source: sasview/sansmodels/src/sans/models/c_models/prolate.cpp @ 8dc0b746

/**
        This software was developed by the University of Tennessee as part of the
        Distributed Data Analysis of Neutron Scattering Experiments (DANSE)
        project funded by the US National Science Foundation.

        If you use DANSE applications to do scientific research that leads to
        publication, we ask that you acknowledge the use of the software with the
        following sentence:

        "This work benefited from DANSE software developed under NSF award DMR-0520547."

        copyright 2008, University of Tennessee
 */

/**
 * Scattering model classes
 * The classes use the IGOR library found in
 *   sansmodels/src/libigor
 *
 *      TODO: refactor so that we pull in the old sansmodels.c_extensions
 */

#include <math.h>
#include "models.hh"
#include "parameters.hh"
#include <stdio.h>
using namespace std;

extern "C" {
        #include "libCylinder.h"
        #include "prolate.h"
}

ProlateModel :: ProlateModel() {
        scale      = Parameter(1.0);
        major_core     = Parameter(100.0, true);
        major_core.set_min(0.0);
        minor_core     = Parameter(50.0, true);
        minor_core.set_min(0.0);
        major_shell   = Parameter(110.0, true);
        major_shell.set_min(0.0);
        minor_shell    = Parameter(60.0, true);
        minor_shell.set_min(0.0);
        contrast   = Parameter(1e-6);
        sld_solvent = Parameter(6.3e-6);
        background = Parameter(0.0);
}

/**
 * Function to evaluate 1D scattering function
 * The NIST IGOR library is used for the actual calculation.
 * @param q: q-value
 * @return: function value
 */
double ProlateModel :: operator()(double q) {
        double dp[8];

        // Fill parameter array for IGOR library
        // Add the background after averaging
        dp[0] = scale();
        dp[1] = major_core();
        dp[2] = minor_core();
        dp[3] = major_shell();
        dp[4] = minor_shell();
        dp[5] = contrast();
        dp[6] = sld_solvent();
        dp[7] = 0.0;

        // Get the dispersion points for the major core
        vector<WeightPoint> weights_major_core;
        major_core.get_weights(weights_major_core);

        // Get the dispersion points for the minor core
        vector<WeightPoint> weights_minor_core;
        minor_core.get_weights(weights_minor_core);

        // Get the dispersion points for the major shell
        vector<WeightPoint> weights_major_shell;
        major_shell.get_weights(weights_major_shell);

        // Get the dispersion points for the minor_shell
        vector<WeightPoint> weights_minor_shell;
        minor_shell.get_weights(weights_minor_shell);


        // Perform the computation, with all weight points
        double sum = 0.0;
        double norm = 0.0;

        // Loop over major core weight points
        for(int i=0; i<(int)weights_major_core.size(); i++) {
                dp[1] = weights_major_core[i].value;

                // Loop over minor core weight points
                for(int j=0; j<(int)weights_minor_core.size(); j++) {
                        dp[2] = weights_minor_core[j].value;

                        // Loop over major shell weight points
                        for(int k=0; k<(int)weights_major_shell.size(); k++) {
                                dp[3] = weights_major_shell[k].value;

                                // Loop over minor shell weight points
                                for(int l=0; l<(int)weights_minor_shell.size(); l++) {
                                        dp[4] = weights_minor_shell[l].value;

                                        sum += weights_major_core[i].weight* weights_minor_core[j].weight * weights_major_shell[k].weight
                                                * weights_minor_shell[l].weight * ProlateForm(dp, q);
                                        norm += weights_major_core[i].weight* weights_minor_core[j].weight * weights_major_shell[k].weight
                                                        * weights_minor_shell[l].weight;
                                }
                        }
                }
        }
        return sum/norm + background();
}

