/*@
BVMult - Computes Y = beta*Y + alpha*X*Q.
Logically Collective on BV
Input Parameters:
+ Y,X - basis vectors
. alpha,beta - scalars
- Q - a sequential dense matrix
Output Parameter:
. Y - the modified basis vectors
Notes:
X and Y must be different objects. The case X=Y can be addressed with
BVMultInPlace().
The matrix Q must be a sequential dense Mat, with all entries equal on
all processes (otherwise each process will compute a different update).
The dimensions of Q must be at least m,n where m is the number of active
columns of X and n is the number of active columns of Y.
The leading columns of Y are not modified. Also, if X has leading
columns specified, then these columns do not participate in the computation.
Hence, only rows (resp. columns) of Q starting from lx (resp. ly) are used,
where lx (resp. ly) is the number of leading columns of X (resp. Y).
Level: intermediate
.seealso: BVMultVec(), BVMultColumn(), BVMultInPlace(), BVSetActiveColumns()
@*/
PetscErrorCode BVMult(BV Y,PetscScalar alpha,PetscScalar beta,BV X,Mat Q)
{
PetscErrorCode ierr;
PetscBool match;
PetscInt m,n;
PetscFunctionBegin;
PetscValidHeaderSpecific(Y,BV_CLASSID,1);
PetscValidLogicalCollectiveScalar(Y,alpha,2);
PetscValidLogicalCollectiveScalar(Y,beta,3);
PetscValidHeaderSpecific(X,BV_CLASSID,4);
PetscValidHeaderSpecific(Q,MAT_CLASSID,5);
PetscValidType(Y,1);
BVCheckSizes(Y,1);
PetscValidType(X,4);
BVCheckSizes(X,4);
PetscValidType(Q,5);
PetscCheckSameTypeAndComm(Y,1,X,4);
if (X==Y) SETERRQ(PetscObjectComm((PetscObject)Y),PETSC_ERR_ARG_WRONG,"X and Y arguments must be different");
ierr = PetscObjectTypeCompare((PetscObject)Q,MATSEQDENSE,&match);CHKERRQ(ierr);
if (!match) SETERRQ(PetscObjectComm((PetscObject)Y),PETSC_ERR_SUP,"Mat argument must be of type seqdense");
ierr = MatGetSize(Q,&m,&n);CHKERRQ(ierr);
if (m<X->k) SETERRQ2(PetscObjectComm((PetscObject)Y),PETSC_ERR_ARG_SIZ,"Mat argument has %D rows, should have at least %D",m,X->k);
if (n<Y->k) SETERRQ2(PetscObjectComm((PetscObject)Y),PETSC_ERR_ARG_SIZ,"Mat argument has %D columns, should have at least %D",n,Y->k);
if (X->n!=Y->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Mismatching local dimension X %D, Y %D",X->n,Y->n);
if (!X->n) PetscFunctionReturn(0);
ierr = PetscLogEventBegin(BV_Mult,X,Y,0,0);CHKERRQ(ierr);
ierr = (*Y->ops->mult)(Y,alpha,beta,X,Q);CHKERRQ(ierr);
ierr = PetscLogEventEnd(BV_Mult,X,Y,0,0);CHKERRQ(ierr);
ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
/*@
BVMatMult - Computes the matrix-vector product for each column, Y=A*X.
Neighbor-wise Collective on Mat and BV
Input Parameters:
+ V - basis vectors context
- A - the matrix
Output Parameter:
. Y - the result
Note:
Both V and Y must be distributed in the same manner. Only active columns
(excluding the leading ones) are processed.
In the result Y, columns are overwritten starting from the leading ones.
