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Used for solving minimization problems subject to constraints. Refs #7492
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Code/Mantid/Framework/CurveFitting/inc/MantidCurveFitting/AugmentedLagrangianOptimizer.h
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| #ifndef MANTID_CURVEFITTING_AUGMENTEDLAGRANGIANOPTIMIZER_H_ | ||
| #define MANTID_CURVEFITTING_AUGMENTEDLAGRANGIANOPTIMIZER_H_ | ||
| /** | ||
| Copyright © 2013 ISIS Rutherford Appleton Laboratory & NScD Oak Ridge National Laboratory | ||
| This file is part of Mantid. | ||
| Mantid is free software; you can redistribute it and/or modify | ||
| it under the terms of the GNU General Public License as published by | ||
| the Free Software Foundation; either version 3 of the License, or | ||
| (at your option) any later version. | ||
| Mantid is distributed in the hope that it will be useful, | ||
| but WITHOUT ANY WARRANTY; without even the implied warranty of | ||
| MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the | ||
| GNU General Public License for more details. | ||
| You should have received a copy of the GNU General Public License | ||
| along with this program. If not, see <http://www.gnu.org/licenses/>. | ||
| File change history is stored at: <https://github.com/mantidproject/mantid> | ||
| Code Documentation is available at: <http://doxygen.mantidproject.org> | ||
| */ | ||
| #include "MantidCurveFitting/DllConfig.h" | ||
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| #include "MantidKernel/ClassMacros.h" | ||
| #include "MantidKernel/Matrix.h" | ||
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| namespace Mantid | ||
| { | ||
| namespace CurveFitting | ||
| { | ||
| /** | ||
| * The results of the optimization | ||
| */ | ||
| enum OptimizerResult | ||
| { | ||
| Failure = -1, | ||
| Success = 1, | ||
| FTolReached = 2, | ||
| XTolReached = 3 | ||
| }; | ||
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| /// Non-templated wrapper for objective function object to allow it to be stored | ||
| /// without templating the class | ||
| class FunctionWrapper | ||
| { | ||
| private: | ||
| class BaseHolder | ||
| { | ||
| public: | ||
| virtual ~BaseHolder() {}; | ||
| virtual double eval(const std::vector<double> & x) const = 0; | ||
| }; | ||
| template<typename T> | ||
| class TypeHolder : public BaseHolder | ||
| { | ||
| public: | ||
| TypeHolder(const T & func) : func(func) {} | ||
| double eval(const std::vector<double> & x) const { return func.eval(x); } | ||
| /// The actual function supplied by the user | ||
| T func; | ||
| }; | ||
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| public: | ||
| /// Construct | ||
| template<typename T> | ||
| FunctionWrapper(const T & func) : m_funcHolder(new TypeHolder<T>(func)) {} | ||
| ~FunctionWrapper() | ||
| { | ||
| delete m_funcHolder; | ||
| } | ||
| /** | ||
| * Calls user supplied function | ||
| * @param x - The current pt | ||
| * @returns The value of the function | ||
| */ | ||
| inline double eval(const std::vector<double> & x) const { return m_funcHolder->eval(x); } | ||
| /// Templated holder | ||
| BaseHolder *m_funcHolder; | ||
| }; | ||
|
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| //--------------------------------------------------------------------------------------------- | ||
| // Forward declaration | ||
| //--------------------------------------------------------------------------------------------- | ||
| class UnconstrainedCostFunction; | ||
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| /** | ||
| Implements the Augmented Lagrangian optimization method of Birgin & Martinez. See | ||
| E. G. Birgin and J. M. Martiinez, "Improving ultimate convergence of an augmented Lagrangian method,", | ||
| Optimization Methods and Software vol. 23, no. 2, p. 177-195 (2008). | ||
| If the objective function is written as | ||
| \f[ | ||
| Cx = d | ||
| \f] | ||
| where \f$x\f$ are the parameters, then the routine attempts to minimize | ||
| \f[ | ||
| \frac{1}{2}||Cx - d||^2 | ||
| \f] | ||
| where \f$ ||f|| \f$ denotes the 2nd-norm of \f$f\f$. It possible to specify an optional set of constraints | ||
| such that the function is minimized subject to | ||
| \f[ | ||
| Ax \geq 0 | ||
| \f] | ||
| and | ||
| \f[ | ||
| A_{eq} x = 0 | ||
| \f] | ||
| Copyright © 2013 ISIS Rutherford Appleton Laboratory & NScD Oak Ridge National Laboratory | ||
| This file is part of Mantid. | ||
| Mantid is free software; you can redistribute it and/or modify | ||
| it under the terms of the GNU General Public License as published by | ||
| the Free Software Foundation; either version 3 of the License, or | ||
| (at your option) any later version. | ||
