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Update Colvars to version 2022-05-09

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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
This commit is contained in:
Giacomo Fiorin
2022-05-10 11:24:54 -04:00
parent 4737b9efb7
commit 1220bea011
66 changed files with 4040 additions and 1221 deletions
Download Patch File Download Diff File Expand all files Collapse all files

79
lib/colvars/colvarcomp_distances.cpp
View File

@ -20,7 +20,7 @@
colvar::distance::distance(std::string const &conf)
: cvc(conf)
{
function_type = "distance";
set_function_type("distance");
init_as_distance();
provide(f_cvc_inv_gradient);
@ -37,7 +37,7 @@ colvar::distance::distance(std::string const &conf)
colvar::distance::distance()
: cvc()
{
function_type = "distance";
set_function_type("distance");
init_as_distance();
provide(f_cvc_inv_gradient);
@ -101,7 +101,7 @@ simple_scalar_dist_functions(distance)
colvar::distance_vec::distance_vec(std::string const &conf)
: distance(conf)
{
function_type = "distance_vec";
set_function_type("distanceVec");
enable(f_cvc_com_based);
disable(f_cvc_explicit_gradient);
x.type(colvarvalue::type_3vector);
@ -111,7 +111,7 @@ colvar::distance_vec::distance_vec(std::string const &conf)
colvar::distance_vec::distance_vec()
: distance()
{
function_type = "distance_vec";
set_function_type("distanceVec");
enable(f_cvc_com_based);
disable(f_cvc_explicit_gradient);
x.type(colvarvalue::type_3vector);
@ -171,7 +171,7 @@ colvarvalue colvar::distance_vec::dist2_rgrad(colvarvalue const &x1,
colvar::distance_z::distance_z(std::string const &conf)
: cvc(conf)
{
function_type = "distance_z";
set_function_type("distanceZ");
provide(f_cvc_inv_gradient);
provide(f_cvc_Jacobian);
enable(f_cvc_com_based);
@ -179,10 +179,11 @@ colvar::distance_z::distance_z(std::string const &conf)
// TODO detect PBC from MD engine (in simple cases)
// and then update period in real time
if (period != 0.0)
if (period != 0.0) {
enable(f_cvc_periodic);
}
if ((wrap_center != 0.0) && (period == 0.0)) {
if ((wrap_center != 0.0) && !is_enabled(f_cvc_periodic)) {
cvm::error("Error: wrapAround was defined in a distanceZ component,"
" but its period has not been set.\n");
return;
@ -219,7 +220,7 @@ colvar::distance_z::distance_z(std::string const &conf)
colvar::distance_z::distance_z()
{
function_type = "distance_z";
set_function_type("distanceZ");
provide(f_cvc_inv_gradient);
provide(f_cvc_Jacobian);
enable(f_cvc_com_based);
@ -368,7 +369,7 @@ void colvar::distance_z::wrap(colvarvalue &x_unwrapped) const
colvar::distance_xy::distance_xy(std::string const &conf)
: distance_z(conf)
{
function_type = "distance_xy";
set_function_type("distanceXY");
init_as_distance();
provide(f_cvc_inv_gradient);
@ -380,7 +381,7 @@ colvar::distance_xy::distance_xy(std::string const &conf)
colvar::distance_xy::distance_xy()
: distance_z()
{
function_type = "distance_xy";
set_function_type("distanceXY");
init_as_distance();
provide(f_cvc_inv_gradient);
@ -481,7 +482,7 @@ simple_scalar_dist_functions(distance_xy)
colvar::distance_dir::distance_dir(std::string const &conf)
: distance(conf)
{
function_type = "distance_dir";
set_function_type("distanceDir");
enable(f_cvc_com_based);
disable(f_cvc_explicit_gradient);
x.type(colvarvalue::type_unit3vector);
@ -491,7 +492,7 @@ colvar::distance_dir::distance_dir(std::string const &conf)
colvar::distance_dir::distance_dir()
: distance()
{
function_type = "distance_dir";
set_function_type("distanceDir");
enable(f_cvc_com_based);
disable(f_cvc_explicit_gradient);
x.type(colvarvalue::type_unit3vector);
@ -559,7 +560,7 @@ colvarvalue colvar::distance_dir::dist2_rgrad(colvarvalue const &x1,
colvar::distance_inv::distance_inv(std::string const &conf)
: cvc(conf)
{
function_type = "distance_inv";
set_function_type("distanceInv");
init_as_distance();
group1 = parse_group(conf, "group1");
@ -658,7 +659,7 @@ simple_scalar_dist_functions(distance_inv)
colvar::distance_pairs::distance_pairs(std::string const &conf)
: cvc(conf)
{
function_type = "distance_pairs";
set_function_type("distancePairs");
group1 = parse_group(conf, "group1");
group2 = parse_group(conf, "group2");
@ -671,7 +672,7 @@ colvar::distance_pairs::distance_pairs(std::string const &conf)
colvar::distance_pairs::distance_pairs()
{
function_type = "distance_pairs";
set_function_type("distancePairs");
disable(f_cvc_explicit_gradient);
x.type(colvarvalue::type_vector);
}
@ -743,7 +744,7 @@ void colvar::distance_pairs::apply_force(colvarvalue const &force)
colvar::dipole_magnitude::dipole_magnitude(std::string const &conf)
: cvc(conf)
{
function_type = "dipole_magnitude";
set_function_type("dipoleMagnitude");
