decoding_analysis.py 文件源码

def split_and_zscore(self, data, test_run):

        # Enforse type and size of the data
        data = np.asarray(data)
        if data.ndim == 1:
            data = np.expand_dims(data, 1)

        # Identify training and test samples
        train = np.asarray(self.runs != test_run)
        test = np.asarray(self.runs == test_run)

        train_data = data[train]
        test_data = data[test]

        # Compute the mean and standard deviation of the training set
        m, s = np.nanmean(train_data), np.nanstd(train_data)

        # Scale the training and test set
        train_data = (train_data - m) / s
        test_data = (test_data - m) / s

        return train_data, test_data