1276 lines
37 KiB
C++
1276 lines
37 KiB
C++
// -*- c++ -*-
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// This file is part of the Collective Variables module (Colvars).
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// The original version of Colvars and its updates are located at:
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// https://github.com/Colvars/colvars
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// Please update all Colvars source files before making any changes.
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// If you wish to distribute your changes, please submit them to the
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// Colvars repository at GitHub.
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#include <ctime>
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#include "colvarmodule.h"
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#include "colvarvalue.h"
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#include "colvarparse.h"
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#include "colvar.h"
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#include "colvargrid.h"
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#include "colvargrid_def.h"
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colvar_grid_count::colvar_grid_count()
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: colvar_grid<size_t>()
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{
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mult = 1;
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}
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colvar_grid_count::colvar_grid_count(std::vector<int> const &nx_i,
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size_t const &def_count)
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: colvar_grid<size_t>(nx_i, def_count, 1)
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{}
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colvar_grid_count::colvar_grid_count(std::vector<colvar *> &colvars,
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size_t const &def_count,
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bool margin)
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: colvar_grid<size_t>(colvars, def_count, 1, margin)
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{}
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std::string colvar_grid_count::get_state_params() const
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{
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return colvar_grid<size_t>::get_state_params();
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}
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int colvar_grid_count::parse_params(std::string const &conf,
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colvarparse::Parse_Mode const parse_mode)
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{
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return colvar_grid<size_t>::parse_params(conf, parse_mode);
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}
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std::istream & colvar_grid_count::read_restart(std::istream &is)
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{
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return colvar_grid<size_t>::read_restart(is);
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}
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cvm::memory_stream & colvar_grid_count::read_restart(cvm::memory_stream &is)
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{
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return colvar_grid<size_t>::read_restart(is);
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}
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std::ostream & colvar_grid_count::write_restart(std::ostream &os)
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{
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return colvar_grid<size_t>::write_restart(os);
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}
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cvm::memory_stream & colvar_grid_count::write_restart(cvm::memory_stream &os)
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{
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return colvar_grid<size_t>::write_restart(os);
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}
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std::istream &colvar_grid_count::read_raw(std::istream &is)
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{
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return colvar_grid<size_t>::read_raw(is);
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}
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cvm::memory_stream &colvar_grid_count::read_raw(cvm::memory_stream &is)
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{
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return colvar_grid<size_t>::read_raw(is);
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}
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std::ostream &colvar_grid_count::write_raw(std::ostream &os, size_t const buf_size) const
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{
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return colvar_grid<size_t>::write_raw(os, buf_size);
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}
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cvm::memory_stream &colvar_grid_count::write_raw(cvm::memory_stream &os,
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size_t const buf_size) const
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{
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return colvar_grid<size_t>::write_raw(os, buf_size);
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}
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std::istream & colvar_grid_count::read_multicol(std::istream &is, bool add)
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{
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return colvar_grid<size_t>::read_multicol(is, add);
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}
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int colvar_grid_count::read_multicol(std::string const &filename,
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std::string description,
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bool add)
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{
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return colvar_grid<size_t>::read_multicol(filename, description, add);
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}
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std::ostream & colvar_grid_count::write_multicol(std::ostream &os) const
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{
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return colvar_grid<size_t>::write_multicol(os);
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}
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int colvar_grid_count::write_multicol(std::string const &filename,
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std::string description) const
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{
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return colvar_grid<size_t>::write_multicol(filename, description);
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}
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std::ostream & colvar_grid_count::write_opendx(std::ostream &os) const
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{
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return colvar_grid<size_t>::write_opendx(os);
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}
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int colvar_grid_count::write_opendx(std::string const &filename,
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std::string description) const
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{
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return colvar_grid<size_t>::write_opendx(filename, description);
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}
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colvar_grid_scalar::colvar_grid_scalar()
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: colvar_grid<cvm::real>(), samples(NULL)
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{}
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colvar_grid_scalar::colvar_grid_scalar(colvar_grid_scalar const &g)
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: colvar_grid<cvm::real>(g), samples(NULL)
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{
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}
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colvar_grid_scalar::colvar_grid_scalar(std::vector<int> const &nx_i)
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: colvar_grid<cvm::real>(nx_i, 0.0, 1), samples(NULL)
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{
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}
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colvar_grid_scalar::colvar_grid_scalar(std::vector<colvar *> &colvars, bool margin)
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: colvar_grid<cvm::real>(colvars, 0.0, 1, margin), samples(NULL)
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{
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}
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colvar_grid_scalar::~colvar_grid_scalar()
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{
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}
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std::string colvar_grid_scalar::get_state_params() const
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{
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return colvar_grid<cvm::real>::get_state_params();
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}
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int colvar_grid_scalar::parse_params(std::string const &conf,
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colvarparse::Parse_Mode const parse_mode)
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{
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return colvar_grid<cvm::real>::parse_params(conf, parse_mode);
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}
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std::istream &colvar_grid_scalar::read_restart(std::istream &is)
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{
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return colvar_grid<cvm::real>::read_restart(is);
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}
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cvm::memory_stream &colvar_grid_scalar::read_restart(cvm::memory_stream &is)
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{
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return colvar_grid<cvm::real>::read_restart(is);
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}
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std::ostream &colvar_grid_scalar::write_restart(std::ostream &os)
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{
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return colvar_grid<cvm::real>::write_restart(os);
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}
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cvm::memory_stream &colvar_grid_scalar::write_restart(cvm::memory_stream &os)
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{
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return colvar_grid<cvm::real>::write_restart(os);
