distances.py 文件源码

def covariance_matrices(im, labels, return_mm3=True):
    """
    Considers the label as a point distribution in the space, and returns the covariance matrix of the points
    distributions.
    :param im: input nibabel image
    :param labels: list of labels input.
    :param return_mm3: if true the answer is in mm if false in voxel indexes.
    :return: covariance matrix of the point distribution of the label
    """
    cov_matrices = [np.zeros([3, 3])] * len(labels)
    for l_id, l in enumerate(labels):
        coords = np.where(im.get_data() == l)  # returns [X_vector, Y_vector, Z_vector]
        if np.count_nonzero(coords) > 0:
            cov_matrices[l_id] = np.cov(coords)
        else:
            cov_matrices[l_id] = np.nan * np.ones([3, 3])
    if return_mm3:
        cov_matrices = [im.affine[:3, :3].dot(cm.astype(np.float64)) for cm in cov_matrices]

    return cov_matrices