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Add BOA(Bull) and Test_AO_AntiCheat

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JQSakaJoo
2026-04-28 00:29:35 +04:00
parent 2e574ae823
commit b7c018d497
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MQL5/Include/Math/AOs/PopulationAO/#C_AO_enum.mqh
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MQL5/Include/Math/AOs/PopulationAO/AO_BOA_BullOptimizationAlgorithm.mqh
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MQL5/Include/Math/AOs/PopulationAO/links.html
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@@ -98,6 +98,7 @@
<tr><td>DA(Duelist)</td><td><a href="https://www.mql5.com/ru/articles/19093" target="_blank">duelist algorithm</a></td></tr>
<tr><td>ECOi</td><td><a href="https://www.mql5.com/ru/articles/20608" target="_blank">eco-inspired evolutionary algorithm</a></td></tr>
<tr><td>BFO-GA</td><td><a href="https://www.mql5.com/ru/articles/14011" target="_blank">bacterial foraging optimization - genetic algorithm</a></td></tr>
<tr><td>BOA(Bull)</td><td><a href="https://www.mql5.com/ru/articles/22390" target="_blank">bull optimization algorithm</a></td></tr>
<tr><td>SOA</td><td><a href="https://www.mql5.com/ru/articles/16364#tag3" target="_blank">simple optimization algorithm</a></td></tr>
<tr><td>ABHA</td><td><a href="https://www.mql5.com/ru/articles/15347" target="_blank">artificial bee hive algorithm</a></td></tr>
<tr><td>DO</td><td><a href="https://www.mql5.com/ru/articles/20540" target="_blank">dandelion optimizer</a></td></tr>
MQL5/Include/Math/AOs/TestStand3D.mqh
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MQL5/Scripts/Testing AOs/Test_AO_All.mq5
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//+----------------------------------------------------------------------------+
//| Copyright 2007-2026, Andrey Dik |
//| https://www.mql5.com/ru/users/joo |
//+----------------------------------------------------------------------------+
#property copyright "Copyright 2007-2026, JQS aka Joo."
#property link "https://www.mql5.com/ru/users/joo"
#property version "1.00"
#property script_show_inputs
#include <Math\AOs\TestFunctions.mqh>
#include <Math\AOs\TestStandFunctions.mqh>
#include <Math\AOs\TestStand3D.mqh>
#include <Math\AOs\PopulationAO\#C_AO.mqh>
#include <Math\AOs\PopulationAO\#C_AO_enum.mqh>
//+------------------------------------------------------------------+
input string AOparam = "----------------"; //AO parameters-----------
input E_AO AOexactly_P = NONE_AO;
input string TestStand_1 = "----------------"; //Test stand--------------
input double ArgumentStep_P = 0.0; //Argument Step
input string TestStand_2 = "----------------"; //------------------------
input int Test1FuncRuns_P = 5; //Test #1: Number of functions in the test
input int Test2FuncRuns_P = 25; //Test #2: Number of functions in the test
input int Test3FuncRuns_P = 500; //Test #3: Number of functions in the test
input string TestStand_3 = "----------------"; //------------------------
input EFunc Function1 = Hilly;
input EFunc Function2 = Forest;
input EFunc Function3 = Megacity;
input string TestStand_4 = "----------------"; //------------------------
input int NumbTestFuncRuns_P = 10000; //Number of test function runs
input int NumberRepetTest_P = 10; //Test repets number
input string TestStand_5 = "----------------"; //------------------------
input int DelayInMS_P = 0;
input bool Video_P = true; //Show video
input bool Use3D_P = true; //Показывать 3D-визуализацию
input int Grid3D_P = 80; //Разрешение 3D-сетки (10..200)
//+------------------------------------------------------------------+
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
void OnStart()
{
C_AO *AO = SelectAO(AOexactly_P);
if(AO == NULL)
{
Print("AO is not selected...");
return;
}
Print(AO.GetName(), "|", AO.GetDesc(), "|", AO.GetParams());
//--- 2D стенд
C_TestStand ST;
ST.Init(750, 375);
//--- 3D стенд
C_TestStand3D *ST3 = NULL;
if(Use3D_P)
{
ST3 = new C_TestStand3D();
if(!ST3.Init("__3DView__", 5, 30, ST.H, ST.H))
{
Print("C_TestStand3D: Init failed — 3D-режим отключён");
delete ST3;
ST3 = NULL;
}
}
double allScore = 0.0;
double allTests = 0.0;
C_Function *F1 = SelectFunction(Function1);
C_Function *F2 = SelectFunction(Function2);
C_Function *F3 = SelectFunction(Function3);
if(F1 != NULL)
{
Print("=============================");
ST.CanvasErase();
if(ST3 != NULL)
{ST3.BuildSurface(*F1, Grid3D_P); ST3.Show(true); }
FuncTests(AO, ST, ST3, *F1, Test1FuncRuns_P, clrLime, allScore, allTests);
FuncTests(AO, ST, ST3, *F1, Test2FuncRuns_P, clrAqua, allScore, allTests);
