Page MenuHomec4science

colvarmodule.cpp
No OneTemporary

File Metadata

Created
Tue, May 21, 03:27

colvarmodule.cpp

// -*- c++ -*-
#include <sstream>
#include <string.h>
#include "colvarmodule.h"
#include "colvarparse.h"
#include "colvarproxy.h"
#include "colvar.h"
#include "colvarbias.h"
#include "colvarbias_abf.h"
#include "colvarbias_alb.h"
#include "colvarbias_histogram.h"
#include "colvarbias_meta.h"
#include "colvarbias_restraint.h"
#include "colvarscript.h"
colvarmodule::colvarmodule(colvarproxy *proxy_in)
{
// pointer to the proxy object
if (proxy == NULL) {
proxy = proxy_in;
parse = new colvarparse();
} else {
// TODO relax this error to handle multiple molecules in VMD
// once the module is not static anymore
cvm::error("Error: trying to allocate the collective "
"variable module twice.\n");
return;
}
cvm::log(cvm::line_marker);
cvm::log("Initializing the collective variables module, version "+
cvm::to_str(COLVARS_VERSION)+".\n");
cvm::log("Please cite Fiorin et al, Mol Phys 2013:\n "
"http://dx.doi.org/10.1080/00268976.2013.813594\n"
"in any publication based on this calculation.\n");
if (proxy->smp_enabled() == COLVARS_OK) {
cvm::log("SMP parallelism is available.\n");
}
// set initial default values
// "it_restart" will be set by the input state file, if any;
// "it" should be updated by the proxy
colvarmodule::it = colvarmodule::it_restart = 0;
colvarmodule::it_restart_from_state_file = true;
colvarmodule::use_scripted_forces = false;
colvarmodule::b_analysis = false;
colvarmodule::debug_gradients_step_size = 1.0e-07;
colvarmodule::rotation::monitor_crossings = false;
colvarmodule::rotation::crossing_threshold = 1.0e-02;
colvarmodule::cv_traj_freq = 100;
colvarmodule::restart_out_freq = proxy->restart_frequency();
// by default overwrite the existing trajectory file
colvarmodule::cv_traj_append = false;
}
int colvarmodule::read_config_file(char const *config_filename)
{
cvm::log(cvm::line_marker);
cvm::log("Reading new configuration from file \""+
std::string(config_filename)+"\":\n");
// open the configfile
config_s.open(config_filename);
if (!config_s.is_open()) {
cvm::error("Error: in opening configuration file \""+
std::string(config_filename)+"\".\n",
FILE_ERROR);
return COLVARS_ERROR;
}
// read the config file into a string
std::string conf = "";
std::string line;
while (colvarparse::getline_nocomments(config_s, line)) {
// Delete lines that contain only white space after removing comments
if (line.find_first_not_of(colvarparse::white_space) != std::string::npos)
conf.append(line+"\n");
}
config_s.close();
return parse_config(conf);
}
int colvarmodule::read_config_string(std::string const &config_str)
{
cvm::log(cvm::line_marker);
cvm::log("Reading new configuration:\n");
std::istringstream config_s(config_str);
// strip the comments away
std::string conf = "";
std::string line;
while (colvarparse::getline_nocomments(config_s, line)) {
// Delete lines that contain only white space after removing comments
if (line.find_first_not_of(colvarparse::white_space) != std::string::npos)
conf.append(line+"\n");
}
return parse_config(conf);
}
int colvarmodule::parse_config(std::string &conf)
{
// parse global options
if (catch_input_errors(parse_global_params(conf))) {
return get_error();
}
// parse the options for collective variables
if (catch_input_errors(parse_colvars(conf))) {
return get_error();
}
// parse the options for biases
if (catch_input_errors(parse_biases(conf))) {
return get_error();
}
// done parsing known keywords, check that all keywords found were valid ones
if (catch_input_errors(parse->check_keywords(conf, "colvarmodule"))) {
return get_error();
}
cvm::log(cvm::line_marker);
cvm::log("Collective variables module (re)initialized.\n");
cvm::log(cvm::line_marker);
// update any necessary proxy data
proxy->setup();
if (cv_traj_os.is_open()) {
// configuration might have changed, better redo the labels
write_traj_label(cv_traj_os);
}
return get_error();
}
int colvarmodule::parse_global_params(std::string const &conf)
{
std::string index_file_name;
if (parse->get_keyval(conf, "indexFile", index_file_name)) {
read_index_file(index_file_name.c_str());
}
parse->get_keyval(conf, "analysis", b_analysis, b_analysis);
parse->get_keyval(conf, "debugGradientsStepSize", debug_gradients_step_size,
debug_gradients_step_size,
colvarparse::parse_silent);
parse->get_keyval(conf, "monitorEigenvalueCrossing",
colvarmodule::rotation::monitor_crossings,
colvarmodule::rotation::monitor_crossings,
colvarparse::parse_silent);
parse->get_keyval(conf, "eigenvalueCrossingThreshold",
