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
640 lines
18 KiB
C++
640 lines
18 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 <cstdlib>
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#include <cstring>
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#include "colvarmodule.h"
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#include "colvartypes.h"
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#include "colvarparse.h"
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#ifdef COLVARS_LAMMPS
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// Use open-source Jacobi implementation
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#include "math_eigen_impl.h"
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#else
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// Fall back to NR routine
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#include "nr_jacobi.h"
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#endif
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bool colvarmodule::rotation::monitor_crossings = false;
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cvm::real colvarmodule::rotation::crossing_threshold = 1.0E-02;
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std::string cvm::rvector::to_simple_string() const
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{
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std::ostringstream os;
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os.setf(std::ios::scientific, std::ios::floatfield);
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os.precision(cvm::cv_prec);
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os << x << " " << y << " " << z;
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return os.str();
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}
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int cvm::rvector::from_simple_string(std::string const &s)
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{
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std::stringstream stream(s);
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if ( !(stream >> x) ||
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!(stream >> y) ||
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!(stream >> z) ) {
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return COLVARS_ERROR;
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}
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return COLVARS_OK;
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}
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std::ostream & operator << (std::ostream &os, colvarmodule::rvector const &v)
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{
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std::streamsize const w = os.width();
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std::streamsize const p = os.precision();
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os.width(2);
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os << "( ";
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os.width(w); os.precision(p);
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os << v.x << " , ";
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os.width(w); os.precision(p);
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os << v.y << " , ";
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os.width(w); os.precision(p);
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os << v.z << " )";
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return os;
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}
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std::istream & operator >> (std::istream &is, colvarmodule::rvector &v)
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{
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std::streampos const start_pos = is.tellg();
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char sep;
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if ( !(is >> sep) || !(sep == '(') ||
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!(is >> v.x) || !(is >> sep) || !(sep == ',') ||
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!(is >> v.y) || !(is >> sep) || !(sep == ',') ||
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!(is >> v.z) || !(is >> sep) || !(sep == ')') ) {
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is.clear();
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is.seekg(start_pos, std::ios::beg);
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is.setstate(std::ios::failbit);
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return is;
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}
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return is;
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}
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std::string cvm::quaternion::to_simple_string() const
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{
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std::ostringstream os;
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os.setf(std::ios::scientific, std::ios::floatfield);
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os.precision(cvm::cv_prec);
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os << q0 << " " << q1 << " " << q2 << " " << q3;
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return os.str();
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}
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int cvm::quaternion::from_simple_string(std::string const &s)
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{
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std::stringstream stream(s);
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if ( !(stream >> q0) ||
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!(stream >> q1) ||
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!(stream >> q2) ||
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!(stream >> q3) ) {
