code: def fit(self, X, y=None):
          '''
          Fit the transform
  
          Parameters
          ----------
          X : array-like, shape [n_series, ...]
              Segmented time series data and (optionally) contextual data
          y : None
              There is no need of a target in a transformer, yet the pipeline API requires this
              parameter.
  
          Returns
          -------
          self : object
              Returns self.
          '''
          check_ts_data(X, y)
          self._reset()
          if self.verbose:
              print("X Shape: ", X.shape)
          self.f_labels = self._generate_feature_labels(X)
          return self fit(self, X, y=None):
          '''
          Fit the transform
  
          Parameters
          ----------
          X : array-like, shape [n_series, ...]
              Segmented time series data and (optionally) contextual data
          y : None
              There is no need of a target in a transformer, yet the pipeline API requires this
              parameter.
  
          Returns
          -------
          self : object
              Returns self.
          '''
          check_ts_data(X, y)
          self._reset()
          if self.verbose:
              print("X Shape: ", X.shape)
          self.f_labels = self._generate_feature_labels(X)
          return self
docs: Fit the transform
  
          Parameters
          ----------
          X : array-like, shape [n_series, ...]
              Segmented time series data and (optionally) contextual data
          y : None
              There is no need of a target in a transformer, yet the pipeline API requires this
              parameter.
  
          Returns
          -------
          self : object
              Returns self.