[fca6936] | 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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[1d78e4b] | 70 | double nsigmas; |
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[fca6936] | 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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[eba9885] | 79 | * Schulz dispersion model |
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| 80 | */ |
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| 81 | class SchulzDispersion: 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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[1d78e4b] | 84 | double nsigmas; |
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[eba9885] | 85 | |
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| 86 | SchulzDispersion(); |
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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 | * LogNormal dispersion model |
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| 94 | */ |
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| 95 | class LogNormalDispersion: 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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[1d78e4b] | 98 | double nsigmas; |
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[eba9885] | 99 | |
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| 100 | LogNormalDispersion(); |
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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 | /** |
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[fca6936] | 108 | * Dispersion model based on arrays provided by the user |
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| 109 | */ |
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| 110 | class ArrayDispersion: public DispersionModel { |
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| 111 | private: |
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| 112 | /// Array of values |
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| 113 | double* _values; |
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| 114 | /// Array of weights |
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| 115 | double* _weights; |
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| 116 | |
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| 117 | /// Method to set the weight points from arrays |
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| 118 | void set_weights(int, double*, double*); |
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| 119 | void operator()(void *, vector<WeightPoint>&); |
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| 120 | void accept_as_source(DispersionVisitor*, void*, void*); |
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| 121 | void accept_as_destination(DispersionVisitor*, void*, void*); |
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| 122 | public: |
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| 123 | |
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| 124 | }; |
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| 125 | |
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| 126 | /** |
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| 127 | * Parameter class to hold information about a |
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| 128 | * parameter. |
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| 129 | */ |
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| 130 | class Parameter { |
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| 131 | public: |
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| 132 | /// Current value of the parameter |
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| 133 | double value; |
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| 134 | /// True if the parameter has a minimum bound |
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| 135 | bool has_min; |
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| 136 | /// True if the parameter has a maximum bound |
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| 137 | bool has_max; |
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| 138 | /// Minimum bound |
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| 139 | double min; |
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| 140 | /// Maximum bound |
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| 141 | double max; |
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| 142 | /// True if the parameter can be dispersed or averaged |
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| 143 | bool has_dispersion; |
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| 144 | /// Pointer to the dispersion model object for this parameter |
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| 145 | DispersionModel* dispersion; |
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| 146 | |
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| 147 | Parameter(); |
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| 148 | Parameter(double); |
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| 149 | Parameter(double, bool); |
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| 150 | |
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| 151 | /// Method to set a minimum value |
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| 152 | void set_min(double); |
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| 153 | /// Method to set a maximum value |
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| 154 | void set_max(double); |
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| 155 | /// Method to get weight points for this parameter |
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| 156 | void get_weights(vector<WeightPoint>&); |
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| 157 | /// Returns the value of the parameter |
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| 158 | double operator()(); |
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| 159 | /// Sets the value of the parameter |
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| 160 | double operator=(double); |
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| 161 | }; |
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| 162 | #endif |
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