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2
.gitignore
vendored
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.gitignore
vendored
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__pycache__
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.vscode
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124
R.py
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124
R.py
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"""
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Modeling the logic R
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"""
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from logic import (
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PropositionalVariable,
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Rule,
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Logic,
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Implication,
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Conjunction,
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Negation,
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Disjunction,
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Rule,
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)
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from model import Model, ModelFunction, ModelValue
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from generate_model import generate_model
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# ===================================================
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# Defining the logic of R
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x = PropositionalVariable("x")
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y = PropositionalVariable("y")
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z = PropositionalVariable("z")
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implication_rules = {
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Rule({}, Implication(x, x)),
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Rule({Implication(x, y), Implication(y, z)}, Implication(x, z)),
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Rule({}, Implication(Implication(x, Implication(x, y)), Implication(x, y))),
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Rule({}, Implication(Implication(x, Implication(y, z)), Implication(y, Implication(x, z)))),
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Rule({}, Implication(Implication(x, y), Implication(Implication(z, x), Implication(z, y)))),
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Rule({}, Implication(Implication(x, y), Implication(Implication(y, z), Implication(x, z)))),
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Rule({Implication(x, y), x}, y)
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}
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negation_rules = {
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Rule({}, Implication(Negation(Negation(x)), x)),
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Rule({}, Implication(x, Negation(Negation(x)))),
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Rule({Implication(x, y)}, Implication(Negation(y), Negation(x))),
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Rule({}, Implication(Implication(x, y), Implication(Negation(y), Negation(x))))
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}
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conjunction_rules = {
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Rule({y, z}, Conjunction(y, z)),
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Rule({}, Implication(Conjunction(x, y), x)),
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Rule({}, Implication(Conjunction(x, y), y)),
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Rule({}, Implication(Conjunction(Implication(x, y), Implication(x, z)), Implication(x, Conjunction(y, z))))
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}
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disjunction_rules = {
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Rule({}, Implication(x, Disjunction(x, y))),
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Rule({}, Implication(y, Disjunction(x, y))),
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Rule({}, Implication(Conjunction(Implication(x, z), Implication(y, z)), Implication(Disjunction(x, y), z))),
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Rule({}, Implication(Conjunction(x, Disjunction(y, z)), Disjunction(Conjunction(x, y), Conjunction(x, z))))
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}
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logic_rules = implication_rules | negation_rules | conjunction_rules | disjunction_rules
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operations = {Negation, Conjunction, Disjunction, Implication}
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R_logic = Logic(operations, logic_rules)
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# ===============================
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# Example Model of R
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a0 = ModelValue("a0")
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a1 = ModelValue("a1")
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carrier_set = {a0, a1}
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mnegation = ModelFunction({
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a0: a1,
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a1: a0
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})
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mimplication = ModelFunction({
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(a0, a0): a1,
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(a0, a1): a1,
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(a1, a0): a0,
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(a1, a1): a1
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})
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mconjunction = ModelFunction({
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(a0, a0): a0,
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(a0, a1): a0,
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(a1, a0): a0,
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(a1, a1): a1
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})
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mdisjunction = ModelFunction({
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(a0, a0): a0,
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(a0, a1): a1,
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(a1, a0): a1,
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(a1, a1): a1
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})
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designated_values = {a1}
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logical_operations = {
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mnegation, mimplication, mconjunction, mdisjunction
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}
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R_model_2 = Model(carrier_set, logical_operations, designated_values)
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interpretation = {
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Negation: mnegation,
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Conjunction: mconjunction,
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Disjunction: mdisjunction,
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Implication: mimplication
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}
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# =================================
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# Generate models of R of a given size
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model_size = 2
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satisfiable_models = generate_model(R_logic, model_size)
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print(f"There are {len(satisfiable_models)} satisfiable models of element length {model_size}")
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63
generate_model.py
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generate_model.py
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"""
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File which generates all the models
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"""
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from logic import Logic
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from model import ModelValue, Model, satisfiable, ModelFunction
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from itertools import combinations, chain, product
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def possible_designations(iterable):
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"""Powerset without the empty and complete set"""
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s = list(iterable)
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return chain.from_iterable(combinations(s, r) for r in range(1, len(s)))
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def possible_functions(operation, carrier_set):
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arity = operation.arity
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inputs = list(product(*(carrier_set for _ in range(arity))))
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possible_outputs = product(*(carrier_set for _ in range(len(inputs))))
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for outputs in possible_outputs:
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assert len(inputs) == len(outputs)
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new_function = dict()
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for input, output in zip(inputs, outputs):
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new_function[input] = output
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yield ModelFunction(new_function, operation.symbol)
