pymor.reductors package¶
Submodules¶
basic module¶

class
pymor.reductors.basic.
GenericRBReductor
(d, RB=None, orthogonal_projection=('initial_data', ), product=None)[source]¶ Bases:
pymor.core.interfaces.BasicInterface
Generic reduced basis reductor.
Replaces each
Operator
of the givenDiscretization
with the Galerkin projection onto the span of the given reduced basis.Parameters
 d
 The
Discretization
which is to be reduced.  RB
VectorArray
containing the reduced basis on which to project. orthogonal_projection
 List of keys in
d.operators
for which the correspondingOperator
should be orthogonally projected (i.e. operators which map to vectors in contrast to bilinear forms which map to functionals).  product
 Inner product for the projection of the
Operators
given byorthogonal_projection
.
Methods
GenericRBReductor
extend_basis
,reconstruct
,reduce
BasicInterface
disable_logging
,enable_logging
,has_interface_name
,implementor_names
,implementors
Attributes
BasicInterface
logger
,logging_disabled
,name
,uid

extend_basis
(U, method='gram_schmidt', pod_modes=1, pod_orthonormalize=True, copy_U=True)[source]¶ Extend basis by new vectors.
Parameters
 U
VectorArray
containing the new basis vectors. method
Basis extension method to use. The following methods are available:
trivial: Vectors in U
are appended to the basis. Duplicate vectors in the sense ofalmost_equal
are removed.gram_schmidt: New basis vectors are orthonormalized w.r.t. to the old basis using the gram_schmidt
algorithm.pod: Append the first POD modes of the defects of the projections of the vectors in U onto the existing basis (e.g. for use in PODGreedy algorithm). Warning
In case of the
'gram_schmidt'
and'pod'
extension methods, the existing reduced basis is assumed to be orthonormal w.r.t. the given inner product. pod_modes
 In case
method == 'pod'
, the number of POD modes that shall be appended to the basis.  pod_orthonormalize
 If
True
andmethod == 'pod'
, reorthonormalize the new basis vectors obtained by the POD in order to improve numerical accuracy.  copy_U
 If
copy_U
isFalse
, the new basis vectors might be removed fromU
.
Raises
 ExtensionError
 Raised when the selected extension method does not yield a basis of increased dimension.

reduce
(dim=None)[source]¶ Perform the reduced basis projection.
Parameters
 dim
 If specified, the desired reduced state dimension. Must not be larger than the current reduced basis dimension.
Returns
The reduced
Discretization
.
coercive module¶

class
pymor.reductors.coercive.
CoerciveRBEstimator
(residual, residual_range_dims, coercivity_estimator)[source]¶ Bases:
pymor.core.interfaces.ImmutableInterface
Instantiated by
CoerciveRBReductor
.Not to be used directly.
Methods
CoerciveRBEstimator
estimate
,restricted_to_subbasis
ImmutableInterface
generate_sid
,with_
,__setattr__
BasicInterface
disable_logging
,enable_logging
,has_interface_name
,implementor_names
,implementors

