ScalingFunctional

class odl.solvers.functional.default_functionals.ScalingFunctional(*args, **kwargs)

Bases: odl.solvers.functional.functional.Functional, odl.operator.default_ops.ScalingOperator

Functional that scales the input argument by a value.

Since the range of a functional is always a field, the domain of this functional is also a field, i.e. real or complex numbers.

Attributes

adjoint

Adjoint, given as scaling with the conjugate of the scalar.

convex_conj

Convex conjugate functional of the functional.

domain

Set of objects on which this operator can be evaluated.

grad_lipschitz

Lipschitz constant for the gradient of the functional.

gradient

Gradient operator of the functional.

inverse

Return the inverse operator.

is_functional

True if this operator’s range is a Field.

is_linear

True if this operator is linear.

proximal

Proximal factory of the functional.

range

Set in which the result of an evaluation of this operator lies.

scalar

Fixed scaling factor of this operator.

Methods

_call(self, x[, out])	Scale x and write to out if given.
bregman(self, point, subgrad)	Return the Bregman distance functional.
derivative(self, point)	Return the derivative operator in the given point.
norm(self[, estimate])	Return the operator norm of this operator.
translated(self, shift)	Return a translation of the functional.

__init__(self, field, scale)

Initialize a new instance.

Parameters

fieldField

Domain of the functional.

scaleelement in domain

The constant value to scale by.

Examples

>>> field = odl.RealNumbers()
>>> func = ScalingFunctional(field, 3)
>>> func(5)
15.0