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env-llmeval/lib/python3.10/site-packages/sympy/core/__init__.py

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+"""Core module. Provides the basic operations needed in sympy.
+"""
+
+from .sympify import sympify, SympifyError
+from .cache import cacheit
+from .assumptions import assumptions, check_assumptions, failing_assumptions, common_assumptions
+from .basic import Basic, Atom
+from .singleton import S
+from .expr import Expr, AtomicExpr, UnevaluatedExpr
+from .symbol import Symbol, Wild, Dummy, symbols, var
+from .numbers import Number, Float, Rational, Integer, NumberSymbol, \
+    RealNumber, igcd, ilcm, seterr, E, I, nan, oo, pi, zoo, \
+    AlgebraicNumber, comp, mod_inverse
+from .power import Pow, integer_nthroot, integer_log
+from .mul import Mul, prod
+from .add import Add
+from .mod import Mod
+from .relational import ( Rel, Eq, Ne, Lt, Le, Gt, Ge,
+    Equality, GreaterThan, LessThan, Unequality, StrictGreaterThan,
+    StrictLessThan )
+from .multidimensional import vectorize
+from .function import Lambda, WildFunction, Derivative, diff, FunctionClass, \
+    Function, Subs, expand, PoleError, count_ops, \
+    expand_mul, expand_log, expand_func, \
+    expand_trig, expand_complex, expand_multinomial, nfloat, \
+    expand_power_base, expand_power_exp, arity
+from .evalf import PrecisionExhausted, N
+from .containers import Tuple, Dict
+from .exprtools import gcd_terms, factor_terms, factor_nc
+from .parameters import evaluate
+from .kind import UndefinedKind, NumberKind, BooleanKind
+from .traversal import preorder_traversal, bottom_up, use, postorder_traversal
+from .sorting import default_sort_key, ordered
+
+# expose singletons
+Catalan = S.Catalan
+EulerGamma = S.EulerGamma
+GoldenRatio = S.GoldenRatio
+TribonacciConstant = S.TribonacciConstant
+
+__all__ = [
+    'sympify', 'SympifyError',
+
+    'cacheit',
+
+    'assumptions', 'check_assumptions', 'failing_assumptions',
+    'common_assumptions',
+
+    'Basic', 'Atom',
+
+    'S',
+
+    'Expr', 'AtomicExpr', 'UnevaluatedExpr',
+
+    'Symbol', 'Wild', 'Dummy', 'symbols', 'var',
+
+    'Number', 'Float', 'Rational', 'Integer', 'NumberSymbol', 'RealNumber',
+    'igcd', 'ilcm', 'seterr', 'E', 'I', 'nan', 'oo', 'pi', 'zoo',
+    'AlgebraicNumber', 'comp', 'mod_inverse',
+
+    'Pow', 'integer_nthroot', 'integer_log',
+
+    'Mul', 'prod',
+
+    'Add',
+
+    'Mod',
+
+    'Rel', 'Eq', 'Ne', 'Lt', 'Le', 'Gt', 'Ge', 'Equality', 'GreaterThan',
+    'LessThan', 'Unequality', 'StrictGreaterThan', 'StrictLessThan',
+
+    'vectorize',
+
+    'Lambda', 'WildFunction', 'Derivative', 'diff', 'FunctionClass',
+    'Function', 'Subs', 'expand', 'PoleError', 'count_ops', 'expand_mul',
+    'expand_log', 'expand_func', 'expand_trig', 'expand_complex',
+    'expand_multinomial', 'nfloat', 'expand_power_base', 'expand_power_exp',
+    'arity',
+
+    'PrecisionExhausted', 'N',
+
+    'evalf', # The module?
+
+    'Tuple', 'Dict',
+
+    'gcd_terms', 'factor_terms', 'factor_nc',
+
+    'evaluate',
+
+    'Catalan',
+    'EulerGamma',
+    'GoldenRatio',
+    'TribonacciConstant',
+
+    'UndefinedKind', 'NumberKind', 'BooleanKind',
+
+    'preorder_traversal', 'bottom_up', 'use', 'postorder_traversal',
+
+    'default_sort_key', 'ordered',
+]

env-llmeval/lib/python3.10/site-packages/sympy/core/assumptions.py

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+"""
+This module contains the machinery handling assumptions.
+Do also consider the guide :ref:`assumptions-guide`.
+
+All symbolic objects have assumption attributes that can be accessed via
+``.is_<assumption name>`` attribute.
+
+Assumptions determine certain properties of symbolic objects and can
+have 3 possible values: ``True``, ``False``, ``None``.  ``True`` is returned if the
+object has the property and ``False`` is returned if it does not or cannot
+(i.e. does not make sense):
+
+    >>> from sympy import I
+    >>> I.is_algebraic
+    True
+    >>> I.is_real
+    False
+    >>> I.is_prime
+    False
+
+When the property cannot be determined (or when a method is not
+implemented) ``None`` will be returned. For example,  a generic symbol, ``x``,
+may or may not be positive so a value of ``None`` is returned for ``x.is_positive``.
+
+By default, all symbolic values are in the largest set in the given context
+without specifying the property. For example, a symbol that has a property
+being integer, is also real, complex, etc.
+
+Here follows a list of possible assumption names:
+
+.. glossary::
+
+    commutative
+        object commutes with any other object with
+        respect to multiplication operation. See [12]_.
+
+    complex
+        object can have only values from the set
+        of complex numbers. See [13]_.
+
+    imaginary
+        object value is a number that can be written as a real
+        number multiplied by the imaginary unit ``I``.  See
+        [3]_.  Please note that ``0`` is not considered to be an
+        imaginary number, see
+        `issue #7649 <https://github.com/sympy/sympy/issues/7649>`_.
+
+    real
+        object can have only values from the set
+        of real numbers.
+
+    extended_real
+        object can have only values from the set
+        of real numbers, ``oo`` and ``-oo``.
+
+    integer
+        object can have only values from the set
+        of integers.
+
+    odd
+    even
+        object can have only values from the set of
+        odd (even) integers [2]_.
+
+    prime
+        object is a natural number greater than 1 that has
+        no positive divisors other than 1 and itself.  See [6]_.
+
+    composite
+        object is a positive integer that has at least one positive
+        divisor other than 1 or the number itself.  See [4]_.
+
+    zero
+        object has the value of 0.
+
+    nonzero
+        object is a real number that is not zero.
+
+    rational
+        object can have only values from the set
+        of rationals.
+
+    algebraic
+        object can have only values from the set
+        of algebraic numbers [11]_.
+
+    transcendental
+        object can have only values from the set
+        of transcendental numbers [10]_.
+
+    irrational
+        object value cannot be represented exactly by :class:`~.Rational`, see [5]_.
+
+    finite
+    infinite
+        object absolute value is bounded (arbitrarily large).
+        See [7]_, [8]_, [9]_.
+
+    negative
+    nonnegative
+        object can have only negative (nonnegative)
+        values [1]_.
+
+    positive
+    nonpositive
+        object can have only positive (nonpositive) values.
+
+    extended_negative
+    extended_nonnegative
+    extended_positive
+    extended_nonpositive
+    extended_nonzero
+        as without the extended part, but also including infinity with
+        corresponding sign, e.g., extended_positive includes ``oo``
+
+    hermitian
+    antihermitian
+        object belongs to the field of Hermitian
+        (antihermitian) operators.
+
+Examples
+========
+
+    >>> from sympy import Symbol
+    >>> x = Symbol('x', real=True); x
+    x
+    >>> x.is_real
+    True
+    >>> x.is_complex
+    True
+
+See Also
+========
+
+.. seealso::
+
+    :py:class:`sympy.core.numbers.ImaginaryUnit`
+    :py:class:`sympy.core.numbers.Zero`
+    :py:class:`sympy.core.numbers.One`
+    :py:class:`sympy.core.numbers.Infinity`
+    :py:class:`sympy.core.numbers.NegativeInfinity`
+    :py:class:`sympy.core.numbers.ComplexInfinity`
+
+Notes
+=====
+
+The fully-resolved assumptions for any SymPy expression
+can be obtained as follows:
+
+    >>> from sympy.core.assumptions import assumptions
+    >>> x = Symbol('x',positive=True)
+    >>> assumptions(x + I)
+    {'commutative': True, 'complex': True, 'composite': False, 'even':
+    False, 'extended_negative': False, 'extended_nonnegative': False,
+    'extended_nonpositive': False, 'extended_nonzero': False,
+    'extended_positive': False, 'extended_real': False, 'finite': True,
+    'imaginary': False, 'infinite': False, 'integer': False, 'irrational':
+    False, 'negative': False, 'noninteger': False, 'nonnegative': False,
+    'nonpositive': False, 'nonzero': False, 'odd': False, 'positive':
+    False, 'prime': False, 'rational': False, 'real': False, 'zero':
+    False}
+
+Developers Notes
+================
+
+The current (and possibly incomplete) values are stored
+in the ``obj._assumptions dictionary``; queries to getter methods
+(with property decorators) or attributes of objects/classes
+will return values and update the dictionary.
+
+    >>> eq = x**2 + I
+    >>> eq._assumptions
+    {}
+    >>> eq.is_finite
+    True
+    >>> eq._assumptions
+    {'finite': True, 'infinite': False}
+
+For a :class:`~.Symbol`, there are two locations for assumptions that may
+be of interest. The ``assumptions0`` attribute gives the full set of
+assumptions derived from a given set of initial assumptions. The
+latter assumptions are stored as ``Symbol._assumptions_orig``
+
+    >>> Symbol('x', prime=True, even=True)._assumptions_orig
+    {'even': True, 'prime': True}
+
+The ``_assumptions_orig`` are not necessarily canonical nor are they filtered
+in any way: they records the assumptions used to instantiate a Symbol and (for
+storage purposes) represent a more compact representation of the assumptions
+needed to recreate the full set in ``Symbol.assumptions0``.
+
+
+References
+==========
+
+.. [1] https://en.wikipedia.org/wiki/Negative_number
+.. [2] https://en.wikipedia.org/wiki/Parity_%28mathematics%29
+.. [3] https://en.wikipedia.org/wiki/Imaginary_number
+.. [4] https://en.wikipedia.org/wiki/Composite_number
+.. [5] https://en.wikipedia.org/wiki/Irrational_number
+.. [6] https://en.wikipedia.org/wiki/Prime_number
+.. [7] https://en.wikipedia.org/wiki/Finite
+.. [8] https://docs.python.org/3/library/math.html#math.isfinite
+.. [9] https://numpy.org/doc/stable/reference/generated/numpy.isfinite.html
+.. [10] https://en.wikipedia.org/wiki/Transcendental_number
+.. [11] https://en.wikipedia.org/wiki/Algebraic_number
+.. [12] https://en.wikipedia.org/wiki/Commutative_property
+.. [13] https://en.wikipedia.org/wiki/Complex_number
+
+"""
+
+from sympy.utilities.exceptions import sympy_deprecation_warning
+
+from .facts import FactRules, FactKB
+from .sympify import sympify
+
+from sympy.core.random import _assumptions_shuffle as shuffle
+from sympy.core.assumptions_generated import generated_assumptions as _assumptions
+
+def _load_pre_generated_assumption_rules():
+    """ Load the assumption rules from pre-generated data
+
+    To update the pre-generated data, see :method::`_generate_assumption_rules`
+    """
+    _assume_rules=FactRules._from_python(_assumptions)
+    return _assume_rules
+
+def _generate_assumption_rules():
+    """ Generate the default assumption rules
+
+    This method should only be called to update the pre-generated
+    assumption rules.
+
+    To update the pre-generated assumptions run: bin/ask_update.py
+
+    """
+    _assume_rules = FactRules([
+
+    'integer        ->  rational',
+    'rational       ->  real',
+    'rational       ->  algebraic',
+    'algebraic      ->  complex',
+    'transcendental ==  complex & !algebraic',
+    'real           ->  hermitian',
+    'imaginary      ->  complex',
+    'imaginary      ->  antihermitian',
+    'extended_real  ->  commutative',
+    'complex        ->  commutative',
+    'complex        ->  finite',
+
+    'odd            ==  integer & !even',
+    'even           ==  integer & !odd',
+
+    'real           ->  complex',
+    'extended_real  ->  real | infinite',
+    'real           ==  extended_real & finite',
+
+    'extended_real        ==  extended_negative | zero | extended_positive',
+    'extended_negative    ==  extended_nonpositive & extended_nonzero',
+    'extended_positive    ==  extended_nonnegative & extended_nonzero',
+
+    'extended_nonpositive ==  extended_real & !extended_positive',
+    'extended_nonnegative ==  extended_real & !extended_negative',
+
+    'real           ==  negative | zero | positive',
+    'negative       ==  nonpositive & nonzero',
+    'positive       ==  nonnegative & nonzero',
+
+    'nonpositive    ==  real & !positive',
+    'nonnegative    ==  real & !negative',
+
+    'positive       ==  extended_positive & finite',
+    'negative       ==  extended_negative & finite',
+    'nonpositive    ==  extended_nonpositive & finite',
+    'nonnegative    ==  extended_nonnegative & finite',
+    'nonzero        ==  extended_nonzero & finite',
+
+    'zero           ->  even & finite',
+    'zero           ==  extended_nonnegative & extended_nonpositive',
+    'zero           ==  nonnegative & nonpositive',
+    'nonzero        ->  real',
+
+    'prime          ->  integer & positive',
+    'composite      ->  integer & positive & !prime',
+    '!composite     ->  !positive | !even | prime',
+
+    'irrational     ==  real & !rational',
+
+    'imaginary      ->  !extended_real',
+
+    'infinite       ==  !finite',
+    'noninteger     ==  extended_real & !integer',
+    'extended_nonzero == extended_real & !zero',
+    ])
+    return _assume_rules
+
+
+_assume_rules = _load_pre_generated_assumption_rules()
+_assume_defined = _assume_rules.defined_facts.copy()
+_assume_defined.add('polar')
+_assume_defined = frozenset(_assume_defined)
+
+
+def assumptions(expr, _check=None):
+    """return the T/F assumptions of ``expr``"""
+    n = sympify(expr)
+    if n.is_Symbol:
+        rv = n.assumptions0  # are any important ones missing?
+        if _check is not None:
+            rv = {k: rv[k] for k in set(rv) & set(_check)}
+        return rv
+    rv = {}
+    for k in _assume_defined if _check is None else _check:
+        v = getattr(n, 'is_{}'.format(k))
+        if v is not None:
+            rv[k] = v
+    return rv
+
+
+def common_assumptions(exprs, check=None):
+    """return those assumptions which have the same True or False
+    value for all the given expressions.
+
+    Examples
+    ========
+
+    >>> from sympy.core import common_assumptions
+    >>> from sympy import oo, pi, sqrt
+    >>> common_assumptions([-4, 0, sqrt(2), 2, pi, oo])
+    {'commutative': True, 'composite': False,
+    'extended_real': True, 'imaginary': False, 'odd': False}
+
+    By default, all assumptions are tested; pass an iterable of the
+    assumptions to limit those that are reported:
+
+    >>> common_assumptions([0, 1, 2], ['positive', 'integer'])
+    {'integer': True}
+    """
+    check = _assume_defined if check is None else set(check)
+    if not check or not exprs:
+        return {}
+
+    # get all assumptions for each
+    assume = [assumptions(i, _check=check) for i in sympify(exprs)]
+    # focus on those of interest that are True
+    for i, e in enumerate(assume):
+        assume[i] = {k: e[k] for k in set(e) & check}
+    # what assumptions are in common?
+    common = set.intersection(*[set(i) for i in assume])
+    # which ones hold the same value
+    a = assume[0]
+    return {k: a[k] for k in common if all(a[k] == b[k]
+        for b in assume)}
+
+
+def failing_assumptions(expr, **assumptions):
+    """
+    Return a dictionary containing assumptions with values not
+    matching those of the passed assumptions.
+
+    Examples
+    ========
+
+    >>> from sympy import failing_assumptions, Symbol
+
+    >>> x = Symbol('x', positive=True)
+    >>> y = Symbol('y')
+    >>> failing_assumptions(6*x + y, positive=True)
+    {'positive': None}
+
+    >>> failing_assumptions(x**2 - 1, positive=True)
+    {'positive': None}
+
+    If *expr* satisfies all of the assumptions, an empty dictionary is returned.
+
+    >>> failing_assumptions(x**2, positive=True)
+    {}
+
+    """
+    expr = sympify(expr)
+    failed = {}
+    for k in assumptions:
+        test = getattr(expr, 'is_%s' % k, None)
+        if test is not assumptions[k]:
+            failed[k] = test
+    return failed  # {} or {assumption: value != desired}
+
+
+def check_assumptions(expr, against=None, **assume):
+    """
+    Checks whether assumptions of ``expr`` match the T/F assumptions
+    given (or possessed by ``against``). True is returned if all
+    assumptions match; False is returned if there is a mismatch and
+    the assumption in ``expr`` is not None; else None is returned.
+
+    Explanation
+    ===========
+
+    *assume* is a dict of assumptions with True or False values
+
+    Examples
+    ========
+
+    >>> from sympy import Symbol, pi, I, exp, check_assumptions
+    >>> check_assumptions(-5, integer=True)
+    True
+    >>> check_assumptions(pi, real=True, integer=False)
+    True
+    >>> check_assumptions(pi, negative=True)
+    False
+    >>> check_assumptions(exp(I*pi/7), real=False)
+    True
+    >>> x = Symbol('x', positive=True)
+    >>> check_assumptions(2*x + 1, positive=True)
+    True
+    >>> check_assumptions(-2*x - 5, positive=True)
+    False
+
+    To check assumptions of *expr* against another variable or expression,
+    pass the expression or variable as ``against``.
+
+    >>> check_assumptions(2*x + 1, x)
+    True
+
+    To see if a number matches the assumptions of an expression, pass
+    the number as the first argument, else its specific assumptions
+    may not have a non-None value in the expression:
+
+    >>> check_assumptions(x, 3)
+    >>> check_assumptions(3, x)
+    True
+
+    ``None`` is returned if ``check_assumptions()`` could not conclude.
+
+    >>> check_assumptions(2*x - 1, x)
+
+    >>> z = Symbol('z')
+    >>> check_assumptions(z, real=True)
+
+    See Also
+    ========
+
+    failing_assumptions
+
+    """
+    expr = sympify(expr)
+    if against is not None:
+        if assume:
+            raise ValueError(
+                'Expecting `against` or `assume`, not both.')
+        assume = assumptions(against)
+    known = True
+    for k, v in assume.items():
+        if v is None:
+            continue
+        e = getattr(expr, 'is_' + k, None)
+        if e is None:
+            known = None
+        elif v != e:
+            return False
+    return known
+
+
+class StdFactKB(FactKB):
+    """A FactKB specialized for the built-in rules
+
+    This is the only kind of FactKB that Basic objects should use.
+    """
+    def __init__(self, facts=None):
+        super().__init__(_assume_rules)
+        # save a copy of the facts dict
+        if not facts:
+            self._generator = {}
+        elif not isinstance(facts, FactKB):
+            self._generator = facts.copy()
+        else:
+            self._generator = facts.generator
+        if facts:
+            self.deduce_all_facts(facts)
+
+    def copy(self):
+        return self.__class__(self)
+
+    @property
+    def generator(self):
+        return self._generator.copy()
+
+
+def as_property(fact):
+    """Convert a fact name to the name of the corresponding property"""
+    return 'is_%s' % fact
+
+
+def make_property(fact):
+    """Create the automagic property corresponding to a fact."""
+
+    def getit(self):
+        try:
+            return self._assumptions[fact]
+        except KeyError:
+            if self._assumptions is self.default_assumptions:
+                self._assumptions = self.default_assumptions.copy()
+            return _ask(fact, self)
+
+    getit.func_name = as_property(fact)
+    return property(getit)
+
+
+def _ask(fact, obj):
+    """
+    Find the truth value for a property of an object.
+
+    This function is called when a request is made to see what a fact
+    value is.
+
+    For this we use several techniques:
+
+    First, the fact-evaluation function is tried, if it exists (for
+    example _eval_is_integer). Then we try related facts. For example
+
+        rational   -->   integer
+
+    another example is joined rule:
+
+        integer & !odd  --> even
+
+    so in the latter case if we are looking at what 'even' value is,
+    'integer' and 'odd' facts will be asked.
+
+    In all cases, when we settle on some fact value, its implications are
+    deduced, and the result is cached in ._assumptions.
+    """
+    # FactKB which is dict-like and maps facts to their known values:
+    assumptions = obj._assumptions
+
+    # A dict that maps facts to their handlers:
+    handler_map = obj._prop_handler
+
+    # This is our queue of facts to check:
+    facts_to_check = [fact]
+    facts_queued = {fact}
+
+    # Loop over the queue as it extends
+    for fact_i in facts_to_check:
+
+        # If fact_i has already been determined then we don't need to rerun the
+        # handler. There is a potential race condition for multithreaded code
+        # though because it's possible that fact_i was checked in another
+        # thread. The main logic of the loop below would potentially skip
+        # checking assumptions[fact] in this case so we check it once after the
+        # loop to be sure.
+        if fact_i in assumptions:
+            continue
+
+        # Now we call the associated handler for fact_i if it exists.
+        fact_i_value = None
+        handler_i = handler_map.get(fact_i)
+        if handler_i is not None:
+            fact_i_value = handler_i(obj)
+
+        # If we get a new value for fact_i then we should update our knowledge
+        # of fact_i as well as any related facts that can be inferred using the
+        # inference rules connecting the fact_i and any other fact values that
+        # are already known.
+        if fact_i_value is not None:
+            assumptions.deduce_all_facts(((fact_i, fact_i_value),))
+
+        # Usually if assumptions[fact] is now not None then that is because of
+        # the call to deduce_all_facts above. The handler for fact_i returned
+        # True or False and knowing fact_i (which is equal to fact in the first
+        # iteration) implies knowing a value for fact. It is also possible
+        # though that independent code e.g. called indirectly by the handler or
+        # called in another thread in a multithreaded context might have
+        # resulted in assumptions[fact] being set. Either way we return it.
+        fact_value = assumptions.get(fact)
+        if fact_value is not None:
+            return fact_value
+
+        # Extend the queue with other facts that might determine fact_i. Here
+        # we randomise the order of the facts that are checked. This should not
+        # lead to any non-determinism if all handlers are logically consistent
+        # with the inference rules for the facts. Non-deterministic assumptions
+        # queries can result from bugs in the handlers that are exposed by this
+        # call to shuffle. These are pushed to the back of the queue meaning
+        # that the inference graph is traversed in breadth-first order.
+        new_facts_to_check = list(_assume_rules.prereq[fact_i] - facts_queued)
+        shuffle(new_facts_to_check)
+        facts_to_check.extend(new_facts_to_check)
+        facts_queued.update(new_facts_to_check)
+
+    # The above loop should be able to handle everything fine in a
+    # single-threaded context but in multithreaded code it is possible that
+    # this thread skipped computing a particular fact that was computed in
+    # another thread (due to the continue). In that case it is possible that
+    # fact was inferred and is now stored in the assumptions dict but it wasn't
+    # checked for in the body of the loop. This is an obscure case but to make
+    # sure we catch it we check once here at the end of the loop.
+    if fact in assumptions:
+        return assumptions[fact]
+
+    # This query can not be answered. It's possible that e.g. another thread
+    # has already stored None for fact but assumptions._tell does not mind if
+    # we call _tell twice setting the same value. If this raises
+    # InconsistentAssumptions then it probably means that another thread
+    # attempted to compute this and got a value of True or False rather than
+    # None. In that case there must be a bug in at least one of the handlers.
+    # If the handlers are all deterministic and are consistent with the
+    # inference rules then the same value should be computed for fact in all
+    # threads.
+    assumptions._tell(fact, None)
+    return None
+
+
+def _prepare_class_assumptions(cls):
+    """Precompute class level assumptions and generate handlers.
+
+    This is called by Basic.__init_subclass__ each time a Basic subclass is
+    defined.
+    """
+
+    local_defs = {}
+    for k in _assume_defined:
+        attrname = as_property(k)
+        v = cls.__dict__.get(attrname, '')
+        if isinstance(v, (bool, int, type(None))):
+            if v is not None:
+                v = bool(v)
+            local_defs[k] = v
+
+    defs = {}
+    for base in reversed(cls.__bases__):
+        assumptions = getattr(base, '_explicit_class_assumptions', None)
+        if assumptions is not None:
+            defs.update(assumptions)
+    defs.update(local_defs)
+
+    cls._explicit_class_assumptions = defs
+    cls.default_assumptions = StdFactKB(defs)
+
+    cls._prop_handler = {}
+    for k in _assume_defined:
+        eval_is_meth = getattr(cls, '_eval_is_%s' % k, None)
+        if eval_is_meth is not None:
+            cls._prop_handler[k] = eval_is_meth
+
+    # Put definite results directly into the class dict, for speed
+    for k, v in cls.default_assumptions.items():
+        setattr(cls, as_property(k), v)
+
+    # protection e.g. for Integer.is_even=F <- (Rational.is_integer=F)
+    derived_from_bases = set()
+    for base in cls.__bases__:
+        default_assumptions = getattr(base, 'default_assumptions', None)
+        # is an assumption-aware class
+        if default_assumptions is not None:
+            derived_from_bases.update(default_assumptions)
+
+    for fact in derived_from_bases - set(cls.default_assumptions):
+        pname = as_property(fact)
+        if pname not in cls.__dict__:
+            setattr(cls, pname, make_property(fact))
+
+    # Finally, add any missing automagic property (e.g. for Basic)
+    for fact in _assume_defined:
+        pname = as_property(fact)
+        if not hasattr(cls, pname):
+            setattr(cls, pname, make_property(fact))
+
+
+# XXX: ManagedProperties used to be the metaclass for Basic but now Basic does
+# not use a metaclass. We leave this here for backwards compatibility for now
+# in case someone has been using the ManagedProperties class in downstream
+# code. The reason that it might have been used is that when subclassing a
+# class and wanting to use a metaclass the metaclass must be a subclass of the
+# metaclass for the class that is being subclassed. Anyone wanting to subclass
+# Basic and use a metaclass in their subclass would have needed to subclass
+# ManagedProperties. Here ManagedProperties is not the metaclass for Basic any
+# more but it should still be usable as a metaclass for Basic subclasses since
+# it is a subclass of type which is now the metaclass for Basic.
+class ManagedProperties(type):
+    def __init__(cls, *args, **kwargs):
+        msg = ("The ManagedProperties metaclass. "
+               "Basic does not use metaclasses any more")
+        sympy_deprecation_warning(msg,
+            deprecated_since_version="1.12",
+            active_deprecations_target='managedproperties')
+
+        # Here we still call this function in case someone is using
+        # ManagedProperties for something that is not a Basic subclass. For
+        # Basic subclasses this function is now called by __init_subclass__ and
+        # so this metaclass is not needed any more.
+        _prepare_class_assumptions(cls)

env-llmeval/lib/python3.10/site-packages/sympy/core/backend.py

@@ -0,0 +1,84 @@
+import os
+USE_SYMENGINE = os.getenv('USE_SYMENGINE', '0')
+USE_SYMENGINE = USE_SYMENGINE.lower() in ('1', 't', 'true')  # type: ignore
+
+if USE_SYMENGINE:
+    from symengine import (Symbol, Integer, sympify, S,
+        SympifyError, exp, log, gamma, sqrt, I, E, pi, Matrix,
+        sin, cos, tan, cot, csc, sec, asin, acos, atan, acot, acsc, asec,
+        sinh, cosh, tanh, coth, asinh, acosh, atanh, acoth,
+        lambdify, symarray, diff, zeros, eye, diag, ones,
+        expand, Function, symbols, var, Add, Mul, Derivative,
+        ImmutableMatrix, MatrixBase, Rational, Basic)
+    from symengine.lib.symengine_wrapper import gcd as igcd
+    from symengine import AppliedUndef
+else:
+    from sympy.core.add import Add
+    from sympy.core.basic import Basic
+    from sympy.core.function import (diff, Function, AppliedUndef,
+        expand, Derivative)
+    from sympy.core.mul import Mul
+    from sympy.core.numbers import igcd, pi, I, Integer, Rational, E
+    from sympy.core.singleton import S
+    from sympy.core.symbol import Symbol, var, symbols
+    from sympy.core.sympify import SympifyError, sympify
+    from sympy.functions.elementary.exponential import log, exp
+    from sympy.functions.elementary.hyperbolic import (coth, sinh,
+        acosh, acoth, tanh, asinh, atanh, cosh)
+    from sympy.functions.elementary.miscellaneous import sqrt
+    from sympy.functions.elementary.trigonometric import (csc,
+        asec, cos, atan, sec, acot, asin, tan, sin, cot, acsc, acos)
+    from sympy.functions.special.gamma_functions import gamma
+    from sympy.matrices.dense import (eye, zeros, diag, Matrix,
+        ones, symarray)
+    from sympy.matrices.immutable import ImmutableMatrix
+    from sympy.matrices.matrices import MatrixBase
+    from sympy.utilities.lambdify import lambdify
+
+
+#
+# XXX: Handling of immutable and mutable matrices in SymEngine is inconsistent
+# with SymPy's matrix classes in at least SymEngine version 0.7.0. Until that
+# is fixed the function below is needed for consistent behaviour when
+# attempting to simplify a matrix.
+#
+# Expected behaviour of a SymPy mutable/immutable matrix .simplify() method:
+#
+#   Matrix.simplify() : works in place, returns None
+#   ImmutableMatrix.simplify() : returns a simplified copy
+#
+# In SymEngine both mutable and immutable matrices simplify in place and return
+# None. This is inconsistent with the matrix being "immutable" and also the
+# returned None leads to problems in the mechanics module.
+#
+# The simplify function should not be used because simplify(M) sympifies the
+# matrix M and the SymEngine matrices all sympify to SymPy matrices. If we want
+# to work with SymEngine matrices then we need to use their .simplify() method
+# but that method does not work correctly with immutable matrices.
+#
+# The _simplify_matrix function can be removed when the SymEngine bug is fixed.
+# Since this should be a temporary problem we do not make this function part of
+# the public API.
+#
+#   SymEngine issue: https://github.com/symengine/symengine.py/issues/363
+#
+
+def _simplify_matrix(M):
+    """Return a simplified copy of the matrix M"""
+    assert isinstance(M, (Matrix, ImmutableMatrix))
+    Mnew = M.as_mutable() # makes a copy if mutable
+    Mnew.simplify()
+    if isinstance(M, ImmutableMatrix):
+        Mnew = Mnew.as_immutable()
+    return Mnew
+
+
+__all__ = [
+    'Symbol', 'Integer', 'sympify', 'S', 'SympifyError', 'exp', 'log',
+    'gamma', 'sqrt', 'I', 'E', 'pi', 'Matrix', 'sin', 'cos', 'tan', 'cot',
+    'csc', 'sec', 'asin', 'acos', 'atan', 'acot', 'acsc', 'asec', 'sinh',
+    'cosh', 'tanh', 'coth', 'asinh', 'acosh', 'atanh', 'acoth', 'lambdify',
+    'symarray', 'diff', 'zeros', 'eye', 'diag', 'ones', 'expand', 'Function',
+    'symbols', 'var', 'Add', 'Mul', 'Derivative', 'ImmutableMatrix',
+    'MatrixBase', 'Rational', 'Basic', 'igcd', 'AppliedUndef',
+]

env-llmeval/lib/python3.10/site-packages/sympy/core/basic.py

@@ -0,0 +1,2233 @@
+"""Base class for all the objects in SymPy"""
+from __future__ import annotations
+
+from collections import defaultdict
+from collections.abc import Mapping
+from itertools import chain, zip_longest
+
+from .assumptions import _prepare_class_assumptions
+from .cache import cacheit
+from .core import ordering_of_classes
+from .sympify import _sympify, sympify, SympifyError, _external_converter
+from .sorting import ordered
+from .kind import Kind, UndefinedKind
+from ._print_helpers import Printable
+
+from sympy.utilities.decorator import deprecated
+from sympy.utilities.exceptions import sympy_deprecation_warning
+from sympy.utilities.iterables import iterable, numbered_symbols
+from sympy.utilities.misc import filldedent, func_name
+
+from inspect import getmro
+
+
+def as_Basic(expr):
+    """Return expr as a Basic instance using strict sympify
+    or raise a TypeError; this is just a wrapper to _sympify,
+    raising a TypeError instead of a SympifyError."""
+    try:
+        return _sympify(expr)
+    except SympifyError:
+        raise TypeError(
+            'Argument must be a Basic object, not `%s`' % func_name(
+            expr))
+
+
+def _old_compare(x: type, y: type) -> int:
+    # If the other object is not a Basic subclass, then we are not equal to it.
+    if not issubclass(y, Basic):
+        return -1
+
+    n1 = x.__name__
+    n2 = y.__name__
+    if n1 == n2:
+        return 0
+
+    UNKNOWN = len(ordering_of_classes) + 1
+    try:
+        i1 = ordering_of_classes.index(n1)
+    except ValueError:
+        i1 = UNKNOWN
+    try:
+        i2 = ordering_of_classes.index(n2)
+    except ValueError:
+        i2 = UNKNOWN
+    if i1 == UNKNOWN and i2 == UNKNOWN:
+        return (n1 > n2) - (n1 < n2)
+    return (i1 > i2) - (i1 < i2)
+
+
+class Basic(Printable):
+    """
+    Base class for all SymPy objects.
+
+    Notes and conventions
+    =====================
+
+    1) Always use ``.args``, when accessing parameters of some instance:
+
+    >>> from sympy import cot
+    >>> from sympy.abc import x, y
+
+    >>> cot(x).args
+    (x,)
+
+    >>> cot(x).args[0]
+    x
+
+    >>> (x*y).args
+    (x, y)
+
+    >>> (x*y).args[1]
+    y
+
+
+    2) Never use internal methods or variables (the ones prefixed with ``_``):
+
+    >>> cot(x)._args    # do not use this, use cot(x).args instead
+    (x,)
+
+
+    3)  By "SymPy object" we mean something that can be returned by
+        ``sympify``.  But not all objects one encounters using SymPy are
+        subclasses of Basic.  For example, mutable objects are not:
+
+        >>> from sympy import Basic, Matrix, sympify
+        >>> A = Matrix([[1, 2], [3, 4]]).as_mutable()
+        >>> isinstance(A, Basic)
+        False
+
+        >>> B = sympify(A)
+        >>> isinstance(B, Basic)
+        True
+    """
+    __slots__ = ('_mhash',              # hash value
+                 '_args',               # arguments
+                 '_assumptions'
+                )
+
+    _args: tuple[Basic, ...]
+    _mhash: int | None
+
+    @property
+    def __sympy__(self):
+        return True
+
+    def __init_subclass__(cls):
+        # Initialize the default_assumptions FactKB and also any assumptions
+        # property methods. This method will only be called for subclasses of
+        # Basic but not for Basic itself so we call
+        # _prepare_class_assumptions(Basic) below the class definition.
+        _prepare_class_assumptions(cls)
+
+    # To be overridden with True in the appropriate subclasses
+    is_number = False
+    is_Atom = False
+    is_Symbol = False
+    is_symbol = False
+    is_Indexed = False
+    is_Dummy = False
+    is_Wild = False
+    is_Function = False
+    is_Add = False
+    is_Mul = False
+    is_Pow = False
+    is_Number = False
+    is_Float = False
+    is_Rational = False
+    is_Integer = False
+    is_NumberSymbol = False
+    is_Order = False
+    is_Derivative = False
+    is_Piecewise = False
+    is_Poly = False
+    is_AlgebraicNumber = False
+    is_Relational = False
+    is_Equality = False
+    is_Boolean = False
+    is_Not = False
+    is_Matrix = False
+    is_Vector = False
+    is_Point = False
+    is_MatAdd = False
+    is_MatMul = False
+    is_real: bool | None
+    is_extended_real: bool | None
+    is_zero: bool | None
+    is_negative: bool | None
+    is_commutative: bool | None
+
+    kind: Kind = UndefinedKind
+
+    def __new__(cls, *args):
+        obj = object.__new__(cls)
+        obj._assumptions = cls.default_assumptions
+        obj._mhash = None  # will be set by __hash__ method.
+
+        obj._args = args  # all items in args must be Basic objects
+        return obj
+
+    def copy(self):
+        return self.func(*self.args)
+
+    def __getnewargs__(self):
+        return self.args
+
+    def __getstate__(self):
+        return None
+
+    def __setstate__(self, state):
+        for name, value in state.items():
+            setattr(self, name, value)
+
+    def __reduce_ex__(self, protocol):
+        if protocol < 2:
+            msg = "Only pickle protocol 2 or higher is supported by SymPy"
+            raise NotImplementedError(msg)
+        return super().__reduce_ex__(protocol)
+
+    def __hash__(self) -> int:
+        # hash cannot be cached using cache_it because infinite recurrence
+        # occurs as hash is needed for setting cache dictionary keys
+        h = self._mhash
+        if h is None:
+            h = hash((type(self).__name__,) + self._hashable_content())
+            self._mhash = h
+        return h
+
+    def _hashable_content(self):
+        """Return a tuple of information about self that can be used to
+        compute the hash. If a class defines additional attributes,
+        like ``name`` in Symbol, then this method should be updated
+        accordingly to return such relevant attributes.
+
+        Defining more than _hashable_content is necessary if __eq__ has
+        been defined by a class. See note about this in Basic.__eq__."""
+        return self._args
+
+    @property
+    def assumptions0(self):
+        """
+        Return object `type` assumptions.
+
+        For example:
+
+          Symbol('x', real=True)
+          Symbol('x', integer=True)
+
+        are different objects. In other words, besides Python type (Symbol in
+        this case), the initial assumptions are also forming their typeinfo.
+
+        Examples
+        ========
+
+        >>> from sympy import Symbol
+        >>> from sympy.abc import x
+        >>> x.assumptions0
+        {'commutative': True}
+        >>> x = Symbol("x", positive=True)
+        >>> x.assumptions0
+        {'commutative': True, 'complex': True, 'extended_negative': False,
+         'extended_nonnegative': True, 'extended_nonpositive': False,
+         'extended_nonzero': True, 'extended_positive': True, 'extended_real':
+         True, 'finite': True, 'hermitian': True, 'imaginary': False,
+         'infinite': False, 'negative': False, 'nonnegative': True,
+         'nonpositive': False, 'nonzero': True, 'positive': True, 'real':
+         True, 'zero': False}
+        """
+        return {}
+
+    def compare(self, other):
+        """
+        Return -1, 0, 1 if the object is smaller, equal, or greater than other.
+
+        Not in the mathematical sense. If the object is of a different type
+        from the "other" then their classes are ordered according to
+        the sorted_classes list.
+
+        Examples
+        ========
+
+        >>> from sympy.abc import x, y
+        >>> x.compare(y)
+        -1
+        >>> x.compare(x)
+        0
+        >>> y.compare(x)
+        1
+
+        """
+        # all redefinitions of __cmp__ method should start with the
+        # following lines:
+        if self is other:
+            return 0
+        n1 = self.__class__
+        n2 = other.__class__
+        c = _old_compare(n1, n2)
+        if c:
+            return c
+        #
+        st = self._hashable_content()
+        ot = other._hashable_content()
+        c = (len(st) > len(ot)) - (len(st) < len(ot))
+        if c:
+            return c
+        for l, r in zip(st, ot):
+            l = Basic(*l) if isinstance(l, frozenset) else l
+            r = Basic(*r) if isinstance(r, frozenset) else r
+            if isinstance(l, Basic):
+                c = l.compare(r)
+            else:
+                c = (l > r) - (l < r)
+            if c:
+                return c
+        return 0
+
+    @staticmethod
+    def _compare_pretty(a, b):
+        from sympy.series.order import Order
+        if isinstance(a, Order) and not isinstance(b, Order):
+            return 1
+        if not isinstance(a, Order) and isinstance(b, Order):
+            return -1
+
+        if a.is_Rational and b.is_Rational:
+            l = a.p * b.q
+            r = b.p * a.q
+            return (l > r) - (l < r)
+        else:
+            from .symbol import Wild
+            p1, p2, p3 = Wild("p1"), Wild("p2"), Wild("p3")
+            r_a = a.match(p1 * p2**p3)
+            if r_a and p3 in r_a:
+                a3 = r_a[p3]
+                r_b = b.match(p1 * p2**p3)
+                if r_b and p3 in r_b:
+                    b3 = r_b[p3]
+                    c = Basic.compare(a3, b3)
+                    if c != 0:
+                        return c
+
+        return Basic.compare(a, b)
+
+    @classmethod
+    def fromiter(cls, args, **assumptions):
+        """
+        Create a new object from an iterable.
+
+        This is a convenience function that allows one to create objects from
+        any iterable, without having to convert to a list or tuple first.
+
+        Examples
+        ========
+
+        >>> from sympy import Tuple
+        >>> Tuple.fromiter(i for i in range(5))
+        (0, 1, 2, 3, 4)
+
+        """
+        return cls(*tuple(args), **assumptions)
+
+    @classmethod
+    def class_key(cls):
+        """Nice order of classes."""
+        return 5, 0, cls.__name__
+
+    @cacheit
+    def sort_key(self, order=None):
+        """
+        Return a sort key.
+
+        Examples
+        ========
+
+        >>> from sympy import S, I
+
+        >>> sorted([S(1)/2, I, -I], key=lambda x: x.sort_key())
+        [1/2, -I, I]
+
+        >>> S("[x, 1/x, 1/x**2, x**2, x**(1/2), x**(1/4), x**(3/2)]")
+        [x, 1/x, x**(-2), x**2, sqrt(x), x**(1/4), x**(3/2)]
+        >>> sorted(_, key=lambda x: x.sort_key())
+        [x**(-2), 1/x, x**(1/4), sqrt(x), x, x**(3/2), x**2]
+
+        """
+
+        # XXX: remove this when issue 5169 is fixed
+        def inner_key(arg):
+            if isinstance(arg, Basic):
+                return arg.sort_key(order)
+            else:
+                return arg
+
+        args = self._sorted_args
+        args = len(args), tuple([inner_key(arg) for arg in args])
+        return self.class_key(), args, S.One.sort_key(), S.One
+
+    def _do_eq_sympify(self, other):
+        """Returns a boolean indicating whether a == b when either a
+        or b is not a Basic. This is only done for types that were either
+        added to `converter` by a 3rd party or when the object has `_sympy_`
+        defined. This essentially reuses the code in `_sympify` that is
+        specific for this use case. Non-user defined types that are meant
+        to work with SymPy should be handled directly in the __eq__ methods
+        of the `Basic` classes it could equate to and not be converted. Note
+        that after conversion, `==`  is used again since it is not
+        necessarily clear whether `self` or `other`'s __eq__ method needs
+        to be used."""
+        for superclass in type(other).__mro__:
+            conv = _external_converter.get(superclass)
+            if conv is not None:
+                return self == conv(other)
+        if hasattr(other, '_sympy_'):
+            return self == other._sympy_()
+        return NotImplemented
+
+    def __eq__(self, other):
+        """Return a boolean indicating whether a == b on the basis of
+        their symbolic trees.
+
+        This is the same as a.compare(b) == 0 but faster.
+
+        Notes
+        =====
+
+        If a class that overrides __eq__() needs to retain the
+        implementation of __hash__() from a parent class, the
+        interpreter must be told this explicitly by setting
+        __hash__ : Callable[[object], int] = <ParentClass>.__hash__.
+        Otherwise the inheritance of __hash__() will be blocked,
+        just as if __hash__ had been explicitly set to None.
+
+        References
+        ==========
+
+        from https://docs.python.org/dev/reference/datamodel.html#object.__hash__
+        """
+        if self is other:
+            return True
+
+        if not isinstance(other, Basic):
+            return self._do_eq_sympify(other)
+
+        # check for pure number expr
+        if  not (self.is_Number and other.is_Number) and (
+                type(self) != type(other)):
+            return False
+        a, b = self._hashable_content(), other._hashable_content()
+        if a != b:
+            return False
+        # check number *in* an expression
+        for a, b in zip(a, b):
+            if not isinstance(a, Basic):
+                continue
+            if a.is_Number and type(a) != type(b):
+                return False
+        return True
+
+    def __ne__(self, other):
+        """``a != b``  -> Compare two symbolic trees and see whether they are different
+
+        this is the same as:
+
+        ``a.compare(b) != 0``
+
+        but faster
+        """
+        return not self == other
+
+    def dummy_eq(self, other, symbol=None):
+        """
+        Compare two expressions and handle dummy symbols.
+
+        Examples
+        ========
+
+        >>> from sympy import Dummy
+        >>> from sympy.abc import x, y
+
+        >>> u = Dummy('u')
+
+        >>> (u**2 + 1).dummy_eq(x**2 + 1)
+        True
+        >>> (u**2 + 1) == (x**2 + 1)
+        False
+
+        >>> (u**2 + y).dummy_eq(x**2 + y, x)
+        True
+        >>> (u**2 + y).dummy_eq(x**2 + y, y)
+        False
+
+        """
+        s = self.as_dummy()
+        o = _sympify(other)
+        o = o.as_dummy()
+
+        dummy_symbols = [i for i in s.free_symbols if i.is_Dummy]
+
+        if len(dummy_symbols) == 1:
+            dummy = dummy_symbols.pop()
+        else:
+            return s == o
+
+        if symbol is None:
+            symbols = o.free_symbols
+
+            if len(symbols) == 1:
+                symbol = symbols.pop()
+            else:
+                return s == o
+
+        tmp = dummy.__class__()
+
+        return s.xreplace({dummy: tmp}) == o.xreplace({symbol: tmp})
+
+    def atoms(self, *types):
+        """Returns the atoms that form the current object.
+
+        By default, only objects that are truly atomic and cannot
+        be divided into smaller pieces are returned: symbols, numbers,
+        and number symbols like I and pi. It is possible to request
+        atoms of any type, however, as demonstrated below.
+
+        Examples
+        ========
+
+        >>> from sympy import I, pi, sin
+        >>> from sympy.abc import x, y
+        >>> (1 + x + 2*sin(y + I*pi)).atoms()
+        {1, 2, I, pi, x, y}
+
+        If one or more types are given, the results will contain only
+        those types of atoms.
+
+        >>> from sympy import Number, NumberSymbol, Symbol
+        >>> (1 + x + 2*sin(y + I*pi)).atoms(Symbol)
+        {x, y}
+
+        >>> (1 + x + 2*sin(y + I*pi)).atoms(Number)
+        {1, 2}
+
+        >>> (1 + x + 2*sin(y + I*pi)).atoms(Number, NumberSymbol)
+        {1, 2, pi}
+
+        >>> (1 + x + 2*sin(y + I*pi)).atoms(Number, NumberSymbol, I)
+        {1, 2, I, pi}
+
+        Note that I (imaginary unit) and zoo (complex infinity) are special
+        types of number symbols and are not part of the NumberSymbol class.
+
+        The type can be given implicitly, too:
+
+        >>> (1 + x + 2*sin(y + I*pi)).atoms(x) # x is a Symbol
+        {x, y}
+
+        Be careful to check your assumptions when using the implicit option
+        since ``S(1).is_Integer = True`` but ``type(S(1))`` is ``One``, a special type
+        of SymPy atom, while ``type(S(2))`` is type ``Integer`` and will find all
+        integers in an expression:
+
+        >>> from sympy import S
+        >>> (1 + x + 2*sin(y + I*pi)).atoms(S(1))
+        {1}
+
+        >>> (1 + x + 2*sin(y + I*pi)).atoms(S(2))
+        {1, 2}
+
+        Finally, arguments to atoms() can select more than atomic atoms: any
+        SymPy type (loaded in core/__init__.py) can be listed as an argument
+        and those types of "atoms" as found in scanning the arguments of the
+        expression recursively:
+
+        >>> from sympy import Function, Mul
+        >>> from sympy.core.function import AppliedUndef
+        >>> f = Function('f')
+        >>> (1 + f(x) + 2*sin(y + I*pi)).atoms(Function)
+        {f(x), sin(y + I*pi)}
+        >>> (1 + f(x) + 2*sin(y + I*pi)).atoms(AppliedUndef)
+        {f(x)}
+
+        >>> (1 + x + 2*sin(y + I*pi)).atoms(Mul)
+        {I*pi, 2*sin(y + I*pi)}
+
+        """
+        if types:
+            types = tuple(
+                [t if isinstance(t, type) else type(t) for t in types])
+        nodes = _preorder_traversal(self)
+        if types:
+            result = {node for node in nodes if isinstance(node, types)}
+        else:
+            result = {node for node in nodes if not node.args}
+        return result
+
+    @property
+    def free_symbols(self) -> set[Basic]:
+        """Return from the atoms of self those which are free symbols.
+
+        Not all free symbols are ``Symbol``. Eg: IndexedBase('I')[0].free_symbols
+
+        For most expressions, all symbols are free symbols. For some classes
+        this is not true. e.g. Integrals use Symbols for the dummy variables
+        which are bound variables, so Integral has a method to return all
+        symbols except those. Derivative keeps track of symbols with respect
+        to which it will perform a derivative; those are
+        bound variables, too, so it has its own free_symbols method.
+
+        Any other method that uses bound variables should implement a
+        free_symbols method."""
+        empty: set[Basic] = set()
+        return empty.union(*(a.free_symbols for a in self.args))
+
+    @property
+    def expr_free_symbols(self):
+        sympy_deprecation_warning("""
+        The expr_free_symbols property is deprecated. Use free_symbols to get
+        the free symbols of an expression.
+        """,
+            deprecated_since_version="1.9",
+            active_deprecations_target="deprecated-expr-free-symbols")
+        return set()
+
+    def as_dummy(self):
+        """Return the expression with any objects having structurally
+        bound symbols replaced with unique, canonical symbols within
+        the object in which they appear and having only the default
+        assumption for commutativity being True. When applied to a
+        symbol a new symbol having only the same commutativity will be
+        returned.
+
+        Examples
+        ========
+
+        >>> from sympy import Integral, Symbol
+        >>> from sympy.abc import x
+        >>> r = Symbol('r', real=True)
+        >>> Integral(r, (r, x)).as_dummy()
+        Integral(_0, (_0, x))
+        >>> _.variables[0].is_real is None
+        True
+        >>> r.as_dummy()
+        _r
+
+        Notes
+        =====
+
+        Any object that has structurally bound variables should have
+        a property, `bound_symbols` that returns those symbols
+        appearing in the object.
+        """
+        from .symbol import Dummy, Symbol
+        def can(x):
+            # mask free that shadow bound
+            free = x.free_symbols
+            bound = set(x.bound_symbols)
+            d = {i: Dummy() for i in bound & free}
+            x = x.subs(d)
+            # replace bound with canonical names
+            x = x.xreplace(x.canonical_variables)
+            # return after undoing masking
+            return x.xreplace({v: k for k, v in d.items()})
+        if not self.has(Symbol):
+            return self
+        return self.replace(
+            lambda x: hasattr(x, 'bound_symbols'),
+            can,
+            simultaneous=False)
+
+    @property
+    def canonical_variables(self):
+        """Return a dictionary mapping any variable defined in
+        ``self.bound_symbols`` to Symbols that do not clash
+        with any free symbols in the expression.
+
+        Examples
+        ========
+
+        >>> from sympy import Lambda
+        >>> from sympy.abc import x
+        >>> Lambda(x, 2*x).canonical_variables
+        {x: _0}
+        """
+        if not hasattr(self, 'bound_symbols'):
+            return {}
+        dums = numbered_symbols('_')
+        reps = {}
+        # watch out for free symbol that are not in bound symbols;
+        # those that are in bound symbols are about to get changed
+        bound = self.bound_symbols
+        names = {i.name for i in self.free_symbols - set(bound)}
+        for b in bound:
+            d = next(dums)
+            if b.is_Symbol:
+                while d.name in names:
+                    d = next(dums)
+            reps[b] = d
+        return reps
+
+    def rcall(self, *args):
+        """Apply on the argument recursively through the expression tree.
+
+        This method is used to simulate a common abuse of notation for
+        operators. For instance, in SymPy the following will not work:
+
+        ``(x+Lambda(y, 2*y))(z) == x+2*z``,
+
+        however, you can use:
+
+        >>> from sympy import Lambda
+        >>> from sympy.abc import x, y, z
+        >>> (x + Lambda(y, 2*y)).rcall(z)
+        x + 2*z
+        """
+        return Basic._recursive_call(self, args)
+
+    @staticmethod
+    def _recursive_call(expr_to_call, on_args):
+        """Helper for rcall method."""
+        from .symbol import Symbol
+        def the_call_method_is_overridden(expr):
+            for cls in getmro(type(expr)):
+                if '__call__' in cls.__dict__:
+                    return cls != Basic
+
+        if callable(expr_to_call) and the_call_method_is_overridden(expr_to_call):
+            if isinstance(expr_to_call, Symbol):  # XXX When you call a Symbol it is
+                return expr_to_call               # transformed into an UndefFunction
+            else:
+                return expr_to_call(*on_args)
+        elif expr_to_call.args:
+            args = [Basic._recursive_call(
+                sub, on_args) for sub in expr_to_call.args]
+            return type(expr_to_call)(*args)
+        else:
+            return expr_to_call
+
+    def is_hypergeometric(self, k):
+        from sympy.simplify.simplify import hypersimp
+        from sympy.functions.elementary.piecewise import Piecewise
+        if self.has(Piecewise):
+            return None
+        return hypersimp(self, k) is not None
+
+    @property
+    def is_comparable(self):
+        """Return True if self can be computed to a real number
+        (or already is a real number) with precision, else False.
+
+        Examples
+        ========
+
+        >>> from sympy import exp_polar, pi, I
+        >>> (I*exp_polar(I*pi/2)).is_comparable
+        True
+        >>> (I*exp_polar(I*pi*2)).is_comparable
+        False
+
+        A False result does not mean that `self` cannot be rewritten
+        into a form that would be comparable. For example, the
+        difference computed below is zero but without simplification
+        it does not evaluate to a zero with precision:
+
+        >>> e = 2**pi*(1 + 2**pi)
+        >>> dif = e - e.expand()
+        >>> dif.is_comparable
+        False
+        >>> dif.n(2)._prec
+        1
+
+        """
+        is_extended_real = self.is_extended_real
+        if is_extended_real is False:
+            return False
+        if not self.is_number:
+            return False
+        # don't re-eval numbers that are already evaluated since
+        # this will create spurious precision
+        n, i = [p.evalf(2) if not p.is_Number else p
+            for p in self.as_real_imag()]
+        if not (i.is_Number and n.is_Number):
+            return False
+        if i:
+            # if _prec = 1 we can't decide and if not,
+            # the answer is False because numbers with
+            # imaginary parts can't be compared
+            # so return False
+            return False
+        else:
+            return n._prec != 1
+
+    @property
+    def func(self):
+        """
+        The top-level function in an expression.
+
+        The following should hold for all objects::
+
+            >> x == x.func(*x.args)
+
+        Examples
+        ========
+
+        >>> from sympy.abc import x
+        >>> a = 2*x
+        >>> a.func
+        <class 'sympy.core.mul.Mul'>
+        >>> a.args
+        (2, x)
+        >>> a.func(*a.args)
+        2*x
+        >>> a == a.func(*a.args)
+        True
+
+        """
+        return self.__class__
+
+    @property
+    def args(self) -> tuple[Basic, ...]:
+        """Returns a tuple of arguments of 'self'.
+
+        Examples
+        ========
+
+        >>> from sympy import cot
+        >>> from sympy.abc import x, y
+
+        >>> cot(x).args
+        (x,)
+
+        >>> cot(x).args[0]
+        x
+
+        >>> (x*y).args
+        (x, y)
+
+        >>> (x*y).args[1]
+        y
+
+        Notes
+        =====
+
+        Never use self._args, always use self.args.
+        Only use _args in __new__ when creating a new function.
+        Do not override .args() from Basic (so that it is easy to
+        change the interface in the future if needed).
+        """
+        return self._args
+
+    @property
+    def _sorted_args(self):
+        """
+        The same as ``args``.  Derived classes which do not fix an
+        order on their arguments should override this method to
+        produce the sorted representation.
+        """
+        return self.args
+
+    def as_content_primitive(self, radical=False, clear=True):
+        """A stub to allow Basic args (like Tuple) to be skipped when computing
+        the content and primitive components of an expression.
+
+        See Also
+        ========
+
+        sympy.core.expr.Expr.as_content_primitive
+        """
+        return S.One, self
+
+    def subs(self, *args, **kwargs):
+        """
+        Substitutes old for new in an expression after sympifying args.
+
+        `args` is either:
+          - two arguments, e.g. foo.subs(old, new)
+          - one iterable argument, e.g. foo.subs(iterable). The iterable may be
+             o an iterable container with (old, new) pairs. In this case the
+               replacements are processed in the order given with successive
+               patterns possibly affecting replacements already made.
+             o a dict or set whose key/value items correspond to old/new pairs.
+               In this case the old/new pairs will be sorted by op count and in
+               case of a tie, by number of args and the default_sort_key. The
+               resulting sorted list is then processed as an iterable container
+               (see previous).
+
+        If the keyword ``simultaneous`` is True, the subexpressions will not be
+        evaluated until all the substitutions have been made.
+
+        Examples
+        ========
+
+        >>> from sympy import pi, exp, limit, oo
+        >>> from sympy.abc import x, y
+        >>> (1 + x*y).subs(x, pi)
+        pi*y + 1
+        >>> (1 + x*y).subs({x:pi, y:2})
+        1 + 2*pi
+        >>> (1 + x*y).subs([(x, pi), (y, 2)])
+        1 + 2*pi
+        >>> reps = [(y, x**2), (x, 2)]
+        >>> (x + y).subs(reps)
+        6
+        >>> (x + y).subs(reversed(reps))
+        x**2 + 2
+
+        >>> (x**2 + x**4).subs(x**2, y)
+        y**2 + y
+
+        To replace only the x**2 but not the x**4, use xreplace:
+
+        >>> (x**2 + x**4).xreplace({x**2: y})
+        x**4 + y
+
+        To delay evaluation until all substitutions have been made,
+        set the keyword ``simultaneous`` to True:
+
+        >>> (x/y).subs([(x, 0), (y, 0)])
+        0
+        >>> (x/y).subs([(x, 0), (y, 0)], simultaneous=True)
+        nan
+
+        This has the added feature of not allowing subsequent substitutions
+        to affect those already made:
+
+        >>> ((x + y)/y).subs({x + y: y, y: x + y})
+        1
+        >>> ((x + y)/y).subs({x + y: y, y: x + y}, simultaneous=True)
+        y/(x + y)
+
+        In order to obtain a canonical result, unordered iterables are
+        sorted by count_op length, number of arguments and by the
+        default_sort_key to break any ties. All other iterables are left
+        unsorted.
+
+        >>> from sympy import sqrt, sin, cos
+        >>> from sympy.abc import a, b, c, d, e
+
+        >>> A = (sqrt(sin(2*x)), a)
+        >>> B = (sin(2*x), b)
+        >>> C = (cos(2*x), c)
+        >>> D = (x, d)
+        >>> E = (exp(x), e)
+
+        >>> expr = sqrt(sin(2*x))*sin(exp(x)*x)*cos(2*x) + sin(2*x)
+
+        >>> expr.subs(dict([A, B, C, D, E]))
+        a*c*sin(d*e) + b
+
+        The resulting expression represents a literal replacement of the
+        old arguments with the new arguments. This may not reflect the
+        limiting behavior of the expression:
+
+        >>> (x**3 - 3*x).subs({x: oo})
+        nan
+
+        >>> limit(x**3 - 3*x, x, oo)
+        oo
+
+        If the substitution will be followed by numerical
+        evaluation, it is better to pass the substitution to
+        evalf as
+
+        >>> (1/x).evalf(subs={x: 3.0}, n=21)
+        0.333333333333333333333
+
+        rather than
+
+        >>> (1/x).subs({x: 3.0}).evalf(21)
+        0.333333333333333314830
+
+        as the former will ensure that the desired level of precision is
+        obtained.
+
+        See Also
+        ========
+        replace: replacement capable of doing wildcard-like matching,
+                 parsing of match, and conditional replacements
+        xreplace: exact node replacement in expr tree; also capable of
+                  using matching rules
+        sympy.core.evalf.EvalfMixin.evalf: calculates the given formula to a desired level of precision
+
+        """
+        from .containers import Dict
+        from .symbol import Dummy, Symbol
+        from .numbers import _illegal
+
+        unordered = False
+        if len(args) == 1:
+
+            sequence = args[0]
+            if isinstance(sequence, set):
+                unordered = True
+            elif isinstance(sequence, (Dict, Mapping)):
+                unordered = True
+                sequence = sequence.items()
+            elif not iterable(sequence):
+                raise ValueError(filldedent("""
+                   When a single argument is passed to subs
+                   it should be a dictionary of old: new pairs or an iterable
+                   of (old, new) tuples."""))
+        elif len(args) == 2:
+            sequence = [args]
+        else:
+            raise ValueError("subs accepts either 1 or 2 arguments")
+
+        def sympify_old(old):
+            if isinstance(old, str):
+                # Use Symbol rather than parse_expr for old
+                return Symbol(old)
+            elif isinstance(old, type):
+                # Allow a type e.g. Function('f') or sin
+                return sympify(old, strict=False)
+            else:
+                return sympify(old, strict=True)
+
+        def sympify_new(new):
+            if isinstance(new, (str, type)):
+                # Allow a type or parse a string input
+                return sympify(new, strict=False)
+            else:
+                return sympify(new, strict=True)
+
+        sequence = [(sympify_old(s1), sympify_new(s2)) for s1, s2 in sequence]
+
+        # skip if there is no change
+        sequence = [(s1, s2) for s1, s2 in sequence if not _aresame(s1, s2)]
+
+        simultaneous = kwargs.pop('simultaneous', False)
+
+        if unordered:
+            from .sorting import _nodes, default_sort_key
+            sequence = dict(sequence)
+            # order so more complex items are first and items
+            # of identical complexity are ordered so
+            # f(x) < f(y) < x < y
+            # \___ 2 __/    \_1_/  <- number of nodes
+            #
+            # For more complex ordering use an unordered sequence.
+            k = list(ordered(sequence, default=False, keys=(
+                lambda x: -_nodes(x),
+                default_sort_key,
+                )))
+            sequence = [(k, sequence[k]) for k in k]
+            # do infinities first
+            if not simultaneous:
+                redo = [i for i, seq in enumerate(sequence) if seq[1] in _illegal]
+                for i in reversed(redo):
+                    sequence.insert(0, sequence.pop(i))
+
+        if simultaneous:  # XXX should this be the default for dict subs?
+            reps = {}
+            rv = self
+            kwargs['hack2'] = True
+            m = Dummy('subs_m')
+            for old, new in sequence:
+                com = new.is_commutative
+                if com is None:
+                    com = True
+                d = Dummy('subs_d', commutative=com)
+                # using d*m so Subs will be used on dummy variables
+                # in things like Derivative(f(x, y), x) in which x
+                # is both free and bound
+                rv = rv._subs(old, d*m, **kwargs)
+                if not isinstance(rv, Basic):
+                    break
+                reps[d] = new
+            reps[m] = S.One  # get rid of m
+            return rv.xreplace(reps)
+        else:
+            rv = self
+            for old, new in sequence:
+                rv = rv._subs(old, new, **kwargs)
+                if not isinstance(rv, Basic):
+                    break
+            return rv
+
+    @cacheit
+    def _subs(self, old, new, **hints):
+        """Substitutes an expression old -> new.
+
+        If self is not equal to old then _eval_subs is called.
+        If _eval_subs does not want to make any special replacement
+        then a None is received which indicates that the fallback
+        should be applied wherein a search for replacements is made
+        amongst the arguments of self.
+
+        >>> from sympy import Add
+        >>> from sympy.abc import x, y, z
+
+        Examples
+        ========
+
+        Add's _eval_subs knows how to target x + y in the following
+        so it makes the change:
+
+        >>> (x + y + z).subs(x + y, 1)
+        z + 1
+
+        Add's _eval_subs does not need to know how to find x + y in
+        the following:
+
+        >>> Add._eval_subs(z*(x + y) + 3, x + y, 1) is None
+        True
+
+        The returned None will cause the fallback routine to traverse the args and
+        pass the z*(x + y) arg to Mul where the change will take place and the
+        substitution will succeed:
+
+        >>> (z*(x + y) + 3).subs(x + y, 1)
+        z + 3
+
+        ** Developers Notes **
+
+        An _eval_subs routine for a class should be written if:
+
+            1) any arguments are not instances of Basic (e.g. bool, tuple);
+
+            2) some arguments should not be targeted (as in integration
+               variables);
+
+            3) if there is something other than a literal replacement
+               that should be attempted (as in Piecewise where the condition
+               may be updated without doing a replacement).
+
+        If it is overridden, here are some special cases that might arise:
+
+            1) If it turns out that no special change was made and all
+               the original sub-arguments should be checked for
+               replacements then None should be returned.
+
+            2) If it is necessary to do substitutions on a portion of
+               the expression then _subs should be called. _subs will
+               handle the case of any sub-expression being equal to old
+               (which usually would not be the case) while its fallback
+               will handle the recursion into the sub-arguments. For
+               example, after Add's _eval_subs removes some matching terms
+               it must process the remaining terms so it calls _subs
+               on each of the un-matched terms and then adds them
+               onto the terms previously obtained.
+
+           3) If the initial expression should remain unchanged then
+              the original expression should be returned. (Whenever an
+              expression is returned, modified or not, no further
+              substitution of old -> new is attempted.) Sum's _eval_subs
+              routine uses this strategy when a substitution is attempted
+              on any of its summation variables.
+        """
+
+        def fallback(self, old, new):
+            """
+            Try to replace old with new in any of self's arguments.
+            """
+            hit = False
+            args = list(self.args)
+            for i, arg in enumerate(args):
+                if not hasattr(arg, '_eval_subs'):
+                    continue
+                arg = arg._subs(old, new, **hints)
+                if not _aresame(arg, args[i]):
+                    hit = True
+                    args[i] = arg
+            if hit:
+                rv = self.func(*args)
+                hack2 = hints.get('hack2', False)
+                if hack2 and self.is_Mul and not rv.is_Mul:  # 2-arg hack
+                    coeff = S.One
+                    nonnumber = []
+                    for i in args:
+                        if i.is_Number:
+                            coeff *= i
+                        else:
+                            nonnumber.append(i)
+                    nonnumber = self.func(*nonnumber)
+                    if coeff is S.One:
+                        return nonnumber
+                    else:
+                        return self.func(coeff, nonnumber, evaluate=False)
+                return rv
+            return self
+
+        if _aresame(self, old):
+            return new
+
+        rv = self._eval_subs(old, new)
+        if rv is None:
+            rv = fallback(self, old, new)
+        return rv
+
+    def _eval_subs(self, old, new):
+        """Override this stub if you want to do anything more than
+        attempt a replacement of old with new in the arguments of self.
+
+        See also
+        ========
+
+        _subs
+        """
+        return None
+
+    def xreplace(self, rule):
+        """
+        Replace occurrences of objects within the expression.
+
+        Parameters
+        ==========
+
+        rule : dict-like
+            Expresses a replacement rule
+
+        Returns
+        =======
+
+        xreplace : the result of the replacement
+
+        Examples
+        ========
+
+        >>> from sympy import symbols, pi, exp
+        >>> x, y, z = symbols('x y z')
+        >>> (1 + x*y).xreplace({x: pi})
+        pi*y + 1
+        >>> (1 + x*y).xreplace({x: pi, y: 2})
+        1 + 2*pi
+
+        Replacements occur only if an entire node in the expression tree is
+        matched:
+
+        >>> (x*y + z).xreplace({x*y: pi})
+        z + pi
+        >>> (x*y*z).xreplace({x*y: pi})
+        x*y*z
+        >>> (2*x).xreplace({2*x: y, x: z})
+        y
+        >>> (2*2*x).xreplace({2*x: y, x: z})
+        4*z
+        >>> (x + y + 2).xreplace({x + y: 2})
+        x + y + 2
+        >>> (x + 2 + exp(x + 2)).xreplace({x + 2: y})
+        x + exp(y) + 2
+
+        xreplace does not differentiate between free and bound symbols. In the
+        following, subs(x, y) would not change x since it is a bound symbol,
+        but xreplace does:
+
+        >>> from sympy import Integral
+        >>> Integral(x, (x, 1, 2*x)).xreplace({x: y})
+        Integral(y, (y, 1, 2*y))
+
+        Trying to replace x with an expression raises an error:
+
+        >>> Integral(x, (x, 1, 2*x)).xreplace({x: 2*y}) # doctest: +SKIP
+        ValueError: Invalid limits given: ((2*y, 1, 4*y),)
+
+        See Also
+        ========
+        replace: replacement capable of doing wildcard-like matching,
+                 parsing of match, and conditional replacements
+        subs: substitution of subexpressions as defined by the objects
+              themselves.
+
+        """
+        value, _ = self._xreplace(rule)
+        return value
+
+    def _xreplace(self, rule):
+        """
+        Helper for xreplace. Tracks whether a replacement actually occurred.
+        """
+        if self in rule:
+            return rule[self], True
+        elif rule:
+            args = []
+            changed = False
+            for a in self.args:
+                _xreplace = getattr(a, '_xreplace', None)
+                if _xreplace is not None:
+                    a_xr = _xreplace(rule)
+                    args.append(a_xr[0])
+                    changed |= a_xr[1]
+                else:
+                    args.append(a)
+            args = tuple(args)
+            if changed:
+                return self.func(*args), True
+        return self, False
+
+    @cacheit
+    def has(self, *patterns):
+        """
+        Test whether any subexpression matches any of the patterns.
+
+        Examples
+        ========
+
+        >>> from sympy import sin
+        >>> from sympy.abc import x, y, z
+        >>> (x**2 + sin(x*y)).has(z)
+        False
+        >>> (x**2 + sin(x*y)).has(x, y, z)
+        True
+        >>> x.has(x)
+        True
+
+        Note ``has`` is a structural algorithm with no knowledge of
+        mathematics. Consider the following half-open interval:
+
+        >>> from sympy import Interval
+        >>> i = Interval.Lopen(0, 5); i
+        Interval.Lopen(0, 5)
+        >>> i.args
+        (0, 5, True, False)
+        >>> i.has(4)  # there is no "4" in the arguments
+        False
+        >>> i.has(0)  # there *is* a "0" in the arguments
+        True
+
+        Instead, use ``contains`` to determine whether a number is in the
+        interval or not:
+
+        >>> i.contains(4)
+        True
+        >>> i.contains(0)
+        False
+
+
+        Note that ``expr.has(*patterns)`` is exactly equivalent to
+        ``any(expr.has(p) for p in patterns)``. In particular, ``False`` is
+        returned when the list of patterns is empty.
+
+        >>> x.has()
+        False
+
+        """
+        return self._has(iterargs, *patterns)
+
+    def has_xfree(self, s: set[Basic]):
+        """Return True if self has any of the patterns in s as a
+        free argument, else False. This is like `Basic.has_free`
+        but this will only report exact argument matches.
+
+        Examples
+        ========
+
+        >>> from sympy import Function
+        >>> from sympy.abc import x, y
+        >>> f = Function('f')
+        >>> f(x).has_xfree({f})
+        False
+        >>> f(x).has_xfree({f(x)})
+        True
+        >>> f(x + 1).has_xfree({x})
+        True
+        >>> f(x + 1).has_xfree({x + 1})
+        True
+        >>> f(x + y + 1).has_xfree({x + 1})
+        False
+        """
+        # protect O(1) containment check by requiring:
+        if type(s) is not set:
+            raise TypeError('expecting set argument')
+        return any(a in s for a in iterfreeargs(self))
+
+    @cacheit
+    def has_free(self, *patterns):
+        """Return True if self has object(s) ``x`` as a free expression
+        else False.
+
+        Examples
+        ========
+
+        >>> from sympy import Integral, Function
+        >>> from sympy.abc import x, y
+        >>> f = Function('f')
+        >>> g = Function('g')
+        >>> expr = Integral(f(x), (f(x), 1, g(y)))
+        >>> expr.free_symbols
+        {y}
+        >>> expr.has_free(g(y))
+        True
+        >>> expr.has_free(*(x, f(x)))
+        False
+
+        This works for subexpressions and types, too:
+
+        >>> expr.has_free(g)
+        True
+        >>> (x + y + 1).has_free(y + 1)
+        True
+        """
+        if not patterns:
+            return False
+        p0 = patterns[0]
+        if len(patterns) == 1 and iterable(p0) and not isinstance(p0, Basic):
+            # Basic can contain iterables (though not non-Basic, ideally)
+            # but don't encourage mixed passing patterns
+            raise TypeError(filldedent('''
+                Expecting 1 or more Basic args, not a single
+                non-Basic iterable. Don't forget to unpack
+                iterables: `eq.has_free(*patterns)`'''))
+        # try quick test first
+        s = set(patterns)
+        rv = self.has_xfree(s)
+        if rv:
+            return rv
+        # now try matching through slower _has
+        return self._has(iterfreeargs, *patterns)
+
+    def _has(self, iterargs, *patterns):
+        # separate out types and unhashable objects
+        type_set = set()  # only types
+        p_set = set()  # hashable non-types
+        for p in patterns:
+            if isinstance(p, type) and issubclass(p, Basic):
+                type_set.add(p)
+                continue
+            if not isinstance(p, Basic):
+                try:
+                    p = _sympify(p)
+                except SympifyError:
+                    continue  # Basic won't have this in it
+            p_set.add(p)  # fails if object defines __eq__ but
+                          # doesn't define __hash__
+        types = tuple(type_set)   #
+        for i in iterargs(self):  #
+            if i in p_set:        # <--- here, too
+                return True
+            if isinstance(i, types):
+                return True
+
+        # use matcher if defined, e.g. operations defines
+        # matcher that checks for exact subset containment,
+        # (x + y + 1).has(x + 1) -> True
+        for i in p_set - type_set:  # types don't have matchers
+            if not hasattr(i, '_has_matcher'):
+                continue
+            match = i._has_matcher()
+            if any(match(arg) for arg in iterargs(self)):
+                return True
+
+        # no success
+        return False
+
+    def replace(self, query, value, map=False, simultaneous=True, exact=None):
+        """
+        Replace matching subexpressions of ``self`` with ``value``.
+
+        If ``map = True`` then also return the mapping {old: new} where ``old``
+        was a sub-expression found with query and ``new`` is the replacement
+        value for it. If the expression itself does not match the query, then
+        the returned value will be ``self.xreplace(map)`` otherwise it should
+        be ``self.subs(ordered(map.items()))``.
+
+        Traverses an expression tree and performs replacement of matching
+        subexpressions from the bottom to the top of the tree. The default
+        approach is to do the replacement in a simultaneous fashion so
+        changes made are targeted only once. If this is not desired or causes
+        problems, ``simultaneous`` can be set to False.
+
+        In addition, if an expression containing more than one Wild symbol
+        is being used to match subexpressions and the ``exact`` flag is None
+        it will be set to True so the match will only succeed if all non-zero
+        values are received for each Wild that appears in the match pattern.
+        Setting this to False accepts a match of 0; while setting it True
+        accepts all matches that have a 0 in them. See example below for
+        cautions.
+
+        The list of possible combinations of queries and replacement values
+        is listed below:
+
+        Examples
+        ========
+
+        Initial setup
+
+        >>> from sympy import log, sin, cos, tan, Wild, Mul, Add
+        >>> from sympy.abc import x, y
+        >>> f = log(sin(x)) + tan(sin(x**2))
+
+        1.1. type -> type
+            obj.replace(type, newtype)
+
+            When object of type ``type`` is found, replace it with the
+            result of passing its argument(s) to ``newtype``.
+
+            >>> f.replace(sin, cos)
+            log(cos(x)) + tan(cos(x**2))
+            >>> sin(x).replace(sin, cos, map=True)
+            (cos(x), {sin(x): cos(x)})
+            >>> (x*y).replace(Mul, Add)
+            x + y
+
+        1.2. type -> func
+            obj.replace(type, func)
+
+            When object of type ``type`` is found, apply ``func`` to its
+            argument(s). ``func`` must be written to handle the number
+            of arguments of ``type``.
+
+            >>> f.replace(sin, lambda arg: sin(2*arg))
+            log(sin(2*x)) + tan(sin(2*x**2))
+            >>> (x*y).replace(Mul, lambda *args: sin(2*Mul(*args)))
+            sin(2*x*y)
+
+        2.1. pattern -> expr
+            obj.replace(pattern(wild), expr(wild))
+
+            Replace subexpressions matching ``pattern`` with the expression
+            written in terms of the Wild symbols in ``pattern``.
+
+            >>> a, b = map(Wild, 'ab')
+            >>> f.replace(sin(a), tan(a))
+            log(tan(x)) + tan(tan(x**2))
+            >>> f.replace(sin(a), tan(a/2))
+            log(tan(x/2)) + tan(tan(x**2/2))
+            >>> f.replace(sin(a), a)
+            log(x) + tan(x**2)
+            >>> (x*y).replace(a*x, a)
+            y
+
+            Matching is exact by default when more than one Wild symbol
+            is used: matching fails unless the match gives non-zero
+            values for all Wild symbols:
+
+            >>> (2*x + y).replace(a*x + b, b - a)
+            y - 2
+            >>> (2*x).replace(a*x + b, b - a)
+            2*x
+
+            When set to False, the results may be non-intuitive:
+
+            >>> (2*x).replace(a*x + b, b - a, exact=False)
+            2/x
+
+        2.2. pattern -> func
+            obj.replace(pattern(wild), lambda wild: expr(wild))
+
+            All behavior is the same as in 2.1 but now a function in terms of
+            pattern variables is used rather than an expression:
+
+            >>> f.replace(sin(a), lambda a: sin(2*a))
+            log(sin(2*x)) + tan(sin(2*x**2))
+
+        3.1. func -> func
+            obj.replace(filter, func)
+
+            Replace subexpression ``e`` with ``func(e)`` if ``filter(e)``
+            is True.
+
+            >>> g = 2*sin(x**3)
+            >>> g.replace(lambda expr: expr.is_Number, lambda expr: expr**2)
+            4*sin(x**9)
+
+        The expression itself is also targeted by the query but is done in
+        such a fashion that changes are not made twice.
+
+            >>> e = x*(x*y + 1)
+            >>> e.replace(lambda x: x.is_Mul, lambda x: 2*x)
+            2*x*(2*x*y + 1)
+
+        When matching a single symbol, `exact` will default to True, but
+        this may or may not be the behavior that is desired:
+
+        Here, we want `exact=False`:
+
+        >>> from sympy import Function
+        >>> f = Function('f')
+        >>> e = f(1) + f(0)
+        >>> q = f(a), lambda a: f(a + 1)
+        >>> e.replace(*q, exact=False)
+        f(1) + f(2)
+        >>> e.replace(*q, exact=True)
+        f(0) + f(2)
+
+        But here, the nature of matching makes selecting
+        the right setting tricky:
+
+        >>> e = x**(1 + y)
+        >>> (x**(1 + y)).replace(x**(1 + a), lambda a: x**-a, exact=False)
+        x
+        >>> (x**(1 + y)).replace(x**(1 + a), lambda a: x**-a, exact=True)
+        x**(-x - y + 1)
+        >>> (x**y).replace(x**(1 + a), lambda a: x**-a, exact=False)
+        x
+        >>> (x**y).replace(x**(1 + a), lambda a: x**-a, exact=True)
+        x**(1 - y)
+
+        It is probably better to use a different form of the query
+        that describes the target expression more precisely:
+
+        >>> (1 + x**(1 + y)).replace(
+        ... lambda x: x.is_Pow and x.exp.is_Add and x.exp.args[0] == 1,
+        ... lambda x: x.base**(1 - (x.exp - 1)))
+        ...
+        x**(1 - y) + 1
+
+        See Also
+        ========
+
+        subs: substitution of subexpressions as defined by the objects
+              themselves.
+        xreplace: exact node replacement in expr tree; also capable of
+                  using matching rules
+
+        """
+
+        try:
+            query = _sympify(query)
+        except SympifyError:
+            pass
+        try:
+            value = _sympify(value)
+        except SympifyError:
+            pass
+        if isinstance(query, type):
+            _query = lambda expr: isinstance(expr, query)
+
+            if isinstance(value, type):
+                _value = lambda expr, result: value(*expr.args)
+            elif callable(value):
+                _value = lambda expr, result: value(*expr.args)
+            else:
+                raise TypeError(
+                    "given a type, replace() expects another "
+                    "type or a callable")
+        elif isinstance(query, Basic):
+            _query = lambda expr: expr.match(query)
+            if exact is None:
+                from .symbol import Wild
+                exact = (len(query.atoms(Wild)) > 1)
+
+            if isinstance(value, Basic):
+                if exact:
+                    _value = lambda expr, result: (value.subs(result)
+                        if all(result.values()) else expr)
+                else:
+                    _value = lambda expr, result: value.subs(result)
+            elif callable(value):
+                # match dictionary keys get the trailing underscore stripped
+                # from them and are then passed as keywords to the callable;
+                # if ``exact`` is True, only accept match if there are no null
+                # values amongst those matched.
+                if exact:
+                    _value = lambda expr, result: (value(**
+                        {str(k)[:-1]: v for k, v in result.items()})
+                        if all(val for val in result.values()) else expr)
+                else:
+                    _value = lambda expr, result: value(**
+                        {str(k)[:-1]: v for k, v in result.items()})
+            else:
+                raise TypeError(
+                    "given an expression, replace() expects "
+                    "another expression or a callable")
+        elif callable(query):
+            _query = query
+
+            if callable(value):
+                _value = lambda expr, result: value(expr)
+            else:
+                raise TypeError(
+                    "given a callable, replace() expects "
+                    "another callable")
+        else:
+            raise TypeError(
+                "first argument to replace() must be a "
+                "type, an expression or a callable")
+
+        def walk(rv, F):
+            """Apply ``F`` to args and then to result.
+            """
+            args = getattr(rv, 'args', None)
+            if args is not None:
+                if args:
+                    newargs = tuple([walk(a, F) for a in args])
+                    if args != newargs:
+                        rv = rv.func(*newargs)
+                        if simultaneous:
+                            # if rv is something that was already
+                            # matched (that was changed) then skip
+                            # applying F again
+                            for i, e in enumerate(args):
+                                if rv == e and e != newargs[i]:
+                                    return rv
+                rv = F(rv)
+            return rv
+
+        mapping = {}  # changes that took place
+
+        def rec_replace(expr):
+            result = _query(expr)
+            if result or result == {}:
+                v = _value(expr, result)
+                if v is not None and v != expr:
+                    if map:
+                        mapping[expr] = v
+                    expr = v
+            return expr
+
+        rv = walk(self, rec_replace)
+        return (rv, mapping) if map else rv
+
+    def find(self, query, group=False):
+        """Find all subexpressions matching a query."""
+        query = _make_find_query(query)
+        results = list(filter(query, _preorder_traversal(self)))
+
+        if not group:
+            return set(results)
+        else:
+            groups = {}
+
+            for result in results:
+                if result in groups:
+                    groups[result] += 1
+                else:
+                    groups[result] = 1
+
+            return groups
+
+    def count(self, query):
+        """Count the number of matching subexpressions."""
+        query = _make_find_query(query)
+        return sum(bool(query(sub)) for sub in _preorder_traversal(self))
+
+    def matches(self, expr, repl_dict=None, old=False):
+        """
+        Helper method for match() that looks for a match between Wild symbols
+        in self and expressions in expr.
+
+        Examples
+        ========
+
+        >>> from sympy import symbols, Wild, Basic
+        >>> a, b, c = symbols('a b c')
+        >>> x = Wild('x')
+        >>> Basic(a + x, x).matches(Basic(a + b, c)) is None
+        True
+        >>> Basic(a + x, x).matches(Basic(a + b + c, b + c))
+        {x_: b + c}
+        """
+        expr = sympify(expr)
+        if not isinstance(expr, self.__class__):
+            return None
+
+        if repl_dict is None:
+            repl_dict = {}
+        else:
+            repl_dict = repl_dict.copy()
+
+        if self == expr:
+            return repl_dict
+
+        if len(self.args) != len(expr.args):
+            return None
+
+        d = repl_dict  # already a copy
+        for arg, other_arg in zip(self.args, expr.args):
+            if arg == other_arg:
+                continue
+            if arg.is_Relational:
+                try:
+                    d = arg.xreplace(d).matches(other_arg, d, old=old)
+                except TypeError: # Should be InvalidComparisonError when introduced
+                    d = None
+            else:
+                    d = arg.xreplace(d).matches(other_arg, d, old=old)
+            if d is None:
+                return None
+        return d
+
+    def match(self, pattern, old=False):
+        """
+        Pattern matching.
+
+        Wild symbols match all.
+
+        Return ``None`` when expression (self) does not match
+        with pattern. Otherwise return a dictionary such that::
+
+          pattern.xreplace(self.match(pattern)) == self
+
+        Examples
+        ========
+
+        >>> from sympy import Wild, Sum
+        >>> from sympy.abc import x, y
+        >>> p = Wild("p")
+        >>> q = Wild("q")
+        >>> r = Wild("r")
+        >>> e = (x+y)**(x+y)
+        >>> e.match(p**p)
+        {p_: x + y}
+        >>> e.match(p**q)
+        {p_: x + y, q_: x + y}
+        >>> e = (2*x)**2
+        >>> e.match(p*q**r)
+        {p_: 4, q_: x, r_: 2}
+        >>> (p*q**r).xreplace(e.match(p*q**r))
+        4*x**2
+
+        Structurally bound symbols are ignored during matching:
+
+        >>> Sum(x, (x, 1, 2)).match(Sum(y, (y, 1, p)))
+        {p_: 2}
+
+        But they can be identified if desired:
+
+        >>> Sum(x, (x, 1, 2)).match(Sum(q, (q, 1, p)))
+        {p_: 2, q_: x}
+
+        The ``old`` flag will give the old-style pattern matching where
+        expressions and patterns are essentially solved to give the
+        match. Both of the following give None unless ``old=True``:
+
+        >>> (x - 2).match(p - x, old=True)
+        {p_: 2*x - 2}
+        >>> (2/x).match(p*x, old=True)
+        {p_: 2/x**2}
+
+        """
+        pattern = sympify(pattern)
+        # match non-bound symbols
+        canonical = lambda x: x if x.is_Symbol else x.as_dummy()
+        m = canonical(pattern).matches(canonical(self), old=old)
+        if m is None:
+            return m
+        from .symbol import Wild
+        from .function import WildFunction
+        from ..tensor.tensor import WildTensor, WildTensorIndex, WildTensorHead
+        wild = pattern.atoms(Wild, WildFunction, WildTensor, WildTensorIndex, WildTensorHead)
+        # sanity check
+        if set(m) - wild:
+            raise ValueError(filldedent('''
+            Some `matches` routine did not use a copy of repl_dict
+            and injected unexpected symbols. Report this as an
+            error at https://github.com/sympy/sympy/issues'''))
+        # now see if bound symbols were requested
+        bwild = wild - set(m)
+        if not bwild:
+            return m
+        # replace free-Wild symbols in pattern with match result
+        # so they will match but not be in the next match
+        wpat = pattern.xreplace(m)
+        # identify remaining bound wild
+        w = wpat.matches(self, old=old)
+        # add them to m
+        if w:
+            m.update(w)
+        # done
+        return m
+
+    def count_ops(self, visual=None):
+        """Wrapper for count_ops that returns the operation count."""
+        from .function import count_ops
+        return count_ops(self, visual)
+
+    def doit(self, **hints):
+        """Evaluate objects that are not evaluated by default like limits,
+        integrals, sums and products. All objects of this kind will be
+        evaluated recursively, unless some species were excluded via 'hints'
+        or unless the 'deep' hint was set to 'False'.
+
+        >>> from sympy import Integral
+        >>> from sympy.abc import x
+
+        >>> 2*Integral(x, x)
+        2*Integral(x, x)
+
+        >>> (2*Integral(x, x)).doit()
+        x**2
+
+        >>> (2*Integral(x, x)).doit(deep=False)
+        2*Integral(x, x)
+
+        """
+        if hints.get('deep', True):
+            terms = [term.doit(**hints) if isinstance(term, Basic) else term
+                                         for term in self.args]
+            return self.func(*terms)
+        else:
+            return self
+
+    def simplify(self, **kwargs):
+        """See the simplify function in sympy.simplify"""
+        from sympy.simplify.simplify import simplify
+        return simplify(self, **kwargs)
+
+    def refine(self, assumption=True):
+        """See the refine function in sympy.assumptions"""
+        from sympy.assumptions.refine import refine
+        return refine(self, assumption)
+
+    def _eval_derivative_n_times(self, s, n):
+        # This is the default evaluator for derivatives (as called by `diff`
+        # and `Derivative`), it will attempt a loop to derive the expression
+        # `n` times by calling the corresponding `_eval_derivative` method,
+        # while leaving the derivative unevaluated if `n` is symbolic.  This
+        # method should be overridden if the object has a closed form for its
+        # symbolic n-th derivative.
+        from .numbers import Integer
+        if isinstance(n, (int, Integer)):
+            obj = self
+            for i in range(n):
+                obj2 = obj._eval_derivative(s)
+                if obj == obj2 or obj2 is None:
+                    break
+                obj = obj2
+            return obj2
+        else:
+            return None
+
+    def rewrite(self, *args, deep=True, **hints):
+        """
+        Rewrite *self* using a defined rule.
+
+        Rewriting transforms an expression to another, which is mathematically
+        equivalent but structurally different. For example you can rewrite
+        trigonometric functions as complex exponentials or combinatorial
+        functions as gamma function.
+
+        This method takes a *pattern* and a *rule* as positional arguments.
+        *pattern* is optional parameter which defines the types of expressions
+        that will be transformed. If it is not passed, all possible expressions
+        will be rewritten. *rule* defines how the expression will be rewritten.
+
+        Parameters
+        ==========
+
+        args : Expr
+            A *rule*, or *pattern* and *rule*.
+            - *pattern* is a type or an iterable of types.
+            - *rule* can be any object.
+
+        deep : bool, optional
+            If ``True``, subexpressions are recursively transformed. Default is
+            ``True``.
+
+        Examples
+        ========
+
+        If *pattern* is unspecified, all possible expressions are transformed.
+
+        >>> from sympy import cos, sin, exp, I
+        >>> from sympy.abc import x
+        >>> expr = cos(x) + I*sin(x)
+        >>> expr.rewrite(exp)
+        exp(I*x)
+
+        Pattern can be a type or an iterable of types.
+
+        >>> expr.rewrite(sin, exp)
+        exp(I*x)/2 + cos(x) - exp(-I*x)/2
+        >>> expr.rewrite([cos,], exp)
+        exp(I*x)/2 + I*sin(x) + exp(-I*x)/2
+        >>> expr.rewrite([cos, sin], exp)
+        exp(I*x)
+
+        Rewriting behavior can be implemented by defining ``_eval_rewrite()``
+        method.
+
+        >>> from sympy import Expr, sqrt, pi
+        >>> class MySin(Expr):
+        ...     def _eval_rewrite(self, rule, args, **hints):
+        ...         x, = args
+        ...         if rule == cos:
+        ...             return cos(pi/2 - x, evaluate=False)
+        ...         if rule == sqrt:
+        ...             return sqrt(1 - cos(x)**2)
+        >>> MySin(MySin(x)).rewrite(cos)
+        cos(-cos(-x + pi/2) + pi/2)
+        >>> MySin(x).rewrite(sqrt)
+        sqrt(1 - cos(x)**2)
+
+        Defining ``_eval_rewrite_as_[...]()`` method is supported for backwards
+        compatibility reason. This may be removed in the future and using it is
+        discouraged.
+
+        >>> class MySin(Expr):
+        ...     def _eval_rewrite_as_cos(self, *args, **hints):
+        ...         x, = args
+        ...         return cos(pi/2 - x, evaluate=False)
+        >>> MySin(x).rewrite(cos)
+        cos(-x + pi/2)
+
+        """
+        if not args:
+            return self
+
+        hints.update(deep=deep)
+
+        pattern = args[:-1]
+        rule = args[-1]
+
+        # support old design by _eval_rewrite_as_[...] method
+        if isinstance(rule, str):
+            method = "_eval_rewrite_as_%s" % rule
+        elif hasattr(rule, "__name__"):
+            # rule is class or function
+            clsname = rule.__name__
+            method = "_eval_rewrite_as_%s" % clsname
+        else:
+            # rule is instance
+            clsname = rule.__class__.__name__
+            method = "_eval_rewrite_as_%s" % clsname
+
+        if pattern:
+            if iterable(pattern[0]):
+                pattern = pattern[0]
+            pattern = tuple(p for p in pattern if self.has(p))
+            if not pattern:
+                return self
+        # hereafter, empty pattern is interpreted as all pattern.
+
+        return self._rewrite(pattern, rule, method, **hints)
+
+    def _rewrite(self, pattern, rule, method, **hints):
+        deep = hints.pop('deep', True)
+        if deep:
+            args = [a._rewrite(pattern, rule, method, **hints)
+                    for a in self.args]
+        else:
+            args = self.args
+        if not pattern or any(isinstance(self, p) for p in pattern):
+            meth = getattr(self, method, None)
+            if meth is not None:
+                rewritten = meth(*args, **hints)
+            else:
+                rewritten = self._eval_rewrite(rule, args, **hints)
+            if rewritten is not None:
+                return rewritten
+        if not args:
+            return self
+        return self.func(*args)
+
+    def _eval_rewrite(self, rule, args, **hints):
+        return None
+
+    _constructor_postprocessor_mapping = {}  # type: ignore
+
+    @classmethod
+    def _exec_constructor_postprocessors(cls, obj):
+        # WARNING: This API is experimental.
+
+        # This is an experimental API that introduces constructor
+        # postprosessors for SymPy Core elements. If an argument of a SymPy
+        # expression has a `_constructor_postprocessor_mapping` attribute, it will
+        # be interpreted as a dictionary containing lists of postprocessing
+        # functions for matching expression node names.
+
+        clsname = obj.__class__.__name__
+        postprocessors = defaultdict(list)
+        for i in obj.args:
+            try:
+                postprocessor_mappings = (
+                    Basic._constructor_postprocessor_mapping[cls].items()
+                    for cls in type(i).mro()
+                    if cls in Basic._constructor_postprocessor_mapping
+                )
+                for k, v in chain.from_iterable(postprocessor_mappings):
+                    postprocessors[k].extend([j for j in v if j not in postprocessors[k]])
+            except TypeError:
+                pass
+
+        for f in postprocessors.get(clsname, []):
+            obj = f(obj)
+
+        return obj
+
+    def _sage_(self):
+        """
+        Convert *self* to a symbolic expression of SageMath.
+
+        This version of the method is merely a placeholder.
+        """
+        old_method = self._sage_
+        from sage.interfaces.sympy import sympy_init
+        sympy_init()  # may monkey-patch _sage_ method into self's class or superclasses
+        if old_method == self._sage_:
+            raise NotImplementedError('conversion to SageMath is not implemented')
+        else:
+            # call the freshly monkey-patched method
+            return self._sage_()
+
+    def could_extract_minus_sign(self):
+        return False  # see Expr.could_extract_minus_sign
+
+
+# For all Basic subclasses _prepare_class_assumptions is called by
+# Basic.__init_subclass__ but that method is not called for Basic itself so we
+# call the function here instead.
+_prepare_class_assumptions(Basic)
+
+
+class Atom(Basic):
+    """
+    A parent class for atomic things. An atom is an expression with no subexpressions.
+
+    Examples
+    ========
+
+    Symbol, Number, Rational, Integer, ...
+    But not: Add, Mul, Pow, ...
+    """
+
+    is_Atom = True
+
+    __slots__ = ()
+
+    def matches(self, expr, repl_dict=None, old=False):
+        if self == expr:
+            if repl_dict is None:
+                return {}
+            return repl_dict.copy()
+
+    def xreplace(self, rule, hack2=False):
+        return rule.get(self, self)
+
+    def doit(self, **hints):
+        return self
+
+    @classmethod
+    def class_key(cls):
+        return 2, 0, cls.__name__
+
+    @cacheit
+    def sort_key(self, order=None):
+        return self.class_key(), (1, (str(self),)), S.One.sort_key(), S.One
+
+    def _eval_simplify(self, **kwargs):
+        return self
+
+    @property
+    def _sorted_args(self):
+        # this is here as a safeguard against accidentally using _sorted_args
+        # on Atoms -- they cannot be rebuilt as atom.func(*atom._sorted_args)
+        # since there are no args. So the calling routine should be checking
+        # to see that this property is not called for Atoms.
+        raise AttributeError('Atoms have no args. It might be necessary'
+        ' to make a check for Atoms in the calling code.')
+
+
+def _aresame(a, b):
+    """Return True if a and b are structurally the same, else False.
+
+    Examples
+    ========
+
+    In SymPy (as in Python) two numbers compare the same if they
+    have the same underlying base-2 representation even though
+    they may not be the same type:
+
+    >>> from sympy import S
+    >>> 2.0 == S(2)
+    True
+    >>> 0.5 == S.Half
+    True
+
+    This routine was written to provide a query for such cases that
+    would give false when the types do not match:
+
+    >>> from sympy.core.basic import _aresame
+    >>> _aresame(S(2.0), S(2))
+    False
+
+    """
+    from .numbers import Number
+    from .function import AppliedUndef, UndefinedFunction as UndefFunc
+    if isinstance(a, Number) and isinstance(b, Number):
+        return a == b and a.__class__ == b.__class__
+    for i, j in zip_longest(_preorder_traversal(a), _preorder_traversal(b)):
+        if i != j or type(i) != type(j):
+            if ((isinstance(i, UndefFunc) and isinstance(j, UndefFunc)) or
+                (isinstance(i, AppliedUndef) and isinstance(j, AppliedUndef))):
+                if i.class_key() != j.class_key():
+                    return False
+            else:
+                return False
+    return True
+
+
+def _ne(a, b):
+    # use this as a second test after `a != b` if you want to make
+    # sure that things are truly equal, e.g.
+    # a, b = 0.5, S.Half
+    # a !=b or _ne(a, b) -> True
+    from .numbers import Number
+    # 0.5 == S.Half
+    if isinstance(a, Number) and isinstance(b, Number):
+        return a.__class__ != b.__class__
+
+
+def _atomic(e, recursive=False):
+    """Return atom-like quantities as far as substitution is
+    concerned: Derivatives, Functions and Symbols. Do not
+    return any 'atoms' that are inside such quantities unless
+    they also appear outside, too, unless `recursive` is True.
+
+    Examples
+    ========
+
+    >>> from sympy import Derivative, Function, cos
+    >>> from sympy.abc import x, y
+    >>> from sympy.core.basic import _atomic
+    >>> f = Function('f')
+    >>> _atomic(x + y)
+    {x, y}
+    >>> _atomic(x + f(y))
+    {x, f(y)}
+    >>> _atomic(Derivative(f(x), x) + cos(x) + y)
+    {y, cos(x), Derivative(f(x), x)}
+
+    """
+    pot = _preorder_traversal(e)
+    seen = set()
+    if isinstance(e, Basic):
+        free = getattr(e, "free_symbols", None)
+        if free is None:
+            return {e}
+    else:
+        return set()
+    from .symbol import Symbol
+    from .function import Derivative, Function
+    atoms = set()
+    for p in pot:
+        if p in seen:
+            pot.skip()
+            continue
+        seen.add(p)
+        if isinstance(p, Symbol) and p in free:
+            atoms.add(p)
+        elif isinstance(p, (Derivative, Function)):
+            if not recursive:
+                pot.skip()
+            atoms.add(p)
+    return atoms
+
+
+def _make_find_query(query):
+    """Convert the argument of Basic.find() into a callable"""
+    try:
+        query = _sympify(query)
+    except SympifyError:
+        pass
+    if isinstance(query, type):
+        return lambda expr: isinstance(expr, query)
+    elif isinstance(query, Basic):
+        return lambda expr: expr.match(query) is not None
+    return query
+
+# Delayed to avoid cyclic import
+from .singleton import S
+from .traversal import (preorder_traversal as _preorder_traversal,
+   iterargs, iterfreeargs)
+
+preorder_traversal = deprecated(
+    """
+    Using preorder_traversal from the sympy.core.basic submodule is
+    deprecated.
+
+    Instead, use preorder_traversal from the top-level sympy namespace, like
+
+        sympy.preorder_traversal
+    """,
+    deprecated_since_version="1.10",
+    active_deprecations_target="deprecated-traversal-functions-moved",
+)(_preorder_traversal)

env-llmeval/lib/python3.10/site-packages/sympy/core/cache.py

@@ -0,0 +1,210 @@
+""" Caching facility for SymPy """
+from importlib import import_module
+from typing import Callable
+
+class _cache(list):
+    """ List of cached functions """
+
+    def print_cache(self):
+        """print cache info"""
+
+        for item in self:
+            name = item.__name__
+            myfunc = item
+            while hasattr(myfunc, '__wrapped__'):
+                if hasattr(myfunc, 'cache_info'):
+                    info = myfunc.cache_info()
+                    break
+                else:
+                    myfunc = myfunc.__wrapped__
+            else:
+                info = None
+
+            print(name, info)
+
+    def clear_cache(self):
+        """clear cache content"""
+        for item in self:
+            myfunc = item
+            while hasattr(myfunc, '__wrapped__'):
+                if hasattr(myfunc, 'cache_clear'):
+                    myfunc.cache_clear()
+                    break
+                else:
+                    myfunc = myfunc.__wrapped__
+
+
+# global cache registry:
+CACHE = _cache()
+# make clear and print methods available
+print_cache = CACHE.print_cache
+clear_cache = CACHE.clear_cache
+
+from functools import lru_cache, wraps
+
+def __cacheit(maxsize):
+    """caching decorator.
+
+        important: the result of cached function must be *immutable*
+
+
+        Examples
+        ========
+
+        >>> from sympy import cacheit
+        >>> @cacheit
+        ... def f(a, b):
+        ...    return a+b
+
+        >>> @cacheit
+        ... def f(a, b): # noqa: F811
+        ...    return [a, b] # <-- WRONG, returns mutable object
+
+        to force cacheit to check returned results mutability and consistency,
+        set environment variable SYMPY_USE_CACHE to 'debug'
+    """
+    def func_wrapper(func):
+        cfunc = lru_cache(maxsize, typed=True)(func)
+
+        @wraps(func)
+        def wrapper(*args, **kwargs):
+            try:
+                retval = cfunc(*args, **kwargs)
+            except TypeError as e:
+                if not e.args or not e.args[0].startswith('unhashable type:'):
+                    raise
+                retval = func(*args, **kwargs)
+            return retval
+
+        wrapper.cache_info = cfunc.cache_info
+        wrapper.cache_clear = cfunc.cache_clear
+
+        CACHE.append(wrapper)
+        return wrapper
+
+    return func_wrapper
+########################################
+
+
+def __cacheit_nocache(func):
+    return func
+
+
+def __cacheit_debug(maxsize):
+    """cacheit + code to check cache consistency"""
+    def func_wrapper(func):
+        cfunc = __cacheit(maxsize)(func)
+
+        @wraps(func)
+        def wrapper(*args, **kw_args):
+            # always call function itself and compare it with cached version
+            r1 = func(*args, **kw_args)
+            r2 = cfunc(*args, **kw_args)
+
+            # try to see if the result is immutable
+            #
+            # this works because:
+            #
+            # hash([1,2,3])         -> raise TypeError
+            # hash({'a':1, 'b':2})  -> raise TypeError
+            # hash((1,[2,3]))       -> raise TypeError
+            #
+            # hash((1,2,3))         -> just computes the hash
+            hash(r1), hash(r2)
+
+            # also see if returned values are the same
+            if r1 != r2:
+                raise RuntimeError("Returned values are not the same")
+            return r1
+        return wrapper
+    return func_wrapper
+
+
+def _getenv(key, default=None):
+    from os import getenv
+    return getenv(key, default)
+
+# SYMPY_USE_CACHE=yes/no/debug
+USE_CACHE = _getenv('SYMPY_USE_CACHE', 'yes').lower()
+# SYMPY_CACHE_SIZE=some_integer/None
+# special cases :
+#  SYMPY_CACHE_SIZE=0    -> No caching
+#  SYMPY_CACHE_SIZE=None -> Unbounded caching
+scs = _getenv('SYMPY_CACHE_SIZE', '1000')
+if scs.lower() == 'none':
+    SYMPY_CACHE_SIZE = None
+else:
+    try:
+        SYMPY_CACHE_SIZE = int(scs)
+    except ValueError:
+        raise RuntimeError(
+            'SYMPY_CACHE_SIZE must be a valid integer or None. ' + \
+            'Got: %s' % SYMPY_CACHE_SIZE)
+
+if USE_CACHE == 'no':
+    cacheit = __cacheit_nocache
+elif USE_CACHE == 'yes':
+    cacheit = __cacheit(SYMPY_CACHE_SIZE)
+elif USE_CACHE == 'debug':
+    cacheit = __cacheit_debug(SYMPY_CACHE_SIZE)   # a lot slower
+else:
+    raise RuntimeError(
+        'unrecognized value for SYMPY_USE_CACHE: %s' % USE_CACHE)
+
+
+def cached_property(func):
+    '''Decorator to cache property method'''
+    attrname = '__' + func.__name__
+    _cached_property_sentinel = object()
+    def propfunc(self):
+        val = getattr(self, attrname, _cached_property_sentinel)
+        if val is _cached_property_sentinel:
+            val = func(self)
+            setattr(self, attrname, val)
+        return val
+    return property(propfunc)
+
+
+def lazy_function(module : str, name : str) -> Callable:
+    """Create a lazy proxy for a function in a module.
+
+    The module containing the function is not imported until the function is used.
+
+    """
+    func = None
+
+    def _get_function():
+        nonlocal func
+        if func is None:
+            func = getattr(import_module(module), name)
+        return func
+
+    # The metaclass is needed so that help() shows the docstring
+    class LazyFunctionMeta(type):
+        @property
+        def __doc__(self):
+            docstring = _get_function().__doc__
+            docstring += f"\n\nNote: this is a {self.__class__.__name__} wrapper of '{module}.{name}'"
+            return docstring
+
+    class LazyFunction(metaclass=LazyFunctionMeta):
+        def __call__(self, *args, **kwargs):
+            # inline get of function for performance gh-23832
+            nonlocal func
+            if func is None:
+                func = getattr(import_module(module), name)
+            return func(*args, **kwargs)
+
+        @property
+        def __doc__(self):
+            docstring = _get_function().__doc__
+            docstring += f"\n\nNote: this is a {self.__class__.__name__} wrapper of '{module}.{name}'"
+            return docstring
+
+        def __str__(self):
+            return _get_function().__str__()
+
+        def __repr__(self):
+            return f"<{__class__.__name__} object at 0x{id(self):x}>: wrapping '{module}.{name}'"
+
+    return LazyFunction()

env-llmeval/lib/python3.10/site-packages/sympy/core/compatibility.py

@@ -0,0 +1,35 @@
+"""
+.. deprecated:: 1.10
+
+   ``sympy.core.compatibility`` is deprecated. See
+   :ref:`sympy-core-compatibility`.
+
+Reimplementations of constructs introduced in later versions of Python than
+we support. Also some functions that are needed SymPy-wide and are located
+here for easy import.
+
+"""
+
+
+from sympy.utilities.exceptions import sympy_deprecation_warning
+
+sympy_deprecation_warning("""
+The sympy.core.compatibility submodule is deprecated.
+
+This module was only ever intended for internal use. Some of the functions
+that were in this module are available from the top-level SymPy namespace,
+i.e.,
+
+    from sympy import ordered, default_sort_key
+
+The remaining were only intended for internal SymPy use and should not be used
+by user code.
+""",
+                          deprecated_since_version="1.10",
+                          active_deprecations_target="deprecated-sympy-core-compatibility",
+                          )
+
+
+from .sorting import ordered, _nodes, default_sort_key # noqa:F401
+from sympy.utilities.misc import as_int as _as_int # noqa:F401
+from sympy.utilities.iterables import iterable, is_sequence, NotIterable # noqa:F401

env-llmeval/lib/python3.10/site-packages/sympy/core/containers.py

@@ -0,0 +1,410 @@
+"""Module for SymPy containers
+
+    (SymPy objects that store other SymPy objects)
+
+    The containers implemented in this module are subclassed to Basic.
+    They are supposed to work seamlessly within the SymPy framework.
+"""
+
+from collections import OrderedDict
+from collections.abc import MutableSet
+from typing import Any, Callable
+
+from .basic import Basic
+from .sorting import default_sort_key, ordered
+from .sympify import _sympify, sympify, _sympy_converter, SympifyError
+from sympy.core.kind import Kind
+from sympy.utilities.iterables import iterable
+from sympy.utilities.misc import as_int
+
+
+class Tuple(Basic):
+    """
+    Wrapper around the builtin tuple object.
+
+    Explanation
+    ===========
+
+    The Tuple is a subclass of Basic, so that it works well in the
+    SymPy framework.  The wrapped tuple is available as self.args, but
+    you can also access elements or slices with [:] syntax.
+
+    Parameters
+    ==========
+
+    sympify : bool
+        If ``False``, ``sympify`` is not called on ``args``. This
+        can be used for speedups for very large tuples where the
+        elements are known to already be SymPy objects.
+
+    Examples
+    ========
+
+    >>> from sympy import Tuple, symbols
+    >>> a, b, c, d = symbols('a b c d')
+    >>> Tuple(a, b, c)[1:]
+    (b, c)
+    >>> Tuple(a, b, c).subs(a, d)
+    (d, b, c)
+
+    """
+
+    def __new__(cls, *args, **kwargs):
+        if kwargs.get('sympify', True):
+            args = (sympify(arg) for arg in args)
+        obj = Basic.__new__(cls, *args)
+        return obj
+
+    def __getitem__(self, i):
+        if isinstance(i, slice):
+            indices = i.indices(len(self))
+            return Tuple(*(self.args[j] for j in range(*indices)))
+        return self.args[i]
+
+    def __len__(self):
+        return len(self.args)
+
+    def __contains__(self, item):
+        return item in self.args
+
+    def __iter__(self):
+        return iter(self.args)
+
+    def __add__(self, other):
+        if isinstance(other, Tuple):
+            return Tuple(*(self.args + other.args))
+        elif isinstance(other, tuple):
+            return Tuple(*(self.args + other))
+        else:
+            return NotImplemented
+
+    def __radd__(self, other):
+        if isinstance(other, Tuple):
+            return Tuple(*(other.args + self.args))
+        elif isinstance(other, tuple):
+            return Tuple(*(other + self.args))
+        else:
+            return NotImplemented
+
+    def __mul__(self, other):
+        try:
+            n = as_int(other)
+        except ValueError:
+            raise TypeError("Can't multiply sequence by non-integer of type '%s'" % type(other))
+        return self.func(*(self.args*n))
+
+    __rmul__ = __mul__
+
+    def __eq__(self, other):
+        if isinstance(other, Basic):
+            return super().__eq__(other)
+        return self.args == other
+
+    def __ne__(self, other):
+        if isinstance(other, Basic):
+            return super().__ne__(other)
+        return self.args != other
+
+    def __hash__(self):
+        return hash(self.args)
+
+    def _to_mpmath(self, prec):
+        return tuple(a._to_mpmath(prec) for a in self.args)
+
+    def __lt__(self, other):
+        return _sympify(self.args < other.args)
+
+    def __le__(self, other):
+        return _sympify(self.args <= other.args)
+
+    # XXX: Basic defines count() as something different, so we can't
+    # redefine it here. Originally this lead to cse() test failure.
+    def tuple_count(self, value) -> int:
+        """Return number of occurrences of value."""
+        return self.args.count(value)
+
+    def index(self, value, start=None, stop=None):
+        """Searches and returns the first index of the value."""
+        # XXX: One would expect:
+        #
+        # return self.args.index(value, start, stop)
+        #
+        # here. Any trouble with that? Yes:
+        #
+        # >>> (1,).index(1, None, None)
+        # Traceback (most recent call last):
+        #   File "<stdin>", line 1, in <module>
+        # TypeError: slice indices must be integers or None or have an __index__ method
+        #
+        # See: http://bugs.python.org/issue13340
+
+        if start is None and stop is None:
+            return self.args.index(value)
+        elif stop is None:
+            return self.args.index(value, start)
+        else:
+            return self.args.index(value, start, stop)
+
+    @property
+    def kind(self):
+        """
+        The kind of a Tuple instance.
+
+        The kind of a Tuple is always of :class:`TupleKind` but
+        parametrised by the number of elements and the kind of each element.
+
+        Examples
+        ========
+
+        >>> from sympy import Tuple, Matrix
+        >>> Tuple(1, 2).kind
+        TupleKind(NumberKind, NumberKind)
+        >>> Tuple(Matrix([1, 2]), 1).kind
+        TupleKind(MatrixKind(NumberKind), NumberKind)
+        >>> Tuple(1, 2).kind.element_kind
+        (NumberKind, NumberKind)
+
+        See Also
+        ========
+
+        sympy.matrices.common.MatrixKind
+        sympy.core.kind.NumberKind
+        """
+        return TupleKind(*(i.kind for i in self.args))
+
+_sympy_converter[tuple] = lambda tup: Tuple(*tup)
+
+
+
+
+
+def tuple_wrapper(method):
+    """
+    Decorator that converts any tuple in the function arguments into a Tuple.
+
+    Explanation
+    ===========
+
+    The motivation for this is to provide simple user interfaces.  The user can
+    call a function with regular tuples in the argument, and the wrapper will
+    convert them to Tuples before handing them to the function.
+
+    Explanation
+    ===========
+
+    >>> from sympy.core.containers import tuple_wrapper
+    >>> def f(*args):
+    ...    return args
+    >>> g = tuple_wrapper(f)
+
+    The decorated function g sees only the Tuple argument:
+
+    >>> g(0, (1, 2), 3)
+    (0, (1, 2), 3)
+
+    """
+    def wrap_tuples(*args, **kw_args):
+        newargs = []
+        for arg in args:
+            if isinstance(arg, tuple):
+                newargs.append(Tuple(*arg))
+            else:
+                newargs.append(arg)
+        return method(*newargs, **kw_args)
+    return wrap_tuples
+
+
+class Dict(Basic):
+    """
+    Wrapper around the builtin dict object.
+
+    Explanation
+    ===========
+
+    The Dict is a subclass of Basic, so that it works well in the
+    SymPy framework.  Because it is immutable, it may be included
+    in sets, but its values must all be given at instantiation and
+    cannot be changed afterwards.  Otherwise it behaves identically
+    to the Python dict.
+
+    Examples
+    ========
+
+    >>> from sympy import Dict, Symbol
+
+    >>> D = Dict({1: 'one', 2: 'two'})
+    >>> for key in D:
+    ...    if key == 1:
+    ...        print('%s %s' % (key, D[key]))
+    1 one
+
+    The args are sympified so the 1 and 2 are Integers and the values
+    are Symbols. Queries automatically sympify args so the following work:
+
+    >>> 1 in D
+    True
+    >>> D.has(Symbol('one')) # searches keys and values
+    True
+    >>> 'one' in D # not in the keys
+    False
+    >>> D[1]
+    one
+
+    """
+
+    def __new__(cls, *args):
+        if len(args) == 1 and isinstance(args[0], (dict, Dict)):
+            items = [Tuple(k, v) for k, v in args[0].items()]
+        elif iterable(args) and all(len(arg) == 2 for arg in args):
+            items = [Tuple(k, v) for k, v in args]
+        else:
+            raise TypeError('Pass Dict args as Dict((k1, v1), ...) or Dict({k1: v1, ...})')
+        elements = frozenset(items)
+        obj = Basic.__new__(cls, *ordered(items))
+        obj.elements = elements
+        obj._dict = dict(items)  # In case Tuple decides it wants to sympify
+        return obj
+
+    def __getitem__(self, key):
+        """x.__getitem__(y) <==> x[y]"""
+        try:
+            key = _sympify(key)
+        except SympifyError:
+            raise KeyError(key)
+
+        return self._dict[key]
+
+    def __setitem__(self, key, value):
+        raise NotImplementedError("SymPy Dicts are Immutable")
+
+    def items(self):
+        '''Returns a set-like object providing a view on dict's items.
+        '''
+        return self._dict.items()
+
+    def keys(self):
+        '''Returns the list of the dict's keys.'''
+        return self._dict.keys()
+
+    def values(self):
+        '''Returns the list of the dict's values.'''
+        return self._dict.values()
+
+    def __iter__(self):
+        '''x.__iter__() <==> iter(x)'''
+        return iter(self._dict)
+
+    def __len__(self):
+        '''x.__len__() <==> len(x)'''
+        return self._dict.__len__()
+
+    def get(self, key, default=None):
+        '''Returns the value for key if the key is in the dictionary.'''
+        try:
+            key = _sympify(key)
+        except SympifyError:
+            return default
+        return self._dict.get(key, default)
+
+    def __contains__(self, key):
+        '''D.__contains__(k) -> True if D has a key k, else False'''
+        try:
+            key = _sympify(key)
+        except SympifyError:
+            return False
+        return key in self._dict
+
+    def __lt__(self, other):
+        return _sympify(self.args < other.args)
+
+    @property
+    def _sorted_args(self):
+        return tuple(sorted(self.args, key=default_sort_key))
+
+    def __eq__(self, other):
+        if isinstance(other, dict):
+            return self == Dict(other)
+        return super().__eq__(other)
+
+    __hash__ : Callable[[Basic], Any] = Basic.__hash__
+
+# this handles dict, defaultdict, OrderedDict
+_sympy_converter[dict] = lambda d: Dict(*d.items())
+
+class OrderedSet(MutableSet):
+    def __init__(self, iterable=None):
+        if iterable:
+            self.map = OrderedDict((item, None) for item in iterable)
+        else:
+            self.map = OrderedDict()
+
+    def __len__(self):
+        return len(self.map)
+
+    def __contains__(self, key):
+        return key in self.map
+
+    def add(self, key):
+        self.map[key] = None
+
+    def discard(self, key):
+        self.map.pop(key)
+
+    def pop(self, last=True):
+        return self.map.popitem(last=last)[0]
+
+    def __iter__(self):
+        yield from self.map.keys()
+
+    def __repr__(self):
+        if not self.map:
+            return '%s()' % (self.__class__.__name__,)
+        return '%s(%r)' % (self.__class__.__name__, list(self.map.keys()))
+
+    def intersection(self, other):
+        return self.__class__([val for val in self if val in other])
+
+    def difference(self, other):
+        return self.__class__([val for val in self if val not in other])
+
+    def update(self, iterable):
+        for val in iterable:
+            self.add(val)
+
+class TupleKind(Kind):
+    """
+    TupleKind is a subclass of Kind, which is used to define Kind of ``Tuple``.
+
+    Parameters of TupleKind will be kinds of all the arguments in Tuples, for
+    example
+
+    Parameters
+    ==========
+
+    args : tuple(element_kind)
+       element_kind is kind of element.
+       args is tuple of kinds of element
+
+    Examples
+    ========
+
+    >>> from sympy import Tuple
+    >>> Tuple(1, 2).kind
+    TupleKind(NumberKind, NumberKind)
+    >>> Tuple(1, 2).kind.element_kind
+    (NumberKind, NumberKind)
+
+    See Also
+    ========
+
+    sympy.core.kind.NumberKind
+    MatrixKind
+    sympy.sets.sets.SetKind
+    """
+    def __new__(cls, *args):
+        obj = super().__new__(cls, *args)
+        obj.element_kind = args
+        return obj
+
+    def __repr__(self):
+        return "TupleKind{}".format(self.element_kind)

env-llmeval/lib/python3.10/site-packages/sympy/core/core.py

@@ -0,0 +1,63 @@
+""" The core's core. """
+from __future__ import annotations
+
+
+# used for canonical ordering of symbolic sequences
+# via __cmp__ method:
+# FIXME this is *so* irrelevant and outdated!
+ordering_of_classes = [
+    # singleton numbers
+    'Zero', 'One', 'Half', 'Infinity', 'NaN', 'NegativeOne', 'NegativeInfinity',
+    # numbers
+    'Integer', 'Rational', 'Float',
+    # singleton symbols
+    'Exp1', 'Pi', 'ImaginaryUnit',
+    # symbols
+    'Symbol', 'Wild', 'Temporary',
+    # arithmetic operations
+    'Pow', 'Mul', 'Add',
+    # function values
+    'Derivative', 'Integral',
+    # defined singleton functions
+    'Abs', 'Sign', 'Sqrt',
+    'Floor', 'Ceiling',
+    'Re', 'Im', 'Arg',
+    'Conjugate',
+    'Exp', 'Log',
+    'Sin', 'Cos', 'Tan', 'Cot', 'ASin', 'ACos', 'ATan', 'ACot',
+    'Sinh', 'Cosh', 'Tanh', 'Coth', 'ASinh', 'ACosh', 'ATanh', 'ACoth',
+    'RisingFactorial', 'FallingFactorial',
+    'factorial', 'binomial',
+    'Gamma', 'LowerGamma', 'UpperGamma', 'PolyGamma',
+    'Erf',
+    # special polynomials
+    'Chebyshev', 'Chebyshev2',
+    # undefined functions
+    'Function', 'WildFunction',
+    # anonymous functions
+    'Lambda',
+    # Landau O symbol
+    'Order',
+    # relational operations
+    'Equality', 'Unequality', 'StrictGreaterThan', 'StrictLessThan',
+    'GreaterThan', 'LessThan',
+]
+
+
+class Registry:
+    """
+    Base class for registry objects.
+
+    Registries map a name to an object using attribute notation. Registry
+    classes behave singletonically: all their instances share the same state,
+    which is stored in the class object.
+
+    All subclasses should set `__slots__ = ()`.
+    """
+    __slots__ = ()
+
+    def __setattr__(self, name, obj):
+        setattr(self.__class__, name, obj)
+
+    def __delattr__(self, name):
+        delattr(self.__class__, name)

env-llmeval/lib/python3.10/site-packages/sympy/core/coreerrors.py

@@ -0,0 +1,9 @@
+"""Definitions of common exceptions for :mod:`sympy.core` module. """
+
+
+class BaseCoreError(Exception):
+    """Base class for core related exceptions. """
+
+
+class NonCommutativeExpression(BaseCoreError):
+    """Raised when expression didn't have commutative property. """

