int meibo_input(LPMYDATA lp)
{
int index = index_input();
if (index == -1) return -1;
LPMYDATA lp_target = lp + index;
printf("-- INPUT [%d]--\n", index);
printf("your name:");
gets(lp_target->name);
printf("your email:");
gets(lp_target->email);
}
int meibo_output(LPMYDATA lp)
{
int index = index_input();
if (index == -1) return -1;
LPMYDATA lp_target = lp + index;
printf("-- OUTPUT [%d]--\n", index);
if (strcmp(lp_target->name ,"") == 0) {
printf("NO DATA\n");
return -1;
}
printf("name : %s\n", lp_target->name);
printf("email : %s\n", lp_target->email);
}
// Solves turning point equations via classic Salinger bordering
// The first m columns of input_x and input_null store the RHS while
// the last column stores df/dp, d(Jn)/dp respectively. Note however
// input_param has only m columns (not m+1). result_x, result_null,
// are result_param have the same dimensions as their input counterparts
NOX::Abstract::Group::ReturnType
LOCA::TurningPoint::MooreSpence::PhippsBordering::solveTransposeContiguous(
Teuchos::ParameterList& params,
const NOX::Abstract::MultiVector& input_x,
const NOX::Abstract::MultiVector& input_null,
const NOX::Abstract::MultiVector::DenseMatrix& input_param,
NOX::Abstract::MultiVector& result_x,
NOX::Abstract::MultiVector& result_null,
NOX::Abstract::MultiVector::DenseMatrix& result_param) const
{
std::string callingFunction =
"LOCA::TurningPoint::MooreSpence::PhippsBordering::solveTransposeContiguous()";
NOX::Abstract::Group::ReturnType finalStatus = NOX::Abstract::Group::Ok;
NOX::Abstract::Group::ReturnType status;
int m = input_x.numVectors()-2;
std::vector<int> index_input(m);
std::vector<int> index_input_dp(m+1);
std::vector<int> index_null(1);
std::vector<int> index_dp(1);
for (int i=0; i<m; i++) {
index_input[i] = i;
index_input_dp[i] = i;
}
index_input_dp[m] = m;
index_dp[0] = m;
index_null[0] = m+1;
NOX::Abstract::MultiVector::DenseMatrix tmp_mat_1(1, m+1);
NOX::Abstract::MultiVector::DenseMatrix tmp_mat_2(1, m+2);
// Create view of first m+1 columns of input_null, result_null
Teuchos::RCP<NOX::Abstract::MultiVector> input_null_view =
input_null.subView(index_input_dp);
Teuchos::RCP<NOX::Abstract::MultiVector> result_null_view =
result_null.subView(index_input_dp);
// verify underlying Jacobian is valid
if (!group->isJacobian()) {
status = group->computeJacobian();
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(status,
finalStatus,
callingFunction);
}
// Solve |J^T v||A B| = |G -phi|
// |u^T 0||a b| |0 0 |
status =
transposeBorderedSolver->applyInverseTranspose(params,
input_null_view.get(),
NULL,
*result_null_view,
tmp_mat_1);
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(status, finalStatus,
callingFunction);
Teuchos::RCP<NOX::Abstract::MultiVector> A =
result_null.subView(index_input);
Teuchos::RCP<NOX::Abstract::MultiVector> B =
result_null.subView(index_dp);
double b = tmp_mat_1(0,m);
// compute (Jv)_x^T[A B u]
result_null[m+1] = *uVector;
Teuchos::RCP<NOX::Abstract::MultiVector> tmp =
result_null.clone(NOX::ShapeCopy);
status = group->computeDwtJnDxMulti(result_null, *nullVector, *tmp);
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(status,
finalStatus,
callingFunction);
// compute [F 0 0] - (Jv)_x^T[A B u]
tmp->update(1.0, input_x, -1.0);
// verify underlying Jacobian is valid
if (!group->isJacobian()) {
status = group->computeJacobian();
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(status,
finalStatus,
callingFunction);
}
// Solve |J^T v||C D E| = |F - (Jv)_x^T A -(Jv)_x^T B -(Jv)_x^T u|
// |u^T 0||c d e| | 0 0 0 |
status =
transposeBorderedSolver->applyInverseTranspose(params,
tmp.get(),
NULL,
result_x,
tmp_mat_2);
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(status, finalStatus,
callingFunction);
Teuchos::RCP<NOX::Abstract::MultiVector> C =
result_x.subView(index_input);
Teuchos::RCP<NOX::Abstract::MultiVector> D =
