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Fix MQL5 compile: rename 'input' params in NeuralNet (keyword conflict), replace Orchestrator pointers with direct array access (MQL5 doesn't support struct pointers)

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pietro_giacobazzi
2026-06-13 15:18:49 +02:00
parent c70c2f28ce
commit a29befcd67
2 changed files with 128 additions and 133 deletions
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MQL5/Experts/MultiAgentTest/Core/NeuralNet.mqh
+4 -4
View File
@@ -498,9 +498,9 @@ for(int i = 0; i < m_hidden; i++) {
first, last, best, bestEpoch+1, ArraySize(m_lossHistory)); first, last, best, bestEpoch+1, ArraySize(m_lossHistory));
} }
int Predict(vector &input) { int Predict(vector &inp) {
vector output; vector output;
Forward(input, output); Forward(inp, output);
int bestIdx = 0; int bestIdx = 0;
double bestVal = output[0]; double bestVal = output[0];
for(int i = 1; i < m_outputs; i++) { for(int i = 1; i < m_outputs; i++) {
@@ -512,9 +512,9 @@ for(int i = 0; i < m_hidden; i++) {
return bestIdx; return bestIdx;
} }
double GetCombinedZ(vector &input) { double GetCombinedZ(vector &inp) {
vector output; vector output;
Forward(input, output); Forward(inp, output);
return output[0] - output[2]; return output[0] - output[2];
} }
MQL5/Experts/MultiAgentTest/Core/Orchestrator.mqh
+55 -60
View File
@@ -424,42 +424,41 @@ public:
Print("ERROR: slot non disponibile nonostante capacity expansion"); Print("ERROR: slot non disponibile nonostante capacity expansion");
return -1; return -1;
} }
TrackedTrade *t = &openTrades[idx]; openTrades[idx].ticket = ticket;
t.ticket = ticket; openTrades[idx].entryPrice = price;
t.entryPrice = price; openTrades[idx].entryATR = MathMax(atr, 1e-10);
t.entryATR = MathMax(atr, 1e-10); openTrades[idx].entryZ = z;
t.entryZ = z; openTrades[idx].isBuy = isBuy;
t.isBuy = isBuy; openTrades[idx].highestPrice = price;
t.highestPrice = price; openTrades[idx].lowestPrice = price;
t.lowestPrice = price; openTrades[idx].barsHeld = 0;
t.barsHeld = 0; openTrades[idx].maeATR = 0;
t.maeATR = 0; openTrades[idx].mfeATR = 0;
t.mfeATR = 0; openTrades[idx].active = true;
t.active = true;
for(int i=0; i<agentCount; i++) for(int i=0; i<agentCount; i++)
t.entryZScores[i] = agents[i].lastZScore; openTrades[idx].entryZScores[i] = agents[i].lastZScore;
// Feature vector per NN // Feature vector per NN
for(int f = 0; f < NN_FEATURES; f++) t.entryFeatures[f] = 0.0; for(int f = 0; f < NN_FEATURES; f++) openTrades[idx].entryFeatures[f] = 0.0;
for(int i=0; i<agentCount; i++) { for(int i=0; i<agentCount; i++) {
if(agents[i].name == "Hurst") t.entryFeatures[0] = agents[i].lastZScore; if(agents[i].name == "Hurst") openTrades[idx].entryFeatures[0] = agents[i].lastZScore;
else if(agents[i].name == "ADX") t.entryFeatures[1] = agents[i].lastZScore; else if(agents[i].name == "ADX") openTrades[idx].entryFeatures[1] = agents[i].lastZScore;
else if(agents[i].name == "MA") t.entryFeatures[2] = agents[i].lastZScore; else if(agents[i].name == "MA") openTrades[idx].entryFeatures[2] = agents[i].lastZScore;
else if(agents[i].name == "Momentum") t.entryFeatures[3] = agents[i].lastZScore; else if(agents[i].name == "Momentum") openTrades[idx].entryFeatures[3] = agents[i].lastZScore;
else if(agents[i].name == "Consensus") t.entryFeatures[4] = agents[i].lastZScore; else if(agents[i].name == "Consensus") openTrades[idx].entryFeatures[4] = agents[i].lastZScore;
else if(agents[i].name == "Hunter") t.entryFeatures[5] = agents[i].lastZScore; else if(agents[i].name == "Hunter") openTrades[idx].entryFeatures[5] = agents[i].lastZScore;
} }
t.entryFeatures[6] = SHARED_regimeAgreement; openTrades[idx].entryFeatures[6] = SHARED_regimeAgreement;
t.entryFeatures[7] = SHARED_trendStrength; openTrades[idx].entryFeatures[7] = SHARED_trendStrength;
// SL iniziale adattivo // SL iniziale adattivo
