source: src/Potentials/Specifics/ManyBodyPotential_Tersoff.hpp@ fc38cb

Candidate_v1.7.0 stable
Last change on this file since fc38cb was 3f8238, checked in by Frederik Heber <frederik.heber@…>, 4 years ago

Added number of particle types getter to EmpiricalPotential.

  • Property mode set to 100644
File size: 10.2 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
215 /** Getter for the graph specifying the binding model of the potential.
216 *
217 * \return BindingModel ref of the binding model
218 */
219 const BindingModel& getBindingModel() const
220 { return bindingmodel; }
221
222 /**
223 * Returns the number of particle types associated with the potential.
224 *
225 * \return number of particle types
226 */
227 unsigned int getParticleTypeNumber() const
228 { return 2; }
229
230private:
231 /** This function represents the cutoff \f$ f_C \f$.
232 *
233 * @param distance variable of the function
234 * @return a value in [0,1].
235 */
236 result_t function_cutoff(
237 const double &distance
238 ) const;
239 /** This function has the exponential feature from the Morse potential.
240 *
241 * @param prefactor prefactor parameter to exp function
242 * @param lambda scale parameter of exp function's argument
243 * @param distance variable of the function
244 * @return
245 */
246 result_t function_smoother(
247 const double &prefactor,
248 const double &lambda,
249 const double &distance
250 ) const;
251
252 /** This function represents \f$ (1 + \alpha^n \eta^n)^{-1/2n} \f$.
253 *
254 * @param alpha prefactor to eta function
255 * @param r_ij distance argument
256 * @param eta result value of eta or zeta
257 * @return \f$ (1 + \alpha^n \eta^n)^{-1/2n} \f$
258 */
259 result_t function_prefactor(
260 const double &alpha,
261 const double &eta
262 ) const;
263
264 result_t
265 function_eta(
266 const argument_t &r_ij
267 ) const;
268
269 result_t
270 function_zeta(
271 const argument_t &r_ij
272 ) const;
273
274 result_t
275 function_theta(
276 const double &r_ij,
277 const double &r_ik,
278 const double &r_jk
279 ) const;
280
281 result_t
282 function_angle(
283 const double &r_ij,
284 const double &r_ik,
285 const double &r_jk
286 ) const;
287
288private:
289 result_t
290 function_derivative_c(
291 const argument_t &r_ij
292 ) const;
293
294 result_t
295 function_derivative_d(
296 const argument_t &r_ij
297 ) const;
298
299 result_t
300 function_derivative_h(
301 const argument_t &r_ij
302 ) const;
303
304public:
305 enum parameter_enum_t {
306 A,
307 B,
308 lambda,
309 mu,
310 beta,
311 n,
312 c,
313 d,
314 h,
315// R,
316// S,
317// lambda3,
318// alpha,
319// chi,
320// omega,
321 MAXPARAMS
322 };
323
324private:
325 //!> parameter vector with parameters as in enum parameter_enum_t
326 parameters_t params;
327
328public:
329 // some internal parameters which are fixed
330 const double R;
331 const double S;
332 const double lambda3;
333 const double alpha;
334 const double chi;
335 const double omega;
336
337public:
338 /** Setter for parameters as required by FunctionModel interface.
339 *
340 * \param _params given set of parameters
341 */
342 void setParameters(const parameters_t &_params);
343
344 /** Getter for parameters as required by FunctionModel interface.
345 *
346 * \return set of parameters
347 */
348 parameters_t getParameters() const
349 {
350 return params;
351 }
352
353 /** Sets the parameter randomly within the sensible range of each parameter.
354 *
355 * \param data container with training data for guesstimating range
356 */
357 void setParametersToRandomInitialValues(const TrainingData &data);
358
359 /** Getter for the number of parameters of this model function.
360 *
361 * \return number of parameters
362 */
363 size_t getParameterDimension() const
364 {
365 return MAXPARAMS;
366 }
367
368private:
369 //!> bound function that obtains the triples for the internal coordinationb summation.
370 boost::function< std::vector< arguments_t >(const argument_t &, const double)> triplefunction;
371
372 //!> static definitions of the parameter name for this potential
373 static const ParameterNames_t ParameterNames;
374
375 //!> static token of this potential type
376 static const std::string potential_token;
377
378 //!> internal coordinator object for converting arguments_t
379 static Coordinator::ptr coordinator;
380
381 //!> binding model for this potential
382 const BindingModel bindingmodel;
383};
384
385
386#endif /* MANYBODYPOTENTIAL_TERSOFF_HPP_ */
Note: See TracBrowser for help on using the repository browser.