source: sasview/sansmodels/igor_wrapper/templates/weighted_template.c @ eb4f2fd

/**
 * Evaluate [PYTHONCLASS] with angular distribution given
 * by user. 
 * 
 * This code was written as part of the DANSE project
 *  http://danse.us/trac/sans/
 *
 * WARNING: THIS FILE WAS GENERATED BY IGORGENERATOR.PY
 *          DO NOT MODIFY THIS FILE, MODIFY [INCLUDE_FILE]
 *          AND RE-RUN THE GENERATOR SCRIPT
 *   
 *  @copyright 2007: University of Tennessee, for the DANSE project
 *
 */

#include "c_disperser.h"
#include "danse.h"
#include <math.h>

/**
 * Evaluate model for given angular distributions in theta and phi.
 * 
 * Angles are in radian.
 * 
 * See [C_FILE_NAME] for more information about the model parameters.
 * 
 * @param dp: model parameters
 * @param phi_values: vector of phi_values
 * @param phi_weights: vector of weights for each entry in phi_values
 * @param n_phi: length of phi_values and phi_weights vectors
 * @param theta_values: vector of theta values
 * @param theta_weights: vector of weights for each entry in theta_values
 * @param n_theta: length of theta_Values and theta_weights vectors
 * @param q: q-value to evaluate the model at
 * @param phi_q: angle between the q-vector and the q_x axis
 * @return: scattering intensity
 * 
[PARS_LIST]
 * 
 */
double [MODEL_NAME]_Weights(double dp[], double *phi_values, double *phi_weights, int n_phi, 
                                                                double *theta_values, double *theta_weights, int n_theta, 
                                                                double q, double phi_q) {
        // Copy of parameters
        double pars[[NPARS]];
        // Parameter index for theta
        int theta_index = [THETA_INDEX];
        // Parameter index for phi
        int phi_index   = [PHI_INDEX];
        int i, i_theta;
        double sum, norm;
        
        // Copy parameters because they will be modified
        for(i=0; i<[NPARS]; i++) {
                pars[i] = dp[i];
        }

        if (n_theta == 0) {
                return weight_dispersion( &disperse_[MODEL_NAME]_analytical_2D,
                                phi_values, phi_weights, n_phi, phi_index, pars, q, phi_q );
        } else {
                sum = 0.0;
                norm = 0.0;
                
                for(i_theta=0; i_theta<n_theta; i_theta++) {
                        // Assign new theta value
                        pars[theta_index] = theta_values[i_theta];
                        // Evaluate the function, weight by sin(theta) 
                        sum += sin(theta_values[i_theta]) * theta_weights[i_theta] * 
                                        weight_dispersion( &disperse_[MODEL_NAME]_analytical_2D,
                                        phi_values, phi_weights, n_phi, phi_index, pars, q, phi_q );
                        // Keep track of normalization
                        norm += theta_weights[i_theta];
                }
                
                // Protect against null weight vector
                if(norm > 0) {
                        return sum/norm;
                }
        }
        return 0.0;
}