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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code: def __init__(
      self,
      global_constraint=None,
      sakoe_chiba_radius=None,
      itakura_max_slope=None,
      n_jobs=None,
      verbose=0,
  ):
      self.global_constraint = global_constraint
      self.sakoe_chiba_radius = sakoe_chiba_radius
      self.itakura_max_slope = itakura_max_slope
      self.n_jobs = n_jobs
      self.verbose = verbose
  
      super().__init__()
  
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 1 to create a new DtwDistTslearn object from inherited base classes: _TslearnPwTrafoAdapter, BasePairwiseTransformerPanel with example: obj = DtwDistTslearn(global_constraint, sakoe_chiba_radius, itakura_max_slope, n_jobs, verbose)