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
956 lines
28 KiB
C++
956 lines
28 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 "colvarmodule.h"
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#include "colvarvalue.h"
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#include "colvarparse.h"
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#include "colvar.h"
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#include "colvarcomp.h"
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#include "colvargrid.h"
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#include <ctime>
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colvar_grid_count::colvar_grid_count()
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: colvar_grid<size_t>()
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{
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mult = 1;
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}
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colvar_grid_count::colvar_grid_count(std::vector<int> const &nx_i,
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size_t const &def_count)
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: colvar_grid<size_t>(nx_i, def_count, 1)
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{}
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colvar_grid_count::colvar_grid_count(std::vector<colvar *> &colvars,
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size_t const &def_count,
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bool margin)
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: colvar_grid<size_t>(colvars, def_count, 1, margin)
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{}
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colvar_grid_scalar::colvar_grid_scalar()
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: colvar_grid<cvm::real>(), samples(NULL)
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{}
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colvar_grid_scalar::colvar_grid_scalar(colvar_grid_scalar const &g)
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: colvar_grid<cvm::real>(g), samples(NULL)
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{
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}
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colvar_grid_scalar::colvar_grid_scalar(std::vector<int> const &nx_i)
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: colvar_grid<cvm::real>(nx_i, 0.0, 1), samples(NULL)
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{
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}
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colvar_grid_scalar::colvar_grid_scalar(std::vector<colvar *> &colvars, bool margin)
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: colvar_grid<cvm::real>(colvars, 0.0, 1, margin), samples(NULL)
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{
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}
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colvar_grid_scalar::~colvar_grid_scalar()
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{
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}
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cvm::real colvar_grid_scalar::maximum_value() const
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{
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cvm::real max = data[0];
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for (size_t i = 0; i < nt; i++) {
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if (data[i] > max) max = data[i];
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}
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return max;
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}
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cvm::real colvar_grid_scalar::minimum_value() const
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{
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cvm::real min = data[0];
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for (size_t i = 0; i < nt; i++) {
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if (data[i] < min) min = data[i];
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}
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return min;
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}
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cvm::real colvar_grid_scalar::minimum_pos_value() const
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{
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cvm::real minpos = data[0];
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size_t i;
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for (i = 0; i < nt; i++) {
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if(data[i] > 0) {
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minpos = data[i];
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break;
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}
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}
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for (i = 0; i < nt; i++) {
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if (data[i] > 0 && data[i] < minpos) minpos = data[i];
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}
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return minpos;
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}
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cvm::real colvar_grid_scalar::integral() const
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{
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cvm::real sum = 0.0;
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for (size_t i = 0; i < nt; i++) {
