ShiftIntensityd, RandShiftIntensityd

monai/transforms/intensity/dictionary.py

@@ -245,6 +245,8 @@ class ShiftIntensityd(MapTransform):
     Dictionary-based wrapper of :py:class:`monai.transforms.ShiftIntensity`.
     """
 
+    backend = ShiftIntensity.backend
+
     def __init__(
         self,
         keys: KeysCollection,
@@ -283,7 +285,7 @@ def __init__(
         self.meta_key_postfix = ensure_tuple_rep(meta_key_postfix, len(self.keys))
         self.shifter = ShiftIntensity(offset)
 
-    def __call__(self, data) -> Dict[Hashable, np.ndarray]:
+    def __call__(self, data) -> Dict[Hashable, NdarrayOrTensor]:
         d = dict(data)
         for key, factor_key, meta_key, meta_key_postfix in self.key_iterator(
             d, self.factor_key, self.meta_keys, self.meta_key_postfix
@@ -300,6 +302,8 @@ class RandShiftIntensityd(RandomizableTransform, MapTransform):
     Dictionary-based version :py:class:`monai.transforms.RandShiftIntensity`.
     """
 
+    backend = ShiftIntensity.backend
+
     def __init__(
         self,
         keys: KeysCollection,
@@ -355,7 +359,7 @@ def randomize(self, data: Optional[Any] = None) -> None:
         self._offset = self.R.uniform(low=self.offsets[0], high=self.offsets[1])
         super().randomize(None)
 
-    def __call__(self, data) -> Dict[Hashable, np.ndarray]:
+    def __call__(self, data) -> Dict[Hashable, NdarrayOrTensor]:
         d = dict(data)
         self.randomize()
         if not self._do_transform:

tests/test_rand_shift_intensityd.py

@@ -14,18 +14,19 @@
 import numpy as np
 
 from monai.transforms import IntensityStatsd, RandShiftIntensityd
-from tests.utils import NumpyImageTestCase2D
+from tests.utils import TEST_NDARRAYS, NumpyImageTestCase2D, assert_allclose
 
 
 class TestRandShiftIntensityd(NumpyImageTestCase2D):
     def test_value(self):
-        key = "img"
-        shifter = RandShiftIntensityd(keys=[key], offsets=1.0, prob=1.0)
-        shifter.set_random_state(seed=0)
-        result = shifter({key: self.imt})
-        np.random.seed(0)
-        expected = self.imt + np.random.uniform(low=-1.0, high=1.0)
-        np.testing.assert_allclose(result[key], expected)
+        for p in TEST_NDARRAYS:
+            key = "img"
+            shifter = RandShiftIntensityd(keys=[key], offsets=1.0, prob=1.0)
+            shifter.set_random_state(seed=0)
+            result = shifter({key: p(self.imt)})
+            np.random.seed(0)
+            expected = self.imt + np.random.uniform(low=-1.0, high=1.0)
+            assert_allclose(result[key], expected)
 
     def test_factor(self):
         key = "img"

tests/test_shift_intensityd.py

@@ -14,16 +14,17 @@
 import numpy as np
 
 from monai.transforms import IntensityStatsd, ShiftIntensityd
-from tests.utils import NumpyImageTestCase2D
+from tests.utils import TEST_NDARRAYS, NumpyImageTestCase2D, assert_allclose
 
 
 class TestShiftIntensityd(NumpyImageTestCase2D):
     def test_value(self):
         key = "img"
-        shifter = ShiftIntensityd(keys=[key], offset=1.0)
-        result = shifter({key: self.imt})
-        expected = self.imt + 1.0
-        np.testing.assert_allclose(result[key], expected)
+        for p in TEST_NDARRAYS:
+            shifter = ShiftIntensityd(keys=[key], offset=1.0)
+            result = shifter({key: p(self.imt)})
+            expected = self.imt + 1.0
+            assert_allclose(result[key], expected)
 
     def test_factor(self):
         key = "img"