forked from mnbvc188199/Warrior_EA
1120 lines
68 KiB
MQL5
1120 lines
68 KiB
MQL5
//+------------------------------------------------------------------+
| |
//| Trajectory.mqh |
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//| Copyright DNG® |
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//| https://www.mql5.com/en/users/dng |
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//+------------------------------------------------------------------+
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#property copyright "Copyright DNG®"
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#property link "https://www.mql5.com/en/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 open positions |
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//+------------------------------------------------------------------+
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#include "..\NeuroNet_DNG\NeuroNet.mqh"
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//---
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#define HistoryBars 1 //Depth of history
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#define GPTBars 100 //Analitic Depth of history
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#define PrecoderBars 10 //Forecast Depth
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#define BarDescr 9 //Elements for 1 bar description
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#define AccountDescr 12 //Account description
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#define NActions 6 //Number of possible Actions
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#define NRewards 3 //Number of rewards
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#define NForecast 5 //Number of forecast
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#define Lenc 3 //Number ADAPT Encoder blocks
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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 "ADAPT"
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#define SignalFile(agent) StringFormat("Signals\\Signal%d.csv",agent)
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#define LatentCount 512
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#define MaxSL 1000
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#define MaxTP 1000
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#define MaxReplayBuffer 500
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#define StartTargetIteration 200000
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#define STE_Multiplier 1.0f/2
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#define STE_Noise_Multiplier 1.0f/10 // λ defines the impact of noise prediction error
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#define STD_Delta_Multiplier 1.0f/20 // noise factor ω
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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[HistoryBars * BarDescr];
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float account[AccountDescr - 4];
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float action[NActions];
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float rewards[NRewards];
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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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//--- 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(rewards, obj.rewards);
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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(rewards, 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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total = ArraySize(rewards);
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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, rewards[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(rewards))
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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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rewards[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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float DiscountFactor;
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bool CumCounted;
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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 CumRevards(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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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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STrajectory::STrajectory(void) : Total(0),
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DiscountFactor(DiscFactor),
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CumCounted(false)
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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(!CumCounted)
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CumRevards();
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if(FileWriteInteger(file_handle, Total) < sizeof(int))
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return false;
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if(FileWriteFloat(file_handle, DiscountFactor) < 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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DiscountFactor = FileReadFloat(file_handle);
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CumCounted = true;
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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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void STrajectory::CumRevards(void)
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{
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if(CumCounted)