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sum += data[i];
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}
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cvm::real bin_volume = 1.0;
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for (size_t id = 0; id < widths.size(); id++) {
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bin_volume *= widths[id];
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}
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return bin_volume * sum;
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}
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cvm::real colvar_grid_scalar::entropy() const
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{
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cvm::real sum = 0.0;
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for (size_t i = 0; i < nt; i++) {
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if (data[i] >0) {
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sum += -1.0 * data[i] * cvm::logn(data[i]);
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}
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}
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cvm::real bin_volume = 1.0;
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for (size_t id = 0; id < widths.size(); id++) {
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bin_volume *= widths[id];
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}
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return bin_volume * sum;
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}
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colvar_grid_gradient::colvar_grid_gradient()
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: colvar_grid<cvm::real>(),
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samples(NULL),
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weights(NULL)
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{}
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colvar_grid_gradient::colvar_grid_gradient(std::vector<int> const &nx_i)
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: colvar_grid<cvm::real>(nx_i, 0.0, nx_i.size()),
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samples(NULL),
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weights(NULL)
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{}
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colvar_grid_gradient::colvar_grid_gradient(std::vector<colvar *> &colvars)
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: colvar_grid<cvm::real>(colvars, 0.0, colvars.size()),
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samples(NULL),
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weights(NULL)
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{}
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colvar_grid_gradient::colvar_grid_gradient(std::string &filename)
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: colvar_grid<cvm::real>(),
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samples(NULL),
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weights(NULL)
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{
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std::ifstream is;
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is.open(filename.c_str());
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if (!is.is_open()) {
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cvm::error("Error opening multicol gradient file " + filename + " for reading.\n");
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return;
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}
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// Data in the header: nColvars, then for each
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// xiMin, dXi, nPoints, periodic flag
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std::string hash;
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size_t i;
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if ( !(is >> hash) || (hash != "#") ) {
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cvm::error("Error reading grid at position "+
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cvm::to_str(static_cast<size_t>(is.tellg()))+
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" in stream(read \"" + hash + "\")\n");
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return;
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}
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is >> nd;
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if (nd > 50) {
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cvm::error("Error: excessive number of dimensions in file \""+
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filename+"\". Please ensure that the file is not corrupt.\n",
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COLVARS_INPUT_ERROR);
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return;
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}
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mult = nd;
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std::vector<cvm::real> lower_in(nd), widths_in(nd);
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std::vector<int> nx_in(nd);
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std::vector<int> periodic_in(nd);
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for (i = 0; i < nd; i++ ) {
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if ( !(is >> hash) || (hash != "#") ) {
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cvm::error("Error reading grid at position "+
