public List <BetterMatchMaking.Library.Data.Line> LoadCsv(string csvFile)
{
var parser = new BetterMatchMaking.Library.Data.CsvParser();
parser.Read(csvFile);
return(parser.DistinctCars);
}
public void Test(string csv)
{
// get fieldsize from file name
int fieldSize = 0;
string cst_fieldsize = "-fieldsize";
if (csv.Contains(cst_fieldsize))
{
string strfieldsize = csv.Substring(
csv.IndexOf(cst_fieldsize) + cst_fieldsize.Length,
2
);
Int32.TryParse(strfieldsize, out fieldSize);
}
// -->
// read csv
var parser = new BetterMatchMaking.Library.Data.CsvParser();
parser.Read(csv);
var entrylist = parser.DistinctCars;
// -->
// run algorithm
BetterMatchMaking.Library.BetterMatchMakingCalculator calculator = new Library.BetterMatchMakingCalculator("SmartPredictedMoveDownAffineDistribution");
for (int p = 5; p < 50; p++)
{
Console.WriteLine("");
Console.WriteLine("------------------------------------");
Console.WriteLine(new FileInfo(csv).Name);
Console.WriteLine("Max Soff Diff = " + p);
calculator.ParameterMinCarsValue = p;
calculator.ParameterMaxSofDiffValue = 17;
calculator.ParameterMaxSofFunctStartingIRValue = 2800;
calculator.ParameterMaxSofFunctStartingThreshold = 18;
calculator.ParameterMaxSofFunctExtraThresoldPerK = 11;
calculator.ParameterTopSplitExceptionValue = 0;
calculator.ParameterNoMiddleClassesEmptyValue = 0;
calculator.ParameterRatingThresholdValue = 1700;
calculator.Compute(entrylist, fieldSize);
var audit = calculator.GetAudit();
Console.WriteLine(audit.ToString());
Console.WriteLine("AverageSplitClassesSofDifference = " + audit.AverageSplitClassesSofDifference);
Console.WriteLine("MinSplitSizePercent = " + audit.MinSplitSizePercent);
if (!audit.Success)
{
testsFailed++;
}
if (audit.MinSplitSizePercent < 0.5)
{
testsSplitsDiff++;
}
if (audit.IROrderInconsistencySplits.Count > 0)
{
}
diff.Add(audit.AverageSplitClassesSofDifference);
tests++;
}
// -->
}