arithmetic.py

# -*- coding: utf-8 -*-
# cython: language_level=3

"""
Mathematical Functions

Basic arithmetic functions, including complex number arithmetic.
"""

from functools import lru_cache
from typing import Optional

import mpmath
import sympy

from mathics.builtin.base import (
    Builtin,
    IterationFunction,
    Predefined,
    SympyFunction,
    SympyObject,
    Test,
)
from mathics.builtin.inference import evaluate_predicate, get_assumptions_list
from mathics.builtin.scoping import dynamic_scoping
from mathics.core.atoms import (
    MATHICS3_COMPLEX_I,
    MATHICS3_COMPLEX_I_NEG,
    Complex,
    Integer,
    Integer0,
    Integer1,
    IntegerM1,
    Number,
    Rational,
    Real,
    String,
)
from mathics.core.attributes import (
    A_HOLD_ALL,
    A_HOLD_REST,
    A_LISTABLE,
    A_NO_ATTRIBUTES,
    A_NUMERIC_FUNCTION,
    A_PROTECTED,
)
from mathics.core.convert.expression import to_expression
from mathics.core.convert.sympy import SympyExpression, from_sympy, sympy_symbol_prefix
from mathics.core.element import BaseElement
from mathics.core.evaluation import Evaluation
from mathics.core.expression import Expression
from mathics.core.expression_predefined import (
    MATHICS3_COMPLEX_INFINITY,
    MATHICS3_I_INFINITY,
    MATHICS3_I_NEG_INFINITY,
    MATHICS3_INFINITY,
    MATHICS3_NEG_INFINITY,
    PredefinedExpression,
)
from mathics.core.list import ListExpression
from mathics.core.number import dps, min_prec
from mathics.core.symbols import (
    Atom,
    Symbol,
    SymbolFalse,
    SymbolList,
    SymbolPlus,
    SymbolTimes,
    SymbolTrue,
)
from mathics.core.systemsymbols import (
    SymbolAnd,
    SymbolDirectedInfinity,
    SymbolInfix,
    SymbolPiecewise,
    SymbolPossibleZeroQ,
    SymbolTable,
    SymbolUndefined,
)
from mathics.eval.arithmetic import (
    eval_Abs,
    eval_mpmath_function,
    eval_negate_number,
    eval_RealSign,
    eval_Sign,
)
from mathics.eval.nevaluator import eval_N
from mathics.eval.numerify import numerify

# This tells documentation how to sort this module
sort_order = "mathics.builtin.mathematical-functions"


map_direction_infinity = {
    Integer1: MATHICS3_INFINITY,
    IntegerM1: MATHICS3_NEG_INFINITY,
    MATHICS3_COMPLEX_I: MATHICS3_I_INFINITY,
    MATHICS3_COMPLEX_I_NEG: MATHICS3_I_NEG_INFINITY,
}


class _MPMathFunction(SympyFunction):

    # These below attributes are the default attributes:
    #
    # * functions take lists as an argument
    # * functions take numeric values only
    # * functions can't be changed
    #
    # However hey are not correct for some derived classes, like
    # InverseErf or InverseErfc.
    # So those classes should expclicitly set/override this.
    attributes = A_LISTABLE | A_NUMERIC_FUNCTION | A_PROTECTED

    mpmath_name = None
    nargs = {1}

    @lru_cache(maxsize=1024)
    def get_mpmath_function(self, args):
        if self.mpmath_name is None or len(args) not in self.nargs:
            return None
        return getattr(mpmath, self.mpmath_name)

    def eval(self, z, evaluation: Evaluation):
        "%(name)s[z__]"

        args = numerify(z, evaluation).get_sequence()

        # if no arguments are inexact attempt to use sympy
        if all(not x.is_inexact() for x in args):
            result = to_expression(self.get_name(), *args).to_sympy()
            result = self.prepare_mathics(result)
            result = from_sympy(result)
            # evaluate elements to convert e.g. Plus[2, I] -> Complex[2, 1]
            return result.evaluate_elements(evaluation)

        if not all(isinstance(arg, Number) for arg in args):
            return

        mpmath_function = self.get_mpmath_function(tuple(args))
        if mpmath_function is None:
            return

        if any(arg.is_machine_precision() for arg in args):
            prec = None
        else:
            prec = min_prec(*args)
            d = dps(prec)
            args = [arg.round(d) for arg in args]

        return eval_mpmath_function(mpmath_function, *args, prec=prec)


class _MPMathMultiFunction(_MPMathFunction):

    sympy_names = None
    mpmath_names = None

    def get_sympy_names(self):
        if self.sympy_names is None:
            return [self.sympy_name]
        return self.sympy_names.values()

    def get_function(self, module, names, fallback_name, elements):
        try:
            name = fallback_name
            if names is not None:
                name = names[len(elements)]
            if name is None:
                return None
            return getattr(module, name)
        except KeyError:
            return None

    def get_sympy_function(self, elements):
        return self.get_function(sympy, self.sympy_names, self.sympy_name, elements)

    def get_mpmath_function(self, elements):
        return self.get_function(mpmath, self.mpmath_names, self.mpmath_name, elements)


def create_infix(items, operator, prec, grouping):
    if len(items) == 1:
        return items[0]
    else:
        return Expression(
            SymbolInfix,
            ListExpression(*items),
            String(operator),
            Integer(prec),
            Symbol(grouping),
        )


class Abs(_MPMathFunction):
    """
        <url>
        :Absolute value:
        https://en.wikipedia.org/wiki/Absolute_value</url> (<url>
        :SymPy:
        https://docs.sympy.org/latest/modules/functions/
    elementary.html#sympy.functions.elementary.complexes.Abs</url>, <url>
        :WMA: https://reference.wolfram.com/language/ref/Abs</url>)

        <dl>
          <dt>'Abs[$x$]'
          <dd>returns the absolute value of $x$.
        </dl>

        >> Abs[-3]
         = 3

        >> Plot[Abs[x], {x, -4, 4}]
         = -Graphics-

        'Abs' returns the magnitude of complex numbers:
        >> Abs[3 + I]
         = Sqrt[10]
        >> Abs[3.0 + I]
         = 3.16228

        All of the below evaluate to Infinity:

