Resampling

class odl.Resampling(*args, **kwargs)

Bases: Operator

An operator that resamples on a different grid in the same set.

__init__(domain, range, interp)[source]

Initialize a new instance.

Parameters

domainDiscretizedSpace

Set of elements that are to be resampled.

rangeDiscretizedSpace

Set in which the resampled elements lie. Must have the same DiscretizedSpace.domain as domain.

interpstr or sequence of str

Interpolation type that should be used to resample. A single value applies to all axes, and a sequence gives the interpolation scheme per axis.

Supported values: 'nearest', 'linear'

Examples

Create two spaces with different number of points and a resampling operator using nearest-neighbor interpolation:

>>> coarse_discr = odl.uniform_discr(0, 1, 3)
>>> fine_discr = odl.uniform_discr(0, 1, 6)
>>> resampling = odl.Resampling(coarse_discr, fine_discr, 'nearest')
>>> resampling.domain
uniform_discr(0.0, 1.0, 3)
>>> resampling.range
uniform_discr(0.0, 1.0, 6)
>>> resampling.interp
'nearest'

Apply the corresponding resampling operator to an element:

>>> print(resampling([0, 1, 0]))
[ 0.,  0.,  1.,  1.,  0.,  0.]

With linear interpolation:

>>> resampling = odl.Resampling(coarse_discr, fine_discr, 'linear')
>>> print(resampling([0, 1, 0]))
[ 0.  ,  0.25,  0.75,  0.75,  0.25,  0.  ]