using System;
using System.Collections.Generic;
using System.Linq;
using ExcelDna.Integration;
using HeuristicLab.Problems.DataAnalysis;

namespace HeuristicLabExcel {

  public class ExcelFunctions {
    /* Standard example from ExcelDNA */
    [ExcelFunction(Description = "Multiplies two numbers", Category = "Useful functions")]
    public static double MultiplyThem(double x, double y) {
      return x * y;
    }
    [ExcelFunction(Description = "Random forest", Category = "Useful functions")]
    public static double[,] PredictRandomForest(double[,] x, double[] y) {
      int nRows = x.GetLength(0);
      int nCols = x.GetLength(1);
      if (nRows > 5000) throw new ArgumentException("y");
      if (nCols >= nRows) throw new ArgumentException("x");
      var inputs = Enumerable.Range(0, nCols).Select(i => "x" + i);
      var target = "y";
      var variables = inputs.Concat(new string[] { target });
      // copy data
      var xy = new double[nRows, nCols + 1];
      for (int r = 0; r < nRows; r++) {
        for (int c = 0; c < nCols; c++) {
          xy[r, c] = x[r, c];
        }
        if (r < y.Length)
          xy[r, nCols] = y[r];
      }
      var ds = new Dataset(variables, xy);

      var problemData = new RegressionProblemData(ds, inputs, target);
      problemData.TrainingPartition.Start = 0;
      problemData.TrainingPartition.End = y.Length;
      problemData.TestPartition.Start = y.Length;
      problemData.TestPartition.End = nRows;

      double rmsError;
      double oobAvgRelError;
      double oobRmsError;
      double avgRelError;
      var rf = HeuristicLab.Algorithms.DataAnalysis.RandomForestRegression.CreateRandomForestRegressionSolution(problemData, 100, 0.5, 0.5, 31415, out rmsError, out avgRelError, out oobRmsError, out oobAvgRelError);

      // copy for output
      var res = new double[nRows, 1];
      var estValuesEnum = rf.EstimatedValues.GetEnumerator();
      estValuesEnum.MoveNext();
      for (int r = 0; r < nRows; r++) {
        res[r, 0] = estValuesEnum.Current;
        estValuesEnum.MoveNext();
      }
      return res;
    }
  }
}