transformer.py 文件源码

def transform(self, epochs_data, y=None):
        """Standardizes data across channels

        Parameters
        ----------
        epochs_data : array, shape (n_epochs, n_channels, n_times)
            The data.
        y : None | array, shape (n_epochs,)
            The label for each epoch.
            If None not used. Defaults to None.

        Returns
        -------
        X : array, shape (n_epochs, n_channels, n_times)
            The data concatenated over channels.
        """
        if not isinstance(epochs_data, np.ndarray):
            raise ValueError("epochs_data should be of type ndarray (got %s)."
                             % type(epochs_data))

        X = np.atleast_3d(epochs_data)

        for key, this_pick in six.iteritems(self.picks_list_):
            if self.with_mean:
                X[:, this_pick, :] -= self.ch_mean_[key]
            if self.with_std:
                X[:, this_pick, :] /= self.std_[key]

        return X