def _process(t):
"""Encode tree *t* and return the string."""
# tree transformations
if normalize_options['make_variables']:
t.reset_variables(normalize_options['make_variables'])
if normalize_options['canonicalize_roles']:
t = transform.canonicalize_roles(t, model)
if normalize_options['rearrange'] == 'canonical':
layout.rearrange(t, key=model.canonical_order)
elif normalize_options['rearrange'] == 'random':
layout.rearrange(t, key=model.random_order)
g = layout.interpret(t, model)
# graph transformations
if normalize_options['reify_edges']:
g = transform.reify_edges(g, model)
if normalize_options['dereify_edges']:
g = transform.dereify_edges(g, model)
if normalize_options['reify_attributes']:
g = transform.reify_attributes(g)
if normalize_options['indicate_branches']:
g = transform.indicate_branches(g, model)
if triples:
return codec.format_triples(g.triples,
indent=bool(
format_options.get('indent',
True)))
else:
return codec.encode(g, **format_options)
def test_dereify_edges_default_codec():
decode = def_codec.decode
norm = lambda g: dereify_edges(g, def_model)
encode = lambda g: def_codec.encode(g, indent=None)
g = norm(
decode('(a / alpha :ARG1-of (_ / have-mod-91'
' :ARG2 (b / beta)))'))
assert encode(g) == (
'(a / alpha :ARG1-of (_ / have-mod-91 :ARG2 (b / beta)))')
g = norm(
decode('(a / alpha :ARG2-of (_ / have-mod-91'
' :ARG1 (b / beta)))'))
assert encode(g) == (
'(a / alpha :ARG2-of (_ / have-mod-91 :ARG1 (b / beta)))')
def _process_in(t, model, normalize_options):
"""Encode tree *t* and return the string."""
# tree transformations
if normalize_options['canonicalize_roles']:
t = transform.canonicalize_roles(t, model)
g = layout.interpret(t, model)
# graph transformations
if normalize_options['reify_edges']:
g = transform.reify_edges(g, model)
if normalize_options['dereify_edges']:
g = transform.dereify_edges(g, model)
if normalize_options['reify_attributes']:
g = transform.reify_attributes(g)
if normalize_options['indicate_branches']:
g = transform.indicate_branches(g, model)
return g
def test_dereify_edges_amr_codec():
decode = amr_codec.decode
norm = lambda g: dereify_edges(g, amr_model)
encode = lambda g: amr_codec.encode(g, indent=None)
g = norm(
decode('(a / alpha :ARG1-of~1 (_ / have-mod-91~2'
' :ARG2~3 7~4))'))
assert encode(g) == '(a / alpha :mod~2 7~4)'
g = norm(
decode('(a / alpha :ARG1-of~1 (_ / have-mod-91~2'
' :ARG2~3 (b / beta~4)))'))
assert encode(g) == '(a / alpha :mod~2 (b / beta~4))'
g = norm(
decode('(a / alpha :ARG2-of (_ / have-mod-91'
' :ARG1 (b / beta)))'))
assert encode(g) == '(a / alpha :mod-of (b / beta))'
# dereification is blocked because node has additional relations
g = norm(
decode('(a / alpha :ARG1-of (_ / have-mod-91'
' :ARG2 (b / beta)'
' :polarity -))'))
assert encode(g) == (
'(a / alpha :ARG1-of (_ / have-mod-91 :ARG2 (b / beta) :polarity -))')
g = norm(
decode('''
(a / alpha
:ARG1-of (b / beta
:ARG0 p)
:ARG1-of (g / gamma
:ARG0-of (_ / own-01
:ARG1 (p / pi))))'''))
assert encode(g) == ('(a / alpha :ARG1-of (b / beta :ARG0 p)'
' :ARG1-of (g / gamma :poss (p / pi)))')