colvarmodule::rotation::crossing_threshold,
colvarmodule::rotation::crossing_threshold,
colvarparse::parse_silent);
parse->get_keyval(conf, "colvarsTrajFrequency", cv_traj_freq, cv_traj_freq);
parse->get_keyval(conf, "colvarsRestartFrequency",
restart_out_freq, restart_out_freq);
// if this is true when initializing, it means
// we are continuing after a reset(): default to true
parse->get_keyval(conf, "colvarsTrajAppend", cv_traj_append, cv_traj_append);
parse->get_keyval(conf, "scriptedColvarForces", use_scripted_forces, false);
parse->get_keyval(conf, "scriptingAfterBiases", scripting_after_biases, true);
if (use_scripted_forces && !proxy->force_script_defined) {
cvm::error("User script for scripted colvar forces not found.", INPUT_ERROR);
}
return (cvm::get_error() ? COLVARS_ERROR : COLVARS_OK);
}
int colvarmodule::parse_colvars(std::string const &conf)
{
if (cvm::debug())
cvm::log("Initializing the collective variables.\n");
std::string colvar_conf = "";
size_t pos = 0;
while (parse->key_lookup(conf, "colvar", colvar_conf, pos)) {
if (colvar_conf.size()) {
cvm::log(cvm::line_marker);
cvm::increase_depth();
colvars.push_back(new colvar(colvar_conf));
if (cvm::get_error() ||
((colvars.back())->check_keywords(colvar_conf, "colvar") != COLVARS_OK)) {
cvm::log("Error while constructing colvar number " +
cvm::to_str(colvars.size()) + " : deleting.");
delete colvars.back(); // the colvar destructor updates the colvars array
return COLVARS_ERROR;
}
cvm::decrease_depth();
} else {
cvm::error("Error: \"colvar\" keyword found without any configuration.\n", INPUT_ERROR);
return COLVARS_ERROR;
}
cvm::decrease_depth();
colvar_conf = "";
}
if (!colvars.size()) {
cvm::log("Warning: no collective variables defined.\n");
}
if (colvars.size())
cvm::log(cvm::line_marker);
cvm::log("Collective variables initialized, "+
cvm::to_str(colvars.size())+
" in total.\n");
return (cvm::get_error() ? COLVARS_ERROR : COLVARS_OK);
}
bool colvarmodule::check_new_bias(std::string &conf, char const *key)
{
if (cvm::get_error() ||
(biases.back()->check_keywords(conf, key) != COLVARS_OK)) {
cvm::log("Error while constructing bias number " +
cvm::to_str(biases.size()) + " : deleting.\n");
delete biases.back(); // the bias destructor updates the biases array
return true;
}
return false;
}
template <class bias_type>
int colvarmodule::parse_biases_type(std::string const &conf,
char const *keyword,
size_t &bias_count)
{
std::string bias_conf = "";
size_t conf_saved_pos = 0;
while (parse->key_lookup(conf, keyword, bias_conf, conf_saved_pos)) {
if (bias_conf.size()) {
cvm::log(cvm::line_marker);
cvm::increase_depth();
biases.push_back(new bias_type(keyword));
biases.back()->init(bias_conf);
if (cvm::check_new_bias(bias_conf, keyword) != COLVARS_OK) {
return COLVARS_ERROR;
}
cvm::decrease_depth();
bias_count++;
} else {
cvm::error("Error: keyword \""+std::string(keyword)+"\" found without configuration.\n",
INPUT_ERROR);
return COLVARS_ERROR;
}
bias_conf = "";
}
return COLVARS_OK;
}
int colvarmodule::parse_biases(std::string const &conf)
{
if (cvm::debug())
cvm::log("Initializing the collective variables biases.\n");
/// initialize ABF instances
parse_biases_type<colvarbias_abf>(conf, "abf", n_abf_biases);
/// initialize adaptive linear biases
parse_biases_type<colvarbias_alb>(conf, "ALB", n_rest_biases);
/// initialize harmonic restraints
parse_biases_type<colvarbias_restraint_harmonic>(conf, "harmonic", n_rest_biases);
/// initialize histograms
parse_biases_type<colvarbias_histogram>(conf, "histogram", n_histo_biases);
/// initialize linear restraints
parse_biases_type<colvarbias_restraint_linear>(conf, "linear", n_rest_biases);
/// initialize metadynamics instances
parse_biases_type<colvarbias_meta>(conf, "metadynamics", n_meta_biases);
if (use_scripted_forces) {
cvm::log(cvm::line_marker);
cvm::increase_depth();
cvm::log("User forces script will be run at each bias update.");
cvm::decrease_depth();
}
size_t i;
for (i = 0; i < biases.size(); i++) {
biases[i]->enable(colvardeps::f_cvb_active);
if (cvm::debug())
biases[i]->print_state();
}
size_t n_hist_dep_biases = 0;
std::vector<std::string> hist_dep_biases_names;
for (i = 0; i < biases.size(); i++) {
if (biases[i]->is_enabled(colvardeps::f_cvb_apply_force) &&
biases[i]->is_enabled(colvardeps::f_cvb_history_dependent)) {
n_hist_dep_biases++;
hist_dep_biases_names.push_back(biases[i]->name);
}
}
if (n_hist_dep_biases > 1) {
cvm::log("WARNING: there are "+cvm::to_str(n_hist_dep_biases)+
" history-dependent biases with non-zero force parameters:\n"+
