howto_read_XDF_recordings.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### How to read:\n",
    "### [LSL (LabStreamingLayer)](https://labstreaminglayer.readthedocs.io/info/intro.html) and [XDF](https://github.com/sccn/xdf) recordings\n",
    "#### An example with simultaneous streams from a [mobile EEG Android App](https://github.com/adrocampos/EEG-Droid) and a [Python script sending keyboard triggers](https://github.com/mvidaldp/pylsl-keyboard-trigger)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Dependencies for reading XDF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pyxdf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Dependencies for calculations and plotting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import itertools\n",
    "\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "from matplotlib import pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Read file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "data, header = pyxdf.load_xdf(\"eeg_plus_triggers.xdf\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "How the header looks like"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'info': defaultdict(list, {'version': ['1.0']})}"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "header"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "How the recorded streams looks like"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'info': defaultdict(list,\n",
       "              {'name': ['KeyboardTriggers'],\n",
       "               'type': ['Markers'],\n",
       "               'channel_count': ['2'],\n",
       "               'channel_format': ['float32'],\n",
       "               'source_id': ['3a4dca8c-0efd-11eb-82d9-da25bd87aa5a'],\n",
       "               'nominal_srate': ['0.000000000000000'],\n",
       "               'version': ['1.100000000000000'],\n",
       "               'created_at': ['18657.16455691900'],\n",
       "               'uid': ['3bd64861-0636-40e0-b74a-1c3d2ce4a2d6'],\n",
       "               'session_id': ['default'],\n",
       "               'hostname': ['velorum'],\n",
       "               'v4address': [None],\n",
       "               'v4data_port': ['16572'],\n",
       "               'v4service_port': ['16572'],\n",
       "               'v6address': [None],\n",
       "               'v6data_port': ['16573'],\n",
       "               'v6service_port': ['16573'],\n",
       "               'desc': [None],\n",
       "               'stream_id': 1,\n",
       "               'effective_srate': 0}),\n",
       "  'footer': {'info': defaultdict(list,\n",
       "               {'first_timestamp': ['18692.426129456'],\n",
       "                'last_timestamp': ['18713.67744727'],\n",
       "                'sample_count': ['9'],\n",
       "                'clock_offsets': [defaultdict(list,\n",
       "                             {'offset': [defaultdict(list,\n",
       "                                           {'time': ['18693.872479023'],\n",
       "                                            'value': ['7.184999049059115e-06']}),\n",
       "                               defaultdict(list,\n",
       "                                           {'time': ['18698.872561483'],\n",
       "                                            'value': ['-7.589002052554861e-06']}),\n",
       "                               defaultdict(list,\n",
       "                                           {'time': ['18703.872660776'],\n",
       "                                            'value': ['-2.577400118752848e-05']}),\n",
       "                               defaultdict(list,\n",
       "                                           {'time': ['18708.872784644'],\n",
       "                                            'value': ['-3.343599928484764e-05']}),\n",
       "                               defaultdict(list,\n",
       "                                           {'time': ['18713.872949355'],\n",
       "                                            'value': ['-2.73040004685754e-05']}),\n",
       "                               defaultdict(list,\n",
       "                                           {'time': ['18718.8730267395'],\n",
       "                                            'value': ['-1.134349986386951e-05']})]})]})},\n",
       "  'time_series': array([[1.6027767e+09, 1.0000000e+00],\n",
       "         [1.6027767e+09, 0.0000000e+00],\n",
       "         [1.6027767e+09, 1.0000000e+00],\n",
       "         [1.6027767e+09, 0.0000000e+00],\n",
       "         [1.6027767e+09, 1.0000000e+00],\n",
       "         [1.6027767e+09, 0.0000000e+00],\n",
       "         [1.6027767e+09, 1.0000000e+00],\n",
       "         [1.6027767e+09, 0.0000000e+00],\n",
       "         [1.6027767e+09, 1.0000000e+00],\n",
       "         [1.6027767e+09, 0.0000000e+00]], dtype=float32),\n",
       "  'time_stamps': array([18692.42612579, 18695.09653543, 18697.36005416, 18699.68524659,\n",
       "         18702.18734364, 18704.60320733, 18706.81185163, 18709.12982383,\n",
