TR_Agent/MQL5/Experts/MultiAgentTest/MultiAgentTest.mq5

#property copyright "MultiAgent Test v7"
#property version   "7.00"
#property description "6 agenti: Hurst, ADX, Consensus, MA, Momentum, Hunter"
#property description "Neural orchestrator (CNeuralNet) + Pattern hunter cross-agente"

#include <Trade\Trade.mqh>
#include <Trade\PositionInfo.mqh>
#include "Core\Orchestrator.mqh"
#include "Agents\RegimeDetector.mqh"
#include "Agents\RegimeADX.mqh"
#include "Agents\RegimeConsensus.mqh"
#include "Agents\PatternHunter.mqh"
#include "Agents\MAAgent.mqh"
#include "Agents\MomentumAgent.mqh"

input string   Inp_Symbol        = "";           // Simbolo da testare (vuoto = simbolo corrente)
input ENUM_TIMEFRAMES Inp_TF     = PERIOD_CURRENT; // Timeframe del test
input double   Inp_MinZ          = 0.0;           // Min |z| per aprire trade (0 = soglia adattiva automatica)
input double   Inp_WMin          = 0.0;           // Peso minimo per agente (0 = 1/(N*0.1) automatico)
input int      Inp_BufferBars    = 0;             // Barre buffer storico (0 = max(HurstPeriod*10, 300))
input double   Inp_SLRiskATR     = 0.0;           // SL in ATR (0 = SL adattivo basato su MAE storico)
input double   Inp_TPRiskATR     = 0.0;           // TP in ATR (0 = stesso fattore dello SL)
input int      Inp_HurstPeriod   = 0;             // Periodo Hurst (0 = 200)
input int      Inp_ADXPeriod     = 0;             // Periodo ADX (0 = 14)
input bool     Inp_UseNeural     = false;         // Usa Neural Network invece di softmax pesato
input string   Inp_NNModelFile   = "";            // File modello NN da caricare (vuoto = auto)
input bool     Inp_TrainMode     = false;         // Addestra NN durante il test (colleziona campioni)
input int      Inp_TrainEpochs   = 100;           // Epoche di training NN per sessione
input double   Inp_TrainLR       = 0.001;         // Learning rate NN
input int      Inp_NNHidden      = 6;             // Neuroni hidden layer NN
input double   Inp_RiskPerTrade  = 0.01;          // % capitale da rischiare per trade (0.01 = 1%)
input double   Inp_RiskTotal     = 0.05;          // % capitale massima in rischio su TUTTE le posizioni
input bool     Inp_UseReversalClose = true;       // Chiudi posizione se segnale opposto (false = long+short coesistono)

Orchestrator *orchestrator;
CTrade       *trade;
CPositionInfo posInfo;
string       sym;
int          dig;
datetime     lastBarTime = 0;
int          lastBarTotal = 0;
int          bufferBars = 0;

int magicNumber;

// Hash semplice per magic number
int StringHash(string s) {
   int h = 0;
   int len = StringLen(s);
   for(int i=0; i<len; i++) {
      h = (h * 31 + (int)StringGetCharacter(s, i)) % 999999;
   }
   return h;
}

int OnInit() {
   int nAgents = 6;  // Hurst, ADX, MA, Momentum, Consensus, Hunter
   
   // Buffer bars auto: HurstMaxPeriod * 10
   int hurstMaxP = (Inp_HurstPeriod > 0) ? Inp_HurstPeriod : 200;
   bufferBars = (Inp_BufferBars > 0) ? Inp_BufferBars : MathMax(300, hurstMaxP * 10);
   
   // Peso minimo auto: 1/agentCount * 0.1
   double wMinAuto = 1.0 / nAgents * 0.1;
    double wMin = (Inp_WMin > 0.0) ? Inp_WMin : wMinAuto;

    sym = (Inp_Symbol == "") ? _Symbol : Inp_Symbol;

    magicNumber = StringHash(sym + (string)Inp_TF + "MAT") % 999999;
    if(magicNumber < 10000) magicNumber += 10000;

