Homec4science
Diffusion lammps (lammps-icms) Browse

lammps/lib/colvars/colvarbias_alb.cpp
2fcd26f6c41blammps-icms

Last Change
Raw File

colvarbias_alb.cpp
View Options

// -*- c++ -*-
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include "colvarmodule.h"
#include "colvarbias_alb.h"
#include "colvarbias.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(std::string const &conf, char const *key) :
colvarbias(conf, key), update_calls(0), b_equilibration(true) {
size_t i;
// get the initial restraint centers
colvar_centers.resize(colvars.size());
means.resize(colvars.size());
ssd.resize(colvars.size()); //sum of squares of differences from mean
//setup force vectors
max_coupling_range.resize(colvars.size());
max_coupling_rate.resize(colvars.size());
coupling_accum.resize(colvars.size());
set_coupling.resize(colvars.size());
current_coupling.resize(colvars.size());
coupling_rate.resize(colvars.size());
enable(f_cvb_apply_force);
for (i = 0; i < colvars.size(); 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 < colvars.size(); 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() != colvars.size())
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 == 0)
cvm::fatal_error("Error: must set updateFrequency to greater than 2.\n");
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 < colvars.size(); i++)
set_coupling[i] = 0.;
//how we're going to increase to that point
for (i = 0; i < colvars.size(); 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 < colvars.size(); 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 < colvars.size(); i++) {
max_coupling_rate[i] = max_coupling_range[i] / (10 * update_freq);
}
}
if (cvm::debug())
cvm::log(" bias.\n");
}
colvarbias_alb::~colvarbias_alb() {
if (cvm::n_rest_biases > 0)
cvm::n_rest_biases -= 1;
}
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 < colvars.size(); 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
if (coupling_rate[i] == 0 || pow(current_coupling[i] - set_coupling[i],2) < pow(coupling_rate[i],2)) {
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 < colvars.size(); 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 (colvars.size() == 1 || rand() < RAND_MAX / ((int) colvars.size())) {
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;
}
std::istream & colvarbias_alb::read_restart(std::istream &is)
{
size_t const start_pos = is.tellg();
cvm::log("Restarting adaptive linear bias \""+
this->name+"\".\n");
std::string key, brace, conf;
if ( !(is >> key) || !(key == "ALB") ||
!(is >> brace) || !(brace == "{") ||
!(is >> colvarparse::read_block("configuration", conf)) ) {
cvm::log("Error: in reading restart configuration for restraint bias \""+
this->name+"\" at position "+
cvm::to_str(is.tellg())+" in stream.\n");
is.clear();
is.seekg(start_pos, std::ios::beg);
is.setstate(std::ios::failbit);
return is;
}
std::string name = "";
if ( (colvarparse::get_keyval(conf, "name", name, std::string(""), colvarparse::parse_silent)) &&
(name != this->name) )
cvm::fatal_error("Error: in the restart file, the "
"\"ALB\" block has a wrong name\n");
if (name.size() == 0) {
cvm::fatal_error("Error: \"ALB\" block in the restart file "
"has no identifiers.\n");
}
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");
is >> brace;
if (brace != "}") {
cvm::fatal_error("Error: corrupt restart information for adaptive linear bias \""+
this->name+"\": no matching brace at position "+
cvm::to_str(is.tellg())+" in the restart file.\n");
is.setstate(std::ios::failbit);
}
return is;
}
std::ostream & colvarbias_alb::write_restart(std::ostream &os)
{
os << "ALB {\n"
<< " configuration {\n"
<< " name " << this->name << "\n";
os << " setCoupling ";
size_t i;
for (i = 0; i < colvars.size(); i++) {
os << std::setprecision(cvm::en_prec)
<< std::setw(cvm::en_width) << set_coupling[i] << "\n";
}
os << " currentCoupling ";
for (i = 0; i < colvars.size(); i++) {
os << std::setprecision(cvm::en_prec)
<< std::setw(cvm::en_width) << current_coupling[i] << "\n";
}
os << " maxCouplingRange ";
for (i = 0; i < colvars.size(); i++) {
os << std::setprecision(cvm::en_prec)
<< std::setw(cvm::en_width) << max_coupling_range[i] << "\n";
}
os << " couplingRate ";
for (i = 0; i < colvars.size(); i++) {
os << std::setprecision(cvm::en_prec)
<< std::setw(cvm::en_width) << coupling_rate[i] << "\n";
}
os << " couplingAccum ";
for (i = 0; i < colvars.size(); i++) {
os << std::setprecision(cvm::en_prec)
<< std::setw(cvm::en_width) << coupling_accum[i] << "\n";
}
os << " mean ";
for (i = 0; i < colvars.size(); i++) {
os << std::setprecision(cvm::en_prec)
<< std::setw(cvm::en_width) << means[i] << "\n";
}
os << " ssd ";
for (i = 0; i < colvars.size(); 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";
os << " }\n"
<< "}\n\n";
return os;
}
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 < colvars.size(); 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 < colvars.size(); 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. * (means[i] / (static_cast<cvm::real> (colvar_centers[i])) - 1) * ssd[i] / (fmax(update_calls,2) - 1);
}
return os;
}
cvm::real colvarbias_alb::restraint_potential(cvm::real k, const colvar* x, const colvarvalue &xcenter) const
{
return k * (x->value() - xcenter);
}
colvarvalue colvarbias_alb::restraint_force(cvm::real k, const colvar* x, const colvarvalue &xcenter) const
{
return k;
}
cvm::real colvarbias_alb::restraint_convert_k(cvm::real k, cvm::real dist_measure) const
{
return k / dist_measure;
}
c4science · Help