enh: add ITK-to-LTA tests

Closes #72

Author: oesteban

nitransforms/linear.py

@@ -166,10 +166,16 @@ def to_filename(self, filename, fmt="X5", moving=None):
             # xform info
             lt = io.LinearTransform()
             lt["sigma"] = 1.
-            lt["m_L"] = self.matrix
             # Just for reference, nitransforms does not write VOX2VOX
-            lt["src"] = io.VolumeGeometry.from_image(moving)
-            lt["dst"] = io.VolumeGeometry.from_image(self.reference)
+            # PLEASE NOTE THAT LTA USES THE "POINTS" CONVENTION, therefore
+            # the source is the reference (coordinates for which we need
+            # to find a projection) and destination is the moving image
+            # (from which data is pulled-back).
+            lt["src"] = io.VolumeGeometry.from_image(self.reference)
+            lt["dst"] = io.VolumeGeometry.from_image(moving)
+            # However, the affine needs to be inverted
+            # (i.e., it is not a pure "points" convention).
+            lt["m_L"] = np.linalg.inv(self.matrix)
             # to make LTA file format
             lta = io.LinearTransformArray()
             lta["type"] = 1  # RAS2RAS

nitransforms/tests/data/regressions/from-fsnative_to-bold_mode-image_type-ras2ras.lta

@@ -0,0 +1,31 @@
+# Created with lta_convert
+# lta_convert --inlta from-fsnative_to-bold_mode-image.lta --outlta from-fsnative_to-bold_mode-image_type-ras2ras.lta
+type      = 1 # LINEAR_RAS_TO_RAS
+nxforms   = 1
+mean      = 0.0000 0.0000 0.0000
+sigma     = 10000.0000
+1 4 4
+9.997106194496155e-01 9.580537676811218e-03 2.206108532845974e-02 -4.897087097167969e+00
+5.824727471917868e-03 7.934973239898682e-01 -6.085451841354370e-01 -6.588146209716797e+01
+-2.333561331033707e-02 6.084975600242615e-01 7.932120561599731e-01 1.111579895019531e+01
+0.000000000000000e+00 0.000000000000000e+00 0.000000000000000e+00 1.000000000000000e+00
+src volume info
+valid = 1  # volume info valid
+filename = /home/oesteban/tmp/fmriprep-ds005/fprep-work/fmriprep_wf/single_subject_01_wf/func_preproc_task_mixedgamblestask_run_01_wf/bold_reg_wf/bbreg_wf/bbregister/uni_xform_masked.nii.gz
+volume = 64 64 34
+voxelsize = 3.125000000000000e+00 3.125000000000000e+00 4.000000000000000e+00
+xras   = -1.000000000000000e+00 0.000000000000000e+00 0.000000000000000e+00
+yras   = 0.000000000000000e+00 1.000000000000000e+00 0.000000000000000e+00
+zras   = 0.000000000000000e+00 0.000000000000000e+00 1.000000000000000e+00
+cras   = 1.000000000000000e+00 2.800000000000000e+01 -3.100000000000000e+01
+dst volume info
+valid = 1  # volume info valid
+filename = /oak/stanford/groups/russpold/data/openfmri/derivatives/ds000005/freesurfer-6.0.1/sub-01/mri/orig.mgz
+volume = 256 256 256
+voxelsize = 1.000000000000000e+00 1.000000000000000e+00 1.000000000000000e+00
+xras   = -9.999999403953552e-01 0.000000000000000e+00 0.000000000000000e+00
+yras   = 0.000000000000000e+00 0.000000000000000e+00 -9.999999403953552e-01
+zras   = 0.000000000000000e+00 9.999999403953552e-01 0.000000000000000e+00
+cras   = -9.999847412109375e-01 -5.000015258789062e+00 -1.000038146972656e+00
+subject sub-01
+fscale 0.100000

nitransforms/tests/data/regressions/from-scanner_to-bold_mode-image_type-ras2ras.lta

