code: def test_dtw_subseq_path():
      for be in backends:
          for array_type in array_types:
              backend = instantiate_backend(be, array_type)
              # subseq, longseq = [1, 4], [1.0, 2.0, 2.0, 3.0, 4.0]
              subseq = cast([1, 4], array_type)
              longseq = cast([1.0, 2.0, 2.0, 3.0, 4.0], array_type)
              subseq = to_time_series(subseq, be=None)
              longseq = to_time_series(longseq, be=None)
              cost_matrix = tslearn.metrics.subsequence_cost_matrix(
                  subseq, longseq, be=be
              )
              assert backend.belongs_to_backend(cost_matrix)
  
              path = tslearn.metrics.subsequence_path(
                  cost_matrix, 3, be=be
              )
              np.testing.assert_equal(path, [(0, 2), (1, 3)])
              assert isinstance(path, list)
  
              path = tslearn.metrics.subsequence_path(
                  cost_matrix, 1, be=be
              )
              np.testing.assert_equal(path, [(0, 0), (1, 1)])
              assert isinstance(path, list)
  
imports: import platform
  import sys
  import numpy
  import pytest
  import tslearn.clustering
  import tslearn.metrics
  from scipy.spatial.distance import cdist
  from tslearn.backend.backend import Backend, cast, instantiate_backend
  from tslearn.metrics.dtw_variants import dtw_path
  from tslearn.utils import to_time_series
label_desc: Use image node_id 9 for calling a global function with example usage: test_dtw_subseq_path() without return types