/**
 * Function to evaluate 2D scattering function
 * @param q_x: value of Q along x
 * @param q_y: value of Q along y
 * @return: function value
 */
double ProlateModel :: operator()(double qx, double qy) {
        double q = sqrt(qx*qx + qy*qy);

        return (*this).operator()(q);
}

/**
 * Function to evaluate 2D scattering function
 * @param pars: parameters of the prolate
 * @param q: q-value
 * @param phi: angle phi
 * @return: function value
 */
double ProlateModel :: evaluate_rphi(double q, double phi) {
        return (*this).operator()(q);
}
/*
double ProlateModel :: operator()(double qx, double qy) {
        ProlateParameters dp;
        // Fill parameter array
        dp.scale      = scale();
        dp.major_core = major_core();
        dp.minor_core = minor_core();
        dp.major_shell = major_shell();
        dp.minor_shell = minor_shell();
        dp.contrast = contrast();
        dp.sld_solvent = sld_solvent();
        dp.background = background();
        dp.axis_theta = axis_theta();
        dp.axis_phi = axis_phi();

        // Get the dispersion points for the major core
        vector<WeightPoint> weights_major_core;
        major_core.get_weights(weights_major_core);

        // Get the dispersion points for the minor core
        vector<WeightPoint> weights_minor_core;
        minor_core.get_weights(weights_minor_core);

        // Get the dispersion points for the major shell
        vector<WeightPoint> weights_major_shell;
        major_shell.get_weights(weights_major_shell);

        // Get the dispersion points for the minor shell
        vector<WeightPoint> weights_minor_shell;
        minor_shell.get_weights(weights_minor_shell);


        // Get angular averaging for theta
        vector<WeightPoint> weights_theta;
        axis_theta.get_weights(weights_theta);

        // Get angular averaging for phi
        vector<WeightPoint> weights_phi;
        axis_phi.get_weights(weights_phi);

        // Perform the computation, with all weight points
        double sum = 0.0;
        double norm = 0.0;

        // Loop over major core weight points
        for(int i=0; i< (int)weights_major_core.size(); i++) {
                dp.major_core = weights_major_core[i].value;

                // Loop over minor core weight points
                for(int j=0; j< (int)weights_minor_core.size(); j++) {
                        dp.minor_core = weights_minor_core[j].value;

                        // Loop over major shell weight points
                        for(int k=0; k< (int)weights_major_shell.size(); k++) {
                                dp.major_shell = weights_major_shell[i].value;

                                // Loop over minor shell weight points
                                for(int l=0; l< (int)weights_minor_shell.size(); l++) {
                                        dp.minor_shell = weights_minor_shell[l].value;

                                        // Average over theta distribution
                                        for(int m=0; m< (int)weights_theta.size(); m++) {
                                                dp.axis_theta = weights_theta[m].value;

                                                // Average over phi distribution
                                                for(int n=0; n< (int)weights_phi.size(); n++) {
                                                        dp.axis_phi = weights_phi[n].value;

                                                        double _ptvalue = weights_major_core[i].weight *weights_minor_core[j].weight
                                                                * weights_major_shell[k].weight * weights_minor_shell[l].weight
                                                                * weights_theta[m].weight
                                                                * weights_phi[n].weight
                                                                * prolate_analytical_2DXY(&dp, qx, qy);
                                                        if (weights_theta.size()>1) {
                                                                _ptvalue *= sin(weights_theta[k].value);
                                                        }
                                                        sum += _ptvalue;

                                                        norm += weights_major_core[i].weight *weights_minor_core[j].weight
                                                                * weights_major_shell[k].weight * weights_minor_shell[l].weight
                                                                * weights_theta[m].weight * weights_phi[n].weight;
                                                }
                                        }
                                }
                        }
                }
        }
        // Averaging in theta needs an extra normalization
        // factor to account for the sin(theta) term in the
        // integration (see documentation).
        if (weights_theta.size()>1) norm = norm / asin(1.0);
        return sum/norm + background();
}

*/