@@ -0,0 +1,31 @@
+# Created with lta_convert
+# lta_convert --inlta from-scanner_to-bold_mode-image.lta --outlta from-scanner_to-bold_mode-image_type-ras2ras.lta
+type      = 1 # LINEAR_RAS_TO_RAS
+nxforms   = 1
+mean      = 0.0000 0.0000 0.0000
+sigma     = 1.0000
+1 4 4
+9.997058510780334e-01 9.539666585624218e-03 2.228682115674019e-02 -4.884338378906250e+00
+5.996740423142910e-03 7.934408783912659e-01 -6.086167693138123e-01 -6.589652252197266e+01
+-2.348928898572922e-02 6.085714697837830e-01 7.931506037712097e-01 1.110400390625000e+01
+0.000000000000000e+00 0.000000000000000e+00 0.000000000000000e+00 9.999998807907104e-01
+src volume info
+valid = 1  # volume info valid
+filename = /home/oesteban/tmp/fmriprep-ds005/fprep-work/fmriprep_wf/single_subject_01_wf/func_preproc_task_mixedgamblestask_run_01_wf/bold_reg_wf/bbreg_wf/bbregister/uni_xform_masked.nii.gz
+volume = 64 64 34
+voxelsize = 3.125000000000000e+00 3.125000000000000e+00 4.000000000000000e+00
+xras   = -1.000000000000000e+00 0.000000000000000e+00 0.000000000000000e+00
+yras   = 0.000000000000000e+00 1.000000000000000e+00 0.000000000000000e+00
+zras   = 0.000000000000000e+00 0.000000000000000e+00 1.000000000000000e+00
+cras   = 1.000000000000000e+00 2.800000000000000e+01 -3.100000000000000e+01
+dst volume info
+valid = 1  # volume info valid
+filename = /oak/stanford/groups/russpold/data/openfmri/ds000005/sub-01/anat/sub-01_T1w.nii.gz
+volume = 160 192 192
+voxelsize = 1.000000000000000e+00 1.333333015441895e+00 1.333333015441895e+00
+xras   = 1.000000000000000e+00 0.000000000000000e+00 0.000000000000000e+00
+yras   = 0.000000000000000e+00 1.000000000000000e+00 0.000000000000000e+00
+zras   = 0.000000000000000e+00 0.000000000000000e+00 1.000000000000000e+00
+cras   = -1.000000000000000e+00 -5.000030517578125e+00 -1.000030517578125e+00
+subject sub-01
+fscale 0.100000

nitransforms/tests/test_conversions.py

@@ -4,6 +4,7 @@
 import numpy as np
 import pytest
 from .. import linear as _l
+from ..io import LinearTransformArray as LTA
 
 
 @pytest.mark.parametrize('filename', [
@@ -21,6 +22,30 @@ def test_lta2itk_conversions(data_path, filename):
     assert np.allclose(lta.matrix, itk.matrix)
 
 
+@pytest.mark.parametrize('filename,moving,reference', [
+    ("from-fsnative_to-bold_mode-image", "T1w_fsnative.nii.gz", "bold.nii.gz"),
+    ("from-fsnative_to-scanner_mode-image", "T1w_fsnative.nii.gz", "T1w_scanner.nii.gz"),
+    ("from-scanner_to-bold_mode-image", "T1w_scanner.nii.gz", "bold.nii.gz"),
+    ("from-scanner_to-fsnative_mode-image", "T1w_scanner.nii.gz", "T1w_fsnative.nii.gz"),
+])
+def test_itk2lta_conversions(data_path, tmp_path, filename, moving, reference):
+    """Check conversions between formats."""
+    itk = _l.load(data_path / "regressions" / "".join((filename, ".tfm")),
+                  fmt="itk")
+    itk.reference = data_path / "regressions" / reference
+    itk.to_filename(tmp_path / "test.lta", fmt="fs",
+                    moving=data_path / "regressions" / moving)
+
+    converted_lta = LTA.from_filename(tmp_path / "test.lta")
+    expected_fname = data_path / "regressions" / "".join((filename, "_type-ras2ras.lta"))
+    if not expected_fname.exists():
+        expected_fname = data_path / "regressions" / "".join((filename, ".lta"))
+
+    exp_lta = LTA.from_filename(expected_fname)
+    assert np.allclose(converted_lta['xforms'][0]['m_L'],
+                       exp_lta['xforms'][0]['m_L'])
+
+
 def test_concatenation(data_path):
     """Check replacement to lta_concat."""
     lta0 = _l.load(data_path / "regressions" / "from-scanner_to-fsnative_mode-image.lta",