841 lines
51 KiB
MQL5
841 lines
51 KiB
MQL5
//+------------------------------------------------------------------+
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//| Trajectory.mqh |
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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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//| Rewards structure |
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//| 0 - Delta Balance |
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//| 1 - Delta Equity ( "-" Drawdown / "+" Profit) |
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//| 2 - Penalty for no opened positions |
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//+------------------------------------------------------------------+
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#include "..\RL\FQF.mqh"
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//---
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#define HistoryBars 48 //Depth of history
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#define BarDescr 9 //Elements for 1 bar description
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#define NBarInPattern 1 //Bars for 1 pattern description
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#define AccountDescr 8 //Account description
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#define NActions 6 //Number of possible Actions
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#define TimeDescription 4
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#define LatentCount 1024
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#define LatentLayer 2
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#define EmbeddingSize 32
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#define Buffer_Size 6500
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#define DiscFactor 0.99f
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#define FileName "OPPO"
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#define MaxReplayBuffer 500
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#define MaxSL 1000
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#define MaxTP 1000
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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struct STrajectory;
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extern STrajectory Buffer[];
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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struct SState
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{
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float state[BarDescr * NBarInPattern];
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float account[AccountDescr];
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float action[NActions];
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float scheduler[EmbeddingSize];
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//---
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SState(void);
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//---
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bool Save(int file_handle);
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bool Load(int file_handle);
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//---
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void Clear(void)
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{
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ArrayInitialize(state, 0);
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ArrayInitialize(account, 0);
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ArrayInitialize(action, 0);
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ArrayInitialize(scheduler, 0);
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}
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//--- overloading
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void operator=(const SState &obj)
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{
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ArrayCopy(state, obj.state);
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ArrayCopy(account, obj.account);
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ArrayCopy(action, obj.action);
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ArrayCopy(scheduler, obj.scheduler);
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}
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};
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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SState::SState(void)
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{
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ArrayInitialize(state, 0);
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ArrayInitialize(account, 0);
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ArrayInitialize(action, 0);
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ArrayInitialize(scheduler, 0);
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}
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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bool SState::Save(int file_handle)
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{
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if(file_handle == INVALID_HANDLE)
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return false;
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//---
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int total = ArraySize(state);
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if(FileWriteInteger(file_handle, total) < sizeof(int))
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return false;
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for(int i = 0; i < total; i++)
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if(FileWriteFloat(file_handle, state[i]) < sizeof(float))
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return false;
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//---
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total = ArraySize(account);
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if(FileWriteInteger(file_handle, total) < sizeof(int))
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return false;
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for(int i = 0; i < total; i++)
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if(FileWriteFloat(file_handle, account[i]) < sizeof(float))
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return false;
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//---
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total = ArraySize(action);
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if(FileWriteInteger(file_handle, total) < sizeof(int))
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return false;
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for(int i = 0; i < total; i++)
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if(FileWriteFloat(file_handle, action[i]) < sizeof(float))
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return false;
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//---
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total = ArraySize(scheduler);
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if(FileWriteInteger(file_handle, total) < sizeof(int))
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return false;
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for(int i = 0; i < total; i++)
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if(FileWriteFloat(file_handle, scheduler[i]) < sizeof(float))
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return false;
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//---
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return true;
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}
