source: src/FunctionApproximation/FunctionModel.hpp@ d449a9

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Last change on this file since d449a9 was 035c0d, checked in by Frederik Heber <heber@…>, 12 years ago

Removed typedef charges_t from FunctionModel, using SerializationPotential's instead.

  • Property mode set to 100644
File size: 4.4 KB
Line 
1/*
2 * FunctionModel.hpp
3 *
4 * Created on: 02.10.2012
5 * Author: heber
6 */
7
8#ifndef FUNCTIONMODEL_HPP_
9#define FUNCTIONMODEL_HPP_
10
11// include config.h
12#ifdef HAVE_CONFIG_H
13#include <config.h>
14#endif
15
16#include <boost/function.hpp>
17#include <vector>
18
19#include "FunctionApproximation/FunctionArgument.hpp"
20
21class Fragment;
22class TrainingData;
23
24/** This class represents the interface for a given function to model a
25 * high-dimensional data set in FunctionApproximation.
26 *
27 * As the parameters may be stored differently, the interface functions for
28 * getting and setting them are as light-weight (and not speed-optimized)
29 * as possible.
30 *
31 */
32class FunctionModel
33{
34public:
35 //!> typedef for a single parameter degree of freedom of the function
36 typedef double parameter_t;
37 //!> typedef for the whole set of parameters of the function
38 typedef std::vector<parameter_t> parameters_t;
39 //!> typedef for the argument vector as input to the function
40 typedef std::vector<argument_t> arguments_t;
41 //!> typedef for a single result degree of freedom
42 typedef double result_t;
43 //!> typedef for the result vector as returned by the function
44 typedef std::vector<result_t> results_t;
45 //!> typedef for a function containing how to extract required information from a Fragment.
46 typedef boost::function< arguments_t (const Fragment &, const size_t)> extractor_t;
47 //!> typedef for the magic triple function that gets the other two distances for a given argument
48 typedef boost::function< std::vector<arguments_t>(const argument_t &, const double)> triplefunction_t;
49
50public:
51 FunctionModel() {}
52 virtual ~FunctionModel() {}
53
54 /** Setter for the parameters of the model function.
55 *
56 * \param params set of parameters to set
57 */
58 virtual void setParameters(const parameters_t &params)=0;
59
60 /** Getter for the parameters of this model function.
61 *
62 * \return current set of parameters of the model function
63 */
64 virtual parameters_t getParameters() const=0;
65
66 /** Sets the parameter randomly within the sensible range of each parameter.
67 *
68 * \param data container with training data for guesstimating range
69 */
70 virtual void setParametersToRandomInitialValues(const TrainingData &data)=0;
71
72 /** Getter for the number of parameters of this model function.
73 *
74 * \return number of parameters
75 */
76 virtual size_t getParameterDimension() const=0;
77
78 /** Sets the magic triple function that we use for getting angle distances.
79 *
80 * @param _triplefunction function that returns a list of triples (i.e. the
81 * two remaining distances) to a given pair of points (contained as
82 * indices within the argument)
83 */
84 virtual void setTriplefunction(triplefunction_t &_triplefunction)
85 {}
86
87 /** Evaluates the function with the given \a arguments and the current set of
88 * parameters.
89 *
90 * \param arguments set of arguments as input variables to the function
91 * \return result of the function
92 */
93 virtual results_t operator()(const arguments_t &arguments) const=0;
94
95 /** Evaluates the derivative of the function with the given \a arguments
96 * with respect to a specific parameter indicated by \a index.
97 *
98 * \param arguments set of arguments as input variables to the function
99 * \param index derivative of which parameter
100 * \return result vector containing the derivative with respect to the given
101 * input
102 */
103 virtual results_t parameter_derivative(const arguments_t &arguments, const size_t index) const=0;
104
105 /** States whether lower and upper boundaries should be used to constraint
106 * the parameter search for this function model.
107 *
108 * \return true - constraints should be used, false - else
109 */
110 virtual bool isBoxConstraint() const=0;
111
112 /** Returns a vector which are the lower boundaries for each parameter_t
113 * of this FunctionModel.
114 *
115 * \return vector of parameter_t resembling lowest allowed values
116 */
117 virtual parameters_t getLowerBoxConstraints() const=0;
118
119 /** Returns a vector which are the upper boundaries for each parameter_t
120 * of this FunctionModel.
121 *
122 * \return vector of parameter_t resembling highest allowed values
123 */
124 virtual parameters_t getUpperBoxConstraints() const=0;
125
126 /** Returns a bound function to be used with TrainingData, extracting distances
127 * from a Fragment.
128 *
129 * \return bound function extracting distances from a fragment
130 */
131 virtual extractor_t getFragmentSpecificExtractor() const=0;
132};
133
134#endif /* FUNCTIONMODEL_HPP_ */
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