code: def test_unsharp_masking_dtypes(shape, channel_axis, preserve, dtype):
      radius = 2.0
      amount = 1.0
      array = (np.random.random(shape) * 10).astype(dtype, copy=False)
      negative = np.any(array < 0)
      output = unsharp_mask(
          array,
          radius,
          amount,
          preserve_range=preserve,
          channel_axis=channel_axis,
      )
      if preserve is False:
          assert np.any(output <= 1)
          assert np.any(output >= -1)
          if negative is False:
              assert np.any(output >= 0)
      assert output.dtype == _supported_float_type(dtype)
      assert output.shape == shape
  
file_path: scikit-image/skimage/filters/tests/test_unsharp_mask.py
imports: import numpy
  import pytest
  from skimage._shared.utils import _supported_float_type
  from skimage.filters import unsharp_mask
label_desc: Use image node_id 5 for calling a global function with example usage: test_unsharp_masking_dtypes(shape, channel_axis, preserve, dtype) without return types