LearningSnapshot buildSnapshot() {
    LearningSnapshot s;
    s.meanScore = 0; s.meanCompactness = 0; s.meanVol = 0;
    for(int i=0;i<N_ASSETS;i++) {
      s.meanScore += (double)scores[i];
      s.meanCompactness += (double)compactness[i];
      s.meanVol += (double)featSoA.get(2, i, 0);
    }
    s.meanScore /= (double)N_ASSETS;
    s.meanCompactness /= (double)N_ASSETS;
    s.meanVol /= (double)N_ASSETS;

    double sumAbs = 0;
    double sumSq = 0;
    int nCorr = 0;
    for(int i=0;i<N_ASSETS;i++) {
      for(int j=i+1;j<N_ASSETS;j++) {
        double c = fabs((double)corrMatrix[i*N_ASSETS + j]);
        sumAbs += c;
        sumSq += c * c;
        nCorr++;
      }
    }
    if(nCorr > 0) {
      s.meanAbsCorr = sumAbs / (double)nCorr;
      double m2 = sumSq / (double)nCorr - s.meanAbsCorr * s.meanAbsCorr;
      if(m2 < 0) m2 = 0;
      s.stdAbsCorr = sqrt(m2);
    } else {
      s.meanAbsCorr = 0;
      s.stdAbsCorr = 0;
    }

    s.momentumMean = 0;
    for(int i=0;i<N_ASSETS;i++) s.momentumMean += (double)featSoA.get(1, i, 0);
    s.momentumMean /= (double)N_ASSETS;

    s.regime = 0;
    s.regimeConfidence = 0;
    return s;
  }

  void onBar() {
    barCount++;

    for(int i=0;i<N_ASSETS;i++) computeFeatures(i);

    if(barCount % UPDATE_EVERY == 0) {
      updateCount++;

      computeCorrelationMatrix();
      computeDistanceMatrix();
#if USE_COMMUNITY
      hclust.update(distMatrix.data);
#endif
#if USE_COMMUNITY
      comm.update(corrMatrix.data, distMatrix.data);
#endif
      floydWarshall();
      computeScores();
      LearningSnapshot snap = buildSnapshot();
      controller.onUpdate(snap, scores.data, N_ASSETS, updateCount);
#if USE_DENSITY
      double dz[DENSITY_DIM];
      densityState.build(snap, updateCount, openCL.ready, controller.scoreScale, controller.dynamicTopK, dz);
      densityModel.observe(dz, updateCount, &densityLabel, &densityConf, &densityNoise);
      densityRegimeCtrl.apply(densityNoise, densityLabel, densityConf, STRATEGY_PROFILE, &controller.dynamicTopK, &controller.scoreScale, &controller.riskScale);
      for(int i=0;i<N_ASSETS;i++) {
        double s = (double)scores[i] * densityRegimeCtrl.appliedRiskScale;
        if(s > 1.0) s = 1.0;
        if(s < 0.0) s = 0.0;
        scores[i] = (fvar)s;
      }
#endif
#if USE_AE
      double aeState[AE_INPUT_DIM];
      double ms=0, mc=0, mv=0;
      for(int i=0;i<N_ASSETS;i++){ ms += (double)scores[i]; mc += (double)compactness[i]; mv += (double)featSoA.get(2, i, 0); }
      ms /= (double)N_ASSETS; mc /= (double)N_ASSETS; mv /= (double)N_ASSETS;
      aeState[0] = ms;
      aeState[1] = mc;
      aeState[2] = mv;
      aeState[3] = controller.scoreScale;
      aeState[4] = (double)controller.dynamicTopK;
      aeState[5] = (double)barCount / (double)(LookBack + 1);
      aeState[6] = (double)updateCount / 1000.0;
      aeState[7] = (double)openCL.ready;
      double reconErr = ae.infer(aeState);
      novelty.update(reconErr);
      novelty.apply(&controller.dynamicTopK, &controller.scoreScale);
      for(int i=0;i<N_ASSETS;i++){{
        double s = (double)scores[i] * novelty.riskScale;
        if(s > 1.0) s = 1.0;
        if(s < 0.0) s = 0.0;
        scores[i] = (fvar)s;
      }}
#endif
      printTopK();
    }
  }

