78 lines
2.4 KiB
Python
78 lines
2.4 KiB
Python
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import numpy as np
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from skimage import dtype_limits
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from skimage.util.dtype import dtype_range
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from skimage.util import invert
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from skimage._shared.testing import assert_array_equal
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def test_invert_bool():
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dtype = 'bool'
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image = np.zeros((3, 3), dtype=dtype)
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upper_dtype_limit = dtype_limits(image, clip_negative=False)[1]
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image[1, :] = upper_dtype_limit
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expected = np.zeros((3, 3), dtype=dtype) + upper_dtype_limit
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expected[1, :] = 0
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result = invert(image)
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assert_array_equal(expected, result)
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def test_invert_uint8():
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dtype = 'uint8'
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image = np.zeros((3, 3), dtype=dtype)
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upper_dtype_limit = dtype_limits(image, clip_negative=False)[1]
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image[1, :] = upper_dtype_limit
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expected = np.zeros((3, 3), dtype=dtype) + upper_dtype_limit
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expected[1, :] = 0
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result = invert(image)
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assert_array_equal(expected, result)
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def test_invert_int8():
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dtype = 'int8'
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image = np.zeros((3, 3), dtype=dtype)
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lower_dtype_limit, upper_dtype_limit = \
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dtype_limits(image, clip_negative=False)
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image[1, :] = lower_dtype_limit
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image[2, :] = upper_dtype_limit
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expected = np.zeros((3, 3), dtype=dtype)
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expected[2, :] = lower_dtype_limit
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expected[1, :] = upper_dtype_limit
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expected[0, :] = -1
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result = invert(image)
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assert_array_equal(expected, result)
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def test_invert_float64_signed():
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dtype = 'float64'
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image = np.zeros((3, 3), dtype=dtype)
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lower_dtype_limit, upper_dtype_limit = \
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dtype_limits(image, clip_negative=False)
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image[1, :] = lower_dtype_limit
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image[2, :] = upper_dtype_limit
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expected = np.zeros((3, 3), dtype=dtype)
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expected[2, :] = lower_dtype_limit
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expected[1, :] = upper_dtype_limit
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result = invert(image, signed_float=True)
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assert_array_equal(expected, result)
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def test_invert_float64_unsigned():
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dtype = 'float64'
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image = np.zeros((3, 3), dtype=dtype)
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lower_dtype_limit, upper_dtype_limit = \
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dtype_limits(image, clip_negative=True)
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image[2, :] = upper_dtype_limit
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expected = np.zeros((3, 3), dtype=dtype)
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expected[0, :] = upper_dtype_limit
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expected[1, :] = upper_dtype_limit
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result = invert(image)
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assert_array_equal(expected, result)
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def test_invert_roundtrip():
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for t, limits in dtype_range.items():
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image = np.array(limits, dtype=t)
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expected = invert(invert(image))
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assert_array_equal(image, expected)
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