notebooks/test_pybids_braindecode_BIDSDataset.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Tests showing BIDSDataset not able to handle example EEGLAB dataset and slower than pybids"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from braindecode.datasets import BIDSDataset\n",
    "from bids import BIDSLayout"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 2 μs, sys: 1e+03 ns, total: 3 μs\n",
      "Wall time: 4.05 μs\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unknown types found, setting as type EEG:\n",
      "ekg: ['EEG063', 'EEG064']\n",
      "heog: ['EEG061']\n",
      "veog: ['EEG062']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n"
     ]
    },
    {
     "ename": "ValueError",
     "evalue": "The file extension must be .set or .fdt, not ",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[2], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m get_ipython()\u001b[38;5;241m.\u001b[39mrun_line_magic(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtime\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m----> 2\u001b[0m bids \u001b[38;5;241m=\u001b[39m \u001b[43mBIDSDataset\u001b[49m\u001b[43m(\u001b[49m\u001b[43mroot\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m/mnt/nemar/openneuro/ds003645\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpreload\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m<string>:20\u001b[0m, in \u001b[0;36m__init__\u001b[0;34m(self, root, subjects, sessions, tasks, acquisitions, runs, processings, recordings, spaces, splits, descriptions, suffixes, extensions, datatypes, check, preload, n_jobs)\u001b[0m\n",
      "File \u001b[0;32m~/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:183\u001b[0m, in \u001b[0;36mBIDSDataset.__post_init__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    176\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_filter_out_epochs:\n\u001b[1;32m    177\u001b[0m     bids_paths \u001b[38;5;241m=\u001b[39m [\n\u001b[1;32m    178\u001b[0m         bids_path\n\u001b[1;32m    179\u001b[0m         \u001b[38;5;28;01mfor\u001b[39;00m bids_path \u001b[38;5;129;01min\u001b[39;00m bids_paths\n\u001b[1;32m    180\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (bids_path\u001b[38;5;241m.\u001b[39msuffix \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mepo\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m bids_path\u001b[38;5;241m.\u001b[39mextension \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.fif\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m    181\u001b[0m     ]\n\u001b[0;32m--> 183\u001b[0m all_base_ds \u001b[38;5;241m=\u001b[39m \u001b[43mParallel\u001b[49m\u001b[43m(\u001b[49m\u001b[43mn_jobs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mn_jobs\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    184\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdelayed\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_dataset\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbids_path\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mbids_path\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mbids_paths\u001b[49m\n\u001b[1;32m    185\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    186\u001b[0m \u001b[38;5;28msuper\u001b[39m()\u001b[38;5;241m.\u001b[39m\u001b[38;5;21m__init__\u001b[39m(all_base_ds)\n",
      "File \u001b[0;32m~/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/joblib/parallel.py:1918\u001b[0m, in \u001b[0;36mParallel.__call__\u001b[0;34m(self, iterable)\u001b[0m\n\u001b[1;32m   1916\u001b[0m     output \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_get_sequential_output(iterable)\n\u001b[1;32m   1917\u001b[0m     \u001b[38;5;28mnext\u001b[39m(output)\n\u001b[0;32m-> 1918\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m output \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mreturn_generator \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;43mlist\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43moutput\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1920\u001b[0m \u001b[38;5;66;03m# Let's create an ID that uniquely identifies the current call. If the\u001b[39;00m\n\u001b[1;32m   1921\u001b[0m \u001b[38;5;66;03m# call is interrupted early and that the same instance is immediately\u001b[39;00m\n\u001b[1;32m   1922\u001b[0m \u001b[38;5;66;03m# re-used, this id will be used to prevent workers that were\u001b[39;00m\n\u001b[1;32m   1923\u001b[0m \u001b[38;5;66;03m# concurrently finalizing a task from the previous call to run the\u001b[39;00m\n\u001b[1;32m   1924\u001b[0m \u001b[38;5;66;03m# callback.\u001b[39;00m\n\u001b[1;32m   1925\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_lock:\n",
      "File \u001b[0;32m~/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/joblib/parallel.py:1847\u001b[0m, in \u001b[0;36mParallel._get_sequential_output\u001b[0;34m(self, iterable)\u001b[0m\n\u001b[1;32m   1845\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mn_dispatched_batches \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m   1846\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mn_dispatched_tasks \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[0;32m-> 1847\u001b[0m res \u001b[38;5;241m=\u001b[39m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1848\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mn_completed_tasks \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m   1849\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mprint_progress()\n",
