| //+------------------------------------------------------------------+
|
| //| Faza2.mq5 |
|
| //| Copyright 2023, DNG |
|
| //| https://www.mql5.com/ru/users/dng |
|
| //+------------------------------------------------------------------+
|
| #property copyright "Copyright 2023, DNG"
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| #property link "https://www.mql5.com/ru/users/dng"
|
| #property version "1.00"
|
| //+------------------------------------------------------------------+
|
| //| Includes |
|
| //+------------------------------------------------------------------+
|
| #include "Cell.mqh"
|
| #include "..\RL\FQF.mqh"
|
| //+------------------------------------------------------------------+
|
| //| Input parameters |
|
| //+------------------------------------------------------------------+
|
| input int Iterations = 100000;
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| input int UpdateTarget = 10000;
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| //+------------------------------------------------------------------+
|
| //| |
|
| //+------------------------------------------------------------------+
|
| CFQF StudyNet;
|
| //---
|
| float dError;
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| datetime dtStudied;
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| bool bEventStudy;
|
| //---
|
| CBufferFloat State1;
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| CBufferFloat *Rewards;
|
|
|
| Cell Base[];
|
| //+------------------------------------------------------------------+
|
| //| Expert initialization function |
|
| //+------------------------------------------------------------------+
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| int OnInit()
|
| {
|
| //---
|
| if(!LoadTotalBase())
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| return(INIT_FAILED);
|
| //---
|
| if(!StudyNet.Load(FileName + ".nnw", dtStudied, true))
|
| {
|
| CArrayObj *model = new CArrayObj();
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| if(!CreateDescriptions(model))
|
| {
|
| delete model;
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| return INIT_FAILED;
|
| }
|
| if(!StudyNet.Create(model))
|
| {
|
| delete model;
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| return INIT_FAILED;
|
| }
|
| delete model;
|
| }
|
| if(!StudyNet.TrainMode(true))
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| return INIT_FAILED;
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| StudyNet.SetUpdateTarget(UpdateTarget);
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| //---
|
| bEventStudy = EventChartCustom(ChartID(), 1, 0, 0, "Init");
|
| //---
|
| return(INIT_SUCCEEDED);
|
| }
|
| //+------------------------------------------------------------------+
|
| //| Expert deinitialization function |
|
| //+------------------------------------------------------------------+
|
| void OnDeinit(const int reason)
|
| {
|
| if(!!Rewards)
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| delete Rewards;
|
| //---
|
| StudyNet.Save(FileName + ".nnw", 0, true);
|
| }
|
| //+------------------------------------------------------------------+
|
| //| Train function |
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| //+------------------------------------------------------------------+
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| void Train(void)
|
| {
|
| int total = ArraySize(Base);
|
| uint ticks = GetTickCount();
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| for(int iter = 0; (iter < Iterations && !IsStopped()); iter ++)
|
| {
|
| int i = 0;
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| int count = 0;
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| int total_max = 0;
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| i = (int)((MathRand() * MathRand() / MathPow(32767, 2)) * (total - 1));
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| State1.AssignArray(Base[i].state);
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| if(IsStopped())
|
| {
|
| PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
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| ExpertRemove();
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| return;
|
| }
|
| int action = Base[i].total_actions;
|
| if(action < 0)
|
| {
|
| iter--;
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| continue;
|
| }
|
| if(!StudyNet.feedForward(GetPointer(State1), 12, true))
|
| return;
|
| action = Base[i].actions[action];
|
| if(action < 0 || action > 3)
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| action = 3;
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| StudyNet.getResults(Rewards);
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| Rewards.BufferInit(4, 0);
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| if(!Rewards.Update(action, -Base[i].value))
