def setUp(self):
names = ['zspace', 'yspace', 'xspace']
shape = (10,20,30)
self.img = Image(np.zeros(shape),
Affine.from_start_step(names, names, (0,)*3, (1,)*3))
self.img2 = Image(np.ones(shape),
Affine.from_start_step(names, names, (0,)*3, (1,)*3))
shape = (3,5,4)
self.img3 = Image(np.zeros(shape),
Affine.from_start_step(names, names, (0,)*3, (1,)*3))
self.img4 = Image(np.zeros(shape),
Affine.from_start_step(names, names, (0,)*3, (1,)*3))
def test_nonaffine():
# resamples an image along a curve through the image.
#
# FIXME: use the reference.evaluate.Grid to perform this nicer
# FIXME: Remove pylab references
def curve(x): # function accept N by 1, returns N by 2
return (np.vstack([5*np.sin(x.T),5*np.cos(x.T)]).T + [52,47])
for names in (('xy', 'ij', 't', 'u'),('ij', 'xy', 't', 's')):
in_names, out_names, tin_names, tout_names = names
g = Affine.from_params(in_names, out_names, np.identity(3))
img = Image(np.ones((100,90)), g)
img[50:55,40:55] = 3.
tcoordmap = Affine.from_start_step(
tin_names,
tout_names,
[0],
[np.pi*1.8/100])
ir = resample(img, tcoordmap, curve, (100,))
if gui_review:
import pylab
pylab.figure(num=3)
pylab.imshow(img, interpolation='nearest')
d = curve(np.linspace(0,1.8*np.pi,100))
pylab.plot(d[0], d[1])
pylab.gca().set_ylim([0,99])
pylab.gca().set_xlim([0,89])
pylab.figure(num=4)
pylab.plot(np.asarray(ir))