Level: beginner
.seealso: BVCopy(), BVSetActiveColumns(), BVMatMultColumn()
@*/
PetscErrorCode BVMatMult(BV V,Mat A,BV Y)
{
PetscErrorCode ierr;
PetscFunctionBegin;
PetscValidHeaderSpecific(V,BV_CLASSID,1);
PetscValidType(V,1);
BVCheckSizes(V,1);
PetscValidHeaderSpecific(A,MAT_CLASSID,2);
PetscValidHeaderSpecific(Y,BV_CLASSID,3);
PetscValidType(Y,3);
BVCheckSizes(Y,3);
PetscCheckSameComm(V,1,A,2);
PetscCheckSameTypeAndComm(V,1,Y,3);
if (V->n!=Y->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Mismatching local dimension V %D, Y %D",V->n,Y->n);
if (V->k-V->l>Y->m-Y->l) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Y has %D non-leading columns, not enough to store %D columns",Y->m-Y->l,V->k-V->l);
ierr = PetscLogEventBegin(BV_MatMult,V,A,Y,0);CHKERRQ(ierr);
ierr = (*V->ops->matmult)(V,A,Y);CHKERRQ(ierr);
ierr = PetscLogEventEnd(BV_MatMult,V,A,Y,0);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
/*@C
BVAXPY - Computes Y = Y + alpha*X.
Logically Collective on BV
Input Parameters:
+ Y,X - basis vectors
- alpha - scalar
Output Parameter:
. Y - the modified basis vectors
Notes:
X and Y must be different objects, with compatible dimensions.
The effect is the same as doing a VecAXPY for each of the active
columns (excluding the leading ones).
Level: intermediate
.seealso: BVMult(), BVSetActiveColumns()
@*/
PetscErrorCode BVAXPY(BV Y,PetscScalar alpha,BV X)
{
PetscErrorCode ierr;
PetscFunctionBegin;
PetscValidHeaderSpecific(Y,BV_CLASSID,1);
PetscValidLogicalCollectiveScalar(Y,alpha,2);
PetscValidHeaderSpecific(X,BV_CLASSID,3);
PetscValidType(Y,1);
BVCheckSizes(Y,1);
PetscValidType(X,3);
BVCheckSizes(X,3);
PetscCheckSameTypeAndComm(Y,1,X,3);
if (X==Y) SETERRQ(PetscObjectComm((PetscObject)Y),PETSC_ERR_ARG_WRONG,"X and Y arguments must be different");
if (X->n!=Y->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Mismatching local dimension X %D, Y %D",X->n,Y->n);
if (X->k-X->l!=Y->k-Y->l) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Y has %D non-leading columns, while X has %D",Y->m-Y->l,X->k-X->l);
if (!X->n) PetscFunctionReturn(0);
ierr = PetscLogEventBegin(BV_AXPY,X,Y,0,0);CHKERRQ(ierr);
ierr = (*Y->ops->axpy)(Y,alpha,X);CHKERRQ(ierr);
ierr = PetscLogEventEnd(BV_AXPY,X,Y,0,0);CHKERRQ(ierr);
ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
PetscErrorCode TaoLineSearchApply(TaoLineSearch ls, Vec x, PetscReal *f, Vec g, Vec s, PetscReal *steplength, TaoLineSearchConvergedReason *reason)
{
PetscErrorCode ierr;
PetscViewer viewer;
PetscInt low1,low2,low3,high1,high2,high3;
PetscBool flg;
char filename[PETSC_MAX_PATH_LEN];
PetscFunctionBegin;
*reason = TAOLINESEARCH_CONTINUE_ITERATING;
PetscValidHeaderSpecific(ls,TAOLINESEARCH_CLASSID,1);
PetscValidHeaderSpecific(x,VEC_CLASSID,2);
PetscValidScalarPointer(f,3);
PetscValidHeaderSpecific(g,VEC_CLASSID,4);
PetscValidHeaderSpecific(s,VEC_CLASSID,5);
