#region License Information
/* HeuristicLab
* Copyright (C) 2002-2017 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
*
* This file is part of HeuristicLab.
*
* HeuristicLab is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* HeuristicLab is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with HeuristicLab. If not, see .
*/
#endregion
using System;
using System.Collections.Generic;
using System.Linq;
using System.Threading;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Optimization;
using HeuristicLab.Problems.DataAnalysis;
namespace HeuristicLab.Algorithms.DataAnalysis {
internal static class RegressionTreeUtilities {
public static ResultCollection RunSubAlgorithm(IAlgorithm alg, int random, CancellationToken cancellationToken) {
if (alg.Parameters.ContainsKey("SetSeedRandomly") && alg.Parameters.ContainsKey("Seed")) {
var seed = alg.Parameters["Seed"].ActualValue as IntValue;
var setSeed = alg.Parameters["SetSeedRandomly"].ActualValue as BoolValue;
if (seed == null || setSeed == null)
throw new ArgumentException("The parameters SetSeedRandomly and Seed do not have the expected type");
setSeed.Value = false;
seed.Value = random;
}
if (alg.ExecutionState != ExecutionState.Paused) alg.Prepare();
alg.Start(cancellationToken);
var res = alg.Results;
alg.Runs.Clear();
return res;
}
public static void SplitRows(IReadOnlyList rows, IDataset data, string splitAttr, double splitValue, out IReadOnlyList leftRows, out IReadOnlyList rightRows) {
//TODO check and revert?: points at borders are now used multipe times
var assignment = data.GetDoubleValues(splitAttr, rows).Select(x => x.IsAlmost(splitValue) ? 2 : x < splitValue ? 0 : 1).ToArray();
leftRows = rows.Zip(assignment, (i, b) => new {i, b}).Where(x => x.b == 0 || x.b == 2).Select(x => x.i).ToList();
rightRows = rows.Zip(assignment, (i, b) => new {i, b}).Where(x => x.b > 0).Select(x => x.i).ToList();
}
public static IDataset ReduceDataset(IDataset data, IReadOnlyList rows, IReadOnlyList inputVariables, string target) {
return new Dataset(inputVariables.Concat(new[] {target}), inputVariables.Concat(new[] {target}).Select(x => data.GetDoubleValues(x, rows).ToList()));
}
}
}