forked from lijiext/lammps
441 lines
13 KiB
C++
441 lines
13 KiB
C++
// -*- c++ -*-
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#include <stdio.h>
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#include <stdlib.h>
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#include <math.h>
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#include "colvarmodule.h"
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#include "colvarbias_alb.h"
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#include "colvarbias.h"
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#ifdef _MSC_VER
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#if _MSC_VER <= 1700
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#define copysign(A,B) _copysign(A,B)
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double fmax(double A, double B) { return ( A > B ? A : B ); }
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double fmin(double A, double B) { return ( A < B ? A : B ); }
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#endif
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#endif
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/* Note about nomenclature. Force constant is called a coupling
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* constant here to emphasize its changing in the code. Outwards,
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* everything is called a force constant to keep it consistent with
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* the rest of colvars.
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*
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*/
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colvarbias_alb::colvarbias_alb(std::string const &conf, char const *key) :
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colvarbias(conf, key), update_calls(0), b_equilibration(true) {
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size_t i;
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// get the initial restraint centers
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colvar_centers.resize(colvars.size());
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means.resize(colvars.size());
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ssd.resize(colvars.size()); //sum of squares of differences from mean
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//setup force vectors
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max_coupling_range.resize(colvars.size());
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max_coupling_rate.resize(colvars.size());
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coupling_accum.resize(colvars.size());
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set_coupling.resize(colvars.size());
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current_coupling.resize(colvars.size());
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coupling_rate.resize(colvars.size());
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enable(f_cvb_apply_force);
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for (i = 0; i < colvars.size(); i++) {
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colvar_centers[i].type(colvars[i]->value());
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//zero moments
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means[i] = ssd[i] = 0;
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//zero force some of the force vectors that aren't initialized
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coupling_accum[i] = current_coupling[i] = 0;
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}
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if (get_keyval(conf, "centers", colvar_centers, colvar_centers)) {
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for (i = 0; i < colvars.size(); i++) {
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colvar_centers[i].apply_constraints();
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}
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} else {
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colvar_centers.clear();
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cvm::fatal_error("Error: must define the initial centers of adaptive linear bias .\n");
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}
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if (colvar_centers.size() != colvars.size())
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cvm::fatal_error("Error: number of centers does not match "
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"that of collective variables.\n");
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if (!get_keyval(conf, "UpdateFrequency", update_freq, 0))
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cvm::fatal_error("Error: must set updateFrequency for adaptive linear bias.\n");
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//we split the time between updating and equilibrating
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update_freq /= 2;
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if (update_freq == 0)
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cvm::fatal_error("Error: must set updateFrequency to greater than 2.\n");
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get_keyval(conf, "outputCenters", b_output_centers, false);
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get_keyval(conf, "outputGradient", b_output_grad, false);
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get_keyval(conf, "outputCoupling", b_output_coupling, true);
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get_keyval(conf, "hardForceRange", b_hard_coupling_range, true);
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//initial guess
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if (!get_keyval(conf, "forceConstant", set_coupling, set_coupling))
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for (i =0 ; i < colvars.size(); i++)
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set_coupling[i] = 0.;
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//how we're going to increase to that point
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for (i = 0; i < colvars.size(); i++)
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coupling_rate[i] = (set_coupling[i] - current_coupling[i]) / update_freq;
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if (!get_keyval(conf, "forceRange", max_coupling_range, max_coupling_range)) {
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//set to default
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for (i = 0; i < colvars.size(); i++) {
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if (cvm::temperature() > 0)
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max_coupling_range[i] = 3 * cvm::temperature() * cvm::boltzmann();
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else
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max_coupling_range[i] = 3 * cvm::boltzmann();
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}
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}
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if (!get_keyval(conf, "rateMax", max_coupling_rate, max_coupling_rate)) {
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//set to default
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for (i = 0; i < colvars.size(); i++) {
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max_coupling_rate[i] = max_coupling_range[i] / (10 * update_freq);
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}
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}
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if (cvm::debug())
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cvm::log(" bias.\n");
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}
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colvarbias_alb::~colvarbias_alb() {
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if (cvm::n_rest_biases > 0)
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cvm::n_rest_biases -= 1;
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}
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int colvarbias_alb::update() {
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bias_energy = 0.0;
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update_calls++;
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if (cvm::debug())
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cvm::log("Updating the adaptive linear bias \""+this->name+"\".\n");
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//log the moments of the CVs
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// Force and energy calculation
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bool finished_equil_flag = 1;
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cvm::real delta;
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for (size_t i = 0; i < colvars.size(); i++) {
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colvar_forces[i] = -1.0 * restraint_force(restraint_convert_k(current_coupling[i], colvars[i]->width),
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colvars[i],
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colvar_centers[i]);
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bias_energy += restraint_potential(restraint_convert_k(current_coupling[i], colvars[i]->width),
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colvars[i],
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colvar_centers[i]);
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if (!b_equilibration) {
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//Welford, West, and Hanso online variance method
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delta = static_cast<cvm::real>(colvars[i]->value()) - means[i];