    // weightAlpha: 1/(N+10) per N agenti
    orchestrator = new Orchestrator(Inp_MinZ, wMin, 1.0 / (nAgents + 10),
                                    Inp_UseNeural, Inp_NNModelFile,
                                    Inp_TrainMode, Inp_TrainEpochs,
                                    Inp_TrainLR, Inp_NNHidden,
                                    Inp_RiskPerTrade, Inp_RiskTotal);
    trade = new CTrade();
   
    dig = (int)SymbolInfoInteger(sym, SYMBOL_DIGITS);
   trade.SetExpertMagicNumber(magicNumber);
   
orchestrator.AddAgent(new RegimeDetector("Hurst", 1.0, Inp_HurstPeriod));
    orchestrator.AddAgent(new RegimeADX("ADX", 1.0, Inp_ADXPeriod));
    orchestrator.AddAgent(new RegimeConsensus("Consensus", 1.0));
    orchestrator.AddAgent(new MAAgent("MA", 1.0, 8, 40));
    orchestrator.AddAgent(new MomentumAgent("Momentum", 1.0, 6, 40));
    orchestrator.AddAgent(new PatternHunter("Hunter", 1.0));
    orchestrator.InitAgents(sym, Inp_TF);
    orchestrator.LoadState(sym, Inp_TF);
    
    // Carica o inizializza modello NN
    if(Inp_UseNeural || Inp_TrainMode) {
       if(!orchestrator.LoadNNModel()) {
          if(Inp_UseNeural) {
             Print("  NN model not found, initializing fresh network...");
          }
           orchestrator.InitNeuralNet(8, Inp_NNHidden, 3, Inp_UseNeural);
       }
    }
    
     string modeStr = Inp_UseNeural ? "NEURAL" : "SOFTMAX";
     Print("MultiAgentTest v7 avviato: ", sym, " ", EnumToString(Inp_TF), " [", modeStr, "]");
     Print("Agenti: ", orchestrator.TotalAgents(), " (Hurst, ADX, MA, Momentum, Consensus, Hunter)");
     Print("Min |z|: ", Inp_MinZ, " | Buffer: ", bufferBars, " barre | Neural: ", modeStr);
    
    // Warm-up statistiche: passa i dati storici per inizializzare le EWMA
    MarketData warmup(sym, Inp_TF, bufferBars);
   if(warmup.Fetch()) {
       Print("Warm-up statistiche... (", warmup.count, " barre)");
       // Processa ogni barra storica una volta, dalla più vecchia alla più recente
       for(int bar = warmup.count - 1; bar >= 1; bar--) {
           MarketData single(sym, Inp_TF, 1);
           single.open[0]  = warmup.open[bar];
           single.high[0]  = warmup.high[bar];
           single.low[0]   = warmup.low[bar];
           single.close[0] = warmup.close[bar];
           single.volume[0] = warmup.volume[bar];
           single.time[0]  = warmup.time[bar];
           single.count = 1;
           orchestrator.Analyze(single);
       }
       // Ultima barra (current) processata una volta
       orchestrator.Analyze(warmup);
       Print("Hurst: H=", StringFormat("%.3f", SHARED_regimeH),
             " ADX: ", StringFormat("%.1f", SHARED_adxRaw),
             " Consensus: ", StringFormat("%+.2f", SHARED_regimeConsensus),
             " pattern: ", SHARED_patternName);
    }
   
    if(Inp_UseNeural) {
       if(orchestrator.IsNeuralReady()) {
          Print("  Neural: READY — ", orchestrator.NeuralInfo());
       } else {
          Print("  Neural: INITIALIZED (untrained — will fallback to softmax)");
       }
    }
    if(Inp_TrainMode) Print("  TrainMode: ON (collecting samples)");
    Print(orchestrator.TotalAgents(), " agenti pronti.");
    return INIT_SUCCEEDED;
}

void OnDeinit(const int reason) {
   CloseAllPositions();

   Print("=== MultiAgentTest: Final Report ===");
   Print("  Reason: ", reasonToStr(reason));
   Print("  Symbol: ", sym, " | TF: ", EnumToString(Inp_TF));
   Print("  Mode: ", Inp_UseNeural ? "NEURAL" : "SOFTMAX",
         " | TrainMode: ", Inp_TrainMode ? "ON" : "OFF");
   Print("  Trades: ", orchestrator.TradeCount(),
         " | Win rate: ", orchestrator.TradeCount() > 0
            ? StringFormat("%.1f%%", 100.0 * orchestrator.WinCount() / orchestrator.TradeCount())
            : "N/A");
   PrintAgentStats();

   // Neural: training e salvataggio
   bool nnTrained = false;
   if(Inp_TrainMode && orchestrator.TradeCount() >= 3) {
      Print("=== Neural Network Training (fine backtest) ===");
      Print("  Trade count: ", orchestrator.TradeCount());
      double loss = orchestrator.TrainNN();
      if(loss >= 0) {
         nnTrained = true;
         Print("  Training complete: loss=", StringFormat("%.6f", loss));
         PrintNeuralStats();
      } else {
         Print("  Training skipped: insufficient samples (need >=3)");
      }
   }

