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ckpts/universal/global_step120/zero/24.mlp.dense_4h_to_h.weight/exp_avg.pt

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+size 33555612

ckpts/universal/global_step120/zero/5.mlp.dense_4h_to_h.weight/fp32.pt

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+size 33555533

ckpts/universal/global_step120/zero/7.mlp.dense_h_to_4h.weight/exp_avg.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:94e850a68e721f623d9f9eea5fb35c677d26e0318639373bd748828e58951108
+size 33555612

venv/lib/python3.10/site-packages/sympy/concrete/__init__.py

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+from .products import product, Product
+from .summations import summation, Sum
+
+__all__ = [
+    'product', 'Product',
+
+    'summation', 'Sum',
+]

venv/lib/python3.10/site-packages/sympy/concrete/delta.py

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+"""
+This module implements sums and products containing the Kronecker Delta function.
+
+References
+==========
+
+.. [1] https://mathworld.wolfram.com/KroneckerDelta.html
+
+"""
+from .products import product
+from .summations import Sum, summation
+from sympy.core import Add, Mul, S, Dummy
+from sympy.core.cache import cacheit
+from sympy.core.sorting import default_sort_key
+from sympy.functions import KroneckerDelta, Piecewise, piecewise_fold
+from sympy.polys.polytools import factor
+from sympy.sets.sets import Interval
+from sympy.solvers.solvers import solve
+
+
+@cacheit
+def _expand_delta(expr, index):
+    """
+    Expand the first Add containing a simple KroneckerDelta.
+    """
+    if not expr.is_Mul:
+        return expr
+    delta = None
+    func = Add
+    terms = [S.One]
+    for h in expr.args:
+        if delta is None and h.is_Add and _has_simple_delta(h, index):
+            delta = True
+            func = h.func
+            terms = [terms[0]*t for t in h.args]
+        else:
+            terms = [t*h for t in terms]
+    return func(*terms)
+
+
+@cacheit
+def _extract_delta(expr, index):
+    """
+    Extract a simple KroneckerDelta from the expression.
+
+    Explanation
+    ===========
+
+    Returns the tuple ``(delta, newexpr)`` where:
+
+      - ``delta`` is a simple KroneckerDelta expression if one was found,
+        or ``None`` if no simple KroneckerDelta expression was found.
+
+      - ``newexpr`` is a Mul containing the remaining terms; ``expr`` is
+        returned unchanged if no simple KroneckerDelta expression was found.
+
+    Examples
+    ========
+
+    >>> from sympy import KroneckerDelta
+    >>> from sympy.concrete.delta import _extract_delta
+    >>> from sympy.abc import x, y, i, j, k
+    >>> _extract_delta(4*x*y*KroneckerDelta(i, j), i)
+    (KroneckerDelta(i, j), 4*x*y)
+    >>> _extract_delta(4*x*y*KroneckerDelta(i, j), k)
+    (None, 4*x*y*KroneckerDelta(i, j))
+
+    See Also
+    ========
+
+    sympy.functions.special.tensor_functions.KroneckerDelta
+    deltaproduct
+    deltasummation
+    """
+    if not _has_simple_delta(expr, index):
+        return (None, expr)
+    if isinstance(expr, KroneckerDelta):
+        return (expr, S.One)
+    if not expr.is_Mul:
+        raise ValueError("Incorrect expr")
+    delta = None
+    terms = []
+
+    for arg in expr.args:
+        if delta is None and _is_simple_delta(arg, index):
+            delta = arg
+        else:
+            terms.append(arg)
+    return (delta, expr.func(*terms))
+
+
+@cacheit
+def _has_simple_delta(expr, index):
+    """
+    Returns True if ``expr`` is an expression that contains a KroneckerDelta
+    that is simple in the index ``index``, meaning that this KroneckerDelta
+    is nonzero for a single value of the index ``index``.
+    """
+    if expr.has(KroneckerDelta):
+        if _is_simple_delta(expr, index):
+            return True
+        if expr.is_Add or expr.is_Mul:
+            for arg in expr.args:
+                if _has_simple_delta(arg, index):
+                    return True
+    return False
+
+
+@cacheit
+def _is_simple_delta(delta, index):
+    """
+    Returns True if ``delta`` is a KroneckerDelta and is nonzero for a single
+    value of the index ``index``.
+    """
+    if isinstance(delta, KroneckerDelta) and delta.has(index):
+        p = (delta.args[0] - delta.args[1]).as_poly(index)
+        if p:
+            return p.degree() == 1
+    return False
+
+
+@cacheit
+def _remove_multiple_delta(expr):
+    """
+    Evaluate products of KroneckerDelta's.
+    """
+    if expr.is_Add:
+        return expr.func(*list(map(_remove_multiple_delta, expr.args)))
+    if not expr.is_Mul:
+        return expr
+    eqs = []
+    newargs = []
+    for arg in expr.args:
+        if isinstance(arg, KroneckerDelta):
+            eqs.append(arg.args[0] - arg.args[1])
+        else:
+            newargs.append(arg)
+    if not eqs:
+        return expr
+    solns = solve(eqs, dict=True)
+    if len(solns) == 0:
+        return S.Zero
+    elif len(solns) == 1:
+        for key in solns[0].keys():
+            newargs.append(KroneckerDelta(key, solns[0][key]))
+        expr2 = expr.func(*newargs)
+        if expr != expr2:
+            return _remove_multiple_delta(expr2)
+    return expr
+
+
+@cacheit
+def _simplify_delta(expr):
+    """
+    Rewrite a KroneckerDelta's indices in its simplest form.
+    """
+    if isinstance(expr, KroneckerDelta):
+        try:
+            slns = solve(expr.args[0] - expr.args[1], dict=True)
+            if slns and len(slns) == 1:
+                return Mul(*[KroneckerDelta(*(key, value))
+                            for key, value in slns[0].items()])
+        except NotImplementedError:
+            pass
+    return expr
+
+
+@cacheit
+def deltaproduct(f, limit):
+    """
+    Handle products containing a KroneckerDelta.
+
+    See Also
+    ========
+
+    deltasummation
+    sympy.functions.special.tensor_functions.KroneckerDelta
+    sympy.concrete.products.product
+    """
+    if ((limit[2] - limit[1]) < 0) == True:
+        return S.One
+
+    if not f.has(KroneckerDelta):
+        return product(f, limit)
+
+    if f.is_Add:
+        # Identify the term in the Add that has a simple KroneckerDelta
+        delta = None
+        terms = []
+        for arg in sorted(f.args, key=default_sort_key):
+            if delta is None and _has_simple_delta(arg, limit[0]):
+                delta = arg
+            else:
+                terms.append(arg)
+        newexpr = f.func(*terms)
+        k = Dummy("kprime", integer=True)
+        if isinstance(limit[1], int) and isinstance(limit[2], int):
+            result = deltaproduct(newexpr, limit) + sum([
+                deltaproduct(newexpr, (limit[0], limit[1], ik - 1)) *
+                delta.subs(limit[0], ik) *
+                deltaproduct(newexpr, (limit[0], ik + 1, limit[2])) for ik in range(int(limit[1]), int(limit[2] + 1))]
+            )
+        else:
+            result = deltaproduct(newexpr, limit) + deltasummation(
+                deltaproduct(newexpr, (limit[0], limit[1], k - 1)) *
+                delta.subs(limit[0], k) *
+                deltaproduct(newexpr, (limit[0], k + 1, limit[2])),
+                (k, limit[1], limit[2]),
+                no_piecewise=_has_simple_delta(newexpr, limit[0])
+            )
+        return _remove_multiple_delta(result)
+
+    delta, _ = _extract_delta(f, limit[0])
+
+    if not delta:
+        g = _expand_delta(f, limit[0])
+        if f != g:
+            try:
+                return factor(deltaproduct(g, limit))
+            except AssertionError:
+                return deltaproduct(g, limit)
+        return product(f, limit)
+
+    return _remove_multiple_delta(f.subs(limit[0], limit[1])*KroneckerDelta(limit[2], limit[1])) + \
+        S.One*_simplify_delta(KroneckerDelta(limit[2], limit[1] - 1))
+
+
+@cacheit
+def deltasummation(f, limit, no_piecewise=False):
+    """
+    Handle summations containing a KroneckerDelta.
+
+    Explanation
+    ===========
+
+    The idea for summation is the following:
+
+    - If we are dealing with a KroneckerDelta expression, i.e. KroneckerDelta(g(x), j),
+      we try to simplify it.
+
+      If we could simplify it, then we sum the resulting expression.
+      We already know we can sum a simplified expression, because only
+      simple KroneckerDelta expressions are involved.
+
+      If we could not simplify it, there are two cases:
+
+      1) The expression is a simple expression: we return the summation,
+         taking care if we are dealing with a Derivative or with a proper
+         KroneckerDelta.
+
+      2) The expression is not simple (i.e. KroneckerDelta(cos(x))): we can do
+         nothing at all.
+
+    - If the expr is a multiplication expr having a KroneckerDelta term:
+
+      First we expand it.
+
+      If the expansion did work, then we try to sum the expansion.
+
+      If not, we try to extract a simple KroneckerDelta term, then we have two
+      cases:
+
+      1) We have a simple KroneckerDelta term, so we return the summation.
+
+      2) We did not have a simple term, but we do have an expression with
+         simplified KroneckerDelta terms, so we sum this expression.
+
+    Examples
+    ========
+
+    >>> from sympy import oo, symbols
+    >>> from sympy.abc import k
+    >>> i, j = symbols('i, j', integer=True, finite=True)
+    >>> from sympy.concrete.delta import deltasummation
+    >>> from sympy import KroneckerDelta
+    >>> deltasummation(KroneckerDelta(i, k), (k, -oo, oo))
+    1
+    >>> deltasummation(KroneckerDelta(i, k), (k, 0, oo))
+    Piecewise((1, i >= 0), (0, True))
+    >>> deltasummation(KroneckerDelta(i, k), (k, 1, 3))
+    Piecewise((1, (i >= 1) & (i <= 3)), (0, True))
+    >>> deltasummation(k*KroneckerDelta(i, j)*KroneckerDelta(j, k), (k, -oo, oo))
+    j*KroneckerDelta(i, j)
+    >>> deltasummation(j*KroneckerDelta(i, j), (j, -oo, oo))
+    i
+    >>> deltasummation(i*KroneckerDelta(i, j), (i, -oo, oo))
+    j
+
+    See Also
+    ========
+
+    deltaproduct
+    sympy.functions.special.tensor_functions.KroneckerDelta
+    sympy.concrete.sums.summation
+    """
+    if ((limit[2] - limit[1]) < 0) == True:
+        return S.Zero
+
+    if not f.has(KroneckerDelta):
+        return summation(f, limit)
+
+    x = limit[0]
+
+    g = _expand_delta(f, x)
+    if g.is_Add:
+        return piecewise_fold(
+            g.func(*[deltasummation(h, limit, no_piecewise) for h in g.args]))
+
+    # try to extract a simple KroneckerDelta term
+    delta, expr = _extract_delta(g, x)
+
+    if (delta is not None) and (delta.delta_range is not None):
+        dinf, dsup = delta.delta_range
+        if (limit[1] - dinf <= 0) == True and (limit[2] - dsup >= 0) == True:
+            no_piecewise = True
+
+    if not delta:
+        return summation(f, limit)
+
+    solns = solve(delta.args[0] - delta.args[1], x)
+    if len(solns) == 0:
+        return S.Zero
+    elif len(solns) != 1:
+        return Sum(f, limit)
+    value = solns[0]
+    if no_piecewise:
+        return expr.subs(x, value)
+    return Piecewise(
+        (expr.subs(x, value), Interval(*limit[1:3]).as_relational(value)),
+        (S.Zero, True)
+    )

venv/lib/python3.10/site-packages/sympy/concrete/expr_with_intlimits.py

@@ -0,0 +1,354 @@
+from sympy.concrete.expr_with_limits import ExprWithLimits
+from sympy.core.singleton import S
+from sympy.core.relational import Eq
+
+class ReorderError(NotImplementedError):
+    """
+    Exception raised when trying to reorder dependent limits.
+    """
+    def __init__(self, expr, msg):
+        super().__init__(
+            "%s could not be reordered: %s." % (expr, msg))
+
+class ExprWithIntLimits(ExprWithLimits):
+    """
+    Superclass for Product and Sum.
+
+    See Also
+    ========
+
+    sympy.concrete.expr_with_limits.ExprWithLimits
+    sympy.concrete.products.Product
+    sympy.concrete.summations.Sum
+    """
+    __slots__ = ()
+
+    def change_index(self, var, trafo, newvar=None):
+        r"""
+        Change index of a Sum or Product.
+
+        Perform a linear transformation `x \mapsto a x + b` on the index variable
+        `x`. For `a` the only values allowed are `\pm 1`. A new variable to be used
+        after the change of index can also be specified.
+
+        Explanation
+        ===========
+
+        ``change_index(expr, var, trafo, newvar=None)`` where ``var`` specifies the
+        index variable `x` to transform. The transformation ``trafo`` must be linear
+        and given in terms of ``var``. If the optional argument ``newvar`` is
+        provided then ``var`` gets replaced by ``newvar`` in the final expression.
+
+        Examples
+        ========
+
+        >>> from sympy import Sum, Product, simplify
+        >>> from sympy.abc import x, y, a, b, c, d, u, v, i, j, k, l
+
+        >>> S = Sum(x, (x, a, b))
+        >>> S.doit()
+        -a**2/2 + a/2 + b**2/2 + b/2
+
+        >>> Sn = S.change_index(x, x + 1, y)
+        >>> Sn
+        Sum(y - 1, (y, a + 1, b + 1))
+        >>> Sn.doit()
+        -a**2/2 + a/2 + b**2/2 + b/2
+
+        >>> Sn = S.change_index(x, -x, y)
+        >>> Sn
+        Sum(-y, (y, -b, -a))
+        >>> Sn.doit()
+        -a**2/2 + a/2 + b**2/2 + b/2
+
+        >>> Sn = S.change_index(x, x+u)
+        >>> Sn
+        Sum(-u + x, (x, a + u, b + u))
+        >>> Sn.doit()
+        -a**2/2 - a*u + a/2 + b**2/2 + b*u + b/2 - u*(-a + b + 1) + u
+        >>> simplify(Sn.doit())
+        -a**2/2 + a/2 + b**2/2 + b/2
+
+        >>> Sn = S.change_index(x, -x - u, y)
+        >>> Sn
+        Sum(-u - y, (y, -b - u, -a - u))
+        >>> Sn.doit()
+        -a**2/2 - a*u + a/2 + b**2/2 + b*u + b/2 - u*(-a + b + 1) + u
+        >>> simplify(Sn.doit())
+        -a**2/2 + a/2 + b**2/2 + b/2
+
+        >>> P = Product(i*j**2, (i, a, b), (j, c, d))
+        >>> P
+        Product(i*j**2, (i, a, b), (j, c, d))
+        >>> P2 = P.change_index(i, i+3, k)
+        >>> P2
+        Product(j**2*(k - 3), (k, a + 3, b + 3), (j, c, d))
+        >>> P3 = P2.change_index(j, -j, l)
+        >>> P3
+        Product(l**2*(k - 3), (k, a + 3, b + 3), (l, -d, -c))
+
+        When dealing with symbols only, we can make a
+        general linear transformation:
+
+        >>> Sn = S.change_index(x, u*x+v, y)
+        >>> Sn
+        Sum((-v + y)/u, (y, b*u + v, a*u + v))
+        >>> Sn.doit()
+        -v*(a*u - b*u + 1)/u + (a**2*u**2/2 + a*u*v + a*u/2 - b**2*u**2/2 - b*u*v + b*u/2 + v)/u
+        >>> simplify(Sn.doit())
+        a**2*u/2 + a/2 - b**2*u/2 + b/2
+
+        However, the last result can be inconsistent with usual
+        summation where the index increment is always 1. This is
+        obvious as we get back the original value only for ``u``
+        equal +1 or -1.
+
+        See Also
+        ========
+
+        sympy.concrete.expr_with_intlimits.ExprWithIntLimits.index,
+        reorder_limit,
+        sympy.concrete.expr_with_intlimits.ExprWithIntLimits.reorder,
+        sympy.concrete.summations.Sum.reverse_order,
+        sympy.concrete.products.Product.reverse_order
+        """
+        if newvar is None:
+            newvar = var
+
+        limits = []
+        for limit in self.limits:
+            if limit[0] == var:
+                p = trafo.as_poly(var)
+                if p.degree() != 1:
+                    raise ValueError("Index transformation is not linear")
+                alpha = p.coeff_monomial(var)
+                beta = p.coeff_monomial(S.One)
+                if alpha.is_number:
+                    if alpha == S.One:
+                        limits.append((newvar, alpha*limit[1] + beta, alpha*limit[2] + beta))
+                    elif alpha == S.NegativeOne:
+                        limits.append((newvar, alpha*limit[2] + beta, alpha*limit[1] + beta))
+                    else:
+                        raise ValueError("Linear transformation results in non-linear summation stepsize")
+                else:
+                    # Note that the case of alpha being symbolic can give issues if alpha < 0.
+                    limits.append((newvar, alpha*limit[2] + beta, alpha*limit[1] + beta))
+            else:
+                limits.append(limit)
+
+        function = self.function.subs(var, (var - beta)/alpha)
+        function = function.subs(var, newvar)
+
+        return self.func(function, *limits)
+
+
+    def index(expr, x):
+        """
+        Return the index of a dummy variable in the list of limits.
+
+        Explanation
+        ===========
+
+        ``index(expr, x)``  returns the index of the dummy variable ``x`` in the
+        limits of ``expr``. Note that we start counting with 0 at the inner-most
+        limits tuple.
+
+        Examples
+        ========
+
+        >>> from sympy.abc import x, y, a, b, c, d
+        >>> from sympy import Sum, Product
+        >>> Sum(x*y, (x, a, b), (y, c, d)).index(x)
+        0
+        >>> Sum(x*y, (x, a, b), (y, c, d)).index(y)
+        1
+        >>> Product(x*y, (x, a, b), (y, c, d)).index(x)
+        0
+        >>> Product(x*y, (x, a, b), (y, c, d)).index(y)
+        1
+
+        See Also
+        ========
+
+        reorder_limit, reorder, sympy.concrete.summations.Sum.reverse_order,
+        sympy.concrete.products.Product.reverse_order
+        """
+        variables = [limit[0] for limit in expr.limits]
+
+        if variables.count(x) != 1:
+            raise ValueError(expr, "Number of instances of variable not equal to one")
+        else:
+            return variables.index(x)
+
+    def reorder(expr, *arg):
+        """
+        Reorder limits in a expression containing a Sum or a Product.
+
+        Explanation
+        ===========
+
+        ``expr.reorder(*arg)`` reorders the limits in the expression ``expr``
+        according to the list of tuples given by ``arg``. These tuples can
+        contain numerical indices or index variable names or involve both.
+
+        Examples
+        ========
+
+        >>> from sympy import Sum, Product
+        >>> from sympy.abc import x, y, z, a, b, c, d, e, f
+
+        >>> Sum(x*y, (x, a, b), (y, c, d)).reorder((x, y))
+        Sum(x*y, (y, c, d), (x, a, b))
+
+        >>> Sum(x*y*z, (x, a, b), (y, c, d), (z, e, f)).reorder((x, y), (x, z), (y, z))
+        Sum(x*y*z, (z, e, f), (y, c, d), (x, a, b))
+
+        >>> P = Product(x*y*z, (x, a, b), (y, c, d), (z, e, f))
+        >>> P.reorder((x, y), (x, z), (y, z))
+        Product(x*y*z, (z, e, f), (y, c, d), (x, a, b))
+
+        We can also select the index variables by counting them, starting
+        with the inner-most one:
+
+        >>> Sum(x**2, (x, a, b), (x, c, d)).reorder((0, 1))
+        Sum(x**2, (x, c, d), (x, a, b))
+
+        And of course we can mix both schemes:
+
+        >>> Sum(x*y, (x, a, b), (y, c, d)).reorder((y, x))
+        Sum(x*y, (y, c, d), (x, a, b))
+        >>> Sum(x*y, (x, a, b), (y, c, d)).reorder((y, 0))
+        Sum(x*y, (y, c, d), (x, a, b))
+
+        See Also
+        ========
+
+        reorder_limit, index, sympy.concrete.summations.Sum.reverse_order,
+        sympy.concrete.products.Product.reverse_order
+        """
+        new_expr = expr
+
+        for r in arg:
+            if len(r) != 2:
+                raise ValueError(r, "Invalid number of arguments")
+
+            index1 = r[0]
+            index2 = r[1]
+
+            if not isinstance(r[0], int):
+                index1 = expr.index(r[0])
+            if not isinstance(r[1], int):
+                index2 = expr.index(r[1])
+
+            new_expr = new_expr.reorder_limit(index1, index2)
+
+        return new_expr
+
+
+    def reorder_limit(expr, x, y):
+        """
+        Interchange two limit tuples of a Sum or Product expression.
+
+        Explanation
+        ===========
+
+        ``expr.reorder_limit(x, y)`` interchanges two limit tuples. The
+        arguments ``x`` and ``y`` are integers corresponding to the index
+        variables of the two limits which are to be interchanged. The
+        expression ``expr`` has to be either a Sum or a Product.
+
+        Examples
+        ========
+
+        >>> from sympy.abc import x, y, z, a, b, c, d, e, f
+        >>> from sympy import Sum, Product
+
+        >>> Sum(x*y*z, (x, a, b), (y, c, d), (z, e, f)).reorder_limit(0, 2)
+        Sum(x*y*z, (z, e, f), (y, c, d), (x, a, b))
+        >>> Sum(x**2, (x, a, b), (x, c, d)).reorder_limit(1, 0)
+        Sum(x**2, (x, c, d), (x, a, b))
+
+        >>> Product(x*y*z, (x, a, b), (y, c, d), (z, e, f)).reorder_limit(0, 2)
+        Product(x*y*z, (z, e, f), (y, c, d), (x, a, b))
+
+        See Also
+        ========
+
+        index, reorder, sympy.concrete.summations.Sum.reverse_order,
+        sympy.concrete.products.Product.reverse_order
+        """
+        var = {limit[0] for limit in expr.limits}
+        limit_x = expr.limits[x]
+        limit_y = expr.limits[y]
+
+        if (len(set(limit_x[1].free_symbols).intersection(var)) == 0 and
+            len(set(limit_x[2].free_symbols).intersection(var)) == 0 and
+            len(set(limit_y[1].free_symbols).intersection(var)) == 0 and
+            len(set(limit_y[2].free_symbols).intersection(var)) == 0):
+
+            limits = []
+            for i, limit in enumerate(expr.limits):
+                if i == x:
+                    limits.append(limit_y)
+                elif i == y:
+                    limits.append(limit_x)
+                else:
+                    limits.append(limit)
+
+            return type(expr)(expr.function, *limits)
+        else:
+            raise ReorderError(expr, "could not interchange the two limits specified")
+
+    @property
+    def has_empty_sequence(self):
+        """
+        Returns True if the Sum or Product is computed for an empty sequence.
+
+        Examples
+        ========
+
+        >>> from sympy import Sum, Product, Symbol
+        >>> m = Symbol('m')
+        >>> Sum(m, (m, 1, 0)).has_empty_sequence
+        True
+
+        >>> Sum(m, (m, 1, 1)).has_empty_sequence
+        False
+
+        >>> M = Symbol('M', integer=True, positive=True)
+        >>> Product(m, (m, 1, M)).has_empty_sequence
+        False
+
+        >>> Product(m, (m, 2, M)).has_empty_sequence
+
+        >>> Product(m, (m, M + 1, M)).has_empty_sequence
+        True
+
+        >>> N = Symbol('N', integer=True, positive=True)
+        >>> Sum(m, (m, N, M)).has_empty_sequence
+
+        >>> N = Symbol('N', integer=True, negative=True)
+        >>> Sum(m, (m, N, M)).has_empty_sequence
+        False
+
+        See Also
+        ========
+
+        has_reversed_limits
+        has_finite_limits
+
+        """
+        ret_None = False
+        for lim in self.limits:
+            dif = lim[1] - lim[2]
+            eq = Eq(dif, 1)
+            if eq == True:
+                return True
+            elif eq == False:
+                continue
+            else:
+                ret_None = True
+
+        if ret_None:
+            return None
+        return False

