def test_linear_altref(seed):
with tempdir.tempdir():
src2ref = affine.scaleOffsetXform([1, 1, 1], [5, 5, 5])
altv2w = affine.scaleOffsetXform([1, 1, 1], [10, 10, 10])
srcdata = np.random.randint(1, 65536, (10, 10, 10))
src = fslimage.Image(srcdata, xform=np.eye(4))
ref = fslimage.Image(src.data, xform=src2ref)
altref = fslimage.Image(src.data, xform=altv2w)
src.save('src')
ref.save('ref')
altref.save('altref')
x5.writeLinearX5('xform.x5', src2ref, src, ref)
fsl_apply_x5.main('src xform.x5 out -r altref'.split())
result = fslimage.Image('out')
expect = np.zeros(srcdata.shape)
expect[:5, :5, :5] = srcdata[5:, 5:, 5:]
assert result.sameSpace(altref)
assert np.all(result.data == expect)
def test_nonlinear(seed):
with tempdir.tempdir():
src2ref = _random_affine()
ref2src = affine.invert(src2ref)
src = _random_image(np.eye(4))
ref = _random_image(src2ref)
field = _affine_field(src, ref, ref2src, 'world', 'world')
x5.writeNonLinearX5('xform.x5', field)
src.save('src')
fsl_apply_x5.main('src xform.x5 out'.split())
result = fslimage.Image('out')
expect = resample.resampleToReference(src,
ref,
matrix=src2ref,
smooth=False)[0]
assert result.sameSpace(ref)
# We might get truncation on the edges
result = result.data[1:-1, 1:-1, 1:-1]
expect = expect[1:-1, 1:-1, 1:-1]
tol = dict(atol=1e-3, rtol=1e-3)
assert np.all(np.isclose(result, expect, **tol))
def test_linear(seed):
with tempdir.tempdir():
src2ref = _random_affine()
src = _random_image(np.eye(4))
ref = _random_image(src2ref)
x5.writeLinearX5('xform.x5', src2ref, src, ref)
src.save('src')
ref.save('ref')
fsl_apply_x5.main('src xform.x5 out'.split())
result = fslimage.Image('out')
expect = resample.resampleToReference(src, ref, matrix=src2ref)[0]
assert result.sameSpace(ref)
assert np.all(np.isclose(result.data, expect))
def test_linear_altsrc(seed):
with tempdir.tempdir():
src2ref = _random_affine()
src = _random_image(np.eye(4), (20, 20, 20))
ref = _random_image(src2ref)
x5.writeLinearX5('xform.x5', src2ref, src, ref)
src.save('src')
ref.save('ref')
srclo, xf = resample.resample(src, (10, 10, 10))
srclo = fslimage.Image(srclo, xform=xf)
srchi, xf = resample.resample(src, (40, 40, 40))
srchi = fslimage.Image(srchi, xform=xf)
srcoff = roi.roi(src, [(-10, 10), (-10, 10), (-10, 10)])
srclo.save('srclo')
srchi.save('srchi')
srcoff.save('srcoff')
fsl_apply_x5.main('src xform.x5 out'.split())
fsl_apply_x5.main('srclo xform.x5 outlo'.split())
fsl_apply_x5.main('srchi xform.x5 outhi'.split())
fsl_apply_x5.main('srcoff xform.x5 outoff'.split())
out = fslimage.Image('out')
outlo = fslimage.Image('outlo')
outhi = fslimage.Image('outhi')
outoff = fslimage.Image('outoff')
exp = resample.resampleToReference(src, ref, matrix=src2ref)[0]
explo = resample.resampleToReference(srclo, ref, matrix=src2ref)[0]
exphi = resample.resampleToReference(srchi, ref, matrix=src2ref)[0]
expoff = resample.resampleToReference(srcoff, ref, matrix=src2ref)[0]
assert out.sameSpace(ref)
assert outlo.sameSpace(ref)
assert outhi.sameSpace(ref)
assert outoff.sameSpace(ref)
assert np.all(np.isclose(out.data, exp))
assert np.all(np.isclose(outlo.data, explo))
assert np.all(np.isclose(outhi.data, exphi))
assert np.all(np.isclose(outoff.data, expoff))
def run(args):
with pytest.raises(SystemExit) as e:
fsl_apply_x5.main(args)
assert e.value.code == 0
def test_nonlinear_altsrc(seed):
with tempdir.tempdir():
src2ref = _random_affine()
ref2src = affine.invert(src2ref)
src = _random_image(np.eye(4), (20, 20, 20))
ref = _random_image(src2ref, (20, 20, 20))
field = _affine_field(src, ref, ref2src, 'world', 'world')
x5.writeNonLinearX5('xform.x5', field)
src.save('src')
ref.save('ref')
# use origin=corner so that the
# resampled variants are exactly
# aligned in the world coordinate
# system
srclo, xf = resample.resample(src, (10, 10, 10),
origin='corner',
smooth=False)
srclo = fslimage.Image(srclo, xform=xf)
srchi, xf = resample.resample(src, (40, 40, 40),
origin='corner',
smooth=False)
srchi = fslimage.Image(srchi, xform=xf)
srcoff = roi.roi(src, [(-10, 10), (-10, 10), (-10, 10)])
srclo.save('srclo')
srchi.save('srchi')
srcoff.save('srcoff')
fsl_apply_x5.main('src xform.x5 out'.split())
fsl_apply_x5.main('srclo xform.x5 outlo'.split())
fsl_apply_x5.main('srchi xform.x5 outhi'.split())
fsl_apply_x5.main('srcoff xform.x5 outoff'.split())
out = fslimage.Image('out')
outlo = fslimage.Image('outlo')
outhi = fslimage.Image('outhi')
outoff = fslimage.Image('outoff')
exp, x1 = resample.resampleToReference(src,
ref,
matrix=src2ref,
mode='constant',
smooth=False)
explo, x2 = resample.resampleToReference(srclo,
ref,
matrix=src2ref,
mode='constant',
smooth=False)
exphi, x3 = resample.resampleToReference(srchi,
ref,
matrix=src2ref,
mode='constant',
smooth=False)
expoff, x4 = resample.resampleToReference(srcoff,
ref,
matrix=src2ref,
mode='constant',
smooth=False)
assert out.sameSpace(ref)
assert outlo.sameSpace(ref)
assert outhi.sameSpace(ref)
assert outoff.sameSpace(ref)
# We get boundary cropping,
# so ignore edge slices
out = out.data[1:-1, 1:-1, 1:-1]
outlo = outlo.data[1:-1, 1:-1, 1:-1]
outhi = outhi.data[1:-1, 1:-1, 1:-1]
outoff = outoff.data[:9, :9, :9]
exp = exp[1:-1, 1:-1, 1:-1]
explo = explo[1:-1, 1:-1, 1:-1]
exphi = exphi[1:-1, 1:-1, 1:-1]
expoff = expoff[:9, :9, :9]
tol = dict(atol=1e-3, rtol=1e-3)
assert np.all(np.isclose(out, exp, **tol))
assert np.all(np.isclose(outlo, explo, **tol))
assert np.all(np.isclose(outhi, exphi, **tol))
assert np.all(np.isclose(outoff, expoff, **tol))