       "         18711.39721317, 18713.67742424])},\n",
       " {'info': defaultdict(list,\n",
       "              {'name': ['Traumschreiber-EEG'],\n",
       "               'type': ['Markers'],\n",
       "               'channel_count': ['24'],\n",
       "               'channel_format': ['float32'],\n",
       "               'source_id': ['37f209f1-9aab-4a41-b386-56387bc4b937'],\n",
       "               'nominal_srate': ['0.000000000000000'],\n",
       "               'version': ['1.100000000000000'],\n",
       "               'created_at': ['63077.37698702900'],\n",
       "               'uid': ['a7dff592-222c-4aba-93b2-6bf809f139ba'],\n",
       "               'session_id': ['default'],\n",
       "               'hostname': ['localhost'],\n",
       "               'v4address': [None],\n",
       "               'v4data_port': ['16574'],\n",
       "               'v4service_port': ['16574'],\n",
       "               'v6address': [None],\n",
       "               'v6data_port': ['16575'],\n",
       "               'v6service_port': ['16575'],\n",
       "               'desc': [None],\n",
       "               'stream_id': 2,\n",
       "               'effective_srate': 0}),\n",
       "  'footer': {'info': defaultdict(list,\n",
       "               {'first_timestamp': ['63151.218883251'],\n",
       "                'last_timestamp': ['63179.721298032'],\n",
       "                'sample_count': ['7113'],\n",
       "                'clock_offsets': [defaultdict(list,\n",
       "                             {'offset': [defaultdict(list,\n",
       "                                           {'time': ['63156.8671146405'],\n",
       "                                            'value': ['-44462.99462843849']}),\n",
       "                               defaultdict(list,\n",
       "                                           {'time': ['63161.8685086535'],\n",
       "                                            'value': ['-44462.9959094835']}),\n",
       "                               defaultdict(list,\n",
       "                                           {'time': ['63166.867092952'],\n",
       "                                            'value': ['-44462.99436651']}),\n",
       "                               defaultdict(list,\n",
       "                                           {'time': ['63171.86739596151'],\n",
       "                                            'value': ['-44462.99456075051']}),\n",
       "                               defaultdict(list,\n",
       "                                           {'time': ['63176.86724635201'],\n",
       "                                            'value': ['-44462.994291562']}),\n",
       "                               defaultdict(list,\n",
       "                                           {'time': ['63181.86833529599'],\n",
       "                                            'value': ['-44462.99527644899']})]})]})},\n",
       "  'time_series': array([[ 0.10281  , -1.566884 ,  0.578716 , ...,  0.       ,  0.       ,\n",
       "           0.       ],\n",
       "         [ 0.107876 , -1.5701619,  0.577226 , ...,  0.       ,  0.       ,\n",
       "           0.       ],\n",
       "         [ 0.09834  , -1.579102 ,  0.585868 , ...,  0.       ,  0.       ,\n",
       "           0.       ],\n",
       "         ...,\n",
       "         [ 0.103108 , -1.566586 ,  0.59153  , ...,  0.       ,  0.       ,\n",
       "           0.       ],\n",
       "         [ 0.088506 , -1.572248 ,  0.587656 , ...,  0.       ,  0.       ,\n",
       "           0.       ],\n",
       "         [ 0.090592 , -1.57046  ,  0.570968 , ...,  0.       ,  0.       ,\n",
       "           0.       ]], dtype=float32),\n",
       "  'time_stamps': array([18688.22422918, 18688.22649997, 18688.227458  , ...,\n",
       "         18716.71308079, 18716.72445876, 18716.72677289])},\n",
       " {'info': defaultdict(list,\n",
       "              {'name': ['Traumschreiber-EEG'],\n",
       "               'type': ['Markers'],\n",
       "               'channel_count': ['24'],\n",
       "               'channel_format': ['float32'],\n",
       "               'source_id': ['94eed3de-7445-463c-b358-3fe2c58b5116'],\n",
       "               'nominal_srate': ['0.000000000000000'],\n",
       "               'version': ['1.100000000000000'],\n",
       "               'created_at': ['63027.78544668400'],\n",
       "               'uid': ['d459e608-9113-46aa-9927-74ff6c118c71'],\n",
       "               'session_id': ['default'],\n",
       "               'hostname': ['localhost'],\n",
       "               'v4address': [None],\n",
       "               'v4data_port': ['16572'],\n",
       "               'v4service_port': ['16572'],\n",
       "               'v6address': [None],\n",
       "               'v6data_port': ['16573'],\n",
       "               'v6service_port': ['16573'],\n",
       "               'desc': [None],\n",
       "               'stream_id': 3,\n",
       "               'effective_srate': 0}),\n",
