308 行
23 KiB
MQL5
308 行
23 KiB
MQL5
//+------------------------------------------------------------------+
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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 int Iterations = 100000;
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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STrajectory Buffer[];
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CNet RelateEncoder;
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CNet RelateDecoder;
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CNet ShortEncoder;
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CNet ShortDecoder;
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CNet LongEncoder;
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CNet LongDecoder;
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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 bState;
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CBufferFloat bShort;
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CBufferFloat bLong;
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CBufferFloat *Result;
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//---
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COpenCLMy *OpenCL;
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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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if(!LoadTotalBase())
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{
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PrintFormat("Error of load study data: %d", GetLastError());
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return INIT_FAILED;
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}
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//--- load models
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float temp = 0;
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if(!RelateEncoder.Load(FileName + "RelE.nnw", temp, temp, temp, dtStudied, true) ||
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!RelateDecoder.Load(FileName + "RelD.nnw", temp, temp, temp, dtStudied, true)
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)
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{
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Print("Create new Relate models");
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CArrayObj *encoder = new CArrayObj();
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CArrayObj *decoder = new CArrayObj();
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if(!CreateRelationDescriptions(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(!RelateEncoder.Create(encoder) ||
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!RelateDecoder.Create(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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delete encoder;
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delete decoder;
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}
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//---
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if(!ShortEncoder.Load(FileName + "ShE.nnw", temp, temp, temp, dtStudied, true) ||
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!ShortDecoder.Load(FileName + "ShD.nnw", temp, temp, temp, dtStudied, true)
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)
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{
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Print("Create new Short predict models");
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CArrayObj *encoder = new CArrayObj();
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CArrayObj *decoder = new CArrayObj();
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if(!CreatePredictionDescriptions(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(!ShortEncoder.Create(encoder) ||
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!ShortDecoder.Create(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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delete encoder;
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delete decoder;
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}
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//---
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if(!LongEncoder.Load(FileName + "LnE.nnw", temp, temp, temp, dtStudied, true) ||
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!LongDecoder.Load(FileName + "LnD.nnw", temp, temp, temp, dtStudied, true)
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)
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{
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Print("Create new Long predict models");
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CArrayObj *encoder = new CArrayObj();
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CArrayObj *decoder = new CArrayObj();
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if(!CreatePredictionDescriptions(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(!LongEncoder.Create(encoder) ||
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!LongDecoder.Create(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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delete encoder;
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delete decoder;
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}
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//---
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RelateEncoder.TrainMode(true);
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RelateDecoder.TrainMode(true);
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ShortEncoder.TrainMode(true);
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ShortDecoder.TrainMode(true);
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LongEncoder.TrainMode(true);
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LongDecoder.TrainMode(true);
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//---
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OpenCL = RelateEncoder.GetOpenCL();
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RelateDecoder.SetOpenCL(OpenCL);
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ShortEncoder.SetOpenCL(OpenCL);
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ShortDecoder.SetOpenCL(OpenCL);
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LongEncoder.SetOpenCL(OpenCL);
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LongDecoder.SetOpenCL(OpenCL);
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//---
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RelateDecoder.getResults(Result);
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if(Result.Total() != MathMin(HistoryBars, 100)*BarDescr)
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{
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PrintFormat("The scope of the Decoder does not match the actions count (%d <> %d)", MathMin(HistoryBars, 100)*BarDescr, Result.Total());
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return INIT_FAILED;
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}
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//---
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RelateEncoder.GetLayerOutput(0, Result);
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if(Result.Total() != (HistoryBars * BarDescr))
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{
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PrintFormat("Input size of Encoder 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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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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RelateEncoder.Save(FileName + "RelE.nnw", 0, 0, 0, TimeCurrent(), true);
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RelateDecoder.Save(FileName + "RelD.nnw", 0, 0, 0, TimeCurrent(), true);
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ShortEncoder.Save(FileName + "ShE.nnw", 0, 0, 0, TimeCurrent(), true);
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ShortDecoder.Save(FileName + "ShD.nnw", 0, 0, 0, TimeCurrent(), true);
