""" File which generates all the models """ from common import set_to_str from logic import Logic, Operation, Rule, get_operations_from_term, PropositionalVariable from model import ModelValue, Model, satisfiable, ModelFunction from itertools import combinations, chain, product from typing import Set def possible_designations(iterable): """Powerset without the empty and complete set""" s = list(iterable) return chain.from_iterable(combinations(s, r) for r in range(1, len(s))) def possible_functions(operation, carrier_set): arity = operation.arity inputs = list(product(*(carrier_set for _ in range(arity)))) possible_outputs = product(*(carrier_set for _ in range(len(inputs)))) for outputs in possible_outputs: assert len(inputs) == len(outputs) new_function = dict() for input, output in zip(inputs, outputs): new_function[input] = output yield ModelFunction(new_function, operation.symbol) def only_rules_with(rules: Set[Rule], operation: Operation) -> Set[Rule]: result_rules = [] for rule in rules: is_valid = True for t in (rule.premises | {rule.conclusion,}): t_operations = get_operations_from_term(t) if len(t_operations) > 1: is_valid = False break if len(t_operations) == 0: continue t_operation = next(iter(t_operations)) if t_operation != operation: is_valid = False break if is_valid: result_rules.append(rule) return result_rules def possible_interpretations( logic: Logic, carrier_set: Set[ModelValue], designated_values: Set[ModelValue]): operations = [] model_functions = [] for operation in logic.operations: operations.append(operation) candidate_functions = list(possible_functions(operation, carrier_set)) passed_functions = [] """ Only consider functions that at least pass in the rules with the operation by itself. """ restricted_rules = only_rules_with(logic.rules, operation) if len(restricted_rules) > 0: small_logic = Logic({operation,}, restricted_rules) for f in candidate_functions: small_model = Model(carrier_set, {f,}, designated_values) interp = {operation: f} if satisfiable(small_logic, small_model, interp): passed_functions.append(f) else: passed_functions = candidate_functions if len(passed_functions) == 0: raise Exception("No interpretation satisfies the axioms for the operation " + str(operation)) else: print( f"Operation {operation.symbol} has {len(passed_functions)} candidate functions" ) model_functions.append(passed_functions) functions_choice = product(*model_functions) for functions in functions_choice: assert len(operations) == len(functions) interpretation = dict() for operation, function in zip(operations, functions): interpretation[operation] = function yield interpretation def generate_model(logic: Logic, number_elements: int, num_solutions: int = -1, print_model=False): carrier_set = { ModelValue("a" + str(i)) for i in range(number_elements) } possible_designated_values = possible_designations(carrier_set) satisfied_models = [] for designated_values in possible_designated_values: designated_values = set(designated_values) print("Considering models for designated values", set_to_str(designated_values)) possible_interps = possible_interpretations(logic, carrier_set, designated_values) for interpretation in possible_interps: is_valid = True model = Model(carrier_set, set(interpretation.values()), designated_values) # Iteratively test possible interpretations # by adding one axiom at a time for rule in logic.rules: small_logic = Logic(logic.operations, {rule,}) if not satisfiable(small_logic, model, interpretation): is_valid = False break if is_valid: satisfied_models.append(model) if print_model: print(model, flush=True) if num_solutions >= 0 and len(satisfied_models) >= num_solutions: return satisfied_models return satisfied_models