FuncTests(AO, ST, ST3, *F1, Test3FuncRuns_P, clrOrangeRed, allScore, allTests);
delete F1;
}
if(F2 != NULL)
{
Print("=============================");
ST.CanvasErase();
if(ST3 != NULL)
{ST3.BuildSurface(*F2, Grid3D_P); ST3.Show(true); }
FuncTests(AO, ST, ST3, *F2, Test1FuncRuns_P, clrLime, allScore, allTests);
FuncTests(AO, ST, ST3, *F2, Test2FuncRuns_P, clrAqua, allScore, allTests);
FuncTests(AO, ST, ST3, *F2, Test3FuncRuns_P, clrOrangeRed, allScore, allTests);
delete F2;
}
if(F3 != NULL)
{
Print("=============================");
ST.CanvasErase();
if(ST3 != NULL)
{ST3.BuildSurface(*F3, Grid3D_P); ST3.Show(true); }
FuncTests(AO, ST, ST3, *F3, Test1FuncRuns_P, clrLime, allScore, allTests);
FuncTests(AO, ST, ST3, *F3, Test2FuncRuns_P, clrAqua, allScore, allTests);
FuncTests(AO, ST, ST3, *F3, Test3FuncRuns_P, clrOrangeRed, allScore, allTests);
delete F3;
}
Print("=============================");
if(allTests > 0.0)
Print("All score: ", DoubleToString(allScore, 5), " (", DoubleToString(allScore * 100.0 / allTests, 2), "%)");
if(ST3 != NULL)
{ST3.Show(false); delete ST3; }
ST.Canvas.Destroy();
delete AO;
}
//+------------------------------------------------------------------+
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
void FuncTests(C_AO &ao,
C_TestStand &st,
C_TestStand3D *st3,
C_Function &f,
const int funcCount,
const color clrConv,
double &allScore,
double &allTests)
{
if(funcCount <= 0)
return;
allTests++;
if(Video_P)
{
st.DrawFunctionGraph(f);
st.SendGraphToCanvas();
st.MaxMinDr(f);
st.Update();
}
int xConv = 0.0;
int yConv = 0.0;
double aveResult = 0.0;
int params = funcCount * 2;
int epochCount = NumbTestFuncRuns_P / (int)ao.params [0].val;
//----------------------------------------------------------------------------
double rangeMin [], rangeMax [], rangeStep [];
ArrayResize(rangeMin, params);
ArrayResize(rangeMax, params);
ArrayResize(rangeStep, params);
for(int i = 0; i < funcCount; i++)
{
rangeMax [i * 2] = f.GetMaxRangeX();
rangeMin [i * 2] = f.GetMinRangeX();
rangeStep [i * 2] = ArgumentStep_P;
rangeMax [i * 2 + 1] = f.GetMaxRangeY();
rangeMin [i * 2 + 1] = f.GetMinRangeY();
rangeStep [i * 2 + 1] = ArgumentStep_P;
}
double ag3D [];
for(int test = 0; test < NumberRepetTest_P; test++)
{
//--------------------------------------------------------------------------
if(!ao.Init(rangeMin, rangeMax, rangeStep, epochCount))
break;
int agCnt = ArraySize(ao.a);
if(st3 != NULL)
{ArrayResize(ag3D, agCnt * funcCount * 2); st3.ResetTrail(); }
// Optimization-------------------------------------------------------------
for(int epochCNT = 1; epochCNT <= epochCount && !IsStopped(); epochCNT++)
{
if(DelayInMS_P > 0)
Sleep(DelayInMS_P);
Comment(epochCNT);
ao.Moving();
for(int set = 0; set < ArraySize(ao.a); set++)
{
ao.a [set].f = f.CalcFunc(ao.a [set].c);
}
ao.Revision();
//--- 2D визуализация -------------------------------------------
if(Video_P)
{
//drawing a population--------------------------------------------------
st.SendGraphToCanvas();
for(int i = 0; i < agCnt; i++)
{
st.PointDr(ao.a [i].c, f, 1, 1, funcCount, false);
}
st.PointDr(ao.cB, f, 1, 1, funcCount, true);
st.MaxMinDr(f);
//drawing a convergence graph-------------------------------------------
xConv = (int)st.Scale(epochCNT, 1, epochCount, st.H + 2, st.W - 3, false);
yConv = (int)st.Scale(ao.fB, f.GetMinFunValue(), f.GetMaxFunValue(), 2, st.H - 2, true);
st.Canvas.FillCircle(xConv, yConv, 1, COLOR2RGB(clrConv));
st.Update();
}
//--- 3D визуализация -------------------------------------------
if(st3 != NULL)
{
for(int i = 0; i < agCnt; i++)
for(int j = 0; j < funcCount; j++)
{
ag3D [(i * funcCount + j) * 2] = ao.a [i].c [j * 2];
ag3D [(i * funcCount + j) * 2 + 1] = ao.a [i].c [j * 2 + 1];
}
st3.OnTimer(0.033);
st3.SetAgents(ag3D, agCnt, funcCount, f, ao.cB);
st3.Redraw();
}
}
aveResult += ao.fB;
}
aveResult /= (double)NumberRepetTest_P;
double score = aveResult;
Print(funcCount, " ", f.GetFuncName(), "'s; Func runs: ", NumbTestFuncRuns_P, "; result: ", aveResult);
allScore += score;
}
//+------------------------------------------------------------------+
//+------------------------------------------------------------------+
MQL5/Scripts/Testing AOs/Test_AO_AntiCheat.mq5
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//+------------------------------------------------------------------+
//| Copyright 2007-2026, Andrey Dik |
//| https://www.mql5.com/ru/users/joo |
//+------------------------------------------------------------------+
#property copyright "Copyright 2007-2026, JQS aka Joo."
