def get_net_vectors(subject_list, kind, atlas_name='aal'):
    '\n        subject_list : the subject short IDs list\n        kind         : the kind of connectivity to be used, e.g. lasso, partial correlation, correlation\n        atlas_name   : name of the atlas used\n\n    returns:\n        matrix       : matrix of connectivity vectors (num_subjects x num_connections)\n    '
    networks = load_all_networks(subject_list, kind, atlas_name=atlas_name)
    norm_networks = [np.arctanh(mat) for mat in networks]
    idx = np.triu_indices_from(norm_networks[0], 1)
    vec_networks = [mat[idx] for mat in norm_networks]
    matrix = np.vstack(vec_networks)
    return matrix
subject_list : the subject short IDs list
    kind         : the kind of connectivity to be used, e.g. lasso, partial correlation, correlation
    atlas_name   : name of the atlas used

returns:
    matrix       : matrix of connectivity vectors (num_subjects x num_connections)
def get_net_vectors(subject_list, kind, atlas_name='aal'):
    '\n        subject_list : the subject short IDs list\n        kind         : the kind of connectivity to be used, e.g. lasso, partial correlation, correlation\n        atlas_name   : name of the atlas used\n\n    returns:\n        matrix       : matrix of connectivity vectors (num_subjects x num_connections)\n    '
    networks = load_all_networks(subject_list, kind, atlas_name=atlas_name)
    norm_networks = [np.arctanh(mat) for mat in networks]
    idx = np.triu_indices_from(norm_networks[0], 1)
    vec_networks = [mat[idx] for mat in norm_networks]
    matrix = np.vstack(vec_networks)
    return matrix