[5068697] | 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 | */ |
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| 22 | |
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| 23 | #include <math.h> |
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| 24 | #include "models.hh" |
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| 25 | #include "parameters.hh" |
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| 26 | #include <stdio.h> |
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| 27 | using namespace std; |
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| 28 | |
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| 29 | extern "C" { |
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| 30 | #include "libCylinder.h" |
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[f9bf661] | 31 | #include "libStructureFactor.h" |
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[5068697] | 32 | #include "triaxial_ellipsoid.h" |
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| 33 | } |
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| 34 | |
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| 35 | TriaxialEllipsoidModel :: TriaxialEllipsoidModel() { |
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| 36 | scale = Parameter(1.0); |
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[3c102d4] | 37 | semi_axisA = Parameter(35.0, true); |
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[5068697] | 38 | semi_axisA.set_min(0.0); |
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[3c102d4] | 39 | semi_axisB = Parameter(100.0, true); |
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[5068697] | 40 | semi_axisB.set_min(0.0); |
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| 41 | semi_axisC = Parameter(400.0, true); |
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| 42 | semi_axisC.set_min(0.0); |
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| 43 | contrast = Parameter(5.3e-6); |
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| 44 | background = Parameter(0.0); |
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[3c102d4] | 45 | axis_theta = Parameter(1.0, true); |
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| 46 | axis_phi = Parameter(1.0, true); |
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[975ec8e] | 47 | axis_psi = Parameter(0.0, true); |
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[5068697] | 48 | } |
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| 49 | |
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| 50 | /** |
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| 51 | * Function to evaluate 1D scattering function |
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| 52 | * The NIST IGOR library is used for the actual calculation. |
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| 53 | * @param q: q-value |
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| 54 | * @return: function value |
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| 55 | */ |
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| 56 | double TriaxialEllipsoidModel :: operator()(double q) { |
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[975ec8e] | 57 | double dp[6]; |
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[5068697] | 58 | |
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| 59 | // Fill parameter array for IGOR library |
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| 60 | // Add the background after averaging |
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| 61 | dp[0] = scale(); |
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| 62 | dp[1] = semi_axisA(); |
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| 63 | dp[2] = semi_axisB(); |
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| 64 | dp[3] = semi_axisC(); |
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| 65 | dp[4] = contrast(); |
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[9188cc1] | 66 | dp[5] = 0.0; |
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[5068697] | 67 | |
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| 68 | // Get the dispersion points for the semi axis A |
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| 69 | vector<WeightPoint> weights_semi_axisA; |
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| 70 | semi_axisA.get_weights(weights_semi_axisA); |
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| 71 | |
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| 72 | // Get the dispersion points for the semi axis B |
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| 73 | vector<WeightPoint> weights_semi_axisB; |
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| 74 | semi_axisB.get_weights(weights_semi_axisB); |
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| 75 | |
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| 76 | // Get the dispersion points for the semi axis C |
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| 77 | vector<WeightPoint> weights_semi_axisC; |
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| 78 | semi_axisC.get_weights(weights_semi_axisC); |
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| 79 | |
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| 80 | // Perform the computation, with all weight points |
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| 81 | double sum = 0.0; |
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| 82 | double norm = 0.0; |
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[c451be9] | 83 | double vol = 0.0; |
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[5068697] | 84 | |
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| 85 | // Loop over semi axis A weight points |
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| 86 | for(int i=0; i< (int)weights_semi_axisA.size(); i++) { |
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| 87 | dp[1] = weights_semi_axisA[i].value; |
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| 88 | |
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| 89 | // Loop over semi axis B weight points |
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| 90 | for(int j=0; j< (int)weights_semi_axisB.size(); j++) { |
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| 91 | dp[2] = weights_semi_axisB[j].value; |
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| 92 | |
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| 93 | // Loop over semi axis C weight points |
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| 94 | for(int k=0; k< (int)weights_semi_axisC.size(); k++) { |
