source: src/FunctionApproximation/FunctionModel.hpp@ 9291d04

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Last change on this file since 9291d04 was e36ba2, checked in by Frederik Heber <heber@…>, 12 years ago

FunctionModel extended by triplefunction setter, does nothing by default.

  • SaturationPotential's setTriplefunction() removed.
  • Tersoff's setTriplefunction now truely sets the function.
  • LevMartester always sets a triple function whether the potential uses it or not.
  • Property mode set to 100644
File size: 4.6 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 a vector of particle tyoes
48 typedef std::vector< double > charges_t;
49 //!> typedef for the magic triple function that gets the other two distances for a given argument
50 typedef boost::function< std::vector<arguments_t>(const argument_t &, const double)> triplefunction_t;
51
52public:
53 FunctionModel() {}
54 virtual ~FunctionModel() {}
55
56 /** Setter for the parameters of the model function.
57 *
58 * \param params set of parameters to set
59 */
60 virtual void setParameters(const parameters_t &params)=0;
61
62 /** Getter for the parameters of this model function.
63 *
64 * \return current set of parameters of the model function
65 */
66 virtual parameters_t getParameters() const=0;
67
68 /** Sets the parameter randomly within the sensible range of each parameter.
69 *
70 * \param data container with training data for guesstimating range
71 */
72 virtual void setParametersToRandomInitialValues(const TrainingData &data)=0;
73
74 /** Getter for the number of parameters of this model function.
75 *
76 * \return number of parameters
77 */
78 virtual size_t getParameterDimension() const=0;
79
80 /** Sets the magic triple function that we use for getting angle distances.
81 *
82 * @param _triplefunction function that returns a list of triples (i.e. the
83 * two remaining distances) to a given pair of points (contained as
84 * indices within the argument)
85 */
86 virtual void setTriplefunction(triplefunction_t &_triplefunction)
87 {}
88
89 /** Evaluates the function with the given \a arguments and the current set of
90 * parameters.
91 *
92 * \param arguments set of arguments as input variables to the function
93 * \return result of the function
94 */
95 virtual results_t operator()(const arguments_t &arguments) const=0;
96
97 /** Evaluates the derivative of the function with the given \a arguments
98 * with respect to a specific parameter indicated by \a index.
99 *
100 * \param arguments set of arguments as input variables to the function
101 * \param index derivative of which parameter
102 * \return result vector containing the derivative with respect to the given
103 * input
104 */
105 virtual results_t parameter_derivative(const arguments_t &arguments, const size_t index) const=0;
106
107 /** States whether lower and upper boundaries should be used to constraint
108 * the parameter search for this function model.
109 *
110 * \return true - constraints should be used, false - else
111 */
112 virtual bool isBoxConstraint() const=0;
113
114 /** Returns a vector which are the lower boundaries for each parameter_t
115 * of this FunctionModel.
116 *
117 * \return vector of parameter_t resembling lowest allowed values
118 */
119 virtual parameters_t getLowerBoxConstraints() const=0;
120
121 /** Returns a vector which are the upper boundaries for each parameter_t
122 * of this FunctionModel.
123 *
124 * \return vector of parameter_t resembling highest allowed values
125 */
126 virtual parameters_t getUpperBoxConstraints() const=0;
127
128 /** Returns a bound function to be used with TrainingData, extracting distances
129 * from a Fragment.
130 *
131 * \param charges vector of charges to be extracted
132 * \return bound function extracting distances from a fragment
133 */
134 virtual extractor_t getFragmentSpecificExtractor(const charges_t &charges) const=0;
135};
136
137#endif /* FUNCTIONMODEL_HPP_ */
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