| //+------------------------------------------------------------------+
|
| //| 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 Study
|
| #include "Trajectory.mqh"
|
| //+------------------------------------------------------------------+
|
| //| Input parameters |
|
| //+------------------------------------------------------------------+
|
| input int Iterations = 1e6;
|
| //+------------------------------------------------------------------+
|
| //| |
|
| //+------------------------------------------------------------------+
|
| STrajectory Buffer[];
|
| CNet StateEncoder;
|
| CNet Critic1;
|
| CNet Critic2;
|
| //---
|
| float dError;
|
| datetime dtStudied;
|
| //---
|
| CBufferFloat State;
|
| CBufferFloat Account;
|
| CBufferFloat Actions;
|
| CBufferFloat Gradient;
|
| CBufferFloat *Result;
|
| //---
|
| COpenCLMy *OpenCL;
|
| //+------------------------------------------------------------------+
|
| //| Expert initialization function |
|
| //+------------------------------------------------------------------+
|
| int OnInit()
|
| {
|
| //---
|
| ResetLastError();
|
| if(!LoadTotalBase())
|
| {
|
| PrintFormat("Error of load study data: %d", GetLastError());
|
| return INIT_FAILED;
|
| }
|
| //--- load models
|
| float temp;
|
| if(!StateEncoder.Load(FileName + "Enc.nnw", temp, temp, temp, dtStudied, true) ||
|
| !Critic1.Load(FileName + "Crt1.nnw", temp, temp, temp, dtStudied, true) ||
|
| !Critic2.Load(FileName + "Crt2.nnw", temp, temp, temp, dtStudied, true))
|
| {
|
| Print("Init new models");
|
| CArrayObj *actor = new CArrayObj();
|
| CArrayObj *critic = new CArrayObj();
|
| CArrayObj *encoder = new CArrayObj();
|
| if(!CreateDescriptions(actor, critic, encoder))
|
| {
|
| delete actor;
|
| delete critic;
|
| delete encoder;
|
| return INIT_FAILED;
|
| }
|
| if(!Critic1.Create(critic) || !Critic2.Create(critic) ||
|
| !StateEncoder.Create(encoder))
|
| {
|
| delete actor;
|
| delete critic;
|
| delete encoder;
|
| return INIT_FAILED;
|
| }
|
| delete actor;
|
| delete critic;
|
| delete encoder;
|
| //---
|
| }
|
| //---
|
| OpenCL = Critic1.GetOpenCL();
|
| Critic2.SetOpenCL(OpenCL);
|
| StateEncoder.SetOpenCL(OpenCL);
|
| //---
|
| StateEncoder.getResults(Result);
|
| if(Result.Total() != LatentCount)
|
| {
|
| PrintFormat("The scope of the State Encoder does not match the latent size count (%d <> %d)", LatentCount, Result.Total());
|
| return INIT_FAILED;
|
| }
|
| //---
|
| StateEncoder.GetLayerOutput(0, Result);
|
| if(Result.Total() != (HistoryBars * BarDescr))
|
| {
|
| PrintFormat("Input size of State Encoder doesn't match state description (%d <> %d)", Result.Total(), (HistoryBars * BarDescr));
|
| return INIT_FAILED;
|
| }
|
| //---
|
| Critic1.GetLayerOutput(0, Result);
|
| if(Result.Total() != LatentCount)
|
| {
|
| PrintFormat("Input size of Critic1 doesn't match State Encoder output (%d <> %d)", Result.Total(), LatentCount);
|
| return INIT_FAILED;
|
| }
|
| //---
|
| Critic2.GetLayerOutput(0, Result);
|
| if(Result.Total() != LatentCount)
|
| {
|
| PrintFormat("Input size of Critic2 doesn't match State Encoder output (%d <> %d)", Result.Total(), LatentCount);
|
| return INIT_FAILED;
|
| }
|
| //---
|
| Gradient.BufferInit(AccountDescr, 0);
|
| //---
|
| 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)
|
| {
|
| //---
|
| if(!(reason == REASON_INITFAILED || reason == REASON_RECOMPILE))
|
| {
|
| StateEncoder.Save(FileName + "Enc.nnw", 0, 0, 0, TimeCurrent(), true);
|
| Critic1.Save(FileName + "Crt1.nnw", Critic1.getRecentAverageError(), 0, 0, TimeCurrent(), true);
|
| Critic2.Save(FileName + "Crt2.nnw", Critic2.getRecentAverageError(), 0, 0, TimeCurrent(), true);
|
| }
|
| delete Result;
|
| delete OpenCL;
|
| }
|
| //+------------------------------------------------------------------+
|
| //| 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)
|
| {
|
| //---
|
| vector<float> probability = GetProbTrajectories(Buffer, 0.9);