PetscValidPointer(reason,7);
PetscCheckSameComm(ls,1,x,2);
PetscCheckSameTypeAndComm(x,2,g,4);
PetscCheckSameTypeAndComm(x,2,s,5);
ierr = VecGetOwnershipRange(x, &low1, &high1);CHKERRQ(ierr);
ierr = VecGetOwnershipRange(g, &low2, &high2);CHKERRQ(ierr);
ierr = VecGetOwnershipRange(s, &low3, &high3);CHKERRQ(ierr);
if ( low1!= low2 || low1!= low3 || high1!= high2 || high1!= high3) SETERRQ(PETSC_COMM_SELF,1,"InCompatible vector local lengths");
ierr = PetscObjectReference((PetscObject)s);CHKERRQ(ierr);
ierr = VecDestroy(&ls->stepdirection);CHKERRQ(ierr);
ls->stepdirection = s;
ierr = TaoLineSearchSetUp(ls);CHKERRQ(ierr);
if (!ls->ops->apply) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Line Search Object does not have 'apply' routine");
ls->nfeval=0;
ls->ngeval=0;
ls->nfgeval=0;
/* Check parameter values */
if (ls->ftol < 0.0) {
ierr = PetscInfo1(ls,"Bad Line Search Parameter: ftol (%g) < 0\n",(double)ls->ftol);CHKERRQ(ierr);
*reason=TAOLINESEARCH_FAILED_BADPARAMETER;
}
if (ls->rtol < 0.0) {
ierr = PetscInfo1(ls,"Bad Line Search Parameter: rtol (%g) < 0\n",(double)ls->rtol);CHKERRQ(ierr);
*reason=TAOLINESEARCH_FAILED_BADPARAMETER;
}
if (ls->gtol < 0.0) {
ierr = PetscInfo1(ls,"Bad Line Search Parameter: gtol (%g) < 0\n",(double)ls->gtol);CHKERRQ(ierr);
*reason=TAOLINESEARCH_FAILED_BADPARAMETER;
}
if (ls->stepmin < 0.0) {
ierr = PetscInfo1(ls,"Bad Line Search Parameter: stepmin (%g) < 0\n",(double)ls->stepmin);CHKERRQ(ierr);
*reason=TAOLINESEARCH_FAILED_BADPARAMETER;
}
if (ls->stepmax < ls->stepmin) {
ierr = PetscInfo2(ls,"Bad Line Search Parameter: stepmin (%g) > stepmax (%g)\n",(double)ls->stepmin,(double)ls->stepmax);CHKERRQ(ierr);
*reason=TAOLINESEARCH_FAILED_BADPARAMETER;
}
if (ls->max_funcs < 0) {
ierr = PetscInfo1(ls,"Bad Line Search Parameter: max_funcs (%D) < 0\n",ls->max_funcs);CHKERRQ(ierr);
*reason=TAOLINESEARCH_FAILED_BADPARAMETER;
}
if (PetscIsInfOrNanReal(*f)) {
ierr = PetscInfo1(ls,"Initial Line Search Function Value is Inf or Nan (%g)\n",(double)*f);CHKERRQ(ierr);
*reason=TAOLINESEARCH_FAILED_INFORNAN;
}
ierr = PetscObjectReference((PetscObject)x);
ierr = VecDestroy(&ls->start_x);CHKERRQ(ierr);
ls->start_x = x;
ierr = PetscLogEventBegin(TaoLineSearch_ApplyEvent,ls,0,0,0);CHKERRQ(ierr);
ierr = (*ls->ops->apply)(ls,x,f,g,s);CHKERRQ(ierr);
ierr = PetscLogEventEnd(TaoLineSearch_ApplyEvent, ls, 0,0,0);CHKERRQ(ierr);
*reason=ls->reason;
ls->new_f = *f;
if (steplength) {
*steplength=ls->step;
}
ierr = PetscOptionsGetString(((PetscObject)ls)->prefix,"-tao_ls_view",filename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr);
if (ls->viewls && !PetscPreLoadingOn) {
ierr = PetscViewerASCIIOpen(((PetscObject)ls)->comm,filename,&viewer);CHKERRQ(ierr);
ierr = TaoLineSearchView(ls,viewer);CHKERRQ(ierr);
ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr);
}
PetscFunctionReturn(0);
}
