//+------------------------------------------------------------------+ //| 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 = 10000; //+------------------------------------------------------------------+ //| | //+------------------------------------------------------------------+ STrajectory Buffer[]; CNet BLEncoder; CNet BLEndpoints; CNet BLProbability; CNet StateEncoder; CNet EndpointEncoder; CNet Actor; //--- float dError; datetime dtStudied; //--- CBufferFloat bState; CBufferFloat bAccount; CBufferFloat bGradient; CBufferFloat bProbs; CBufferFloat *Result; vector check; vector STD_Actor; vector STD_Goal; //--- 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(!BLEncoder.Load(FileName + "Enc.nnw", temp, temp, temp, dtStudied, true) || !BLEndpoints.Load(FileName + "Endp.nnw", temp, temp, temp, dtStudied, true) || !BLProbability.Load(FileName + "Prob.nnw", temp, temp, temp, dtStudied, true) ) { CArrayObj *encoder = new CArrayObj(); CArrayObj *endpoint = new CArrayObj(); CArrayObj *prob = new CArrayObj(); if(!CreateTrajNetDescriptions(encoder, endpoint, prob)) { delete endpoint; delete prob; delete encoder; return INIT_FAILED; } if(!BLEncoder.Create(encoder) || !BLEndpoints.Create(endpoint) || !BLProbability.Create(prob)) { delete endpoint; delete prob; delete encoder; return INIT_FAILED; } delete endpoint; delete prob; delete encoder; } //--- if(!StateEncoder.Load(FileName + "StEnc.nnw", temp, temp, temp, dtStudied, true) || !EndpointEncoder.Load(FileName + "EndEnc.nnw", temp, temp, temp, dtStudied, true) || !Actor.Load(FileName + "Act.nnw", temp, temp, temp, dtStudied, true)) { CArrayObj *actor = new CArrayObj(); CArrayObj *endpoint = new CArrayObj(); CArrayObj *encoder = new CArrayObj(); if(!CreateDescriptions(actor, endpoint, encoder)) { delete actor; delete endpoint; delete encoder; return INIT_FAILED; } if(!Actor.Create(actor) || !StateEncoder.Create(encoder) || !EndpointEncoder.Create(endpoint)) { delete actor; delete endpoint; delete encoder; return INIT_FAILED; } delete actor; delete endpoint; delete encoder; //--- } //--- OpenCL = Actor.GetOpenCL(); StateEncoder.SetOpenCL(OpenCL); EndpointEncoder.SetOpenCL(OpenCL); BLEncoder.SetOpenCL(OpenCL); BLEndpoints.SetOpenCL(OpenCL); BLProbability.SetOpenCL(OpenCL); //--- Actor.getResults(Result); if(Result.Total() != NActions) { PrintFormat("The scope of the actor does not match the actions count (%d <> %d)", NActions, Result.Total()); return INIT_FAILED; } //--- BLEndpoints.getResults(Result); if(Result.Total() != 3 * NForecast) { PrintFormat("The scope of the Endpoints does not match forecast endpoints (%d <> %d)", 3 * NForecast, Result.Total()); return INIT_FAILED; } //--- BLEncoder.GetLayerOutput(0, Result); if(Result.Total() != (HistoryBars * BarDescr)) { PrintFormat("Input size of Encoder doesn't match state description (%d <> %d)", Result.Total(), (HistoryBars * BarDescr)); return INIT_FAILED; } //--- if(!bGradient.BufferInit(MathMax(AccountDescr, NForecast), 0) || !bGradient.BufferCreate(OpenCL)) { PrintFormat("Error of create buffers: %d", GetLastError()); return INIT_FAILED; } //--- 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)) { Actor.Save(FileName + "Act.nnw", 0, 0, 0, TimeCurrent(), true); StateEncoder.Save(FileName + "StEnc.nnw", 0, 0, 0, TimeCurrent(), true); EndpointEncoder.Save(FileName + "EndEnc.nnw", 0, 0, 