Transpose nifti on read

elf/io/nifti_wrapper.py

@@ -1,4 +1,5 @@
 from collections.abc import Mapping
+from ..util import normalize_index, squeeze_singletons
 
 import numpy as np
 try:
@@ -60,10 +61,13 @@ def chunks(self):
 
     @property
     def shape(self):
-        return self._data.shape
+        return self._data.shape[::-1]
 
     def __getitem__(self, key):
-        return self._data.dataobj[key]
+        key, to_squeeze = normalize_index(key, self.shape)
+        transposed_key = key[::-1]
+        data = self._data.dataobj[transposed_key].T
+        return squeeze_singletons(data, to_squeeze)
 
     @property
     def size(self):

test/io_tests/test_nifti_wrapper.py

@@ -20,7 +20,7 @@ def _check_data(self, expected_data, f):
         shape = dset.shape
 
         #  bounding boxes for testing sub-sampling
-        bbs = [np.s_[:]]
+        bbs = [0, np.s_[:]]
         for i in range(dset.ndim):
             bbs.extend([
                 tuple(slice(0, shape[i] // 2) if d == i else slice(None) for d in range(dset.ndim)),
@@ -39,7 +39,7 @@ def test_read_nifti(self):
 
         paths = glob(os.path.join(data_path, "*.nii"))
         for path in paths:
-            expected_data = np.asarray(nibabel.load(path).dataobj)
+            expected_data = np.asarray(nibabel.load(path).dataobj).T
             # the resampled image causes errors
             if os.path.basename(path).startswith("resampled"):
                 continue
@@ -52,7 +52,7 @@ def test_read_nifti_compressed(self):
 
         paths = glob(os.path.join(data_path, "*.nii.gz"))
         for path in paths:
-            expected_data = np.asarray(nibabel.load(path).dataobj)
+            expected_data = np.asarray(nibabel.load(path).dataobj).T
             with open_file(path, "r") as f:
                 self._check_data(expected_data, f)