def printClusters(reduced_data, algo="kmean"):
#Dessin des donnes avec matplotlib
clust = Clustering(reduced_data, 5)
if (algo == "ga"):
clust.GA(10)
else:
clust.kMeans()
centroids, clusterAssment = clust.centroids, clust.clusterAssment
cluster1X = []
cluster1Y = []
cluster2X = []
cluster2Y = []
cluster3X = []
cluster3Y = []
cluster4X = []
cluster4Y = []
cluster5X = []
cluster5Y = []
for i in range(len(reduced_data)):
if (clusterAssment[i][0, 0] == 0):
cluster1X.append(reduced_data[i, 0])
cluster1Y.append(reduced_data[i, 1])
if (clusterAssment[i][0, 0] == 1):
cluster2X.append(reduced_data[i, 0])
cluster2Y.append(reduced_data[i, 1])
if (clusterAssment[i][0, 0] == 2):
cluster3X.append(reduced_data[i, 0])
cluster3Y.append(reduced_data[i, 1])
if (clusterAssment[i][0, 0] == 3):
cluster4X.append(reduced_data[i, 0])
cluster4Y.append(reduced_data[i, 1])
if (clusterAssment[i][0, 0] == 4):
cluster5X.append(reduced_data[i, 0])
cluster5Y.append(reduced_data[i, 1])
plot(cluster1X, cluster1Y, 'sg')
plot(cluster2X, cluster2Y, 'ob')
plot(cluster3X, cluster3Y, 'or')
plot(cluster4X, cluster4Y, 'mo')
plot(cluster5X, cluster5Y, 'ys')
show()
