void
OPViscosityCollisionalE::stream(const double& edt)
{
//Move the time forward
//currentdt += edt;
//Now test if we've gone over the step time
if (currentdt + edt >= dt)
{
newG (delG);
currentdt += edt - dt;
//Now calculate the start of the new delG
for (size_t iDim = 0; iDim < NDIM; ++iDim)
for (size_t jDim = 0; jDim < NDIM; ++jDim)
delG[iDim][jDim] = 0.0;
while (currentdt >= dt)
{
currentdt -= dt;
newG(delG);
}
}
else
currentdt += edt;
}
void
OPThermalDiffusionE::stream(const double edt)
{
//Now test if we've gone over the step time
if (currentdt + edt >= dt)
{
delG += constDelG * (dt - currentdt);
delGsp1 += (constDelGsp1 - massFracSp1 * sysMom) * (dt - currentdt);
newG();
currentdt += edt - dt;
while (currentdt >= dt)
{
delG = constDelG * dt;
delGsp1 = (constDelGsp1 - massFracSp1 * sysMom) * dt;
currentdt -= dt;
newG();
}
//Now calculate the start of the new delG
delG = constDelG * currentdt;
delGsp1 = (constDelGsp1 - massFracSp1 * sysMom) * currentdt;
}
else
{
currentdt += edt;
delG += constDelG * edt;
delGsp1 += (constDelGsp1 - massFracSp1 * sysMom) * edt;
}
}
void
OPThermalConductivityE::stream(const double& edt)
{
//Now test if we've gone over the step time
if (currentdt + edt >= dt)
{
delG += constDelG * (dt - currentdt);
newG();
currentdt += edt - dt;
while (currentdt >= dt)
{
delG = constDelG * dt;
currentdt -= dt;
newG();
}
//Now calculate the start of the new delG
delG = constDelG * currentdt;
}
else
{
currentdt += edt;
delG += constDelG * edt;
}
}
Form::Form(QWidget *parent) : game(NULL), // подключение формы
QWidget(parent),
ui(new Ui::Form)
{
ui -> setupUi(this);
layout = new QVBoxLayout(this);
settingsLayout = new QHBoxLayout;
QPushButton* newgame = new QPushButton();
QPushButton* exitgame = new QPushButton();
QPixmap newG(":/sprite/new.png");
QPixmap exG(":/sprite/exit.png");
QIcon newGIcon(newG);
QIcon exGIcon(exG);
newgame -> setIcon(newGIcon);
exitgame -> setIcon(exGIcon);
newgame -> setIconSize(QSize(304,70)); // загрузка картинки "Новая игра"
exitgame -> setIconSize(QSize(290,70)); // загрузка картинки "Выход"
connect(newgame, SIGNAL(clicked()), this, SLOT(newGame())); // Если нажата кнопка, то новая игра
connect(exitgame, SIGNAL(clicked()), this, SLOT(exitGame())); // Если нажата кнопка, то выход
settingsLayout -> addWidget(newgame);
settingsLayout -> addWidget(exitgame);
layout -> setContentsMargins(2, 2, 2, 2);
layout -> addLayout(settingsLayout);
newGame();
setLayout(layout);
}
void
OPViscosityE::stream(const double& edt)
{
//Move the time forward
//currentdt += edt;
//Now test if we've gone over the step time
if (currentdt + edt >= dt)
{
for (size_t iDim = 0; iDim < NDIM; ++iDim)
for (size_t jDim = 0; jDim < NDIM; ++jDim)
delG[iDim][jDim] += constDelG[iDim][jDim] * (dt - currentdt);
newG (delG);
currentdt += edt - dt;
while (currentdt >= dt)
{
for (size_t iDim = 0; iDim < NDIM; ++iDim)
for (size_t jDim = 0; jDim < NDIM; ++jDim)
delG[iDim][jDim] = constDelG[iDim][jDim] * dt;
currentdt -= dt;
newG(delG);
}
//Now calculate the start of the new delG
for (size_t iDim = 0; iDim < NDIM; ++iDim)