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}
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std::istream &colvar_grid_scalar::read_raw(std::istream &is)
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{
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return colvar_grid<cvm::real>::read_raw(is);
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}
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cvm::memory_stream &colvar_grid_scalar::read_raw(cvm::memory_stream &is)
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{
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return colvar_grid<cvm::real>::read_raw(is);
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}
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std::ostream &colvar_grid_scalar::write_raw(std::ostream &os, size_t const buf_size) const
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{
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return colvar_grid<cvm::real>::write_raw(os, buf_size);
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}
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cvm::memory_stream &colvar_grid_scalar::write_raw(cvm::memory_stream &os,
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size_t const buf_size) const
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{
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return colvar_grid<cvm::real>::write_raw(os, buf_size);
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}
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std::istream & colvar_grid_scalar::read_multicol(std::istream &is, bool add)
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{
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return colvar_grid<cvm::real>::read_multicol(is, add);
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}
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int colvar_grid_scalar::read_multicol(std::string const &filename,
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std::string description,
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bool add)
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{
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return colvar_grid<cvm::real>::read_multicol(filename, description, add);
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}
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std::ostream & colvar_grid_scalar::write_multicol(std::ostream &os) const
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{
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return colvar_grid<cvm::real>::write_multicol(os);
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}
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int colvar_grid_scalar::write_multicol(std::string const &filename,
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std::string description) const
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{
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return colvar_grid<cvm::real>::write_multicol(filename, description);
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}
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std::ostream & colvar_grid_scalar::write_opendx(std::ostream &os) const
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{
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return colvar_grid<cvm::real>::write_opendx(os);
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}
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int colvar_grid_scalar::write_opendx(std::string const &filename,
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std::string description) const
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{
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return colvar_grid<cvm::real>::write_opendx(filename, description);
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}
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cvm::real colvar_grid_scalar::maximum_value() const
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{
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cvm::real max = data[0];
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for (size_t i = 0; i < nt; i++) {
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if (data[i] > max) max = data[i];
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}
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return max;
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}
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cvm::real colvar_grid_scalar::minimum_value() const
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{
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cvm::real min = data[0];
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for (size_t i = 0; i < nt; i++) {
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if (data[i] < min) min = data[i];
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}
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return min;
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}
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cvm::real colvar_grid_scalar::minimum_pos_value() const
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{
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cvm::real minpos = data[0];
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size_t i;
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for (i = 0; i < nt; i++) {
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if(data[i] > 0) {
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minpos = data[i];
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break;
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}
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}
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for (i = 0; i < nt; i++) {
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if (data[i] > 0 && data[i] < minpos) minpos = data[i];
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}
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return minpos;
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}
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cvm::real colvar_grid_scalar::integral() const
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{
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cvm::real sum = 0.0;
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for (size_t i = 0; i < nt; i++) {
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sum += data[i];
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}
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cvm::real bin_volume = 1.0;
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for (size_t id = 0; id < widths.size(); id++) {
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bin_volume *= widths[id];
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}
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return bin_volume * sum;
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}
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cvm::real colvar_grid_scalar::entropy() const
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{
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cvm::real sum = 0.0;
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for (size_t i = 0; i < nt; i++) {
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if (data[i] >0) {
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sum += -1.0 * data[i] * cvm::logn(data[i]);
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}
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}
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cvm::real bin_volume = 1.0;
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for (size_t id = 0; id < widths.size(); id++) {
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bin_volume *= widths[id];
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}
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return bin_volume * sum;
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}
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/// \brief Return the RMSD between this grid's data and another one
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/// Grids must have the same dimensions.
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cvm::real colvar_grid_scalar::grid_rmsd(colvar_grid_scalar const &other_grid) const
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{
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if (other_grid.data.size() != this->data.size()) {
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cvm::error("Error: trying to subtract two grids with "
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"different size.\n");
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return -1.;
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}
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cvm::real sum2 = 0.0;
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if (samples && other_grid.samples) {
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for (size_t i = 0; i < data.size(); i++) {
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size_t n = samples->get_value(i);
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cvm::real us = n ? data[i] / n : 0.0;
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n = other_grid.samples->get_value(i);
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cvm::real them = n ? other_grid.data[i ] / n : 0.0;
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cvm::real d = us - them;
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sum2 += d*d;
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}
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} else {
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for (size_t i = 0; i < data.size(); i++) {
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cvm::real d = other_grid.data[i] - data[i];
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sum2 += d*d;
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}
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}
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return sqrt(sum2/this->data.size());
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}
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colvar_grid_gradient::colvar_grid_gradient()
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: colvar_grid<cvm::real>(), samples(NULL), full_samples(0), min_samples(0)
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{}
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colvar_grid_gradient::colvar_grid_gradient(std::vector<int> const &nx_i)
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: colvar_grid<cvm::real>(nx_i, 0.0, nx_i.size()), samples(NULL), full_samples(0), min_samples(0)
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{}
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colvar_grid_gradient::colvar_grid_gradient(std::vector<colvar *> &colvars)
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: colvar_grid<cvm::real>(colvars, 0.0, colvars.size()), samples(NULL), full_samples(0), min_samples(0)
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{}
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colvar_grid_gradient::colvar_grid_gradient(std::vector<colvar *> &colvars, std::shared_ptr<colvar_grid_count> samples_in)
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: colvar_grid<cvm::real>(colvars, 0.0, colvars.size()), samples(samples_in), full_samples(0), min_samples(0)
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{
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samples_in->has_parent_data = true;
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}