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cvm::to_str(static_cast<size_t>(is.tellg()))+
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" in stream(read \"" + hash + "\")\n");
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return;
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}
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is >> lower_in[i] >> widths_in[i] >> nx_in[i] >> periodic_in[i];
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}
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this->setup(nx_in, 0., mult);
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widths = widths_in;
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for (i = 0; i < nd; i++ ) {
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lower_boundaries.push_back(colvarvalue(lower_in[i]));
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periodic.push_back(static_cast<bool>(periodic_in[i]));
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}
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// Reset the istream for read_multicol, which expects the whole file
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is.clear();
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is.seekg(0);
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read_multicol(is);
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is.close();
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}
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void colvar_grid_gradient::write_1D_integral(std::ostream &os)
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{
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cvm::real bin, min, integral;
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std::vector<cvm::real> int_vals;
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os << "# xi A(xi)\n";
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if (cv.size() != 1) {
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cvm::error("Cannot write integral for multi-dimensional gradient grids.");
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return;
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}
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integral = 0.0;
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int_vals.push_back(0.0);
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min = 0.0;
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// correction for periodic colvars, so that the PMF is periodic
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cvm::real corr;
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if (periodic[0]) {
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corr = average();
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} else {
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corr = 0.0;
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}
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for (std::vector<int> ix = new_index(); index_ok(ix); incr(ix)) {
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if (samples) {
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size_t const samples_here = samples->value(ix);
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if (samples_here)
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integral += (value(ix) / cvm::real(samples_here) - corr) * cv[0]->width;
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} else {
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integral += (value(ix) - corr) * cv[0]->width;
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}
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if ( integral < min ) min = integral;
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int_vals.push_back(integral);
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}
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bin = 0.0;
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for ( int i = 0; i < nx[0]; i++, bin += 1.0 ) {
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os << std::setw(10) << cv[0]->lower_boundary.real_value + cv[0]->width * bin << " "
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<< std::setw(cvm::cv_width)
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<< std::setprecision(cvm::cv_prec)
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<< int_vals[i] - min << "\n";
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}
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os << std::setw(10) << cv[0]->lower_boundary.real_value + cv[0]->width * bin << " "
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<< std::setw(cvm::cv_width)
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<< std::setprecision(cvm::cv_prec)
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<< int_vals[nx[0]] - min << "\n";
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return;
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}
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integrate_potential::integrate_potential(std::vector<colvar *> &colvars, colvar_grid_gradient * gradients)
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: colvar_grid_scalar(colvars, true),
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gradients(gradients)
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{
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// parent class colvar_grid_scalar is constructed with margin option set to true
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// hence PMF grid is wider than gradient grid if non-PBC
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if (nd > 1) {
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cvm::main()->cite_feature("Poisson integration of 2D/3D free energy surfaces");