venv/lib/python3.10/site-packages/sympy/concrete/expr_with_limits.py

@@ -0,0 +1,603 @@
+from sympy.core.add import Add
+from sympy.core.containers import Tuple
+from sympy.core.expr import Expr
+from sympy.core.function import AppliedUndef, UndefinedFunction
+from sympy.core.mul import Mul
+from sympy.core.relational import Equality, Relational
+from sympy.core.singleton import S
+from sympy.core.symbol import Symbol, Dummy
+from sympy.core.sympify import sympify
+from sympy.functions.elementary.piecewise import (piecewise_fold,
+    Piecewise)
+from sympy.logic.boolalg import BooleanFunction
+from sympy.matrices.matrices import MatrixBase
+from sympy.sets.sets import Interval, Set
+from sympy.sets.fancysets import Range
+from sympy.tensor.indexed import Idx
+from sympy.utilities import flatten
+from sympy.utilities.iterables import sift, is_sequence
+from sympy.utilities.exceptions import sympy_deprecation_warning
+
+
+def _common_new(cls, function, *symbols, discrete, **assumptions):
+    """Return either a special return value or the tuple,
+    (function, limits, orientation). This code is common to
+    both ExprWithLimits and AddWithLimits."""
+    function = sympify(function)
+
+    if isinstance(function, Equality):
+        # This transforms e.g. Integral(Eq(x, y)) to Eq(Integral(x), Integral(y))
+        # but that is only valid for definite integrals.
+        limits, orientation = _process_limits(*symbols, discrete=discrete)
+        if not (limits and all(len(limit) == 3 for limit in limits)):
+            sympy_deprecation_warning(
+                """
+                Creating a indefinite integral with an Eq() argument is
+                deprecated.
+
+                This is because indefinite integrals do not preserve equality
+                due to the arbitrary constants. If you want an equality of
+                indefinite integrals, use Eq(Integral(a, x), Integral(b, x))
+                explicitly.
+                """,
+                deprecated_since_version="1.6",
+                active_deprecations_target="deprecated-indefinite-integral-eq",
+                stacklevel=5,
+            )
+
+        lhs = function.lhs
+        rhs = function.rhs
+        return Equality(cls(lhs, *symbols, **assumptions), \
+                        cls(rhs, *symbols, **assumptions))
+
+    if function is S.NaN:
+        return S.NaN
+
+    if symbols:
+        limits, orientation = _process_limits(*symbols, discrete=discrete)
+        for i, li in enumerate(limits):
+            if len(li) == 4:
+                function = function.subs(li[0], li[-1])
+                limits[i] = Tuple(*li[:-1])
+    else:
+        # symbol not provided -- we can still try to compute a general form
+        free = function.free_symbols
+        if len(free) != 1:
+            raise ValueError(
+                "specify dummy variables for %s" % function)
+        limits, orientation = [Tuple(s) for s in free], 1
+
+    # denest any nested calls
+    while cls == type(function):
+        limits = list(function.limits) + limits
+        function = function.function
+
+    # Any embedded piecewise functions need to be brought out to the
+    # top level. We only fold Piecewise that contain the integration
+    # variable.
+    reps = {}
+    symbols_of_integration = {i[0] for i in limits}
+    for p in function.atoms(Piecewise):
+        if not p.has(*symbols_of_integration):
+            reps[p] = Dummy()
+    # mask off those that don't
+    function = function.xreplace(reps)
+    # do the fold
+    function = piecewise_fold(function)
+    # remove the masking
+    function = function.xreplace({v: k for k, v in reps.items()})
+
+    return function, limits, orientation
+
+
+def _process_limits(*symbols, discrete=None):
+    """Process the list of symbols and convert them to canonical limits,
+    storing them as Tuple(symbol, lower, upper). The orientation of
+    the function is also returned when the upper limit is missing
+    so (x, 1, None) becomes (x, None, 1) and the orientation is changed.
+    In the case that a limit is specified as (symbol, Range), a list of
+    length 4 may be returned if a change of variables is needed; the
+    expression that should replace the symbol in the expression is
+    the fourth element in the list.
+    """
+    limits = []
+    orientation = 1
+    if discrete is None:
+        err_msg = 'discrete must be True or False'
+    elif discrete:
+        err_msg = 'use Range, not Interval or Relational'
+    else:
+        err_msg = 'use Interval or Relational, not Range'
+    for V in symbols:
+        if isinstance(V, (Relational, BooleanFunction)):
+            if discrete:
+                raise TypeError(err_msg)
+            variable = V.atoms(Symbol).pop()
+            V = (variable, V.as_set())
+        elif isinstance(V, Symbol) or getattr(V, '_diff_wrt', False):
+            if isinstance(V, Idx):
+                if V.lower is None or V.upper is None:
+                    limits.append(Tuple(V))
+                else:
+                    limits.append(Tuple(V, V.lower, V.upper))
+            else:
+                limits.append(Tuple(V))
+            continue
+        if is_sequence(V) and not isinstance(V, Set):
+            if len(V) == 2 and isinstance(V[1], Set):
+                V = list(V)
+                if isinstance(V[1], Interval):  # includes Reals
+                    if discrete:
+                        raise TypeError(err_msg)
+                    V[1:] = V[1].inf, V[1].sup
+                elif isinstance(V[1], Range):
+                    if not discrete:
+                        raise TypeError(err_msg)
+                    lo = V[1].inf
+                    hi = V[1].sup
+                    dx = abs(V[1].step)  # direction doesn't matter
+                    if dx == 1:
+                        V[1:] = [lo, hi]
+                    else:
+                        if lo is not S.NegativeInfinity:
+                            V = [V[0]] + [0, (hi - lo)//dx, dx*V[0] + lo]
+                        else:
+                            V = [V[0]] + [0, S.Infinity, -dx*V[0] + hi]
+                else:
+                    # more complicated sets would require splitting, e.g.
+                    # Union(Interval(1, 3), interval(6,10))
+                    raise NotImplementedError(
+                        'expecting Range' if discrete else
+                        'Relational or single Interval' )
+            V = sympify(flatten(V))  # list of sympified elements/None
+            if isinstance(V[0], (Symbol, Idx)) or getattr(V[0], '_diff_wrt', False):
+                newsymbol = V[0]
+                if len(V) == 3:
+                    # general case
+                    if V[2] is None and V[1] is not None:
+                        orientation *= -1
+                    V = [newsymbol] + [i for i in V[1:] if i is not None]
+
+                lenV = len(V)
+                if not isinstance(newsymbol, Idx) or lenV == 3:
+                    if lenV == 4:
+                        limits.append(Tuple(*V))
+                        continue
+                    if lenV == 3:
+                        if isinstance(newsymbol, Idx):
+                            # Idx represents an integer which may have
+                            # specified values it can take on; if it is
+                            # given such a value, an error is raised here
+                            # if the summation would try to give it a larger
+                            # or smaller value than permitted. None and Symbolic
+                            # values will not raise an error.
+                            lo, hi = newsymbol.lower, newsymbol.upper
+                            try:
+                                if lo is not None and not bool(V[1] >= lo):
+                                    raise ValueError("Summation will set Idx value too low.")
+                            except TypeError:
+                                pass
+                            try:
+                                if hi is not None and not bool(V[2] <= hi):
+                                    raise ValueError("Summation will set Idx value too high.")
+                            except TypeError:
+                                pass
+                        limits.append(Tuple(*V))
+                        continue
+                    if lenV == 1 or (lenV == 2 and V[1] is None):
+                        limits.append(Tuple(newsymbol))
+                        continue
+                    elif lenV == 2:
+                        limits.append(Tuple(newsymbol, V[1]))
+                        continue
+
+        raise ValueError('Invalid limits given: %s' % str(symbols))
+
+    return limits, orientation
+
+
+class ExprWithLimits(Expr):
+    __slots__ = ('is_commutative',)
+
+    def __new__(cls, function, *symbols, **assumptions):
+        from sympy.concrete.products import Product
+        pre = _common_new(cls, function, *symbols,
+            discrete=issubclass(cls, Product), **assumptions)
+        if isinstance(pre, tuple):
+            function, limits, _ = pre
+        else:
+            return pre
+
+        # limits must have upper and lower bounds; the indefinite form
+        # is not supported. This restriction does not apply to AddWithLimits
+        if any(len(l) != 3 or None in l for l in limits):
+            raise ValueError('ExprWithLimits requires values for lower and upper bounds.')
+
+        obj = Expr.__new__(cls, **assumptions)
+        arglist = [function]
+        arglist.extend(limits)
+        obj._args = tuple(arglist)
+        obj.is_commutative = function.is_commutative  # limits already checked
+
+        return obj
+
+    @property
+    def function(self):
+        """Return the function applied across limits.
+
+        Examples
+        ========
+
+        >>> from sympy import Integral
+        >>> from sympy.abc import x
+        >>> Integral(x**2, (x,)).function
+        x**2
+
+        See Also
+        ========
+
+        limits, variables, free_symbols
+        """
+        return self._args[0]
+
+    @property
+    def kind(self):
+        return self.function.kind
+
+    @property
+    def limits(self):
+        """Return the limits of expression.
+
+        Examples
+        ========
+
+        >>> from sympy import Integral
+        >>> from sympy.abc import x, i
+        >>> Integral(x**i, (i, 1, 3)).limits
+        ((i, 1, 3),)
+
+        See Also
+        ========
+
+        function, variables, free_symbols
+        """
+        return self._args[1:]
+
+    @property
+    def variables(self):
+        """Return a list of the limit variables.
+
+        >>> from sympy import Sum
+        >>> from sympy.abc import x, i
+        >>> Sum(x**i, (i, 1, 3)).variables
+        [i]
+
+        See Also
+        ========
+
+        function, limits, free_symbols
+        as_dummy : Rename dummy variables
+        sympy.integrals.integrals.Integral.transform : Perform mapping on the dummy variable
+        """
+        return [l[0] for l in self.limits]
+
+    @property
+    def bound_symbols(self):
+        """Return only variables that are dummy variables.
+
+        Examples
+        ========
+
+        >>> from sympy import Integral
+        >>> from sympy.abc import x, i, j, k
+        >>> Integral(x**i, (i, 1, 3), (j, 2), k).bound_symbols
+        [i, j]
+
+        See Also
+        ========
+
+        function, limits, free_symbols
+        as_dummy : Rename dummy variables
+        sympy.integrals.integrals.Integral.transform : Perform mapping on the dummy variable
+        """
+        return [l[0] for l in self.limits if len(l) != 1]
+
+    @property
+    def free_symbols(self):
+        """
+        This method returns the symbols in the object, excluding those
+        that take on a specific value (i.e. the dummy symbols).
+
+        Examples
+        ========
+
+        >>> from sympy import Sum
+        >>> from sympy.abc import x, y
+        >>> Sum(x, (x, y, 1)).free_symbols
+        {y}
+        """
+        # don't test for any special values -- nominal free symbols
+        # should be returned, e.g. don't return set() if the
+        # function is zero -- treat it like an unevaluated expression.
+        function, limits = self.function, self.limits
+        # mask off non-symbol integration variables that have
+        # more than themself as a free symbol
+        reps = {i[0]: i[0] if i[0].free_symbols == {i[0]} else Dummy()
+            for i in self.limits}
+        function = function.xreplace(reps)
+        isyms = function.free_symbols
+        for xab in limits:
+            v = reps[xab[0]]
+            if len(xab) == 1:
+                isyms.add(v)
+                continue
+            # take out the target symbol
+            if v in isyms:
+                isyms.remove(v)
+            # add in the new symbols
+            for i in xab[1:]:
+                isyms.update(i.free_symbols)
+        reps = {v: k for k, v in reps.items()}
+        return {reps.get(_, _) for _ in isyms}
+
+    @property
+    def is_number(self):
+        """Return True if the Sum has no free symbols, else False."""
+        return not self.free_symbols
+
+    def _eval_interval(self, x, a, b):
+        limits = [(i if i[0] != x else (x, a, b)) for i in self.limits]
+        integrand = self.function
+        return self.func(integrand, *limits)
+
+    def _eval_subs(self, old, new):
+        """
+        Perform substitutions over non-dummy variables
+        of an expression with limits.  Also, can be used
+        to specify point-evaluation of an abstract antiderivative.
+
+        Examples
+        ========
+
+        >>> from sympy import Sum, oo
+        >>> from sympy.abc import s, n
+        >>> Sum(1/n**s, (n, 1, oo)).subs(s, 2)
+        Sum(n**(-2), (n, 1, oo))
+
+        >>> from sympy import Integral
+        >>> from sympy.abc import x, a
+        >>> Integral(a*x**2, x).subs(x, 4)
+        Integral(a*x**2, (x, 4))
+
+        See Also
+        ========
+
+        variables : Lists the integration variables
+        transform : Perform mapping on the dummy variable for integrals
+        change_index : Perform mapping on the sum and product dummy variables
+
+        """
+        func, limits = self.function, list(self.limits)
+
+        # If one of the expressions we are replacing is used as a func index
+        # one of two things happens.
+        #   - the old variable first appears as a free variable
+        #     so we perform all free substitutions before it becomes
+        #     a func index.
+        #   - the old variable first appears as a func index, in
+        #     which case we ignore.  See change_index.
+
+        # Reorder limits to match standard mathematical practice for scoping
+        limits.reverse()
+
+        if not isinstance(old, Symbol) or \
+                old.free_symbols.intersection(self.free_symbols):
+            sub_into_func = True
+            for i, xab in enumerate(limits):
+                if 1 == len(xab) and old == xab[0]:
+                    if new._diff_wrt:
+                        xab = (new,)
+                    else:
+                        xab = (old, old)
+                limits[i] = Tuple(xab[0], *[l._subs(old, new) for l in xab[1:]])
+                if len(xab[0].free_symbols.intersection(old.free_symbols)) != 0:
+                    sub_into_func = False
+                    break
+            if isinstance(old, (AppliedUndef, UndefinedFunction)):
+                sy2 = set(self.variables).intersection(set(new.atoms(Symbol)))
+                sy1 = set(self.variables).intersection(set(old.args))
+                if not sy2.issubset(sy1):
+                    raise ValueError(
+                        "substitution cannot create dummy dependencies")
+                sub_into_func = True
+            if sub_into_func:
+                func = func.subs(old, new)
+        else:
+            # old is a Symbol and a dummy variable of some limit
+            for i, xab in enumerate(limits):
+                if len(xab) == 3:
+                    limits[i] = Tuple(xab[0], *[l._subs(old, new) for l in xab[1:]])
+                    if old == xab[0]:
+                        break
+        # simplify redundant limits (x, x)  to (x, )
+        for i, xab in enumerate(limits):
+            if len(xab) == 2 and (xab[0] - xab[1]).is_zero:
+                limits[i] = Tuple(xab[0], )
+
+        # Reorder limits back to representation-form
+        limits.reverse()
+
+        return self.func(func, *limits)
+
+    @property
+    def has_finite_limits(self):
+        """
+        Returns True if the limits are known to be finite, either by the
+        explicit bounds, assumptions on the bounds, or assumptions on the
+        variables.  False if known to be infinite, based on the bounds.
+        None if not enough information is available to determine.
+
+        Examples
+        ========
+
+        >>> from sympy import Sum, Integral, Product, oo, Symbol
+        >>> x = Symbol('x')
+        >>> Sum(x, (x, 1, 8)).has_finite_limits
+        True
+
+        >>> Integral(x, (x, 1, oo)).has_finite_limits
+        False
+
+        >>> M = Symbol('M')
+        >>> Sum(x, (x, 1, M)).has_finite_limits
+
+        >>> N = Symbol('N', integer=True)
+        >>> Product(x, (x, 1, N)).has_finite_limits
+        True
+
+        See Also
+        ========
+
+        has_reversed_limits
+
+        """
+
+        ret_None = False
+        for lim in self.limits:
+            if len(lim) == 3:
+                if any(l.is_infinite for l in lim[1:]):
+                    # Any of the bounds are +/-oo
+                    return False
+                elif any(l.is_infinite is None for l in lim[1:]):
+                    # Maybe there are assumptions on the variable?
+                    if lim[0].is_infinite is None:
+                        ret_None = True
+            else:
+                if lim[0].is_infinite is None:
+                    ret_None = True
+
+        if ret_None:
+            return None
+        return True
+
+    @property
+    def has_reversed_limits(self):
+        """
+        Returns True if the limits are known to be in reversed order, either
+        by the explicit bounds, assumptions on the bounds, or assumptions on the
+        variables.  False if known to be in normal order, based on the bounds.
+        None if not enough information is available to determine.
+
+        Examples
+        ========
+
+        >>> from sympy import Sum, Integral, Product, oo, Symbol
+        >>> x = Symbol('x')
+        >>> Sum(x, (x, 8, 1)).has_reversed_limits
+        True
+
+        >>> Sum(x, (x, 1, oo)).has_reversed_limits
+        False
+
+        >>> M = Symbol('M')
+        >>> Integral(x, (x, 1, M)).has_reversed_limits
+
+        >>> N = Symbol('N', integer=True, positive=True)
+        >>> Sum(x, (x, 1, N)).has_reversed_limits
+        False
+
+        >>> Product(x, (x, 2, N)).has_reversed_limits
+
+        >>> Product(x, (x, 2, N)).subs(N, N + 2).has_reversed_limits
+        False
+
+        See Also
+        ========
+
+        sympy.concrete.expr_with_intlimits.ExprWithIntLimits.has_empty_sequence
+
+        """
+        ret_None = False
+        for lim in self.limits:
+            if len(lim) == 3:
+                var, a, b = lim
+                dif = b - a
+                if dif.is_extended_negative:
+                    return True
+                elif dif.is_extended_nonnegative:
+                    continue
+                else:
+                    ret_None = True
+            else:
+                return None
+        if ret_None:
+            return None
+        return False
+
+
+class AddWithLimits(ExprWithLimits):
+    r"""Represents unevaluated oriented additions.
+        Parent class for Integral and Sum.
+    """
+
+    __slots__ = ()
+
+    def __new__(cls, function, *symbols, **assumptions):
+        from sympy.concrete.summations import Sum
+        pre = _common_new(cls, function, *symbols,
+            discrete=issubclass(cls, Sum), **assumptions)
+        if isinstance(pre, tuple):
+            function, limits, orientation = pre
+        else:
+            return pre
+
+        obj = Expr.__new__(cls, **assumptions)
+        arglist = [orientation*function]  # orientation not used in ExprWithLimits
+        arglist.extend(limits)
+        obj._args = tuple(arglist)
+        obj.is_commutative = function.is_commutative  # limits already checked
+
+        return obj
+
+    def _eval_adjoint(self):
+        if all(x.is_real for x in flatten(self.limits)):
+            return self.func(self.function.adjoint(), *self.limits)
+        return None
+
+    def _eval_conjugate(self):
+        if all(x.is_real for x in flatten(self.limits)):
+            return self.func(self.function.conjugate(), *self.limits)
+        return None
+
+    def _eval_transpose(self):
+        if all(x.is_real for x in flatten(self.limits)):
+            return self.func(self.function.transpose(), *self.limits)
+        return None
+
+    def _eval_factor(self, **hints):
+        if 1 == len(self.limits):
+            summand = self.function.factor(**hints)
+            if summand.is_Mul:
+                out = sift(summand.args, lambda w: w.is_commutative \
+                    and not set(self.variables) & w.free_symbols)
+                return Mul(*out[True])*self.func(Mul(*out[False]), \
+                    *self.limits)
+        else:
+            summand = self.func(self.function, *self.limits[0:-1]).factor()
+            if not summand.has(self.variables[-1]):
+                return self.func(1, [self.limits[-1]]).doit()*summand
+            elif isinstance(summand, Mul):
+                return self.func(summand, self.limits[-1]).factor()
+        return self
+
+    def _eval_expand_basic(self, **hints):
+        summand = self.function.expand(**hints)
+        force = hints.get('force', False)
+        if (summand.is_Add and (force or summand.is_commutative and
+                 self.has_finite_limits is not False)):
+            return Add(*[self.func(i, *self.limits) for i in summand.args])
+        elif isinstance(summand, MatrixBase):
+            return summand.applyfunc(lambda x: self.func(x, *self.limits))
+        elif summand != self.function:
+            return self.func(summand, *self.limits)
+        return self

