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Add warning in RandHistogramShift #5877

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Merged
wyli merged 3 commits into from
Jan 19, 2023
Merged

Add warning in RandHistogramShift #5877

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f6cb06a
add warn in `RandHistogramShift`
KumoLiu Jan 19, 2023
0a6d454
minor fix
KumoLiu Jan 19, 2023
fecf8f8
add unit test
KumoLiu Jan 19, 2023
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8 changes: 7 additions & 1 deletion monai/transforms/intensity/array.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1468,9 +1468,15 @@ def __call__(self, img: NdarrayOrTensor, randomize: bool = True) -> NdarrayOrTen
if self.reference_control_points is None or self.floating_control_points is None:
raise RuntimeError("please call the `randomize()` function first.")
img_t = convert_to_tensor(img, track_meta=False)
img_min, img_max = img_t.min(), img_t.max()
if img_min == img_max:
warn(
f"The image's intensity is a single value {img_min}. "
"The original image is simply returned, no histogram shift is done."
)
return img
xp, *_ = convert_to_dst_type(self.reference_control_points, dst=img_t)
yp, *_ = convert_to_dst_type(self.floating_control_points, dst=img_t)
img_min, img_max = img_t.min(), img_t.max()
reference_control_points_scaled = xp * (img_max - img_min) + img_min
floating_control_points_scaled = yp * (img_max - img_min) + img_min
img_t = self.interp(img_t, reference_control_points_scaled, floating_control_points_scaled)
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16 changes: 16 additions & 0 deletions tests/test_rand_histogram_shift.py
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Original file line number Diff line number Diff line change
Expand Up @@ -44,6 +44,16 @@
]
)

WARN_TESTS = []
for p in TEST_NDARRAYS:
WARN_TESTS.append(
[
{"num_control_points": 5, "prob": 1.0},
{"img": p(np.zeros(8).reshape((1, 2, 2, 2)))},
np.zeros(8).reshape((1, 2, 2, 2)),
]
)


class TestRandHistogramShift(unittest.TestCase):
@parameterized.expand(TESTS)
Expand Down Expand Up @@ -71,6 +81,12 @@ def test_interp(self):
self.assertEqual(yi.shape, (3, 2))
assert_allclose(yi, array_type([[1.0, 5.0], [0.5, -0.5], [4.0, 5.0]]))

@parameterized.expand(WARN_TESTS)
def test_warn(self, input_param, input_data, expected_val):
with self.assertWarns(Warning):
result = RandHistogramShift(**input_param)(**input_data)
assert_allclose(result, expected_val, type_test="tensor")


if __name__ == "__main__":
unittest.main()