from sympy import Order, S, log, limit, lcm_list, im, re, Dummy
from sympy.core import Add, Mul, Pow
from sympy.core.basic import Basic
from sympy.core.compatibility import iterable
from sympy.core.expr import AtomicExpr, Expr
from sympy.core.function import expand_mul
from sympy.core.numbers import _sympifyit, oo
from sympy.core.relational import is_le, is_lt, is_ge, is_gt
from sympy.core.sympify import _sympify
from sympy.functions.elementary.miscellaneous import Min, Max
from sympy.logic.boolalg import And
from sympy.sets.sets import (Interval, Intersection, FiniteSet, Union,
                             Complement, EmptySet)
from sympy.sets.fancysets import ImageSet
from sympy.solvers.inequalities import solve_univariate_inequality
from sympy.utilities import filldedent
from sympy.multipledispatch import dispatch

def continuous_domain(f, symbol, domain):
    """
    Returns the intervals in the given domain for which the function
    is continuous.
    This method is limited by the ability to determine the various
    singularities and discontinuities of the given function.

    Parameters
    ==========

    f : Expr
        The concerned function.
    symbol : Symbol
        The variable for which the intervals are to be determined.
    domain : Interval
        The domain over which the continuity of the symbol has to be checked.

    Examples
    ========

    >>> from sympy import Symbol, S, tan, log, pi, sqrt
    >>> from sympy.sets import Interval
    >>> from sympy.calculus.util import continuous_domain
    >>> x = Symbol('x')
    >>> continuous_domain(1/x, x, S.Reals)
    Union(Interval.open(-oo, 0), Interval.open(0, oo))
    >>> continuous_domain(tan(x), x, Interval(0, pi))
    Union(Interval.Ropen(0, pi/2), Interval.Lopen(pi/2, pi))
    >>> continuous_domain(sqrt(x - 2), x, Interval(-5, 5))
    Interval(2, 5)
    >>> continuous_domain(log(2*x - 1), x, S.Reals)
    Interval.open(1/2, oo)

    Returns
    =======

    Interval
        Union of all intervals where the function is continuous.

    Raises
    ======

    NotImplementedError
        If the method to determine continuity of such a function
        has not yet been developed.

    """
    from sympy.solvers.inequalities import solve_univariate_inequality
    from sympy.solvers.solveset import _has_rational_power
    from sympy.calculus.singularities import singularities

    if domain.is_subset(S.Reals):
        constrained_interval = domain
        for atom in f.atoms(Pow):
            predicate, denomin = _has_rational_power(atom, symbol)
            if predicate and denomin == 2:
                constraint = solve_univariate_inequality(atom.base >= 0,
                                                         symbol).as_set()
                constrained_interval = Intersection(constraint,
                                                    constrained_interval)

        for atom in f.atoms(log):
            constraint = solve_univariate_inequality(atom.args[0] > 0,
                                                     symbol).as_set()
            constrained_interval = Intersection(constraint,
                                                constrained_interval)


    return constrained_interval - singularities(f, symbol, domain)


def function_range(f, symbol, domain):
    """
    Finds the range of a function in a given domain.
    This method is limited by the ability to determine the singularities and
    determine limits.

    Parameters
    ==========

    f : Expr
        The concerned function.
    symbol : Symbol
        The variable for which the range of function is to be determined.
    domain : Interval
        The domain under which the range of the function has to be found.

    Examples
    ========

    >>> from sympy import Symbol, S, exp, log, pi, sqrt, sin, tan
    >>> from sympy.sets import Interval
    >>> from sympy.calculus.util import function_range
    >>> x = Symbol('x')
    >>> function_range(sin(x), x, Interval(0, 2*pi))
    Interval(-1, 1)
    >>> function_range(tan(x), x, Interval(-pi/2, pi/2))
    Interval(-oo, oo)
    >>> function_range(1/x, x, S.Reals)
    Union(Interval.open(-oo, 0), Interval.open(0, oo))
    >>> function_range(exp(x), x, S.Reals)
    Interval.open(0, oo)
    >>> function_range(log(x), x, S.Reals)
    Interval(-oo, oo)
    >>> function_range(sqrt(x), x , Interval(-5, 9))
    Interval(0, 3)

    Returns
    =======

    Interval
        Union of all ranges for all intervals under domain where function is
        continuous.

    Raises
    ======

    NotImplementedError
        If any of the intervals, in the given domain, for which function
        is continuous are not finite or real,
        OR if the critical points of the function on the domain can't be found.
    """
    from sympy.solvers.solveset import solveset

    if isinstance(domain, EmptySet):
        return S.EmptySet

    period = periodicity(f, symbol)
    if period == S.Zero:
        # the expression is constant wrt symbol
        return FiniteSet(f.expand())

    if period is not None:
        if isinstance(domain, Interval):
            if (domain.inf - domain.sup).is_infinite:
                domain = Interval(0, period)
        elif isinstance(domain, Union):
            for sub_dom in domain.args:
                if isinstance(sub_dom, Interval) and \
                ((sub_dom.inf - sub_dom.sup).is_infinite):
                    domain = Interval(0, period)

    intervals = continuous_domain(f, symbol, domain)
    range_int = S.EmptySet
    if isinstance(intervals,(Interval, FiniteSet)):
        interval_iter = (intervals,)

    elif isinstance(intervals, Union):
        interval_iter = intervals.args

    else:
            raise NotImplementedError(filldedent('''
                Unable to find range for the given domain.
                '''))

    for interval in interval_iter:
        if isinstance(interval, FiniteSet):
            for singleton in interval:
                if singleton in domain:
                    range_int += FiniteSet(f.subs(symbol, singleton))
        elif isinstance(interval, Interval):
            vals = S.EmptySet
            critical_points = S.EmptySet
            critical_values = S.EmptySet
            bounds = ((interval.left_open, interval.inf, '+'),
                   (interval.right_open, interval.sup, '-'))