venv/lib/python3.10/site-packages/sympy/concrete/gosper.py

@@ -0,0 +1,227 @@
+"""Gosper's algorithm for hypergeometric summation. """
+
+from sympy.core import S, Dummy, symbols
+from sympy.polys import Poly, parallel_poly_from_expr, factor
+from sympy.utilities.iterables import is_sequence
+
+
+def gosper_normal(f, g, n, polys=True):
+    r"""
+    Compute the Gosper's normal form of ``f`` and ``g``.
+
+    Explanation
+    ===========
+
+    Given relatively prime univariate polynomials ``f`` and ``g``,
+    rewrite their quotient to a normal form defined as follows:
+
+    .. math::
+        \frac{f(n)}{g(n)} = Z \cdot \frac{A(n) C(n+1)}{B(n) C(n)}
+
+    where ``Z`` is an arbitrary constant and ``A``, ``B``, ``C`` are
+    monic polynomials in ``n`` with the following properties:
+
+    1. `\gcd(A(n), B(n+h)) = 1 \forall h \in \mathbb{N}`
+    2. `\gcd(B(n), C(n+1)) = 1`
+    3. `\gcd(A(n), C(n)) = 1`
+
+    This normal form, or rational factorization in other words, is a
+    crucial step in Gosper's algorithm and in solving of difference
+    equations. It can be also used to decide if two hypergeometric
+    terms are similar or not.
+
+    This procedure will return a tuple containing elements of this
+    factorization in the form ``(Z*A, B, C)``.
+
+    Examples
+    ========
+
+    >>> from sympy.concrete.gosper import gosper_normal
+    >>> from sympy.abc import n
+
+    >>> gosper_normal(4*n+5, 2*(4*n+1)*(2*n+3), n, polys=False)
+    (1/4, n + 3/2, n + 1/4)
+
+    """
+    (p, q), opt = parallel_poly_from_expr(
+        (f, g), n, field=True, extension=True)
+
+    a, A = p.LC(), p.monic()
+    b, B = q.LC(), q.monic()
+
+    C, Z = A.one, a/b
+    h = Dummy('h')
+
+    D = Poly(n + h, n, h, domain=opt.domain)
+
+    R = A.resultant(B.compose(D))
+    roots = set(R.ground_roots().keys())
+
+    for r in set(roots):
+        if not r.is_Integer or r < 0:
+            roots.remove(r)
+
+    for i in sorted(roots):
+        d = A.gcd(B.shift(+i))
+
+        A = A.quo(d)
+        B = B.quo(d.shift(-i))
+
+        for j in range(1, i + 1):
+            C *= d.shift(-j)
+
+    A = A.mul_ground(Z)
+
+    if not polys:
+        A = A.as_expr()
+        B = B.as_expr()
+        C = C.as_expr()
+
+    return A, B, C
+
+
+def gosper_term(f, n):
+    r"""
+    Compute Gosper's hypergeometric term for ``f``.
+
+    Explanation
+    ===========
+
+    Suppose ``f`` is a hypergeometric term such that:
+
+    .. math::
+        s_n = \sum_{k=0}^{n-1} f_k
+
+    and `f_k` does not depend on `n`. Returns a hypergeometric
+    term `g_n` such that `g_{n+1} - g_n = f_n`.
+
+    Examples
+    ========
+
+    >>> from sympy.concrete.gosper import gosper_term
+    >>> from sympy import factorial
+    >>> from sympy.abc import n
+
+    >>> gosper_term((4*n + 1)*factorial(n)/factorial(2*n + 1), n)
+    (-n - 1/2)/(n + 1/4)
+
+    """
+    from sympy.simplify import hypersimp
+    r = hypersimp(f, n)
+
+    if r is None:
+        return None    # 'f' is *not* a hypergeometric term
+
+    p, q = r.as_numer_denom()
+
+    A, B, C = gosper_normal(p, q, n)
+    B = B.shift(-1)
+
+    N = S(A.degree())
+    M = S(B.degree())
+    K = S(C.degree())
+
+    if (N != M) or (A.LC() != B.LC()):
+        D = {K - max(N, M)}
+    elif not N:
+        D = {K - N + 1, S.Zero}
+    else:
+        D = {K - N + 1, (B.nth(N - 1) - A.nth(N - 1))/A.LC()}
+
+    for d in set(D):
+        if not d.is_Integer or d < 0:
+            D.remove(d)
+
+    if not D:
+        return None    # 'f(n)' is *not* Gosper-summable
+
+    d = max(D)
+
+    coeffs = symbols('c:%s' % (d + 1), cls=Dummy)
+    domain = A.get_domain().inject(*coeffs)
+
+    x = Poly(coeffs, n, domain=domain)
+    H = A*x.shift(1) - B*x - C
+
+    from sympy.solvers.solvers import solve
+    solution = solve(H.coeffs(), coeffs)
+
+    if solution is None:
+        return None    # 'f(n)' is *not* Gosper-summable
+
+    x = x.as_expr().subs(solution)
+
+    for coeff in coeffs:
+        if coeff not in solution:
+            x = x.subs(coeff, 0)
+
+    if x.is_zero:
+        return None    # 'f(n)' is *not* Gosper-summable
+    else:
+        return B.as_expr()*x/C.as_expr()
+
+
+def gosper_sum(f, k):
+    r"""
+    Gosper's hypergeometric summation algorithm.
+
+    Explanation
+    ===========
+
+    Given a hypergeometric term ``f`` such that:
+
+    .. math ::
+        s_n = \sum_{k=0}^{n-1} f_k
+
+    and `f(n)` does not depend on `n`, returns `g_{n} - g(0)` where
+    `g_{n+1} - g_n = f_n`, or ``None`` if `s_n` cannot be expressed
+    in closed form as a sum of hypergeometric terms.
+
+    Examples
+    ========
+
+    >>> from sympy.concrete.gosper import gosper_sum
+    >>> from sympy import factorial
+    >>> from sympy.abc import n, k
+
+    >>> f = (4*k + 1)*factorial(k)/factorial(2*k + 1)
+    >>> gosper_sum(f, (k, 0, n))
+    (-factorial(n) + 2*factorial(2*n + 1))/factorial(2*n + 1)
+    >>> _.subs(n, 2) == sum(f.subs(k, i) for i in [0, 1, 2])
+    True
+    >>> gosper_sum(f, (k, 3, n))
+    (-60*factorial(n) + factorial(2*n + 1))/(60*factorial(2*n + 1))
+    >>> _.subs(n, 5) == sum(f.subs(k, i) for i in [3, 4, 5])
+    True
+
+    References
+    ==========
+
+    .. [1] Marko Petkovsek, Herbert S. Wilf, Doron Zeilberger, A = B,
+           AK Peters, Ltd., Wellesley, MA, USA, 1997, pp. 73--100
+
+    """
+    indefinite = False
+
+    if is_sequence(k):
+        k, a, b = k
+    else:
+        indefinite = True
+
+    g = gosper_term(f, k)
+
+    if g is None:
+        return None
+
+    if indefinite:
+        result = f*g
+    else:
+        result = (f*(g + 1)).subs(k, b) - (f*g).subs(k, a)
+
+        if result is S.NaN:
+            try:
+                result = (f*(g + 1)).limit(k, b) - (f*g).limit(k, a)
+            except NotImplementedError:
+                result = None
+
+    return factor(result)

venv/lib/python3.10/site-packages/sympy/concrete/guess.py

@@ -0,0 +1,473 @@
+"""Various algorithms for helping identifying numbers and sequences."""
+
+
+from sympy.concrete.products import (Product, product)
+from sympy.core import Function, S
+from sympy.core.add import Add
+from sympy.core.numbers import Integer, Rational
+from sympy.core.symbol import Symbol, symbols
+from sympy.core.sympify import sympify
+from sympy.functions.elementary.exponential import exp
+from sympy.functions.elementary.integers import floor
+from sympy.integrals.integrals import integrate
+from sympy.polys.polyfuncs import rational_interpolate as rinterp
+from sympy.polys.polytools import lcm
+from sympy.simplify.radsimp import denom
+from sympy.utilities import public
+
+
+@public
+def find_simple_recurrence_vector(l):
+    """
+    This function is used internally by other functions from the
+    sympy.concrete.guess module. While most users may want to rather use the
+    function find_simple_recurrence when looking for recurrence relations
+    among rational numbers, the current function may still be useful when
+    some post-processing has to be done.
+
+    Explanation
+    ===========
+
+    The function returns a vector of length n when a recurrence relation of
+    order n is detected in the sequence of rational numbers v.
+
+    If the returned vector has a length 1, then the returned value is always
+    the list [0], which means that no relation has been found.
+
+    While the functions is intended to be used with rational numbers, it should
+    work for other kinds of real numbers except for some cases involving
+    quadratic numbers; for that reason it should be used with some caution when
+    the argument is not a list of rational numbers.
+
+    Examples
+    ========
+
+    >>> from sympy.concrete.guess import find_simple_recurrence_vector
+    >>> from sympy import fibonacci
+    >>> find_simple_recurrence_vector([fibonacci(k) for k in range(12)])
+    [1, -1, -1]
+
+    See Also
+    ========
+
+    See the function sympy.concrete.guess.find_simple_recurrence which is more
+    user-friendly.
+
+    """
+    q1 = [0]
+    q2 = [1]
+    b, z = 0, len(l) >> 1
+    while len(q2) <= z:
+        while l[b]==0:
+            b += 1
+            if b == len(l):
+                c = 1
+                for x in q2:
+                    c = lcm(c, denom(x))
+                if q2[0]*c < 0: c = -c
+                for k in range(len(q2)):
+                    q2[k] = int(q2[k]*c)
+                return q2
+        a = S.One/l[b]
+        m = [a]
+        for k in range(b+1, len(l)):
+            m.append(-sum(l[j+1]*m[b-j-1] for j in range(b, k))*a)
+        l, m = m, [0] * max(len(q2), b+len(q1))
+        for k, q in enumerate(q2):
+            m[k] = a*q
+        for k, q in enumerate(q1):
+            m[k+b] += q
+        while m[-1]==0: m.pop() # because trailing zeros can occur
+        q1, q2, b = q2, m, 1
+    return [0]
+
+@public
+def find_simple_recurrence(v, A=Function('a'), N=Symbol('n')):
+    """
+    Detects and returns a recurrence relation from a sequence of several integer
+    (or rational) terms. The name of the function in the returned expression is
+    'a' by default; the main variable is 'n' by default. The smallest index in
+    the returned expression is always n (and never n-1, n-2, etc.).
+
+    Examples
+    ========
+
+    >>> from sympy.concrete.guess import find_simple_recurrence
+    >>> from sympy import fibonacci
+    >>> find_simple_recurrence([fibonacci(k) for k in range(12)])
+    -a(n) - a(n + 1) + a(n + 2)
+
+    >>> from sympy import Function, Symbol
+    >>> a = [1, 1, 1]
+    >>> for k in range(15): a.append(5*a[-1]-3*a[-2]+8*a[-3])
+    >>> find_simple_recurrence(a, A=Function('f'), N=Symbol('i'))
+    -8*f(i) + 3*f(i + 1) - 5*f(i + 2) + f(i + 3)
+
+    """
+    p = find_simple_recurrence_vector(v)
+    n = len(p)
+    if n <= 1: return S.Zero
+
+    return Add(*[A(N+n-1-k)*p[k] for k in range(n)])
+
+
+@public
+def rationalize(x, maxcoeff=10000):
+    """
+    Helps identifying a rational number from a float (or mpmath.mpf) value by
+    using a continued fraction. The algorithm stops as soon as a large partial
+    quotient is detected (greater than 10000 by default).
+
+    Examples
+    ========
+
+    >>> from sympy.concrete.guess import rationalize
+    >>> from mpmath import cos, pi
+    >>> rationalize(cos(pi/3))
+    1/2
+
+    >>> from mpmath import mpf
+    >>> rationalize(mpf("0.333333333333333"))
+    1/3
+
+    While the function is rather intended to help 'identifying' rational
+    values, it may be used in some cases for approximating real numbers.
+    (Though other functions may be more relevant in that case.)
+
+    >>> rationalize(pi, maxcoeff = 250)
+    355/113
+
+    See Also
+    ========
+
+    Several other methods can approximate a real number as a rational, like:
+
+      * fractions.Fraction.from_decimal
+      * fractions.Fraction.from_float
+      * mpmath.identify
+      * mpmath.pslq by using the following syntax: mpmath.pslq([x, 1])
+      * mpmath.findpoly by using the following syntax: mpmath.findpoly(x, 1)
+      * sympy.simplify.nsimplify (which is a more general function)
+
+    The main difference between the current function and all these variants is
+    that control focuses on magnitude of partial quotients here rather than on
+    global precision of the approximation. If the real is "known to be" a
+    rational number, the current function should be able to detect it correctly
+    with the default settings even when denominator is great (unless its
+    expansion contains unusually big partial quotients) which may occur
+    when studying sequences of increasing numbers. If the user cares more
+    on getting simple fractions, other methods may be more convenient.
+
+    """
+    p0, p1 = 0, 1
+    q0, q1 = 1, 0
+    a = floor(x)
+    while a < maxcoeff or q1==0:
+        p = a*p1 + p0
+        q = a*q1 + q0
+        p0, p1 = p1, p
+        q0, q1 = q1, q
+        if x==a: break
+        x = 1/(x-a)
+        a = floor(x)
+    return sympify(p) / q
+
+
+@public
+def guess_generating_function_rational(v, X=Symbol('x')):
+    """
+    Tries to "guess" a rational generating function for a sequence of rational
+    numbers v.
+
+    Examples
+    ========
+
+    >>> from sympy.concrete.guess import guess_generating_function_rational
+    >>> from sympy import fibonacci
+    >>> l = [fibonacci(k) for k in range(5,15)]
+    >>> guess_generating_function_rational(l)
+    (3*x + 5)/(-x**2 - x + 1)
+
+    See Also
+    ========
+
+    sympy.series.approximants
+    mpmath.pade
+
+    """
+    #   a) compute the denominator as q
+    q = find_simple_recurrence_vector(v)
+    n = len(q)
+    if n <= 1: return None
+    #   b) compute the numerator as p
+    p = [sum(v[i-k]*q[k] for k in range(min(i+1, n)))
+            for i in range(len(v)>>1)]
+    return (sum(p[k]*X**k for k in range(len(p)))
+            / sum(q[k]*X**k for k in range(n)))
+
+
+@public
+def guess_generating_function(v, X=Symbol('x'), types=['all'], maxsqrtn=2):
+    """
+    Tries to "guess" a generating function for a sequence of rational numbers v.
+    Only a few patterns are implemented yet.
+
+    Explanation
+    ===========
+
+    The function returns a dictionary where keys are the name of a given type of
+    generating function. Six types are currently implemented:
+
+         type  |  formal definition
+        -------+----------------------------------------------------------------
+        ogf    | f(x) = Sum(            a_k * x^k       ,  k: 0..infinity )
+        egf    | f(x) = Sum(            a_k * x^k / k!  ,  k: 0..infinity )
+        lgf    | f(x) = Sum( (-1)^(k+1) a_k * x^k / k   ,  k: 1..infinity )
+               |        (with initial index being hold as 1 rather than 0)
+        hlgf   | f(x) = Sum(            a_k * x^k / k   ,  k: 1..infinity )
+               |        (with initial index being hold as 1 rather than 0)
+        lgdogf | f(x) = derivate( log(Sum( a_k * x^k, k: 0..infinity )), x)
+        lgdegf | f(x) = derivate( log(Sum( a_k * x^k / k!, k: 0..infinity )), x)
+
+    In order to spare time, the user can select only some types of generating
+    functions (default being ['all']). While forgetting to use a list in the
+    case of a single type may seem to work most of the time as in: types='ogf'
+    this (convenient) syntax may lead to unexpected extra results in some cases.
+
+    Discarding a type when calling the function does not mean that the type will
+    not be present in the returned dictionary; it only means that no extra
+    computation will be performed for that type, but the function may still add
+    it in the result when it can be easily converted from another type.
+
+    Two generating functions (lgdogf and lgdegf) are not even computed if the
+    initial term of the sequence is 0; it may be useful in that case to try
+    again after having removed the leading zeros.
+
+    Examples
+    ========
+
+    >>> from sympy.concrete.guess import guess_generating_function as ggf
+    >>> ggf([k+1 for k in range(12)], types=['ogf', 'lgf', 'hlgf'])
+    {'hlgf': 1/(1 - x), 'lgf': 1/(x + 1), 'ogf': 1/(x**2 - 2*x + 1)}
+
+    >>> from sympy import sympify
+    >>> l = sympify("[3/2, 11/2, 0, -121/2, -363/2, 121]")
+    >>> ggf(l)
+    {'ogf': (x + 3/2)/(11*x**2 - 3*x + 1)}
+
+    >>> from sympy import fibonacci
+    >>> ggf([fibonacci(k) for k in range(5, 15)], types=['ogf'])
+    {'ogf': (3*x + 5)/(-x**2 - x + 1)}
+
+    >>> from sympy import factorial
+    >>> ggf([factorial(k) for k in range(12)], types=['ogf', 'egf', 'lgf'])
+    {'egf': 1/(1 - x)}
+
+    >>> ggf([k+1 for k in range(12)], types=['egf'])
+    {'egf': (x + 1)*exp(x), 'lgdegf': (x + 2)/(x + 1)}
+
+    N-th root of a rational function can also be detected (below is an example
+    coming from the sequence A108626 from https://oeis.org).
+    The greatest n-th root to be tested is specified as maxsqrtn (default 2).
+
+    >>> ggf([1, 2, 5, 14, 41, 124, 383, 1200, 3799, 12122, 38919])['ogf']
+    sqrt(1/(x**4 + 2*x**2 - 4*x + 1))
+
+    References
+    ==========
+
+    .. [1] "Concrete Mathematics", R.L. Graham, D.E. Knuth, O. Patashnik
+    .. [2] https://oeis.org/wiki/Generating_functions
+
+    """
+    # List of all types of all g.f. known by the algorithm
+    if 'all' in types:
+        types = ('ogf', 'egf', 'lgf', 'hlgf', 'lgdogf', 'lgdegf')
+
+    result = {}
+
+    # Ordinary Generating Function (ogf)
+    if 'ogf' in types:
+        # Perform some convolutions of the sequence with itself
+        t = [1] + [0]*(len(v) - 1)
+        for d in range(max(1, maxsqrtn)):
+            t = [sum(t[n-i]*v[i] for i in range(n+1)) for n in range(len(v))]
+            g = guess_generating_function_rational(t, X=X)
+            if g:
+                result['ogf'] = g**Rational(1, d+1)
+                break
+
+    # Exponential Generating Function (egf)
+    if 'egf' in types:
+        # Transform sequence (division by factorial)
+        w, f = [], S.One
+        for i, k in enumerate(v):
+            f *= i if i else 1
+            w.append(k/f)
+        # Perform some convolutions of the sequence with itself
+        t = [1] + [0]*(len(w) - 1)
+        for d in range(max(1, maxsqrtn)):
+            t = [sum(t[n-i]*w[i] for i in range(n+1)) for n in range(len(w))]
+            g = guess_generating_function_rational(t, X=X)
+            if g:
+                result['egf'] = g**Rational(1, d+1)
+                break
+
+    # Logarithmic Generating Function (lgf)
+    if 'lgf' in types:
+        # Transform sequence (multiplication by (-1)^(n+1) / n)
+        w, f = [], S.NegativeOne
+        for i, k in enumerate(v):
+            f = -f
+            w.append(f*k/Integer(i+1))
+        # Perform some convolutions of the sequence with itself
+        t = [1] + [0]*(len(w) - 1)
+        for d in range(max(1, maxsqrtn)):
+            t = [sum(t[n-i]*w[i] for i in range(n+1)) for n in range(len(w))]
+            g = guess_generating_function_rational(t, X=X)
+            if g:
+                result['lgf'] = g**Rational(1, d+1)
+                break
+
+    # Hyperbolic logarithmic Generating Function (hlgf)
+    if 'hlgf' in types:
+        # Transform sequence (division by n+1)
+        w = []
+        for i, k in enumerate(v):
+            w.append(k/Integer(i+1))
+        # Perform some convolutions of the sequence with itself
+        t = [1] + [0]*(len(w) - 1)
+        for d in range(max(1, maxsqrtn)):
+            t = [sum(t[n-i]*w[i] for i in range(n+1)) for n in range(len(w))]
+            g = guess_generating_function_rational(t, X=X)
+            if g:
+                result['hlgf'] = g**Rational(1, d+1)
+                break
+
+    # Logarithmic derivative of ordinary generating Function (lgdogf)
+    if v[0] != 0 and ('lgdogf' in types
+                       or ('ogf' in types and 'ogf' not in result)):
+        # Transform sequence by computing f'(x)/f(x)
+        # because log(f(x)) = integrate( f'(x)/f(x) )
+        a, w = sympify(v[0]), []
+        for n in range(len(v)-1):
+            w.append(
+               (v[n+1]*(n+1) - sum(w[-i-1]*v[i+1] for i in range(n)))/a)
+        # Perform some convolutions of the sequence with itself
+        t = [1] + [0]*(len(w) - 1)
+        for d in range(max(1, maxsqrtn)):
+            t = [sum(t[n-i]*w[i] for i in range(n+1)) for n in range(len(w))]
+            g = guess_generating_function_rational(t, X=X)
+            if g:
+                result['lgdogf'] = g**Rational(1, d+1)
+                if 'ogf' not in result:
+                    result['ogf'] = exp(integrate(result['lgdogf'], X))
+                break
+
+    # Logarithmic derivative of exponential generating Function (lgdegf)
+    if v[0] != 0 and ('lgdegf' in types
+                       or ('egf' in types and 'egf' not in result)):
+        # Transform sequence / step 1 (division by factorial)
+        z, f = [], S.One
+        for i, k in enumerate(v):
+            f *= i if i else 1
+            z.append(k/f)
+        # Transform sequence / step 2 by computing f'(x)/f(x)
+        # because log(f(x)) = integrate( f'(x)/f(x) )
+        a, w = z[0], []
+        for n in range(len(z)-1):
+            w.append(
+               (z[n+1]*(n+1) - sum(w[-i-1]*z[i+1] for i in range(n)))/a)
+        # Perform some convolutions of the sequence with itself
+        t = [1] + [0]*(len(w) - 1)
+        for d in range(max(1, maxsqrtn)):
+            t = [sum(t[n-i]*w[i] for i in range(n+1)) for n in range(len(w))]
+            g = guess_generating_function_rational(t, X=X)
+            if g:
+                result['lgdegf'] = g**Rational(1, d+1)
+                if 'egf' not in result:
+                    result['egf'] = exp(integrate(result['lgdegf'], X))
+                break
+
+    return result
+
+
+@public
+def guess(l, all=False, evaluate=True, niter=2, variables=None):
+    """
+    This function is adapted from the Rate.m package for Mathematica
+    written by Christian Krattenthaler.
+    It tries to guess a formula from a given sequence of rational numbers.
+
+    Explanation
+    ===========
+
+    In order to speed up the process, the 'all' variable is set to False by
+    default, stopping the computation as some results are returned during an
+    iteration; the variable can be set to True if more iterations are needed
+    (other formulas may be found; however they may be equivalent to the first
+    ones).
+
+    Another option is the 'evaluate' variable (default is True); setting it
+    to False will leave the involved products unevaluated.
+
+    By default, the number of iterations is set to 2 but a greater value (up
+    to len(l)-1) can be specified with the optional 'niter' variable.
+    More and more convoluted results are found when the order of the
+    iteration gets higher:
+
+      * first iteration returns polynomial or rational functions;
+      * second iteration returns products of rising factorials and their
+        inverses;
+      * third iteration returns products of products of rising factorials
+        and their inverses;
+      * etc.
+
+    The returned formulas contain symbols i0, i1, i2, ... where the main
+    variables is i0 (and auxiliary variables are i1, i2, ...). A list of
+    other symbols can be provided in the 'variables' option; the length of
+    the least should be the value of 'niter' (more is acceptable but only
+    the first symbols will be used); in this case, the main variable will be
+    the first symbol in the list.
+
+    Examples
+    ========
+
+    >>> from sympy.concrete.guess import guess
+    >>> guess([1,2,6,24,120], evaluate=False)
+    [Product(i1 + 1, (i1, 1, i0 - 1))]
+
+    >>> from sympy import symbols
+    >>> r = guess([1,2,7,42,429,7436,218348,10850216], niter=4)
+    >>> i0 = symbols("i0")
+    >>> [r[0].subs(i0,n).doit() for n in range(1,10)]
+    [1, 2, 7, 42, 429, 7436, 218348, 10850216, 911835460]
+    """
+    if any(a==0 for a in l[:-1]):
+        return []
+    N = len(l)
+    niter = min(N-1, niter)
+    myprod = product if evaluate else Product
+    g = []
+    res = []
+    if variables is None:
+        symb = symbols('i:'+str(niter))
+    else:
+        symb = variables
+    for k, s in enumerate(symb):
+        g.append(l)
+        n, r = len(l), []
+        for i in range(n-2-1, -1, -1):
+            ri = rinterp(enumerate(g[k][:-1], start=1), i, X=s)
+            if ((denom(ri).subs({s:n}) != 0)
+                    and (ri.subs({s:n}) - g[k][-1] == 0)
+                    and ri not in r):
+              r.append(ri)
+        if r:
+            for i in range(k-1, -1, -1):
+                r = [g[i][0]
+                      * myprod(v, (symb[i+1], 1, symb[i]-1)) for v in r]
+            if not all: return r
+            res += r
+        l = [Rational(l[i+1], l[i]) for i in range(N-k-1)]
+    return res