result_x.subView(index_dp);
Teuchos::RCP<NOX::Abstract::MultiVector> E =
result_x.subView(index_null);
double d = tmp_mat_2(0, m);
double e = tmp_mat_2(0, m+1);
// compute (Jv)_p^T*[A B u]
NOX::Abstract::MultiVector::DenseMatrix t1(1,m+2);
result_null.multiply(1.0, *dJndp, t1);
// compute f_p^T*[C D E]
NOX::Abstract::MultiVector::DenseMatrix t2(1,m+2);
result_x.multiply(1.0, *dfdp, t2);
// compute f_p^T*u
double fptu = uVector->innerProduct((*dfdp)[0]);
// Fill coefficient arrays
double M[9];
M[0] = st; M[1] = -e; M[2] = t1(0,m+1) + t2(0,m+1);
M[3] = 0.0; M[4] = st; M[5] = fptu;
M[6] = -b; M[7] = -d; M[8] = t1(0,m) + t2(0,m);
// Compute RHS
double *R = new double[3*m];
for (int i=0; i<m; i++) {
R[3*i] = tmp_mat_1(0,i);
R[3*i+1] = tmp_mat_2(0,i);
R[3*i+2] = result_param(0,i) - t1(0,i) - t2(0,i);
}
// Solve M*P = R
int three = 3;
int piv[3];
int info;
Teuchos::LAPACK<int,double> L;
L.GESV(three, m, M, three, piv, R, three, &info);
if (info != 0) {
globalData->locaErrorCheck->throwError(
callingFunction,
"Solve of 3x3 coefficient matrix failed!");
return NOX::Abstract::Group::Failed;
}
NOX::Abstract::MultiVector::DenseMatrix alpha(1,m);
NOX::Abstract::MultiVector::DenseMatrix beta(1,m);
for (int i=0; i<m; i++) {
alpha(0,i) = R[3*i];
beta(0,i) = R[3*i+1];
result_param(0,i) = R[3*i+2];
}
// compute A = A + B*z + alpha*u (remember A is a sub-view of result_null)
A->update(Teuchos::NO_TRANS, 1.0, *B, result_param, 1.0);
A->update(Teuchos::NO_TRANS, 1.0, *uMultiVector, alpha, 1.0);
// compute C = C + D*z + alpha*E + beta*u
// (remember C is a sub-view of result_x)
C->update(Teuchos::NO_TRANS, 1.0, *D, result_param, 1.0);
C->update(Teuchos::NO_TRANS, 1.0, *E, alpha, 1.0);
C->update(Teuchos::NO_TRANS, 1.0, *uMultiVector, beta, 1.0);
delete [] R;
return finalStatus;
}
// Solves turning point equations via Phipps modified bordering
// The first m columns of input_x and input_null store the RHS while
// the last column stores df/dp, d(Jn)/dp respectively. Note however
// input_param has only m columns (not m+1). result_x, result_null,
// are result_param have the same dimensions as their input counterparts
NOX::Abstract::Group::ReturnType
LOCA::TurningPoint::MooreSpence::PhippsBordering::solveContiguous(
Teuchos::ParameterList& params,
const NOX::Abstract::MultiVector& input_x,
const NOX::Abstract::MultiVector& input_null,
const NOX::Abstract::MultiVector::DenseMatrix& input_param,
NOX::Abstract::MultiVector& result_x,
NOX::Abstract::MultiVector& result_null,
NOX::Abstract::MultiVector::DenseMatrix& result_param) const
{
std::string callingFunction =
"LOCA::TurningPoint::MooreSpence::PhippsBordering::solveContiguous()";
NOX::Abstract::Group::ReturnType finalStatus = NOX::Abstract::Group::Ok;
NOX::Abstract::Group::ReturnType status;
int m = input_x.numVectors()-2;
std::vector<int> index_input(m);
std::vector<int> index_input_dp(m+1);
std::vector<int> index_null(1);
std::vector<int> index_dp(1);
for (int i=0; i<m; i++) {
index_input[i] = i;
index_input_dp[i] = i;
}
index_input_dp[m] = m;
index_dp[0] = m;
index_null[0] = m+1;
NOX::Abstract::MultiVector::DenseMatrix tmp_mat_1(1, m+1);
NOX::Abstract::MultiVector::DenseMatrix tmp_mat_2(1, m+2);
// Create view of first m+1 columns of input_x, result_x
Teuchos::RCP<NOX::Abstract::MultiVector> input_x_view =
input_x.subView(index_input_dp);
Teuchos::RCP<NOX::Abstract::MultiVector> result_x_view =
result_x.subView(index_input_dp);
// verify underlying Jacobian is valid
if (!group->isJacobian()) {
status = group->computeJacobian();
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(status,
finalStatus,
callingFunction);
}
// Solve |J u||A B| = |F df/dp|
// |v^T 0||a b| |0 0 |
status = borderedSolver->applyInverse(params, input_x_view.get(), NULL,
*result_x_view, tmp_mat_1);
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(status, finalStatus,
