bool ASMs1D::updateRotations (const Vector& displ, bool reInit)
{
if (shareFE || nf != 6) return true;
if (displ.size() != 6*myT.size())
{
std::cerr <<" *** ASMs1D::updateRotations: Invalid dimension "
<< displ.size() <<" on displ, should be "
<< 6*myT.size() << std::endl;
return false;
}
if (reInit)
{
if (prevT.empty())
{
for (size_t i = 0; i < myT.size(); i++)
myT[i] = Tensor(displ[6*i+3],displ[6*i+4],displ[6*i+5]);
return true;
}
else
myT = prevT; // Restore rotation tensors from previous step
}
for (size_t i = 0; i < myT.size(); i++)
myT[i].preMult(Tensor(displ[6*i+3],displ[6*i+4],displ[6*i+5]));
return true;
}
inline void
FixedQuadrupleListInteractionTemplate < _DihedralPotential >::
computeVirialTensor(Tensor& w) {
LOG4ESPP_INFO(theLogger, "compute the virial tensor of the quadruples");
Tensor wlocal(0.0);
const bc::BC& bc = *getSystemRef().bc;
for (FixedQuadrupleList::QuadrupleList::Iterator it(*fixedquadrupleList); it.isValid(); ++it) {
const Particle &p1 = *it->first;
const Particle &p2 = *it->second;
const Particle &p3 = *it->third;
const Particle &p4 = *it->fourth;
Real3D dist21, dist32, dist43;
bc.getMinimumImageVectorBox(dist21, p2.position(), p1.position());
bc.getMinimumImageVectorBox(dist32, p3.position(), p2.position());
bc.getMinimumImageVectorBox(dist43, p4.position(), p3.position());
Real3D force1, force2, force3, force4;
potential->_computeForce(force1, force2, force3, force4,
dist21, dist32, dist43);
// TODO: formulas are not correct yet
wlocal += Tensor(dist21, force1) - Tensor(dist32, force2);
}
// reduce over all CPUs
Tensor wsum(0.0);
boost::mpi::all_reduce(*mpiWorld, (double*)&wlocal, 6, (double*)&wsum, std::plus<double>());
w += wsum;
}
template < typename _AngularPotential > inline void
FixedTripleAngleListInteractionTemplate < _AngularPotential >::
computeVirialTensor(Tensor& w) {
LOG4ESPP_INFO(theLogger, "compute the virial tensor of the triples");
Tensor wlocal(0.0);
const bc::BC& bc = *getSystemRef().bc;
for (FixedTripleAngleList::TripleList::Iterator it(*fixedtripleList); it.isValid(); ++it){
const Particle &p1 = *it->first;
const Particle &p2 = *it->second;
const Particle &p3 = *it->third;
//const Potential &potential = getPotential(0, 0);
Real3D r12, r32;
bc.getMinimumImageVectorBox(r12, p1.position(), p2.position());
bc.getMinimumImageVectorBox(r32, p3.position(), p2.position());
Real3D force12, force32;
real currentAngle = fixedtripleList->getAngle(p1.getId(), p2.getId(), p3.getId());
potential->_computeForce(force12, force32, r12, r32, currentAngle);
wlocal += Tensor(r12, force12) + Tensor(r32, force32);
}
// reduce over all CPUs
Tensor wsum(0.0);
boost::mpi::all_reduce(*mpiWorld, (double*)&wlocal,6, (double*)&wsum, std::plus<double>());
w += wsum;
}
inline void
FixedTripleListTypesInteractionTemplate<_Potential>::computeVirialTensor(Tensor &w) {
LOG4ESPP_INFO(theLogger, "compute the virial tensor for the FixedTriple List");
Tensor wlocal(0.0);
const bc::BC& bc = *getSystemRef().bc;
for (FixedTripleList::TripleList::Iterator it(*fixedtripleList); it.isValid(); ++it) {
const Particle &p1 = *it->first;
const Particle &p2 = *it->second;
const Particle &p3 = *it->third;
int type1 = p1.type();
int type2 = p2.type();
int type3 = p3.type();
const Potential &potential = getPotential(type1, type2, type3);
Real3D r12, r32;
bc.getMinimumImageVectorBox(r12, p1.position(), p2.position());
bc.getMinimumImageVectorBox(r32, p3.position(), p2.position());
Real3D force12, force32;
potential._computeForce(force12, force32, r12, r32);
wlocal += Tensor(r12, force12) + Tensor(r32, force32);
}
// reduce over all CPUs
Tensor wsum(0.0);
boost::mpi::all_reduce(*mpiWorld, wlocal, wsum, std::plus<Tensor>());
w += wsum;
}
poly* SAtensor(boolean alt,_index m,poly* p)
{ _index n,r=Lierank(grp); poly** adams,** q,* result;
if (m==0) return poly_one(r); else if (m==1) return p;
adams=alloc_array(poly*,m+1);
for (n=1; n<=m; ++n) adams[n]=Adams(n,p);
q=alloc_array(poly*,m+1);
q[0]=poly_one(r);
for (n=1; n<=m; ++n)
{
{ _index i; q[n]=Tensor(p,q[n-1]); /* the initial term of the summation */
for (i=2; i<=n; ++i) q[n] =
Add_pol_pol(q[n],Tensor(adams[i],q[n-i]),alt&&i%2==0);
}
{ _index i; bigint* big_n=entry2bigint(n); setshared(big_n);
for (i=0; i<q[n]->nrows; ++i)
{ bigint** cc= &q[n]->coef[i]
,* c= (clrshared(*cc),isshared(*cc)) ? copybigint(*cc,NULL) : *cc;
*cc=divq(c,big_n); setshared(*cc);
{ if (c->size != 0)
error("Internal error (SAtensor): remainder from %ld.\n" ,(long)n);
freemem(c);
}
}
clrshared(big_n); freemem(big_n);
}
}
result=q[m];
{ for (n=1; n<=m; ++n) freepol(adams[n]); } freearr(adams);
{ for (n=0; n<m; ++n) freepol(q[n]); } freearr(q);
return result;
}
double VolumeTetrapore::calculateNumberInside( const Vector& cpos, Vector& derivatives, Tensor& vir, std::vector<Vector>& rderiv ) const {