class
pymor.reductors.coercive.
CoerciveRBReductor
(d, RB=None, orthogonal_projection=('initial_data', ), product=None, coercivity_estimator=None)[source]¶ Bases:
pymor.reductors.basic.GenericRBReductor
Reduced Basis reductor for
StationaryDiscretizations
with coercive linear operator.The only addition to
GenericRBReductor
is an error estimator which evaluates the dual norm of the residual with respect to a given inner product. For the reduction of the residual we useResidualReductor
for improved numerical stability [BEOR14].[BEOR14] (1, 2) A. Buhr, C. Engwer, M. Ohlberger, S. Rave, A Numerically Stable A Posteriori Error Estimator for Reduced Basis Approximations of Elliptic Equations, Proceedings of the 11th World Congress on Computational Mechanics, 2014. Parameters
 d
 The
Discretization
which is to be reduced.  RB
VectorArray
containing the reduced basis on which to project. orthogonal_projection
 List of keys in
d.operators
for which the correspondingOperator
should be orthogonally projected (i.e. operators which map to vectors in contrast to bilinear forms which map to functionals).  product
 Inner product for the projection of the
Operators
given byorthogonal_projection
and for the computation of Riesz representatives of the residual. IfNone
, the Euclidean product is used.  coercivity_estimator
None
or aParameterFunctional
returning a lower bound for the coercivity constant of the given problem. Note that the computed error estimate is only guaranteed to be an upper bound for the error when an appropriate coercivity estimate is specified.
Methods
GenericRBReductor
extend_basis
,reconstruct
,reduce
BasicInterface
disable_logging
,enable_logging
,has_interface_name
,implementor_names
,implementors
Attributes
BasicInterface
logger
,logging_disabled
,name
,uid

class
pymor.reductors.coercive.
SimpleCoerciveRBEstimator
(estimator_matrix, coercivity_estimator)[source]¶ Bases:
pymor.core.interfaces.ImmutableInterface
Instantiated by
SimpleCoerciveRBReductor
.Not to be used directly.
Methods
SimpleCoerciveRBEstimator
estimate
,restricted_to_subbasis
ImmutableInterface
generate_sid
,with_
,__setattr__
BasicInterface
disable_logging
,enable_logging
,has_interface_name
,implementor_names
,implementors

class
pymor.reductors.coercive.
SimpleCoerciveRBReductor
(d, RB=None, orthogonal_projection=('initial_data', ), product=None, coercivity_estimator=None)[source]¶ Bases:
pymor.reductors.basic.GenericRBReductor
Reductor for linear
StationaryDiscretizations
with affinely decomposed operator and rhs.Note
The reductor
CoerciveRBReductor
can be used for arbitrary coerciveStationaryDiscretizations
and offers an improved error estimator with better numerical stability.The only addition is to
GenericRBReductor
is an error estimator, which evaluates the norm of the residual with respect to a given inner product.Parameters
 d
 The
Discretization
which is to be reduced.  RB
VectorArray
containing the reduced basis on which to project. orthogonal_projection
 List of keys in
d.operators
for which the correspondingOperator
should be orthogonally projected (i.e. operators which map to vectors in contrast to bilinear forms which map to functionals).  product
 Inner product for the projection of the
Operators
given byorthogonal_projection
and for the computation of Riesz representatives of the residual. IfNone
, the Euclidean product is used.  coercivity_estimator
None
or aParameterFunctional
returning a lower bound for the coercivity constant of the given problem. Note that the computed error estimate is only guaranteed to be an upper bound for the error when an appropriate coercivity estimate is specified.
Methods
GenericRBReductor
extend_basis
,reconstruct
,reduce
BasicInterface
disable_logging
,enable_logging
,has_interface_name
,implementor_names
,implementors
Attributes
BasicInterface
logger
,logging_disabled
,name
,uid
parabolic module¶

class
pymor.reductors.parabolic.
ParabolicRBEstimator
(residual, residual_range_dims, initial_residual, initial_residual_range_dims, coercivity_estimator)[source]¶ Bases:
pymor.core.interfaces.ImmutableInterface
Instantiated by
ParabolicRBReductor
.Not to be used directly.
Methods
ParabolicRBEstimator
estimate
,restricted_to_subbasis
ImmutableInterface
generate_sid
,with_
,__setattr__
BasicInterface
disable_logging
,enable_logging
,has_interface_name
,implementor_names
,implementors

