def transform(self, X):
        """Transform the provided data.

        It extracts the three features from all the selected windows
        for all the samples.

        Parameters
        ----------
        X : array-like, shape = (n_samples, n_timestamps)
            Univariate time series.

        Returns
        -------
        X_new : array, shape = (n_samples * n_subseries, 3 * n_intervals + 4)
            Extracted features.

        """
        X = check_array(X, dtype='float64')
        n_samples = X.shape[0]

        # Extract the features from each interval
        interval_indices = np.array(
            [self.interval_indices_[:, :-1], self.interval_indices_[:, 1:]]
        )

        n_subseries, n_intervals = interval_indices.shape[1:]
        X_features = extract_features(X, interval_indices, n_samples,
                                      n_subseries, n_intervals)
        return X_features
Transform the provided data.

        It extracts the three features from all the selected windows
        for all the samples.

        Parameters
        ----------
        X : array-like, shape = (n_samples, n_timestamps)
            Univariate time series.

        Returns
        -------
        X_new : array, shape = (n_samples * n_subseries, 3 * n_intervals + 4)
            Extracted features.

        
pyts/classification/tsbf.py