| //+------------------------------------------------------------------+
|
| //| Study.mq5 |
|
| //| Copyright DNG® |
|
| //| https://www.mql5.com/ru/users/dng |
|
| //+------------------------------------------------------------------+
|
| #property copyright "Copyright DNG®"
|
| #property link "https://www.mql5.com/ru/users/dng"
|
| #property version "1.00"
|
| //+------------------------------------------------------------------+
|
| //| |
|
| //+------------------------------------------------------------------+
|
| #define StudyExpert
|
| #include "Trajectory.mqh"
|
| //+------------------------------------------------------------------+
|
| //| Input parameters |
|
| //+------------------------------------------------------------------+
|
| input int Iterations = 100000;
|
| input float Tau = 0.01f;
|
| //+------------------------------------------------------------------+
|
| //| |
|
| //+------------------------------------------------------------------+
|
| STrajectory Buffer[];
|
| CNet_SAC_DICE Net;
|
| //---
|
| float dError;
|
| datetime dtStudied;
|
| //---
|
| CBufferFloat bState;
|
| CBufferFloat bAccount;
|
| CBufferFloat bActions;
|
| CBufferFloat bNextState;
|
| CBufferFloat bNextAccount;
|
| //+------------------------------------------------------------------+
|
| //| Expert initialization function |
|
| //+------------------------------------------------------------------+
|
| int OnInit()
|
| {
|
| //---
|
| ResetLastError();
|
| if(!LoadTotalBase())
|
| {
|
| PrintFormat("Error of load study data: %d", GetLastError());
|
| return INIT_FAILED;
|
| }
|
| //--- load models
|
| if(!Net.Load(FileName, true))
|
| {
|
| CArrayObj *actor = new CArrayObj();
|
| CArrayObj *critic = new CArrayObj();
|
| if(!CreateDescriptions(actor, critic))
|
| {
|
| delete actor;
|
| delete critic;
|
| return INIT_FAILED;
|
| }
|
| if(!Net.Create(actor, critic, critic, critic, LatentLayer))
|
| {
|
| delete actor;
|
| delete critic;
|
| return INIT_FAILED;
|
| }
|
| delete actor;
|
| delete critic;
|
| }
|
| //---
|
| if(!EventChartCustom(ChartID(), 1, 0, 0, "Init"))
|
| {
|
| PrintFormat("Error of create study event: %d", GetLastError());
|
| return INIT_FAILED;
|
| }
|
| //---
|
| return(INIT_SUCCEEDED);
|
| }
|
| //+------------------------------------------------------------------+
|
| //| Expert deinitialization function |
|
| //+------------------------------------------------------------------+
|
| void OnDeinit(const int reason)
|
| {
|
| //---
|
| Net.Save(FileName, true);
|
| }
|
| //+------------------------------------------------------------------+
|
| //| ChartEvent function |
|
| //+------------------------------------------------------------------+
|
| void OnChartEvent(const int id,
|
| const long &lparam,
|
| const double &dparam,
|
| const string &sparam)
|
| {
|
| //---
|
| if(id == 1001)
|
| Train();
|
| }
|
| //+------------------------------------------------------------------+
|
| //| Train function |
|
| //+------------------------------------------------------------------+
|
| void Train(void)
|
| {
|
| int total_tr = ArraySize(Buffer);
|
| uint ticks = GetTickCount();
|
| //---
|
| for(int iter = 0; (iter < Iterations && !IsStopped()); iter ++)
|
| {
|
| int tr = (int)((MathRand() / 32767.0) * (total_tr - 1));
|
| int i = (int)((MathRand() * MathRand() / MathPow(32767, 2)) * (Buffer[tr].Total - 2));
|
| if(i<0)
|
| {
|
| iter--;
|
| continue;
|
| }
|
| //--- Target
|
| bNextState.AssignArray(Buffer[tr].States[i + 1].state);
|
| float PrevBalance = Buffer[tr].States[i].account[0];
|
| float PrevEquity = Buffer[tr].States[i].account[1];
|
| if(PrevBalance==0)
|
| {
|
| iter--;
|
| continue;
|
| }
|
| bNextAccount.Clear();
|