cvm::to_str(hist_dep_biases_names)+"\n"+
"Please make sure that their forces do not counteract each other.\n");
}
if (biases.size() || use_scripted_forces) {
cvm::log(cvm::line_marker);
cvm::log("Collective variables biases initialized, "+
cvm::to_str(biases.size())+" in total.\n");
} else {
if (!use_scripted_forces) {
cvm::log("No collective variables biases were defined.\n");
}
}
return (cvm::get_error() ? COLVARS_ERROR : COLVARS_OK);
}
int colvarmodule::catch_input_errors(int result)
{
if (result != COLVARS_OK || get_error()) {
set_error_bits(result);
set_error_bits(INPUT_ERROR);
parse->init();
return get_error();
}
return COLVARS_OK;
}
colvarbias * colvarmodule::bias_by_name(std::string const &name) {
for (std::vector<colvarbias *>::iterator bi = biases.begin();
bi != biases.end();
bi++) {
if ((*bi)->name == name) {
return (*bi);
}
}
return NULL;
}
colvar *colvarmodule::colvar_by_name(std::string const &name) {
for (std::vector<colvar *>::iterator cvi = colvars.begin();
cvi != colvars.end();
cvi++) {
if ((*cvi)->name == name) {
return (*cvi);
}
}
return NULL;
}
int colvarmodule::change_configuration(std::string const &bias_name,
std::string const &conf)
{
// This is deprecated; supported strategy is to delete the bias
// and parse the new config
cvm::increase_depth();
colvarbias *b;
b = bias_by_name(bias_name);
if (b == NULL) { cvm::error("Error: bias not found: " + bias_name); }
b->change_configuration(conf);
cvm::decrease_depth();
return (cvm::get_error() ? COLVARS_ERROR : COLVARS_OK);
}
std::string colvarmodule::read_colvar(std::string const &name)
{
cvm::increase_depth();
colvar *c;
std::stringstream ss;
c = colvar_by_name(name);
if (c == NULL) { cvm::fatal_error("Error: colvar not found: " + name); }
ss << c->value();
cvm::decrease_depth();
return ss.str();
}
cvm::real colvarmodule::energy_difference(std::string const &bias_name,
std::string const &conf)
{
cvm::increase_depth();
colvarbias *b;
cvm::real energy_diff = 0.;
b = bias_by_name(bias_name);
if (b == NULL) { cvm::fatal_error("Error: bias not found: " + bias_name); }
energy_diff = b->energy_difference(conf);
cvm::decrease_depth();
return energy_diff;
}
int colvarmodule::bias_current_bin(std::string const &bias_name)
{
cvm::increase_depth();
int ret;
colvarbias *b = bias_by_name(bias_name);
if (b != NULL) {
ret = b->current_bin();
} else {
cvm::error("Error: bias not found.\n");
ret = COLVARS_ERROR;
}
cvm::decrease_depth();
return ret;
}
int colvarmodule::bias_bin_num(std::string const &bias_name)
{
cvm::increase_depth();
int ret;
colvarbias *b = bias_by_name(bias_name);
if (b != NULL) {
ret = b->bin_num();
} else {
cvm::error("Error: bias not found.\n");
ret = COLVARS_ERROR;
}
cvm::decrease_depth();
return ret;
}
int colvarmodule::bias_bin_count(std::string const &bias_name, size_t bin_index)
{
cvm::increase_depth();
int ret;
colvarbias *b = bias_by_name(bias_name);
if (b != NULL) {
ret = b->bin_count(bin_index);
} else {
cvm::error("Error: bias not found.\n");
ret = COLVARS_ERROR;
}
cvm::decrease_depth();
return ret;
}
int colvarmodule::bias_share(std::string const &bias_name)
{
cvm::increase_depth();
int ret;
colvarbias *b = bias_by_name(bias_name);
if (b != NULL) {
b->replica_share();
ret = COLVARS_OK;
} else {
cvm::error("Error: bias not found.\n");
ret = COLVARS_ERROR;
}
cvm::decrease_depth();
return ret;
}
int colvarmodule::calc()
{
int error_code = COLVARS_OK;
if (cvm::debug()) {
cvm::log(cvm::line_marker);
cvm::log("Collective variables module, step no. "+
cvm::to_str(cvm::step_absolute())+"\n");
}
error_code |= calc_colvars();
// set biasing forces to zero before biases are calculated and summed over
for (std::vector<colvar *>::iterator cvi = colvars.begin();
cvi != colvars.end(); cvi++) {
(*cvi)->reset_bias_force();
}
error_code |= calc_biases();
error_code |= update_colvar_forces();
if (cvm::b_analysis) {
error_code |= analyze();
}
// write trajectory files, if needed
if (cv_traj_freq && cv_traj_name.size()) {
error_code |= write_traj_files();
}
// write restart files, if needed
if (restart_out_freq && restart_out_name.size()) {
error_code |= write_restart_files();
}
return error_code;
}
int colvarmodule::calc_colvars()
{
if (cvm::debug())
cvm::log("Calculating collective variables.\n");
// calculate collective variables and their gradients
int error_code = COLVARS_OK;
std::vector<colvar *>::iterator cvi;
// Determine which colvars are active at this time step
for (cvi = colvars.begin(); cvi != colvars.end(); cvi++) {
(*cvi)->feature_states[colvardeps::f_cv_active]->enabled = (step_absolute() % (*cvi)->get_time_step_factor() == 0);