0, TimeCurrent(), true); BLEncoder.Save(FileName + "Enc.nnw", 0, 0, 0, TimeCurrent(), true); BLEndpoints.Save(FileName + "Endp.nnw", 0, 0, 0, TimeCurrent(), true); BLProbability.Save(FileName + "Prob.nnw", 0, 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 probability = GetProbTrajectories(Buffer, 0.9); //--- vector result, target; matrix targets, temp_m; bool Stop = false; //--- uint ticks = GetTickCount(); //--- for(int iter = 0; (iter < Iterations && !IsStopped() && !Stop); iter ++) { int tr = SampleTrajectory(probability); int batch = GPTBars + 48; int state = (int)((MathRand() * MathRand() / MathPow(32767, 2)) * (Buffer[tr].Total - 2 - PrecoderBars - batch)); if(state <= 0) { iter--; continue; } BLEncoder.Clear(); BLEndpoints.Clear(); int end = MathMin(state + batch, Buffer[tr].Total - PrecoderBars); for(int i = state; i < end; i++) { bState.AssignArray(Buffer[tr].States[i].state); //--- Trajectory if(!BLEncoder.feedForward((CBufferFloat*)GetPointer(bState), 1, false, (CBufferFloat*)NULL)) { PrintFormat("%s -> %d", __FUNCTION__, __LINE__); Stop = true; break; } if(!BLEndpoints.feedForward((CNet*)GetPointer(BLEncoder), -1, (CBufferFloat*)NULL)) { PrintFormat("%s -> %d", __FUNCTION__, __LINE__); Stop = true; break; } if(!BLProbability.feedForward((CNet*)GetPointer(BLEncoder), -1, (CNet*)GetPointer(BLEndpoints))) { PrintFormat("%s -> %d", __FUNCTION__, __LINE__); Stop = true; break; } //--- targets = matrix::Zeros(PrecoderBars, 3); for(int t = 0; t < PrecoderBars; t++) { target.Assign(Buffer[tr].States[i + 1 + t].state); if(target.Size() > BarDescr) { matrix temp(1, target.Size()); temp.Row(target, 0); temp.Reshape(target.Size() / BarDescr, BarDescr); temp.Resize(temp.Rows(), 3); target = temp.Row(temp.Rows() - 1); } targets.Row(target, t); } target = targets.Col(0).CumSum(); targets.Col(target, 0); targets.Col(target + targets.Col(1), 1); targets.Col(target + targets.Col(2), 2); int direct = (Buffer[tr].States[i].state[8] >= Buffer[tr].States[i].state[7] ? 1 : -1); ulong extr = (direct > 0 ? target.ArgMax() : target.ArgMin()); if(extr == 0) { direct = -direct; extr = (direct > 0 ? target.ArgMax() : target.ArgMin()); } targets.Resize(extr + 1, 3); if(direct >= 0) { target = targets.Max(AXIS_HORZ); target[2] = targets.Col(2).Min(); } else { target = targets.Min(AXIS_HORZ); target[1] = targets.Col(1).Max(); } //--- BLEndpoints.getResults(result); targets.Reshape(1, result.Size()); targets.Row(result, 0); targets.Reshape(NForecast, 3); temp_m = targets; for(int i = 0; i < 3; i++) temp_m.Col(temp_m.Col(i) - target[i], i); temp_m = MathPow(temp_m, 2.0f); ulong pos = temp_m.Sum(AXIS_VERT).ArgMin(); targets.Row(target, pos); Result.AssignArray(targets); //--- if(!BLEndpoints.backProp(Result, (CBufferFloat*)NULL)) { PrintFormat("%s -> %d", __FUNCTION__, __LINE__); Stop = true; break; } if(!BLEncoder.backPropGradient((CBufferFloat*)NULL)) { PrintFormat("%s -> %d", __FUNCTION__, __LINE__); Stop = true; break; } bProbs.AssignArray(vector::Zeros(NForecast)); bProbs.Update((int)pos, 1); bProbs.BufferWrite(); if(!BLProbability.backProp(GetPointer(bProbs), GetPointer(BLEndpoints))) { PrintFormat("%s -> %d", __FUNCTION__, __LINE__); Stop = true; break; } //--- Policy float PrevBalance = Buffer[tr].States[MathMax(i - 1, 0)].account[0]; float 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); double time = (double)Buffer[tr].States[i].account[7]; double x = time / (double)(D'2024.01.01' - D'2023.01.01'); bAccount.Add((float)MathSin(x != 0 ? 