callingFunction);
Teuchos::RCP<NOX::Abstract::MultiVector> A =
result_x.subView(index_input);
Teuchos::RCP<NOX::Abstract::MultiVector> B =
result_x.subView(index_dp);
double b = tmp_mat_1(0,m);
// compute (Jv)_x[A B v]
result_x[m+1] = *nullVector;
Teuchos::RCP<NOX::Abstract::MultiVector> tmp =
result_x.clone(NOX::ShapeCopy);
status = group->computeDJnDxaMulti(*nullVector, *JnVector, result_x,
*tmp);
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(status, finalStatus,
callingFunction);
// compute (Jv)_x[A B v] - [G d(Jn)/dp 0]
tmp->update(-1.0, input_null, 1.0);
// verify underlying Jacobian is valid
if (!group->isJacobian()) {
status = group->computeJacobian();
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(status,
finalStatus,
callingFunction);
}
// Solve |J u||C D E| = |(Jv)_x A - G (Jv)_x B - d(Jv)/dp (Jv)_x v|
// |v^T 0||c d e| | 0 0 0 |
status = borderedSolver->applyInverse(params, tmp.get(), NULL, result_null,
tmp_mat_2);
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(status, finalStatus,
callingFunction);
Teuchos::RCP<NOX::Abstract::MultiVector> C =
result_null.subView(index_input);
Teuchos::RCP<NOX::Abstract::MultiVector> D =
result_null.subView(index_dp);
Teuchos::RCP<NOX::Abstract::MultiVector> E =
result_null.subView(index_null);
double d = tmp_mat_2(0, m);
double e = tmp_mat_2(0, m+1);
// Fill coefficient arrays
double M[9];
M[0] = s; M[1] = e; M[2] = -tpGroup->lTransNorm((*E)[0]);
M[3] = 0.0; M[4] = s; M[5] = tpGroup->lTransNorm(*nullVector);
M[6] = b; M[7] = -d; M[8] = tpGroup->lTransNorm((*D)[0]);
// compute h + phi^T C
tpGroup->lTransNorm(*C, result_param);
result_param += input_param;
double *R = new double[3*m];
for (int i=0; i<m; i++) {
R[3*i] = tmp_mat_1(0,i);
R[3*i+1] = -tmp_mat_2(0,i);
R[3*i+2] = result_param(0,i);
}
// Solve M*P = R
int three = 3;
int piv[3];
int info;
Teuchos::LAPACK<int,double> L;
L.GESV(three, m, M, three, piv, R, three, &info);
if (info != 0) {
globalData->locaErrorCheck->throwError(
callingFunction,
"Solve of 3x3 coefficient matrix failed!");
return NOX::Abstract::Group::Failed;
}
NOX::Abstract::MultiVector::DenseMatrix alpha(1,m);
NOX::Abstract::MultiVector::DenseMatrix beta(1,m);
for (int i=0; i<m; i++) {
alpha(0,i) = R[3*i];
beta(0,i) = R[3*i+1];
result_param(0,i) = R[3*i+2];
}
// compute A = A - B*z + v*alpha (remember A is a sub-view of result_x)
A->update(Teuchos::NO_TRANS, -1.0, *B, result_param, 1.0);
A->update(Teuchos::NO_TRANS, 1.0, *nullMultiVector, alpha, 1.0);
// compute C = -C + d*z - E*alpha + v*beta
// (remember C is a sub-view of result_null)
C->update(Teuchos::NO_TRANS, 1.0, *D, result_param, -1.0);
C->update(Teuchos::NO_TRANS, -1.0, *E, alpha, 1.0);
C->update(Teuchos::NO_TRANS, 1.0, *nullMultiVector, beta, 1.0);
delete [] R;
return finalStatus;
}
NOX::Abstract::Group::ReturnType
LOCA::TurningPoint::MooreSpence::PhippsBordering::solveTranspose(
Teuchos::ParameterList& params,
const LOCA::TurningPoint::MooreSpence::ExtendedMultiVector& input,
LOCA::TurningPoint::MooreSpence::ExtendedMultiVector& result) const
{
std::string callingFunction =
"LOCA::TurningPoint::MooreSpence::PhippsBordering::solveTranspose()";
NOX::Abstract::Group::ReturnType status;
// Get components of input
Teuchos::RCP<const NOX::Abstract::MultiVector> input_x =
input.getXMultiVec();
Teuchos::RCP<const NOX::Abstract::MultiVector> input_null =
input.getNullMultiVec();
Teuchos::RCP<const NOX::Abstract::MultiVector::DenseMatrix> input_param = input.getScalars();
// Get components of result
Teuchos::RCP<NOX::Abstract::MultiVector> result_x =
result.getXMultiVec();
Teuchos::RCP<NOX::Abstract::MultiVector> result_null =
result.getNullMultiVec();
Teuchos::RCP<NOX::Abstract::MultiVector::DenseMatrix> result_param =
result.getScalars();
int m = input.numVectors();
std::vector<int> index_input(m);
for (int i=0; i<m; i++)
