source: sasview/sansmodels/src/sans/models/c_models/triaxialellipsoid.cpp @ ba69349

/**
        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 "libStructureFactor.h"
        #include "triaxial_ellipsoid.h"
}

TriaxialEllipsoidModel :: TriaxialEllipsoidModel() {
        scale      = Parameter(1.0);
        semi_axisA     = Parameter(35.0, true);
        semi_axisA.set_min(0.0);
        semi_axisB     = Parameter(100.0, true);
        semi_axisB.set_min(0.0);
        semi_axisC  = Parameter(400.0, true);
        semi_axisC.set_min(0.0);
        contrast   = Parameter(5.3e-6);
        background = Parameter(0.0);
        axis_theta  = Parameter(1.0, true);
        axis_phi    = Parameter(1.0, true);
        axis_psi    = Parameter(0.0, true);
}

/**
 * Function to evaluate 1D scattering function
 * The NIST IGOR library is used for the actual calculation.
 * @param q: q-value
 * @return: function value
 */
double TriaxialEllipsoidModel :: operator()(double q) {
        double dp[6];

        // Fill parameter array for IGOR library
        // Add the background after averaging
        dp[0] = scale();
        dp[1] = semi_axisA();
        dp[2] = semi_axisB();
        dp[3] = semi_axisC();
        dp[4] = contrast();
        dp[5] = 0.0;

        // Get the dispersion points for the semi axis A
        vector<WeightPoint> weights_semi_axisA;
        semi_axisA.get_weights(weights_semi_axisA);

        // Get the dispersion points for the semi axis B
        vector<WeightPoint> weights_semi_axisB;
        semi_axisB.get_weights(weights_semi_axisB);

        // Get the dispersion points for the semi axis C
        vector<WeightPoint> weights_semi_axisC;
        semi_axisC.get_weights(weights_semi_axisC);

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

        // Loop over semi axis A weight points
        for(int i=0; i< (int)weights_semi_axisA.size(); i++) {
                dp[1] = weights_semi_axisA[i].value;

                // Loop over semi axis B weight points
                for(int j=0; j< (int)weights_semi_axisB.size(); j++) {
                        dp[2] = weights_semi_axisB[j].value;

                        // Loop over semi axis C weight points
                        for(int k=0; k< (int)weights_semi_axisC.size(); k++) {
                                dp[3] = weights_semi_axisC[k].value;
                                //Un-normalize  by volume
                                sum += weights_semi_axisA[i].weight
                                        * weights_semi_axisB[j].weight * weights_semi_axisC[k].weight* TriaxialEllipsoid(dp, q)
                                        * weights_semi_axisA[i].value*weights_semi_axisB[j].value*weights_semi_axisC[k].value;
                                //Find average volume
                                vol += weights_semi_axisA[i].weight
                                        * weights_semi_axisB[j].weight * weights_semi_axisC[k].weight
                                        * weights_semi_axisA[i].value*weights_semi_axisB[j].value*weights_semi_axisC[k].value;

                                norm += weights_semi_axisA[i].weight
                                        * weights_semi_axisB[j].weight * weights_semi_axisC[k].weight;
                        }
                }
        }
        if (vol != 0.0 && norm != 0.0) {
                //Re-normalize by avg volume
                sum = sum/(vol/norm);}

        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 TriaxialEllipsoidModel :: operator()(double qx, double qy) {
        TriaxialEllipsoidParameters dp;
        // Fill parameter array
        dp.scale      = scale();
        dp.semi_axisA   = semi_axisA();
        dp.semi_axisB     = semi_axisB();
        dp.semi_axisC     = semi_axisC();
        dp.contrast   = contrast();
        dp.background = 0.0;
        dp.axis_theta  = axis_theta();
        dp.axis_phi    = axis_phi();
        dp.axis_psi    = axis_psi();

        // Get the dispersion points for the semi_axis A
        vector<WeightPoint> weights_semi_axisA;
        semi_axisA.get_weights(weights_semi_axisA);

        // Get the dispersion points for the semi_axis B
        vector<WeightPoint> weights_semi_axisB;
        semi_axisB.get_weights(weights_semi_axisB);

        // Get the dispersion points for the semi_axis C
        vector<WeightPoint> weights_semi_axisC;
        semi_axisC.get_weights(weights_semi_axisC);

        // 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);

        // Get angular averaging for psi
        vector<WeightPoint> weights_psi;
        axis_psi.get_weights(weights_psi);

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

        // Loop over semi axis A weight points
        for(int i=0; i< (int)weights_semi_axisA.size(); i++) {
                dp.semi_axisA = weights_semi_axisA[i].value;

                // Loop over semi axis B weight points
                for(int j=0; j< (int)weights_semi_axisB.size(); j++) {
                        dp.semi_axisB = weights_semi_axisB[j].value;

