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from pynlpl.statistics import FrequencyList, Distribution
class WordAlignment(object):
def __init__(self, casesensitive = False):
self.casesensitive = casesensitive
def train(self, sourcefile, targetfile):
sourcefile = open(sourcefile)
targetfile = open(targetfile)
self.sourcefreqlist = FrequencyList(None, self.casesensitive)
self.targetfreqlist = FrequencyList(None, self.casesensitive)
#frequency lists
self.source2target = {}
self.target2source = {}
for sourceline, targetline in zip(sourcefile, targetfile):
sourcetokens = sourceline.split()
targettokens = targetline.split()
self.sourcefreqlist.append(sourcetokens)
self.targetfreqlist.append(targettokens)
for sourcetoken in sourcetokens:
if not sourcetoken in self.source2target:
self.source2target[sourcetoken] = FrequencyList(targettokens,self.casesensitive)
else:
self.source2target[sourcetoken].append(targettokens)
for targettoken in targettokens:
if not targettoken in self.target2source:
self.target2source[targettoken] = FrequencyList(sourcetokens,self.casesensitive)
else:
self.target2source[targettoken].append(sourcetokens)
sourcefile.close()
targetfile.close()
def test(self, sourcefile, targetfile):
sourcefile = open(sourcefile)
targetfile = open(targetfile)
#stage 2
for sourceline, targetline in zip(sourcefile, targetfile):
sourcetokens = sourceline.split()
targettokens = targetline.split()
S2Talignment = []
T2Salignment = []
for sourcetoken in sourcetokens:
#which of the target-tokens is most frequent?
besttoken = None
bestscore = -1
for i, targettoken in enumerate(targettokens):
if targettoken in self.source2target[sourcetoken]:
score = self.source2target[sourcetoken][targettoken] / float(self.targetfreqlist[targettoken])
if score > bestscore:
bestscore = self.source2target[sourcetoken][targettoken]
besttoken = i
S2Talignment.append(besttoken) #TODO: multi-alignment?
for targettoken in targettokens:
besttoken = None
bestscore = -1
for i, sourcetoken in enumerate(sourcetokens):
if sourcetoken in self.target2source[targettoken]:
score = self.target2source[targettoken][sourcetoken] / float(self.sourcefreqlist[sourcetoken])
if score > bestscore:
bestscore = self.target2source[targettoken][sourcetoken]
besttoken = i
T2Salignment.append(besttoken) #TODO: multi-alignment?
yield sourcetokens, targettokens, S2Talignment, T2Salignment
sourcefile.close()
targetfile.close()
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