""" Check to see if the model has the variable sharing property. """ from itertools import product, chain, combinations from typing import List, Optional, Set, Tuple from common import set_to_str from model import ( Model, model_closure, ModelFunction, ModelValue ) class VSP_Result: def __init__( self, has_vsp: bool, model_name: Optional[str] = None, subalgebra1: Optional[Set[ModelValue]] = None, subalgebra2: Optional[Set[ModelValue]] = None): self.has_vsp = has_vsp self.model_name = model_name self.subalgebra1 = subalgebra1 self.subalgebra2 = subalgebra2 def __str__(self): if not self.has_vsp: return f"Model {self.model_name} does not have the variable sharing property." return f"""Model {self.model_name} has the variable sharing property. Subalgebra 1: {set_to_str(self.subalgebra1)} Subalgebra 2: {set_to_str(self.subalgebra2)} """ def has_vsp(model: Model, impfunction: ModelFunction, negation_defined: bool) -> VSP_Result: """ Checks whether a model has the variable sharing property. """ # NOTE: No models with only one designated # value satisfies VSP if len(model.designated_values) == 1: return VSP_Result(False, model.name) assert model.ordering is not None, "Expected ordering table in model" top = model.ordering.top() bottom = model.ordering.bottom() # Compute I the set of tuples (x, y) where # x -> y does not take a designiated value I: List[Tuple[ModelValue, ModelValue]] = [] for (x, y) in product(model.designated_values, model.designated_values): if impfunction(x, y) not in model.designated_values: I.append((x, y)) # Find the subalgebras which falsify implication for xys in I: xi = xys[0] # Discard ({⊥} ∪ A', B) subalgebras if bottom is not None and xi == bottom: continue # Discard ({⊤} ∪ A', B) subalgebras when negation is defined if top is not None and negation_defined and xi == top: continue yi = xys[1] # Discard (A, {⊤} ∪ B') subalgebras if top is not None and yi == top: continue # Discard (A, {⊥} ∪ B') subalgebras when negation is defined if bottom is not None and negation_defined and yi == bottom: continue # Discard ({a} ∪ A', {b} ∪ B') subalgebras when a <= b if model.ordering.is_lt(xi, yi): continue # Discard ({a} ∪ A', {b} ∪ B') subalgebras when b <= a and negation is defined if negation_defined and model.ordering.is_lt(yi, xi): continue # Compute the left closure of the set containing xi under all the operations carrier_set_left: Set[ModelValue] = model_closure({xi,}, model.logical_operations, bottom) # Discard ({⊥} ∪ A', B) subalgebras if bottom is not None and bottom in carrier_set_left: continue # Discard ({⊤} ∪ A', B) subalgebras when negation is defined if top is not None and negation_defined and top in carrier_set_left: continue # Compute the closure of all operations # with just the ys carrier_set_right: Set[ModelValue] = model_closure({yi,}, model.logical_operations, top) # Discard (A, {⊤} ∪ B') subalgebras if top is not None and top in carrier_set_right: continue # Discard (A, {⊥} ∪ B') subalgebras when negation is defined if bottom is not None and negation_defined and bottom in carrier_set_right: continue # Discard subalgebras that intersect if not carrier_set_left.isdisjoint(carrier_set_right): continue # Check whether for all pairs in the subalgebra, # that implication is falsified. falsified = True for (x2, y2) in product(carrier_set_left, carrier_set_right): if impfunction(x2, y2) in model.designated_values: falsified = False break if falsified: return VSP_Result(True, model.name, carrier_set_left, carrier_set_right) return VSP_Result(False, model.name) class SVSP_Result: def __init__( self, has_svsp: bool, model_name: Optional[str] = None, subalgebra1: Optional[Set[ModelValue]] = None, subalgebra2: Optional[Set[ModelValue]] = None, U: Optional[Set[ModelValue]] = None, L: Optional[Set[ModelValue]] = None): self.has_svsp = has_svsp self.model_name = model_name self.subalgebra1 = subalgebra1 self.subalgebra2 = subalgebra2 self.U = U self.L = L def __str__(self): if not self.has_svsp: return f"Model {self.model_name} does not have the signed variable sharing property." return f"""Model {self.model_name} has the signed variable sharing property. Subalgebra 1: {set_to_str(self.subalgebra1)} Subalgebra 2: {set_to_str(self.subalgebra2)} U: {set_to_str(self.U)} L: {set_to_str(self.L)} """ def powerset_minus_empty(s): return chain.from_iterable(combinations(s, r) for r in range(1, len(s) + 1)) def find_k1_k2(model, impfunction: ModelFunction, negation_defined: bool) -> List[Tuple[Set[ModelValue], Set[ModelValue]]]: """ Returns a list of possible subalgebra pairs (K1, K2) """ assert model.ordering is not None, "Expected ordering table in model" result = [] top = model.ordering.top() bottom = model.ordering.bottom() # Compute I the set of tuples (x, y) where # x -> y does not take a designiated value I: List[Tuple[ModelValue, ModelValue]] = [] for (x, y) in product(model.designated_values, model.designated_values): if impfunction(x, y) not in model.designated_values: I.append((x, y)) # Find the subalgebras which falsify implication for xys in I: xi = xys[0] # Discard ({⊥} ∪ A', B) subalgebras if bottom is not None and xi == bottom: continue # Discard ({⊤} ∪ A', B) subalgebras when negation is defined if top is not None and negation_defined and xi == top: continue yi = xys[1] # Discard (A, {⊤} ∪ B') subalgebras if top is not None and yi == top: continue # Discard (A, {⊥} ∪ B') subalgebras when negation is defined if bottom is not None and negation_defined and yi == bottom: continue # Discard ({a} ∪ A', {b} ∪ B') subalgebras when a <= b if model.ordering.is_lt(xi, yi): continue # Discard ({a} ∪ A', {b} ∪ B') subalgebras when b <= a and negation is defined if negation_defined and model.ordering.is_lt(yi, xi): continue # Compute the left closure of the set containing xi under all the operations carrier_set_left: Set[ModelValue] = model_closure({xi,}, model.logical_operations, bottom) # Discard ({⊥} ∪ A', B) subalgebras if bottom is not None and bottom in carrier_set_left: continue # Discard ({⊤} ∪ A', B) subalgebras when negation is defined if top is not None and negation_defined and top in carrier_set_left: continue # Compute the closure of all operations # with just the ys carrier_set_right: Set[ModelValue] = model_closure({yi,}, model.logical_operations, top) # Discard (A, {⊤} ∪ B') subalgebras if top is not None and top in carrier_set_right: continue # Discard (A, {⊥} ∪ B') subalgebras when negation is defined if bottom is not None and negation_defined and bottom in carrier_set_right: continue # Discard subalgebras that intersect if not carrier_set_left.isdisjoint(carrier_set_right): continue # Check whether for all pairs in the subalgebra, # that implication is falsified. falsified = True for (x2, y2) in product(carrier_set_left, carrier_set_right): if impfunction(x2, y2) in model.designated_values: falsified = False break if falsified: result.append((carrier_set_left, carrier_set_right)) return result def find_candidate_u_l(model: Model, impfn: ModelFunction, negfn: Optional[ModelFunction]) -> List[Tuple[Set[ModelValue], Set[ModelValue]]]: result: List[Tuple[Set[ModelValue], Set[ModelValue]]] = [] F = model.carrier_set - model.designated_values Us = powerset_minus_empty(model.carrier_set) Ls = powerset_minus_empty(model.carrier_set) for (U, L) in product(Us, Ls): unsat = False U = set(U) L = set(L) LFi = F.intersection(L) # Required property: ∀x ∈ U, y ∈ L(x → y ∈ L ∩ F) for (x, y) in product(U, L): if impfn(x, y) not in LFi: unsat = True break if unsat: continue # Required Property: ∀x ∈ L, y ∈ U(x → y ∈ U) for (x, y) in product(L, U): if impfn(x, y) not in U: unsat = True break if unsat: continue if negfn is not None: for x in L: # Required Property: ∀x(x ∈ L ⇒ ¬x ∈ U) if negfn(x) not in U: unsat = True break if unsat: continue for x in U: # Required Property: ∀x(x ∈ U ⇒ ¬x ∈ L) if negfn(x) not in L: unsat = True break if unsat: continue # Passed all required properties result.append((U, L)) return result def has_svsp(model: Model, impfn: ModelFunction, conjfn: Optional[ModelFunction], disjfn: Optional[ModelFunction], negfn: Optional[ModelFunction]) -> SVSP_Result: """ Checks whether a model has the signed variable sharing property. """ # NOTE: No models with only one designated # value satisfies SVSP if len(model.designated_values) == 1: return SVSP_Result(False, model.name) F = model.carrier_set - model.designated_values starops = [conjfn, disjfn] K1K2s = find_k1_k2(model, impfn, negfn is not None) ULs = find_candidate_u_l(model, impfn, negfn) candidates = ((k1, k2, u, l) for (k1, k2), (u, l) in product(K1K2s, ULs)) for K1, K2, U, L in candidates: unsat = False K1Uu = K1 | U K1Lu = K1 | L K1LuFi = K1Lu.intersection(F) # (K1 ∪ L) ∩ F K2Uu = K2 | U K2Lu = K2 | L K2LuFi = K2Lu.intersection(F) # (K2 ∪ L) ∩ F # (6) for x, y in product(K1, U): # b) x → y ∈ K1 ∪ U if impfn(x, y) not in K1Uu: unsat = True break # c) y → x ∈ K1 ∪ L if impfn(y, x) not in K1Lu: unsat = True break # a) x ∗ y, y ∗ x, y ∗ z ∈ K1 ∪ U for z in U: for op in starops: if op is not None: if op(x, y) not in K1Uu: unsat = True break if op(y, x) not in K1Uu: unsat = True break if op(y, z) not in K1Uu: unsat = True break if unsat: break if unsat: # Verification for these set of matrices failed break if unsat: # Move onto the next candidates K1, K2, U, L continue # (7) for x, y in product(K1, L): # b) x → y ∈ (K1 ∪ L) ∩ F if impfn(x, y) not in K1LuFi: unsat = True break # c) y → x ∈ K1 ∪ U if impfn(y, x) not in K1Uu: unsat = True break # a) x ∗ y, y ∗ x, y ∗ z ∈ K1 ∪ L for z in L: for op in starops: if op is not None: if op(x, y) not in K1Lu: unsat = True break if op(y, x) not in K1Lu: unsat = True break if op(y, z) not in K1Lu: unsat = True break if unsat: break if unsat: break if unsat: continue # (8) for x, y in product(K2, U): # b) x → y ∈ K2 ∪ U if impfn(x, y) not in K2Uu: unsat = True break # c) y → x ∈ (K2 ∪ L) ∩ F if impfn(y, x) not in K2LuFi: unsat = True break # a) x ∗ y, y ∗ x, y ∗ z ∈ K2 ∪ U for z in U: for op in starops: if op is not None: if op(x, y) not in K2Uu: unsat = True break if op(y, x) not in K2Uu: unsat = True break if op(y, z) not in K2Uu: unsat = True break if unsat: break if unsat: break if unsat: continue # (9) for x, y in product(K2, L): # b) x → y ∈ K2 ∪ L if impfn(x, y) not in K2Lu: unsat = True break # c) y → x ∈ K2 ∪ U if impfn(y, x) not in K2Uu: unsat = True break # a) x ∗ y, y ∗ x, y ∗ z ∈ K2 ∪ L for z in L: for op in starops: if op is not None: if op(x, y) not in K2Lu: unsat = True break if op(y, x) not in K2Lu: unsat = True break if op(y, z) not in K2Lu: unsat = True break if unsat: break if unsat: break if not unsat: return SVSP_Result(True, model.name, K1, K2, U, L) return SVSP_Result(False, model.name)