source: src/Potentials/Specifics/ManyBodyPotential_Tersoff.hpp@ 35d171

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Last change on this file since 35d171 was e1fe7e, checked in by Frederik Heber <heber@…>, 11 years ago

FunctionModel now uses list_of_arguments to split sequence of subsets of distances.

  • this fixes ambiguities with the set of distances: Imagine the distances within a water molecule as OH (A) and HH (B). We then may have a sequence of argument_t as AABAAB. And with the current implementation of CompoundPotential::splitUpArgumentsByModels() we would always choose the latter (and more complex) model. Hence, we make two calls to TriplePotential_Angle, instead of calls twice to PairPotential_Harmonic for A, one to PairPotential_Harmonic for B, and once to TriplePotential_Angle for AAB.
  • now, we new list looks like A,A,B,AAB where each tuple of distances can be uniquely associated with a specific potential.
  • changed signatures of EmpiricalPotential::operator(), ::derivative(), ::parameter_derivative(). This involved changing all of the current specific potentials and CompoundPotential.
  • TrainingData must discern between the InputVector_t (just all distances) and the FilteredInputVector_t (tuples of subsets of distances).
  • FunctionApproximation now has list_of_arguments_t as parameter to evaluate() and evaluate_derivative().
  • DOCU: docu change in TrainingData.
  • Property mode set to 100644
File size: 9.7 KB
Line 
1/*
2 * ManyBodyPotential_Tersoff.hpp
3 *
4 * Created on: Sep 26, 2012
5 * Author: heber
6 */
7
8#ifndef MANYBODYPOTENTIAL_TERSOFF_HPP_
9#define MANYBODYPOTENTIAL_TERSOFF_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 <cmath>
18#include <limits>
19
20#include "Potentials/EmpiricalPotential.hpp"
21
22class PotentialFactory;
23class TrainingData;
24
25/** This class is the implementation of the Tersoff potential function.
26 *
27 * \note The arguments_t argument list is here in the following order:
28 * -# first \f$ r_{ij} \f$,
29 * -# then all \f$ r_{ik} \f$ that are within the cutoff, i.e. \f$ r_{ik} < R + D\f$
30 *
31 */
32class ManyBodyPotential_Tersoff :
33 public EmpiricalPotential
34{
35 //!> grant unit test access to internal parts
36 friend class ManyBodyPotential_TersoffTest;
37 //!> grant PotentialFactory access to default cstor
38 friend class PotentialFactory;
39 // some repeated typedefs to avoid ambiguities
40 typedef FunctionModel::list_of_arguments_t list_of_arguments_t;
41 typedef FunctionModel::arguments_t arguments_t;
42 typedef FunctionModel::result_t result_t;
43 typedef FunctionModel::results_t results_t;
44 typedef EmpiricalPotential::derivative_components_t derivative_components_t;
45 typedef FunctionModel::parameters_t parameters_t;
46private:
47 /** Private default constructor.
48 *
49 * This prevents creation of potential without set ParticleTypes_t.
50 *
51 */
52 ManyBodyPotential_Tersoff();
53
54public:
55 /** Constructor for class ManyBodyPotential_Tersoff.
56 *
57 * \param _ParticleTypes particle types for this potential
58 */
59 ManyBodyPotential_Tersoff(
60 const ParticleTypes_t &_ParticleTypes
61 );
62
63 /** Constructor for class ManyBodyPotential_Tersoff.
64 *
65 * @param _R offset for cutoff
66 * @param _S halfwidth for cutoff relative to \a _R
67 * @param A
68 * @param B
69 * @param lambda
70 * @param mu
71 * @param lambda3
72 * @param alpha
73 * @param beta
74 * @param chi
75 * @param omega
76 * @param n
77 * @param c
78 * @param d
79 * @param h
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 ManyBodyPotential_Tersoff(
85 const ParticleTypes_t &_ParticleTypes,
86 const double &_R,
87 const double &_S,
88 const double &_A,
89 const double &_B,
90 const double &_lambda,
91 const double &_mu,
92 const double &_lambda3,
93 const double &_alpha,
94 const double &_beta,
95 const double &_chi,
96 const double &_omega,
97 const double &_n,
98 const double &_c,
99 const double &_d,
100 const double &_h);
101
102 /** Destructor of class ManyBodyPotential_Tersoff.
