Files
lammps-gran-kokkos/lib/colvars/colvardeps.h
Giacomo Fiorin cba479bf6e Update Colvars library to version 2025-04-18
The following is a list of pull requests relevant to LAMMPS in the Colvars repository since 2024-08-06:

- 752 New tool poisson_integrator_conv
  https://github.com/Colvars/colvars/pull/752 (@jhenin)

- 733 Custom grids for all biases
  https://github.com/Colvars/colvars/pull/733 (@giacomofiorin, @jhenin)

- 776 Avoid error in acos and asin with fast-math
  https://github.com/Colvars/colvars/pull/776 (@jhenin)

- 773 fix: fix the clang build test failure of OPES
  https://github.com/Colvars/colvars/pull/773 (@HanatoK)

- 768 fix: clamp the input values of asin and acos in case of fast math on aarch64
  https://github.com/Colvars/colvars/pull/768 (@HanatoK)

- 761 Add debug code for the Jacobi failure
  https://github.com/Colvars/colvars/pull/761 (@HanatoK)

- 759 min_image fix; Saves long runs from crashes;
  https://github.com/Colvars/colvars/pull/759 (@PolyachenkoYA)

- 757 Fix MSVC OpenMP issue
  https://github.com/Colvars/colvars/pull/757 (@HanatoK)

- 755 Fix indentation of 'Init CVC' message in standard output
  https://github.com/Colvars/colvars/pull/755 (@jhenin)

- 750 Optimize and simplify the calculation of dihedral gradients
  https://github.com/Colvars/colvars/pull/750 (@HanatoK)

- 749 Add references to new Colvars paper
  https://github.com/Colvars/colvars/pull/749 (@jhenin, @giacomofiorin)

- 740 Report the specific C++ standard at init time, stop warning about C++97/03
  https://github.com/Colvars/colvars/pull/740 (@giacomofiorin)

- 731 Improve detection of hard/mathematical boundaries
  https://github.com/Colvars/colvars/pull/731 (@giacomofiorin)

- 729 Optimize the fit gradients
  https://github.com/Colvars/colvars/pull/729 (@HanatoK, @jhenin)

- 728 Fix undefined behavior when getting the current working directory from std::filesystem
  https://github.com/Colvars/colvars/pull/728 (@giacomofiorin)

- 727 Add patchversion scripting command
  https://github.com/Colvars/colvars/pull/727 (@giacomofiorin)

- 724 Fix gradients and metric functions of distanceDir
  https://github.com/Colvars/colvars/pull/724 (@giacomofiorin)

- 715 Add missing rotation in orientation component
  https://github.com/Colvars/colvars/pull/715 (@giacomofiorin)

- 713 fix: try to solve #87 for non-scala components
  https://github.com/Colvars/colvars/pull/713 (@HanatoK)

- 709 Implementation of OPES in Colvars
  https://github.com/Colvars/colvars/pull/709 (@HanatoK, @giacomofiorin, @jhenin)

- 706 BUGFIX for Segmentation fault in colvarbias_meta::calc_energy() with useGrids off
  https://github.com/Colvars/colvars/pull/706 (@alphataubio)

- 570 enable use of CVs defined by PyTorch neural network models
  https://github.com/Colvars/colvars/pull/570 (@zwpku, @giacomofiorin, @HanatoK, @jhenin)

Authors: @alphataubio, @EzryStIago, @giacomofiorin, @HanatoK, @jhenin, @PolyachenkoYA, @zwpku
2025-04-30 15:32:30 -04:00