       "  'footer': {'info': defaultdict(list,\n",
       "               {'first_timestamp': ['0'],\n",
       "                'last_timestamp': ['0'],\n",
       "                'sample_count': ['0'],\n",
       "                'clock_offsets': [defaultdict(list,\n",
       "                             {'offset': [defaultdict(list,\n",
       "                                           {'time': ['63156.8670803585'],\n",
       "                                            'value': ['-44462.9946112915']}),\n",
       "                               defaultdict(list,\n",
       "                                           {'time': ['63161.8683851695'],\n",
       "                                            'value': ['-44462.9958041955']}),\n",
       "                               defaultdict(list,\n",
       "                                           {'time': ['63166.8670923825'],\n",
       "                                            'value': ['-44462.9943906785']}),\n",
       "                               defaultdict(list,\n",
       "                                           {'time': ['63171.86752227'],\n",
       "                                            'value': ['-44462.994670349']}),\n",
       "                               defaultdict(list,\n",
       "                                           {'time': ['63176.8674222525'],\n",
       "                                            'value': ['-44462.9944453355']}),\n",
       "                               defaultdict(list,\n",
       "                                           {'time': ['63181.868393611'],\n",
       "                                            'value': ['-44462.995321747']})]})]})},\n",
       "  'time_series': array([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "          0., 0., 0., 0., 0., 0., 0., 0.]], dtype=float32),\n",
       "  'time_stamps': array([-44462.74848036])}]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `data` part read from the file is an array/list of dictionaries. So, each dict represents a different stream. We recorded two streams. The first one is from the [keyboard-trigger.py](https://github.com/mvidaldp/pylsl-keyboard-trigger/blob/main/keyboard-trigger.py) Python script sending triggers via keyboard press. The second is from the [mobile EEG App](https://github.com/adrocampos/EEG-Droid) sending the measured EEG channel values of the Traumschreiber (mobile EEG) device.\n",
    "\n",
    "The keys inside each dict (stream) are explained below.\n",
    "\n",
    "On `info` there's the recorded stream/s information (name, type, data type, hostname, uid, sampling rate, etc.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "defaultdict(list,\n",
       "            {'name': ['KeyboardTriggers'],\n",
       "             'type': ['Markers'],\n",
       "             'channel_count': ['2'],\n",
       "             'channel_format': ['float32'],\n",
       "             'source_id': ['3a4dca8c-0efd-11eb-82d9-da25bd87aa5a'],\n",
       "             'nominal_srate': ['0.000000000000000'],\n",
       "             'version': ['1.100000000000000'],\n",
       "             'created_at': ['18657.16455691900'],\n",
       "             'uid': ['3bd64861-0636-40e0-b74a-1c3d2ce4a2d6'],\n",
       "             'session_id': ['default'],\n",
       "             'hostname': ['velorum'],\n",
       "             'v4address': [None],\n",
       "             'v4data_port': ['16572'],\n",
       "             'v4service_port': ['16572'],\n",
       "             'v6address': [None],\n",
       "             'v6data_port': ['16573'],\n",
       "             'v6service_port': ['16573'],\n",
       "             'desc': [None],\n",
       "             'stream_id': 1,\n",
       "             'effective_srate': 0})"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[0][\"info\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "defaultdict(list,\n",
       "            {'name': ['Traumschreiber-EEG'],\n",
       "             'type': ['Markers'],\n",
       "             'channel_count': ['24'],\n",
       "             'channel_format': ['float32'],\n",
       "             'source_id': ['37f209f1-9aab-4a41-b386-56387bc4b937'],\n",
       "             'nominal_srate': ['0.000000000000000'],\n",
       "             'version': ['1.100000000000000'],\n",
       "             'created_at': ['63077.37698702900'],\n",
       "             'uid': ['a7dff592-222c-4aba-93b2-6bf809f139ba'],\n",
       "             'session_id': ['default'],\n",
       "             'hostname': ['localhost'],\n",
       "             'v4address': [None],\n",
       "             'v4data_port': ['16574'],\n",
       "             'v4service_port': ['16574'],\n",
       "             'v6address': [None],\n",
       "             'v6data_port': ['16575'],\n",
       "             'v6service_port': ['16575'],\n",
       "             'desc': [None],\n",
       "             'stream_id': 2,\n",
