"""Module for querying SymPy objects about assumptions.""" from sympy.assumptions.assume import (global_assumptions, Predicate, AppliedPredicate) from sympy.assumptions.cnf import CNF, EncodedCNF, Literal from sympy.core import sympify from sympy.core.kind import BooleanKind from sympy.core.relational import Eq, Ne, Gt, Lt, Ge, Le from sympy.logic.inference import satisfiable from sympy.utilities.decorator import memoize_property from sympy.utilities.exceptions import (sympy_deprecation_warning, SymPyDeprecationWarning, ignore_warnings) # Memoization is necessary for the properties of AssumptionKeys to # ensure that only one object of Predicate objects are created. # This is because assumption handlers are registered on those objects. class AssumptionKeys: """ This class contains all the supported keys by ``ask``. It should be accessed via the instance ``sympy.Q``. """ # DO NOT add methods or properties other than predicate keys. # SAT solver checks the properties of Q and use them to compute the # fact system. Non-predicate attributes will break this. @memoize_property def hermitian(self): from .handlers.sets import HermitianPredicate return HermitianPredicate() @memoize_property def antihermitian(self): from .handlers.sets import AntihermitianPredicate return AntihermitianPredicate() @memoize_property def real(self): from .handlers.sets import RealPredicate return RealPredicate() @memoize_property def extended_real(self): from .handlers.sets import ExtendedRealPredicate return ExtendedRealPredicate() @memoize_property def imaginary(self): from .handlers.sets import ImaginaryPredicate return ImaginaryPredicate() @memoize_property def complex(self): from .handlers.sets import ComplexPredicate return ComplexPredicate() @memoize_property def algebraic(self): from .handlers.sets import AlgebraicPredicate return AlgebraicPredicate() @memoize_property def transcendental(self): from .predicates.sets import TranscendentalPredicate return TranscendentalPredicate() @memoize_property def integer(self): from .handlers.sets import IntegerPredicate return IntegerPredicate() @memoize_property def noninteger(self): from .predicates.sets import NonIntegerPredicate return NonIntegerPredicate() @memoize_property def rational(self): from .handlers.sets import RationalPredicate return RationalPredicate() @memoize_property def irrational(self): from .handlers.sets import IrrationalPredicate return IrrationalPredicate() @memoize_property def finite(self): from .handlers.calculus import FinitePredicate return FinitePredicate() @memoize_property def infinite(self): from .handlers.calculus import InfinitePredicate return InfinitePredicate() @memoize_property def positive_infinite(self): from .handlers.calculus import PositiveInfinitePredicate return PositiveInfinitePredicate() @memoize_property def negative_infinite(self): from .handlers.calculus import NegativeInfinitePredicate return NegativeInfinitePredicate() @memoize_property def positive(self): from .handlers.order import PositivePredicate return PositivePredicate() @memoize_property def negative(self): from .handlers.order import NegativePredicate return NegativePredicate() @memoize_property def zero(self): from .handlers.order import ZeroPredicate return ZeroPredicate() @memoize_property def extended_positive(self): from .handlers.order import ExtendedPositivePredicate return ExtendedPositivePredicate() @memoize_property def extended_negative(self): from .handlers.order import ExtendedNegativePredicate return ExtendedNegativePredicate() @memoize_property def nonzero(self): from .handlers.order import NonZeroPredicate return NonZeroPredicate() @memoize_property def nonpositive(self): from .handlers.order import NonPositivePredicate return NonPositivePredicate() @memoize_property def nonnegative(self): from .handlers.order import NonNegativePredicate return NonNegativePredicate() @memoize_property def extended_nonzero(self): from .handlers.order import ExtendedNonZeroPredicate return ExtendedNonZeroPredicate() @memoize_property def