env-llmeval/lib/python3.10/site-packages/sympy/core/evalf.py

@@ -0,0 +1,1801 @@
+"""
+Adaptive numerical evaluation of SymPy expressions, using mpmath
+for mathematical functions.
+"""
+from __future__ import annotations
+from typing import Tuple as tTuple, Optional, Union as tUnion, Callable, List, Dict as tDict, Type, TYPE_CHECKING, \
+    Any, overload
+
+import math
+
+import mpmath.libmp as libmp
+from mpmath import (
+    make_mpc, make_mpf, mp, mpc, mpf, nsum, quadts, quadosc, workprec)
+from mpmath import inf as mpmath_inf
+from mpmath.libmp import (from_int, from_man_exp, from_rational, fhalf,
+        fnan, finf, fninf, fnone, fone, fzero, mpf_abs, mpf_add,
+        mpf_atan, mpf_atan2, mpf_cmp, mpf_cos, mpf_e, mpf_exp, mpf_log, mpf_lt,
+        mpf_mul, mpf_neg, mpf_pi, mpf_pow, mpf_pow_int, mpf_shift, mpf_sin,
+        mpf_sqrt, normalize, round_nearest, to_int, to_str)
+from mpmath.libmp import bitcount as mpmath_bitcount
+from mpmath.libmp.backend import MPZ
+from mpmath.libmp.libmpc import _infs_nan
+from mpmath.libmp.libmpf import dps_to_prec, prec_to_dps
+
+from .sympify import sympify
+from .singleton import S
+from sympy.external.gmpy import SYMPY_INTS
+from sympy.utilities.iterables import is_sequence
+from sympy.utilities.lambdify import lambdify
+from sympy.utilities.misc import as_int
+
+if TYPE_CHECKING:
+    from sympy.core.expr import Expr
+    from sympy.core.add import Add
+    from sympy.core.mul import Mul
+    from sympy.core.power import Pow
+    from sympy.core.symbol import Symbol
+    from sympy.integrals.integrals import Integral
+    from sympy.concrete.summations import Sum
+    from sympy.concrete.products import Product
+    from sympy.functions.elementary.exponential import exp, log
+    from sympy.functions.elementary.complexes import Abs, re, im
+    from sympy.functions.elementary.integers import ceiling, floor
+    from sympy.functions.elementary.trigonometric import atan
+    from .numbers import Float, Rational, Integer, AlgebraicNumber, Number
+
+LG10 = math.log(10, 2)
+rnd = round_nearest
+
+
+def bitcount(n):
+    """Return smallest integer, b, such that |n|/2**b < 1.
+    """
+    return mpmath_bitcount(abs(int(n)))
+
+# Used in a few places as placeholder values to denote exponents and
+# precision levels, e.g. of exact numbers. Must be careful to avoid
+# passing these to mpmath functions or returning them in final results.
+INF = float(mpmath_inf)
+MINUS_INF = float(-mpmath_inf)
+
+# ~= 100 digits. Real men set this to INF.
+DEFAULT_MAXPREC = 333
+
+
+class PrecisionExhausted(ArithmeticError):
+    pass
+
+#----------------------------------------------------------------------------#
+#                                                                            #
+#              Helper functions for arithmetic and complex parts             #
+#                                                                            #
+#----------------------------------------------------------------------------#
+
+"""
+An mpf value tuple is a tuple of integers (sign, man, exp, bc)
+representing a floating-point number: [1, -1][sign]*man*2**exp where
+sign is 0 or 1 and bc should correspond to the number of bits used to
+represent the mantissa (man) in binary notation, e.g.
+"""
+MPF_TUP = tTuple[int, int, int, int]  # mpf value tuple
+
+"""
+Explanation
+===========
+
+>>> from sympy.core.evalf import bitcount
+>>> sign, man, exp, bc = 0, 5, 1, 3
+>>> n = [1, -1][sign]*man*2**exp
+>>> n, bitcount(man)
+(10, 3)
+
+A temporary result is a tuple (re, im, re_acc, im_acc) where
+re and im are nonzero mpf value tuples representing approximate
+numbers, or None to denote exact zeros.
+
+re_acc, im_acc are integers denoting log2(e) where e is the estimated
+relative accuracy of the respective complex part, but may be anything
+if the corresponding complex part is None.
+
+"""
+TMP_RES = Any  # temporary result, should be some variant of
+# tUnion[tTuple[Optional[MPF_TUP], Optional[MPF_TUP],
+#               Optional[int], Optional[int]],
+#        'ComplexInfinity']
+# but mypy reports error because it doesn't know as we know
+# 1. re and re_acc are either both None or both MPF_TUP
+# 2. sometimes the result can't be zoo
+
+# type of the "options" parameter in internal evalf functions
+OPT_DICT = tDict[str, Any]
+
+
+def fastlog(x: Optional[MPF_TUP]) -> tUnion[int, Any]:
+    """Fast approximation of log2(x) for an mpf value tuple x.
+
+    Explanation
+    ===========
+
+    Calculated as exponent + width of mantissa. This is an
+    approximation for two reasons: 1) it gives the ceil(log2(abs(x)))
+    value and 2) it is too high by 1 in the case that x is an exact
+    power of 2. Although this is easy to remedy by testing to see if
+    the odd mpf mantissa is 1 (indicating that one was dealing with
+    an exact power of 2) that would decrease the speed and is not
+    necessary as this is only being used as an approximation for the
+    number of bits in x. The correct return value could be written as
+    "x[2] + (x[3] if x[1] != 1 else 0)".
+        Since mpf tuples always have an odd mantissa, no check is done
+    to see if the mantissa is a multiple of 2 (in which case the
+    result would be too large by 1).
+
+    Examples
+    ========
+
+    >>> from sympy import log
+    >>> from sympy.core.evalf import fastlog, bitcount
+    >>> s, m, e = 0, 5, 1
+    >>> bc = bitcount(m)
+    >>> n = [1, -1][s]*m*2**e
+    >>> n, (log(n)/log(2)).evalf(2), fastlog((s, m, e, bc))
+    (10, 3.3, 4)
+    """
+
+    if not x or x == fzero:
+        return MINUS_INF
+    return x[2] + x[3]
+
+
+def pure_complex(v: 'Expr', or_real=False) -> tuple['Number', 'Number'] | None:
+    """Return a and b if v matches a + I*b where b is not zero and
+    a and b are Numbers, else None. If `or_real` is True then 0 will
+    be returned for `b` if `v` is a real number.
+
+    Examples
+    ========
+
+    >>> from sympy.core.evalf import pure_complex
+    >>> from sympy import sqrt, I, S
+    >>> a, b, surd = S(2), S(3), sqrt(2)
+    >>> pure_complex(a)
+    >>> pure_complex(a, or_real=True)
+    (2, 0)
+    >>> pure_complex(surd)
+    >>> pure_complex(a + b*I)
+    (2, 3)
+    >>> pure_complex(I)
+    (0, 1)
+    """
+    h, t = v.as_coeff_Add()
+    if t:
+        c, i = t.as_coeff_Mul()
+        if i is S.ImaginaryUnit:
+            return h, c
+    elif or_real:
+        return h, S.Zero
+    return None
+
+
+# I don't know what this is, see function scaled_zero below
+SCALED_ZERO_TUP = tTuple[List[int], int, int, int]
+
+
+@overload
+def scaled_zero(mag: SCALED_ZERO_TUP, sign=1) -> MPF_TUP:
+    ...
+@overload
+def scaled_zero(mag: int, sign=1) -> tTuple[SCALED_ZERO_TUP, int]:
+    ...
+def scaled_zero(mag: tUnion[SCALED_ZERO_TUP, int], sign=1) -> \
+        tUnion[MPF_TUP, tTuple[SCALED_ZERO_TUP, int]]:
+    """Return an mpf representing a power of two with magnitude ``mag``
+    and -1 for precision. Or, if ``mag`` is a scaled_zero tuple, then just
+    remove the sign from within the list that it was initially wrapped
+    in.
+
+    Examples
+    ========
+
+    >>> from sympy.core.evalf import scaled_zero
+    >>> from sympy import Float
+    >>> z, p = scaled_zero(100)
+    >>> z, p
+    (([0], 1, 100, 1), -1)
+    >>> ok = scaled_zero(z)
+    >>> ok
+    (0, 1, 100, 1)
+    >>> Float(ok)
+    1.26765060022823e+30
+    >>> Float(ok, p)
+    0.e+30
+    >>> ok, p = scaled_zero(100, -1)
+    >>> Float(scaled_zero(ok), p)
+    -0.e+30
+    """
+    if isinstance(mag, tuple) and len(mag) == 4 and iszero(mag, scaled=True):
+        return (mag[0][0],) + mag[1:]
+    elif isinstance(mag, SYMPY_INTS):
+        if sign not in [-1, 1]:
+            raise ValueError('sign must be +/-1')
+        rv, p = mpf_shift(fone, mag), -1
+        s = 0 if sign == 1 else 1
+        rv = ([s],) + rv[1:]
+        return rv, p
+    else:
+        raise ValueError('scaled zero expects int or scaled_zero tuple.')
+
+
+def iszero(mpf: tUnion[MPF_TUP, SCALED_ZERO_TUP, None], scaled=False) -> Optional[bool]:
+    if not scaled:
+        return not mpf or not mpf[1] and not mpf[-1]
+    return mpf and isinstance(mpf[0], list) and mpf[1] == mpf[-1] == 1
+
+
+def complex_accuracy(result: TMP_RES) -> tUnion[int, Any]:
+    """
+    Returns relative accuracy of a complex number with given accuracies
+    for the real and imaginary parts. The relative accuracy is defined
+    in the complex norm sense as ||z|+|error|| / |z| where error
+    is equal to (real absolute error) + (imag absolute error)*i.
+
+    The full expression for the (logarithmic) error can be approximated
+    easily by using the max norm to approximate the complex norm.
+
+    In the worst case (re and im equal), this is wrong by a factor
+    sqrt(2), or by log2(sqrt(2)) = 0.5 bit.
+    """
+    if result is S.ComplexInfinity:
+        return INF
+    re, im, re_acc, im_acc = result
+    if not im:
+        if not re:
+            return INF
+        return re_acc
+    if not re:
+        return im_acc
+    re_size = fastlog(re)
+    im_size = fastlog(im)
+    absolute_error = max(re_size - re_acc, im_size - im_acc)
+    relative_error = absolute_error - max(re_size, im_size)
+    return -relative_error
+
+
+def get_abs(expr: 'Expr', prec: int, options: OPT_DICT) -> TMP_RES:
+    result = evalf(expr, prec + 2, options)
+    if result is S.ComplexInfinity:
+        return finf, None, prec, None
+    re, im, re_acc, im_acc = result
+    if not re:
+        re, re_acc, im, im_acc = im, im_acc, re, re_acc
+    if im:
+        if expr.is_number:
+            abs_expr, _, acc, _ = evalf(abs(N(expr, prec + 2)),
+                                        prec + 2, options)
+            return abs_expr, None, acc, None
+        else:
+            if 'subs' in options:
+                return libmp.mpc_abs((re, im), prec), None, re_acc, None
+            return abs(expr), None, prec, None
+    elif re:
+        return mpf_abs(re), None, re_acc, None
+    else:
+        return None, None, None, None
+
+
+def get_complex_part(expr: 'Expr', no: int, prec: int, options: OPT_DICT) -> TMP_RES:
+    """no = 0 for real part, no = 1 for imaginary part"""
+    workprec = prec
+    i = 0
+    while 1:
+        res = evalf(expr, workprec, options)
+        if res is S.ComplexInfinity:
+            return fnan, None, prec, None
+        value, accuracy = res[no::2]
+        # XXX is the last one correct? Consider re((1+I)**2).n()
+        if (not value) or accuracy >= prec or -value[2] > prec:
+            return value, None, accuracy, None
+        workprec += max(30, 2**i)
+        i += 1
+
+
+def evalf_abs(expr: 'Abs', prec: int, options: OPT_DICT) -> TMP_RES:
+    return get_abs(expr.args[0], prec, options)
+
+
+def evalf_re(expr: 're', prec: int, options: OPT_DICT) -> TMP_RES:
+    return get_complex_part(expr.args[0], 0, prec, options)
+
+
+def evalf_im(expr: 'im', prec: int, options: OPT_DICT) -> TMP_RES:
+    return get_complex_part(expr.args[0], 1, prec, options)
+
+
+def finalize_complex(re: MPF_TUP, im: MPF_TUP, prec: int) -> TMP_RES:
+    if re == fzero and im == fzero:
+        raise ValueError("got complex zero with unknown accuracy")
+    elif re == fzero:
+        return None, im, None, prec
+    elif im == fzero:
+        return re, None, prec, None
+
+    size_re = fastlog(re)
+    size_im = fastlog(im)
+    if size_re > size_im:
+        re_acc = prec
+        im_acc = prec + min(-(size_re - size_im), 0)
+    else:
+        im_acc = prec
+        re_acc = prec + min(-(size_im - size_re), 0)
+    return re, im, re_acc, im_acc
+
+
+def chop_parts(value: TMP_RES, prec: int) -> TMP_RES:
+    """
+    Chop off tiny real or complex parts.
+    """
+    if value is S.ComplexInfinity:
+        return value
+    re, im, re_acc, im_acc = value
+    # Method 1: chop based on absolute value
+    if re and re not in _infs_nan and (fastlog(re) < -prec + 4):
+        re, re_acc = None, None
+    if im and im not in _infs_nan and (fastlog(im) < -prec + 4):
+        im, im_acc = None, None
+    # Method 2: chop if inaccurate and relatively small
+    if re and im:
+        delta = fastlog(re) - fastlog(im)
+        if re_acc < 2 and (delta - re_acc <= -prec + 4):
+            re, re_acc = None, None
+        if im_acc < 2 and (delta - im_acc >= prec - 4):
+            im, im_acc = None, None
+    return re, im, re_acc, im_acc
+
+
+def check_target(expr: 'Expr', result: TMP_RES, prec: int):
+    a = complex_accuracy(result)
+    if a < prec:
+        raise PrecisionExhausted("Failed to distinguish the expression: \n\n%s\n\n"
+            "from zero. Try simplifying the input, using chop=True, or providing "
+            "a higher maxn for evalf" % (expr))
+
+
+def get_integer_part(expr: 'Expr', no: int, options: OPT_DICT, return_ints=False) -> \
+        tUnion[TMP_RES, tTuple[int, int]]:
+    """
+    With no = 1, computes ceiling(expr)
+    With no = -1, computes floor(expr)
+
+    Note: this function either gives the exact result or signals failure.
+    """
+    from sympy.functions.elementary.complexes import re, im
+    # The expression is likely less than 2^30 or so
+    assumed_size = 30
+    result = evalf(expr, assumed_size, options)
+    if result is S.ComplexInfinity:
+        raise ValueError("Cannot get integer part of Complex Infinity")
+    ire, iim, ire_acc, iim_acc = result
+
+    # We now know the size, so we can calculate how much extra precision
+    # (if any) is needed to get within the nearest integer
+    if ire and iim:
+        gap = max(fastlog(ire) - ire_acc, fastlog(iim) - iim_acc)
+    elif ire:
+        gap = fastlog(ire) - ire_acc
+    elif iim:
+        gap = fastlog(iim) - iim_acc
+    else:
+        # ... or maybe the expression was exactly zero
+        if return_ints:
+            return 0, 0
+        else:
+            return None, None, None, None
+
+    margin = 10
+
+    if gap >= -margin:
+        prec = margin + assumed_size + gap
+        ire, iim, ire_acc, iim_acc = evalf(
+            expr, prec, options)
+    else:
+        prec = assumed_size
+
+    # We can now easily find the nearest integer, but to find floor/ceil, we
+    # must also calculate whether the difference to the nearest integer is
+    # positive or negative (which may fail if very close).
+    def calc_part(re_im: 'Expr', nexpr: MPF_TUP):
+        from .add import Add
+        _, _, exponent, _ = nexpr
+        is_int = exponent == 0
+        nint = int(to_int(nexpr, rnd))
+        if is_int:
+            # make sure that we had enough precision to distinguish
+            # between nint and the re or im part (re_im) of expr that
+            # was passed to calc_part
+            ire, iim, ire_acc, iim_acc = evalf(
+                re_im - nint, 10, options)  # don't need much precision
+            assert not iim
+            size = -fastlog(ire) + 2  # -ve b/c ire is less than 1
+            if size > prec:
+                ire, iim, ire_acc, iim_acc = evalf(
+                    re_im, size, options)
+                assert not iim
+                nexpr = ire
+            nint = int(to_int(nexpr, rnd))
+            _, _, new_exp, _ = ire
+            is_int = new_exp == 0
+        if not is_int:
+            # if there are subs and they all contain integer re/im parts
+            # then we can (hopefully) safely substitute them into the
+            # expression
+            s = options.get('subs', False)
+            if s:
+                doit = True
+                # use strict=False with as_int because we take
+                # 2.0 == 2
+                for v in s.values():
+                    try:
+                        as_int(v, strict=False)
+                    except ValueError:
+                        try:
+                            [as_int(i, strict=False) for i in v.as_real_imag()]
+                            continue
+                        except (ValueError, AttributeError):
+                            doit = False
+                            break
+                if doit:
+                    re_im = re_im.subs(s)
+
+            re_im = Add(re_im, -nint, evaluate=False)
+            x, _, x_acc, _ = evalf(re_im, 10, options)
+            try:
+                check_target(re_im, (x, None, x_acc, None), 3)
+            except PrecisionExhausted:
+                if not re_im.equals(0):
+                    raise PrecisionExhausted
+                x = fzero
+            nint += int(no*(mpf_cmp(x or fzero, fzero) == no))
+        nint = from_int(nint)
+        return nint, INF
+
+    re_, im_, re_acc, im_acc = None, None, None, None
+
+    if ire:
+        re_, re_acc = calc_part(re(expr, evaluate=False), ire)
+    if iim:
+        im_, im_acc = calc_part(im(expr, evaluate=False), iim)
+
+    if return_ints:
+        return int(to_int(re_ or fzero)), int(to_int(im_ or fzero))
+    return re_, im_, re_acc, im_acc
+
+
+def evalf_ceiling(expr: 'ceiling', prec: int, options: OPT_DICT) -> TMP_RES:
+    return get_integer_part(expr.args[0], 1, options)
+
+
+def evalf_floor(expr: 'floor', prec: int, options: OPT_DICT) -> TMP_RES:
+    return get_integer_part(expr.args[0], -1, options)
+
+
+def evalf_float(expr: 'Float', prec: int, options: OPT_DICT) -> TMP_RES:
+    return expr._mpf_, None, prec, None
+
+
+def evalf_rational(expr: 'Rational', prec: int, options: OPT_DICT) -> TMP_RES:
+    return from_rational(expr.p, expr.q, prec), None, prec, None
+
+
+def evalf_integer(expr: 'Integer', prec: int, options: OPT_DICT) -> TMP_RES:
+    return from_int(expr.p, prec), None, prec, None
+
+#----------------------------------------------------------------------------#
+#                                                                            #
+#                            Arithmetic operations                           #
+#                                                                            #
+#----------------------------------------------------------------------------#
+
+
+def add_terms(terms: list, prec: int, target_prec: int) -> \
+        tTuple[tUnion[MPF_TUP, SCALED_ZERO_TUP, None], Optional[int]]:
+    """
+    Helper for evalf_add. Adds a list of (mpfval, accuracy) terms.
+
+    Returns
+    =======
+
+    - None, None if there are no non-zero terms;
+    - terms[0] if there is only 1 term;
+    - scaled_zero if the sum of the terms produces a zero by cancellation
+      e.g. mpfs representing 1 and -1 would produce a scaled zero which need
+      special handling since they are not actually zero and they are purposely
+      malformed to ensure that they cannot be used in anything but accuracy
+      calculations;
+    - a tuple that is scaled to target_prec that corresponds to the
+      sum of the terms.
+
+    The returned mpf tuple will be normalized to target_prec; the input
+    prec is used to define the working precision.
+
+    XXX explain why this is needed and why one cannot just loop using mpf_add
+    """
+
+    terms = [t for t in terms if not iszero(t[0])]
+    if not terms:
+        return None, None
+    elif len(terms) == 1:
+        return terms[0]
+
+    # see if any argument is NaN or oo and thus warrants a special return
+    special = []
+    from .numbers import Float
+    for t in terms:
+        arg = Float._new(t[0], 1)
+        if arg is S.NaN or arg.is_infinite:
+            special.append(arg)
+    if special:
+        from .add import Add
+        rv = evalf(Add(*special), prec + 4, {})
+        return rv[0], rv[2]
+
+    working_prec = 2*prec
+    sum_man, sum_exp = 0, 0
+    absolute_err: List[int] = []
+
+    for x, accuracy in terms:
+        sign, man, exp, bc = x
+        if sign:
+            man = -man
+        absolute_err.append(bc + exp - accuracy)
+        delta = exp - sum_exp
+        if exp >= sum_exp:
+            # x much larger than existing sum?
+            # first: quick test
+            if ((delta > working_prec) and
+                ((not sum_man) or
+                 delta - bitcount(abs(sum_man)) > working_prec)):
+                sum_man = man
+                sum_exp = exp
+            else:
+                sum_man += (man << delta)
+        else:
+            delta = -delta
+            # x much smaller than existing sum?
+            if delta - bc > working_prec:
+                if not sum_man:
+                    sum_man, sum_exp = man, exp
+            else:
+                sum_man = (sum_man << delta) + man
+                sum_exp = exp
+    absolute_error = max(absolute_err)
+    if not sum_man:
+        return scaled_zero(absolute_error)
+    if sum_man < 0:
+        sum_sign = 1
+        sum_man = -sum_man
+    else:
+        sum_sign = 0
+    sum_bc = bitcount(sum_man)
+    sum_accuracy = sum_exp + sum_bc - absolute_error
+    r = normalize(sum_sign, sum_man, sum_exp, sum_bc, target_prec,
+        rnd), sum_accuracy
+    return r
+
+
+def evalf_add(v: 'Add', prec: int, options: OPT_DICT) -> TMP_RES:
+    res = pure_complex(v)
+    if res:
+        h, c = res
+        re, _, re_acc, _ = evalf(h, prec, options)
+        im, _, im_acc, _ = evalf(c, prec, options)
+        return re, im, re_acc, im_acc
+
+    oldmaxprec = options.get('maxprec', DEFAULT_MAXPREC)
+
+    i = 0
+    target_prec = prec
+    while 1:
+        options['maxprec'] = min(oldmaxprec, 2*prec)
+
+        terms = [evalf(arg, prec + 10, options) for arg in v.args]
+        n = terms.count(S.ComplexInfinity)
+        if n >= 2:
+            return fnan, None, prec, None
+        re, re_acc = add_terms(
+            [a[0::2] for a in terms if isinstance(a, tuple) and a[0]], prec, target_prec)
+        im, im_acc = add_terms(
+            [a[1::2] for a in terms if isinstance(a, tuple) and a[1]], prec, target_prec)
+        if n == 1:
+            if re in (finf, fninf, fnan) or im in (finf, fninf, fnan):
+                return fnan, None, prec, None
+            return S.ComplexInfinity
+        acc = complex_accuracy((re, im, re_acc, im_acc))
+        if acc >= target_prec:
+            if options.get('verbose'):
+                print("ADD: wanted", target_prec, "accurate bits, got", re_acc, im_acc)
+            break
+        else:
+            if (prec - target_prec) > options['maxprec']:
+                break
+
+            prec = prec + max(10 + 2**i, target_prec - acc)
+            i += 1
+            if options.get('verbose'):
+                print("ADD: restarting with prec", prec)
+
+    options['maxprec'] = oldmaxprec
+    if iszero(re, scaled=True):
+        re = scaled_zero(re)
+    if iszero(im, scaled=True):
+        im = scaled_zero(im)
+    return re, im, re_acc, im_acc
+
+
+def evalf_mul(v: 'Mul', prec: int, options: OPT_DICT) -> TMP_RES:
+    res = pure_complex(v)
+    if res:
+        # the only pure complex that is a mul is h*I
+        _, h = res
+        im, _, im_acc, _ = evalf(h, prec, options)
+        return None, im, None, im_acc
+    args = list(v.args)
+
+    # see if any argument is NaN or oo and thus warrants a special return
+    has_zero = False
+    special = []
+    from .numbers import Float
+    for arg in args:
+        result = evalf(arg, prec, options)
+        if result is S.ComplexInfinity:
+            special.append(result)
+            continue
+        if result[0] is None:
+            if result[1] is None:
+                has_zero = True
+            continue
+        num = Float._new(result[0], 1)
+        if num is S.NaN:
+            return fnan, None, prec, None
+        if num.is_infinite:
+            special.append(num)
+    if special:
+        if has_zero:
+            return fnan, None, prec, None
+        from .mul import Mul
+        return evalf(Mul(*special), prec + 4, {})
+    if has_zero:
+        return None, None, None, None
+
+    # With guard digits, multiplication in the real case does not destroy
+    # accuracy. This is also true in the complex case when considering the
+    # total accuracy; however accuracy for the real or imaginary parts
+    # separately may be lower.
+    acc = prec
+
+    # XXX: big overestimate
+    working_prec = prec + len(args) + 5
+
+    # Empty product is 1
+    start = man, exp, bc = MPZ(1), 0, 1
+
+    # First, we multiply all pure real or pure imaginary numbers.
+    # direction tells us that the result should be multiplied by
+    # I**direction; all other numbers get put into complex_factors
+    # to be multiplied out after the first phase.
+    last = len(args)
+    direction = 0
+    args.append(S.One)
+    complex_factors = []
+
+    for i, arg in enumerate(args):
+        if i != last and pure_complex(arg):
+            args[-1] = (args[-1]*arg).expand()
+            continue
+        elif i == last and arg is S.One:
+            continue
+        re, im, re_acc, im_acc = evalf(arg, working_prec, options)
+        if re and im:
+            complex_factors.append((re, im, re_acc, im_acc))
+            continue
+        elif re:
+            (s, m, e, b), w_acc = re, re_acc
+        elif im:
+            (s, m, e, b), w_acc = im, im_acc
+            direction += 1
+        else:
+            return None, None, None, None
+        direction += 2*s
+        man *= m
+        exp += e
+        bc += b
+        while bc > 3*working_prec:
+            man >>= working_prec
+            exp += working_prec
+            bc -= working_prec
+        acc = min(acc, w_acc)
+    sign = (direction & 2) >> 1
+    if not complex_factors:
+        v = normalize(sign, man, exp, bitcount(man), prec, rnd)
+        # multiply by i
+        if direction & 1:
+            return None, v, None, acc
+        else:
+            return v, None, acc, None
+    else:
+        # initialize with the first term
+        if (man, exp, bc) != start:
+            # there was a real part; give it an imaginary part
+            re, im = (sign, man, exp, bitcount(man)), (0, MPZ(0), 0, 0)
+            i0 = 0
+        else:
+            # there is no real part to start (other than the starting 1)
+            wre, wim, wre_acc, wim_acc = complex_factors[0]
+            acc = min(acc,
+                      complex_accuracy((wre, wim, wre_acc, wim_acc)))
+            re = wre
+            im = wim
+            i0 = 1
+
+        for wre, wim, wre_acc, wim_acc in complex_factors[i0:]:
+            # acc is the overall accuracy of the product; we aren't
+            # computing exact accuracies of the product.
+            acc = min(acc,
+                      complex_accuracy((wre, wim, wre_acc, wim_acc)))
+
+            use_prec = working_prec
+            A = mpf_mul(re, wre, use_prec)
+            B = mpf_mul(mpf_neg(im), wim, use_prec)
+            C = mpf_mul(re, wim, use_prec)
+            D = mpf_mul(im, wre, use_prec)
+            re = mpf_add(A, B, use_prec)
+            im = mpf_add(C, D, use_prec)
+        if options.get('verbose'):
+            print("MUL: wanted", prec, "accurate bits, got", acc)
+        # multiply by I
+        if direction & 1:
+            re, im = mpf_neg(im), re
+        return re, im, acc, acc
+
+
+def evalf_pow(v: 'Pow', prec: int, options) -> TMP_RES:
+
+    target_prec = prec
+    base, exp = v.args
+
+    # We handle x**n separately. This has two purposes: 1) it is much
+    # faster, because we avoid calling evalf on the exponent, and 2) it
+    # allows better handling of real/imaginary parts that are exactly zero
+    if exp.is_Integer:
+        p: int = exp.p  # type: ignore
+        # Exact
+        if not p:
+            return fone, None, prec, None
+        # Exponentiation by p magnifies relative error by |p|, so the
+        # base must be evaluated with increased precision if p is large
+        prec += int(math.log(abs(p), 2))
+        result = evalf(base, prec + 5, options)
+        if result is S.ComplexInfinity:
+            if p < 0:
+                return None, None, None, None
+            return result
+        re, im, re_acc, im_acc = result
+        # Real to integer power
+        if re and not im:
+            return mpf_pow_int(re, p, target_prec), None, target_prec, None
+        # (x*I)**n = I**n * x**n
+        if im and not re:
+            z = mpf_pow_int(im, p, target_prec)
+            case = p % 4
+            if case == 0:
+                return z, None, target_prec, None
+            if case == 1:
+                return None, z, None, target_prec
+            if case == 2:
+                return mpf_neg(z), None, target_prec, None
+            if case == 3:
+                return None, mpf_neg(z), None, target_prec
+        # Zero raised to an integer power
+        if not re:
+            if p < 0:
+                return S.ComplexInfinity
+            return None, None, None, None
+        # General complex number to arbitrary integer power
+        re, im = libmp.mpc_pow_int((re, im), p, prec)
+        # Assumes full accuracy in input
+        return finalize_complex(re, im, target_prec)
+
+    result = evalf(base, prec + 5, options)
+    if result is S.ComplexInfinity:
+        if exp.is_Rational:
+            if exp < 0:
+                return None, None, None, None
+            return result
+        raise NotImplementedError
+
+    # Pure square root
+    if exp is S.Half:
+        xre, xim, _, _ = result
+        # General complex square root
+        if xim:
+            re, im = libmp.mpc_sqrt((xre or fzero, xim), prec)
+            return finalize_complex(re, im, prec)
+        if not xre:
+            return None, None, None, None
+        # Square root of a negative real number
+        if mpf_lt(xre, fzero):
+            return None, mpf_sqrt(mpf_neg(xre), prec), None, prec
+        # Positive square root
+        return mpf_sqrt(xre, prec), None, prec, None
+
+    # We first evaluate the exponent to find its magnitude
+    # This determines the working precision that must be used
+    prec += 10
+    result = evalf(exp, prec, options)
+    if result is S.ComplexInfinity:
+        return fnan, None, prec, None
+    yre, yim, _, _ = result
+    # Special cases: x**0
+    if not (yre or yim):
+        return fone, None, prec, None
+
+    ysize = fastlog(yre)
+    # Restart if too big
+    # XXX: prec + ysize might exceed maxprec
+    if ysize > 5:
+        prec += ysize
+        yre, yim, _, _ = evalf(exp, prec, options)
+
+    # Pure exponential function; no need to evalf the base
+    if base is S.Exp1:
+        if yim:
+            re, im = libmp.mpc_exp((yre or fzero, yim), prec)
+            return finalize_complex(re, im, target_prec)
+        return mpf_exp(yre, target_prec), None, target_prec, None
+
+    xre, xim, _, _ = evalf(base, prec + 5, options)
+    # 0**y
+    if not (xre or xim):
+        if yim:
+            return fnan, None, prec, None
+        if yre[0] == 1:  # y < 0
+            return S.ComplexInfinity
+        return None, None, None, None
+
+    # (real ** complex) or (complex ** complex)
+    if yim:
+        re, im = libmp.mpc_pow(
+            (xre or fzero, xim or fzero), (yre or fzero, yim),
+            target_prec)
+        return finalize_complex(re, im, target_prec)
+    # complex ** real
+    if xim:
+        re, im = libmp.mpc_pow_mpf((xre or fzero, xim), yre, target_prec)
+        return finalize_complex(re, im, target_prec)
+    # negative ** real
+    elif mpf_lt(xre, fzero):
+        re, im = libmp.mpc_pow_mpf((xre, fzero), yre, target_prec)
+        return finalize_complex(re, im, target_prec)
+    # positive ** real
+    else:
+        return mpf_pow(xre, yre, target_prec), None, target_prec, None
+
+
+#----------------------------------------------------------------------------#
+#                                                                            #
+#                            Special functions                               #
+#                                                                            #
+#----------------------------------------------------------------------------#
+
+
+def evalf_exp(expr: 'exp', prec: int, options: OPT_DICT) -> TMP_RES:
+    from .power import Pow
+    return evalf_pow(Pow(S.Exp1, expr.exp, evaluate=False), prec, options)
+
+
+def evalf_trig(v: 'Expr', prec: int, options: OPT_DICT) -> TMP_RES:
+    """
+    This function handles sin and cos of complex arguments.
+
+    TODO: should also handle tan of complex arguments.
+    """
+    from sympy.functions.elementary.trigonometric import cos, sin
+    if isinstance(v, cos):
+        func = mpf_cos
+    elif isinstance(v, sin):
+        func = mpf_sin
+    else:
+        raise NotImplementedError
+    arg = v.args[0]
+    # 20 extra bits is possibly overkill. It does make the need
+    # to restart very unlikely
+    xprec = prec + 20
+    re, im, re_acc, im_acc = evalf(arg, xprec, options)
+    if im:
+        if 'subs' in options:
+            v = v.subs(options['subs'])
+        return evalf(v._eval_evalf(prec), prec, options)
+    if not re:
+        if isinstance(v, cos):
+            return fone, None, prec, None
+        elif isinstance(v, sin):
+            return None, None, None, None
+        else:
+            raise NotImplementedError
+    # For trigonometric functions, we are interested in the
+    # fixed-point (absolute) accuracy of the argument.
+    xsize = fastlog(re)
+    # Magnitude <= 1.0. OK to compute directly, because there is no
+    # danger of hitting the first root of cos (with sin, magnitude
+    # <= 2.0 would actually be ok)
+    if xsize < 1:
+        return func(re, prec, rnd), None, prec, None
+    # Very large
+    if xsize >= 10:
+        xprec = prec + xsize
+        re, im, re_acc, im_acc = evalf(arg, xprec, options)
+    # Need to repeat in case the argument is very close to a
+    # multiple of pi (or pi/2), hitting close to a root
+    while 1:
+        y = func(re, prec, rnd)
+        ysize = fastlog(y)
+        gap = -ysize
+        accuracy = (xprec - xsize) - gap
+        if accuracy < prec:
+            if options.get('verbose'):
+                print("SIN/COS", accuracy, "wanted", prec, "gap", gap)
+                print(to_str(y, 10))
+            if xprec > options.get('maxprec', DEFAULT_MAXPREC):
+                return y, None, accuracy, None
+            xprec += gap
+            re, im, re_acc, im_acc = evalf(arg, xprec, options)
+            continue
+        else:
+            return y, None, prec, None
+
+
+def evalf_log(expr: 'log', prec: int, options: OPT_DICT) -> TMP_RES:
+    if len(expr.args)>1:
+        expr = expr.doit()
+        return evalf(expr, prec, options)
+    arg = expr.args[0]
+    workprec = prec + 10
+    result = evalf(arg, workprec, options)
+    if result is S.ComplexInfinity:
+        return result
+    xre, xim, xacc, _ = result
+
+    # evalf can return NoneTypes if chop=True
+    # issue 18516, 19623
+    if xre is xim is None:
+        # Dear reviewer, I do not know what -inf is;
+        # it looks to be (1, 0, -789, -3)
+        # but I'm not sure in general,
+        # so we just let mpmath figure
+        # it out by taking log of 0 directly.
+        # It would be better to return -inf instead.
+        xre = fzero
+
+    if xim:
+        from sympy.functions.elementary.complexes import Abs
+        from sympy.functions.elementary.exponential import log
+
+        # XXX: use get_abs etc instead
+        re = evalf_log(
+            log(Abs(arg, evaluate=False), evaluate=False), prec, options)
+        im = mpf_atan2(xim, xre or fzero, prec)
+        return re[0], im, re[2], prec
+
+    imaginary_term = (mpf_cmp(xre, fzero) < 0)
+
+    re = mpf_log(mpf_abs(xre), prec, rnd)
+    size = fastlog(re)
+    if prec - size > workprec and re != fzero:
+        from .add import Add
+        # We actually need to compute 1+x accurately, not x
+        add = Add(S.NegativeOne, arg, evaluate=False)
+        xre, xim, _, _ = evalf_add(add, prec, options)
+        prec2 = workprec - fastlog(xre)
+        # xre is now x - 1 so we add 1 back here to calculate x
+        re = mpf_log(mpf_abs(mpf_add(xre, fone, prec2)), prec, rnd)
+
+    re_acc = prec
+
+    if imaginary_term:
+        return re, mpf_pi(prec), re_acc, prec
+    else:
+        return re, None, re_acc, None
+
+
+def evalf_atan(v: 'atan', prec: int, options: OPT_DICT) -> TMP_RES:
+    arg = v.args[0]
+    xre, xim, reacc, imacc = evalf(arg, prec + 5, options)
+    if xre is xim is None:
+        return (None,)*4
+    if xim:
+        raise NotImplementedError
+    return mpf_atan(xre, prec, rnd), None, prec, None
+
+
+def evalf_subs(prec: int, subs: dict) -> dict:
+    """ Change all Float entries in `subs` to have precision prec. """
+    newsubs = {}
+    for a, b in subs.items():
+        b = S(b)
+        if b.is_Float:
+            b = b._eval_evalf(prec)
+        newsubs[a] = b
+    return newsubs
+
+
+def evalf_piecewise(expr: 'Expr', prec: int, options: OPT_DICT) -> TMP_RES:
+    from .numbers import Float, Integer
+    if 'subs' in options:
+        expr = expr.subs(evalf_subs(prec, options['subs']))
+        newopts = options.copy()
+        del newopts['subs']
+        if hasattr(expr, 'func'):
+            return evalf(expr, prec, newopts)
+        if isinstance(expr, float):
+            return evalf(Float(expr), prec, newopts)
+        if isinstance(expr, int):
+            return evalf(Integer(expr), prec, newopts)
+
+    # We still have undefined symbols
+    raise NotImplementedError
+
+
+def evalf_alg_num(a: 'AlgebraicNumber', prec: int, options: OPT_DICT) -> TMP_RES:
+    return evalf(a.to_root(), prec, options)
+
+#----------------------------------------------------------------------------#
+#                                                                            #
+#                            High-level operations                           #
+#                                                                            #
+#----------------------------------------------------------------------------#
+
+
+def as_mpmath(x: Any, prec: int, options: OPT_DICT) -> tUnion[mpc, mpf]:
+    from .numbers import Infinity, NegativeInfinity, Zero
+    x = sympify(x)
+    if isinstance(x, Zero) or x == 0.0:
+        return mpf(0)
+    if isinstance(x, Infinity):
+        return mpf('inf')
+    if isinstance(x, NegativeInfinity):
+        return mpf('-inf')
+    # XXX
+    result = evalf(x, prec, options)
+    return quad_to_mpmath(result)
+
+
+def do_integral(expr: 'Integral', prec: int, options: OPT_DICT) -> TMP_RES:
+    func = expr.args[0]
+    x, xlow, xhigh = expr.args[1]
+    if xlow == xhigh:
+        xlow = xhigh = 0
+    elif x not in func.free_symbols:
+        # only the difference in limits matters in this case
+        # so if there is a symbol in common that will cancel
+        # out when taking the difference, then use that
+        # difference
+        if xhigh.free_symbols & xlow.free_symbols:
+            diff = xhigh - xlow
+            if diff.is_number:
+                xlow, xhigh = 0, diff
+
+    oldmaxprec = options.get('maxprec', DEFAULT_MAXPREC)
+    options['maxprec'] = min(oldmaxprec, 2*prec)
+
+    with workprec(prec + 5):
+        xlow = as_mpmath(xlow, prec + 15, options)
+        xhigh = as_mpmath(xhigh, prec + 15, options)
+
+        # Integration is like summation, and we can phone home from
+        # the integrand function to update accuracy summation style
+        # Note that this accuracy is inaccurate, since it fails
+        # to account for the variable quadrature weights,
+        # but it is better than nothing
+
+        from sympy.functions.elementary.trigonometric import cos, sin
+        from .symbol import Wild
+
+        have_part = [False, False]
+        max_real_term: tUnion[float, int] = MINUS_INF
+        max_imag_term: tUnion[float, int] = MINUS_INF
+
+        def f(t: 'Expr') -> tUnion[mpc, mpf]:
+            nonlocal max_real_term, max_imag_term
+            re, im, re_acc, im_acc = evalf(func, mp.prec, {'subs': {x: t}})
+
+            have_part[0] = re or have_part[0]
+            have_part[1] = im or have_part[1]
+
+            max_real_term = max(max_real_term, fastlog(re))
+            max_imag_term = max(max_imag_term, fastlog(im))
+
+            if im:
+                return mpc(re or fzero, im)
+            return mpf(re or fzero)
+
+        if options.get('quad') == 'osc':
+            A = Wild('A', exclude=[x])
+            B = Wild('B', exclude=[x])
+            D = Wild('D')
+            m = func.match(cos(A*x + B)*D)
+            if not m:
+                m = func.match(sin(A*x + B)*D)
+            if not m:
+                raise ValueError("An integrand of the form sin(A*x+B)*f(x) "
+                  "or cos(A*x+B)*f(x) is required for oscillatory quadrature")
+            period = as_mpmath(2*S.Pi/m[A], prec + 15, options)
+            result = quadosc(f, [xlow, xhigh], period=period)
+            # XXX: quadosc does not do error detection yet
+            quadrature_error = MINUS_INF
+        else:
+            result, quadrature_err = quadts(f, [xlow, xhigh], error=1)
+            quadrature_error = fastlog(quadrature_err._mpf_)
+
+    options['maxprec'] = oldmaxprec
+
+    if have_part[0]:
+        re: Optional[MPF_TUP] = result.real._mpf_
+        re_acc: Optional[int]
+        if re == fzero:
+            re_s, re_acc = scaled_zero(int(-max(prec, max_real_term, quadrature_error)))
+            re = scaled_zero(re_s)  # handled ok in evalf_integral
+        else:
+            re_acc = int(-max(max_real_term - fastlog(re) - prec, quadrature_error))
+    else:
+        re, re_acc = None, None
+
+    if have_part[1]:
+        im: Optional[MPF_TUP] = result.imag._mpf_
+        im_acc: Optional[int]
+        if im == fzero:
+            im_s, im_acc = scaled_zero(int(-max(prec, max_imag_term, quadrature_error)))
+            im = scaled_zero(im_s)  # handled ok in evalf_integral
+        else:
+            im_acc = int(-max(max_imag_term - fastlog(im) - prec, quadrature_error))
+    else:
+        im, im_acc = None, None
+
+    result = re, im, re_acc, im_acc
+    return result
+
+
+def evalf_integral(expr: 'Integral', prec: int, options: OPT_DICT) -> TMP_RES:
+    limits = expr.limits
+    if len(limits) != 1 or len(limits[0]) != 3:
+        raise NotImplementedError
+    workprec = prec
+    i = 0
+    maxprec = options.get('maxprec', INF)
+    while 1:
+        result = do_integral(expr, workprec, options)
+        accuracy = complex_accuracy(result)
+        if accuracy >= prec:  # achieved desired precision
+            break
+        if workprec >= maxprec:  # can't increase accuracy any more
+            break
+        if accuracy == -1:
+            # maybe the answer really is zero and maybe we just haven't increased
+            # the precision enough. So increase by doubling to not take too long
+            # to get to maxprec.
+            workprec *= 2
+        else:
+            workprec += max(prec, 2**i)
+        workprec = min(workprec, maxprec)
+        i += 1
+    return result
+
+
+def check_convergence(numer: 'Expr', denom: 'Expr', n: 'Symbol') -> tTuple[int, Any, Any]:
+    """
+    Returns
+    =======
+
+    (h, g, p) where
+    -- h is:
+        > 0 for convergence of rate 1/factorial(n)**h
+        < 0 for divergence of rate factorial(n)**(-h)
+        = 0 for geometric or polynomial convergence or divergence
+
+    -- abs(g) is:
+        > 1 for geometric convergence of rate 1/h**n
+        < 1 for geometric divergence of rate h**n
+        = 1 for polynomial convergence or divergence
+
+        (g < 0 indicates an alternating series)
+
+    -- p is:
+        > 1 for polynomial convergence of rate 1/n**h
+        <= 1 for polynomial divergence of rate n**(-h)
+
+    """
+    from sympy.polys.polytools import Poly
+    npol = Poly(numer, n)
+    dpol = Poly(denom, n)
+    p = npol.degree()
+    q = dpol.degree()
+    rate = q - p
+    if rate:
+        return rate, None, None
+    constant = dpol.LC() / npol.LC()
+    from .numbers import equal_valued
+    if not equal_valued(abs(constant), 1):
+        return rate, constant, None
+    if npol.degree() == dpol.degree() == 0:
+        return rate, constant, 0
+    pc = npol.all_coeffs()[1]
+    qc = dpol.all_coeffs()[1]
+    return rate, constant, (qc - pc)/dpol.LC()
+
+
+def hypsum(expr: 'Expr', n: 'Symbol', start: int, prec: int) -> mpf:
+    """
+    Sum a rapidly convergent infinite hypergeometric series with
+    given general term, e.g. e = hypsum(1/factorial(n), n). The
+    quotient between successive terms must be a quotient of integer
+    polynomials.
+    """
+    from .numbers import Float, equal_valued
+    from sympy.simplify.simplify import hypersimp
+
+    if prec == float('inf'):
+        raise NotImplementedError('does not support inf prec')
+
+    if start:
+        expr = expr.subs(n, n + start)
+    hs = hypersimp(expr, n)
+    if hs is None:
+        raise NotImplementedError("a hypergeometric series is required")
+    num, den = hs.as_numer_denom()
+
+    func1 = lambdify(n, num)
+    func2 = lambdify(n, den)
+
+    h, g, p = check_convergence(num, den, n)
+
+    if h < 0:
+        raise ValueError("Sum diverges like (n!)^%i" % (-h))
+
+    term = expr.subs(n, 0)
+    if not term.is_Rational:
+        raise NotImplementedError("Non rational term functionality is not implemented.")
+
+    # Direct summation if geometric or faster
+    if h > 0 or (h == 0 and abs(g) > 1):
+        term = (MPZ(term.p) << prec) // term.q
+        s = term
+        k = 1
+        while abs(term) > 5:
+            term *= MPZ(func1(k - 1))
+            term //= MPZ(func2(k - 1))
+            s += term
+            k += 1
+        return from_man_exp(s, -prec)
+    else:
+        alt = g < 0
+        if abs(g) < 1:
+            raise ValueError("Sum diverges like (%i)^n" % abs(1/g))
+        if p < 1 or (equal_valued(p, 1) and not alt):
+            raise ValueError("Sum diverges like n^%i" % (-p))
+        # We have polynomial convergence: use Richardson extrapolation
+        vold = None
+        ndig = prec_to_dps(prec)
+        while True:
+            # Need to use at least quad precision because a lot of cancellation
+            # might occur in the extrapolation process; we check the answer to
+            # make sure that the desired precision has been reached, too.
+            prec2 = 4*prec
+            term0 = (MPZ(term.p) << prec2) // term.q
+
+            def summand(k, _term=[term0]):
+                if k:
+                    k = int(k)
+                    _term[0] *= MPZ(func1(k - 1))
+                    _term[0] //= MPZ(func2(k - 1))
+                return make_mpf(from_man_exp(_term[0], -prec2))
+
+            with workprec(prec):
+                v = nsum(summand, [0, mpmath_inf], method='richardson')
+            vf = Float(v, ndig)
+            if vold is not None and vold == vf:
+                break
+            prec += prec  # double precision each time
+            vold = vf
+
+        return v._mpf_
+
+
+def evalf_prod(expr: 'Product', prec: int, options: OPT_DICT) -> TMP_RES:
+    if all((l[1] - l[2]).is_Integer for l in expr.limits):
+        result = evalf(expr.doit(), prec=prec, options=options)
+    else:
+        from sympy.concrete.summations import Sum
+        result = evalf(expr.rewrite(Sum), prec=prec, options=options)
+    return result
+
+
+def evalf_sum(expr: 'Sum', prec: int, options: OPT_DICT) -> TMP_RES:
+    from .numbers import Float
+    if 'subs' in options:
+        expr = expr.subs(options['subs'])
+    func = expr.function
+    limits = expr.limits
+    if len(limits) != 1 or len(limits[0]) != 3:
+        raise NotImplementedError
+    if func.is_zero:
+        return None, None, prec, None
+    prec2 = prec + 10
+    try:
+        n, a, b = limits[0]
+        if b is not S.Infinity or a is S.NegativeInfinity or a != int(a):
+            raise NotImplementedError
+        # Use fast hypergeometric summation if possible
+        v = hypsum(func, n, int(a), prec2)
+        delta = prec - fastlog(v)
+        if fastlog(v) < -10:
+            v = hypsum(func, n, int(a), delta)
+        return v, None, min(prec, delta), None
+    except NotImplementedError:
+        # Euler-Maclaurin summation for general series
+        eps = Float(2.0)**(-prec)
+        for i in range(1, 5):
+            m = n = 2**i * prec
+            s, err = expr.euler_maclaurin(m=m, n=n, eps=eps,
+                eval_integral=False)
+            err = err.evalf()
+            if err is S.NaN:
+                raise NotImplementedError
+            if err <= eps:
+                break
+        err = fastlog(evalf(abs(err), 20, options)[0])
+        re, im, re_acc, im_acc = evalf(s, prec2, options)
+        if re_acc is None:
+            re_acc = -err
+        if im_acc is None:
+            im_acc = -err
+        return re, im, re_acc, im_acc
+
+
+#----------------------------------------------------------------------------#
+#                                                                            #
+#                            Symbolic interface                              #
+#                                                                            #
+#----------------------------------------------------------------------------#
+
+def evalf_symbol(x: 'Expr', prec: int, options: OPT_DICT) -> TMP_RES:
+    val = options['subs'][x]
+    if isinstance(val, mpf):
+        if not val:
+            return None, None, None, None
+        return val._mpf_, None, prec, None
+    else:
+        if '_cache' not in options:
+            options['_cache'] = {}
+        cache = options['_cache']
+        cached, cached_prec = cache.get(x, (None, MINUS_INF))
+        if cached_prec >= prec:
+            return cached
+        v = evalf(sympify(val), prec, options)
+        cache[x] = (v, prec)
+        return v
+
+
+evalf_table: tDict[Type['Expr'], Callable[['Expr', int, OPT_DICT], TMP_RES]] = {}
+
+
+def _create_evalf_table():
+    global evalf_table
+    from sympy.concrete.products import Product
+    from sympy.concrete.summations import Sum
+    from .add import Add
+    from .mul import Mul
+    from .numbers import Exp1, Float, Half, ImaginaryUnit, Integer, NaN, NegativeOne, One, Pi, Rational, \
+        Zero, ComplexInfinity, AlgebraicNumber
+    from .power import Pow
+    from .symbol import Dummy, Symbol
+    from sympy.functions.elementary.complexes import Abs, im, re
+    from sympy.functions.elementary.exponential import exp, log
+    from sympy.functions.elementary.integers import ceiling, floor
+    from sympy.functions.elementary.piecewise import Piecewise
+    from sympy.functions.elementary.trigonometric import atan, cos, sin
+    from sympy.integrals.integrals import Integral
+    evalf_table = {
+        Symbol: evalf_symbol,
+        Dummy: evalf_symbol,
+        Float: evalf_float,
+        Rational: evalf_rational,
+        Integer: evalf_integer,
+        Zero: lambda x, prec, options: (None, None, prec, None),
+        One: lambda x, prec, options: (fone, None, prec, None),
+        Half: lambda x, prec, options: (fhalf, None, prec, None),
+        Pi: lambda x, prec, options: (mpf_pi(prec), None, prec, None),
+        Exp1: lambda x, prec, options: (mpf_e(prec), None, prec, None),
+        ImaginaryUnit: lambda x, prec, options: (None, fone, None, prec),
+        NegativeOne: lambda x, prec, options: (fnone, None, prec, None),
+        ComplexInfinity: lambda x, prec, options: S.ComplexInfinity,
+        NaN: lambda x, prec, options: (fnan, None, prec, None),
+
+        exp: evalf_exp,
+
+        cos: evalf_trig,
+        sin: evalf_trig,
+
+        Add: evalf_add,
+        Mul: evalf_mul,
+        Pow: evalf_pow,
+
+        log: evalf_log,
+        atan: evalf_atan,
+        Abs: evalf_abs,
+
+        re: evalf_re,
+        im: evalf_im,
+        floor: evalf_floor,
+        ceiling: evalf_ceiling,
+
+        Integral: evalf_integral,
+        Sum: evalf_sum,
+        Product: evalf_prod,
+        Piecewise: evalf_piecewise,
+
+        AlgebraicNumber: evalf_alg_num,
+    }
+
+
+def evalf(x: 'Expr', prec: int, options: OPT_DICT) -> TMP_RES:
+    """
+    Evaluate the ``Expr`` instance, ``x``
+    to a binary precision of ``prec``. This
+    function is supposed to be used internally.
+
+    Parameters
+    ==========
+
+    x : Expr
+        The formula to evaluate to a float.
+    prec : int
+        The binary precision that the output should have.
+    options : dict
+        A dictionary with the same entries as
+        ``EvalfMixin.evalf`` and in addition,
+        ``maxprec`` which is the maximum working precision.
+
+    Returns
+    =======
+
+    An optional tuple, ``(re, im, re_acc, im_acc)``
+    which are the real, imaginary, real accuracy
+    and imaginary accuracy respectively. ``re`` is
+    an mpf value tuple and so is ``im``. ``re_acc``
+    and ``im_acc`` are ints.
+
+    NB: all these return values can be ``None``.
+    If all values are ``None``, then that represents 0.
+    Note that 0 is also represented as ``fzero = (0, 0, 0, 0)``.
+    """
+    from sympy.functions.elementary.complexes import re as re_, im as im_
+    try:
+        rf = evalf_table[type(x)]
+        r = rf(x, prec, options)
+    except KeyError:
+        # Fall back to ordinary evalf if possible
+        if 'subs' in options:
+            x = x.subs(evalf_subs(prec, options['subs']))
+        xe = x._eval_evalf(prec)
+        if xe is None:
+            raise NotImplementedError
+        as_real_imag = getattr(xe, "as_real_imag", None)
+        if as_real_imag is None:
+            raise NotImplementedError # e.g. FiniteSet(-1.0, 1.0).evalf()
+        re, im = as_real_imag()
+        if re.has(re_) or im.has(im_):
+            raise NotImplementedError
+        if re == 0.0:
+            re = None
+            reprec = None
+        elif re.is_number:
+            re = re._to_mpmath(prec, allow_ints=False)._mpf_
+            reprec = prec
+        else:
+            raise NotImplementedError
+        if im == 0.0:
+            im = None
+            imprec = None
+        elif im.is_number:
+            im = im._to_mpmath(prec, allow_ints=False)._mpf_
+            imprec = prec
+        else:
+            raise NotImplementedError
+        r = re, im, reprec, imprec
+
+    if options.get("verbose"):
+        print("### input", x)
+        print("### output", to_str(r[0] or fzero, 50) if isinstance(r, tuple) else r)
+        print("### raw", r) # r[0], r[2]
+        print()
+    chop = options.get('chop', False)
+    if chop:
+        if chop is True:
+            chop_prec = prec
+        else:
+            # convert (approximately) from given tolerance;
+            # the formula here will will make 1e-i rounds to 0 for
+            # i in the range +/-27 while 2e-i will not be chopped
+            chop_prec = int(round(-3.321*math.log10(chop) + 2.5))
+            if chop_prec == 3:
+                chop_prec -= 1
+        r = chop_parts(r, chop_prec)
+    if options.get("strict"):
+        check_target(x, r, prec)
+    return r
+
+
+def quad_to_mpmath(q, ctx=None):
+    """Turn the quad returned by ``evalf`` into an ``mpf`` or ``mpc``. """
+    mpc = make_mpc if ctx is None else ctx.make_mpc
+    mpf = make_mpf if ctx is None else ctx.make_mpf
+    if q is S.ComplexInfinity:
+        raise NotImplementedError
+    re, im, _, _ = q
+    if im:
+        if not re:
+            re = fzero
+        return mpc((re, im))
+    elif re:
+        return mpf(re)
+    else:
+        return mpf(fzero)
+
+
+class EvalfMixin:
+    """Mixin class adding evalf capability."""
+
+    __slots__ = ()  # type: tTuple[str, ...]
+
+    def evalf(self, n=15, subs=None, maxn=100, chop=False, strict=False, quad=None, verbose=False):
+        """
+        Evaluate the given formula to an accuracy of *n* digits.
+
+        Parameters
+        ==========
+
+        subs : dict, optional
+            Substitute numerical values for symbols, e.g.
+            ``subs={x:3, y:1+pi}``. The substitutions must be given as a
+            dictionary.
+
+        maxn : int, optional
+            Allow a maximum temporary working precision of maxn digits.
+
+        chop : bool or number, optional
+            Specifies how to replace tiny real or imaginary parts in
+            subresults by exact zeros.
+
+            When ``True`` the chop value defaults to standard precision.
+
+            Otherwise the chop value is used to determine the
+            magnitude of "small" for purposes of chopping.
+
+            >>> from sympy import N
+            >>> x = 1e-4
+            >>> N(x, chop=True)
+            0.000100000000000000
+            >>> N(x, chop=1e-5)
+            0.000100000000000000
+            >>> N(x, chop=1e-4)
+            0
+
+        strict : bool, optional
+            Raise ``PrecisionExhausted`` if any subresult fails to
+            evaluate to full accuracy, given the available maxprec.
+
+        quad : str, optional
+            Choose algorithm for numerical quadrature. By default,
+            tanh-sinh quadrature is used. For oscillatory
+            integrals on an infinite interval, try ``quad='osc'``.
+
+        verbose : bool, optional
+            Print debug information.
+
+        Notes
+        =====
+
+        When Floats are naively substituted into an expression,
+        precision errors may adversely affect the result. For example,
+        adding 1e16 (a Float) to 1 will truncate to 1e16; if 1e16 is
+        then subtracted, the result will be 0.
+        That is exactly what happens in the following:
+
+        >>> from sympy.abc import x, y, z
+        >>> values = {x: 1e16, y: 1, z: 1e16}
+        >>> (x + y - z).subs(values)
+        0
+
+        Using the subs argument for evalf is the accurate way to
+        evaluate such an expression:
+
+        >>> (x + y - z).evalf(subs=values)
+        1.00000000000000
+        """
+        from .numbers import Float, Number
+        n = n if n is not None else 15
+
+        if subs and is_sequence(subs):
+            raise TypeError('subs must be given as a dictionary')
+
+        # for sake of sage that doesn't like evalf(1)
+        if n == 1 and isinstance(self, Number):
+            from .expr import _mag
+            rv = self.evalf(2, subs, maxn, chop, strict, quad, verbose)
+            m = _mag(rv)
+            rv = rv.round(1 - m)
+            return rv
+
+        if not evalf_table:
+            _create_evalf_table()
+        prec = dps_to_prec(n)
+        options = {'maxprec': max(prec, int(maxn*LG10)), 'chop': chop,
+               'strict': strict, 'verbose': verbose}
+        if subs is not None:
+            options['subs'] = subs
+        if quad is not None:
+            options['quad'] = quad
+        try:
+            result = evalf(self, prec + 4, options)
+        except NotImplementedError:
+            # Fall back to the ordinary evalf
+            if hasattr(self, 'subs') and subs is not None:  # issue 20291
+                v = self.subs(subs)._eval_evalf(prec)
+            else:
+                v = self._eval_evalf(prec)
+            if v is None:
+                return self
+            elif not v.is_number:
+                return v
+            try:
+                # If the result is numerical, normalize it
+                result = evalf(v, prec, options)
+            except NotImplementedError:
+                # Probably contains symbols or unknown functions
+                return v
+        if result is S.ComplexInfinity:
+            return result
+        re, im, re_acc, im_acc = result
+        if re is S.NaN or im is S.NaN:
+            return S.NaN
+        if re:
+            p = max(min(prec, re_acc), 1)
+            re = Float._new(re, p)
+        else:
+            re = S.Zero
+        if im:
+            p = max(min(prec, im_acc), 1)
+            im = Float._new(im, p)
+            return re + im*S.ImaginaryUnit
+        else:
+            return re
+
+    n = evalf
+
+    def _evalf(self, prec):
+        """Helper for evalf. Does the same thing but takes binary precision"""
+        r = self._eval_evalf(prec)
+        if r is None:
+            r = self
+        return r
+
+    def _eval_evalf(self, prec):
+        return
+
+    def _to_mpmath(self, prec, allow_ints=True):
+        # mpmath functions accept ints as input
+        errmsg = "cannot convert to mpmath number"
+        if allow_ints and self.is_Integer:
+            return self.p
+        if hasattr(self, '_as_mpf_val'):
+            return make_mpf(self._as_mpf_val(prec))
+        try:
+            result = evalf(self, prec, {})
+            return quad_to_mpmath(result)
+        except NotImplementedError:
+            v = self._eval_evalf(prec)
+            if v is None:
+                raise ValueError(errmsg)
+            if v.is_Float:
+                return make_mpf(v._mpf_)
+            # Number + Number*I is also fine
+            re, im = v.as_real_imag()
+            if allow_ints and re.is_Integer:
+                re = from_int(re.p)
+            elif re.is_Float:
+                re = re._mpf_
+            else:
+                raise ValueError(errmsg)
+            if allow_ints and im.is_Integer:
+                im = from_int(im.p)
+            elif im.is_Float:
+                im = im._mpf_
+            else:
+                raise ValueError(errmsg)
+            return make_mpc((re, im))
+
+
+def N(x, n=15, **options):
+    r"""
+    Calls x.evalf(n, \*\*options).
+
+    Explanations
+    ============
+
+    Both .n() and N() are equivalent to .evalf(); use the one that you like better.
+    See also the docstring of .evalf() for information on the options.
+
+    Examples
+    ========
+
+    >>> from sympy import Sum, oo, N
+    >>> from sympy.abc import k
+    >>> Sum(1/k**k, (k, 1, oo))
+    Sum(k**(-k), (k, 1, oo))
+    >>> N(_, 4)
+    1.291
+
+    """
+    # by using rational=True, any evaluation of a string
+    # will be done using exact values for the Floats
+    return sympify(x, rational=True).evalf(n, **options)
+
+
+def _evalf_with_bounded_error(x: 'Expr', eps: 'Optional[Expr]' = None,
+                              m: int = 0,
+                              options: Optional[OPT_DICT] = None) -> TMP_RES:
+    """
+    Evaluate *x* to within a bounded absolute error.
+
+    Parameters
+    ==========
+
+    x : Expr
+        The quantity to be evaluated.
+    eps : Expr, None, optional (default=None)
+        Positive real upper bound on the acceptable error.
+    m : int, optional (default=0)
+        If *eps* is None, then use 2**(-m) as the upper bound on the error.
+    options: OPT_DICT
+        As in the ``evalf`` function.
+
+    Returns
+    =======
+
+    A tuple ``(re, im, re_acc, im_acc)``, as returned by ``evalf``.
+
+    See Also
+    ========
+
+    evalf
+
+    """
+    if eps is not None:
+        if not (eps.is_Rational or eps.is_Float) or not eps > 0:
+            raise ValueError("eps must be positive")
+        r, _, _, _ = evalf(1/eps, 1, {})
+        m = fastlog(r)
+
+    c, d, _, _ = evalf(x, 1, {})
+    # Note: If x = a + b*I, then |a| <= 2|c| and |b| <= 2|d|, with equality
+    # only in the zero case.
+    # If a is non-zero, then |c| = 2**nc for some integer nc, and c has
+    # bitcount 1. Therefore 2**fastlog(c) = 2**(nc+1) = 2|c| is an upper bound
+    # on |a|. Likewise for b and d.
+    nr, ni = fastlog(c), fastlog(d)
+    n = max(nr, ni) + 1
+    # If x is 0, then n is MINUS_INF, and p will be 1. Otherwise,
+    # n - 1 bits get us past the integer parts of a and b, and +1 accounts for
+    # the factor of <= sqrt(2) that is |x|/max(|a|, |b|).
+    p = max(1, m + n + 1)
+
+    options = options or {}
+    return evalf(x, p, options)

env-llmeval/lib/python3.10/site-packages/sympy/core/exprtools.py

@@ -0,0 +1,1569 @@
+"""Tools for manipulating of large commutative expressions. """
+
+from .add import Add
+from .mul import Mul, _keep_coeff
+from .power import Pow
+from .basic import Basic
+from .expr import Expr
+from .function import expand_power_exp
+from .sympify import sympify
+from .numbers import Rational, Integer, Number, I, equal_valued
+from .singleton import S
+from .sorting import default_sort_key, ordered
+from .symbol import Dummy
+from .traversal import preorder_traversal
+from .coreerrors import NonCommutativeExpression
+from .containers import Tuple, Dict
+from sympy.external.gmpy import SYMPY_INTS
+from sympy.utilities.iterables import (common_prefix, common_suffix,
+        variations, iterable, is_sequence)
+
+from collections import defaultdict
+from typing import Tuple as tTuple
+
+
+_eps = Dummy(positive=True)
+
+
+def _isnumber(i):
+    return isinstance(i, (SYMPY_INTS, float)) or i.is_Number
+
+
+def _monotonic_sign(self):
+    """Return the value closest to 0 that ``self`` may have if all symbols
+    are signed and the result is uniformly the same sign for all values of symbols.
+    If a symbol is only signed but not known to be an
+    integer or the result is 0 then a symbol representative of the sign of self
+    will be returned. Otherwise, None is returned if a) the sign could be positive
+    or negative or b) self is not in one of the following forms:
+
+    - L(x, y, ...) + A: a function linear in all symbols x, y, ... with an
+      additive constant; if A is zero then the function can be a monomial whose
+      sign is monotonic over the range of the variables, e.g. (x + 1)**3 if x is
+      nonnegative.
+    - A/L(x, y, ...) + B: the inverse of a function linear in all symbols x, y, ...
+      that does not have a sign change from positive to negative for any set
+      of values for the variables.
+    - M(x, y, ...) + A: a monomial M whose factors are all signed and a constant, A.
+    - A/M(x, y, ...) + B: the inverse of a monomial and constants A and B.
+    - P(x): a univariate polynomial
+
+    Examples
+    ========
+
+    >>> from sympy.core.exprtools import _monotonic_sign as F
+    >>> from sympy import Dummy
+    >>> nn = Dummy(integer=True, nonnegative=True)
+    >>> p = Dummy(integer=True, positive=True)
+    >>> p2 = Dummy(integer=True, positive=True)
+    >>> F(nn + 1)
+    1
+    >>> F(p - 1)
+    _nneg
+    >>> F(nn*p + 1)
+    1
+    >>> F(p2*p + 1)
+    2
+    >>> F(nn - 1)  # could be negative, zero or positive
+    """
+    if not self.is_extended_real:
+        return
+
+    if (-self).is_Symbol:
+        rv = _monotonic_sign(-self)
+        return rv if rv is None else -rv
+
+    if not self.is_Add and self.as_numer_denom()[1].is_number:
+        s = self
+        if s.is_prime:
+            if s.is_odd:
+                return Integer(3)
+            else:
+                return Integer(2)
+        elif s.is_composite:
+            if s.is_odd:
+                return Integer(9)
+            else:
+                return Integer(4)
+        elif s.is_positive:
+            if s.is_even:
+                if s.is_prime is False:
+                    return Integer(4)
+                else:
+                    return Integer(2)
+            elif s.is_integer:
+                return S.One
+            else:
+                return _eps
+        elif s.is_extended_negative:
+            if s.is_even:
+                return Integer(-2)
+            elif s.is_integer:
+                return S.NegativeOne
+            else:
+                return -_eps
+        if s.is_zero or s.is_extended_nonpositive or s.is_extended_nonnegative:
+            return S.Zero
+        return None
+
+    # univariate polynomial
+    free = self.free_symbols
+    if len(free) == 1:
+        if self.is_polynomial():
+            from sympy.polys.polytools import real_roots
+            from sympy.polys.polyroots import roots
+            from sympy.polys.polyerrors import PolynomialError
+            x = free.pop()
+            x0 = _monotonic_sign(x)
+            if x0 in (_eps, -_eps):
+                x0 = S.Zero
+            if x0 is not None:
+                d = self.diff(x)
+                if d.is_number:
+                    currentroots = []
+                else:
+                    try:
+                        currentroots = real_roots(d)
+                    except (PolynomialError, NotImplementedError):
+                        currentroots = [r for r in roots(d, x) if r.is_extended_real]
+                y = self.subs(x, x0)
+                if x.is_nonnegative and all(
+                        (r - x0).is_nonpositive for r in currentroots):
+                    if y.is_nonnegative and d.is_positive:
+                        if y:
+                            return y if y.is_positive else Dummy('pos', positive=True)
+                        else:
+                            return Dummy('nneg', nonnegative=True)
+                    if y.is_nonpositive and d.is_negative:
+                        if y:
+                            return y if y.is_negative else Dummy('neg', negative=True)
+                        else:
+                            return Dummy('npos', nonpositive=True)
+                elif x.is_nonpositive and all(
+                        (r - x0).is_nonnegative for r in currentroots):
+                    if y.is_nonnegative and d.is_negative:
+                        if y:
+                            return Dummy('pos', positive=True)
+                        else:
+                            return Dummy('nneg', nonnegative=True)
+                    if y.is_nonpositive and d.is_positive:
+                        if y:
+                            return Dummy('neg', negative=True)
+                        else:
+                            return Dummy('npos', nonpositive=True)
+        else:
+            n, d = self.as_numer_denom()
+            den = None
+            if n.is_number:
+                den = _monotonic_sign(d)
+            elif not d.is_number:
+                if _monotonic_sign(n) is not None:
+                    den = _monotonic_sign(d)
+            if den is not None and (den.is_positive or den.is_negative):
+                v = n*den
+                if v.is_positive:
+                    return Dummy('pos', positive=True)
+                elif v.is_nonnegative:
+                    return Dummy('nneg', nonnegative=True)
+                elif v.is_negative:
+                    return Dummy('neg', negative=True)
+                elif v.is_nonpositive:
+                    return Dummy('npos', nonpositive=True)
+        return None
+
+    # multivariate
+    c, a = self.as_coeff_Add()
+    v = None
+    if not a.is_polynomial():
+        # F/A or A/F where A is a number and F is a signed, rational monomial
+        n, d = a.as_numer_denom()
+        if not (n.is_number or d.is_number):
+            return
+        if (
+                a.is_Mul or a.is_Pow) and \
+                a.is_rational and \
+                all(p.exp.is_Integer for p in a.atoms(Pow) if p.is_Pow) and \
+                (a.is_positive or a.is_negative):
+            v = S.One
+            for ai in Mul.make_args(a):
+                if ai.is_number:
+                    v *= ai
+                    continue
+                reps = {}
+                for x in ai.free_symbols:
+                    reps[x] = _monotonic_sign(x)
+                    if reps[x] is None:
+                        return
+                v *= ai.subs(reps)
+    elif c:
+        # signed linear expression
+        if not any(p for p in a.atoms(Pow) if not p.is_number) and (a.is_nonpositive or a.is_nonnegative):
+            free = list(a.free_symbols)
+            p = {}
+            for i in free:
+                v = _monotonic_sign(i)
+                if v is None:
+                    return
+                p[i] = v or (_eps if i.is_nonnegative else -_eps)
+            v = a.xreplace(p)
+    if v is not None:
+        rv = v + c
+        if v.is_nonnegative and rv.is_positive:
+            return rv.subs(_eps, 0)
+        if v.is_nonpositive and rv.is_negative:
+            return rv.subs(_eps, 0)
+
+
+def decompose_power(expr: Expr) -> tTuple[Expr, int]:
+    """
+    Decompose power into symbolic base and integer exponent.
+
+    Examples
+    ========
+
+    >>> from sympy.core.exprtools import decompose_power
+    >>> from sympy.abc import x, y
+    >>> from sympy import exp
+
+    >>> decompose_power(x)
+    (x, 1)
+    >>> decompose_power(x**2)
+    (x, 2)
+    >>> decompose_power(exp(2*y/3))
+    (exp(y/3), 2)
+
+    """
+    base, exp = expr.as_base_exp()
+
+    if exp.is_Number:
+        if exp.is_Rational:
+            if not exp.is_Integer:
+                base = Pow(base, Rational(1, exp.q))  # type: ignore
+            e = exp.p  # type: ignore
+        else:
+            base, e = expr, 1
+    else:
+        exp, tail = exp.as_coeff_Mul(rational=True)
+
+        if exp is S.NegativeOne:
+            base, e = Pow(base, tail), -1
+        elif exp is not S.One:
+            # todo: after dropping python 3.7 support, use overload and Literal
+            #  in as_coeff_Mul to make exp Rational, and remove these 2 ignores
+            tail = _keep_coeff(Rational(1, exp.q), tail)  # type: ignore
+            base, e = Pow(base, tail), exp.p  # type: ignore
+        else:
+            base, e = expr, 1
+
+    return base, e
+
+
+def decompose_power_rat(expr: Expr) -> tTuple[Expr, Rational]:
+    """
+    Decompose power into symbolic base and rational exponent;
+    if the exponent is not a Rational, then separate only the
+    integer coefficient.
+
+    Examples
+    ========
+
+    >>> from sympy.core.exprtools import decompose_power_rat
+    >>> from sympy.abc import x
+    >>> from sympy import sqrt, exp
+
+    >>> decompose_power_rat(sqrt(x))
+    (x, 1/2)
+    >>> decompose_power_rat(exp(-3*x/2))
+    (exp(x/2), -3)
+
+    """
+    _ = base, exp = expr.as_base_exp()
+    return _ if exp.is_Rational else decompose_power(expr)
+
+
+class Factors:
+    """Efficient representation of ``f_1*f_2*...*f_n``."""
+
+    __slots__ = ('factors', 'gens')
+
+    def __init__(self, factors=None):  # Factors
+        """Initialize Factors from dict or expr.
+
+        Examples
+        ========
+
+        >>> from sympy.core.exprtools import Factors
+        >>> from sympy.abc import x
+        >>> from sympy import I
+        >>> e = 2*x**3
+        >>> Factors(e)
+        Factors({2: 1, x: 3})
+        >>> Factors(e.as_powers_dict())
+        Factors({2: 1, x: 3})
+        >>> f = _
+        >>> f.factors  # underlying dictionary
+        {2: 1, x: 3}
+        >>> f.gens  # base of each factor
+        frozenset({2, x})
+        >>> Factors(0)
+        Factors({0: 1})
+        >>> Factors(I)
+        Factors({I: 1})
+
+        Notes
+        =====
+
+        Although a dictionary can be passed, only minimal checking is
+        performed: powers of -1 and I are made canonical.
+
+        """
+        if isinstance(factors, (SYMPY_INTS, float)):
+            factors = S(factors)
+        if isinstance(factors, Factors):
+            factors = factors.factors.copy()
+        elif factors in (None, S.One):
+            factors = {}
+        elif factors is S.Zero or factors == 0:
+            factors = {S.Zero: S.One}
+        elif isinstance(factors, Number):
+            n = factors
+            factors = {}
+            if n < 0:
+                factors[S.NegativeOne] = S.One
+                n = -n
+            if n is not S.One:
+                if n.is_Float or n.is_Integer or n is S.Infinity:
+                    factors[n] = S.One
+                elif n.is_Rational:
+                    # since we're processing Numbers, the denominator is
+                    # stored with a negative exponent; all other factors
+                    # are left .
+                    if n.p != 1:
+                        factors[Integer(n.p)] = S.One
+                    factors[Integer(n.q)] = S.NegativeOne
+                else:
+                    raise ValueError('Expected Float|Rational|Integer, not %s' % n)
+        elif isinstance(factors, Basic) and not factors.args:
+            factors = {factors: S.One}
+        elif isinstance(factors, Expr):
+            c, nc = factors.args_cnc()
+            i = c.count(I)
+            for _ in range(i):
+                c.remove(I)
+            factors = dict(Mul._from_args(c).as_powers_dict())
+            # Handle all rational Coefficients
+            for f in list(factors.keys()):
+                if isinstance(f, Rational) and not isinstance(f, Integer):
+                    p, q = Integer(f.p), Integer(f.q)
+                    factors[p] = (factors[p] if p in factors else S.Zero) + factors[f]
+                    factors[q] = (factors[q] if q in factors else S.Zero) - factors[f]
+                    factors.pop(f)
+            if i:
+                factors[I] = factors.get(I, S.Zero) + i
+            if nc:
+                factors[Mul(*nc, evaluate=False)] = S.One
+        else:
+            factors = factors.copy()  # /!\ should be dict-like
+
+            # tidy up -/+1 and I exponents if Rational
+
+            handle = [k for k in factors if k is I or k in (-1, 1)]
+            if handle:
+                i1 = S.One
+                for k in handle:
+                    if not _isnumber(factors[k]):
+                        continue
+                    i1 *= k**factors.pop(k)
+                if i1 is not S.One:
+                    for a in i1.args if i1.is_Mul else [i1]:  # at worst, -1.0*I*(-1)**e
+                        if a is S.NegativeOne:
+                            factors[a] = S.One
+                        elif a is I:
+                            factors[I] = S.One
+                        elif a.is_Pow:
+                            factors[a.base] = factors.get(a.base, S.Zero) + a.exp
+                        elif equal_valued(a, 1):
+                            factors[a] = S.One
+                        elif equal_valued(a, -1):
+                            factors[-a] = S.One
+                            factors[S.NegativeOne] = S.One
+                        else:
+                            raise ValueError('unexpected factor in i1: %s' % a)
+
+        self.factors = factors
+        keys = getattr(factors, 'keys', None)
+        if keys is None:
+            raise TypeError('expecting Expr or dictionary')
+        self.gens = frozenset(keys())
+
+    def __hash__(self):  # Factors
+        keys = tuple(ordered(self.factors.keys()))
+        values = [self.factors[k] for k in keys]
+        return hash((keys, values))
+
+    def __repr__(self):  # Factors
+        return "Factors({%s})" % ', '.join(
+            ['%s: %s' % (k, v) for k, v in ordered(self.factors.items())])
+
+    @property
+    def is_zero(self):  # Factors
+        """
+        >>> from sympy.core.exprtools import Factors
+        >>> Factors(0).is_zero
+        True
+        """
+        f = self.factors
+        return len(f) == 1 and S.Zero in f
+
+    @property
+    def is_one(self):  # Factors
+        """
+        >>> from sympy.core.exprtools import Factors
+        >>> Factors(1).is_one
+        True
+        """
+        return not self.factors
+
+    def as_expr(self):  # Factors
+        """Return the underlying expression.
+
+        Examples
+        ========
+
+        >>> from sympy.core.exprtools import Factors
+        >>> from sympy.abc import x, y
+        >>> Factors((x*y**2).as_powers_dict()).as_expr()
+        x*y**2
+
+        """
+
+        args = []
+        for factor, exp in self.factors.items():
+            if exp != 1:
+                if isinstance(exp, Integer):
+                    b, e = factor.as_base_exp()
+                    e = _keep_coeff(exp, e)
+                    args.append(b**e)
+                else:
+                    args.append(factor**exp)
+            else:
+                args.append(factor)
+        return Mul(*args)
+
+    def mul(self, other):  # Factors
+        """Return Factors of ``self * other``.
+
+        Examples
+        ========
+
+        >>> from sympy.core.exprtools import Factors
+        >>> from sympy.abc import x, y, z
+        >>> a = Factors((x*y**2).as_powers_dict())
+        >>> b = Factors((x*y/z).as_powers_dict())
+        >>> a.mul(b)
+        Factors({x: 2, y: 3, z: -1})
+        >>> a*b
+        Factors({x: 2, y: 3, z: -1})
+        """
+        if not isinstance(other, Factors):
+            other = Factors(other)
+        if any(f.is_zero for f in (self, other)):
+            return Factors(S.Zero)
+        factors = dict(self.factors)
+
+        for factor, exp in other.factors.items():
+            if factor in factors:
+                exp = factors[factor] + exp
+
+                if not exp:
+                    del factors[factor]
+                    continue
+
+            factors[factor] = exp
+
+        return Factors(factors)
+
+    def normal(self, other):
+        """Return ``self`` and ``other`` with ``gcd`` removed from each.
+        The only differences between this and method ``div`` is that this
+        is 1) optimized for the case when there are few factors in common and
+        2) this does not raise an error if ``other`` is zero.
+
+        See Also
+        ========
+        div
+
+        """
+        if not isinstance(other, Factors):
+            other = Factors(other)
+            if other.is_zero:
+                return (Factors(), Factors(S.Zero))
+            if self.is_zero:
+                return (Factors(S.Zero), Factors())
+
+        self_factors = dict(self.factors)
+        other_factors = dict(other.factors)
+
+        for factor, self_exp in self.factors.items():
+            try:
+                other_exp = other.factors[factor]
+            except KeyError:
+                continue
+
+            exp = self_exp - other_exp
+
+            if not exp:
+                del self_factors[factor]
+                del other_factors[factor]
+            elif _isnumber(exp):
+                if exp > 0:
+                    self_factors[factor] = exp
+                    del other_factors[factor]
+                else:
+                    del self_factors[factor]
+                    other_factors[factor] = -exp
+            else:
+                r = self_exp.extract_additively(other_exp)
+                if r is not None:
+                    if r:
+                        self_factors[factor] = r
+                        del other_factors[factor]
+                    else:  # should be handled already
+                        del self_factors[factor]
+                        del other_factors[factor]
+                else:
+                    sc, sa = self_exp.as_coeff_Add()
+                    if sc:
+                        oc, oa = other_exp.as_coeff_Add()
+                        diff = sc - oc
+                        if diff > 0:
+                            self_factors[factor] -= oc
+                            other_exp = oa
+                        elif diff < 0:
+                            self_factors[factor] -= sc
+                            other_factors[factor] -= sc
+                            other_exp = oa - diff
+                        else:
+                            self_factors[factor] = sa
+                            other_exp = oa
+                    if other_exp:
+                        other_factors[factor] = other_exp
+                    else:
+                        del other_factors[factor]
+
+        return Factors(self_factors), Factors(other_factors)
+
+    def div(self, other):  # Factors
+        """Return ``self`` and ``other`` with ``gcd`` removed from each.
+        This is optimized for the case when there are many factors in common.
+
+        Examples
+        ========
+
+        >>> from sympy.core.exprtools import Factors
+        >>> from sympy.abc import x, y, z
+        >>> from sympy import S
+
+        >>> a = Factors((x*y**2).as_powers_dict())
+        >>> a.div(a)
+        (Factors({}), Factors({}))
+        >>> a.div(x*z)
+        (Factors({y: 2}), Factors({z: 1}))
+
+        The ``/`` operator only gives ``quo``:
+
+        >>> a/x
+        Factors({y: 2})
+
+        Factors treats its factors as though they are all in the numerator, so
+        if you violate this assumption the results will be correct but will
+        not strictly correspond to the numerator and denominator of the ratio:
+
+        >>> a.div(x/z)
+        (Factors({y: 2}), Factors({z: -1}))
+
+        Factors is also naive about bases: it does not attempt any denesting
+        of Rational-base terms, for example the following does not become
+        2**(2*x)/2.
+
+        >>> Factors(2**(2*x + 2)).div(S(8))
+        (Factors({2: 2*x + 2}), Factors({8: 1}))
+
+        factor_terms can clean up such Rational-bases powers:
+
+        >>> from sympy import factor_terms
+        >>> n, d = Factors(2**(2*x + 2)).div(S(8))
+        >>> n.as_expr()/d.as_expr()
+        2**(2*x + 2)/8
+        >>> factor_terms(_)
+        2**(2*x)/2
+
+        """
+        quo, rem = dict(self.factors), {}
+
+        if not isinstance(other, Factors):
+            other = Factors(other)
+            if other.is_zero:
+                raise ZeroDivisionError
+            if self.is_zero:
+                return (Factors(S.Zero), Factors())
+
+        for factor, exp in other.factors.items():
+            if factor in quo:
+                d = quo[factor] - exp
+                if _isnumber(d):
+                    if d <= 0:
+                        del quo[factor]
+
+                    if d >= 0:
+                        if d:
+                            quo[factor] = d
+
+                        continue
+
+                    exp = -d
+
+                else:
+                    r = quo[factor].extract_additively(exp)
+                    if r is not None:
+                        if r:
+                            quo[factor] = r
+                        else:  # should be handled already
+                            del quo[factor]
+                    else:
+                        other_exp = exp
+                        sc, sa = quo[factor].as_coeff_Add()
+                        if sc:
+                            oc, oa = other_exp.as_coeff_Add()
+                            diff = sc - oc
+                            if diff > 0:
+                                quo[factor] -= oc
+                                other_exp = oa
+                            elif diff < 0:
+                                quo[factor] -= sc
+                                other_exp = oa - diff
+                            else:
+                                quo[factor] = sa
+                                other_exp = oa
+                        if other_exp:
+                            rem[factor] = other_exp
+                        else:
+                            assert factor not in rem
+                    continue
+
+            rem[factor] = exp
+
+        return Factors(quo), Factors(rem)
+
+    def quo(self, other):  # Factors
+        """Return numerator Factor of ``self / other``.
+
+        Examples
+        ========
+
+        >>> from sympy.core.exprtools import Factors
+        >>> from sympy.abc import x, y, z
+        >>> a = Factors((x*y**2).as_powers_dict())
+        >>> b = Factors((x*y/z).as_powers_dict())
+        >>> a.quo(b)  # same as a/b
+        Factors({y: 1})
+        """
+        return self.div(other)[0]
+
+    def rem(self, other):  # Factors
+        """Return denominator Factors of ``self / other``.
+
+        Examples
+        ========
+
+        >>> from sympy.core.exprtools import Factors
+        >>> from sympy.abc import x, y, z
+        >>> a = Factors((x*y**2).as_powers_dict())
+        >>> b = Factors((x*y/z).as_powers_dict())
+        >>> a.rem(b)
+        Factors({z: -1})
+        >>> a.rem(a)
+        Factors({})
+        """
+        return self.div(other)[1]
+
+    def pow(self, other):  # Factors
+        """Return self raised to a non-negative integer power.
+
+        Examples
+        ========
+
+        >>> from sympy.core.exprtools import Factors
+        >>> from sympy.abc import x, y
+        >>> a = Factors((x*y**2).as_powers_dict())
+        >>> a**2
+        Factors({x: 2, y: 4})
+
+        """
+        if isinstance(other, Factors):
+            other = other.as_expr()
+            if other.is_Integer:
+                other = int(other)
+        if isinstance(other, SYMPY_INTS) and other >= 0:
+            factors = {}
+
+            if other:
+                for factor, exp in self.factors.items():
+                    factors[factor] = exp*other
+
+            return Factors(factors)
+        else:
+            raise ValueError("expected non-negative integer, got %s" % other)
+
+    def gcd(self, other):  # Factors
+        """Return Factors of ``gcd(self, other)``. The keys are
+        the intersection of factors with the minimum exponent for
+        each factor.
+
+        Examples
+        ========
+
+        >>> from sympy.core.exprtools import Factors
+        >>> from sympy.abc import x, y, z
+        >>> a = Factors((x*y**2).as_powers_dict())
+        >>> b = Factors((x*y/z).as_powers_dict())
+        >>> a.gcd(b)
+        Factors({x: 1, y: 1})
+        """
+        if not isinstance(other, Factors):
+            other = Factors(other)
+            if other.is_zero:
+                return Factors(self.factors)
+
+        factors = {}
+
+        for factor, exp in self.factors.items():
+            factor, exp = sympify(factor), sympify(exp)
+            if factor in other.factors:
+                lt = (exp - other.factors[factor]).is_negative
+                if lt == True:
+                    factors[factor] = exp
+                elif lt == False:
+                    factors[factor] = other.factors[factor]
+
+        return Factors(factors)
+
+    def lcm(self, other):  # Factors
+        """Return Factors of ``lcm(self, other)`` which are
+        the union of factors with the maximum exponent for
+        each factor.
+
+        Examples
+        ========
+
+        >>> from sympy.core.exprtools import Factors
+        >>> from sympy.abc import x, y, z
+        >>> a = Factors((x*y**2).as_powers_dict())
+        >>> b = Factors((x*y/z).as_powers_dict())
+        >>> a.lcm(b)
+        Factors({x: 1, y: 2, z: -1})
+        """
+        if not isinstance(other, Factors):
+            other = Factors(other)
+            if any(f.is_zero for f in (self, other)):
+                return Factors(S.Zero)
+
+        factors = dict(self.factors)
+
+        for factor, exp in other.factors.items():
+            if factor in factors:
+                exp = max(exp, factors[factor])
+
+            factors[factor] = exp
+
+        return Factors(factors)
+
+    def __mul__(self, other):  # Factors
+        return self.mul(other)
+
+    def __divmod__(self, other):  # Factors
+        return self.div(other)
+
+    def __truediv__(self, other):  # Factors
+        return self.quo(other)
+
+    def __mod__(self, other):  # Factors
+        return self.rem(other)
+
+    def __pow__(self, other):  # Factors
+        return self.pow(other)
+
+    def __eq__(self, other):  # Factors
+        if not isinstance(other, Factors):
+            other = Factors(other)
+        return self.factors == other.factors
+
+    def __ne__(self, other):  # Factors
+        return not self == other
+
+
+class Term:
+    """Efficient representation of ``coeff*(numer/denom)``. """
+
+    __slots__ = ('coeff', 'numer', 'denom')
+
+    def __init__(self, term, numer=None, denom=None):  # Term
+        if numer is None and denom is None:
+            if not term.is_commutative:
+                raise NonCommutativeExpression(
+                    'commutative expression expected')
+
+            coeff, factors = term.as_coeff_mul()
+            numer, denom = defaultdict(int), defaultdict(int)
+
+            for factor in factors:
+                base, exp = decompose_power(factor)
+
+                if base.is_Add:
+                    cont, base = base.primitive()
+                    coeff *= cont**exp
+
+                if exp > 0:
+                    numer[base] += exp
+                else:
+                    denom[base] += -exp
+
+            numer = Factors(numer)
+            denom = Factors(denom)
+        else:
+            coeff = term
+
+            if numer is None:
+                numer = Factors()
+
+            if denom is None:
+                denom = Factors()
+
+        self.coeff = coeff
+        self.numer = numer
+        self.denom = denom
+
+    def __hash__(self):  # Term
+        return hash((self.coeff, self.numer, self.denom))
+
+    def __repr__(self):  # Term
+        return "Term(%s, %s, %s)" % (self.coeff, self.numer, self.denom)
+
+    def as_expr(self):  # Term
+        return self.coeff*(self.numer.as_expr()/self.denom.as_expr())
+
+    def mul(self, other):  # Term
+        coeff = self.coeff*other.coeff
+        numer = self.numer.mul(other.numer)
+        denom = self.denom.mul(other.denom)
+
+        numer, denom = numer.normal(denom)
+
+        return Term(coeff, numer, denom)
+
+    def inv(self):  # Term
+        return Term(1/self.coeff, self.denom, self.numer)
+
+    def quo(self, other):  # Term
+        return self.mul(other.inv())
+
+    def pow(self, other):  # Term
+        if other < 0:
+            return self.inv().pow(-other)
+        else:
+            return Term(self.coeff ** other,
+                        self.numer.pow(other),
+                        self.denom.pow(other))
+
+    def gcd(self, other):  # Term
+        return Term(self.coeff.gcd(other.coeff),
+                    self.numer.gcd(other.numer),
+                    self.denom.gcd(other.denom))
+
+    def lcm(self, other):  # Term
+        return Term(self.coeff.lcm(other.coeff),
+                    self.numer.lcm(other.numer),
+                    self.denom.lcm(other.denom))
+
+    def __mul__(self, other):  # Term
+        if isinstance(other, Term):
+            return self.mul(other)
+        else:
+            return NotImplemented
+
+    def __truediv__(self, other):  # Term
+        if isinstance(other, Term):
+            return self.quo(other)
+        else:
+            return NotImplemented
+
+    def __pow__(self, other):  # Term
+        if isinstance(other, SYMPY_INTS):
+            return self.pow(other)
+        else:
+            return NotImplemented
+
+    def __eq__(self, other):  # Term
+        return (self.coeff == other.coeff and
+                self.numer == other.numer and
+                self.denom == other.denom)
+
+    def __ne__(self, other):  # Term
+        return not self == other
+
+
+def _gcd_terms(terms, isprimitive=False, fraction=True):
+    """Helper function for :func:`gcd_terms`.
+
+    Parameters
+    ==========
+
+    isprimitive : boolean, optional
+        If ``isprimitive`` is True then the call to primitive
+        for an Add will be skipped. This is useful when the
+        content has already been extracted.
+
+    fraction : boolean, optional
+        If ``fraction`` is True then the expression will appear over a common
+        denominator, the lcm of all term denominators.
+    """
+
+    if isinstance(terms, Basic) and not isinstance(terms, Tuple):
+        terms = Add.make_args(terms)
+
+    terms = list(map(Term, [t for t in terms if t]))
+
+    # there is some simplification that may happen if we leave this
+    # here rather than duplicate it before the mapping of Term onto
+    # the terms
+    if len(terms) == 0:
+        return S.Zero, S.Zero, S.One
+
+    if len(terms) == 1:
+        cont = terms[0].coeff
+        numer = terms[0].numer.as_expr()
+        denom = terms[0].denom.as_expr()
+
+    else:
+        cont = terms[0]
+        for term in terms[1:]:
+            cont = cont.gcd(term)
+
+        for i, term in enumerate(terms):
+            terms[i] = term.quo(cont)
+
+        if fraction:
+            denom = terms[0].denom
+
+            for term in terms[1:]:
+                denom = denom.lcm(term.denom)
+
+            numers = []
+            for term in terms:
+                numer = term.numer.mul(denom.quo(term.denom))
+                numers.append(term.coeff*numer.as_expr())
+        else:
+            numers = [t.as_expr() for t in terms]
+            denom = Term(S.One).numer
+
+        cont = cont.as_expr()
+        numer = Add(*numers)
+        denom = denom.as_expr()
+
+    if not isprimitive and numer.is_Add:
+        _cont, numer = numer.primitive()
+        cont *= _cont
+
+    return cont, numer, denom
+
+
+def gcd_terms(terms, isprimitive=False, clear=True, fraction=True):
+    """Compute the GCD of ``terms`` and put them together.
+
+    Parameters
+    ==========
+
+    terms : Expr
+        Can be an expression or a non-Basic sequence of expressions
+        which will be handled as though they are terms from a sum.
+
+    isprimitive : bool, optional
+        If ``isprimitive`` is True the _gcd_terms will not run the primitive
+        method on the terms.
+
+    clear : bool, optional
+        It controls the removal of integers from the denominator of an Add
+        expression. When True (default), all numerical denominator will be cleared;
+        when False the denominators will be cleared only if all terms had numerical
+        denominators other than 1.
+
+    fraction : bool, optional
+        When True (default), will put the expression over a common
+        denominator.
+
+    Examples
+    ========
+
+    >>> from sympy import gcd_terms
+    >>> from sympy.abc import x, y
+
+    >>> gcd_terms((x + 1)**2*y + (x + 1)*y**2)
+    y*(x + 1)*(x + y + 1)
+    >>> gcd_terms(x/2 + 1)
+    (x + 2)/2
+    >>> gcd_terms(x/2 + 1, clear=False)
+    x/2 + 1
+    >>> gcd_terms(x/2 + y/2, clear=False)
+    (x + y)/2
+    >>> gcd_terms(x/2 + 1/x)
+    (x**2 + 2)/(2*x)
+    >>> gcd_terms(x/2 + 1/x, fraction=False)
+    (x + 2/x)/2
+    >>> gcd_terms(x/2 + 1/x, fraction=False, clear=False)
+    x/2 + 1/x
+
+    >>> gcd_terms(x/2/y + 1/x/y)
+    (x**2 + 2)/(2*x*y)
+    >>> gcd_terms(x/2/y + 1/x/y, clear=False)
+    (x**2/2 + 1)/(x*y)
+    >>> gcd_terms(x/2/y + 1/x/y, clear=False, fraction=False)
+    (x/2 + 1/x)/y
+
+    The ``clear`` flag was ignored in this case because the returned
+    expression was a rational expression, not a simple sum.
+
+    See Also
+    ========
+
+    factor_terms, sympy.polys.polytools.terms_gcd
+
+    """
+    def mask(terms):
+        """replace nc portions of each term with a unique Dummy symbols
+        and return the replacements to restore them"""
+        args = [(a, []) if a.is_commutative else a.args_cnc() for a in terms]
+        reps = []
+        for i, (c, nc) in enumerate(args):
+            if nc:
+                nc = Mul(*nc)
+                d = Dummy()
+                reps.append((d, nc))
+                c.append(d)
+                args[i] = Mul(*c)
+            else:
+                args[i] = c
+        return args, dict(reps)
+
+    isadd = isinstance(terms, Add)
+    addlike = isadd or not isinstance(terms, Basic) and \
+        is_sequence(terms, include=set) and \
+        not isinstance(terms, Dict)
+
+    if addlike:
+        if isadd:  # i.e. an Add
+            terms = list(terms.args)
+        else:
+            terms = sympify(terms)
+        terms, reps = mask(terms)
+        cont, numer, denom = _gcd_terms(terms, isprimitive, fraction)
+        numer = numer.xreplace(reps)
+        coeff, factors = cont.as_coeff_Mul()
+        if not clear:
+            c, _coeff = coeff.as_coeff_Mul()
+            if not c.is_Integer and not clear and numer.is_Add:
+                n, d = c.as_numer_denom()
+                _numer = numer/d
+                if any(a.as_coeff_Mul()[0].is_Integer
+                        for a in _numer.args):
+                    numer = _numer
+                    coeff = n*_coeff
+        return _keep_coeff(coeff, factors*numer/denom, clear=clear)
+
+    if not isinstance(terms, Basic):
+        return terms
+
+    if terms.is_Atom:
+        return terms
+
+    if terms.is_Mul:
+        c, args = terms.as_coeff_mul()
+        return _keep_coeff(c, Mul(*[gcd_terms(i, isprimitive, clear, fraction)
+            for i in args]), clear=clear)
+
+    def handle(a):
+        # don't treat internal args like terms of an Add
+        if not isinstance(a, Expr):
+            if isinstance(a, Basic):
+                if not a.args:
+                    return a
+                return a.func(*[handle(i) for i in a.args])
+            return type(a)([handle(i) for i in a])
+        return gcd_terms(a, isprimitive, clear, fraction)
+
+    if isinstance(terms, Dict):
+        return Dict(*[(k, handle(v)) for k, v in terms.args])
+    return terms.func(*[handle(i) for i in terms.args])
+
+
+def _factor_sum_int(expr, **kwargs):
+    """Return Sum or Integral object with factors that are not
+    in the wrt variables removed. In cases where there are additive
+    terms in the function of the object that are independent, the
+    object will be separated into two objects.
+
+    Examples
+    ========
+
+    >>> from sympy import Sum, factor_terms
+    >>> from sympy.abc import x, y
+    >>> factor_terms(Sum(x + y, (x, 1, 3)))
+    y*Sum(1, (x, 1, 3)) + Sum(x, (x, 1, 3))
+    >>> factor_terms(Sum(x*y, (x, 1, 3)))
+    y*Sum(x, (x, 1, 3))
+
+    Notes
+    =====
+
+    If a function in the summand or integrand is replaced
+    with a symbol, then this simplification should not be
+    done or else an incorrect result will be obtained when
+    the symbol is replaced with an expression that depends
+    on the variables of summation/integration:
+
+    >>> eq = Sum(y, (x, 1, 3))
+    >>> factor_terms(eq).subs(y, x).doit()
+    3*x
+    >>> eq.subs(y, x).doit()
+    6
+    """
+    result = expr.function
+    if result == 0:
+        return S.Zero
+    limits = expr.limits
+
+    # get the wrt variables
+    wrt = {i.args[0] for i in limits}
+
+    # factor out any common terms that are independent of wrt
+    f = factor_terms(result, **kwargs)
+    i, d = f.as_independent(*wrt)
+    if isinstance(f, Add):
+        return i * expr.func(1, *limits) + expr.func(d, *limits)
+    else:
+        return i * expr.func(d, *limits)
+
+
+def factor_terms(expr, radical=False, clear=False, fraction=False, sign=True):
+    """Remove common factors from terms in all arguments without
+    changing the underlying structure of the expr. No expansion or
+    simplification (and no processing of non-commutatives) is performed.
+
+    Parameters
+    ==========
+
+    radical: bool, optional
+        If radical=True then a radical common to all terms will be factored
+        out of any Add sub-expressions of the expr.
+
+    clear : bool, optional
+        If clear=False (default) then coefficients will not be separated
+        from a single Add if they can be distributed to leave one or more
+        terms with integer coefficients.
+
+    fraction : bool, optional
+        If fraction=True (default is False) then a common denominator will be
+        constructed for the expression.
+
+    sign : bool, optional
+        If sign=True (default) then even if the only factor in common is a -1,
+        it will be factored out of the expression.
+
+    Examples
+    ========
+
+    >>> from sympy import factor_terms, Symbol
+    >>> from sympy.abc import x, y
+    >>> factor_terms(x + x*(2 + 4*y)**3)
+    x*(8*(2*y + 1)**3 + 1)
+    >>> A = Symbol('A', commutative=False)
+    >>> factor_terms(x*A + x*A + x*y*A)
+    x*(y*A + 2*A)
+
+    When ``clear`` is False, a rational will only be factored out of an
+    Add expression if all terms of the Add have coefficients that are
+    fractions:
+
+    >>> factor_terms(x/2 + 1, clear=False)
+    x/2 + 1
+    >>> factor_terms(x/2 + 1, clear=True)
+    (x + 2)/2
+
+    If a -1 is all that can be factored out, to *not* factor it out, the
+    flag ``sign`` must be False:
+
+    >>> factor_terms(-x - y)
+    -(x + y)
+    >>> factor_terms(-x - y, sign=False)
+    -x - y
+    >>> factor_terms(-2*x - 2*y, sign=False)
+    -2*(x + y)
+
+    See Also
+    ========
+
+    gcd_terms, sympy.polys.polytools.terms_gcd
+
+    """
+    def do(expr):
+        from sympy.concrete.summations import Sum
+        from sympy.integrals.integrals import Integral
+        is_iterable = iterable(expr)
+
+        if not isinstance(expr, Basic) or expr.is_Atom:
+            if is_iterable:
+                return type(expr)([do(i) for i in expr])
+            return expr
+
+        if expr.is_Pow or expr.is_Function or \
+                is_iterable or not hasattr(expr, 'args_cnc'):
+            args = expr.args
+            newargs = tuple([do(i) for i in args])
+            if newargs == args:
+                return expr
+            return expr.func(*newargs)
+
+        if isinstance(expr, (Sum, Integral)):
+            return _factor_sum_int(expr,
+                radical=radical, clear=clear,
+                fraction=fraction, sign=sign)
+
+        cont, p = expr.as_content_primitive(radical=radical, clear=clear)
+        if p.is_Add:
+            list_args = [do(a) for a in Add.make_args(p)]
+            # get a common negative (if there) which gcd_terms does not remove
+            if not any(a.as_coeff_Mul()[0].extract_multiplicatively(-1) is None
+                       for a in list_args):
+                cont = -cont
+                list_args = [-a for a in list_args]
+            # watch out for exp(-(x+2)) which gcd_terms will change to exp(-x-2)
+            special = {}
+            for i, a in enumerate(list_args):
+                b, e = a.as_base_exp()
+                if e.is_Mul and e != Mul(*e.args):
+                    list_args[i] = Dummy()
+                    special[list_args[i]] = a
+            # rebuild p not worrying about the order which gcd_terms will fix
+            p = Add._from_args(list_args)
+            p = gcd_terms(p,
+                isprimitive=True,
+                clear=clear,
+                fraction=fraction).xreplace(special)
+        elif p.args:
+            p = p.func(
+                *[do(a) for a in p.args])
+        rv = _keep_coeff(cont, p, clear=clear, sign=sign)
+        return rv
+    expr = sympify(expr)
+    return do(expr)
+
+
+def _mask_nc(eq, name=None):
+    """
+    Return ``eq`` with non-commutative objects replaced with Dummy
+    symbols. A dictionary that can be used to restore the original
+    values is returned: if it is None, the expression is noncommutative
+    and cannot be made commutative. The third value returned is a list
+    of any non-commutative symbols that appear in the returned equation.
+
+    Explanation
+    ===========
+
+    All non-commutative objects other than Symbols are replaced with
+    a non-commutative Symbol. Identical objects will be identified
+    by identical symbols.
+
+    If there is only 1 non-commutative object in an expression it will
+    be replaced with a commutative symbol. Otherwise, the non-commutative
+    entities are retained and the calling routine should handle
+    replacements in this case since some care must be taken to keep
+    track of the ordering of symbols when they occur within Muls.
+
+    Parameters
+    ==========
+
+    name : str
+        ``name``, if given, is the name that will be used with numbered Dummy
+        variables that will replace the non-commutative objects and is mainly
+        used for doctesting purposes.
+
+    Examples
+    ========
+
+    >>> from sympy.physics.secondquant import Commutator, NO, F, Fd
+    >>> from sympy import symbols
+    >>> from sympy.core.exprtools import _mask_nc
+    >>> from sympy.abc import x, y
+    >>> A, B, C = symbols('A,B,C', commutative=False)
+
+    One nc-symbol:
+
+    >>> _mask_nc(A**2 - x**2, 'd')
+    (_d0**2 - x**2, {_d0: A}, [])
+
+    Multiple nc-symbols:
+
+    >>> _mask_nc(A**2 - B**2, 'd')
+    (A**2 - B**2, {}, [A, B])
+
+    An nc-object with nc-symbols but no others outside of it:
+
+    >>> _mask_nc(1 + x*Commutator(A, B), 'd')
+    (_d0*x + 1, {_d0: Commutator(A, B)}, [])
+    >>> _mask_nc(NO(Fd(x)*F(y)), 'd')
+    (_d0, {_d0: NO(CreateFermion(x)*AnnihilateFermion(y))}, [])
+
+    Multiple nc-objects:
+
+    >>> eq = x*Commutator(A, B) + x*Commutator(A, C)*Commutator(A, B)
+    >>> _mask_nc(eq, 'd')
+    (x*_d0 + x*_d1*_d0, {_d0: Commutator(A, B), _d1: Commutator(A, C)}, [_d0, _d1])
+
+    Multiple nc-objects and nc-symbols:
+
+    >>> eq = A*Commutator(A, B) + B*Commutator(A, C)
+    >>> _mask_nc(eq, 'd')
+    (A*_d0 + B*_d1, {_d0: Commutator(A, B), _d1: Commutator(A, C)}, [_d0, _d1, A, B])
+
+    """
+    name = name or 'mask'
+    # Make Dummy() append sequential numbers to the name
+
+    def numbered_names():
+        i = 0
+        while True:
+            yield name + str(i)
+            i += 1
+
+    names = numbered_names()
+
+    def Dummy(*args, **kwargs):
+        from .symbol import Dummy
+        return Dummy(next(names), *args, **kwargs)
+
+    expr = eq
+    if expr.is_commutative:
+        return eq, {}, []
+
+    # identify nc-objects; symbols and other
+    rep = []
+    nc_obj = set()
+    nc_syms = set()
+    pot = preorder_traversal(expr, keys=default_sort_key)
+    for i, a in enumerate(pot):
+        if any(a == r[0] for r in rep):
+            pot.skip()
+        elif not a.is_commutative:
+            if a.is_symbol:
+                nc_syms.add(a)
+                pot.skip()
+            elif not (a.is_Add or a.is_Mul or a.is_Pow):
+                nc_obj.add(a)
+                pot.skip()
+
+    # If there is only one nc symbol or object, it can be factored regularly
+    # but polys is going to complain, so replace it with a Dummy.
+    if len(nc_obj) == 1 and not nc_syms:
+        rep.append((nc_obj.pop(), Dummy()))
+    elif len(nc_syms) == 1 and not nc_obj:
+        rep.append((nc_syms.pop(), Dummy()))
+
+    # Any remaining nc-objects will be replaced with an nc-Dummy and
+    # identified as an nc-Symbol to watch out for
+    nc_obj = sorted(nc_obj, key=default_sort_key)
+    for n in nc_obj:
+        nc = Dummy(commutative=False)
+        rep.append((n, nc))
+        nc_syms.add(nc)
+    expr = expr.subs(rep)
+
+    nc_syms = list(nc_syms)
+    nc_syms.sort(key=default_sort_key)
+    return expr, {v: k for k, v in rep}, nc_syms
+
+
+def factor_nc(expr):
+    """Return the factored form of ``expr`` while handling non-commutative
+    expressions.
+
+    Examples
+    ========
+
+    >>> from sympy import factor_nc, Symbol
+    >>> from sympy.abc import x
+    >>> A = Symbol('A', commutative=False)
+    >>> B = Symbol('B', commutative=False)
+    >>> factor_nc((x**2 + 2*A*x + A**2).expand())
+    (x + A)**2
+    >>> factor_nc(((x + A)*(x + B)).expand())
+    (x + A)*(x + B)
+    """
+    expr = sympify(expr)
+    if not isinstance(expr, Expr) or not expr.args:
+        return expr
+    if not expr.is_Add:
+        return expr.func(*[factor_nc(a) for a in expr.args])
+    expr = expr.func(*[expand_power_exp(i) for i in expr.args])
+
+    from sympy.polys.polytools import gcd, factor
+    expr, rep, nc_symbols = _mask_nc(expr)
+
+    if rep:
+        return factor(expr).subs(rep)
+    else:
+        args = [a.args_cnc() for a in Add.make_args(expr)]
+        c = g = l = r = S.One
+        hit = False
+        # find any commutative gcd term
+        for i, a in enumerate(args):
+            if i == 0:
+                c = Mul._from_args(a[0])
+            elif a[0]:
+                c = gcd(c, Mul._from_args(a[0]))
+            else:
+                c = S.One
+        if c is not S.One:
+            hit = True
+            c, g = c.as_coeff_Mul()
+            if g is not S.One:
+                for i, (cc, _) in enumerate(args):
+                    cc = list(Mul.make_args(Mul._from_args(list(cc))/g))
+                    args[i][0] = cc
+            for i, (cc, _) in enumerate(args):
+                if cc:
+                    cc[0] = cc[0]/c
+                else:
+                    cc = [1/c]
+                args[i][0] = cc
+        # find any noncommutative common prefix
+        for i, a in enumerate(args):
+            if i == 0:
+                n = a[1][:]
+            else:
+                n = common_prefix(n, a[1])
+            if not n:
+                # is there a power that can be extracted?
+                if not args[0][1]:
+                    break
+                b, e = args[0][1][0].as_base_exp()
+                ok = False
+                if e.is_Integer:
+                    for t in args:
+                        if not t[1]:
+                            break
+                        bt, et = t[1][0].as_base_exp()
+                        if et.is_Integer and bt == b:
+                            e = min(e, et)
+                        else:
+                            break
+                    else:
+                        ok = hit = True
+                        l = b**e
+                        il = b**-e
+                        for _ in args:
+                            _[1][0] = il*_[1][0]
+                        break
+                if not ok:
+                    break
+        else:
+            hit = True
+            lenn = len(n)
+            l = Mul(*n)
+            for _ in args:
+                _[1] = _[1][lenn:]
+        # find any noncommutative common suffix
+        for i, a in enumerate(args):
+            if i == 0:
+                n = a[1][:]
+            else:
+                n = common_suffix(n, a[1])
+            if not n:
+                # is there a power that can be extracted?
+                if not args[0][1]:
+                    break
+                b, e = args[0][1][-1].as_base_exp()
+                ok = False
+                if e.is_Integer:
+                    for t in args:
+                        if not t[1]:
+                            break
+                        bt, et = t[1][-1].as_base_exp()
+                        if et.is_Integer and bt == b:
+                            e = min(e, et)
+                        else:
+                            break
+                    else:
+                        ok = hit = True
+                        r = b**e
+                        il = b**-e
+                        for _ in args:
+                            _[1][-1] = _[1][-1]*il
+                        break
+                if not ok:
+                    break
+        else:
+            hit = True
+            lenn = len(n)
+            r = Mul(*n)
+            for _ in args:
+                _[1] = _[1][:len(_[1]) - lenn]
+        if hit:
+            mid = Add(*[Mul(*cc)*Mul(*nc) for cc, nc in args])
+        else:
+            mid = expr
+
+        from sympy.simplify.powsimp import powsimp
+
+        # sort the symbols so the Dummys would appear in the same
+        # order as the original symbols, otherwise you may introduce
+        # a factor of -1, e.g. A**2 - B**2) -- {A:y, B:x} --> y**2 - x**2
+        # and the former factors into two terms, (A - B)*(A + B) while the
+        # latter factors into 3 terms, (-1)*(x - y)*(x + y)
+        rep1 = [(n, Dummy()) for n in sorted(nc_symbols, key=default_sort_key)]
+        unrep1 = [(v, k) for k, v in rep1]
+        unrep1.reverse()
+        new_mid, r2, _ = _mask_nc(mid.subs(rep1))
+        new_mid = powsimp(factor(new_mid))
+
+        new_mid = new_mid.subs(r2).subs(unrep1)
+
+        if new_mid.is_Pow:
+            return _keep_coeff(c, g*l*new_mid*r)
+
+        if new_mid.is_Mul:
+            def _pemexpand(expr):
+                "Expand with the minimal set of hints necessary to check the result."
+                return expr.expand(deep=True, mul=True, power_exp=True,
+                    power_base=False, basic=False, multinomial=True, log=False)
+            # XXX TODO there should be a way to inspect what order the terms
+            # must be in and just select the plausible ordering without
+            # checking permutations
+            cfac = []
+            ncfac = []
+            for f in new_mid.args:
+                if f.is_commutative:
+                    cfac.append(f)
+                else:
+                    b, e = f.as_base_exp()
+                    if e.is_Integer:
+                        ncfac.extend([b]*e)
+                    else:
+                        ncfac.append(f)
+            pre_mid = g*Mul(*cfac)*l
+            target = _pemexpand(expr/c)
+            for s in variations(ncfac, len(ncfac)):
+                ok = pre_mid*Mul(*s)*r
+                if _pemexpand(ok) == target:
+                    return _keep_coeff(c, ok)
+
+        # mid was an Add that didn't factor successfully
+        return _keep_coeff(c, g*l*mid*r)

env-llmeval/lib/python3.10/site-packages/sympy/core/facts.py

@@ -0,0 +1,634 @@
+r"""This is rule-based deduction system for SymPy
+
+The whole thing is split into two parts
+
+ - rules compilation and preparation of tables
+ - runtime inference
+
+For rule-based inference engines, the classical work is RETE algorithm [1],
+[2] Although we are not implementing it in full (or even significantly)
+it's still worth a read to understand the underlying ideas.
+
+In short, every rule in a system of rules is one of two forms:
+
+ - atom                     -> ...      (alpha rule)
+ - And(atom1, atom2, ...)   -> ...      (beta rule)
+
+
+The major complexity is in efficient beta-rules processing and usually for an
+expert system a lot of effort goes into code that operates on beta-rules.
+
+
+Here we take minimalistic approach to get something usable first.
+
+ - (preparation)    of alpha- and beta- networks, everything except
+ - (runtime)        FactRules.deduce_all_facts
+
+             _____________________________________
+            ( Kirr: I've never thought that doing )
+            ( logic stuff is that difficult...    )
+             -------------------------------------
+                    o   ^__^
+                     o  (oo)\_______
+                        (__)\       )\/\
+                            ||----w |
+                            ||     ||
+
+
+Some references on the topic
+----------------------------
+
+[1] https://en.wikipedia.org/wiki/Rete_algorithm
+[2] http://reports-archive.adm.cs.cmu.edu/anon/1995/CMU-CS-95-113.pdf
+
+https://en.wikipedia.org/wiki/Propositional_formula
+https://en.wikipedia.org/wiki/Inference_rule
+https://en.wikipedia.org/wiki/List_of_rules_of_inference
+"""
+
+from collections import defaultdict
+from typing import Iterator
+
+from .logic import Logic, And, Or, Not
+
+
+def _base_fact(atom):
+    """Return the literal fact of an atom.
+
+    Effectively, this merely strips the Not around a fact.
+    """
+    if isinstance(atom, Not):
+        return atom.arg
+    else:
+        return atom
+
+
+def _as_pair(atom):
+    if isinstance(atom, Not):
+        return (atom.arg, False)
+    else:
+        return (atom, True)
+
+# XXX this prepares forward-chaining rules for alpha-network
+
+
+def transitive_closure(implications):
+    """
+    Computes the transitive closure of a list of implications
+
+    Uses Warshall's algorithm, as described at
+    http://www.cs.hope.edu/~cusack/Notes/Notes/DiscreteMath/Warshall.pdf.
+    """
+    full_implications = set(implications)
+    literals = set().union(*map(set, full_implications))
+
+    for k in literals:
+        for i in literals:
+            if (i, k) in full_implications:
+                for j in literals:
+                    if (k, j) in full_implications:
+                        full_implications.add((i, j))
+
+    return full_implications
+
+
+def deduce_alpha_implications(implications):
+    """deduce all implications
+
+       Description by example
+       ----------------------
+
+       given set of logic rules:
+
+         a -> b
+         b -> c
+
+       we deduce all possible rules:
+
+         a -> b, c
+         b -> c
+
+
+       implications: [] of (a,b)
+       return:       {} of a -> set([b, c, ...])
+    """
+    implications = implications + [(Not(j), Not(i)) for (i, j) in implications]
+    res = defaultdict(set)
+    full_implications = transitive_closure(implications)
+    for a, b in full_implications:
+        if a == b:
+            continue    # skip a->a cyclic input
+
+        res[a].add(b)
+
+    # Clean up tautologies and check consistency
+    for a, impl in res.items():
+        impl.discard(a)
+        na = Not(a)
+        if na in impl:
+            raise ValueError(
+                'implications are inconsistent: %s -> %s %s' % (a, na, impl))
+
+    return res
+
+
+def apply_beta_to_alpha_route(alpha_implications, beta_rules):
+    """apply additional beta-rules (And conditions) to already-built
+    alpha implication tables
+
+       TODO: write about
+
+       - static extension of alpha-chains
+       - attaching refs to beta-nodes to alpha chains
+
+
+       e.g.
+
+       alpha_implications:
+
+       a  ->  [b, !c, d]
+       b  ->  [d]
+       ...
+
+
+       beta_rules:
+
+       &(b,d) -> e
+
+
+       then we'll extend a's rule to the following
+
+       a  ->  [b, !c, d, e]
+    """
+    x_impl = {}
+    for x in alpha_implications.keys():
+        x_impl[x] = (set(alpha_implications[x]), [])
+    for bcond, bimpl in beta_rules:
+        for bk in bcond.args:
+            if bk in x_impl:
+                continue
+            x_impl[bk] = (set(), [])
+
+    # static extensions to alpha rules:
+    # A: x -> a,b   B: &(a,b) -> c  ==>  A: x -> a,b,c
+    seen_static_extension = True
+    while seen_static_extension:
+        seen_static_extension = False
+
+        for bcond, bimpl in beta_rules:
+            if not isinstance(bcond, And):
+                raise TypeError("Cond is not And")
+            bargs = set(bcond.args)
+            for x, (ximpls, bb) in x_impl.items():
+                x_all = ximpls | {x}
+                # A: ... -> a   B: &(...) -> a  is non-informative
+                if bimpl not in x_all and bargs.issubset(x_all):
+                    ximpls.add(bimpl)
+
+                    # we introduced new implication - now we have to restore
+                    # completeness of the whole set.
+                    bimpl_impl = x_impl.get(bimpl)
+                    if bimpl_impl is not None:
+                        ximpls |= bimpl_impl[0]
+                    seen_static_extension = True
+
+    # attach beta-nodes which can be possibly triggered by an alpha-chain
+    for bidx, (bcond, bimpl) in enumerate(beta_rules):
+        bargs = set(bcond.args)
+        for x, (ximpls, bb) in x_impl.items():
+            x_all = ximpls | {x}
+            # A: ... -> a   B: &(...) -> a      (non-informative)
+            if bimpl in x_all:
+                continue
+            # A: x -> a...  B: &(!a,...) -> ... (will never trigger)
+            # A: x -> a...  B: &(...) -> !a     (will never trigger)
+            if any(Not(xi) in bargs or Not(xi) == bimpl for xi in x_all):
+                continue
+
+            if bargs & x_all:
+                bb.append(bidx)
+
+    return x_impl
+
+
+def rules_2prereq(rules):
+    """build prerequisites table from rules
+
+       Description by example
+       ----------------------
+
+       given set of logic rules:
+
+         a -> b, c
+         b -> c
+
+       we build prerequisites (from what points something can be deduced):
+
+         b <- a
+         c <- a, b
+
+       rules:   {} of a -> [b, c, ...]
+       return:  {} of c <- [a, b, ...]
+
+       Note however, that this prerequisites may be *not* enough to prove a
+       fact. An example is 'a -> b' rule, where prereq(a) is b, and prereq(b)
+       is a. That's because a=T -> b=T, and b=F -> a=F, but a=F -> b=?
+    """
+    prereq = defaultdict(set)
+    for (a, _), impl in rules.items():
+        if isinstance(a, Not):
+            a = a.args[0]
+        for (i, _) in impl:
+            if isinstance(i, Not):
+                i = i.args[0]
+            prereq[i].add(a)
+    return prereq
+
+################
+# RULES PROVER #
+################
+
+
+class TautologyDetected(Exception):
+    """(internal) Prover uses it for reporting detected tautology"""
+    pass
+
+
+class Prover:
+    """ai - prover of logic rules
+
+       given a set of initial rules, Prover tries to prove all possible rules
+       which follow from given premises.
+
+       As a result proved_rules are always either in one of two forms: alpha or
+       beta:
+
+       Alpha rules
+       -----------
+
+       This are rules of the form::
+
+         a -> b & c & d & ...
+
+
+       Beta rules
+       ----------
+
+       This are rules of the form::
+
+         &(a,b,...) -> c & d & ...
+
+
+       i.e. beta rules are join conditions that say that something follows when
+       *several* facts are true at the same time.
+    """
+
+    def __init__(self):
+        self.proved_rules = []
+        self._rules_seen = set()
+
+    def split_alpha_beta(self):
+        """split proved rules into alpha and beta chains"""
+        rules_alpha = []    # a      -> b
+        rules_beta = []     # &(...) -> b
+        for a, b in self.proved_rules:
+            if isinstance(a, And):
+                rules_beta.append((a, b))
+            else:
+                rules_alpha.append((a, b))
+        return rules_alpha, rules_beta
+
+    @property
+    def rules_alpha(self):
+        return self.split_alpha_beta()[0]
+
+    @property
+    def rules_beta(self):
+        return self.split_alpha_beta()[1]
+
+    def process_rule(self, a, b):
+        """process a -> b rule"""   # TODO write more?
+        if (not a) or isinstance(b, bool):
+            return
+        if isinstance(a, bool):
+            return
+        if (a, b) in self._rules_seen:
+            return
+        else:
+            self._rules_seen.add((a, b))
+
+        # this is the core of processing
+        try:
+            self._process_rule(a, b)
+        except TautologyDetected:
+            pass
+
+    def _process_rule(self, a, b):
+        # right part first
+
+        # a -> b & c    -->  a -> b  ;  a -> c
+        # (?) FIXME this is only correct when b & c != null !
+
+        if isinstance(b, And):
+            sorted_bargs = sorted(b.args, key=str)
+            for barg in sorted_bargs:
+                self.process_rule(a, barg)
+
+        # a -> b | c    -->  !b & !c -> !a
+        #               -->   a & !b -> c
+        #               -->   a & !c -> b
+        elif isinstance(b, Or):
+            sorted_bargs = sorted(b.args, key=str)
+            # detect tautology first
+            if not isinstance(a, Logic):    # Atom
+                # tautology:  a -> a|c|...
+                if a in sorted_bargs:
+                    raise TautologyDetected(a, b, 'a -> a|c|...')
+            self.process_rule(And(*[Not(barg) for barg in b.args]), Not(a))
+
+            for bidx in range(len(sorted_bargs)):
+                barg = sorted_bargs[bidx]
+                brest = sorted_bargs[:bidx] + sorted_bargs[bidx + 1:]
+                self.process_rule(And(a, Not(barg)), Or(*brest))
+
+        # left part
+
+        # a & b -> c    -->  IRREDUCIBLE CASE -- WE STORE IT AS IS
+        #                    (this will be the basis of beta-network)
+        elif isinstance(a, And):
+            sorted_aargs = sorted(a.args, key=str)
+            if b in sorted_aargs:
+                raise TautologyDetected(a, b, 'a & b -> a')
+            self.proved_rules.append((a, b))
+            # XXX NOTE at present we ignore  !c -> !a | !b
+
+        elif isinstance(a, Or):
+            sorted_aargs = sorted(a.args, key=str)
+            if b in sorted_aargs:
+                raise TautologyDetected(a, b, 'a | b -> a')
+            for aarg in sorted_aargs:
+                self.process_rule(aarg, b)
+
+        else:
+            # both `a` and `b` are atoms
+            self.proved_rules.append((a, b))             # a  -> b
+            self.proved_rules.append((Not(b), Not(a)))   # !b -> !a
+
+########################################
+
+
+class FactRules:
+    """Rules that describe how to deduce facts in logic space
+
+       When defined, these rules allow implications to quickly be determined
+       for a set of facts. For this precomputed deduction tables are used.
+       see `deduce_all_facts`   (forward-chaining)
+
+       Also it is possible to gather prerequisites for a fact, which is tried
+       to be proven.    (backward-chaining)
+
+
+       Definition Syntax
+       -----------------
+
+       a -> b       -- a=T -> b=T  (and automatically b=F -> a=F)
+       a -> !b      -- a=T -> b=F
+       a == b       -- a -> b & b -> a
+       a -> b & c   -- a=T -> b=T & c=T
+       # TODO b | c
+
+
+       Internals
+       ---------
+
+       .full_implications[k, v]: all the implications of fact k=v
+       .beta_triggers[k, v]: beta rules that might be triggered when k=v
+       .prereq  -- {} k <- [] of k's prerequisites
+
+       .defined_facts -- set of defined fact names
+    """
+
+    def __init__(self, rules):
+        """Compile rules into internal lookup tables"""
+
+        if isinstance(rules, str):
+            rules = rules.splitlines()
+
+        # --- parse and process rules ---
+        P = Prover()
+
+        for rule in rules:
+            # XXX `a` is hardcoded to be always atom
+            a, op, b = rule.split(None, 2)
+
+            a = Logic.fromstring(a)
+            b = Logic.fromstring(b)
+
+            if op == '->':
+                P.process_rule(a, b)
+            elif op == '==':
+                P.process_rule(a, b)
+                P.process_rule(b, a)
+            else:
+                raise ValueError('unknown op %r' % op)
+
+        # --- build deduction networks ---
+        self.beta_rules = []
+        for bcond, bimpl in P.rules_beta:
+            self.beta_rules.append(
+                ({_as_pair(a) for a in bcond.args}, _as_pair(bimpl)))
+
+        # deduce alpha implications
+        impl_a = deduce_alpha_implications(P.rules_alpha)
+
+        # now:
+        # - apply beta rules to alpha chains  (static extension), and
+        # - further associate beta rules to alpha chain (for inference
+        # at runtime)
+        impl_ab = apply_beta_to_alpha_route(impl_a, P.rules_beta)
+
+        # extract defined fact names
+        self.defined_facts = {_base_fact(k) for k in impl_ab.keys()}
+
+        # build rels (forward chains)
+        full_implications = defaultdict(set)
+        beta_triggers = defaultdict(set)
+        for k, (impl, betaidxs) in impl_ab.items():
+            full_implications[_as_pair(k)] = {_as_pair(i) for i in impl}
+            beta_triggers[_as_pair(k)] = betaidxs
+
+        self.full_implications = full_implications
+        self.beta_triggers = beta_triggers
+
+        # build prereq (backward chains)
+        prereq = defaultdict(set)
+        rel_prereq = rules_2prereq(full_implications)
+        for k, pitems in rel_prereq.items():
+            prereq[k] |= pitems
+        self.prereq = prereq
+
+    def _to_python(self) -> str:
+        """ Generate a string with plain python representation of the instance """
+        return '\n'.join(self.print_rules())
+
+    @classmethod
+    def _from_python(cls, data : dict):
+        """ Generate an instance from the plain python representation """
+        self = cls('')
+        for key in ['full_implications', 'beta_triggers', 'prereq']:
+            d=defaultdict(set)
+            d.update(data[key])
+            setattr(self, key, d)
+        self.beta_rules = data['beta_rules']
+        self.defined_facts = set(data['defined_facts'])
+
+        return self
+
+    def _defined_facts_lines(self):
+        yield 'defined_facts = ['
+        for fact in sorted(self.defined_facts):
+            yield f'    {fact!r},'
+        yield '] # defined_facts'
+
+    def _full_implications_lines(self):
+        yield 'full_implications = dict( ['
+        for fact in sorted(self.defined_facts):
+            for value in (True, False):
+                yield f'    # Implications of {fact} = {value}:'
+                yield f'    (({fact!r}, {value!r}), set( ('
+                implications = self.full_implications[(fact, value)]
+                for implied in sorted(implications):
+                    yield f'        {implied!r},'
+                yield '       ) ),'
+                yield '     ),'
+        yield ' ] ) # full_implications'
+
+    def _prereq_lines(self):
+        yield 'prereq = {'
+        yield ''
+        for fact in sorted(self.prereq):
+            yield f'    # facts that could determine the value of {fact}'
+            yield f'    {fact!r}: {{'
+            for pfact in sorted(self.prereq[fact]):
+                yield f'        {pfact!r},'
+            yield '    },'
+            yield ''
+        yield '} # prereq'
+
+    def _beta_rules_lines(self):
+        reverse_implications = defaultdict(list)
+        for n, (pre, implied) in enumerate(self.beta_rules):
+            reverse_implications[implied].append((pre, n))
+
+        yield '# Note: the order of the beta rules is used in the beta_triggers'
+        yield 'beta_rules = ['
+        yield ''
+        m = 0
+        indices = {}
+        for implied in sorted(reverse_implications):
+            fact, value = implied
+            yield f'    # Rules implying {fact} = {value}'
+            for pre, n in reverse_implications[implied]:
+                indices[n] = m
+                m += 1
+                setstr = ", ".join(map(str, sorted(pre)))
+                yield f'    ({{{setstr}}},'
+                yield f'        {implied!r}),'
+            yield ''
+        yield '] # beta_rules'
+
+        yield 'beta_triggers = {'
+        for query in sorted(self.beta_triggers):
+            fact, value = query
+            triggers = [indices[n] for n in self.beta_triggers[query]]
+            yield f'    {query!r}: {triggers!r},'
+        yield '} # beta_triggers'
+
+    def print_rules(self) -> Iterator[str]:
+        """ Returns a generator with lines to represent the facts and rules """
+        yield from self._defined_facts_lines()
+        yield ''
+        yield ''
+        yield from self._full_implications_lines()
+        yield ''
+        yield ''
+        yield from self._prereq_lines()
+        yield ''
+        yield ''
+        yield from self._beta_rules_lines()
+        yield ''
+        yield ''
+        yield "generated_assumptions = {'defined_facts': defined_facts, 'full_implications': full_implications,"
+        yield "               'prereq': prereq, 'beta_rules': beta_rules, 'beta_triggers': beta_triggers}"
+
+
+class InconsistentAssumptions(ValueError):
+    def __str__(self):
+        kb, fact, value = self.args
+        return "%s, %s=%s" % (kb, fact, value)
+
+
+class FactKB(dict):
+    """
+    A simple propositional knowledge base relying on compiled inference rules.
+    """
+    def __str__(self):
+        return '{\n%s}' % ',\n'.join(
+            ["\t%s: %s" % i for i in sorted(self.items())])
+
+    def __init__(self, rules):
+        self.rules = rules
+
+    def _tell(self, k, v):
+        """Add fact k=v to the knowledge base.
+
+        Returns True if the KB has actually been updated, False otherwise.
+        """
+        if k in self and self[k] is not None:
+            if self[k] == v:
+                return False
+            else:
+                raise InconsistentAssumptions(self, k, v)
+        else:
+            self[k] = v
+            return True
+
+    # *********************************************
+    # * This is the workhorse, so keep it *fast*. *
+    # *********************************************
+    def deduce_all_facts(self, facts):
+        """
+        Update the KB with all the implications of a list of facts.
+
+        Facts can be specified as a dictionary or as a list of (key, value)
+        pairs.
+        """
+        # keep frequently used attributes locally, so we'll avoid extra
+        # attribute access overhead
+        full_implications = self.rules.full_implications
+        beta_triggers = self.rules.beta_triggers
+        beta_rules = self.rules.beta_rules
+
+        if isinstance(facts, dict):
+            facts = facts.items()
+
+        while facts:
+            beta_maytrigger = set()
+
+            # --- alpha chains ---
+            for k, v in facts:
+                if not self._tell(k, v) or v is None:
+                    continue
+
+                # lookup routing tables
+                for key, value in full_implications[k, v]:
+                    self._tell(key, value)
+
+                beta_maytrigger.update(beta_triggers[k, v])
+
+            # --- beta chains ---
+            facts = []
+            for bidx in beta_maytrigger:
+                bcond, bimpl = beta_rules[bidx]
+                if all(self.get(k) is v for k, v in bcond):
+                    facts.append(bimpl)

env-llmeval/lib/python3.10/site-packages/sympy/core/kind.py

@@ -0,0 +1,388 @@
+"""
+Module to efficiently partition SymPy objects.
+
+This system is introduced because class of SymPy object does not always
+represent the mathematical classification of the entity. For example,
+``Integral(1, x)`` and ``Integral(Matrix([1,2]), x)`` are both instance
+of ``Integral`` class. However the former is number and the latter is
+matrix.
+
+One way to resolve this is defining subclass for each mathematical type,
+such as ``MatAdd`` for the addition between matrices. Basic algebraic
+operation such as addition or multiplication take this approach, but
+defining every class for every mathematical object is not scalable.
+
+Therefore, we define the "kind" of the object and let the expression
+infer the kind of itself from its arguments. Function and class can
+filter the arguments by their kind, and behave differently according to
+the type of itself.
+
+This module defines basic kinds for core objects. Other kinds such as
+``ArrayKind`` or ``MatrixKind`` can be found in corresponding modules.
+
+.. notes::
+       This approach is experimental, and can be replaced or deleted in the future.
+       See https://github.com/sympy/sympy/pull/20549.
+"""
+
+from collections import defaultdict
+
+from .cache import cacheit
+from sympy.multipledispatch.dispatcher import (Dispatcher,
+    ambiguity_warn, ambiguity_register_error_ignore_dup,
+    str_signature, RaiseNotImplementedError)
+
+
+class KindMeta(type):
+    """
+    Metaclass for ``Kind``.
+
+    Assigns empty ``dict`` as class attribute ``_inst`` for every class,
+    in order to endow singleton-like behavior.
+    """
+    def __new__(cls, clsname, bases, dct):
+        dct['_inst'] = {}
+        return super().__new__(cls, clsname, bases, dct)
+
+
+class Kind(object, metaclass=KindMeta):
+    """
+    Base class for kinds.
+
+    Kind of the object represents the mathematical classification that
+    the entity falls into. It is expected that functions and classes
+    recognize and filter the argument by its kind.
+
+    Kind of every object must be carefully selected so that it shows the
+    intention of design. Expressions may have different kind according
+    to the kind of its arguments. For example, arguments of ``Add``
+    must have common kind since addition is group operator, and the
+    resulting ``Add()`` has the same kind.
+
+    For the performance, each kind is as broad as possible and is not
+    based on set theory. For example, ``NumberKind`` includes not only
+    complex number but expression containing ``S.Infinity`` or ``S.NaN``
+    which are not strictly number.
+
+    Kind may have arguments as parameter. For example, ``MatrixKind()``
+    may be constructed with one element which represents the kind of its
+    elements.
+
+    ``Kind`` behaves in singleton-like fashion. Same signature will
+    return the same object.
+
+    """
+    def __new__(cls, *args):
+        if args in cls._inst:
+            inst = cls._inst[args]
+        else:
+            inst = super().__new__(cls)
+            cls._inst[args] = inst
+        return inst
+
+
+class _UndefinedKind(Kind):
+    """
+    Default kind for all SymPy object. If the kind is not defined for
+    the object, or if the object cannot infer the kind from its
+    arguments, this will be returned.
+
+    Examples
+    ========
+
+    >>> from sympy import Expr
+    >>> Expr().kind
+    UndefinedKind
+    """
+    def __new__(cls):
+        return super().__new__(cls)
+
+    def __repr__(self):
+        return "UndefinedKind"
+
+UndefinedKind = _UndefinedKind()
+
+
+class _NumberKind(Kind):
+    """
+    Kind for all numeric object.
+
+    This kind represents every number, including complex numbers,
+    infinity and ``S.NaN``. Other objects such as quaternions do not
+    have this kind.
+
+    Most ``Expr`` are initially designed to represent the number, so
+    this will be the most common kind in SymPy core. For example
+    ``Symbol()``, which represents a scalar, has this kind as long as it
+    is commutative.
+
+    Numbers form a field. Any operation between number-kind objects will
+    result this kind as well.
+
+    Examples
+    ========
+
+    >>> from sympy import S, oo, Symbol
+    >>> S.One.kind
+    NumberKind
+    >>> (-oo).kind
+    NumberKind
+    >>> S.NaN.kind
+    NumberKind
+
+    Commutative symbol are treated as number.
+
+    >>> x = Symbol('x')
+    >>> x.kind
+    NumberKind
+    >>> Symbol('y', commutative=False).kind
+    UndefinedKind
+
+    Operation between numbers results number.
+
+    >>> (x+1).kind
+    NumberKind
+
+    See Also
+    ========
+
+    sympy.core.expr.Expr.is_Number : check if the object is strictly
+    subclass of ``Number`` class.
+
+    sympy.core.expr.Expr.is_number : check if the object is number
+    without any free symbol.
+
+    """
+    def __new__(cls):
+        return super().__new__(cls)
+
+    def __repr__(self):
+        return "NumberKind"
+
+NumberKind = _NumberKind()
+
+
+class _BooleanKind(Kind):
+    """
+    Kind for boolean objects.
+
+    SymPy's ``S.true``, ``S.false``, and built-in ``True`` and ``False``
+    have this kind. Boolean number ``1`` and ``0`` are not relevant.
+
+    Examples
+    ========
+
+    >>> from sympy import S, Q
+    >>> S.true.kind
+    BooleanKind
+    >>> Q.even(3).kind
+    BooleanKind
+    """
+    def __new__(cls):
+        return super().__new__(cls)
+
+    def __repr__(self):
+        return "BooleanKind"
+
+BooleanKind = _BooleanKind()
+
+
+class KindDispatcher:
+    """
+    Dispatcher to select a kind from multiple kinds by binary dispatching.
+
+    .. notes::
+       This approach is experimental, and can be replaced or deleted in
+       the future.
+
+    Explanation
+    ===========
+
+    SymPy object's :obj:`sympy.core.kind.Kind()` vaguely represents the
+    algebraic structure where the object belongs to. Therefore, with
+    given operation, we can always find a dominating kind among the
+    different kinds. This class selects the kind by recursive binary
+    dispatching. If the result cannot be determined, ``UndefinedKind``
+    is returned.
+
+    Examples
+    ========
+
+    Multiplication between numbers return number.
+
+    >>> from sympy import NumberKind, Mul
+    >>> Mul._kind_dispatcher(NumberKind, NumberKind)
+    NumberKind
+
+    Multiplication between number and unknown-kind object returns unknown kind.
+
+    >>> from sympy import UndefinedKind
+    >>> Mul._kind_dispatcher(NumberKind, UndefinedKind)
+    UndefinedKind
+
+    Any number and order of kinds is allowed.
+
+    >>> Mul._kind_dispatcher(UndefinedKind, NumberKind)
+    UndefinedKind
+    >>> Mul._kind_dispatcher(NumberKind, UndefinedKind, NumberKind)
+    UndefinedKind
+
+    Since matrix forms a vector space over scalar field, multiplication
+    between matrix with numeric element and number returns matrix with
+    numeric element.
+
+    >>> from sympy.matrices import MatrixKind
+    >>> Mul._kind_dispatcher(MatrixKind(NumberKind), NumberKind)
+    MatrixKind(NumberKind)
+
+    If a matrix with number element and another matrix with unknown-kind
+    element are multiplied, we know that the result is matrix but the
+    kind of its elements is unknown.
+
+    >>> Mul._kind_dispatcher(MatrixKind(NumberKind), MatrixKind(UndefinedKind))
+    MatrixKind(UndefinedKind)
+
+    Parameters
+    ==========
+
+    name : str
+
+    commutative : bool, optional
+        If True, binary dispatch will be automatically registered in
+        reversed order as well.
+
+    doc : str, optional
+
+    """
+    def __init__(self, name, commutative=False, doc=None):
+        self.name = name
+        self.doc = doc
+        self.commutative = commutative
+        self._dispatcher = Dispatcher(name)
+
+    def __repr__(self):
+        return "<dispatched %s>" % self.name
+
+    def register(self, *types, **kwargs):
+        """
+        Register the binary dispatcher for two kind classes.
+
+        If *self.commutative* is ``True``, signature in reversed order is
+        automatically registered as well.
+        """
+        on_ambiguity = kwargs.pop("on_ambiguity", None)
+        if not on_ambiguity:
+            if self.commutative:
+                on_ambiguity = ambiguity_register_error_ignore_dup
+            else:
+                on_ambiguity = ambiguity_warn
+        kwargs.update(on_ambiguity=on_ambiguity)
+
+        if not len(types) == 2:
+            raise RuntimeError(
+                "Only binary dispatch is supported, but got %s types: <%s>." % (
+                len(types), str_signature(types)
+            ))
+
+        def _(func):
+            self._dispatcher.add(types, func, **kwargs)
+            if self.commutative:
+                self._dispatcher.add(tuple(reversed(types)), func, **kwargs)
+        return _
+
+    def __call__(self, *args, **kwargs):
+        if self.commutative:
+            kinds = frozenset(args)
+        else:
+            kinds = []
+            prev = None
+            for a in args:
+                if prev is not a:
+                    kinds.append(a)
+                    prev = a
+        return self.dispatch_kinds(kinds, **kwargs)
+
+    @cacheit
+    def dispatch_kinds(self, kinds, **kwargs):
+        # Quick exit for the case where all kinds are same
+        if len(kinds) == 1:
+            result, = kinds
+            if not isinstance(result, Kind):
+                raise RuntimeError("%s is not a kind." % result)
+            return result
+
+        for i,kind in enumerate(kinds):
+            if not isinstance(kind, Kind):
+                raise RuntimeError("%s is not a kind." % kind)
+
+            if i == 0:
+                result = kind
+            else:
+                prev_kind = result
+
+                t1, t2 = type(prev_kind), type(kind)
+                k1, k2 = prev_kind, kind
+                func = self._dispatcher.dispatch(t1, t2)
+                if func is None and self.commutative:
+                    # try reversed order
+                    func = self._dispatcher.dispatch(t2, t1)
+                    k1, k2 = k2, k1
+                if func is None:
+                    # unregistered kind relation
+                    result = UndefinedKind
+                else:
+                    result = func(k1, k2)
+                if not isinstance(result, Kind):
+                    raise RuntimeError(
+                        "Dispatcher for {!r} and {!r} must return a Kind, but got {!r}".format(
+                        prev_kind, kind, result
+                    ))
+
+        return result
+
+    @property
+    def __doc__(self):
+        docs = [
+            "Kind dispatcher : %s" % self.name,
+            "Note that support for this is experimental. See the docs for :class:`KindDispatcher` for details"
+        ]
+
+        if self.doc:
+            docs.append(self.doc)
+
+        s = "Registered kind classes\n"
+        s += '=' * len(s)
+        docs.append(s)
+
+        amb_sigs = []
+
+        typ_sigs = defaultdict(list)
+        for sigs in self._dispatcher.ordering[::-1]:
+            key = self._dispatcher.funcs[sigs]
+            typ_sigs[key].append(sigs)
+
+        for func, sigs in typ_sigs.items():
+
+            sigs_str = ', '.join('<%s>' % str_signature(sig) for sig in sigs)
+
+            if isinstance(func, RaiseNotImplementedError):
+                amb_sigs.append(sigs_str)
+                continue
+
+            s = 'Inputs: %s\n' % sigs_str
+            s += '-' * len(s) + '\n'
+            if func.__doc__:
+                s += func.__doc__.strip()
+            else:
+                s += func.__name__
+            docs.append(s)
+
+        if amb_sigs:
+            s = "Ambiguous kind classes\n"
+            s += '=' * len(s)
+            docs.append(s)
+
+            s = '\n'.join(amb_sigs)
+            docs.append(s)
+
+        return '\n\n'.join(docs)

env-llmeval/lib/python3.10/site-packages/sympy/core/logic.py

@@ -0,0 +1,427 @@
+"""Logic expressions handling
+
+NOTE
+----
+
+at present this is mainly needed for facts.py, feel free however to improve
+this stuff for general purpose.
+"""
+
+from __future__ import annotations
+from typing import Optional
+
+# Type of a fuzzy bool
+FuzzyBool = Optional[bool]
+
+
+def _torf(args):
+    """Return True if all args are True, False if they
+    are all False, else None.
+
+    >>> from sympy.core.logic import _torf
+    >>> _torf((True, True))
+    True
+    >>> _torf((False, False))
+    False
+    >>> _torf((True, False))
+    """
+    sawT = sawF = False
+    for a in args:
+        if a is True:
+            if sawF:
+                return
+            sawT = True
+        elif a is False:
+            if sawT:
+                return
+            sawF = True
+        else:
+            return
+    return sawT
+
+
+def _fuzzy_group(args, quick_exit=False):
+    """Return True if all args are True, None if there is any None else False
+    unless ``quick_exit`` is True (then return None as soon as a second False
+    is seen.
+
+     ``_fuzzy_group`` is like ``fuzzy_and`` except that it is more
+    conservative in returning a False, waiting to make sure that all
+    arguments are True or False and returning None if any arguments are
+    None. It also has the capability of permiting only a single False and
+    returning None if more than one is seen. For example, the presence of a
+    single transcendental amongst rationals would indicate that the group is
+    no longer rational; but a second transcendental in the group would make the
+    determination impossible.
+
+
+    Examples
+    ========
+
+    >>> from sympy.core.logic import _fuzzy_group
+
+    By default, multiple Falses mean the group is broken:
+
+    >>> _fuzzy_group([False, False, True])
+    False
+
+    If multiple Falses mean the group status is unknown then set
+    `quick_exit` to True so None can be returned when the 2nd False is seen:
+
+    >>> _fuzzy_group([False, False, True], quick_exit=True)
+
+    But if only a single False is seen then the group is known to
+    be broken:
+
+    >>> _fuzzy_group([False, True, True], quick_exit=True)
+    False
+
+    """
+    saw_other = False
+    for a in args:
+        if a is True:
+            continue
+        if a is None:
+            return
+        if quick_exit and saw_other:
+            return
+        saw_other = True
+    return not saw_other
+
+
+def fuzzy_bool(x):
+    """Return True, False or None according to x.
+
+    Whereas bool(x) returns True or False, fuzzy_bool allows
+    for the None value and non-false values (which become None), too.
+
+    Examples
+    ========
+
+    >>> from sympy.core.logic import fuzzy_bool
+    >>> from sympy.abc import x
+    >>> fuzzy_bool(x), fuzzy_bool(None)
+    (None, None)
+    >>> bool(x), bool(None)
+    (True, False)
+
+    """
+    if x is None:
+        return None
+    if x in (True, False):
+        return bool(x)
+
+
+def fuzzy_and(args):
+    """Return True (all True), False (any False) or None.
+
+    Examples
+    ========
+
+    >>> from sympy.core.logic import fuzzy_and
+    >>> from sympy import Dummy
+
+    If you had a list of objects to test the commutivity of
+    and you want the fuzzy_and logic applied, passing an
+    iterator will allow the commutativity to only be computed
+    as many times as necessary. With this list, False can be
+    returned after analyzing the first symbol:
+
+    >>> syms = [Dummy(commutative=False), Dummy()]
+    >>> fuzzy_and(s.is_commutative for s in syms)
+    False
+
+    That False would require less work than if a list of pre-computed
+    items was sent:
+
+    >>> fuzzy_and([s.is_commutative for s in syms])
+    False
+    """
+
+    rv = True
+    for ai in args:
+        ai = fuzzy_bool(ai)
+        if ai is False:
+            return False
+        if rv:  # this will stop updating if a None is ever trapped
+            rv = ai
+    return rv
+
+
+def fuzzy_not(v):
+    """
+    Not in fuzzy logic
+
+    Return None if `v` is None else `not v`.
+
+    Examples
+    ========
+
+    >>> from sympy.core.logic import fuzzy_not
+    >>> fuzzy_not(True)
+    False
+    >>> fuzzy_not(None)
+    >>> fuzzy_not(False)
+    True
+
+    """
+    if v is None:
+        return v
+    else:
+        return not v
+
+
+def fuzzy_or(args):
+    """
+    Or in fuzzy logic. Returns True (any True), False (all False), or None
+
+    See the docstrings of fuzzy_and and fuzzy_not for more info.  fuzzy_or is
+    related to the two by the standard De Morgan's law.
+
+    >>> from sympy.core.logic import fuzzy_or
+    >>> fuzzy_or([True, False])
+    True
+    >>> fuzzy_or([True, None])
+    True
+    >>> fuzzy_or([False, False])
+    False
+    >>> print(fuzzy_or([False, None]))
+    None
+
+    """
+    rv = False
+    for ai in args:
+        ai = fuzzy_bool(ai)
+        if ai is True:
+            return True
+        if rv is False:  # this will stop updating if a None is ever trapped
+            rv = ai
+    return rv
+
+
+def fuzzy_xor(args):
+    """Return None if any element of args is not True or False, else
+    True (if there are an odd number of True elements), else False."""
+    t = f = 0
+    for a in args:
+        ai = fuzzy_bool(a)
+        if ai:
+            t += 1
+        elif ai is False:
+            f += 1
+        else:
+            return
+    return t % 2 == 1
+
+
+def fuzzy_nand(args):
+    """Return False if all args are True, True if they are all False,
+    else None."""
+    return fuzzy_not(fuzzy_and(args))
+
+
+class Logic:
+    """Logical expression"""
+    # {} 'op' -> LogicClass
+    op_2class: dict[str, type[Logic]] = {}
+
+    def __new__(cls, *args):
+        obj = object.__new__(cls)
+        obj.args = args
+        return obj
+
+    def __getnewargs__(self):
+        return self.args
+
+    def __hash__(self):
+        return hash((type(self).__name__,) + tuple(self.args))
+
+    def __eq__(a, b):
+        if not isinstance(b, type(a)):
+            return False
+        else:
+            return a.args == b.args
+
+    def __ne__(a, b):
+        if not isinstance(b, type(a)):
+            return True
+        else:
+            return a.args != b.args
+
+    def __lt__(self, other):
+        if self.__cmp__(other) == -1:
+            return True
+        return False
+
+    def __cmp__(self, other):
+        if type(self) is not type(other):
+            a = str(type(self))
+            b = str(type(other))
+        else:
+            a = self.args
+            b = other.args
+        return (a > b) - (a < b)
+
+    def __str__(self):
+        return '%s(%s)' % (self.__class__.__name__,
+                           ', '.join(str(a) for a in self.args))
+
+    __repr__ = __str__
+
+    @staticmethod
+    def fromstring(text):
+        """Logic from string with space around & and | but none after !.
+
+           e.g.
+
+           !a & b | c
+        """
+        lexpr = None  # current logical expression
+        schedop = None  # scheduled operation
+        for term in text.split():
+            # operation symbol
+            if term in '&|':
+                if schedop is not None:
+                    raise ValueError(
+                        'double op forbidden: "%s %s"' % (term, schedop))
+                if lexpr is None:
+                    raise ValueError(
+                        '%s cannot be in the beginning of expression' % term)
+                schedop = term
+                continue
+            if '&' in term or '|' in term:
+                raise ValueError('& and | must have space around them')
+            if term[0] == '!':
+                if len(term) == 1:
+                    raise ValueError('do not include space after "!"')
+                term = Not(term[1:])
+
+            # already scheduled operation, e.g. '&'
+            if schedop:
+                lexpr = Logic.op_2class[schedop](lexpr, term)
+                schedop = None
+                continue
+
+            # this should be atom
+            if lexpr is not None:
+                raise ValueError(
+                    'missing op between "%s" and "%s"' % (lexpr, term))
+
+            lexpr = term
+
+        # let's check that we ended up in correct state
+        if schedop is not None:
+            raise ValueError('premature end-of-expression in "%s"' % text)
+        if lexpr is None:
+            raise ValueError('"%s" is empty' % text)
+
+        # everything looks good now
+        return lexpr
+
+
+class AndOr_Base(Logic):
+
+    def __new__(cls, *args):
+        bargs = []
+        for a in args:
+            if a == cls.op_x_notx:
+                return a
+            elif a == (not cls.op_x_notx):
+                continue    # skip this argument
+            bargs.append(a)
+
+        args = sorted(set(cls.flatten(bargs)), key=hash)
+
+        for a in args:
+            if Not(a) in args:
+                return cls.op_x_notx
+
+        if len(args) == 1:
+            return args.pop()
+        elif len(args) == 0:
+            return not cls.op_x_notx
+
+        return Logic.__new__(cls, *args)
+
+    @classmethod
+    def flatten(cls, args):
+        # quick-n-dirty flattening for And and Or
+        args_queue = list(args)
+        res = []
+
+        while True:
+            try:
+                arg = args_queue.pop(0)
+            except IndexError:
+                break
+            if isinstance(arg, Logic):
+                if isinstance(arg, cls):
+                    args_queue.extend(arg.args)
+                    continue
+            res.append(arg)
+
+        args = tuple(res)
+        return args
+
+
+class And(AndOr_Base):
+    op_x_notx = False
+
+    def _eval_propagate_not(self):
+        # !(a&b&c ...) == !a | !b | !c ...
+        return Or(*[Not(a) for a in self.args])
+
+    # (a|b|...) & c == (a&c) | (b&c) | ...
+    def expand(self):
+
+        # first locate Or
+        for i, arg in enumerate(self.args):
+            if isinstance(arg, Or):
+                arest = self.args[:i] + self.args[i + 1:]
+
+                orterms = [And(*(arest + (a,))) for a in arg.args]
+                for j in range(len(orterms)):
+                    if isinstance(orterms[j], Logic):
+                        orterms[j] = orterms[j].expand()
+
+                res = Or(*orterms)
+                return res
+
+        return self
+
+
+class Or(AndOr_Base):
+    op_x_notx = True
+
+    def _eval_propagate_not(self):
+        # !(a|b|c ...) == !a & !b & !c ...
+        return And(*[Not(a) for a in self.args])
+
+
+class Not(Logic):
+
+    def __new__(cls, arg):
+        if isinstance(arg, str):
+            return Logic.__new__(cls, arg)
+
+        elif isinstance(arg, bool):
+            return not arg
+        elif isinstance(arg, Not):
+            return arg.args[0]
+
+        elif isinstance(arg, Logic):
+            # XXX this is a hack to expand right from the beginning
+            arg = arg._eval_propagate_not()
+            return arg
+
+        else:
+            raise ValueError('Not: unknown argument %r' % (arg,))
+
+    @property
+    def arg(self):
+        return self.args[0]
+
+
+Logic.op_2class['&'] = And
+Logic.op_2class['|'] = Or
+Logic.op_2class['!'] = Not

