Files
lammps/lib/colvars/colvarbias_alb.cpp
Giacomo Fiorin 7be004512f Update Colvars to version 2020-02-27
This update contains several small new features or usability improvements.
    Descriptions and authorship information can be accessed from the pull
    requests listed below.

    Allow setting sigma parameter directly for metadynamics
    https://github.com/Colvars/colvars/pull/325

    Remove default values for lowerWall and upperWall legacy keywords
    https://github.com/Colvars/colvars/pull/324

    biasActualColvar option to bypass extended-Lagragian for a bias
    https://github.com/Colvars/colvars/pull/321

    Flexible restart-reading
    https://github.com/Colvars/colvars/pull/320
2020-02-27 19:55:31 -05:00

425 lines
12 KiB
C++

// -*- c++ -*-
// This file is part of the Collective Variables module (Colvars).
// The original version of Colvars and its updates are located at:
// https://github.com/Colvars/colvars
// Please update all Colvars source files before making any changes.
// If you wish to distribute your changes, please submit them to the
// Colvars repository at GitHub.
#include <cstdlib>
#include "colvarmodule.h"
#include "colvarbias.h"
#include "colvarbias_alb.h"
#ifdef _MSC_VER
#if _MSC_VER <= 1700
#define copysign(A,B) _copysign(A,B)
double fmax(double A, double B) { return ( A > B ? A : B ); }
double fmin(double A, double B) { return ( A < B ? A : B ); }
#endif
#endif
/* Note about nomenclature. Force constant is called a coupling
* constant here to emphasize its changing in the code. Outwards,
* everything is called a force constant to keep it consistent with
* the rest of colvars.
*
*/
colvarbias_alb::colvarbias_alb(char const *key)
: colvarbias(key), update_calls(0), b_equilibration(true)
{
}
int colvarbias_alb::init(std::string const &conf)
{
colvarbias::init(conf);
enable(f_cvb_scalar_variables);
size_t i;
// get the initial restraint centers
colvar_centers.resize(num_variables());
means.resize(num_variables());
ssd.resize(num_variables()); //sum of squares of differences from mean
//setup force vectors
max_coupling_range.resize(num_variables());
max_coupling_rate.resize(num_variables());
coupling_accum.resize(num_variables());
set_coupling.resize(num_variables());
current_coupling.resize(num_variables());
coupling_rate.resize(num_variables());
enable(f_cvb_apply_force);
for (i = 0; i < num_variables(); i++) {
colvar_centers[i].type(colvars[i]->value());
//zero moments
means[i] = ssd[i] = 0;
//zero force some of the force vectors that aren't initialized
coupling_accum[i] = current_coupling[i] = 0;
}
if (get_keyval(conf, "centers", colvar_centers, colvar_centers)) {
for (i = 0; i < num_variables(); i++) {
colvar_centers[i].apply_constraints();
}
} else {
colvar_centers.clear();
cvm::fatal_error("Error: must define the initial centers of adaptive linear bias .\n");
}
if (colvar_centers.size() != num_variables())
cvm::fatal_error("Error: number of centers does not match "
"that of collective variables.\n");
if (!get_keyval(conf, "UpdateFrequency", update_freq, 0))
cvm::fatal_error("Error: must set updateFrequency for adaptive linear bias.\n");
//we split the time between updating and equilibrating
update_freq /= 2;
if (update_freq <= 1)
cvm::fatal_error("Error: must set updateFrequency to greater than 2.\n");
enable(f_cvb_history_dependent);
get_keyval(conf, "outputCenters", b_output_centers, false);
get_keyval(conf, "outputGradient", b_output_grad, false);
get_keyval(conf, "outputCoupling", b_output_coupling, true);
get_keyval(conf, "hardForceRange", b_hard_coupling_range, true);
//initial guess
if (!get_keyval(conf, "forceConstant", set_coupling, set_coupling))
for (i =0 ; i < num_variables(); i++)
set_coupling[i] = 0.;
//how we're going to increase to that point
for (i = 0; i < num_variables(); i++)
coupling_rate[i] = (set_coupling[i] - current_coupling[i]) / update_freq;
if (!get_keyval(conf, "forceRange", max_coupling_range, max_coupling_range)) {
//set to default