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divergence.resize(nt);
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// Compute inverse of Laplacian diagonal for Jacobi preconditioning
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// For now all code related to preconditioning is commented out
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// until a method better than Jacobi is implemented
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// cvm::log("Preparing inverse diagonal for preconditioning...\n");
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// inv_lap_diag.resize(nt);
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// std::vector<cvm::real> id(nt), lap_col(nt);
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// for (int i = 0; i < nt; i++) {
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// if (i % (nt / 100) == 0)
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// cvm::log(cvm::to_str(i));
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// id[i] = 1.;
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// atimes(id, lap_col);
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// id[i] = 0.;
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// inv_lap_diag[i] = 1. / lap_col[i];
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// }
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// cvm::log("Done.\n");
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}
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}
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integrate_potential::integrate_potential(colvar_grid_gradient * gradients)
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: gradients(gradients)
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{
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nd = gradients->num_variables();
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nx = gradients->number_of_points_vec();
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widths = gradients->widths;
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periodic = gradients->periodic;
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// Expand grid by 1 bin in non-periodic dimensions
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for (size_t i = 0; i < nd; i++ ) {
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if (!periodic[i]) nx[i]++;
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// Shift the grid by half the bin width (values at edges instead of center of bins)
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lower_boundaries.push_back(gradients->lower_boundaries[i].real_value - 0.5 * widths[i]);
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}
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setup(nx);
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if (nd > 1) {
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divergence.resize(nt);
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}
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}
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int integrate_potential::integrate(const int itmax, const cvm::real &tol, cvm::real & err)
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{
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int iter = 0;
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if (nd == 1) {
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cvm::real sum = 0.0;
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cvm::real corr;
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if ( periodic[0] ) {
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corr = gradients->average(); // Enforce PBC by subtracting average gradient
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} else {
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corr = 0.0;
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}
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std::vector<int> ix;
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// Iterate over valid indices in gradient grid
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for (ix = new_index(); gradients->index_ok(ix); incr(ix)) {
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set_value(ix, sum);
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sum += (gradients->value_output(ix) - corr) * widths[0];
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}
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if (index_ok(ix)) {
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// This will happen if non-periodic: then PMF grid has one extra bin wrt gradient grid
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set_value(ix, sum);
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}
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} else if (nd <= 3) {
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nr_linbcg_sym(divergence, data, tol, itmax, iter, err);
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cvm::log("Integrated in " + cvm::to_str(iter) + " steps, error: " + cvm::to_str(err) + "\n");
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} else {
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cvm::error("Cannot integrate PMF in dimension > 3\n");
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}
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return iter;
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}
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void integrate_potential::set_div()
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{
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if (nd == 1) return;
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for (std::vector<int> ix = new_index(); index_ok(ix); incr(ix)) {
