Warrior_EA/Variables/ConfidenceBridge.mqh

//+------------------------------------------------------------------+
//|                                                       Warrior_EA |
//|                                                     AnimateDread |
//|                                                                  |
//+------------------------------------------------------------------+
// Money management classes (CExpertMoney) are invoked by the standard library's
// CExpert with a fixed (price, sl) signature - they have no pointer back to the
// signal filter that computed those levels. CExpertSignalCustom::OpenParams()
// refreshes these globals right before Money.CheckOpenLong/Short() is called for
// the same trade, so Money classes can read a same-tick confidence value without
// requiring an intrusive change to the wizard framework's call chain.
double g_AISignedConfidence = 0.0;   // -1..1, sign = direction, magnitude = AI confidence; 0 if no AI filter
double g_DBConfidence = 0.0;         // 0..1, historical time-based win rate of the active pattern set
// source takes CONFIDENCE_SOURCE's underlying int values (0=CONF_AI, 1=CONF_DB, 2=CONF_BLENDED).
// Declared as int rather than the enum type so this header has no dependency on the include
// order of Enumerations\InputEnums.mqh (this file is pulled in from class headers that are
// included before Inputs.mqh in Warrior_EA.mq5).
// reward:risk ratio of the specific trade OpenParams() just sized (b in the Kelly-criterion
// formula CMoneyIntelligent::AdjustRiskAmount() uses) - refreshed on the same same-tick
// contract as the two confidence globals above; always > 0 when populated, since OpenParams()
// already rejects any setup below Min_Risk_Reward_Ratio before Money is ever consulted.
double g_TradeRewardRiskRatio = 0.0;
//+------------------------------------------------------------------+
//| Combine AI/DB confidence into a single 0..1 magnitude            |
//+------------------------------------------------------------------+
double CombinedConfidence(int source)
  {
   double aiMag = MathMax(0.0, MathMin(MathAbs(g_AISignedConfidence), 1.0));
   double dbMag = MathMax(0.0, MathMin(g_DBConfidence, 1.0));
   switch(source)
     {
      case 1: // CONF_DB
         return dbMag;
      case 2: // CONF_BLENDED
         return (aiMag + dbMag) / 2.0;
      default: // CONF_AI
         return aiMag;
     }
  }
//+------------------------------------------------------------------+