TEST: use new resample module

tests/test_atlases.py

@@ -17,9 +17,10 @@ import mock
 import pytest
 
 import tests
-import fsl.utils.transform as transform
-import fsl.data.atlases    as atlases
-import fsl.data.image      as fslimage
+import fsl.utils.transform      as transform
+import fsl.utils.image.resample as resample
+import fsl.data.atlases         as atlases
+import fsl.data.image           as fslimage
 
 
 datadir = op.join(op.dirname(__file__), 'testdata')
@@ -286,7 +287,7 @@ def test_prepareMask():
             np.array(np.random.random(ashape), dtype=np.float32),
             xform=atlas.voxToWorldMat)
 
-        goodmask2, xf = goodmask1.resample(m2shape)
+        goodmask2, xf = resample.resample(goodmask1, m2shape)
         goodmask2     = fslimage.Image(goodmask2, xform=xf)
 
         wrongdims     = fslimage.Image(

tests/test_atlases_query.py

@@ -14,6 +14,7 @@ import                    pytest
 import fsl.data.atlases    as fslatlases
 import fsl.data.image      as fslimage
 import fsl.utils.transform as transform
+import fsl.utils.image.resample as resample
 import fsl.utils.cache     as cache
 
 from . import (testdir, make_random_mask)
@@ -256,7 +257,8 @@ def _gen_mask_query(atlas, qtype, qin, maskres):
         # aggresively to make sure there
         # is no overlap between the different
         # resolutions
-        mask, xform = mask.resample(a.shape[:3], dtype=np.float32, order=1)
+        mask, xform = resample.resample(
+            mask, a.shape[:3], dtype=np.float32, order=1)
 
         mask[mask   < 1.0] = 0
         mask[a_zmask == 0] = 0
@@ -279,7 +281,8 @@ def _eval_mask_query(atlas, query, qtype, qin):
     if maskres == res:
         rmask = mask[:]
     else:
-        rmask = mask.resample(atlas.shape[:3], dtype=np.float32, order=0)[0]
+        rmask = resample.resample(
+            mask, atlas.shape[:3], dtype=np.float32, order=0)[0]
 
     rmask = np.array(rmask, dtype=np.bool)
 

tests/test_scripts/test_atlasq_query.py

@@ -16,6 +16,7 @@ import scipy.ndimage as ndi
 import                  pytest
 
 import fsl.utils.transform as transform
+import fsl.utils.image.resample as resample
 import fsl.data.atlases    as fslatlases
 import fsl.data.image      as fslimage
 import fsl.scripts.atlasq  as fslatlasq
@@ -329,7 +330,8 @@ def _gen_mask_query(atlas, use_label, q_type, q_in, res):
             # resampled into the atlas resolution,
             # it is still either in or out of the
             # atlas space
-            mask, xform = mask.resample(a.shape[:3], dtype=np.float32, order=1)
+            mask, xform = resample.resample(
+                mask, a.shape[:3], dtype=np.float32, order=1)
 
             thres = np.percentile(mask[mask > 0], 75)