Fix MQL5 compile: rename 'input' params in NeuralNet (keyword conflict), replace Orchestrator pointers with direct array access (MQL5 doesn't support struct pointers)
This commit is contained in:
pietro_giacobazzi
@@ -498,9 +498,9 @@ for(int i = 0; i < m_hidden; i++) {
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first, last, best, bestEpoch+1, ArraySize(m_lossHistory));
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first, last, best, bestEpoch+1, ArraySize(m_lossHistory));
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}
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}
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int Predict(vector &input) {
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int Predict(vector &inp) {
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vector output;
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vector output;
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Forward(input, output);
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Forward(inp, output);
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int bestIdx = 0;
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int bestIdx = 0;
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double bestVal = output[0];
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double bestVal = output[0];
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for(int i = 1; i < m_outputs; i++) {
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for(int i = 1; i < m_outputs; i++) {
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@@ -512,9 +512,9 @@ for(int i = 0; i < m_hidden; i++) {
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return bestIdx;
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return bestIdx;
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}
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}
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double GetCombinedZ(vector &input) {
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double GetCombinedZ(vector &inp) {
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vector output;
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vector output;
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Forward(input, output);
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Forward(inp, output);
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return output[0] - output[2];
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return output[0] - output[2];
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}
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}
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@@ -424,42 +424,41 @@ public:
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Print("ERROR: slot non disponibile nonostante capacity expansion");
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Print("ERROR: slot non disponibile nonostante capacity expansion");
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return -1;
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return -1;
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}
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}
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TrackedTrade *t = &openTrades[idx];
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openTrades[idx].ticket = ticket;
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t.ticket = ticket;
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openTrades[idx].entryPrice = price;
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t.entryPrice = price;
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openTrades[idx].entryATR = MathMax(atr, 1e-10);
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t.entryATR = MathMax(atr, 1e-10);
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openTrades[idx].entryZ = z;
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t.entryZ = z;
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openTrades[idx].isBuy = isBuy;
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t.isBuy = isBuy;
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openTrades[idx].highestPrice = price;
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t.highestPrice = price;
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openTrades[idx].lowestPrice = price;
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t.lowestPrice = price;
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openTrades[idx].barsHeld = 0;
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t.barsHeld = 0;
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openTrades[idx].maeATR = 0;
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t.maeATR = 0;
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openTrades[idx].mfeATR = 0;
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t.mfeATR = 0;
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openTrades[idx].active = true;
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t.active = true;
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for(int i=0; i<agentCount; i++)
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for(int i=0; i<agentCount; i++)
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t.entryZScores[i] = agents[i].lastZScore;
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openTrades[idx].entryZScores[i] = agents[i].lastZScore;
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// Feature vector per NN
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// Feature vector per NN
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for(int f = 0; f < NN_FEATURES; f++) t.entryFeatures[f] = 0.0;
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for(int f = 0; f < NN_FEATURES; f++) openTrades[idx].entryFeatures[f] = 0.0;
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for(int i=0; i<agentCount; i++) {
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for(int i=0; i<agentCount; i++) {
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if(agents[i].name == "Hurst") t.entryFeatures[0] = agents[i].lastZScore;
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if(agents[i].name == "Hurst") openTrades[idx].entryFeatures[0] = agents[i].lastZScore;
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else if(agents[i].name == "ADX") t.entryFeatures[1] = agents[i].lastZScore;
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else if(agents[i].name == "ADX") openTrades[idx].entryFeatures[1] = agents[i].lastZScore;
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else if(agents[i].name == "MA") t.entryFeatures[2] = agents[i].lastZScore;
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else if(agents[i].name == "MA") openTrades[idx].entryFeatures[2] = agents[i].lastZScore;
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else if(agents[i].name == "Momentum") t.entryFeatures[3] = agents[i].lastZScore;
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else if(agents[i].name == "Momentum") openTrades[idx].entryFeatures[3] = agents[i].lastZScore;
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else if(agents[i].name == "Consensus") t.entryFeatures[4] = agents[i].lastZScore;
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else if(agents[i].name == "Consensus") openTrades[idx].entryFeatures[4] = agents[i].lastZScore;
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else if(agents[i].name == "Hunter") t.entryFeatures[5] = agents[i].lastZScore;
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else if(agents[i].name == "Hunter") openTrades[idx].entryFeatures[5] = agents[i].lastZScore;
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}
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}
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t.entryFeatures[6] = SHARED_regimeAgreement;
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openTrades[idx].entryFeatures[6] = SHARED_regimeAgreement;
