def trainClasificator(self):
class0 = readSamples(self.routeClase0, self.dimenssion)
print("clase0: " +str(class0) + "\n")
class1 = readSamples(self.routeClase1, self.dimenssion)
print("clase1: " +str(class1)+ "\n")
print("\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n clusterinr \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n")
clusterContainer0 = ClusterContainer(class0,class1)
clusterContainer1 = ClusterContainer(class1,class0)
writeClusters(clusterContainer0, class0,routeCluster0)
writeClusters(clusterContainer1, class1, routeCluster1)
parameters = [(len(class0 + class1)), self.dimenssion, len(class0), len(class1), self.numGroups, clusterContainer0.getCantClusters(), clusterContainer1.getCantClusters(),M]
writeParameters(parameters, routeParameters)
print("\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n grupeo \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n")
groupContainer = Grouper.GroupContainer(class0,class1, clusterContainer1, self.numGroups)
Grouper.deleteOutliers(class0, clusterContainer0, groupContainer.model.e0Vals)
print("\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n definiendo hiperplanos \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n")
regions = Hiperplane.defineHiperplanes(groupContainer, clusterContainer0)
return regions
def testDefineGroupsOnlyOneSampleK3(self):
claseA = [(1.0, 1.0)]
claseB = [(0.0, 0.0), (2.0, 2.0)]
k = 3
d = 2
clusterContainerA, model = prepare(claseA, claseB, k, d)
self.assertEquals([((1.0, 1.0),)], Grouper.defineGroups(clusterContainerA, model, k))
def testDefineGroupsOnlyOneGroupK33D(self):
claseA = [(1.0, 1.0, 0.0), (2.0, 1.0, 0.0), (3.0, 1.0, 0.0)]
claseB = [(0.0, 1.0, 0.0), (4.0, 1.0, 0.0)]
k = 3
d = 3
clusterContainerA, model = prepare(claseA, claseB, k, d)
self.assertEquals([((3.0, 1.0, 0.0), (1.0, 1.0, 0.0), (2.0, 1.0, 0.0))], Grouper.defineGroups(clusterContainerA, model, k))
pass
def testdefineGroups4D(self):
claseA = [(0.0, 0.0, 1.0, 0.0), (0.0, 0.0, 2.0, 0.0), (0.0, 0.0, 3.0, 0.0), (0.0, 0.0, 4.0, 0.0), (0.0, 0.0, 5.0, 0.0), (0.0, 0.0, 6.0, 0.0), (0.0, 0.0, 7.0, 0.0), (0.0, 0.0, 8.0, 0.0), (0.0, 0.0, 9.0, 0.0), (0.0, 0.0, 10.0, 0.0), (0.0, 0.0, 11.0, 0.0)]
claseB = [(0.0, 0.0, 2.5, 0.0), (0.0, 0.0, 5.5, 0.0), (0.0, 0.0, 9.5, 0.0)]
k = 4
d = 4
writeSample(claseA, "model/class1.dat")
writeSample(claseB, "model/class0.dat")
clusterContainerA, model = prepare(claseA, claseB, k, d)
self.assertEquals(set([((0.0, 0.0, 1.0, 0.0), (0.0, 0.0, 2.0, 0.0)), ((0.0, 0.0, 5.0, 0.0), (0.0, 0.0, 3.0, 0.0), (0.0, 0.0, 4.0, 0.0)), ((0.0, 0.0, 10.0, 0.0), (0.0, 0.0, 11.0, 0.0)), ((0.0, 0.0, 6.0, 0.0), (0.0, 0.0, 7.0, 0.0), (0.0, 0.0, 8.0, 0.0), (0.0, 0.0, 9.0, 0.0))]), set(Grouper.defineGroups(clusterContainerA, model, k)))
pass
def testdefineGroups3D(self):
claseA = [(0.0, 0.0, 1.0), (0.0, 0.0, 2.0), (0.0, 0.0, 3.0), (0.0, 0.0, 4.0), (0.0, 0.0, 5.0), (0.0, 0.0, 6.0), (0.0, 0.0, 7.0), (0.0, 0.0, 8.0), (0.0, 0.0, 9.0), (0.0, 0.0, 10.0)]
claseB = [(0.0, 0.0, 2.5), (0.0, 0.0, 5.5), (0.0, 0.0, 9.5)]
k = 4
d = 3
clusterContainerA, model = prepare(claseA, claseB, k, d)
self.assertEquals(set([((0.0, 0.0, 1.0), (0.0, 0.0, 2.0)), ((0.0, 0.0, 5.0), (0.0, 0.0, 3.0), (0.0, 0.0, 4.0)), ((0.0, 0.0, 10.0),), ((0.0, 0.0, 6.0), (0.0, 0.0, 7.0), (0.0, 0.0, 8.0), (0.0, 0.0, 9.0))]), set(Grouper.defineGroups(clusterContainerA, model, k)))
pass
def testDefineGroupsOneGroupForeachSample4D(self):
claseA = [(0.0, 0.0, 0.0, 0.0), (0.0, 0.0, 2.0, 0.0), (0.0, 2.0, 0.0, 0.0), (0.0, 2.0, 2.0, 0.0)]
claseB = [(0.0, 0.0, 0.1, 0.0), (0.0, 1.0, 2.0, 0.0), (0.0, 2.0, 1.0, 0.0), (0.0, 0.0, 1.0, 0.0), (0.0, 1.0, 1.0, 0.0)]
k = 4
d = 4
clusterContainerA, model = prepare(claseA, claseB, k, d)
self.assertEquals([((0.0, 0.0, 0.0, 0.0),), ((0.0, 2.0, 0.0, 0.0),), ((0.0, 2.0, 2.0, 0.0),), ((0.0, 0.0, 2.0, 0.0),)], Grouper.defineGroups(clusterContainerA, model, k))
def testDefineGroupsOnlyOneGroupK24D(self):
claseA = [(0.0, 1.0, 1.0, 0.0), (0.0, 2.0, 1.0, 0.0), (0.0, 3.0, 1.0, 0.0)]
claseB = [(0.0, 0.0, 1.0, 0.0), (0.0, 4.0, 1.0, 0.0)]
k = 2
d = 4
clusterContainerA, model = prepare(claseA, claseB, k, d)
self.assertEquals([((0.0, 3.0, 1.0, 0.0), (0.0, 1.0, 1.0, 0.0), (0.0, 2.0, 1.0, 0.0))], Grouper.defineGroups(clusterContainerA, model, k))
pass