Warrior_EA/references/MQL5/Experts/CT/Study.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                 Agent;

CNet                 Worker;

//---

float                dError;

datetime             dtStudied;

//---

CBufferFloat         State;

CBufferFloat         *Result;

vector<float>        Actions;

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

//| Expert initialization function                                   |

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

int OnInit()

  {

//---

   ResetLastError();

   if(!LoadTotalBase())

     {

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

      return INIT_FAILED;

     }

//--- load models

   float temp;

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

     {

      PrintFormat("Error of load worker model: %d", GetLastError());

      return INIT_FAILED;

     }

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

     {

      CArrayObj *agent = new CArrayObj();

      if(!CreateDescriptions(agent))

        {

         delete agent;

         return INIT_FAILED;

        }

      if(!Agent.Create(agent))

        {

         delete agent;

         return INIT_FAILED;

        }

      delete agent;

      //---

     }

//---

   Worker.SetOpenCL(Agent.GetOpenCL());

   Worker.TrainMode(false);

//---

   Worker.getResults(Result);

   if(Result.Total() != NActions)

     {

      PrintFormat("The scope of the worker does not match the actions count (%d <> %d)", NActions, Result.Total());

      return INIT_FAILED;

     }

//---

   Worker.GetLayerOutput(0, Result);

   if(Result.Total() != WorkerInput)

     {

      PrintFormat("Input size of Worker model doesn't match skills count (%d <> %d)", Result.Total(), WorkerInput);

      return INIT_FAILED;

     }

//---

   Agent.getResults(Result);

   if(Result.Total() != WorkerInput)

     {

      PrintFormat("The scope of the Agent does not match the skills count (%d <> %d)", WorkerInput, 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)

  {

//---

   Agent.Save(FileName + "Act.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)

  {

   int total_tr = ArraySize(Buffer);

   uint ticks = GetTickCount();

   float err=0;

   int err_count=0;

//---

   bool StopFlag = false;

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

     {

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

      int i = (int)((MathRand() * MathRand() / MathPow(32767, 2)) * MathMax(Buffer[tr].Total - 2 * HistoryBars-ValueBars,MathMin(Buffer[tr].Total,20+ValueBars)));