>\n",
       "      <td>blue</td>\n",
       "      <td>2020-11-10 09:39:10.882007</td>\n",
       "      <td>jtm</td>\n",
       "      <td>pulse</td>\n",
       "      <td>1000</td>\n",
       "      <td>[0, 0, 0, 2500, 0, 0, 0, 0, 0, 0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86181.688172</th>\n",
       "      <td>40801</td>\n",
       "      <td>LIGHT_ON</td>\n",
       "      <td>NaN</td>\n",
       "      <td>red</td>\n",
       "      <td>2020-11-10 09:39:10.888989</td>\n",
       "      <td>jtm</td>\n",
       "      <td>pulse</td>\n",
       "      <td>1000</td>\n",
       "      <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 1979]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              index     label  duration color               creation_time  \\\n",
       "timestamp                                                                   \n",
       "85854.348667   1835  LIGHT_ON       NaN   red  2020-11-10 09:39:10.888989   \n",
       "85919.820362   9629  LIGHT_ON       NaN  blue  2020-11-10 09:39:10.882007   \n",
       "85985.280630  17422  LIGHT_ON       NaN  blue  2020-11-10 09:39:10.882007   \n",
       "86050.768628  25217  LIGHT_ON       NaN   red  2020-11-10 09:39:10.888989   \n",
       "86116.228025  33008  LIGHT_ON       NaN  blue  2020-11-10 09:39:10.882007   \n",
       "86181.688172  40801  LIGHT_ON       NaN   red  2020-11-10 09:39:10.888989   \n",
       "\n",
       "             creator protocol  pulse_duration  \\\n",
       "timestamp                                       \n",
       "85854.348667     jtm    pulse            1000   \n",
       "85919.820362     jtm    pulse            1000   \n",
       "85985.280630     jtm    pulse            1000   \n",
       "86050.768628     jtm    pulse            1000   \n",
       "86116.228025     jtm    pulse            1000   \n",
       "86181.688172     jtm    pulse            1000   \n",
       "\n",
       "                                     pulse_spec  \n",
       "timestamp                                        \n",
       "85854.348667  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1979]  \n",
       "85919.820362  [0, 0, 0, 2500, 0, 0, 0, 0, 0, 0]  \n",
       "85985.280630  [0, 0, 0, 2500, 0, 0, 0, 0, 0, 0]  \n",
       "86050.768628  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1979]  \n",
       "86116.228025  [0, 0, 0, 2500, 0, 0, 0, 0, 0, 0]  \n",
       "86181.688172  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1979]  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "events = utils.load_annotations(s['data_dir'])\n",
    "events"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can pass our samples and events to `utils.extract(...)` along with some parameters defining the number of samples to extract and how much to offset the data relative to the event. Here we extract-65 second epochs and offset by a 5 second baseline period."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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     "text": [
      "Extracted ranges for 6 events\n"
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       "             eye_id  confidence   diameter  method  diameter_3d  interpolated  \\\n",
       "event onset                                                                     \n",
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       "\n",
       "                 orig_idx color  \n",
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     "execution_count": 5,
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   ],
   "source": [
    "# Number of samples to extract and which sample\n",
    "# should mark the onset of the event\n",
    "DURATION = 7800\n",
    "ONSET_IDX = 600\n",
    "\n",
    "# Extract the event ranges\n",
    "ranges = utils.extract(\n",
    "    samples, \n",
    "    events, \n",
    "    offset=-ONSET_IDX, \n",
    "    duration=DURATION, \n",
    "    borrow_attributes=['color'])\n",
    "ranges"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "``utils.extract(...)`` returns a pandas DataFrame with a two-level (event, onset) [hierarchichal index](https://pandas.pydata.org/pandas-docs/stable/user_guide/advanced.html). The original index to the data is preserved in a column along with any attributes borrowed from the annotations. Now is a good time to create additional columns expressing the pupil data as percent signal change from baseline."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
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      "text/plain": [
       "             eye_id  confidence   diameter  method  diameter_3d  interpolated  \\\n",
       "event onset                                                                     \n",
       "0     0         1.0    0.998989  48.404937  3d c++     5.990967             0   \n",