        >> Abs[Infinity] == Abs[I Infinity] == Abs[ComplexInfinity]
         = True
    """

    mpmath_name = "fabs"  # mpmath actually uses python abs(x) / x.__abs__()
    rules = {
        "Abs[Undefined]": "Undefined",
    }
    summary_text = "absolute value of a number"
    sympy_name = "Abs"

    def eval(self, x, evaluation: Evaluation):
        "Abs[x_]"
        result = eval_Abs(x)
        if result is not None:
            return result
        return super(Abs, self).eval(x, evaluation)


class Arg(_MPMathFunction):
    """
    <url>:Argument (complex analysis):
    https://en.wikipedia.org/wiki/Argument_(complex_analysis)</url> (<url>
    :WMA link:https://reference.wolfram.com/language/ref/Arg.html</url>)

    <dl>
      <dt>'Arg'[$z$, $method_option$]
      <dd>returns the argument of a complex value $z$.
    </dl>

    <ul>
         <li>'Arg'[$z$] is left unevaluated if $z$ is not a numeric quantity.
         <li>'Arg'[$z$] gives the phase angle of $z$ in radians.
         <li>The result from 'Arg'[$z$] is always between -Pi and +Pi.
         <li>'Arg'[$z$] has a branch cut discontinuity in the complex $z$ plane running from -Infinity to 0.
         <li>'Arg'[0] is 0.
    </ul>

     >> Arg[-3]
      = Pi

     Same as above using sympy's method:
     >> Arg[-3, Method->"sympy"]
      = Pi

    >> Arg[1-I]
     = -Pi / 4

    Arg evaluate the direction of DirectedInfinity quantities by
    the Arg of they arguments:
    >> Arg[DirectedInfinity[1+I]]
     = Pi / 4
    >> Arg[DirectedInfinity[]]
     = 1
    Arg for 0 is assumed to be 0:
    >> Arg[0]
     = 0
    """

    summary_text = "phase of a complex number"
    rules = {
        "Arg[0]": "0",
        "Arg[DirectedInfinity[]]": "1",
        "Arg[DirectedInfinity[a_]]": "Arg[a]",
    }

    attributes = A_LISTABLE | A_NUMERIC_FUNCTION | A_PROTECTED
    options = {"Method": "Automatic"}

    numpy_name = "angle"  # for later
    mpmath_name = "arg"
    sympy_name = "arg"

    def eval(self, z, evaluation, options={}):
        "Arg[z_, OptionsPattern[Arg]]"
        if Expression(SymbolPossibleZeroQ, z).evaluate(evaluation) is SymbolTrue:
            return Integer0
        preference = self.get_option(options, "Method", evaluation).get_string_value()
        if preference is None or preference == "Automatic":
            return super(Arg, self).eval(z, evaluation)
        elif preference == "mpmath":
            return _MPMathFunction.eval(self, z, evaluation)
        elif preference == "sympy":
            return SympyFunction.eval(self, z, evaluation)
        # TODO: add NumpyFunction
        evaluation.message(
            "meth", f'Arg Method {preference} not in ("sympy", "mpmath")'
        )
        return


class Assuming(Builtin):
    """
    <url>:WMA link:https://reference.wolfram.com/language/ref/Assuming.html</url>

    <dl>
      <dt>'Assuming[$cond$, $expr$]'
      <dd>Evaluates $expr$ assuming the conditions $cond$.
    </dl>
    >> $Assumptions = { x > 0 }
     = {x > 0}
    >> Assuming[y>0, ConditionalExpression[y x^2, y>0]//Simplify]
     = x ^ 2 y
    >> Assuming[Not[y>0], ConditionalExpression[y x^2, y>0]//Simplify]
     = Undefined
    >> ConditionalExpression[y x ^ 2, y > 0]//Simplify
     = ConditionalExpression[x ^ 2 y, y > 0]
    """

    summary_text = "set assumptions during the evaluation"
    attributes = A_HOLD_REST | A_PROTECTED

    def eval_assuming(self, assumptions, expr, evaluation: Evaluation):
        "Assuming[assumptions_, expr_]"
        assumptions = assumptions.evaluate(evaluation)
        if assumptions is SymbolTrue:
            cond = []
        elif isinstance(assumptions, Symbol) or not assumptions.has_form("List", None):
            cond = [assumptions]
        else:
            cond = assumptions.elements
        cond = tuple(cond) + get_assumptions_list(evaluation)
        list_cond = ListExpression(*cond)
        # TODO: reduce the list of predicates
        return dynamic_scoping(
            lambda ev: expr.evaluate(ev), {"System`$Assumptions": list_cond}, evaluation
        )


class Assumptions(Predefined):
    """
    <url>:WMA link:https://reference.wolfram.com/language/ref/$Assumptions.html</url>
    <dl>
      <dt>'$Assumptions'
      <dd>is the default setting for the Assumptions option used in such functions as Simplify, Refine, and Integrate.
    </dl>
    """

    summary_text = "assumptions used to simplify expressions"
    name = "$Assumptions"
    attributes = A_NO_ATTRIBUTES
    rules = {
        "$Assumptions": "True",
    }

    messages = {
        "faas": "Assumptions should not be False.",
        "baas": "Bad formed assumption.",
    }


class Boole(Builtin):
    """
    <url>:WMA link:https://reference.wolfram.com/language/ref/Boole.html</url>

    <dl>
      <dt>'Boole[expr]'
      <dd>returns 1 if expr is True and 0 if expr is False.
    </dl>

    >> Boole[2 == 2]
     = 1
    >> Boole[7 < 5]
     = 0
    >> Boole[a == 7]
     = Boole[a == 7]
    """

    attributes = A_LISTABLE | A_PROTECTED
    summary_text = "translate 'True' to 1, and 'False' to 0"

    def eval(self, expr, evaluation: Evaluation):
        "Boole[expr_]"
        if expr is SymbolTrue:
            return Integer1
        elif expr is SymbolFalse:
            return Integer0
        return None


class Complex_(Builtin):
    """
    <url>:WMA link:https://reference.wolfram.com/language/ref/Complex.html</url>

    <dl>
      <dt>'Complex'
      <dd>is the head of complex numbers.