}
// if SMP support is available, split up the work
if (proxy->smp_enabled() == COLVARS_OK) {
// first, calculate how much work (currently, how many active CVCs) each colvar has
colvars_smp.resize(0);
colvars_smp_items.resize(0);
colvars_smp.reserve(colvars.size());
colvars_smp_items.reserve(colvars.size());
// set up a vector containing all components
size_t num_colvar_items = 0;
cvm::increase_depth();
for (cvi = colvars.begin(); cvi != colvars.end(); cvi++) {
if (!(*cvi)->is_enabled()) continue;
error_code |= (*cvi)->update_cvc_flags();
size_t num_items = (*cvi)->num_active_cvcs();
colvars_smp.reserve(colvars_smp.size() + num_items);
colvars_smp_items.reserve(colvars_smp_items.size() + num_items);
for (size_t icvc = 0; icvc < num_items; icvc++) {
colvars_smp.push_back(*cvi);
colvars_smp_items.push_back(icvc);
}
num_colvar_items += num_items;
}
cvm::decrease_depth();
// calculate colvar components in parallel
error_code |= proxy->smp_colvars_loop();
cvm::increase_depth();
for (cvi = colvars.begin(); cvi != colvars.end(); cvi++) {
if (!(*cvi)->is_enabled()) continue;
error_code |= (*cvi)->collect_cvc_data();
}
cvm::decrease_depth();
} else {
// calculate colvars one at a time
cvm::increase_depth();
for (cvi = colvars.begin(); cvi != colvars.end(); cvi++) {
if (!(*cvi)->is_enabled()) continue;
error_code |= (*cvi)->calc();
if (cvm::get_error()) {
return COLVARS_ERROR;
}
}
cvm::decrease_depth();
}
error_code |= cvm::get_error();
return error_code;
}
int colvarmodule::calc_biases()
{
// update the biases and communicate their forces to the collective
// variables
if (cvm::debug() && biases.size())
cvm::log("Updating collective variable biases.\n");
std::vector<colvarbias *>::iterator bi;
int error_code = COLVARS_OK;
// if SMP support is available, split up the work
if (proxy->smp_enabled() == COLVARS_OK) {
if (use_scripted_forces && !scripting_after_biases) {
// calculate biases and scripted forces in parallel
error_code |= proxy->smp_biases_script_loop();
} else {
// calculate biases in parallel
error_code |= proxy->smp_biases_loop();
}
} else {
if (use_scripted_forces && !scripting_after_biases) {
error_code |= calc_scripted_forces();
}
cvm::increase_depth();
for (bi = biases.begin(); bi != biases.end(); bi++) {
error_code |= (*bi)->update();
if (cvm::get_error()) {
return COLVARS_ERROR;
}
}
cvm::decrease_depth();
}
cvm::real total_bias_energy = 0.0;
for (bi = biases.begin(); bi != biases.end(); bi++) {
total_bias_energy += (*bi)->get_energy();
}
proxy->add_energy(total_bias_energy);
return (cvm::get_error() ? COLVARS_ERROR : COLVARS_OK);
}
int colvarmodule::update_colvar_forces()
{
int error_code = COLVARS_OK;
std::vector<colvar *>::iterator cvi;
std::vector<colvarbias *>::iterator bi;
// sum the forces from all biases for each collective variable
if (cvm::debug() && biases.size())
cvm::log("Collecting forces from all biases.\n");
cvm::increase_depth();
for (bi = biases.begin(); bi != biases.end(); bi++) {
(*bi)->communicate_forces();
if (cvm::get_error()) {
return COLVARS_ERROR;
}
}
cvm::decrease_depth();
if (use_scripted_forces && scripting_after_biases) {
error_code |= calc_scripted_forces();
}
cvm::real total_colvar_energy = 0.0;
// sum up the forces for each colvar, including wall forces
// and integrate any internal
// equation of motion (extended system)
if (cvm::debug())
cvm::log("Updating the internal degrees of freedom "
"of colvars (if they have any).\n");
cvm::increase_depth();
for (cvi = colvars.begin(); cvi != colvars.end(); cvi++) {
// Here we call even inactive colvars, so they accumulate biasing forces
// as well as update their extended-system dynamics
total_colvar_energy += (*cvi)->update_forces_energy();
if (cvm::get_error()) {
return COLVARS_ERROR;
}
}
cvm::decrease_depth();
proxy->add_energy(total_colvar_energy);
// make collective variables communicate their forces to their
// coupled degrees of freedom (i.e. atoms)
if (cvm::debug())
cvm::log("Communicating forces from the colvars to the atoms.\n");
cvm::increase_depth();
for (cvi = colvars.begin(); cvi != colvars.end(); cvi++) {
if ((*cvi)->is_enabled(colvardeps::f_cv_gradient)) {
if (!(*cvi)->is_enabled()) continue;
(*cvi)->communicate_forces();
if (cvm::get_error()) {
return COLVARS_ERROR;
}
}
}
cvm::decrease_depth();
return (cvm::get_error() ? COLVARS_ERROR : COLVARS_OK);
}
int colvarmodule::calc_scripted_forces()
{
// Run user force script, if provided,
// potentially adding scripted forces to the colvars
int res;
res = proxy->run_force_callback();
if (res == COLVARS_NOT_IMPLEMENTED) {
