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gezelter |
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#include <math.h> |
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#include "OOPSEMinimizer.hpp" |
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#include "Integrator.cpp" |
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OOPSEMinimizer::OOPSEMinimizer( SimInfo *theInfo, ForceFields* the_ff , |
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MinimizerParameterSet * param) : |
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RealIntegrator(theInfo, the_ff), bShake(true), bVerbose(false) { |
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dumpOut = NULL; |
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statOut = NULL; |
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tStats = new Thermo(info); |
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paramSet = param; |
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calcDim(); |
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curX = getCoor(); |
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curG.resize(ndim); |
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preMove(); |
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} |
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OOPSEMinimizer::~OOPSEMinimizer(){ |
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delete tStats; |
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if(dumpOut) |
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delete dumpOut; |
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if(statOut) |
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delete statOut; |
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delete paramSet; |
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} |
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void OOPSEMinimizer::calcEnergyGradient(vector<double>& x, vector<double>& grad, |
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double& energy, int& status){ |
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DirectionalAtom* dAtom; |
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int index; |
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double force[3]; |
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double dAtomGrad[6]; |
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int shakeStatus; |
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status = 1; |
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setCoor(x); |
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if (nConstrained && bShake){ |
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shakeStatus = shakeR(); |
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} |
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calcForce(1, 1); |
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if (nConstrained && bShake){ |
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shakeStatus = shakeF(); |
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} |
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x = getCoor(); |
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index = 0; |
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for(int i = 0; i < integrableObjects.size(); i++){ |
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if (integrableObjects[i]->isDirectional()) { |
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integrableObjects[i]->getGrad(dAtomGrad); |
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//gradient is equal to -f |
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grad[index++] = -dAtomGrad[0]; |
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grad[index++] = -dAtomGrad[1]; |
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grad[index++] = -dAtomGrad[2]; |
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grad[index++] = -dAtomGrad[3]; |
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grad[index++] = -dAtomGrad[4]; |
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grad[index++] = -dAtomGrad[5]; |
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} |
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else{ |
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integrableObjects[i]->getFrc(force); |
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grad[index++] = -force[0]; |
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grad[index++] = -force[1]; |
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grad[index++] = -force[2]; |
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} |
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} |
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energy = tStats->getPotential(); |
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} |
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void OOPSEMinimizer::setCoor(vector<double>& x){ |
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DirectionalAtom* dAtom; |
