NN_in_Trading/Experts/StockFormer/Study1.mq5

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<EFBFBD><EFBFBD>//+------------------------------------------------------------------+
//| Study.mq5 |
//| Copyright DNG<EFBFBD> |
//| https://www.mql5.com/ru/users/dng |
//+------------------------------------------------------------------+
#property copyright "Copyright DNG<00>"
#property link "https://www.mql5.com/ru/users/dng"
#property version "1.00"
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
#define Study
#include "Trajectory.mqh"
//+------------------------------------------------------------------+
//| Input parameters |
//+------------------------------------------------------------------+
input int Iterations = 100000;
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
STrajectory Buffer[];
CNet RelateEncoder;
CNet RelateDecoder;
CNet ShortEncoder;
CNet ShortDecoder;
CNet LongEncoder;
CNet LongDecoder;
//---
float dError;
datetime dtStudied;
//---
CBufferFloat bState;
CBufferFloat bShort;
CBufferFloat bLong;
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 = 0;
if(!RelateEncoder.Load(FileName + "RelE.nnw", temp, temp, temp, dtStudied, true) ||
!RelateDecoder.Load(FileName + "RelD.nnw", temp, temp, temp, dtStudied, true)
)
{
Print("Create new Relate models");
CArrayObj *encoder = new CArrayObj();
CArrayObj *decoder = new CArrayObj();
if(!CreateRelationDescriptions(encoder, decoder))
{
delete encoder;
delete decoder;
return INIT_FAILED;
}
if(!RelateEncoder.Create(encoder) ||
!RelateDecoder.Create(decoder))
{
delete encoder;
delete decoder;
return INIT_FAILED;
}
delete encoder;
delete decoder;
}
//---
if(!ShortEncoder.Load(FileName + "ShE.nnw", temp, temp, temp, dtStudied, true) ||
!ShortDecoder.Load(FileName + "ShD.nnw", temp, temp, temp, dtStudied, true)
)
{
Print("Create new Short predict models");
CArrayObj *encoder = new CArrayObj();
CArrayObj *decoder = new CArrayObj();
if(!CreatePredictionDescriptions(encoder, decoder))
{
delete encoder;
delete decoder;
return INIT_FAILED;
}
if(!ShortEncoder.Create(encoder) ||
!ShortDecoder.Create(decoder))
{
delete encoder;
delete decoder;
return INIT_FAILED;
}
delete encoder;
delete decoder;
}
//---
if(!LongEncoder.Load(FileName + "LnE.nnw", temp, temp, temp, dtStudied, true) ||
!LongDecoder.Load(FileName + "LnD.nnw", temp, temp, temp, dtStudied, true)
)
{
Print("Create new Long predict models");
CArrayObj *encoder = new CArrayObj();
CArrayObj *decoder = new CArrayObj();
if(!CreatePredictionDescriptions(encoder, decoder))
{
delete encoder;
delete decoder;
return INIT_FAILED;
}
if(!LongEncoder.Create(encoder) ||
!LongDecoder.Create(decoder))
{
delete encoder;
delete decoder;
return INIT_FAILED;
}
delete encoder;
delete decoder;
}
//---
RelateEncoder.TrainMode(true);
RelateDecoder.TrainMode(true);
ShortEncoder.TrainMode(true);
ShortDecoder.TrainMode(true);
LongEncoder.TrainMode(true);
LongDecoder.TrainMode(true);
//---
OpenCL = RelateEncoder.GetOpenCL();
RelateDecoder.SetOpenCL(OpenCL);
ShortEncoder.SetOpenCL(OpenCL);
ShortDecoder.SetOpenCL(OpenCL);
LongEncoder.SetOpenCL(OpenCL);
LongDecoder.SetOpenCL(OpenCL);
//---
RelateDecoder.getResults(Result);
if(Result.Total() != MathMin(HistoryBars, 100)*BarDescr)
{
PrintFormat("The scope of the Decoder does not match the actions count (%d <> %d)", MathMin(HistoryBars, 100)*BarDescr, Result.Total());
return INIT_FAILED;
}
//---
RelateEncoder.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(!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))
{
RelateEncoder.Save(FileName + "RelE.nnw", 0, 0, 0, TimeCurrent(), true);
RelateDecoder.Save(FileName + "RelD.nnw", 0, 0, 0, TimeCurrent(), true);
ShortEncoder.Save(FileName + "ShE.nnw", 0, 0, 0, TimeCurrent(), true);
ShortDecoder.Save(FileName + "ShD.nnw", 0, 0, 0, TimeCurrent(), true);
