text: """
  Other functions
  
  TESTS:
  
  Check that gamma function imports are deprecated (:trac:`24411`)::
  
      sage: from sage.functions.other import beta
      sage: beta(x, x)
      doctest:...: DeprecationWarning:
      Importing beta from here is deprecated. If you need to use it, please import it directly from sage.functions.gamma
      See http://trac.sagemath.org/24411 for details.
      beta(x, x)
  """
  from __future__ import print_function
  from six.moves import range
  from six import integer_types
  
  from sage.misc.lazy_import import lazy_import
  lazy_import('sage.functions.gamma',
              ('gamma', 'log_gamma', 'gamma_inc',
               'gamma_inc_lower', 'psi', 'beta'), deprecation=24411)
  
  from sage.symbolic.function import GinacFunction, BuiltinFunction
  from sage.symbolic.expression import Expression
  from sage.libs.pynac.pynac import (register_symbol, symbol_table, I)
  from sage.symbolic.all import SR
  from sage.rings.all import Integer, Rational, RealField, ZZ, ComplexField
  from sage.misc.latex import latex
  import math
  
  from sage.structure.element import coercion_model
  
  # avoid name conflicts with `parent` as a function parameter
  from sage.structure.all import parent as s_parent
  
  from sage.functions.trig import arctan2
  from sage.arith.all import binomial as arith_binomial
  
  one_half = SR.one() / SR(2)
  
  
  class Function_abs(GinacFunction):
      def __init__(self):
          r"""
          The absolute value function.
  
          EXAMPLES::
  
              sage: var('x y')
              (x, y)
              sage: abs(x)
              abs(x)
              sage: abs(x^2 + y^2)
              abs(x^2 + y^2)
              sage: abs(-2)
              2
              sage: sqrt(x^2)
              sqrt(x^2)
              sage: abs(sqrt(x))
              sqrt(abs(x))
              sage: complex(abs(3*I))
              (3+0j)
  
              sage: f = sage.functions.other.Function_abs()
              sage: latex(f)
              \mathrm{abs}
              sage: latex(abs(x))
              {\left| x \right|}
              sage: abs(x)._sympy_()
              Abs(x)
  
          Test pickling::
  
              sage: loads(dumps(abs(x)))
              abs(x)
  
          TESTS:
  
          Check that :trac:`12588` is fixed::
  
              sage: abs(pi*I)
              pi
              sage: abs(pi*I*catalan)
              catalan*pi
              sage: abs(pi*catalan*x)
              catalan*pi*abs(x)
              sage: abs(pi*I*catalan*x)
              catalan*pi*abs(x)
              sage: abs(1.0j*pi)
              1.00000000000000*pi
              sage: abs(I*x)
              abs(x)
              sage: abs(I*pi)
              pi
              sage: abs(I*log(2))
              log(2)
              sage: abs(I*e^5)
              e^5
              sage: abs(log(1/2))
              -log(1/2)
              sage: abs(log(3/2))
              log(3/2)
              sage: abs(log(1/2)*log(1/3))
              log(1/2)*log(1/3)
              sage: abs(log(1/2)*log(1/3)*log(1/4))
              -log(1/2)*log(1/3)*log(1/4)
              sage: abs(log(1/2)*log(1/3)*log(1/4)*i)
              -log(1/2)*log(1/3)*log(1/4)
              sage: abs(log(x))
              abs(log(x))
              sage: abs(zeta(I))
              abs(zeta(I))
              sage: abs(e^2*x)
              abs(x)*e^2
              sage: abs((pi+e)*x)
              (pi + e)*abs(x)
  
              sage: fricas(abs(x)).sage().derivative()  # optional - fricas
              1/2*(x + conjugate(x))/abs(x)
          """
          GinacFunction.__init__(self, "abs", latex_name=r"\mathrm{abs}",
                                 conversions=dict(sympy='Abs',
                                                  mathematica='Abs',
                                                  giac='abs',
                                                  fricas='abs'))
  
  abs = abs_symbolic = Function_abs()
  
  
  def _eval_floor_ceil(self, x, method, bits=0, **kwds):
      """
      Helper function to compute ``floor(x)`` or ``ceil(x)``.
  
      INPUT:
  
      - ``x`` -- a number
  
      - ``method`` -- should be either ``"floor"`` or ``"ceil"``
  
      - ``bits`` -- how many bits to use before giving up
  
      See :class:`Function_floor` and :class:`Function_ceil` for examples
      and tests.
  
      TESTS::
  
          sage: numbers = [SR(10^100 + exp(-100)), SR(10^100 - exp(-100)), SR(10^100)]
          sage: numbers += [-n for n in numbers]
          sage: for n in numbers:
          ....:     f = floor(n)
          ....:     c = ceil(n)
          ....:     if f == c:
          ....:         assert n in ZZ
          ....:     else:
          ....:         assert f + 1 == c
  
      A test from :trac:`12121`::
  
          sage: e1 = pi - continued_fraction(pi).convergent(2785)
          sage: e2 = e - continued_fraction(e).convergent(1500)
          sage: f = e1/e2
          sage: f = 1 / (f - continued_fraction(f).convergent(1000))
          sage: f = f - continued_fraction(f).convergent(1)
          sage: floor(f, bits=10000)
          -1
          sage: ceil(f, bits=10000)
          0
  
      These do not work but fail gracefully::
  
          sage: ceil(Infinity)
          Traceback (most recent call last):
          ...
          ValueError: Calling ceil() on infinity or NaN
          sage: ceil(NaN)
          Traceback (most recent call last):
          ...
          ValueError: Calling ceil() on infinity or NaN
      """
      # First, some obvious things...
      try:
          m = getattr(x, method)
      except AttributeError:
          pass
      else:
          return m()
  
      if isinstance(x, integer_types):
          return Integer(x)
      if isinstance(x, (float, complex)):
          m = getattr(math, method)
          return Integer(m(x))
      if type(x).__module__ == 'numpy':
          import numpy
          m = getattr(numpy, method)
          return m(x)
  
      # The strategy is to convert the number to an interval field and
      # hope that this interval will have a unique floor/ceiling.
      #
      # There are 2 reasons why this could fail:
      # (A) The expression is very complicated and we simply require
      #     more bits.
      # (B) The expression is a non-obvious exact integer. In this
      #     case, adding bits will not help since an interval around
      #     an integer will not have a unique floor/ceiling, no matter
      #     how many bits are used.
      #
      # The strategy is to first reduce the absolute diameter of the
      # interval until its size is at most 10^(-6). Then we check for
      # (B) by simplifying the expression.
      from sage.rings.all import RealIntervalField
  
      # Might it be needed to simplify x? This only applies for
      # elements of SR.
      need_to_simplify = (s_parent(x) is SR)
  
      # An integer which is close to x. We use this to increase precision
      # by subtracting this guess before converting to an interval field.
      # This mostly helps with the case that x is close to, but not equal
      # to, an exact integer.
      guess = Integer(0)
  
      # We do not use the target number of bits immediately, we just use
      # it as indication of when to stop.
      target_bits = bits
      bits = 32
      attempts = 5
      while attempts:
          attempts -= 1
          if not attempts and bits < target_bits:
              # Add one more attempt as long as the precision is less
              # than requested
              attempts = 1
  
