NN_in_Trading/Experts/OPPO/Trajectory.mqh
2026-03-14 22:28:53 +02:00

841 lines
51 KiB
MQL5

//+------------------------------------------------------------------+
//| Trajectory.mqh |
//| Copyright DNG® |
//| https://www.mql5.com/ru/users/dng |
//+------------------------------------------------------------------+
#property copyright "Copyright DNG®"
#property link "https://www.mql5.com/ru/users/dng"
#property version "1.00"
//+------------------------------------------------------------------+
//| Rewards structure |
//| 0 - Delta Balance |
//| 1 - Delta Equity ( "-" Drawdown / "+" Profit) |
//| 2 - Penalty for no opened positions |
//+------------------------------------------------------------------+
#include "..\RL\FQF.mqh"
//---
#define HistoryBars 48 //Depth of history
#define BarDescr 9 //Elements for 1 bar description
#define NBarInPattern 1 //Bars for 1 pattern description
#define AccountDescr 8 //Account description
#define NActions 6 //Number of possible Actions
#define TimeDescription 4
#define LatentCount 1024
#define LatentLayer 2
#define EmbeddingSize 32
#define Buffer_Size 6500
#define DiscFactor 0.99f
#define FileName "OPPO"
#define MaxReplayBuffer 500
#define MaxSL 1000
#define MaxTP 1000
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
struct STrajectory;
extern STrajectory Buffer[];
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
struct SState
{
float state[BarDescr * NBarInPattern];
float account[AccountDescr];
float action[NActions];
float scheduler[EmbeddingSize];
//---
SState(void);
//---
bool Save(int file_handle);
bool Load(int file_handle);
//---
void Clear(void)
{
ArrayInitialize(state, 0);
ArrayInitialize(account, 0);
ArrayInitialize(action, 0);
ArrayInitialize(scheduler, 0);
}
//--- overloading
void operator=(const SState &obj)
{
ArrayCopy(state, obj.state);
ArrayCopy(account, obj.account);
ArrayCopy(action, obj.action);
ArrayCopy(scheduler, obj.scheduler);
}
};
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
SState::SState(void)
{
ArrayInitialize(state, 0);
ArrayInitialize(account, 0);
ArrayInitialize(action, 0);
ArrayInitialize(scheduler, 0);
}
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
bool SState::Save(int file_handle)
{
if(file_handle == INVALID_HANDLE)
return false;
//---
int total = ArraySize(state);
if(FileWriteInteger(file_handle, total) < sizeof(int))
return false;
for(int i = 0; i < total; i++)
if(FileWriteFloat(file_handle, state[i]) < sizeof(float))
return false;
//---
total = ArraySize(account);
if(FileWriteInteger(file_handle, total) < sizeof(int))
return false;
for(int i = 0; i < total; i++)
if(FileWriteFloat(file_handle, account[i]) < sizeof(float))
return false;
//---
total = ArraySize(action);
if(FileWriteInteger(file_handle, total) < sizeof(int))
return false;
for(int i = 0; i < total; i++)
if(FileWriteFloat(file_handle, action[i]) < sizeof(float))
return false;
//---
total = ArraySize(scheduler);
if(FileWriteInteger(file_handle, total) < sizeof(int))
return false;
for(int i = 0; i < total; i++)
if(FileWriteFloat(file_handle, scheduler[i]) < sizeof(float))
return false;
//---
return true;
}
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
bool SState::Load(int file_handle)
{
if(file_handle == INVALID_HANDLE)
return false;
if(FileIsEnding(file_handle))
return false;
//---
int total = FileReadInteger(file_handle);
if(total != ArraySize(state))
return false;
//---
for(int i = 0; i < total; i++)
{
if(FileIsEnding(file_handle))
return false;
state[i] = FileReadFloat(file_handle);
}
//---
total = FileReadInteger(file_handle);
if(total != ArraySize(account))
return false;
//---
for(int i = 0; i < total; i++)
{
if(FileIsEnding(file_handle))
return false;
account[i] = FileReadFloat(file_handle);
}
//---
total = FileReadInteger(file_handle);
if(total != ArraySize(action))
return false;
//---
for(int i = 0; i < total; i++)
{
if(FileIsEnding(file_handle))
return false;
action[i] = FileReadFloat(file_handle);
}
//---
total = FileReadInteger(file_handle);