cvm::error("Colvar forces scripts are not implemented.");
return COLVARS_NOT_IMPLEMENTED;
}
if (res != COLVARS_OK) {
cvm::error("Error running user colvar forces script");
return COLVARS_ERROR;
}
return COLVARS_OK;
}
int colvarmodule::write_restart_files()
{
if ( (cvm::step_relative() > 0) &&
((cvm::step_absolute() % restart_out_freq) == 0) ) {
cvm::log("Writing the state file \""+
restart_out_name+"\".\n");
proxy->backup_file(restart_out_name.c_str());
restart_out_os.open(restart_out_name.c_str());
if (!restart_out_os.is_open() || !write_restart(restart_out_os))
cvm::error("Error: in writing restart file.\n");
restart_out_os.close();
}
return (cvm::get_error() ? COLVARS_ERROR : COLVARS_OK);
}
int colvarmodule::write_traj_files()
{
if (!cv_traj_os.is_open()) {
open_traj_file(cv_traj_name);
}
// write labels in the traj file every 1000 lines and at first timestep
if ((cvm::step_absolute() % (cv_traj_freq * 1000)) == 0 || cvm::step_relative() == 0) {
write_traj_label(cv_traj_os);
}
if ((cvm::step_absolute() % cv_traj_freq) == 0) {
write_traj(cv_traj_os);
}
if (restart_out_freq && cv_traj_os.is_open()) {
// flush the trajectory file if we are at the restart frequency
if ( (cvm::step_relative() > 0) &&
((cvm::step_absolute() % restart_out_freq) == 0) ) {
cvm::log("Synchronizing (emptying the buffer of) trajectory file \""+
cv_traj_name+"\".\n");
cv_traj_os.flush();
}
}
return (cvm::get_error() ? COLVARS_ERROR : COLVARS_OK);
}
int colvarmodule::analyze()
{
if (cvm::debug()) {
cvm::log("colvarmodule::analyze(), step = "+cvm::to_str(it)+".\n");
}
if (cvm::step_relative() == 0)
cvm::log("Performing analysis.\n");
// perform colvar-specific analysis
for (std::vector<colvar *>::iterator cvi = colvars.begin();
cvi != colvars.end();
cvi++) {
cvm::increase_depth();
(*cvi)->analyze();
cvm::decrease_depth();
}
// perform bias-specific analysis
for (std::vector<colvarbias *>::iterator bi = biases.begin();
bi != biases.end();
bi++) {
cvm::increase_depth();
(*bi)->analyze();
cvm::decrease_depth();
}
return (cvm::get_error() ? COLVARS_ERROR : COLVARS_OK);
}
int colvarmodule::setup()
{
// loop over all components of all colvars to reset masses of all groups
for (std::vector<colvar *>::iterator cvi = colvars.begin();
cvi != colvars.end(); cvi++) {
(*cvi)->setup();
}
return (cvm::get_error() ? COLVARS_ERROR : COLVARS_OK);
}
colvarmodule::~colvarmodule()
{
if ((proxy->smp_thread_id() == COLVARS_NOT_IMPLEMENTED) ||
(proxy->smp_thread_id() == 0)) {
reset();
delete parse;
parse = NULL;
proxy = NULL;
}
}
int colvarmodule::reset()
{
parse->init();
cvm::log("Resetting the Collective Variables Module.\n");
// Iterate backwards because we are deleting the elements as we go
for (std::vector<colvarbias *>::reverse_iterator bi = biases.rbegin();
bi != biases.rend();
bi++) {
delete *bi; // the bias destructor updates the biases array
}
biases.clear();
// Iterate backwards because we are deleting the elements as we go
for (std::vector<colvar *>::reverse_iterator cvi = colvars.rbegin();
cvi != colvars.rend();
cvi++) {
delete *cvi; // the colvar destructor updates the colvars array
}
colvars.clear();
index_groups.clear();
index_group_names.clear();
if (cv_traj_os.is_open()) {
// Do not close file here, as we might not be done with it yet.
cv_traj_os.flush();
}
return (cvm::get_error() ? COLVARS_ERROR : COLVARS_OK);
}
int colvarmodule::setup_input()
{
// name of input state file
restart_in_name = proxy->input_prefix().size() ?
std::string(proxy->input_prefix()+".colvars.state") :
std::string("") ;
// read the restart configuration, if available
if (restart_in_name.size()) {
// read the restart file
std::ifstream input_is(restart_in_name.c_str());
if (!input_is.good()) {
cvm::error("Error: in opening restart file \""+
std::string(restart_in_name)+"\".\n",
FILE_ERROR);
return COLVARS_ERROR;
} else {
cvm::log("Restarting from file \""+restart_in_name+"\".\n");
read_restart(input_is);
if (cvm::get_error() != COLVARS_OK) {
return COLVARS_ERROR;
}
cvm::log(cvm::line_marker);
}
}
return (cvm::get_error() ? COLVARS_ERROR : COLVARS_OK);
}
int colvarmodule::setup_output()
{
int error_code = 0;
// output state file (restart)
restart_out_name = proxy->restart_output_prefix().size() ?
std::string(proxy->restart_output_prefix()+".colvars.state") :
std::string("");
if (restart_out_name.size()) {
cvm::log("The restart output state file will be \""+restart_out_name+"\".\n");
}
output_prefix = proxy->output_prefix();
if (output_prefix.size()) {
cvm::log("The final output state file will be \""+
(output_prefix.size() ?