459 lines
18 KiB
C++

// -*- c++ -*-
// This file is part of the Collective Variables module (Colvars).
// The original version of Colvars and its updates are located at:
// https://github.com/Colvars/colvars
// Please update all Colvars source files before making any changes.
// If you wish to distribute your changes, please submit them to the
// Colvars repository at GitHub.
#ifndef COLVARDEPS_H
#define COLVARDEPS_H
#include "colvarmodule.h"
#include "colvarparse.h"
/// \brief Parent class for a member object of a bias, cv or cvc etc. containing features and
/// their dependencies, and handling dependency resolution
///
/// There are 3 kinds of features:
/// 1. Dynamic features are under the control of the dependency resolution
/// system. They may be enabled or disabled depending on dependencies.
/// 2. User features may be enabled based on user input (they may trigger a failure upon dependency resolution, though)
/// 3. Static features are static properties of the object, determined
/// programmatically at initialization time.
///
/// The following diagram summarizes the dependency tree at the bias, colvar, and colvarcomp levels.
/// Isolated and atom group features are not shown to save space.
/// @image html deps_2019.svg
///
/// In all classes, feature 0 is `active`. When an object is inactivated
/// all its children dependencies are dereferenced (free_children_deps)
/// While the object is inactive, no dependency solving is done on children
/// it is done when the object is activated back (restore_children_deps)
class colvardeps {
public:
colvardeps();
virtual ~colvardeps();
// Subclasses should initialize the following members:
std::string description; // reference to object name (cv, cvc etc.)
/// This contains the current state of each feature for each object
// since the feature class only contains static properties
struct feature_state {
feature_state(bool a, bool e)
: available(a), enabled(e), ref_count(0) {}
/// Feature may be enabled, subject to possible dependencies
bool available;
/// Currently enabled - this flag is subject to change dynamically
/// TODO consider implications for dependency solving: anyone who disables
/// it should trigger a refresh of parent objects
bool enabled; // see if this should be private depending on implementation
// bool enabledOnce; // this should trigger an update when object is evaluated
/// Number of features requiring this one as a dependency
/// When it falls to zero:
/// - a dynamic feature is disabled automatically
/// - other features may be disabled statically
int ref_count;
/// List of features that were enabled by this one
/// as part of an alternate requirement (for ref counting purposes)
/// This is necessary because we don't know which feature in the list
/// we enabled, otherwise
std::vector<int> alternate_refs;
};
protected:
/// Time step multiplier (for coarse-timestep biases & colvars)
/// Biases and colvars will only be calculated at those times
/// (f_cvb_awake and f_cv_awake); a
/// Biases use this to apply "impulse" biasing forces at the outer timestep
/// Unused by lower-level objects (cvcs and atom groups)
int time_step_factor;
/// List of the states of all features
std::vector<feature_state> feature_states;
/// Enum of possible feature types
enum feature_type {
f_type_not_set,
f_type_dynamic,
f_type_user,
f_type_static
};
public:
/// \brief returns time_step_factor
inline int get_time_step_factor() const {return time_step_factor;}
/// Pair a numerical feature ID with a description and type
void init_feature(int feature_id, const char *description, feature_type type);
/// Describes a feature and its dependencies
/// used in a static array within each subclass
class feature {
public:
feature() : type(f_type_not_set) {}
~feature() {}
std::string description; // Set by derived object initializer
// features that this feature requires in the same object
// NOTE: we have no safety mechanism against circular dependencies, however, they would have to be internal to an object (ie. requires_self or requires_alt)
std::vector<int> requires_self;
// Features that are incompatible, ie. required disabled
// if enabled, they will cause a dependency failure (they will not be disabled)
