def prune(self):
"""
Function actually do the pruning process
return a sorted hypothesis list of this fragment
@rtype: list of NovelDepStrHypothesis
"""
hypBest = self.getHypothesisByPosition(self.bestPosition)
if hypBest.failed:
log_error("[AllInOneCubePruner] failed to build 0,0,0 hyp !!!")
stack_output = []
self.lastBestScore = 0
else:
stack_output = [hypBest]
self.lastBestScore = hypBest.getScore()
while len(stack_output) < self.size:
# expand currently best lattice
self.expandEdges()
if self.needStop : break
# pop the best hyp of edges to output
hypBest = self.popBestHypothesis()
self.lastBestScore = hypBest.getScore()
stack_output.append( hypBest )
stack_output.sort( key=lambda x:x.getScore() , reverse=True )
return stack_output
def expandEdges(self):
"""
expand edge lattices of cube
save new hypothesises to self.heapEdges
-------------
Expand could be done by add each dimension by 1 , of course , if it can be
"""
# first get all positions to expand
# [pos,...]
newedges = []
for idx_dimension in range(self.dimensionSize):
cur_index = self.bestPosition[idx_dimension]
if idx_dimension == 0:
# rule dimension
if cur_index+1 < len(self.stackRules):
newedge = self.bestPosition[:]
newedge[0] = cur_index+1
newedges.append( newedge )
else:
# hyp dimensions
if cur_index+1 < len(self.stacksHyps[idx_dimension-1]):
newedge = self.bestPosition[:]
newedge[idx_dimension] = cur_index+1
newedges.append( newedge )
# for each new edge lattice , build hypothesis
for position in newedges:
pastedpos = self.pastePosition(position)
if pastedpos in self.positionExpanded : continue
#print position
hyp = self.getHypothesisByPosition(position)
if hyp.failed:
log_error("[AllInOneCubePruner] failed to build a hyp.")
else:
# !!! to prevent one direction expanding
if hyp.getScore() == self.lastBestScore : continue
self.mapPositionHyp[pastedpos] = hyp
self.heapEdges.append( (0-hyp.getScore(),pastedpos) )
self.positionExpanded.append(pastedpos)
if len(self.heapEdges) == 0:
# no new hyp could be found
self.needStop = True