// Setup the histogram bead
HistogramBead bead; bead.isNotPeriodic(); bead.setKernelType( getKernelType() );
// Calculate distance of atom from origin of new coordinate frame
Vector datom=pbcDistance( origin, cpos );
double ucontr, uder, vcontr, vder, wcontr, wder;
// Calculate contribution from integral along bi
bead.set( 0, len_bi, sigma );
double upos=dotProduct( datom, bi );
ucontr=bead.calculate( upos, uder );
double udlen=bead.uboundDerivative( upos );
double uder2 = bead.lboundDerivative( upos ) - udlen;
// Calculate contribution from integral along cross
bead.set( 0, len_cross, sigma );
double vpos=dotProduct( datom, cross );
vcontr=bead.calculate( vpos, vder );
double vdlen=bead.uboundDerivative( vpos );
double vder2 = bead.lboundDerivative( vpos ) - vdlen;
// Calculate contribution from integral along perp
bead.set( 0, len_perp, sigma );
double wpos=dotProduct( datom, perp );
wcontr=bead.calculate( wpos, wder );
double wdlen=bead.uboundDerivative( wpos );
double wder2 = bead.lboundDerivative( wpos ) - wdlen;
Vector dfd; dfd[0]=uder*vcontr*wcontr; dfd[1]=ucontr*vder*wcontr; dfd[2]=ucontr*vcontr*wder;
derivatives[0] = (dfd[0]*bi[0]+dfd[1]*cross[0]+dfd[2]*perp[0]);
derivatives[1] = (dfd[0]*bi[1]+dfd[1]*cross[1]+dfd[2]*perp[1]);
derivatives[2] = (dfd[0]*bi[2]+dfd[1]*cross[2]+dfd[2]*perp[2]);
double tot = ucontr*vcontr*wcontr*jacob_det;
// Add reference atom derivatives
dfd[0]=uder2*vcontr*wcontr; dfd[1]=ucontr*vder2*wcontr; dfd[2]=ucontr*vcontr*wder2;
Vector dfld; dfld[0]=udlen*vcontr*wcontr; dfld[1]=ucontr*vdlen*wcontr; dfld[2]=ucontr*vcontr*wdlen;
rderiv[0] = dfd[0]*matmul(datom,dbi[0]) + dfd[1]*matmul(datom,dcross[0]) + dfd[2]*matmul(datom,dperp[0]) +
dfld[0]*dlbi[0] + dfld[1]*dlcross[0] + dfld[2]*dlperp[0] - derivatives;
rderiv[1] = dfd[0]*matmul(datom,dbi[1]) + dfd[1]*matmul(datom,dcross[1]) + dfd[2]*matmul(datom,dperp[1]) +
dfld[0]*dlbi[1] + dfld[1]*dlcross[1] + dfld[2]*dlperp[1];
rderiv[2] = dfd[0]*matmul(datom,dbi[2]) + dfd[1]*matmul(datom,dcross[2]) + dfd[2]*matmul(datom,dperp[2]) +
dfld[0]*dlbi[2] + dfld[1]*dlcross[2] + dfld[2]*dlperp[2];
rderiv[3] = dfld[0]*dlbi[3] + dfld[1]*dlcross[3] + dfld[2]*dlperp[3];
vir.zero(); vir-=Tensor( cpos,derivatives );
for(unsigned i=0;i<4;++i){
vir -= Tensor( getPosition(i), rderiv[i] );
}
return tot;
}
pair<Tensor, float> computeSampleGradient(const TrainingSample &sample, NetworkContext &ctx) {
Vector output = process(sample.input, ctx);
ctx.layerDeltas.resize(numLayers);
ctx.layerDeltas[ctx.layerDeltas.size() - 1] = output - sample.expectedOutput; // cross entropy error function.
for (int i = ctx.layerDeltas.size() - 2; i >= 0; i--) {
Matrix noBiasWeights =
layerWeights(i+1).bottomRightCorner(layerWeights(i+1).rows(), layerWeights(i+1).cols()-1);
ctx.layerDeltas[i] = noBiasWeights.transpose() * ctx.layerDeltas[i+1];
assert(ctx.layerDeltas[i].rows() == ctx.layerOutputs[i].rows());
for (unsigned r = 0; r < ctx.layerDeltas[i].rows(); r++) {
float out = ctx.layerOutputs[i](r);
ctx.layerDeltas[i](r) *= out * (1.0f - out);
}
}
auto result = make_pair(Tensor(), 0.0f);
for (unsigned i = 0; i < numLayers; i++) {
auto inputs = getInputWithBias(i == 0 ? sample.input : ctx.layerOutputs[i-1]);
result.first.AddLayer(ctx.layerDeltas[i] * inputs.transpose());
}
for (unsigned i = 0; i < output.rows(); i++) {
result.second += (output(i) - sample.expectedOutput(i)) * (output(i) - sample.expectedOutput(i));
}
return result;
}
Tensor TensorFieldFunction::evaluate (const Vec3& X) const
{
if (pidx >= field.size() || !field[pidx])
return Tensor(3);
return const_cast<TensorFieldFunction*>(this)->getValues(X);
}
double ContactAlignedMatrix::compute( const unsigned& tindex, multicolvar::AtomValuePack& myatoms ) const {
double f_dot, dot_df;
std::vector<double> orient0(ncomp), orient1(ncomp);
getOrientationVector( myatoms.getIndex(0), true, orient0 );
getOrientationVector( myatoms.getIndex(1), true, orient1 );
double dot=0; for(unsigned k=2;k<orient0.size();++k) dot+=orient0[k]*orient1[k];
f_dot=0.5*( 1 + dot ); dot_df=0.5;
// Retrieve the weight of the connection
double weight = myatoms.getValue(0); myatoms.setValue(0,1.0);
if( !doNotCalculateDerivatives() ){
Vector distance = getSeparation( myatoms.getPosition(0), myatoms.getPosition(1) );
double dfunc, sw = switchingFunction( getBaseColvarNumber( myatoms.getIndex(0) ), getBaseColvarNumber( myatoms.getIndex(1) ) ).calculate( distance.modulo(), dfunc );
addAtomDerivatives( 1, 0, (-dfunc)*f_dot*distance, myatoms );
addAtomDerivatives( 1, 1, (+dfunc)*f_dot*distance, myatoms );
myatoms.addBoxDerivatives( 1, (-dfunc)*f_dot*Tensor(distance,distance) );
// Add derivatives of orientation
for(unsigned k=2;k<orient0.size();++k){ orient0[k]*=sw*dot_df; orient1[k]*=sw*dot_df; }
addOrientationDerivatives( 1, 0, orient1, myatoms );
addOrientationDerivatives( 1, 1, orient0, myatoms );