if(total != ArraySize(scheduler))
return false;
//---
for(int i = 0; i < total; i++)
{
if(FileIsEnding(file_handle))
return false;
scheduler[i] = FileReadFloat(file_handle);
}
//---
return true;
}
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
struct STrajectory
{
SState States[Buffer_Size];
int Total;
double Profit;
//---
STrajectory(void);
//---
bool Add(SState &state);
void ClearFirstN(const int n);
//---
bool Save(int file_handle);
bool Load(int file_handle);
//--- overloading
void operator=(const STrajectory &obj)
{
Total = obj.Total;
Profit = obj.Profit;
for(int i = 0; i < Buffer_Size; i++)
States[i] = obj.States[i];
}
};
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
STrajectory::STrajectory(void) : Total(0),
Profit(0)
{
}
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
bool STrajectory::Save(int file_handle)
{
if(file_handle == INVALID_HANDLE)
return false;
//---
if(FileWriteInteger(file_handle, Total) < sizeof(int))
return false;
if(FileWriteDouble(file_handle, Profit) < sizeof(float))
return false;
for(int i = 0; i < Total; i++)
if(!States[i].Save(file_handle))
return false;
//---
return true;
}
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
bool STrajectory::Load(int file_handle)
{
if(file_handle == INVALID_HANDLE)
return false;
//---
Total = FileReadInteger(file_handle);
if(FileIsEnding(file_handle) || Total >= ArraySize(States))
return false;
Profit = FileReadDouble(file_handle);
//---
for(int i = 0; i < Total; i++)
if(!States[i].Load(file_handle))
return false;
//---
return true;
}
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
bool STrajectory::Add(SState &state)
{
if(Total + 1 >= ArraySize(States))
return false;
States[Total] = state;
Total++;
//---
return true;
}
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
void STrajectory::ClearFirstN(const int n)
{
for(int i = 0; i < Buffer_Size - n; i++)
States[i] = States[i + n];
Total = MathMax(0, Buffer_Size - n);
for(int i = Total; i < Buffer_Size; i++)
States[i].Clear();
}
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
int SaveTotalBase(int min_bars)
{
int total = ArraySize(Buffer);
if(total < 0)
return 0;
int handle = FileOpen(FileName + ".bd", FILE_WRITE | FILE_BIN | FILE_COMMON);
if(handle < 0)
return 0;
int indexes[MaxReplayBuffer];
int count = 0;
for(int i = total - 1; i >= 0; i--)
{
if(Buffer[i].Total < min_bars)
continue;
indexes[count] = i;
count++;
}
if(FileWriteInteger(handle, count) < INT_VALUE)
{
FileClose(handle);
return 0;
}
for(int i = count - 1; i >= 0; i--)
if(!Buffer[indexes[i]].Save(handle))
{
FileClose(handle);
return (count - (i + 1));
}
FileFlush(handle);
FileClose(handle);
//---
return count;
}
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
bool LoadTotalBase(void)
{
int handle = FileOpen(FileName + ".bd", FILE_READ | FILE_BIN | FILE_COMMON | FILE_SHARE_READ);
if(handle < 0)
return false;
int total = FileReadInteger(handle);
if(total <= 0)
{
FileClose(handle);
return false;
}
if(ArrayResize(Buffer, total) < total)
{
FileClose(handle);
return false;
}
for(int i = 0; i < total; i++)
if(!Buffer[i].Load(handle))
{
FileClose(handle);
return false;
}
FileClose(handle);
//---
return true;
}
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
bool CreateAgentDescriptions(CArrayObj *agent)
{
//---
CLayerDescription *descr;
//---
if(!agent)
{
agent = new CArrayObj();
if(!agent)
return false;
}
//--- Agent
agent.Clear();
//--- Input layer
if(!(descr = new CLayerDescription()))
return false;
descr.type = defNeuronBaseOCL;
uint prev_count = descr.count = (BarDescr * NBarInPattern + AccountDescr + TimeDescription + NActions + EmbeddingSize);
descr.activation = None;
descr.optimization = ADAM;
if(!agent.Add(descr))
{
delete descr;
return false;
}
//--- layer 1
if(!(descr = new CLayerDescription()))
return false;
descr.type = defNeuronBatchNormOCL;
descr.count = prev_count;
descr.batch = 1000;
descr.activation = None;
descr.optimization = ADAM;
if(!agent.Add(descr))
{
delete descr;
return false;
}