for (size_t jDim = 0; jDim < NDIM; ++jDim)
delG[iDim][jDim] = constDelG[iDim][jDim] * currentdt;
}
else
{
currentdt += edt;
for (size_t iDim = 0; iDim < NDIM; ++iDim)
for (size_t jDim = 0; jDim < NDIM; ++jDim)
delG[iDim][jDim] += constDelG[iDim][jDim] * edt;
}
}
void
OPVACF::eventUpdate(const System&, const NEventData& PDat, const double& edt)
{
//Move the time forward
currentdt += edt;
//Now test if we've gone over the step time
while (currentdt >= dt)
{
currentdt -= dt;
newG(PDat);
}
}
void
OPVACF::eventUpdate(const LocalEvent& iEvent, const NEventData& PDat)
{
//Move the time forward
currentdt += iEvent.getdt();
//Now test if we've gone over the step time
while (currentdt >= dt)
{
currentdt -= dt;
newG(PDat);
}
}
void
OPThermalConductivitySpeciesSpeciesE::stream(const double& edt)
{
size_t Nsp(Sim->dynamics.getSpecies().size());
//Now test if we've gone over the step time
if (currentdt + edt >= dt)
{
for (size_t spec(0); spec < Nsp; ++spec)
delG[spec] += constDelG[spec] * (dt - currentdt);
newG();
currentdt += edt - dt;
while (currentdt >= dt)
{
for (size_t spec(0); spec < Nsp; ++spec)
delG[spec] = constDelG[spec] * dt;
currentdt -= dt;
newG();
}
//Now calculate the start of the new delG
for (size_t spec(0); spec < Nsp; ++spec)
delG[spec] = constDelG[spec] * currentdt;
}
else
{
currentdt += edt;
for (size_t spec(0); spec < Nsp; ++spec)
delG[spec] += constDelG[spec] * edt;
}
}
EvolveCloudFunctionObject<CloudType>::EvolveCloudFunctionObject
(
const word& name,
const Time& t,
const dictionary& dict
)
:
functionObject(
name
),
dict_(dict),
regionName_(
dict_.found("region")
? dict_.lookup("region")
: polyMesh::defaultRegion
),
obr_(t.lookupObject<objectRegistry>(regionName_)),
cloudName_(
dict.lookup("cloudName")
),
g_("dummy",dimless,vector::zero)
{
if(dict_.found("g")) {
dimensionedVector newG(dict_.lookup("g"));
g_.dimensions().reset(newG.dimensions());
g_=newG;
} else {
const Time &runTime=t;
// const fvMesh &mesh=dynamicCast<const fvMesh &>(obr_);
const fvMesh &mesh=dynamic_cast<const fvMesh &>(obr_);
#include "readGravitationalAcceleration.H"
g_.dimensions().reset(g.dimensions());
g_=g;
}
}
bool VMCcuda::run() {
if (UseDrift == "yes")
return runWithDrift();
resetRun();
IndexType block = 0;
IndexType nAcceptTot = 0;
IndexType nRejectTot = 0;
IndexType updatePeriod= (QMCDriverMode[QMC_UPDATE_MODE])
? Period4CheckProperties
: (nBlocks+1)*nSteps;
int nat = W.getTotalNum();
int nw = W.getActiveWalkers();
vector<RealType> LocalEnergy(nw);
vector<PosType> delpos(nw);
vector<PosType> newpos(nw);
vector<ValueType> ratios(nw);
vector<GradType> oldG(nw), newG(nw);
vector<ValueType> oldL(nw), newL(nw);
vector<Walker_t*> accepted(nw);
Matrix<ValueType> lapl(nw, nat);
Matrix<GradType> grad(nw, nat);
double Esum;
// First do warmup steps
for (int step=0; step<myWarmupSteps; step++) {
for(int iat=0; iat<nat; ++iat) {
//create a 3N-Dimensional Gaussian with variance=1
makeGaussRandomWithEngine(delpos,Random);
for(int iw=0; iw<nw; ++iw) {
PosType G = W[iw]->Grad[iat];
newpos[iw]=W[iw]->R[iat] + m_sqrttau*delpos[iw];
