{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Basic single trial fNIRS finger tapping classification  \n",
    "\n",
    "This notebook sketches the analysis of a finger tapping dataset with multiple subjects. A simple Linear Discriminant Analysis (LDA) classifier is trained to distinguish left and right fingertapping."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T16:01:54.125408Z",
     "iopub.status.busy": "2024-09-02T16:01:54.124967Z",
     "iopub.status.idle": "2024-09-02T16:01:55.702088Z",
     "shell.execute_reply": "2024-09-02T16:01:55.701595Z"
    }
   },
   "outputs": [],
   "source": [
    "import cedalion\n",
    "import cedalion.nirs\n",
    "from cedalion.datasets import get_multisubject_fingertapping_snirf_paths\n",
    "import numpy as np\n",
    "import xarray as xr\n",
    "import matplotlib.pyplot as p\n",
    "\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import accuracy_score\n",
    "\n",
    "xr.set_options(display_max_rows=3, display_values_threshold=50)\n",
    "np.set_printoptions(precision=4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Loading raw CW-NIRS data from a SNIRF file\n",
    "\n",
    "This notebook uses a finger-tapping dataset in BIDS layout provided by [Rob Luke](https://github.com/rob-luke/BIDS-NIRS-Tapping). It can can be downloaded via `cedalion.datasets`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Cedalion's `read_snirf` method returns a list of `Recording` objects. These are containers for timeseries and adjunct data objects."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T16:01:55.704931Z",
     "iopub.status.busy": "2024-09-02T16:01:55.704388Z",
     "iopub.status.idle": "2024-09-02T16:01:59.372821Z",
     "shell.execute_reply": "2024-09-02T16:01:59.372327Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading file 'multisubject-fingertapping.zip' from 'https://doc.ml.tu-berlin.de/cedalion/datasets/multisubject-fingertapping.zip' to '/home/runner/.cache/cedalion'.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Unzipping contents of '/home/runner/.cache/cedalion/multisubject-fingertapping.zip' to '/home/runner/.cache/cedalion/multisubject-fingertapping.zip.unzip'\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Recording |  timeseries: ['amp'],  masks: [],  stim: ['1.0', '15.0', '2.0', '3.0'],  aux_ts: [],  aux_obj: []>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Recording |  timeseries: ['amp'],  masks: [],  stim: ['1.0', '15.0', '2.0', '3.0'],  aux_ts: [],  aux_obj: []>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Recording |  timeseries: ['amp'],  masks: [],  stim: ['1.0', '15.0', '2.0', '3.0'],  aux_ts: [],  aux_obj: []>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Recording |  timeseries: ['amp'],  masks: [],  stim: ['1.0', '15.0', '2.0', '3.0'],  aux_ts: [],  aux_obj: []>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Recording |  timeseries: ['amp'],  masks: [],  stim: ['1.0', '15.0', '2.0', '3.0'],  aux_ts: [],  aux_obj: []>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fnames = get_multisubject_fingertapping_snirf_paths()\n",
    "subjects = [f\"sub-{i:02d}\" for i in [1, 2, 3, 4, 5]]\n",
    "\n",
    "# store data of different subjects in a dictionary\n",
    "data = {}\n",
    "for subject, fname in zip(subjects, fnames):\n",
    "    records = cedalion.io.read_snirf(fname)\n",
    "    rec = records[0]\n",
    "    display(rec)\n",
    "\n",
    "    # Cedalion registers an accessor (attribute .cd ) on pandas DataFrames.\n",
    "    # Use this to rename trial_types inplace.\n",
    "    rec.stim.cd.rename_events(\n",
    "        {\"1.0\": \"control\", \"2.0\": \"Tapping/Left\", \"3.0\": \"Tapping/Right\"}\n",
    "    )\n",
    "\n",
    "    dpf = xr.DataArray(\n",
    "        [6, 6],\n",
    "        dims=\"wavelength\",\n",
    "        coords={\"wavelength\": rec[\"amp\"].wavelength},\n",
    "    )\n",
    "\n",
    "    rec[\"od\"] = -np.log(rec[\"amp\"] / rec[\"amp\"].mean(\"time\")),\n",
    "    rec[\"conc\"] = cedalion.nirs.beer_lambert(rec[\"amp\"], rec.geo3d, dpf)\n",
    "\n",
    "    data[subject] = rec"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Illustrate the dataset of one subject"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T16:01:59.374971Z",
     "iopub.status.busy": "2024-09-02T16:01:59.374815Z",
     "iopub.status.idle": "2024-09-02T16:01:59.378259Z",
     "shell.execute_reply": "2024-09-02T16:01:59.377830Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Recording |  timeseries: ['amp', 'od', 'conc'],  masks: [],  stim: ['control', '15.0', 'Tapping/Left', 'Tapping/Right'],  aux_ts: [],  aux_obj: []>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(data[\"sub-01\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Frequency filtering and splitting into epochs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T16:01:59.380160Z",
     "iopub.status.busy": "2024-09-02T16:01:59.379867Z",
     "iopub.status.idle": "2024-09-02T16:01:59.800885Z",
     "shell.execute_reply": "2024-09-02T16:01:59.800401Z"
    }
   },
   "outputs": [],
   "source": [
    "for subject, rec in data.items():\n",
    "    # cedalion registers the accessor .cd on DataArrays\n",
    "    # to provide common functionality like frequency filters...\n",
    "    rec[\"conc_freqfilt\"] = rec[\"conc\"].cd.freq_filter(\n",
    "        fmin=0.02, fmax=0.5, butter_order=4\n",
    "    )\n",
    "\n",
    "    # ... or epoch splitting\n",
    "    rec[\"cfepochs\"] = rec[\"conc_freqfilt\"].cd.to_epochs(\n",
    "        rec.stim,  # stimulus dataframe\n",
    "        [\"Tapping/Left\", \"Tapping/Right\"],  # select events\n",
    "        before=5,  # seconds before stimulus\n",
    "        after=20,  # seconds after stimulus\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot frequency filtered data\n",
    "Illustrate for a single subject and channel the effect of the bandpass filter."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T16:01:59.803343Z",
     "iopub.status.busy": "2024-09-02T16:01:59.803000Z",
     "iopub.status.idle": "2024-09-02T16:02:00.057718Z",
     "shell.execute_reply": "2024-09-02T16:02:00.057209Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rec = data[\"sub-01\"]\n",
    "channel = \"S5D7\"\n",
    "\n",
    "f, ax = p.subplots(2, 1, figsize=(12, 4), sharex=True)\n",
    "ax[0].plot(rec[\"conc\"].time, rec[\"conc\"].sel(channel=channel, chromo=\"HbO\"), \"r-\", label=\"HbO\")\n",
    "ax[0].plot(rec[\"conc\"].time, rec[\"conc\"].sel(channel=channel, chromo=\"HbR\"), \"b-\", label=\"HbR\")\n",
    "ax[1].plot(\n",
    "    rec[\"conc_freqfilt\"].time,\n",
    "    rec[\"conc_freqfilt\"].sel(channel=channel, chromo=\"HbO\"),\n",
    "    \"r-\",\n",
    "    label=\"HbO\",\n",
    ")\n",
    "ax[1].plot(\n",
    "    rec[\"conc_freqfilt\"].time,\n",
    "    rec[\"conc_freqfilt\"].sel(channel=channel, chromo=\"HbR\"),\n",
    "    \"b-\",\n",
    "    label=\"HbR\",\n",
    ")\n",
    "ax[0].set_xlim(1000, 1200)\n",
    "ax[1].set_xlabel(\"time / s\")\n",
    "ax[0].set_ylabel(\"$\\Delta c$ / $\\mu M$\")\n",
    "ax[1].set_ylabel(\"$\\Delta c$ / $\\mu M$\")\n",
    "ax[0].legend(loc=\"upper left\")\n",
    "ax[1].legend(loc=\"upper left\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T16:02:00.059891Z",
     "iopub.status.busy": "2024-09-02T16:02:00.059496Z",
     "iopub.status.idle": "2024-09-02T16:02:00.074240Z",
     "shell.execute_reply": "2024-09-02T16:02:00.073772Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
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       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;concentration&#x27; (epoch: 60, chromo: 2, channel: 28,\n",
       "                                   reltime: 196)&gt; Size: 5MB\n",
       "&lt;Quantity([[[[-1.9479e-02 -1.9950e-02 -2.0945e-02 ... -1.9397e-01 -2.1930e-01\n",
       "    -2.4552e-01]\n",
       "   [-1.0442e-02 -1.1375e-02 -1.2845e-02 ... -2.5376e-01 -2.5998e-01\n",
       "    -2.6454e-01]\n",
       "   [-1.2500e-02 -8.8897e-03 -5.8428e-03 ... -2.1148e-01 -2.2557e-01\n",
       "    -2.3975e-01]\n",
       "   ...\n",
       "   [ 9.5644e-02  1.0075e-01  1.0499e-01 ... -3.2907e-01 -3.4702e-01\n",
       "    -3.6405e-01]\n",
       "   [ 2.0733e-02  2.2404e-02  2.3932e-02 ... -2.9462e-01 -2.9954e-01\n",
       "    -3.0371e-01]\n",
       "   [ 1.4324e-03  2.0415e-03  4.1027e-03 ... -3.0974e-01 -3.2710e-01\n",
       "    -3.4287e-01]]\n",
       "\n",
       "  [[ 1.4641e-02  6.4301e-03 -1.6853e-03 ... -6.5363e-02 -6.2839e-02\n",
       "    -5.7220e-02]\n",
       "   [ 2.0950e-03  5.5313e-03  8.9983e-03 ... -4.8858e-02 -5.4990e-02\n",
       "    -6.0070e-02]\n",
       "   [ 4.5053e-02  4.2005e-02  3.9300e-02 ... -4.3936e-02 -4.3039e-02\n",
       "    -4.0861e-02]\n",
       "...\n",
       "   [ 2.8454e-01  2.9324e-01  3.0016e-01 ...  1.0617e-01  1.1339e-01\n",
       "     1.2119e-01]\n",
       "   [ 3.4306e-01  3.9592e-01  4.4809e-01 ... -1.8578e-01 -1.7872e-01\n",
       "    -1.7142e-01]\n",
       "   [ 6.1801e-01  6.1059e-01  6.0291e-01 ...  1.8868e-01  1.9003e-01\n",
       "     1.9076e-01]]\n",
       "\n",
       "  [[ 6.5167e-02  5.7419e-02  4.9134e-02 ...  3.1521e-02  3.2053e-02\n",
       "     3.1760e-02]\n",
       "   [ 3.6845e-02  3.4700e-02  3.1450e-02 ... -3.0447e-02 -2.7677e-02\n",
       "    -2.3868e-02]\n",
       "   [ 4.8888e-02  3.9980e-02  3.2743e-02 ...  3.0387e-02  3.4824e-02\n",
       "     3.9630e-02]\n",
       "   ...\n",
       "   [ 5.8174e-02  5.3107e-02  4.7739e-02 ... -8.1364e-03 -6.2961e-03\n",
       "    -5.3040e-03]\n",
       "   [ 1.5154e-01  1.6202e-01  1.7299e-01 ...  2.6186e-02  3.2992e-02\n",
       "     3.8859e-02]\n",
       "   [ 1.5938e-01  1.5348e-01  1.4687e-01 ...  3.8222e-02  4.2833e-02\n",
       "     4.6774e-02]]]], &#x27;micromolar&#x27;)&gt;\n",
       "Coordinates: (3/6)\n",
       "  * chromo      (chromo) &lt;U3 24B &#x27;HbO&#x27; &#x27;HbR&#x27;\n",
       "  * channel     (channel) object 224B &#x27;S1D1&#x27; &#x27;S1D2&#x27; &#x27;S1D3&#x27; ... &#x27;S8D8&#x27; &#x27;S8D16&#x27;\n",
       "    ...          ...\n",
       "    trial_type  (epoch) object 480B &#x27;Tapping/Left&#x27; ... &#x27;Tapping/Right&#x27;\n",