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| 95 | dp[3] = weights_semi_axisC[k].value; |
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[c451be9] | 96 | //Un-normalize by volume |
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[5068697] | 97 | sum += weights_semi_axisA[i].weight |
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[c451be9] | 98 | * weights_semi_axisB[j].weight * weights_semi_axisC[k].weight* TriaxialEllipsoid(dp, q) |
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| 99 | * weights_semi_axisA[i].value*weights_semi_axisB[j].value*weights_semi_axisC[k].value; |
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| 100 | //Find average volume |
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| 101 | vol += weights_semi_axisA[i].weight |
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| 102 | * weights_semi_axisB[j].weight * weights_semi_axisC[k].weight |
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| 103 | * weights_semi_axisA[i].value*weights_semi_axisB[j].value*weights_semi_axisC[k].value; |
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| 104 | |
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[5068697] | 105 | norm += weights_semi_axisA[i].weight |
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| 106 | * weights_semi_axisB[j].weight * weights_semi_axisC[k].weight; |
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| 107 | } |
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| 108 | } |
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| 109 | } |
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[c451be9] | 110 | if (vol != 0.0 && norm != 0.0) { |
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| 111 | //Re-normalize by avg volume |
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| 112 | sum = sum/(vol/norm);} |
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| 113 | |
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[5068697] | 114 | return sum/norm + background(); |
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| 115 | } |
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| 116 | |
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| 117 | /** |
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| 118 | * Function to evaluate 2D scattering function |
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| 119 | * @param q_x: value of Q along x |
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| 120 | * @param q_y: value of Q along y |
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| 121 | * @return: function value |
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| 122 | */ |
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| 123 | double TriaxialEllipsoidModel :: operator()(double qx, double qy) { |
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| 124 | TriaxialEllipsoidParameters dp; |
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| 125 | // Fill parameter array |
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| 126 | dp.scale = scale(); |
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| 127 | dp.semi_axisA = semi_axisA(); |
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| 128 | dp.semi_axisB = semi_axisB(); |
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| 129 | dp.semi_axisC = semi_axisC(); |
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| 130 | dp.contrast = contrast(); |
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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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[975ec8e] | 134 | dp.axis_psi = axis_psi(); |
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[5068697] | 135 | |
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| 136 | // Get the dispersion points for the semi_axis A |
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| 137 | vector<WeightPoint> weights_semi_axisA; |
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| 138 | semi_axisA.get_weights(weights_semi_axisA); |
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| 139 | |
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| 140 | // Get the dispersion points for the semi_axis B |
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| 141 | vector<WeightPoint> weights_semi_axisB; |
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| 142 | semi_axisB.get_weights(weights_semi_axisB); |
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| 143 | |
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| 144 | // Get the dispersion points for the semi_axis C |
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| 145 | vector<WeightPoint> weights_semi_axisC; |
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| 146 | semi_axisC.get_weights(weights_semi_axisC); |
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| 147 | |
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| 148 | // Get angular averaging for theta |
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| 149 | vector<WeightPoint> weights_theta; |
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| 150 | axis_theta.get_weights(weights_theta); |
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| 151 | |
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| 152 | // Get angular averaging for phi |
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| 153 | vector<WeightPoint> weights_phi; |
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| 154 | axis_phi.get_weights(weights_phi); |
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| 155 | |
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[975ec8e] | 156 | // Get angular averaging for psi |
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| 157 | vector<WeightPoint> weights_psi; |
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| 158 | axis_psi.get_weights(weights_psi); |
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| 159 | |
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[5068697] | 160 | // Perform the computation, with all weight points |
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| 161 | double sum = 0.0; |
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| 162 | double norm = 0.0; |
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[c451be9] | 163 | double norm_vol = 0.0; |
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| 164 | double vol = 0.0; |
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[5068697] | 165 | |
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| 166 | // Loop over semi axis A weight points |
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| 167 | for(int i=0; i< (int)weights_semi_axisA.size(); i++) { |