      "File \u001b[0;32m~/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190\u001b[0m, in \u001b[0;36mBIDSDataset._get_dataset\u001b[0;34m(self, bids_path)\u001b[0m\n\u001b[1;32m    188\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21m_get_dataset\u001b[39m(\u001b[38;5;28mself\u001b[39m, bids_path: mne_bids\u001b[38;5;241m.\u001b[39mBIDSPath) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m BaseDataset:\n\u001b[1;32m    189\u001b[0m     description \u001b[38;5;241m=\u001b[39m _descriptiion_from_bids_path(bids_path)\n\u001b[0;32m--> 190\u001b[0m     raw \u001b[38;5;241m=\u001b[39m \u001b[43mmne_bids\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread_raw_bids\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbids_path\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mverbose\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[1;32m    191\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpreload:\n\u001b[1;32m    192\u001b[0m         raw\u001b[38;5;241m.\u001b[39mload_data()\n",
      "File \u001b[0;32m<decorator-gen-392>:10\u001b[0m, in \u001b[0;36mread_raw_bids\u001b[0;34m(bids_path, extra_params, verbose)\u001b[0m\n",
      "File \u001b[0;32m~/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/mne_bids/read.py:905\u001b[0m, in \u001b[0;36mread_raw_bids\u001b[0;34m(bids_path, extra_params, verbose)\u001b[0m\n\u001b[1;32m    903\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m raw_path\u001b[38;5;241m.\u001b[39msuffix \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.fif\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mallow_maxshield\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m extra_params:\n\u001b[1;32m    904\u001b[0m     extra_params[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mallow_maxshield\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[0;32m--> 905\u001b[0m raw \u001b[38;5;241m=\u001b[39m \u001b[43m_read_raw\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    906\u001b[0m \u001b[43m    \u001b[49m\u001b[43mraw_path\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    907\u001b[0m \u001b[43m    \u001b[49m\u001b[43melectrode\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m    908\u001b[0m \u001b[43m    \u001b[49m\u001b[43mhsp\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m    909\u001b[0m \u001b[43m    \u001b[49m\u001b[43mhpi\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m    910\u001b[0m \u001b[43m    \u001b[49m\u001b[43mconfig_path\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconfig_path\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    911\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mextra_params\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    912\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    914\u001b[0m \u001b[38;5;66;03m# Try to find an associated events.tsv to get information about the\u001b[39;00m\n\u001b[1;32m    915\u001b[0m \u001b[38;5;66;03m# events in the recorded data\u001b[39;00m\n\u001b[1;32m    916\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m (\n\u001b[1;32m    917\u001b[0m     bids_path\u001b[38;5;241m.\u001b[39msubject \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124memptyroom\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m bids_path\u001b[38;5;241m.\u001b[39mtask \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnoise\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    918\u001b[0m ) \u001b[38;5;129;01mor\u001b[39;00m bids_path\u001b[38;5;241m.\u001b[39mtask\u001b[38;5;241m.\u001b[39mstartswith(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrest\u001b[39m\u001b[38;5;124m\"\u001b[39m):\n",
      "File \u001b[0;32m~/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/mne_bids/read.py:72\u001b[0m, in \u001b[0;36m_read_raw\u001b[0;34m(raw_path, electrode, hsp, hpi, allow_maxshield, config_path, **kwargs)\u001b[0m\n\u001b[1;32m     70\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m ext \u001b[38;5;129;01min\u001b[39;00m [\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.ds\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.vhdr\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.set\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.edf\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.bdf\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.EDF\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.snirf\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.cdt\u001b[39m\u001b[38;5;124m\"\u001b[39m]:\n\u001b[1;32m     71\u001b[0m     raw_path \u001b[38;5;241m=\u001b[39m Path(raw_path)\n\u001b[0;32m---> 72\u001b[0m     raw \u001b[38;5;241m=\u001b[39m \u001b[43mreader\u001b[49m\u001b[43m[\u001b[49m\u001b[43mext\u001b[49m\u001b[43m]\u001b[49m\u001b[43m(\u001b[49m\u001b[43mraw_path\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     74\u001b[0m \u001b[38;5;66;03m# MEF and NWB are allowed, but not yet implemented\u001b[39;00m\n\u001b[1;32m     75\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m ext \u001b[38;5;129;01min\u001b[39;00m [\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.mef\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.nwb\u001b[39m\u001b[38;5;124m\"\u001b[39m]:\n",
      "File \u001b[0;32m~/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/mne/io/eeglab/eeglab.py:327\u001b[0m, in \u001b[0;36mread_raw_eeglab\u001b[0;34m(input_fname, eog, preload, uint16_codec, montage_units, verbose)\u001b[0m\n\u001b[1;32m    285\u001b[0m \u001b[38;5;129m@fill_doc\u001b[39m\n\u001b[1;32m    286\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mread_raw_eeglab\u001b[39m(\n\u001b[1;32m    287\u001b[0m     input_fname,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    292\u001b[0m     verbose\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m    293\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mRawEEGLAB\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m    294\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124;03m\"\"\"Read an EEGLAB .set file.