190 satır
16 KiB
MQL5
190 satır
16 KiB
MQL5
//+------------------------------------------------------------------+
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//| Study.mq5 |
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//| Copyright DNG® |
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//| https://www.mql5.com/ru/users/dng |
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//+------------------------------------------------------------------+
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#property copyright "Copyright 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 StudyExpert
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#include "Trajectory.mqh"
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//+------------------------------------------------------------------+
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//| Input parameters |
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//+------------------------------------------------------------------+
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input int Iterations = 100000;
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input float Tau = 0.01f;
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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STrajectory Buffer[];
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CNet_SAC_DICE Net;
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//---
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float dError;
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datetime dtStudied;
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//---
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CBufferFloat bState;
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CBufferFloat bAccount;
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CBufferFloat bActions;
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CBufferFloat bNextState;
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CBufferFloat bNextAccount;
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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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ResetLastError();
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if(!LoadTotalBase())
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{
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PrintFormat("Error of load study data: %d", GetLastError());
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return INIT_FAILED;
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}
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//--- load models
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if(!Net.Load(FileName, true))
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{
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CArrayObj *actor = new CArrayObj();
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CArrayObj *critic = new CArrayObj();
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if(!CreateDescriptions(actor, critic))
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{
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delete actor;
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delete critic;
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return INIT_FAILED;
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}
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if(!Net.Create(actor, critic, critic, critic, LatentLayer))
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{
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delete actor;
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delete critic;
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return INIT_FAILED;
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}
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delete actor;
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delete critic;
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}
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//---
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if(!EventChartCustom(ChartID(), 1, 0, 0, "Init"))
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{
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PrintFormat("Error of create study event: %d", GetLastError());
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return INIT_FAILED;
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}
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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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Net.Save(FileName, true);
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}
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//+------------------------------------------------------------------+
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//| ChartEvent function |
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//+------------------------------------------------------------------+
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void OnChartEvent(const int id,
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const long &lparam,
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const double &dparam,
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const string &sparam)
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{
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//---
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if(id == 1001)
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Train();
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}
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//+------------------------------------------------------------------+
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//| Train function |
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//+------------------------------------------------------------------+
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void Train(void)
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{
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int total_tr = ArraySize(Buffer);
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uint ticks = GetTickCount();
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//---
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for(int iter = 0; (iter < Iterations && !IsStopped()); iter ++)
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{
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int tr = (int)((MathRand() / 32767.0) * (total_tr - 1));
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int i = (int)((MathRand() * MathRand() / MathPow(32767, 2)) * (Buffer[tr].Total - 2));
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if(i<0)
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{
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iter--;
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continue;
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}
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//--- Target
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bNextState.AssignArray(Buffer[tr].States[i + 1].state);
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float PrevBalance = Buffer[tr].States[i].account[0];
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float PrevEquity = Buffer[tr].States[i].account[1];
