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// SPDX-License-Identifier: LGPL-3.0-or-later
// Author: Kristian Lytje
#include <api/api_sasview.h>
#include <settings/All.h>
#include <dataset/SimpleDataset.h>
#include <data/Molecule.h>
#include <data/Body.h>
#include <hist/detail/SimpleExvModel.h>
#include <hist/intensity_calculator/CompositeDistanceHistogram.h>
#include <hist/intensity_calculator/CompositeDistanceHistogramFFGridSurface.h>
#include <fitter/SmartFitter.h>
#include <fitter/FitReporter.h>
#include <constants/Constants.h>
#include <utility/Utility.h>
using namespace ausaxs;
using namespace ausaxs::data;
void test_integration(int* test_value) {
*test_value += 1;
}
struct {
std::unique_ptr<data::Molecule> protein;
std::unique_ptr<SimpleDataset> data;
} iterative_fit_state;
// void iterative_fit_start(
// double* _data_q, double* _data_I, double* _data_Ierr, int _n_data,
// double* _pdb_x, double* _pdb_y, double* _pdb_z,
// const char** _atom_names, const char** _residue_names, const char** _elements,
// int _n_pdb, int* _return_status
// ) {
// std::cout << "AUSAXS: Starting method \"iterative_fit::start\"." << std::endl;
// // default state is error since we don't trust the input enough to assume success
// *_return_status = 1;
// // use the multithreaded version of the simple histogram manager
// settings::exv::exv_method = settings::exv::ExvMethod::GridScalable;
// settings::fit::fit_excluded_volume = true;
// // set qmax as high as it can go
// settings::axes::qmax = 1;
// // convert C data
// std::vector<std::string> atom_names(_n_pdb), residue_names(_n_pdb), elements(_n_pdb);
// {
// std::vector<double> q(_data_q, _data_q+_n_data);
// std::vector<double> I(_data_I, _data_I+_n_data);
// std::vector<double> Ierr(_data_Ierr, _data_Ierr+_n_data);
// iterative_fit_state.data = std::make_unique<SimpleDataset>(std::move(q), std::move(I), std::move(Ierr));
// for (int i = 0; i < _n_pdb; ++i) {
// atom_names[i] = std::string(_atom_names[i]);
// residue_names[i] = std::string(_residue_names[i]);
// elements[i] = std::string(_elements[i]);
// }
// }
// std::vector<data::AtomFF> atoms(_n_pdb);
// for (int i = 0; i < _n_pdb; ++i) {
// auto atom = constants::symbols::parse_element_string(elements[i]);
// auto group = constants::symbols::get_atomic_group(residue_names[i], atom_names[i], atom);
// atoms[i] = data::AtomFF({_pdb_x[i], _pdb_y[i], _pdb_z[i]}, form_factor::get_type(atom, group));
// }
// *_return_status = 2;
// iterative_fit_state.protein = std::make_unique<Molecule>(std::vector{Body{atoms}});
// iterative_fit_state.protein->generate_new_hydration();
// *_return_status = 0;
// }
// void iterative_fit_step(double* pars, double* return_I, int* return_status) {
// std::cout << "AUSAXS: Starting method \"iterative_fit::step\"." << std::endl;
// std::cout << "DEBUG VERSION!" << std::endl;
// // default state is error since we don't trust the input enough to assume success
// *return_status = 1;
// if (!iterative_fit_state.protein || !iterative_fit_state.data) {return;}
// *return_status = 2;
// auto hist = iterative_fit_state.protein->get_histogram();
// *return_status = 3;
// double c = pars[0];
// double d = pars[1];
// hist->apply_water_scaling_factor(c);
// static_cast<hist::CompositeDistanceHistogramFFGridSurface*>(hist.get())->apply_excluded_volume_scaling_factor(d);
// *return_status = 4;
// auto I = hist->debye_transform(iterative_fit_state.data->x());
// // write the fitted intensity to the output array
// *return_status = 5;
// for (int i = 0; i < static_cast<int>(I.size()); ++i) {
// return_I[i] = I.y(i);
// }
// *return_status = 0;
// }
// void iterative_fit_finish(double* pars, double* return_I, int* return_status) {
// std::cout << "AUSAXS: Starting method \"iterative_fit::finish" << std::endl;
// iterative_fit_step(pars, return_I, return_status);
// if (*return_status != 0) {return;}
// *return_status = 1;
// iterative_fit_state.protein->save("fitted_model.pdb");
// *return_status = 0;
// }
// void fit_saxs(