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colvar_grid_gradient::colvar_grid_gradient(std::string &filename)
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: colvar_grid<cvm::real>(),
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samples(NULL)
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{
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std::istream &is = cvm::main()->proxy->input_stream(filename,
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"gradient file");
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if (!is) {
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return;
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}
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// Data in the header: nColvars, then for each
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// xiMin, dXi, nPoints, periodic flag
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std::string hash;
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size_t i;
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if ( !(is >> hash) || (hash != "#") ) {
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cvm::error("Error reading grid at position "+
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cvm::to_str(static_cast<size_t>(is.tellg()))+
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" in stream(read \"" + hash + "\")\n");
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return;
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}
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is >> nd;
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if (nd > 50) {
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cvm::error("Error: excessive number of dimensions in file \""+
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filename+"\". Please ensure that the file is not corrupt.\n",
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COLVARS_INPUT_ERROR);
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return;
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}
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mult = nd;
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std::vector<cvm::real> lower_in(nd), widths_in(nd);
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std::vector<int> nx_in(nd);
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std::vector<int> periodic_in(nd);
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for (i = 0; i < nd; i++ ) {
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if ( !(is >> hash) || (hash != "#") ) {
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cvm::error("Error reading grid at position "+
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cvm::to_str(static_cast<size_t>(is.tellg()))+
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" in stream(read \"" + hash + "\")\n");
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return;
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}
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is >> lower_in[i] >> widths_in[i] >> nx_in[i] >> periodic_in[i];
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}
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this->setup(nx_in, 0., mult);
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widths = widths_in;
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for (i = 0; i < nd; i++ ) {
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lower_boundaries.push_back(colvarvalue(lower_in[i]));
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periodic.push_back(static_cast<bool>(periodic_in[i]));
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}
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// Reset the istream for read_multicol, which expects the whole file
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is.clear();
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is.seekg(0);
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read_multicol(is);
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cvm::main()->proxy->close_input_stream(filename);
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}
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std::string colvar_grid_gradient::get_state_params() const
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{
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return colvar_grid<cvm::real>::get_state_params();
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}
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int colvar_grid_gradient::parse_params(std::string const &conf,
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colvarparse::Parse_Mode const parse_mode)
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{
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return colvar_grid<cvm::real>::parse_params(conf, parse_mode);
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}
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std::istream &colvar_grid_gradient::read_restart(std::istream &is)
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{
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return colvar_grid<cvm::real>::read_restart(is);
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}
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cvm::memory_stream &colvar_grid_gradient::read_restart(cvm::memory_stream &is)
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{
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return colvar_grid<cvm::real>::read_restart(is);
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}
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std::ostream &colvar_grid_gradient::write_restart(std::ostream &os)
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{
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return colvar_grid<cvm::real>::write_restart(os);
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}
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cvm::memory_stream &colvar_grid_gradient::write_restart(cvm::memory_stream &os)
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{
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return colvar_grid<cvm::real>::write_restart(os);
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}
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std::istream &colvar_grid_gradient::read_raw(std::istream &is)
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{
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return colvar_grid<cvm::real>::read_raw(is);
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}
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cvm::memory_stream &colvar_grid_gradient::read_raw(cvm::memory_stream &is)
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{
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return colvar_grid<cvm::real>::read_raw(is);
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}
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std::ostream &colvar_grid_gradient::write_raw(std::ostream &os, size_t const buf_size) const
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{
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return colvar_grid<cvm::real>::write_raw(os, buf_size);
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}
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cvm::memory_stream &colvar_grid_gradient::write_raw(cvm::memory_stream &os,
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size_t const buf_size) const
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{
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return colvar_grid<cvm::real>::write_raw(os, buf_size);
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}
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std::istream & colvar_grid_gradient::read_multicol(std::istream &is, bool add)
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{
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return colvar_grid<cvm::real>::read_multicol(is, add);
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}
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int colvar_grid_gradient::read_multicol(std::string const &filename,
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std::string description,
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bool add)
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{
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return colvar_grid<cvm::real>::read_multicol(filename, description, add);
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}
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std::ostream & colvar_grid_gradient::write_multicol(std::ostream &os) const
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{
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return colvar_grid<cvm::real>::write_multicol(os);
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}
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int colvar_grid_gradient::write_multicol(std::string const &filename,
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std::string description) const
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{
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return colvar_grid<cvm::real>::write_multicol(filename, description);
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}
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std::ostream & colvar_grid_gradient::write_opendx(std::ostream &os) const
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{
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return colvar_grid<cvm::real>::write_opendx(os);
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}
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int colvar_grid_gradient::write_opendx(std::string const &filename,
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std::string description) const
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{
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return colvar_grid<cvm::real>::write_opendx(filename, description);
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}
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void colvar_grid_gradient::write_1D_integral(std::ostream &os)
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{
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|
cvm::real bin, min, integral;
|
|
std::vector<cvm::real> int_vals;
|
|
|
|
os << "# xi A(xi)\n";
|
|
|
|
if (cv.size() != 1) {
|
|
cvm::error("Cannot write integral for multi-dimensional gradient grids.");
|
|
return;
|
|
}
|
|
|
|
integral = 0.0;
|
|
int_vals.push_back(0.0);
|
|
min = 0.0;
|
|
|
|
// correction for periodic colvars, so that the PMF is periodic
|
|
cvm::real corr;
|
|
if (periodic[0]) {
|
|
corr = average();
|
|
} else {
|
|
corr = 0.0;
|
|
}
|
|
|
|
for (std::vector<int> ix = new_index(); index_ok(ix); incr(ix)) {
|
|
|
|
if (samples) {
|
|
size_t const samples_here = samples->value(ix);
|
|
if (samples_here)
|
|
integral += (value(ix) / cvm::real(samples_here) - corr) * cv[0]->width;
|
|
} else {
|
|
integral += (value(ix) - corr) * cv[0]->width;
|
|
}
|
|
|
|
if ( integral < min ) min = integral;
|
|
int_vals.push_back(integral);
|
|
}
|
|
|
|
bin = 0.0;
|
|
for ( int i = 0; i < nx[0]; i++, bin += 1.0 ) {
|
|
os << std::setw(10) << cv[0]->lower_boundary.real_value + cv[0]->width * bin << " "
|
|
<< std::setw(cvm::cv_width)
|
|
<< std::setprecision(cvm::cv_prec)
|
|
<< int_vals[i] - min << "\n";
|
|
}
|
|
|
|
os << std::setw(10) << cv[0]->lower_boundary.real_value + cv[0]->width * bin << " "
|
|
<< std::setw(cvm::cv_width)
|
|
<< std::setprecision(cvm::cv_prec)
|
|
<< int_vals[nx[0]] - min << "\n";
|
|
|
|
return;
|
|
}
|
|
|
|
|
|
/// \brief Return the RMSD between this grid's data and another one
|
|
/// Grids must have the same dimensions.