ratios[iw] = 1.0;
}
W.proposeMove_GPU(newpos, iat);
Psi.ratio(W,iat,ratios,newG, newL);
accepted.clear();
vector<bool> acc(nw, false);
for(int iw=0; iw<nw; ++iw) {
if(ratios[iw]*ratios[iw] > Random()) {
accepted.push_back(W[iw]);
nAccept++;
W[iw]->R[iat] = newpos[iw];
acc[iw] = true;
}
else
nReject++;
}
W.acceptMove_GPU(acc);
if (accepted.size())
Psi.update(accepted,iat);
}
}
do {
IndexType step = 0;
nAccept = nReject = 0;
Esum = 0.0;
Estimators->startBlock(nSteps);
do
{
++step;
++CurrentStep;
for (int isub=0; isub<nSubSteps; isub++) {
for(int iat=0; iat<nat; ++iat) {
//create a 3N-Dimensional Gaussian with variance=1
makeGaussRandomWithEngine(delpos,Random);
for(int iw=0; iw<nw; ++iw) {
PosType G = W[iw]->Grad[iat];
newpos[iw]=W[iw]->R[iat] + m_sqrttau*delpos[iw];
ratios[iw] = 1.0;
}
W.proposeMove_GPU(newpos, iat);
Psi.ratio(W,iat,ratios,newG, newL);
accepted.clear();
vector<bool> acc(nw, false);
for(int iw=0; iw<nw; ++iw) {
if(ratios[iw]*ratios[iw] > Random()) {
accepted.push_back(W[iw]);
nAccept++;
W[iw]->R[iat] = newpos[iw];
acc[iw] = true;
}
else
nReject++;
}
W.acceptMove_GPU(acc);
if (accepted.size())
Psi.update(accepted,iat);
}
}
Psi.gradLapl(W, grad, lapl);
H.evaluate (W, LocalEnergy);
if (myPeriod4WalkerDump && (CurrentStep % myPeriod4WalkerDump)==0)
W.saveEnsemble();
Estimators->accumulate(W);
} while(step<nSteps);
Psi.recompute(W);
// vector<RealType> logPsi(W.WalkerList.size(), 0.0);
// Psi.evaluateLog(W, logPsi);
double accept_ratio = (double)nAccept/(double)(nAccept+nReject);
Estimators->stopBlock(accept_ratio);
nAcceptTot += nAccept;
nRejectTot += nReject;
++block;
recordBlock(block);
} while(block<nBlocks);
//Mover->stopRun();
//finalize a qmc section
return finalize(block);
}
bool VMCcuda::runWithDrift()
{
resetRun();
IndexType block = 0;
IndexType nAcceptTot = 0;
IndexType nRejectTot = 0;
int nat = W.getTotalNum();
int nw = W.getActiveWalkers();
vector<RealType> LocalEnergy(nw), oldScale(nw), newScale(nw);
vector<PosType> delpos(nw);
vector<PosType> dr(nw);
vector<PosType> newpos(nw);
vector<ValueType> ratios(nw), rplus(nw), rminus(nw);
vector<PosType> oldG(nw), newG(nw);
vector<ValueType> oldL(nw), newL(nw);
vector<Walker_t*> accepted(nw);
Matrix<ValueType> lapl(nw, nat);
Matrix<GradType> grad(nw, nat);
// First, do warmup steps
for (int step=0; step<myWarmupSteps; step++) {
for(int iat=0; iat<nat; iat++) {
Psi.getGradient (W, iat, oldG);
//create a 3N-Dimensional Gaussian with variance=1
makeGaussRandomWithEngine(delpos,Random);
for(int iw=0; iw<nw; iw++) {
oldScale[iw] = getDriftScale(m_tauovermass,oldG[iw]);
dr[iw] = (m_sqrttau*delpos[iw]) + (oldScale[iw]*oldG[iw]);
newpos[iw]=W[iw]->R[iat] + dr[iw];
ratios[iw] = 1.0;
}
W.proposeMove_GPU(newpos, iat);
Psi.ratio(W,iat,ratios,newG, newL);
accepted.clear();
vector<bool> acc(nw, false);
for(int iw=0; iw<nw; ++iw) {
PosType drOld =
newpos[iw] - (W[iw]->R[iat] + oldScale[iw]*oldG[iw]);
RealType logGf = -m_oneover2tau * dot(drOld, drOld);
newScale[iw] = getDriftScale(m_tauovermass,newG[iw]);
PosType drNew =