|
| //---
|
| vector<float> rewards, rewards1, rewards2, target_reward;
|
| uint ticks = GetTickCount();
|
| //---
|
| for(int iter = 0; (iter < Iterations && !IsStopped()); iter ++)
|
| {
|
| int tr = SampleTrajectory(probability);
|
| int i = (int)((MathRand() * MathRand() / MathPow(32767, 2)) * (Buffer[tr].Total - 3));
|
| if(i < 0)
|
| {
|
| iter--;
|
| continue;
|
| }
|
| //--- Q-function study
|
| State.AssignArray(Buffer[tr].States[i].state);
|
| float PrevBalance = Buffer[tr].States[MathMax(i - 1, 0)].account[0];
|
| float PrevEquity = Buffer[tr].States[MathMax(i - 1, 0)].account[1];
|
| Account.Clear();
|
| Account.Add((Buffer[tr].States[i].account[0] - PrevBalance) / PrevBalance);
|
| Account.Add(Buffer[tr].States[i].account[1] / PrevBalance);
|
| Account.Add((Buffer[tr].States[i].account[1] - PrevEquity) / PrevEquity);
|
| Account.Add(Buffer[tr].States[i].account[2]);
|
| Account.Add(Buffer[tr].States[i].account[3]);
|
| Account.Add(Buffer[tr].States[i].account[4] / PrevBalance);
|
| Account.Add(Buffer[tr].States[i].account[5] / PrevBalance);
|
| Account.Add(Buffer[tr].States[i].account[6] / PrevBalance);
|
| double time = (double)Buffer[tr].States[i].account[7];
|
| double x = time / (double)(D'2024.01.01' - D'2023.01.01');
|
| Account.Add((float)MathSin(x != 0 ? 2.0 * M_PI * x : 0));
|
| x = time / (double)PeriodSeconds(PERIOD_MN1);
|
| Account.Add((float)MathCos(x != 0 ? 2.0 * M_PI * x : 0));
|
| x = time / (double)PeriodSeconds(PERIOD_W1);
|
| Account.Add((float)MathSin(x != 0 ? 2.0 * M_PI * x : 0));
|
| x = time / (double)PeriodSeconds(PERIOD_D1);
|
| Account.Add((float)MathSin(x != 0 ? 2.0 * M_PI * x : 0));
|
| if(Account.GetIndex() >= 0)
|
| Account.BufferWrite();
|
| //---
|
| if(!StateEncoder.feedForward(GetPointer(State), 1, false, GetPointer(Account)))
|
| {
|
| PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
|
| break;
|
| }
|
| //---
|
| Actions.AssignArray(Buffer[tr].States[i].action);
|
| if(Actions.GetIndex() >= 0)
|
| Actions.BufferWrite();
|
| //---
|
| if(!Critic1.feedForward(GetPointer(StateEncoder), -1, GetPointer(Actions)) ||
|
| !Critic2.feedForward(GetPointer(StateEncoder), -1, GetPointer(Actions)))
|
| {
|
| PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
|
| break;
|
| }
|
| //---
|
| Critic1.getResults(rewards1);
|
| Critic2.getResults(rewards2);
|
| //---
|
| rewards.Assign(Buffer[tr].States[i + 1].rewards);
|
| target_reward.Assign(Buffer[tr].States[i + 2].rewards);
|
| rewards = rewards - target_reward * DiscFactor;
|
| Result.AssignArray(CAGrad(rewards - rewards1) + rewards1);
|
| if(!Critic1.backProp(Result, GetPointer(Actions), GetPointer(Gradient)) ||
|
| !StateEncoder.backPropGradient(GetPointer(Account), GetPointer(Gradient)))
|
| {
|
| PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
|
| break;
|
| }
|
| Result.AssignArray(CAGrad(rewards - rewards2) + rewards2);
|
| if(!Critic2.backProp(Result, GetPointer(Actions), GetPointer(Gradient)) ||
|
| !StateEncoder.backPropGradient(GetPointer(Account), GetPointer(Gradient)))
|
| {
|
| PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
|
| break;
|
| }
|
| //---
|
| if(GetTickCount() - ticks > 500)
|
| {
|
| string str = StringFormat("%-15s %5.2f%% -> Error %15.8f\n", "Critic1", iter * 100.0 / (double)(Iterations), Critic1.getRecentAverageError());
|
| str += StringFormat("%-15s %5.2f%% -> Error %15.8f\n", "Critic2", iter * 100.0 / (double)(Iterations), Critic2.getRecentAverageError());
|
| Comment(str);
|
| ticks = GetTickCount();
|
| }
|
| }
|
| Comment("");
|
| //---
|
| PrintFormat("%s -> %d -> %-15s %10.7f", __FUNCTION__, __LINE__, "Critic1", Critic1.getRecentAverageError());
|
| PrintFormat("%s -> %d -> %-15s %10.7f", __FUNCTION__, __LINE__, "Critic2", Critic2.getRecentAverageError());
|
| ExpertRemove();
|
| //---
|
| }
|
| //+------------------------------------------------------------------+
|
|
|