}
return weight*f_dot;
}
void Mapping::mergeDerivatives( const unsigned& ider, const double& df ){
unsigned cur = getCurrentTask(), frameno=ider*getNumberOfReferencePoints() + cur;
for(unsigned i=0;i<getNumberOfArguments();++i){
accumulateDerivative( i, df*dfframes[frameno]*mymap->getArgumentDerivative(cur,i) );
}
if( getNumberOfAtoms()>0 ){
Vector ader; Tensor tmpvir; tmpvir.zero();
unsigned n=getNumberOfArguments();
for(unsigned i=0;i<getNumberOfAtoms();++i){
ader=mymap->getAtomDerivatives( cur, i );
accumulateDerivative( n, df*dfframes[frameno]*ader[0] ); n++;
accumulateDerivative( n, df*dfframes[frameno]*ader[1] ); n++;
accumulateDerivative( n, df*dfframes[frameno]*ader[2] ); n++;
tmpvir += -1.0*Tensor( getPosition(i), ader );
}
Tensor vir;
if( !mymap->getVirial( cur, vir ) ) vir=tmpvir;
accumulateDerivative( n, df*dfframes[frameno]*vir(0,0) ); n++;
accumulateDerivative( n, df*dfframes[frameno]*vir(0,1) ); n++;
accumulateDerivative( n, df*dfframes[frameno]*vir(0,2) ); n++;
accumulateDerivative( n, df*dfframes[frameno]*vir(1,0) ); n++;
accumulateDerivative( n, df*dfframes[frameno]*vir(1,1) ); n++;
accumulateDerivative( n, df*dfframes[frameno]*vir(1,2) ); n++;
accumulateDerivative( n, df*dfframes[frameno]*vir(2,0) ); n++;
accumulateDerivative( n, df*dfframes[frameno]*vir(2,1) ); n++;
accumulateDerivative( n, df*dfframes[frameno]*vir(2,2) );
}
}
double DistanceFromContour::compute( const unsigned& tindex, AtomValuePack& myatoms ) const {
Vector distance = getSeparation( getPosition(getNumberOfAtoms()-1), myatoms.getPosition(0) );
std::vector<double> pp(3), der(3,0); for(unsigned j=0;j<3;++j) pp[j] = distance[j];
// Now create the kernel and evaluate
KernelFunctions kernel( pp, bw, kerneltype, false, 1.0, true );
double newval = kernel.evaluate( pval, der, true );
if( mybasemulticolvars[0]->isDensity() ){
if( !doNotCalculateDerivatives() && derivTime ){
MultiValue& myvals=myatoms.getUnderlyingMultiValue();
Vector vder; unsigned basen=myvals.getNumberOfDerivatives() - 12;
for(unsigned i=0;i<3;++i){
vder[i]=der[i]; myvals.addDerivative( 1, basen+i, vder[i] );
}
myatoms.setValue( 2, der[dir] );
addAtomDerivatives( 1, 0, -vder, myatoms );
myatoms.addBoxDerivatives( 1, Tensor(vder,distance) );
}
myatoms.setValue( 0, 1.0 ); return newval;
}
// This does the stuff for averaging
myatoms.setValue( 0, newval );
// This gets the average if we are using a phase field
std::vector<double> cvals( mybasemulticolvars[0]->getNumberOfQuantities() );
mybasedata[0]->retrieveValueWithIndex( tindex, false, cvals );
return newval*cvals[0]*cvals[1];
}
poly* Plethysm(entry* lambda,_index l,_index n,poly* p)
{ if (n==0) return poly_one(Lierank(grp)); else if (n==1) return p;
{ _index i,j;
poly* sum= poly_null(Lierank(grp)),**adams=alloc_array(poly*,n+1);
poly* chi_lambda=MN_char(lambda,l);
for (i=1; i<=n; ++i) { adams[i]=Adams(i,p); setshared(adams[i]); }
for (i=0;i<chi_lambda->nrows;i++)
{ entry* mu=chi_lambda->elm[i]; poly* prod=adams[mu[0]],*t;
for (j=1; j<n && mu[j]>0; ++j)
{ t=prod; prod=Tensor(t,adams[mu[j]]); freepol(t); }
sum= Addmul_pol_pol_bin(sum,prod,mult(chi_lambda->coef[i],Classord(mu,n)));
}
freemem(chi_lambda);
setshared(p); /* protect |p|; it coincides with |adams[1]| */
for (i=1; i<=n; ++i)
{ clrshared(adams[i]); freepol(adams[i]); } freearr(adams);
clrshared(p);
{ bigint* fac_n=fac(n); setshared(fac_n); /* used repeatedly */
for (i=0; i<sum->nrows; ++i)
{ bigint** cc= &sum->coef[i]
,* c= (clrshared(*cc),isshared(*cc)) ? copybigint(*cc,NULL) : *cc;
*cc=divq(c,fac_n); setshared(*cc);
if (c->size!=0) error("Internal error (plethysm).\n"); else freemem(c);
}
clrshared(fac_n); freemem(fac_n);
}
return sum;
}
}
double OrientationSphere::compute(){
// Make sure derivatives for central atom are only calculated once
VectorMultiColvar* vv = dynamic_cast<VectorMultiColvar*>( getBaseMultiColvar(0) );
vv->firstcall=true;
weightHasDerivatives=true; // The weight has no derivatives really
double sw, value=0, denom=0, dot, f_dot, dot_df, dfunc; Vector distance;
getVectorForBaseTask(0, catom_orient );
for(unsigned i=1;i<getNAtoms();++i){
distance=getSeparation( getPositionOfCentralAtom(0), getPositionOfCentralAtom(i) );
sw = switchingFunction.calculateSqr( distance.modulo2(), dfunc );
if( sw>=getTolerance() ){
getVectorForBaseTask( i, this_orient );
// Calculate the dot product wrt to this position
dot=0; for(unsigned k=0;k<catom_orient.size();++k) dot+=catom_orient[k]*this_orient[k];
f_dot = transformDotProduct( dot, dot_df );
// N.B. We are assuming here that the imaginary part of the dot product is zero
for(unsigned k=0;k<catom_orient.size();++k){
this_orient[k]*=sw*dot_df; catom_der[k]=sw*dot_df*catom_orient[k];
}
// Set the derivatives wrt of the numerator
addOrientationDerivatives( 0, this_orient );
addOrientationDerivatives( i, catom_der );