venv/lib/python3.10/site-packages/sympy/concrete/products.py

@@ -0,0 +1,610 @@
+from typing import Tuple as tTuple
+
+from .expr_with_intlimits import ExprWithIntLimits
+from .summations import Sum, summation, _dummy_with_inherited_properties_concrete
+from sympy.core.expr import Expr
+from sympy.core.exprtools import factor_terms
+from sympy.core.function import Derivative
+from sympy.core.mul import Mul
+from sympy.core.singleton import S
+from sympy.core.symbol import Dummy, Symbol
+from sympy.functions.combinatorial.factorials import RisingFactorial
+from sympy.functions.elementary.exponential import exp, log
+from sympy.functions.special.tensor_functions import KroneckerDelta
+from sympy.polys import quo, roots
+
+
+class Product(ExprWithIntLimits):
+    r"""
+    Represents unevaluated products.
+
+    Explanation
+    ===========
+
+    ``Product`` represents a finite or infinite product, with the first
+    argument being the general form of terms in the series, and the second
+    argument being ``(dummy_variable, start, end)``, with ``dummy_variable``
+    taking all integer values from ``start`` through ``end``. In accordance
+    with long-standing mathematical convention, the end term is included in
+    the product.
+
+    Finite products
+    ===============
+
+    For finite products (and products with symbolic limits assumed to be finite)
+    we follow the analogue of the summation convention described by Karr [1],
+    especially definition 3 of section 1.4. The product:
+
+    .. math::
+
+        \prod_{m \leq i < n} f(i)
+
+    has *the obvious meaning* for `m < n`, namely:
+
+    .. math::
+
+        \prod_{m \leq i < n} f(i) = f(m) f(m+1) \cdot \ldots \cdot f(n-2) f(n-1)
+
+    with the upper limit value `f(n)` excluded. The product over an empty set is
+    one if and only if `m = n`:
+
+    .. math::
+
+        \prod_{m \leq i < n} f(i) = 1  \quad \mathrm{for} \quad  m = n
+
+    Finally, for all other products over empty sets we assume the following
+    definition:
+
+    .. math::
+
+        \prod_{m \leq i < n} f(i) = \frac{1}{\prod_{n \leq i < m} f(i)}  \quad \mathrm{for} \quad  m > n
+
+    It is important to note that above we define all products with the upper
+    limit being exclusive. This is in contrast to the usual mathematical notation,
+    but does not affect the product convention. Indeed we have:
+
+    .. math::
+
+        \prod_{m \leq i < n} f(i) = \prod_{i = m}^{n - 1} f(i)
+
+    where the difference in notation is intentional to emphasize the meaning,
+    with limits typeset on the top being inclusive.
+
+    Examples
+    ========
+
+    >>> from sympy.abc import a, b, i, k, m, n, x
+    >>> from sympy import Product, oo
+    >>> Product(k, (k, 1, m))
+    Product(k, (k, 1, m))
+    >>> Product(k, (k, 1, m)).doit()
+    factorial(m)
+    >>> Product(k**2,(k, 1, m))
+    Product(k**2, (k, 1, m))
+    >>> Product(k**2,(k, 1, m)).doit()
+    factorial(m)**2
+
+    Wallis' product for pi:
+
+    >>> W = Product(2*i/(2*i-1) * 2*i/(2*i+1), (i, 1, oo))
+    >>> W
+    Product(4*i**2/((2*i - 1)*(2*i + 1)), (i, 1, oo))
+
+    Direct computation currently fails:
+
+    >>> W.doit()
+    Product(4*i**2/((2*i - 1)*(2*i + 1)), (i, 1, oo))
+
+    But we can approach the infinite product by a limit of finite products:
+
+    >>> from sympy import limit
+    >>> W2 = Product(2*i/(2*i-1)*2*i/(2*i+1), (i, 1, n))
+    >>> W2
+    Product(4*i**2/((2*i - 1)*(2*i + 1)), (i, 1, n))
+    >>> W2e = W2.doit()
+    >>> W2e
+    4**n*factorial(n)**2/(2**(2*n)*RisingFactorial(1/2, n)*RisingFactorial(3/2, n))
+    >>> limit(W2e, n, oo)
+    pi/2
+
+    By the same formula we can compute sin(pi/2):
+
+    >>> from sympy import combsimp, pi, gamma, simplify
+    >>> P = pi * x * Product(1 - x**2/k**2, (k, 1, n))
+    >>> P = P.subs(x, pi/2)
+    >>> P
+    pi**2*Product(1 - pi**2/(4*k**2), (k, 1, n))/2
+    >>> Pe = P.doit()
+    >>> Pe
+    pi**2*RisingFactorial(1 - pi/2, n)*RisingFactorial(1 + pi/2, n)/(2*factorial(n)**2)
+    >>> limit(Pe, n, oo).gammasimp()
+    sin(pi**2/2)
+    >>> Pe.rewrite(gamma)
+    (-1)**n*pi**2*gamma(pi/2)*gamma(n + 1 + pi/2)/(2*gamma(1 + pi/2)*gamma(-n + pi/2)*gamma(n + 1)**2)
+
+    Products with the lower limit being larger than the upper one:
+
+    >>> Product(1/i, (i, 6, 1)).doit()
+    120
+    >>> Product(i, (i, 2, 5)).doit()
+    120
+
+    The empty product:
+
+    >>> Product(i, (i, n, n-1)).doit()
+    1
+
+    An example showing that the symbolic result of a product is still
+    valid for seemingly nonsensical values of the limits. Then the Karr
+    convention allows us to give a perfectly valid interpretation to
+    those products by interchanging the limits according to the above rules:
+
+    >>> P = Product(2, (i, 10, n)).doit()
+    >>> P
+    2**(n - 9)
+    >>> P.subs(n, 5)
+    1/16
+    >>> Product(2, (i, 10, 5)).doit()
+    1/16
+    >>> 1/Product(2, (i, 6, 9)).doit()
+    1/16
+
+    An explicit example of the Karr summation convention applied to products:
+
+    >>> P1 = Product(x, (i, a, b)).doit()
+    >>> P1
+    x**(-a + b + 1)
+    >>> P2 = Product(x, (i, b+1, a-1)).doit()
+    >>> P2
+    x**(a - b - 1)
+    >>> simplify(P1 * P2)
+    1
+
+    And another one:
+
+    >>> P1 = Product(i, (i, b, a)).doit()
+    >>> P1
+    RisingFactorial(b, a - b + 1)
+    >>> P2 = Product(i, (i, a+1, b-1)).doit()
+    >>> P2
+    RisingFactorial(a + 1, -a + b - 1)
+    >>> P1 * P2
+    RisingFactorial(b, a - b + 1)*RisingFactorial(a + 1, -a + b - 1)
+    >>> combsimp(P1 * P2)
+    1
+
+    See Also
+    ========
+
+    Sum, summation
+    product
+
+    References
+    ==========
+
+    .. [1] Michael Karr, "Summation in Finite Terms", Journal of the ACM,
+           Volume 28 Issue 2, April 1981, Pages 305-350
+           https://dl.acm.org/doi/10.1145/322248.322255
+    .. [2] https://en.wikipedia.org/wiki/Multiplication#Capital_Pi_notation
+    .. [3] https://en.wikipedia.org/wiki/Empty_product
+    """
+
+    __slots__ = ()
+
+    limits: tTuple[tTuple[Symbol, Expr, Expr]]
+
+    def __new__(cls, function, *symbols, **assumptions):
+        obj = ExprWithIntLimits.__new__(cls, function, *symbols, **assumptions)
+        return obj
+
+    def _eval_rewrite_as_Sum(self, *args, **kwargs):
+        return exp(Sum(log(self.function), *self.limits))
+
+    @property
+    def term(self):
+        return self._args[0]
+    function = term
+
+    def _eval_is_zero(self):
+        if self.has_empty_sequence:
+            return False
+
+        z = self.term.is_zero
+        if z is True:
+            return True
+        if self.has_finite_limits:
+            # A Product is zero only if its term is zero assuming finite limits.
+            return z
+
+    def _eval_is_extended_real(self):
+        if self.has_empty_sequence:
+            return True
+
+        return self.function.is_extended_real
+
+    def _eval_is_positive(self):
+        if self.has_empty_sequence:
+            return True
+        if self.function.is_positive and self.has_finite_limits:
+            return True
+
+    def _eval_is_nonnegative(self):
+        if self.has_empty_sequence:
+            return True
+        if self.function.is_nonnegative and self.has_finite_limits:
+            return True
+
+    def _eval_is_extended_nonnegative(self):
+        if self.has_empty_sequence:
+            return True
+        if self.function.is_extended_nonnegative:
+            return True
+
+    def _eval_is_extended_nonpositive(self):
+        if self.has_empty_sequence:
+            return True
+
+    def _eval_is_finite(self):
+        if self.has_finite_limits and self.function.is_finite:
+            return True
+
+    def doit(self, **hints):
+        # first make sure any definite limits have product
+        # variables with matching assumptions
+        reps = {}
+        for xab in self.limits:
+            d = _dummy_with_inherited_properties_concrete(xab)
+            if d:
+                reps[xab[0]] = d
+        if reps:
+            undo = {v: k for k, v in reps.items()}
+            did = self.xreplace(reps).doit(**hints)
+            if isinstance(did, tuple):  # when separate=True
+                did = tuple([i.xreplace(undo) for i in did])
+            else:
+                did = did.xreplace(undo)
+            return did
+
+        from sympy.simplify.powsimp import powsimp
+        f = self.function
+        for index, limit in enumerate(self.limits):
+            i, a, b = limit
+            dif = b - a
+            if dif.is_integer and dif.is_negative:
+                a, b = b + 1, a - 1
+                f = 1 / f
+
+            g = self._eval_product(f, (i, a, b))
+            if g in (None, S.NaN):
+                return self.func(powsimp(f), *self.limits[index:])
+            else:
+                f = g
+
+        if hints.get('deep', True):
+            return f.doit(**hints)
+        else:
+            return powsimp(f)
+
+    def _eval_adjoint(self):
+        if self.is_commutative:
+            return self.func(self.function.adjoint(), *self.limits)
+        return None
+
+    def _eval_conjugate(self):
+        return self.func(self.function.conjugate(), *self.limits)
+
+    def _eval_product(self, term, limits):
+
+        (k, a, n) = limits
+
+        if k not in term.free_symbols:
+            if (term - 1).is_zero:
+                return S.One
+            return term**(n - a + 1)
+
+        if a == n:
+            return term.subs(k, a)
+
+        from .delta import deltaproduct, _has_simple_delta
+        if term.has(KroneckerDelta) and _has_simple_delta(term, limits[0]):
+            return deltaproduct(term, limits)
+
+        dif = n - a
+        definite = dif.is_Integer
+        if definite and (dif < 100):
+            return self._eval_product_direct(term, limits)
+
+        elif term.is_polynomial(k):
+            poly = term.as_poly(k)
+
+            A = B = Q = S.One
+
+            all_roots = roots(poly)
+
+            M = 0
+            for r, m in all_roots.items():
+                M += m
+                A *= RisingFactorial(a - r, n - a + 1)**m
+                Q *= (n - r)**m
+
+            if M < poly.degree():
+                arg = quo(poly, Q.as_poly(k))
+                B = self.func(arg, (k, a, n)).doit()
+
+            return poly.LC()**(n - a + 1) * A * B
+
+        elif term.is_Add:
+            factored = factor_terms(term, fraction=True)
+            if factored.is_Mul:
+                return self._eval_product(factored, (k, a, n))
+
+        elif term.is_Mul:
+            # Factor in part without the summation variable and part with
+            without_k, with_k = term.as_coeff_mul(k)
+
+            if len(with_k) >= 2:
+                # More than one term including k, so still a multiplication
+                exclude, include = [], []
+                for t in with_k:
+                    p = self._eval_product(t, (k, a, n))
+
+                    if p is not None:
+                        exclude.append(p)
+                    else:
+                        include.append(t)
+
+                if not exclude:
+                    return None
+                else:
+                    arg = term._new_rawargs(*include)
+                    A = Mul(*exclude)
+                    B = self.func(arg, (k, a, n)).doit()
+                    return without_k**(n - a + 1)*A * B
+            else:
+                # Just a single term
+                p = self._eval_product(with_k[0], (k, a, n))
+                if p is None:
+                    p = self.func(with_k[0], (k, a, n)).doit()
+                return without_k**(n - a + 1)*p
+
+
+        elif term.is_Pow:
+            if not term.base.has(k):
+                s = summation(term.exp, (k, a, n))
+
+                return term.base**s
+            elif not term.exp.has(k):
+                p = self._eval_product(term.base, (k, a, n))
+
+                if p is not None:
+                    return p**term.exp
+
+        elif isinstance(term, Product):
+            evaluated = term.doit()
+            f = self._eval_product(evaluated, limits)
+            if f is None:
+                return self.func(evaluated, limits)
+            else:
+                return f
+
+        if definite:
+            return self._eval_product_direct(term, limits)
+
+    def _eval_simplify(self, **kwargs):
+        from sympy.simplify.simplify import product_simplify
+        rv = product_simplify(self, **kwargs)
+        return rv.doit() if kwargs['doit'] else rv
+
+    def _eval_transpose(self):
+        if self.is_commutative:
+            return self.func(self.function.transpose(), *self.limits)
+        return None
+
+    def _eval_product_direct(self, term, limits):
+        (k, a, n) = limits
+        return Mul(*[term.subs(k, a + i) for i in range(n - a + 1)])
+
+    def _eval_derivative(self, x):
+        if isinstance(x, Symbol) and x not in self.free_symbols:
+            return S.Zero
+        f, limits = self.function, list(self.limits)
+        limit = limits.pop(-1)
+        if limits:
+            f = self.func(f, *limits)
+        i, a, b = limit
+        if x in a.free_symbols or x in b.free_symbols:
+            return None
+        h = Dummy()
+        rv = Sum( Product(f, (i, a, h - 1)) * Product(f, (i, h + 1, b)) * Derivative(f, x, evaluate=True).subs(i, h), (h, a, b))
+        return rv
+
+    def is_convergent(self):
+        r"""
+        See docs of :obj:`.Sum.is_convergent()` for explanation of convergence
+        in SymPy.
+
+        Explanation
+        ===========
+
+        The infinite product:
+
+        .. math::
+
+            \prod_{1 \leq i < \infty} f(i)
+
+        is defined by the sequence of partial products:
+
+        .. math::
+
+            \prod_{i=1}^{n} f(i) = f(1) f(2) \cdots f(n)
+
+        as n increases without bound. The product converges to a non-zero
+        value if and only if the sum:
+
+        .. math::
+
+            \sum_{1 \leq i < \infty} \log{f(n)}
+
+        converges.
+
+        Examples
+        ========
+
+        >>> from sympy import Product, Symbol, cos, pi, exp, oo
+        >>> n = Symbol('n', integer=True)
+        >>> Product(n/(n + 1), (n, 1, oo)).is_convergent()
+        False
+        >>> Product(1/n**2, (n, 1, oo)).is_convergent()
+        False
+        >>> Product(cos(pi/n), (n, 1, oo)).is_convergent()
+        True
+        >>> Product(exp(-n**2), (n, 1, oo)).is_convergent()
+        False
+
+        References
+        ==========
+
+        .. [1] https://en.wikipedia.org/wiki/Infinite_product
+        """
+        sequence_term = self.function
+        log_sum = log(sequence_term)
+        lim = self.limits
+        try:
+            is_conv = Sum(log_sum, *lim).is_convergent()
+        except NotImplementedError:
+            if Sum(sequence_term - 1, *lim).is_absolutely_convergent() is S.true:
+                return S.true
+            raise NotImplementedError("The algorithm to find the product convergence of %s "
+                                        "is not yet implemented" % (sequence_term))
+        return is_conv
+
+    def reverse_order(expr, *indices):
+        """
+        Reverse the order of a limit in a Product.
+
+        Explanation
+        ===========
+
+        ``reverse_order(expr, *indices)`` reverses some limits in the expression
+        ``expr`` which can be either a ``Sum`` or a ``Product``. The selectors in
+        the argument ``indices`` specify some indices whose limits get reversed.
+        These selectors are either variable names or numerical indices counted
+        starting from the inner-most limit tuple.
+
+        Examples
+        ========
+
+        >>> from sympy import gamma, Product, simplify, Sum
+        >>> from sympy.abc import x, y, a, b, c, d
+        >>> P = Product(x, (x, a, b))
+        >>> Pr = P.reverse_order(x)
+        >>> Pr
+        Product(1/x, (x, b + 1, a - 1))
+        >>> Pr = Pr.doit()
+        >>> Pr
+        1/RisingFactorial(b + 1, a - b - 1)
+        >>> simplify(Pr.rewrite(gamma))
+        Piecewise((gamma(b + 1)/gamma(a), b > -1), ((-1)**(-a + b + 1)*gamma(1 - a)/gamma(-b), True))
+        >>> P = P.doit()
+        >>> P
+        RisingFactorial(a, -a + b + 1)
+        >>> simplify(P.rewrite(gamma))
+        Piecewise((gamma(b + 1)/gamma(a), a > 0), ((-1)**(-a + b + 1)*gamma(1 - a)/gamma(-b), True))
+
+        While one should prefer variable names when specifying which limits
+        to reverse, the index counting notation comes in handy in case there
+        are several symbols with the same name.
+
+        >>> S = Sum(x*y, (x, a, b), (y, c, d))
+        >>> S
+        Sum(x*y, (x, a, b), (y, c, d))
+        >>> S0 = S.reverse_order(0)
+        >>> S0
+        Sum(-x*y, (x, b + 1, a - 1), (y, c, d))
+        >>> S1 = S0.reverse_order(1)
+        >>> S1
+        Sum(x*y, (x, b + 1, a - 1), (y, d + 1, c - 1))
+
+        Of course we can mix both notations:
+
+        >>> Sum(x*y, (x, a, b), (y, 2, 5)).reverse_order(x, 1)
+        Sum(x*y, (x, b + 1, a - 1), (y, 6, 1))
+        >>> Sum(x*y, (x, a, b), (y, 2, 5)).reverse_order(y, x)
+        Sum(x*y, (x, b + 1, a - 1), (y, 6, 1))
+
+        See Also
+        ========
+
+        sympy.concrete.expr_with_intlimits.ExprWithIntLimits.index,
+        reorder_limit,
+        sympy.concrete.expr_with_intlimits.ExprWithIntLimits.reorder
+
+        References
+        ==========
+
+        .. [1] Michael Karr, "Summation in Finite Terms", Journal of the ACM,
+               Volume 28 Issue 2, April 1981, Pages 305-350
+               https://dl.acm.org/doi/10.1145/322248.322255
+
+        """
+        l_indices = list(indices)
+
+        for i, indx in enumerate(l_indices):
+            if not isinstance(indx, int):
+                l_indices[i] = expr.index(indx)
+
+        e = 1
+        limits = []
+        for i, limit in enumerate(expr.limits):
+            l = limit
+            if i in l_indices:
+                e = -e
+                l = (limit[0], limit[2] + 1, limit[1] - 1)
+            limits.append(l)
+
+        return Product(expr.function ** e, *limits)
+
+
+def product(*args, **kwargs):
+    r"""
+    Compute the product.
+
+    Explanation
+    ===========
+
+    The notation for symbols is similar to the notation used in Sum or
+    Integral. product(f, (i, a, b)) computes the product of f with
+    respect to i from a to b, i.e.,
+
+    ::
+
+                                     b
+                                   _____
+        product(f(n), (i, a, b)) = |   | f(n)
+                                   |   |
+                                   i = a
+
+    If it cannot compute the product, it returns an unevaluated Product object.
+    Repeated products can be computed by introducing additional symbols tuples::
+
+    Examples
+    ========
+
+    >>> from sympy import product, symbols
+    >>> i, n, m, k = symbols('i n m k', integer=True)
+
+    >>> product(i, (i, 1, k))
+    factorial(k)
+    >>> product(m, (i, 1, k))
+    m**k
+    >>> product(i, (i, 1, k), (k, 1, n))
+    Product(factorial(k), (k, 1, n))
+
+    """
+
+    prod = Product(*args, **kwargs)
+
+    if isinstance(prod, Product):
+        return prod.doit(deep=False)
+    else:
+        return prod

