docstr: Train the transformer, and tranform the time series used for
  training.
  
  Parameters
  ----------
  ts: pandas.Series or pandas.DataFrame
      Time series to be used for training and be transformed.
      If a DataFrame with k columns, it is treated as k independent
      univariate time series, and k univariate transformers will be
      trained and applied to each series independently.
  
  Returns
  -------
  pandas.Series or pandas.DataFrame
      Transformed time series.
docstr_tok: ["Train","the","transformer",",","and","tranform","the","time","series","used","for","training",".","Parameters","--","--","--","--","--","ts",":","pandas.Series","or","pandas.DataFrame","Time","series","to","be","used","for","training","and","be","transformed",".","If","a","DataFrame","with","k","columns",",","it","is","treated","as","k","independent","univariate","time","series",",","and","k","univariate","transformers","will","be","trained","and","applied","to","each","series","independently",".","Returns","--","--","--","-","pandas.Series","or","pandas.DataFrame","Transformed","time","series","."]
code: def fit_predict(
      self, ts: Union[pd.Series, pd.DataFrame]
  ) -> Union[pd.Series, pd.DataFrame]:
      """Train the transformer, and tranform the time series used for
      training.
  
      Parameters
      ----------
      ts: pandas.Series or pandas.DataFrame
          Time series to be used for training and be transformed.
          If a DataFrame with k columns, it is treated as k independent
          univariate time series, and k univariate transformers will be
          trained and applied to each series independently.
  
      Returns
      -------
      pandas.Series or pandas.DataFrame
          Transformed time series.
  
      """
      self.fit(ts)
      return self.predict(ts)
  
file_path: adtk/src/adtk/_transformer_base.py
imports: from typing import Union
  import pandas
  from ._base import _NonTrainableMultivariateModel, _NonTrainableUnivariateModel, _TrainableMultivariateModel, _TrainableUnivariateModel
label_desc: Use image node_id 3 for calling the _TrainableUnivariateTransformer obj's underlying member method code with example usage: obj.fit_predict(ts) and returns: self