NumpyTensorSpaceCustomDist

class odl.space.npy_tensors.NumpyTensorSpaceCustomDist(dist)

Bases: odl.space.weighting.CustomDist

Class for handling a user-specified distance in TensorSpace.

Note that this removes inner and norm.

Attributes

dist

Custom distance of this instance..

exponent

Exponent of this weighting.

impl

Implementation backend of this weighting.

repr_part

Return a string usable in a space’s __repr__ method.

Methods

equiv(self, other)	Test if other is an equivalent weighting.
inner(self, x1, x2)	Inner product is not defined for custom distance.
norm(self, x)	Norm is not defined for custom distance.

__init__(self, dist)

Initialize a new instance.

Parameters

distcallable

The distance function defining a metric on TensorSpace. It must accept two Tensor arguments, return a float and fulfill the following mathematical conditions for any three elements x, y, z:

• dist(x, y) >= 0

• dist(x, y) = 0 if and only if x = y

• dist(x, y) = dist(y, x)

• dist(x, y) <= dist(x, z) + dist(z, y)