Try again, this time with lists and more tests...

Author: Ben Cipollini

nibabel/funcs.py

@@ -117,19 +117,18 @@ def concat_images(images, check_affines=True, axis=None):
     affine = img0.affine
     header = img0.header
     out_shape = (n_imgs, ) + i0shape
-    out_data = np.empty(out_shape)
+    out_data = []
     for i, img in enumerate(images):
         if is_filename:
             img = load(img)
         if check_affines:
             if not np.all(img.affine == affine):
                 raise ValueError('Affines do not match')
-        out_data[i] = img.get_data().copy()
+        out_data.append(img.get_data())
     if axis is not None:
         out_data = np.concatenate(out_data, axis=axis)
-    elif np.all([d.shape[-1] == 1 for d in out_data]):
-        out_data = np.concatenate(out_data, axis=d.ndim-1)
     else:
+        out_data = np.asarray(out_data)
         out_data = np.rollaxis(out_data, 0, len(i0shape)+1)
     klass = img0.__class__
     return klass(out_data, affine, header)

nibabel/tests/test_funcs.py

@@ -66,16 +66,35 @@ def test_concat():
     img0_mem = Nifti1Image(data0, affine)
     img1_mem = Nifti1Image(data0 - 10, affine)
 
-    concat_img1 = concat_images([img0_mem, img1_mem])
+    # 4d, same shape, append on axis 3
+    concat_img1 = concat_images([img0_mem, img1_mem], axis=3)
     expected_shape1 = shape_4D.copy()
     expected_shape1[-1] *= 2
     assert_array_equal(concat_img1.shape, expected_shape1)
 
+    # 4d, same shape, append on axis 0
     concat_img2 = concat_images([img0_mem, img1_mem], axis=0)
     expected_shape2 = shape_4D.copy()
     expected_shape2[0] *= 2
     assert_array_equal(concat_img2.shape, expected_shape2)
 
+    # 4d, same shape, append on axis -1
+    concat_img3 = concat_images([img0_mem, img1_mem], axis=-1)
+    expected_shape3 = shape_4D.copy()
+    expected_shape3[-1] *= 2
+    assert_array_equal(concat_img3.shape, expected_shape3)
+
+    # 4d, different shape, append on axis that's different
+    print('%s %s' % (str(concat_img3.shape), str(img1_mem.shape)))
+    concat_img4 = concat_images([concat_img3, img1_mem], axis=-1)
+    expected_shape4 = shape_4D.copy()
+    expected_shape4[-1] *= 3
+    assert_array_equal(concat_img4.shape, expected_shape4)
+
+    # 4d, different shape, append on axis that's not different...
+    # Doesn't work!
+    assert_raises(ValueError, concat_images, [concat_img3, img1_mem], axis=1)
+
 
 def test_closest_canonical():
     arr = np.arange(24).reshape((2,3,4,1))