\u001b[39;00m\n\u001b[1;32m    295\u001b[0m \n\u001b[1;32m    296\u001b[0m \u001b[38;5;124;03m    Parameters\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    325\u001b[0m \u001b[38;5;124;03m    .. versionadded:: 0.11.0\u001b[39;00m\n\u001b[1;32m    326\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[0;32m--> 327\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mRawEEGLAB\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    328\u001b[0m \u001b[43m        \u001b[49m\u001b[43minput_fname\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43minput_fname\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    329\u001b[0m \u001b[43m        \u001b[49m\u001b[43mpreload\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpreload\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    330\u001b[0m \u001b[43m        \u001b[49m\u001b[43meog\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43meog\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    331\u001b[0m \u001b[43m        \u001b[49m\u001b[43muint16_codec\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43muint16_codec\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    332\u001b[0m \u001b[43m        \u001b[49m\u001b[43mmontage_units\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmontage_units\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    333\u001b[0m \u001b[43m        \u001b[49m\u001b[43mverbose\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mverbose\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    334\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m<decorator-gen-279>:12\u001b[0m, in \u001b[0;36m__init__\u001b[0;34m(self, input_fname, eog, preload, uint16_codec, montage_units, verbose)\u001b[0m\n",
      "File \u001b[0;32m~/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/mne/io/eeglab/eeglab.py:460\u001b[0m, in \u001b[0;36mRawEEGLAB.__init__\u001b[0;34m(self, input_fname, eog, preload, uint16_codec, montage_units, verbose)\u001b[0m\n\u001b[1;32m    458\u001b[0m \u001b[38;5;66;03m# read the data\u001b[39;00m\n\u001b[1;32m    459\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(eeg\u001b[38;5;241m.\u001b[39mdata, \u001b[38;5;28mstr\u001b[39m):\n\u001b[0;32m--> 460\u001b[0m     data_fname \u001b[38;5;241m=\u001b[39m \u001b[43m_check_eeglab_fname\u001b[49m\u001b[43m(\u001b[49m\u001b[43minput_fname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43meeg\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdata\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    461\u001b[0m     logger\u001b[38;5;241m.\u001b[39minfo(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mReading \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mdata_fname\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m    463\u001b[0m     \u001b[38;5;28msuper\u001b[39m()\u001b[38;5;241m.\u001b[39m\u001b[38;5;21m__init__\u001b[39m(\n\u001b[1;32m    464\u001b[0m         info,\n\u001b[1;32m    465\u001b[0m         preload,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    469\u001b[0m         verbose\u001b[38;5;241m=\u001b[39mverbose,\n\u001b[1;32m    470\u001b[0m     )\n",
      "File \u001b[0;32m~/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/mne/io/eeglab/eeglab.py:53\u001b[0m, in \u001b[0;36m_check_eeglab_fname\u001b[0;34m(fname, dataname)\u001b[0m\n\u001b[1;32m     48\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mNotImplementedError\u001b[39;00m(\n\u001b[1;32m     49\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mOld data format .dat detected. Please update your EEGLAB \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m     50\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mversion and resave the data in .fdt format\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m     51\u001b[0m     )\n\u001b[1;32m     52\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m fmt \u001b[38;5;241m!=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.set\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m fmt \u001b[38;5;241m!=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.fdt\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[0;32m---> 53\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mThe file extension must be .set or .fdt, not \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfmt\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m     54\u001b[0m basedir \u001b[38;5;241m=\u001b[39m op\u001b[38;5;241m.\u001b[39mdirname(fname)\n\u001b[1;32m     55\u001b[0m data_fname \u001b[38;5;241m=\u001b[39m op\u001b[38;5;241m.\u001b[39mjoin(basedir, dataname)\n",
      "\u001b[0;31mValueError\u001b[0m: The file extension must be .set or .fdt, not "
     ]
    }
   ],
   "source": [
    "bids = BIDSDataset(root='/mnt/nemar/openneuro/ds003645', preload=False)\n",
    "# Can't import regular EEGLAB dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unknown types found, setting as type EEG:\n",
      "ekg: ['EEG063', 'EEG064']\n",
      "heog: ['EEG061']\n",
      "veog: ['EEG062']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: The data contains 'boundary' events, indicating data discontinuities. Be cautious of filtering and epoching around these events.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: There are channels without locations (n/a) that are not marked as bad: ['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Not setting positions of 4 ecg/eog channels found in montage:\n",
      "['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "Consider setting the channel types to be of EEG/sEEG/ECoG/DBS/fNIRS using inst.set_channel_types before calling inst.set_montage, or omit these channels when creating your montage.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unable to map the following column(s) to to MNE:\n",
      "gender: M\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unknown types found, setting as type EEG:\n",
      "ekg: ['EEG063', 'EEG064']\n",
      "heog: ['EEG061']\n",
      "veog: ['EEG062']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: The data contains 'boundary' events, indicating data discontinuities. Be cautious of filtering and epoching around these events.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: There are channels without locations (n/a) that are not marked as bad: ['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Not setting positions of 4 ecg/eog channels found in montage:\n",
