def test_find_argument_target():
assert query.find_argument_target(m, 10000, 'RSTR') == 10002
assert query.find_argument_target(m, 10001, 'ARG1') == 10002
assert query.find_argument_target(m, 10003, 'ARG2') == 10005
# test CARGs and unbound vars: "Abrams tried."
m2 = Xmrs(
top='h0',
eps=[
EP(10000, sp('proper_q_rel'), 'h4', {
'ARG0': 'x3',
'RSTR': 'h5'
}),
EP(10001, sp('named_rel'), 'h7', {
'ARG0': 'x3',
'CARG': 'Abrams'
}),
EP(10002, sp('"_try_v_1_rel"'), 'h1', {
'ARG0': 'e2',
'ARG1': 'x3',
'ARG2': 'i9'
}),
],
hcons=[qeq('h0', 'h1'), qeq('h5', 'h7')],
)
assert query.find_argument_target(m2, 10001, 'CARG') == 'Abrams'
assert query.find_argument_target(m2, 10002, 'ARG2') == 'i9'
def test_construct(self):
with pytest.raises(TypeError): EP()
with pytest.raises(TypeError): EP(10)
with pytest.raises(TypeError): EP(10, spred('_dog_n_rel'))
e = EP(10, spred('_dog_n_rel'), 'h1')
assert e.nodeid == 10
assert e.pred == '_dog_n_rel'
assert e.label == 'h1'
def test_is_quantifier(self):
e = EP(10, spred('_the_q_rel'), 'h1', args={RSTR_ROLE: 'h2'})
assert e.is_quantifier() == True
# not a q pred, but has RSTR
e = EP(10, spred('_dog_n_rel'), 'h1', args={RSTR_ROLE: 'h2'})
assert e.is_quantifier() == True
# a q pred, but no RSTR
e = EP(10, spred('_the_q_rel'), 'h1', args={})
assert e.is_quantifier() == False
def test_args(self):
p = spred('_chase_v_rel')
lbl = 'h1'
e = EP(11, p, lbl)
assert len(e.args) == 0
v1 = 'e2'
e = EP(11, p, lbl, args={IVARG_ROLE: v1})
assert len(e.args) == 1
assert e.args[IVARG_ROLE] == v1
v2 = 'x3'
e = EP(11, p, lbl, args={IVARG_ROLE: v1, 'ARG1': v2})
assert len(e.args) == 2
assert e.args[IVARG_ROLE] == v1
assert e.args['ARG1'] == v2
def test_from_dict(self):
assert Mrs.from_dict({}) == Mrs()
m1 = Mrs.from_dict({
'relations': [{
'label': 'h1',
'predicate': '_rain_v_1',
'arguments': {
'ARG0': 'e2'
}
}],
'constraints': [],
'variables': {
'h1': {
'type': 'h'
},
'e2': {
'type': 'e'
}
}
})
m2 = Mrs(rels=[
EP(FIRST_NODEID, sp('"_rain_v_1_rel"'), 'h1', {'ARG0': 'e2'})
])
assert m1 == m2
def test_to_dict(self):
assert Mrs().to_dict() == {
'relations': [], 'constraints': [], 'variables': {}
}
x = Mrs(rels=[EP(10, sp('"_rain_v_1_rel"'), 'h1', {'ARG0': 'e2'})])
assert x.to_dict() == {
'relations': [
{'label': 'h1', 'predicate': '_rain_v_1',
'arguments': {'ARG0': 'e2'}}
],
'constraints': [],
'variables': {'h1': {'type': 'h'}, 'e2': {'type': 'e'}}
}
x = Mrs(
top='h0',
rels=[EP(10, sp('"_rain_v_1_rel"'), 'h1', {'ARG0': 'e2'})],
hcons=[('h0', 'qeq', 'h1')],
vars={'e2': {'SF': 'prop', 'TENSE': 'pres'}}
)
assert x.to_dict() == {
'top': 'h0',
'relations': [
{'label': 'h1', 'predicate': '_rain_v_1',
'arguments': {'ARG0': 'e2'}}
],
'constraints': [{'relation': 'qeq', 'high': 'h0', 'low': 'h1'}],
'variables': {
'h0': {'type': 'h'}, 'h1': {'type': 'h'},
'e2': {'type': 'e',
'properties': {'SF': 'prop', 'TENSE': 'pres'}}
}
}
assert x.to_dict(properties=False) == {
'top': 'h0',
'relations': [
{'label': 'h1', 'predicate': '_rain_v_1',
