okWarrior_EA/references/MQL5/Experts/EDL/StudyModel.mq5

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

//|                                                   StudyModel.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"

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

//|                                                                  |

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

#include "Trajectory.mqh"

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

//| Input parameters                                                 |

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

input int                  Iterations     = 1000000;

bool                 TrainMode = true;

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

//|                                                                  |

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

STrajectory          Buffer[];

CNet                 Scheduler;

//---

float                dError;

datetime             dtStudied;

//---

CBufferFloat         State;

CBufferFloat         *Result;

vector<float>        SchedulerResult;

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

//| Expert initialization function                                   |

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

int OnInit()

  {

//---

   ResetLastError();

   if(!LoadTotalBase())

     {

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

      return INIT_FAILED;

     }

//--- load models

   float temp;

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

     {

      CArrayObj *actor = new CArrayObj();

      CArrayObj *scheduler = new CArrayObj();

      if(!CreateDescriptions(actor, scheduler))

        {

         delete actor;

         delete scheduler;

         return INIT_FAILED;

        }

      if(!Scheduler.Create(scheduler))

        {

         delete actor;

         delete scheduler;

         return INIT_FAILED;

        }

      delete actor;

      delete scheduler;

      //---

     }

//---

   Scheduler.getResults(Result);

   if(Result.Total() != AccountDescr)

     {

      PrintFormat("The scope of the scheduler does not match the account description (%d <> %d)", AccountDescr, 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)

  {

//---

   Scheduler.Save(FileName + "Sch.nnw", Scheduler.getRecentAverageError(), 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();

  }

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

//|                                                                  |

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

bool LoadTotalBase(void)

  {

   int handle = FileOpen(FileName + ".bd", FILE_READ | FILE_BIN | FILE_COMMON | FILE_SHARE_READ);

   if(handle < 0)

      return false;

   int total = FileReadInteger(handle);

   if(total <= 0)

     {

      FileClose(handle);

      return false;

     }

   if(ArrayResize(Buffer, total) < total)

     {

      FileClose(handle);

      return false;

     }

   for(int i = 0; i < total; i++)

      if(!Buffer[i].Load(handle))

        {

         FileClose(handle);

         return false;

        }

   FileClose(handle);

//---

   return true;

  }

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

//| Train function                                                   |

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

void Train(void)

  {

   int total_tr = ArraySize(Buffer);

   uint ticks = GetTickCount();

   vector<float> account, reward;

   int bar, action;

//---

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

     {

      int tr = (int)(((double)MathRand() / 32767.0) * (total_tr - 1));

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

      State.AssignArray(Buffer[tr].States[i].state);