def evalparser(path='./examples', report=False,
bcvocab=None, draw=True,
withdp=False, fdpvocab=None, fprojmat=None):
""" Test the parsing performance
:type path: string
:param path: path to the evaluation data
:type report: boolean
:param report: whether to report (calculate) the f1 score
"""
# ----------------------------------------
# Load the parsing model
print 'Load parsing model ...'
pm = ParsingModel(withdp=withdp,
fdpvocab=fdpvocab, fprojmat=fprojmat)
pm.loadmodel("model/parsing-model.pickle.gz")
# ----------------------------------------
# Evaluation
met = Metrics(levels=['span','nuclearity','relation'])
# ----------------------------------------
# Read all files from the given path
doclist = [joinpath(path, fname) for fname in listdir(path) if fname.endswith('.merge')]
for fmerge in doclist:
# ----------------------------------------
# Read *.merge file
dr = DocReader()
doc = dr.read(fmerge)
# ----------------------------------------
# Parsing
pred_rst = pm.sr_parse(doc, bcvocab)
if draw:
strtree = pred_rst.parse()
drawrst(strtree, fmerge.replace(".merge",".ps"))
# Get brackets from parsing results
pred_brackets = pred_rst.bracketing()
fbrackets = fmerge.replace('.merge', '.brackets')
# Write brackets into file
writebrackets(fbrackets, pred_brackets)
# ----------------------------------------
# Evaluate with gold RST tree
if report:
fdis = fmerge.replace('.merge', '.dis')
gold_rst = RSTTree(fdis, fmerge)
gold_rst.build()
gold_brackets = gold_rst.bracketing()
met.eval(gold_rst, pred_rst)
if report:
met.report()