      "['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "Consider setting the channel types to be of EEG/sEEG/ECoG/DBS/fNIRS using inst.set_channel_types before calling inst.set_montage, or omit these channels when creating your montage.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unable to map the following column(s) to to MNE:\n",
      "gender: M\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unknown types found, setting as type EEG:\n",
      "ekg: ['EEG063', 'EEG064']\n",
      "heog: ['EEG061']\n",
      "veog: ['EEG062']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: The data contains 'boundary' events, indicating data discontinuities. Be cautious of filtering and epoching around these events.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: There are channels without locations (n/a) that are not marked as bad: ['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Not setting positions of 4 ecg/eog channels found in montage:\n",
      "['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "Consider setting the channel types to be of EEG/sEEG/ECoG/DBS/fNIRS using inst.set_channel_types before calling inst.set_montage, or omit these channels when creating your montage.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unable to map the following column(s) to to MNE:\n",
      "gender: n/a\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unknown types found, setting as type EEG:\n",
      "ekg: ['EEG063', 'EEG064']\n",
      "heog: ['EEG061']\n",
      "veog: ['EEG062']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: The data contains 'boundary' events, indicating data discontinuities. Be cautious of filtering and epoching around these events.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: There are channels without locations (n/a) that are not marked as bad: ['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Not setting positions of 4 ecg/eog channels found in montage:\n",
      "['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "Consider setting the channel types to be of EEG/sEEG/ECoG/DBS/fNIRS using inst.set_channel_types before calling inst.set_montage, or omit these channels when creating your montage.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unable to map the following column(s) to to MNE:\n",
      "gender: M\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unknown types found, setting as type EEG:\n",
      "ekg: ['EEG063', 'EEG064']\n",
      "heog: ['EEG061']\n",
      "veog: ['EEG062']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: The data contains 'boundary' events, indicating data discontinuities. Be cautious of filtering and epoching around these events.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: There are channels without locations (n/a) that are not marked as bad: ['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Not setting positions of 4 ecg/eog channels found in montage:\n",
      "['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "Consider setting the channel types to be of EEG/sEEG/ECoG/DBS/fNIRS using inst.set_channel_types before calling inst.set_montage, or omit these channels when creating your montage.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unable to map the following column(s) to to MNE:\n",
      "gender: n/a\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unknown types found, setting as type EEG:\n",
      "ekg: ['EEG063', 'EEG064']\n",
      "heog: ['EEG061']\n",
      "veog: ['EEG062']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Estimated head radius (11.1 cm) is above the 99th percentile for adult head size. Check if the montage_units argument is correct (the default is \"mm\", but your channel positions may be in different units).\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: The data contains 'boundary' events, indicating data discontinuities. Be cautious of filtering and epoching around these events.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: There are channels without locations (n/a) that are not marked as bad: ['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Not setting positions of 4 ecg/eog channels found in montage:\n",
      "['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "Consider setting the channel types to be of EEG/sEEG/ECoG/DBS/fNIRS using inst.set_channel_types before calling inst.set_montage, or omit these channels when creating your montage.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unable to map the following column(s) to to MNE:\n",
      "gender: n/a\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unknown types found, setting as type EEG:\n",
      "ekg: ['EEG063', 'EEG064']\n",
      "heog: ['EEG061']\n",
      "veog: ['EEG062']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: The data contains 'boundary' events, indicating data discontinuities. Be cautious of filtering and epoching around these events.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: There are channels without locations (n/a) that are not marked as bad: ['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Not setting positions of 4 ecg/eog channels found in montage:\n",
      "['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "Consider setting the channel types to be of EEG/sEEG/ECoG/DBS/fNIRS using inst.set_channel_types before calling inst.set_montage, or omit these channels when creating your montage.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unable to map the following column(s) to to MNE:\n",
      "gender: F\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unknown types found, setting as type EEG:\n",
      "ekg: ['EEG063', 'EEG064']\n",
      "heog: ['EEG061']\n",
