public ActionResult Upload(HttpPostedFileBase upload)
{
string FileFormat = "";
if (upload != null)
{
// получаем имя файла
string fileName = System.IO.Path.GetFileName(upload.FileName);
// сохраняем файл в папку Files в проекте
FuzzyKnowledgeBase FKB = new FuzzyKnowledgeBase();
FKB.ListOfRule.Clear();
FKB.ListVar.Clear();
upload.SaveAs(Server.MapPath("~/Files/" + fileName));
HttpContext.Response.Cookies["FileName"].Value = fileName;
FileFormat = FileHelper.CheckFileFormat(fileName);
if (FileFormat == "txt")
{
return(RedirectToAction("ReadyForms", "Сonclusion", new { FileName = fileName }));
}
else if (FileFormat == "xls")
{
ExelReader.ReadFromXLS(upload.FileName);
K_means k = new K_means(ExelReader.ElementsMulti, null, ExelReader.ClusterCount, ExelReader.ElementsMatrix);
double epsilon = 0.05;
k.Clustering(ExelReader.ClusterCount, epsilon);
k.FindRulesModelTypeMamdani(ExelReader.NameOfLinguisticVariables, ExelReader.ValueIntervalTerm, ExelReader.NameOfTerms, ExelReader.countColumnData, ExelReader.NumbersOfZonesOneLP, ExelReader.counterFoRowDataFromFile, "Трикутна", ExelReader.WeightOfTerms, FKB);
k.GausFunction(ExelReader.countColumnData, FKB);
FKBHelper.WithRullToVar(FKB);
FKBHelper.Save_BNZ(FKB, Server.MapPath("~/Files/BNZauto.txt"));
return(RedirectToAction("ReadyForms", "Сonclusion", new { FileName = "BNZauto.txt" }));
}
}
return(RedirectToAction("Index"));
}
public void ComputeTest()
{
List <Pointer> pointers = new List <Pointer>()
{
new Pointer()
{
X = 1, Y = 21, Z = 0
},
new Pointer()
{
X = 12, Y = 23, Z = 0
},
new Pointer()
{
X = 10, Y = 2, Z = 0
},
new Pointer()
{
X = 3, Y = 10, Z = 0
},
new Pointer()
{
X = 13, Y = 12, Z = 0
},
new Pointer()
{
X = 4, Y = 15, Z = 0
},
new Pointer()
{
X = 9, Y = 6, Z = 0
},
new Pointer()
{
X = 21, Y = 8, Z = 0
},
new Pointer()
{
X = 11, Y = 6, Z = 0
},
new Pointer()
{
X = 21, Y = 9, Z = 0
},
};
K_means kmeans = new K_means(pointers);
kmeans.Compute(3);
}
public static ClusteringResult Kmeans(IMathSet mathSet, ClusteringOptions options)
{
if (mathSet != null)
{
if (options.ClusterCount <= mathSet.RowsCount)
{
switch (options.Mode)
{
case ModeType.SINGLETHREADED:
return(K_means.Singlethreaded(mathSet, options));
case ModeType.MULTITHREADED:
return(K_means.Multithreaded(mathSet, options));
default:
throw new ArgumentException("был выбран неприемлемый параметр из enum AlgoritmType");
}
}
throw new ArgumentException("количество точек с данными в input Set должно быть больше или равно количества кластеров в options");
}
throw new ArgumentNullException("входной набор данных inputSet равен null");
}