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int index; |
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double position[3]; |
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double eulerAngle[3]; |
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index = 0; |
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for(int i = 0; i < integrableObjects.size(); i++){ |
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position[0] = x[index++]; |
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position[1] = x[index++]; |
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position[2] = x[index++]; |
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integrableObjects[i]->setPos(position); |
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if (integrableObjects[i]->isDirectional()){ |
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eulerAngle[0] = x[index++]; |
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eulerAngle[1] = x[index++]; |
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eulerAngle[2] = x[index++]; |
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integrableObjects[i]->setEuler(eulerAngle[0], |
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eulerAngle[1], |
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eulerAngle[2]); |
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} |
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} |
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} |
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vector<double> OOPSEMinimizer::getCoor(){ |
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DirectionalAtom* dAtom; |
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int index; |
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double position[3]; |
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double eulerAngle[3]; |
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vector<double> x; |
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x.resize(getDim()); |
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index = 0; |
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for(int i = 0; i < integrableObjects.size(); i++){ |
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integrableObjects[i]->getPos(position); |
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x[index++] = position[0]; |
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x[index++] = position[1]; |
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x[index++] = position[2]; |
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if (integrableObjects[i]->isDirectional()){ |
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integrableObjects[i]->getEulerAngles(eulerAngle); |
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x[index++] = eulerAngle[0]; |
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x[index++] = eulerAngle[1]; |
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x[index++] = eulerAngle[2]; |
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} |
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} |
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return x; |
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} |
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int OOPSEMinimizer::shakeR(){ |
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int i, j; |
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int done; |
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double posA[3], posB[3]; |
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double velA[3], velB[3]; |
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double pab[3]; |
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double rab[3]; |
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int a, b, ax, ay, az, bx, by, bz; |
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double rma, rmb; |
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double dx, dy, dz; |
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double rpab; |
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double rabsq, pabsq, rpabsq; |
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double diffsq; |
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double gab; |
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int iteration; |
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for (i = 0; i < nAtoms; i++){ |
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moving[i] = 0; |
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moved[i] = 1; |
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} |
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iteration = 0; |
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done = 0; |
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while (!done && (iteration < maxIteration)){ |
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done = 1; |
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for (i = 0; i < nConstrained; i++){ |