index_input[i] = i;
// Create new multivectors with m+2 columns
// First m columns store input_x, input_null, result_x, result_null
// respectively, next column stores 0, -phi, J^-T tmp , -J^-T phi
// respectively, last column is for solving (Jv)_x^T u
Teuchos::RCP<NOX::Abstract::MultiVector> cont_input_x =
input_x->clone(m+2);
Teuchos::RCP<NOX::Abstract::MultiVector> cont_input_null =
input_null->clone(m+2);
Teuchos::RCP<NOX::Abstract::MultiVector> cont_result_x =
result_x->clone(m+2);
Teuchos::RCP<NOX::Abstract::MultiVector> cont_result_null =
result_null->clone(m+2);
// Set first m columns to input_x
cont_input_x->setBlock(*input_x, index_input);
// Set last two columns to 0
(*cont_input_x)[m].init(0);
(*cont_input_x)[m+1].init(0);
// Set first m columns to input_null
cont_input_null->setBlock(*input_null, index_input);
// Set next column to -phi
Teuchos::RCP<NOX::Abstract::Vector> phi = tpGroup->getLengthVector();
(*cont_input_null)[m].update(-1.0, *phi, 0.0);
// Set last column to 0
(*cont_input_null)[m].init(0);
// Initialize result multivectors to 0
cont_result_x->init(0.0);
cont_result_null->init(0.0);
// Solve
status = solveTransposeContiguous(params, *cont_input_x, *cont_input_null,
*input_param, *cont_result_x,
*cont_result_null,
*result_param);
// Create views of first m columns for result_x, result_null
Teuchos::RCP<NOX::Abstract::MultiVector> cont_result_x_view =
cont_result_x->subView(index_input);
Teuchos::RCP<NOX::Abstract::MultiVector> cont_result_null_view =
cont_result_null->subView(index_input);
// Copy first m columns back into result_x, result_null
*result_x = *cont_result_x_view;
*result_null = *cont_result_null_view;
return status;
}
// Solves Hopf equations via classic Salinger bordering
// The first m columns of input_x, input_y, input_z store the RHS, the
// next column stores df/dp, (Jy-wBz)_p and (Jz+wBy)_p respectively, the
// last column of input_y and input_z store Bz and -By respectively. Note
// input_x has m+1 columns, input_y and input_z have m+2, and input_w and
// input_p have m columns. result_x, result_y, result_z, result_w and
// result_param have the same dimensions as their input counterparts
NOX::Abstract::Group::ReturnType
LOCA::Hopf::MooreSpence::SalingerBordering::solveContiguous(
Teuchos::ParameterList& params,
const NOX::Abstract::MultiVector& input_x,
const NOX::Abstract::MultiVector& input_y,
const NOX::Abstract::MultiVector& input_z,
const NOX::Abstract::MultiVector::DenseMatrix& input_w,
const NOX::Abstract::MultiVector::DenseMatrix& input_p,
NOX::Abstract::MultiVector& result_x,
NOX::Abstract::MultiVector& result_y,
NOX::Abstract::MultiVector& result_z,
NOX::Abstract::MultiVector::DenseMatrix& result_w,
NOX::Abstract::MultiVector::DenseMatrix& result_p) const
{
std::string callingFunction =
"LOCA::Hopf::MooreSpence::SalingerBordering::solveContiguous()";
NOX::Abstract::Group::ReturnType finalStatus = NOX::Abstract::Group::Ok;
NOX::Abstract::Group::ReturnType status;
int m = input_x.numVectors()-1;
std::vector<int> index_input(m);
std::vector<int> index_dp(1);
std::vector<int> index_B(1);
std::vector<int> index_ip(m+1);
for (int i=0; i<m; i++) {
index_input[i] = i;
index_ip[i] = i;
}
index_ip[m] = m;
index_dp[0] = m;
index_B[0] = m+1;
// verify underlying Jacobian is valid
if (!group->isJacobian()) {
status = group->computeJacobian();
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(status,
finalStatus,
callingFunction);
}
// compute [A b] = J^-1 [F df/dp]
status = group->applyJacobianInverseMultiVector(params, input_x, result_x);
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(status, finalStatus,
callingFunction);
Teuchos::RCP<NOX::Abstract::MultiVector> A =
result_x.subView(index_input);
Teuchos::RCP<NOX::Abstract::MultiVector> b =
result_x.subView(index_dp);
// verify underlying complex matrix is valid