|
|
cvm::real colvar_grid_gradient::grid_rmsd(colvar_grid_gradient const &other_grid) const
|
|
{
|
|
if (other_grid.multiplicity() != this->multiplicity()) {
|
|
cvm::error("Error: trying to subtract two grids with "
|
|
"different multiplicity.\n");
|
|
return -1.;
|
|
}
|
|
|
|
if (other_grid.data.size() != this->data.size()) {
|
|
cvm::error("Error: trying to subtract two grids with "
|
|
"different size.\n");
|
|
return -1.;
|
|
}
|
|
|
|
cvm::real sum2 = 0.0;
|
|
std::vector<int> ix;
|
|
size_t imult;
|
|
for (ix = new_index(); index_ok(ix); incr(ix)) {
|
|
for (imult = 0; imult < this->multiplicity(); imult++) {
|
|
cvm::real d = this->value_output(ix, imult) - other_grid.value_output(ix, imult);
|
|
sum2 += d*d;
|
|
}
|
|
}
|
|
return sqrt(sum2/this->data.size());
|
|
}
|
|
|
|
|
|
integrate_potential::integrate_potential(std::vector<colvar *> &colvars, std::shared_ptr<colvar_grid_gradient> gradients)
|
|
: colvar_grid_scalar(colvars, true),
|
|
b_smoothed(false),
|
|
gradients(gradients)
|
|
{
|
|
// parent class colvar_grid_scalar is constructed with margin option set to true
|
|
// hence PMF grid is wider than gradient grid if non-PBC
|
|
|
|
if (nd > 1) {
|
|
cvm::main()->cite_feature("Poisson integration of 2D/3D free energy surfaces");
|
|
divergence.resize(nt);
|
|
|
|
// Compute inverse of Laplacian diagonal for Jacobi preconditioning
|
|
// For now all code related to preconditioning is commented out
|
|
// until a method better than Jacobi is implemented
|
|
// cvm::log("Preparing inverse diagonal for preconditioning...\n");
|
|
// inv_lap_diag.resize(nt);
|
|
// std::vector<cvm::real> id(nt), lap_col(nt);
|
|
// for (int i = 0; i < nt; i++) {
|
|
// if (i % (nt / 100) == 0)
|
|
// cvm::log(cvm::to_str(i));
|
|
// id[i] = 1.;
|
|
// atimes(id, lap_col);
|
|
// id[i] = 0.;
|
|
// inv_lap_diag[i] = 1. / lap_col[i];
|
|
// }
|
|
// cvm::log("Done.\n");
|
|
}
|
|
}
|
|
|
|
|
|
integrate_potential::integrate_potential(std::shared_ptr<colvar_grid_gradient> gradients)
|
|
: b_smoothed(false),
|
|
gradients(gradients)
|
|
{
|
|
nd = gradients->num_variables();
|
|
nx = gradients->number_of_points_vec();
|
|
widths = gradients->widths;
|
|
periodic = gradients->periodic;
|
|
|
|
// Expand grid by 1 bin in non-periodic dimensions
|
|
for (size_t i = 0; i < nd; i++ ) {
|
|
if (!periodic[i]) nx[i]++;
|
|
// Shift the grid by half the bin width (values at edges instead of center of bins)
|
|
lower_boundaries.push_back(gradients->lower_boundaries[i].real_value - 0.5 * widths[i]);
|
|
}
|
|
|
|
setup(nx);
|
|
|
|
if (nd > 1) {
|
|
divergence.resize(nt);
|
|
}
|
|
}
|
|
|
|
|
|
int integrate_potential::integrate(const int itmax, const cvm::real &tol, cvm::real & err, bool verbose)
|
|
{
|
|
int iter = 0;
|
|
|
|
if (nd == 1) {
|
|
|
|
cvm::real sum = 0.0;
|
|
cvm::real corr;
|
|
if ( periodic[0] ) {
|
|
corr = gradients->average(); // Enforce PBC by subtracting average gradient
|
|
} else {
|
|
corr = 0.0;
|
|
}
|
|
std::vector<int> ix;
|
|
// Iterate over valid indices in gradient grid
|
|
for (ix = new_index(); gradients->index_ok(ix); incr(ix)) {
|
|
set_value(ix, sum);
|
|
cvm::real val = gradients->value_output_smoothed(ix, b_smoothed);
|
|
sum += (val - corr) * widths[0];
|
|
}
|
|
if (index_ok(ix)) {
|
|
// This will happen if non-periodic: then PMF grid has one extra bin wrt gradient grid
|
|
// If not, sum should be zero
|
|
set_value(ix, sum);
|
|
}
|
|
|
|
} else if (nd <= 3) {
|
|
|
|
nr_linbcg_sym(divergence, data, tol, itmax, iter, err);
|
|
if (verbose)
|
|
cvm::log("Integrated in " + cvm::to_str(iter) + " steps, error: " + cvm::to_str(err));
|
|
|
|
} else {
|
|
cvm::error("Cannot integrate PMF in dimension > 3\n");
|
|
}
|
|
|
|
return iter;
|
|
}
|
|
|
|
|
|
void integrate_potential::set_div()
|
|
{
|
|
if (nd == 1) return;
|
|
for (std::vector<int> ix = new_index(); index_ok(ix); incr(ix)) {
|
|
update_div_local(ix);
|
|
}
|
|
}
|
|
|
|
|
|
void integrate_potential::update_div_neighbors(const std::vector<int> &ix0)
|
|
{
|
|
std::vector<int> ix(ix0);
|
|
int i, j, k;
|
|
|
|
// If not periodic, expanded grid ensures that upper neighbors of ix0 are valid grid points
|
|
if (nd == 1) {
|
|
return;
|
|
|
|
} else if (nd == 2) {
|
|
|
|
update_div_local(ix);
|
|
ix[0]++; wrap(ix);
|
|
update_div_local(ix);
|
|
ix[1]++; wrap(ix);
|
|
update_div_local(ix);
|
|
ix[0]--; wrap(ix);
|
|
update_div_local(ix);
|
|
|
|