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a = constrainedA[i]; |
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b = constrainedB[i]; |
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ax = (a * 3) + 0; |
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ay = (a * 3) + 1; |
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az = (a * 3) + 2; |
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bx = (b * 3) + 0; |
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by = (b * 3) + 1; |
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bz = (b * 3) + 2; |
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if (moved[a] || moved[b]){ |
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atoms[a]->getPos(posA); |
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atoms[b]->getPos(posB); |
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for (j = 0; j < 3; j++) |
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pab[j] = posA[j] - posB[j]; |
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//periodic boundary condition |
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info->wrapVector(pab); |
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pabsq = pab[0] * pab[0] + pab[1] * pab[1] + pab[2] * pab[2]; |
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rabsq = constrainedDsqr[i]; |
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diffsq = rabsq - pabsq; |
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// the original rattle code from alan tidesley |
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if (fabs(diffsq) > (tol * rabsq * 2)){ |
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rab[0] = oldPos[ax] - oldPos[bx]; |
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rab[1] = oldPos[ay] - oldPos[by]; |
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rab[2] = oldPos[az] - oldPos[bz]; |
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info->wrapVector(rab); |
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rpab = rab[0] * pab[0] + rab[1] * pab[1] + rab[2] * pab[2]; |
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rpabsq = rpab * rpab; |
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if (rpabsq < (rabsq * -diffsq)){ |
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#ifdef IS_MPI |
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a = atoms[a]->getGlobalIndex(); |
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b = atoms[b]->getGlobalIndex(); |
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#endif //is_mpi |
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//cerr << "Waring: constraint failure" << endl; |
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gab = sqrt(rabsq/pabsq); |
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rab[0] = (posA[0] - posB[0])*gab; |
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rab[1]= (posA[1] - posB[1])*gab; |
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rab[2] = (posA[2] - posB[2])*gab; |
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info->wrapVector(rab); |
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rpab = rab[0] * pab[0] + rab[1] * pab[1] + rab[2] * pab[2]; |
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} |
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//rma = 1.0 / atoms[a]->getMass(); |
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//rmb = 1.0 / atoms[b]->getMass(); |
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rma = 1.0; |
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rmb =1.0; |
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gab = diffsq / (2.0 * (rma + rmb) * rpab); |
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dx = rab[0] * gab; |
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dy = rab[1] * gab; |
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dz = rab[2] * gab; |
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posA[0] += rma * dx; |
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posA[1] += rma * dy; |
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posA[2] += rma * dz; |
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atoms[a]->setPos(posA); |
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posB[0] -= rmb * dx; |
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posB[1] -= rmb * dy; |
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posB[2] -= rmb * dz; |
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atoms[b]->setPos(posB); |
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moving[a] = 1; |
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moving[b] = 1; |
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done = 0; |
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} |
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} |
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} |
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for (i = 0; i < nAtoms; i++){ |
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moved[i] = moving[i]; |