      <dt>'Complex[$a$, $b$]'
      <dd>constructs the complex number '$a$ + I $b$'.
    </dl>

    >> Head[2 + 3*I]
     = Complex
    >> Complex[1, 2/3]
     = 1 + 2 I / 3
    >> Abs[Complex[3, 4]]
     = 5

    #> OutputForm[Complex[2.0 ^ 40, 3]]
     = 1.09951×10^12 + 3. I
    #> InputForm[Complex[2.0 ^ 40, 3]]
     = 1.099511627776*^12 + 3.*I

    #> -2 / 3 - I
     = -2 / 3 - I

    #> Complex[10, 0]
     = 10

    #> 0. + I
     = 0. + 1. I

    #> 1 + 0 I
     = 1
    #> Head[%]
     = Integer

    #> Complex[0.0, 0.0]
     = 0. + 0. I
    #> 0. I
     = 0.
    #> 0. + 0. I
     = 0.

    #> 1. + 0. I
     = 1.
    #> 0. + 1. I
     = 0. + 1. I

    ## Check Nesting Complex
    #> Complex[1, Complex[0, 1]]
     = 0
    #> Complex[1, Complex[1, 0]]
     = 1 + I
    #> Complex[1, Complex[1, 1]]
     = I
    """

    summary_text = "head for complex numbers"
    name = "Complex"

    def eval(self, r, i, evaluation: Evaluation):
        "Complex[r_?NumberQ, i_?NumberQ]"

        if isinstance(r, Complex) or isinstance(i, Complex):
            sym_form = r.to_sympy() + sympy.I * i.to_sympy()
            r, i = sym_form.simplify().as_real_imag()
            r, i = from_sympy(r), from_sympy(i)
        return Complex(r, i)


class ConditionalExpression(Builtin):
    """
    <url>:WMA link:https://reference.wolfram.com/
language/ref/ConditionalExpression.html</url>

    <dl>
      <dt>'ConditionalExpression[$expr$, $cond$]'
      <dd>returns $expr$ if $cond$ evaluates to $True$, $Undefined$ if $cond$ \
          evaluates to $False$.
    </dl>

    >> ConditionalExpression[x^2, True]
     = x ^ 2

     >> ConditionalExpression[x^2, False]
     = Undefined

    >> f = ConditionalExpression[x^2, x>0]
     = ConditionalExpression[x ^ 2, x > 0]
    >> f /. x -> 2
     = 4
    >> f /. x -> -2
     = Undefined
    'ConditionalExpression' uses assumptions to evaluate the condition:
    >> $Assumptions = x > 0;
    >> ConditionalExpression[x ^ 2, x>0]//Simplify
     = x ^ 2
    >> $Assumptions = True;
    # >> ConditionalExpression[ConditionalExpression[s,x>a], x<b]
    # = ConditionalExpression[s, And[x>a, x<b]]
    """

    summary_text = "expression defined under condition"
    sympy_name = "Piecewise"

    rules = {
        "ConditionalExpression[expr_, True]": "expr",
        "ConditionalExpression[expr_, False]": "Undefined",
        "ConditionalExpression[ConditionalExpression[expr_, cond1_], cond2_]": "ConditionalExpression[expr, And@@Flatten[{cond1, cond2}]]",
        "ConditionalExpression[expr1_, cond_] + expr2_": "ConditionalExpression[expr1+expr2, cond]",
        "ConditionalExpression[expr1_, cond_]  expr2_": "ConditionalExpression[expr1 expr2, cond]",
        "ConditionalExpression[expr1_, cond_]^expr2_": "ConditionalExpression[expr1^expr2, cond]",
        "expr1_ ^ ConditionalExpression[expr2_, cond_]": "ConditionalExpression[expr1^expr2, cond]",
    }

    def eval_generic(self, expr, cond, evaluation: Evaluation):
        "ConditionalExpression[expr_, cond_]"
        # What we need here is a way to evaluate
        # cond as a predicate, using assumptions.
        # Let's delegate this to the And (and Or) symbols...
        if not isinstance(cond, Atom) and cond._head is SymbolList:
            cond = Expression(SymbolAnd, *(cond.elements))
        else:
            cond = Expression(SymbolAnd, cond)
        if cond is None:
            return
        if cond is SymbolTrue:
            return expr
        if cond is SymbolFalse:
            return SymbolUndefined
        return

    def to_sympy(self, expr, **kwargs):
        elements = expr.elements
        if len(elements) != 2:
            return
        expr, cond = elements

        sympy_cond = None
        if isinstance(cond, Symbol):
            if cond is SymbolTrue:
                sympy_cond = True
            elif cond is SymbolFalse:
                sympy_cond = False
        if sympy_cond is None:
            sympy_cond = cond.to_sympy(**kwargs)
            if not (sympy_cond.is_Relational or sympy_cond.is_Boolean):
                return

        sympy_cases = (
            (expr.to_sympy(**kwargs), sympy_cond),
            (sympy.Symbol(sympy_symbol_prefix + "System`Undefined"), True),
        )
        return sympy.Piecewise(*sympy_cases)


class Conjugate(_MPMathFunction):
    """
    <url>:Complex Conjugate:
    https://en.wikipedia.org/wiki/Complex_conjugate</url> \
    (<url>:WMA:https://reference.wolfram.com/language/ref/Conjugate.html</url>)

    <dl>
      <dt>'Conjugate[$z$]'
      <dd>returns the complex conjugate of the complex number $z$.
    </dl>

    >> Conjugate[3 + 4 I]
     = 3 - 4 I

    >> Conjugate[3]
     = 3

    >> Conjugate[a + b * I]
     = Conjugate[a] - I Conjugate[b]

    >> Conjugate[{{1, 2 + I 4, a + I b}, {I}}]
     = {{1, 2 - 4 I, Conjugate[a] - I Conjugate[b]}, {-I}}

    ## Issue #272
    #> {Conjugate[Pi], Conjugate[E]}
     = {Pi, E}

    >> Conjugate[1.5 + 2.5 I]
     = 1.5 - 2.5 I
    """

    mpmath_name = "conj"
    rules = {
        "Conjugate[Undefined]": "Undefined",
    }
    summary_text = "complex conjugation"


class DirectedInfinity(SympyFunction):
    """
    <url>:WMA link:
    https://reference.wolfram.com/language/ref/DirectedInfinity.html</url>

    <dl>
      <dt>'DirectedInfinity[$z$]'
      <dd>represents an infinite multiple of the complex number $z$.
      <dt>'DirectedInfinity[]'
      <dd>is the same as 'ComplexInfinity'.
    </dl>

    >> DirectedInfinity[1]
     = Infinity
    >> DirectedInfinity[]
     = ComplexInfinity
    >> DirectedInfinity[1 + I]
     = (1 / 2 + I / 2) Sqrt[2] Infinity