            for is_open, limit_point, direction in bounds:
                if is_open:
                    critical_values += FiniteSet(limit(f, symbol, limit_point, direction))
                    vals += critical_values

                else:
                    vals += FiniteSet(f.subs(symbol, limit_point))

            solution = solveset(f.diff(symbol), symbol, interval)

            if not iterable(solution):
                raise NotImplementedError(
                        'Unable to find critical points for {}'.format(f))
            if isinstance(solution, ImageSet):
                raise NotImplementedError(
                        'Infinite number of critical points for {}'.format(f))

            critical_points += solution

            for critical_point in critical_points:
                vals += FiniteSet(f.subs(symbol, critical_point))

            left_open, right_open = False, False

            if critical_values is not S.EmptySet:
                if critical_values.inf == vals.inf:
                    left_open = True

                if critical_values.sup == vals.sup:
                    right_open = True

            range_int += Interval(vals.inf, vals.sup, left_open, right_open)
        else:
            raise NotImplementedError(filldedent('''
                Unable to find range for the given domain.
                '''))

    return range_int


def not_empty_in(finset_intersection, *syms):
    """
    Finds the domain of the functions in `finite_set` in which the
    `finite_set` is not-empty

    Parameters
    ==========

    finset_intersection : The unevaluated intersection of FiniteSet containing
                        real-valued functions with Union of Sets
    syms : Tuple of symbols
            Symbol for which domain is to be found

    Raises
    ======

    NotImplementedError
        The algorithms to find the non-emptiness of the given FiniteSet are
        not yet implemented.
    ValueError
        The input is not valid.
    RuntimeError
        It is a bug, please report it to the github issue tracker
        (https://github.com/sympy/sympy/issues).

    Examples
    ========

    >>> from sympy import FiniteSet, Interval, not_empty_in, oo
    >>> from sympy.abc import x
    >>> not_empty_in(FiniteSet(x/2).intersect(Interval(0, 1)), x)
    Interval(0, 2)
    >>> not_empty_in(FiniteSet(x, x**2).intersect(Interval(1, 2)), x)
    Union(Interval(1, 2), Interval(-sqrt(2), -1))
    >>> not_empty_in(FiniteSet(x**2/(x + 2)).intersect(Interval(1, oo)), x)
    Union(Interval.Lopen(-2, -1), Interval(2, oo))
    """

    # TODO: handle piecewise defined functions
    # TODO: handle transcendental functions
    # TODO: handle multivariate functions
    if len(syms) == 0:
        raise ValueError("One or more symbols must be given in syms.")

    if finset_intersection is S.EmptySet:
        return S.EmptySet

    if isinstance(finset_intersection, Union):
        elm_in_sets = finset_intersection.args[0]
        return Union(not_empty_in(finset_intersection.args[1], *syms),
                     elm_in_sets)

    if isinstance(finset_intersection, FiniteSet):
        finite_set = finset_intersection
        _sets = S.Reals
    else:
        finite_set = finset_intersection.args[1]
        _sets = finset_intersection.args[0]

    if not isinstance(finite_set, FiniteSet):
        raise ValueError('A FiniteSet must be given, not %s: %s' %
                         (type(finite_set), finite_set))

    if len(syms) == 1:
        symb = syms[0]
    else:
        raise NotImplementedError('more than one variables %s not handled' %
                                  (syms,))

    def elm_domain(expr, intrvl):
        """ Finds the domain of an expression in any given interval """
        from sympy.solvers.solveset import solveset

        _start = intrvl.start
        _end = intrvl.end
        _singularities = solveset(expr.as_numer_denom()[1], symb,
                                  domain=S.Reals)

        if intrvl.right_open:
            if _end is S.Infinity:
                _domain1 = S.Reals
            else:
                _domain1 = solveset(expr < _end, symb, domain=S.Reals)
        else:
            _domain1 = solveset(expr <= _end, symb, domain=S.Reals)

        if intrvl.left_open:
            if _start is S.NegativeInfinity:
                _domain2 = S.Reals
            else:
                _domain2 = solveset(expr > _start, symb, domain=S.Reals)
        else:
            _domain2 = solveset(expr >= _start, symb, domain=S.Reals)

        # domain in the interval
        expr_with_sing = Intersection(_domain1, _domain2)
        expr_domain = Complement(expr_with_sing, _singularities)
        return expr_domain

    if isinstance(_sets, Interval):
        return Union(*[elm_domain(element, _sets) for element in finite_set])

    if isinstance(_sets, Union):
        _domain = S.EmptySet
        for intrvl in _sets.args:
            _domain_element = Union(*[elm_domain(element, intrvl)
                                      for element in finite_set])
            _domain = Union(_domain, _domain_element)
        return _domain


def periodicity(f, symbol, check=False):
    """
    Tests the given function for periodicity in the given symbol.

    Parameters
    ==========

    f : Expr.
        The concerned function.
    symbol : Symbol
        The variable for which the period is to be determined.
    check : Boolean, optional
        The flag to verify whether the value being returned is a period or not.

    Returns
    =======

    period
        The period of the function is returned.
        `None` is returned when the function is aperiodic or has a complex period.
        The value of `0` is returned as the period of a constant function.

    Raises
    ======

    NotImplementedError
        The value of the period computed cannot be verified.


    Notes
    =====

    Currently, we do not support functions with a complex period.
    The period of functions having complex periodic values such
    as `exp`, `sinh` is evaluated to `None`.

    The value returned might not be the "fundamental" period of the given
    function i.e. it may not be the smallest periodic value of the function.

    The verification of the period through the `check` flag is not reliable
    due to internal simplification of the given expression. Hence, it is set
    to `False` by default.