| bNextAccount.Add((Buffer[tr].States[i + 1].account[0] - PrevBalance) / PrevBalance);
|
| bNextAccount.Add(Buffer[tr].States[i + 1].account[1] / PrevBalance);
|
| bNextAccount.Add((Buffer[tr].States[i + 1].account[1] - PrevEquity) / PrevEquity);
|
| bNextAccount.Add(Buffer[tr].States[i + 1].account[2]);
|
| bNextAccount.Add(Buffer[tr].States[i + 1].account[3]);
|
| bNextAccount.Add(Buffer[tr].States[i + 1].account[4] / PrevBalance);
|
| bNextAccount.Add(Buffer[tr].States[i + 1].account[5] / PrevBalance);
|
| bNextAccount.Add(Buffer[tr].States[i + 1].account[6] / PrevBalance);
|
| double x = (double)Buffer[tr].States[i + 1].account[7] / (double)(D'2024.01.01' - D'2023.01.01');
|
| bNextAccount.Add((float)MathSin(x != 0 ? 2.0 * M_PI * x : 0));
|
| x = (double)Buffer[tr].States[i + 1].account[7] / (double)PeriodSeconds(PERIOD_MN1);
|
| bNextAccount.Add((float)MathCos(x != 0 ? 2.0 * M_PI * x : 0));
|
| x = (double)Buffer[tr].States[i + 1].account[7] / (double)PeriodSeconds(PERIOD_W1);
|
| bNextAccount.Add((float)MathSin(x != 0 ? 2.0 * M_PI * x : 0));
|
| x = (double)Buffer[tr].States[i + 1].account[7] / (double)PeriodSeconds(PERIOD_D1);
|
| bNextAccount.Add((float)MathSin(x != 0 ? 2.0 * M_PI * x : 0));
|
| //---
|
| bState.AssignArray(Buffer[tr].States[i].state);
|
| PrevBalance = Buffer[tr].States[MathMax(i - 1, 0)].account[0];
|
| PrevEquity = Buffer[tr].States[MathMax(i - 1, 0)].account[1];
|
| bAccount.Clear();
|
| bAccount.Add((Buffer[tr].States[i].account[0] - PrevBalance) / PrevBalance);
|
| bAccount.Add(Buffer[tr].States[i].account[1] / PrevBalance);
|
| bAccount.Add((Buffer[tr].States[i].account[1] - PrevEquity) / PrevEquity);
|
| bAccount.Add(Buffer[tr].States[i].account[2]);
|
| bAccount.Add(Buffer[tr].States[i].account[3]);
|
| bAccount.Add(Buffer[tr].States[i].account[4] / PrevBalance);
|
| bAccount.Add(Buffer[tr].States[i].account[5] / PrevBalance);
|
| bAccount.Add(Buffer[tr].States[i].account[6] / PrevBalance);
|
| x = (double)Buffer[tr].States[i].account[7] / (double)(D'2024.01.01' - D'2023.01.01');
|
| bAccount.Add((float)MathSin(x != 0 ? 2.0 * M_PI * x : 0));
|
| x = (double)Buffer[tr].States[i].account[7] / (double)PeriodSeconds(PERIOD_MN1);
|
| bAccount.Add((float)MathCos(x != 0 ? 2.0 * M_PI * x : 0));
|
| x = (double)Buffer[tr].States[i].account[7] / (double)PeriodSeconds(PERIOD_W1);
|
| bAccount.Add((float)MathSin(x != 0 ? 2.0 * M_PI * x : 0));
|
| x = (double)Buffer[tr].States[i].account[7] / (double)PeriodSeconds(PERIOD_D1);
|
| bAccount.Add((float)MathSin(x != 0 ? 2.0 * M_PI * x : 0));
|
| //---
|
| bActions.AssignArray(Buffer[tr].States[i].action);
|
| vector<float> log_prob;
|
| log_prob.Assign(Buffer[tr].States[i].log_prob);
|
| //---
|
| if(!Net.Study(GetPointer(bState), GetPointer(bAccount), GetPointer(bActions), log_prob,
|
| GetPointer(bNextState), GetPointer(bNextAccount),
|
| Buffer[tr].Revards[i] - DiscFactor * Buffer[tr].Revards[i + 1], DiscFactor, Tau))
|
| {
|
| PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
|
| break;
|
| }
|
| //---
|
| if(GetTickCount() - ticks > 500)
|
| {
|
| float loss1, loss2;
|
| Net.GetLoss(loss1, loss2);
|
| string str = StringFormat("%-15s %5.2f%% -> Error %15.8f\n", "Critic1", iter * 100.0 / (double)(Iterations), loss1);
|
| str += StringFormat("%-15s %5.2f%% -> Error %15.8f\n", "Critic2", iter * 100.0 / (double)(Iterations), loss2);
|
| Comment(str);
|
| ticks = GetTickCount();
|
| }
|
| }
|
| Comment("");
|
| //---
|
| float loss1, loss2;
|
| Net.GetLoss(loss1, loss2);
|
| PrintFormat("%s -> %d -> %-15s %10.7f", __FUNCTION__, __LINE__, "Critic1", loss1);
|
| PrintFormat("%s -> %d -> %-15s %10.7f", __FUNCTION__, __LINE__, "Critic2", loss2);
|
| ExpertRemove();
|
| //---
|
| }
|
| //+------------------------------------------------------------------+
|
|
|
