Migration from SVN

branches/rc2.0/eo/src/es/CMAState.h

@@ -1,78 +0,0 @@
-/*
- * C++ification of Nikolaus Hansen's original C-source code for the
- * CMA-ES.
- *
- * Copyright (C) 1996, 2003, Nikolaus Hansen
- *           (C) 2005, Maarten Keijzer
- *
- * License: LGPL (see source file)
- *
- */
-
-#ifndef CMASTATE_H_
-#define CMASTATE_H_
-
-#include <vector>
-#include <valarray>
-
-namespace eo {
-
-
-class CMAStateImpl;
-class CMAParams;
-class CMAState {
-
-    CMAStateImpl* pimpl; /* pointer to implementation, hidden in source file */
-
-    public:
-
-    CMAState(const CMAParams&, const std::vector<double>& initial_point, const double initial_sigma = 1.0);
-    ~CMAState();
-    CMAState(const CMAState&);
-    CMAState& operator=(const CMAState&);
-
-    /**
-     *	sample a vector from the distribution
-     *
-     *   If the sample is not to your liking (i.e., not within bounds)
-     *   you can do one of two things:
-     *
-     *   a) Call sample again
-     *   b) multiply the entire vector with a number between -1 and 1
-     *
-     *   Do not modify the sample in any other way as this will invalidate the
-     *   internal consistency of the system.
-     *
-     *   A final approach is to copy the sample and modify the copy externally (in the evaluation function)
-     *   and possibly add a penalty depending on the size of the modification.
-     *
-     */
-    void sample(std::vector<double>& v) const;
-
-    /**
-     * Reestimate covariance matrix and other internal parameters
-     * Does NOT update the eigen system (call that seperately)
-     *
-     * Needs a population of mu individuals, sorted on fitness, plus
-     *
-     * muBest:   the best fitness in the population
-     * muWorst:  the worst fitness in the population
-     */
-
-    void reestimate(const std::vector<const std::vector<double>* >& sorted_population, double muBest, double muWorst);
-
-    /**
-     * call this function after reestimate in order to update the eigen system
-     * It is a seperate call to allow the user to periodically skip this expensive step
-     *
-     * max_iters = 0 implies 30 * N iterations
-     *
-     * If after max_tries still no numerically sound eigen system is constructed,
-     * the function returns false
-     */
-    bool updateEigenSystem(unsigned max_tries = 1, unsigned max_iters = 0);
-};
-
-} // namespace eo
-
-#endif