#property link "https://www.mql5.com/ru/users/joo"
#property version "1.00"
#property script_show_inputs
#include <Math\AOs\TestFunctions.mqh>
#include <Math\AOs\PopulationAO\#C_AO.mqh>
#include <Math\AOs\PopulationAO\#C_AO_enum.mqh>
//————————————————————————————————————————————————————————————————————
input string AOparam = "----------------"; //AO parameters-----------
input E_AO AOexactly_P = NONE_AO;
input string TestStand_P = "----------------"; //Test stand---------------
input int NumbTestFuncRuns_P = 1e4; // Количество вычислений функции
input int NumberRepetTest_P = 10; // Количество повторных прогонов
//————————————————————————————————————————————————————————————————————
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
void OnStart()
{
C_AO *AO = SelectAO(AOexactly_P);
if(AO == NULL)
{
Print("AO is not selected...");
return;
}
Print(AO.GetName(), "|", AO.GetDesc(), "|", AO.GetParams());
//--- создаём 5 функций
#define NFUNCS 5
C_Function *funcs [NFUNCS];
funcs [0] = new C_Hilly();
funcs [1] = new C_Forest();
funcs [2] = new C_Megacity();
funcs [3] = new C_Peaks();
funcs [4] = new C_Skin();
//--- 10 координат: пара 0-1 = Hilly, 2-3 = Forest, 4-5 = Megacity,
// 6-7 = Peaks, 8-9 = Skin
int params = NFUNCS * 2;
double rangeMin [];
double rangeMax [];
double rangeStep [];
ArrayResize(rangeMin, params);
ArrayResize(rangeMax, params);
ArrayResize(rangeStep, params);
for(int i = 0; i < NFUNCS; i++)
{
rangeMin [i * 2] = funcs [i].GetMinRangeX();
rangeMax [i * 2] = funcs [i].GetMaxRangeX();
rangeStep [i * 2] = 0.0;
rangeMin [i * 2 + 1] = funcs [i].GetMinRangeY();
rangeMax [i * 2 + 1] = funcs [i].GetMaxRangeY();
rangeStep [i * 2 + 1] = 0.0;
}
//--- запуск тестов
int epochCount = NumbTestFuncRuns_P / (int)AO.params [0].val;
double aveResult = 0.0;
Print("=============================");
Print("Composite test: Hilly + Forest + Megacity + Peaks + Skin");
Print("Coordinates: ", params, "; Epochs: ", epochCount,
"; Repeats: ", NumberRepetTest_P);
Print("=============================");
for(int test = 0; test < NumberRepetTest_P; test++)
{
if(!AO.Init(rangeMin, rangeMax, rangeStep, epochCount))
break;
for(int epochCNT = 1; epochCNT <= epochCount && !IsStopped(); epochCNT++)
{
AO.Moving();
//--- расчёт fitness для каждого агента
for(int set = 0; set < ArraySize(AO.a); set++)
{
double sum = 0.0;
for(int i = 0; i < NFUNCS; i++)
{
sum += funcs [i].Core(AO.a [set].c [i * 2],
AO.a [set].c [i * 2 + 1]);
}
AO.a [set].f = sum / NFUNCS;
}
AO.Revision();
}
Print("Run ", test + 1, "/", NumberRepetTest_P, ": ", AO.fB);
aveResult += AO.fB;
}
aveResult /= (double)NumberRepetTest_P;
Print("=============================");
Print("Average result: ", DoubleToString(aveResult, 10),
" (", DoubleToString(aveResult * 100.0, 2), "%)");
Print("=============================");
//--- освобождение
for(int i = 0; i < NFUNCS; i++)
delete funcs [i];
delete AO;
}
//+------------------------------------------------------------------+
//+------------------------------------------------------------------+
MQL5/Scripts/Testing AOs/Testing AOs.mq5
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README.md
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@@ -49,6 +49,7 @@ CMAES (covariance matrix adaptation evolution strategy)
DA_Duelist (duelist algorithm)
ECOi (eco-inspired evolutionary algorithm)
SOA (simple optimization algorithm)
BOA(Bull) (bull optimization algorithm)
ABHA (artificial bee hive algorithm)
DO (dandelion optimizer)
CLA_L (competitive learning algorithm)