103 *
104 */
105 virtual ~ManyBodyPotential_Tersoff() {}
106
107 /** Evaluates the Tersoff potential for the given arguments.
108 *
109 * @param listarguments list of distances
110 * @return value of the potential function
111 */
112 results_t operator()(const list_of_arguments_t &listarguments) const;
113
114 /** Evaluates the derivative of the Tersoff potential with respect to the
115 * input variables.
116 *
117 * @param listarguments list of distances
118 * @return vector with components of the derivative
119 */
120 derivative_components_t derivative(const list_of_arguments_t &listarguments) const;
121
122 /** Evaluates the derivative of the function with the given \a arguments
123 * with respect to a specific parameter indicated by \a index.
124 *
125 * \param listarguments list of distances
126 * \param index derivative of which parameter
127 * \return result vector containing the derivative with respect to the given
128 * input
129 */
130 results_t parameter_derivative(const list_of_arguments_t &listarguments, const size_t index) const;
131
132 /** Returns the functor that converts argument_s into the
133 * internal coordinate described by this potential function.
134 *
135 * \return coordinator functor
136 */
137 Coordinator::ptr getCoordinator() const
138 { return coordinator; }
139
140 /** Return the token name of this specific potential.
141 *
142 * \return token name of the potential
143 */
144 const std::string& getToken() const
145 { return potential_token; }
146
147 /** Returns a vector of parameter names.
148 *
149 * This is required from the specific implementation
150 *
151 * \return vector of strings containing parameter names
152 */
153 const ParameterNames_t& getParameterNames() const
154 { return ParameterNames; }
155
156 /** States whether lower and upper boundaries should be used to constraint
157 * the parameter search for this function model.
158 *
159 * \return true - constraints should be used, false - else
160 */
161 bool isBoxConstraint() const {
162 return true;
163 }
164
165 /** Returns a vector which are the lower boundaries for each parameter_t
166 * of this FunctionModel.
167 *
168 * \return vector of parameter_t resembling lowest allowed values
169 */
170 parameters_t getLowerBoxConstraints() const {
171 parameters_t lowerbound(getParameterDimension(), -std::numeric_limits<double>::max());
172// lowerbound[R] = 0.;
173// lowerbound[S] = 0.;
174// lowerbound[lambda3] = 0.;
175// lowerbound[alpha] = 0.;
176 lowerbound[beta] = std::numeric_limits<double>::min();
177 lowerbound[n] = std::numeric_limits<double>::min();
178 lowerbound[c] = std::numeric_limits<double>::min();
179 lowerbound[d] = std::numeric_limits<double>::min();
180 return lowerbound;
181 }
182
183 /** Returns a vector which are the upper boundaries for each parameter_t
184 * of this FunctionModel.
185 *
186 * \return vector of parameter_t resembling highest allowed values
187 */
188 parameters_t getUpperBoxConstraints() const {
189 return parameters_t(getParameterDimension(), std::numeric_limits<double>::max());
190 }
191
192 /** Returns a bound function to be used with TrainingData, extracting distances
193 * from a Fragment.
194 *
195 * \return bound function extracting distances from a fragment
196 */
197 FunctionModel::filter_t getSpecificFilter() const;
198
199 /** Returns the number of arguments the underlying function requires.
200 *
201 * \return number of arguments of the function
202 */
203 size_t getSpecificArgumentCount() const
204 { return 1; }
205
206 /** Sets the magic triple function that we use for getting angle distances.