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| 168 | dp.semi_axisA = weights_semi_axisA[i].value; |
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| 169 | |
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| 170 | // Loop over semi axis B weight points |
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| 171 | for(int j=0; j< (int)weights_semi_axisB.size(); j++) { |
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| 172 | dp.semi_axisB = weights_semi_axisB[j].value; |
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| 173 | |
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| 174 | // Loop over semi axis C weight points |
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| 175 | for(int k=0; k < (int)weights_semi_axisC.size(); k++) { |
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| 176 | dp.semi_axisC = weights_semi_axisC[k].value; |
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| 177 | |
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| 178 | // Average over theta distribution |
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| 179 | for(int l=0; l< (int)weights_theta.size(); l++) { |
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| 180 | dp.axis_theta = weights_theta[l].value; |
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| 181 | |
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| 182 | // Average over phi distribution |
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| 183 | for(int m=0; m <(int)weights_phi.size(); m++) { |
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| 184 | dp.axis_phi = weights_phi[m].value; |
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[975ec8e] | 185 | // Average over psi distribution |
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| 186 | for(int n=0; n <(int)weights_psi.size(); n++) { |
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| 187 | dp.axis_psi = weights_psi[n].value; |
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[c451be9] | 188 | //Un-normalize by volume |
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[975ec8e] | 189 | double _ptvalue = weights_semi_axisA[i].weight |
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| 190 | * weights_semi_axisB[j].weight |
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| 191 | * weights_semi_axisC[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 | * weights_psi[n].weight |
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[c451be9] | 195 | * triaxial_ellipsoid_analytical_2DXY(&dp, qx, qy) |
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| 196 | * weights_semi_axisA[i].value*weights_semi_axisB[j].value*weights_semi_axisC[k].value; |
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[975ec8e] | 197 | if (weights_theta.size()>1) { |
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| 198 | _ptvalue *= sin(weights_theta[k].value); |
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| 199 | } |
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| 200 | sum += _ptvalue; |
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[c451be9] | 201 | //Find average volume |
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| 202 | vol += weights_semi_axisA[i].weight |
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| 203 | * weights_semi_axisB[j].weight |
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| 204 | * weights_semi_axisC[k].weight |
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| 205 | * weights_semi_axisA[i].value*weights_semi_axisB[j].value*weights_semi_axisC[k].value; |
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| 206 | //Find norm for volume |
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| 207 | norm_vol += weights_semi_axisA[i].weight |
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| 208 | * weights_semi_axisB[j].weight |
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| 209 | * weights_semi_axisC[k].weight; |
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[975ec8e] | 210 | |
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| 211 | norm += weights_semi_axisA[i].weight |
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| 212 | * weights_semi_axisB[j].weight |
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| 213 | * weights_semi_axisC[k].weight |
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| 214 | * weights_theta[l].weight |
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| 215 | * weights_phi[m].weight |
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[3c102d4] | 216 | * weights_psi[n].weight; |
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[5068697] | 217 | } |
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| 218 | } |
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| 219 | |
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| 220 | } |
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| 221 | } |
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| 222 | } |
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| 223 | } |
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| 224 | // Averaging in theta needs an extra normalization |
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| 225 | // factor to account for the sin(theta) term in the |
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| 226 | // integration (see documentation). |
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| 227 | if (weights_theta.size()>1) norm = norm / asin(1.0); |
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[c451be9] | 228 | |
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| 229 | if (vol != 0.0 && norm_vol != 0.0) { |
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| 230 | //Re-normalize by avg volume |
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| 231 | sum = sum/(vol/norm_vol);} |
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| 232 | |
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[5068697] | 233 | return sum/norm + background(); |
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| 234 | } |
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| 235 | |
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| 236 | /** |
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| 237 | * Function to evaluate 2D scattering function |
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| 238 | * @param pars: parameters of the triaxial ellipsoid |
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| 239 | * @param q: q-value |
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| 240 | * @param phi: angle phi |
