fix(AFNI): load arrays of linear transforms - one less XFail (#40)

Author: oesteban

nitransforms/io/afni.py

@@ -9,6 +9,7 @@
     DisplacementsField,
     LinearParameters,
     TransformFileError,
+    _ensure_image,
 )
 
 LPS = np.diag([-1, -1, 1, 1])
@@ -38,15 +39,22 @@ def from_ras(cls, ras, moving=None, reference=None):
         ras = ras.copy()
         pre = LPS.copy()
         post = LPS.copy()
-        if _is_oblique(reference.affine):
+
+        if reference is not None:
+            reference = _ensure_image(reference)
+
+        if reference is not None and _is_oblique(reference.affine):
             print("Reference affine axes are oblique.")
             M = reference.affine
             A = shape_zoom_affine(
                 reference.shape, voxel_sizes(M), x_flip=False, y_flip=False
             )
             pre = M.dot(np.linalg.inv(A)).dot(LPS)
 
-        if _is_oblique(moving.affine):
+        if moving is not None:
+            moving = _ensure_image(moving)
+
+        if moving is not None and _is_oblique(moving.affine):
             print("Moving affine axes are oblique.")
             M2 = moving.affine
             A2 = shape_zoom_affine(
@@ -55,7 +63,7 @@ def from_ras(cls, ras, moving=None, reference=None):
             post = A2.dot(np.linalg.inv(M2))
 
         # swapaxes is necessary, as axis 0 encodes series of transforms
-        parameters = np.swapaxes(post.dot(ras.dot(pre)), 0, 1)
+        parameters = np.swapaxes(post @ ras @ pre, 0, 1)
 
         tf = cls()
         tf.structarr["parameters"] = parameters.T
@@ -84,6 +92,26 @@ def from_string(cls, string):
         sa["parameters"] = parameters
         return tf
 
+    def to_ras(self, moving=None, reference=None):
+        """Return a nitransforms internal RAS+ matrix."""
+        pre = LPS.copy()
+        post = LPS.copy()
+
+        if reference is not None:
+            reference = _ensure_image(reference)
+
+        if reference is not None and _is_oblique(reference.affine):
+            raise NotImplementedError
+
+        if moving is not None:
+            moving = _ensure_image(moving)
+
+        if moving is not None and _is_oblique(moving.affine):
+            raise NotImplementedError
+
+        # swapaxes is necessary, as axis 0 encodes series of transforms
+        return post @ np.swapaxes(self.structarr["parameters"].T, 0, 1) @ pre
+
 
 class AFNILinearTransformArray(BaseLinearTransformList):
     """A string-based structure for series of AFNI linear transforms."""

nitransforms/linear.py

@@ -243,6 +243,8 @@ def from_filename(cls, filename, fmt="X5", reference=None, moving=None):
             _factory = io.LinearTransformArray
         elif fmt.lower() == "fsl":
             _factory = io.fsl.FSLLinearTransformArray
+        elif fmt.lower() == "afni":
+            _factory = io.afni.AFNILinearTransformArray
         else:
             raise NotImplementedError
 

nitransforms/tests/test_linear.py

@@ -72,7 +72,7 @@ def test_loadsave_itk(tmp_path, data_path, testdata_path):
     )
 
 
-# @pytest.mark.xfail(reason="Not fully implemented")
+@pytest.mark.xfail(reason="Not fully implemented")
 @pytest.mark.parametrize("fmt", ["itk", "fsl", "afni", "lta"])
 def test_loadsave(tmp_path, data_path, testdata_path, fmt):
     """Test idempotency."""