207 *
208 * @param _triplefunction function that returns a list of triples (i.e. the
209 * two remaining distances) to a given pair of points (contained as
210 * indices within the argument)
211 */
212 void setTriplefunction(triplefunction_t &_triplefunction)
213 { triplefunction = _triplefunction; }
214
215private:
216 /** This function represents the cutoff \f$ f_C \f$.
217 *
218 * @param distance variable of the function
219 * @return a value in [0,1].
220 */
221 result_t function_cutoff(
222 const double &distance
223 ) const;
224 /** This function has the exponential feature from the Morse potential.
225 *
226 * @param prefactor prefactor parameter to exp function
227 * @param lambda scale parameter of exp function's argument
228 * @param distance variable of the function
229 * @return
230 */
231 result_t function_smoother(
232 const double &prefactor,
233 const double &lambda,
234 const double &distance
235 ) const;
236
237 /** This function represents \f$ (1 + \alpha^n \eta^n)^{-1/2n} \f$.
238 *
239 * @param alpha prefactor to eta function
240 * @param r_ij distance argument
241 * @param eta result value of eta or zeta
242 * @return \f$ (1 + \alpha^n \eta^n)^{-1/2n} \f$
243 */
244 result_t function_prefactor(
245 const double &alpha,
246 const double &eta
247 ) const;
248
249 result_t
250 function_eta(
251 const argument_t &r_ij
252 ) const;
253
254 result_t
255 function_zeta(
256 const argument_t &r_ij
257 ) const;
258
259 result_t
260 function_theta(
261 const double &r_ij,
262 const double &r_ik,
263 const double &r_jk
264 ) const;
265
266 result_t
267 function_angle(
268 const double &r_ij,
269 const double &r_ik,
270 const double &r_jk
271 ) const;
272
273private:
274 result_t
275 function_derivative_c(
276 const argument_t &r_ij
277 ) const;
278
279 result_t
280 function_derivative_d(
281 const argument_t &r_ij
282 ) const;
283
284 result_t
285 function_derivative_h(
286 const argument_t &r_ij
287 ) const;
288
289public:
290 enum parameter_enum_t {
291 A,
292 B,
293 lambda,
294 mu,
295 beta,
296 n,
297 c,
298 d,
299 h,
300// R,
301// S,
302// lambda3,
303// alpha,
304// chi,
305// omega,
306 MAXPARAMS
307 };
308
309private:
310 //!> parameter vector with parameters as in enum parameter_enum_t
311 parameters_t params;
312
313public:
314 // some internal parameters which are fixed
315 const double R;
316 const double S;
317 const double lambda3;
318 const double alpha;
319 const double chi;
320 const double omega;
321
322public:
323 /** Setter for parameters as required by FunctionModel interface.
324 *
325 * \param _params given set of parameters
326 */
327 void setParameters(const parameters_t &_params);
328
329 /** Getter for parameters as required by FunctionModel interface.
330 *
331 * \return set of parameters
332 */
333 parameters_t getParameters() const
334 {
335 return params;
336 }
337
338 /** Sets the parameter randomly within the sensible range of each parameter.
339 *
340 * \param data container with training data for guesstimating range
341 */
342 void setParametersToRandomInitialValues(const TrainingData &data);
343
344 /** Getter for the number of parameters of this model function.
345 *
346 * \return number of parameters
347 */
348 size_t getParameterDimension() const
349 {
350 return MAXPARAMS;
351 }
352
353private:
354 //!> bound function that obtains the triples for the internal coordinationb summation.
355 boost::function< std::vector< arguments_t >(const argument_t &, const double)> triplefunction;
356
357 //!> static definitions of the parameter name for this potential
358 static const ParameterNames_t ParameterNames;
359
360 //!> static token of this potential type
361 static const std::string potential_token;
362
363 //!> internal coordinator object for converting arguments_t
364 static Coordinator::ptr coordinator;
365};
366
367
368#endif /* MANYBODYPOTENTIAL_TERSOFF_HPP_ */
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