class_docstr: Dynamic time warping distance, from tslearn.
  
  Direct interface to ``tslearn.metrics.cdist_dtw``.
  
  Parameters
  ----------
  global_constraint : {"itakura", "sakoe_chiba"} or None (default: None)
      Global constraint to restrict admissible paths for DTW.
  sakoe_chiba_radius : int or None (default: None)
      Radius to be used for Sakoe-Chiba band global constraint.
      If None and ``global_constraint`` is set to ``"sakoe_chiba"``, a radius of
      1 is used.
      If both ``sakoe_chiba_radius`` and ``itakura_max_slope`` are set,
      ``global_constraint`` is used to infer which constraint to use among the
      two. In this case, if ``global_constraint`` corresponds to no global
      constraint, a ``RuntimeWarning`` is raised and no global constraint is
      used.
  itakura_max_slope : float or None (default: None)
      Maximum slope for the Itakura parallelogram constraint.
      If None and ``global_constraint`` is set to ``"itakura"``, a maximum slope
      of 2 is used.
      If both ``sakoe_chiba_radius`` and ``itakura_max_slope`` are set,
      ``global_constraint`` is used to infer which constraint to use among the
      two. In this case, if ``global_constraint`` corresponds to no global
      constraint, a ``RuntimeWarning`` is raised and no global constraint is
      used.
  n_jobs : int or None, optional (default=None)
      The number of jobs to run in parallel.
      ``None`` means 1 unless in a ``joblib.parallel_backend`` context.
      ``-1`` means using all processors.
  verbose : int, optional (default=0)
      The verbosity level: if non zero, progress messages are printed.
      Above 50, the output is sent to stdout.
      The frequency of the messages increases with the verbosity level.
      If it more than 10, all iterations are reported.
  
  References
  ----------
  .. [1] H. Sakoe, S. Chiba, "Dynamic programming algorithm optimization for
         spoken word recognition," IEEE Transactions on Acoustics, Speech and
         Signal Processing, vol. 26(1), pp. 43--49, 1978.
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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.
      There are currently no reserved values for distance/kernel transformers.
  
  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`
docstr_tok: ["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",".","There","are","currently","no","reserved","values","for","distance\/kernel","transformers",".","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, 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.
          There are currently no reserved values for distance/kernel transformers.
  
      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`
      """
      params0 = {}
      params1 = {
          "global_constraint": "itakura",
          "itakura_max_slope": 1.5,
      }
      params2 = {
          "global_constraint": "sakoe_chiba",
          "sakoe_chiba_radius": 2,
      }
  
      return [params0, params1, params2]
  
file_path: sktime/sktime/dists_kernels/dtw/_dtw_tslearn.py
imports: from sktime.dists_kernels.base import BasePairwiseTransformerPanel
  from sktime.dists_kernels.base.adapters import _TslearnPwTrafoAdapter
label_desc: Use image node_id 3 for calling the DtwDistTslearn obj's underlying member method code with example usage: obj.get_test_params(cls, parameter_set) and returns: list