       "Dimensions without coordinates: epoch</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'concentration'</div><ul class='xr-dim-list'><li><span>epoch</span>: 60</li><li><span class='xr-has-index'>chromo</span>: 2</li><li><span class='xr-has-index'>channel</span>: 28</li><li><span class='xr-has-index'>reltime</span>: 196</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-81acc1c6-238d-47ab-a946-7dbde8d715c1' class='xr-array-in' type='checkbox' checked><label for='section-81acc1c6-238d-47ab-a946-7dbde8d715c1' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>[µM] -0.01948 -0.01995 -0.02094 -0.02283 ... 0.03822 0.04283 0.04677</span></div><div class='xr-array-data'><table><tbody><tr><th>Magnitude</th><td style='text-align:left;'><pre>[[[[-0.019479227904779864 -0.019949803121088072 -0.020944862365435135    ... -0.19396728521201947 -0.2192953849118962 -0.24552374080934836]   [-0.010442437262024568 -0.01137464781969473 -0.012844651116150595    ... -0.2537623560476126 -0.2599765434840468 -0.26453994089475324]   [-0.012500137899257621 -0.008889665533562616 -0.005842775061250138    ... -0.21147629641187346 -0.22556507891258754 -0.23975459376426295]   ...   [0.09564382471734861 0.10075400311149017 0.10498850078694187 ...    -0.32906737595045693 -0.3470209036232094 -0.36405253490628386]   [0.02073331862467027 0.02240410573924423 0.023932469505019465 ...    -0.2946193204011545 -0.29954485679413323 -0.3037124963432165]   [0.0014324483820571804 0.002041518935667369 0.00410266121592423 ...    -0.309737041480441 -0.32710234801413063 -0.3428657293600665]]  [[0.014641087461924353 0.006430101268136906 -0.0016853371926331961    ... -0.06536342592264233 -0.0628387182743406 -0.05722042972985735]   [0.0020950352040165765 0.005531340663382384 0.008998255771246626 ...    -0.04885801530794028 -0.05498985030552434 -0.060070259522844734]   [0.04505340491280541 0.0420051178910538 0.039300057958497024 ...    -0.043935747548922745 -0.04303946650217799 -0.04086088298135485]   ...   [-0.03338603019317778 -0.04169986646647208 -0.049176851699081515 ...    0.018678277976380837 0.023968129642260756 0.029608835039424415]   [-0.005663990012169901 -0.00791978854019747 -0.008959482030420886    ... 0.0027336554733310044 0.008553829678634117 0.01346927666010259]   [0.03380304565647034 0.026696608366679066 0.019688313523119373 ...    -0.0320929643509965 -0.02872931255613297 -0.026682306573001028]]] [[[-0.39483392190657596 -0.3842727936360807 -0.3709815793928322 ...    0.2886440391066605 0.27685950212555793 0.2644619681329554]   [-0.24809304588999334 -0.2398978975239601 -0.23039909080835702 ...    0.13518596486713513 0.11215473006693981 0.09017530969264903]   [-0.2690311021184204 -0.2550811787455487 -0.2422909965889089 ...    0.12124409544789037 0.10713734166463074 0.0945996360261197]   ...   [-0.3934638612626595 -0.38153411816072214 -0.3702218568053693 ...    0.19415260729896852 0.18136192772899568 0.16763068863822922]   [-0.1631397550651507 -0.15364592274827807 -0.14548119157330952 ...    -0.03494579899698398 -0.04795982450323956 -0.05882060446113206]   [-0.2847404811436402 -0.2756466929551349 -0.26665403987285535 ...    0.22990539120931514 0.20423045915964422 0.17852307819097324]]  [[0.05188850356185281 0.0535169958579957 0.05320372369234118 ...    0.028657149354729836 0.01398492645041843 -0.0008021051409376374]   [0.013998881386903056 0.01694325793664331 0.0187207318226984 ...    -0.016108966159807662 -0.015005266191941771 -0.01393712199470932]   [0.02372213386597678 0.023847321923027284 0.024904724156080194 ...    0.049826822766645115 0.04809730227789012 0.04418343861194539]   ...   [0.11171879127809611 0.1098557474817456 0.1065029853011252 ...    0.0007434045346105915 -0.0028522744593848636 -0.007375504518286632]   [0.060289396798233544 0.0606540815658029 0.060772312836179315 ...    0.00044409966986978604 0.00030604127058869507    -0.0010501482744916107]   [0.007966592259385008 0.014339733703091329 0.018420738953473938 ...    -0.011221899176185351 -0.012884670514984885 -0.014706354020731394]]] [[[-0.031631491545395525 -0.039593985500421994 -0.04904237685141537    ... 0.0794394263285286 0.09102078463761623 0.10148668076847848]   [-0.014915679110159414 -0.027294764386520516 -0.03925988377170477    ... 0.10266070267122657 0.11202871836856267 0.11838386437529469]   [-0.0395712581271572 -0.03370753725262676 -0.027666372596872962 ...    0.04830334731187527 0.055097701373529914 0.06037990716299137]   ...   [-0.04925718059187662 -0.059004561301951315 -0.06903687176339153 ...    -0.019167366079796758 -0.011607233751924875 -0.004298095410669247]   [0.037034366342457326 0.03173919898309721 0.02677779038920991 ...    -0.030481521022230805 -0.03432020762856923 -0.039544459124111135]   [0.019057282382088783 0.008786754713841133 -0.002358949710122467 ...    0.005314473471256728 0.011426491628558882 0.014989602120076481]]  [[0.01185401271048274 0.00776060762630363 0.0053742907023142245 ...    0.003092352943875821 0.01125406801392161 0.019138848448882306]   [0.0061973495347122445 0.004541322900970799 0.0013109873829367383    ... 0.02276570606420884 0.020331216297537966 0.01840668217327564]   [0.028412402046383914 0.01177426389695356 -0.004778113093795094 ...    0.023946406428886777 0.02735541338633181 0.030296799815257403]   ...   [0.010881098460320777 0.017142212379528413 0.02407733956119246 ...    0.023977877175851335 0.02799887269753048 0.03166628694994235]   [0.061971967890095375 0.06544976783780995 0.06799118374122907 ...    0.05968566768315118 0.05202574627991818 0.04366047755063998]   [-0.0015850342637984977 -0.002735243719139741 -0.003366509821012222    ... -0.014750537768514163 -0.011597042009116872    -0.007596640980530284]]] ... [[[0.04786177788103574 0.06603465189939148 0.08183582946295298 ...    -0.20504681959909277 -0.20081032933090107 -0.1954750644954438]   [0.09833367236118383 0.1098925397657606 0.1207062947670258 ...    -0.05971631123913257 -0.06252011194053174 -0.06451078820179847]   [0.015458889999799524 0.029023495268171398 0.04228663375323892 ...    -0.0700682609803819 -0.07405049325322055 -0.07895076172377867]   ...   [0.06887975029793639 0.09060316754716777 0.11249065908006897 ...    -0.1593062565566883 -0.15941535773174442 -0.15923254180199034]   [0.052735016065268536 0.06992834843434978 0.08653870937768215 ...    -0.0703807624465078 -0.07052182217974083 -0.06942070765556686]   [0.3244065360655345 0.3443368506561314 0.36450515785655674 ...    -0.09377309836676458 -0.09713012658113723 -0.09772877913628213]]  [[0.05021607902984154 0.05706637803288904 0.06552325178072894 ...    0.05796317874250878 0.0430107912687764 0.026852348389656985]   [0.011804173147039652 0.012698406146719982 0.014379373769180817 ...    -0.011446231924868079 -0.011753202039135342 -0.011664155082818458]   [0.04171805437027497 0.04743438445848744 0.05361977182112996 ...    -0.0168196394756778 -0.020797293109371298 -0.022289088190054582]   ...   [0.03147137008714056 0.026959374631618016 0.021637055904307576 ...    0.04439302005674897 0.04324630357025236 0.04291664049011243]   [0.002804184722554434 0.00256965393602257 0.002272432812645088 ...    0.021242413968121147 0.020908452995808152 0.019692820643238632]   [0.06295882864641246 0.06919188507471252 0.07461462385423244 ...    -0.009903149363900285 -0.00745141615358568 -0.005742101775306175]]] [[[-0.28644850868331206 -0.2962741621468066 -0.3045414396457737 ...    0.26417279766137514 0.2507552210306122 0.23337292442387733]   [-0.21291417884266226 -0.21448508245805567 -0.21360395634427112 ...    0.19419913124226904 0.17614079212228773 0.15739051312200172]   [-0.21577921700806518 -0.2217985955596637 -0.2272701870670311 ...    0.18016867245931453 0.16408709701892632 0.1461718700333642]   ...   [-0.25380066196103135 -0.26008085625727395 -0.2660075155010426 ...    0.3426031070613399 0.31971522163515687 0.2945143286048745]   [-0.5774359270916989 -0.5865096156979305 -0.5938309891762129 ...    0.28597402031593283 0.26342376047111354 0.23953817629836371]   [-0.2372996729373593 -0.24174604395375077 -0.24684248193904038 ...    0.33613069302001813 0.3084129407063594 0.27992679936742126]]  [[0.0013150860981634496 0.009536906308080115 0.017565838438253288 ...    -0.004058591756449537 -0.011300354894003075 -0.015753229023695463]   [-0.00781616053839272 -0.004960152226364874 -0.001193106558274858    ... -1.3687861639056186e-05 -0.002799490723247427    -0.004870553501538497]   [-0.0077612343772902985 -0.005610246283409824 -0.0025603771486961083    ... 0.01355534440233966 0.012219836447999297 0.012373301668678994]   ...   [0.0004092942202245705 0.0049608813968480756 0.011133169514683908    ... -0.045239161485423895 -0.039225287437315605    -0.03265212464536585]   [-0.05316512792263981 -0.05336862910134466 -0.05442279708416024 ...    -0.11620309867800106 -0.11849277964014576 -0.1209614279149383]   [-0.014790981245242243 -0.015025814831491825 -0.014466245753332519    ... -0.007344595491754983 -0.007701106622587422    -0.008588525222043935]]] [[[0.2393104324261763 0.24275770174425618 0.24714548313922946 ...    0.138026872433699 0.14448847046770688 0.1503254966328949]   [0.10102233631730155 0.1073003755171007 0.11406346375838505 ...    0.1361145580566365 0.13149502324414486 0.12661802051032037]   [0.16072776733646937 0.16570198015301932 0.1695229258562482 ...    0.08956298430555626 0.08843394041568216 0.08558077406772306]   ...   [0.2845449852424982 0.29323853157718843 0.30015605958761726 ...    0.10617299745740776 0.11339114715712684 0.12118967219048027]   [0.34306204845275673 0.3959208850515991 0.4480934064628179 ...    -0.18577662969583286 -0.1787157053714591 -0.17141892166130257]   [0.61800777319673 0.61058713283057 0.6029147958936198 ...    0.18868040418512272 0.1900284025150343 0.19076393652100776]]  [[0.06516686843057705 0.05741888945747505 0.04913424697005694 ...    0.03152127332199576 0.03205329401575985 0.0317599102439223]   [0.036845313612311026 0.03469972860744697 0.03144981582224679 ...    -0.030446833796848254 -0.02767697194220472 -0.023867590249112385]   [0.048887787071113256 0.0399800347549235 0.032742936223389446 ...    0.030386978167461488 0.03482446248002365 0.039630442679694566]   ...   [0.05817427014660733 0.053106992573620226 0.047739115831344915 ...    -0.008136357897478744 -0.006296054250854929 -0.0053039718529942145]   [0.15154120305893376 0.16202284338215098 0.1729860912319436 ...    0.026185957394741416 0.03299190619324434 0.03885868522696512]   [0.15937614966844307 0.15347814059510467 0.14687328060473473 ...    0.03822183109250351 0.04283251117318556 0.04677441847550019]]]]</pre></td></tr><tr><th>Units</th><td style='text-align:left;'>micromolar</td></tr></tbody></table></div></div></li><li class='xr-section-item'><input id='section-f8b1c5cc-20f2-44bb-9dba-e53c852cf55a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f8b1c5cc-20f2-44bb-9dba-e53c852cf55a' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>chromo</span></div><div class='xr-var-dims'>(chromo)</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;HbO&#x27; &#x27;HbR&#x27;</div><input id='attrs-bc36ab44-d5b5-40e2-935e-ab44119eddeb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bc36ab44-d5b5-40e2-935e-ab44119eddeb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a6c9286-e730-420b-bf39-8700b95ff4cc' class='xr-var-data-in' type='checkbox'><label for='data-9a6c9286-e730-420b-bf39-8700b95ff4cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;HbO&#x27;, &#x27;HbR&#x27;], dtype=&#x27;&lt;U3&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;S1D1&#x27; &#x27;S1D2&#x27; ... &#x27;S8D8&#x27; &#x27;S8D16&#x27;</div><input id='attrs-71b5ba05-a59f-4457-9105-0a0df66873fa' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-71b5ba05-a59f-4457-9105-0a0df66873fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1117b51-e472-4e5f-be1b-8affd1e7799a' class='xr-var-data-in' type='checkbox'><label for='data-b1117b51-e472-4e5f-be1b-8affd1e7799a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;S1D1&#x27;, &#x27;S1D2&#x27;, &#x27;S1D3&#x27;, &#x27;S1D9&#x27;, &#x27;S2D1&#x27;, &#x27;S2D3&#x27;, &#x27;S2D4&#x27;, &#x27;S2D10&#x27;, &#x27;S3D2&#x27;,\n",