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moving[i] = 0; |
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} |
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iteration++; |
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} |
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if (!done){ |
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cerr << "Waring: can not constraint within maxIteration" << endl; |
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return -1; |
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} |
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else |
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return 1; |
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} |
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//remove constraint force along the bond direction |
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int OOPSEMinimizer::shakeF(){ |
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int i, j; |
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int done; |
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double posA[3], posB[3]; |
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double frcA[3], frcB[3]; |
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double rab[3], fpab[3]; |
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int a, b, ax, ay, az, bx, by, bz; |
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double rma, rmb; |
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double rvab; |
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double gab; |
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double rabsq; |
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double rfab; |
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int iteration; |
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for (i = 0; i < nAtoms; i++){ |
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moving[i] = 0; |
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moved[i] = 1; |
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} |
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done = 0; |
| 312 |
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iteration = 0; |
| 313 |
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while (!done && (iteration < maxIteration)){ |
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done = 1; |
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| 316 |
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for (i = 0; i < nConstrained; i++){ |
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a = constrainedA[i]; |
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b = constrainedB[i]; |
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| 320 |
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ax = (a * 3) + 0; |
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ay = (a * 3) + 1; |
| 322 |
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az = (a * 3) + 2; |
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| 324 |
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bx = (b * 3) + 0; |
| 325 |
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by = (b * 3) + 1; |
| 326 |
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bz = (b * 3) + 2; |
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| 328 |
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if (moved[a] || moved[b]){ |
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| 330 |
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atoms[a]->getPos(posA); |
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atoms[b]->getPos(posB); |
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| 333 |
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for (j = 0; j < 3; j++) |
| 334 |
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rab[j] = posA[j] - posB[j]; |
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| 336 |
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info->wrapVector(rab); |
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| 338 |
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atoms[a]->getFrc(frcA); |
| 339 |
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atoms[b]->getFrc(frcB); |
| 340 |
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| 341 |
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//rma = 1.0 / atoms[a]->getMass(); |
| 342 |
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//rmb = 1.0 / atoms[b]->getMass(); |
| 343 |
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rma = 1.0; |
| 344 |
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rmb = 1.0; |
| 345 |
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| 346 |
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| 347 |
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fpab[0] = frcA[0] * rma - frcB[0] * rmb; |
| 348 |
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fpab[1] = frcA[1] * rma - frcB[1] * rmb; |