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update_div_local(ix);
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}
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}
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void integrate_potential::update_div_neighbors(const std::vector<int> &ix0)
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{
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std::vector<int> ix(ix0);
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int i, j, k;
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// If not periodic, expanded grid ensures that neighbors of ix0 are valid grid points
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if (nd == 1) {
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return;
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} else if (nd == 2) {
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update_div_local(ix);
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ix[0]++; wrap(ix);
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update_div_local(ix);
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ix[1]++; wrap(ix);
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update_div_local(ix);
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ix[0]--; wrap(ix);
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update_div_local(ix);
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} else if (nd == 3) {
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for (i = 0; i<2; i++) {
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ix[1] = ix0[1];
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for (j = 0; j<2; j++) {
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ix[2] = ix0[2];
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for (k = 0; k<2; k++) {
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wrap(ix);
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update_div_local(ix);
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ix[2]++;
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}
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ix[1]++;
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}
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ix[0]++;
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}
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}
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}
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void integrate_potential::get_grad(cvm::real * g, std::vector<int> &ix)
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{
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size_t count, i;
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bool edge = gradients->wrap_edge(ix); // Detect edge if non-PBC
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if (gradients->samples) {
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count = gradients->samples->value(ix);
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} else {
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count = 1;
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}
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if (!edge && count) {
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cvm::real const *grad = &(gradients->value(ix));
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cvm::real const fact = 1.0 / count;
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for ( i = 0; i<nd; i++ ) {
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g[i] = fact * grad[i];
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}
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} else {
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for ( i = 0; i<nd; i++ ) {
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g[i] = 0.0;
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}
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}
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}
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void integrate_potential::update_div_local(const std::vector<int> &ix0)
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{
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const size_t linear_index = address(ix0);
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int i, j, k;
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std::vector<int> ix = ix0;
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if (nd == 2) {
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// gradients at grid points surrounding the current scalar grid point
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cvm::real g00[2], g01[2], g10[2], g11[2];
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get_grad(g11, ix);
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ix[0] = ix0[0] - 1;
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get_grad(g01, ix);
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ix[1] = ix0[1] - 1;
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get_grad(g00, ix);
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ix[0] = ix0[0];
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get_grad(g10, ix);
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divergence[linear_index] = ((g10[0]-g00[0] + g11[0]-g01[0]) / widths[0]
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+ (g01[1]-g00[1] + g11[1]-g10[1]) / widths[1]) * 0.5;
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} else if (nd == 3) {
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cvm::real gc[24]; // stores 3d gradients in 8 contiguous bins
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int index = 0;
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ix[0] = ix0[0] - 1;
