source: branches/HeuristicLab.Problems.GrammaticalOptimization/HeuristicLab.Common/Extensions.cs @ 11732

using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;

namespace HeuristicLab.Common {
  public static class Extensions {
    public static bool IsAlmost(this double x, double y) {
      return Math.Abs(x - y) < 1.0e-6;
    }

    public static T SelectRandom<T>(this IEnumerable<T> xs, Random rand) {
      var xsArr = xs.ToArray();
      return xsArr[rand.Next(xsArr.Length)];
    }

    public static IEnumerable<T> SampleProportional<T>(this IEnumerable<T> source, Random random, IEnumerable<double> weights) {
      var sourceArray = source.ToArray();
      var valueArray = weights.ToArray();
      double total = valueArray.Sum();

      while (true) {
        int index = 0;
        double ball = valueArray[index], sum = random.NextDouble() * total;
        while (ball < sum)
          ball += valueArray[++index];
        yield return sourceArray[index];
      }
    }

    public static double RSq(IEnumerable<double> xs, IEnumerable<double> ys) {
      // two pass implementation, but we don't care
      var meanX = xs.Average();
      var meanY = ys.Average();

      var s = 0.0;
      var ssX = 0.0;
      var ssY = 0.0;
      foreach (var p in xs.Zip(ys, (x, y) => new { x, y })) {
        s += (p.x - meanX) * (p.y - meanY);
        ssX += Math.Pow(p.x - meanX, 2);
        ssY += Math.Pow(p.y - meanY, 2);
      }

      if (s.IsAlmost(0)) return 0;
      if (ssX.IsAlmost(0) || ssY.IsAlmost(0)) return 0;
      return s * s / (ssX * ssY);
    }


  }
}