#if (__cplusplus >= 201103L) #include #include #include #include #include #include "colvarmodule.h" #include "colvarvalue.h" #include "colvarparse.h" #include "colvar.h" #include "colvarcomp.h" colvar::aspathCV::aspathCV(std::string const &conf): CVBasedPath(conf) { function_type = "aspathCV"; cvm::log(std::string("Total number of frames: ") + cvm::to_str(total_reference_frames) + std::string("\n")); std::vector p_weights(cv.size(), 1.0); get_keyval(conf, "weights", p_weights, std::vector(cv.size(), 1.0)); x.type(colvarvalue::type_scalar); use_explicit_gradients = true; std::vector rmsd_between_refs(total_reference_frames - 1, 0.0); computeDistanceBetweenReferenceFrames(rmsd_between_refs); cvm::real mean_square_displacements = 0.0; for (size_t i_frame = 1; i_frame < total_reference_frames; ++i_frame) { cvm::log(std::string("Distance between frame ") + cvm::to_str(i_frame) + " and " + cvm::to_str(i_frame + 1) + " is " + cvm::to_str(rmsd_between_refs[i_frame - 1]) + std::string("\n")); mean_square_displacements += rmsd_between_refs[i_frame - 1] * rmsd_between_refs[i_frame - 1]; } mean_square_displacements /= cvm::real(total_reference_frames - 1); cvm::real suggested_lambda = 1.0 / mean_square_displacements; cvm::real p_lambda; get_keyval(conf, "lambda", p_lambda, suggested_lambda); ArithmeticPathCV::ArithmeticPathBase::initialize(cv.size(), total_reference_frames, p_lambda, ref_cv[0], p_weights); cvm::log(std::string("Lambda is ") + cvm::to_str(lambda) + std::string("\n")); for (size_t i_cv = 0; i_cv < cv.size(); ++i_cv) { if (!cv[i_cv]->is_enabled(f_cvc_explicit_gradient)) { use_explicit_gradients = false; } cvm::log(std::string("The weight of CV ") + cvm::to_str(i_cv) + std::string(" is ") + cvm::to_str(weights[i_cv]) + std::string("\n")); } } void colvar::aspathCV::updateDistanceToReferenceFrames() { for (size_t i_cv = 0; i_cv < cv.size(); ++i_cv) { cv[i_cv]->calc_value(); } for (size_t i_frame = 0; i_frame < ref_cv.size(); ++i_frame) { for (size_t i_cv = 0; i_cv < cv.size(); ++i_cv) { colvarvalue ref_cv_value(ref_cv[i_frame][i_cv]); colvarvalue current_cv_value(cv[i_cv]->value()); if (current_cv_value.type() == colvarvalue::type_scalar) { frame_element_distances[i_frame][i_cv] = 0.5 * cv[i_cv]->dist2_lgrad(cv[i_cv]->sup_coeff * (cvm::pow(current_cv_value.real_value, cv[i_cv]->sup_np)), ref_cv_value.real_value); } else { frame_element_distances[i_frame][i_cv] = 0.5 * cv[i_cv]->dist2_lgrad(cv[i_cv]->sup_coeff * current_cv_value, ref_cv_value); } } } } void colvar::aspathCV::calc_value() { computeValue(); x = s; } void colvar::aspathCV::calc_gradients() { computeDerivatives(); for (size_t i_cv = 0; i_cv < cv.size(); ++i_cv) { cv[i_cv]->calc_gradients(); if ( cv[i_cv]->is_enabled(f_cvc_explicit_gradient) && !cv[i_cv]->is_enabled(f_cvc_scalable) && !cv[i_cv]->is_enabled(f_cvc_scalable_com)) { cvm::real factor_polynomial = getPolynomialFactorOfCVGradient(i_cv); for (size_t j_elem = 0; j_elem < cv[i_cv]->value().size(); ++j_elem) { for (size_t k_ag = 0 ; k_ag < cv[i_cv]->atom_groups.size(); ++k_ag) { for (size_t l_atom = 0; l_atom < (cv[i_cv]->atom_groups)[k_ag]->size(); ++l_atom) { (*(cv[i_cv]->atom_groups)[k_ag])[l_atom].grad = dsdx[i_cv][j_elem] * factor_polynomial * (*(cv[i_cv]->atom_groups)[k_ag])[l_atom].grad; } } } } } } void colvar::aspathCV::apply_force(colvarvalue const &force) { for (size_t i_cv = 0; i_cv < cv.size(); ++i_cv) { if ( cv[i_cv]->is_enabled(f_cvc_explicit_gradient) && !cv[i_cv]->is_enabled(f_cvc_scalable) && !cv[i_cv]->is_enabled(f_cvc_scalable_com) ) { for (size_t k_ag = 0 ; k_ag < cv[i_cv]->atom_groups.size(); ++k_ag) { (cv[i_cv]->atom_groups)[k_ag]->apply_colvar_force(force.real_value); } } else { cvm::real factor_polynomial = getPolynomialFactorOfCVGradient(i_cv); colvarvalue cv_force = dsdx[i_cv] * force.real_value * factor_polynomial; cv[i_cv]->apply_force(cv_force); } } } colvar::aspathCV::~aspathCV() {} colvar::azpathCV::azpathCV(std::string const &conf): CVBasedPath(conf) { function_type = "azpathCV"; cvm::log(std::string("Total number of frames: ") + cvm::to_str(total_reference_frames) + std::string("\n")); std::vector p_weights(cv.size(), 1.0); get_keyval(conf, "weights", p_weights, std::vector(cv.size(), 1.0)); x.type(colvarvalue::type_scalar); use_explicit_gradients = true; std::vector rmsd_between_refs(total_reference_frames - 1, 0.0); computeDistanceBetweenReferenceFrames(rmsd_between_refs); cvm::real mean_square_displacements = 0.0; for (size_t i_frame = 1; i_frame < total_reference_frames; ++i_frame) { cvm::log(std::string("Distance between frame ") + cvm::to_str(i_frame) + " and " + cvm::to_str(i_frame + 1) + " is " + cvm::to_str(rmsd_between_refs[i_frame - 1]) + std::string("\n")); mean_square_displacements += rmsd_between_refs[i_frame - 1] * rmsd_between_refs[i_frame - 1]; } mean_square_displacements /= cvm::real(total_reference_frames - 1); cvm::real suggested_lambda = 1.0 / mean_square_displacements; cvm::real p_lambda; get_keyval(conf, "lambda", p_lambda, suggested_lambda); ArithmeticPathCV::ArithmeticPathBase::initialize(cv.size(), total_reference_frames, p_lambda, ref_cv[0], p_weights); cvm::log(std::string("Lambda is ") + cvm::to_str(lambda) + std::string("\n")); for (size_t i_cv = 0; i_cv < cv.size(); ++i_cv) { if (!cv[i_cv]->is_enabled(f_cvc_explicit_gradient)) { use_explicit_gradients = false; } cvm::log(std::string("The weight of CV ") + cvm::to_str(i_cv) + std::string(" is ") + cvm::to_str(weights[i_cv]) + std::string("\n")); } } void colvar::azpathCV::updateDistanceToReferenceFrames() { for (size_t i_cv = 0; i_cv < cv.size(); ++i_cv) { cv[i_cv]->calc_value(); } for (size_t i_frame = 0; i_frame < ref_cv.size(); ++i_frame) { for (size_t i_cv = 0; i_cv < cv.size(); ++i_cv) { colvarvalue ref_cv_value(ref_cv[i_frame][i_cv]); colvarvalue current_cv_value(cv[i_cv]->value()); if (current_cv_value.type() == colvarvalue::type_scalar) { frame_element_distances[i_frame][i_cv] = 0.5 * cv[i_cv]->dist2_lgrad(cv[i_cv]->sup_coeff * (cvm::pow(current_cv_value.real_value, cv[i_cv]->sup_np)), ref_cv_value.real_value); } else { frame_element_distances[i_frame][i_cv] = 0.5 * cv[i_cv]->dist2_lgrad(cv[i_cv]->sup_coeff * current_cv_value, ref_cv_value); } } } } void colvar::azpathCV::calc_value() { computeValue(); x = z; } void colvar::azpathCV::calc_gradients() { computeDerivatives(); for (size_t i_cv = 0; i_cv < cv.size(); ++i_cv) { cv[i_cv]->calc_gradients(); if ( cv[i_cv]->is_enabled(f_cvc_explicit_gradient) && !cv[i_cv]->is_enabled(f_cvc_scalable) && !cv[i_cv]->is_enabled(f_cvc_scalable_com)) { cvm::real factor_polynomial = getPolynomialFactorOfCVGradient(i_cv); for (size_t j_elem = 0; j_elem < cv[i_cv]->value().size(); ++j_elem) { for (size_t k_ag = 0 ; k_ag < cv[i_cv]->atom_groups.size(); ++k_ag) { for (size_t l_atom = 0; l_atom < (cv[i_cv]->atom_groups)[k_ag]->size(); ++l_atom) { (*(cv[i_cv]->atom_groups)[k_ag])[l_atom].grad = dzdx[i_cv][j_elem] * factor_polynomial * (*(cv[i_cv]->atom_groups)[k_ag])[l_atom].grad; } } } } } } void colvar::azpathCV::apply_force(colvarvalue const &force) { for (size_t i_cv = 0; i_cv < cv.size(); ++i_cv) { if ( cv[i_cv]->is_enabled(f_cvc_explicit_gradient) && !cv[i_cv]->is_enabled(f_cvc_scalable) && !cv[i_cv]->is_enabled(f_cvc_scalable_com) ) { for (size_t k_ag = 0 ; k_ag < cv[i_cv]->atom_groups.size(); ++k_ag) { (cv[i_cv]->atom_groups)[k_ag]->apply_colvar_force(force.real_value); } } else { cvm::real factor_polynomial = getPolynomialFactorOfCVGradient(i_cv); const colvarvalue cv_force = dzdx[i_cv] * force.real_value * factor_polynomial; cv[i_cv]->apply_force(cv_force); } } } colvar::azpathCV::~azpathCV() {} #endif