          RIF = RealIntervalField(bits)
          if guess:
              y = x - guess
          else:
              y = x
          try:
              y_interval = RIF(y)
          except TypeError:
              # If we cannot compute a numerical enclosure, leave the
              # expression unevaluated.
              return BuiltinFunction.__call__(self, SR(x))
          diam = y_interval.absolute_diameter()
          if diam.is_infinity():
              # We have a very bad approximation => increase the number
              # of bits a lot
              bits *= 4
              continue
          fdiam = float(diam)
          if fdiam >= 1.0:
              # Increase number of bits to get to a diameter less than
              # 2^(-32), assuming that the diameter scales as 2^(-bits)
              bits += 32 + int(diam.log2())
              continue
  
          # Compute ceil/floor of both ends of the interval:
          # if these match, we are done!
          a = getattr(y_interval.lower(), method)()
          b = getattr(y_interval.upper(), method)()
          if a == b:
              return a + guess
  
          # Compute a better guess for the next attempt. Since diam < 1,
          # there is a unique integer in our interval. This integer equals
          # the ceil of the lower bound and the floor of the upper bound.
          if self is floor:
              guess += b
          else:
              assert self is ceil
              guess += a
  
          if need_to_simplify and fdiam <= 1e-6:
              x = x.full_simplify().canonicalize_radical()
              need_to_simplify = False
              continue
  
          bits *= 2
  
      raise ValueError("cannot compute {}({!r}) using {} bits of precision".format(method, x, RIF.precision()))
  
  
  class Function_ceil(BuiltinFunction):
      def __init__(self):
          r"""
          The ceiling function.
  
          The ceiling of `x` is computed in the following manner.
  
  
          #. The ``x.ceil()`` method is called and returned if it
             is there. If it is not, then Sage checks if `x` is one of
             Python's native numeric data types. If so, then it calls and
             returns ``Integer(math.ceil(x))``.
  
          #. Sage tries to convert `x` into a
             ``RealIntervalField`` with 53 bits of precision. Next,
             the ceilings of the endpoints are computed. If they are the same,
             then that value is returned. Otherwise, the precision of the
             ``RealIntervalField`` is increased until they do match
             up or it reaches ``bits`` of precision.
  
          #. If none of the above work, Sage returns a
             ``Expression`` object.
  
  
          EXAMPLES::
  
              sage: a = ceil(2/5 + x)
              sage: a
              ceil(x + 2/5)
              sage: a(x=4)
              5
              sage: a(x=4.0)
              5
              sage: ZZ(a(x=3))
              4
              sage: a = ceil(x^3 + x + 5/2); a
              ceil(x^3 + x + 5/2)
              sage: a.simplify()
              ceil(x^3 + x + 1/2) + 2
              sage: a(x=2)
              13
  
          ::
  
              sage: ceil(sin(8)/sin(2))
              2
  
          ::
  
              sage: ceil(5.4)
              6
              sage: type(ceil(5.4))
              <type 'sage.rings.integer.Integer'>
  
          ::
  
              sage: ceil(factorial(50)/exp(1))
              11188719610782480504630258070757734324011354208865721592720336801
              sage: ceil(SR(10^50 + 10^(-50)))
              100000000000000000000000000000000000000000000000001
              sage: ceil(SR(10^50 - 10^(-50)))
              100000000000000000000000000000000000000000000000000
  
          Small numbers which are extremely close to an integer are hard to
          deal with::
  
              sage: ceil((33^100 + 1)^(1/100))
              Traceback (most recent call last):
              ...
              ValueError: cannot compute ceil(...) using 256 bits of precision
  
          This can be fixed by giving a sufficiently large ``bits`` argument::
  
              sage: ceil((33^100 + 1)^(1/100), bits=500)
              Traceback (most recent call last):
              ...
              ValueError: cannot compute ceil(...) using 512 bits of precision
              sage: ceil((33^100 + 1)^(1/100), bits=1000)
              34
  
          ::
  
              sage: ceil(sec(e))
              -1
  
              sage: latex(ceil(x))
              \left \lceil x \right \rceil
              sage: ceil(x)._sympy_()
              ceiling(x)
  
          ::
  
              sage: import numpy
              sage: a = numpy.linspace(0,2,6)
              sage: ceil(a)
              array([0., 1., 1., 2., 2., 2.])
  
          Test pickling::
  
              sage: loads(dumps(ceil))
              ceil
          """
          BuiltinFunction.__init__(self, "ceil",
                                     conversions=dict(maxima='ceiling',
                                                      sympy='ceiling',
                                                      giac='ceil'))
  
      def _print_latex_(self, x):
          r"""
          EXAMPLES::
  
              sage: latex(ceil(x)) # indirect doctest
              \left \lceil x \right \rceil
          """
          return r"\left \lceil %s \right \rceil"%latex(x)
  
      #FIXME: this should be moved to _eval_
      def __call__(self, x, **kwds):
          """
          Allows an object of this class to behave like a function. If
          ``ceil`` is an instance of this class, we can do ``ceil(n)`` to get
          the ceiling of ``n``.
  
          TESTS::
  
              sage: ceil(SR(10^50 + 10^(-50)))
              100000000000000000000000000000000000000000000000001
              sage: ceil(SR(10^50 - 10^(-50)))
              100000000000000000000000000000000000000000000000000
              sage: ceil(int(10^50))
              100000000000000000000000000000000000000000000000000
              sage: ceil((1725033*pi - 5419351)/(25510582*pi - 80143857))
              -2
          """
          return _eval_floor_ceil(self, x, "ceil", **kwds)
  
      def _eval_(self, x):
          """
          EXAMPLES::
  
              sage: ceil(x).subs(x==7.5)
              8
              sage: ceil(x)
              ceil(x)
  
              sage: var('x',domain='integer')
              x
              sage: ceil(x)
              x
              sage: ceil(factorial(x) + binomial(x^2, x))
              binomial(x^2, x) + factorial(x)
              sage: ceil(gamma(abs(2*x)+1) * real(x))
              x*gamma(2*abs(x) + 1)
              sage: forget()
          """
          try:
              if SR(x).variables() and x.is_integer():
                  return x
          except TypeError:
              pass
          try:
              return x.ceil()
          except AttributeError:
              if isinstance(x, integer_types):
                  return Integer(x)
              elif isinstance(x, (float, complex)):
                  return Integer(math.ceil(x))
          return None
  
  ceil = Function_ceil()
  
  
  class Function_floor(BuiltinFunction):
      def __init__(self):
          r"""
          The floor function.
  
          The floor of `x` is computed in the following manner.
  
  
          #. The ``x.floor()`` method is called and returned if
             it is there. If it is not, then Sage checks if `x` is one
             of Python's native numeric data types. If so, then it calls and
             returns ``Integer(math.floor(x))``.
  
          #. Sage tries to convert `x` into a
             ``RealIntervalField`` with 53 bits of precision. Next,
             the floors of the endpoints are computed. If they are the same,
             then that value is returned. Otherwise, the precision of the
             ``RealIntervalField`` is increased until they do match
             up or it reaches ``bits`` of precision.
  
          #. If none of the above work, Sage returns a
             symbolic ``Expression`` object.
  