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return COLVARS_ERROR;
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}
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return COLVARS_OK;
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}
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std::ostream & operator << (std::ostream &os, colvarmodule::quaternion const &q)
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{
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std::streamsize const w = os.width();
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std::streamsize const p = os.precision();
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os.width(2);
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os << "( ";
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os.width(w); os.precision(p);
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os << q.q0 << " , ";
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os.width(w); os.precision(p);
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os << q.q1 << " , ";
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os.width(w); os.precision(p);
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os << q.q2 << " , ";
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os.width(w); os.precision(p);
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os << q.q3 << " )";
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return os;
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}
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std::istream & operator >> (std::istream &is, colvarmodule::quaternion &q)
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{
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std::streampos const start_pos = is.tellg();
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std::string euler("");
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if ( (is >> euler) && (colvarparse::to_lower_cppstr(euler) ==
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std::string("euler")) ) {
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// parse the Euler angles
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char sep;
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cvm::real phi, theta, psi;
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if ( !(is >> sep) || !(sep == '(') ||
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!(is >> phi) || !(is >> sep) || !(sep == ',') ||
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!(is >> theta) || !(is >> sep) || !(sep == ',') ||
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!(is >> psi) || !(is >> sep) || !(sep == ')') ) {
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is.clear();
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is.seekg(start_pos, std::ios::beg);
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is.setstate(std::ios::failbit);
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return is;
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}
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q = colvarmodule::quaternion(phi, theta, psi);
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} else {
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// parse the quaternion components
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is.seekg(start_pos, std::ios::beg);
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char sep;
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if ( !(is >> sep) || !(sep == '(') ||
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!(is >> q.q0) || !(is >> sep) || !(sep == ',') ||
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!(is >> q.q1) || !(is >> sep) || !(sep == ',') ||
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!(is >> q.q2) || !(is >> sep) || !(sep == ',') ||
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!(is >> q.q3) || !(is >> sep) || !(sep == ')') ) {
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is.clear();
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is.seekg(start_pos, std::ios::beg);
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is.setstate(std::ios::failbit);
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return is;
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}
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}
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return is;
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}
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cvm::quaternion
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cvm::quaternion::position_derivative_inner(cvm::rvector const &pos,
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cvm::rvector const &vec) const
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{
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cvm::quaternion result(0.0, 0.0, 0.0, 0.0);
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result.q0 = 2.0 * pos.x * q0 * vec.x
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+2.0 * pos.y * q0 * vec.y
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+2.0 * pos.z * q0 * vec.z
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-2.0 * pos.y * q3 * vec.x
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+2.0 * pos.z * q2 * vec.x
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+2.0 * pos.x * q3 * vec.y
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-2.0 * pos.z * q1 * vec.y
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-2.0 * pos.x * q2 * vec.z
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+2.0 * pos.y * q1 * vec.z;
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result.q1 = +2.0 * pos.x * q1 * vec.x
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-2.0 * pos.y * q1 * vec.y
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-2.0 * pos.z * q1 * vec.z
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+2.0 * pos.y * q2 * vec.x
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+2.0 * pos.z * q3 * vec.x
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+2.0 * pos.x * q2 * vec.y
