398 satır
25 KiB
MQL5
398 satır
25 KiB
MQL5
//+------------------------------------------------------------------+
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//| EVDRL-Learning.mq5 |
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//| Copyright 2023, DNG |
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//| https://www.mql5.com/ru/users/dng |
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//+------------------------------------------------------------------+
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#property copyright "Copyright 2023, DNG"
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#property link "https://www.mql5.com/ru/users/dng"
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#property version "1.00"
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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#define FileName Symb.Name()+"_"+EnumToString(TimeFrame)+"_"+StringSubstr(__FILE__,0,StringFind(__FILE__,".",0))
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//+------------------------------------------------------------------+
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//| Includes |
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//+------------------------------------------------------------------+
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#include "EVD.mqh"
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#include <Trade\Trade.mqh>
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#include <Trade\SymbolInfo.mqh>
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#include <Indicators\Oscilators.mqh>
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//+------------------------------------------------------------------+
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//| Input parameters |
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//+------------------------------------------------------------------+
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uint HistoryBars = 20; //Depth of history
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input ENUM_TIMEFRAMES TimeFrame = PERIOD_H1;
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input int Batch = 100;
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input float DiscountFactor = 0.3f;
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//---
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input group "---- RSI ----"
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input int RSIPeriod = 14; //Period
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input ENUM_APPLIED_PRICE RSIPrice = PRICE_CLOSE; //Applied price
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//---
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input group "---- CCI ----"
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input int CCIPeriod = 14; //Period
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input ENUM_APPLIED_PRICE CCIPrice = PRICE_TYPICAL; //Applied price
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//---
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input group "---- ATR ----"
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input int ATRPeriod = 14; //Period
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//---
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input group "---- MACD ----"
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input int FastPeriod = 12; //Fast
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input int SlowPeriod = 26; //Slow
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input int SignalPeriod = 9; //Signal
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input ENUM_APPLIED_PRICE MACDPrice = PRICE_CLOSE; //Applied price
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input bool TrainMode = true;
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input bool InitNormalization = false;
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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CSymbolInfo Symb;
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MqlRates Rates[];
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CEVD StudyNet;
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CiRSI RSI;
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CiCCI CCI;
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CiATR ATR;
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CiMACD MACD;
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//---
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float dError;
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datetime dtStudied;
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bool bEventStudy;
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MqlDateTime sTime;
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//---
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CBufferFloat State1;
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float min_loss = FLT_MAX;
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CTrade Trade;
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//+------------------------------------------------------------------+
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//| Expert initialization function |
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//+------------------------------------------------------------------+
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int OnInit()
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{
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//---
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if(!Symb.Name(_Symbol))
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return INIT_FAILED;
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Symb.Refresh();
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//---
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if(!RSI.Create(Symb.Name(), TimeFrame, RSIPeriod, RSIPrice))
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return INIT_FAILED;
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//---
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if(!CCI.Create(Symb.Name(), TimeFrame, CCIPeriod, CCIPrice))
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return INIT_FAILED;
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//---
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if(!ATR.Create(Symb.Name(), TimeFrame, ATRPeriod))
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return INIT_FAILED;
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//---
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if(!MACD.Create(Symb.Name(), TimeFrame, FastPeriod, SlowPeriod, SignalPeriod, MACDPrice))
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return INIT_FAILED;
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//---
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if(!StudyNet.Load(FileName + ".evd", true))
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if(!StudyNet.Load(FileName + ".nnw", FileName + ".fwe", 5, true))
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{
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CArrayObj *model = new CArrayObj();
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CArrayObj *forward = new CArrayObj();
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if(!CreateDescriptions(model, forward))
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{
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delete model;
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delete forward;
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return INIT_FAILED;
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}
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if(!StudyNet.Create(model, forward))
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{
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delete model;
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delete forward;
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return INIT_FAILED;
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}
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StudyNet.SetStateEmbedingLayer(5);
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delete model;
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delete forward;
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}
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if(!StudyNet.TrainMode(TrainMode))
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return INIT_FAILED;
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StudyNet.SetBufferSize(Batch, 10 * Batch);
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//---
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CBufferFloat* temp;
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if(!StudyNet.GetLayerOutput(0, temp))
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return INIT_FAILED;
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HistoryBars = (temp.Total() - 9) / 12;
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delete temp;
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if(!RSI.BufferResize(HistoryBars) || !CCI.BufferResize(HistoryBars) ||
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!ATR.BufferResize(HistoryBars) || !MACD.BufferResize(HistoryBars))
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{
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PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
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return INIT_FAILED;
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}
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//---
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if(!Trade.SetTypeFillingBySymbol(Symb.Name()))
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return INIT_FAILED;
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//---
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return(INIT_SUCCEEDED);
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}
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//+------------------------------------------------------------------+
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//| Expert deinitialization function |
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//+------------------------------------------------------------------+
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void OnDeinit(const int reason)
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{
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//---
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StudyNet.Save(FileName + ".evd", true);
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StudyNet.Save(FileName + ".nnw", FileName + ".fwe", true);
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}
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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void OnTesterPass()
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{
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StudyNet.Save(FileName + ".evd", true);
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StudyNet.Save(FileName + ".nnw", FileName + ".fwe", true);
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}
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//+------------------------------------------------------------------+
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//| Expert tick function |
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//+------------------------------------------------------------------+
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void OnTick()
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{
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if(!IsNewBar())
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return;
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//---
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int bars = CopyRates(Symb.Name(), TimeFrame, iTime(Symb.Name(), TimeFrame, 1), HistoryBars, Rates);
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if(!ArraySetAsSeries(Rates, true))
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{
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PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
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return;
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}
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//---
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RSI.Refresh();
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CCI.Refresh();
