public void ClusterNoDataObjects()
{
var upgma = new UpgmaClusterer <char>((o1, o2) => 0);
IBidirectionalGraph <Cluster <char>, ClusterEdge <char> > tree = upgma.GenerateClusters(Enumerable.Empty <char>());
Assert.That(tree.IsEdgesEmpty);
}
public void ClusterOneDataObject()
{
var upgma = new UpgmaClusterer<char>((o1, o2) => 0);
IBidirectionalGraph<Cluster<char>, ClusterEdge<char>> tree = upgma.GenerateClusters(new[] {'A'});
Assert.That(tree.VertexCount, Is.EqualTo(1));
Assert.That(tree.IsEdgesEmpty);
}
public void ClusterTwoDataObjects()
{
var upgma = new UpgmaClusterer <char>((o1, o2) => 1);
IBidirectionalGraph <Cluster <char>, ClusterEdge <char> > tree = upgma.GenerateClusters(new[] { 'A', 'B' });
var vertices = new Dictionary <string, Cluster <char> >
{
{ "root", new Cluster <char> {
Description = "root"
} },
{ "A", new Cluster <char>('A')
{
Description = "A"
} },
{ "B", new Cluster <char>('B')
{
Description = "B"
} }
};
var edges = new[]
{
new ClusterEdge <char>(vertices["root"], vertices["A"], 0.5),
new ClusterEdge <char>(vertices["root"], vertices["B"], 0.5)
};
AssertTreeEqual(tree, edges.ToBidirectionalGraph <Cluster <char>, ClusterEdge <char> >());
}
public void ClusterOneDataObject()
{
var upgma = new UpgmaClusterer <char>((o1, o2) => 0);
IBidirectionalGraph <Cluster <char>, ClusterEdge <char> > tree = upgma.GenerateClusters(new[] { 'A' });
Assert.That(tree.VertexCount, Is.EqualTo(1));
Assert.That(tree.IsEdgesEmpty);
}
public IBidirectionalGraph <HierarchicalGraphVertex, HierarchicalGraphEdge> GenerateHierarchicalGraph(HierarchicalGraphType graphType,
ClusteringMethod clusteringMethod, SimilarityMetric similarityMetric)
{
switch (clusteringMethod)
{
case ClusteringMethod.Upgma:
Func <Variety, Variety, double> upgmaGetDistance = null;
switch (similarityMetric)
{
case SimilarityMetric.Lexical:
upgmaGetDistance = (v1, v2) => 1.0 - v1.VarietyPairs[v2].LexicalSimilarityScore;
break;
case SimilarityMetric.Phonetic:
upgmaGetDistance = (v1, v2) => 1.0 - v1.VarietyPairs[v2].PhoneticSimilarityScore;
break;
}
var upgma = new UpgmaClusterer <Variety>(upgmaGetDistance);
IBidirectionalGraph <Cluster <Variety>, ClusterEdge <Variety> > upgmaTree = upgma.GenerateClusters(_projectService.Project.Varieties);
return(BuildHierarchicalGraph(upgmaTree));
case ClusteringMethod.NeighborJoining:
Func <Variety, Variety, double> njGetDistance = null;
switch (similarityMetric)
{
case SimilarityMetric.Lexical:
njGetDistance = (v1, v2) => 1.0 - v1.VarietyPairs[v2].LexicalSimilarityScore;
break;
case SimilarityMetric.Phonetic:
njGetDistance = (v1, v2) => 1.0 - v1.VarietyPairs[v2].PhoneticSimilarityScore;
break;
}
var nj = new NeighborJoiningClusterer <Variety>(njGetDistance);
IUndirectedGraph <Cluster <Variety>, ClusterEdge <Variety> > njTree = nj.GenerateClusters(_projectService.Project.Varieties);
switch (graphType)
{
case HierarchicalGraphType.Dendrogram:
IBidirectionalGraph <Cluster <Variety>, ClusterEdge <Variety> > rootedTree = njTree.ToRootedTree();
return(BuildHierarchicalGraph(rootedTree));