  
          EXAMPLES::
  
              sage: floor(5.4)
              5
              sage: type(floor(5.4))
              <type 'sage.rings.integer.Integer'>
              sage: var('x')
              x
              sage: a = floor(5.4 + x); a
              floor(x + 5.40000000000000)
              sage: a.simplify()
              floor(x + 0.4000000000000004) + 5
              sage: a(x=2)
              7
  
          ::
  
              sage: floor(cos(8) / cos(2))
              0
              sage: floor(log(4) / log(2))
              2
              sage: a = floor(5.4 + x); a
              floor(x + 5.40000000000000)
              sage: a.subs(x==2)
              7
              sage: floor(log(2^(3/2)) / log(2) + 1/2)
              2
              sage: floor(log(2^(-3/2)) / log(2) + 1/2)
              -1
  
          ::
  
              sage: floor(factorial(50)/exp(1))
              11188719610782480504630258070757734324011354208865721592720336800
              sage: floor(SR(10^50 + 10^(-50)))
              100000000000000000000000000000000000000000000000000
              sage: floor(SR(10^50 - 10^(-50)))
              99999999999999999999999999999999999999999999999999
              sage: floor(int(10^50))
              100000000000000000000000000000000000000000000000000
  
          Small numbers which are extremely close to an integer are hard to
          deal with::
  
              sage: floor((33^100 + 1)^(1/100))
              Traceback (most recent call last):
              ...
              ValueError: cannot compute floor(...) using 256 bits of precision
  
          This can be fixed by giving a sufficiently large ``bits`` argument::
  
              sage: floor((33^100 + 1)^(1/100), bits=500)
              Traceback (most recent call last):
              ...
              ValueError: cannot compute floor(...) using 512 bits of precision
              sage: floor((33^100 + 1)^(1/100), bits=1000)
              33
  
          ::
  
              sage: import numpy
              sage: a = numpy.linspace(0,2,6)
              sage: floor(a)
              array([0., 0., 0., 1., 1., 2.])
              sage: floor(x)._sympy_()
              floor(x)
  
          Test pickling::
  
              sage: loads(dumps(floor))
              floor
          """
          BuiltinFunction.__init__(self, "floor",
                                   conversions=dict(sympy='floor', giac='floor'))
  
      def _print_latex_(self, x):
          r"""
          EXAMPLES::
  
              sage: latex(floor(x))
              \left \lfloor x \right \rfloor
          """
          return r"\left \lfloor %s \right \rfloor"%latex(x)
  
      #FIXME: this should be moved to _eval_
      def __call__(self, x, **kwds):
          """
          Allows an object of this class to behave like a function. If
          ``floor`` is an instance of this class, we can do ``floor(n)`` to
          obtain the floor of ``n``.
  
          TESTS::
  
              sage: floor(SR(10^50 + 10^(-50)))
              100000000000000000000000000000000000000000000000000
              sage: floor(SR(10^50 - 10^(-50)))
              99999999999999999999999999999999999999999999999999
              sage: floor(int(10^50))
              100000000000000000000000000000000000000000000000000
              sage: floor((1725033*pi - 5419351)/(25510582*pi - 80143857))
              -3
          """
          return _eval_floor_ceil(self, x, "floor", **kwds)
  
      def _eval_(self, x):
          """
          EXAMPLES::
  
              sage: floor(x).subs(x==7.5)
              7
              sage: floor(x)
              floor(x)
  
              sage: var('x',domain='integer')
              x
              sage: floor(x)
              x
              sage: floor(factorial(x) + binomial(x^2, x))
              binomial(x^2, x) + factorial(x)
              sage: floor(gamma(abs(2*x)+1) * real(x))
              x*gamma(2*abs(x) + 1)
              sage: forget()
          """
          try:
              if SR(x).variables() and x.is_integer():
                  return x
          except TypeError:
              pass
          try:
              return x.floor()
          except AttributeError:
              if isinstance(x, integer_types):
                  return Integer(x)
              elif isinstance(x, (float, complex)):
                  return Integer(math.floor(x))
          return None
  
  floor = Function_floor()
  
  class Function_Order(GinacFunction):
      def __init__(self):
          r"""
          The order function.
  
          This function gives the order of magnitude of some expression,
          similar to `O`-terms.
  
          .. SEEALSO::
  
              :meth:`~sage.symbolic.expression.Expression.Order`,
              :mod:`~sage.rings.big_oh`
  
          EXAMPLES::
  
              sage: x = SR('x')
              sage: x.Order()
              Order(x)
              sage: (x^2 + x).Order()
              Order(x^2 + x)
              sage: x.Order()._sympy_()
              O(x)
  
          TESTS:
  
          Check that :trac:`19425` is resolved::
  
              sage: x.Order().operator()
              Order
          """
          GinacFunction.__init__(self, "Order",
                  conversions=dict(sympy='O'),
                  latex_name=r"\mathcal{O}")
  
  Order = Function_Order()
  
  class Function_frac(BuiltinFunction):
      def __init__(self):
          r"""
          The fractional part function `\{x\}`.
  
          ``frac(x)`` is defined as `\{x\} = x - \lfloor x\rfloor`.
  
          EXAMPLES::
  
              sage: frac(5.4)
              0.400000000000000
              sage: type(frac(5.4))
              <type 'sage.rings.real_mpfr.RealNumber'>
              sage: frac(456/123)
              29/41
              sage: var('x')
              x
              sage: a = frac(5.4 + x); a
              frac(x + 5.40000000000000)
              sage: frac(cos(8)/cos(2))
              cos(8)/cos(2)
              sage: latex(frac(x))
              \operatorname{frac}\left(x\right)
              sage: frac(x)._sympy_()
              frac(x)
  
          Test pickling::
  
              sage: loads(dumps(floor))
              floor
          """
          BuiltinFunction.__init__(self, "frac",
                                   conversions=dict(sympy='frac'),
                                   latex_name=r"\operatorname{frac}")
  
      def _evalf_(self, x, **kwds):
          """
          EXAMPLES::
  
              sage: frac(pi).n()
              0.141592653589793
              sage: frac(pi).n(200)
              0.14159265358979323846264338327950288419716939937510582097494
          """
          return x - floor(x)
  
      def _eval_(self, x):
          """
          EXAMPLES::
  
              sage: frac(x).subs(x==7.5)
              0.500000000000000
              sage: frac(x)
              frac(x)
          """
          try:
              return x - x.floor()
          except AttributeError:
              if isinstance(x, integer_types):
                  return Integer(0)
              elif isinstance(x, (float, complex)):
                  return x - Integer(math.floor(x))
              elif isinstance(x, Expression):
                  ret = floor(x)
                  if not hasattr(ret, "operator") or not ret.operator() == floor:
                      return x - ret
          return None
  
  frac = Function_frac()
  
  def _do_sqrt(x, prec=None, extend=True, all=False):
          r"""
          Used internally to compute the square root of x.
  
          INPUT:
  
          -  ``x`` - a number
  
          -  ``prec`` - None (default) or a positive integer
             (bits of precision) If not None, then compute the square root
             numerically to prec bits of precision.
  
          -  ``extend`` - bool (default: True); this is a place
             holder, and is always ignored since in the symbolic ring everything
             has a square root.
  
          -  ``extend`` - bool (default: True); whether to extend
             the base ring to find roots. The extend parameter is ignored if
             prec is a positive integer.
  
          -  ``all`` - bool (default: False); whether to return
             a list of all the square roots of x.
  
  
          EXAMPLES::
  
              sage: from sage.functions.other import _do_sqrt
              sage: _do_sqrt(3)
              sqrt(3)
              sage: _do_sqrt(3,prec=10)
              1.7
              sage: _do_sqrt(3,prec=100)
              1.7320508075688772935274463415
              sage: _do_sqrt(3,all=True)
              [sqrt(3), -sqrt(3)]
  
          Note that the extend parameter is ignored in the symbolic ring::
  
              sage: _do_sqrt(3,extend=False)
              sqrt(3)
          """
          if prec:
              if x >= 0:
                   return RealField(prec)(x).sqrt(all=all)
              else:
                   return ComplexField(prec)(x).sqrt(all=all)
          if x == -1:
              z = I
          else:
              z = SR(x) ** one_half
  
          if all:
              if z:
                  return [z, -z]
              else:
                  return [z]
          return z
  
  def sqrt(x, *args, **kwds):
          r"""
          INPUT:
  
          -  ``x`` - a number
  
          -  ``prec`` - integer (default: None): if None, returns
             an exact square root; otherwise returns a numerical square root if
             necessary, to the given bits of precision.
  