env-llmeval/lib/python3.10/site-packages/sympy/core/mul.py

@@ -0,0 +1,2195 @@
+from typing import Tuple as tTuple
+from collections import defaultdict
+from functools import cmp_to_key, reduce
+from itertools import product
+import operator
+
+from .sympify import sympify
+from .basic import Basic
+from .singleton import S
+from .operations import AssocOp, AssocOpDispatcher
+from .cache import cacheit
+from .logic import fuzzy_not, _fuzzy_group
+from .expr import Expr
+from .parameters import global_parameters
+from .kind import KindDispatcher
+from .traversal import bottom_up
+
+from sympy.utilities.iterables import sift
+
+# internal marker to indicate:
+#   "there are still non-commutative objects -- don't forget to process them"
+class NC_Marker:
+    is_Order = False
+    is_Mul = False
+    is_Number = False
+    is_Poly = False
+
+    is_commutative = False
+
+
+# Key for sorting commutative args in canonical order
+_args_sortkey = cmp_to_key(Basic.compare)
+def _mulsort(args):
+    # in-place sorting of args
+    args.sort(key=_args_sortkey)
+
+
+def _unevaluated_Mul(*args):
+    """Return a well-formed unevaluated Mul: Numbers are collected and
+    put in slot 0, any arguments that are Muls will be flattened, and args
+    are sorted. Use this when args have changed but you still want to return
+    an unevaluated Mul.
+
+    Examples
+    ========
+
+    >>> from sympy.core.mul import _unevaluated_Mul as uMul
+    >>> from sympy import S, sqrt, Mul
+    >>> from sympy.abc import x
+    >>> a = uMul(*[S(3.0), x, S(2)])
+    >>> a.args[0]
+    6.00000000000000
+    >>> a.args[1]
+    x
+
+    Two unevaluated Muls with the same arguments will
+    always compare as equal during testing:
+
+    >>> m = uMul(sqrt(2), sqrt(3))
+    >>> m == uMul(sqrt(3), sqrt(2))
+    True
+    >>> u = Mul(sqrt(3), sqrt(2), evaluate=False)
+    >>> m == uMul(u)
+    True
+    >>> m == Mul(*m.args)
+    False
+
+    """
+    args = list(args)
+    newargs = []
+    ncargs = []
+    co = S.One
+    while args:
+        a = args.pop()
+        if a.is_Mul:
+            c, nc = a.args_cnc()
+            args.extend(c)
+            if nc:
+                ncargs.append(Mul._from_args(nc))
+        elif a.is_Number:
+            co *= a
+        else:
+            newargs.append(a)
+    _mulsort(newargs)
+    if co is not S.One:
+        newargs.insert(0, co)
+    if ncargs:
+        newargs.append(Mul._from_args(ncargs))
+    return Mul._from_args(newargs)
+
+
+class Mul(Expr, AssocOp):
+    """
+    Expression representing multiplication operation for algebraic field.
+
+    .. deprecated:: 1.7
+
+       Using arguments that aren't subclasses of :class:`~.Expr` in core
+       operators (:class:`~.Mul`, :class:`~.Add`, and :class:`~.Pow`) is
+       deprecated. See :ref:`non-expr-args-deprecated` for details.
+
+    Every argument of ``Mul()`` must be ``Expr``. Infix operator ``*``
+    on most scalar objects in SymPy calls this class.
+
+    Another use of ``Mul()`` is to represent the structure of abstract
+    multiplication so that its arguments can be substituted to return
+    different class. Refer to examples section for this.
+
+    ``Mul()`` evaluates the argument unless ``evaluate=False`` is passed.
+    The evaluation logic includes:
+
+    1. Flattening
+        ``Mul(x, Mul(y, z))`` -> ``Mul(x, y, z)``
+
+    2. Identity removing
+        ``Mul(x, 1, y)`` -> ``Mul(x, y)``
+
+    3. Exponent collecting by ``.as_base_exp()``
+        ``Mul(x, x**2)`` -> ``Pow(x, 3)``
+
+    4. Term sorting
+        ``Mul(y, x, 2)`` -> ``Mul(2, x, y)``
+
+    Since multiplication can be vector space operation, arguments may
+    have the different :obj:`sympy.core.kind.Kind()`. Kind of the
+    resulting object is automatically inferred.
+
+    Examples
+    ========
+
+    >>> from sympy import Mul
+    >>> from sympy.abc import x, y
+    >>> Mul(x, 1)
+    x
+    >>> Mul(x, x)
+    x**2
+
+    If ``evaluate=False`` is passed, result is not evaluated.
+
+    >>> Mul(1, 2, evaluate=False)
+    1*2
+    >>> Mul(x, x, evaluate=False)
+    x*x
+
+    ``Mul()`` also represents the general structure of multiplication
+    operation.
+
+    >>> from sympy import MatrixSymbol
+    >>> A = MatrixSymbol('A', 2,2)
+    >>> expr = Mul(x,y).subs({y:A})
+    >>> expr
+    x*A
+    >>> type(expr)
+    <class 'sympy.matrices.expressions.matmul.MatMul'>
+
+    See Also
+    ========
+
+    MatMul
+
+    """
+    __slots__ = ()
+
+    args: tTuple[Expr]
+
+    is_Mul = True
+
+    _args_type = Expr
+    _kind_dispatcher = KindDispatcher("Mul_kind_dispatcher", commutative=True)
+
+    @property
+    def kind(self):
+        arg_kinds = (a.kind for a in self.args)
+        return self._kind_dispatcher(*arg_kinds)
+
+    def could_extract_minus_sign(self):
+        if self == (-self):
+            return False  # e.g. zoo*x == -zoo*x
+        c = self.args[0]
+        return c.is_Number and c.is_extended_negative
+
+    def __neg__(self):
+        c, args = self.as_coeff_mul()
+        if args[0] is not S.ComplexInfinity:
+            c = -c
+        if c is not S.One:
+            if args[0].is_Number:
+                args = list(args)
+                if c is S.NegativeOne:
+                    args[0] = -args[0]
+                else:
+                    args[0] *= c
+            else:
+                args = (c,) + args
+        return self._from_args(args, self.is_commutative)
+
+    @classmethod
+    def flatten(cls, seq):
+        """Return commutative, noncommutative and order arguments by
+        combining related terms.
+
+        Notes
+        =====
+            * In an expression like ``a*b*c``, Python process this through SymPy
+              as ``Mul(Mul(a, b), c)``. This can have undesirable consequences.
+
+              -  Sometimes terms are not combined as one would like:
+                 {c.f. https://github.com/sympy/sympy/issues/4596}
+
+                >>> from sympy import Mul, sqrt
+                >>> from sympy.abc import x, y, z
+                >>> 2*(x + 1) # this is the 2-arg Mul behavior
+                2*x + 2
+                >>> y*(x + 1)*2
+                2*y*(x + 1)
+                >>> 2*(x + 1)*y # 2-arg result will be obtained first
+                y*(2*x + 2)
+                >>> Mul(2, x + 1, y) # all 3 args simultaneously processed
+                2*y*(x + 1)
+                >>> 2*((x + 1)*y) # parentheses can control this behavior
+                2*y*(x + 1)
+
+                Powers with compound bases may not find a single base to
+                combine with unless all arguments are processed at once.
+                Post-processing may be necessary in such cases.
+                {c.f. https://github.com/sympy/sympy/issues/5728}
+
+                >>> a = sqrt(x*sqrt(y))
+                >>> a**3
+                (x*sqrt(y))**(3/2)
+                >>> Mul(a,a,a)
+                (x*sqrt(y))**(3/2)
+                >>> a*a*a
+                x*sqrt(y)*sqrt(x*sqrt(y))
+                >>> _.subs(a.base, z).subs(z, a.base)
+                (x*sqrt(y))**(3/2)
+
+              -  If more than two terms are being multiplied then all the
+                 previous terms will be re-processed for each new argument.
+                 So if each of ``a``, ``b`` and ``c`` were :class:`Mul`
+                 expression, then ``a*b*c`` (or building up the product
+                 with ``*=``) will process all the arguments of ``a`` and
+                 ``b`` twice: once when ``a*b`` is computed and again when
+                 ``c`` is multiplied.
+
+                 Using ``Mul(a, b, c)`` will process all arguments once.
+
+            * The results of Mul are cached according to arguments, so flatten
+              will only be called once for ``Mul(a, b, c)``. If you can
+              structure a calculation so the arguments are most likely to be
+              repeats then this can save time in computing the answer. For
+              example, say you had a Mul, M, that you wished to divide by ``d[i]``
+              and multiply by ``n[i]`` and you suspect there are many repeats
+              in ``n``. It would be better to compute ``M*n[i]/d[i]`` rather
+              than ``M/d[i]*n[i]`` since every time n[i] is a repeat, the
+              product, ``M*n[i]`` will be returned without flattening -- the
+              cached value will be returned. If you divide by the ``d[i]``
+              first (and those are more unique than the ``n[i]``) then that will
+              create a new Mul, ``M/d[i]`` the args of which will be traversed
+              again when it is multiplied by ``n[i]``.
+
+              {c.f. https://github.com/sympy/sympy/issues/5706}
+
+              This consideration is moot if the cache is turned off.
+
+            NB
+            --
+              The validity of the above notes depends on the implementation
+              details of Mul and flatten which may change at any time. Therefore,
+              you should only consider them when your code is highly performance
+              sensitive.
+
+              Removal of 1 from the sequence is already handled by AssocOp.__new__.
+        """
+
+        from sympy.calculus.accumulationbounds import AccumBounds
+        from sympy.matrices.expressions import MatrixExpr
+        rv = None
+        if len(seq) == 2:
+            a, b = seq
+            if b.is_Rational:
+                a, b = b, a
+                seq = [a, b]
+            assert a is not S.One
+            if not a.is_zero and a.is_Rational:
+                r, b = b.as_coeff_Mul()
+                if b.is_Add:
+                    if r is not S.One:  # 2-arg hack
+                        # leave the Mul as a Mul?
+                        ar = a*r
+                        if ar is S.One:
+                            arb = b
+                        else:
+                            arb = cls(a*r, b, evaluate=False)
+                        rv = [arb], [], None
+                    elif global_parameters.distribute and b.is_commutative:
+                        newb = Add(*[_keep_coeff(a, bi) for bi in b.args])
+                        rv = [newb], [], None
+            if rv:
+                return rv
+
+        # apply associativity, separate commutative part of seq
+        c_part = []         # out: commutative factors
+        nc_part = []        # out: non-commutative factors
+
+        nc_seq = []
+
+        coeff = S.One       # standalone term
+                            # e.g. 3 * ...
+
+        c_powers = []       # (base,exp)      n
+                            # e.g. (x,n) for x
+
+        num_exp = []        # (num-base, exp)           y
+                            # e.g.  (3, y)  for  ... * 3  * ...
+
+        neg1e = S.Zero      # exponent on -1 extracted from Number-based Pow and I
+
+        pnum_rat = {}       # (num-base, Rat-exp)          1/2
+                            # e.g.  (3, 1/2)  for  ... * 3     * ...
+
+        order_symbols = None
+
+        # --- PART 1 ---
+        #
+        # "collect powers and coeff":
+        #
+        # o coeff
+        # o c_powers
+        # o num_exp
+        # o neg1e
+        # o pnum_rat
+        #
+        # NOTE: this is optimized for all-objects-are-commutative case
+        for o in seq:
+            # O(x)
+            if o.is_Order:
+                o, order_symbols = o.as_expr_variables(order_symbols)
+
+            # Mul([...])
+            if o.is_Mul:
+                if o.is_commutative:
+                    seq.extend(o.args)    # XXX zerocopy?
+
+                else:
+                    # NCMul can have commutative parts as well
+                    for q in o.args:
+                        if q.is_commutative:
+                            seq.append(q)
+                        else:
+                            nc_seq.append(q)
+
+                    # append non-commutative marker, so we don't forget to
+                    # process scheduled non-commutative objects
+                    seq.append(NC_Marker)
+
+                continue
+
+            # 3
+            elif o.is_Number:
+                if o is S.NaN or coeff is S.ComplexInfinity and o.is_zero:
+                    # we know for sure the result will be nan
+                    return [S.NaN], [], None
+                elif coeff.is_Number or isinstance(coeff, AccumBounds):  # it could be zoo
+                    coeff *= o
+                    if coeff is S.NaN:
+                        # we know for sure the result will be nan
+                        return [S.NaN], [], None
+                continue
+
+            elif isinstance(o, AccumBounds):
+                coeff = o.__mul__(coeff)
+                continue
+
+            elif o is S.ComplexInfinity:
+                if not coeff:
+                    # 0 * zoo = NaN
+                    return [S.NaN], [], None
+                coeff = S.ComplexInfinity
+                continue
+
+            elif o is S.ImaginaryUnit:
+                neg1e += S.Half
+                continue
+
+            elif o.is_commutative:
+                #      e
+                # o = b
+                b, e = o.as_base_exp()
+
+                #  y
+                # 3
+                if o.is_Pow:
+                    if b.is_Number:
+
+                        # get all the factors with numeric base so they can be
+                        # combined below, but don't combine negatives unless
+                        # the exponent is an integer
+                        if e.is_Rational:
+                            if e.is_Integer:
+                                coeff *= Pow(b, e)  # it is an unevaluated power
+                                continue
+                            elif e.is_negative:    # also a sign of an unevaluated power
+                                seq.append(Pow(b, e))
+                                continue
+                            elif b.is_negative:
+                                neg1e += e
+                                b = -b
+                            if b is not S.One:
+                                pnum_rat.setdefault(b, []).append(e)
+                            continue
+                        elif b.is_positive or e.is_integer:
+                            num_exp.append((b, e))
+                            continue
+
+                c_powers.append((b, e))
+
+            # NON-COMMUTATIVE
+            # TODO: Make non-commutative exponents not combine automatically
+            else:
+                if o is not NC_Marker:
+                    nc_seq.append(o)
+
+                # process nc_seq (if any)
+                while nc_seq:
+                    o = nc_seq.pop(0)
+                    if not nc_part:
+                        nc_part.append(o)
+                        continue
+
+                    #                             b    c       b+c
+                    # try to combine last terms: a  * a   ->  a
+                    o1 = nc_part.pop()
+                    b1, e1 = o1.as_base_exp()
+                    b2, e2 = o.as_base_exp()
+                    new_exp = e1 + e2
+                    # Only allow powers to combine if the new exponent is
+                    # not an Add. This allow things like a**2*b**3 == a**5
+                    # if a.is_commutative == False, but prohibits
+                    # a**x*a**y and x**a*x**b from combining (x,y commute).
+                    if b1 == b2 and (not new_exp.is_Add):
+                        o12 = b1 ** new_exp
+
+                        # now o12 could be a commutative object
+                        if o12.is_commutative:
+                            seq.append(o12)
+                            continue
+                        else:
+                            nc_seq.insert(0, o12)
+
+                    else:
+                        nc_part.extend([o1, o])
+
+        # We do want a combined exponent if it would not be an Add, such as
+        #  y    2y     3y
+        # x  * x   -> x
+        # We determine if two exponents have the same term by using
+        # as_coeff_Mul.
+        #
+        # Unfortunately, this isn't smart enough to consider combining into
+        # exponents that might already be adds, so things like:
+        #  z - y    y
+        # x      * x  will be left alone.  This is because checking every possible
+        # combination can slow things down.
+
+        # gather exponents of common bases...
+        def _gather(c_powers):
+            common_b = {}  # b:e
+            for b, e in c_powers:
+                co = e.as_coeff_Mul()
+                common_b.setdefault(b, {}).setdefault(
+                    co[1], []).append(co[0])
+            for b, d in common_b.items():
+                for di, li in d.items():
+                    d[di] = Add(*li)
+            new_c_powers = []
+            for b, e in common_b.items():
+                new_c_powers.extend([(b, c*t) for t, c in e.items()])
+            return new_c_powers
+
+        # in c_powers
+        c_powers = _gather(c_powers)
+
+        # and in num_exp
+        num_exp = _gather(num_exp)
+
+        # --- PART 2 ---
+        #
+        # o process collected powers  (x**0 -> 1; x**1 -> x; otherwise Pow)
+        # o combine collected powers  (2**x * 3**x -> 6**x)
+        #   with numeric base
+
+        # ................................
+        # now we have:
+        # - coeff:
+        # - c_powers:    (b, e)
+        # - num_exp:     (2, e)
+        # - pnum_rat:    {(1/3, [1/3, 2/3, 1/4])}
+
+        #  0             1
+        # x  -> 1       x  -> x
+
+        # this should only need to run twice; if it fails because
+        # it needs to be run more times, perhaps this should be
+        # changed to a "while True" loop -- the only reason it
+        # isn't such now is to allow a less-than-perfect result to
+        # be obtained rather than raising an error or entering an
+        # infinite loop
+        for i in range(2):
+            new_c_powers = []
+            changed = False
+            for b, e in c_powers:
+                if e.is_zero:
+                    # canceling out infinities yields NaN
+                    if (b.is_Add or b.is_Mul) and any(infty in b.args
+                        for infty in (S.ComplexInfinity, S.Infinity,
+                                      S.NegativeInfinity)):
+                        return [S.NaN], [], None
+                    continue
+                if e is S.One:
+                    if b.is_Number:
+                        coeff *= b
+                        continue
+                    p = b
+                if e is not S.One:
+                    p = Pow(b, e)
+                    # check to make sure that the base doesn't change
+                    # after exponentiation; to allow for unevaluated
+                    # Pow, we only do so if b is not already a Pow
+                    if p.is_Pow and not b.is_Pow:
+                        bi = b
+                        b, e = p.as_base_exp()
+                        if b != bi:
+                            changed = True
+                c_part.append(p)
+                new_c_powers.append((b, e))
+            # there might have been a change, but unless the base
+            # matches some other base, there is nothing to do
+            if changed and len({
+                    b for b, e in new_c_powers}) != len(new_c_powers):
+                # start over again
+                c_part = []
+                c_powers = _gather(new_c_powers)
+            else:
+                break
+
+        #  x    x     x
+        # 2  * 3  -> 6
+        inv_exp_dict = {}   # exp:Mul(num-bases)     x    x
+                            # e.g.  x:6  for  ... * 2  * 3  * ...
+        for b, e in num_exp:
+            inv_exp_dict.setdefault(e, []).append(b)
+        for e, b in inv_exp_dict.items():
+            inv_exp_dict[e] = cls(*b)
+        c_part.extend([Pow(b, e) for e, b in inv_exp_dict.items() if e])
+
+        # b, e -> e' = sum(e), b
+        # {(1/5, [1/3]), (1/2, [1/12, 1/4]} -> {(1/3, [1/5, 1/2])}
+        comb_e = {}
+        for b, e in pnum_rat.items():
+            comb_e.setdefault(Add(*e), []).append(b)
+        del pnum_rat
+        # process them, reducing exponents to values less than 1
+        # and updating coeff if necessary else adding them to
+        # num_rat for further processing
+        num_rat = []
+        for e, b in comb_e.items():
+            b = cls(*b)
+            if e.q == 1:
+                coeff *= Pow(b, e)
+                continue
+            if e.p > e.q:
+                e_i, ep = divmod(e.p, e.q)
+                coeff *= Pow(b, e_i)
+                e = Rational(ep, e.q)
+            num_rat.append((b, e))
+        del comb_e
+
+        # extract gcd of bases in num_rat
+        # 2**(1/3)*6**(1/4) -> 2**(1/3+1/4)*3**(1/4)
+        pnew = defaultdict(list)
+        i = 0  # steps through num_rat which may grow
+        while i < len(num_rat):
+            bi, ei = num_rat[i]
+            grow = []
+            for j in range(i + 1, len(num_rat)):
+                bj, ej = num_rat[j]
+                g = bi.gcd(bj)
+                if g is not S.One:
+                    # 4**r1*6**r2 -> 2**(r1+r2)  *  2**r1 *  3**r2
+                    # this might have a gcd with something else
+                    e = ei + ej
+                    if e.q == 1:
+                        coeff *= Pow(g, e)
+                    else:
+                        if e.p > e.q:
+                            e_i, ep = divmod(e.p, e.q)  # change e in place
+                            coeff *= Pow(g, e_i)
+                            e = Rational(ep, e.q)
+                        grow.append((g, e))
+                    # update the jth item
+                    num_rat[j] = (bj/g, ej)
+                    # update bi that we are checking with
+                    bi = bi/g
+                    if bi is S.One:
+                        break
+            if bi is not S.One:
+                obj = Pow(bi, ei)
+                if obj.is_Number:
+                    coeff *= obj
+                else:
+                    # changes like sqrt(12) -> 2*sqrt(3)
+                    for obj in Mul.make_args(obj):
+                        if obj.is_Number:
+                            coeff *= obj
+                        else:
+                            assert obj.is_Pow
+                            bi, ei = obj.args
+                            pnew[ei].append(bi)
+
+            num_rat.extend(grow)
+            i += 1
+
+        # combine bases of the new powers
+        for e, b in pnew.items():
+            pnew[e] = cls(*b)
+
+        # handle -1 and I
+        if neg1e:
+            # treat I as (-1)**(1/2) and compute -1's total exponent
+            p, q =  neg1e.as_numer_denom()
+            # if the integer part is odd, extract -1
+            n, p = divmod(p, q)
+            if n % 2:
+                coeff = -coeff
+            # if it's a multiple of 1/2 extract I
+            if q == 2:
+                c_part.append(S.ImaginaryUnit)
+            elif p:
+                # see if there is any positive base this power of
+                # -1 can join
+                neg1e = Rational(p, q)
+                for e, b in pnew.items():
+                    if e == neg1e and b.is_positive:
+                        pnew[e] = -b
+                        break
+                else:
+                    # keep it separate; we've already evaluated it as
+                    # much as possible so evaluate=False
+                    c_part.append(Pow(S.NegativeOne, neg1e, evaluate=False))
+
+        # add all the pnew powers
+        c_part.extend([Pow(b, e) for e, b in pnew.items()])
+
+        # oo, -oo
+        if coeff in (S.Infinity, S.NegativeInfinity):
+            def _handle_for_oo(c_part, coeff_sign):
+                new_c_part = []
+                for t in c_part:
+                    if t.is_extended_positive:
+                        continue
+                    if t.is_extended_negative:
+                        coeff_sign *= -1
+                        continue
+                    new_c_part.append(t)
+                return new_c_part, coeff_sign
+            c_part, coeff_sign = _handle_for_oo(c_part, 1)
+            nc_part, coeff_sign = _handle_for_oo(nc_part, coeff_sign)
+            coeff *= coeff_sign
+
+        # zoo
+        if coeff is S.ComplexInfinity:
+            # zoo might be
+            #   infinite_real + bounded_im
+            #   bounded_real + infinite_im
+            #   infinite_real + infinite_im
+            # and non-zero real or imaginary will not change that status.
+            c_part = [c for c in c_part if not (fuzzy_not(c.is_zero) and
+                                                c.is_extended_real is not None)]
+            nc_part = [c for c in nc_part if not (fuzzy_not(c.is_zero) and
+                                                  c.is_extended_real is not None)]
+
+        # 0
+        elif coeff.is_zero:
+            # we know for sure the result will be 0 except the multiplicand
+            # is infinity or a matrix
+            if any(isinstance(c, MatrixExpr) for c in nc_part):
+                return [coeff], nc_part, order_symbols
+            if any(c.is_finite == False for c in c_part):
+                return [S.NaN], [], order_symbols
+            return [coeff], [], order_symbols
+
+        # check for straggling Numbers that were produced
+        _new = []
+        for i in c_part:
+            if i.is_Number:
+                coeff *= i
+            else:
+                _new.append(i)
+        c_part = _new
+
+        # order commutative part canonically
+        _mulsort(c_part)
+
+        # current code expects coeff to be always in slot-0
+        if coeff is not S.One:
+            c_part.insert(0, coeff)
+
+        # we are done
+        if (global_parameters.distribute and not nc_part and len(c_part) == 2 and
+                c_part[0].is_Number and c_part[0].is_finite and c_part[1].is_Add):
+            # 2*(1+a) -> 2 + 2 * a
+            coeff = c_part[0]
+            c_part = [Add(*[coeff*f for f in c_part[1].args])]
+
+        return c_part, nc_part, order_symbols
+
+    def _eval_power(self, e):
+
+        # don't break up NC terms: (A*B)**3 != A**3*B**3, it is A*B*A*B*A*B
+        cargs, nc = self.args_cnc(split_1=False)
+
+        if e.is_Integer:
+            return Mul(*[Pow(b, e, evaluate=False) for b in cargs]) * \
+                Pow(Mul._from_args(nc), e, evaluate=False)
+        if e.is_Rational and e.q == 2:
+            if self.is_imaginary:
+                a = self.as_real_imag()[1]
+                if a.is_Rational:
+                    from .power import integer_nthroot
+                    n, d = abs(a/2).as_numer_denom()
+                    n, t = integer_nthroot(n, 2)
+                    if t:
+                        d, t = integer_nthroot(d, 2)
+                        if t:
+                            from sympy.functions.elementary.complexes import sign
+                            r = sympify(n)/d
+                            return _unevaluated_Mul(r**e.p, (1 + sign(a)*S.ImaginaryUnit)**e.p)
+
+        p = Pow(self, e, evaluate=False)
+
+        if e.is_Rational or e.is_Float:
+            return p._eval_expand_power_base()
+
+        return p
+
+    @classmethod
+    def class_key(cls):
+        return 3, 0, cls.__name__
+
+    def _eval_evalf(self, prec):
+        c, m = self.as_coeff_Mul()
+        if c is S.NegativeOne:
+            if m.is_Mul:
+                rv = -AssocOp._eval_evalf(m, prec)
+            else:
+                mnew = m._eval_evalf(prec)
+                if mnew is not None:
+                    m = mnew
+                rv = -m
+        else:
+            rv = AssocOp._eval_evalf(self, prec)
+        if rv.is_number:
+            return rv.expand()
+        return rv
+
+    @property
+    def _mpc_(self):
+        """
+        Convert self to an mpmath mpc if possible
+        """
+        from .numbers import Float
+        im_part, imag_unit = self.as_coeff_Mul()
+        if imag_unit is not S.ImaginaryUnit:
+            # ValueError may seem more reasonable but since it's a @property,
+            # we need to use AttributeError to keep from confusing things like
+            # hasattr.
+            raise AttributeError("Cannot convert Mul to mpc. Must be of the form Number*I")
+
+        return (Float(0)._mpf_, Float(im_part)._mpf_)
+
+    @cacheit
+    def as_two_terms(self):
+        """Return head and tail of self.
+
+        This is the most efficient way to get the head and tail of an
+        expression.
+
+        - if you want only the head, use self.args[0];
+        - if you want to process the arguments of the tail then use
+          self.as_coef_mul() which gives the head and a tuple containing
+          the arguments of the tail when treated as a Mul.
+        - if you want the coefficient when self is treated as an Add
+          then use self.as_coeff_add()[0]
+
+        Examples
+        ========
+
+        >>> from sympy.abc import x, y
+        >>> (3*x*y).as_two_terms()
+        (3, x*y)
+        """
+        args = self.args
+
+        if len(args) == 1:
+            return S.One, self
+        elif len(args) == 2:
+            return args
+
+        else:
+            return args[0], self._new_rawargs(*args[1:])
+
+    @cacheit
+    def as_coeff_mul(self, *deps, rational=True, **kwargs):
+        if deps:
+            l1, l2 = sift(self.args, lambda x: x.has(*deps), binary=True)
+            return self._new_rawargs(*l2), tuple(l1)
+        args = self.args
+        if args[0].is_Number:
+            if not rational or args[0].is_Rational:
+                return args[0], args[1:]
+            elif args[0].is_extended_negative:
+                return S.NegativeOne, (-args[0],) + args[1:]
+        return S.One, args
+
+    def as_coeff_Mul(self, rational=False):
+        """
+        Efficiently extract the coefficient of a product.
+        """
+        coeff, args = self.args[0], self.args[1:]
+
+        if coeff.is_Number:
+            if not rational or coeff.is_Rational:
+                if len(args) == 1:
+                    return coeff, args[0]
+                else:
+                    return coeff, self._new_rawargs(*args)
+            elif coeff.is_extended_negative:
+                return S.NegativeOne, self._new_rawargs(*((-coeff,) + args))
+        return S.One, self
+
+    def as_real_imag(self, deep=True, **hints):
+        from sympy.functions.elementary.complexes import Abs, im, re
+        other = []
+        coeffr = []
+        coeffi = []
+        addterms = S.One
+        for a in self.args:
+            r, i = a.as_real_imag()
+            if i.is_zero:
+                coeffr.append(r)
+            elif r.is_zero:
+                coeffi.append(i*S.ImaginaryUnit)
+            elif a.is_commutative:
+                aconj = a.conjugate() if other else None
+                # search for complex conjugate pairs:
+                for i, x in enumerate(other):
+                    if x == aconj:
+                        coeffr.append(Abs(x)**2)
+                        del other[i]
+                        break
+                else:
+                    if a.is_Add:
+                        addterms *= a
+                    else:
+                        other.append(a)
+            else:
+                other.append(a)
+        m = self.func(*other)
+        if hints.get('ignore') == m:
+            return
+        if len(coeffi) % 2:
+            imco = im(coeffi.pop(0))
+            # all other pairs make a real factor; they will be
+            # put into reco below
+        else:
+            imco = S.Zero
+        reco = self.func(*(coeffr + coeffi))
+        r, i = (reco*re(m), reco*im(m))
+        if addterms == 1:
+            if m == 1:
+                if imco.is_zero:
+                    return (reco, S.Zero)
+                else:
+                    return (S.Zero, reco*imco)
+            if imco is S.Zero:
+                return (r, i)
+            return (-imco*i, imco*r)
+        from .function import expand_mul
+        addre, addim = expand_mul(addterms, deep=False).as_real_imag()
+        if imco is S.Zero:
+            return (r*addre - i*addim, i*addre + r*addim)
+        else:
+            r, i = -imco*i, imco*r
+            return (r*addre - i*addim, r*addim + i*addre)
+
+    @staticmethod
+    def _expandsums(sums):
+        """
+        Helper function for _eval_expand_mul.
+
+        sums must be a list of instances of Basic.
+        """
+
+        L = len(sums)
+        if L == 1:
+            return sums[0].args
+        terms = []
+        left = Mul._expandsums(sums[:L//2])
+        right = Mul._expandsums(sums[L//2:])
+
+        terms = [Mul(a, b) for a in left for b in right]
+        added = Add(*terms)
+        return Add.make_args(added)  # it may have collapsed down to one term
+
+    def _eval_expand_mul(self, **hints):
+        from sympy.simplify.radsimp import fraction
+
+        # Handle things like 1/(x*(x + 1)), which are automatically converted
+        # to 1/x*1/(x + 1)
+        expr = self
+        n, d = fraction(expr)
+        if d.is_Mul:
+            n, d = [i._eval_expand_mul(**hints) if i.is_Mul else i
+                for i in (n, d)]
+        expr = n/d
+        if not expr.is_Mul:
+            return expr
+
+        plain, sums, rewrite = [], [], False
+        for factor in expr.args:
+            if factor.is_Add:
+                sums.append(factor)
+                rewrite = True
+            else:
+                if factor.is_commutative:
+                    plain.append(factor)
+                else:
+                    sums.append(Basic(factor))  # Wrapper
+
+        if not rewrite:
+            return expr
+        else:
+            plain = self.func(*plain)
+            if sums:
+                deep = hints.get("deep", False)
+                terms = self.func._expandsums(sums)
+                args = []
+                for term in terms:
+                    t = self.func(plain, term)
+                    if t.is_Mul and any(a.is_Add for a in t.args) and deep:
+                        t = t._eval_expand_mul()
+                    args.append(t)
+                return Add(*args)
+            else:
+                return plain
+
+    @cacheit
+    def _eval_derivative(self, s):
+        args = list(self.args)
+        terms = []
+        for i in range(len(args)):
+            d = args[i].diff(s)
+            if d:
+                # Note: reduce is used in step of Mul as Mul is unable to
+                # handle subtypes and operation priority:
+                terms.append(reduce(lambda x, y: x*y, (args[:i] + [d] + args[i + 1:]), S.One))
+        return Add.fromiter(terms)
+
+    @cacheit
+    def _eval_derivative_n_times(self, s, n):
+        from .function import AppliedUndef
+        from .symbol import Symbol, symbols, Dummy
+        if not isinstance(s, (AppliedUndef, Symbol)):
+            # other types of s may not be well behaved, e.g.
+            # (cos(x)*sin(y)).diff([[x, y, z]])
+            return super()._eval_derivative_n_times(s, n)
+        from .numbers import Integer
+        args = self.args
+        m = len(args)
+        if isinstance(n, (int, Integer)):
+            # https://en.wikipedia.org/wiki/General_Leibniz_rule#More_than_two_factors
+            terms = []
+            from sympy.ntheory.multinomial import multinomial_coefficients_iterator
+            for kvals, c in multinomial_coefficients_iterator(m, n):
+                p = Mul(*[arg.diff((s, k)) for k, arg in zip(kvals, args)])
+                terms.append(c * p)
+            return Add(*terms)
+        from sympy.concrete.summations import Sum
+        from sympy.functions.combinatorial.factorials import factorial
+        from sympy.functions.elementary.miscellaneous import Max
+        kvals = symbols("k1:%i" % m, cls=Dummy)
+        klast = n - sum(kvals)
+        nfact = factorial(n)
+        e, l = (# better to use the multinomial?
+            nfact/prod(map(factorial, kvals))/factorial(klast)*\
+            Mul(*[args[t].diff((s, kvals[t])) for t in range(m-1)])*\
+            args[-1].diff((s, Max(0, klast))),
+            [(k, 0, n) for k in kvals])
+        return Sum(e, *l)
+
+    def _eval_difference_delta(self, n, step):
+        from sympy.series.limitseq import difference_delta as dd
+        arg0 = self.args[0]
+        rest = Mul(*self.args[1:])
+        return (arg0.subs(n, n + step) * dd(rest, n, step) + dd(arg0, n, step) *
+                rest)
+
+    def _matches_simple(self, expr, repl_dict):
+        # handle (w*3).matches('x*5') -> {w: x*5/3}
+        coeff, terms = self.as_coeff_Mul()
+        terms = Mul.make_args(terms)
+        if len(terms) == 1:
+            newexpr = self.__class__._combine_inverse(expr, coeff)
+            return terms[0].matches(newexpr, repl_dict)
+        return
+
+    def matches(self, expr, repl_dict=None, old=False):
+        expr = sympify(expr)
+        if self.is_commutative and expr.is_commutative:
+            return self._matches_commutative(expr, repl_dict, old)
+        elif self.is_commutative is not expr.is_commutative:
+            return None
+
+        # Proceed only if both both expressions are non-commutative
+        c1, nc1 = self.args_cnc()
+        c2, nc2 = expr.args_cnc()
+        c1, c2 = [c or [1] for c in [c1, c2]]
+
+        # TODO: Should these be self.func?
+        comm_mul_self = Mul(*c1)
+        comm_mul_expr = Mul(*c2)
+
+        repl_dict = comm_mul_self.matches(comm_mul_expr, repl_dict, old)
+
+        # If the commutative arguments didn't match and aren't equal, then
+        # then the expression as a whole doesn't match
+        if not repl_dict and c1 != c2:
+            return None
+
+        # Now match the non-commutative arguments, expanding powers to
+        # multiplications
+        nc1 = Mul._matches_expand_pows(nc1)
+        nc2 = Mul._matches_expand_pows(nc2)
+
+        repl_dict = Mul._matches_noncomm(nc1, nc2, repl_dict)
+
+        return repl_dict or None
+
+    @staticmethod
+    def _matches_expand_pows(arg_list):
+        new_args = []
+        for arg in arg_list:
+            if arg.is_Pow and arg.exp > 0:
+                new_args.extend([arg.base] * arg.exp)
+            else:
+                new_args.append(arg)
+        return new_args
+
+    @staticmethod
+    def _matches_noncomm(nodes, targets, repl_dict=None):
+        """Non-commutative multiplication matcher.
+
+        `nodes` is a list of symbols within the matcher multiplication
+        expression, while `targets` is a list of arguments in the
+        multiplication expression being matched against.
+        """
+        if repl_dict is None:
+            repl_dict = {}
+        else:
+            repl_dict = repl_dict.copy()
+
+        # List of possible future states to be considered
+        agenda = []
+        # The current matching state, storing index in nodes and targets
+        state = (0, 0)
+        node_ind, target_ind = state
+        # Mapping between wildcard indices and the index ranges they match
+        wildcard_dict = {}
+
+        while target_ind < len(targets) and node_ind < len(nodes):
+            node = nodes[node_ind]
+
+            if node.is_Wild:
+                Mul._matches_add_wildcard(wildcard_dict, state)
+
+            states_matches = Mul._matches_new_states(wildcard_dict, state,
+                                                     nodes, targets)
+            if states_matches:
+                new_states, new_matches = states_matches
+                agenda.extend(new_states)
+                if new_matches:
+                    for match in new_matches:
+                        repl_dict[match] = new_matches[match]
+            if not agenda:
+                return None
+            else:
+                state = agenda.pop()
+                node_ind, target_ind = state
+
+        return repl_dict
+
+    @staticmethod
+    def _matches_add_wildcard(dictionary, state):
+        node_ind, target_ind = state
+        if node_ind in dictionary:
+            begin, end = dictionary[node_ind]
+            dictionary[node_ind] = (begin, target_ind)
+        else:
+            dictionary[node_ind] = (target_ind, target_ind)
+
+    @staticmethod
+    def _matches_new_states(dictionary, state, nodes, targets):
+        node_ind, target_ind = state
+        node = nodes[node_ind]
+        target = targets[target_ind]
+
+        # Don't advance at all if we've exhausted the targets but not the nodes
+        if target_ind >= len(targets) - 1 and node_ind < len(nodes) - 1:
+            return None
+
+        if node.is_Wild:
+            match_attempt = Mul._matches_match_wilds(dictionary, node_ind,
+                                                     nodes, targets)
+            if match_attempt:
+                # If the same node has been matched before, don't return
+                # anything if the current match is diverging from the previous
+                # match
+                other_node_inds = Mul._matches_get_other_nodes(dictionary,
+                                                               nodes, node_ind)
+                for ind in other_node_inds:
+                    other_begin, other_end = dictionary[ind]
+                    curr_begin, curr_end = dictionary[node_ind]
+
+                    other_targets = targets[other_begin:other_end + 1]
+                    current_targets = targets[curr_begin:curr_end + 1]
+
+                    for curr, other in zip(current_targets, other_targets):
+                        if curr != other:
+                            return None
+
+                # A wildcard node can match more than one target, so only the
+                # target index is advanced
+                new_state = [(node_ind, target_ind + 1)]
+                # Only move on to the next node if there is one
+                if node_ind < len(nodes) - 1:
+                    new_state.append((node_ind + 1, target_ind + 1))
+                return new_state, match_attempt
+        else:
+            # If we're not at a wildcard, then make sure we haven't exhausted
+            # nodes but not targets, since in this case one node can only match
+            # one target
+            if node_ind >= len(nodes) - 1 and target_ind < len(targets) - 1:
+                return None
+
+            match_attempt = node.matches(target)
+
+            if match_attempt:
+                return [(node_ind + 1, target_ind + 1)], match_attempt
+            elif node == target:
+                return [(node_ind + 1, target_ind + 1)], None
+            else:
+                return None
+
+    @staticmethod
+    def _matches_match_wilds(dictionary, wildcard_ind, nodes, targets):
+        """Determine matches of a wildcard with sub-expression in `target`."""
+        wildcard = nodes[wildcard_ind]
+        begin, end = dictionary[wildcard_ind]
+        terms = targets[begin:end + 1]
+        # TODO: Should this be self.func?
+        mult = Mul(*terms) if len(terms) > 1 else terms[0]
+        return wildcard.matches(mult)
+
+    @staticmethod
+    def _matches_get_other_nodes(dictionary, nodes, node_ind):
+        """Find other wildcards that may have already been matched."""
+        ind_node = nodes[node_ind]
+        return [ind for ind in dictionary if nodes[ind] == ind_node]
+
+    @staticmethod
+    def _combine_inverse(lhs, rhs):
+        """
+        Returns lhs/rhs, but treats arguments like symbols, so things
+        like oo/oo return 1 (instead of a nan) and ``I`` behaves like
+        a symbol instead of sqrt(-1).
+        """
+        from sympy.simplify.simplify import signsimp
+        from .symbol import Dummy
+        if lhs == rhs:
+            return S.One
+
+        def check(l, r):
+            if l.is_Float and r.is_comparable:
+                # if both objects are added to 0 they will share the same "normalization"
+                # and are more likely to compare the same. Since Add(foo, 0) will not allow
+                # the 0 to pass, we use __add__ directly.
+                return l.__add__(0) == r.evalf().__add__(0)
+            return False
+        if check(lhs, rhs) or check(rhs, lhs):
+            return S.One
+        if any(i.is_Pow or i.is_Mul for i in (lhs, rhs)):
+            # gruntz and limit wants a literal I to not combine
+            # with a power of -1
+            d = Dummy('I')
+            _i = {S.ImaginaryUnit: d}
+            i_ = {d: S.ImaginaryUnit}
+            a = lhs.xreplace(_i).as_powers_dict()
+            b = rhs.xreplace(_i).as_powers_dict()
+            blen = len(b)
+            for bi in tuple(b.keys()):
+                if bi in a:
+                    a[bi] -= b.pop(bi)
+                    if not a[bi]:
+                        a.pop(bi)
+            if len(b) != blen:
+                lhs = Mul(*[k**v for k, v in a.items()]).xreplace(i_)
+                rhs = Mul(*[k**v for k, v in b.items()]).xreplace(i_)
+        rv = lhs/rhs
+        srv = signsimp(rv)
+        return srv if srv.is_Number else rv
+
+    def as_powers_dict(self):
+        d = defaultdict(int)
+        for term in self.args:
+            for b, e in term.as_powers_dict().items():
+                d[b] += e
+        return d
+
+    def as_numer_denom(self):
+        # don't use _from_args to rebuild the numerators and denominators
+        # as the order is not guaranteed to be the same once they have
+        # been separated from each other
+        numers, denoms = list(zip(*[f.as_numer_denom() for f in self.args]))
+        return self.func(*numers), self.func(*denoms)
+
+    def as_base_exp(self):
+        e1 = None
+        bases = []
+        nc = 0
+        for m in self.args:
+            b, e = m.as_base_exp()
+            if not b.is_commutative:
+                nc += 1
+            if e1 is None:
+                e1 = e
+            elif e != e1 or nc > 1:
+                return self, S.One
+            bases.append(b)
+        return self.func(*bases), e1
+
+    def _eval_is_polynomial(self, syms):
+        return all(term._eval_is_polynomial(syms) for term in self.args)
+
+    def _eval_is_rational_function(self, syms):
+        return all(term._eval_is_rational_function(syms) for term in self.args)
+
+    def _eval_is_meromorphic(self, x, a):
+        return _fuzzy_group((arg.is_meromorphic(x, a) for arg in self.args),
+                            quick_exit=True)
+
+    def _eval_is_algebraic_expr(self, syms):
+        return all(term._eval_is_algebraic_expr(syms) for term in self.args)
+
+    _eval_is_commutative = lambda self: _fuzzy_group(
+        a.is_commutative for a in self.args)
+
+    def _eval_is_complex(self):
+        comp = _fuzzy_group(a.is_complex for a in self.args)
+        if comp is False:
+            if any(a.is_infinite for a in self.args):
+                if any(a.is_zero is not False for a in self.args):
+                    return None
+                return False
+        return comp
+
+    def _eval_is_zero_infinite_helper(self):
+        #
+        # Helper used by _eval_is_zero and _eval_is_infinite.
+        #
+        # Three-valued logic is tricky so let us reason this carefully. It
+        # would be nice to say that we just check is_zero/is_infinite in all
+        # args but we need to be careful about the case that one arg is zero
+        # and another is infinite like Mul(0, oo) or more importantly a case
+        # where it is not known if the arguments are zero or infinite like
+        # Mul(y, 1/x). If either y or x could be zero then there is a
+        # *possibility* that we have Mul(0, oo) which should give None for both
+        # is_zero and is_infinite.
+        #
+        # We keep track of whether we have seen a zero or infinity but we also
+        # need to keep track of whether we have *possibly* seen one which
+        # would be indicated by None.
+        #
+        # For each argument there is the possibility that is_zero might give
+        # True, False or None and likewise that is_infinite might give True,
+        # False or None, giving 9 combinations. The True cases for is_zero and
+        # is_infinite are mutually exclusive though so there are 3 main cases:
+        #
+        # - is_zero = True
+        # - is_infinite = True
+        # - is_zero and is_infinite are both either False or None
+        #
+        # At the end seen_zero and seen_infinite can be any of 9 combinations
+        # of True/False/None. Unless one is False though we cannot return
+        # anything except None:
+        #
+        # - is_zero=True needs seen_zero=True and seen_infinite=False
+        # - is_zero=False needs seen_zero=False
+        # - is_infinite=True needs seen_infinite=True and seen_zero=False
+        # - is_infinite=False needs seen_infinite=False
+        # - anything else gives both is_zero=None and is_infinite=None
+        #
+        # The loop only sets the flags to True or None and never back to False.
+        # Hence as soon as neither flag is False we exit early returning None.
+        # In particular as soon as we encounter a single arg that has
+        # is_zero=is_infinite=None we exit. This is a common case since it is
+        # the default assumptions for a Symbol and also the case for most
+        # expressions containing such a symbol. The early exit gives a big
+        # speedup for something like Mul(*symbols('x:1000')).is_zero.
+        #
+        seen_zero = seen_infinite = False
+
+        for a in self.args:
+            if a.is_zero:
+                if seen_infinite is not False:
+                    return None, None
+                seen_zero = True
+            elif a.is_infinite:
+                if seen_zero is not False:
+                    return None, None
+                seen_infinite = True
+            else:
+                if seen_zero is False and a.is_zero is None:
+                    if seen_infinite is not False:
+                        return None, None
+                    seen_zero = None
+                if seen_infinite is False and a.is_infinite is None:
+                    if seen_zero is not False:
+                        return None, None
+                    seen_infinite = None
+
+        return seen_zero, seen_infinite
+
+    def _eval_is_zero(self):
+        # True iff any arg is zero and no arg is infinite but need to handle
+        # three valued logic carefully.
+        seen_zero, seen_infinite = self._eval_is_zero_infinite_helper()
+
+        if seen_zero is False:
+            return False
+        elif seen_zero is True and seen_infinite is False:
+            return True
+        else:
+            return None
+
+    def _eval_is_infinite(self):
+        # True iff any arg is infinite and no arg is zero but need to handle
+        # three valued logic carefully.
+        seen_zero, seen_infinite = self._eval_is_zero_infinite_helper()
+
+        if seen_infinite is True and seen_zero is False:
+            return True
+        elif seen_infinite is False:
+            return False
+        else:
+            return None
+
+    # We do not need to implement _eval_is_finite because the assumptions
+    # system can infer it from finite = not infinite.
+
+    def _eval_is_rational(self):
+        r = _fuzzy_group((a.is_rational for a in self.args), quick_exit=True)
+        if r:
+            return r
+        elif r is False:
+            # All args except one are rational
+            if all(a.is_zero is False for a in self.args):
+                return False
+
+    def _eval_is_algebraic(self):
+        r = _fuzzy_group((a.is_algebraic for a in self.args), quick_exit=True)
+        if r:
+            return r
+        elif r is False:
+            # All args except one are algebraic
+            if all(a.is_zero is False for a in self.args):
+                return False
+
+    # without involving odd/even checks this code would suffice:
+    #_eval_is_integer = lambda self: _fuzzy_group(
+    #    (a.is_integer for a in self.args), quick_exit=True)
+    def _eval_is_integer(self):
+        from sympy.ntheory.factor_ import trailing
+        is_rational = self._eval_is_rational()
+        if is_rational is False:
+            return False
+
+        numerators = []
+        denominators = []
+        unknown = False
+        for a in self.args:
+            hit = False
+            if a.is_integer:
+                if abs(a) is not S.One:
+                    numerators.append(a)
+            elif a.is_Rational:
+                n, d = a.as_numer_denom()
+                if abs(n) is not S.One:
+                    numerators.append(n)
+                if d is not S.One:
+                    denominators.append(d)
+            elif a.is_Pow:
+                b, e = a.as_base_exp()
+                if not b.is_integer or not e.is_integer:
+                    hit = unknown = True
+                if e.is_negative:
+                    denominators.append(2 if a is S.Half else
+                        Pow(a, S.NegativeOne))
+                elif not hit:
+                    # int b and pos int e: a = b**e is integer
+                    assert not e.is_positive
+                    # for rational self and e equal to zero: a = b**e is 1
+                    assert not e.is_zero
+                    return # sign of e unknown -> self.is_integer unknown
+                else:
+                    # x**2, 2**x, or x**y with x and y int-unknown -> unknown
+                    return
+            else:
+                return
+
+        if not denominators and not unknown:
+            return True
+
+        allodd = lambda x: all(i.is_odd for i in x)
+        alleven = lambda x: all(i.is_even for i in x)
+        anyeven = lambda x: any(i.is_even for i in x)
+
+        from .relational import is_gt
+        if not numerators and denominators and all(
+                is_gt(_, S.One) for _ in denominators):
+            return False
+        elif unknown:
+            return
+        elif allodd(numerators) and anyeven(denominators):
+            return False
+        elif anyeven(numerators) and denominators == [2]:
+            return True
+        elif alleven(numerators) and allodd(denominators
+                ) and (Mul(*denominators, evaluate=False) - 1
+                ).is_positive:
+            return False
+        if len(denominators) == 1:
+            d = denominators[0]
+            if d.is_Integer and d.is_even:
+                # if minimal power of 2 in num vs den is not
+                # negative then we have an integer
+                if (Add(*[i.as_base_exp()[1] for i in
+                        numerators if i.is_even]) - trailing(d.p)
+                        ).is_nonnegative:
+                    return True
+        if len(numerators) == 1:
+            n = numerators[0]
+            if n.is_Integer and n.is_even:
+                # if minimal power of 2 in den vs num is positive
+                # then we have have a non-integer
+                if (Add(*[i.as_base_exp()[1] for i in
+                        denominators if i.is_even]) - trailing(n.p)
+                        ).is_positive:
+                    return False
+
+    def _eval_is_polar(self):
+        has_polar = any(arg.is_polar for arg in self.args)
+        return has_polar and \
+            all(arg.is_polar or arg.is_positive for arg in self.args)
+
+    def _eval_is_extended_real(self):
+        return self._eval_real_imag(True)
+
+    def _eval_real_imag(self, real):
+        zero = False
+        t_not_re_im = None
+
+        for t in self.args:
+            if (t.is_complex or t.is_infinite) is False and t.is_extended_real is False:
+                return False
+            elif t.is_imaginary:  # I
+                real = not real
+            elif t.is_extended_real:  # 2
+                if not zero:
+                    z = t.is_zero
+                    if not z and zero is False:
+                        zero = z
+                    elif z:
+                        if all(a.is_finite for a in self.args):
+                            return True
+                        return
+            elif t.is_extended_real is False:
+                # symbolic or literal like `2 + I` or symbolic imaginary
+                if t_not_re_im:
+                    return  # complex terms might cancel
+                t_not_re_im = t
+            elif t.is_imaginary is False:  # symbolic like `2` or `2 + I`
+                if t_not_re_im:
+                    return  # complex terms might cancel
+                t_not_re_im = t
+            else:
+                return
+
+        if t_not_re_im:
+            if t_not_re_im.is_extended_real is False:
+                if real:  # like 3
+                    return zero  # 3*(smthng like 2 + I or i) is not real
+            if t_not_re_im.is_imaginary is False:  # symbolic 2 or 2 + I
+                if not real:  # like I
+                    return zero  # I*(smthng like 2 or 2 + I) is not real
+        elif zero is False:
+            return real  # can't be trumped by 0
+        elif real:
+            return real  # doesn't matter what zero is
+
+    def _eval_is_imaginary(self):
+        if all(a.is_zero is False and a.is_finite for a in self.args):
+            return self._eval_real_imag(False)
+
+    def _eval_is_hermitian(self):
+        return self._eval_herm_antiherm(True)
+
+    def _eval_is_antihermitian(self):
+        return self._eval_herm_antiherm(False)
+
+    def _eval_herm_antiherm(self, herm):
+        for t in self.args:
+            if t.is_hermitian is None or t.is_antihermitian is None:
+                return
+            if t.is_hermitian:
+                continue
+            elif t.is_antihermitian:
+                herm = not herm
+            else:
+                return
+
+        if herm is not False:
+            return herm
+
+        is_zero = self._eval_is_zero()
+        if is_zero:
+            return True
+        elif is_zero is False:
+            return herm
+
+    def _eval_is_irrational(self):
+        for t in self.args:
+            a = t.is_irrational
+            if a:
+                others = list(self.args)
+                others.remove(t)
+                if all((x.is_rational and fuzzy_not(x.is_zero)) is True for x in others):
+                    return True
+                return
+            if a is None:
+                return
+        if all(x.is_real for x in self.args):
+            return False
+
+    def _eval_is_extended_positive(self):
+        """Return True if self is positive, False if not, and None if it
+        cannot be determined.
+
+        Explanation
+        ===========
+
+        This algorithm is non-recursive and works by keeping track of the
+        sign which changes when a negative or nonpositive is encountered.
+        Whether a nonpositive or nonnegative is seen is also tracked since
+        the presence of these makes it impossible to return True, but
+        possible to return False if the end result is nonpositive. e.g.
+
+            pos * neg * nonpositive -> pos or zero -> None is returned
+            pos * neg * nonnegative -> neg or zero -> False is returned
+        """
+        return self._eval_pos_neg(1)
+
+    def _eval_pos_neg(self, sign):
+        saw_NON = saw_NOT = False
+        for t in self.args:
+            if t.is_extended_positive:
+                continue
+            elif t.is_extended_negative:
+                sign = -sign
+            elif t.is_zero:
+                if all(a.is_finite for a in self.args):
+                    return False
+                return
+            elif t.is_extended_nonpositive:
+                sign = -sign
+                saw_NON = True
+            elif t.is_extended_nonnegative:
+                saw_NON = True
+            # FIXME: is_positive/is_negative is False doesn't take account of
+            # Symbol('x', infinite=True, extended_real=True) which has
+            # e.g. is_positive is False but has uncertain sign.
+            elif t.is_positive is False:
+                sign = -sign
+                if saw_NOT:
+                    return
+                saw_NOT = True
+            elif t.is_negative is False:
+                if saw_NOT:
+                    return
+                saw_NOT = True
+            else:
+                return
+        if sign == 1 and saw_NON is False and saw_NOT is False:
+            return True
+        if sign < 0:
+            return False
+
+    def _eval_is_extended_negative(self):
+        return self._eval_pos_neg(-1)
+
+    def _eval_is_odd(self):
+        is_integer = self._eval_is_integer()
+        if is_integer is not True:
+            return is_integer
+
+        from sympy.simplify.radsimp import fraction
+        n, d = fraction(self)
+        if d.is_Integer and d.is_even:
+            from sympy.ntheory.factor_ import trailing
+            # if minimal power of 2 in num vs den is
+            # positive then we have an even number
+            if (Add(*[i.as_base_exp()[1] for i in
+                    Mul.make_args(n) if i.is_even]) - trailing(d.p)
+                    ).is_positive:
+                return False
+            return
+        r, acc = True, 1
+        for t in self.args:
+            if abs(t) is S.One:
+                continue
+            if t.is_even:
+                return False
+            if r is False:
+                pass
+            elif acc != 1 and (acc + t).is_odd:
+                r = False
+            elif t.is_even is None:
+                r = None
+            acc = t
+        return r
+
+    def _eval_is_even(self):
+        from sympy.simplify.radsimp import fraction
+        n, d = fraction(self)
+        if n.is_Integer and n.is_even:
+            # if minimal power of 2 in den vs num is not
+            # negative then this is not an integer and
+            # can't be even
+            from sympy.ntheory.factor_ import trailing
+            if (Add(*[i.as_base_exp()[1] for i in
+                    Mul.make_args(d) if i.is_even]) - trailing(n.p)
+                    ).is_nonnegative:
+                return False
+
+    def _eval_is_composite(self):
+        """
+        Here we count the number of arguments that have a minimum value
+        greater than two.
+        If there are more than one of such a symbol then the result is composite.
+        Else, the result cannot be determined.
+        """
+        number_of_args = 0 # count of symbols with minimum value greater than one
+        for arg in self.args:
+            if not (arg.is_integer and arg.is_positive):
+                return None
+            if (arg-1).is_positive:
+                number_of_args += 1
+
+        if number_of_args > 1:
+            return True
+
+    def _eval_subs(self, old, new):
+        from sympy.functions.elementary.complexes import sign
+        from sympy.ntheory.factor_ import multiplicity
+        from sympy.simplify.powsimp import powdenest
+        from sympy.simplify.radsimp import fraction
+
+        if not old.is_Mul:
+            return None
+
+        # try keep replacement literal so -2*x doesn't replace 4*x
+        if old.args[0].is_Number and old.args[0] < 0:
+            if self.args[0].is_Number:
+                if self.args[0] < 0:
+                    return self._subs(-old, -new)
+                return None
+
+        def base_exp(a):
+            # if I and -1 are in a Mul, they get both end up with
+            # a -1 base (see issue 6421); all we want here are the
+            # true Pow or exp separated into base and exponent
+            from sympy.functions.elementary.exponential import exp
+            if a.is_Pow or isinstance(a, exp):
+                return a.as_base_exp()
+            return a, S.One
+
+        def breakup(eq):
+            """break up powers of eq when treated as a Mul:
+                   b**(Rational*e) -> b**e, Rational
+                commutatives come back as a dictionary {b**e: Rational}
+                noncommutatives come back as a list [(b**e, Rational)]
+            """
+
+            (c, nc) = (defaultdict(int), [])
+            for a in Mul.make_args(eq):
+                a = powdenest(a)
+                (b, e) = base_exp(a)
+                if e is not S.One:
+                    (co, _) = e.as_coeff_mul()
+                    b = Pow(b, e/co)
+                    e = co
+                if a.is_commutative:
+                    c[b] += e
+                else:
+                    nc.append([b, e])
+            return (c, nc)
+
+        def rejoin(b, co):
+            """
+            Put rational back with exponent; in general this is not ok, but
+            since we took it from the exponent for analysis, it's ok to put
+            it back.
+            """
+
+            (b, e) = base_exp(b)
+            return Pow(b, e*co)
+
+        def ndiv(a, b):
+            """if b divides a in an extractive way (like 1/4 divides 1/2
+            but not vice versa, and 2/5 does not divide 1/3) then return
+            the integer number of times it divides, else return 0.
+            """
+            if not b.q % a.q or not a.q % b.q:
+                return int(a/b)
+            return 0
+
+        # give Muls in the denominator a chance to be changed (see issue 5651)
+        # rv will be the default return value
+        rv = None
+        n, d = fraction(self)
+        self2 = self
+        if d is not S.One:
+            self2 = n._subs(old, new)/d._subs(old, new)
+            if not self2.is_Mul:
+                return self2._subs(old, new)
+            if self2 != self:
+                rv = self2
+
+        # Now continue with regular substitution.
+
+        # handle the leading coefficient and use it to decide if anything
+        # should even be started; we always know where to find the Rational
+        # so it's a quick test
+
+        co_self = self2.args[0]
+        co_old = old.args[0]
+        co_xmul = None
+        if co_old.is_Rational and co_self.is_Rational:
+            # if coeffs are the same there will be no updating to do
+            # below after breakup() step; so skip (and keep co_xmul=None)
+            if co_old != co_self:
+                co_xmul = co_self.extract_multiplicatively(co_old)
+        elif co_old.is_Rational:
+            return rv
+
+        # break self and old into factors
+
+        (c, nc) = breakup(self2)
+        (old_c, old_nc) = breakup(old)
+
+        # update the coefficients if we had an extraction
+        # e.g. if co_self were 2*(3/35*x)**2 and co_old = 3/5
+        # then co_self in c is replaced by (3/5)**2 and co_residual
+        # is 2*(1/7)**2
+
+        if co_xmul and co_xmul.is_Rational and abs(co_old) != 1:
+            mult = S(multiplicity(abs(co_old), co_self))
+            c.pop(co_self)
+            if co_old in c:
+                c[co_old] += mult
+            else:
+                c[co_old] = mult
+            co_residual = co_self/co_old**mult
+        else:
+            co_residual = 1
+
+        # do quick tests to see if we can't succeed
+
+        ok = True
+        if len(old_nc) > len(nc):
+            # more non-commutative terms
+            ok = False
+        elif len(old_c) > len(c):
+            # more commutative terms
+            ok = False
+        elif {i[0] for i in old_nc}.difference({i[0] for i in nc}):
+            # unmatched non-commutative bases
+            ok = False
+        elif set(old_c).difference(set(c)):
+            # unmatched commutative terms
+            ok = False
+        elif any(sign(c[b]) != sign(old_c[b]) for b in old_c):
+            # differences in sign
+            ok = False
+        if not ok:
+            return rv
+
+        if not old_c:
+            cdid = None
+        else:
+            rat = []
+            for (b, old_e) in old_c.items():
+                c_e = c[b]
+                rat.append(ndiv(c_e, old_e))
+                if not rat[-1]:
+                    return rv
+            cdid = min(rat)
+
+        if not old_nc:
+            ncdid = None
+            for i in range(len(nc)):
+                nc[i] = rejoin(*nc[i])
+        else:
+            ncdid = 0  # number of nc replacements we did
+            take = len(old_nc)  # how much to look at each time
+            limit = cdid or S.Infinity  # max number that we can take
+            failed = []  # failed terms will need subs if other terms pass
+            i = 0
+            while limit and i + take <= len(nc):
+                hit = False
+
+                # the bases must be equivalent in succession, and
+                # the powers must be extractively compatible on the
+                # first and last factor but equal in between.
+
+                rat = []
+                for j in range(take):
+                    if nc[i + j][0] != old_nc[j][0]:
+                        break
+                    elif j == 0:
+                        rat.append(ndiv(nc[i + j][1], old_nc[j][1]))
+                    elif j == take - 1:
+                        rat.append(ndiv(nc[i + j][1], old_nc[j][1]))
+                    elif nc[i + j][1] != old_nc[j][1]:
+                        break
+                    else:
+                        rat.append(1)
+                    j += 1
+                else:
+                    ndo = min(rat)
+                    if ndo:
+                        if take == 1:
+                            if cdid:
+                                ndo = min(cdid, ndo)
+                            nc[i] = Pow(new, ndo)*rejoin(nc[i][0],
+                                    nc[i][1] - ndo*old_nc[0][1])
+                        else:
+                            ndo = 1
+
+                            # the left residual
+
+                            l = rejoin(nc[i][0], nc[i][1] - ndo*
+                                    old_nc[0][1])
+
+                            # eliminate all middle terms
+
+                            mid = new
+
+                            # the right residual (which may be the same as the middle if take == 2)
+
+                            ir = i + take - 1
+                            r = (nc[ir][0], nc[ir][1] - ndo*
+                                 old_nc[-1][1])
+                            if r[1]:
+                                if i + take < len(nc):
+                                    nc[i:i + take] = [l*mid, r]
+                                else:
+                                    r = rejoin(*r)
+                                    nc[i:i + take] = [l*mid*r]
+                            else:
+
+                                # there was nothing left on the right
+
+                                nc[i:i + take] = [l*mid]
+
+                        limit -= ndo
+                        ncdid += ndo
+                        hit = True
+                if not hit:
+
+                    # do the subs on this failing factor
+
+                    failed.append(i)
+                i += 1
+            else:
+
+                if not ncdid:
+                    return rv
+
+                # although we didn't fail, certain nc terms may have
+                # failed so we rebuild them after attempting a partial
+                # subs on them
+
+                failed.extend(range(i, len(nc)))
+                for i in failed:
+                    nc[i] = rejoin(*nc[i]).subs(old, new)
+
+        # rebuild the expression
+
+        if cdid is None:
+            do = ncdid
+        elif ncdid is None:
+            do = cdid
+        else:
+            do = min(ncdid, cdid)
+
+        margs = []
+        for b in c:
+            if b in old_c:
+
+                # calculate the new exponent
+
+                e = c[b] - old_c[b]*do
+                margs.append(rejoin(b, e))
+            else:
+                margs.append(rejoin(b.subs(old, new), c[b]))
+        if cdid and not ncdid:
+
+            # in case we are replacing commutative with non-commutative,
+            # we want the new term to come at the front just like the
+            # rest of this routine
+
+            margs = [Pow(new, cdid)] + margs
+        return co_residual*self2.func(*margs)*self2.func(*nc)
+
+    def _eval_nseries(self, x, n, logx, cdir=0):
+        from .function import PoleError
+        from sympy.functions.elementary.integers import ceiling
+        from sympy.series.order import Order
+
+        def coeff_exp(term, x):
+            lt = term.as_coeff_exponent(x)
+            if lt[0].has(x):
+                try:
+                    lt = term.leadterm(x)
+                except ValueError:
+                    return term, S.Zero
+            return lt
+
+        ords = []
+
+        try:
+            for t in self.args:
+                coeff, exp = t.leadterm(x)
+                if not coeff.has(x):
+                    ords.append((t, exp))
+                else:
+                    raise ValueError
+
+            n0 = sum(t[1] for t in ords if t[1].is_number)
+            facs = []
+            for t, m in ords:
+                n1 = ceiling(n - n0 + (m if m.is_number else 0))
+                s = t.nseries(x, n=n1, logx=logx, cdir=cdir)
+                ns = s.getn()
+                if ns is not None:
+                    if ns < n1:  # less than expected
+                        n -= n1 - ns    # reduce n
+                facs.append(s)
+
+        except (ValueError, NotImplementedError, TypeError, AttributeError, PoleError):
+            n0 = sympify(sum(t[1] for t in ords if t[1].is_number))
+            if n0.is_nonnegative:
+                n0 = S.Zero
+            facs = [t.nseries(x, n=ceiling(n-n0), logx=logx, cdir=cdir) for t in self.args]
+            from sympy.simplify.powsimp import powsimp
+            res = powsimp(self.func(*facs).expand(), combine='exp', deep=True)
+            if res.has(Order):
+                res += Order(x**n, x)
+            return res
+
+        res = S.Zero
+        ords2 = [Add.make_args(factor) for factor in facs]
+
+        for fac in product(*ords2):
+            ords3 = [coeff_exp(term, x) for term in fac]
+            coeffs, powers = zip(*ords3)
+            power = sum(powers)
+            if (power - n).is_negative:
+                res += Mul(*coeffs)*(x**power)
+
+        def max_degree(e, x):
+            if e is x:
+                return S.One
+            if e.is_Atom:
+                return S.Zero
+            if e.is_Add:
+                return max(max_degree(a, x) for a in e.args)
+            if e.is_Mul:
+                return Add(*[max_degree(a, x) for a in e.args])
+            if e.is_Pow:
+                return max_degree(e.base, x)*e.exp
+            return S.Zero
+
+        if self.is_polynomial(x):
+            from sympy.polys.polyerrors import PolynomialError
+            from sympy.polys.polytools import degree
+            try:
+                if max_degree(self, x) >= n or degree(self, x) != degree(res, x):
+                    res += Order(x**n, x)
+            except PolynomialError:
+                pass
+            else:
+                return res
+
+        if res != self:
+            if (self - res).subs(x, 0) == S.Zero and n > 0:
+                lt = self._eval_as_leading_term(x, logx=logx, cdir=cdir)
+                if lt == S.Zero:
+                    return res
+            res += Order(x**n, x)
+        return res
+
+    def _eval_as_leading_term(self, x, logx=None, cdir=0):
+        return self.func(*[t.as_leading_term(x, logx=logx, cdir=cdir) for t in self.args])
+
+    def _eval_conjugate(self):
+        return self.func(*[t.conjugate() for t in self.args])
+
+    def _eval_transpose(self):
+        return self.func(*[t.transpose() for t in self.args[::-1]])
+
+    def _eval_adjoint(self):
+        return self.func(*[t.adjoint() for t in self.args[::-1]])
+
+    def as_content_primitive(self, radical=False, clear=True):
+        """Return the tuple (R, self/R) where R is the positive Rational
+        extracted from self.
+
+        Examples
+        ========
+
+        >>> from sympy import sqrt
+        >>> (-3*sqrt(2)*(2 - 2*sqrt(2))).as_content_primitive()
+        (6, -sqrt(2)*(1 - sqrt(2)))
+
+        See docstring of Expr.as_content_primitive for more examples.
+        """
+
+        coef = S.One
+        args = []
+        for a in self.args:
+            c, p = a.as_content_primitive(radical=radical, clear=clear)
+            coef *= c
+            if p is not S.One:
+                args.append(p)
+        # don't use self._from_args here to reconstruct args
+        # since there may be identical args now that should be combined
+        # e.g. (2+2*x)*(3+3*x) should be (6, (1 + x)**2) not (6, (1+x)*(1+x))
+        return coef, self.func(*args)
+
+    def as_ordered_factors(self, order=None):
+        """Transform an expression into an ordered list of factors.
+
+        Examples
+        ========
+
+        >>> from sympy import sin, cos
+        >>> from sympy.abc import x, y
+
+        >>> (2*x*y*sin(x)*cos(x)).as_ordered_factors()
+        [2, x, y, sin(x), cos(x)]
+
+        """
+        cpart, ncpart = self.args_cnc()
+        cpart.sort(key=lambda expr: expr.sort_key(order=order))
+        return cpart + ncpart
+
+    @property
+    def _sorted_args(self):
+        return tuple(self.as_ordered_factors())
+
+mul = AssocOpDispatcher('mul')
+
+
+def prod(a, start=1):
+    """Return product of elements of a. Start with int 1 so if only
+       ints are included then an int result is returned.
+
+    Examples
+    ========
+
+    >>> from sympy import prod, S
+    >>> prod(range(3))
+    0
+    >>> type(_) is int
+    True
+    >>> prod([S(2), 3])
+    6
+    >>> _.is_Integer
+    True
+
+    You can start the product at something other than 1:
+
+    >>> prod([1, 2], 3)
+    6
+
+    """
+    return reduce(operator.mul, a, start)
+
+
+def _keep_coeff(coeff, factors, clear=True, sign=False):
+    """Return ``coeff*factors`` unevaluated if necessary.
+
+    If ``clear`` is False, do not keep the coefficient as a factor
+    if it can be distributed on a single factor such that one or
+    more terms will still have integer coefficients.
+
+    If ``sign`` is True, allow a coefficient of -1 to remain factored out.
+
+    Examples
+    ========
+
+    >>> from sympy.core.mul import _keep_coeff
+    >>> from sympy.abc import x, y
+    >>> from sympy import S
+
+    >>> _keep_coeff(S.Half, x + 2)
+    (x + 2)/2
+    >>> _keep_coeff(S.Half, x + 2, clear=False)
+    x/2 + 1
+    >>> _keep_coeff(S.Half, (x + 2)*y, clear=False)
+    y*(x + 2)/2
+    >>> _keep_coeff(S(-1), x + y)
+    -x - y
+    >>> _keep_coeff(S(-1), x + y, sign=True)
+    -(x + y)
+    """
+    if not coeff.is_Number:
+        if factors.is_Number:
+            factors, coeff = coeff, factors
+        else:
+            return coeff*factors
+    if factors is S.One:
+        return coeff
+    if coeff is S.One:
+        return factors
+    elif coeff is S.NegativeOne and not sign:
+        return -factors
+    elif factors.is_Add:
+        if not clear and coeff.is_Rational and coeff.q != 1:
+            args = [i.as_coeff_Mul() for i in factors.args]
+            args = [(_keep_coeff(c, coeff), m) for c, m in args]
+            if any(c.is_Integer for c, _ in args):
+                return Add._from_args([Mul._from_args(
+                    i[1:] if i[0] == 1 else i) for i in args])
+        return Mul(coeff, factors, evaluate=False)
+    elif factors.is_Mul:
+        margs = list(factors.args)
+        if margs[0].is_Number:
+            margs[0] *= coeff
+            if margs[0] == 1:
+                margs.pop(0)
+        else:
+            margs.insert(0, coeff)
+        return Mul._from_args(margs)
+    else:
+        m = coeff*factors
+        if m.is_Number and not factors.is_Number:
+            m = Mul._from_args((coeff, factors))
+        return m
+
+def expand_2arg(e):
+    def do(e):
+        if e.is_Mul:
+            c, r = e.as_coeff_Mul()
+            if c.is_Number and r.is_Add:
+                return _unevaluated_Add(*[c*ri for ri in r.args])
+        return e
+    return bottom_up(e, do)
+
+
+from .numbers import Rational
+from .power import Pow
+from .add import Add, _unevaluated_Add

env-llmeval/lib/python3.10/site-packages/sympy/core/operations.py

@@ -0,0 +1,722 @@
+from __future__ import annotations
+from operator import attrgetter
+from collections import defaultdict
+
+from sympy.utilities.exceptions import sympy_deprecation_warning
+
+from .sympify import _sympify as _sympify_, sympify
+from .basic import Basic
+from .cache import cacheit
+from .sorting import ordered
+from .logic import fuzzy_and
+from .parameters import global_parameters
+from sympy.utilities.iterables import sift
+from sympy.multipledispatch.dispatcher import (Dispatcher,
+    ambiguity_register_error_ignore_dup,
+    str_signature, RaiseNotImplementedError)
+
+
+class AssocOp(Basic):
+    """ Associative operations, can separate noncommutative and
+    commutative parts.
+
+    (a op b) op c == a op (b op c) == a op b op c.
+
+    Base class for Add and Mul.
+
+    This is an abstract base class, concrete derived classes must define
+    the attribute `identity`.
+
+    .. deprecated:: 1.7
+
+       Using arguments that aren't subclasses of :class:`~.Expr` in core
+       operators (:class:`~.Mul`, :class:`~.Add`, and :class:`~.Pow`) is
+       deprecated. See :ref:`non-expr-args-deprecated` for details.
+
+    Parameters
+    ==========
+
+    *args :
+        Arguments which are operated
+
+    evaluate : bool, optional
+        Evaluate the operation. If not passed, refer to ``global_parameters.evaluate``.
+    """
+
+    # for performance reason, we don't let is_commutative go to assumptions,
+    # and keep it right here
+    __slots__: tuple[str, ...] = ('is_commutative',)
+
+    _args_type: type[Basic] | None = None
+
+    @cacheit
+    def __new__(cls, *args, evaluate=None, _sympify=True):
+        # Allow faster processing by passing ``_sympify=False``, if all arguments
+        # are already sympified.
+        if _sympify:
+            args = list(map(_sympify_, args))
+
+        # Disallow non-Expr args in Add/Mul
+        typ = cls._args_type
+        if typ is not None:
+            from .relational import Relational
+            if any(isinstance(arg, Relational) for arg in args):
+                raise TypeError("Relational cannot be used in %s" % cls.__name__)
+
+            # This should raise TypeError once deprecation period is over:
+            for arg in args:
+                if not isinstance(arg, typ):
+                    sympy_deprecation_warning(
+                        f"""
+
+Using non-Expr arguments in {cls.__name__} is deprecated (in this case, one of
+the arguments has type {type(arg).__name__!r}).
+
+If you really did intend to use a multiplication or addition operation with
+this object, use the * or + operator instead.
+
+                        """,
+                        deprecated_since_version="1.7",
+                        active_deprecations_target="non-expr-args-deprecated",
+                        stacklevel=4,
+                    )
+
+        if evaluate is None:
+            evaluate = global_parameters.evaluate
+        if not evaluate:
+            obj = cls._from_args(args)
+            obj = cls._exec_constructor_postprocessors(obj)
+            return obj
+
+        args = [a for a in args if a is not cls.identity]
+
+        if len(args) == 0:
+            return cls.identity
+        if len(args) == 1:
+            return args[0]
+
+        c_part, nc_part, order_symbols = cls.flatten(args)
+        is_commutative = not nc_part
+        obj = cls._from_args(c_part + nc_part, is_commutative)
+        obj = cls._exec_constructor_postprocessors(obj)
+
+        if order_symbols is not None:
+            from sympy.series.order import Order
+            return Order(obj, *order_symbols)
+        return obj
+
+    @classmethod
+    def _from_args(cls, args, is_commutative=None):
+        """Create new instance with already-processed args.
+        If the args are not in canonical order, then a non-canonical
+        result will be returned, so use with caution. The order of
+        args may change if the sign of the args is changed."""
+        if len(args) == 0:
+            return cls.identity
+        elif len(args) == 1:
+            return args[0]
+
+        obj = super().__new__(cls, *args)
+        if is_commutative is None:
+            is_commutative = fuzzy_and(a.is_commutative for a in args)
+        obj.is_commutative = is_commutative
+        return obj
+
+    def _new_rawargs(self, *args, reeval=True, **kwargs):
+        """Create new instance of own class with args exactly as provided by
+        caller but returning the self class identity if args is empty.
+
+        Examples
+        ========
+
+           This is handy when we want to optimize things, e.g.
+
+               >>> from sympy import Mul, S
+               >>> from sympy.abc import x, y
+               >>> e = Mul(3, x, y)
+               >>> e.args
+               (3, x, y)
+               >>> Mul(*e.args[1:])
+               x*y
+               >>> e._new_rawargs(*e.args[1:])  # the same as above, but faster
+               x*y
+
+           Note: use this with caution. There is no checking of arguments at
+           all. This is best used when you are rebuilding an Add or Mul after
+           simply removing one or more args. If, for example, modifications,
+           result in extra 1s being inserted they will show up in the result:
+
+               >>> m = (x*y)._new_rawargs(S.One, x); m
+               1*x
+               >>> m == x
+               False
+               >>> m.is_Mul
+               True
+
+           Another issue to be aware of is that the commutativity of the result
+           is based on the commutativity of self. If you are rebuilding the
+           terms that came from a commutative object then there will be no
+           problem, but if self was non-commutative then what you are
+           rebuilding may now be commutative.
+
+           Although this routine tries to do as little as possible with the
+           input, getting the commutativity right is important, so this level
+           of safety is enforced: commutativity will always be recomputed if
+           self is non-commutative and kwarg `reeval=False` has not been
+           passed.
+        """
+        if reeval and self.is_commutative is False:
+            is_commutative = None
+        else:
+            is_commutative = self.is_commutative
+        return self._from_args(args, is_commutative)
+
+    @classmethod
+    def flatten(cls, seq):
+        """Return seq so that none of the elements are of type `cls`. This is
+        the vanilla routine that will be used if a class derived from AssocOp
+        does not define its own flatten routine."""
+        # apply associativity, no commutativity property is used
+        new_seq = []
+        while seq:
+            o = seq.pop()
+            if o.__class__ is cls:  # classes must match exactly
+                seq.extend(o.args)
+            else:
+                new_seq.append(o)
+        new_seq.reverse()
+
+        # c_part, nc_part, order_symbols
+        return [], new_seq, None
+
+    def _matches_commutative(self, expr, repl_dict=None, old=False):
+        """
+        Matches Add/Mul "pattern" to an expression "expr".
+
+        repl_dict ... a dictionary of (wild: expression) pairs, that get
+                      returned with the results
+
+        This function is the main workhorse for Add/Mul.
+
+        Examples
+        ========
+
+        >>> from sympy import symbols, Wild, sin
+        >>> a = Wild("a")
+        >>> b = Wild("b")
+        >>> c = Wild("c")
+        >>> x, y, z = symbols("x y z")
+        >>> (a+sin(b)*c)._matches_commutative(x+sin(y)*z)
+        {a_: x, b_: y, c_: z}
+
+        In the example above, "a+sin(b)*c" is the pattern, and "x+sin(y)*z" is
+        the expression.
+
+        The repl_dict contains parts that were already matched. For example
+        here:
+
+        >>> (x+sin(b)*c)._matches_commutative(x+sin(y)*z, repl_dict={a: x})
+        {a_: x, b_: y, c_: z}
+
+        the only function of the repl_dict is to return it in the
+        result, e.g. if you omit it:
+
+        >>> (x+sin(b)*c)._matches_commutative(x+sin(y)*z)
+        {b_: y, c_: z}
+
+        the "a: x" is not returned in the result, but otherwise it is
+        equivalent.
+
+        """
+        from .function import _coeff_isneg
+        # make sure expr is Expr if pattern is Expr
+        from .expr import Expr
+        if isinstance(self, Expr) and not isinstance(expr, Expr):
+            return None
+
+        if repl_dict is None:
+            repl_dict = {}
+
+        # handle simple patterns
+        if self == expr:
+            return repl_dict
+
+        d = self._matches_simple(expr, repl_dict)
+        if d is not None:
+            return d
+
+        # eliminate exact part from pattern: (2+a+w1+w2).matches(expr) -> (w1+w2).matches(expr-a-2)
+        from .function import WildFunction
+        from .symbol import Wild
+        wild_part, exact_part = sift(self.args, lambda p:
+            p.has(Wild, WildFunction) and not expr.has(p),
+            binary=True)
+        if not exact_part:
+            wild_part = list(ordered(wild_part))
+            if self.is_Add:
+                # in addition to normal ordered keys, impose
+                # sorting on Muls with leading Number to put
+                # them in order
+                wild_part = sorted(wild_part, key=lambda x:
+                    x.args[0] if x.is_Mul and x.args[0].is_Number else
+                    0)
+        else:
+            exact = self._new_rawargs(*exact_part)
+            free = expr.free_symbols
+            if free and (exact.free_symbols - free):
+                # there are symbols in the exact part that are not
+                # in the expr; but if there are no free symbols, let
+                # the matching continue
+                return None
+            newexpr = self._combine_inverse(expr, exact)
+            if not old and (expr.is_Add or expr.is_Mul):
+                check = newexpr
+                if _coeff_isneg(check):
+                    check = -check
+                if check.count_ops() > expr.count_ops():
+                    return None
+            newpattern = self._new_rawargs(*wild_part)
+            return newpattern.matches(newexpr, repl_dict)
+
+        # now to real work ;)
+        i = 0
+        saw = set()
+        while expr not in saw:
+            saw.add(expr)
+            args = tuple(ordered(self.make_args(expr)))
+            if self.is_Add and expr.is_Add:
+                # in addition to normal ordered keys, impose
+                # sorting on Muls with leading Number to put
+                # them in order
+                args = tuple(sorted(args, key=lambda x:
+                    x.args[0] if x.is_Mul and x.args[0].is_Number else
+                    0))
+            expr_list = (self.identity,) + args
+            for last_op in reversed(expr_list):
+                for w in reversed(wild_part):
+                    d1 = w.matches(last_op, repl_dict)
+                    if d1 is not None:
+                        d2 = self.xreplace(d1).matches(expr, d1)
+                        if d2 is not None:
+                            return d2
+
+            if i == 0:
+                if self.is_Mul:
+                    # make e**i look like Mul
+                    if expr.is_Pow and expr.exp.is_Integer:
+                        from .mul import Mul
+                        if expr.exp > 0:
+                            expr = Mul(*[expr.base, expr.base**(expr.exp - 1)], evaluate=False)
+                        else:
+                            expr = Mul(*[1/expr.base, expr.base**(expr.exp + 1)], evaluate=False)
+                        i += 1
+                        continue
+
+                elif self.is_Add:
+                    # make i*e look like Add
+                    c, e = expr.as_coeff_Mul()
+                    if abs(c) > 1:
+                        from .add import Add
+                        if c > 0:
+                            expr = Add(*[e, (c - 1)*e], evaluate=False)
+                        else:
+                            expr = Add(*[-e, (c + 1)*e], evaluate=False)
+                        i += 1
+                        continue
+
+                    # try collection on non-Wild symbols
+                    from sympy.simplify.radsimp import collect
+                    was = expr
+                    did = set()
+                    for w in reversed(wild_part):
+                        c, w = w.as_coeff_mul(Wild)
+                        free = c.free_symbols - did
+                        if free:
+                            did.update(free)
+                            expr = collect(expr, free)
+                    if expr != was:
+                        i += 0
+                        continue
+
+                break  # if we didn't continue, there is nothing more to do
+
+        return
+
+    def _has_matcher(self):
+        """Helper for .has() that checks for containment of
+        subexpressions within an expr by using sets of args
+        of similar nodes, e.g. x + 1 in x + y + 1 checks
+        to see that {x, 1} & {x, y, 1} == {x, 1}
+        """
+        def _ncsplit(expr):
+            # this is not the same as args_cnc because here
+            # we don't assume expr is a Mul -- hence deal with args --
+            # and always return a set.
+            cpart, ncpart = sift(expr.args,
+                lambda arg: arg.is_commutative is True, binary=True)
+            return set(cpart), ncpart
+
+        c, nc = _ncsplit(self)
+        cls = self.__class__
+
+        def is_in(expr):
+            if isinstance(expr, cls):
+                if expr == self:
+                    return True
+                _c, _nc = _ncsplit(expr)
+                if (c & _c) == c:
+                    if not nc:
+                        return True
+                    elif len(nc) <= len(_nc):
+                        for i in range(len(_nc) - len(nc) + 1):
+                            if _nc[i:i + len(nc)] == nc:
+                                return True
+            return False
+        return is_in
+
+    def _eval_evalf(self, prec):
+        """
+        Evaluate the parts of self that are numbers; if the whole thing
+        was a number with no functions it would have been evaluated, but
+        it wasn't so we must judiciously extract the numbers and reconstruct
+        the object. This is *not* simply replacing numbers with evaluated
+        numbers. Numbers should be handled in the largest pure-number
+        expression as possible. So the code below separates ``self`` into
+        number and non-number parts and evaluates the number parts and
+        walks the args of the non-number part recursively (doing the same
+        thing).
+        """
+        from .add import Add
+        from .mul import Mul
+        from .symbol import Symbol
+        from .function import AppliedUndef
+        if isinstance(self, (Mul, Add)):
+            x, tail = self.as_independent(Symbol, AppliedUndef)
+            # if x is an AssocOp Function then the _evalf below will
+            # call _eval_evalf (here) so we must break the recursion
+            if not (tail is self.identity or
+                    isinstance(x, AssocOp) and x.is_Function or
+                    x is self.identity and isinstance(tail, AssocOp)):
+                # here, we have a number so we just call to _evalf with prec;
+                # prec is not the same as n, it is the binary precision so
+                # that's why we don't call to evalf.
+                x = x._evalf(prec) if x is not self.identity else self.identity
+                args = []
+                tail_args = tuple(self.func.make_args(tail))
+                for a in tail_args:
+                    # here we call to _eval_evalf since we don't know what we
+                    # are dealing with and all other _eval_evalf routines should
+                    # be doing the same thing (i.e. taking binary prec and
+                    # finding the evalf-able args)
+                    newa = a._eval_evalf(prec)
+                    if newa is None:
+                        args.append(a)
+                    else:
+                        args.append(newa)
+                return self.func(x, *args)
+
+        # this is the same as above, but there were no pure-number args to
+        # deal with
+        args = []
+        for a in self.args:
+            newa = a._eval_evalf(prec)
+            if newa is None:
+                args.append(a)
+            else:
+                args.append(newa)
+        return self.func(*args)
+
+    @classmethod
+    def make_args(cls, expr):
+        """
+        Return a sequence of elements `args` such that cls(*args) == expr
+
+        Examples
+        ========
+
+        >>> from sympy import Symbol, Mul, Add
+        >>> x, y = map(Symbol, 'xy')
+
+        >>> Mul.make_args(x*y)
+        (x, y)
+        >>> Add.make_args(x*y)
+        (x*y,)
+        >>> set(Add.make_args(x*y + y)) == set([y, x*y])
+        True
+
+        """
+        if isinstance(expr, cls):
+            return expr.args
+        else:
+            return (sympify(expr),)
+
+    def doit(self, **hints):
+        if hints.get('deep', True):
+            terms = [term.doit(**hints) for term in self.args]
+        else:
+            terms = self.args
+        return self.func(*terms, evaluate=True)
+
+class ShortCircuit(Exception):
+    pass
+
+
+class LatticeOp(AssocOp):
+    """
+    Join/meet operations of an algebraic lattice[1].
+
+    Explanation
+    ===========
+
+    These binary operations are associative (op(op(a, b), c) = op(a, op(b, c))),
+    commutative (op(a, b) = op(b, a)) and idempotent (op(a, a) = op(a) = a).
+    Common examples are AND, OR, Union, Intersection, max or min. They have an
+    identity element (op(identity, a) = a) and an absorbing element
+    conventionally called zero (op(zero, a) = zero).
+
+    This is an abstract base class, concrete derived classes must declare
+    attributes zero and identity. All defining properties are then respected.
+
+    Examples
+    ========
+
+    >>> from sympy import Integer
+    >>> from sympy.core.operations import LatticeOp
+    >>> class my_join(LatticeOp):
+    ...     zero = Integer(0)
+    ...     identity = Integer(1)
+    >>> my_join(2, 3) == my_join(3, 2)
+    True
+    >>> my_join(2, my_join(3, 4)) == my_join(2, 3, 4)
+    True
+    >>> my_join(0, 1, 4, 2, 3, 4)
+    0
+    >>> my_join(1, 2)
+    2
+
+    References
+    ==========
+
+    .. [1] https://en.wikipedia.org/wiki/Lattice_%28order%29
+    """
+
+    is_commutative = True
+
+    def __new__(cls, *args, **options):
+        args = (_sympify_(arg) for arg in args)
+
+        try:
+            # /!\ args is a generator and _new_args_filter
+            # must be careful to handle as such; this
+            # is done so short-circuiting can be done
+            # without having to sympify all values
+            _args = frozenset(cls._new_args_filter(args))
+        except ShortCircuit:
+            return sympify(cls.zero)
+        if not _args:
+            return sympify(cls.identity)
+        elif len(_args) == 1:
+            return set(_args).pop()
+        else:
+            # XXX in almost every other case for __new__, *_args is
+            # passed along, but the expectation here is for _args
+            obj = super(AssocOp, cls).__new__(cls, *ordered(_args))
+            obj._argset = _args
+            return obj
+
+    @classmethod
+    def _new_args_filter(cls, arg_sequence, call_cls=None):
+        """Generator filtering args"""
+        ncls = call_cls or cls
+        for arg in arg_sequence:
+            if arg == ncls.zero:
+                raise ShortCircuit(arg)
+            elif arg == ncls.identity:
+                continue
+            elif arg.func == ncls:
+                yield from arg.args
+            else:
+                yield arg
+
+    @classmethod
+    def make_args(cls, expr):
+        """
+        Return a set of args such that cls(*arg_set) == expr.
+        """
+        if isinstance(expr, cls):
+            return expr._argset
+        else:
+            return frozenset([sympify(expr)])
+
+    @staticmethod
+    def _compare_pretty(a, b):
+        return (str(a) > str(b)) - (str(a) < str(b))
+
+
+class AssocOpDispatcher:
+    """
+    Handler dispatcher for associative operators
+
+    .. notes::
+       This approach is experimental, and can be replaced or deleted in the future.
+       See https://github.com/sympy/sympy/pull/19463.
+
+    Explanation
+    ===========
+
+    If arguments of different types are passed, the classes which handle the operation for each type
+    are collected. Then, a class which performs the operation is selected by recursive binary dispatching.
+    Dispatching relation can be registered by ``register_handlerclass`` method.
+
+    Priority registration is unordered. You cannot make ``A*B`` and ``B*A`` refer to
+    different handler classes. All logic dealing with the order of arguments must be implemented
+    in the handler class.
+
+    Examples
+    ========
+
+    >>> from sympy import Add, Expr, Symbol
+    >>> from sympy.core.add import add
+
+    >>> class NewExpr(Expr):
+    ...     @property
+    ...     def _add_handler(self):
+    ...         return NewAdd
+    >>> class NewAdd(NewExpr, Add):
+    ...     pass
+    >>> add.register_handlerclass((Add, NewAdd), NewAdd)
+
+    >>> a, b = Symbol('a'), NewExpr()
+    >>> add(a, b) == NewAdd(a, b)
+    True
+
+    """
+    def __init__(self, name, doc=None):
+        self.name = name
+        self.doc = doc
+        self.handlerattr = "_%s_handler" % name
+        self._handlergetter = attrgetter(self.handlerattr)
+        self._dispatcher = Dispatcher(name)
+
+    def __repr__(self):
+        return "<dispatched %s>" % self.name
+
+    def register_handlerclass(self, classes, typ, on_ambiguity=ambiguity_register_error_ignore_dup):
+        """
+        Register the handler class for two classes, in both straight and reversed order.
+
+        Paramteters
+        ===========
+
+        classes : tuple of two types
+            Classes who are compared with each other.
+
+        typ:
+            Class which is registered to represent *cls1* and *cls2*.
+            Handler method of *self* must be implemented in this class.
+        """
+        if not len(classes) == 2:
+            raise RuntimeError(
+                "Only binary dispatch is supported, but got %s types: <%s>." % (
+                len(classes), str_signature(classes)
+            ))
+        if len(set(classes)) == 1:
+            raise RuntimeError(
+                "Duplicate types <%s> cannot be dispatched." % str_signature(classes)
+            )
+        self._dispatcher.add(tuple(classes), typ, on_ambiguity=on_ambiguity)
+        self._dispatcher.add(tuple(reversed(classes)), typ, on_ambiguity=on_ambiguity)
+
+    @cacheit
+    def __call__(self, *args, _sympify=True, **kwargs):
+        """
+        Parameters
+        ==========
+
+        *args :
+            Arguments which are operated
+        """
+        if _sympify:
+            args = tuple(map(_sympify_, args))
+        handlers = frozenset(map(self._handlergetter, args))
+
+        # no need to sympify again
+        return self.dispatch(handlers)(*args, _sympify=False, **kwargs)
+
+    @cacheit
+    def dispatch(self, handlers):
+        """
+        Select the handler class, and return its handler method.
+        """
+
+        # Quick exit for the case where all handlers are same
+        if len(handlers) == 1:
+            h, = handlers
+            if not isinstance(h, type):
+                raise RuntimeError("Handler {!r} is not a type.".format(h))
+            return h
+
+        # Recursively select with registered binary priority
+        for i, typ in enumerate(handlers):
+
+            if not isinstance(typ, type):
+                raise RuntimeError("Handler {!r} is not a type.".format(typ))
+
+            if i == 0:
+                handler = typ
+            else:
+                prev_handler = handler
+                handler = self._dispatcher.dispatch(prev_handler, typ)
+
+                if not isinstance(handler, type):
+                    raise RuntimeError(
+                        "Dispatcher for {!r} and {!r} must return a type, but got {!r}".format(
+                        prev_handler, typ, handler
+                    ))
+
+        # return handler class
+        return handler
+
+    @property
+    def __doc__(self):
+        docs = [
+            "Multiply dispatched associative operator: %s" % self.name,
+            "Note that support for this is experimental, see the docs for :class:`AssocOpDispatcher` for details"
+        ]
+
+        if self.doc:
+            docs.append(self.doc)
+
+        s = "Registered handler classes\n"
+        s += '=' * len(s)
+        docs.append(s)
+
+        amb_sigs = []
+
+        typ_sigs = defaultdict(list)
+        for sigs in self._dispatcher.ordering[::-1]:
+            key = self._dispatcher.funcs[sigs]
+            typ_sigs[key].append(sigs)
+
+        for typ, sigs in typ_sigs.items():
+
+            sigs_str = ', '.join('<%s>' % str_signature(sig) for sig in sigs)
+
+            if isinstance(typ, RaiseNotImplementedError):
+                amb_sigs.append(sigs_str)
+                continue
+
+            s = 'Inputs: %s\n' % sigs_str
+            s += '-' * len(s) + '\n'
+            s += typ.__name__
+            docs.append(s)
+
+        if amb_sigs:
+            s = "Ambiguous handler classes\n"
+            s += '=' * len(s)
+            docs.append(s)
+
+            s = '\n'.join(amb_sigs)
+            docs.append(s)
+
+        return '\n\n'.join(docs)

env-llmeval/lib/python3.10/site-packages/sympy/core/parameters.py

@@ -0,0 +1,161 @@
+"""Thread-safe global parameters"""
+
+from .cache import clear_cache
+from contextlib import contextmanager
+from threading import local
+
+class _global_parameters(local):
+    """
+    Thread-local global parameters.
+
+    Explanation
+    ===========
+
+    This class generates thread-local container for SymPy's global parameters.
+    Every global parameters must be passed as keyword argument when generating
+    its instance.
+    A variable, `global_parameters` is provided as default instance for this class.
+
+    WARNING! Although the global parameters are thread-local, SymPy's cache is not
+    by now.
+    This may lead to undesired result in multi-threading operations.
+
+    Examples
+    ========
+
+    >>> from sympy.abc import x
+    >>> from sympy.core.cache import clear_cache
+    >>> from sympy.core.parameters import global_parameters as gp
+
+    >>> gp.evaluate
+    True
+    >>> x+x
+    2*x
+
+    >>> log = []
+    >>> def f():
+    ...     clear_cache()
+    ...     gp.evaluate = False
+    ...     log.append(x+x)
+    ...     clear_cache()
+    >>> import threading
+    >>> thread = threading.Thread(target=f)
+    >>> thread.start()
+    >>> thread.join()
+
+    >>> print(log)
+    [x + x]
+
+    >>> gp.evaluate
+    True
+    >>> x+x
+    2*x
+
+    References
+    ==========
+
+    .. [1] https://docs.python.org/3/library/threading.html
+
+    """
+    def __init__(self, **kwargs):
+        self.__dict__.update(kwargs)
+
+    def __setattr__(self, name, value):
+        if getattr(self, name) != value:
+            clear_cache()
+        return super().__setattr__(name, value)
+
+global_parameters = _global_parameters(evaluate=True, distribute=True, exp_is_pow=False)
+
+@contextmanager
+def evaluate(x):
+    """ Control automatic evaluation
+
+    Explanation
+    ===========
+
+    This context manager controls whether or not all SymPy functions evaluate
+    by default.
+
+    Note that much of SymPy expects evaluated expressions.  This functionality
+    is experimental and is unlikely to function as intended on large
+    expressions.
+
+    Examples
+    ========
+
+    >>> from sympy import evaluate
+    >>> from sympy.abc import x
+    >>> print(x + x)
+    2*x
+    >>> with evaluate(False):
+    ...     print(x + x)
+    x + x
+    """
+
+    old = global_parameters.evaluate
+
+    try:
+        global_parameters.evaluate = x
+        yield
+    finally:
+        global_parameters.evaluate = old
+
+
+@contextmanager
+def distribute(x):
+    """ Control automatic distribution of Number over Add
+
+    Explanation
+    ===========
+
+    This context manager controls whether or not Mul distribute Number over
+    Add. Plan is to avoid distributing Number over Add in all of sympy. Once
+    that is done, this contextmanager will be removed.
+
+    Examples
+    ========
+
+    >>> from sympy.abc import x
+    >>> from sympy.core.parameters import distribute
+    >>> print(2*(x + 1))
+    2*x + 2
+    >>> with distribute(False):
+    ...     print(2*(x + 1))
+    2*(x + 1)
+    """
+
+    old = global_parameters.distribute
+
+    try:
+        global_parameters.distribute = x
+        yield
+    finally:
+        global_parameters.distribute = old
+
+
+@contextmanager
+def _exp_is_pow(x):
+    """
+    Control whether `e^x` should be represented as ``exp(x)`` or a ``Pow(E, x)``.
+
+    Examples
+    ========
+
+    >>> from sympy import exp
+    >>> from sympy.abc import x
+    >>> from sympy.core.parameters import _exp_is_pow
+    >>> with _exp_is_pow(True): print(type(exp(x)))
+    <class 'sympy.core.power.Pow'>
+    >>> with _exp_is_pow(False): print(type(exp(x)))
+    exp
+    """
+    old = global_parameters.exp_is_pow
+
+    clear_cache()
+    try:
+        global_parameters.exp_is_pow = x
+        yield
+    finally:
+        clear_cache()
+        global_parameters.exp_is_pow = old

env-llmeval/lib/python3.10/site-packages/sympy/core/random.py

@@ -0,0 +1,227 @@
+"""
+When you need to use random numbers in SymPy library code, import from here
+so there is only one generator working for SymPy. Imports from here should
+behave the same as if they were being imported from Python's random module.
+But only the routines currently used in SymPy are included here. To use others
+import ``rng`` and access the method directly. For example, to capture the
+current state of the generator use ``rng.getstate()``.
+
+There is intentionally no Random to import from here. If you want
+to control the state of the generator, import ``seed`` and call it
+with or without an argument to set the state.
+
+Examples
+========
+
+>>> from sympy.core.random import random, seed
+>>> assert random() < 1
+>>> seed(1); a = random()
+>>> b = random()
+>>> seed(1); c = random()
+>>> assert a == c
+>>> assert a != b  # remote possibility this will fail
+
+"""
+from sympy.utilities.iterables import is_sequence
+from sympy.utilities.misc import as_int
+
+import random as _random
+rng = _random.Random()
+
+choice = rng.choice
+random = rng.random
+randint = rng.randint
+randrange = rng.randrange
+sample = rng.sample
+# seed = rng.seed
+shuffle = rng.shuffle
+uniform = rng.uniform
+
+_assumptions_rng = _random.Random()
+_assumptions_shuffle = _assumptions_rng.shuffle
+
+
+def seed(a=None, version=2):
+    rng.seed(a=a, version=version)
+    _assumptions_rng.seed(a=a, version=version)
+
+
+def random_complex_number(a=2, b=-1, c=3, d=1, rational=False, tolerance=None):
+    """
+    Return a random complex number.
+
+    To reduce chance of hitting branch cuts or anything, we guarantee
+    b <= Im z <= d, a <= Re z <= c
+
+    When rational is True, a rational approximation to a random number
+    is obtained within specified tolerance, if any.
+    """
+    from sympy.core.numbers import I
+    from sympy.simplify.simplify import nsimplify
+    A, B = uniform(a, c), uniform(b, d)
+    if not rational:
+        return A + I*B
+    return (nsimplify(A, rational=True, tolerance=tolerance) +
+        I*nsimplify(B, rational=True, tolerance=tolerance))
+
+
+def verify_numerically(f, g, z=None, tol=1.0e-6, a=2, b=-1, c=3, d=1):
+    """
+    Test numerically that f and g agree when evaluated in the argument z.
+
+    If z is None, all symbols will be tested. This routine does not test
+    whether there are Floats present with precision higher than 15 digits
+    so if there are, your results may not be what you expect due to round-
+    off errors.
+
+    Examples
+    ========
+
+    >>> from sympy import sin, cos
+    >>> from sympy.abc import x
+    >>> from sympy.core.random import verify_numerically as tn
+    >>> tn(sin(x)**2 + cos(x)**2, 1, x)
+    True
+    """
+    from sympy.core.symbol import Symbol
+    from sympy.core.sympify import sympify
+    from sympy.core.numbers import comp
+    f, g = (sympify(i) for i in (f, g))
+    if z is None:
+        z = f.free_symbols | g.free_symbols
+    elif isinstance(z, Symbol):
+        z = [z]
+    reps = list(zip(z, [random_complex_number(a, b, c, d) for _ in z]))
+    z1 = f.subs(reps).n()
+    z2 = g.subs(reps).n()
+    return comp(z1, z2, tol)
+
+
+def test_derivative_numerically(f, z, tol=1.0e-6, a=2, b=-1, c=3, d=1):
+    """
+    Test numerically that the symbolically computed derivative of f
+    with respect to z is correct.
+
+    This routine does not test whether there are Floats present with
+    precision higher than 15 digits so if there are, your results may
+    not be what you expect due to round-off errors.
+
+    Examples
+    ========
+
+    >>> from sympy import sin
+    >>> from sympy.abc import x
+    >>> from sympy.core.random import test_derivative_numerically as td
+    >>> td(sin(x), x)
+    True
+    """
+    from sympy.core.numbers import comp
+    from sympy.core.function import Derivative
+    z0 = random_complex_number(a, b, c, d)
+    f1 = f.diff(z).subs(z, z0)
+    f2 = Derivative(f, z).doit_numerically(z0)
+    return comp(f1.n(), f2.n(), tol)
+
+
+def _randrange(seed=None):
+    """Return a randrange generator.
+
+    ``seed`` can be
+
+    * None - return randomly seeded generator
+    * int - return a generator seeded with the int
+    * list - the values to be returned will be taken from the list
+      in the order given; the provided list is not modified.
+
+    Examples
+    ========
+
+    >>> from sympy.core.random import _randrange
+    >>> rr = _randrange()
+    >>> rr(1000) # doctest: +SKIP
+    999
+    >>> rr = _randrange(3)
+    >>> rr(1000) # doctest: +SKIP
+    238
+    >>> rr = _randrange([0, 5, 1, 3, 4])
+    >>> rr(3), rr(3)
+    (0, 1)
+    """
+    if seed is None:
+        return randrange
+    elif isinstance(seed, int):
+        rng.seed(seed)
+        return randrange
+    elif is_sequence(seed):
+        seed = list(seed)  # make a copy
+        seed.reverse()
+
+        def give(a, b=None, seq=seed):
+            if b is None:
+                a, b = 0, a
+            a, b = as_int(a), as_int(b)
+            w = b - a
+            if w < 1:
+                raise ValueError('_randrange got empty range')
+            try:
+                x = seq.pop()
+            except IndexError:
+                raise ValueError('_randrange sequence was too short')
+            if a <= x < b:
+                return x
+            else:
+                return give(a, b, seq)
+        return give
+    else:
+        raise ValueError('_randrange got an unexpected seed')
+
+
+def _randint(seed=None):
+    """Return a randint generator.
+
+    ``seed`` can be
+
+    * None - return randomly seeded generator
+    * int - return a generator seeded with the int
+    * list - the values to be returned will be taken from the list
+      in the order given; the provided list is not modified.
+
+    Examples
+    ========
+
+    >>> from sympy.core.random import _randint
+    >>> ri = _randint()
+    >>> ri(1, 1000) # doctest: +SKIP
+    999
+    >>> ri = _randint(3)
+    >>> ri(1, 1000) # doctest: +SKIP
+    238
+    >>> ri = _randint([0, 5, 1, 2, 4])
+    >>> ri(1, 3), ri(1, 3)
+    (1, 2)
+    """
+    if seed is None:
+        return randint
+    elif isinstance(seed, int):
+        rng.seed(seed)
+        return randint
+    elif is_sequence(seed):
+        seed = list(seed)  # make a copy
+        seed.reverse()
+
+        def give(a, b, seq=seed):
+            a, b = as_int(a), as_int(b)
+            w = b - a
+            if w < 0:
+                raise ValueError('_randint got empty range')
+            try:
+                x = seq.pop()
+            except IndexError:
+                raise ValueError('_randint sequence was too short')
+            if a <= x <= b:
+                return x
+            else:
+                return give(a, b, seq)
+        return give
+    else:
+        raise ValueError('_randint got an unexpected seed')

