ai-content-maker/.venv/Lib/site-packages/sympy/assumptions/ask.py

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"""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 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 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
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)
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)