          -  ``extend`` - bool (default: True); this is a place
             holder, and is always ignored or passed to the sqrt function for x,
             since in the symbolic ring everything has a square root.
  
          -  ``all`` - bool (default: False); if True, return all
             square roots of self, instead of just one.
  
          EXAMPLES::
  
              sage: sqrt(-1)
              I
              sage: sqrt(2)
              sqrt(2)
              sage: sqrt(2)^2
              2
              sage: sqrt(4)
              2
              sage: sqrt(4,all=True)
              [2, -2]
              sage: sqrt(x^2)
              sqrt(x^2)
  
          For a non-symbolic square root, there are a few options.
          The best is to numerically approximate afterward::
  
              sage: sqrt(2).n()
              1.41421356237310
              sage: sqrt(2).n(prec=100)
              1.4142135623730950488016887242
  
          Or one can input a numerical type.
  
              sage: sqrt(2.)
              1.41421356237310
              sage: sqrt(2.000000000000000000000000)
              1.41421356237309504880169
              sage: sqrt(4.0)
              2.00000000000000
  
          To prevent automatic evaluation, one can use the ``hold`` parameter
          after coercing to the symbolic ring::
  
              sage: sqrt(SR(4),hold=True)
              sqrt(4)
              sage: sqrt(4,hold=True)
              Traceback (most recent call last):
              ...
              TypeError: _do_sqrt() got an unexpected keyword argument 'hold'
  
          This illustrates that the bug reported in :trac:`6171` has been fixed::
  
              sage: a = 1.1
              sage: a.sqrt(prec=100)  # this is supposed to fail
              Traceback (most recent call last):
              ...
              TypeError: sqrt() got an unexpected keyword argument 'prec'
              sage: sqrt(a, prec=100)
              1.0488088481701515469914535137
              sage: sqrt(4.00, prec=250)
              2.0000000000000000000000000000000000000000000000000000000000000000000000000
  
          One can use numpy input as well::
  
              sage: import numpy
              sage: a = numpy.arange(2,5)
              sage: sqrt(a)
              array([1.41421356, 1.73205081, 2.        ])
          """
          if isinstance(x, float):
              return math.sqrt(x)
          elif type(x).__module__ == 'numpy':
              from numpy import sqrt
              return sqrt(x)
          try:
              return x.sqrt(*args, **kwds)
          # The following includes TypeError to catch cases where sqrt
          # is called with a "prec" keyword, for example, but the sqrt
          # method for x doesn't accept such a keyword.
          except (AttributeError, TypeError):
              pass
          return _do_sqrt(x, *args, **kwds)
  
  # register sqrt in pynac symbol_table for conversion back from other systems
  register_symbol(sqrt, dict(mathematica='Sqrt'))
  symbol_table['functions']['sqrt'] = sqrt
  
  Function_sqrt = type('deprecated_sqrt', (),
          {'__call__': staticmethod(sqrt),
              '__setstate__': lambda x, y: None})
  
  class Function_arg(BuiltinFunction):
      def __init__(self):
          r"""
          The argument function for complex numbers.
  
          EXAMPLES::
  
              sage: arg(3+i)
              arctan(1/3)
              sage: arg(-1+i)
              3/4*pi
              sage: arg(2+2*i)
              1/4*pi
              sage: arg(2+x)
              arg(x + 2)
              sage: arg(2.0+i+x)
              arg(x + 2.00000000000000 + 1.00000000000000*I)
              sage: arg(-3)
              pi
              sage: arg(3)
              0
              sage: arg(0)
              0
  
              sage: latex(arg(x))
              {\rm arg}\left(x\right)
              sage: maxima(arg(x))
              atan2(0,_SAGE_VAR_x)
              sage: maxima(arg(2+i))
              atan(1/2)
              sage: maxima(arg(sqrt(2)+i))
              atan(1/sqrt(2))
              sage: arg(x)._sympy_()
              arg(x)
  
              sage: arg(2+i)
              arctan(1/2)
              sage: arg(sqrt(2)+i)
              arg(sqrt(2) + I)
              sage: arg(sqrt(2)+i).simplify()
              arctan(1/2*sqrt(2))
  
          TESTS::
  
              sage: arg(0.0)
              0.000000000000000
              sage: arg(3.0)
              0.000000000000000
              sage: arg(-2.5)
              3.14159265358979
              sage: arg(2.0+3*i)
              0.982793723247329
          """
          BuiltinFunction.__init__(self, "arg",
                  conversions=dict(maxima='carg',
                                   mathematica='Arg',
                                   sympy='arg',
                                   giac='arg'))
  
      def _eval_(self, x):
          """
          EXAMPLES::
  
              sage: arg(3+i)
              arctan(1/3)
              sage: arg(-1+i)
              3/4*pi
              sage: arg(2+2*i)
              1/4*pi
              sage: arg(2+x)
              arg(x + 2)
              sage: arg(2.0+i+x)
              arg(x + 2.00000000000000 + 1.00000000000000*I)
              sage: arg(-3)
              pi
              sage: arg(3)
              0
              sage: arg(0)
              0
              sage: arg(sqrt(2)+i)
              arg(sqrt(2) + I)
  
          """
          if isinstance(x,Expression):
              if x.is_trivial_zero():
                  return x
          else:
              if not x:
                  return x
              else:
                  return arctan2(imag_part(x),real_part(x))
  
      def _evalf_(self, x, parent=None, algorithm=None):
          """
          EXAMPLES::
  
              sage: arg(0.0)
              0.000000000000000
              sage: arg(3.0)
              0.000000000000000
              sage: arg(3.00000000000000000000000000)
              0.00000000000000000000000000
              sage: arg(3.00000000000000000000000000).prec()
              90
              sage: arg(ComplexIntervalField(90)(3)).prec()
              90
              sage: arg(ComplexIntervalField(90)(3)).parent()
              Real Interval Field with 90 bits of precision
              sage: arg(3.0r)
              0.0
              sage: arg(RDF(3))
              0.0
              sage: arg(RDF(3)).parent()
              Real Double Field
              sage: arg(-2.5)
              3.14159265358979
              sage: arg(2.0+3*i)
              0.982793723247329
  
          TESTS:
  
          Make sure that the ``_evalf_`` method works when it receives a
          keyword argument ``parent`` :trac:`12289`::
  
              sage: arg(5+I, hold=True).n()
              0.197395559849881
          """
          try:
              return x.arg()
          except AttributeError:
              pass
          # try to find a parent that support .arg()
          if parent is None:
              parent = s_parent(x)
          try:
              parent = parent.complex_field()
          except AttributeError:
              try:
                  parent = ComplexField(x.prec())
              except AttributeError:
                  parent = ComplexField()
  
          return parent(x).arg()
  
  arg=Function_arg()
  
  
  ############################
  # Real and Imaginary Parts #
  ############################
  class Function_real_part(GinacFunction):
      def __init__(self):
          r"""
          Returns the real part of the (possibly complex) input.
  
