NumpyTensorSpaceCustomNorm

class odl.space.npy_tensors.NumpyTensorSpaceCustomNorm(norm)

Bases: CustomNorm

Class for handling a user-specified norm.

Note that this removes inner.

Attributes:

exponent

Exponent of this weighting.

impl

Implementation backend of this weighting.

norm

Custom norm of this instance..

repr_part

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

Methods

dist(x1, x2)	Calculate the distance between two elements.
equiv(other)	Test if other is an equivalent weighting.
inner(x1, x2)	Inner product is not defined for custom distance.

__init__(norm)

Initialize a new instance.

Parameters:

normcallable

The norm implementation. It must accept a Tensor argument, return a float and satisfy the following conditions for all any two elements x, y and scalars s:

• ||x|| >= 0

• ||x|| = 0 if and only if x = 0

• ||s * x|| = |s| * ||x||

• ||x + y|| <= ||x|| + ||y||