'arguments': {'ARG0': 'e2'}}
],
'constraints': [{'relation': 'qeq', 'high': 'h0', 'low': 'h1'}],
'variables': {
'h0': {'type': 'h'}, 'h1': {'type': 'h'},
'e2': {'type': 'e'}
}
}
def test_single_ep(self):
# basic, one EP, no TOP
x = Mrs(rels=[EP(10, sp('"_rain_v_1_rel"'), 'h1')])
check_xmrs(x, None, None, None, 1, 0, 0, 1)
# variables don't need to be created predictably, but it's nice
# to get the expected values for simple cases
assert x.label(10) == 'h1'
assert x.ep(10).iv == None
# now with ARG0
x = Mrs(rels=[EP(10, sp('"_rain_v_1_rel"'), 'h1', {'ARG0': 'e2'})])
check_xmrs(x, None, None, None, 1, 0, 0, 2)
assert x.label(10) == 'h1'
assert x.ep(10).iv == 'e2'
# now with TOP
x = Mrs(top='h0',
rels=[EP(10, sp('"_rain_v_1_rel"'), 'h1', {'ARG0': 'e2'})],
hcons=[('h0', 'qeq', 'h1')])
check_xmrs(x, 'h0', None, None, 1, 1, 0, 3)
assert x.label(10) == 'h1'
assert x.ep(10).iv == 'e2'
from delphin.mrs.xmrs import Xmrs
from delphin.mrs.components import ElementaryPredication as EP, Pred
from delphin.mrs import query
sp = Pred.surface
qeq = lambda hi, lo: (hi, 'qeq', lo)
# "Cats are chased by big dogs." (reordered, but equivalent)
m = Xmrs(top='h0',
eps=[
EP(10000, sp('udef_q_rel'), 'h4', {
'ARG0': 'x3',
'RSTR': 'h5'
}),
EP(10001, sp('"_big_a_1_rel"'), 'h7', {
'ARG0': 'e8',
'ARG1': 'x3'
}),
EP(10002, sp('"_dog_n_1_rel"'), 'h7', {'ARG0': 'x3'}),
EP(10003, sp('"_chase_v_1_rel"'), 'h1', {
'ARG0': 'e2',
'ARG1': 'x3',
'ARG2': 'x9'
}),
EP(10004, sp('udef_q_rel'), 'h10', {
'ARG0': 'x9',
'RSTR': 'h11'
}),
EP(10005, sp('"_cat_n_1_rel"'), 'h13', {'ARG0': 'x9'})
],
hcons=[qeq('h0', 'h1'),
from delphin.mrs import xmrs, path as mp
from delphin.mrs.components import Pred, ElementaryPredication as EP
sp = Pred.surface
def qeq(hi, lo):
return (hi, 'qeq', lo)
m0 = xmrs.Xmrs()
# "It rains."
m1 = xmrs.Xmrs(top='h0',
eps=[EP(10000, sp('"_rain_v_1_rel"'), 'h1', {'ARG0': 'e2'})],
hcons=[qeq('h0', 'h1')])
# "Big dogs bark."
m2 = xmrs.Xmrs(top='h0',
eps=[
EP(10000, sp('udef_q_rel'), 'h4', {
'ARG0': 'x3',
'RSTR': 'h5'
}),
EP(10001, sp('"_big_a_1_rel"'), 'h7', {
'ARG0': 'e8',
'ARG1': 'x3'
}),
EP(10002, sp('"_dog_n_1_rel"'), 'h7', {'ARG0': 'x3'}),
EP(10003, sp('"_bark_v_1_rel"'), 'h1', {
'ARG0': 'e2',
Node, ElementaryPredication as EP
)
spred = Pred.stringpred
from delphin.mrs.xmrs import Xmrs
from delphin.mrs.config import (
CVARSORT, IVARG_ROLE, CONSTARG_ROLE,
EQ_POST, HEQ_POST, NEQ_POST, H_POST, NIL_POST,
LTOP_NODEID, FIRST_NODEID
)
# store some example MRSs for later tests (note, some are made by hand)
# just a verb; e.g. "it rains"
x1 = Xmrs(
top='h0',
eps=[EP(10000, spred('_rain_v_1_rel'), 'h1', {'ARG0': 'e2'})],
hcons=[('h0', 'qeq', 'h1')]
)
# modified verb, e.g. "it rains heavily"
x2 = Xmrs(
top='h0',
eps=[
EP(10000, spred('_rain_v_1_rel'), 'h1', {'ARG0': 'e2'}),
EP(10001, spred('_heavy_a_1_rel'), 'h1',
{'ARG0': 'e4', 'ARG1': 'e2'})
],
hcons=[('h0', 'qeq', 'h1')]
)
# Verb and noun with quantifier; e.g. "the dog barks"
x3 = Xmrs(
top='h0',