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return;
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//---
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for(int i = Total - 2; i >= 0; i--)
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for(int r = 0; r < NRewards; r++)
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States[i].rewards[r] += States[i + 1].rewards[r] * DiscountFactor;
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CumCounted = 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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bool SaveTotalBase(void)
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{
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int total = ArraySize(Buffer);
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if(total < 0)
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return true;
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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 false;
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int start = MathMax(total - MaxReplayBuffer, 0);
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if(FileWriteInteger(handle, total - start) < INT_VALUE)
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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 = start; i < total; i++)
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if(!Buffer[i].Save(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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FileFlush(handle);
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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 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 CreateDescriptions(CArrayObj *actor, CArrayObj *end_encoder, CArrayObj *state_encoder)
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{
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//---
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CLayerDescription *descr;
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//---
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if(!actor)
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{
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actor = new CArrayObj();
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if(!actor)
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return false;
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}
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if(!end_encoder)
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{
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end_encoder = new CArrayObj();
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if(!end_encoder)
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return false;
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}
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if(!state_encoder)
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{
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state_encoder = new CArrayObj();
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if(!state_encoder)
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return false;
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}
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//--- Endpoints Encoder
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end_encoder.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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int prev_count = descr.count = 3 * NForecast;
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descr.activation = None;
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descr.optimization = ADAM;
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if(!end_encoder.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 = defNeuronConcatenate;
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descr.count = LatentCount;
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descr.window = prev_count;
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descr.step = NForecast;
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descr.optimization = ADAM;
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descr.activation = LReLU;
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if(!end_encoder.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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//--- State Encoder
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state_encoder.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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prev_count = descr.count = GPTBars * EmbeddingSize;
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descr.activation = None;
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descr.optimization = ADAM;
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if(!state_encoder.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 = defNeuronConcatenate;
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descr.count = LatentCount;
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descr.window = prev_count;
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descr.step = AccountDescr;
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descr.optimization = ADAM;
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descr.activation = SIGMOID;
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if(!state_encoder.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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//--- Actor
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actor.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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prev_count = descr.count = LatentCount;