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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bool SState::Load(int file_handle)
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{
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if(file_handle == INVALID_HANDLE)
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return false;
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if(FileIsEnding(file_handle))
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return false;
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//---
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int total = FileReadInteger(file_handle);
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if(total != ArraySize(state))
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return false;
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//---
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for(int i = 0; i < total; i++)
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{
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if(FileIsEnding(file_handle))
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return false;
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state[i] = FileReadFloat(file_handle);
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}
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//---
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total = FileReadInteger(file_handle);
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if(total != ArraySize(account))
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return false;
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//---
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for(int i = 0; i < total; i++)
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{
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if(FileIsEnding(file_handle))
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return false;
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account[i] = FileReadFloat(file_handle);
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}
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//---
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total = FileReadInteger(file_handle);
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if(total != ArraySize(action))
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return false;
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//---
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for(int i = 0; i < total; i++)
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{
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if(FileIsEnding(file_handle))
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return false;
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action[i] = FileReadFloat(file_handle);
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}
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//---
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total = FileReadInteger(file_handle);
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if(total != ArraySize(scheduler))
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return false;
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//---
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for(int i = 0; i < total; i++)
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{
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if(FileIsEnding(file_handle))
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return false;
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scheduler[i] = FileReadFloat(file_handle);
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}
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//---
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return true;
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}
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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struct STrajectory
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{
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SState States[Buffer_Size];
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int Total;
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double Profit;
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//---
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STrajectory(void);
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//---
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bool Add(SState &state);
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void ClearFirstN(const int n);
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//---
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bool Save(int file_handle);
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bool Load(int file_handle);
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//--- overloading
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void operator=(const STrajectory &obj)
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{
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Total = obj.Total;
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Profit = obj.Profit;
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for(int i = 0; i < Buffer_Size; i++)
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States[i] = obj.States[i];
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}
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};
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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STrajectory::STrajectory(void) : Total(0),
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Profit(0)
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{
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}
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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bool STrajectory::Save(int file_handle)
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{
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if(file_handle == INVALID_HANDLE)
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return false;
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//---
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if(FileWriteInteger(file_handle, Total) < sizeof(int))
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return false;
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if(FileWriteDouble(file_handle, Profit) < sizeof(float))
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return false;
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for(int i = 0; i < Total; i++)
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if(!States[i].Save(file_handle))
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return false;
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//---
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return true;
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}
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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bool STrajectory::Load(int file_handle)
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{
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if(file_handle == INVALID_HANDLE)
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return false;
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//---
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Total = FileReadInteger(file_handle);
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if(FileIsEnding(file_handle) || Total >= ArraySize(States))
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return false;
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Profit = FileReadDouble(file_handle);
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//---
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for(int i = 0; i < Total; i++)
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if(!States[i].Load(file_handle))
