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 "models.hh" |
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24 | #include "parameters.hh" |
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25 | #include <stdio.h> |
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26 | using namespace std; |
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27 | |
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28 | extern "C" { |
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29 | #include "libTwoPhase.h" |
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30 | #include "polygausscoil.h" |
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31 | } |
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32 | |
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33 | Poly_GaussCoil :: Poly_GaussCoil() { |
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34 | scale = Parameter(1.0); |
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35 | rg = Parameter(60.0, true); |
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36 | rg.set_min(0.0); |
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37 | poly_m = Parameter(2.0); |
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38 | background = Parameter(0.001); |
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39 | } |
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40 | |
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41 | /** |
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42 | * Function to evaluate 1D scattering function |
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43 | * The NIST IGOR library is used for the actual calculation. |
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44 | * @param q: q-value |
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45 | * @return: function value |
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46 | */ |
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47 | double Poly_GaussCoil :: operator()(double q) { |
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48 | double dp[4]; |
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49 | |
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50 | // Fill parameter array for IGOR library |
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51 | // Add the background after averaging |
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52 | dp[0] = scale(); |
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53 | dp[1] = rg(); |
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54 | dp[2] = poly_m(); |
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55 | dp[3] = 0.0; |
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56 | |
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57 | // Get the dispersion points for the radius |
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58 | vector<WeightPoint> weights_rad; |
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59 | rg.get_weights(weights_rad); |
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60 | |
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61 | // Perform the computation, with all weight points |
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62 | double sum = 0.0; |
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63 | |
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64 | |
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65 | double norm = 0.0; |
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66 | double vol = 0.0; |
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67 | |
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68 | // Loop over radius weight points |
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69 | for(int i=0; i<weights_rad.size(); i++) { |
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70 | dp[1] = weights_rad[i].value; |
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71 | |
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72 | //Un-normalize SphereForm by volume |
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73 | sum += weights_rad[i].weight |
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74 | * PolyGaussCoil(dp, q) * pow(weights_rad[i].value,3); |
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75 | //Find average volume |
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76 | vol += weights_rad[i].weight |
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77 | * pow(weights_rad[i].value,3); |
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78 | |
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79 | norm += weights_rad[i].weight; |
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80 | } |
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81 | |
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82 | if (vol != 0.0 && norm != 0.0) { |
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83 | //Re-normalize by avg volume |
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84 | sum = sum/(vol/norm);} |
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85 | return sum/norm + background(); |
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86 | |
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87 | |
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88 | sum = PolyGaussCoil(dp, q); |
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89 | return sum + background(); |
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90 | } |
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91 | |
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92 | /** |
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93 | * Function to evaluate 2D scattering function |
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94 | * @param q_x: value of Q along x |
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95 | * @param q_y: value of Q along y |
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96 | * @return: function value |
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97 | */ |
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98 | double Poly_GaussCoil :: operator()(double qx, double qy) { |
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99 | double q = sqrt(qx*qx + qy*qy); |
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100 | return (*this).operator()(q); |
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101 | } |
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102 | |
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103 | /** |
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104 | * Function to evaluate 2D scattering function |
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105 | * @param pars: parameters of the sphere |
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106 | * @param q: q-value |
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107 | * @param phi: angle phi |
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108 | * @return: function value |
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109 | */ |
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110 | double Poly_GaussCoil :: evaluate_rphi(double q, double phi) { |
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111 | return (*this).operator()(q); |
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112 | } |
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113 | |
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114 | /** |
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115 | * Function to calculate effective radius |
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116 | * @return: effective radius value |
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117 | */ |
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118 | double Poly_GaussCoil :: calculate_ER() { |
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119 | PolyGaussCoilParameters dp; |
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120 | dp.scale = scale(); |
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121 | dp.rg= rg(); |
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122 | dp.poly_m = poly_m(); |
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123 | dp.background = background(); |
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124 | double rad_out = 0.0; |
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125 | |
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126 | // Perform the computation, with all weight points |
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127 | double sum = 0.0; |
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128 | double norm = 0.0; |
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129 | |
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130 | // Get the dispersion points for the radius |
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131 | vector<WeightPoint> weights_rad; |
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132 | rg.get_weights(weights_rad); |
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133 | // Loop over radius weight points to average the radius value |
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134 | for(int i=0; i<weights_rad.size(); i++) { |
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135 | sum += weights_rad[i].weight |
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136 | * weights_rad[i].value; |
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137 | norm += weights_rad[i].weight; |
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138 | } |
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139 | if (norm != 0){ |
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140 | //return the averaged value |
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141 | rad_out = sum/norm;} |
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142 | else{ |
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143 | //return normal value |
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144 | rad_out = rg();} |
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145 | |
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146 | return rad_out; |
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147 | } |
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