class_docstr: Longest Common Subsequence similarity distance, from tslearn.
  
  Direct interface to ``tslearn.metrics.lcss``.
  
  Parameters
  ----------
  eps : float (default: 1.)
      Maximum matching distance threshold.
  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.
  
  References
  ----------
  .. [1] M. Vlachos, D. Gunopoulos, and G. Kollios. 2002. "Discovering
          Similar Multidimensional Trajectories", In Proceedings of the
          18th International Conference on Data Engineering (ICDE '02).
          IEEE Computer Society, USA, 673.
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 = {
          "eps": 0.9,
          "global_constraint": "itakura",
          "itakura_max_slope": 1.5,
      }
      params2 = {
          "global_constraint": "sakoe_chiba",
          "sakoe_chiba_radius": 2,
      }
  
      return [params0, params1, params2]
  
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 LcssTslearn obj's underlying member method code with example usage: obj.get_test_params(cls, parameter_set) and returns: list