def mismatches(sentence, mismatches=False):
parsed = sentence.parsed
goldstandard = sentence.goldstandard
leaves = sentence.leaves
for x in parsed:
if x in goldstandard and not parsed[x].hd == goldstandard[x].hd:
ca = commonancestor(x, parsed, goldstandard, leaves)
if ca:
st1 = showDTree(ca[0])
rewrite = showDTree(ca[1])
rule = "%s => %s"%(st1, rewrite)
cb = commonancestorX(x, parsed, goldstandard, leaves)
r1 = parsed[x]
r2 = goldstandard[x]
positions = [r1.hd, r2.hd, x]
rule = leaves[min(positions):max(positions)+1]
for w in rule:
if w.position == x:
w.mark = "/*"
elif w.position == r1.hd:
w.mark = "/1"
elif w.position == r2.hd:
w.mark = "/2"
else:
w.mark = ""
rule = " ".join(["%s%s"%(w.tag, w.mark) for w in rule])
if type(mismatches) == "dict":
incTable(rule, mismatches)
else:
print "************************%s%s"%(st1, rewrite)
def showErrors(sentences):
for sentence in sentences:
if not sentence.goldstandard == sentence.parsed:
print "**************************************"
print "GOLD STANDARD"
print showDTree(buildtree(sentence.goldstandard, sentence.leaves))
print "PARSED"
print showDTree(buildtree(sentence.parsed, sentence.leaves))
print errors(sentence.parsed, sentence.goldstandard, sentence.leaves)
def nfold(trees, n=5, stackwindow=2, qwindow=2, tagsize=2, precision=0.95, threshold=500):
print "nfold, tagsize=%s"%(tagsize)
a = 0
ca = 0
for i in range(0, n):
training, testing = makefold(i, n, trees)
if training == []:
training, testing = testing, training
print "makeclassifier(%s)"%(i)
parser = onefold(i, n, training, testing, stackwindow=stackwindow, qwindow=qwindow, tagsize=tagsize, precision=precision, threshold=threshold)
print "testing[0].dtree before testparser"
testing[0].showDTree()
print "testing[0].parsed"
print tb.showDTree(malt.buildtree(testing[0].parsed, testing[0].leaves))
a += parser.parseraccuracy
c = parser.classifier
ca += c.accuracy
return a/n, ca/n, c, parser, training, testing
def showChanged(sentences):
for sentence in sentences:
if not sentence.tbr == sentence.parsed:
x0 = scoreSentence(sentence, lambda x: x.tbr)
x1 = scoreSentence(sentence, lambda x: x.parsed)
print "**************************************"
print "Change in accuracy %.3f (%s)"%((x0[0]/x0[1])-(x1[0]/x1[1]), x0[0]-x1[0])
print showDTree(buildtree(sentence.goldstandard, sentence.leaves))
print showDTree(buildtree(sentence.tbr, sentence.leaves))
print errors(sentence.tbr, sentence.goldstandard, sentence.leaves)
print showDTree(buildtree(sentence.parsed, sentence.leaves))
print errors(sentence.parsed, sentence.goldstandard, sentence.leaves)