class
pymor.reductors.parabolic.
ParabolicRBReductor
(d, RB=None, product=None, coercivity_estimator=None)[source]¶ Bases:
pymor.reductors.basic.GenericRBReductor
Reduced Basis Reductor for parabolic equations.
This reductor uses
GenericRBReductor
for the actual RBprojection. The only addition is the assembly of an error estimator which bounds the discrete l2in time / energyin space error similar to [GP05], [HO08] as follows:Here, denotes the norm induced by the problem’s mass matrix (e.g. the L^2norm) and is an arbitrary energy norm w.r.t. which the space operator is coercive, and is a lower bound for its coercivity constant. Finally, denotes the implicit Euler timestepping residual for the (fixed) time step size ,
where denotes the mass operator and the source term. The dual norm of the residual is computed using the numerically stable projection from [BEOR14].
Warning
The reduced basis
RB
is required to be orthonormal w.r.t. the given energy product. If not, the projection of the initial values will be computed incorrectly.[GP05] M. A. Grepl, A. T. Patera, A Posteriori Error Bounds For ReducedBasis Approximations Of Parametrized Parabolic Partial Differential Equations, M2AN 39(1), 157181, 2005. [HO08] B. Haasdonk, M. Ohlberger, Reduced basis method for finite volume approximations of parametrized evolution equations, M2AN 42(2), 277302, 2008. Parameters
 d
 The
InstationaryDiscretization
which is to be reduced.  RB
VectorArray
containing the reduced basis on which to project. product
 The energy inner product
Operator
w.r.t. the reduction error is estimated. RB must be to be orthonomrmal w.r.t. this product!  coercivity_estimator
None
or aParameterFunctional
returning a lower bound for the coercivity constant ofd.operator
w.r.t.product
.
Methods
GenericRBReductor
extend_basis
,reconstruct
,reduce
BasicInterface
disable_logging
,enable_logging
,has_interface_name
,implementor_names
,implementors
Attributes
BasicInterface
logger
,logging_disabled
,name
,uid
residual module¶

class
pymor.reductors.residual.
ImplicitEulerResidualOperator
(operator, mass, functional, dt, name=None)[source]¶ Bases:
pymor.operators.basic.OperatorBase
Instantiated by
ImplicitEulerResidualReductor
.Methods
Attributes

apply
(U, U_old, mu=None)[source]¶ Apply the operator to a
VectorArray
.Parameters
 U
VectorArray
of vectors to which the operator is applied. mu
 The
Parameter
for which to evaluate the operator.
Returns
VectorArray
of the operator evaluations.


class
pymor.reductors.residual.
ImplicitEulerResidualReductor
(RB, operator, mass, dt, functional=None, product=None)[source]¶ Bases:
pymor.core.interfaces.BasicInterface
Reduced basis residual reductor with mass operator for implicit Euler timestepping.
Given an operator, mass and a functional, the concatenation of residual operator with the Riesz isomorphism is given by:
riesz_residual.apply(U, U_old, mu) == product.apply_inverse(operator.apply(U, mu) + 1/dt*mass.apply(U, mu)  1/dt*mass.apply(U_old, mu)  functional.as_vector(mu))
This reductor determines a lowdimensional subspace of the image of a reduced basis space under
riesz_residual
usingestimate_image_hierarchical
, computes an orthonormal basisresidual_range
of this range space and then returns the PetrovGalerkin projectionprojected_riesz_residual == riesz_residual.projected(range_basis=residual_range, source_basis=RB)
of the
riesz_residual
operator. Given reduced basis coefficient vectorsu
andu_old
, the dual norm of the residual can then be computed asprojected_riesz_residual.apply(u, u_old, mu).l2_norm()
Moreover, a
reconstruct
method is provided such thatresidual_reductor.reconstruct(projected_riesz_residual.apply(u, u_old, mu)) == riesz_residual.apply(RB.lincomb(u), RB.lincomb(u_old), mu)
Parameters
 operator
 See definition of
riesz_residual
.  mass
 The mass operator. See definition of
riesz_residual
.  dt
 The time step size. See definition of
riesz_residual
.  functional
 See definition of
riesz_residual
. IfNone
, zero righthand side is assumed.  RB
VectorArray
containing a basis of the reduced space onto which to project. product
 Inner product
Operator
w.r.t. which to compute the Riesz representatives.
Methods
ImplicitEulerResidualReductor
reconstruct
,reduce
BasicInterface
disable_logging
,enable_logging
,has_interface_name
,implementor_names
,implementors
Attributes
BasicInterface
logger
,logging_disabled
,name
,uid

