source: sasview/sansmodels/src/sans/models/c_models/stackeddisks.cpp @ 0a9871c

/**
        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
 *      TODO: add 2d
 */

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

extern "C" {
        #include "libCylinder.h"
        #include "libStructureFactor.h"
        #include "stacked_disks.h"
}

StackedDisksModel :: StackedDisksModel() {
        scale      = Parameter(1.0);
        radius     = Parameter(3000.0, true);
        radius.set_min(0.0);
        core_thick  = Parameter(10.0, true);
        core_thick.set_min(0.0);
        layer_thick     = Parameter(15.0);
        layer_thick.set_min(0.0);
        core_sld = Parameter(4.0e-6);
        layer_sld  = Parameter(-4.0e-7);
        solvent_sld  = Parameter(5.0e-6);
        n_stacking   = Parameter(1);
        sigma_d   = Parameter(0);
        background = Parameter(0.001);
        axis_theta  = Parameter(0.0, true);
        axis_phi    = 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 StackedDisksModel :: operator()(double q) {
        double dp[10];

        // Fill parameter array for IGOR library
        // Add the background after averaging
        dp[0] = scale();
        dp[1] = radius();
        dp[2] = core_thick();
        dp[3] = layer_thick();
        dp[4] = core_sld();
        dp[5] = layer_sld();
        dp[6] = solvent_sld();
        dp[7] = n_stacking();
        dp[8] = sigma_d();
        dp[9] = 0.0;

        // Get the dispersion points for the radius
        vector<WeightPoint> weights_radius;
        radius.get_weights(weights_radius);

        // Get the dispersion points for the core_thick
        vector<WeightPoint> weights_core_thick;
        core_thick.get_weights(weights_core_thick);

        // Get the dispersion points for the layer_thick
        vector<WeightPoint> weights_layer_thick;
        layer_thick.get_weights(weights_layer_thick);

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

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

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

                        // Loop over thickness weight points
                        for(int k=0; k< (int)weights_layer_thick.size(); k++) {
                                dp[3] = weights_layer_thick[k].value;
                                //Un-normalize by volume
                                sum += weights_radius[i].weight
                                        * weights_core_thick[j].weight * weights_layer_thick[k].weight* StackedDiscs(dp, q)
                                        *pow(weights_radius[i].value,2)*(weights_core_thick[j].value+2*weights_layer_thick[k].value);
                                //Find average volume
                                vol += weights_radius[i].weight
                                        * weights_core_thick[j].weight * weights_layer_thick[k].weight
                                        *pow(weights_radius[i].value,2)*(weights_core_thick[j].value+2*weights_layer_thick[k].value);
                                norm += weights_radius[i].weight
                                        * weights_core_thick[j].weight* weights_layer_thick[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 StackedDisksModel :: operator()(double qx, double qy) {
        StackedDisksParameters dp;
        // Fill parameter array
        dp.scale      = scale();
        dp.core_thick    = core_thick();
        dp.radius         = radius();
        dp.layer_thick  = layer_thick();
        dp.core_sld   = core_sld();
        dp.layer_sld  = layer_sld();
        dp.solvent_sld= solvent_sld();
        dp.n_stacking     = n_stacking();
        dp.sigma_d   = sigma_d();
        dp.background = 0.0;
        dp.axis_theta = axis_theta();
        dp.axis_phi   = axis_phi();

        // Get the dispersion points for the length
        vector<WeightPoint> weights_core_thick;
        core_thick.get_weights(weights_core_thick);

        // Get the dispersion points for the radius
        vector<WeightPoint> weights_radius;
        radius.get_weights(weights_radius);

        // Get the dispersion points for the thickness
        vector<WeightPoint> weights_layer_thick;
        layer_thick.get_weights(weights_layer_thick);

        // 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;
        double norm_vol = 0.0;
        double vol = 0.0;

        // Loop over length weight points
        for(int i=0; i< (int)weights_core_thick.size(); i++) {
                dp.core_thick = weights_core_thick[i].value;

                // Loop over radius weight points
                for(int j=0; j< (int)weights_radius.size(); j++) {
                        dp.radius = weights_radius[j].value;

                                // Loop over thickness weight points
                                for(int k=0; k< (int)weights_layer_thick.size(); k++) {
                                dp.layer_thick = weights_layer_thick[k].value;

                                        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;

                                                        //Un-normalize by volume
                                                        double _ptvalue = weights_core_thick[i].weight
                                                                * weights_radius[j].weight
                                                                * weights_layer_thick[k].weight
                                                                * weights_theta[l].weight
                                                                * weights_phi[m].weight
                                                                * stacked_disks_analytical_2DXY(&dp, qx, qy)
                                                                *pow(weights_radius[j].value,2)*(weights_core_thick[i].value+2*weights_layer_thick[k].value);
                                                        if (weights_theta.size()>1) {
                                                                _ptvalue *= fabs(sin(weights_theta[l].value));
                                                        }
                                                        sum += _ptvalue;
                                                        //Find average volume
                                                        vol += weights_radius[j].weight
                                                                * weights_core_thick[i].weight * weights_layer_thick[k].weight
                                                                *pow(weights_radius[j].value,2)*(weights_core_thick[i].value+2*weights_layer_thick[k].value);
                                                        //Find norm for volume
                                                        norm_vol += weights_radius[j].weight
                                                                * weights_core_thick[i].weight * weights_layer_thick[k].weight;

                                                        norm += weights_core_thick[i].weight
                                                                * weights_radius[j].weight
                                                                * weights_layer_thick[k].weight
                                                                * weights_theta[l].weight
                                                                * weights_phi[m].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 StackedDisksModel :: 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 StackedDisksModel :: calculate_ER() {
        StackedDisksParameters dp;

        dp.core_thick    = core_thick();
        dp.radius         = radius();
        dp.layer_thick  = layer_thick();
        dp.n_stacking     = n_stacking();

        double rad_out = 0.0;
        if (dp.n_stacking <= 0.0){
                return rad_out;
        }

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

        // Get the dispersion points for the length
        vector<WeightPoint> weights_core_thick;
        core_thick.get_weights(weights_core_thick);

        // Get the dispersion points for the radius
        vector<WeightPoint> weights_radius;
        radius.get_weights(weights_radius);

        // Get the dispersion points for the thickness
        vector<WeightPoint> weights_layer_thick;
        layer_thick.get_weights(weights_layer_thick);

        // Loop over major shell weight points
        for(int i=0; i< (int)weights_core_thick.size(); i++) {
                dp.core_thick = weights_core_thick[i].value;
                for(int j=0; j< (int)weights_layer_thick.size(); j++) {
                        dp.layer_thick = weights_layer_thick[j].value;
                        for(int k=0; k< (int)weights_radius.size(); k++) {
                                dp.radius = weights_radius[k].value;
                                //Note: output of "DiamCyl(dp.length,dp.radius)" is DIAMETER.
                                sum +=weights_core_thick[i].weight*weights_layer_thick[j].weight
                                        * weights_radius[k].weight*DiamCyl(dp.n_stacking*(dp.layer_thick*2.0+dp.core_thick),dp.radius)/2.0;
                                norm += weights_core_thick[i].weight*weights_layer_thick[j].weight* weights_radius[k].weight;
                        }
                }
        }
        if (norm != 0){
                //return the averaged value
                rad_out =  sum/norm;}
        else{
                //return normal value
                //Note: output of "DiamCyl(dp.length,dp.radius)" is DIAMETER.
                rad_out = DiamCyl(dp.n_stacking*(dp.layer_thick*2.0+dp.core_thick),dp.radius)/2.0;}

        return rad_out;
}