    Examples
    ========
    >>> from sympy import Symbol, sin, cos, tan, exp
    >>> from sympy.calculus.util import periodicity
    >>> x = Symbol('x')
    >>> f = sin(x) + sin(2*x) + sin(3*x)
    >>> periodicity(f, x)
    2*pi
    >>> periodicity(sin(x)*cos(x), x)
    pi
    >>> periodicity(exp(tan(2*x) - 1), x)
    pi/2
    >>> periodicity(sin(4*x)**cos(2*x), x)
    pi
    >>> periodicity(exp(x), x)
    """
    from sympy.core.mod import Mod
    from sympy.core.relational import Relational
    from sympy.functions.elementary.exponential import exp
    from sympy.functions.elementary.complexes import Abs
    from sympy.functions.elementary.trigonometric import (
        TrigonometricFunction, sin, cos, csc, sec)
    from sympy.simplify.simplify import simplify
    from sympy.solvers.decompogen import decompogen
    from sympy.polys.polytools import degree

    temp = Dummy('x', real=True)
    f = f.subs(symbol, temp)
    symbol = temp

    def _check(orig_f, period):
        '''Return the checked period or raise an error.'''
        new_f = orig_f.subs(symbol, symbol + period)
        if new_f.equals(orig_f):
            return period
        else:
            raise NotImplementedError(filldedent('''
                The period of the given function cannot be verified.
                When `%s` was replaced with `%s + %s` in `%s`, the result
                was `%s` which was not recognized as being the same as
                the original function.
                So either the period was wrong or the two forms were
                not recognized as being equal.
                Set check=False to obtain the value.''' %
                (symbol, symbol, period, orig_f, new_f)))

    orig_f = f
    period = None

    if isinstance(f, Relational):
        f = f.lhs - f.rhs

    f = simplify(f)

    if symbol not in f.free_symbols:
        return S.Zero

    if isinstance(f, TrigonometricFunction):
        try:
            period = f.period(symbol)
        except NotImplementedError:
            pass

    if isinstance(f, Abs):
        arg = f.args[0]
        if isinstance(arg, (sec, csc, cos)):
            # all but tan and cot might have a
            # a period that is half as large
            # so recast as sin
            arg = sin(arg.args[0])
        period = periodicity(arg, symbol)
        if period is not None and isinstance(arg, sin):
            # the argument of Abs was a trigonometric other than
            # cot or tan; test to see if the half-period
            # is valid. Abs(arg) has behaviour equivalent to
            # orig_f, so use that for test:
            orig_f = Abs(arg)
            try:
                return _check(orig_f, period/2)
            except NotImplementedError as err:
                if check:
                    raise NotImplementedError(err)
            # else let new orig_f and period be
            # checked below

    if isinstance(f, exp) or (f.is_Pow and f.base == S.Exp1):
        f = Pow(S.Exp1, expand_mul(f.exp))
        if im(f) != 0:
            period_real = periodicity(re(f), symbol)
            period_imag = periodicity(im(f), symbol)
            if period_real is not None and period_imag is not None:
                period = lcim([period_real, period_imag])

    if f.is_Pow and f.base != S.Exp1:
        base, expo = f.args
        base_has_sym = base.has(symbol)
        expo_has_sym = expo.has(symbol)

        if base_has_sym and not expo_has_sym:
            period = periodicity(base, symbol)

        elif expo_has_sym and not base_has_sym:
            period = periodicity(expo, symbol)

        else:
            period = _periodicity(f.args, symbol)

    elif f.is_Mul:
        coeff, g = f.as_independent(symbol, as_Add=False)
        if isinstance(g, TrigonometricFunction) or coeff is not S.One:
            period = periodicity(g, symbol)

        else:
            period = _periodicity(g.args, symbol)

    elif f.is_Add:
        k, g = f.as_independent(symbol)
        if k is not S.Zero:
            return periodicity(g, symbol)

        period = _periodicity(g.args, symbol)

    elif isinstance(f, Mod):
        a, n = f.args

        if a == symbol:
            period = n
        elif isinstance(a, TrigonometricFunction):
            period = periodicity(a, symbol)
        #check if 'f' is linear in 'symbol'
        elif (a.is_polynomial(symbol) and degree(a, symbol) == 1 and
            symbol not in n.free_symbols):
                period = Abs(n / a.diff(symbol))

    elif period is None:
        from sympy.solvers.decompogen import compogen
        g_s = decompogen(f, symbol)
        num_of_gs = len(g_s)
        if num_of_gs > 1:
            for index, g in enumerate(reversed(g_s)):
                start_index = num_of_gs - 1 - index
                g = compogen(g_s[start_index:], symbol)
                if g != orig_f and g != f: # Fix for issue 12620
                    period = periodicity(g, symbol)
                    if period is not None:
                        break

    if period is not None:
        if check:
            return _check(orig_f, period)
        return period

    return None


def _periodicity(args, symbol):
    """
    Helper for `periodicity` to find the period of a list of simpler
    functions.
    It uses the `lcim` method to find the least common period of
    all the functions.

    Parameters
    ==========

    args : Tuple of Symbol
        All the symbols present in a function.

    symbol : Symbol
        The symbol over which the function is to be evaluated.

    Returns
    =======

    period
        The least common period of the function for all the symbols
        of the function.
        None if for at least one of the symbols the function is aperiodic

    """
    periods = []
    for f in args:
        period = periodicity(f, symbol)
        if period is None:
            return None

        if period is not S.Zero:
            periods.append(period)

    if len(periods) > 1:
        return lcim(periods)

    if periods:
        return periods[0]


def lcim(numbers):
    """Returns the least common integral multiple of a list of numbers.

    The numbers can be rational or irrational or a mixture of both.
    `None` is returned for incommensurable numbers.

    Parameters
    ==========

    numbers : list
        Numbers (rational and/or irrational) for which lcim is to be found.

    Returns
    =======

    number
        lcim if it exists, otherwise `None` for incommensurable numbers.

