source: src/Potentials/Specifics/ConstantPotential.hpp@ a82d33

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Last change on this file since a82d33 was a82d33, checked in by Frederik Heber <heber@…>, 11 years ago

FIX: Default cstor of specific potentials did not allocate parameter vector.

  • is used by PotentialFactory and would seg'fault on subsequent parameter filling via stream_from().
  • Property mode set to 100644
File size: 5.0 KB
Line 
1/*
2 * ConstantPotential.hpp
3 *
4 * Created on: May 09, 2013
5 * Author: heber
6 */
7
8#ifndef CONSTANTPOTENTIAL_HPP_
9#define CONSTANTPOTENTIAL_HPP_
10
11
12// include config.h
13#ifdef HAVE_CONFIG_H
14#include <config.h>
15#endif
16
17#include <limits>
18
19#include "Potentials/EmpiricalPotential.hpp"
20
21class PotentialFactory;
22class TrainingData;
23
24/** This is the implementation of a constant potential to adapt to any offset
25 * in the potential energy.
26 *
27 * This evaluates \f$ k \f$.
28 *
29 */
30class ConstantPotential :
31 public EmpiricalPotential
32{
33 //!> grant unit test access to internal parts
34 friend class ConstantPotentialTest;
35 //!> grant PotentialFactory access to default cstor
36 friend class PotentialFactory;
37 // some repeated typedefs to avoid ambiguities
38 typedef FunctionModel::arguments_t arguments_t;
39 typedef FunctionModel::result_t result_t;
40 typedef FunctionModel::results_t results_t;
41 typedef EmpiricalPotential::derivative_components_t derivative_components_t;
42 typedef FunctionModel::parameters_t parameters_t;
43private:
44 /** Private default constructor.
45 *
46 * This prevents creation of potential without set ParticleTypes_t.
47 *
48 * \note PotentialFactory may use this default cstor
49 *
50 */
51 ConstantPotential();
52
53public:
54 ConstantPotential(const ParticleTypes_t &_ParticleTypes);
55 ConstantPotential(
56 const ParticleTypes_t &_ParticleTypes,
57 const double _energy_offset);
58 virtual ~ConstantPotential() {}
59
60 /** Setter for parameters as required by FunctionModel interface.
61 *
62 * \param _params given set of parameters
63 */
64 void setParameters(const parameters_t &_params);
65
66 /** Getter for parameters as required by FunctionModel interface.
67 *
68 * \return set of parameters
69 */
70 parameters_t getParameters() const
71 {
72 return params;
73 }
74
75 /** Sets the parameter randomly within the sensible range of each parameter.
76 *
77 * \param data container with training data for guesstimating range
78 */
79 void setParametersToRandomInitialValues(const TrainingData &data);
80
81 /** Getter for the number of parameters of this model function.
82 *
83 * \return number of parameters
84 */
85 size_t getParameterDimension() const
86 {
87 return 1;
88 }
89
90 /** Evaluates the harmonic potential function for the given arguments.
91 *
92 * @param arguments single distance
93 * @return value of the potential function
94 */
95 results_t operator()(const arguments_t &arguments) const;
96
97 /** Evaluates the derivative of the potential function.
98 *
99 * @param arguments single distance
100 * @return vector with derivative with respect to the input degrees of freedom
101 */
102 derivative_components_t derivative(const arguments_t &arguments) const;
103
104 /** Evaluates the derivative of the function with the given \a arguments
105 * with respect to a specific parameter indicated by \a index.
106 *
107 * \param arguments set of arguments as input variables to the function
108 * \param index derivative of which parameter
109 * \return result vector containing the derivative with respect to the given
110 * input
111 */
112 results_t parameter_derivative(const arguments_t &arguments, const size_t index) const;
113
114 /** Return the token name of this specific potential.
115 *
116 * \return token name of the potential
117 */
118 const std::string& getToken() const
119 { return potential_token; }
120
121 /** Returns a vector of parameter names.
122 *
123 * This is required from the specific implementation
124 *
125 * \return vector of strings containing parameter names
126 */
127 const ParameterNames_t& getParameterNames() const
128 { return ParameterNames; }
129
130 /** States whether lower and upper boundaries should be used to constraint
131 * the parameter search for this function model.
132 *
133 * \return true - constraints should be used, false - else
134 */
135 bool isBoxConstraint() const {
136 return true;
137 }
138
139 /** Returns a vector which are the lower boundaries for each parameter_t
140 * of this FunctionModel.
141 *
142 * \return vector of parameter_t resembling lowest allowed values
143 */
144 parameters_t getLowerBoxConstraints() const {
145 parameters_t lowerbound(getParameterDimension(), -std::numeric_limits<double>::max());
146 return lowerbound;
147 }
148
149 /** Returns a vector which are the upper boundaries for each parameter_t
150 * of this FunctionModel.
151 *
152 * \return vector of parameter_t resembling highest allowed values
153 */
154 parameters_t getUpperBoxConstraints() const {
155 return parameters_t(getParameterDimension(), std::numeric_limits<double>::max());
156 }
157
158 /** Returns a bound function to be used with TrainingData, extracting distances
159 * from a Fragment.
160 *
161 * \return bound function extracting distances from a fragment
162 */
163 FunctionModel::extractor_t getFragmentSpecificExtractor() const;
164
165 enum parameter_enum_t {
166 energy_offset=0,
167 MAXPARAMS
168 };
169
170private:
171 //!> parameter vector with parameters as in enum parameter_enum_t
172 parameters_t params;
173
174 //!> static definitions of the parameter name for this potential
175 static const ParameterNames_t ParameterNames;
176
177 //!> static token of this potential type
178 static const std::string potential_token;
179};
180
181#endif /* CONSTANTPOTENTIAL_HPP_ */
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