extended_nonpositive(self): from .handlers.order import ExtendedNonPositivePredicate return ExtendedNonPositivePredicate() @memoize_property def extended_nonnegative(self): from .handlers.order import ExtendedNonNegativePredicate return ExtendedNonNegativePredicate() @memoize_property def even(self): from .handlers.ntheory import EvenPredicate return EvenPredicate() @memoize_property def odd(self): from .handlers.ntheory import OddPredicate return OddPredicate() @memoize_property def prime(self): from .handlers.ntheory import PrimePredicate return PrimePredicate() @memoize_property def composite(self): from .handlers.ntheory import CompositePredicate return CompositePredicate() @memoize_property def commutative(self): from .handlers.common import CommutativePredicate return CommutativePredicate() @memoize_property def is_true(self): from .handlers.common import IsTruePredicate return IsTruePredicate() @memoize_property def symmetric(self): from .handlers.matrices import SymmetricPredicate return SymmetricPredicate() @memoize_property def invertible(self): from .handlers.matrices import InvertiblePredicate return InvertiblePredicate() @memoize_property def orthogonal(self): from .handlers.matrices import OrthogonalPredicate return OrthogonalPredicate() @memoize_property def unitary(self): from .handlers.matrices import UnitaryPredicate return UnitaryPredicate() @memoize_property def positive_definite(self): from .handlers.matrices import PositiveDefinitePredicate return PositiveDefinitePredicate() @memoize_property def upper_triangular(self): from .handlers.matrices import UpperTriangularPredicate return UpperTriangularPredicate() @memoize_property def lower_triangular(self): from .handlers.matrices import LowerTriangularPredicate return LowerTriangularPredicate() @memoize_property def diagonal(self): from .handlers.matrices import DiagonalPredicate return DiagonalPredicate() @memoize_property def fullrank(self): from .handlers.matrices import FullRankPredicate return FullRankPredicate() @memoize_property def square(self): from .handlers.matrices import SquarePredicate return SquarePredicate() @memoize_property def integer_elements(self): from .handlers.matrices import IntegerElementsPredicate return IntegerElementsPredicate() @memoize_property def real_elements(self): from .handlers.matrices import RealElementsPredicate return RealElementsPredicate() @memoize_property def complex_elements(self): from .handlers.matrices import ComplexElementsPredicate return ComplexElementsPredicate() @memoize_property def singular(self): from .predicates.matrices import SingularPredicate return SingularPredicate() @memoize_property def normal(self): from .predicates.matrices import NormalPredicate return NormalPredicate() @memoize_property def triangular(self): from .predicates.matrices import TriangularPredicate return TriangularPredicate() @memoize_property def unit_triangular(self): from .predicates.matrices import UnitTriangularPredicate return UnitTriangularPredicate() @memoize_property def eq(self): from .relation.equality import EqualityPredicate return EqualityPredicate() @memoize_property def ne(self): from .relation.equality import UnequalityPredicate return UnequalityPredicate() @memoize_property def gt(self): from .relation.equality import StrictGreaterThanPredicate return StrictGreaterThanPredicate() @memoize_property def ge(self): from .relation.equality import GreaterThanPredicate return GreaterThanPredicate() @memoize_property def lt(self): from .relation.equality import StrictLessThanPredicate return StrictLessThanPredicate() @memoize_property def le(self): from .relation.equality import LessThanPredicate return LessThanPredicate() Q = AssumptionKeys() def _extract_all_facts(assump, exprs): """ Extract all relevant assumptions from *assump* with respect to given *exprs*. Parameters ========== assump : sympy.assumptions.cnf.CNF exprs : tuple of expressions Returns ======= sympy.assumptions.cnf.CNF Examples ======== >>> from sympy import Q >>> from sympy.assumptions.cnf