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| 241 | * @return: function value |
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| 242 | */ |
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| 243 | double TriaxialEllipsoidModel :: evaluate_rphi(double q, double phi) { |
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| 244 | double qx = q*cos(phi); |
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| 245 | double qy = q*sin(phi); |
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| 246 | return (*this).operator()(qx, qy); |
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| 247 | } |
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[5eb9154] | 248 | /** |
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| 249 | * Function to calculate effective radius |
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| 250 | * @return: effective radius value |
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| 251 | */ |
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| 252 | double TriaxialEllipsoidModel :: calculate_ER() { |
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[f9bf661] | 253 | TriaxialEllipsoidParameters dp; |
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| 254 | |
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| 255 | dp.semi_axisA = semi_axisA(); |
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| 256 | dp.semi_axisB = semi_axisB(); |
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| 257 | //polar axis C |
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| 258 | dp.semi_axisC = semi_axisC(); |
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| 259 | |
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| 260 | double rad_out = 0.0; |
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| 261 | //Surface average radius at the equat. cross section. |
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| 262 | double suf_rad = sqrt(dp.semi_axisA * dp.semi_axisB); |
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| 263 | |
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| 264 | // Perform the computation, with all weight points |
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| 265 | double sum = 0.0; |
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| 266 | double norm = 0.0; |
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| 267 | |
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| 268 | // Get the dispersion points for the semi_axis A |
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| 269 | vector<WeightPoint> weights_semi_axisA; |
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| 270 | semi_axisA.get_weights(weights_semi_axisA); |
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| 271 | |
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| 272 | // Get the dispersion points for the semi_axis B |
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| 273 | vector<WeightPoint> weights_semi_axisB; |
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| 274 | semi_axisB.get_weights(weights_semi_axisB); |
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| 275 | |
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| 276 | // Get the dispersion points for the semi_axis C |
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| 277 | vector<WeightPoint> weights_semi_axisC; |
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| 278 | semi_axisC.get_weights(weights_semi_axisC); |
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| 279 | |
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| 280 | // Loop over semi axis A weight points |
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| 281 | for(int i=0; i< (int)weights_semi_axisA.size(); i++) { |
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| 282 | dp.semi_axisA = weights_semi_axisA[i].value; |
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| 283 | |
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| 284 | // Loop over semi axis B weight points |
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| 285 | for(int j=0; j< (int)weights_semi_axisB.size(); j++) { |
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| 286 | dp.semi_axisB = weights_semi_axisB[j].value; |
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| 287 | |
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| 288 | // Loop over semi axis C weight points |
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| 289 | for(int k=0; k < (int)weights_semi_axisC.size(); k++) { |
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| 290 | dp.semi_axisC = weights_semi_axisC[k].value; |
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| 291 | |
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| 292 | //Calculate surface averaged radius |
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| 293 | suf_rad = sqrt(dp.semi_axisA * dp.semi_axisB); |
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| 294 | |
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| 295 | //Sum |
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| 296 | sum += weights_semi_axisA[i].weight |
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| 297 | * weights_semi_axisB[j].weight |
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| 298 | * weights_semi_axisC[k].weight * DiamEllip(dp.semi_axisC, suf_rad)/2.0; |
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| 299 | //Norm |
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| 300 | norm += weights_semi_axisA[i].weight* weights_semi_axisB[j].weight |
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| 301 | * weights_semi_axisC[k].weight; |
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| 302 | } |
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| 303 | } |
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| 304 | } |
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| 305 | if (norm != 0){ |
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| 306 | //return the averaged value |
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| 307 | rad_out = sum/norm;} |
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| 308 | else{ |
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| 309 | //return normal value |
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| 310 | rad_out = DiamEllip(dp.semi_axisC, suf_rad)/2.0;} |
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| 311 | |
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| 312 | return rad_out; |
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[5eb9154] | 313 | } |
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