(newpos[iw] + newScale[iw]*newG[iw]) - W[iw]->R[iat];
RealType logGb = -m_oneover2tau * dot(drNew, drNew);
RealType x = logGb - logGf;
RealType prob = ratios[iw]*ratios[iw]*std::exp(x);
if(Random() < prob) {
accepted.push_back(W[iw]);
nAccept++;
W[iw]->R[iat] = newpos[iw];
acc[iw] = true;
}
else
nReject++;
}
W.acceptMove_GPU(acc);
if (accepted.size())
Psi.update(accepted,iat);
}
}
// Now do data collection steps
do {
IndexType step = 0;
nAccept = nReject = 0;
Estimators->startBlock(nSteps);
do {
step++;
CurrentStep++;
for (int isub=0; isub<nSubSteps; isub++) {
for(int iat=0; iat<nat; iat++) {
Psi.getGradient (W, iat, oldG);
//create a 3N-Dimensional Gaussian with variance=1
makeGaussRandomWithEngine(delpos,Random);
for(int iw=0; iw<nw; iw++) {
oldScale[iw] = getDriftScale(m_tauovermass,oldG[iw]);
dr[iw] = (m_sqrttau*delpos[iw]) + (oldScale[iw]*oldG[iw]);
newpos[iw]=W[iw]->R[iat] + dr[iw];
ratios[iw] = 1.0;
}
W.proposeMove_GPU(newpos, iat);
Psi.ratio(W,iat,ratios,newG, newL);
accepted.clear();
vector<bool> acc(nw, false);
for(int iw=0; iw<nw; ++iw) {
PosType drOld =
newpos[iw] - (W[iw]->R[iat] + oldScale[iw]*oldG[iw]);
// if (dot(drOld, drOld) > 25.0)
// cerr << "Large drift encountered! Old drift = " << drOld << endl;
RealType logGf = -m_oneover2tau * dot(drOld, drOld);
newScale[iw] = getDriftScale(m_tauovermass,newG[iw]);
PosType drNew =
(newpos[iw] + newScale[iw]*newG[iw]) - W[iw]->R[iat];
// if (dot(drNew, drNew) > 25.0)
// cerr << "Large drift encountered! Drift = " << drNew << endl;
RealType logGb = -m_oneover2tau * dot(drNew, drNew);
RealType x = logGb - logGf;
RealType prob = ratios[iw]*ratios[iw]*std::exp(x);
if(Random() < prob) {
accepted.push_back(W[iw]);
nAccept++;
W[iw]->R[iat] = newpos[iw];
acc[iw] = true;
}
else
nReject++;
}
W.acceptMove_GPU(acc);
if (accepted.size())
Psi.update(accepted,iat);
}
// cerr << "Rank = " << myComm->rank() <<
// " CurrentStep = " << CurrentStep << " isub = " << isub << endl;
}
Psi.gradLapl(W, grad, lapl);
H.evaluate (W, LocalEnergy);
if (myPeriod4WalkerDump && (CurrentStep % myPeriod4WalkerDump)==0)
W.saveEnsemble();
Estimators->accumulate(W);
} while(step<nSteps);
Psi.recompute(W);
double accept_ratio = (double)nAccept/(double)(nAccept+nReject);
Estimators->stopBlock(accept_ratio);
nAcceptTot += nAccept;
nRejectTot += nReject;
++block;
recordBlock(block);
} while(block<nBlocks);
//finalize a qmc section
if (!myComm->rank())
gpu::cuda_memory_manager.report();
return finalize(block);
}
bool DMCcuda::run()
{
bool NLmove = NonLocalMove == "yes";
bool scaleweight = ScaleWeight == "yes";
if (NLmove)
app_log() << " Using Casula nonlocal moves in DMCcuda.\n";
if (scaleweight)
app_log() << " Scaling weight per Umrigar/Nightengale.\n";
resetRun();
Mover->MaxAge = 1;
IndexType block = 0;
IndexType nAcceptTot = 0;
IndexType nRejectTot = 0;
int nat = W.getTotalNum();
int nw = W.getActiveWalkers();
vector<RealType> LocalEnergy(nw), LocalEnergyOld(nw),
oldScale(nw), newScale(nw);
vector<PosType> delpos(nw);
vector<PosType> dr(nw);
vector<PosType> newpos(nw);