2.0 * M_PI * x : 0)); x = time / (double)PeriodSeconds(PERIOD_MN1); bAccount.Add((float)MathCos(x != 0 ? 2.0 * M_PI * x : 0)); x = time / (double)PeriodSeconds(PERIOD_W1); bAccount.Add((float)MathSin(x != 0 ? 2.0 * M_PI * x : 0)); x = time / (double)PeriodSeconds(PERIOD_D1); bAccount.Add((float)MathSin(x != 0 ? 2.0 * M_PI * x : 0)); if(bAccount.GetIndex() >= 0) bAccount.BufferWrite(); //--- State embedding if(!StateEncoder.feedForward((CNet *)GetPointer(BLEncoder), -1, (CBufferFloat*)GetPointer(bAccount))) { PrintFormat("%s -> %d", __FUNCTION__, __LINE__); Stop = true; break; } //--- Endpoint embedding if(!EndpointEncoder.feedForward((CNet *)GetPointer(BLEndpoints), -1, (CNet*)GetPointer(BLProbability))) { PrintFormat("%s -> %d", __FUNCTION__, __LINE__); Stop = true; break; } //--- Actor if(!Actor.feedForward((CNet *)GetPointer(StateEncoder), -1, (CNet*)GetPointer(EndpointEncoder))) { PrintFormat("%s -> %d", __FUNCTION__, __LINE__); Stop = true; break; } result = vector::Zeros(NActions); double value = SymbolInfoDouble(_Symbol, SYMBOL_TRADE_TICK_VALUE_LOSS); double risk = AccountInfoDouble(ACCOUNT_EQUITY) * 0.01; if(direct > 0) { if(Buffer[tr].States[i].state[4] > 30 && Buffer[tr].States[i].state[5] > -100 ) { float tp = float(target[1] / _Point / MaxTP); result[1] = tp; int sl = int(MathMax(MathMax(target[1] / 3, -target[2]) / _Point, MaxSL / 10)); result[2] = float(sl) / MaxSL; result[0] = float(MathMax(risk / (value * sl), 0.01)) + FLT_EPSILON; } } else { if(Buffer[tr].States[i].state[4] < 70 && Buffer[tr].States[i].state[5] < 100 ) { float tp = float((-target[2]) / _Point / MaxTP); result[4] = tp; int sl = int(MathMax(MathMax((-target[2]) / 3, target[1]) / _Point, MaxSL / 10)); result[5] = float(sl) / MaxSL; result[3] = float(MathMax(risk / (value * sl), 0.01)) + FLT_EPSILON; } } Result.AssignArray(result); if(!Actor.backProp(Result, (CNet *)GetPointer(EndpointEncoder)) || !StateEncoder.backPropGradient(GetPointer(bAccount), (CBufferFloat *)GetPointer(bGradient)) || !EndpointEncoder.backPropGradient((CNet*)GetPointer(BLProbability)) ) { PrintFormat("%s -> %d", __FUNCTION__, __LINE__); Stop = true; break; } if(!BLEncoder.backPropGradient((CBufferFloat*)NULL)) { PrintFormat("%s -> %d", __FUNCTION__, __LINE__); Stop = true; break; } //--- if(GetTickCount() - ticks > 500) { double percent = (double(i - state) / ((end - state)) + iter) * 100.0 / (Iterations); string str = StringFormat("%-14s %6.2f%% -> Error %15.8f\n", "Actor", percent, Actor.getRecentAverageError()); str += StringFormat("%-14s %6.2f%% -> Error %15.8f\n", "Endpoints", percent, BLEndpoints.getRecentAverageError()); str += StringFormat("%-14s %6.2f%% -> Error %15.8f\n", "Probability", percent, BLProbability.getRecentAverageError()); Comment(str); ticks = GetTickCount(); } } } Comment(""); //--- PrintFormat("%s -> %d -> %-15s %10.7f", __FUNCTION__, __LINE__, "Actor", Actor.getRecentAverageError()); PrintFormat("%s -> %d -> %-15s %10.7f", __FUNCTION__, __LINE__, "Endpoints", BLEndpoints.getRecentAverageError()); PrintFormat("%s -> %d -> %-15s %10.7f", __FUNCTION__, __LINE__, "Probability", BLProbability.getRecentAverageError()); ExpertRemove(); //--- } //+------------------------------------------------------------------+