Warrior_EA/references/MQL5/Experts/CWBC/StudyRTG.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     = 1e7;

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

//|                                                                  |

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

STrajectory          Buffer[];

CNet                 RTG;

//---

float                dError;

datetime             dtStudied;

//---

CBufferFloat         State;

CBufferFloat         *Result;

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

//| Expert initialization function                                   |

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

int OnInit()

  {

//---

   ResetLastError();

   if(!LoadTotalBase())

     {

      PrintFormat("Error of load study data: %d", GetLastError());

      return INIT_FAILED;

     }

//--- load models

   float temp;

   if(!RTG.Load(FileName + "RTG.nnw", temp, temp, temp, dtStudied, true))

     {

      CArrayObj *rtg = new CArrayObj();

      if(!CreateRTGDescriptions(rtg))

        {

         delete rtg;

         return INIT_FAILED;

        }

      if(!RTG.Create(rtg))

        {

         delete rtg;

         return INIT_FAILED;

        }

      delete rtg;

      //---

     }

//---

   RTG.getResults(Result);

   if(Result.Total() != NRewards)

     {

      PrintFormat("The scope of the RTG-model does not match the rewards count (%d <> %d)", NRewards, Result.Total());

      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)

  {

//---

   RTG.Save(FileName + "RTG.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)

  {

   float max_reward = 0, quanitle = 0;

   vector<float> std;

   vector<float> probability = GetProbTrajectories(Buffer, max_reward, quanitle, std, 0.95, 0.1f);

   uint ticks = GetTickCount();

//---

   bool StopFlag = false;

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

     {

      int tr = SampleTrajectory(probability);

      int i = (int)((MathRand() * MathRand() / MathPow(32767, 2)) * (Buffer[tr].Total - 2 * ValueBars));

      if(i < 0)

        {

         iter--;

         continue;

        }