atoms = parse_group(conf, "atoms");
init_total_force_params(conf);
x.type(colvarvalue::type_scalar);
@ -752,6 +753,7 @@ colvar::dipole_magnitude::dipole_magnitude(std::string const &conf)
colvar::dipole_magnitude::dipole_magnitude(cvm::atom const &a1)
{
set_function_type("dipoleMagnitude");
atoms = new cvm::atom_group(std::vector<cvm::atom>(1, a1));
register_atom_group(atoms);
x.type(colvarvalue::type_scalar);
@ -760,7 +762,7 @@ colvar::dipole_magnitude::dipole_magnitude(cvm::atom const &a1)
colvar::dipole_magnitude::dipole_magnitude()
{
function_type = "dipole_magnitude";
set_function_type("dipoleMagnitude");
x.type(colvarvalue::type_scalar);
}
@ -800,7 +802,7 @@ simple_scalar_dist_functions(dipole_magnitude)
colvar::gyration::gyration(std::string const &conf)
: cvc(conf)
{
function_type = "gyration";
set_function_type("gyration");
init_as_distance();
provide(f_cvc_inv_gradient);
@ -869,7 +871,7 @@ simple_scalar_dist_functions(gyration)
colvar::inertia::inertia(std::string const &conf)
: gyration(conf)
{
function_type = "inertia";
set_function_type("inertia");
init_as_distance();
}
@ -905,11 +907,11 @@ simple_scalar_dist_functions(inertia_z)
colvar::inertia_z::inertia_z(std::string const &conf)
: inertia(conf)
{
function_type = "inertia_z";
set_function_type("inertiaZ");
init_as_distance();
if (get_keyval(conf, "axis", axis, cvm::rvector(0.0, 0.0, 1.0))) {
if (axis.norm2() == 0.0) {
cvm::error("Axis vector is zero!", INPUT_ERROR);
cvm::error("Axis vector is zero!", COLVARS_INPUT_ERROR);
return;
}
if (axis.norm2() != 1.0) {
@ -953,7 +955,7 @@ simple_scalar_dist_functions(inertia)
colvar::rmsd::rmsd(std::string const &conf)
: cvc(conf)
{
function_type = "rmsd";
set_function_type("rmsd");
init_as_distance();
provide(f_cvc_inv_gradient);
@ -1217,9 +1219,9 @@ simple_scalar_dist_functions(rmsd)
colvar::eigenvector::eigenvector(std::string const &conf)
: cvc(conf)
{
set_function_type("eigenvector");
provide(f_cvc_inv_gradient);
provide(f_cvc_Jacobian);
function_type = "eigenvector";
x.type(colvarvalue::type_scalar);
atoms = parse_group(conf, "atoms");
@ -1263,13 +1265,13 @@ colvar::eigenvector::eigenvector(std::string const &conf)
}
if (ref_pos.size() == 0) {
cvm::error("Error: reference positions were not provided.\n", INPUT_ERROR);
cvm::error("Error: reference positions were not provided.\n", COLVARS_INPUT_ERROR);
return;
}
if (ref_pos.size() != atoms->size()) {
cvm::error("Error: reference positions do not "
"match the number of requested atoms.\n", INPUT_ERROR);
"match the number of requested atoms.\n", COLVARS_INPUT_ERROR);
return;
}
@ -1368,7 +1370,7 @@ colvar::eigenvector::eigenvector(std::string const &conf)
eigenvec[i] = atoms->rot.rotate(eigenvec[i]);
}
}
cvm::log("\"differenceVector\" is on: subtracting the reference positions from the provided vector: v = v - x0.\n");
cvm::log("\"differenceVector\" is on: subtracting the reference positions from the provided vector: v = x_vec - x_ref.\n");
for (size_t i = 0; i < atoms->size(); i++) {
eigenvec[i] -= ref_pos[i];
}
@ -1386,22 +1388,32 @@ colvar::eigenvector::eigenvector(std::string const &conf)
}
}
// cvm::log("The first three components(v1x, v1y, v1z) of the resulting vector are: "+cvm::to_str (eigenvec[0])+".\n");
// for inverse gradients
// eigenvec_invnorm2 is used when computing inverse gradients
eigenvec_invnorm2 = 0.0;
for (size_t ein = 0; ein < atoms->size(); ein++) {
eigenvec_invnorm2 += eigenvec[ein].norm2();
}
eigenvec_invnorm2 = 1.0 / eigenvec_invnorm2;
if (b_difference_vector) {
cvm::log("\"differenceVector\" is on: normalizing the vector.\n");
// Vector normalization overrides the default normalization for differenceVector
bool normalize = false;
get_keyval(conf, "normalizeVector", normalize, normalize);
if (normalize) {
cvm::log("Normalizing the vector so that |v| = 1.\n");
for (size_t i = 0; i < atoms->size(); i++) {
eigenvec[i] *= cvm::sqrt(eigenvec_invnorm2);
}
eigenvec_invnorm2 = 1.0;
} else if (b_difference_vector) {
cvm::log("Normalizing the vector so that the norm of the projection |v ⋅ (x_vec - x_ref)| = 1.\n");
for (size_t i = 0; i < atoms->size(); i++) {
eigenvec[i] *= eigenvec_invnorm2;
}
eigenvec_invnorm2 = 1.0/eigenvec_invnorm2;
} else {
cvm::log("The norm of the vector is |v| = "+cvm::to_str(eigenvec_invnorm2)+".\n");
cvm::log("The norm of the vector is |v| = "+
cvm::to_str(1.0/cvm::sqrt(eigenvec_invnorm2))+".\n");
}
}
@ -1500,7 +1512,7 @@ simple_scalar_dist_functions(eigenvector)
colvar::cartesian::cartesian(std::string const &conf)
: cvc(conf)
{
function_type = "cartesian";
set_function_type("cartesian");
atoms = parse_group(conf, "atoms");
@ -1560,4 +1572,3 @@ void colvar::cartesian::apply_force(colvarvalue const &force)
}
}
}