Warrior_EA/Signals/SignalHYBRID.mqh

//+------------------------------------------------------------------+
//|                                                       Warrior_EA |
//|                                                     AnimateDread |
//|                                                                  |
//+------------------------------------------------------------------+
#include "..\Expert\ExpertSignalAIBase.mqh"
// wizard description start
//+------------------------------------------------------------------+
//| Description of the class                                         |
//| Title=Signals of indicator 'CNN-LSTM AI'                         |
//| Type=SignalAdvanced                                              |
//| Name=CNN-LSTM AI                                                 |
//| ShortName=HYB                                                    |
//| Class=CSignalHYBRID                                              |
//| Page=signal_hybrid                                               |
//+------------------------------------------------------------------+
// wizard description end
//+------------------------------------------------------------------+
//| Class CSignalHYBRID.                                             |
//| Purpose: a single fused CNN-LSTM signal that stacks Conv+Pool    |
//| layers before the LSTM layer, then the shared dense taper.       |
//| The base AI voting path still applies, so this module trades as  |
//| one coherent signal instead of three loosely synchronized ones.  |
//+------------------------------------------------------------------+
class CSignalHYBRID : public CExpertSignalAIBase
  {
protected:
   virtual bool      AddCustomLayers(CArrayObj *topology) override;
   //--- AddCustomLayers below appends BOTH stages, conv first - so this topology's LSTM is fed the conv
   //--- feature map rather than the raw input. Keep these in step with AddCustomLayers: they are what let
   //--- the capacity budget size the recurrent block against its REAL fan-in (see LstmFanIn()).
   virtual bool      UsesConvStage(void) const override { return true; }
   virtual bool      UsesLstmStage(void) const override { return true; }
   virtual ENUM_ACTIVATION HiddenLayerActivation(void) override { return TANH; }
public:
                     CSignalHYBRID(void);
   virtual bool      InitIndicators(CIndicators *indicators) override;
  };
//+------------------------------------------------------------------+
//| Constructor                                                      |
//+------------------------------------------------------------------+
CSignalHYBRID::CSignalHYBRID(void)
  {
   //--- Display name follows the 2026-08-15 rename (AI_CONVLSTM: conv front-end + LSTM).
   //--- The SHORT id stays "HYB" deliberately: it names the model folder
   //--- (Neural Networks\State\HYB\) and changing it would orphan every model trained
   //--- under the old path - a rename is not worth a forced retrain.
   SetIdentity("ConvLSTM", "HYB");
  }
//+------------------------------------------------------------------+
//| Create indicators and bootstrap/load the network.                |
//+------------------------------------------------------------------+
bool CSignalHYBRID::InitIndicators(CIndicators *indicators)
  {
   return InitNeuralNetwork(indicators);
  }
//+------------------------------------------------------------------+
//| Conv + Pool front-end followed by an LSTM sequence layer. This   |
//| matches the standalone CONV front-end exactly, then adds LSTM.   |
//+------------------------------------------------------------------+
bool CSignalHYBRID::AddCustomLayers(CArrayObj *topology)
  {
   //--- "the standalone CONV front-end exactly, then adds LSTM" is now enforced by construction:
   //--- both stages are the same code CSignalCONV and CSignalLSTM run.
   return AddConvStage(topology) && AddLstmStage(topology);
  }
//+------------------------------------------------------------------+