def test_rollaxis():
data = np.random.standard_normal((3,4,7,5))
im = Image(data, AffineTransform.from_params('ijkl', 'xyzt', np.diag([1,2,3,4,1])))
# for the inverse we must specify an integer
yield assert_raises, ValueError, image.rollaxis, im, 'i', True
# Check that rollaxis preserves diagonal affines, as claimed
yield assert_almost_equal, image.rollaxis(im, 1).affine, np.diag([2,1,3,4,1])
yield assert_almost_equal, image.rollaxis(im, 2).affine, np.diag([3,1,2,4,1])
yield assert_almost_equal, image.rollaxis(im, 3).affine, np.diag([4,1,2,3,1])
# Check that ambiguous axes raise an exception
# 'l' appears both as an axis and a reference coord name
# and in different places
im_amb = Image(data, AffineTransform.from_params('ijkl', 'xylt', np.diag([1,2,3,4,1])))
yield assert_raises, ValueError, image.rollaxis, im_amb, 'l'
# But if it's unambiguous, then
# 'l' can appear both as an axis and a reference coord name
im_unamb = Image(data, AffineTransform.from_params('ijkl', 'xyzl', np.diag([1,2,3,4,1])))
im_rolled = image.rollaxis(im_unamb, 'l')
yield assert_almost_equal, im_rolled.get_data(), \
im_unamb.get_data().transpose([3,0,1,2])
for i, o, n in zip('ijkl', 'xyzt', range(4)):
im_i = image.rollaxis(im, i)
im_o = image.rollaxis(im, o)
im_n = image.rollaxis(im, n)
yield assert_almost_equal, im_i.get_data(), \
im_o.get_data()
yield assert_almost_equal, im_i.affine, \
im_o.affine
yield assert_almost_equal, im_n.get_data(), \
im_o.get_data()
for _im in [im_n, im_o, im_i]:
im_n_inv = image.rollaxis(_im, n, inverse=True)
yield assert_almost_equal, im_n_inv.affine, \
im.affine
yield assert_almost_equal, im_n_inv.get_data(), \
im.get_data()
def from_image(klass, image, axis=0):
# Now, reorder the axes and reference
image = rollaxis(image, axis)
imlist = []
coordmap = image.coordmap
# We drop the first output coordinate of image's coordmap
drop1st = np.identity(coordmap.ndims[1]+1)[1:]
drop1st_domain = image.reference
drop1st_range = CoordinateSystem(image.reference.coord_names[1:],
name=image.reference.name,
coord_dtype=image.reference.coord_dtype)
drop1st_coordmap = AffineTransform(drop1st_domain, drop1st_range,
drop1st)
# And arbitrarily add a 0 for the first axis
add0 = np.vstack([np.zeros(image.axes.ndim),
np.identity(image.axes.ndim)])
add0_domain = CoordinateSystem(image.axes.coord_names[1:],
name=image.axes.name,
coord_dtype=image.axes.coord_dtype)
add0_range = image.axes
add0_coordmap = AffineTransform(add0_domain, add0_range,
add0)
coordmap = compose(drop1st_coordmap, image.coordmap, add0_coordmap)
data = np.asarray(image)
imlist = [Image(dataslice, copy(coordmap))
for dataslice in data]
return klass(imlist)