      "veog: ['EEG062']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: The data contains 'boundary' events, indicating data discontinuities. Be cautious of filtering and epoching around these events.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: There are channels without locations (n/a) that are not marked as bad: ['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Not setting positions of 4 ecg/eog channels found in montage:\n",
      "['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "Consider setting the channel types to be of EEG/sEEG/ECoG/DBS/fNIRS using inst.set_channel_types before calling inst.set_montage, or omit these channels when creating your montage.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unable to map the following column(s) to to MNE:\n",
      "gender: M\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unknown types found, setting as type EEG:\n",
      "ekg: ['EEG063', 'EEG064']\n",
      "heog: ['EEG061']\n",
      "veog: ['EEG062']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Estimated head radius (11.0 cm) is above the 99th percentile for adult head size. Check if the montage_units argument is correct (the default is \"mm\", but your channel positions may be in different units).\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: The data contains 'boundary' events, indicating data discontinuities. Be cautious of filtering and epoching around these events.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: There are channels without locations (n/a) that are not marked as bad: ['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Not setting positions of 4 ecg/eog channels found in montage:\n",
      "['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "Consider setting the channel types to be of EEG/sEEG/ECoG/DBS/fNIRS using inst.set_channel_types before calling inst.set_montage, or omit these channels when creating your montage.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unable to map the following column(s) to to MNE:\n",
      "gender: F\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unknown types found, setting as type EEG:\n",
      "ekg: ['EEG063', 'EEG064']\n",
      "heog: ['EEG061']\n",
      "veog: ['EEG062']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Estimated head radius (11.0 cm) is above the 99th percentile for adult head size. Check if the montage_units argument is correct (the default is \"mm\", but your channel positions may be in different units).\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: The data contains 'boundary' events, indicating data discontinuities. Be cautious of filtering and epoching around these events.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: There are channels without locations (n/a) that are not marked as bad: ['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Not setting positions of 4 ecg/eog channels found in montage:\n",
      "['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "Consider setting the channel types to be of EEG/sEEG/ECoG/DBS/fNIRS using inst.set_channel_types before calling inst.set_montage, or omit these channels when creating your montage.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unable to map the following column(s) to to MNE:\n",
      "gender: M\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unknown types found, setting as type EEG:\n",
      "ekg: ['EEG063', 'EEG064']\n",
      "heog: ['EEG061']\n",
      "veog: ['EEG062']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: The data contains 'boundary' events, indicating data discontinuities. Be cautious of filtering and epoching around these events.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: There are channels without locations (n/a) that are not marked as bad: ['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Not setting positions of 4 ecg/eog channels found in montage:\n",
      "['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "Consider setting the channel types to be of EEG/sEEG/ECoG/DBS/fNIRS using inst.set_channel_types before calling inst.set_montage, or omit these channels when creating your montage.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unable to map the following column(s) to to MNE:\n",
      "gender: M\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unknown types found, setting as type EEG:\n",
      "ekg: ['EEG063', 'EEG064']\n",
      "heog: ['EEG061']\n",
      "veog: ['EEG062']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: The data contains 'boundary' events, indicating data discontinuities. Be cautious of filtering and epoching around these events.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: There are channels without locations (n/a) that are not marked as bad: ['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Not setting positions of 4 ecg/eog channels found in montage:\n",
      "['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "Consider setting the channel types to be of EEG/sEEG/ECoG/DBS/fNIRS using inst.set_channel_types before calling inst.set_montage, or omit these channels when creating your montage.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unable to map the following column(s) to to MNE:\n",
      "gender: n/a\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unknown types found, setting as type EEG:\n",
      "ekg: ['EEG063', 'EEG064']\n",
      "heog: ['EEG061']\n",
      "veog: ['EEG062']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: The data contains 'boundary' events, indicating data discontinuities. Be cautious of filtering and epoching around these events.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: There are channels without locations (n/a) that are not marked as bad: ['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Not setting positions of 4 ecg/eog channels found in montage:\n",