if (!group->isComplex()) {
status = group->computeComplex(w);
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(status,
finalStatus,
callingFunction);
}
// compute (J+iwB)(y+iz)_x [A b]
Teuchos::RCP<NOX::Abstract::MultiVector> tmp_real =
result_y.clone(NOX::ShapeCopy);
Teuchos::RCP<NOX::Abstract::MultiVector> tmp_real_sub =
tmp_real->subView(index_ip);
Teuchos::RCP<NOX::Abstract::MultiVector> tmp_imag =
result_y.clone(NOX::ShapeCopy);
Teuchos::RCP<NOX::Abstract::MultiVector> tmp_imag_sub =
tmp_imag->subView(index_ip);
tmp_real->init(0.0);
tmp_imag->init(0.0);
status = group->computeDCeDxa(*yVector, *zVector, w, result_x,
*CeRealVector, *CeImagVector, *tmp_real_sub,
*tmp_imag_sub);
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(status, finalStatus,
callingFunction);
// compute [G+iH d(J+iwB)(y+iz)/dp iB(y+iz)] - [(J+iwB)_x[A b] 0+i0]
tmp_real->update(1.0, input_y, -1.0);
tmp_imag->update(1.0, input_z, -1.0);
// verify underlying complex matrix is valid
if (!group->isComplex()) {
status = group->computeComplex(w);
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(status,
finalStatus,
callingFunction);
}
// compute [C+iD e+if g+ih] = (J+iwB)^-1 (tmp_real + i tmp_imag)
status = group->applyComplexInverseMultiVector(params, *tmp_real, *tmp_imag,
result_y, result_z);
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(status, finalStatus,
callingFunction);
Teuchos::RCP<NOX::Abstract::MultiVector> C =
result_y.subView(index_input);
Teuchos::RCP<NOX::Abstract::MultiVector> D =
result_z.subView(index_input);
Teuchos::RCP<NOX::Abstract::MultiVector> e =
result_y.subView(index_dp);
Teuchos::RCP<NOX::Abstract::MultiVector> f =
result_z.subView(index_dp);
Teuchos::RCP<NOX::Abstract::MultiVector> g =
result_y.subView(index_B);
Teuchos::RCP<NOX::Abstract::MultiVector> h =
result_z.subView(index_B);
// compute lambda = ((phi^T h)(phi^T C-u) - (phi^T g)(phi^T D-v)) /
// ((phi^T h)(phi^T e)-(phi^T g)(phi^T f))
NOX::Abstract::MultiVector::DenseMatrix ltC(1,m);
NOX::Abstract::MultiVector::DenseMatrix ltD(1,m);
double lte = hopfGroup->lTransNorm((*e)[0]);
double ltf = hopfGroup->lTransNorm((*f)[0]);
double ltg = hopfGroup->lTransNorm((*g)[0]);
double lth = hopfGroup->lTransNorm((*h)[0]);
double denom = lth*lte - ltg*ltf;
hopfGroup->lTransNorm(*C, ltC);
ltC -= input_w;
ltC.scale(lth);
hopfGroup->lTransNorm(*D, ltD);
ltD -= input_p;
result_p.assign(ltD);
result_p.scale(-ltg);
result_p += ltC;
result_p.scale(1.0/denom);
// compute omega = (phi^T D-v - (phi^T f)lambda)/(phi^T h)
result_w.assign(result_p);
result_w.scale(-ltf);
result_w += ltD;
result_w.scale(1.0/lth);
// compute A = A - b*lambda (remember A is a sub-view of result_x)
A->update(Teuchos::NO_TRANS, -1.0, *b, result_p, 1.0);
// compute C = C - e*lambda - g*omega (remember C is a sub-view of result_y)
C->update(Teuchos::NO_TRANS, -1.0, *e, result_p, 1.0);
C->update(Teuchos::NO_TRANS, -1.0, *g, result_w, 1.0);
// compute D = D - f*lambda - h*omega (remember D is a sub-view of result_z)
D->update(Teuchos::NO_TRANS, -1.0, *f, result_p, 1.0);
D->update(Teuchos::NO_TRANS, -1.0, *h, result_w, 1.0);
return finalStatus;
}
NOX::Abstract::Group::ReturnType
LOCA::Hopf::MooreSpence::SalingerBordering::solve(
Teuchos::ParameterList& params,
const LOCA::Hopf::MooreSpence::ExtendedMultiVector& input,
LOCA::Hopf::MooreSpence::ExtendedMultiVector& result) const
{
std::string callingFunction =
"LOCA::Hopf::MooreSpence::SalingerBordering::solve()";
NOX::Abstract::Group::ReturnType status;
// Get components of input
Teuchos::RCP<const NOX::Abstract::MultiVector> input_x =
input.getXMultiVec();
Teuchos::RCP<const NOX::Abstract::MultiVector> input_y =
input.getRealEigenMultiVec();
Teuchos::RCP<const NOX::Abstract::MultiVector> input_z =
input.getImagEigenMultiVec();
Teuchos::RCP<const NOX::Abstract::MultiVector::DenseMatrix> input_w
= input.getFrequencies();