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means[i] += delta / update_calls;
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ssd[i] += delta * (static_cast<cvm::real>(colvars[i]->value()) - means[i]);
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} else {
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//check if we've reached the setpoint
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if (coupling_rate[i] == 0 || pow(current_coupling[i] - set_coupling[i],2) < pow(coupling_rate[i],2)) {
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finished_equil_flag &= 1; //we continue equilibrating as long as we haven't reached all the set points
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}
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else {
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current_coupling[i] += coupling_rate[i];
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finished_equil_flag = 0;
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}
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//update max_coupling_range
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if (!b_hard_coupling_range && fabs(current_coupling[i]) > max_coupling_range[i]) {
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std::ostringstream logStream;
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logStream << "Coupling constant for "
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<< colvars[i]->name
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<< " has exceeded coupling range of "
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<< max_coupling_range[i]
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<< ".\n";
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max_coupling_range[i] *= 1.25;
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logStream << "Expanding coupling range to " << max_coupling_range[i] << ".\n";
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cvm::log(logStream.str());
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}
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}
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}
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if (b_equilibration && finished_equil_flag) {
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b_equilibration = false;
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update_calls = 0;
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}
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//now we update coupling constant, if necessary
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if (!b_equilibration && update_calls == update_freq) {
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//use estimated variance to take a step
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cvm::real step_size = 0;
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cvm::real temp;
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//reset means and sum of squares of differences
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for (size_t i = 0; i < colvars.size(); i++) {
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temp = 2. * (means[i] / (static_cast<cvm::real> (colvar_centers[i])) - 1) * ssd[i] / (update_calls - 1);
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if (cvm::temperature() > 0)
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step_size = temp / (cvm::temperature() * cvm::boltzmann());
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else
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step_size = temp / cvm::boltzmann();
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means[i] = 0;
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ssd[i] = 0;
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//stochastic if we do that update or not
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if (colvars.size() == 1 || rand() < RAND_MAX / ((int) colvars.size())) {
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coupling_accum[i] += step_size * step_size;
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current_coupling[i] = set_coupling[i];
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set_coupling[i] += max_coupling_range[i] / sqrt(coupling_accum[i]) * step_size;
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coupling_rate[i] = (set_coupling[i] - current_coupling[i]) / update_freq;
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//set to the minimum rate and then put the sign back on it
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coupling_rate[i] = copysign(fmin(fabs(coupling_rate[i]), max_coupling_rate[i]), coupling_rate[i]);
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} else {
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coupling_rate[i] = 0;
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}
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}
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update_calls = 0;
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b_equilibration = true;
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}
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return COLVARS_OK;
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}
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std::istream & colvarbias_alb::read_restart(std::istream &is)
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{
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size_t const start_pos = is.tellg();
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cvm::log("Restarting adaptive linear bias \""+
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this->name+"\".\n");
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std::string key, brace, conf;
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if ( !(is >> key) || !(key == "ALB") ||
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!(is >> brace) || !(brace == "{") ||
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!(is >> colvarparse::read_block("configuration", conf)) ) {
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cvm::log("Error: in reading restart configuration for restraint bias \""+
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this->name+"\" at position "+
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cvm::to_str(is.tellg())+" in stream.\n");
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is.clear();
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is.seekg(start_pos, std::ios::beg);
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is.setstate(std::ios::failbit);
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return is;
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}
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std::string name = "";
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if ( (colvarparse::get_keyval(conf, "name", name, std::string(""), colvarparse::parse_silent)) &&
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(name != this->name) )
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cvm::fatal_error("Error: in the restart file, the "
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"\"ALB\" block has a wrong name\n");
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if (name.size() == 0) {
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cvm::fatal_error("Error: \"ALB\" block in the restart file "
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"has no identifiers.\n");
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}
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if (!get_keyval(conf, "setCoupling", set_coupling))
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cvm::fatal_error("Error: current setCoupling is missing from the restart.\n");
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if (!get_keyval(conf, "currentCoupling", current_coupling))
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cvm::fatal_error("Error: current setCoupling is missing from the restart.\n");
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if (!get_keyval(conf, "maxCouplingRange", max_coupling_range))
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cvm::fatal_error("Error: maxCouplingRange is missing from the restart.\n");
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if (!get_keyval(conf, "couplingRate", coupling_rate))
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cvm::fatal_error("Error: current setCoupling is missing from the restart.\n");
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if (!get_keyval(conf, "couplingAccum", coupling_accum))
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cvm::fatal_error("Error: couplingAccum is missing from the restart.\n");
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if (!get_keyval(conf, "mean", means))
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cvm::fatal_error("Error: current mean is missing from the restart.\n");
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if (!get_keyval(conf, "ssd", ssd))
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cvm::fatal_error("Error: current ssd is missing from the restart.\n");
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if (!get_keyval(conf, "updateCalls", update_calls))
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cvm::fatal_error("Error: current updateCalls is missing from the restart.\n");
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if (!get_keyval(conf, "b_equilibration", b_equilibration))
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cvm::fatal_error("Error: current updateCalls is missing from the restart.\n");
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is >> brace;
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if (brace != "}") {
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cvm::fatal_error("Error: corrupt restart information for adaptive linear bias \""+