| 349 |
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fpab[2] = frcA[2] * rma - frcB[2] * rmb; |
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gab=fpab[0] * fpab[0] + fpab[1] * fpab[1] + fpab[2] * fpab[2]; |
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| 354 |
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if (gab < 1.0) |
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gab = 1.0; |
| 356 |
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| 357 |
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rabsq = rab[0] * rab[0] + rab[1] * rab[1] + rab[2] * rab[2]; |
| 358 |
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rfab = rab[0] * fpab[0] + rab[1] * fpab[1] + rab[2] * fpab[2]; |
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| 360 |
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if (fabs(rfab) > sqrt(rabsq*gab) * 0.00001){ |
| 361 |
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| 362 |
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gab = -rfab /(rabsq*(rma + rmb)); |
| 363 |
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| 364 |
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frcA[0] = rab[0] * gab; |
| 365 |
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frcA[1] = rab[1] * gab; |
| 366 |
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frcA[2] = rab[2] * gab; |
| 367 |
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| 368 |
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atoms[a]->addFrc(frcA); |
| 369 |
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| 370 |
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| 371 |
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frcB[0] = -rab[0] * gab; |
| 372 |
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frcB[1] = -rab[1] * gab; |
| 373 |
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frcB[2] = -rab[2] * gab; |
| 374 |
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| 375 |
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atoms[b]->addFrc(frcB); |
| 376 |
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| 377 |
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moving[a] = 1; |
| 378 |
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moving[b] = 1; |
| 379 |
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done = 0; |
| 380 |
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} |
| 381 |
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} |
| 382 |
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} |
| 383 |
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| 384 |
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for (i = 0; i < nAtoms; i++){ |
| 385 |
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moved[i] = moving[i]; |
| 386 |
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moving[i] = 0; |
| 387 |
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} |
| 388 |
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| 389 |
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iteration++; |
| 390 |
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} |
| 391 |
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| 392 |
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if (!done){ |
| 393 |
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cerr << "Waring: can not constraint within maxIteration" << endl; |
| 394 |
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return -1; |
| 395 |
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|
} |
| 396 |
|
|
else |
| 397 |
|
|
return 1; |
| 398 |
|
|
} |
| 399 |
|
|
|
| 400 |
|
|
|
| 401 |
|
|
|
| 402 |
|
|
//calculate the value of object function |
| 403 |
|
|
void OOPSEMinimizer::calcF(){ |
| 404 |
|
|
calcEnergyGradient(curX, curG, curF, egEvalStatus); |
| 405 |
|
|
} |
| 406 |
|
|
|
| 407 |
|
|
void OOPSEMinimizer::calcF(vector<double>& x, double&f, int& status){ |
| 408 |
|
|
vector<double> tempG; |
| 409 |
|
|
tempG.resize(x.size()); |
| 410 |
|
|
|
| 411 |
|
|
calcEnergyGradient(x, tempG, f, status); |
| 412 |
|
|
} |
| 413 |
|
|
|
| 414 |
|
|
//calculate the gradient |
| 415 |
|
|
void OOPSEMinimizer::calcG(){ |
| 416 |
|
|
calcEnergyGradient(curX, curG, curF, egEvalStatus); |
| 417 |
|
|
} |
| 418 |
|
|
|
| 419 |
|
|
void OOPSEMinimizer::calcG(vector<double>& x, vector<double>& g, double& f, int& status){ |
| 420 |
|
|
calcEnergyGradient(x, g, f, status); |
| 421 |
|
|
} |
| 422 |
|
|
|
| 423 |
|
|
void OOPSEMinimizer::calcDim(){ |
| 424 |
|
|
DirectionalAtom* dAtom; |
| 425 |
|
|
|
| 426 |
|
|
ndim = 0; |
| 427 |
|
|
|
| 428 |
|
|
for(int i = 0; i < integrableObjects.size(); i++){ |
| 429 |
|
|
ndim += 3; |
| 430 |
|
|
if (integrableObjects[i]->isDirectional()) |
| 431 |
|
|
ndim += 3; |
| 432 |
|
|
} |
| 433 |
|
|
} |
| 434 |
|
|
|
| 435 |
|
|
void OOPSEMinimizer::setX(vector < double > & x){ |
| 436 |
|
|
|
| 437 |
|
|
if (x.size() != ndim && bVerbose){ |
| 438 |
|
|
//sprintf(painCave.errMsg, |
| 439 |
|
|