// To enforce these dependencies regardless of the order in which they
// are enabled, they are always set in a symmetric way, so whichever is enabled
// second will cause the dependency to fail
std::vector<int> requires_exclude;
// sets of features that are required in an alternate way
// when parent feature is enabled, if none are enabled, the first one listed that is available will be enabled
std::vector<std::vector<int> > requires_alt;
// features that this feature requires in children
std::vector<int> requires_children;
inline bool is_dynamic() { return type == f_type_dynamic; }
inline bool is_static() { return type == f_type_static; }
inline bool is_user() { return type == f_type_user; }
/// Type of this feature, from the enum feature_type
feature_type type;
};
inline bool is_not_set(int id) { return features()[id]->type == f_type_not_set; }
inline bool is_dynamic(int id) { return features()[id]->type == f_type_dynamic; }
inline bool is_static(int id) { return features()[id]->type == f_type_static; }
inline bool is_user(int id) { return features()[id]->type == f_type_user; }
// Accessor to array of all features with deps, static in most derived classes
// Subclasses with dynamic dependency trees may override this
// with a non-static array
// Intermediate classes (colvarbias and colvarcomp, which are also base classes)
// implement this as virtual to allow overriding
virtual const std::vector<feature *> &features() const = 0;
virtual std::vector<feature *>&modify_features() = 0;
void add_child(colvardeps *child);
void remove_child(colvardeps *child);
/// Used before deleting an object, if not handled by that object's destructor
/// (useful for cvcs because their children are member objects)
void remove_all_children();
private:
/// pointers to objects this object depends on
/// list should be maintained by any code that modifies the object
/// this could be secured by making lists of colvars / cvcs / atom groups private and modified through accessor functions
std::vector<colvardeps *> children;
/// pointers to objects that depend on this object
/// the size of this array is in effect a reference counter
std::vector<colvardeps *> parents;
public:
// Checks whether given feature is enabled
// Defaults to querying f_*_active
inline bool is_enabled(int f = f_cv_active) const {
return feature_states[f].enabled;
}
// Checks whether given feature is available
// Defaults to querying f_*_active
inline bool is_available(int f = f_cv_active) const {
return feature_states[f].available;
}
/// Set the feature's available flag, without checking
/// To be used for dynamic properties
/// dependencies will be checked by enable()
void provide(int feature_id, bool truefalse = true);
/// Enable or disable, depending on flag value
void set_enabled(int feature_id, bool truefalse = true);
protected:
/// Parse a keyword and enable a feature accordingly
bool get_keyval_feature(colvarparse *cvp,
std::string const &conf, char const *key,
int feature_id, bool const &def_value,
colvarparse::Parse_Mode const parse_mode = colvarparse::parse_normal);
public:
/// Enable a feature and recursively solve its dependencies.
/// For accurate reference counting, do not add spurious calls to enable()
/// \param dry_run Recursively test whether a feature is available, without enabling it
/// \param toplevel False if this is called as part of a chain of dependency resolution.
/// This is used to diagnose failed dependencies by displaying the full stack:
/// only the toplevel dependency will throw a fatal error.
/// \param error Recursively enable, printing error messages along the way
/// Necessary when propagating errors across alternate dependencies
int enable(int f, bool dry_run = false, bool toplevel = true, bool error = false);
/// Disable a feature, decrease the reference count of its dependencies
/// and recursively disable them as applicable
int disable(int f);
/// disable all enabled features to free their dependencies
/// to be done when deleting the object
/// Cannot be in the base class destructor because it needs the derived class features()
void free_children_deps();