Teuchos::RCP<const NOX::Abstract::MultiVector::DenseMatrix> input_p
= input.getBifParams();
// Get components of result
Teuchos::RCP<NOX::Abstract::MultiVector> result_x =
result.getXMultiVec();
Teuchos::RCP<NOX::Abstract::MultiVector> result_y =
result.getRealEigenMultiVec();
Teuchos::RCP<NOX::Abstract::MultiVector> result_z =
result.getImagEigenMultiVec();
Teuchos::RCP<NOX::Abstract::MultiVector::DenseMatrix> result_w =
result.getFrequencies();
Teuchos::RCP<NOX::Abstract::MultiVector::DenseMatrix> result_p =
result.getBifParams();
int m = input.numVectors();
std::vector<int> index_input(m);
for (int i=0; i<m; i++)
index_input[i] = i;
// Create new multivectors with m+2 columns
// First m columns store input_x, input_y, input_z, result_x, result_y,
// and result_z respectively, next column stores df/dp, (Jy-wBz)_p,
// (Jz+wBy)_p, J^-1 dfdp, C^-1 (Jy-wBz)_p, C^-1 (Jz+wBy)_p
// respectively. Last column stores -Bz, By C^-1 (-Bz) and C^-1 (By)
Teuchos::RCP<NOX::Abstract::MultiVector> cont_input_x =
input_x->clone(m+1);
Teuchos::RCP<NOX::Abstract::MultiVector> cont_input_y =
input_y->clone(m+2);
Teuchos::RCP<NOX::Abstract::MultiVector> cont_input_z =
input_z->clone(m+2);
Teuchos::RCP<NOX::Abstract::MultiVector> cont_result_x =
result_x->clone(m+1);
Teuchos::RCP<NOX::Abstract::MultiVector> cont_result_y =
result_y->clone(m+2);
Teuchos::RCP<NOX::Abstract::MultiVector> cont_result_z =
result_y->clone(m+2);
// Set first m columns to input_x
cont_input_x->setBlock(*input_x, index_input);
// Set last column to dfdp
(*cont_input_x)[m] = *dfdp;
// Set first m columns to input_y
cont_input_y->setBlock(*input_y, index_input);
// Set next column to (Jy-wBz)_p
(*cont_input_y)[m] = *dCedpReal;
// Set last column to -Bz
(*cont_input_y)[m+1] = *minusBzVector;
// Set first m columns to input_z
cont_input_z->setBlock(*input_z, index_input);
// Set next column to (Jz+wBy)_p
(*cont_input_z)[m] = *dCedpImag;
// Set last column to By
(*cont_input_z)[m+1] = *ByVector;
// Initialize result multivectors to 0
cont_result_x->init(0.0);
cont_result_y->init(0.0);
cont_result_z->init(0.0);
// Solve
status = solveContiguous(params, *cont_input_x, *cont_input_y, *cont_input_z,
*input_w, *input_p, *cont_result_x, *cont_result_y,
*cont_result_z, *result_w, *result_p);
// Create views of first m columns for result_x, result_y, result_z
Teuchos::RCP<NOX::Abstract::MultiVector> cont_result_x_view =
cont_result_x->subView(index_input);
Teuchos::RCP<NOX::Abstract::MultiVector> cont_result_y_view =
cont_result_y->subView(index_input);
Teuchos::RCP<NOX::Abstract::MultiVector> cont_result_z_view =
cont_result_z->subView(index_input);
// Copy first m columns back into result_x, result_null
*result_x = *cont_result_x_view;
*result_y = *cont_result_y_view;
*result_z = *cont_result_z_view;
return status;
}
NOX::Abstract::Group::ReturnType
LOCA::TurningPoint::MooreSpence::PhippsBordering::solve(
Teuchos::ParameterList& params,
const LOCA::TurningPoint::MooreSpence::ExtendedMultiVector& input,
LOCA::TurningPoint::MooreSpence::ExtendedMultiVector& result) const
{
string callingFunction =
"LOCA::TurningPoint::MooreSpence::PhippsBordering::solve()";
NOX::Abstract::Group::ReturnType status;
// Get components of input
Teuchos::RCP<const NOX::Abstract::MultiVector> input_x =
input.getXMultiVec();
Teuchos::RCP<const NOX::Abstract::MultiVector> input_null =
input.getNullMultiVec();
Teuchos::RCP<const NOX::Abstract::MultiVector::DenseMatrix> input_param = input.getScalars();
// Get components of result
Teuchos::RCP<NOX::Abstract::MultiVector> result_x =
result.getXMultiVec();
Teuchos::RCP<NOX::Abstract::MultiVector> result_null =
result.getNullMultiVec();
Teuchos::RCP<NOX::Abstract::MultiVector::DenseMatrix> result_param =
result.getScalars();
int m = input.numVectors();
vector<int> index_input(m);
for (int i=0; i<m; i++)
index_input[i] = i;