double slWidth = AdaptiveSLWidth(); double slWidth = AdaptiveSLWidth();
t.slPrice = isBuy ? price - atr * slWidth : price + atr * slWidth; openTrades[idx].slPrice = isBuy ? price - atr * slWidth : price + atr * slWidth;
Print("Trade #", ticket, " ", isBuy ? "BUY" : "SELL", Print("Trade #", ticket, " ", isBuy ? "BUY" : "SELL",
" entry=", price, " z=", StringFormat("%+.3f", z), " entry=", price, " z=", StringFormat("%+.3f", z),
" SL=", StringFormat("%.5f", t.slPrice), " SL=", StringFormat("%.5f", openTrades[idx].slPrice),
" (", StringFormat("%.1f", slWidth), " ATR)"); " (", StringFormat("%.1f", slWidth), " ATR)");
return idx; return idx;
} }
@@ -476,26 +475,24 @@ void OnTradeClose(int ticket, double closePrice) {
} }
if(idx < 0) return; if(idx < 0) return;
TrackedTrade *t = &openTrades[idx];
// Calcola MAE/MFE finali // Calcola MAE/MFE finali
if(t.isBuy) { if(openTrades[idx].isBuy) {
t.maeATR = (t.entryPrice - t.lowestPrice) / t.entryATR; openTrades[idx].maeATR = (openTrades[idx].entryPrice - openTrades[idx].lowestPrice) / openTrades[idx].entryATR;
t.mfeATR = (t.highestPrice - t.entryPrice) / t.entryATR; openTrades[idx].mfeATR = (openTrades[idx].highestPrice - openTrades[idx].entryPrice) / openTrades[idx].entryATR;
} else { } else {
t.maeATR = (t.highestPrice - t.entryPrice) / t.entryATR; openTrades[idx].maeATR = (openTrades[idx].highestPrice - openTrades[idx].entryPrice) / openTrades[idx].entryATR;
t.mfeATR = (t.entryPrice - t.lowestPrice) / t.entryATR; openTrades[idx].mfeATR = (openTrades[idx].entryPrice - openTrades[idx].lowestPrice) / openTrades[idx].entryATR;
} }
// ROI in ATR (positivo = profitto nella direzione del trade) // ROI in ATR (positivo = profitto nella direzione del trade)
double actualReturn = t.isBuy double actualReturn = openTrades[idx].isBuy
? (closePrice - t.entryPrice) / t.entryATR ? (closePrice - openTrades[idx].entryPrice) / openTrades[idx].entryATR
: (t.entryPrice - closePrice) / t.entryATR; : (openTrades[idx].entryPrice - closePrice) / openTrades[idx].entryATR;
returnStats.Update(actualReturn); returnStats.Update(actualReturn);
maeStats.Update(t.maeATR); maeStats.Update(openTrades[idx].maeATR);
mfeStats.Update(t.mfeATR); mfeStats.Update(openTrades[idx].mfeATR);
if(actualReturn > 0) maeWinStats.Update(t.maeATR); if(actualReturn > 0) maeWinStats.Update(openTrades[idx].maeATR);
tradeReturns[tradeCount % ROLLING_TRADES] = actualReturn; tradeReturns[tradeCount % ROLLING_TRADES] = actualReturn;
tradeCount++; tradeCount++;
@@ -507,12 +504,12 @@ void OnTradeClose(int ticket, double closePrice) {
if(dd > maxDrawdown) maxDrawdown = dd; if(dd > maxDrawdown) maxDrawdown = dd;
double actualReturnZ = returnStats.RawZScore(actualReturn); double actualReturnZ = returnStats.RawZScore(actualReturn);
Print("=== Learning: Trade #", ticket, " ", t.isBuy ? "BUY" : "SELL", " chiuso ==="); Print("=== Learning: Trade #", ticket, " ", openTrades[idx].isBuy ? "BUY" : "SELL", " chiuso ===");
Print(" Return: ", StringFormat("%+.2f ATR", actualReturn), Print(" Return: ", StringFormat("%+.2f ATR", actualReturn),
" | MAE: ", StringFormat("%.2f", t.maeATR), " | MAE: ", StringFormat("%.2f", openTrades[idx].maeATR),
" | MFE: ", StringFormat("%.2f", t.mfeATR), " | MFE: ", StringFormat("%.2f", openTrades[idx].mfeATR),
" | bars: ", t.barsHeld); " | bars: ", openTrades[idx].barsHeld);
Print(" Entry z=", StringFormat("%+.3f", t.entryZ), Print(" Entry z=", StringFormat("%+.3f", openTrades[idx].entryZ),
" | SL width: ", StringFormat("%.2f ATR", AdaptiveSLWidth())); " | SL width: ", StringFormat("%.2f ATR", AdaptiveSLWidth()));
double sigThr = combinedZStats.Ready() double sigThr = combinedZStats.Ready()
@@ -521,19 +518,19 @@ void OnTradeClose(int ticket, double closePrice) {
for(int i=0; i<agentCount; i++) { for(int i=0; i<agentCount; i++) {
if(MathAbs(t.entryZScores[i]) < sigThr) continue; if(MathAbs(t.entryZScores[i]) < sigThr) continue;
