problem.hpp source code [quantlib/ql/math/optimization/problem.hpp]

1	/ -- mode: c++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -- /
2
3	/*
4	Copyright (C) 2007 Ferdinando Ametrano
5	Copyright (C) 2007 François du Vignaud
6	Copyright (C) 2001, 2002, 2003 Nicolas Di Césaré
7
8	This file is part of QuantLib, a free-software/open-source library
9	for financial quantitative analysts and developers - http://quantlib.org/
10
11	QuantLib is free software: you can redistribute it and/or modify it
12	under the terms of the QuantLib license. You should have received a
13	copy of the license along with this program; if not, please email
14	<quantlib-dev@lists.sf.net>. The license is also available online at
15	<http://quantlib.org/license.shtml>.
16
17	This program is distributed in the hope that it will be useful, but WITHOUT
18	ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
19	FOR A PARTICULAR PURPOSE. See the license for more details.
20	*/
21
22	/! \file problem.hpp*
23	\brief Abstract optimization problem class
24	*/
25
26	#ifndef quantlib_optimization_problem_h
27	#define quantlib_optimization_problem_h
28
29	#include <ql/math/optimization/constraint.hpp>
30	#include <ql/math/optimization/costfunction.hpp>
31	#include <ql/math/optimization/method.hpp>
32	#include <utility>
33
34	namespace QuantLib {
35
36	//! Constrained optimization problem
37	/! \warning The passed CostFunction and Constraint instances are*
38	stored by reference. The user of this class must
39	make sure that they are not destroyed before the
40	Problem instance.
41	*/
42	class Problem {
43	public:
44	//! default constructor
45	Problem(CostFunction& costFunction, Constraint& constraint, Array initialValue = Array ())
46	: costFunction_(costFunction), constraint_(constraint),
47	currentValue_(std::move(initialValue)) {
48	QL_REQUIRE(!constraint.empty(), "empty constraint given");
49	}
50
51	/! \warning it does not reset the current minumum to any initial value*
52	*/
53	void reset();
54
55	//! call cost function computation and increment evaluation counter
56	Real value(const Array& x);
57
58	//! call cost values computation and increment evaluation counter
59	Array values(const Array& x);
60
61	//! call cost function gradient computation and increment
62	// evaluation counter
63	void gradient(Array& grad_f,
64	const Array& x);
65
66	//! call cost function computation and it gradient
67	Real valueAndGradient(Array& grad_f,
68	const Array& x);
69
70	//! Constraint
71	Constraint& constraint() const { return constraint_; }
72
73	//! Cost function
74	CostFunction& costFunction() const { return costFunction_; }
75
76	void setCurrentValue(const Array& currentValue) {
77	currentValue_=currentValue;
78	}
79
80	//! current value of the local minimum
81	const Array& currentValue() const { return currentValue_; }
82
83	void setFunctionValue(Real functionValue) {
84	functionValue_=functionValue;
85	}
86
87	//! value of cost function
88	Real functionValue() const { return functionValue_; }
89
90	void setGradientNormValue(Real squaredNorm) {
91	squaredNorm_=squaredNorm;
92	}
93	//! value of cost function gradient norm
94	Real gradientNormValue() const { return squaredNorm_; }
95
96	//! number of evaluation of cost function
97	Integer functionEvaluation() const { return functionEvaluation_; }
98
99	//! number of evaluation of cost function gradient
100	Integer gradientEvaluation() const { return gradientEvaluation_; }
101
102	protected:
103	//! Unconstrained cost function
104	CostFunction& costFunction_;
105	//! Constraint
106	Constraint& constraint_;
107	//! current value of the local minimum
108	Array currentValue_;
109	//! function and gradient norm values at the currentValue_ (i.e. the last step)
110	Real functionValue_, squaredNorm_;
111	//! number of evaluation of cost function and its gradient
112	Integer functionEvaluation_, gradientEvaluation_;
113	};
114
115	// inline definitions
116	inline Real Problem::value(const Array& x) {
117	++functionEvaluation_;
118	return costFunction_.value(x);
119	}
120
121	inline Array Problem::values(const Array& x) {
122	++functionEvaluation_;
123	return costFunction_.values(x);
124	}
125
126	inline void Problem::gradient(Array& grad_f,
127	const Array& x) {
128	++gradientEvaluation_;
129	costFunction_.gradient(grad&: grad_f, x);
130	}
131
132	inline Real Problem::valueAndGradient(Array& grad_f,
133	const Array& x) {
134	++functionEvaluation_;
135	++gradientEvaluation_;
136	return costFunction_.valueAndGradient(grad&: grad_f, x);
137	}
138
139	inline void Problem::reset() {
140	functionEvaluation_ = gradientEvaluation_ = `0`;
141	functionValue_ = squaredNorm_ = Null<Real>();
142	}
143
144	}
145
146	#endif
147

source code of quantlib/ql/math/optimization/problem.hpp