    Examples
    ========

    >>> from sympy import S, pi
    >>> from sympy.calculus.util import lcim
    >>> lcim([S(1)/2, S(3)/4, S(5)/6])
    15/2
    >>> lcim([2*pi, 3*pi, pi, pi/2])
    6*pi
    >>> lcim([S(1), 2*pi])
    """
    result = None
    if all(num.is_irrational for num in numbers):
        factorized_nums = list(map(lambda num: num.factor(), numbers))
        factors_num = list(
            map(lambda num: num.as_coeff_Mul(),
                factorized_nums))
        term = factors_num[0][1]
        if all(factor == term for coeff, factor in factors_num):
            common_term = term
            coeffs = [coeff for coeff, factor in factors_num]
            result = lcm_list(coeffs) * common_term

    elif all(num.is_rational for num in numbers):
        result = lcm_list(numbers)

    else:
        pass

    return result

def is_convex(f, *syms, domain=S.Reals):
    """Determines the  convexity of the function passed in the argument.

    Parameters
    ==========

    f : Expr
        The concerned function.
    syms : Tuple of symbols
        The variables with respect to which the convexity is to be determined.
    domain : Interval, optional
        The domain over which the convexity of the function has to be checked.
        If unspecified, S.Reals will be the default domain.

    Returns
    =======

    Boolean
        The method returns `True` if the function is convex otherwise it
        returns `False`.

    Raises
    ======

    NotImplementedError
        The check for the convexity of multivariate functions is not implemented yet.

    Notes
    =====

    To determine concavity of a function pass `-f` as the concerned function.
    To determine logarithmic convexity of a function pass log(f) as
    concerned function.
    To determine logartihmic concavity of a function pass -log(f) as
    concerned function.

    Currently, convexity check of multivariate functions is not handled.

    Examples
    ========

    >>> from sympy import symbols, exp, oo, Interval
    >>> from sympy.calculus.util import is_convex
    >>> x = symbols('x')
    >>> is_convex(exp(x), x)
    True
    >>> is_convex(x**3, x, domain = Interval(-1, oo))
    False

    References
    ==========

    .. [1] https://en.wikipedia.org/wiki/Convex_function
    .. [2] http://www.ifp.illinois.edu/~angelia/L3_convfunc.pdf
    .. [3] https://en.wikipedia.org/wiki/Logarithmically_convex_function
    .. [4] https://en.wikipedia.org/wiki/Logarithmically_concave_function
    .. [5] https://en.wikipedia.org/wiki/Concave_function

    """

    if len(syms) > 1:
        raise NotImplementedError(
            "The check for the convexity of multivariate functions is not implemented yet.")

    f = _sympify(f)
    var = syms[0]
    condition = f.diff(var, 2) < 0
    if solve_univariate_inequality(condition, var, False, domain):
        return False
    return True


def stationary_points(f, symbol, domain=S.Reals):
    """
    Returns the stationary points of a function (where derivative of the
    function is 0) in the given domain.

    Parameters
    ==========

    f : Expr
        The concerned function.
    symbol : Symbol
        The variable for which the stationary points are to be determined.
    domain : Interval
        The domain over which the stationary points have to be checked.
        If unspecified, S.Reals will be the default domain.

    Returns
    =======

    Set
        A set of stationary points for the function. If there are no
        stationary point, an EmptySet is returned.

    Examples
    ========

    >>> from sympy import Symbol, S, sin, pi, pprint, stationary_points
    >>> from sympy.sets import Interval
    >>> x = Symbol('x')

    >>> stationary_points(1/x, x, S.Reals)
    EmptySet

    >>> pprint(stationary_points(sin(x), x), use_unicode=False)
              pi                              3*pi
    {2*n*pi + -- | n in Integers} U {2*n*pi + ---- | n in Integers}
              2                                2

    >>> stationary_points(sin(x),x, Interval(0, 4*pi))
    FiniteSet(pi/2, 3*pi/2, 5*pi/2, 7*pi/2)

    """
    from sympy import solveset, diff

    if isinstance(domain, EmptySet):
        return S.EmptySet

    domain = continuous_domain(f, symbol, domain)
    set = solveset(diff(f, symbol), symbol, domain)

    return set


def maximum(f, symbol, domain=S.Reals):
    """
    Returns the maximum value of a function in the given domain.

    Parameters
    ==========

    f : Expr
        The concerned function.
    symbol : Symbol
        The variable for maximum value needs to be determined.
    domain : Interval
        The domain over which the maximum have to be checked.
        If unspecified, then Global maximum is returned.

    Returns
    =======

    number
        Maximum value of the function in given domain.

    Examples
    ========

    >>> from sympy import Symbol, S, sin, cos, pi, maximum
    >>> from sympy.sets import Interval
    >>> x = Symbol('x')

    >>> f = -x**2 + 2*x + 5
    >>> maximum(f, x, S.Reals)
    6

    >>> maximum(sin(x), x, Interval(-pi, pi/4))
    sqrt(2)/2

    >>> maximum(sin(x)*cos(x), x)
    1/2

    """
    from sympy import Symbol

    if isinstance(symbol, Symbol):
        if isinstance(domain, EmptySet):
            raise ValueError("Maximum value not defined for empty domain.")

        return function_range(f, symbol, domain).sup
    else:
        raise ValueError("%s is not a valid symbol." % symbol)


def minimum(f, symbol, domain=S.Reals):
    """
    Returns the minimum value of a function in the given domain.

    Parameters
    ==========

    f : Expr
        The concerned function.
    symbol : Symbol
        The variable for minimum value needs to be determined.
    domain : Interval
        The domain over which the minimum have to be checked.
        If unspecified, then Global minimum is returned.

    Returns
    =======

    number
        Minimum value of the function in the given domain.

    Examples
    ========

    >>> from sympy import Symbol, S, sin, cos, minimum
    >>> from sympy.sets import Interval
    >>> x = Symbol('x')

    >>> f = x**2 + 2*x + 5
    >>> minimum(f, x, S.Reals)
    4

    >>> minimum(sin(x), x, Interval(2, 3))
    sin(3)

    >>> minimum(sin(x)*cos(x), x)
    -1/2

    """
    from sympy import Symbol

    if isinstance(symbol, Symbol):
        if isinstance(domain, EmptySet):
            raise ValueError("Minimum value not defined for empty domain.")

        return function_range(f, symbol, domain).inf
    else:
        raise ValueError("%s is not a valid symbol." % symbol)


class AccumulationBounds(AtomicExpr):
    r"""
    # Note AccumulationBounds has an alias: AccumBounds

    AccumulationBounds represent an interval `[a, b]`, which is always closed
    at the ends. Here `a` and `b` can be any value from extended real numbers.

