PetscErrorCode SaveObservation(TS ts)
{
PetscErrorCode ierr;
Userctx *user;
Vec X;
PetscReal t;
PetscFunctionBegin;
ierr = TSGetApplicationContext(ts,&user);CHKERRQ(ierr);
ierr = TSGetTime(ts,&t);CHKERRQ(ierr);
ierr = TSGetSolution(ts,&X);CHKERRQ(ierr);
ierr = SetObservation(user,t,X);CHKERRQ(ierr);
ierr = SetSolution(user,t,X);CHKERRQ(ierr);
user->stepnum++;
PetscFunctionReturn(0);
}
PetscErrorCode InitializeData(const PetscScalar* P, void *ctx0, double noise, PetscScalar data_dt)
{
TS ts;
SNES snes_alg;
PetscErrorCode ierr;
Userctx *ctx = (Userctx*)ctx0;
Vec X;
Mat J;
Vec F_alg;
Vec Xdot;
PetscInt i,j,m,n;
PetscReal *mat;
//PetscReal temp;
PetscViewer obsView;
PetscFunctionBegin;
H[0] = P[0];
H[1] = P[1];
H[2] = P[2];
printf("InitializeData: x=[%.14f, %.14f, %.14f], obs_noise=%5.3f Nt = %4.2f, Nobs=%4.2f\n", H[0], H[1], H[2], noise, ((ctx->tfinal-ctx->t0)/ctx->dt)+1, ((ctx->tfinal-ctx->trestore)/ctx->data_dt)+1);
if(ctx->t0 > ctx->tdisturb) {
printf("t0 cannot be greater than tdisturb\n");
PetscFunctionReturn(-1);
}
if( (ctx->tdisturb >= ctx->trestore-1.0e-8) || (ctx->tdisturb >= ctx->tfinal-1.0e-8) ) {
printf("tdisturb should be less than trestore and tfinal\n");
PetscFunctionReturn(-1);
}
//use the reference PD0 from t0 to t_disturb to ensure steady state
for(i=0; i<3; i++) PD0[i] = PD0_ref[i];
ctx->stepnum = 0;
ierr = DMCreateGlobalVector(ctx->dmpgrid,&X);CHKERRQ(ierr);
ierr = MatCreate(PETSC_COMM_WORLD,&J);CHKERRQ(ierr);
ierr = MatSetSizes(J,PETSC_DECIDE,PETSC_DECIDE,ctx->neqs_pgrid,ctx->neqs_pgrid);CHKERRQ(ierr);
ierr = MatSetFromOptions(J);CHKERRQ(ierr);
ierr = PreallocateJacobian(J,ctx);CHKERRQ(ierr);
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Create timestepping solver context
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
ierr = TSCreate(PETSC_COMM_WORLD,&ts);CHKERRQ(ierr);
ierr = TSSetProblemType(ts,TS_NONLINEAR);CHKERRQ(ierr);
ierr = TSSetType(ts,TSCN);CHKERRQ(ierr);
ierr = TSSetIFunction(ts,NULL,(TSIFunction) IFunction,ctx);CHKERRQ(ierr);
ierr = TSSetIJacobian(ts,J,J,(TSIJacobian)IJacobian,ctx);CHKERRQ(ierr);
ierr = TSSetApplicationContext(ts,ctx);CHKERRQ(ierr);
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Set initial conditions
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
ierr = SetInitialGuess(X,ctx);CHKERRQ(ierr);
ierr = VecDuplicate(X,&F_alg);CHKERRQ(ierr);
ierr = SNESCreate(PETSC_COMM_WORLD,&snes_alg);CHKERRQ(ierr);
ierr = SNESSetFunction(snes_alg,F_alg,AlgFunction,ctx);CHKERRQ(ierr);
ierr = MatZeroEntries(J);CHKERRQ(ierr);
ierr = SNESSetJacobian(snes_alg,J,J,AlgJacobian,ctx);CHKERRQ(ierr);
ierr = SNESSetOptionsPrefix(snes_alg,"alg_");CHKERRQ(ierr);
ierr = SNESSetFromOptions(snes_alg);CHKERRQ(ierr);
/* Solve the algebraic equations */
ierr = SNESSolve(snes_alg,NULL,X);CHKERRQ(ierr);
ierr = SetSolution(ctx, ctx->t0, X); CHKERRQ(ierr);
ierr = SetObservation(ctx, ctx->t0, X); CHKERRQ(ierr);
/* Just to set up the Jacobian structure */
ierr = VecDuplicate(X,&Xdot);CHKERRQ(ierr);
ierr = IJacobian(ts,ctx->t0,X,Xdot,0.0,J,J,ctx);CHKERRQ(ierr);
ierr = VecDestroy(&Xdot);CHKERRQ(ierr);
