Exemple #1
0
def load_current_fmri_clusters_labels_file():
    constrast_name = bpy.context.scene.fmri_clusters_labels_files
    minmax_fname = op.join(
        mu.get_user_fol(), 'fmri',
        '{}_minmax.pkl'.format('_'.join(constrast_name.split('_')[:-1])))
    minmax_exist = op.isfile(minmax_fname)
    # if minmax_exist and not _addon().colorbar_values_are_locked():
    #     min_val, max_val = mu.load(minmax_fname)
    #     _addon().set_colorbar_max_min(max_val, min_val)
    fMRIPanel.constrast = {}
    for hemi in mu.HEMIS:
        contrast_fname = get_contrast_fname(constrast_name, hemi)
        if contrast_fname != '':
            print('Loading {}'.format(contrast_fname))
            fMRIPanel.constrast[hemi] = np.load(contrast_fname)
    if not minmax_exist:
        data = None
        for hemi in mu.HEMIS:
            x_ravel = fMRIPanel.constrast[hemi]
            data = x_ravel if data is None else np.hstack((x_ravel, data))
        norm_percs = (bpy.context.scene.fmri_blobs_percentile_min,
                      bpy.context.scene.fmri_blobs_percentile_max)
        min_val, max_val = mu.calc_min_max(data, norm_percs=norm_percs)
        _addon().colorbar.set_colorbar_max_min(max_val,
                                               min_val,
                                               force_update=True)
        mu.save((min_val, max_val), minmax_fname)
def _calc_best_curves_sep(data, norm_percs=[3, 97]):
    if len(data) == 0:
        return 0
    try:
        max_diff = max([np.diff(mu.calc_min_max(data[k], norm_percs=norm_percs))[0] for k in range(data.shape[0])])
        return max_diff * 1.1
    except:
        print('Error in _calc_best_curves_sep')
        return 0