1 | /** |
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2 | This software was developed by the University of Tennessee as part of the |
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3 | Distributed Data Analysis of Neutron Scattering Experiments (DANSE) |
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4 | project funded by the US National Science Foundation. |
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5 | |
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6 | If you use DANSE applications to do scientific research that leads to |
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7 | publication, we ask that you acknowledge the use of the software with the |
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8 | following sentence: |
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9 | |
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10 | "This work benefited from DANSE software developed under NSF award DMR-0520547." |
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11 | |
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12 | copyright 2008, University of Tennessee |
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13 | */ |
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14 | |
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15 | /** |
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16 | * Scattering model classes |
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17 | * The classes use the IGOR library found in |
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18 | * sansmodels/src/libigor |
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19 | * |
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20 | * TODO: refactor so that we pull in the old sansmodels.c_extensions |
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21 | * TODO: add 2d |
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22 | */ |
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23 | |
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24 | #include <math.h> |
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25 | #include "models.hh" |
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26 | #include "parameters.hh" |
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27 | #include <stdio.h> |
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28 | using namespace std; |
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29 | |
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30 | extern "C" { |
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31 | #include "libCylinder.h" |
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32 | #include "stacked_disks.h" |
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33 | } |
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34 | |
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35 | StackedDisksModel :: StackedDisksModel() { |
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36 | scale = Parameter(1.0); |
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37 | radius = Parameter(3000.0, true); |
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38 | radius.set_min(0.0); |
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39 | core_thick = Parameter(10.0, true); |
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40 | core_thick.set_min(0.0); |
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41 | layer_thick = Parameter(15.0); |
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42 | layer_thick.set_min(0.0); |
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43 | core_sld = Parameter(4.0e-6); |
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44 | layer_sld = Parameter(-4.0e-7); |
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45 | solvent_sld = Parameter(5.0e-6); |
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46 | n_stacking = Parameter(1); |
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47 | sigma_d = Parameter(0); |
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48 | background = Parameter(0.001); |
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49 | axis_theta = Parameter(0.0, true); |
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50 | axis_phi = Parameter(0.0, true); |
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51 | } |
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52 | |
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53 | /** |
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54 | * Function to evaluate 1D scattering function |
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55 | * The NIST IGOR library is used for the actual calculation. |
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56 | * @param q: q-value |
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57 | * @return: function value |
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58 | */ |
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59 | double StackedDisksModel :: operator()(double q) { |
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60 | double dp[10]; |
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61 | |
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62 | // Fill parameter array for IGOR library |
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63 | // Add the background after averaging |
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64 | dp[0] = scale(); |
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65 | dp[1] = radius(); |
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66 | dp[2] = core_thick(); |
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67 | dp[3] = layer_thick(); |
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68 | dp[4] = core_sld(); |
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69 | dp[5] = layer_sld(); |
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70 | dp[6] = solvent_sld(); |
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71 | dp[7] = n_stacking(); |
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72 | dp[8] = sigma_d(); |
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73 | dp[9] = 0.0; |
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74 | |
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75 | // Get the dispersion points for the radius |
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76 | vector<WeightPoint> weights_radius; |
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77 | radius.get_weights(weights_radius); |
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78 | |
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79 | // Get the dispersion points for the core_thick |
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80 | vector<WeightPoint> weights_core_thick; |
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81 | core_thick.get_weights(weights_core_thick); |
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82 | |
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83 | // Get the dispersion points for the layer_thick |
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84 | vector<WeightPoint> weights_layer_thick; |
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85 | layer_thick.get_weights(weights_layer_thick); |
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86 | |
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87 | // Perform the computation, with all weight points |
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88 | double sum = 0.0; |
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89 | double norm = 0.0; |
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90 | |
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91 | // Loop over length weight points |
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92 | for(int i=0; i< (int)weights_radius.size(); i++) { |
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93 | dp[1] = weights_radius[i].value; |
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94 | |
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95 | // Loop over radius weight points |
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96 | for(int j=0; j< (int)weights_core_thick.size(); j++) { |
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97 | dp[2] = weights_core_thick[j].value; |
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98 | |
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99 | // Loop over thickness weight points |
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100 | for(int k=0; k< (int)weights_layer_thick.size(); k++) { |
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101 | dp[3] = weights_layer_thick[k].value; |
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102 | |
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103 | sum += weights_radius[i].weight |
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104 | * weights_core_thick[j].weight * weights_layer_thick[k].weight* StackedDiscs(dp, q); |
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105 | norm += weights_radius[i].weight |
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106 | * weights_core_thick[j].weight* weights_layer_thick[k].weight; |
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107 | } |
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108 | } |
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109 | } |
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110 | return sum/norm + background(); |