vector<ValueType> ratios(nw), rplus(nw), rminus(nw), R2prop(nw), R2acc(nw);
vector<PosType> oldG(nw), newG(nw);
vector<ValueType> oldL(nw), newL(nw);
vector<Walker_t*> accepted(nw);
Matrix<ValueType> lapl(nw, nat);
Matrix<GradType> grad(nw, nat);
vector<ValueType> V2(nw), V2bar(nw);
vector<vector<NonLocalData> > Txy(nw);
for (int iw=0; iw<nw; iw++)
W[iw]->Weight = 1.0;
do {
IndexType step = 0;
nAccept = nReject = 0;
Estimators->startBlock(nSteps);
do {
step++;
CurrentStep++;
nw = W.getActiveWalkers();
ResizeTimer.start();
LocalEnergy.resize(nw); oldScale.resize(nw);
newScale.resize(nw); delpos.resize(nw);
dr.resize(nw); newpos.resize(nw);
ratios.resize(nw); rplus.resize(nw);
rminus.resize(nw); oldG.resize(nw);
newG.resize(nw); oldL.resize(nw);
newL.resize(nw); accepted.resize(nw);
lapl.resize(nw, nat); grad.resize(nw, nat);
R2prop.resize(nw,0.0); R2acc.resize(nw,0.0);
V2.resize(nw,0.0); V2bar.resize(nw,0.0);
W.updateLists_GPU();
ResizeTimer.stop();
if (NLmove) {
Txy.resize(nw);
for (int iw=0; iw<nw; iw++) {
Txy[iw].clear();
Txy[iw].push_back(NonLocalData(-1, 1.0, PosType()));
}
}
for (int iw=0; iw<nw; iw++)
W[iw]->Age++;
DriftDiffuseTimer.start();
for(int iat=0; iat<nat; iat++) {
Psi.getGradient (W, iat, oldG);
//create a 3N-Dimensional Gaussian with variance=1
makeGaussRandomWithEngine(delpos,Random);
for(int iw=0; iw<nw; iw++) {
delpos[iw] *= m_sqrttau;
oldScale[iw] = getDriftScale(m_tauovermass,oldG[iw]);
dr[iw] = delpos[iw] + (oldScale[iw]*oldG[iw]);
newpos[iw]=W[iw]->R[iat] + dr[iw];
ratios[iw] = 1.0;
R2prop[iw] += dot(delpos[iw], delpos[iw]);
}
W.proposeMove_GPU(newpos, iat);
Psi.ratio(W,iat,ratios,newG, newL);
accepted.clear();
vector<bool> acc(nw, false);
for(int iw=0; iw<nw; ++iw) {
PosType drOld =
newpos[iw] - (W[iw]->R[iat] + oldScale[iw]*oldG[iw]);
RealType logGf = -m_oneover2tau * dot(drOld, drOld);
newScale[iw] = getDriftScale(m_tauovermass,newG[iw]);
PosType drNew =
(newpos[iw] + newScale[iw]*newG[iw]) - W[iw]->R[iat];
RealType logGb = -m_oneover2tau * dot(drNew, drNew);
RealType x = logGb - logGf;
RealType prob = ratios[iw]*ratios[iw]*std::exp(x);
if(Random() < prob && ratios[iw] > 0.0) {
accepted.push_back(W[iw]);
nAccept++;
W[iw]->R[iat] = newpos[iw];
W[iw]->Age = 0;
acc[iw] = true;
R2acc[iw] += dot(delpos[iw], delpos[iw]);
V2[iw] += m_tauovermass * m_tauovermass * dot(newG[iw],newG[iw]);
V2bar[iw] += newScale[iw] * newScale[iw] * dot(newG[iw],newG[iw]);
}
else {
nReject++;
V2[iw] += m_tauovermass * m_tauovermass * dot(oldG[iw],oldG[iw]);
V2bar[iw] += oldScale[iw] * oldScale[iw] * dot(oldG[iw],oldG[iw]);
}
}
W.acceptMove_GPU(acc);
if (accepted.size())
Psi.update(accepted,iat);
}
DriftDiffuseTimer.stop();
// Psi.recompute(W, false);
Psi.gradLapl(W, grad, lapl);
HTimer.start();
if (NLmove) H.evaluate (W, LocalEnergy, Txy);
else H.evaluate (W, LocalEnergy);
HTimer.stop();
// for (int iw=0; iw<nw; iw++) {
// branchEngine->clampEnergy(LocalEnergy[iw]);
// W[iw]->getPropertyBase()[LOCALENERGY] = LocalEnergy[iw];
// }
if (CurrentStep == 1)
LocalEnergyOld = LocalEnergy;
if (NLmove) {
// Now, attempt nonlocal move