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return false;
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//---
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return true;
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}
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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bool STrajectory::Add(SState &state)
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{
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if(Total + 1 >= ArraySize(States))
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return false;
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States[Total] = state;
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Total++;
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//---
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return true;
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}
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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void STrajectory::ClearFirstN(const int n)
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{
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for(int i = 0; i < Buffer_Size - n; i++)
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States[i] = States[i + n];
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Total = MathMax(0, Buffer_Size - n);
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for(int i = Total; i < Buffer_Size; i++)
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States[i].Clear();
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}
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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int SaveTotalBase(int min_bars)
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{
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int total = ArraySize(Buffer);
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if(total < 0)
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return 0;
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int handle = FileOpen(FileName + ".bd", FILE_WRITE | FILE_BIN | FILE_COMMON);
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if(handle < 0)
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return 0;
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int indexes[MaxReplayBuffer];
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int count = 0;
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for(int i = total - 1; i >= 0; i--)
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{
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if(Buffer[i].Total < min_bars)
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continue;
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indexes[count] = i;
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count++;
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}
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if(FileWriteInteger(handle, count) < INT_VALUE)
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{
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FileClose(handle);
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return 0;
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}
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for(int i = count - 1; i >= 0; i--)
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if(!Buffer[indexes[i]].Save(handle))
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{
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FileClose(handle);
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return (count - (i + 1));
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}
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FileFlush(handle);
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FileClose(handle);
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//---
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return count;
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}
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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bool LoadTotalBase(void)
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{
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int handle = FileOpen(FileName + ".bd", FILE_READ | FILE_BIN | FILE_COMMON | FILE_SHARE_READ);
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if(handle < 0)
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return false;
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int total = FileReadInteger(handle);
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if(total <= 0)
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{
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FileClose(handle);
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return false;
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}
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if(ArrayResize(Buffer, total) < total)
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{
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FileClose(handle);
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return false;
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}
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for(int i = 0; i < total; i++)
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if(!Buffer[i].Load(handle))
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{
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FileClose(handle);
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return false;
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}
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FileClose(handle);
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//---
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return true;
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}
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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bool CreateAgentDescriptions(CArrayObj *agent)
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{
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//---
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CLayerDescription *descr;
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//---
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if(!agent)
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{
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agent = new CArrayObj();
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if(!agent)
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return false;
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}
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//--- Agent
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agent.Clear();
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//--- Input layer
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronBaseOCL;
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uint prev_count = descr.count = (BarDescr * NBarInPattern + AccountDescr + TimeDescription + NActions + EmbeddingSize);
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descr.activation = None;
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descr.optimization = ADAM;
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if(!agent.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 1
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronBatchNormOCL;
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descr.count = prev_count;
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descr.batch = 1000;
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descr.activation = None;
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descr.optimization = ADAM;
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if(!agent.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 2