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-2.0 * pos.z * q0 * vec.y
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+2.0 * pos.x * q3 * vec.z
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+2.0 * pos.y * q0 * vec.z;
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result.q2 = -2.0 * pos.x * q2 * vec.x
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+2.0 * pos.y * q2 * vec.y
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-2.0 * pos.z * q2 * vec.z
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+2.0 * pos.y * q1 * vec.x
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+2.0 * pos.z * q0 * vec.x
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+2.0 * pos.x * q1 * vec.y
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+2.0 * pos.z * q3 * vec.y
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-2.0 * pos.x * q0 * vec.z
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+2.0 * pos.y * q3 * vec.z;
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result.q3 = -2.0 * pos.x * q3 * vec.x
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-2.0 * pos.y * q3 * vec.y
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+2.0 * pos.z * q3 * vec.z
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-2.0 * pos.y * q0 * vec.x
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+2.0 * pos.z * q1 * vec.x
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+2.0 * pos.x * q0 * vec.y
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+2.0 * pos.z * q2 * vec.y
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+2.0 * pos.x * q1 * vec.z
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+2.0 * pos.y * q2 * vec.z;
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return result;
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}
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// Calculate the optimal rotation between two groups, and implement it
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// as a quaternion. Uses the method documented in: Coutsias EA,
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// Seok C, Dill KA. Using quaternions to calculate RMSD. J Comput
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// Chem. 25(15):1849-57 (2004) DOI: 10.1002/jcc.20110 PubMed: 15376254
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#ifdef COLVARS_LAMMPS
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namespace {
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inline void *new_Jacobi_solver(int size) {
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return reinterpret_cast<void *>(new MathEigen::Jacobi<cvm::real,
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cvm::vector1d<cvm::real> &,
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cvm::matrix2d<cvm::real> &>(4));
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}
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}
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#endif
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int colvarmodule::rotation::init()
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{
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b_debug_gradients = false;
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lambda = 0.0;
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cvm::main()->cite_feature("Optimal rotation via flexible fitting");
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return COLVARS_OK;
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}
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colvarmodule::rotation::rotation()
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{
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init();
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#ifdef COLVARS_LAMMPS
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jacobi = new_Jacobi_solver(4);
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#else
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jacobi = NULL;
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#endif
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}
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colvarmodule::rotation::rotation(cvm::quaternion const &qi)
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: q(qi)
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{
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init();
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#ifdef COLVARS_LAMMPS
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jacobi = new_Jacobi_solver(4);
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#else
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jacobi = NULL;
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#endif
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}
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colvarmodule::rotation::rotation(cvm::real angle, cvm::rvector const &axis)
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{
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init();
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cvm::rvector const axis_n = axis.unit();
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cvm::real const sina = cvm::sin(angle/2.0);
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q = cvm::quaternion(cvm::cos(angle/2.0),
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sina * axis_n.x, sina * axis_n.y, sina * axis_n.z);
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#ifdef COLVARS_LAMMPS
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jacobi = new_Jacobi_solver(4);
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#else
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jacobi = NULL;
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#endif
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}
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colvarmodule::rotation::~rotation()
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{
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#ifdef COLVARS_LAMMPS
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delete reinterpret_cast<
