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 | */ |
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21 | |
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22 | #include <math.h> |
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23 | #include "parameters.hh" |
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24 | #include <stdio.h> |
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25 | using namespace std; |
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26 | #include "multishell.h" |
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27 | |
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28 | extern "C" { |
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29 | #include "libSphere.h" |
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30 | } |
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31 | |
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32 | typedef struct { |
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33 | double scale; |
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34 | double core_radius; |
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35 | double s_thickness; |
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36 | double w_thickness; |
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37 | double core_sld; |
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38 | double shell_sld; |
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39 | double n_pairs; |
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40 | double background; |
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41 | |
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42 | } MultiShellParameters; |
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43 | |
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44 | MultiShellModel :: MultiShellModel() { |
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45 | scale = Parameter(1.0); |
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46 | core_radius = Parameter(60.0, true); |
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47 | core_radius.set_min(0.0); |
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48 | s_thickness = Parameter(10.0, true); |
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49 | s_thickness.set_min(0.0); |
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50 | w_thickness = Parameter(10.0, true); |
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51 | w_thickness.set_min(0.0); |
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52 | core_sld = Parameter(6.4e-6); |
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53 | shell_sld = Parameter(4.0e-7); |
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54 | n_pairs = Parameter(2); |
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55 | background = Parameter(0.0); |
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56 | } |
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57 | |
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58 | /** |
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59 | * Function to evaluate 1D scattering function |
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60 | * The NIST IGOR library is used for the actual calculation. |
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61 | * @param q: q-value |
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62 | * @return: function value |
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63 | */ |
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64 | double MultiShellModel :: operator()(double q) { |
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65 | double dp[8]; |
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66 | |
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67 | // Fill parameter array for IGOR library |
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68 | // Add the background after averaging |
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69 | dp[0] = scale(); |
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70 | dp[1] = core_radius(); |
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71 | dp[2] = s_thickness(); |
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72 | dp[3] = w_thickness(); |
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73 | dp[4] = core_sld(); |
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74 | dp[5] = shell_sld(); |
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75 | dp[6] = n_pairs(); |
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76 | dp[7] = 0.0; |
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77 | |
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78 | // Get the dispersion points for the core radius |
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79 | vector<WeightPoint> weights_core_radius; |
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80 | core_radius.get_weights(weights_core_radius); |
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81 | |
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82 | // Get the dispersion points for the s_thickness |
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83 | vector<WeightPoint> weights_s_thickness; |
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84 | s_thickness.get_weights(weights_s_thickness); |
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85 | |
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86 | // Get the dispersion points for the w_thickness |
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87 | vector<WeightPoint> weights_w_thickness; |
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88 | w_thickness.get_weights(weights_w_thickness); |
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89 | |
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90 | // Perform the computation, with all weight points |
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91 | double sum = 0.0; |
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92 | double norm = 0.0; |
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93 | double vol = 0.0; |
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94 | |
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95 | // Loop over radius weight points |
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96 | for(int i=0; i< (int)weights_core_radius.size(); i++) { |
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97 | dp[1] = weights_core_radius[i].value; |
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98 | for(int j=0; j< (int)weights_s_thickness.size(); j++){ |
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99 | dp[2] = weights_s_thickness[j].value; |
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100 | for(int k=0; k< (int)weights_w_thickness.size(); k++){ |
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101 | dp[3] = weights_w_thickness[k].value; |
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102 | //Un-normalize SphereForm by volume |
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103 | sum += weights_core_radius[i].weight*weights_s_thickness[j].weight |
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104 | *weights_w_thickness[k].weight* MultiShell(dp, q) |
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105 | *pow(weights_core_radius[i].value+dp[6]*weights_s_thickness[j].value+(dp[6]-1)*weights_w_thickness[k].value,3); |
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106 | //Find average volume |
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107 | vol += weights_core_radius[i].weight*weights_s_thickness[j].weight |
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108 | *weights_w_thickness[k].weight |
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109 | *pow(weights_core_radius[i].value+dp[6]*weights_s_thickness[j].value+(dp[6]-1)*weights_w_thickness[k].value,3); |