env-llmeval/lib/python3.10/site-packages/sympy/core/relational.py

@@ -0,0 +1,1587 @@
+from __future__ import annotations
+
+from .basic import Atom, Basic
+from .sorting import ordered
+from .evalf import EvalfMixin
+from .function import AppliedUndef
+from .singleton import S
+from .sympify import _sympify, SympifyError
+from .parameters import global_parameters
+from .logic import fuzzy_bool, fuzzy_xor, fuzzy_and, fuzzy_not
+from sympy.logic.boolalg import Boolean, BooleanAtom
+from sympy.utilities.iterables import sift
+from sympy.utilities.misc import filldedent
+
+__all__ = (
+    'Rel', 'Eq', 'Ne', 'Lt', 'Le', 'Gt', 'Ge',
+    'Relational', 'Equality', 'Unequality', 'StrictLessThan', 'LessThan',
+    'StrictGreaterThan', 'GreaterThan',
+)
+
+from .expr import Expr
+from sympy.multipledispatch import dispatch
+from .containers import Tuple
+from .symbol import Symbol
+
+
+def _nontrivBool(side):
+    return isinstance(side, Boolean) and \
+           not isinstance(side, Atom)
+
+
+# Note, see issue 4986.  Ideally, we wouldn't want to subclass both Boolean
+# and Expr.
+# from .. import Expr
+
+
+def _canonical(cond):
+    # return a condition in which all relationals are canonical
+    reps = {r: r.canonical for r in cond.atoms(Relational)}
+    return cond.xreplace(reps)
+    # XXX: AttributeError was being caught here but it wasn't triggered by any of
+    # the tests so I've removed it...
+
+
+def _canonical_coeff(rel):
+    # return -2*x + 1 < 0 as x > 1/2
+    # XXX make this part of Relational.canonical?
+    rel = rel.canonical
+    if not rel.is_Relational or rel.rhs.is_Boolean:
+        return rel  # Eq(x, True)
+    b, l = rel.lhs.as_coeff_Add(rational=True)
+    m, lhs = l.as_coeff_Mul(rational=True)
+    rhs = (rel.rhs - b)/m
+    if m < 0:
+        return rel.reversed.func(lhs, rhs)
+    return rel.func(lhs, rhs)
+
+
+class Relational(Boolean, EvalfMixin):
+    """Base class for all relation types.
+
+    Explanation
+    ===========
+
+    Subclasses of Relational should generally be instantiated directly, but
+    Relational can be instantiated with a valid ``rop`` value to dispatch to
+    the appropriate subclass.
+
+    Parameters
+    ==========
+
+    rop : str or None
+        Indicates what subclass to instantiate.  Valid values can be found
+        in the keys of Relational.ValidRelationOperator.
+
+    Examples
+    ========
+
+    >>> from sympy import Rel
+    >>> from sympy.abc import x, y
+    >>> Rel(y, x + x**2, '==')
+    Eq(y, x**2 + x)
+
+    A relation's type can be defined upon creation using ``rop``.
+    The relation type of an existing expression can be obtained
+    using its ``rel_op`` property.
+    Here is a table of all the relation types, along with their
+    ``rop`` and ``rel_op`` values:
+
+    +---------------------+----------------------------+------------+
+    |Relation             |``rop``                     |``rel_op``  |
+    +=====================+============================+============+
+    |``Equality``         |``==`` or ``eq`` or ``None``|``==``      |
+    +---------------------+----------------------------+------------+
+    |``Unequality``       |``!=`` or ``ne``            |``!=``      |
+    +---------------------+----------------------------+------------+
+    |``GreaterThan``      |``>=`` or ``ge``            |``>=``      |
+    +---------------------+----------------------------+------------+
+    |``LessThan``         |``<=`` or ``le``            |``<=``      |
+    +---------------------+----------------------------+------------+
+    |``StrictGreaterThan``|``>`` or ``gt``             |``>``       |
+    +---------------------+----------------------------+------------+
+    |``StrictLessThan``   |``<`` or ``lt``             |``<``       |
+    +---------------------+----------------------------+------------+
+
+    For example, setting ``rop`` to ``==`` produces an
+    ``Equality`` relation, ``Eq()``.
+    So does setting ``rop`` to ``eq``, or leaving ``rop`` unspecified.
+    That is, the first three ``Rel()`` below all produce the same result.
+    Using a ``rop`` from a different row in the table produces a
+    different relation type.
+    For example, the fourth ``Rel()`` below using ``lt`` for ``rop``
+    produces a ``StrictLessThan`` inequality:
+
+    >>> from sympy import Rel
+    >>> from sympy.abc import x, y
+    >>> Rel(y, x + x**2, '==')
+        Eq(y, x**2 + x)
+    >>> Rel(y, x + x**2, 'eq')
+        Eq(y, x**2 + x)
+    >>> Rel(y, x + x**2)
+        Eq(y, x**2 + x)
+    >>> Rel(y, x + x**2, 'lt')
+        y < x**2 + x
+
+    To obtain the relation type of an existing expression,
+    get its ``rel_op`` property.
+    For example, ``rel_op`` is ``==`` for the ``Equality`` relation above,
+    and ``<`` for the strict less than inequality above:
+
+    >>> from sympy import Rel
+    >>> from sympy.abc import x, y
+    >>> my_equality = Rel(y, x + x**2, '==')
+    >>> my_equality.rel_op
+        '=='
+    >>> my_inequality = Rel(y, x + x**2, 'lt')
+    >>> my_inequality.rel_op
+        '<'
+
+    """
+    __slots__ = ()
+
+    ValidRelationOperator: dict[str | None, type[Relational]] = {}
+
+    is_Relational = True
+
+    # ValidRelationOperator - Defined below, because the necessary classes
+    #   have not yet been defined
+
+    def __new__(cls, lhs, rhs, rop=None, **assumptions):
+        # If called by a subclass, do nothing special and pass on to Basic.
+        if cls is not Relational:
+            return Basic.__new__(cls, lhs, rhs, **assumptions)
+
+        # XXX: Why do this? There should be a separate function to make a
+        # particular subclass of Relational from a string.
+        #
+        # If called directly with an operator, look up the subclass
+        # corresponding to that operator and delegate to it
+        cls = cls.ValidRelationOperator.get(rop, None)
+        if cls is None:
+            raise ValueError("Invalid relational operator symbol: %r" % rop)
+
+        if not issubclass(cls, (Eq, Ne)):
+            # validate that Booleans are not being used in a relational
+            # other than Eq/Ne;
+            # Note: Symbol is a subclass of Boolean but is considered
+            # acceptable here.
+            if any(map(_nontrivBool, (lhs, rhs))):
+                raise TypeError(filldedent('''
+                    A Boolean argument can only be used in
+                    Eq and Ne; all other relationals expect
+                    real expressions.
+                '''))
+
+        return cls(lhs, rhs, **assumptions)
+
+    @property
+    def lhs(self):
+        """The left-hand side of the relation."""
+        return self._args[0]
+
+    @property
+    def rhs(self):
+        """The right-hand side of the relation."""
+        return self._args[1]
+
+    @property
+    def reversed(self):
+        """Return the relationship with sides reversed.
+
+        Examples
+        ========
+
+        >>> from sympy import Eq
+        >>> from sympy.abc import x
+        >>> Eq(x, 1)
+        Eq(x, 1)
+        >>> _.reversed
+        Eq(1, x)
+        >>> x < 1
+        x < 1
+        >>> _.reversed
+        1 > x
+        """
+        ops = {Eq: Eq, Gt: Lt, Ge: Le, Lt: Gt, Le: Ge, Ne: Ne}
+        a, b = self.args
+        return Relational.__new__(ops.get(self.func, self.func), b, a)
+
+    @property
+    def reversedsign(self):
+        """Return the relationship with signs reversed.
+
+        Examples
+        ========
+
+        >>> from sympy import Eq
+        >>> from sympy.abc import x
+        >>> Eq(x, 1)
+        Eq(x, 1)
+        >>> _.reversedsign
+        Eq(-x, -1)
+        >>> x < 1
+        x < 1
+        >>> _.reversedsign
+        -x > -1
+        """
+        a, b = self.args
+        if not (isinstance(a, BooleanAtom) or isinstance(b, BooleanAtom)):
+            ops = {Eq: Eq, Gt: Lt, Ge: Le, Lt: Gt, Le: Ge, Ne: Ne}
+            return Relational.__new__(ops.get(self.func, self.func), -a, -b)
+        else:
+            return self
+
+    @property
+    def negated(self):
+        """Return the negated relationship.
+
+        Examples
+        ========
+
+        >>> from sympy import Eq
+        >>> from sympy.abc import x
+        >>> Eq(x, 1)
+        Eq(x, 1)
+        >>> _.negated
+        Ne(x, 1)
+        >>> x < 1
+        x < 1
+        >>> _.negated
+        x >= 1
+
+        Notes
+        =====
+
+        This works more or less identical to ``~``/``Not``. The difference is
+        that ``negated`` returns the relationship even if ``evaluate=False``.
+        Hence, this is useful in code when checking for e.g. negated relations
+        to existing ones as it will not be affected by the `evaluate` flag.
+
+        """
+        ops = {Eq: Ne, Ge: Lt, Gt: Le, Le: Gt, Lt: Ge, Ne: Eq}
+        # If there ever will be new Relational subclasses, the following line
+        # will work until it is properly sorted out
+        # return ops.get(self.func, lambda a, b, evaluate=False: ~(self.func(a,
+        #      b, evaluate=evaluate)))(*self.args, evaluate=False)
+        return Relational.__new__(ops.get(self.func), *self.args)
+
+    @property
+    def weak(self):
+        """return the non-strict version of the inequality or self
+
+        EXAMPLES
+        ========
+
+        >>> from sympy.abc import x
+        >>> (x < 1).weak
+        x <= 1
+        >>> _.weak
+        x <= 1
+        """
+        return self
+
+    @property
+    def strict(self):
+        """return the strict version of the inequality or self
+
+        EXAMPLES
+        ========
+
+        >>> from sympy.abc import x
+        >>> (x <= 1).strict
+        x < 1
+        >>> _.strict
+        x < 1
+        """
+        return self
+
+    def _eval_evalf(self, prec):
+        return self.func(*[s._evalf(prec) for s in self.args])
+
+    @property
+    def canonical(self):
+        """Return a canonical form of the relational by putting a
+        number on the rhs, canonically removing a sign or else
+        ordering the args canonically. No other simplification is
+        attempted.
+
+        Examples
+        ========
+
+        >>> from sympy.abc import x, y
+        >>> x < 2
+        x < 2
+        >>> _.reversed.canonical
+        x < 2
+        >>> (-y < x).canonical
+        x > -y
+        >>> (-y > x).canonical
+        x < -y
+        >>> (-y < -x).canonical
+        x < y
+
+        The canonicalization is recursively applied:
+
+        >>> from sympy import Eq
+        >>> Eq(x < y, y > x).canonical
+        True
+        """
+        args = tuple([i.canonical if isinstance(i, Relational) else i for i in self.args])
+        if args != self.args:
+            r = self.func(*args)
+            if not isinstance(r, Relational):
+                return r
+        else:
+            r = self
+        if r.rhs.is_number:
+            if r.rhs.is_Number and r.lhs.is_Number and r.lhs > r.rhs:
+                r = r.reversed
+        elif r.lhs.is_number:
+            r = r.reversed
+        elif tuple(ordered(args)) != args:
+            r = r.reversed
+
+        LHS_CEMS = getattr(r.lhs, 'could_extract_minus_sign', None)
+        RHS_CEMS = getattr(r.rhs, 'could_extract_minus_sign', None)
+
+        if isinstance(r.lhs, BooleanAtom) or isinstance(r.rhs, BooleanAtom):
+            return r
+
+        # Check if first value has negative sign
+        if LHS_CEMS and LHS_CEMS():
+            return r.reversedsign
+        elif not r.rhs.is_number and RHS_CEMS and RHS_CEMS():
+            # Right hand side has a minus, but not lhs.
+            # How does the expression with reversed signs behave?
+            # This is so that expressions of the type
+            # Eq(x, -y) and Eq(-x, y)
+            # have the same canonical representation
+            expr1, _ = ordered([r.lhs, -r.rhs])
+            if expr1 != r.lhs:
+                return r.reversed.reversedsign
+
+        return r
+
+    def equals(self, other, failing_expression=False):
+        """Return True if the sides of the relationship are mathematically
+        identical and the type of relationship is the same.
+        If failing_expression is True, return the expression whose truth value
+        was unknown."""
+        if isinstance(other, Relational):
+            if other in (self, self.reversed):
+                return True
+            a, b = self, other
+            if a.func in (Eq, Ne) or b.func in (Eq, Ne):
+                if a.func != b.func:
+                    return False
+                left, right = [i.equals(j,
+                                        failing_expression=failing_expression)
+                               for i, j in zip(a.args, b.args)]
+                if left is True:
+                    return right
+                if right is True:
+                    return left
+                lr, rl = [i.equals(j, failing_expression=failing_expression)
+                          for i, j in zip(a.args, b.reversed.args)]
+                if lr is True:
+                    return rl
+                if rl is True:
+                    return lr
+                e = (left, right, lr, rl)
+                if all(i is False for i in e):
+                    return False
+                for i in e:
+                    if i not in (True, False):
+                        return i
+            else:
+                if b.func != a.func:
+                    b = b.reversed
+                if a.func != b.func:
+                    return False
+                left = a.lhs.equals(b.lhs,
+                                    failing_expression=failing_expression)
+                if left is False:
+                    return False
+                right = a.rhs.equals(b.rhs,
+                                     failing_expression=failing_expression)
+                if right is False:
+                    return False
+                if left is True:
+                    return right
+                return left
+
+    def _eval_simplify(self, **kwargs):
+        from .add import Add
+        from .expr import Expr
+        r = self
+        r = r.func(*[i.simplify(**kwargs) for i in r.args])
+        if r.is_Relational:
+            if not isinstance(r.lhs, Expr) or not isinstance(r.rhs, Expr):
+                return r
+            dif = r.lhs - r.rhs
+            # replace dif with a valid Number that will
+            # allow a definitive comparison with 0
+            v = None
+            if dif.is_comparable:
+                v = dif.n(2)
+            elif dif.equals(0):  # XXX this is expensive
+                v = S.Zero
+            if v is not None:
+                r = r.func._eval_relation(v, S.Zero)
+            r = r.canonical
+            # If there is only one symbol in the expression,
+            # try to write it on a simplified form
+            free = list(filter(lambda x: x.is_real is not False, r.free_symbols))
+            if len(free) == 1:
+                try:
+                    from sympy.solvers.solveset import linear_coeffs
+                    x = free.pop()
+                    dif = r.lhs - r.rhs
+                    m, b = linear_coeffs(dif, x)
+                    if m.is_zero is False:
+                        if m.is_negative:
+                            # Dividing with a negative number, so change order of arguments
+                            # canonical will put the symbol back on the lhs later
+                            r = r.func(-b / m, x)
+                        else:
+                            r = r.func(x, -b / m)
+                    else:
+                        r = r.func(b, S.Zero)
+                except ValueError:
+                    # maybe not a linear function, try polynomial
+                    from sympy.polys.polyerrors import PolynomialError
+                    from sympy.polys.polytools import gcd, Poly, poly
+                    try:
+                        p = poly(dif, x)
+                        c = p.all_coeffs()
+                        constant = c[-1]
+                        c[-1] = 0
+                        scale = gcd(c)
+                        c = [ctmp / scale for ctmp in c]
+                        r = r.func(Poly.from_list(c, x).as_expr(), -constant / scale)
+                    except PolynomialError:
+                        pass
+            elif len(free) >= 2:
+                try:
+                    from sympy.solvers.solveset import linear_coeffs
+                    from sympy.polys.polytools import gcd
+                    free = list(ordered(free))
+                    dif = r.lhs - r.rhs
+                    m = linear_coeffs(dif, *free)
+                    constant = m[-1]
+                    del m[-1]
+                    scale = gcd(m)
+                    m = [mtmp / scale for mtmp in m]
+                    nzm = list(filter(lambda f: f[0] != 0, list(zip(m, free))))
+                    if scale.is_zero is False:
+                        if constant != 0:
+                            # lhs: expression, rhs: constant
+                            newexpr = Add(*[i * j for i, j in nzm])
+                            r = r.func(newexpr, -constant / scale)
+                        else:
+                            # keep first term on lhs
+                            lhsterm = nzm[0][0] * nzm[0][1]
+                            del nzm[0]
+                            newexpr = Add(*[i * j for i, j in nzm])
+                            r = r.func(lhsterm, -newexpr)
+
+                    else:
+                        r = r.func(constant, S.Zero)
+                except ValueError:
+                    pass
+        # Did we get a simplified result?
+        r = r.canonical
+        measure = kwargs['measure']
+        if measure(r) < kwargs['ratio'] * measure(self):
+            return r
+        else:
+            return self
+
+    def _eval_trigsimp(self, **opts):
+        from sympy.simplify.trigsimp import trigsimp
+        return self.func(trigsimp(self.lhs, **opts), trigsimp(self.rhs, **opts))
+
+    def expand(self, **kwargs):
+        args = (arg.expand(**kwargs) for arg in self.args)
+        return self.func(*args)
+
+    def __bool__(self):
+        raise TypeError("cannot determine truth value of Relational")
+
+    def _eval_as_set(self):
+        # self is univariate and periodicity(self, x) in (0, None)
+        from sympy.solvers.inequalities import solve_univariate_inequality
+        from sympy.sets.conditionset import ConditionSet
+        syms = self.free_symbols
+        assert len(syms) == 1
+        x = syms.pop()
+        try:
+            xset = solve_univariate_inequality(self, x, relational=False)
+        except NotImplementedError:
+            # solve_univariate_inequality raises NotImplementedError for
+            # unsolvable equations/inequalities.
+            xset = ConditionSet(x, self, S.Reals)
+        return xset
+
+    @property
+    def binary_symbols(self):
+        # override where necessary
+        return set()
+
+
+Rel = Relational
+
+
+class Equality(Relational):
+    """
+    An equal relation between two objects.
+
+    Explanation
+    ===========
+
+    Represents that two objects are equal.  If they can be easily shown
+    to be definitively equal (or unequal), this will reduce to True (or
+    False).  Otherwise, the relation is maintained as an unevaluated
+    Equality object.  Use the ``simplify`` function on this object for
+    more nontrivial evaluation of the equality relation.
+
+    As usual, the keyword argument ``evaluate=False`` can be used to
+    prevent any evaluation.
+
+    Examples
+    ========
+
+    >>> from sympy import Eq, simplify, exp, cos
+    >>> from sympy.abc import x, y
+    >>> Eq(y, x + x**2)
+    Eq(y, x**2 + x)
+    >>> Eq(2, 5)
+    False
+    >>> Eq(2, 5, evaluate=False)
+    Eq(2, 5)
+    >>> _.doit()
+    False
+    >>> Eq(exp(x), exp(x).rewrite(cos))
+    Eq(exp(x), sinh(x) + cosh(x))
+    >>> simplify(_)
+    True
+
+    See Also
+    ========
+
+    sympy.logic.boolalg.Equivalent : for representing equality between two
+        boolean expressions
+
+    Notes
+    =====
+
+    Python treats 1 and True (and 0 and False) as being equal; SymPy
+    does not. And integer will always compare as unequal to a Boolean:
+
+    >>> Eq(True, 1), True == 1
+    (False, True)
+
+    This class is not the same as the == operator.  The == operator tests
+    for exact structural equality between two expressions; this class
+    compares expressions mathematically.
+
+    If either object defines an ``_eval_Eq`` method, it can be used in place of
+    the default algorithm.  If ``lhs._eval_Eq(rhs)`` or ``rhs._eval_Eq(lhs)``
+    returns anything other than None, that return value will be substituted for
+    the Equality.  If None is returned by ``_eval_Eq``, an Equality object will
+    be created as usual.
+
+    Since this object is already an expression, it does not respond to
+    the method ``as_expr`` if one tries to create `x - y` from ``Eq(x, y)``.
+    This can be done with the ``rewrite(Add)`` method.
+
+    .. deprecated:: 1.5
+
+       ``Eq(expr)`` with a single argument is a shorthand for ``Eq(expr, 0)``,
+       but this behavior is deprecated and will be removed in a future version
+       of SymPy.
+
+    """
+    rel_op = '=='
+
+    __slots__ = ()
+
+    is_Equality = True
+
+    def __new__(cls, lhs, rhs, **options):
+        evaluate = options.pop('evaluate', global_parameters.evaluate)
+        lhs = _sympify(lhs)
+        rhs = _sympify(rhs)
+        if evaluate:
+            val = is_eq(lhs, rhs)
+            if val is None:
+                return cls(lhs, rhs, evaluate=False)
+            else:
+                return _sympify(val)
+
+        return Relational.__new__(cls, lhs, rhs)
+
+    @classmethod
+    def _eval_relation(cls, lhs, rhs):
+        return _sympify(lhs == rhs)
+
+    def _eval_rewrite_as_Add(self, *args, **kwargs):
+        """
+        return Eq(L, R) as L - R. To control the evaluation of
+        the result set pass `evaluate=True` to give L - R;
+        if `evaluate=None` then terms in L and R will not cancel
+        but they will be listed in canonical order; otherwise
+        non-canonical args will be returned. If one side is 0, the
+        non-zero side will be returned.
+
+        Examples
+        ========
+
+        >>> from sympy import Eq, Add
+        >>> from sympy.abc import b, x
+        >>> eq = Eq(x + b, x - b)
+        >>> eq.rewrite(Add)
+        2*b
+        >>> eq.rewrite(Add, evaluate=None).args
+        (b, b, x, -x)
+        >>> eq.rewrite(Add, evaluate=False).args
+        (b, x, b, -x)
+        """
+        from .add import _unevaluated_Add, Add
+        L, R = args
+        if L == 0:
+            return R
+        if R == 0:
+            return L
+        evaluate = kwargs.get('evaluate', True)
+        if evaluate:
+            # allow cancellation of args
+            return L - R
+        args = Add.make_args(L) + Add.make_args(-R)
+        if evaluate is None:
+            # no cancellation, but canonical
+            return _unevaluated_Add(*args)
+        # no cancellation, not canonical
+        return Add._from_args(args)
+
+    @property
+    def binary_symbols(self):
+        if S.true in self.args or S.false in self.args:
+            if self.lhs.is_Symbol:
+                return {self.lhs}
+            elif self.rhs.is_Symbol:
+                return {self.rhs}
+        return set()
+
+    def _eval_simplify(self, **kwargs):
+        # standard simplify
+        e = super()._eval_simplify(**kwargs)
+        if not isinstance(e, Equality):
+            return e
+        from .expr import Expr
+        if not isinstance(e.lhs, Expr) or not isinstance(e.rhs, Expr):
+            return e
+        free = self.free_symbols
+        if len(free) == 1:
+            try:
+                from .add import Add
+                from sympy.solvers.solveset import linear_coeffs
+                x = free.pop()
+                m, b = linear_coeffs(
+                    e.rewrite(Add, evaluate=False), x)
+                if m.is_zero is False:
+                    enew = e.func(x, -b / m)
+                else:
+                    enew = e.func(m * x, -b)
+                measure = kwargs['measure']
+                if measure(enew) <= kwargs['ratio'] * measure(e):
+                    e = enew
+            except ValueError:
+                pass
+        return e.canonical
+
+    def integrate(self, *args, **kwargs):
+        """See the integrate function in sympy.integrals"""
+        from sympy.integrals.integrals import integrate
+        return integrate(self, *args, **kwargs)
+
+    def as_poly(self, *gens, **kwargs):
+        '''Returns lhs-rhs as a Poly
+
+        Examples
+        ========
+
+        >>> from sympy import Eq
+        >>> from sympy.abc import x
+        >>> Eq(x**2, 1).as_poly(x)
+        Poly(x**2 - 1, x, domain='ZZ')
+        '''
+        return (self.lhs - self.rhs).as_poly(*gens, **kwargs)
+
+
+Eq = Equality
+
+
+class Unequality(Relational):
+    """An unequal relation between two objects.
+
+    Explanation
+    ===========
+
+    Represents that two objects are not equal.  If they can be shown to be
+    definitively equal, this will reduce to False; if definitively unequal,
+    this will reduce to True.  Otherwise, the relation is maintained as an
+    Unequality object.
+
+    Examples
+    ========
+
+    >>> from sympy import Ne
+    >>> from sympy.abc import x, y
+    >>> Ne(y, x+x**2)
+    Ne(y, x**2 + x)
+
+    See Also
+    ========
+    Equality
+
+    Notes
+    =====
+    This class is not the same as the != operator.  The != operator tests
+    for exact structural equality between two expressions; this class
+    compares expressions mathematically.
+
+    This class is effectively the inverse of Equality.  As such, it uses the
+    same algorithms, including any available `_eval_Eq` methods.
+
+    """
+    rel_op = '!='
+
+    __slots__ = ()
+
+    def __new__(cls, lhs, rhs, **options):
+        lhs = _sympify(lhs)
+        rhs = _sympify(rhs)
+        evaluate = options.pop('evaluate', global_parameters.evaluate)
+        if evaluate:
+            val = is_neq(lhs, rhs)
+            if val is None:
+                return cls(lhs, rhs, evaluate=False)
+            else:
+                return _sympify(val)
+
+        return Relational.__new__(cls, lhs, rhs, **options)
+
+    @classmethod
+    def _eval_relation(cls, lhs, rhs):
+        return _sympify(lhs != rhs)
+
+    @property
+    def binary_symbols(self):
+        if S.true in self.args or S.false in self.args:
+            if self.lhs.is_Symbol:
+                return {self.lhs}
+            elif self.rhs.is_Symbol:
+                return {self.rhs}
+        return set()
+
+    def _eval_simplify(self, **kwargs):
+        # simplify as an equality
+        eq = Equality(*self.args)._eval_simplify(**kwargs)
+        if isinstance(eq, Equality):
+            # send back Ne with the new args
+            return self.func(*eq.args)
+        return eq.negated  # result of Ne is the negated Eq
+
+
+Ne = Unequality
+
+
+class _Inequality(Relational):
+    """Internal base class for all *Than types.
+
+    Each subclass must implement _eval_relation to provide the method for
+    comparing two real numbers.
+
+    """
+    __slots__ = ()
+
+    def __new__(cls, lhs, rhs, **options):
+
+        try:
+            lhs = _sympify(lhs)
+            rhs = _sympify(rhs)
+        except SympifyError:
+            return NotImplemented
+
+        evaluate = options.pop('evaluate', global_parameters.evaluate)
+        if evaluate:
+            for me in (lhs, rhs):
+                if me.is_extended_real is False:
+                    raise TypeError("Invalid comparison of non-real %s" % me)
+                if me is S.NaN:
+                    raise TypeError("Invalid NaN comparison")
+            # First we invoke the appropriate inequality method of `lhs`
+            # (e.g., `lhs.__lt__`).  That method will try to reduce to
+            # boolean or raise an exception.  It may keep calling
+            # superclasses until it reaches `Expr` (e.g., `Expr.__lt__`).
+            # In some cases, `Expr` will just invoke us again (if neither it
+            # nor a subclass was able to reduce to boolean or raise an
+            # exception).  In that case, it must call us with
+            # `evaluate=False` to prevent infinite recursion.
+            return cls._eval_relation(lhs, rhs, **options)
+
+        # make a "non-evaluated" Expr for the inequality
+        return Relational.__new__(cls, lhs, rhs, **options)
+
+    @classmethod
+    def _eval_relation(cls, lhs, rhs, **options):
+        val = cls._eval_fuzzy_relation(lhs, rhs)
+        if val is None:
+            return cls(lhs, rhs, evaluate=False)
+        else:
+            return _sympify(val)
+
+
+class _Greater(_Inequality):
+    """Not intended for general use
+
+    _Greater is only used so that GreaterThan and StrictGreaterThan may
+    subclass it for the .gts and .lts properties.
+
+    """
+    __slots__ = ()
+
+    @property
+    def gts(self):
+        return self._args[0]
+
+    @property
+    def lts(self):
+        return self._args[1]
+
+
+class _Less(_Inequality):
+    """Not intended for general use.
+
+    _Less is only used so that LessThan and StrictLessThan may subclass it for
+    the .gts and .lts properties.
+
+    """
+    __slots__ = ()
+
+    @property
+    def gts(self):
+        return self._args[1]
+
+    @property
+    def lts(self):
+        return self._args[0]
+
+
+class GreaterThan(_Greater):
+    r"""Class representations of inequalities.
+
+    Explanation
+    ===========
+
+    The ``*Than`` classes represent inequal relationships, where the left-hand
+    side is generally bigger or smaller than the right-hand side.  For example,
+    the GreaterThan class represents an inequal relationship where the
+    left-hand side is at least as big as the right side, if not bigger.  In
+    mathematical notation:
+
+    lhs $\ge$ rhs
+
+    In total, there are four ``*Than`` classes, to represent the four
+    inequalities:
+
+    +-----------------+--------+
+    |Class Name       | Symbol |
+    +=================+========+
+    |GreaterThan      | ``>=`` |
+    +-----------------+--------+
+    |LessThan         | ``<=`` |
+    +-----------------+--------+
+    |StrictGreaterThan| ``>``  |
+    +-----------------+--------+
+    |StrictLessThan   | ``<``  |
+    +-----------------+--------+
+
+    All classes take two arguments, lhs and rhs.
+
+    +----------------------------+-----------------+
+    |Signature Example           | Math Equivalent |
+    +============================+=================+
+    |GreaterThan(lhs, rhs)       |   lhs $\ge$ rhs |
+    +----------------------------+-----------------+
+    |LessThan(lhs, rhs)          |   lhs $\le$ rhs |
+    +----------------------------+-----------------+
+    |StrictGreaterThan(lhs, rhs) |   lhs $>$ rhs   |
+    +----------------------------+-----------------+
+    |StrictLessThan(lhs, rhs)    |   lhs $<$ rhs   |
+    +----------------------------+-----------------+
+
+    In addition to the normal .lhs and .rhs of Relations, ``*Than`` inequality
+    objects also have the .lts and .gts properties, which represent the "less
+    than side" and "greater than side" of the operator.  Use of .lts and .gts
+    in an algorithm rather than .lhs and .rhs as an assumption of inequality
+    direction will make more explicit the intent of a certain section of code,
+    and will make it similarly more robust to client code changes:
+
+    >>> from sympy import GreaterThan, StrictGreaterThan
+    >>> from sympy import LessThan, StrictLessThan
+    >>> from sympy import And, Ge, Gt, Le, Lt, Rel, S
+    >>> from sympy.abc import x, y, z
+    >>> from sympy.core.relational import Relational
+
+    >>> e = GreaterThan(x, 1)
+    >>> e
+    x >= 1
+    >>> '%s >= %s is the same as %s <= %s' % (e.gts, e.lts, e.lts, e.gts)
+    'x >= 1 is the same as 1 <= x'
+
+    Examples
+    ========
+
+    One generally does not instantiate these classes directly, but uses various
+    convenience methods:
+
+    >>> for f in [Ge, Gt, Le, Lt]:  # convenience wrappers
+    ...     print(f(x, 2))
+    x >= 2
+    x > 2
+    x <= 2
+    x < 2
+
+    Another option is to use the Python inequality operators (``>=``, ``>``,
+    ``<=``, ``<``) directly.  Their main advantage over the ``Ge``, ``Gt``,
+    ``Le``, and ``Lt`` counterparts, is that one can write a more
+    "mathematical looking" statement rather than littering the math with
+    oddball function calls.  However there are certain (minor) caveats of
+    which to be aware (search for 'gotcha', below).
+
+    >>> x >= 2
+    x >= 2
+    >>> _ == Ge(x, 2)
+    True
+
+    However, it is also perfectly valid to instantiate a ``*Than`` class less
+    succinctly and less conveniently:
+
+    >>> Rel(x, 1, ">")
+    x > 1
+    >>> Relational(x, 1, ">")
+    x > 1
+
+    >>> StrictGreaterThan(x, 1)
+    x > 1
+    >>> GreaterThan(x, 1)
+    x >= 1
+    >>> LessThan(x, 1)
+    x <= 1
+    >>> StrictLessThan(x, 1)
+    x < 1
+
+    Notes
+    =====
+
+    There are a couple of "gotchas" to be aware of when using Python's
+    operators.
+
+    The first is that what your write is not always what you get:
+
+        >>> 1 < x
+        x > 1
+
+        Due to the order that Python parses a statement, it may
+        not immediately find two objects comparable.  When ``1 < x``
+        is evaluated, Python recognizes that the number 1 is a native
+        number and that x is *not*.  Because a native Python number does
+        not know how to compare itself with a SymPy object
+        Python will try the reflective operation, ``x > 1`` and that is the
+        form that gets evaluated, hence returned.
+
+        If the order of the statement is important (for visual output to
+        the console, perhaps), one can work around this annoyance in a
+        couple ways:
+
+        (1) "sympify" the literal before comparison
+
+        >>> S(1) < x
+        1 < x
+
+        (2) use one of the wrappers or less succinct methods described
+        above
+
+        >>> Lt(1, x)
+        1 < x
+        >>> Relational(1, x, "<")
+        1 < x
+
+    The second gotcha involves writing equality tests between relationals
+    when one or both sides of the test involve a literal relational:
+
+        >>> e = x < 1; e
+        x < 1
+        >>> e == e  # neither side is a literal
+        True
+        >>> e == x < 1  # expecting True, too
+        False
+        >>> e != x < 1  # expecting False
+        x < 1
+        >>> x < 1 != x < 1  # expecting False or the same thing as before
+        Traceback (most recent call last):
+        ...
+        TypeError: cannot determine truth value of Relational
+
+        The solution for this case is to wrap literal relationals in
+        parentheses:
+
+        >>> e == (x < 1)
+        True
+        >>> e != (x < 1)
+        False
+        >>> (x < 1) != (x < 1)
+        False
+
+    The third gotcha involves chained inequalities not involving
+    ``==`` or ``!=``. Occasionally, one may be tempted to write:
+
+        >>> e = x < y < z
+        Traceback (most recent call last):
+        ...
+        TypeError: symbolic boolean expression has no truth value.
+
+        Due to an implementation detail or decision of Python [1]_,
+        there is no way for SymPy to create a chained inequality with
+        that syntax so one must use And:
+
+        >>> e = And(x < y, y < z)
+        >>> type( e )
+        And
+        >>> e
+        (x < y) & (y < z)
+
+        Although this can also be done with the '&' operator, it cannot
+        be done with the 'and' operarator:
+
+        >>> (x < y) & (y < z)
+        (x < y) & (y < z)
+        >>> (x < y) and (y < z)
+        Traceback (most recent call last):
+        ...
+        TypeError: cannot determine truth value of Relational
+
+    .. [1] This implementation detail is that Python provides no reliable
+       method to determine that a chained inequality is being built.
+       Chained comparison operators are evaluated pairwise, using "and"
+       logic (see
+       https://docs.python.org/3/reference/expressions.html#not-in). This
+       is done in an efficient way, so that each object being compared
+       is only evaluated once and the comparison can short-circuit. For
+       example, ``1 > 2 > 3`` is evaluated by Python as ``(1 > 2) and (2
+       > 3)``. The ``and`` operator coerces each side into a bool,
+       returning the object itself when it short-circuits. The bool of
+       the --Than operators will raise TypeError on purpose, because
+       SymPy cannot determine the mathematical ordering of symbolic
+       expressions. Thus, if we were to compute ``x > y > z``, with
+       ``x``, ``y``, and ``z`` being Symbols, Python converts the
+       statement (roughly) into these steps:
+
+        (1) x > y > z
+        (2) (x > y) and (y > z)
+        (3) (GreaterThanObject) and (y > z)
+        (4) (GreaterThanObject.__bool__()) and (y > z)
+        (5) TypeError
+
+       Because of the ``and`` added at step 2, the statement gets turned into a
+       weak ternary statement, and the first object's ``__bool__`` method will
+       raise TypeError.  Thus, creating a chained inequality is not possible.
+
+           In Python, there is no way to override the ``and`` operator, or to
+           control how it short circuits, so it is impossible to make something
+           like ``x > y > z`` work.  There was a PEP to change this,
+           :pep:`335`, but it was officially closed in March, 2012.
+
+    """
+    __slots__ = ()
+
+    rel_op = '>='
+
+    @classmethod
+    def _eval_fuzzy_relation(cls, lhs, rhs):
+        return is_ge(lhs, rhs)
+
+    @property
+    def strict(self):
+        return Gt(*self.args)
+
+Ge = GreaterThan
+
+
+class LessThan(_Less):
+    __doc__ = GreaterThan.__doc__
+    __slots__ = ()
+
+    rel_op = '<='
+
+    @classmethod
+    def _eval_fuzzy_relation(cls, lhs, rhs):
+        return is_le(lhs, rhs)
+
+    @property
+    def strict(self):
+        return Lt(*self.args)
+
+Le = LessThan
+
+
+class StrictGreaterThan(_Greater):
+    __doc__ = GreaterThan.__doc__
+    __slots__ = ()
+
+    rel_op = '>'
+
+    @classmethod
+    def _eval_fuzzy_relation(cls, lhs, rhs):
+        return is_gt(lhs, rhs)
+
+    @property
+    def weak(self):
+        return Ge(*self.args)
+
+
+Gt = StrictGreaterThan
+
+
+class StrictLessThan(_Less):
+    __doc__ = GreaterThan.__doc__
+    __slots__ = ()
+
+    rel_op = '<'
+
+    @classmethod
+    def _eval_fuzzy_relation(cls, lhs, rhs):
+        return is_lt(lhs, rhs)
+
+    @property
+    def weak(self):
+        return Le(*self.args)
+
+Lt = StrictLessThan
+
+# A class-specific (not object-specific) data item used for a minor speedup.
+# It is defined here, rather than directly in the class, because the classes
+# that it references have not been defined until now (e.g. StrictLessThan).
+Relational.ValidRelationOperator = {
+    None: Equality,
+    '==': Equality,
+    'eq': Equality,
+    '!=': Unequality,
+    '<>': Unequality,
+    'ne': Unequality,
+    '>=': GreaterThan,
+    'ge': GreaterThan,
+    '<=': LessThan,
+    'le': LessThan,
+    '>': StrictGreaterThan,
+    'gt': StrictGreaterThan,
+    '<': StrictLessThan,
+    'lt': StrictLessThan,
+}
+
+
+def _n2(a, b):
+    """Return (a - b).evalf(2) if a and b are comparable, else None.
+    This should only be used when a and b are already sympified.
+    """
+    # /!\ it is very important (see issue 8245) not to
+    # use a re-evaluated number in the calculation of dif
+    if a.is_comparable and b.is_comparable:
+        dif = (a - b).evalf(2)
+        if dif.is_comparable:
+            return dif
+
+
+@dispatch(Expr, Expr)
+def _eval_is_ge(lhs, rhs):
+    return None
+
+
+@dispatch(Basic, Basic)
+def _eval_is_eq(lhs, rhs):
+    return None
+
+
+@dispatch(Tuple, Expr) # type: ignore
+def _eval_is_eq(lhs, rhs):  # noqa:F811
+    return False
+
+
+@dispatch(Tuple, AppliedUndef) # type: ignore
+def _eval_is_eq(lhs, rhs):  # noqa:F811
+    return None
+
+
+@dispatch(Tuple, Symbol) # type: ignore
+def _eval_is_eq(lhs, rhs):  # noqa:F811
+    return None
+
+
+@dispatch(Tuple, Tuple) # type: ignore
+def _eval_is_eq(lhs, rhs):  # noqa:F811
+    if len(lhs) != len(rhs):
+        return False
+
+    return fuzzy_and(fuzzy_bool(is_eq(s, o)) for s, o in zip(lhs, rhs))
+
+
+def is_lt(lhs, rhs, assumptions=None):
+    """Fuzzy bool for lhs is strictly less than rhs.
+
+    See the docstring for :func:`~.is_ge` for more.
+    """
+    return fuzzy_not(is_ge(lhs, rhs, assumptions))
+
+
+def is_gt(lhs, rhs, assumptions=None):
+    """Fuzzy bool for lhs is strictly greater than rhs.
+
+    See the docstring for :func:`~.is_ge` for more.
+    """
+    return fuzzy_not(is_le(lhs, rhs, assumptions))
+
+
+def is_le(lhs, rhs, assumptions=None):
+    """Fuzzy bool for lhs is less than or equal to rhs.
+
+    See the docstring for :func:`~.is_ge` for more.
+    """
+    return is_ge(rhs, lhs, assumptions)
+
+
+def is_ge(lhs, rhs, assumptions=None):
+    """
+    Fuzzy bool for *lhs* is greater than or equal to *rhs*.
+
+    Parameters
+    ==========
+
+    lhs : Expr
+        The left-hand side of the expression, must be sympified,
+        and an instance of expression. Throws an exception if
+        lhs is not an instance of expression.
+
+    rhs : Expr
+        The right-hand side of the expression, must be sympified
+        and an instance of expression. Throws an exception if
+        lhs is not an instance of expression.
+
+    assumptions: Boolean, optional
+        Assumptions taken to evaluate the inequality.
+
+    Returns
+    =======
+
+    ``True`` if *lhs* is greater than or equal to *rhs*, ``False`` if *lhs*
+    is less than *rhs*, and ``None`` if the comparison between *lhs* and
+    *rhs* is indeterminate.
+
+    Explanation
+    ===========
+
+    This function is intended to give a relatively fast determination and
+    deliberately does not attempt slow calculations that might help in
+    obtaining a determination of True or False in more difficult cases.
+
+    The four comparison functions ``is_le``, ``is_lt``, ``is_ge``, and ``is_gt`` are
+    each implemented in terms of ``is_ge`` in the following way:
+
+    is_ge(x, y) := is_ge(x, y)
+    is_le(x, y) := is_ge(y, x)
+    is_lt(x, y) := fuzzy_not(is_ge(x, y))
+    is_gt(x, y) := fuzzy_not(is_ge(y, x))
+
+    Therefore, supporting new type with this function will ensure behavior for
+    other three functions as well.
+
+    To maintain these equivalences in fuzzy logic it is important that in cases where
+    either x or y is non-real all comparisons will give None.
+
+    Examples
+    ========
+
+    >>> from sympy import S, Q
+    >>> from sympy.core.relational import is_ge, is_le, is_gt, is_lt
+    >>> from sympy.abc import x
+    >>> is_ge(S(2), S(0))
+    True
+    >>> is_ge(S(0), S(2))
+    False
+    >>> is_le(S(0), S(2))
+    True
+    >>> is_gt(S(0), S(2))
+    False
+    >>> is_lt(S(2), S(0))
+    False
+
+    Assumptions can be passed to evaluate the quality which is otherwise
+    indeterminate.
+
+    >>> print(is_ge(x, S(0)))
+    None
+    >>> is_ge(x, S(0), assumptions=Q.positive(x))
+    True
+
+    New types can be supported by dispatching to ``_eval_is_ge``.
+
+    >>> from sympy import Expr, sympify
+    >>> from sympy.multipledispatch import dispatch
+    >>> class MyExpr(Expr):
+    ...     def __new__(cls, arg):
+    ...         return super().__new__(cls, sympify(arg))
+    ...     @property
+    ...     def value(self):
+    ...         return self.args[0]
+    >>> @dispatch(MyExpr, MyExpr)
+    ... def _eval_is_ge(a, b):
+    ...     return is_ge(a.value, b.value)
+    >>> a = MyExpr(1)
+    >>> b = MyExpr(2)
+    >>> is_ge(b, a)
+    True
+    >>> is_le(a, b)
+    True
+    """
+    from sympy.assumptions.wrapper import AssumptionsWrapper, is_extended_nonnegative
+
+    if not (isinstance(lhs, Expr) and isinstance(rhs, Expr)):
+        raise TypeError("Can only compare inequalities with Expr")
+
+    retval = _eval_is_ge(lhs, rhs)
+
+    if retval is not None:
+        return retval
+    else:
+        n2 = _n2(lhs, rhs)
+        if n2 is not None:
+            # use float comparison for infinity.
+            # otherwise get stuck in infinite recursion
+            if n2 in (S.Infinity, S.NegativeInfinity):
+                n2 = float(n2)
+            return n2 >= 0
+
+        _lhs = AssumptionsWrapper(lhs, assumptions)
+        _rhs = AssumptionsWrapper(rhs, assumptions)
+        if _lhs.is_extended_real and _rhs.is_extended_real:
+            if (_lhs.is_infinite and _lhs.is_extended_positive) or (_rhs.is_infinite and _rhs.is_extended_negative):
+                return True
+            diff = lhs - rhs
+            if diff is not S.NaN:
+                rv = is_extended_nonnegative(diff, assumptions)
+                if rv is not None:
+                    return rv
+
+
+def is_neq(lhs, rhs, assumptions=None):
+    """Fuzzy bool for lhs does not equal rhs.
+
+    See the docstring for :func:`~.is_eq` for more.
+    """
+    return fuzzy_not(is_eq(lhs, rhs, assumptions))
+
+
+def is_eq(lhs, rhs, assumptions=None):
+    """
+    Fuzzy bool representing mathematical equality between *lhs* and *rhs*.
+
+    Parameters
+    ==========
+
+    lhs : Expr
+        The left-hand side of the expression, must be sympified.
+
+    rhs : Expr
+        The right-hand side of the expression, must be sympified.
+
+    assumptions: Boolean, optional
+        Assumptions taken to evaluate the equality.
+
+    Returns
+    =======
+
+    ``True`` if *lhs* is equal to *rhs*, ``False`` is *lhs* is not equal to *rhs*,
+    and ``None`` if the comparison between *lhs* and *rhs* is indeterminate.
+
+    Explanation
+    ===========
+
+    This function is intended to give a relatively fast determination and
+    deliberately does not attempt slow calculations that might help in
+    obtaining a determination of True or False in more difficult cases.
+
+    :func:`~.is_neq` calls this function to return its value, so supporting
+    new type with this function will ensure correct behavior for ``is_neq``
+    as well.
+
+    Examples
+    ========
+
+    >>> from sympy import Q, S
+    >>> from sympy.core.relational import is_eq, is_neq
+    >>> from sympy.abc import x
+    >>> is_eq(S(0), S(0))
+    True
+    >>> is_neq(S(0), S(0))
+    False
+    >>> is_eq(S(0), S(2))
+    False
+    >>> is_neq(S(0), S(2))
+    True
+
+    Assumptions can be passed to evaluate the equality which is otherwise
+    indeterminate.
+
+    >>> print(is_eq(x, S(0)))
+    None
+    >>> is_eq(x, S(0), assumptions=Q.zero(x))
+    True
+
+    New types can be supported by dispatching to ``_eval_is_eq``.
+
+    >>> from sympy import Basic, sympify
+    >>> from sympy.multipledispatch import dispatch
+    >>> class MyBasic(Basic):
+    ...     def __new__(cls, arg):
+    ...         return Basic.__new__(cls, sympify(arg))
+    ...     @property
+    ...     def value(self):
+    ...         return self.args[0]
+    ...
+    >>> @dispatch(MyBasic, MyBasic)
+    ... def _eval_is_eq(a, b):
+    ...     return is_eq(a.value, b.value)
+    ...
+    >>> a = MyBasic(1)
+    >>> b = MyBasic(1)
+    >>> is_eq(a, b)
+    True
+    >>> is_neq(a, b)
+    False
+
+    """
+    # here, _eval_Eq is only called for backwards compatibility
+    # new code should use is_eq with multiple dispatch as
+    # outlined in the docstring
+    for side1, side2 in (lhs, rhs), (rhs, lhs):
+        eval_func = getattr(side1, '_eval_Eq', None)
+        if eval_func is not None:
+            retval = eval_func(side2)
+            if retval is not None:
+                return retval
+
+    retval = _eval_is_eq(lhs, rhs)
+    if retval is not None:
+        return retval
+
+    if dispatch(type(lhs), type(rhs)) != dispatch(type(rhs), type(lhs)):
+        retval = _eval_is_eq(rhs, lhs)
+        if retval is not None:
+            return retval
+
+    # retval is still None, so go through the equality logic
+    # If expressions have the same structure, they must be equal.
+    if lhs == rhs:
+        return True  # e.g. True == True
+    elif all(isinstance(i, BooleanAtom) for i in (rhs, lhs)):
+        return False  # True != False
+    elif not (lhs.is_Symbol or rhs.is_Symbol) and (
+        isinstance(lhs, Boolean) !=
+        isinstance(rhs, Boolean)):
+        return False  # only Booleans can equal Booleans
+
+    from sympy.assumptions.wrapper import (AssumptionsWrapper,
+        is_infinite, is_extended_real)
+    from .add import Add
+
+    _lhs = AssumptionsWrapper(lhs, assumptions)
+    _rhs = AssumptionsWrapper(rhs, assumptions)
+
+    if _lhs.is_infinite or _rhs.is_infinite:
+        if fuzzy_xor([_lhs.is_infinite, _rhs.is_infinite]):
+            return False
+        if fuzzy_xor([_lhs.is_extended_real, _rhs.is_extended_real]):
+            return False
+        if fuzzy_and([_lhs.is_extended_real, _rhs.is_extended_real]):
+            return fuzzy_xor([_lhs.is_extended_positive, fuzzy_not(_rhs.is_extended_positive)])
+
+        # Try to split real/imaginary parts and equate them
+        I = S.ImaginaryUnit
+
+        def split_real_imag(expr):
+            real_imag = lambda t: (
+                'real' if is_extended_real(t, assumptions) else
+                'imag' if is_extended_real(I*t, assumptions) else None)
+            return sift(Add.make_args(expr), real_imag)
+
+        lhs_ri = split_real_imag(lhs)
+        if not lhs_ri[None]:
+            rhs_ri = split_real_imag(rhs)
+            if not rhs_ri[None]:
+                eq_real = is_eq(Add(*lhs_ri['real']), Add(*rhs_ri['real']), assumptions)
+                eq_imag = is_eq(I * Add(*lhs_ri['imag']), I * Add(*rhs_ri['imag']), assumptions)
+                return fuzzy_and(map(fuzzy_bool, [eq_real, eq_imag]))
+
+        from sympy.functions.elementary.complexes import arg
+        # Compare e.g. zoo with 1+I*oo by comparing args
+        arglhs = arg(lhs)
+        argrhs = arg(rhs)
+        # Guard against Eq(nan, nan) -> False
+        if not (arglhs == S.NaN and argrhs == S.NaN):
+            return fuzzy_bool(is_eq(arglhs, argrhs, assumptions))
+
+    if all(isinstance(i, Expr) for i in (lhs, rhs)):
+        # see if the difference evaluates
+        dif = lhs - rhs
+        _dif = AssumptionsWrapper(dif, assumptions)
+        z = _dif.is_zero
+        if z is not None:
+            if z is False and _dif.is_commutative:  # issue 10728
+                return False
+            if z:
+                return True
+
+        n2 = _n2(lhs, rhs)
+        if n2 is not None:
+            return _sympify(n2 == 0)
+
+        # see if the ratio evaluates
+        n, d = dif.as_numer_denom()
+        rv = None
+        _n = AssumptionsWrapper(n, assumptions)
+        _d = AssumptionsWrapper(d, assumptions)
+        if _n.is_zero:
+            rv = _d.is_nonzero
+        elif _n.is_finite:
+            if _d.is_infinite:
+                rv = True
+            elif _n.is_zero is False:
+                rv = _d.is_infinite
+                if rv is None:
+                    # if the condition that makes the denominator
+                    # infinite does not make the original expression
+                    # True then False can be returned
+                    from sympy.simplify.simplify import clear_coefficients
+                    l, r = clear_coefficients(d, S.Infinity)
+                    args = [_.subs(l, r) for _ in (lhs, rhs)]
+                    if args != [lhs, rhs]:
+                        rv = fuzzy_bool(is_eq(*args, assumptions))
+                        if rv is True:
+                            rv = None
+        elif any(is_infinite(a, assumptions) for a in Add.make_args(n)):
+            # (inf or nan)/x != 0
+            rv = False
+        if rv is not None:
+            return rv

env-llmeval/lib/python3.10/site-packages/sympy/core/singleton.py

@@ -0,0 +1,174 @@
+"""Singleton mechanism"""
+
+
+from .core import Registry
+from .sympify import sympify
+
+
+class SingletonRegistry(Registry):
+    """
+    The registry for the singleton classes (accessible as ``S``).
+
+    Explanation
+    ===========
+
+    This class serves as two separate things.
+
+    The first thing it is is the ``SingletonRegistry``. Several classes in
+    SymPy appear so often that they are singletonized, that is, using some
+    metaprogramming they are made so that they can only be instantiated once
+    (see the :class:`sympy.core.singleton.Singleton` class for details). For
+    instance, every time you create ``Integer(0)``, this will return the same
+    instance, :class:`sympy.core.numbers.Zero`. All singleton instances are
+    attributes of the ``S`` object, so ``Integer(0)`` can also be accessed as
+    ``S.Zero``.
+
+    Singletonization offers two advantages: it saves memory, and it allows
+    fast comparison. It saves memory because no matter how many times the
+    singletonized objects appear in expressions in memory, they all point to
+    the same single instance in memory. The fast comparison comes from the
+    fact that you can use ``is`` to compare exact instances in Python
+    (usually, you need to use ``==`` to compare things). ``is`` compares
+    objects by memory address, and is very fast.
+
+    Examples
+    ========
+
+    >>> from sympy import S, Integer
+    >>> a = Integer(0)
+    >>> a is S.Zero
+    True
+
+    For the most part, the fact that certain objects are singletonized is an
+    implementation detail that users should not need to worry about. In SymPy
+    library code, ``is`` comparison is often used for performance purposes
+    The primary advantage of ``S`` for end users is the convenient access to
+    certain instances that are otherwise difficult to type, like ``S.Half``
+    (instead of ``Rational(1, 2)``).
+
+    When using ``is`` comparison, make sure the argument is sympified. For
+    instance,
+
+    >>> x = 0
+    >>> x is S.Zero
+    False
+
+    This problem is not an issue when using ``==``, which is recommended for
+    most use-cases:
+
+    >>> 0 == S.Zero
+    True
+
+    The second thing ``S`` is is a shortcut for
+    :func:`sympy.core.sympify.sympify`. :func:`sympy.core.sympify.sympify` is
+    the function that converts Python objects such as ``int(1)`` into SymPy
+    objects such as ``Integer(1)``. It also converts the string form of an
+    expression into a SymPy expression, like ``sympify("x**2")`` ->
+    ``Symbol("x")**2``. ``S(1)`` is the same thing as ``sympify(1)``
+    (basically, ``S.__call__`` has been defined to call ``sympify``).
+
+    This is for convenience, since ``S`` is a single letter. It's mostly
+    useful for defining rational numbers. Consider an expression like ``x +
+    1/2``. If you enter this directly in Python, it will evaluate the ``1/2``
+    and give ``0.5``, because both arguments are ints (see also
+    :ref:`tutorial-gotchas-final-notes`). However, in SymPy, you usually want
+    the quotient of two integers to give an exact rational number. The way
+    Python's evaluation works, at least one side of an operator needs to be a
+    SymPy object for the SymPy evaluation to take over. You could write this
+    as ``x + Rational(1, 2)``, but this is a lot more typing. A shorter
+    version is ``x + S(1)/2``. Since ``S(1)`` returns ``Integer(1)``, the
+    division will return a ``Rational`` type, since it will call
+    ``Integer.__truediv__``, which knows how to return a ``Rational``.
+
+    """
+    __slots__ = ()
+
+    # Also allow things like S(5)
+    __call__ = staticmethod(sympify)
+
+    def __init__(self):
+        self._classes_to_install = {}
+        # Dict of classes that have been registered, but that have not have been
+        # installed as an attribute of this SingletonRegistry.
+        # Installation automatically happens at the first attempt to access the
+        # attribute.
+        # The purpose of this is to allow registration during class
+        # initialization during import, but not trigger object creation until
+        # actual use (which should not happen until after all imports are
+        # finished).
+
+    def register(self, cls):
+        # Make sure a duplicate class overwrites the old one
+        if hasattr(self, cls.__name__):
+            delattr(self, cls.__name__)
+        self._classes_to_install[cls.__name__] = cls
+
+    def __getattr__(self, name):
+        """Python calls __getattr__ if no attribute of that name was installed
+        yet.
+
+        Explanation
+        ===========
+
+        This __getattr__ checks whether a class with the requested name was
+        already registered but not installed; if no, raises an AttributeError.
+        Otherwise, retrieves the class, calculates its singleton value, installs
+        it as an attribute of the given name, and unregisters the class."""
+        if name not in self._classes_to_install:
+            raise AttributeError(
+                "Attribute '%s' was not installed on SymPy registry %s" % (
+                name, self))
+        class_to_install = self._classes_to_install[name]
+        value_to_install = class_to_install()
+        self.__setattr__(name, value_to_install)
+        del self._classes_to_install[name]
+        return value_to_install
+
+    def __repr__(self):
+        return "S"
+
+S = SingletonRegistry()
+
+
+class Singleton(type):
+    """
+    Metaclass for singleton classes.
+
+    Explanation
+    ===========
+
+    A singleton class has only one instance which is returned every time the
+    class is instantiated. Additionally, this instance can be accessed through
+    the global registry object ``S`` as ``S.<class_name>``.
+
+    Examples
+    ========
+
+        >>> from sympy import S, Basic
+        >>> from sympy.core.singleton import Singleton
+        >>> class MySingleton(Basic, metaclass=Singleton):
+        ...     pass
+        >>> Basic() is Basic()
+        False
+        >>> MySingleton() is MySingleton()
+        True
+        >>> S.MySingleton is MySingleton()
+        True
+
+    Notes
+    =====
+
+    Instance creation is delayed until the first time the value is accessed.
+    (SymPy versions before 1.0 would create the instance during class
+    creation time, which would be prone to import cycles.)
+    """
+    def __init__(cls, *args, **kwargs):
+        cls._instance = obj = Basic.__new__(cls)
+        cls.__new__ = lambda cls: obj
+        cls.__getnewargs__ = lambda obj: ()
+        cls.__getstate__ = lambda obj: None
+        S.register(cls)
+
+
+# Delayed to avoid cyclic import
+from .basic import Basic

env-llmeval/lib/python3.10/site-packages/sympy/core/sorting.py

@@ -0,0 +1,309 @@
+from collections import defaultdict
+
+from .sympify import sympify, SympifyError
+from sympy.utilities.iterables import iterable, uniq
+
+
+__all__ = ['default_sort_key', 'ordered']
+
+
+def default_sort_key(item, order=None):
+    """Return a key that can be used for sorting.
+
+    The key has the structure:
+
+    (class_key, (len(args), args), exponent.sort_key(), coefficient)
+
+    This key is supplied by the sort_key routine of Basic objects when
+    ``item`` is a Basic object or an object (other than a string) that
+    sympifies to a Basic object. Otherwise, this function produces the
+    key.
+
+    The ``order`` argument is passed along to the sort_key routine and is
+    used to determine how the terms *within* an expression are ordered.
+    (See examples below) ``order`` options are: 'lex', 'grlex', 'grevlex',
+    and reversed values of the same (e.g. 'rev-lex'). The default order
+    value is None (which translates to 'lex').
+
+    Examples
+    ========
+
+    >>> from sympy import S, I, default_sort_key, sin, cos, sqrt
+    >>> from sympy.core.function import UndefinedFunction
+    >>> from sympy.abc import x
+
+    The following are equivalent ways of getting the key for an object:
+
+    >>> x.sort_key() == default_sort_key(x)
+    True
+
+    Here are some examples of the key that is produced:
+
+    >>> default_sort_key(UndefinedFunction('f'))
+    ((0, 0, 'UndefinedFunction'), (1, ('f',)), ((1, 0, 'Number'),
+        (0, ()), (), 1), 1)
+    >>> default_sort_key('1')
+    ((0, 0, 'str'), (1, ('1',)), ((1, 0, 'Number'), (0, ()), (), 1), 1)
+    >>> default_sort_key(S.One)
+    ((1, 0, 'Number'), (0, ()), (), 1)
+    >>> default_sort_key(2)
+    ((1, 0, 'Number'), (0, ()), (), 2)
+
+    While sort_key is a method only defined for SymPy objects,
+    default_sort_key will accept anything as an argument so it is
+    more robust as a sorting key. For the following, using key=
+    lambda i: i.sort_key() would fail because 2 does not have a sort_key
+    method; that's why default_sort_key is used. Note, that it also
+    handles sympification of non-string items likes ints:
+
+    >>> a = [2, I, -I]
+    >>> sorted(a, key=default_sort_key)
+    [2, -I, I]
+
+    The returned key can be used anywhere that a key can be specified for
+    a function, e.g. sort, min, max, etc...:
+
+    >>> a.sort(key=default_sort_key); a[0]
+    2
+    >>> min(a, key=default_sort_key)
+    2
+
+    Notes
+    =====
+
+    The key returned is useful for getting items into a canonical order
+    that will be the same across platforms. It is not directly useful for
+    sorting lists of expressions:
+
+    >>> a, b = x, 1/x
+
+    Since ``a`` has only 1 term, its value of sort_key is unaffected by
+    ``order``:
+
+    >>> a.sort_key() == a.sort_key('rev-lex')
+    True
+
+    If ``a`` and ``b`` are combined then the key will differ because there
+    are terms that can be ordered:
+
+    >>> eq = a + b
+    >>> eq.sort_key() == eq.sort_key('rev-lex')
+    False
+    >>> eq.as_ordered_terms()
+    [x, 1/x]
+    >>> eq.as_ordered_terms('rev-lex')
+    [1/x, x]
+
+    But since the keys for each of these terms are independent of ``order``'s
+    value, they do not sort differently when they appear separately in a list:
+
+    >>> sorted(eq.args, key=default_sort_key)
+    [1/x, x]
+    >>> sorted(eq.args, key=lambda i: default_sort_key(i, order='rev-lex'))
+    [1/x, x]
+
+    The order of terms obtained when using these keys is the order that would
+    be obtained if those terms were *factors* in a product.
+
+    Although it is useful for quickly putting expressions in canonical order,
+    it does not sort expressions based on their complexity defined by the
+    number of operations, power of variables and others:
+
+    >>> sorted([sin(x)*cos(x), sin(x)], key=default_sort_key)
+    [sin(x)*cos(x), sin(x)]
+    >>> sorted([x, x**2, sqrt(x), x**3], key=default_sort_key)
+    [sqrt(x), x, x**2, x**3]
+
+    See Also
+    ========
+
+    ordered, sympy.core.expr.Expr.as_ordered_factors, sympy.core.expr.Expr.as_ordered_terms
+
+    """
+    from .basic import Basic
+    from .singleton import S
+
+    if isinstance(item, Basic):
+        return item.sort_key(order=order)
+
+    if iterable(item, exclude=str):
+        if isinstance(item, dict):
+            args = item.items()
+            unordered = True
+        elif isinstance(item, set):
+            args = item
+            unordered = True
+        else:
+            # e.g. tuple, list
+            args = list(item)
+            unordered = False
+
+        args = [default_sort_key(arg, order=order) for arg in args]
+
+        if unordered:
+            # e.g. dict, set
+            args = sorted(args)
+
+        cls_index, args = 10, (len(args), tuple(args))
+    else:
+        if not isinstance(item, str):
+            try:
+                item = sympify(item, strict=True)
+            except SympifyError:
+                # e.g. lambda x: x
+                pass
+            else:
+                if isinstance(item, Basic):
+                    # e.g int -> Integer
+                    return default_sort_key(item)
+                # e.g. UndefinedFunction
+
+        # e.g. str
+        cls_index, args = 0, (1, (str(item),))
+
+    return (cls_index, 0, item.__class__.__name__
+            ), args, S.One.sort_key(), S.One
+
+
+def _node_count(e):
+    # this not only counts nodes, it affirms that the
+    # args are Basic (i.e. have an args property). If
+    # some object has a non-Basic arg, it needs to be
+    # fixed since it is intended that all Basic args
+    # are of Basic type (though this is not easy to enforce).
+    if e.is_Float:
+        return 0.5
+    return 1 + sum(map(_node_count, e.args))
+
+
+def _nodes(e):
+    """
+    A helper for ordered() which returns the node count of ``e`` which
+    for Basic objects is the number of Basic nodes in the expression tree
+    but for other objects is 1 (unless the object is an iterable or dict
+    for which the sum of nodes is returned).
+    """
+    from .basic import Basic
+    from .function import Derivative
+
+    if isinstance(e, Basic):
+        if isinstance(e, Derivative):
+            return _nodes(e.expr) + sum(i[1] if i[1].is_Number else
+                _nodes(i[1]) for i in e.variable_count)
+        return _node_count(e)
+    elif iterable(e):
+        return 1 + sum(_nodes(ei) for ei in e)
+    elif isinstance(e, dict):
+        return 1 + sum(_nodes(k) + _nodes(v) for k, v in e.items())
+    else:
+        return 1
+
+
+def ordered(seq, keys=None, default=True, warn=False):
+    """Return an iterator of the seq where keys are used to break ties in
+    a conservative fashion: if, after applying a key, there are no ties
+    then no other keys will be computed.
+
+    Two default keys will be applied if 1) keys are not provided or 2) the
+    given keys do not resolve all ties (but only if ``default`` is True). The
+    two keys are ``_nodes`` (which places smaller expressions before large) and
+    ``default_sort_key`` which (if the ``sort_key`` for an object is defined
+    properly) should resolve any ties.
+
+    If ``warn`` is True then an error will be raised if there were no
+    keys remaining to break ties. This can be used if it was expected that
+    there should be no ties between items that are not identical.
+
+    Examples
+    ========
+
+    >>> from sympy import ordered, count_ops
+    >>> from sympy.abc import x, y
+
+    The count_ops is not sufficient to break ties in this list and the first
+    two items appear in their original order (i.e. the sorting is stable):
+
+    >>> list(ordered([y + 2, x + 2, x**2 + y + 3],
+    ...    count_ops, default=False, warn=False))
+    ...
+    [y + 2, x + 2, x**2 + y + 3]
+
+    The default_sort_key allows the tie to be broken:
+
+    >>> list(ordered([y + 2, x + 2, x**2 + y + 3]))
+    ...
+    [x + 2, y + 2, x**2 + y + 3]
+
+    Here, sequences are sorted by length, then sum:
+
+    >>> seq, keys = [[[1, 2, 1], [0, 3, 1], [1, 1, 3], [2], [1]], [
+    ...    lambda x: len(x),
+    ...    lambda x: sum(x)]]
+    ...
+    >>> list(ordered(seq, keys, default=False, warn=False))
+    [[1], [2], [1, 2, 1], [0, 3, 1], [1, 1, 3]]
+
+    If ``warn`` is True, an error will be raised if there were not
+    enough keys to break ties:
+
+    >>> list(ordered(seq, keys, default=False, warn=True))
+    Traceback (most recent call last):
+    ...
+    ValueError: not enough keys to break ties
+
+
+    Notes
+    =====
+
+    The decorated sort is one of the fastest ways to sort a sequence for
+    which special item comparison is desired: the sequence is decorated,
+    sorted on the basis of the decoration (e.g. making all letters lower
+    case) and then undecorated. If one wants to break ties for items that
+    have the same decorated value, a second key can be used. But if the
+    second key is expensive to compute then it is inefficient to decorate
+    all items with both keys: only those items having identical first key
+    values need to be decorated. This function applies keys successively
+    only when needed to break ties. By yielding an iterator, use of the
+    tie-breaker is delayed as long as possible.
+
+    This function is best used in cases when use of the first key is
+    expected to be a good hashing function; if there are no unique hashes
+    from application of a key, then that key should not have been used. The
+    exception, however, is that even if there are many collisions, if the
+    first group is small and one does not need to process all items in the
+    list then time will not be wasted sorting what one was not interested
+    in. For example, if one were looking for the minimum in a list and
+    there were several criteria used to define the sort order, then this
+    function would be good at returning that quickly if the first group
+    of candidates is small relative to the number of items being processed.
+
+    """
+
+    d = defaultdict(list)
+    if keys:
+        if isinstance(keys, (list, tuple)):
+            keys = list(keys)
+            f = keys.pop(0)
+        else:
+            f = keys
+            keys = []
+        for a in seq:
+            d[f(a)].append(a)
+    else:
+        if not default:
+            raise ValueError('if default=False then keys must be provided')
+        d[None].extend(seq)
+
+    for k, value in sorted(d.items()):
+        if len(value) > 1:
+            if keys:
+                value = ordered(value, keys, default, warn)
+            elif default:
+                value = ordered(value, (_nodes, default_sort_key,),
+                               default=False, warn=warn)
+            elif warn:
+                u = list(uniq(value))
+                if len(u) > 1:
+                    raise ValueError(
+                        'not enough keys to break ties: %s' % u)
+        yield from value

env-llmeval/lib/python3.10/site-packages/sympy/core/sympify.py

@@ -0,0 +1,634 @@
+"""sympify -- convert objects SymPy internal format"""
+
+from __future__ import annotations
+from typing import Any, Callable
+
+from inspect import getmro
+import string
+from sympy.core.random import choice
+
+from .parameters import global_parameters
+
+from sympy.utilities.exceptions import sympy_deprecation_warning
+from sympy.utilities.iterables import iterable
+
+
+class SympifyError(ValueError):
+    def __init__(self, expr, base_exc=None):
+        self.expr = expr
+        self.base_exc = base_exc
+
+    def __str__(self):
+        if self.base_exc is None:
+            return "SympifyError: %r" % (self.expr,)
+
+        return ("Sympify of expression '%s' failed, because of exception being "
+            "raised:\n%s: %s" % (self.expr, self.base_exc.__class__.__name__,
+            str(self.base_exc)))
+
+
+converter: dict[type[Any], Callable[[Any], Basic]] = {}
+
+#holds the conversions defined in SymPy itself, i.e. non-user defined conversions
+_sympy_converter: dict[type[Any], Callable[[Any], Basic]] = {}
+
+#alias for clearer use in the library
+_external_converter = converter
+
+class CantSympify:
+    """
+    Mix in this trait to a class to disallow sympification of its instances.
+
+    Examples
+    ========
+
+    >>> from sympy import sympify
+    >>> from sympy.core.sympify import CantSympify
+
+    >>> class Something(dict):
+    ...     pass
+    ...
+    >>> sympify(Something())
+    {}
+
+    >>> class Something(dict, CantSympify):
+    ...     pass
+    ...
+    >>> sympify(Something())
+    Traceback (most recent call last):
+    ...
+    SympifyError: SympifyError: {}
+
+    """
+
+    __slots__ = ()
+
+
+def _is_numpy_instance(a):
+    """
+    Checks if an object is an instance of a type from the numpy module.
+    """
+    # This check avoids unnecessarily importing NumPy.  We check the whole
+    # __mro__ in case any base type is a numpy type.
+    return any(type_.__module__ == 'numpy'
+               for type_ in type(a).__mro__)
+
+
+def _convert_numpy_types(a, **sympify_args):
+    """
+    Converts a numpy datatype input to an appropriate SymPy type.
+    """
+    import numpy as np
+    if not isinstance(a, np.floating):
+        if np.iscomplex(a):
+            return _sympy_converter[complex](a.item())
+        else:
+            return sympify(a.item(), **sympify_args)
+    else:
+        try:
+            from .numbers import Float
+            prec = np.finfo(a).nmant + 1
+            # E.g. double precision means prec=53 but nmant=52
+            # Leading bit of mantissa is always 1, so is not stored
+            a = str(list(np.reshape(np.asarray(a),
+                                    (1, np.size(a)))[0]))[1:-1]
+            return Float(a, precision=prec)
+        except NotImplementedError:
+            raise SympifyError('Translation for numpy float : %s '
+                               'is not implemented' % a)
+
+
+def sympify(a, locals=None, convert_xor=True, strict=False, rational=False,
+        evaluate=None):
+    """
+    Converts an arbitrary expression to a type that can be used inside SymPy.
+
+    Explanation
+    ===========
+
+    It will convert Python ints into instances of :class:`~.Integer`, floats
+    into instances of :class:`~.Float`, etc. It is also able to coerce
+    symbolic expressions which inherit from :class:`~.Basic`. This can be
+    useful in cooperation with SAGE.
+
+    .. warning::
+        Note that this function uses ``eval``, and thus shouldn't be used on
+        unsanitized input.
+
+    If the argument is already a type that SymPy understands, it will do
+    nothing but return that value. This can be used at the beginning of a
+    function to ensure you are working with the correct type.
+
+    Examples
+    ========
+
+    >>> from sympy import sympify
+
+    >>> sympify(2).is_integer
+    True
+    >>> sympify(2).is_real
+    True
+
+    >>> sympify(2.0).is_real
+    True
+    >>> sympify("2.0").is_real
+    True
+    >>> sympify("2e-45").is_real
+    True
+
+    If the expression could not be converted, a SympifyError is raised.
+
+    >>> sympify("x***2")
+    Traceback (most recent call last):
+    ...
+    SympifyError: SympifyError: "could not parse 'x***2'"
+
+    Locals
+    ------
+
+    The sympification happens with access to everything that is loaded
+    by ``from sympy import *``; anything used in a string that is not
+    defined by that import will be converted to a symbol. In the following,
+    the ``bitcount`` function is treated as a symbol and the ``O`` is
+    interpreted as the :class:`~.Order` object (used with series) and it raises
+    an error when used improperly:
+
+    >>> s = 'bitcount(42)'
+    >>> sympify(s)
+    bitcount(42)
+    >>> sympify("O(x)")
+    O(x)
+    >>> sympify("O + 1")
+    Traceback (most recent call last):
+    ...
+    TypeError: unbound method...
+
+    In order to have ``bitcount`` be recognized it can be imported into a
+    namespace dictionary and passed as locals:
+
+    >>> ns = {}
+    >>> exec('from sympy.core.evalf import bitcount', ns)
+    >>> sympify(s, locals=ns)
+    6
+
+    In order to have the ``O`` interpreted as a Symbol, identify it as such
+    in the namespace dictionary. This can be done in a variety of ways; all
+    three of the following are possibilities:
+
+    >>> from sympy import Symbol
+    >>> ns["O"] = Symbol("O")  # method 1
+    >>> exec('from sympy.abc import O', ns)  # method 2
+    >>> ns.update(dict(O=Symbol("O")))  # method 3
+    >>> sympify("O + 1", locals=ns)
+    O + 1
+
+    If you want *all* single-letter and Greek-letter variables to be symbols
+    then you can use the clashing-symbols dictionaries that have been defined
+    there as private variables: ``_clash1`` (single-letter variables),
+    ``_clash2`` (the multi-letter Greek names) or ``_clash`` (both single and
+    multi-letter names that are defined in ``abc``).
+
+    >>> from sympy.abc import _clash1
+    >>> set(_clash1)  # if this fails, see issue #23903
+    {'E', 'I', 'N', 'O', 'Q', 'S'}
+    >>> sympify('I & Q', _clash1)
+    I & Q
+
+    Strict
+    ------
+
+    If the option ``strict`` is set to ``True``, only the types for which an
+    explicit conversion has been defined are converted. In the other
+    cases, a SympifyError is raised.
+
+    >>> print(sympify(None))
+    None
+    >>> sympify(None, strict=True)
+    Traceback (most recent call last):
+    ...
+    SympifyError: SympifyError: None
+
+    .. deprecated:: 1.6
+
+       ``sympify(obj)`` automatically falls back to ``str(obj)`` when all
+       other conversion methods fail, but this is deprecated. ``strict=True``
+       will disable this deprecated behavior. See
+       :ref:`deprecated-sympify-string-fallback`.
+
+    Evaluation
+    ----------
+
+    If the option ``evaluate`` is set to ``False``, then arithmetic and
+    operators will be converted into their SymPy equivalents and the
+    ``evaluate=False`` option will be added. Nested ``Add`` or ``Mul`` will
+    be denested first. This is done via an AST transformation that replaces
+    operators with their SymPy equivalents, so if an operand redefines any
+    of those operations, the redefined operators will not be used. If
+    argument a is not a string, the mathematical expression is evaluated
+    before being passed to sympify, so adding ``evaluate=False`` will still
+    return the evaluated result of expression.
+
+    >>> sympify('2**2 / 3 + 5')
+    19/3
+    >>> sympify('2**2 / 3 + 5', evaluate=False)
+    2**2/3 + 5
+    >>> sympify('4/2+7', evaluate=True)
+    9
+    >>> sympify('4/2+7', evaluate=False)
+    4/2 + 7
+    >>> sympify(4/2+7, evaluate=False)
+    9.00000000000000
+
+    Extending
+    ---------
+
+    To extend ``sympify`` to convert custom objects (not derived from ``Basic``),
+    just define a ``_sympy_`` method to your class. You can do that even to
+    classes that you do not own by subclassing or adding the method at runtime.
+
+    >>> from sympy import Matrix
+    >>> class MyList1(object):
+    ...     def __iter__(self):
+    ...         yield 1
+    ...         yield 2
+    ...         return
+    ...     def __getitem__(self, i): return list(self)[i]
+    ...     def _sympy_(self): return Matrix(self)
+    >>> sympify(MyList1())
+    Matrix([
+    [1],
+    [2]])
+
+    If you do not have control over the class definition you could also use the
+    ``converter`` global dictionary. The key is the class and the value is a
+    function that takes a single argument and returns the desired SymPy
+    object, e.g. ``converter[MyList] = lambda x: Matrix(x)``.
+
+    >>> class MyList2(object):   # XXX Do not do this if you control the class!
+    ...     def __iter__(self):  #     Use _sympy_!
+    ...         yield 1
+    ...         yield 2
+    ...         return
+    ...     def __getitem__(self, i): return list(self)[i]
+    >>> from sympy.core.sympify import converter
+    >>> converter[MyList2] = lambda x: Matrix(x)
+    >>> sympify(MyList2())
+    Matrix([
+    [1],
+    [2]])
+
+    Notes
+    =====
+
+    The keywords ``rational`` and ``convert_xor`` are only used
+    when the input is a string.
+
+    convert_xor
+    -----------
+
+    >>> sympify('x^y',convert_xor=True)
+    x**y
+    >>> sympify('x^y',convert_xor=False)
+    x ^ y
+
+    rational
+    --------
+
+    >>> sympify('0.1',rational=False)
+    0.1
+    >>> sympify('0.1',rational=True)
+    1/10
+
+    Sometimes autosimplification during sympification results in expressions
+    that are very different in structure than what was entered. Until such
+    autosimplification is no longer done, the ``kernS`` function might be of
+    some use. In the example below you can see how an expression reduces to
+    $-1$ by autosimplification, but does not do so when ``kernS`` is used.
+
+    >>> from sympy.core.sympify import kernS
+    >>> from sympy.abc import x
+    >>> -2*(-(-x + 1/x)/(x*(x - 1/x)**2) - 1/(x*(x - 1/x))) - 1
+    -1
+    >>> s = '-2*(-(-x + 1/x)/(x*(x - 1/x)**2) - 1/(x*(x - 1/x))) - 1'
+    >>> sympify(s)
+    -1
+    >>> kernS(s)
+    -2*(-(-x + 1/x)/(x*(x - 1/x)**2) - 1/(x*(x - 1/x))) - 1
+
+    Parameters
+    ==========
+
+    a :
+        - any object defined in SymPy
+        - standard numeric Python types: ``int``, ``long``, ``float``, ``Decimal``
+        - strings (like ``"0.09"``, ``"2e-19"`` or ``'sin(x)'``)
+        - booleans, including ``None`` (will leave ``None`` unchanged)
+        - dicts, lists, sets or tuples containing any of the above
+
+    convert_xor : bool, optional
+        If true, treats ``^`` as exponentiation.
+        If False, treats ``^`` as XOR itself.
+        Used only when input is a string.
+
+    locals : any object defined in SymPy, optional
+        In order to have strings be recognized it can be imported
+        into a namespace dictionary and passed as locals.
+
+    strict : bool, optional
+        If the option strict is set to ``True``, only the types for which
+        an explicit conversion has been defined are converted. In the
+        other cases, a SympifyError is raised.
+
+    rational : bool, optional
+        If ``True``, converts floats into :class:`~.Rational`.
+        If ``False``, it lets floats remain as it is.
+        Used only when input is a string.
+
+    evaluate : bool, optional
+        If False, then arithmetic and operators will be converted into
+        their SymPy equivalents. If True the expression will be evaluated
+        and the result will be returned.
+
+    """
+    # XXX: If a is a Basic subclass rather than instance (e.g. sin rather than
+    # sin(x)) then a.__sympy__ will be the property. Only on the instance will
+    # a.__sympy__ give the *value* of the property (True). Since sympify(sin)
+    # was used for a long time we allow it to pass. However if strict=True as
+    # is the case in internal calls to _sympify then we only allow
+    # is_sympy=True.
+    #
+    # https://github.com/sympy/sympy/issues/20124
+    is_sympy = getattr(a, '__sympy__', None)
+    if is_sympy is True:
+        return a
+    elif is_sympy is not None:
+        if not strict:
+            return a
+        else:
+            raise SympifyError(a)
+
+    if isinstance(a, CantSympify):
+        raise SympifyError(a)
+
+    cls = getattr(a, "__class__", None)
+
+    #Check if there exists a converter for any of the types in the mro
+    for superclass in getmro(cls):
+        #First check for user defined converters
+        conv = _external_converter.get(superclass)
+        if conv is None:
+            #if none exists, check for SymPy defined converters
+            conv = _sympy_converter.get(superclass)
+        if conv is not None:
+            return conv(a)
+
+    if cls is type(None):
+        if strict:
+            raise SympifyError(a)
+        else:
+            return a
+
+    if evaluate is None:
+        evaluate = global_parameters.evaluate
+
+    # Support for basic numpy datatypes
+    if _is_numpy_instance(a):
+        import numpy as np
+        if np.isscalar(a):
+            return _convert_numpy_types(a, locals=locals,
+                convert_xor=convert_xor, strict=strict, rational=rational,
+                evaluate=evaluate)
+
+    _sympy_ = getattr(a, "_sympy_", None)
+    if _sympy_ is not None:
+        try:
+            return a._sympy_()
+        # XXX: Catches AttributeError: 'SymPyConverter' object has no
+        # attribute 'tuple'
+        # This is probably a bug somewhere but for now we catch it here.
+        except AttributeError:
+            pass
+
+    if not strict:
+        # Put numpy array conversion _before_ float/int, see
+        # <https://github.com/sympy/sympy/issues/13924>.
+        flat = getattr(a, "flat", None)
+        if flat is not None:
+            shape = getattr(a, "shape", None)
+            if shape is not None:
+                from sympy.tensor.array import Array
+                return Array(a.flat, a.shape)  # works with e.g. NumPy arrays
+
+    if not isinstance(a, str):
+        if _is_numpy_instance(a):
+            import numpy as np
+            assert not isinstance(a, np.number)
+            if isinstance(a, np.ndarray):
+                # Scalar arrays (those with zero dimensions) have sympify
+                # called on the scalar element.
+                if a.ndim == 0:
+                    try:
+                        return sympify(a.item(),
+                                       locals=locals,
+                                       convert_xor=convert_xor,
+                                       strict=strict,
+                                       rational=rational,
+                                       evaluate=evaluate)
+                    except SympifyError:
+                        pass
+        else:
+            # float and int can coerce size-one numpy arrays to their lone
+            # element.  See issue https://github.com/numpy/numpy/issues/10404.
+            for coerce in (float, int):
+                try:
+                    return sympify(coerce(a))
+                except (TypeError, ValueError, AttributeError, SympifyError):
+                    continue
+
+    if strict:
+        raise SympifyError(a)
+
+    if iterable(a):
+        try:
+            return type(a)([sympify(x, locals=locals, convert_xor=convert_xor,
+                rational=rational, evaluate=evaluate) for x in a])
+        except TypeError:
+            # Not all iterables are rebuildable with their type.
+            pass
+
+    if not isinstance(a, str):
+        try:
+            a = str(a)
+        except Exception as exc:
+            raise SympifyError(a, exc)
+        sympy_deprecation_warning(
+            f"""
+The string fallback in sympify() is deprecated.
+
+To explicitly convert the string form of an object, use
+sympify(str(obj)). To add define sympify behavior on custom
+objects, use sympy.core.sympify.converter or define obj._sympy_
+(see the sympify() docstring).
+
+sympify() performed the string fallback resulting in the following string:
+
+{a!r}
+            """,
+            deprecated_since_version='1.6',
+            active_deprecations_target="deprecated-sympify-string-fallback",
+        )
+
+    from sympy.parsing.sympy_parser import (parse_expr, TokenError,
+                                            standard_transformations)
+    from sympy.parsing.sympy_parser import convert_xor as t_convert_xor
+    from sympy.parsing.sympy_parser import rationalize as t_rationalize
+
+    transformations = standard_transformations
+
+    if rational:
+        transformations += (t_rationalize,)
+    if convert_xor:
+        transformations += (t_convert_xor,)
+
+    try:
+        a = a.replace('\n', '')
+        expr = parse_expr(a, local_dict=locals, transformations=transformations, evaluate=evaluate)
+    except (TokenError, SyntaxError) as exc:
+        raise SympifyError('could not parse %r' % a, exc)
+
+    return expr
+
+
+def _sympify(a):
+    """
+    Short version of :func:`~.sympify` for internal usage for ``__add__`` and
+    ``__eq__`` methods where it is ok to allow some things (like Python
+    integers and floats) in the expression. This excludes things (like strings)
+    that are unwise to allow into such an expression.
+
+    >>> from sympy import Integer
+    >>> Integer(1) == 1
+    True
+
+    >>> Integer(1) == '1'
+    False
+
+    >>> from sympy.abc import x
+    >>> x + 1
+    x + 1
+
+    >>> x + '1'
+    Traceback (most recent call last):
+    ...
+    TypeError: unsupported operand type(s) for +: 'Symbol' and 'str'
+
+    see: sympify
+
+    """
+    return sympify(a, strict=True)
+
+
+def kernS(s):
+    """Use a hack to try keep autosimplification from distributing a
+    a number into an Add; this modification does not
+    prevent the 2-arg Mul from becoming an Add, however.
+
+    Examples
+    ========
+
+    >>> from sympy.core.sympify import kernS
+    >>> from sympy.abc import x, y
+
+    The 2-arg Mul distributes a number (or minus sign) across the terms
+    of an expression, but kernS will prevent that:
+
+    >>> 2*(x + y), -(x + 1)
+    (2*x + 2*y, -x - 1)
+    >>> kernS('2*(x + y)')
+    2*(x + y)
+    >>> kernS('-(x + 1)')
+    -(x + 1)
+
+    If use of the hack fails, the un-hacked string will be passed to sympify...
+    and you get what you get.
+
+    XXX This hack should not be necessary once issue 4596 has been resolved.
+    """
+    hit = False
+    quoted = '"' in s or "'" in s
+    if '(' in s and not quoted:
+        if s.count('(') != s.count(")"):
+            raise SympifyError('unmatched left parenthesis')
+
+        # strip all space from s
+        s = ''.join(s.split())
+        olds = s
+        # now use space to represent a symbol that
+        # will
+        # step 1. turn potential 2-arg Muls into 3-arg versions
+        # 1a. *( -> * *(
+        s = s.replace('*(', '* *(')
+        # 1b. close up exponentials
+        s = s.replace('** *', '**')
+        # 2. handle the implied multiplication of a negated
+        # parenthesized expression in two steps
+        # 2a:  -(...)  -->  -( *(...)
+        target = '-( *('
+        s = s.replace('-(', target)
+        # 2b: double the matching closing parenthesis
+        # -( *(...)  -->  -( *(...))
+        i = nest = 0
+        assert target.endswith('(')  # assumption below
+        while True:
+            j = s.find(target, i)
+            if j == -1:
+                break
+            j += len(target) - 1
+            for j in range(j, len(s)):
+                if s[j] == "(":
+                    nest += 1
+                elif s[j] == ")":
+                    nest -= 1
+                if nest == 0:
+                    break
+            s = s[:j] + ")" + s[j:]
+            i = j + 2  # the first char after 2nd )
+        if ' ' in s:
+            # get a unique kern
+            kern = '_'
+            while kern in s:
+                kern += choice(string.ascii_letters + string.digits)
+            s = s.replace(' ', kern)
+            hit = kern in s
+        else:
+            hit = False
+
+    for i in range(2):
+        try:
+            expr = sympify(s)
+            break
+        except TypeError:  # the kern might cause unknown errors...
+            if hit:
+                s = olds  # maybe it didn't like the kern; use un-kerned s
+                hit = False
+                continue
+            expr = sympify(s)  # let original error raise
+
+    if not hit:
+        return expr
+
+    from .symbol import Symbol
+    rep = {Symbol(kern): 1}
+    def _clear(expr):
+        if isinstance(expr, (list, tuple, set)):
+            return type(expr)([_clear(e) for e in expr])
+        if hasattr(expr, 'subs'):
+            return expr.subs(rep, hack2=True)
+        return expr
+    expr = _clear(expr)
+    # hope that kern is not there anymore
+    return expr
+
+
+# Avoid circular import
+from .basic import Basic

env-llmeval/lib/python3.10/site-packages/sympy/core/tests/test_arit.py

@@ -0,0 +1,2463 @@
+from sympy.core.add import Add
+from sympy.core.basic import Basic
+from sympy.core.mod import Mod
+from sympy.core.mul import Mul
+from sympy.core.numbers import (Float, I, Integer, Rational, comp, nan,
+    oo, pi, zoo)
+from sympy.core.power import Pow
+from sympy.core.singleton import S
+from sympy.core.symbol import (Dummy, Symbol, symbols)
+from sympy.core.sympify import sympify
+from sympy.functions.combinatorial.factorials import factorial
+from sympy.functions.elementary.complexes import (im, re, sign)
+from sympy.functions.elementary.exponential import (exp, log)
+from sympy.functions.elementary.integers import floor
+from sympy.functions.elementary.miscellaneous import (Max, sqrt)
+from sympy.functions.elementary.trigonometric import (atan, cos, sin)
+from sympy.polys.polytools import Poly
+from sympy.sets.sets import FiniteSet
+
+from sympy.core.parameters import distribute, evaluate
+from sympy.core.expr import unchanged
+from sympy.utilities.iterables import permutations
+from sympy.testing.pytest import XFAIL, raises, warns
+from sympy.utilities.exceptions import SymPyDeprecationWarning
+from sympy.core.random import verify_numerically
+from sympy.functions.elementary.trigonometric import asin
+
+from itertools import product
+
+a, c, x, y, z = symbols('a,c,x,y,z')
+b = Symbol("b", positive=True)
+
+
+def same_and_same_prec(a, b):
+    # stricter matching for Floats
+    return a == b and a._prec == b._prec
+
+
+def test_bug1():
+    assert re(x) != x
+    x.series(x, 0, 1)
+    assert re(x) != x
+
+
+def test_Symbol():
+    e = a*b
+    assert e == a*b
+    assert a*b*b == a*b**2
+    assert a*b*b + c == c + a*b**2
+    assert a*b*b - c == -c + a*b**2
+
+    x = Symbol('x', complex=True, real=False)
+    assert x.is_imaginary is None  # could be I or 1 + I
+    x = Symbol('x', complex=True, imaginary=False)
+    assert x.is_real is None  # could be 1 or 1 + I
+    x = Symbol('x', real=True)
+    assert x.is_complex
+    x = Symbol('x', imaginary=True)
+    assert x.is_complex
+    x = Symbol('x', real=False, imaginary=False)
+    assert x.is_complex is None  # might be a non-number
+
+
+def test_arit0():
+    p = Rational(5)
+    e = a*b
+    assert e == a*b
+    e = a*b + b*a
+    assert e == 2*a*b
+    e = a*b + b*a + a*b + p*b*a
+    assert e == 8*a*b
+    e = a*b + b*a + a*b + p*b*a + a
+    assert e == a + 8*a*b
+    e = a + a
+    assert e == 2*a
+    e = a + b + a
+    assert e == b + 2*a
+    e = a + b*b + a + b*b
+    assert e == 2*a + 2*b**2
+    e = a + Rational(2) + b*b + a + b*b + p
+    assert e == 7 + 2*a + 2*b**2
+    e = (a + b*b + a + b*b)*p
+    assert e == 5*(2*a + 2*b**2)
+    e = (a*b*c + c*b*a + b*a*c)*p
+    assert e == 15*a*b*c
+    e = (a*b*c + c*b*a + b*a*c)*p - Rational(15)*a*b*c
+    assert e == Rational(0)
+    e = Rational(50)*(a - a)
+    assert e == Rational(0)
+    e = b*a - b - a*b + b
+    assert e == Rational(0)
+    e = a*b + c**p
+    assert e == a*b + c**5
+    e = a/b
+    assert e == a*b**(-1)
+    e = a*2*2
+    assert e == 4*a
+    e = 2 + a*2/2
+    assert e == 2 + a
+    e = 2 - a - 2
+    assert e == -a
+    e = 2*a*2
+    assert e == 4*a
+    e = 2/a/2
+    assert e == a**(-1)
+    e = 2**a**2
+    assert e == 2**(a**2)
+    e = -(1 + a)
+    assert e == -1 - a
+    e = S.Half*(1 + a)
+    assert e == S.Half + a/2
+
+
+def test_div():
+    e = a/b
+    assert e == a*b**(-1)
+    e = a/b + c/2
+    assert e == a*b**(-1) + Rational(1)/2*c
+    e = (1 - b)/(b - 1)
+    assert e == (1 + -b)*((-1) + b)**(-1)
+
+
+def test_pow_arit():
+    n1 = Rational(1)
+    n2 = Rational(2)
+    n5 = Rational(5)
+    e = a*a
+    assert e == a**2
+    e = a*a*a
+    assert e == a**3
+    e = a*a*a*a**Rational(6)
+    assert e == a**9
+    e = a*a*a*a**Rational(6) - a**Rational(9)
+    assert e == Rational(0)
+    e = a**(b - b)
+    assert e == Rational(1)
+    e = (a + Rational(1) - a)**b
+    assert e == Rational(1)
+
+    e = (a + b + c)**n2
+    assert e == (a + b + c)**2
+    assert e.expand() == 2*b*c + 2*a*c + 2*a*b + a**2 + c**2 + b**2
+
+    e = (a + b)**n2
+    assert e == (a + b)**2
+    assert e.expand() == 2*a*b + a**2 + b**2
+
+    e = (a + b)**(n1/n2)
+    assert e == sqrt(a + b)
+    assert e.expand() == sqrt(a + b)
+
+    n = n5**(n1/n2)
+    assert n == sqrt(5)
+    e = n*a*b - n*b*a
+    assert e == Rational(0)
+    e = n*a*b + n*b*a
+    assert e == 2*a*b*sqrt(5)
+    assert e.diff(a) == 2*b*sqrt(5)
+    assert e.diff(a) == 2*b*sqrt(5)
+    e = a/b**2
+    assert e == a*b**(-2)
+
+    assert sqrt(2*(1 + sqrt(2))) == (2*(1 + 2**S.Half))**S.Half
+
+    x = Symbol('x')
+    y = Symbol('y')
+
+    assert ((x*y)**3).expand() == y**3 * x**3
+    assert ((x*y)**-3).expand() == y**-3 * x**-3
+
+    assert (x**5*(3*x)**(3)).expand() == 27 * x**8
+    assert (x**5*(-3*x)**(3)).expand() == -27 * x**8
+    assert (x**5*(3*x)**(-3)).expand() == x**2 * Rational(1, 27)
+    assert (x**5*(-3*x)**(-3)).expand() == x**2 * Rational(-1, 27)
+
+    # expand_power_exp
+    _x = Symbol('x', zero=False)
+    _y = Symbol('y', zero=False)
+    assert (_x**(y**(x + exp(x + y)) + z)).expand(deep=False) == \
+        _x**z*_x**(y**(x + exp(x + y)))
+    assert (_x**(_y**(x + exp(x + y)) + z)).expand() == \
+        _x**z*_x**(_y**x*_y**(exp(x)*exp(y)))
+
+    n = Symbol('n', even=False)
+    k = Symbol('k', even=True)
+    o = Symbol('o', odd=True)
+
+    assert unchanged(Pow, -1, x)
+    assert unchanged(Pow, -1, n)
+    assert (-2)**k == 2**k
+    assert (-1)**k == 1
+    assert (-1)**o == -1
+
+
+def test_pow2():
+    # x**(2*y) is always (x**y)**2 but is only (x**2)**y if
+    #                                  x.is_positive or y.is_integer
+    # let x = 1 to see why the following are not true.
+    assert (-x)**Rational(2, 3) != x**Rational(2, 3)
+    assert (-x)**Rational(5, 7) != -x**Rational(5, 7)
+    assert ((-x)**2)**Rational(1, 3) != ((-x)**Rational(1, 3))**2
+    assert sqrt(x**2) != x
+
+
+def test_pow3():
+    assert sqrt(2)**3 == 2 * sqrt(2)
+    assert sqrt(2)**3 == sqrt(8)
+
+
+def test_mod_pow():
+    for s, t, u, v in [(4, 13, 497, 445), (4, -3, 497, 365),
+            (3.2, 2.1, 1.9, 0.1031015682350942), (S(3)/2, 5, S(5)/6, S(3)/32)]:
+        assert pow(S(s), t, u) == v
+        assert pow(S(s), S(t), u) == v
+        assert pow(S(s), t, S(u)) == v
+        assert pow(S(s), S(t), S(u)) == v
+    assert pow(S(2), S(10000000000), S(3)) == 1
+    assert pow(x, y, z) == x**y%z
+    raises(TypeError, lambda: pow(S(4), "13", 497))
+    raises(TypeError, lambda: pow(S(4), 13, "497"))
+
+
+def test_pow_E():
+    assert 2**(y/log(2)) == S.Exp1**y
+    assert 2**(y/log(2)/3) == S.Exp1**(y/3)
+    assert 3**(1/log(-3)) != S.Exp1
+    assert (3 + 2*I)**(1/(log(-3 - 2*I) + I*pi)) == S.Exp1
+    assert (4 + 2*I)**(1/(log(-4 - 2*I) + I*pi)) == S.Exp1
+    assert (3 + 2*I)**(1/(log(-3 - 2*I, 3)/2 + I*pi/log(3)/2)) == 9
+    assert (3 + 2*I)**(1/(log(3 + 2*I, 3)/2)) == 9
+    # every time tests are run they will affirm with a different random
+    # value that this identity holds
+    while 1:
+        b = x._random()
+        r, i = b.as_real_imag()
+        if i:
+            break
+    assert verify_numerically(b**(1/(log(-b) + sign(i)*I*pi).n()), S.Exp1)
+
+
+def test_pow_issue_3516():
+    assert 4**Rational(1, 4) == sqrt(2)
+
+
+def test_pow_im():
+    for m in (-2, -1, 2):
+        for d in (3, 4, 5):
+            b = m*I
+            for i in range(1, 4*d + 1):
+                e = Rational(i, d)
+                assert (b**e - b.n()**e.n()).n(2, chop=1e-10) == 0
+
+    e = Rational(7, 3)
+    assert (2*x*I)**e == 4*2**Rational(1, 3)*(I*x)**e  # same as Wolfram Alpha
+    im = symbols('im', imaginary=True)
+    assert (2*im*I)**e == 4*2**Rational(1, 3)*(I*im)**e
+
+    args = [I, I, I, I, 2]
+    e = Rational(1, 3)
+    ans = 2**e
+    assert Mul(*args, evaluate=False)**e == ans
+    assert Mul(*args)**e == ans
+    args = [I, I, I, 2]
+    e = Rational(1, 3)
+    ans = 2**e*(-I)**e
+    assert Mul(*args, evaluate=False)**e == ans
+    assert Mul(*args)**e == ans
+    args.append(-3)
+    ans = (6*I)**e
+    assert Mul(*args, evaluate=False)**e == ans
+    assert Mul(*args)**e == ans
+    args.append(-1)
+    ans = (-6*I)**e
+    assert Mul(*args, evaluate=False)**e == ans
+    assert Mul(*args)**e == ans
+
+    args = [I, I, 2]
+    e = Rational(1, 3)
+    ans = (-2)**e
+    assert Mul(*args, evaluate=False)**e == ans
+    assert Mul(*args)**e == ans
+    args.append(-3)
+    ans = (6)**e
+    assert Mul(*args, evaluate=False)**e == ans
+    assert Mul(*args)**e == ans
+    args.append(-1)
+    ans = (-6)**e
+    assert Mul(*args, evaluate=False)**e == ans
+    assert Mul(*args)**e == ans
+    assert Mul(Pow(-1, Rational(3, 2), evaluate=False), I, I) == I
+    assert Mul(I*Pow(I, S.Half, evaluate=False)) == sqrt(I)*I
+
+
+def test_real_mul():
+    assert Float(0) * pi * x == 0
+    assert set((Float(1) * pi * x).args) == {Float(1), pi, x}
+
+
+def test_ncmul():
+    A = Symbol("A", commutative=False)
+    B = Symbol("B", commutative=False)
+    C = Symbol("C", commutative=False)
+    assert A*B != B*A
+    assert A*B*C != C*B*A
+    assert A*b*B*3*C == 3*b*A*B*C
+    assert A*b*B*3*C != 3*b*B*A*C
+    assert A*b*B*3*C == 3*A*B*C*b
+
+    assert A + B == B + A
+    assert (A + B)*C != C*(A + B)
+
+    assert C*(A + B)*C != C*C*(A + B)
+
+    assert A*A == A**2
+    assert (A + B)*(A + B) == (A + B)**2
+
+    assert A**-1 * A == 1
+    assert A/A == 1
+    assert A/(A**2) == 1/A
+
+    assert A/(1 + A) == A/(1 + A)
+
+    assert set((A + B + 2*(A + B)).args) == \
+        {A, B, 2*(A + B)}
+
+
+def test_mul_add_identity():
+    m = Mul(1, 2)
+    assert isinstance(m, Rational) and m.p == 2 and m.q == 1
+    m = Mul(1, 2, evaluate=False)
+    assert isinstance(m, Mul) and m.args == (1, 2)
+    m = Mul(0, 1)
+    assert m is S.Zero
+    m = Mul(0, 1, evaluate=False)
+    assert isinstance(m, Mul) and m.args == (0, 1)
+    m = Add(0, 1)
+    assert m is S.One
+    m = Add(0, 1, evaluate=False)
+    assert isinstance(m, Add) and m.args == (0, 1)
+
+
+def test_ncpow():
+    x = Symbol('x', commutative=False)
+    y = Symbol('y', commutative=False)
+    z = Symbol('z', commutative=False)
+    a = Symbol('a')
+    b = Symbol('b')
+    c = Symbol('c')
+
+    assert (x**2)*(y**2) != (y**2)*(x**2)
+    assert (x**-2)*y != y*(x**2)
+    assert 2**x*2**y != 2**(x + y)
+    assert 2**x*2**y*2**z != 2**(x + y + z)
+    assert 2**x*2**(2*x) == 2**(3*x)
+    assert 2**x*2**(2*x)*2**x == 2**(4*x)
+    assert exp(x)*exp(y) != exp(y)*exp(x)
+    assert exp(x)*exp(y)*exp(z) != exp(y)*exp(x)*exp(z)
+    assert exp(x)*exp(y)*exp(z) != exp(x + y + z)
+    assert x**a*x**b != x**(a + b)
+    assert x**a*x**b*x**c != x**(a + b + c)
+    assert x**3*x**4 == x**7
+    assert x**3*x**4*x**2 == x**9
+    assert x**a*x**(4*a) == x**(5*a)
+    assert x**a*x**(4*a)*x**a == x**(6*a)
+
+
+def test_powerbug():
+    x = Symbol("x")
+    assert x**1 != (-x)**1
+    assert x**2 == (-x)**2
+    assert x**3 != (-x)**3
+    assert x**4 == (-x)**4
+    assert x**5 != (-x)**5
+    assert x**6 == (-x)**6
+
+    assert x**128 == (-x)**128
+    assert x**129 != (-x)**129
+
+    assert (2*x)**2 == (-2*x)**2
+
+
+def test_Mul_doesnt_expand_exp():
+    x = Symbol('x')
+    y = Symbol('y')
+    assert unchanged(Mul, exp(x), exp(y))
+    assert unchanged(Mul, 2**x, 2**y)
+    assert x**2*x**3 == x**5
+    assert 2**x*3**x == 6**x
+    assert x**(y)*x**(2*y) == x**(3*y)
+    assert sqrt(2)*sqrt(2) == 2
+    assert 2**x*2**(2*x) == 2**(3*x)
+    assert sqrt(2)*2**Rational(1, 4)*5**Rational(3, 4) == 10**Rational(3, 4)
+    assert (x**(-log(5)/log(3))*x)/(x*x**( - log(5)/log(3))) == sympify(1)
+
+
+def test_Mul_is_integer():
+    k = Symbol('k', integer=True)
+    n = Symbol('n', integer=True)
+    nr = Symbol('nr', rational=False)
+    ir = Symbol('ir', irrational=True)
+    nz = Symbol('nz', integer=True, zero=False)
+    e = Symbol('e', even=True)
+    o = Symbol('o', odd=True)
+    i2 = Symbol('2', prime=True, even=True)
+
+    assert (k/3).is_integer is None
+    assert (nz/3).is_integer is None
+    assert (nr/3).is_integer is False
+    assert (ir/3).is_integer is False
+    assert (x*k*n).is_integer is None
+    assert (e/2).is_integer is True
+    assert (e**2/2).is_integer is True
+    assert (2/k).is_integer is None
+    assert (2/k**2).is_integer is None
+    assert ((-1)**k*n).is_integer is True
+    assert (3*k*e/2).is_integer is True
+    assert (2*k*e/3).is_integer is None
+    assert (e/o).is_integer is None
+    assert (o/e).is_integer is False
+    assert (o/i2).is_integer is False
+    assert Mul(k, 1/k, evaluate=False).is_integer is None
+    assert Mul(2., S.Half, evaluate=False).is_integer is None
+    assert (2*sqrt(k)).is_integer is None
+    assert (2*k**n).is_integer is None
+
+    s = 2**2**2**Pow(2, 1000, evaluate=False)
+    m = Mul(s, s, evaluate=False)
+    assert m.is_integer
+
+    # broken in 1.6 and before, see #20161
+    xq = Symbol('xq', rational=True)
+    yq = Symbol('yq', rational=True)
+    assert (xq*yq).is_integer is None
+    e_20161 = Mul(-1,Mul(1,Pow(2,-1,evaluate=False),evaluate=False),evaluate=False)
+    assert e_20161.is_integer is not True # expand(e_20161) -> -1/2, but no need to see that in the assumption without evaluation
+
+
+def test_Add_Mul_is_integer():
+    x = Symbol('x')
+
+    k = Symbol('k', integer=True)
+    n = Symbol('n', integer=True)
+    nk = Symbol('nk', integer=False)
+    nr = Symbol('nr', rational=False)
+    nz = Symbol('nz', integer=True, zero=False)
+
+    assert (-nk).is_integer is None
+    assert (-nr).is_integer is False
+    assert (2*k).is_integer is True
+    assert (-k).is_integer is True
+
+    assert (k + nk).is_integer is False
+    assert (k + n).is_integer is True
+    assert (k + x).is_integer is None
+    assert (k + n*x).is_integer is None
+    assert (k + n/3).is_integer is None
+    assert (k + nz/3).is_integer is None
+    assert (k + nr/3).is_integer is False
+
+    assert ((1 + sqrt(3))*(-sqrt(3) + 1)).is_integer is not False
+    assert (1 + (1 + sqrt(3))*(-sqrt(3) + 1)).is_integer is not False
+
+
+def test_Add_Mul_is_finite():
+    x = Symbol('x', extended_real=True, finite=False)
+
+    assert sin(x).is_finite is True
+    assert (x*sin(x)).is_finite is None
+    assert (x*atan(x)).is_finite is False
+    assert (1024*sin(x)).is_finite is True
+    assert (sin(x)*exp(x)).is_finite is None
+    assert (sin(x)*cos(x)).is_finite is True
+    assert (x*sin(x)*exp(x)).is_finite is None
+
+    assert (sin(x) - 67).is_finite is True
+    assert (sin(x) + exp(x)).is_finite is not True
+    assert (1 + x).is_finite is False
+    assert (1 + x**2 + (1 + x)*(1 - x)).is_finite is None
+    assert (sqrt(2)*(1 + x)).is_finite is False
+    assert (sqrt(2)*(1 + x)*(1 - x)).is_finite is False
+
+
+def test_Mul_is_even_odd():
+    x = Symbol('x', integer=True)
+    y = Symbol('y', integer=True)
+
+    k = Symbol('k', odd=True)
+    n = Symbol('n', odd=True)
+    m = Symbol('m', even=True)
+
+    assert (2*x).is_even is True
+    assert (2*x).is_odd is False
+
+    assert (3*x).is_even is None
+    assert (3*x).is_odd is None
+
+    assert (k/3).is_integer is None
+    assert (k/3).is_even is None
+    assert (k/3).is_odd is None
+
+    assert (2*n).is_even is True
+    assert (2*n).is_odd is False
+
+    assert (2*m).is_even is True
+    assert (2*m).is_odd is False
+
+    assert (-n).is_even is False
+    assert (-n).is_odd is True
+
+    assert (k*n).is_even is False
+    assert (k*n).is_odd is True
+
+    assert (k*m).is_even is True
+    assert (k*m).is_odd is False
+
+    assert (k*n*m).is_even is True
+    assert (k*n*m).is_odd is False
+
+    assert (k*m*x).is_even is True
+    assert (k*m*x).is_odd is False
+
+    # issue 6791:
+    assert (x/2).is_integer is None
+    assert (k/2).is_integer is False
+    assert (m/2).is_integer is True
+
+    assert (x*y).is_even is None
+    assert (x*x).is_even is None
+    assert (x*(x + k)).is_even is True
+    assert (x*(x + m)).is_even is None
+
+    assert (x*y).is_odd is None
+    assert (x*x).is_odd is None
+    assert (x*(x + k)).is_odd is False
+    assert (x*(x + m)).is_odd is None
+
+    # issue 8648
+    assert (m**2/2).is_even
+    assert (m**2/3).is_even is False
+    assert (2/m**2).is_odd is False
+    assert (2/m).is_odd is None
+
+
+@XFAIL
+def test_evenness_in_ternary_integer_product_with_odd():
+    # Tests that oddness inference is independent of term ordering.
+    # Term ordering at the point of testing depends on SymPy's symbol order, so
+    # we try to force a different order by modifying symbol names.
+    x = Symbol('x', integer=True)
+    y = Symbol('y', integer=True)
+    k = Symbol('k', odd=True)
+    assert (x*y*(y + k)).is_even is True
+    assert (y*x*(x + k)).is_even is True
+
+
+def test_evenness_in_ternary_integer_product_with_even():
+    x = Symbol('x', integer=True)
+    y = Symbol('y', integer=True)
+    m = Symbol('m', even=True)
+    assert (x*y*(y + m)).is_even is None
+
+
+@XFAIL
+def test_oddness_in_ternary_integer_product_with_odd():
+    # Tests that oddness inference is independent of term ordering.
+    # Term ordering at the point of testing depends on SymPy's symbol order, so
+    # we try to force a different order by modifying symbol names.
+    x = Symbol('x', integer=True)
+    y = Symbol('y', integer=True)
+    k = Symbol('k', odd=True)
+    assert (x*y*(y + k)).is_odd is False
+    assert (y*x*(x + k)).is_odd is False
+
+
+def test_oddness_in_ternary_integer_product_with_even():
+    x = Symbol('x', integer=True)
+    y = Symbol('y', integer=True)
+    m = Symbol('m', even=True)
+    assert (x*y*(y + m)).is_odd is None
+
+
+def test_Mul_is_rational():
+    x = Symbol('x')
+    n = Symbol('n', integer=True)
+    m = Symbol('m', integer=True, nonzero=True)
+
+    assert (n/m).is_rational is True
+    assert (x/pi).is_rational is None
+    assert (x/n).is_rational is None
+    assert (m/pi).is_rational is False
+
+    r = Symbol('r', rational=True)
+    assert (pi*r).is_rational is None
+
+    # issue 8008
+    z = Symbol('z', zero=True)
+    i = Symbol('i', imaginary=True)
+    assert (z*i).is_rational is True
+    bi = Symbol('i', imaginary=True, finite=True)
+    assert (z*bi).is_zero is True
+
+
+def test_Add_is_rational():
+    x = Symbol('x')
+    n = Symbol('n', rational=True)
+    m = Symbol('m', rational=True)
+
+    assert (n + m).is_rational is True
+    assert (x + pi).is_rational is None
+    assert (x + n).is_rational is None
+    assert (n + pi).is_rational is False
+
+
+def test_Add_is_even_odd():
+    x = Symbol('x', integer=True)
+
+    k = Symbol('k', odd=True)
+    n = Symbol('n', odd=True)
+    m = Symbol('m', even=True)
+
+    assert (k + 7).is_even is True
+    assert (k + 7).is_odd is False
+
+    assert (-k + 7).is_even is True
+    assert (-k + 7).is_odd is False
+
+    assert (k - 12).is_even is False
+    assert (k - 12).is_odd is True
+
+    assert (-k - 12).is_even is False
+    assert (-k - 12).is_odd is True
+
+    assert (k + n).is_even is True
+    assert (k + n).is_odd is False
+
+    assert (k + m).is_even is False
+    assert (k + m).is_odd is True
+
+    assert (k + n + m).is_even is True
+    assert (k + n + m).is_odd is False
+
+    assert (k + n + x + m).is_even is None
+    assert (k + n + x + m).is_odd is None
+
+
+def test_Mul_is_negative_positive():
+    x = Symbol('x', real=True)
+    y = Symbol('y', extended_real=False, complex=True)
+    z = Symbol('z', zero=True)
+
+    e = 2*z
+    assert e.is_Mul and e.is_positive is False and e.is_negative is False
+
+    neg = Symbol('neg', negative=True)
+    pos = Symbol('pos', positive=True)
+    nneg = Symbol('nneg', nonnegative=True)
+    npos = Symbol('npos', nonpositive=True)
+
+    assert neg.is_negative is True
+    assert (-neg).is_negative is False
+    assert (2*neg).is_negative is True
+
+    assert (2*pos)._eval_is_extended_negative() is False
+    assert (2*pos).is_negative is False
+
+    assert pos.is_negative is False
+    assert (-pos).is_negative is True
+    assert (2*pos).is_negative is False
+
+    assert (pos*neg).is_negative is True
+    assert (2*pos*neg).is_negative is True
+    assert (-pos*neg).is_negative is False
+    assert (pos*neg*y).is_negative is False     # y.is_real=F;  !real -> !neg
+
+    assert nneg.is_negative is False
+    assert (-nneg).is_negative is None
+    assert (2*nneg).is_negative is False
+
+    assert npos.is_negative is None
+    assert (-npos).is_negative is False
+    assert (2*npos).is_negative is None
+
+    assert (nneg*npos).is_negative is None
+
+    assert (neg*nneg).is_negative is None
+    assert (neg*npos).is_negative is False
+
+    assert (pos*nneg).is_negative is False
+    assert (pos*npos).is_negative is None
+
+    assert (npos*neg*nneg).is_negative is False
+    assert (npos*pos*nneg).is_negative is None
+
+    assert (-npos*neg*nneg).is_negative is None
+    assert (-npos*pos*nneg).is_negative is False
+
+    assert (17*npos*neg*nneg).is_negative is False
+    assert (17*npos*pos*nneg).is_negative is None
+
+    assert (neg*npos*pos*nneg).is_negative is False
+
+    assert (x*neg).is_negative is None
+    assert (nneg*npos*pos*x*neg).is_negative is None
+
+    assert neg.is_positive is False
+    assert (-neg).is_positive is True
+    assert (2*neg).is_positive is False
+
+    assert pos.is_positive is True
+    assert (-pos).is_positive is False
+    assert (2*pos).is_positive is True
+
+    assert (pos*neg).is_positive is False
+    assert (2*pos*neg).is_positive is False
+    assert (-pos*neg).is_positive is True
+    assert (-pos*neg*y).is_positive is False    # y.is_real=F;  !real -> !neg
+
+    assert nneg.is_positive is None
+    assert (-nneg).is_positive is False
+    assert (2*nneg).is_positive is None
+
+    assert npos.is_positive is False
+    assert (-npos).is_positive is None
+    assert (2*npos).is_positive is False
+
+    assert (nneg*npos).is_positive is False
+
+    assert (neg*nneg).is_positive is False
+    assert (neg*npos).is_positive is None
+
+    assert (pos*nneg).is_positive is None
+    assert (pos*npos).is_positive is False
+
+    assert (npos*neg*nneg).is_positive is None
+    assert (npos*pos*nneg).is_positive is False
+
+    assert (-npos*neg*nneg).is_positive is False
+    assert (-npos*pos*nneg).is_positive is None
+
+    assert (17*npos*neg*nneg).is_positive is None
+    assert (17*npos*pos*nneg).is_positive is False
+
+    assert (neg*npos*pos*nneg).is_positive is None
+
+    assert (x*neg).is_positive is None
+    assert (nneg*npos*pos*x*neg).is_positive is None
+
+
+def test_Mul_is_negative_positive_2():
+    a = Symbol('a', nonnegative=True)
+    b = Symbol('b', nonnegative=True)
+    c = Symbol('c', nonpositive=True)
+    d = Symbol('d', nonpositive=True)
+
+    assert (a*b).is_nonnegative is True
+    assert (a*b).is_negative is False
+    assert (a*b).is_zero is None
+    assert (a*b).is_positive is None
+
+    assert (c*d).is_nonnegative is True
+    assert (c*d).is_negative is False
+    assert (c*d).is_zero is None
+    assert (c*d).is_positive is None
+
+    assert (a*c).is_nonpositive is True
+    assert (a*c).is_positive is False
+    assert (a*c).is_zero is None
+    assert (a*c).is_negative is None
+
+
+def test_Mul_is_nonpositive_nonnegative():
+    x = Symbol('x', real=True)
+
+    k = Symbol('k', negative=True)
+    n = Symbol('n', positive=True)
+    u = Symbol('u', nonnegative=True)
+    v = Symbol('v', nonpositive=True)
+
+    assert k.is_nonpositive is True
+    assert (-k).is_nonpositive is False
+    assert (2*k).is_nonpositive is True
+
+    assert n.is_nonpositive is False
+    assert (-n).is_nonpositive is True
+    assert (2*n).is_nonpositive is False
+
+    assert (n*k).is_nonpositive is True
+    assert (2*n*k).is_nonpositive is True
+    assert (-n*k).is_nonpositive is False
+
+    assert u.is_nonpositive is None
+    assert (-u).is_nonpositive is True
+    assert (2*u).is_nonpositive is None
+
+    assert v.is_nonpositive is True
+    assert (-v).is_nonpositive is None
+    assert (2*v).is_nonpositive is True
+
+    assert (u*v).is_nonpositive is True
+
+    assert (k*u).is_nonpositive is True
+    assert (k*v).is_nonpositive is None
+
+    assert (n*u).is_nonpositive is None
+    assert (n*v).is_nonpositive is True
+
+    assert (v*k*u).is_nonpositive is None
+    assert (v*n*u).is_nonpositive is True
+
+    assert (-v*k*u).is_nonpositive is True
+    assert (-v*n*u).is_nonpositive is None
+
+    assert (17*v*k*u).is_nonpositive is None
+    assert (17*v*n*u).is_nonpositive is True
+
+    assert (k*v*n*u).is_nonpositive is None
+
+    assert (x*k).is_nonpositive is None
+    assert (u*v*n*x*k).is_nonpositive is None
+
+    assert k.is_nonnegative is False
+    assert (-k).is_nonnegative is True
+    assert (2*k).is_nonnegative is False
+
+    assert n.is_nonnegative is True
+    assert (-n).is_nonnegative is False
+    assert (2*n).is_nonnegative is True
+
+    assert (n*k).is_nonnegative is False
+    assert (2*n*k).is_nonnegative is False
+    assert (-n*k).is_nonnegative is True
+
+    assert u.is_nonnegative is True
+    assert (-u).is_nonnegative is None
+    assert (2*u).is_nonnegative is True
+
+    assert v.is_nonnegative is None
+    assert (-v).is_nonnegative is True
+    assert (2*v).is_nonnegative is None
+
+    assert (u*v).is_nonnegative is None
+
+    assert (k*u).is_nonnegative is None
+    assert (k*v).is_nonnegative is True
+
+    assert (n*u).is_nonnegative is True
+    assert (n*v).is_nonnegative is None
+
+    assert (v*k*u).is_nonnegative is True
+    assert (v*n*u).is_nonnegative is None
+
+    assert (-v*k*u).is_nonnegative is None
+    assert (-v*n*u).is_nonnegative is True
+
+    assert (17*v*k*u).is_nonnegative is True
+    assert (17*v*n*u).is_nonnegative is None
+
+    assert (k*v*n*u).is_nonnegative is True
+
+    assert (x*k).is_nonnegative is None
+    assert (u*v*n*x*k).is_nonnegative is None
+
+
+def test_Add_is_negative_positive():
+    x = Symbol('x', real=True)
+
+    k = Symbol('k', negative=True)
+    n = Symbol('n', positive=True)
+    u = Symbol('u', nonnegative=True)
+    v = Symbol('v', nonpositive=True)
+
+    assert (k - 2).is_negative is True
+    assert (k + 17).is_negative is None
+    assert (-k - 5).is_negative is None
+    assert (-k + 123).is_negative is False
+
+    assert (k - n).is_negative is True
+    assert (k + n).is_negative is None
+    assert (-k - n).is_negative is None
+    assert (-k + n).is_negative is False
+
+    assert (k - n - 2).is_negative is True
+    assert (k + n + 17).is_negative is None
+    assert (-k - n - 5).is_negative is None
+    assert (-k + n + 123).is_negative is False
+
+    assert (-2*k + 123*n + 17).is_negative is False
+
+    assert (k + u).is_negative is None
+    assert (k + v).is_negative is True
+    assert (n + u).is_negative is False
+    assert (n + v).is_negative is None
+
+    assert (u - v).is_negative is False
+    assert (u + v).is_negative is None
+    assert (-u - v).is_negative is None
+    assert (-u + v).is_negative is None
+
+    assert (u - v + n + 2).is_negative is False
+    assert (u + v + n + 2).is_negative is None
+    assert (-u - v + n + 2).is_negative is None
+    assert (-u + v + n + 2).is_negative is None
+
+    assert (k + x).is_negative is None
+    assert (k + x - n).is_negative is None
+
+    assert (k - 2).is_positive is False
+    assert (k + 17).is_positive is None
+    assert (-k - 5).is_positive is None
+    assert (-k + 123).is_positive is True
+
+    assert (k - n).is_positive is False
+    assert (k + n).is_positive is None
+    assert (-k - n).is_positive is None
+    assert (-k + n).is_positive is True
+
+    assert (k - n - 2).is_positive is False
+    assert (k + n + 17).is_positive is None
+    assert (-k - n - 5).is_positive is None
+    assert (-k + n + 123).is_positive is True
+
+    assert (-2*k + 123*n + 17).is_positive is True
+
+    assert (k + u).is_positive is None
+    assert (k + v).is_positive is False
+    assert (n + u).is_positive is True
+    assert (n + v).is_positive is None
+
+    assert (u - v).is_positive is None
+    assert (u + v).is_positive is None
+    assert (-u - v).is_positive is None
+    assert (-u + v).is_positive is False
+
+    assert (u - v - n - 2).is_positive is None
+    assert (u + v - n - 2).is_positive is None
+    assert (-u - v - n - 2).is_positive is None
+    assert (-u + v - n - 2).is_positive is False
+
+    assert (n + x).is_positive is None
+    assert (n + x - k).is_positive is None
+
+    z = (-3 - sqrt(5) + (-sqrt(10)/2 - sqrt(2)/2)**2)
+    assert z.is_zero
+    z = sqrt(1 + sqrt(3)) + sqrt(3 + 3*sqrt(3)) - sqrt(10 + 6*sqrt(3))
+    assert z.is_zero
+
+
+def test_Add_is_nonpositive_nonnegative():
+    x = Symbol('x', real=True)
+
+    k = Symbol('k', negative=True)
+    n = Symbol('n', positive=True)
+    u = Symbol('u', nonnegative=True)
+    v = Symbol('v', nonpositive=True)
+
+    assert (u - 2).is_nonpositive is None
+    assert (u + 17).is_nonpositive is False
+    assert (-u - 5).is_nonpositive is True
+    assert (-u + 123).is_nonpositive is None
+
+    assert (u - v).is_nonpositive is None
+    assert (u + v).is_nonpositive is None
+    assert (-u - v).is_nonpositive is None
+    assert (-u + v).is_nonpositive is True
+
+    assert (u - v - 2).is_nonpositive is None
+    assert (u + v + 17).is_nonpositive is None
+    assert (-u - v - 5).is_nonpositive is None
+    assert (-u + v - 123).is_nonpositive is True
+
+    assert (-2*u + 123*v - 17).is_nonpositive is True
+
+    assert (k + u).is_nonpositive is None
+    assert (k + v).is_nonpositive is True
+    assert (n + u).is_nonpositive is False
+    assert (n + v).is_nonpositive is None
+
+    assert (k - n).is_nonpositive is True
+    assert (k + n).is_nonpositive is None
+    assert (-k - n).is_nonpositive is None
+    assert (-k + n).is_nonpositive is False
+
+    assert (k - n + u + 2).is_nonpositive is None
+    assert (k + n + u + 2).is_nonpositive is None
+    assert (-k - n + u + 2).is_nonpositive is None
+    assert (-k + n + u + 2).is_nonpositive is False
+
+    assert (u + x).is_nonpositive is None
+    assert (v - x - n).is_nonpositive is None
+
+    assert (u - 2).is_nonnegative is None
+    assert (u + 17).is_nonnegative is True
+    assert (-u - 5).is_nonnegative is False
+    assert (-u + 123).is_nonnegative is None
+
+    assert (u - v).is_nonnegative is True
+    assert (u + v).is_nonnegative is None
+    assert (-u - v).is_nonnegative is None
+    assert (-u + v).is_nonnegative is None
+
+    assert (u - v + 2).is_nonnegative is True
+    assert (u + v + 17).is_nonnegative is None
+    assert (-u - v - 5).is_nonnegative is None
+    assert (-u + v - 123).is_nonnegative is False
+
+    assert (2*u - 123*v + 17).is_nonnegative is True
+
+    assert (k + u).is_nonnegative is None
+    assert (k + v).is_nonnegative is False
+    assert (n + u).is_nonnegative is True
+    assert (n + v).is_nonnegative is None
+
+    assert (k - n).is_nonnegative is False
+    assert (k + n).is_nonnegative is None
+    assert (-k - n).is_nonnegative is None
+    assert (-k + n).is_nonnegative is True
+
+    assert (k - n - u - 2).is_nonnegative is False
+    assert (k + n - u - 2).is_nonnegative is None
+    assert (-k - n - u - 2).is_nonnegative is None
+    assert (-k + n - u - 2).is_nonnegative is None
+
+    assert (u - x).is_nonnegative is None
+    assert (v + x + n).is_nonnegative is None
+
+
+def test_Pow_is_integer():
+    x = Symbol('x')
+
+    k = Symbol('k', integer=True)
+    n = Symbol('n', integer=True, nonnegative=True)
+    m = Symbol('m', integer=True, positive=True)
+
+    assert (k**2).is_integer is True
+    assert (k**(-2)).is_integer is None
+    assert ((m + 1)**(-2)).is_integer is False
+    assert (m**(-1)).is_integer is None  # issue 8580
+
+    assert (2**k).is_integer is None
+    assert (2**(-k)).is_integer is None
+
+    assert (2**n).is_integer is True
+    assert (2**(-n)).is_integer is None
+
+    assert (2**m).is_integer is True
+    assert (2**(-m)).is_integer is False
+
+    assert (x**2).is_integer is None
+    assert (2**x).is_integer is None
+
+    assert (k**n).is_integer is True
+    assert (k**(-n)).is_integer is None
+
+    assert (k**x).is_integer is None
+    assert (x**k).is_integer is None
+
+    assert (k**(n*m)).is_integer is True
+    assert (k**(-n*m)).is_integer is None
+
+    assert sqrt(3).is_integer is False
+    assert sqrt(.3).is_integer is False
+    assert Pow(3, 2, evaluate=False).is_integer is True
+    assert Pow(3, 0, evaluate=False).is_integer is True
+    assert Pow(3, -2, evaluate=False).is_integer is False
+    assert Pow(S.Half, 3, evaluate=False).is_integer is False
+    # decided by re-evaluating
+    assert Pow(3, S.Half, evaluate=False).is_integer is False
+    assert Pow(3, S.Half, evaluate=False).is_integer is False
+    assert Pow(4, S.Half, evaluate=False).is_integer is True
+    assert Pow(S.Half, -2, evaluate=False).is_integer is True
+
+    assert ((-1)**k).is_integer
+
+    # issue 8641
+    x = Symbol('x', real=True, integer=False)
+    assert (x**2).is_integer is None
+
+    # issue 10458
+    x = Symbol('x', positive=True)
+    assert (1/(x + 1)).is_integer is False
+    assert (1/(-x - 1)).is_integer is False
+    assert (-1/(x + 1)).is_integer is False
+    # issue 23287
+    assert (x**2/2).is_integer is None
+
+    # issue 8648-like
+    k = Symbol('k', even=True)
+    assert (k**3/2).is_integer
+    assert (k**3/8).is_integer
+    assert (k**3/16).is_integer is None
+    assert (2/k).is_integer is None
+    assert (2/k**2).is_integer is False
+    o = Symbol('o', odd=True)
+    assert (k/o).is_integer is None
+    o = Symbol('o', odd=True, prime=True)
+    assert (k/o).is_integer is False
+
+
+def test_Pow_is_real():
+    x = Symbol('x', real=True)
+    y = Symbol('y', positive=True)
+
+    assert (x**2).is_real is True
+    assert (x**3).is_real is True
+    assert (x**x).is_real is None
+    assert (y**x).is_real is True
+
+    assert (x**Rational(1, 3)).is_real is None
+    assert (y**Rational(1, 3)).is_real is True
+
+    assert sqrt(-1 - sqrt(2)).is_real is False
+
+    i = Symbol('i', imaginary=True)
+    assert (i**i).is_real is None
+    assert (I**i).is_extended_real is True
+    assert ((-I)**i).is_extended_real is True
+    assert (2**i).is_real is None  # (2**(pi/log(2) * I)) is real, 2**I is not
+    assert (2**I).is_real is False
+    assert (2**-I).is_real is False
+    assert (i**2).is_extended_real is True
+    assert (i**3).is_extended_real is False
+    assert (i**x).is_real is None  # could be (-I)**(2/3)
+    e = Symbol('e', even=True)
+    o = Symbol('o', odd=True)
+    k = Symbol('k', integer=True)
+    assert (i**e).is_extended_real is True
+    assert (i**o).is_extended_real is False
+    assert (i**k).is_real is None
+    assert (i**(4*k)).is_extended_real is True
+
+    x = Symbol("x", nonnegative=True)
+    y = Symbol("y", nonnegative=True)
+    assert im(x**y).expand(complex=True) is S.Zero
+    assert (x**y).is_real is True
+    i = Symbol('i', imaginary=True)
+    assert (exp(i)**I).is_extended_real is True
+    assert log(exp(i)).is_imaginary is None  # i could be 2*pi*I
+    c = Symbol('c', complex=True)
+    assert log(c).is_real is None  # c could be 0 or 2, too
+    assert log(exp(c)).is_real is None  # log(0), log(E), ...
+    n = Symbol('n', negative=False)
+    assert log(n).is_real is None
+    n = Symbol('n', nonnegative=True)
+    assert log(n).is_real is None
+
+    assert sqrt(-I).is_real is False  # issue 7843
+
+    i = Symbol('i', integer=True)
+    assert (1/(i-1)).is_real is None
+    assert (1/(i-1)).is_extended_real is None
+
+    # test issue 20715
+    from sympy.core.parameters import evaluate
+    x = S(-1)
+    with evaluate(False):
+        assert x.is_negative is True
+
+    f = Pow(x, -1)
+    with evaluate(False):
+        assert f.is_imaginary is False
+
+
+def test_real_Pow():
+    k = Symbol('k', integer=True, nonzero=True)
+    assert (k**(I*pi/log(k))).is_real
+
+
+def test_Pow_is_finite():
+    xe = Symbol('xe', extended_real=True)
+    xr = Symbol('xr', real=True)
+    p = Symbol('p', positive=True)
+    n = Symbol('n', negative=True)
+    i = Symbol('i', integer=True)
+
+    assert (xe**2).is_finite is None  # xe could be oo
+    assert (xr**2).is_finite is True
+
+    assert (xe**xe).is_finite is None
+    assert (xr**xe).is_finite is None
+    assert (xe**xr).is_finite is None
+    # FIXME: The line below should be True rather than None
+    # assert (xr**xr).is_finite is True
+    assert (xr**xr).is_finite is None
+
+    assert (p**xe).is_finite is None
+    assert (p**xr).is_finite is True
+
+    assert (n**xe).is_finite is None
+    assert (n**xr).is_finite is True
+
+    assert (sin(xe)**2).is_finite is True
+    assert (sin(xr)**2).is_finite is True
+
+    assert (sin(xe)**xe).is_finite is None  # xe, xr could be -pi
+    assert (sin(xr)**xr).is_finite is None
+
+    # FIXME: Should the line below be True rather than None?
+    assert (sin(xe)**exp(xe)).is_finite is None
+    assert (sin(xr)**exp(xr)).is_finite is True
+
+    assert (1/sin(xe)).is_finite is None  # if zero, no, otherwise yes
+    assert (1/sin(xr)).is_finite is None
+
+    assert (1/exp(xe)).is_finite is None  # xe could be -oo
+    assert (1/exp(xr)).is_finite is True
+
+    assert (1/S.Pi).is_finite is True
+
+    assert (1/(i-1)).is_finite is None
+
+
+def test_Pow_is_even_odd():
+    x = Symbol('x')
+
+    k = Symbol('k', even=True)
+    n = Symbol('n', odd=True)
+    m = Symbol('m', integer=True, nonnegative=True)
+    p = Symbol('p', integer=True, positive=True)
+
+    assert ((-1)**n).is_odd
+    assert ((-1)**k).is_odd
+    assert ((-1)**(m - p)).is_odd
+
+    assert (k**2).is_even is True
+    assert (n**2).is_even is False
+    assert (2**k).is_even is None
+    assert (x**2).is_even is None
+
+    assert (k**m).is_even is None
+    assert (n**m).is_even is False
+
+    assert (k**p).is_even is True
+    assert (n**p).is_even is False
+
+    assert (m**k).is_even is None
+    assert (p**k).is_even is None
+
+    assert (m**n).is_even is None
+    assert (p**n).is_even is None
+
+    assert (k**x).is_even is None
+    assert (n**x).is_even is None
+
+    assert (k**2).is_odd is False
+    assert (n**2).is_odd is True
+    assert (3**k).is_odd is None
+
+    assert (k**m).is_odd is None
+    assert (n**m).is_odd is True
+
+    assert (k**p).is_odd is False
+    assert (n**p).is_odd is True
+
+    assert (m**k).is_odd is None
+    assert (p**k).is_odd is None
+
+    assert (m**n).is_odd is None
+    assert (p**n).is_odd is None
+
+    assert (k**x).is_odd is None
+    assert (n**x).is_odd is None
+
+
+def test_Pow_is_negative_positive():
+    r = Symbol('r', real=True)
+
+    k = Symbol('k', integer=True, positive=True)
+    n = Symbol('n', even=True)
+    m = Symbol('m', odd=True)
+
+    x = Symbol('x')
+
+    assert (2**r).is_positive is True
+    assert ((-2)**r).is_positive is None
+    assert ((-2)**n).is_positive is True
+    assert ((-2)**m).is_positive is False
+
+    assert (k**2).is_positive is True
+    assert (k**(-2)).is_positive is True
+
+    assert (k**r).is_positive is True
+    assert ((-k)**r).is_positive is None
+    assert ((-k)**n).is_positive is True
+    assert ((-k)**m).is_positive is False
+
+    assert (2**r).is_negative is False
+    assert ((-2)**r).is_negative is None
+    assert ((-2)**n).is_negative is False
+    assert ((-2)**m).is_negative is True
+
+    assert (k**2).is_negative is False
+    assert (k**(-2)).is_negative is False
+
+    assert (k**r).is_negative is False
+    assert ((-k)**r).is_negative is None
+    assert ((-k)**n).is_negative is False
+    assert ((-k)**m).is_negative is True
+
+    assert (2**x).is_positive is None
+    assert (2**x).is_negative is None
+
+
+def test_Pow_is_zero():
+    z = Symbol('z', zero=True)
+    e = z**2
+    assert e.is_zero
+    assert e.is_positive is False
+    assert e.is_negative is False
+
+    assert Pow(0, 0, evaluate=False).is_zero is False
+    assert Pow(0, 3, evaluate=False).is_zero
+    assert Pow(0, oo, evaluate=False).is_zero
+    assert Pow(0, -3, evaluate=False).is_zero is False
+    assert Pow(0, -oo, evaluate=False).is_zero is False
+    assert Pow(2, 2, evaluate=False).is_zero is False
+
+    a = Symbol('a', zero=False)
+    assert Pow(a, 3).is_zero is False  # issue 7965
+
+    assert Pow(2, oo, evaluate=False).is_zero is False
+    assert Pow(2, -oo, evaluate=False).is_zero
+    assert Pow(S.Half, oo, evaluate=False).is_zero
+    assert Pow(S.Half, -oo, evaluate=False).is_zero is False
+
+    # All combinations of real/complex base/exponent
+    h = S.Half
+    T = True
+    F = False
+    N = None
+
+    pow_iszero = [
+        ['**',  0,  h,  1,  2, -h, -1,-2,-2*I,-I/2,I/2,1+I,oo,-oo,zoo],
+        [   0,  F,  T,  T,  T,  F,  F,  F,  F,  F,  F,  N,  T,  F,  N],
+        [   h,  F,  F,  F,  F,  F,  F,  F,  F,  F,  F,  F,  T,  F,  N],
+        [   1,  F,  F,  F,  F,  F,  F,  F,  F,  F,  F,  F,  F,  F,  N],
+        [   2,  F,  F,  F,  F,  F,  F,  F,  F,  F,  F,  F,  F,  T,  N],
+        [  -h,  F,  F,  F,  F,  F,  F,  F,  F,  F,  F,  F,  T,  F,  N],
+        [  -1,  F,  F,  F,  F,  F,  F,  F,  F,  F,  F,  F,  F,  F,  N],
+        [  -2,  F,  F,  F,  F,  F,  F,  F,  F,  F,  F,  F,  F,  T,  N],
+        [-2*I,  F,  F,  F,  F,  F,  F,  F,  F,  F,  F,  F,  F,  T,  N],
+        [-I/2,  F,  F,  F,  F,  F,  F,  F,  F,  F,  F,  F,  T,  F,  N],
+        [ I/2,  F,  F,  F,  F,  F,  F,  F,  F,  F,  F,  F,  T,  F,  N],
+        [ 1+I,  F,  F,  F,  F,  F,  F,  F,  F,  F,  F,  F,  F,  T,  N],
+        [  oo,  F,  F,  F,  F,  T,  T,  T,  F,  F,  F,  F,  F,  T,  N],
+        [ -oo,  F,  F,  F,  F,  T,  T,  T,  F,  F,  F,  F,  F,  T,  N],
+        [ zoo,  F,  F,  F,  F,  T,  T,  T,  N,  N,  N,  N,  F,  T,  N]
+    ]
+
+    def test_table(table):
+        n = len(table[0])
+        for row in range(1, n):
+            base = table[row][0]
+            for col in range(1, n):
+                exp = table[0][col]
+                is_zero = table[row][col]
+                # The actual test here:
+                assert Pow(base, exp, evaluate=False).is_zero is is_zero
+
+    test_table(pow_iszero)
+
+    # A zero symbol...
+    zo, zo2 = symbols('zo, zo2', zero=True)
+
+    # All combinations of finite symbols
+    zf, zf2 = symbols('zf, zf2', finite=True)
+    wf, wf2 = symbols('wf, wf2', nonzero=True)
+    xf, xf2 = symbols('xf, xf2', real=True)
+    yf, yf2 = symbols('yf, yf2', nonzero=True)
+    af, af2 = symbols('af, af2', positive=True)
+    bf, bf2 = symbols('bf, bf2', nonnegative=True)
+    cf, cf2 = symbols('cf, cf2', negative=True)
+    df, df2 = symbols('df, df2', nonpositive=True)
+
+    # Without finiteness:
+    zi, zi2 = symbols('zi, zi2')
+    wi, wi2 = symbols('wi, wi2', zero=False)
+    xi, xi2 = symbols('xi, xi2', extended_real=True)
+    yi, yi2 = symbols('yi, yi2', zero=False, extended_real=True)
+    ai, ai2 = symbols('ai, ai2', extended_positive=True)
+    bi, bi2 = symbols('bi, bi2', extended_nonnegative=True)
+    ci, ci2 = symbols('ci, ci2', extended_negative=True)
+    di, di2 = symbols('di, di2', extended_nonpositive=True)
+
+    pow_iszero_sym = [
+        ['**',zo,wf,yf,af,cf,zf,xf,bf,df,zi,wi,xi,yi,ai,bi,ci,di],
+        [ zo2, F, N, N, T, F, N, N, N, F, N, N, N, N, T, N, F, F],
+        [ wf2, F, F, F, F, F, F, F, F, F, N, N, N, N, N, N, N, N],
+        [ yf2, F, F, F, F, F, F, F, F, F, N, N, N, N, N, N, N, N],
+        [ af2, F, F, F, F, F, F, F, F, F, N, N, N, N, N, N, N, N],
+        [ cf2, F, F, F, F, F, F, F, F, F, N, N, N, N, N, N, N, N],
+        [ zf2, N, N, N, N, F, N, N, N, N, N, N, N, N, N, N, N, N],
+        [ xf2, N, N, N, N, F, N, N, N, N, N, N, N, N, N, N, N, N],
+        [ bf2, N, N, N, N, F, N, N, N, N, N, N, N, N, N, N, N, N],
+        [ df2, N, N, N, N, F, N, N, N, N, N, N, N, N, N, N, N, N],
+        [ zi2, N, N, N, N, N, N, N, N, N, N, N, N, N, N, N, N, N],
+        [ wi2, F, N, N, F, N, N, N, F, N, N, N, N, N, N, N, N, N],
+        [ xi2, N, N, N, N, N, N, N, N, N, N, N, N, N, N, N, N, N],
+        [ yi2, F, N, N, F, N, N, N, F, N, N, N, N, N, N, N, N, N],
+        [ ai2, F, N, N, F, N, N, N, F, N, N, N, N, N, N, N, N, N],
+        [ bi2, N, N, N, N, N, N, N, N, N, N, N, N, N, N, N, N, N],
+        [ ci2, F, N, N, F, N, N, N, F, N, N, N, N, N, N, N, N, N],
+        [ di2, N, N, N, N, N, N, N, N, N, N, N, N, N, N, N, N, N]
+    ]
+
+    test_table(pow_iszero_sym)
+
+    # In some cases (x**x).is_zero is different from (x**y).is_zero even if y
+    # has the same assumptions as x.
+    assert (zo ** zo).is_zero is False
+    assert (wf ** wf).is_zero is False
+    assert (yf ** yf).is_zero is False
+    assert (af ** af).is_zero is False
+    assert (cf ** cf).is_zero is False
+    assert (zf ** zf).is_zero is None
+    assert (xf ** xf).is_zero is None
+    assert (bf ** bf).is_zero is False # None in table
+    assert (df ** df).is_zero is None
+    assert (zi ** zi).is_zero is None
+    assert (wi ** wi).is_zero is None
+    assert (xi ** xi).is_zero is None
+    assert (yi ** yi).is_zero is None
+    assert (ai ** ai).is_zero is False # None in table
+    assert (bi ** bi).is_zero is False # None in table
+    assert (ci ** ci).is_zero is None
+    assert (di ** di).is_zero is None
+
+
+def test_Pow_is_nonpositive_nonnegative():
+    x = Symbol('x', real=True)
+
+    k = Symbol('k', integer=True, nonnegative=True)
+    l = Symbol('l', integer=True, positive=True)
+    n = Symbol('n', even=True)
+    m = Symbol('m', odd=True)
+
+    assert (x**(4*k)).is_nonnegative is True
+    assert (2**x).is_nonnegative is True
+    assert ((-2)**x).is_nonnegative is None
+    assert ((-2)**n).is_nonnegative is True
+    assert ((-2)**m).is_nonnegative is False
+
+    assert (k**2).is_nonnegative is True
+    assert (k**(-2)).is_nonnegative is None
+    assert (k**k).is_nonnegative is True
+
+    assert (k**x).is_nonnegative is None    # NOTE (0**x).is_real = U
+    assert (l**x).is_nonnegative is True
+    assert (l**x).is_positive is True
+    assert ((-k)**x).is_nonnegative is None
+
+    assert ((-k)**m).is_nonnegative is None
+
+    assert (2**x).is_nonpositive is False
+    assert ((-2)**x).is_nonpositive is None
+    assert ((-2)**n).is_nonpositive is False
+    assert ((-2)**m).is_nonpositive is True
+
+    assert (k**2).is_nonpositive is None
+    assert (k**(-2)).is_nonpositive is None
+
+    assert (k**x).is_nonpositive is None
+    assert ((-k)**x).is_nonpositive is None
+    assert ((-k)**n).is_nonpositive is None
+
+
+    assert (x**2).is_nonnegative is True
+    i = symbols('i', imaginary=True)
+    assert (i**2).is_nonpositive is True
+    assert (i**4).is_nonpositive is False
+    assert (i**3).is_nonpositive is False
+    assert (I**i).is_nonnegative is True
+    assert (exp(I)**i).is_nonnegative is True
+
+    assert ((-l)**n).is_nonnegative is True
+    assert ((-l)**m).is_nonpositive is True
+    assert ((-k)**n).is_nonnegative is None
+    assert ((-k)**m).is_nonpositive is None
+
+
+def test_Mul_is_imaginary_real():
+    r = Symbol('r', real=True)
+    p = Symbol('p', positive=True)
+    i1 = Symbol('i1', imaginary=True)
+    i2 = Symbol('i2', imaginary=True)
+    x = Symbol('x')
+
+    assert I.is_imaginary is True
+    assert I.is_real is False
+    assert (-I).is_imaginary is True
+    assert (-I).is_real is False
+    assert (3*I).is_imaginary is True
+    assert (3*I).is_real is False
+    assert (I*I).is_imaginary is False
+    assert (I*I).is_real is True
+
+    e = (p + p*I)
+    j = Symbol('j', integer=True, zero=False)
+    assert (e**j).is_real is None
+    assert (e**(2*j)).is_real is None
+    assert (e**j).is_imaginary is None
+    assert (e**(2*j)).is_imaginary is None
+
+    assert (e**-1).is_imaginary is False
+    assert (e**2).is_imaginary
+    assert (e**3).is_imaginary is False
+    assert (e**4).is_imaginary is False
+    assert (e**5).is_imaginary is False
+    assert (e**-1).is_real is False
+    assert (e**2).is_real is False
+    assert (e**3).is_real is False
+    assert (e**4).is_real is True
+    assert (e**5).is_real is False
+    assert (e**3).is_complex
+
+    assert (r*i1).is_imaginary is None
+    assert (r*i1).is_real is None
+
+    assert (x*i1).is_imaginary is None
+    assert (x*i1).is_real is None
+
+    assert (i1*i2).is_imaginary is False
+    assert (i1*i2).is_real is True
+
+    assert (r*i1*i2).is_imaginary is False
+    assert (r*i1*i2).is_real is True
+
+    # Github's issue 5874:
+    nr = Symbol('nr', real=False, complex=True)  # e.g. I or 1 + I
+    a = Symbol('a', real=True, nonzero=True)
+    b = Symbol('b', real=True)
+    assert (i1*nr).is_real is None
+    assert (a*nr).is_real is False
+    assert (b*nr).is_real is None
+
+    ni = Symbol('ni', imaginary=False, complex=True)  # e.g. 2 or 1 + I
+    a = Symbol('a', real=True, nonzero=True)
+    b = Symbol('b', real=True)
+    assert (i1*ni).is_real is False
+    assert (a*ni).is_real is None
+    assert (b*ni).is_real is None
+
+
+def test_Mul_hermitian_antihermitian():
+    xz, yz = symbols('xz, yz', zero=True, antihermitian=True)
+    xf, yf = symbols('xf, yf', hermitian=False, antihermitian=False, finite=True)
+    xh, yh = symbols('xh, yh', hermitian=True, antihermitian=False, nonzero=True)
+    xa, ya = symbols('xa, ya', hermitian=False, antihermitian=True, zero=False, finite=True)
+    assert (xz*xh).is_hermitian is True
+    assert (xz*xh).is_antihermitian is True
+    assert (xz*xa).is_hermitian is True
+    assert (xz*xa).is_antihermitian is True
+    assert (xf*yf).is_hermitian is None
+    assert (xf*yf).is_antihermitian is None
+    assert (xh*yh).is_hermitian is True
+    assert (xh*yh).is_antihermitian is False
+    assert (xh*ya).is_hermitian is False
+    assert (xh*ya).is_antihermitian is True
+    assert (xa*ya).is_hermitian is True
+    assert (xa*ya).is_antihermitian is False
+
+    a = Symbol('a', hermitian=True, zero=False)
+    b = Symbol('b', hermitian=True)
+    c = Symbol('c', hermitian=False)
+    d = Symbol('d', antihermitian=True)
+    e1 = Mul(a, b, c, evaluate=False)
+    e2 = Mul(b, a, c, evaluate=False)
+    e3 = Mul(a, b, c, d, evaluate=False)
+    e4 = Mul(b, a, c, d, evaluate=False)
+    e5 = Mul(a, c, evaluate=False)
+    e6 = Mul(a, c, d, evaluate=False)
+    assert e1.is_hermitian is None
+    assert e2.is_hermitian is None
+    assert e1.is_antihermitian is None
+    assert e2.is_antihermitian is None
+    assert e3.is_antihermitian is None
+    assert e4.is_antihermitian is None
+    assert e5.is_antihermitian is None
+    assert e6.is_antihermitian is None
+
+
+def test_Add_is_comparable():
+    assert (x + y).is_comparable is False
+    assert (x + 1).is_comparable is False
+    assert (Rational(1, 3) - sqrt(8)).is_comparable is True
+
+
+def test_Mul_is_comparable():
+    assert (x*y).is_comparable is False
+    assert (x*2).is_comparable is False
+    assert (sqrt(2)*Rational(1, 3)).is_comparable is True
+
+
+def test_Pow_is_comparable():
+    assert (x**y).is_comparable is False
+    assert (x**2).is_comparable is False
+    assert (sqrt(Rational(1, 3))).is_comparable is True
+
+
+def test_Add_is_positive_2():
+    e = Rational(1, 3) - sqrt(8)
+    assert e.is_positive is False
+    assert e.is_negative is True
+
+    e = pi - 1
+    assert e.is_positive is True
+    assert e.is_negative is False
+
+
+def test_Add_is_irrational():
+    i = Symbol('i', irrational=True)
+
+    assert i.is_irrational is True
+    assert i.is_rational is False
+
+    assert (i + 1).is_irrational is True
+    assert (i + 1).is_rational is False
+
+
+def test_Mul_is_irrational():
+    expr = Mul(1, 2, 3, evaluate=False)
+    assert expr.is_irrational is False
+    expr = Mul(1, I, I, evaluate=False)
+    assert expr.is_rational is None # I * I = -1 but *no evaluation allowed*
+    # sqrt(2) * I * I = -sqrt(2) is irrational but
+    # this can't be determined without evaluating the
+    # expression and the eval_is routines shouldn't do that
+    expr = Mul(sqrt(2), I, I, evaluate=False)
+    assert expr.is_irrational is None
+
+
+def test_issue_3531():
+    # https://github.com/sympy/sympy/issues/3531
+    # https://github.com/sympy/sympy/pull/18116
+    class MightyNumeric(tuple):
+        def __rtruediv__(self, other):
+            return "something"
+
+    assert sympify(1)/MightyNumeric((1, 2)) == "something"
+
+
+def test_issue_3531b():
+    class Foo:
+        def __init__(self):
+            self.field = 1.0
+
+        def __mul__(self, other):
+            self.field = self.field * other
+
+        def __rmul__(self, other):
+            self.field = other * self.field
+    f = Foo()
+    x = Symbol("x")
+    assert f*x == x*f
+
+
+def test_bug3():
+    a = Symbol("a")
+    b = Symbol("b", positive=True)
+    e = 2*a + b
+    f = b + 2*a
+    assert e == f
+
+
+def test_suppressed_evaluation():
+    a = Add(0, 3, 2, evaluate=False)
+    b = Mul(1, 3, 2, evaluate=False)
+    c = Pow(3, 2, evaluate=False)
+    assert a != 6
+    assert a.func is Add
+    assert a.args == (0, 3, 2)
+    assert b != 6
+    assert b.func is Mul
+    assert b.args == (1, 3, 2)
+    assert c != 9
+    assert c.func is Pow
+    assert c.args == (3, 2)
+
+
+def test_AssocOp_doit():
+    a = Add(x,x, evaluate=False)
+    b = Mul(y,y, evaluate=False)
+    c = Add(b,b, evaluate=False)
+    d = Mul(a,a, evaluate=False)
+    assert c.doit(deep=False).func == Mul
+    assert c.doit(deep=False).args == (2,y,y)
+    assert c.doit().func == Mul
+    assert c.doit().args == (2, Pow(y,2))
+    assert d.doit(deep=False).func == Pow
+    assert d.doit(deep=False).args == (a, 2*S.One)
+    assert d.doit().func == Mul
+    assert d.doit().args == (4*S.One, Pow(x,2))
+
+
+def test_Add_Mul_Expr_args():
+    nonexpr = [Basic(), Poly(x, x), FiniteSet(x)]
+    for typ in [Add, Mul]:
+        for obj in nonexpr:
+            # The cache can mess with the stacklevel check
+            with warns(SymPyDeprecationWarning, test_stacklevel=False):
+                typ(obj, 1)
+
+
+def test_Add_as_coeff_mul():
+    # issue 5524.  These should all be (1, self)
+    assert (x + 1).as_coeff_mul() == (1, (x + 1,))
+    assert (x + 2).as_coeff_mul() == (1, (x + 2,))
+    assert (x + 3).as_coeff_mul() == (1, (x + 3,))
+
+    assert (x - 1).as_coeff_mul() == (1, (x - 1,))
+    assert (x - 2).as_coeff_mul() == (1, (x - 2,))
+    assert (x - 3).as_coeff_mul() == (1, (x - 3,))
+
+    n = Symbol('n', integer=True)
+    assert (n + 1).as_coeff_mul() == (1, (n + 1,))
+    assert (n + 2).as_coeff_mul() == (1, (n + 2,))
+    assert (n + 3).as_coeff_mul() == (1, (n + 3,))
+
+    assert (n - 1).as_coeff_mul() == (1, (n - 1,))
+    assert (n - 2).as_coeff_mul() == (1, (n - 2,))
+    assert (n - 3).as_coeff_mul() == (1, (n - 3,))
+
+
+def test_Pow_as_coeff_mul_doesnt_expand():
+    assert exp(x + y).as_coeff_mul() == (1, (exp(x + y),))
+    assert exp(x + exp(x + y)) != exp(x + exp(x)*exp(y))
+
+def test_issue_24751():
+    expr = Add(-2, -3, evaluate=False)
+    expr1 = Add(-1, expr, evaluate=False)
+    assert int(expr1) == int((-3 - 2) - 1)
+
+
+def test_issue_3514_18626():
+    assert sqrt(S.Half) * sqrt(6) == 2 * sqrt(3)/2
+    assert S.Half*sqrt(6)*sqrt(2) == sqrt(3)
+    assert sqrt(6)/2*sqrt(2) == sqrt(3)
+    assert sqrt(6)*sqrt(2)/2 == sqrt(3)
+    assert sqrt(8)**Rational(2, 3) == 2
+
+
+def test_make_args():
+    assert Add.make_args(x) == (x,)
+    assert Mul.make_args(x) == (x,)
+
+    assert Add.make_args(x*y*z) == (x*y*z,)
+    assert Mul.make_args(x*y*z) == (x*y*z).args
+
+    assert Add.make_args(x + y + z) == (x + y + z).args
+    assert Mul.make_args(x + y + z) == (x + y + z,)
+
+    assert Add.make_args((x + y)**z) == ((x + y)**z,)
+    assert Mul.make_args((x + y)**z) == ((x + y)**z,)
+
+
+def test_issue_5126():
+    assert (-2)**x*(-3)**x != 6**x
+    i = Symbol('i', integer=1)
+    assert (-2)**i*(-3)**i == 6**i
+
+
+def test_Rational_as_content_primitive():
+    c, p = S.One, S.Zero
+    assert (c*p).as_content_primitive() == (c, p)
+    c, p = S.Half, S.One
+    assert (c*p).as_content_primitive() == (c, p)
+
+
+def test_Add_as_content_primitive():
+    assert (x + 2).as_content_primitive() == (1, x + 2)
+
+    assert (3*x + 2).as_content_primitive() == (1, 3*x + 2)
+    assert (3*x + 3).as_content_primitive() == (3, x + 1)
+    assert (3*x + 6).as_content_primitive() == (3, x + 2)
+
+    assert (3*x + 2*y).as_content_primitive() == (1, 3*x + 2*y)
+    assert (3*x + 3*y).as_content_primitive() == (3, x + y)
+    assert (3*x + 6*y).as_content_primitive() == (3, x + 2*y)
+
+    assert (3/x + 2*x*y*z**2).as_content_primitive() == (1, 3/x + 2*x*y*z**2)
+    assert (3/x + 3*x*y*z**2).as_content_primitive() == (3, 1/x + x*y*z**2)
+    assert (3/x + 6*x*y*z**2).as_content_primitive() == (3, 1/x + 2*x*y*z**2)
+
+    assert (2*x/3 + 4*y/9).as_content_primitive() == \
+        (Rational(2, 9), 3*x + 2*y)
+    assert (2*x/3 + 2.5*y).as_content_primitive() == \
+        (Rational(1, 3), 2*x + 7.5*y)
+
+    # the coefficient may sort to a position other than 0
+    p = 3 + x + y
+    assert (2*p).expand().as_content_primitive() == (2, p)
+    assert (2.0*p).expand().as_content_primitive() == (1, 2.*p)
+    p *= -1
+    assert (2*p).expand().as_content_primitive() == (2, p)
+
+
+def test_Mul_as_content_primitive():
+    assert (2*x).as_content_primitive() == (2, x)
+    assert (x*(2 + 2*x)).as_content_primitive() == (2, x*(1 + x))
+    assert (x*(2 + 2*y)*(3*x + 3)**2).as_content_primitive() == \
+        (18, x*(1 + y)*(x + 1)**2)
+    assert ((2 + 2*x)**2*(3 + 6*x) + S.Half).as_content_primitive() == \
+        (S.Half, 24*(x + 1)**2*(2*x + 1) + 1)
+
+
+def test_Pow_as_content_primitive():
+    assert (x**y).as_content_primitive() == (1, x**y)
+    assert ((2*x + 2)**y).as_content_primitive() == \
+        (1, (Mul(2, (x + 1), evaluate=False))**y)
+    assert ((2*x + 2)**3).as_content_primitive() == (8, (x + 1)**3)
+
+
+def test_issue_5460():
+    u = Mul(2, (1 + x), evaluate=False)
+    assert (2 + u).args == (2, u)
+
+
+def test_product_irrational():
+    assert (I*pi).is_irrational is False
+    # The following used to be deduced from the above bug:
+    assert (I*pi).is_positive is False
+
+
+def test_issue_5919():
+    assert (x/(y*(1 + y))).expand() == x/(y**2 + y)
+
+
+def test_Mod():
+    assert Mod(x, 1).func is Mod
+    assert pi % pi is S.Zero
+    assert Mod(5, 3) == 2
+    assert Mod(-5, 3) == 1
+    assert Mod(5, -3) == -1
+    assert Mod(-5, -3) == -2
+    assert type(Mod(3.2, 2, evaluate=False)) == Mod
+    assert 5 % x == Mod(5, x)
+    assert x % 5 == Mod(x, 5)
+    assert x % y == Mod(x, y)
+    assert (x % y).subs({x: 5, y: 3}) == 2
+    assert Mod(nan, 1) is nan
+    assert Mod(1, nan) is nan
+    assert Mod(nan, nan) is nan
+
+    assert Mod(0, x) == 0
+    with raises(ZeroDivisionError):
+        Mod(x, 0)
+
+    k = Symbol('k', integer=True)
+    m = Symbol('m', integer=True, positive=True)
+    assert (x**m % x).func is Mod
+    assert (k**(-m) % k).func is Mod
+    assert k**m % k == 0
+    assert (-2*k)**m % k == 0
+
+    # Float handling
+    point3 = Float(3.3) % 1
+    assert (x - 3.3) % 1 == Mod(1.*x + 1 - point3, 1)
+    assert Mod(-3.3, 1) == 1 - point3
+    assert Mod(0.7, 1) == Float(0.7)
+    e = Mod(1.3, 1)
+    assert comp(e, .3) and e.is_Float
+    e = Mod(1.3, .7)
+    assert comp(e, .6) and e.is_Float
+    e = Mod(1.3, Rational(7, 10))
+    assert comp(e, .6) and e.is_Float
+    e = Mod(Rational(13, 10), 0.7)
+    assert comp(e, .6) and e.is_Float
+    e = Mod(Rational(13, 10), Rational(7, 10))
+    assert comp(e, .6) and e.is_Rational
+
+    # check that sign is right
+    r2 = sqrt(2)
+    r3 = sqrt(3)
+    for i in [-r3, -r2, r2, r3]:
+        for j in [-r3, -r2, r2, r3]:
+            assert verify_numerically(i % j, i.n() % j.n())
+    for _x in range(4):
+        for _y in range(9):
+            reps = [(x, _x), (y, _y)]
+            assert Mod(3*x + y, 9).subs(reps) == (3*_x + _y) % 9
+
+    # denesting
+    t = Symbol('t', real=True)
+    assert Mod(Mod(x, t), t) == Mod(x, t)
+    assert Mod(-Mod(x, t), t) == Mod(-x, t)
+    assert Mod(Mod(x, 2*t), t) == Mod(x, t)
+    assert Mod(-Mod(x, 2*t), t) == Mod(-x, t)
+    assert Mod(Mod(x, t), 2*t) == Mod(x, t)
+    assert Mod(-Mod(x, t), -2*t) == -Mod(x, t)
+    for i in [-4, -2, 2, 4]:
+        for j in [-4, -2, 2, 4]:
+            for k in range(4):
+                assert Mod(Mod(x, i), j).subs({x: k}) == (k % i) % j
+                assert Mod(-Mod(x, i), j).subs({x: k}) == -(k % i) % j
+
+    # known difference
+    assert Mod(5*sqrt(2), sqrt(5)) == 5*sqrt(2) - 3*sqrt(5)
+    p = symbols('p', positive=True)
+    assert Mod(2, p + 3) == 2
+    assert Mod(-2, p + 3) == p + 1
+    assert Mod(2, -p - 3) == -p - 1
+    assert Mod(-2, -p - 3) == -2
+    assert Mod(p + 5, p + 3) == 2
+    assert Mod(-p - 5, p + 3) == p + 1
+    assert Mod(p + 5, -p - 3) == -p - 1
+    assert Mod(-p - 5, -p - 3) == -2
+    assert Mod(p + 1, p - 1).func is Mod
+
+    # handling sums
+    assert (x + 3) % 1 == Mod(x, 1)
+    assert (x + 3.0) % 1 == Mod(1.*x, 1)
+    assert (x - S(33)/10) % 1 == Mod(x + S(7)/10, 1)
+
+    a = Mod(.6*x + y, .3*y)
+    b = Mod(0.1*y + 0.6*x, 0.3*y)
+    # Test that a, b are equal, with 1e-14 accuracy in coefficients
+    eps = 1e-14
+    assert abs((a.args[0] - b.args[0]).subs({x: 1, y: 1})) < eps
+    assert abs((a.args[1] - b.args[1]).subs({x: 1, y: 1})) < eps
+
+    assert (x + 1) % x == 1 % x
+    assert (x + y) % x == y % x
+    assert (x + y + 2) % x == (y + 2) % x
+    assert (a + 3*x + 1) % (2*x) == Mod(a + x + 1, 2*x)
+    assert (12*x + 18*y) % (3*x) == 3*Mod(6*y, x)
+
+    # gcd extraction
+    assert (-3*x) % (-2*y) == -Mod(3*x, 2*y)
+    assert (.6*pi) % (.3*x*pi) == 0.3*pi*Mod(2, x)
+    assert (.6*pi) % (.31*x*pi) == pi*Mod(0.6, 0.31*x)
+    assert (6*pi) % (.3*x*pi) == 0.3*pi*Mod(20, x)
+    assert (6*pi) % (.31*x*pi) == pi*Mod(6, 0.31*x)
+    assert (6*pi) % (.42*x*pi) == pi*Mod(6, 0.42*x)
+    assert (12*x) % (2*y) == 2*Mod(6*x, y)
+    assert (12*x) % (3*5*y) == 3*Mod(4*x, 5*y)
+    assert (12*x) % (15*x*y) == 3*x*Mod(4, 5*y)
+    assert (-2*pi) % (3*pi) == pi
+    assert (2*x + 2) % (x + 1) == 0
+    assert (x*(x + 1)) % (x + 1) == (x + 1)*Mod(x, 1)
+    assert Mod(5.0*x, 0.1*y) == 0.1*Mod(50*x, y)
+    i = Symbol('i', integer=True)
+    assert (3*i*x) % (2*i*y) == i*Mod(3*x, 2*y)
+    assert Mod(4*i, 4) == 0
+
+    # issue 8677
+    n = Symbol('n', integer=True, positive=True)
+    assert factorial(n) % n == 0
+    assert factorial(n + 2) % n == 0
+    assert (factorial(n + 4) % (n + 5)).func is Mod
+
+    # Wilson's theorem
+    assert factorial(18042, evaluate=False) % 18043 == 18042
+    p = Symbol('n', prime=True)
+    assert factorial(p - 1) % p == p - 1
+    assert factorial(p - 1) % -p == -1
+    assert (factorial(3, evaluate=False) % 4).doit() == 2
+    n = Symbol('n', composite=True, odd=True)
+    assert factorial(n - 1) % n == 0
+
+    # symbolic with known parity
+    n = Symbol('n', even=True)
+    assert Mod(n, 2) == 0
+    n = Symbol('n', odd=True)
+    assert Mod(n, 2) == 1
+
+    # issue 10963
+    assert (x**6000%400).args[1] == 400
+
+    #issue 13543
+    assert Mod(Mod(x + 1, 2) + 1, 2) == Mod(x, 2)
+
+    x1 = Symbol('x1', integer=True)
+    assert Mod(Mod(x1 + 2, 4)*(x1 + 4), 4) == Mod(x1*(x1 + 2), 4)
+    assert Mod(Mod(x1 + 2, 4)*4, 4) == 0
+
+    # issue 15493
+    i, j = symbols('i j', integer=True, positive=True)
+    assert Mod(3*i, 2) == Mod(i, 2)
+    assert Mod(8*i/j, 4) == 4*Mod(2*i/j, 1)
+    assert Mod(8*i, 4) == 0
+
+    # rewrite
+    assert Mod(x, y).rewrite(floor) == x - y*floor(x/y)
+    assert ((x - Mod(x, y))/y).rewrite(floor) == floor(x/y)
+
+    # issue 21373
+    from sympy.functions.elementary.hyperbolic import sinh
+    from sympy.functions.elementary.piecewise import Piecewise
+
+    x_r, y_r = symbols('x_r y_r', real=True)
+    assert (Piecewise((x_r, y_r > x_r), (y_r, True)) / z) % 1
+    expr = exp(sinh(Piecewise((x_r, y_r > x_r), (y_r, True)) / z))
+    expr.subs({1: 1.0})
+    sinh(Piecewise((x_r, y_r > x_r), (y_r, True)) * z ** -1.0).is_zero
+
+    # issue 24215
+    from sympy.abc import phi
+    assert Mod(4.0*Mod(phi, 1) , 2) == 2.0*(Mod(2*(Mod(phi, 1)), 1))
+
+
+def test_Mod_Pow():
+    # modular exponentiation
+    assert isinstance(Mod(Pow(2, 2, evaluate=False), 3), Integer)
+
+    assert Mod(Pow(4, 13, evaluate=False), 497) == Mod(Pow(4, 13), 497)
+    assert Mod(Pow(2, 10000000000, evaluate=False), 3) == 1
+    assert Mod(Pow(32131231232, 9**10**6, evaluate=False),10**12) == \
+        pow(32131231232,9**10**6,10**12)
+    assert Mod(Pow(33284959323, 123**999, evaluate=False),11**13) == \
+        pow(33284959323,123**999,11**13)
+    assert Mod(Pow(78789849597, 333**555, evaluate=False),12**9) == \
+        pow(78789849597,333**555,12**9)
+
+    # modular nested exponentiation
+    expr = Pow(2, 2, evaluate=False)
+    expr = Pow(2, expr, evaluate=False)
+    assert Mod(expr, 3**10) == 16
+    expr = Pow(2, expr, evaluate=False)
+    assert Mod(expr, 3**10) == 6487
+    expr = Pow(2, expr, evaluate=False)
+    assert Mod(expr, 3**10) == 32191
+    expr = Pow(2, expr, evaluate=False)
+    assert Mod(expr, 3**10) == 18016
+    expr = Pow(2, expr, evaluate=False)
+    assert Mod(expr, 3**10) == 5137
+
+    expr = Pow(2, 2, evaluate=False)
+    expr = Pow(expr, 2, evaluate=False)
+    assert Mod(expr, 3**10) == 16
+    expr = Pow(expr, 2, evaluate=False)
+    assert Mod(expr, 3**10) == 256
+    expr = Pow(expr, 2, evaluate=False)
+    assert Mod(expr, 3**10) == 6487
+    expr = Pow(expr, 2, evaluate=False)
+    assert Mod(expr, 3**10) == 38281
+    expr = Pow(expr, 2, evaluate=False)
+    assert Mod(expr, 3**10) == 15928
+
+    expr = Pow(2, 2, evaluate=False)
+    expr = Pow(expr, expr, evaluate=False)
+    assert Mod(expr, 3**10) == 256
+    expr = Pow(expr, expr, evaluate=False)
+    assert Mod(expr, 3**10) == 9229
+    expr = Pow(expr, expr, evaluate=False)
+    assert Mod(expr, 3**10) == 25708
+    expr = Pow(expr, expr, evaluate=False)
+    assert Mod(expr, 3**10) == 26608
+    expr = Pow(expr, expr, evaluate=False)
+    # XXX This used to fail in a nondeterministic way because of overflow
+    # error.
+    assert Mod(expr, 3**10) == 1966
+
+
+def test_Mod_is_integer():
+    p = Symbol('p', integer=True)
+    q1 = Symbol('q1', integer=True)
+    q2 = Symbol('q2', integer=True, nonzero=True)
+    assert Mod(x, y).is_integer is None
+    assert Mod(p, q1).is_integer is None
+    assert Mod(x, q2).is_integer is None
+    assert Mod(p, q2).is_integer
+
+
+def test_Mod_is_nonposneg():
+    n = Symbol('n', integer=True)
+    k = Symbol('k', integer=True, positive=True)
+    assert (n%3).is_nonnegative
+    assert Mod(n, -3).is_nonpositive
+    assert Mod(n, k).is_nonnegative
+    assert Mod(n, -k).is_nonpositive
+    assert Mod(k, n).is_nonnegative is None
+
+
+def test_issue_6001():
+    A = Symbol("A", commutative=False)
+    eq = A + A**2
+    # it doesn't matter whether it's True or False; they should
+    # just all be the same
+    assert (
+        eq.is_commutative ==
+        (eq + 1).is_commutative ==
+        (A + 1).is_commutative)
+
+    B = Symbol("B", commutative=False)
+    # Although commutative terms could cancel we return True
+    # meaning "there are non-commutative symbols; aftersubstitution
+    # that definition can change, e.g. (A*B).subs(B,A**-1) -> 1
+    assert (sqrt(2)*A).is_commutative is False
+    assert (sqrt(2)*A*B).is_commutative is False
+
+
+def test_polar():
+    from sympy.functions.elementary.complexes import polar_lift
+    p = Symbol('p', polar=True)
+    x = Symbol('x')
+    assert p.is_polar
+    assert x.is_polar is None
+    assert S.One.is_polar is None
+    assert (p**x).is_polar is True
+    assert (x**p).is_polar is None
+    assert ((2*p)**x).is_polar is True
+    assert (2*p).is_polar is True
+    assert (-2*p).is_polar is not True
+    assert (polar_lift(-2)*p).is_polar is True
+
+    q = Symbol('q', polar=True)
+    assert (p*q)**2 == p**2 * q**2
+    assert (2*q)**2 == 4 * q**2
+    assert ((p*q)**x).expand() == p**x * q**x
+
+
+def test_issue_6040():
+    a, b = Pow(1, 2, evaluate=False), S.One
+    assert a != b
+    assert b != a
+    assert not (a == b)
+    assert not (b == a)
+
+
+def test_issue_6082():
+    # Comparison is symmetric
+    assert Basic.compare(Max(x, 1), Max(x, 2)) == \
+      - Basic.compare(Max(x, 2), Max(x, 1))
+    # Equal expressions compare equal
+    assert Basic.compare(Max(x, 1), Max(x, 1)) == 0
+    # Basic subtypes (such as Max) compare different than standard types
+    assert Basic.compare(Max(1, x), frozenset((1, x))) != 0
+
+
+def test_issue_6077():
+    assert x**2.0/x == x**1.0
+    assert x/x**2.0 == x**-1.0
+    assert x*x**2.0 == x**3.0
+    assert x**1.5*x**2.5 == x**4.0
+
+    assert 2**(2.0*x)/2**x == 2**(1.0*x)
+    assert 2**x/2**(2.0*x) == 2**(-1.0*x)
+    assert 2**x*2**(2.0*x) == 2**(3.0*x)
+    assert 2**(1.5*x)*2**(2.5*x) == 2**(4.0*x)
+
+
+def test_mul_flatten_oo():
+    p = symbols('p', positive=True)
+    n, m = symbols('n,m', negative=True)
+    x_im = symbols('x_im', imaginary=True)
+    assert n*oo is -oo
+    assert n*m*oo is oo
+    assert p*oo is oo
+    assert x_im*oo != I*oo  # i could be +/- 3*I -> +/-oo
+
+
+def test_add_flatten():
+    # see https://github.com/sympy/sympy/issues/2633#issuecomment-29545524
+    a = oo + I*oo
+    b = oo - I*oo
+    assert a + b is nan
+    assert a - b is nan
+    # FIXME: This evaluates as:
+    #   >>> 1/a
+    #   0*(oo + oo*I)
+    # which should not simplify to 0. Should be fixed in Pow.eval
+    #assert (1/a).simplify() == (1/b).simplify() == 0
+
+    a = Pow(2, 3, evaluate=False)
+    assert a + a == 16
+
+
+def test_issue_5160_6087_6089_6090():
+    # issue 6087
+    assert ((-2*x*y**y)**3.2).n(2) == (2**3.2*(-x*y**y)**3.2).n(2)
+    # issue 6089
+    A, B, C = symbols('A,B,C', commutative=False)
+    assert (2.*B*C)**3 == 8.0*(B*C)**3
+    assert (-2.*B*C)**3 == -8.0*(B*C)**3
+    assert (-2*B*C)**2 == 4*(B*C)**2
+    # issue 5160
+    assert sqrt(-1.0*x) == 1.0*sqrt(-x)
+    assert sqrt(1.0*x) == 1.0*sqrt(x)
+    # issue 6090
+    assert (-2*x*y*A*B)**2 == 4*x**2*y**2*(A*B)**2
+
+
+def test_float_int_round():
+    assert int(float(sqrt(10))) == int(sqrt(10))
+    assert int(pi**1000) % 10 == 2
+    assert int(Float('1.123456789012345678901234567890e20', '')) == \
+        int(112345678901234567890)
+    assert int(Float('1.123456789012345678901234567890e25', '')) == \
+        int(11234567890123456789012345)
+    # decimal forces float so it's not an exact integer ending in 000000
+    assert int(Float('1.123456789012345678901234567890e35', '')) == \
+        112345678901234567890123456789000192
+    assert int(Float('123456789012345678901234567890e5', '')) == \
+        12345678901234567890123456789000000
+    assert Integer(Float('1.123456789012345678901234567890e20', '')) == \
+        112345678901234567890
+    assert Integer(Float('1.123456789012345678901234567890e25', '')) == \
+        11234567890123456789012345
+    # decimal forces float so it's not an exact integer ending in 000000
+    assert Integer(Float('1.123456789012345678901234567890e35', '')) == \
+        112345678901234567890123456789000192
+    assert Integer(Float('123456789012345678901234567890e5', '')) == \
+        12345678901234567890123456789000000
+    assert same_and_same_prec(Float('123000e-2',''), Float('1230.00', ''))
+    assert same_and_same_prec(Float('123000e2',''), Float('12300000', ''))
+
+    assert int(1 + Rational('.9999999999999999999999999')) == 1
+    assert int(pi/1e20) == 0
+    assert int(1 + pi/1e20) == 1
+    assert int(Add(1.2, -2, evaluate=False)) == int(1.2 - 2)
+    assert int(Add(1.2, +2, evaluate=False)) == int(1.2 + 2)
+    assert int(Add(1 + Float('.99999999999999999', ''), evaluate=False)) == 1
+    raises(TypeError, lambda: float(x))
+    raises(TypeError, lambda: float(sqrt(-1)))
+
+    assert int(12345678901234567890 + cos(1)**2 + sin(1)**2) == \
+        12345678901234567891
+
+
+def test_issue_6611a():
+    assert Mul.flatten([3**Rational(1, 3),
+        Pow(-Rational(1, 9), Rational(2, 3), evaluate=False)]) == \
+        ([Rational(1, 3), (-1)**Rational(2, 3)], [], None)
+
+
+def test_denest_add_mul():
+    # when working with evaluated expressions make sure they denest
+    eq = x + 1
+    eq = Add(eq, 2, evaluate=False)
+    eq = Add(eq, 2, evaluate=False)
+    assert Add(*eq.args) == x + 5
+    eq = x*2
+    eq = Mul(eq, 2, evaluate=False)
+    eq = Mul(eq, 2, evaluate=False)
+    assert Mul(*eq.args) == 8*x
+    # but don't let them denest unnecessarily
+    eq = Mul(-2, x - 2, evaluate=False)
+    assert 2*eq == Mul(-4, x - 2, evaluate=False)
+    assert -eq == Mul(2, x - 2, evaluate=False)
+
+
+def test_mul_coeff():
+    # It is important that all Numbers be removed from the seq;
+    # This can be tricky when powers combine to produce those numbers
+    p = exp(I*pi/3)
+    assert p**2*x*p*y*p*x*p**2 == x**2*y
+
+
+def test_mul_zero_detection():
+    nz = Dummy(real=True, zero=False)
+    r = Dummy(extended_real=True)
+    c = Dummy(real=False, complex=True)
+    c2 = Dummy(real=False, complex=True)
+    i = Dummy(imaginary=True)
+    e = nz*r*c
+    assert e.is_imaginary is None
+    assert e.is_extended_real is None
+    e = nz*c
+    assert e.is_imaginary is None
+    assert e.is_extended_real is False
+    e = nz*i*c
+    assert e.is_imaginary is False
+    assert e.is_extended_real is None
+    # check for more than one complex; it is important to use
+    # uniquely named Symbols to ensure that two factors appear
+    # e.g. if the symbols have the same name they just become
+    # a single factor, a power.
+    e = nz*i*c*c2
+    assert e.is_imaginary is None
+    assert e.is_extended_real is None
+
+    # _eval_is_extended_real and _eval_is_zero both employ trapping of the
+    # zero value so args should be tested in both directions and
+    # TO AVOID GETTING THE CACHED RESULT, Dummy MUST BE USED
+
+    # real is unknown
+    def test(z, b, e):
+        if z.is_zero and b.is_finite:
+            assert e.is_extended_real and e.is_zero
+        else:
+            assert e.is_extended_real is None
+            if b.is_finite:
+                if z.is_zero:
+                    assert e.is_zero
+                else:
+                    assert e.is_zero is None
+            elif b.is_finite is False:
+                if z.is_zero is None:
+                    assert e.is_zero is None
+                else:
+                    assert e.is_zero is False
+
+
+    for iz, ib in product(*[[True, False, None]]*2):
+        z = Dummy('z', nonzero=iz)
+        b = Dummy('f', finite=ib)
+        e = Mul(z, b, evaluate=False)
+        test(z, b, e)
+        z = Dummy('nz', nonzero=iz)
+        b = Dummy('f', finite=ib)
+        e = Mul(b, z, evaluate=False)
+        test(z, b, e)
+
+    # real is True
+    def test(z, b, e):
+        if z.is_zero and not b.is_finite:
+            assert e.is_extended_real is None
+        else:
+            assert e.is_extended_real is True
+
+    for iz, ib in product(*[[True, False, None]]*2):
+        z = Dummy('z', nonzero=iz, extended_real=True)
+        b = Dummy('b', finite=ib, extended_real=True)
+        e = Mul(z, b, evaluate=False)
+        test(z, b, e)
+        z = Dummy('z', nonzero=iz, extended_real=True)
+        b = Dummy('b', finite=ib, extended_real=True)
+        e = Mul(b, z, evaluate=False)
+        test(z, b, e)
+
+
+def test_Mul_with_zero_infinite():
+    zer = Dummy(zero=True)
+    inf = Dummy(finite=False)
+
+    e = Mul(zer, inf, evaluate=False)
+    assert e.is_extended_positive is None
+    assert e.is_hermitian is None
+
+    e = Mul(inf, zer, evaluate=False)
+    assert e.is_extended_positive is None
+    assert e.is_hermitian is None
+
+
+def test_Mul_does_not_cancel_infinities():
+    a, b = symbols('a b')
+    assert ((zoo + 3*a)/(3*a + zoo)) is nan
+    assert ((b - oo)/(b - oo)) is nan
+    # issue 13904
+    expr = (1/(a+b) + 1/(a-b))/(1/(a+b) - 1/(a-b))
+    assert expr.subs(b, a) is nan
+
+
+def test_Mul_does_not_distribute_infinity():
+    a, b = symbols('a b')
+    assert ((1 + I)*oo).is_Mul
+    assert ((a + b)*(-oo)).is_Mul
+    assert ((a + 1)*zoo).is_Mul
+    assert ((1 + I)*oo).is_finite is False
+    z = (1 + I)*oo
+    assert ((1 - I)*z).expand() is oo
+
+
+def test_issue_8247_8354():
+    from sympy.functions.elementary.trigonometric import tan
+    z = sqrt(1 + sqrt(3)) + sqrt(3 + 3*sqrt(3)) - sqrt(10 + 6*sqrt(3))
+    assert z.is_positive is False  # it's 0
+    z = S('''-2**(1/3)*(3*sqrt(93) + 29)**2 - 4*(3*sqrt(93) + 29)**(4/3) +
+        12*sqrt(93)*(3*sqrt(93) + 29)**(1/3) + 116*(3*sqrt(93) + 29)**(1/3) +
+        174*2**(1/3)*sqrt(93) + 1678*2**(1/3)''')
+    assert z.is_positive is False  # it's 0
+    z = 2*(-3*tan(19*pi/90) + sqrt(3))*cos(11*pi/90)*cos(19*pi/90) - \
+        sqrt(3)*(-3 + 4*cos(19*pi/90)**2)
+    assert z.is_positive is not True  # it's zero and it shouldn't hang
+    z = S('''9*(3*sqrt(93) + 29)**(2/3)*((3*sqrt(93) +
+        29)**(1/3)*(-2**(2/3)*(3*sqrt(93) + 29)**(1/3) - 2) - 2*2**(1/3))**3 +
+        72*(3*sqrt(93) + 29)**(2/3)*(81*sqrt(93) + 783) + (162*sqrt(93) +
+        1566)*((3*sqrt(93) + 29)**(1/3)*(-2**(2/3)*(3*sqrt(93) + 29)**(1/3) -
+        2) - 2*2**(1/3))**2''')
+    assert z.is_positive is False  # it's 0 (and a single _mexpand isn't enough)
+
+
+def test_Add_is_zero():
+    x, y = symbols('x y', zero=True)
+    assert (x + y).is_zero
+
+    # Issue 15873
+    e = -2*I + (1 + I)**2
+    assert e.is_zero is None
+
+
+def test_issue_14392():
+    assert (sin(zoo)**2).as_real_imag() == (nan, nan)
+
+
+def test_divmod():
+    assert divmod(x, y) == (x//y, x % y)
+    assert divmod(x, 3) == (x//3, x % 3)
+    assert divmod(3, x) == (3//x, 3 % x)
+
+
+def test__neg__():
+    assert -(x*y) == -x*y
+    assert -(-x*y) == x*y
+    assert -(1.*x) == -1.*x
+    assert -(-1.*x) == 1.*x
+    assert -(2.*x) == -2.*x
+    assert -(-2.*x) == 2.*x
+    with distribute(False):
+        eq = -(x + y)
+        assert eq.is_Mul and eq.args == (-1, x + y)
+    with evaluate(False):
+        eq = -(x + y)
+        assert eq.is_Mul and eq.args == (-1, x + y)
+
+
+def test_issue_18507():
+    assert Mul(zoo, zoo, 0) is nan
+
+
+def test_issue_17130():
+    e = Add(b, -b, I, -I, evaluate=False)
+    assert e.is_zero is None # ideally this would be True
+
+
+def test_issue_21034():
+    e = -I*log((re(asin(5)) + I*im(asin(5)))/sqrt(re(asin(5))**2 + im(asin(5))**2))/pi
+    assert e.round(2)
+
+
+def test_issue_22021():
+    from sympy.calculus.accumulationbounds import AccumBounds
+    # these objects are special cases in Mul
+    from sympy.tensor.tensor import TensorIndexType, tensor_indices, tensor_heads
+    L = TensorIndexType("L")
+    i = tensor_indices("i", L)
+    A, B = tensor_heads("A B", [L])
+    e = A(i) + B(i)
+    assert -e == -1*e
+    e = zoo + x
+    assert -e == -1*e
+    a = AccumBounds(1, 2)
+    e = a + x
+    assert -e == -1*e
+    for args in permutations((zoo, a, x)):
+        e = Add(*args, evaluate=False)
+        assert -e == -1*e
+    assert 2*Add(1, x, x, evaluate=False) == 4*x + 2
+
+
+def test_issue_22244():
+    assert -(zoo*x) == zoo*x
+
+
+def test_issue_22453():
+    from sympy.utilities.iterables import cartes
+    e = Symbol('e', extended_positive=True)
+    for a, b in cartes(*[[oo, -oo, 3]]*2):
+        if a == b == 3:
+            continue
+        i = a + I*b
+        assert i**(1 + e) is S.ComplexInfinity
+        assert i**-e is S.Zero
+        assert unchanged(Pow, i, e)
+    assert 1/(oo + I*oo) is S.Zero
+    r, i = [Dummy(infinite=True, extended_real=True) for _ in range(2)]
+    assert 1/(r + I*i) is S.Zero
+    assert 1/(3 + I*i) is S.Zero
+    assert 1/(r + I*3) is S.Zero
+
+
+def test_issue_22613():
+    assert (0**(x - 2)).as_content_primitive() == (1, 0**(x - 2))
+    assert (0**(x + 2)).as_content_primitive() == (1, 0**(x + 2))