    >> 1 / DirectedInfinity[1 + I]
     = 0
    >> DirectedInfinity[1] + DirectedInfinity[-1]
     : Indeterminate expression -Infinity + Infinity encountered.
     = Indeterminate

    >> DirectedInfinity[0]
     = ComplexInfinity

    #> DirectedInfinity[1+I]+DirectedInfinity[2+I]
     = (2 / 5 + I / 5) Sqrt[5] Infinity + (1 / 2 + I / 2) Sqrt[2] Infinity

    #> DirectedInfinity[Sqrt[3]]
     = Infinity
    """

    summary_text = "infinite quantity with a defined direction in the complex plane"
    rules = {
        "DirectedInfinity[args___] ^ -1": "0",
        # Special arguments:
        "DirectedInfinity[DirectedInfinity[args___]]": "DirectedInfinity[args]",
        "DirectedInfinity[Indeterminate]": "Indeterminate",
        "DirectedInfinity[Alternatives[0, 0.]]": "DirectedInfinity[]",
        # Plus
        "DirectedInfinity[a_] + DirectedInfinity[b_] /; b == -a": (
            "Message[Infinity::indet,"
            "  Unevaluated[DirectedInfinity[a] + DirectedInfinity[b]]];"
            "Indeterminate"
        ),
        "DirectedInfinity[] + DirectedInfinity[args___]": (
            "Message[Infinity::indet,"
            "  Unevaluated[DirectedInfinity[] + DirectedInfinity[args]]];"
            "Indeterminate"
        ),
        "DirectedInfinity[args___] + _?NumberQ": "DirectedInfinity[args]",
        # Times. See if can be reinstalled in eval_Times
        "Alternatives[0, 0.] DirectedInfinity[z___]": (
            "Message[Infinity::indet,"
            "  Unevaluated[0 DirectedInfinity[z]]];"
            "Indeterminate"
        ),
        "a_?NumericQ * DirectedInfinity[b_]": "DirectedInfinity[a * b]",
        "a_ DirectedInfinity[]": "DirectedInfinity[]",
        "DirectedInfinity[a_] * DirectedInfinity[b_]": "DirectedInfinity[a * b]",
    }

    formats = {
        "DirectedInfinity[1]": "HoldForm[Infinity]",
        "DirectedInfinity[-1]": "HoldForm[-Infinity]",
        "DirectedInfinity[]": "HoldForm[ComplexInfinity]",
        "DirectedInfinity[DirectedInfinity[z_]]": "DirectedInfinity[z]",
        "DirectedInfinity[z_?NumericQ]": "HoldForm[z Infinity]",
    }

    def eval_complex_infinity(self, evaluation: Evaluation):
        """DirectedInfinity[]"""
        return MATHICS3_COMPLEX_INFINITY

    def eval_directed_infinity(self, direction, evaluation: Evaluation):
        """DirectedInfinity[direction_]"""
        result = map_direction_infinity.get(direction, None)
        if result:
            return result

        if direction.is_zero:
            return MATHICS3_COMPLEX_INFINITY

        normalized_direction = eval_Sign(direction)
        # TODO: improve eval_Sign, to avoid the need of the
        # following block:
        #   ############################################
        if normalized_direction is None:
            ndir = eval_N(direction, evaluation)
            if isinstance(ndir, (Integer, Rational, Real)):
                if abs(ndir.value) == 1.0:
                    normalized_direction = direction
                else:
                    normalized_direction = direction / Abs(direction)
            elif isinstance(ndir, Complex):
                re, im = ndir.value
                if abs(re.value**2 + im.value**2 - 1.0) < 1.0e-9:
                    normalized_direction = direction
                else:
                    normalized_direction = direction / Abs(direction)
            else:
                return None
        #  ##############################################

        if normalized_direction is None:
            return None
        return PredefinedExpression(
            SymbolDirectedInfinity,
            normalized_direction.evaluate(evaluation),
        )

    def to_sympy(self, expr, **kwargs):
        if len(expr.elements) == 1:
            dir = expr.elements[0].get_int_value()
            if dir == 1:
                return sympy.oo
            elif dir == -1:
                return -sympy.oo
            else:
                return sympy.Mul((expr.elements[0].to_sympy()), sympy.zoo)
        else:
            return sympy.zoo


class Element(Builtin):
    """
    <url>:Element of:https://en.wikipedia.org/wiki/Element_(mathematics)</url> \
    (<url>:WMA:https://reference.wolfram.com/language/ref/Element.html</url>)

    <dl>
      <dt>'Element[$expr$, $domain$]'
      <dd>returns $True$ if $expr$ is an element of $domain$
      <dt>'Element[$expr_1$|$expr_2$|..., $domain$]'
      <dd>returns $True$ if all the $expr_i$ belongs to $domain$, and \
    $False$ if one of the items doesn't.
    </dl>


    Check if $3$ and $a$ are both integers. If $a$ is not defined, then \
'Element' reduces the condition:
    >> Element[3 | a, Integers]
     = Element[a, Integers]

    Notice that standard domain names ('Primes', 'Integers', 'Rationals', \
'Algebraics', 'Reals', 'Complexes', and 'Booleans')\
    are in plural form. If a singular form is used, a warning is shown:

    >> Element[a, Real]
     : The second argument Real of Element should be one of: Primes, Integers, \
Rationals, Algebraics, Reals, Complexes, or Booleans.
     = Element[a, Real]

    """

    messages = {
        "bset": (
            "The second argument `1` of Element should be one of: "
            "Primes, Integers, Rationals, Algebraics, "
            "Reals, Complexes, or Booleans."
        ),
    }

    summary_text = "check whether belongs the domain"

    def eval_wrong_domain(
        self, elem: BaseElement, domain: BaseElement, evaluation: Evaluation
    ):
        (
            "Element[elem_, domain:(Alternatives["
            "Algebraic, Bool, Integer, Prime, Rational, Real, Complex])]"
        )
        evaluation.message("Element", "bset", domain)
        return None

    def eval_Element_alternatives(
        self, elems: BaseElement, domain: BaseElement, evaluation: Evaluation
    ) -> Optional[Expression]:
        """Element[elems_Alternatives, domain_]"""
        items = elems.elements
        unknown = []
        for item in items:
            item_belongs = Element(item, domain).evaluate(evaluation)
            if item_belongs is SymbolTrue:
                continue
            if item_belongs is SymbolFalse:
                return SymbolFalse
            unknown.append(item)
        if len(unknown) == len(items):
            return None
        if len(unknown) == 0:
            return SymbolTrue
        # If some of the items remain unkown, return a reduced expression
        return Element(Expression(elems.head, *unknown), domain)


class I_(Predefined, SympyObject):
    """
    <url>:Imaginary unit:https://en.wikipedia.org/wiki/Imaginary_unit</url> \
    (<url>:WMA:https://reference.wolfram.com/language/ref/I.html</url>)

