okWarrior_EA/references/MQL5/Experts/AutoBots/StudyTraj.mq5

<EFBFBD><EFBFBD>//+------------------------------------------------------------------+

//|                                                        Study.mq5 |

//|                                                   Copyright DNG<EFBFBD> |

//|                                https://www.mql5.com/en/users/dng |

//+------------------------------------------------------------------+

#property copyright "Copyright DNG<00>"

#property link      "https://www.mql5.com/en/users/dng"

#property version   "1.00"

//+------------------------------------------------------------------+

//|                                                                  |

//+------------------------------------------------------------------+

#define Study

#include "Trajectory.mqh"

//+------------------------------------------------------------------+

//| Input parameters                                                 |

//+------------------------------------------------------------------+

input int                  Iterations     = 1e4;

//+------------------------------------------------------------------+

//|                                                                  |

//+------------------------------------------------------------------+

STrajectory          Buffer[];

CNet                 Autobot;

//---

float                dError;

datetime             dtStudied;

//---

CBufferFloat         State;

CBufferFloat        *Result;

CBufferFloat         Ones;

CBufferFloat         Gradient;

vector<float>        STE;

vector<float>        STE_Noise;

//---

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(!Autobot.Load(FileName + "Traj.nnw", temp, temp, temp, dtStudied, true))

     {

      Print("Init new models");

      CArrayObj *autobot = new CArrayObj();

      if(!CreateTrajNetDescriptions(autobot))

        {

         delete autobot;

         return INIT_FAILED;

        }

      if(!Autobot.Create(autobot))

        {

         delete autobot;

         return INIT_FAILED;

        }

      delete autobot;

      //---

     }

//---

   Autobot.getResults(Result);

   if(Result.Total() != PrecoderBars * 3)

     {

      PrintFormat("The scope of the Autobot does not match the precoder bars (%d <> %d)", PrecoderBars * 3, Result.Total());

      return INIT_FAILED;

     }

//---

   Autobot.GetLayerOutput(0, Result);

   if(Result.Total() != (HistoryBars * BarDescr))

     {

      PrintFormat("Input size of Autobot doesn't match state description (%d <> %d)", Result.Total(), (HistoryBars * BarDescr));

      return INIT_FAILED;

     }

//---

   OpenCL = Autobot.GetOpenCL();

   if(!Ones.BufferInit(EmbeddingSize, 1) ||

      !Gradient.BufferInit(EmbeddingSize, 0) ||

      !Ones.BufferCreate(OpenCL) ||

      !Gradient.BufferCreate(OpenCL))

     {

      PrintFormat("Error of create buffers: %d", GetLastError());

      return INIT_FAILED;

     }

   State.BufferInit(HistoryBars * BarDescr, 0);

//---

   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))

      Autobot.Save(FileName + "Traj.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, inp;

   matrix<float> targets;

   matrix<float> delta;

   STE = vector<float>::Zeros(PrecoderBars * 3);

   int std_count = 0;

   int batch = GPTBars + 50;

   bool Stop = false;

   uint ticks = GetTickCount();

   ulong size = HistoryBars * BarDescr;

//---

   for(int iter = 0; (iter < Iterations && !IsStopped() && !Stop); iter ++)

     {

      int tr = SampleTrajectory(probability);

      int state = (int)((MathRand() * MathRand() / MathPow(32767, 2)) * (Buffer[tr].Total - 3 - PrecoderBars - batch));

      if(state < 0)

        {

         iter--;

         continue;

        }

      int end = MathMin(state + batch, Buffer[tr].Total - PrecoderBars);