    The intended meaning of AccummulationBounds is to give an approximate
    location of the accumulation points of a real function at a limit point.

    Let `a` and `b` be reals such that a <= b.

    `\left\langle a, b\right\rangle = \{x \in \mathbb{R} \mid a \le x \le b\}`

    `\left\langle -\infty, b\right\rangle = \{x \in \mathbb{R} \mid x \le b\} \cup \{-\infty, \infty\}`

    `\left\langle a, \infty \right\rangle = \{x \in \mathbb{R} \mid a \le x\} \cup \{-\infty, \infty\}`

    `\left\langle -\infty, \infty \right\rangle = \mathbb{R} \cup \{-\infty, \infty\}`

    `oo` and `-oo` are added to the second and third definition respectively,
    since if either `-oo` or `oo` is an argument, then the other one should
    be included (though not as an end point). This is forced, since we have,
    for example, `1/AccumBounds(0, 1) = AccumBounds(1, oo)`, and the limit at
    `0` is not one-sided. As x tends to `0-`, then `1/x -> -oo`, so `-oo`
    should be interpreted as belonging to `AccumBounds(1, oo)` though it need
    not appear explicitly.

    In many cases it suffices to know that the limit set is bounded.
    However, in some other cases more exact information could be useful.
    For example, all accumulation values of cos(x) + 1 are non-negative.
    (AccumBounds(-1, 1) + 1 = AccumBounds(0, 2))

    A AccumulationBounds object is defined to be real AccumulationBounds,
    if its end points are finite reals.

    Let `X`, `Y` be real AccumulationBounds, then their sum, difference,
    product are defined to be the following sets:

    `X + Y = \{ x+y \mid x \in X \cap y \in Y\}`

    `X - Y = \{ x-y \mid x \in X \cap y \in Y\}`

    `X * Y = \{ x*y \mid x \in X \cap y \in Y\}`

    There is, however, no consensus on Interval division.

    `X / Y = \{ z \mid \exists x \in X, y \in Y \mid y \neq 0, z = x/y\}`

    Note: According to this definition the quotient of two AccumulationBounds
    may not be a AccumulationBounds object but rather a union of
    AccumulationBounds.

    Note
    ====

    The main focus in the interval arithmetic is on the simplest way to
    calculate upper and lower endpoints for the range of values of a
    function in one or more variables. These barriers are not necessarily
    the supremum or infimum, since the precise calculation of those values
    can be difficult or impossible.

    Examples
    ========

    >>> from sympy import AccumBounds, sin, exp, log, pi, E, S, oo
    >>> from sympy.abc import x

    >>> AccumBounds(0, 1) + AccumBounds(1, 2)
    AccumBounds(1, 3)

    >>> AccumBounds(0, 1) - AccumBounds(0, 2)
    AccumBounds(-2, 1)

    >>> AccumBounds(-2, 3)*AccumBounds(-1, 1)
    AccumBounds(-3, 3)

    >>> AccumBounds(1, 2)*AccumBounds(3, 5)
    AccumBounds(3, 10)

    The exponentiation of AccumulationBounds is defined
    as follows:

    If 0 does not belong to `X` or `n > 0` then

    `X^n = \{ x^n \mid x \in X\}`

    otherwise

    `X^n = \{ x^n \mid x \neq 0, x \in X\} \cup \{-\infty, \infty\}`

    Here for fractional `n`, the part of `X` resulting in a complex
    AccumulationBounds object is neglected.

    >>> AccumBounds(-1, 4)**(S(1)/2)
    AccumBounds(0, 2)

    >>> AccumBounds(1, 2)**2
    AccumBounds(1, 4)

    >>> AccumBounds(-1, oo)**(-1)
    AccumBounds(-oo, oo)

    Note: `<a, b>^2` is not same as `<a, b>*<a, b>`

    >>> AccumBounds(-1, 1)**2
    AccumBounds(0, 1)

    >>> AccumBounds(1, 3) < 4
    True

    >>> AccumBounds(1, 3) < -1
    False

    Some elementary functions can also take AccumulationBounds as input.
    A function `f` evaluated for some real AccumulationBounds `<a, b>`
    is defined as `f(\left\langle a, b\right\rangle) = \{ f(x) \mid a \le x \le b \}`

    >>> sin(AccumBounds(pi/6, pi/3))
    AccumBounds(1/2, sqrt(3)/2)

    >>> exp(AccumBounds(0, 1))
    AccumBounds(1, E)

    >>> log(AccumBounds(1, E))
    AccumBounds(0, 1)

    Some symbol in an expression can be substituted for a AccumulationBounds
    object. But it doesn't necessarily evaluate the AccumulationBounds for
    that expression.

    Same expression can be evaluated to different values depending upon
    the form it is used for substitution. For example:

    >>> (x**2 + 2*x + 1).subs(x, AccumBounds(-1, 1))
    AccumBounds(-1, 4)

    >>> ((x + 1)**2).subs(x, AccumBounds(-1, 1))
    AccumBounds(0, 4)

    References
    ==========

    .. [1] https://en.wikipedia.org/wiki/Interval_arithmetic

    .. [2] http://fab.cba.mit.edu/classes/S62.12/docs/Hickey_interval.pdf

    Notes
    =====

    Do not use ``AccumulationBounds`` for floating point interval arithmetic
    calculations, use ``mpmath.iv`` instead.
    """

    is_extended_real = True

    def __new__(cls, min, max):

        min = _sympify(min)
        max = _sympify(max)

        # Only allow real intervals (use symbols with 'is_extended_real=True').
        if not min.is_extended_real or not max.is_extended_real:
            raise ValueError("Only real AccumulationBounds are supported")

        # Make sure that the created AccumBounds object will be valid.
        if max.is_comparable and min.is_comparable:
            if max < min:
                raise ValueError(
                    "Lower limit should be smaller than upper limit")

        if max == min:
            return max

        return Basic.__new__(cls, min, max)

    # setting the operation priority
    _op_priority = 11.0

    def _eval_is_real(self):
        if self.min.is_real and self.max.is_real:
            return True

    @property
    def min(self):
        """
        Returns the minimum possible value attained by AccumulationBounds
        object.