      "['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "Consider setting the channel types to be of EEG/sEEG/ECoG/DBS/fNIRS using inst.set_channel_types before calling inst.set_montage, or omit these channels when creating your montage.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unable to map the following column(s) to to MNE:\n",
      "gender: F\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unknown types found, setting as type EEG:\n",
      "ekg: ['EEG063', 'EEG064']\n",
      "heog: ['EEG061']\n",
      "veog: ['EEG062']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: The data contains 'boundary' events, indicating data discontinuities. Be cautious of filtering and epoching around these events.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: There are channels without locations (n/a) that are not marked as bad: ['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Not setting positions of 4 ecg/eog channels found in montage:\n",
      "['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "Consider setting the channel types to be of EEG/sEEG/ECoG/DBS/fNIRS using inst.set_channel_types before calling inst.set_montage, or omit these channels when creating your montage.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unable to map the following column(s) to to MNE:\n",
      "gender: M\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unknown types found, setting as type EEG:\n",
      "ekg: ['EEG063', 'EEG064']\n",
      "heog: ['EEG061']\n",
      "veog: ['EEG062']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: The data contains 'boundary' events, indicating data discontinuities. Be cautious of filtering and epoching around these events.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: There are channels without locations (n/a) that are not marked as bad: ['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Not setting positions of 4 ecg/eog channels found in montage:\n",
      "['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "Consider setting the channel types to be of EEG/sEEG/ECoG/DBS/fNIRS using inst.set_channel_types before calling inst.set_montage, or omit these channels when creating your montage.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unable to map the following column(s) to to MNE:\n",
      "gender: F\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unknown types found, setting as type EEG:\n",
      "ekg: ['EEG063', 'EEG064']\n",
      "heog: ['EEG061']\n",
      "veog: ['EEG062']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: The data contains 'boundary' events, indicating data discontinuities. Be cautious of filtering and epoching around these events.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: There are channels without locations (n/a) that are not marked as bad: ['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Not setting positions of 4 ecg/eog channels found in montage:\n",
      "['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "Consider setting the channel types to be of EEG/sEEG/ECoG/DBS/fNIRS using inst.set_channel_types before calling inst.set_montage, or omit these channels when creating your montage.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unable to map the following column(s) to to MNE:\n",
      "gender: F\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unknown types found, setting as type EEG:\n",
      "ekg: ['EEG063', 'EEG064']\n",
      "heog: ['EEG061']\n",
      "veog: ['EEG062']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: The data contains 'boundary' events, indicating data discontinuities. Be cautious of filtering and epoching around these events.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: There are channels without locations (n/a) that are not marked as bad: ['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Not setting positions of 4 ecg/eog channels found in montage:\n",
      "['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "Consider setting the channel types to be of EEG/sEEG/ECoG/DBS/fNIRS using inst.set_channel_types before calling inst.set_montage, or omit these channels when creating your montage.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unable to map the following column(s) to to MNE:\n",
      "gender: F\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unknown types found, setting as type EEG:\n",
      "ekg: ['EEG063', 'EEG064']\n",
      "heog: ['EEG061']\n",
      "veog: ['EEG062']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Estimated head radius (11.8 cm) is above the 99th percentile for adult head size. Check if the montage_units argument is correct (the default is \"mm\", but your channel positions may be in different units).\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 10.8 s, sys: 11.4 s, total: 22.2 s\n",
      "Wall time: 1min 29s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: The data contains 'boundary' events, indicating data discontinuities. Be cautious of filtering and epoching around these events.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: There are channels without locations (n/a) that are not marked as bad: ['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Not setting positions of 4 ecg/eog channels found in montage:\n",
      "['EEG061', 'EEG062', 'EEG063', 'EEG064']\n",
      "Consider setting the channel types to be of EEG/sEEG/ECoG/DBS/fNIRS using inst.set_channel_types before calling inst.set_montage, or omit these channels when creating your montage.\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n",
      "/home/dung/Documents/EEG-Dash-Data/.venv/lib/python3.10/site-packages/braindecode/datasets/bids.py:190: RuntimeWarning: Unable to map the following column(s) to to MNE:\n",
      "gender: n/a\n",
      "  raw = mne_bids.read_raw_bids(bids_path, verbose=False)\n"
     ]
    }
   ],
   "source": [
    "%time bids = BIDSDataset(root='/mnt/nemar/openneuro/ds002718', preload=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1.37 s, sys: 33.1 ms, total: 1.41 s\n",
      "Wall time: 1.56 s\n",