case HierarchicalGraphType.Tree:
return(BuildHierarchicalGraph(njTree));
}
break;
}
return(null);
}
public void Cluster()
{
var matrix = new double[,]
{
{0, 2, 4, 6, 6, 8},
{2, 0, 4, 6, 6, 8},
{4, 4, 0, 6, 6, 8},
{6, 6, 6, 0, 4, 8},
{6, 6, 6, 4, 0, 8},
{8, 8, 8, 8, 8, 0}
};
var upgma = new UpgmaClusterer<char>((o1, o2) => matrix[o1 - 'A', o2 - 'A']);
IBidirectionalGraph<Cluster<char>, ClusterEdge<char>> tree = upgma.GenerateClusters(new[] {'A', 'B', 'C', 'D', 'E', 'F'});
var vertices = new Dictionary<string, Cluster<char>>
{
{"root", new Cluster<char> {Description = "root"}},
{"A", new Cluster<char>('A') {Description = "A"}},
{"B", new Cluster<char>('B') {Description = "B"}},
{"C", new Cluster<char>('C') {Description = "C"}},
{"D", new Cluster<char>('D') {Description = "D"}},
{"E", new Cluster<char>('E') {Description = "E"}},
{"F", new Cluster<char>('F') {Description = "F"}},
{"ABCDE", new Cluster<char> {Description = "ABCDE"}},
{"ABC", new Cluster<char> {Description = "ABC"}},
{"AB", new Cluster<char> {Description = "AB"}},
{"DE", new Cluster<char> {Description = "DE"}}
};
var edges = new[]
{
new ClusterEdge<char>(vertices["root"], vertices["ABCDE"], 1),
new ClusterEdge<char>(vertices["root"], vertices["F"], 4),
new ClusterEdge<char>(vertices["ABCDE"], vertices["ABC"], 1),
new ClusterEdge<char>(vertices["ABCDE"], vertices["DE"], 1),
new ClusterEdge<char>(vertices["ABC"], vertices["AB"], 1),
new ClusterEdge<char>(vertices["ABC"], vertices["C"], 2),
new ClusterEdge<char>(vertices["AB"], vertices["A"], 1),
new ClusterEdge<char>(vertices["AB"], vertices["B"], 1),
new ClusterEdge<char>(vertices["DE"], vertices["D"], 2),
new ClusterEdge<char>(vertices["DE"], vertices["E"], 2)
};
AssertTreeEqual(tree, edges.ToBidirectionalGraph<Cluster<char>, ClusterEdge<char>>());
}
public void ClusterTwoDataObjects()
{
var upgma = new UpgmaClusterer<char>((o1, o2) => 1);
IBidirectionalGraph<Cluster<char>, ClusterEdge<char>> tree = upgma.GenerateClusters(new[] {'A', 'B'});
var vertices = new Dictionary<string, Cluster<char>>
{
{"root", new Cluster<char> {Description = "root"}},
{"A", new Cluster<char>('A') {Description = "A"}},
{"B", new Cluster<char>('B') {Description = "B"}}
};
var edges = new[]
{
new ClusterEdge<char>(vertices["root"], vertices["A"], 0.5),
new ClusterEdge<char>(vertices["root"], vertices["B"], 0.5)
};
AssertTreeEqual(tree, edges.ToBidirectionalGraph<Cluster<char>, ClusterEdge<char>>());
}
public void ClusterNoDataObjects()
{
var upgma = new UpgmaClusterer<char>((o1, o2) => 0);
IBidirectionalGraph<Cluster<char>, ClusterEdge<char>> tree = upgma.GenerateClusters(Enumerable.Empty<char>());
Assert.That(tree.IsEdgesEmpty);
}
public IBidirectionalGraph<HierarchicalGraphVertex, HierarchicalGraphEdge> GenerateHierarchicalGraph(HierarchicalGraphType graphType,
ClusteringMethod clusteringMethod, SimilarityMetric similarityMetric)
{
switch (clusteringMethod)
{
case ClusteringMethod.Upgma:
Func<Variety, Variety, double> upgmaGetDistance = null;
switch (similarityMetric)
{
case SimilarityMetric.Lexical:
upgmaGetDistance = (v1, v2) => 1.0 - v1.VarietyPairs[v2].LexicalSimilarityScore;
break;
case SimilarityMetric.Phonetic:
upgmaGetDistance = (v1, v2) => 1.0 - v1.VarietyPairs[v2].PhoneticSimilarityScore;
break;
}
var upgma = new UpgmaClusterer<Variety>(upgmaGetDistance);
IBidirectionalGraph<Cluster<Variety>, ClusterEdge<Variety>> upgmaTree = upgma.GenerateClusters(_projectService.Project.Varieties);
return BuildHierarchicalGraph(upgmaTree);
case ClusteringMethod.NeighborJoining:
Func<Variety, Variety, double> njGetDistance = null;
switch (similarityMetric)
{
case SimilarityMetric.Lexical:
njGetDistance = (v1, v2) => 1.0 - v1.VarietyPairs[v2].LexicalSimilarityScore;
break;
case SimilarityMetric.Phonetic:
njGetDistance = (v1, v2) => 1.0 - v1.VarietyPairs[v2].PhoneticSimilarityScore;
break;
}
var nj = new NeighborJoiningClusterer<Variety>(njGetDistance);
IUndirectedGraph<Cluster<Variety>, ClusterEdge<Variety>> njTree = nj.GenerateClusters(_projectService.Project.Varieties);
switch (graphType)
{
case HierarchicalGraphType.Dendrogram:
IBidirectionalGraph<Cluster<Variety>, ClusterEdge<Variety>> rootedTree = njTree.ToRootedTree();
return BuildHierarchicalGraph(rootedTree);
case HierarchicalGraphType.Tree:
return BuildHierarchicalGraph(njTree);
}
break;
}
return null;
}
public void Cluster()
{
var matrix = new double[, ]
{
{ 0, 2, 4, 6, 6, 8 },
{ 2, 0, 4, 6, 6, 8 },
{ 4, 4, 0, 6, 6, 8 },
{ 6, 6, 6, 0, 4, 8 },
{ 6, 6, 6, 4, 0, 8 },
{ 8, 8, 8, 8, 8, 0 }
};
var upgma = new UpgmaClusterer <char>((o1, o2) => matrix[o1 - 'A', o2 - 'A']);
IBidirectionalGraph <Cluster <char>, ClusterEdge <char> > tree = upgma.GenerateClusters(new[] { 'A', 'B', 'C', 'D', 'E', 'F' });
var vertices = new Dictionary <string, Cluster <char> >
{
{ "root", new Cluster <char> {
Description = "root"
} },
{ "A", new Cluster <char>('A')
{
Description = "A"
} },
{ "B", new Cluster <char>('B')
{
Description = "B"
} },
{ "C", new Cluster <char>('C')
{
Description = "C"
} },
{ "D", new Cluster <char>('D')
{
Description = "D"
} },
{ "E", new Cluster <char>('E')
{
Description = "E"
} },
{ "F", new Cluster <char>('F')
{
Description = "F"
} },
{ "ABCDE", new Cluster <char> {
Description = "ABCDE"
} },
{ "ABC", new Cluster <char> {
Description = "ABC"
} },
{ "AB", new Cluster <char> {
Description = "AB"
} },
{ "DE", new Cluster <char> {
Description = "DE"
} }
};
var edges = new[]
{
new ClusterEdge <char>(vertices["root"], vertices["ABCDE"], 1),
new ClusterEdge <char>(vertices["root"], vertices["F"], 4),
new ClusterEdge <char>(vertices["ABCDE"], vertices["ABC"], 1),
new ClusterEdge <char>(vertices["ABCDE"], vertices["DE"], 1),
new ClusterEdge <char>(vertices["ABC"], vertices["AB"], 1),
new ClusterEdge <char>(vertices["ABC"], vertices["C"], 2),
new ClusterEdge <char>(vertices["AB"], vertices["A"], 1),
new ClusterEdge <char>(vertices["AB"], vertices["B"], 1),
new ClusterEdge <char>(vertices["DE"], vertices["D"], 2),
new ClusterEdge <char>(vertices["DE"], vertices["E"], 2)
};
AssertTreeEqual(tree, edges.ToBidirectionalGraph <Cluster <char>, ClusterEdge <char> >());
}
