本文整理汇总了Python中cluster.Cluster.add_semantic_for_token方法的典型用法代码示例。如果您正苦于以下问题:Python Cluster.add_semantic_for_token方法的具体用法?Python Cluster.add_semantic_for_token怎么用?Python Cluster.add_semantic_for_token使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类cluster.Cluster
的用法示例。
在下文中一共展示了Cluster.add_semantic_for_token方法的1个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: perform_recursive_clustering
# 需要导入模块: from cluster import Cluster [as 别名]
# 或者: from cluster.Cluster import add_semantic_for_token [as 别名]
def perform_recursive_clustering(cluster_collection, startAt):
"""
Performs a recursive clustering on a list of clusters given via cluster_collection.
The recursion is performed according to the Discoverer paper by Cui et al.
At first new number of distinct values for each token are calculated in each cluster and
if this number is lower than a configurable number, the token is considered a FD.
Then the number of subclusters that would be generated is calculated. If these subclusters
contain at least one cluster containing more than a configurable amount of messages, the clustering
is performed and the token is considered a FD. Then the recursion is performed on each of the new clusters
with the next token.
"""
# Scan for FD token, Phase 1
clusters = cluster_collection.get_all_cluster()[:] # <-- "[:]" Very very important... otherwise our iterated list will change because of deletions...
# Save startAt information over cluster iteration
__startAt = startAt
for cluster in clusters:
if Globals.getConfig().debug:
print "Starting processing for next cluster ({0} messages)".format(len(cluster.get_messages()))
startAt = __startAt
#tokenValue = token.get_token()
# Check distinct number of values of token
foundFD = False
maxTokenIdx = len(cluster.get_messages()[0].get_tokenlist())
while not foundFD and startAt<maxTokenIdx:
l = []
#print "Analyzing token %s" % startAt
# Check whether this might be a length token
if "lengthfield" in set(cluster.get_semantics_for_token(startAt)):
# Current token is a length token. Do not treat as FD
startAt += 1
continue
if not Globals.getConfig().allowAdjacentFDs:
if startAt>0:
if "FD"in set(cluster.get_semantics_for_token(startAt-1)): # We have an adjacent FD
print "Two adjacent FDs forbidden by configuration, skipping to next token"
continue
for message in cluster.get_messages():
l.append(message.get_tokenAt(startAt).get_token())
numOfDistinctValuesForToken = len(set(l))
if Globals.getConfig().minDistinctFDValues < numOfDistinctValuesForToken <= Globals.getConfig().maxDistinctFDValues:
# FD candidate found
# Check number of potential clusters
sumUp = Counter(l)
wouldCluster = False
for key in sumUp.keys():
if sumUp.get(key)>Globals.getConfig().minimumClusterSize: # Minimum cluster size of at least one cluster
wouldCluster = True
break
if wouldCluster:
# Check if adjacent text/text FDs are allowed in text protocols
if Globals.getProtocolClassification()==Globals.protocolText:
if not Globals.getConfig().allowAdjacentTextFDs:
if startAt>0:
# Check whether the previous one is a text FD (type text and no semantic numeric)
if "FD" in set(cluster.get_semantics_for_token(startAt-1)):
if cluster.get_format(startAt-1)==Message.typeText and (
cluster.get_format(startAt)==Message.typeText and ("numeric" not in cluster.get_semantics_for_token(startAt-1))):
print "Two adjacent text FDs forbidden by configuration, skipping to next token"
continue
# Create new cluster
if Globals.getConfig().debug:
print "Subcluster prerequisites fulfilled. Adding FD semantic, splitting cluster and entering recursion"
# Senseless here: message.get_tokenAt(startAt).add_semantic("FD")
cluster.add_semantic_for_token(startAt,"FD")
newCollection = ClusterCollection()
for key in sumUp.keys():
messagesWithValue = cluster.get_messages_with_value_at(startAt,key)
newCluster = Cluster(messagesWithValue[0].get_tokenrepresentation(), "recursion")
newCluster.setSplitpoint("{0}".format(startAt))
newCluster.add_messages(messagesWithValue)
newCluster.add_semantic_for_token(startAt, "FD")
newCollection.add_cluster(newCluster)
if Globals.getConfig().debug:
print "{0} sub clusters generated".format(len(sumUp.keys()))
# Perform format inference on new cluster collection
formatinference.perform_format_inference_for_cluster_collection(newCollection)
semanticinference.perform_semantic_inference(newCollection)
# Merge clusters with same format
while newCollection.mergeClustersWithSameFormat():
pass
# Perform needle wunsch
# Edit 20120120 - not here
#===========================================================
# cluster1 = newCollection.get_random_cluster()
# cluster2 = newCollection.get_random_cluster()
# format1 = cluster1.get_formats()
# format2 = cluster2.get_formats()
# needlewunsch.needlewunsch(format1, format2)
#
#.........这里部分代码省略.........