for (i = 0; i < num_variables(); i++) {
if (cvm::temperature() > 0)
max_coupling_range[i] = 3 * cvm::temperature() * cvm::boltzmann();
else
max_coupling_range[i] = 3 * cvm::boltzmann();
}
}
if (!get_keyval(conf, "rateMax", max_coupling_rate, max_coupling_rate)) {
//set to default
for (i = 0; i < num_variables(); i++) {
max_coupling_rate[i] = max_coupling_range[i] / (10 * update_freq);
}
}
if (cvm::debug())
cvm::log(" bias.\n");
return COLVARS_OK;
}
colvarbias_alb::~colvarbias_alb()
{
}
int colvarbias_alb::update()
{
bias_energy = 0.0;
update_calls++;
if (cvm::debug())
cvm::log("Updating the adaptive linear bias \""+this->name+"\".\n");
//log the moments of the CVs
// Force and energy calculation
bool finished_equil_flag = 1;
cvm::real delta;
for (size_t i = 0; i < num_variables(); i++) {
colvar_forces[i] = -1.0 * restraint_force(restraint_convert_k(current_coupling[i], colvars[i]->width),
colvars[i],
colvar_centers[i]);
bias_energy += restraint_potential(restraint_convert_k(current_coupling[i], colvars[i]->width),
colvars[i],
colvar_centers[i]);
if (!b_equilibration) {
//Welford, West, and Hanso online variance method
delta = static_cast<cvm::real>(colvars[i]->value()) - means[i];
means[i] += delta / update_calls;
ssd[i] += delta * (static_cast<cvm::real>(colvars[i]->value()) - means[i]);
} else {
//check if we've reached the setpoint
cvm::real const coupling_diff = current_coupling[i] - set_coupling[i];
if ((coupling_rate[i] == 0) ||
((coupling_diff*coupling_diff) < (coupling_rate[i]*coupling_rate[i]))) {
finished_equil_flag &= 1; //we continue equilibrating as long as we haven't reached all the set points
}
else {
current_coupling[i] += coupling_rate[i];
finished_equil_flag = 0;
}
//update max_coupling_range
if (!b_hard_coupling_range && fabs(current_coupling[i]) > max_coupling_range[i]) {
std::ostringstream logStream;
logStream << "Coupling constant for "
<< colvars[i]->name
<< " has exceeded coupling range of "
<< max_coupling_range[i]
<< ".\n";
max_coupling_range[i] *= 1.25;
logStream << "Expanding coupling range to " << max_coupling_range[i] << ".\n";
cvm::log(logStream.str());
}
}
}
if (b_equilibration && finished_equil_flag) {
b_equilibration = false;
update_calls = 0;
}
//now we update coupling constant, if necessary
if (!b_equilibration && update_calls == update_freq) {
//use estimated variance to take a step
cvm::real step_size = 0;
cvm::real temp;
//reset means and sum of squares of differences
for (size_t i = 0; i < num_variables(); i++) {
temp = 2. * (means[i] / (static_cast<cvm::real> (colvar_centers[i])) - 1) * ssd[i] / (update_calls - 1);
if (cvm::temperature() > 0)
step_size = temp / (cvm::temperature() * cvm::boltzmann());
else
step_size = temp / cvm::boltzmann();
means[i] = 0;
ssd[i] = 0;
//stochastic if we do that update or not
if (num_variables() == 1 || rand() < RAND_MAX / ((int) num_variables())) {
coupling_accum[i] += step_size * step_size;
current_coupling[i] = set_coupling[i];
set_coupling[i] += max_coupling_range[i] / sqrt(coupling_accum[i]) * step_size;
coupling_rate[i] = (set_coupling[i] - current_coupling[i]) / update_freq;
//set to the minimum rate and then put the sign back on it
coupling_rate[i] = copysign(fmin(fabs(coupling_rate[i]), max_coupling_rate[i]), coupling_rate[i]);
} else {
coupling_rate[i] = 0;
}
}
update_calls = 0;
b_equilibration = true;
}
return COLVARS_OK;
}
int colvarbias_alb::set_state_params(std::string const &conf)
{
int error_code = colvarbias::set_state_params(conf);
if (error_code != COLVARS_OK) {
return error_code;
}
if (!get_keyval(conf, "setCoupling", set_coupling))
cvm::fatal_error("Error: current setCoupling is missing from the restart.\n");
if (!get_keyval(conf, "currentCoupling", current_coupling))
cvm::fatal_error("Error: current setCoupling is missing from the restart.\n");
if (!get_keyval(conf, "maxCouplingRange", max_coupling_range))
cvm::fatal_error("Error: maxCouplingRange is missing from the restart.\n");
if (!get_keyval(conf, "couplingRate", coupling_rate))
