/usr/include/trilinos/ROL_HelperFunctions.hpp is in libtrilinos-rol-dev 12.10.1-3.
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// ************************************************************************
//
// Rapid Optimization Library (ROL) Package
// Copyright (2014) Sandia Corporation
//
// Under terms of Contract DE-AC04-94AL85000, there is a non-exclusive
// license for use of this work by or on behalf of the U.S. Government.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
// 1. Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
//
// 2. Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// 3. Neither the name of the Corporation nor the names of the
// contributors may be used to endorse or promote products derived from
// this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY
// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE
// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
//
// Questions? Contact lead developers:
// Drew Kouri (dpkouri@sandia.gov) and
// Denis Ridzal (dridzal@sandia.gov)
//
// ************************************************************************
// @HEADER
/** \file
\brief Contains definitions for helper functions in ROL.
\author Created by D. Ridzal and D. Kouri.
*/
#ifndef ROL_HELPERFUNCTIONS_HPP
#define ROL_HELPERFUNCTIONS_HPP
#include "ROL_Vector.hpp"
#include "ROL_Objective.hpp"
#include "ROL_BoundConstraint.hpp"
#include "ROL_Secant.hpp"
#include "Teuchos_SerialDenseMatrix.hpp"
#include "Teuchos_SerialDenseVector.hpp"
#include "Teuchos_LAPACK.hpp"
namespace ROL {
template<class Real>
Teuchos::SerialDenseMatrix<int, Real> computeDenseHessian(Objective<Real> &obj, const Vector<Real> &x) {
Real tol = std::sqrt(ROL_EPSILON<Real>());
int dim = x.dimension();
Teuchos::SerialDenseMatrix<int, Real> H(dim, dim);
Teuchos::RCP<Vector<Real> > e = x.clone();
Teuchos::RCP<Vector<Real> > h = x.clone();
for (int i=0; i<dim; i++) {
e = x.basis(i);
obj.hessVec(*h, *e, x, tol);
for (int j=0; j<dim; j++) {
e = x.basis(j);
H(j,i) = e->dot(*h);
}
}
return H;
}
template<class Real>
Teuchos::SerialDenseMatrix<int, Real> computeDotMatrix(const Vector<Real> &x) {
int dim = x.dimension();
Teuchos::SerialDenseMatrix<int, Real> M(dim, dim);
Teuchos::RCP<Vector<Real> > ei = x.clone();
Teuchos::RCP<Vector<Real> > ej = x.clone();
for (int i=0; i<dim; i++) {
ei = x.basis(i);
for (int j=0; j<dim; j++) {
ej = x.basis(j);
M(j,i) = ej->dot(*ei);
}
}
return M;
}
template<class Real>
std::vector<std::vector<Real> > computeEigenvalues(const Teuchos::SerialDenseMatrix<int, Real> & mat) {
Teuchos::LAPACK<int, Real> lapack;
Teuchos::SerialDenseMatrix<int, Real> mymat(Teuchos::Copy, mat);
char jobvl = 'N';
char jobvr = 'N';
int n = mat.numRows();
std::vector<Real> real(n, 0);
std::vector<Real> imag(n, 0);
std::vector<std::vector<Real> > eigenvals;
Real* vl = 0;
Real* vr = 0;
int ldvl = 1;
int ldvr = 1;
int lwork = 4*n;
std::vector<Real> work(lwork, 0);
int info = 0;
lapack.GEEV(jobvl, jobvr, n, &mymat(0,0), n, &real[0], &imag[0], vl, ldvl, vr, ldvr, &work[0], lwork, &info);
eigenvals.push_back(real);
eigenvals.push_back(imag);
return eigenvals;
}
template<class Real>
std::vector<std::vector<Real> > computeGenEigenvalues(const Teuchos::SerialDenseMatrix<int, Real> & A,
