How to use the tedana.combine.make_optcom function in tedana

fittype)
    else:
        (t2s_limited, s0_limited,
         t2s_full, s0_full) = decay.fit_decay_ts(catd, tes, mask, masksum,
                                                 fittype)

    # set a hard cap for the T2* map/timeseries
    # anything that is 10x higher than the 99.5 %ile will be reset to 99.5 %ile
    cap_t2s = stats.scoreatpercentile(t2s_limited.flatten(), 99.5,
                                      interpolation_method='lower')
    LGR.debug('Setting cap on T2* map at {:.5f}'.format(cap_t2s * 10))
    t2s_limited[t2s_limited > cap_t2s * 10] = cap_t2s

    LGR.info('Computing optimal combination')
    # optimally combine data
    OCcatd = combine.make_optcom(catd, tes, mask, t2s=t2s_full,
                                 combmode=combmode)

    # clean up numerical errors
    for arr in (OCcatd, s0_limited, t2s_limited):
        np.nan_to_num(arr, copy=False)

    s0_limited[s0_limited < 0] = 0
    t2s_limited[t2s_limited < 0] = 0

    io.filewrite(t2s_limited, op.join(out_dir, 't2sv.nii'), ref_img)
    io.filewrite(s0_limited, op.join(out_dir, 's0v.nii'), ref_img)
    io.filewrite(t2s_full, op.join(out_dir, 't2svG.nii'), ref_img)
    io.filewrite(s0_full, op.join(out_dir, 's0vG.nii'), ref_img)
    io.filewrite(OCcatd, op.join(out_dir, 'ts_OC.nii'), ref_img)

# set a hard cap for the T2* map
    # anything that is 10x higher than the 99.5 %ile will be reset to 99.5 %ile
    cap_t2s = stats.scoreatpercentile(t2s_limited.flatten(), 99.5,
                                      interpolation_method='lower')
    LGR.debug('Setting cap on T2* map at {:.5f}'.format(cap_t2s * 10))
    t2s_limited[t2s_limited > cap_t2s * 10] = cap_t2s
    io.filewrite(t2s_limited, op.join(out_dir, 't2sv.nii'), ref_img)
    io.filewrite(s0_limited, op.join(out_dir, 's0v.nii'), ref_img)

    if verbose:
        io.filewrite(t2s_full, op.join(out_dir, 't2svG.nii'), ref_img)
        io.filewrite(s0_full, op.join(out_dir, 's0vG.nii'), ref_img)

    # optimally combine data
    data_oc = combine.make_optcom(catd, tes, mask, t2s=t2s_full, combmode=combmode)

    # regress out global signal unless explicitly not desired
    if 'gsr' in gscontrol:
        catd, data_oc = gsc.gscontrol_raw(catd, data_oc, n_echos, ref_img)

    if mixm is None:
        # Identify and remove thermal noise from data
        dd, n_components = decomposition.tedpca(catd, data_oc, combmode, mask,
                                                t2s_limited, t2s_full, ref_img,
                                                tes=tes, algorithm=tedpca,
                                                source_tes=source_tes,
                                                kdaw=10., rdaw=1.,
                                                out_dir=out_dir,
                                                verbose=verbose,
                                                low_mem=low_mem)
        mmix_orig = decomposition.tedica(dd, n_components, fixed_seed,