// Create new multivectors with m+2 columns
// First m columns store input_x, input_null, result_x, result_null
// respectively, next column stores dfdp, dJndp, J^-1 dfdp, J^-1 dJndp
// respectively. Last column is for solving (Jv)_x v
Teuchos::RCP<NOX::Abstract::MultiVector> cont_input_x =
input_x->clone(m+2);
Teuchos::RCP<NOX::Abstract::MultiVector> cont_input_null =
input_null->clone(m+2);
Teuchos::RCP<NOX::Abstract::MultiVector> cont_result_x =
result_x->clone(m+2);
Teuchos::RCP<NOX::Abstract::MultiVector> cont_result_null =
result_null->clone(m+2);
// Set first m columns to input_x
cont_input_x->setBlock(*input_x, index_input);
// Set column m+1 to dfdp
(*cont_input_x)[m] = (*dfdp)[0];
// Initialize column m+2 to 0
(*cont_input_x)[m+1].init(0.0);
// Set first m columns to input_null
cont_input_null->setBlock(*input_null, index_input);
// Set column m+1 to dJndp
(*cont_input_null)[m] = (*dJndp)[0];
// Initialize column m+2 to 0
(*cont_input_null)[m+1].init(0.0);
// Initialize result multivectors to 0
cont_result_x->init(0.0);
cont_result_null->init(0.0);
// Solve
status = solveContiguous(params, *cont_input_x, *cont_input_null,
*input_param, *cont_result_x, *cont_result_null,
*result_param);
// Create views of first m columns for result_x, result_null
Teuchos::RCP<NOX::Abstract::MultiVector> cont_result_x_view =
cont_result_x->subView(index_input);
Teuchos::RCP<NOX::Abstract::MultiVector> cont_result_null_view =
cont_result_null->subView(index_input);
// Copy first m columns back into result_x, result_null
*result_x = *cont_result_x_view;
*result_null = *cont_result_null_view;
return status;
}
// Solves pitchfork equations via Phipps modified bordering
// The first m columns of input_x and input_null store the RHS,
// column m+1 stores df/dp, d(Jn)/dp, column m+2 stores psi and 0,
// and the last column provides space for solving (Jv_x) v. Note however
// input_param has only m columns. result_x, result_null,
// are result_param have the same dimensions as their input counterparts
NOX::Abstract::Group::ReturnType
LOCA::Pitchfork::MooreSpence::PhippsBordering::solveContiguous(
Teuchos::ParameterList& params,
const NOX::Abstract::MultiVector& input_x,
const NOX::Abstract::MultiVector& input_null,
const NOX::Abstract::MultiVector::DenseMatrix& input_slack,
const NOX::Abstract::MultiVector::DenseMatrix& input_param,
NOX::Abstract::MultiVector& result_x,
NOX::Abstract::MultiVector& result_null,
NOX::Abstract::MultiVector::DenseMatrix& result_slack,
NOX::Abstract::MultiVector::DenseMatrix& result_param) const
{
string callingFunction =
"LOCA::Pitchfork::MooreSpence::PhippsBordering::solveContiguous()";
NOX::Abstract::Group::ReturnType finalStatus = NOX::Abstract::Group::Ok;
NOX::Abstract::Group::ReturnType status;
int m = input_x.numVectors()-3;
vector<int> index_input(m);
vector<int> index_input_dp(m+2);
vector<int> index_null(1);
vector<int> index_dp(1);
vector<int> index_s(1);
for (int i=0; i<m; i++) {
index_input[i] = i;
index_input_dp[i] = i;
}
index_input_dp[m] = m;
index_input_dp[m+1] = m+1;
index_dp[0] = m;
index_s[0] = m+1;
index_null[0] = m+2;
NOX::Abstract::MultiVector::DenseMatrix tmp_mat_1(1, m+2);
NOX::Abstract::MultiVector::DenseMatrix tmp_mat_2(1, m+3);
// Create view of first m+2 columns of input_x, result_x
Teuchos::RCP<NOX::Abstract::MultiVector> input_x_view =
input_x.subView(index_input_dp);
Teuchos::RCP<NOX::Abstract::MultiVector> result_x_view =
result_x.subView(index_input_dp);
// verify underlying Jacobian is valid
if (!group->isJacobian()) {
status = group->computeJacobian();
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(status,
finalStatus,
callingFunction);
}
// Solve |J u||A B C| = |F df/dp psi|
// |v^T 0||a b c| |0 0 0 |
status = borderedSolver->applyInverse(params, input_x_view.get(), NULL,
*result_x_view, tmp_mat_1);