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this->name+"\": no matching brace at position "+
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cvm::to_str(is.tellg())+" in the restart file.\n");
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is.setstate(std::ios::failbit);
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}
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return is;
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}
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std::ostream & colvarbias_alb::write_restart(std::ostream &os)
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{
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os << "ALB {\n"
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<< " configuration {\n"
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<< " name " << this->name << "\n";
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os << " setCoupling ";
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size_t i;
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for (i = 0; i < colvars.size(); i++) {
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os << std::setprecision(cvm::en_prec)
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<< std::setw(cvm::en_width) << set_coupling[i] << "\n";
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}
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os << " currentCoupling ";
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for (i = 0; i < colvars.size(); i++) {
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os << std::setprecision(cvm::en_prec)
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<< std::setw(cvm::en_width) << current_coupling[i] << "\n";
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}
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os << " maxCouplingRange ";
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for (i = 0; i < colvars.size(); i++) {
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os << std::setprecision(cvm::en_prec)
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<< std::setw(cvm::en_width) << max_coupling_range[i] << "\n";
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}
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os << " couplingRate ";
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for (i = 0; i < colvars.size(); i++) {
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os << std::setprecision(cvm::en_prec)
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<< std::setw(cvm::en_width) << coupling_rate[i] << "\n";
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}
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os << " couplingAccum ";
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for (i = 0; i < colvars.size(); i++) {
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os << std::setprecision(cvm::en_prec)
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<< std::setw(cvm::en_width) << coupling_accum[i] << "\n";
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}
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os << " mean ";
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for (i = 0; i < colvars.size(); i++) {
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os << std::setprecision(cvm::en_prec)
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<< std::setw(cvm::en_width) << means[i] << "\n";
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}
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os << " ssd ";
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for (i = 0; i < colvars.size(); i++) {
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os << std::setprecision(cvm::en_prec)
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<< std::setw(cvm::en_width) << ssd[i] << "\n";
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}
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os << " updateCalls " << update_calls << "\n";
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if (b_equilibration)
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os << " b_equilibration yes\n";
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else
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os << " b_equilibration no\n";
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os << " }\n"
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<< "}\n\n";
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return os;
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}
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std::ostream & colvarbias_alb::write_traj_label(std::ostream &os)
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{
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os << " ";
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if (b_output_energy)
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os << " E_"
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<< cvm::wrap_string(this->name, cvm::en_width-2);
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if (b_output_coupling)
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for (size_t i = 0; i < current_coupling.size(); i++) {
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os << " ForceConst_" << i
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<<std::setw(cvm::en_width - 6 - (i / 10 + 1))
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<< "";
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}
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if (b_output_grad)
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for (size_t i = 0; i < means.size(); i++) {
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os << "Grad_"
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<< cvm::wrap_string(colvars[i]->name, cvm::cv_width - 4);
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}
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if (b_output_centers)
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for (size_t i = 0; i < colvars.size(); i++) {
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size_t const this_cv_width = (colvars[i]->value()).output_width(cvm::cv_width);
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os << " x0_"
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<< cvm::wrap_string(colvars[i]->name, this_cv_width-3);
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}
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return os;
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}
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std::ostream & colvarbias_alb::write_traj(std::ostream &os)
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{
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os << " ";
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if (b_output_energy)
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os << " "
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<< std::setprecision(cvm::en_prec) << std::setw(cvm::en_width)
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<< bias_energy;
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if (b_output_coupling)
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for (size_t i = 0; i < current_coupling.size(); i++) {
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os << " "
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<< std::setprecision(cvm::en_prec) << std::setw(cvm::en_width)
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<< current_coupling[i];
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}
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if (b_output_centers)
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for (size_t i = 0; i < colvars.size(); i++) {
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os << " "
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<< std::setprecision(cvm::cv_prec) << std::setw(cvm::cv_width)
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<< colvar_centers[i];
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}
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if (b_output_grad)
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for (size_t i = 0; i < means.size(); i++) {
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os << " "
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<< std::setprecision(cvm::cv_prec) << std::setw(cvm::cv_width)
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<< -2. * (means[i] / (static_cast<cvm::real> (colvar_centers[i])) - 1) * ssd[i] / (fmax(update_calls,2) - 1);
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}
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return os;
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}
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cvm::real colvarbias_alb::restraint_potential(cvm::real k, const colvar* x, const colvarvalue &xcenter) const
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{
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return k * (x->value() - xcenter);
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}
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colvarvalue colvarbias_alb::restraint_force(cvm::real k, const colvar* x, const colvarvalue &xcenter) const
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{
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return k;
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}
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cvm::real colvarbias_alb::restraint_convert_k(cvm::real k, cvm::real dist_measure) const
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{
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return k / dist_measure;
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}
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