code: def _test_pw_equal_single_dists(
      x: np.ndarray,
      y: np.ndarray,
      distance_function: Callable,
      conical_name: str,
  ) -> None:
      """Test pairwise result is equal to individual distance.
  
      Parameters
      ----------
      x: np.ndarray (1d, 2d or 3d array)
          First time series
      y: np.ndarray (1d, 2d or 3d array)
          Second time series
      distance_function: Callable
          Distance function to test
      conical_name: str
          Name of the metric
      """
      if x.ndim < 2:
          return
  
      # use euclidean distance so this test will fail
      if (
          conical_name == "lcss"
          or conical_name == "edr"
          or conical_name == "erp"
      ):
          return
      pw_result = pairwise_distance(x, y, metric=conical_name)
  
      x = _make_3d_series(x)
      y = _make_3d_series(y)
  
      matrix = np.zeros((len(x), len(y)))
  
      for i in range(len(x)):
          curr_x = x[i]
          for j in range(len(y)):
              curr_y = y[j]
              matrix[i, j] = distance_function(curr_x, curr_y)
  
      assert np.allclose(matrix, pw_result)
  
file_path: sktime/sktime/distances/tests/test_pairwise_distances.py
imports: from typing import Callable
  import numpy
  import pytest
  from sktime.distances._distance import _METRIC_INFOS, pairwise_distance
  from sktime.distances._numba_utils import _make_3d_series
  from sktime.distances.base import MetricInfo, NumbaDistance
  from sktime.distances.tests._shared_tests import _test_incorrect_parameters, _test_metric_parameters
  from sktime.distances.tests._utils import create_test_distance_numpy
  from sktime.utils.validation._dependencies import _check_soft_dependencies
label_desc: Use image node_id 3 for calling a global function with example usage: _test_pw_equal_single_dists(x, y, distance_function, conical_name) without return types