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 | #ifndef PARAM_CLASS_H |
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15 | #define PARAM_CLASS_H |
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16 | /** |
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17 | * TODO: will need to write a bridge class |
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18 | * to convert the dispersion model parameters |
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19 | * into dictionary parameters for python. |
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20 | */ |
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21 | #include <vector> |
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22 | #include "dispersion_visitor.hh" |
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23 | |
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24 | using namespace std; |
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25 | |
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26 | /** |
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27 | * Weight point class to hold averaging points |
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28 | */ |
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29 | class WeightPoint { |
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30 | public: |
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31 | /// Value of the weight point |
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32 | double value; |
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33 | /// Weight of the weight point |
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34 | double weight; |
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35 | |
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36 | WeightPoint(); |
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37 | WeightPoint(double, double); |
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38 | }; |
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39 | |
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40 | /** |
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41 | * Basic averaging model. The class instance will |
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42 | * generate a flat distribution of weight points |
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43 | * according to the number of points specified |
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44 | * and the width of the distribution. The center |
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45 | * of the distribution is specified by the |
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46 | * Parameter object taken in as a parameter. |
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47 | */ |
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48 | class DispersionModel { |
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49 | public: |
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50 | /// Number of points to average over |
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51 | int npts; |
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52 | /// Width of the distribution (step function) |
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53 | double width; |
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54 | |
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55 | DispersionModel(); |
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56 | /// Method that generates the weight points |
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57 | virtual void operator()(void *, vector<WeightPoint>&); |
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58 | virtual void set_weights(int, double*, double*); |
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59 | virtual void accept_as_source(DispersionVisitor*, void*, void*); |
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60 | virtual void accept_as_destination(DispersionVisitor*, void*, void*); |
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61 | }; |
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62 | |
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63 | |
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64 | /** |
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65 | * Gaussian dispersion model |
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66 | */ |
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67 | class GaussianDispersion: public DispersionModel { |
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68 | public: |
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69 | /// Number of sigmas on each side of the mean |
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70 | double nsigmas; |
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71 | |
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72 | GaussianDispersion(); |
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73 | void operator()(void *, vector<WeightPoint>&); |
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74 | void accept_as_source(DispersionVisitor*, void*, void*); |
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75 | void accept_as_destination(DispersionVisitor*, void*, void*); |
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76 | }; |
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77 | |
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78 | /** |
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79 | * Flat dispersion model |
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80 | */ |
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81 | class RectangleDispersion: public DispersionModel { |
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82 | public: |
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83 | /// Number of sigmas on each side of the mean |
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84 | double nsigmas; |
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85 | |
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86 | RectangleDispersion(); |
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87 | void operator()(void *, vector<WeightPoint>&); |
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88 | void accept_as_source(DispersionVisitor*, void*, void*); |
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89 | void accept_as_destination(DispersionVisitor*, void*, void*); |
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90 | }; |
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91 | |
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92 | /** |
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93 | * Schulz dispersion model |
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94 | */ |
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95 | class SchulzDispersion: public DispersionModel { |
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96 | public: |
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97 | /// Number of sigmas on each side of the mean |
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98 | double nsigmas; |
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99 | |
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100 | SchulzDispersion(); |
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101 | void operator()(void *, vector<WeightPoint>&); |
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102 | void accept_as_source(DispersionVisitor*, void*, void*); |
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103 | void accept_as_destination(DispersionVisitor*, void*, void*); |
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104 | }; |
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105 | |
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106 | /** |
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107 | * LogNormal dispersion model |
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108 | */ |
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109 | class LogNormalDispersion: public DispersionModel { |
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110 | public: |
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111 | /// Number of sigmas on each side of the mean |
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112 | double nsigmas; |
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113 | |
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114 | LogNormalDispersion(); |
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115 | void operator()(void *, vector<WeightPoint>&); |
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116 | void accept_as_source(DispersionVisitor*, void*, void*); |
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117 | void accept_as_destination(DispersionVisitor*, void*, void*); |
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118 | }; |
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119 | |
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120 | |
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121 | /** |
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122 | * Dispersion model based on arrays provided by the user |
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123 | */ |
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124 | class ArrayDispersion: public DispersionModel { |
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125 | private: |
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126 | /// Array of values |
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127 | double* _values; |
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128 | /// Array of weights |
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129 | double* _weights; |
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130 | |
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131 | /// Method to set the weight points from arrays |
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132 | void set_weights(int, double*, double*); |
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133 | void operator()(void *, vector<WeightPoint>&); |
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134 | void accept_as_source(DispersionVisitor*, void*, void*); |
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135 | void accept_as_destination(DispersionVisitor*, void*, void*); |
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136 | public: |
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137 | |
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138 | }; |
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139 | |
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140 | /** |
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141 | * Parameter class to hold information about a |
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142 | * parameter. |
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143 | */ |
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144 | class Parameter { |
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145 | public: |
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146 | /// Current value of the parameter |
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147 | double value; |
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148 | /// True if the parameter has a minimum bound |
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149 | bool has_min; |
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150 | /// True if the parameter has a maximum bound |
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151 | bool has_max; |
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152 | /// Minimum bound |
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153 | double min; |
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154 | /// Maximum bound |
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155 | double max; |
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156 | /// True if the parameter can be dispersed or averaged |
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157 | bool has_dispersion; |
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158 | /// Pointer to the dispersion model object for this parameter |
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159 | DispersionModel* dispersion; |
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160 | |
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161 | Parameter(); |
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162 | Parameter(double); |
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163 | Parameter(double, bool); |
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164 | |
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165 | /// Method to set a minimum value |
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166 | void set_min(double); |
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167 | /// Method to set a maximum value |
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168 | void set_max(double); |
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169 | /// Method to get weight points for this parameter |
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170 | void get_weights(vector<WeightPoint>&); |
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171 | /// Returns the value of the parameter |
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172 | double operator()(); |
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173 | /// Sets the value of the parameter |
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174 | double operator=(double); |
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175 | }; |
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176 | #endif |
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