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    {
      "execution_count": null, 
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        "%matplotlib inline"
      ], 
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      "source": [
        "\n# Extracting time course from source_estimate object\n\n\nLoad a SourceEstimate object from stc files and\nextract the time course of activation in\nindividual labels, as well as in a complex label\nformed through merging two labels.\n\n\n"
      ], 
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      "execution_count": null, 
      "cell_type": "code", 
      "source": [
        "# Author: Christian Brodbeck <christianbrodbeck@nyu.edu>\n#\n# License: BSD (3-clause)\n\nimport os\n\nimport mne\nfrom mne.datasets import sample\nimport matplotlib.pyplot as plt\n\nprint(__doc__)\n\ndata_path = sample.data_path()\nos.environ['SUBJECTS_DIR'] = data_path + '/subjects'\nmeg_path = data_path + '/MEG/sample'\n\n# load the stc\nstc = mne.read_source_estimate(meg_path + '/sample_audvis-meg')\n\n# load the labels\naud_lh = mne.read_label(meg_path + '/labels/Aud-lh.label')\naud_rh = mne.read_label(meg_path + '/labels/Aud-rh.label')\n\n# extract the time course for different labels from the stc\nstc_lh = stc.in_label(aud_lh)\nstc_rh = stc.in_label(aud_rh)\nstc_bh = stc.in_label(aud_lh + aud_rh)\n\n# calculate center of mass and transform to mni coordinates\nvtx, _, t_lh = stc_lh.center_of_mass('sample')\nmni_lh = mne.vertex_to_mni(vtx, 0, 'sample')[0]\nvtx, _, t_rh = stc_rh.center_of_mass('sample')\nmni_rh = mne.vertex_to_mni(vtx, 1, 'sample')[0]\n\n# plot the activation\nplt.figure()\nplt.axes([.1, .275, .85, .625])\nhl = plt.plot(stc.times, stc_lh.data.mean(0), 'b')[0]\nhr = plt.plot(stc.times, stc_rh.data.mean(0), 'g')[0]\nhb = plt.plot(stc.times, stc_bh.data.mean(0), 'r')[0]\nplt.xlabel('Time (s)')\nplt.ylabel('Source amplitude (dSPM)')\nplt.xlim(stc.times[0], stc.times[-1])\n\n# add a legend including center-of-mass mni coordinates to the plot\nlabels = ['LH: center of mass = %s' % mni_lh.round(2),\n          'RH: center of mass = %s' % mni_rh.round(2),\n          'Combined LH & RH']\nplt.figlegend([hl, hr, hb], labels, 'lower center')\nplt.suptitle('Average activation in auditory cortex labels', fontsize=20)\nplt.show()"
      ], 
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      "metadata": {
        "collapsed": false
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