import CNF >>> from sympy.assumptions.ask import _extract_all_facts >>> from sympy.abc import x, y >>> assump = CNF.from_prop(Q.positive(x) & Q.integer(y)) >>> exprs = (x,) >>> cnf = _extract_all_facts(assump, exprs) >>> cnf.clauses {frozenset({Literal(Q.positive, False)})} """ facts = set() for clause in assump.clauses: args = [] for literal in clause: if isinstance(literal.lit, AppliedPredicate) and len(literal.lit.arguments) == 1: if literal.lit.arg in exprs: # Add literal if it has matching in it args.append(Literal(literal.lit.function, literal.is_Not)) else: # If any of the literals doesn't have matching expr don't add the whole clause. break else: # If any of the literals aren't unary predicate don't add the whole clause. break else: if args: facts.add(frozenset(args)) return CNF(facts) def ask(proposition, assumptions=True, context=global_assumptions): """ Function to evaluate the proposition with assumptions. Explanation =========== This function evaluates the proposition to ``True`` or ``False`` if the truth value can be determined. If not, it returns ``None``. It should be discerned from :func:`~.refine()` which, when applied to a proposition, simplifies the argument to symbolic ``Boolean`` instead of Python built-in ``True``, ``False`` or ``None``. **Syntax** * ask(proposition) Evaluate the *proposition* in global assumption context. * ask(proposition, assumptions) Evaluate the *proposition* with respect to *assumptions* in global assumption context. Parameters ========== proposition : Boolean Proposition which will be evaluated to boolean value. If this is not ``AppliedPredicate``, it will be wrapped by ``Q.is_true``. assumptions : Boolean, optional Local assumptions to evaluate the *proposition*. context : AssumptionsContext, optional Default assumptions to evaluate the *proposition*. By default, this is ``sympy.assumptions.global_assumptions`` variable. Returns ======= ``True``, ``False``, or ``None`` Raises ====== TypeError : *proposition* or *assumptions* is not valid logical expression. ValueError : assumptions are inconsistent. Examples ======== >>> from sympy import ask, Q, pi >>> from sympy.abc import x, y >>> ask(Q.rational(pi)) False >>> ask(Q.even(x*y), Q.even(x) & Q.integer(y)) True >>> ask(Q.prime(4*x), Q.integer(x)) False If the truth value cannot be determined, ``None`` will be returned. >>> print(ask(Q.odd(3*x))) # cannot determine unless we know x None ``ValueError`` is raised if assumptions are inconsistent. >>> ask(Q.integer(x), Q.even(x) & Q.odd(x)) Traceback (most recent call last): ... ValueError: inconsistent assumptions Q.even(x) & Q.odd(x) Notes ===== Relations in assumptions are not implemented (yet), so the following will not give a meaningful result. >>> ask(Q.positive(x), x > 0) It is however a work in progress. See Also ======== sympy.assumptions.refine.refine : Simplification using assumptions. Proposition is not reduced to ``None`` if the truth value cannot be determined. """ from sympy.assumptions.satask import satask from sympy.assumptions.lra_satask import lra_satask from sympy.logic.algorithms.lra_theory import UnhandledInput proposition = sympify(proposition) assumptions = sympify(assumptions) if isinstance(proposition, Predicate) or proposition.kind is not BooleanKind: raise TypeError("proposition must be a valid logical expression") if isinstance(assumptions, Predicate) or assumptions.kind is not BooleanKind: raise TypeError("assumptions must be a valid logical expression") binrelpreds = {Eq: Q.eq, Ne: Q.ne, Gt: Q.gt, Lt: Q.lt, Ge: Q.ge, Le: Q.le} if isinstance(proposition, AppliedPredicate): key, args = proposition.function, proposition.arguments elif proposition.func in binrelpreds: key, args = binrelpreds[type(proposition)], proposition.args else: key, args = Q.is_true, (proposition,) # convert local and global assumptions to CNF assump_cnf = CNF.from_prop(assumptions) assump_cnf.extend(context) # extract the relevant facts from assumptions with respect to args local_facts = _extract_all_facts(assump_cnf, args) # convert