venv/lib/python3.10/site-packages/sympy/concrete/summations.py

@@ -0,0 +1,1646 @@
+from typing import Tuple as tTuple
+
+from sympy.calculus.singularities import is_decreasing
+from sympy.calculus.accumulationbounds import AccumulationBounds
+from .expr_with_intlimits import ExprWithIntLimits
+from .expr_with_limits import AddWithLimits
+from .gosper import gosper_sum
+from sympy.core.expr import Expr
+from sympy.core.add import Add
+from sympy.core.containers import Tuple
+from sympy.core.function import Derivative, expand
+from sympy.core.mul import Mul
+from sympy.core.numbers import Float, _illegal
+from sympy.core.relational import Eq
+from sympy.core.singleton import S
+from sympy.core.sorting import ordered
+from sympy.core.symbol import Dummy, Wild, Symbol, symbols
+from sympy.functions.combinatorial.factorials import factorial
+from sympy.functions.combinatorial.numbers import bernoulli, harmonic
+from sympy.functions.elementary.exponential import exp, log
+from sympy.functions.elementary.piecewise import Piecewise
+from sympy.functions.elementary.trigonometric import cot, csc
+from sympy.functions.special.hyper import hyper
+from sympy.functions.special.tensor_functions import KroneckerDelta
+from sympy.functions.special.zeta_functions import zeta
+from sympy.integrals.integrals import Integral
+from sympy.logic.boolalg import And
+from sympy.polys.partfrac import apart
+from sympy.polys.polyerrors import PolynomialError, PolificationFailed
+from sympy.polys.polytools import parallel_poly_from_expr, Poly, factor
+from sympy.polys.rationaltools import together
+from sympy.series.limitseq import limit_seq
+from sympy.series.order import O
+from sympy.series.residues import residue
+from sympy.sets.sets import FiniteSet, Interval
+from sympy.utilities.iterables import sift
+import itertools
+
+
+class Sum(AddWithLimits, ExprWithIntLimits):
+    r"""
+    Represents unevaluated summation.
+
+    Explanation
+    ===========
+
+    ``Sum`` represents a finite or infinite series, with the first argument
+    being the general form of terms in the series, and the second argument
+    being ``(dummy_variable, start, end)``, with ``dummy_variable`` taking
+    all integer values from ``start`` through ``end``. In accordance with
+    long-standing mathematical convention, the end term is included in the
+    summation.
+
+    Finite sums
+    ===========
+
+    For finite sums (and sums with symbolic limits assumed to be finite) we
+    follow the summation convention described by Karr [1], especially
+    definition 3 of section 1.4. The sum:
+
+    .. math::
+
+        \sum_{m \leq i < n} f(i)
+
+    has *the obvious meaning* for `m < n`, namely:
+
+    .. math::
+
+        \sum_{m \leq i < n} f(i) = f(m) + f(m+1) + \ldots + f(n-2) + f(n-1)
+
+    with the upper limit value `f(n)` excluded. The sum over an empty set is
+    zero if and only if `m = n`:
+
+    .. math::
+
+        \sum_{m \leq i < n} f(i) = 0  \quad \mathrm{for} \quad  m = n
+
+    Finally, for all other sums over empty sets we assume the following
+    definition:
+
+    .. math::
+
+        \sum_{m \leq i < n} f(i) = - \sum_{n \leq i < m} f(i)  \quad \mathrm{for} \quad  m > n
+
+    It is important to note that Karr defines all sums with the upper
+    limit being exclusive. This is in contrast to the usual mathematical notation,
+    but does not affect the summation convention. Indeed we have:
+
+    .. math::
+
+        \sum_{m \leq i < n} f(i) = \sum_{i = m}^{n - 1} f(i)
+
+    where the difference in notation is intentional to emphasize the meaning,
+    with limits typeset on the top being inclusive.
+
+    Examples
+    ========
+
+    >>> from sympy.abc import i, k, m, n, x
+    >>> from sympy import Sum, factorial, oo, IndexedBase, Function
+    >>> Sum(k, (k, 1, m))
+    Sum(k, (k, 1, m))
+    >>> Sum(k, (k, 1, m)).doit()
+    m**2/2 + m/2
+    >>> Sum(k**2, (k, 1, m))
+    Sum(k**2, (k, 1, m))
+    >>> Sum(k**2, (k, 1, m)).doit()
+    m**3/3 + m**2/2 + m/6
+    >>> Sum(x**k, (k, 0, oo))
+    Sum(x**k, (k, 0, oo))
+    >>> Sum(x**k, (k, 0, oo)).doit()
+    Piecewise((1/(1 - x), Abs(x) < 1), (Sum(x**k, (k, 0, oo)), True))
+    >>> Sum(x**k/factorial(k), (k, 0, oo)).doit()
+    exp(x)
+
+    Here are examples to do summation with symbolic indices.  You
+    can use either Function of IndexedBase classes:
+
+    >>> f = Function('f')
+    >>> Sum(f(n), (n, 0, 3)).doit()
+    f(0) + f(1) + f(2) + f(3)
+    >>> Sum(f(n), (n, 0, oo)).doit()
+    Sum(f(n), (n, 0, oo))
+    >>> f = IndexedBase('f')
+    >>> Sum(f[n]**2, (n, 0, 3)).doit()
+    f[0]**2 + f[1]**2 + f[2]**2 + f[3]**2
+
+    An example showing that the symbolic result of a summation is still
+    valid for seemingly nonsensical values of the limits. Then the Karr
+    convention allows us to give a perfectly valid interpretation to
+    those sums by interchanging the limits according to the above rules:
+
+    >>> S = Sum(i, (i, 1, n)).doit()
+    >>> S
+    n**2/2 + n/2
+    >>> S.subs(n, -4)
+    6
+    >>> Sum(i, (i, 1, -4)).doit()
+    6
+    >>> Sum(-i, (i, -3, 0)).doit()
+    6
+
+    An explicit example of the Karr summation convention:
+
+    >>> S1 = Sum(i**2, (i, m, m+n-1)).doit()
+    >>> S1
+    m**2*n + m*n**2 - m*n + n**3/3 - n**2/2 + n/6
+    >>> S2 = Sum(i**2, (i, m+n, m-1)).doit()
+    >>> S2
+    -m**2*n - m*n**2 + m*n - n**3/3 + n**2/2 - n/6
+    >>> S1 + S2
+    0
+    >>> S3 = Sum(i, (i, m, m-1)).doit()
+    >>> S3
+    0
+
+    See Also
+    ========
+
+    summation
+    Product, sympy.concrete.products.product
+
+    References
+    ==========
+
+    .. [1] Michael Karr, "Summation in Finite Terms", Journal of the ACM,
+           Volume 28 Issue 2, April 1981, Pages 305-350
+           https://dl.acm.org/doi/10.1145/322248.322255
+    .. [2] https://en.wikipedia.org/wiki/Summation#Capital-sigma_notation
+    .. [3] https://en.wikipedia.org/wiki/Empty_sum
+    """
+
+    __slots__ = ()
+
+    limits: tTuple[tTuple[Symbol, Expr, Expr]]
+
+    def __new__(cls, function, *symbols, **assumptions):
+        obj = AddWithLimits.__new__(cls, function, *symbols, **assumptions)
+        if not hasattr(obj, 'limits'):
+            return obj
+        if any(len(l) != 3 or None in l for l in obj.limits):
+            raise ValueError('Sum requires values for lower and upper bounds.')
+
+        return obj
+
+    def _eval_is_zero(self):
+        # a Sum is only zero if its function is zero or if all terms
+        # cancel out. This only answers whether the summand is zero; if
+        # not then None is returned since we don't analyze whether all
+        # terms cancel out.
+        if self.function.is_zero or self.has_empty_sequence:
+            return True
+
+    def _eval_is_extended_real(self):
+        if self.has_empty_sequence:
+            return True
+        return self.function.is_extended_real
+
+    def _eval_is_positive(self):
+        if self.has_finite_limits and self.has_reversed_limits is False:
+            return self.function.is_positive
+
+    def _eval_is_negative(self):
+        if self.has_finite_limits and self.has_reversed_limits is False:
+            return self.function.is_negative
+
+    def _eval_is_finite(self):
+        if self.has_finite_limits and self.function.is_finite:
+            return True
+
+    def doit(self, **hints):
+        if hints.get('deep', True):
+            f = self.function.doit(**hints)
+        else:
+            f = self.function
+
+        # first make sure any definite limits have summation
+        # variables with matching assumptions
+        reps = {}
+        for xab in self.limits:
+            d = _dummy_with_inherited_properties_concrete(xab)
+            if d:
+                reps[xab[0]] = d
+        if reps:
+            undo = {v: k for k, v in reps.items()}
+            did = self.xreplace(reps).doit(**hints)
+            if isinstance(did, tuple):  # when separate=True
+                did = tuple([i.xreplace(undo) for i in did])
+            elif did is not None:
+                did = did.xreplace(undo)
+            else:
+                did = self
+            return did
+
+
+        if self.function.is_Matrix:
+            expanded = self.expand()
+            if self != expanded:
+                return expanded.doit()
+            return _eval_matrix_sum(self)
+
+        for n, limit in enumerate(self.limits):
+            i, a, b = limit
+            dif = b - a
+            if dif == -1:
+                # Any summation over an empty set is zero
+                return S.Zero
+            if dif.is_integer and dif.is_negative:
+                a, b = b + 1, a - 1
+                f = -f
+
+            newf = eval_sum(f, (i, a, b))
+            if newf is None:
+                if f == self.function:
+                    zeta_function = self.eval_zeta_function(f, (i, a, b))
+                    if zeta_function is not None:
+                        return zeta_function
+                    return self
+                else:
+                    return self.func(f, *self.limits[n:])
+            f = newf
+
+        if hints.get('deep', True):
+            # eval_sum could return partially unevaluated
+            # result with Piecewise.  In this case we won't
+            # doit() recursively.
+            if not isinstance(f, Piecewise):
+                return f.doit(**hints)
+
+        return f
+
+    def eval_zeta_function(self, f, limits):
+        """
+        Check whether the function matches with the zeta function.
+
+        If it matches, then return a `Piecewise` expression because
+        zeta function does not converge unless `s > 1` and `q > 0`
+        """
+        i, a, b = limits
+        w, y, z = Wild('w', exclude=[i]), Wild('y', exclude=[i]), Wild('z', exclude=[i])
+        result = f.match((w * i + y) ** (-z))
+        if result is not None and b is S.Infinity:
+            coeff = 1 / result[w] ** result[z]
+            s = result[z]
+            q = result[y] / result[w] + a
+            return Piecewise((coeff * zeta(s, q), And(q > 0, s > 1)), (self, True))
+
+    def _eval_derivative(self, x):
+        """
+        Differentiate wrt x as long as x is not in the free symbols of any of
+        the upper or lower limits.
+
+        Explanation
+        ===========
+
+        Sum(a*b*x, (x, 1, a)) can be differentiated wrt x or b but not `a`
+        since the value of the sum is discontinuous in `a`. In a case
+        involving a limit variable, the unevaluated derivative is returned.
+        """
+
+        # diff already confirmed that x is in the free symbols of self, but we
+        # don't want to differentiate wrt any free symbol in the upper or lower
+        # limits
+        # XXX remove this test for free_symbols when the default _eval_derivative is in
+        if isinstance(x, Symbol) and x not in self.free_symbols:
+            return S.Zero
+
+        # get limits and the function
+        f, limits = self.function, list(self.limits)
+
+        limit = limits.pop(-1)
+
+        if limits:  # f is the argument to a Sum
+            f = self.func(f, *limits)
+
+        _, a, b = limit
+        if x in a.free_symbols or x in b.free_symbols:
+            return None
+        df = Derivative(f, x, evaluate=True)
+        rv = self.func(df, limit)
+        return rv
+
+    def _eval_difference_delta(self, n, step):
+        k, _, upper = self.args[-1]
+        new_upper = upper.subs(n, n + step)
+
+        if len(self.args) == 2:
+            f = self.args[0]
+        else:
+            f = self.func(*self.args[:-1])
+
+        return Sum(f, (k, upper + 1, new_upper)).doit()
+
+    def _eval_simplify(self, **kwargs):
+
+        function = self.function
+
+        if kwargs.get('deep', True):
+            function = function.simplify(**kwargs)
+
+        # split the function into adds
+        terms = Add.make_args(expand(function))
+        s_t = [] # Sum Terms
+        o_t = [] # Other Terms
+
+        for term in terms:
+            if term.has(Sum):
+                # if there is an embedded sum here
+                # it is of the form x * (Sum(whatever))
+                # hence we make a Mul out of it, and simplify all interior sum terms
+                subterms = Mul.make_args(expand(term))
+                out_terms = []
+                for subterm in subterms:
+                    # go through each term
+                    if isinstance(subterm, Sum):
+                        # if it's a sum, simplify it
+                        out_terms.append(subterm._eval_simplify(**kwargs))
+                    else:
+                        # otherwise, add it as is
+                        out_terms.append(subterm)
+
+                # turn it back into a Mul
+                s_t.append(Mul(*out_terms))
+            else:
+                o_t.append(term)
+
+        # next try to combine any interior sums for further simplification
+        from sympy.simplify.simplify import factor_sum, sum_combine
+        result = Add(sum_combine(s_t), *o_t)
+
+        return factor_sum(result, limits=self.limits)
+
+    def is_convergent(self):
+        r"""
+        Checks for the convergence of a Sum.
+
+        Explanation
+        ===========
+
+        We divide the study of convergence of infinite sums and products in
+        two parts.
+
+        First Part:
+        One part is the question whether all the terms are well defined, i.e.,
+        they are finite in a sum and also non-zero in a product. Zero
+        is the analogy of (minus) infinity in products as
+        :math:`e^{-\infty} = 0`.
+
+        Second Part:
+        The second part is the question of convergence after infinities,
+        and zeros in products, have been omitted assuming that their number
+        is finite. This means that we only consider the tail of the sum or
+        product, starting from some point after which all terms are well
+        defined.
+
+        For example, in a sum of the form:
+
+        .. math::
+
+            \sum_{1 \leq i < \infty} \frac{1}{n^2 + an + b}
+
+        where a and b are numbers. The routine will return true, even if there
+        are infinities in the term sequence (at most two). An analogous
+        product would be:
+
+        .. math::
+
+            \prod_{1 \leq i < \infty} e^{\frac{1}{n^2 + an + b}}
+
+        This is how convergence is interpreted. It is concerned with what
+        happens at the limit. Finding the bad terms is another independent
+        matter.
+
+        Note: It is responsibility of user to see that the sum or product
+        is well defined.
+
+        There are various tests employed to check the convergence like
+        divergence test, root test, integral test, alternating series test,
+        comparison tests, Dirichlet tests. It returns true if Sum is convergent
+        and false if divergent and NotImplementedError if it cannot be checked.
+
+        References
+        ==========
+
+        .. [1] https://en.wikipedia.org/wiki/Convergence_tests
+
+        Examples
+        ========
+
+        >>> from sympy import factorial, S, Sum, Symbol, oo
+        >>> n = Symbol('n', integer=True)
+        >>> Sum(n/(n - 1), (n, 4, 7)).is_convergent()
+        True
+        >>> Sum(n/(2*n + 1), (n, 1, oo)).is_convergent()
+        False
+        >>> Sum(factorial(n)/5**n, (n, 1, oo)).is_convergent()
+        False
+        >>> Sum(1/n**(S(6)/5), (n, 1, oo)).is_convergent()
+        True
+
+        See Also
+        ========
+
+        Sum.is_absolutely_convergent
+        sympy.concrete.products.Product.is_convergent
+        """
+        p, q, r = symbols('p q r', cls=Wild)
+
+        sym = self.limits[0][0]
+        lower_limit = self.limits[0][1]
+        upper_limit = self.limits[0][2]
+        sequence_term = self.function.simplify()
+
+        if len(sequence_term.free_symbols) > 1:
+            raise NotImplementedError("convergence checking for more than one symbol "
+                                      "containing series is not handled")
+
+        if lower_limit.is_finite and upper_limit.is_finite:
+            return S.true
+
+        # transform sym -> -sym and swap the upper_limit = S.Infinity
+        # and lower_limit = - upper_limit
+        if lower_limit is S.NegativeInfinity:
+            if upper_limit is S.Infinity:
+                return Sum(sequence_term, (sym, 0, S.Infinity)).is_convergent() and \
+                        Sum(sequence_term, (sym, S.NegativeInfinity, 0)).is_convergent()
+            from sympy.simplify.simplify import simplify
+            sequence_term = simplify(sequence_term.xreplace({sym: -sym}))
+            lower_limit = -upper_limit
+            upper_limit = S.Infinity
+
+        sym_ = Dummy(sym.name, integer=True, positive=True)
+        sequence_term = sequence_term.xreplace({sym: sym_})
+        sym = sym_
+
+        interval = Interval(lower_limit, upper_limit)
+
+        # Piecewise function handle
+        if sequence_term.is_Piecewise:
+            for func, cond in sequence_term.args:
+                # see if it represents something going to oo
+                if cond == True or cond.as_set().sup is S.Infinity:
+                    s = Sum(func, (sym, lower_limit, upper_limit))
+                    return s.is_convergent()
+            return S.true
+
+        ###  -------- Divergence test ----------- ###
+        try:
+           lim_val = limit_seq(sequence_term, sym)
+           if lim_val is not None and lim_val.is_zero is False:
+               return S.false
+        except NotImplementedError:
+            pass
+
+        try:
+            lim_val_abs = limit_seq(abs(sequence_term), sym)
+            if lim_val_abs is not None and lim_val_abs.is_zero is False:
+                return S.false
+        except NotImplementedError:
+            pass
+
+        order = O(sequence_term, (sym, S.Infinity))
+
+        ### --------- p-series test (1/n**p) ---------- ###
+        p_series_test = order.expr.match(sym**p)
+        if p_series_test is not None:
+            if p_series_test[p] < -1:
+                return S.true
+            if p_series_test[p] >= -1:
+                return S.false
+
+        ### ------------- comparison test ------------- ###
+        # 1/(n**p*log(n)**q*log(log(n))**r) comparison
+        n_log_test = (order.expr.match(1/(sym**p*log(1/sym)**q*log(-log(1/sym))**r)) or
+                      order.expr.match(1/(sym**p*(-log(1/sym))**q*log(-log(1/sym))**r)))
+        if n_log_test is not None:
+            if (n_log_test[p] > 1 or
+                (n_log_test[p] == 1 and n_log_test[q] > 1) or
+                (n_log_test[p] == n_log_test[q] == 1 and n_log_test[r] > 1)):
+                    return S.true
+            return S.false
+
+        ### ------------- Limit comparison test -----------###
+        # (1/n) comparison
+        try:
+            lim_comp = limit_seq(sym*sequence_term, sym)
+            if lim_comp is not None and lim_comp.is_number and lim_comp > 0:
