code: def test_hausdorff_region_different_points(points_a, points_b):
      shape = (7, 7)
      coords_a = np.zeros(shape, dtype=bool)
      coords_b = np.zeros(shape, dtype=bool)
      coords_a[points_a] = True
      coords_b[points_b] = True
  
      dist = np.sqrt(
          sum((ca - cb) ** 2 for ca, cb in zip(points_a, points_b))
      )
      d = distance.cdist([points_a], [points_b])
      dist_modified = max(
          np.mean(np.min(d, axis=0)), np.mean(np.min(d, axis=1))
      )
      assert_almost_equal(hausdorff_distance(coords_a, coords_b), dist)
      assert_array_equal(
          hausdorff_pair(coords_a, coords_b), (points_a, points_b)
      )
      assert_almost_equal(
          hausdorff_distance(coords_a, coords_b, method="modified"),
          dist_modified,
      )
  
file_path: scikit-image/skimage/metrics/tests/test_set_metrics.py
imports: import numpy
  import pytest
  from numpy.testing import assert_almost_equal, assert_array_equal
  from scipy.spatial import distance
  from skimage._shared._warnings import expected_warnings
  from skimage.metrics import hausdorff_distance, hausdorff_pair
label_desc: Use image node_id 4 for calling a global function with example usage: test_hausdorff_region_different_points(points_a, points_b) without return types