     // Agent learning summary
     orchestrator.PrintAgentLearningSummary();
     orchestrator.SaveAgentLearningCsv();

     // Per-bar agent z-scores, combinedZ, SHARED variables
     orchestrator.SaveBarHistoryCSV(sym, Inp_TF);

     // Per-bar agent weights, biases, correlations, raw signals
     orchestrator.SaveAgentInteractionCSV(sym, Inp_TF);

     // Per-trade details with PnL, exitReason, full features
     orchestrator.SaveTradeHistoryCSV(sym, Inp_TF);

     // Entry/exit decision log
     orchestrator.SaveDecisionLogCSV(sym, Inp_TF);

     // Analisi completa: tutti i parametri derivati, soglie, periodi, stats
     orchestrator.SaveAnalysisCSV(sym, Inp_TF);

     // Save state file (include NN weights inline se addestrata)
     orchestrator.SaveState(sym, Inp_TF);

   // Salva anche NN standalone (utile per debug/backup)
   if(nnTrained || orchestrator.IsNeuralReady())
      orchestrator.SaveNNModel();

   orchestrator.ReleaseAgents();
   delete orchestrator;
   delete trade;
   Print("=== MultiAgentTest terminato ===");
}

string reasonToStr(int r) {
   switch(r) {
      case REASON_PROGRAM:     return "Program";
      case REASON_REMOVE:      return "Remove";
      case REASON_CHARTCLOSE:  return "Chart Close";
      case REASON_PARAMETERS:  return "Parameters Changed";
      case REASON_RECOMPILE:   return "Recompiled";
      case REASON_ACCOUNT:     return "Account Changed";
      case REASON_TEMPLATE:    return "Template";
      case REASON_INITFAILED:  return "Init Failed";
      case REASON_CLOSE:       return "Terminal Close";
      default:                 return "Unknown (" + (string)r + ")";
   }
}

void PrintAgentStats() {
   Print("  Hurst H: ", StringFormat("%.3f", SHARED_regimeH),
         " | ADX: ", StringFormat("%.1f", SHARED_adxRaw),
         " | Consensus: ", StringFormat("%+.2f", SHARED_regimeConsensus),
         " | Agreement: ", StringFormat("%.2f", SHARED_regimeAgreement),
         " | Pattern: ", SHARED_patternName);
}

void PrintNeuralStats() {
   Print("  " + orchestrator.NeuralInfo());
   // Feature importanza approssimata: media |W1| per input
   if(orchestrator.IsNeuralReady()) {
      // Non possiamo accedere direttamente ai pesi
      Print("  (vedi CSV per loss history e training samples)");
   }
}

int CountPositions() {
   int count = 0;
   for(int i=PositionsTotal()-1; i>=0; i--) {
      if(posInfo.SelectByIndex(i)) {
          if(posInfo.Symbol() == sym && posInfo.Magic() == magicNumber)
             count++;
      }
   }
   return count;
}

void CloseAllPositions() {
   for(int i=PositionsTotal()-1; i>=0; i--) {
      if(posInfo.SelectByIndex(i)) {
          if(posInfo.Symbol() == sym && posInfo.Magic() == magicNumber)
             trade.PositionClose(posInfo.Ticket());
      }
   }
}

void OnTick() {
   if(!IsNewBar()) return;
   
    MarketData data(sym, Inp_TF, bufferBars);
   if(!data.Fetch()) return;
   
    double z = orchestrator.Analyze(data);
    FinalSignal fs = orchestrator.GetFinalSignal(Inp_MinZ);
    
    double minZ = (Inp_MinZ > 0) ? Inp_MinZ : orchestrator.AdaptiveMinZ();
    if(fs.IsActionable(minZ)) {
       ManagePositions(data, fs);
    }
   
   LogSignal(data, fs);
   
    if(CountPositions() == 0 && orchestrator.HasOpenTrade()) {
       orchestrator.ResetTradeState();
    }
}

bool IsNewBar() {
   int barsTotal = Bars(sym, Inp_TF);
   datetime timeArr[];
   CopyTime(sym, Inp_TF, 0, 1, timeArr);
   if(ArraySize(timeArr) < 1) return false;
   datetime barTime = timeArr[0];
   
   if(lastBarTime == 0) {
      lastBarTime = barTime;
      lastBarTotal = barsTotal;
      return false;
   }
   
   if(barTime != lastBarTime || barsTotal != lastBarTotal) {
      lastBarTime = barTime;
      lastBarTotal = barsTotal;
      return true;
   }
   return false;
}

void ManagePositions(const MarketData &data, const FinalSignal &fs) {
    double minZ = (Inp_MinZ > 0) ? Inp_MinZ : orchestrator.AdaptiveMinZ();

