pymor.algorithms.to_matrix

Module Contents

class pymor.algorithms.to_matrix.ToMatrixRules(format, mu)

Bases: pymor.algorithms.rules.RuleTable

Define algorithm by a table of match conditions and corresponding actions.

RuleTable manages a table of rules, stored in the rules attributes, which can be applied to given objects.

A new table is created by subclassing RuleTable and defining new methods which are decorated with match_class, match_generic or another rule subclass. The order of the method definitions determines the order in which the defined rules are applied.

Parameters

use_caching

If True, cache results of apply.

rules

list of all defined rules.

Methods

action_AdjointOperator
action_BlockOperator
action_ComponentProjectionOperator
action_ConcatenationOperator
action_IdentityOperator
action_LincombOperator
action_LowRankOperator
action_LowRankUpdatedOperator
action_NumpyHankelOperator
action_NumpyMatrixOperator
action_VectorArrayOperator
action_ZeroOperator
action_as_array

action_AdjointOperator(op)

action_BlockOperator(op)

action_ComponentProjectionOperator(op)

action_ConcatenationOperator(op)

action_IdentityOperator(op)

action_LincombOperator(op)

action_LowRankOperator(op)

action_LowRankUpdatedOperator(op)

action_NumpyHankelOperator(op)

action_NumpyMatrixOperator(op)

action_VectorArrayOperator(op)

action_ZeroOperator(op)

action_as_array(op)

pymor.algorithms.to_matrix.action_DuneXTMatrixOperator(self, op)

pymor.algorithms.to_matrix.to_matrix(op, format=None, mu=None)

Convert a linear Operator to a matrix.

Parameters

op

The Operator to convert.

format

Format of the resulting matrix: NumPy array if ‘dense’, otherwise the appropriate SciPy spmatrix. If None, a choice between dense and sparse format is automatically made.

mu

The parameter values for which to convert op.

Returns

res

The matrix equivalent to op.