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(status, finalStatus,
callingFunction);
Teuchos::RCP<NOX::Abstract::MultiVector> A =
result_x.subView(index_input);
Teuchos::RCP<NOX::Abstract::MultiVector> B =
result_x.subView(index_dp);
Teuchos::RCP<NOX::Abstract::MultiVector> C =
result_x.subView(index_s);
double b = tmp_mat_1(0,m);
double c = tmp_mat_1(0,m+1);
// compute (Jv)_x[A B C v]
result_x[m+2] = *nullVector;
Teuchos::RCP<NOX::Abstract::MultiVector> tmp =
result_x.clone(NOX::ShapeCopy);
status = group->computeDJnDxaMulti(*nullVector, *JnVector, result_x,
*tmp);
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(status, finalStatus,
callingFunction);
// compute [G d(Jn)/dp 0 0] - (Jv)_x[A B C v]
tmp->update(1.0, input_null, -1.0);
// verify underlying Jacobian is valid
if (!group->isJacobian()) {
status = group->computeJacobian();
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(status,
finalStatus,
callingFunction);
}
// Solve |J u||D E K L| = |G-(Jv)_xA d(Jv)/dp-(Jv)_xB -(Jv)_xC -(Jv)_xv|
// |v^T 0||d e k l| | 0 0 0 0 |
status = borderedSolver->applyInverse(params, tmp.get(), NULL, result_null,
tmp_mat_2);
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(status, finalStatus,
callingFunction);
Teuchos::RCP<NOX::Abstract::MultiVector> D =
result_null.subView(index_input);
Teuchos::RCP<NOX::Abstract::MultiVector> E =
result_null.subView(index_dp);
Teuchos::RCP<NOX::Abstract::MultiVector> K =
result_null.subView(index_s);
Teuchos::RCP<NOX::Abstract::MultiVector> L =
result_null.subView(index_null);
double e = tmp_mat_2(0, m);
double k = tmp_mat_2(0, m+1);
double l = tmp_mat_2(0, m+2);
double ltE = pfGroup->lTransNorm((*E)[0]);
double ltK = pfGroup->lTransNorm((*K)[0]);
double ltL = pfGroup->lTransNorm((*L)[0]);
double ltv = pfGroup->lTransNorm(*nullVector);
double ipv = group->innerProduct(*nullVector, *asymVector);
double ipB = group->innerProduct((*B)[0], *asymVector);
double ipC = group->innerProduct((*C)[0], *asymVector);
// Fill coefficient arrays
double M[16];
M[0] = sigma; M[1] = -l; M[2] = ipv; M[3] = ltL;
M[4] = 0.0; M[5] = sigma; M[6] = 0.0; M[7] = ltv;
M[8] = b; M[9] = e; M[10] = -ipB; M[11] = -ltE;
M[12] = c; M[13] = k; M[14] = -ipC; M[15] = -ltK;
// compute s - <A,psi>
NOX::Abstract::MultiVector::DenseMatrix tmp_mat_3(1, m);
group->innerProduct(*asymMultiVector, *A, tmp_mat_3);
tmp_mat_3 -= input_slack;
tmp_mat_3.scale(-1.0);
// compute h - phi^T D
NOX::Abstract::MultiVector::DenseMatrix tmp_mat_4(1, m);
pfGroup->lTransNorm(*D, tmp_mat_4);
tmp_mat_4 -= input_param;
tmp_mat_4.scale(-1.0);
double *R = new double[4*m];
for (int i=0; i<m; i++) {
R[4*i] = tmp_mat_1(0,i);
R[4*i+1] = tmp_mat_2(0,i);
R[4*i+2] = tmp_mat_3(0,i);
R[4*i+3] = tmp_mat_4(0,i);
}
// Solve M*P = R
int piv[4];
int info;
Teuchos::LAPACK<int,double> dlapack;
dlapack.GESV(4, m, M, 4, piv, R, 4, &info);
if (info != 0) {
globalData->locaErrorCheck->throwError(
callingFunction,
"Solve of 4x4 coefficient matrix failed!");
return NOX::Abstract::Group::Failed;
}
NOX::Abstract::MultiVector::DenseMatrix alpha(1,m);
NOX::Abstract::MultiVector::DenseMatrix beta(1,m);
for (int i=0; i<m; i++) {
alpha(0,i) = R[4*i];
beta(0,i) = R[4*i+1];
result_param(0,i) = R[4*i+2];
result_slack(0,i) = R[4*i+3];
}
// compute A = A - B*z -C*w + v*alpha (remember A is a sub-view of result_x)
A->update(Teuchos::NO_TRANS, -1.0, *B, result_param, 1.0);
A->update(Teuchos::NO_TRANS, -1.0, *C, result_slack, 1.0);
A->update(Teuchos::NO_TRANS, 1.0, *nullMultiVector, alpha, 1.0);
// compute D = D - E*z - K*w + L*alpha + v*beta
// (remember D is a sub-view of result_null)
D->update(Teuchos::NO_TRANS, -1.0, *E, result_param, 1.0);
D->update(Teuchos::NO_TRANS, -1.0, *K, result_slack, 1.0);
D->update(Teuchos::NO_TRANS, 1.0, *L, alpha, 1.0);
D->update(Teuchos::NO_TRANS, 1.0, *nullMultiVector, beta, 1.0);
delete [] R;
return finalStatus;
}
