megplot/megplot.py at master · jdirani/megplot · GitHub

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# J. Dirani
# Quick way to plot eelbrain results

import mne, eelbrain
import numpy as np


def plot(res, ds, out_dir, match, subjects_dir, surf=None, hemi=None, pmin=None):

    '''
    Plot Timecourse, Brain, and Barplot of signidicant clusters from an eelbrain ANOVA/t-test results object.


    Parameters
    -------------
    res : eelbrain ANOVA or t-test result object

    ds: eelbrain.Dataset
    Dataset containing stcs and condidion labels needs to be specified

    out_dir : str
    Output directory, ends with "/"

    surf : 'inflated' | 'pial' | 'smoothwm' | 'sphere' | 'white'
    surfer.Brain surface to use as brain geometry. Default = 'white'

    match : str | None
    Match cases for a repeated measures design in pairwsie t-test for barplots.

    hemi: 'lh' | 'rh'
    Hemisphere. Defaults to 'lh'


    subjects_dir : str
    subjects directory associated with the source space dimension.

    pmin: float
    permutation p-value (threshold)

    '''


    if surf == None:
        surf = 'white'
    if hemi == None:
        hemi = 'lh'
    if pmin == None:
        pmin = 0.05

    reset_stc = ds['stc']

    mask_sign_clusters = np.where(res.clusters['p'] <= pmin, True, False)
    sign_clusters = res.clusters[mask_sign_clusters]

    if sign_clusters.n_cases != None: #check for significant clusters
        for i in range(sign_clusters.n_cases):
            cluster_nb = i+1
            cluster = sign_clusters[i]['cluster']
            tstart = sign_clusters[i]['tstart']
            tstop = sign_clusters[i]['tstop']
            effect = sign_clusters[i]['effect']

            effect = effect.replace(' x ', '%') # Changing format of string for interaction effects.

            # save significant cluster as a temporary label for plotting.
            ds['stc'] = reset_stc
            label = eelbrain.labels_from_clusters(cluster)
            label[0].name = 'TempLabel-%s'%hemi
            mne.write_labels_to_annot(label,subject='fsaverage', parc='workspace' ,subjects_dir=subjects_dir, overwrite=True)
            ds['stc'].source.set_parc('workspace')
            ds['stc'] = ds['stc'].sub(source='TempLabel-%s'%hemi)
            timecourse = ds['stc'].mean('source')


            #Plot
                # 1)Timecourse
            activation = eelbrain.plot.UTSStat(timecourse, effect, ds=ds, title = 'Effect = %s, cluster #%s'%(effect, cluster_nb))
            activation.add_vspan(xmin=tstart, xmax=tstop, color='lightgrey', zorder=-50)
            activation.save(out_dir+'Cluster #%s, Effect = %s - Timecourse.png'%(cluster_nb, effect))
            activation.close()
                # 2) Brain
            brain = eelbrain.plot.brain.cluster(cluster.mean(time=(tstart,tstop)), subjects_dir=subjects_dir, surf=surf, colorbar=True)
            brain.save_image(out_dir+'Cluster #%s, Effect = %s - Brain.png'%(cluster_nb, effect))
            brain.close()
                # 3) Bars
            ds['average_source_activation'] = timecourse.mean(time=(tstart,tstop))
            bar = eelbrain.plot.Barplot(ds['average_source_activation'], X=effect, ds=ds, match=match)
            bar.save(out_dir+'Cluster #%s, Effect = %s - Bars.png'%(cluster_nb, effect))
            bar.close()


    ds['stc'] = reset_stc # resets ds['stc'] before exiting the loop. Otherwise, returns an errror if run again.