        Examples
        ========

        >>> from sympy import AccumBounds
        >>> AccumBounds(1, 3).min
        1

        """
        return self.args[0]

    @property
    def max(self):
        """
        Returns the maximum possible value attained by AccumulationBounds
        object.

        Examples
        ========

        >>> from sympy import AccumBounds
        >>> AccumBounds(1, 3).max
        3

        """
        return self.args[1]

    @property
    def delta(self):
        """
        Returns the difference of maximum possible value attained by
        AccumulationBounds object and minimum possible value attained
        by AccumulationBounds object.

        Examples
        ========

        >>> from sympy import AccumBounds
        >>> AccumBounds(1, 3).delta
        2

        """
        return self.max - self.min

    @property
    def mid(self):
        """
        Returns the mean of maximum possible value attained by
        AccumulationBounds object and minimum possible value
        attained by AccumulationBounds object.

        Examples
        ========

        >>> from sympy import AccumBounds
        >>> AccumBounds(1, 3).mid
        2

        """
        return (self.min + self.max) / 2

    @_sympifyit('other', NotImplemented)
    def _eval_power(self, other):
        return self.__pow__(other)

    @_sympifyit('other', NotImplemented)
    def __add__(self, other):
        if isinstance(other, Expr):
            if isinstance(other, AccumBounds):
                return AccumBounds(
                    Add(self.min, other.min),
                    Add(self.max, other.max))
            if other is S.Infinity and self.min is S.NegativeInfinity or \
                    other is S.NegativeInfinity and self.max is S.Infinity:
                return AccumBounds(-oo, oo)
            elif other.is_extended_real:
                if self.min is S.NegativeInfinity and self.max is S.Infinity:
                    return AccumBounds(-oo, oo)
                elif self.min is S.NegativeInfinity:
                    return AccumBounds(-oo, self.max + other)
                elif self.max is S.Infinity:
                    return AccumBounds(self.min + other, oo)
                else:
                    return AccumBounds(Add(self.min, other), Add(self.max, other))
            return Add(self, other, evaluate=False)
        return NotImplemented

    __radd__ = __add__

    def __neg__(self):
        return AccumBounds(-self.max, -self.min)

    @_sympifyit('other', NotImplemented)
    def __sub__(self, other):
        if isinstance(other, Expr):
            if isinstance(other, AccumBounds):
                return AccumBounds(
                    Add(self.min, -other.max),
                    Add(self.max, -other.min))
            if other is S.NegativeInfinity and self.min is S.NegativeInfinity or \
                    other is S.Infinity and self.max is S.Infinity:
                return AccumBounds(-oo, oo)
            elif other.is_extended_real:
                if self.min is S.NegativeInfinity and self.max is S.Infinity:
                    return AccumBounds(-oo, oo)
                elif self.min is S.NegativeInfinity:
                    return AccumBounds(-oo, self.max - other)
                elif self.max is S.Infinity:
                    return AccumBounds(self.min - other, oo)
                else:
                    return AccumBounds(
                        Add(self.min, -other),
                        Add(self.max, -other))
            return Add(self, -other, evaluate=False)
        return NotImplemented

    @_sympifyit('other', NotImplemented)
    def __rsub__(self, other):
        return self.__neg__() + other

    @_sympifyit('other', NotImplemented)
    def __mul__(self, other):
        if isinstance(other, Expr):
            if isinstance(other, AccumBounds):
                return AccumBounds(Min(Mul(self.min, other.min),
                                       Mul(self.min, other.max),
                                       Mul(self.max, other.min),
                                       Mul(self.max, other.max)),
                                   Max(Mul(self.min, other.min),
                                       Mul(self.min, other.max),
                                       Mul(self.max, other.min),
                                       Mul(self.max, other.max)))
            if other is S.Infinity:
                if self.min.is_zero:
                    return AccumBounds(0, oo)
                if self.max.is_zero:
                    return AccumBounds(-oo, 0)
            if other is S.NegativeInfinity:
                if self.min.is_zero:
                    return AccumBounds(-oo, 0)
                if self.max.is_zero:
                    return AccumBounds(0, oo)
            if other.is_extended_real:
                if other.is_zero:
                    if self == AccumBounds(-oo, oo):
                        return AccumBounds(-oo, oo)
                    if self.max is S.Infinity:
                        return AccumBounds(0, oo)
                    if self.min is S.NegativeInfinity:
                        return AccumBounds(-oo, 0)
                    return S.Zero
                if other.is_extended_positive:
                    return AccumBounds(
                        Mul(self.min, other),
                        Mul(self.max, other))
                elif other.is_extended_negative:
                    return AccumBounds(
                        Mul(self.max, other),
                        Mul(self.min, other))
            if isinstance(other, Order):
                return other
            return Mul(self, other, evaluate=False)
        return NotImplemented

