flScalar ShoulderTerm::membership(flScalar crisp) const {
if (isLeft()) {
if (crisp < minimum())
return flScalar(1.0);
if (crisp > maximum())
return flScalar(0.0);
return FuzzyOperation::Scale(minimum(), maximum(), crisp, 1, 0);
} else {
if (crisp < minimum())
return flScalar(0.0);
if (crisp > maximum())
return flScalar(1.0);
return FuzzyOperation::Scale(minimum(), maximum(), crisp, 0, 1);
}
}
flScalar CompoundTerm::membership(flScalar crisp) const {
flScalar max = flScalar(0);
for (size_t i = 0; i < _terms.size(); ++i) {
max = fuzzyOperator().aggregation().execute(max, _terms[i]->membership(crisp));
}
return fuzzyOperator().modulation().execute(modulation(), max);
}
flScalar TrapezoidalTerm::membership(flScalar crisp) const {
if (crisp < minimum() || crisp > maximum()) {
return flScalar(0);
}
if (crisp < b()) {
return fuzzyOperator().modulation().execute(modulation(),
FuzzyOperation::Scale(a(), b(), crisp, 0, 1));
}
if (crisp < c()) {
return fuzzyOperator().modulation().execute(modulation(), flScalar(1.0));
}
if (crisp < d()) {
return fuzzyOperator().modulation().execute(modulation(),
FuzzyOperation::Scale(c(), d(), crisp, 1, 0));
}
return flScalar(0.0);
}
flScalar TriangularTerm::membership(flScalar crisp) const {
if (crisp > maximum() || crisp < minimum()) {
return flScalar(0.0);
}
flScalar result = crisp < b() ? FuzzyOperation::Scale(a(), b(), crisp, 0, 1)
: FuzzyOperation::Scale(b(), c(), crisp, 1, 0);
return fuzzyOperator().modulation().execute(result, modulation());
}
void FuzzyRule::fire(flScalar strength) {
if (!FuzzyOperation::IsEq(strength, flScalar(0.0))) {
// FL_LOG("DoT: " << strength << " - Fired: " << toString());
for (int i = 0; i < numberOfConsequents(); ++i) {
consequent(i)->execute(strength);
}
}
}
std::string MamdaniConsequent::toString() const {
std::stringstream ss;
ss << outputLVar()->name() << " " << FuzzyRule::FR_IS;
for (int i = 0; i < numberOfHedges(); ++i) {
ss << " " << hedge(i)->name();
}
ss << " " << term()->name();
if (weight() < flScalar(1.0)) {
ss << " " + FuzzyRule::FR_WITH + " " << weight();
}
return ss.str();
}
flScalar TriangulationAlgorithm::areaAndCentroid(
const LinguisticTerm* term, flScalar& centroid_x,
flScalar& centroid_y, int samples) const {
centroid_x = flScalar(0);
centroid_y = flScalar(0);
flScalar sum_area = flScalar(0.0);
flScalar sum_a_x = flScalar(0.0);
flScalar sum_a_y = flScalar(0.0);
flScalar tmp_area = flScalar(0.0);
flScalar range = term->maximum() - term->minimum();
flScalar step_size = range / samples;
int pi = 0;
flScalar x[3];
flScalar y[3];
/*******
* first triangle should include (minimum, 0)
* fix requires y_is_0 to start false & pi to start at 1
* updated by rctaylor 02/08/11
********/
bool y_is_0 = false;
x[0] = term->minimum();
y[0] = term->membership(x[0]);
x[1] = term->minimum();
y[1] = 0;
pi = 1;
// end update 02/08/11
int i = 1;
//Triangulation:
// rctaylor 02/08/11 - updated to <= because that is the only way x will ever equal
// term->maximum (ie. term->maximum = term->minimum + samples * step_size)
while (pi <= samples) {
++i;
if (y_is_0) {
x[i % 3] = x[(i - 1) % 3];
y[i % 3] = 0;
++pi; // rctaylor 02/08/11 - since y_is_0 starts false, this moves here
} else {
x[i % 3] = term->minimum() + pi * step_size;
y[i % 3] = term->membership(x[i % 3]);
}
y_is_0 = !y_is_0;
//Area of triangle:
// |Ax(By - Cy) + Bx(Cy - Ay) + Cx(Ay - By)| / 2
// |x0(y1 - y2) + x1(y2 - y0) + x2(y0 - y1)| / 2
tmp_area = FuzzyOperation::Absolute(x[0] * (y[1] - y[2]) + x[1]
* (y[2] - y[0]) + x[2] * (y[0] - y[1])) / 2;
//Centroid of a triangle:
// x = (x0 + x1 + x2)/3; y = (y0 + y1 + y2)/3;
sum_a_x += tmp_area * (x[0] + x[1] + x[2]) / 3;
sum_a_y += tmp_area * (y[0] + y[1] + y[2]) / 3;
sum_area += tmp_area;
}
centroid_x = sum_a_x / sum_area;
centroid_y = sum_a_y / sum_area;
return sum_area;
}
LinguisticTerm::LinguisticTerm(const FuzzyOperator& fuzzy_op,
const std::string& name, flScalar minimum, flScalar maximum) :
_fuzzy_operator(&fuzzy_op), _name(name), _minimum(minimum), _maximum(maximum),
_modulation(flScalar(1.0)) {
}
LinguisticTerm::LinguisticTerm(const std::string& name, flScalar minimum,
flScalar maximum) :
_fuzzy_operator(NULL), _name(name), _minimum(minimum), _maximum(maximum),
_modulation(flScalar(1.0)) {
setFuzzyOperator(FuzzyOperator::DefaultFuzzyOperator());
}
LinguisticTerm::LinguisticTerm() :
_fuzzy_operator(NULL), _name(""), _minimum(-(log (0.0))), _maximum((log (0.0))),
_modulation(flScalar(1.0)) {
setFuzzyOperator(FuzzyOperator::DefaultFuzzyOperator());
}
flScalar SingletonTerm::membership(flScalar crisp) const {
return fuzzyOperator().modulation().execute(modulation(), FuzzyOperation::IsEq(crisp, value())
? flScalar(1.0) : flScalar(0.0));
}
flScalar RectangularTerm::membership(flScalar crisp) const {
if (crisp > maximum() || crisp < minimum()) {
return flScalar(0.0);
}
return fuzzyOperator().modulation().execute(1.0, modulation());
}