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t.entryFeatures[7] = SHARED_trendStrength;
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openTrades[idx].entryFeatures[7] = SHARED_trendStrength;
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// SL iniziale adattivo
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// SL iniziale adattivo
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double slWidth = AdaptiveSLWidth();
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double slWidth = AdaptiveSLWidth();
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t.slPrice = isBuy ? price - atr * slWidth : price + atr * slWidth;
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openTrades[idx].slPrice = isBuy ? price - atr * slWidth : price + atr * slWidth;
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Print("Trade #", ticket, " ", isBuy ? "BUY" : "SELL",
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Print("Trade #", ticket, " ", isBuy ? "BUY" : "SELL",
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" entry=", price, " z=", StringFormat("%+.3f", z),
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" entry=", price, " z=", StringFormat("%+.3f", z),
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" SL=", StringFormat("%.5f", t.slPrice),
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" SL=", StringFormat("%.5f", openTrades[idx].slPrice),
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" (", StringFormat("%.1f", slWidth), " ATR)");
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" (", StringFormat("%.1f", slWidth), " ATR)");
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return idx;
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return idx;
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}
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}
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@@ -476,44 +475,42 @@ void OnTradeClose(int ticket, double closePrice) {
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}
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}
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if(idx < 0) return;
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if(idx < 0) return;
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TrackedTrade *t = &openTrades[idx];
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// Calcola MAE/MFE finali
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if(openTrades[idx].isBuy) {
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openTrades[idx].maeATR = (openTrades[idx].entryPrice - openTrades[idx].lowestPrice) / openTrades[idx].entryATR;
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openTrades[idx].mfeATR = (openTrades[idx].highestPrice - openTrades[idx].entryPrice) / openTrades[idx].entryATR;
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} else {
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openTrades[idx].maeATR = (openTrades[idx].highestPrice - openTrades[idx].entryPrice) / openTrades[idx].entryATR;
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openTrades[idx].mfeATR = (openTrades[idx].entryPrice - openTrades[idx].lowestPrice) / openTrades[idx].entryATR;
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}
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// Calcola MAE/MFE finali
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// ROI in ATR (positivo = profitto nella direzione del trade)
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if(t.isBuy) {
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double actualReturn = openTrades[idx].isBuy
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t.maeATR = (t.entryPrice - t.lowestPrice) / t.entryATR;
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? (closePrice - openTrades[idx].entryPrice) / openTrades[idx].entryATR
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t.mfeATR = (t.highestPrice - t.entryPrice) / t.entryATR;
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: (openTrades[idx].entryPrice - closePrice) / openTrades[idx].entryATR;
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} else {
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t.maeATR = (t.highestPrice - t.entryPrice) / t.entryATR;
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t.mfeATR = (t.entryPrice - t.lowestPrice) / t.entryATR;
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}
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// ROI in ATR (positivo = profitto nella direzione del trade)
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returnStats.Update(actualReturn);
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double actualReturn = t.isBuy
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maeStats.Update(openTrades[idx].maeATR);
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? (closePrice - t.entryPrice) / t.entryATR
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mfeStats.Update(openTrades[idx].mfeATR);
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: (t.entryPrice - closePrice) / t.entryATR;
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if(actualReturn > 0) maeWinStats.Update(openTrades[idx].maeATR);
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returnStats.Update(actualReturn);
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tradeReturns[tradeCount % ROLLING_TRADES] = actualReturn;
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maeStats.Update(t.maeATR);
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tradeCount++;
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mfeStats.Update(t.mfeATR);
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if(actualReturn > 0) winCount++;
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if(actualReturn > 0) maeWinStats.Update(t.maeATR);
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tradeReturns[tradeCount % ROLLING_TRADES] = actualReturn;
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double eq = AccountInfoDouble(ACCOUNT_EQUITY);
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tradeCount++;
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if(eq > peakEquity) peakEquity = eq;
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if(actualReturn > 0) winCount++;
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double dd = (peakEquity > 0) ? (peakEquity - eq) / peakEquity : 0;
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if(dd > maxDrawdown) maxDrawdown = dd;
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double actualReturnZ = returnStats.RawZScore(actualReturn);
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double eq = AccountInfoDouble(ACCOUNT_EQUITY);
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Print("=== Learning: Trade #", ticket, " ", openTrades[idx].isBuy ? "BUY" : "SELL", " chiuso ===");
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if(eq > peakEquity) peakEquity = eq;
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Print(" Return: ", StringFormat("%+.2f ATR", actualReturn),
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double dd = (peakEquity > 0) ? (peakEquity - eq) / peakEquity : 0;
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" | MAE: ", StringFormat("%.2f", openTrades[idx].maeATR),
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if(dd > maxDrawdown) maxDrawdown = dd;
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" | MFE: ", StringFormat("%.2f", openTrades[idx].mfeATR),
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double actualReturnZ = returnStats.RawZScore(actualReturn);
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" | bars: ", openTrades[idx].barsHeld);
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Print(" Entry z=", StringFormat("%+.3f", openTrades[idx].entryZ),
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Print("=== Learning: Trade #", ticket, " ", t.isBuy ? "BUY" : "SELL", " chiuso ===");