    // 1. Update MAE/MFE per tutti gli aperti (traccia high/low intra-barra)
    orchestrator.UpdateOpenTrades(data.High(0), data.Low(0));
    orchestrator.TrailStops();

    // 2. Reversal close (opzionale): chiudi posizioni con segnale opposto
    //    Se disabilitato, long e short coesistono — massimizza profitto multi-direzionale
    if(Inp_UseReversalClose) {
       int closeTickets[];
       orchestrator.GetTradesToClose(closeTickets, fs.zScore, minZ);
       for(int c = 0; c < ArraySize(closeTickets); c++) {
          int tkt = closeTickets[c];
          if(PositionSelectByTicket(tkt)) {
             bool isBuy = orchestrator.IsBuyTrade(tkt);
             double closePrice = isBuy ? SymbolInfoDouble(sym, SYMBOL_BID) : SymbolInfoDouble(sym, SYMBOL_ASK);
              orchestrator.OnTradeClose(tkt, closePrice, "REVERSAL");
              trade.PositionClose(tkt);
           }
        }
     }

    // 3. Aggiorna trailing stop sul terminale (tester supporta PositionModify)
    for(int i=PositionsTotal()-1; i>=0; i--) {
       if(posInfo.SelectByIndex(i)) {
          if(posInfo.Symbol() != sym || posInfo.Magic() != magicNumber) continue;
          int tkt = (int)posInfo.Ticket();
          double newSL = orchestrator.GetTradeSL(tkt);
          if(newSL <= 0) continue;
          double curSL = posInfo.StopLoss();
          bool isBuy = posInfo.PositionType() == POSITION_TYPE_BUY;
          bool shouldUpdate = isBuy ? (newSL > curSL + _Point) : (newSL < curSL - _Point);
          if(shouldUpdate) {
             double curTP = posInfo.TakeProfit();
             trade.PositionModify(tkt, newSL, curTP);
          }
       }
    }

    // 4. Apri nuova posizione OGNI BARRA con segnale actionable (aggressivo)
    if(MathAbs(fs.zScore) > minZ) {
        double ask = SymbolInfoDouble(sym, SYMBOL_ASK);
        double bid = SymbolInfoDouble(sym, SYMBOL_BID);
       double price = (fs.direction == 1) ? ask : bid;
        // ATR period: scala con N agenti e buffer disponibile
        int atrPeriod = MathMax(orchestrator.TotalAgents() + 1, MathMin(bufferBars / 15, 50));
        double atr = data.ATR(atrPeriod);
        if(atr <= 0) return;

        // SL adattivo via MAE (trailing stop gestisce l'uscita, no TP fisso)
        double slWidth = (Inp_SLRiskATR > 0) ? Inp_SLRiskATR : orchestrator.AdaptiveSLWidth();
         double sl = (fs.direction == 1) ? price - atr * slWidth
                                         : price + atr * slWidth;
         sl = NormalizeDouble(sl, dig);
         double slPoints = price - sl;
         if(fs.direction == -1) slPoints = sl - price;
         if(slPoints <= 0) { Print("SL troppo stretto — skip"); return; }

         // Posizione sizing risk-based tramite Orchestrator
         double lot = orchestrator.CalcRiskLot(fs.zScore, slPoints);
         if(lot <= 0) { Print("Lot calcolato = 0 — skip"); return; }

         // Solo il margine libero limita i trade
        double freeMargin = AccountInfoDouble(ACCOUNT_MARGIN_FREE);
        double marginReq = lot * SymbolInfoDouble(sym, SYMBOL_MARGIN_INITIAL);
        if(marginReq >= freeMargin && freeMargin > 0) {
           Print("Margine insufficiente: lot=", lot, " free=", freeMargin, " req=", marginReq);
           return;  // Skip — solo il margine blocca i trade
        }

