GroupL1Norm¶
- class odl.solvers.functional.default_functionals.GroupL1Norm(*args, **kwargs)[source]¶
Bases:
Functional
The functional corresponding to the mixed L1-Lp norm on
ProductSpace
.The L1-norm,
|| ||x||_p ||_1
, is defined as the integral/sum of||x||_p
, where||x||_p
is the pointwise p-norm.This is also known as the cross norm.
Notes
If the functional is defined on an -like space, the group -norm, denoted is defined as
If the functional is defined on an -like space, the group -norm is defined as
- Attributes:
adjoint
Adjoint of this operator (abstract).
convex_conj
The convex conjugate functional of the group L1-norm.
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 operator inverse.
is_functional
True
if this operator's range is aField
.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__(vfspace, exponent=None)[source]¶
Initialize a new instance.
- Parameters:
- vfspace
ProductSpace
Space of vector fields on which the operator acts. It has to be a product space of identical spaces, i.e. a power space.
- exponentnon-zero float, optional
Exponent of the norm in each point. Values between 0 and 1 are currently not supported due to numerical instability. Infinity gives the supremum norm. Default:
vfspace.exponent
, usually 2.
- vfspace
Examples
>>> space = odl.rn(2) >>> pspace = odl.ProductSpace(space, 2) >>> op = GroupL1Norm(pspace) >>> op([[3, 3], [4, 4]]) 10.0
Set exponent of inner (p) norm:
>>> op2 = GroupL1Norm(pspace, exponent=1) >>> op2([[3, 3], [4, 4]]) 14.0