addCentralAtomsDerivatives( 0, 0, f_dot*(-dfunc)*distance );
addCentralAtomsDerivatives( i, 0, f_dot*(dfunc)*distance );
addBoxDerivatives( f_dot*(-dfunc)*Tensor(distance,distance) );
value += sw*f_dot;
// Set the derivatives wrt to the numerator
addCentralAtomsDerivatives( 0, 1, (-dfunc)*distance );
addCentralAtomsDerivatives( i, 1, (dfunc)*distance );
addBoxDerivativesOfWeight( (-dfunc)*Tensor(distance,distance) );
denom += sw;
}
}
// Now divide everything
unsigned nder = getNumberOfDerivatives();
for(unsigned i=0;i<nder;++i){
setElementDerivative( i, getElementDerivative(i)/denom - (value*getElementDerivative(nder+i))/(denom*denom) );
setElementDerivative( nder + i, 0.0 );
}
weightHasDerivatives=false; // Weight has no derivatives we just use the holder for weight to store some stuff
return value / denom;
}
void Colvar::setBoxDerivativesNoPbc(Value* v){
Tensor virial;
unsigned nat=getNumberOfAtoms();
for(unsigned i=0;i<nat;i++) virial-=Tensor(getPosition(i),
Vector(v->getDerivative(3*i+0),
v->getDerivative(3*i+1),
v->getDerivative(3*i+2)));
setBoxDerivatives(v,virial);
}
void BondOrientation::calculateVector( multicolvar::AtomValuePack& myatoms ) const {
Vector distance=getSeparation( myatoms.getPosition(0), myatoms.getPosition(1) );
addAtomDerivatives( 2, 0, Vector(-1.0,0,0), myatoms );
addAtomDerivatives( 2, 1, Vector(+1.0,0,0), myatoms );
myatoms.addBoxDerivatives( 2, Tensor(distance,Vector(-1.0,0,0)) );
myatoms.addValue( 2, distance[0] );
addAtomDerivatives( 3, 0, Vector(0,-1.0,0), myatoms );
addAtomDerivatives( 3, 1, Vector(0,+1.0,0), myatoms );
myatoms.addBoxDerivatives( 3, Tensor(distance,Vector(0,-1.0,0)) );
myatoms.addValue( 3, distance[1] );
addAtomDerivatives( 4, 0, Vector(0,0,-1.0), myatoms );
addAtomDerivatives( 4, 1, Vector(0,0,+1.0), myatoms );
myatoms.addBoxDerivatives( 4, Tensor(distance,Vector(0,0,-1.0)) );
myatoms.addValue( 4, distance[2] );
}
inline void
FixedQuadrupleListTypesInteractionTemplate<_DihedralPotential>::
computeVirialTensor(Tensor &w, real z) {
LOG4ESPP_INFO(theLogger, "compute the virial tensor of the quadruples");
Tensor wlocal(0.0);
const bc::BC &bc = *getSystemRef().bc;
std::cout << "Warning!!! computeVirialTensor in specified volume doesn't work for "
"FixedQuadrupleListTypesInteractionTemplate at the moment" << std::endl;
for (FixedQuadrupleList::QuadrupleList::Iterator it(*fixedquadrupleList); it.isValid(); ++it) {
const Particle &p1 = *it->first;
const Particle &p2 = *it->second;
const Particle &p3 = *it->third;
const Particle &p4 = *it->fourth;
longint type1 = p1.type();
longint type2 = p2.type();
longint type3 = p3.type();
longint type4 = p4.type();
const Potential &potential = getPotential(type1, type2, type3, type4);
Real3D dist21, dist32, dist43;
bc.getMinimumImageVectorBox(dist21, p2.position(), p1.position());
bc.getMinimumImageVectorBox(dist32, p3.position(), p2.position());
bc.getMinimumImageVectorBox(dist43, p4.position(), p3.position());
Real3D force1, force2, force3, force4;
potential.computeForce(force1, force2, force3, force4,
dist21, dist32, dist43);
// TODO: formulas are not correct yet
wlocal += Tensor(dist21, force1) - Tensor(dist32, force2);
}
// reduce over all CPUs
Tensor wsum(0.0);
boost::mpi::all_reduce(*mpiWorld, (double *) &wlocal, 6, (double *) &wsum, std::plus<double>());
w += wsum;
}
TTTensor peaking_diagonals(size_t _degree, size_t _n, value_t _alpha) {
REQUIRE(_degree >= 2, "");
REQUIRE(_n>=2, "");
TTTensor e1(Tensor({_n}, [](){return 1.0;}));
TTTensor cross(Tensor({_n,_n}, [&](const std::vector<size_t> &idx){
return 1.0/(double(idx[0]>idx[1]?idx[0]-idx[1]:idx[1]-idx[0]) + _alpha) + 1.0/(double(idx[0])+_alpha) + 1.0/(double(idx[1])+_alpha);
}));
TTTensor result(cross);
TTTensor buffer(e1);
while (result.degree() < _degree) {
result = dyadic_product(result, e1);
TTTensor tmp = dyadic_product(buffer, cross);
result += tmp;
result.round(0.0);
buffer = dyadic_product(buffer, e1);
}
return result;
}
// calculator
void CoordinationBase::calculate()
{
double ncoord=0.;
Tensor virial;
vector<Vector> deriv(getNumberOfAtoms());
// deriv.resize(getPositions().size());
if(nl->getStride()>0 && invalidateList){
nl->update(getPositions());
}
unsigned stride=comm.Get_size();
unsigned rank=comm.Get_rank();
if(serial){
stride=1;
rank=0;
}else{
stride=comm.Get_size();
rank=comm.Get_rank();
}
for(unsigned int i=rank;i<nl->size();i+=stride) { // sum over close pairs
Vector distance;
unsigned i0=nl->getClosePair(i).first;
unsigned i1=nl->getClosePair(i).second;
if(getAbsoluteIndex(i0)==getAbsoluteIndex(i1)) continue;
if(pbc){
distance=pbcDistance(getPosition(i0),getPosition(i1));
} else {
distance=delta(getPosition(i0),getPosition(i1));
}
double dfunc=0.;
ncoord += pairing(distance.modulo2(), dfunc,i0,i1);
deriv[i0] = deriv[i0] + (-dfunc)*distance ;