       "       &#x27;S3D3&#x27;, &#x27;S3D11&#x27;, &#x27;S4D3&#x27;, &#x27;S4D4&#x27;, &#x27;S4D12&#x27;, &#x27;S5D5&#x27;, &#x27;S5D6&#x27;, &#x27;S5D7&#x27;,\n",
       "       &#x27;S5D13&#x27;, &#x27;S6D5&#x27;, &#x27;S6D7&#x27;, &#x27;S6D8&#x27;, &#x27;S6D14&#x27;, &#x27;S7D6&#x27;, &#x27;S7D7&#x27;, &#x27;S7D15&#x27;,\n",
       "       &#x27;S8D7&#x27;, &#x27;S8D8&#x27;, &#x27;S8D16&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;S1&#x27; &#x27;S1&#x27; &#x27;S1&#x27; ... &#x27;S8&#x27; &#x27;S8&#x27; &#x27;S8&#x27;</div><input id='attrs-7168ceed-4e5e-4b85-8d1d-50963c3001f9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7168ceed-4e5e-4b85-8d1d-50963c3001f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6bb1587d-78ea-4b27-a5e3-4f6efaaeb6a8' class='xr-var-data-in' type='checkbox'><label for='data-6bb1587d-78ea-4b27-a5e3-4f6efaaeb6a8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;S1&#x27;, &#x27;S1&#x27;, &#x27;S1&#x27;, &#x27;S1&#x27;, &#x27;S2&#x27;, &#x27;S2&#x27;, &#x27;S2&#x27;, &#x27;S2&#x27;, &#x27;S3&#x27;, &#x27;S3&#x27;, &#x27;S3&#x27;,\n",
       "       &#x27;S4&#x27;, &#x27;S4&#x27;, &#x27;S4&#x27;, &#x27;S5&#x27;, &#x27;S5&#x27;, &#x27;S5&#x27;, &#x27;S5&#x27;, &#x27;S6&#x27;, &#x27;S6&#x27;, &#x27;S6&#x27;, &#x27;S6&#x27;,\n",
       "       &#x27;S7&#x27;, &#x27;S7&#x27;, &#x27;S7&#x27;, &#x27;S8&#x27;, &#x27;S8&#x27;, &#x27;S8&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>detector</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;D1&#x27; &#x27;D2&#x27; &#x27;D3&#x27; ... &#x27;D7&#x27; &#x27;D8&#x27; &#x27;D16&#x27;</div><input id='attrs-20cfea56-d2e4-455d-89c3-23dd412f63f2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-20cfea56-d2e4-455d-89c3-23dd412f63f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a7092709-8d77-45ee-994c-722065c267e5' class='xr-var-data-in' type='checkbox'><label for='data-a7092709-8d77-45ee-994c-722065c267e5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;D1&#x27;, &#x27;D2&#x27;, &#x27;D3&#x27;, &#x27;D9&#x27;, &#x27;D1&#x27;, &#x27;D3&#x27;, &#x27;D4&#x27;, &#x27;D10&#x27;, &#x27;D2&#x27;, &#x27;D3&#x27;, &#x27;D11&#x27;,\n",
       "       &#x27;D3&#x27;, &#x27;D4&#x27;, &#x27;D12&#x27;, &#x27;D5&#x27;, &#x27;D6&#x27;, &#x27;D7&#x27;, &#x27;D13&#x27;, &#x27;D5&#x27;, &#x27;D7&#x27;, &#x27;D8&#x27;,\n",
       "       &#x27;D14&#x27;, &#x27;D6&#x27;, &#x27;D7&#x27;, &#x27;D15&#x27;, &#x27;D7&#x27;, &#x27;D8&#x27;, &#x27;D16&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>reltime</span></div><div class='xr-var-dims'>(reltime)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-4.992 -4.864 ... 19.84 19.97</div><input id='attrs-e4d54a3d-3af6-4e9c-9702-c9ea870eb43b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e4d54a3d-3af6-4e9c-9702-c9ea870eb43b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4fc5d3e-8fa1-4145-b02f-15ecd3897bab' class='xr-var-data-in' type='checkbox'><label for='data-d4fc5d3e-8fa1-4145-b02f-15ecd3897bab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-4.992, -4.864, -4.736, ..., 19.712, 19.84 , 19.968])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>trial_type</span></div><div class='xr-var-dims'>(epoch)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;Tapping/Left&#x27; ... &#x27;Tapping/Right&#x27;</div><input id='attrs-ce9f5c96-fc3c-422d-b609-77cc3190cb38' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ce9f5c96-fc3c-422d-b609-77cc3190cb38' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d616ab4-ad13-40ad-bbac-2252b425561f' class='xr-var-data-in' type='checkbox'><label for='data-6d616ab4-ad13-40ad-bbac-2252b425561f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;],\n",
       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cee9d568-1b42-4251-a04a-0d14045f0af4' class='xr-section-summary-in' type='checkbox'  ><label for='section-cee9d568-1b42-4251-a04a-0d14045f0af4' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>chromo</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-04209cb2-ef96-454c-9b67-dd5808f261f2' class='xr-index-data-in' type='checkbox'/><label for='index-04209cb2-ef96-454c-9b67-dd5808f261f2' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;HbO&#x27;, &#x27;HbR&#x27;], dtype=&#x27;object&#x27;, name=&#x27;chromo&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>channel</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-5272ef27-ba29-418f-b1bf-28b13473c075' class='xr-index-data-in' type='checkbox'/><label for='index-5272ef27-ba29-418f-b1bf-28b13473c075' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;S1D1&#x27;, &#x27;S1D2&#x27;, &#x27;S1D3&#x27;, &#x27;S1D9&#x27;, &#x27;S2D1&#x27;, &#x27;S2D3&#x27;, &#x27;S2D4&#x27;, &#x27;S2D10&#x27;, &#x27;S3D2&#x27;,\n",
       "       &#x27;S3D3&#x27;, &#x27;S3D11&#x27;, &#x27;S4D3&#x27;, &#x27;S4D4&#x27;, &#x27;S4D12&#x27;, &#x27;S5D5&#x27;, &#x27;S5D6&#x27;, &#x27;S5D7&#x27;,\n",
       "       &#x27;S5D13&#x27;, &#x27;S6D5&#x27;, &#x27;S6D7&#x27;, &#x27;S6D8&#x27;, &#x27;S6D14&#x27;, &#x27;S7D6&#x27;, &#x27;S7D7&#x27;, &#x27;S7D15&#x27;,\n",
       "       &#x27;S8D7&#x27;, &#x27;S8D8&#x27;, &#x27;S8D16&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;channel&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>reltime</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3ad57411-5ff0-4c95-be83-9295e6f4857a' class='xr-index-data-in' type='checkbox'/><label for='index-3ad57411-5ff0-4c95-be83-9295e6f4857a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-4.992, -4.864, -4.736, -4.608,  -4.48, -4.352, -4.224, -4.096, -3.968,\n",
       "        -3.84,\n",
       "       ...\n",
       "       18.816, 18.944, 19.072,   19.2, 19.328, 19.456, 19.584, 19.712,  19.84,\n",
       "       19.968],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;reltime&#x27;, length=196))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6392e0dc-d5a8-47f2-9daa-eed70531f158' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6392e0dc-d5a8-47f2-9daa-eed70531f158' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'concentration' (epoch: 60, chromo: 2, channel: 28,\n",
       "                                   reltime: 196)> Size: 5MB\n",
       "<Quantity([[[[-1.9479e-02 -1.9950e-02 -2.0945e-02 ... -1.9397e-01 -2.1930e-01\n",
       "    -2.4552e-01]\n",
       "   [-1.0442e-02 -1.1375e-02 -1.2845e-02 ... -2.5376e-01 -2.5998e-01\n",
       "    -2.6454e-01]\n",
       "   [-1.2500e-02 -8.8897e-03 -5.8428e-03 ... -2.1148e-01 -2.2557e-01\n",
       "    -2.3975e-01]\n",
       "   ...\n",
       "   [ 9.5644e-02  1.0075e-01  1.0499e-01 ... -3.2907e-01 -3.4702e-01\n",
       "    -3.6405e-01]\n",
       "   [ 2.0733e-02  2.2404e-02  2.3932e-02 ... -2.9462e-01 -2.9954e-01\n",
       "    -3.0371e-01]\n",
       "   [ 1.4324e-03  2.0415e-03  4.1027e-03 ... -3.0974e-01 -3.2710e-01\n",
       "    -3.4287e-01]]\n",
       "\n",
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       "\n",
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       "   ...\n",
       "   [ 5.8174e-02  5.3107e-02  4.7739e-02 ... -8.1364e-03 -6.2961e-03\n",
       "    -5.3040e-03]\n",
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       "     3.8859e-02]\n",
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       "     4.6774e-02]]]], 'micromolar')>\n",
       "Coordinates: (3/6)\n",
       "  * chromo      (chromo) <U3 24B 'HbO' 'HbR'\n",
       "  * channel     (channel) object 224B 'S1D1' 'S1D2' 'S1D3' ... 'S8D8' 'S8D16'\n",
       "    ...          ...\n",
       "    trial_type  (epoch) object 480B 'Tapping/Left' ... 'Tapping/Right'\n",
       "Dimensions without coordinates: epoch"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(data[\"sub-01\"][\"cfepochs\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T16:02:00.076172Z",
     "iopub.status.busy": "2024-09-02T16:02:00.075785Z",
     "iopub.status.idle": "2024-09-02T16:02:00.099613Z",
     "shell.execute_reply": "2024-09-02T16:02:00.099146Z"
    },
    "scrolled": false
   },
   "outputs": [
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       "    ...          ...\n",
       "    trial_type  (epoch) object 2kB &#x27;Tapping/Left&#x27; ... &#x27;Tapping/Right&#x27;\n",
       "Dimensions without coordinates: epoch</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'concentration'</div><ul class='xr-dim-list'><li><span>epoch</span>: 300</li><li><span class='xr-has-index'>chromo</span>: 2</li><li><span class='xr-has-index'>channel</span>: 28</li><li><span class='xr-has-index'>reltime</span>: 196</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-3bcabd77-1671-4dc9-a180-cd083f4599f5' class='xr-array-in' type='checkbox' checked><label for='section-3bcabd77-1671-4dc9-a180-cd083f4599f5' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>[µM] -0.01948 -0.01995 -0.02094 ... 0.004134 0.003112 0.0005393</span></div><div class='xr-array-data'><table><tbody><tr><th>Magnitude</th><td style='text-align:left;'><pre>[[[[-0.019479227904779864 -0.019949803121088072 -0.020944862365435135    ... -0.19396728521201947 -0.2192953849118962 -0.24552374080934836]   [-0.010442437262024568 -0.01137464781969473 -0.012844651116150595    ... -0.2537623560476126 -0.2599765434840468 -0.26453994089475324]   [-0.012500137899257621 -0.008889665533562616 -0.005842775061250138    ... -0.21147629641187346 -0.22556507891258754 -0.23975459376426295]   ...   [0.09564382471734861 0.10075400311149017 0.10498850078694187 ...    -0.32906737595045693 -0.3470209036232094 -0.36405253490628386]   [0.02073331862467027 0.02240410573924423 0.023932469505019465 ...    -0.2946193204011545 -0.29954485679413323 -0.3037124963432165]   [0.0014324483820571804 0.002041518935667369 0.00410266121592423 ...    -0.309737041480441 -0.32710234801413063 -0.3428657293600665]]  [[0.014641087461924353 0.006430101268136906 -0.0016853371926331961    ... -0.06536342592264233 -0.0628387182743406 -0.05722042972985735]   [0.0020950352040165765 0.005531340663382384 0.008998255771246626 ...    -0.04885801530794028 -0.05498985030552434 -0.060070259522844734]   [0.04505340491280541 0.0420051178910538 0.039300057958497024 ...    -0.043935747548922745 -0.04303946650217799 -0.04086088298135485]   ...   [-0.03338603019317778 -0.04169986646647208 -0.049176851699081515 ...    0.018678277976380837 0.023968129642260756 0.029608835039424415]   [-0.005663990012169901 -0.00791978854019747 -0.008959482030420886    ... 0.0027336554733310044 0.008553829678634117 0.01346927666010259]   [0.03380304565647034 0.026696608366679066 0.019688313523119373 ...    -0.0320929643509965 -0.02872931255613297 -0.026682306573001028]]] [[[-0.39483392190657596 -0.3842727936360807 -0.3709815793928322 ...    0.2886440391066605 0.27685950212555793 0.2644619681329554]   [-0.24809304588999334 -0.2398978975239601 -0.23039909080835702 ...    0.13518596486713513 0.11215473006693981 0.09017530969264903]   [-0.2690311021184204 -0.2550811787455487 -0.2422909965889089 ...    0.12124409544789037 0.10713734166463074 0.0945996360261197]   ...   [-0.3934638612626595 -0.38153411816072214 -0.3702218568053693 ...    0.19415260729896852 0.18136192772899568 0.16763068863822922]   [-0.1631397550651507 -0.15364592274827807 -0.14548119157330952 ...    -0.03494579899698398 -0.04795982450323956 -0.05882060446113206]   [-0.2847404811436402 -0.2756466929551349 -0.26665403987285535 ...    0.22990539120931514 0.20423045915964422 0.17852307819097324]]  [[0.05188850356185281 0.0535169958579957 0.05320372369234118 ...    0.028657149354729836 0.01398492645041843 -0.0008021051409376374]   [0.013998881386903056 0.01694325793664331 0.0187207318226984 ...    -0.016108966159807662 -0.015005266191941771 -0.01393712199470932]   [0.02372213386597678 0.023847321923027284 0.024904724156080194 ...    0.049826822766645115 0.04809730227789012 0.04418343861194539]   ...   [0.11171879127809611 0.1098557474817456 0.1065029853011252 ...    0.0007434045346105915 -0.0028522744593848636 -0.007375504518286632]   [0.060289396798233544 0.0606540815658029 0.060772312836179315 ...    0.00044409966986978604 0.00030604127058869507    -0.0010501482744916107]   [0.007966592259385008 0.014339733703091329 0.018420738953473938 ...    -0.011221899176185351 -0.012884670514984885 -0.014706354020731394]]] [[[-0.031631491545395525 -0.039593985500421994 -0.04904237685141537    ... 0.0794394263285286 0.09102078463761623 0.10148668076847848]   [-0.014915679110159414 -0.027294764386520516 -0.03925988377170477    ... 0.10266070267122657 0.11202871836856267 0.11838386437529469]   [-0.0395712581271572 -0.03370753725262676 -0.027666372596872962 ...    0.04830334731187527 0.055097701373529914 0.06037990716299137]   ...   [-0.04925718059187662 -0.059004561301951315 -0.06903687176339153 ...    -0.019167366079796758 -0.011607233751924875 -0.004298095410669247]   [0.037034366342457326 0.03173919898309721 0.02677779038920991 ...    -0.030481521022230805 -0.03432020762856923 -0.039544459124111135]   [0.019057282382088783 0.008786754713841133 -0.002358949710122467 ...    0.005314473471256728 0.011426491628558882 0.014989602120076481]]  [[0.01185401271048274 0.00776060762630363 0.0053742907023142245 ...    0.003092352943875821 0.01125406801392161 0.019138848448882306]   [0.0061973495347122445 0.004541322900970799 0.0013109873829367383    ... 0.02276570606420884 0.020331216297537966 0.01840668217327564]   [0.028412402046383914 0.01177426389695356 -0.004778113093795094 ...    0.023946406428886777 0.02735541338633181 0.030296799815257403]   ...   [0.010881098460320777 0.017142212379528413 0.02407733956119246 ...    0.023977877175851335 0.02799887269753048 0.03166628694994235]   [0.061971967890095375 0.06544976783780995 0.06799118374122907 ...    0.05968566768315118 0.05202574627991818 0.04366047755063998]   [-0.0015850342637984977 -0.002735243719139741 -0.003366509821012222    ... -0.014750537768514163 -0.011597042009116872    -0.007596640980530284]]] ... [[[0.08704266523990231 0.09315916777523038 0.10157128797564946 ...    0.01636801025859641 0.022083055177162567 0.02780420982271105]   [-0.13679391337503127 -0.10767247104486644 -0.07060608878602252 ...    -0.0483795134792545 -0.0777946361854697 -0.10802069967747555]   [-0.2812306341575782 -0.27331816281311594 -0.25773252126285184 ...    -0.2847004869293059 -0.2930299521462399 -0.29772618739103407]   ...   [0.08181361380039603 0.0956811333101938 0.11096584055291603 ...    -0.04801234280243881 -0.04038393397371927 -0.031970192997840305]   [0.0382015680194956 0.04268480010008449 0.04896945255986847 ...    -0.15529858908058145 -0.14841315061913105 -0.14293098677341506]   [-0.3079380881598152 -0.2938484291018347 -0.2762768765418241 ...    0.08914607736283713 0.09475908573318646 0.1022110759766003]]  [[-0.048005095396057795 -0.04720317772956417 -0.04922089261187743 ...    0.009887172412000336 0.0063995899035010975 0.002070488382658422]   [0.02114611982907392 0.004803879239509375 -0.01744959873565922 ...    -0.07245300181628656 -0.031554831327187956 0.012474221048494702]   [0.11511338591199649 0.12327007735182337 0.12894862190903827 ...    0.23512502311930628 0.24654293235232932 0.2512333089163796]   ...   [-0.03479051770115989 -0.03636505593511828 -0.037173486890149966 ...    0.08102883866759018 0.08185351600790305 0.08167749502914669]   [0.035479650538076335 0.039820882323768556 0.044065973585059724 ...    0.12789520017352535 0.12294243373720672 0.11783041828639687]   [0.02583491676492331 0.027316461839373467 0.030690891044412506 ...    0.02448030274677874 0.034865402936184765 0.044635371551759215]]] [[[0.23642971906438698 0.25310741123922564 0.26991570810222754 ...    0.16832553148052495 0.17935807868604803 0.18889940864007734]   [0.24680470758135595 0.2423789105316714 0.2360887059104627 ...    0.0742487620653343 0.09250440205931923 0.10660589444853195]   [0.2661728581917138 0.24061121902380436 0.2163396847015893 ...    -0.09790258686411638 -0.0927242770422696 -0.08371097415877762]   ...   [0.2678941095932814 0.2684058907211375 0.2694887173990256 ...    0.1004604883231347 0.09553231914098098 0.09019085222359241]   [0.1919533794028926 0.19593019496575845 0.19994873296844323 ...    -0.05731914455809044 -0.056199371151736316 -0.05440375858556761]   [0.4121378003230346 0.4102486348907042 0.4065349968855463 ...    0.223683064220736 0.22612480145114106 0.22638079507092812]]  [[-0.009082930148617385 -0.029237143151622666 -0.04839452738868469    ... 0.010971810970058466 -0.0018013295159317391    -0.011457439520874677]   [-0.14228422821090442 -0.12573821694806475 -0.1056187881657007 ...    0.09254315555273568 0.06179281845248288 0.035121874070042775]   [-0.09509353296261827 -0.08403913569473591 -0.07939219384194862 ...    0.15374379929635176 0.14888495621681672 0.14137828852503959]   ...   [-0.026756131548354586 -0.02263266362137028 -0.0184052080339331 ...    0.03679406622661587 0.0394972479996131 0.04200469883687388]   [-0.00872284150427255 -0.010809962820268602 -0.013323071880276205    ... 0.0700925874037352 0.07199014655708691 0.07391171748331933]   [-0.04100633743758576 -0.04490531450733956 -0.048035294770634875 ...    -0.02003378904769199 -0.019650695442217814 -0.01695785421756526]]] [[[-0.2519505495195606 -0.25881129901140554 -0.2643782559294214 ...    0.08680360758570331 0.10765111968068512 0.1292226234575672]   [-0.34235540864610253 -0.33236308187859426 -0.3185019027332976 ...    -0.09737684492104468 -0.11181255442987277 -0.11655384042210695]   [-0.3657808413040003 -0.35841290607395165 -0.3521581623545319 ...    -0.14664786099323263 -0.12952631966094147 -0.11392293764123704]   ...   [-0.18641632894660626 -0.18383491371814015 -0.18030676555379482 ...    0.009358214086068517 0.01107627554994392 0.013422716816032076]   [-0.2833532862136716 -0.27513021206499927 -0.26599992030202313 ...    -0.013274470014697615 -0.004611567713028203 0.002369868454679]   [-0.37101837301647583 -0.364172494671039 -0.358202881164293 ...    0.189969061463424 0.1960992961674719 0.20283248068926693]]  [[0.06941299557592809 0.06762761261583145 0.06508561766817544 ...    0.02335376466083253 0.00824931741260251 -0.006509104912517362]   [0.093747645828337 0.07159856738026388 0.048921619653053604 ...    0.00604414115134231 0.03171601516194879 0.048578665477463416]   [0.1325966039459575 0.12931485192519546 0.12488905821359852 ...    0.18629194494491189 0.16656880397054175 0.14594080992531436]   ...   [0.03504573907710292 0.031737623328540444 0.02859403975986763 ...    0.09859694337589996 0.10092682492329506 0.10221808945348111]   [0.08763391810641225 0.08359815773636464 0.08012571185510092 ...    0.11028151304737702 0.10262986512099806 0.09536960561696518]   [-0.03330561277173065 -0.03638165613207743 -0.037579922788424806 ...    0.004133665022607209 0.0031121174666417194 0.0005393399747720337]]]]</pre></td></tr><tr><th>Units</th><td style='text-align:left;'>micromolar</td></tr></tbody></table></div></div></li><li class='xr-section-item'><input id='section-f0b7ae38-db7b-4f4d-b98c-b4bbc117bbc5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f0b7ae38-db7b-4f4d-b98c-b4bbc117bbc5' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>chromo</span></div><div class='xr-var-dims'>(chromo)</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;HbO&#x27; &#x27;HbR&#x27;</div><input id='attrs-6e9b4b4f-cd9e-4e19-8d53-e2d3106fe239' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6e9b4b4f-cd9e-4e19-8d53-e2d3106fe239' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec5447f1-ceaa-4f89-910d-9b615ab64068' class='xr-var-data-in' type='checkbox'><label for='data-ec5447f1-ceaa-4f89-910d-9b615ab64068' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;HbO&#x27;, &#x27;HbR&#x27;], dtype=&#x27;&lt;U3&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;S1D1&#x27; &#x27;S1D2&#x27; ... &#x27;S8D8&#x27; &#x27;S8D16&#x27;</div><input id='attrs-b388e3b0-ee34-465b-8430-4f46da93f8f9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b388e3b0-ee34-465b-8430-4f46da93f8f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e092082-f791-4a73-9adc-1cd9b8295d2f' class='xr-var-data-in' type='checkbox'><label for='data-8e092082-f791-4a73-9adc-1cd9b8295d2f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;S1D1&#x27;, &#x27;S1D2&#x27;, &#x27;S1D3&#x27;, &#x27;S1D9&#x27;, &#x27;S2D1&#x27;, &#x27;S2D3&#x27;, &#x27;S2D4&#x27;, &#x27;S2D10&#x27;, &#x27;S3D2&#x27;,\n",
       "       &#x27;S3D3&#x27;, &#x27;S3D11&#x27;, &#x27;S4D3&#x27;, &#x27;S4D4&#x27;, &#x27;S4D12&#x27;, &#x27;S5D5&#x27;, &#x27;S5D6&#x27;, &#x27;S5D7&#x27;,\n",
       "       &#x27;S5D13&#x27;, &#x27;S6D5&#x27;, &#x27;S6D7&#x27;, &#x27;S6D8&#x27;, &#x27;S6D14&#x27;, &#x27;S7D6&#x27;, &#x27;S7D7&#x27;, &#x27;S7D15&#x27;,\n",
       "       &#x27;S8D7&#x27;, &#x27;S8D8&#x27;, &#x27;S8D16&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;S1&#x27; &#x27;S1&#x27; &#x27;S1&#x27; ... &#x27;S8&#x27; &#x27;S8&#x27; &#x27;S8&#x27;</div><input id='attrs-0ef5bfae-df02-41a0-831e-1306b8075216' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0ef5bfae-df02-41a0-831e-1306b8075216' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3e45958-9455-4e42-9d27-6b60040f0610' class='xr-var-data-in' type='checkbox'><label for='data-a3e45958-9455-4e42-9d27-6b60040f0610' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;S1&#x27;, &#x27;S1&#x27;, &#x27;S1&#x27;, &#x27;S1&#x27;, &#x27;S2&#x27;, &#x27;S2&#x27;, &#x27;S2&#x27;, &#x27;S2&#x27;, &#x27;S3&#x27;, &#x27;S3&#x27;, &#x27;S3&#x27;,\n",
