`pymor.reductors.basic`¶

Module Contents¶

class pymor.reductors.basic.DelayLTIPGReductor(fom, W, V, E_biorthonormal=False)[source]¶

Bases: ProjectionBasedReductor

Petrov-Galerkin projection of an LinearDelayModel.

Parameters

fom: The full order Model to reduce.
W: The basis of the test space.
V: The basis of the ansatz space.
E_biorthonormal: If True, no E matrix will be assembled for the reduced Model. Set to True if W and V are biorthonormal w.r.t. fom.E.

Methods

`build_rom`
`extend_basis`
`project_operators`
`project_operators_to_subbasis`
`reconstruct`	Reconstruct high-dimensional vector from reduced vector `u`.

build_rom(projected_operators, error_estimator)[source]¶

abstract extend_basis(**kwargs)[source]¶

project_operators()[source]¶

project_operators_to_subbasis(dims)[source]¶

reconstruct(u, basis='V')[source]¶: Reconstruct high-dimensional vector from reduced vector u.

class pymor.reductors.basic.InstationaryRBReductor(fom, RB=None, product=None, initial_data_product=None, product_is_mass=False, check_orthonormality=None, check_tol=None)[source]¶

Bases: ProjectionBasedReductor

Galerkin projection of an InstationaryModel.

Parameters

fom: The full order Model to reduce.
RB: The basis of the reduced space onto which to project. If None an empty basis is used.
product: Inner product Operator w.r.t. which RB is orthonormalized. If None, the the Euclidean inner product is used.
initial_data_product: Inner product Operator w.r.t. which the initial_data of fom is orthogonally projected. If None, the Euclidean inner product is used.
product_is_mass: If True, no mass matrix for the reduced Model is assembled. Set to True if RB is orthonormal w.r.t. the mass matrix of fom.
check_orthonormality: See ProjectionBasedReductor.
check_tol: See ProjectionBasedReductor.

Methods

`build_rom`
`project_operators`
`project_operators_to_subbasis`

build_rom(projected_operators, error_estimator)[source]¶

project_operators()[source]¶

project_operators_to_subbasis(dims)[source]¶

class pymor.reductors.basic.LTIPGReductor(fom, W, V, E_biorthonormal=False)[source]¶

Bases: ProjectionBasedReductor

Petrov-Galerkin projection of an LTIModel.

Parameters

fom: The full order Model to reduce.
W: The basis of the test space.
V: The basis of the ansatz space.
E_biorthonormal: If True, no E matrix will be assembled for the reduced Model. Set to True if W and V are biorthonormal w.r.t. fom.E.

Methods

`build_rom`
`extend_basis`
`project_operators`
`project_operators_to_subbasis`
`reconstruct`	Reconstruct high-dimensional vector from reduced vector `u`.

build_rom(projected_operators, error_estimator)[source]¶

abstract extend_basis(**kwargs)[source]¶

project_operators()[source]¶

project_operators_to_subbasis(dims)[source]¶

reconstruct(u, basis='V')[source]¶: Reconstruct high-dimensional vector from reduced vector u.

class pymor.reductors.basic.ProjectionBasedReductor(fom, bases, products={}, check_orthonormality=True, check_tol=0.001)[source]¶

Bases: pymor.core.base.BasicObject

Generic projection based reductor.

Parameters

fom: The full order Model to reduce.
bases: A dict of VectorArrays of basis vectors.
products: A dict of inner product Operators w.r.t. which the corresponding bases are orthonormalized. A value of None corresponds to orthonormalization of the basis w.r.t. the Euclidean inner product.
check_orthonormality: If True, check if bases which have a corresponding entry in the products dict are orthonormal w.r.t. the given inner product. After each basis extension, orthonormality is checked again.
check_tol: If check_orthonormality is True, the numerical tolerance with which the checks are performed.

Methods

`assemble_error_estimator`
`assemble_error_estimator_for_subbasis`
`build_rom`
`extend_basis`
`project_operators`
`project_operators_to_subbasis`
`reconstruct`	Reconstruct high-dimensional vector from reduced vector `u`.
`reduce`

assemble_error_estimator()[source]¶

assemble_error_estimator_for_subbasis(dims)[source]¶

abstract build_rom(projected_operators, error_estimator)[source]¶

extend_basis(U, basis='RB', method='gram_schmidt', pod_modes=1, pod_orthonormalize=True, copy_U=True)[source]¶

abstract project_operators()[source]¶

abstract project_operators_to_subbasis(dims)[source]¶

reconstruct(u, basis='RB')[source]¶: Reconstruct high-dimensional vector from reduced vector u.

reduce(dims=None)[source]¶

class pymor.reductors.basic.SOLTIPGReductor(fom, W, V, M_biorthonormal=False)[source]¶

Bases: ProjectionBasedReductor

Petrov-Galerkin projection of an SecondOrderModel.

Parameters

fom: The full order Model to reduce.
W: The basis of the test space.
V: The basis of the ansatz space.
E_biorthonormal: If True, no E matrix will be assembled for the reduced Model. Set to True if W and V are biorthonormal w.r.t. fom.E.

Methods

`build_rom`
`extend_basis`
`project_operators`
`project_operators_to_subbasis`
`reconstruct`	Reconstruct high-dimensional vector from reduced vector `u`.

build_rom(projected_operators, error_estimator)[source]¶

abstract extend_basis(**kwargs)[source]¶

project_operators()[source]¶

project_operators_to_subbasis(dims)[source]¶

reconstruct(u, basis='V')[source]¶: Reconstruct high-dimensional vector from reduced vector u.

class pymor.reductors.basic.StationaryRBReductor(fom, RB=None, product=None, check_orthonormality=None, check_tol=None)[source]¶

Bases: ProjectionBasedReductor

Galerkin projection of a StationaryModel.

Parameters

fom: The full order Model to reduce.
RB: The basis of the reduced space onto which to project. If None an empty basis is used.
product: Inner product Operator w.r.t. which RB is orthonormalized. If None, the Euclidean inner product is used.
check_orthonormality: See ProjectionBasedReductor.
check_tol: See ProjectionBasedReductor.

Methods

`build_rom`
`project_operators`
`project_operators_to_subbasis`

build_rom(projected_operators, error_estimator)[source]¶

project_operators()[source]¶

project_operators_to_subbasis(dims)[source]¶

pymor.reductors.basic.extend_basis(U, basis, product=None, method='gram_schmidt', pod_modes=1, pod_orthonormalize=True, copy_U=True)[source]¶

pymor.reductors.basic¶

Module Contents¶

`pymor.reductors.basic`¶