class_docstr: Mock forecaster, returns data frames filled with a constant.
  
  Parameters
  ----------
  prediction_constant : float, optional
      The forecasted value for all steps in the horizon, by default 10
  
  Examples
  --------
  >>> from sktime.datasets import load_airline
  >>> from sktime.utils.estimators import MockUnivariateForecasterLogger
  >>> y = load_airline()
  >>> forecaster = MockUnivariateForecasterLogger()
  >>> forecaster.fit(y)
  MockUnivariateForecasterLogger(...)
  >>> y_pred = forecaster.predict(fh=[1,2,3])
  >>> print(forecaster.log)
  [('_fit', ...), ('_predict', ...)]
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docstr: Return testing parameter settings for the estimator.
  
  Parameters
  ----------
  parameter_set : str, default="default"
      Name of the set of test parameters to return, for use in tests. If no
      special parameters are defined for a value, will return `"default"` set.
  
  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`
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code: def get_test_params(cls, parameter_set="default"):
      """Return testing parameter settings for the estimator.
  
      Parameters
      ----------
      parameter_set : str, default="default"
          Name of the set of test parameters to return, for use in tests. If no
          special parameters are defined for a value, will return `"default"` set.
  
      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`
      """
      return [
          {"prediction_constant": 42},
          {"prediction_constant": -4.2},
      ]
  
file_path: sktime/sktime/utils/estimators/_forecasters.py
imports: import pandas
  from sktime.forecasting.base import BaseForecaster
  from sktime.utils.estimators._base import _method_logger, _MockEstimatorMixin
label_desc: Use image node_id 6 for calling the MockForecaster obj's underlying member method code with example usage: obj.get_test_params(cls, parameter_set) and returns: list