LongEncoder.Save(FileName + "LnE.nnw", 0, 0, 0, TimeCurrent(), true);
LongDecoder.Save(FileName + "LnD.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<float> probability = GetProbTrajectories(Buffer, 0.9);
//---
vector<float> result, target, state;
matrix<float> predict;
bool Stop = false;
//---
uint ticks = GetTickCount();
//---
for(int iter = 0; (iter < Iterations && !IsStopped() && !Stop); iter ++)
{
int tr = SampleTrajectory(probability);
int i = (int)((MathRand() * MathRand() / MathPow(32767, 2)) * (Buffer[tr].Total - 2 - NForecast));
if(i <= 0)
{
iter --;
continue;
}
if(!state.Assign(Buffer[tr].States[i].state) ||
MathAbs(state).Sum() == 0 ||
!bState.AssignArray(state))
{
iter --;
continue;
}
if(!state.Assign(Buffer[tr].States[i + NForecast].state) ||
!state.Resize((NForecast + 1)*BarDescr) ||
MathAbs(state).Sum() == 0)
{
iter --;
continue;
}
//--- Feed Forward
if(!RelateEncoder.feedForward((CBufferFloat*)GetPointer(bState), 1, false, (CBufferFloat*)NULL) ||
!RelateDecoder.feedForward((CBufferFloat*)GetPointer(bState), 1, false, (CNet*)GetPointer(RelateEncoder)) ||
!ShortEncoder.feedForward((CBufferFloat*)GetPointer(bState), 1, false, (CBufferFloat*)NULL) ||
!ShortDecoder.feedForward((CBufferFloat*)GetPointer(bState), 1, false, (CNet*)GetPointer(ShortEncoder)) ||
!LongEncoder.feedForward((CBufferFloat*)GetPointer(bState), 1, false, (CBufferFloat*)NULL) ||
!LongDecoder.feedForward((CBufferFloat*)GetPointer(bState), 1, false, (CNet*)GetPointer(LongEncoder)))
{
PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
Stop = true;
break;
}
//--- Relation
if(!RelateDecoder.backProp(GetPointer(bState), (CNet *)GetPointer(RelateEncoder)) ||
!RelateEncoder.backPropGradient((CBufferFloat*)NULL))
{
PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
Stop = true;
break;
}
//--- Prediction
if(!predict.Resize(1, state.Size()) ||
!predict.Row(state, 0) ||
!predict.Reshape(NForecast + 1, BarDescr)
)
{
iter --;
continue;
}
result = MathAbs(predict).Max(0);
target = (predict.Row(NForecast - 1) - predict.Row(NForecast)) / result;
if(!bShort.AssignArray(target))
{
PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
Stop = true;
break;
}
for(int i = 0; i < NForecast - 1; i++)
target += (predict.Row(i) - predict.Row(i + 1)) / result *
MathPow(DiscFactor, NForecast - i - 1);
if(!bLong.AssignArray(target))
{
PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
Stop = true;
break;
}
//--- Short prediction
if(!ShortDecoder.backProp(GetPointer(bShort), (CNet *)GetPointer(ShortEncoder)) ||
!ShortEncoder.backPropGradient((CBufferFloat*)NULL))
{
PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
Stop = true;
break;
}
//--- Long prediction
if(!LongDecoder.backProp(GetPointer(bLong), (CNet *)GetPointer(LongEncoder)) ||
!LongEncoder.backPropGradient((CBufferFloat*)NULL))
{
PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
Stop = true;
break;
}
//---
if(GetTickCount() - ticks > 500)
{
double percent = double(iter) * 100.0 / (Iterations);
string str = StringFormat("%-14s %6.2f%% -> Error %15.8f\n", "Relate", percent, RelateDecoder.getRecentAverageError());
str += StringFormat("%-14s %6.2f%% -> Error %15.8f\n", "Short", percent, ShortDecoder.getRecentAverageError());
str += StringFormat("%-14s %6.2f%% -> Error %15.8f\n", "Long", percent, LongDecoder.getRecentAverageError());
Comment(str);
ticks = GetTickCount();
}
}
Comment("");
//---
PrintFormat("%s -> %d -> %-15s %10.7f", __FUNCTION__, __LINE__, "Relate", RelateDecoder.getRecentAverageError());
PrintFormat("%s -> %d -> %-15s %10.7f", __FUNCTION__, __LINE__, "Short", ShortDecoder.getRecentAverageError());
PrintFormat("%s -> %d -> %-15s %10.7f", __FUNCTION__, __LINE__, "Long", LongDecoder.getRecentAverageError());
ExpertRemove();
//---
}
//+------------------------------------------------------------------+