/// <summary>
/// 3-d OLAP cube operator; Fills all cells of the given vectors into the given histogram.
/// If you use Hep.Aida.Ref.Converter.ToString(histo) on the result, the OLAP cube of x-"column" vsd y-"column" vsd z-"column", summing the weights "column" will be printed.
/// For example, aggregate sales by product by region by time.
/// <p>
/// Computes the distinct values of x and y and z, yielding histogram axes that capture one distinct value per bin.
/// Then fills the histogram.
/// </summary>
/// <param name="x"></param>
/// <param name="y"></param>
/// <param name="z"></param>
/// <param name="weights"></param>
/// <returns>the histogram containing the cube.</returns>
/// <excption cref="ArgumentException">if <i>x.Count != y.Count || x.Count != z.Count || x.Count != weights.Count</i>.</excption>
public static Hep.Aida.IHistogram3D cube(DoubleMatrix1D x, DoubleMatrix1D y, DoubleMatrix1D z, DoubleMatrix1D weights)
{
if (x.Size != y.Size || x.Size != z.Size || x.Size != weights.Size)
{
throw new ArgumentException("vectors must have same size");
}
var epsilon = 1.0E-9;
var distinct = new DoubleArrayList();
var vals = new double[x.Size];
var sorted = new DoubleArrayList(vals);
// compute distinct values of x
vals = x.ToArray(); // copy x into vals
sorted.Sort();
Cern.Jet.Stat.Descriptive.Frequencies(sorted, distinct, null);
// since bins are right-open [from,to) we need an additional dummy bin so that the last distinct value does not fall into the overflow bin
if (distinct.Count > 0)
{
distinct.Add(distinct[distinct.Count - 1] + epsilon);
}
distinct.TrimToSize();
Hep.Aida.IAxis xaxis = new Hep.Aida.Ref.VariableAxis(distinct.ToArray());
// compute distinct values of y
vals = y.ToArray();
sorted.Sort();
Cern.Jet.Stat.Descriptive.Frequencies(sorted, distinct, null);
// since bins are right-open [from,to) we need an additional dummy bin so that the last distinct value does not fall into the overflow bin
if (distinct.Count > 0)
{
distinct.Add(distinct[distinct.Count - 1] + epsilon);
}
distinct.TrimToSize();
Hep.Aida.IAxis yaxis = new Hep.Aida.Ref.VariableAxis(distinct.ToArray());
// compute distinct values of z
vals = z.ToArray();
sorted.Sort();
Cern.Jet.Stat.Descriptive.Frequencies(sorted, distinct, null);
// since bins are right-open [from,to) we need an additional dummy bin so that the last distinct value does not fall into the overflow bin
if (distinct.Count > 0)
{
distinct.Add(distinct[distinct.Count - 1] + epsilon);
}
distinct.TrimToSize();
Hep.Aida.IAxis zaxis = new Hep.Aida.Ref.VariableAxis(distinct.ToArray());
Hep.Aida.IHistogram3D histo = new Hep.Aida.Ref.Histogram3D("Cube", xaxis, yaxis, zaxis);
return(Histogram(histo, x, y, z, weights));
}