// "OOPSEMinimizer Error: dimesion of x and curX does not match\n"); |
| 440 |
|
|
// painCave.isFatal = 1; |
| 441 |
|
|
// simError(); |
| 442 |
|
|
} |
| 443 |
|
|
|
| 444 |
|
|
curX = x; |
| 445 |
|
|
} |
| 446 |
|
|
|
| 447 |
|
|
void OOPSEMinimizer::setG(vector < double > & g){ |
| 448 |
|
|
|
| 449 |
|
|
if (g.size() != ndim && bVerbose){ |
| 450 |
|
|
//sprintf(painCave.errMsg, |
| 451 |
|
|
// "OOPSEMinimizer Error: dimesion of g and curG does not match\n"); |
| 452 |
|
|
// painCave.isFatal = 1; |
| 453 |
|
|
//simError(); |
| 454 |
|
|
} |
| 455 |
|
|
|
| 456 |
|
|
curG = g; |
| 457 |
|
|
} |
| 458 |
|
|
|
| 459 |
|
|
void OOPSEMinimizer::writeOut(vector<double>& x, double iter){ |
| 460 |
|
|
|
| 461 |
|
|
setX(x); |
| 462 |
|
|
|
| 463 |
|
|
calcG(); |
| 464 |
|
|
|
| 465 |
|
|
dumpOut->writeDump(iter); |
| 466 |
|
|
statOut->writeStat(iter); |
| 467 |
|
|
} |
| 468 |
|
|
|
| 469 |
|
|
|
| 470 |
|
|
void OOPSEMinimizer::printMinimizerInfo(){ |
| 471 |
|
|
cout << "--------------------------------------------------------------------" << endl; |
| 472 |
|
|
cout << minimizerName << endl; |
| 473 |
|
|
cout << "minimization parameter set" << endl; |
| 474 |
|
|
cout << "function tolerance = " << paramSet->getFTol() << endl; |
| 475 |
|
|
cout << "gradient tolerance = " << paramSet->getGTol() << endl; |
| 476 |
|
|
cout << "step tolerance = "<< paramSet->getFTol() << endl; |
| 477 |
|
|
cout << "absolute gradient tolerance = " << endl; |
| 478 |
|
|
cout << "max iteration = " << paramSet->getMaxIteration() << endl; |
| 479 |
|
|
cout << "max line search iteration = " << paramSet->getLineSearchMaxIteration() <<endl; |
| 480 |
|
|
cout << "shake algorithm = " << bShake << endl; |
| 481 |
|
|
cout << "--------------------------------------------------------------------" << endl; |
| 482 |
|
|
|
| 483 |
|
|
} |
| 484 |
|
|
|
| 485 |
|
|
/** |
| 486 |
|
|
* In thoery, we need to find the minimum along the search direction |
| 487 |
|
|
* However, function evaluation is too expensive. |
| 488 |
|
|
* At the very begining of the problem, we check the search direction and make sure |
| 489 |
|
|
* it is a descent direction |
| 490 |
|
|
* we will compare the energy of two end points, |
| 491 |
|
|
* if the right end point has lower energy, we just take it |
| 492 |
|
|
* |
| 493 |
|
|
* |
| 494 |
|
|
* |
| 495 |
|
|
*/ |
| 496 |
|
|
|
| 497 |
|
|
int OOPSEMinimizer::doLineSearch(vector<double>& direction, double stepSize){ |
| 498 |
|
|
vector<double> xa; |
| 499 |
|
|
vector<double> xb; |
| 500 |
|
|
vector<double> xc; |
| 501 |
|
|
vector<double> ga; |
| 502 |
|
|
vector<double> gb; |
| 503 |
|
|
vector<double> gc; |
| 504 |
|
|
double fa; |
| 505 |
|
|
double fb; |
| 506 |
|
|
double fc; |
| 507 |
|
|
double a; |
| 508 |
|
|
double b; |
| 509 |
|
|
double c; |
| 510 |
|
|
int status; |
| 511 |
|
|
double initSlope; |
| 512 |
|
|
double slopeA; |
| 513 |
|
|
double slopeB; |
| 514 |
|
|
double slopeC; |
| 515 |
|
|
bool foundLower; |
| 516 |
|
|
int iter; |
| 517 |
|
|
int maxLSIter; |
| 518 |
|
|
double mu; |
| 519 |
|
|
double eta; |
| 520 |
|
|
double ftol; |
| 521 |
|
|
double lsTol; |
| 522 |
|
|
|
| 523 |
|
|
xa.resize(ndim); |
| 524 |
|
|
xb.resize(ndim); |
| 525 |
|
|
xc.resize(ndim); |
| 526 |
|
|
|
| 527 |
|
|
ga.resize(ndim); |
| 528 |
|
|
gb.resize(ndim); |
| 529 |
|
|
gc.resize(ndim); |
| 530 |
|
|
|
| 531 |
|
|
a = 0.0; |
| 532 |
|
|
fa = curF; |
| 533 |
|
|
xa = curX; |
| 534 |
|
|
ga = curG; |
| 535 |
|
|
c = a + stepSize; |
| 536 |
|
|
ftol = paramSet->getFTol(); |
| 537 |
|
|
lsTol = paramSet->getLineSearchTol(); |
| 538 |
|
|
|
| 539 |
|
|
//calculate the derivative at a = 0 |
| 540 |
|
|
slopeA = 0; |
| 541 |
|
|
for (size_t i = 0; i < ndim; i++) |
| 542 |
|
|
slopeA += curG[i]*direction[i]; |
| 543 |
|
|
|
| 544 |
|
|
initSlope = slopeA; |
| 545 |
|
|
|
| 546 |
|
|
// if going uphill, use negative gradient as searching direction |
| 547 |
|
|
if (slopeA > 0) { |
| 548 |
|
|
|
| 549 |
|
|
if (bVerbose){ |
| 550 |
|
|
cout << "LineSearch Warning: initial searching direction is not a descent searching direction, " |
| 551 |
|
|
<< " use negative gradient instead. Therefore, finding a smaller vaule of function " |
| 552 |
|
|
<< " is guaranteed" |
| 553 |
|
|
<< endl; |
| 554 |
|
|
} |
| 555 |
|
|
|
| 556 |
|
|
for (size_t i = 0; i < ndim; i++) |
| 557 |
|
|
direction[i] = -curG[i]; |
| 558 |
|
|
|
| 559 |
|
|
for (size_t i = 0; i < ndim; i++) |
| 560 |
|
|
slopeA += curG[i]*direction[i]; |
| 561 |
|
|
|
| 562 |
|
|
initSlope = slopeA; |
| 563 |
|
|
} |
| 564 |
|
|
|
| 565 |
|
|
// Take a trial step |
| 566 |
|
|
for(size_t i = 0; i < ndim; i++) |
| 567 |
|
|
xc[i] = curX[i] + direction[i] * c; |
| 568 |
|
|
|
| 569 |
|
|
calcG(xc, gc, fc, status); |
| 570 |
|
|
|
| 571 |
|
|
if (status < 0){ |
| 572 |
|
|
if (bVerbose) |
| 573 |
|
|
cerr << "Function Evaluation Error" << endl; |
| 574 |
|
|
} |
| 575 |
|
|
|
| 576 |
|
|
//calculate the derivative at c |
| 577 |
|
|
slopeC = 0; |
| 578 |
|
|
for (size_t i = 0; i < ndim; i++) |
| 579 |
