forked from dng/NN_in_Trading
262 lines
9.1 KiB
MQL5
262 lines
9.1 KiB
MQL5
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//+------------------------------------------------------------------+
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//| Study.mq5 |
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//| Copyright DNG® |
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//| https://www.mql5.com/ru/users/dng |
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//+------------------------------------------------------------------+
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#property copyright "Copyright DNG®"
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#property link "https://www.mql5.com/ru/users/dng"
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#property version "1.00"
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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#define Study
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#include "Trajectory.mqh"
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//+------------------------------------------------------------------+
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//| Input parameters |
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//+------------------------------------------------------------------+
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input datetime Start = D'2024.01.01';
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input datetime End = D'2026.01.01';
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input int Epochs = 100;
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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CNet StateEncoder;
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CNet ForecastDecoder;
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//---
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float dError;
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datetime dtStudied;
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//---
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CBufferFloat bStateE;
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CBufferFloat bTarget;
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CBufferFloat bTime;
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CBufferFloat *Result;
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vector<float> check;
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//+------------------------------------------------------------------+
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//| Expert initialization function |
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//+------------------------------------------------------------------+
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int OnInit()
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{
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//---
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ResetLastError();
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//--- load models
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float temp;
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if(!StateEncoder.Load(FileName + "StEnc.nnw", temp, temp, temp, dtStudied, true) ||
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!ForecastDecoder.Load(FileName + "FDec.nnw", temp, temp, temp, dtStudied, true)
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)
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{
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Print("Create new model");
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CArrayObj *encoder = NULL, *decoder = NULL;
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if(!CreateStateDescriptions(encoder, decoder))
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{
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delete encoder;
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delete decoder;
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return INIT_FAILED;
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}
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if(!StateEncoder.Create(encoder) ||
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!ForecastDecoder.Create(decoder)
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)
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{
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delete encoder;
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delete decoder;
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return INIT_FAILED;
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}
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delete encoder;
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delete decoder;
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}
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//---
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StateEncoder.SetOpenCL(ForecastDecoder.GetOpenCL());
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//---
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StateEncoder.getResults(Result);
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if(Result.Total() != NForecast * ForecastTokenDim)
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{
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PrintFormat("The scope of the StateEncoder doesn't match forecast token plan (%d <> %d)", Result.Total(), (NForecast * ForecastTokenDim));
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return INIT_FAILED;
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}
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//---
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StateEncoder.GetLayerOutput(0, Result);
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if(Result.Total() != (HistoryBars * BarDescr))
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{
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PrintFormat("The inputs of the StateEncoder doesn't match state description (%d <> %d)", Result.Total(), (HistoryBars * BarDescr));
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return INIT_FAILED;
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}
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//---
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StateEncoder.GetLayerOutput(StateRawForecastLayer, Result);
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if(Result.Total() != (NForecast * EmbeddingSize))
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{
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PrintFormat("The raw forecast layer does not match latent forecast size (%d <> %d)", NForecast * EmbeddingSize, Result.Total());
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return INIT_FAILED;
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}
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//---
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ForecastDecoder.getResults(Result);
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if(Result.Total() != BarDescr * NForecast)
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{
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PrintFormat("The scope of the ForecastDecoder does not match the forecast state count (%d <> %d)", NForecast * BarDescr, Result.Total());
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return INIT_FAILED;
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}
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//---
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if(!Symb.Name(_Symbol) || !Symb.Refresh())
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return INIT_FAILED;
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//---
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if(!RSI.Create(Symb.Name(), TimeFrame, RSIPeriod, RSIPrice))
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return INIT_FAILED;
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//---
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if(!CCI.Create(Symb.Name(), TimeFrame, CCIPeriod, CCIPrice))
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return INIT_FAILED;
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//---
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if(!ATR.Create(Symb.Name(), TimeFrame, ATRPeriod))
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return INIT_FAILED;
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//---
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if(!MACD.Create(Symb.Name(), TimeFrame, FastPeriod, SlowPeriod, SignalPeriod, MACDPrice))
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return INIT_FAILED;
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//---
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if(!EventChartCustom(ChartID(), 1, 0, 0, "Init"))
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{
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PrintFormat("Error of create study event: %d", GetLastError());
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return INIT_FAILED;
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}
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//---
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return(INIT_SUCCEEDED);
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}
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//+------------------------------------------------------------------+
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//| Expert deinitialization function |
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//+------------------------------------------------------------------+
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void OnDeinit(const int reason)
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{
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//---
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if(!(reason == REASON_INITFAILED || reason == REASON_RECOMPILE))
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{
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StateEncoder.Save(FileName + "StEnc.nnw", 0, 0, 0, TimeCurrent(), true);
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ForecastDecoder.Save(FileName + "FDec.nnw", 0, 0, 0, TimeCurrent(), true);
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}