          It is possible to prevent automatic evaluation using the
          ``hold`` parameter::
  
              sage: real_part(I,hold=True)
              real_part(I)
  
          To then evaluate again, we currently must use Maxima via
          :meth:`sage.symbolic.expression.Expression.simplify`::
  
              sage: real_part(I,hold=True).simplify()
              0
  
          EXAMPLES::
  
              sage: z = 1+2*I
              sage: real(z)
              1
              sage: real(5/3)
              5/3
              sage: a = 2.5
              sage: real(a)
              2.50000000000000
              sage: type(real(a))
              <type 'sage.rings.real_mpfr.RealLiteral'>
              sage: real(1.0r)
              1.0
              sage: real(complex(3, 4))
              3.0
  
          Sage can recognize some expressions as real and accordingly
          return the identical argument::
  
              sage: SR.var('x', domain='integer').real_part()
              x
              sage: SR.var('x', domain='integer').imag_part()
              0
              sage: real_part(sin(x)+x)
              x + sin(x)
              sage: real_part(x*exp(x))
              x*e^x
              sage: imag_part(sin(x)+x)
              0
              sage: real_part(real_part(x))
              x
              sage: forget()
  
          TESTS::
  
              sage: loads(dumps(real_part))
              real_part
              sage: real_part(x)._sympy_()
              re(x)
  
          Check if :trac:`6401` is fixed::
  
              sage: latex(x.real())
              \Re \left( x \right)
  
              sage: f(x) = function('f')(x)
              sage: latex( f(x).real())
              \Re \left( f\left(x\right) \right)
  
          Check that some real part expansions evaluate correctly
          (:trac:`21614`)::
  
              sage: real(sqrt(sin(x))).subs(x==0)
              0
          """
          GinacFunction.__init__(self, "real_part",
                                 conversions=dict(maxima='realpart',
                                                  sympy='re',
                                                  giac='re'),
                                 alt_name="real")
  
      def __call__(self, x, **kwargs):
          r"""
          TESTS::
  
              sage: type(real(complex(3, 4)))
              <... 'float'>
          """
          if isinstance(x, complex):
              return x.real
          else:
              return GinacFunction.__call__(self, x, **kwargs)
  
  real = real_part = Function_real_part()
  
  class Function_imag_part(GinacFunction):
      def __init__(self):
          r"""
          Returns the imaginary part of the (possibly complex) input.
  
          It is possible to prevent automatic evaluation using the
          ``hold`` parameter::
  
              sage: imag_part(I,hold=True)
              imag_part(I)
  
          To then evaluate again, we currently must use Maxima via
          :meth:`sage.symbolic.expression.Expression.simplify`::
  
              sage: imag_part(I,hold=True).simplify()
              1
  
          TESTS::
  
              sage: z = 1+2*I
              sage: imaginary(z)
              2
              sage: imag(z)
              2
              sage: imag(complex(3, 4))
              4.0
              sage: loads(dumps(imag_part))
              imag_part
              sage: imag_part(x)._sympy_()
              im(x)
  
          Check if :trac:`6401` is fixed::
  
              sage: latex(x.imag())
              \Im \left( x \right)
  
              sage: f(x) = function('f')(x)
              sage: latex( f(x).imag())
              \Im \left( f\left(x\right) \right)
          """
          GinacFunction.__init__(self, "imag_part",
                                 conversions=dict(maxima='imagpart',
                                                  sympy='im',
                                                  giac='im'),
                                 alt_name="imag")
  
      def __call__(self, x, **kwargs):
          r"""
          TESTS::
  
              sage: type(imag(complex(3, 4)))
              <... 'float'>
          """
          if isinstance(x, complex):
              return x.imag
          else:
              return GinacFunction.__call__(self, x, **kwargs)
  
  imag = imag_part = imaginary = Function_imag_part()
  
  
  ############################
  # Complex Conjugate        #
  ############################
  class Function_conjugate(GinacFunction):
      def __init__(self):
          r"""
          Returns the complex conjugate of the input.
  
          It is possible to prevent automatic evaluation using the
          ``hold`` parameter::
  
              sage: conjugate(I,hold=True)
              conjugate(I)
  
          To then evaluate again, we currently must use Maxima via
          :meth:`sage.symbolic.expression.Expression.simplify`::
  
              sage: conjugate(I,hold=True).simplify()
              -I
  
          TESTS::
  
              sage: x,y = var('x,y')
              sage: x.conjugate()
              conjugate(x)
              sage: _._sympy_()
              conjugate(x)
              sage: latex(conjugate(x))
              \overline{x}
              sage: f = function('f')
              sage: latex(f(x).conjugate())
              \overline{f\left(x\right)}
              sage: f = function('psi')(x,y)
              sage: latex(f.conjugate())
              \overline{\psi\left(x, y\right)}
              sage: x.conjugate().conjugate()
              x
              sage: x.conjugate().operator()
              conjugate
              sage: x.conjugate().operator() == conjugate
              True
  
          Check if :trac:`8755` is fixed::
  
              sage: conjugate(sqrt(-3))
              conjugate(sqrt(-3))
              sage: conjugate(sqrt(3))
              sqrt(3)
              sage: conjugate(sqrt(x))
              conjugate(sqrt(x))
              sage: conjugate(x^2)
              conjugate(x)^2
              sage: var('y',domain='positive')
              y
              sage: conjugate(sqrt(y))
              sqrt(y)
  
          Check if :trac:`10964` is fixed::
  
              sage: z= I*sqrt(-3); z
              I*sqrt(-3)
              sage: conjugate(z)
              -I*conjugate(sqrt(-3))
              sage: var('a')
              a
              sage: conjugate(a*sqrt(-2)*sqrt(-3))
              conjugate(sqrt(-2))*conjugate(sqrt(-3))*conjugate(a)
  
          Check that sums are handled correctly::
  
              sage: y = var('y', domain='real')
              sage: conjugate(y + I)
              y - I
  
          Test pickling::
  
              sage: loads(dumps(conjugate))
              conjugate
          """
          GinacFunction.__init__(self, "conjugate",
                                 conversions=dict(sympy='conjugate',
                                                  giac='conj'))
  
  conjugate = Function_conjugate()
  
  class Function_factorial(GinacFunction):
      def __init__(self):
          r"""
          Returns the factorial of `n`.
  
          INPUT:
  
          -  ``n`` - a non-negative integer, a complex number (except negative
             integers) or any symbolic expression
  
  
          OUTPUT: an integer or symbolic expression
  
          EXAMPLES::
  
              sage: factorial(0)
              1
              sage: factorial(4)
              24
              sage: factorial(10)
              3628800
              sage: factorial(6) == 6*5*4*3*2
              True
  
              sage: x = SR.var('x')
              sage: f = factorial(x + factorial(x)); f
              factorial(x + factorial(x))
              sage: f(x=3)
              362880
              sage: factorial(x)^2
              factorial(x)^2
  
          To prevent automatic evaluation use the ``hold`` argument::
  
              sage: factorial(5, hold=True)
              factorial(5)
  
          To then evaluate again, we currently must use Maxima via
          :meth:`sage.symbolic.expression.Expression.simplify`::
  
              sage: factorial(5, hold=True).simplify()
              120
  
          We can also give input other than nonnegative integers.  For
          other nonnegative numbers, the :func:`sage.functions.gamma.gamma`
          function is used::
  
              sage: factorial(1/2)
              1/2*sqrt(pi)
              sage: factorial(3/4)
              gamma(7/4)
              sage: factorial(2.3)
              2.68343738195577
  
          But negative input always fails::
  
              sage: factorial(-32)
              Traceback (most recent call last):
              ...
              ValueError: factorial only defined for non-negative integers
  
          And very large integers remain unevaluated::
  
              sage: factorial(2**64)
              factorial(18446744073709551616)
              sage: SR(2**64).factorial()
              factorial(18446744073709551616)
  
          TESTS:
  
          We verify that we can convert this function to Maxima and
          bring it back into Sage.::
  
              sage: z = var('z')
              sage: factorial._maxima_init_()
              'factorial'
              sage: maxima(factorial(z))
              factorial(_SAGE_VAR_z)
              sage: _.sage()
              factorial(z)
              sage: _._sympy_()
              factorial(z)
              sage: k = var('k')
              sage: factorial(k)
              factorial(k)
  
              sage: factorial(3.14)
              7.173269190187...
  
