private static int Main(string[] args)
{
var customCulture = (System.Globalization.CultureInfo)Thread.CurrentThread.CurrentCulture.Clone();
customCulture.NumberFormat.NumberDecimalSeparator = ".";
Thread.CurrentThread.CurrentCulture = customCulture;
if (args.Length != 9)
{
DisplayUsage();
Console.ReadKey();
return(-1);
}
try
{
PrepareParameters(args);
PrintParameters(args);
if (DatabaseUtils.CheckIfExists(args))
{
Console.WriteLine("Experiment already exists in database!");
return(0);
}
var sw = new Stopwatch();
sw.Start();
Console.WriteLine("----- Generating data ------");
var dataGenerator = new DataGenerator();
dataGenerator.GenerateTrainingData();
dataGenerator.GenerateTestData();
Console.WriteLine("----- Classification data ------");
var dataClassificator = new C45BinaryClassificator(dataGenerator.TrainingData.ToArray());
dataClassificator.Learn();
Console.WriteLine("----- Creating model ------");
var modelCreator = new ModelCreator(dataClassificator.OutputPath);
modelCreator.Create();
sw.Stop();
Console.WriteLine("----- Calculating statistics ------");
// Calculating jaccard index for training data
var statistics = new StatisticsCalculator();
statistics.CalculateStatistics(dataClassificator.DecisionTree,
modelCreator.UniqueConstraints,
dataGenerator);
// Saving data to database
DatabaseUtils.SaveToDatabase(dataClassificator, modelCreator,
statistics,
dataGenerator,
sw.ElapsedMilliseconds);
}
catch (ArgumentException ex)
{
Console.WriteLine(ex.Message);
DatabaseUtils.SaveErrorToDatabase(ex.Message);
return(-1);
}
catch (FormatException)
{
const string message = "Error parsing input parameters";
DatabaseUtils.SaveErrorToDatabase(message);
Console.WriteLine(message);
return(-1);
}
return(0);
}
/// <summary>
/// Saves experiments data to database. Data is gathered from different program's classes given as parameters
/// </summary>
/// <param name="classificator">Instance of <see cref="C45BinaryClassificator"/>class
/// (Used only for rules saving which is commented)</param>
/// <param name="model"></param>
/// <param name="statistics"></param>
/// <param name="data"></param>
/// <param name="executionTime"></param>
public static void SaveToDatabase(C45BinaryClassificator classificator, ModelCreator model,
StatisticsCalculator statistics, DataGenerator data,
long executionTime)
{
Console.WriteLine(GlobalVariables.Dbpath);
var db = new Database(GlobalVariables.Dbpath);
var experiment = db.NewExperiment();
// Input variables
experiment["Benchmark"] = GlobalVariables.BenchmarkName;
experiment["FeasibleExamples"] = GlobalVariables.FeasibleExamplesCount;
experiment["InfeasibleExamples"] = GlobalVariables.InfeasibleExamplesCount;
experiment["Dimensions"] = GlobalVariables.Dimensions;
experiment["K"] = GlobalVariables.K;
experiment["Join"] = GlobalVariables.Join;
experiment["MaxHeight"] = GlobalVariables.MaxHeight;
experiment["Seed"] = GlobalVariables.Seed;
experiment["Components"] = GlobalVariables.Components;
experiment["ExperimentName"] = GlobalVariables.ExperimentName;
// Sometimes is extending SQlite cell length limits which leads to damaging database
//experiment["Rules"] = classificator.DecisionTree.ToRules().ToString();
// data
experiment["Eps"] = data.BoundryRescaler.Eps;
var sb = new StringBuilder();
for (var i = 0; i < data.NewBoundries.GetLength(0); i++)
{
sb.AppendLine($"{data.NewBoundries[i, 0]},{data.NewBoundries[i, 1]}");
}
experiment["NewBoundries"] = sb.ToString();
// Gurobi model data
experiment["Constraints"] = model.Constraints;
experiment["Terms"] = model.Terms;
// Same situaction as with "Rules" cell above
//using ( var sr = new StreamReader(GlobalVariables.GurobiModelPath) )
//{
// experiment["GurobiModel"] = sr.ReadToEnd();
//}
// Statistics
experiment["FJaccard"] = statistics.FixedJaccardIndex;
experiment["FAccuracy"] = statistics.FixedAccuracy;
experiment["FTP"] = statistics.FixedTruePositive;
experiment["FFP"] = statistics.FixedFalsePositive;
experiment["FTN"] = statistics.FixedTrueNegative;
experiment["FFN"] = statistics.FixedFalseNegative;
experiment["HJaccard"] = statistics.HomogenousJaccardIndex;
experiment["HAccuracy"] = statistics.HomogenousAccuracy;
experiment["HTP"] = statistics.HomogenousTruePositive;
experiment["HFP"] = statistics.HomogenousFalsePositive;
experiment["HTN"] = statistics.HomogenousTrueNegative;
experiment["HFN"] = statistics.HomogenousFalseNegative;
experiment["Total"] = statistics.DataLength;
experiment["MeanAngle"] = statistics.MeanAngle;
experiment["StatisticsCalculationTime"] = statistics.ExecutionTime;
experiment["ProcessingTime"] = executionTime;
// Errors
experiment["Errors"] = GlobalVariables.ErrorLog.ToString();
experiment.Save();
experiment.Dispose();
db.Dispose();
}