UpdateCorrelation(i, t.entryZScores[i], actualReturnZ); UpdateCorrelation(i, openTrades[idx].entryZScores[i], actualReturnZ);
double rho = GetCorrelation(i); double rho = GetCorrelation(i);
agents[i].weight = MathMax(weightMin, rho); agents[i].weight = MathMax(weightMin, rho);
agents[i].Learn(t.entryZScores[i], actualReturnZ); agents[i].Learn(openTrades[idx].entryZScores[i], actualReturnZ);
double bias = agents[i].predictionError.Mean(); double bias = agents[i].predictionError.Mean();
double biasStd = agents[i].predictionError.Std(); double biasStd = agents[i].predictionError.Std();
double rhoLearn = agents[i].predCorr.Ready() ? agents[i].predCorr.Correlation() : 0; double rhoLearn = agents[i].predCorr.Ready() ? agents[i].predCorr.Correlation() : 0;
Print(" ", agents[i].name, Print(" ", agents[i].name,
" | pred=", StringFormat("%+.2f", t.entryZScores[i]), " | pred=", StringFormat("%+.2f", openTrades[idx].entryZScores[i]),
" | ρ=", StringFormat("%+.3f", rho), " | ρ=", StringFormat("%+.3f", rho),
" | w=", StringFormat("%.3f", agents[i].weight), " | w=", StringFormat("%.3f", agents[i].weight),
" | bias=", StringFormat("%+.4f", bias), " | bias=", StringFormat("%+.4f", bias),
@@ -545,10 +542,10 @@ void OnTradeClose(int ticket, double closePrice) {
if(m_trainMode && m_trainBuffer != NULL && m_neuralNet != NULL) { if(m_trainMode && m_trainBuffer != NULL && m_neuralNet != NULL) {
double features[NN_FEATURES]; double features[NN_FEATURES];
double target[NN_TARGETS]; double target[NN_TARGETS];
for(int f = 0; f < NN_FEATURES; f++) features[f] = t.entryFeatures[f]; for(int f = 0; f < NN_FEATURES; f++) features[f] = openTrades[idx].entryFeatures[f];
target[0] = 0; target[1] = 0; target[2] = 0; target[0] = 0; target[1] = 0; target[2] = 0;
int tradeDir = t.isBuy ? 1 : -1; int tradeDir = openTrades[idx].isBuy ? 1 : -1;
if(actualReturn > 0) { if(actualReturn > 0) {
if(tradeDir == 1) target[0] = 1; if(tradeDir == 1) target[0] = 1;
@@ -591,10 +588,9 @@ void OnTradeClose(int ticket, double closePrice) {
void UpdateOpenTrades(double high, double low) { void UpdateOpenTrades(double high, double low) {
for(int i=0; i<maxOpenTrades; i++) { for(int i=0; i<maxOpenTrades; i++) {
if(!openTrades[i].active) continue; if(!openTrades[i].active) continue;
TrackedTrade *t = &openTrades[i]; if(high > openTrades[i].highestPrice) openTrades[i].highestPrice = high;
if(high > t.highestPrice) t.highestPrice = high; if(low < openTrades[i].lowestPrice) openTrades[i].lowestPrice = low;
if(low < t.lowestPrice) t.lowestPrice = low; openTrades[i].barsHeld++;
t.barsHeld++;
} }
} }
@@ -602,22 +598,21 @@ void OnTradeClose(int ticket, double closePrice) {
void TrailStops() { void TrailStops() {
for(int i=0; i<maxOpenTrades; i++) { for(int i=0; i<maxOpenTrades; i++) {
if(!openTrades[i].active) continue; if(!openTrades[i].active) continue;
TrackedTrade *t = &openTrades[i];
double profitATR = t.isBuy double profitATR = openTrades[i].isBuy
? (t.highestPrice - t.entryPrice) / t.entryATR ? (openTrades[i].highestPrice - openTrades[i].entryPrice) / openTrades[i].entryATR
: (t.entryPrice - t.lowestPrice) / t.entryATR; : (openTrades[i].entryPrice - openTrades[i].lowestPrice) / openTrades[i].entryATR;
double trigger = AdaptiveTrailTrigger(); double trigger = AdaptiveTrailTrigger();
if(profitATR > trigger) { if(profitATR > trigger) {
double offset = AdaptiveTrailOffset(); double offset = AdaptiveTrailOffset();
double newSL; double newSL;
if(t.isBuy) { if(openTrades[i].isBuy) {
newSL = t.highestPrice - offset * t.entryATR; newSL = openTrades[i].highestPrice - offset * openTrades[i].entryATR;
if(newSL > t.slPrice) t.slPrice = newSL; if(newSL > openTrades[i].slPrice) openTrades[i].slPrice = newSL;
} else { } else {
newSL = t.lowestPrice + offset * t.entryATR; newSL = openTrades[i].lowestPrice + offset * openTrades[i].entryATR;
if(newSL < t.slPrice) t.slPrice = newSL; if(newSL < openTrades[i].slPrice) openTrades[i].slPrice = newSL;
} }
} }
} }