env-llmeval/lib/python3.10/site-packages/sympy/core/tests/test_assumptions.py

@@ -0,0 +1,1335 @@
+from sympy.core.mod import Mod
+from sympy.core.numbers import (I, oo, pi)
+from sympy.functions.combinatorial.factorials import factorial
+from sympy.functions.elementary.exponential import (exp, log)
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.functions.elementary.trigonometric import (asin, sin)
+from sympy.simplify.simplify import simplify
+from sympy.core import Symbol, S, Rational, Integer, Dummy, Wild, Pow
+from sympy.core.assumptions import (assumptions, check_assumptions,
+    failing_assumptions, common_assumptions, _generate_assumption_rules,
+    _load_pre_generated_assumption_rules)
+from sympy.core.facts import InconsistentAssumptions
+from sympy.core.random import seed
+from sympy.combinatorics import Permutation
+from sympy.combinatorics.perm_groups import PermutationGroup
+
+from sympy.testing.pytest import raises, XFAIL
+
+
+def test_symbol_unset():
+    x = Symbol('x', real=True, integer=True)
+    assert x.is_real is True
+    assert x.is_integer is True
+    assert x.is_imaginary is False
+    assert x.is_noninteger is False
+    assert x.is_number is False
+
+
+def test_zero():
+    z = Integer(0)
+    assert z.is_commutative is True
+    assert z.is_integer is True
+    assert z.is_rational is True
+    assert z.is_algebraic is True
+    assert z.is_transcendental is False
+    assert z.is_real is True
+    assert z.is_complex is True
+    assert z.is_noninteger is False
+    assert z.is_irrational is False
+    assert z.is_imaginary is False
+    assert z.is_positive is False
+    assert z.is_negative is False
+    assert z.is_nonpositive is True
+    assert z.is_nonnegative is True
+    assert z.is_even is True
+    assert z.is_odd is False
+    assert z.is_finite is True
+    assert z.is_infinite is False
+    assert z.is_comparable is True
+    assert z.is_prime is False
+    assert z.is_composite is False
+    assert z.is_number is True
+
+
+def test_one():
+    z = Integer(1)
+    assert z.is_commutative is True
+    assert z.is_integer is True
+    assert z.is_rational is True
+    assert z.is_algebraic is True
+    assert z.is_transcendental is False
+    assert z.is_real is True
+    assert z.is_complex is True
+    assert z.is_noninteger is False
+    assert z.is_irrational is False
+    assert z.is_imaginary is False
+    assert z.is_positive is True
+    assert z.is_negative is False
+    assert z.is_nonpositive is False
+    assert z.is_nonnegative is True
+    assert z.is_even is False
+    assert z.is_odd is True
+    assert z.is_finite is True
+    assert z.is_infinite is False
+    assert z.is_comparable is True
+    assert z.is_prime is False
+    assert z.is_number is True
+    assert z.is_composite is False  # issue 8807
+
+
+def test_negativeone():
+    z = Integer(-1)
+    assert z.is_commutative is True
+    assert z.is_integer is True
+    assert z.is_rational is True
+    assert z.is_algebraic is True
+    assert z.is_transcendental is False
+    assert z.is_real is True
+    assert z.is_complex is True
+    assert z.is_noninteger is False
+    assert z.is_irrational is False
+    assert z.is_imaginary is False
+    assert z.is_positive is False
+    assert z.is_negative is True
+    assert z.is_nonpositive is True
+    assert z.is_nonnegative is False
+    assert z.is_even is False
+    assert z.is_odd is True
+    assert z.is_finite is True
+    assert z.is_infinite is False
+    assert z.is_comparable is True
+    assert z.is_prime is False
+    assert z.is_composite is False
+    assert z.is_number is True
+
+
+def test_infinity():
+    oo = S.Infinity
+
+    assert oo.is_commutative is True
+    assert oo.is_integer is False
+    assert oo.is_rational is False
+    assert oo.is_algebraic is False
+    assert oo.is_transcendental is False
+    assert oo.is_extended_real is True
+    assert oo.is_real is False
+    assert oo.is_complex is False
+    assert oo.is_noninteger is True
+    assert oo.is_irrational is False
+    assert oo.is_imaginary is False
+    assert oo.is_nonzero is False
+    assert oo.is_positive is False
+    assert oo.is_negative is False
+    assert oo.is_nonpositive is False
+    assert oo.is_nonnegative is False
+    assert oo.is_extended_nonzero is True
+    assert oo.is_extended_positive is True
+    assert oo.is_extended_negative is False
+    assert oo.is_extended_nonpositive is False
+    assert oo.is_extended_nonnegative is True
+    assert oo.is_even is False
+    assert oo.is_odd is False
+    assert oo.is_finite is False
+    assert oo.is_infinite is True
+    assert oo.is_comparable is True
+    assert oo.is_prime is False
+    assert oo.is_composite is False
+    assert oo.is_number is True
+
+
+def test_neg_infinity():
+    mm = S.NegativeInfinity
+
+    assert mm.is_commutative is True
+    assert mm.is_integer is False
+    assert mm.is_rational is False
+    assert mm.is_algebraic is False
+    assert mm.is_transcendental is False
+    assert mm.is_extended_real is True
+    assert mm.is_real is False
+    assert mm.is_complex is False
+    assert mm.is_noninteger is True
+    assert mm.is_irrational is False
+    assert mm.is_imaginary is False
+    assert mm.is_nonzero is False
+    assert mm.is_positive is False
+    assert mm.is_negative is False
+    assert mm.is_nonpositive is False
+    assert mm.is_nonnegative is False
+    assert mm.is_extended_nonzero is True
+    assert mm.is_extended_positive is False
+    assert mm.is_extended_negative is True
+    assert mm.is_extended_nonpositive is True
+    assert mm.is_extended_nonnegative is False
+    assert mm.is_even is False
+    assert mm.is_odd is False
+    assert mm.is_finite is False
+    assert mm.is_infinite is True
+    assert mm.is_comparable is True
+    assert mm.is_prime is False
+    assert mm.is_composite is False
+    assert mm.is_number is True
+
+
+def test_zoo():
+    zoo = S.ComplexInfinity
+    assert zoo.is_complex is False
+    assert zoo.is_real is False
+    assert zoo.is_prime is False
+
+
+def test_nan():
+    nan = S.NaN
+
+    assert nan.is_commutative is True
+    assert nan.is_integer is None
+    assert nan.is_rational is None
+    assert nan.is_algebraic is None
+    assert nan.is_transcendental is None
+    assert nan.is_real is None
+    assert nan.is_complex is None
+    assert nan.is_noninteger is None
+    assert nan.is_irrational is None
+    assert nan.is_imaginary is None
+    assert nan.is_positive is None
+    assert nan.is_negative is None
+    assert nan.is_nonpositive is None
+    assert nan.is_nonnegative is None
+    assert nan.is_even is None
+    assert nan.is_odd is None
+    assert nan.is_finite is None
+    assert nan.is_infinite is None
+    assert nan.is_comparable is False
+    assert nan.is_prime is None
+    assert nan.is_composite is None
+    assert nan.is_number is True
+
+
+def test_pos_rational():
+    r = Rational(3, 4)
+    assert r.is_commutative is True
+    assert r.is_integer is False
+    assert r.is_rational is True
+    assert r.is_algebraic is True
+    assert r.is_transcendental is False
+    assert r.is_real is True
+    assert r.is_complex is True
+    assert r.is_noninteger is True
+    assert r.is_irrational is False
+    assert r.is_imaginary is False
+    assert r.is_positive is True
+    assert r.is_negative is False
+    assert r.is_nonpositive is False
+    assert r.is_nonnegative is True
+    assert r.is_even is False
+    assert r.is_odd is False
+    assert r.is_finite is True
+    assert r.is_infinite is False
+    assert r.is_comparable is True
+    assert r.is_prime is False
+    assert r.is_composite is False
+
+    r = Rational(1, 4)
+    assert r.is_nonpositive is False
+    assert r.is_positive is True
+    assert r.is_negative is False
+    assert r.is_nonnegative is True
+    r = Rational(5, 4)
+    assert r.is_negative is False
+    assert r.is_positive is True
+    assert r.is_nonpositive is False
+    assert r.is_nonnegative is True
+    r = Rational(5, 3)
+    assert r.is_nonnegative is True
+    assert r.is_positive is True
+    assert r.is_negative is False
+    assert r.is_nonpositive is False
+
+
+def test_neg_rational():
+    r = Rational(-3, 4)
+    assert r.is_positive is False
+    assert r.is_nonpositive is True
+    assert r.is_negative is True
+    assert r.is_nonnegative is False
+    r = Rational(-1, 4)
+    assert r.is_nonpositive is True
+    assert r.is_positive is False
+    assert r.is_negative is True
+    assert r.is_nonnegative is False
+    r = Rational(-5, 4)
+    assert r.is_negative is True
+    assert r.is_positive is False
+    assert r.is_nonpositive is True
+    assert r.is_nonnegative is False
+    r = Rational(-5, 3)
+    assert r.is_nonnegative is False
+    assert r.is_positive is False
+    assert r.is_negative is True
+    assert r.is_nonpositive is True
+
+
+def test_pi():
+    z = S.Pi
+    assert z.is_commutative is True
+    assert z.is_integer is False
+    assert z.is_rational is False
+    assert z.is_algebraic is False
+    assert z.is_transcendental is True
+    assert z.is_real is True
+    assert z.is_complex is True
+    assert z.is_noninteger is True
+    assert z.is_irrational is True
+    assert z.is_imaginary is False
+    assert z.is_positive is True
+    assert z.is_negative is False
+    assert z.is_nonpositive is False
+    assert z.is_nonnegative is True
+    assert z.is_even is False
+    assert z.is_odd is False
+    assert z.is_finite is True
+    assert z.is_infinite is False
+    assert z.is_comparable is True
+    assert z.is_prime is False
+    assert z.is_composite is False
+
+
+def test_E():
+    z = S.Exp1
+    assert z.is_commutative is True
+    assert z.is_integer is False
+    assert z.is_rational is False
+    assert z.is_algebraic is False
+    assert z.is_transcendental is True
+    assert z.is_real is True
+    assert z.is_complex is True
+    assert z.is_noninteger is True
+    assert z.is_irrational is True
+    assert z.is_imaginary is False
+    assert z.is_positive is True
+    assert z.is_negative is False
+    assert z.is_nonpositive is False
+    assert z.is_nonnegative is True
+    assert z.is_even is False
+    assert z.is_odd is False
+    assert z.is_finite is True
+    assert z.is_infinite is False
+    assert z.is_comparable is True
+    assert z.is_prime is False
+    assert z.is_composite is False
+
+
+def test_I():
+    z = S.ImaginaryUnit
+    assert z.is_commutative is True
+    assert z.is_integer is False
+    assert z.is_rational is False
+    assert z.is_algebraic is True
+    assert z.is_transcendental is False
+    assert z.is_real is False
+    assert z.is_complex is True
+    assert z.is_noninteger is False
+    assert z.is_irrational is False
+    assert z.is_imaginary is True
+    assert z.is_positive is False
+    assert z.is_negative is False
+    assert z.is_nonpositive is False
+    assert z.is_nonnegative is False
+    assert z.is_even is False
+    assert z.is_odd is False
+    assert z.is_finite is True
+    assert z.is_infinite is False
+    assert z.is_comparable is False
+    assert z.is_prime is False
+    assert z.is_composite is False
+
+
+def test_symbol_real_false():
+    # issue 3848
+    a = Symbol('a', real=False)
+
+    assert a.is_real is False
+    assert a.is_integer is False
+    assert a.is_zero is False
+
+    assert a.is_negative is False
+    assert a.is_positive is False
+    assert a.is_nonnegative is False
+    assert a.is_nonpositive is False
+    assert a.is_nonzero is False
+
+    assert a.is_extended_negative is None
+    assert a.is_extended_positive is None
+    assert a.is_extended_nonnegative is None
+    assert a.is_extended_nonpositive is None
+    assert a.is_extended_nonzero is None
+
+
+def test_symbol_extended_real_false():
+    # issue 3848
+    a = Symbol('a', extended_real=False)
+
+    assert a.is_real is False
+    assert a.is_integer is False
+    assert a.is_zero is False
+
+    assert a.is_negative is False
+    assert a.is_positive is False
+    assert a.is_nonnegative is False
+    assert a.is_nonpositive is False
+    assert a.is_nonzero is False
+
+    assert a.is_extended_negative is False
+    assert a.is_extended_positive is False
+    assert a.is_extended_nonnegative is False
+    assert a.is_extended_nonpositive is False
+    assert a.is_extended_nonzero is False
+
+
+def test_symbol_imaginary():
+    a = Symbol('a', imaginary=True)
+
+    assert a.is_real is False
+    assert a.is_integer is False
+    assert a.is_negative is False
+    assert a.is_positive is False
+    assert a.is_nonnegative is False
+    assert a.is_nonpositive is False
+    assert a.is_zero is False
+    assert a.is_nonzero is False  # since nonzero -> real
+
+
+def test_symbol_zero():
+    x = Symbol('x', zero=True)
+    assert x.is_positive is False
+    assert x.is_nonpositive
+    assert x.is_negative is False
+    assert x.is_nonnegative
+    assert x.is_zero is True
+    # TODO Change to x.is_nonzero is None
+    # See https://github.com/sympy/sympy/pull/9583
+    assert x.is_nonzero is False
+    assert x.is_finite is True
+
+
+def test_symbol_positive():
+    x = Symbol('x', positive=True)
+    assert x.is_positive is True
+    assert x.is_nonpositive is False
+    assert x.is_negative is False
+    assert x.is_nonnegative is True
+    assert x.is_zero is False
+    assert x.is_nonzero is True
+
+
+def test_neg_symbol_positive():
+    x = -Symbol('x', positive=True)
+    assert x.is_positive is False
+    assert x.is_nonpositive is True
+    assert x.is_negative is True
+    assert x.is_nonnegative is False
+    assert x.is_zero is False
+    assert x.is_nonzero is True
+
+
+def test_symbol_nonpositive():
+    x = Symbol('x', nonpositive=True)
+    assert x.is_positive is False
+    assert x.is_nonpositive is True
+    assert x.is_negative is None
+    assert x.is_nonnegative is None
+    assert x.is_zero is None
+    assert x.is_nonzero is None
+
+
+def test_neg_symbol_nonpositive():
+    x = -Symbol('x', nonpositive=True)
+    assert x.is_positive is None
+    assert x.is_nonpositive is None
+    assert x.is_negative is False
+    assert x.is_nonnegative is True
+    assert x.is_zero is None
+    assert x.is_nonzero is None
+
+
+def test_symbol_falsepositive():
+    x = Symbol('x', positive=False)
+    assert x.is_positive is False
+    assert x.is_nonpositive is None
+    assert x.is_negative is None
+    assert x.is_nonnegative is None
+    assert x.is_zero is None
+    assert x.is_nonzero is None
+
+
+def test_symbol_falsepositive_mul():
+    # To test pull request 9379
+    # Explicit handling of arg.is_positive=False was added to Mul._eval_is_positive
+    x = 2*Symbol('x', positive=False)
+    assert x.is_positive is False  # This was None before
+    assert x.is_nonpositive is None
+    assert x.is_negative is None
+    assert x.is_nonnegative is None
+    assert x.is_zero is None
+    assert x.is_nonzero is None
+
+
+@XFAIL
+def test_symbol_infinitereal_mul():
+    ix = Symbol('ix', infinite=True, extended_real=True)
+    assert (-ix).is_extended_positive is None
+
+
+def test_neg_symbol_falsepositive():
+    x = -Symbol('x', positive=False)
+    assert x.is_positive is None
+    assert x.is_nonpositive is None
+    assert x.is_negative is False
+    assert x.is_nonnegative is None
+    assert x.is_zero is None
+    assert x.is_nonzero is None
+
+
+def test_neg_symbol_falsenegative():
+    # To test pull request 9379
+    # Explicit handling of arg.is_negative=False was added to Mul._eval_is_positive
+    x = -Symbol('x', negative=False)
+    assert x.is_positive is False  # This was None before
+    assert x.is_nonpositive is None
+    assert x.is_negative is None
+    assert x.is_nonnegative is None
+    assert x.is_zero is None
+    assert x.is_nonzero is None
+
+
+def test_symbol_falsepositive_real():
+    x = Symbol('x', positive=False, real=True)
+    assert x.is_positive is False
+    assert x.is_nonpositive is True
+    assert x.is_negative is None
+    assert x.is_nonnegative is None
+    assert x.is_zero is None
+    assert x.is_nonzero is None
+
+
+def test_neg_symbol_falsepositive_real():
+    x = -Symbol('x', positive=False, real=True)
+    assert x.is_positive is None
+    assert x.is_nonpositive is None
+    assert x.is_negative is False
+    assert x.is_nonnegative is True
+    assert x.is_zero is None
+    assert x.is_nonzero is None
+
+
+def test_symbol_falsenonnegative():
+    x = Symbol('x', nonnegative=False)
+    assert x.is_positive is False
+    assert x.is_nonpositive is None
+    assert x.is_negative is None
+    assert x.is_nonnegative is False
+    assert x.is_zero is False
+    assert x.is_nonzero is None
+
+
+@XFAIL
+def test_neg_symbol_falsenonnegative():
+    x = -Symbol('x', nonnegative=False)
+    assert x.is_positive is None
+    assert x.is_nonpositive is False  # this currently returns None
+    assert x.is_negative is False  # this currently returns None
+    assert x.is_nonnegative is None
+    assert x.is_zero is False  # this currently returns None
+    assert x.is_nonzero is True  # this currently returns None
+
+
+def test_symbol_falsenonnegative_real():
+    x = Symbol('x', nonnegative=False, real=True)
+    assert x.is_positive is False
+    assert x.is_nonpositive is True
+    assert x.is_negative is True
+    assert x.is_nonnegative is False
+    assert x.is_zero is False
+    assert x.is_nonzero is True
+
+
+def test_neg_symbol_falsenonnegative_real():
+    x = -Symbol('x', nonnegative=False, real=True)
+    assert x.is_positive is True
+    assert x.is_nonpositive is False
+    assert x.is_negative is False
+    assert x.is_nonnegative is True
+    assert x.is_zero is False
+    assert x.is_nonzero is True
+
+
+def test_prime():
+    assert S.NegativeOne.is_prime is False
+    assert S(-2).is_prime is False
+    assert S(-4).is_prime is False
+    assert S.Zero.is_prime is False
+    assert S.One.is_prime is False
+    assert S(2).is_prime is True
+    assert S(17).is_prime is True
+    assert S(4).is_prime is False
+
+
+def test_composite():
+    assert S.NegativeOne.is_composite is False
+    assert S(-2).is_composite is False
+    assert S(-4).is_composite is False
+    assert S.Zero.is_composite is False
+    assert S(2).is_composite is False
+    assert S(17).is_composite is False
+    assert S(4).is_composite is True
+    x = Dummy(integer=True, positive=True, prime=False)
+    assert x.is_composite is None # x could be 1
+    assert (x + 1).is_composite is None
+    x = Dummy(positive=True, even=True, prime=False)
+    assert x.is_integer is True
+    assert x.is_composite is True
+
+
+def test_prime_symbol():
+    x = Symbol('x', prime=True)
+    assert x.is_prime is True
+    assert x.is_integer is True
+    assert x.is_positive is True
+    assert x.is_negative is False
+    assert x.is_nonpositive is False
+    assert x.is_nonnegative is True
+
+    x = Symbol('x', prime=False)
+    assert x.is_prime is False
+    assert x.is_integer is None
+    assert x.is_positive is None
+    assert x.is_negative is None
+    assert x.is_nonpositive is None
+    assert x.is_nonnegative is None
+
+
+def test_symbol_noncommutative():
+    x = Symbol('x', commutative=True)
+    assert x.is_complex is None
+
+    x = Symbol('x', commutative=False)
+    assert x.is_integer is False
+    assert x.is_rational is False
+    assert x.is_algebraic is False
+    assert x.is_irrational is False
+    assert x.is_real is False
+    assert x.is_complex is False
+
+
+def test_other_symbol():
+    x = Symbol('x', integer=True)
+    assert x.is_integer is True
+    assert x.is_real is True
+    assert x.is_finite is True
+
+    x = Symbol('x', integer=True, nonnegative=True)
+    assert x.is_integer is True
+    assert x.is_nonnegative is True
+    assert x.is_negative is False
+    assert x.is_positive is None
+    assert x.is_finite is True
+
+    x = Symbol('x', integer=True, nonpositive=True)
+    assert x.is_integer is True
+    assert x.is_nonpositive is True
+    assert x.is_positive is False
+    assert x.is_negative is None
+    assert x.is_finite is True
+
+    x = Symbol('x', odd=True)
+    assert x.is_odd is True
+    assert x.is_even is False
+    assert x.is_integer is True
+    assert x.is_finite is True
+
+    x = Symbol('x', odd=False)
+    assert x.is_odd is False
+    assert x.is_even is None
+    assert x.is_integer is None
+    assert x.is_finite is None
+
+    x = Symbol('x', even=True)
+    assert x.is_even is True
+    assert x.is_odd is False
+    assert x.is_integer is True
+    assert x.is_finite is True
+
+    x = Symbol('x', even=False)
+    assert x.is_even is False
+    assert x.is_odd is None
+    assert x.is_integer is None
+    assert x.is_finite is None
+
+    x = Symbol('x', integer=True, nonnegative=True)
+    assert x.is_integer is True
+    assert x.is_nonnegative is True
+    assert x.is_finite is True
+
+    x = Symbol('x', integer=True, nonpositive=True)
+    assert x.is_integer is True
+    assert x.is_nonpositive is True
+    assert x.is_finite is True
+
+    x = Symbol('x', rational=True)
+    assert x.is_real is True
+    assert x.is_finite is True
+
+    x = Symbol('x', rational=False)
+    assert x.is_real is None
+    assert x.is_finite is None
+
+    x = Symbol('x', irrational=True)
+    assert x.is_real is True
+    assert x.is_finite is True
+
+    x = Symbol('x', irrational=False)
+    assert x.is_real is None
+    assert x.is_finite is None
+
+    with raises(AttributeError):
+        x.is_real = False
+
+    x = Symbol('x', algebraic=True)
+    assert x.is_transcendental is False
+    x = Symbol('x', transcendental=True)
+    assert x.is_algebraic is False
+    assert x.is_rational is False
+    assert x.is_integer is False
+
+
+def test_evaluate_false():
+    # Previously this failed because the assumptions query would make new
+    # expressions and some of the evaluation logic would fail under
+    # evaluate(False).
+    from sympy.core.parameters import evaluate
+    from sympy.abc import x, h
+    f = 2**x**7
+    with evaluate(False):
+        fh = f.xreplace({x: x+h})
+        assert fh.exp.is_rational is None
+
+
+def test_issue_3825():
+    """catch: hash instability"""
+    x = Symbol("x")
+    y = Symbol("y")
+    a1 = x + y
+    a2 = y + x
+    a2.is_comparable
+
+    h1 = hash(a1)
+    h2 = hash(a2)
+    assert h1 == h2
+
+
+def test_issue_4822():
+    z = (-1)**Rational(1, 3)*(1 - I*sqrt(3))
+    assert z.is_real in [True, None]
+
+
+def test_hash_vs_typeinfo():
+    """seemingly different typeinfo, but in fact equal"""
+
+    # the following two are semantically equal
+    x1 = Symbol('x', even=True)
+    x2 = Symbol('x', integer=True, odd=False)
+
+    assert hash(x1) == hash(x2)
+    assert x1 == x2
+
+
+def test_hash_vs_typeinfo_2():
+    """different typeinfo should mean !eq"""
+    # the following two are semantically different
+    x = Symbol('x')
+    x1 = Symbol('x', even=True)
+
+    assert x != x1
+    assert hash(x) != hash(x1)  # This might fail with very low probability
+
+
+def test_hash_vs_eq():
+    """catch: different hash for equal objects"""
+    a = 1 + S.Pi    # important: do not fold it into a Number instance
+    ha = hash(a)  # it should be Add/Mul/... to trigger the bug
+
+    a.is_positive   # this uses .evalf() and deduces it is positive
+    assert a.is_positive is True
+
+    # be sure that hash stayed the same
+    assert ha == hash(a)
+
+    # now b should be the same expression
+    b = a.expand(trig=True)
+    hb = hash(b)
+
+    assert a == b
+    assert ha == hb
+
+
+def test_Add_is_pos_neg():
+    # these cover lines not covered by the rest of tests in core
+    n = Symbol('n', extended_negative=True, infinite=True)
+    nn = Symbol('n', extended_nonnegative=True, infinite=True)
+    np = Symbol('n', extended_nonpositive=True, infinite=True)
+    p = Symbol('p', extended_positive=True, infinite=True)
+    r = Dummy(extended_real=True, finite=False)
+    x = Symbol('x')
+    xf = Symbol('xf', finite=True)
+    assert (n + p).is_extended_positive is None
+    assert (n + x).is_extended_positive is None
+    assert (p + x).is_extended_positive is None
+    assert (n + p).is_extended_negative is None
+    assert (n + x).is_extended_negative is None
+    assert (p + x).is_extended_negative is None
+
+    assert (n + xf).is_extended_positive is False
+    assert (p + xf).is_extended_positive is True
+    assert (n + xf).is_extended_negative is True
+    assert (p + xf).is_extended_negative is False
+
+    assert (x - S.Infinity).is_extended_negative is None  # issue 7798
+    # issue 8046, 16.2
+    assert (p + nn).is_extended_positive
+    assert (n + np).is_extended_negative
+    assert (p + r).is_extended_positive is None
+
+
+def test_Add_is_imaginary():
+    nn = Dummy(nonnegative=True)
+    assert (I*nn + I).is_imaginary  # issue 8046, 17
+
+
+def test_Add_is_algebraic():
+    a = Symbol('a', algebraic=True)
+    b = Symbol('a', algebraic=True)
+    na = Symbol('na', algebraic=False)
+    nb = Symbol('nb', algebraic=False)
+    x = Symbol('x')
+    assert (a + b).is_algebraic
+    assert (na + nb).is_algebraic is None
+    assert (a + na).is_algebraic is False
+    assert (a + x).is_algebraic is None
+    assert (na + x).is_algebraic is None
+
+
+def test_Mul_is_algebraic():
+    a = Symbol('a', algebraic=True)
+    b = Symbol('b', algebraic=True)
+    na = Symbol('na', algebraic=False)
+    an = Symbol('an', algebraic=True, nonzero=True)
+    nb = Symbol('nb', algebraic=False)
+    x = Symbol('x')
+    assert (a*b).is_algebraic is True
+    assert (na*nb).is_algebraic is None
+    assert (a*na).is_algebraic is None
+    assert (an*na).is_algebraic is False
+    assert (a*x).is_algebraic is None
+    assert (na*x).is_algebraic is None
+
+
+def test_Pow_is_algebraic():
+    e = Symbol('e', algebraic=True)
+
+    assert Pow(1, e, evaluate=False).is_algebraic
+    assert Pow(0, e, evaluate=False).is_algebraic
+
+    a = Symbol('a', algebraic=True)
+    azf = Symbol('azf', algebraic=True, zero=False)
+    na = Symbol('na', algebraic=False)
+    ia = Symbol('ia', algebraic=True, irrational=True)
+    ib = Symbol('ib', algebraic=True, irrational=True)
+    r = Symbol('r', rational=True)
+    x = Symbol('x')
+    assert (a**2).is_algebraic is True
+    assert (a**r).is_algebraic is None
+    assert (azf**r).is_algebraic is True
+    assert (a**x).is_algebraic is None
+    assert (na**r).is_algebraic is None
+    assert (ia**r).is_algebraic is True
+    assert (ia**ib).is_algebraic is False
+
+    assert (a**e).is_algebraic is None
+
+    # Gelfond-Schneider constant:
+    assert Pow(2, sqrt(2), evaluate=False).is_algebraic is False
+
+    assert Pow(S.GoldenRatio, sqrt(3), evaluate=False).is_algebraic is False
+
+    # issue 8649
+    t = Symbol('t', real=True, transcendental=True)
+    n = Symbol('n', integer=True)
+    assert (t**n).is_algebraic is None
+    assert (t**n).is_integer is None
+
+    assert (pi**3).is_algebraic is False
+    r = Symbol('r', zero=True)
+    assert (pi**r).is_algebraic is True
+
+
+def test_Mul_is_prime_composite():
+    x = Symbol('x', positive=True, integer=True)
+    y = Symbol('y', positive=True, integer=True)
+    assert (x*y).is_prime is None
+    assert ( (x+1)*(y+1) ).is_prime is False
+    assert ( (x+1)*(y+1) ).is_composite is True
+
+    x = Symbol('x', positive=True)
+    assert ( (x+1)*(y+1) ).is_prime is None
+    assert ( (x+1)*(y+1) ).is_composite is None
+
+
+def test_Pow_is_pos_neg():
+    z = Symbol('z', real=True)
+    w = Symbol('w', nonpositive=True)
+
+    assert (S.NegativeOne**S(2)).is_positive is True
+    assert (S.One**z).is_positive is True
+    assert (S.NegativeOne**S(3)).is_positive is False
+    assert (S.Zero**S.Zero).is_positive is True  # 0**0 is 1
+    assert (w**S(3)).is_positive is False
+    assert (w**S(2)).is_positive is None
+    assert (I**2).is_positive is False
+    assert (I**4).is_positive is True
+
+    # tests emerging from #16332 issue
+    p = Symbol('p', zero=True)
+    q = Symbol('q', zero=False, real=True)
+    j = Symbol('j', zero=False, even=True)
+    x = Symbol('x', zero=True)
+    y = Symbol('y', zero=True)
+    assert (p**q).is_positive is False
+    assert (p**q).is_negative is False
+    assert (p**j).is_positive is False
+    assert (x**y).is_positive is True   # 0**0
+    assert (x**y).is_negative is False
+
+
+def test_Pow_is_prime_composite():
+    x = Symbol('x', positive=True, integer=True)
+    y = Symbol('y', positive=True, integer=True)
+    assert (x**y).is_prime is None
+    assert ( x**(y+1) ).is_prime is False
+    assert ( x**(y+1) ).is_composite is None
+    assert ( (x+1)**(y+1) ).is_composite is True
+    assert ( (-x-1)**(2*y) ).is_composite is True
+
+    x = Symbol('x', positive=True)
+    assert (x**y).is_prime is None
+
+
+def test_Mul_is_infinite():
+    x = Symbol('x')
+    f = Symbol('f', finite=True)
+    i = Symbol('i', infinite=True)
+    z = Dummy(zero=True)
+    nzf = Dummy(finite=True, zero=False)
+    from sympy.core.mul import Mul
+    assert (x*f).is_finite is None
+    assert (x*i).is_finite is None
+    assert (f*i).is_finite is None
+    assert (x*f*i).is_finite is None
+    assert (z*i).is_finite is None
+    assert (nzf*i).is_finite is False
+    assert (z*f).is_finite is True
+    assert Mul(0, f, evaluate=False).is_finite is True
+    assert Mul(0, i, evaluate=False).is_finite is None
+
+    assert (x*f).is_infinite is None
+    assert (x*i).is_infinite is None
+    assert (f*i).is_infinite is None
+    assert (x*f*i).is_infinite is None
+    assert (z*i).is_infinite is S.NaN.is_infinite
+    assert (nzf*i).is_infinite is True
+    assert (z*f).is_infinite is False
+    assert Mul(0, f, evaluate=False).is_infinite is False
+    assert Mul(0, i, evaluate=False).is_infinite is S.NaN.is_infinite
+
+
+def test_Add_is_infinite():
+    x = Symbol('x')
+    f = Symbol('f', finite=True)
+    i = Symbol('i', infinite=True)
+    i2 = Symbol('i2', infinite=True)
+    z = Dummy(zero=True)
+    nzf = Dummy(finite=True, zero=False)
+    from sympy.core.add import Add
+    assert (x+f).is_finite is None
+    assert (x+i).is_finite is None
+    assert (f+i).is_finite is False
+    assert (x+f+i).is_finite is None
+    assert (z+i).is_finite is False
+    assert (nzf+i).is_finite is False
+    assert (z+f).is_finite is True
+    assert (i+i2).is_finite is None
+    assert Add(0, f, evaluate=False).is_finite is True
+    assert Add(0, i, evaluate=False).is_finite is False
+
+    assert (x+f).is_infinite is None
+    assert (x+i).is_infinite is None
+    assert (f+i).is_infinite is True
+    assert (x+f+i).is_infinite is None
+    assert (z+i).is_infinite is True
+    assert (nzf+i).is_infinite is True
+    assert (z+f).is_infinite is False
+    assert (i+i2).is_infinite is None
+    assert Add(0, f, evaluate=False).is_infinite is False
+    assert Add(0, i, evaluate=False).is_infinite is True
+
+
+def test_special_is_rational():
+    i = Symbol('i', integer=True)
+    i2 = Symbol('i2', integer=True)
+    ni = Symbol('ni', integer=True, nonzero=True)
+    r = Symbol('r', rational=True)
+    rn = Symbol('r', rational=True, nonzero=True)
+    nr = Symbol('nr', irrational=True)
+    x = Symbol('x')
+    assert sqrt(3).is_rational is False
+    assert (3 + sqrt(3)).is_rational is False
+    assert (3*sqrt(3)).is_rational is False
+    assert exp(3).is_rational is False
+    assert exp(ni).is_rational is False
+    assert exp(rn).is_rational is False
+    assert exp(x).is_rational is None
+    assert exp(log(3), evaluate=False).is_rational is True
+    assert log(exp(3), evaluate=False).is_rational is True
+    assert log(3).is_rational is False
+    assert log(ni + 1).is_rational is False
+    assert log(rn + 1).is_rational is False
+    assert log(x).is_rational is None
+    assert (sqrt(3) + sqrt(5)).is_rational is None
+    assert (sqrt(3) + S.Pi).is_rational is False
+    assert (x**i).is_rational is None
+    assert (i**i).is_rational is True
+    assert (i**i2).is_rational is None
+    assert (r**i).is_rational is None
+    assert (r**r).is_rational is None
+    assert (r**x).is_rational is None
+    assert (nr**i).is_rational is None  # issue 8598
+    assert (nr**Symbol('z', zero=True)).is_rational
+    assert sin(1).is_rational is False
+    assert sin(ni).is_rational is False
+    assert sin(rn).is_rational is False
+    assert sin(x).is_rational is None
+    assert asin(r).is_rational is False
+    assert sin(asin(3), evaluate=False).is_rational is True
+
+
+@XFAIL
+def test_issue_6275():
+    x = Symbol('x')
+    # both zero or both Muls...but neither "change would be very appreciated.
+    # This is similar to x/x => 1 even though if x = 0, it is really nan.
+    assert isinstance(x*0, type(0*S.Infinity))
+    if 0*S.Infinity is S.NaN:
+        b = Symbol('b', finite=None)
+        assert (b*0).is_zero is None
+
+
+def test_sanitize_assumptions():
+    # issue 6666
+    for cls in (Symbol, Dummy, Wild):
+        x = cls('x', real=1, positive=0)
+        assert x.is_real is True
+        assert x.is_positive is False
+        assert cls('', real=True, positive=None).is_positive is None
+        raises(ValueError, lambda: cls('', commutative=None))
+    raises(ValueError, lambda: Symbol._sanitize({"commutative": None}))
+
+
+def test_special_assumptions():
+    e = -3 - sqrt(5) + (-sqrt(10)/2 - sqrt(2)/2)**2
+    assert simplify(e < 0) is S.false
+    assert simplify(e > 0) is S.false
+    assert (e == 0) is False  # it's not a literal 0
+    assert e.equals(0) is True
+
+
+def test_inconsistent():
+    # cf. issues 5795 and 5545
+    raises(InconsistentAssumptions, lambda: Symbol('x', real=True,
+           commutative=False))
+
+
+def test_issue_6631():
+    assert ((-1)**(I)).is_real is True
+    assert ((-1)**(I*2)).is_real is True
+    assert ((-1)**(I/2)).is_real is True
+    assert ((-1)**(I*S.Pi)).is_real is True
+    assert (I**(I + 2)).is_real is True
+
+
+def test_issue_2730():
+    assert (1/(1 + I)).is_real is False
+
+
+def test_issue_4149():
+    assert (3 + I).is_complex
+    assert (3 + I).is_imaginary is False
+    assert (3*I + S.Pi*I).is_imaginary
+    # as Zero.is_imaginary is False, see issue 7649
+    y = Symbol('y', real=True)
+    assert (3*I + S.Pi*I + y*I).is_imaginary is None
+    p = Symbol('p', positive=True)
+    assert (3*I + S.Pi*I + p*I).is_imaginary
+    n = Symbol('n', negative=True)
+    assert (-3*I - S.Pi*I + n*I).is_imaginary
+
+    i = Symbol('i', imaginary=True)
+    assert ([(i**a).is_imaginary for a in range(4)] ==
+            [False, True, False, True])
+
+    # tests from the PR #7887:
+    e = S("-sqrt(3)*I/2 + 0.866025403784439*I")
+    assert e.is_real is False
+    assert e.is_imaginary
+
+
+def test_issue_2920():
+    n = Symbol('n', negative=True)
+    assert sqrt(n).is_imaginary
+
+
+def test_issue_7899():
+    x = Symbol('x', real=True)
+    assert (I*x).is_real is None
+    assert ((x - I)*(x - 1)).is_zero is None
+    assert ((x - I)*(x - 1)).is_real is None
+
+
+@XFAIL
+def test_issue_7993():
+    x = Dummy(integer=True)
+    y = Dummy(noninteger=True)
+    assert (x - y).is_zero is False
+
+
+def test_issue_8075():
+    raises(InconsistentAssumptions, lambda: Dummy(zero=True, finite=False))
+    raises(InconsistentAssumptions, lambda: Dummy(zero=True, infinite=True))
+
+
+def test_issue_8642():
+    x = Symbol('x', real=True, integer=False)
+    assert (x*2).is_integer is None, (x*2).is_integer
+
+
+def test_issues_8632_8633_8638_8675_8992():
+    p = Dummy(integer=True, positive=True)
+    nn = Dummy(integer=True, nonnegative=True)
+    assert (p - S.Half).is_positive
+    assert (p - 1).is_nonnegative
+    assert (nn + 1).is_positive
+    assert (-p + 1).is_nonpositive
+    assert (-nn - 1).is_negative
+    prime = Dummy(prime=True)
+    assert (prime - 2).is_nonnegative
+    assert (prime - 3).is_nonnegative is None
+    even = Dummy(positive=True, even=True)
+    assert (even - 2).is_nonnegative
+
+    p = Dummy(positive=True)
+    assert (p/(p + 1) - 1).is_negative
+    assert ((p + 2)**3 - S.Half).is_positive
+    n = Dummy(negative=True)
+    assert (n - 3).is_nonpositive
+
+
+def test_issue_9115_9150():
+    n = Dummy('n', integer=True, nonnegative=True)
+    assert (factorial(n) >= 1) == True
+    assert (factorial(n) < 1) == False
+
+    assert factorial(n + 1).is_even is None
+    assert factorial(n + 2).is_even is True
+    assert factorial(n + 2) >= 2
+
+
+def test_issue_9165():
+    z = Symbol('z', zero=True)
+    f = Symbol('f', finite=False)
+    assert 0/z is S.NaN
+    assert 0*(1/z) is S.NaN
+    assert 0*f is S.NaN
+
+
+def test_issue_10024():
+    x = Dummy('x')
+    assert Mod(x, 2*pi).is_zero is None
+
+
+def test_issue_10302():
+    x = Symbol('x')
+    r = Symbol('r', real=True)
+    u = -(3*2**pi)**(1/pi) + 2*3**(1/pi)
+    i = u + u*I
+
+    assert i.is_real is None  # w/o simplification this should fail
+    assert (u + i).is_zero is None
+    assert (1 + i).is_zero is False
+
+    a = Dummy('a', zero=True)
+    assert (a + I).is_zero is False
+    assert (a + r*I).is_zero is None
+    assert (a + I).is_imaginary
+    assert (a + x + I).is_imaginary is None
+    assert (a + r*I + I).is_imaginary is None
+
+
+def test_complex_reciprocal_imaginary():
+    assert (1 / (4 + 3*I)).is_imaginary is False
+
+
+def test_issue_16313():
+    x = Symbol('x', extended_real=False)
+    k = Symbol('k', real=True)
+    l = Symbol('l', real=True, zero=False)
+    assert (-x).is_real is False
+    assert (k*x).is_real is None  # k can be zero also
+    assert (l*x).is_real is False
+    assert (l*x*x).is_real is None  # since x*x can be a real number
+    assert (-x).is_positive is False
+
+
+def test_issue_16579():
+    # extended_real -> finite | infinite
+    x = Symbol('x', extended_real=True, infinite=False)
+    y = Symbol('y', extended_real=True, finite=False)
+    assert x.is_finite is True
+    assert y.is_infinite is True
+
+    # With PR 16978, complex now implies finite
+    c = Symbol('c', complex=True)
+    assert c.is_finite is True
+    raises(InconsistentAssumptions, lambda: Dummy(complex=True, finite=False))
+
+    # Now infinite == !finite
+    nf = Symbol('nf', finite=False)
+    assert nf.is_infinite is True
+
+
+def test_issue_17556():
+    z = I*oo
+    assert z.is_imaginary is False
+    assert z.is_finite is False
+
+
+def test_issue_21651():
+    k = Symbol('k', positive=True, integer=True)
+    exp = 2*2**(-k)
+    assert exp.is_integer is None
+
+
+def test_assumptions_copy():
+    assert assumptions(Symbol('x'), {"commutative": True}
+        ) == {'commutative': True}
+    assert assumptions(Symbol('x'), ['integer']) == {}
+    assert assumptions(Symbol('x'), ['commutative']
+        ) == {'commutative': True}
+    assert assumptions(Symbol('x')) == {'commutative': True}
+    assert assumptions(1)['positive']
+    assert assumptions(3 + I) == {
+        'algebraic': True,
+        'commutative': True,
+        'complex': True,
+        'composite': False,
+        'even': False,
+        'extended_negative': False,
+        'extended_nonnegative': False,
+        'extended_nonpositive': False,
+        'extended_nonzero': False,
+        'extended_positive': False,
+        'extended_real': False,
+        'finite': True,
+        'imaginary': False,
+        'infinite': False,
+        'integer': False,
+        'irrational': False,
+        'negative': False,
+        'noninteger': False,
+        'nonnegative': False,
+        'nonpositive': False,
+        'nonzero': False,
+        'odd': False,
+        'positive': False,
+        'prime': False,
+        'rational': False,
+        'real': False,
+        'transcendental': False,
+        'zero': False}
+
+
+def test_check_assumptions():
+    assert check_assumptions(1, 0) is False
+    x = Symbol('x', positive=True)
+    assert check_assumptions(1, x) is True
+    assert check_assumptions(1, 1) is True
+    assert check_assumptions(-1, 1) is False
+    i = Symbol('i', integer=True)
+    # don't know if i is positive (or prime, etc...)
+    assert check_assumptions(i, 1) is None
+    assert check_assumptions(Dummy(integer=None), integer=True) is None
+    assert check_assumptions(Dummy(integer=None), integer=False) is None
+    assert check_assumptions(Dummy(integer=False), integer=True) is False
+    assert check_assumptions(Dummy(integer=True), integer=False) is False
+    # no T/F assumptions to check
+    assert check_assumptions(Dummy(integer=False), integer=None) is True
+    raises(ValueError, lambda: check_assumptions(2*x, x, positive=True))
+
+
+def test_failing_assumptions():
+    x = Symbol('x', positive=True)
+    y = Symbol('y')
+    assert failing_assumptions(6*x + y, **x.assumptions0) == \
+    {'real': None, 'imaginary': None, 'complex': None, 'hermitian': None,
+    'positive': None, 'nonpositive': None, 'nonnegative': None, 'nonzero': None,
+    'negative': None, 'zero': None, 'extended_real': None, 'finite': None,
+    'infinite': None, 'extended_negative': None, 'extended_nonnegative': None,
+    'extended_nonpositive': None, 'extended_nonzero': None,
+    'extended_positive': None }
+
+
+def test_common_assumptions():
+    assert common_assumptions([0, 1, 2]
+        ) == {'algebraic': True, 'irrational': False, 'hermitian':
+        True, 'extended_real': True, 'real': True, 'extended_negative':
+        False, 'extended_nonnegative': True, 'integer': True,
+        'rational': True, 'imaginary': False, 'complex': True,
+        'commutative': True,'noninteger': False, 'composite': False,
+        'infinite': False, 'nonnegative': True, 'finite': True,
+        'transcendental': False,'negative': False}
+    assert common_assumptions([0, 1, 2], 'positive integer'.split()
+        ) == {'integer': True}
+    assert common_assumptions([0, 1, 2], []) == {}
+    assert common_assumptions([], ['integer']) == {}
+    assert common_assumptions([0], ['integer']) == {'integer': True}
+
+def test_pre_generated_assumption_rules_are_valid():
+    # check the pre-generated assumptions match freshly generated assumptions
+    # if this check fails, consider updating the assumptions
+    # see sympy.core.assumptions._generate_assumption_rules
+    pre_generated_assumptions =_load_pre_generated_assumption_rules()
+    generated_assumptions =_generate_assumption_rules()
+    assert pre_generated_assumptions._to_python() == generated_assumptions._to_python(), "pre-generated assumptions are invalid, see sympy.core.assumptions._generate_assumption_rules"
+
+
+def test_ask_shuffle():
+    grp = PermutationGroup(Permutation(1, 0, 2), Permutation(2, 1, 3))
+
+    seed(123)
+    first = grp.random()
+    seed(123)
+    simplify(I)
+    second = grp.random()
+    seed(123)
+    simplify(-I)
+    third = grp.random()
+
+    assert first == second == third

env-llmeval/lib/python3.10/site-packages/sympy/core/tests/test_basic.py

@@ -0,0 +1,319 @@
+"""This tests sympy/core/basic.py with (ideally) no reference to subclasses
+of Basic or Atom."""
+
+import collections
+
+from sympy.assumptions.ask import Q
+from sympy.core.basic import (Basic, Atom, as_Basic,
+    _atomic, _aresame)
+from sympy.core.containers import Tuple
+from sympy.core.function import Function, Lambda
+from sympy.core.numbers import I, pi
+from sympy.core.singleton import S
+from sympy.core.symbol import symbols, Symbol, Dummy
+from sympy.concrete.summations import Sum
+from sympy.functions.elementary.trigonometric import (cos, sin)
+from sympy.functions.special.gamma_functions import gamma
+from sympy.integrals.integrals import Integral
+from sympy.functions.elementary.exponential import exp
+from sympy.testing.pytest import raises, warns_deprecated_sympy
+
+b1 = Basic()
+b2 = Basic(b1)
+b3 = Basic(b2)
+b21 = Basic(b2, b1)
+
+
+def test__aresame():
+    assert not _aresame(Basic(Tuple()), Basic())
+    assert not _aresame(Basic(S(2)), Basic(S(2.)))
+
+
+def test_structure():
+    assert b21.args == (b2, b1)
+    assert b21.func(*b21.args) == b21
+    assert bool(b1)
+
+
+def test_immutable():
+    assert not hasattr(b1, '__dict__')
+    with raises(AttributeError):
+        b1.x = 1
+
+
+def test_equality():
+    instances = [b1, b2, b3, b21, Basic(b1, b1, b1), Basic]
+    for i, b_i in enumerate(instances):
+        for j, b_j in enumerate(instances):
+            assert (b_i == b_j) == (i == j)
+            assert (b_i != b_j) == (i != j)
+
+    assert Basic() != []
+    assert not(Basic() == [])
+    assert Basic() != 0
+    assert not(Basic() == 0)
+
+    class Foo:
+        """
+        Class that is unaware of Basic, and relies on both classes returning
+        the NotImplemented singleton for equivalence to evaluate to False.
+
+        """
+
+    b = Basic()
+    foo = Foo()
+
+    assert b != foo
+    assert foo != b
+    assert not b == foo
+    assert not foo == b
+
+    class Bar:
+        """
+        Class that considers itself equal to any instance of Basic, and relies
+        on Basic returning the NotImplemented singleton in order to achieve
+        a symmetric equivalence relation.
+
+        """
+        def __eq__(self, other):
+            if isinstance(other, Basic):
+                return True
+            return NotImplemented
+
+        def __ne__(self, other):
+            return not self == other
+
+    bar = Bar()
+
+    assert b == bar
+    assert bar == b
+    assert not b != bar
+    assert not bar != b
+
+
+def test_matches_basic():
+    instances = [Basic(b1, b1, b2), Basic(b1, b2, b1), Basic(b2, b1, b1),
+                 Basic(b1, b2), Basic(b2, b1), b2, b1]
+    for i, b_i in enumerate(instances):
+        for j, b_j in enumerate(instances):
+            if i == j:
+                assert b_i.matches(b_j) == {}
+            else:
+                assert b_i.matches(b_j) is None
+    assert b1.match(b1) == {}
+
+
+def test_has():
+    assert b21.has(b1)
+    assert b21.has(b3, b1)
+    assert b21.has(Basic)
+    assert not b1.has(b21, b3)
+    assert not b21.has()
+    assert not b21.has(str)
+    assert not Symbol("x").has("x")
+
+
+def test_subs():
+    assert b21.subs(b2, b1) == Basic(b1, b1)
+    assert b21.subs(b2, b21) == Basic(b21, b1)
+    assert b3.subs(b2, b1) == b2
+
+    assert b21.subs([(b2, b1), (b1, b2)]) == Basic(b2, b2)
+
+    assert b21.subs({b1: b2, b2: b1}) == Basic(b2, b2)
+    assert b21.subs(collections.ChainMap({b1: b2}, {b2: b1})) == Basic(b2, b2)
+    assert b21.subs(collections.OrderedDict([(b2, b1), (b1, b2)])) == Basic(b2, b2)
+
+    raises(ValueError, lambda: b21.subs('bad arg'))
+    raises(ValueError, lambda: b21.subs(b1, b2, b3))
+    # dict(b1=foo) creates a string 'b1' but leaves foo unchanged; subs
+    # will convert the first to a symbol but will raise an error if foo
+    # cannot be sympified; sympification is strict if foo is not string
+    raises(ValueError, lambda: b21.subs(b1='bad arg'))
+
+    assert Symbol("text").subs({"text": b1}) == b1
+    assert Symbol("s").subs({"s": 1}) == 1
+
+
+def test_subs_with_unicode_symbols():
+    expr = Symbol('var1')
+    replaced = expr.subs('var1', 'x')
+    assert replaced.name == 'x'
+
+    replaced = expr.subs('var1', 'x')
+    assert replaced.name == 'x'
+
+
+def test_atoms():
+    assert b21.atoms() == {Basic()}
+
+
+def test_free_symbols_empty():
+    assert b21.free_symbols == set()
+
+
+def test_doit():
+    assert b21.doit() == b21
+    assert b21.doit(deep=False) == b21
+
+
+def test_S():
+    assert repr(S) == 'S'
+
+
+def test_xreplace():
+    assert b21.xreplace({b2: b1}) == Basic(b1, b1)
+    assert b21.xreplace({b2: b21}) == Basic(b21, b1)
+    assert b3.xreplace({b2: b1}) == b2
+    assert Basic(b1, b2).xreplace({b1: b2, b2: b1}) == Basic(b2, b1)
+    assert Atom(b1).xreplace({b1: b2}) == Atom(b1)
+    assert Atom(b1).xreplace({Atom(b1): b2}) == b2
+    raises(TypeError, lambda: b1.xreplace())
+    raises(TypeError, lambda: b1.xreplace([b1, b2]))
+    for f in (exp, Function('f')):
+        assert f.xreplace({}) == f
+        assert f.xreplace({}, hack2=True) == f
+        assert f.xreplace({f: b1}) == b1
+        assert f.xreplace({f: b1}, hack2=True) == b1
+
+
+def test_sorted_args():
+    x = symbols('x')
+    assert b21._sorted_args == b21.args
+    raises(AttributeError, lambda: x._sorted_args)
+
+def test_call():
+    x, y = symbols('x y')
+    # See the long history of this in issues 5026 and 5105.
+
+    raises(TypeError, lambda: sin(x)({ x : 1, sin(x) : 2}))
+    raises(TypeError, lambda: sin(x)(1))
+
+    # No effect as there are no callables
+    assert sin(x).rcall(1) == sin(x)
+    assert (1 + sin(x)).rcall(1) == 1 + sin(x)
+
+    # Effect in the pressence of callables
+    l = Lambda(x, 2*x)
+    assert (l + x).rcall(y) == 2*y + x
+    assert (x**l).rcall(2) == x**4
+    # TODO UndefinedFunction does not subclass Expr
+    #f = Function('f')
+    #assert (2*f)(x) == 2*f(x)
+
+    assert (Q.real & Q.positive).rcall(x) == Q.real(x) & Q.positive(x)
+
+
+def test_rewrite():
+    x, y, z = symbols('x y z')
+    a, b = symbols('a b')
+    f1 = sin(x) + cos(x)
+    assert f1.rewrite(cos,exp) == exp(I*x)/2 + sin(x) + exp(-I*x)/2
+    assert f1.rewrite([cos],sin) == sin(x) + sin(x + pi/2, evaluate=False)
+    f2 = sin(x) + cos(y)/gamma(z)
+    assert f2.rewrite(sin,exp) == -I*(exp(I*x) - exp(-I*x))/2 + cos(y)/gamma(z)
+
+    assert f1.rewrite() == f1
+
+def test_literal_evalf_is_number_is_zero_is_comparable():
+    x = symbols('x')
+    f = Function('f')
+
+    # issue 5033
+    assert f.is_number is False
+    # issue 6646
+    assert f(1).is_number is False
+    i = Integral(0, (x, x, x))
+    # expressions that are symbolically 0 can be difficult to prove
+    # so in case there is some easy way to know if something is 0
+    # it should appear in the is_zero property for that object;
+    # if is_zero is true evalf should always be able to compute that
+    # zero
+    assert i.n() == 0
+    assert i.is_zero
+    assert i.is_number is False
+    assert i.evalf(2, strict=False) == 0
+
+    # issue 10268
+    n = sin(1)**2 + cos(1)**2 - 1
+    assert n.is_comparable is False
+    assert n.n(2).is_comparable is False
+    assert n.n(2).n(2).is_comparable
+
+
+def test_as_Basic():
+    assert as_Basic(1) is S.One
+    assert as_Basic(()) == Tuple()
+    raises(TypeError, lambda: as_Basic([]))
+
+
+def test_atomic():
+    g, h = map(Function, 'gh')
+    x = symbols('x')
+    assert _atomic(g(x + h(x))) == {g(x + h(x))}
+    assert _atomic(g(x + h(x)), recursive=True) == {h(x), x, g(x + h(x))}
+    assert _atomic(1) == set()
+    assert _atomic(Basic(S(1), S(2))) == set()
+
+
+def test_as_dummy():
+    u, v, x, y, z, _0, _1 = symbols('u v x y z _0 _1')
+    assert Lambda(x, x + 1).as_dummy() == Lambda(_0, _0 + 1)
+    assert Lambda(x, x + _0).as_dummy() == Lambda(_1, _0 + _1)
+    eq = (1 + Sum(x, (x, 1, x)))
+    ans = 1 + Sum(_0, (_0, 1, x))
+    once = eq.as_dummy()
+    assert once == ans
+    twice = once.as_dummy()
+    assert twice == ans
+    assert Integral(x + _0, (x, x + 1), (_0, 1, 2)
+        ).as_dummy() == Integral(_0 + _1, (_0, x + 1), (_1, 1, 2))
+    for T in (Symbol, Dummy):
+        d = T('x', real=True)
+        D = d.as_dummy()
+        assert D != d and D.func == Dummy and D.is_real is None
+    assert Dummy().as_dummy().is_commutative
+    assert Dummy(commutative=False).as_dummy().is_commutative is False
+
+
+def test_canonical_variables():
+    x, i0, i1 = symbols('x _:2')
+    assert Integral(x, (x, x + 1)).canonical_variables == {x: i0}
+    assert Integral(x, (x, x + 1), (i0, 1, 2)).canonical_variables == {
+        x: i0, i0: i1}
+    assert Integral(x, (x, x + i0)).canonical_variables == {x: i1}
+
+
+def test_replace_exceptions():
+    from sympy.core.symbol import Wild
+    x, y = symbols('x y')
+    e = (x**2 + x*y)
+    raises(TypeError, lambda: e.replace(sin, 2))
+    b = Wild('b')
+    c = Wild('c')
+    raises(TypeError, lambda: e.replace(b*c, c.is_real))
+    raises(TypeError, lambda: e.replace(b.is_real, 1))
+    raises(TypeError, lambda: e.replace(lambda d: d.is_Number, 1))
+
+
+def test_ManagedProperties():
+    # ManagedProperties is now deprecated. Here we do our best to check that if
+    # someone is using it then it does work in the way that it previously did
+    # but gives a deprecation warning.
+    from sympy.core.assumptions import ManagedProperties
+
+    myclasses = []
+
+    class MyMeta(ManagedProperties):
+        def __init__(cls, *args, **kwargs):
+            myclasses.append('executed')
+            super().__init__(*args, **kwargs)
+
+    code = """
+class MySubclass(Basic, metaclass=MyMeta):
+    pass
+"""
+    with warns_deprecated_sympy():
+        exec(code)
+
+    assert myclasses == ['executed']

env-llmeval/lib/python3.10/site-packages/sympy/core/tests/test_cache.py

@@ -0,0 +1,91 @@
+import sys
+from sympy.core.cache import cacheit, cached_property, lazy_function
+from sympy.testing.pytest import raises
+
+def test_cacheit_doc():
+    @cacheit
+    def testfn():
+        "test docstring"
+        pass
+
+    assert testfn.__doc__ == "test docstring"
+    assert testfn.__name__ == "testfn"
+
+def test_cacheit_unhashable():
+    @cacheit
+    def testit(x):
+        return x
+
+    assert testit(1) == 1
+    assert testit(1) == 1
+    a = {}
+    assert testit(a) == {}
+    a[1] = 2
+    assert testit(a) == {1: 2}
+
+def test_cachit_exception():
+    # Make sure the cache doesn't call functions multiple times when they
+    # raise TypeError
+
+    a = []
+
+    @cacheit
+    def testf(x):
+        a.append(0)
+        raise TypeError
+
+    raises(TypeError, lambda: testf(1))
+    assert len(a) == 1
+
+    a.clear()
+    # Unhashable type
+    raises(TypeError, lambda: testf([]))
+    assert len(a) == 1
+
+    @cacheit
+    def testf2(x):
+        a.append(0)
+        raise TypeError("Error")
+
+    a.clear()
+    raises(TypeError, lambda: testf2(1))
+    assert len(a) == 1
+
+    a.clear()
+    # Unhashable type
+    raises(TypeError, lambda: testf2([]))
+    assert len(a) == 1
+
+def test_cached_property():
+    class A:
+        def __init__(self, value):
+            self.value = value
+            self.calls = 0
+
+        @cached_property
+        def prop(self):
+            self.calls = self.calls + 1
+            return self.value
+
+    a = A(2)
+    assert a.calls == 0
+    assert a.prop == 2
+    assert a.calls == 1
+    assert a.prop == 2
+    assert a.calls == 1
+    b = A(None)
+    assert b.prop == None
+
+
+def test_lazy_function():
+    module_name='xmlrpc.client'
+    function_name = 'gzip_decode'
+    lazy = lazy_function(module_name, function_name)
+    assert lazy(b'') == b''
+    assert module_name in sys.modules
+    assert function_name in str(lazy)
+    repr_lazy = repr(lazy)
+    assert 'LazyFunction' in repr_lazy
+    assert function_name in repr_lazy
+
+    lazy = lazy_function('sympy.core.cache', 'cheap')

env-llmeval/lib/python3.10/site-packages/sympy/core/tests/test_compatibility.py

@@ -0,0 +1,6 @@
+from sympy.testing.pytest import warns_deprecated_sympy
+
+def test_compatibility_submodule():
+    # Test the sympy.core.compatibility deprecation warning
+    with warns_deprecated_sympy():
+        import sympy.core.compatibility # noqa:F401

env-llmeval/lib/python3.10/site-packages/sympy/core/tests/test_complex.py

@@ -0,0 +1,226 @@
+from sympy.core.function import expand_complex
+from sympy.core.numbers import (I, Integer, Rational, pi)
+from sympy.core.power import Pow
+from sympy.core.singleton import S
+from sympy.core.symbol import (Symbol, symbols)
+from sympy.functions.elementary.complexes import (Abs, conjugate, im, re, sign)
+from sympy.functions.elementary.exponential import exp
+from sympy.functions.elementary.hyperbolic import (cosh, coth, sinh, tanh)
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.functions.elementary.trigonometric import (cos, cot, sin, tan)
+
+def test_complex():
+    a = Symbol("a", real=True)
+    b = Symbol("b", real=True)
+    e = (a + I*b)*(a - I*b)
+    assert e.expand() == a**2 + b**2
+    assert sqrt(I) == Pow(I, S.Half)
+
+
+def test_conjugate():
+    a = Symbol("a", real=True)
+    b = Symbol("b", real=True)
+    c = Symbol("c", imaginary=True)
+    d = Symbol("d", imaginary=True)
+    x = Symbol('x')
+    z = a + I*b + c + I*d
+    zc = a - I*b - c + I*d
+    assert conjugate(z) == zc
+    assert conjugate(exp(z)) == exp(zc)
+    assert conjugate(exp(I*x)) == exp(-I*conjugate(x))
+    assert conjugate(z**5) == zc**5
+    assert conjugate(abs(x)) == abs(x)
+    assert conjugate(sign(z)) == sign(zc)
+    assert conjugate(sin(z)) == sin(zc)
+    assert conjugate(cos(z)) == cos(zc)
+    assert conjugate(tan(z)) == tan(zc)
+    assert conjugate(cot(z)) == cot(zc)
+    assert conjugate(sinh(z)) == sinh(zc)
+    assert conjugate(cosh(z)) == cosh(zc)
+    assert conjugate(tanh(z)) == tanh(zc)
+    assert conjugate(coth(z)) == coth(zc)
+
+
+def test_abs1():
+    a = Symbol("a", real=True)
+    b = Symbol("b", real=True)
+    assert abs(a) == Abs(a)
+    assert abs(-a) == abs(a)
+    assert abs(a + I*b) == sqrt(a**2 + b**2)
+
+
+def test_abs2():
+    a = Symbol("a", real=False)
+    b = Symbol("b", real=False)
+    assert abs(a) != a
+    assert abs(-a) != a
+    assert abs(a + I*b) != sqrt(a**2 + b**2)
+
+
+def test_evalc():
+    x = Symbol("x", real=True)
+    y = Symbol("y", real=True)
+    z = Symbol("z")
+    assert ((x + I*y)**2).expand(complex=True) == x**2 + 2*I*x*y - y**2
+    assert expand_complex(z**(2*I)) == (re((re(z) + I*im(z))**(2*I)) +
+        I*im((re(z) + I*im(z))**(2*I)))
+    assert expand_complex(
+        z**(2*I), deep=False) == I*im(z**(2*I)) + re(z**(2*I))
+
+    assert exp(I*x) != cos(x) + I*sin(x)
+    assert exp(I*x).expand(complex=True) == cos(x) + I*sin(x)
+    assert exp(I*x + y).expand(complex=True) == exp(y)*cos(x) + I*sin(x)*exp(y)
+
+    assert sin(I*x).expand(complex=True) == I * sinh(x)
+    assert sin(x + I*y).expand(complex=True) == sin(x)*cosh(y) + \
+        I * sinh(y) * cos(x)
+
+    assert cos(I*x).expand(complex=True) == cosh(x)
+    assert cos(x + I*y).expand(complex=True) == cos(x)*cosh(y) - \
+        I * sinh(y) * sin(x)
+
+    assert tan(I*x).expand(complex=True) == tanh(x) * I
+    assert tan(x + I*y).expand(complex=True) == (
+        sin(2*x)/(cos(2*x) + cosh(2*y)) +
+        I*sinh(2*y)/(cos(2*x) + cosh(2*y)))
+
+    assert sinh(I*x).expand(complex=True) == I * sin(x)
+    assert sinh(x + I*y).expand(complex=True) == sinh(x)*cos(y) + \
+        I * sin(y) * cosh(x)
+
+    assert cosh(I*x).expand(complex=True) == cos(x)
+    assert cosh(x + I*y).expand(complex=True) == cosh(x)*cos(y) + \
+        I * sin(y) * sinh(x)
+
+    assert tanh(I*x).expand(complex=True) == tan(x) * I
+    assert tanh(x + I*y).expand(complex=True) == (
+        (sinh(x)*cosh(x) + I*cos(y)*sin(y)) /
+        (sinh(x)**2 + cos(y)**2)).expand()
+
+
+def test_pythoncomplex():
+    x = Symbol("x")
+    assert 4j*x != 4*x*I
+    assert 4j*x == 4.0*x*I
+    assert 4.1j*x != 4*x*I
+
+
+def test_rootcomplex():
+    R = Rational
+    assert ((+1 + I)**R(1, 2)).expand(
+        complex=True) == 2**R(1, 4)*cos(  pi/8) + 2**R(1, 4)*sin(  pi/8)*I
+    assert ((-1 - I)**R(1, 2)).expand(
+        complex=True) == 2**R(1, 4)*cos(3*pi/8) - 2**R(1, 4)*sin(3*pi/8)*I
+    assert (sqrt(-10)*I).as_real_imag() == (-sqrt(10), 0)
+
+
+def test_expand_inverse():
+    assert (1/(1 + I)).expand(complex=True) == (1 - I)/2
+    assert ((1 + 2*I)**(-2)).expand(complex=True) == (-3 - 4*I)/25
+    assert ((1 + I)**(-8)).expand(complex=True) == Rational(1, 16)
+
+
+def test_expand_complex():
+    assert ((2 + 3*I)**10).expand(complex=True) == -341525 - 145668*I
+    # the following two tests are to ensure the SymPy uses an efficient
+    # algorithm for calculating powers of complex numbers. They should execute
+    # in something like 0.01s.
+    assert ((2 + 3*I)**1000).expand(complex=True) == \
+        -81079464736246615951519029367296227340216902563389546989376269312984127074385455204551402940331021387412262494620336565547972162814110386834027871072723273110439771695255662375718498785908345629702081336606863762777939617745464755635193139022811989314881997210583159045854968310911252660312523907616129080027594310008539817935736331124833163907518549408018652090650537035647520296539436440394920287688149200763245475036722326561143851304795139005599209239350981457301460233967137708519975586996623552182807311159141501424576682074392689622074945519232029999 + \
+        46938745946789557590804551905243206242164799136976022474337918748798900569942573265747576032611189047943842446167719177749107138603040963603119861476016947257034472364028585381714774667326478071264878108114128915685688115488744955550920239128462489496563930809677159214598114273887061533057125164518549173898349061972857446844052995037423459472376202251620778517659247970283904820245958198842631651569984310559418135975795868314764489884749573052997832686979294085577689571149679540256349988338406458116270429842222666345146926395233040564229555893248370000*I
+    assert ((2 + 3*I/4)**1000).expand(complex=True) == \
+        Integer(1)*37079892761199059751745775382463070250205990218394308874593455293485167797989691280095867197640410033222367257278387021789651672598831503296531725827158233077451476545928116965316544607115843772405184272449644892857783761260737279675075819921259597776770965829089907990486964515784097181964312256560561065607846661496055417619388874421218472707497847700629822858068783288579581649321248495739224020822198695759609598745114438265083593711851665996586461937988748911532242908776883696631067311443171682974330675406616373422505939887984366289623091300746049101284856530270685577940283077888955692921951247230006346681086274961362500646889925803654263491848309446197554307105991537357310209426736453173441104334496173618419659521888945605315751089087820455852582920963561495787655250624781448951403353654348109893478206364632640344111022531861683064175862889459084900614967785405977231549003280842218501570429860550379522498497412180001/114813069527425452423283320117768198402231770208869520047764273682576626139237031385665948631650626991844596463898746277344711896086305533142593135616665318539129989145312280000688779148240044871428926990063486244781615463646388363947317026040466353970904996558162398808944629605623311649536164221970332681344168908984458505602379484807914058900934776500429002716706625830522008132236281291761267883317206598995396418127021779858404042159853183251540889433902091920554957783589672039160081957216630582755380425583726015528348786419432054508915275783882625175435528800822842770817965453762184851149029376 + \
+        I*421638390580169706973991429333213477486930178424989246669892530737775352519112934278994501272111385966211392610029433824534634841747911783746811994443436271013377059560245191441549885048056920190833693041257216263519792201852046825443439142932464031501882145407459174948712992271510309541474392303461939389368955986650538525895866713074543004916049550090364398070215427272240155060576252568700906004691224321432509053286859100920489253598392100207663785243368195857086816912514025693453058403158416856847185079684216151337200057494966741268925263085619240941610301610538225414050394612058339070756009433535451561664522479191267503989904464718368605684297071150902631208673621618217106272361061676184840810762902463998065947687814692402219182668782278472952758690939877465065070481351343206840649517150634973307937551168752642148704904383991876969408056379195860410677814566225456558230131911142229028179902418223009651437985670625/1793954211366022694113801876840128100034871409513586250746316776290259783425578615401030447369541046747571819748417910583511123376348523955353017744010395602173906080395504375010762174191250701116076984219741972574712741619474818186676828531882286780795390571221287481389759837587864244524002565968286448146002639202882164150037179450123657170327105882819203167448541028601906377066191895183769810676831353109303069033234715310287563158747705988305326397404720186258671215368588625611876280581509852855552819149745718992630449787803625851701801184123166018366180137512856918294030710215034138299203584
+    assert ((2 + 3*I)**-1000).expand(complex=True) == \
+        Integer(1)*-81079464736246615951519029367296227340216902563389546989376269312984127074385455204551402940331021387412262494620336565547972162814110386834027871072723273110439771695255662375718498785908345629702081336606863762777939617745464755635193139022811989314881997210583159045854968310911252660312523907616129080027594310008539817935736331124833163907518549408018652090650537035647520296539436440394920287688149200763245475036722326561143851304795139005599209239350981457301460233967137708519975586996623552182807311159141501424576682074392689622074945519232029999/8777125472973511649630750050295188683351430110097915876250894978429797369155961290321829625004920141758416719066805645579710744290541337680113772670040386863849283653078324415471816788604945889094925784900885812724984087843737442111926413818245854362613018058774368703971604921858023116665586358870612944209398056562604561248859926344335598822815885851096698226775053153403320782439987679978321289537645645163767251396759519805603090332694449553371530571613352311006350058217982509738362083094920649452123351717366337410243853659113315547584871655479914439219520157174729130746351059075207407866012574386726064196992865627149566238044625779078186624347183905913357718850537058578084932880569701242598663149911276357125355850792073635533676541250531086757377369962506979378337216411188347761901006460813413505861461267545723590468627854202034450569581626648934062198718362303420281555886394558137408159453103395918783625713213314350531051312551733021627153081075080140680608080529736975658786227362251632725009435866547613598753584705455955419696609282059191031962604169242974038517575645939316377801594539335940001 - Integer(1)*46938745946789557590804551905243206242164799136976022474337918748798900569942573265747576032611189047943842446167719177749107138603040963603119861476016947257034472364028585381714774667326478071264878108114128915685688115488744955550920239128462489496563930809677159214598114273887061533057125164518549173898349061972857446844052995037423459472376202251620778517659247970283904820245958198842631651569984310559418135975795868314764489884749573052997832686979294085577689571149679540256349988338406458116270429842222666345146926395233040564229555893248370000*I/8777125472973511649630750050295188683351430110097915876250894978429797369155961290321829625004920141758416719066805645579710744290541337680113772670040386863849283653078324415471816788604945889094925784900885812724984087843737442111926413818245854362613018058774368703971604921858023116665586358870612944209398056562604561248859926344335598822815885851096698226775053153403320782439987679978321289537645645163767251396759519805603090332694449553371530571613352311006350058217982509738362083094920649452123351717366337410243853659113315547584871655479914439219520157174729130746351059075207407866012574386726064196992865627149566238044625779078186624347183905913357718850537058578084932880569701242598663149911276357125355850792073635533676541250531086757377369962506979378337216411188347761901006460813413505861461267545723590468627854202034450569581626648934062198718362303420281555886394558137408159453103395918783625713213314350531051312551733021627153081075080140680608080529736975658786227362251632725009435866547613598753584705455955419696609282059191031962604169242974038517575645939316377801594539335940001
+    assert ((2 + 3*I/4)**-1000).expand(complex=True) == \
+        Integer(1)*4257256305661027385394552848555894604806501409793288342610746813288539790051927148781268212212078237301273165351052934681382567968787279534591114913777456610214738290619922068269909423637926549603264174216950025398244509039145410016404821694746262142525173737175066432954496592560621330313807235750500564940782099283410261748370262433487444897446779072067625787246390824312580440138770014838135245148574339248259670887549732495841810961088930810608893772914812838358159009303794863047635845688453859317690488124382253918725010358589723156019888846606295866740117645571396817375322724096486161308083462637370825829567578309445855481578518239186117686659177284332344643124760453112513611749309168470605289172320376911472635805822082051716625171429727162039621902266619821870482519063133136820085579315127038372190224739238686708451840610064871885616258831386810233957438253532027049148030157164346719204500373766157143311767338973363806106967439378604898250533766359989107510507493549529158818602327525235240510049484816090584478644771183158342479140194633579061295740839490629457435283873180259847394582069479062820225159699506175855369539201399183443253793905149785994830358114153241481884290274629611529758663543080724574566578220908907477622643689220814376054314972190402285121776593824615083669045183404206291739005554569305329760211752815718335731118664756831942466773261465213581616104242113894521054475516019456867271362053692785300826523328020796670205463390909136593859765912483565093461468865534470710132881677639651348709376/2103100954337624833663208713697737151593634525061637972297915388685604042449504336765884978184588688426595940401280828953096857809292320006227881797146858511436638446932833617514351442216409828605662238790280753075176269765767010004889778647709740770757817960711900340755635772183674511158570690702969774966791073165467918123298694584729211212414462628433370481195120564586361368504153395406845170075275051749019600057116719726628746724489572189061061036426955163696859127711110719502594479795200686212257570291758725259007379710596548777812659422174199194837355646482046783616494013289495563083118517507178847555801163089723056310287760875135196081975602765511153122381201303871673391366630940702817360340900568748719988954847590748960761446218262344767250783946365392689256634180417145926390656439421745644011831124277463643383712803287985472471755648426749842410972650924240795946699346613614779460399530274263580007672855851663196114585312432954432654691485867618908420370875753749297487803461900447407917655296784879220450937110470920633595689721819488638484547259978337741496090602390463594556401615298457456112485536498177883358587125449801777718900375736758266215245325999241624148841915093787519330809347240990363802360596034171167818310322276373120180985148650099673289383722502488957717848531612020897298448601714154586319660314294591620415272119454982220034319689607295960162971300417552364254983071768070124456169427638371140064235083443242844616326538396503937972586505546495649094344512270582463639152160238137952390380581401171977159154009407415523525096743009110916334144716516647041176989758534635251844947906038080852185583742296318878233394998111078843229681030277039104786225656992262073797524057992347971177720807155842376332851559276430280477639539393920006008737472164850104411971830120295750221200029811143140323763349636629725073624360001 - Integer(1)*3098214262599218784594285246258841485430681674561917573155883806818465520660668045042109232930382494608383663464454841313154390741655282039877410154577448327874989496074260116195788919037407420625081798124301494353693248757853222257918294662198297114746822817460991242508743651430439120439020484502408313310689912381846149597061657483084652685283853595100434135149479564507015504022249330340259111426799121454516345905101620532787348293877485702600390665276070250119465888154331218827342488849948540687659846652377277250614246402784754153678374932540789808703029043827352976139228402417432199779415751301480406673762521987999573209628597459357964214510139892316208670927074795773830798600837815329291912002136924506221066071242281626618211060464126372574400100990746934953437169840312584285942093951405864225230033279614235191326102697164613004299868695519642598882914862568516635347204441042798206770888274175592401790040170576311989738272102077819127459014286741435419468254146418098278519775722104890854275995510700298782146199325790002255362719776098816136732897323406228294203133323296591166026338391813696715894870956511298793595675308998014158717167429941371979636895553724830981754579086664608880698350866487717403917070872269853194118364230971216854931998642990452908852258008095741042117326241406479532880476938937997238098399302185675832474590293188864060116934035867037219176916416481757918864533515526389079998129329045569609325290897577497835388451456680707076072624629697883854217331728051953671643278797380171857920000*I/2103100954337624833663208713697737151593634525061637972297915388685604042449504336765884978184588688426595940401280828953096857809292320006227881797146858511436638446932833617514351442216409828605662238790280753075176269765767010004889778647709740770757817960711900340755635772183674511158570690702969774966791073165467918123298694584729211212414462628433370481195120564586361368504153395406845170075275051749019600057116719726628746724489572189061061036426955163696859127711110719502594479795200686212257570291758725259007379710596548777812659422174199194837355646482046783616494013289495563083118517507178847555801163089723056310287760875135196081975602765511153122381201303871673391366630940702817360340900568748719988954847590748960761446218262344767250783946365392689256634180417145926390656439421745644011831124277463643383712803287985472471755648426749842410972650924240795946699346613614779460399530274263580007672855851663196114585312432954432654691485867618908420370875753749297487803461900447407917655296784879220450937110470920633595689721819488638484547259978337741496090602390463594556401615298457456112485536498177883358587125449801777718900375736758266215245325999241624148841915093787519330809347240990363802360596034171167818310322276373120180985148650099673289383722502488957717848531612020897298448601714154586319660314294591620415272119454982220034319689607295960162971300417552364254983071768070124456169427638371140064235083443242844616326538396503937972586505546495649094344512270582463639152160238137952390380581401171977159154009407415523525096743009110916334144716516647041176989758534635251844947906038080852185583742296318878233394998111078843229681030277039104786225656992262073797524057992347971177720807155842376332851559276430280477639539393920006008737472164850104411971830120295750221200029811143140323763349636629725073624360001
+
+    a = Symbol('a', real=True)
+    b = Symbol('b', real=True)
+    assert exp(a*(2 + I*b)).expand(complex=True) == \
+        I*exp(2*a)*sin(a*b) + exp(2*a)*cos(a*b)
+
+
+def test_expand():
+    f = (16 - 2*sqrt(29))**2
+    assert f.expand() == 372 - 64*sqrt(29)
+    f = (Integer(1)/2 + I/2)**10
+    assert f.expand() == I/32
+    f = (Integer(1)/2 + I)**10
+    assert f.expand() == Integer(237)/1024 - 779*I/256
+
+
+def test_re_im1652():
+    x = Symbol('x')
+    assert re(x) == re(conjugate(x))
+    assert im(x) == - im(conjugate(x))
+    assert im(x)*re(conjugate(x)) + im(conjugate(x)) * re(x) == 0
+
+
+def test_issue_5084():
+    x = Symbol('x')
+    assert ((x + x*I)/(1 + I)).as_real_imag() == (re((x + I*x)/(1 + I)
+            ), im((x + I*x)/(1 + I)))
+
+
+def test_issue_5236():
+    assert (cos(1 + I)**3).as_real_imag() == (-3*sin(1)**2*sinh(1)**2*cos(1)*cosh(1) +
+        cos(1)**3*cosh(1)**3, -3*cos(1)**2*cosh(1)**2*sin(1)*sinh(1) + sin(1)**3*sinh(1)**3)
+
+
+def test_real_imag():
+    x, y, z = symbols('x, y, z')
+    X, Y, Z = symbols('X, Y, Z', commutative=False)
+    a = Symbol('a', real=True)
+    assert (2*a*x).as_real_imag() == (2*a*re(x), 2*a*im(x))
+
+    # issue 5395:
+    assert (x*x.conjugate()).as_real_imag() == (Abs(x)**2, 0)
+    assert im(x*x.conjugate()) == 0
+    assert im(x*y.conjugate()*z*y) == im(x*z)*Abs(y)**2
+    assert im(x*y.conjugate()*x*y) == im(x**2)*Abs(y)**2
+    assert im(Z*y.conjugate()*X*y) == im(Z*X)*Abs(y)**2
+    assert im(X*X.conjugate()) == im(X*X.conjugate(), evaluate=False)
+    assert (sin(x)*sin(x).conjugate()).as_real_imag() == \
+        (Abs(sin(x))**2, 0)
+
+    # issue 6573:
+    assert (x**2).as_real_imag() == (re(x)**2 - im(x)**2, 2*re(x)*im(x))
+
+    # issue 6428:
+    r = Symbol('r', real=True)
+    i = Symbol('i', imaginary=True)
+    assert (i*r*x).as_real_imag() == (I*i*r*im(x), -I*i*r*re(x))
+    assert (i*r*x*(y + 2)).as_real_imag() == (
+        I*i*r*(re(y) + 2)*im(x) + I*i*r*re(x)*im(y),
+        -I*i*r*(re(y) + 2)*re(x) + I*i*r*im(x)*im(y))
+
+    # issue 7106:
+    assert ((1 + I)/(1 - I)).as_real_imag() == (0, 1)
+    assert ((1 + 2*I)*(1 + 3*I)).as_real_imag() == (-5, 5)
+
+
+def test_pow_issue_1724():
+    e = ((S.NegativeOne)**(S.One/3))
+    assert e.conjugate().n() == e.n().conjugate()
+    e = S('-2/3 - (-29/54 + sqrt(93)/18)**(1/3) - 1/(9*(-29/54 + sqrt(93)/18)**(1/3))')
+    assert e.conjugate().n() == e.n().conjugate()
+    e = 2**I
+    assert e.conjugate().n() == e.n().conjugate()
+
+
+def test_issue_5429():
+    assert sqrt(I).conjugate() != sqrt(I)
+
+def test_issue_4124():
+    from sympy.core.numbers import oo
+    assert expand_complex(I*oo) == oo*I
+
+def test_issue_11518():
+    x = Symbol("x", real=True)
+    y = Symbol("y", real=True)
+    r = sqrt(x**2 + y**2)
+    assert conjugate(r) == r
+    s = abs(x + I * y)
+    assert conjugate(s) == r

env-llmeval/lib/python3.10/site-packages/sympy/core/tests/test_constructor_postprocessor.py

@@ -0,0 +1,87 @@
+from sympy.core.basic import Basic
+from sympy.core.mul import Mul
+from sympy.core.symbol import (Symbol, symbols)
+
+from sympy.testing.pytest import XFAIL
+
+class SymbolInMulOnce(Symbol):
+    # Test class for a symbol that can only appear once in a `Mul` expression.
+    pass
+
+
+Basic._constructor_postprocessor_mapping[SymbolInMulOnce] = {
+    "Mul": [lambda x: x],
+    "Pow": [lambda x: x.base if isinstance(x.base, SymbolInMulOnce) else x],
+    "Add": [lambda x: x],
+}
+
+
+def _postprocess_SymbolRemovesOtherSymbols(expr):
+    args = tuple(i for i in expr.args if not isinstance(i, Symbol) or isinstance(i, SymbolRemovesOtherSymbols))
+    if args == expr.args:
+        return expr
+    return Mul.fromiter(args)
+
+
+class SymbolRemovesOtherSymbols(Symbol):
+    # Test class for a symbol that removes other symbols in `Mul`.
+    pass
+
+Basic._constructor_postprocessor_mapping[SymbolRemovesOtherSymbols] = {
+    "Mul": [_postprocess_SymbolRemovesOtherSymbols],
+}
+
+class SubclassSymbolInMulOnce(SymbolInMulOnce):
+    pass
+
+class SubclassSymbolRemovesOtherSymbols(SymbolRemovesOtherSymbols):
+    pass
+
+
+def test_constructor_postprocessors1():
+    x = SymbolInMulOnce("x")
+    y = SymbolInMulOnce("y")
+    assert isinstance(3*x, Mul)
+    assert (3*x).args == (3, x)
+    assert x*x == x
+    assert 3*x*x == 3*x
+    assert 2*x*x + x == 3*x
+    assert x**3*y*y == x*y
+    assert x**5 + y*x**3 == x + x*y
+
+    w = SymbolRemovesOtherSymbols("w")
+    assert x*w == w
+    assert (3*w).args == (3, w)
+    assert set((w + x).args) == {x, w}
+
+def test_constructor_postprocessors2():
+    x = SubclassSymbolInMulOnce("x")
+    y = SubclassSymbolInMulOnce("y")
+    assert isinstance(3*x, Mul)
+    assert (3*x).args == (3, x)
+    assert x*x == x
+    assert 3*x*x == 3*x
+    assert 2*x*x + x == 3*x
+    assert x**3*y*y == x*y
+    assert x**5 + y*x**3 == x + x*y
+
+    w = SubclassSymbolRemovesOtherSymbols("w")
+    assert x*w == w
+    assert (3*w).args == (3, w)
+    assert set((w + x).args) == {x, w}
+
+
+@XFAIL
+def test_subexpression_postprocessors():
+    # The postprocessors used to work with subexpressions, but the
+    # functionality was removed. See #15948.
+    a = symbols("a")
+    x = SymbolInMulOnce("x")
+    w = SymbolRemovesOtherSymbols("w")
+    assert 3*a*w**2 == 3*w**2
+    assert 3*a*x**3*w**2 == 3*w**2
+
+    x = SubclassSymbolInMulOnce("x")
+    w = SubclassSymbolRemovesOtherSymbols("w")
+    assert 3*a*w**2 == 3*w**2
+    assert 3*a*x**3*w**2 == 3*w**2

env-llmeval/lib/python3.10/site-packages/sympy/core/tests/test_containers.py

@@ -0,0 +1,217 @@
+from collections import defaultdict
+
+from sympy.core.basic import Basic
+from sympy.core.containers import (Dict, Tuple)
+from sympy.core.numbers import Integer
+from sympy.core.kind import NumberKind
+from sympy.matrices.common import MatrixKind
+from sympy.core.singleton import S
+from sympy.core.symbol import symbols
+from sympy.core.sympify import sympify
+from sympy.matrices.dense import Matrix
+from sympy.sets.sets import FiniteSet
+from sympy.core.containers import tuple_wrapper, TupleKind
+from sympy.core.expr import unchanged
+from sympy.core.function import Function, Lambda
+from sympy.core.relational import Eq
+from sympy.testing.pytest import raises
+from sympy.utilities.iterables import is_sequence, iterable
+
+from sympy.abc import x, y
+
+
+def test_Tuple():
+    t = (1, 2, 3, 4)
+    st = Tuple(*t)
+    assert set(sympify(t)) == set(st)
+    assert len(t) == len(st)
+    assert set(sympify(t[:2])) == set(st[:2])
+    assert isinstance(st[:], Tuple)
+    assert st == Tuple(1, 2, 3, 4)
+    assert st.func(*st.args) == st
+    p, q, r, s = symbols('p q r s')
+    t2 = (p, q, r, s)
+    st2 = Tuple(*t2)
+    assert st2.atoms() == set(t2)
+    assert st == st2.subs({p: 1, q: 2, r: 3, s: 4})
+    # issue 5505
+    assert all(isinstance(arg, Basic) for arg in st.args)
+    assert Tuple(p, 1).subs(p, 0) == Tuple(0, 1)
+    assert Tuple(p, Tuple(p, 1)).subs(p, 0) == Tuple(0, Tuple(0, 1))
+
+    assert Tuple(t2) == Tuple(Tuple(*t2))
+    assert Tuple.fromiter(t2) == Tuple(*t2)
+    assert Tuple.fromiter(x for x in range(4)) == Tuple(0, 1, 2, 3)
+    assert st2.fromiter(st2.args) == st2
+
+
+def test_Tuple_contains():
+    t1, t2 = Tuple(1), Tuple(2)
+    assert t1 in Tuple(1, 2, 3, t1, Tuple(t2))
+    assert t2 not in Tuple(1, 2, 3, t1, Tuple(t2))
+
+
+def test_Tuple_concatenation():
+    assert Tuple(1, 2) + Tuple(3, 4) == Tuple(1, 2, 3, 4)
+    assert (1, 2) + Tuple(3, 4) == Tuple(1, 2, 3, 4)
+    assert Tuple(1, 2) + (3, 4) == Tuple(1, 2, 3, 4)
+    raises(TypeError, lambda: Tuple(1, 2) + 3)
+    raises(TypeError, lambda: 1 + Tuple(2, 3))
+
+    #the Tuple case in __radd__ is only reached when a subclass is involved
+    class Tuple2(Tuple):
+        def __radd__(self, other):
+            return Tuple.__radd__(self, other + other)
+    assert Tuple(1, 2) + Tuple2(3, 4) == Tuple(1, 2, 1, 2, 3, 4)
+    assert Tuple2(1, 2) + Tuple(3, 4) == Tuple(1, 2, 3, 4)
+
+
+def test_Tuple_equality():
+    assert not isinstance(Tuple(1, 2), tuple)
+    assert (Tuple(1, 2) == (1, 2)) is True
+    assert (Tuple(1, 2) != (1, 2)) is False
+    assert (Tuple(1, 2) == (1, 3)) is False
+    assert (Tuple(1, 2) != (1, 3)) is True
+    assert (Tuple(1, 2) == Tuple(1, 2)) is True
+    assert (Tuple(1, 2) != Tuple(1, 2)) is False
+    assert (Tuple(1, 2) == Tuple(1, 3)) is False
+    assert (Tuple(1, 2) != Tuple(1, 3)) is True
+
+
+def test_Tuple_Eq():
+    assert Eq(Tuple(), Tuple()) is S.true
+    assert Eq(Tuple(1), 1) is S.false
+    assert Eq(Tuple(1, 2), Tuple(1)) is S.false
+    assert Eq(Tuple(1), Tuple(1)) is S.true
+    assert Eq(Tuple(1, 2), Tuple(1, 3)) is S.false
+    assert Eq(Tuple(1, 2), Tuple(1, 2)) is S.true
+    assert unchanged(Eq, Tuple(1, x), Tuple(1, 2))
+    assert Eq(Tuple(1, x), Tuple(1, 2)).subs(x, 2) is S.true
+    assert unchanged(Eq, Tuple(1, 2), x)
+    f = Function('f')
+    assert unchanged(Eq, Tuple(1), f(x))
+    assert Eq(Tuple(1), f(x)).subs(x, 1).subs(f, Lambda(y, (y,))) is S.true
+
+
+def test_Tuple_comparision():
+    assert (Tuple(1, 3) >= Tuple(-10, 30)) is S.true
+    assert (Tuple(1, 3) <= Tuple(-10, 30)) is S.false
+    assert (Tuple(1, 3) >= Tuple(1, 3)) is S.true
+    assert (Tuple(1, 3) <= Tuple(1, 3)) is S.true
+
+
+def test_Tuple_tuple_count():
+    assert Tuple(0, 1, 2, 3).tuple_count(4) == 0
+    assert Tuple(0, 4, 1, 2, 3).tuple_count(4) == 1
+    assert Tuple(0, 4, 1, 4, 2, 3).tuple_count(4) == 2
+    assert Tuple(0, 4, 1, 4, 2, 4, 3).tuple_count(4) == 3
+
+
+def test_Tuple_index():
+    assert Tuple(4, 0, 1, 2, 3).index(4) == 0
+    assert Tuple(0, 4, 1, 2, 3).index(4) == 1
+    assert Tuple(0, 1, 4, 2, 3).index(4) == 2
+    assert Tuple(0, 1, 2, 4, 3).index(4) == 3
+    assert Tuple(0, 1, 2, 3, 4).index(4) == 4
+
+    raises(ValueError, lambda: Tuple(0, 1, 2, 3).index(4))
+    raises(ValueError, lambda: Tuple(4, 0, 1, 2, 3).index(4, 1))
+    raises(ValueError, lambda: Tuple(0, 1, 2, 3, 4).index(4, 1, 4))
+
+
+def test_Tuple_mul():
+    assert Tuple(1, 2, 3)*2 == Tuple(1, 2, 3, 1, 2, 3)
+    assert 2*Tuple(1, 2, 3) == Tuple(1, 2, 3, 1, 2, 3)
+    assert Tuple(1, 2, 3)*Integer(2) == Tuple(1, 2, 3, 1, 2, 3)
+    assert Integer(2)*Tuple(1, 2, 3) == Tuple(1, 2, 3, 1, 2, 3)
+
+    raises(TypeError, lambda: Tuple(1, 2, 3)*S.Half)
+    raises(TypeError, lambda: S.Half*Tuple(1, 2, 3))
+
+
+def test_tuple_wrapper():
+
+    @tuple_wrapper
+    def wrap_tuples_and_return(*t):
+        return t
+
+    p = symbols('p')
+    assert wrap_tuples_and_return(p, 1) == (p, 1)
+    assert wrap_tuples_and_return((p, 1)) == (Tuple(p, 1),)
+    assert wrap_tuples_and_return(1, (p, 2), 3) == (1, Tuple(p, 2), 3)
+
+
+def test_iterable_is_sequence():
+    ordered = [[], (), Tuple(), Matrix([[]])]
+    unordered = [set()]
+    not_sympy_iterable = [{}, '', '']
+    assert all(is_sequence(i) for i in ordered)
+    assert all(not is_sequence(i) for i in unordered)
+    assert all(iterable(i) for i in ordered + unordered)
+    assert all(not iterable(i) for i in not_sympy_iterable)
+    assert all(iterable(i, exclude=None) for i in not_sympy_iterable)
+
+
+def test_TupleKind():
+    kind = TupleKind(NumberKind, MatrixKind(NumberKind))
+    assert Tuple(1, Matrix([1, 2])).kind is kind
+    assert Tuple(1, 2).kind is TupleKind(NumberKind, NumberKind)
+    assert Tuple(1, 2).kind.element_kind == (NumberKind, NumberKind)
+
+
+def test_Dict():
+    x, y, z = symbols('x y z')
+    d = Dict({x: 1, y: 2, z: 3})
+    assert d[x] == 1
+    assert d[y] == 2
+    raises(KeyError, lambda: d[2])
+    raises(KeyError, lambda: d['2'])
+    assert len(d) == 3
+    assert set(d.keys()) == {x, y, z}
+    assert set(d.values()) == {S.One, S(2), S(3)}
+    assert d.get(5, 'default') == 'default'
+    assert d.get('5', 'default') == 'default'
+    assert x in d and z in d and 5 not in d and '5' not in d
+    assert d.has(x) and d.has(1)  # SymPy Basic .has method
+
+    # Test input types
+    # input - a Python dict
+    # input - items as args - SymPy style
+    assert (Dict({x: 1, y: 2, z: 3}) ==
+            Dict((x, 1), (y, 2), (z, 3)))
+
+    raises(TypeError, lambda: Dict(((x, 1), (y, 2), (z, 3))))
+    with raises(NotImplementedError):
+        d[5] = 6  # assert immutability
+
+    assert set(
+        d.items()) == {Tuple(x, S.One), Tuple(y, S(2)), Tuple(z, S(3))}
+    assert set(d) == {x, y, z}
+    assert str(d) == '{x: 1, y: 2, z: 3}'
+    assert d.__repr__() == '{x: 1, y: 2, z: 3}'
+
+    # Test creating a Dict from a Dict.
+    d = Dict({x: 1, y: 2, z: 3})
+    assert d == Dict(d)
+
+    # Test for supporting defaultdict
+    d = defaultdict(int)
+    assert d[x] == 0
+    assert d[y] == 0
+    assert d[z] == 0
+    assert Dict(d)
+    d = Dict(d)
+    assert len(d) == 3
+    assert set(d.keys()) == {x, y, z}
+    assert set(d.values()) == {S.Zero, S.Zero, S.Zero}
+
+
+def test_issue_5788():
+    args = [(1, 2), (2, 1)]
+    for o in [Dict, Tuple, FiniteSet]:
+        # __eq__ and arg handling
+        if o != Tuple:
+            assert o(*args) == o(*reversed(args))
+        pair = [o(*args), o(*reversed(args))]
+        assert sorted(pair) == sorted(pair)
+        assert set(o(*args))  # doesn't fail

env-llmeval/lib/python3.10/site-packages/sympy/core/tests/test_count_ops.py

@@ -0,0 +1,155 @@
+from sympy.concrete.summations import Sum
+from sympy.core.basic import Basic
+from sympy.core.function import (Derivative, Function, count_ops)
+from sympy.core.numbers import (I, Rational, pi)
+from sympy.core.relational import (Eq, Rel)
+from sympy.core.singleton import S
+from sympy.core.symbol import (Symbol, symbols)
+from sympy.functions.elementary.exponential import exp
+from sympy.functions.elementary.trigonometric import (cos, sin)
+from sympy.integrals.integrals import Integral
+from sympy.logic.boolalg import (And, Equivalent, ITE, Implies, Nand,
+    Nor, Not, Or, Xor)
+from sympy.matrices.expressions.matexpr import MatrixSymbol
+from sympy.core.containers import Tuple
+
+x, y, z = symbols('x,y,z')
+a, b, c = symbols('a,b,c')
+
+def test_count_ops_non_visual():
+    def count(val):
+        return count_ops(val, visual=False)
+    assert count(x) == 0
+    assert count(x) is not S.Zero
+    assert count(x + y) == 1
+    assert count(x + y) is not S.One
+    assert count(x + y*x + 2*y) == 4
+    assert count({x + y: x}) == 1
+    assert count({x + y: S(2) + x}) is not S.One
+    assert count(x < y) == 1
+    assert count(Or(x,y)) == 1
+    assert count(And(x,y)) == 1
+    assert count(Not(x)) == 1
+    assert count(Nor(x,y)) == 2
+    assert count(Nand(x,y)) == 2
+    assert count(Xor(x,y)) == 1
+    assert count(Implies(x,y)) == 1
+    assert count(Equivalent(x,y)) == 1
+    assert count(ITE(x,y,z)) == 1
+    assert count(ITE(True,x,y)) == 0
+
+
+def test_count_ops_visual():
+    ADD, MUL, POW, SIN, COS, EXP, AND, D, G, M = symbols(
+        'Add Mul Pow sin cos exp And Derivative Integral Sum'.upper())
+    DIV, SUB, NEG = symbols('DIV SUB NEG')
+    LT, LE, GT, GE, EQ, NE = symbols('LT LE GT GE EQ NE')
+    NOT, OR, AND, XOR, IMPLIES, EQUIVALENT, _ITE, BASIC, TUPLE = symbols(
+        'Not Or And Xor Implies Equivalent ITE Basic Tuple'.upper())
+
+    def count(val):
+        return count_ops(val, visual=True)
+
+    assert count(7) is S.Zero
+    assert count(S(7)) is S.Zero
+    assert count(-1) == NEG
+    assert count(-2) == NEG
+    assert count(S(2)/3) == DIV
+    assert count(Rational(2, 3)) == DIV
+    assert count(pi/3) == DIV
+    assert count(-pi/3) == DIV + NEG
+    assert count(I - 1) == SUB
+    assert count(1 - I) == SUB
+    assert count(1 - 2*I) == SUB + MUL
+
+    assert count(x) is S.Zero
+    assert count(-x) == NEG
+    assert count(-2*x/3) == NEG + DIV + MUL
+    assert count(Rational(-2, 3)*x) == NEG + DIV + MUL
+    assert count(1/x) == DIV
+    assert count(1/(x*y)) == DIV + MUL
+    assert count(-1/x) == NEG + DIV
+    assert count(-2/x) == NEG + DIV
+    assert count(x/y) == DIV
+    assert count(-x/y) == NEG + DIV
+
+    assert count(x**2) == POW
+    assert count(-x**2) == POW + NEG
+    assert count(-2*x**2) == POW + MUL + NEG
+
+    assert count(x + pi/3) == ADD + DIV
+    assert count(x + S.One/3) == ADD + DIV
+    assert count(x + Rational(1, 3)) == ADD + DIV
+    assert count(x + y) == ADD
+    assert count(x - y) == SUB
+    assert count(y - x) == SUB
+    assert count(-1/(x - y)) == DIV + NEG + SUB
+    assert count(-1/(y - x)) == DIV + NEG + SUB
+    assert count(1 + x**y) == ADD + POW
+    assert count(1 + x + y) == 2*ADD
+    assert count(1 + x + y + z) == 3*ADD
+    assert count(1 + x**y + 2*x*y + y**2) == 3*ADD + 2*POW + 2*MUL
+    assert count(2*z + y + x + 1) == 3*ADD + MUL
+    assert count(2*z + y**17 + x + 1) == 3*ADD + MUL + POW
+    assert count(2*z + y**17 + x + sin(x)) == 3*ADD + POW + MUL + SIN
+    assert count(2*z + y**17 + x + sin(x**2)) == 3*ADD + MUL + 2*POW + SIN
+    assert count(2*z + y**17 + x + sin(
+        x**2) + exp(cos(x))) == 4*ADD + MUL + 2*POW + EXP + COS + SIN
+
+    assert count(Derivative(x, x)) == D
+    assert count(Integral(x, x) + 2*x/(1 + x)) == G + DIV + MUL + 2*ADD
+    assert count(Sum(x, (x, 1, x + 1)) + 2*x/(1 + x)) == M + DIV + MUL + 3*ADD
+    assert count(Basic()) is S.Zero
+
+    assert count({x + 1: sin(x)}) == ADD + SIN
+    assert count([x + 1, sin(x) + y, None]) == ADD + SIN + ADD
+    assert count({x + 1: sin(x), y: cos(x) + 1}) == SIN + COS + 2*ADD
+    assert count({}) is S.Zero
+    assert count([x + 1, sin(x)*y, None]) == SIN + ADD + MUL
+    assert count([]) is S.Zero
+
+    assert count(Basic()) == 0
+    assert count(Basic(Basic(),Basic(x,x+y))) == ADD + 2*BASIC
+    assert count(Basic(x, x + y)) == ADD + BASIC
+    assert [count(Rel(x, y, op)) for op in '< <= > >= == <> !='.split()
+        ] == [LT, LE, GT, GE, EQ, NE, NE]
+    assert count(Or(x, y)) == OR
+    assert count(And(x, y)) == AND
+    assert count(Or(x, Or(y, And(z, a)))) == AND + OR
+    assert count(Nor(x, y)) == NOT + OR
+    assert count(Nand(x, y)) == NOT + AND
+    assert count(Xor(x, y)) == XOR
+    assert count(Implies(x, y)) == IMPLIES
+    assert count(Equivalent(x, y)) == EQUIVALENT
+    assert count(ITE(x, y, z)) == _ITE
+    assert count([Or(x, y), And(x, y), Basic(x + y)]
+        ) == ADD + AND + BASIC + OR
+
+    assert count(Basic(Tuple(x))) == BASIC + TUPLE
+    #It checks that TUPLE is counted as an operation.
+
+    assert count(Eq(x + y, S(2))) == ADD + EQ
+
+
+def test_issue_9324():
+    def count(val):
+        return count_ops(val, visual=False)
+
+    M = MatrixSymbol('M', 10, 10)
+    assert count(M[0, 0]) == 0
+    assert count(2 * M[0, 0] + M[5, 7]) == 2
+    P = MatrixSymbol('P', 3, 3)
+    Q = MatrixSymbol('Q', 3, 3)
+    assert count(P + Q) == 1
+    m = Symbol('m', integer=True)
+    n = Symbol('n', integer=True)
+    M = MatrixSymbol('M', m + n, m * m)
+    assert count(M[0, 1]) == 2
+
+
+def test_issue_21532():
+    f = Function('f')
+    g = Function('g')
+    FUNC_F, FUNC_G = symbols('FUNC_F, FUNC_G')
+    assert f(x).count_ops(visual=True) == FUNC_F
+    assert g(x).count_ops(visual=True) == FUNC_G

env-llmeval/lib/python3.10/site-packages/sympy/core/tests/test_diff.py

@@ -0,0 +1,160 @@
+from sympy.concrete.summations import Sum
+from sympy.core.expr import Expr
+from sympy.core.function import (Derivative, Function, diff, Subs)
+from sympy.core.numbers import (I, Rational, pi)
+from sympy.core.relational import Eq
+from sympy.core.singleton import S
+from sympy.core.symbol import Symbol
+from sympy.functions.combinatorial.factorials import factorial
+from sympy.functions.elementary.complexes import (im, re)
+from sympy.functions.elementary.exponential import (exp, log)
+from sympy.functions.elementary.miscellaneous import Max
+from sympy.functions.elementary.piecewise import Piecewise
+from sympy.functions.elementary.trigonometric import (cos, cot, sin, tan)
+from sympy.tensor.array.ndim_array import NDimArray
+from sympy.testing.pytest import raises
+from sympy.abc import a, b, c, x, y, z
+
+def test_diff():
+    assert Rational(1, 3).diff(x) is S.Zero
+    assert I.diff(x) is S.Zero
+    assert pi.diff(x) is S.Zero
+    assert x.diff(x, 0) == x
+    assert (x**2).diff(x, 2, x) == 0
+    assert (x**2).diff((x, 2), x) == 0
+    assert (x**2).diff((x, 1), x) == 2
+    assert (x**2).diff((x, 1), (x, 1)) == 2
+    assert (x**2).diff((x, 2)) == 2
+    assert (x**2).diff(x, y, 0) == 2*x
+    assert (x**2).diff(x, (y, 0)) == 2*x
+    assert (x**2).diff(x, y) == 0
+    raises(ValueError, lambda: x.diff(1, x))
+
+    p = Rational(5)
+    e = a*b + b**p
+    assert e.diff(a) == b
+    assert e.diff(b) == a + 5*b**4
+    assert e.diff(b).diff(a) == Rational(1)
+    e = a*(b + c)
+    assert e.diff(a) == b + c
+    assert e.diff(b) == a
+    assert e.diff(b).diff(a) == Rational(1)
+    e = c**p
+    assert e.diff(c, 6) == Rational(0)
+    assert e.diff(c, 5) == Rational(120)
+    e = c**Rational(2)
+    assert e.diff(c) == 2*c
+    e = a*b*c
+    assert e.diff(c) == a*b
+
+
+def test_diff2():
+    n3 = Rational(3)
+    n2 = Rational(2)
+    n6 = Rational(6)
+
+    e = n3*(-n2 + x**n2)*cos(x) + x*(-n6 + x**n2)*sin(x)
+    assert e == 3*(-2 + x**2)*cos(x) + x*(-6 + x**2)*sin(x)
+    assert e.diff(x).expand() == x**3*cos(x)
+
+    e = (x + 1)**3
+    assert e.diff(x) == 3*(x + 1)**2
+    e = x*(x + 1)**3
+    assert e.diff(x) == (x + 1)**3 + 3*x*(x + 1)**2
+    e = 2*exp(x*x)*x
+    assert e.diff(x) == 2*exp(x**2) + 4*x**2*exp(x**2)
+
+
+def test_diff3():
+    p = Rational(5)
+    e = a*b + sin(b**p)
+    assert e == a*b + sin(b**5)
+    assert e.diff(a) == b
+    assert e.diff(b) == a + 5*b**4*cos(b**5)
+    e = tan(c)
+    assert e == tan(c)
+    assert e.diff(c) in [cos(c)**(-2), 1 + sin(c)**2/cos(c)**2, 1 + tan(c)**2]
+    e = c*log(c) - c
+    assert e == -c + c*log(c)
+    assert e.diff(c) == log(c)
+    e = log(sin(c))
+    assert e == log(sin(c))
+    assert e.diff(c) in [sin(c)**(-1)*cos(c), cot(c)]
+    e = (Rational(2)**a/log(Rational(2)))
+    assert e == 2**a*log(Rational(2))**(-1)
+    assert e.diff(a) == 2**a
+
+
+def test_diff_no_eval_derivative():
+    class My(Expr):
+        def __new__(cls, x):
+            return Expr.__new__(cls, x)
+
+    # My doesn't have its own _eval_derivative method
+    assert My(x).diff(x).func is Derivative
+    assert My(x).diff(x, 3).func is Derivative
+    assert re(x).diff(x, 2) == Derivative(re(x), (x, 2))  # issue 15518
+    assert diff(NDimArray([re(x), im(x)]), (x, 2)) == NDimArray(
+        [Derivative(re(x), (x, 2)), Derivative(im(x), (x, 2))])
+    # it doesn't have y so it shouldn't need a method for this case
+    assert My(x).diff(y) == 0
+
+
+def test_speed():
+    # this should return in 0.0s. If it takes forever, it's wrong.
+    assert x.diff(x, 10**8) == 0
+
+
+def test_deriv_noncommutative():
+    A = Symbol("A", commutative=False)
+    f = Function("f")
+    assert A*f(x)*A == f(x)*A**2
+    assert A*f(x).diff(x)*A == f(x).diff(x) * A**2
+
+
+def test_diff_nth_derivative():
+    f =  Function("f")
+    n = Symbol("n", integer=True)
+
+    expr = diff(sin(x), (x, n))
+    expr2 = diff(f(x), (x, 2))
+    expr3 = diff(f(x), (x, n))
+
+    assert expr.subs(sin(x), cos(-x)) == Derivative(cos(-x), (x, n))
+    assert expr.subs(n, 1).doit() == cos(x)
+    assert expr.subs(n, 2).doit() == -sin(x)
+
+    assert expr2.subs(Derivative(f(x), x), y) == Derivative(y, x)
+    # Currently not supported (cannot determine if `n > 1`):
+    #assert expr3.subs(Derivative(f(x), x), y) == Derivative(y, (x, n-1))
+    assert expr3 == Derivative(f(x), (x, n))
+
+    assert diff(x, (x, n)) == Piecewise((x, Eq(n, 0)), (1, Eq(n, 1)), (0, True))
+    assert diff(2*x, (x, n)).dummy_eq(
+        Sum(Piecewise((2*x*factorial(n)/(factorial(y)*factorial(-y + n)),
+        Eq(y, 0) & Eq(Max(0, -y + n), 0)),
+        (2*factorial(n)/(factorial(y)*factorial(-y + n)), Eq(y, 0) & Eq(Max(0,
+        -y + n), 1)), (0, True)), (y, 0, n)))
+    # TODO: assert diff(x**2, (x, n)) == x**(2-n)*ff(2, n)
+    exprm = x*sin(x)
+    mul_diff = diff(exprm, (x, n))
+    assert isinstance(mul_diff, Sum)
+    for i in range(5):
+        assert mul_diff.subs(n, i).doit() == exprm.diff((x, i)).expand()
+
+    exprm2 = 2*y*x*sin(x)*cos(x)*log(x)*exp(x)
+    dex = exprm2.diff((x, n))
+    assert isinstance(dex, Sum)
+    for i in range(7):
+        assert dex.subs(n, i).doit().expand() == \
+        exprm2.diff((x, i)).expand()
+
+    assert (cos(x)*sin(y)).diff([[x, y, z]]) == NDimArray([
+        -sin(x)*sin(y), cos(x)*cos(y), 0])
+
+
+def test_issue_16160():
+    assert Derivative(x**3, (x, x)).subs(x, 2) == Subs(
+        Derivative(x**3, (x, 2)), x, 2)
+    assert Derivative(1 + x**3, (x, x)).subs(x, 0
+        ) == Derivative(1 + y**3, (y, 0)).subs(y, 0)