       "             'effective_srate': 0})"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[1][\"info\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On `footer` there's the timing information of the recorded stream/s (first and last timestamps, sample count, etc.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'info': defaultdict(list,\n",
       "             {'first_timestamp': ['18692.426129456'],\n",
       "              'last_timestamp': ['18713.67744727'],\n",
       "              'sample_count': ['9'],\n",
       "              'clock_offsets': [defaultdict(list,\n",
       "                           {'offset': [defaultdict(list,\n",
       "                                         {'time': ['18693.872479023'],\n",
       "                                          'value': ['7.184999049059115e-06']}),\n",
       "                             defaultdict(list,\n",
       "                                         {'time': ['18698.872561483'],\n",
       "                                          'value': ['-7.589002052554861e-06']}),\n",
       "                             defaultdict(list,\n",
       "                                         {'time': ['18703.872660776'],\n",
       "                                          'value': ['-2.577400118752848e-05']}),\n",
       "                             defaultdict(list,\n",
       "                                         {'time': ['18708.872784644'],\n",
       "                                          'value': ['-3.343599928484764e-05']}),\n",
       "                             defaultdict(list,\n",
       "                                         {'time': ['18713.872949355'],\n",
       "                                          'value': ['-2.73040004685754e-05']}),\n",
       "                             defaultdict(list,\n",
       "                                         {'time': ['18718.8730267395'],\n",
       "                                          'value': ['-1.134349986386951e-05']})]})]})}"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[0][\"footer\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'info': defaultdict(list,\n",
       "             {'first_timestamp': ['63151.218883251'],\n",
       "              'last_timestamp': ['63179.721298032'],\n",
       "              'sample_count': ['7113'],\n",
       "              'clock_offsets': [defaultdict(list,\n",
       "                           {'offset': [defaultdict(list,\n",
       "                                         {'time': ['63156.8671146405'],\n",
       "                                          'value': ['-44462.99462843849']}),\n",
       "                             defaultdict(list,\n",
       "                                         {'time': ['63161.8685086535'],\n",
       "                                          'value': ['-44462.9959094835']}),\n",
       "                             defaultdict(list,\n",
       "                                         {'time': ['63166.867092952'],\n",
       "                                          'value': ['-44462.99436651']}),\n",
       "                             defaultdict(list,\n",
       "                                         {'time': ['63171.86739596151'],\n",
       "                                          'value': ['-44462.99456075051']}),\n",
       "                             defaultdict(list,\n",
       "                                         {'time': ['63176.86724635201'],\n",
       "                                          'value': ['-44462.994291562']}),\n",
       "                             defaultdict(list,\n",
       "                                         {'time': ['63181.86833529599'],\n",
       "                                          'value': ['-44462.99527644899']})]})]})}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[1][\"footer\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On `time_series` is where the information streamed is stored.\n",
    "\n",
    "In this case, for the keyboard triggers these are the UNIX timestamps (index 0 of each sample) plus boolean values (index 1: eyes opened = 1.0, eyes closed = 0.0) sent from the Python script [keyboard-trigger.py](https://github.com/mvidaldp/pylsl-keyboard-trigger/blob/main/keyboard-trigger.py) at each key press event."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1.6027767e+09, 1.0000000e+00],\n",
       "       [1.6027767e+09, 0.0000000e+00],\n",
       "       [1.6027767e+09, 1.0000000e+00],\n",
       "       [1.6027767e+09, 0.0000000e+00],\n",
       "       [1.6027767e+09, 1.0000000e+00],\n",
       "       [1.6027767e+09, 0.0000000e+00],\n",
       "       [1.6027767e+09, 1.0000000e+00],\n",
       "       [1.6027767e+09, 0.0000000e+00],\n",
       "       [1.6027767e+09, 1.0000000e+00],\n",
       "       [1.6027767e+09, 0.0000000e+00]], dtype=float32)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[0][\"time_series\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.10281  , -1.566884 ,  0.578716 , ...,  0.       ,  0.       ,\n",
       "         0.       ],\n",
       "       [ 0.107876 , -1.5701619,  0.577226 , ...,  0.       ,  0.       ,\n",
