decoding_analysis.py 文件源码

def X(self):

        # Scale the data across features
        X = stats.zscore(np.asarray(self.betas))

        # Remove zero-variance features
        X = X[:, self.good_voxels]
        assert not np.isnan(X).any()

        # Regress out behavioral confounds
        rt = np.asarray(self.rt)
        m, s = np.nanmean(rt), np.nanstd(rt)
        rt = np.nan_to_num((rt - m) / s)
        X = OLS(X, rt).fit().resid

        return X