          Test latex typesetting::
  
              sage: latex(factorial(x))
              x!
              sage: latex(factorial(2*x))
              \left(2 \, x\right)!
              sage: latex(factorial(sin(x)))
              \sin\left(x\right)!
              sage: latex(factorial(sqrt(x+1)))
              \left(\sqrt{x + 1}\right)!
              sage: latex(factorial(sqrt(x)))
              \sqrt{x}!
              sage: latex(factorial(x^(2/3)))
              \left(x^{\frac{2}{3}}\right)!
  
              sage: latex(factorial)
              {\rm factorial}
  
          Check that :trac:`11539` is fixed::
  
              sage: (factorial(x) == 0).simplify()
              factorial(x) == 0
              sage: maxima(factorial(x) == 0).sage()
              factorial(x) == 0
              sage: y = var('y')
              sage: (factorial(x) == y).solve(x)
              [factorial(x) == y]
  
          Check that :trac:`16166` is fixed::
  
              sage: RBF = RealBallField(53)
              sage: factorial(RBF(4.2))
              [32.5780960503313 +/- 6.72e-14]
  
          Test pickling::
  
              sage: loads(dumps(factorial))
              factorial
          """
          GinacFunction.__init__(self, "factorial", latex_name='{\\rm factorial}',
                  conversions=dict(maxima='factorial',
                                   mathematica='Factorial',
                                   sympy='factorial',
                                   fricas='factorial',
                                   giac='factorial'))
  
      def _eval_(self, x):
          """
          Evaluate the factorial function.
  
          Note that this method overrides the eval method defined in GiNaC
          which calls numeric evaluation on all numeric input. We preserve
          exact results if the input is a rational number.
  
          EXAMPLES::
  
              sage: k = var('k')
              sage: k.factorial()
              factorial(k)
              sage: SR(1/2).factorial()
              1/2*sqrt(pi)
              sage: SR(3/4).factorial()
              gamma(7/4)
              sage: SR(5).factorial()
              120
              sage: SR(3245908723049857203948572398475r).factorial()
              factorial(3245908723049857203948572398475)
              sage: SR(3245908723049857203948572398475).factorial()
              factorial(3245908723049857203948572398475)
  
          TESTS:
  
          Check that :trac:`25421` is fixed::
  
              sage: factorial(RBF(2)**64)
              [+/- 2.30e+347382171326740403407]
          """
          if isinstance(x, Integer):
              try:
                  return x.factorial()
              except OverflowError:
                  return
          elif isinstance(x, Rational):
              from sage.functions.gamma import gamma
              return gamma(x + 1)
          elif self._is_numerical(x):
              return (x + 1).gamma()
  
  factorial = Function_factorial()
  
  class Function_binomial(GinacFunction):
      def __init__(self):
          r"""
          Return the binomial coefficient
  
          .. MATH::
  
              \binom{x}{m} = x (x-1) \cdots (x-m+1) / m!
  
  
          which is defined for `m \in \ZZ` and any
          `x`. We extend this definition to include cases when
          `x-m` is an integer but `m` is not by
  
          .. MATH::
  
              \binom{x}{m}= \binom{x}{x-m}
  
          If `m < 0`, return `0`.
  
          INPUT:
  
          -  ``x``, ``m`` - numbers or symbolic expressions. Either ``m``
             or ``x-m`` must be an integer, else the output is symbolic.
  
          OUTPUT: number or symbolic expression (if input is symbolic)
  
          EXAMPLES::
  
              sage: binomial(5,2)
              10
              sage: binomial(2,0)
              1
              sage: binomial(1/2, 0)
              1
              sage: binomial(3,-1)
              0
              sage: binomial(20,10)
              184756
              sage: binomial(-2, 5)
              -6
              sage: binomial(RealField()('2.5'), 2)
              1.87500000000000
              sage: n=var('n'); binomial(n,2)
              1/2*(n - 1)*n
              sage: n=var('n'); binomial(n,n)
              1
              sage: n=var('n'); binomial(n,n-1)
              n
              sage: binomial(2^100, 2^100)
              1
  
          ::
  
              sage: k, i = var('k,i')
              sage: binomial(k,i)
              binomial(k, i)
  
          We can use a ``hold`` parameter to prevent automatic evaluation::
  
              sage: SR(5).binomial(3, hold=True)
              binomial(5, 3)
              sage: SR(5).binomial(3, hold=True).simplify()
              10
  
          TESTS:
  
          We verify that we can convert this function to Maxima and
          bring it back into Sage.
  
          ::
  
              sage: n,k = var('n,k')
              sage: maxima(binomial(n,k))
              binomial(_SAGE_VAR_n,_SAGE_VAR_k)
              sage: _.sage()
              binomial(n, k)
              sage: _._sympy_()
              binomial(n, k)
              sage: binomial._maxima_init_()
              'binomial'
  
          For polynomials::
  
              sage: y = polygen(QQ, 'y')
              sage: binomial(y, 2).parent()
              Univariate Polynomial Ring in y over Rational Field
  
          :trac:`16726`::
  
              sage: binomial(CIF(1), 2)
              0
              sage: binomial(CIF(3), 2)
              3
  
          Test pickling::
  
              sage: loads(dumps(binomial(n,k)))
              binomial(n, k)
          """
          GinacFunction.__init__(self, "binomial", nargs=2, preserved_arg=1,
                  conversions=dict(maxima='binomial',
                                   mathematica='Binomial',
                                   sympy='binomial',
                                   fricas='binomial',
                                   giac='comb'))
  
      def _binomial_sym(self, n, k):
          """
          Expand the binomial formula symbolically when the second argument
          is an integer.
  
          EXAMPLES::
  
              sage: binomial._binomial_sym(x, 3)
              1/6*(x - 1)*(x - 2)*x
              sage: binomial._binomial_sym(x, x)
              Traceback (most recent call last):
              ...
              ValueError: second argument must be an integer
              sage: binomial._binomial_sym(x, SR(3))
              1/6*(x - 1)*(x - 2)*x
  
              sage: binomial._binomial_sym(x, 0r)
              1
              sage: binomial._binomial_sym(x, -1)
              0
  
              sage: y = polygen(QQ, 'y')
              sage: binomial._binomial_sym(y, 2).parent()
              Univariate Polynomial Ring in y over Rational Field
          """
          if isinstance(k, Expression):
              if k.is_integer():
                  k = k.pyobject()
              else:
                  raise ValueError("second argument must be an integer")
  
          if k < 0:
              return s_parent(k)(0)
          if k == 0:
              return s_parent(k)(1)
          if k == 1:
              return n
  
          from sage.misc.all import prod
          return prod(n - i for i in range(k)) / factorial(k)
  
      def _eval_(self, n, k):
          """
          EXAMPLES::
  
              sage: binomial._eval_(5, 3)
              10
              sage: type(binomial._eval_(5, 3))
              <type 'sage.rings.integer.Integer'>
              sage: type(binomial._eval_(5., 3))
              <type 'sage.rings.real_mpfr.RealNumber'>
              sage: binomial._eval_(x, 3)
              1/6*(x - 1)*(x - 2)*x
              sage: binomial._eval_(x, x-2)
              1/2*(x - 1)*x
              sage: n = var('n')
              sage: binomial._eval_(x, n) is None
              True
  