} else if (nd == 3) {
|
|
|
|
for (i = 0; i<2; i++) {
|
|
ix[1] = ix0[1];
|
|
for (j = 0; j<2; j++) {
|
|
ix[2] = ix0[2];
|
|
for (k = 0; k<2; k++) {
|
|
wrap(ix);
|
|
update_div_local(ix);
|
|
ix[2]++;
|
|
}
|
|
ix[1]++;
|
|
}
|
|
ix[0]++;
|
|
}
|
|
}
|
|
}
|
|
|
|
|
|
void integrate_potential::get_grad(cvm::real * g, std::vector<int> &ix)
|
|
{
|
|
size_t i;
|
|
bool edge = gradients->wrap_detect_edge(ix); // Detect edge if non-PBC
|
|
|
|
if (edge) {
|
|
for ( i = 0; i<nd; i++ ) {
|
|
g[i] = 0.0;
|
|
}
|
|
return;
|
|
}
|
|
|
|
gradients->vector_value_smoothed(ix, g, b_smoothed);
|
|
}
|
|
|
|
|
|
void integrate_potential::update_div_local(const std::vector<int> &ix0)
|
|
{
|
|
const size_t linear_index = address(ix0);
|
|
int i, j, k;
|
|
std::vector<int> ix = ix0;
|
|
|
|
if (nd == 2) {
|
|
// gradients at grid points surrounding the current scalar grid point
|
|
cvm::real g00[2], g01[2], g10[2], g11[2];
|
|
|
|
get_grad(g11, ix);
|
|
ix[0] = ix0[0] - 1;
|
|
get_grad(g01, ix);
|
|
ix[1] = ix0[1] - 1;
|
|
get_grad(g00, ix);
|
|
ix[0] = ix0[0];
|
|
get_grad(g10, ix);
|
|
|
|
divergence[linear_index] = ((g10[0]-g00[0] + g11[0]-g01[0]) / widths[0]
|
|
+ (g01[1]-g00[1] + g11[1]-g10[1]) / widths[1]) * 0.5;
|
|
} else if (nd == 3) {
|
|
cvm::real gc[24]; // stores 3d gradients in 8 contiguous bins
|
|
int index = 0;
|
|
|
|
ix[0] = ix0[0] - 1;
|
|
for (i = 0; i<2; i++) {
|
|
ix[1] = ix0[1] - 1;
|
|
for (j = 0; j<2; j++) {
|
|
ix[2] = ix0[2] - 1;
|
|
for (k = 0; k<2; k++) {
|
|
get_grad(gc + index, ix);
|
|
index += 3;
|
|
ix[2]++;
|
|
}
|
|
ix[1]++;
|
|
}
|
|
ix[0]++;
|
|
}
|
|
|
|
divergence[linear_index] =
|
|
((gc[3*4]-gc[0] + gc[3*5]-gc[3*1] + gc[3*6]-gc[3*2] + gc[3*7]-gc[3*3])
|
|
/ widths[0]
|
|
+ (gc[3*2+1]-gc[0+1] + gc[3*3+1]-gc[3*1+1] + gc[3*6+1]-gc[3*4+1] + gc[3*7+1]-gc[3*5+1])
|
|
/ widths[1]
|
|
+ (gc[3*1+2]-gc[0+2] + gc[3*3+2]-gc[3*2+2] + gc[3*5+2]-gc[3*4+2] + gc[3*7+2]-gc[3*6+2])
|
|
/ widths[2]) * 0.25;
|
|
}
|
|
}
|
|
|
|
|
|
/// Multiplication by sparse matrix representing Laplacian
|
|
/// NOTE: Laplacian must be symmetric for solving with CG
|
|
void integrate_potential::atimes(const std::vector<cvm::real> &A, std::vector<cvm::real> &LA)
|
|
{
|
|
if (nd == 2) {
|
|
// DIMENSION 2
|
|
|
|
size_t index, index2;
|
|
int i, j;
|
|
cvm::real fact;
|
|
const cvm::real ffx = 1.0 / (widths[0] * widths[0]);
|
|
const cvm::real ffy = 1.0 / (widths[1] * widths[1]);
|
|
const int h = nx[1];
|
|
const int w = nx[0];
|
|
// offsets for 4 reference points of the Laplacian stencil
|
|
int xm = -h;
|
|
int xp = h;
|
|
int ym = -1;
|
|
int yp = 1;
|
|
|
|
// NOTE on performance: this version is slightly sub-optimal because
|
|
// it contains two double loops on the core of the array (for x and y terms)
|
|
// The slightly faster version is in commit 0254cb5a2958cb2e135f268371c4b45fad34866b
|
|
// yet it is much uglier, and probably horrible to extend to dimension 3
|
|
// All terms in the matrix are assigned (=) during the x loops, then updated (+=)
|
|
// with the y (and z) contributions
|
|
|
|
|
|
// All x components except on x edges
|
|
index = h; // Skip first column
|
|
|
|
// Halve the term on y edges (if any) to preserve symmetry of the Laplacian matrix
|
|
// (Long Chen, Finite Difference Methods, UCI, 2017)
|
|
fact = periodic[1] ? 1.0 : 0.5;
|
|
|
|
for (i=1; i<w-1; i++) {
|
|
// Full range of j, but factor may change on y edges (j == 0 and j == h-1)
|
|
LA[index] = fact * ffx * (A[index + xm] + A[index + xp] - 2.0 * A[index]);
|
|
index++;
|
|
for (j=1; j<h-1; j++) {
|
|
LA[index] = ffx * (A[index + xm] + A[index + xp] - 2.0 * A[index]);
|
|
index++;
|
|
}
|
|
LA[index] = fact * ffx * (A[index + xm] + A[index + xp] - 2.0 * A[index]);
|
|
index++;
|
|
}
|
|
// Edges along x (x components only)
|
|
index = 0L; // Follows left edge
|
|
index2 = h * static_cast<size_t>(w - 1); // Follows right edge
|
|
if (periodic[0]) {
|
|
xm = h * (w - 1);
|
|
xp = h;
|
|
fact = periodic[1] ? 1.0 : 0.5;
|
|
LA[index] = fact * ffx * (A[index + xm] + A[index + xp] - 2.0 * A[index]);
|
|
LA[index2] = fact * ffx * (A[index2 - xp] + A[index2 - xm] - 2.0 * A[index2]);
|
|
index++;
|
|
index2++;
|
|
for (j=1; j<h-1; j++) {
|
|
LA[index] = ffx * (A[index + xm] + A[index + xp] - 2.0 * A[index]);
|
|
LA[index2] = ffx * (A[index2 - xp] + A[index2 - xm] - 2.0 * A[index2]);
|
|
index++;
|
|
index2++;
|
|
}
|
|
LA[index] = fact * ffx * (A[index + xm] + A[index + xp] - 2.0 * A[index]);