accepted.clear();
vector<int> iatList;
vector<PosType> accPos;
for (int iw=0; iw<nw; iw++) {
/// HACK HACK HACK
// if (LocalEnergy[iw] < -2300.0) {
// cerr << "Walker " << iw << " has energy "
// << LocalEnergy[iw] << endl;;
// double maxWeight = 0.0;
// int elMax = -1;
// PosType posMax;
// for (int j=1; j<Txy[iw].size(); j++)
// if (std::fabs(Txy[iw][j].Weight) > std::fabs(maxWeight)) {
// maxWeight = Txy[iw][j].Weight;
// elMax = Txy[iw][j].PID;
// posMax = W[iw]->R[elMax] + Txy[iw][j].Delta;
// }
// cerr << "Maximum weight is " << maxWeight << " for electron "
// << elMax << " at position " << posMax << endl;
// PosType unit = W.Lattice.toUnit(posMax);
// unit[0] -= round(unit[0]);
// unit[1] -= round(unit[1]);
// unit[2] -= round(unit[2]);
// cerr << "Reduced position = " << unit << endl;
// }
int ibar = NLop.selectMove(Random(), Txy[iw]);
if (ibar) {
accepted.push_back(W[iw]);
int iat = Txy[iw][ibar].PID;
iatList.push_back(iat);
accPos.push_back(W[iw]->R[iat] + Txy[iw][ibar].Delta);
}
}
if (accepted.size()) {
Psi.ratio(accepted,iatList, accPos, ratios, newG, newL);
Psi.update(accepted,iatList);
for (int i=0; i<accepted.size(); i++)
accepted[i]->R[iatList[i]] = accPos[i];
W.NLMove_GPU (accepted, accPos, iatList);
// HACK HACK HACK
// Recompute the kinetic energy
// Psi.gradLapl(W, grad, lapl);
// H.evaluate (W, LocalEnergy);
//W.copyWalkersToGPU();
}
}
// Now branch
BranchTimer.start();
for (int iw=0; iw<nw; iw++) {
RealType v2=0.0, v2bar=0.0;
for(int iat=0; iat<nat; iat++) {
v2 += dot(W.G[iat],W.G[iat]);
RealType newscale = getDriftScale(m_tauovermass,newG[iw]);
v2 += m_tauovermass * m_tauovermass * dot(newG[iw],newG[iw]);
v2bar += newscale * newscale * dot(newG[iw],newG[iw]);
}
//RealType scNew = std::sqrt(V2bar[iw] / V2[iw]);
RealType scNew = std::sqrt(v2bar/v2);
RealType scOld = (CurrentStep == 1) ? scNew : W[iw]->getPropertyBase()[DRIFTSCALE];
W[iw]->getPropertyBase()[DRIFTSCALE] = scNew;
// fprintf (stderr, "iw = %d scNew = %1.8f scOld = %1.8f\n", iw, scNew, scOld);
RealType tauRatio = R2acc[iw] / R2prop[iw];
if (tauRatio < 0.5)
cerr << " tauRatio = " << tauRatio << endl;
RealType taueff = m_tauovermass * tauRatio;
if (scaleweight)
W[iw]->Weight *= branchEngine->branchWeightTau
(LocalEnergy[iw], LocalEnergyOld[iw], scNew, scOld, taueff);
else
W[iw]->Weight *= branchEngine->branchWeight
(LocalEnergy[iw], LocalEnergyOld[iw]);
W[iw]->getPropertyBase()[R2ACCEPTED] = R2acc[iw];
W[iw]->getPropertyBase()[R2PROPOSED] = R2prop[iw];
}
Mover->setMultiplicity(W.begin(), W.end());
branchEngine->branch(CurrentStep,W);
nw = W.getActiveWalkers();
LocalEnergyOld.resize(nw);
for (int iw=0; iw<nw; iw++)
LocalEnergyOld[iw] = W[iw]->getPropertyBase()[LOCALENERGY];
BranchTimer.stop();
} while(step<nSteps);
Psi.recompute(W, true);
double accept_ratio = (double)nAccept/(double)(nAccept+nReject);
Estimators->stopBlock(accept_ratio);
nAcceptTot += nAccept;
nRejectTot += nReject;
++block;
recordBlock(block);
} while(block<nBlocks);
//finalize a qmc section
return finalize(block);
}
bool DMCcuda::runWithNonlocal()