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110 | norm += weights_core_radius[i].weight*weights_s_thickness[j].weight |
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111 | *weights_w_thickness[k].weight; |
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112 | } |
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113 | } |
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114 | } |
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115 | if (vol != 0.0 && norm != 0.0) { |
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116 | //Re-normalize by avg volume |
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117 | sum = sum/(vol/norm);} |
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118 | return sum/norm + background(); |
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119 | } |
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120 | |
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121 | /** |
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122 | * Function to evaluate 2D scattering function |
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123 | * @param q_x: value of Q along x |
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124 | * @param q_y: value of Q along y |
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125 | * @return: function value |
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126 | */ |
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127 | double MultiShellModel :: operator()(double qx, double qy) { |
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128 | double q = sqrt(qx*qx + qy*qy); |
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129 | return (*this).operator()(q); |
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130 | } |
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131 | |
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132 | /** |
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133 | * Function to evaluate 2D scattering function |
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134 | * @param pars: parameters of the multishell |
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135 | * @param q: q-value |
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136 | * @param phi: angle phi |
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137 | * @return: function value |
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138 | */ |
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139 | double MultiShellModel :: evaluate_rphi(double q, double phi) { |
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140 | return (*this).operator()(q); |
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141 | } |
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142 | /** |
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143 | * Function to calculate effective radius |
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144 | * @return: effective radius value |
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145 | */ |
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146 | double MultiShellModel :: calculate_ER() { |
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147 | MultiShellParameters dp; |
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148 | |
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149 | dp.core_radius = core_radius(); |
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150 | dp.s_thickness = s_thickness(); |
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151 | dp.w_thickness = w_thickness(); |
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152 | dp.n_pairs = n_pairs(); |
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153 | |
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154 | double rad_out = 0.0; |
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155 | |
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156 | // Perform the computation, with all weight points |
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157 | double sum = 0.0; |
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158 | double norm = 0.0; |
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159 | if (dp.n_pairs <= 0.0 ){ |
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160 | dp.n_pairs = 0.0; |
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161 | } |
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162 | |
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163 | // Get the dispersion points for the core radius |
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164 | vector<WeightPoint> weights_core_radius; |
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165 | core_radius.get_weights(weights_core_radius); |
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166 | |
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167 | // Get the dispersion points for the s_thickness |
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168 | vector<WeightPoint> weights_s_thickness; |
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169 | s_thickness.get_weights(weights_s_thickness); |
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170 | |
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171 | // Get the dispersion points for the w_thickness |
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172 | vector<WeightPoint> weights_w_thickness; |
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173 | w_thickness.get_weights(weights_w_thickness); |
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174 | |
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175 | // Loop over major shell weight points |
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176 | for(int i=0; i< (int)weights_s_thickness.size(); i++) { |
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177 | dp.s_thickness = weights_s_thickness[i].value; |
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178 | for(int j=0; j< (int)weights_w_thickness.size(); j++) { |
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179 | dp.w_thickness = weights_w_thickness[j].value; |
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180 | for(int k=0; k< (int)weights_core_radius.size(); k++) { |
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181 | dp.core_radius = weights_core_radius[k].value; |
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182 | sum += weights_s_thickness[i].weight*weights_w_thickness[j].weight |
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183 | * weights_core_radius[k].weight*(dp.core_radius+dp.n_pairs*dp.s_thickness+(dp.n_pairs-1.0)*dp.w_thickness); |
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184 | norm += weights_s_thickness[i].weight*weights_w_thickness[j].weight* weights_core_radius[k].weight; |
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185 | } |
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186 | } |
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187 | } |
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188 | if (norm != 0){ |
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189 | //return the averaged value |
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190 | rad_out = sum/norm;} |
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191 | else{ |
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192 | //return normal value |
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193 | rad_out = (dp.core_radius+dp.n_pairs*dp.s_thickness+(dp.n_pairs-1.0)*dp.w_thickness);} |
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194 | |
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195 | return rad_out; |
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196 | } |
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