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" | SL width: ", StringFormat("%.2f ATR", AdaptiveSLWidth()));
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Print(" Return: ", StringFormat("%+.2f ATR", actualReturn),
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" | MAE: ", StringFormat("%.2f", t.maeATR),
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" | MFE: ", StringFormat("%.2f", t.mfeATR),
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" | bars: ", t.barsHeld);
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Print(" Entry z=", StringFormat("%+.3f", t.entryZ),
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" | SL width: ", StringFormat("%.2f ATR", AdaptiveSLWidth()));
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double sigThr = combinedZStats.Ready()
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double sigThr = combinedZStats.Ready()
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? combinedZStats.Std() / MathSqrt(MathMax(1, agentCount))
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? combinedZStats.Std() / MathSqrt(MathMax(1, agentCount))
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@@ -521,55 +518,55 @@ void OnTradeClose(int ticket, double closePrice) {
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for(int i=0; i<agentCount; i++) {
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for(int i=0; i<agentCount; i++) {
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if(MathAbs(t.entryZScores[i]) < sigThr) continue;
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if(MathAbs(t.entryZScores[i]) < sigThr) continue;
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UpdateCorrelation(i, t.entryZScores[i], actualReturnZ);
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UpdateCorrelation(i, openTrades[idx].entryZScores[i], actualReturnZ);
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double rho = GetCorrelation(i);
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double rho = GetCorrelation(i);
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agents[i].weight = MathMax(weightMin, rho);
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agents[i].weight = MathMax(weightMin, rho);
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agents[i].Learn(t.entryZScores[i], actualReturnZ);
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agents[i].Learn(openTrades[idx].entryZScores[i], actualReturnZ);
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double bias = agents[i].predictionError.Mean();
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double bias = agents[i].predictionError.Mean();
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double biasStd = agents[i].predictionError.Std();
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double biasStd = agents[i].predictionError.Std();
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double rhoLearn = agents[i].predCorr.Ready() ? agents[i].predCorr.Correlation() : 0;
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double rhoLearn = agents[i].predCorr.Ready() ? agents[i].predCorr.Correlation() : 0;
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Print(" ", agents[i].name,
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Print(" ", agents[i].name,
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" | pred=", StringFormat("%+.2f", t.entryZScores[i]),
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" | pred=", StringFormat("%+.2f", openTrades[idx].entryZScores[i]),
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" | ρ=", StringFormat("%+.3f", rho),
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" | ρ=", StringFormat("%+.3f", rho),
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" | w=", StringFormat("%.3f", agents[i].weight),
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" | w=", StringFormat("%.3f", agents[i].weight),
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" | bias=", StringFormat("%+.4f", bias),
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" | bias=", StringFormat("%+.4f", bias),
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" | biasσ=", StringFormat("%.4f", biasStd),
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" | biasσ=", StringFormat("%.4f", biasStd),
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" | ρ_learn=", StringFormat("%+.3f", rhoLearn));
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" | ρ_learn=", StringFormat("%+.3f", rhoLearn));
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}
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}
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// --- Neural Network: colleziona training sample ---
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// --- Neural Network: colleziona training sample ---
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if(m_trainMode && m_trainBuffer != NULL && m_neuralNet != NULL) {
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if(m_trainMode && m_trainBuffer != NULL && m_neuralNet != NULL) {
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double features[NN_FEATURES];
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double features[NN_FEATURES];
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double target[NN_TARGETS];
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double target[NN_TARGETS];
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for(int f = 0; f < NN_FEATURES; f++) features[f] = t.entryFeatures[f];
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for(int f = 0; f < NN_FEATURES; f++) features[f] = openTrades[idx].entryFeatures[f];
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target[0] = 0; target[1] = 0; target[2] = 0;
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target[0] = 0; target[1] = 0; target[2] = 0;
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int tradeDir = t.isBuy ? 1 : -1;
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int tradeDir = openTrades[idx].isBuy ? 1 : -1;
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if(actualReturn > 0) {
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if(actualReturn > 0) {
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if(tradeDir == 1) target[0] = 1;
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if(tradeDir == 1) target[0] = 1;
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else target[2] = 1;
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else target[2] = 1;
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} else {
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} else {
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if(tradeDir == 1) target[2] = 1;
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if(tradeDir == 1) target[2] = 1;
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else target[0] = 1;
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else target[0] = 1;
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}
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}
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double sampleWeight = MathAbs(actualReturn) + 1.0; // trade profittevoli/perdenti pesano di più
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double sampleWeight = MathAbs(actualReturn) + 1.0; // trade profittevoli/perdenti pesano di più
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m_trainBuffer.Add(features, target, sampleWeight);
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m_trainBuffer.Add(features, target, sampleWeight);
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if(m_trainBuffer.Count() < 20)
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if(m_trainBuffer.Count() < 20)
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Print(" NN sample #", m_trainBuffer.Count(), " collected (w=", StringFormat("%.2f", sampleWeight), ")");