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LongEncoder.Save(FileName + "LnE.nnw", 0, 0, 0, TimeCurrent(), true);
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LongDecoder.Save(FileName + "LnD.nnw", 0, 0, 0, TimeCurrent(), true);
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}
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delete Result;
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delete OpenCL;
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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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//---
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vector<float> probability = GetProbTrajectories(Buffer, 0.9);
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//---
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vector<float> result, target, state;
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matrix<float> predict;
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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 iter = 0; (iter < Iterations && !IsStopped() && !Stop); iter ++)
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{
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int tr = SampleTrajectory(probability);
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int i = (int)((MathRand() * MathRand() / MathPow(32767, 2)) * (Buffer[tr].Total - 2 - NForecast));
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if(i <= 0)
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{
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iter --;
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continue;
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}
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if(!state.Assign(Buffer[tr].States[i].state) ||
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MathAbs(state).Sum() == 0 ||
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!bState.AssignArray(state))
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{
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iter --;
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continue;
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}
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if(!state.Assign(Buffer[tr].States[i + NForecast].state) ||
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!state.Resize((NForecast + 1)*BarDescr) ||
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MathAbs(state).Sum() == 0)
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{
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iter --;
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continue;
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}
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//--- Feed Forward
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if(!RelateEncoder.feedForward((CBufferFloat*)GetPointer(bState), 1, false, (CBufferFloat*)NULL) ||
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!RelateDecoder.feedForward((CBufferFloat*)GetPointer(bState), 1, false, (CNet*)GetPointer(RelateEncoder)) ||
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!ShortEncoder.feedForward((CBufferFloat*)GetPointer(bState), 1, false, (CBufferFloat*)NULL) ||
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!ShortDecoder.feedForward((CBufferFloat*)GetPointer(bState), 1, false, (CNet*)GetPointer(ShortEncoder)) ||
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!LongEncoder.feedForward((CBufferFloat*)GetPointer(bState), 1, false, (CBufferFloat*)NULL) ||
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!LongDecoder.feedForward((CBufferFloat*)GetPointer(bState), 1, false, (CNet*)GetPointer(LongEncoder)))
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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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//--- Relation
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if(!RelateDecoder.backProp(GetPointer(bState), (CNet *)GetPointer(RelateEncoder)) ||
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!RelateEncoder.backPropGradient((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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//--- Prediction
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if(!predict.Resize(1, state.Size()) ||
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!predict.Row(state, 0) ||
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!predict.Reshape(NForecast + 1, BarDescr)
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)
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{
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iter --;
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continue;
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}
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result = MathAbs(predict).Max(0);
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target = (predict.Row(NForecast - 1) - predict.Row(NForecast)) / result;
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if(!bShort.AssignArray(target))
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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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for(int i = 0; i < NForecast - 1; i++)
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target += (predict.Row(i) - predict.Row(i + 1)) / result *
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MathPow(DiscFactor, NForecast - i - 1);
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if(!bLong.AssignArray(target))
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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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//--- Short prediction
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if(!ShortDecoder.backProp(GetPointer(bShort), (CNet *)GetPointer(ShortEncoder)) ||
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!ShortEncoder.backPropGradient((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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//--- Long prediction
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if(!LongDecoder.backProp(GetPointer(bLong), (CNet *)GetPointer(LongEncoder)) ||
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!LongEncoder.backPropGradient((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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//---
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if(GetTickCount() - ticks > 500)
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{
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double percent = double(iter) * 100.0 / (Iterations);
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string str = StringFormat("%-14s %6.2f%% -> Error %15.8f\n", "Relate", percent, RelateDecoder.getRecentAverageError());
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str += StringFormat("%-14s %6.2f%% -> Error %15.8f\n", "Short", percent, ShortDecoder.getRecentAverageError());
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str += StringFormat("%-14s %6.2f%% -> Error %15.8f\n", "Long", percent, LongDecoder.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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Comment("");
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//---
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PrintFormat("%s -> %d -> %-15s %10.7f", __FUNCTION__, __LINE__, "Relate", RelateDecoder.getRecentAverageError());
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PrintFormat("%s -> %d -> %-15s %10.7f", __FUNCTION__, __LINE__, "Short", ShortDecoder.getRecentAverageError());
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PrintFormat("%s -> %d -> %-15s %10.7f", __FUNCTION__, __LINE__, "Long", LongDecoder.getRecentAverageError());
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ExpertRemove();
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//---
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}
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//+------------------------------------------------------------------+
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