| 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 "libStructureFactor.h" |
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| 33 | #include "stacked_disks.h" |
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| 34 | } |
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| 35 | |
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| 36 | StackedDisksModel :: StackedDisksModel() { |
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| 37 | scale = Parameter(1.0); |
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| 38 | radius = Parameter(3000.0, true); |
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| 39 | radius.set_min(0.0); |
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| 40 | core_thick = Parameter(10.0, true); |
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| 41 | core_thick.set_min(0.0); |
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| 42 | layer_thick = Parameter(15.0); |
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| 43 | layer_thick.set_min(0.0); |
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| 44 | core_sld = Parameter(4.0e-6); |
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| 45 | layer_sld = Parameter(-4.0e-7); |
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| 46 | solvent_sld = Parameter(5.0e-6); |
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| 47 | n_stacking = Parameter(1); |
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| 48 | sigma_d = Parameter(0); |
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| 49 | background = Parameter(0.001); |
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| 50 | axis_theta = Parameter(0.0, true); |
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| 51 | axis_phi = Parameter(0.0, true); |
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| 52 | } |
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| 53 | |
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| 54 | /** |
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| 55 | * Function to evaluate 1D scattering function |
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| 56 | * The NIST IGOR library is used for the actual calculation. |
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| 57 | * @param q: q-value |
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| 58 | * @return: function value |
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| 59 | */ |
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| 60 | double StackedDisksModel :: operator()(double q) { |
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| 61 | double dp[10]; |
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| 62 | |
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| 63 | // Fill parameter array for IGOR library |
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| 64 | // Add the background after averaging |
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| 65 | dp[0] = scale(); |
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| 66 | dp[1] = radius(); |
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| 67 | dp[2] = core_thick(); |
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| 68 | dp[3] = layer_thick(); |
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| 69 | dp[4] = core_sld(); |
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| 70 | dp[5] = layer_sld(); |
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| 71 | dp[6] = solvent_sld(); |
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| 72 | dp[7] = n_stacking(); |
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| 73 | dp[8] = sigma_d(); |
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| 74 | dp[9] = 0.0; |
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| 75 | |
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| 76 | // Get the dispersion points for the radius |
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| 77 | vector<WeightPoint> weights_radius; |
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| 78 | radius.get_weights(weights_radius); |
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| 79 | |
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| 80 | // Get the dispersion points for the core_thick |
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| 81 | vector<WeightPoint> weights_core_thick; |
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| 82 | core_thick.get_weights(weights_core_thick); |
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| 83 | |
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| 84 | // Get the dispersion points for the layer_thick |
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| 85 | vector<WeightPoint> weights_layer_thick; |
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| 86 | layer_thick.get_weights(weights_layer_thick); |
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| 87 | |
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| 88 | // Perform the computation, with all weight points |
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| 89 | double sum = 0.0; |
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| 90 | double norm = 0.0; |
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| 91 | double vol = 0.0; |
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| 92 | |
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| 93 | // Loop over length weight points |
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| 94 | for(int i=0; i< (int)weights_radius.size(); i++) { |
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| 95 | dp[1] = weights_radius[i].value; |
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| 96 | |
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| 97 | // Loop over radius weight points |
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| 98 | for(int j=0; j< (int)weights_core_thick.size(); j++) { |
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| 99 | dp[2] = weights_core_thick[j].value; |
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| 100 | |
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| 101 | // Loop over thickness weight points |
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| 102 | for(int k=0; k< (int)weights_layer_thick.size(); k++) { |
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| 103 | dp[3] = weights_layer_thick[k].value; |
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| 104 | //Un-normalize by volume |
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| 105 | sum += weights_radius[i].weight |
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| 106 | * weights_core_thick[j].weight * weights_layer_thick[k].weight* StackedDiscs(dp, q) |
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| 107 | *pow(weights_radius[i].value,2)*(weights_core_thick[j].value+2*weights_layer_thick[k].value); |
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| 108 | //Find average volume |
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| 109 | vol += weights_radius[i].weight |
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| 110 | * weights_core_thick[j].weight * weights_layer_thick[k].weight |
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| 111 | *pow(weights_radius[i].value,2)*(weights_core_thick[j].value+2*weights_layer_thick[k].value); |
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| 112 | norm += weights_radius[i].weight |
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| 113 | * weights_core_thick[j].weight* weights_layer_thick[k].weight; |
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| 114 | } |
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| 115 | } |
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| 116 | } |
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| 117 | if (vol != 0.0 && norm != 0.0) { |
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| 118 | //Re-normalize by avg volume |
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| 119 | sum = sum/(vol/norm);} |
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| 120 | |
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| 121 | return sum/norm + background(); |
