code: def test_func(self):
      transform = UltrasoundConfidenceMapTransform(
          alpha=2.0, beta=90.0, gamma=0.05, mode="B", sink_mode="all"
      )
      output = transform(self.input_img_np)
      assert_allclose(output, SINK_ALL_OUTPUT, rtol=1e-4, atol=1e-4)
  
      transform = UltrasoundConfidenceMapTransform(
          alpha=2.0, beta=90.0, gamma=0.05, mode="B", sink_mode="mid"
      )
      output = transform(self.input_img_np)
      assert_allclose(output, SINK_MID_OUTPUT, rtol=1e-4, atol=1e-4)
  
      transform = UltrasoundConfidenceMapTransform(
          alpha=2.0, beta=90.0, gamma=0.05, mode="B", sink_mode="min"
      )
      output = transform(self.input_img_np)
      assert_allclose(output, SINK_MIN_OUTPUT, rtol=1e-4, atol=1e-4)
  
      transform = UltrasoundConfidenceMapTransform(
          alpha=2.0, beta=90.0, gamma=0.05, mode="B", sink_mode="mask"
      )
      output = transform(self.input_img_np, self.input_mask_np)
      assert_allclose(output, SINK_MASK_OUTPUT, rtol=1e-4, atol=1e-4)
  
      transform = UltrasoundConfidenceMapTransform(
          alpha=2.0, beta=90.0, gamma=0.05, mode="B", sink_mode="all"
      )
      output = transform(self.input_img_torch)
      assert_allclose(
          output, torch.tensor(SINK_ALL_OUTPUT), rtol=1e-4, atol=1e-4
      )
  
      transform = UltrasoundConfidenceMapTransform(
          alpha=2.0, beta=90.0, gamma=0.05, mode="B", sink_mode="mid"
      )
      output = transform(self.input_img_torch)
      assert_allclose(
          output, torch.tensor(SINK_MID_OUTPUT), rtol=1e-4, atol=1e-4
      )
  
      transform = UltrasoundConfidenceMapTransform(
          alpha=2.0, beta=90.0, gamma=0.05, mode="B", sink_mode="min"
      )
      output = transform(self.input_img_torch)
      assert_allclose(
          output, torch.tensor(SINK_MIN_OUTPUT), rtol=1e-4, atol=1e-4
      )
  
      transform = UltrasoundConfidenceMapTransform(
          alpha=2.0, beta=90.0, gamma=0.05, mode="B", sink_mode="mask"
      )
      output = transform(self.input_img_torch, self.input_mask_torch)
      assert_allclose(
          output, torch.tensor(SINK_MASK_OUTPUT), rtol=1e-4, atol=1e-4
      )
  
file_path: MONAI/tests/test_ultrasound_confidence_map_transform.py
imports: from __future__ import annotations
  import unittest
  import numpy
  import torch
  from monai.transforms import UltrasoundConfidenceMapTransform
  from tests.utils import assert_allclose
label_desc: Use image node_id 11 for calling the TestUltrasoundConfidenceMapTransform obj's underlying member method code with example usage: obj.test_func() without return types