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for (i = 0; i<2; i++) {
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ix[1] = ix0[1] - 1;
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for (j = 0; j<2; j++) {
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ix[2] = ix0[2] - 1;
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for (k = 0; k<2; k++) {
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get_grad(gc + index, ix);
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index += 3;
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ix[2]++;
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}
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ix[1]++;
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}
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ix[0]++;
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}
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divergence[linear_index] =
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((gc[3*4]-gc[0] + gc[3*5]-gc[3*1] + gc[3*6]-gc[3*2] + gc[3*7]-gc[3*3])
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/ widths[0]
|
|
+ (gc[3*2+1]-gc[0+1] + gc[3*3+1]-gc[3*1+1] + gc[3*6+1]-gc[3*4+1] + gc[3*7+1]-gc[3*5+1])
|
|
/ widths[1]
|
|
+ (gc[3*1+2]-gc[0+2] + gc[3*3+2]-gc[3*2+2] + gc[3*5+2]-gc[3*4+2] + gc[3*7+2]-gc[3*6+2])
|
|
/ widths[2]) * 0.25;
|
|
}
|
|
}
|
|
|
|
|
|
/// Multiplication by sparse matrix representing Laplacian
|
|
/// NOTE: Laplacian must be symmetric for solving with CG
|
|
void integrate_potential::atimes(const std::vector<cvm::real> &A, std::vector<cvm::real> &LA)
|
|
{
|
|
if (nd == 2) {
|
|
// DIMENSION 2
|
|
|
|
size_t index, index2;
|
|
int i, j;
|
|
cvm::real fact;
|
|
const cvm::real ffx = 1.0 / (widths[0] * widths[0]);
|
|
const cvm::real ffy = 1.0 / (widths[1] * widths[1]);
|
|
const int h = nx[1];
|
|
const int w = nx[0];
|
|
// offsets for 4 reference points of the Laplacian stencil
|
|
int xm = -h;
|
|
int xp = h;
|
|
int ym = -1;
|
|
int yp = 1;
|
|
|
|
// NOTE on performance: this version is slightly sub-optimal because
|
|
// it contains two double loops on the core of the array (for x and y terms)
|
|
// The slightly faster version is in commit 0254cb5a2958cb2e135f268371c4b45fad34866b
|
|
// yet it is much uglier, and probably horrible to extend to dimension 3
|
|
// All terms in the matrix are assigned (=) during the x loops, then updated (+=)
|
|
// with the y (and z) contributions
|
|
|
|
|
|
// All x components except on x edges
|
|
index = h; // Skip first column
|
|
|
|
// Halve the term on y edges (if any) to preserve symmetry of the Laplacian matrix
|
|
// (Long Chen, Finite Difference Methods, UCI, 2017)
|
|
fact = periodic[1] ? 1.0 : 0.5;
|
|
|
|
for (i=1; i<w-1; i++) {
|
|
// Full range of j, but factor may change on y edges (j == 0 and j == h-1)
|
|
LA[index] = fact * ffx * (A[index + xm] + A[index + xp] - 2.0 * A[index]);
|
|
index++;
|
|
for (j=1; j<h-1; j++) {
|
|
LA[index] = ffx * (A[index + xm] + A[index + xp] - 2.0 * A[index]);
|
|
index++;
|
|
}
|
|
LA[index] = fact * ffx * (A[index + xm] + A[index + xp] - 2.0 * A[index]);
|
|
index++;
|
|
}
|
|
// Edges along x (x components only)
|
|
index = 0L; // Follows left edge
|
|
index2 = h * static_cast<size_t>(w - 1); // Follows right edge
|
|
if (periodic[0]) {
|
|
xm = h * (w - 1);
|
|
xp = h;
|
|
fact = periodic[1] ? 1.0 : 0.5;
|
|
LA[index] = fact * ffx * (A[index + xm] + A[index + xp] - 2.0 * A[index]);
|
|
LA[index2] = fact * ffx * (A[index2 - xp] + A[index2 - xm] - 2.0 * A[index2]);
|
|
index++;
|
|
index2++;
|
|
for (j=1; j<h-1; j++) {
|
|
LA[index] = ffx * (A[index + xm] + A[index + xp] - 2.0 * A[index]);
|
|
LA[index2] = ffx * (A[index2 - xp] + A[index2 - xm] - 2.0 * A[index2]);
|
|
index++;
|
|
index2++;
|
|
}
|
|
LA[index] = fact * ffx * (A[index + xm] + A[index + xp] - 2.0 * A[index]);
|
|
LA[index2] = fact * ffx * (A[index2 - xp] + A[index2 - xm] - 2.0 * A[index2]);
|
|
} else {
|
|
xm = -h;
|
|
xp = h;
|
|
fact = periodic[1] ? 1.0 : 0.5; // Halve in corners in full PBC only
|
|
// lower corner, "j == 0"
|
|
LA[index] = fact * ffx * (A[index + xp] - A[index]);
|
|
LA[index2] = fact * ffx * (A[index2 + xm] - A[index2]);
|
|
index++;
|
|
index2++;
|
|
for (j=1; j<h-1; j++) {
|
|
// x gradient (+ y term of laplacian, calculated below)
|
|
LA[index] = ffx * (A[index + xp] - A[index]);
|
|
LA[index2] = ffx * (A[index2 + xm] - A[index2]);
|
|
index++;
|
|
index2++;
|
|
}
|
|
// upper corner, j == h-1
|
|
LA[index] = fact * ffx * (A[index + xp] - A[index]);
|
|
LA[index2] = fact * ffx * (A[index2 + xm] - A[index2]);
|
|
}
|
|
|
|
// Now adding all y components
|
|
// All y components except on y edges
|
|
index = 1; // Skip first element (in first row)
|
|
|
|
fact = periodic[0] ? 1.0 : 0.5; // for i == 0
|
|
for (i=0; i<w; i++) {
|
|
// Factor of 1/2 on x edges if non-periodic
|
|
if (i == 1) fact = 1.0;
|
|
if (i == w - 1) fact = periodic[0] ? 1.0 : 0.5;
|
|
for (j=1; j<h-1; j++) {
|
|
LA[index] += fact * ffy * (A[index + ym] + A[index + yp] - 2.0 * A[index]);
|
|
index++;
|
|
}
|
|
index += 2; // skip the edges and move to next column
|
|
}
|
|
// Edges along y (y components only)
|
|
index = 0L; // Follows bottom edge
|
|
index2 = h - 1; // Follows top edge
|
|
if (periodic[1]) {
|
|
fact = periodic[0] ? 1.0 : 0.5;
|
|
ym = h - 1;
|
|
yp = 1;
|
|
LA[index] += fact * ffy * (A[index + ym] + A[index + yp] - 2.0 * A[index]);
|
|
LA[index2] += fact * ffy * (A[index2 - yp] + A[index2 - ym] - 2.0 * A[index2]);
|
|
index += h;
|
|
index2 += h;
|
|
for (i=1; i<w-1; i++) {
|
|
LA[index] += ffy * (A[index + ym] + A[index + yp] - 2.0 * A[index]);
|
|
LA[index2] += ffy * (A[index2 - yp] + A[index2 - ym] - 2.0 * A[index2]);
|
|
