IndicatorLpUnitBall

class odl.solvers.functional.default_functionals.IndicatorLpUnitBall(*args, **kwargs)[source]

Bases: Functional

The indicator function on the unit ball in given the Lp norm.

It does not implement gradient since it is not differentiable everywhere.

Notes

This functional is defined as

f(x) = \begin{cases}
    0       & \text{if } ||x||_{L_p} \leq 1,
 \\ +\infty & \text{else}
\end{cases}

where ||x||_{L_p} is the L_p-norm, which for finite values of p is defined as

\| x \|_{L_p} = \left( \int_{\Omega} |x|^p dx \right)^{1/p},

and for p = \infty it is defined as

||x||_{\infty} = \max_x (|x|).

The functional also allows noninteger and nonpositive values of the exponent p, however in this case \| x \|_{L_p} is not a norm.

Attributes:
adjoint

Adjoint of this operator (abstract).

convex_conj

The conjugate functional of IndicatorLpUnitBall.

domain

Set of objects on which this operator can be evaluated.

exponent

Exponent corresponding to the norm.

grad_lipschitz

Lipschitz constant for the gradient of the functional.

gradient

Gradient operator of the functional.

inverse

Return the operator inverse.

is_functional

True if this operator's range is a Field.

is_linear

True if this operator is linear.

proximal

Return the proximal factory of the functional.

range

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

Methods

__call__(x[, out])

Return self(x[, out, **kwargs]).

bregman(point, subgrad)

Return the Bregman distance functional.

derivative(point)

Return the derivative operator in the given point.

norm([estimate])

Return the operator norm of this operator.

translated(shift)

Return a translation of the functional.

__init__(space, exponent)[source]

Initialize a new instance.

Parameters:
spaceDiscretizedSpace or TensorSpace

Domain of the functional.

exponentint or infinity

Specifies wich norm to use.