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From: Alex Shafir (alex_at_[hidden])
Date: 2008-06-25 17:45:23

I am trying to determine if there might be any interest in a couple of
possible library submissions. Both ideas were very useful and
instrumental for many C++ development projects that I was doing for the
last years.

The fuzzy logic library is a simple, pure C++, optimized for speed,
practical implementation of the fuzzy logic calculations that DOES NOT
attempts to comply with the FCL(Fuzzy Control Language) standard (like
IEC 1131). It CANNOT load FCL files. Instead similar to the Boost Spirit
framework it provides a syntax that enables fuzzy logic rules to be
written exclusively in C++. Compiled fuzzy model specifications are
immediately executable. A snippet of what this syntax currently looks
like is at the end of this message.

The other idea is the “sparse array” container. Working for securities
trading industry I used it innumerable number of times. It is useful in
situations where there is a set of entities identified by
integer(unsigned) numbers. Most often the numbers are identity keys in a
database, a protocol field ids, etc. The potential range of the numbers
makes it impractical to use a C++ array or the STL <vector>. On the
other hand the average percentage of the keys that are really used in an
application relative to the potential range is often less then 5% and
there are huge holes of unused keys between zero and max(used key). The
data elements or pointers to objects are kept in a structure similar to
a balanced B-tree. Elements are directly accessed by an index operator.
Access involves only a few arithmetic and redirection operations. When
storing a new element that is outside of the range provided by exiting
data structure the structure bilds itself up extending the indes range
enough to accommodate a new index value. Existing data are never
physically moved like in the STL vector. So, all
references/pointers/iterators referencing existing elements are never

Feel free to comment.

Fuzzy model syntax sample:

#include "TestModel.h"

using namespace Fuzzy;

// test model definition
TestModel::TestModel(string file): Model(file), angle(-1), velocity(-1),
        // fuzzy variables definitions created by the base class (Fuzzy::Model)
        // Input/Output methods; Input/Output arguments are refs
        // to double scalar variables
        Var& Angle = Input(angle);
        Var& Vlcty = Input(velocity);
        Var& Speed = Output(speed);
        // membership functions definitions created by fuzzy variables
        // Term method; Term method takes curve name as an argument;
        // cureve names are defined in the Fuzzy::Model curve definition
        // file

        MemFun& AngleNegHigh = Angle.Term("AngleNegHigh");
        MemFun& AngleNegLow = Angle.Term("AngleNegLow");
        MemFun& AngleZero = Angle.Term("AngleZero");
        MemFun& AnglePosLow = Angle.Term("AnglePosLow");
        MemFun& AnglePosHigh = Angle.Term("AnglePosHigh");

        MemFun& VlctyNegHigh = Vlcty.Term("VelocityNegHigh");
        MemFun& VlctyNegLow = Vlcty.Term("VelocityNegLow");
        MemFun& VlctyZero = Vlcty.Term("VelocityZero");
        MemFun& VlctyPosLow = Vlcty.Term("VelocityPosLow");
        MemFun& VlctyPosHigh = Vlcty.Term("VelocityPosHigh");

        MemFun& SpeedNegHigh = Speed.Term("AngleNegHigh");
        MemFun& SpeedNegLow = Speed.Term("AngleNegLow");
        MemFun& SpeedZero = Speed.Term("AngleZero");
        MemFun& SpeedPosLow = Speed.Term("AnglePosLow");
        MemFun& SpeedPosHigh = Speed.Term("AnglePosHigh");
        // these are the model rules; syntax is pretty strightforward;
        // rules look like operator >> where lhs is the condition and
        // rhs is the conclusion;
        // lhs and rhs have to be in parens if they contain more then
        // one term because of the c++ operators precedence rules;
        // conclusion may be a comma separated list of output terms
        // in parens
        ((AngleZero and VlctyZero)or(AnglePosLow and VlctyNegLow)or(AngleNegLow
and VlctyPosLow))
>> SpeedZero;
        ((AngleZero and VlctyNegLow)or(AngleNegLow and VlctyZero))
>> SpeedNegLow;

        ((AnglePosLow and VlctyZero)or(AngleZero and VlctyPosLow))
>> SpeedPosLow;

        ((AngleZero and VlctyNegHigh)or(AngleNegHigh and VlctyZero))
>> SpeedNegHigh;
        ((AnglePosHigh and VlctyZero)or(AngleZero and VlctyPosHigh))
>> SpeedPosHigh;

TestModel::~TestModel() {

TestModel::run(double a, double v, double &s) {

        // we assign scalar variables to class members
        angle = a;
        velocity = v;
        speed = s;

        // then run the model
        // it should be pretty fast as it all designed to preallocate
        // all the needed large objects in the model constructor
        // and assign the values of output variables
        s = speed;

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