enh: finalize some tests to increase coverage

Author: oesteban

nitransforms/base.py

@@ -225,13 +225,13 @@ def apply(self, spatialimage, reference=None,
 
         """
         if reference is not None and isinstance(reference, (str, Path)):
-            reference = load(reference)
+            reference = load(str(reference))
 
         _ref = self.reference if reference is None \
             else SpatialReference.factory(reference)
 
         if isinstance(spatialimage, (str, Path)):
-            spatialimage = load(spatialimage)
+            spatialimage = load(str(spatialimage))
 
         data = np.asanyarray(spatialimage.dataobj)
         output_dtype = output_dtype or data.dtype

nitransforms/io/afni.py

@@ -4,7 +4,7 @@
 from nibabel.affines import obliquity, voxel_sizes
 
 from ..patched import shape_zoom_affine
-from .base import BaseLinearTransformList, LinearParameters
+from .base import BaseLinearTransformList, LinearParameters, TransformFileError
 
 LPS = np.diag([-1, -1, 1, 1])
 OBLIQUITY_THRESHOLD_DEG = 0.01
@@ -58,14 +58,14 @@ def from_string(cls, string):
         """Read the struct from string."""
         tf = cls()
         sa = tf.structarr
-        lines = [l for l in string.splitlines()
-                 if l.strip() and not l.startswith('#')]
-
-        if '3dvolreg matrices' in lines[0]:
-            lines = lines[1:]  # Drop header
+        lines = [
+            l for l in string.splitlines()
+            if l.strip() and not (l.startswith('#') or '3dvolreg matrices' in l)
+        ]
 
         if not lines:
-            raise ValueError('String "%s"' % string)
+            raise TransformFileError
+
         parameters = np.vstack((
             np.genfromtxt([lines[0].encode()],
                           dtype='f8').reshape((3, 4)),
@@ -108,9 +108,14 @@ def from_ras(cls, ras, moving=None, reference=None):
     def from_string(cls, string):
         """Read the struct from string."""
         _self = cls()
-        _self.xforms = [cls._inner_type.from_string(l.strip())
-                        for l in string.splitlines()
-                        if l.strip() and not l.startswith('#')]
+
+        lines = [l.strip() for l in string.splitlines()
+                 if l.strip() and not l.startswith('#')]
+        if not lines:
+            raise TransformFileError('Input string is empty.')
+
+        _self.xforms = [cls._inner_type.from_string(l)
+                        for l in lines]
         return _self
 
 

nitransforms/io/fsl.py

@@ -3,7 +3,7 @@
 import numpy as np
 from nibabel.affines import voxel_sizes
 
-from .base import BaseLinearTransformList, LinearParameters
+from .base import BaseLinearTransformList, LinearParameters, TransformFileError
 
 
 class FSLLinearTransform(LinearParameters):
@@ -45,8 +45,14 @@ def from_string(cls, string):
         """Read the struct from string."""
         tf = cls()
         sa = tf.structarr
+        lines = [l.strip() for l in string.splitlines()
+                 if l.strip()]
+        if not lines or len(lines) < 4:
+            raise TransformFileError
+
+        print(lines)
         sa['parameters'] = np.genfromtxt(
-            [string], dtype=cls.dtype['parameters'])
+            ['\n'.join(lines)], dtype=cls.dtype['parameters'])
         return tf
 
 
@@ -92,8 +98,7 @@ def from_ras(cls, ras, moving=None, reference=None):
     def from_string(cls, string):
         """Read the struct from string."""
         _self = cls()
-        _self.xforms = [cls._inner_type.from_string(l.strip())
-                        for l in string.splitlines() if l.strip()]
+        _self.xforms = [cls._inner_type.from_string(string)]
         return _self
 
     @classmethod

nitransforms/io/itk.py

@@ -131,9 +131,11 @@ def from_string(cls, string):
         """Read the struct from string."""
         tf = cls()
         sa = tf.structarr
-        lines = [l for l in string.splitlines()
+        lines = [l.strip() for l in string.splitlines()
                  if l.strip()]
-        assert lines[0][0] == '#'
+        if not lines or not lines[0].startswith('#'):
+            raise TransformFileError
+
         if lines[1][0] == '#':
             lines = lines[1:]  # Drop banner with version
 
@@ -182,7 +184,7 @@ def to_string(self):
         strings = []
         for i, xfm in enumerate(self.xforms):
             xfm.structarr['index'] = i
-            strings.append(xfm.to_string())
+            strings.append(xfm.to_string(banner=(i == 0)))
         return '\n'.join(strings)
 