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descr.activation = None;
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descr.optimization = ADAM;
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if(!actor.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 = defNeuronConcatenate;
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descr.count = LatentCount;
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descr.window = prev_count;
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descr.step = LatentCount;
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descr.optimization = ADAM;
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descr.activation = LReLU;
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if(!actor.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 = defNeuronBaseOCL;
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descr.count = LatentCount;
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descr.activation = SIGMOID;
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descr.optimization = ADAM;
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if(!actor.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 = defNeuronBaseOCL;
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descr.count = 2 * NActions;
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descr.activation = None;
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descr.optimization = ADAM;
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if(!actor.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 = defNeuronVAEOCL;
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descr.count = NActions;
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descr.optimization = ADAM;
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if(!actor.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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//+------------------------------------------------------------------+
| |
bool CreateTrajNetDescriptions(CArrayObj *encoder, CArrayObj *endpoints, CArrayObj *probability)
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{
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//---
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CLayerDescription *descr;
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//---
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if(!encoder)
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{
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encoder = new CArrayObj();
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if(!encoder)
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return false;
| |
}
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if(!endpoints)
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{
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endpoints = new CArrayObj();
| |
if(!endpoints)
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return false;
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}
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if(!probability)
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{
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probability = new CArrayObj();
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if(!probability)
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return false;
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}
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//--- Encoder
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encoder.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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int prev_count = descr.count = (HistoryBars * BarDescr);
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descr.activation = None;
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descr.optimization = ADAM;
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if(!encoder.Add(descr))
| |
{
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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 = MathMax(1000, GPTBars);
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descr.activation = None;
| |
descr.optimization = ADAM;
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if(!encoder.Add(descr))
| |
{
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delete descr;
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return false;
| |
}
| |
//--- layer 2
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if(!(descr = new CLayerDescription()))
| |
return false;
| |
descr.type = defNeuronEmbeddingOCL;
| |
{
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int temp[] = {prev_count};
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ArrayCopy(descr.windows, temp);
| |
}
| |
prev_count = descr.count = GPTBars;
| |
int prev_wout = descr.window_out = EmbeddingSize;
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if(!encoder.Add(descr))
| |
{
| |
delete descr;
| |
return false;
| |
}
| |
//--- layer 3
| |
if(!(descr = new CLayerDescription()))
| |
return false;
| |
descr.type = defNeuronPEOCL;
| |
descr.count = prev_count;
| |
descr.window = prev_wout;
| |
if(!encoder.Add(descr))
| |
{
| |
delete descr;
| |
return false;
| |
}
| |
for(int l = 0; l < Lenc; l++)
| |
{
| |
//--- layer 4
| |
if(!(descr = new CLayerDescription()))
| |
return false;
| |
descr.type = defNeuronTransposeOCL;
| |
descr.count = prev_count;
| |
descr.window = prev_wout;
| |
if(!encoder.Add(descr))
| |
{
| |
delete descr;
| |
return false;
| |
}
| |
//--- layer 5
| |
if(!(descr = new CLayerDescription()))
| |
return false;
| |
descr.type = defNeuronMH2AttentionOCL;
| |
descr.count = prev_wout;
| |
descr.window = prev_count;
| |
descr.step = 8;
| |
descr.window_out = 16;
