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- removed the dependency on Trajectory from ROMol and ForceField

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This commit is contained in:
Paolo Tosco
2016-05-11 19:37:09 +01:00
parent 8b5176f8c9
commit 2b3a818f84
18 changed files with 716 additions and 664 deletions
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36
Code/Numerics/Optimizer/BFGSOpt.h
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@@ -9,11 +9,10 @@
//
#include <math.h>
#include <RDGeneral/Invariant.h>
#include <Geometry/Trajectory.h>
#include <GraphMol/Trajectory/Snapshot.h>
#include <cstring>
#include <vector>
#include <algorithm>
#include <boost/shared_array.hpp>
namespace BFGSOpt {
const double FUNCTOL =
@@ -169,12 +168,13 @@ void linearSearch(unsigned int dim, double *oldPt, double oldVal, double *grad,
\param gradFunc calculates the gradient of func
\param funcTol tolerance for changes in the function value for convergence.
\param maxIts maximum number of iterations allowed
\param trajEverySteps a snapshot of the minimization trajectory
\param snapshotFreq a snapshot of the minimization trajectory
will be stored after as many steps as indicated
through this parameter; defaults to 0 (no
trajectory stored)
\param traj pointer to the Trajectory object that will receive the trajectory
every trajEverySteps steps; defaults to NULL (no trajectory stored)
snapshots stored)
\param snapshotVect pointer to a std::vector<Snapshot> object that will receive
the coordinates and energies every snapshotFreq steps;
defaults to NULL (no snapshots stored)
\return a flag indicating success (or type of failure). Possible values are:
- 0: success
@@ -183,8 +183,8 @@ void linearSearch(unsigned int dim, double *oldPt, double oldVal, double *grad,
template <typename EnergyFunctor, typename GradientFunctor>
int minimize(unsigned int dim, double *pos, double gradTol,
unsigned int &numIters, double &funcVal, EnergyFunctor func,
GradientFunctor gradFunc, unsigned int trajEverySteps,
RDGeom::Trajectory *traj, double funcTol = TOLX,
GradientFunctor gradFunc, unsigned int snapshotFreq,
SnapshotVect *snapshotVect, double funcTol = TOLX,
unsigned int maxIts = MAXITS) {
RDUNUSED_PARAM(funcTol);
PRECONDITION(pos, "bad input array");
@@ -202,7 +202,7 @@ int minimize(unsigned int dim, double *pos, double gradTol,
newPos = new double[dim];
xi = new double[dim];
invHessian = new double[dim * dim];
trajEverySteps = std::min(trajEverySteps, maxIts);
snapshotFreq = std::min(snapshotFreq, maxIts);
// evaluate the function and gradient in our current position:
fp = func(pos);
@@ -245,9 +245,9 @@ int minimize(unsigned int dim, double *pos, double gradTol,
// std::cerr<<" iter: "<<iter<<" "<<fp<<" "<<test<<"
// "<<TOLX<<std::endl;
if (test < TOLX) {
if (traj && trajEverySteps) {
RDGeom::Snapshot s(boost::shared_array<double>(newPos), fp);
traj->addSnapshot(s);
if (snapshotVect && snapshotFreq) {
RDKit::Snapshot s(boost::shared_array<double>(newPos), fp);
snapshotVect->push_back(s);
newPos = NULL;
}
CLEANUP();
@@ -269,9 +269,9 @@ int minimize(unsigned int dim, double *pos, double gradTol,
// std::cerr<<" "<<gradScale<<" "<<test<<"
// "<<gradTol<<std::endl;
if (test < gradTol) {
if (traj && trajEverySteps) {
RDGeom::Snapshot s(boost::shared_array<double>(newPos), fp);
traj->addSnapshot(s);
if (snapshotVect && snapshotFreq) {
RDKit::Snapshot s(boost::shared_array<double>(newPos), fp);
snapshotVect->push_back(s);
newPos = NULL;
}
CLEANUP();
@@ -348,9 +348,9 @@ int minimize(unsigned int dim, double *pos, double gradTol,
}
#endif
}
if (traj && trajEverySteps && !(iter % trajEverySteps)) {
RDGeom::Snapshot s(boost::shared_array<double>(newPos), fp);
traj->addSnapshot(s);
if (snapshotVect && snapshotFreq && !(iter % snapshotFreq)) {
RDKit::Snapshot s(boost::shared_array<double>(newPos), fp);
snapshotVect->push_back(s);
newPos = new double[dim];
}
}