diff options
Diffstat (limited to 'fuzzylite/src/term/GaussianProduct.cpp')
-rw-r--r-- | fuzzylite/src/term/GaussianProduct.cpp | 120 |
1 files changed, 120 insertions, 0 deletions
diff --git a/fuzzylite/src/term/GaussianProduct.cpp b/fuzzylite/src/term/GaussianProduct.cpp new file mode 100644 index 0000000..b9652e1 --- /dev/null +++ b/fuzzylite/src/term/GaussianProduct.cpp @@ -0,0 +1,120 @@ +/* + 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/>. + + fuzzyliteâ„¢ is a 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"; + } + + scalar GaussianProduct::membership(scalar x) const { + if (fl::Op::isNaN(x)) return fl::nan; + bool xLEa = fl::Op::isLE(x, _meanA); + scalar a = (1 - xLEa) + xLEa * std::exp( + (-(x - _meanA) * (x - _meanA)) / (2 * _standardDeviationA * _standardDeviationA) + ); + bool xGEb = fl::Op::isGE(x, _meanB); + scalar b = (1 - xGEb) + xGEb * std::exp( + (-(x - _meanB) * (x - _meanB)) / (2 * _standardDeviationB * _standardDeviationB) + ); + return _height * a * b; + } + + std::string GaussianProduct::parameters() const { + return Op::join(4, " ", _meanA, _standardDeviationA, _meanB, _standardDeviationB) + + (not Op::isEq(_height, 1.0) ? " " + Op::str(_height) : ""); + } + + 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 fl::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; + } + + +} |