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def possible_interpretations(logic, carrier_set):
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operations = []
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model_functions = []
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for operation in logic.operations:
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operations.append(operation)
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model_functions.append(possible_functions(operation, carrier_set))
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functions_choice = product(*model_functions)
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for functions in functions_choice:
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assert len(operations) == len(functions)
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interpretation = dict()
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for operation, function in zip(operations, functions):
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interpretation[operation] = function
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yield interpretation
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def generate_model(logic: Logic, number_elements: int):
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carrier_set = {
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ModelValue("a" + str(i)) for i in range(number_elements)
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}
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possible_designated_values = possible_designations(carrier_set)
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possible_interps = possible_interpretations(logic, carrier_set)
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satisfied_models = []
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checked = 0
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for designated_values, interpretation in product(possible_designated_values, possible_interps):
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checked += 1
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designated_values = set(designated_values)
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model = Model(carrier_set, set(interpretation.values()), designated_values)
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if satisfiable(logic, model, interpretation):
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satisfied_models.append(model)
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print(model)
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print("Checked", checked)
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return satisfied_models
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128
logic.py
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128
logic.py
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from typing import Any, Set
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from functools import lru_cache
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class Operation:
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def __init__(self, symbol: str, arity: int):
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self.symbol = symbol
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self.arity = arity
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self.hashed_value = hash(self.symbol) + self.arity
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def immutable(self, name, value):
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raise Exception("Operations are immutable")
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self.__setattr__ = immutable
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def __hash__(self):
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return self.hashed_value
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def __call__(self, *args):
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# Ensure the arity is met
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assert len(args) == self.arity
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# Ensure every argument is a term
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for t in args:
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assert isinstance(t, Term)
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return OpTerm(self, args)
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class Term:
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def __init__(self):
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pass
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def __lt__(self, y):
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return Inequation(self, y)
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class PropositionalVariable(Term):
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def __init__(self, name):
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self.name = name
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self.hashed_value = hash(self.name)
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def immutable(self, name, value):
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raise Exception("Propositional variables are immutable")
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self.__setattr__ = immutable
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def __hash__(self):
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return self.hashed_value
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# def __setattr__(self, name: str, value: Any):
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# raise Exception("Propositional variables are immutable")
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def __str__(self):
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return self.name
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# def PropTerm(Term):
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# def __init__(self, v: PropositionalVariable):
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# self.v = v
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class OpTerm(Term):
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def __init__(self, operation: Operation, arguments):
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assert len(arguments) == operation.arity
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self.operation = operation
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self.arguments = arguments
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self.hashed_value = hash(self.operation) * hash(self.arguments)
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def immutable(self, name, value):
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raise Exception("Terms are immutable")
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self.__setattr__ = immutable
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def __hash__(self):
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return self.hashed_value
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def __str__(self):
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arg_strs = [str(a) for a in self.arguments]
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return self.operation.symbol + "(" + ",".join(arg_strs) + ")"
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Negation = Operation("¬", 1)
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Conjunction = Operation("∧", 2)
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Disjunction = Operation("∨", 2)
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Implication = Operation("→", 2)
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class Inequation:
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def __init__(self, antecedant : Term, consequent: Term):
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self.antecedant = antecedant
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self.consequent = consequent
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def __str__(self):
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return str(self.antecedant) + "≤" + str(self.consequent)
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class InequalityRule:
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def __init__(self, premises : Set[Inequation], conclusion: Inequation):
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self.premises = premises
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self.conclusion = conclusion
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def __str__(self):
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str_premises = [str(p) for p in self.premises]
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str_premises2 = "{" + ",".join(str_premises) + "}"
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return str(str_premises2) + "=>" + str(self.conclusion)
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class Rule:
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def __init__(self, premises : Set[Term], conclusion: Term):
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self.premises = premises
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self.conclusion = conclusion
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def __str__(self):
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str_premises = [str(p) for p in self.premises]
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str_premises2 = "{" + ",".join(str_premises) + "}"
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return str(str_premises2) + "=>" + str(self.conclusion)
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class Logic:
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def __init__(self, operations: Set[Operation], rules: Set[Rule]):
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self.operations = operations
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self.rules = rules
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def get_prop_var_from_term(t: Term):
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if isinstance(t, PropositionalVariable):
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return {t,}
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result = set()
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for arg in t.arguments:
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result |= get_prop_var_from_term(arg)
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return result
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def get_propostional_variables(rules):
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vars = set()
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for rule in rules:
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# Get all vars in premises
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for premise in rule.premises:
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vars |= get_prop_var_from_term(premise)
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# Get vars in conclusion
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vars |= get_prop_var_from_term(rule.conclusion)
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return vars
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130
model.py
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model.py
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"""
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Defining what it means to be a model
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"""
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from logic import (
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PropositionalVariable, get_propostional_variables, Logic, Term,
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Operation
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)
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from typing import Set, List, Dict
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from itertools import product
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__all__ = ['ModelValue', 'ModelFunction', 'Model']
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def set_to_str(x):
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return "{" + ", ".join((str(xi) for xi in x)) + "}"
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class ModelValue:
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def __init__(self, name):
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self.name = name
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self.hashed_value = hash(self.name)
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def immutable(self, name, value):
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raise Exception("Model values are immutable")
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self.__setattr__ = immutable
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def __str__(self):
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return self.name
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def __hash__(self):
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return self.hashed_value
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def __eq__(self, other):
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return isinstance(other, ModelValue) and self.name == other.name
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class ModelFunction:
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def __init__(self, mapping, operation_name = ""):
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self.operation_name = operation_name
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# Correct input to always be a tuple
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corrected_mapping = dict()
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for k, v in mapping.items():
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if isinstance(k, tuple):
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corrected_mapping[k] = v
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elif isinstance(k, list):
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corrected_mapping[tuple(k)] = v
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else: # Assume it's atomic
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corrected_mapping[(k,)] = v
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self.mapping = corrected_mapping
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def __str__(self):
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str_dict = dict()
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for k, v in self.mapping.items():
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inputstr = "(" + ", ".join(str(ki) for ki in k) + ")"
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str_dict[inputstr] = str(v)
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return str(str_dict)
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def __call__(self, *args):
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return self.mapping[args]
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# def __eq__(self, other):
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# return isinstance(other, ModelFunction) and self.name == other.name and self.arity == other.arity
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class Model:
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def __init__(
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self,
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carrier_set: Set[ModelValue],
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logical_operations: Set[ModelFunction],
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designated_values: Set[ModelValue]
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):
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assert designated_values <= carrier_set
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self.carrier_set = carrier_set
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self.logical_operations = logical_operations
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self.designated_values = designated_values
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def __str__(self):
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result = f"""Carrier Set: {set_to_str(self.carrier_set)}
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Designated Values: {set_to_str(self.designated_values)}
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"""
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for function in self.logical_operations:
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result += f"{str(function)}\n"
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return result
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def evaluate_term(t: Term, f: Dict[PropositionalVariable, ModelValue], interpretation: Dict[Operation, ModelFunction]):
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if isinstance(t, PropositionalVariable):
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return f[t]
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model_function = interpretation[t.operation]
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model_arguments = []
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for logic_arg in t.arguments:
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model_arg = evaluate_term(logic_arg, f, interpretation)
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model_arguments.append(model_arg)
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return model_function(*model_arguments)
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def all_model_valuations(
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pvars: Set[PropositionalVariable],
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mvalues: Set[ModelValue]):
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pvars = list(pvars)
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possible_valuations = [mvalues for _ in pvars]
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all_possible_values = product(*possible_valuations)
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for valuation in all_possible_values:
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mapping = dict()
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assert len(pvars) == len(valuation)
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for pvar, value in zip(pvars, valuation):
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mapping[pvar] = value
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yield mapping
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def satisfiable(logic: Logic, model: Model, interpretation: Dict[Operation, ModelFunction]):
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pvars = get_propostional_variables(logic.rules)
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mappings = all_model_valuations(pvars, model.carrier_set)
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for mapping in mappings:
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for rule in logic.rules:
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premise_met = True
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for premise in rule.premises:
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t = evaluate_term(premise, mapping, interpretation)
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if t not in model.designated_values:
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premise_met = False
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break
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if not premise_met:
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continue
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t = evaluate_term(rule.conclusion, mapping, interpretation)
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if t not in model.designated_values:
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return False
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return True
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