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111 | } |
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112 | |
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113 | /** |
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114 | * Function to evaluate 2D scattering function |
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115 | * @param q_x: value of Q along x |
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116 | * @param q_y: value of Q along y |
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117 | * @return: function value |
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118 | */ |
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119 | double StackedDisksModel :: operator()(double qx, double qy) { |
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120 | StackedDisksParameters dp; |
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121 | // Fill parameter array |
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122 | dp.scale = scale(); |
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123 | dp.core_thick = core_thick(); |
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124 | dp.radius = radius(); |
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125 | dp.core_thick = core_thick(); |
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126 | dp.core_sld = core_sld(); |
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127 | dp.layer_sld = layer_sld(); |
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128 | dp.solvent_sld= solvent_sld(); |
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129 | dp.n_stacking = n_stacking(); |
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130 | dp.sigma_d = sigma_d(); |
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131 | dp.background = 0.0; |
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132 | dp.axis_theta = axis_theta(); |
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133 | dp.axis_phi = axis_phi(); |
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134 | |
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135 | // Get the dispersion points for the length |
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136 | vector<WeightPoint> weights_core_thick; |
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137 | core_thick.get_weights(weights_core_thick); |
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138 | |
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139 | // Get the dispersion points for the radius |
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140 | vector<WeightPoint> weights_radius; |
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141 | radius.get_weights(weights_radius); |
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142 | |
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143 | // Get the dispersion points for the thickness |
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144 | vector<WeightPoint> weights_layer_thick; |
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145 | layer_thick.get_weights(weights_layer_thick); |
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146 | |
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147 | // Get angular averaging for theta |
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148 | vector<WeightPoint> weights_theta; |
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149 | axis_theta.get_weights(weights_theta); |
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150 | |
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151 | // Get angular averaging for phi |
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152 | vector<WeightPoint> weights_phi; |
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153 | axis_phi.get_weights(weights_phi); |
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154 | |
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155 | // Perform the computation, with all weight points |
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156 | double sum = 0.0; |
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157 | double norm = 0.0; |
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158 | |
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159 | // Loop over length weight points |
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160 | for(int i=0; i< (int)weights_core_thick.size(); i++) { |
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161 | dp.core_thick = weights_core_thick[i].value; |
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162 | |
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163 | // Loop over radius weight points |
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164 | for(int j=0; j< (int)weights_radius.size(); j++) { |
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165 | dp.radius = weights_radius[j].value; |
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166 | |
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167 | // Loop over thickness weight points |
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168 | for(int k=0; k< (int)weights_layer_thick.size(); k++) { |
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169 | dp.layer_thick = weights_layer_thick[k].value; |
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170 | |
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171 | for(int l=0; l< (int)weights_theta.size(); l++) { |
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172 | dp.axis_theta = weights_theta[l].value; |
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173 | |
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174 | // Average over phi distribution |
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175 | for(int m=0; m <(int)weights_phi.size(); m++) { |
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176 | dp.axis_phi = weights_phi[m].value; |
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177 | |
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178 | double _ptvalue = weights_core_thick[i].weight |
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179 | * weights_radius[j].weight |
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180 | * weights_layer_thick[k].weight |
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181 | * weights_theta[l].weight |
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182 | * weights_phi[m].weight |
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183 | * stacked_disks_analytical_2DXY(&dp, qx, qy); |
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184 | if (weights_theta.size()>1) { |
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185 | _ptvalue *= sin(weights_theta[l].value); |
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186 | } |
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187 | sum += _ptvalue; |
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188 | |
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189 | norm += weights_core_thick[i].weight |
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190 | * weights_radius[j].weight |
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191 | * weights_layer_thick[k].weight |
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192 | * weights_theta[l].weight |
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193 | * weights_phi[m].weight; |
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194 | } |
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195 | } |
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196 | } |
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197 | } |
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198 | } |
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199 | // Averaging in theta needs an extra normalization |
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200 | // factor to account for the sin(theta) term in the |
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201 | // integration (see documentation). |
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202 | if (weights_theta.size()>1) norm = norm / asin(1.0); |
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203 | return sum/norm + background(); |
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204 | } |
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205 | |
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206 | /** |
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207 | * Function to evaluate 2D scattering function |
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208 | * @param pars: parameters of the triaxial ellipsoid |
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209 | * @param q: q-value |
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210 | * @param phi: angle phi |
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211 | * @return: function value |
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212 | */ |
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213 | double StackedDisksModel :: evaluate_rphi(double q, double phi) { |
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214 | double qx = q*cos(phi); |
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215 | double qy = q*sin(phi); |
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216 | return (*this).operator()(qx, qy); |
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217 | } |
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