       "       &#x27;S4&#x27;, &#x27;S4&#x27;, &#x27;S4&#x27;, &#x27;S5&#x27;, &#x27;S5&#x27;, &#x27;S5&#x27;, &#x27;S5&#x27;, &#x27;S6&#x27;, &#x27;S6&#x27;, &#x27;S6&#x27;, &#x27;S6&#x27;,\n",
       "       &#x27;S7&#x27;, &#x27;S7&#x27;, &#x27;S7&#x27;, &#x27;S8&#x27;, &#x27;S8&#x27;, &#x27;S8&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>detector</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;D1&#x27; &#x27;D2&#x27; &#x27;D3&#x27; ... &#x27;D7&#x27; &#x27;D8&#x27; &#x27;D16&#x27;</div><input id='attrs-41c94767-ad06-4bed-8e9d-f7937fc45290' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-41c94767-ad06-4bed-8e9d-f7937fc45290' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d14352bc-8c1f-4b9e-848e-de5ff2b473e2' class='xr-var-data-in' type='checkbox'><label for='data-d14352bc-8c1f-4b9e-848e-de5ff2b473e2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;D1&#x27;, &#x27;D2&#x27;, &#x27;D3&#x27;, &#x27;D9&#x27;, &#x27;D1&#x27;, &#x27;D3&#x27;, &#x27;D4&#x27;, &#x27;D10&#x27;, &#x27;D2&#x27;, &#x27;D3&#x27;, &#x27;D11&#x27;,\n",
       "       &#x27;D3&#x27;, &#x27;D4&#x27;, &#x27;D12&#x27;, &#x27;D5&#x27;, &#x27;D6&#x27;, &#x27;D7&#x27;, &#x27;D13&#x27;, &#x27;D5&#x27;, &#x27;D7&#x27;, &#x27;D8&#x27;,\n",
       "       &#x27;D14&#x27;, &#x27;D6&#x27;, &#x27;D7&#x27;, &#x27;D15&#x27;, &#x27;D7&#x27;, &#x27;D8&#x27;, &#x27;D16&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>reltime</span></div><div class='xr-var-dims'>(reltime)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-4.992 -4.864 ... 19.84 19.97</div><input id='attrs-43d977ac-1e49-49d3-89f6-34b5892e0c6a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-43d977ac-1e49-49d3-89f6-34b5892e0c6a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-611c926f-b406-4803-ada2-9562f923301e' class='xr-var-data-in' type='checkbox'><label for='data-611c926f-b406-4803-ada2-9562f923301e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-4.992, -4.864, -4.736, ..., 19.712, 19.84 , 19.968])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>trial_type</span></div><div class='xr-var-dims'>(epoch)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;Tapping/Left&#x27; ... &#x27;Tapping/Right&#x27;</div><input id='attrs-8301ad37-c9f3-46c8-89f9-557375cb84d0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8301ad37-c9f3-46c8-89f9-557375cb84d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-55b625bc-abb7-4fd8-9a8b-addca49c1e0e' class='xr-var-data-in' type='checkbox'><label for='data-55b625bc-abb7-4fd8-9a8b-addca49c1e0e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "...\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;],\n",
       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a65fe2a1-eefa-43d0-a56c-3045b7cda0f6' class='xr-section-summary-in' type='checkbox'  ><label for='section-a65fe2a1-eefa-43d0-a56c-3045b7cda0f6' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>chromo</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-654f9fbe-e901-47d3-b585-cc845ee6b14c' class='xr-index-data-in' type='checkbox'/><label for='index-654f9fbe-e901-47d3-b585-cc845ee6b14c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;HbO&#x27;, &#x27;HbR&#x27;], dtype=&#x27;object&#x27;, name=&#x27;chromo&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>channel</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3e999e94-b35b-404c-aef5-61b72a4c8168' class='xr-index-data-in' type='checkbox'/><label for='index-3e999e94-b35b-404c-aef5-61b72a4c8168' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;S1D1&#x27;, &#x27;S1D2&#x27;, &#x27;S1D3&#x27;, &#x27;S1D9&#x27;, &#x27;S2D1&#x27;, &#x27;S2D3&#x27;, &#x27;S2D4&#x27;, &#x27;S2D10&#x27;, &#x27;S3D2&#x27;,\n",
       "       &#x27;S3D3&#x27;, &#x27;S3D11&#x27;, &#x27;S4D3&#x27;, &#x27;S4D4&#x27;, &#x27;S4D12&#x27;, &#x27;S5D5&#x27;, &#x27;S5D6&#x27;, &#x27;S5D7&#x27;,\n",
       "       &#x27;S5D13&#x27;, &#x27;S6D5&#x27;, &#x27;S6D7&#x27;, &#x27;S6D8&#x27;, &#x27;S6D14&#x27;, &#x27;S7D6&#x27;, &#x27;S7D7&#x27;, &#x27;S7D15&#x27;,\n",
       "       &#x27;S8D7&#x27;, &#x27;S8D8&#x27;, &#x27;S8D16&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;channel&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>reltime</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a3df3ff6-98cf-44b2-b8ad-1d3e3efeef31' class='xr-index-data-in' type='checkbox'/><label for='index-a3df3ff6-98cf-44b2-b8ad-1d3e3efeef31' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-4.992, -4.864, -4.736, -4.608,  -4.48, -4.352, -4.224, -4.096, -3.968,\n",
       "        -3.84,\n",
       "       ...\n",
       "       18.816, 18.944, 19.072,   19.2, 19.328, 19.456, 19.584, 19.712,  19.84,\n",
       "       19.968],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;reltime&#x27;, length=196))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-008ed0c5-d440-416a-a623-9d7a7df95b9b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-008ed0c5-d440-416a-a623-9d7a7df95b9b' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'concentration' (epoch: 300, chromo: 2, channel: 28,\n",
       "                                   reltime: 196)> Size: 26MB\n",
       "<Quantity([[[[-1.9479e-02 -1.9950e-02 -2.0945e-02 ... -1.9397e-01 -2.1930e-01\n",
       "    -2.4552e-01]\n",
       "   [-1.0442e-02 -1.1375e-02 -1.2845e-02 ... -2.5376e-01 -2.5998e-01\n",
       "    -2.6454e-01]\n",
       "   [-1.2500e-02 -8.8897e-03 -5.8428e-03 ... -2.1148e-01 -2.2557e-01\n",
       "    -2.3975e-01]\n",
       "   ...\n",
       "   [ 9.5644e-02  1.0075e-01  1.0499e-01 ... -3.2907e-01 -3.4702e-01\n",
       "    -3.6405e-01]\n",
       "   [ 2.0733e-02  2.2404e-02  2.3932e-02 ... -2.9462e-01 -2.9954e-01\n",
       "    -3.0371e-01]\n",
       "   [ 1.4324e-03  2.0415e-03  4.1027e-03 ... -3.0974e-01 -3.2710e-01\n",
       "    -3.4287e-01]]\n",
       "\n",
       "  [[ 1.4641e-02  6.4301e-03 -1.6853e-03 ... -6.5363e-02 -6.2839e-02\n",
       "    -5.7220e-02]\n",
       "   [ 2.0950e-03  5.5313e-03  8.9983e-03 ... -4.8858e-02 -5.4990e-02\n",
       "    -6.0070e-02]\n",
       "   [ 4.5053e-02  4.2005e-02  3.9300e-02 ... -4.3936e-02 -4.3039e-02\n",
       "    -4.0861e-02]\n",
       "...\n",
       "   [-1.8642e-01 -1.8383e-01 -1.8031e-01 ...  9.3582e-03  1.1076e-02\n",
       "     1.3423e-02]\n",
       "   [-2.8335e-01 -2.7513e-01 -2.6600e-01 ... -1.3274e-02 -4.6116e-03\n",
       "     2.3699e-03]\n",
       "   [-3.7102e-01 -3.6417e-01 -3.5820e-01 ...  1.8997e-01  1.9610e-01\n",
       "     2.0283e-01]]\n",
       "\n",
       "  [[ 6.9413e-02  6.7628e-02  6.5086e-02 ...  2.3354e-02  8.2493e-03\n",
       "    -6.5091e-03]\n",
       "   [ 9.3748e-02  7.1599e-02  4.8922e-02 ...  6.0441e-03  3.1716e-02\n",
       "     4.8579e-02]\n",
       "   [ 1.3260e-01  1.2931e-01  1.2489e-01 ...  1.8629e-01  1.6657e-01\n",
       "     1.4594e-01]\n",
       "   ...\n",
       "   [ 3.5046e-02  3.1738e-02  2.8594e-02 ...  9.8597e-02  1.0093e-01\n",
       "     1.0222e-01]\n",
       "   [ 8.7634e-02  8.3598e-02  8.0126e-02 ...  1.1028e-01  1.0263e-01\n",
       "     9.5370e-02]\n",
       "   [-3.3306e-02 -3.6382e-02 -3.7580e-02 ...  4.1337e-03  3.1121e-03\n",
       "     5.3934e-04]]]], 'micromolar')>\n",
       "Coordinates: (3/6)\n",
       "  * chromo      (chromo) <U3 24B 'HbO' 'HbR'\n",
       "  * channel     (channel) object 224B 'S1D1' 'S1D2' 'S1D3' ... 'S8D8' 'S8D16'\n",
       "    ...          ...\n",
       "    trial_type  (epoch) object 2kB 'Tapping/Left' ... 'Tapping/Right'\n",
       "Dimensions without coordinates: epoch"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_epochs = xr.concat([rec[\"cfepochs\"] for rec in data.values()], dim=\"epoch\")\n",
    "all_epochs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Block Averages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T16:02:00.101612Z",
     "iopub.status.busy": "2024-09-02T16:02:00.101206Z",
     "iopub.status.idle": "2024-09-02T16:02:00.125535Z",
     "shell.execute_reply": "2024-09-02T16:02:00.125017Z"
    }
   },
   "outputs": [],
   "source": [
    "# calculate baseline\n",
    "baseline = all_epochs.sel(reltime=(all_epochs.reltime < 0)).mean(\"reltime\")\n",
    "# subtract baseline\n",
    "all_epochs_blcorrected = all_epochs - baseline\n",
    "\n",
    "# group trials by trial_type. For each group individually average the epoch dimension\n",
    "blockaverage = all_epochs_blcorrected.groupby(\"trial_type\").mean(\"epoch\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plotting averaged epochs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T16:02:00.127904Z",
     "iopub.status.busy": "2024-09-02T16:02:00.127624Z",
     "iopub.status.idle": "2024-09-02T16:02:02.499529Z",
     "shell.execute_reply": "2024-09-02T16:02:02.499041Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1000 with 30 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = p.subplots(5, 6, figsize=(12, 10))\n",
    "ax = ax.flatten()\n",
    "for i_ch, ch in enumerate(blockaverage.channel):\n",
    "    for ls, trial_type in zip([\"-\", \"--\"], blockaverage.trial_type):\n",
    "        ax[i_ch].plot(\n",
    "            blockaverage.reltime,\n",
    "            blockaverage.sel(chromo=\"HbO\", trial_type=trial_type, channel=ch),\n",
    "            \"r\",\n",
    "            lw=2,\n",
    "            ls=ls,\n",
    "        )\n",
    "        ax[i_ch].plot(\n",
    "            blockaverage.reltime,\n",
    "            blockaverage.sel(chromo=\"HbR\", trial_type=trial_type, channel=ch),\n",
    "            \"b\",\n",
    "            lw=2,\n",
    "            ls=ls,\n",
    "        )\n",
    "    ax[i_ch].grid(1)\n",
    "    ax[i_ch].set_title(ch.values)\n",
    "    ax[i_ch].set_ylim(-0.3, 0.6)\n",
    "\n",
    "p.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Training a LDA classifier with Scikit-Learn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T16:02:02.502001Z",
     "iopub.status.busy": "2024-09-02T16:02:02.501846Z",
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     "shell.execute_reply": "2024-09-02T16:02:02.516546Z"
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   "source": [
    "# start with the frequency-filtered, epoched and baseline-corrected concentration data\n",
    "# discard the samples before the stimulus onset\n",
    "epochs = all_epochs_blcorrected.sel(reltime=all_epochs_blcorrected.reltime >=0)\n",
    "# strip units. sklearn would strip them anyway and issue a warning about it.\n",
    "epochs = epochs.pint.dequantify()\n",
    "\n",