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Print(" NN sample #", m_trainBuffer.Count(), " collected (w=", StringFormat("%.2f", sampleWeight), ")");
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if(m_trainBuffer.Count() % 50 == 0 && m_trainBuffer.Count() >= 20) {
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if(m_trainBuffer.Count() % 50 == 0 && m_trainBuffer.Count() >= 20) {
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if(m_useNeural) {
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if(m_useNeural) {
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TrainNN();
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TrainNN();
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string nnFn = (m_modelFilename != "") ? m_modelFilename : "TR_Agent_NN_v1.dat";
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string nnFn = (m_modelFilename != "") ? m_modelFilename : "TR_Agent_NN_v1.dat";
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m_neuralNet.Save(nnFn);
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m_neuralNet.Save(nnFn);
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Print(" NN auto-saved to ", nnFn, " after ", m_trainBuffer.Count(), " samples");
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Print(" NN auto-saved to ", nnFn, " after ", m_trainBuffer.Count(), " samples");
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}
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}
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}
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}
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}
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}
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@@ -588,40 +585,38 @@ void OnTradeClose(int ticket, double closePrice) {
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}
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}
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// Aggiorna MAE/MFE per tutti i trade aperti (chiamato ogni barra)
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// Aggiorna MAE/MFE per tutti i trade aperti (chiamato ogni barra)
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void UpdateOpenTrades(double high, double low) {
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void UpdateOpenTrades(double high, double low) {
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for(int i=0; i<maxOpenTrades; i++) {
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for(int i=0; i<maxOpenTrades; i++) {
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if(!openTrades[i].active) continue;
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if(!openTrades[i].active) continue;
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TrackedTrade *t = &openTrades[i];
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if(high > openTrades[i].highestPrice) openTrades[i].highestPrice = high;
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if(high > t.highestPrice) t.highestPrice = high;
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if(low < openTrades[i].lowestPrice) openTrades[i].lowestPrice = low;
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if(low < t.lowestPrice) t.lowestPrice = low;
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openTrades[i].barsHeld++;
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t.barsHeld++;
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}
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}
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}
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}
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// Trailing stop: sposta SL dopo che il profitto supera la soglia
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// Trailing stop: sposta SL dopo che il profitto supera la soglia
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void TrailStops() {
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void TrailStops() {
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for(int i=0; i<maxOpenTrades; i++) {
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for(int i=0; i<maxOpenTrades; i++) {
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if(!openTrades[i].active) continue;
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if(!openTrades[i].active) continue;
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TrackedTrade *t = &openTrades[i];
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double profitATR = t.isBuy
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double profitATR = openTrades[i].isBuy
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? (t.highestPrice - t.entryPrice) / t.entryATR
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? (openTrades[i].highestPrice - openTrades[i].entryPrice) / openTrades[i].entryATR
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: (t.entryPrice - t.lowestPrice) / t.entryATR;
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: (openTrades[i].entryPrice - openTrades[i].lowestPrice) / openTrades[i].entryATR;
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double trigger = AdaptiveTrailTrigger();
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double trigger = AdaptiveTrailTrigger();
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if(profitATR > trigger) {
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if(profitATR > trigger) {
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double offset = AdaptiveTrailOffset();
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double offset = AdaptiveTrailOffset();
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double newSL;
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double newSL;
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if(t.isBuy) {
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if(openTrades[i].isBuy) {
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newSL = t.highestPrice - offset * t.entryATR;
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newSL = openTrades[i].highestPrice - offset * openTrades[i].entryATR;
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if(newSL > t.slPrice) t.slPrice = newSL;
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if(newSL > openTrades[i].slPrice) openTrades[i].slPrice = newSL;
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} else {
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} else {
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newSL = t.lowestPrice + offset * t.entryATR;
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newSL = openTrades[i].lowestPrice + offset * openTrades[i].entryATR;
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if(newSL < t.slPrice) t.slPrice = newSL;
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if(newSL < openTrades[i].slPrice) openTrades[i].slPrice = newSL;
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}
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}
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}
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}
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}
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}
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}
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}
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// Trade da chiudere per inversione di segnale (ritorna array di ticket)
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// Trade da chiudere per inversione di segnale (ritorna array di ticket)
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void GetTradesToClose(int &closeTickets[], double currentZ, double minZ) {
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void GetTradesToClose(int &closeTickets[], double currentZ, double minZ) {
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