const Teuchos::SerialDenseMatrix<int, Real> & B) {
Teuchos::LAPACK<int, Real> lapack;
Teuchos::SerialDenseMatrix<int, Real> myA(Teuchos::Copy, A);
Teuchos::SerialDenseMatrix<int, Real> myB(Teuchos::Copy, B);
char jobvl = 'N';
char jobvr = 'N';
int n = A.numRows();
std::vector<Real> real(n, 0);
std::vector<Real> imag(n, 0);
std::vector<Real> beta(n, 0);
std::vector<std::vector<Real> > eigenvals;
Real* vl = 0;
Real* vr = 0;
int ldvl = 1;
int ldvr = 1;
int lwork = 10*n;
std::vector<Real> work(lwork, 0);
int info = 0;
lapack.GGEV(jobvl, jobvr, n, &myA(0,0), n, &myB(0,0), n, &real[0], &imag[0], &beta[0],
vl, ldvl, vr, ldvr, &work[0], lwork, &info);
for (int i=0; i<n; i++) {
real[i] /= beta[i];
imag[i] /= beta[i];
}
eigenvals.push_back(real);
eigenvals.push_back(imag);
return eigenvals;
}
template<class Real>
Teuchos::SerialDenseMatrix<int, Real> computeInverse(const Teuchos::SerialDenseMatrix<int, Real> & mat) {
Teuchos::LAPACK<int, Real> lapack;
Teuchos::SerialDenseMatrix<int, Real> mymat(Teuchos::Copy, mat);
int n = mat.numRows();
std::vector<int> ipiv(n, 0);
int lwork = 5*n;
std::vector<Real> work(lwork, 0);
int info = 0;
lapack.GETRF(n, n, &mymat(0,0), n, &ipiv[0], &info);
lapack.GETRI(n, &mymat(0,0), n, &ipiv[0], &work[0], lwork, &info);
return mymat;
}
template<class Real>
class ProjectedObjective : public Objective<Real> {
private:
Teuchos::RCP<Objective<Real> > obj_;
Teuchos::RCP<BoundConstraint<Real> > con_;
Teuchos::RCP<Secant<Real> > secant_;
Teuchos::RCP<ROL::Vector<Real> > primalV_;
Teuchos::RCP<ROL::Vector<Real> > dualV_;
bool isInitialized_;
bool useSecantPrecond_;
bool useSecantHessVec_;
Real eps_;
public:
ProjectedObjective( Objective<Real> &obj, BoundConstraint<Real> &con,
Teuchos::RCP<Secant<Real> > &secant,
bool useSecantPrecond = false,
bool useSecantHessVec = false,
Real eps = 0.0 )
: isInitialized_(false), useSecantPrecond_(useSecantPrecond),
useSecantHessVec_(useSecantHessVec), eps_(eps) {
obj_ = Teuchos::rcpFromRef(obj);
con_ = Teuchos::rcpFromRef(con);
secant_ = secant;
}
void update( const Vector<Real> &x, bool flag = true, int iter = -1 ) {
obj_->update(x,flag,iter);
con_->update(x,flag,iter);
}
Real value( const Vector<Real> &x, Real &tol ) {
return obj_->value(x,tol);
}
void gradient( Vector<Real> &g, const Vector<Real> &x, Real &tol ) {
obj_->gradient(g,x,tol);
}
Real dirDeriv( const Vector<Real> &x, const Vector<Real> &d, Real &tol ) {
return obj_->dirDeriv(x,d,tol);
}
void hessVec( Vector<Real> &Hv, const Vector<Real> &v, const Vector<Real> &x, Real &tol ) {
if ( useSecantHessVec_ ) {
secant_->applyB( Hv, v );
}
else {
obj_->hessVec( Hv, v, x, tol );
}
}
void invHessVec( Vector<Real> &Hv, const Vector<Real> &v, const Vector<Real> &x, Real &tol ) {
if ( useSecantHessVec_ ) {
secant_->applyH(Hv,v);
}
else {
obj_->invHessVec(Hv,v,x,tol);
}
}
void precond( Vector<Real> &Mv, const Vector<Real> &v, const Vector<Real> &x, Real &tol ) {
if ( useSecantPrecond_ ) {
secant_->applyH( Mv, v );
}
else {
obj_->precond( Mv, v, x, tol );
}
}
/** \brief Apply the reduced Hessian to a vector, v.
The reduced Hessian first removes elements of v
corresponding to the feasible indices from
the point p in the direction -d.
