def fetch_alignment(basename, langs, backend='hunalign'):
assert langs
real_langs = list(set(lang[:2]
for lang in langs))
if len(real_langs) == 1:
text_len = len(fetch_sentences(basename, real_langs[0]))
return Alignment.create_straight(text_len, len(langs))
elif len(real_langs) == 2:
try:
a = Alignment.from_file("%s/%s-%s.%s" %
(basename, real_langs[0], real_langs[1], backend))
except IOError:
real_langs.reverse()
a = Alignment.from_file("%s/%s-%s.%s" %
(basename, real_langs[0], real_langs[1], backend))
else: # len(real_langs) == 3 :(
a1 = Alignment.from_file('%s/pl-cu.%s' % (basename, backend)).as_ladder()
a2 = Alignment.from_file('%s/cu-el.%s' % (basename, backend)).as_ladder()
a3 = Alignment.from_file('%s/pl-el.%s' % (basename, backend)).as_ladder()
a3 = [(b, a) for (a, b) in a3] # reversed
a = merge_3_alignments(a1, a2, a3)
real_langs = ['pl', 'cu', 'el'] # needed later
columns = _transpose(a.data)
columns_map = { real_langs[i] : columns[i]
for i in range(len(real_langs)) }
# common part for 2 and 3
chosen_columns = [columns_map[lang[:2]] for lang in langs]
chosen_columns.append(columns[2])
return Alignment(_transpose(chosen_columns))
def get_alignment(self, langs, backend=None):
"""like fetcher"""
assert len(langs) >= 2
assert not backend or backend in possible_backends
real_langs = list(set(lang[:2]
for lang in langs))
if len(real_langs) == 1:
text_len = len(fetch_sentences(basename, real_langs[0]))
return Alignment.create_straight(text_len, len(langs))
elif len(real_langs) == 2:
a = None
for i in range(2):
for b in ([backend] if backend else possible_backends):
try:
langs_string = '-'.join(str(l) for l in real_langs)
a = Alignment.from_file(self._p(langs_string + '.' + b))
break
except IOError:
continue
if a:
break
real_langs.reverse()
if not a:
raise IOError
else: # len(real_langs) == 3 :(
a1 = self.get_alignment(['pl', 'cu'], backend).as_ladder()
a2 = self.get_alignment(['cu', 'el'], backend).as_ladder()
a3 = self.get_alignment(['pl', 'el'], backend).as_ladder()
# a3 = [(b, a) for (a, b) in a3] # reversed
a = merge_3_alignments(a1, a2, a3)
real_langs = ['pl', 'cu', 'el'] # needed later
columns = _transpose(a.data)
columns_map = { real_langs[i] : columns[i]
for i in range(len(real_langs)) }
# common part for 2 and 3
chosen_columns = [columns_map[lang[:2]] for lang in langs]
chosen_columns.append(columns[2])
return Alignment(_transpose(chosen_columns))