env-llmeval/lib/python3.10/site-packages/sympy/core/tests/test_equal.py

@@ -0,0 +1,89 @@
+from sympy.core.numbers import Rational
+from sympy.core.symbol import (Dummy, Symbol)
+from sympy.functions.elementary.exponential import exp
+
+
+def test_equal():
+    b = Symbol("b")
+    a = Symbol("a")
+    e1 = a + b
+    e2 = 2*a*b
+    e3 = a**3*b**2
+    e4 = a*b + b*a
+    assert not e1 == e2
+    assert not e1 == e2
+    assert e1 != e2
+    assert e2 == e4
+    assert e2 != e3
+    assert not e2 == e3
+
+    x = Symbol("x")
+    e1 = exp(x + 1/x)
+    y = Symbol("x")
+    e2 = exp(y + 1/y)
+    assert e1 == e2
+    assert not e1 != e2
+    y = Symbol("y")
+    e2 = exp(y + 1/y)
+    assert not e1 == e2
+    assert e1 != e2
+
+    e5 = Rational(3) + 2*x - x - x
+    assert e5 == 3
+    assert 3 == e5
+    assert e5 != 4
+    assert 4 != e5
+    assert e5 != 3 + x
+    assert 3 + x != e5
+
+
+def test_expevalbug():
+    x = Symbol("x")
+    e1 = exp(1*x)
+    e3 = exp(x)
+    assert e1 == e3
+
+
+def test_cmp_bug1():
+    class T:
+        pass
+
+    t = T()
+    x = Symbol("x")
+
+    assert not (x == t)
+    assert (x != t)
+
+
+def test_cmp_bug2():
+    class T:
+        pass
+
+    t = T()
+
+    assert not (Symbol == t)
+    assert (Symbol != t)
+
+
+def test_cmp_issue_4357():
+    """ Check that Basic subclasses can be compared with sympifiable objects.
+
+    https://github.com/sympy/sympy/issues/4357
+    """
+    assert not (Symbol == 1)
+    assert (Symbol != 1)
+    assert not (Symbol == 'x')
+    assert (Symbol != 'x')
+
+
+def test_dummy_eq():
+    x = Symbol('x')
+    y = Symbol('y')
+
+    u = Dummy('u')
+
+    assert (u**2 + 1).dummy_eq(x**2 + 1) is True
+    assert ((u**2 + 1) == (x**2 + 1)) is False
+
+    assert (u**2 + y).dummy_eq(x**2 + y, x) is True
+    assert (u**2 + y).dummy_eq(x**2 + y, y) is False

env-llmeval/lib/python3.10/site-packages/sympy/core/tests/test_eval.py

@@ -0,0 +1,95 @@
+from sympy.core.function import Function
+from sympy.core.numbers import (I, Rational)
+from sympy.core.singleton import S
+from sympy.core.symbol import Symbol
+from sympy.functions.elementary.exponential import exp
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.functions.elementary.trigonometric import (cos, tan)
+from sympy.testing.pytest import XFAIL
+
+
+def test_add_eval():
+    a = Symbol("a")
+    b = Symbol("b")
+    c = Rational(1)
+    p = Rational(5)
+    assert a*b + c + p == a*b + 6
+    assert c + a + p == a + 6
+    assert c + a - p == a + (-4)
+    assert a + a == 2*a
+    assert a + p + a == 2*a + 5
+    assert c + p == Rational(6)
+    assert b + a - b == a
+
+
+def test_addmul_eval():
+    a = Symbol("a")
+    b = Symbol("b")
+    c = Rational(1)
+    p = Rational(5)
+    assert c + a + b*c + a - p == 2*a + b + (-4)
+    assert a*2 + p + a == a*2 + 5 + a
+    assert a*2 + p + a == 3*a + 5
+    assert a*2 + a == 3*a
+
+
+def test_pow_eval():
+    # XXX Pow does not fully support conversion of negative numbers
+    #     to their complex equivalent
+
+    assert sqrt(-1) == I
+
+    assert sqrt(-4) == 2*I
+    assert sqrt( 4) == 2
+    assert (8)**Rational(1, 3) == 2
+    assert (-8)**Rational(1, 3) == 2*((-1)**Rational(1, 3))
+
+    assert sqrt(-2) == I*sqrt(2)
+    assert (-1)**Rational(1, 3) != I
+    assert (-10)**Rational(1, 3) != I*((10)**Rational(1, 3))
+    assert (-2)**Rational(1, 4) != (2)**Rational(1, 4)
+
+    assert 64**Rational(1, 3) == 4
+    assert 64**Rational(2, 3) == 16
+    assert 24/sqrt(64) == 3
+    assert (-27)**Rational(1, 3) == 3*(-1)**Rational(1, 3)
+
+    assert (cos(2) / tan(2))**2 == (cos(2) / tan(2))**2
+
+
+@XFAIL
+def test_pow_eval_X1():
+    assert (-1)**Rational(1, 3) == S.Half + S.Half*I*sqrt(3)
+
+
+def test_mulpow_eval():
+    x = Symbol('x')
+    assert sqrt(50)/(sqrt(2)*x) == 5/x
+    assert sqrt(27)/sqrt(3) == 3
+
+
+def test_evalpow_bug():
+    x = Symbol("x")
+    assert 1/(1/x) == x
+    assert 1/(-1/x) == -x
+
+
+def test_symbol_expand():
+    x = Symbol('x')
+    y = Symbol('y')
+
+    f = x**4*y**4
+    assert f == x**4*y**4
+    assert f == f.expand()
+
+    g = (x*y)**4
+    assert g == f
+    assert g.expand() == f
+    assert g.expand() == g.expand().expand()
+
+
+def test_function():
+    f, l = map(Function, 'fl')
+    x = Symbol('x')
+    assert exp(l(x))*l(x)/exp(l(x)) == l(x)
+    assert exp(f(x))*f(x)/exp(f(x)) == f(x)

env-llmeval/lib/python3.10/site-packages/sympy/core/tests/test_evalf.py

@@ -0,0 +1,732 @@
+import math
+
+from sympy.concrete.products import (Product, product)
+from sympy.concrete.summations import Sum
+from sympy.core.add import Add
+from sympy.core.evalf import N
+from sympy.core.function import (Function, nfloat)
+from sympy.core.mul import Mul
+from sympy.core import (GoldenRatio)
+from sympy.core.numbers import (AlgebraicNumber, E, Float, I, Rational,
+                                oo, zoo, nan, pi)
+from sympy.core.power import Pow
+from sympy.core.relational import Eq
+from sympy.core.singleton import S
+from sympy.core.symbol import Symbol
+from sympy.core.sympify import sympify
+from sympy.functions.combinatorial.factorials import factorial
+from sympy.functions.combinatorial.numbers import fibonacci
+from sympy.functions.elementary.complexes import (Abs, re, im)
+from sympy.functions.elementary.exponential import (exp, log)
+from sympy.functions.elementary.hyperbolic import (acosh, cosh)
+from sympy.functions.elementary.integers import (ceiling, floor)
+from sympy.functions.elementary.miscellaneous import (Max, sqrt)
+from sympy.functions.elementary.trigonometric import (acos, atan, cos, sin, tan)
+from sympy.integrals.integrals import (Integral, integrate)
+from sympy.polys.polytools import factor
+from sympy.polys.rootoftools import CRootOf
+from sympy.polys.specialpolys import cyclotomic_poly
+from sympy.printing import srepr
+from sympy.printing.str import sstr
+from sympy.simplify.simplify import simplify
+from sympy.core.numbers import comp
+from sympy.core.evalf import (complex_accuracy, PrecisionExhausted,
+                              scaled_zero, get_integer_part, as_mpmath, evalf, _evalf_with_bounded_error)
+from mpmath import inf, ninf, make_mpc
+from mpmath.libmp.libmpf import from_float, fzero
+from sympy.core.expr import unchanged
+from sympy.testing.pytest import raises, XFAIL
+from sympy.abc import n, x, y
+
+
+def NS(e, n=15, **options):
+    return sstr(sympify(e).evalf(n, **options), full_prec=True)
+
+
+def test_evalf_helpers():
+    from mpmath.libmp import finf
+    assert complex_accuracy((from_float(2.0), None, 35, None)) == 35
+    assert complex_accuracy((from_float(2.0), from_float(10.0), 35, 100)) == 37
+    assert complex_accuracy(
+        (from_float(2.0), from_float(1000.0), 35, 100)) == 43
+    assert complex_accuracy((from_float(2.0), from_float(10.0), 100, 35)) == 35
+    assert complex_accuracy(
+        (from_float(2.0), from_float(1000.0), 100, 35)) == 35
+    assert complex_accuracy(finf) == math.inf
+    assert complex_accuracy(zoo) == math.inf
+    raises(ValueError, lambda: get_integer_part(zoo, 1, {}))
+
+
+def test_evalf_basic():
+    assert NS('pi', 15) == '3.14159265358979'
+    assert NS('2/3', 10) == '0.6666666667'
+    assert NS('355/113-pi', 6) == '2.66764e-7'
+    assert NS('16*atan(1/5)-4*atan(1/239)', 15) == '3.14159265358979'
+
+
+def test_cancellation():
+    assert NS(Add(pi, Rational(1, 10**1000), -pi, evaluate=False), 15,
+              maxn=1200) == '1.00000000000000e-1000'
+
+
+def test_evalf_powers():
+    assert NS('pi**(10**20)', 10) == '1.339148777e+49714987269413385435'
+    assert NS(pi**(10**100), 10) == ('4.946362032e+4971498726941338543512682882'
+          '9089887365167832438044244613405349992494711208'
+          '95526746555473864642912223')
+    assert NS('2**(1/10**50)', 15) == '1.00000000000000'
+    assert NS('2**(1/10**50)-1', 15) == '6.93147180559945e-51'
+
+# Evaluation of Rump's ill-conditioned polynomial
+
+
+def test_evalf_rump():
+    a = 1335*y**6/4 + x**2*(11*x**2*y**2 - y**6 - 121*y**4 - 2) + 11*y**8/2 + x/(2*y)
+    assert NS(a, 15, subs={x: 77617, y: 33096}) == '-0.827396059946821'
+
+
+def test_evalf_complex():
+    assert NS('2*sqrt(pi)*I', 10) == '3.544907702*I'
+    assert NS('3+3*I', 15) == '3.00000000000000 + 3.00000000000000*I'
+    assert NS('E+pi*I', 15) == '2.71828182845905 + 3.14159265358979*I'
+    assert NS('pi * (3+4*I)', 15) == '9.42477796076938 + 12.5663706143592*I'
+    assert NS('I*(2+I)', 15) == '-1.00000000000000 + 2.00000000000000*I'
+
+
+@XFAIL
+def test_evalf_complex_bug():
+    assert NS('(pi+E*I)*(E+pi*I)', 15) in ('0.e-15 + 17.25866050002*I',
+              '0.e-17 + 17.25866050002*I', '-0.e-17 + 17.25866050002*I')
+
+
+def test_evalf_complex_powers():
+    assert NS('(E+pi*I)**100000000000000000') == \
+        '-3.58896782867793e+61850354284995199 + 4.58581754997159e+61850354284995199*I'
+    # XXX: rewrite if a+a*I simplification introduced in SymPy
+    #assert NS('(pi + pi*I)**2') in ('0.e-15 + 19.7392088021787*I', '0.e-16 + 19.7392088021787*I')
+    assert NS('(pi + pi*I)**2', chop=True) == '19.7392088021787*I'
+    assert NS(
+        '(pi + 1/10**8 + pi*I)**2') == '6.2831853e-8 + 19.7392088650106*I'
+    assert NS('(pi + 1/10**12 + pi*I)**2') == '6.283e-12 + 19.7392088021850*I'
+    assert NS('(pi + pi*I)**4', chop=True) == '-389.636364136010'
+    assert NS(
+        '(pi + 1/10**8 + pi*I)**4') == '-389.636366616512 + 2.4805021e-6*I'
+    assert NS('(pi + 1/10**12 + pi*I)**4') == '-389.636364136258 + 2.481e-10*I'
+    assert NS(
+        '(10000*pi + 10000*pi*I)**4', chop=True) == '-3.89636364136010e+18'
+
+
+@XFAIL
+def test_evalf_complex_powers_bug():
+    assert NS('(pi + pi*I)**4') == '-389.63636413601 + 0.e-14*I'
+
+
+def test_evalf_exponentiation():
+    assert NS(sqrt(-pi)) == '1.77245385090552*I'
+    assert NS(Pow(pi*I, Rational(
+        1, 2), evaluate=False)) == '1.25331413731550 + 1.25331413731550*I'
+    assert NS(pi**I) == '0.413292116101594 + 0.910598499212615*I'
+    assert NS(pi**(E + I/3)) == '20.8438653991931 + 8.36343473930031*I'
+    assert NS((pi + I/3)**(E + I/3)) == '17.2442906093590 + 13.6839376767037*I'
+    assert NS(exp(pi)) == '23.1406926327793'
+    assert NS(exp(pi + E*I)) == '-21.0981542849657 + 9.50576358282422*I'
+    assert NS(pi**pi) == '36.4621596072079'
+    assert NS((-pi)**pi) == '-32.9138577418939 - 15.6897116534332*I'
+    assert NS((-pi)**(-pi)) == '-0.0247567717232697 + 0.0118013091280262*I'
+
+# An example from Smith, "Multiple Precision Complex Arithmetic and Functions"
+
+
+def test_evalf_complex_cancellation():
+    A = Rational('63287/100000')
+    B = Rational('52498/100000')
+    C = Rational('69301/100000')
+    D = Rational('83542/100000')
+    F = Rational('2231321613/2500000000')
+    # XXX: the number of returned mantissa digits in the real part could
+    # change with the implementation. What matters is that the returned digits are
+    # correct; those that are showing now are correct.
+    # >>> ((A+B*I)*(C+D*I)).expand()
+    # 64471/10000000000 + 2231321613*I/2500000000
+    # >>> 2231321613*4
+    # 8925286452L
+    assert NS((A + B*I)*(C + D*I), 6) == '6.44710e-6 + 0.892529*I'
+    assert NS((A + B*I)*(C + D*I), 10) == '6.447100000e-6 + 0.8925286452*I'
+    assert NS((A + B*I)*(
+        C + D*I) - F*I, 5) in ('6.4471e-6 + 0.e-14*I', '6.4471e-6 - 0.e-14*I')
+
+
+def test_evalf_logs():
+    assert NS("log(3+pi*I)", 15) == '1.46877619736226 + 0.808448792630022*I'
+    assert NS("log(pi*I)", 15) == '1.14472988584940 + 1.57079632679490*I'
+    assert NS('log(-1 + 0.00001)', 2) == '-1.0e-5 + 3.1*I'
+    assert NS('log(100, 10, evaluate=False)', 15) == '2.00000000000000'
+    assert NS('-2*I*log(-(-1)**(S(1)/9))', 15) == '-5.58505360638185'
+
+
+def test_evalf_trig():
+    assert NS('sin(1)', 15) == '0.841470984807897'
+    assert NS('cos(1)', 15) == '0.540302305868140'
+    assert NS('sin(10**-6)', 15) == '9.99999999999833e-7'
+    assert NS('cos(10**-6)', 15) == '0.999999999999500'
+    assert NS('sin(E*10**100)', 15) == '0.409160531722613'
+    # Some input near roots
+    assert NS(sin(exp(pi*sqrt(163))*pi), 15) == '-2.35596641936785e-12'
+    assert NS(sin(pi*10**100 + Rational(7, 10**5), evaluate=False), 15, maxn=120) == \
+        '6.99999999428333e-5'
+    assert NS(sin(Rational(7, 10**5), evaluate=False), 15) == \
+        '6.99999999428333e-5'
+
+# Check detection of various false identities
+
+
+def test_evalf_near_integers():
+    # Binet's formula
+    f = lambda n: ((1 + sqrt(5))**n)/(2**n * sqrt(5))
+    assert NS(f(5000) - fibonacci(5000), 10, maxn=1500) == '5.156009964e-1046'
+    # Some near-integer identities from
+    # http://mathworld.wolfram.com/AlmostInteger.html
+    assert NS('sin(2017*2**(1/5))', 15) == '-1.00000000000000'
+    assert NS('sin(2017*2**(1/5))', 20) == '-0.99999999999999997857'
+    assert NS('1+sin(2017*2**(1/5))', 15) == '2.14322287389390e-17'
+    assert NS('45 - 613*E/37 + 35/991', 15) == '6.03764498766326e-11'
+
+
+def test_evalf_ramanujan():
+    assert NS(exp(pi*sqrt(163)) - 640320**3 - 744, 10) == '-7.499274028e-13'
+    # A related identity
+    A = 262537412640768744*exp(-pi*sqrt(163))
+    B = 196884*exp(-2*pi*sqrt(163))
+    C = 103378831900730205293632*exp(-3*pi*sqrt(163))
+    assert NS(1 - A - B + C, 10) == '1.613679005e-59'
+
+# Input that for various reasons have failed at some point
+
+
+def test_evalf_bugs():
+    assert NS(sin(1) + exp(-10**10), 10) == NS(sin(1), 10)
+    assert NS(exp(10**10) + sin(1), 10) == NS(exp(10**10), 10)
+    assert NS('expand_log(log(1+1/10**50))', 20) == '1.0000000000000000000e-50'
+    assert NS('log(10**100,10)', 10) == '100.0000000'
+    assert NS('log(2)', 10) == '0.6931471806'
+    assert NS(
+        '(sin(x)-x)/x**3', 15, subs={x: '1/10**50'}) == '-0.166666666666667'
+    assert NS(sin(1) + Rational(
+        1, 10**100)*I, 15) == '0.841470984807897 + 1.00000000000000e-100*I'
+    assert x.evalf() == x
+    assert NS((1 + I)**2*I, 6) == '-2.00000'
+    d = {n: (
+        -1)**Rational(6, 7), y: (-1)**Rational(4, 7), x: (-1)**Rational(2, 7)}
+    assert NS((x*(1 + y*(1 + n))).subs(d).evalf(), 6) == '0.346011 + 0.433884*I'
+    assert NS(((-I - sqrt(2)*I)**2).evalf()) == '-5.82842712474619'
+    assert NS((1 + I)**2*I, 15) == '-2.00000000000000'
+    # issue 4758 (1/2):
+    assert NS(pi.evalf(69) - pi) == '-4.43863937855894e-71'
+    # issue 4758 (2/2): With the bug present, this still only fails if the
+    # terms are in the order given here. This is not generally the case,
+    # because the order depends on the hashes of the terms.
+    assert NS(20 - 5008329267844*n**25 - 477638700*n**37 - 19*n,
+              subs={n: .01}) == '19.8100000000000'
+    assert NS(((x - 1)*(1 - x)**1000).n()
+              ) == '(1.00000000000000 - x)**1000*(x - 1.00000000000000)'
+    assert NS((-x).n()) == '-x'
+    assert NS((-2*x).n()) == '-2.00000000000000*x'
+    assert NS((-2*x*y).n()) == '-2.00000000000000*x*y'
+    assert cos(x).n(subs={x: 1+I}) == cos(x).subs(x, 1+I).n()
+    # issue 6660. Also NaN != mpmath.nan
+    # In this order:
+    # 0*nan, 0/nan, 0*inf, 0/inf
+    # 0+nan, 0-nan, 0+inf, 0-inf
+    # >>> n = Some Number
+    # n*nan, n/nan, n*inf, n/inf
+    # n+nan, n-nan, n+inf, n-inf
+    assert (0*E**(oo)).n() is S.NaN
+    assert (0/E**(oo)).n() is S.Zero
+
+    assert (0+E**(oo)).n() is S.Infinity
+    assert (0-E**(oo)).n() is S.NegativeInfinity
+
+    assert (5*E**(oo)).n() is S.Infinity
+    assert (5/E**(oo)).n() is S.Zero
+
+    assert (5+E**(oo)).n() is S.Infinity
+    assert (5-E**(oo)).n() is S.NegativeInfinity
+
+    #issue 7416
+    assert as_mpmath(0.0, 10, {'chop': True}) == 0
+
+    #issue 5412
+    assert ((oo*I).n() == S.Infinity*I)
+    assert ((oo+oo*I).n() == S.Infinity + S.Infinity*I)
+
+    #issue 11518
+    assert NS(2*x**2.5, 5) == '2.0000*x**2.5000'
+
+    #issue 13076
+    assert NS(Mul(Max(0, y), x, evaluate=False).evalf()) == 'x*Max(0, y)'
+
+    #issue 18516
+    assert NS(log(S(3273390607896141870013189696827599152216642046043064789483291368096133796404674554883270092325904157150886684127560071009217256545885393053328527589376)/36360291795869936842385267079543319118023385026001623040346035832580600191583895484198508262979388783308179702534403855752855931517013066142992430916562025780021771247847643450125342836565813209972590371590152578728008385990139795377610001).evalf(15, chop=True)) == '-oo'
+
+
+def test_evalf_integer_parts():
+    a = floor(log(8)/log(2) - exp(-1000), evaluate=False)
+    b = floor(log(8)/log(2), evaluate=False)
+    assert a.evalf() == 3.0
+    assert b.evalf() == 3.0
+    # equals, as a fallback, can still fail but it might succeed as here
+    assert ceiling(10*(sin(1)**2 + cos(1)**2)) == 10
+
+    assert int(floor(factorial(50)/E, evaluate=False).evalf(70)) == \
+        int(11188719610782480504630258070757734324011354208865721592720336800)
+    assert int(ceiling(factorial(50)/E, evaluate=False).evalf(70)) == \
+        int(11188719610782480504630258070757734324011354208865721592720336801)
+    assert int(floor(GoldenRatio**999 / sqrt(5) + S.Half)
+               .evalf(1000)) == fibonacci(999)
+    assert int(floor(GoldenRatio**1000 / sqrt(5) + S.Half)
+               .evalf(1000)) == fibonacci(1000)
+
+    assert ceiling(x).evalf(subs={x: 3}) == 3.0
+    assert ceiling(x).evalf(subs={x: 3*I}) == 3.0*I
+    assert ceiling(x).evalf(subs={x: 2 + 3*I}) == 2.0 + 3.0*I
+    assert ceiling(x).evalf(subs={x: 3.}) == 3.0
+    assert ceiling(x).evalf(subs={x: 3.*I}) == 3.0*I
+    assert ceiling(x).evalf(subs={x: 2. + 3*I}) == 2.0 + 3.0*I
+
+    assert float((floor(1.5, evaluate=False)+1/9).evalf()) == 1 + 1/9
+    assert float((floor(0.5, evaluate=False)+20).evalf()) == 20
+
+    # issue 19991
+    n = 1169809367327212570704813632106852886389036911
+    r = 744723773141314414542111064094745678855643068
+
+    assert floor(n / (pi / 2)) == r
+    assert floor(80782 * sqrt(2)) == 114242
+
+    # issue 20076
+    assert 260515 - floor(260515/pi + 1/2) * pi == atan(tan(260515))
+
+
+def test_evalf_trig_zero_detection():
+    a = sin(160*pi, evaluate=False)
+    t = a.evalf(maxn=100)
+    assert abs(t) < 1e-100
+    assert t._prec < 2
+    assert a.evalf(chop=True) == 0
+    raises(PrecisionExhausted, lambda: a.evalf(strict=True))
+
+
+def test_evalf_sum():
+    assert Sum(n,(n,1,2)).evalf() == 3.
+    assert Sum(n,(n,1,2)).doit().evalf() == 3.
+    # the next test should return instantly
+    assert Sum(1/n,(n,1,2)).evalf() == 1.5
+
+    # issue 8219
+    assert Sum(E/factorial(n), (n, 0, oo)).evalf() == (E*E).evalf()
+    # issue 8254
+    assert Sum(2**n*n/factorial(n), (n, 0, oo)).evalf() == (2*E*E).evalf()
+    # issue 8411
+    s = Sum(1/x**2, (x, 100, oo))
+    assert s.n() == s.doit().n()
+
+
+def test_evalf_divergent_series():
+    raises(ValueError, lambda: Sum(1/n, (n, 1, oo)).evalf())
+    raises(ValueError, lambda: Sum(n/(n**2 + 1), (n, 1, oo)).evalf())
+    raises(ValueError, lambda: Sum((-1)**n, (n, 1, oo)).evalf())
+    raises(ValueError, lambda: Sum((-1)**n, (n, 1, oo)).evalf())
+    raises(ValueError, lambda: Sum(n**2, (n, 1, oo)).evalf())
+    raises(ValueError, lambda: Sum(2**n, (n, 1, oo)).evalf())
+    raises(ValueError, lambda: Sum((-2)**n, (n, 1, oo)).evalf())
+    raises(ValueError, lambda: Sum((2*n + 3)/(3*n**2 + 4), (n, 0, oo)).evalf())
+    raises(ValueError, lambda: Sum((0.5*n**3)/(n**4 + 1), (n, 0, oo)).evalf())
+
+
+def test_evalf_product():
+    assert Product(n, (n, 1, 10)).evalf() == 3628800.
+    assert comp(Product(1 - S.Half**2/n**2, (n, 1, oo)).n(5), 0.63662)
+    assert Product(n, (n, -1, 3)).evalf() == 0
+
+
+def test_evalf_py_methods():
+    assert abs(float(pi + 1) - 4.1415926535897932) < 1e-10
+    assert abs(complex(pi + 1) - 4.1415926535897932) < 1e-10
+    assert abs(
+        complex(pi + E*I) - (3.1415926535897931 + 2.7182818284590451j)) < 1e-10
+    raises(TypeError, lambda: float(pi + x))
+
+
+def test_evalf_power_subs_bugs():
+    assert (x**2).evalf(subs={x: 0}) == 0
+    assert sqrt(x).evalf(subs={x: 0}) == 0
+    assert (x**Rational(2, 3)).evalf(subs={x: 0}) == 0
+    assert (x**x).evalf(subs={x: 0}) == 1.0
+    assert (3**x).evalf(subs={x: 0}) == 1.0
+    assert exp(x).evalf(subs={x: 0}) == 1.0
+    assert ((2 + I)**x).evalf(subs={x: 0}) == 1.0
+    assert (0**x).evalf(subs={x: 0}) == 1.0
+
+
+def test_evalf_arguments():
+    raises(TypeError, lambda: pi.evalf(method="garbage"))
+
+
+def test_implemented_function_evalf():
+    from sympy.utilities.lambdify import implemented_function
+    f = Function('f')
+    f = implemented_function(f, lambda x: x + 1)
+    assert str(f(x)) == "f(x)"
+    assert str(f(2)) == "f(2)"
+    assert f(2).evalf() == 3.0
+    assert f(x).evalf() == f(x)
+    f = implemented_function(Function('sin'), lambda x: x + 1)
+    assert f(2).evalf() != sin(2)
+    del f._imp_     # XXX: due to caching _imp_ would influence all other tests
+
+
+def test_evaluate_false():
+    for no in [0, False]:
+        assert Add(3, 2, evaluate=no).is_Add
+        assert Mul(3, 2, evaluate=no).is_Mul
+        assert Pow(3, 2, evaluate=no).is_Pow
+    assert Pow(y, 2, evaluate=True) - Pow(y, 2, evaluate=True) == 0
+
+
+def test_evalf_relational():
+    assert Eq(x/5, y/10).evalf() == Eq(0.2*x, 0.1*y)
+    # if this first assertion fails it should be replaced with
+    # one that doesn't
+    assert unchanged(Eq, (3 - I)**2/2 + I, 0)
+    assert Eq((3 - I)**2/2 + I, 0).n() is S.false
+    assert nfloat(Eq((3 - I)**2 + I, 0)) == S.false
+
+
+def test_issue_5486():
+    assert not cos(sqrt(0.5 + I)).n().is_Function
+
+
+def test_issue_5486_bug():
+    from sympy.core.expr import Expr
+    from sympy.core.numbers import I
+    assert abs(Expr._from_mpmath(I._to_mpmath(15), 15) - I) < 1.0e-15
+
+
+def test_bugs():
+    from sympy.functions.elementary.complexes import (polar_lift, re)
+
+    assert abs(re((1 + I)**2)) < 1e-15
+
+    # anything that evalf's to 0 will do in place of polar_lift
+    assert abs(polar_lift(0)).n() == 0
+
+
+def test_subs():
+    assert NS('besseli(-x, y) - besseli(x, y)', subs={x: 3.5, y: 20.0}) == \
+        '-4.92535585957223e-10'
+    assert NS('Piecewise((x, x>0)) + Piecewise((1-x, x>0))', subs={x: 0.1}) == \
+        '1.00000000000000'
+    raises(TypeError, lambda: x.evalf(subs=(x, 1)))
+
+
+def test_issue_4956_5204():
+    # issue 4956
+    v = S('''(-27*12**(1/3)*sqrt(31)*I +
+    27*2**(2/3)*3**(1/3)*sqrt(31)*I)/(-2511*2**(2/3)*3**(1/3) +
+    (29*18**(1/3) + 9*2**(1/3)*3**(2/3)*sqrt(31)*I +
+    87*2**(1/3)*3**(1/6)*I)**2)''')
+    assert NS(v, 1) == '0.e-118 - 0.e-118*I'
+
+    # issue 5204
+    v = S('''-(357587765856 + 18873261792*249**(1/2) + 56619785376*I*83**(1/2) +
+    108755765856*I*3**(1/2) + 41281887168*6**(1/3)*(1422 +
+    54*249**(1/2))**(1/3) - 1239810624*6**(1/3)*249**(1/2)*(1422 +
+    54*249**(1/2))**(1/3) - 3110400000*I*6**(1/3)*83**(1/2)*(1422 +
+    54*249**(1/2))**(1/3) + 13478400000*I*3**(1/2)*6**(1/3)*(1422 +
+    54*249**(1/2))**(1/3) + 1274950152*6**(2/3)*(1422 +
+    54*249**(1/2))**(2/3) + 32347944*6**(2/3)*249**(1/2)*(1422 +
+    54*249**(1/2))**(2/3) - 1758790152*I*3**(1/2)*6**(2/3)*(1422 +
+    54*249**(1/2))**(2/3) - 304403832*I*6**(2/3)*83**(1/2)*(1422 +
+    4*249**(1/2))**(2/3))/(175732658352 + (1106028 + 25596*249**(1/2) +
+    76788*I*83**(1/2))**2)''')
+    assert NS(v, 5) == '0.077284 + 1.1104*I'
+    assert NS(v, 1) == '0.08 + 1.*I'
+
+
+def test_old_docstring():
+    a = (E + pi*I)*(E - pi*I)
+    assert NS(a) == '17.2586605000200'
+    assert a.n() == 17.25866050002001
+
+
+def test_issue_4806():
+    assert integrate(atan(x)**2, (x, -1, 1)).evalf().round(1) == Float(0.5, 1)
+    assert atan(0, evaluate=False).n() == 0
+
+
+def test_evalf_mul():
+    # SymPy should not try to expand this; it should be handled term-wise
+    # in evalf through mpmath
+    assert NS(product(1 + sqrt(n)*I, (n, 1, 500)), 1) == '5.e+567 + 2.e+568*I'
+
+
+def test_scaled_zero():
+    a, b = (([0], 1, 100, 1), -1)
+    assert scaled_zero(100) == (a, b)
+    assert scaled_zero(a) == (0, 1, 100, 1)
+    a, b = (([1], 1, 100, 1), -1)
+    assert scaled_zero(100, -1) == (a, b)
+    assert scaled_zero(a) == (1, 1, 100, 1)
+    raises(ValueError, lambda: scaled_zero(scaled_zero(100)))
+    raises(ValueError, lambda: scaled_zero(100, 2))
+    raises(ValueError, lambda: scaled_zero(100, 0))
+    raises(ValueError, lambda: scaled_zero((1, 5, 1, 3)))
+
+
+def test_chop_value():
+    for i in range(-27, 28):
+        assert (Pow(10, i)*2).n(chop=10**i) and not (Pow(10, i)).n(chop=10**i)
+
+
+def test_infinities():
+    assert oo.evalf(chop=True) == inf
+    assert (-oo).evalf(chop=True) == ninf
+
+
+def test_to_mpmath():
+    assert sqrt(3)._to_mpmath(20)._mpf_ == (0, int(908093), -19, 20)
+    assert S(3.2)._to_mpmath(20)._mpf_ == (0, int(838861), -18, 20)
+
+
+def test_issue_6632_evalf():
+    add = (-100000*sqrt(2500000001) + 5000000001)
+    assert add.n() == 9.999999998e-11
+    assert (add*add).n() == 9.999999996e-21
+
+
+def test_issue_4945():
+    from sympy.abc import H
+    assert (H/0).evalf(subs={H:1}) == zoo
+
+
+def test_evalf_integral():
+    # test that workprec has to increase in order to get a result other than 0
+    eps = Rational(1, 1000000)
+    assert Integral(sin(x), (x, -pi, pi + eps)).n(2)._prec == 10
+
+
+def test_issue_8821_highprec_from_str():
+    s = str(pi.evalf(128))
+    p = N(s)
+    assert Abs(sin(p)) < 1e-15
+    p = N(s, 64)
+    assert Abs(sin(p)) < 1e-64
+
+
+def test_issue_8853():
+    p = Symbol('x', even=True, positive=True)
+    assert floor(-p - S.Half).is_even == False
+    assert floor(-p + S.Half).is_even == True
+    assert ceiling(p - S.Half).is_even == True
+    assert ceiling(p + S.Half).is_even == False
+
+    assert get_integer_part(S.Half, -1, {}, True) == (0, 0)
+    assert get_integer_part(S.Half, 1, {}, True) == (1, 0)
+    assert get_integer_part(Rational(-1, 2), -1, {}, True) == (-1, 0)
+    assert get_integer_part(Rational(-1, 2), 1, {}, True) == (0, 0)
+
+
+def test_issue_17681():
+    class identity_func(Function):
+
+        def _eval_evalf(self, *args, **kwargs):
+            return self.args[0].evalf(*args, **kwargs)
+
+    assert floor(identity_func(S(0))) == 0
+    assert get_integer_part(S(0), 1, {}, True) == (0, 0)
+
+
+def test_issue_9326():
+    from sympy.core.symbol import Dummy
+    d1 = Dummy('d')
+    d2 = Dummy('d')
+    e = d1 + d2
+    assert e.evalf(subs = {d1: 1, d2: 2}) == 3.0
+
+
+def test_issue_10323():
+    assert ceiling(sqrt(2**30 + 1)) == 2**15 + 1
+
+
+def test_AssocOp_Function():
+    # the first arg of Min is not comparable in the imaginary part
+    raises(ValueError, lambda: S('''
+    Min(-sqrt(3)*cos(pi/18)/6 + re(1/((-1/2 - sqrt(3)*I/2)*(1/6 +
+    sqrt(3)*I/18)**(1/3)))/3 + sin(pi/18)/2 + 2 + I*(-cos(pi/18)/2 -
+    sqrt(3)*sin(pi/18)/6 + im(1/((-1/2 - sqrt(3)*I/2)*(1/6 +
+    sqrt(3)*I/18)**(1/3)))/3), re(1/((-1/2 + sqrt(3)*I/2)*(1/6 +
+    sqrt(3)*I/18)**(1/3)))/3 - sqrt(3)*cos(pi/18)/6 - sin(pi/18)/2 + 2 +
+    I*(im(1/((-1/2 + sqrt(3)*I/2)*(1/6 + sqrt(3)*I/18)**(1/3)))/3 -
+    sqrt(3)*sin(pi/18)/6 + cos(pi/18)/2))'''))
+    # if that is changed so a non-comparable number remains as
+    # an arg, then the Min/Max instantiation needs to be changed
+    # to watch out for non-comparable args when making simplifications
+    # and the following test should be added instead (with e being
+    # the sympified expression above):
+    # raises(ValueError, lambda: e._eval_evalf(2))
+
+
+def test_issue_10395():
+    eq = x*Max(0, y)
+    assert nfloat(eq) == eq
+    eq = x*Max(y, -1.1)
+    assert nfloat(eq) == eq
+    assert Max(y, 4).n() == Max(4.0, y)
+
+
+def test_issue_13098():
+    assert floor(log(S('9.'+'9'*20), 10)) == 0
+    assert ceiling(log(S('9.'+'9'*20), 10)) == 1
+    assert floor(log(20 - S('9.'+'9'*20), 10)) == 1
+    assert ceiling(log(20 - S('9.'+'9'*20), 10)) == 2
+
+
+def test_issue_14601():
+    e = 5*x*y/2 - y*(35*(x**3)/2 - 15*x/2)
+    subst = {x:0.0, y:0.0}
+    e2 = e.evalf(subs=subst)
+    assert float(e2) == 0.0
+    assert float((x + x*(x**2 + x)).evalf(subs={x: 0.0})) == 0.0
+
+
+def test_issue_11151():
+    z = S.Zero
+    e = Sum(z, (x, 1, 2))
+    assert e != z  # it shouldn't evaluate
+    # when it does evaluate, this is what it should give
+    assert evalf(e, 15, {}) == \
+        evalf(z, 15, {}) == (None, None, 15, None)
+    # so this shouldn't fail
+    assert (e/2).n() == 0
+    # this was where the issue appeared
+    expr0 = Sum(x**2 + x, (x, 1, 2))
+    expr1 = Sum(0, (x, 1, 2))
+    expr2 = expr1/expr0
+    assert simplify(factor(expr2) - expr2) == 0
+
+
+def test_issue_13425():
+    assert N('2**.5', 30) == N('sqrt(2)', 30)
+    assert N('x - x', 30) == 0
+    assert abs((N('pi*.1', 22)*10 - pi).n()) < 1e-22
+
+
+def test_issue_17421():
+    assert N(acos(-I + acosh(cosh(cosh(1) + I)))) == 1.0*I
+
+
+def test_issue_20291():
+    from sympy.sets import EmptySet, Reals
+    from sympy.sets.sets import (Complement, FiniteSet, Intersection)
+    a = Symbol('a')
+    b = Symbol('b')
+    A = FiniteSet(a, b)
+    assert A.evalf(subs={a: 1, b: 2}) == FiniteSet(1.0, 2.0)
+    B = FiniteSet(a-b, 1)
+    assert B.evalf(subs={a: 1, b: 2}) == FiniteSet(-1.0, 1.0)
+
+    sol = Complement(Intersection(FiniteSet(-b/2 - sqrt(b**2-4*pi)/2), Reals), FiniteSet(0))
+    assert sol.evalf(subs={b: 1}) == EmptySet
+
+
+def test_evalf_with_zoo():
+    assert (1/x).evalf(subs={x: 0}) == zoo  # issue 8242
+    assert (-1/x).evalf(subs={x: 0}) == zoo  # PR 16150
+    assert (0 ** x).evalf(subs={x: -1}) == zoo  # PR 16150
+    assert (0 ** x).evalf(subs={x: -1 + I}) == nan
+    assert Mul(2, Pow(0, -1, evaluate=False), evaluate=False).evalf() == zoo  # issue 21147
+    assert Mul(x, 1/x, evaluate=False).evalf(subs={x: 0}) == Mul(x, 1/x, evaluate=False).subs(x, 0) == nan
+    assert Mul(1/x, 1/x, evaluate=False).evalf(subs={x: 0}) == zoo
+    assert Mul(1/x, Abs(1/x), evaluate=False).evalf(subs={x: 0}) == zoo
+    assert Abs(zoo, evaluate=False).evalf() == oo
+    assert re(zoo, evaluate=False).evalf() == nan
+    assert im(zoo, evaluate=False).evalf() == nan
+    assert Add(zoo, zoo, evaluate=False).evalf() == nan
+    assert Add(oo, zoo, evaluate=False).evalf() == nan
+    assert Pow(zoo, -1, evaluate=False).evalf() == 0
+    assert Pow(zoo, Rational(-1, 3), evaluate=False).evalf() == 0
+    assert Pow(zoo, Rational(1, 3), evaluate=False).evalf() == zoo
+    assert Pow(zoo, S.Half, evaluate=False).evalf() == zoo
+    assert Pow(zoo, 2, evaluate=False).evalf() == zoo
+    assert Pow(0, zoo, evaluate=False).evalf() == nan
+    assert log(zoo, evaluate=False).evalf() == zoo
+    assert zoo.evalf(chop=True) == zoo
+    assert x.evalf(subs={x: zoo}) == zoo
+
+
+def test_evalf_with_bounded_error():
+    cases = [
+        # zero
+        (Rational(0), None, 1),
+        # zero im part
+        (pi, None, 10),
+        # zero real part
+        (pi*I, None, 10),
+        # re and im nonzero
+        (2-3*I, None, 5),
+        # similar tests again, but using eps instead of m
+        (Rational(0), Rational(1, 2), None),
+        (pi, Rational(1, 1000), None),
+        (pi * I, Rational(1, 1000), None),
+        (2 - 3 * I, Rational(1, 1000), None),
+        # very large eps
+        (2 - 3 * I, Rational(1000), None),
+        # case where x already small, hence some cancellation in p = m + n - 1
+        (Rational(1234, 10**8), Rational(1, 10**12), None),
+    ]
+    for x0, eps, m in cases:
+        a, b, _, _ = evalf(x0, 53, {})
+        c, d, _, _ = _evalf_with_bounded_error(x0, eps, m)
+        if eps is None:
+            eps = 2**(-m)
+        z = make_mpc((a or fzero, b or fzero))
+        w = make_mpc((c or fzero, d or fzero))
+        assert abs(w - z) < eps
+
+    # eps must be positive
+    raises(ValueError, lambda: _evalf_with_bounded_error(pi, Rational(0)))
+    raises(ValueError, lambda: _evalf_with_bounded_error(pi, -pi))
+    raises(ValueError, lambda: _evalf_with_bounded_error(pi, I))
+
+
+def test_issue_22849():
+    a = -8 + 3 * sqrt(3)
+    x = AlgebraicNumber(a)
+    assert evalf(a, 1, {}) == evalf(x, 1, {})
+
+
+def test_evalf_real_alg_num():
+    # This test demonstrates why the entry for `AlgebraicNumber` in
+    # `sympy.core.evalf._create_evalf_table()` has to use `x.to_root()`,
+    # instead of `x.as_expr()`. If the latter is used, then `z` will be
+    # a complex number with `0.e-20` for imaginary part, even though `a5`
+    # is a real number.
+    zeta = Symbol('zeta')
+    a5 = AlgebraicNumber(CRootOf(cyclotomic_poly(5), -1), [-1, -1, 0, 0], alias=zeta)
+    z = a5.evalf()
+    assert isinstance(z, Float)
+    assert not hasattr(z, '_mpc_')
+    assert hasattr(z, '_mpf_')
+
+
+def test_issue_20733():
+    expr = 1/((x - 9)*(x - 8)*(x - 7)*(x - 4)**2*(x - 3)**3*(x - 2))
+    assert str(expr.evalf(1, subs={x:1})) == '-4.e-5'
+    assert str(expr.evalf(2, subs={x:1})) == '-4.1e-5'
+    assert str(expr.evalf(11, subs={x:1})) == '-4.1335978836e-5'
+    assert str(expr.evalf(20, subs={x:1})) == '-0.000041335978835978835979'
+
+    expr = Mul(*((x - i) for i in range(2, 1000)))
+    assert srepr(expr.evalf(2, subs={x: 1})) == "Float('4.0271e+2561', precision=10)"
+    assert srepr(expr.evalf(10, subs={x: 1})) == "Float('4.02790050126e+2561', precision=37)"
+    assert srepr(expr.evalf(53, subs={x: 1})) == "Float('4.0279005012722099453824067459760158730668154575647110393e+2561', precision=179)"

env-llmeval/lib/python3.10/site-packages/sympy/core/tests/test_expr.py

@@ -0,0 +1,2261 @@
+from sympy.assumptions.refine import refine
+from sympy.concrete.summations import Sum
+from sympy.core.add import Add
+from sympy.core.basic import Basic
+from sympy.core.containers import Tuple
+from sympy.core.expr import (ExprBuilder, unchanged, Expr,
+    UnevaluatedExpr)
+from sympy.core.function import (Function, expand, WildFunction,
+    AppliedUndef, Derivative, diff, Subs)
+from sympy.core.mul import Mul
+from sympy.core.numbers import (NumberSymbol, E, zoo, oo, Float, I,
+    Rational, nan, Integer, Number, pi, _illegal)
+from sympy.core.power import Pow
+from sympy.core.relational import Ge, Lt, Gt, Le
+from sympy.core.singleton import S
+from sympy.core.sorting import default_sort_key
+from sympy.core.symbol import Symbol, symbols, Dummy, Wild
+from sympy.core.sympify import sympify
+from sympy.functions.combinatorial.factorials import factorial
+from sympy.functions.elementary.exponential import exp_polar, exp, log
+from sympy.functions.elementary.miscellaneous import sqrt, Max
+from sympy.functions.elementary.piecewise import Piecewise
+from sympy.functions.elementary.trigonometric import tan, sin, cos
+from sympy.functions.special.delta_functions import (Heaviside,
+    DiracDelta)
+from sympy.functions.special.error_functions import Si
+from sympy.functions.special.gamma_functions import gamma
+from sympy.integrals.integrals import integrate, Integral
+from sympy.physics.secondquant import FockState
+from sympy.polys.partfrac import apart
+from sympy.polys.polytools import factor, cancel, Poly
+from sympy.polys.rationaltools import together
+from sympy.series.order import O
+from sympy.sets.sets import FiniteSet
+from sympy.simplify.combsimp import combsimp
+from sympy.simplify.gammasimp import gammasimp
+from sympy.simplify.powsimp import powsimp
+from sympy.simplify.radsimp import collect, radsimp
+from sympy.simplify.ratsimp import ratsimp
+from sympy.simplify.simplify import simplify, nsimplify
+from sympy.simplify.trigsimp import trigsimp
+from sympy.tensor.indexed import Indexed
+from sympy.physics.units import meter
+
+from sympy.testing.pytest import raises, XFAIL
+
+from sympy.abc import a, b, c, n, t, u, x, y, z
+
+
+f, g, h = symbols('f,g,h', cls=Function)
+
+
+class DummyNumber:
+    """
+    Minimal implementation of a number that works with SymPy.
+
+    If one has a Number class (e.g. Sage Integer, or some other custom class)
+    that one wants to work well with SymPy, one has to implement at least the
+    methods of this class DummyNumber, resp. its subclasses I5 and F1_1.
+
+    Basically, one just needs to implement either __int__() or __float__() and
+    then one needs to make sure that the class works with Python integers and
+    with itself.
+    """
+
+    def __radd__(self, a):
+        if isinstance(a, (int, float)):
+            return a + self.number
+        return NotImplemented
+
+    def __add__(self, a):
+        if isinstance(a, (int, float, DummyNumber)):
+            return self.number + a
+        return NotImplemented
+
+    def __rsub__(self, a):
+        if isinstance(a, (int, float)):
+            return a - self.number
+        return NotImplemented
+
+    def __sub__(self, a):
+        if isinstance(a, (int, float, DummyNumber)):
+            return self.number - a
+        return NotImplemented
+
+    def __rmul__(self, a):
+        if isinstance(a, (int, float)):
+            return a * self.number
+        return NotImplemented
+
+    def __mul__(self, a):
+        if isinstance(a, (int, float, DummyNumber)):
+            return self.number * a
+        return NotImplemented
+
+    def __rtruediv__(self, a):
+        if isinstance(a, (int, float)):
+            return a / self.number
+        return NotImplemented
+
+    def __truediv__(self, a):
+        if isinstance(a, (int, float, DummyNumber)):
+            return self.number / a
+        return NotImplemented
+
+    def __rpow__(self, a):
+        if isinstance(a, (int, float)):
+            return a ** self.number
+        return NotImplemented
+
+    def __pow__(self, a):
+        if isinstance(a, (int, float, DummyNumber)):
+            return self.number ** a
+        return NotImplemented
+
+    def __pos__(self):
+        return self.number
+
+    def __neg__(self):
+        return - self.number
+
+
+class I5(DummyNumber):
+    number = 5
+
+    def __int__(self):
+        return self.number
+
+
+class F1_1(DummyNumber):
+    number = 1.1
+
+    def __float__(self):
+        return self.number
+
+i5 = I5()
+f1_1 = F1_1()
+
+# basic SymPy objects
+basic_objs = [
+    Rational(2),
+    Float("1.3"),
+    x,
+    y,
+    pow(x, y)*y,
+]
+
+# all supported objects
+all_objs = basic_objs + [
+    5,
+    5.5,
+    i5,
+    f1_1
+]
+
+
+def dotest(s):
+    for xo in all_objs:
+        for yo in all_objs:
+            s(xo, yo)
+    return True
+
+
+def test_basic():
+    def j(a, b):
+        x = a
+        x = +a
+        x = -a
+        x = a + b
+        x = a - b
+        x = a*b
+        x = a/b
+        x = a**b
+        del x
+    assert dotest(j)
+
+
+def test_ibasic():
+    def s(a, b):
+        x = a
+        x += b
+        x = a
+        x -= b
+        x = a
+        x *= b
+        x = a
+        x /= b
+    assert dotest(s)
+
+
+class NonBasic:
+    '''This class represents an object that knows how to implement binary
+    operations like +, -, etc with Expr but is not a subclass of Basic itself.
+    The NonExpr subclass below does subclass Basic but not Expr.
+
+    For both NonBasic and NonExpr it should be possible for them to override
+    Expr.__add__ etc because Expr.__add__ should be returning NotImplemented
+    for non Expr classes. Otherwise Expr.__add__ would create meaningless
+    objects like Add(Integer(1), FiniteSet(2)) and it wouldn't be possible for
+    other classes to override these operations when interacting with Expr.
+    '''
+    def __add__(self, other):
+        return SpecialOp('+', self, other)
+
+    def __radd__(self, other):
+        return SpecialOp('+', other, self)
+
+    def __sub__(self, other):
+        return SpecialOp('-', self, other)
+
+    def __rsub__(self, other):
+        return SpecialOp('-', other, self)
+
+    def __mul__(self, other):
+        return SpecialOp('*', self, other)
+
+    def __rmul__(self, other):
+        return SpecialOp('*', other, self)
+
+    def __truediv__(self, other):
+        return SpecialOp('/', self, other)
+
+    def __rtruediv__(self, other):
+        return SpecialOp('/', other, self)
+
+    def __floordiv__(self, other):
+        return SpecialOp('//', self, other)
+
+    def __rfloordiv__(self, other):
+        return SpecialOp('//', other, self)
+
+    def __mod__(self, other):
+        return SpecialOp('%', self, other)
+
+    def __rmod__(self, other):
+        return SpecialOp('%', other, self)
+
+    def __divmod__(self, other):
+        return SpecialOp('divmod', self, other)
+
+    def __rdivmod__(self, other):
+        return SpecialOp('divmod', other, self)
+
+    def __pow__(self, other):
+        return SpecialOp('**', self, other)
+
+    def __rpow__(self, other):
+        return SpecialOp('**', other, self)
+
+    def __lt__(self, other):
+        return SpecialOp('<', self, other)
+
+    def __gt__(self, other):
+        return SpecialOp('>', self, other)
+
+    def __le__(self, other):
+        return SpecialOp('<=', self, other)
+
+    def __ge__(self, other):
+        return SpecialOp('>=', self, other)
+
+
+class NonExpr(Basic, NonBasic):
+    '''Like NonBasic above except this is a subclass of Basic but not Expr'''
+    pass
+
+
+class SpecialOp():
+    '''Represents the results of operations with NonBasic and NonExpr'''
+    def __new__(cls, op, arg1, arg2):
+        obj = object.__new__(cls)
+        obj.args = (op, arg1, arg2)
+        return obj
+
+
+class NonArithmetic(Basic):
+    '''Represents a Basic subclass that does not support arithmetic operations'''
+    pass
+
+
+def test_cooperative_operations():
+    '''Tests that Expr uses binary operations cooperatively.
+
+    In particular it should be possible for non-Expr classes to override
+    binary operators like +, - etc when used with Expr instances. This should
+    work for non-Expr classes whether they are Basic subclasses or not. Also
+    non-Expr classes that do not define binary operators with Expr should give
+    TypeError.
+    '''
+    # A bunch of instances of Expr subclasses
+    exprs = [
+        Expr(),
+        S.Zero,
+        S.One,
+        S.Infinity,
+        S.NegativeInfinity,
+        S.ComplexInfinity,
+        S.Half,
+        Float(0.5),
+        Integer(2),
+        Symbol('x'),
+        Mul(2, Symbol('x')),
+        Add(2, Symbol('x')),
+        Pow(2, Symbol('x')),
+    ]
+
+    for e in exprs:
+        # Test that these classes can override arithmetic operations in
+        # combination with various Expr types.
+        for ne in [NonBasic(), NonExpr()]:
+
+            results = [
+                (ne + e, ('+', ne, e)),
+                (e + ne, ('+', e, ne)),
+                (ne - e, ('-', ne, e)),
+                (e - ne, ('-', e, ne)),
+                (ne * e, ('*', ne, e)),
+                (e * ne, ('*', e, ne)),
+                (ne / e, ('/', ne, e)),
+                (e / ne, ('/', e, ne)),
+                (ne // e, ('//', ne, e)),
+                (e // ne, ('//', e, ne)),
+                (ne % e, ('%', ne, e)),
+                (e % ne, ('%', e, ne)),
+                (divmod(ne, e), ('divmod', ne, e)),
+                (divmod(e, ne), ('divmod', e, ne)),
+                (ne ** e, ('**', ne, e)),
+                (e ** ne, ('**', e, ne)),
+                (e < ne, ('>', ne, e)),
+                (ne < e, ('<', ne, e)),
+                (e > ne, ('<', ne, e)),
+                (ne > e, ('>', ne, e)),
+                (e <= ne, ('>=', ne, e)),
+                (ne <= e, ('<=', ne, e)),
+                (e >= ne, ('<=', ne, e)),
+                (ne >= e, ('>=', ne, e)),
+            ]
+
+            for res, args in results:
+                assert type(res) is SpecialOp and res.args == args
+
+        # These classes do not support binary operators with Expr. Every
+        # operation should raise in combination with any of the Expr types.
+        for na in [NonArithmetic(), object()]:
+
+            raises(TypeError, lambda : e + na)
+            raises(TypeError, lambda : na + e)
+            raises(TypeError, lambda : e - na)
+            raises(TypeError, lambda : na - e)
+            raises(TypeError, lambda : e * na)
+            raises(TypeError, lambda : na * e)
+            raises(TypeError, lambda : e / na)
+            raises(TypeError, lambda : na / e)
+            raises(TypeError, lambda : e // na)
+            raises(TypeError, lambda : na // e)
+            raises(TypeError, lambda : e % na)
+            raises(TypeError, lambda : na % e)
+            raises(TypeError, lambda : divmod(e, na))
+            raises(TypeError, lambda : divmod(na, e))
+            raises(TypeError, lambda : e ** na)
+            raises(TypeError, lambda : na ** e)
+            raises(TypeError, lambda : e > na)
+            raises(TypeError, lambda : na > e)
+            raises(TypeError, lambda : e < na)
+            raises(TypeError, lambda : na < e)
+            raises(TypeError, lambda : e >= na)
+            raises(TypeError, lambda : na >= e)
+            raises(TypeError, lambda : e <= na)
+            raises(TypeError, lambda : na <= e)
+
+
+def test_relational():
+    from sympy.core.relational import Lt
+    assert (pi < 3) is S.false
+    assert (pi <= 3) is S.false
+    assert (pi > 3) is S.true
+    assert (pi >= 3) is S.true
+    assert (-pi < 3) is S.true
+    assert (-pi <= 3) is S.true
+    assert (-pi > 3) is S.false
+    assert (-pi >= 3) is S.false
+    r = Symbol('r', real=True)
+    assert (r - 2 < r - 3) is S.false
+    assert Lt(x + I, x + I + 2).func == Lt  # issue 8288
+
+
+def test_relational_assumptions():
+    m1 = Symbol("m1", nonnegative=False)
+    m2 = Symbol("m2", positive=False)
+    m3 = Symbol("m3", nonpositive=False)
+    m4 = Symbol("m4", negative=False)
+    assert (m1 < 0) == Lt(m1, 0)
+    assert (m2 <= 0) == Le(m2, 0)
+    assert (m3 > 0) == Gt(m3, 0)
+    assert (m4 >= 0) == Ge(m4, 0)
+    m1 = Symbol("m1", nonnegative=False, real=True)
+    m2 = Symbol("m2", positive=False, real=True)
+    m3 = Symbol("m3", nonpositive=False, real=True)
+    m4 = Symbol("m4", negative=False, real=True)
+    assert (m1 < 0) is S.true
+    assert (m2 <= 0) is S.true
+    assert (m3 > 0) is S.true
+    assert (m4 >= 0) is S.true
+    m1 = Symbol("m1", negative=True)
+    m2 = Symbol("m2", nonpositive=True)
+    m3 = Symbol("m3", positive=True)
+    m4 = Symbol("m4", nonnegative=True)
+    assert (m1 < 0) is S.true
+    assert (m2 <= 0) is S.true
+    assert (m3 > 0) is S.true
+    assert (m4 >= 0) is S.true
+    m1 = Symbol("m1", negative=False, real=True)
+    m2 = Symbol("m2", nonpositive=False, real=True)
+    m3 = Symbol("m3", positive=False, real=True)
+    m4 = Symbol("m4", nonnegative=False, real=True)
+    assert (m1 < 0) is S.false
+    assert (m2 <= 0) is S.false
+    assert (m3 > 0) is S.false
+    assert (m4 >= 0) is S.false
+
+
+# See https://github.com/sympy/sympy/issues/17708
+#def test_relational_noncommutative():
+#    from sympy import Lt, Gt, Le, Ge
+#    A, B = symbols('A,B', commutative=False)
+#    assert (A < B) == Lt(A, B)
+#    assert (A <= B) == Le(A, B)
+#    assert (A > B) == Gt(A, B)
+#    assert (A >= B) == Ge(A, B)
+
+
+def test_basic_nostr():
+    for obj in basic_objs:
+        raises(TypeError, lambda: obj + '1')
+        raises(TypeError, lambda: obj - '1')
+        if obj == 2:
+            assert obj * '1' == '11'
+        else:
+            raises(TypeError, lambda: obj * '1')
+        raises(TypeError, lambda: obj / '1')
+        raises(TypeError, lambda: obj ** '1')
+
+
+def test_series_expansion_for_uniform_order():
+    assert (1/x + y + x).series(x, 0, 0) == 1/x + O(1, x)
+    assert (1/x + y + x).series(x, 0, 1) == 1/x + y + O(x)
+    assert (1/x + 1 + x).series(x, 0, 0) == 1/x + O(1, x)
+    assert (1/x + 1 + x).series(x, 0, 1) == 1/x + 1 + O(x)
+    assert (1/x + x).series(x, 0, 0) == 1/x + O(1, x)
+    assert (1/x + y + y*x + x).series(x, 0, 0) == 1/x + O(1, x)
+    assert (1/x + y + y*x + x).series(x, 0, 1) == 1/x + y + O(x)
+
+
+def test_leadterm():
+    assert (3 + 2*x**(log(3)/log(2) - 1)).leadterm(x) == (3, 0)
+
+    assert (1/x**2 + 1 + x + x**2).leadterm(x)[1] == -2
+    assert (1/x + 1 + x + x**2).leadterm(x)[1] == -1
+    assert (x**2 + 1/x).leadterm(x)[1] == -1
+    assert (1 + x**2).leadterm(x)[1] == 0
+    assert (x + 1).leadterm(x)[1] == 0
+    assert (x + x**2).leadterm(x)[1] == 1
+    assert (x**2).leadterm(x)[1] == 2
+
+
+def test_as_leading_term():
+    assert (3 + 2*x**(log(3)/log(2) - 1)).as_leading_term(x) == 3
+    assert (1/x**2 + 1 + x + x**2).as_leading_term(x) == 1/x**2
+    assert (1/x + 1 + x + x**2).as_leading_term(x) == 1/x
+    assert (x**2 + 1/x).as_leading_term(x) == 1/x
+    assert (1 + x**2).as_leading_term(x) == 1
+    assert (x + 1).as_leading_term(x) == 1
+    assert (x + x**2).as_leading_term(x) == x
+    assert (x**2).as_leading_term(x) == x**2
+    assert (x + oo).as_leading_term(x) is oo
+
+    raises(ValueError, lambda: (x + 1).as_leading_term(1))
+
+    # https://github.com/sympy/sympy/issues/21177
+    e = -3*x + (x + Rational(3, 2) - sqrt(3)*S.ImaginaryUnit/2)**2\
+        - Rational(3, 2) + 3*sqrt(3)*S.ImaginaryUnit/2
+    assert e.as_leading_term(x) == \
+        (12*sqrt(3)*x - 12*S.ImaginaryUnit*x)/(4*sqrt(3) + 12*S.ImaginaryUnit)
+
+    # https://github.com/sympy/sympy/issues/21245
+    e = 1 - x - x**2
+    d = (1 + sqrt(5))/2
+    assert e.subs(x, y + 1/d).as_leading_term(y) == \
+        (-576*sqrt(5)*y - 1280*y)/(256*sqrt(5) + 576)
+
+
+def test_leadterm2():
+    assert (x*cos(1)*cos(1 + sin(1)) + sin(1 + sin(1))).leadterm(x) == \
+           (sin(1 + sin(1)), 0)
+
+
+def test_leadterm3():
+    assert (y + z + x).leadterm(x) == (y + z, 0)
+
+
+def test_as_leading_term2():
+    assert (x*cos(1)*cos(1 + sin(1)) + sin(1 + sin(1))).as_leading_term(x) == \
+        sin(1 + sin(1))
+
+
+def test_as_leading_term3():
+    assert (2 + pi + x).as_leading_term(x) == 2 + pi
+    assert (2*x + pi*x + x**2).as_leading_term(x) == 2*x + pi*x
+
+
+def test_as_leading_term4():
+    # see issue 6843
+    n = Symbol('n', integer=True, positive=True)
+    r = -n**3/(2*n**2 + 4*n + 2) - n**2/(n**2 + 2*n + 1) + \
+        n**2/(n + 1) - n/(2*n**2 + 4*n + 2) + n/(n*x + x) + 2*n/(n + 1) - \
+        1 + 1/(n*x + x) + 1/(n + 1) - 1/x
+    assert r.as_leading_term(x).cancel() == n/2
+
+
+def test_as_leading_term_stub():
+    class foo(Function):
+        pass
+    assert foo(1/x).as_leading_term(x) == foo(1/x)
+    assert foo(1).as_leading_term(x) == foo(1)
+    raises(NotImplementedError, lambda: foo(x).as_leading_term(x))
+
+
+def test_as_leading_term_deriv_integral():
+    # related to issue 11313
+    assert Derivative(x ** 3, x).as_leading_term(x) == 3*x**2
+    assert Derivative(x ** 3, y).as_leading_term(x) == 0
+
+    assert Integral(x ** 3, x).as_leading_term(x) == x**4/4
+    assert Integral(x ** 3, y).as_leading_term(x) == y*x**3
+
+    assert Derivative(exp(x), x).as_leading_term(x) == 1
+    assert Derivative(log(x), x).as_leading_term(x) == (1/x).as_leading_term(x)
+
+
+def test_atoms():
+    assert x.atoms() == {x}
+    assert (1 + x).atoms() == {x, S.One}
+
+    assert (1 + 2*cos(x)).atoms(Symbol) == {x}
+    assert (1 + 2*cos(x)).atoms(Symbol, Number) == {S.One, S(2), x}
+
+    assert (2*(x**(y**x))).atoms() == {S(2), x, y}
+
+    assert S.Half.atoms() == {S.Half}
+    assert S.Half.atoms(Symbol) == set()
+
+    assert sin(oo).atoms(oo) == set()
+
+    assert Poly(0, x).atoms() == {S.Zero, x}
+    assert Poly(1, x).atoms() == {S.One, x}
+
+    assert Poly(x, x).atoms() == {x}
+    assert Poly(x, x, y).atoms() == {x, y}
+    assert Poly(x + y, x, y).atoms() == {x, y}
+    assert Poly(x + y, x, y, z).atoms() == {x, y, z}
+    assert Poly(x + y*t, x, y, z).atoms() == {t, x, y, z}
+
+    assert (I*pi).atoms(NumberSymbol) == {pi}
+    assert (I*pi).atoms(NumberSymbol, I) == \
+        (I*pi).atoms(I, NumberSymbol) == {pi, I}
+
+    assert exp(exp(x)).atoms(exp) == {exp(exp(x)), exp(x)}
+    assert (1 + x*(2 + y) + exp(3 + z)).atoms(Add) == \
+        {1 + x*(2 + y) + exp(3 + z), 2 + y, 3 + z}
+
+    # issue 6132
+    e = (f(x) + sin(x) + 2)
+    assert e.atoms(AppliedUndef) == \
+        {f(x)}
+    assert e.atoms(AppliedUndef, Function) == \
+        {f(x), sin(x)}
+    assert e.atoms(Function) == \
+        {f(x), sin(x)}
+    assert e.atoms(AppliedUndef, Number) == \
+        {f(x), S(2)}
+    assert e.atoms(Function, Number) == \
+        {S(2), sin(x), f(x)}
+
+
+def test_is_polynomial():
+    k = Symbol('k', nonnegative=True, integer=True)
+
+    assert Rational(2).is_polynomial(x, y, z) is True
+    assert (S.Pi).is_polynomial(x, y, z) is True
+
+    assert x.is_polynomial(x) is True
+    assert x.is_polynomial(y) is True
+
+    assert (x**2).is_polynomial(x) is True
+    assert (x**2).is_polynomial(y) is True
+
+    assert (x**(-2)).is_polynomial(x) is False
+    assert (x**(-2)).is_polynomial(y) is True
+
+    assert (2**x).is_polynomial(x) is False
+    assert (2**x).is_polynomial(y) is True
+
+    assert (x**k).is_polynomial(x) is False
+    assert (x**k).is_polynomial(k) is False
+    assert (x**x).is_polynomial(x) is False
+    assert (k**k).is_polynomial(k) is False
+    assert (k**x).is_polynomial(k) is False
+
+    assert (x**(-k)).is_polynomial(x) is False
+    assert ((2*x)**k).is_polynomial(x) is False
+
+    assert (x**2 + 3*x - 8).is_polynomial(x) is True
+    assert (x**2 + 3*x - 8).is_polynomial(y) is True
+
+    assert (x**2 + 3*x - 8).is_polynomial() is True
+
+    assert sqrt(x).is_polynomial(x) is False
+    assert (sqrt(x)**3).is_polynomial(x) is False
+
+    assert (x**2 + 3*x*sqrt(y) - 8).is_polynomial(x) is True
+    assert (x**2 + 3*x*sqrt(y) - 8).is_polynomial(y) is False
+
+    assert ((x**2)*(y**2) + x*(y**2) + y*x + exp(2)).is_polynomial() is True
+    assert ((x**2)*(y**2) + x*(y**2) + y*x + exp(x)).is_polynomial() is False
+
+    assert (
+        (x**2)*(y**2) + x*(y**2) + y*x + exp(2)).is_polynomial(x, y) is True
+    assert (
+        (x**2)*(y**2) + x*(y**2) + y*x + exp(x)).is_polynomial(x, y) is False
+
+    assert (1/f(x) + 1).is_polynomial(f(x)) is False
+
+
+def test_is_rational_function():
+    assert Integer(1).is_rational_function() is True
+    assert Integer(1).is_rational_function(x) is True
+
+    assert Rational(17, 54).is_rational_function() is True
+    assert Rational(17, 54).is_rational_function(x) is True
+
+    assert (12/x).is_rational_function() is True
+    assert (12/x).is_rational_function(x) is True
+
+    assert (x/y).is_rational_function() is True
+    assert (x/y).is_rational_function(x) is True
+    assert (x/y).is_rational_function(x, y) is True
+
+    assert (x**2 + 1/x/y).is_rational_function() is True
+    assert (x**2 + 1/x/y).is_rational_function(x) is True
+    assert (x**2 + 1/x/y).is_rational_function(x, y) is True
+
+    assert (sin(y)/x).is_rational_function() is False
+    assert (sin(y)/x).is_rational_function(y) is False
+    assert (sin(y)/x).is_rational_function(x) is True
+    assert (sin(y)/x).is_rational_function(x, y) is False
+
+    for i in _illegal:
+        assert not i.is_rational_function()
+        for d in (1, x):
+            assert not (i/d).is_rational_function()
+
+
+def test_is_meromorphic():
+    f = a/x**2 + b + x + c*x**2
+    assert f.is_meromorphic(x, 0) is True
+    assert f.is_meromorphic(x, 1) is True
+    assert f.is_meromorphic(x, zoo) is True
+
+    g = 3 + 2*x**(log(3)/log(2) - 1)
+    assert g.is_meromorphic(x, 0) is False
+    assert g.is_meromorphic(x, 1) is True
+    assert g.is_meromorphic(x, zoo) is False
+
+    n = Symbol('n', integer=True)
+    e = sin(1/x)**n*x
+    assert e.is_meromorphic(x, 0) is False
+    assert e.is_meromorphic(x, 1) is True
+    assert e.is_meromorphic(x, zoo) is False
+
+    e = log(x)**pi
+    assert e.is_meromorphic(x, 0) is False
+    assert e.is_meromorphic(x, 1) is False
+    assert e.is_meromorphic(x, 2) is True
+    assert e.is_meromorphic(x, zoo) is False
+
+    assert (log(x)**a).is_meromorphic(x, 0) is False
+    assert (log(x)**a).is_meromorphic(x, 1) is False
+    assert (a**log(x)).is_meromorphic(x, 0) is None
+    assert (3**log(x)).is_meromorphic(x, 0) is False
+    assert (3**log(x)).is_meromorphic(x, 1) is True
+
+def test_is_algebraic_expr():
+    assert sqrt(3).is_algebraic_expr(x) is True
+    assert sqrt(3).is_algebraic_expr() is True
+
+    eq = ((1 + x**2)/(1 - y**2))**(S.One/3)
+    assert eq.is_algebraic_expr(x) is True
+    assert eq.is_algebraic_expr(y) is True
+
+    assert (sqrt(x) + y**(S(2)/3)).is_algebraic_expr(x) is True
+    assert (sqrt(x) + y**(S(2)/3)).is_algebraic_expr(y) is True
+    assert (sqrt(x) + y**(S(2)/3)).is_algebraic_expr() is True
+
+    assert (cos(y)/sqrt(x)).is_algebraic_expr() is False
+    assert (cos(y)/sqrt(x)).is_algebraic_expr(x) is True
+    assert (cos(y)/sqrt(x)).is_algebraic_expr(y) is False
+    assert (cos(y)/sqrt(x)).is_algebraic_expr(x, y) is False
+
+
+def test_SAGE1():
+    #see https://github.com/sympy/sympy/issues/3346
+    class MyInt:
+        def _sympy_(self):
+            return Integer(5)
+    m = MyInt()
+    e = Rational(2)*m
+    assert e == 10
+
+    raises(TypeError, lambda: Rational(2)*MyInt)
+
+
+def test_SAGE2():
+    class MyInt:
+        def __int__(self):
+            return 5
+    assert sympify(MyInt()) == 5
+    e = Rational(2)*MyInt()
+    assert e == 10
+
+    raises(TypeError, lambda: Rational(2)*MyInt)
+
+
+def test_SAGE3():
+    class MySymbol:
+        def __rmul__(self, other):
+            return ('mys', other, self)
+
+    o = MySymbol()
+    e = x*o
+
+    assert e == ('mys', x, o)
+
+
+def test_len():
+    e = x*y
+    assert len(e.args) == 2
+    e = x + y + z
+    assert len(e.args) == 3
+
+
+def test_doit():
+    a = Integral(x**2, x)
+
+    assert isinstance(a.doit(), Integral) is False
+
+    assert isinstance(a.doit(integrals=True), Integral) is False
+    assert isinstance(a.doit(integrals=False), Integral) is True
+
+    assert (2*Integral(x, x)).doit() == x**2
+
+
+def test_attribute_error():
+    raises(AttributeError, lambda: x.cos())
+    raises(AttributeError, lambda: x.sin())
+    raises(AttributeError, lambda: x.exp())
+
+
+def test_args():
+    assert (x*y).args in ((x, y), (y, x))
+    assert (x + y).args in ((x, y), (y, x))
+    assert (x*y + 1).args in ((x*y, 1), (1, x*y))
+    assert sin(x*y).args == (x*y,)
+    assert sin(x*y).args[0] == x*y
+    assert (x**y).args == (x, y)
+    assert (x**y).args[0] == x
+    assert (x**y).args[1] == y
+
+
+def test_noncommutative_expand_issue_3757():
+    A, B, C = symbols('A,B,C', commutative=False)
+    assert A*B - B*A != 0
+    assert (A*(A + B)*B).expand() == A**2*B + A*B**2
+    assert (A*(A + B + C)*B).expand() == A**2*B + A*B**2 + A*C*B
+
+
+def test_as_numer_denom():
+    a, b, c = symbols('a, b, c')
+
+    assert nan.as_numer_denom() == (nan, 1)
+    assert oo.as_numer_denom() == (oo, 1)
+    assert (-oo).as_numer_denom() == (-oo, 1)
+    assert zoo.as_numer_denom() == (zoo, 1)
+    assert (-zoo).as_numer_denom() == (zoo, 1)
+
+    assert x.as_numer_denom() == (x, 1)
+    assert (1/x).as_numer_denom() == (1, x)
+    assert (x/y).as_numer_denom() == (x, y)
+    assert (x/2).as_numer_denom() == (x, 2)
+    assert (x*y/z).as_numer_denom() == (x*y, z)
+    assert (x/(y*z)).as_numer_denom() == (x, y*z)
+    assert S.Half.as_numer_denom() == (1, 2)
+    assert (1/y**2).as_numer_denom() == (1, y**2)
+    assert (x/y**2).as_numer_denom() == (x, y**2)
+    assert ((x**2 + 1)/y).as_numer_denom() == (x**2 + 1, y)
+    assert (x*(y + 1)/y**7).as_numer_denom() == (x*(y + 1), y**7)
+    assert (x**-2).as_numer_denom() == (1, x**2)
+    assert (a/x + b/2/x + c/3/x).as_numer_denom() == \
+        (6*a + 3*b + 2*c, 6*x)
+    assert (a/x + b/2/x + c/3/y).as_numer_denom() == \
+        (2*c*x + y*(6*a + 3*b), 6*x*y)
+    assert (a/x + b/2/x + c/.5/x).as_numer_denom() == \
+        (2*a + b + 4.0*c, 2*x)
+    # this should take no more than a few seconds
+    assert int(log(Add(*[Dummy()/i/x for i in range(1, 705)]
+                       ).as_numer_denom()[1]/x).n(4)) == 705
+    for i in [S.Infinity, S.NegativeInfinity, S.ComplexInfinity]:
+        assert (i + x/3).as_numer_denom() == \
+            (x + i, 3)
+    assert (S.Infinity + x/3 + y/4).as_numer_denom() == \
+        (4*x + 3*y + S.Infinity, 12)
+    assert (oo*x + zoo*y).as_numer_denom() == \
+        (zoo*y + oo*x, 1)
+
+    A, B, C = symbols('A,B,C', commutative=False)
+
+    assert (A*B*C**-1).as_numer_denom() == (A*B*C**-1, 1)
+    assert (A*B*C**-1/x).as_numer_denom() == (A*B*C**-1, x)
+    assert (C**-1*A*B).as_numer_denom() == (C**-1*A*B, 1)
+    assert (C**-1*A*B/x).as_numer_denom() == (C**-1*A*B, x)
+    assert ((A*B*C)**-1).as_numer_denom() == ((A*B*C)**-1, 1)
+    assert ((A*B*C)**-1/x).as_numer_denom() == ((A*B*C)**-1, x)
+
+    # the following morphs from Add to Mul during processing
+    assert Add(0, (x + y)/z/-2, evaluate=False).as_numer_denom(
+        ) == (-x - y, 2*z)
+
+
+def test_trunc():
+    import math
+    x, y = symbols('x y')
+    assert math.trunc(2) == 2
+    assert math.trunc(4.57) == 4
+    assert math.trunc(-5.79) == -5
+    assert math.trunc(pi) == 3
+    assert math.trunc(log(7)) == 1
+    assert math.trunc(exp(5)) == 148
+    assert math.trunc(cos(pi)) == -1
+    assert math.trunc(sin(5)) == 0
+
+    raises(TypeError, lambda: math.trunc(x))
+    raises(TypeError, lambda: math.trunc(x + y**2))
+    raises(TypeError, lambda: math.trunc(oo))
+
+
+def test_as_independent():
+    assert S.Zero.as_independent(x, as_Add=True) == (0, 0)
+    assert S.Zero.as_independent(x, as_Add=False) == (0, 0)
+    assert (2*x*sin(x) + y + x).as_independent(x) == (y, x + 2*x*sin(x))
+    assert (2*x*sin(x) + y + x).as_independent(y) == (x + 2*x*sin(x), y)
+
+    assert (2*x*sin(x) + y + x).as_independent(x, y) == (0, y + x + 2*x*sin(x))
+
+    assert (x*sin(x)*cos(y)).as_independent(x) == (cos(y), x*sin(x))
+    assert (x*sin(x)*cos(y)).as_independent(y) == (x*sin(x), cos(y))
+
+    assert (x*sin(x)*cos(y)).as_independent(x, y) == (1, x*sin(x)*cos(y))
+
+    assert (sin(x)).as_independent(x) == (1, sin(x))
+    assert (sin(x)).as_independent(y) == (sin(x), 1)
+
+    assert (2*sin(x)).as_independent(x) == (2, sin(x))
+    assert (2*sin(x)).as_independent(y) == (2*sin(x), 1)
+
+    # issue 4903 = 1766b
+    n1, n2, n3 = symbols('n1 n2 n3', commutative=False)
+    assert (n1 + n1*n2).as_independent(n2) == (n1, n1*n2)
+    assert (n2*n1 + n1*n2).as_independent(n2) == (0, n1*n2 + n2*n1)
+    assert (n1*n2*n1).as_independent(n2) == (n1, n2*n1)
+    assert (n1*n2*n1).as_independent(n1) == (1, n1*n2*n1)
+
+    assert (3*x).as_independent(x, as_Add=True) == (0, 3*x)
+    assert (3*x).as_independent(x, as_Add=False) == (3, x)
+    assert (3 + x).as_independent(x, as_Add=True) == (3, x)
+    assert (3 + x).as_independent(x, as_Add=False) == (1, 3 + x)
+
+    # issue 5479
+    assert (3*x).as_independent(Symbol) == (3, x)
+
+    # issue 5648
+    assert (n1*x*y).as_independent(x) == (n1*y, x)
+    assert ((x + n1)*(x - y)).as_independent(x) == (1, (x + n1)*(x - y))
+    assert ((x + n1)*(x - y)).as_independent(y) == (x + n1, x - y)
+    assert (DiracDelta(x - n1)*DiracDelta(x - y)).as_independent(x) \
+        == (1, DiracDelta(x - n1)*DiracDelta(x - y))
+    assert (x*y*n1*n2*n3).as_independent(n2) == (x*y*n1, n2*n3)
+    assert (x*y*n1*n2*n3).as_independent(n1) == (x*y, n1*n2*n3)
+    assert (x*y*n1*n2*n3).as_independent(n3) == (x*y*n1*n2, n3)
+    assert (DiracDelta(x - n1)*DiracDelta(y - n1)*DiracDelta(x - n2)).as_independent(y) == \
+           (DiracDelta(x - n1)*DiracDelta(x - n2), DiracDelta(y - n1))
+
+    # issue 5784
+    assert (x + Integral(x, (x, 1, 2))).as_independent(x, strict=True) == \
+           (Integral(x, (x, 1, 2)), x)
+
+    eq = Add(x, -x, 2, -3, evaluate=False)
+    assert eq.as_independent(x) == (-1, Add(x, -x, evaluate=False))
+    eq = Mul(x, 1/x, 2, -3, evaluate=False)
+    assert eq.as_independent(x) == (-6, Mul(x, 1/x, evaluate=False))
+
+    assert (x*y).as_independent(z, as_Add=True) == (x*y, 0)
+
+@XFAIL
+def test_call_2():
+    # TODO UndefinedFunction does not subclass Expr
+    assert (2*f)(x) == 2*f(x)
+
+
+def test_replace():
+    e = log(sin(x)) + tan(sin(x**2))
+
+    assert e.replace(sin, cos) == log(cos(x)) + tan(cos(x**2))
+    assert e.replace(
+        sin, lambda a: sin(2*a)) == log(sin(2*x)) + tan(sin(2*x**2))
+
+    a = Wild('a')
+    b = Wild('b')
+
+    assert e.replace(sin(a), cos(a)) == log(cos(x)) + tan(cos(x**2))
+    assert e.replace(
+        sin(a), lambda a: sin(2*a)) == log(sin(2*x)) + tan(sin(2*x**2))
+    # test exact
+    assert (2*x).replace(a*x + b, b - a, exact=True) == 2*x
+    assert (2*x).replace(a*x + b, b - a) == 2*x
+    assert (2*x).replace(a*x + b, b - a, exact=False) == 2/x
+    assert (2*x).replace(a*x + b, lambda a, b: b - a, exact=True) == 2*x
+    assert (2*x).replace(a*x + b, lambda a, b: b - a) == 2*x
+    assert (2*x).replace(a*x + b, lambda a, b: b - a, exact=False) == 2/x
+
+    g = 2*sin(x**3)
+
+    assert g.replace(
+        lambda expr: expr.is_Number, lambda expr: expr**2) == 4*sin(x**9)
+
+    assert cos(x).replace(cos, sin, map=True) == (sin(x), {cos(x): sin(x)})
+    assert sin(x).replace(cos, sin) == sin(x)
+
+    cond, func = lambda x: x.is_Mul, lambda x: 2*x
+    assert (x*y).replace(cond, func, map=True) == (2*x*y, {x*y: 2*x*y})
+    assert (x*(1 + x*y)).replace(cond, func, map=True) == \
+        (2*x*(2*x*y + 1), {x*(2*x*y + 1): 2*x*(2*x*y + 1), x*y: 2*x*y})
+    assert (y*sin(x)).replace(sin, lambda expr: sin(expr)/y, map=True) == \
+        (sin(x), {sin(x): sin(x)/y})
+    # if not simultaneous then y*sin(x) -> y*sin(x)/y = sin(x) -> sin(x)/y
+    assert (y*sin(x)).replace(sin, lambda expr: sin(expr)/y,
+        simultaneous=False) == sin(x)/y
+    assert (x**2 + O(x**3)).replace(Pow, lambda b, e: b**e/e
+        ) == x**2/2 + O(x**3)
+    assert (x**2 + O(x**3)).replace(Pow, lambda b, e: b**e/e,
+        simultaneous=False) == x**2/2 + O(x**3)
+    assert (x*(x*y + 3)).replace(lambda x: x.is_Mul, lambda x: 2 + x) == \
+        x*(x*y + 5) + 2
+    e = (x*y + 1)*(2*x*y + 1) + 1
+    assert e.replace(cond, func, map=True) == (
+        2*((2*x*y + 1)*(4*x*y + 1)) + 1,
+        {2*x*y: 4*x*y, x*y: 2*x*y, (2*x*y + 1)*(4*x*y + 1):
+        2*((2*x*y + 1)*(4*x*y + 1))})
+    assert x.replace(x, y) == y
+    assert (x + 1).replace(1, 2) == x + 2
+
+    # https://groups.google.com/forum/#!topic/sympy/8wCgeC95tz0
+    n1, n2, n3 = symbols('n1:4', commutative=False)
+    assert (n1*f(n2)).replace(f, lambda x: x) == n1*n2
+    assert (n3*f(n2)).replace(f, lambda x: x) == n3*n2
+
+    # issue 16725
+    assert S.Zero.replace(Wild('x'), 1) == 1
+    # let the user override the default decision of False
+    assert S.Zero.replace(Wild('x'), 1, exact=True) == 0
+
+
+def test_find():
+    expr = (x + y + 2 + sin(3*x))
+
+    assert expr.find(lambda u: u.is_Integer) == {S(2), S(3)}
+    assert expr.find(lambda u: u.is_Symbol) == {x, y}
+
+    assert expr.find(lambda u: u.is_Integer, group=True) == {S(2): 1, S(3): 1}
+    assert expr.find(lambda u: u.is_Symbol, group=True) == {x: 2, y: 1}
+
+    assert expr.find(Integer) == {S(2), S(3)}
+    assert expr.find(Symbol) == {x, y}
+
+    assert expr.find(Integer, group=True) == {S(2): 1, S(3): 1}
+    assert expr.find(Symbol, group=True) == {x: 2, y: 1}
+
+    a = Wild('a')
+
+    expr = sin(sin(x)) + sin(x) + cos(x) + x
+
+    assert expr.find(lambda u: type(u) is sin) == {sin(x), sin(sin(x))}
+    assert expr.find(
+        lambda u: type(u) is sin, group=True) == {sin(x): 2, sin(sin(x)): 1}
+
+    assert expr.find(sin(a)) == {sin(x), sin(sin(x))}
+    assert expr.find(sin(a), group=True) == {sin(x): 2, sin(sin(x)): 1}
+
+    assert expr.find(sin) == {sin(x), sin(sin(x))}
+    assert expr.find(sin, group=True) == {sin(x): 2, sin(sin(x)): 1}
+
+
+def test_count():
+    expr = (x + y + 2 + sin(3*x))
+
+    assert expr.count(lambda u: u.is_Integer) == 2
+    assert expr.count(lambda u: u.is_Symbol) == 3
+
+    assert expr.count(Integer) == 2
+    assert expr.count(Symbol) == 3
+    assert expr.count(2) == 1
+
+    a = Wild('a')
+
+    assert expr.count(sin) == 1
+    assert expr.count(sin(a)) == 1
+    assert expr.count(lambda u: type(u) is sin) == 1
+
+    assert f(x).count(f(x)) == 1
+    assert f(x).diff(x).count(f(x)) == 1
+    assert f(x).diff(x).count(x) == 2
+
+
+def test_has_basics():
+    p = Wild('p')
+
+    assert sin(x).has(x)
+    assert sin(x).has(sin)
+    assert not sin(x).has(y)
+    assert not sin(x).has(cos)
+    assert f(x).has(x)
+    assert f(x).has(f)
+    assert not f(x).has(y)
+    assert not f(x).has(g)
+
+    assert f(x).diff(x).has(x)
+    assert f(x).diff(x).has(f)
+    assert f(x).diff(x).has(Derivative)
+    assert not f(x).diff(x).has(y)
+    assert not f(x).diff(x).has(g)
+    assert not f(x).diff(x).has(sin)
+
+    assert (x**2).has(Symbol)
+    assert not (x**2).has(Wild)
+    assert (2*p).has(Wild)
+
+    assert not x.has()
+
+
+def test_has_multiple():
+    f = x**2*y + sin(2**t + log(z))
+
+    assert f.has(x)
+    assert f.has(y)
+    assert f.has(z)
+    assert f.has(t)
+
+    assert not f.has(u)
+
+    assert f.has(x, y, z, t)
+    assert f.has(x, y, z, t, u)
+
+    i = Integer(4400)
+
+    assert not i.has(x)
+
+    assert (i*x**i).has(x)
+    assert not (i*y**i).has(x)
+    assert (i*y**i).has(x, y)
+    assert not (i*y**i).has(x, z)
+
+
+def test_has_piecewise():
+    f = (x*y + 3/y)**(3 + 2)
+    p = Piecewise((g(x), x < -1), (1, x <= 1), (f, True))
+
+    assert p.has(x)
+    assert p.has(y)
+    assert not p.has(z)
+    assert p.has(1)
+    assert p.has(3)
+    assert not p.has(4)
+    assert p.has(f)
+    assert p.has(g)
+    assert not p.has(h)
+
+
+def test_has_iterative():
+    A, B, C = symbols('A,B,C', commutative=False)
+    f = x*gamma(x)*sin(x)*exp(x*y)*A*B*C*cos(x*A*B)
+
+    assert f.has(x)
+    assert f.has(x*y)
+    assert f.has(x*sin(x))
+    assert not f.has(x*sin(y))
+    assert f.has(x*A)
+    assert f.has(x*A*B)
+    assert not f.has(x*A*C)
+    assert f.has(x*A*B*C)
+    assert not f.has(x*A*C*B)
+    assert f.has(x*sin(x)*A*B*C)
+    assert not f.has(x*sin(x)*A*C*B)
+    assert not f.has(x*sin(y)*A*B*C)
+    assert f.has(x*gamma(x))
+    assert not f.has(x + sin(x))
+
+    assert (x & y & z).has(x & z)
+
+
+def test_has_integrals():
+    f = Integral(x**2 + sin(x*y*z), (x, 0, x + y + z))
+
+    assert f.has(x + y)
+    assert f.has(x + z)
+    assert f.has(y + z)
+
+    assert f.has(x*y)
+    assert f.has(x*z)
+    assert f.has(y*z)
+
+    assert not f.has(2*x + y)
+    assert not f.has(2*x*y)
+
+
+def test_has_tuple():
+    assert Tuple(x, y).has(x)
+    assert not Tuple(x, y).has(z)
+    assert Tuple(f(x), g(x)).has(x)
+    assert not Tuple(f(x), g(x)).has(y)
+    assert Tuple(f(x), g(x)).has(f)
+    assert Tuple(f(x), g(x)).has(f(x))
+    # XXX to be deprecated
+    #assert not Tuple(f, g).has(x)
+    #assert Tuple(f, g).has(f)
+    #assert not Tuple(f, g).has(h)
+    assert Tuple(True).has(True)
+    assert Tuple(True).has(S.true)
+    assert not Tuple(True).has(1)
+
+
+def test_has_units():
+    from sympy.physics.units import m, s
+
+    assert (x*m/s).has(x)
+    assert (x*m/s).has(y, z) is False
+
+
+def test_has_polys():
+    poly = Poly(x**2 + x*y*sin(z), x, y, t)
+
+    assert poly.has(x)
+    assert poly.has(x, y, z)
+    assert poly.has(x, y, z, t)
+
+
+def test_has_physics():
+    assert FockState((x, y)).has(x)
+
+
+def test_as_poly_as_expr():
+    f = x**2 + 2*x*y
+
+    assert f.as_poly().as_expr() == f
+    assert f.as_poly(x, y).as_expr() == f
+
+    assert (f + sin(x)).as_poly(x, y) is None
+
+    p = Poly(f, x, y)
+
+    assert p.as_poly() == p
+
+    # https://github.com/sympy/sympy/issues/20610
+    assert S(2).as_poly() is None
+    assert sqrt(2).as_poly(extension=True) is None
+
+    raises(AttributeError, lambda: Tuple(x, x).as_poly(x))
+    raises(AttributeError, lambda: Tuple(x ** 2, x, y).as_poly(x))
+
+
+def test_nonzero():
+    assert bool(S.Zero) is False
+    assert bool(S.One) is True
+    assert bool(x) is True
+    assert bool(x + y) is True
+    assert bool(x - x) is False
+    assert bool(x*y) is True
+    assert bool(x*1) is True
+    assert bool(x*0) is False
+
+
+def test_is_number():
+    assert Float(3.14).is_number is True
+    assert Integer(737).is_number is True
+    assert Rational(3, 2).is_number is True
+    assert Rational(8).is_number is True
+    assert x.is_number is False
+    assert (2*x).is_number is False
+    assert (x + y).is_number is False
+    assert log(2).is_number is True
+    assert log(x).is_number is False
+    assert (2 + log(2)).is_number is True
+    assert (8 + log(2)).is_number is True
+    assert (2 + log(x)).is_number is False
+    assert (8 + log(2) + x).is_number is False
+    assert (1 + x**2/x - x).is_number is True
+    assert Tuple(Integer(1)).is_number is False
+    assert Add(2, x).is_number is False
+    assert Mul(3, 4).is_number is True
+    assert Pow(log(2), 2).is_number is True
+    assert oo.is_number is True
+    g = WildFunction('g')
+    assert g.is_number is False
+    assert (2*g).is_number is False
+    assert (x**2).subs(x, 3).is_number is True
+
+    # test extensibility of .is_number
+    # on subinstances of Basic
+    class A(Basic):
+        pass
+    a = A()
+    assert a.is_number is False
+
+
+def test_as_coeff_add():
+    assert S(2).as_coeff_add() == (2, ())
+    assert S(3.0).as_coeff_add() == (0, (S(3.0),))
+    assert S(-3.0).as_coeff_add() == (0, (S(-3.0),))
+    assert x.as_coeff_add() == (0, (x,))
+    assert (x - 1).as_coeff_add() == (-1, (x,))
+    assert (x + 1).as_coeff_add() == (1, (x,))
+    assert (x + 2).as_coeff_add() == (2, (x,))
+    assert (x + y).as_coeff_add(y) == (x, (y,))
+    assert (3*x).as_coeff_add(y) == (3*x, ())
+    # don't do expansion
+    e = (x + y)**2
+    assert e.as_coeff_add(y) == (0, (e,))
+
+
+def test_as_coeff_mul():
+    assert S(2).as_coeff_mul() == (2, ())
+    assert S(3.0).as_coeff_mul() == (1, (S(3.0),))
+    assert S(-3.0).as_coeff_mul() == (-1, (S(3.0),))
+    assert S(-3.0).as_coeff_mul(rational=False) == (-S(3.0), ())
+    assert x.as_coeff_mul() == (1, (x,))
+    assert (-x).as_coeff_mul() == (-1, (x,))
+    assert (2*x).as_coeff_mul() == (2, (x,))
+    assert (x*y).as_coeff_mul(y) == (x, (y,))
+    assert (3 + x).as_coeff_mul() == (1, (3 + x,))
+    assert (3 + x).as_coeff_mul(y) == (3 + x, ())
+    # don't do expansion
+    e = exp(x + y)
+    assert e.as_coeff_mul(y) == (1, (e,))
+    e = 2**(x + y)
+    assert e.as_coeff_mul(y) == (1, (e,))
+    assert (1.1*x).as_coeff_mul(rational=False) == (1.1, (x,))
+    assert (1.1*x).as_coeff_mul() == (1, (1.1, x))
+    assert (-oo*x).as_coeff_mul(rational=True) == (-1, (oo, x))
+
+
+def test_as_coeff_exponent():
+    assert (3*x**4).as_coeff_exponent(x) == (3, 4)
+    assert (2*x**3).as_coeff_exponent(x) == (2, 3)
+    assert (4*x**2).as_coeff_exponent(x) == (4, 2)
+    assert (6*x**1).as_coeff_exponent(x) == (6, 1)
+    assert (3*x**0).as_coeff_exponent(x) == (3, 0)
+    assert (2*x**0).as_coeff_exponent(x) == (2, 0)
+    assert (1*x**0).as_coeff_exponent(x) == (1, 0)
+    assert (0*x**0).as_coeff_exponent(x) == (0, 0)
+    assert (-1*x**0).as_coeff_exponent(x) == (-1, 0)
+    assert (-2*x**0).as_coeff_exponent(x) == (-2, 0)
+    assert (2*x**3 + pi*x**3).as_coeff_exponent(x) == (2 + pi, 3)
+    assert (x*log(2)/(2*x + pi*x)).as_coeff_exponent(x) == \
+        (log(2)/(2 + pi), 0)
+    # issue 4784
+    D = Derivative
+    fx = D(f(x), x)
+    assert fx.as_coeff_exponent(f(x)) == (fx, 0)
+
+
+def test_extractions():
+    for base in (2, S.Exp1):
+        assert Pow(base**x, 3, evaluate=False
+            ).extract_multiplicatively(base**x) == base**(2*x)
+        assert (base**(5*x)).extract_multiplicatively(
+            base**(3*x)) == base**(2*x)
+    assert ((x*y)**3).extract_multiplicatively(x**2 * y) == x*y**2
+    assert ((x*y)**3).extract_multiplicatively(x**4 * y) is None
+    assert (2*x).extract_multiplicatively(2) == x
+    assert (2*x).extract_multiplicatively(3) is None
+    assert (2*x).extract_multiplicatively(-1) is None
+    assert (S.Half*x).extract_multiplicatively(3) == x/6
+    assert (sqrt(x)).extract_multiplicatively(x) is None
+    assert (sqrt(x)).extract_multiplicatively(1/x) is None
+    assert x.extract_multiplicatively(-x) is None
+    assert (-2 - 4*I).extract_multiplicatively(-2) == 1 + 2*I
+    assert (-2 - 4*I).extract_multiplicatively(3) is None
+    assert (-2*x - 4*y - 8).extract_multiplicatively(-2) == x + 2*y + 4
+    assert (-2*x*y - 4*x**2*y).extract_multiplicatively(-2*y) == 2*x**2 + x
+    assert (2*x*y + 4*x**2*y).extract_multiplicatively(2*y) == 2*x**2 + x
+    assert (-4*y**2*x).extract_multiplicatively(-3*y) is None
+    assert (2*x).extract_multiplicatively(1) == 2*x
+    assert (-oo).extract_multiplicatively(5) is -oo
+    assert (oo).extract_multiplicatively(5) is oo
+
+    assert ((x*y)**3).extract_additively(1) is None
+    assert (x + 1).extract_additively(x) == 1
+    assert (x + 1).extract_additively(2*x) is None
+    assert (x + 1).extract_additively(-x) is None
+    assert (-x + 1).extract_additively(2*x) is None
+    assert (2*x + 3).extract_additively(x) == x + 3
+    assert (2*x + 3).extract_additively(2) == 2*x + 1
+    assert (2*x + 3).extract_additively(3) == 2*x
+    assert (2*x + 3).extract_additively(-2) is None
+    assert (2*x + 3).extract_additively(3*x) is None
+    assert (2*x + 3).extract_additively(2*x) == 3
+    assert x.extract_additively(0) == x
+    assert S(2).extract_additively(x) is None
+    assert S(2.).extract_additively(2.) is S.Zero
+    assert S(2.).extract_additively(2) is S.Zero
+    assert S(2*x + 3).extract_additively(x + 1) == x + 2
+    assert S(2*x + 3).extract_additively(y + 1) is None
+    assert S(2*x - 3).extract_additively(x + 1) is None
+    assert S(2*x - 3).extract_additively(y + z) is None
+    assert ((a + 1)*x*4 + y).extract_additively(x).expand() == \
+        4*a*x + 3*x + y
+    assert ((a + 1)*x*4 + 3*y).extract_additively(x + 2*y).expand() == \
+        4*a*x + 3*x + y
+    assert (y*(x + 1)).extract_additively(x + 1) is None
+    assert ((y + 1)*(x + 1) + 3).extract_additively(x + 1) == \
+        y*(x + 1) + 3
+    assert ((x + y)*(x + 1) + x + y + 3).extract_additively(x + y) == \
+        x*(x + y) + 3
+    assert (x + y + 2*((x + y)*(x + 1)) + 3).extract_additively((x + y)*(x + 1)) == \
+        x + y + (x + 1)*(x + y) + 3
+    assert ((y + 1)*(x + 2*y + 1) + 3).extract_additively(y + 1) == \
+        (x + 2*y)*(y + 1) + 3
+    assert (-x - x*I).extract_additively(-x) == -I*x
+    # extraction does not leave artificats, now
+    assert (4*x*(y + 1) + y).extract_additively(x) == x*(4*y + 3) + y
+
+    n = Symbol("n", integer=True)
+    assert (Integer(-3)).could_extract_minus_sign() is True
+    assert (-n*x + x).could_extract_minus_sign() != \
+        (n*x - x).could_extract_minus_sign()
+    assert (x - y).could_extract_minus_sign() != \
+        (-x + y).could_extract_minus_sign()
+    assert (1 - x - y).could_extract_minus_sign() is True
+    assert (1 - x + y).could_extract_minus_sign() is False
+    assert ((-x - x*y)/y).could_extract_minus_sign() is False
+    assert ((x + x*y)/(-y)).could_extract_minus_sign() is True
+    assert ((x + x*y)/y).could_extract_minus_sign() is False
+    assert ((-x - y)/(x + y)).could_extract_minus_sign() is False
+
+    class sign_invariant(Function, Expr):
+        nargs = 1
+        def __neg__(self):
+            return self
+    foo = sign_invariant(x)
+    assert foo == -foo
+    assert foo.could_extract_minus_sign() is False
+    assert (x - y).could_extract_minus_sign() is False
+    assert (-x + y).could_extract_minus_sign() is True
+    assert (x - 1).could_extract_minus_sign() is False
+    assert (1 - x).could_extract_minus_sign() is True
+    assert (sqrt(2) - 1).could_extract_minus_sign() is True
+    assert (1 - sqrt(2)).could_extract_minus_sign() is False
+    # check that result is canonical
+    eq = (3*x + 15*y).extract_multiplicatively(3)
+    assert eq.args == eq.func(*eq.args).args
+
+
+def test_nan_extractions():
+    for r in (1, 0, I, nan):
+        assert nan.extract_additively(r) is None
+        assert nan.extract_multiplicatively(r) is None
+
+
+def test_coeff():
+    assert (x + 1).coeff(x + 1) == 1
+    assert (3*x).coeff(0) == 0
+    assert (z*(1 + x)*x**2).coeff(1 + x) == z*x**2
+    assert (1 + 2*x*x**(1 + x)).coeff(x*x**(1 + x)) == 2
+    assert (1 + 2*x**(y + z)).coeff(x**(y + z)) == 2
+    assert (3 + 2*x + 4*x**2).coeff(1) == 0
+    assert (3 + 2*x + 4*x**2).coeff(-1) == 0
+    assert (3 + 2*x + 4*x**2).coeff(x) == 2
+    assert (3 + 2*x + 4*x**2).coeff(x**2) == 4
+    assert (3 + 2*x + 4*x**2).coeff(x**3) == 0
+
+    assert (-x/8 + x*y).coeff(x) == Rational(-1, 8) + y
+    assert (-x/8 + x*y).coeff(-x) == S.One/8
+    assert (4*x).coeff(2*x) == 0
+    assert (2*x).coeff(2*x) == 1
+    assert (-oo*x).coeff(x*oo) == -1
+    assert (10*x).coeff(x, 0) == 0
+    assert (10*x).coeff(10*x, 0) == 0
+
+    n1, n2 = symbols('n1 n2', commutative=False)
+    assert (n1*n2).coeff(n1) == 1
+    assert (n1*n2).coeff(n2) == n1
+    assert (n1*n2 + x*n1).coeff(n1) == 1  # 1*n1*(n2+x)
+    assert (n2*n1 + x*n1).coeff(n1) == n2 + x
+    assert (n2*n1 + x*n1**2).coeff(n1) == n2
+    assert (n1**x).coeff(n1) == 0
+    assert (n1*n2 + n2*n1).coeff(n1) == 0
+    assert (2*(n1 + n2)*n2).coeff(n1 + n2, right=1) == n2
+    assert (2*(n1 + n2)*n2).coeff(n1 + n2, right=0) == 2
+
+    assert (2*f(x) + 3*f(x).diff(x)).coeff(f(x)) == 2
+
+    expr = z*(x + y)**2
+    expr2 = z*(x + y)**2 + z*(2*x + 2*y)**2
+    assert expr.coeff(z) == (x + y)**2
+    assert expr.coeff(x + y) == 0
+    assert expr2.coeff(z) == (x + y)**2 + (2*x + 2*y)**2
+
+    assert (x + y + 3*z).coeff(1) == x + y
+    assert (-x + 2*y).coeff(-1) == x
+    assert (x - 2*y).coeff(-1) == 2*y
+    assert (3 + 2*x + 4*x**2).coeff(1) == 0
+    assert (-x - 2*y).coeff(2) == -y
+    assert (x + sqrt(2)*x).coeff(sqrt(2)) == x
+    assert (3 + 2*x + 4*x**2).coeff(x) == 2
+    assert (3 + 2*x + 4*x**2).coeff(x**2) == 4
+    assert (3 + 2*x + 4*x**2).coeff(x**3) == 0
+    assert (z*(x + y)**2).coeff((x + y)**2) == z
+    assert (z*(x + y)**2).coeff(x + y) == 0
+    assert (2 + 2*x + (x + 1)*y).coeff(x + 1) == y
+
+    assert (x + 2*y + 3).coeff(1) == x
+    assert (x + 2*y + 3).coeff(x, 0) == 2*y + 3
+    assert (x**2 + 2*y + 3*x).coeff(x**2, 0) == 2*y + 3*x
+    assert x.coeff(0, 0) == 0
+    assert x.coeff(x, 0) == 0
+
+    n, m, o, l = symbols('n m o l', commutative=False)
+    assert n.coeff(n) == 1
+    assert y.coeff(n) == 0
+    assert (3*n).coeff(n) == 3
+    assert (2 + n).coeff(x*m) == 0
+    assert (2*x*n*m).coeff(x) == 2*n*m
+    assert (2 + n).coeff(x*m*n + y) == 0
+    assert (2*x*n*m).coeff(3*n) == 0
+    assert (n*m + m*n*m).coeff(n) == 1 + m
+    assert (n*m + m*n*m).coeff(n, right=True) == m  # = (1 + m)*n*m
+    assert (n*m + m*n).coeff(n) == 0
+    assert (n*m + o*m*n).coeff(m*n) == o
+    assert (n*m + o*m*n).coeff(m*n, right=True) == 1
+    assert (n*m + n*m*n).coeff(n*m, right=True) == 1 + n  # = n*m*(n + 1)
+
+    assert (x*y).coeff(z, 0) == x*y
+
+    assert (x*n + y*n + z*m).coeff(n) == x + y
+    assert (n*m + n*o + o*l).coeff(n, right=True) == m + o
+    assert (x*n*m*n + y*n*m*o + z*l).coeff(m, right=True) == x*n + y*o
+    assert (x*n*m*n + x*n*m*o + z*l).coeff(m, right=True) == n + o
+    assert (x*n*m*n + x*n*m*o + z*l).coeff(m) == x*n
+
+
+def test_coeff2():
+    r, kappa = symbols('r, kappa')
+    psi = Function("psi")
+    g = 1/r**2 * (2*r*psi(r).diff(r, 1) + r**2 * psi(r).diff(r, 2))
+    g = g.expand()
+    assert g.coeff(psi(r).diff(r)) == 2/r
+
+
+def test_coeff2_0():
+    r, kappa = symbols('r, kappa')
+    psi = Function("psi")
+    g = 1/r**2 * (2*r*psi(r).diff(r, 1) + r**2 * psi(r).diff(r, 2))
+    g = g.expand()
+
+    assert g.coeff(psi(r).diff(r, 2)) == 1
+
+
+def test_coeff_expand():
+    expr = z*(x + y)**2
+    expr2 = z*(x + y)**2 + z*(2*x + 2*y)**2
+    assert expr.coeff(z) == (x + y)**2
+    assert expr2.coeff(z) == (x + y)**2 + (2*x + 2*y)**2
+
+
+def test_integrate():
+    assert x.integrate(x) == x**2/2
+    assert x.integrate((x, 0, 1)) == S.Half
+
+
+def test_as_base_exp():
+    assert x.as_base_exp() == (x, S.One)
+    assert (x*y*z).as_base_exp() == (x*y*z, S.One)
+    assert (x + y + z).as_base_exp() == (x + y + z, S.One)
+    assert ((x + y)**z).as_base_exp() == (x + y, z)
+
+
+def test_issue_4963():
+    assert hasattr(Mul(x, y), "is_commutative")
+    assert hasattr(Mul(x, y, evaluate=False), "is_commutative")
+    assert hasattr(Pow(x, y), "is_commutative")
+    assert hasattr(Pow(x, y, evaluate=False), "is_commutative")
+    expr = Mul(Pow(2, 2, evaluate=False), 3, evaluate=False) + 1
+    assert hasattr(expr, "is_commutative")
+
+
+def test_action_verbs():
+    assert nsimplify(1/(exp(3*pi*x/5) + 1)) == \
+        (1/(exp(3*pi*x/5) + 1)).nsimplify()
+    assert ratsimp(1/x + 1/y) == (1/x + 1/y).ratsimp()
+    assert trigsimp(log(x), deep=True) == (log(x)).trigsimp(deep=True)
+    assert radsimp(1/(2 + sqrt(2))) == (1/(2 + sqrt(2))).radsimp()
+    assert radsimp(1/(a + b*sqrt(c)), symbolic=False) == \
+        (1/(a + b*sqrt(c))).radsimp(symbolic=False)
+    assert powsimp(x**y*x**z*y**z, combine='all') == \
+        (x**y*x**z*y**z).powsimp(combine='all')
+    assert (x**t*y**t).powsimp(force=True) == (x*y)**t
+    assert simplify(x**y*x**z*y**z) == (x**y*x**z*y**z).simplify()
+    assert together(1/x + 1/y) == (1/x + 1/y).together()
+    assert collect(a*x**2 + b*x**2 + a*x - b*x + c, x) == \
+        (a*x**2 + b*x**2 + a*x - b*x + c).collect(x)
+    assert apart(y/(y + 2)/(y + 1), y) == (y/(y + 2)/(y + 1)).apart(y)
+    assert combsimp(y/(x + 2)/(x + 1)) == (y/(x + 2)/(x + 1)).combsimp()
+    assert gammasimp(gamma(x)/gamma(x-5)) == (gamma(x)/gamma(x-5)).gammasimp()
+    assert factor(x**2 + 5*x + 6) == (x**2 + 5*x + 6).factor()
+    assert refine(sqrt(x**2)) == sqrt(x**2).refine()
+    assert cancel((x**2 + 5*x + 6)/(x + 2)) == ((x**2 + 5*x + 6)/(x + 2)).cancel()
+
+
+def test_as_powers_dict():
+    assert x.as_powers_dict() == {x: 1}
+    assert (x**y*z).as_powers_dict() == {x: y, z: 1}
+    assert Mul(2, 2, evaluate=False).as_powers_dict() == {S(2): S(2)}
+    assert (x*y).as_powers_dict()[z] == 0
+    assert (x + y).as_powers_dict()[z] == 0
+
+
+def test_as_coefficients_dict():
+    check = [S.One, x, y, x*y, 1]
+    assert [Add(3*x, 2*x, y, 3).as_coefficients_dict()[i] for i in check] == \
+        [3, 5, 1, 0, 3]
+    assert [Add(3*x, 2*x, y, 3, evaluate=False).as_coefficients_dict()[i]
+            for i in check] == [3, 5, 1, 0, 3]
+    assert [(3*x*y).as_coefficients_dict()[i] for i in check] == \
+        [0, 0, 0, 3, 0]
+    assert [(3.0*x*y).as_coefficients_dict()[i] for i in check] == \
+        [0, 0, 0, 3.0, 0]
+    assert (3.0*x*y).as_coefficients_dict()[3.0*x*y] == 0
+    eq = x*(x + 1)*a + x*b + c/x
+    assert eq.as_coefficients_dict(x) == {x: b, 1/x: c,
+        x*(x + 1): a}
+    assert eq.expand().as_coefficients_dict(x) == {x**2: a, x: a + b, 1/x: c}
+    assert x.as_coefficients_dict() == {x: S.One}
+
+
+def test_args_cnc():
+    A = symbols('A', commutative=False)
+    assert (x + A).args_cnc() == \
+        [[], [x + A]]
+    assert (x + a).args_cnc() == \
+        [[a + x], []]
+    assert (x*a).args_cnc() == \
+        [[a, x], []]
+    assert (x*y*A*(A + 1)).args_cnc(cset=True) == \
+        [{x, y}, [A, 1 + A]]
+    assert Mul(x, x, evaluate=False).args_cnc(cset=True, warn=False) == \
+        [{x}, []]
+    assert Mul(x, x**2, evaluate=False).args_cnc(cset=True, warn=False) == \
+        [{x, x**2}, []]
+    raises(ValueError, lambda: Mul(x, x, evaluate=False).args_cnc(cset=True))
+    assert Mul(x, y, x, evaluate=False).args_cnc() == \
+        [[x, y, x], []]
+    # always split -1 from leading number
+    assert (-1.*x).args_cnc() == [[-1, 1.0, x], []]
+
+
+def test_new_rawargs():
+    n = Symbol('n', commutative=False)
+    a = x + n
+    assert a.is_commutative is False
+    assert a._new_rawargs(x).is_commutative
+    assert a._new_rawargs(x, y).is_commutative
+    assert a._new_rawargs(x, n).is_commutative is False
+    assert a._new_rawargs(x, y, n).is_commutative is False
+    m = x*n
+    assert m.is_commutative is False
+    assert m._new_rawargs(x).is_commutative
+    assert m._new_rawargs(n).is_commutative is False
+    assert m._new_rawargs(x, y).is_commutative
+    assert m._new_rawargs(x, n).is_commutative is False
+    assert m._new_rawargs(x, y, n).is_commutative is False
+
+    assert m._new_rawargs(x, n, reeval=False).is_commutative is False
+    assert m._new_rawargs(S.One) is S.One
+
+
+def test_issue_5226():
+    assert Add(evaluate=False) == 0
+    assert Mul(evaluate=False) == 1
+    assert Mul(x + y, evaluate=False).is_Add
+
+
+def test_free_symbols():
+    # free_symbols should return the free symbols of an object
+    assert S.One.free_symbols == set()
+    assert x.free_symbols == {x}
+    assert Integral(x, (x, 1, y)).free_symbols == {y}
+    assert (-Integral(x, (x, 1, y))).free_symbols == {y}
+    assert meter.free_symbols == set()
+    assert (meter**x).free_symbols == {x}
+
+
+def test_has_free():
+    assert x.has_free(x)
+    assert not x.has_free(y)
+    assert (x + y).has_free(x)
+    assert (x + y).has_free(*(x, z))
+    assert f(x).has_free(x)
+    assert f(x).has_free(f(x))
+    assert Integral(f(x), (f(x), 1, y)).has_free(y)
+    assert not Integral(f(x), (f(x), 1, y)).has_free(x)
+    assert not Integral(f(x), (f(x), 1, y)).has_free(f(x))
+    # simple extraction
+    assert (x + 1 + y).has_free(x + 1)
+    assert not (x + 2 + y).has_free(x + 1)
+    assert (2 + 3*x*y).has_free(3*x)
+    raises(TypeError, lambda: x.has_free({x, y}))
+    s = FiniteSet(1, 2)
+    assert Piecewise((s, x > 3), (4, True)).has_free(s)
+    assert not Piecewise((1, x > 3), (4, True)).has_free(s)
+    # can't make set of these, but fallback will handle
+    raises(TypeError, lambda: x.has_free(y, []))
+
+
+def test_has_xfree():
+    assert (x + 1).has_xfree({x})
+    assert ((x + 1)**2).has_xfree({x + 1})
+    assert not (x + y + 1).has_xfree({x + 1})
+    raises(TypeError, lambda: x.has_xfree(x))
+    raises(TypeError, lambda: x.has_xfree([x]))
+
+
+def test_issue_5300():
+    x = Symbol('x', commutative=False)
+    assert x*sqrt(2)/sqrt(6) == x*sqrt(3)/3
+
+
+def test_floordiv():
+    from sympy.functions.elementary.integers import floor
+    assert x // y == floor(x / y)
+
+
+def test_as_coeff_Mul():
+    assert Integer(3).as_coeff_Mul() == (Integer(3), Integer(1))
+    assert Rational(3, 4).as_coeff_Mul() == (Rational(3, 4), Integer(1))
+    assert Float(5.0).as_coeff_Mul() == (Float(5.0), Integer(1))
+
+    assert (Integer(3)*x).as_coeff_Mul() == (Integer(3), x)
+    assert (Rational(3, 4)*x).as_coeff_Mul() == (Rational(3, 4), x)
+    assert (Float(5.0)*x).as_coeff_Mul() == (Float(5.0), x)
+
+    assert (Integer(3)*x*y).as_coeff_Mul() == (Integer(3), x*y)
+    assert (Rational(3, 4)*x*y).as_coeff_Mul() == (Rational(3, 4), x*y)
+    assert (Float(5.0)*x*y).as_coeff_Mul() == (Float(5.0), x*y)
+
+    assert (x).as_coeff_Mul() == (S.One, x)
+    assert (x*y).as_coeff_Mul() == (S.One, x*y)
+    assert (-oo*x).as_coeff_Mul(rational=True) == (-1, oo*x)
+
+
+def test_as_coeff_Add():
+    assert Integer(3).as_coeff_Add() == (Integer(3), Integer(0))
+    assert Rational(3, 4).as_coeff_Add() == (Rational(3, 4), Integer(0))
+    assert Float(5.0).as_coeff_Add() == (Float(5.0), Integer(0))
+
+    assert (Integer(3) + x).as_coeff_Add() == (Integer(3), x)
+    assert (Rational(3, 4) + x).as_coeff_Add() == (Rational(3, 4), x)
+    assert (Float(5.0) + x).as_coeff_Add() == (Float(5.0), x)
+    assert (Float(5.0) + x).as_coeff_Add(rational=True) == (0, Float(5.0) + x)
+
+    assert (Integer(3) + x + y).as_coeff_Add() == (Integer(3), x + y)
+    assert (Rational(3, 4) + x + y).as_coeff_Add() == (Rational(3, 4), x + y)
+    assert (Float(5.0) + x + y).as_coeff_Add() == (Float(5.0), x + y)
+
+    assert (x).as_coeff_Add() == (S.Zero, x)
+    assert (x*y).as_coeff_Add() == (S.Zero, x*y)
+
+
+def test_expr_sorting():
+
+    exprs = [1/x**2, 1/x, sqrt(sqrt(x)), sqrt(x), x, sqrt(x)**3, x**2]
+    assert sorted(exprs, key=default_sort_key) == exprs
+
+    exprs = [x, 2*x, 2*x**2, 2*x**3, x**n, 2*x**n, sin(x), sin(x)**n,
+             sin(x**2), cos(x), cos(x**2), tan(x)]
+    assert sorted(exprs, key=default_sort_key) == exprs
+
+    exprs = [x + 1, x**2 + x + 1, x**3 + x**2 + x + 1]
+    assert sorted(exprs, key=default_sort_key) == exprs
+
+    exprs = [S(4), x - 3*I/2, x + 3*I/2, x - 4*I + 1, x + 4*I + 1]
+    assert sorted(exprs, key=default_sort_key) == exprs
+
+    exprs = [f(1), f(2), f(3), f(1, 2, 3), g(1), g(2), g(3), g(1, 2, 3)]
+    assert sorted(exprs, key=default_sort_key) == exprs
+
+    exprs = [f(x), g(x), exp(x), sin(x), cos(x), factorial(x)]
+    assert sorted(exprs, key=default_sort_key) == exprs
+
+    exprs = [Tuple(x, y), Tuple(x, z), Tuple(x, y, z)]
+    assert sorted(exprs, key=default_sort_key) == exprs
+
+    exprs = [[3], [1, 2]]
+    assert sorted(exprs, key=default_sort_key) == exprs
+
+    exprs = [[1, 2], [2, 3]]
+    assert sorted(exprs, key=default_sort_key) == exprs
+
+    exprs = [[1, 2], [1, 2, 3]]
+    assert sorted(exprs, key=default_sort_key) == exprs
+
+    exprs = [{x: -y}, {x: y}]
+    assert sorted(exprs, key=default_sort_key) == exprs
+
+    exprs = [{1}, {1, 2}]
+    assert sorted(exprs, key=default_sort_key) == exprs
+
+    a, b = exprs = [Dummy('x'), Dummy('x')]
+    assert sorted([b, a], key=default_sort_key) == exprs
+
+
+def test_as_ordered_factors():
+
+    assert x.as_ordered_factors() == [x]
+    assert (2*x*x**n*sin(x)*cos(x)).as_ordered_factors() \
+        == [Integer(2), x, x**n, sin(x), cos(x)]
+
+    args = [f(1), f(2), f(3), f(1, 2, 3), g(1), g(2), g(3), g(1, 2, 3)]
+    expr = Mul(*args)
+
+    assert expr.as_ordered_factors() == args
+
+    A, B = symbols('A,B', commutative=False)
+
+    assert (A*B).as_ordered_factors() == [A, B]
+    assert (B*A).as_ordered_factors() == [B, A]
+
+
+def test_as_ordered_terms():
+
+    assert x.as_ordered_terms() == [x]
+    assert (sin(x)**2*cos(x) + sin(x)*cos(x)**2 + 1).as_ordered_terms() \
+        == [sin(x)**2*cos(x), sin(x)*cos(x)**2, 1]
+
+    args = [f(1), f(2), f(3), f(1, 2, 3), g(1), g(2), g(3), g(1, 2, 3)]
+    expr = Add(*args)
+
+    assert expr.as_ordered_terms() == args
+
+    assert (1 + 4*sqrt(3)*pi*x).as_ordered_terms() == [4*pi*x*sqrt(3), 1]
+
+    assert ( 2 + 3*I).as_ordered_terms() == [2, 3*I]
+    assert (-2 + 3*I).as_ordered_terms() == [-2, 3*I]
+    assert ( 2 - 3*I).as_ordered_terms() == [2, -3*I]
+    assert (-2 - 3*I).as_ordered_terms() == [-2, -3*I]
+
+    assert ( 4 + 3*I).as_ordered_terms() == [4, 3*I]
+    assert (-4 + 3*I).as_ordered_terms() == [-4, 3*I]
+    assert ( 4 - 3*I).as_ordered_terms() == [4, -3*I]
+    assert (-4 - 3*I).as_ordered_terms() == [-4, -3*I]
+
+    e = x**2*y**2 + x*y**4 + y + 2
+
+    assert e.as_ordered_terms(order="lex") == [x**2*y**2, x*y**4, y, 2]
+    assert e.as_ordered_terms(order="grlex") == [x*y**4, x**2*y**2, y, 2]
+    assert e.as_ordered_terms(order="rev-lex") == [2, y, x*y**4, x**2*y**2]
+    assert e.as_ordered_terms(order="rev-grlex") == [2, y, x**2*y**2, x*y**4]
+
+    k = symbols('k')
+    assert k.as_ordered_terms(data=True) == ([(k, ((1.0, 0.0), (1,), ()))], [k])
+
+
+def test_sort_key_atomic_expr():
+    from sympy.physics.units import m, s
+    assert sorted([-m, s], key=lambda arg: arg.sort_key()) == [-m, s]
+
+
+def test_eval_interval():
+    assert exp(x)._eval_interval(*Tuple(x, 0, 1)) == exp(1) - exp(0)
+
+    # issue 4199
+    a = x/y
+    raises(NotImplementedError, lambda: a._eval_interval(x, S.Zero, oo)._eval_interval(y, oo, S.Zero))
+    raises(NotImplementedError, lambda: a._eval_interval(x, S.Zero, oo)._eval_interval(y, S.Zero, oo))
+    a = x - y
+    raises(NotImplementedError, lambda: a._eval_interval(x, S.One, oo)._eval_interval(y, oo, S.One))
+    raises(ValueError, lambda: x._eval_interval(x, None, None))
+    a = -y*Heaviside(x - y)
+    assert a._eval_interval(x, -oo, oo) == -y
+    assert a._eval_interval(x, oo, -oo) == y
+
+
+def test_eval_interval_zoo():
+    # Test that limit is used when zoo is returned
+    assert Si(1/x)._eval_interval(x, S.Zero, S.One) == -pi/2 + Si(1)
+
+
+def test_primitive():
+    assert (3*(x + 1)**2).primitive() == (3, (x + 1)**2)
+    assert (6*x + 2).primitive() == (2, 3*x + 1)
+    assert (x/2 + 3).primitive() == (S.Half, x + 6)
+    eq = (6*x + 2)*(x/2 + 3)
+    assert eq.primitive()[0] == 1
+    eq = (2 + 2*x)**2
+    assert eq.primitive()[0] == 1
+    assert (4.0*x).primitive() == (1, 4.0*x)
+    assert (4.0*x + y/2).primitive() == (S.Half, 8.0*x + y)
+    assert (-2*x).primitive() == (2, -x)
+    assert Add(5*z/7, 0.5*x, 3*y/2, evaluate=False).primitive() == \
+        (S.One/14, 7.0*x + 21*y + 10*z)
+    for i in [S.Infinity, S.NegativeInfinity, S.ComplexInfinity]:
+        assert (i + x/3).primitive() == \
+            (S.One/3, i + x)
+    assert (S.Infinity + 2*x/3 + 4*y/7).primitive() == \
+        (S.One/21, 14*x + 12*y + oo)
+    assert S.Zero.primitive() == (S.One, S.Zero)
+
+
+def test_issue_5843():
+    a = 1 + x
+    assert (2*a).extract_multiplicatively(a) == 2
+    assert (4*a).extract_multiplicatively(2*a) == 2
+    assert ((3*a)*(2*a)).extract_multiplicatively(a) == 6*a
+
+
+def test_is_constant():
+    from sympy.solvers.solvers import checksol
+    assert Sum(x, (x, 1, 10)).is_constant() is True
+    assert Sum(x, (x, 1, n)).is_constant() is False
+    assert Sum(x, (x, 1, n)).is_constant(y) is True
+    assert Sum(x, (x, 1, n)).is_constant(n) is False
+    assert Sum(x, (x, 1, n)).is_constant(x) is True
+    eq = a*cos(x)**2 + a*sin(x)**2 - a
+    assert eq.is_constant() is True
+    assert eq.subs({x: pi, a: 2}) == eq.subs({x: pi, a: 3}) == 0
+    assert x.is_constant() is False
+    assert x.is_constant(y) is True
+    assert log(x/y).is_constant() is False
+
+    assert checksol(x, x, Sum(x, (x, 1, n))) is False
+    assert checksol(x, x, Sum(x, (x, 1, n))) is False
+    assert f(1).is_constant
+    assert checksol(x, x, f(x)) is False
+
+    assert Pow(x, S.Zero, evaluate=False).is_constant() is True  # == 1
+    assert Pow(S.Zero, x, evaluate=False).is_constant() is False  # == 0 or 1
+    assert (2**x).is_constant() is False
+    assert Pow(S(2), S(3), evaluate=False).is_constant() is True
+
+    z1, z2 = symbols('z1 z2', zero=True)
+    assert (z1 + 2*z2).is_constant() is True
+
+    assert meter.is_constant() is True
+    assert (3*meter).is_constant() is True
+    assert (x*meter).is_constant() is False
+
+
+def test_equals():
+    assert (-3 - sqrt(5) + (-sqrt(10)/2 - sqrt(2)/2)**2).equals(0)
+    assert (x**2 - 1).equals((x + 1)*(x - 1))
+    assert (cos(x)**2 + sin(x)**2).equals(1)
+    assert (a*cos(x)**2 + a*sin(x)**2).equals(a)
+    r = sqrt(2)
+    assert (-1/(r + r*x) + 1/r/(1 + x)).equals(0)
+    assert factorial(x + 1).equals((x + 1)*factorial(x))
+    assert sqrt(3).equals(2*sqrt(3)) is False
+    assert (sqrt(5)*sqrt(3)).equals(sqrt(3)) is False
+    assert (sqrt(5) + sqrt(3)).equals(0) is False
+    assert (sqrt(5) + pi).equals(0) is False
+    assert meter.equals(0) is False
+    assert (3*meter**2).equals(0) is False
+    eq = -(-1)**(S(3)/4)*6**(S.One/4) + (-6)**(S.One/4)*I
+    if eq != 0:  # if canonicalization makes this zero, skip the test
+        assert eq.equals(0)
+    assert sqrt(x).equals(0) is False
+
+    # from integrate(x*sqrt(1 + 2*x), x);
+    # diff is zero only when assumptions allow
+    i = 2*sqrt(2)*x**(S(5)/2)*(1 + 1/(2*x))**(S(5)/2)/5 + \
+        2*sqrt(2)*x**(S(3)/2)*(1 + 1/(2*x))**(S(5)/2)/(-6 - 3/x)
+    ans = sqrt(2*x + 1)*(6*x**2 + x - 1)/15
+    diff = i - ans
+    assert diff.equals(0) is None  # should be False, but previously this was False due to wrong intermediate result
+    assert diff.subs(x, Rational(-1, 2)/2) == 7*sqrt(2)/120
+    # there are regions for x for which the expression is True, for
+    # example, when x < -1/2 or x > 0 the expression is zero
+    p = Symbol('p', positive=True)
+    assert diff.subs(x, p).equals(0) is True
+    assert diff.subs(x, -1).equals(0) is True
+
+    # prove via minimal_polynomial or self-consistency
+    eq = sqrt(1 + sqrt(3)) + sqrt(3 + 3*sqrt(3)) - sqrt(10 + 6*sqrt(3))
+    assert eq.equals(0)
+    q = 3**Rational(1, 3) + 3
+    p = expand(q**3)**Rational(1, 3)
+    assert (p - q).equals(0)
+
+    # issue 6829
+    # eq = q*x + q/4 + x**4 + x**3 + 2*x**2 - S.One/3
+    # z = eq.subs(x, solve(eq, x)[0])
+    q = symbols('q')
+    z = (q*(-sqrt(-2*(-(q - S(7)/8)**S(2)/8 - S(2197)/13824)**(S.One/3) -
+    S(13)/12)/2 - sqrt((2*q - S(7)/4)/sqrt(-2*(-(q - S(7)/8)**S(2)/8 -
+    S(2197)/13824)**(S.One/3) - S(13)/12) + 2*(-(q - S(7)/8)**S(2)/8 -
+    S(2197)/13824)**(S.One/3) - S(13)/6)/2 - S.One/4) + q/4 + (-sqrt(-2*(-(q
+    - S(7)/8)**S(2)/8 - S(2197)/13824)**(S.One/3) - S(13)/12)/2 - sqrt((2*q
+    - S(7)/4)/sqrt(-2*(-(q - S(7)/8)**S(2)/8 - S(2197)/13824)**(S.One/3) -
+    S(13)/12) + 2*(-(q - S(7)/8)**S(2)/8 - S(2197)/13824)**(S.One/3) -
+    S(13)/6)/2 - S.One/4)**4 + (-sqrt(-2*(-(q - S(7)/8)**S(2)/8 -
+    S(2197)/13824)**(S.One/3) - S(13)/12)/2 - sqrt((2*q -
+    S(7)/4)/sqrt(-2*(-(q - S(7)/8)**S(2)/8 - S(2197)/13824)**(S.One/3) -
+    S(13)/12) + 2*(-(q - S(7)/8)**S(2)/8 - S(2197)/13824)**(S.One/3) -
+    S(13)/6)/2 - S.One/4)**3 + 2*(-sqrt(-2*(-(q - S(7)/8)**S(2)/8 -
+    S(2197)/13824)**(S.One/3) - S(13)/12)/2 - sqrt((2*q -
+    S(7)/4)/sqrt(-2*(-(q - S(7)/8)**S(2)/8 - S(2197)/13824)**(S.One/3) -
+    S(13)/12) + 2*(-(q - S(7)/8)**S(2)/8 - S(2197)/13824)**(S.One/3) -
+    S(13)/6)/2 - S.One/4)**2 - Rational(1, 3))
+    assert z.equals(0)
+
+
+def test_random():
+    from sympy.functions.combinatorial.numbers import lucas
+    from sympy.simplify.simplify import posify
+    assert posify(x)[0]._random() is not None
+    assert lucas(n)._random(2, -2, 0, -1, 1) is None
+
+    # issue 8662
+    assert Piecewise((Max(x, y), z))._random() is None
+
+
+def test_round():
+    assert str(Float('0.1249999').round(2)) == '0.12'
+    d20 = 12345678901234567890
+    ans = S(d20).round(2)
+    assert ans.is_Integer and ans == d20
+    ans = S(d20).round(-2)
+    assert ans.is_Integer and ans == 12345678901234567900
+    assert str(S('1/7').round(4)) == '0.1429'
+    assert str(S('.[12345]').round(4)) == '0.1235'
+    assert str(S('.1349').round(2)) == '0.13'
+    n = S(12345)
+    ans = n.round()
+    assert ans.is_Integer
+    assert ans == n
+    ans = n.round(1)
+    assert ans.is_Integer
+    assert ans == n
+    ans = n.round(4)
+    assert ans.is_Integer
+    assert ans == n
+    assert n.round(-1) == 12340
+
+    r = Float(str(n)).round(-4)
+    assert r == 10000.0
+
+    assert n.round(-5) == 0
+
+    assert str((pi + sqrt(2)).round(2)) == '4.56'
+    assert (10*(pi + sqrt(2))).round(-1) == 50.0
+    raises(TypeError, lambda: round(x + 2, 2))
+    assert str(S(2.3).round(1)) == '2.3'
+    # rounding in SymPy (as in Decimal) should be
+    # exact for the given precision; we check here
+    # that when a 5 follows the last digit that
+    # the rounded digit will be even.
+    for i in range(-99, 100):
+        # construct a decimal that ends in 5, e.g. 123 -> 0.1235
+        s = str(abs(i))
+        p = len(s)  # we are going to round to the last digit of i
+        n = '0.%s5' % s  # put a 5 after i's digits
+        j = p + 2  # 2 for '0.'
+        if i < 0:  # 1 for '-'
+            j += 1
+            n = '-' + n
+        v = str(Float(n).round(p))[:j]  # pertinent digits
+        if v.endswith('.'):
+          continue  # it ends with 0 which is even
+        L = int(v[-1])  # last digit
+        assert L % 2 == 0, (n, '->', v)
+
+    assert (Float(.3, 3) + 2*pi).round() == 7
+    assert (Float(.3, 3) + 2*pi*100).round() == 629
+    assert (pi + 2*E*I).round() == 3 + 5*I
+    # don't let request for extra precision give more than
+    # what is known (in this case, only 3 digits)
+    assert str((Float(.03, 3) + 2*pi/100).round(5)) == '0.0928'
+    assert str((Float(.03, 3) + 2*pi/100).round(4)) == '0.0928'
+
+    assert S.Zero.round() == 0
+
+    a = (Add(1, Float('1.' + '9'*27, ''), evaluate=0))
+    assert a.round(10) == Float('3.000000000000000000000000000', '')
+    assert a.round(25) == Float('3.000000000000000000000000000', '')
+    assert a.round(26) == Float('3.000000000000000000000000000', '')
+    assert a.round(27) == Float('2.999999999999999999999999999', '')
+    assert a.round(30) == Float('2.999999999999999999999999999', '')
+
+    # XXX: Should round set the precision of the result?
+    #      The previous version of the tests above is this but they only pass
+    #      because Floats with unequal precision compare equal:
+    #
+    # assert a.round(10) == Float('3.0000000000', '')
+    # assert a.round(25) == Float('3.0000000000000000000000000', '')
+    # assert a.round(26) == Float('3.00000000000000000000000000', '')
+    # assert a.round(27) == Float('2.999999999999999999999999999', '')
+    # assert a.round(30) == Float('2.999999999999999999999999999', '')
+
+    raises(TypeError, lambda: x.round())
+    raises(TypeError, lambda: f(1).round())
+
+    # exact magnitude of 10
+    assert str(S.One.round()) == '1'
+    assert str(S(100).round()) == '100'
+
+    # applied to real and imaginary portions
+    assert (2*pi + E*I).round() == 6 + 3*I
+    assert (2*pi + I/10).round() == 6
+    assert (pi/10 + 2*I).round() == 2*I
+    # the lhs re and im parts are Float with dps of 2
+    # and those on the right have dps of 15 so they won't compare
+    # equal unless we use string or compare components (which will
+    # then coerce the floats to the same precision) or re-create
+    # the floats
+    assert str((pi/10 + E*I).round(2)) == '0.31 + 2.72*I'
+    assert str((pi/10 + E*I).round(2).as_real_imag()) == '(0.31, 2.72)'
+    assert str((pi/10 + E*I).round(2)) == '0.31 + 2.72*I'
+
+    # issue 6914
+    assert (I**(I + 3)).round(3) == Float('-0.208', '')*I
+
+    # issue 8720
+    assert S(-123.6).round() == -124
+    assert S(-1.5).round() == -2
+    assert S(-100.5).round() == -100
+    assert S(-1.5 - 10.5*I).round() == -2 - 10*I
+
+    # issue 7961
+    assert str(S(0.006).round(2)) == '0.01'
+    assert str(S(0.00106).round(4)) == '0.0011'
+
+    # issue 8147
+    assert S.NaN.round() is S.NaN
+    assert S.Infinity.round() is S.Infinity
+    assert S.NegativeInfinity.round() is S.NegativeInfinity
+    assert S.ComplexInfinity.round() is S.ComplexInfinity
+
+    # check that types match
+    for i in range(2):
+        fi = float(i)
+        # 2 args
+        assert all(type(round(i, p)) is int for p in (-1, 0, 1))
+        assert all(S(i).round(p).is_Integer for p in (-1, 0, 1))
+        assert all(type(round(fi, p)) is float for p in (-1, 0, 1))
+        assert all(S(fi).round(p).is_Float for p in (-1, 0, 1))
+        # 1 arg (p is None)
+        assert type(round(i)) is int
+        assert S(i).round().is_Integer
+        assert type(round(fi)) is int
+        assert S(fi).round().is_Integer
+
+
+def test_held_expression_UnevaluatedExpr():
+    x = symbols("x")
+    he = UnevaluatedExpr(1/x)
+    e1 = x*he
+
+    assert isinstance(e1, Mul)
+    assert e1.args == (x, he)
+    assert e1.doit() == 1
+    assert UnevaluatedExpr(Derivative(x, x)).doit(deep=False
+        ) == Derivative(x, x)
+    assert UnevaluatedExpr(Derivative(x, x)).doit() == 1
+
+    xx = Mul(x, x, evaluate=False)
+    assert xx != x**2
+
+    ue2 = UnevaluatedExpr(xx)
+    assert isinstance(ue2, UnevaluatedExpr)
+    assert ue2.args == (xx,)
+    assert ue2.doit() == x**2
+    assert ue2.doit(deep=False) == xx
+
+    x2 = UnevaluatedExpr(2)*2
+    assert type(x2) is Mul
+    assert x2.args == (2, UnevaluatedExpr(2))
+
+def test_round_exception_nostr():
+    # Don't use the string form of the expression in the round exception, as
+    # it's too slow
+    s = Symbol('bad')
+    try:
+        s.round()
+    except TypeError as e:
+        assert 'bad' not in str(e)
+    else:
+        # Did not raise
+        raise AssertionError("Did not raise")
+
+
+def test_extract_branch_factor():
+    assert exp_polar(2.0*I*pi).extract_branch_factor() == (1, 1)
+
+
+def test_identity_removal():
+    assert Add.make_args(x + 0) == (x,)
+    assert Mul.make_args(x*1) == (x,)
+
+
+def test_float_0():
+    assert Float(0.0) + 1 == Float(1.0)
+
+
+@XFAIL
+def test_float_0_fail():
+    assert Float(0.0)*x == Float(0.0)
+    assert (x + Float(0.0)).is_Add
+
+
+def test_issue_6325():
+    ans = (b**2 + z**2 - (b*(a + b*t) + z*(c + t*z))**2/(
+        (a + b*t)**2 + (c + t*z)**2))/sqrt((a + b*t)**2 + (c + t*z)**2)
+    e = sqrt((a + b*t)**2 + (c + z*t)**2)
+    assert diff(e, t, 2) == ans
+    assert e.diff(t, 2) == ans
+    assert diff(e, t, 2, simplify=False) != ans
+
+
+def test_issue_7426():
+    f1 = a % c
+    f2 = x % z
+    assert f1.equals(f2) is None
+
+
+def test_issue_11122():
+    x = Symbol('x', extended_positive=False)
+    assert unchanged(Gt, x, 0)  # (x > 0)
+    # (x > 0) should remain unevaluated after PR #16956
+
+    x = Symbol('x', positive=False, real=True)
+    assert (x > 0) is S.false
+
+
+def test_issue_10651():
+    x = Symbol('x', real=True)
+    e1 = (-1 + x)/(1 - x)
+    e3 = (4*x**2 - 4)/((1 - x)*(1 + x))
+    e4 = 1/(cos(x)**2) - (tan(x))**2
+    x = Symbol('x', positive=True)
+    e5 = (1 + x)/x
+    assert e1.is_constant() is None
+    assert e3.is_constant() is None
+    assert e4.is_constant() is None
+    assert e5.is_constant() is False
+
+
+def test_issue_10161():
+    x = symbols('x', real=True)
+    assert x*abs(x)*abs(x) == x**3
+
+
+def test_issue_10755():
+    x = symbols('x')
+    raises(TypeError, lambda: int(log(x)))
+    raises(TypeError, lambda: log(x).round(2))
+
+
+def test_issue_11877():
+    x = symbols('x')
+    assert integrate(log(S.Half - x), (x, 0, S.Half)) == Rational(-1, 2) -log(2)/2
+
+
+def test_normal():
+    x = symbols('x')
+    e = Mul(S.Half, 1 + x, evaluate=False)
+    assert e.normal() == e
+
+
+def test_expr():
+    x = symbols('x')
+    raises(TypeError, lambda: tan(x).series(x, 2, oo, "+"))
+
+
+def test_ExprBuilder():
+    eb = ExprBuilder(Mul)
+    eb.args.extend([x, x])
+    assert eb.build() == x**2
+
+
+def test_issue_22020():
+    from sympy.parsing.sympy_parser import parse_expr
+    x = parse_expr("log((2*V/3-V)/C)/-(R+r)*C")
+    y = parse_expr("log((2*V/3-V)/C)/-(R+r)*2")
+    assert x.equals(y) is False
+
+
+def test_non_string_equality():
+    # Expressions should not compare equal to strings
+    x = symbols('x')
+    one = sympify(1)
+    assert (x == 'x') is False
+    assert (x != 'x') is True
+    assert (one == '1') is False
+    assert (one != '1') is True
+    assert (x + 1 == 'x + 1') is False
+    assert (x + 1 != 'x + 1') is True
+
+    # Make sure == doesn't try to convert the resulting expression to a string
+    # (e.g., by calling sympify() instead of _sympify())
+
+    class BadRepr:
+        def __repr__(self):
+            raise RuntimeError
+
+    assert (x == BadRepr()) is False
+    assert (x != BadRepr()) is True
+
+
+def test_21494():
+    from sympy.testing.pytest import warns_deprecated_sympy
+
+    with warns_deprecated_sympy():
+        assert x.expr_free_symbols == {x}
+
+    with warns_deprecated_sympy():
+        assert Basic().expr_free_symbols == set()
+
+    with warns_deprecated_sympy():
+        assert S(2).expr_free_symbols == {S(2)}
+
+    with warns_deprecated_sympy():
+        assert Indexed("A", x).expr_free_symbols == {Indexed("A", x)}
+
+    with warns_deprecated_sympy():
+        assert Subs(x, x, 0).expr_free_symbols == set()
+
+
+def test_Expr__eq__iterable_handling():
+    assert x != range(3)
+
+
+def test_format():
+    assert '{:1.2f}'.format(S.Zero) == '0.00'
+    assert '{:+3.0f}'.format(S(3)) == ' +3'
+    assert '{:23.20f}'.format(pi) == ' 3.14159265358979323846'
+    assert '{:50.48f}'.format(exp(sin(1))) == '2.319776824715853173956590377503266813254904772376'