Hv the Hessian times a vector
v input vector
p starting point for tangent cone
d negative of search direction
x current iteration vector
tol objective function tolerance
*/
void reducedHessVec( Vector<Real> &Hv, const Vector<Real> &v, const Vector<Real> &p,
const Vector<Real> &d, const Vector<Real> &x, Real &tol ) {
if ( con_->isActivated() ) {
if (!isInitialized_) {
primalV_ = x.clone();
dualV_ = x.dual().clone();
isInitialized_ = true;
}
// Set vnew to v
primalV_->set(v);
// Remove elements of vnew corresponding to binding set
con_->pruneActive(*primalV_,d,p,eps_);
// Apply full Hessian to reduced vector
hessVec(Hv,*primalV_,x,tol);
// Remove elements of Hv corresponding to binding set
con_->pruneActive(Hv,d,p,eps_);
// Set vnew to v
primalV_->set(v);
// Remove Elements of vnew corresponding to complement of binding set
con_->pruneInactive(*primalV_,d,p,eps_);
dualV_->set(primalV_->dual());
con_->pruneInactive(*dualV_,d,p,eps_);
// Fill complement of binding set elements in Hp with v
Hv.plus(*dualV_);
}
else {
hessVec(Hv,v,x,tol);
}
}
/** \brief Apply the reduced Hessian to a vector, v.
The reduced Hessian first removes elements of v
corresponding to the feasible indices from
the point p.
Hv the Hessian times a vector
v input vector
p starting point for tangent cone
x current iteration vector
tol objective function tolerance
*/
void reducedHessVec( Vector<Real> &Hv, const Vector<Real> &v, const Vector<Real> &p,
const Vector<Real> &x, Real &tol ) {
if ( con_->isActivated() ) {
if (!isInitialized_) {
primalV_ = x.clone();
dualV_ = x.dual().clone();
isInitialized_ = true;
}
// Set vnew to v
primalV_->set(v);
// Remove elements of vnew corresponding to binding set
con_->pruneActive(*primalV_,p,eps_);
// Apply full Hessian to reduced vector
hessVec(Hv,*primalV_,x,tol);
// Remove elements of Hv corresponding to binding set
con_->pruneActive(Hv,p,eps_);
// Set vnew to v
primalV_->set(v);
// Remove Elements of vnew corresponding to complement of binding set
con_->pruneInactive(*primalV_,p,eps_);
dualV_->set(primalV_->dual());
con_->pruneInactive(*dualV_,p,eps_);
// Fill complement of binding set elements in Hp with v
Hv.plus(*dualV_);
}
else {
hessVec(Hv,v,x,tol);
}
}
/** \brief Apply the reduced inverse Hessian to a vector, v.
The reduced inverse Hessian first removes elements
of v corresponding to the feasible indices from
the point p in the direction -d.
Hv the inverse Hessian times a vector
v input vector
p starting point for tangent cone
d negative of search direction
x current iteration vector
tol objective function tolerance
*/
void reducedInvHessVec( Vector<Real> &Hv, const Vector<Real> &v, const Vector<Real> &p,
const Vector<Real> &d, const Vector<Real> &x, Real &tol ) {
if ( con_->isActivated() ) {
if (!isInitialized_) {
primalV_ = x.clone();
dualV_ = x.dual().clone();
isInitialized_ = true;
}
// Set vnew to v
dualV_->set(v);
// Remove elements of vnew corresponding to binding set
con_->pruneActive(*dualV_,d,p,eps_);
// Apply full Hessian to reduced vector
invHessVec(Hv,*dualV_,x,tol);
// Remove elements of Hv corresponding to binding set
con_->pruneActive(Hv,d,p,eps_);
// Set vnew to v
dualV_->set(v);
// Remove Elements of vnew corresponding to complement of binding set
con_->pruneInactive(*dualV_,d,p,eps_);
primalV_->set(dualV_->dual());
con_->pruneInactive(*primalV_,d,p,eps_);
// Fill complement of binding set elements in Hv with v
Hv.plus(*primalV_);
}
else {
invHessVec(Hv,v,x,tol);
}
}
/** \brief Apply the reduced inverse Hessian to a vector, v.
The reduced inverse Hessian first removes elements
of v corresponding to the feasible indices from
the point p.
