private static void GenerateTestResults()
{
var referencePareto = LoadReferencePareto();
NsgaHelper.AssignCrowdingDistances(referencePareto.ResultPoints);
var filteredIndividuals =
referencePareto.ResultPoints.OrderByDescending(i => i.CrowdingDistance).Take(150).ToList();
var nadir = FindNadir(filteredIndividuals);
var referenceParetoHyperVolume = RInvoker.HyperVolume(filteredIndividuals, nadir);
var results = LoadResults(OutputsDirectory);
var counter = 0;
var counterMax = results.Count;
foreach (var result in results)
{
try
{
result.HyperVolume = referenceParetoHyperVolume - RInvoker.HyperVolume(result.ResultPoints, nadir);
result.EpsilonIndicator = RInvoker.Epsilon(result.ResultPoints, referencePareto.ResultPoints);
}
catch (Exception e)
{
Console.WriteLine("error in caling R script\n " + e.Message);
}
counter++;
Console.WriteLine($"{counter}/{counterMax}");
}
WriteToCsv(OutputsDirectory, results);
SaveAverageValues(results);
Console.WriteLine("done");
}
public List <GroupDietIndividual> TopsisSort(List <GroupDietIndividual> individuals, List <WeightsModel> topisModels)
{
var macroMin = individuals.Select(i => i.Evaluations.Single(e => e.Type == ObjectiveType.Macro).Score).Min();
var prepTimeMin = individuals.Select(i => i.Evaluations.Single(e => e.Type == ObjectiveType.PreparationTime).Score).Min();
var costMin = individuals.Select(i => i.Evaluations.Single(e => e.Type == ObjectiveType.Cost).Score).Min();
var preferencesMin = individuals.Select(i => i.Evaluations.Single(e => e.Type == ObjectiveType.Preferences).Score).Min();
var macroMax = individuals.Select(i => i.Evaluations.Single(e => e.Type == ObjectiveType.Macro).Score).Max();
var prepTimeMax = individuals.Select(i => i.Evaluations.Single(e => e.Type == ObjectiveType.PreparationTime).Score).Max();
var costMax = individuals.Select(i => i.Evaluations.Single(e => e.Type == ObjectiveType.Cost).Score).Max();
var preferencesMax = individuals.Select(i => i.Evaluations.Single(e => e.Type == ObjectiveType.Preferences).Score).Max();
var normalized = individuals.Select(i => new GroupDietIndividual(new GroupDiet())
{
Evaluations = new List <Evaluation>
{
Normalize(i.Evaluations.Single(e => e.Type == ObjectiveType.Macro), macroMin, macroMax),
Normalize(i.Evaluations.Single(e => e.Type == ObjectiveType.PreparationTime), prepTimeMin, prepTimeMax),
Normalize(i.Evaluations.Single(e => e.Type == ObjectiveType.Cost), costMin, costMax),
Normalize(i.Evaluations.Single(e => e.Type == ObjectiveType.Preferences), preferencesMin, preferencesMax)
},
Rank = individuals.IndexOf(i)
});
var averageTopsis = MakeAverage(topisModels);
var result = RInvoker.Topsis(normalized.ToList(), averageTopsis.CostWeight, averageTopsis.PreferncesWeight, averageTopsis.PreparationTimeWeight, averageTopsis.MacroWeight);
return(result.Select(i => individuals[i.Rank]).ToList());
}
private static void SaveAverageValues(List <FrontResult> results)
{
var groupped =
results.GroupBy(
r =>
r.PopulationSize.ToString(CultureInfo.InvariantCulture) + "_" +
r.Iterations.ToString(CultureInfo.InvariantCulture) + "_" +
r.MutationProbability.ToString(CultureInfo.InvariantCulture)).ToList();
var csv = new StringBuilder();
csv.AppendLine("Iterations;MutationProbability;PopulationSize;Time;pvalue;w;HyperVolume;pvalue;w;Epsilon;pvalue;w");
foreach (var group in groupped)
{
var hvs = group.Select(i => i.HyperVolume).ToList();
var times = group.Select(i => i.Time).ToList();
var epsolons = group.Select(i => i.EpsilonIndicator).ToList();
var avg = new AverageResult();
if (hvs.Count > 3 && hvs.Any(value => value > 0))
{
avg.NormalityHv = RInvoker.Shapiro(hvs);
}
if (times.Count > 3 && hvs.Any(value => value > 0))
{
avg.NormalityTime = RInvoker.Shapiro(times);
}
if (epsolons.Count > 3 && epsolons.Any(value => value > 0))
{
avg.NormalityEpsilon = RInvoker.Shapiro(epsolons);
}
avg.Hypervolume = group.Select(i => i.HyperVolume).Average();
avg.Time = group.Select(i => i.Time).Average();
avg.Epsilon = group.Select(i => i.EpsilonIndicator).Average();
csv.AppendLine(
$"{group.First().Iterations};{group.First().MutationProbability};{group.First().PopulationSize};{avg.Time};{avg.NormalityTime.Pvalue};{avg.NormalityTime.Statistic};{avg.Hypervolume};{avg.NormalityHv.Pvalue};{avg.NormalityHv.Statistic};{avg.Epsilon};{avg.NormalityEpsilon.Pvalue};{avg.NormalityEpsilon.Statistic}");
}
var filesInOutputDir = Directory.GetFiles(OutputsDirectory);
var fileIndex = 0;
var fileName = "averageResults.csv";
while (filesInOutputDir.Any(path => path.EndsWith(fileName)))
{
fileIndex++;
fileName = $"averageResults_{fileIndex}.csv";
}
File.WriteAllText($"{OutputsDirectory}\\{fileName}", csv.ToString());
}
private static void TestMethod()
{
var results = LoadResults(OutputsDirectory);
var referencePareto = LoadReferencePareto();
var epsilons = new List <double>();
foreach (var result in results)
{
var eps = RInvoker.Epsilon(result.ResultPoints, referencePareto.ResultPoints);
epsilons.Add(eps);
}
Console.ReadLine();
}