|
|
LA[index2] = fact * ffx * (A[index2 - xp] + A[index2 - xm] - 2.0 * A[index2]);
|
|
} else {
|
|
xm = -h;
|
|
xp = h;
|
|
fact = periodic[1] ? 1.0 : 0.5; // Halve in corners in full PBC only
|
|
// lower corner, "j == 0"
|
|
LA[index] = fact * ffx * (A[index + xp] - A[index]);
|
|
LA[index2] = fact * ffx * (A[index2 + xm] - A[index2]);
|
|
index++;
|
|
index2++;
|
|
for (j=1; j<h-1; j++) {
|
|
// x gradient (+ y term of laplacian, calculated below)
|
|
LA[index] = ffx * (A[index + xp] - A[index]);
|
|
LA[index2] = ffx * (A[index2 + xm] - A[index2]);
|
|
index++;
|
|
index2++;
|
|
}
|
|
// upper corner, j == h-1
|
|
LA[index] = fact * ffx * (A[index + xp] - A[index]);
|
|
LA[index2] = fact * ffx * (A[index2 + xm] - A[index2]);
|
|
}
|
|
|
|
// Now adding all y components
|
|
// All y components except on y edges
|
|
index = 1; // Skip first element (in first row)
|
|
|
|
fact = periodic[0] ? 1.0 : 0.5; // for i == 0
|
|
for (i=0; i<w; i++) {
|
|
// Factor of 1/2 on x edges if non-periodic
|
|
if (i == 1) fact = 1.0;
|
|
if (i == w - 1) fact = periodic[0] ? 1.0 : 0.5;
|
|
for (j=1; j<h-1; j++) {
|
|
LA[index] += fact * ffy * (A[index + ym] + A[index + yp] - 2.0 * A[index]);
|
|
index++;
|
|
}
|
|
index += 2; // skip the edges and move to next column
|
|
}
|
|
// Edges along y (y components only)
|
|
index = 0L; // Follows bottom edge
|
|
index2 = h - 1; // Follows top edge
|
|
if (periodic[1]) {
|
|
fact = periodic[0] ? 1.0 : 0.5;
|
|
ym = h - 1;
|
|
yp = 1;
|
|
LA[index] += fact * ffy * (A[index + ym] + A[index + yp] - 2.0 * A[index]);
|
|
LA[index2] += fact * ffy * (A[index2 - yp] + A[index2 - ym] - 2.0 * A[index2]);
|
|
index += h;
|
|
index2 += h;
|
|
for (i=1; i<w-1; i++) {
|
|
LA[index] += ffy * (A[index + ym] + A[index + yp] - 2.0 * A[index]);
|
|
LA[index2] += ffy * (A[index2 - yp] + A[index2 - ym] - 2.0 * A[index2]);
|
|
index += h;
|
|
index2 += h;
|
|
}
|
|
LA[index] += fact * ffy * (A[index + ym] + A[index + yp] - 2.0 * A[index]);
|
|
LA[index2] += fact * ffy * (A[index2 - yp] + A[index2 - ym] - 2.0 * A[index2]);
|
|
} else {
|
|
ym = -1;
|
|
yp = 1;
|
|
fact = periodic[0] ? 1.0 : 0.5; // Halve in corners in full PBC only
|
|
// Left corner
|
|
LA[index] += fact * ffy * (A[index + yp] - A[index]);
|
|
LA[index2] += fact * ffy * (A[index2 + ym] - A[index2]);
|
|
index += h;
|
|
index2 += h;
|
|
for (i=1; i<w-1; i++) {
|
|
// y gradient (+ x term of laplacian, calculated above)
|
|
LA[index] += ffy * (A[index + yp] - A[index]);
|
|
LA[index2] += ffy * (A[index2 + ym] - A[index2]);
|
|
index += h;
|
|
index2 += h;
|
|
}
|
|
// Right corner
|
|
LA[index] += fact * ffy * (A[index + yp] - A[index]);
|
|
LA[index2] += fact * ffy * (A[index2 + ym] - A[index2]);
|
|
}
|
|
|
|
} else if (nd == 3) {
|
|
// DIMENSION 3
|
|
|
|
int i, j, k;
|
|
size_t index, index2;
|
|
cvm::real fact = 1.0;
|
|
const cvm::real ffx = 1.0 / (widths[0] * widths[0]);
|
|
const cvm::real ffy = 1.0 / (widths[1] * widths[1]);
|
|
const cvm::real ffz = 1.0 / (widths[2] * widths[2]);
|
|
const int h = nx[2]; // height
|
|
const int d = nx[1]; // depth
|
|
const int w = nx[0]; // width
|
|
// offsets for 6 reference points of the Laplacian stencil
|
|
int xm = -d * h;
|
|
int xp = d * h;
|
|
int ym = -h;
|
|
int yp = h;
|
|
int zm = -1;
|
|
int zp = 1;
|
|
|
|
cvm::real factx = periodic[0] ? 1 : 0.5; // factor to be applied on x edges
|
|
cvm::real facty = periodic[1] ? 1 : 0.5; // same for y
|
|
cvm::real factz = periodic[2] ? 1 : 0.5; // same for z
|
|
cvm::real ifactx = 1 / factx;
|
|
cvm::real ifacty = 1 / facty;
|
|
cvm::real ifactz = 1 / factz;
|
|
|
|
// All x components except on x edges
|
|
index = d * static_cast<size_t>(h); // Skip left slab
|
|
fact = facty * factz;
|
|
for (i=1; i<w-1; i++) {
|
|
for (j=0; j<d; j++) { // full range of y
|
|
if (j == 1) fact *= ifacty;
|
|
if (j == d-1) fact *= facty;
|
|
LA[index] = fact * ffx * (A[index + xm] + A[index + xp] - 2.0 * A[index]);
|
|
index++;
|
|
fact *= ifactz;
|
|
for (k=1; k<h-1; k++) { // full range of z
|
|
LA[index] = fact * ffx * (A[index + xm] + A[index + xp] - 2.0 * A[index]);
|
|
index++;
|
|
}
|
|
fact *= factz;
|
|
LA[index] = fact * ffx * (A[index + xm] + A[index + xp] - 2.0 * A[index]);
|
|
index++;
|
|
}
|
|
}
|
|
// Edges along x (x components only)
|
|
index = 0L; // Follows left slab
|
|
index2 = static_cast<size_t>(d) * h * (w - 1); // Follows right slab