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MathEigen::Jacobi<cvm::real,
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cvm::vector1d<cvm::real> &,
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cvm::matrix2d<cvm::real> &> *>(jacobi);
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#endif
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}
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void colvarmodule::rotation::build_correlation_matrix(
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std::vector<cvm::atom_pos> const &pos1,
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std::vector<cvm::atom_pos> const &pos2)
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{
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// build the correlation matrix
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size_t i;
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for (i = 0; i < pos1.size(); i++) {
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C.xx() += pos1[i].x * pos2[i].x;
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C.xy() += pos1[i].x * pos2[i].y;
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C.xz() += pos1[i].x * pos2[i].z;
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C.yx() += pos1[i].y * pos2[i].x;
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C.yy() += pos1[i].y * pos2[i].y;
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C.yz() += pos1[i].y * pos2[i].z;
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C.zx() += pos1[i].z * pos2[i].x;
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C.zy() += pos1[i].z * pos2[i].y;
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C.zz() += pos1[i].z * pos2[i].z;
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}
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}
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void colvarmodule::rotation::compute_overlap_matrix()
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{
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// build the "overlap" matrix, whose eigenvectors are stationary
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// points of the RMSD in the space of rotations
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S[0][0] = C.xx() + C.yy() + C.zz();
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S[1][0] = C.yz() - C.zy();
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S[0][1] = S[1][0];
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S[2][0] = - C.xz() + C.zx() ;
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S[0][2] = S[2][0];
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S[3][0] = C.xy() - C.yx();
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S[0][3] = S[3][0];
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S[1][1] = C.xx() - C.yy() - C.zz();
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S[2][1] = C.xy() + C.yx();
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S[1][2] = S[2][1];
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S[3][1] = C.xz() + C.zx();
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S[1][3] = S[3][1];
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S[2][2] = - C.xx() + C.yy() - C.zz();
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S[3][2] = C.yz() + C.zy();
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S[2][3] = S[3][2];
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S[3][3] = - C.xx() - C.yy() + C.zz();
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}
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#ifndef COLVARS_LAMMPS
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namespace {
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void diagonalize_matrix(cvm::matrix2d<cvm::real> &m,
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cvm::vector1d<cvm::real> &eigval,
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cvm::matrix2d<cvm::real> &eigvec)
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{
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eigval.resize(4);
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eigval.reset();
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eigvec.resize(4, 4);
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eigvec.reset();
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// diagonalize
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int jac_nrot = 0;
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if (NR_Jacobi::jacobi(m.c_array(), eigval.c_array(), eigvec.c_array(), &jac_nrot) !=
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COLVARS_OK) {
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cvm::error("Too many iterations in jacobi diagonalization.\n"
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"This is usually the result of an ill-defined set of atoms for "
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"rotational alignment (RMSD, rotateReference, etc).\n");
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}
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NR_Jacobi::eigsrt(eigval.c_array(), eigvec.c_array());
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// jacobi saves eigenvectors by columns
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NR_Jacobi::transpose(eigvec.c_array());
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// normalize eigenvectors
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for (size_t ie = 0; ie < 4; ie++) {
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cvm::real norm2 = 0.0;
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size_t i;
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for (i = 0; i < 4; i++) {
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norm2 += eigvec[ie][i] * eigvec[ie][i];
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}
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cvm::real const norm = cvm::sqrt(norm2);
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for (i = 0; i < 4; i++) {
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eigvec[ie][i] /= norm;