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| return;
|
| //---
|
| if(!StudyNet.backProp(GetPointer(Rewards)))
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| return;
|
| if(GetTickCount() - ticks > 500)
|
| {
|
| Comment(StringFormat("%.2f%% -> Error %.8f", iter * 100.0 / (double)(Iterations), StudyNet.getRecentAverageError()));
|
| ticks = GetTickCount();
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| }
|
| }
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| Comment("");
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| //---
|
| PrintFormat("%s -> %d -> %10.7f", __FUNCTION__, __LINE__, StudyNet.getRecentAverageError());
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| ExpertRemove();
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| //---
|
| }
|
| //+------------------------------------------------------------------+
|
| //| |
|
| //+------------------------------------------------------------------+
|
| //| | Creates or initializes Descriptions. |
|
| //+------------------------------------------------------------------+
|
| bool CreateDescriptions(CArrayObj *Description)
|
| {
|
| //---
|
| if(!Description)
|
| {
|
| Description = new CArrayObj();
|
| if(!Description)
|
| return false;
|
| }
|
| //--- Model
|
| Description.Clear();
|
| CLayerDescription *descr;
|
| //--- Input layer
|
| if(!(descr = new CLayerDescription()))
|
| return false;
|
| descr.type = defNeuronBaseOCL;
|
| uint prev_count = descr.count = (int)(HistoryBars * 12 + 9);
|
| descr.window = 0;
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| descr.activation = None;
|
| descr.optimization = ADAM;
|
| if(!Description.Add(descr))
|
| {
|
| delete descr;
|
| return false;
|
| }
|
| //--- layer 1
|
| if(!(descr = new CLayerDescription()))
|
| return false;
|
| descr.type = defNeuronBatchNormOCL;
|
| descr.count = prev_count;
|
| descr.batch = 200;
|
| descr.activation = None;
|
| descr.optimization = ADAM;
|
| if(!Description.Add(descr))
|
| {
|
| delete descr;
|
| return false;
|
| }
|
| //--- layer 2
|
| if(!(descr = new CLayerDescription()))
|
| return false;
|
| descr.type = defNeuronConvOCL;
|
| descr.count = prev_count / 3 - 1 ;
|
| descr.window = 6;
|
| descr.step = 3;
|
| descr.window_out = 6;
|
| descr.activation = LReLU;
|
| descr.optimization = ADAM;
|
| if(!Description.Add(descr))
|
| {
|
| delete descr;
|
| return false;
|
| }
|
| //--- layer 3
|
| if(!(descr = new CLayerDescription()))
|
| return false;
|
| descr.type = defNeuronBaseOCL;
|
| descr.count = 100;
|
| descr.optimization = ADAM;
|
| descr.activation = SIGMOID;
|
| if(!Description.Add(descr))
|
| {
|
| delete descr;
|
| return false;
|
| }
|
| //--- layer 4
|
| if(!(descr = new CLayerDescription()))
|
| return false;
|
| descr.type = defNeuronConvOCL;
|
| descr.count = 49;
|
| descr.window = 4;
|
| descr.step = 2;
|
| descr.window_out = 8;
|
| descr.activation = LReLU;
|
| descr.optimization = ADAM;
|
| if(!Description.Add(descr))
|
| {
|
| delete descr;
|
| return false;
|
| }
|
| //--- layer 5
|
| if(!(descr = new CLayerDescription()))
|
| return false;
|
| descr.type = defNeuronBaseOCL;
|
| descr.count = 100;
|
| descr.optimization = ADAM;
|
| descr.activation = TANH;
|
| if(!Description.Add(descr))
|
| {
|
| delete descr;
|
| return false;
|
| }
|
| //--- layer 6
|
| if(!(descr = new CLayerDescription()))
|
| return false;
|
| descr.type = defNeuronFQF;
|
| descr.count = 4;
|
| descr.window_out = 32;
|
| descr.optimization = ADAM;
|
| if(!Description.Add(descr))
|
| {
|
| delete descr;
|
| return false;
|
| }
|
| //---
|
| return true;
|
| }
|
| //+------------------------------------------------------------------+
|
| //| ChartEvent function |
|
| //+------------------------------------------------------------------+
|
| void OnChartEvent(const int id,
|
| const long &lparam,
|
| const double &dparam,
|
| const string &sparam)
|
| {
|
| //---
|
| if(id == 1001)
|
| Train();
|
| }
|
| //+------------------------------------------------------------------+
|
| //| |
|
| //+------------------------------------------------------------------+
|
| //| | Loads TotalBase. |
|
| //+------------------------------------------------------------------+
|
| bool LoadTotalBase(void)
|
| {
|
| int handle = FileOpen(FileName + ".bd", FILE_READ | FILE_BIN | FILE_COMMON);
|
| if(handle < 0)
|
| return false;
|
| int total = FileReadInteger(handle);
|
| if(total <= 0)
|
| {
|
| FileClose(handle);
|
| return false;
|
| }
|
| if(ArrayResize(Base, total) < total)
|
| {
|
| FileClose(handle);
|
| return false;
|
| }
|
| for(int i = 0; i < total; i++)
|
| if(!Base[i].Load(handle))
|
| {
|
| FileClose(handle);
|
| return false;
|
| }
|
| FileClose(handle);
|
| //---
|
| return true;
|
| }
|
| //+------------------------------------------------------------------+
|
|
|
