def _read_stc(filename):
    """ Aux Function
    """
    fid = open(filename, 'rb')

    stc = dict()

    fid.seek(0, 2)  # go to end of file
    file_length = fid.tell()
    fid.seek(0, 0)  # go to beginning of file

    # read tmin in ms
    stc['tmin'] = float(np.fromfile(fid, dtype=">f4", count=1))
    stc['tmin'] /= 1000.0

    # read sampling rate in ms
    stc['tstep'] = float(np.fromfile(fid, dtype=">f4", count=1))
    stc['tstep'] /= 1000.0

    # read number of vertices/sources
    vertices_n = int(np.fromfile(fid, dtype=">u4", count=1))

    # read the source vector
    stc['vertices'] = np.fromfile(fid, dtype=">u4", count=vertices_n)

    # read the number of timepts
    data_n = int(np.fromfile(fid, dtype=">u4", count=1))

    if (vertices_n and  # vertices_n can be 0 (empty stc)
            ((4 / file_length - 4 - vertices_n) % (data_n * vertices_n)) != 0):
        raise ValueError('incorrect stc file size')

    # read the data matrix
    stc['data'] = np.fromfile(fid, dtype=">f4", count=vertices_n * data_n)
    stc['data'] = stc['data'].reshape([data_n, vertices_n]).T

    # close the file
    fid.close()
    return stc
dataset/ETHPy150Open mne-tools/mne-python/mne/source_estimate.py/_read_stc/swapped operands of `/`