      "CPU times: user 310 ms, sys: 12.8 ms, total: 323 ms\n",
      "Wall time: 703 ms\n"
     ]
    }
   ],
   "source": [
    "%time layout = BIDSLayout('/mnt/nemar/openneuro/ds003645')\n",
    "%time layout = BIDSLayout('/mnt/nemar/openneuro/ds002718') "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Tests showing pybids utilities as well as limitations\n",
    "\n",
    "- Recording files can be retrieved fast\n",
    "- File path can be mapped to BIDS file using simple additional parsing\n",
    "- Needed info such as duration and channel count can be retrieved easily\n",
    "- Not all file level metadata files can be retrieved even though they exist\n",
    "- Top level json associated with a file can't be retrieved from file level"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['/mnt/nemar/openneuro/ds002718/sub-002/eeg/sub-002_task-FaceRecognition_eeg.set', '/mnt/nemar/openneuro/ds002718/sub-003/eeg/sub-003_task-FaceRecognition_eeg.set', '/mnt/nemar/openneuro/ds002718/sub-004/eeg/sub-004_task-FaceRecognition_eeg.set', '/mnt/nemar/openneuro/ds002718/sub-005/eeg/sub-005_task-FaceRecognition_eeg.set', '/mnt/nemar/openneuro/ds002718/sub-006/eeg/sub-006_task-FaceRecognition_eeg.set', '/mnt/nemar/openneuro/ds002718/sub-007/eeg/sub-007_task-FaceRecognition_eeg.set', '/mnt/nemar/openneuro/ds002718/sub-008/eeg/sub-008_task-FaceRecognition_eeg.set', '/mnt/nemar/openneuro/ds002718/sub-009/eeg/sub-009_task-FaceRecognition_eeg.set', '/mnt/nemar/openneuro/ds002718/sub-010/eeg/sub-010_task-FaceRecognition_eeg.set', '/mnt/nemar/openneuro/ds002718/sub-011/eeg/sub-011_task-FaceRecognition_eeg.set', '/mnt/nemar/openneuro/ds002718/sub-012/eeg/sub-012_task-FaceRecognition_eeg.set', '/mnt/nemar/openneuro/ds002718/sub-013/eeg/sub-013_task-FaceRecognition_eeg.set', '/mnt/nemar/openneuro/ds002718/sub-014/eeg/sub-014_task-FaceRecognition_eeg.set', '/mnt/nemar/openneuro/ds002718/sub-015/eeg/sub-015_task-FaceRecognition_eeg.set', '/mnt/nemar/openneuro/ds002718/sub-016/eeg/sub-016_task-FaceRecognition_eeg.set', '/mnt/nemar/openneuro/ds002718/sub-017/eeg/sub-017_task-FaceRecognition_eeg.set', '/mnt/nemar/openneuro/ds002718/sub-018/eeg/sub-018_task-FaceRecognition_eeg.set', '/mnt/nemar/openneuro/ds002718/sub-019/eeg/sub-019_task-FaceRecognition_eeg.set']\n",
      "['/mnt/nemar/openneuro/ds004770/sub-01/ses-base/ieeg/sub-01_ses-base_task-game_run-01_ieeg.edf', '/mnt/nemar/openneuro/ds004770/sub-01/ses-task/ieeg/sub-01_ses-task_task-game_run-01_ieeg.edf', '/mnt/nemar/openneuro/ds004770/sub-02/ses-base/ieeg/sub-02_ses-base_task-game_run-01_ieeg.edf', '/mnt/nemar/openneuro/ds004770/sub-02/ses-task/ieeg/sub-02_ses-task_task-game_run-01_ieeg.edf', '/mnt/nemar/openneuro/ds004770/sub-02/ses-task/ieeg/sub-02_ses-task_task-game_run-02_ieeg.edf', '/mnt/nemar/openneuro/ds004770/sub-03/ses-base/ieeg/sub-03_ses-base_task-game_run-01_ieeg.edf', '/mnt/nemar/openneuro/ds004770/sub-03/ses-task/ieeg/sub-03_ses-task_task-game_run-01_ieeg.edf', '/mnt/nemar/openneuro/ds004770/sub-04/ses-base/ieeg/sub-04_ses-base_task-game_run-01_ieeg.edf', '/mnt/nemar/openneuro/ds004770/sub-04/ses-task/ieeg/sub-04_ses-task_task-game_run-01_ieeg.edf', '/mnt/nemar/openneuro/ds004770/sub-05/ses-base/ieeg/sub-05_ses-base_task-game_run-01_ieeg.edf', '/mnt/nemar/openneuro/ds004770/sub-05/ses-task/ieeg/sub-05_ses-task_task-game_run-01_ieeg.edf', '/mnt/nemar/openneuro/ds004770/sub-06/ses-base/ieeg/sub-06_ses-base_task-game_run-01_ieeg.edf', '/mnt/nemar/openneuro/ds004770/sub-06/ses-task/ieeg/sub-06_ses-task_task-game_run-01_ieeg.edf', '/mnt/nemar/openneuro/ds004770/sub-06/ses-task/ieeg/sub-06_ses-task_task-game_run-02_ieeg.edf', '/mnt/nemar/openneuro/ds004770/sub-07/ses-base/ieeg/sub-07_ses-base_task-game_run-01_ieeg.edf', '/mnt/nemar/openneuro/ds004770/sub-07/ses-task/ieeg/sub-07_ses-task_task-game_run-01_ieeg.edf', '/mnt/nemar/openneuro/ds004770/sub-08/ses-base/ieeg/sub-08_ses-base_task-game_run-01_ieeg.edf', '/mnt/nemar/openneuro/ds004770/sub-08/ses-task/ieeg/sub-08_ses-task_task-game_run-01_ieeg.edf', '/mnt/nemar/openneuro/ds004770/sub-09/ses-base/ieeg/sub-09_ses-base_task-game_run-01_ieeg.edf', '/mnt/nemar/openneuro/ds004770/sub-09/ses-task/ieeg/sub-09_ses-task_task-game_run-01_ieeg.edf', '/mnt/nemar/openneuro/ds004770/sub-10/ses-base/ieeg/sub-10_ses-base_task-game_run-01_ieeg.edf', '/mnt/nemar/openneuro/ds004770/sub-10/ses-task/ieeg/sub-10_ses-task_task-game_run-01_ieeg.edf']\n",
      "['/mnt/nemar/openneuro/ds004561/sub-01/eeg/sub-01_task-agencyRT_eeg.vhdr', '/mnt/nemar/openneuro/ds004561/sub-02/eeg/sub-02_task-agencyRT_eeg.vhdr', '/mnt/nemar/openneuro/ds004561/sub-03/eeg/sub-03_task-agencyRT_eeg.vhdr', '/mnt/nemar/openneuro/ds004561/sub-04/eeg/sub-04_task-agencyRT_eeg.vhdr', '/mnt/nemar/openneuro/ds004561/sub-05/eeg/sub-05_task-agencyRT_eeg.vhdr', '/mnt/nemar/openneuro/ds004561/sub-07/eeg/sub-07_task-agencyRT_eeg.vhdr', '/mnt/nemar/openneuro/ds004561/sub-08/eeg/sub-08_task-agencyRT_eeg.vhdr', '/mnt/nemar/openneuro/ds004561/sub-09/eeg/sub-09_task-agencyRT_eeg.vhdr', '/mnt/nemar/openneuro/ds004561/sub-10/eeg/sub-10_task-agencyRT_eeg.vhdr', '/mnt/nemar/openneuro/ds004561/sub-11/eeg/sub-11_task-agencyRT_eeg.vhdr', '/mnt/nemar/openneuro/ds004561/sub-12/eeg/sub-12_task-agencyRT_eeg.vhdr', '/mnt/nemar/openneuro/ds004561/sub-13/eeg/sub-13_task-agencyRT_eeg.vhdr', '/mnt/nemar/openneuro/ds004561/sub-14/eeg/sub-14_task-agencyRT_eeg.vhdr', '/mnt/nemar/openneuro/ds004561/sub-15/eeg/sub-15_task-agencyRT_eeg.vhdr', '/mnt/nemar/openneuro/ds004561/sub-16/eeg/sub-16_task-agencyRT_eeg.vhdr', '/mnt/nemar/openneuro/ds004561/sub-17/eeg/sub-17_task-agencyRT_eeg.vhdr', '/mnt/nemar/openneuro/ds004561/sub-18/eeg/sub-18_task-agencyRT_eeg.vhdr', '/mnt/nemar/openneuro/ds004561/sub-19/eeg/sub-19_task-agencyRT_eeg.vhdr', '/mnt/nemar/openneuro/ds004561/sub-20/eeg/sub-20_task-agencyRT_eeg.vhdr', '/mnt/nemar/openneuro/ds004561/sub-21/eeg/sub-21_task-agencyRT_eeg.vhdr', '/mnt/nemar/openneuro/ds004561/sub-22/eeg/sub-22_task-agencyRT_eeg.vhdr', '/mnt/nemar/openneuro/ds004561/sub-23/eeg/sub-23_task-agencyRT_eeg.vhdr', '/mnt/nemar/openneuro/ds004561/sub-25/eeg/sub-25_task-agencyRT_eeg.vhdr']\n"
