31775c422876534b0df7f26d253f2380db90d4b0,pynets/dmri/track.py,,prep_tissues,#Any#Any#Any#Any#Any#Any#,51

Before Change

        include_map[background > 0] = 1
        tiss_classifier = ActStoppingCriterion(include_map, vent_csf_in_dwi_data)
        del background
        del include_map
    elif tiss_class == "bin":
        tiss_classifier = BinaryStoppingCriterion(wm_mask_data.astype("bool"))
    elif tiss_class == "cmc":
        voxel_size = np.average(mask_img.header["pixdim"][1:4])

After Change

    // Load tissue maps and prepare tissue classifier
    wm_img = nib.load(wm_in_dwi)
    gm_img = nib.load(gm_in_dwi)
    gm_mask_data = np.asarray(gm_img.dataobj)
    wm_mask_data = np.asarray(wm_img.dataobj)
    vent_csf_in_dwi_data = np.asarray(nib.load(vent_csf_in_dwi).dataobj)
    if tiss_class == "act":
        background = np.ones(mask_img.shape)

Instances