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| 122 | } |
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| 123 | |
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| 124 | /** |
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| 125 | * Function to evaluate 2D scattering function |
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| 126 | * @param q_x: value of Q along x |
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| 127 | * @param q_y: value of Q along y |
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| 128 | * @return: function value |
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| 129 | */ |
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| 130 | double StackedDisksModel :: operator()(double qx, double qy) { |
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| 131 | StackedDisksParameters dp; |
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| 132 | // Fill parameter array |
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| 133 | dp.scale = scale(); |
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| 134 | dp.core_thick = core_thick(); |
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| 135 | dp.radius = radius(); |
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| 136 | dp.layer_thick = layer_thick(); |
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| 137 | dp.core_sld = core_sld(); |
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| 138 | dp.layer_sld = layer_sld(); |
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| 139 | dp.solvent_sld= solvent_sld(); |
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| 140 | dp.n_stacking = n_stacking(); |
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| 141 | dp.sigma_d = sigma_d(); |
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| 142 | dp.background = 0.0; |
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| 143 | dp.axis_theta = axis_theta(); |
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| 144 | dp.axis_phi = axis_phi(); |
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| 145 | |
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| 146 | // Get the dispersion points for the length |
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| 147 | vector<WeightPoint> weights_core_thick; |
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| 148 | core_thick.get_weights(weights_core_thick); |
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| 149 | |
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| 150 | // Get the dispersion points for the radius |
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| 151 | vector<WeightPoint> weights_radius; |
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| 152 | radius.get_weights(weights_radius); |
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| 153 | |
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| 154 | // Get the dispersion points for the thickness |
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| 155 | vector<WeightPoint> weights_layer_thick; |
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| 156 | layer_thick.get_weights(weights_layer_thick); |
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| 157 | |
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| 158 | // Get angular averaging for theta |
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| 159 | vector<WeightPoint> weights_theta; |
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| 160 | axis_theta.get_weights(weights_theta); |
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| 161 | |
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| 162 | // Get angular averaging for phi |
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| 163 | vector<WeightPoint> weights_phi; |
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| 164 | axis_phi.get_weights(weights_phi); |
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| 165 | |
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| 166 | // Perform the computation, with all weight points |
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| 167 | double sum = 0.0; |
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| 168 | double norm = 0.0; |
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| 169 | double norm_vol = 0.0; |
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| 170 | double vol = 0.0; |
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| 171 | |
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| 172 | // Loop over length weight points |
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| 173 | for(int i=0; i< (int)weights_core_thick.size(); i++) { |
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| 174 | dp.core_thick = weights_core_thick[i].value; |
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| 175 | |
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| 176 | // Loop over radius weight points |
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| 177 | for(int j=0; j< (int)weights_radius.size(); j++) { |
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| 178 | dp.radius = weights_radius[j].value; |
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| 179 | |
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| 180 | // Loop over thickness weight points |
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| 181 | for(int k=0; k< (int)weights_layer_thick.size(); k++) { |
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| 182 | dp.layer_thick = weights_layer_thick[k].value; |
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| 183 | |
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| 184 | for(int l=0; l< (int)weights_theta.size(); l++) { |
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| 185 | dp.axis_theta = weights_theta[l].value; |
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| 186 | |
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| 187 | // Average over phi distribution |
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| 188 | for(int m=0; m <(int)weights_phi.size(); m++) { |
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| 189 | dp.axis_phi = weights_phi[m].value; |
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| 190 | |
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| 191 | //Un-normalize by volume |
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| 192 | double _ptvalue = weights_core_thick[i].weight |
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| 193 | * weights_radius[j].weight |
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| 194 | * weights_layer_thick[k].weight |
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| 195 | * weights_theta[l].weight |
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| 196 | * weights_phi[m].weight |
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| 197 | * stacked_disks_analytical_2DXY(&dp, qx, qy) |
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| 198 | *pow(weights_radius[j].value,2)*(weights_core_thick[i].value+2*weights_layer_thick[k].value); |
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| 199 | if (weights_theta.size()>1) { |
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| 200 | _ptvalue *= sin(weights_theta[l].value); |
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| 201 | } |
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| 202 | sum += _ptvalue; |
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| 203 | //Find average volume |
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| 204 | vol += weights_radius[j].weight |
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| 205 | * weights_core_thick[i].weight * weights_layer_thick[k].weight |
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| 206 | *pow(weights_radius[j].value,2)*(weights_core_thick[i].value+2*weights_layer_thick[k].value); |
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| 207 | //Find norm for volume |
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| 208 | norm_vol += weights_radius[j].weight |
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| 209 | * weights_core_thick[i].weight * weights_layer_thick[k].weight; |
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| 210 | |
