Divergence.norm

Divergence.norm(self, estimate=False, \*\*kwargs)

Return the operator norm of this operator.

If this operator is non-linear, this should be the Lipschitz constant.

Parameters

estimatebool

If true, estimate the operator norm. By default, it is estimated using power_method_opnorm, which is only applicable for linear operators. Subclasses are allowed to ignore this parameter if they can provide an exact value.

Returns

normfloat

Other Parameters

kwargs :

If estimate is True, pass these arguments to the power_method_opnorm call.

Examples

Some operators know their own operator norm and do not need an estimate

>>> spc = odl.rn(3)
>>> id = odl.IdentityOperator(spc)
>>> id.norm(True)
1.0

For others, there is no closed form expression and an estimate is needed:

>>> spc = odl.uniform_discr(0, 1, 3)
>>> grad = odl.Gradient(spc)
>>> opnorm = grad.norm(estimate=True)