       "      1         1.0    0.998972  48.436117  3d c++     5.994949             0   \n",
       "      2         1.0    0.999134  48.469848  3d c++     5.999237             0   \n",
       "      3         1.0    0.998426  48.505896  3d c++     6.003802             0   \n",
       "      4         1.0    0.998895  48.544031  3d c++     6.008612             0   \n",
       "...             ...         ...        ...     ...          ...           ...   \n",
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       "      7799      1.0    0.903852  54.249187  3d c++     6.696413             0   \n",
       "\n",
       "                 orig_idx color  diameter_3d_pc  diameter_pc  \n",
       "event onset                                                   \n",
       "0     0      85849.311553   red       -6.907039    -7.009474  \n",
       "      1      85849.319757   red       -6.845173    -6.949574  \n",
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       "...                   ...   ...             ...          ...  \n",
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       "\n",
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     },
     "execution_count": 6,
     "metadata": {},
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    }
   ],
   "source": [
    "# Calculate baselines\n",
    "baselines = ranges.loc[:, range(0, ONSET_IDX), :].mean(level=0)\n",
    "\n",
    "# New columns for percent signal change\n",
    "ranges = preproc.percent_signal_change(\n",
    "    ranges, baselines, pupil_cols)\n",
    "ranges"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plotting and parametrisation\n",
    "----------------------------\n",
    "\n",
    "It is common practice when analysing the PLR to describe it in terms of paremeters relating to time, velocity and acceleration. So once you have an array of data representing a pupil's response to light, be it from a single trial or an average of multiple trials, simply pass it to `pyplr.plr.PLR` along with some basic parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyplr.plr import PLR\n",
    "\n",
    "average_plr = ranges.mean(level=1)['diameter_3d'].to_numpy()\n",
    "plr = PLR(average_plr, \n",
    "          sample_rate=SAMPLE_RATE, \n",
    "          onset_idx=ONSET_IDX, \n",
    "          stim_duration=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now you can do a quick plot with options to display the velocity and acceleration profiles and the derived parameters:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plr.plot(vel=True, acc=True, print_params=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Or simply access the parameters as a DataFrame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Baseline</th>\n",
       "      <td>6.751031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Latency_a</th>\n",
       "      <td>0.225000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Latency_b</th>\n",
       "      <td>0.283333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T2MaxVel</th>\n",
       "      <td>0.425000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T2MaxCon</th>\n",
       "      <td>1.550000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T2Rec75pc</th>\n",
       "      <td>18.825000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PeakCon</th>\n",
       "      <td>3.164023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ConAmplitude</th>\n",
       "      <td>3.587008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VelConMax</th>\n",
       "      <td>5.940593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VelConAve</th>\n",
       "      <td>2.670336</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AccConMax</th>\n",
       "      <td>35.127363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ConTime</th>\n",
       "      <td>1.325000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VelRedMax</th>\n",
       "      <td>0.999670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AccRedMax</th>\n",
       "      <td>7.021978</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  value\n",
       "Baseline       6.751031\n",
       "Latency_a      0.225000\n",
       "Latency_b      0.283333\n",
       "T2MaxVel       0.425000\n",
       "T2MaxCon       1.550000\n",
       "T2Rec75pc     18.825000\n",
       "PeakCon        3.164023\n",
       "ConAmplitude   3.587008\n",
       "VelConMax      5.940593\n",
       "VelConAve      2.670336\n",
       "AccConMax     35.127363\n",
       "ConTime        1.325000\n",
       "VelRedMax      0.999670\n",
       "AccRedMax      7.021978"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "params = plr.parameters()\n",
    "params"
   ]
  }
 ],
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