    <dl>
      <dt>'I'
      <dd>represents the imaginary number 'Sqrt[-1]'.
    </dl>

    >> I^2
     = -1
    >> (3+I)*(3-I)
     = 10
    """

    name = "I"
    sympy_name = "I"
    sympy_obj = sympy.I
    summary_text = "imaginary unit"
    python_equivalent = 1j

    def is_constant(self) -> bool:
        return True

    def to_sympy(self, symb, **kwargs):
        return self.sympy_obj

    def evaluate(self, evaluation: Evaluation):
        return Complex(Integer0, Integer1)


class Im(SympyFunction):
    """
    <url>
    :WMA link:
    https://reference.wolfram.com/language/ref/Im.html</url>

    <dl>
      <dt>'Im[$z$]'
      <dd>returns the imaginary component of the complex number $z$.
    </dl>

    >> Im[3+4I]
     = 4

    >> Plot[{Sin[a], Im[E^(I a)]}, {a, 0, 2 Pi}]
     = -Graphics-

    #> Re[0.5 + 2.3 I]
     = 0.5
    #> % // Precision
     = MachinePrecision
    """

    summary_text = "imaginary part"
    attributes = A_LISTABLE | A_NUMERIC_FUNCTION | A_PROTECTED

    def eval_complex(self, number, evaluation: Evaluation):
        "Im[number_Complex]"
        if isinstance(number, Complex):
            return number.imag

    def eval_number(self, number, evaluation: Evaluation):
        "Im[number_?NumberQ]"

        return Integer0

    def eval(self, number, evaluation: Evaluation):
        "Im[number_]"

        return from_sympy(sympy.im(number.to_sympy().expand(complex=True)))


class Integer_(Builtin):
    """
    <url>:WMA link:https://reference.wolfram.com/language/ref/Integer.html</url>

    <dl>
      <dt>'Integer'
      <dd>is the head of integers.
    </dl>

    >> Head[5]
     = Integer

    ## Test large Integer comparison bug
    #> {a, b} = {2^10000, 2^10000 + 1}; {a == b, a < b, a <= b}
     = {False, True, True}
    """

    summary_text = "head for integer numbers"
    name = "Integer"


class Piecewise(SympyFunction):
    """
    <url>:WMA link:https://reference.wolfram.com/language/ref/Piecewise.html</url>

    <dl>
      <dt>'Piecewise[{{expr1, cond1}, ...}]'
      <dd>represents a piecewise function.

      <dt>'Piecewise[{{expr1, cond1}, ...}, expr]'
      <dd>represents a piecewise function with default 'expr'.
    </dl>

    Heaviside function
    >> Piecewise[{{0, x <= 0}}, 1]
     = Piecewise[{{0, x <= 0}}, 1]

    ## D[%, x]
    ## Piecewise({{0, Or[x < 0, x > 0]}}, Indeterminate).

    >> Integrate[Piecewise[{{1, x <= 0}, {-1, x > 0}}], x]
     = Piecewise[{{x, x <= 0}}, -x]

    >> Integrate[Piecewise[{{1, x <= 0}, {-1, x > 0}}], {x, -1, 2}]
     = -1

    Piecewise defaults to 0 if no other case is matching.
    >> Piecewise[{{1, False}}]
     = 0

    >> Plot[Piecewise[{{Log[x], x > 0}, {x*-0.5, x < 0}}], {x, -1, 1}]
     = -Graphics-

    >> Piecewise[{{0 ^ 0, False}}, -1]
     = -1
    """

    summary_text = "an arbitrary piecewise function"
    sympy_name = "Piecewise"

    attributes = A_HOLD_ALL | A_PROTECTED

    def eval(self, items, evaluation: Evaluation):
        "%(name)s[items__]"
        result = self.to_sympy(
            Expression(SymbolPiecewise, *items.get_sequence()), evaluation=evaluation
        )
        if result is None:
            return
        if not isinstance(result, sympy.Piecewise):
            result = from_sympy(result)
            return result

    def to_sympy(self, expr, **kwargs):
        elements = expr.elements
        evaluation = kwargs.get("evaluation", None)
        if len(elements) not in (1, 2):
            return

        sympy_cases = []
        for case in elements[0].elements:
            if case.get_head_name() != "System`List":
                return
            if len(case.elements) != 2:
                return
            then, cond = case.elements
            if evaluation:
                cond = evaluate_predicate(cond, evaluation)

            sympy_cond = None
            if isinstance(cond, Symbol):
                if cond is SymbolTrue:
                    sympy_cond = True
                elif cond is SymbolFalse:
                    sympy_cond = False
            if sympy_cond is None:
                sympy_cond = cond.to_sympy(**kwargs)
                if not (sympy_cond.is_Relational or sympy_cond.is_Boolean):
                    return

            sympy_cases.append((then.to_sympy(**kwargs), sympy_cond))

        if len(elements) == 2:  # default case
            sympy_cases.append((elements[1].to_sympy(**kwargs), True))
        else:
            sympy_cases.append((Integer0.to_sympy(**kwargs), True))

        return sympy.Piecewise(*sympy_cases)

    def from_sympy(self, sympy_name, args):
        # Hack to get around weird sympy.Piecewise 'otherwise' behaviour
        if str(args[-1].elements[1]).startswith("System`_True__Dummy_"):
            args[-1].elements[1] = SymbolTrue
        return Expression(self.get_name(), args)


class Product(IterationFunction, SympyFunction):
    """
    <url>:WMA link:https://reference.wolfram.com/language/ref/Product.html</url>

    <dl>
      <dt>'Product[$expr$, {$i$, $imin$, $imax$}]'
      <dd>evaluates the discrete product of $expr$ with $i$ ranging from $imin$ to $imax$.

      <dt>'Product[$expr$, {$i$, $imax$}]'
      <dd>same as 'Product[$expr$, {$i$, 1, $imax$}]'.

      <dt>'Product[$expr$, {$i$, $imin$, $imax$, $di$}]'
      <dd>$i$ ranges from $imin$ to $imax$ in steps of $di$.