cvm::fatal_error("Error: current setCoupling is missing from the restart.\n");
if (!get_keyval(conf, "couplingAccum", coupling_accum))
cvm::fatal_error("Error: couplingAccum is missing from the restart.\n");
if (!get_keyval(conf, "mean", means))
cvm::fatal_error("Error: current mean is missing from the restart.\n");
if (!get_keyval(conf, "ssd", ssd))
cvm::fatal_error("Error: current ssd is missing from the restart.\n");
if (!get_keyval(conf, "updateCalls", update_calls))
cvm::fatal_error("Error: current updateCalls is missing from the restart.\n");
if (!get_keyval(conf, "b_equilibration", b_equilibration))
cvm::fatal_error("Error: current updateCalls is missing from the restart.\n");
return COLVARS_OK;
}
std::string const colvarbias_alb::get_state_params() const
{
std::ostringstream os;
os << " setCoupling ";
size_t i;
for (i = 0; i < num_variables(); i++) {
os << std::setprecision(cvm::en_prec)
<< std::setw(cvm::en_width) << set_coupling[i] << "\n";
}
os << " currentCoupling ";
for (i = 0; i < num_variables(); i++) {
os << std::setprecision(cvm::en_prec)
<< std::setw(cvm::en_width) << current_coupling[i] << "\n";
}
os << " maxCouplingRange ";
for (i = 0; i < num_variables(); i++) {
os << std::setprecision(cvm::en_prec)
<< std::setw(cvm::en_width) << max_coupling_range[i] << "\n";
}
os << " couplingRate ";
for (i = 0; i < num_variables(); i++) {
os << std::setprecision(cvm::en_prec)
<< std::setw(cvm::en_width) << coupling_rate[i] << "\n";
}
os << " couplingAccum ";
for (i = 0; i < num_variables(); i++) {
os << std::setprecision(cvm::en_prec)
<< std::setw(cvm::en_width) << coupling_accum[i] << "\n";
}
os << " mean ";
for (i = 0; i < num_variables(); i++) {
os << std::setprecision(cvm::en_prec)
<< std::setw(cvm::en_width) << means[i] << "\n";
}
os << " ssd ";
for (i = 0; i < num_variables(); i++) {
os << std::setprecision(cvm::en_prec)
<< std::setw(cvm::en_width) << ssd[i] << "\n";
}
os << " updateCalls " << update_calls << "\n";
if (b_equilibration)
os << " b_equilibration yes\n";
else
os << " b_equilibration no\n";
return os.str();
}
std::ostream & colvarbias_alb::write_traj_label(std::ostream &os)
{
os << " ";
if (b_output_energy)
os << " E_"
<< cvm::wrap_string(this->name, cvm::en_width-2);
if (b_output_coupling)
for (size_t i = 0; i < current_coupling.size(); i++) {
os << " ForceConst_" << i
<<std::setw(cvm::en_width - 6 - (i / 10 + 1))
<< "";
}
if (b_output_grad)
for (size_t i = 0; i < means.size(); i++) {
os << "Grad_"
<< cvm::wrap_string(colvars[i]->name, cvm::cv_width - 4);
}
if (b_output_centers)
for (size_t i = 0; i < num_variables(); i++) {
size_t const this_cv_width = (colvars[i]->value()).output_width(cvm::cv_width);
os << " x0_"
<< cvm::wrap_string(colvars[i]->name, this_cv_width-3);
}
return os;
}
std::ostream & colvarbias_alb::write_traj(std::ostream &os)
{
os << " ";
if (b_output_energy)
os << " "
<< std::setprecision(cvm::en_prec) << std::setw(cvm::en_width)
<< bias_energy;
if (b_output_coupling)
for (size_t i = 0; i < current_coupling.size(); i++) {
os << " "
<< std::setprecision(cvm::en_prec) << std::setw(cvm::en_width)
<< current_coupling[i];
}
if (b_output_centers)
for (size_t i = 0; i < num_variables(); i++) {
os << " "
<< std::setprecision(cvm::cv_prec) << std::setw(cvm::cv_width)
<< colvar_centers[i];
}
if (b_output_grad)
for (size_t i = 0; i < means.size(); i++) {
os << " "
<< std::setprecision(cvm::cv_prec) << std::setw(cvm::cv_width)
<< -2.0 * (means[i] / (static_cast<cvm::real>(colvar_centers[i])) - 1) * ssd[i] / (fmax(update_calls, 2.0) - 1);
}
return os;
}
cvm::real colvarbias_alb::restraint_potential(cvm::real k,
colvar const *x,
colvarvalue const &xcenter) const
{
return k * (x->value() - xcenter);
}
colvarvalue colvarbias_alb::restraint_force(cvm::real k,
colvar const * /* x */,
colvarvalue const & /* xcenter */) const
{
return k;
}
cvm::real colvarbias_alb::restraint_convert_k(cvm::real k,
cvm::real dist_measure) const
{
return k / dist_measure;
}