          TESTS::
  
              sage: y = polygen(QQ, 'y')
              sage: binomial._eval_(y, 2).parent()
              Univariate Polynomial Ring in y over Rational Field
          """
          if not isinstance(k, Expression):
              if not isinstance(n, Expression):
                  n, k = coercion_model.canonical_coercion(n, k)
                  return self._evalf_(n, k)
          if k in ZZ:
              return self._binomial_sym(n, k)
          if (n - k) in ZZ:
              return self._binomial_sym(n, n - k)
  
          return None
  
      def _evalf_(self, n, k, parent=None, algorithm=None):
          """
          EXAMPLES::
  
              sage: binomial._evalf_(5.r, 3)
              10.0
              sage: type(binomial._evalf_(5.r, 3))
              <... 'float'>
              sage: binomial._evalf_(1/2,1/1)
              1/2
              sage: binomial._evalf_(10^20+1/1,10^20)
              100000000000000000001
              sage: binomial._evalf_(SR(10**7),10**7)
              1
              sage: binomial._evalf_(3/2,SR(1/1))
              3/2
          """
          return arith_binomial(n, k)
  
  binomial = Function_binomial()
  
  
  class Function_sum(BuiltinFunction):
      """
      Placeholder symbolic sum function that is only accessible internally.
  
      EXAMPLES::
  
          sage: from sage.functions.other import symbolic_sum as ssum
          sage: r = ssum(x, x, 1, 10); r
          sum(x, x, 1, 10)
          sage: r.unhold()
          55
      """
      def __init__(self):
          """
          EXAMPLES::
  
              sage: from sage.functions.other import symbolic_sum as ssum
              sage: maxima(ssum(x, x, 1, 10))
              55
          """
          BuiltinFunction.__init__(self, "sum", nargs=4,
                                 conversions=dict(maxima='sum'))
  
      def _print_latex_(self, x, var, a, b):
          r"""
          EXAMPLES::
  
              sage: from sage.functions.other import symbolic_sum as ssum
              sage: latex(ssum(x^2, x, 1, 10))
              {\sum_{x=1}^{10} x^{2}}
          """
          return r"{{\sum_{{{}={}}}^{{{}}} {}}}".format(latex(var), latex(a),
                                                        latex(b), latex(x))
  
      def _sympy_(self, term, k, a, n):
          """
          Convert to sympy Sum.
  
          EXAMPLES::
  
              sage: var('k, n')
              (k, n)
              sage: s = sum(k, k, 1, n, hold=True)
              sage: s
              sum(k, k, 1, n)
              sage: s._sympy_() # indirect test
              Sum(k, (k, 1, n))
              sage: s._sympy_().doit()
              n**2/2 + n/2
  
          """
          import sympy
          return sympy.Sum(term, (k, a, n))
  
  symbolic_sum = Function_sum()
  
  
  class Function_prod(BuiltinFunction):
      """
      Placeholder symbolic product function that is only accessible internally.
  
      EXAMPLES::
  
          sage: from sage.functions.other import symbolic_product as sprod
          sage: r = sprod(x, x, 1, 10); r
          product(x, x, 1, 10)
          sage: r.unhold()
          3628800
      """
      def __init__(self):
          """
          EXAMPLES::
  
              sage: from sage.functions.other import symbolic_product as sprod
              sage: _ = var('m n', domain='integer')
              sage: r = maxima(sprod(sin(m), m, 1, n)).sage(); r
              product(sin(m), m, 1, n)
              sage: isinstance(r.operator(), sage.functions.other.Function_prod)
              True
              sage: r = sympy(sprod(sin(m), m, 1, n)).sage(); r # known bug
              product(sin(m), m, 1, n)
              sage: isinstance(r.operator(),
              ....:     sage.functions.other.Function_prod) # known bug
              True
              sage: giac(sprod(m, m, 1, n))
              n!
          """
          BuiltinFunction.__init__(self, "product", nargs=4,
                                 conversions=dict(maxima='product',
                                     sympy='Product', giac='product'))
  
      def _print_latex_(self, x, var, a, b):
          r"""
          EXAMPLES::
  
              sage: from sage.functions.other import symbolic_product as sprod
              sage: latex(sprod(x^2, x, 1, 10))
              {\prod_{x=1}^{10} x^{2}}
          """
          return r"{{\prod_{{{}={}}}^{{{}}} {}}}".format(latex(var), latex(a),
                                                         latex(b), latex(x))
  
      def _sympy_(self, term, k, a, n):
          """
          Convert to sympy Product.
  
          EXAMPLES::
  
              sage: var('k, n')
              (k, n)
              sage: p = product(k^2+k+1,k,1,n, hold=True)
              sage: p._sympy_() # indirect test
              Product(k**2 + k + 1, (k, 1, n))
          """
          import sympy
          return sympy.Product(term, (k, a, n))
  
  symbolic_product = Function_prod()
  
  
  class Function_limit(BuiltinFunction):
      """
      Placeholder symbolic limit function that is only accessible internally.
  
      This function is called to create formal wrappers of limits that
      Maxima can't compute::
  
          sage: a = lim(exp(x^2)*(1-erf(x)), x=infinity); a
          -limit((erf(x) - 1)*e^(x^2), x, +Infinity)
  
      EXAMPLES::
  
          sage: from sage.functions.other import symbolic_limit as slimit
          sage: slimit(1/x, x, +oo)
          limit(1/x, x, +Infinity)
          sage: var('minus,plus')
          (minus, plus)
          sage: slimit(1/x, x, +oo)
          limit(1/x, x, +Infinity)
          sage: slimit(1/x, x, 0, plus)
          limit(1/x, x, 0, plus)
          sage: slimit(1/x, x, 0, minus)
          limit(1/x, x, 0, minus)
      """
      def __init__(self):
          """
          EXAMPLES::
  
              sage: from sage.functions.other import symbolic_limit as slimit
              sage: maxima(slimit(1/x, x, +oo))
              0
          """
          BuiltinFunction.__init__(self, "limit", nargs=0,
                                 conversions=dict(maxima='limit'))
  
      def _latex_(self):
          r"""
          EXAMPLES::
  
              sage: from sage.functions.other import symbolic_limit as slimit
              sage: latex(slimit)
              \lim
          """
          return r'\lim'
  
      def _print_latex_(self, ex, var, to, direction=''):
          r"""
          EXAMPLES::
  
              sage: from sage.functions.other import symbolic_limit as slimit
              sage: var('x,a')
              (x, a)
              sage: f = function('f')
              sage: latex(slimit(f(x), x, a))
              \lim_{x \to a}\, f\left(x\right)
              sage: latex(limit(f(x), x=oo))
              \lim_{x \to +\infty}\, f\left(x\right)
  
          TESTS:
  
          When one-sided limits are converted back from maxima, the direction
          argument becomes a symbolic variable. We check if typesetting these works::
  
              sage: from sage.functions.other import symbolic_limit as slimit
              sage: var('minus,plus')
              (minus, plus)
              sage: latex(slimit(f(x), x, a, minus))
              \lim_{x \to a^-}\, f\left(x\right)
              sage: latex(slimit(f(x), x, a, plus))
              \lim_{x \to a^+}\, f\left(x\right)
              sage: latex(limit(f(x),x=a,dir='+'))
              \lim_{x \to a^+}\, f\left(x\right)
              sage: latex(limit(f(x),x=a,dir='right'))
              \lim_{x \to a^+}\, f\left(x\right)
              sage: latex(limit(f(x),x=a,dir='-'))
              \lim_{x \to a^-}\, f\left(x\right)
              sage: latex(limit(f(x),x=a,dir='left'))
              \lim_{x \to a^-}\, f\left(x\right)
  
