ENH: Add ITK-LTA conversion test

Also, finally fixes #64.

nitransforms/linear.py

@@ -66,7 +66,7 @@ def __init__(self, matrix=None, reference=None):
                 raise TypeError('Matrix is not square.')
             self._matrix = matrix
 
-            if np.any(self._matrix[3, :] != (0, 0, 0, 1)):
+            if not np.allclose(self._matrix[3, :], (0, 0, 0, 1)):
                 raise ValueError("Matrix does not represent a valid transform.")
 
     def __eq__(self, other):

nitransforms/tests/data/regressions/robust_register.lta

@@ -1,30 +1,28 @@
-# transform file /home/oesteban/tmp/fmriprep-ds005/fprep-work/fmriprep_wf/single_subject_01_wf/anat_preproc_wf/surface_recon_wf/fsnative2t1w_xfm/T1_robustreg.lta
-# created by oesteban on Sat Mar 14 19:28:37 2020
-
 type      = 1 # LINEAR_RAS_TO_RAS
 nxforms   = 1
 mean      = 129.0000 157.0000 132.0000
 sigma     = 10000.0000
 1 4 4
-9.999999403953552e-01 -1.698292035143822e-04 1.542967074783519e-04 -1.678466796875000e-04 
-1.698438863968477e-04 9.999999403953552e-01 -9.513227996649221e-05 -1.318359375000000e-02 
--1.542805403005332e-04 9.515848068986088e-05 9.999999403953552e-01 -6.271362304687500e-03 
-0.000000000000000e+00 0.000000000000000e+00 0.000000000000000e+00 9.999999403953552e-01 
+1.000000000000000e+00 1.698439009487629e-04 -1.542805694043636e-04 1.691182987997308e-04 
+-1.698292180662975e-04 1.000000000000000e+00 9.515849524177611e-05 1.318416278809309e-02 
+1.542967220302671e-04 -9.513228724244982e-05 1.000000000000000e+00 6.270134821534157e-03 
+0.000000000000000e+00 0.000000000000000e+00 0.000000000000000e+00 1.000000000000000e+00 
 src volume info
 valid = 1  # volume info valid
-filename = /oak/stanford/groups/russpold/data/openfmri/derivatives/ds000005/freesurfer-6.0.1/sub-01/mri/T1.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
-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
+dst volume info
+valid = 1  # volume info valid
+filename = /oak/stanford/groups/russpold/data/openfmri/derivatives/ds000005/freesurfer-6.0.1/sub-01/mri/T1.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
+fscale 0.100000

nitransforms/tests/data/regressions/robust_register.tfm

@@ -0,0 +1,5 @@
+#Insight Transform File V1.0
+#Transform 0
+Transform: AffineTransform_double_3_3
+Parameters: 1 -0.00016982921806629747 -0.00015429673658218235 0.00016984390094876289 1 9.5132294518407434e-05 0.00015428056940436363 -9.5158495241776109e-05 1 0.00016784669423941523 0.013183594681322575 -0.0062713632360100746
+FixedParameters: 0 0 0

nitransforms/tests/test_conversions.py

@@ -0,0 +1,12 @@
+# emacs: -*- mode: python-mode; py-indent-offset: 4; indent-tabs-mode: nil -*-
+# vi: set ft=python sts=4 ts=4 sw=4 et:
+"""Conversions between formats."""
+import numpy as np
+import pytest
+from .. import linear as _l
+
+def test_conversions(data_path):
+    lta = _l.load(data_path / "regressions" / "robust_register.lta", fmt="lta")
+    itk = _l.load(data_path / "regressions" / "robust_register.tfm", fmt="itk")
+
+    assert np.allclose(lta.matrix, itk.matrix)