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Solve from on [t0,tdisturb] (steady state)
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
ierr = TSSetDuration(ts,1000000,ctx->tdisturb);CHKERRQ(ierr);
ierr = TSSetInitialTimeStep(ts,ctx->t0,ctx->dt);CHKERRQ(ierr);
ierr = TSSetFromOptions(ts);CHKERRQ(ierr);
ierr = TSSetPostStep(ts,SaveObservation);CHKERRQ(ierr);
/* Solve (from t0 to tdisturb) */
ierr = TSSolve(ts,X);CHKERRQ(ierr);
/* set X at tdisturb as IC for the optimization/estimation */
/*ierr = VecDuplicate(X, &ctx->X0_disturb);CHKERRQ(ierr);*/
/*ierr = VecCopy(X, ctx->X0_disturb);CHKERRQ(ierr);*/
/* Continue integrating the DAE only if observations file is not specified */
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Solve from on [tdisturb, trestore] (disturbance part of the transient)
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
/* Induce a load perturbation at t=tdisturb */
for(i=0; i<3; i++) PD0[i] = PD0_disturb[i];
printf("Generate data - initiated a bump in load: new PD0[0]=%g\n", PD0[0]);
printf("Running with: tfinal=%.12f dt=%.12f data_dt=%.12f data_noise=%.12f prior_noise=%.12f load_disturb=%.12f\n",
ctx->tfinal, ctx->dt, ctx->data_dt,
ctx->data_noise, ctx->prior_noise, PD0[0]);
/* Solve the algebraic equations */
ierr = SNESSolve(snes_alg,NULL,X);CHKERRQ(ierr);
ierr = TSSetDuration(ts,100000,fmin(ctx->trestore,ctx->tfinal));CHKERRQ(ierr);
ierr = TSSetInitialTimeStep(ts,ctx->tdisturb,ctx->dt);CHKERRQ(ierr);
/* Solve (from tdisturb to trestore) */
ierr = TSSolve(ts,X);CHKERRQ(ierr);
/* set X at trestore as IC for the optimization/estimation */
ierr = VecDuplicate(X, &ctx->X0_disturb);CHKERRQ(ierr);
ierr = VecCopy(X, ctx->X0_disturb);CHKERRQ(ierr);
if(0==strlen(ctx->loadObsFile)) {
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Solve from on [trestore, tfinal] (post-disturbance transient)
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
if(ctx->tfinal>=ctx->trestore+1.0e-8) {
//restore load at trestore
for(i=0; i<3; i++) PD0[i] = PD0_ref[i];
printf("In generate data: Restore load to PD0[0]=%g\n", PD0[0]);
/* Solve the algebraic equations */
ierr = SNESSolve(snes_alg,NULL,X);CHKERRQ(ierr);
ierr = TSSetDuration(ts,100000,ctx->tfinal);CHKERRQ(ierr);
ierr = TSSetInitialTimeStep(ts,ctx->trestore,ctx->dt);CHKERRQ(ierr);
/* Solve (from trestore to tfinal) */
ierr = TSSolve(ts,X);CHKERRQ(ierr);
} else {
printf("Ignoring trestore since tfinal is less than it.\n");
}
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Generate noise at level 'noise' percent
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
ierr = MatGetSize(ctx->obs, &m, &n);CHKERRQ(ierr);
/* allocate std dev for data */
ierr = PetscMalloc(m*sizeof(PetscReal),&ctx->data_stddev);CHKERRQ(ierr);
ierr = MatDenseGetArray(ctx->obs,&mat);CHKERRQ(ierr);
for(i=0;i<m;i++)
ctx->data_stddev[i] = ctx->data_noise;
/* for(i=0; i<m; i++) {
temp = 0.0;
for(j=0; j<n; j++) {
temp += mat[i*n+j]*mat[i*n+j];
}
ctx->data_stddev[i] = ctx->data_noise*sqrt(temp);
}
*/
for(i=0; i<m; i++) {
for(j=0; j<n; j++) {
mat[i*n+j] += ctx->data_stddev[i]*nrand();
}
}
ierr = MatDenseRestoreArray(ctx->obs,&mat);CHKERRQ(ierr);
