/// <summary>
/// This method appends to the debug file a list of predictions results
/// in a compact like table style.
/// </summary>
/// <param name="predictions">the predictions</param>
/// <param name="take">number of predictions to output (null = all)</param>
private void AppendDebugDecisionResults(List <Data.PredictionOfSplits> predictions, int?take)
{
List <Data.PredictionOfSplits> choices = predictions;
if (take != null)
{
choices = choices.Take(take.Value).ToList();
}
List <string> columns = new List <string>();
columns.Add("Prediction");
foreach (var carClass in _classesQueues)
{
columns.Add(ReadClassName(carClass.CarClassId) + " cars");
columns.Add(ReadClassName(carClass.CarClassId) + " SoF");
}
columns.Add("Diff.");
var opt = new ConsoleTableOptions
{
Columns = columns.ToArray(),
EnableCount = false,
NumberAlignment = Alignment.Right
};
var table = new ConsoleTable(opt);
foreach (var c in choices)
{
columns.Clear();
columns.Add(c.Id);
foreach (var carClass in _classesQueues)
{
int classIndex = c.CurrentSplit.GetClassIndexOfId(carClass.CarClassId);
if (classIndex > -1)
{
columns.Add(c.CurrentSplit.CountClassCars(classIndex).ToString());
columns.Add(c.CurrentSplit.GetClassSof(classIndex).ToString());
}
else
{
columns.Add("x");
columns.Add("");
}
}
columns.Add(c.CurrentSplit.ClassesSofDifference);
table.AddRow2(columns.ToArray());
}
sbDecisionsAppends.AppendLine(table.ToString());
}
/// <summary>
/// This method will allow all predictions possible
/// for a split in 'predictlogs\XX.txt'
/// XX is the split number, starting from 01.
/// </summary>
private void WriteSplitPredictionsFile()
{
string splitNumber = _predictions.First().CurrentSplit.Number.ToString();
while (splitNumber.Length < 2)
{
splitNumber = "0" + splitNumber;
}
DirectoryInfo di = new DirectoryInfo("predictlogs");
if (!di.Exists)
{
di.Create();
}
StringBuilder sb = new StringBuilder();
foreach (var item in _predictions)
{
sb.AppendLine(" > PREDICTION " + item.Id);
/*
* OUTPUT SPLITS TABLE
* colums are classes
* rows :
* - car count for current split
* - sofs for current split
* - car count for next split
* - sofs count for next split
*/
List <string> columns = new List <string>();
columns.Add("SPLIT");
foreach (var c in _classesQueues)
{
columns.Add(ReadClassName(c.CarClassId));
}
var opt = new ConsoleTableOptions
{
Columns = columns.ToArray(),
EnableCount = false,
NumberAlignment = Alignment.Right
};
var table = new ConsoleTable(opt);
columns = new List <string>();
columns.Add(item.CurrentSplit.Number.ToString());
foreach (var carClass in _classesQueues)
{
string cell = "x";
int classIndex = item.CurrentSplit.GetClassIndexOfId(carClass.CarClassId);
if (classIndex > -1)
{
string cell2 = item.CurrentSplit.CountClassCars(classIndex).ToString();
if (cell2 != "0")
{
cell = cell2;
}
}
columns.Add(cell);
}
table.AddRow2(columns.ToArray());
columns = new List <string>();
columns.Add("");
foreach (var carClass in _classesQueues)
{
string cell = "x";
int classIndex = item.CurrentSplit.GetClassIndexOfId(carClass.CarClassId);
if (classIndex > -1)
{
string cell2 = item.CurrentSplit.GetClassSof(classIndex).ToString();
if (cell2 != "0")
{
cell = cell2;
}
}
columns.Add(cell);
}
table.AddRow2(columns.ToArray());
columns = new List <string>();
columns.Add(item.NextSplit.Number.ToString());
foreach (var carClass in _classesQueues)
{
string cell = "x";
int classIndex = item.NextSplit.GetClassIndexOfId(carClass.CarClassId);
if (classIndex > -1)
{
string cell2 = item.NextSplit.CountClassCars(classIndex).ToString();
if (cell2 != "0")
{
cell = cell2;
}
}
columns.Add(cell);
}
table.AddRow2(columns.ToArray());
columns = new List <string>();
columns.Add("");
foreach (var carClass in _classesQueues)
{
string cell = "x";
int classIndex = item.NextSplit.GetClassIndexOfId(carClass.CarClassId);
if (classIndex > -1)
{
string cell2 = item.NextSplit.GetClassSof(classIndex).ToString();
if (cell2 != "0")
{
cell = cell2;
}
}
columns.Add(cell);
}
table.AddRow2(columns.ToArray());
sb.AppendLine(table.ToString());
/*
* OUTPUT STATISTICS ABOUT THAT PREDICTION
* 2 columns (name, value)
* rows are any available metrics
*/
columns = new List <string>();
columns.Add("Statistics");
columns.Add("Value");
opt = new ConsoleTableOptions
{
Columns = columns.ToArray(),
EnableCount = false,
NumberAlignment = Alignment.Right
};
table = new ConsoleTable(opt);
table.AddRow("Number of Classes", item.NumberOfClasses);
table.AddRow("No Middle Classes Missing", item.NoMiddleClassesMissing);
table.AddRow("Diff Between Classes (%)", Math.Round(item.DiffBetweenClassesPercent, 2));
table.AddRow("Diff Between Classes (pts)", item.DiffBetweenClassesPoints);
table.AddRow("All SoFs are Lower than Previous split Max", item.AllSofsLowerThanPrevSplitMax);
table.AddRow("All SoFs are Higher than Next split Min", item.AllSofsHigherThanNextSplitMax);
table.AddRow("Most Populated Class has the Max Split SoF", item.MostPopulatedClassIsTheMaxSox);
table.AddRow("Diff between Current split Min Sof and Next split Max Sof (%)", Math.Round(item.DiffBetweenMinCurrentSplitSofAndMaxNextSplitSof, 2));
foreach (var rd in item.RatingDiffPerClassPercent)
{
table.AddRow("iRating diff in class Percent (" + ReadClassName(rd.Key) + ")", Math.Round(rd.Value, 2));
table.AddRow("iRating diff in class Points (" + ReadClassName(rd.Key) + ")", item.RatingDiffPerClassPoints[rd.Key]);
}
foreach (var cut in item.ClassesCuttedAroundRatingThreshold)
{
table.AddRow("Variation with class cutted around rating threshold", "(" + ReadClassName(cut) + ")");
}
sb.AppendLine(table.ToString());
sb.AppendLine("");
sb.AppendLine("");
}
string file = Path.Combine(di.FullName, splitNumber + ".txt");
System.IO.File.WriteAllText(file, sb.ToString());
}