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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/>.
+
+ 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;
+ }
+
+
+}