[DB] Importing KNNL library
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emeric
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/*
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* Copyright (c) 2006, Seweryn Habdank-Wojewodzki
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* Copyright (c) 2006, Janusz Rybarski
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*
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* All rights reserved.
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*
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* Redistribution and use in source and binary forms,
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* with or without modification, are permitted provided
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* that the following conditions are met:
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*
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* Redistributions of source code must retain the above
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* copyright notice, this list of conditions and the
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* following disclaimer.
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*
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* Redistributions in binary form must reproduce the
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* above copyright notice, this list of conditions
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* and the following disclaimer in the documentation
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* and/or other materials provided with the distribution.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS
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* AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED
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* WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
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* WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
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* A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL
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* THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY
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* DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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* CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF
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* USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
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* HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
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* WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY
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* WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED
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* OF THE POSSIBILITY OF SUCH DAMAGE.
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*/
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/*
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* e-mail: habdank AT gmail DOT com
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* e-mail: janusz.rybarski AT gmail DOT com
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*
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* File created: Wed 10 May 2006 11:16:03 CEST
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* Last modified: Wed 08 Aug 2007 18:21:33 CEST
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*/
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#ifndef FUNCTORS_HPP_INCLUDED
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#define FUNCTORS_HPP_INCLUDED
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#include <cmath>
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#include "basic_activation_function.hpp"
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#include "operators.hpp"
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#include "training_functional.hpp"
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/**
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* \file functors.hpp
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* \brief File contains template class Basic_function and some other classes derived form that one.
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* \ingroup neural_net
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*/
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namespace neural_net
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{
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/**
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* \addtogroup neural_net
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*/
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/*\@{*/
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/**
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* \class Basic_function
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* \brief Basic class for defining functions.
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* \param Value_type is a type of values.
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*/
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template < typename Value_type >
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struct Basic_function
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{
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typedef Value_type value_type;
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};
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/**
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* \class Gauss_function
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* \brief Functor that compute Gauss hat function.
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* \param Value_type is a type of values.
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* \param Scalar_type is a type of scaling factor which multiplies values.
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* \param Exponent_type is a type of exponential factor.
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* \f[
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* y = e ^{-\frac{1}{2}\left (\frac{v}{\sigma}\right)^p}
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* \f]
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*/
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template
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<
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typename Value_type,
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typename Scalar_type,
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typename Exponent_type
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>
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class Gauss_function
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: public Basic_function < Value_type >,
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public Basic_activation_function
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<
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typename ::operators::Max_type < Scalar_type, Exponent_type >::type,
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Value_type,
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typename ::operators::Max_type
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<
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typename ::operators::Max_type
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<
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typename ::operators::Max_type < Scalar_type, Exponent_type >::type,
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Value_type
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>::type,
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double
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>::type
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>
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{
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public:
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typedef Scalar_type scalar_type;
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typedef Exponent_type exponent_type;
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typedef Value_type value_type;
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typedef typename ::operators::Max_type
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<
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typename ::operators::Max_type
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<
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typename ::operators::Max_type < Scalar_type, Exponent_type >::type,
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Value_type
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>::type,
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double
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>::type result_type;
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/** Sigma coafficient in the function. */
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Scalar_type sigma;
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/** Exponential factor. */
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Exponent_type exponent;
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/**
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* Constructor.
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* \param sigma_ is sigma coefficient in Gauss hat function.
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* \param exp_ is exponential factor in Gauss hat function.
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*/
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Gauss_function ( Scalar_type const & sigma_, Exponent_type const & exp_ )
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: sigma ( sigma_ ), exponent ( exp_ )
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{}
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/**
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* Result of the functor.
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* \param value is a value.
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* \return calcutaled result.
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* \f[
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* y = e ^{-\frac{1}{2}\left (\frac{v}{\sigma}\right)^p}
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* \f]
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* where: v is value.