std::string(output_prefix+".colvars.state") :
std::string("colvars.state"))+"\".\n");
// cvm::log (cvm::line_marker);
}
cv_traj_name =
(output_prefix.size() ?
std::string(output_prefix+".colvars.traj") :
std::string(""));
if (cv_traj_freq && cv_traj_name.size()) {
error_code |= open_traj_file(cv_traj_name);
}
for (std::vector<colvarbias *>::iterator bi = biases.begin();
bi != biases.end();
bi++) {
error_code |= (*bi)->setup_output();
}
if (error_code != COLVARS_OK || cvm::get_error()) {
set_error_bits(FILE_ERROR);
}
return (cvm::get_error() ? COLVARS_ERROR : COLVARS_OK);
}
std::istream & colvarmodule::read_restart(std::istream &is)
{
{
// read global restart information
std::string restart_conf;
if (is >> colvarparse::read_block("configuration", restart_conf)) {
if (it_restart_from_state_file) {
parse->get_keyval(restart_conf, "step",
it_restart, (size_t) 0,
colvarparse::parse_silent);
it = it_restart;
}
std::string restart_version;
parse->get_keyval(restart_conf, "version",
restart_version, std::string(""),
colvarparse::parse_silent);
if (restart_version.size() && (restart_version != std::string(COLVARS_VERSION))) {
cvm::log("This state file was generated with version "+restart_version+"\n");
}
}
is.clear();
parse->clear_keyword_registry();
}
// colvars restart
cvm::increase_depth();
for (std::vector<colvar *>::iterator cvi = colvars.begin();
cvi != colvars.end();
cvi++) {
if ( !((*cvi)->read_restart(is)) ) {
cvm::error("Error: in reading restart configuration for collective variable \""+
(*cvi)->name+"\".\n",
INPUT_ERROR);
}
}
// biases restart
for (std::vector<colvarbias *>::iterator bi = biases.begin();
bi != biases.end();
bi++) {
if (!((*bi)->read_restart(is))) {
cvm::error("Error: in reading restart configuration for bias \""+
(*bi)->name+"\".\n",
INPUT_ERROR);
}
}
cvm::decrease_depth();
return is;
}
int colvarmodule::backup_file(char const *filename)
{
return proxy->backup_file(filename);
}
int colvarmodule::write_output_files()
{
// if this is a simulation run (i.e. not a postprocessing), output data
// must be written to be able to restart the simulation
std::string const out_name =
(output_prefix.size() ?
std::string(output_prefix+".colvars.state") :
std::string("colvars.state"));
cvm::log("Saving collective variables state to \""+out_name+"\".\n");
std::ostream * os = proxy->output_stream(out_name);
os->setf(std::ios::scientific, std::ios::floatfield);
this->write_restart(*os);
proxy->close_output_stream(out_name);
cvm::increase_depth();
for (std::vector<colvar *>::iterator cvi = colvars.begin();
cvi != colvars.end();
cvi++) {
(*cvi)->write_output_files();
}
cvm::decrease_depth();
cvm::increase_depth();
for (std::vector<colvarbias *>::iterator bi = biases.begin();
bi != biases.end();
bi++) {
(*bi)->write_output_files();
}
cvm::decrease_depth();
if (cv_traj_os.is_open()) {
// do not close to avoid problems with multiple NAMD runs
cv_traj_os.flush();
}
return (cvm::get_error() ? COLVARS_ERROR : COLVARS_OK);
}
int colvarmodule::read_traj(char const *traj_filename,
long traj_read_begin,
long traj_read_end)
{
cvm::log("Opening trajectory file \""+
std::string(traj_filename)+"\".\n");
std::ifstream traj_is(traj_filename);
while (true) {
while (true) {
std::string line("");
do {
if (!colvarparse::getline_nocomments(traj_is, line)) {
cvm::log("End of file \""+std::string(traj_filename)+
"\" reached, or corrupted file.\n");
traj_is.close();
return false;
}
} while (line.find_first_not_of(colvarparse::white_space) == std::string::npos);
std::istringstream is(line);
if (!(is >> it)) return false;
if ( (it < traj_read_begin) ) {
if ((it % 1000) == 0)
std::cerr << "Skipping trajectory step " << it
<< " \r";
continue;
} else {
if ((it % 1000) == 0)
std::cerr << "Reading from trajectory, step = " << it
<< " \r";
if ( (traj_read_end > traj_read_begin) &&
(it > traj_read_end) ) {
std::cerr << "\n";
cvm::error("Reached the end of the trajectory, "
"read_end = "+cvm::to_str(traj_read_end)+"\n",
FILE_ERROR);
return COLVARS_ERROR;
}
for (std::vector<colvar *>::iterator cvi = colvars.begin();
cvi != colvars.end();
cvi++) {
if (!(*cvi)->read_traj(is)) {
cvm::error("Error: in reading colvar \""+(*cvi)->name+
"\" from trajectory file \""+
std::string(traj_filename)+"\".\n",
FILE_ERROR);
return COLVARS_ERROR;
}
}
break;
}
}
}
return (cvm::get_error() ? COLVARS_ERROR : COLVARS_OK);
}
std::ostream & colvarmodule::write_restart(std::ostream &os)
{