          Check if :trac:`13181` is fixed::
  
              sage: t = var('t')
              sage: latex(limit(exp_integral_e(1/2, I*t - I*x)*sqrt(-t + x),t=x,dir='-'))
              \lim_{t \to x^-}\, \sqrt{-t + x} E_{\frac{1}{2}}\left(i \, t - i \, x\right)
              sage: latex(limit(exp_integral_e(1/2, I*t - I*x)*sqrt(-t + x),t=x,dir='+'))
              \lim_{t \to x^+}\, \sqrt{-t + x} E_{\frac{1}{2}}\left(i \, t - i \, x\right)
              sage: latex(limit(exp_integral_e(1/2, I*t - I*x)*sqrt(-t + x),t=x))
              \lim_{t \to x}\, \sqrt{-t + x} E_{\frac{1}{2}}\left(i \, t - i \, x\right)
          """
          if repr(direction) == 'minus':
              dir_str = '^-'
          elif repr(direction) == 'plus':
              dir_str = '^+'
          else:
              dir_str = ''
          return r"\lim_{{{} \to {}{}}}\, {}".format(latex(var),
                  latex(to), dir_str, latex(ex))
  
  symbolic_limit = Function_limit()
  
  
  class Function_cases(GinacFunction):
      """
      Formal function holding ``(condition, expression)`` pairs.
  
      Numbers are considered conditions with zero being ``False``.
      A true condition marks a default value. The function is not
      evaluated as long as it contains a relation that cannot be
      decided by Pynac.
  
      EXAMPLES::
  
          sage: ex = cases([(x==0, pi), (True, 0)]); ex
          cases(((x == 0, pi), (1, 0)))
          sage: ex.subs(x==0)
          pi
          sage: ex.subs(x==2)
          0
          sage: ex + 1
          cases(((x == 0, pi), (1, 0))) + 1
          sage: _.subs(x==0)
          pi + 1
  
      The first encountered default is used, as well as the first relation
      that can be trivially decided::
  
          sage: cases(((True, pi), (True, 0)))
          pi
  
          sage: _ = var('y')
          sage: ex = cases(((x==0, pi), (y==1, 0))); ex
          cases(((x == 0, pi), (y == 1, 0)))
          sage: ex.subs(x==0)
          pi
          sage: ex.subs(x==0, y==1)
          pi
      """
      def __init__(self):
          """
          EXAMPLES::
  
              sage: loads(dumps(cases))
              cases
          """
          GinacFunction.__init__(self, "cases")
  
      def __call__(self, l, **kwargs):
          """
          EXAMPLES::
  
              sage: ex = cases([(x==0, pi), (True, 0)]); ex
              cases(((x == 0, pi), (1, 0)))
  
          TESTS::
  
              sage: cases()  # py2
              Traceback (most recent call last):
              ...
              TypeError: __call__() takes exactly 2 arguments (1 given)
              sage: cases()  # py3
              Traceback (most recent call last):
              ...
              TypeError: __call__() missing 1 required positional argument: 'l'
  
              sage: cases(x)
              Traceback (most recent call last):
              ...
              RuntimeError: cases argument not a sequence
          """
          return GinacFunction.__call__(self,
                  SR._force_pyobject(l), **kwargs)
  
      def _print_latex_(self, l, **kwargs):
          r"""
          EXAMPLES::
  
              sage: ex = cases([(x==0, pi), (True, 0)]); ex
              cases(((x == 0, pi), (1, 0)))
              sage: latex(ex)
              \begin{cases}{\pi} & {x = 0}\\{0} & {1}\end{cases}
          """
          if not isinstance(l, (list, tuple)):
              raise ValueError("cases() argument must be a list")
          str = r"\begin{cases}"
          for pair in l:
              left = None
              if (isinstance(pair, tuple)):
                  right,left = pair
              else:
                  right = pair
              str += r"{%s} & {%s}\\" % (latex(left), latex(right))
          print(str[:-2] + r"\end{cases}")
  
      def _sympy_(self, l):
          """
          Convert this cases expression to its SymPy equivalent.
  
          EXAMPLES::
  
              sage: ex = cases(((x<0, pi), (x==1, 1), (True, 0)))
              sage: assert ex == ex._sympy_()._sage_()
          """
          from sage.symbolic.ring import SR
          from sympy import Piecewise as pw
          args = []
          for tup in l.operands():
              cond,expr = tup.operands()
              if SR(cond).is_numeric():
                  args.append((SR(expr)._sympy_(), bool(SR(cond)._sympy_())))
              else:
                  args.append((SR(expr)._sympy_(), SR(cond)._sympy_()))
          return pw(*args)
  
  cases = Function_cases()
  
  
  class Function_crootof(BuiltinFunction):
      """
      Formal function holding ``(polynomial, index)`` pairs.
  
      The expression evaluates to a floating point value that is an
      approximation to a specific complex root of the polynomial. The
      ordering is fixed so you always get the same root.
  
      The functionality is imported from SymPy, see
      http://docs.sympy.org/latest/_modules/sympy/polys/rootoftools.html
  
      EXAMPLES::
  
          sage: c = complex_root_of(x^6 + x + 1, 1); c
          complex_root_of(x^6 + x + 1, 1)
          sage: c.n()
          -0.790667188814418 + 0.300506920309552*I
          sage: c.n(100)
          -0.79066718881441764449859281847 + 0.30050692030955162512001002521*I
          sage: (c^6 + c + 1).n(100) < 1e-25
          True
      """
      def __init__(self):
          """
          EXAMPLES::
  
              sage: loads(dumps(complex_root_of))
              complex_root_of
          """
          BuiltinFunction.__init__(self, "complex_root_of", nargs=2,
                                     conversions=dict(sympy='CRootOf'),
                                     evalf_params_first=False)
  
      def _eval_(self, poly, index):
          """
          TESTS::
  
              sage: _ = var('y')
              sage: complex_root_of(1, 1)
              Traceback (most recent call last):
              ...
              ValueError: polynomial in one variable required
              sage: complex_root_of(x+y, 1)
              Traceback (most recent call last):
              ...
              ValueError: polynomial in one variable required
              sage: complex_root_of(sin(x), 1)
              Traceback (most recent call last):
              ...
              ValueError: polynomial in one variable required
          """
          try:
              vars = poly.variables()
          except AttributeError:
              raise ValueError('polynomial in one variable required')
          if len(vars) != 1 or not poly.is_polynomial(vars[0]):
              raise ValueError('polynomial in one variable required')
  
      def _evalf_(self, poly, index, parent=None, algorithm=None):
          """
          EXAMPLES::
  
              sage: complex_root_of(x^2-2, 1).n()
              1.41421356237309
              sage: complex_root_of(x^2-2, 3).n()
              Traceback (most recent call last):
              ...
              IndexError: root index out of [-2, 1] range, got 3
  
          TESTS:
  
          Check that low precision is handled (:trac:`24378`)::
  
              sage: complex_root_of(x^8-1, 7).n(2)
              0.75 + 0.75*I
              sage: complex_root_of(x^8-1, 7).n(20)
              0.70711 + 0.70711*I
          """
          from sympy.core.evalf import prec_to_dps
          from sympy.polys import CRootOf, Poly
          try:
              prec = parent.precision()
          except AttributeError:
              prec = 53
          sobj = CRootOf(Poly(poly._sympy_()), int(index))
          return parent(sobj.n(1 + prec_to_dps(prec))._sage_())
  
  complex_root_of = Function_crootof()
  
  