default facts and assumed facts to encoded CNF known_facts_cnf = get_all_known_facts() enc_cnf = EncodedCNF() enc_cnf.from_cnf(CNF(known_facts_cnf)) enc_cnf.add_from_cnf(local_facts) # check the satisfiability of given assumptions if local_facts.clauses and satisfiable(enc_cnf) is False: raise ValueError("inconsistent assumptions %s" % assumptions) # quick computation for single fact res = _ask_single_fact(key, local_facts) if res is not None: return res # direct resolution method, no logic res = key(*args)._eval_ask(assumptions) if res is not None: return bool(res) # using satask (still costly) res = satask(proposition, assumptions=assumptions, context=context) if res is not None: return res try: res = lra_satask(proposition, assumptions=assumptions, context=context) except UnhandledInput: return None return res def _ask_single_fact(key, local_facts): """ Compute the truth value of single predicate using assumptions. Parameters ========== key : sympy.assumptions.assume.Predicate Proposition predicate. local_facts : sympy.assumptions.cnf.CNF Local assumption in CNF form. Returns ======= ``True``, ``False`` or ``None`` Examples ======== >>> from sympy import Q >>> from sympy.assumptions.cnf import CNF >>> from sympy.assumptions.ask import _ask_single_fact If prerequisite of proposition is rejected by the assumption, return ``False``. >>> key, assump = Q.zero, ~Q.zero >>> local_facts = CNF.from_prop(assump) >>> _ask_single_fact(key, local_facts) False >>> key, assump = Q.zero, ~Q.even >>> local_facts = CNF.from_prop(assump) >>> _ask_single_fact(key, local_facts) False If assumption implies the proposition, return ``True``. >>> key, assump = Q.even, Q.zero >>> local_facts = CNF.from_prop(assump) >>> _ask_single_fact(key, local_facts) True If proposition rejects the assumption, return ``False``. >>> key, assump = Q.even, Q.odd >>> local_facts = CNF.from_prop(assump) >>> _ask_single_fact(key, local_facts) False """ if local_facts.clauses: known_facts_dict = get_known_facts_dict() if len(local_facts.clauses) == 1: cl, = local_facts.clauses if len(cl) == 1: f, = cl prop_facts = known_facts_dict.get(key, None) prop_req = prop_facts[0] if prop_facts is not None else set() if f.is_Not and f.arg in prop_req: # the prerequisite of proposition is rejected return False for clause in local_facts.clauses: if len(clause) == 1: f, = clause prop_facts = known_facts_dict.get(f.arg, None) if not f.is_Not else None if prop_facts is None: continue prop_req, prop_rej = prop_facts if key in prop_req: # assumption implies the proposition return True elif key in prop_rej: # proposition rejects the assumption return False return None def register_handler(key, handler): """ Register a handler in the ask system. key must be a string and handler a class inheriting from AskHandler. .. deprecated:: 1.8. Use multipledispatch handler instead. See :obj:`~.Predicate`. """ sympy_deprecation_warning( """ The AskHandler system is deprecated. The register_handler() function should be replaced with the multipledispatch handler of Predicate. """, deprecated_since_version="1.8", active_deprecations_target='deprecated-askhandler', ) if isinstance(key, Predicate): key = key.name.name Qkey = getattr(Q, key, None) if Qkey is not None: Qkey.add_handler(handler) else: setattr(Q, key, Predicate(key, handlers=[handler])) def remove_handler(key, handler): """ Removes a handler from the ask system. .. deprecated:: 1.8. Use multipledispatch handler instead. See :obj:`~.Predicate`. """ sympy_deprecation_warning( """ The AskHandler system is deprecated. The remove_handler() function should be replaced with the multipledispatch handler of Predicate. """, deprecated_since_version="1.8", active_deprecations_target='deprecated-askhandler', ) if isinstance(key, Predicate): key = key.name.name # Don't show the same warning again recursively with ignore_warnings(SymPyDeprecationWarning): getattr(Q, key).remove_handler(handler) from sympy.assumptions.ask_generated import (get_all_known_facts, get_known_facts_dict)