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if(PrevBalance==0)
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{
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iter--;
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continue;
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}
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bNextAccount.Clear();
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bNextAccount.Add((Buffer[tr].States[i + 1].account[0] - PrevBalance) / PrevBalance);
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bNextAccount.Add(Buffer[tr].States[i + 1].account[1] / PrevBalance);
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bNextAccount.Add((Buffer[tr].States[i + 1].account[1] - PrevEquity) / PrevEquity);
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bNextAccount.Add(Buffer[tr].States[i + 1].account[2]);
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bNextAccount.Add(Buffer[tr].States[i + 1].account[3]);
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bNextAccount.Add(Buffer[tr].States[i + 1].account[4] / PrevBalance);
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bNextAccount.Add(Buffer[tr].States[i + 1].account[5] / PrevBalance);
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bNextAccount.Add(Buffer[tr].States[i + 1].account[6] / PrevBalance);
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double x = (double)Buffer[tr].States[i + 1].account[7] / (double)(D'2024.01.01' - D'2023.01.01');
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bNextAccount.Add((float)MathSin(x != 0 ? 2.0 * M_PI * x : 0));
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x = (double)Buffer[tr].States[i + 1].account[7] / (double)PeriodSeconds(PERIOD_MN1);
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bNextAccount.Add((float)MathCos(x != 0 ? 2.0 * M_PI * x : 0));
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x = (double)Buffer[tr].States[i + 1].account[7] / (double)PeriodSeconds(PERIOD_W1);
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bNextAccount.Add((float)MathSin(x != 0 ? 2.0 * M_PI * x : 0));
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x = (double)Buffer[tr].States[i + 1].account[7] / (double)PeriodSeconds(PERIOD_D1);
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bNextAccount.Add((float)MathSin(x != 0 ? 2.0 * M_PI * x : 0));
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//---
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bState.AssignArray(Buffer[tr].States[i].state);
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PrevBalance = Buffer[tr].States[MathMax(i - 1, 0)].account[0];
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PrevEquity = Buffer[tr].States[MathMax(i - 1, 0)].account[1];
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bAccount.Clear();
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bAccount.Add((Buffer[tr].States[i].account[0] - PrevBalance) / PrevBalance);
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bAccount.Add(Buffer[tr].States[i].account[1] / PrevBalance);
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bAccount.Add((Buffer[tr].States[i].account[1] - PrevEquity) / PrevEquity);
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bAccount.Add(Buffer[tr].States[i].account[2]);
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bAccount.Add(Buffer[tr].States[i].account[3]);
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bAccount.Add(Buffer[tr].States[i].account[4] / PrevBalance);
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bAccount.Add(Buffer[tr].States[i].account[5] / PrevBalance);
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bAccount.Add(Buffer[tr].States[i].account[6] / PrevBalance);
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x = (double)Buffer[tr].States[i].account[7] / (double)(D'2024.01.01' - D'2023.01.01');
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bAccount.Add((float)MathSin(x != 0 ? 2.0 * M_PI * x : 0));
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x = (double)Buffer[tr].States[i].account[7] / (double)PeriodSeconds(PERIOD_MN1);
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bAccount.Add((float)MathCos(x != 0 ? 2.0 * M_PI * x : 0));
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x = (double)Buffer[tr].States[i].account[7] / (double)PeriodSeconds(PERIOD_W1);
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bAccount.Add((float)MathSin(x != 0 ? 2.0 * M_PI * x : 0));
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x = (double)Buffer[tr].States[i].account[7] / (double)PeriodSeconds(PERIOD_D1);
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bAccount.Add((float)MathSin(x != 0 ? 2.0 * M_PI * x : 0));
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//---
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bActions.AssignArray(Buffer[tr].States[i].action);
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vector<float> log_prob;
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log_prob.Assign(Buffer[tr].States[i].log_prob);
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//---
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if(!Net.Study(GetPointer(bState), GetPointer(bAccount), GetPointer(bActions), log_prob,
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GetPointer(bNextState), GetPointer(bNextAccount),
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Buffer[tr].Revards[i] - DiscFactor * Buffer[tr].Revards[i + 1], DiscFactor, Tau))
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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(GetTickCount() - ticks > 500)
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{
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float loss1, loss2;
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Net.GetLoss(loss1, loss2);
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string str = StringFormat("%-15s %5.2f%% -> Error %15.8f\n", "Critic1", iter * 100.0 / (double)(Iterations), loss1);
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str += StringFormat("%-15s %5.2f%% -> Error %15.8f\n", "Critic2", iter * 100.0 / (double)(Iterations), loss2);
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Comment(str);
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ticks = GetTickCount();
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}
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}
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Comment("");
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//---
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float loss1, loss2;
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Net.GetLoss(loss1, loss2);
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PrintFormat("%s -> %d -> %-15s %10.7f", __FUNCTION__, __LINE__, "Critic1", loss1);
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PrintFormat("%s -> %d -> %-15s %10.7f", __FUNCTION__, __LINE__, "Critic2", loss2);
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ExpertRemove();
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//---
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}
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//+------------------------------------------------------------------+
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