} else {
/* observations are in an external file */
printf("Loading observations from %s.\n", ctx->loadObsFile);
ierr = PetscViewerBinaryOpen(PETSC_COMM_WORLD,ctx->loadObsFile,FILE_MODE_READ, &obsView);CHKERRQ(ierr);
ierr = MatLoad(ctx->obs, obsView);CHKERRQ(ierr);
ierr = PetscViewerDestroy(&obsView);CHKERRQ(ierr);
ierr = MatGetSize(ctx->obs, &m, &n);CHKERRQ(ierr);
ierr = PetscMalloc(m*sizeof(PetscReal),&ctx->data_stddev);CHKERRQ(ierr);
for(i=0;i<m;i++)
ctx->data_stddev[i] = ctx->data_noise;
}
ierr = SNESDestroy(&snes_alg);CHKERRQ(ierr);
ierr = VecDestroy(&F_alg);CHKERRQ(ierr);
ierr = MatDestroy(&J);CHKERRQ(ierr);
ierr = VecDestroy(&X);CHKERRQ(ierr);
ierr = TSDestroy(&ts);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
/* ProcessFrame
Takes the observation vector and propatagets all tokens and
performs pruning as necessary.
*/
void Decoder::ProcessFrame (Observation **obsBlock, int nObs, AdaptXForm *xform) {
inXForm = xform; /* sepcifies the transform to use */
/* reset obs */
SetObservation(obsBlock, nObs);
GarbageCollectPaths ();
InternalPropagation();
// Set the lowerbound of beam
_dec->beamLimit = _dec->bestScore - _dec->curBeamWidth;
// Beam pruning & External propagation
for (int l = 0; l < _dec->nLayers; ++l) {
LexNodeInst* &head = _dec->instsLayer[l];
// Update word end time/score in tok->path when passing through layer
if (l == _dec->net->wordEndLayerId) {
for (auto inst = head; inst; inst = inst->next)
UpdateWordEndHyp (inst);
}
TokScore beamLimit = _dec->beamLimit;
if ((_dec->weBeamWidth < _dec->beamWidth) && (l == LAYER_WE))
WordEndBeamPruning(head, beamLimit);
else if ((_dec->zsBeamWidth < _dec->beamWidth) && (l == LAYER_ZS || l == LAYER_SA))
ZSLayerBeamPruning(head, beamLimit);
// Go external propagation and pruning
LexNodeInst* prev = NULL, *next = NULL;
for (auto inst = head; inst; inst = next) {
next = inst->next;
if (inst->node->type != LN_WORDEND && inst->node->lmlaIdx != 0 && inst->ts->n > 0) {
/* don't bother if inst will be pruned anyway */
if (inst->ts[0].score >= beamLimit)
UpdateLMlookahead (inst->node);
/* UpLMLA might have killed the entire TS, esp. in latlm */
if (inst->ts->n > 0)
inst->best = std::max(inst->best, inst->ts[0].score);
}
// Pruning
if (inst->best < beamLimit) {
RemoveLexNode(head, prev, inst);
DeactivateNode (inst->node);
continue;
}
++_dec->stats.nActive;
// Pronprob handling before sil layer
if (_dec->net->silDict && (l == _dec->net->spSkipLayer) && inst->ts[0].n > 0) {
HandleSpSkipLayer (inst);
continue;
}
// Normal case: non silDict or non spSkipLayer
if (l == LAYER_SIL && inst->node->type == LN_MODEL)
this->SetWordEndTag(inst);
bool handleWE = !(_dec->weBeamWidth < _dec->beamWidth) || (l == LAYER_SIL) || (l == LAYER_AB);
ExternalPropagation (inst, handleWE, l == LAYER_BY);
prev = inst;
} // for each node in the same layer
} // for each layer
this->RelaxBeamLimit();
++_dec->stats.nFrames;
_dec->outPCache->cacheHit = _dec->outPCache->cacheMiss = 0;
_dec->lmCache->transHit = _dec->lmCache->transMiss = 0;
_dec->lmCache->laHit = _dec->lmCache->laMiss = 0;
if (_dec->nPhone > 0)
CalcPhonePost ();
}