deriv[i1] = deriv[i1] + dfunc*distance ;
virial=virial+(-dfunc)*Tensor(distance,distance);
}
if(!serial){
comm.Sum(ncoord);
if(!deriv.empty()) comm.Sum(&deriv[0][0],3*deriv.size());
comm.Sum(virial);
}
for(unsigned i=0;i<deriv.size();++i) setAtomsDerivatives(i,deriv[i]);
setValue (ncoord);
setBoxDerivatives (virial);
}
double ContactMatrix::compute( const unsigned& tindex, multicolvar::AtomValuePack& myatoms ) const {
if( !doNotCalculateDerivatives() ){
Vector distance = getSeparation( myatoms.getPosition(0), myatoms.getPosition(1) );
double dfunc, sw = switchingFunction( getBaseColvarNumber( myatoms.getIndex(0) ), getBaseColvarNumber( myatoms.getIndex(1) ) - ncol_t ).calculate( distance.modulo(), dfunc );
addAtomDerivatives( 1, 0, (-dfunc)*distance, myatoms );
addAtomDerivatives( 1, 1, (+dfunc)*distance, myatoms );
myatoms.addBoxDerivatives( 1, (-dfunc)*Tensor(distance,distance) );
}
double val=myatoms.getValue(0); myatoms.setValue(0,1.0);
return val;
}
bool ASMs1D::initLocalElementAxes (const Vec3& Zaxis)
{
// Calculate local element axes for 3D beam elements
for (size_t i = 0; i < myCS.size(); i++)
if (MLGE[i] > 0)
{
Vec3 X1 = this->getCoord(1+MNPC[i].front());
Vec3 X2 = this->getCoord(1+MNPC[i][curv->order()-1]);
if (Zaxis.isZero())
myCS[i] = Tensor(X2-X1,true);
else
myCS[i] = Tensor(X2-X1,Zaxis,false,true);
#ifdef SP_DEBUG
std::cout <<"Local axes for beam element "<< MLGE[i]
<<", from "<< X1 <<" to "<< X2 <<":\n"<< myCS[i];
#endif
}
return true;
}
void SecondaryStructureRMSD::performTask( const unsigned& task_index, const unsigned& current, MultiValue& myvals ) const {
// Retrieve the positions
std::vector<Vector> pos( references[0]->getNumberOfAtoms() );
const unsigned n=pos.size();
for(unsigned i=0;i<n;++i) pos[i]=ActionAtomistic::getPosition( getAtomIndex(current,i) );
// This does strands cutoff
Vector distance=pbcDistance( pos[align_atom_1],pos[align_atom_2] );
if( s_cutoff2>0 ){
if( distance.modulo2()>s_cutoff2 ){
myvals.setValue( 0, 0.0 );
return;
}
}
// This aligns the two strands if this is required
if( alignType!="DRMSD" && align_strands ){
Vector origin_old, origin_new; origin_old=pos[align_atom_2];
origin_new=pos[align_atom_1]+distance;
for(unsigned i=15;i<30;++i){
pos[i]+=( origin_new - origin_old );
}
}
// Create a holder for the derivatives
ReferenceValuePack mypack( 0, pos.size(), myvals ); mypack.setValIndex( 1 );
for(unsigned i=0;i<n;++i) mypack.setAtomIndex( i, getAtomIndex(current,i) );
// And now calculate the RMSD
const Pbc& pbc=getPbc();
unsigned closest=0;
double r = references[0]->calculate( pos, pbc, mypack, false );
const unsigned rs = references.size();
for(unsigned i=1;i<rs;++i){
mypack.setValIndex( i+1 );
double nr=references[i]->calculate( pos, pbc, mypack, false );
if( nr<r ){ closest=i; r=nr; }
}
// Transfer everything to the value
myvals.setValue( 0, 1.0 ); myvals.setValue( 1, r );
if( closest>0 ) mypack.moveDerivatives( closest+1, 1 );
if( !mypack.virialWasSet() ){
Tensor vir;
const unsigned cacs = colvar_atoms[current].size();
for(unsigned i=0;i<cacs;++i){
vir+=(-1.0*Tensor( pos[i], mypack.getAtomDerivative(i) ));
}
mypack.setValIndex(1); mypack.addBoxDerivatives( vir );
}
return;
}
void FacenetClassifier::create_input_tensor (long start_index, long end_index) {
cout << "Using " << input_images.size() << " images" << endl;
cout << "Start Index:" << start_index << " End Index:" << end_index << endl;
Tensor input_tensor(DT_FLOAT, TensorShape({(int) (end_index - start_index), 160, 160, 3}));
// get pointer to memory for that Tensor
float *p = input_tensor.flat<float>().data();
int i;
for (i = 0; i < (end_index - start_index) ; i++) {
// create a "fake" cv::Mat from it
Mat camera_image(160, 160, CV_32FC3, p + i*160*160*3);
input_images[i + start_index].convertTo(camera_image, CV_32FC3);
}
cout << input_tensor.DebugString() << endl;
this->input_tensor = Tensor (input_tensor);
}
double TopologyMatrix::compute( const unsigned& tindex, multicolvar::AtomValuePack& myatoms ) const {
HistogramBead bead; bead.isNotPeriodic(); bead.setKernelType( kerneltype );
// Initialise to zero density on all bins
for(unsigned bin=0; bin<maxbins; ++bin) myatoms.setValue(bin+1,0);
// Calculate whether or not atoms 1 and 2 are within cutoff (can use delta here as pbc are done in atom setup)
Vector d1 = getSeparation( myatoms.getPosition(0), myatoms.getPosition(1) ); double d1_len = d1.modulo();
d1 = d1 / d1_len; // Convert vector into director
AtomNumber a1 = myatoms.getAbsoluteIndex( 0 );
AtomNumber a2 = myatoms.getAbsoluteIndex( 1 );
for(unsigned i=2; i<myatoms.getNumberOfAtoms(); ++i) {
AtomNumber a3 = myatoms.getAbsoluteIndex( i );
if( a3!=a1 && a3!=a2 ) calculateForThreeAtoms( i, d1, d1_len, bead, myatoms );
}
// std::vector<double> binvals( 1+maxbins ); for(unsigned i=1;i<maxbins;++i) binvals[i]=myatoms.getValue(i);