env-llmeval/lib/python3.10/site-packages/sympy/core/tests/test_exprtools.py

@@ -0,0 +1,493 @@
+"""Tests for tools for manipulating of large commutative expressions. """
+
+from sympy.concrete.summations import Sum
+from sympy.core.add import Add
+from sympy.core.basic import Basic
+from sympy.core.containers import (Dict, Tuple)
+from sympy.core.function import Function
+from sympy.core.mul import Mul
+from sympy.core.numbers import (I, Rational, oo)
+from sympy.core.singleton import S
+from sympy.core.symbol import (Dummy, Symbol, symbols)
+from sympy.functions.elementary.exponential import (exp, log)
+from sympy.functions.elementary.miscellaneous import (root, sqrt)
+from sympy.functions.elementary.trigonometric import (cos, sin)
+from sympy.integrals.integrals import Integral
+from sympy.series.order import O
+from sympy.sets.sets import Interval
+from sympy.simplify.radsimp import collect
+from sympy.simplify.simplify import simplify
+from sympy.core.exprtools import (decompose_power, Factors, Term, _gcd_terms,
+                                  gcd_terms, factor_terms, factor_nc, _mask_nc,
+                                  _monotonic_sign)
+from sympy.core.mul import _keep_coeff as _keep_coeff
+from sympy.simplify.cse_opts import sub_pre
+from sympy.testing.pytest import raises
+
+from sympy.abc import a, b, t, x, y, z
+
+
+def test_decompose_power():
+    assert decompose_power(x) == (x, 1)
+    assert decompose_power(x**2) == (x, 2)
+    assert decompose_power(x**(2*y)) == (x**y, 2)
+    assert decompose_power(x**(2*y/3)) == (x**(y/3), 2)
+    assert decompose_power(x**(y*Rational(2, 3))) == (x**(y/3), 2)
+
+
+def test_Factors():
+    assert Factors() == Factors({}) == Factors(S.One)
+    assert Factors().as_expr() is S.One
+    assert Factors({x: 2, y: 3, sin(x): 4}).as_expr() == x**2*y**3*sin(x)**4
+    assert Factors(S.Infinity) == Factors({oo: 1})
+    assert Factors(S.NegativeInfinity) == Factors({oo: 1, -1: 1})
+    # issue #18059:
+    assert Factors((x**2)**S.Half).as_expr() == (x**2)**S.Half
+
+    a = Factors({x: 5, y: 3, z: 7})
+    b = Factors({      y: 4, z: 3, t: 10})
+
+    assert a.mul(b) == a*b == Factors({x: 5, y: 7, z: 10, t: 10})
+
+    assert a.div(b) == divmod(a, b) == \
+        (Factors({x: 5, z: 4}), Factors({y: 1, t: 10}))
+    assert a.quo(b) == a/b == Factors({x: 5, z: 4})
+    assert a.rem(b) == a % b == Factors({y: 1, t: 10})
+
+    assert a.pow(3) == a**3 == Factors({x: 15, y: 9, z: 21})
+    assert b.pow(3) == b**3 == Factors({y: 12, z: 9, t: 30})
+
+    assert a.gcd(b) == Factors({y: 3, z: 3})
+    assert a.lcm(b) == Factors({x: 5, y: 4, z: 7, t: 10})
+
+    a = Factors({x: 4, y: 7, t: 7})
+    b = Factors({z: 1, t: 3})
+
+    assert a.normal(b) == (Factors({x: 4, y: 7, t: 4}), Factors({z: 1}))
+
+    assert Factors(sqrt(2)*x).as_expr() == sqrt(2)*x
+
+    assert Factors(-I)*I == Factors()
+    assert Factors({S.NegativeOne: S(3)})*Factors({S.NegativeOne: S.One, I: S(5)}) == \
+        Factors(I)
+    assert Factors(sqrt(I)*I) == Factors(I**(S(3)/2)) == Factors({I: S(3)/2})
+    assert Factors({I: S(3)/2}).as_expr() == I**(S(3)/2)
+
+    assert Factors(S(2)**x).div(S(3)**x) == \
+        (Factors({S(2): x}), Factors({S(3): x}))
+    assert Factors(2**(2*x + 2)).div(S(8)) == \
+        (Factors({S(2): 2*x + 2}), Factors({S(8): S.One}))
+
+    # coverage
+    # /!\ things break if this is not True
+    assert Factors({S.NegativeOne: Rational(3, 2)}) == Factors({I: S.One, S.NegativeOne: S.One})
+    assert Factors({I: S.One, S.NegativeOne: Rational(1, 3)}).as_expr() == I*(-1)**Rational(1, 3)
+
+    assert Factors(-1.) == Factors({S.NegativeOne: S.One, S(1.): 1})
+    assert Factors(-2.) == Factors({S.NegativeOne: S.One, S(2.): 1})
+    assert Factors((-2.)**x) == Factors({S(-2.): x})
+    assert Factors(S(-2)) == Factors({S.NegativeOne: S.One, S(2): 1})
+    assert Factors(S.Half) == Factors({S(2): -S.One})
+    assert Factors(Rational(3, 2)) == Factors({S(3): S.One, S(2): S.NegativeOne})
+    assert Factors({I: S.One}) == Factors(I)
+    assert Factors({-1.0: 2, I: 1}) == Factors({S(1.0): 1, I: 1})
+    assert Factors({S.NegativeOne: Rational(-3, 2)}).as_expr() == I
+    A = symbols('A', commutative=False)
+    assert Factors(2*A**2) == Factors({S(2): 1, A**2: 1})
+    assert Factors(I) == Factors({I: S.One})
+    assert Factors(x).normal(S(2)) == (Factors(x), Factors(S(2)))
+    assert Factors(x).normal(S.Zero) == (Factors(), Factors(S.Zero))
+    raises(ZeroDivisionError, lambda: Factors(x).div(S.Zero))
+    assert Factors(x).mul(S(2)) == Factors(2*x)
+    assert Factors(x).mul(S.Zero).is_zero
+    assert Factors(x).mul(1/x).is_one
+    assert Factors(x**sqrt(2)**3).as_expr() == x**(2*sqrt(2))
+    assert Factors(x)**Factors(S(2)) == Factors(x**2)
+    assert Factors(x).gcd(S.Zero) == Factors(x)
+    assert Factors(x).lcm(S.Zero).is_zero
+    assert Factors(S.Zero).div(x) == (Factors(S.Zero), Factors())
+    assert Factors(x).div(x) == (Factors(), Factors())
+    assert Factors({x: .2})/Factors({x: .2}) == Factors()
+    assert Factors(x) != Factors()
+    assert Factors(S.Zero).normal(x) == (Factors(S.Zero), Factors())
+    n, d = x**(2 + y), x**2
+    f = Factors(n)
+    assert f.div(d) == f.normal(d) == (Factors(x**y), Factors())
+    assert f.gcd(d) == Factors()
+    d = x**y
+    assert f.div(d) == f.normal(d) == (Factors(x**2), Factors())
+    assert f.gcd(d) == Factors(d)
+    n = d = 2**x
+    f = Factors(n)
+    assert f.div(d) == f.normal(d) == (Factors(), Factors())
+    assert f.gcd(d) == Factors(d)
+    n, d = 2**x, 2**y
+    f = Factors(n)
+    assert f.div(d) == f.normal(d) == (Factors({S(2): x}), Factors({S(2): y}))
+    assert f.gcd(d) == Factors()
+
+    # extraction of constant only
+    n = x**(x + 3)
+    assert Factors(n).normal(x**-3) == (Factors({x: x + 6}), Factors({}))
+    assert Factors(n).normal(x**3) == (Factors({x: x}), Factors({}))
+    assert Factors(n).normal(x**4) == (Factors({x: x}), Factors({x: 1}))
+    assert Factors(n).normal(x**(y - 3)) == \
+        (Factors({x: x + 6}), Factors({x: y}))
+    assert Factors(n).normal(x**(y + 3)) == (Factors({x: x}), Factors({x: y}))
+    assert Factors(n).normal(x**(y + 4)) == \
+        (Factors({x: x}), Factors({x: y + 1}))
+
+    assert Factors(n).div(x**-3) == (Factors({x: x + 6}), Factors({}))
+    assert Factors(n).div(x**3) == (Factors({x: x}), Factors({}))
+    assert Factors(n).div(x**4) == (Factors({x: x}), Factors({x: 1}))
+    assert Factors(n).div(x**(y - 3)) == \
+        (Factors({x: x + 6}), Factors({x: y}))
+    assert Factors(n).div(x**(y + 3)) == (Factors({x: x}), Factors({x: y}))
+    assert Factors(n).div(x**(y + 4)) == \
+        (Factors({x: x}), Factors({x: y + 1}))
+
+    assert Factors(3 * x / 2) == Factors({3: 1, 2: -1, x: 1})
+    assert Factors(x * x / y) == Factors({x: 2, y: -1})
+    assert Factors(27 * x / y**9) == Factors({27: 1, x: 1, y: -9})
+
+
+def test_Term():
+    a = Term(4*x*y**2/z/t**3)
+    b = Term(2*x**3*y**5/t**3)
+
+    assert a == Term(4, Factors({x: 1, y: 2}), Factors({z: 1, t: 3}))
+    assert b == Term(2, Factors({x: 3, y: 5}), Factors({t: 3}))
+
+    assert a.as_expr() == 4*x*y**2/z/t**3
+    assert b.as_expr() == 2*x**3*y**5/t**3
+
+    assert a.inv() == \
+        Term(S.One/4, Factors({z: 1, t: 3}), Factors({x: 1, y: 2}))
+    assert b.inv() == Term(S.Half, Factors({t: 3}), Factors({x: 3, y: 5}))
+
+    assert a.mul(b) == a*b == \
+        Term(8, Factors({x: 4, y: 7}), Factors({z: 1, t: 6}))
+    assert a.quo(b) == a/b == Term(2, Factors({}), Factors({x: 2, y: 3, z: 1}))
+
+    assert a.pow(3) == a**3 == \
+        Term(64, Factors({x: 3, y: 6}), Factors({z: 3, t: 9}))
+    assert b.pow(3) == b**3 == Term(8, Factors({x: 9, y: 15}), Factors({t: 9}))
+
+    assert a.pow(-3) == a**(-3) == \
+        Term(S.One/64, Factors({z: 3, t: 9}), Factors({x: 3, y: 6}))
+    assert b.pow(-3) == b**(-3) == \
+        Term(S.One/8, Factors({t: 9}), Factors({x: 9, y: 15}))
+
+    assert a.gcd(b) == Term(2, Factors({x: 1, y: 2}), Factors({t: 3}))
+    assert a.lcm(b) == Term(4, Factors({x: 3, y: 5}), Factors({z: 1, t: 3}))
+
+    a = Term(4*x*y**2/z/t**3)
+    b = Term(2*x**3*y**5*t**7)
+
+    assert a.mul(b) == Term(8, Factors({x: 4, y: 7, t: 4}), Factors({z: 1}))
+
+    assert Term((2*x + 2)**3) == Term(8, Factors({x + 1: 3}), Factors({}))
+    assert Term((2*x + 2)*(3*x + 6)**2) == \
+        Term(18, Factors({x + 1: 1, x + 2: 2}), Factors({}))
+
+
+def test_gcd_terms():
+    f = 2*(x + 1)*(x + 4)/(5*x**2 + 5) + (2*x + 2)*(x + 5)/(x**2 + 1)/5 + \
+        (2*x + 2)*(x + 6)/(5*x**2 + 5)
+
+    assert _gcd_terms(f) == ((Rational(6, 5))*((1 + x)/(1 + x**2)), 5 + x, 1)
+    assert _gcd_terms(Add.make_args(f)) == \
+        ((Rational(6, 5))*((1 + x)/(1 + x**2)), 5 + x, 1)
+
+    newf = (Rational(6, 5))*((1 + x)*(5 + x)/(1 + x**2))
+    assert gcd_terms(f) == newf
+    args = Add.make_args(f)
+    # non-Basic sequences of terms treated as terms of Add
+    assert gcd_terms(list(args)) == newf
+    assert gcd_terms(tuple(args)) == newf
+    assert gcd_terms(set(args)) == newf
+    # but a Basic sequence is treated as a container
+    assert gcd_terms(Tuple(*args)) != newf
+    assert gcd_terms(Basic(Tuple(S(1), 3*y + 3*x*y), Tuple(S(1), S(3)))) == \
+        Basic(Tuple(S(1), 3*y*(x + 1)), Tuple(S(1), S(3)))
+    # but we shouldn't change keys of a dictionary or some may be lost
+    assert gcd_terms(Dict((x*(1 + y), S(2)), (x + x*y, y + x*y))) == \
+        Dict({x*(y + 1): S(2), x + x*y: y*(1 + x)})
+
+    assert gcd_terms((2*x + 2)**3 + (2*x + 2)**2) == 4*(x + 1)**2*(2*x + 3)
+
+    assert gcd_terms(0) == 0
+    assert gcd_terms(1) == 1
+    assert gcd_terms(x) == x
+    assert gcd_terms(2 + 2*x) == Mul(2, 1 + x, evaluate=False)
+    arg = x*(2*x + 4*y)
+    garg = 2*x*(x + 2*y)
+    assert gcd_terms(arg) == garg
+    assert gcd_terms(sin(arg)) == sin(garg)
+
+    # issue 6139-like
+    alpha, alpha1, alpha2, alpha3 = symbols('alpha:4')
+    a = alpha**2 - alpha*x**2 + alpha + x**3 - x*(alpha + 1)
+    rep = (alpha, (1 + sqrt(5))/2 + alpha1*x + alpha2*x**2 + alpha3*x**3)
+    s = (a/(x - alpha)).subs(*rep).series(x, 0, 1)
+    assert simplify(collect(s, x)) == -sqrt(5)/2 - Rational(3, 2) + O(x)
+
+    # issue 5917
+    assert _gcd_terms([S.Zero, S.Zero]) == (0, 0, 1)
+    assert _gcd_terms([2*x + 4]) == (2, x + 2, 1)
+
+    eq = x/(x + 1/x)
+    assert gcd_terms(eq, fraction=False) == eq
+    eq = x/2/y + 1/x/y
+    assert gcd_terms(eq, fraction=True, clear=True) == \
+        (x**2 + 2)/(2*x*y)
+    assert gcd_terms(eq, fraction=True, clear=False) == \
+        (x**2/2 + 1)/(x*y)
+    assert gcd_terms(eq, fraction=False, clear=True) == \
+        (x + 2/x)/(2*y)
+    assert gcd_terms(eq, fraction=False, clear=False) == \
+        (x/2 + 1/x)/y
+
+
+def test_factor_terms():
+    A = Symbol('A', commutative=False)
+    assert factor_terms(9*(x + x*y + 1) + (3*x + 3)**(2 + 2*x)) == \
+        9*x*y + 9*x + _keep_coeff(S(3), x + 1)**_keep_coeff(S(2), x + 1) + 9
+    assert factor_terms(9*(x + x*y + 1) + (3)**(2 + 2*x)) == \
+        _keep_coeff(S(9), 3**(2*x) + x*y + x + 1)
+    assert factor_terms(3**(2 + 2*x) + a*3**(2 + 2*x)) == \
+        9*3**(2*x)*(a + 1)
+    assert factor_terms(x + x*A) == \
+        x*(1 + A)
+    assert factor_terms(sin(x + x*A)) == \
+        sin(x*(1 + A))
+    assert factor_terms((3*x + 3)**((2 + 2*x)/3)) == \
+        _keep_coeff(S(3), x + 1)**_keep_coeff(Rational(2, 3), x + 1)
+    assert factor_terms(x + (x*y + x)**(3*x + 3)) == \
+        x + (x*(y + 1))**_keep_coeff(S(3), x + 1)
+    assert factor_terms(a*(x + x*y) + b*(x*2 + y*x*2)) == \
+        x*(a + 2*b)*(y + 1)
+    i = Integral(x, (x, 0, oo))
+    assert factor_terms(i) == i
+
+    assert factor_terms(x/2 + y) == x/2 + y
+    # fraction doesn't apply to integer denominators
+    assert factor_terms(x/2 + y, fraction=True) == x/2 + y
+    # clear *does* apply to the integer denominators
+    assert factor_terms(x/2 + y, clear=True) == Mul(S.Half, x + 2*y, evaluate=False)
+
+    # check radical extraction
+    eq = sqrt(2) + sqrt(10)
+    assert factor_terms(eq) == eq
+    assert factor_terms(eq, radical=True) == sqrt(2)*(1 + sqrt(5))
+    eq = root(-6, 3) + root(6, 3)
+    assert factor_terms(eq, radical=True) == 6**(S.One/3)*(1 + (-1)**(S.One/3))
+
+    eq = [x + x*y]
+    ans = [x*(y + 1)]
+    for c in [list, tuple, set]:
+        assert factor_terms(c(eq)) == c(ans)
+    assert factor_terms(Tuple(x + x*y)) == Tuple(x*(y + 1))
+    assert factor_terms(Interval(0, 1)) == Interval(0, 1)
+    e = 1/sqrt(a/2 + 1)
+    assert factor_terms(e, clear=False) == 1/sqrt(a/2 + 1)
+    assert factor_terms(e, clear=True) == sqrt(2)/sqrt(a + 2)
+
+    eq = x/(x + 1/x) + 1/(x**2 + 1)
+    assert factor_terms(eq, fraction=False) == eq
+    assert factor_terms(eq, fraction=True) == 1
+
+    assert factor_terms((1/(x**3 + x**2) + 2/x**2)*y) == \
+        y*(2 + 1/(x + 1))/x**2
+
+    # if not True, then processesing for this in factor_terms is not necessary
+    assert gcd_terms(-x - y) == -x - y
+    assert factor_terms(-x - y) == Mul(-1, x + y, evaluate=False)
+
+    # if not True, then "special" processesing in factor_terms is not necessary
+    assert gcd_terms(exp(Mul(-1, x + 1))) == exp(-x - 1)
+    e = exp(-x - 2) + x
+    assert factor_terms(e) == exp(Mul(-1, x + 2, evaluate=False)) + x
+    assert factor_terms(e, sign=False) == e
+    assert factor_terms(exp(-4*x - 2) - x) == -x + exp(Mul(-2, 2*x + 1, evaluate=False))
+
+    # sum/integral tests
+    for F in (Sum, Integral):
+        assert factor_terms(F(x, (y, 1, 10))) == x * F(1, (y, 1, 10))
+        assert factor_terms(F(x, (y, 1, 10)) + x) == x * (1 + F(1, (y, 1, 10)))
+        assert factor_terms(F(x*y + x*y**2, (y, 1, 10))) == x*F(y*(y + 1), (y, 1, 10))
+
+    # expressions involving Pow terms with base 0
+    assert factor_terms(0**(x - 2) - 1) == 0**(x - 2) - 1
+    assert factor_terms(0**(x + 2) - 1) == 0**(x + 2) - 1
+    assert factor_terms((0**(x + 2) - 1).subs(x,-2)) == 0
+
+
+def test_xreplace():
+    e = Mul(2, 1 + x, evaluate=False)
+    assert e.xreplace({}) == e
+    assert e.xreplace({y: x}) == e
+
+
+def test_factor_nc():
+    x, y = symbols('x,y')
+    k = symbols('k', integer=True)
+    n, m, o = symbols('n,m,o', commutative=False)
+
+    # mul and multinomial expansion is needed
+    from sympy.core.function import _mexpand
+    e = x*(1 + y)**2
+    assert _mexpand(e) == x + x*2*y + x*y**2
+
+    def factor_nc_test(e):
+        ex = _mexpand(e)
+        assert ex.is_Add
+        f = factor_nc(ex)
+        assert not f.is_Add and _mexpand(f) == ex
+
+    factor_nc_test(x*(1 + y))
+    factor_nc_test(n*(x + 1))
+    factor_nc_test(n*(x + m))
+    factor_nc_test((x + m)*n)
+    factor_nc_test(n*m*(x*o + n*o*m)*n)
+    s = Sum(x, (x, 1, 2))
+    factor_nc_test(x*(1 + s))
+    factor_nc_test(x*(1 + s)*s)
+    factor_nc_test(x*(1 + sin(s)))
+    factor_nc_test((1 + n)**2)
+
+    factor_nc_test((x + n)*(x + m)*(x + y))
+    factor_nc_test(x*(n*m + 1))
+    factor_nc_test(x*(n*m + x))
+    factor_nc_test(x*(x*n*m + 1))
+    factor_nc_test(n*(m/x + o))
+    factor_nc_test(m*(n + o/2))
+    factor_nc_test(x*n*(x*m + 1))
+    factor_nc_test(x*(m*n + x*n*m))
+    factor_nc_test(n*(1 - m)*n**2)
+
+    factor_nc_test((n + m)**2)
+    factor_nc_test((n - m)*(n + m)**2)
+    factor_nc_test((n + m)**2*(n - m))
+    factor_nc_test((m - n)*(n + m)**2*(n - m))
+
+    assert factor_nc(n*(n + n*m)) == n**2*(1 + m)
+    assert factor_nc(m*(m*n + n*m*n**2)) == m*(m + n*m*n)*n
+    eq = m*sin(n) - sin(n)*m
+    assert factor_nc(eq) == eq
+
+    # for coverage:
+    from sympy.physics.secondquant import Commutator
+    from sympy.polys.polytools import factor
+    eq = 1 + x*Commutator(m, n)
+    assert factor_nc(eq) == eq
+    eq = x*Commutator(m, n) + x*Commutator(m, o)*Commutator(m, n)
+    assert factor(eq) == x*(1 + Commutator(m, o))*Commutator(m, n)
+
+    # issue 6534
+    assert (2*n + 2*m).factor() == 2*(n + m)
+
+    # issue 6701
+    _n = symbols('nz', zero=False, commutative=False)
+    assert factor_nc(_n**k + _n**(k + 1)) == _n**k*(1 + _n)
+    assert factor_nc((m*n)**k + (m*n)**(k + 1)) == (1 + m*n)*(m*n)**k
+
+    # issue 6918
+    assert factor_nc(-n*(2*x**2 + 2*x)) == -2*n*x*(x + 1)
+
+
+def test_issue_6360():
+    a, b = symbols("a b")
+    apb = a + b
+    eq = apb + apb**2*(-2*a - 2*b)
+    assert factor_terms(sub_pre(eq)) == a + b - 2*(a + b)**3
+
+
+def test_issue_7903():
+    a = symbols(r'a', real=True)
+    t = exp(I*cos(a)) + exp(-I*sin(a))
+    assert t.simplify()
+
+def test_issue_8263():
+    F, G = symbols('F, G', commutative=False, cls=Function)
+    x, y = symbols('x, y')
+    expr, dummies, _ = _mask_nc(F(x)*G(y) - G(y)*F(x))
+    for v in dummies.values():
+        assert not v.is_commutative
+    assert not expr.is_zero
+
+def test_monotonic_sign():
+    F = _monotonic_sign
+    x = symbols('x')
+    assert F(x) is None
+    assert F(-x) is None
+    assert F(Dummy(prime=True)) == 2
+    assert F(Dummy(prime=True, odd=True)) == 3
+    assert F(Dummy(composite=True)) == 4
+    assert F(Dummy(composite=True, odd=True)) == 9
+    assert F(Dummy(positive=True, integer=True)) == 1
+    assert F(Dummy(positive=True, even=True)) == 2
+    assert F(Dummy(positive=True, even=True, prime=False)) == 4
+    assert F(Dummy(negative=True, integer=True)) == -1
+    assert F(Dummy(negative=True, even=True)) == -2
+    assert F(Dummy(zero=True)) == 0
+    assert F(Dummy(nonnegative=True)) == 0
+    assert F(Dummy(nonpositive=True)) == 0
+
+    assert F(Dummy(positive=True) + 1).is_positive
+    assert F(Dummy(positive=True, integer=True) - 1).is_nonnegative
+    assert F(Dummy(positive=True) - 1) is None
+    assert F(Dummy(negative=True) + 1) is None
+    assert F(Dummy(negative=True, integer=True) - 1).is_nonpositive
+    assert F(Dummy(negative=True) - 1).is_negative
+    assert F(-Dummy(positive=True) + 1) is None
+    assert F(-Dummy(positive=True, integer=True) - 1).is_negative
+    assert F(-Dummy(positive=True) - 1).is_negative
+    assert F(-Dummy(negative=True) + 1).is_positive
+    assert F(-Dummy(negative=True, integer=True) - 1).is_nonnegative
+    assert F(-Dummy(negative=True) - 1) is None
+    x = Dummy(negative=True)
+    assert F(x**3).is_nonpositive
+    assert F(x**3 + log(2)*x - 1).is_negative
+    x = Dummy(positive=True)
+    assert F(-x**3).is_nonpositive
+
+    p = Dummy(positive=True)
+    assert F(1/p).is_positive
+    assert F(p/(p + 1)).is_positive
+    p = Dummy(nonnegative=True)
+    assert F(p/(p + 1)).is_nonnegative
+    p = Dummy(positive=True)
+    assert F(-1/p).is_negative
+    p = Dummy(nonpositive=True)
+    assert F(p/(-p + 1)).is_nonpositive
+
+    p = Dummy(positive=True, integer=True)
+    q = Dummy(positive=True, integer=True)
+    assert F(-2/p/q).is_negative
+    assert F(-2/(p - 1)/q) is None
+
+    assert F((p - 1)*q + 1).is_positive
+    assert F(-(p - 1)*q - 1).is_negative
+
+def test_issue_17256():
+    from sympy.sets.fancysets import Range
+    x = Symbol('x')
+    s1 = Sum(x + 1, (x, 1, 9))
+    s2 = Sum(x + 1, (x, Range(1, 10)))
+    a = Symbol('a')
+    r1 = s1.xreplace({x:a})
+    r2 = s2.xreplace({x:a})
+
+    assert r1.doit() == r2.doit()
+    s1 = Sum(x + 1, (x, 0, 9))
+    s2 = Sum(x + 1, (x, Range(10)))
+    a = Symbol('a')
+    r1 = s1.xreplace({x:a})
+    r2 = s2.xreplace({x:a})
+    assert r1 == r2
+
+def test_issue_21623():
+    from sympy.matrices.expressions.matexpr import MatrixSymbol
+    M = MatrixSymbol('X', 2, 2)
+    assert gcd_terms(M[0,0], 1) == M[0,0]

env-llmeval/lib/python3.10/site-packages/sympy/core/tests/test_facts.py

@@ -0,0 +1,312 @@
+from sympy.core.facts import (deduce_alpha_implications,
+        apply_beta_to_alpha_route, rules_2prereq, FactRules, FactKB)
+from sympy.core.logic import And, Not
+from sympy.testing.pytest import raises
+
+T = True
+F = False
+U = None
+
+
+def test_deduce_alpha_implications():
+    def D(i):
+        I = deduce_alpha_implications(i)
+        P = rules_2prereq({
+            (k, True): {(v, True) for v in S} for k, S in I.items()})
+        return I, P
+
+    # transitivity
+    I, P = D([('a', 'b'), ('b', 'c')])
+    assert I == {'a': {'b', 'c'}, 'b': {'c'}, Not('b'):
+        {Not('a')}, Not('c'): {Not('a'), Not('b')}}
+    assert P == {'a': {'b', 'c'}, 'b': {'a', 'c'}, 'c': {'a', 'b'}}
+
+    # Duplicate entry
+    I, P = D([('a', 'b'), ('b', 'c'), ('b', 'c')])
+    assert I == {'a': {'b', 'c'}, 'b': {'c'}, Not('b'): {Not('a')}, Not('c'): {Not('a'), Not('b')}}
+    assert P == {'a': {'b', 'c'}, 'b': {'a', 'c'}, 'c': {'a', 'b'}}
+
+    # see if it is tolerant to cycles
+    assert D([('a', 'a'), ('a', 'a')]) == ({}, {})
+    assert D([('a', 'b'), ('b', 'a')]) == (
+        {'a': {'b'}, 'b': {'a'}, Not('a'): {Not('b')}, Not('b'): {Not('a')}},
+        {'a': {'b'}, 'b': {'a'}})
+
+    # see if it catches inconsistency
+    raises(ValueError, lambda: D([('a', Not('a'))]))
+    raises(ValueError, lambda: D([('a', 'b'), ('b', Not('a'))]))
+    raises(ValueError, lambda: D([('a', 'b'), ('b', 'c'), ('b', 'na'),
+           ('na', Not('a'))]))
+
+    # see if it handles implications with negations
+    I, P = D([('a', Not('b')), ('c', 'b')])
+    assert I == {'a': {Not('b'), Not('c')}, 'b': {Not('a')}, 'c': {'b', Not('a')}, Not('b'): {Not('c')}}
+    assert P == {'a': {'b', 'c'}, 'b': {'a', 'c'}, 'c': {'a', 'b'}}
+    I, P = D([(Not('a'), 'b'), ('a', 'c')])
+    assert I == {'a': {'c'}, Not('a'): {'b'}, Not('b'): {'a',
+    'c'}, Not('c'): {Not('a'), 'b'},}
+    assert P == {'a': {'b', 'c'}, 'b': {'a', 'c'}, 'c': {'a', 'b'}}
+
+
+    # Long deductions
+    I, P = D([('a', 'b'), ('b', 'c'), ('c', 'd'), ('d', 'e')])
+    assert I == {'a': {'b', 'c', 'd', 'e'}, 'b': {'c', 'd', 'e'},
+        'c': {'d', 'e'}, 'd': {'e'}, Not('b'): {Not('a')},
+        Not('c'): {Not('a'), Not('b')}, Not('d'): {Not('a'), Not('b'),
+            Not('c')}, Not('e'): {Not('a'), Not('b'), Not('c'), Not('d')}}
+    assert P == {'a': {'b', 'c', 'd', 'e'}, 'b': {'a', 'c', 'd',
+        'e'}, 'c': {'a', 'b', 'd', 'e'}, 'd': {'a', 'b', 'c', 'e'},
+        'e': {'a', 'b', 'c', 'd'}}
+
+    # something related to real-world
+    I, P = D([('rat', 'real'), ('int', 'rat')])
+
+    assert I == {'int': {'rat', 'real'}, 'rat': {'real'},
+        Not('real'): {Not('rat'), Not('int')}, Not('rat'): {Not('int')}}
+    assert P == {'rat': {'int', 'real'}, 'real': {'int', 'rat'},
+        'int': {'rat', 'real'}}
+
+
+# TODO move me to appropriate place
+def test_apply_beta_to_alpha_route():
+    APPLY = apply_beta_to_alpha_route
+
+    # indicates empty alpha-chain with attached beta-rule #bidx
+    def Q(bidx):
+        return (set(), [bidx])
+
+    # x -> a        &(a,b) -> x     --  x -> a
+    A = {'x': {'a'}}
+    B = [(And('a', 'b'), 'x')]
+    assert APPLY(A, B) == {'x': ({'a'}, []), 'a': Q(0), 'b': Q(0)}
+
+    # x -> a        &(a,!x) -> b    --  x -> a
+    A = {'x': {'a'}}
+    B = [(And('a', Not('x')), 'b')]
+    assert APPLY(A, B) == {'x': ({'a'}, []), Not('x'): Q(0), 'a': Q(0)}
+
+    # x -> a b      &(a,b) -> c     --  x -> a b c
+    A = {'x': {'a', 'b'}}
+    B = [(And('a', 'b'), 'c')]
+    assert APPLY(A, B) == \
+        {'x': ({'a', 'b', 'c'}, []), 'a': Q(0), 'b': Q(0)}
+
+    # x -> a        &(a,b) -> y     --  x -> a [#0]
+    A = {'x': {'a'}}
+    B = [(And('a', 'b'), 'y')]
+    assert APPLY(A, B) == {'x': ({'a'}, [0]), 'a': Q(0), 'b': Q(0)}
+
+    # x -> a b c    &(a,b) -> c     --  x -> a b c
+    A = {'x': {'a', 'b', 'c'}}
+    B = [(And('a', 'b'), 'c')]
+    assert APPLY(A, B) == \
+        {'x': ({'a', 'b', 'c'}, []), 'a': Q(0), 'b': Q(0)}
+
+    # x -> a b      &(a,b,c) -> y   --  x -> a b [#0]
+    A = {'x': {'a', 'b'}}
+    B = [(And('a', 'b', 'c'), 'y')]
+    assert APPLY(A, B) == \
+        {'x': ({'a', 'b'}, [0]), 'a': Q(0), 'b': Q(0), 'c': Q(0)}
+
+    # x -> a b      &(a,b) -> c     --  x -> a b c d
+    # c -> d                            c -> d
+    A = {'x': {'a', 'b'}, 'c': {'d'}}
+    B = [(And('a', 'b'), 'c')]
+    assert APPLY(A, B) == {'x': ({'a', 'b', 'c', 'd'}, []),
+        'c': ({'d'}, []), 'a': Q(0), 'b': Q(0)}
+
+    # x -> a b      &(a,b) -> c     --  x -> a b c d e
+    # c -> d        &(c,d) -> e         c -> d e
+    A = {'x': {'a', 'b'}, 'c': {'d'}}
+    B = [(And('a', 'b'), 'c'), (And('c', 'd'), 'e')]
+    assert APPLY(A, B) == {'x': ({'a', 'b', 'c', 'd', 'e'}, []),
+        'c': ({'d', 'e'}, []), 'a': Q(0), 'b': Q(0), 'd': Q(1)}
+
+    # x -> a b      &(a,y) -> z     --  x -> a b y z
+    #               &(a,b) -> y
+    A = {'x': {'a', 'b'}}
+    B = [(And('a', 'y'), 'z'), (And('a', 'b'), 'y')]
+    assert APPLY(A, B) == {'x': ({'a', 'b', 'y', 'z'}, []),
+        'a': (set(), [0, 1]), 'y': Q(0), 'b': Q(1)}
+
+    # x -> a b      &(a,!b) -> c    --  x -> a b
+    A = {'x': {'a', 'b'}}
+    B = [(And('a', Not('b')), 'c')]
+    assert APPLY(A, B) == \
+        {'x': ({'a', 'b'}, []), 'a': Q(0), Not('b'): Q(0)}
+
+    # !x -> !a !b   &(!a,b) -> c    --  !x -> !a !b
+    A = {Not('x'): {Not('a'), Not('b')}}
+    B = [(And(Not('a'), 'b'), 'c')]
+    assert APPLY(A, B) == \
+        {Not('x'): ({Not('a'), Not('b')}, []), Not('a'): Q(0), 'b': Q(0)}
+
+    # x -> a b      &(b,c) -> !a    --  x -> a b
+    A = {'x': {'a', 'b'}}
+    B = [(And('b', 'c'), Not('a'))]
+    assert APPLY(A, B) == {'x': ({'a', 'b'}, []), 'b': Q(0), 'c': Q(0)}
+
+    # x -> a b      &(a, b) -> c    --  x -> a b c p
+    # c -> p a
+    A = {'x': {'a', 'b'}, 'c': {'p', 'a'}}
+    B = [(And('a', 'b'), 'c')]
+    assert APPLY(A, B) == {'x': ({'a', 'b', 'c', 'p'}, []),
+        'c': ({'p', 'a'}, []), 'a': Q(0), 'b': Q(0)}
+
+
+def test_FactRules_parse():
+    f = FactRules('a -> b')
+    assert f.prereq == {'b': {'a'}, 'a': {'b'}}
+
+    f = FactRules('a -> !b')
+    assert f.prereq == {'b': {'a'}, 'a': {'b'}}
+
+    f = FactRules('!a -> b')
+    assert f.prereq == {'b': {'a'}, 'a': {'b'}}
+
+    f = FactRules('!a -> !b')
+    assert f.prereq == {'b': {'a'}, 'a': {'b'}}
+
+    f = FactRules('!z == nz')
+    assert f.prereq == {'z': {'nz'}, 'nz': {'z'}}
+
+
+def test_FactRules_parse2():
+    raises(ValueError, lambda: FactRules('a -> !a'))
+
+
+def test_FactRules_deduce():
+    f = FactRules(['a -> b', 'b -> c', 'b -> d', 'c -> e'])
+
+    def D(facts):
+        kb = FactKB(f)
+        kb.deduce_all_facts(facts)
+        return kb
+
+    assert D({'a': T}) == {'a': T, 'b': T, 'c': T, 'd': T, 'e': T}
+    assert D({'b': T}) == {        'b': T, 'c': T, 'd': T, 'e': T}
+    assert D({'c': T}) == {                'c': T,         'e': T}
+    assert D({'d': T}) == {                        'd': T        }
+    assert D({'e': T}) == {                                'e': T}
+
+    assert D({'a': F}) == {'a': F                                }
+    assert D({'b': F}) == {'a': F, 'b': F                        }
+    assert D({'c': F}) == {'a': F, 'b': F, 'c': F                }
+    assert D({'d': F}) == {'a': F, 'b': F,         'd': F        }
+
+    assert D({'a': U}) == {'a': U}  # XXX ok?
+
+
+def test_FactRules_deduce2():
+    # pos/neg/zero, but the rules are not sufficient to derive all relations
+    f = FactRules(['pos -> !neg', 'pos -> !z'])
+
+    def D(facts):
+        kb = FactKB(f)
+        kb.deduce_all_facts(facts)
+        return kb
+
+    assert D({'pos': T}) == {'pos': T, 'neg': F, 'z': F}
+    assert D({'pos': F}) == {'pos': F                  }
+    assert D({'neg': T}) == {'pos': F, 'neg': T        }
+    assert D({'neg': F}) == {          'neg': F        }
+    assert D({'z': T}) == {'pos': F,           'z': T}
+    assert D({'z': F}) == {                    'z': F}
+
+    # pos/neg/zero. rules are sufficient to derive all relations
+    f = FactRules(['pos -> !neg', 'neg -> !pos', 'pos -> !z', 'neg -> !z'])
+
+    assert D({'pos': T}) == {'pos': T, 'neg': F, 'z': F}
+    assert D({'pos': F}) == {'pos': F                  }
+    assert D({'neg': T}) == {'pos': F, 'neg': T, 'z': F}
+    assert D({'neg': F}) == {          'neg': F        }
+    assert D({'z': T}) == {'pos': F, 'neg': F, 'z': T}
+    assert D({'z': F}) == {                    'z': F}
+
+
+def test_FactRules_deduce_multiple():
+    # deduction that involves _several_ starting points
+    f = FactRules(['real == pos | npos'])
+
+    def D(facts):
+        kb = FactKB(f)
+        kb.deduce_all_facts(facts)
+        return kb
+
+    assert D({'real': T}) == {'real': T}
+    assert D({'real': F}) == {'real': F, 'pos': F, 'npos': F}
+    assert D({'pos': T}) == {'real': T, 'pos': T}
+    assert D({'npos': T}) == {'real': T, 'npos': T}
+
+    # --- key tests below ---
+    assert D({'pos': F, 'npos': F}) == {'real': F, 'pos': F, 'npos': F}
+    assert D({'real': T, 'pos': F}) == {'real': T, 'pos': F, 'npos': T}
+    assert D({'real': T, 'npos': F}) == {'real': T, 'pos': T, 'npos': F}
+
+    assert D({'pos': T, 'npos': F}) == {'real': T, 'pos': T, 'npos': F}
+    assert D({'pos': F, 'npos': T}) == {'real': T, 'pos': F, 'npos': T}
+
+
+def test_FactRules_deduce_multiple2():
+    f = FactRules(['real == neg | zero | pos'])
+
+    def D(facts):
+        kb = FactKB(f)
+        kb.deduce_all_facts(facts)
+        return kb
+
+    assert D({'real': T}) == {'real': T}
+    assert D({'real': F}) == {'real': F, 'neg': F, 'zero': F, 'pos': F}
+    assert D({'neg': T}) == {'real': T, 'neg': T}
+    assert D({'zero': T}) == {'real': T, 'zero': T}
+    assert D({'pos': T}) == {'real': T, 'pos': T}
+
+    # --- key tests below ---
+    assert D({'neg': F, 'zero': F, 'pos': F}) == {'real': F, 'neg': F,
+             'zero': F, 'pos': F}
+    assert D({'real': T, 'neg': F}) == {'real': T, 'neg': F}
+    assert D({'real': T, 'zero': F}) == {'real': T, 'zero': F}
+    assert D({'real': T, 'pos': F}) == {'real': T, 'pos': F}
+
+    assert D({'real': T,           'zero': F, 'pos': F}) == {'real': T,
+             'neg': T, 'zero': F, 'pos': F}
+    assert D({'real': T, 'neg': F,            'pos': F}) == {'real': T,
+             'neg': F, 'zero': T, 'pos': F}
+    assert D({'real': T, 'neg': F, 'zero': F          }) == {'real': T,
+             'neg': F, 'zero': F, 'pos': T}
+
+    assert D({'neg': T, 'zero': F, 'pos': F}) == {'real': T, 'neg': T,
+             'zero': F, 'pos': F}
+    assert D({'neg': F, 'zero': T, 'pos': F}) == {'real': T, 'neg': F,
+             'zero': T, 'pos': F}
+    assert D({'neg': F, 'zero': F, 'pos': T}) == {'real': T, 'neg': F,
+             'zero': F, 'pos': T}
+
+
+def test_FactRules_deduce_base():
+    # deduction that starts from base
+
+    f = FactRules(['real  == neg | zero | pos',
+                   'neg   -> real & !zero & !pos',
+                   'pos   -> real & !zero & !neg'])
+    base = FactKB(f)
+
+    base.deduce_all_facts({'real': T, 'neg': F})
+    assert base == {'real': T, 'neg': F}
+
+    base.deduce_all_facts({'zero': F})
+    assert base == {'real': T, 'neg': F, 'zero': F, 'pos': T}
+
+
+def test_FactRules_deduce_staticext():
+    # verify that static beta-extensions deduction takes place
+    f = FactRules(['real  == neg | zero | pos',
+                   'neg   -> real & !zero & !pos',
+                   'pos   -> real & !zero & !neg',
+                   'nneg  == real & !neg',
+                   'npos  == real & !pos'])
+
+    assert ('npos', True) in f.full_implications[('neg', True)]
+    assert ('nneg', True) in f.full_implications[('pos', True)]
+    assert ('nneg', True) in f.full_implications[('zero', True)]
+    assert ('npos', True) in f.full_implications[('zero', True)]

env-llmeval/lib/python3.10/site-packages/sympy/core/tests/test_function.py

@@ -0,0 +1,1455 @@
+from sympy.concrete.summations import Sum
+from sympy.core.basic import Basic, _aresame
+from sympy.core.cache import clear_cache
+from sympy.core.containers import Dict, Tuple
+from sympy.core.expr import Expr, unchanged
+from sympy.core.function import (Subs, Function, diff, Lambda, expand,
+    nfloat, Derivative)
+from sympy.core.numbers import E, Float, zoo, Rational, pi, I, oo, nan
+from sympy.core.power import Pow
+from sympy.core.relational import Eq
+from sympy.core.singleton import S
+from sympy.core.symbol import symbols, Dummy, Symbol
+from sympy.functions.elementary.complexes import im, re
+from sympy.functions.elementary.exponential import log, exp
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.functions.elementary.piecewise import Piecewise
+from sympy.functions.elementary.trigonometric import sin, cos, acos
+from sympy.functions.special.error_functions import expint
+from sympy.functions.special.gamma_functions import loggamma, polygamma
+from sympy.matrices.dense import Matrix
+from sympy.printing.str import sstr
+from sympy.series.order import O
+from sympy.tensor.indexed import Indexed
+from sympy.core.function import (PoleError, _mexpand, arity,
+        BadSignatureError, BadArgumentsError)
+from sympy.core.parameters import _exp_is_pow
+from sympy.core.sympify import sympify, SympifyError
+from sympy.matrices import MutableMatrix, ImmutableMatrix
+from sympy.sets.sets import FiniteSet
+from sympy.solvers.solveset import solveset
+from sympy.tensor.array import NDimArray
+from sympy.utilities.iterables import subsets, variations
+from sympy.testing.pytest import XFAIL, raises, warns_deprecated_sympy, _both_exp_pow
+
+from sympy.abc import t, w, x, y, z
+f, g, h = symbols('f g h', cls=Function)
+_xi_1, _xi_2, _xi_3 = [Dummy() for i in range(3)]
+
+def test_f_expand_complex():
+    x = Symbol('x', real=True)
+
+    assert f(x).expand(complex=True) == I*im(f(x)) + re(f(x))
+    assert exp(x).expand(complex=True) == exp(x)
+    assert exp(I*x).expand(complex=True) == cos(x) + I*sin(x)
+    assert exp(z).expand(complex=True) == cos(im(z))*exp(re(z)) + \
+        I*sin(im(z))*exp(re(z))
+
+
+def test_bug1():
+    e = sqrt(-log(w))
+    assert e.subs(log(w), -x) == sqrt(x)
+
+    e = sqrt(-5*log(w))
+    assert e.subs(log(w), -x) == sqrt(5*x)
+
+
+def test_general_function():
+    nu = Function('nu')
+
+    e = nu(x)
+    edx = e.diff(x)
+    edy = e.diff(y)
+    edxdx = e.diff(x).diff(x)
+    edxdy = e.diff(x).diff(y)
+    assert e == nu(x)
+    assert edx != nu(x)
+    assert edx == diff(nu(x), x)
+    assert edy == 0
+    assert edxdx == diff(diff(nu(x), x), x)
+    assert edxdy == 0
+
+def test_general_function_nullary():
+    nu = Function('nu')
+
+    e = nu()
+    edx = e.diff(x)
+    edxdx = e.diff(x).diff(x)
+    assert e == nu()
+    assert edx != nu()
+    assert edx == 0
+    assert edxdx == 0
+
+
+def test_derivative_subs_bug():
+    e = diff(g(x), x)
+    assert e.subs(g(x), f(x)) != e
+    assert e.subs(g(x), f(x)) == Derivative(f(x), x)
+    assert e.subs(g(x), -f(x)) == Derivative(-f(x), x)
+
+    assert e.subs(x, y) == Derivative(g(y), y)
+
+
+def test_derivative_subs_self_bug():
+    d = diff(f(x), x)
+
+    assert d.subs(d, y) == y
+
+
+def test_derivative_linearity():
+    assert diff(-f(x), x) == -diff(f(x), x)
+    assert diff(8*f(x), x) == 8*diff(f(x), x)
+    assert diff(8*f(x), x) != 7*diff(f(x), x)
+    assert diff(8*f(x)*x, x) == 8*f(x) + 8*x*diff(f(x), x)
+    assert diff(8*f(x)*y*x, x).expand() == 8*y*f(x) + 8*y*x*diff(f(x), x)
+
+
+def test_derivative_evaluate():
+    assert Derivative(sin(x), x) != diff(sin(x), x)
+    assert Derivative(sin(x), x).doit() == diff(sin(x), x)
+
+    assert Derivative(Derivative(f(x), x), x) == diff(f(x), x, x)
+    assert Derivative(sin(x), x, 0) == sin(x)
+    assert Derivative(sin(x), (x, y), (x, -y)) == sin(x)
+
+
+def test_diff_symbols():
+    assert diff(f(x, y, z), x, y, z) == Derivative(f(x, y, z), x, y, z)
+    assert diff(f(x, y, z), x, x, x) == Derivative(f(x, y, z), x, x, x) == Derivative(f(x, y, z), (x, 3))
+    assert diff(f(x, y, z), x, 3) == Derivative(f(x, y, z), x, 3)
+
+    # issue 5028
+    assert [diff(-z + x/y, sym) for sym in (z, x, y)] == [-1, 1/y, -x/y**2]
+    assert diff(f(x, y, z), x, y, z, 2) == Derivative(f(x, y, z), x, y, z, z)
+    assert diff(f(x, y, z), x, y, z, 2, evaluate=False) == \
+        Derivative(f(x, y, z), x, y, z, z)
+    assert Derivative(f(x, y, z), x, y, z)._eval_derivative(z) == \
+        Derivative(f(x, y, z), x, y, z, z)
+    assert Derivative(Derivative(f(x, y, z), x), y)._eval_derivative(z) == \
+        Derivative(f(x, y, z), x, y, z)
+
+    raises(TypeError, lambda: cos(x).diff((x, y)).variables)
+    assert cos(x).diff((x, y))._wrt_variables == [x]
+
+    # issue 23222
+    assert sympify("a*x+b").diff("x") == sympify("a")
+
+def test_Function():
+    class myfunc(Function):
+        @classmethod
+        def eval(cls):  # zero args
+            return
+
+    assert myfunc.nargs == FiniteSet(0)
+    assert myfunc().nargs == FiniteSet(0)
+    raises(TypeError, lambda: myfunc(x).nargs)
+
+    class myfunc(Function):
+        @classmethod
+        def eval(cls, x):  # one arg
+            return
+
+    assert myfunc.nargs == FiniteSet(1)
+    assert myfunc(x).nargs == FiniteSet(1)
+    raises(TypeError, lambda: myfunc(x, y).nargs)
+
+    class myfunc(Function):
+        @classmethod
+        def eval(cls, *x):  # star args
+            return
+
+    assert myfunc.nargs == S.Naturals0
+    assert myfunc(x).nargs == S.Naturals0
+
+
+def test_nargs():
+    f = Function('f')
+    assert f.nargs == S.Naturals0
+    assert f(1).nargs == S.Naturals0
+    assert Function('f', nargs=2)(1, 2).nargs == FiniteSet(2)
+    assert sin.nargs == FiniteSet(1)
+    assert sin(2).nargs == FiniteSet(1)
+    assert log.nargs == FiniteSet(1, 2)
+    assert log(2).nargs == FiniteSet(1, 2)
+    assert Function('f', nargs=2).nargs == FiniteSet(2)
+    assert Function('f', nargs=0).nargs == FiniteSet(0)
+    assert Function('f', nargs=(0, 1)).nargs == FiniteSet(0, 1)
+    assert Function('f', nargs=None).nargs == S.Naturals0
+    raises(ValueError, lambda: Function('f', nargs=()))
+
+def test_nargs_inheritance():
+    class f1(Function):
+        nargs = 2
+    class f2(f1):
+        pass
+    class f3(f2):
+        pass
+    class f4(f3):
+        nargs = 1,2
+    class f5(f4):
+        pass
+    class f6(f5):
+        pass
+    class f7(f6):
+        nargs=None
+    class f8(f7):
+        pass
+    class f9(f8):
+        pass
+    class f10(f9):
+        nargs = 1
+    class f11(f10):
+        pass
+    assert f1.nargs == FiniteSet(2)
+    assert f2.nargs == FiniteSet(2)
+    assert f3.nargs == FiniteSet(2)
+    assert f4.nargs == FiniteSet(1, 2)
+    assert f5.nargs == FiniteSet(1, 2)
+    assert f6.nargs == FiniteSet(1, 2)
+    assert f7.nargs == S.Naturals0
+    assert f8.nargs == S.Naturals0
+    assert f9.nargs == S.Naturals0
+    assert f10.nargs == FiniteSet(1)
+    assert f11.nargs == FiniteSet(1)
+
+def test_arity():
+    f = lambda x, y: 1
+    assert arity(f) == 2
+    def f(x, y, z=None):
+        pass
+    assert arity(f) == (2, 3)
+    assert arity(lambda *x: x) is None
+    assert arity(log) == (1, 2)
+
+
+def test_Lambda():
+    e = Lambda(x, x**2)
+    assert e(4) == 16
+    assert e(x) == x**2
+    assert e(y) == y**2
+
+    assert Lambda((), 42)() == 42
+    assert unchanged(Lambda, (), 42)
+    assert Lambda((), 42) != Lambda((), 43)
+    assert Lambda((), f(x))() == f(x)
+    assert Lambda((), 42).nargs == FiniteSet(0)
+
+    assert unchanged(Lambda, (x,), x**2)
+    assert Lambda(x, x**2) == Lambda((x,), x**2)
+    assert Lambda(x, x**2) != Lambda(x, x**2 + 1)
+    assert Lambda((x, y), x**y) != Lambda((y, x), y**x)
+    assert Lambda((x, y), x**y) != Lambda((x, y), y**x)
+
+    assert Lambda((x, y), x**y)(x, y) == x**y
+    assert Lambda((x, y), x**y)(3, 3) == 3**3
+    assert Lambda((x, y), x**y)(x, 3) == x**3
+    assert Lambda((x, y), x**y)(3, y) == 3**y
+    assert Lambda(x, f(x))(x) == f(x)
+    assert Lambda(x, x**2)(e(x)) == x**4
+    assert e(e(x)) == x**4
+
+    x1, x2 = (Indexed('x', i) for i in (1, 2))
+    assert Lambda((x1, x2), x1 + x2)(x, y) == x + y
+
+    assert Lambda((x, y), x + y).nargs == FiniteSet(2)
+
+    p = x, y, z, t
+    assert Lambda(p, t*(x + y + z))(*p) == t * (x + y + z)
+
+    eq = Lambda(x, 2*x) + Lambda(y, 2*y)
+    assert eq != 2*Lambda(x, 2*x)
+    assert eq.as_dummy() == 2*Lambda(x, 2*x).as_dummy()
+    assert Lambda(x, 2*x) not in [ Lambda(x, x) ]
+    raises(BadSignatureError, lambda: Lambda(1, x))
+    assert Lambda(x, 1)(1) is S.One
+
+    raises(BadSignatureError, lambda: Lambda((x, x), x + 2))
+    raises(BadSignatureError, lambda: Lambda(((x, x), y), x))
+    raises(BadSignatureError, lambda: Lambda(((y, x), x), x))
+    raises(BadSignatureError, lambda: Lambda(((y, 1), 2), x))
+
+    with warns_deprecated_sympy():
+        assert Lambda([x, y], x+y) == Lambda((x, y), x+y)
+
+    flam = Lambda(((x, y),), x + y)
+    assert flam((2, 3)) == 5
+    flam = Lambda(((x, y), z), x + y + z)
+    assert flam((2, 3), 1) == 6
+    flam = Lambda((((x, y), z),), x + y + z)
+    assert flam(((2, 3), 1)) == 6
+    raises(BadArgumentsError, lambda: flam(1, 2, 3))
+    flam = Lambda( (x,), (x, x))
+    assert flam(1,) == (1, 1)
+    assert flam((1,)) == ((1,), (1,))
+    flam = Lambda( ((x,),), (x, x))
+    raises(BadArgumentsError, lambda: flam(1))
+    assert flam((1,)) == (1, 1)
+
+    # Previously TypeError was raised so this is potentially needed for
+    # backwards compatibility.
+    assert issubclass(BadSignatureError, TypeError)
+    assert issubclass(BadArgumentsError, TypeError)
+
+    # These are tested to see they don't raise:
+    hash(Lambda(x, 2*x))
+    hash(Lambda(x, x))  # IdentityFunction subclass
+
+
+def test_IdentityFunction():
+    assert Lambda(x, x) is Lambda(y, y) is S.IdentityFunction
+    assert Lambda(x, 2*x) is not S.IdentityFunction
+    assert Lambda((x, y), x) is not S.IdentityFunction
+
+
+def test_Lambda_symbols():
+    assert Lambda(x, 2*x).free_symbols == set()
+    assert Lambda(x, x*y).free_symbols == {y}
+    assert Lambda((), 42).free_symbols == set()
+    assert Lambda((), x*y).free_symbols == {x,y}
+
+
+def test_functionclas_symbols():
+    assert f.free_symbols == set()
+
+
+def test_Lambda_arguments():
+    raises(TypeError, lambda: Lambda(x, 2*x)(x, y))
+    raises(TypeError, lambda: Lambda((x, y), x + y)(x))
+    raises(TypeError, lambda: Lambda((), 42)(x))
+
+
+def test_Lambda_equality():
+    assert Lambda((x, y), 2*x) == Lambda((x, y), 2*x)
+    # these, of course, should never be equal
+    assert Lambda(x, 2*x) != Lambda((x, y), 2*x)
+    assert Lambda(x, 2*x) != 2*x
+    # But it is tempting to want expressions that differ only
+    # in bound symbols to compare the same.  But this is not what
+    # Python's `==` is intended to do; two objects that compare
+    # as equal means that they are indistibguishable and cache to the
+    # same value.  We wouldn't want to expression that are
+    # mathematically the same but written in different variables to be
+    # interchanged else what is the point of allowing for different
+    # variable names?
+    assert Lambda(x, 2*x) != Lambda(y, 2*y)
+
+
+def test_Subs():
+    assert Subs(1, (), ()) is S.One
+    # check null subs influence on hashing
+    assert Subs(x, y, z) != Subs(x, y, 1)
+    # neutral subs works
+    assert Subs(x, x, 1).subs(x, y).has(y)
+    # self mapping var/point
+    assert Subs(Derivative(f(x), (x, 2)), x, x).doit() == f(x).diff(x, x)
+    assert Subs(x, x, 0).has(x)  # it's a structural answer
+    assert not Subs(x, x, 0).free_symbols
+    assert Subs(Subs(x + y, x, 2), y, 1) == Subs(x + y, (x, y), (2, 1))
+    assert Subs(x, (x,), (0,)) == Subs(x, x, 0)
+    assert Subs(x, x, 0) == Subs(y, y, 0)
+    assert Subs(x, x, 0).subs(x, 1) == Subs(x, x, 0)
+    assert Subs(y, x, 0).subs(y, 1) == Subs(1, x, 0)
+    assert Subs(f(x), x, 0).doit() == f(0)
+    assert Subs(f(x**2), x**2, 0).doit() == f(0)
+    assert Subs(f(x, y, z), (x, y, z), (0, 1, 1)) != \
+        Subs(f(x, y, z), (x, y, z), (0, 0, 1))
+    assert Subs(x, y, 2).subs(x, y).doit() == 2
+    assert Subs(f(x, y), (x, y, z), (0, 1, 1)) != \
+        Subs(f(x, y) + z, (x, y, z), (0, 1, 0))
+    assert Subs(f(x, y), (x, y), (0, 1)).doit() == f(0, 1)
+    assert Subs(Subs(f(x, y), x, 0), y, 1).doit() == f(0, 1)
+    raises(ValueError, lambda: Subs(f(x, y), (x, y), (0, 0, 1)))
+    raises(ValueError, lambda: Subs(f(x, y), (x, x, y), (0, 0, 1)))
+
+    assert len(Subs(f(x, y), (x, y), (0, 1)).variables) == 2
+    assert Subs(f(x, y), (x, y), (0, 1)).point == Tuple(0, 1)
+
+    assert Subs(f(x), x, 0) == Subs(f(y), y, 0)
+    assert Subs(f(x, y), (x, y), (0, 1)) == Subs(f(x, y), (y, x), (1, 0))
+    assert Subs(f(x)*y, (x, y), (0, 1)) == Subs(f(y)*x, (y, x), (0, 1))
+    assert Subs(f(x)*y, (x, y), (1, 1)) == Subs(f(y)*x, (x, y), (1, 1))
+
+    assert Subs(f(x), x, 0).subs(x, 1).doit() == f(0)
+    assert Subs(f(x), x, y).subs(y, 0) == Subs(f(x), x, 0)
+    assert Subs(y*f(x), x, y).subs(y, 2) == Subs(2*f(x), x, 2)
+    assert (2 * Subs(f(x), x, 0)).subs(Subs(f(x), x, 0), y) == 2*y
+
+    assert Subs(f(x), x, 0).free_symbols == set()
+    assert Subs(f(x, y), x, z).free_symbols == {y, z}
+
+    assert Subs(f(x).diff(x), x, 0).doit(), Subs(f(x).diff(x), x, 0)
+    assert Subs(1 + f(x).diff(x), x, 0).doit(), 1 + Subs(f(x).diff(x), x, 0)
+    assert Subs(y*f(x, y).diff(x), (x, y), (0, 2)).doit() == \
+        2*Subs(Derivative(f(x, 2), x), x, 0)
+    assert Subs(y**2*f(x), x, 0).diff(y) == 2*y*f(0)
+
+    e = Subs(y**2*f(x), x, y)
+    assert e.diff(y) == e.doit().diff(y) == y**2*Derivative(f(y), y) + 2*y*f(y)
+
+    assert Subs(f(x), x, 0) + Subs(f(x), x, 0) == 2*Subs(f(x), x, 0)
+    e1 = Subs(z*f(x), x, 1)
+    e2 = Subs(z*f(y), y, 1)
+    assert e1 + e2 == 2*e1
+    assert e1.__hash__() == e2.__hash__()
+    assert Subs(z*f(x + 1), x, 1) not in [ e1, e2 ]
+    assert Derivative(f(x), x).subs(x, g(x)) == Derivative(f(g(x)), g(x))
+    assert Derivative(f(x), x).subs(x, x + y) == Subs(Derivative(f(x), x),
+        x, x + y)
+    assert Subs(f(x)*cos(y) + z, (x, y), (0, pi/3)).n(2) == \
+        Subs(f(x)*cos(y) + z, (x, y), (0, pi/3)).evalf(2) == \
+        z + Rational('1/2').n(2)*f(0)
+
+    assert f(x).diff(x).subs(x, 0).subs(x, y) == f(x).diff(x).subs(x, 0)
+    assert (x*f(x).diff(x).subs(x, 0)).subs(x, y) == y*f(x).diff(x).subs(x, 0)
+    assert Subs(Derivative(g(x)**2, g(x), x), g(x), exp(x)
+        ).doit() == 2*exp(x)
+    assert Subs(Derivative(g(x)**2, g(x), x), g(x), exp(x)
+        ).doit(deep=False) == 2*Derivative(exp(x), x)
+    assert Derivative(f(x, g(x)), x).doit() == Derivative(
+        f(x, g(x)), g(x))*Derivative(g(x), x) + Subs(Derivative(
+        f(y, g(x)), y), y, x)
+
+def test_doitdoit():
+    done = Derivative(f(x, g(x)), x, g(x)).doit()
+    assert done == done.doit()
+
+
+@XFAIL
+def test_Subs2():
+    # this reflects a limitation of subs(), probably won't fix
+    assert Subs(f(x), x**2, x).doit() == f(sqrt(x))
+
+
+def test_expand_function():
+    assert expand(x + y) == x + y
+    assert expand(x + y, complex=True) == I*im(x) + I*im(y) + re(x) + re(y)
+    assert expand((x + y)**11, modulus=11) == x**11 + y**11
+
+
+def test_function_comparable():
+    assert sin(x).is_comparable is False
+    assert cos(x).is_comparable is False
+
+    assert sin(Float('0.1')).is_comparable is True
+    assert cos(Float('0.1')).is_comparable is True
+
+    assert sin(E).is_comparable is True
+    assert cos(E).is_comparable is True
+
+    assert sin(Rational(1, 3)).is_comparable is True
+    assert cos(Rational(1, 3)).is_comparable is True
+
+
+def test_function_comparable_infinities():
+    assert sin(oo).is_comparable is False
+    assert sin(-oo).is_comparable is False
+    assert sin(zoo).is_comparable is False
+    assert sin(nan).is_comparable is False
+
+
+def test_deriv1():
+    # These all require derivatives evaluated at a point (issue 4719) to work.
+    # See issue 4624
+    assert f(2*x).diff(x) == 2*Subs(Derivative(f(x), x), x, 2*x)
+    assert (f(x)**3).diff(x) == 3*f(x)**2*f(x).diff(x)
+    assert (f(2*x)**3).diff(x) == 6*f(2*x)**2*Subs(
+        Derivative(f(x), x), x, 2*x)
+
+    assert f(2 + x).diff(x) == Subs(Derivative(f(x), x), x, x + 2)
+    assert f(2 + 3*x).diff(x) == 3*Subs(
+        Derivative(f(x), x), x, 3*x + 2)
+    assert f(3*sin(x)).diff(x) == 3*cos(x)*Subs(
+        Derivative(f(x), x), x, 3*sin(x))
+
+    # See issue 8510
+    assert f(x, x + z).diff(x) == (
+        Subs(Derivative(f(y, x + z), y), y, x) +
+        Subs(Derivative(f(x, y), y), y, x + z))
+    assert f(x, x**2).diff(x) == (
+        2*x*Subs(Derivative(f(x, y), y), y, x**2) +
+        Subs(Derivative(f(y, x**2), y), y, x))
+    # but Subs is not always necessary
+    assert f(x, g(y)).diff(g(y)) == Derivative(f(x, g(y)), g(y))
+
+
+def test_deriv2():
+    assert (x**3).diff(x) == 3*x**2
+    assert (x**3).diff(x, evaluate=False) != 3*x**2
+    assert (x**3).diff(x, evaluate=False) == Derivative(x**3, x)
+
+    assert diff(x**3, x) == 3*x**2
+    assert diff(x**3, x, evaluate=False) != 3*x**2
+    assert diff(x**3, x, evaluate=False) == Derivative(x**3, x)
+
+
+def test_func_deriv():
+    assert f(x).diff(x) == Derivative(f(x), x)
+    # issue 4534
+    assert f(x, y).diff(x, y) - f(x, y).diff(y, x) == 0
+    assert Derivative(f(x, y), x, y).args[1:] == ((x, 1), (y, 1))
+    assert Derivative(f(x, y), y, x).args[1:] == ((y, 1), (x, 1))
+    assert (Derivative(f(x, y), x, y) - Derivative(f(x, y), y, x)).doit() == 0
+
+
+def test_suppressed_evaluation():
+    a = sin(0, evaluate=False)
+    assert a != 0
+    assert a.func is sin
+    assert a.args == (0,)
+
+
+def test_function_evalf():
+    def eq(a, b, eps):
+        return abs(a - b) < eps
+    assert eq(sin(1).evalf(15), Float("0.841470984807897"), 1e-13)
+    assert eq(
+        sin(2).evalf(25), Float("0.9092974268256816953960199", 25), 1e-23)
+    assert eq(sin(1 + I).evalf(
+        15), Float("1.29845758141598") + Float("0.634963914784736")*I, 1e-13)
+    assert eq(exp(1 + I).evalf(15), Float(
+        "1.46869393991588") + Float("2.28735528717884239")*I, 1e-13)
+    assert eq(exp(-0.5 + 1.5*I).evalf(15), Float(
+        "0.0429042815937374") + Float("0.605011292285002")*I, 1e-13)
+    assert eq(log(pi + sqrt(2)*I).evalf(
+        15), Float("1.23699044022052") + Float("0.422985442737893")*I, 1e-13)
+    assert eq(cos(100).evalf(15), Float("0.86231887228768"), 1e-13)
+
+
+def test_extensibility_eval():
+    class MyFunc(Function):
+        @classmethod
+        def eval(cls, *args):
+            return (0, 0, 0)
+    assert MyFunc(0) == (0, 0, 0)
+
+
+@_both_exp_pow
+def test_function_non_commutative():
+    x = Symbol('x', commutative=False)
+    assert f(x).is_commutative is False
+    assert sin(x).is_commutative is False
+    assert exp(x).is_commutative is False
+    assert log(x).is_commutative is False
+    assert f(x).is_complex is False
+    assert sin(x).is_complex is False
+    assert exp(x).is_complex is False
+    assert log(x).is_complex is False
+
+
+def test_function_complex():
+    x = Symbol('x', complex=True)
+    xzf = Symbol('x', complex=True, zero=False)
+    assert f(x).is_commutative is True
+    assert sin(x).is_commutative is True
+    assert exp(x).is_commutative is True
+    assert log(x).is_commutative is True
+    assert f(x).is_complex is None
+    assert sin(x).is_complex is True
+    assert exp(x).is_complex is True
+    assert log(x).is_complex is None
+    assert log(xzf).is_complex is True
+
+
+def test_function__eval_nseries():
+    n = Symbol('n')
+
+    assert sin(x)._eval_nseries(x, 2, None) == x + O(x**2)
+    assert sin(x + 1)._eval_nseries(x, 2, None) == x*cos(1) + sin(1) + O(x**2)
+    assert sin(pi*(1 - x))._eval_nseries(x, 2, None) == pi*x + O(x**2)
+    assert acos(1 - x**2)._eval_nseries(x, 2, None) == sqrt(2)*sqrt(x**2) + O(x**2)
+    assert polygamma(n, x + 1)._eval_nseries(x, 2, None) == \
+        polygamma(n, 1) + polygamma(n + 1, 1)*x + O(x**2)
+    raises(PoleError, lambda: sin(1/x)._eval_nseries(x, 2, None))
+    assert acos(1 - x)._eval_nseries(x, 2, None) == sqrt(2)*sqrt(x) + sqrt(2)*x**(S(3)/2)/12 + O(x**2)
+    assert acos(1 + x)._eval_nseries(x, 2, None) == sqrt(2)*sqrt(-x) + sqrt(2)*(-x)**(S(3)/2)/12 + O(x**2)
+    assert loggamma(1/x)._eval_nseries(x, 0, None) == \
+        log(x)/2 - log(x)/x - 1/x + O(1, x)
+    assert loggamma(log(1/x)).nseries(x, n=1, logx=y) == loggamma(-y)
+
+    # issue 6725:
+    assert expint(Rational(3, 2), -x)._eval_nseries(x, 5, None) == \
+        2 - 2*sqrt(pi)*sqrt(-x) - 2*x + x**2 + x**3/3 + x**4/12 + 4*I*x**(S(3)/2)*sqrt(-x)/3 + \
+        2*I*x**(S(5)/2)*sqrt(-x)/5 + 2*I*x**(S(7)/2)*sqrt(-x)/21 + O(x**5)
+    assert sin(sqrt(x))._eval_nseries(x, 3, None) == \
+        sqrt(x) - x**Rational(3, 2)/6 + x**Rational(5, 2)/120 + O(x**3)
+
+    # issue 19065:
+    s1 = f(x,y).series(y, n=2)
+    assert {i.name for i in s1.atoms(Symbol)} == {'x', 'xi', 'y'}
+    xi = Symbol('xi')
+    s2 = f(xi, y).series(y, n=2)
+    assert {i.name for i in s2.atoms(Symbol)} == {'xi', 'xi0', 'y'}
+
+def test_doit():
+    n = Symbol('n', integer=True)
+    f = Sum(2 * n * x, (n, 1, 3))
+    d = Derivative(f, x)
+    assert d.doit() == 12
+    assert d.doit(deep=False) == Sum(2*n, (n, 1, 3))
+
+
+def test_evalf_default():
+    from sympy.functions.special.gamma_functions import polygamma
+    assert type(sin(4.0)) == Float
+    assert type(re(sin(I + 1.0))) == Float
+    assert type(im(sin(I + 1.0))) == Float
+    assert type(sin(4)) == sin
+    assert type(polygamma(2.0, 4.0)) == Float
+    assert type(sin(Rational(1, 4))) == sin
+
+
+def test_issue_5399():
+    args = [x, y, S(2), S.Half]
+
+    def ok(a):
+        """Return True if the input args for diff are ok"""
+        if not a:
+            return False
+        if a[0].is_Symbol is False:
+            return False
+        s_at = [i for i in range(len(a)) if a[i].is_Symbol]
+        n_at = [i for i in range(len(a)) if not a[i].is_Symbol]
+        # every symbol is followed by symbol or int
+        # every number is followed by a symbol
+        return (all(a[i + 1].is_Symbol or a[i + 1].is_Integer
+            for i in s_at if i + 1 < len(a)) and
+            all(a[i + 1].is_Symbol
+            for i in n_at if i + 1 < len(a)))
+    eq = x**10*y**8
+    for a in subsets(args):
+        for v in variations(a, len(a)):
+            if ok(v):
+                eq.diff(*v) # does not raise
+            else:
+                raises(ValueError, lambda: eq.diff(*v))
+
+
+def test_derivative_numerically():
+    z0 = x._random()
+    assert abs(Derivative(sin(x), x).doit_numerically(z0) - cos(z0)) < 1e-15
+
+
+def test_fdiff_argument_index_error():
+    from sympy.core.function import ArgumentIndexError
+
+    class myfunc(Function):
+        nargs = 1  # define since there is no eval routine
+
+        def fdiff(self, idx):
+            raise ArgumentIndexError
+    mf = myfunc(x)
+    assert mf.diff(x) == Derivative(mf, x)
+    raises(TypeError, lambda: myfunc(x, x))
+
+
+def test_deriv_wrt_function():
+    x = f(t)
+    xd = diff(x, t)
+    xdd = diff(xd, t)
+    y = g(t)
+    yd = diff(y, t)
+
+    assert diff(x, t) == xd
+    assert diff(2 * x + 4, t) == 2 * xd
+    assert diff(2 * x + 4 + y, t) == 2 * xd + yd
+    assert diff(2 * x + 4 + y * x, t) == 2 * xd + x * yd + xd * y
+    assert diff(2 * x + 4 + y * x, x) == 2 + y
+    assert (diff(4 * x**2 + 3 * x + x * y, t) == 3 * xd + x * yd + xd * y +
+            8 * x * xd)
+    assert (diff(4 * x**2 + 3 * xd + x * y, t) == 3 * xdd + x * yd + xd * y +
+            8 * x * xd)
+    assert diff(4 * x**2 + 3 * xd + x * y, xd) == 3
+    assert diff(4 * x**2 + 3 * xd + x * y, xdd) == 0
+    assert diff(sin(x), t) == xd * cos(x)
+    assert diff(exp(x), t) == xd * exp(x)
+    assert diff(sqrt(x), t) == xd / (2 * sqrt(x))
+
+
+def test_diff_wrt_value():
+    assert Expr()._diff_wrt is False
+    assert x._diff_wrt is True
+    assert f(x)._diff_wrt is True
+    assert Derivative(f(x), x)._diff_wrt is True
+    assert Derivative(x**2, x)._diff_wrt is False
+
+
+def test_diff_wrt():
+    fx = f(x)
+    dfx = diff(f(x), x)
+    ddfx = diff(f(x), x, x)
+
+    assert diff(sin(fx) + fx**2, fx) == cos(fx) + 2*fx
+    assert diff(sin(dfx) + dfx**2, dfx) == cos(dfx) + 2*dfx
+    assert diff(sin(ddfx) + ddfx**2, ddfx) == cos(ddfx) + 2*ddfx
+    assert diff(fx**2, dfx) == 0
+    assert diff(fx**2, ddfx) == 0
+    assert diff(dfx**2, fx) == 0
+    assert diff(dfx**2, ddfx) == 0
+    assert diff(ddfx**2, dfx) == 0
+
+    assert diff(fx*dfx*ddfx, fx) == dfx*ddfx
+    assert diff(fx*dfx*ddfx, dfx) == fx*ddfx
+    assert diff(fx*dfx*ddfx, ddfx) == fx*dfx
+
+    assert diff(f(x), x).diff(f(x)) == 0
+    assert (sin(f(x)) - cos(diff(f(x), x))).diff(f(x)) == cos(f(x))
+
+    assert diff(sin(fx), fx, x) == diff(sin(fx), x, fx)
+
+    # Chain rule cases
+    assert f(g(x)).diff(x) == \
+        Derivative(g(x), x)*Derivative(f(g(x)), g(x))
+    assert diff(f(g(x), h(y)), x) == \
+        Derivative(g(x), x)*Derivative(f(g(x), h(y)), g(x))
+    assert diff(f(g(x), h(x)), x) == (
+        Derivative(f(g(x), h(x)), g(x))*Derivative(g(x), x) +
+        Derivative(f(g(x), h(x)), h(x))*Derivative(h(x), x))
+    assert f(
+        sin(x)).diff(x) == cos(x)*Subs(Derivative(f(x), x), x, sin(x))
+
+    assert diff(f(g(x)), g(x)) == Derivative(f(g(x)), g(x))
+
+
+def test_diff_wrt_func_subs():
+    assert f(g(x)).diff(x).subs(g, Lambda(x, 2*x)).doit() == f(2*x).diff(x)
+
+
+def test_subs_in_derivative():
+    expr = sin(x*exp(y))
+    u = Function('u')
+    v = Function('v')
+    assert Derivative(expr, y).subs(expr, y) == Derivative(y, y)
+    assert Derivative(expr, y).subs(y, x).doit() == \
+        Derivative(expr, y).doit().subs(y, x)
+    assert Derivative(f(x, y), y).subs(y, x) == Subs(Derivative(f(x, y), y), y, x)
+    assert Derivative(f(x, y), y).subs(x, y) == Subs(Derivative(f(x, y), y), x, y)
+    assert Derivative(f(x, y), y).subs(y, g(x, y)) == Subs(Derivative(f(x, y), y), y, g(x, y)).doit()
+    assert Derivative(f(x, y), y).subs(x, g(x, y)) == Subs(Derivative(f(x, y), y), x, g(x, y))
+    assert Derivative(f(x, y), g(y)).subs(x, g(x, y)) == Derivative(f(g(x, y), y), g(y))
+    assert Derivative(f(u(x), h(y)), h(y)).subs(h(y), g(x, y)) == \
+        Subs(Derivative(f(u(x), h(y)), h(y)), h(y), g(x, y)).doit()
+    assert Derivative(f(x, y), y).subs(y, z) == Derivative(f(x, z), z)
+    assert Derivative(f(x, y), y).subs(y, g(y)) == Derivative(f(x, g(y)), g(y))
+    assert Derivative(f(g(x), h(y)), h(y)).subs(h(y), u(y)) == \
+        Derivative(f(g(x), u(y)), u(y))
+    assert Derivative(f(x, f(x, x)), f(x, x)).subs(
+        f, Lambda((x, y), x + y)) == Subs(
+        Derivative(z + x, z), z, 2*x)
+    assert Subs(Derivative(f(f(x)), x), f, cos).doit() == sin(x)*sin(cos(x))
+    assert Subs(Derivative(f(f(x)), f(x)), f, cos).doit() == -sin(cos(x))
+    # Issue 13791. No comparison (it's a long formula) but this used to raise an exception.
+    assert isinstance(v(x, y, u(x, y)).diff(y).diff(x).diff(y), Expr)
+    # This is also related to issues 13791 and 13795; issue 15190
+    F = Lambda((x, y), exp(2*x + 3*y))
+    abstract = f(x, f(x, x)).diff(x, 2)
+    concrete = F(x, F(x, x)).diff(x, 2)
+    assert (abstract.subs(f, F).doit() - concrete).simplify() == 0
+    # don't introduce a new symbol if not necessary
+    assert x in f(x).diff(x).subs(x, 0).atoms()
+    # case (4)
+    assert Derivative(f(x,f(x,y)), x, y).subs(x, g(y)
+        ) == Subs(Derivative(f(x, f(x, y)), x, y), x, g(y))
+
+    assert Derivative(f(x, x), x).subs(x, 0
+        ) == Subs(Derivative(f(x, x), x), x, 0)
+    # issue 15194
+    assert Derivative(f(y, g(x)), (x, z)).subs(z, x
+        ) == Derivative(f(y, g(x)), (x, x))
+
+    df = f(x).diff(x)
+    assert df.subs(df, 1) is S.One
+    assert df.diff(df) is S.One
+    dxy = Derivative(f(x, y), x, y)
+    dyx = Derivative(f(x, y), y, x)
+    assert dxy.subs(Derivative(f(x, y), y, x), 1) is S.One
+    assert dxy.diff(dyx) is S.One
+    assert Derivative(f(x, y), x, 2, y, 3).subs(
+        dyx, g(x, y)) == Derivative(g(x, y), x, 1, y, 2)
+    assert Derivative(f(x, x - y), y).subs(x, x + y) == Subs(
+        Derivative(f(x, x - y), y), x, x + y)
+
+
+def test_diff_wrt_not_allowed():
+    # issue 7027 included
+    for wrt in (
+            cos(x), re(x), x**2, x*y, 1 + x,
+            Derivative(cos(x), x), Derivative(f(f(x)), x)):
+        raises(ValueError, lambda: diff(f(x), wrt))
+    # if we don't differentiate wrt then don't raise error
+    assert diff(exp(x*y), x*y, 0) == exp(x*y)
+
+
+def test_diff_wrt_intlike():
+    class Two:
+        def __int__(self):
+            return 2
+
+    assert cos(x).diff(x, Two()) == -cos(x)
+
+
+def test_klein_gordon_lagrangian():
+    m = Symbol('m')
+    phi = f(x, t)
+
+    L = -(diff(phi, t)**2 - diff(phi, x)**2 - m**2*phi**2)/2
+    eqna = Eq(
+        diff(L, phi) - diff(L, diff(phi, x), x) - diff(L, diff(phi, t), t), 0)
+    eqnb = Eq(diff(phi, t, t) - diff(phi, x, x) + m**2*phi, 0)
+    assert eqna == eqnb
+
+
+def test_sho_lagrangian():
+    m = Symbol('m')
+    k = Symbol('k')
+    x = f(t)
+
+    L = m*diff(x, t)**2/2 - k*x**2/2
+    eqna = Eq(diff(L, x), diff(L, diff(x, t), t))
+    eqnb = Eq(-k*x, m*diff(x, t, t))
+    assert eqna == eqnb
+
+    assert diff(L, x, t) == diff(L, t, x)
+    assert diff(L, diff(x, t), t) == m*diff(x, t, 2)
+    assert diff(L, t, diff(x, t)) == -k*x + m*diff(x, t, 2)
+
+
+def test_straight_line():
+    F = f(x)
+    Fd = F.diff(x)
+    L = sqrt(1 + Fd**2)
+    assert diff(L, F) == 0
+    assert diff(L, Fd) == Fd/sqrt(1 + Fd**2)
+
+
+def test_sort_variable():
+    vsort = Derivative._sort_variable_count
+    def vsort0(*v, reverse=False):
+        return [i[0] for i in vsort([(i, 0) for i in (
+            reversed(v) if reverse else v)])]
+
+    for R in range(2):
+        assert vsort0(y, x, reverse=R) == [x, y]
+        assert vsort0(f(x), x, reverse=R) == [x, f(x)]
+        assert vsort0(f(y), f(x), reverse=R) == [f(x), f(y)]
+        assert vsort0(g(x), f(y), reverse=R) == [f(y), g(x)]
+        assert vsort0(f(x, y), f(x), reverse=R) == [f(x), f(x, y)]
+        fx = f(x).diff(x)
+        assert vsort0(fx, y, reverse=R) == [y, fx]
+        fy = f(y).diff(y)
+        assert vsort0(fy, fx, reverse=R) == [fx, fy]
+        fxx = fx.diff(x)
+        assert vsort0(fxx, fx, reverse=R) == [fx, fxx]
+        assert vsort0(Basic(x), f(x), reverse=R) == [f(x), Basic(x)]
+        assert vsort0(Basic(y), Basic(x), reverse=R) == [Basic(x), Basic(y)]
+        assert vsort0(Basic(y, z), Basic(x), reverse=R) == [
+            Basic(x), Basic(y, z)]
+        assert vsort0(fx, x, reverse=R) == [
+            x, fx] if R else [fx, x]
+        assert vsort0(Basic(x), x, reverse=R) == [
+            x, Basic(x)] if R else [Basic(x), x]
+        assert vsort0(Basic(f(x)), f(x), reverse=R) == [
+            f(x), Basic(f(x))] if R else [Basic(f(x)), f(x)]
+        assert vsort0(Basic(x, z), Basic(x), reverse=R) == [
+            Basic(x), Basic(x, z)] if R else [Basic(x, z), Basic(x)]
+    assert vsort([]) == []
+    assert _aresame(vsort([(x, 1)]), [Tuple(x, 1)])
+    assert vsort([(x, y), (x, z)]) == [(x, y + z)]
+    assert vsort([(y, 1), (x, 1 + y)]) == [(x, 1 + y), (y, 1)]
+    # coverage complete; legacy tests below
+    assert vsort([(x, 3), (y, 2), (z, 1)]) == [(x, 3), (y, 2), (z, 1)]
+    assert vsort([(h(x), 1), (g(x), 1), (f(x), 1)]) == [
+        (f(x), 1), (g(x), 1), (h(x), 1)]
+    assert vsort([(z, 1), (y, 2), (x, 3), (h(x), 1), (g(x), 1),
+        (f(x), 1)]) == [(x, 3), (y, 2), (z, 1), (f(x), 1), (g(x), 1),
+        (h(x), 1)]
+    assert vsort([(x, 1), (f(x), 1), (y, 1), (f(y), 1)]) == [(x, 1),
+        (y, 1), (f(x), 1), (f(y), 1)]
+    assert vsort([(y, 1), (x, 2), (g(x), 1), (f(x), 1), (z, 1),
+        (h(x), 1), (y, 2), (x, 1)]) == [(x, 3), (y, 3), (z, 1),
+        (f(x), 1), (g(x), 1), (h(x), 1)]
+    assert vsort([(z, 1), (y, 1), (f(x), 1), (x, 1), (f(x), 1),
+        (g(x), 1)]) == [(x, 1), (y, 1), (z, 1), (f(x), 2), (g(x), 1)]
+    assert vsort([(z, 1), (y, 2), (f(x), 1), (x, 2), (f(x), 2),
+        (g(x), 1), (z, 2), (z, 1), (y, 1), (x, 1)]) == [(x, 3), (y, 3),
+        (z, 4), (f(x), 3), (g(x), 1)]
+    assert vsort(((y, 2), (x, 1), (y, 1), (x, 1))) == [(x, 2), (y, 3)]
+    assert isinstance(vsort([(x, 3), (y, 2), (z, 1)])[0], Tuple)
+    assert vsort([(x, 1), (f(x), 1), (x, 1)]) == [(x, 2), (f(x), 1)]
+    assert vsort([(y, 2), (x, 3), (z, 1)]) == [(x, 3), (y, 2), (z, 1)]
+    assert vsort([(h(y), 1), (g(x), 1), (f(x), 1)]) == [
+        (f(x), 1), (g(x), 1), (h(y), 1)]
+    assert vsort([(x, 1), (y, 1), (x, 1)]) == [(x, 2), (y, 1)]
+    assert vsort([(f(x), 1), (f(y), 1), (f(x), 1)]) == [
+        (f(x), 2), (f(y), 1)]
+    dfx = f(x).diff(x)
+    self = [(dfx, 1), (x, 1)]
+    assert vsort(self) == self
+    assert vsort([
+        (dfx, 1), (y, 1), (f(x), 1), (x, 1), (f(y), 1), (x, 1)]) == [
+        (y, 1), (f(x), 1), (f(y), 1), (dfx, 1), (x, 2)]
+    dfy = f(y).diff(y)
+    assert vsort([(dfy, 1), (dfx, 1)]) == [(dfx, 1), (dfy, 1)]
+    d2fx = dfx.diff(x)
+    assert vsort([(d2fx, 1), (dfx, 1)]) == [(dfx, 1), (d2fx, 1)]
+
+
+def test_multiple_derivative():
+    # Issue #15007
+    assert f(x, y).diff(y, y, x, y, x
+        ) == Derivative(f(x, y), (x, 2), (y, 3))
+
+
+def test_unhandled():
+    class MyExpr(Expr):
+        def _eval_derivative(self, s):
+            if not s.name.startswith('xi'):
+                return self
+            else:
+                return None
+
+    eq = MyExpr(f(x), y, z)
+    assert diff(eq, x, y, f(x), z) == Derivative(eq, f(x))
+    assert diff(eq, f(x), x) == Derivative(eq, f(x))
+    assert f(x, y).diff(x,(y, z)) == Derivative(f(x, y), x, (y, z))
+    assert f(x, y).diff(x,(y, 0)) == Derivative(f(x, y), x)
+
+
+def test_nfloat():
+    from sympy.core.basic import _aresame
+    from sympy.polys.rootoftools import rootof
+
+    x = Symbol("x")
+    eq = x**Rational(4, 3) + 4*x**(S.One/3)/3
+    assert _aresame(nfloat(eq), x**Rational(4, 3) + (4.0/3)*x**(S.One/3))
+    assert _aresame(nfloat(eq, exponent=True), x**(4.0/3) + (4.0/3)*x**(1.0/3))
+    eq = x**Rational(4, 3) + 4*x**(x/3)/3
+    assert _aresame(nfloat(eq), x**Rational(4, 3) + (4.0/3)*x**(x/3))
+    big = 12345678901234567890
+    # specify precision to match value used in nfloat
+    Float_big = Float(big, 15)
+    assert _aresame(nfloat(big), Float_big)
+    assert _aresame(nfloat(big*x), Float_big*x)
+    assert _aresame(nfloat(x**big, exponent=True), x**Float_big)
+    assert nfloat(cos(x + sqrt(2))) == cos(x + nfloat(sqrt(2)))
+
+    # issue 6342
+    f = S('x*lamda + lamda**3*(x/2 + 1/2) + lamda**2 + 1/4')
+    assert not any(a.free_symbols for a in solveset(f.subs(x, -0.139)))
+
+    # issue 6632
+    assert nfloat(-100000*sqrt(2500000001) + 5000000001) == \
+        9.99999999800000e-11
+
+    # issue 7122
+    eq = cos(3*x**4 + y)*rootof(x**5 + 3*x**3 + 1, 0)
+    assert str(nfloat(eq, exponent=False, n=1)) == '-0.7*cos(3.0*x**4 + y)'
+
+    # issue 10933
+    for ti in (dict, Dict):
+        d = ti({S.Half: S.Half})
+        n = nfloat(d)
+        assert isinstance(n, ti)
+        assert _aresame(list(n.items()).pop(), (S.Half, Float(.5)))
+    for ti in (dict, Dict):
+        d = ti({S.Half: S.Half})
+        n = nfloat(d, dkeys=True)
+        assert isinstance(n, ti)
+        assert _aresame(list(n.items()).pop(), (Float(.5), Float(.5)))
+    d = [S.Half]
+    n = nfloat(d)
+    assert type(n) is list
+    assert _aresame(n[0], Float(.5))
+    assert _aresame(nfloat(Eq(x, S.Half)).rhs, Float(.5))
+    assert _aresame(nfloat(S(True)), S(True))
+    assert _aresame(nfloat(Tuple(S.Half))[0], Float(.5))
+    assert nfloat(Eq((3 - I)**2/2 + I, 0)) == S.false
+    # pass along kwargs
+    assert nfloat([{S.Half: x}], dkeys=True) == [{Float(0.5): x}]
+
+    # Issue 17706
+    A = MutableMatrix([[1, 2], [3, 4]])
+    B = MutableMatrix(
+        [[Float('1.0', precision=53), Float('2.0', precision=53)],
+        [Float('3.0', precision=53), Float('4.0', precision=53)]])
+    assert _aresame(nfloat(A), B)
+    A = ImmutableMatrix([[1, 2], [3, 4]])
+    B = ImmutableMatrix(
+        [[Float('1.0', precision=53), Float('2.0', precision=53)],
+        [Float('3.0', precision=53), Float('4.0', precision=53)]])
+    assert _aresame(nfloat(A), B)
+
+    # issue 22524
+    f = Function('f')
+    assert not nfloat(f(2)).atoms(Float)
+
+
+def test_issue_7068():
+    from sympy.abc import a, b
+    f = Function('f')
+    y1 = Dummy('y')
+    y2 = Dummy('y')
+    func1 = f(a + y1 * b)
+    func2 = f(a + y2 * b)
+    func1_y = func1.diff(y1)
+    func2_y = func2.diff(y2)
+    assert func1_y != func2_y
+    z1 = Subs(f(a), a, y1)
+    z2 = Subs(f(a), a, y2)
+    assert z1 != z2
+
+
+def test_issue_7231():
+    from sympy.abc import a
+    ans1 = f(x).series(x, a)
+    res = (f(a) + (-a + x)*Subs(Derivative(f(y), y), y, a) +
+           (-a + x)**2*Subs(Derivative(f(y), y, y), y, a)/2 +
+           (-a + x)**3*Subs(Derivative(f(y), y, y, y),
+                            y, a)/6 +
+           (-a + x)**4*Subs(Derivative(f(y), y, y, y, y),
+                            y, a)/24 +
+           (-a + x)**5*Subs(Derivative(f(y), y, y, y, y, y),
+                            y, a)/120 + O((-a + x)**6, (x, a)))
+    assert res == ans1
+    ans2 = f(x).series(x, a)
+    assert res == ans2
+
+
+def test_issue_7687():
+    from sympy.core.function import Function
+    from sympy.abc import x
+    f = Function('f')(x)
+    ff = Function('f')(x)
+    match_with_cache = ff.matches(f)
+    assert isinstance(f, type(ff))
+    clear_cache()
+    ff = Function('f')(x)
+    assert isinstance(f, type(ff))
+    assert match_with_cache == ff.matches(f)
+
+
+def test_issue_7688():
+    from sympy.core.function import Function, UndefinedFunction
+
+    f = Function('f')  # actually an UndefinedFunction
+    clear_cache()
+    class A(UndefinedFunction):
+        pass
+    a = A('f')
+    assert isinstance(a, type(f))
+
+
+def test_mexpand():
+    from sympy.abc import x
+    assert _mexpand(None) is None
+    assert _mexpand(1) is S.One
+    assert _mexpand(x*(x + 1)**2) == (x*(x + 1)**2).expand()
+
+
+def test_issue_8469():
+    # This should not take forever to run
+    N = 40
+    def g(w, theta):
+        return 1/(1+exp(w-theta))
+
+    ws = symbols(['w%i'%i for i in range(N)])
+    import functools
+    expr = functools.reduce(g, ws)
+    assert isinstance(expr, Pow)
+
+
+def test_issue_12996():
+    # foo=True imitates the sort of arguments that Derivative can get
+    # from Integral when it passes doit to the expression
+    assert Derivative(im(x), x).doit(foo=True) == Derivative(im(x), x)
+
+
+def test_should_evalf():
+    # This should not take forever to run (see #8506)
+    assert isinstance(sin((1.0 + 1.0*I)**10000 + 1), sin)
+
+
+def test_Derivative_as_finite_difference():
+    # Central 1st derivative at gridpoint
+    x, h = symbols('x h', real=True)
+    dfdx = f(x).diff(x)
+    assert (dfdx.as_finite_difference([x-2, x-1, x, x+1, x+2]) -
+            (S.One/12*(f(x-2)-f(x+2)) + Rational(2, 3)*(f(x+1)-f(x-1)))).simplify() == 0
+
+    # Central 1st derivative "half-way"
+    assert (dfdx.as_finite_difference() -
+            (f(x + S.Half)-f(x - S.Half))).simplify() == 0
+    assert (dfdx.as_finite_difference(h) -
+            (f(x + h/S(2))-f(x - h/S(2)))/h).simplify() == 0
+    assert (dfdx.as_finite_difference([x - 3*h, x-h, x+h, x + 3*h]) -
+            (S(9)/(8*2*h)*(f(x+h) - f(x-h)) +
+             S.One/(24*2*h)*(f(x - 3*h) - f(x + 3*h)))).simplify() == 0
+
+    # One sided 1st derivative at gridpoint
+    assert (dfdx.as_finite_difference([0, 1, 2], 0) -
+            (Rational(-3, 2)*f(0) + 2*f(1) - f(2)/2)).simplify() == 0
+    assert (dfdx.as_finite_difference([x, x+h], x) -
+            (f(x+h) - f(x))/h).simplify() == 0
+    assert (dfdx.as_finite_difference([x-h, x, x+h], x-h) -
+            (-S(3)/(2*h)*f(x-h) + 2/h*f(x) -
+             S.One/(2*h)*f(x+h))).simplify() == 0
+
+    # One sided 1st derivative "half-way"
+    assert (dfdx.as_finite_difference([x-h, x+h, x + 3*h, x + 5*h, x + 7*h])
+            - 1/(2*h)*(-S(11)/(12)*f(x-h) + S(17)/(24)*f(x+h)
+                       + Rational(3, 8)*f(x + 3*h) - Rational(5, 24)*f(x + 5*h)
+                       + S.One/24*f(x + 7*h))).simplify() == 0
+
+    d2fdx2 = f(x).diff(x, 2)
+    # Central 2nd derivative at gridpoint
+    assert (d2fdx2.as_finite_difference([x-h, x, x+h]) -
+            h**-2 * (f(x-h) + f(x+h) - 2*f(x))).simplify() == 0
+
+    assert (d2fdx2.as_finite_difference([x - 2*h, x-h, x, x+h, x + 2*h]) -
+            h**-2 * (Rational(-1, 12)*(f(x - 2*h) + f(x + 2*h)) +
+                     Rational(4, 3)*(f(x+h) + f(x-h)) - Rational(5, 2)*f(x))).simplify() == 0
+
+    # Central 2nd derivative "half-way"
+    assert (d2fdx2.as_finite_difference([x - 3*h, x-h, x+h, x + 3*h]) -
+            (2*h)**-2 * (S.Half*(f(x - 3*h) + f(x + 3*h)) -
+                         S.Half*(f(x+h) + f(x-h)))).simplify() == 0
+
+    # One sided 2nd derivative at gridpoint
+    assert (d2fdx2.as_finite_difference([x, x+h, x + 2*h, x + 3*h]) -
+            h**-2 * (2*f(x) - 5*f(x+h) +
+                     4*f(x+2*h) - f(x+3*h))).simplify() == 0
+
+    # One sided 2nd derivative at "half-way"
+    assert (d2fdx2.as_finite_difference([x-h, x+h, x + 3*h, x + 5*h]) -
+            (2*h)**-2 * (Rational(3, 2)*f(x-h) - Rational(7, 2)*f(x+h) + Rational(5, 2)*f(x + 3*h) -
+                         S.Half*f(x + 5*h))).simplify() == 0
+
+    d3fdx3 = f(x).diff(x, 3)
+    # Central 3rd derivative at gridpoint
+    assert (d3fdx3.as_finite_difference() -
+            (-f(x - Rational(3, 2)) + 3*f(x - S.Half) -
+             3*f(x + S.Half) + f(x + Rational(3, 2)))).simplify() == 0
+
+    assert (d3fdx3.as_finite_difference(
+        [x - 3*h, x - 2*h, x-h, x, x+h, x + 2*h, x + 3*h]) -
+        h**-3 * (S.One/8*(f(x - 3*h) - f(x + 3*h)) - f(x - 2*h) +
+                 f(x + 2*h) + Rational(13, 8)*(f(x-h) - f(x+h)))).simplify() == 0
+
+    # Central 3rd derivative at "half-way"
+    assert (d3fdx3.as_finite_difference([x - 3*h, x-h, x+h, x + 3*h]) -
+            (2*h)**-3 * (f(x + 3*h)-f(x - 3*h) +
+                         3*(f(x-h)-f(x+h)))).simplify() == 0
+
+    # One sided 3rd derivative at gridpoint
+    assert (d3fdx3.as_finite_difference([x, x+h, x + 2*h, x + 3*h]) -
+            h**-3 * (f(x + 3*h)-f(x) + 3*(f(x+h)-f(x + 2*h)))).simplify() == 0
+
+    # One sided 3rd derivative at "half-way"
+    assert (d3fdx3.as_finite_difference([x-h, x+h, x + 3*h, x + 5*h]) -
+            (2*h)**-3 * (f(x + 5*h)-f(x-h) +
+                         3*(f(x+h)-f(x + 3*h)))).simplify() == 0
+
+    # issue 11007
+    y = Symbol('y', real=True)
+    d2fdxdy = f(x, y).diff(x, y)
+
+    ref0 = Derivative(f(x + S.Half, y), y) - Derivative(f(x - S.Half, y), y)
+    assert (d2fdxdy.as_finite_difference(wrt=x) - ref0).simplify() == 0
+
+    half = S.Half
+    xm, xp, ym, yp = x-half, x+half, y-half, y+half
+    ref2 = f(xm, ym) + f(xp, yp) - f(xp, ym) - f(xm, yp)
+    assert (d2fdxdy.as_finite_difference() - ref2).simplify() == 0
+
+
+def test_issue_11159():
+    # Tests Application._eval_subs
+    with _exp_is_pow(False):
+        expr1 = E
+        expr0 = expr1 * expr1
+        expr1 = expr0.subs(expr1,expr0)
+        assert expr0 == expr1
+    with _exp_is_pow(True):
+        expr1 = E
+        expr0 = expr1 * expr1
+        expr2 = expr0.subs(expr1, expr0)
+        assert expr2 == E ** 4
+
+
+def test_issue_12005():
+    e1 = Subs(Derivative(f(x), x), x, x)
+    assert e1.diff(x) == Derivative(f(x), x, x)
+    e2 = Subs(Derivative(f(x), x), x, x**2 + 1)
+    assert e2.diff(x) == 2*x*Subs(Derivative(f(x), x, x), x, x**2 + 1)
+    e3 = Subs(Derivative(f(x) + y**2 - y, y), y, y**2)
+    assert e3.diff(y) == 4*y
+    e4 = Subs(Derivative(f(x + y), y), y, (x**2))
+    assert e4.diff(y) is S.Zero
+    e5 = Subs(Derivative(f(x), x), (y, z), (y, z))
+    assert e5.diff(x) == Derivative(f(x), x, x)
+    assert f(g(x)).diff(g(x), g(x)) == Derivative(f(g(x)), g(x), g(x))
+
+
+def test_issue_13843():
+    x = symbols('x')
+    f = Function('f')
+    m, n = symbols('m n', integer=True)
+    assert Derivative(Derivative(f(x), (x, m)), (x, n)) == Derivative(f(x), (x, m + n))
+    assert Derivative(Derivative(f(x), (x, m+5)), (x, n+3)) == Derivative(f(x), (x, m + n + 8))
+
+    assert Derivative(f(x), (x, n)).doit() == Derivative(f(x), (x, n))
+
+
+def test_order_could_be_zero():
+    x, y = symbols('x, y')
+    n = symbols('n', integer=True, nonnegative=True)
+    m = symbols('m', integer=True, positive=True)
+    assert diff(y, (x, n)) == Piecewise((y, Eq(n, 0)), (0, True))
+    assert diff(y, (x, n + 1)) is S.Zero
+    assert diff(y, (x, m)) is S.Zero
+
+
+def test_undefined_function_eq():
+    f = Function('f')
+    f2 = Function('f')
+    g = Function('g')
+    f_real = Function('f', is_real=True)
+
+    # This test may only be meaningful if the cache is turned off
+    assert f == f2
+    assert hash(f) == hash(f2)
+    assert f == f
+
+    assert f != g
+
+    assert f != f_real
+
+
+def test_function_assumptions():
+    x = Symbol('x')
+    f = Function('f')
+    f_real = Function('f', real=True)
+    f_real1 = Function('f', real=1)
+    f_real_inherit = Function(Symbol('f', real=True))
+
+    assert f_real == f_real1  # assumptions are sanitized
+    assert f != f_real
+    assert f(x) != f_real(x)
+
+    assert f(x).is_real is None
+    assert f_real(x).is_real is True
+    assert f_real_inherit(x).is_real is True and f_real_inherit.name == 'f'
+
+    # Can also do it this way, but it won't be equal to f_real because of the
+    # way UndefinedFunction.__new__ works. Any non-recognized assumptions
+    # are just added literally as something which is used in the hash
+    f_real2 = Function('f', is_real=True)
+    assert f_real2(x).is_real is True
+
+
+def test_undef_fcn_float_issue_6938():
+    f = Function('ceil')
+    assert not f(0.3).is_number
+    f = Function('sin')
+    assert not f(0.3).is_number
+    assert not f(pi).evalf().is_number
+    x = Symbol('x')
+    assert not f(x).evalf(subs={x:1.2}).is_number
+
+
+def test_undefined_function_eval():
+    # Issue 15170. Make sure UndefinedFunction with eval defined works
+    # properly.
+
+    fdiff = lambda self, argindex=1: cos(self.args[argindex - 1])
+    eval = classmethod(lambda cls, t: None)
+    _imp_ = classmethod(lambda cls, t: sin(t))
+
+    temp = Function('temp', fdiff=fdiff, eval=eval, _imp_=_imp_)
+
+    expr = temp(t)
+    assert sympify(expr) == expr
+    assert type(sympify(expr)).fdiff.__name__ == "<lambda>"
+    assert expr.diff(t) == cos(t)
+
+
+def test_issue_15241():
+    F = f(x)
+    Fx = F.diff(x)
+    assert (F + x*Fx).diff(x, Fx) == 2
+    assert (F + x*Fx).diff(Fx, x) == 1
+    assert (x*F + x*Fx*F).diff(F, x) == x*Fx.diff(x) + Fx + 1
+    assert (x*F + x*Fx*F).diff(x, F) == x*Fx.diff(x) + Fx + 1
+    y = f(x)
+    G = f(y)
+    Gy = G.diff(y)
+    assert (G + y*Gy).diff(y, Gy) == 2
+    assert (G + y*Gy).diff(Gy, y) == 1
+    assert (y*G + y*Gy*G).diff(G, y) == y*Gy.diff(y) + Gy + 1
+    assert (y*G + y*Gy*G).diff(y, G) == y*Gy.diff(y) + Gy + 1
+
+
+def test_issue_15226():
+    assert Subs(Derivative(f(y), x, y), y, g(x)).doit() != 0
+
+
+def test_issue_7027():
+    for wrt in (cos(x), re(x), Derivative(cos(x), x)):
+        raises(ValueError, lambda: diff(f(x), wrt))
+
+
+def test_derivative_quick_exit():
+    assert f(x).diff(y) == 0
+    assert f(x).diff(y, f(x)) == 0
+    assert f(x).diff(x, f(y)) == 0
+    assert f(f(x)).diff(x, f(x), f(y)) == 0
+    assert f(f(x)).diff(x, f(x), y) == 0
+    assert f(x).diff(g(x)) == 0
+    assert f(x).diff(x, f(x).diff(x)) == 1
+    df = f(x).diff(x)
+    assert f(x).diff(df) == 0
+    dg = g(x).diff(x)
+    assert dg.diff(df).doit() == 0
+
+
+def test_issue_15084_13166():
+    eq = f(x, g(x))
+    assert eq.diff((g(x), y)) == Derivative(f(x, g(x)), (g(x), y))
+    # issue 13166
+    assert eq.diff(x, 2).doit() == (
+        (Derivative(f(x, g(x)), (g(x), 2))*Derivative(g(x), x) +
+        Subs(Derivative(f(x, _xi_2), _xi_2, x), _xi_2, g(x)))*Derivative(g(x),
+        x) + Derivative(f(x, g(x)), g(x))*Derivative(g(x), (x, 2)) +
+        Derivative(g(x), x)*Subs(Derivative(f(_xi_1, g(x)), _xi_1, g(x)),
+        _xi_1, x) + Subs(Derivative(f(_xi_1, g(x)), (_xi_1, 2)), _xi_1, x))
+    # issue 6681
+    assert diff(f(x, t, g(x, t)), x).doit() == (
+        Derivative(f(x, t, g(x, t)), g(x, t))*Derivative(g(x, t), x) +
+        Subs(Derivative(f(_xi_1, t, g(x, t)), _xi_1), _xi_1, x))
+    # make sure the order doesn't matter when using diff
+    assert eq.diff(x, g(x)) == eq.diff(g(x), x)
+
+
+def test_negative_counts():
+    # issue 13873
+    raises(ValueError, lambda: sin(x).diff(x, -1))
+
+
+def test_Derivative__new__():
+    raises(TypeError, lambda: f(x).diff((x, 2), 0))
+    assert f(x, y).diff([(x, y), 0]) == f(x, y)
+    assert f(x, y).diff([(x, y), 1]) == NDimArray([
+        Derivative(f(x, y), x), Derivative(f(x, y), y)])
+    assert f(x,y).diff(y, (x, z), y, x) == Derivative(
+        f(x, y), (x, z + 1), (y, 2))
+    assert Matrix([x]).diff(x, 2) == Matrix([0])  # is_zero exit
+
+
+def test_issue_14719_10150():
+    class V(Expr):
+        _diff_wrt = True
+        is_scalar = False
+    assert V().diff(V()) == Derivative(V(), V())
+    assert (2*V()).diff(V()) == 2*Derivative(V(), V())
+    class X(Expr):
+        _diff_wrt = True
+    assert X().diff(X()) == 1
+    assert (2*X()).diff(X()) == 2
+
+
+def test_noncommutative_issue_15131():
+    x = Symbol('x', commutative=False)
+    t = Symbol('t', commutative=False)
+    fx = Function('Fx', commutative=False)(x)
+    ft = Function('Ft', commutative=False)(t)
+    A = Symbol('A', commutative=False)
+    eq = fx * A * ft
+    eqdt = eq.diff(t)
+    assert eqdt.args[-1] == ft.diff(t)
+
+
+def test_Subs_Derivative():
+    a = Derivative(f(g(x), h(x)), g(x), h(x),x)
+    b = Derivative(Derivative(f(g(x), h(x)), g(x), h(x)),x)
+    c = f(g(x), h(x)).diff(g(x), h(x), x)
+    d = f(g(x), h(x)).diff(g(x), h(x)).diff(x)
+    e = Derivative(f(g(x), h(x)), x)
+    eqs = (a, b, c, d, e)
+    subs = lambda arg: arg.subs(f, Lambda((x, y), exp(x + y))
+        ).subs(g(x), 1/x).subs(h(x), x**3)
+    ans = 3*x**2*exp(1/x)*exp(x**3) - exp(1/x)*exp(x**3)/x**2
+    assert all(subs(i).doit().expand() == ans for i in eqs)
+    assert all(subs(i.doit()).doit().expand() == ans for i in eqs)
+
+def test_issue_15360():
+    f = Function('f')
+    assert f.name == 'f'
+
+
+def test_issue_15947():
+    assert f._diff_wrt is False
+    raises(TypeError, lambda: f(f))
+    raises(TypeError, lambda: f(x).diff(f))
+
+
+def test_Derivative_free_symbols():
+    f = Function('f')
+    n = Symbol('n', integer=True, positive=True)
+    assert diff(f(x), (x, n)).free_symbols == {n, x}
+
+
+def test_issue_20683():
+    x = Symbol('x')
+    y = Symbol('y')
+    z = Symbol('z')
+    y = Derivative(z, x).subs(x,0)
+    assert y.doit() == 0
+    y = Derivative(8, x).subs(x,0)
+    assert y.doit() == 0
+
+
+def test_issue_10503():
+    f = exp(x**3)*cos(x**6)
+    assert f.series(x, 0, 14) == 1 + x**3 + x**6/2 + x**9/6 - 11*x**12/24 + O(x**14)
+
+
+def test_issue_17382():
+    # copied from sympy/core/tests/test_evalf.py
+    def NS(e, n=15, **options):
+        return sstr(sympify(e).evalf(n, **options), full_prec=True)
+
+    x = Symbol('x')
+    expr = solveset(2 * cos(x) * cos(2 * x) - 1, x, S.Reals)
+    expected = "Union(" \
+               "ImageSet(Lambda(_n, 6.28318530717959*_n + 5.79812359592087), Integers), " \
+               "ImageSet(Lambda(_n, 6.28318530717959*_n + 0.485061711258717), Integers))"
+    assert NS(expr) == expected
+
+def test_eval_sympified():
+    # Check both arguments and return types from eval are sympified
+
+    class F(Function):
+        @classmethod
+        def eval(cls, x):
+            assert x is S.One
+            return 1
+
+    assert F(1) is S.One
+
+    # String arguments are not allowed
+    class F2(Function):
+        @classmethod
+        def eval(cls, x):
+            if x == 0:
+                return '1'
+
+    raises(SympifyError, lambda: F2(0))
+    F2(1) # Doesn't raise
+
+    # TODO: Disable string inputs (https://github.com/sympy/sympy/issues/11003)
+    # raises(SympifyError, lambda: F2('2'))
+
+def test_eval_classmethod_check():
+    with raises(TypeError):
+        class F(Function):
+            def eval(self, x):
+                pass

env-llmeval/lib/python3.10/site-packages/sympy/core/tests/test_kind.py

@@ -0,0 +1,57 @@
+from sympy.core.add import Add
+from sympy.core.kind import NumberKind, UndefinedKind
+from sympy.core.mul import Mul
+from sympy.core.numbers import pi, zoo, I, AlgebraicNumber
+from sympy.core.singleton import S
+from sympy.core.symbol import Symbol
+from sympy.integrals.integrals import Integral
+from sympy.core.function import Derivative
+from sympy.matrices import (Matrix, SparseMatrix, ImmutableMatrix,
+    ImmutableSparseMatrix, MatrixSymbol, MatrixKind, MatMul)
+
+comm_x = Symbol('x')
+noncomm_x = Symbol('x', commutative=False)
+
+def test_NumberKind():
+    assert S.One.kind is NumberKind
+    assert pi.kind is NumberKind
+    assert S.NaN.kind is NumberKind
+    assert zoo.kind is NumberKind
+    assert I.kind is NumberKind
+    assert AlgebraicNumber(1).kind is NumberKind
+
+def test_Add_kind():
+    assert Add(2, 3, evaluate=False).kind is NumberKind
+    assert Add(2,comm_x).kind is NumberKind
+    assert Add(2,noncomm_x).kind is UndefinedKind
+
+def test_mul_kind():
+    assert Mul(2,comm_x, evaluate=False).kind is NumberKind
+    assert Mul(2,3, evaluate=False).kind is NumberKind
+    assert Mul(noncomm_x,2, evaluate=False).kind is UndefinedKind
+    assert Mul(2,noncomm_x, evaluate=False).kind is UndefinedKind
+
+def test_Symbol_kind():
+    assert comm_x.kind is NumberKind
+    assert noncomm_x.kind is UndefinedKind
+
+def test_Integral_kind():
+    A = MatrixSymbol('A', 2,2)
+    assert Integral(comm_x, comm_x).kind is NumberKind
+    assert Integral(A, comm_x).kind is MatrixKind(NumberKind)
+
+def test_Derivative_kind():
+    A = MatrixSymbol('A', 2,2)
+    assert Derivative(comm_x, comm_x).kind is NumberKind
+    assert Derivative(A, comm_x).kind is MatrixKind(NumberKind)
+
+def test_Matrix_kind():
+    classes = (Matrix, SparseMatrix, ImmutableMatrix, ImmutableSparseMatrix)
+    for cls in classes:
+        m = cls.zeros(3, 2)
+        assert m.kind is MatrixKind(NumberKind)
+
+def test_MatMul_kind():
+    M = Matrix([[1,2],[3,4]])
+    assert MatMul(2, M).kind is MatrixKind(NumberKind)
+    assert MatMul(comm_x, M).kind is MatrixKind(NumberKind)

env-llmeval/lib/python3.10/site-packages/sympy/core/tests/test_logic.py

@@ -0,0 +1,198 @@
+from sympy.core.logic import (fuzzy_not, Logic, And, Or, Not, fuzzy_and,
+    fuzzy_or, _fuzzy_group, _torf, fuzzy_nand, fuzzy_xor)
+from sympy.testing.pytest import raises
+
+from itertools import product
+
+T = True
+F = False
+U = None
+
+
+
+def test_torf():
+    v = [T, F, U]
+    for i in product(*[v]*3):
+        assert _torf(i) is (True if all(j for j in i) else
+                            (False if all(j is False for j in i) else None))
+
+
+def test_fuzzy_group():
+    v = [T, F, U]
+    for i in product(*[v]*3):
+        assert _fuzzy_group(i) is (None if None in i else
+                                   (True if all(j for j in i) else False))
+        assert _fuzzy_group(i, quick_exit=True) is \
+            (None if (i.count(False) > 1) else
+             (None if None in i else (True if all(j for j in i) else False)))
+    it = (True if (i == 0) else None for i in range(2))
+    assert _torf(it) is None
+    it = (True if (i == 1) else None for i in range(2))
+    assert _torf(it) is None
+
+
+def test_fuzzy_not():
+    assert fuzzy_not(T) == F
+    assert fuzzy_not(F) == T
+    assert fuzzy_not(U) == U
+
+
+def test_fuzzy_and():
+    assert fuzzy_and([T, T]) == T
+    assert fuzzy_and([T, F]) == F
+    assert fuzzy_and([T, U]) == U
+    assert fuzzy_and([F, F]) == F
+    assert fuzzy_and([F, U]) == F
+    assert fuzzy_and([U, U]) == U
+    assert [fuzzy_and([w]) for w in [U, T, F]] == [U, T, F]
+    assert fuzzy_and([T, F, U]) == F
+    assert fuzzy_and([]) == T
+    raises(TypeError, lambda: fuzzy_and())
+
+
+def test_fuzzy_or():
+    assert fuzzy_or([T, T]) == T
+    assert fuzzy_or([T, F]) == T
+    assert fuzzy_or([T, U]) == T
+    assert fuzzy_or([F, F]) == F
+    assert fuzzy_or([F, U]) == U
+    assert fuzzy_or([U, U]) == U
+    assert [fuzzy_or([w]) for w in [U, T, F]] == [U, T, F]
+    assert fuzzy_or([T, F, U]) == T
+    assert fuzzy_or([]) == F
+    raises(TypeError, lambda: fuzzy_or())
+
+
+def test_logic_cmp():
+    l1 = And('a', Not('b'))
+    l2 = And('a', Not('b'))
+
+    assert hash(l1) == hash(l2)
+    assert (l1 == l2) == T
+    assert (l1 != l2) == F
+
+    assert And('a', 'b', 'c') == And('b', 'a', 'c')
+    assert And('a', 'b', 'c') == And('c', 'b', 'a')
+    assert And('a', 'b', 'c') == And('c', 'a', 'b')
+
+    assert Not('a') < Not('b')
+    assert (Not('b') < Not('a')) is False
+    assert (Not('a') < 2) is False
+
+
+def test_logic_onearg():
+    assert And() is True
+    assert Or() is False
+
+    assert And(T) == T
+    assert And(F) == F
+    assert Or(T) == T
+    assert Or(F) == F
+
+    assert And('a') == 'a'
+    assert Or('a') == 'a'
+
+
+def test_logic_xnotx():
+    assert And('a', Not('a')) == F
+    assert Or('a', Not('a')) == T
+
+
+def test_logic_eval_TF():
+    assert And(F, F) == F
+    assert And(F, T) == F
+    assert And(T, F) == F
+    assert And(T, T) == T
+
+    assert Or(F, F) == F
+    assert Or(F, T) == T
+    assert Or(T, F) == T
+    assert Or(T, T) == T
+
+    assert And('a', T) == 'a'
+    assert And('a', F) == F
+    assert Or('a', T) == T
+    assert Or('a', F) == 'a'
+
+
+def test_logic_combine_args():
+    assert And('a', 'b', 'a') == And('a', 'b')
+    assert Or('a', 'b', 'a') == Or('a', 'b')
+
+    assert And(And('a', 'b'), And('c', 'd')) == And('a', 'b', 'c', 'd')
+    assert Or(Or('a', 'b'), Or('c', 'd')) == Or('a', 'b', 'c', 'd')
+
+    assert Or('t', And('n', 'p', 'r'), And('n', 'r'), And('n', 'p', 'r'), 't',
+              And('n', 'r')) == Or('t', And('n', 'p', 'r'), And('n', 'r'))
+
+
+def test_logic_expand():
+    t = And(Or('a', 'b'), 'c')
+    assert t.expand() == Or(And('a', 'c'), And('b', 'c'))
+
+    t = And(Or('a', Not('b')), 'b')
+    assert t.expand() == And('a', 'b')
+
+    t = And(Or('a', 'b'), Or('c', 'd'))
+    assert t.expand() == \
+        Or(And('a', 'c'), And('a', 'd'), And('b', 'c'), And('b', 'd'))
+
+
+def test_logic_fromstring():
+    S = Logic.fromstring
+
+    assert S('a') == 'a'
+    assert S('!a') == Not('a')
+    assert S('a & b') == And('a', 'b')
+    assert S('a | b') == Or('a', 'b')
+    assert S('a | b & c') == And(Or('a', 'b'), 'c')
+    assert S('a & b | c') == Or(And('a', 'b'), 'c')
+    assert S('a & b & c') == And('a', 'b', 'c')
+    assert S('a | b | c') == Or('a', 'b', 'c')
+
+    raises(ValueError, lambda: S('| a'))
+    raises(ValueError, lambda: S('& a'))
+    raises(ValueError, lambda: S('a | | b'))
+    raises(ValueError, lambda: S('a | & b'))
+    raises(ValueError, lambda: S('a & & b'))
+    raises(ValueError, lambda: S('a |'))
+    raises(ValueError, lambda: S('a|b'))
+    raises(ValueError, lambda: S('!'))
+    raises(ValueError, lambda: S('! a'))
+    raises(ValueError, lambda: S('!(a + 1)'))
+    raises(ValueError, lambda: S(''))
+
+
+def test_logic_not():
+    assert Not('a') != '!a'
+    assert Not('!a') != 'a'
+    assert Not(True) == False
+    assert Not(False) == True
+
+    # NOTE: we may want to change default Not behaviour and put this
+    # functionality into some method.
+    assert Not(And('a', 'b')) == Or(Not('a'), Not('b'))
+    assert Not(Or('a', 'b')) == And(Not('a'), Not('b'))
+
+    raises(ValueError, lambda: Not(1))
+
+
+def test_formatting():
+    S = Logic.fromstring
+    raises(ValueError, lambda: S('a&b'))
+    raises(ValueError, lambda: S('a|b'))
+    raises(ValueError, lambda: S('! a'))
+
+
+def test_fuzzy_xor():
+    assert fuzzy_xor((None,)) is None
+    assert fuzzy_xor((None, True)) is None
+    assert fuzzy_xor((None, False)) is None
+    assert fuzzy_xor((True, False)) is True
+    assert fuzzy_xor((True, True)) is False
+    assert fuzzy_xor((True, True, False)) is False
+    assert fuzzy_xor((True, True, False, True)) is True
+
+def test_fuzzy_nand():
+    for args in [(1, 0), (1, 1), (0, 0)]:
+        assert fuzzy_nand(args) == fuzzy_not(fuzzy_and(args))