     @classmethod
@@ -223,8 +225,9 @@ def from_string(cls, string):
         lines = [l.strip() for l in string.splitlines()
                  if l.strip()]
 
-        if lines[0][0] != '#' or 'Insight Transform File V1.0' not in lines[0]:
-            raise ValueError('Unknown Insight Transform File format.')
+        if not lines or not lines[0].startswith('#') or \
+           'Insight Transform File V1.0' not in lines[0]:
+            raise TransformFileError('Unknown Insight Transform File format.')
 
         string = '\n'.join(lines[1:])
         for xfm in string.split('#')[1:]:

nitransforms/tests/test_base.py

@@ -76,21 +76,21 @@ def _to_hdf5(klass, x5_root):
 
     monkeypatch.setattr(TransformBase, 'map', _fakemap)
     monkeypatch.setattr(TransformBase, '_to_hdf5', _to_hdf5)
-    fname = str(data_path / 'someones_anatomy.nii.gz')
+    fname = data_path / 'someones_anatomy.nii.gz'
 
     # Test identity transform
     xfm = TransformBase()
     xfm.reference = fname
     assert xfm.ndim == 3
     moved = xfm.apply(fname, order=0)
-    assert np.all(nb.load(fname).get_fdata() == moved.get_fdata())
+    assert np.all(nb.load(str(fname)).get_fdata() == moved.get_fdata())
 
     # Test identity transform - setting reference
     xfm = TransformBase()
     xfm.reference = fname
     assert xfm.ndim == 3
-    moved = xfm.apply(fname, reference=fname, order=0)
-    assert np.all(nb.load(fname).get_fdata() == moved.get_fdata())
+    moved = xfm.apply(str(fname), reference=fname, order=0)
+    assert np.all(nb.load(str(fname)).get_fdata() == moved.get_fdata())
 
     # Test applying to Gifti
     gii = nb.gifti.GiftiImage(darrays=[

nitransforms/tests/test_io.py

@@ -120,14 +120,22 @@ def test_Linear_common(tmpdir, data_path, sw, image_orientation,
         ext = '.lta'
         factory = fs.LinearTransformArray
 
+    with pytest.raises(TransformFileError):
+        factory.from_string('')
+
     fname = 'affine-%s.%s%s' % (image_orientation, sw, ext)
 
     # Test the transform loaders are implemented
     xfm = factory.from_filename(data_path / fname)
 
     with open(str(data_path / fname)) as f:
+        text = f.read()
+        f.seek(0)
         xfm = factory.from_fileobj(f)
 
+    # Test to_string
+    assert text == xfm.to_string()
+
     xfm.to_filename(fname)
     assert filecmp.cmp(fname, str((data_path / fname).resolve()))
 
@@ -142,7 +150,7 @@ def test_Linear_common(tmpdir, data_path, sw, image_orientation,
 ])
 @pytest.mark.parametrize('sw', ['afni', 'fsl', 'itk'])
 def test_LinearList_common(tmpdir, data_path, sw, image_orientation,
-                       get_testdata):
+                           get_testdata):
     tmpdir.chdir()
 
     angles = np.random.uniform(low=-3.14, high=3.14, size=(5, 3))
@@ -162,13 +170,22 @@ def test_LinearList_common(tmpdir, data_path, sw, image_orientation,
     tflist1 = factory(mats)
 
     fname = 'affine-%s.%s%s' % (image_orientation, sw, ext)
+
+    with pytest.raises(FileNotFoundError):
+        factory.from_filename(fname)
+
+    tmpdir.join('singlemat.%s' % ext).write('')
+    with pytest.raises(TransformFileError):
+        factory.from_filename('singlemat.%s' % ext)
+
     tflist1.to_filename(fname)
     tflist2 = factory.from_filename(fname)
 
     assert tflist1['nxforms'] == tflist2['nxforms']
     assert all([np.allclose(x1['parameters'], x2['parameters'])
                 for x1, x2 in zip(tflist1.xforms, tflist2.xforms)])
 
+
 def test_ITKLinearTransform(tmpdir, data_path):
     tmpdir.chdir()
 
@@ -223,7 +240,7 @@ def test_ITKLinearTransformArray(tmpdir, data_path):
 
     assert itklist['nxforms'] == 9
     assert text == itklist.to_string()
-    with pytest.raises(ValueError):
+    with pytest.raises(TransformFileError):
         itk.ITKLinearTransformArray.from_string(
             '\n'.join(text.splitlines()[1:]))