public CoverageResult(IEnumerable <Batch> batches, List <string> xml, string database)
{
_batches = batches;
_database = database;
var parser = new EventsParser(xml);
var statement = parser.GetNextStatement();
while (statement != null)
{
var batch = _batches.FirstOrDefault(p => p.ObjectId == statement.ObjectId);
if (batch != null)
{
var item = batch.Statements.FirstOrDefault(p => _statementChecker.Overlaps(p, statement));
if (item != null)
{
item.HitCount++;
}
}
statement = parser.GetNextStatement();
}
foreach (var batch in _batches)
{
batch.CoveredStatementCount = batch.Statements.Count(p => p.HitCount > 0);
batch.HitCount = batch.Statements.Sum(p => p.HitCount);
}
CoveredStatementCount = _batches.Sum(p => p.CoveredStatementCount);
StatementCount = _batches.Sum(p => p.StatementCount);
HitCount = _batches.Sum(p => p.HitCount);
}
public IEnumerable <LogEvent> Read(TextReader reader)
{
var itemParser = new EventsParser();
var fieldMap = (FieldMapping)null;
string line;
while ((line = reader.ReadLine()) != null)
{
if (line.StartsWith("#", StringComparison.OrdinalIgnoreCase))
{
ParseHeader(line, fieldsLine => { fieldMap = new FieldsParser().Parse(fieldsLine); });
continue;
}
if (fieldMap == null)
{
continue;
}
yield return(itemParser.Parse(line, fieldMap));
}
}
static void Main(string[] args)
{
EmailService emailService = new EmailService();
EventsParser eventsParser = new EventsParser();
DataBaseOperations dbOperations = new DataBaseOperations();
var eventList = eventsParser.Parse(new ParseConfiguration()
{
City = ParseCity(ConfigurationManager.AppSettings["city"]),
Type = ConfigurationManager.AppSettings["type"],
Cost = ParseCost(ConfigurationManager.AppSettings["cost"])
});
var events = eventList as IList <Event> ?? eventList.ToList();
ShowParsedList(events);
Console.WriteLine();
while (true)
{
Console.WriteLine("*** calling MyMethod *** ");
dbOperations.Insert(events);
try
{
var eventsListFromDb = dbOperations.ReadAllToList();
emailService.Send(eventsListFromDb);
}
catch (Exception ex)
{
Console.WriteLine(ex.Message);
}
Console.WriteLine("\n All done");
Thread.Sleep(60 * 1000 * int.Parse(ConfigurationManager.AppSettings["time"]));
}
}
public CoverageResult(IEnumerable <Batch> batches, List <string> xml, string database, string dataSource, List <string> sqlExceptions, string commandDetail)
{
_batches = batches;
_sqlExceptions = sqlExceptions;
_commandDetail = $"{commandDetail} at {DateTime.Now}";
DatabaseName = database;
DataSource = dataSource;
var parser = new EventsParser(xml);
var statement = parser.GetNextStatement();
while (statement != null)
{
var batch = _batches.FirstOrDefault(p => p.ObjectId == statement.ObjectId);
if (batch != null)
{
var item = batch.Statements.FirstOrDefault(p => _statementChecker.Overlaps(p, statement));
if (item != null)
{
item.HitCount++;
}
}
statement = parser.GetNextStatement();
}
foreach (var batch in _batches)
{
batch.CoveredStatementCount = batch.Statements.Count(p => p.HitCount > 0);
batch.HitCount = batch.Statements.Sum(p => p.HitCount);
}
CoveredStatementCount = _batches.Sum(p => p.CoveredStatementCount);
StatementCount = _batches.Sum(p => p.StatementCount);
HitCount = _batches.Sum(p => p.HitCount);
}
private static void Main(string[] args)
{
if (args.Length < 3 || args.Length > 6)
{