env-llmeval/lib/python3.10/site-packages/sympy/core/tests/test_match.py

@@ -0,0 +1,766 @@
+from sympy import abc
+from sympy.concrete.summations import Sum
+from sympy.core.add import Add
+from sympy.core.function import (Derivative, Function, diff)
+from sympy.core.mul import Mul
+from sympy.core.numbers import (Float, I, Integer, Rational, oo, pi)
+from sympy.core.singleton import S
+from sympy.core.symbol import (Symbol, Wild, symbols)
+from sympy.functions.elementary.exponential import (exp, log)
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.functions.elementary.trigonometric import (cos, sin)
+from sympy.functions.special.hyper import meijerg
+from sympy.polys.polytools import Poly
+from sympy.simplify.radsimp import collect
+from sympy.simplify.simplify import signsimp
+
+from sympy.testing.pytest import XFAIL
+
+
+def test_symbol():
+    x = Symbol('x')
+    a, b, c, p, q = map(Wild, 'abcpq')
+
+    e = x
+    assert e.match(x) == {}
+    assert e.matches(x) == {}
+    assert e.match(a) == {a: x}
+
+    e = Rational(5)
+    assert e.match(c) == {c: 5}
+    assert e.match(e) == {}
+    assert e.match(e + 1) is None
+
+
+def test_add():
+    x, y, a, b, c = map(Symbol, 'xyabc')
+    p, q, r = map(Wild, 'pqr')
+
+    e = a + b
+    assert e.match(p + b) == {p: a}
+    assert e.match(p + a) == {p: b}
+
+    e = 1 + b
+    assert e.match(p + b) == {p: 1}
+
+    e = a + b + c
+    assert e.match(a + p + c) == {p: b}
+    assert e.match(b + p + c) == {p: a}
+
+    e = a + b + c + x
+    assert e.match(a + p + x + c) == {p: b}
+    assert e.match(b + p + c + x) == {p: a}
+    assert e.match(b) is None
+    assert e.match(b + p) == {p: a + c + x}
+    assert e.match(a + p + c) == {p: b + x}
+    assert e.match(b + p + c) == {p: a + x}
+
+    e = 4*x + 5
+    assert e.match(4*x + p) == {p: 5}
+    assert e.match(3*x + p) == {p: x + 5}
+    assert e.match(p*x + 5) == {p: 4}
+
+
+def test_power():
+    x, y, a, b, c = map(Symbol, 'xyabc')
+    p, q, r = map(Wild, 'pqr')
+
+    e = (x + y)**a
+    assert e.match(p**q) == {p: x + y, q: a}
+    assert e.match(p**p) is None
+
+    e = (x + y)**(x + y)
+    assert e.match(p**p) == {p: x + y}
+    assert e.match(p**q) == {p: x + y, q: x + y}
+
+    e = (2*x)**2
+    assert e.match(p*q**r) == {p: 4, q: x, r: 2}
+
+    e = Integer(1)
+    assert e.match(x**p) == {p: 0}
+
+
+def test_match_exclude():
+    x = Symbol('x')
+    y = Symbol('y')
+    p = Wild("p")
+    q = Wild("q")
+    r = Wild("r")
+
+    e = Rational(6)
+    assert e.match(2*p) == {p: 3}
+
+    e = 3/(4*x + 5)
+    assert e.match(3/(p*x + q)) == {p: 4, q: 5}
+
+    e = 3/(4*x + 5)
+    assert e.match(p/(q*x + r)) == {p: 3, q: 4, r: 5}
+
+    e = 2/(x + 1)
+    assert e.match(p/(q*x + r)) == {p: 2, q: 1, r: 1}
+
+    e = 1/(x + 1)
+    assert e.match(p/(q*x + r)) == {p: 1, q: 1, r: 1}
+
+    e = 4*x + 5
+    assert e.match(p*x + q) == {p: 4, q: 5}
+
+    e = 4*x + 5*y + 6
+    assert e.match(p*x + q*y + r) == {p: 4, q: 5, r: 6}
+
+    a = Wild('a', exclude=[x])
+
+    e = 3*x
+    assert e.match(p*x) == {p: 3}
+    assert e.match(a*x) == {a: 3}
+
+    e = 3*x**2
+    assert e.match(p*x) == {p: 3*x}
+    assert e.match(a*x) is None
+
+    e = 3*x + 3 + 6/x
+    assert e.match(p*x**2 + p*x + 2*p) == {p: 3/x}
+    assert e.match(a*x**2 + a*x + 2*a) is None
+
+
+def test_mul():
+    x, y, a, b, c = map(Symbol, 'xyabc')
+    p, q = map(Wild, 'pq')
+
+    e = 4*x
+    assert e.match(p*x) == {p: 4}
+    assert e.match(p*y) is None
+    assert e.match(e + p*y) == {p: 0}
+
+    e = a*x*b*c
+    assert e.match(p*x) == {p: a*b*c}
+    assert e.match(c*p*x) == {p: a*b}
+
+    e = (a + b)*(a + c)
+    assert e.match((p + b)*(p + c)) == {p: a}
+
+    e = x
+    assert e.match(p*x) == {p: 1}
+
+    e = exp(x)
+    assert e.match(x**p*exp(x*q)) == {p: 0, q: 1}
+
+    e = I*Poly(x, x)
+    assert e.match(I*p) == {p: x}
+
+
+def test_mul_noncommutative():
+    x, y = symbols('x y')
+    A, B, C = symbols('A B C', commutative=False)
+    u, v = symbols('u v', cls=Wild)
+    w, z = symbols('w z', cls=Wild, commutative=False)
+
+    assert (u*v).matches(x) in ({v: x, u: 1}, {u: x, v: 1})
+    assert (u*v).matches(x*y) in ({v: y, u: x}, {u: y, v: x})
+    assert (u*v).matches(A) is None
+    assert (u*v).matches(A*B) is None
+    assert (u*v).matches(x*A) is None
+    assert (u*v).matches(x*y*A) is None
+    assert (u*v).matches(x*A*B) is None
+    assert (u*v).matches(x*y*A*B) is None
+
+    assert (v*w).matches(x) is None
+    assert (v*w).matches(x*y) is None
+    assert (v*w).matches(A) == {w: A, v: 1}
+    assert (v*w).matches(A*B) == {w: A*B, v: 1}
+    assert (v*w).matches(x*A) == {w: A, v: x}
+    assert (v*w).matches(x*y*A) == {w: A, v: x*y}
+    assert (v*w).matches(x*A*B) == {w: A*B, v: x}
+    assert (v*w).matches(x*y*A*B) == {w: A*B, v: x*y}
+
+    assert (v*w).matches(-x) is None
+    assert (v*w).matches(-x*y) is None
+    assert (v*w).matches(-A) == {w: A, v: -1}
+    assert (v*w).matches(-A*B) == {w: A*B, v: -1}
+    assert (v*w).matches(-x*A) == {w: A, v: -x}
+    assert (v*w).matches(-x*y*A) == {w: A, v: -x*y}
+    assert (v*w).matches(-x*A*B) == {w: A*B, v: -x}
+    assert (v*w).matches(-x*y*A*B) == {w: A*B, v: -x*y}
+
+    assert (w*z).matches(x) is None
+    assert (w*z).matches(x*y) is None
+    assert (w*z).matches(A) is None
+    assert (w*z).matches(A*B) == {w: A, z: B}
+    assert (w*z).matches(B*A) == {w: B, z: A}
+    assert (w*z).matches(A*B*C) in [{w: A, z: B*C}, {w: A*B, z: C}]
+    assert (w*z).matches(x*A) is None
+    assert (w*z).matches(x*y*A) is None
+    assert (w*z).matches(x*A*B) is None
+    assert (w*z).matches(x*y*A*B) is None
+
+    assert (w*A).matches(A) is None
+    assert (A*w*B).matches(A*B) is None
+
+    assert (u*w*z).matches(x) is None
+    assert (u*w*z).matches(x*y) is None
+    assert (u*w*z).matches(A) is None
+    assert (u*w*z).matches(A*B) == {u: 1, w: A, z: B}
+    assert (u*w*z).matches(B*A) == {u: 1, w: B, z: A}
+    assert (u*w*z).matches(x*A) is None
+    assert (u*w*z).matches(x*y*A) is None
+    assert (u*w*z).matches(x*A*B) == {u: x, w: A, z: B}
+    assert (u*w*z).matches(x*B*A) == {u: x, w: B, z: A}
+    assert (u*w*z).matches(x*y*A*B) == {u: x*y, w: A, z: B}
+    assert (u*w*z).matches(x*y*B*A) == {u: x*y, w: B, z: A}
+
+    assert (u*A).matches(x*A) == {u: x}
+    assert (u*A).matches(x*A*B) is None
+    assert (u*B).matches(x*A) is None
+    assert (u*A*B).matches(x*A*B) == {u: x}
+    assert (u*A*B).matches(x*B*A) is None
+    assert (u*A*B).matches(x*A) is None
+
+    assert (u*w*A).matches(x*A*B) is None
+    assert (u*w*B).matches(x*A*B) == {u: x, w: A}
+
+    assert (u*v*A*B).matches(x*A*B) in [{u: x, v: 1}, {v: x, u: 1}]
+    assert (u*v*A*B).matches(x*B*A) is None
+    assert (u*v*A*B).matches(u*v*A*C) is None
+
+
+def test_mul_noncommutative_mismatch():
+    A, B, C = symbols('A B C', commutative=False)
+    w = symbols('w', cls=Wild, commutative=False)
+
+    assert (w*B*w).matches(A*B*A) == {w: A}
+    assert (w*B*w).matches(A*C*B*A*C) == {w: A*C}
+    assert (w*B*w).matches(A*C*B*A*B) is None
+    assert (w*B*w).matches(A*B*C) is None
+    assert (w*w*C).matches(A*B*C) is None
+
+
+def test_mul_noncommutative_pow():
+    A, B, C = symbols('A B C', commutative=False)
+    w = symbols('w', cls=Wild, commutative=False)
+
+    assert (A*B*w).matches(A*B**2) == {w: B}
+    assert (A*(B**2)*w*(B**3)).matches(A*B**8) == {w: B**3}
+    assert (A*B*w*C).matches(A*(B**4)*C) == {w: B**3}
+
+    assert (A*B*(w**(-1))).matches(A*B*(C**(-1))) == {w: C}
+    assert (A*(B*w)**(-1)*C).matches(A*(B*C)**(-1)*C) == {w: C}
+
+    assert ((w**2)*B*C).matches((A**2)*B*C) == {w: A}
+    assert ((w**2)*B*(w**3)).matches((A**2)*B*(A**3)) == {w: A}
+    assert ((w**2)*B*(w**4)).matches((A**2)*B*(A**2)) is None
+
+def test_complex():
+    a, b, c = map(Symbol, 'abc')
+    x, y = map(Wild, 'xy')
+
+    assert (1 + I).match(x + I) == {x: 1}
+    assert (a + I).match(x + I) == {x: a}
+    assert (2*I).match(x*I) == {x: 2}
+    assert (a*I).match(x*I) == {x: a}
+    assert (a*I).match(x*y) == {x: I, y: a}
+    assert (2*I).match(x*y) == {x: 2, y: I}
+    assert (a + b*I).match(x + y*I) == {x: a, y: b}
+
+
+def test_functions():
+    from sympy.core.function import WildFunction
+    x = Symbol('x')
+    g = WildFunction('g')
+    p = Wild('p')
+    q = Wild('q')
+
+    f = cos(5*x)
+    notf = x
+    assert f.match(p*cos(q*x)) == {p: 1, q: 5}
+    assert f.match(p*g) == {p: 1, g: cos(5*x)}
+    assert notf.match(g) is None
+
+
+@XFAIL
+def test_functions_X1():
+    from sympy.core.function import WildFunction
+    x = Symbol('x')
+    g = WildFunction('g')
+    p = Wild('p')
+    q = Wild('q')
+
+    f = cos(5*x)
+    assert f.match(p*g(q*x)) == {p: 1, g: cos, q: 5}
+
+
+def test_interface():
+    x, y = map(Symbol, 'xy')
+    p, q = map(Wild, 'pq')
+
+    assert (x + 1).match(p + 1) == {p: x}
+    assert (x*3).match(p*3) == {p: x}
+    assert (x**3).match(p**3) == {p: x}
+    assert (x*cos(y)).match(p*cos(q)) == {p: x, q: y}
+
+    assert (x*y).match(p*q) in [{p:x, q:y}, {p:y, q:x}]
+    assert (x + y).match(p + q) in [{p:x, q:y}, {p:y, q:x}]
+    assert (x*y + 1).match(p*q) in [{p:1, q:1 + x*y}, {p:1 + x*y, q:1}]
+
+
+def test_derivative1():
+    x, y = map(Symbol, 'xy')
+    p, q = map(Wild, 'pq')
+
+    f = Function('f', nargs=1)
+    fd = Derivative(f(x), x)
+
+    assert fd.match(p) == {p: fd}
+    assert (fd + 1).match(p + 1) == {p: fd}
+    assert (fd).match(fd) == {}
+    assert (3*fd).match(p*fd) is not None
+    assert (3*fd - 1).match(p*fd + q) == {p: 3, q: -1}
+
+
+def test_derivative_bug1():
+    f = Function("f")
+    x = Symbol("x")
+    a = Wild("a", exclude=[f, x])
+    b = Wild("b", exclude=[f])
+    pattern = a * Derivative(f(x), x, x) + b
+    expr = Derivative(f(x), x) + x**2
+    d1 = {b: x**2}
+    d2 = pattern.xreplace(d1).matches(expr, d1)
+    assert d2 is None
+
+
+def test_derivative2():
+    f = Function("f")
+    x = Symbol("x")
+    a = Wild("a", exclude=[f, x])
+    b = Wild("b", exclude=[f])
+    e = Derivative(f(x), x)
+    assert e.match(Derivative(f(x), x)) == {}
+    assert e.match(Derivative(f(x), x, x)) is None
+    e = Derivative(f(x), x, x)
+    assert e.match(Derivative(f(x), x)) is None
+    assert e.match(Derivative(f(x), x, x)) == {}
+    e = Derivative(f(x), x) + x**2
+    assert e.match(a*Derivative(f(x), x) + b) == {a: 1, b: x**2}
+    assert e.match(a*Derivative(f(x), x, x) + b) is None
+    e = Derivative(f(x), x, x) + x**2
+    assert e.match(a*Derivative(f(x), x) + b) is None
+    assert e.match(a*Derivative(f(x), x, x) + b) == {a: 1, b: x**2}
+
+
+def test_match_deriv_bug1():
+    n = Function('n')
+    l = Function('l')
+
+    x = Symbol('x')
+    p = Wild('p')
+
+    e = diff(l(x), x)/x - diff(diff(n(x), x), x)/2 - \
+        diff(n(x), x)**2/4 + diff(n(x), x)*diff(l(x), x)/4
+    e = e.subs(n(x), -l(x)).doit()
+    t = x*exp(-l(x))
+    t2 = t.diff(x, x)/t
+    assert e.match( (p*t2).expand() ) == {p: Rational(-1, 2)}
+
+
+def test_match_bug2():
+    x, y = map(Symbol, 'xy')
+    p, q, r = map(Wild, 'pqr')
+    res = (x + y).match(p + q + r)
+    assert (p + q + r).subs(res) == x + y
+
+
+def test_match_bug3():
+    x, a, b = map(Symbol, 'xab')
+    p = Wild('p')
+    assert (b*x*exp(a*x)).match(x*exp(p*x)) is None
+
+
+def test_match_bug4():
+    x = Symbol('x')
+    p = Wild('p')
+    e = x
+    assert e.match(-p*x) == {p: -1}
+
+
+def test_match_bug5():
+    x = Symbol('x')
+    p = Wild('p')
+    e = -x
+    assert e.match(-p*x) == {p: 1}
+
+
+def test_match_bug6():
+    x = Symbol('x')
+    p = Wild('p')
+    e = x
+    assert e.match(3*p*x) == {p: Rational(1)/3}
+
+
+def test_match_polynomial():
+    x = Symbol('x')
+    a = Wild('a', exclude=[x])
+    b = Wild('b', exclude=[x])
+    c = Wild('c', exclude=[x])
+    d = Wild('d', exclude=[x])
+
+    eq = 4*x**3 + 3*x**2 + 2*x + 1
+    pattern = a*x**3 + b*x**2 + c*x + d
+    assert eq.match(pattern) == {a: 4, b: 3, c: 2, d: 1}
+    assert (eq - 3*x**2).match(pattern) == {a: 4, b: 0, c: 2, d: 1}
+    assert (x + sqrt(2) + 3).match(a + b*x + c*x**2) == \
+        {b: 1, a: sqrt(2) + 3, c: 0}
+
+
+def test_exclude():
+    x, y, a = map(Symbol, 'xya')
+    p = Wild('p', exclude=[1, x])
+    q = Wild('q')
+    r = Wild('r', exclude=[sin, y])
+
+    assert sin(x).match(r) is None
+    assert cos(y).match(r) is None
+
+    e = 3*x**2 + y*x + a
+    assert e.match(p*x**2 + q*x + r) == {p: 3, q: y, r: a}
+
+    e = x + 1
+    assert e.match(x + p) is None
+    assert e.match(p + 1) is None
+    assert e.match(x + 1 + p) == {p: 0}
+
+    e = cos(x) + 5*sin(y)
+    assert e.match(r) is None
+    assert e.match(cos(y) + r) is None
+    assert e.match(r + p*sin(q)) == {r: cos(x), p: 5, q: y}
+
+
+def test_floats():
+    a, b = map(Wild, 'ab')
+
+    e = cos(0.12345, evaluate=False)**2
+    r = e.match(a*cos(b)**2)
+    assert r == {a: 1, b: Float(0.12345)}
+
+
+def test_Derivative_bug1():
+    f = Function("f")
+    x = abc.x
+    a = Wild("a", exclude=[f(x)])
+    b = Wild("b", exclude=[f(x)])
+    eq = f(x).diff(x)
+    assert eq.match(a*Derivative(f(x), x) + b) == {a: 1, b: 0}
+
+
+def test_match_wild_wild():
+    p = Wild('p')
+    q = Wild('q')
+    r = Wild('r')
+
+    assert p.match(q + r) in [ {q: p, r: 0}, {q: 0, r: p} ]
+    assert p.match(q*r) in [ {q: p, r: 1}, {q: 1, r: p} ]
+
+    p = Wild('p')
+    q = Wild('q', exclude=[p])
+    r = Wild('r')
+
+    assert p.match(q + r) == {q: 0, r: p}
+    assert p.match(q*r) == {q: 1, r: p}
+
+    p = Wild('p')
+    q = Wild('q', exclude=[p])
+    r = Wild('r', exclude=[p])
+
+    assert p.match(q + r) is None
+    assert p.match(q*r) is None
+
+
+def test__combine_inverse():
+    x, y = symbols("x y")
+    assert Mul._combine_inverse(x*I*y, x*I) == y
+    assert Mul._combine_inverse(x*x**(1 + y), x**(1 + y)) == x
+    assert Mul._combine_inverse(x*I*y, y*I) == x
+    assert Mul._combine_inverse(oo*I*y, y*I) is oo
+    assert Mul._combine_inverse(oo*I*y, oo*I) == y
+    assert Mul._combine_inverse(oo*I*y, oo*I) == y
+    assert Mul._combine_inverse(oo*y, -oo) == -y
+    assert Mul._combine_inverse(-oo*y, oo) == -y
+    assert Mul._combine_inverse((1-exp(x/y)),(exp(x/y)-1)) == -1
+    assert Add._combine_inverse(oo, oo) is S.Zero
+    assert Add._combine_inverse(oo*I, oo*I) is S.Zero
+    assert Add._combine_inverse(x*oo, x*oo) is S.Zero
+    assert Add._combine_inverse(-x*oo, -x*oo) is S.Zero
+    assert Add._combine_inverse((x - oo)*(x + oo), -oo)
+
+
+def test_issue_3773():
+    x = symbols('x')
+    z, phi, r = symbols('z phi r')
+    c, A, B, N = symbols('c A B N', cls=Wild)
+    l = Wild('l', exclude=(0,))
+
+    eq = z * sin(2*phi) * r**7
+    matcher = c * sin(phi*N)**l * r**A * log(r)**B
+
+    assert eq.match(matcher) == {c: z, l: 1, N: 2, A: 7, B: 0}
+    assert (-eq).match(matcher) == {c: -z, l: 1, N: 2, A: 7, B: 0}
+    assert (x*eq).match(matcher) == {c: x*z, l: 1, N: 2, A: 7, B: 0}
+    assert (-7*x*eq).match(matcher) == {c: -7*x*z, l: 1, N: 2, A: 7, B: 0}
+
+    matcher = c*sin(phi*N)**l * r**A
+
+    assert eq.match(matcher) == {c: z, l: 1, N: 2, A: 7}
+    assert (-eq).match(matcher) == {c: -z, l: 1, N: 2, A: 7}
+    assert (x*eq).match(matcher) == {c: x*z, l: 1, N: 2, A: 7}
+    assert (-7*x*eq).match(matcher) == {c: -7*x*z, l: 1, N: 2, A: 7}
+
+
+def test_issue_3883():
+    from sympy.abc import gamma, mu, x
+    f = (-gamma * (x - mu)**2 - log(gamma) + log(2*pi))/2
+    a, b, c = symbols('a b c', cls=Wild, exclude=(gamma,))
+
+    assert f.match(a * log(gamma) + b * gamma + c) == \
+        {a: Rational(-1, 2), b: -(-mu + x)**2/2, c: log(2*pi)/2}
+    assert f.expand().collect(gamma).match(a * log(gamma) + b * gamma + c) == \
+        {a: Rational(-1, 2), b: (-(x - mu)**2/2).expand(), c: (log(2*pi)/2).expand()}
+    g1 = Wild('g1', exclude=[gamma])
+    g2 = Wild('g2', exclude=[gamma])
+    g3 = Wild('g3', exclude=[gamma])
+    assert f.expand().match(g1 * log(gamma) + g2 * gamma + g3) == \
+    {g3: log(2)/2 + log(pi)/2, g1: Rational(-1, 2), g2: -mu**2/2 + mu*x - x**2/2}
+
+
+def test_issue_4418():
+    x = Symbol('x')
+    a, b, c = symbols('a b c', cls=Wild, exclude=(x,))
+    f, g = symbols('f g', cls=Function)
+
+    eq = diff(g(x)*f(x).diff(x), x)
+
+    assert eq.match(
+        g(x).diff(x)*f(x).diff(x) + g(x)*f(x).diff(x, x) + c) == {c: 0}
+    assert eq.match(a*g(x).diff(
+        x)*f(x).diff(x) + b*g(x)*f(x).diff(x, x) + c) == {a: 1, b: 1, c: 0}
+
+
+def test_issue_4700():
+    f = Function('f')
+    x = Symbol('x')
+    a, b = symbols('a b', cls=Wild, exclude=(f(x),))
+
+    p = a*f(x) + b
+    eq1 = sin(x)
+    eq2 = f(x) + sin(x)
+    eq3 = f(x) + x + sin(x)
+    eq4 = x + sin(x)
+
+    assert eq1.match(p) == {a: 0, b: sin(x)}
+    assert eq2.match(p) == {a: 1, b: sin(x)}
+    assert eq3.match(p) == {a: 1, b: x + sin(x)}
+    assert eq4.match(p) == {a: 0, b: x + sin(x)}
+
+
+def test_issue_5168():
+    a, b, c = symbols('a b c', cls=Wild)
+    x = Symbol('x')
+    f = Function('f')
+
+    assert x.match(a) == {a: x}
+    assert x.match(a*f(x)**c) == {a: x, c: 0}
+    assert x.match(a*b) == {a: 1, b: x}
+    assert x.match(a*b*f(x)**c) == {a: 1, b: x, c: 0}
+
+    assert (-x).match(a) == {a: -x}
+    assert (-x).match(a*f(x)**c) == {a: -x, c: 0}
+    assert (-x).match(a*b) == {a: -1, b: x}
+    assert (-x).match(a*b*f(x)**c) == {a: -1, b: x, c: 0}
+
+    assert (2*x).match(a) == {a: 2*x}
+    assert (2*x).match(a*f(x)**c) == {a: 2*x, c: 0}
+    assert (2*x).match(a*b) == {a: 2, b: x}
+    assert (2*x).match(a*b*f(x)**c) == {a: 2, b: x, c: 0}
+
+    assert (-2*x).match(a) == {a: -2*x}
+    assert (-2*x).match(a*f(x)**c) == {a: -2*x, c: 0}
+    assert (-2*x).match(a*b) == {a: -2, b: x}
+    assert (-2*x).match(a*b*f(x)**c) == {a: -2, b: x, c: 0}
+
+
+def test_issue_4559():
+    x = Symbol('x')
+    e = Symbol('e')
+    w = Wild('w', exclude=[x])
+    y = Wild('y')
+
+    # this is as it should be
+
+    assert (3/x).match(w/y) == {w: 3, y: x}
+    assert (3*x).match(w*y) == {w: 3, y: x}
+    assert (x/3).match(y/w) == {w: 3, y: x}
+    assert (3*x).match(y/w) == {w: S.One/3, y: x}
+    assert (3*x).match(y/w) == {w: Rational(1, 3), y: x}
+
+    # these could be allowed to fail
+
+    assert (x/3).match(w/y) == {w: S.One/3, y: 1/x}
+    assert (3*x).match(w/y) == {w: 3, y: 1/x}
+    assert (3/x).match(w*y) == {w: 3, y: 1/x}
+
+    # Note that solve will give
+    # multiple roots but match only gives one:
+    #
+    # >>> solve(x**r-y**2,y)
+    # [-x**(r/2), x**(r/2)]
+
+    r = Symbol('r', rational=True)
+    assert (x**r).match(y**2) == {y: x**(r/2)}
+    assert (x**e).match(y**2) == {y: sqrt(x**e)}
+
+    # since (x**i = y) -> x = y**(1/i) where i is an integer
+    # the following should also be valid as long as y is not
+    # zero when i is negative.
+
+    a = Wild('a')
+
+    e = S.Zero
+    assert e.match(a) == {a: e}
+    assert e.match(1/a) is None
+    assert e.match(a**.3) is None
+
+    e = S(3)
+    assert e.match(1/a) == {a: 1/e}
+    assert e.match(1/a**2) == {a: 1/sqrt(e)}
+    e = pi
+    assert e.match(1/a) == {a: 1/e}
+    assert e.match(1/a**2) == {a: 1/sqrt(e)}
+    assert (-e).match(sqrt(a)) is None
+    assert (-e).match(a**2) == {a: I*sqrt(pi)}
+
+# The pattern matcher doesn't know how to handle (x - a)**2 == (a - x)**2. To
+# avoid ambiguity in actual applications, don't put a coefficient (including a
+# minus sign) in front of a wild.
+@XFAIL
+def test_issue_4883():
+    a = Wild('a')
+    x = Symbol('x')
+
+    e = [i**2 for i in (x - 2, 2 - x)]
+    p = [i**2 for i in (x - a, a- x)]
+    for eq in e:
+        for pat in p:
+            assert eq.match(pat) == {a: 2}
+
+
+def test_issue_4319():
+    x, y = symbols('x y')
+
+    p = -x*(S.One/8 - y)
+    ans = {S.Zero, y - S.One/8}
+
+    def ok(pat):
+        assert set(p.match(pat).values()) == ans
+
+    ok(Wild("coeff", exclude=[x])*x + Wild("rest"))
+    ok(Wild("w", exclude=[x])*x + Wild("rest"))
+    ok(Wild("coeff", exclude=[x])*x + Wild("rest"))
+    ok(Wild("w", exclude=[x])*x + Wild("rest"))
+    ok(Wild("e", exclude=[x])*x + Wild("rest"))
+    ok(Wild("ress", exclude=[x])*x + Wild("rest"))
+    ok(Wild("resu", exclude=[x])*x + Wild("rest"))
+
+
+def test_issue_3778():
+    p, c, q = symbols('p c q', cls=Wild)
+    x = Symbol('x')
+
+    assert (sin(x)**2).match(sin(p)*sin(q)*c) == {q: x, c: 1, p: x}
+    assert (2*sin(x)).match(sin(p) + sin(q) + c) == {q: x, c: 0, p: x}
+
+
+def test_issue_6103():
+    x = Symbol('x')
+    a = Wild('a')
+    assert (-I*x*oo).match(I*a*oo) == {a: -x}
+
+
+def test_issue_3539():
+    a = Wild('a')
+    x = Symbol('x')
+    assert (x - 2).match(a - x) is None
+    assert (6/x).match(a*x) is None
+    assert (6/x**2).match(a/x) == {a: 6/x}
+
+def test_gh_issue_2711():
+    x = Symbol('x')
+    f = meijerg(((), ()), ((0,), ()), x)
+    a = Wild('a')
+    b = Wild('b')
+
+    assert f.find(a) == {(S.Zero,), ((), ()), ((S.Zero,), ()), x, S.Zero,
+                             (), meijerg(((), ()), ((S.Zero,), ()), x)}
+    assert f.find(a + b) == \
+        {meijerg(((), ()), ((S.Zero,), ()), x), x, S.Zero}
+    assert f.find(a**2) == {meijerg(((), ()), ((S.Zero,), ()), x), x}
+
+
+def test_issue_17354():
+    from sympy.core.symbol import (Wild, symbols)
+    x, y = symbols("x y", real=True)
+    a, b = symbols("a b", cls=Wild)
+    assert ((0 <= x).reversed | (y <= x)).match((1/a <= b) | (a <= b)) is None
+
+
+def test_match_issue_17397():
+    f = Function("f")
+    x = Symbol("x")
+    a3 = Wild('a3', exclude=[f(x), f(x).diff(x), f(x).diff(x, 2)])
+    b3 = Wild('b3', exclude=[f(x), f(x).diff(x), f(x).diff(x, 2)])
+    c3 = Wild('c3', exclude=[f(x), f(x).diff(x), f(x).diff(x, 2)])
+    deq = a3*(f(x).diff(x, 2)) + b3*f(x).diff(x) + c3*f(x)
+
+    eq = (x-2)**2*(f(x).diff(x, 2)) + (x-2)*(f(x).diff(x)) + ((x-2)**2 - 4)*f(x)
+    r = collect(eq, [f(x).diff(x, 2), f(x).diff(x), f(x)]).match(deq)
+    assert r == {a3: (x - 2)**2, c3: (x - 2)**2 - 4, b3: x - 2}
+
+    eq =x*f(x) + x*Derivative(f(x), (x, 2)) - 4*f(x) + Derivative(f(x), x) \
+        - 4*Derivative(f(x), (x, 2)) - 2*Derivative(f(x), x)/x + 4*Derivative(f(x), (x, 2))/x
+    r = collect(eq, [f(x).diff(x, 2), f(x).diff(x), f(x)]).match(deq)
+    assert r == {a3: x - 4 + 4/x, b3: 1 - 2/x, c3: x - 4}
+
+
+def test_match_issue_21942():
+    a, r, w = symbols('a, r, w', nonnegative=True)
+    p = symbols('p', positive=True)
+    g_ = Wild('g')
+    pattern = g_ ** (1 / (1 - p))
+    eq = (a * r ** (1 - p) + w ** (1 - p) * (1 - a)) ** (1 / (1 - p))
+    m = {g_: a * r ** (1 - p) + w ** (1 - p) * (1 - a)}
+    assert pattern.matches(eq) == m
+    assert (-pattern).matches(-eq) == m
+    assert pattern.matches(signsimp(eq)) is None
+
+
+def test_match_terms():
+    X, Y = map(Wild, "XY")
+    x, y, z = symbols('x y z')
+    assert (5*y - x).match(5*X - Y) == {X: y, Y: x}
+    # 15907
+    assert (x + (y - 1)*z).match(x + X*z) == {X: y - 1}
+    # 20747
+    assert (x - log(x/y)*(1-exp(x/y))).match(x - log(X/y)*(1-exp(x/y))) == {X: x}
+
+
+def test_match_bound():
+    V, W = map(Wild, "VW")
+    x, y = symbols('x y')
+    assert Sum(x, (x, 1, 2)).match(Sum(y, (y, 1, W))) == {W: 2}
+    assert Sum(x, (x, 1, 2)).match(Sum(V, (V, 1, W))) == {W: 2, V:x}
+    assert Sum(x, (x, 1, 2)).match(Sum(V, (V, 1, 2))) == {V:x}
+
+
+def test_issue_22462():
+    x, f = symbols('x'), Function('f')
+    n, Q = symbols('n Q', cls=Wild)
+    pattern = -Q*f(x)**n
+    eq = 5*f(x)**2
+    assert pattern.matches(eq) == {n: 2, Q: -5}

env-llmeval/lib/python3.10/site-packages/sympy/core/tests/test_multidimensional.py

@@ -0,0 +1,24 @@
+from sympy.core.function import (Derivative, Function, diff)
+from sympy.core.symbol import symbols
+from sympy.functions.elementary.trigonometric import sin
+from sympy.core.multidimensional import vectorize
+x, y, z = symbols('x y z')
+f, g, h = list(map(Function, 'fgh'))
+
+
+def test_vectorize():
+    @vectorize(0)
+    def vsin(x):
+        return sin(x)
+
+    assert vsin([1, x, y]) == [sin(1), sin(x), sin(y)]
+
+    @vectorize(0, 1)
+    def vdiff(f, y):
+        return diff(f, y)
+
+    assert vdiff([f(x, y, z), g(x, y, z), h(x, y, z)], [x, y, z]) == \
+         [[Derivative(f(x, y, z), x), Derivative(f(x, y, z), y),
+           Derivative(f(x, y, z), z)], [Derivative(g(x, y, z), x),
+                     Derivative(g(x, y, z), y), Derivative(g(x, y, z), z)],
+         [Derivative(h(x, y, z), x), Derivative(h(x, y, z), y), Derivative(h(x, y, z), z)]]

env-llmeval/lib/python3.10/site-packages/sympy/core/tests/test_noncommutative.py

@@ -0,0 +1,140 @@
+"""Tests for noncommutative symbols and expressions."""
+
+from sympy.core.function import expand
+from sympy.core.numbers import I
+from sympy.core.symbol import symbols
+from sympy.functions.elementary.complexes import (adjoint, conjugate, transpose)
+from sympy.functions.elementary.trigonometric import (cos, sin)
+from sympy.polys.polytools import (cancel, factor)
+from sympy.simplify.combsimp import combsimp
+from sympy.simplify.gammasimp import gammasimp
+from sympy.simplify.radsimp import (collect, radsimp, rcollect)
+from sympy.simplify.ratsimp import ratsimp
+from sympy.simplify.simplify import (posify, simplify)
+from sympy.simplify.trigsimp import trigsimp
+from sympy.abc import x, y, z
+from sympy.testing.pytest import XFAIL
+
+A, B, C = symbols("A B C", commutative=False)
+X = symbols("X", commutative=False, hermitian=True)
+Y = symbols("Y", commutative=False, antihermitian=True)
+
+
+def test_adjoint():
+    assert adjoint(A).is_commutative is False
+    assert adjoint(A*A) == adjoint(A)**2
+    assert adjoint(A*B) == adjoint(B)*adjoint(A)
+    assert adjoint(A*B**2) == adjoint(B)**2*adjoint(A)
+    assert adjoint(A*B - B*A) == adjoint(B)*adjoint(A) - adjoint(A)*adjoint(B)
+    assert adjoint(A + I*B) == adjoint(A) - I*adjoint(B)
+
+    assert adjoint(X) == X
+    assert adjoint(-I*X) == I*X
+    assert adjoint(Y) == -Y
+    assert adjoint(-I*Y) == -I*Y
+
+    assert adjoint(X) == conjugate(transpose(X))
+    assert adjoint(Y) == conjugate(transpose(Y))
+    assert adjoint(X) == transpose(conjugate(X))
+    assert adjoint(Y) == transpose(conjugate(Y))
+
+
+def test_cancel():
+    assert cancel(A*B - B*A) == A*B - B*A
+    assert cancel(A*B*(x - 1)) == A*B*(x - 1)
+    assert cancel(A*B*(x**2 - 1)/(x + 1)) == A*B*(x - 1)
+    assert cancel(A*B*(x**2 - 1)/(x + 1) - B*A*(x - 1)) == A*B*(x - 1) + (1 - x)*B*A
+
+
+@XFAIL
+def test_collect():
+    assert collect(A*B - B*A, A) == A*B - B*A
+    assert collect(A*B - B*A, B) == A*B - B*A
+    assert collect(A*B - B*A, x) == A*B - B*A
+
+
+def test_combsimp():
+    assert combsimp(A*B - B*A) == A*B - B*A
+
+
+def test_gammasimp():
+    assert gammasimp(A*B - B*A) == A*B - B*A
+
+
+def test_conjugate():
+    assert conjugate(A).is_commutative is False
+    assert (A*A).conjugate() == conjugate(A)**2
+    assert (A*B).conjugate() == conjugate(A)*conjugate(B)
+    assert (A*B**2).conjugate() == conjugate(A)*conjugate(B)**2
+    assert (A*B - B*A).conjugate() == \
+        conjugate(A)*conjugate(B) - conjugate(B)*conjugate(A)
+    assert (A*B).conjugate() - (B*A).conjugate() == \
+        conjugate(A)*conjugate(B) - conjugate(B)*conjugate(A)
+    assert (A + I*B).conjugate() == conjugate(A) - I*conjugate(B)
+
+
+def test_expand():
+    assert expand((A*B)**2) == A*B*A*B
+    assert expand(A*B - B*A) == A*B - B*A
+    assert expand((A*B/A)**2) == A*B*B/A
+    assert expand(B*A*(A + B)*B) == B*A**2*B + B*A*B**2
+    assert expand(B*A*(A + C)*B) == B*A**2*B + B*A*C*B
+
+
+def test_factor():
+    assert factor(A*B - B*A) == A*B - B*A
+
+
+def test_posify():
+    assert posify(A)[0].is_commutative is False
+    for q in (A*B/A, (A*B/A)**2, (A*B)**2, A*B - B*A):
+        p = posify(q)
+        assert p[0].subs(p[1]) == q
+
+
+def test_radsimp():
+    assert radsimp(A*B - B*A) == A*B - B*A
+
+
+@XFAIL
+def test_ratsimp():
+    assert ratsimp(A*B - B*A) == A*B - B*A
+
+
+@XFAIL
+def test_rcollect():
+    assert rcollect(A*B - B*A, A) == A*B - B*A
+    assert rcollect(A*B - B*A, B) == A*B - B*A
+    assert rcollect(A*B - B*A, x) == A*B - B*A
+
+
+def test_simplify():
+    assert simplify(A*B - B*A) == A*B - B*A
+
+
+def test_subs():
+    assert (x*y*A).subs(x*y, z) == A*z
+    assert (x*A*B).subs(x*A, C) == C*B
+    assert (x*A*x*x).subs(x**2*A, C) == x*C
+    assert (x*A*x*B).subs(x**2*A, C) == C*B
+    assert (A**2*B**2).subs(A*B**2, C) == A*C
+    assert (A*A*A + A*B*A).subs(A*A*A, C) == C + A*B*A
+
+
+def test_transpose():
+    assert transpose(A).is_commutative is False
+    assert transpose(A*A) == transpose(A)**2
+    assert transpose(A*B) == transpose(B)*transpose(A)
+    assert transpose(A*B**2) == transpose(B)**2*transpose(A)
+    assert transpose(A*B - B*A) == \
+        transpose(B)*transpose(A) - transpose(A)*transpose(B)
+    assert transpose(A + I*B) == transpose(A) + I*transpose(B)
+
+    assert transpose(X) == conjugate(X)
+    assert transpose(-I*X) == -I*conjugate(X)
+    assert transpose(Y) == -conjugate(Y)
+    assert transpose(-I*Y) == I*conjugate(Y)
+
+
+def test_trigsimp():
+    assert trigsimp(A*sin(x)**2 + A*cos(x)**2) == A

env-llmeval/lib/python3.10/site-packages/sympy/core/tests/test_numbers.py

@@ -0,0 +1,2266 @@
+import numbers as nums
+import decimal
+from sympy.concrete.summations import Sum
+from sympy.core import (EulerGamma, Catalan, TribonacciConstant,
+    GoldenRatio)
+from sympy.core.containers import Tuple
+from sympy.core.expr import unchanged
+from sympy.core.logic import fuzzy_not
+from sympy.core.mul import Mul
+from sympy.core.numbers import (mpf_norm, mod_inverse, igcd, seterr,
+    igcd_lehmer, Integer, I, pi, comp, ilcm, Rational, E, nan, igcd2,
+    oo, AlgebraicNumber, igcdex, Number, Float, zoo, equal_valued)
+from sympy.core.power import Pow
+from sympy.core.relational import Ge, Gt, Le, Lt
+from sympy.core.singleton import S
+from sympy.core.symbol import Dummy, Symbol
+from sympy.core.sympify import sympify
+from sympy.functions.combinatorial.factorials import factorial
+from sympy.functions.elementary.integers import floor
+from sympy.functions.combinatorial.numbers import fibonacci
+from sympy.functions.elementary.exponential import exp, log
+from sympy.functions.elementary.miscellaneous import sqrt, cbrt
+from sympy.functions.elementary.trigonometric import cos, sin
+from sympy.polys.domains.realfield import RealField
+from sympy.printing.latex import latex
+from sympy.printing.repr import srepr
+from sympy.simplify import simplify
+from sympy.core.power import integer_nthroot, isqrt, integer_log
+from sympy.polys.domains.groundtypes import PythonRational
+from sympy.utilities.decorator import conserve_mpmath_dps
+from sympy.utilities.iterables import permutations
+from sympy.testing.pytest import XFAIL, raises, _both_exp_pow
+
+from mpmath import mpf
+from mpmath.rational import mpq
+import mpmath
+from sympy.core import numbers
+t = Symbol('t', real=False)
+
+_ninf = float(-oo)
+_inf = float(oo)
+
+
+def same_and_same_prec(a, b):
+    # stricter matching for Floats
+    return a == b and a._prec == b._prec
+
+
+def test_seterr():
+    seterr(divide=True)
+    raises(ValueError, lambda: S.Zero/S.Zero)
+    seterr(divide=False)
+    assert S.Zero / S.Zero is S.NaN
+
+
+def test_mod():
+    x = S.Half
+    y = Rational(3, 4)
+    z = Rational(5, 18043)
+
+    assert x % x == 0
+    assert x % y == S.Half
+    assert x % z == Rational(3, 36086)
+    assert y % x == Rational(1, 4)
+    assert y % y == 0
+    assert y % z == Rational(9, 72172)
+    assert z % x == Rational(5, 18043)
+    assert z % y == Rational(5, 18043)
+    assert z % z == 0
+
+    a = Float(2.6)
+
+    assert (a % .2) == 0.0
+    assert (a % 2).round(15) == 0.6
+    assert (a % 0.5).round(15) == 0.1
+
+    p = Symbol('p', infinite=True)
+
+    assert oo % oo is nan
+    assert zoo % oo is nan
+    assert 5 % oo is nan
+    assert p % 5 is nan
+
+    # In these two tests, if the precision of m does
+    # not match the precision of the ans, then it is
+    # likely that the change made now gives an answer
+    # with degraded accuracy.
+    r = Rational(500, 41)
+    f = Float('.36', 3)
+    m = r % f
+    ans = Float(r % Rational(f), 3)
+    assert m == ans and m._prec == ans._prec
+    f = Float('8.36', 3)
+    m = f % r
+    ans = Float(Rational(f) % r, 3)
+    assert m == ans and m._prec == ans._prec
+
+    s = S.Zero
+
+    assert s % float(1) == 0.0
+
+    # No rounding required since these numbers can be represented
+    # exactly.
+    assert Rational(3, 4) % Float(1.1) == 0.75
+    assert Float(1.5) % Rational(5, 4) == 0.25
+    assert Rational(5, 4).__rmod__(Float('1.5')) == 0.25
+    assert Float('1.5').__rmod__(Float('2.75')) == Float('1.25')
+    assert 2.75 % Float('1.5') == Float('1.25')
+
+    a = Integer(7)
+    b = Integer(4)
+
+    assert type(a % b) == Integer
+    assert a % b == Integer(3)
+    assert Integer(1) % Rational(2, 3) == Rational(1, 3)
+    assert Rational(7, 5) % Integer(1) == Rational(2, 5)
+    assert Integer(2) % 1.5 == 0.5
+
+    assert Integer(3).__rmod__(Integer(10)) == Integer(1)
+    assert Integer(10) % 4 == Integer(2)
+    assert 15 % Integer(4) == Integer(3)
+
+
+def test_divmod():
+    x = Symbol("x")
+    assert divmod(S(12), S(8)) == Tuple(1, 4)
+    assert divmod(-S(12), S(8)) == Tuple(-2, 4)
+    assert divmod(S.Zero, S.One) == Tuple(0, 0)
+    raises(ZeroDivisionError, lambda: divmod(S.Zero, S.Zero))
+    raises(ZeroDivisionError, lambda: divmod(S.One, S.Zero))
+    assert divmod(S(12), 8) == Tuple(1, 4)
+    assert divmod(12, S(8)) == Tuple(1, 4)
+    assert S(1024)//x == 1024//x == floor(1024/x)
+
+    assert divmod(S("2"), S("3/2")) == Tuple(S("1"), S("1/2"))
+    assert divmod(S("3/2"), S("2")) == Tuple(S("0"), S("3/2"))
+    assert divmod(S("2"), S("3.5")) == Tuple(S("0"), S("2"))
+    assert divmod(S("3.5"), S("2")) == Tuple(S("1"), S("1.5"))
+    assert divmod(S("2"), S("1/3")) == Tuple(S("6"), S("0"))
+    assert divmod(S("1/3"), S("2")) == Tuple(S("0"), S("1/3"))
+    assert divmod(S("2"), S("1/10")) == Tuple(S("20"), S("0"))
+    assert divmod(S("2"), S(".1"))[0] == 19
+    assert divmod(S("0.1"), S("2")) == Tuple(S("0"), S("0.1"))
+    assert divmod(S("2"), 2) == Tuple(S("1"), S("0"))
+    assert divmod(2, S("2")) == Tuple(S("1"), S("0"))
+    assert divmod(S("2"), 1.5) == Tuple(S("1"), S("0.5"))
+    assert divmod(1.5, S("2")) == Tuple(S("0"), S("1.5"))
+    assert divmod(0.3, S("2")) == Tuple(S("0"), S("0.3"))
+    assert divmod(S("3/2"), S("3.5")) == Tuple(S("0"), S("3/2"))
+    assert divmod(S("3.5"), S("3/2")) == Tuple(S("2"), S("0.5"))
+    assert divmod(S("3/2"), S("1/3")) == Tuple(S("4"), S("1/6"))
+    assert divmod(S("1/3"), S("3/2")) == Tuple(S("0"), S("1/3"))
+    assert divmod(S("3/2"), S("0.1"))[0] == 14
+    assert divmod(S("0.1"), S("3/2")) == Tuple(S("0"), S("0.1"))
+    assert divmod(S("3/2"), 2) == Tuple(S("0"), S("3/2"))
+    assert divmod(2, S("3/2")) == Tuple(S("1"), S("1/2"))
+    assert divmod(S("3/2"), 1.5) == Tuple(S("1"), S("0"))
+    assert divmod(1.5, S("3/2")) == Tuple(S("1"), S("0"))
+    assert divmod(S("3/2"), 0.3) == Tuple(S("5"), S("0"))
+    assert divmod(0.3, S("3/2")) == Tuple(S("0"), S("0.3"))
+    assert divmod(S("1/3"), S("3.5")) == Tuple(S("0"), S("1/3"))
+    assert divmod(S("3.5"), S("0.1")) == Tuple(S("35"), S("0"))
+    assert divmod(S("0.1"), S("3.5")) == Tuple(S("0"), S("0.1"))
+    assert divmod(S("3.5"), 2) == Tuple(S("1"), S("1.5"))
+    assert divmod(2, S("3.5")) == Tuple(S("0"), S("2"))
+    assert divmod(S("3.5"), 1.5) == Tuple(S("2"), S("0.5"))
+    assert divmod(1.5, S("3.5")) == Tuple(S("0"), S("1.5"))
+    assert divmod(0.3, S("3.5")) == Tuple(S("0"), S("0.3"))
+    assert divmod(S("0.1"), S("1/3")) == Tuple(S("0"), S("0.1"))
+    assert divmod(S("1/3"), 2) == Tuple(S("0"), S("1/3"))
+    assert divmod(2, S("1/3")) == Tuple(S("6"), S("0"))
+    assert divmod(S("1/3"), 1.5) == Tuple(S("0"), S("1/3"))
+    assert divmod(0.3, S("1/3")) == Tuple(S("0"), S("0.3"))
+    assert divmod(S("0.1"), 2) == Tuple(S("0"), S("0.1"))
+    assert divmod(2, S("0.1"))[0] == 19
+    assert divmod(S("0.1"), 1.5) == Tuple(S("0"), S("0.1"))
+    assert divmod(1.5, S("0.1")) == Tuple(S("15"), S("0"))
+    assert divmod(S("0.1"), 0.3) == Tuple(S("0"), S("0.1"))
+
+    assert str(divmod(S("2"), 0.3)) == '(6, 0.2)'
+    assert str(divmod(S("3.5"), S("1/3"))) == '(10, 0.166666666666667)'
+    assert str(divmod(S("3.5"), 0.3)) == '(11, 0.2)'
+    assert str(divmod(S("1/3"), S("0.1"))) == '(3, 0.0333333333333333)'
+    assert str(divmod(1.5, S("1/3"))) == '(4, 0.166666666666667)'
+    assert str(divmod(S("1/3"), 0.3)) == '(1, 0.0333333333333333)'
+    assert str(divmod(0.3, S("0.1"))) == '(2, 0.1)'
+
+    assert divmod(-3, S(2)) == (-2, 1)
+    assert divmod(S(-3), S(2)) == (-2, 1)
+    assert divmod(S(-3), 2) == (-2, 1)
+
+    assert divmod(S(4), S(-3.1)) == Tuple(-2, -2.2)
+    assert divmod(S(4), S(-2.1)) == divmod(4, -2.1)
+    assert divmod(S(-8), S(-2.5) ) == Tuple(3, -0.5)
+
+    assert divmod(oo, 1) == (S.NaN, S.NaN)
+    assert divmod(S.NaN, 1) == (S.NaN, S.NaN)
+    assert divmod(1, S.NaN) == (S.NaN, S.NaN)
+    ans = [(-1, oo), (-1, oo), (0, 0), (0, 1), (0, 2)]
+    OO = float('inf')
+    ANS = [tuple(map(float, i)) for i in ans]
+    assert [divmod(i, oo) for i in range(-2, 3)] == ans
+    ans = [(0, -2), (0, -1), (0, 0), (-1, -oo), (-1, -oo)]
+    ANS = [tuple(map(float, i)) for i in ans]
+    assert [divmod(i, -oo) for i in range(-2, 3)] == ans
+    assert [divmod(i, -OO) for i in range(-2, 3)] == ANS
+    assert divmod(S(3.5), S(-2)) == divmod(3.5, -2)
+    assert divmod(-S(3.5), S(-2)) == divmod(-3.5, -2)
+    assert divmod(S(0.0), S(9)) == divmod(0.0, 9)
+    assert divmod(S(0), S(9.0)) == divmod(0, 9.0)
+
+
+def test_igcd():
+    assert igcd(0, 0) == 0
+    assert igcd(0, 1) == 1
+    assert igcd(1, 0) == 1
+    assert igcd(0, 7) == 7
+    assert igcd(7, 0) == 7
+    assert igcd(7, 1) == 1
+    assert igcd(1, 7) == 1
+    assert igcd(-1, 0) == 1
+    assert igcd(0, -1) == 1
+    assert igcd(-1, -1) == 1
+    assert igcd(-1, 7) == 1
+    assert igcd(7, -1) == 1
+    assert igcd(8, 2) == 2
+    assert igcd(4, 8) == 4
+    assert igcd(8, 16) == 8
+    assert igcd(7, -3) == 1
+    assert igcd(-7, 3) == 1
+    assert igcd(-7, -3) == 1
+    assert igcd(*[10, 20, 30]) == 10
+    raises(TypeError, lambda: igcd())
+    raises(TypeError, lambda: igcd(2))
+    raises(ValueError, lambda: igcd(0, None))
+    raises(ValueError, lambda: igcd(1, 2.2))
+    for args in permutations((45.1, 1, 30)):
+        raises(ValueError, lambda: igcd(*args))
+    for args in permutations((1, 2, None)):
+        raises(ValueError, lambda: igcd(*args))
+
+
+def test_igcd_lehmer():
+    a, b = fibonacci(10001), fibonacci(10000)
+    # len(str(a)) == 2090
+    # small divisors, long Euclidean sequence
+    assert igcd_lehmer(a, b) == 1
+    c = fibonacci(100)
+    assert igcd_lehmer(a*c, b*c) == c
+    # big divisor
+    assert igcd_lehmer(a, 10**1000) == 1
+    # swapping argument
+    assert igcd_lehmer(1, 2) == igcd_lehmer(2, 1)
+
+
+def test_igcd2():
+    # short loop
+    assert igcd2(2**100 - 1, 2**99 - 1) == 1
+    # Lehmer's algorithm
+    a, b = int(fibonacci(10001)), int(fibonacci(10000))
+    assert igcd2(a, b) == 1
+
+
+def test_ilcm():
+    assert ilcm(0, 0) == 0
+    assert ilcm(1, 0) == 0
+    assert ilcm(0, 1) == 0
+    assert ilcm(1, 1) == 1
+    assert ilcm(2, 1) == 2
+    assert ilcm(8, 2) == 8
+    assert ilcm(8, 6) == 24
+    assert ilcm(8, 7) == 56
+    assert ilcm(*[10, 20, 30]) == 60
+    raises(ValueError, lambda: ilcm(8.1, 7))
+    raises(ValueError, lambda: ilcm(8, 7.1))
+    raises(TypeError, lambda: ilcm(8))
+
+
+def test_igcdex():
+    assert igcdex(2, 3) == (-1, 1, 1)
+    assert igcdex(10, 12) == (-1, 1, 2)
+    assert igcdex(100, 2004) == (-20, 1, 4)
+    assert igcdex(0, 0) == (0, 1, 0)
+    assert igcdex(1, 0) == (1, 0, 1)
+
+
+def _strictly_equal(a, b):
+    return (a.p, a.q, type(a.p), type(a.q)) == \
+           (b.p, b.q, type(b.p), type(b.q))
+
+
+def _test_rational_new(cls):
+    """
+    Tests that are common between Integer and Rational.
+    """
+    assert cls(0) is S.Zero
+    assert cls(1) is S.One
+    assert cls(-1) is S.NegativeOne
+    # These look odd, but are similar to int():
+    assert cls('1') is S.One
+    assert cls('-1') is S.NegativeOne
+
+    i = Integer(10)
+    assert _strictly_equal(i, cls('10'))
+    assert _strictly_equal(i, cls('10'))
+    assert _strictly_equal(i, cls(int(10)))
+    assert _strictly_equal(i, cls(i))
+
+    raises(TypeError, lambda: cls(Symbol('x')))
+
+
+def test_Integer_new():
+    """
+    Test for Integer constructor
+    """
+    _test_rational_new(Integer)
+
+    assert _strictly_equal(Integer(0.9), S.Zero)
+    assert _strictly_equal(Integer(10.5), Integer(10))
+    raises(ValueError, lambda: Integer("10.5"))
+    assert Integer(Rational('1.' + '9'*20)) == 1
+
+
+def test_Rational_new():
+    """"
+    Test for Rational constructor
+    """
+    _test_rational_new(Rational)
+
+    n1 = S.Half
+    assert n1 == Rational(Integer(1), 2)
+    assert n1 == Rational(Integer(1), Integer(2))
+    assert n1 == Rational(1, Integer(2))
+    assert n1 == Rational(S.Half)
+    assert 1 == Rational(n1, n1)
+    assert Rational(3, 2) == Rational(S.Half, Rational(1, 3))
+    assert Rational(3, 1) == Rational(1, Rational(1, 3))
+    n3_4 = Rational(3, 4)
+    assert Rational('3/4') == n3_4
+    assert -Rational('-3/4') == n3_4
+    assert Rational('.76').limit_denominator(4) == n3_4
+    assert Rational(19, 25).limit_denominator(4) == n3_4
+    assert Rational('19/25').limit_denominator(4) == n3_4
+    assert Rational(1.0, 3) == Rational(1, 3)
+    assert Rational(1, 3.0) == Rational(1, 3)
+    assert Rational(Float(0.5)) == S.Half
+    assert Rational('1e2/1e-2') == Rational(10000)
+    assert Rational('1 234') == Rational(1234)
+    assert Rational('1/1 234') == Rational(1, 1234)
+    assert Rational(-1, 0) is S.ComplexInfinity
+    assert Rational(1, 0) is S.ComplexInfinity
+    # Make sure Rational doesn't lose precision on Floats
+    assert Rational(pi.evalf(100)).evalf(100) == pi.evalf(100)
+    raises(TypeError, lambda: Rational('3**3'))
+    raises(TypeError, lambda: Rational('1/2 + 2/3'))
+
+    # handle fractions.Fraction instances
+    try:
+        import fractions
+        assert Rational(fractions.Fraction(1, 2)) == S.Half
+    except ImportError:
+        pass
+
+    assert Rational(mpq(2, 6)) == Rational(1, 3)
+    assert Rational(PythonRational(2, 6)) == Rational(1, 3)
+
+    assert Rational(2, 4, gcd=1).q == 4
+    n = Rational(2, -4, gcd=1)
+    assert n.q == 4
+    assert n.p == -2
+
+def test_issue_24543():
+    for p in ('1.5', 1.5, 2):
+        for q in ('1.5', 1.5, 2):
+            assert Rational(p, q).as_numer_denom() == Rational('%s/%s'%(p,q)).as_numer_denom()
+
+    assert Rational('0.5', '100') == Rational(1, 200)
+
+
+def test_Number_new():
+    """"
+    Test for Number constructor
+    """
+    # Expected behavior on numbers and strings
+    assert Number(1) is S.One
+    assert Number(2).__class__ is Integer
+    assert Number(-622).__class__ is Integer
+    assert Number(5, 3).__class__ is Rational
+    assert Number(5.3).__class__ is Float
+    assert Number('1') is S.One
+    assert Number('2').__class__ is Integer
+    assert Number('-622').__class__ is Integer
+    assert Number('5/3').__class__ is Rational
+    assert Number('5.3').__class__ is Float
+    raises(ValueError, lambda: Number('cos'))
+    raises(TypeError, lambda: Number(cos))
+    a = Rational(3, 5)
+    assert Number(a) is a  # Check idempotence on Numbers
+    u = ['inf', '-inf', 'nan', 'iNF', '+inf']
+    v = [oo, -oo, nan, oo, oo]
+    for i, a in zip(u, v):
+        assert Number(i) is a, (i, Number(i), a)
+
+
+def test_Number_cmp():
+    n1 = Number(1)
+    n2 = Number(2)
+    n3 = Number(-3)
+
+    assert n1 < n2
+    assert n1 <= n2
+    assert n3 < n1
+    assert n2 > n3
+    assert n2 >= n3
+
+    raises(TypeError, lambda: n1 < S.NaN)
+    raises(TypeError, lambda: n1 <= S.NaN)
+    raises(TypeError, lambda: n1 > S.NaN)
+    raises(TypeError, lambda: n1 >= S.NaN)
+
+
+def test_Rational_cmp():
+    n1 = Rational(1, 4)
+    n2 = Rational(1, 3)
+    n3 = Rational(2, 4)
+    n4 = Rational(2, -4)
+    n5 = Rational(0)
+    n6 = Rational(1)
+    n7 = Rational(3)
+    n8 = Rational(-3)
+
+    assert n8 < n5
+    assert n5 < n6
+    assert n6 < n7
+    assert n8 < n7
+    assert n7 > n8
+    assert (n1 + 1)**n2 < 2
+    assert ((n1 + n6)/n7) < 1
+
+    assert n4 < n3
+    assert n2 < n3
+    assert n1 < n2
+    assert n3 > n1
+    assert not n3 < n1
+    assert not (Rational(-1) > 0)
+    assert Rational(-1) < 0
+
+    raises(TypeError, lambda: n1 < S.NaN)
+    raises(TypeError, lambda: n1 <= S.NaN)
+    raises(TypeError, lambda: n1 > S.NaN)
+    raises(TypeError, lambda: n1 >= S.NaN)
+
+
+def test_Float():
+    def eq(a, b):
+        t = Float("1.0E-15")
+        return (-t < a - b < t)
+
+    zeros = (0, S.Zero, 0., Float(0))
+    for i, j in permutations(zeros, 2):
+        assert i == j
+    for z in zeros:
+        assert z in zeros
+    assert S.Zero.is_zero
+
+    a = Float(2) ** Float(3)
+    assert eq(a.evalf(), Float(8))
+    assert eq((pi ** -1).evalf(), Float("0.31830988618379067"))
+    a = Float(2) ** Float(4)
+    assert eq(a.evalf(), Float(16))
+    assert (S(.3) == S(.5)) is False
+
+    mpf = (0, 5404319552844595, -52, 53)
+    x_str = Float((0, '13333333333333', -52, 53))
+    x_0xstr = Float((0, '0x13333333333333', -52, 53))
+    x2_str = Float((0, '26666666666666', -53, 54))
+    x_hex = Float((0, int(0x13333333333333), -52, 53))
+    x_dec = Float(mpf)
+    assert x_str == x_0xstr == x_hex == x_dec == Float(1.2)
+    # x2_str was entered slightly malformed in that the mantissa
+    # was even -- it should be odd and the even part should be
+    # included with the exponent, but this is resolved by normalization
+    # ONLY IF REQUIREMENTS of mpf_norm are met: the bitcount must
+    # be exact: double the mantissa ==> increase bc by 1
+    assert Float(1.2)._mpf_ == mpf
+    assert x2_str._mpf_ == mpf
+
+    assert Float((0, int(0), -123, -1)) is S.NaN
+    assert Float((0, int(0), -456, -2)) is S.Infinity
+    assert Float((1, int(0), -789, -3)) is S.NegativeInfinity
+    # if you don't give the full signature, it's not special
+    assert Float((0, int(0), -123)) == Float(0)
+    assert Float((0, int(0), -456)) == Float(0)
+    assert Float((1, int(0), -789)) == Float(0)
+
+    raises(ValueError, lambda: Float((0, 7, 1, 3), ''))
+
+    assert Float('0.0').is_finite is True
+    assert Float('0.0').is_negative is False
+    assert Float('0.0').is_positive is False
+    assert Float('0.0').is_infinite is False
+    assert Float('0.0').is_zero is True
+
+    # rationality properties
+    # if the integer test fails then the use of intlike
+    # should be removed from gamma_functions.py
+    assert Float(1).is_integer is False
+    assert Float(1).is_rational is None
+    assert Float(1).is_irrational is None
+    assert sqrt(2).n(15).is_rational is None
+    assert sqrt(2).n(15).is_irrational is None
+
+    # do not automatically evalf
+    def teq(a):
+        assert (a.evalf() == a) is False
+        assert (a.evalf() != a) is True
+        assert (a == a.evalf()) is False
+        assert (a != a.evalf()) is True
+
+    teq(pi)
+    teq(2*pi)
+    teq(cos(0.1, evaluate=False))
+
+    # long integer
+    i = 12345678901234567890
+    assert same_and_same_prec(Float(12, ''), Float('12', ''))
+    assert same_and_same_prec(Float(Integer(i), ''), Float(i, ''))
+    assert same_and_same_prec(Float(i, ''), Float(str(i), 20))
+    assert same_and_same_prec(Float(str(i)), Float(i, ''))
+    assert same_and_same_prec(Float(i), Float(i, ''))
+
+    # inexact floats (repeating binary = denom not multiple of 2)
+    # cannot have precision greater than 15
+    assert Float(.125, 22) == .125
+    assert Float(2.0, 22) == 2
+    assert float(Float('.12500000000000001', '')) == .125
+    raises(ValueError, lambda: Float(.12500000000000001, ''))
+
+    # allow spaces
+    assert Float('123 456.123 456') == Float('123456.123456')
+    assert Integer('123 456') == Integer('123456')
+    assert Rational('123 456.123 456') == Rational('123456.123456')
+    assert Float(' .3e2') == Float('0.3e2')
+
+    # allow underscore
+    assert Float('1_23.4_56') == Float('123.456')
+    assert Float('1_') == Float('1.0')
+    assert Float('1_.') == Float('1.0')
+    assert Float('1._') == Float('1.0')
+    assert Float('1__2') == Float('12.0')
+    # assert Float('1_23.4_5_6', 12) == Float('123.456', 12)
+    # ...but not in all cases (per Py 3.6)
+    raises(ValueError, lambda: Float('_1'))
+    raises(ValueError, lambda: Float('_inf'))
+
+    # allow auto precision detection
+    assert Float('.1', '') == Float(.1, 1)
+    assert Float('.125', '') == Float(.125, 3)
+    assert Float('.100', '') == Float(.1, 3)
+    assert Float('2.0', '') == Float('2', 2)
+
+    raises(ValueError, lambda: Float("12.3d-4", ""))
+    raises(ValueError, lambda: Float(12.3, ""))
+    raises(ValueError, lambda: Float('.'))
+    raises(ValueError, lambda: Float('-.'))
+
+    zero = Float('0.0')
+    assert Float('-0') == zero
+    assert Float('.0') == zero
+    assert Float('-.0') == zero
+    assert Float('-0.0') == zero
+    assert Float(0.0) == zero
+    assert Float(0) == zero
+    assert Float(0, '') == Float('0', '')
+    assert Float(1) == Float(1.0)
+    assert Float(S.Zero) == zero
+    assert Float(S.One) == Float(1.0)
+
+    assert Float(decimal.Decimal('0.1'), 3) == Float('.1', 3)
+    assert Float(decimal.Decimal('nan')) is S.NaN
+    assert Float(decimal.Decimal('Infinity')) is S.Infinity
+    assert Float(decimal.Decimal('-Infinity')) is S.NegativeInfinity
+
+    assert '{:.3f}'.format(Float(4.236622)) == '4.237'
+    assert '{:.35f}'.format(Float(pi.n(40), 40)) == \
+        '3.14159265358979323846264338327950288'
+
+    # unicode
+    assert Float('0.73908513321516064100000000') == \
+        Float('0.73908513321516064100000000')
+    assert Float('0.73908513321516064100000000', 28) == \
+        Float('0.73908513321516064100000000', 28)
+
+    # binary precision
+    # Decimal value 0.1 cannot be expressed precisely as a base 2 fraction
+    a = Float(S.One/10, dps=15)
+    b = Float(S.One/10, dps=16)
+    p = Float(S.One/10, precision=53)
+    q = Float(S.One/10, precision=54)
+    assert a._mpf_ == p._mpf_
+    assert not a._mpf_ == q._mpf_
+    assert not b._mpf_ == q._mpf_
+
+    # Precision specifying errors
+    raises(ValueError, lambda: Float("1.23", dps=3, precision=10))
+    raises(ValueError, lambda: Float("1.23", dps="", precision=10))
+    raises(ValueError, lambda: Float("1.23", dps=3, precision=""))
+    raises(ValueError, lambda: Float("1.23", dps="", precision=""))
+
+    # from NumberSymbol
+    assert same_and_same_prec(Float(pi, 32), pi.evalf(32))
+    assert same_and_same_prec(Float(Catalan), Catalan.evalf())
+
+    # oo and nan
+    u = ['inf', '-inf', 'nan', 'iNF', '+inf']
+    v = [oo, -oo, nan, oo, oo]
+    for i, a in zip(u, v):
+        assert Float(i) is a
+
+
+def test_zero_not_false():
+    # https://github.com/sympy/sympy/issues/20796
+    assert (S(0.0) == S.false) is False
+    assert (S.false == S(0.0)) is False
+    assert (S(0) == S.false) is False
+    assert (S.false == S(0)) is False
+
+
+@conserve_mpmath_dps
+def test_float_mpf():
+    import mpmath
+    mpmath.mp.dps = 100
+    mp_pi = mpmath.pi()
+
+    assert Float(mp_pi, 100) == Float(mp_pi._mpf_, 100) == pi.evalf(100)
+
+    mpmath.mp.dps = 15
+
+    assert Float(mp_pi, 100) == Float(mp_pi._mpf_, 100) == pi.evalf(100)
+
+
+def test_Float_RealElement():
+    repi = RealField(dps=100)(pi.evalf(100))
+    # We still have to pass the precision because Float doesn't know what
+    # RealElement is, but make sure it keeps full precision from the result.
+    assert Float(repi, 100) == pi.evalf(100)
+
+
+def test_Float_default_to_highprec_from_str():
+    s = str(pi.evalf(128))
+    assert same_and_same_prec(Float(s), Float(s, ''))
+
+
+def test_Float_eval():
+    a = Float(3.2)
+    assert (a**2).is_Float
+
+
+def test_Float_issue_2107():
+    a = Float(0.1, 10)
+    b = Float("0.1", 10)
+
+    assert a - a == 0
+    assert a + (-a) == 0
+    assert S.Zero + a - a == 0
+    assert S.Zero + a + (-a) == 0
+
+    assert b - b == 0
+    assert b + (-b) == 0
+    assert S.Zero + b - b == 0
+    assert S.Zero + b + (-b) == 0
+
+
+def test_issue_14289():
+    from sympy.polys.numberfields import to_number_field
+
+    a = 1 - sqrt(2)
+    b = to_number_field(a)
+    assert b.as_expr() == a
+    assert b.minpoly(a).expand() == 0
+
+
+def test_Float_from_tuple():
+    a = Float((0, '1L', 0, 1))
+    b = Float((0, '1', 0, 1))
+    assert a == b
+
+
+def test_Infinity():
+    assert oo != 1
+    assert 1*oo is oo
+    assert 1 != oo
+    assert oo != -oo
+    assert oo != Symbol("x")**3
+    assert oo + 1 is oo
+    assert 2 + oo is oo
+    assert 3*oo + 2 is oo
+    assert S.Half**oo == 0
+    assert S.Half**(-oo) is oo
+    assert -oo*3 is -oo
+    assert oo + oo is oo
+    assert -oo + oo*(-5) is -oo
+    assert 1/oo == 0
+    assert 1/(-oo) == 0
+    assert 8/oo == 0
+    assert oo % 2 is nan
+    assert 2 % oo is nan
+    assert oo/oo is nan
+    assert oo/-oo is nan
+    assert -oo/oo is nan
+    assert -oo/-oo is nan
+    assert oo - oo is nan
+    assert oo - -oo is oo
+    assert -oo - oo is -oo
+    assert -oo - -oo is nan
+    assert oo + -oo is nan
+    assert -oo + oo is nan
+    assert oo + oo is oo
+    assert -oo + oo is nan
+    assert oo + -oo is nan
+    assert -oo + -oo is -oo
+    assert oo*oo is oo
+    assert -oo*oo is -oo
+    assert oo*-oo is -oo
+    assert -oo*-oo is oo
+    assert oo/0 is oo
+    assert -oo/0 is -oo
+    assert 0/oo == 0
+    assert 0/-oo == 0
+    assert oo*0 is nan
+    assert -oo*0 is nan
+    assert 0*oo is nan
+    assert 0*-oo is nan
+    assert oo + 0 is oo
+    assert -oo + 0 is -oo
+    assert 0 + oo is oo
+    assert 0 + -oo is -oo
+    assert oo - 0 is oo
+    assert -oo - 0 is -oo
+    assert 0 - oo is -oo
+    assert 0 - -oo is oo
+    assert oo/2 is oo
+    assert -oo/2 is -oo
+    assert oo/-2 is -oo
+    assert -oo/-2 is oo
+    assert oo*2 is oo
+    assert -oo*2 is -oo
+    assert oo*-2 is -oo
+    assert 2/oo == 0
+    assert 2/-oo == 0
+    assert -2/oo == 0
+    assert -2/-oo == 0
+    assert 2*oo is oo
+    assert 2*-oo is -oo
+    assert -2*oo is -oo
+    assert -2*-oo is oo
+    assert 2 + oo is oo
+    assert 2 - oo is -oo
+    assert -2 + oo is oo
+    assert -2 - oo is -oo
+    assert 2 + -oo is -oo
+    assert 2 - -oo is oo
+    assert -2 + -oo is -oo
+    assert -2 - -oo is oo
+    assert S(2) + oo is oo
+    assert S(2) - oo is -oo
+    assert oo/I == -oo*I
+    assert -oo/I == oo*I
+    assert oo*float(1) == _inf and (oo*float(1)) is oo
+    assert -oo*float(1) == _ninf and (-oo*float(1)) is -oo
+    assert oo/float(1) == _inf and (oo/float(1)) is oo
+    assert -oo/float(1) == _ninf and (-oo/float(1)) is -oo
+    assert oo*float(-1) == _ninf and (oo*float(-1)) is -oo
+    assert -oo*float(-1) == _inf and (-oo*float(-1)) is oo
+    assert oo/float(-1) == _ninf and (oo/float(-1)) is -oo
+    assert -oo/float(-1) == _inf and (-oo/float(-1)) is oo
+    assert oo + float(1) == _inf and (oo + float(1)) is oo
+    assert -oo + float(1) == _ninf and (-oo + float(1)) is -oo
+    assert oo - float(1) == _inf and (oo - float(1)) is oo
+    assert -oo - float(1) == _ninf and (-oo - float(1)) is -oo
+    assert float(1)*oo == _inf and (float(1)*oo) is oo
+    assert float(1)*-oo == _ninf and (float(1)*-oo) is -oo
+    assert float(1)/oo == 0
+    assert float(1)/-oo == 0
+    assert float(-1)*oo == _ninf and (float(-1)*oo) is -oo
+    assert float(-1)*-oo == _inf and (float(-1)*-oo) is oo
+    assert float(-1)/oo == 0
+    assert float(-1)/-oo == 0
+    assert float(1) + oo is oo
+    assert float(1) + -oo is -oo
+    assert float(1) - oo is -oo
+    assert float(1) - -oo is oo
+    assert oo == float(oo)
+    assert (oo != float(oo)) is False
+    assert type(float(oo)) is float
+    assert -oo == float(-oo)
+    assert (-oo != float(-oo)) is False
+    assert type(float(-oo)) is float
+
+    assert Float('nan') is nan
+    assert nan*1.0 is nan
+    assert -1.0*nan is nan
+    assert nan*oo is nan
+    assert nan*-oo is nan
+    assert nan/oo is nan
+    assert nan/-oo is nan
+    assert nan + oo is nan
+    assert nan + -oo is nan
+    assert nan - oo is nan
+    assert nan - -oo is nan
+    assert -oo * S.Zero is nan
+
+    assert oo*nan is nan
+    assert -oo*nan is nan
+    assert oo/nan is nan
+    assert -oo/nan is nan
+    assert oo + nan is nan
+    assert -oo + nan is nan
+    assert oo - nan is nan
+    assert -oo - nan is nan
+    assert S.Zero * oo is nan
+    assert oo.is_Rational is False
+    assert isinstance(oo, Rational) is False
+
+    assert S.One/oo == 0
+    assert -S.One/oo == 0
+    assert S.One/-oo == 0
+    assert -S.One/-oo == 0
+    assert S.One*oo is oo
+    assert -S.One*oo is -oo
+    assert S.One*-oo is -oo
+    assert -S.One*-oo is oo
+    assert S.One/nan is nan
+    assert S.One - -oo is oo
+    assert S.One + nan is nan
+    assert S.One - nan is nan
+    assert nan - S.One is nan
+    assert nan/S.One is nan
+    assert -oo - S.One is -oo
+
+
+def test_Infinity_2():
+    x = Symbol('x')
+    assert oo*x != oo
+    assert oo*(pi - 1) is oo
+    assert oo*(1 - pi) is -oo
+
+    assert (-oo)*x != -oo
+    assert (-oo)*(pi - 1) is -oo
+    assert (-oo)*(1 - pi) is oo
+
+    assert (-1)**S.NaN is S.NaN
+    assert oo - _inf is S.NaN
+    assert oo + _ninf is S.NaN
+    assert oo*0 is S.NaN
+    assert oo/_inf is S.NaN
+    assert oo/_ninf is S.NaN
+    assert oo**S.NaN is S.NaN
+    assert -oo + _inf is S.NaN
+    assert -oo - _ninf is S.NaN
+    assert -oo*S.NaN is S.NaN
+    assert -oo*0 is S.NaN
+    assert -oo/_inf is S.NaN
+    assert -oo/_ninf is S.NaN
+    assert -oo/S.NaN is S.NaN
+    assert abs(-oo) is oo
+    assert all((-oo)**i is S.NaN for i in (oo, -oo, S.NaN))
+    assert (-oo)**3 is -oo
+    assert (-oo)**2 is oo
+    assert abs(S.ComplexInfinity) is oo
+
+
+def test_Mul_Infinity_Zero():
+    assert Float(0)*_inf is nan
+    assert Float(0)*_ninf is nan
+    assert Float(0)*_inf is nan
+    assert Float(0)*_ninf is nan
+    assert _inf*Float(0) is nan
+    assert _ninf*Float(0) is nan
+    assert _inf*Float(0) is nan
+    assert _ninf*Float(0) is nan
+
+
+def test_Div_By_Zero():
+    assert 1/S.Zero is zoo
+    assert 1/Float(0) is zoo
+    assert 0/S.Zero is nan
+    assert 0/Float(0) is nan
+    assert S.Zero/0 is nan
+    assert Float(0)/0 is nan
+    assert -1/S.Zero is zoo
+    assert -1/Float(0) is zoo
+
+
+@_both_exp_pow
+def test_Infinity_inequations():
+    assert oo > pi
+    assert not (oo < pi)
+    assert exp(-3) < oo
+
+    assert _inf > pi
+    assert not (_inf < pi)
+    assert exp(-3) < _inf
+
+    raises(TypeError, lambda: oo < I)
+    raises(TypeError, lambda: oo <= I)
+    raises(TypeError, lambda: oo > I)
+    raises(TypeError, lambda: oo >= I)
+    raises(TypeError, lambda: -oo < I)
+    raises(TypeError, lambda: -oo <= I)
+    raises(TypeError, lambda: -oo > I)
+    raises(TypeError, lambda: -oo >= I)
+
+    raises(TypeError, lambda: I < oo)
+    raises(TypeError, lambda: I <= oo)
+    raises(TypeError, lambda: I > oo)
+    raises(TypeError, lambda: I >= oo)
+    raises(TypeError, lambda: I < -oo)
+    raises(TypeError, lambda: I <= -oo)
+    raises(TypeError, lambda: I > -oo)
+    raises(TypeError, lambda: I >= -oo)
+
+    assert oo > -oo and oo >= -oo
+    assert (oo < -oo) == False and (oo <= -oo) == False
+    assert -oo < oo and -oo <= oo
+    assert (-oo > oo) == False and (-oo >= oo) == False
+
+    assert (oo < oo) == False  # issue 7775
+    assert (oo > oo) == False
+    assert (-oo > -oo) == False and (-oo < -oo) == False
+    assert oo >= oo and oo <= oo and -oo >= -oo and -oo <= -oo
+    assert (-oo < -_inf) ==  False
+    assert (oo > _inf) == False
+    assert -oo >= -_inf
+    assert oo <= _inf
+
+    x = Symbol('x')
+    b = Symbol('b', finite=True, real=True)
+    assert (x < oo) == Lt(x, oo)  # issue 7775
+    assert b < oo and b > -oo and b <= oo and b >= -oo
+    assert oo > b and oo >= b and (oo < b) == False and (oo <= b) == False
+    assert (-oo > b) == False and (-oo >= b) == False and -oo < b and -oo <= b
+    assert (oo < x) == Lt(oo, x) and (oo > x) == Gt(oo, x)
+    assert (oo <= x) == Le(oo, x) and (oo >= x) == Ge(oo, x)
+    assert (-oo < x) == Lt(-oo, x) and (-oo > x) == Gt(-oo, x)
+    assert (-oo <= x) == Le(-oo, x) and (-oo >= x) == Ge(-oo, x)
+
+
+def test_NaN():
+    assert nan is nan
+    assert nan != 1
+    assert 1*nan is nan
+    assert 1 != nan
+    assert -nan is nan
+    assert oo != Symbol("x")**3
+    assert 2 + nan is nan
+    assert 3*nan + 2 is nan
+    assert -nan*3 is nan
+    assert nan + nan is nan
+    assert -nan + nan*(-5) is nan
+    assert 8/nan is nan
+    raises(TypeError, lambda: nan > 0)
+    raises(TypeError, lambda: nan < 0)
+    raises(TypeError, lambda: nan >= 0)
+    raises(TypeError, lambda: nan <= 0)
+    raises(TypeError, lambda: 0 < nan)
+    raises(TypeError, lambda: 0 > nan)
+    raises(TypeError, lambda: 0 <= nan)
+    raises(TypeError, lambda: 0 >= nan)
+    assert nan**0 == 1  # as per IEEE 754
+    assert 1**nan is nan # IEEE 754 is not the best choice for symbolic work
+    # test Pow._eval_power's handling of NaN
+    assert Pow(nan, 0, evaluate=False)**2 == 1
+    for n in (1, 1., S.One, S.NegativeOne, Float(1)):
+        assert n + nan is nan
+        assert n - nan is nan
+        assert nan + n is nan
+        assert nan - n is nan
+        assert n/nan is nan
+        assert nan/n is nan
+
+
+def test_special_numbers():
+    assert isinstance(S.NaN, Number) is True
+    assert isinstance(S.Infinity, Number) is True
+    assert isinstance(S.NegativeInfinity, Number) is True
+
+    assert S.NaN.is_number is True
+    assert S.Infinity.is_number is True
+    assert S.NegativeInfinity.is_number is True
+    assert S.ComplexInfinity.is_number is True
+
+    assert isinstance(S.NaN, Rational) is False
+    assert isinstance(S.Infinity, Rational) is False
+    assert isinstance(S.NegativeInfinity, Rational) is False
+
+    assert S.NaN.is_rational is not True
+    assert S.Infinity.is_rational is not True
+    assert S.NegativeInfinity.is_rational is not True
+
+
+def test_powers():
+    assert integer_nthroot(1, 2) == (1, True)
+    assert integer_nthroot(1, 5) == (1, True)
+    assert integer_nthroot(2, 1) == (2, True)
+    assert integer_nthroot(2, 2) == (1, False)
+    assert integer_nthroot(2, 5) == (1, False)
+    assert integer_nthroot(4, 2) == (2, True)
+    assert integer_nthroot(123**25, 25) == (123, True)
+    assert integer_nthroot(123**25 + 1, 25) == (123, False)
+    assert integer_nthroot(123**25 - 1, 25) == (122, False)
+    assert integer_nthroot(1, 1) == (1, True)
+    assert integer_nthroot(0, 1) == (0, True)
+    assert integer_nthroot(0, 3) == (0, True)
+    assert integer_nthroot(10000, 1) == (10000, True)
+    assert integer_nthroot(4, 2) == (2, True)
+    assert integer_nthroot(16, 2) == (4, True)
+    assert integer_nthroot(26, 2) == (5, False)
+    assert integer_nthroot(1234567**7, 7) == (1234567, True)
+    assert integer_nthroot(1234567**7 + 1, 7) == (1234567, False)
+    assert integer_nthroot(1234567**7 - 1, 7) == (1234566, False)
+    b = 25**1000
+    assert integer_nthroot(b, 1000) == (25, True)
+    assert integer_nthroot(b + 1, 1000) == (25, False)
+    assert integer_nthroot(b - 1, 1000) == (24, False)
+    c = 10**400
+    c2 = c**2
+    assert integer_nthroot(c2, 2) == (c, True)
+    assert integer_nthroot(c2 + 1, 2) == (c, False)
+    assert integer_nthroot(c2 - 1, 2) == (c - 1, False)
+    assert integer_nthroot(2, 10**10) == (1, False)
+
+    p, r = integer_nthroot(int(factorial(10000)), 100)
+    assert p % (10**10) == 5322420655
+    assert not r
+
+    # Test that this is fast
+    assert integer_nthroot(2, 10**10) == (1, False)
+
+    # output should be int if possible
+    assert type(integer_nthroot(2**61, 2)[0]) is int
+
+
+def test_integer_nthroot_overflow():
+    assert integer_nthroot(10**(50*50), 50) == (10**50, True)
+    assert integer_nthroot(10**100000, 10000) == (10**10, True)
+
+
+def test_integer_log():
+    raises(ValueError, lambda: integer_log(2, 1))
+    raises(ValueError, lambda: integer_log(0, 2))
+    raises(ValueError, lambda: integer_log(1.1, 2))
+    raises(ValueError, lambda: integer_log(1, 2.2))
+
+    assert integer_log(1, 2) == (0, True)
+    assert integer_log(1, 3) == (0, True)
+    assert integer_log(2, 3) == (0, False)
+    assert integer_log(3, 3) == (1, True)
+    assert integer_log(3*2, 3) == (1, False)
+    assert integer_log(3**2, 3) == (2, True)
+    assert integer_log(3*4, 3) == (2, False)
+    assert integer_log(3**3, 3) == (3, True)
+    assert integer_log(27, 5) == (2, False)
+    assert integer_log(2, 3) == (0, False)
+    assert integer_log(-4, -2) == (2, False)
+    assert integer_log(27, -3) == (3, False)
+    assert integer_log(-49, 7) == (0, False)
+    assert integer_log(-49, -7) == (2, False)
+
+
+def test_isqrt():
+    from math import sqrt as _sqrt
+    limit = 4503599761588223
+    assert int(_sqrt(limit)) == integer_nthroot(limit, 2)[0]
+    assert int(_sqrt(limit + 1)) != integer_nthroot(limit + 1, 2)[0]
+    assert isqrt(limit + 1) == integer_nthroot(limit + 1, 2)[0]
+    assert isqrt(limit + S.Half) == integer_nthroot(limit, 2)[0]
+    assert isqrt(limit + 1 + S.Half) == integer_nthroot(limit + 1, 2)[0]
+    assert isqrt(limit + 2 + S.Half) == integer_nthroot(limit + 2, 2)[0]
+
+    # Regression tests for https://github.com/sympy/sympy/issues/17034
+    assert isqrt(4503599761588224) == 67108864
+    assert isqrt(9999999999999999) == 99999999
+
+    # Other corner cases, especially involving non-integers.
+    raises(ValueError, lambda: isqrt(-1))
+    raises(ValueError, lambda: isqrt(-10**1000))
+    raises(ValueError, lambda: isqrt(Rational(-1, 2)))
+
+    tiny = Rational(1, 10**1000)
+    raises(ValueError, lambda: isqrt(-tiny))
+    assert isqrt(1-tiny) == 0
+    assert isqrt(4503599761588224-tiny) == 67108864
+    assert isqrt(10**100 - tiny) == 10**50 - 1
+
+    # Check that using an inaccurate math.sqrt doesn't affect the results.
+    from sympy.core import power
+    old_sqrt = power._sqrt
+    power._sqrt = lambda x: 2.999999999
+    try:
+        assert isqrt(9) == 3
+        assert isqrt(10000) == 100
+    finally:
+        power._sqrt = old_sqrt
+
+
+def test_powers_Integer():
+    """Test Integer._eval_power"""
+    # check infinity
+    assert S.One ** S.Infinity is S.NaN
+    assert S.NegativeOne** S.Infinity is S.NaN
+    assert S(2) ** S.Infinity is S.Infinity
+    assert S(-2)** S.Infinity == zoo
+    assert S(0) ** S.Infinity is S.Zero
+
+    # check Nan
+    assert S.One ** S.NaN is S.NaN
+    assert S.NegativeOne ** S.NaN is S.NaN
+
+    # check for exact roots
+    assert S.NegativeOne ** Rational(6, 5) == - (-1)**(S.One/5)
+    assert sqrt(S(4)) == 2
+    assert sqrt(S(-4)) == I * 2
+    assert S(16) ** Rational(1, 4) == 2
+    assert S(-16) ** Rational(1, 4) == 2 * (-1)**Rational(1, 4)
+    assert S(9) ** Rational(3, 2) == 27
+    assert S(-9) ** Rational(3, 2) == -27*I
+    assert S(27) ** Rational(2, 3) == 9
+    assert S(-27) ** Rational(2, 3) == 9 * (S.NegativeOne ** Rational(2, 3))
+    assert (-2) ** Rational(-2, 1) == Rational(1, 4)
+
+    # not exact roots
+    assert sqrt(-3) == I*sqrt(3)
+    assert (3) ** (Rational(3, 2)) == 3 * sqrt(3)
+    assert (-3) ** (Rational(3, 2)) == - 3 * sqrt(-3)
+    assert (-3) ** (Rational(5, 2)) == 9 * I * sqrt(3)
+    assert (-3) ** (Rational(7, 2)) == - I * 27 * sqrt(3)
+    assert (2) ** (Rational(3, 2)) == 2 * sqrt(2)
+    assert (2) ** (Rational(-3, 2)) == sqrt(2) / 4
+    assert (81) ** (Rational(2, 3)) == 9 * (S(3) ** (Rational(2, 3)))
+    assert (-81) ** (Rational(2, 3)) == 9 * (S(-3) ** (Rational(2, 3)))
+    assert (-3) ** Rational(-7, 3) == \
+        -(-1)**Rational(2, 3)*3**Rational(2, 3)/27
+    assert (-3) ** Rational(-2, 3) == \
+        -(-1)**Rational(1, 3)*3**Rational(1, 3)/3
+
+    # join roots
+    assert sqrt(6) + sqrt(24) == 3*sqrt(6)
+    assert sqrt(2) * sqrt(3) == sqrt(6)
+
+    # separate symbols & constansts
+    x = Symbol("x")
+    assert sqrt(49 * x) == 7 * sqrt(x)
+    assert sqrt((3 - sqrt(pi)) ** 2) == 3 - sqrt(pi)
+
+    # check that it is fast for big numbers
+    assert (2**64 + 1) ** Rational(4, 3)
+    assert (2**64 + 1) ** Rational(17, 25)
+
+    # negative rational power and negative base
+    assert (-3) ** Rational(-7, 3) == \
+        -(-1)**Rational(2, 3)*3**Rational(2, 3)/27
+    assert (-3) ** Rational(-2, 3) == \
+        -(-1)**Rational(1, 3)*3**Rational(1, 3)/3
+    assert (-2) ** Rational(-10, 3) == \
+        (-1)**Rational(2, 3)*2**Rational(2, 3)/16
+    assert abs(Pow(-2, Rational(-10, 3)).n() -
+        Pow(-2, Rational(-10, 3), evaluate=False).n()) < 1e-16
+
+    # negative base and rational power with some simplification
+    assert (-8) ** Rational(2, 5) == \
+        2*(-1)**Rational(2, 5)*2**Rational(1, 5)
+    assert (-4) ** Rational(9, 5) == \
+        -8*(-1)**Rational(4, 5)*2**Rational(3, 5)
+
+    assert S(1234).factors() == {617: 1, 2: 1}
+    assert Rational(2*3, 3*5*7).factors() == {2: 1, 5: -1, 7: -1}
+
+    # test that eval_power factors numbers bigger than
+    # the current limit in factor_trial_division (2**15)
+    from sympy.ntheory.generate import nextprime
+    n = nextprime(2**15)
+    assert sqrt(n**2) == n
+    assert sqrt(n**3) == n*sqrt(n)
+    assert sqrt(4*n) == 2*sqrt(n)
+
+    # check that factors of base with powers sharing gcd with power are removed
+    assert (2**4*3)**Rational(1, 6) == 2**Rational(2, 3)*3**Rational(1, 6)
+    assert (2**4*3)**Rational(5, 6) == 8*2**Rational(1, 3)*3**Rational(5, 6)
+
+    # check that bases sharing a gcd are exptracted
+    assert 2**Rational(1, 3)*3**Rational(1, 4)*6**Rational(1, 5) == \
+        2**Rational(8, 15)*3**Rational(9, 20)
+    assert sqrt(8)*24**Rational(1, 3)*6**Rational(1, 5) == \
+        4*2**Rational(7, 10)*3**Rational(8, 15)
+    assert sqrt(8)*(-24)**Rational(1, 3)*(-6)**Rational(1, 5) == \
+        4*(-3)**Rational(8, 15)*2**Rational(7, 10)
+    assert 2**Rational(1, 3)*2**Rational(8, 9) == 2*2**Rational(2, 9)
+    assert 2**Rational(2, 3)*6**Rational(1, 3) == 2*3**Rational(1, 3)
+    assert 2**Rational(2, 3)*6**Rational(8, 9) == \
+        2*2**Rational(5, 9)*3**Rational(8, 9)
+    assert (-2)**Rational(2, S(3))*(-4)**Rational(1, S(3)) == -2*2**Rational(1, 3)
+    assert 3*Pow(3, 2, evaluate=False) == 3**3
+    assert 3*Pow(3, Rational(-1, 3), evaluate=False) == 3**Rational(2, 3)
+    assert (-2)**Rational(1, 3)*(-3)**Rational(1, 4)*(-5)**Rational(5, 6) == \
+        -(-1)**Rational(5, 12)*2**Rational(1, 3)*3**Rational(1, 4) * \
+        5**Rational(5, 6)
+
+    assert Integer(-2)**Symbol('', even=True) == \
+        Integer(2)**Symbol('', even=True)
+    assert (-1)**Float(.5) == 1.0*I
+
+
+def test_powers_Rational():
+    """Test Rational._eval_power"""
+    # check infinity
+    assert S.Half ** S.Infinity == 0
+    assert Rational(3, 2) ** S.Infinity is S.Infinity
+    assert Rational(-1, 2) ** S.Infinity == 0
+    assert Rational(-3, 2) ** S.Infinity == zoo
+
+    # check Nan
+    assert Rational(3, 4) ** S.NaN is S.NaN
+    assert Rational(-2, 3) ** S.NaN is S.NaN
+
+    # exact roots on numerator
+    assert sqrt(Rational(4, 3)) == 2 * sqrt(3) / 3
+    assert Rational(4, 3) ** Rational(3, 2) == 8 * sqrt(3) / 9
+    assert sqrt(Rational(-4, 3)) == I * 2 * sqrt(3) / 3
+    assert Rational(-4, 3) ** Rational(3, 2) == - I * 8 * sqrt(3) / 9
+    assert Rational(27, 2) ** Rational(1, 3) == 3 * (2 ** Rational(2, 3)) / 2
+    assert Rational(5**3, 8**3) ** Rational(4, 3) == Rational(5**4, 8**4)
+
+    # exact root on denominator
+    assert sqrt(Rational(1, 4)) == S.Half
+    assert sqrt(Rational(1, -4)) == I * S.Half
+    assert sqrt(Rational(3, 4)) == sqrt(3) / 2
+    assert sqrt(Rational(3, -4)) == I * sqrt(3) / 2
+    assert Rational(5, 27) ** Rational(1, 3) == (5 ** Rational(1, 3)) / 3
+
+    # not exact roots
+    assert sqrt(S.Half) == sqrt(2) / 2
+    assert sqrt(Rational(-4, 7)) == I * sqrt(Rational(4, 7))
+    assert Rational(-3, 2)**Rational(-7, 3) == \
+        -4*(-1)**Rational(2, 3)*2**Rational(1, 3)*3**Rational(2, 3)/27
+    assert Rational(-3, 2)**Rational(-2, 3) == \
+        -(-1)**Rational(1, 3)*2**Rational(2, 3)*3**Rational(1, 3)/3
+    assert Rational(-3, 2)**Rational(-10, 3) == \
+        8*(-1)**Rational(2, 3)*2**Rational(1, 3)*3**Rational(2, 3)/81
+    assert abs(Pow(Rational(-2, 3), Rational(-7, 4)).n() -
+        Pow(Rational(-2, 3), Rational(-7, 4), evaluate=False).n()) < 1e-16
+
+    # negative integer power and negative rational base
+    assert Rational(-2, 3) ** Rational(-2, 1) == Rational(9, 4)
+
+    a = Rational(1, 10)
+    assert a**Float(a, 2) == Float(a, 2)**Float(a, 2)
+    assert Rational(-2, 3)**Symbol('', even=True) == \
+        Rational(2, 3)**Symbol('', even=True)
+
+
+def test_powers_Float():
+    assert str((S('-1/10')**S('3/10')).n()) == str(Float(-.1)**(.3))
+
+
+def test_lshift_Integer():
+    assert Integer(0) << Integer(2) == Integer(0)
+    assert Integer(0) << 2 == Integer(0)
+    assert 0 << Integer(2) == Integer(0)
+
+    assert Integer(0b11) << Integer(0) == Integer(0b11)
+    assert Integer(0b11) << 0 == Integer(0b11)
+    assert 0b11 << Integer(0) == Integer(0b11)
+
+    assert Integer(0b11) << Integer(2) == Integer(0b11 << 2)
+    assert Integer(0b11) << 2 == Integer(0b11 << 2)
+    assert 0b11 << Integer(2) == Integer(0b11 << 2)
+
+    assert Integer(-0b11) << Integer(2) == Integer(-0b11 << 2)
+    assert Integer(-0b11) << 2 == Integer(-0b11 << 2)
+    assert -0b11 << Integer(2) == Integer(-0b11 << 2)
+
+    raises(TypeError, lambda: Integer(2) << 0.0)
+    raises(TypeError, lambda: 0.0 << Integer(2))
+    raises(ValueError, lambda: Integer(1) << Integer(-1))
+
+
+def test_rshift_Integer():
+    assert Integer(0) >> Integer(2) == Integer(0)
+    assert Integer(0) >> 2 == Integer(0)
+    assert 0 >> Integer(2) == Integer(0)
+
+    assert Integer(0b11) >> Integer(0) == Integer(0b11)
+    assert Integer(0b11) >> 0 == Integer(0b11)
+    assert 0b11 >> Integer(0) == Integer(0b11)
+
+    assert Integer(0b11) >> Integer(2) == Integer(0)
+    assert Integer(0b11) >> 2 == Integer(0)
+    assert 0b11 >> Integer(2) == Integer(0)
+
+    assert Integer(-0b11) >> Integer(2) == Integer(-1)
+    assert Integer(-0b11) >> 2 == Integer(-1)
+    assert -0b11 >> Integer(2) == Integer(-1)
+
+    assert Integer(0b1100) >> Integer(2) == Integer(0b1100 >> 2)
+    assert Integer(0b1100) >> 2 == Integer(0b1100 >> 2)
+    assert 0b1100 >> Integer(2) == Integer(0b1100 >> 2)
+
+    assert Integer(-0b1100) >> Integer(2) == Integer(-0b1100 >> 2)
+    assert Integer(-0b1100) >> 2 == Integer(-0b1100 >> 2)
+    assert -0b1100 >> Integer(2) == Integer(-0b1100 >> 2)
+
+    raises(TypeError, lambda: Integer(0b10) >> 0.0)
+    raises(TypeError, lambda: 0.0 >> Integer(2))
+    raises(ValueError, lambda: Integer(1) >> Integer(-1))
+
+
+def test_and_Integer():
+    assert Integer(0b01010101) & Integer(0b10101010) == Integer(0)
+    assert Integer(0b01010101) & 0b10101010 == Integer(0)
+    assert 0b01010101 & Integer(0b10101010) == Integer(0)
+
+    assert Integer(0b01010101) & Integer(0b11011011) == Integer(0b01010001)
+    assert Integer(0b01010101) & 0b11011011 == Integer(0b01010001)
+    assert 0b01010101 & Integer(0b11011011) == Integer(0b01010001)
+
+    assert -Integer(0b01010101) & Integer(0b11011011) == Integer(-0b01010101 & 0b11011011)
+    assert Integer(-0b01010101) & 0b11011011 == Integer(-0b01010101 & 0b11011011)
+    assert -0b01010101 & Integer(0b11011011) == Integer(-0b01010101 & 0b11011011)
+
+    assert Integer(0b01010101) & -Integer(0b11011011) == Integer(0b01010101 & -0b11011011)
+    assert Integer(0b01010101) & -0b11011011 == Integer(0b01010101 & -0b11011011)
+    assert 0b01010101 & Integer(-0b11011011) == Integer(0b01010101 & -0b11011011)
+
+    raises(TypeError, lambda: Integer(2) & 0.0)
+    raises(TypeError, lambda: 0.0 & Integer(2))
+
+
+def test_xor_Integer():
+    assert Integer(0b01010101) ^ Integer(0b11111111) == Integer(0b10101010)
+    assert Integer(0b01010101) ^ 0b11111111 == Integer(0b10101010)
+    assert 0b01010101 ^ Integer(0b11111111) == Integer(0b10101010)
+
+    assert Integer(0b01010101) ^ Integer(0b11011011) == Integer(0b10001110)
+    assert Integer(0b01010101) ^ 0b11011011 == Integer(0b10001110)
+    assert 0b01010101 ^ Integer(0b11011011) == Integer(0b10001110)
+
+    assert -Integer(0b01010101) ^ Integer(0b11011011) == Integer(-0b01010101 ^ 0b11011011)
+    assert Integer(-0b01010101) ^ 0b11011011 == Integer(-0b01010101 ^ 0b11011011)
+    assert -0b01010101 ^ Integer(0b11011011) == Integer(-0b01010101 ^ 0b11011011)
+
+    assert Integer(0b01010101) ^ -Integer(0b11011011) == Integer(0b01010101 ^ -0b11011011)
+    assert Integer(0b01010101) ^ -0b11011011 == Integer(0b01010101 ^ -0b11011011)
+    assert 0b01010101 ^ Integer(-0b11011011) == Integer(0b01010101 ^ -0b11011011)
+
+    raises(TypeError, lambda: Integer(2) ^ 0.0)
+    raises(TypeError, lambda: 0.0 ^ Integer(2))
+
+
+def test_or_Integer():
+    assert Integer(0b01010101) | Integer(0b10101010) == Integer(0b11111111)
+    assert Integer(0b01010101) | 0b10101010 == Integer(0b11111111)
+    assert 0b01010101 | Integer(0b10101010) == Integer(0b11111111)
+
+    assert Integer(0b01010101) | Integer(0b11011011) == Integer(0b11011111)
+    assert Integer(0b01010101) | 0b11011011 == Integer(0b11011111)
+    assert 0b01010101 | Integer(0b11011011) == Integer(0b11011111)
+
+    assert -Integer(0b01010101) | Integer(0b11011011) == Integer(-0b01010101 | 0b11011011)
+    assert Integer(-0b01010101) | 0b11011011 == Integer(-0b01010101 | 0b11011011)
+    assert -0b01010101 | Integer(0b11011011) == Integer(-0b01010101 | 0b11011011)
+
+    assert Integer(0b01010101) | -Integer(0b11011011) == Integer(0b01010101 | -0b11011011)
+    assert Integer(0b01010101) | -0b11011011 == Integer(0b01010101 | -0b11011011)
+    assert 0b01010101 | Integer(-0b11011011) == Integer(0b01010101 | -0b11011011)
+
+    raises(TypeError, lambda: Integer(2) | 0.0)
+    raises(TypeError, lambda: 0.0 | Integer(2))
+
+
+def test_invert_Integer():
+    assert ~Integer(0b01010101) == Integer(-0b01010110)
+    assert ~Integer(0b01010101) == Integer(~0b01010101)
+    assert ~(~Integer(0b01010101)) == Integer(0b01010101)
+
+
+def test_abs1():
+    assert Rational(1, 6) != Rational(-1, 6)
+    assert abs(Rational(1, 6)) == abs(Rational(-1, 6))
+
+
+def test_accept_int():
+    assert Float(4) == 4
+
+
+def test_dont_accept_str():
+    assert Float("0.2") != "0.2"
+    assert not (Float("0.2") == "0.2")
+
+
+def test_int():
+    a = Rational(5)
+    assert int(a) == 5
+    a = Rational(9, 10)
+    assert int(a) == int(-a) == 0
+    assert 1/(-1)**Rational(2, 3) == -(-1)**Rational(1, 3)
+    # issue 10368
+    a = Rational(32442016954, 78058255275)
+    assert type(int(a)) is type(int(-a)) is int
+
+
+def test_int_NumberSymbols():
+    assert int(Catalan) == 0
+    assert int(EulerGamma) == 0
+    assert int(pi) == 3
+    assert int(E) == 2
+    assert int(GoldenRatio) == 1
+    assert int(TribonacciConstant) == 1
+    for i in [Catalan, E, EulerGamma, GoldenRatio, TribonacciConstant, pi]:
+        a, b = i.approximation_interval(Integer)
+        ia = int(i)
+        assert ia == a
+        assert isinstance(ia, int)
+        assert b == a + 1
+        assert a.is_Integer and b.is_Integer
+
+
+def test_real_bug():
+    x = Symbol("x")
+    assert str(2.0*x*x) in ["(2.0*x)*x", "2.0*x**2", "2.00000000000000*x**2"]
+    assert str(2.1*x*x) != "(2.0*x)*x"
+
+
+def test_bug_sqrt():
+    assert ((sqrt(Rational(2)) + 1)*(sqrt(Rational(2)) - 1)).expand() == 1
+
+
+def test_pi_Pi():
+    "Test that pi (instance) is imported, but Pi (class) is not"
+    from sympy import pi  # noqa
+    with raises(ImportError):
+        from sympy import Pi  # noqa
+
+
+def test_no_len():
+    # there should be no len for numbers
+    raises(TypeError, lambda: len(Rational(2)))
+    raises(TypeError, lambda: len(Rational(2, 3)))
+    raises(TypeError, lambda: len(Integer(2)))
+
+
+def test_issue_3321():
+    assert sqrt(Rational(1, 5)) == Rational(1, 5)**S.Half
+    assert 5 * sqrt(Rational(1, 5)) == sqrt(5)
+
+
+def test_issue_3692():
+    assert ((-1)**Rational(1, 6)).expand(complex=True) == I/2 + sqrt(3)/2
+    assert ((-5)**Rational(1, 6)).expand(complex=True) == \
+        5**Rational(1, 6)*I/2 + 5**Rational(1, 6)*sqrt(3)/2
+    assert ((-64)**Rational(1, 6)).expand(complex=True) == I + sqrt(3)
+
+
+def test_issue_3423():
+    x = Symbol("x")
+    assert sqrt(x - 1).as_base_exp() == (x - 1, S.Half)
+    assert sqrt(x - 1) != I*sqrt(1 - x)
+
+
+def test_issue_3449():
+    x = Symbol("x")
+    assert sqrt(x - 1).subs(x, 5) == 2
+
+
+def test_issue_13890():
+    x = Symbol("x")
+    e = (-x/4 - S.One/12)**x - 1
+    f = simplify(e)
+    a = Rational(9, 5)
+    assert abs(e.subs(x,a).evalf() - f.subs(x,a).evalf()) < 1e-15
+
+
+def test_Integer_factors():
+    def F(i):
+        return Integer(i).factors()
+
+    assert F(1) == {}
+    assert F(2) == {2: 1}
+    assert F(3) == {3: 1}
+    assert F(4) == {2: 2}
+    assert F(5) == {5: 1}
+    assert F(6) == {2: 1, 3: 1}
+    assert F(7) == {7: 1}
+    assert F(8) == {2: 3}
+    assert F(9) == {3: 2}
+    assert F(10) == {2: 1, 5: 1}
+    assert F(11) == {11: 1}
+    assert F(12) == {2: 2, 3: 1}
+    assert F(13) == {13: 1}
+    assert F(14) == {2: 1, 7: 1}
+    assert F(15) == {3: 1, 5: 1}
+    assert F(16) == {2: 4}
+    assert F(17) == {17: 1}
+    assert F(18) == {2: 1, 3: 2}
+    assert F(19) == {19: 1}
+    assert F(20) == {2: 2, 5: 1}
+    assert F(21) == {3: 1, 7: 1}
+    assert F(22) == {2: 1, 11: 1}
+    assert F(23) == {23: 1}
+    assert F(24) == {2: 3, 3: 1}
+    assert F(25) == {5: 2}
+    assert F(26) == {2: 1, 13: 1}
+    assert F(27) == {3: 3}
+    assert F(28) == {2: 2, 7: 1}
+    assert F(29) == {29: 1}
+    assert F(30) == {2: 1, 3: 1, 5: 1}
+    assert F(31) == {31: 1}
+    assert F(32) == {2: 5}
+    assert F(33) == {3: 1, 11: 1}
+    assert F(34) == {2: 1, 17: 1}
+    assert F(35) == {5: 1, 7: 1}
+    assert F(36) == {2: 2, 3: 2}
+    assert F(37) == {37: 1}
+    assert F(38) == {2: 1, 19: 1}
+    assert F(39) == {3: 1, 13: 1}
+    assert F(40) == {2: 3, 5: 1}
+    assert F(41) == {41: 1}
+    assert F(42) == {2: 1, 3: 1, 7: 1}
+    assert F(43) == {43: 1}
+    assert F(44) == {2: 2, 11: 1}
+    assert F(45) == {3: 2, 5: 1}
+    assert F(46) == {2: 1, 23: 1}
+    assert F(47) == {47: 1}
+    assert F(48) == {2: 4, 3: 1}
+    assert F(49) == {7: 2}
+    assert F(50) == {2: 1, 5: 2}
+    assert F(51) == {3: 1, 17: 1}
+
+
+def test_Rational_factors():
+    def F(p, q, visual=None):
+        return Rational(p, q).factors(visual=visual)
+
+    assert F(2, 3) == {2: 1, 3: -1}
+    assert F(2, 9) == {2: 1, 3: -2}
+    assert F(2, 15) == {2: 1, 3: -1, 5: -1}
+    assert F(6, 10) == {3: 1, 5: -1}
+
+
+def test_issue_4107():
+    assert pi*(E + 10) + pi*(-E - 10) != 0
+    assert pi*(E + 10**10) + pi*(-E - 10**10) != 0
+    assert pi*(E + 10**20) + pi*(-E - 10**20) != 0
+    assert pi*(E + 10**80) + pi*(-E - 10**80) != 0
+
+    assert (pi*(E + 10) + pi*(-E - 10)).expand() == 0
+    assert (pi*(E + 10**10) + pi*(-E - 10**10)).expand() == 0
+    assert (pi*(E + 10**20) + pi*(-E - 10**20)).expand() == 0
+    assert (pi*(E + 10**80) + pi*(-E - 10**80)).expand() == 0
+
+
+def test_IntegerInteger():
+    a = Integer(4)
+    b = Integer(a)
+
+    assert a == b
+
+
+def test_Rational_gcd_lcm_cofactors():
+    assert Integer(4).gcd(2) == Integer(2)
+    assert Integer(4).lcm(2) == Integer(4)
+    assert Integer(4).gcd(Integer(2)) == Integer(2)
+    assert Integer(4).lcm(Integer(2)) == Integer(4)
+    a, b = 720**99911, 480**12342
+    assert Integer(a).lcm(b) == a*b/Integer(a).gcd(b)
+
+    assert Integer(4).gcd(3) == Integer(1)
+    assert Integer(4).lcm(3) == Integer(12)
+    assert Integer(4).gcd(Integer(3)) == Integer(1)
+    assert Integer(4).lcm(Integer(3)) == Integer(12)
+
+    assert Rational(4, 3).gcd(2) == Rational(2, 3)
+    assert Rational(4, 3).lcm(2) == Integer(4)
+    assert Rational(4, 3).gcd(Integer(2)) == Rational(2, 3)
+    assert Rational(4, 3).lcm(Integer(2)) == Integer(4)
+
+    assert Integer(4).gcd(Rational(2, 9)) == Rational(2, 9)
+    assert Integer(4).lcm(Rational(2, 9)) == Integer(4)
+
+    assert Rational(4, 3).gcd(Rational(2, 9)) == Rational(2, 9)
+    assert Rational(4, 3).lcm(Rational(2, 9)) == Rational(4, 3)
+    assert Rational(4, 5).gcd(Rational(2, 9)) == Rational(2, 45)
+    assert Rational(4, 5).lcm(Rational(2, 9)) == Integer(4)
+    assert Rational(5, 9).lcm(Rational(3, 7)) == Rational(Integer(5).lcm(3),Integer(9).gcd(7))
+
+    assert Integer(4).cofactors(2) == (Integer(2), Integer(2), Integer(1))
+    assert Integer(4).cofactors(Integer(2)) == \
+        (Integer(2), Integer(2), Integer(1))
+
+    assert Integer(4).gcd(Float(2.0)) == Float(1.0)
+    assert Integer(4).lcm(Float(2.0)) == Float(8.0)
+    assert Integer(4).cofactors(Float(2.0)) == (Float(1.0), Float(4.0), Float(2.0))
+
+    assert S.Half.gcd(Float(2.0)) == Float(1.0)
+    assert S.Half.lcm(Float(2.0)) == Float(1.0)
+    assert S.Half.cofactors(Float(2.0)) == \
+        (Float(1.0), Float(0.5), Float(2.0))
+
+
+def test_Float_gcd_lcm_cofactors():
+    assert Float(2.0).gcd(Integer(4)) == Float(1.0)
+    assert Float(2.0).lcm(Integer(4)) == Float(8.0)
+    assert Float(2.0).cofactors(Integer(4)) == (Float(1.0), Float(2.0), Float(4.0))
+
+    assert Float(2.0).gcd(S.Half) == Float(1.0)
+    assert Float(2.0).lcm(S.Half) == Float(1.0)
+    assert Float(2.0).cofactors(S.Half) == \
+        (Float(1.0), Float(2.0), Float(0.5))
+
+
+def test_issue_4611():
+    assert abs(pi._evalf(50) - 3.14159265358979) < 1e-10
+    assert abs(E._evalf(50) - 2.71828182845905) < 1e-10
+    assert abs(Catalan._evalf(50) - 0.915965594177219) < 1e-10
+    assert abs(EulerGamma._evalf(50) - 0.577215664901533) < 1e-10
+    assert abs(GoldenRatio._evalf(50) - 1.61803398874989) < 1e-10
+    assert abs(TribonacciConstant._evalf(50) - 1.83928675521416) < 1e-10
+
+    x = Symbol("x")
+    assert (pi + x).evalf() == pi.evalf() + x
+    assert (E + x).evalf() == E.evalf() + x
+    assert (Catalan + x).evalf() == Catalan.evalf() + x
+    assert (EulerGamma + x).evalf() == EulerGamma.evalf() + x
+    assert (GoldenRatio + x).evalf() == GoldenRatio.evalf() + x
+    assert (TribonacciConstant + x).evalf() == TribonacciConstant.evalf() + x
+
+
+@conserve_mpmath_dps
+def test_conversion_to_mpmath():
+    assert mpmath.mpmathify(Integer(1)) == mpmath.mpf(1)
+    assert mpmath.mpmathify(S.Half) == mpmath.mpf(0.5)
+    assert mpmath.mpmathify(Float('1.23', 15)) == mpmath.mpf('1.23')
+
+    assert mpmath.mpmathify(I) == mpmath.mpc(1j)
+
+    assert mpmath.mpmathify(1 + 2*I) == mpmath.mpc(1 + 2j)
+    assert mpmath.mpmathify(1.0 + 2*I) == mpmath.mpc(1 + 2j)
+    assert mpmath.mpmathify(1 + 2.0*I) == mpmath.mpc(1 + 2j)
+    assert mpmath.mpmathify(1.0 + 2.0*I) == mpmath.mpc(1 + 2j)
+    assert mpmath.mpmathify(S.Half + S.Half*I) == mpmath.mpc(0.5 + 0.5j)
+
+    assert mpmath.mpmathify(2*I) == mpmath.mpc(2j)
+    assert mpmath.mpmathify(2.0*I) == mpmath.mpc(2j)
+    assert mpmath.mpmathify(S.Half*I) == mpmath.mpc(0.5j)
+
+    mpmath.mp.dps = 100
+    assert mpmath.mpmathify(pi.evalf(100) + pi.evalf(100)*I) == mpmath.pi + mpmath.pi*mpmath.j
+    assert mpmath.mpmathify(pi.evalf(100)*I) == mpmath.pi*mpmath.j
+
+
+def test_relational():
+    # real
+    x = S(.1)
+    assert (x != cos) is True
+    assert (x == cos) is False
+
+    # rational
+    x = Rational(1, 3)
+    assert (x != cos) is True
+    assert (x == cos) is False
+
+    # integer defers to rational so these tests are omitted
+
+    # number symbol
+    x = pi
+    assert (x != cos) is True
+    assert (x == cos) is False
+
+
+def test_Integer_as_index():
+    assert 'hello'[Integer(2):] == 'llo'
+
+
+def test_Rational_int():
+    assert int( Rational(7, 5)) == 1
+    assert int( S.Half) == 0
+    assert int(Rational(-1, 2)) == 0
+    assert int(-Rational(7, 5)) == -1
+
+
+def test_zoo():
+    b = Symbol('b', finite=True)
+    nz = Symbol('nz', nonzero=True)
+    p = Symbol('p', positive=True)
+    n = Symbol('n', negative=True)
+    im = Symbol('i', imaginary=True)
+    c = Symbol('c', complex=True)
+    pb = Symbol('pb', positive=True)
+    nb = Symbol('nb', negative=True)
+    imb = Symbol('ib', imaginary=True, finite=True)
+    for i in [I, S.Infinity, S.NegativeInfinity, S.Zero, S.One, S.Pi, S.Half, S(3), log(3),
+              b, nz, p, n, im, pb, nb, imb, c]:
+        if i.is_finite and (i.is_real or i.is_imaginary):
+            assert i + zoo is zoo
+            assert i - zoo is zoo
+            assert zoo + i is zoo
+            assert zoo - i is zoo
+        elif i.is_finite is not False:
+            assert (i + zoo).is_Add
+            assert (i - zoo).is_Add
+            assert (zoo + i).is_Add
+            assert (zoo - i).is_Add
+        else:
+            assert (i + zoo) is S.NaN
+            assert (i - zoo) is S.NaN
+            assert (zoo + i) is S.NaN
+            assert (zoo - i) is S.NaN
+
+        if fuzzy_not(i.is_zero) and (i.is_extended_real or i.is_imaginary):
+            assert i*zoo is zoo
+            assert zoo*i is zoo
+        elif i.is_zero:
+            assert i*zoo is S.NaN
+            assert zoo*i is S.NaN
+        else:
+            assert (i*zoo).is_Mul
+            assert (zoo*i).is_Mul
+
+        if fuzzy_not((1/i).is_zero) and (i.is_real or i.is_imaginary):
+            assert zoo/i is zoo
+        elif (1/i).is_zero:
+            assert zoo/i is S.NaN
+        elif i.is_zero:
+            assert zoo/i is zoo
+        else:
+            assert (zoo/i).is_Mul
+
+    assert (I*oo).is_Mul  # allow directed infinity
+    assert zoo + zoo is S.NaN
+    assert zoo * zoo is zoo
+    assert zoo - zoo is S.NaN
+    assert zoo/zoo is S.NaN
+    assert zoo**zoo is S.NaN
+    assert zoo**0 is S.One
+    assert zoo**2 is zoo
+    assert 1/zoo is S.Zero
+
+    assert Mul.flatten([S.NegativeOne, oo, S(0)]) == ([S.NaN], [], None)
+
+
+def test_issue_4122():
+    x = Symbol('x', nonpositive=True)
+    assert oo + x is oo
+    x = Symbol('x', extended_nonpositive=True)
+    assert (oo + x).is_Add
+    x = Symbol('x', finite=True)
+    assert (oo + x).is_Add  # x could be imaginary
+    x = Symbol('x', nonnegative=True)
+    assert oo + x is oo
+    x = Symbol('x', extended_nonnegative=True)
+    assert oo + x is oo
+    x = Symbol('x', finite=True, real=True)
+    assert oo + x is oo
+
+    # similarly for negative infinity
+    x = Symbol('x', nonnegative=True)
+    assert -oo + x is -oo
+    x = Symbol('x', extended_nonnegative=True)
+    assert (-oo + x).is_Add
+    x = Symbol('x', finite=True)
+    assert (-oo + x).is_Add
+    x = Symbol('x', nonpositive=True)
+    assert -oo + x is -oo
+    x = Symbol('x', extended_nonpositive=True)
+    assert -oo + x is -oo
+    x = Symbol('x', finite=True, real=True)
+    assert -oo + x is -oo
+
+
+def test_GoldenRatio_expand():
+    assert GoldenRatio.expand(func=True) == S.Half + sqrt(5)/2
+
+
+def test_TribonacciConstant_expand():
+        assert TribonacciConstant.expand(func=True) == \
+          (1 + cbrt(19 - 3*sqrt(33)) + cbrt(19 + 3*sqrt(33))) / 3
+
+
+def test_as_content_primitive():
+    assert S.Zero.as_content_primitive() == (1, 0)
+    assert S.Half.as_content_primitive() == (S.Half, 1)
+    assert (Rational(-1, 2)).as_content_primitive() == (S.Half, -1)
+    assert S(3).as_content_primitive() == (3, 1)
+    assert S(3.1).as_content_primitive() == (1, 3.1)
+
+
+def test_hashing_sympy_integers():
+    # Test for issue 5072
+    assert {Integer(3)} == {int(3)}
+    assert hash(Integer(4)) == hash(int(4))
+
+
+def test_rounding_issue_4172():
+    assert int((E**100).round()) == \
+        26881171418161354484126255515800135873611119
+    assert int((pi**100).round()) == \
+        51878483143196131920862615246303013562686760680406
+    assert int((Rational(1)/EulerGamma**100).round()) == \
+        734833795660954410469466
+
+
+@XFAIL
+def test_mpmath_issues():
+    from mpmath.libmp.libmpf import _normalize
+    import mpmath.libmp as mlib
+    rnd = mlib.round_nearest
+    mpf = (0, int(0), -123, -1, 53, rnd)  # nan
+    assert _normalize(mpf, 53) != (0, int(0), 0, 0)
+    mpf = (0, int(0), -456, -2, 53, rnd)  # +inf
+    assert _normalize(mpf, 53) != (0, int(0), 0, 0)
+    mpf = (1, int(0), -789, -3, 53, rnd)  # -inf
+    assert _normalize(mpf, 53) != (0, int(0), 0, 0)
+
+    from mpmath.libmp.libmpf import fnan
+    assert mlib.mpf_eq(fnan, fnan)
+
+
+def test_Catalan_EulerGamma_prec():
+    n = GoldenRatio
+    f = Float(n.n(), 5)
+    assert f._mpf_ == (0, int(212079), -17, 18)
+    assert f._prec == 20
+    assert n._as_mpf_val(20) == f._mpf_
+
+    n = EulerGamma
+    f = Float(n.n(), 5)
+    assert f._mpf_ == (0, int(302627), -19, 19)
+    assert f._prec == 20
+    assert n._as_mpf_val(20) == f._mpf_
+
+
+def test_Catalan_rewrite():
+    k = Dummy('k', integer=True, nonnegative=True)
+    assert Catalan.rewrite(Sum).dummy_eq(
+            Sum((-1)**k/(2*k + 1)**2, (k, 0, oo)))
+    assert Catalan.rewrite() == Catalan
+
+
+def test_bool_eq():
+    assert 0 == False
+    assert S(0) == False
+    assert S(0) != S.false
+    assert 1 == True
+    assert S.One == True
+    assert S.One != S.true
+
+
+def test_Float_eq():
+    # all .5 values are the same
+    assert Float(.5, 10) == Float(.5, 11) == Float(.5, 1)
+    # but floats that aren't exact in base-2 still
+    # don't compare the same because they have different
+    # underlying mpf values
+    assert Float(.12, 3) != Float(.12, 4)
+    assert Float(.12, 3) != .12
+    assert 0.12 != Float(.12, 3)
+    assert Float('.12', 22) != .12
+    # issue 11707
+    # but Float/Rational -- except for 0 --
+    # are exact so Rational(x) = Float(y) only if
+    # Rational(x) == Rational(Float(y))
+    assert Float('1.1') != Rational(11, 10)
+    assert Rational(11, 10) != Float('1.1')
+    # coverage
+    assert not Float(3) == 2
+    assert not Float(2**2) == S.Half
+    assert Float(2**2) == 4
+    assert not Float(2**-2) == 1
+    assert Float(2**-1) == S.Half
+    assert not Float(2*3) == 3
+    assert not Float(2*3) == S.Half
+    assert Float(2*3) == 6
+    assert not Float(2*3) == 8
+    assert Float(.75) == Rational(3, 4)
+    assert Float(5/18) == 5/18
+    # 4473
+    assert Float(2.) != 3
+    assert Float((0,1,-3)) == S.One/8
+    assert Float((0,1,-3)) != S.One/9
+    # 16196
+    assert 2 == Float(2)  # as per Python
+    # but in a computation...
+    assert t**2 != t**2.0
+
+
+def test_issue_6640():
+    from mpmath.libmp.libmpf import finf, fninf
+    # fnan is not included because Float no longer returns fnan,
+    # but otherwise, the same sort of test could apply
+    assert Float(finf).is_zero is False
+    assert Float(fninf).is_zero is False
+    assert bool(Float(0)) is False
+
+
+def test_issue_6349():
+    assert Float('23.e3', '')._prec == 10
+    assert Float('23e3', '')._prec == 20
+    assert Float('23000', '')._prec == 20
+    assert Float('-23000', '')._prec == 20
+
+
+def test_mpf_norm():
+    assert mpf_norm((1, 0, 1, 0), 10) == mpf('0')._mpf_
+    assert Float._new((1, 0, 1, 0), 10)._mpf_ == mpf('0')._mpf_
+
+
+def test_latex():
+    assert latex(pi) == r"\pi"
+    assert latex(E) == r"e"
+    assert latex(GoldenRatio) == r"\phi"
+    assert latex(TribonacciConstant) == r"\text{TribonacciConstant}"
+    assert latex(EulerGamma) == r"\gamma"
+    assert latex(oo) == r"\infty"
+    assert latex(-oo) == r"-\infty"
+    assert latex(zoo) == r"\tilde{\infty}"
+    assert latex(nan) == r"\text{NaN}"
+    assert latex(I) == r"i"
+
+
+def test_issue_7742():
+    assert -oo % 1 is nan
+
+
+def test_simplify_AlgebraicNumber():
+    A = AlgebraicNumber
+    e = 3**(S.One/6)*(3 + (135 + 78*sqrt(3))**Rational(2, 3))/(45 + 26*sqrt(3))**(S.One/3)
+    assert simplify(A(e)) == A(12)  # wester test_C20
+
+    e = (41 + 29*sqrt(2))**(S.One/5)
+    assert simplify(A(e)) == A(1 + sqrt(2))  # wester test_C21
+
+    e = (3 + 4*I)**Rational(3, 2)
+    assert simplify(A(e)) == A(2 + 11*I)  # issue 4401
+
+
+def test_Float_idempotence():
+    x = Float('1.23', '')
+    y = Float(x)
+    z = Float(x, 15)
+    assert same_and_same_prec(y, x)
+    assert not same_and_same_prec(z, x)
+    x = Float(10**20)
+    y = Float(x)
+    z = Float(x, 15)
+    assert same_and_same_prec(y, x)
+    assert not same_and_same_prec(z, x)
+
+
+def test_comp1():
+    # sqrt(2) = 1.414213 5623730950...
+    a = sqrt(2).n(7)
+    assert comp(a, 1.4142129) is False
+    assert comp(a, 1.4142130)
+    #                  ...
+    assert comp(a, 1.4142141)
+    assert comp(a, 1.4142142) is False
+    assert comp(sqrt(2).n(2), '1.4')
+    assert comp(sqrt(2).n(2), Float(1.4, 2), '')
+    assert comp(sqrt(2).n(2), 1.4, '')
+    assert comp(sqrt(2).n(2), Float(1.4, 3), '') is False
+    assert comp(sqrt(2) + sqrt(3)*I, 1.4 + 1.7*I, .1)
+    assert not comp(sqrt(2) + sqrt(3)*I, (1.5 + 1.7*I)*0.89, .1)
+    assert comp(sqrt(2) + sqrt(3)*I, (1.5 + 1.7*I)*0.90, .1)
+    assert comp(sqrt(2) + sqrt(3)*I, (1.5 + 1.7*I)*1.07, .1)
+    assert not comp(sqrt(2) + sqrt(3)*I, (1.5 + 1.7*I)*1.08, .1)
+    assert [(i, j)
+            for i in range(130, 150)
+            for j in range(170, 180)
+            if comp((sqrt(2)+ I*sqrt(3)).n(3), i/100. + I*j/100.)] == [
+        (141, 173), (142, 173)]
+    raises(ValueError, lambda: comp(t, '1'))
+    raises(ValueError, lambda: comp(t, 1))
+    assert comp(0, 0.0)
+    assert comp(.5, S.Half)
+    assert comp(2 + sqrt(2), 2.0 + sqrt(2))
+    assert not comp(0, 1)
+    assert not comp(2, sqrt(2))
+    assert not comp(2 + I, 2.0 + sqrt(2))
+    assert not comp(2.0 + sqrt(2), 2 + I)
+    assert not comp(2.0 + sqrt(2), sqrt(3))
+    assert comp(1/pi.n(4), 0.3183, 1e-5)
+    assert not comp(1/pi.n(4), 0.3183, 8e-6)
+
+
+def test_issue_9491():
+    assert oo**zoo is nan
+
+
+def test_issue_10063():
+    assert 2**Float(3) == Float(8)
+
+
+def test_issue_10020():
+    assert oo**I is S.NaN
+    assert oo**(1 + I) is S.ComplexInfinity
+    assert oo**(-1 + I) is S.Zero
+    assert (-oo)**I is S.NaN
+    assert (-oo)**(-1 + I) is S.Zero
+    assert oo**t == Pow(oo, t, evaluate=False)
+    assert (-oo)**t == Pow(-oo, t, evaluate=False)
+
+
+def test_invert_numbers():
+    assert S(2).invert(5) == 3
+    assert S(2).invert(Rational(5, 2)) == S.Half
+    assert S(2).invert(5.) == S.Half
+    assert S(2).invert(S(5)) == 3
+    assert S(2.).invert(5) == 0.5
+    assert S(sqrt(2)).invert(5) == 1/sqrt(2)
+    assert S(sqrt(2)).invert(sqrt(3)) == 1/sqrt(2)
+
+
+def test_mod_inverse():
+    assert mod_inverse(3, 11) == 4
+    assert mod_inverse(5, 11) == 9
+    assert mod_inverse(21124921, 521512) == 7713
+    assert mod_inverse(124215421, 5125) == 2981
+    assert mod_inverse(214, 12515) == 1579
+    assert mod_inverse(5823991, 3299) == 1442
+    assert mod_inverse(123, 44) == 39
+    assert mod_inverse(2, 5) == 3
+    assert mod_inverse(-2, 5) == 2
+    assert mod_inverse(2, -5) == -2
+    assert mod_inverse(-2, -5) == -3
+    assert mod_inverse(-3, -7) == -5
+    x = Symbol('x')
+    assert S(2).invert(x) == S.Half
+    raises(TypeError, lambda: mod_inverse(2, x))
+    raises(ValueError, lambda: mod_inverse(2, S.Half))
+    raises(ValueError, lambda: mod_inverse(2, cos(1)**2 + sin(1)**2))
+
+
+def test_golden_ratio_rewrite_as_sqrt():
+    assert GoldenRatio.rewrite(sqrt) == S.Half + sqrt(5)*S.Half
+
+
+def test_tribonacci_constant_rewrite_as_sqrt():
+    assert TribonacciConstant.rewrite(sqrt) == \
+      (1 + cbrt(19 - 3*sqrt(33)) + cbrt(19 + 3*sqrt(33))) / 3
+
+
+def test_comparisons_with_unknown_type():
+    class Foo:
+        """
+        Class that is unaware of Basic, and relies on both classes returning
+        the NotImplemented singleton for equivalence to evaluate to False.
+
+        """
+
+    ni, nf, nr = Integer(3), Float(1.0), Rational(1, 3)
+    foo = Foo()
+
+    for n in ni, nf, nr, oo, -oo, zoo, nan:
+        assert n != foo
+        assert foo != n
+        assert not n == foo
+        assert not foo == n
+        raises(TypeError, lambda: n < foo)
+        raises(TypeError, lambda: foo > n)
+        raises(TypeError, lambda: n > foo)
+        raises(TypeError, lambda: foo < n)
+        raises(TypeError, lambda: n <= foo)
+        raises(TypeError, lambda: foo >= n)
+        raises(TypeError, lambda: n >= foo)
+        raises(TypeError, lambda: foo <= n)
+
+    class Bar:
+        """
+        Class that considers itself equal to any instance of Number except
+        infinities and nans, and relies on SymPy types returning the
+        NotImplemented singleton for symmetric equality relations.
+
+        """
+        def __eq__(self, other):
+            if other in (oo, -oo, zoo, nan):
+                return False
+            if isinstance(other, Number):
+                return True
+            return NotImplemented
+
+        def __ne__(self, other):
+            return not self == other
+
+    bar = Bar()
+
+    for n in ni, nf, nr:
+        assert n == bar
+        assert bar == n
+        assert not n != bar
+        assert not bar != n
+
+    for n in oo, -oo, zoo, nan:
+        assert n != bar
+        assert bar != n
+        assert not n == bar
+        assert not bar == n
+
+    for n in ni, nf, nr, oo, -oo, zoo, nan:
+        raises(TypeError, lambda: n < bar)
+        raises(TypeError, lambda: bar > n)
+        raises(TypeError, lambda: n > bar)
+        raises(TypeError, lambda: bar < n)
+        raises(TypeError, lambda: n <= bar)
+        raises(TypeError, lambda: bar >= n)
+        raises(TypeError, lambda: n >= bar)
+        raises(TypeError, lambda: bar <= n)
+
+
+def test_NumberSymbol_comparison():
+    from sympy.core.tests.test_relational import rel_check
+    rpi = Rational('905502432259640373/288230376151711744')
+    fpi = Float(float(pi))
+    assert rel_check(rpi, fpi)
+
+
+def test_Integer_precision():
+    # Make sure Integer inputs for keyword args work
+    assert Float('1.0', dps=Integer(15))._prec == 53
+    assert Float('1.0', precision=Integer(15))._prec == 15
+    assert type(Float('1.0', precision=Integer(15))._prec) == int
+    assert sympify(srepr(Float('1.0', precision=15))) == Float('1.0', precision=15)
+
+
+def test_numpy_to_float():
+    from sympy.testing.pytest import skip
+    from sympy.external import import_module
+    np = import_module('numpy')
+    if not np:
+        skip('numpy not installed. Abort numpy tests.')
+
+    def check_prec_and_relerr(npval, ratval):
+        prec = np.finfo(npval).nmant + 1
+        x = Float(npval)
+        assert x._prec == prec
+        y = Float(ratval, precision=prec)
+        assert abs((x - y)/y) < 2**(-(prec + 1))
+
+    check_prec_and_relerr(np.float16(2.0/3), Rational(2, 3))
+    check_prec_and_relerr(np.float32(2.0/3), Rational(2, 3))
+    check_prec_and_relerr(np.float64(2.0/3), Rational(2, 3))
+    # extended precision, on some arch/compilers:
+    x = np.longdouble(2)/3
+    check_prec_and_relerr(x, Rational(2, 3))
+    y = Float(x, precision=10)
+    assert same_and_same_prec(y, Float(Rational(2, 3), precision=10))
+
+    raises(TypeError, lambda: Float(np.complex64(1+2j)))
+    raises(TypeError, lambda: Float(np.complex128(1+2j)))
+
+
+def test_Integer_ceiling_floor():
+    a = Integer(4)
+
+    assert a.floor() == a
+    assert a.ceiling() == a
+
+
+def test_ComplexInfinity():
+    assert zoo.floor() is zoo
+    assert zoo.ceiling() is zoo
+    assert zoo**zoo is S.NaN
+
+
+def test_Infinity_floor_ceiling_power():
+    assert oo.floor() is oo
+    assert oo.ceiling() is oo
+    assert oo**S.NaN is S.NaN
+    assert oo**zoo is S.NaN
+
+
+def test_One_power():
+    assert S.One**12 is S.One
+    assert S.NegativeOne**S.NaN is S.NaN
+
+
+def test_NegativeInfinity():
+    assert (-oo).floor() is -oo
+    assert (-oo).ceiling() is -oo
+    assert (-oo)**11 is -oo
+    assert (-oo)**12 is oo
+
+
+def test_issue_6133():
+    raises(TypeError, lambda: (-oo < None))
+    raises(TypeError, lambda: (S(-2) < None))
+    raises(TypeError, lambda: (oo < None))
+    raises(TypeError, lambda: (oo > None))
+    raises(TypeError, lambda: (S(2) < None))
+
+
+def test_abc():
+    x = numbers.Float(5)
+    assert(isinstance(x, nums.Number))
+    assert(isinstance(x, numbers.Number))
+    assert(isinstance(x, nums.Real))
+    y = numbers.Rational(1, 3)
+    assert(isinstance(y, nums.Number))
+    assert(y.numerator == 1)
+    assert(y.denominator == 3)
+    assert(isinstance(y, nums.Rational))
+    z = numbers.Integer(3)
+    assert(isinstance(z, nums.Number))
+    assert(isinstance(z, numbers.Number))
+    assert(isinstance(z, nums.Rational))
+    assert(isinstance(z, numbers.Rational))
+    assert(isinstance(z, nums.Integral))
+
+
+def test_floordiv():
+    assert S(2)//S.Half == 4
+
+
+def test_negation():
+    assert -S.Zero is S.Zero
+    assert -Float(0) is not S.Zero and -Float(0) == 0.0
+
+
+def test_exponentiation_of_0():
+    x = Symbol('x')
+    assert 0**-x == zoo**x
+    assert unchanged(Pow, 0, x)
+    x = Symbol('x', zero=True)
+    assert 0**-x == S.One
+    assert 0**x == S.One
+
+
+def test_equal_valued():
+    x = Symbol('x')
+
+    equal_values = [
+        [1, 1.0, S(1), S(1.0), S(1).n(5)],
+        [2, 2.0, S(2), S(2.0), S(2).n(5)],
+        [-1, -1.0, -S(1), -S(1.0), -S(1).n(5)],
+        [0.5, S(0.5), S(1)/2],
+        [-0.5, -S(0.5), -S(1)/2],
+        [0, 0.0, S(0), S(0.0), S(0).n()],
+        [pi], [pi.n()],           # <-- not equal
+        [S(1)/10], [0.1, S(0.1)], # <-- not equal
+        [S(0.1).n(5)],
+        [oo],
+        [cos(x/2)], [cos(0.5*x)], # <-- no recursion
+    ]
+
+    for m, values_m in enumerate(equal_values):
+        for value_i in values_m:
+
+            # All values in same list equal
+            for value_j in values_m:
+                assert equal_valued(value_i, value_j) is True
+
+            # Not equal to anything in any other list:
+            for n, values_n in enumerate(equal_values):
+                if n == m:
+                    continue
+                for value_j in values_n:
+                    assert equal_valued(value_i, value_j) is False

env-llmeval/lib/python3.10/site-packages/sympy/core/tests/test_operations.py

@@ -0,0 +1,110 @@
+from sympy.core.expr import Expr
+from sympy.core.numbers import Integer
+from sympy.core.singleton import S
+from sympy.core.symbol import (Symbol, symbols)
+from sympy.core.operations import AssocOp, LatticeOp
+from sympy.testing.pytest import raises
+from sympy.core.sympify import SympifyError
+from sympy.core.add import Add, add
+from sympy.core.mul import Mul, mul
+
+# create the simplest possible Lattice class
+
+
+class join(LatticeOp):
+    zero = Integer(0)
+    identity = Integer(1)
+
+
+def test_lattice_simple():
+    assert join(join(2, 3), 4) == join(2, join(3, 4))
+    assert join(2, 3) == join(3, 2)
+    assert join(0, 2) == 0
+    assert join(1, 2) == 2
+    assert join(2, 2) == 2
+
+    assert join(join(2, 3), 4) == join(2, 3, 4)
+    assert join() == 1
+    assert join(4) == 4
+    assert join(1, 4, 2, 3, 1, 3, 2) == join(2, 3, 4)
+
+
+def test_lattice_shortcircuit():
+    raises(SympifyError, lambda: join(object))
+    assert join(0, object) == 0
+
+
+def test_lattice_print():
+    assert str(join(5, 4, 3, 2)) == 'join(2, 3, 4, 5)'
+
+
+def test_lattice_make_args():
+    assert join.make_args(join(2, 3, 4)) == {S(2), S(3), S(4)}
+    assert join.make_args(0) == {0}
+    assert list(join.make_args(0))[0] is S.Zero
+    assert Add.make_args(0)[0] is S.Zero
+
+
+def test_issue_14025():
+    a, b, c, d = symbols('a,b,c,d', commutative=False)
+    assert Mul(a, b, c).has(c*b) == False
+    assert Mul(a, b, c).has(b*c) == True
+    assert Mul(a, b, c, d).has(b*c*d) == True
+
+
+def test_AssocOp_flatten():
+    a, b, c, d = symbols('a,b,c,d')
+
+    class MyAssoc(AssocOp):
+        identity = S.One
+
+    assert MyAssoc(a, MyAssoc(b, c)).args == \
+        MyAssoc(MyAssoc(a, b), c).args == \
+        MyAssoc(MyAssoc(a, b, c)).args == \
+        MyAssoc(a, b, c).args == \
+            (a, b, c)
+    u = MyAssoc(b, c)
+    v = MyAssoc(u, d, evaluate=False)
+    assert v.args == (u, d)
+    # like Add, any unevaluated outer call will flatten inner args
+    assert MyAssoc(a, v).args == (a, b, c, d)
+
+
+def test_add_dispatcher():
+
+    class NewBase(Expr):
+        @property
+        def _add_handler(self):
+            return NewAdd
+    class NewAdd(NewBase, Add):
+        pass
+    add.register_handlerclass((Add, NewAdd), NewAdd)
+
+    a, b = Symbol('a'), NewBase()
+
+    # Add called as fallback
+    assert add(1, 2) == Add(1, 2)
+    assert add(a, a) == Add(a, a)
+
+    # selection by registered priority
+    assert add(a,b,a) == NewAdd(2*a, b)
+
+
+def test_mul_dispatcher():
+
+    class NewBase(Expr):
+        @property
+        def _mul_handler(self):
+            return NewMul
+    class NewMul(NewBase, Mul):
+        pass
+    mul.register_handlerclass((Mul, NewMul), NewMul)
+
+    a, b = Symbol('a'), NewBase()
+
+    # Mul called as fallback
+    assert mul(1, 2) == Mul(1, 2)
+    assert mul(a, a) == Mul(a, a)
+
+    # selection by registered priority
+    assert mul(a,b,a) == NewMul(a**2, b)

env-llmeval/lib/python3.10/site-packages/sympy/core/tests/test_parameters.py

@@ -0,0 +1,90 @@
+from sympy.abc import x, y
+from sympy.core.parameters import evaluate
+from sympy.core import Mul, Add, Pow, S
+from sympy.core.numbers import oo
+from sympy.functions.elementary.miscellaneous import sqrt
+
+def test_add():
+    with evaluate(False):
+        p = oo - oo
+        assert isinstance(p, Add) and p.args == (oo, -oo)
+        p = 5 - oo
+        assert isinstance(p, Add) and p.args == (-oo, 5)
+        p = oo - 5
+        assert isinstance(p, Add) and p.args == (oo, -5)
+        p = oo + 5
+        assert isinstance(p, Add) and p.args == (oo, 5)
+        p = 5 + oo
+        assert isinstance(p, Add) and p.args == (oo, 5)
+        p = -oo + 5
+        assert isinstance(p, Add) and p.args == (-oo, 5)
+        p = -5 - oo
+        assert isinstance(p, Add) and p.args == (-oo, -5)
+
+    with evaluate(False):
+        expr = x + x
+        assert isinstance(expr, Add)
+        assert expr.args == (x, x)
+
+        with evaluate(True):
+            assert (x + x).args == (2, x)
+
+        assert (x + x).args == (x, x)
+
+    assert isinstance(x + x, Mul)
+
+    with evaluate(False):
+        assert S.One + 1 == Add(1, 1)
+        assert 1 + S.One == Add(1, 1)
+
+        assert S(4) - 3 == Add(4, -3)
+        assert -3 + S(4) == Add(4, -3)
+
+        assert S(2) * 4 == Mul(2, 4)
+        assert 4 * S(2) == Mul(2, 4)
+
+        assert S(6) / 3 == Mul(6, Pow(3, -1))
+        assert S.One / 3 * 6 == Mul(S.One / 3, 6)
+
+        assert 9 ** S(2) == Pow(9, 2)
+        assert S(2) ** 9 == Pow(2, 9)
+
+        assert S(2) / 2 == Mul(2, Pow(2, -1))
+        assert S.One / 2 * 2 == Mul(S.One / 2, 2)
+
+        assert S(2) / 3 + 1 == Add(S(2) / 3, 1)
+        assert 1 + S(2) / 3 == Add(1, S(2) / 3)
+
+        assert S(4) / 7 - 3 == Add(S(4) / 7, -3)
+        assert -3 + S(4) / 7 == Add(-3, S(4) / 7)
+
+        assert S(2) / 4 * 4 == Mul(S(2) / 4, 4)
+        assert 4 * (S(2) / 4) == Mul(4, S(2) / 4)
+
+        assert S(6) / 3 == Mul(6, Pow(3, -1))
+        assert S.One / 3 * 6 == Mul(S.One / 3, 6)
+
+        assert S.One / 3 + sqrt(3) == Add(S.One / 3, sqrt(3))
+        assert sqrt(3) + S.One / 3 == Add(sqrt(3), S.One / 3)
+
+        assert S.One / 2 * 10.333 == Mul(S.One / 2, 10.333)
+        assert 10.333 * (S.One / 2) == Mul(10.333, S.One / 2)
+
+        assert sqrt(2) * sqrt(2) == Mul(sqrt(2), sqrt(2))
+
+        assert S.One / 2 + x == Add(S.One / 2, x)
+        assert x + S.One / 2 == Add(x, S.One / 2)
+
+        assert S.One / x * x == Mul(S.One / x, x)
+        assert x * (S.One / x) == Mul(x, Pow(x, -1))
+
+        assert S.One / 3 == Pow(3, -1)
+        assert S.One / x == Pow(x, -1)
+        assert 1 / S(3) == Pow(3, -1)
+        assert 1 / x == Pow(x, -1)
+
+def test_nested():
+    with evaluate(False):
+        expr = (x + x) + (y + y)
+        assert expr.args == ((x + x), (y + y))
+        assert expr.args[0].args == (x, x)