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delete Result;
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}
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//+------------------------------------------------------------------+
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//| ChartEvent function |
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//+------------------------------------------------------------------+
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void OnChartEvent(const int id,
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const long &lparam,
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const double &dparam,
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const string &sparam)
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{
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//---
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if(id == 1001)
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Train();
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}
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//+------------------------------------------------------------------+
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//| Train function |
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//+------------------------------------------------------------------+
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void Train(void)
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{
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int start = iBarShift(Symb.Name(), TimeFrame, Start);
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int end = iBarShift(Symb.Name(), TimeFrame, End);
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int bars = CopyRates(Symb.Name(), TimeFrame, 0, start, Rates);
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//---
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if(!RSI.BufferResize(bars) || !CCI.BufferResize(bars) ||
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!ATR.BufferResize(bars) || !MACD.BufferResize(bars))
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{
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PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
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ExpertRemove();
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return;
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}
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//---
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int count = -1;
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bool calculated = false;
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do
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{
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calculated = (RSI.BarsCalculated() >= bars &&
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CCI.BarsCalculated() >= bars &&
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ATR.BarsCalculated() >= bars &&
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MACD.BarsCalculated() >= bars
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);
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Sleep(100);
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count++;
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}
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while(!calculated && count < 100);
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if(!calculated)
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{
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PrintFormat("%s -> %d The training data has not been loaded", __FUNCTION__, __LINE__);
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ExpertRemove();
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return;
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}
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RSI.Refresh();
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CCI.Refresh();
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ATR.Refresh();
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MACD.Refresh();
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//---
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if(!ArraySetAsSeries(Rates, true))
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{
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PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
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ExpertRemove();
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return;
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}
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bars -= end + HistoryBars + NForecast;
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if(bars < 0)
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{
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PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
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ExpertRemove();
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return;
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}
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//---
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bool Stop = false;
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//---
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uint ticks = GetTickCount();
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//---
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for(int epoch = 0; (epoch < Epochs && !IsStopped() && !Stop); epoch ++)
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{
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if(!StateEncoder.Clear() ||
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!ForecastDecoder.Clear())
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{
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PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
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ExpertRemove();
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return;
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}
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for(int posit = start - HistoryBars - NForecast - 1; posit >= end; posit--)
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{
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if(!CreateBuffers(posit, GetPointer(bStateE), GetPointer(bTime), GetPointer(bTarget)))
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{
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PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
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Stop = true;
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break;
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}
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//--- State Encoder
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if(!StateEncoder.feedForward((CBufferFloat*)GetPointer(bStateE), 1, false, (CBufferFloat*)NULL))
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{
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PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
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Stop = true;
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break;
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}
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if(!ForecastDecoder.feedForward((CNet*)GetPointer(StateEncoder), StateRawForecastLayer, (CBufferFloat*)NULL))
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{
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PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
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Stop = true;
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break;
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}
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if(!ForecastDecoder.backProp(GetPointer(bTarget), (CBufferFloat*)NULL, (CBufferFloat*)NULL))
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{
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PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
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Stop = true;
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break;
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}
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if(!StateEncoder.backPropGradient((CBufferFloat*)NULL, (CBufferFloat*)NULL, StateRawForecastLayer, true))
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{
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PrintFormat("%s -> %d", __FUNCTION__, __LINE__);
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Stop = true;
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break;
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}
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//---
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if(GetTickCount() - ticks > 500)
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{
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double percent = (double(epoch) + 1.0 - double(posit - end) / (start - end - HistoryBars - NForecast)) * 100.0 / Epochs;
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string str = StringFormat("%-14s %6.2f%% -> Error %15.8f\n", "ForecastDecoder", percent, ForecastDecoder.getRecentAverageError());
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Comment(str);
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ticks = GetTickCount();
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}
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}
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}
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Comment("");
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//---
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PrintFormat("%s -> %d -> %-15s %10.7f", __FUNCTION__, __LINE__, "ForecastDecoder", ForecastDecoder.getRecentAverageError());
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ExpertRemove();
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//---
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}
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//+------------------------------------------------------------------+
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