// unsigned ii; double fdf;
//std::cout<<"HELLO DENSITY "<<myatoms.getIndex(0)<<" "<<myatoms.getIndex(1)<<" "<<transformStoredValues( binvals, ii, fdf )<<std::endl;
// Now find the element for which the density is maximal
unsigned vout=2; double max=myatoms.getValue( 2 );
for(unsigned i=3; i<myatoms.getUnderlyingMultiValue().getNumberOfValues()-1; ++i) {
if( myatoms.getValue(i)>max ) { max=myatoms.getValue(i); vout=i; }
}
// Calculate value and derivative of switching function between atoms 1 and 2
double dfuncl, sw = switchingFunction( getBaseColvarNumber( myatoms.getIndex(0) ),
getBaseColvarNumber( myatoms.getIndex(1) ) ).calculate( d1_len, dfuncl );
// Transform the density
double df, tsw = threshold_switch.calculate( max, df );
if( !doNotCalculateDerivatives() ) {
// Factor of d1_len is required here because d1 is normalized
d1 *= d1_len;
addAtomDerivatives( 2+maxbins, 0, -dfuncl*d1, myatoms );
addAtomDerivatives( 2+maxbins, 1, dfuncl*d1, myatoms );
myatoms.addBoxDerivatives( 2+maxbins, (-dfuncl)*Tensor(d1,d1) );
// Update active atoms so that next bit works
updateActiveAtoms( myatoms );
// Now finish caclulation of derivatives
MultiValue& myvals=myatoms.getUnderlyingMultiValue();
for(unsigned jd=0; jd<myvals.getNumberActive(); ++jd) {
unsigned ider=myvals.getActiveIndex(jd);
myvals.addDerivative( 1, ider, sw*df*max*myvals.getDerivative( vout, ider ) + tsw*myvals.getDerivative( 2+maxbins, ider ) );
}
}
return sw*tsw;
}
void DFSClusterDiameter::performTask( const unsigned& task_index, const unsigned& current, MultiValue& myvals ) const {
unsigned iatom=current/getNumberOfNodes(), jatom = current - iatom*getNumberOfNodes();
Vector distance=getSeparation( getPosition(iatom), getPosition(jatom) );
double dd = distance.modulo(), inv = 1.0/dd ; myvals.setValue( 1, dd );
if( !doNotCalculateDerivatives() ){
myvals.addDerivative( 1, 3*iatom + 0, -inv*distance[0] );
myvals.addDerivative( 1, 3*iatom + 1, -inv*distance[1] );
myvals.addDerivative( 1, 3*iatom + 2, -inv*distance[2] );
myvals.addDerivative( 1, 3*jatom + 0, +inv*distance[0] );
myvals.addDerivative( 1, 3*jatom + 1, +inv*distance[1] );
myvals.addDerivative( 1, 3*jatom + 2, +inv*distance[2] );
Tensor vir = -inv*Tensor(distance,distance);
unsigned vbase = myvals.getNumberOfDerivatives() - 9;
for(unsigned i=0;i<3;++i){
for(unsigned j=0;j<3;++j) myvals.addDerivative( 1, vbase+3*i+j, vir(i,j) );
}
}
}
bool ASMs1D::generateTwistedFEModel (const RealFunc& twist, const Vec3& Zaxis)
{
if (!this->generateOrientedFEModel(Zaxis))
return false;
// Update the local element axes for 3D beam elements
Tensor rotX(3);
for (size_t i = 0; i < myCS.size(); i++)
if (MLGE[i] > 0)
{
Vec3 X1 = this->getCoord(1+MNPC[i].front());
Vec3 X2 = this->getCoord(1+MNPC[i][curv->order()-1]);
double alpha = twist(0.5*(X1+X2)); // twist angle in the element mid-point
myCS[i] *= Tensor(alpha*M_PI/180.0,1); // rotate about local X-axis
#ifdef SP_DEBUG
std::cout <<"Twisted axes for beam element "<< MLGE[i]
<<", from "<< X1 <<" to "<< X2 <<":\n"<< myCS[i];
#endif
}
return true;
}
double DRMSD::calc( const std::vector<Vector>& pos, const Pbc& pbc, ReferenceValuePack& myder, const bool& squared ) const {
plumed_dbg_assert(!targets.empty());
Vector distance;
myder.clear();
double drmsd=0.;
for(std::map< std::pair <unsigned,unsigned> , double>::const_iterator it=targets.begin();it!=targets.end();++it){
const unsigned i=getAtomIndex( it->first.first );
const unsigned j=getAtomIndex( it->first.second );
if(nopbc) distance=delta( pos[i] , pos[j] );
else distance=pbc.distance( pos[i] , pos[j] );
const double len = distance.modulo();
const double diff = len - it->second;
const double der = diff / len;
drmsd += diff * diff;
myder.addAtomDerivatives( i, -der * distance );
myder.addAtomDerivatives( j, der * distance );
myder.addBoxDerivatives( - der * Tensor(distance,distance) );
}
const double inpairs = 1./static_cast<double>(targets.size());
double idrmsd;
if(squared){
drmsd = drmsd * inpairs;
idrmsd = 2.0 * inpairs;
} else {
drmsd = sqrt( drmsd * inpairs );
idrmsd = inpairs / drmsd ;
}
myder.scaleAllDerivatives( idrmsd );
return drmsd;
}
double DRMSD::calc( const std::vector<Vector>& pos, const Pbc& pbc, const bool& squared ){
plumed_dbg_assert( !targets.empty() );
Vector distance;
double drmsd=0.;
for(std::map< std::pair <unsigned,unsigned> , double>::const_iterator it=targets.begin();it!=targets.end();++it){
unsigned i=getAtomIndex( it->first.first );
unsigned j=getAtomIndex( it->first.second );
if(nopbc){ distance=delta( pos[i] , pos[j] ); }
else{ distance=pbc.distance( pos[i] , pos[j] ); }
double len = distance.modulo();
double diff = len - it->second;
drmsd += diff * diff;
addAtomicDerivatives( i, -( diff / len ) * distance );
addAtomicDerivatives( j, ( diff / len ) * distance );
addBoxDerivatives( -( diff / len ) * Tensor(distance,distance) );
