class_docstr: Alignment path based on lucky dynamic time warping distance.
  
  This aligner returns the alignment path produced by the lucky time warping
  distance [1]_.
  Uses Euclidean distance for multivariate data.
  
  Based on code by Krisztian A Buza's research group.
  
  Parameters
  ----------
  window: int, optional (default=None)
      Maximum distance between indices of aligned series, aka warping window.
      If None, defaults to max(len(ts1), len(ts2)), i.e., no warping window.
  
  References
  ----------
  ..[1] Stephan Spiegel, Brijnesh-Johannes Jain, and Sahin Albayrak.
      Fast time series classification under lucky time warping distance.
      Proceedings of the 29th Annual ACM Symposium on Applied Computing. 2014.
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 aligners.
  
  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 aligners.
  
      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 = {"window": 3}
  
      return [params0, params1]
  
file_path: sktime/sktime/alignment/lucky.py
imports: import numpy
  import pandas
  from sktime.alignment.base import BaseAligner
label_desc: Use image node_id 5 for calling the AlignerLuckyDtw obj's underlying member method code with example usage: obj.get_test_params(cls, parameter_set) and returns: list