    __rmul__ = __mul__

    @_sympifyit('other', NotImplemented)
    def __truediv__(self, other):
        if isinstance(other, Expr):
            if isinstance(other, AccumBounds):
                if other.min.is_positive or other.max.is_negative:
                    return self * AccumBounds(1/other.max, 1/other.min)

                if (self.min.is_extended_nonpositive and self.max.is_extended_nonnegative and
                    other.min.is_extended_nonpositive and other.max.is_extended_nonnegative):
                    if self.min.is_zero and other.min.is_zero:
                        return AccumBounds(0, oo)
                    if self.max.is_zero and other.min.is_zero:
                        return AccumBounds(-oo, 0)
                    return AccumBounds(-oo, oo)

                if self.max.is_extended_negative:
                    if other.min.is_extended_negative:
                        if other.max.is_zero:
                            return AccumBounds(self.max / other.min, oo)
                        if other.max.is_extended_positive:
                            # the actual answer is a Union of AccumBounds,
                            # Union(AccumBounds(-oo, self.max/other.max),
                            #       AccumBounds(self.max/other.min, oo))
                            return AccumBounds(-oo, oo)

                    if other.min.is_zero and other.max.is_extended_positive:
                        return AccumBounds(-oo, self.max / other.max)

                if self.min.is_extended_positive:
                    if other.min.is_extended_negative:
                        if other.max.is_zero:
                            return AccumBounds(-oo, self.min / other.min)
                        if other.max.is_extended_positive:
                            # the actual answer is a Union of AccumBounds,
                            # Union(AccumBounds(-oo, self.min/other.min),
                            #       AccumBounds(self.min/other.max, oo))
                            return AccumBounds(-oo, oo)

                    if other.min.is_zero and other.max.is_extended_positive:
                        return AccumBounds(self.min / other.max, oo)

            elif other.is_extended_real:
                if other is S.Infinity or other is S.NegativeInfinity:
                    if self == AccumBounds(-oo, oo):
                        return AccumBounds(-oo, oo)
                    if self.max is S.Infinity:
                        return AccumBounds(Min(0, other), Max(0, other))
                    if self.min is S.NegativeInfinity:
                        return AccumBounds(Min(0, -other), Max(0, -other))
                if other.is_extended_positive:
                    return AccumBounds(self.min / other, self.max / other)
                elif other.is_extended_negative:
                    return AccumBounds(self.max / other, self.min / other)
            if (1 / other) is S.ComplexInfinity:
                return Mul(self, 1 / other, evaluate=False)
            else:
                return Mul(self, 1 / other)

        return NotImplemented

    @_sympifyit('other', NotImplemented)
    def __rtruediv__(self, other):
        if isinstance(other, Expr):
            if other.is_extended_real:
                if other.is_zero:
                    return S.Zero
                if (self.min.is_extended_nonpositive and self.max.is_extended_nonnegative):
                    if self.min.is_zero:
                        if other.is_extended_positive:
                            return AccumBounds(Mul(other, 1 / self.max), oo)
                        if other.is_extended_negative:
                            return AccumBounds(-oo, Mul(other, 1 / self.max))
                    if self.max.is_zero:
                        if other.is_extended_positive:
                            return AccumBounds(-oo, Mul(other, 1 / self.min))
                        if other.is_extended_negative:
                            return AccumBounds(Mul(other, 1 / self.min), oo)
                    return AccumBounds(-oo, oo)
                else:
                    return AccumBounds(Min(other / self.min, other / self.max),
                                       Max(other / self.min, other / self.max))
            return Mul(other, 1 / self, evaluate=False)
        else:
            return NotImplemented

    @_sympifyit('other', NotImplemented)
    def __pow__(self, other):
        from sympy.functions.elementary.miscellaneous import real_root
        if isinstance(other, Expr):
            if other is S.Infinity:
                if self.min.is_extended_nonnegative:
                    if self.max < 1:
                        return S.Zero
                    if self.min > 1:
                        return S.Infinity
                    return AccumBounds(0, oo)
                elif self.max.is_extended_negative:
                    if self.min > -1:
                        return S.Zero
                    if self.max < -1:
                        return FiniteSet(-oo, oo)
                    return AccumBounds(-oo, oo)
                else:
                    if self.min > -1:
                        if self.max < 1:
                            return S.Zero
                        return AccumBounds(0, oo)
                    return AccumBounds(-oo, oo)

            if other is S.NegativeInfinity:
                return (1 / self)**oo

            if other.is_extended_real and other.is_number:
                if other.is_zero:
                    return S.One

                if other.is_Integer:
                    if self.min.is_extended_positive:
                        return AccumBounds(
                            Min(self.min ** other, self.max ** other),
                            Max(self.min ** other, self.max ** other))
                    elif self.max.is_extended_negative:
                        return AccumBounds(
                            Min(self.max ** other, self.min ** other),
                            Max(self.max ** other, self.min ** other))

                    if other % 2 == 0:
                        if other.is_extended_negative:
                            if self.min.is_zero:
                                return AccumBounds(self.max**other, oo)
                            if self.max.is_zero:
                                return AccumBounds(self.min**other, oo)
                            return AccumBounds(0, oo)
                        return AccumBounds(
                            S.Zero, Max(self.min**other, self.max**other))
                    else:
                        if other.is_extended_negative:
                            if self.min.is_zero:
                                return AccumBounds(self.max**other, oo)
                            if self.max.is_zero:
                                return AccumBounds(-oo, self.min**other)
                            return AccumBounds(-oo, oo)
                        return AccumBounds(self.min**other, self.max**other)

                num, den = other.as_numer_denom()
                if num == S.One:
                    if den % 2 == 0:
                        if S.Zero in self:
                            if self.min.is_extended_negative:
                                return AccumBounds(0, real_root(self.max, den))
                    return AccumBounds(real_root(self.min, den),
                                       real_root(self.max, den))
                if den!=1:
                    num_pow = self**num
                    return num_pow**(1 / den)
            return AccumBounds(-oo, oo)

        return NotImplemented

    def __abs__(self):
        if self.max.is_extended_negative:
            return self.__neg__()
        elif self.min.is_extended_negative:
            return AccumBounds(S.Zero, Max(abs(self.min), self.max))
        else:
            return self


    def __contains__(self, other):
        """
        Returns True if other is contained in self, where other
        belongs to extended real numbers, False if not contained,
        otherwise TypeError is raised.