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}
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}
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}
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}
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#endif
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// Calculate the rotation, plus its derivatives
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void colvarmodule::rotation::calc_optimal_rotation(
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std::vector<cvm::atom_pos> const &pos1,
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std::vector<cvm::atom_pos> const &pos2)
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{
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C.resize(3, 3);
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C.reset();
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build_correlation_matrix(pos1, pos2);
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S.resize(4, 4);
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S.reset();
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compute_overlap_matrix();
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S_backup.resize(4, 4);
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S_backup = S;
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if (b_debug_gradients) {
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cvm::log("S = "+cvm::to_str(S_backup, cvm::cv_width, cvm::cv_prec)+"\n");
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}
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S_eigval.resize(4);
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S_eigvec.resize(4, 4);
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#ifdef COLVARS_LAMMPS
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MathEigen::Jacobi<cvm::real,
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cvm::vector1d<cvm::real> &,
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cvm::matrix2d<cvm::real> &> *ecalc =
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reinterpret_cast<MathEigen::Jacobi<cvm::real,
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cvm::vector1d<cvm::real> &,
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cvm::matrix2d<cvm::real> &> *>(jacobi);
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int ierror = ecalc->Diagonalize(S, S_eigval, S_eigvec);
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if (ierror) {
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cvm::error("Too many iterations in jacobi diagonalization.\n"
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"This is usually the result of an ill-defined set of atoms for "
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"rotational alignment (RMSD, rotateReference, etc).\n");
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}
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#else
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diagonalize_matrix(S, S_eigval, S_eigvec);
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#endif
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// eigenvalues and eigenvectors
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cvm::real const L0 = S_eigval[0];
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cvm::real const L1 = S_eigval[1];
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cvm::real const L2 = S_eigval[2];
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cvm::real const L3 = S_eigval[3];
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cvm::quaternion const Q0(S_eigvec[0]);
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cvm::quaternion const Q1(S_eigvec[1]);
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cvm::quaternion const Q2(S_eigvec[2]);
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cvm::quaternion const Q3(S_eigvec[3]);
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lambda = L0;
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q = Q0;
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if (cvm::rotation::monitor_crossings) {
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if (q_old.norm2() > 0.0) {
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q.match(q_old);
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if (q_old.inner(q) < (1.0 - crossing_threshold)) {
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cvm::log("Warning: one molecular orientation has changed by more than "+
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cvm::to_str(crossing_threshold)+": discontinuous rotation ?\n");
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}
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}
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q_old = q;
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}
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if (b_debug_gradients) {
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cvm::log("L0 = "+cvm::to_str(L0, cvm::cv_width, cvm::cv_prec)+
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", Q0 = "+cvm::to_str(Q0, cvm::cv_width, cvm::cv_prec)+
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", Q0*Q0 = "+cvm::to_str(Q0.inner(Q0), cvm::cv_width, cvm::cv_prec)+
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"\n");
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cvm::log("L1 = "+cvm::to_str(L1, cvm::cv_width, cvm::cv_prec)+
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", Q1 = "+cvm::to_str(Q1, cvm::cv_width, cvm::cv_prec)+
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", Q0*Q1 = "+cvm::to_str(Q0.inner(Q1), cvm::cv_width, cvm::cv_prec)+
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"\n");
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cvm::log("L2 = "+cvm::to_str(L2, cvm::cv_width, cvm::cv_prec)+
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", Q2 = "+cvm::to_str(Q2, cvm::cv_width, cvm::cv_prec)+
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", Q0*Q2 = "+cvm::to_str(Q0.inner(Q2), cvm::cv_width, cvm::cv_prec)+
