code: def test_compute_distance(self):
      x1 = np.array([1, 0, 1])
      x2 = np.array([0, 0, 1])
      mean_vector = np.array([2, 1, 3])
      epsilon = 0
      expected = 0.5
      t = _compute_distance(x1, x2, mean_vector, epsilon)
      assert t == expected
  
file_path: shapash/tests/unit_tests/utils/test_explanation_metrics.py
imports: import unittest
  import numpy
  import pandas
  from sklearn.linear_model import LinearRegression
  from shapash.utils.explanation_metrics import _df_to_array, _compute_distance, _compute_similarities, _get_radius, find_neighbors, shap_neighbors, get_min_nb_features, get_distance
label_desc: Use image node_id 2 for calling the TestExplanationMetrics obj's underlying member method code with example usage: obj.test_compute_distance() without return types