}
double npairs = static_cast<double>(targets.size());
double idrmsd;
if(squared){
drmsd = drmsd / npairs;
idrmsd = 2.0 / npairs;
} else {
drmsd = sqrt( drmsd / npairs );
idrmsd = 1.0/( drmsd * npairs );
}
virial *= idrmsd;
for(unsigned i=0;i<getNumberOfAtoms();++i){atom_ders[i] *= idrmsd;}
return drmsd;
}
static inline const Tensor
do_string_order_many(const iTEBD<Tensor> &psi,
const Tensor &Opi, const Tensor &Opmiddle,
const Tensor &Opj, int N)
{
if (!psi.is_canonical()) {
return do_string_order_many(psi.canonical_form(), Opi, Opmiddle, Opj, N);
} else {
Tensor v1 = psi.left_boundary(0);
Tensor v2 = v1;
Tensor output(N);
Tensor nextv2;
for (int site = 0; (site < N); ++site) {
const Tensor &aux = psi.combined_matrix(site);
Tensor v = propagate_right(v1, aux, site? Opj : mmult(Opi,Opj));
if (nextv2.size()) {
v2 = nextv2;
} else {
v2 = propagate_right(v2, aux);
}
if (!(site & 1)) {
const Tensor &aux = psi.combined_matrix(site+1);
nextv2 = propagate_right(v2, aux);
v = propagate_right(v, aux);
output.at(site) = trace(v) / trace(nextv2);
} else {
nextv2 = Tensor();
output.at(site) = trace(v) / trace(v2);
}
if (site) {
v1 = propagate_right(v1, aux, Opmiddle);
} else {
v1 = propagate_right(v1, aux, Opi);
}
}
return output;
}
}
double OrientationSphere::compute( const unsigned& tindex, multicolvar::AtomValuePack& myatoms ) const {
// Make sure derivatives for central atom are only calculated once
VectorMultiColvar* vv = dynamic_cast<VectorMultiColvar*>( getBaseMultiColvar(0) );
vv->firstcall=true;
double d2, sw, value=0, denom=0, dot, f_dot, dot_df, dfunc;
unsigned ncomponents=getBaseMultiColvar(0)->getNumberOfQuantities();
unsigned nder=myatoms.getNumberOfDerivatives();
std::vector<double> catom_orient( ncomponents ), this_orient( ncomponents ), catom_der( ncomponents );
Vector catom_pos = myatoms.getPosition(0);
getVectorForTask( myatoms.getIndex(0), true, catom_orient );
multicolvar::CatomPack atom0; MultiValue myder0(0,0), myder1(0,0);
if( !doNotCalculateDerivatives() ){
myder0.resize( ncomponents,nder ); myder1.resize(ncomponents,nder);
atom0=getCentralAtomPackFromInput( myatoms.getIndex(0) );
getVectorDerivatives( myatoms.getIndex(0), true, myder0 );
}
for(unsigned i=1;i<myatoms.getNumberOfAtoms();++i){
Vector& distance=myatoms.getPosition(i);
if ( (d2=distance[0]*distance[0])<rcut2 &&
(d2+=distance[1]*distance[1])<rcut2 &&
(d2+=distance[2]*distance[2])<rcut2) {
sw = switchingFunction.calculateSqr( d2, dfunc );
getVectorForTask( myatoms.getIndex(i), true, this_orient );
// Calculate the dot product wrt to this position
dot=0; for(unsigned k=2;k<catom_orient.size();++k) dot+=catom_orient[k]*this_orient[k];
f_dot = transformDotProduct( dot, dot_df );
if( !doNotCalculateDerivatives() ){
// N.B. We are assuming here that the imaginary part of the dot product is zero
for(unsigned k=2;k<catom_orient.size();++k){
this_orient[k]*=sw*dot_df; catom_der[k]=sw*dot_df*catom_orient[k];
}
getVectorDerivatives( myatoms.getIndex(i), true, myder1 );
mergeVectorDerivatives( 1, 2, this_orient.size(), myatoms.getIndex(0), this_orient, myder0, myatoms );
mergeVectorDerivatives( 1, 2, catom_der.size(), myatoms.getIndex(i), catom_der, myder1, myatoms );
myatoms.addComDerivatives( 1, f_dot*(-dfunc)*distance, atom0 );
addAtomDerivatives( 1, i, f_dot*(dfunc)*distance, myatoms );
myatoms.addBoxDerivatives( 1, (-dfunc)*f_dot*Tensor(distance,distance) );
myder1.clearAll();
myatoms.addComDerivatives( -1, (-dfunc)*distance, atom0 );
addAtomDerivatives( -1, i, (dfunc)*distance, myatoms );
myatoms.addTemporyBoxDerivatives( (-dfunc)*Tensor(distance,distance) );
}
value += sw*f_dot;
denom += sw;
}
}
double rdenom, df2, pref=calculateCoordinationPrefactor( denom, df2 );
if( fabs(denom)>epsilon ){ rdenom = 1.0 / denom; }
else { plumed_assert(fabs(value)<epsilon); rdenom=1.0; }
// Now divide everything
double rdenom2=rdenom*rdenom;
updateActiveAtoms( myatoms ); MultiValue& myvals=myatoms.getUnderlyingMultiValue();
for(unsigned i=0;i<myvals.getNumberActive();++i){
unsigned ider=myvals.getActiveIndex(i);
double dgd=myvals.getTemporyDerivative(ider);
myvals.setDerivative( 1, ider, rdenom*(pref*myvals.getDerivative(1,ider)+value*df2*dgd) - (value*pref*dgd)*rdenom2 );
}
return pref*rdenom*value;
}
Tensor5D CVX_ADMM_MSA (SequenceSet& allSeqs, vector<int>& lenSeqs, int T2, string& dir_path) {
// 1. initialization
int numSeq = allSeqs.size();
vector<Tensor4D> C (numSeq, Tensor4D(0, Tensor(T2, Matrix(NUM_DNA_TYPE,
vector<double>(NUM_MOVEMENT, 0.0)))));
vector<Tensor4D> W_1 (numSeq, Tensor4D(0, Tensor(T2, Matrix(NUM_DNA_TYPE,
vector<double>(NUM_MOVEMENT, 0.0)))));
vector<Tensor4D> W_2 (numSeq, Tensor4D(0, Tensor(T2, Matrix(NUM_DNA_TYPE,
vector<double>(NUM_MOVEMENT, 0.0)))));
vector<Tensor4D> Y (numSeq, Tensor4D(0, Tensor(T2, Matrix(NUM_DNA_TYPE,