  void printTopK() {
    int indices[N_ASSETS];
    for(int i=0;i<N_ASSETS;i++) indices[i] = i;

    int topN = controller.dynamicTopK;
#if USE_COMMUNITY
    if(comm.qSmooth < (fvar)COMM_Q_LOW && topN > 2) topN--;
    if(comm.qSmooth > (fvar)COMM_Q_HIGH && topN < TOP_K) topN++;
#endif
    for(int i=0;i<topN;i++){
      for(int j=i+1;j<N_ASSETS;j++){
        if(scores[indices[j]] > scores[indices[i]]) {
          int tmp = indices[i];
          indices[i] = indices[j];
          indices[j] = tmp;
        }
      }
    }

    if(updateCount % 10 == 0) {
      printf("===CrowdAverse_v14 Top-K(update#%d,OpenCL=%d)===\n",
        updateCount, openCL.ready);
#if USE_COMMUNITY
      printf(" communities=%d Q=%.4f\n", comm.nCommunities, (double)comm.qSmooth);
#endif
#if USE_DENSITY
      printf(" density(label=%d,noise=%d,conf=%.3f,pause=%d)\n", densityLabel, densityNoise, densityConf, densityRegimeCtrl.paused);
#endif

      int selected[N_ASSETS];
      int selCount = 0;
#if USE_COMMUNITY
      int coarseUsed[HCLUST_COARSE_K];
      int fineTake[HCLUST_FINE_K];
      int fineCap = (topN + HCLUST_FINE_K - 1) / HCLUST_FINE_K;
      for(int c=0;c<HCLUST_COARSE_K;c++) coarseUsed[c] = 0;
      for(int c=0;c<HCLUST_FINE_K;c++) fineTake[c] = 0;

      for(int i=0;i<topN;i++){
        int idx = indices[i];
        int cid = comm.clusterCoarse[idx];
        if(cid < 0 || cid >= HCLUST_COARSE_K) cid = 0;
        if(coarseUsed[cid]) continue;
        coarseUsed[cid] = 1;
        selected[selCount++] = idx;
        int fid = comm.clusterFine[idx];
        if(fid < 0 || fid >= HCLUST_FINE_K) fid = 0;
        fineTake[fid]++;
      }

      for(int i=0;i<topN && selCount<topN;i++){
        int idx = indices[i];
        int dup = 0;
        for(int k=0;k<selCount;k++) if(selected[k]==idx){ dup=1; break; }
        if(dup) continue;
        int fid = comm.clusterFine[idx];
        if(fid < 0 || fid >= HCLUST_FINE_K) fid = 0;
        if(fineTake[fid] >= fineCap) continue;
        selected[selCount++] = idx;
        fineTake[fid]++;
      }
#else
      for(int i=0;i<topN;i++) selected[selCount++] = indices[i];
#endif
      for(int i=0;i<selCount;i++){
        int idx = selected[i];
        printf(" %d.%s: score=%.4f, C=%.4f, Ent=%.6f\n", i+1, ASSET_NAMES[idx], (double)scores[idx], (double)compactness[idx], (double)entropy[idx]);
      }
    }
  }
};

// ---------------------------- Zorro DLL entry ----------------------------

static CrowdAverseStrategy* S = NULL;

DLLFUNC void run()
{
  if(is(INITRUN)) {
    BarPeriod = 60;
    LookBack = max(LookBack, FEAT_WINDOW + 50);

    asset((char*)ASSET_NAMES[0]);

    if(!S) {
      S = new CrowdAverseStrategy();
      S->init();
    }
  }

  if(is(EXITRUN)) {
    if(S) {
      S->shutdown();
      delete S;
      S = NULL;
    }
    return;
  }

  if(!S || Bar < LookBack)
    return;

  S->onBar();
}