|
|
if (periodic[0]) {
|
|
xm = d * h * (w - 1);
|
|
xp = d * h;
|
|
fact = facty * factz;
|
|
for (j=0; j<d; j++) {
|
|
if (j == 1) fact *= ifacty;
|
|
if (j == d-1) fact *= facty;
|
|
LA[index] = fact * ffx * (A[index + xm] + A[index + xp] - 2.0 * A[index]);
|
|
LA[index2] = fact * ffx * (A[index2 - xp] + A[index2 - xm] - 2.0 * A[index2]);
|
|
index++;
|
|
index2++;
|
|
fact *= ifactz;
|
|
for (k=1; k<h-1; k++) {
|
|
LA[index] = fact * ffx * (A[index + xm] + A[index + xp] - 2.0 * A[index]);
|
|
LA[index2] = fact * ffx * (A[index2 - xp] + A[index2 - xm] - 2.0 * A[index2]);
|
|
index++;
|
|
index2++;
|
|
}
|
|
fact *= factz;
|
|
LA[index] = fact * ffx * (A[index + xm] + A[index + xp] - 2.0 * A[index]);
|
|
LA[index2] = fact * ffx * (A[index2 - xp] + A[index2 - xm] - 2.0 * A[index2]);
|
|
index++;
|
|
index2++;
|
|
}
|
|
} else {
|
|
xm = -d * h;
|
|
xp = d * h;
|
|
fact = facty * factz;
|
|
for (j=0; j<d; j++) {
|
|
if (j == 1) fact *= ifacty;
|
|
if (j == d-1) fact *= facty;
|
|
LA[index] = fact * ffx * (A[index + xp] - A[index]);
|
|
LA[index2] = fact * ffx * (A[index2 + xm] - A[index2]);
|
|
index++;
|
|
index2++;
|
|
fact *= ifactz;
|
|
for (k=1; k<h-1; k++) {
|
|
// x gradient (+ y, z terms of laplacian, calculated below)
|
|
LA[index] = fact * ffx * (A[index + xp] - A[index]);
|
|
LA[index2] = fact * ffx * (A[index2 + xm] - A[index2]);
|
|
index++;
|
|
index2++;
|
|
}
|
|
fact *= factz;
|
|
LA[index] = fact * ffx * (A[index + xp] - A[index]);
|
|
LA[index2] = fact * ffx * (A[index2 + xm] - A[index2]);
|
|
index++;
|
|
index2++;
|
|
}
|
|
}
|
|
|
|
// Now adding all y components
|
|
// All y components except on y edges
|
|
index = h; // Skip first column (in front slab)
|
|
fact = factx * factz;
|
|
for (i=0; i<w; i++) { // full range of x
|
|
if (i == 1) fact *= ifactx;
|
|
if (i == w-1) fact *= factx;
|
|
for (j=1; j<d-1; j++) {
|
|
LA[index] += fact * ffy * (A[index + ym] + A[index + yp] - 2.0 * A[index]);
|
|
index++;
|
|
fact *= ifactz;
|
|
for (k=1; k<h-1; k++) {
|
|
LA[index] += fact * ffy * (A[index + ym] + A[index + yp] - 2.0 * A[index]);
|
|
index++;
|
|
}
|
|
fact *= factz;
|
|
LA[index] += fact * ffy * (A[index + ym] + A[index + yp] - 2.0 * A[index]);
|
|
index++;
|
|
}
|
|
index += 2 * h; // skip columns in front and back slabs
|
|
}
|
|
// Edges along y (y components only)
|
|
index = 0L; // Follows front slab
|
|
index2 = h * static_cast<size_t>(d - 1); // Follows back slab
|
|
if (periodic[1]) {
|
|
ym = h * (d - 1);
|
|
yp = h;
|
|
fact = factx * factz;
|
|
for (i=0; i<w; i++) {
|
|
if (i == 1) fact *= ifactx;
|
|
if (i == w-1) fact *= factx;
|
|
LA[index] += fact * ffy * (A[index + ym] + A[index + yp] - 2.0 * A[index]);
|
|
LA[index2] += fact * ffy * (A[index2 - yp] + A[index2 - ym] - 2.0 * A[index2]);
|
|
index++;
|
|
index2++;
|
|
fact *= ifactz;
|
|
for (k=1; k<h-1; k++) {
|
|
LA[index] += fact * ffy * (A[index + ym] + A[index + yp] - 2.0 * A[index]);
|
|
LA[index2] += fact * ffy * (A[index2 - yp] + A[index2 - ym] - 2.0 * A[index2]);
|
|
index++;
|
|
index2++;
|
|
}
|
|
fact *= factz;
|
|
LA[index] += fact * ffy * (A[index + ym] + A[index + yp] - 2.0 * A[index]);
|
|
LA[index2] += fact * ffy * (A[index2 - yp] + A[index2 - ym] - 2.0 * A[index2]);
|
|
index++;
|
|
index2++;
|
|
index += h * static_cast<size_t>(d - 1);
|
|
index2 += h * static_cast<size_t>(d - 1);
|
|
}
|
|
} else {
|
|
ym = -h;
|
|
yp = h;
|
|
fact = factx * factz;
|
|
for (i=0; i<w; i++) {
|
|
if (i == 1) fact *= ifactx;
|
|
if (i == w-1) fact *= factx;
|
|
LA[index] += fact * ffy * (A[index + yp] - A[index]);
|
|
LA[index2] += fact * ffy * (A[index2 + ym] - A[index2]);
|
|
index++;
|
|
index2++;
|
|
fact *= ifactz;
|
|
for (k=1; k<h-1; k++) {
|
|
// y gradient (+ x, z terms of laplacian, calculated above and below)
|
|
LA[index] += fact * ffy * (A[index + yp] - A[index]);
|
|
LA[index2] += fact * ffy * (A[index2 + ym] - A[index2]);
|
|
index++;
|
|
index2++;
|
|
}
|
|
fact *= factz;
|
|
LA[index] += fact * ffy * (A[index + yp] - A[index]);
|
|
LA[index2] += fact * ffy * (A[index2 + ym] - A[index2]);
|
|
index++;
|
|
index2++;
|
|
index += h * static_cast<size_t>(d - 1);
|
|
index2 += h * static_cast<size_t>(d - 1);
|
|
}
|
|
}
|
|
|
|
// Now adding all z components
|
|
// All z components except on z edges
|
|
index = 1; // Skip first element (in bottom slab)
|
|
fact = factx * facty;
|
|
for (i=0; i<w; i++) { // full range of x
|
|
