From 25fae0f5202d09229d8065ace6518a8818774edd Mon Sep 17 00:00:00 2001
From: Mohammad Adil <madil@nvidia.com>
Date: Thu, 27 Feb 2020 17:51:35 -0800
Subject: [PATCH] Adding rotation transform.

---
 monai/transforms/transforms.py | 37 ++++++++++++++++++++++++++++++
 requirements.txt               |  1 +
 tests/test_rotate.py           | 41 ++++++++++++++++++++++++++++++++++
 3 files changed, 79 insertions(+)
 create mode 100644 tests/test_rotate.py

diff --git a/monai/transforms/transforms.py b/monai/transforms/transforms.py
index dc6f571106..454c3aa7f6 100644
--- a/monai/transforms/transforms.py
+++ b/monai/transforms/transforms.py
@@ -15,6 +15,7 @@
 
 import numpy as np
 import torch
+import scipy.ndimage
 
 import monai
 from monai.data.utils import get_random_patch, get_valid_patch_size
@@ -80,6 +81,42 @@ def __call__(self, img):
         return np.flip(img, self.axis)
 
 
+@export
+class Rotate:
+    """
+    Rotates an input image by given angle. Uses scipy.ndimage.rotate. For more details, see
+    http://lagrange.univ-lyon1.fr/docs/scipy/0.17.1/generated/scipy.ndimage.rotate.html.
+
+    Args:
+        angle (float): Rotation angle in degrees.
+        axes (tuple of 2 ints): Axes of rotation. Default: (1, 2). This is the first two
+            axis in spatial dimensions according to MONAI channel first shape assumption.
+        reshape (bool): If true, output shape is made same as input. Default: True.
+        order (int): Order of spline interpolation. Range 0-5. Default: 1. This is
+            different from scipy where default interpolation is 3.
+        mode (str): Points outside boundary filled according to this mode. Options are 
+            'constant', 'nearest', 'reflect', 'wrap'. Default: 'constant'.
+        cval (scalar): Values to fill outside boundary. Default: 0.
+        prefiter (bool): Apply spline_filter before interpolation. Default: True.
+    """
+
+    def __init__(self, angle, axes=(1, 2), reshape=True, order=1, 
+                 mode='constant', cval=0, prefilter=True):
+        self.angle = angle
+        self.reshape = reshape
+        self.order = order
+        self.mode = mode
+        self.cval = cval
+        self.prefilter = prefilter
+        self.axes = axes
+
+    def __call__(self, img):
+        return scipy.ndimage.rotate(img, self.angle, self.axes,
+                                    reshape=self.reshape, order=self.order, 
+                                    mode=self.mode, cval=self.cval, 
+                                    prefilter=self.prefilter)
+
+
 @export
 class ToTensor:
     """
diff --git a/requirements.txt b/requirements.txt
index 8325300968..91985396c3 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -7,3 +7,4 @@ coverage
 nibabel
 parameterized
 tensorboard
+scipy
\ No newline at end of file
diff --git a/tests/test_rotate.py b/tests/test_rotate.py
new file mode 100644
index 0000000000..98e25f587f
--- /dev/null
+++ b/tests/test_rotate.py
@@ -0,0 +1,41 @@
+# Copyright 2020 MONAI Consortium
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#     http://www.apache.org/licenses/LICENSE-2.0
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import unittest
+import numpy as np
+
+import scipy.ndimage
+from parameterized import parameterized
+
+from monai.transforms import Rotate
+from tests.utils import NumpyImageTestCase2D
+
+
+class RotateTest(NumpyImageTestCase2D):
+
+    @parameterized.expand([
+        (90, (1, 2), True, 1, 'reflect', 0, True),
+        (-90, (2, 1), True, 3, 'constant', 0, True),
+        (180, (2, 3), False, 2, 'constant', 4, False),
+    ])
+    def test_correct_results(self, angle, axes, reshape, 
+                             order, mode, cval, prefilter):
+        rotate_fn = Rotate(angle, axes, reshape, 
+                           order, mode, cval, prefilter)
+        rotated = rotate_fn(self.imt)
+
+        expected = scipy.ndimage.rotate(self.imt, angle, axes, reshape, order=order,
+                                        mode=mode, cval=cval, prefilter=prefilter)
+        self.assertTrue(np.allclose(expected, rotated))
+
+
+if __name__ == '__main__':
+    unittest.main()