How to use the tedana.io.load_data function in tedana

good data, the full map uses the single echo's
                              value while the limited map has a NaN.
    s0vG.nii                  Full S0 map/timeseries.
    ts_OC.nii                 Optimally combined timeseries.
    ======================    =================================================
    """
    # ensure tes are in appropriate format
    tes = [float(te) for te in tes]
    n_echos = len(tes)

    # coerce data to samples x echos x time array
    if isinstance(data, str):
        data = [data]

    LGR.info('Loading input data: {}'.format([f for f in data]))
    catd, ref_img = io.load_data(data, n_echos=n_echos)
    n_samp, n_echos, n_vols = catd.shape
    LGR.debug('Resulting data shape: {}'.format(catd.shape))

    try:
        ref_label = op.basename(ref_img).split('.')[0]
    except (TypeError, AttributeError):
        ref_label = op.basename(str(data[0])).split('.')[0]

    if label is not None:
        out_dir = 'TED.{0}.{1}'.format(ref_label, label)
    else:
        out_dir = 'TED.{0}'.format(ref_label)
    out_dir = op.abspath(out_dir)
    if not op.isdir(out_dir):
        LGR.info('Creating output directory: {}'.format(out_dir))
        os.mkdir(out_dir)

# ensure tes are in appropriate format
    tes = [float(te) for te in tes]
    n_echos = len(tes)

    # Coerce gscontrol to list
    if not isinstance(gscontrol, list):
        gscontrol = [gscontrol]

    # coerce data to samples x echos x time array
    if isinstance(data, str):
        if not op.exists(data):
            raise ValueError('Zcat file {} does not exist'.format(data))
        data = [data]

    LGR.info('Loading input data: {}'.format([f for f in data]))
    catd, ref_img = io.load_data(data, n_echos=n_echos)
    n_samp, n_echos, n_vols = catd.shape
    LGR.debug('Resulting data shape: {}'.format(catd.shape))

    if no_png and (png_cmap != 'coolwarm'):
        LGR.warning('Overriding --no-png since --png-cmap provided.')
        no_png = False

    # check if TR is 0
    img_t_r = ref_img.header.get_zooms()[-1]
    if img_t_r == 0 and not no_png:
        raise IOError('Dataset has a TR of 0. This indicates incorrect'
                      ' header information. To correct this, we recommend'
                      ' using this snippet:'
                      '\n'
                      'https://gist.github.com/jbteves/032c87aeb080dd8de8861cb151bff5d6'
                      '\n'