code: def test_lcss():
      for be in backends:
          for array_type in array_types:
              sim = tslearn.metrics.lcss(
                  cast([1, 2, 3], array_type),
                  cast([1.0, 2.0, 2.0, 3.0], array_type),
                  be=be,
              )
              np.testing.assert_equal(sim, 1.0)
              assert isinstance(sim, float)
  
              sim = tslearn.metrics.lcss(
                  [1, 2, 3], [1.0, 2.0, 2.0, 4.0], be=be
              )
              np.testing.assert_equal(sim, 1.0)
  
              sim = tslearn.metrics.lcss(
                  [1, 2, 3], [-2.0, 5.0, 7.0], eps=3, be=be
              )
              np.testing.assert_equal(round(sim, 2), 0.67)
  
              sim = tslearn.metrics.lcss(
                  [1, 2, 3], [1.0, 2.0, 2.0, 2.0, 3.0], eps=0, be=be
              )
              np.testing.assert_equal(sim, 1.0)
  
              sim = tslearn.metrics.lcss(
                  [[1, 1], [2, 2], [3, 3]],
                  [
                      [1.0, 1.0],
                      [2.0, 2.0],
                      [2.0, 2.0],
                      [2.0, 2.0],
                      [3.0, 3.0],
                  ],
                  eps=0,
                  be=be,
              )
              np.testing.assert_equal(sim, 1.0)
  
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 4 for calling a global function with example usage: test_lcss() without return types