Method transform

mne/decoding/transformer.py:336–355

Convert given array into two dimensions. Parameters ---------- X : array-like The data to fit. Can be, for example a list, or an array of at least 2d. The first dimension must be of length n_samples, where samples are the independent sampl

(self, X)

        return self

    def transform(self, X):
        """Convert given array into two dimensions.

        Parameters
        ----------
        X : array-like
            The data to fit. Can be, for example a list, or an array of at
            least 2d. The first dimension must be of length n_samples, where
            samples are the independent samples used by the estimator
            (e.g. n_epochs for epoched data).

        Returns
        -------
        X : array, shape (n_samples, n_features)
            The transformed data.
        """
        X = self._check_data(X, atleast_3d=False)
        if X.shape[1:] != self.features_shape_:
            raise ValueError("Shape of X used in fit and transform must be same")
        return X.reshape(len(X), -1)

    def fit_transform(self, X, y=None):
        """Fit the data, then transform in one step.