openModeller  Version 1.5.0
Public Member Functions | Protected Member Functions | Private Member Functions | Private Attributes | List of all members
MinimumDistance Class Reference

#include <minimum_distance.hh>

Inheritance diagram for MinimumDistance:
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Collaboration diagram for MinimumDistance:
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Public Member Functions

 MinimumDistance ()
 
virtual ~MinimumDistance ()
 
int initialize ()
 
int iterate ()
 
int done () const
 
Scalar getValue (const Sample &x) const
 
int getConvergence (Scalar *val)
 
- Public Member Functions inherited from AlgorithmImpl
 AlgorithmImpl (AlgMetadata const *metadata)
 
virtual ~AlgorithmImpl ()
 
void setParameters (int nparam, AlgParameter const *param)
 
void setParameters (const ParamSetType &)
 
std::string const getID () const
 
AlgMetadata const * getMetadata () const
 
AlgorithmPtr getFreshCopy ()
 
virtual int supportsModelProjection () const
 
Model createModel (const SamplerPtr &samp, CallbackWrapper *func=0)
 
void setSampler (const SamplerPtr &samp)
 
virtual int finalize ()
 
virtual int getConvergence (Scalar *const val) const
 
virtual float getProgress () const
 
virtual int needNormalization ()
 
Normalizer * getNormalizer () const
 
void setNormalization (const SamplerPtr &samp) const
 
void setNormalization (const EnvironmentPtr &env) const
 
virtual Model getModel () const
 
ConfigurationPtr getConfiguration () const
 
void setConfiguration (const ConstConfigurationPtr &)
 
- Public Member Functions inherited from Configurable
virtual ~Configurable ()
 

Protected Member Functions

virtual void _getConfiguration (ConfigurationPtr &) const
 
virtual void _setConfiguration (const ConstConfigurationPtr &)
 
- Protected Member Functions inherited from AlgorithmImpl
int dimDomain ()
 
int getParameter (std::string const &name, std::string *value)
 
int getParameter (std::string const &name, double *value)
 
int getParameter (std::string const &name, float *value)
 
int getParameter (std::string const &name, int *value)
 

Private Member Functions

Scalar findDist (const Sample &x, const Sample &pnt) const
 

Private Attributes

bool _done
 
Scalar _dist
 Parameter for MaxDistance. More...
 
bool _hasCategorical
 
int _numLayers
 
Sample _isCategorical
 
std::vector< Sample > _envPoints
 

Additional Inherited Members

- Public Types inherited from AlgorithmImpl
typedef std::map< icstring,
std::string > 		ParamSetType
 
- Protected Attributes inherited from AlgorithmImpl
SamplerPtr _samp
 
Normalizer * _normalizerPtr
 
ParamSetType _param
 

Detailed Description

Declaration of Minimum Distance algorithm.

Author
Mauro E S Muņoz (mauro.nosp@m.@cri.nosp@m.a.org.nosp@m..br)
Date
2003-09-20
Id:
minimum_distance.hh 3382 2007-07-19 19:09:18Z rdg

LICENSE INFORMATION

Copyright(c) 2003 by CRIA - Centro de Referencia em Informacao Ambiental

http://www.cria.org.br

This program 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 2 of the License, or (at your option) any later version.

This program 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:

http://www.gnu.org/copyleft/gpl.html Algorithm to generate models based on the cartesian distance from the closest occurrence point.

Definition at line 40 of file minimum_distance.hh.

Constructor & Destructor Documentation

MinimumDistance::MinimumDistance ( )

Occurrences within this distance will be considered the same one.

Definition at line 131 of file minimum_distance.cpp.

References AlgorithmImpl::_normalizerPtr.

MinimumDistance::~MinimumDistance ( )
virtual

Definition at line 145 of file minimum_distance.cpp.

Member Function Documentation

void MinimumDistance::_getConfiguration ( ConfigurationPtr &  config) const
protectedvirtual

Reimplemented from AlgorithmImpl.

Definition at line 288 of file minimum_distance.cpp.

References _dist, _done, _envPoints, and _isCategorical.

void MinimumDistance::_setConfiguration ( const ConstConfigurationPtr &  config)
protectedvirtual

Reimplemented from AlgorithmImpl.

Definition at line 312 of file minimum_distance.cpp.

References _dist, _done, _envPoints, _hasCategorical, _isCategorical, _numLayers, and Sample::size().

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int MinimumDistance::done ( ) const
virtual

Return != 0 if algorithm finished.

Reimplemented from AlgorithmImpl.

Definition at line 219 of file minimum_distance.cpp.

References _done.

Scalar MinimumDistance::findDist ( const Sample &  x,
const Sample &  pnt 
) const
private

Calculate cartesian distance between 'x' and 'pnt', with dimensions equal to dim.

Definition at line 264 of file minimum_distance.cpp.

References _hasCategorical, _isCategorical, _numLayers, and Sample::norm().

Referenced by getValue().

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int MinimumDistance::getConvergence ( Scalar *  val)

Definition at line 254 of file minimum_distance.cpp.

Scalar MinimumDistance::getValue ( const Sample &  x) const
virtual

The algorithm must return the occurrence probability at the given environment conditions.

Parameters
xEnvironmental conditions.
Returns
The occurrence probability in the range [0,1].

Implements AlgorithmImpl.

Definition at line 228 of file minimum_distance.cpp.

References _dist, _envPoints, findDist(), and min().

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int MinimumDistance::initialize ( )
virtual

Initiate a new training.

Implements AlgorithmImpl.

Definition at line 153 of file minimum_distance.cpp.

References _dist, _done, _envPoints, _hasCategorical, _isCategorical, _numLayers, AlgorithmImpl::_samp, Log::error(), AlgorithmImpl::getParameter(), Log::instance(), MAXDIST_ID, Sample::resize(), and Log::warn().

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int MinimumDistance::iterate ( )
virtual

One step further on the training. Return 0 if something wrong happened.

Reimplemented from AlgorithmImpl.

Definition at line 210 of file minimum_distance.cpp.

Member Data Documentation

Scalar MinimumDistance::_dist
private

Parameter for MaxDistance.

Definition at line 68 of file minimum_distance.hh.

Referenced by _getConfiguration(), _setConfiguration(), getValue(), and initialize().

bool MinimumDistance::_done
private

Definition at line 62 of file minimum_distance.hh.

Referenced by _getConfiguration(), _setConfiguration(), done(), and initialize().

std::vector<Sample> MinimumDistance::_envPoints
private

Definition at line 74 of file minimum_distance.hh.

Referenced by _getConfiguration(), _setConfiguration(), getValue(), and initialize().

bool MinimumDistance::_hasCategorical
private

Definition at line 70 of file minimum_distance.hh.

Referenced by _setConfiguration(), findDist(), and initialize().

Sample MinimumDistance::_isCategorical
private

Definition at line 72 of file minimum_distance.hh.

Referenced by _getConfiguration(), _setConfiguration(), findDist(), and initialize().

int MinimumDistance::_numLayers
private

Definition at line 71 of file minimum_distance.hh.

Referenced by _setConfiguration(), findDist(), and initialize().

The documentation for this class was generated from the following files: