def test_implies_A_B_and_C(self):
A, B, C, *_ = self.alpha_symbols
expr = A >> (A & C)
model = mental_model_builder(expr, Insight.INTUITIVE)
npt.assert_almost_equal(model.model, np.array([
[POS_VAL, POS_VAL],
]))
def test_or_notA_B(self):
A, B = self.alpha_symbols[:2]
expr = A | ~B
model = mental_model_builder(expr, Insight.INTUITIVE)
npt.assert_allclose(
model.model,
np.array([[POS_VAL, IMPL_NEG], [POS_VAL, EXPL_NEG],
[POS_VAL, POS_VAL], [IMPL_NEG, EXPL_NEG]]))
def test_implication(self):
A, B = self.alpha_symbols[:2]
expr = Implies(A, B)
model = mental_model_builder(expr, Insight.EXPLICIT)
npt.assert_allclose(
model.model,
np.array([[POS_VAL, POS_VAL], [IMPL_NEG, POS_VAL],
[IMPL_NEG, IMPL_NEG]]))
def test_A_and_B_XOR_B_and_C(self):
A, B, C, D, *_ = self.alpha_symbols
expr = Xor(And(A, B), And(B, C))
model = mental_model_builder(expr, Insight.INTUITIVE)
print("this is is the interesting part", model)
npt.assert_allclose(
model.model,
np.array([[POS_VAL, POS_VAL, IMPL_NEG],
[IMPL_NEG, POS_VAL, POS_VAL]]))
def test_B_in_or_xor(self):
A, B, C, D, *_ = self.alpha_symbols
expr = And(A, Or(B, C), Xor(B, D))
model = mental_model_builder(expr, Insight.INTUITIVE)
npt.assert_allclose(
model.model,
np.array([[POS_VAL, POS_VAL, IMPL_NEG, IMPL_NEG],
[POS_VAL, POS_VAL, POS_VAL, IMPL_NEG],
[POS_VAL, IMPL_NEG, POS_VAL, POS_VAL]]))
def test_print_long_example(self):
A, B, C, D, E, F, G = self.alpha_symbols
expr = And(A, Or(B, C), Xor(D, E))
model = mental_model_builder(expr, Insight.INTUITIVE)
npt.assert_allclose(
model.model,
np.array([[POS_VAL, POS_VAL, IMPL_NEG, POS_VAL, IMPL_NEG],
[POS_VAL, POS_VAL, IMPL_NEG, IMPL_NEG, POS_VAL],
[POS_VAL, IMPL_NEG, POS_VAL, POS_VAL, IMPL_NEG],
[POS_VAL, IMPL_NEG, POS_VAL, IMPL_NEG, POS_VAL],
[POS_VAL, POS_VAL, POS_VAL, POS_VAL, IMPL_NEG],
[POS_VAL, POS_VAL, POS_VAL, IMPL_NEG, POS_VAL]]))
def _infer(expressions, mode):
sympified_expressions = [parse_format(expr) for expr in expressions]
print(sympified_expressions)
models = []
for sympified_expression in sympified_expressions:
print("The expression to be evaluated is: {}".format(
sympified_expression))
model = mental_model_builder(sympified_expression, mode)
print(model)
models.append(model)
print("The mental model that has been created is:")
for possible_world in model.model:
print(
pretty_print_atom_assign(model.atoms_model, possible_world,
mode))
result = infer(models)
for possible_world in result.model:
print(possible_world)
print(
pretty_print_atom_assign(result.atoms_model, possible_world, mode))
def main(args):
expressions_to_parse = args.expression.split(", ")
sympified_expressions = [
parse_format(expr) for expr in expressions_to_parse
]
print("The following expressions have been parsed:")
for exp in sympified_expressions:
print("\t{}".format(exp))
models = []
for sympified_expression in sympified_expressions:
print()
print("The expression to be evaluated is: {}".format(
sympified_expression))
model = mental_model_builder(sympified_expression, args.mode)
logging.debug("{}".format(model))
models.append(model)
print("The mental model that has been created is:")
for possible_world in model.model:
print(
pretty_print_atom_assign(possible_world, model.atoms_model,
args.mode))
if len(models) <= 1:
return "Nothing to infer"
result = infer(models, args.infer)
print(result, flush=True)
if args.infer == InferenceTask.FOLLOWS:
if not result:
print("The result is the empty model", result.model)
print(result)
for possible_world in result.model:
print(
pretty_print_atom_assign(possible_world, result.atoms_model,
args.mode))
def test_not(self):
A, B = self.alpha_symbols[:2]
expr = Not(A)
model = mental_model_builder(expr, Insight.INTUITIVE)
npt.assert_allclose(model.model, np.array([[EXPL_NEG]]))
def _eval_expr(expressions, mode):
# Does the right thing
result = infer([
mental_model_builder(parse_format(expr), mode) for expr in expressions
], InferenceTask.FOLLOWS)
return result.model
def test_basic_cases(self):
"""
1 A AND NOT A.
This premise is a self-contradiction.
The models of premise 1 represent: Null model.
Number of models constructed equals 0
"""
npt.assert_array_equal(
mental_model_builder(parse_format("a & ~a"),
Insight.INTUITIVE).model, np.array([[]]))
"""
2 A OR NOT A.
The models of premise 1 represent:
A {T2 (((A)))}
¬ A {T1 (((- A)))}
Number of models constructed equals 2
"""
npt.assert_array_equal(
mental_model_builder(parse_format("a | ~a"),
Insight.INTUITIVE).model,
np.array([[POS_VAL], [EXPL_NEG]]))
"""
3 B. IF A THEN B.
The models of premise 1 represent:
B
The models of premise 2 represent:
A B
{T3 (((- A)))}
Premise 2 is POSSIBLE given previous premise or premises, and vice versa [consistent]. Premises so far yield models of only one possible outcome:-
B, and A.
Number of models constructed equals 3
"""
npt.assert_array_equal(_eval_expr(["b", "a -> b"], Insight.INTUITIVE),
np.array([[POS_VAL, POS_VAL]]))
"""
4 NOT A. IF A THEN B.
The models of premise 1 represent:
¬ A
The models of premise 2 represent:
A B
{T4 (((- A)))}
Premise 2 suggests no intuitive conclusion. Premises so far yield models of only one possible outcome:-
NOT A, and T4.
Number of models constructed equals 3
"""
npt.assert_array_equal(_eval_expr(["~a", "a -> b"], Insight.INTUITIVE),
np.array([[]]))
"""
5 A. IF A THEN B. B.
The models of premise 1 represent:
A
The models of premise 2 represent:
A B
{T5 (((- A)))}
Premise 2 is POSSIBLE given previous premise or premises, and vice versa [consistent]. Premises so far yield models of only one possible outcome:-
A, and B.
The models of premise 3 represent:
B
Premise 3 FOLLOWS from previous premise or premises [valid]. Premises so far yield models of only one possible outcome:-
A, and B.
Number of models constructed equals 5
"""
npt.assert_array_equal(
_eval_expr(["a", "a -> b", "b"], Insight.INTUITIVE),
np.array([[POS_VAL, POS_VAL]]))
"""
6 A. IF A THEN B. A AND B AND C.
The models of premise 1 represent:
A
The models of premise 2 represent:
A B
{T6 (((- A)))}
Premise 2 is POSSIBLE given previous premise or premises, and vice versa [consistent]. Premises so far yield models of only one possible outcome:-
A, and B.
The models of premise 3 represent:
A B C
Premise 3 is POSSIBLE given previous premise or premises, and vice versa [consistent]. Premises so far yield models of only one possible outcome:-
A, B, and C.
Number of models constructed equals 5
"""
npt.assert_array_equal(
_eval_expr(["a", "a -> b", "a & b & c"], Insight.INTUITIVE),
np.array([[POS_VAL, POS_VAL, POS_VAL]]))
"""
7 A. IF A THEN COMMA B AND C. A AND B AND C.
The models of premise 1 represent:
A
The models of premise 2 represent:
A B C
{T7 (((- A)))}
Premise 2 is POSSIBLE given previous premise or premises, and vice versa [consistent]. Premises so far yield models of only one possible outcome:-
A, B, and C.
The models of premise 3 represent:
A B C
Premise 3 FOLLOWS from previous premise or premises, and vice versa [mutually valid]. Premises so far yield models of only one possible outcome:-
A, B, and C.
Number of models constructed equals 5
"""
npt.assert_array_equal(
_eval_expr(["a", "a -> (b & c)", "a & b & c"], Insight.INTUITIVE),
np.array([[POS_VAL, POS_VAL, POS_VAL]]))
"""
8 A. IF A THEN B. B AND A.
The models of premise 1 represent:
A
The models of premise 2 represent:
A B
{T8 (((- A)))}
Premise 2 is POSSIBLE given previous premise or premises, and vice versa [consistent]. Premises so far yield models of only one possible outcome:-
A, and B.
The models of premise 3 represent:
B A
Premise 3 FOLLOWS from previous premise or premises, and vice versa [mutually valid]. Premises so far yield models of only one possible outcome:-
A, and B.
Number of models constructed equals 5
"""
npt.assert_array_equal(
_eval_expr(["a", "a -> b", "b & a"], Insight.INTUITIVE),
np.array([[POS_VAL, POS_VAL]]))
"""
9 IF A THEN B. A AND NOT B.
The models of premise 1 represent:
A B
{T9 (((- A)))}
The models of premise 2 represent:
A ¬ B
Premise 2 is IMPOSSIBLE given the previous premise or premises, and vice versa [inconsistent]. Premises so far yield models of 0 possibilities:- Null model.
Number of models constructed equals 2
"""
"""
10 IF A THEN B. A. NOT B.
The models of premise 1 represent:
A B
{T10 (((- A)))}
The models of premise 2 represent:
A
Premise 2 is CONSISTENT with previous premise or premises, and vice versa. Premises so far yield models of only one possible outcome:-
A, and B.
The models of premise 3 represent:
¬ B
Premise 3 is IMPOSSIBLE given the previous premise or premises, and vice versa [inconsistent]. Premises so far yield models of 0 possibilities:- Null model.
Number of models constructed equals 4
"""
"""
11 A OR B. A.
The models of premise 1 represent:
A {T12 (((- B)))}
B {T11 (((- A)))}
A B
The models of premise 2 represent:
A
Premise 2 is CONSISTENT with previous premise or premises, and vice versa. Premises so far yield models of 3 possibilities:-
A {T12 (((- B)))}
A B {T11 (((- A)))}
A B
Number of models constructed equals 7
"""
"""
12 A OR B. B.
The models of premise 1 represent:
A {T14 (((- B)))}
B {T13 (((- A)))}
A B
The models of premise 2 represent:
B
Premise 2 is CONSISTENT with previous premise or premises, and vice versa. Premises so far yield models of 3 possibilities:-
A B {T14 (((- B)))}
B {T13 (((- A)))}
A B
Number of models constructed equals 7
"""
"""
13 A OR B. A AND B.
The models of premise 1 represent:
A {T16 (((- B)))}
B {T15 (((- A)))}
A B
The models of premise 2 represent:
A B
Premise 2 is CONSISTENT with previous premise or premises, and vice versa. Premises so far yield models of 3 possibilities:-
A B {T16 (((- B)))}
A B {T15 (((- A)))}
A B
Number of models constructed equals 7
"""
"""
14 A. A OR B.
The models of premise 1 represent:
A
The models of premise 2 represent:
A {T18 (((- B)))}
B {T17 (((- A)))}
A B
Premise 2 is POSSIBLE given previous premise or premises, and vice versa [consistent]. Premises so far yield models of 3 possibilities:-
A {T18 (((- B)))}
A B {T17 (((- A)))}
A B
Number of models constructed equals 7
"""
"""
15 A OR B. C.
The models of premise 1 represent:
A {T20 (((- B)))}
B {T19 (((- A)))}
A B
The models of premise 2 represent:
C
Premise 2 is wholly independent of previous premises [consistent]. Premises so far yield models of 3 possibilities:-
A C {T20 (((- B)))}
C B {T19 (((- A)))}
A C B
Number of models constructed equals 7
"""
"""
16 A. A ORE B. NOT B.
The models of premise 1 represent:
A
The models of premise 2 represent:
A {T22 (((- B)))}
B {T21 (((- A)))}
Premise 2 is POSSIBLE given previous premise or premises, and vice versa [consistent]. Premises so far yield models of 2 possibilities:-
A {T22 (((- B)))}
A B {T21 (((- A)))}
The models of premise 3 represent:
¬ B
Premise 3 suggests no intuitive conclusion. Premises so far yield models of only one possible outcome:-
A, T22, and NOT B.
Number of models constructed equals 7
"""
"""
17 NOT A. A ORE B. B.
The models of premise 1 represent:
¬ A
The models of premise 2 represent:
A {T24 (((- B)))}
B {T23 (((- A)))}
Premise 2 suggests no intuitive conclusion. Premises so far yield models of only one possible outcome:-
NOT A, B, and T23.
The models of premise 3 represent:
B
Premise 3 FOLLOWS from previous premise or premises [valid]. Premises so far yield models of only one possible outcome:-
NOT A, B, and T23.
Number of models constructed equals 6
"""
"""
18 NOT A. A OR B. B.
The models of premise 1 represent:
¬ A
The models of premise 2 represent:
A {T26 (((- B)))}
B {T25 (((- A)))}
A B
Premise 2 suggests no intuitive conclusion. Premises so far yield models of only one possible outcome:-
NOT A, B, and T25.
The models of premise 3 represent:
B
Premise 3 FOLLOWS from previous premise or premises [valid]. Premises so far yield models of only one possible outcome:-
NOT A, B, and T25.
Number of models constructed equals 7
"""
"""
19 A OR B. NOT B. A.
The models of premise 1 represent:
A {T28 (((- B)))}
B {T27 (((- A)))}
A B
The models of premise 2 represent:
¬ B
Premise 2 suggests no intuitive conclusion. Premises so far yield models of only one possible outcome:-
A, T28, and NOT B.
The models of premise 3 represent:
A
Premise 3 FOLLOWS from previous premise or premises [valid]. Premises so far yield models of only one possible outcome:-
A, T28, and NOT B.
Number of models constructed equals 7
"""
"""
20 A OR B. NOT A. NOT A AND B AND C.
The models of premise 1 represent:
A {T30 (((- B)))}
B {T29 (((- A)))}
A B
The models of premise 2 represent:
¬ A
Premise 2 suggests no intuitive conclusion. Premises so far yield models of only one possible outcome:-
B, T29, and NOT A.
The models of premise 3 represent:
¬ A B C
Premise 3 suggests no intuitive conclusion. Premises so far yield models of only one possible outcome:-
B, T29, NOT A, and C.
Number of models constructed equals 7
"""
"""
21 A OR B. NOT B. A AND NOT B.
The models of premise 1 represent:
A {T32 (((- B)))}
B {T31 (((- A)))}
A B
The models of premise 2 represent:
¬ B
Premise 2 suggests no intuitive conclusion. Premises so far yield models of only one possible outcome:-
A, T32, and NOT B.
The models of premise 3 represent:
A ¬ B
Premise 3 FOLLOWS from previous premise or premises [valid]. Premises so far yield models of only one possible outcome:-
A, T32, and NOT B.
Number of models constructed equals 7
"""
"""
22 A OR B. NOT A. NOT B.
The models of premise 1 represent:
A {T34 (((- B)))}
B {T33 (((- A)))}
A B
The models of premise 2 represent:
¬ A
Premise 2 suggests no intuitive conclusion. Premises so far yield models of only one possible outcome:-
B, T33, and NOT A.
The models of premise 3 represent:
¬ B
Premise 3 is IMPOSSIBLE given the previous premise or premises, and vice versa [inconsistent]. Premises so far yield models of 0 possibilities:- Null model.
Number of models constructed equals 6
"""
"""
23 A ORE B. A OR B.
The models of premise 1 represent:
A {T36 (((- B)))}
B {T35 (((- A)))}
The models of premise 2 represent:
A {T38 (((- B)))}
B {T37 (((- A)))}
A B
Premise 2 suggests no intuitive conclusion. Premises so far yield models of 6 possibilities:-
A {T36 (((- B)))} {T38 (((- B)))}
A B {T37 (((- A)))} {T36 (((- B)))}
A B {T36 (((- B)))}
A B {T35 (((- A)))} {T38 (((- B)))}
B {T37 (((- A)))} {T35 (((- A)))}
A B {T35 (((- A)))}
Number of models constructed equals 11
"""
"""
def test_A_or_A(self):
A, B = self.alpha_symbols[:2]
expr = Or(A, A)
model = mental_model_builder(expr, Insight.INTUITIVE)
npt.assert_allclose(model.model, np.array([[POS_VAL]]))
def test_A_or_B_and_A_ore_B(self):
A, B, *_ = self.alpha_symbols
expr = (A | B) & (A ^ B)
model = mental_model_builder(expr, Insight.INTUITIVE)
npt.assert_almost_equal(
model.model, np.array([[POS_VAL, IMPL_NEG], [IMPL_NEG, POS_VAL]]))
def test_and_negA_negB(self):
A, B = self.alpha_symbols[:2]
expr = And(~A, ~B)
model = mental_model_builder(expr, Insight.INTUITIVE)
npt.assert_allclose(model.model, np.array([[EXPL_NEG, EXPL_NEG]]))
def test_and_not_A_B(self):
A, B = self.alpha_symbols[:2]
expr = And(Not(A), B)
model = mental_model_builder(expr, Insight.INTUITIVE)
npt.assert_allclose(model.model, np.array([[EXPL_NEG, POS_VAL]]))
def test_implies_intuitive(self):
A, B = self.alpha_symbols[:2]
expr = Implies(A, B)
model = mental_model_builder(expr, Insight.INTUITIVE)
npt.assert_allclose(model.model, np.array([[POS_VAL, POS_VAL]]))
def test_xor(self):
A, B = self.alpha_symbols[:2]
expr = Xor(A, B)
model = mental_model_builder(expr, Insight.INTUITIVE)
npt.assert_allclose(
model.model, np.array([[POS_VAL, IMPL_NEG], [IMPL_NEG, POS_VAL]]))
def test_equals(self):
A, B = self.alpha_symbols[:2]
expr = Equivalent(A, B)
model = mental_model_builder(expr, Insight.INTUITIVE)
npt.assert_allclose(model.model, np.array([[POS_VAL, POS_VAL]]))