Diff of /trunk/gadget/optinfo.h

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	revision 1, Mon Feb 10 17:09:07 2014 UTC	revision 15, Tue Sep 1 19:14:33 2015 UTC
#	Line 5	Line 5
5	#include "doublematrix.h"	#include "doublematrix.h"
6	#include "doublevector.h"	#include "doublevector.h"
7	#include "intvector.h"	#include "intvector.h"
8		#include "seq_optimize_template.h"
9
10	enum OptType { OPTHOOKE = 1, OPTSIMANN, OPTBFGS };	enum OptType { OPTHOOKE = 1, OPTSIMANN, OPTBFGS };
11
#	Line 41	Line 42
42	*/	*/
43	virtual void OptimiseLikelihood() {};	virtual void OptimiseLikelihood() {};
44	/**	/**
45		* \brief This is the function used to call the optimisation algorithms parallelized with OpenMP of the reproducible version
46		*/
47		virtual void OptimiseLikelihoodOMP() {};
48		/**
49		* \brief This function set the seeds used in SA
50		* \param val array of unsigned int with the seeds
51		*/
52		void setSeed(unsigned* val) {seed = val[0]; seedM =  val[1]; seedP = val[2];};
53		/**
54	* \brief This will return the type of optimisation class	* \brief This will return the type of optimisation class
55	* \return type	* \return type
56	*/	*/
#	Line 62	Line 72
72	* \brief This denotes what type of optimisation class has been created	* \brief This denotes what type of optimisation class has been created
73	*/	*/
74	OptType type;	OptType type;
75		/**
76		* \brief This is the seed used for the calculation of the new value of the parameters
77		*/
78		unsigned seed;
79		/**
80		* \brief This is the seed used for the acceptance of the metropolis
81		*/
82		unsigned seedM;
83		/**
84		* \brief This is the seed used to change the order of the parameters
85		*/
86		unsigned seedP;
87	};	};
88
89	/**	/**
#	Line 99	Line 121
121	* \brief This is the function that will calculate the likelihood score using the Hooke & Jeeves optimiser	* \brief This is the function that will calculate the likelihood score using the Hooke & Jeeves optimiser
122	*/	*/
123	virtual void OptimiseLikelihood();	virtual void OptimiseLikelihood();
124		#ifdef SPECULATIVE
125		/**
126		* \brief This is the function that will calculate the likelihood score using the Hooke & Jeeves optimiser parallelized with the reproducible version implemented OpenMP
127		*/
128		virtual void OptimiseLikelihoodOMP();
129		#endif
130	private:	private:
131	/**	/**
132	* \brief This function will calculate the best point that can be found close to the current point	* \brief This function will calculate the best point that can be found close to the current point
#	Line 110	Line 138
138	*/	*/
139	double bestNearby(DoubleVector& delta, DoubleVector& point, double prevbest, IntVector& param);	double bestNearby(DoubleVector& delta, DoubleVector& point, double prevbest, IntVector& param);
140	/**	/**
141		* \brief This function implemented the reproducible version with OpenMP will calculate the best point that can be found close to the current point
142		* \param delta is the DoubleVector of the steps to take when looking for the best point
143		* \param point is the DoubleVector that will contain the parameters corresponding to the best function value found from the search
144		* \param prevbest is the current best point value
145		* \param param is the IntVector containing the order that the parameters should be searched in
146		* \return the best function value found from the search
147		*/
148		double bestNearbyRepro(DoubleVector& delta, DoubleVector& point, double prevbest, IntVector& param);
149		/**
150		* \brief This function implemented the speculative version with OpenMP will calculate the best point that can be found close to the current point
151		* \param delta is the DoubleVector of the steps to take when looking for the best point
152		* \param point is the DoubleVector that will contain the parameters corresponding to the best function value found from the search
153		* \param prevbest is the current best point value
154		* \param param is the IntVector containing the order that the parameters should be searched in
155		* \return the best function value found from the search
156		*/
157		double bestNearbySpec(DoubleVector& delta, DoubleVector& point, double prevbest, IntVector& param);
158		/**
159	* \brief This is the maximum number of iterations for the Hooke & Jeeves optimisation	* \brief This is the maximum number of iterations for the Hooke & Jeeves optimisation
160	*/	*/
161	int hookeiter;	int hookeiter;
#	Line 165	Line 211
211	* \brief This is the function that will calculate the likelihood score using the Simulated Annealing optimiser	* \brief This is the function that will calculate the likelihood score using the Simulated Annealing optimiser
212	*/	*/
213	virtual void OptimiseLikelihood();	virtual void OptimiseLikelihood();
214		#ifdef SPECULATIVE
215		/**
216		* \brief This is the function that will calculate the likelihood score using the Simulated Annealing optimiser parallelized with the reproducible version implemented OpenMP
217		*/
218		virtual void OptimiseLikelihoodOMP();
219		#endif
220		/**
221		* \brief This function calculate a new valor for the parameter l
222		* \param nvars the number of variables to be optimised
223		* \param l the parameter to change
224		* \param param IntVector with the order of the parameters
225		* \param trialx DoubleVector that storage the values of the parameters to evaluate during this iteration
226		* \param x DoubleVector that storage the best values of the parameters
227		* \param lowerb DoubleVector with the lower bounds of the variables to be optimised
228		* \param upperb DoubleVector with the upper bounds of the variables to be optimised
229		* \param vm DoubleVector with the value for the maximum step length for each parameter
230		*/
231		virtual void newValue(int nvars, int l, IntVector& param, DoubleVector& trialx,
232		DoubleVector& x, DoubleVector& lowerb, DoubleVector& upperb, DoubleVector& vm);
233	private:	private:
234	/**	/**
235	* \brief This is the temperature reduction factor	* \brief This is the temperature reduction factor
#	Line 250	Line 315
315	* \brief This is the function that will calculate the likelihood score using the BFGS optimiser	* \brief This is the function that will calculate the likelihood score using the BFGS optimiser
316	*/	*/
317	virtual void OptimiseLikelihood();	virtual void OptimiseLikelihood();
318		#ifdef SPECULATIVE
319		/**
320		* \brief This function call the sequential function. BFGS isn't implemented with OpenMP
321		*/
322		virtual void OptimiseLikelihoodOMP();
323		#endif
324	private:	private:
325	/**	/**
326	* \brief This function will numerically calculate the gradient of the function at the current point	* \brief This function will numerically calculate the gradient of the function at the current point

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