    "# need to manually tell xarray to create an index for trial_type\n",
    "epochs = epochs.set_xindex(\"trial_type\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
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    "execution": {
     "iopub.execute_input": "2024-09-02T16:02:02.519188Z",
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     "iopub.status.idle": "2024-09-02T16:02:02.534430Z",
     "shell.execute_reply": "2024-09-02T16:02:02.534018Z"
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;concentration&#x27; (epoch: 300, chromo: 2, channel: 28,\n",
       "                                   reltime: 157)&gt; Size: 21MB\n",
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       "\n",
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       "          -1.2774e-02, -2.7533e-02],\n",
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       "           3.6992e-02,  5.3854e-02],\n",
       "         [-3.5104e-02, -3.3747e-02, -3.9994e-02, ...,  7.3406e-02,\n",
       "           5.3683e-02,  3.3055e-02],\n",
       "         ...,\n",
       "         [ 1.1524e-02,  1.4339e-02,  1.6261e-02, ...,  9.8163e-02,\n",
       "           1.0049e-01,  1.0178e-01],\n",
       "         [-5.6057e-02, -5.8393e-02, -5.9799e-02, ...,  6.0866e-02,\n",
       "           5.3214e-02,  4.5954e-02],\n",
       "         [ 3.0087e-02,  3.2592e-02,  3.6472e-02, ..., -5.2316e-03,\n",
       "          -6.2531e-03, -8.8259e-03]]]])\n",
       "Coordinates: (3/6)\n",
       "  * chromo      (chromo) &lt;U3 24B &#x27;HbO&#x27; &#x27;HbR&#x27;\n",
       "  * channel     (channel) object 224B &#x27;S1D1&#x27; &#x27;S1D2&#x27; &#x27;S1D3&#x27; ... &#x27;S8D8&#x27; &#x27;S8D16&#x27;\n",
       "    ...          ...\n",
       "  * trial_type  (epoch) object 2kB &#x27;Tapping/Left&#x27; ... &#x27;Tapping/Right&#x27;\n",
       "Dimensions without coordinates: epoch\n",
       "Attributes:\n",
       "    units:    micromolar</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'concentration'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>epoch</span>: 300</li><li><span class='xr-has-index'>chromo</span>: 2</li><li><span class='xr-has-index'>channel</span>: 28</li><li><span class='xr-has-index'>reltime</span>: 157</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-4415495f-e8cf-4bed-93b3-ff3574b09e7b' class='xr-array-in' type='checkbox' checked><label for='section-4415495f-e8cf-4bed-93b3-ff3574b09e7b' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>-0.03627 -0.01806 0.002047 0.02364 ... -0.005232 -0.006253 -0.008826</span></div><div class='xr-array-data'><pre>array([[[[-3.6270e-02, -1.8064e-02,  2.0471e-03, ..., -6.8976e-02,\n",
       "          -9.4304e-02, -1.2053e-01],\n",
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       "          -1.4658e-01, -1.6077e-01],\n",
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       "          -2.6958e-01, -2.7375e-01],\n",
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       "          -2.7617e-01, -2.9194e-01]],\n",
       "\n",
       "        [[ 1.5914e-02,  1.3944e-02,  1.0925e-02, ..., -7.7108e-02,\n",
       "          -7.4584e-02, -6.8965e-02],\n",
       "         [-1.2916e-02, -9.4326e-03, -4.7285e-03, ..., -5.5005e-02,\n",
       "          -6.1136e-02, -6.6217e-02],\n",
       "         [-6.1391e-03, -2.1726e-03, -2.9566e-05, ..., -8.1372e-02,\n",
       "          -8.0476e-02, -7.8297e-02],\n",
       "...\n",
       "         [ 1.5353e-01,  1.5630e-01,  1.5688e-01, ...,  6.7293e-02,\n",
       "           6.9011e-02,  7.1357e-02],\n",
       "         [ 2.4956e-01,  2.4903e-01,  2.4447e-01, ...,  7.8465e-02,\n",
       "           8.7128e-02,  9.4109e-02],\n",
       "         [ 4.8391e-01,  4.8248e-01,  4.7416e-01, ...,  3.1090e-01,\n",
       "           3.1703e-01,  3.2376e-01]],\n",
       "\n",
       "        [[-1.5826e-02, -1.2935e-02, -5.2803e-03, ...,  2.3303e-03,\n",
       "          -1.2774e-02, -2.7533e-02],\n",
       "         [-1.3622e-02, -1.8221e-02, -2.3395e-02, ...,  1.1320e-02,\n",
       "           3.6992e-02,  5.3854e-02],\n",
       "         [-3.5104e-02, -3.3747e-02, -3.9994e-02, ...,  7.3406e-02,\n",
       "           5.3683e-02,  3.3055e-02],\n",
       "         ...,\n",
       "         [ 1.1524e-02,  1.4339e-02,  1.6261e-02, ...,  9.8163e-02,\n",
       "           1.0049e-01,  1.0178e-01],\n",
       "         [-5.6057e-02, -5.8393e-02, -5.9799e-02, ...,  6.0866e-02,\n",
       "           5.3214e-02,  4.5954e-02],\n",
       "         [ 3.0087e-02,  3.2592e-02,  3.6472e-02, ..., -5.2316e-03,\n",
       "          -6.2531e-03, -8.8259e-03]]]])</pre></div></div></li><li class='xr-section-item'><input id='section-a9d301cb-517f-4f8e-b0b1-b8b20027bb81' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a9d301cb-517f-4f8e-b0b1-b8b20027bb81' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>chromo</span></div><div class='xr-var-dims'>(chromo)</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;HbO&#x27; &#x27;HbR&#x27;</div><input id='attrs-3d0d9a72-26e0-4f57-a0f6-30de71c96e2b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3d0d9a72-26e0-4f57-a0f6-30de71c96e2b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eba90856-4412-402b-992f-e92aea2dede9' class='xr-var-data-in' type='checkbox'><label for='data-eba90856-4412-402b-992f-e92aea2dede9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;HbO&#x27;, &#x27;HbR&#x27;], dtype=&#x27;&lt;U3&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;S1D1&#x27; &#x27;S1D2&#x27; ... &#x27;S8D8&#x27; &#x27;S8D16&#x27;</div><input id='attrs-856be3e7-a2bf-4313-bcb9-7379066b36e2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-856be3e7-a2bf-4313-bcb9-7379066b36e2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6205be1-8ab7-44f9-84de-57655044f52a' class='xr-var-data-in' type='checkbox'><label for='data-c6205be1-8ab7-44f9-84de-57655044f52a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;S1D1&#x27;, &#x27;S1D2&#x27;, &#x27;S1D3&#x27;, &#x27;S1D9&#x27;, &#x27;S2D1&#x27;, &#x27;S2D3&#x27;, &#x27;S2D4&#x27;, &#x27;S2D10&#x27;, &#x27;S3D2&#x27;,\n",
       "       &#x27;S3D3&#x27;, &#x27;S3D11&#x27;, &#x27;S4D3&#x27;, &#x27;S4D4&#x27;, &#x27;S4D12&#x27;, &#x27;S5D5&#x27;, &#x27;S5D6&#x27;, &#x27;S5D7&#x27;,\n",
       "       &#x27;S5D13&#x27;, &#x27;S6D5&#x27;, &#x27;S6D7&#x27;, &#x27;S6D8&#x27;, &#x27;S6D14&#x27;, &#x27;S7D6&#x27;, &#x27;S7D7&#x27;, &#x27;S7D15&#x27;,\n",
       "       &#x27;S8D7&#x27;, &#x27;S8D8&#x27;, &#x27;S8D16&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;S1&#x27; &#x27;S1&#x27; &#x27;S1&#x27; ... &#x27;S8&#x27; &#x27;S8&#x27; &#x27;S8&#x27;</div><input id='attrs-e8cf3816-52cf-4cb2-b71c-2fa2b7b46013' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e8cf3816-52cf-4cb2-b71c-2fa2b7b46013' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65e3bbc3-0884-4a66-8e07-67a9a6838e0b' class='xr-var-data-in' type='checkbox'><label for='data-65e3bbc3-0884-4a66-8e07-67a9a6838e0b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;S1&#x27;, &#x27;S1&#x27;, &#x27;S1&#x27;, &#x27;S1&#x27;, &#x27;S2&#x27;, &#x27;S2&#x27;, &#x27;S2&#x27;, &#x27;S2&#x27;, &#x27;S3&#x27;, &#x27;S3&#x27;, &#x27;S3&#x27;,\n",
       "       &#x27;S4&#x27;, &#x27;S4&#x27;, &#x27;S4&#x27;, &#x27;S5&#x27;, &#x27;S5&#x27;, &#x27;S5&#x27;, &#x27;S5&#x27;, &#x27;S6&#x27;, &#x27;S6&#x27;, &#x27;S6&#x27;, &#x27;S6&#x27;,\n",
       "       &#x27;S7&#x27;, &#x27;S7&#x27;, &#x27;S7&#x27;, &#x27;S8&#x27;, &#x27;S8&#x27;, &#x27;S8&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>detector</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;D1&#x27; &#x27;D2&#x27; &#x27;D3&#x27; ... &#x27;D7&#x27; &#x27;D8&#x27; &#x27;D16&#x27;</div><input id='attrs-63323208-5517-48ff-86ba-2aa0d496fa71' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-63323208-5517-48ff-86ba-2aa0d496fa71' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-db80ff77-ab69-4210-9b37-18270779d5e6' class='xr-var-data-in' type='checkbox'><label for='data-db80ff77-ab69-4210-9b37-18270779d5e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;D1&#x27;, &#x27;D2&#x27;, &#x27;D3&#x27;, &#x27;D9&#x27;, &#x27;D1&#x27;, &#x27;D3&#x27;, &#x27;D4&#x27;, &#x27;D10&#x27;, &#x27;D2&#x27;, &#x27;D3&#x27;, &#x27;D11&#x27;,\n",
       "       &#x27;D3&#x27;, &#x27;D4&#x27;, &#x27;D12&#x27;, &#x27;D5&#x27;, &#x27;D6&#x27;, &#x27;D7&#x27;, &#x27;D13&#x27;, &#x27;D5&#x27;, &#x27;D7&#x27;, &#x27;D8&#x27;,\n",
       "       &#x27;D14&#x27;, &#x27;D6&#x27;, &#x27;D7&#x27;, &#x27;D15&#x27;, &#x27;D7&#x27;, &#x27;D8&#x27;, &#x27;D16&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>reltime</span></div><div class='xr-var-dims'>(reltime)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.128 0.256 ... 19.84 19.97</div><input id='attrs-9a001893-dbda-497b-8d42-2f4d5d8bdc20' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9a001893-dbda-497b-8d42-2f4d5d8bdc20' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-087b1ce1-8ce8-4151-8505-25ce6d1e81da' class='xr-var-data-in' type='checkbox'><label for='data-087b1ce1-8ce8-4151-8505-25ce6d1e81da' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0.   ,  0.128,  0.256, ..., 19.712, 19.84 , 19.968])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>trial_type</span></div><div class='xr-var-dims'>(epoch)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;Tapping/Left&#x27; ... &#x27;Tapping/Right&#x27;</div><input id='attrs-250d1f69-a059-4234-95c5-74b966835fd8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-250d1f69-a059-4234-95c5-74b966835fd8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-22282b9e-6f51-432d-bed5-5c206f6271ce' class='xr-var-data-in' type='checkbox'><label for='data-22282b9e-6f51-432d-bed5-5c206f6271ce' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, ..., &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-18c96140-300f-4628-ac71-3da445d6469d' class='xr-section-summary-in' type='checkbox'  ><label for='section-18c96140-300f-4628-ac71-3da445d6469d' class='xr-section-summary' >Indexes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>chromo</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d069c8a0-943d-4658-9861-5264c9b3dd3a' class='xr-index-data-in' type='checkbox'/><label for='index-d069c8a0-943d-4658-9861-5264c9b3dd3a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;HbO&#x27;, &#x27;HbR&#x27;], dtype=&#x27;object&#x27;, name=&#x27;chromo&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>channel</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3a9150c7-5c70-4206-9896-2d5cf5de8266' class='xr-index-data-in' type='checkbox'/><label for='index-3a9150c7-5c70-4206-9896-2d5cf5de8266' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;S1D1&#x27;, &#x27;S1D2&#x27;, &#x27;S1D3&#x27;, &#x27;S1D9&#x27;, &#x27;S2D1&#x27;, &#x27;S2D3&#x27;, &#x27;S2D4&#x27;, &#x27;S2D10&#x27;, &#x27;S3D2&#x27;,\n",