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronEmbeddingOCL;
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prev_count = descr.count = HistoryBars;
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{
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int temp[] = {BarDescr * NBarInPattern, AccountDescr, TimeDescription, NActions, EmbeddingSize};
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ArrayCopy(descr.windows, temp);
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}
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uint prev_wout = descr.window_out = EmbeddingSize;
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if(!agent.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 3
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronSoftMaxOCL;
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descr.count = EmbeddingSize;
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descr.step = prev_count * 5;
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descr.activation = None;
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descr.optimization = ADAM;
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if(!agent.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 4
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronMLMHAttentionOCL;
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prev_count = descr.count = prev_count * 5;
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descr.window = EmbeddingSize;
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descr.step = 8;
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descr.window_out = 32;
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descr.layers = 4;
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descr.optimization = ADAM;
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if(!agent.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 5
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronSoftMaxOCL;
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descr.count = EmbeddingSize;
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descr.step = prev_count;
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descr.activation = None;
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descr.optimization = ADAM;
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if(!agent.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 6
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronConvOCL;
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prev_count = descr.count = prev_count;
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descr.window = EmbeddingSize;
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descr.step = EmbeddingSize;
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prev_wout = descr.window_out = EmbeddingSize;
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descr.optimization = ADAM;
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descr.activation = LReLU;
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if(!agent.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 7
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronSoftMaxOCL;
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descr.count = prev_count;
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descr.step = prev_wout;
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descr.activation = None;
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descr.optimization = ADAM;
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if(!agent.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 8
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronConvOCL;
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prev_count = descr.count = prev_count;
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descr.window = prev_wout;
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descr.step = prev_wout;
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prev_wout = descr.window_out = prev_wout / 2;
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descr.optimization = ADAM;
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descr.activation = LReLU;
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if(!agent.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 9
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronSoftMaxOCL;
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descr.count = prev_count;
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descr.step = prev_wout;
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descr.activation = None;
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descr.optimization = ADAM;
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if(!agent.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 10
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronBaseOCL;
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descr.count = LatentCount;
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descr.optimization = ADAM;
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descr.activation = LReLU;
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if(!agent.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 11
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronBaseOCL;
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prev_count = descr.count = LatentCount;
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descr.activation = LReLU;
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descr.optimization = ADAM;
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if(!agent.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 12
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronBaseOCL;
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descr.count = LatentCount;
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descr.activation = LReLU;
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descr.optimization = ADAM;
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if(!agent.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 13
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronBaseOCL;
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descr.count = NActions;
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descr.activation = SIGMOID;
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descr.optimization = ADAM;
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if(!agent.Add(descr))
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{
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delete descr;
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return false;
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}
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//---
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return true;
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}
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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bool CreateSchedulerDescriptions(CArrayObj *scheduler)
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{
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//---
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CLayerDescription *descr;
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//---
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if(!scheduler)
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{
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scheduler = new CArrayObj();
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if(!scheduler)
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return false;
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}
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//--- Scheduler
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scheduler.Clear();
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//--- Input layer
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronBaseOCL;