+                return S.false
+        except NotImplementedError:
+            pass
+
+        ### ----------- ratio test ---------------- ###
+        next_sequence_term = sequence_term.xreplace({sym: sym + 1})
+        from sympy.simplify.combsimp import combsimp
+        from sympy.simplify.powsimp import powsimp
+        ratio = combsimp(powsimp(next_sequence_term/sequence_term))
+        try:
+            lim_ratio = limit_seq(ratio, sym)
+            if lim_ratio is not None and lim_ratio.is_number:
+                if abs(lim_ratio) > 1:
+                    return S.false
+                if abs(lim_ratio) < 1:
+                    return S.true
+        except NotImplementedError:
+            lim_ratio = None
+
+        ### ---------- Raabe's test -------------- ###
+        if lim_ratio == 1:  # ratio test inconclusive
+            test_val = sym*(sequence_term/
+                         sequence_term.subs(sym, sym + 1) - 1)
+            test_val = test_val.gammasimp()
+            try:
+                lim_val = limit_seq(test_val, sym)
+                if lim_val is not None and lim_val.is_number:
+                    if lim_val > 1:
+                        return S.true
+                    if lim_val < 1:
+                        return S.false
+            except NotImplementedError:
+                pass
+
+        ### ----------- root test ---------------- ###
+        # lim = Limit(abs(sequence_term)**(1/sym), sym, S.Infinity)
+        try:
+            lim_evaluated = limit_seq(abs(sequence_term)**(1/sym), sym)
+            if lim_evaluated is not None and lim_evaluated.is_number:
+                if lim_evaluated < 1:
+                    return S.true
+                if lim_evaluated > 1:
+                    return S.false
+        except NotImplementedError:
+            pass
+
+        ### ------------- alternating series test ----------- ###
+        dict_val = sequence_term.match(S.NegativeOne**(sym + p)*q)
+        if not dict_val[p].has(sym) and is_decreasing(dict_val[q], interval):
+            return S.true
+
+        ### ------------- integral test -------------- ###
+        check_interval = None
+        from sympy.solvers.solveset import solveset
+        maxima = solveset(sequence_term.diff(sym), sym, interval)
+        if not maxima:
+            check_interval = interval
+        elif isinstance(maxima, FiniteSet) and maxima.sup.is_number:
+            check_interval = Interval(maxima.sup, interval.sup)
+        if (check_interval is not None and
+            (is_decreasing(sequence_term, check_interval) or
+            is_decreasing(-sequence_term, check_interval))):
+                integral_val = Integral(
+                    sequence_term, (sym, lower_limit, upper_limit))
+                try:
+                    integral_val_evaluated = integral_val.doit()
+                    if integral_val_evaluated.is_number:
+                        return S(integral_val_evaluated.is_finite)
+                except NotImplementedError:
+                    pass
+
+        ### ----- Dirichlet and bounded times convergent tests ----- ###
+        # TODO
+        #
+        # Dirichlet_test
+        # https://en.wikipedia.org/wiki/Dirichlet%27s_test
+        #
+        # Bounded times convergent test
+        # It is based on comparison theorems for series.
+        # In particular, if the general term of a series can
+        # be written as a product of two terms a_n and b_n
+        # and if a_n is bounded and if Sum(b_n) is absolutely
+        # convergent, then the original series Sum(a_n * b_n)
+        # is absolutely convergent and so convergent.
+        #
+        # The following code can grows like 2**n where n is the
+        # number of args in order.expr
+        # Possibly combined with the potentially slow checks
+        # inside the loop, could make this test extremely slow
+        # for larger summation expressions.
+
+        if order.expr.is_Mul:
+            args = order.expr.args
+            argset = set(args)
+
+            ### -------------- Dirichlet tests -------------- ###
+            m = Dummy('m', integer=True)
+            def _dirichlet_test(g_n):
+                try:
+                    ing_val = limit_seq(Sum(g_n, (sym, interval.inf, m)).doit(), m)
+                    if ing_val is not None and ing_val.is_finite:
+                        return S.true
+                except NotImplementedError:
+                    pass
+
+            ### -------- bounded times convergent test ---------###
+            def _bounded_convergent_test(g1_n, g2_n):
+                try:
+                    lim_val = limit_seq(g1_n, sym)
+                    if lim_val is not None and (lim_val.is_finite or (
+                        isinstance(lim_val, AccumulationBounds)
+                        and (lim_val.max - lim_val.min).is_finite)):
+                            if Sum(g2_n, (sym, lower_limit, upper_limit)).is_absolutely_convergent():
+                                return S.true
+                except NotImplementedError:
+                    pass
+
+            for n in range(1, len(argset)):
+                for a_tuple in itertools.combinations(args, n):
+                    b_set = argset - set(a_tuple)
+                    a_n = Mul(*a_tuple)
+                    b_n = Mul(*b_set)
+
+                    if is_decreasing(a_n, interval):
+                        dirich = _dirichlet_test(b_n)
+                        if dirich is not None:
+                            return dirich
+
+                    bc_test = _bounded_convergent_test(a_n, b_n)
+                    if bc_test is not None:
+                        return bc_test
+
+        _sym = self.limits[0][0]
+        sequence_term = sequence_term.xreplace({sym: _sym})
+        raise NotImplementedError("The algorithm to find the Sum convergence of %s "
+                                  "is not yet implemented" % (sequence_term))
+
+    def is_absolutely_convergent(self):
+        """
+        Checks for the absolute convergence of an infinite series.
+
+        Same as checking convergence of absolute value of sequence_term of
+        an infinite series.
+
+        References
+        ==========
+
+        .. [1] https://en.wikipedia.org/wiki/Absolute_convergence
+
+        Examples
+        ========
+
+        >>> from sympy import Sum, Symbol, oo
+        >>> n = Symbol('n', integer=True)
+        >>> Sum((-1)**n, (n, 1, oo)).is_absolutely_convergent()
+        False
+        >>> Sum((-1)**n/n**2, (n, 1, oo)).is_absolutely_convergent()
+        True
+
+        See Also
+        ========
+
+        Sum.is_convergent
+        """
+        return Sum(abs(self.function), self.limits).is_convergent()
+
+    def euler_maclaurin(self, m=0, n=0, eps=0, eval_integral=True):
+        """
+        Return an Euler-Maclaurin approximation of self, where m is the
+        number of leading terms to sum directly and n is the number of
+        terms in the tail.
+
+        With m = n = 0, this is simply the corresponding integral
+        plus a first-order endpoint correction.
+
+        Returns (s, e) where s is the Euler-Maclaurin approximation
+        and e is the estimated error (taken to be the magnitude of
+        the first omitted term in the tail):
+
+            >>> from sympy.abc import k, a, b
+            >>> from sympy import Sum
+            >>> Sum(1/k, (k, 2, 5)).doit().evalf()
+            1.28333333333333
+            >>> s, e = Sum(1/k, (k, 2, 5)).euler_maclaurin()
+            >>> s
+            -log(2) + 7/20 + log(5)
+            >>> from sympy import sstr
+            >>> print(sstr((s.evalf(), e.evalf()), full_prec=True))
+            (1.26629073187415, 0.0175000000000000)
+
+        The endpoints may be symbolic:
+
+            >>> s, e = Sum(1/k, (k, a, b)).euler_maclaurin()
+            >>> s
+            -log(a) + log(b) + 1/(2*b) + 1/(2*a)
+            >>> e
+            Abs(1/(12*b**2) - 1/(12*a**2))
+
+        If the function is a polynomial of degree at most 2n+1, the
+        Euler-Maclaurin formula becomes exact (and e = 0 is returned):
+
+            >>> Sum(k, (k, 2, b)).euler_maclaurin()
+            (b**2/2 + b/2 - 1, 0)
+            >>> Sum(k, (k, 2, b)).doit()
+            b**2/2 + b/2 - 1
+
+        With a nonzero eps specified, the summation is ended
+        as soon as the remainder term is less than the epsilon.
+        """
+        m = int(m)
+        n = int(n)
+        f = self.function
+        if len(self.limits) != 1:
+            raise ValueError("More than 1 limit")
+        i, a, b = self.limits[0]
+        if (a > b) == True:
+            if a - b == 1:
+                return S.Zero, S.Zero
+            a, b = b + 1, a - 1
+            f = -f
+        s = S.Zero
+        if m:
+            if b.is_Integer and a.is_Integer:
+                m = min(m, b - a + 1)
+            if not eps or f.is_polynomial(i):
+                s = Add(*[f.subs(i, a + k) for k in range(m)])
+            else:
+                term = f.subs(i, a)
+                if term:
+                    test = abs(term.evalf(3)) < eps
+                    if test == True:
+                        return s, abs(term)
+                    elif not (test == False):
+                        # a symbolic Relational class, can't go further
+                        return term, S.Zero
+                s = term
+                for k in range(1, m):
+                    term = f.subs(i, a + k)
+                    if abs(term.evalf(3)) < eps and term != 0:
+                        return s, abs(term)
+                    s += term
+            if b - a + 1 == m:
+                return s, S.Zero
+            a += m
+        x = Dummy('x')
+        I = Integral(f.subs(i, x), (x, a, b))
+        if eval_integral:
+            I = I.doit()
+        s += I
+
+        def fpoint(expr):
+            if b is S.Infinity:
+                return expr.subs(i, a), 0
+            return expr.subs(i, a), expr.subs(i, b)
+        fa, fb = fpoint(f)
+        iterm = (fa + fb)/2
+        g = f.diff(i)
+        for k in range(1, n + 2):
+            ga, gb = fpoint(g)
+            term = bernoulli(2*k)/factorial(2*k)*(gb - ga)
+            if k > n:
+                break
+            if eps and term:
+                term_evalf = term.evalf(3)
+                if term_evalf is S.NaN:
+                    return S.NaN, S.NaN
+                if abs(term_evalf) < eps:
+                    break
+            s += term
+            g = g.diff(i, 2, simplify=False)
+        return s + iterm, abs(term)
+
+
+    def reverse_order(self, *indices):
+        """
+        Reverse the order of a limit in a Sum.
+
+        Explanation
+        ===========
+
+        ``reverse_order(self, *indices)`` reverses some limits in the expression
+        ``self`` which can be either a ``Sum`` or a ``Product``. The selectors in
+        the argument ``indices`` specify some indices whose limits get reversed.
+        These selectors are either variable names or numerical indices counted
+        starting from the inner-most limit tuple.
+
+        Examples
+        ========
+
+        >>> from sympy import Sum
+        >>> from sympy.abc import x, y, a, b, c, d
+
+        >>> Sum(x, (x, 0, 3)).reverse_order(x)
+        Sum(-x, (x, 4, -1))
+        >>> Sum(x*y, (x, 1, 5), (y, 0, 6)).reverse_order(x, y)
+        Sum(x*y, (x, 6, 0), (y, 7, -1))
+        >>> Sum(x, (x, a, b)).reverse_order(x)
+        Sum(-x, (x, b + 1, a - 1))
+        >>> Sum(x, (x, a, b)).reverse_order(0)
+        Sum(-x, (x, b + 1, a - 1))
+
+        While one should prefer variable names when specifying which limits
+        to reverse, the index counting notation comes in handy in case there
+        are several symbols with the same name.
+
+        >>> S = Sum(x**2, (x, a, b), (x, c, d))
+        >>> S
+        Sum(x**2, (x, a, b), (x, c, d))
+        >>> S0 = S.reverse_order(0)
+        >>> S0
+        Sum(-x**2, (x, b + 1, a - 1), (x, c, d))
+        >>> S1 = S0.reverse_order(1)
+        >>> S1
+        Sum(x**2, (x, b + 1, a - 1), (x, d + 1, c - 1))
+
+        Of course we can mix both notations:
+
+        >>> Sum(x*y, (x, a, b), (y, 2, 5)).reverse_order(x, 1)
+        Sum(x*y, (x, b + 1, a - 1), (y, 6, 1))
+        >>> Sum(x*y, (x, a, b), (y, 2, 5)).reverse_order(y, x)
+        Sum(x*y, (x, b + 1, a - 1), (y, 6, 1))
+
+        See Also
+        ========
+
+        sympy.concrete.expr_with_intlimits.ExprWithIntLimits.index, reorder_limit,
+        sympy.concrete.expr_with_intlimits.ExprWithIntLimits.reorder
+
+        References
+        ==========
+
+        .. [1] Michael Karr, "Summation in Finite Terms", Journal of the ACM,
+               Volume 28 Issue 2, April 1981, Pages 305-350
+               https://dl.acm.org/doi/10.1145/322248.322255
+        """
+        l_indices = list(indices)
+
+        for i, indx in enumerate(l_indices):
+            if not isinstance(indx, int):
+                l_indices[i] = self.index(indx)
+
+        e = 1
+        limits = []
+        for i, limit in enumerate(self.limits):
+            l = limit
+            if i in l_indices:
+                e = -e
+                l = (limit[0], limit[2] + 1, limit[1] - 1)
+            limits.append(l)
+
+        return Sum(e * self.function, *limits)
+
+    def _eval_rewrite_as_Product(self, *args, **kwargs):
+        from sympy.concrete.products import Product
+        if self.function.is_extended_real:
+            return log(Product(exp(self.function), *self.limits))
+
+
+def summation(f, *symbols, **kwargs):
+    r"""
+    Compute the summation of f with respect to symbols.
+
+    Explanation
+    ===========
+
+    The notation for symbols is similar to the notation used in Integral.
+    summation(f, (i, a, b)) computes the sum of f with respect to i from a to b,
+    i.e.,
+
+    ::
+
+                                    b
+                                  ____
+                                  \   `
+        summation(f, (i, a, b)) =  )    f
+                                  /___,
+                                  i = a
+
+    If it cannot compute the sum, it returns an unevaluated Sum object.
+    Repeated sums can be computed by introducing additional symbols tuples::
+
+    Examples
+    ========
+
+    >>> from sympy import summation, oo, symbols, log
+    >>> i, n, m = symbols('i n m', integer=True)
+
+    >>> summation(2*i - 1, (i, 1, n))
+    n**2
+    >>> summation(1/2**i, (i, 0, oo))
+    2
+    >>> summation(1/log(n)**n, (n, 2, oo))
+    Sum(log(n)**(-n), (n, 2, oo))
+    >>> summation(i, (i, 0, n), (n, 0, m))
+    m**3/6 + m**2/2 + m/3
+
+    >>> from sympy.abc import x
+    >>> from sympy import factorial
+    >>> summation(x**n/factorial(n), (n, 0, oo))
+    exp(x)
+
+    See Also
+    ========
+
+    Sum
+    Product, sympy.concrete.products.product
+
+    """
+    return Sum(f, *symbols, **kwargs).doit(deep=False)
+
+
+def telescopic_direct(L, R, n, limits):
+    """
+    Returns the direct summation of the terms of a telescopic sum
+
+    Explanation
+    ===========
+
+    L is the term with lower index
+    R is the term with higher index
+    n difference between the indexes of L and R
+
+    Examples
+    ========
+
+    >>> from sympy.concrete.summations import telescopic_direct
+    >>> from sympy.abc import k, a, b
+    >>> telescopic_direct(1/k, -1/(k+2), 2, (k, a, b))
+    -1/(b + 2) - 1/(b + 1) + 1/(a + 1) + 1/a
+
+    """
+    (i, a, b) = limits
+    return Add(*[L.subs(i, a + m) + R.subs(i, b - m) for m in range(n)])
+
+
+def telescopic(L, R, limits):
+    '''
+    Tries to perform the summation using the telescopic property.
+
+    Return None if not possible.
+    '''
+    (i, a, b) = limits
+    if L.is_Add or R.is_Add:
+        return None
+
+    # We want to solve(L.subs(i, i + m) + R, m)
+    # First we try a simple match since this does things that
+    # solve doesn't do, e.g. solve(cos(k+m)-cos(k), m) gives
+    # a more complicated solution than m == 0.
+
+    k = Wild("k")
+    sol = (-R).match(L.subs(i, i + k))
+    s = None
+    if sol and k in sol:
+        s = sol[k]
+        if not (s.is_Integer and L.subs(i, i + s) + R == 0):
+            # invalid match or match didn't work
+            s = None
+
+    # But there are things that match doesn't do that solve
+    # can do, e.g. determine that 1/(x + m) = 1/(1 - x) when m = 1
+
+    if s is None:
+        m = Dummy('m')
+        try:
+            from sympy.solvers.solvers import solve
+            sol = solve(L.subs(i, i + m) + R, m) or []
+        except NotImplementedError:
+            return None
+        sol = [si for si in sol if si.is_Integer and
+               (L.subs(i, i + si) + R).expand().is_zero]
+        if len(sol) != 1:
+            return None
+        s = sol[0]
+
+    if s < 0:
+        return telescopic_direct(R, L, abs(s), (i, a, b))
+    elif s > 0:
+        return telescopic_direct(L, R, s, (i, a, b))
+
+
+def eval_sum(f, limits):
+    (i, a, b) = limits
+    if f.is_zero:
+        return S.Zero
+    if i not in f.free_symbols:
+        return f*(b - a + 1)
+    if a == b:
+        return f.subs(i, a)
+    if isinstance(f, Piecewise):
+        if not any(i in arg.args[1].free_symbols for arg in f.args):
+            # Piecewise conditions do not depend on the dummy summation variable,
+            # therefore we can fold:     Sum(Piecewise((e, c), ...), limits)
+            #                        --> Piecewise((Sum(e, limits), c), ...)
+            newargs = []
+            for arg in f.args:
+                newexpr = eval_sum(arg.expr, limits)
+                if newexpr is None:
+                    return None
+                newargs.append((newexpr, arg.cond))
+            return f.func(*newargs)
+
+    if f.has(KroneckerDelta):
+        from .delta import deltasummation, _has_simple_delta
+        f = f.replace(
+            lambda x: isinstance(x, Sum),
+            lambda x: x.factor()
+        )
+        if _has_simple_delta(f, limits[0]):
+            return deltasummation(f, limits)
+
+    dif = b - a
+    definite = dif.is_Integer
+    # Doing it directly may be faster if there are very few terms.
+    if definite and (dif < 100):
+        return eval_sum_direct(f, (i, a, b))
+    if isinstance(f, Piecewise):
+        return None
+    # Try to do it symbolically. Even when the number of terms is
+    # known, this can save time when b-a is big.
+    value = eval_sum_symbolic(f.expand(), (i, a, b))
+    if value is not None:
+        return value
+    # Do it directly
+    if definite:
+        return eval_sum_direct(f, (i, a, b))
+
+
+def eval_sum_direct(expr, limits):
+    """
+    Evaluate expression directly, but perform some simple checks first
+    to possibly result in a smaller expression and faster execution.
+    """
+    (i, a, b) = limits
+
+    dif = b - a
+    # Linearity
+    if expr.is_Mul:
+        # Try factor out everything not including i