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*/
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result_type operator() ( Value_type const & value ) const
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{
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::operators::power < result_type, Exponent_type > power_v;
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// calculate result
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return
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(
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::std::exp
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(
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- ::operators::inverse ( static_cast < Scalar_type > ( 2 ) )
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* (power_v)
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(
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::operators::inverse ( sigma ) * value,
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exponent
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)
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)
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);
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}
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/** Copy constructor. */
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template
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<
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typename Value_type_2,
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typename Scalar_type_2,
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typename Exponent_type_2
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>
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Gauss_function
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(
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Gauss_function
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<
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Value_type_2,
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Scalar_type_2,
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Exponent_type_2
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>
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const & gauss_function
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)
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: sigma ( gauss_function.sigma ), exponent ( gauss_function.exponent )
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{}
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};
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/**
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* \class Cauchy_function
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* \brief Functor that computes Cauchy hat function.
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* \param Value_type is a type of value.
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* \param Scalar_type is a type of scalar which will multiplies values.
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* \param Power_type is a type of exponential factor.
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* \f[
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* y=\frac{1}{1 + (\frac{x}{\sigma})^p}
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* \f]
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*/
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template
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<
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typename Value_type,
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typename Scalar_type,
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typename Exponent_type
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>
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class Cauchy_function
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: public Basic_function < Value_type >,
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public Basic_activation_function
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<
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typename ::operators::Max_type < Scalar_type, Exponent_type >::type,
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Value_type,
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typename ::operators::Max_type
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<
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typename ::operators::Max_type < Scalar_type, Exponent_type >::type,
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Value_type
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>::type
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>
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{
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public:
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typedef Scalar_type scalar_type;
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typedef Exponent_type exponent_type;
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typedef Value_type value_type;
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typedef typename ::operators::Max_type
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<
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typename ::operators::Max_type < Scalar_type, Exponent_type >::type,
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Value_type
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>::type result_type;
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/** Sigma scaling coefficient. */
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Scalar_type sigma;
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/** Exponential factor. */
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Exponent_type exponent;
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/**
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* Constuctor.
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* \param sigma_ is scailing coefficient.
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* \param exp_ is exponential factor.
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*/
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Cauchy_function ( Scalar_type const & sigma_, Exponent_type const & exp_ )
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: sigma ( sigma_ ), exponent ( exp_ )
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{}
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/**
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* Function calculates values of the Cauchy hat function.
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* \param value is a value.
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* \return value of the function.
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* \f[
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* y=\frac{1}{1 + (\frac{x}{\sigma})^p}
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* \f]
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* where: x is value.
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*/
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result_type operator() ( Value_type const & value ) const
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{
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::operators::power < result_type, Exponent_type > power_v;
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// calculate result
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return
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(
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::operators::inverse
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(
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(power_v)
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(
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::operators::inverse ( sigma ) * value,
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exponent
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) + 1
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)
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);
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}
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/**constructor. */
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template
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<
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typename Value_type_2,
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typename Scalar_type_2,
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typename Exponent_type_2
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>
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Cauchy_function
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(
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Cauchy_function
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<
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Value_type_2,
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Scalar_type_2,
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Exponent_type_2
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>
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const & cauchy_function
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)
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: sigma ( cauchy_function.sigma ), exponent ( cauchy_function.exponent )
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{}
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};
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/**
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* \class Constant_function
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* \brief Functor that computes constant function.
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* \param Value_type is a type of value.
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* \param Scalar_type is a type of constant value.
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* \f[
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* y=c
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* \f]
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*/
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template
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<
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typename Value_type,
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typename Scalar_type
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>
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class Constant_function
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: public Basic_function < Value_type >
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{
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public:
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typedef Scalar_type scalar_type;
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typedef Scalar_type result_type;
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/** Sigma constant value, but not const. */
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Scalar_type sigma;
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/**
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* Constuctor.
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* \param sigma_ is constant value.
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*/
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Constant_function ( const Scalar_type & sigma_ )
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: sigma ( sigma_ )
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{}
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/** Copy constructor. */
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template
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<
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typename Value_type_2,
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typename Scalar_type_2
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>
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Constant_function
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(
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Constant_function
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<
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Value_type_2,
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Scalar_type_2
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>
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const & constant_function
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)
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: sigma ( constant_function.sigma )
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{}
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/**
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* Constant function.
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* \param value is a value.
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* \return constant value.
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* \f[
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* y=c
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* \f]
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* where: x is value.
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*/
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result_type operator() ( Value_type const & //value
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) const
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{
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// result
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return ( sigma );
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}
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};
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/*\@}*/
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} // namespace neural_net
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#endif // FUNCTORS_HPP_INCLUDED
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