Hv the inverse Hessian times a vector
v input vector
p starting point for tangent cone
x current iteration vector
tol objective function tolerance
*/
void reducedInvHessVec( Vector<Real> &Hv, const Vector<Real> &v, const Vector<Real> &p,
const Vector<Real> &x, Real &tol ) {
if ( con_->isActivated() ) {
if (!isInitialized_) {
primalV_ = x.clone();
dualV_ = x.dual().clone();
isInitialized_ = true;
}
// Set vnew to v
dualV_->set(v);
// Remove elements of vnew corresponding to binding set
con_->pruneActive(*dualV_,p,eps_);
// Apply full Hessian to reduced vector
invHessVec(Hv,*dualV_,x,tol);
// Remove elements of Hv corresponding to binding set
con_->pruneActive(Hv,p,eps_);
// Set vnew to v
dualV_->set(v);
// Remove Elements of vnew corresponding to complement of binding set
con_->pruneInactive(*dualV_,p,eps_);
primalV_->set(dualV_->dual());
con_->pruneInactive(*primalV_,p,eps_);
// Fill complement of binding set elements in Hv with v
Hv.plus(*primalV_);
}
else {
invHessVec(Hv,v,x,tol);
}
}
/** \brief Apply the reduced preconditioner to a vector, v.
The reduced preconditioner first removes elements
of v corresponding to the feasible indices from
the point p in the direction -d.
Hv the preconditioner times a vector
v input vector
p starting point for tangent cone
d negative of search direction
x current iteration vector
tol objective function tolerance
*/
void reducedPrecond( Vector<Real> &Mv, const Vector<Real> &v, const Vector<Real> &p,
const Vector<Real> &d, const Vector<Real> &x, Real &tol ) {
if ( con_->isActivated() ) {
if (!isInitialized_) {
primalV_ = x.clone();
dualV_ = x.dual().clone();
isInitialized_ = true;
}
// Set vnew to v
dualV_->set(v);
// Remove elements of vnew corresponding to binding set
con_->pruneActive(*dualV_,d,p,eps_);
// Apply full Hessian to reduced vector
precond(Mv,*dualV_,x,tol);
// Remove elements of Mv corresponding to binding set
con_->pruneActive(Mv,d,p,eps_);
// Set vnew to v
dualV_->set(v);
// Remove Elements of vnew corresponding to complement of binding set
con_->pruneInactive(*dualV_,d,p,eps_);
primalV_->set(dualV_->dual());
con_->pruneInactive(*primalV_,d,p,eps_);
// Fill complement of binding set elements in Mv with v
Mv.plus(*primalV_);
}
else {
precond(Mv,v,x,tol);
}
}
/** \brief Apply the reduced preconditioner to a vector, v.
The reduced preconditioner first removes elements
of v corresponding to the feasible indices from
the point p.
Hv the preconditioner times a vector
v input vector
p starting point for tangent cone
x current iteration vector
tol objective function tolerance
*/
void reducedPrecond( Vector<Real> &Mv, const Vector<Real> &v, const Vector<Real> &p,
const Vector<Real> &x, Real &tol ) {
if ( con_->isActivated() ) {
if (!isInitialized_) {
primalV_ = x.clone();
dualV_ = x.dual().clone();
isInitialized_ = true;
}
// Set vnew to v
dualV_->set(v);
// Remove elements of vnew corresponding to binding set
con_->pruneActive(*dualV_,p,eps_);
// Apply full Hessian to reduced vector
precond(Mv,*dualV_,x,tol);
// Remove elements of Mv corresponding to binding set
con_->pruneActive(Mv,p,eps_);
// Set vnew to v
dualV_->set(v);
// Remove Elements of vnew corresponding to complement of binding set
con_->pruneInactive(*dualV_,p,eps_);
primalV_->set(dualV_->dual());
con_->pruneInactive(*primalV_,p,eps_);
// Fill complement of binding set elements in Mv with v
Mv.plus(*primalV_);
}
else {
precond(Mv,v,x,tol);
}
}
void project( Vector<Real> &x ) {
con_->project(x);
}
void pruneActive( Vector<Real> &v, const Vector<Real> &g, const Vector<Real> &x ) {
con_->pruneActive(v,g,x,eps_);
}
void pruneActive( Vector<Real> &v, const Vector<Real> &x ) {
con_->pruneActive(v,x,eps_);
}
void pruneInactive( Vector<Real> &v, const Vector<Real> &g, const Vector<Real> &x ) {
con_->pruneInactive(v,g,x,eps_);
}
void pruneInactive( Vector<Real> &v, const Vector<Real> &x ) {
con_->pruneInactive(v,x,eps_);
}
bool isFeasible( const Vector<Real> &v ) {
return con_->isFeasible(v);
}
bool isConActivated(void) {
return con_->isActivated();
}
void computeProjectedStep( Vector<Real> &v, const Vector<Real> &x ) {
con_->computeProjectedStep(v,x);
}
};
} // namespace ROL
#endif
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