class_docstr: Prepare hierarchical data, including aggregate levels, from bottom level.
  
  This transformer adds aggregate levels via summation to a DataFrame with a
  multiindex. The aggregate levels are included with the special tag "__total"
  in the index. The aggregate nodes are discovered from top-to-bottom from
  the input data multiindex.
  
  Parameters
  ----------
  flatten_single_level : boolean (default=True)
      Remove aggregate nodes, i.e. ("__total"), where there is only a single
      child to the level
  
  See Also
  --------
  ReconcilerForecaster
  Reconciler
  
  References
  ----------
  .. [1] https://otexts.com/fpp3/hierarchical.html
  
  Examples
  --------
  >>> from sktime.transformations.hierarchical.aggregate import Aggregator
  >>> from sktime.utils._testing.hierarchical import _bottom_hier_datagen
  >>> agg = Aggregator()
  >>> y = _bottom_hier_datagen(
  ...     no_bottom_nodes=3,
  ...     no_levels=1,
  ...     random_seed=123,
  ... )
  >>> y = agg.fit_transform(y)
docstr: Return testing parameter settings for the estimator.
  
  Returns
  -------
  params : dict or list of dict, default = {}
      Parameters to create testing instances of the class
      Each dict are parameters to construct an "interesting" test instance, i.e.,
      `MyClass(**params)` or `MyClass(**params[i])` creates a valid test instance.
      `create_test_instance` uses the first (or only) dictionary in `params`
code: def get_test_params(cls):
      """Return testing parameter settings for the estimator.
  
      Returns
      -------
      params : dict or list of dict, default = {}
          Parameters to create testing instances of the class
          Each dict are parameters to construct an "interesting" test instance, i.e.,
          `MyClass(**params)` or `MyClass(**params[i])` creates a valid test instance.
          `create_test_instance` uses the first (or only) dictionary in `params`
      """
      params = {"flatten_single_levels": True}
  
      return params
  
file_path: sktime/sktime/transformations/hierarchical/aggregate.py
imports: import numpy
  import pandas
  from sktime.transformations.base import BaseTransformer
  from sktime.utils.warnings import warn
label_desc: Use image node_id 4 for calling the Aggregator obj's underlying member method code with example usage: obj.get_test_params(cls) and returns: params