/* -------------------------------------------------------------------------- * * OpenMM * * -------------------------------------------------------------------------- * * This is part of the OpenMM molecular simulation toolkit originating from * * Simbios, the NIH National Center for Physics-Based Simulation of * * Biological Structures at Stanford, funded under the NIH Roadmap for * * Medical Research, grant U54 GM072970. See https://simtk.org. * * * * Portions copyright (c) 2010-2016 Stanford University and the Authors. * * Authors: Peter Eastman * * Contributors: * * * * Permission is hereby granted, free of charge, to any person obtaining a * * copy of this software and associated documentation files (the "Software"), * * to deal in the Software without restriction, including without limitation * * the rights to use, copy, modify, merge, publish, distribute, sublicense, * * and/or sell copies of the Software, and to permit persons to whom the * * Software is furnished to do so, subject to the following conditions: * * * * The above copyright notice and this permission notice shall be included in * * all copies or substantial portions of the Software. * * * * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR * * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, * * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL * * THE AUTHORS, CONTRIBUTORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, * * DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR * * OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE * * USE OR OTHER DEALINGS IN THE SOFTWARE. * * -------------------------------------------------------------------------- */ #include "openmm/LocalEnergyMinimizer.h" #include "openmm/OpenMMException.h" #include "lbfgs.h" #include "openmm/Platform.h" #include #include #include #include using namespace OpenMM; using namespace std; struct MinimizerData { Context& context; double k; MinimizerData(Context& context, double k) : context(context), k(k) {} }; static lbfgsfloatval_t evaluate(void *instance, const lbfgsfloatval_t *x, lbfgsfloatval_t *g, const int n, const lbfgsfloatval_t step) { MinimizerData* data = reinterpret_cast(instance); Context& context = data->context; const System& system = context.getSystem(); int numParticles = system.getNumParticles(); // Compute the force and energy for this configuration. vector positions(numParticles); for (int i = 0; i < numParticles; i++) positions[i] = Vec3(x[3*i], x[3*i+1], x[3*i+2]); context.setPositions(positions); context.computeVirtualSites(); State state = context.getState(State::Forces | State::Energy); const vector& forces = state.getForces(); for (int i = 0; i < numParticles; i++) { if (system.getParticleMass(i) == 0) { g[3*i] = 0.0; g[3*i+1] = 0.0; g[3*i+2] = 0.0; } else { g[3*i] = -forces[i][0]; g[3*i+1] = -forces[i][1]; g[3*i+2] = -forces[i][2]; } } double energy = state.getPotentialEnergy(); // Add harmonic forces for any constraints. int numConstraints = system.getNumConstraints(); double k = data->k; for (int i = 0; i < numConstraints; i++) { int particle1, particle2; double distance; system.getConstraintParameters(i, particle1, particle2, distance); Vec3 delta = positions[particle2]-positions[particle1]; double r2 = delta.dot(delta); double r = sqrt(r2); delta *= 1/r; double dr = r-distance; double kdr = k*dr; energy += 0.5*kdr*dr; g[3*particle1] -= kdr*delta[0]; g[3*particle1+1] -= kdr*delta[1]; g[3*particle1+2] -= kdr*delta[2]; g[3*particle2] += kdr*delta[0]; g[3*particle2+1] += kdr*delta[1]; g[3*particle2+2] += kdr*delta[2]; } return energy; } void LocalEnergyMinimizer::minimize(Context& context, double tolerance, int maxIterations) { const System& system = context.getSystem(); int numParticles = system.getNumParticles(); lbfgsfloatval_t *x = lbfgs_malloc(numParticles*3); if (x == NULL) throw OpenMMException("LocalEnergyMinimizer: Failed to allocate memory"); double constraintTol = context.getIntegrator().getConstraintTolerance(); double workingConstraintTol = std::max(1e-4, constraintTol); double k = tolerance/workingConstraintTol; // Initialize the minimizer. lbfgs_parameter_t param; lbfgs_parameter_init(¶m); if (!context.getPlatform().supportsDoublePrecision()) param.xtol = 1e-7; param.max_iterations = maxIterations; param.linesearch = LBFGS_LINESEARCH_BACKTRACKING_STRONG_WOLFE; // Make sure the initial configuration satisfies all constraints. context.applyConstraints(workingConstraintTol); // Record the initial positions and determine a normalization constant for scaling the tolerance. vector initialPos = context.getState(State::Positions).getPositions(); double norm = 0.0; for (int i = 0; i < numParticles; i++) { x[3*i] = initialPos[i][0]; x[3*i+1] = initialPos[i][1]; x[3*i+2] = initialPos[i][2]; norm += initialPos[i].dot(initialPos[i]); } norm /= numParticles; norm = (norm < 1 ? 1 : sqrt(norm)); param.epsilon = tolerance/norm; // Repeatedly minimize, steadily increasing the strength of the springs until all constraints are satisfied. double prevMaxError = 1e10; while (true) { // Perform the minimization. lbfgsfloatval_t fx; MinimizerData data(context, k); lbfgs(numParticles*3, x, &fx, evaluate, NULL, &data, ¶m); // Check whether all constraints are satisfied. vector positions = context.getState(State::Positions).getPositions(); int numConstraints = system.getNumConstraints(); double maxError = 0.0; for (int i = 0; i < numConstraints; i++) { int particle1, particle2; double distance; system.getConstraintParameters(i, particle1, particle2, distance); Vec3 delta = positions[particle2]-positions[particle1]; double r = sqrt(delta.dot(delta)); double error = fabs(r-distance); if (error > maxError) maxError = error; } if (maxError <= workingConstraintTol) break; // All constraints are satisfied. context.setPositions(initialPos); if (maxError >= prevMaxError) break; // Further tightening the springs doesn't seem to be helping, so just give up. prevMaxError = maxError; k *= 10; if (maxError > 100*workingConstraintTol) { // We've gotten far enough from a valid state that we might have trouble getting // back, so reset to the original positions. for (int i = 0; i < numParticles; i++) { x[3*i] = initialPos[i][0]; x[3*i+1] = initialPos[i][1]; x[3*i+2] = initialPos[i][2]; } } } lbfgs_free(x); // If necessary, do a final constraint projection to make sure they are satisfied // to the full precision requested by the user. if (constraintTol < workingConstraintTol) context.applyConstraints(workingConstraintTol); }