def setUp(self):
names = ['zspace', 'yspace', 'xspace']
shape = (10,20,30)
self.img = Image(np.zeros(shape),
AffineTransform.from_start_step(names, names, (0,)*3, (1,)*3))
self.img2 = Image(np.ones(shape),
AffineTransform.from_start_step(names, names, (0,)*3, (1,)*3))
shape = (3,5,4)
self.img3 = Image(np.zeros(shape),
AffineTransform.from_start_step(names, names, (0,)*3, (1,)*3))
self.img4 = Image(np.zeros(shape),
AffineTransform.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 = AffineTransform.from_params(in_names, out_names, np.identity(3))
img = Image(np.ones((100, 90)), g)
img.get_data()[50:55, 40:55] = 3.
tcoordmap = AffineTransform.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(ir.get_data())
def __init__(self, data, affine, axis_names, metadata={},
lps=True):
""" Creates a new nipy image with an affine mapping.
Parameters
----------
data : ndarray
ndarray representing the data.
affine : 4x4 ndarray
affine transformation to the reference coordinate system
axis_names : [string]
names of the axes in the coordinate system.
"""
if len(axis_names) < 3:
raise ValueError('XYZImage must have a minimum of 3 axes')
# The first three axes are assumed to be the
# spatial ones
xyz_transform = XYZTransform(affine, axis_names[:3], lps)
nonspatial_names = axis_names[3:]
if nonspatial_names:
nonspatial_affine_transform = AffineTransform.from_start_step(nonspatial_names, nonspatial_names, [0]*(data.ndim-3), [1]*(data.ndim-3))
full_dimensional_affine_transform = cmap_product(xyz_transform, nonspatial_affine_transform)
else:
full_dimensional_affine_transform = xyz_transform
self._xyz_transform = xyz_transform
Image.__init__(self, data, full_dimensional_affine_transform,
metadata=metadata)
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 = AffineTransform.from_params(in_names, out_names, np.identity(3))
img = Image(np.ones((100, 90)), g)
img[50:55, 40:55] = 3.0
tcoordmap = AffineTransform.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))
def __init__(self, data, affine, coord_sys, metadata=None):
""" Creates a new nipy image with an affine mapping.
Parameters
----------
data : ndarray
ndarray representing the data.
affine : 4x4 ndarray
affine transformation to the reference coordinate system
coord_system : string
name of the reference coordinate system.
"""
function_domain = CoordinateSystem(['axis%d' % i for i in range(3)],
name=coord_sys)
function_range = CoordinateSystem(['x','y','z'], name='world')
spatial_coordmap = AffineTransform(function_domain, function_range,
affine)
nonspatial_names = ['axis%d' % i for i in range(3, data.ndim)]
if nonspatial_names:
nonspatial_coordmap = AffineTransform.from_start_step(nonspatial_names, nonspatial_names, [0]*(data.ndim-3), [1]*(data.ndim-3))
full_coordmap = cmap_product(coordmap, nonspatial_coordmap)
else:
full_coordmap = spatial_coordmap
self._spatial_coordmap = spatial_coordmap
self.coord_sys = coord_sys
Image.__init__(self, data, full_coordmap)
if metadata is not None:
self.metadata = metadata