      <dt>'Product[$expr$, {$i$, $imin$, $imax$}, {$j$, $jmin$, $jmax$}, ...]'
      <dd>evaluates $expr$ as a multiple product, with {$i$, ...}, {$j$, ...}, ... being in outermost-to-innermost order.
    </dl>

    >> Product[k, {k, 1, 10}]
     = 3628800
    >> 10!
     = 3628800
    >> Product[x^k, {k, 2, 20, 2}]
     = x ^ 110
    >> Product[2 ^ i, {i, 1, n}]
     = 2 ^ (n / 2 + n ^ 2 / 2)
    >> Product[f[i], {i, 1, 7}]
     = f[1] f[2] f[3] f[4] f[5] f[6] f[7]

    Symbolic products involving the factorial are evaluated:
    >> Product[k, {k, 3, n}]
     = n! / 2

    Evaluate the $n$th primorial:
    >> primorial[0] = 1;
    >> primorial[n_Integer] := Product[Prime[k], {k, 1, n}];
    >> primorial[12]
     = 7420738134810

    ## Used to be a bug in sympy, but now it is solved exactly!
    ## Again a bug in sympy - regressions between 0.7.3 and 0.7.6 (and 0.7.7?)
    ## #> Product[1 + 1 / i ^ 2, {i, Infinity}]
    ##  = 1 / ((-I)! I!)
    """

    summary_text = "discrete product"
    throw_iterb = False

    sympy_name = "Product"

    rules = IterationFunction.rules.copy()
    rules.update(
        {
            "MakeBoxes[Product[f_, {i_, a_, b_, 1}],"
            "  form:StandardForm|TraditionalForm]": (
                r'RowBox[{SubsuperscriptBox["\\[Product]",'
                r'  RowBox[{MakeBoxes[i, form], "=", MakeBoxes[a, form]}],'
                r"  MakeBoxes[b, form]], MakeBoxes[f, form]}]"
            ),
        }
    )

    def get_result(self, items):
        return Expression(SymbolTimes, *items)

    def to_sympy(self, expr, **kwargs):
        if expr.has_form("Product", 2) and expr.elements[1].has_form("List", 3):
            index = expr.elements[1]
            try:
                e_kwargs = kwargs.copy()
                e_kwargs["convert_all_global_functions"] = True
                e = expr.elements[0].to_sympy(**e_kwargs)
                i = index.elements[0].to_sympy(**kwargs)
                start = index.elements[1].to_sympy(**kwargs)
                stop = index.elements[2].to_sympy(**kwargs)

                return sympy.product(e, (i, start, stop))
            except ZeroDivisionError:
                pass


class Rational_(Builtin):
    """
    <url>:WMA link:https://reference.wolfram.com/language/ref/Rational.html</url>

    <dl>
      <dt>'Rational'
      <dd>is the head of rational numbers.
      <dt>'Rational[$a$, $b$]'
      <dd>constructs the rational number $a$ / $b$.
    </dl>

    >> Head[1/2]
     = Rational

    >> Rational[1, 2]
     = 1 / 2

    #> -2/3
     = -2 / 3
    """

    summary_text = "head for rational numbers"
    name = "Rational"

    def eval(self, n: Integer, m: Integer, evaluation: Evaluation):
        "Rational[n_Integer, m_Integer]"

        if m.value == 1:
            return n
        else:
            return Rational(n.value, m.value)


class Re(SympyFunction):
    """
    <url>:WMA link:https://reference.wolfram.com/language/ref/Re.html</url>

    <dl>
      <dt>'Re[$z$]'
      <dd>returns the real component of the complex number $z$.
    </dl>

    >> Re[3+4I]
     = 3

    >> Plot[{Cos[a], Re[E^(I a)]}, {a, 0, 2 Pi}]
     = -Graphics-

    #> Im[0.5 + 2.3 I]
     = 2.3
    #> % // Precision
     = MachinePrecision
    """

    summary_text = "real part"
    attributes = A_LISTABLE | A_NUMERIC_FUNCTION | A_PROTECTED
    sympy_name = "re"

    def eval_complex(self, number, evaluation: Evaluation):
        "Re[number_Complex]"
        if isinstance(number, Complex):
            return number.real

    def eval_number(self, number, evaluation: Evaluation):
        "Re[number_?NumberQ]"

        return number

    def eval(self, number, evaluation: Evaluation):
        "Re[number_]"
        return from_sympy(sympy.re(number.to_sympy().expand(complex=True)))


class Real_(Builtin):
    """
    <url>:WMA link:https://reference.wolfram.com/language/ref/Real.html</url>

    <dl>
      <dt>'Real'
      <dd>is the head of real (inexact) numbers.
    </dl>

    >> x = 3. ^ -20;
    >> InputForm[x]
     = 2.8679719907924413*^-10
    >> Head[x]
     = Real

    ## Formatting tests
    #> 1. * 10^6
     = 1.×10^6
    #> 1. * 10^5
     = 100000.
    #> -1. * 10^6
     = -1.×10^6
    #> -1. * 10^5
     = -100000.
    #> 1. * 10^-6
     = 1.×10^-6
    #> 1. * 10^-5
     = 0.00001
    #> -1. * 10^-6
     = -1.×10^-6
    #> -1. * 10^-5
     = -0.00001

    ## Mathematica treats zero strangely
    #> 0.0000000000000
     = 0.
    #> 0.0000000000000000000000000000
     = 0.×10^-28

    ## Parse *^ Notation
    #> 1.5×10^24
     = 1.5×10^24
    #> 1.5*^+24
     = 1.5×10^24
    #> 1.5*^-24
     = 1.5×10^-24

    ## Don't accept *^ with spaces
    #> 1.5 *^10
     : "1.5 *" cannot be followed by "^10" (line 1 of "<test>").
    #> 1.5*^ 10
     : "1.5*" cannot be followed by "^ 10" (line 1 of "<test>").