/// re-enable children features (to be used when object becomes active)
void restore_children_deps();
/// Decrement the reference count of a feature
/// disabling it if it's dynamic and count reaches zero
int decr_ref_count(int f);
/// Implements possible actions to be carried out
/// when a given feature is enabled
/// Base function does nothing, can be overloaded
virtual void do_feature_side_effects(int /* id */) {}
// NOTE that all feature enums should start with f_*_active
enum features_biases {
/// \brief Bias is active
f_cvb_active,
/// \brief Bias is awake (active on its own accord) this timestep
f_cvb_awake,
/// Accumulates data starting from step 0 of a simulation run
f_cvb_step_zero_data,
/// \brief will apply forces
f_cvb_apply_force,
/// \brief force this bias to act on actual value for extended-Lagrangian coordinates
f_cvb_bypass_ext_lagrangian,
/// \brief requires total forces
f_cvb_get_total_force,
/// \brief whether this bias should record the accumulated work
f_cvb_output_acc_work,
/// \brief depends on simulation history
f_cvb_history_dependent,
/// \brief depends on time
f_cvb_time_dependent,
/// \brief requires scalar colvars
f_cvb_scalar_variables,
/// \brief whether this bias will compute a PMF
f_cvb_calc_pmf,
/// \brief whether this bias will compute TI samples
f_cvb_calc_ti_samples,
/// \brief whether this bias will write TI samples
f_cvb_write_ti_samples,
/// \brief whether this bias should write the TI PMF
f_cvb_write_ti_pmf,
/// \brief whether this bias uses an external grid to scale the biasing forces
f_cvb_scale_biasing_force,
/// \brief whether this bias is applied to one or more ext-Lagrangian colvars
f_cvb_extended,
/// Process this bias's data in parallel over multiple CPU threads
f_cvb_smp,
f_cvb_ntot
};
enum features_colvar {
/// \brief Calculate colvar
f_cv_active,
/// \brief Colvar is awake (active on its own accord) this timestep
f_cv_awake,
/// \brief External force can be applied, either to atoms or to an
/// extended DOF
f_cv_apply_force,
/// \brief Gradients are calculated and temporarily stored,
/// so that external forces can be propagated to atoms
f_cv_gradient,
/// \brief Collect atomic gradient data from all cvcs into vector
/// atomic_gradient
f_cv_collect_gradient,
/// \brief Build list of atoms involved in CV calculation
f_cv_collect_atom_ids,
/// \brief Calculate the velocity with finite differences
f_cv_fdiff_velocity,
/// \brief The total force is calculated, projecting the atomic
/// forces on the inverse gradient
f_cv_total_force,
/// \brief Calculate total force from atomic forces
/// or get it from the back-end for an external parameter
f_cv_total_force_calc,
/// \brief Total force is that of current time step
f_cv_total_force_current_step,
/// \brief Subtract the applied force from the total force
f_cv_subtract_applied_force,
/// \brief Estimate Jacobian derivative
f_cv_Jacobian,
/// \brief Do not report the Jacobian force as part of the total force
/// instead, apply a correction internally to cancel it
f_cv_hide_Jacobian,
/// \brief The variable has a harmonic restraint around a moving
/// center with fictitious mass; bias forces will be applied to
/// the center
f_cv_extended_Lagrangian,
/// \brief A variable that constrains or follows an external parameter
/// in the back-end (eg. an alchemical coupling parameter for lambda-dynamics)
/// If extended Lagrangian, then we drive the external parameter
/// Otherwise we follow it
/// Can have a single component
f_cv_external,
/// \brief The extended system coordinate undergoes Langevin dynamics
f_cv_Langevin,
/// \brief Output the potential and kinetic energies
/// (for extended Lagrangian colvars only)
f_cv_output_energy,
/// \brief Output the value to the trajectory file (on by default)
f_cv_output_value,
/// \brief Output the velocity to the trajectory file
f_cv_output_velocity,
/// \brief Output the applied force to the trajectory file
f_cv_output_applied_force,
/// \brief Output the total force to the trajectory file
f_cv_output_total_force,
/// \brief A lower boundary is defined
f_cv_lower_boundary,
/// \brief An upper boundary is defined
f_cv_upper_boundary,
/// \brief The lower boundary is not defined from user's choice
