{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "\n\n# Reading an STC file\n\nSTC files contain activations on cortex ie. source\nreconstructions\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>\n#\n# License: BSD-3-Clause\n# Copyright the MNE-Python contributors."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "import matplotlib.pyplot as plt\n\nimport mne\nfrom mne.datasets import sample\n\nprint(__doc__)\n\ndata_path = sample.data_path()\nmeg_path = data_path / \"MEG\" / \"sample\"\nfname = meg_path / \"sample_audvis-meg\"\n\nstc = mne.read_source_estimate(fname)\n\nn_vertices, n_samples = stc.data.shape\nprint(f\"stc data size: {n_vertices} (nb of vertices) x {n_samples} (nb of samples)\")\n\n# View source activations\nplt.plot(stc.times, stc.data[::100, :].T)\nplt.xlabel(\"time (ms)\")\nplt.ylabel(\"Source amplitude\")\nplt.show()"
      ]
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "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": "3.12.2"
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