| |
descr.optimization = ADAM;
| |
if(!encoder.Add(descr))
| |
{
| |
delete descr;
| |
return false;
| |
}
| |
//--- layer 6
| |
if(!(descr = new CLayerDescription()))
| |
return false;
| |
descr.type = defNeuronMLMHAttentionOCL;
| |
descr.count = prev_wout;
| |
descr.window = prev_count;
| |
descr.step = 8;
| |
descr.window_out = 16;
| |
descr.layers = 1;
| |
descr.optimization = ADAM;
| |
if(!encoder.Add(descr))
| |
{
| |
delete descr;
| |
return false;
| |
}
| |
//--- layer 7
| |
if(!(descr = new CLayerDescription()))
| |
return false;
| |
descr.type = defNeuronTransposeOCL;
| |
descr.count = prev_wout;
| |
descr.window = prev_count;
| |
if(!encoder.Add(descr))
| |
{
| |
delete descr;
| |
return false;
| |
}
| |
//--- layer 8
| |
if(!(descr = new CLayerDescription()))
| |
return false;
| |
descr.type = defNeuronMH2AttentionOCL;
| |
descr.count = prev_count;
| |
descr.window = prev_wout;
| |
descr.step = 8;
| |
descr.window_out = 16;
| |
descr.layers = 1;
| |
descr.optimization = ADAM;
| |
if(!encoder.Add(descr))
| |
{
| |
delete descr;
| |
return false;
| |
}
| |
//--- layer 9
| |
if(!(descr = new CLayerDescription()))
| |
return false;
| |
descr.type = defNeuronMLMHAttentionOCL;
| |
descr.count = prev_count;
| |
descr.window = prev_wout;
| |
descr.step = 8;
| |
descr.window_out = 16;
| |
descr.layers = 1;
| |
descr.optimization = ADAM;
| |
if(!encoder.Add(descr))
| |
{
| |
delete descr;
| |
return false;
| |
}
| |
}
| |
//--- Endpoints
| |
endpoints.Clear();
| |
//--- Input layer
| |
if(!(descr = new CLayerDescription()))
| |
return false;
| |
descr.type = defNeuronBaseOCL;
| |
prev_count = descr.count = (prev_count * prev_wout);
| |
descr.activation = None;
| |
descr.optimization = ADAM;
| |
if(!endpoints.Add(descr))
| |
{
| |
delete descr;
| |
return false;
| |
}
| |
//--- layer 1
| |
if(!(descr = new CLayerDescription()))
| |
return false;
| |
descr.type = defNeuronBaseOCL;
| |
descr.count = LatentCount;
| |
descr.activation = SIGMOID;
| |
descr.optimization = ADAM;
| |
if(!endpoints.Add(descr))
| |
{
| |
delete descr;
| |
return false;
| |
}
| |
//--- layer 2
| |
if(!(descr = new CLayerDescription()))
| |
return false;
| |
descr.type = defNeuronSoftMaxOCL;
| |
descr.count = LatentCount;
| |
descr.step = 1;
| |
descr.activation = None;
| |
descr.optimization = ADAM;
| |
if(!endpoints.Add(descr))
| |
{
| |
delete descr;
| |
return false;
| |
}
| |
//--- layer 3
| |
if(!(descr = new CLayerDescription()))
| |
return false;
| |
descr.type = defNeuronBaseOCL;
| |
descr.count = 3 * NForecast;
| |
descr.activation = None;
| |
descr.optimization = ADAM;
| |
if(!endpoints.Add(descr))
| |
{
| |
delete descr;
| |
return false;
| |
}
| |
//--- Probability
| |
probability.Clear();
| |
//--- Input layer
| |
if(!probability.Add(endpoints.At(0)))
| |
return false;
| |
//--- layer 1
| |
if(!(descr = new CLayerDescription()))
| |
return false;
| |
descr.type = defNeuronConcatenate;
| |
descr.count = LatentCount;
| |
descr.window = prev_count;
| |
descr.step = 3 * NForecast;
| |
descr.optimization = ADAM;
| |
descr.activation = SIGMOID;
| |
if(!probability.Add(descr))
| |
{
| |
delete descr;
| |
return false;
| |
}
| |
//--- layer 2
| |
if(!(descr = new CLayerDescription()))
| |
return false;
| |
descr.type = defNeuronBaseOCL;
| |
descr.count = LatentCount;
| |
descr.activation = LReLU;
| |
descr.optimization = ADAM;
| |
if(!probability.Add(descr))
| |
{
| |
delete descr;
| |
return false;
| |
}
| |
//--- layer 3
| |
if(!(descr = new CLayerDescription()))
| |
return false;
| |
descr.type = defNeuronBaseOCL;
| |
descr.count = NForecast;
| |
descr.activation = None;
| |
descr.optimization = ADAM;
| |
if(!probability.Add(descr))
| |
{
| |
delete descr;
| |
return false;
| |
}
| |
//--- layer 4
| |
if(!(descr = new CLayerDescription()))
| |
return false;
| |
descr.type = defNeuronSoftMaxOCL;
| |
descr.count = NForecast;
| |
descr.step = 1;
| |
descr.activation = None;
| |
descr.optimization = ADAM;
| |
if(!probability.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<float> GetProbTrajectories(STrajectory &buffer[], double lambda)
| |
{
| |
ulong total = buffer.Size();
| |
vector<float> result = vector<float>::Zeros(total);
| |
vector<float> temp;
| |
for(ulong i = 0; i < total; i++)
| |
{
| |
temp.Assign(buffer[i].States[0].rewards);
| |
result[i] = temp.Sum();
| |
if(!MathIsValidNumber(result[i]))
| |
result[i] = -FLT_MAX;
| |
}
| |
float max_reward = result.Max();
| |
//---
| |
vector<float> sorted = result;
| |
bool sort = true;
| |
int iter = 0;
| |
while(sort)
| |
{
| |
sort = false;
| |
for(ulong i = 0; i < sorted.Size() - 1; i++)
| |
if(sorted[i] > sorted[i + 1])
| |
{
| |
float temp = sorted[i];
| |
sorted[i] = sorted[i + 1];
| |
sorted[i + 1] = temp;
| |
sort = true;
| |
}
| |
iter++;
| |
}
| |
//---
| |
float min = result.Min() - 0.1f * MathAbs(max_reward);
| |
if(max_reward > min)
| |
{
| |
float k = sorted.Percentile(80) - max_reward;
| |
vector<float> multipl = MathExp(MathAbs(result - max_reward) / (k == 0 ? -1 : k));
| |
result = (result - min) / (max_reward - min);
| |
result = result / (result + lambda) * multipl;
| |
result.ReplaceNan(0);
| |
}
| |
else
| |
result.Fill(1);
| |
result = result / result.Sum();
| |
result = result.CumSum();
| |
//---
| |
return result;
| |
}
| |
//+------------------------------------------------------------------+
| |
//| |
| |
//+------------------------------------------------------------------+
| |
int SampleTrajectory(vector<float> &probability)
| |
{
| |
//--- check
| |
ulong total = probability.Size();
| |
if(total <= 0)
| |
return -1;
| |
//--- randomize
| |
float rnd = float(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
| |
{
| |
if(result <= 0)
| |
Sleep(0);
| |
while(probability[result - 1] >= rnd)
