TEST: Expand resample tests

tests/test_image_resample.py

@@ -2,7 +2,6 @@
 
 
 import itertools as it
-import os.path   as op
 import numpy     as np
 
 import pytest
@@ -10,24 +9,17 @@ import pytest
 import fsl.data.image           as     fslimage
 import fsl.utils.transform      as     transform
 import fsl.utils.image.resample as     resample
-from   fsl.utils.tempdir        import tempdir
-
 
 from . import make_random_image
 
 
 def test_resample(seed):
 
-    with tempdir() as td:
-
-        fname = op.join(td, 'test.nii')
-
     # Random base image shapes
     for i in range(25):
 
         shape = np.random.randint(5, 50, 3)
-            make_random_image(fname, shape)
-            img = fslimage.Image(fname, mmap=False)
+        img = fslimage.Image(make_random_image(dims=shape))
 
         # bad shape
         with pytest.raises(ValueError):
@@ -46,10 +38,6 @@ def test_resample(seed):
             rshape        = np.random.randint(5, 50, 3)
             resampled, xf = resample.resample(img, rshape, order=0)
 
-                img.save('base.nii.gz')
-                fslimage.Image(resampled, xform=xf,
-                               mmap=False).save('res.nii.gz')
-
             assert tuple(resampled.shape) == tuple(rshape)
 
             # We used nearest neighbour interp, so the
@@ -91,20 +79,11 @@ def test_resample(seed):
 
             assert np.all(np.isclose(resvals, origvals))
 
-        del img
-        img = None
-
 
 def test_resample_4d(seed):
 
-    fname = 'test.nii.gz'
-
-    with tempdir():
-
-        make_random_image(fname, (10, 10, 10, 10))
-
     # resample one volume
-        img = fslimage.Image(fname)
+    img = fslimage.Image(make_random_image(dims=(10, 10, 10, 10)))
     slc = (slice(None), slice(None), slice(None), 3)
     resampled = resample.resample(img, img.shape[:3], slc)[0]
     assert np.all(resampled == img[..., 3])
@@ -131,18 +110,10 @@ def test_resample_4d(seed):
     resampled = resample.resample(img, (5, 5, 5, 15), None)[0]
     assert tuple(resampled.shape) == (5, 5, 5, 15)
 
-        del img
-        del resampled
-        img = None
-        resampled = None
-
 
 def test_resample_origin(seed):
-    with tempdir() as td:
-        fname = op.join(td, 'test.nii')
 
-        make_random_image(fname, (10, 10, 10))
-        img = fslimage.Image(fname)
+    img = fslimage.Image(make_random_image(dims=(10, 10, 10)))
 
     # with origin='corner', image
     # bounding boxes should match
@@ -183,8 +154,72 @@ def test_resample_origin(seed):
 
 
 def test_resampleToPixdims():
-    pass
+
+    img          = fslimage.Image(make_random_image(dims=(10, 10, 10)))
+    imglo, imghi = transform.axisBounds(img.shape, img.voxToWorldMat)
+    oldpix       = np.array(img.pixdim, dtype=np.float)
+    oldshape     = np.array(img.shape,  dtype=np.float)
+
+    for i, origin in it.product(range(25), ('centre', 'corner')):
+
+        # random pixdims in the range 0.1 - 5.0
+        newpix   = 0.1 + 4.9 * np.random.random(3)
+        expshape = np.round(oldshape * (oldpix / newpix))
+
+        res = resample.resampleToPixdims(img, newpix, origin=origin)
+        res = fslimage.Image(res[0], xform=res[1])
+        reslo, reshi = transform.axisBounds(res.shape, res.voxToWorldMat)
+        resfov       = reshi - reslo
+        expfov       = newpix * res.shape
+
+        assert np.all(np.isclose(res.shape,  expshape))
+        assert np.all(np.isclose(res.pixdim, newpix))
+        assert np.all(np.isclose(resfov, expfov, rtol=1e-2, atol=1e-2))
+
+        if origin == 'corner':
+            assert np.all(np.isclose(imglo, reslo))
+            assert np.all(np.isclose(reshi, reslo + expfov,
+                                     rtol=1e-2, atol=1e-2))
+
 
 
 def test_resampleToReference():
-    pass
+
+    def random_v2w():
+        return transform.compose(
+            0.25   + 4.75      * np.random.random(3),
+            -50    + 100       * np.random.random(3),
+            -np.pi + 2 * np.pi * np.random.random(3))
+
+    # Basic test - output has same
+    # dimensions/space as reference
+    for i in range(25):
+
+        ishape = np.random.randint(5, 50, 3)
+        rshape = np.random.randint(5, 50, 3)
+        iv2w   = random_v2w()
+        rv2w   = random_v2w()
+        img    = fslimage.Image(make_random_image(dims=ishape, xform=iv2w))
+        ref    = fslimage.Image(make_random_image(dims=rshape, xform=rv2w))
+        res    = resample.resampleToReference(img, ref)
+        res    = fslimage.Image(res[0], header=ref.header)
+
+        assert res.sameSpace(ref)
+
+    # More specific test - output
+    # data gets transformed correctly
+    # into reference space
+
+    img          = np.zeros((5, 5, 5), dtype=np.float)
+    img[1, 1, 1] = 1
+    img          = fslimage.Image(img)
+
+    refv2w = transform.scaleOffsetXform([1, 1, 1], [-1, -1, -1])
+    ref    = np.zeros((5, 5, 5), dtype=np.float)
+    ref    = fslimage.Image(ref, xform=refv2w)
+    res    = resample.resampleToReference(img, ref, order=0)
+
+    exp          = np.zeros((5, 5, 5), dtype=np.float)
+    exp[2, 2, 2] = 1
+
+    assert np.all(np.isclose(res[0], exp))