{
resetRun();
Mover->MaxAge = 1;
IndexType block = 0;
IndexType nAcceptTot = 0;
IndexType nRejectTot = 0;
int nat = W.getTotalNum();
int nw = W.getActiveWalkers();
vector<RealType> LocalEnergy(nw), LocalEnergyOld(nw),
oldScale(nw), newScale(nw);
vector<PosType> delpos(nw);
vector<PosType> dr(nw);
vector<PosType> newpos(nw);
vector<ValueType> ratios(nw), rplus(nw), rminus(nw), R2prop(nw), R2acc(nw);
vector<PosType> oldG(nw), newG(nw);
vector<ValueType> oldL(nw), newL(nw);
vector<Walker_t*> accepted(nw);
Matrix<ValueType> lapl(nw, nat);
Matrix<GradType> grad(nw, nat);
vector<vector<NonLocalData> > Txy(nw);
for (int iw=0; iw<nw; iw++)
W[iw]->Weight = 1.0;
do {
IndexType step = 0;
nAccept = nReject = 0;
Estimators->startBlock(nSteps);
do {
step++;
CurrentStep++;
nw = W.getActiveWalkers();
LocalEnergy.resize(nw); oldScale.resize(nw);
newScale.resize(nw); delpos.resize(nw);
dr.resize(nw); newpos.resize(nw);
ratios.resize(nw); rplus.resize(nw);
rminus.resize(nw); oldG.resize(nw);
newG.resize(nw); oldL.resize(nw);
newL.resize(nw); accepted.resize(nw);
lapl.resize(nw, nat); grad.resize(nw, nat);
R2prop.resize(nw,0.0); R2acc.resize(nw,0.0);
W.updateLists_GPU();
Txy.resize(nw);
for (int iw=0; iw<nw; iw++) {
Txy[iw].clear();
Txy[iw].push_back(NonLocalData(-1, 1.0, PosType()));
W[iw]->Age++;
}
for(int iat=0; iat<nat; iat++) {
Psi.getGradient (W, iat, oldG);
//create a 3N-Dimensional Gaussian with variance=1
makeGaussRandomWithEngine(delpos,Random);
for(int iw=0; iw<nw; iw++) {
delpos[iw] *= m_sqrttau;
oldScale[iw] = getDriftScale(m_tauovermass,oldG[iw]);
dr[iw] = delpos[iw] + (oldScale[iw]*oldG[iw]);
newpos[iw]=W[iw]->R[iat] + dr[iw];
ratios[iw] = 1.0;
R2prop[iw] += dot(delpos[iw], delpos[iw]);
}
W.proposeMove_GPU(newpos, iat);
Psi.ratio(W,iat,ratios,newG, newL);
accepted.clear();
vector<bool> acc(nw, false);
for(int iw=0; iw<nw; ++iw) {
PosType drOld =
newpos[iw] - (W[iw]->R[iat] + oldScale[iw]*oldG[iw]);
RealType logGf = -m_oneover2tau * dot(drOld, drOld);
newScale[iw] = getDriftScale(m_tauovermass,newG[iw]);
PosType drNew =
(newpos[iw] + newScale[iw]*newG[iw]) - W[iw]->R[iat];
RealType logGb = -m_oneover2tau * dot(drNew, drNew);
RealType x = logGb - logGf;
RealType prob = ratios[iw]*ratios[iw]*std::exp(x);
if(Random() < prob && ratios[iw] > 0.0) {
accepted.push_back(W[iw]);
nAccept++;
W[iw]->R[iat] = newpos[iw];
W[iw]->Age = 0;
acc[iw] = true;
R2acc[iw] += dot(delpos[iw], delpos[iw]);
}
else
nReject++;
}
W.acceptMove_GPU(acc);
if (accepted.size())
Psi.update(accepted,iat);
}
for (int iw=0; iw < nw; iw++)
if (W[iw]->Age)
cerr << "Encountered stuck walker with iw=" << iw << endl;
// Psi.recompute(W, false);
Psi.gradLapl(W, grad, lapl);
H.evaluate (W, LocalEnergy, Txy);
if (CurrentStep == 1)
LocalEnergyOld = LocalEnergy;
// Now, attempt nonlocal move
accepted.clear();
vector<int> iatList;
vector<PosType> accPos;
for (int iw=0; iw<nw; iw++) {
int ibar = NLop.selectMove(Random(), Txy[iw]);
// cerr << "Txy[iw].size() = " << Txy[iw].size() << endl;
if (ibar) {
accepted.push_back(W[iw]);
int iat = Txy[iw][ibar].PID;
