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 __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