Console.WriteLine(Help);
return;
}
var parser = new EventsParser();
IList <EventModel> events = null;
try
{
events = parser.ParseFromCSV(args[0]);
}
catch (FormatException e)
{
Console.WriteLine(e.Message);
Console.WriteLine(Strings.WrongFileFormat);
Console.WriteLine(Strings.Tweets);
return;
}
if (events == null)
{
Console.WriteLine(Strings.FileNotFound);
return;
}
ISymptomAlgorithm symtopmAlgorithm;
IDetectionMethod method;
var isFastTest = false;
switch (args[1].ToLower())
{
case "bow":
symtopmAlgorithm = new BagOfWords();
break;
case "tf-idf":
symtopmAlgorithm = new TermFrequencyInverseDocumentFrequency();
break;
case "ft":
isFastTest = true;
symtopmAlgorithm = new FastTest(args[2]);
break;
default:
Console.WriteLine(Strings.SymptomAlgorithmError);
Console.WriteLine(Strings.Bow);
return;
}
switch (args[isFastTest ? 3 : 2].ToLower())
{
case "mdm":
method = new MinimalDistanceMethod();
break;
case "knn":
if (args.Length < 4 || !int.TryParse(args[isFastTest ? 4 : 3], out var k) || k <= 0)
{
Console.WriteLine(Strings.PositiveIntegerError);
Console.WriteLine(Strings.KNN);
return;
}
method = new KNearestNeighbors(k);
break;
default:
Console.WriteLine(Strings.DetectionMethodError);
Console.WriteLine(Strings.MDM);
return;
}
Console.WriteLine("Generating symtoms...");
symtopmAlgorithm.GenerateSymptoms(events);
Console.WriteLine("Symptoms generated successfully.");
Console.WriteLine($"There are { events.Count(s => s.SymptomModel != null) } symptoms.");
Console.WriteLine("\nMaking etalons...");
var symptomLength = events[0].SymptomModel.Length;
var etalons = new List <ClusterModel>();
foreach (var e in events)
{
var exist = etalons.Where(etalon => e.EventType == etalon.Type).FirstOrDefault();
if (exist != null)
{
exist.Events.Add(e);
continue;
}
etalons.Add(new ClusterModel
{
Type = e.EventType,
Events = new List <EventModel> {
e
}
});
}
etalons.ForEach(e => Console.WriteLine($"Created etalon { e.Type }"));
Console.WriteLine("\nDetection...");
var clusters = method.Detect(events, etalons);
Console.WriteLine("Detecting done.");
var output = args.Last();
if (output.LastIndexOf('.') > 0 && output.Substring(output.LastIndexOf('.')).ToLower().CompareTo(".csv") == 0)
{
Console.WriteLine("\nWriting result into csv file...\n");
var classifiedEvents = clusters.Select(c => c.Clone() as ClusterModel).ToList();
classifiedEvents.ForEach(c => c.Events.ForEach(e => e.EventType = c.Type));
try
{
parser.ParseIntoCSV(output, classifiedEvents.SelectMany(c => c.Events.Select(e => e)).ToList());
}
catch (Exception e)
{
Console.WriteLine(e.Message);
return;
}
}
else
{
Console.WriteLine(Environment.NewLine + Strings.OutputError + Environment.NewLine);
}
Console.WriteLine("Results:");
double correctResults = clusters.Sum(c => c.Events.Count(e => e.EventType == c.Type));
double all = clusters.Sum(c => c.Events.Count);
var precision = correctResults / all;
var recall = (correctResults / Math.Abs((all - correctResults))) / 100;
var fMeasure = (2 * (precision * recall)) / (precision + recall);
Console.WriteLine($"Precision: { precision }\nRecall: { recall }\nF-measure: { fMeasure }\n");
foreach (var c in clusters)
{
foreach (var e in c.Events)
{
if (e.EventType != c.Type)
{
Console.WriteLine($"Cluster { c.Type } contain wrong classified { e.EventType }");
}
}
}
}
