brsa.py 文件源码

def _chol_idx(self, n_C, rank):
        l_idx = np.tril_indices(n_C)
        if rank is not None:
            # The rank of covariance matrix is specified
            idx_rank = np.where(l_idx[1] < rank)
            l_idx = (l_idx[0][idx_rank], l_idx[1][idx_rank])
            logger.info('Using the rank specified by the user: '
                        '{}'.format(rank))
        else:
            rank = n_C
            # if not specified, we assume you want to
            # estimate a full rank matrix
            logger.warning('Please be aware that you did not specify the'
                           ' rank of covariance matrix to estimate.'
                           'I will assume that the covariance matrix '
                           'shared among voxels is of full rank.'
                           'Rank = {}'.format(rank))
            logger.warning('Please be aware that estimating a matrix of '
                           'high rank can be very slow.'
                           'If you have a good reason to specify a rank '
                           'lower than the number of experiment conditions,'
                           ' do so.')
        return l_idx, rank