public Dictionary <CustomSocketDomain.SocketDomain, List <FuzzyFact> > GetFuzzyFacts(List <FuzzyDomain> domains,
List <CustomSocket> sockets)
{
var socketType = typeof(CustomSocket);
var fuzzyFacts = new Dictionary <CustomSocketDomain.SocketDomain, List <FuzzyFact> >();
foreach (var domain in domains)
{
var type = CustomSocketDomain.SocketDomainType[domain.Domain];
var domainValues = sockets
.Select(p => socketType.GetProperty(domain.Domain.ToString()).GetValue(p))
.Where(p => !CustomSocketDomain.SocketDefaultValue[type].Equals(p))
.Distinct()
.Select(p => Convert.ToDouble(p))
.ToList();
var factList = new List <FuzzyFact>();
foreach (var value in ClusteringService.CMeans(domain.Clusters.Count(), domainValues))
{
factList.Add(new FuzzyFact(domain, value.Value, value.ClusterDegree));
}
fuzzyFacts.Add(domain.Domain, SortClusters(factList));
}
return(fuzzyFacts);
}
public IEnumerable <OutputModel> Get()
{
var predictor = ClusteringService.KMeans();
List <OutputModel> output = new List <OutputModel>();
StreamReader file = new StreamReader("./iris.data");
string line;
while ((line = file.ReadLine()) != null)
{
string[] splitLine = line.Split(',');
InputModel irisData = new InputModel
{
SepalLength = float.Parse(splitLine[0]),
SepalWidth = float.Parse(splitLine[1]),
PetalLength = float.Parse(splitLine[2]),
PetalWidth = float.Parse(splitLine[3])
};
var prediction = predictor.Predict(irisData);
output.Add(new OutputModel(irisData, prediction.PredictedClusterId));
}
file.Close();
return(output);
}
public void Clustering_TwoFrames()
{
var clustering = new ClusteringService();
var frame1 = new Order().Random(10);
var frame2 = new Order().Random(11);
var frame3 = new Order().Random(12);
var frame4 = new Order().Random(13);
var frame5 = new Order().Random(18);
var frame6 = new Order().Random(19);
var frame7 = new Order().Random(20);
var frame8 = new Order().Random(21);
var frame9 = new Order().Random(22);
frame1.OrderDirection = OrderDirections.SELL;
frame3.OrderDirection = OrderDirections.SELL;
frame5.OrderDirection = OrderDirections.SELL;
frame7.OrderDirection = OrderDirections.SELL;
frame9.OrderDirection = OrderDirections.SELL;
var frames = new[] { frame1, frame2, frame3, frame4, frame5, frame6, frame7, frame8, frame9 };
var results = clustering.Cluster(frames);
var hm = results;
}
public List <FuzzyFact> GetAmperageCircuitFact(List <FuzzyFuncStatement> statements, CustomSocket socket)
{
var values = new List <double>();
foreach (var statement in statements)
{
values.Add(statement.Result(socket));
}
var domain = new FuzzyDomain(CustomSocketDomain.SocketDomain.AmperageCircuit, new FuzzyDomainOption
{
ClusterCount =
FuzzyCustomSocket.GetFuzzySocketDomains()[CustomSocketDomain.SocketDomain.AmperageCircuit],
Min = values.Min(),
Max = values.Max()
});
var facts = new List <FuzzyFact>();
foreach (var value in ClusteringService.CMeans(domain.Clusters.Count, values))
{
facts.Add(new FuzzyFact(domain, value.Value, value.ClusterDegree));
}
return(facts);
}
public void Clustering_ReturnsEmpty_ForNullArgs()
{
var clustering = new ClusteringService();
var cluster = clustering.Cluster(null);
Assert.IsNotNull(cluster);
Assert.AreEqual(cluster.Count, 0);
}
public PointsGroupService(DatabaseContext context,
ItemService itemService,
ItemFilterer itemFilterer,
FileHandlerService fileHandlerService,
ClusteringService clusteringService)
{
this._context = context;
this._itemService = itemService;
this._itemFilterer = itemFilterer;
this._fileHandlerService = fileHandlerService;
this._clusteringService = clusteringService;
}
public void ClusteringNullObjectsTest()
{
//Arrange
ClusteringService clusteringService = new ClusteringService();
var objRepo = new DetectedObjectRepository(GetContext());
IEnumerable <DataLayer.Models.DetectedObject> objs = new List <DataLayer.Models.DetectedObject>();
float score = 0;
List <PointF> centroids = new List <PointF>();
//Act
var res = clusteringService.GetClusters(4, objs, out score, out centroids);
//Assert
Assert.Null(res);
}
public void ClusteringNullClustersTest()
{
//Arrange
ClusteringService clusteringService = new ClusteringService();
var objRepo = new DetectedObjectRepository(GetContext());
var objs = objRepo.GetVacantObjects(4);
float score = 0;
List <PointF> centroids = new List <PointF>();
//Act
var res = clusteringService.GetClusters(0, objs, out score, out centroids);
//Assert
Assert.Null(res);
}
public void CMeans_isSeedCapable()
{
var values = new List <double>
{
1,
1,
2,
3,
3,
4,
5,
5
};
var fuzzyValues = ClusteringService.CMeans(3, values, randSeed: 0).ToList();
}
public void CMeans_isPlainCorrect()
{
var plainClusters = new List <double> {
1, 1, 1, 5, 5, 5, 9, 9, 9
};
const int plainClustersExpectedCount = 3;
const int elements = 3;
var result = ClusteringService.CMeans(plainClustersExpectedCount, plainClusters).ToList();
for (var k = 0; k < plainClustersExpectedCount; k++)
{
var clusterDegree = result[k * elements].GetMostProbableCluster();
for (var j = k * elements; j < elements; j++)
{
Assert.Equal(clusterDegree.Key, result[j].GetMostProbableCluster().Key);
}
}
}
public void CMeans_isComplexCorrect()
{
var complexClusters = new List <double>
{
2,
2,
3,
3,
3,
3,
3,
3,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
5,
5,
5,
5,
5,
5,
6,
6,
7,
7,
7,
8,
8,
8,
8,
8,
8,
8,
8,
8,
10,
10,
10,
10,
10,
10,
12,
12,
12,
14,
15,
15,
16,
16,
19,
19,
19,
19,
20,
22,
22,
26,
28,
28,
29,
30,
37,
37,
38,
41,
55,
55,
55,
55,
63,
64,
70,
120,
120,
120,
120,
120,
120,
184
};
const int complexClustersExpectedCount = 3;
var result = ClusteringService.CMeans(complexClustersExpectedCount, complexClusters).ToList();
}