index += h;
|
|
index2 += h;
|
|
}
|
|
LA[index] += fact * ffy * (A[index + ym] + A[index + yp] - 2.0 * A[index]);
|
|
LA[index2] += fact * ffy * (A[index2 - yp] + A[index2 - ym] - 2.0 * A[index2]);
|
|
} else {
|
|
ym = -1;
|
|
yp = 1;
|
|
fact = periodic[0] ? 1.0 : 0.5; // Halve in corners in full PBC only
|
|
// Left corner
|
|
LA[index] += fact * ffy * (A[index + yp] - A[index]);
|
|
LA[index2] += fact * ffy * (A[index2 + ym] - A[index2]);
|
|
index += h;
|
|
index2 += h;
|
|
for (i=1; i<w-1; i++) {
|
|
// y gradient (+ x term of laplacian, calculated above)
|
|
LA[index] += ffy * (A[index + yp] - A[index]);
|
|
LA[index2] += ffy * (A[index2 + ym] - A[index2]);
|
|
index += h;
|
|
index2 += h;
|
|
}
|
|
// Right corner
|
|
LA[index] += fact * ffy * (A[index + yp] - A[index]);
|
|
LA[index2] += fact * ffy * (A[index2 + ym] - A[index2]);
|
|
}
|
|
|
|
} else if (nd == 3) {
|
|
// DIMENSION 3
|
|
|
|
int i, j, k;
|
|
size_t index, index2;
|
|
cvm::real fact = 1.0;
|
|
const cvm::real ffx = 1.0 / (widths[0] * widths[0]);
|
|
const cvm::real ffy = 1.0 / (widths[1] * widths[1]);
|
|
const cvm::real ffz = 1.0 / (widths[2] * widths[2]);
|
|
const int h = nx[2]; // height
|
|
const int d = nx[1]; // depth
|
|
const int w = nx[0]; // width
|
|
// offsets for 6 reference points of the Laplacian stencil
|
|
int xm = -d * h;
|
|
int xp = d * h;
|
|
int ym = -h;
|
|
int yp = h;
|
|
int zm = -1;
|
|
int zp = 1;
|
|
|
|
cvm::real factx = periodic[0] ? 1 : 0.5; // factor to be applied on x edges
|
|
cvm::real facty = periodic[1] ? 1 : 0.5; // same for y
|
|
cvm::real factz = periodic[2] ? 1 : 0.5; // same for z
|
|
cvm::real ifactx = 1 / factx;
|
|
cvm::real ifacty = 1 / facty;
|
|
cvm::real ifactz = 1 / factz;
|
|
|
|
// All x components except on x edges
|
|
index = d * static_cast<size_t>(h); // Skip left slab
|
|
fact = facty * factz;
|
|
for (i=1; i<w-1; i++) {
|
|
for (j=0; j<d; j++) { // full range of y
|
|
if (j == 1) fact *= ifacty;
|
|
if (j == d-1) fact *= facty;
|
|
LA[index] = fact * ffx * (A[index + xm] + A[index + xp] - 2.0 * A[index]);
|
|
index++;
|
|
fact *= ifactz;
|
|
for (k=1; k<h-1; k++) { // full range of z
|
|
LA[index] = fact * ffx * (A[index + xm] + A[index + xp] - 2.0 * A[index]);
|
|
index++;
|
|
}
|
|
fact *= factz;
|
|
LA[index] = fact * ffx * (A[index + xm] + A[index + xp] - 2.0 * A[index]);
|
|
index++;
|
|
}
|
|
}
|
|
// Edges along x (x components only)
|
|
index = 0L; // Follows left slab
|
|
index2 = static_cast<size_t>(d) * h * (w - 1); // Follows right slab
|
|
if (periodic[0]) {
|
|
xm = d * h * (w - 1);
|
|
xp = d * h;
|
|
fact = facty * factz;
|
|
for (j=0; j<d; j++) {
|
|
if (j == 1) fact *= ifacty;
|
|
if (j == d-1) fact *= facty;
|
|
LA[index] = fact * ffx * (A[index + xm] + A[index + xp] - 2.0 * A[index]);
|
|
LA[index2] = fact * ffx * (A[index2 - xp] + A[index2 - xm] - 2.0 * A[index2]);
|
|
index++;
|
|
index2++;
|
|
fact *= ifactz;
|
|
for (k=1; k<h-1; k++) {
|
|
LA[index] = fact * ffx * (A[index + xm] + A[index + xp] - 2.0 * A[index]);
|
|
LA[index2] = fact * ffx * (A[index2 - xp] + A[index2 - xm] - 2.0 * A[index2]);
|
|
index++;
|
|
index2++;
|
|
}
|
|
fact *= factz;
|
|
LA[index] = fact * ffx * (A[index + xm] + A[index + xp] - 2.0 * A[index]);
|
|
LA[index2] = fact * ffx * (A[index2 - xp] + A[index2 - xm] - 2.0 * A[index2]);
|
|
index++;
|
|
index2++;
|
|
}
|
|
} else {
|
|
xm = -d * h;
|
|
xp = d * h;
|
|
fact = facty * factz;
|
|
for (j=0; j<d; j++) {
|
|
if (j == 1) fact *= ifacty;
|
|
if (j == d-1) fact *= facty;
|
|
LA[index] = fact * ffx * (A[index + xp] - A[index]);
|
|
LA[index2] = fact * ffx * (A[index2 + xm] - A[index2]);
|
|
index++;
|
|
index2++;
|
|
fact *= ifactz;
|
|
for (k=1; k<h-1; k++) {
|
|
// x gradient (+ y, z terms of laplacian, calculated below)
|
|
LA[index] = fact * ffx * (A[index + xp] - A[index]);
|
|
LA[index2] = fact * ffx * (A[index2 + xm] - A[index2]);
|
|
index++;
|
|
index2++;
|
|
}
|
|
fact *= factz;
|
|
LA[index] = fact * ffx * (A[index + xp] - A[index]);
|
|
LA[index2] = fact * ffx * (A[index2 + xm] - A[index2]);
|
|
index++;
|
|
index2++;
|
|
}
|
|
}
|
|
|
|
// Now adding all y components
|
|
// All y components except on y edges
|
|
index = h; // Skip first column (in front slab)
|
|
fact = factx * factz;
|
|
for (i=0; i<w; i++) { // full range of x
|
|
if (i == 1) fact *= ifactx;
|
|
if (i == w-1) fact *= factx;
|
|
for (j=1; j<d-1; j++) {
|
|
LA[index] += fact * ffy * (A[index + ym] + A[index + yp] - 2.0 * A[index]);
|
|
index++;
|
|
fact *= ifactz;
|
|
for (k=1; k<h-1; k++) {
|
|
LA[index] += fact * ffy * (A[index + ym] + A[index + yp] - 2.0 * A[index]);
|
|
index++;
|
|
}
|
|
fact *= factz;
|
|
LA[index] += fact * ffy * (A[index + ym] + A[index + yp] - 2.0 * A[index]);
|
|
index++;
|
|
}
|
|
index += 2 * h; // skip columns in front and back slabs
|
|
}
|
|
// Edges along y (y components only)
|
|
index = 0L; // Follows front slab
|
|
index2 = h * static_cast<size_t>(d - 1); // Follows back slab
|
|
if (periodic[1]) {
|
|
ym = h * (d - 1);
|
|
yp = h;
|
|
fact = factx * factz;
|
|
for (i=0; i<w; i++) {
|
|
if (i == 1) fact *= ifactx;
|
|
if (i == w-1) fact *= factx;
|
|
LA[index] += fact * ffy * (A[index + ym] + A[index + yp] - 2.0 * A[index]);
|
|
LA[index2] += fact * ffy * (A[index2 - yp] + A[index2 - ym] - 2.0 * A[index2]);
|
|
index++;
|
|
index2++;
|
|
fact *= ifactz;
|
|
for (k=1; k<h-1; k++) {
|
|
LA[index] += fact * ffy * (A[index + ym] + A[index + yp] - 2.0 * A[index]);
|
|
LA[index2] += fact * ffy * (A[index2 - yp] + A[index2 - ym] - 2.0 * A[index2]);
|
|
index++;
|
|
index2++;
|
|
}
|
|
fact *= factz;
|
|
LA[index] += fact * ffy * (A[index + ym] + A[index + yp] - 2.0 * A[index]);
|
|
LA[index2] += fact * ffy * (A[index2 - yp] + A[index2 - ym] - 2.0 * A[index2]);