+        without_i, with_i = expr.as_independent(i)
+        if without_i != 1:
+            s = eval_sum_direct(with_i, (i, a, b))
+            if s:
+                r = without_i*s
+                if r is not S.NaN:
+                    return r
+        else:
+            # Try term by term
+            L, R = expr.as_two_terms()
+
+            if not L.has(i):
+                sR = eval_sum_direct(R, (i, a, b))
+                if sR:
+                    return L*sR
+
+            if not R.has(i):
+                sL = eval_sum_direct(L, (i, a, b))
+                if sL:
+                    return sL*R
+
+    # do this whether its an Add or Mul
+    # e.g. apart(1/(25*i**2 + 45*i + 14)) and
+    # apart(1/((5*i + 2)*(5*i + 7))) ->
+    # -1/(5*(5*i + 7)) + 1/(5*(5*i + 2))
+    try:
+        expr = apart(expr, i)  # see if it becomes an Add
+    except PolynomialError:
+        pass
+
+    if expr.is_Add:
+        # Try factor out everything not including i
+        without_i, with_i = expr.as_independent(i)
+        if without_i != 0:
+            s = eval_sum_direct(with_i, (i, a, b))
+            if s:
+                r = without_i*(dif + 1) + s
+                if r is not S.NaN:
+                    return r
+        else:
+            # Try term by term
+            L, R = expr.as_two_terms()
+            lsum = eval_sum_direct(L, (i, a, b))
+            rsum = eval_sum_direct(R, (i, a, b))
+
+            if None not in (lsum, rsum):
+                r = lsum + rsum
+                if r is not S.NaN:
+                    return r
+
+    return Add(*[expr.subs(i, a + j) for j in range(dif + 1)])
+
+
+def eval_sum_symbolic(f, limits):
+    f_orig = f
+    (i, a, b) = limits
+    if not f.has(i):
+        return f*(b - a + 1)
+
+    # Linearity
+    if f.is_Mul:
+        # Try factor out everything not including i
+        without_i, with_i = f.as_independent(i)
+        if without_i != 1:
+            s = eval_sum_symbolic(with_i, (i, a, b))
+            if s:
+                r = without_i*s
+                if r is not S.NaN:
+                    return r
+        else:
+            # Try term by term
+            L, R = f.as_two_terms()
+
+            if not L.has(i):
+                sR = eval_sum_symbolic(R, (i, a, b))
+                if sR:
+                    return L*sR
+
+            if not R.has(i):
+                sL = eval_sum_symbolic(L, (i, a, b))
+                if sL:
+                    return sL*R
+
+    # do this whether its an Add or Mul
+    # e.g. apart(1/(25*i**2 + 45*i + 14)) and
+    # apart(1/((5*i + 2)*(5*i + 7))) ->
+    # -1/(5*(5*i + 7)) + 1/(5*(5*i + 2))
+    try:
+        f = apart(f, i)
+    except PolynomialError:
+        pass
+
+    if f.is_Add:
+        L, R = f.as_two_terms()
+        lrsum = telescopic(L, R, (i, a, b))
+
+        if lrsum:
+            return lrsum
+
+        # Try factor out everything not including i
+        without_i, with_i = f.as_independent(i)
+        if without_i != 0:
+            s = eval_sum_symbolic(with_i, (i, a, b))
+            if s:
+                r = without_i*(b - a + 1) + s
+                if r is not S.NaN:
+                    return r
+        else:
+            # Try term by term
+            lsum = eval_sum_symbolic(L, (i, a, b))
+            rsum = eval_sum_symbolic(R, (i, a, b))
+
+            if None not in (lsum, rsum):
+                r = lsum + rsum
+                if r is not S.NaN:
+                    return r
+
+
+    # Polynomial terms with Faulhaber's formula
+    n = Wild('n')
+    result = f.match(i**n)
+
+    if result is not None:
+        n = result[n]
+
+        if n.is_Integer:
+            if n >= 0:
+                if (b is S.Infinity and a is not S.NegativeInfinity) or \
+                   (a is S.NegativeInfinity and b is not S.Infinity):
+                    return S.Infinity
+                return ((bernoulli(n + 1, b + 1) - bernoulli(n + 1, a))/(n + 1)).expand()
+            elif a.is_Integer and a >= 1:
+                if n == -1:
+                    return harmonic(b) - harmonic(a - 1)
+                else:
+                    return harmonic(b, abs(n)) - harmonic(a - 1, abs(n))
+
+    if not (a.has(S.Infinity, S.NegativeInfinity) or
+            b.has(S.Infinity, S.NegativeInfinity)):
+        # Geometric terms
+        c1 = Wild('c1', exclude=[i])
+        c2 = Wild('c2', exclude=[i])
+        c3 = Wild('c3', exclude=[i])
+        wexp = Wild('wexp')
+
+        # Here we first attempt powsimp on f for easier matching with the
+        # exponential pattern, and attempt expansion on the exponent for easier
+        # matching with the linear pattern.
+        e = f.powsimp().match(c1 ** wexp)
+        if e is not None:
+            e_exp = e.pop(wexp).expand().match(c2*i + c3)
+            if e_exp is not None:
+                e.update(e_exp)
+
+                p = (c1**c3).subs(e)
+                q = (c1**c2).subs(e)
+                r = p*(q**a - q**(b + 1))/(1 - q)
+                l = p*(b - a + 1)
+                return Piecewise((l, Eq(q, S.One)), (r, True))
+
+        r = gosper_sum(f, (i, a, b))
+
+        if isinstance(r, (Mul,Add)):
+            from sympy.simplify.radsimp import denom
+            from sympy.solvers.solvers import solve
+            non_limit = r.free_symbols - Tuple(*limits[1:]).free_symbols
+            den = denom(together(r))
+            den_sym = non_limit & den.free_symbols
+            args = []
+            for v in ordered(den_sym):
+                try:
+                    s = solve(den, v)
+                    m = Eq(v, s[0]) if s else S.false
+                    if m != False:
+                        args.append((Sum(f_orig.subs(*m.args), limits).doit(), m))
+                    break
+                except NotImplementedError:
+                    continue
+
+            args.append((r, True))
+            return Piecewise(*args)
+
+        if r not in (None, S.NaN):
+            return r
+
+    h = eval_sum_hyper(f_orig, (i, a, b))
+    if h is not None:
+        return h
+
+    r = eval_sum_residue(f_orig, (i, a, b))
+    if r is not None:
+        return r
+
+    factored = f_orig.factor()
+    if factored != f_orig:
+        return eval_sum_symbolic(factored, (i, a, b))
+
+
+def _eval_sum_hyper(f, i, a):
+    """ Returns (res, cond). Sums from a to oo. """
+    if a != 0:
+        return _eval_sum_hyper(f.subs(i, i + a), i, 0)
+
+    if f.subs(i, 0) == 0:
+        from sympy.simplify.simplify import simplify
+        if simplify(f.subs(i, Dummy('i', integer=True, positive=True))) == 0:
+            return S.Zero, True
+        return _eval_sum_hyper(f.subs(i, i + 1), i, 0)
+
+    from sympy.simplify.simplify import hypersimp
+    hs = hypersimp(f, i)
+    if hs is None:
+        return None
+
+    if isinstance(hs, Float):
+        from sympy.simplify.simplify import nsimplify
+        hs = nsimplify(hs)
+
+    from sympy.simplify.combsimp import combsimp
+    from sympy.simplify.hyperexpand import hyperexpand
+    from sympy.simplify.radsimp import fraction
+    numer, denom = fraction(factor(hs))
+    top, topl = numer.as_coeff_mul(i)
+    bot, botl = denom.as_coeff_mul(i)
+    ab = [top, bot]
+    factors = [topl, botl]
+    params = [[], []]
+    for k in range(2):
+        for fac in factors[k]:
+            mul = 1
+            if fac.is_Pow:
+                mul = fac.exp
+                fac = fac.base
+                if not mul.is_Integer:
+                    return None
+            p = Poly(fac, i)
+            if p.degree() != 1:
+                return None
+            m, n = p.all_coeffs()
+            ab[k] *= m**mul
+            params[k] += [n/m]*mul
+
+    # Add "1" to numerator parameters, to account for implicit n! in
+    # hypergeometric series.
+    ap = params[0] + [1]
+    bq = params[1]
+    x = ab[0]/ab[1]
+    h = hyper(ap, bq, x)
+    f = combsimp(f)
+    return f.subs(i, 0)*hyperexpand(h), h.convergence_statement
+
+
+def eval_sum_hyper(f, i_a_b):
+    i, a, b = i_a_b
+
+    if f.is_hypergeometric(i) is False:
+        return
+
+    if (b - a).is_Integer:
+        # We are never going to do better than doing the sum in the obvious way
+        return None
+
+    old_sum = Sum(f, (i, a, b))
+
+    if b != S.Infinity:
+        if a is S.NegativeInfinity:
+            res = _eval_sum_hyper(f.subs(i, -i), i, -b)
+            if res is not None:
+                return Piecewise(res, (old_sum, True))
+        else:
+            n_illegal = lambda x: sum(x.count(_) for _ in _illegal)
+            had = n_illegal(f)
+            # check that no extra illegals are introduced
+            res1 = _eval_sum_hyper(f, i, a)
+            if res1 is None or n_illegal(res1) > had:
+                return
+            res2 = _eval_sum_hyper(f, i, b + 1)
+            if res2 is None or n_illegal(res2) > had:
+                return
+            (res1, cond1), (res2, cond2) = res1, res2
+            cond = And(cond1, cond2)
+            if cond == False:
+                return None
+            return Piecewise((res1 - res2, cond), (old_sum, True))
+
+    if a is S.NegativeInfinity:
+        res1 = _eval_sum_hyper(f.subs(i, -i), i, 1)
+        res2 = _eval_sum_hyper(f, i, 0)
+        if res1 is None or res2 is None:
+            return None
+        res1, cond1 = res1
+        res2, cond2 = res2
+        cond = And(cond1, cond2)
+        if cond == False or cond.as_set() == S.EmptySet:
+            return None
+        return Piecewise((res1 + res2, cond), (old_sum, True))
+
+    # Now b == oo, a != -oo
+    res = _eval_sum_hyper(f, i, a)
+    if res is not None:
+        r, c = res
+        if c == False:
+            if r.is_number:
+                f = f.subs(i, Dummy('i', integer=True, positive=True) + a)
+                if f.is_positive or f.is_zero:
+                    return S.Infinity
+                elif f.is_negative:
+                    return S.NegativeInfinity
+            return None
+        return Piecewise(res, (old_sum, True))
+
+
+def eval_sum_residue(f, i_a_b):
+    r"""Compute the infinite summation with residues
+
+    Notes
+    =====
+
+    If $f(n), g(n)$ are polynomials with $\deg(g(n)) - \deg(f(n)) \ge 2$,
+    some infinite summations can be computed by the following residue
+    evaluations.
+
+    .. math::
+        \sum_{n=-\infty, g(n) \ne 0}^{\infty} \frac{f(n)}{g(n)} =
+        -\pi \sum_{\alpha|g(\alpha)=0}
+        \text{Res}(\cot(\pi x) \frac{f(x)}{g(x)}, \alpha)
+
+    .. math::
+        \sum_{n=-\infty, g(n) \ne 0}^{\infty} (-1)^n \frac{f(n)}{g(n)} =
+        -\pi \sum_{\alpha|g(\alpha)=0}
+        \text{Res}(\csc(\pi x) \frac{f(x)}{g(x)}, \alpha)
+
+    Examples
+    ========
+
+    >>> from sympy import Sum, oo, Symbol
+    >>> x = Symbol('x')
+
+    Doubly infinite series of rational functions.
+
+    >>> Sum(1 / (x**2 + 1), (x, -oo, oo)).doit()
+    pi/tanh(pi)
+
+    Doubly infinite alternating series of rational functions.
+
+    >>> Sum((-1)**x / (x**2 + 1), (x, -oo, oo)).doit()
+    pi/sinh(pi)
+
+    Infinite series of even rational functions.
+
+    >>> Sum(1 / (x**2 + 1), (x, 0, oo)).doit()
+    1/2 + pi/(2*tanh(pi))
+
+    Infinite series of alternating even rational functions.
+
+    >>> Sum((-1)**x / (x**2 + 1), (x, 0, oo)).doit()
+    pi/(2*sinh(pi)) + 1/2
+
+    This also have heuristics to transform arbitrarily shifted summand or
+    arbitrarily shifted summation range to the canonical problem the
+    formula can handle.
+
+    >>> Sum(1 / (x**2 + 2*x + 2), (x, -1, oo)).doit()
+    1/2 + pi/(2*tanh(pi))
+    >>> Sum(1 / (x**2 + 4*x + 5), (x, -2, oo)).doit()
+    1/2 + pi/(2*tanh(pi))
+    >>> Sum(1 / (x**2 + 1), (x, 1, oo)).doit()
+    -1/2 + pi/(2*tanh(pi))
+    >>> Sum(1 / (x**2 + 1), (x, 2, oo)).doit()
+    -1 + pi/(2*tanh(pi))
+
+    References
+    ==========
+
+    .. [#] http://www.supermath.info/InfiniteSeriesandtheResidueTheorem.pdf
+
+    .. [#] Asmar N.H., Grafakos L. (2018) Residue Theory.
+           In: Complex Analysis with Applications.
+           Undergraduate Texts in Mathematics. Springer, Cham.
+           https://doi.org/10.1007/978-3-319-94063-2_5
+    """
+    i, a, b = i_a_b
+
+    def is_even_function(numer, denom):
+        """Test if the rational function is an even function"""
+        numer_even = all(i % 2 == 0 for (i,) in numer.monoms())
+        denom_even = all(i % 2 == 0 for (i,) in denom.monoms())
+        numer_odd = all(i % 2 == 1 for (i,) in numer.monoms())
+        denom_odd = all(i % 2 == 1 for (i,) in denom.monoms())
+        return (numer_even and denom_even) or (numer_odd and denom_odd)
+
+    def match_rational(f, i):
+        numer, denom = f.as_numer_denom()
+        try:
+            (numer, denom), opt = parallel_poly_from_expr((numer, denom), i)
+        except (PolificationFailed, PolynomialError):
+            return None
+        return numer, denom
+
+    def get_poles(denom):
+        roots = denom.sqf_part().all_roots()
+        roots = sift(roots, lambda x: x.is_integer)
+        if None in roots:
+            return None
+        int_roots, nonint_roots = roots[True], roots[False]
+        return int_roots, nonint_roots
+
+    def get_shift(denom):
+        n = denom.degree(i)
+        a = denom.coeff_monomial(i**n)
+        b = denom.coeff_monomial(i**(n-1))
+        shift = - b / a / n
+        return shift
+
+    #Need a dummy symbol with no assumptions set for get_residue_factor
+    z = Dummy('z')
+
+    def get_residue_factor(numer, denom, alternating):
+        residue_factor = (numer.as_expr() / denom.as_expr()).subs(i, z)
+        if not alternating:
+            residue_factor *= cot(S.Pi * z)
+        else:
+            residue_factor *= csc(S.Pi * z)
+        return residue_factor
+
+    # We don't know how to deal with symbolic constants in summand
+    if f.free_symbols - {i}:
+        return None
+
+    if not (a.is_Integer or a in (S.Infinity, S.NegativeInfinity)):
+        return None
+    if not (b.is_Integer or b in (S.Infinity, S.NegativeInfinity)):
+        return None
+
+    # Quick exit heuristic for the sums which doesn't have infinite range
+    if a != S.NegativeInfinity and b != S.Infinity:
+        return None
+
+    match = match_rational(f, i)
+    if match:
+        alternating = False
+        numer, denom = match
+    else:
+        match = match_rational(f / S.NegativeOne**i, i)
+        if match:
+            alternating = True
+            numer, denom = match
+        else:
+            return None
+
+    if denom.degree(i) - numer.degree(i) < 2:
+        return None
+
+    if (a, b) == (S.NegativeInfinity, S.Infinity):
+        poles = get_poles(denom)
+        if poles is None:
+            return None
+        int_roots, nonint_roots = poles
+
+        if int_roots:
+            return None
+
+        residue_factor = get_residue_factor(numer, denom, alternating)
+        residues = [residue(residue_factor, z, root) for root in nonint_roots]
+        return -S.Pi * sum(residues)
+
+    if not (a.is_finite and b is S.Infinity):
+        return None
+
+    if not is_even_function(numer, denom):
+        # Try shifting summation and check if the summand can be made
+        # and even function from the origin.
+        # Sum(f(n), (n, a, b)) => Sum(f(n + s), (n, a - s, b - s))
+        shift = get_shift(denom)
+
+        if not shift.is_Integer:
+            return None
+        if shift == 0:
+            return None
+
+        numer = numer.shift(shift)
+        denom = denom.shift(shift)
+
+        if not is_even_function(numer, denom):
+            return None
+
+        if alternating:
+            f = S.NegativeOne**i * (S.NegativeOne**shift * numer.as_expr() / denom.as_expr())
+        else:
+            f = numer.as_expr() / denom.as_expr()
+        return eval_sum_residue(f, (i, a-shift, b-shift))
+
+    poles = get_poles(denom)
+    if poles is None:
+        return None
+    int_roots, nonint_roots = poles
+
+    if int_roots:
+        int_roots = [int(root) for root in int_roots]
+        int_roots_max = max(int_roots)
+        int_roots_min = min(int_roots)
+        # Integer valued poles must be next to each other
+        # and also symmetric from origin (Because the function is even)
+        if not len(int_roots) == int_roots_max - int_roots_min + 1:
+            return None
+
+        # Check whether the summation indices contain poles
+        if a <= max(int_roots):
+            return None
+
+    residue_factor = get_residue_factor(numer, denom, alternating)
+    residues = [residue(residue_factor, z, root) for root in int_roots + nonint_roots]
+    full_sum = -S.Pi * sum(residues)
+
+    if not int_roots:
+        # Compute Sum(f, (i, 0, oo)) by adding a extraneous evaluation
+        # at the origin.
+        half_sum = (full_sum + f.xreplace({i: 0})) / 2
+
+        # Add and subtract extraneous evaluations
+        extraneous_neg = [f.xreplace({i: i0}) for i0 in range(int(a), 0)]
+        extraneous_pos = [f.xreplace({i: i0}) for i0 in range(0, int(a))]
+        result = half_sum + sum(extraneous_neg) - sum(extraneous_pos)
+
+        return result
+
+    # Compute Sum(f, (i, min(poles) + 1, oo))
+    half_sum = full_sum / 2
+
+    # Subtract extraneous evaluations
+    extraneous = [f.xreplace({i: i0}) for i0 in range(max(int_roots) + 1, int(a))]
+    result = half_sum - sum(extraneous)
+
+    return result
+
+
+def _eval_matrix_sum(expression):
+    f = expression.function
+    for n, limit in enumerate(expression.limits):
+        i, a, b = limit
+        dif = b - a
+        if dif.is_Integer:
+            if (dif < 0) == True:
+                a, b = b + 1, a - 1
+                f = -f
+
+            newf = eval_sum_direct(f, (i, a, b))
+            if newf is not None:
+                return newf.doit()
+
+
+def _dummy_with_inherited_properties_concrete(limits):
+    """
+    Return a Dummy symbol that inherits as many assumptions as possible
+    from the provided symbol and limits.
+
+    If the symbol already has all True assumption shared by the limits
+    then return None.
+    """
+    x, a, b = limits
+    l = [a, b]
+
+    assumptions_to_consider = ['extended_nonnegative', 'nonnegative',
+                               'extended_nonpositive', 'nonpositive',
+                               'extended_positive', 'positive',
+                               'extended_negative', 'negative',
+                               'integer', 'rational', 'finite',
+                               'zero', 'real', 'extended_real']
+
+    assumptions_to_keep = {}
+    assumptions_to_add = {}
+    for assum in assumptions_to_consider:
+        assum_true = x._assumptions.get(assum, None)
+        if assum_true:
+            assumptions_to_keep[assum] = True
+        elif all(getattr(i, 'is_' + assum) for i in l):
+            assumptions_to_add[assum] = True
+    if assumptions_to_add:
+        assumptions_to_keep.update(assumptions_to_add)
+        return Dummy('d', **assumptions_to_keep)