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| 211 | norm += weights_core_thick[i].weight |
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| 212 | * weights_radius[j].weight |
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| 213 | * weights_layer_thick[k].weight |
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| 214 | * weights_theta[l].weight |
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| 215 | * weights_phi[m].weight; |
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| 216 | } |
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| 217 | } |
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| 218 | } |
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| 219 | } |
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| 220 | } |
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| 221 | // Averaging in theta needs an extra normalization |
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| 222 | // factor to account for the sin(theta) term in the |
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| 223 | // integration (see documentation). |
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| 224 | if (weights_theta.size()>1) norm = norm / asin(1.0); |
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| 225 | if (vol != 0.0 && norm_vol != 0.0) { |
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| 226 | //Re-normalize by avg volume |
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| 227 | sum = sum/(vol/norm_vol);} |
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| 228 | return sum/norm + background(); |
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| 229 | } |
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| 230 | |
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| 231 | /** |
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| 232 | * Function to evaluate 2D scattering function |
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| 233 | * @param pars: parameters of the triaxial ellipsoid |
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| 234 | * @param q: q-value |
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| 235 | * @param phi: angle phi |
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| 236 | * @return: function value |
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| 237 | */ |
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| 238 | double StackedDisksModel :: evaluate_rphi(double q, double phi) { |
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| 239 | double qx = q*cos(phi); |
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| 240 | double qy = q*sin(phi); |
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| 241 | return (*this).operator()(qx, qy); |
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| 242 | } |
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| 243 | /** |
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| 244 | * Function to calculate effective radius |
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| 245 | * @return: effective radius value |
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| 246 | */ |
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| 247 | double StackedDisksModel :: calculate_ER() { |
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| 248 | StackedDisksParameters dp; |
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| 249 | |
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| 250 | dp.core_thick = core_thick(); |
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| 251 | dp.radius = radius(); |
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| 252 | dp.layer_thick = layer_thick(); |
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| 253 | dp.n_stacking = n_stacking(); |
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| 254 | |
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| 255 | double rad_out = 0.0; |
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| 256 | if (dp.n_stacking <= 0.0){ |
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| 257 | return rad_out; |
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| 258 | } |
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| 259 | |
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| 260 | // Perform the computation, with all weight points |
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| 261 | double sum = 0.0; |
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| 262 | double norm = 0.0; |
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| 263 | |
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| 264 | // Get the dispersion points for the length |
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| 265 | vector<WeightPoint> weights_core_thick; |
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| 266 | core_thick.get_weights(weights_core_thick); |
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| 267 | |
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| 268 | // Get the dispersion points for the radius |
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| 269 | vector<WeightPoint> weights_radius; |
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| 270 | radius.get_weights(weights_radius); |
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| 271 | |
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| 272 | // Get the dispersion points for the thickness |
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| 273 | vector<WeightPoint> weights_layer_thick; |
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| 274 | layer_thick.get_weights(weights_layer_thick); |
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| 275 | |
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| 276 | // Loop over major shell weight points |
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| 277 | for(int i=0; i< (int)weights_core_thick.size(); i++) { |
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| 278 | dp.core_thick = weights_core_thick[i].value; |
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| 279 | for(int j=0; j< (int)weights_layer_thick.size(); j++) { |
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| 280 | dp.layer_thick = weights_layer_thick[j].value; |
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| 281 | for(int k=0; k< (int)weights_radius.size(); k++) { |
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| 282 | dp.radius = weights_radius[k].value; |
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| 283 | //Note: output of "DiamCyl(dp.length,dp.radius)" is DIAMETER. |
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| 284 | sum +=weights_core_thick[i].weight*weights_layer_thick[j].weight |
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| 285 | * weights_radius[k].weight*DiamCyl(dp.n_stacking*(dp.layer_thick*2.0+dp.core_thick),dp.radius)/2.0; |
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| 286 | norm += weights_core_thick[i].weight*weights_layer_thick[j].weight* weights_radius[k].weight; |
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| 287 | } |
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| 288 | } |
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| 289 | } |
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| 290 | if (norm != 0){ |
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| 291 | //return the averaged value |
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| 292 | rad_out = sum/norm;} |
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| 293 | else{ |
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| 294 | //return normal value |
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| 295 | //Note: output of "DiamCyl(dp.length,dp.radius)" is DIAMETER. |
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| 296 | rad_out = DiamCyl(dp.n_stacking*(dp.layer_thick*2.0+dp.core_thick),dp.radius)/2.0;} |
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| 297 | |
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| 298 | return rad_out; |
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| 299 | } |
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