class
pymor.reductors.residual.
NonProjectedImplicitEulerResidualOperator
(operator, mass, functional, dt, product)[source]¶ Bases:
pymor.reductors.residual.ImplicitEulerResidualOperator
Instantiated by
ImplicitEulerResidualReductor
.Not to be used directly.
Methods
Attributes

apply
(U, U_old, mu=None)[source]¶ Apply the operator to a
VectorArray
.Parameters
 U
VectorArray
of vectors to which the operator is applied. mu
 The
Parameter
for which to evaluate the operator.
Returns
VectorArray
of the operator evaluations.


class
pymor.reductors.residual.
NonProjectedResidualOperator
(operator, rhs, rhs_is_functional, product)[source]¶ Bases:
pymor.reductors.residual.ResidualOperator
Instantiated by
ResidualReductor
.Not to be used directly.
Methods
Attributes

apply
(U, mu=None)[source]¶ Apply the operator to a
VectorArray
.Parameters
 U
VectorArray
of vectors to which the operator is applied. mu
 The
Parameter
for which to evaluate the operator.
Returns
VectorArray
of the operator evaluations.


class
pymor.reductors.residual.
ResidualOperator
(operator, rhs, rhs_is_functional=True, name=None)[source]¶ Bases:
pymor.operators.basic.OperatorBase
Instantiated by
ResidualReductor
.Methods
Attributes

apply
(U, mu=None)[source]¶ Apply the operator to a
VectorArray
.Parameters
 U
VectorArray
of vectors to which the operator is applied. mu
 The
Parameter
for which to evaluate the operator.
Returns
VectorArray
of the operator evaluations.


class
pymor.reductors.residual.
ResidualReductor
(RB, operator, rhs=None, product=None)[source]¶ Bases:
pymor.core.interfaces.BasicInterface
Generic reduced basis residual reductor.
Given an operator and a righthand side, the residual is given by:
residual.apply(U, mu) == operator.apply(U, mu)  rhs.as_vector(mu)
When the rhs is a functional we are interested in the Riesz representative of the residual:
residual.apply(U, mu) == product.apply_inverse(operator.apply(U, mu)  rhs.as_vector(mu))
Given a basis
RB
of a subspace of the source space ofoperator
, this reductor usesestimate_image_hierarchical
to determine a lowdimensional subspace containing the image of the subspace underresidual
(resp.riesz_residual
), computes an orthonormal basisresidual_range
for this range space and then returns the PetrovGalerkin projectionprojected_residual == project(residual, range_basis=residual_range, source_basis=RB)
of the residual operator. Given a reduced basis coefficient vector
u
, w.r.t.RB
, the (dual) norm of the residual can then be computed asprojected_residual.apply(u, mu).l2_norm()
Moreover, a
reconstruct
method is provided such thatresidual_reductor.reconstruct(projected_residual.apply(u, mu)) == residual.apply(RB.lincomb(u), mu)
Parameters
 RB
VectorArray
containing a basis of the reduced space onto which to project. operator
 See definition of
residual
.  rhs
 See definition of
residual
. IfNone
, zero righthand side is assumed.  product
 Inner product
Operator
w.r.t. which to orthonormalize and w.r.t. which to compute the Riesz representatives in caserhs
is a functional.
Methods
ResidualReductor
reconstruct
,reduce
BasicInterface
disable_logging
,enable_logging
,has_interface_name
,implementor_names
,implementors
Attributes
BasicInterface
logger
,logging_disabled
,name
,uid