forked from lijiext/lammps
285 lines
8.0 KiB
C++
285 lines
8.0 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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#ifndef COLVARBIAS_H
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#define COLVARBIAS_H
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#include "colvar.h"
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#include "colvarparse.h"
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#include "colvardeps.h"
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/// \brief Collective variable bias, base class
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class colvarbias
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: public virtual colvarparse, public virtual colvardeps {
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public:
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/// Name of this bias
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std::string name;
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/// Keyword indicating the type of this bias
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std::string bias_type;
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/// Keyword used in state files (== bias_type most of the time)
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std::string state_keyword;
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/// If there is more than one bias of this type, record its rank
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int rank;
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/// Add a new collective variable to this bias
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int add_colvar(std::string const &cv_name);
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/// How many variables are defined for this bias
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inline size_t num_variables() const
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{
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return colvars.size();
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}
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/// Access the variables vector
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inline std::vector<colvar *> *variables()
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{
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return &colvars;
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}
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/// Access the i-th variable
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inline colvar * variables(int i) const
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{
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return colvars[i];
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}
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/// Retrieve colvar values and calculate their biasing forces
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/// Some implementations may use calc_energy() and calc_forces()
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virtual int update();
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/// Compute the energy of the bias
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/// Uses the vector of colvar values provided if not NULL, and the values
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/// currently cached in the bias instance otherwise
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virtual int calc_energy(std::vector<colvarvalue> const *values);
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/// Compute the forces due to the bias
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/// Uses the vector of colvar values provided if not NULL, and the values
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/// currently cached in the bias instance otherwise
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virtual int calc_forces(std::vector<colvarvalue> const *values);
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/// Send forces to the collective variables
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void communicate_forces();
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/// Carry out operations needed before next step is run
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virtual int end_of_step();
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/// Load new configuration - force constant and/or centers only
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virtual int change_configuration(std::string const &conf);
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/// Calculate change in energy from using alternate configuration
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virtual cvm::real energy_difference(std::string const &conf);
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/// Give the total number of bins for a given bias.
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// FIXME this is currently 1D only
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virtual int bin_num();
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/// Calculate the bin index for a given bias.
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// FIXME this is currently 1D only
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virtual int current_bin();
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//// Give the count at a given bin index.
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// FIXME this is currently 1D only
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virtual int bin_count(int bin_index);
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//// Share information between replicas, whatever it may be.
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virtual int replica_share();
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/// Perform analysis tasks
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virtual void analyze() {}
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/// \brief Constructor
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colvarbias(char const *key);
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/// \brief Parse config string and (re)initialize
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virtual int init(std::string const &conf);
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/// \brief Initialize dependency tree
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virtual int init_dependencies();
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/// \brief Set to zero all mutable data
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virtual int reset();
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private:
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/// Default constructor
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colvarbias();
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/// Copy constructor
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colvarbias(colvarbias &);
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public:
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/// \brief Delete everything
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virtual int clear();
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/// \brief Delete only the allocatable data (save memory)
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virtual int clear_state_data();
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/// Destructor
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virtual ~colvarbias();
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/// Write the values of specific mutable properties to a string
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virtual std::string const get_state_params() const;
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/// Read the values of specific mutable properties from a string
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virtual int set_state_params(std::string const &state_conf);
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/// Write all mutable data not already written by get_state_params()
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virtual std::ostream & write_state_data(std::ostream &os)
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{
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return os;
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}
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/// Read all mutable data not already set by set_state_params()
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virtual std::istream & read_state_data(std::istream &is)
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{
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return is;
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}
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/// Read a keyword from the state data (typically a header)
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std::istream & read_state_data_key(std::istream &is, char const *key);
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/// Write the bias configuration to a restart file or other stream
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std::ostream & write_state(std::ostream &os);
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/// Read the bias configuration from a restart file or other stream
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std::istream & read_state(std::istream &is);
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/// Write a label to the trajectory file (comment line)
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virtual std::ostream & write_traj_label(std::ostream &os);
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/// Output quantities such as the bias energy to the trajectory file
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virtual std::ostream & write_traj(std::ostream &os);
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/// (Re)initialize the output files (does not write them yet)
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virtual int setup_output()
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{
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return COLVARS_OK;
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}
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/// Write any output files that this bias may have (e.g. PMF files)
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virtual int write_output_files()
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{
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return COLVARS_OK;
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}
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/// Use this prefix for all output files
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std::string output_prefix;
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/// If this bias is communicating with other replicas through files, send it to them
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virtual int write_state_to_replicas()
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{
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return COLVARS_OK;
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}
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inline cvm::real get_energy()
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{
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return bias_energy;
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}
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/// \brief Implementation of the feature list for colvarbias
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static std::vector<feature *> cvb_features;
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/// \brief Implementation of the feature list accessor for colvarbias
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virtual const std::vector<feature *> &features() const
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{
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return cvb_features;
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}
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virtual std::vector<feature *> &modify_features()
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{
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return cvb_features;
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}
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static void delete_features() {
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for (size_t i=0; i < cvb_features.size(); i++) {
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delete cvb_features[i];
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}
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cvb_features.clear();
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}
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protected:
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/// \brief Pointers to collective variables to which the bias is
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/// applied; current values and metric functions will be obtained
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/// through each colvar object
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std::vector<colvar *> colvars;
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/// \brief Up to date value of each colvar
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std::vector<colvarvalue> colvar_values;
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/// \brief Current forces from this bias to the variables
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std::vector<colvarvalue> colvar_forces;
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/// \brief Forces last applied by this bias to the variables
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std::vector<colvarvalue> previous_colvar_forces;
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/// \brief Current energy of this bias (colvar_forces should be obtained by deriving this)
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cvm::real bias_energy;
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/// Whether to write the current bias energy from this bias to the trajectory file
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bool b_output_energy;
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/// \brief Whether this bias has already accumulated information
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/// (for history-dependent biases)
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bool has_data;
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/// \brief Step number read from the last state file
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cvm::step_number state_file_step;
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/// Flag used to tell if the state string being read is for this bias
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bool matching_state;
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};
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class colvar_grid_gradient;
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class colvar_grid_count;
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/// \brief Base class for unconstrained thermodynamic-integration FE estimator
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class colvarbias_ti : public virtual colvarbias {
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public:
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colvarbias_ti(char const *key);
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virtual ~colvarbias_ti();
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virtual int clear_state_data();
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virtual int init(std::string const &conf);
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virtual int init_grids();
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virtual int update();
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/// Subtract applied forces (either last forces or argument) from the total
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/// forces
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virtual int update_system_forces(std::vector<colvarvalue> const
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*subtract_forces);
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virtual std::string const get_state_params() const;
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virtual int set_state_params(std::string const &state_conf);
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virtual std::ostream & write_state_data(std::ostream &os);
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virtual std::istream & read_state_data(std::istream &is);
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virtual int write_output_files();
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protected:
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/// \brief Forces exerted from the system to the associated variables
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std::vector<colvarvalue> ti_system_forces;
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/// Averaged system forces
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colvar_grid_gradient *ti_avg_forces;
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/// Histogram of sampled data
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colvar_grid_count *ti_count;
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/// Because total forces may be from the last simulation step,
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/// store the index of the variables then
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std::vector<int> ti_bin;
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};
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#endif
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