    ## Issue654
    #> 1^^2
     : Requested base 1 in 1^^2 should be between 2 and 36.
     : Expression cannot begin with "1^^2" (line 1 of "<test>").
    #> 2^^0101
     = 5
    #> 2^^01210
     : Digit at position 3 in 01210 is too large to be used in base 2.
     : Expression cannot begin with "2^^01210" (line 1 of "<test>").
    #> 16^^5g
     : Digit at position 2 in 5g is too large to be used in base 16.
     : Expression cannot begin with "16^^5g" (line 1 of "<test>").
    #> 36^^0123456789abcDEFxyzXYZ
     = 14142263610074677021975869033659
    #> 37^^3
     : Requested base 37 in 37^^3 should be between 2 and 36.
     : Expression cannot begin with "37^^3" (line 1 of "<test>").
    """

    summary_text = "head for real numbers"
    name = "Real"


class RealAbs(Builtin):
    """
    <url>
        :Abs (Real):
        https://en.wikipedia.org/wiki/Absolute_value</url> (<url>
        :WMA link:
        https://reference.wolfram.com/language/ref/RealAbs.html
        </url>)

    <dl>
      <dt>'RealAbs[$x$]'
      <dd>returns the absolute value of a real number $x$.
    </dl>
    'RealAbs' is also known as modulus. It is evaluated if $x$ can be compared \
    with $0$.

    >> RealAbs[-3.]
     = 3.
    'RealAbs[$z$]' is left unevaluated for complex $z$:
    >> RealAbs[2. + 3. I]
     = RealAbs[2. + 3. I]
    >> D[RealAbs[x ^ 2], x]
     = 2 x ^ 3 / RealAbs[x ^ 2]
    """

    attributes = A_LISTABLE | A_NUMERIC_FUNCTION | A_PROTECTED
    rules = {
        "D[RealAbs[x_],x_]": "x/RealAbs[x]",
        "Integrate[RealAbs[x_],x_]": "1/2 x RealAbs[x]",
        "Integrate[RealAbs[u_],{u_,a_,b_}]": "1/2 b RealAbs[b]-1/2 a RealAbs[a]",
    }
    summary_text = "real absolute value"

    def eval(self, x: BaseElement, evaluation: Evaluation):
        """RealAbs[x_]"""
        real_sign = eval_RealSign(x)
        if real_sign is IntegerM1:
            return eval_negate_number(x)
        if real_sign is None:
            return
        return x


class RealNumberQ(Test):
    """
    ## Not found in WMA
    ## <url>:WMA link:https://reference.wolfram.com/language/ref/RealNumberQ.html</url>

    <dl>
      <dt>'RealNumberQ[$expr$]'
      <dd>returns 'True' if $expr$ is an explicit number with no imaginary component.
    </dl>

    >> RealNumberQ[10]
     = True
    >> RealNumberQ[4.0]
     = True
    >> RealNumberQ[1+I]
     = False
    >> RealNumberQ[0 * I]
     = True
    >> RealNumberQ[0.0 * I]
     = True
    """

    attributes = A_NO_ATTRIBUTES

    summary_text = "test whether an expression is a real number"

    def test(self, expr) -> bool:
        return isinstance(expr, (Integer, Rational, Real))


class RealSign(Builtin):
    """
    <url>
        :Signum:
        https://en.wikipedia.org/wiki/Sign_function</url> (<url>
        :WMA link:
        https://reference.wolfram.com/language/ref/RealSign.html
        </url>)
    <dl>
      <dt>'RealSign[$x$]'
      <dd>returns $-1$, $0$ or $1$ depending on whether $x$ is negative,
    zero or positive.
    </dl>
    'RealSign' is also known as $sgn$ or $signum$ function.

    >> RealSign[-3.]
     = -1
    'RealSign[$z$]' is left unevaluated for complex $z$:
    >> RealSign[2. + 3. I]
     = RealSign[2. + 3. I]

    >> D[RealSign[x^2],x]
     = 2 x Piecewise[{{0, x ^ 2 != 0}}, Indeterminate]
    >> Integrate[RealSign[u],{u,0,x}]
     = RealAbs[x]
    """

    attributes = A_LISTABLE | A_NUMERIC_FUNCTION | A_PROTECTED
    rules = {
        "D[RealSign[x_],x_]": "Piecewise[{{0, x!=0}}, Indeterminate]",
        "Integrate[RealSign[x_],x_]": "RealAbs[x]",
        "Integrate[RealSign[u_],{u_, a_, b_}]": "RealAbs[b]-RealSign[a]",
    }
    summary_text = "real sign"

    def eval(self, x: Number, evaluation: Evaluation) -> Optional[Integer]:
        """RealSign[x_]"""
        return eval_RealSign(x)


class Sign(SympyFunction):
    """
    <url>
        :Sign:
        https://en.wikipedia.org/wiki/Sign_function</url> (<url>
        :WMA link:
        https://reference.wolfram.com/language/ref/Sign.html
        </url>)

    <dl>
      <dt>'Sign[$x$]'
      <dd>return -1, 0, or 1 depending on whether $x$ is negative, zero, or positive.
    </dl>

    >> Sign[19]
     = 1
    >> Sign[-6]
     = -1
    >> Sign[0]
     = 0
    >> Sign[{-5, -10, 15, 20, 0}]
     = {-1, -1, 1, 1, 0}
    #> Sign[{1, 2.3, 4/5, {-6.7, 0}, {8/9, -10}}]
     = {1, 1, 1, {-1, 0}, {1, -1}}
    >> Sign[3 - 4*I]
     = 3 / 5 - 4 I / 5
    #> Sign[1 - 4*I] == (1/17 - 4 I/17) Sqrt[17]
     = True
    #> Sign[4, 5, 6]
     : Sign called with 3 arguments; 1 argument is expected.
     = Sign[4, 5, 6]
    #> Sign["20"]
     = Sign[20]
    """

    summary_text = "complex sign of a number"
    sympy_name = "sign"
    # mpmath_name = 'sign'

    attributes = A_LISTABLE | A_NUMERIC_FUNCTION | A_PROTECTED

    messages = {
        "argx": "Sign called with `1` arguments; 1 argument is expected.",
    }

    rules = {
        "Sign[Power[a_, b_]]": "Power[Sign[a], b]",
    }

    def eval(self, x, evaluation: Evaluation):
        "%(name)s[x_]"
        result = eval_Sign(x)
        if result is not None:
            return result
        # return None

        sympy_x = x.to_sympy()
        if sympy_x is None:
            return None
        # Unhandled cases. Use sympy
        return super(Sign, self).eval(x, evaluation)

    def eval_error(self, x, seqs, evaluation: Evaluation):
        "Sign[x_, seqs__]"
        evaluation.message("Sign", "argx", Integer(len(seqs.get_sequence()) + 1))


class Sum(IterationFunction, SympyFunction):
    """
    <url>:WMA link:https://reference.wolfram.com/language/ref/Sum.html</url>

    <dl>
      <dt>'Sum[$expr$, {$i$, $imin$, $imax$}]'
      <dd>evaluates the discrete sum of $expr$ with $i$ ranging from $imin$ to $imax$.