        Examples
        ========

        >>> from sympy import AccumBounds, oo
        >>> 1 in AccumBounds(-1, 3)
        True

        -oo and oo go together as limits (in AccumulationBounds).

        >>> -oo in AccumBounds(1, oo)
        True

        >>> oo in AccumBounds(-oo, 0)
        True

        """
        other = _sympify(other)

        if other is S.Infinity or other is S.NegativeInfinity:
            if self.min is S.NegativeInfinity or self.max is S.Infinity:
                return True
            return False

        rv = And(self.min <= other, self.max >= other)
        if rv not in (True, False):
            raise TypeError("input failed to evaluate")
        return rv

    def intersection(self, other):
        """
        Returns the intersection of 'self' and 'other'.
        Here other can be an instance of FiniteSet or AccumulationBounds.

        Parameters
        ==========

        other: AccumulationBounds
             Another AccumulationBounds object with which the intersection
             has to be computed.

        Returns
        =======

        AccumulationBounds
            Intersection of 'self' and 'other'.

        Examples
        ========

        >>> from sympy import AccumBounds, FiniteSet
        >>> AccumBounds(1, 3).intersection(AccumBounds(2, 4))
        AccumBounds(2, 3)

        >>> AccumBounds(1, 3).intersection(AccumBounds(4, 6))
        EmptySet

        >>> AccumBounds(1, 4).intersection(FiniteSet(1, 2, 5))
        FiniteSet(1, 2)

        """
        if not isinstance(other, (AccumBounds, FiniteSet)):
            raise TypeError(
                "Input must be AccumulationBounds or FiniteSet object")

        if isinstance(other, FiniteSet):
            fin_set = S.EmptySet
            for i in other:
                if i in self:
                    fin_set = fin_set + FiniteSet(i)
            return fin_set

        if self.max < other.min or self.min > other.max:
            return S.EmptySet

        if self.min <= other.min:
            if self.max <= other.max:
                return AccumBounds(other.min, self.max)
            if self.max > other.max:
                return other

        if other.min <= self.min:
            if other.max < self.max:
                return AccumBounds(self.min, other.max)
            if other.max > self.max:
                return self

    def union(self, other):
        # TODO : Devise a better method for Union of AccumBounds
        # this method is not actually correct and
        # can be made better
        if not isinstance(other, AccumBounds):
            raise TypeError(
                "Input must be AccumulationBounds or FiniteSet object")

        if self.min <= other.min and self.max >= other.min:
            return AccumBounds(self.min, Max(self.max, other.max))

        if other.min <= self.min and other.max >= self.min:
            return AccumBounds(other.min, Max(self.max, other.max))


@dispatch(AccumulationBounds, AccumulationBounds) # type: ignore # noqa:F811
def _eval_is_le(lhs, rhs): # noqa:F811
    if is_le(lhs.max, rhs.min):
        return True
    if is_gt(lhs.min, rhs.max):
        return False


@dispatch(AccumulationBounds, Basic) # type: ignore # noqa:F811
def _eval_is_le(lhs, rhs): # noqa: F811

    """
    Returns True if range of values attained by `self` AccumulationBounds
    object is greater than the range of values attained by `other`,
    where other may be any value of type AccumulationBounds object or
    extended real number value, False if `other` satisfies
    the same property, else an unevaluated Relational.

    Examples
    ========

    >>> from sympy import AccumBounds, oo
    >>> AccumBounds(1, 3) > AccumBounds(4, oo)
    False
    >>> AccumBounds(1, 4) > AccumBounds(3, 4)
    AccumBounds(1, 4) > AccumBounds(3, 4)
    >>> AccumBounds(1, oo) > -1
    True

    """
    if not rhs.is_extended_real:
            raise TypeError(
                "Invalid comparison of %s %s" %
                (type(rhs), rhs))
    elif rhs.is_comparable:
        if is_le(lhs.max, rhs):
            return True
        if is_gt(lhs.min, rhs):
            return False

@dispatch(AccumulationBounds, AccumulationBounds)
def _eval_is_ge(lhs, rhs): # noqa:F811
    if is_ge(lhs.min, rhs.max):
        return True
    if is_lt(lhs.max, rhs.min):
        return False

@dispatch(AccumulationBounds, Expr)  # type:ignore
def _eval_is_ge(lhs, rhs): # noqa: F811
    """
    Returns True if range of values attained by `lhs` AccumulationBounds
    object is less that the range of values attained by `rhs`, where
    other may be any value of type AccumulationBounds object or extended
    real number value, False if `rhs` satisfies the same
    property, else an unevaluated Relational.

    Examples
    ========

    >>> from sympy import AccumBounds, oo
    >>> AccumBounds(1, 3) >= AccumBounds(4, oo)
    False
    >>> AccumBounds(1, 4) >= AccumBounds(3, 4)
    AccumBounds(1, 4) >= AccumBounds(3, 4)
    >>> AccumBounds(1, oo) >= 1
    True
    """

    if not rhs.is_extended_real:
        raise TypeError(
            "Invalid comparison of %s %s" %
            (type(rhs), rhs))
    elif rhs.is_comparable:
        if is_ge(lhs.min, rhs):
            return True
        if is_lt(lhs.max, rhs):
            return False


@dispatch(Expr, AccumulationBounds)  # type:ignore
def _eval_is_ge(lhs, rhs): # noqa:F811
    if not lhs.is_extended_real:
        raise TypeError(
            "Invalid comparison of %s %s" %
            (type(lhs), lhs))
    elif lhs.is_comparable:
        if is_le(rhs.max, lhs):
            return True
        if is_gt(rhs.min, lhs):
            return False


@dispatch(AccumulationBounds, AccumulationBounds)  # type:ignore
def _eval_is_ge(lhs, rhs): # noqa:F811
    if is_ge(lhs.min, rhs.max):
        return True
    if is_lt(lhs.max, rhs.min):
        return False

# setting an alias for AccumulationBounds
AccumBounds = AccumulationBounds