     ]
    }
   ],
   "source": [
    "def get_recordings(layout:BIDSLayout):\n",
    "    extensions = {\n",
    "            '.set': ['.set', '.fdt'], # eeglab\n",
    "            '.edf': ['.edf'], # european\n",
    "            '.vhdr': ['.eeg', '.vhdr', '.vmrk', '.dat', '.raw'], # brainvision\n",
    "            '.bdf': ['.bdf'], # biosemi\n",
    "        }\n",
    "    files = []\n",
    "    for ext, exts in extensions.items():\n",
    "        files = layout.get(extension=ext, return_type='filename')\n",
    "        if files:\n",
    "            break \n",
    "    return files\n",
    "print(get_recordings(BIDSLayout('/mnt/nemar/openneuro/ds002718')))\n",
    "print(get_recordings(BIDSLayout('/mnt/nemar/openneuro/ds004770')))\n",
    "print(get_recordings(BIDSLayout('/mnt/nemar/openneuro/ds004561')))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<BIDSFile filename='/mnt/nemar/openneuro/ds002718/sub-002/eeg/sub-002_task-FaceRecognition_eeg.set'>\n"
     ]
    }
   ],
   "source": [
    "layout = BIDSLayout('/mnt/nemar/openneuro/ds002718') \n",
    "# get file from path\n",
    "entities = layout.parse_file_entities('/mnt/nemar/openneuro/ds002718/sub-002/eeg/sub-002_task-FaceRecognition_eeg.set')\n",
    "bidsfile = layout.get(**entities)[0]\n",
    "print(bidsfile)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'CapManufacturer': 'Easycap',\n",
      " 'ECGChannelCount': 0,\n",
      " 'EEGChannelCount': 70,\n",
      " 'EEGGround': 'left collar bone',\n",
      " 'EEGPlacementScheme': 'extended 10-10% system',\n",
      " 'EEGReference': 'nose',\n",
      " 'EMGChannelCount': 0,\n",
      " 'EOGChannelCount': 2,\n",
      " 'InstitutionAddress': '15 Chaucer Road, Cambridge, UK',\n",
      " 'InstitutionName': 'MRC Cognition & Brain Sciences Unit',\n",
      " 'MiscChannelCount': 4,\n",
      " 'PowerLineFrequency': 50,\n",
      " 'RecordingDuration': 2991,\n",
      " 'RecordingType': 'continuous',\n",
      " 'SamplingFrequency': 250,\n",
      " 'SoftwareFilters': {'LowPassFilter': {'cutoff': '350 (Hz)'}},\n",
      " 'TaskDescription': 'Subjects viewed stimuli on a screen during six, 7.5 '\n",
      "                    'minute runs. The stimuli were photographs of either a '\n",
      "                    'famous face (known to most of British or a scrambled '\n",
      "                    'face, and appeared for a random duration between 800 and '\n",
      "                    '1,000 ms. Subjects were instructed to fixate centrally '\n",
      "                    'throughout the experiment. To ensure attention to each '\n",
      "                    'stimulus, participants were asked to press one of two '\n",
      "                    'keys with either their left or right index finger '\n",
      "                    '(assignment counter-balanced across participants). Their '\n",
      "                    'key-press was based on how symmetric they regarded each '\n",
      "                    'image: pressing one or the other key depending whether '\n",
      "                    \"they thought the image was 'more' or 'less symmetric' \"\n",
      "                    'than average.',\n",
      " 'TaskName': 'FaceRecognition',\n",
      " 'datatype': 'eeg',\n",
      " 'extension': '.set',\n",
      " 'subject': '002',\n",
      " 'suffix': 'eeg',\n",
      " 'task': 'FaceRecognition'}\n"
     ]
    }
   ],
   "source": [
    "import pprint\n",
    "# get general info of a recording\n",
    "pprint.pprint(bidsfile.get_entities(metadata='all'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<BIDSJSONFile filename='/mnt/nemar/openneuro/ds002718/sub-002/eeg/sub-002_task-FaceRecognition_eeg.json'>]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get associations doesn't give us all desired bids dependencies\n",
    "bidsfile.get_associations()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'extension': '.json', 'subject': '002', 'suffix': 'events', 'task': 'FaceRecognition'}\n",
      "[]\n",
      "[<BIDSJSONFile filename='/mnt/nemar/openneuro/ds002718/task-FaceRecognition_events.json'>]\n",
      "{'extension': 'tsv', 'subject': '002', 'suffix': 'events', 'task': 'FaceRecognition'}\n",
      "[<BIDSDataFile filename='/mnt/nemar/openneuro/ds002718/sub-002/eeg/sub-002_task-FaceRecognition_events.tsv'>]\n",
      "{'extension': 'tsv', 'subject': '002', 'suffix': 'electrodes', 'task': 'FaceRecognition'}\n",
      "[]\n",
      "{'extension': 'json', 'subject': '002', 'suffix': 'coordsystem', 'task': 'FaceRecognition'}\n",
      "[]\n"
     ]
    }
   ],
   "source": [
    "# top level events.json can't be retrieved from a file level\n",
    "file_entities = bidsfile.get_entities()\n",
    "# remove 'datatype'\n",
    "file_entities.pop('datatype')\n",
    "\n",
    "file_entities['suffix'] = 'events'\n",
    "file_entities['extension'] = '.json'\n",
    "print(file_entities)\n",
    "print(layout.get(**file_entities))\n",
    "print(layout.get(suffix='events', extension='.json'))\n",
    "\n",
    "# not all file level metadata files can be retrieved even though they exist\n",
    "file_entities['suffix'] = 'events'\n",
    "file_entities['extension'] = 'tsv'\n",
    "print(file_entities)\n",
    "print(layout.get(**file_entities))\n",
    "\n",
    "file_entities['suffix'] = 'electrodes'\n",
    "file_entities['extension'] = 'tsv'\n",
    "print(file_entities)\n",
    "print(layout.get(**file_entities))\n",
    "\n",
    "file_entities['suffix'] = 'coordsystem'\n",
    "file_entities['extension'] = 'json'\n",
    "print(file_entities)\n",
    "print(layout.get(**file_entities))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "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": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}