f_cv_hard_lower_boundary,
/// \brief The upper boundary is not defined from user's choice
f_cv_hard_upper_boundary,
/// \brief Reflecting lower boundary condition
f_cv_reflecting_lower_boundary,
/// \brief Reflecting upper boundary condition
f_cv_reflecting_upper_boundary,
/// \brief Provide a discretization of the values of the colvar to
/// be used by the biases or in analysis (needs lower and upper
/// boundary)
f_cv_grid,
/// \brief Compute running average
f_cv_runave,
/// \brief Compute time correlation function
f_cv_corrfunc,
/// \brief Value and gradient computed by user script
f_cv_scripted,
/// \brief Value and gradient computed by user function through Lepton
f_cv_custom_function,
/// \brief Colvar is periodic
f_cv_periodic,
/// \brief The colvar has only one component
f_cv_single_cvc,
/// \brief is scalar
f_cv_scalar,
f_cv_linear,
f_cv_homogeneous,
/// \brief multiple timestep through time_step_factor
f_cv_multiple_ts,
/// \brief Number of colvar features
f_cv_ntot
};
enum features_cvc {
/// Computation of this CVC is enabled
f_cvc_active,
/// This CVC computes a scalar value
f_cvc_scalar,
/// Values of this CVC lie in a periodic interval
f_cvc_periodic,
/// This CVC provides a default value for the colvar's width
f_cvc_width,
/// This CVC provides a default value for the colvar's lower boundary
f_cvc_lower_boundary,
/// This CVC provides a default value for the colvar's upper boundary
f_cvc_upper_boundary,
/// CVC accesses atom groups directly (as opposed to going throuh other objects)
f_cvc_explicit_atom_groups,
/// CVC calculates atom gradients
f_cvc_gradient,
/// CVC calculates and stores explicit atom gradients on rank 0
f_cvc_explicit_gradient,
/// CVC calculates and stores inverse atom gradients (used for total force)
f_cvc_inv_gradient,
/// CVC calculates the Jacobian term of the total-force expression
f_cvc_Jacobian,
/// The total force for this CVC will be computed from one group only
f_cvc_one_site_total_force,
/// calc_gradients() will call debug_gradients() for every group needed
f_cvc_debug_gradient,
/// With PBCs, minimum-image convention will be used for distances
/// (does not affect the periodicity of CVC values, e.g. angles)
f_cvc_pbc_minimum_image,
/// This CVC is a function of centers of mass
f_cvc_com_based,
/// This CVC can be computed in parallel
f_cvc_scalable,
/// Centers-of-mass used in this CVC can be computed in parallel
f_cvc_scalable_com,
/// \brief Build list of atoms involved in CVC calculation
f_cvc_collect_atom_ids,
/// Number of CVC features
f_cvc_ntot
};
enum features_atomgroup {
f_ag_active,
f_ag_center,
f_ag_center_origin,
f_ag_rotate,
f_ag_fitting_group,
/// Perform a standard minimum msd fit for given atoms
/// ie. not using refpositionsgroup
// f_ag_min_msd_fit,
/// \brief Does not have explicit atom gradients from parent CVC
f_ag_explicit_gradient,
f_ag_fit_gradients,
f_ag_atom_forces,
f_ag_scalable,
f_ag_scalable_com,
/// \brief Build list of atoms involved in atom group
f_ag_collect_atom_ids,
f_ag_ntot
};
/// Initialize dependency tree for object of a derived class
virtual int init_dependencies() = 0;
/// Make feature f require feature g within the same object
void require_feature_self(int f, int g);
/// Make features f and g mutually exclusive within the same object
void exclude_feature_self(int f, int g);
/// Make feature f require feature g within children
void require_feature_children(int f, int g);
/// Make feature f require either g or h within the same object
void require_feature_alt(int f, int g, int h);
/// Make feature f require any of g, h, or i within the same object
void require_feature_alt(int f, int g, int h, int i);
/// Make feature f require any of g, h, i, or j within the same object
void require_feature_alt(int f, int g, int h, int i, int j);
/// \brief print all enabled features and those of children, for debugging
void print_state();
/// \brief Check that a feature is enabled, raising COLVARS_BUG_ERROR if not
inline void check_enabled(int f, std::string const &reason) const
{
if (! is_enabled(f)) {
cvm::error("Error: "+reason+" requires that the feature \""+
features()[f]->description+"\" is active.\n", COLVARS_BUG_ERROR);
}
}
};
#endif