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uint prev_count = descr.count = (BarDescr * NBarInPattern + AccountDescr + TimeDescription + NActions);
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descr.activation = None;
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descr.optimization = ADAM;
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if(!scheduler.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 1
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronBatchNormOCL;
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descr.count = prev_count;
|
|
descr.batch = 1000;
|
|
descr.activation = None;
|
|
descr.optimization = ADAM;
|
|
if(!scheduler.Add(descr))
|
|
{
|
|
delete descr;
|
|
return false;
|
|
}
|
|
//--- layer 2
|
|
if(!(descr = new CLayerDescription()))
|
|
return false;
|
|
descr.type = defNeuronEmbeddingOCL;
|
|
prev_count = descr.count = HistoryBars;
|
|
{
|
|
uint temp[] = {BarDescr * NBarInPattern, AccountDescr, TimeDescription, NActions};
|
|
ArrayCopy(descr.windows, temp);
|
|
}
|
|
uint prev_wout = descr.window_out = EmbeddingSize;
|
|
if(!scheduler.Add(descr))
|
|
{
|
|
delete descr;
|
|
return false;
|
|
}
|
|
//--- layer 3
|
|
if(!(descr = new CLayerDescription()))
|
|
return false;
|
|
descr.type = defNeuronSoftMaxOCL;
|
|
descr.count = EmbeddingSize;
|
|
descr.step = prev_count * 4;
|
|
descr.activation = None;
|
|
descr.optimization = ADAM;
|
|
if(!scheduler.Add(descr))
|
|
{
|
|
delete descr;
|
|
return false;
|
|
}
|
|
//--- layer 4
|
|
if(!(descr = new CLayerDescription()))
|
|
return false;
|
|
descr.type = defNeuronMLMHAttentionOCL;
|
|
prev_count = descr.count = prev_count * 4;
|
|
descr.window = EmbeddingSize;
|
|
descr.step = 8;
|
|
descr.window_out = 32;
|
|
descr.layers = 4;
|
|
descr.optimization = ADAM;
|
|
if(!scheduler.Add(descr))
|
|
{
|
|
delete descr;
|
|
return false;
|
|
}
|
|
//--- layer 5
|
|
if(!(descr = new CLayerDescription()))
|
|
return false;
|
|
descr.type = defNeuronSoftMaxOCL;
|
|
descr.count = EmbeddingSize;
|
|
descr.step = prev_count;
|
|
descr.activation = None;
|
|
descr.optimization = ADAM;
|
|
if(!scheduler.Add(descr))
|
|
{
|
|
delete descr;
|
|
return false;
|
|
}
|
|
//--- layer 6
|
|
if(!(descr = new CLayerDescription()))
|
|
return false;
|
|
descr.type = defNeuronBaseOCL;
|
|
descr.count = LatentCount;
|
|
descr.optimization = ADAM;
|
|
descr.activation = LReLU;
|
|
if(!scheduler.Add(descr))
|
|
{
|
|
delete descr;
|
|
return false;
|
|
}
|
|
//--- layer 7
|
|
if(!(descr = new CLayerDescription()))
|
|
return false;
|
|
descr.type = defNeuronBaseOCL;
|
|
prev_count = descr.count = EmbeddingSize;
|
|
descr.activation = None;
|
|
descr.optimization = ADAM;
|
|
if(!scheduler.Add(descr))
|
|
{
|
|
delete descr;
|
|
return false;
|
|
}
|
|
//---
|
|
return true;
|
|
}
|
|
#ifndef Study
|
|
//+------------------------------------------------------------------+
|
|
//| |
|
|
//+------------------------------------------------------------------+
|
|
bool IsNewBar(void)
|
|
{
|
|
static datetime last_bar = 0;
|
|
if(last_bar >= iTime(Symb.Name(), TimeFrame, 0))
|
|
return false;
|
|
//---
|
|
last_bar = iTime(Symb.Name(), TimeFrame, 0);
|
|
return true;
|
|
}
|
|
//+------------------------------------------------------------------+
|
|
//| |
|
|
//+------------------------------------------------------------------+
|
|
bool CloseByDirection(ENUM_POSITION_TYPE type)
|
|
{
|
|
int total = PositionsTotal();
|
|
bool result = true;
|
|
for(int i = total - 1; i >= 0; i--)
|
|
{
|
|
if(PositionGetSymbol(i) != Symb.Name())
|
|
continue;
|
|
if(PositionGetInteger(POSITION_TYPE) != type)
|
|
continue;
|
|
result = (Trade.PositionClose(PositionGetInteger(POSITION_TICKET)) && result);
|
|
}
|
|
//---
|
|
return result;
|
|
}
|
|
//+------------------------------------------------------------------+
|
|
//| |
|
|
//+------------------------------------------------------------------+
|
|
bool TrailPosition(ENUM_POSITION_TYPE type, double sl, double tp)
|
|
{
|
|
int total = PositionsTotal();
|
|
bool result = true;
|
|
//---
|
|
for(int i = 0; i < total; i++)
|
|
{
|
|
if(PositionGetSymbol(i) != Symb.Name())
|
|
continue;
|
|
if(PositionGetInteger(POSITION_TYPE) != type)
|
|
continue;
|
|
bool modify = false;
|
|
double psl = PositionGetDouble(POSITION_SL);
|
|
double ptp = PositionGetDouble(POSITION_TP);
|
|
switch(type)
|
|
{
|
|
case POSITION_TYPE_BUY:
|
|
if((sl - psl) >= Symb.Point())
|
|
{
|
|
psl = sl;
|
|
modify = true;
|
|
}
|
|
if(MathAbs(tp - ptp) >= Symb.Point())
|
|
{
|
|
ptp = tp;
|
|
modify = true;
|
|
}
|
|
break;
|
|
case POSITION_TYPE_SELL:
|
|
if((psl - sl) >= Symb.Point())
|
|
{
|
|
psl = sl;
|
|
modify = true;
|
|
}
|
|
if(MathAbs(tp - ptp) >= Symb.Point())
|
|
{
|
|
ptp = tp;
|
|
modify = true;
|
|
}
|
|
break;
|
|
}
|
|
if(modify)
|
|
result = (Trade.PositionModify(PositionGetInteger(POSITION_TICKET), psl, ptp) && result);
|
|
}
|
|
//---
|
|
return result;
|
|
}
|
|
//+------------------------------------------------------------------+
|
|
//| |
|
|
//+------------------------------------------------------------------+
|
|
bool ClosePartial(ENUM_POSITION_TYPE type, double value)
|
|
{
|
|
if(value <= 0)
|
|
return true;
|
|
//---
|
|
for(int i = 0; (i < PositionsTotal() && value > 0); i++)
|
|
{
|
|
if(PositionGetSymbol(i) != Symb.Name())
|
|
continue;
|
|
if(PositionGetInteger(POSITION_TYPE) != type)
|
|
continue;
|
|
double pvalue = PositionGetDouble(POSITION_VOLUME);
|
|
if(pvalue <= value)
|
|
{
|
|
if(Trade.PositionClose(PositionGetInteger(POSITION_TICKET)))
|
|
{
|
|
value -= pvalue;
|
|
i--;
|
|
}
|
|
}
|
|
else
|
|
{
|
|
if(Trade.PositionClosePartial(PositionGetInteger(POSITION_TICKET), value))
|
|
value = 0;
|
|
}
|
|
}
|
|
//---
|
|
return (value <= 0);
|
|
}
|
|
#endif
|
|
//+------------------------------------------------------------------+
|
|
//| |
|
|
//+------------------------------------------------------------------+
|
|
vector<double> GetProbTrajectories(STrajectory &buffer[], float lanbda)
|
|
{
|
|
ulong total = buffer.Size();
|
|
vector<double> rewards = vector<double>::Zeros(total);
|
|
for(ulong i = 0; i < total; i++)
|
|
rewards[i]=Buffer[i].Profit;
|
|
double std = rewards.Std();
|
|
double max_profit = rewards.Max();
|
|
//---
|
|
vector<double> sorted = rewards;
|
|
bool sort = true;
|
|
while(sort)
|
|
{
|
|
sort = false;
|
|
for(ulong i = 0; i < sorted.Size() - 1; i++)
|
|
if(sorted[i] > sorted[i + 1])
|
|
{
|
|
double temp = sorted[i];
|
|
sorted[i] = sorted[i + 1];
|
|
sorted[i + 1] = temp;
|
|
sort = true;
|
|
}
|
|
}
|
|
//---
|
|
double min = rewards.Min() - 0.1 * std;
|
|
if(max_profit > min)
|
|
{
|
|
double k = sorted.Percentile(90) - max_profit;
|
|
vector<double> multipl = MathAbs(rewards - max_profit) / (k == 0 ? -std : k);
|
|
multipl = exp(multipl);
|
|
rewards = (rewards - min) / (max_profit - min);
|
|
rewards = rewards / (rewards + lanbda) * multipl;
|
|
rewards.ReplaceNan(0);
|
|
}
|
|
else
|
|
rewards.Fill(1);
|
|
rewards = rewards / rewards.Sum();
|
|
rewards = rewards.CumSum();
|
|
//---
|
|
return rewards;
|
|
}
|
|
//+------------------------------------------------------------------+
|
|
//| |
|
|
//+------------------------------------------------------------------+
|
|
int SampleTrajectory(vector<double> &probability)
|
|
{
|
|
//--- check
|
|
ulong total = probability.Size();
|
|
if(total <= 0)
|
|
return -1;
|
|
//--- randomize
|
|
double rnd = double(MathRand()) / 32767.0;
|
|
//--- search
|
|
if(rnd <= probability[0] || total == 1)
|
|
return 0;
|
|
if(rnd > probability[total - 2])
|
|
return int(total - 1);
|
|
int result = int(rnd * total);
|
|
if(probability[result] < rnd)
|
|
while(probability[result] < rnd)
|
|
result++;
|
|
else
|
|
while(probability[result - 1] >= rnd)
|
|
result--;
|
|
//--- return result
|
|
return result;
|
|
}
|
|
//+------------------------------------------------------------------+
|