      <dt>'Sum[$expr$, {$i$, $imax$}]'
      <dd>same as 'Sum[$expr$, {$i$, 1, $imax$}]'.

      <dt>'Sum[$expr$, {$i$, $imin$, $imax$, $di$}]'
      <dd>$i$ ranges from $imin$ to $imax$ in steps of $di$.

      <dt>'Sum[$expr$, {$i$, $imin$, $imax$}, {$j$, $jmin$, $jmax$}, ...]'
      <dd>evaluates $expr$ as a multiple sum, with {$i$, ...}, {$j$, ...}, ... being \
          in outermost-to-innermost order.
    </dl>


    A sum that Gauss in elementary school was asked to do to kill time:
    >> Sum[k, {k, 1, 10}]
     = 55

    The symbolic form he used:
    >> Sum[k, {k, 1, n}]
     = n (1 + n) / 2

    A Geometric series with a finite limit:
    >> Sum[1 / 2 ^ i, {i, 1, k}]
     = 1 - 2 ^ (-k)

    A Geometric series using Infinity:
    >> Sum[1 / 2 ^ i, {i, 1, Infinity}]
     = 1

    Leibniz formula used in computing Pi:
    >> Sum[1 / ((-1)^k (2k + 1)), {k, 0, Infinity}]
     = Pi / 4

    A table of double sums to compute squares:
    >> Table[ Sum[i * j, {i, 0, n}, {j, 0, n}], {n, 0, 4} ]
     = {0, 1, 9, 36, 100}

    Computing Harmonic using a sum
    >> Sum[1 / k ^ 2, {k, 1, n}]
     = HarmonicNumber[n, 2]

    Other symbolic sums:
    >> Sum[k, {k, n, 2 n}]
     = 3 n (1 + n) / 2

    A sum with Complex-number iteration values
    >> Sum[k, {k, I, I + 1}]
     = 1 + 2 I

    >> Sum[k, {k, Range[5]}]
     = 15

    >> Sum[f[i], {i, 1, 7}]
     = f[1] + f[2] + f[3] + f[4] + f[5] + f[6] + f[7]

    Verify algebraic identities:
    >> Sum[x ^ 2, {x, 1, y}] - y * (y + 1) * (2 * y + 1) / 6
     = 0

    ## >> (-1 + a^n) Sum[a^(k n), {k, 0, m-1}] // Simplify
    ## = -1 + (a ^ n) ^ m  # this is what I am getting
    ## = Piecewise[{{m (-1 + a ^ n), a ^ n == 1}, {-1 + (a ^ n) ^ m, True}}]

    #> a=Sum[x^k*Sum[y^l,{l,0,4}],{k,0,4}]]
     : "a=Sum[x^k*Sum[y^l,{l,0,4}],{k,0,4}]" cannot be followed by "]" (line 1 of "<test>").

    ## Issue #302
    ## The sum should not converge since the first term is 1/0.
    #> Sum[i / Log[i], {i, 1, Infinity}]
     = Sum[i / Log[i], {i, 1, Infinity}]
    #> Sum[Cos[Pi i], {i, 1, Infinity}]
     = Sum[Cos[i Pi], {i, 1, Infinity}]
    """

    summary_text = "discrete sum"
    # Do not throw warning message for symbolic iteration bounds
    throw_iterb = False

    sympy_name = "Sum"

    rules = IterationFunction.rules.copy()
    rules.update(
        {
            "MakeBoxes[Sum[f_, {i_, a_, b_, 1}],"
            "  form:StandardForm|TraditionalForm]": (
                r'RowBox[{SubsuperscriptBox["\\[Sum]",'
                r'  RowBox[{MakeBoxes[i, form], "=", MakeBoxes[a, form]}],'
                r"  MakeBoxes[b, form]], MakeBoxes[f, form]}]"
            ),
        }
    )

    def get_result(self, items):
        return Expression(SymbolPlus, *items)

    def to_sympy(self, expr, **kwargs) -> Optional[SympyExpression]:
        """
        Perform summation via sympy.summation
        """
        if expr.has_form("Sum", 2) and expr.elements[1].has_form("List", 3):
            index = expr.elements[1]
            arg_kwargs = kwargs.copy()
            arg_kwargs["convert_all_global_functions"] = True
            f_sympy = expr.elements[0].to_sympy(**arg_kwargs)
            if f_sympy is None:
                return

            evaluation = kwargs.get("evaluation", None)

            # Handle summation parameters: variable, min, max
            var_min_max = index.elements[:3]
            bounds = [expr.to_sympy(**kwargs) for expr in var_min_max]

            if evaluation:
                # Min and max might be Mathics expressions. If so, evaluate them.
                for i in (1, 2):
                    min_max_expr = var_min_max[i]
                    if not isinstance(expr, Symbol):
                        min_max_expr_eval = min_max_expr.evaluate(evaluation)
                        value = min_max_expr_eval.to_sympy(**kwargs)
                        bounds[i] = value

            # FIXME: The below tests on SympyExpression, but really the
            # test should be broader.
            if isinstance(f_sympy, sympy.core.basic.Basic):
                # sympy.summation() won't be able to handle Mathics functions in
                # in its first argument, the function paramameter.
                # For example in Sum[Identity[x], {x, 3}], sympy.summation can't
                # evaluate Indentity[x].
                # In general we want to avoid using Sympy if we can.
                # If we have integer bounds, we'll use Mathics's iterator Sum
                # (which is Plus)

                if all(hasattr(i, "is_integer") and i.is_integer for i in bounds[1:]):
                    # When we have integer bounds, it is better to not use Sympy but
                    # use Mathics evaluation. We turn:
                    # Sum[f[x], {<limits>}] into
                    #   MathicsSum[Table[f[x], {<limits>}]]
                    # where MathicsSum is self.get_result() our Iteration iterator.
                    values = Expression(SymbolTable, *expr.elements).evaluate(
                        evaluation
                    )
                    ret = self.get_result(values.elements).evaluate(evaluation)
                    # Make sure to convert the result back to sympy.
                    return ret.to_sympy()

            if None not in bounds:
                return sympy.summation(f_sympy, bounds)