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