       "       &#x27;S3D3&#x27;, &#x27;S3D11&#x27;, &#x27;S4D3&#x27;, &#x27;S4D4&#x27;, &#x27;S4D12&#x27;, &#x27;S5D5&#x27;, &#x27;S5D6&#x27;, &#x27;S5D7&#x27;,\n",
       "       &#x27;S5D13&#x27;, &#x27;S6D5&#x27;, &#x27;S6D7&#x27;, &#x27;S6D8&#x27;, &#x27;S6D14&#x27;, &#x27;S7D6&#x27;, &#x27;S7D7&#x27;, &#x27;S7D15&#x27;,\n",
       "       &#x27;S8D7&#x27;, &#x27;S8D8&#x27;, &#x27;S8D16&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;channel&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>reltime</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7e95f8fa-4fa0-46d1-8907-603d2e4e6012' class='xr-index-data-in' type='checkbox'/><label for='index-7e95f8fa-4fa0-46d1-8907-603d2e4e6012' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,  0.128,  0.256,  0.384,  0.512,   0.64,  0.768,  0.896,  1.024,\n",
       "        1.152,\n",
       "       ...\n",
       "       18.816, 18.944, 19.072,   19.2, 19.328, 19.456, 19.584, 19.712,  19.84,\n",
       "       19.968],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;reltime&#x27;, length=157))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>trial_type</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ce9adf87-593f-45f5-b3c4-1b846f435f79' class='xr-index-data-in' type='checkbox'/><label for='index-ce9adf87-593f-45f5-b3c4-1b846f435f79' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       ...\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;trial_type&#x27;, length=300))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9bf839da-0fc2-4f76-a106-564ead953611' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9bf839da-0fc2-4f76-a106-564ead953611' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>micromolar</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'concentration' (epoch: 300, chromo: 2, channel: 28,\n",
       "                                   reltime: 157)> Size: 21MB\n",
       "array([[[[-3.6270e-02, -1.8064e-02,  2.0471e-03, ..., -6.8976e-02,\n",
       "          -9.4304e-02, -1.2053e-01],\n",
       "         [ 4.6475e-03,  1.1837e-02,  1.9097e-02, ..., -1.5186e-01,\n",
       "          -1.5808e-01, -1.6264e-01],\n",
       "         [ 2.4496e-03,  1.2294e-02,  2.3849e-02, ..., -1.3250e-01,\n",
       "          -1.4658e-01, -1.6077e-01],\n",
       "         ...,\n",
       "         [-4.3450e-02, -3.0909e-02, -1.6201e-02, ..., -3.4983e-01,\n",
       "          -3.6779e-01, -3.8482e-01],\n",
       "         [ 2.2952e-02,  3.4524e-02,  4.6622e-02, ..., -2.6465e-01,\n",
       "          -2.6958e-01, -2.7375e-01],\n",
       "         [-4.2557e-03,  1.3953e-02,  3.3226e-02, ..., -2.5881e-01,\n",
       "          -2.7617e-01, -2.9194e-01]],\n",
       "\n",
       "        [[ 1.5914e-02,  1.3944e-02,  1.0925e-02, ..., -7.7108e-02,\n",
       "          -7.4584e-02, -6.8965e-02],\n",
       "         [-1.2916e-02, -9.4326e-03, -4.7285e-03, ..., -5.5005e-02,\n",
       "          -6.1136e-02, -6.6217e-02],\n",
       "         [-6.1391e-03, -2.1726e-03, -2.9566e-05, ..., -8.1372e-02,\n",
       "          -8.0476e-02, -7.8297e-02],\n",
       "...\n",
       "         [ 1.5353e-01,  1.5630e-01,  1.5688e-01, ...,  6.7293e-02,\n",
       "           6.9011e-02,  7.1357e-02],\n",
       "         [ 2.4956e-01,  2.4903e-01,  2.4447e-01, ...,  7.8465e-02,\n",
       "           8.7128e-02,  9.4109e-02],\n",
       "         [ 4.8391e-01,  4.8248e-01,  4.7416e-01, ...,  3.1090e-01,\n",
       "           3.1703e-01,  3.2376e-01]],\n",
       "\n",
       "        [[-1.5826e-02, -1.2935e-02, -5.2803e-03, ...,  2.3303e-03,\n",
       "          -1.2774e-02, -2.7533e-02],\n",
       "         [-1.3622e-02, -1.8221e-02, -2.3395e-02, ...,  1.1320e-02,\n",
       "           3.6992e-02,  5.3854e-02],\n",
       "         [-3.5104e-02, -3.3747e-02, -3.9994e-02, ...,  7.3406e-02,\n",
       "           5.3683e-02,  3.3055e-02],\n",
       "         ...,\n",
       "         [ 1.1524e-02,  1.4339e-02,  1.6261e-02, ...,  9.8163e-02,\n",
       "           1.0049e-01,  1.0178e-01],\n",
       "         [-5.6057e-02, -5.8393e-02, -5.9799e-02, ...,  6.0866e-02,\n",
       "           5.3214e-02,  4.5954e-02],\n",
       "         [ 3.0087e-02,  3.2592e-02,  3.6472e-02, ..., -5.2316e-03,\n",
       "          -6.2531e-03, -8.8259e-03]]]])\n",
       "Coordinates: (3/6)\n",
       "  * chromo      (chromo) <U3 24B 'HbO' 'HbR'\n",
       "  * channel     (channel) object 224B 'S1D1' 'S1D2' 'S1D3' ... 'S8D8' 'S8D16'\n",
       "    ...          ...\n",
       "  * trial_type  (epoch) object 2kB 'Tapping/Left' ... 'Tapping/Right'\n",
       "Dimensions without coordinates: epoch\n",
       "Attributes:\n",
       "    units:    micromolar"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(epochs)"
   ]
  },
  {
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     "shell.execute_reply": "2024-09-02T16:02:02.551279Z"
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;concentration&#x27; (epoch: 300, features: 8792)&gt; Size: 21MB\n",
       "array([[-0.0363, -0.0181,  0.002 , ..., -0.0126, -0.0093, -0.0072],\n",
       "       [ 0.109 ,  0.0983,  0.0847, ..., -0.0343, -0.036 , -0.0378],\n",
       "       [-0.0203, -0.0267, -0.0325, ..., -0.0187, -0.0155, -0.0115],\n",
       "       ...,\n",
       "       [ 0.029 ,  0.0078, -0.0164, ..., -0.0117, -0.0013,  0.0085],\n",
       "       [-0.2281, -0.2284, -0.2273, ...,  0.0104,  0.0108,  0.0135],\n",
       "       [ 0.2505,  0.2608,  0.2643, ..., -0.0052, -0.0063, -0.0088]])\n",
       "Coordinates: (3/7)\n",
       "    source      (features) object 70kB &#x27;S1&#x27; &#x27;S1&#x27; &#x27;S1&#x27; &#x27;S1&#x27; ... &#x27;S8&#x27; &#x27;S8&#x27; &#x27;S8&#x27;\n",
       "    detector    (features) object 70kB &#x27;D1&#x27; &#x27;D1&#x27; &#x27;D1&#x27; &#x27;D1&#x27; ... &#x27;D16&#x27; &#x27;D16&#x27; &#x27;D16&#x27;\n",
       "    ...          ...\n",
       "  * reltime     (features) float64 70kB 0.0 0.128 0.256 ... 19.71 19.84 19.97\n",
       "Dimensions without coordinates: epoch\n",
       "Attributes:\n",
       "    units:    micromolar</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'concentration'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>epoch</span>: 300</li><li><span class='xr-has-index'>features</span>: 8792</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-e8b4a21d-ac39-464c-872c-cbd79ffdb6d0' class='xr-array-in' type='checkbox' checked><label for='section-e8b4a21d-ac39-464c-872c-cbd79ffdb6d0' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>-0.03627 -0.01806 0.002047 0.02364 ... -0.005232 -0.006253 -0.008826</span></div><div class='xr-array-data'><pre>array([[-0.0363, -0.0181,  0.002 , ..., -0.0126, -0.0093, -0.0072],\n",
       "       [ 0.109 ,  0.0983,  0.0847, ..., -0.0343, -0.036 , -0.0378],\n",
       "       [-0.0203, -0.0267, -0.0325, ..., -0.0187, -0.0155, -0.0115],\n",
       "       ...,\n",
       "       [ 0.029 ,  0.0078, -0.0164, ..., -0.0117, -0.0013,  0.0085],\n",
       "       [-0.2281, -0.2284, -0.2273, ...,  0.0104,  0.0108,  0.0135],\n",
       "       [ 0.2505,  0.2608,  0.2643, ..., -0.0052, -0.0063, -0.0088]])</pre></div></div></li><li class='xr-section-item'><input id='section-0b4a431e-c848-4a4e-aea3-4459353ec782' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0b4a431e-c848-4a4e-aea3-4459353ec782' class='xr-section-summary' >Coordinates: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>source</span></div><div class='xr-var-dims'>(features)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;S1&#x27; &#x27;S1&#x27; &#x27;S1&#x27; ... &#x27;S8&#x27; &#x27;S8&#x27; &#x27;S8&#x27;</div><input id='attrs-13ae96b0-7644-4201-aa61-5a5d923b8d33' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-13ae96b0-7644-4201-aa61-5a5d923b8d33' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec3d732f-8214-4e08-a96e-807907599e7b' class='xr-var-data-in' type='checkbox'><label for='data-ec3d732f-8214-4e08-a96e-807907599e7b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;S1&#x27;, &#x27;S1&#x27;, &#x27;S1&#x27;, ..., &#x27;S8&#x27;, &#x27;S8&#x27;, &#x27;S8&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>detector</span></div><div class='xr-var-dims'>(features)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;D1&#x27; &#x27;D1&#x27; &#x27;D1&#x27; ... &#x27;D16&#x27; &#x27;D16&#x27;</div><input id='attrs-bf1dde22-1ec9-43c9-9fd7-92aad086f5d8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bf1dde22-1ec9-43c9-9fd7-92aad086f5d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f7d2d3bb-6e93-41b9-a4d5-8c5d1264a79f' class='xr-var-data-in' type='checkbox'><label for='data-f7d2d3bb-6e93-41b9-a4d5-8c5d1264a79f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;D1&#x27;, &#x27;D1&#x27;, &#x27;D1&#x27;, ..., &#x27;D16&#x27;, &#x27;D16&#x27;, &#x27;D16&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>trial_type</span></div><div class='xr-var-dims'>(epoch)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;Tapping/Left&#x27; ... &#x27;Tapping/Right&#x27;</div><input id='attrs-129ead5f-c9ce-4085-afb6-8ece5b3d5cdc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-129ead5f-c9ce-4085-afb6-8ece5b3d5cdc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3b75c194-131e-435a-91ca-7bbb66bbb067' class='xr-var-data-in' type='checkbox'><label for='data-3b75c194-131e-435a-91ca-7bbb66bbb067' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, ..., &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>features</span></div><div class='xr-var-dims'>(features)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>MultiIndex</div><input id='attrs-915610f6-aaab-4068-8973-c4618ce50b79' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-915610f6-aaab-4068-8973-c4618ce50b79' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1f7f1b08-e246-4e04-938e-dd13737d5cc3' class='xr-var-data-in' type='checkbox'><label for='data-1f7f1b08-e246-4e04-938e-dd13737d5cc3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([(&#x27;HbO&#x27;, &#x27;S1D1&#x27;, 0.0), (&#x27;HbO&#x27;, &#x27;S1D1&#x27;, 0.128), (&#x27;HbO&#x27;, &#x27;S1D1&#x27;, 0.256),\n",
       "       ..., (&#x27;HbR&#x27;, &#x27;S8D16&#x27;, 19.712), (&#x27;HbR&#x27;, &#x27;S8D16&#x27;, 19.84),\n",