| Mantid is distributed in the hope that it will be useful, | ||
| but WITHOUT ANY WARRANTY; without even the implied warranty of | ||
| MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the | ||
| GNU General Public License for more details. | ||
| You should have received a copy of the GNU General Public License | ||
| along with this program. If not, see <http://www.gnu.org/licenses/>. | ||
| File change history is stored at: <https://github.com/mantidproject/mantid> | ||
| Code Documentation is available at: <http://doxygen.mantidproject.org> | ||
| */ | ||
| class MANTID_CURVEFITTING_DLL AugmentedLagrangianOptimizer | ||
| { | ||
| public: | ||
| /** | ||
| * Constructor | ||
| * @param nparams The number of parameters in the problem | ||
| * @param objfunc An object whose type has a member named eval with the following signature | ||
| * "double eval(const std::vector<double> &) const" to return the value of the objective function | ||
| * at a given pt | ||
| */ | ||
| template <typename T> | ||
| AugmentedLagrangianOptimizer(const size_t nparams, const T & objfunc) | ||
| : m_userfunc(FunctionWrapper(objfunc)), m_nparams(nparams), m_neq(0), | ||
| m_eq(), m_nineq(0), m_ineq(), m_maxIter(500) | ||
| { | ||
| } | ||
|
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| /** | ||
| * Constructor with constraints | ||
| * @param nparams The number of parameters in the problem | ||
| * @param objfunc An object whose type has a member named eval with the following signature | ||
| * "double eval(const std::vector<double> &)" to return the value of the objective function | ||
| * at a given pt | ||
| * @param equality A matrix of coefficients, \f$A_{eq}\f$ such that in the final solution \f$A_{eq} x = 0\f$ | ||
| * @param inequality A matrix of coefficients, \f$A\f$ such that in the final solution \f$A_{eq} x\geq 0\f$ | ||
| */ | ||
| template <typename T> | ||
| AugmentedLagrangianOptimizer(const size_t nparams, const T & objfunc, | ||
| const Kernel::DblMatrix & equality, const Kernel::DblMatrix & inequality) | ||
| : m_userfunc(FunctionWrapper(objfunc)), | ||
| m_nparams(nparams), m_neq(equality.numRows()), m_eq(equality), m_nineq(inequality.numRows()), | ||
| m_ineq(inequality), m_maxIter(500) | ||
| { | ||
| checkConstraints(equality, inequality); | ||
| } | ||
|
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| /// @returns The number of parameters under minimization | ||
| inline size_t numParameters() const { return m_nparams; } | ||
| /// @returns The number of equality constraints | ||
| inline size_t numEqualityConstraints() const { return m_neq; } | ||
| /// @returns The number of inequality constraints | ||
| inline size_t numInequalityConstraints() const { return m_nineq; } | ||
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| /** | ||
| * Override the maximum number of iterations (Default = 500) | ||
| * @param maxIter Maximum value for the main minimizer loop | ||
| */ | ||
| inline void setMaxIterations(const int maxIter) { m_maxIter = maxIter; } | ||
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| /// Perform the minimization | ||
| void minimize(std::vector<double> & xv) const; | ||
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| private: | ||
| DISABLE_DEFAULT_CONSTRUCT(AugmentedLagrangianOptimizer); | ||
| DISABLE_COPY_AND_ASSIGN(AugmentedLagrangianOptimizer); | ||
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| friend class UnconstrainedCostFunction; | ||
| /// Using gradient optimizer to perform limited optimization of current set | ||
| void unconstrainedOptimization(const std::vector<double> & lambda, const std::vector<double> & mu, | ||
| const double rho, std::vector<double> & xcur) const; | ||
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| /// Sanity check for constraint inputs | ||
| void checkConstraints(const Kernel::DblMatrix & equality, const Kernel::DblMatrix & inequality); | ||
|
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| /// User-defined function | ||
| FunctionWrapper m_userfunc; | ||
| /// Number of parameters under minimization | ||
| const size_t m_nparams; | ||
| /// Number of equality constraints | ||
| const size_t m_neq; | ||
| /// Defines the equality constraints | ||
| Kernel::DblMatrix m_eq; | ||
| /// Number of inequality constraints | ||
| const size_t m_nineq; | ||
| /// Defines the inequality constraints | ||
| Kernel::DblMatrix m_ineq; | ||
| /// Maximum number of iterations | ||
| int m_maxIter; | ||
| }; | ||
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| } // namespace CurveFitting | ||
| } // namespace Mantid | ||
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| #endif /* MANTID_CURVEFITTING_AUGMENTEDLAGRANGIANOPTIMIZER_H_ */ |
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