        int ticket = 0;
           // Calcolo TakeProfit opzionale (usiamo lo stesso fattoreATR per TP)
           double tp = 0;
           // TakeProfit: se impostato usa Inp_TPRiskATR, altrimenti usa lo stesso fattore di SL (dynamic)
           double tpWidth = (Inp_TPRiskATR > 0) ? Inp_TPRiskATR : ((Inp_SLRiskATR > 0) ? Inp_SLRiskATR : orchestrator.AdaptiveSLWidth());
           if(tpWidth > 0) {
               tp = (fs.direction == 1) ? price + atr * tpWidth : price - atr * tpWidth;
               tp = NormalizeDouble(tp, dig);
           }
           if(fs.direction == 1) {
              // BUY – validate SL and TP
              if(sl <= 0 || sl >= ask) {
                 Print("Invalid BUY SL (", sl, ") – order skipped");
              } else if(tp > 0 && tp <= sl) {
                 Print("Invalid BUY TP (", tp, ") – must be > SL – order skipped");
              } else {
                 ticket = trade.Buy(lot, sym, ask, sl, tp);  // TP may be 0 (no TP)
              }
           } else {
              // SELL – validate SL and TP
              if(sl <= 0 || sl <= bid) {
                 Print("Invalid SELL SL (", sl, ") – order skipped");
              } else if(tp > 0 && tp >= sl) {
                 Print("Invalid SELL TP (", tp, ") – must be < SL – order skipped");
              } else {
                 ticket = trade.Sell(lot, sym, bid, sl, tp);
              }
           }

           if(ticket > 0) {
              orchestrator.OnTradeOpen(ticket, price, atr, lot);
           }
    }
 }

void LogSignal(const MarketData &data, const FinalSignal &fs) {
   string timeStr = TimeToString(TimeCurrent(), TIME_DATE|TIME_MINUTES);
   string dir = "NONE";
   if(fs.direction == 1) dir = "BUY";
   if(fs.direction == -1) dir = "SELL";
   
   string mode = Inp_UseNeural && orchestrator.IsNeuralReady() ? "NN" : "SM";
   string log = timeStr + " [" + mode + "] " + dir;
   log += " | z=" + StringFormat("%+.3f", fs.zScore);
   log += " | conf=" + StringFormat("%.0f%%", fs.confidence*100);
   log += " | agree=" + (string)fs.agreeingCount + "/" + (string)fs.totalAgents;
   
   static int printCounter = 0;
   if(printCounter % 5 == 0) {
      orchestrator.PrintAgentStatus();
      if(Inp_UseNeural)
         Print("  ", orchestrator.NeuralInfo());
   }
   printCounter++;
   
   // Log decision even for non-actionable signals
   double minZ = (Inp_MinZ > 0) ? Inp_MinZ : orchestrator.AdaptiveMinZ();
   orchestrator.LogDecision("SIGNAL", fs.direction, minZ, data.Close(0));
   
   if(MathAbs(fs.zScore) > Inp_MinZ) {
      Print(log);
      Print("  Agents: ", fs.contributingAgents);
   }
}

// Rileva chiusure (SL/TP) fatte dal broker — multi-trade
void OnTrade() {
    static int onTradeCloses = 0;
    static int saveInterval = 0;
    if(saveInterval == 0) {
        // Minimum 5 trades, scaled with number of agents
        saveInterval = MathMax(5, orchestrator.TotalAgents() * 5);
    }
    if(!orchestrator.HasOpenTrade()) return;
    int maxSlots = orchestrator.MaxTradeSlots();
    for(int t = 0; t < maxSlots; t++) {
        int tkt = orchestrator.GetTrackedTicket(t);
        if(tkt < 0) break; // no more active trades
        bool found = false;
        for(int p = PositionsTotal() - 1; p >= 0; p--) {
            if(posInfo.SelectByIndex(p)) {
                if((int)posInfo.Ticket() == tkt) { found = true; break; }
            }
        }
        if(!found) {
            // Trade closed by SL/TP (not by ManagePositions)
            bool isBuy = orchestrator.IsBuyTrade(tkt);
            double closePrice = isBuy ? SymbolInfoDouble(sym, SYMBOL_BID) : SymbolInfoDouble(sym, SYMBOL_ASK);
            orchestrator.OnTradeClose(tkt, closePrice, "SLTP");
            onTradeCloses++;
            Print("SL/TP chiuso trade #", tkt, " (totale SL/TP: ", onTradeCloses, ")");
            if(onTradeCloses % saveInterval == 0)
                orchestrator.SaveState(sym, Inp_TF);
        }
    }
 }

double OnTester() {
   double sharpe = orchestrator.TradeSharpe();
   int trades = orchestrator.TradeCount();
   Print("OnTester: ", trades, " trade, Sharpe=", StringFormat("%.3f", sharpe));
   return sharpe;
}