// double* _data_q, double* _data_I, double* _data_Ierr, int _n_data,
// double* _pdb_x, double* _pdb_y, double* _pdb_z,
// const char** _atom_names, const char** _residue_names, const char** _elements,
// int _n_pdb,
// double* _return_I, int* _return_status
// ) {
// std::cout << "AUSAXS: Starting method \"fit_saxs\"." << std::endl;
// // default state is error since we don't trust the input enough to assume success
// *_return_status = 1;
// // use the multithreaded version of the simple histogram manager
// settings::exv::exv_method = settings::exv::ExvMethod::Simple;
// settings::fit::fit_excluded_volume = false;
// // set qmax as high as it can go
// settings::axes::qmax = 1;
// // convert C data
// SimpleDataset data;
// std::vector<std::string> atom_names(_n_pdb), residue_names(_n_pdb), elements(_n_pdb);
// {
// std::vector<double> q(_data_q, _data_q+_n_data);
// std::vector<double> I(_data_I, _data_I+_n_data);
// std::vector<double> Ierr(_data_Ierr, _data_Ierr+_n_data);
// data = SimpleDataset({std::move(q), std::move(I), std::move(Ierr)});
// for (int i = 0; i < _n_pdb; ++i) {
// atom_names[i] = std::string(_atom_names[i]);
// residue_names[i] = std::string(_residue_names[i]);
// elements[i] = std::string(_elements[i]);
// }
// }
// std::vector<data::AtomFF> atoms(_n_pdb);
// for (int i = 0; i < _n_pdb; ++i) {
// auto atom = constants::symbols::parse_element_string(elements[i]);
// auto group = constants::symbols::get_atomic_group(residue_names[i], atom_names[i], atom);
// atoms[i] = data::AtomFF({_pdb_x[i], _pdb_y[i], _pdb_z[i]}, form_factor::get_type(atom, group));
// }
// // construct a molecule from the collection of atom
// *_return_status = 2;
// Molecule protein({Body{atoms}});
// protein.generate_new_hydration();
// // perform the fit
// *_return_status = 3;
// fitter::SmartFitter fitter(std::move(data), protein.get_histogram());
// auto res = fitter.fit();
// fitter::FitReporter::report(res.get());
// fitter::FitReporter::save(res.get(), settings::general::output + "ausaxs_fit_result.txt");
// res->curves.select_columns({0, 1, 2, 3}).save(
// settings::general::output + "ausaxs.fit",
// "chi2=" + std::to_string(res->fval/res->dof) + " dof=" + std::to_string(res->dof)
// );
// // write the fitted intensity to the output array
// *_return_status = 4;
// auto fitted_I = res->curves.col(3);
// for (int i = 0; i < static_cast<int>(fitted_I.size()); ++i) {
// _return_I[i] = fitted_I[i];
// }
// *_return_status = 0;
// }
void debye_no_ff(double* _q, double* _x, double* _y, double* _z, double* _w, int _nq, int _nc, double* _return_Iq, int* _return_status) {
std::cout << "AUSAXS: Starting method \"evaluate_sans_debye\"." << std::endl;
// default state is error since we don't trust the input enough to assume success
*_return_status = 1;
// use the multithreaded version of the simple histogram manager
settings::exv::exv_method = settings::exv::ExvMethod::Simple;
// do not subtract the solvent charge from the atoms
hist::detail::SimpleExvModel::disable();
// do not subtract the charge of bound hydrogens
settings::molecule::implicit_hydrogens = false;
// set qmax as high as it can go
settings::axes::qmax = 1;
// convert coordinate input to Atom objects
std::vector<double> q(_q, _q+_nq);
std::vector<data::Atom> atoms(_nc);
for (int i = 0; i < _nc; ++i) {
atoms[i] = data::Atom({_x[i], _y[i], _z[i]}, _w[i]);
}
// construct a protein from the collection of atom
*_return_status = 2;
Molecule protein({Body{atoms}});
// calculate the distance histogram for the protein
*_return_status = 3;
auto dist = protein.get_histogram();
// perform the Debye transform
*_return_status = 4;
auto Iq = dist->debye_transform(q);
// sanity check - the number of q values should match the number of I(q) values
if ((int) Iq.size() != _nq) {
*_return_status = 5;
return;
}
// remove the form factor applied by the debye transform
for (unsigned int i = 0; i < Iq.size(); ++i) {
_return_Iq[i] = Iq.y(i) / std::exp(-std::pow(Iq.x(i), 2));
}
*_return_status = 0;
}
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