iatList.push_back(iat);
accPos.push_back(W[iw]->R[iat] + Txy[iw][ibar].Delta);
}
}
if (accepted.size()) {
// W.proposeMove_GPU(newpos, iatList);
Psi.ratio(accepted,iatList, accPos, ratios, newG, newL);
Psi.update(accepted,iatList);
for (int i=0; i<accepted.size(); i++)
accepted[i]->R[iatList[i]] = accPos[i];
W.copyWalkersToGPU();
}
// Now branch
for (int iw=0; iw<nw; iw++) {
W[iw]->Weight *= branchEngine->branchWeight(LocalEnergy[iw], LocalEnergyOld[iw]);
W[iw]->getPropertyBase()[R2ACCEPTED] = R2acc[iw];
W[iw]->getPropertyBase()[R2PROPOSED] = R2prop[iw];
}
Mover->setMultiplicity(W.begin(), W.end());
branchEngine->branch(CurrentStep,W);
nw = W.getActiveWalkers();
LocalEnergyOld.resize(nw);
for (int iw=0; iw<nw; iw++)
LocalEnergyOld[iw] = W[iw]->getPropertyBase()[LOCALENERGY];
} while(step<nSteps);
Psi.recompute(W, true);
double accept_ratio = (double)nAccept/(double)(nAccept+nReject);
Estimators->stopBlock(accept_ratio);
nAcceptTot += nAccept;
nRejectTot += nReject;
++block;
recordBlock(block);
} while(block<nBlocks);
//finalize a qmc section
return finalize(block);
}
void Island::Step(const TimeStep &timeStep)
{
ContactSolver contactSolver(*this);
// update velocity
for (auto &body : mRigidBodies)
{
switch (body.mType)
{
case RigidBody::DYNAMIC:
float dtscale = body.mParent->cphy->dtScale;
// apply gravity
if (body.mHasGravity)
{
Vector3 newG( mGravity + body.mGravityFactor);
body.mLinearVelocity += newG * timeStep.dt;
}
// integrate velocity
body.mLinearVelocity +=
body.mMassData.inverseMass * (body.mLinearImpulseAccumulator + body.mForceAccumulator * timeStep.dt * dtscale);
body.mAngularVelocity +=
body.mGlobalInverseInertiaTensor * (body.mAngularImpulseAccumulator + body.mTorqueAccumulator * timeStep.dt * dtscale);
body.mForceAccumulator.ZeroOut();
body.mTorqueAccumulator.ZeroOut();
body.mLinearImpulseAccumulator.ZeroOut();
body.mAngularImpulseAccumulator.ZeroOut();
body.mLinearVelocity *= mLinearDamp;
body.mAngularVelocity *= mAngularDamp;
break;
}
}
// warm start
if (timeStep.params.warmStart)
contactSolver.WarmStartVelocityConstraints(timeStep);
// initialize constraints
for (auto &joint : mJoints)
joint.InitializeVelocityConstraints(timeStep);
contactSolver.InitializeVelocityConstraints(timeStep);
// solve constraints
for (unsigned char i = 0; i < timeStep.velocityIterations; ++i)
{
for (auto &joint : mJoints)
joint.SolveVelocityConstraints(timeStep);
contactSolver.SolveVelocityConstraints(timeStep);
}
// cache velocity constraint results
if (timeStep.params.warmStart)
contactSolver.CacheVelocityConstraintResults(timeStep);
// integrate position
for (auto &body : mRigidBodies)
{
// integrate
body.IntegratePosition(timeStep);
// update
body.UpdateOrientation();
body.UpdatePositionFromGlobalCentroid();
}
// solve position constraints, NOPE
for (unsigned char i = 0; i < timeStep.positionIterations; ++i)
{
for (auto &joint : mJoints)
joint.SolvePositionConstraints(timeStep);
contactSolver.SolvePositionConstraints(timeStep);
}
// update proxies
for (auto &body : mRigidBodies)
body.UpdateProxies();
}