os.setf(std::ios::scientific, std::ios::floatfield);
os << "configuration {\n"
<< " step " << std::setw(it_width)
<< it << "\n"
<< " dt " << dt() << "\n"
<< " version " << std::string(COLVARS_VERSION) << "\n"
<< "}\n\n";
cvm::increase_depth();
for (std::vector<colvar *>::iterator cvi = colvars.begin();
cvi != colvars.end();
cvi++) {
(*cvi)->write_restart(os);
}
for (std::vector<colvarbias *>::iterator bi = biases.begin();
bi != biases.end();
bi++) {
(*bi)->write_restart(os);
}
cvm::decrease_depth();
return os;
}
int colvarmodule::open_traj_file(std::string const &file_name)
{
if (cv_traj_os.is_open()) {
return COLVARS_OK;
}
// (re)open trajectory file
if (cv_traj_append) {
cvm::log("Appending to colvar trajectory file \""+file_name+
"\".\n");
cv_traj_os.open(file_name.c_str(), std::ios::app);
} else {
cvm::log("Writing to colvar trajectory file \""+file_name+
"\".\n");
proxy->backup_file(file_name.c_str());
cv_traj_os.open(file_name.c_str());
}
if (!cv_traj_os.is_open()) {
cvm::error("Error: cannot write to file \""+file_name+"\".\n",
FILE_ERROR);
}
return (cvm::get_error() ? COLVARS_ERROR : COLVARS_OK);
}
int colvarmodule::close_traj_file()
{
if (cv_traj_os.is_open()) {
cv_traj_os.close();
}
return (cvm::get_error() ? COLVARS_ERROR : COLVARS_OK);
}
std::ostream & colvarmodule::write_traj_label(std::ostream &os)
{
if (!os.good()) {
cvm::error("Cannot write to trajectory file.");
return os;
}
os.setf(std::ios::scientific, std::ios::floatfield);
os << "# " << cvm::wrap_string("step", cvm::it_width-2)
<< " ";
cvm::increase_depth();
for (std::vector<colvar *>::iterator cvi = colvars.begin();
cvi != colvars.end();
cvi++) {
(*cvi)->write_traj_label(os);
}
for (std::vector<colvarbias *>::iterator bi = biases.begin();
bi != biases.end();
bi++) {
(*bi)->write_traj_label(os);
}
os << "\n";
if (cvm::debug()) {
os.flush();
}
cvm::decrease_depth();
return os;
}
std::ostream & colvarmodule::write_traj(std::ostream &os)
{
os.setf(std::ios::scientific, std::ios::floatfield);
os << std::setw(cvm::it_width) << it
<< " ";
cvm::increase_depth();
for (std::vector<colvar *>::iterator cvi = colvars.begin();
cvi != colvars.end();
cvi++) {
(*cvi)->write_traj(os);
}
for (std::vector<colvarbias *>::iterator bi = biases.begin();
bi != biases.end();
bi++) {
(*bi)->write_traj(os);
}
os << "\n";
if (cvm::debug()) {
os.flush();
}
cvm::decrease_depth();
return os;
}
void cvm::log(std::string const &message)
{
size_t const d = depth();
if (d > 0)
proxy->log((std::string(2*d, ' '))+message);
else
proxy->log(message);
}
void cvm::increase_depth()
{
(depth())++;
}
void cvm::decrease_depth()
{
if (depth() > 0) {
(depth())--;
}
}
size_t & cvm::depth()
{
// NOTE: do not call log() or error() here, to avoid recursion
size_t const nt = proxy->smp_num_threads();
if (proxy->smp_enabled() == COLVARS_OK) {
if (depth_v.size() != nt) {
// update array of depths
proxy->smp_lock();
if (depth_v.size() > 0) { depth_s = depth_v[0]; }
depth_v.clear();
depth_v.assign(nt, depth_s);
proxy->smp_unlock();
}
return depth_v[proxy->smp_thread_id()];
}
return depth_s;
}
void colvarmodule::set_error_bits(int code)
{
if (code < 0) {
cvm::fatal_error("Error: set_error_bits() received negative error code.\n");
return;
}
proxy->smp_lock();
errorCode |= code | COLVARS_ERROR;
proxy->smp_unlock();
}
bool colvarmodule::get_error_bit(int code)
{
return bool(errorCode & code);
}
void colvarmodule::clear_error()
{
proxy->smp_lock();
errorCode = COLVARS_OK;
proxy->smp_unlock();
}
void cvm::error(std::string const &message, int code)
{
set_error_bits(code);
proxy->error(message);
}
void cvm::fatal_error(std::string const &message)
{
// TODO once all non-fatal errors have been set to be handled by error(),
// set DELETE_COLVARS here for VMD to handle it
set_error_bits(FATAL_ERROR);
proxy->fatal_error(message);
}
void cvm::exit(std::string const &message)
{
proxy->exit(message);
}
int cvm::read_index_file(char const *filename)
{
std::ifstream is(filename, std::ios::binary);
if (!is.good()) {
cvm::error("Error: in opening index file \""+
std::string(filename)+"\".\n",
FILE_ERROR);
}
while (is.good()) {
char open, close;
std::string group_name;
if ( (is >> open) && (open == '[') &&
(is >> group_name) &&
(is >> close) && (close == ']') ) {
for (std::list<std::string>::iterator names_i = index_group_names.begin();
names_i != index_group_names.end();
names_i++) {
if (*names_i == group_name) {
cvm::error("Error: the group name \""+group_name+
