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    "Automated pupillometer with STLAB\n",
    "=================================\n",
    "\n",
    "Automated pupillometers are the standard instruments for measuring the PLR. These handheld devices are aimed at a person's eye to deliver a light stimulus and use infrared video recording and internal algorithms to provide an instant readout of the PLR and its associated parameters. Our own [NeurOptics PLR-3000](https://neuroptics.com/plr-3000-hand-held/) is one such device, and it does an absolutely fantastic job. The STLAB-integrating sphere rig is no match for its compactness, portability and ease of use, but we figured at least that we could make it function in a similar way.\n"
   ]
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    "```Python\n",
    "#!/usr/bin/env python\n",
    "# -*- coding: utf-8 -*-\n",
    "\n",
    "import sys\n",
    "import os.path as op\n",
    "from time import sleep\n",
    "\n",
    "import numpy as np\n",
    "          \n",
    "from pyplr.stlab import SpectraTuneLab\n",
    "from pyplr.pupil import PupilCore\n",
    "from pyplr.utils import unpack_data_pandas\n",
    "from pyplr.preproc import butterworth_series\n",
    "from pyplr.plr import PLR\n",
    "from pyplr.protocol import (input_subject_id_gui, \n",
    "                            subject_dir, \n",
    "                            record_dir)   \n",
    "def main(subject_id=None, \n",
    "         baseline=2., \n",
    "         duration=8.,\n",
    "         sample_rate=120,\n",
    "         stimulus='./stimuli/PLR-3000-180-mw.dsf',\n",
    "         record=True, \n",
    "         control=False,\n",
    "         config=None):\n",
    "    \n",
    "    # Set up subject and recording\n",
    "    if subject_id is None:\n",
    "        subject_id = input_subject_id_gui()\n",
    "    subj_dir = subject_dir(subject_id)\n",
    "    rec_dir = record_dir(subj_dir)\n",
    "        \n",
    "    # Set up Pupil Core\n",
    "    p = PupilCore()\n",
    "    \n",
    "    # Setup STLAB\n",
    "    d = SpectraTuneLab(password='****************')\n",
    "    d.load_video_file(stimulus)\n",
    "\n",
    "    # Prepare annotation\n",
    "    annotation = p.new_annotation('LIGHT_ON')\n",
    "    \n",
    "    if control:\n",
    "        input(\"Press Enter to administer stimulus...\")\n",
    "        \n",
    "    if record:\n",
    "        p.command('R {}'.format(rec_dir))\n",
    "        sleep(1.)\n",
    "        \n",
    "    # Start light_stamper and pupil_grabber\n",
    "    lst_future = p.light_stamper(\n",
    "        annotation, threshold=15, timeout=6.)\n",
    "    pgr_future = p.pupil_grabber(\n",
    "        topic='pupil.1.3d', seconds=duration+baseline+2)\n",
    "    \n",
    "    # Baseline period\n",
    "    sleep(baseline)\n",
    "    \n",
    "    # Present Stimulus\n",
    "    d.play_video_file()\n",
    "    \n",
    "    # Wait for futures\n",
    "    while lst_future.running() or pgr_future.running():\n",
    "        print('Waiting for futures...')\n",
    "        sleep(1)\n",
    "    \n",
    "    if record:\n",
    "        p.command('r')\n",
    "    \n",
    "    if not lst_future.result()[0]:\n",
    "        print('light was not detected. Ending program.')\n",
    "        sys.exit(0)\n",
    "        \n",
    "    # Retrieve and process pupil data\n",
    "    data = unpack_data_pandas(\n",
    "        pgr_future.result(), cols=['timestamp','diameter_3d'])\n",
    "    data = butterworth_series(\n",
    "        data, \n",
    "        filt_order=3, \n",
    "        cutoff_freq=4/(sample_rate/2), \n",
    "        fields=['diameter_3d'])\n",
    "    \n",
    "    # Get light_stamper timestamp\n",
    "    ts = lst_future.result()[1]\n",
    "    \n",
    "    # Find the closest timestamp in the pupil data\n",
    "    idx = (np.abs(ts - data.index)).argmin()\n",
    "    \n",
    "    # Trim\n",
    "    start = int(idx-(baseline*sample_rate))\n",
    "    end = int(idx+(duration*sample_rate))\n",
    "    data = data.iloc[start:end]\n",
    "    data.reset_index(inplace=True)\n",
    "    \n",
    "    # Analyse PLR\n",
    "    plr = PLR(plr=data.diameter_3d.to_numpy(),\n",
    "              sample_rate=sample_rate, \n",
    "              onset_idx=idx,\n",
    "              stim_duration=1)\n",
    "    plr.parameters().to_csv(op.join(rec_dir, 'plr_parameters.csv'))\n",
    "    plr.plot().savefig(op.join(rec_dir, 'plr_plot.png'), bbox_inches='tight')\n",
    "    data.to_csv(op.join(rec_dir, 'raw_data.csv'))\n",
    "    \n",
    "if __name__ == '__main__':    \n",
    "    try:\n",
    "        main()\n",
    "    except KeyboardInterrupt:\n",
    "        print('Killed by user')\n",
    "        sys.exit(0)\n",
    "```        "
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