def rankingFromClusters(self, clusters):
ranking = []
for cluster in clusters:
cluster = self.reorderInCluster(cluster)
cluster = normalize(cluster)
print ' ==== Cluster ====='
for member in cluster:
print member
ranking.append(member)
ranking.sort(reverse=True)
return averageRanking(ranking)
def rankingFromClusters(self, clusters):
ranking = []
for cluster in clusters:
cluster = self.reorderInCluster(cluster)
cluster = normalize(cluster)
print ' ==== Cluster ====='
for member in cluster:
print member
ranking.append(member)
ranking.sort(reverse=True)
return averageRanking(ranking)
def rankingFromClustersDrawMethod(self, clusters):
outliers = [c for c in clusters if len(c) <= 0]
clusters = [(len(c), -c[0][0], c) for c in clusters if len(c) > 0]
clusters.sort()
clusters = [c[2] for c in clusters]
globalRanking = []
while len(clusters) != 0:
currentCluster = clusters.pop(0)
if len(currentCluster) == 0:
continue
globalRanking.append(currentCluster.pop(0))
if len(currentCluster) != 0:
clusters.append(currentCluster)
for outlierCluster in outliers:
for member in outlierCluster:
globalRanking.append(member)
ranking = averageRanking(globalRanking)
return ranking
def rankingFromClustersDrawMethod(self, clusters):
outliers = [c for c in clusters if len(c) <= 0]
clusters = [(len(c), -c[0][0], c) for c in clusters if len(c) > 0]
clusters.sort()
clusters = [c[2] for c in clusters]
globalRanking = []
while len(clusters) != 0:
currentCluster = clusters.pop(0)
if len(currentCluster) == 0:
continue
globalRanking.append(currentCluster.pop(0))
if len(currentCluster) != 0:
clusters.append(currentCluster)
for outlierCluster in outliers:
for member in outlierCluster:
globalRanking.append(member)
ranking = averageRanking(globalRanking)
return ranking