vector<double>(NUM_MOVEMENT, 0.0)))));
tensor5D_init (C, allSeqs, lenSeqs, T2);
tensor5D_init (W_1, allSeqs, lenSeqs, T2);
tensor5D_init (W_2, allSeqs, lenSeqs, T2);
tensor5D_init (Y, allSeqs, lenSeqs, T2);
set_C (C, allSeqs);
// 2. ADMM iteration
int iter = 0;
double mu = MU;
double prev_CoZ = MAX_DOUBLE;
while (iter < MAX_ADMM_ITER) {
// 2a. Subprogram: FrankWolf Algorithm
// NOTE: parallelize this for to enable parallelism
#ifdef PARRALLEL_COMPUTING
#pragma omp parallel for
#endif
for (int n = 0; n < numSeq; n++)
first_subproblem (W_1[n], W_2[n], Y[n], C[n], mu, allSeqs[n]);
// 2b. Subprogram:
second_subproblem (W_1, W_2, Y, mu, allSeqs, lenSeqs);
// 2d. update Y: Y += mu * (W_1 - W_2)
for (int n = 0; n < numSeq; n ++)
tensor4D_lin_update (Y[n], W_1[n], W_2[n], mu);
// 2e. print out tracking info
double CoZ = 0.0;
for (int n = 0; n < numSeq; n++)
CoZ += tensor4D_frob_prod(C[n], W_2[n]);
double W1mW2 = 0.0;
for (int n = 0; n < numSeq; n ++) {
int T1 = W_1[n].size();
for (int i = 0; i < T1; i ++)
for (int j = 0; j < T2; j ++)
for (int d = 0; d < NUM_DNA_TYPE; d ++)
for (int m = 0; m < NUM_MOVEMENT; m ++) {
double value = (W_1[n][i][j][d][m] - W_2[n][i][j][d][m]);
W1mW2 = max( fabs(value), W1mW2 ) ;
}
}
///////////////////////////////////Copy from Main/////////////////////////////////////////
int T2m = T2;
Tensor tensor (T2m, Matrix (NUM_DNA_TYPE, vector<double>(NUM_DNA_TYPE, 0.0)));
Matrix mat_insertion (T2m, vector<double> (NUM_DNA_TYPE, 0.0));
for (int n = 0; n < numSeq; n ++) {
int T1 = W_2[n].size();
for (int i = 0; i < T1; i ++) {
for (int j = 0; j < T2m; j ++) {
for (int d = 0; d < NUM_DNA_TYPE; d ++) {
for (int m = 0; m < NUM_MOVEMENT; m ++) {
if (m == DELETION_A or m == MATCH_A)
tensor[j][d][dna2T3idx('A')] += max(0.0, W_2[n][i][j][d][m]);
else if (m == DELETION_T or m == MATCH_T)
tensor[j][d][dna2T3idx('T')] += max(0.0, W_2[n][i][j][d][m]);
else if (m == DELETION_C or m == MATCH_C)
tensor[j][d][dna2T3idx('C')] += max(0.0, W_2[n][i][j][d][m]);
else if (m == DELETION_G or m == MATCH_G)
tensor[j][d][dna2T3idx('G')] += max(0.0, W_2[n][i][j][d][m]);
else if (m == DELETION_START or m == MATCH_START)
tensor[j][d][dna2T3idx('*')] += max(0.0, W_2[n][i][j][d][m]);
else if (m == DELETION_END or m == MATCH_END)
tensor[j][d][dna2T3idx('#')] += max(0.0, W_2[n][i][j][d][m]);
else if (m == INSERTION)
mat_insertion[j][d] += max(0.0, W_2[n][i][j][d][m]);
}
}
}
}
}
Trace trace (0, Cell(2)); // 1d: j, 2d: ATCG
refined_viterbi_algo (trace, tensor, mat_insertion);
Sequence recSeq;
for (int i = 0; i < trace.size(); i ++)
if (trace[i].action != INSERTION) {
recSeq.push_back(trace[i].acidB);
if (trace[i].acidB == '#') break;
}
////////////////////////////////END copy from MAIN/////////////////////////////////////////////////////
SequenceSet allModelSeqs, allDataSeqs;
double obj_rounded = 0.0;
for (int n = 0; n < numSeq; n ++) {
Sequence model_seq = recSeq, data_seq = allSeqs[n];
data_seq.erase(data_seq.begin());
model_seq.erase(model_seq.begin());
data_seq.erase(data_seq.end()-1);
model_seq.erase(model_seq.end()-1);
// align sequences locally
Plane plane (data_seq.size()+1, Trace(model_seq.size()+1, Cell(2)));
Trace trace (0, Cell(2));
smith_waterman (model_seq, data_seq, plane, trace);
// get the objective of rounded result
for (int i = 0; i < trace.size(); i ++) {
if (trace[i].acidA == '-' && trace[i].acidB != '-')
obj_rounded += 1.0;//C_I;
else if (trace[i].acidA != '-' && trace[i].acidB == '-')
obj_rounded += 1.0;//C_D;
else if (trace[i].acidA == trace[i].acidB)
obj_rounded += 0.0;//C_M;
else if (trace[i].acidA != trace[i].acidB)
obj_rounded += 1.0;//C_MM;
}
model_seq.clear(); data_seq.clear();
for (int i = 0; i < trace.size(); i ++)
model_seq.push_back(trace[i].acidA);
for (int i = 0; i < trace.size(); i ++)
data_seq.push_back(trace[i].acidB);
allModelSeqs.push_back(model_seq);
allDataSeqs.push_back(data_seq);
}
//writeClusterView( dir_path+to_string(iter), allModelSeqs, allDataSeqs );
// cerr << "=============================================================================" << endl;
char COZ_val [50], w1mw2_val [50];
sprintf(COZ_val, "%6f", CoZ);
sprintf(w1mw2_val, "%6f", W1mW2);
cerr << "ADMM_iter = " << iter
<< ", C o Z = " << COZ_val
<< ", Wdiff_max = " << w1mw2_val
<< ", obj_rounded = " << obj_rounded
<< endl;
// cerr << "sub1_Obj = CoW_1+0.5*mu*||W_1-Z+1/mu*Y_1||^2 = " << sub1_cost << endl;
// cerr << "sub2_Obj = ||W_2-Z+1/mu*Y_2||^2 = " << sub2_cost << endl;
// 2f. stopping conditions
if (ADMM_EARLY_STOP_TOGGLE and iter > MIN_ADMM_ITER)
if ( W1mW2 < EPS_Wdiff ) {
cerr << "CoZ Converges. ADMM early stop!" << endl;
break;
}
prev_CoZ = CoZ;
iter ++;
}
cout << "W_1: " << endl;
for (int i = 0; i < numSeq; i ++) tensor4D_dump(W_1[i]);
cout << "W_2: " << endl;
for (int i = 0; i < numSeq; i ++) tensor4D_dump(W_2[i]);
return W_2;
}