       "         0.       ],\n",
       "       [ 0.09834  , -1.579102 ,  0.585868 , ...,  0.       ,  0.       ,\n",
       "         0.       ],\n",
       "       ...,\n",
       "       [ 0.103108 , -1.566586 ,  0.59153  , ...,  0.       ,  0.       ,\n",
       "         0.       ],\n",
       "       [ 0.088506 , -1.572248 ,  0.587656 , ...,  0.       ,  0.       ,\n",
       "         0.       ],\n",
       "       [ 0.090592 , -1.57046  ,  0.570968 , ...,  0.       ,  0.       ,\n",
       "         0.       ]], dtype=float32)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[1][\"time_series\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On `time_stamps` is where the synchronized timestamps across all the streams are stored. It's time in seconds also but they are not UNIX epochs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([18692.42612579, 18695.09653543, 18697.36005416, 18699.68524659,\n",
       "       18702.18734364, 18704.60320733, 18706.81185163, 18709.12982383,\n",
       "       18711.39721317, 18713.67742424])"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[0][\"time_stamps\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([18688.22422918, 18688.22649997, 18688.227458  , ...,\n",
       "       18716.71308079, 18716.72445876, 18716.72677289])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[1][\"time_stamps\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To visualize the data first we correct the timestamps so that they start at 0. Then we arrange each EEG channel values into a list to plot them as lines. And finally we plot the red (eyes closed = 0.0) or green (eyes opened = 1.0) vertical lines that represent our triggers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1800x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# calculate time values from 0\n",
    "def correct_timestamps(ts):\n",
    "    corrected = [0]\n",
    "    length = len(ts)\n",
    "    [corrected.append(ts[i + 1] - ts[0]) for i in range(length) if i < length - 1]\n",
    "    return np.array(corrected)\n",
    "\n",
    "\n",
    "# rewrite time starting at 0\n",
    "triggers_time = data[0][\"time_stamps\"]\n",
    "eeg_time = data[1][\"time_stamps\"]\n",
    "\n",
    "t_first = triggers_time[0]\n",
    "e_first = eeg_time[0]\n",
    "time_diff = t_first - e_first\n",
    "\n",
    "triggers_time = correct_timestamps(triggers_time)\n",
    "eeg_time = correct_timestamps(eeg_time)\n",
    "\n",
    "# recorrect with the difference\n",
    "if time_diff < 0:\n",
    "    eeg_time = np.array([i + abs(time_diff) for i in eeg_time])\n",
    "else:\n",
    "    triggers_time = np.array([i + time_diff for i in triggers_time])\n",
    "\n",
    "# prepare dict for the eeg channels\n",
    "eeg = {f\"ch-{ch + 1}\": [] for ch in range(int(data[1][\"info\"][\"channel_count\"][0]))}\n",
    "\n",
    "# each EEG channel as a list\n",
    "for sample in data[1][\"time_series\"]:\n",
    "    for ch, value in enumerate(sample):\n",
    "        eeg[f\"ch-{ch + 1}\"].append(value)\n",
    "\n",
    "# prepare list for the eyes state triggers\n",
    "triggers = []\n",
    "# on index 0 we have the python-generated UNIX epoch\n",
    "# on index 1 we have 0.0 for closed and 1.0 for opened\n",
    "triggers = [sample[1] for sample in data[0][\"time_series\"]]\n",
    "\n",
    "# PLOT\n",
    "%matplotlib inline\n",
    "sns.set_style(\"darkgrid\")  # set seaborn plotting style\n",
    "palette = itertools.cycle(sns.color_palette(palette=\"muted\"))\n",
    "plt.figure(figsize=(25, 10))\n",
    "plt.title(\"EEG with eye-status triggers (opened=green, closed=red)\")\n",
    "plt.xlabel(\"Time (s)\")\n",
    "plt.ylabel(\"Amplitude (µV)\")\n",
    "\n",
    "# each EEG channel values as a line\n",
    "for i, ch in enumerate(eeg):\n",
    "    if i < 6:  # all channels of this recording (6)\n",
    "        sns.lineplot(x=eeg_time, y=eeg[ch], color=next(palette), label=ch)\n",
    "\n",
    "colors = [\"red\", \"green\"]\n",
    "# each trigger as a vertical line\n",
    "for i, trigger in enumerate(triggers_time):\n",
    "    label = \"eyes-closed\" if triggers[i] == 0.0 else \"eyes-open\"\n",
    "    color = colors[0] if triggers[i] == 0.0 else colors[1]\n",
    "    plt.axvline(trigger, label=label, color=color)\n",
    "\n",
    "plt.xticks(np.arange(0, eeg_time[-1], 1))\n",
    "plt.savefig(\"recording_visualization.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For more in-depth examples about how to read LSL recordings from XDF files, plots, and so on, check:\n",
    "- https://github.com/mvidaldp/lsl_latency_analysis/blob/master/analysis.ipynb\n",
    "- https://github.com/mvidaldp/lsl_latency_analysis/blob/master/analysis_2.ipynb\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.8.5 64-bit ('keyboard-trigger': venv)",
   "language": "python",
   "name": "python38564bitkeyboardtriggervenva9ba7dcaae0c4aa5ad87b6aa589ec5c5"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {},
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}