| |
result--;
| |
}
| |
//--- return result
| |
return result;
| |
}
| |
//+------------------------------------------------------------------+
| |
//| |
| |
//+------------------------------------------------------------------+
| |
class CDeal : public CObject
| |
{
| |
public:
| |
datetime OpenTime;
| |
datetime CloseTime;
| |
ENUM_POSITION_TYPE Type;
| |
double Volume;
| |
double OpenPrice;
| |
double StopLos;
| |
double TakeProfit;
| |
double point;
| |
//---
| |
CDeal(void);
| |
~CDeal(void) {};
| |
//---
| |
vector<float> Action(datetime current, double ask, double bid, int period_seconds);
| |
};
| |
//+------------------------------------------------------------------+
| |
//| |
| |
//+------------------------------------------------------------------+
| |
void CDeal::CDeal(void) : OpenTime(0),
| |
CloseTime(0),
| |
Type(POSITION_TYPE_BUY),
| |
Volume(0),
| |
OpenPrice(0),
| |
StopLos(0),
| |
TakeProfit(0),
| |
point(1e-5)
| |
{
| |
}
| |
//+------------------------------------------------------------------+
| |
//| |
| |
//+------------------------------------------------------------------+
| |
vector<float> CDeal::Action(datetime current, double ask, double bid, int period_seconds)
| |
{
| |
vector<float> result = vector<float>::Zeros(NActions);
| |
if((OpenTime - period_seconds) > current || CloseTime <= current)
| |
return result;
| |
//---
| |
switch(Type)
| |
{
| |
case POSITION_TYPE_BUY:
| |
result[0] = float(Volume);
| |
if(TakeProfit > 0)
| |
result[1] = float((TakeProfit - ask) / (MaxTP * point));
| |
if(StopLos > 0)
| |
result[2] = float((ask - StopLos) / (MaxSL * point));
| |
break;
| |
case POSITION_TYPE_SELL:
| |
result[3] = float(Volume);
| |
if(TakeProfit > 0)
| |
result[4] = float((bid - TakeProfit) / (MaxTP * point));
| |
if(StopLos > 0)
| |
result[5] = float((StopLos - bid) / (MaxSL * point));
| |
break;
| |
}
| |
//---
| |
return result;
| |
}
| |
//+------------------------------------------------------------------+
| |
//| |
| |
//+------------------------------------------------------------------+
| |
class CDeals
| |
{
| |
protected:
| |
CArrayObj Deals;
| |
public:
| |
CDeals(void) { Deals.Clear(); }
| |
~CDeals(void) { Deals.Clear(); }
| |
//---
| |
bool LoadDeals(string file_name, string symbol, double point);
| |
vector<float> Action(datetime current, double ask, double bid, int period_seconds);
| |
};
| |
//+------------------------------------------------------------------+
| |
//| |
| |
//+------------------------------------------------------------------+
| |
bool CDeals::LoadDeals(string file_name, string symbol, double point)
| |
{
| |
if(file_name == NULL || !FileIsExist(file_name, FILE_COMMON))
| |
{
| |
PrintFormat("File %s not exist", file_name);
| |
return false;
| |
}
| |
if(symbol == NULL)
| |
{
| |
symbol = _Symbol;
| |
point = _Point;
| |
}
| |
//---
| |
ResetLastError();
| |
int handle = FileOpen(file_name, FILE_READ | FILE_ANSI | FILE_CSV | FILE_COMMON, short(';'), CP_ACP);
| |
if(handle == INVALID_HANDLE)
| |
{
| |
PrintFormat("Error of open file %s: %d", file_name, GetLastError());
| |
return false;
| |
}
| |
FileSeek(handle, 0, SEEK_SET);
| |
while(!FileIsEnding(handle))
| |
{
| |
string s = FileReadString(handle);
| |
datetime open_time = StringToTime(s);
| |
string type = FileReadString(handle);
| |
double volume = StringToDouble(FileReadString(handle));
| |
string deal_symbol = FileReadString(handle);
| |
double open_price = StringToDouble(FileReadString(handle));
| |
volume = MathMin(volume, StringToDouble(FileReadString(handle)));
| |
datetime close_time = StringToTime(FileReadString(handle));
| |
double close_price = StringToDouble(FileReadString(handle));
| |
s = FileReadString(handle);
| |
s = FileReadString(handle);
| |
s = FileReadString(handle);
| |
if(StringFind(deal_symbol, symbol, 0) < 0)
| |
continue;
| |
//---
| |
ResetLastError();
| |
CDeal *deal = new CDeal();
| |
if(!deal)
| |
{
| |
PrintFormat("Error of create new deal object: %d", GetLastError());
| |
return false;
| |
}
| |
deal.OpenTime = open_time;
| |
deal.CloseTime = close_time;
| |
deal.OpenPrice = open_price;
| |
deal.Volume = volume;
| |
deal.point = point;
| |
if(type == "Sell")
| |
{
| |
deal.Type = POSITION_TYPE_SELL;
| |
if(close_price < open_price)
| |
{
| |
deal.TakeProfit = close_price;
| |
deal.StopLos = 0;
| |
}
| |
else
| |
{
| |
deal.TakeProfit = 0;
| |
deal.StopLos = close_price;
| |
}
| |
}
| |
else
| |
{
| |
deal.Type = POSITION_TYPE_BUY;
| |
if(close_price > open_price)
| |
{
| |
deal.TakeProfit = close_price;
| |
deal.StopLos = 0;
| |
}
| |
else
| |
{
| |
deal.TakeProfit = 0;
| |
deal.StopLos = close_price;
| |
}
| |
}
| |
//---
| |
ResetLastError();
| |
if(!Deals.Add(deal))
| |
{
| |
PrintFormat("Error of add new deal: %d", GetLastError());
| |
return false;
| |
}
| |
}
| |
//---
| |
FileClose(handle);
| |
//---
| |
return true;
| |
}
| |
//+------------------------------------------------------------------+
| |
//| |
| |
//+------------------------------------------------------------------+
| |
vector<float> CDeals::Action(datetime current, double ask, double bid, int period_seconds)
| |
{
| |
vector<float> result = vector<float>::Zeros(NActions);
| |
for(int i = 0; i < Deals.Total(); i++)
| |
{
| |
CDeal *deal = Deals.At(i);
| |
if(!deal)
| |
continue;
| |
vector<float> action = deal.Action(current, ask, bid, period_seconds);
| |
result[0] += action[0];
| |
result[3] += action[3];
| |
result[1] = MathMax(result[1], action[1]);
| |
result[2] = MathMax(result[2], action[2]);
| |
result[4] = MathMax(result[4], action[4]);
| |
result[5] = MathMax(result[5], action[5]);
| |
}
| |
//---
| |
return result;
| |
}
| |
//+------------------------------------------------------------------+
|