#region License Information
/* HeuristicLab
* Copyright (C) 2002-2010 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.Diagnostics;
using HeuristicLab.Data;
using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.ArchitectureManipulators;
using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.Creators;
using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.Crossovers;
using HeuristicLab.Random;
using Microsoft.VisualStudio.TestTools.UnitTesting;
namespace HeuristicLab.Encodings.SymbolicExpressionTreeEncoding_3._3.Tests {
[TestClass]
public class AllArchitectureAlteringOperatorsTest {
private const int POPULATION_SIZE = 1000;
private const int N_ITERATIONS = 20;
private const int MAX_TREE_SIZE = 100;
private const int MAX_TREE_HEIGHT = 10;
private TestContext testContextInstance;
///
///Gets or sets the test context which provides
///information about and functionality for the current test run.
///
public TestContext TestContext {
get {
return testContextInstance;
}
set {
testContextInstance = value;
}
}
[TestMethod()]
public void AllArchitectureAlteringOperatorsDistributionTest() {
var trees = new List();
var newTrees = new List();
var grammar = Grammars.CreateArithmeticAndAdfGrammar();
var random = new MersenneTwister(31415);
int failedEvents = 0;
IntValue maxTreeSize = new IntValue(100);
IntValue maxTreeHeigth = new IntValue(10);
IntValue maxDefuns = new IntValue(3);
IntValue maxArgs = new IntValue(3);
for (int i = 0; i < POPULATION_SIZE; i++) {
var tree = ProbabilisticTreeCreator.Create(random, grammar, MAX_TREE_SIZE, MAX_TREE_HEIGHT, 3, 3);
Util.IsValid(tree);
trees.Add(tree);
}
Stopwatch stopwatch = new Stopwatch();
stopwatch.Start();
var combinedAAOperator = new MultiSymbolicExpressionTreeArchitectureManipulator();
for (int g = 0; g < N_ITERATIONS; g++) {
for (int i = 0; i < POPULATION_SIZE; i++) {
if (random.NextDouble() < 0.5) {
// manipulate
var selectedTree = (SymbolicExpressionTree)trees.SelectRandom(random).Clone();
var op = combinedAAOperator.Operators.SelectRandom(random);
bool success = false;
op.ModifyArchitecture(random, selectedTree, grammar, maxTreeSize, maxTreeHeigth, maxDefuns, maxArgs, out success);
if (!success) failedEvents++;
Util.IsValid(selectedTree);
newTrees.Add(selectedTree);
} else {
// crossover
var par0 = (SymbolicExpressionTree)trees.SelectRandom(random).Clone();
var par1 = (SymbolicExpressionTree)trees.SelectRandom(random).Clone();
bool success;
newTrees.Add(SubtreeCrossover.Cross(random, par0, par1, 0.9, 100, 10, out success));
if (!success) failedEvents++;
}
}
trees = newTrees;
}
stopwatch.Stop();
var msPerOperation = stopwatch.ElapsedMilliseconds / (double)POPULATION_SIZE / (double)N_ITERATIONS;
Assert.Inconclusive("AllArchitectureAlteringOperators: " + Environment.NewLine +
"Failed events: " + failedEvents / (double)POPULATION_SIZE / N_ITERATIONS * 100 + " %" + Environment.NewLine +
"Operations / s: ~" + Math.Round(1000.0 / (msPerOperation)) + "operations / s)" + Environment.NewLine +
Util.GetSizeDistributionString(trees, 200, 5) + Environment.NewLine +
Util.GetFunctionDistributionString(trees) + Environment.NewLine +
Util.GetNumberOfSubTreesDistributionString(trees) + Environment.NewLine +
Util.GetTerminalDistributionString(trees) + Environment.NewLine
);
}
}
}