def model_check_graph_johnson(goal):
res_lst = []
# load model
with open(VTE + "/work/model_graph_johnson.pkl", 'rb') as f:
model = pickle.load(f)
# load fol
with open(VTE + "/work/fol_graph_johnson_200.pkl", 'rb') as f:
fol = pickle.load(f)
keys = fol.keys()
#keys = list(set(model.keys()) - set(noise_lst))
for key in keys:
m = model[key]
dom = model[key].domain
g = evaluate.Assignment(dom)
goal_preds = lexpr(goal).predicates()
for pred in goal_preds:
if m.valuation.get(str(pred)) is None:
m.valuation[str(pred)] = set()
res = (m.evaluate(goal, g))
if res == "Undefined":
res = False
if res:
res_lst.append(key)
return (res_lst)
def demo_model0():
global m0, g0
# Initialize a valuation of non-logical constants."""
v = [
("john", "b1"),
("mary", "g1"),
("suzie", "g2"),
("fido", "d1"),
("tess", "d2"),
("noosa", "n"),
("girl", {"g1", "g2"}),
("boy", {"b1", "b2"}),
("dog", {"d1", "d2"}),
("bark", {"d1", "d2"}),
("walk", {"b1", "g2", "d1"}),
("chase", {("b1", "g1"), ("b2", "g1"), ("g1", "d1"), ("g2", "d2")}),
(
"see",
{("b1", "g1"), ("b2", "d2"), ("g1", "b1"), ("d2", "b1"),
("g2", "n")},
),
("in", {("b1", "n"), ("b2", "n"), ("d2", "n")}),
("with", {("b1", "g1"), ("g1", "b1"), ("d1", "b1"), ("b1", "d1")}),
]
# Read in the data from ``v``
val = evaluate.Valuation(v)
# Bind ``dom`` to the ``domain`` property of ``val``
dom = val.domain
# Initialize a model with parameters ``dom`` and ``val``.
m0 = evaluate.Model(dom, val)
# Initialize a variable assignment with parameter ``dom``
g0 = evaluate.Assignment(dom)
def model_check(goal, flag_cap):
res_lst = []
if flag_cap:
# load model_cap
with open(VTE + "/work/structure_cap.pkl", 'rb') as f:
model = pickle.load(f)
else:
# load model
with open(VTE + "/work/structure.pkl", 'rb') as f:
model = pickle.load(f)
keys = model.keys()
#keys = list(set(model.keys()) - set(noise_lst))
for key in keys:
m = model[key]
dom = model[key].domain
g = evaluate.Assignment(dom)
goal_preds = lexpr(goal).predicates()
for pred in goal_preds:
if m.valuation.get(str(pred)) is None:
m.valuation[str(pred)] = set()
res = (m.evaluate(goal, g))
if res == "Undefined":
res = False
if res:
res_lst.append(key)
return (res_lst)
def demo_model0():
global m0, g0
# Initialize a valuation of non-logical constants."""
v = [
('john', 'b1'),
('mary', 'g1'),
('suzie', 'g2'),
('fido', 'd1'),
('tess', 'd2'),
('noosa', 'n'),
('girl', set(['g1', 'g2'])),
('boy', set(['b1', 'b2'])),
('dog', set(['d1', 'd2'])),
('bark', set(['d1', 'd2'])),
('walk', set(['b1', 'g2', 'd1'])),
('chase', set([('b1', 'g1'), ('b2', 'g1'), ('g1', 'd1'),
('g2', 'd2')])),
(
'see',
set([('b1', 'g1'), ('b2', 'd2'), ('g1', 'b1'), ('d2', 'b1'),
('g2', 'n')]),
),
('in', set([('b1', 'n'), ('b2', 'n'), ('d2', 'n')])),
('with', set([('b1', 'g1'), ('g1', 'b1'), ('d1', 'b1'),
('b1', 'd1')])),
]
# Read in the data from ``v``
val = evaluate.Valuation(v)
# Bind ``dom`` to the ``domain`` property of ``val``
dom = val.domain
# Initialize a model with parameters ``dom`` and ``val``.
m0 = evaluate.Model(dom, val)
# Initialize a variable assignment with parameter ``dom``
g0 = evaluate.Assignment(dom)
def model_check_key(key, goal, flag_cap):
if flag_cap:
# load model_cap
with open(VTE + "/work/structure_cap.pkl", 'rb') as f:
model = pickle.load(f)
else:
# load model
with open(VTE + "/work/structure.pkl", 'rb') as f:
model = pickle.load(f)
m = model[key]
dom = model[key].domain
g = evaluate.Assignment(dom)
goal_preds = lexpr(goal).predicates()
for pred in goal_preds:
if m.valuation.get(str(pred)) is None:
m.valuation[str(pred)] = set()
res = (m.evaluate(goal, g))
if res == "Undefined":
res = False
return (res)