def cluster(self):
# We cluster for each argument independently!
retval = ClusterResult()
curOffset = 0
argNum = 0
for symbolsForArg in self.contentProvider.getSourceAPISymbols():
D = self._calculateDistanceMatrix(symbolsForArg)
curOffset = len(retval.clusterIdToDatapoint.keys())
if len(symbolsForArg) == 0:
argNum += 1
continue
if len(symbolsForArg) == 1:
retval.register(curOffset, symbolsForArg[0], argNum)
argNum += 1
continue
Z = linkage(D, method=self.linkageMethod)
clustering = fcluster(Z,
self.maxDistInCluster,
criterion='distance')
retval.registerSet(symbolsForArg, clustering, curOffset, argNum)
argNum += 1
return retval
def cluster(self):
# We cluster for each argument independently!
retval = ClusterResult()
curOffset = 0
argNum = 0
for symbolsForArg in self.contentProvider.getSourceAPISymbols():
D = self._calculateDistanceMatrix(symbolsForArg)
curOffset = len(retval.clusterIdToDatapoint.keys())
if len(symbolsForArg) == 0:
argNum += 1
continue
if len(symbolsForArg) == 1:
retval.register(curOffset, symbolsForArg[0], argNum)
argNum += 1
continue
Z = linkage(D, method=self.linkageMethod)
clustering = fcluster(Z, self.maxDistInCluster, criterion = 'distance')
retval.registerSet(symbolsForArg, clustering, curOffset, argNum)
argNum += 1
return retval
