enh: fix lta conversion, add data

Author: mgxd

nitransforms/io/lta.py

@@ -92,7 +92,7 @@ def from_string(klass, string):
 
 class LinearTransform(StringBasedStruct):
     template_dtype = np.dtype([
-        ('mean', 'f4', (3, 1)),       # x0, y0, z0
+        ('mean', 'f4', (3, 1)),  # x0, y0, z0
         ('sigma', 'f4'),
         ('m_L', 'f4', (4, 4)),
         ('m_dL', 'f4', (4, 4)),

nitransforms/linear.py

@@ -257,6 +257,7 @@ def load(filename, fmt='X5', reference=None):
         if lta['nxforms'] > 1:
             raise NotImplementedError("Multiple transforms are not yet supported.")
         if lta['type'] != 1:
+            warnings.warn("Converting LTA to RAS2RAS")
             lta.set_type(1)
         matrix = lta['xforms'][0]['m_L']
     elif fmt.lower() in ('x5', 'bids'):

nitransforms/tests/data/affine-RAS.fs.v2v.lta

@@ -0,0 +1,28 @@
+type      = 0 # LINEAR_VOX_TO_VOX
+nxforms   = 1
+mean      = 0.0000 0.0000 0.0000
+sigma     = 1.0000
+1 4 4
+9.999989867210388e-01 -9.999993490055203e-04 9.999998146668077e-04 1.454572677612305e+00 
+1.404936425387859e-03 6.216088533401489e-01 -7.833265066146851e-01 3.912971496582031e+01 
+1.617172238184139e-04 7.833272218704224e-01 6.216096878051758e-01 -1.376794815063477e+01 
+0.000000000000000e+00 0.000000000000000e+00 0.000000000000000e+00 1.000000000000000e+00 
+src volume info
+valid = 1  # volume info valid
+filename = unknown
+volume = 57 67 56
+voxelsize = 2.750000000000000e+00 2.750000000000000e+00 2.750000000000000e+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   = 3.750000000000000e-01 1.125000000000000e+00 -1.400000000000000e+01
+dst volume info
+valid = 1  # volume info valid
+filename = unknown
+volume = 57 67 56
+voxelsize = 2.750000000000000e+00 2.750000000000000e+00 2.750000000000000e+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   = 3.750000000000000e-01 1.125000000000000e+00 -1.400000000000000e+01
+fscale 0.100000

nitransforms/tests/data/r2r.lta

@@ -36,7 +36,7 @@ def test_LinearTransformArray(tmpdir, data_path):
     assert lta['nxforms'] == 0
     assert len(lta['xforms']) == 0
 
-    test_lta = str(data_path / 'r2r.lta')
+    test_lta = str(data_path / 'affine-RAS.fs.lta')
     with open(test_lta) as fp:
         lta = LTA.from_fileobj(fp)
 
@@ -45,7 +45,7 @@ def test_LinearTransformArray(tmpdir, data_path):
     xform = lta['xforms'][0]
 
     assert np.allclose(
-        xform['m_L'], np.genfromtxt(test_lta, skip_header=8, skip_footer=18)
+        xform['m_L'], np.genfromtxt(test_lta, skip_header=5, skip_footer=20)
     )
 
     outlta = (tmpdir / 'out.lta').strpath
@@ -58,8 +58,8 @@ def test_LinearTransformArray(tmpdir, data_path):
 
 
 def test_LT_conversions(data_path):
-    r = str(data_path / 'r2r.lta')
-    v = str(data_path / 'v2v.lta')
+    r = str(data_path / 'affine-RAS.fs.lta')
+    v = str(data_path / 'affine-RAS.fs.v2v.lta')
     with open(r) as fa, open(v) as fb:
         r2r = LTA.from_fileobj(fa)
         v2v = LTA.from_fileobj(fb)
@@ -72,7 +72,7 @@ def test_LT_conversions(data_path):
     # convert vox2vox LTA to ras2ras
     v2v.set_type('LINEAR_RAS_TO_RAS')
     assert v2v['type'] == 1
-    assert np.allclose(r2r_m, v2v_m)
+    assert np.allclose(r2r_m, v2v_m, atol=1e-05)
 
 
 def test_ITKLinearTransformArray(tmpdir, data_path):