code: def test_horizontal_certical_maps(
      self, in_type, arguments, mask, hv_mask
  ):
      hv_key = list(hv_mask.keys())[0]
      input_image = {}
      for k in mask.keys():
          input_image[k] = in_type(mask[k])
      result = ComputeHoVerMapsd(keys="mask", **arguments)(input_image)[
          hv_key
      ]
      self.assertTrue(isinstance(result, torch.Tensor))
      self.assertTrue(
          str(result.dtype).split(".")[1]
          == arguments.get("dtype", "float32")
      )
      assert_allclose(result, hv_mask[hv_key], type_test="tensor")
  
file_path: MONAI/tests/test_compute_ho_ver_maps_d.py
imports: from __future__ import annotations
  import unittest
  import numpy
  import torch
  from parameterized import parameterized
  from monai.transforms.intensity.dictionary import ComputeHoVerMapsd
  from monai.utils import min_version, optional_import
  from tests.utils import TEST_NDARRAYS, assert_allclose
label_desc: Use image node_id 1 for calling the ComputeHoVerMapsDictTests obj's underlying member method code with example usage: obj.test_horizontal_certical_maps(in_type, arguments, mask, hv_mask) without return types