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/*
Author: Juan Rada-Vilela, Ph.D.
Copyright (C) 2010-2014 FuzzyLite Limited
All rights reserved
This file is part of fuzzylite.
fuzzylite 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 3 of the License, or (at your option)
any later version.
fuzzylite 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 fuzzylite. If not, see <http://www.gnu.org/licenses/>.
fuzzylite™ is a trademark of FuzzyLite Limited.
*/
#include "fl/term/Gaussian.h"
namespace fl {
Gaussian::Gaussian(const std::string& name,
scalar mean, scalar standardDeviation, scalar height)
: Term(name, height), _mean(mean), _standardDeviation(standardDeviation) {
}
Gaussian::~Gaussian() {
}
std::string Gaussian::className() const {
return "Gaussian";
}
scalar Gaussian::membership(scalar x) const {
if (fl::Op::isNaN(x)) return fl::nan;
return _height * std::exp((-(x - _mean) * (x - _mean)) / (2 * _standardDeviation * _standardDeviation));
}
std::string Gaussian::parameters() const {
return Op::join(2, " ", _mean, _standardDeviation) +
(not Op::isEq(_height, 1.0) ? " " + Op::str(_height) : "");
}
void Gaussian::configure(const std::string& parameters) {
if (parameters.empty()) return;
std::vector<std::string> values = Op::split(parameters, " ");
std::size_t required = 2;
if (values.size() < required) {
std::ostringstream ex;
ex << "[configuration error] term <" << className() << ">"
<< " requires <" << required << "> parameters";
throw fl::Exception(ex.str(), FL_AT);
}
setMean(Op::toScalar(values.at(0)));
setStandardDeviation(Op::toScalar(values.at(1)));
if (values.size() > required)
setHeight(Op::toScalar(values.at(required)));
}
void Gaussian::setMean(scalar c) {
this->_mean = c;
}
scalar Gaussian::getMean() const {
return this->_mean;
}
void Gaussian::setStandardDeviation(scalar sigma) {
this->_standardDeviation = sigma;
}
scalar Gaussian::getStandardDeviation() const {
return this->_standardDeviation;
}
Gaussian* Gaussian::clone() const {
return new Gaussian(*this);
}
Term* Gaussian::constructor() {
return new Gaussian;
}
}
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