|
|
index++;
|
|
index2++;
|
|
index += h * static_cast<size_t>(d - 1);
|
|
index2 += h * static_cast<size_t>(d - 1);
|
|
}
|
|
} else {
|
|
ym = -h;
|
|
yp = h;
|
|
fact = factx * factz;
|
|
for (i=0; i<w; i++) {
|
|
if (i == 1) fact *= ifactx;
|
|
if (i == w-1) fact *= factx;
|
|
LA[index] += fact * ffy * (A[index + yp] - A[index]);
|
|
LA[index2] += fact * ffy * (A[index2 + ym] - A[index2]);
|
|
index++;
|
|
index2++;
|
|
fact *= ifactz;
|
|
for (k=1; k<h-1; k++) {
|
|
// y gradient (+ x, z terms of laplacian, calculated above and below)
|
|
LA[index] += fact * ffy * (A[index + yp] - A[index]);
|
|
LA[index2] += fact * ffy * (A[index2 + ym] - A[index2]);
|
|
index++;
|
|
index2++;
|
|
}
|
|
fact *= factz;
|
|
LA[index] += fact * ffy * (A[index + yp] - A[index]);
|
|
LA[index2] += fact * ffy * (A[index2 + ym] - A[index2]);
|
|
index++;
|
|
index2++;
|
|
index += h * static_cast<size_t>(d - 1);
|
|
index2 += h * static_cast<size_t>(d - 1);
|
|
}
|
|
}
|
|
|
|
// Now adding all z components
|
|
// All z components except on z edges
|
|
index = 1; // Skip first element (in bottom slab)
|
|
fact = factx * facty;
|
|
for (i=0; i<w; i++) { // full range of x
|
|
if (i == 1) fact *= ifactx;
|
|
if (i == w-1) fact *= factx;
|
|
for (k=1; k<h-1; k++) {
|
|
LA[index] += fact * ffz * (A[index + zm] + A[index + zp] - 2.0 * A[index]);
|
|
index++;
|
|
}
|
|
fact *= ifacty;
|
|
index += 2; // skip edge slabs
|
|
for (j=1; j<d-1; j++) { // full range of y
|
|
for (k=1; k<h-1; k++) {
|
|
LA[index] += fact * ffz * (A[index + zm] + A[index + zp] - 2.0 * A[index]);
|
|
index++;
|
|
}
|
|
index += 2; // skip edge slabs
|
|
}
|
|
fact *= facty;
|
|
for (k=1; k<h-1; k++) {
|
|
LA[index] += fact * ffz * (A[index + zm] + A[index + zp] - 2.0 * A[index]);
|
|
index++;
|
|
}
|
|
index += 2; // skip edge slabs
|
|
}
|
|
// Edges along z (z components onlz)
|
|
index = 0; // Follows bottom slab
|
|
index2 = h - 1; // Follows top slab
|
|
if (periodic[2]) {
|
|
zm = h - 1;
|
|
zp = 1;
|
|
fact = factx * facty;
|
|
for (i=0; i<w; i++) {
|
|
if (i == 1) fact *= ifactx;
|
|
if (i == w-1) fact *= factx;
|
|
LA[index] += fact * ffz * (A[index + zm] + A[index + zp] - 2.0 * A[index]);
|
|
LA[index2] += fact * ffz * (A[index2 - zp] + A[index2 - zm] - 2.0 * A[index2]);
|
|
index += h;
|
|
index2 += h;
|
|
fact *= ifacty;
|
|
for (j=1; j<d-1; j++) {
|
|
LA[index] += fact * ffz * (A[index + zm] + A[index + zp] - 2.0 * A[index]);
|
|
LA[index2] += fact * ffz * (A[index2 - zp] + A[index2 - zm] - 2.0 * A[index2]);
|
|
index += h;
|
|
index2 += h;
|
|
}
|
|
fact *= facty;
|
|
LA[index] += fact * ffz * (A[index + zm] + A[index + zp] - 2.0 * A[index]);
|
|
LA[index2] += fact * ffz * (A[index2 - zp] + A[index2 - zm] - 2.0 * A[index2]);
|
|
index += h;
|
|
index2 += h;
|
|
}
|
|
} else {
|
|
zm = -1;
|
|
zp = 1;
|
|
fact = factx * facty;
|
|
for (i=0; i<w; i++) {
|
|
if (i == 1) fact *= ifactx;
|
|
if (i == w-1) fact *= factx;
|
|
LA[index] += fact * ffz * (A[index + zp] - A[index]);
|
|
LA[index2] += fact * ffz * (A[index2 + zm] - A[index2]);
|
|
index += h;
|
|
index2 += h;
|
|
fact *= ifacty;
|
|
for (j=1; j<d-1; j++) {
|
|
// z gradient (+ x, y terms of laplacian, calculated above)
|
|
LA[index] += fact * ffz * (A[index + zp] - A[index]);
|
|
LA[index2] += fact * ffz * (A[index2 + zm] - A[index2]);
|
|
index += h;
|
|
index2 += h;
|
|
}
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|
fact *= facty;
|
|
LA[index] += fact * ffz * (A[index + zp] - A[index]);
|
|
LA[index2] += fact * ffz * (A[index2 + zm] - A[index2]);
|
|
index += h;
|
|
index2 += h;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
|
|
/*
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|
/// Inversion of preconditioner matrix (e.g. diagonal of the Laplacian)
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|
void integrate_potential::asolve(const std::vector<cvm::real> &b, std::vector<cvm::real> &x)
|
|
{
|
|
for (size_t i=0; i<int(nt); i++) {
|
|
x[i] = b[i] * inv_lap_diag[i]; // Jacobi preconditioner - little benefit in tests so far
|
|
}
|
|
return;
|
|
}*/
|
|
|
|
|
|
// b : RHS of equation
|
|
// x : initial guess for the solution; output is solution
|
|
// itol : convergence criterion
|
|
void integrate_potential::nr_linbcg_sym(const std::vector<cvm::real> &b, std::vector<cvm::real> &x, const cvm::real &tol,
|
|
const int itmax, int &iter, cvm::real &err)
|
|
{
|
|
cvm::real ak,akden,bk,bkden,bknum,bnrm;
|
|
const cvm::real EPS=1.0e-14;
|
|
int j;
|
|
std::vector<cvm::real> p(nt), r(nt), z(nt);
|
|
|
|
iter=0;
|
|
atimes(x,r);
|
|
for (j=0;j<int(nt);j++) {
|
|
r[j]=b[j]-r[j];
|
|
}
|
|
bnrm=l2norm(b);
|
|
if (bnrm < EPS) {
|
|
return; // Target is zero, will break relative error calc
|
|
}
|
|
// asolve(r,z); // precon
|
|
bkden = 1.0;
|
|
while (iter < itmax) {
|
|
++iter;
|
|
for (bknum=0.0,j=0;j<int(nt);j++) {
|
|
bknum += r[j]*r[j]; // precon: z[j]*r[j]
|
|
}
|
|
if (iter == 1) {
|
|
for (j=0;j<int(nt);j++) {
|
|
p[j] = r[j]; // precon: p[j] = z[j]
|
|
}
|
|
} else {
|
|
bk=bknum/bkden;
|
|
for (j=0;j<int(nt);j++) {
|
|
p[j] = bk*p[j] + r[j]; // precon: bk*p[j] + z[j]
|
|
}
|
|
}
|
|
bkden = bknum;
|
|
atimes(p,z);
|
|
for (akden=0.0,j=0;j<int(nt);j++) {
|
|
akden += z[j]*p[j];
|
|
}
|
|
ak = bknum/akden;
|
|
for (j=0;j<int(nt);j++) {
|
|
x[j] += ak*p[j];
|
|
r[j] -= ak*z[j];
|
|
}
|
|
// asolve(r,z); // precon
|
|
err = l2norm(r)/bnrm;
|
|
if (cvm::debug())
|
|
std::cout << "iter=" << std::setw(4) << iter+1 << std::setw(12) << err << std::endl;
|
|
if (err <= tol)
|
|
break;
|
|
}
|
|
}
|
|
|
|
cvm::real integrate_potential::l2norm(const std::vector<cvm::real> &x)
|
|
{
|
|
size_t i;
|
|
cvm::real sum = 0.0;
|
|
for (i=0;i<x.size();i++)
|
|
sum += x[i]*x[i];
|
|
return sqrt(sum);
|
|
}
|