Update Colvars to version 2022-05-09

This update includes one new feature (neural-network based collective variables), several small enhancements (including an automatic definition of grid boundaries for angle-based CVs, and a normalization option for eigenvector-based CVs), bugfixes and documentation improvements. Usage information for specific features included in the Colvars library (i.e. not just the library as a whole) is now also reported to the screen or LAMMPS logfile (as is done already in other LAMMPS classes). Notable to LAMMPS code development are the removals of duplicated code and of ambiguously-named preprocessor defines in the Colvars headers. Since the last PR, the existing regression tests have also been running automatically via GitHub Actions. The following pull requests in the Colvars repository are relevant to LAMMPS: - 475 Remove fatal error condition https://github.com/Colvars/colvars/pull/475 (@jhenin, @giacomofiorin) - 474 Allow normalizing eigenvector vector components to deal with unit change https://github.com/Colvars/colvars/pull/474 (@giacomofiorin, @jhenin) - 470 Better error handling in the initialization of NeuralNetwork CV https://github.com/Colvars/colvars/pull/470 (@HanatoK) - 468 Add examples of histogram configuration, with and without explicit grid parameters https://github.com/Colvars/colvars/pull/468 (@giacomofiorin) - 464 Fix #463 using more fine-grained features https://github.com/Colvars/colvars/pull/464 (@jhenin, @giacomofiorin) - 447 [RFC] New option "scaledBiasingForce" for colvarbias https://github.com/Colvars/colvars/pull/447 (@HanatoK, @jhenin) - 444 [RFC] Implementation of dense neural network as CV https://github.com/Colvars/colvars/pull/444 (@HanatoK, @giacomofiorin, @jhenin) - 443 Fix explicit gradient dependency of sub-CVs https://github.com/Colvars/colvars/pull/443 (@HanatoK, @jhenin) - 442 Persistent bias count https://github.com/Colvars/colvars/pull/442 (@jhenin, @giacomofiorin) - 437 Return type of bias from scripting interface https://github.com/Colvars/colvars/pull/437 (@giacomofiorin) - 434 More flexible use of boundaries from colvars by grids https://github.com/Colvars/colvars/pull/434 (@jhenin) - 433 Prevent double-free in linearCombination https://github.com/Colvars/colvars/pull/433 (@HanatoK) - 428 More complete documentation for index file format (NDX) https://github.com/Colvars/colvars/pull/428 (@giacomofiorin) - 426 Integrate functional version of backup_file() into base proxy class https://github.com/Colvars/colvars/pull/426 (@giacomofiorin) - 424 Track CVC inheritance when documenting feature usage https://github.com/Colvars/colvars/pull/424 (@giacomofiorin) - 419 Generate citation report while running computations https://github.com/Colvars/colvars/pull/419 (@giacomofiorin, @jhenin) - 415 Rebin metadynamics bias from explicit hills when available https://github.com/Colvars/colvars/pull/415 (@giacomofiorin) - 312 Ignore a keyword if it has content to the left of it (regardless of braces) https://github.com/Colvars/colvars/pull/312 (@giacomofiorin) Authors: @giacomofiorin, @HanatoK, @jhenin
2022-05-10 11:24:54 -04:00
parent 4737b9efb7
commit 1220bea011
66 changed files with 4040 additions and 1221 deletions
--- a/lib/colvars/colvarcomp.h
+++ b/lib/colvars/colvarcomp.h
@ -28,6 +28,7 @@
 #if (__cplusplus >= 201103L)
 // C++11-only functions
 #include "colvar_geometricpath.h"
+#include <memory>
 #include <functional>
 #endif

@ -110,6 +111,9 @@ public:
  /// Calls the init() function of the class
  cvc(std::string const &conf);

+  /// Set the value of \link function_type \endlink and its dependencies
+  int set_function_type(std::string const &type);
+
  /// An init function should be defined for every class inheriting from cvc
  /// \param conf Contents of the configuration file pertaining to this \link
  /// cvc \endlink
@ -279,6 +283,9 @@ public:

 protected:

+  /// Record the type of this class as well as those it is derived from
+  std::vector<std::string> function_types;
+
  /// \brief Cached value
  colvarvalue x;

@ -298,9 +305,12 @@ protected:
  /// \brief Set data types for a scalar distance (convenience function)
  void init_as_distance();

-  /// \brief Set data types for a bounded angle (convenience function)
+  /// \brief Set data types for a bounded angle (0° to 180°)
  void init_as_angle();

+  /// \brief Set data types for a periodic angle (-180° to 180°)
+  void init_as_periodic_angle();
+
  /// \brief Set two scalar boundaries (convenience function)
  void init_scalar_boundaries(cvm::real lb, cvm::real ub);

@ -347,8 +357,6 @@ protected:
  cvm::atom_group  *group2;
  /// Vector distance, cached to be recycled
  cvm::rvector     dist_v;
-  /// Use absolute positions, ignoring PBCs when present
-  bool b_no_PBC;
 public:
  distance(std::string const &conf);
  distance();
@ -432,8 +440,6 @@ protected:
  cvm::atom_group  *ref1;
  /// Optional, second ref atom group
  cvm::atom_group  *ref2;
-  /// Use absolute positions, ignoring PBCs when present
-  bool b_no_PBC;
  /// Vector on which the distance vector is projected
  cvm::rvector axis;
  /// Norm of the axis
@ -560,8 +566,6 @@ protected:
  cvm::atom_group  *group2;
  /// Components of the distance vector orthogonal to the axis
  int exponent;
-  /// Use absolute positions, ignoring PBCs when present
-  bool b_no_PBC;
 public:
  distance_inv(std::string const &conf);
  virtual ~distance_inv() {}
@ -588,8 +592,6 @@ protected:
  cvm::atom_group  *group1;
  /// Second atom group
  cvm::atom_group  *group2;
-  /// Use absolute positions, ignoring PBCs when present
-  bool b_no_PBC;
 public:
  distance_pairs(std::string const &conf);
  distance_pairs();
@ -1500,6 +1502,29 @@ public:
 };


+// \brief Colvar component: alch_Flambda
+// To communicate force on lambda with back-end in lambda-dynamics
+class colvar::alch_Flambda
+  : public colvar::cvc
+{
+protected:
+  // No atom groups needed
+public:
+  alch_Flambda(std::string const &conf);
+  alch_Flambda();
+  virtual ~alch_Flambda() {}
+  virtual void calc_value();
+  virtual void calc_gradients();
+  virtual void apply_force(colvarvalue const &force);
+  virtual cvm::real dist2(colvarvalue const &x1,
+                          colvarvalue const &x2) const;
+  virtual colvarvalue dist2_lgrad(colvarvalue const &x1,
+                                  colvarvalue const &x2) const;
+  virtual colvarvalue dist2_rgrad(colvarvalue const &x1,
+                                  colvarvalue const &x2) const;
+};
+
+
 class colvar::componentDisabled
  : public colvar::cvc
 {
@ -1601,6 +1626,32 @@ public:
 };


+/// custom expression of colvars
+class colvar::customColvar
+  : public colvar::linearCombination
+{
+protected:
+    bool use_custom_function;
+#ifdef LEPTON
+    /// Vector of evaluators for custom functions using Lepton
+    std::vector<Lepton::CompiledExpression *> value_evaluators;
+    /// Vector of evaluators for gradients of custom functions
+    std::vector<Lepton::CompiledExpression *> gradient_evaluators;
+    /// Vector of references to cvc values to be passed to Lepton evaluators
+    std::vector<double *> value_eval_var_refs;
+    std::vector<double *> grad_eval_var_refs;
+    /// Unused value that is written to when a variable simplifies out of a Lepton expression
+    double dev_null;
+#endif
+public:
+    customColvar(std::string const &conf);
+    virtual ~customColvar();
+    virtual void calc_value();
+    virtual void calc_gradients();
+    virtual void apply_force(colvarvalue const &force);
+};
+
+
 class colvar::CVBasedPath
  : public colvar::cvc
 {
@ -1689,6 +1740,27 @@ public:
    virtual void apply_force(colvarvalue const &force);
 };

+// forward declaration
+namespace neuralnetworkCV {
+    class neuralNetworkCompute;
+}
+
+class colvar::neuralNetwork
+  : public linearCombination
+{
+protected:
+    /// actual computation happens in neuralnetworkCV::neuralNetworkCompute
+    std::unique_ptr<neuralnetworkCV::neuralNetworkCompute> nn;
+    /// the index of nn output components
+    size_t m_output_index;
+public:
+    neuralNetwork(std::string const &conf);
+    virtual ~neuralNetwork();
+    virtual void calc_value();
+    virtual void calc_gradients();
+    virtual void apply_force(colvarvalue const &force);
+};
+
 #else // if the compiler doesn't support C++11

 class colvar::linearCombination
@ -1754,6 +1826,13 @@ public:
    azpathCV(std::string const &conf) : componentDisabled(conf) {}
 };

+class colvar::neuralNetwork
+  : public colvar::componentDisabled
+{
+public:
+    neuralNetwork(std::string const &conf) : componentDisabled(conf) {}
+};
+
 #endif // C++11 checking