if (i == 1) fact *= ifactx;
|
|
if (i == w-1) fact *= factx;
|
|
for (k=1; k<h-1; k++) {
|
|
LA[index] += fact * ffz * (A[index + zm] + A[index + zp] - 2.0 * A[index]);
|
|
index++;
|
|
}
|
|
fact *= ifacty;
|
|
index += 2; // skip edge slabs
|
|
for (j=1; j<d-1; j++) { // full range of y
|
|
for (k=1; k<h-1; k++) {
|
|
LA[index] += fact * ffz * (A[index + zm] + A[index + zp] - 2.0 * A[index]);
|
|
index++;
|
|
}
|
|
index += 2; // skip edge slabs
|
|
}
|
|
fact *= facty;
|
|
for (k=1; k<h-1; k++) {
|
|
LA[index] += fact * ffz * (A[index + zm] + A[index + zp] - 2.0 * A[index]);
|
|
index++;
|
|
}
|
|
index += 2; // skip edge slabs
|
|
}
|
|
// Edges along z (z components onlz)
|
|
index = 0; // Follows bottom slab
|
|
index2 = h - 1; // Follows top slab
|
|
if (periodic[2]) {
|
|
zm = h - 1;
|
|
zp = 1;
|
|
fact = factx * facty;
|
|
for (i=0; i<w; i++) {
|
|
if (i == 1) fact *= ifactx;
|
|
if (i == w-1) fact *= factx;
|
|
LA[index] += fact * ffz * (A[index + zm] + A[index + zp] - 2.0 * A[index]);
|
|
LA[index2] += fact * ffz * (A[index2 - zp] + A[index2 - zm] - 2.0 * A[index2]);
|
|
index += h;
|
|
index2 += h;
|
|
fact *= ifacty;
|
|
for (j=1; j<d-1; j++) {
|
|
LA[index] += fact * ffz * (A[index + zm] + A[index + zp] - 2.0 * A[index]);
|
|
LA[index2] += fact * ffz * (A[index2 - zp] + A[index2 - zm] - 2.0 * A[index2]);
|
|
index += h;
|
|
index2 += h;
|
|
}
|
|
fact *= facty;
|
|
LA[index] += fact * ffz * (A[index + zm] + A[index + zp] - 2.0 * A[index]);
|
|
LA[index2] += fact * ffz * (A[index2 - zp] + A[index2 - zm] - 2.0 * A[index2]);
|
|
index += h;
|
|
index2 += h;
|
|
}
|
|
} else {
|
|
zm = -1;
|
|
zp = 1;
|
|
fact = factx * facty;
|
|
for (i=0; i<w; i++) {
|
|
if (i == 1) fact *= ifactx;
|
|
if (i == w-1) fact *= factx;
|
|
LA[index] += fact * ffz * (A[index + zp] - A[index]);
|
|
LA[index2] += fact * ffz * (A[index2 + zm] - A[index2]);
|
|
index += h;
|
|
index2 += h;
|
|
fact *= ifacty;
|
|
for (j=1; j<d-1; j++) {
|
|
// z gradient (+ x, y terms of laplacian, calculated above)
|
|
LA[index] += fact * ffz * (A[index + zp] - A[index]);
|
|
LA[index2] += fact * ffz * (A[index2 + zm] - A[index2]);
|
|
index += h;
|
|
index2 += h;
|
|
}
|
|
fact *= facty;
|
|
LA[index] += fact * ffz * (A[index + zp] - A[index]);
|
|
LA[index2] += fact * ffz * (A[index2 + zm] - A[index2]);
|
|
index += h;
|
|
index2 += h;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
|
|
/*
|
|
/// Inversion of preconditioner matrix (e.g. diagonal of the Laplacian)
|
|
void integrate_potential::asolve(const std::vector<cvm::real> &b, std::vector<cvm::real> &x)
|
|
{
|
|
for (size_t i=0; i<int(nt); i++) {
|
|
x[i] = b[i] * inv_lap_diag[i]; // Jacobi preconditioner - little benefit in tests so far
|
|
}
|
|
return;
|
|
}*/
|
|
|
|
|
|
// b : RHS of equation
|
|
// x : initial guess for the solution; output is solution
|
|
// itol : convergence criterion
|
|
void integrate_potential::nr_linbcg_sym(const std::vector<cvm::real> &b, std::vector<cvm::real> &x, const cvm::real &tol,
|
|
const int itmax, int &iter, cvm::real &err)
|
|
{
|
|
cvm::real ak,akden,bk,bkden,bknum,bnrm;
|
|
const cvm::real EPS=1.0e-14;
|
|
int j;
|
|
std::vector<cvm::real> p(nt), r(nt), z(nt);
|
|
|
|
iter=0;
|
|
atimes(x,r);
|
|
for (j=0;j<int(nt);j++) {
|
|
r[j]=b[j]-r[j];
|
|
}
|
|
bnrm=l2norm(b);
|
|
if (bnrm < EPS) {
|
|
return; // Target is zero, will break relative error calc
|
|
}
|
|
// asolve(r,z); // precon
|
|
bkden = 1.0;
|
|
while (iter < itmax) {
|
|
++iter;
|
|
for (bknum=0.0,j=0;j<int(nt);j++) {
|
|
bknum += r[j]*r[j]; // precon: z[j]*r[j]
|
|
}
|
|
if (iter == 1) {
|
|
for (j=0;j<int(nt);j++) {
|
|
p[j] = r[j]; // precon: p[j] = z[j]
|
|
}
|
|
} else {
|
|
bk=bknum/bkden;
|
|
for (j=0;j<int(nt);j++) {
|
|
p[j] = bk*p[j] + r[j]; // precon: bk*p[j] + z[j]
|
|
}
|
|
}
|
|
bkden = bknum;
|
|
atimes(p,z);
|
|
for (akden=0.0,j=0;j<int(nt);j++) {
|
|
akden += z[j]*p[j];
|
|
}
|
|
ak = bknum/akden;
|
|
for (j=0;j<int(nt);j++) {
|
|
x[j] += ak*p[j];
|
|
r[j] -= ak*z[j];
|
|
}
|
|
// asolve(r,z); // precon
|
|
err = l2norm(r)/bnrm;
|
|
if (cvm::debug())
|
|
std::cout << "iter=" << std::setw(4) << iter+1 << std::setw(12) << err << std::endl;
|
|
if (err <= tol)
|
|
break;
|
|
}
|
|
}
|
|
|
|
cvm::real integrate_potential::l2norm(const std::vector<cvm::real> &x)
|
|
{
|
|
size_t i;
|
|
cvm::real sum = 0.0;
|
|
for (i=0;i<x.size();i++)
|
|
sum += x[i]*x[i];
|
|
return sqrt(sum);
|
|
}
|