//--- layer 2
if(!(descr = new CLayerDescription()))
return false;
descr.type = defNeuronEmbeddingOCL;
prev_count = descr.count = HistoryBars;
{
int temp[] = {BarDescr * NBarInPattern, AccountDescr, TimeDescription, NActions, EmbeddingSize};
ArrayCopy(descr.windows, temp);
}
uint prev_wout = descr.window_out = EmbeddingSize;
if(!agent.Add(descr))
{
delete descr;
return false;
}
//--- layer 3
if(!(descr = new CLayerDescription()))
return false;
descr.type = defNeuronSoftMaxOCL;
descr.count = EmbeddingSize;
descr.step = prev_count * 5;
descr.activation = None;
descr.optimization = ADAM;
if(!agent.Add(descr))
{
delete descr;
return false;
}
//--- layer 4
if(!(descr = new CLayerDescription()))
return false;
descr.type = defNeuronMLMHAttentionOCL;
prev_count = descr.count = prev_count * 5;
descr.window = EmbeddingSize;
descr.step = 8;
descr.window_out = 32;
descr.layers = 4;
descr.optimization = ADAM;
if(!agent.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(!agent.Add(descr))
{
delete descr;
return false;
}
//--- layer 6
if(!(descr = new CLayerDescription()))
return false;
descr.type = defNeuronConvOCL;
prev_count = descr.count = prev_count;
descr.window = EmbeddingSize;
descr.step = EmbeddingSize;
prev_wout = descr.window_out = EmbeddingSize;
descr.optimization = ADAM;
descr.activation = LReLU;
if(!agent.Add(descr))
{
delete descr;
return false;
}
//--- layer 7
if(!(descr = new CLayerDescription()))
return false;
descr.type = defNeuronSoftMaxOCL;
descr.count = prev_count;
descr.step = prev_wout;
descr.activation = None;
descr.optimization = ADAM;
if(!agent.Add(descr))
{
delete descr;
return false;
}
//--- layer 8
if(!(descr = new CLayerDescription()))
return false;
descr.type = defNeuronConvOCL;
prev_count = descr.count = prev_count;
descr.window = prev_wout;
descr.step = prev_wout;
prev_wout = descr.window_out = prev_wout / 2;
descr.optimization = ADAM;
descr.activation = LReLU;
if(!agent.Add(descr))
{
delete descr;
return false;
}
//--- layer 9
if(!(descr = new CLayerDescription()))
return false;
descr.type = defNeuronSoftMaxOCL;
descr.count = prev_count;
descr.step = prev_wout;
descr.activation = None;
descr.optimization = ADAM;
if(!agent.Add(descr))
{
delete descr;
return false;
}
//--- layer 10
if(!(descr = new CLayerDescription()))
return false;
descr.type = defNeuronBaseOCL;
descr.count = LatentCount;
descr.optimization = ADAM;
descr.activation = LReLU;
if(!agent.Add(descr))
{
delete descr;
return false;
}
//--- layer 11
if(!(descr = new CLayerDescription()))
return false;
descr.type = defNeuronBaseOCL;
prev_count = descr.count = LatentCount;
descr.activation = LReLU;
descr.optimization = ADAM;
if(!agent.Add(descr))
{
delete descr;
return false;
}
//--- layer 12
if(!(descr = new CLayerDescription()))
return false;
descr.type = defNeuronBaseOCL;
descr.count = LatentCount;
descr.activation = LReLU;
descr.optimization = ADAM;
if(!agent.Add(descr))
{
delete descr;
return false;
}
//--- layer 13
if(!(descr = new CLayerDescription()))
return false;
descr.type = defNeuronBaseOCL;
descr.count = NActions;
descr.activation = SIGMOID;
descr.optimization = ADAM;
if(!agent.Add(descr))
{
delete descr;
return false;
}
//---
return true;
}
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
bool CreateSchedulerDescriptions(CArrayObj *scheduler)
{
//---
CLayerDescription *descr;
//---
if(!scheduler)
{
scheduler = new CArrayObj();
if(!scheduler)
return false;
}
//--- Scheduler
scheduler.Clear();
//--- Input layer
if(!(descr = new CLayerDescription()))
return false;
descr.type = defNeuronBaseOCL;
uint prev_count = descr.count = (BarDescr * NBarInPattern + AccountDescr + TimeDescription + NActions);
descr.activation = None;
descr.optimization = ADAM;
if(!scheduler.Add(descr))
{
delete descr;
return false;
}
//--- layer 1
if(!(descr = new CLayerDescription()))
return false;
descr.type = defNeuronBatchNormOCL;
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;
}
//+------------------------------------------------------------------+