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/*
fuzzylite (R), a fuzzy logic control library in C++.
Copyright (C) 2010-2017 FuzzyLite Limited. All rights reserved.
Author: Juan Rada-Vilela, Ph.D. <jcrada@fuzzylite.com>
This file is part of fuzzylite.
fuzzylite is free software: you can redistribute it and/or modify it under
the terms of the FuzzyLite License included with the software.
You should have received a copy of the FuzzyLite License along with
fuzzylite. If not, see <http://www.fuzzylite.com/license/>.
fuzzylite is a registered trademark of FuzzyLite Limited.
*/
#include "fl/term/GaussianProduct.h"
namespace fl {
GaussianProduct::GaussianProduct(const std::string& name,
scalar meanA, scalar standardDeviationA, scalar meanB, scalar standardDeviationB,
scalar height)
: Term(name, height), _meanA(meanA), _standardDeviationA(standardDeviationA),
_meanB(meanB), _standardDeviationB(standardDeviationB) { }
GaussianProduct::~GaussianProduct() { }
std::string GaussianProduct::className() const {
return "GaussianProduct";
}
Complexity GaussianProduct::complexity() const {
return Complexity().comparison(1 + 2).arithmetic(9 + 9 + 2).function(2);
}
scalar GaussianProduct::membership(scalar x) const {
if (Op::isNaN(x)) return fl::nan;
scalar a = 1.0, b = 1.0;
if (Op::isLt(x, _meanA)) {
a = std::exp((-(x - _meanA) * (x - _meanA)) /
(2.0 * _standardDeviationA * _standardDeviationA));
}
if (Op::isGt(x, _meanB)) {
b = std::exp((-(x - _meanB) * (x - _meanB)) /
(2.0 * _standardDeviationB * _standardDeviationB));
}
return Term::_height * a * b;
}
std::string GaussianProduct::parameters() const {
return Op::join(4, " ", _meanA, _standardDeviationA, _meanB, _standardDeviationB) +
(not Op::isEq(getHeight(), 1.0) ? " " + Op::str(getHeight()) : "");
}
void GaussianProduct::configure(const std::string& parameters) {
if (parameters.empty()) return;
std::vector<std::string> values = Op::split(parameters, " ");
std::size_t required = 4;
if (values.size() < required) {
std::ostringstream ex;
ex << "[configuration error] term <" << className() << ">"
<< " requires <" << required << "> parameters";
throw Exception(ex.str(), FL_AT);
}
setMeanA(Op::toScalar(values.at(0)));
setStandardDeviationA(Op::toScalar(values.at(1)));
setMeanB(Op::toScalar(values.at(2)));
setStandardDeviationB(Op::toScalar(values.at(3)));
if (values.size() > required)
setHeight(Op::toScalar(values.at(required)));
}
void GaussianProduct::setMeanA(scalar meanA) {
this->_meanA = meanA;
}
scalar GaussianProduct::getMeanA() const {
return this->_meanA;
}
void GaussianProduct::setStandardDeviationA(scalar sigmaA) {
this->_standardDeviationA = sigmaA;
}
scalar GaussianProduct::getStandardDeviationA() const {
return this->_standardDeviationA;
}
void GaussianProduct::setMeanB(scalar meanB) {
this->_meanB = meanB;
}
scalar GaussianProduct::getMeanB() const {
return this->_meanB;
}
void GaussianProduct::setStandardDeviationB(scalar sigmaB) {
this->_standardDeviationB = sigmaB;
}
scalar GaussianProduct::getStandardDeviationB() const {
return this->_standardDeviationB;
}
GaussianProduct* GaussianProduct::clone() const {
return new GaussianProduct(*this);
}
Term* GaussianProduct::constructor() {
return new GaussianProduct;
}
}
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