|
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"\n");
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cvm::log("L3 = "+cvm::to_str(L3, cvm::cv_width, cvm::cv_prec)+
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", Q3 = "+cvm::to_str(Q3, cvm::cv_width, cvm::cv_prec)+
|
|
", Q0*Q3 = "+cvm::to_str(Q0.inner(Q3), cvm::cv_width, cvm::cv_prec)+
|
|
"\n");
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}
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|
|
|
// calculate derivatives of L0 and Q0 with respect to each atom in
|
|
// either group; note: if dS_1 is a null vector, nothing will be
|
|
// calculated
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|
size_t ia;
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|
for (ia = 0; ia < dS_1.size(); ia++) {
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|
|
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cvm::real const &a2x = pos2[ia].x;
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|
cvm::real const &a2y = pos2[ia].y;
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|
cvm::real const &a2z = pos2[ia].z;
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|
|
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cvm::matrix2d<cvm::rvector> &ds_1 = dS_1[ia];
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|
|
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// derivative of the S matrix
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|
ds_1.reset();
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|
ds_1[0][0].set( a2x, a2y, a2z);
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|
ds_1[1][0].set( 0.0, a2z, -a2y);
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ds_1[0][1] = ds_1[1][0];
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|
ds_1[2][0].set(-a2z, 0.0, a2x);
|
|
ds_1[0][2] = ds_1[2][0];
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|
ds_1[3][0].set( a2y, -a2x, 0.0);
|
|
ds_1[0][3] = ds_1[3][0];
|
|
ds_1[1][1].set( a2x, -a2y, -a2z);
|
|
ds_1[2][1].set( a2y, a2x, 0.0);
|
|
ds_1[1][2] = ds_1[2][1];
|
|
ds_1[3][1].set( a2z, 0.0, a2x);
|
|
ds_1[1][3] = ds_1[3][1];
|
|
ds_1[2][2].set(-a2x, a2y, -a2z);
|
|
ds_1[3][2].set( 0.0, a2z, a2y);
|
|
ds_1[2][3] = ds_1[3][2];
|
|
ds_1[3][3].set(-a2x, -a2y, a2z);
|
|
|
|
cvm::rvector &dl0_1 = dL0_1[ia];
|
|
cvm::vector1d<cvm::rvector> &dq0_1 = dQ0_1[ia];
|
|
|
|
// matrix multiplications; derivatives of L_0 and Q_0 are
|
|
// calculated using Hellmann-Feynman theorem (i.e. exploiting the
|
|
// fact that the eigenvectors Q_i form an orthonormal basis)
|
|
|
|
dl0_1.reset();
|
|
for (size_t i = 0; i < 4; i++) {
|
|
for (size_t j = 0; j < 4; j++) {
|
|
dl0_1 += Q0[i] * ds_1[i][j] * Q0[j];
|
|
}
|
|
}
|
|
|
|
dq0_1.reset();
|
|
for (size_t p = 0; p < 4; p++) {
|
|
for (size_t i = 0; i < 4; i++) {
|
|
for (size_t j = 0; j < 4; j++) {
|
|
dq0_1[p] +=
|
|
(Q1[i] * ds_1[i][j] * Q0[j]) / (L0-L1) * Q1[p] +
|
|
(Q2[i] * ds_1[i][j] * Q0[j]) / (L0-L2) * Q2[p] +
|
|
(Q3[i] * ds_1[i][j] * Q0[j]) / (L0-L3) * Q3[p];
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
// do the same for the second group
|
|
for (ia = 0; ia < dS_2.size(); ia++) {
|
|
|
|
cvm::real const &a1x = pos1[ia].x;
|
|
cvm::real const &a1y = pos1[ia].y;
|
|
cvm::real const &a1z = pos1[ia].z;
|
|
|
|
cvm::matrix2d<cvm::rvector> &ds_2 = dS_2[ia];
|
|
|
|
ds_2.reset();
|
|
ds_2[0][0].set( a1x, a1y, a1z);
|
|
ds_2[1][0].set( 0.0, -a1z, a1y);
|
|
ds_2[0][1] = ds_2[1][0];
|
|
ds_2[2][0].set( a1z, 0.0, -a1x);
|
|
ds_2[0][2] = ds_2[2][0];
|
|
ds_2[3][0].set(-a1y, a1x, 0.0);
|
|
ds_2[0][3] = ds_2[3][0];
|
|
ds_2[1][1].set( a1x, -a1y, -a1z);
|
|
ds_2[2][1].set( a1y, a1x, 0.0);
|
|
ds_2[1][2] = ds_2[2][1];
|
|
ds_2[3][1].set( a1z, 0.0, a1x);
|
|
ds_2[1][3] = ds_2[3][1];
|
|
ds_2[2][2].set(-a1x, a1y, -a1z);
|
|
ds_2[3][2].set( 0.0, a1z, a1y);
|
|
ds_2[2][3] = ds_2[3][2];
|
|
ds_2[3][3].set(-a1x, -a1y, a1z);
|
|
|
|
cvm::rvector &dl0_2 = dL0_2[ia];
|
|
cvm::vector1d<cvm::rvector> &dq0_2 = dQ0_2[ia];
|
|
|
|
dl0_2.reset();
|
|
for (size_t i = 0; i < 4; i++) {
|
|
for (size_t j = 0; j < 4; j++) {
|
|
dl0_2 += Q0[i] * ds_2[i][j] * Q0[j];
|
|
}
|
|
}
|
|
|
|
dq0_2.reset();
|
|
for (size_t p = 0; p < 4; p++) {
|
|
for (size_t i = 0; i < 4; i++) {
|
|
for (size_t j = 0; j < 4; j++) {
|
|
dq0_2[p] +=
|
|
(Q1[i] * ds_2[i][j] * Q0[j]) / (L0-L1) * Q1[p] +
|
|
(Q2[i] * ds_2[i][j] * Q0[j]) / (L0-L2) * Q2[p] +
|
|
(Q3[i] * ds_2[i][j] * Q0[j]) / (L0-L3) * Q3[p];
|
|
}
|
|
}
|
|
}
|
|
|
|
if (b_debug_gradients) {
|
|
|
|
cvm::matrix2d<cvm::real> S_new(4, 4);
|
|
cvm::vector1d<cvm::real> S_new_eigval(4);
|
|
cvm::matrix2d<cvm::real> S_new_eigvec(4, 4);
|
|
|
|
// make an infitesimal move along each cartesian coordinate of
|
|
// this atom, and solve again the eigenvector problem
|
|
for (size_t comp = 0; comp < 3; comp++) {
|
|
|
|
S_new = S_backup;
|
|
// diagonalize the new overlap matrix
|
|
for (size_t i = 0; i < 4; i++) {
|
|
for (size_t j = 0; j < 4; j++) {
|
|
S_new[i][j] +=
|
|
colvarmodule::debug_gradients_step_size * ds_2[i][j][comp];
|
|
}
|
|
}
|
|
|
|
// cvm::log("S_new = "+cvm::to_str(cvm::to_str (S_new), cvm::cv_width, cvm::cv_prec)+"\n");
|
|
|
|
#ifdef COLVARS_LAMMPS
|
|
ecalc->Diagonalize(S_new, S_new_eigval, S_new_eigvec);
|
|
#else
|
|
diagonalize_matrix(S_new, S_new_eigval, S_new_eigvec);
|
|
#endif
|
|
|
|
cvm::real const &L0_new = S_new_eigval[0];
|
|
cvm::quaternion const Q0_new(S_new_eigvec[0]);
|
|
|
|
cvm::real const DL0 = (dl0_2[comp]) * colvarmodule::debug_gradients_step_size;
|
|
cvm::quaternion const DQ0(dq0_2[0][comp] * colvarmodule::debug_gradients_step_size,
|
|
dq0_2[1][comp] * colvarmodule::debug_gradients_step_size,
|
|
dq0_2[2][comp] * colvarmodule::debug_gradients_step_size,
|
|
dq0_2[3][comp] * colvarmodule::debug_gradients_step_size);
|
|
|
|
cvm::log( "|(l_0+dl_0) - l_0^new|/l_0 = "+
|
|
cvm::to_str(cvm::fabs(L0+DL0 - L0_new)/L0, cvm::cv_width, cvm::cv_prec)+
|
|
", |(q_0+dq_0) - q_0^new| = "+
|
|
cvm::to_str((Q0+DQ0 - Q0_new).norm(), cvm::cv_width, cvm::cv_prec)+
|
|
"\n");
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
|
|
|