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eodev/eo/src/es/eoEsChromInit.h
2010-11-09 11:44:28 +01:00

208 lines
5.7 KiB
C++

//
/* (c) Maarten Keijzer 2000, GeNeura Team, 1998 - EEAAX 1999
This library is free software; you can redistribute it and/or modify it under
the terms of the GNU Lesser General Public License as published by the Free
Software Foundation; either version 2 of the License, or (at your option) any
later version.
This library 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 Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public License along
with this library; if not, write to the Free Software Foundation, Inc., 59
Temple Place, Suite 330, Boston, MA 02111-1307 USA
Contact: http://eodev.sourceforge.net
todos@geneura.ugr.es, http://geneura.ugr.es
Marc.Schoenauer@polytechnique.fr
mak@dhi.dk
*/
#ifndef _eoEsChromInit_H
#define _eoEsChromInit_H
#include <algorithm>
#include <cassert>
#include <cmath>
#include <vector>
#include <es/eoRealInitBounded.h>
#include <es/eoEsSimple.h>
#include <es/eoEsStdev.h>
#include <es/eoEsFull.h>
#ifndef M_PI
#define M_PI 3.1415926535897932384626433832795
#endif
/** Random Es-chromosome initializer (therefore derived from eoInit)
@ingroup Real
@ingroup Initializators
This class can initialize four types of real-valued genotypes thanks
to tempate specialization of private method create:
- eoReal just an eoVector<double>
- eoEsSimple + one self-adapting single sigma for all variables
- eoEsStdev a whole std::vector of self-adapting sigmas
- eoEsFull a full self-adapting correlation matrix
@see eoReal eoEsSimple eoEsStdev eoEsFull eoInit
*/
template <class EOT>
class eoEsChromInit : public eoRealInitBounded<EOT>
{
public:
using eoRealInitBounded<EOT>::size;
using eoRealInitBounded<EOT>::theBounds;
typedef typename EOT::Fitness FitT;
/** Constructor
@param _bounds bounds for uniform initialization
@param _sigma initial value for the stddev
@param _to_scale wether sigma should be multiplied by the range of each variable
added December 2004 - MS (together with the whole comment :-)
*/
eoEsChromInit(eoRealVectorBounds& _bounds, double _sigma = 0.3, bool _to_scale=false)
: eoRealInitBounded<EOT>(_bounds)
{
// a bit of pre-computations, to save time later (even if some are useless)
//
// first, in the case of one unique sigma
// sigma is scaled by the average range (if that means anything!)
if (_to_scale)
{
double scaleUnique = 0;
for (unsigned i=0; i<size(); i++)
scaleUnique += theBounds().range(i);
scaleUnique /= size();
uniqueSigma = _sigma * scaleUnique;
}
else
uniqueSigma = _sigma;
// now the case of a vector of sigmas first allocate space according
// to the size of the bounds (see eoRealInitBounded)
vecSigma.resize(size());
// each sigma is scaled by the range of the corresponding variable
for(unsigned i=0; i<size(); i++)
if(_to_scale)
vecSigma[i] = _sigma * theBounds().range(i);
else
vecSigma[i] = _sigma;
}
/** Constructor
@overload
Specify individual initial sigmas for each variable.
@param _bounds bounds for uniform initialization
@param _vecSigma initial value for the stddev
*/
eoEsChromInit(eoRealVectorBounds& _bounds, const std::vector<double>& _vecSigma)
: eoRealInitBounded<EOT>(_bounds), uniqueSigma(_vecSigma[0]), vecSigma(_vecSigma)
{
assert(_bounds.size() == size());
assert(_vecSigma.size() == size());
}
void operator()(EOT& _eo)
{
eoRealInitBounded<EOT>::operator()(_eo);
create_self_adapt(_eo);
_eo.invalidate();
}
private:
/** Create intializer
No adaptive mutation at all
*/
void create_self_adapt(eoReal<FitT>&)
{}
/** Create intializer
@overload
Adaptive mutation through a unique sigma
*/
void create_self_adapt(eoEsSimple<FitT>& result)
{
// pre-computed in the Ctor
result.stdev = uniqueSigma;
}
/** Create intializer
@overload
Adaptive mutation through a std::vector of sigmas
@todo Should we scale sigmas to the corresponding object variable range?
*/
void create_self_adapt(eoEsStdev<FitT>& result)
{
// pre-computed in the constructor
result.stdevs = vecSigma;
}
/** Create intializer
@overload
Adaptive mutation through a whole correlation matrix
*/
void create_self_adapt(eoEsFull<FitT>& result)
{
// first the stdevs (pre-computed in the Ctor)
result.stdevs = vecSigma;
unsigned int theSize = size();
// nb of rotation angles: N*(N-1)/2 (in general!)
result.correlations.resize(theSize*(theSize - 1) / 2);
for (unsigned i=0; i<result.correlations.size(); ++i)
{
// uniform in [-PI, PI)
result.correlations[i] = rng.uniform(2 * M_PI) - M_PI;
}
}
/** Initial value in case of a unique sigma */
double uniqueSigma;
/** Initial values in case of a vector of sigmas */
std::vector<double> vecSigma;
};
#endif
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