feat: add an .asaffine() member to TransformChain

This PR starts the implementation of "collapsing" series of transforms,
for the linear case.

It is tested on real data added in the context of nipy#66, nipy#74 and nipy#75.
For the moment does not cover unintended use-cases such as collapsing
transform sequences containing one or more nonlinear transforms.

Resolves: nipy#88

Author: oesteban

nitransforms/manip.py

@@ -8,6 +8,7 @@
 ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
 """Common interface for transforms."""
 from collections.abc import Iterable
+import numpy as np
 
 from .base import (
     TransformBase,
@@ -139,6 +140,13 @@ def map(self, x, inverse=False):
 
         return x
 
+    def asaffine(self):
+        """Combine a succession of linear transforms into one."""
+        matrix = np.eye(4)
+        for xfm in self.transforms:
+            matrix = xfm.matrix.dot(matrix)
+        return Affine(matrix, reference=self.reference)
+
     @classmethod
     def from_filename(cls, filename, fmt="X5",
                       reference=None, moving=None):

nitransforms/tests/test_manip.py

@@ -8,12 +8,15 @@
 
 import numpy as np
 import nibabel as nb
-from ..manip import load as _load
+from ..manip import load as _load, TransformChain
+from ..linear import Affine
 from .test_nonlinear import (
     TESTS_BORDER_TOLERANCE,
     APPLY_NONLINEAR_CMD,
 )
 
+FMT = {"lta": "fs", "tfm": "itk"}
+
 
 def test_itk_h5(tmp_path, testdata_path):
     """Check a translation-only field on one or more axes, different image orientations."""
@@ -51,3 +54,22 @@ def test_itk_h5(tmp_path, testdata_path):
     diff = sw_moved.get_fdata() - nt_moved.get_fdata()
     # A certain tolerance is necessary because of resampling at borders
     assert (np.abs(diff) > 1e-3).sum() / diff.size < TESTS_BORDER_TOLERANCE
+
+
+@pytest.mark.parametrize("ext0", ["lta", "tfm"])
+@pytest.mark.parametrize("ext1", ["lta", "tfm"])
+@pytest.mark.parametrize("ext2", ["lta", "tfm"])
+def test_collapse_affines(tmp_path, data_path, ext0, ext1, ext2):
+    """Check whether affines are correctly collapsed."""
+    chain = TransformChain([
+        Affine.from_filename(data_path / "regressions"
+                             / f"from-fsnative_to-scanner_mode-image.{ext0}", fmt=f"{FMT[ext0]}"),
+        Affine.from_filename(data_path / "regressions"
+                             / f"from-scanner_to-bold_mode-image.{ext1}", fmt=f"{FMT[ext1]}"),
+    ])
+    assert np.allclose(
+        chain.asaffine().matrix,
+        Affine.from_filename(
+            data_path / "regressions" / f"from-fsnative_to-bold_mode-image.{ext2}",
+            fmt=f"{FMT[ext2]}").matrix,
+    )