"\" appears in multiple index files.\n",
FILE_ERROR);
}
}
cvm::index_group_names.push_back(group_name);
cvm::index_groups.push_back(std::vector<int> ());
} else {
cvm::error("Error: in parsing index file \""+
std::string(filename)+"\".\n",
INPUT_ERROR);
}
int atom_number = 1;
size_t pos = is.tellg();
while ( (is >> atom_number) && (atom_number > 0) ) {
(cvm::index_groups.back()).push_back(atom_number);
pos = is.tellg();
}
is.clear();
is.seekg(pos, std::ios::beg);
std::string delim;
if ( (is >> delim) && (delim == "[") ) {
// new group
is.clear();
is.seekg(pos, std::ios::beg);
} else {
break;
}
}
cvm::log("The following index groups were read from the index file \""+
std::string(filename)+"\":\n");
std::list<std::string>::iterator names_i = index_group_names.begin();
std::list<std::vector<int> >::iterator lists_i = index_groups.begin();
for ( ; names_i != index_group_names.end() ; names_i++, lists_i++) {
cvm::log(" "+(*names_i)+" ("+cvm::to_str(lists_i->size())+" atoms).\n");
}
return (cvm::get_error() ? COLVARS_ERROR : COLVARS_OK);
}
int cvm::load_atoms(char const *file_name,
cvm::atom_group &atoms,
std::string const &pdb_field,
double const pdb_field_value)
{
return proxy->load_atoms(file_name, atoms, pdb_field, pdb_field_value);
}
int cvm::load_coords(char const *file_name,
std::vector<cvm::atom_pos> &pos,
const std::vector<int> &indices,
std::string const &pdb_field,
double const pdb_field_value)
{
// Differentiate between PDB and XYZ files
// for XYZ files, use CVM internal parser
// otherwise call proxy function for PDB
std::string const ext(strlen(file_name) > 4 ? (file_name + (strlen(file_name) - 4)) : file_name);
if (colvarparse::to_lower_cppstr(ext) == std::string(".xyz")) {
if ( pdb_field.size() > 0 ) {
cvm::error("Error: PDB column may not be specified for XYZ coordinate file.\n", INPUT_ERROR);
return COLVARS_ERROR;
}
return cvm::load_coords_xyz(file_name, pos, indices);
} else {
return proxy->load_coords(file_name, pos, indices, pdb_field, pdb_field_value);
}
}
int cvm::load_coords_xyz(char const *filename,
std::vector<atom_pos> &pos,
const std::vector<int> &indices)
{
std::ifstream xyz_is(filename);
unsigned int natoms;
char symbol[256];
std::string line;
if ( ! (xyz_is >> natoms) ) {
cvm::error("Error: cannot parse XYZ file "
+ std::string(filename) + ".\n", INPUT_ERROR);
}
// skip comment line
std::getline(xyz_is, line);
std::getline(xyz_is, line);
xyz_is.width(255);
std::vector<atom_pos>::iterator pos_i = pos.begin();
if (pos.size() != natoms) { // Use specified indices
int next = 0; // indices are zero-based
std::vector<int>::const_iterator index = indices.begin();
for ( ; pos_i != pos.end() ; pos_i++, index++) {
while ( next < *index ) {
std::getline(xyz_is, line);
next++;
}
xyz_is >> symbol;
xyz_is >> (*pos_i)[0] >> (*pos_i)[1] >> (*pos_i)[2];
}
} else { // Use all positions
for ( ; pos_i != pos.end() ; pos_i++) {
xyz_is >> symbol;
xyz_is >> (*pos_i)[0] >> (*pos_i)[1] >> (*pos_i)[2];
}
}
return (cvm::get_error() ? COLVARS_ERROR : COLVARS_OK);
}
// static pointers
std::vector<colvar *> colvarmodule::colvars;
std::vector<colvarbias *> colvarmodule::biases;
size_t colvarmodule::n_abf_biases = 0;
size_t colvarmodule::n_rest_biases = 0;
size_t colvarmodule::n_histo_biases = 0;
size_t colvarmodule::n_meta_biases = 0;
colvarproxy *colvarmodule::proxy = NULL;
// static runtime data
cvm::real colvarmodule::debug_gradients_step_size = 1.0e-07;
int colvarmodule::errorCode = 0;
long colvarmodule::it = 0;
long colvarmodule::it_restart = 0;
size_t colvarmodule::restart_out_freq = 0;
size_t colvarmodule::cv_traj_freq = 0;
size_t colvarmodule::depth_s = 0;
std::vector<size_t> colvarmodule::depth_v(0);
bool colvarmodule::b_analysis = false;
std::list<std::string> colvarmodule::index_group_names;
std::list<std::vector<int> > colvarmodule::index_groups;
bool colvarmodule::use_scripted_forces = false;
bool colvarmodule::scripting_after_biases = true;
// file name prefixes
std::string colvarmodule::output_prefix = "";
std::string colvarmodule::restart_in_name = "";
// i/o constants
size_t const colvarmodule::it_width = 12;
size_t const colvarmodule::cv_prec = 14;
size_t const colvarmodule::cv_width = 21;
size_t const colvarmodule::en_prec = 14;
size_t const colvarmodule::en_width = 21;
std::string const colvarmodule::line_marker =
"----------------------------------------------------------------------\n";

Event Timeline