                        // Loop over semi axis C weight points
                        for(int k=0; k < (int)weights_semi_axisC.size(); k++) {
                        dp.semi_axisC = weights_semi_axisC[k].value;

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

                                        // Average over phi distribution
                                        for(int m=0; m <(int)weights_phi.size(); m++) {
                                                dp.axis_phi = weights_phi[m].value;
                                                // Average over psi distribution
                                                for(int n=0; n <(int)weights_psi.size(); n++) {
                                                        dp.axis_psi = weights_psi[n].value;
                                                        //Un-normalize  by volume
                                                        double _ptvalue = weights_semi_axisA[i].weight
                                                                * weights_semi_axisB[j].weight
                                                                * weights_semi_axisC[k].weight
                                                                * weights_theta[l].weight
                                                                * weights_phi[m].weight
                                                                * weights_psi[n].weight
                                                                * triaxial_ellipsoid_analytical_2DXY(&dp, qx, qy)
                                                                * weights_semi_axisA[i].value*weights_semi_axisB[j].value*weights_semi_axisC[k].value;
                                                        if (weights_theta.size()>1) {
                                                                _ptvalue *= sin(weights_theta[k].value);
                                                        }
                                                        sum += _ptvalue;
                                                        //Find average volume
                                                        vol += weights_semi_axisA[i].weight
                                                                * weights_semi_axisB[j].weight
                                                                * weights_semi_axisC[k].weight
                                                                * weights_semi_axisA[i].value*weights_semi_axisB[j].value*weights_semi_axisC[k].value;
                                                        //Find norm for volume
                                                        norm_vol += weights_semi_axisA[i].weight
                                                                * weights_semi_axisB[j].weight
                                                                * weights_semi_axisC[k].weight;

                                                        norm += weights_semi_axisA[i].weight
                                                                * weights_semi_axisB[j].weight
                                                                * weights_semi_axisC[k].weight
                                                                * weights_theta[l].weight
                                                                * weights_phi[m].weight
                                                                * weights_psi[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);

        if (vol != 0.0 && norm_vol != 0.0) {
                //Re-normalize by avg volume
                sum = sum/(vol/norm_vol);}

        return sum/norm + background();
}

/**
 * Function to evaluate 2D scattering function
 * @param pars: parameters of the triaxial ellipsoid
 * @param q: q-value
 * @param phi: angle phi
 * @return: function value
 */
double TriaxialEllipsoidModel :: evaluate_rphi(double q, double phi) {
        double qx = q*cos(phi);
        double qy = q*sin(phi);
        return (*this).operator()(qx, qy);
}
/**
 * Function to calculate effective radius
 * @return: effective radius value
 */
double TriaxialEllipsoidModel :: calculate_ER() {
        TriaxialEllipsoidParameters dp;

        dp.semi_axisA   = semi_axisA();
        dp.semi_axisB     = semi_axisB();
        //polar axis C
        dp.semi_axisC     = semi_axisC();

        double rad_out = 0.0;
        //Surface average radius at the equat. cross section.
        double suf_rad = sqrt(dp.semi_axisA * dp.semi_axisB);

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

        // Get the dispersion points for the semi_axis A
        vector<WeightPoint> weights_semi_axisA;
        semi_axisA.get_weights(weights_semi_axisA);

        // Get the dispersion points for the semi_axis B
        vector<WeightPoint> weights_semi_axisB;
        semi_axisB.get_weights(weights_semi_axisB);

        // Get the dispersion points for the semi_axis C
        vector<WeightPoint> weights_semi_axisC;
        semi_axisC.get_weights(weights_semi_axisC);

        // Loop over semi axis A weight points
        for(int i=0; i< (int)weights_semi_axisA.size(); i++) {
                dp.semi_axisA = weights_semi_axisA[i].value;

                // Loop over semi axis B weight points
                for(int j=0; j< (int)weights_semi_axisB.size(); j++) {
                        dp.semi_axisB = weights_semi_axisB[j].value;

                        // Loop over semi axis C weight points
                        for(int k=0; k < (int)weights_semi_axisC.size(); k++) {
                                dp.semi_axisC = weights_semi_axisC[k].value;

                                //Calculate surface averaged radius
                                suf_rad = sqrt(dp.semi_axisA * dp.semi_axisB);

                                //Sum
                                sum += weights_semi_axisA[i].weight
                                        * weights_semi_axisB[j].weight
                                        * weights_semi_axisC[k].weight * DiamEllip(dp.semi_axisC, suf_rad)/2.0;
                                //Norm
                                norm += weights_semi_axisA[i].weight* weights_semi_axisB[j].weight
                                        * weights_semi_axisC[k].weight;
                        }
                }
        }
        if (norm != 0){
                //return the averaged value
                rad_out =  sum/norm;}
        else{
                //return normal value
                rad_out = DiamEllip(dp.semi_axisC, suf_rad)/2.0;}

        return rad_out;
}