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ATR.Refresh();
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MACD.Refresh();
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//---
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State1.Clear();
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for(int b = 0; b < (int)HistoryBars; b++)
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{
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float open = (float)Rates[b].open;
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TimeToStruct(Rates[b].time, sTime);
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float rsi = (float)RSI.Main(b);
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float cci = (float)CCI.Main(b);
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float atr = (float)ATR.Main(b);
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float macd = (float)MACD.Main(b);
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float sign = (float)MACD.Signal(b);
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if(rsi == EMPTY_VALUE || cci == EMPTY_VALUE || atr == EMPTY_VALUE || macd == EMPTY_VALUE || sign == EMPTY_VALUE)
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continue;
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//---
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if(!State1.Add((float)Rates[b].close - open) || !State1.Add((float)Rates[b].high - open) || !State1.Add((float)Rates[b].low - open) || !State1.Add((float)Rates[b].tick_volume / 1000.0f) ||
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!State1.Add(sTime.hour) || !State1.Add(sTime.day_of_week) || !State1.Add(sTime.mon) ||
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!State1.Add(rsi) || !State1.Add(cci) || !State1.Add(atr) || !State1.Add(macd) || !State1.Add(sign))
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{
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PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
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break;
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}
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}
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if(InitNormalization)
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{
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StudyNet.feedForward(GetPointer(State1), 12, true);
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return;
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}
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switch(StudyNet.feedForward(GetPointer(State1), 12, true))
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{
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case 0:
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Trade.Buy(Symb.LotsMin(), Symb.Name());
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break;
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case 1:
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Trade.Sell(Symb.LotsMin(), Symb.Name());
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break;
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case 2:
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for(int i = PositionsTotal() - 1; i >= 0; i--)
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if(PositionGetSymbol(i) == Symb.Name())
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Trade.PositionClose(PositionGetInteger(POSITION_IDENTIFIER));
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break;
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}
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MqlDateTime time;
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TimeCurrent(time);
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if(time.hour==0)
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StudyNet.backProp(Batch, DiscountFactor);
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//---
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}
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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bool IsNewBar(void)
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{
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static datetime last_bar = 0;
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if(last_bar >= iTime(Symb.Name(), TimeFrame, 0))
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return false;
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//---
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last_bar = iTime(Symb.Name(), TimeFrame, 0);
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return true;
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}
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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bool CreateDescriptions(CArrayObj *Description, CArrayObj *Forward)
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{
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//---
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if(!Description)
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{
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Description = new CArrayObj();
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if(!Description)
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return false;
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}
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//---
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if(!Forward)
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{
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Forward = new CArrayObj();
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if(!Forward)
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return false;
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}
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//--- Model
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Description.Clear();
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CLayerDescription *descr;
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//--- Input layer
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronBaseOCL;
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int prev_count = descr.count = (int)(HistoryBars * 12 + 9);
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descr.window = 0;
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descr.activation = None;
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descr.optimization = ADAM;
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if(!Description.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 1
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronBatchNormOCL;
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descr.count = prev_count;
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descr.batch = 100;
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descr.activation = None;
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descr.optimization = ADAM;
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if(!Description.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 2
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronConvOCL;
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descr.count = prev_count/3-1 ;
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descr.window = 6;
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descr.step = 3;
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descr.window_out = 6;
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descr.activation = LReLU;
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descr.optimization = ADAM;
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if(!Description.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 3
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronBaseOCL;
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descr.count = 100;
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descr.optimization = ADAM;
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descr.activation = SIGMOID;
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if(!Description.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 4
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronConvOCL;
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descr.count = 49;
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descr.window = 4;
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descr.step = 2;
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descr.window_out = 8;
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descr.activation = LReLU;
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descr.optimization = ADAM;
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if(!Description.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 5
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronBaseOCL;
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descr.count = 100;
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descr.optimization = ADAM;
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descr.activation=TANH;
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if(!Description.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 6
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronMLMHSparseAttentionOCL;
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descr.count = 20;
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descr.window = 5;
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descr.step = 4;
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descr.window_out = 8;
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descr.layers = 2;
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descr.probability = 0.3f;
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descr.optimization = ADAM;
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if(!Description.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 7
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronFQF;
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descr.count = 4;
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descr.window_out = 32;
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descr.optimization = ADAM;
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if(!Description.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- Forward
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Forward.Clear();
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//--- Input layer
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronBaseOCL;
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descr.count = 100;
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descr.window = 0;
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descr.activation = None;
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descr.optimization = ADAM;
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if(!Forward.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 1
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronBaseOCL;
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descr.count = 1000;
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descr.activation = TANH;
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descr.optimization = ADAM;
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if(!Forward.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 2
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronMultiModels;
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descr.count = 400;
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descr.window = 200;
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descr.step = 5;
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descr.activation = TANH;
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descr.optimization = ADAM;
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if(!Forward.Add(descr))
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{
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delete descr;
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return false;
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}
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//---
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return true;
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}
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//+------------------------------------------------------------------+
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