get_stc_from_labels.py

import mne
import numpy as np

def labels2stc(labels,labels_data,stc):
    stc_new = stc.copy()
    stc_new.data.fill(0)
    for index,label in enumerate(labels):
        if labels_data.ndim==1:
            if isinstance(label, str):
                temp = stc.in_label(mne.read_label(label))
            else:
                emp = stc.in_label(label)
            temp.data.fill(labels_data[index])
            stc_new += temp.expand(stc.vertices)
        else:
            if isinstance(label, str):
                lab = mne.read_label(label)
                label_name = label
            else:
                lab = label
                label_name = lab.name
            ver = np.intersect1d(lab.vertices, stc.vertices)
            if 'rh.' in label_name:
                ver=ver+len(stc.vertices[0])
            stc_data = np.tile(labels_data[index,:][:,np.newaxis],len(ver)).T
            stc_new.data[ver, :] = stc_data
    return stc_new


def get_stc(labels,data,tmin=0,tstep=1):
    stc_vertices = [np.uint32(np.arange(10242)), np.uint32(np.arange(10242))]

    if data.ndim==1:
        stc_data = np.ones((20484,1), dtype=np.float32)
    else:
        stc_data = np.ones((20484, data.shape[1]), dtype=np.float32)

    stc = mne.SourceEstimate(stc_data, vertices=stc_vertices, tmin=tmin, tstep=tstep, subject='fsaverage')
    stc_new = labels2stc(labels, data, stc)
    return stc_new