|
|
slopeC += gc[i]*direction[i]; |
| 580 |
|
|
|
| 581 |
|
|
// found a lower point |
| 582 |
|
|
if (fc < fa) { |
| 583 |
|
|
curX = xc; |
| 584 |
|
|
curG = gc; |
| 585 |
|
|
curF = fc; |
| 586 |
|
|
return LS_SUCCEED; |
| 587 |
|
|
} |
| 588 |
|
|
else { |
| 589 |
|
|
|
| 590 |
|
|
if (slopeC > 0) |
| 591 |
|
|
stepSize *= 0.618034; |
| 592 |
|
|
} |
| 593 |
|
|
|
| 594 |
|
|
maxLSIter = paramSet->getLineSearchMaxIteration(); |
| 595 |
|
|
|
| 596 |
|
|
iter = 0; |
| 597 |
|
|
|
| 598 |
|
|
do { |
| 599 |
|
|
// Select a new trial point. |
| 600 |
|
|
// If the derivatives at points a & c have different sign we use cubic interpolate |
| 601 |
|
|
//if (slopeC > 0){ |
| 602 |
|
|
eta = 3 *(fa -fc) /(c - a) + slopeA + slopeC; |
| 603 |
|
|
mu = sqrt(eta * eta - slopeA * slopeC); |
| 604 |
|
|
b = a + (c - a) * (1 - (slopeC + mu - eta) /(slopeC - slopeA + 2 * mu)); |
| 605 |
|
|
|
| 606 |
|
|
if (b < lsTol){ |
| 607 |
|
|
if (bVerbose) |
| 608 |
|
|
cout << "stepSize is less than line search tolerance" << endl; |
| 609 |
|
|
break; |
| 610 |
|
|
} |
| 611 |
|
|
//} |
| 612 |
|
|
|
| 613 |
|
|
// Take a trial step to this new point - new coords in xb |
| 614 |
|
|
for(size_t i = 0; i < ndim; i++) |
| 615 |
|
|
xb[i] = curX[i] + direction[i] * b; |
| 616 |
|
|
|
| 617 |
|
|
//function evaluation |
| 618 |
|
|
calcG(xb, gb, fb, status); |
| 619 |
|
|
|
| 620 |
|
|
if (status < 0){ |
| 621 |
|
|
if (bVerbose) |
| 622 |
|
|
cerr << "Function Evaluation Error" << endl; |
| 623 |
|
|
} |
| 624 |
|
|
|
| 625 |
|
|
//calculate the derivative at c |
| 626 |
|
|
slopeB = 0; |
| 627 |
|
|
for (size_t i = 0; i < ndim; i++) |
| 628 |
|
|
slopeB += gb[i]*direction[i]; |
| 629 |
|
|
|
| 630 |
|
|
//Amijo Rule to stop the line search |
| 631 |
|
|
if (fb <= curF + initSlope * ftol * b) { |
| 632 |
|
|
curF = fb; |
| 633 |
|
|
curX = xb; |
| 634 |
|
|
curG = gb; |
| 635 |
|
|
return LS_SUCCEED; |
| 636 |
|
|
} |
| 637 |
|
|
|
| 638 |
|
|
if (slopeB <0 && fb < fa) { |
| 639 |
|
|
//replace a by b |
| 640 |
|
|
fa = fb; |
| 641 |
|
|
a = b; |
| 642 |
|
|
slopeA = slopeB; |
| 643 |
|
|
|
| 644 |
|
|
// swap coord a/b |
| 645 |
|
|
std::swap(xa, xb); |
| 646 |
|
|
std::swap(ga, gb); |
| 647 |
|
|
} |
| 648 |
|
|
else { |
| 649 |
|
|
//replace c by b |
| 650 |
|
|
fc = fb; |
| 651 |
|
|
c = b; |
| 652 |
|
|
slopeC = slopeB; |
| 653 |
|
|
|
| 654 |
|
|
// swap coord b/c |
| 655 |
|
|
std::swap(gb, gc); |
| 656 |
|
|
std::swap(xb, xc); |
| 657 |
|
|
} |
| 658 |
|
|
|
| 659 |
|
|
|
| 660 |
|
|
iter++; |
| 661 |
|
|
} while((fb > fa || fb > fc) && (iter < maxLSIter)); |
| 662 |
|
|
|
| 663 |
|
|
if(fb < curF || iter >= maxLSIter) { |
| 664 |
|
|
//could not find a lower value, we might just go uphill. |
| 665 |
|
|
return LS_ERROR; |
| 666 |
|
|
} |
| 667 |
|
|
|
| 668 |
|
|
//select the end point |
| 669 |
|
|
|
| 670 |
|
|
if (fa <= fc) { |
| 671 |
|
|
curX = xa; |
| 672 |
|
|
curG = ga; |
| 673 |
|
|
curF = fa; |
| 674 |
|
|
} |
| 675 |
|
|
else { |
| 676 |
|
|
curX = xc; |
| 677 |
|
|
curG = gc; |
| 678 |
|
|
curF = fc; |
| 679 |
|
|
} |
| 680 |
|
|
|
| 681 |
|
|
return LS_SUCCEED; |
| 682 |
|
|
|
| 683 |
|
|
} |
| 684 |
|
|
|
| 685 |
|
|
void OOPSEMinimizer::minimize(){ |
| 686 |
|
|
|
| 687 |
|
|
int convgStatus; |
| 688 |
|
|
int stepStatus; |
| 689 |
|
|
int maxIter; |
| 690 |
|
|
int writeFrq; |
| 691 |
|
|
int nextWriteIter; |
| 692 |
|
|
|
| 693 |
|
|
if (bVerbose) |
| 694 |
|
|
printMinimizerInfo(); |
| 695 |
|
|
|
| 696 |
|
|
dumpOut = new DumpWriter(info); |
| 697 |
|
|
statOut = new StatWriter(info); |
| 698 |
|
|
|
| 699 |
|
|
init(); |
| 700 |
|
|
|
| 701 |
|
|
writeFrq = paramSet->getWriteFrq(); |
| 702 |
|
|
nextWriteIter = writeFrq; |
| 703 |
|
|
|
| 704 |
|
|
maxIter = paramSet->getMaxIteration(); |
| 705 |
|
|
|
| 706 |
|
|
for (curIter = 1; curIter <= maxIter; curIter++){ |
| 707 |
|
|
|
| 708 |
|
|
stepStatus = step(); |
| 709 |
|
|
|
| 710 |
|
|
if (nConstrained && bShake) |
| 711 |
|
|
preMove(); |
| 712 |
|
|
|
| 713 |
|
|
if (stepStatus < 0){ |
| 714 |
|
|
saveResult(); |
| 715 |
|
|
minStatus = MIN_LSERROR; |
| 716 |
|
|
cerr << "OOPSEMinimizer Error: line search error, please try a small stepsize" << endl; |
| 717 |
|
|
return; |
| 718 |
|
|
} |
| 719 |
|
|
|
| 720 |
|
|
if (curIter == nextWriteIter){ |
| 721 |
|
|
nextWriteIter += writeFrq; |
| 722 |
|
|
writeOut(curX, curIter); |
| 723 |
|
|
} |
| 724 |
|
|
|
| 725 |
|
|
convgStatus = checkConvg(); |
| 726 |
|
|
|
| 727 |
|
|
if (convgStatus > 0){ |
| 728 |
|
|
saveResult(); |
| 729 |
|
|
minStatus = MIN_CONVERGE; |
| 730 |
|
|
return; |
| 731 |
|
|
} |
| 732 |
|
|
|
| 733 |
|
|
prepareStep(); |
| 734 |
|
|
|
| 735 |
|
|
} |
| 736 |
|
|
|
| 737 |
|
|
|
| 738 |
|
|
if (bVerbose) { |
| 739 |
|
|
cout << "OOPSEMinimizer Warning: " |
| 740 |
|
|
<< minimizerName << " algorithm did not converge within " |
| 741 |
|
|
<< maxIter << " iteration" << endl; |
| 742 |
|
|
} |
| 743 |
|
|
minStatus = MIN_MAXITER; |
| 744 |
|
|
saveResult(); |
| 745 |
|
|
|
| 746 |
|
|
} |
