//+------------------------------------------------------------------+
//|                                            KronosEvalQuality.mq5 |
//|                                      MMQ — Muhammad Minhas Qamar |
//|                                                     www.mql5.com |
//+------------------------------------------------------------------+
#property copyright "MMQ — Muhammad Minhas Qamar"
#property link      "https://www.mql5.com"
#property version   "1.00"
#property strict
#property script_show_inputs

input string InpInFile  = "kronos_eval\\eurusd_h1_forecasts.csv"; // dump file (MQL5/Files)
input int    InpPredLen = 16;                                     // horizon count P in the dump

//+------------------------------------------------------------------+
//| Per-horizon running accumulators.                                |
//+------------------------------------------------------------------+
struct HorizonStat
  {
   int    n;            // samples
   int    dir_hit;      // Kronos directional hits
   int    rw_hit;       // random-walk directional hits (baseline: always "flat")
   double k_abs;        // sum |kronos_ret - actual_ret|
   double k_sq;         // sum (kronos_ret - actual_ret)^2
   double rw_abs;       // sum |0 - actual_ret| == sum |actual_ret|
   double rw_sq;        // sum actual_ret^2
  };

//+------------------------------------------------------------------+
//| Script entry: load dump, score, print table.                     |
//+------------------------------------------------------------------+
void OnStart()
  {
   const int P = InpPredLen;
   if(P < 1) { Print("PredLen must be >= 1"); return; }

   int fh = FileOpen(InpInFile, FILE_READ | FILE_CSV | FILE_ANSI, ',');
   if(fh == INVALID_HANDLE)
     { PrintFormat("Cannot open %s (err %d). Run KronosForecastDump first.", InpInFile, GetLastError()); return; }

   HorizonStat st[];
   ArrayResize(st, P);
   for(int h = 0; h < P; h++)
     { st[h].n = 0; st[h].dir_hit = 0; st[h].rw_hit = 0;
       st[h].k_abs = 0; st[h].k_sq = 0; st[h].rw_abs = 0; st[h].rw_sq = 0; }

   //--- expected columns: time, last_close, fc_c1..cP, ac_c1..cP  => 2 + 2P
   int expected = 2 + 2 * P;
   int rows = 0, skipped_header = 0;

   while(!FileIsEnding(fh))
     {
      string time_s = FileReadString(fh);
      if(time_s == "")          // trailing blank
         break;
      if(time_s == "time")      // header line
        { // consume the rest of the header row
         for(int k = 1; k < expected && !FileIsLineEnding(fh); k++)
            FileReadString(fh);
         skipped_header++;
         continue;
        }

      double last_close = (double)FileReadString(fh);
      double fc[]; ArrayResize(fc, P);
      double ac[]; ArrayResize(ac, P);
      for(int h = 0; h < P; h++) fc[h] = (double)FileReadString(fh);
      for(int h = 0; h < P; h++) ac[h] = (double)FileReadString(fh);

      if(last_close <= 0.0)
         continue;

      for(int h = 0; h < P; h++)
        {
         double k_ret = (fc[h] - last_close) / last_close;   // predicted cumulative return to h
         double a_ret = (ac[h] - last_close) / last_close;   // realized   cumulative return to h

         //--- directional accuracy (skip exact-flat actuals: no direction to call)
         if(a_ret != 0.0)
           {
            if((k_ret > 0.0) == (a_ret > 0.0)) st[h].dir_hit++;
            //--- random-walk predicts no change => never calls a direction; counts as
            //--- a coin-flip baseline of 0 hits here (reported separately below)
            st[h].n++;
           }

         double k_err = k_ret - a_ret;
         st[h].k_abs += MathAbs(k_err);
         st[h].k_sq  += k_err * k_err;
         st[h].rw_abs += MathAbs(a_ret);    // baseline error == |actual return|
         st[h].rw_sq  += a_ret * a_ret;
        }
      rows++;
     }
   FileClose(fh);

   if(rows == 0)
     { Print("No data rows parsed. Check the dump file/PredLen."); return; }

   PrintFormat("=== Kronos forecast-skill report ===  (%d forecasts, P=%d)", rows, P);
   Print("h |  DirAcc  | RMSE_ret  RW_RMSE   skill | MAE_ret   RW_MAE    skill");
   Print("--+----------+----------------------------+---------------------------");

   double agg_dir = 0; int agg_n = 0;
   for(int h = 0; h < P; h++)
     {
      int    n      = st[h].n;
      double diracc = (n > 0) ? (double)st[h].dir_hit / n : 0.0;
      double k_rmse = MathSqrt(st[h].k_sq / rows);
      double rw_rmse= MathSqrt(st[h].rw_sq / rows);
      double k_mae  = st[h].k_abs / rows;
      double rw_mae = st[h].rw_abs / rows;
      //--- skill ratio < 1 means Kronos beats random-walk on that error metric
      double rmse_skill = (rw_rmse > 0) ? k_rmse / rw_rmse : 0.0;
      double mae_skill  = (rw_mae  > 0) ? k_mae  / rw_mae  : 0.0;

      PrintFormat("%2d| %6.2f%%  | %.6f %.6f %5.3f | %.6f %.6f %5.3f",
                  h + 1, diracc * 100.0, k_rmse, rw_rmse, rmse_skill,
                  k_mae, rw_mae, mae_skill);
      agg_dir += st[h].dir_hit; agg_n += n;
     }
   Print("--+----------+----------------------------+---------------------------");
   PrintFormat("Overall directional accuracy across all horizons: %.2f%% (n=%d)",
               (agg_n > 0 ? 100.0 * agg_dir / agg_n : 0.0), agg_n);
   Print("Reading: DirAcc > 50%% = some directional skill; error skill < 1.000 =");
   Print("Kronos beats the random-walk (no-change) baseline on that horizon.");
  }
//+------------------------------------------------------------------+