       "       (&#x27;HbR&#x27;, &#x27;S8D16&#x27;, 19.968)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>chromo</span></div><div class='xr-var-dims'>(features)</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;HbO&#x27; &#x27;HbO&#x27; &#x27;HbO&#x27; ... &#x27;HbR&#x27; &#x27;HbR&#x27;</div><input id='attrs-54306867-5298-463d-a0ee-d193176d1e2d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-54306867-5298-463d-a0ee-d193176d1e2d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b6fac765-51ce-4e39-9fdb-6ff04095d120' class='xr-var-data-in' type='checkbox'><label for='data-b6fac765-51ce-4e39-9fdb-6ff04095d120' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;HbO&#x27;, &#x27;HbO&#x27;, &#x27;HbO&#x27;, ..., &#x27;HbR&#x27;, &#x27;HbR&#x27;, &#x27;HbR&#x27;], dtype=&#x27;&lt;U3&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(features)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;S1D1&#x27; &#x27;S1D1&#x27; ... &#x27;S8D16&#x27; &#x27;S8D16&#x27;</div><input id='attrs-d7e5358d-32aa-4051-9a6c-0bc4cf50a99d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d7e5358d-32aa-4051-9a6c-0bc4cf50a99d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6e1ef67-99af-4bef-80fe-0f073d697b70' class='xr-var-data-in' type='checkbox'><label for='data-c6e1ef67-99af-4bef-80fe-0f073d697b70' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;S1D1&#x27;, &#x27;S1D1&#x27;, &#x27;S1D1&#x27;, ..., &#x27;S8D16&#x27;, &#x27;S8D16&#x27;, &#x27;S8D16&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>reltime</span></div><div class='xr-var-dims'>(features)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.128 0.256 ... 19.84 19.97</div><input id='attrs-77df83f9-3b36-479e-a38a-0a2a2830cfc9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-77df83f9-3b36-479e-a38a-0a2a2830cfc9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4379bbbb-7678-4471-b869-34a7f1ae67ac' class='xr-var-data-in' type='checkbox'><label for='data-4379bbbb-7678-4471-b869-34a7f1ae67ac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0.   ,  0.128,  0.256, ..., 19.712, 19.84 , 19.968])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2ca82f9c-eb8d-4ba1-b65f-afe4eafe9715' class='xr-section-summary-in' type='checkbox'  ><label for='section-2ca82f9c-eb8d-4ba1-b65f-afe4eafe9715' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>trial_type</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d7b24c55-c58a-4716-911f-238c65aa8990' class='xr-index-data-in' type='checkbox'/><label for='index-d7b24c55-c58a-4716-911f-238c65aa8990' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       ...\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;trial_type&#x27;, length=300))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>features<br>chromo<br>channel<br>reltime</div></div><div class='xr-index-preview'>PandasMultiIndex</div><div></div><input id='index-f0aee7af-3bfc-4409-8de0-60d20681b4ad' class='xr-index-data-in' type='checkbox'/><label for='index-f0aee7af-3bfc-4409-8de0-60d20681b4ad' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(MultiIndex([(&#x27;HbO&#x27;,  &#x27;S1D1&#x27;,    0.0),\n",
       "            (&#x27;HbO&#x27;,  &#x27;S1D1&#x27;,  0.128),\n",
       "            (&#x27;HbO&#x27;,  &#x27;S1D1&#x27;,  0.256),\n",
       "            (&#x27;HbO&#x27;,  &#x27;S1D1&#x27;,  0.384),\n",
       "            (&#x27;HbO&#x27;,  &#x27;S1D1&#x27;,  0.512),\n",
       "            (&#x27;HbO&#x27;,  &#x27;S1D1&#x27;,   0.64),\n",
       "            (&#x27;HbO&#x27;,  &#x27;S1D1&#x27;,  0.768),\n",
       "            (&#x27;HbO&#x27;,  &#x27;S1D1&#x27;,  0.896),\n",
       "            (&#x27;HbO&#x27;,  &#x27;S1D1&#x27;,  1.024),\n",
       "            (&#x27;HbO&#x27;,  &#x27;S1D1&#x27;,  1.152),\n",
       "            ...\n",
       "            (&#x27;HbR&#x27;, &#x27;S8D16&#x27;, 18.816),\n",
       "            (&#x27;HbR&#x27;, &#x27;S8D16&#x27;, 18.944),\n",
       "            (&#x27;HbR&#x27;, &#x27;S8D16&#x27;, 19.072),\n",
       "            (&#x27;HbR&#x27;, &#x27;S8D16&#x27;,   19.2),\n",
       "            (&#x27;HbR&#x27;, &#x27;S8D16&#x27;, 19.328),\n",
       "            (&#x27;HbR&#x27;, &#x27;S8D16&#x27;, 19.456),\n",
       "            (&#x27;HbR&#x27;, &#x27;S8D16&#x27;, 19.584),\n",
       "            (&#x27;HbR&#x27;, &#x27;S8D16&#x27;, 19.712),\n",
       "            (&#x27;HbR&#x27;, &#x27;S8D16&#x27;,  19.84),\n",
       "            (&#x27;HbR&#x27;, &#x27;S8D16&#x27;, 19.968)],\n",
       "           name=&#x27;features&#x27;, length=8792))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-572e1aff-6f9f-4c83-bdc6-128f0ae1b60c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-572e1aff-6f9f-4c83-bdc6-128f0ae1b60c' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>micromolar</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'concentration' (epoch: 300, features: 8792)> Size: 21MB\n",
       "array([[-0.0363, -0.0181,  0.002 , ..., -0.0126, -0.0093, -0.0072],\n",
       "       [ 0.109 ,  0.0983,  0.0847, ..., -0.0343, -0.036 , -0.0378],\n",
       "       [-0.0203, -0.0267, -0.0325, ..., -0.0187, -0.0155, -0.0115],\n",
       "       ...,\n",
       "       [ 0.029 ,  0.0078, -0.0164, ..., -0.0117, -0.0013,  0.0085],\n",
       "       [-0.2281, -0.2284, -0.2273, ...,  0.0104,  0.0108,  0.0135],\n",
       "       [ 0.2505,  0.2608,  0.2643, ..., -0.0052, -0.0063, -0.0088]])\n",
       "Coordinates: (3/7)\n",
       "    source      (features) object 70kB 'S1' 'S1' 'S1' 'S1' ... 'S8' 'S8' 'S8'\n",
       "    detector    (features) object 70kB 'D1' 'D1' 'D1' 'D1' ... 'D16' 'D16' 'D16'\n",
       "    ...          ...\n",
       "  * reltime     (features) float64 70kB 0.0 0.128 0.256 ... 19.71 19.84 19.97\n",
       "Dimensions without coordinates: epoch\n",
       "Attributes:\n",
       "    units:    micromolar"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "X = epochs.stack(features=[\"chromo\", \"channel\", \"reltime\"])\n",
    "display(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T16:02:02.553684Z",
     "iopub.status.busy": "2024-09-02T16:02:02.553350Z",
     "iopub.status.idle": "2024-09-02T16:02:02.560015Z",
     "shell.execute_reply": "2024-09-02T16:02:02.559593Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;trial_type&#x27; (epoch: 300)&gt; Size: 2kB\n",
       "array([0, 0, 0, 0, 0, 0, 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, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 0, 0, 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, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1])\n",
       "Coordinates:\n",
       "  * trial_type  (epoch) object 2kB &#x27;Tapping/Left&#x27; ... &#x27;Tapping/Right&#x27;\n",
       "Dimensions without coordinates: epoch</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'trial_type'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>epoch</span>: 300</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-ec49591b-cb39-4a1a-905a-9f238d708ddd' class='xr-array-in' type='checkbox' checked><label for='section-ec49591b-cb39-4a1a-905a-9f238d708ddd' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ... 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1</span></div><div class='xr-array-data'><pre>array([0, 0, 0, 0, 0, 0, 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, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 0, 0, 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, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1])</pre></div></div></li><li class='xr-section-item'><input id='section-f3fc5c62-00b4-4828-9bcd-fb3971307d1b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f3fc5c62-00b4-4828-9bcd-fb3971307d1b' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>trial_type</span></div><div class='xr-var-dims'>(epoch)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;Tapping/Left&#x27; ... &#x27;Tapping/Right&#x27;</div><input id='attrs-dad38b67-7680-473a-8a16-599b9c172a3d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dad38b67-7680-473a-8a16-599b9c172a3d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-54d45bcf-8fbb-475c-b81c-4eb42f2df74a' class='xr-var-data-in' type='checkbox'><label for='data-54d45bcf-8fbb-475c-b81c-4eb42f2df74a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, ..., &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e8d5358c-ec29-445d-b324-ea5a0724ac4d' class='xr-section-summary-in' type='checkbox'  ><label for='section-e8d5358c-ec29-445d-b324-ea5a0724ac4d' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>trial_type</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-012b0d09-8fff-4355-84dc-39eff75a4b15' class='xr-index-data-in' type='checkbox'/><label for='index-012b0d09-8fff-4355-84dc-39eff75a4b15' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       &#x27;Tapping/Left&#x27;, &#x27;Tapping/Left&#x27;,\n",
       "       ...\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;,\n",
       "       &#x27;Tapping/Right&#x27;, &#x27;Tapping/Right&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;trial_type&#x27;, length=300))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-06ddb9ed-6411-42a4-8d7d-cae89c4e107f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-06ddb9ed-6411-42a4-8d7d-cae89c4e107f' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'trial_type' (epoch: 300)> Size: 2kB\n",
       "array([0, 0, 0, 0, 0, 0, 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, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 0, 0, 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, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1])\n",
       "Coordinates:\n",
       "  * trial_type  (epoch) object 2kB 'Tapping/Left' ... 'Tapping/Right'\n",
       "Dimensions without coordinates: epoch"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y = xr.apply_ufunc(LabelEncoder().fit_transform, X.trial_type)\n",
    "display(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T16:02:02.561632Z",
     "iopub.status.busy": "2024-09-02T16:02:02.561485Z",
     "iopub.status.idle": "2024-09-02T16:02:02.748225Z",
     "shell.execute_reply": "2024-09-02T16:02:02.747755Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.8888888888888888\n"
     ]
    }
   ],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, stratify=y)\n",
    "classifier = LinearDiscriminantAnalysis(n_components=1).fit(X_train, y_train)\n",
    "y_pred = classifier.predict(X_test)\n",
    "print(f\"Accuracy: {accuracy_score(y_test, y_pred)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T16:02:02.751434Z",
     "iopub.status.busy": "2024-09-02T16:02:02.750626Z",
     "iopub.status.idle": "2024-09-02T16:02:03.002826Z",
     "shell.execute_reply": "2024-09-02T16:02:03.002309Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = p.subplots(1, 2, figsize=(12, 3))\n",
    "for trial_type, c in zip([\"Tapping/Left\", \"Tapping/Right\"], [\"r\", \"g\"]):\n",
    "    kw = dict(alpha=0.5, fc=c, label=trial_type)\n",
    "    ax[0].hist(classifier.decision_function(X_train.sel(trial_type=trial_type)), **kw)\n",
    "    ax[1].hist(classifier.decision_function(X_test.sel(trial_type=trial_type)), **kw)\n",
    "\n",
    "ax[0].set_xlabel(\"LDA score\")\n",
    "ax[1].set_xlabel(\"LDA score\")\n",
    "ax[0].set_title(\"train\")\n",
    "ax[1].set_title(\"test\")\n",
    "ax[0].legend(ncol=1, loc=\"upper left\")\n",
    "ax[1].legend(ncol=1, loc=\"upper left\");"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}