NN_in_Trading/Experts/RevIN/StudyEncoder.mq5

169 Zeilen
12 KiB
MQL5

2026-03-12 15:02:23 +02:00
<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 = 10000;
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
STrajectory Buffer[];
CNet Encoder;
//---
float dError;
datetime dtStudied;
//---
CBufferFloat bState;
CBufferFloat *Result;
vector<float> check;
//+------------------------------------------------------------------+
//| Expert initialization function |
//+------------------------------------------------------------------+
int OnInit()
{
//---
ResetLastError();
if(!LoadTotalBase())
{
PrintFormat("Error of load study data: %d", GetLastError());
return INIT_FAILED;
}
//--- load models
float temp;
if(!Encoder.Load(FileName + "Enc.nnw", temp, temp, temp, dtStudied, true))
{
CArrayObj *encoder = new CArrayObj();
if(!CreateEncoderDescriptions(encoder))
{
delete encoder;
return INIT_FAILED;
}
if(!Encoder.Create(encoder))
{
delete encoder;
return INIT_FAILED;
}
delete encoder;
}
//---
Encoder.getResults(Result);
if(Result.Total() != NForecast * BarDescr)
{
PrintFormat("The scope of the Encoder does not match the forecast state count (%d <> %d)", NForecast * BarDescr, Result.Total());
return INIT_FAILED;
}
//---
Encoder.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))
Encoder.Save(FileName + "Enc.nnw", 0, 0, 0, TimeCurrent(), true);
delete Result;
}
//+------------------------------------------------------------------+
//| 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;
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 - NForecast - batch));
if(state <= 0)
{
iter--;
continue;
}
Encoder.Clear();
int end = MathMin(state + batch, Buffer[tr].Total - NForecast);
for(int i = state; i < end && !IsStopped() && !Stop; i++)
{
bState.AssignArray(Buffer[tr].States[i].state);
//--- State Encoder
if(!Encoder.feedForward((CBufferFloat*)GetPointer(bState), 1, false, (CBufferFloat*)NULL))
{
PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
Stop = true;
break;
}
//--- Collect target data
bState.Clear();
for(int fst = 1; fst <= NForecast; fst++)
{
if(!bState.AddArray(Buffer[tr].States[i + fst].state))
break;
}
if(!Encoder.backProp(GetPointer(bState), (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", "Encoder", percent, Encoder.getRecentAverageError());
Comment(str);
ticks = GetTickCount();
}
}
}
Comment("");
//---
PrintFormat("%s -> %d -> %-15s %10.7f", __FUNCTION__, __LINE__, "Encoder", Encoder.getRecentAverageError());
ExpertRemove();
//---
}
//+------------------------------------------------------------------+