code: def difference_test():
      """Test the distance functions with allowable input.
  
      TEST 1: Distances. Generate all distances with tsml, compare.
      TEST 2: Classification.
      TEST 3: Clustering.
      TEST 4: tslearn
      """
      X_train, y_train = load_unit_test(
          split="train", return_type="numpy3d"
      )
      d1 = X_train[0]
      d2 = X_train[2]
      dist = erp_distance
      #    d1=np.transpose(d1)
      #    d2=np.transpose(d2)
      print("Shape  = ", d1.shape)
      name = "LCSS"
      no_window = np.zeros((d1.shape[1], d2.shape[1]))
      # "wi [0.0, 0.1, 1.0],  # window
      dist1 = dist(d1, d2, window=0.0)
      print(name, " w = 0 dist = ", dist1)
      dist1 = dist(d1, d2, window=0.1)
      print(name, " w = 0.1. dist 1 = ", dist1)
      dist1 = dist(d1, d2, window=1.0)
      print(name, " w = 1 dist 1 = ", dist1)
      print(" SHAPE  = ", d1.shape)
      X_train, y_train = load_basic_motions(
          split="train", return_type="numpy3d"
      )
      b1 = X_train[0]
      b2 = X_train[1]
      #    b1 = np.transpose(b1)
      #    b2 = np.transpose(b2)
      dist = dtw_distance
      print("BM shape = ", b1.shape)
      dist2 = dist(b1, b2, epsilon=0.0)
      print(" g = 0.0, BASIC MOTIONS DIST = ", dist2)
      dist2 = dist(b1, b2, epsilon=1.0)
      print(" g = 0.1, BASIC MOTIONS DIST = ", dist2)
      dist2 = dist(b1, b2, epsilon=4.0)
      print(" g = 1, BASIC MOTIONS DIST = ", dist2)
  
file_path: sktime/sktime/_contrib/distance_refactor.py
imports: import numpy
  from sklearn import metrics
  from sktime.clustering.k_means import TimeSeriesKMeans
  from sktime.datasets import load_arrow_head, load_basic_motions, load_unit_test
  from sktime.distances import ddtw_distance, dtw_distance, edr_distance, erp_distance, euclidean_distance, lcss_distance, msm_distance, wddtw_distance, wdtw_distance
  from sktime.distances.tests._utils import create_test_distance_numpy
  from sktime.clustering.utils.plotting._plot_partitions import plot_cluster_algorithm
  from sklearn.preprocessing import StandardScaler, normalize
label_desc: Use image node_id 4 for calling a global function with example usage: difference_test() without return types