venv/lib/python3.10/site-packages/sympy/concrete/tests/test_delta.py

@@ -0,0 +1,499 @@
+from sympy.concrete import Sum
+from sympy.concrete.delta import deltaproduct as dp, deltasummation as ds, _extract_delta
+from sympy.core import Eq, S, symbols, oo
+from sympy.functions import KroneckerDelta as KD, Piecewise, piecewise_fold
+from sympy.logic import And
+from sympy.testing.pytest import raises
+
+i, j, k, l, m = symbols("i j k l m", integer=True, finite=True)
+x, y = symbols("x y", commutative=False)
+
+
+def test_deltaproduct_trivial():
+    assert dp(x, (j, 1, 0)) == 1
+    assert dp(x, (j, 1, 3)) == x**3
+    assert dp(x + y, (j, 1, 3)) == (x + y)**3
+    assert dp(x*y, (j, 1, 3)) == (x*y)**3
+    assert dp(KD(i, j), (k, 1, 3)) == KD(i, j)
+    assert dp(x*KD(i, j), (k, 1, 3)) == x**3*KD(i, j)
+    assert dp(x*y*KD(i, j), (k, 1, 3)) == (x*y)**3*KD(i, j)
+
+
+def test_deltaproduct_basic():
+    assert dp(KD(i, j), (j, 1, 3)) == 0
+    assert dp(KD(i, j), (j, 1, 1)) == KD(i, 1)
+    assert dp(KD(i, j), (j, 2, 2)) == KD(i, 2)
+    assert dp(KD(i, j), (j, 3, 3)) == KD(i, 3)
+    assert dp(KD(i, j), (j, 1, k)) == KD(i, 1)*KD(k, 1) + KD(k, 0)
+    assert dp(KD(i, j), (j, k, 3)) == KD(i, 3)*KD(k, 3) + KD(k, 4)
+    assert dp(KD(i, j), (j, k, l)) == KD(i, l)*KD(k, l) + KD(k, l + 1)
+
+
+def test_deltaproduct_mul_x_kd():
+    assert dp(x*KD(i, j), (j, 1, 3)) == 0
+    assert dp(x*KD(i, j), (j, 1, 1)) == x*KD(i, 1)
+    assert dp(x*KD(i, j), (j, 2, 2)) == x*KD(i, 2)
+    assert dp(x*KD(i, j), (j, 3, 3)) == x*KD(i, 3)
+    assert dp(x*KD(i, j), (j, 1, k)) == x*KD(i, 1)*KD(k, 1) + KD(k, 0)
+    assert dp(x*KD(i, j), (j, k, 3)) == x*KD(i, 3)*KD(k, 3) + KD(k, 4)
+    assert dp(x*KD(i, j), (j, k, l)) == x*KD(i, l)*KD(k, l) + KD(k, l + 1)
+
+
+def test_deltaproduct_mul_add_x_y_kd():
+    assert dp((x + y)*KD(i, j), (j, 1, 3)) == 0
+    assert dp((x + y)*KD(i, j), (j, 1, 1)) == (x + y)*KD(i, 1)
+    assert dp((x + y)*KD(i, j), (j, 2, 2)) == (x + y)*KD(i, 2)
+    assert dp((x + y)*KD(i, j), (j, 3, 3)) == (x + y)*KD(i, 3)
+    assert dp((x + y)*KD(i, j), (j, 1, k)) == \
+        (x + y)*KD(i, 1)*KD(k, 1) + KD(k, 0)
+    assert dp((x + y)*KD(i, j), (j, k, 3)) == \
+        (x + y)*KD(i, 3)*KD(k, 3) + KD(k, 4)
+    assert dp((x + y)*KD(i, j), (j, k, l)) == \
+        (x + y)*KD(i, l)*KD(k, l) + KD(k, l + 1)
+
+
+def test_deltaproduct_add_kd_kd():
+    assert dp(KD(i, k) + KD(j, k), (k, 1, 3)) == 0
+    assert dp(KD(i, k) + KD(j, k), (k, 1, 1)) == KD(i, 1) + KD(j, 1)
+    assert dp(KD(i, k) + KD(j, k), (k, 2, 2)) == KD(i, 2) + KD(j, 2)
+    assert dp(KD(i, k) + KD(j, k), (k, 3, 3)) == KD(i, 3) + KD(j, 3)
+    assert dp(KD(i, k) + KD(j, k), (k, 1, l)) == KD(l, 0) + \
+        KD(i, 1)*KD(l, 1) + KD(j, 1)*KD(l, 1) + \
+        KD(i, 1)*KD(j, 2)*KD(l, 2) + KD(j, 1)*KD(i, 2)*KD(l, 2)
+    assert dp(KD(i, k) + KD(j, k), (k, l, 3)) == KD(l, 4) + \
+        KD(i, 3)*KD(l, 3) + KD(j, 3)*KD(l, 3) + \
+        KD(i, 2)*KD(j, 3)*KD(l, 2) + KD(i, 3)*KD(j, 2)*KD(l, 2)
+    assert dp(KD(i, k) + KD(j, k), (k, l, m)) == KD(l, m + 1) + \
+        KD(i, m)*KD(l, m) + KD(j, m)*KD(l, m) + \
+        KD(i, m)*KD(j, m - 1)*KD(l, m - 1) + KD(i, m - 1)*KD(j, m)*KD(l, m - 1)
+
+
+def test_deltaproduct_mul_x_add_kd_kd():
+    assert dp(x*(KD(i, k) + KD(j, k)), (k, 1, 3)) == 0
+    assert dp(x*(KD(i, k) + KD(j, k)), (k, 1, 1)) == x*(KD(i, 1) + KD(j, 1))
+    assert dp(x*(KD(i, k) + KD(j, k)), (k, 2, 2)) == x*(KD(i, 2) + KD(j, 2))
+    assert dp(x*(KD(i, k) + KD(j, k)), (k, 3, 3)) == x*(KD(i, 3) + KD(j, 3))
+    assert dp(x*(KD(i, k) + KD(j, k)), (k, 1, l)) == KD(l, 0) + \
+        x*KD(i, 1)*KD(l, 1) + x*KD(j, 1)*KD(l, 1) + \
+        x**2*KD(i, 1)*KD(j, 2)*KD(l, 2) + x**2*KD(j, 1)*KD(i, 2)*KD(l, 2)
+    assert dp(x*(KD(i, k) + KD(j, k)), (k, l, 3)) == KD(l, 4) + \
+        x*KD(i, 3)*KD(l, 3) + x*KD(j, 3)*KD(l, 3) + \
+        x**2*KD(i, 2)*KD(j, 3)*KD(l, 2) + x**2*KD(i, 3)*KD(j, 2)*KD(l, 2)
+    assert dp(x*(KD(i, k) + KD(j, k)), (k, l, m)) == KD(l, m + 1) + \
+        x*KD(i, m)*KD(l, m) + x*KD(j, m)*KD(l, m) + \
+        x**2*KD(i, m - 1)*KD(j, m)*KD(l, m - 1) + \
+        x**2*KD(i, m)*KD(j, m - 1)*KD(l, m - 1)
+
+
+def test_deltaproduct_mul_add_x_y_add_kd_kd():
+    assert dp((x + y)*(KD(i, k) + KD(j, k)), (k, 1, 3)) == 0
+    assert dp((x + y)*(KD(i, k) + KD(j, k)), (k, 1, 1)) == \
+        (x + y)*(KD(i, 1) + KD(j, 1))
+    assert dp((x + y)*(KD(i, k) + KD(j, k)), (k, 2, 2)) == \
+        (x + y)*(KD(i, 2) + KD(j, 2))
+    assert dp((x + y)*(KD(i, k) + KD(j, k)), (k, 3, 3)) == \
+        (x + y)*(KD(i, 3) + KD(j, 3))
+    assert dp((x + y)*(KD(i, k) + KD(j, k)), (k, 1, l)) == KD(l, 0) + \
+        (x + y)*KD(i, 1)*KD(l, 1) + (x + y)*KD(j, 1)*KD(l, 1) + \
+        (x + y)**2*KD(i, 1)*KD(j, 2)*KD(l, 2) + \
+        (x + y)**2*KD(j, 1)*KD(i, 2)*KD(l, 2)
+    assert dp((x + y)*(KD(i, k) + KD(j, k)), (k, l, 3)) == KD(l, 4) + \
+        (x + y)*KD(i, 3)*KD(l, 3) + (x + y)*KD(j, 3)*KD(l, 3) + \
+        (x + y)**2*KD(i, 2)*KD(j, 3)*KD(l, 2) + \
+        (x + y)**2*KD(i, 3)*KD(j, 2)*KD(l, 2)
+    assert dp((x + y)*(KD(i, k) + KD(j, k)), (k, l, m)) == KD(l, m + 1) + \
+        (x + y)*KD(i, m)*KD(l, m) + (x + y)*KD(j, m)*KD(l, m) + \
+        (x + y)**2*KD(i, m - 1)*KD(j, m)*KD(l, m - 1) + \
+        (x + y)**2*KD(i, m)*KD(j, m - 1)*KD(l, m - 1)
+
+
+def test_deltaproduct_add_mul_x_y_mul_x_kd():
+    assert dp(x*y + x*KD(i, j), (j, 1, 3)) == (x*y)**3 + \
+        x*(x*y)**2*KD(i, 1) + (x*y)*x*(x*y)*KD(i, 2) + (x*y)**2*x*KD(i, 3)
+    assert dp(x*y + x*KD(i, j), (j, 1, 1)) == x*y + x*KD(i, 1)
+    assert dp(x*y + x*KD(i, j), (j, 2, 2)) == x*y + x*KD(i, 2)
+    assert dp(x*y + x*KD(i, j), (j, 3, 3)) == x*y + x*KD(i, 3)
+    assert dp(x*y + x*KD(i, j), (j, 1, k)) == \
+        (x*y)**k + Piecewise(
+            ((x*y)**(i - 1)*x*(x*y)**(k - i), And(1 <= i, i <= k)),
+            (0, True)
+        )
+    assert dp(x*y + x*KD(i, j), (j, k, 3)) == \
+        (x*y)**(-k + 4) + Piecewise(
+            ((x*y)**(i - k)*x*(x*y)**(3 - i), And(k <= i, i <= 3)),
+            (0, True)
+        )
+    assert dp(x*y + x*KD(i, j), (j, k, l)) == \
+        (x*y)**(-k + l + 1) + Piecewise(
+            ((x*y)**(i - k)*x*(x*y)**(l - i), And(k <= i, i <= l)),
+            (0, True)
+        )
+
+
+def test_deltaproduct_mul_x_add_y_kd():
+    assert dp(x*(y + KD(i, j)), (j, 1, 3)) == (x*y)**3 + \
+        x*(x*y)**2*KD(i, 1) + (x*y)*x*(x*y)*KD(i, 2) + (x*y)**2*x*KD(i, 3)
+    assert dp(x*(y + KD(i, j)), (j, 1, 1)) == x*(y + KD(i, 1))
+    assert dp(x*(y + KD(i, j)), (j, 2, 2)) == x*(y + KD(i, 2))
+    assert dp(x*(y + KD(i, j)), (j, 3, 3)) == x*(y + KD(i, 3))
+    assert dp(x*(y + KD(i, j)), (j, 1, k)) == \
+        (x*y)**k + Piecewise(
+            ((x*y)**(i - 1)*x*(x*y)**(k - i), And(1 <= i, i <= k)),
+            (0, True)
+        ).expand()
+    assert dp(x*(y + KD(i, j)), (j, k, 3)) == \
+        ((x*y)**(-k + 4) + Piecewise(
+            ((x*y)**(i - k)*x*(x*y)**(3 - i), And(k <= i, i <= 3)),
+            (0, True)
+        )).expand()
+    assert dp(x*(y + KD(i, j)), (j, k, l)) == \
+        ((x*y)**(-k + l + 1) + Piecewise(
+            ((x*y)**(i - k)*x*(x*y)**(l - i), And(k <= i, i <= l)),
+            (0, True)
+        )).expand()
+
+
+def test_deltaproduct_mul_x_add_y_twokd():
+    assert dp(x*(y + 2*KD(i, j)), (j, 1, 3)) == (x*y)**3 + \
+        2*x*(x*y)**2*KD(i, 1) + 2*x*y*x*x*y*KD(i, 2) + 2*(x*y)**2*x*KD(i, 3)
+    assert dp(x*(y + 2*KD(i, j)), (j, 1, 1)) == x*(y + 2*KD(i, 1))
+    assert dp(x*(y + 2*KD(i, j)), (j, 2, 2)) == x*(y + 2*KD(i, 2))
+    assert dp(x*(y + 2*KD(i, j)), (j, 3, 3)) == x*(y + 2*KD(i, 3))
+    assert dp(x*(y + 2*KD(i, j)), (j, 1, k)) == \
+        (x*y)**k + Piecewise(
+            (2*(x*y)**(i - 1)*x*(x*y)**(k - i), And(1 <= i, i <= k)),
+            (0, True)
+        ).expand()
+    assert dp(x*(y + 2*KD(i, j)), (j, k, 3)) == \
+        ((x*y)**(-k + 4) + Piecewise(
+            (2*(x*y)**(i - k)*x*(x*y)**(3 - i), And(k <= i, i <= 3)),
+            (0, True)
+        )).expand()
+    assert dp(x*(y + 2*KD(i, j)), (j, k, l)) == \
+        ((x*y)**(-k + l + 1) + Piecewise(
+            (2*(x*y)**(i - k)*x*(x*y)**(l - i), And(k <= i, i <= l)),
+            (0, True)
+        )).expand()
+
+
+def test_deltaproduct_mul_add_x_y_add_y_kd():
+    assert dp((x + y)*(y + KD(i, j)), (j, 1, 3)) == ((x + y)*y)**3 + \
+        (x + y)*((x + y)*y)**2*KD(i, 1) + \
+        (x + y)*y*(x + y)**2*y*KD(i, 2) + \
+        ((x + y)*y)**2*(x + y)*KD(i, 3)
+    assert dp((x + y)*(y + KD(i, j)), (j, 1, 1)) == (x + y)*(y + KD(i, 1))
+    assert dp((x + y)*(y + KD(i, j)), (j, 2, 2)) == (x + y)*(y + KD(i, 2))
+    assert dp((x + y)*(y + KD(i, j)), (j, 3, 3)) == (x + y)*(y + KD(i, 3))
+    assert dp((x + y)*(y + KD(i, j)), (j, 1, k)) == \
+        ((x + y)*y)**k + Piecewise(
+            (((x + y)*y)**(-1)*((x + y)*y)**i*(x + y)*((x + y)*y
+            )**k*((x + y)*y)**(-i), (i >= 1) & (i <= k)), (0, True))
+    assert dp((x + y)*(y + KD(i, j)), (j, k, 3)) == (
+        (x + y)*y)**4*((x + y)*y)**(-k) + Piecewise((((x + y)*y)**i*(
+        (x + y)*y)**(-k)*(x + y)*((x + y)*y)**3*((x + y)*y)**(-i),
+        (i >= k) & (i <= 3)), (0, True))
+    assert dp((x + y)*(y + KD(i, j)), (j, k, l)) == \
+        (x + y)*y*((x + y)*y)**l*((x + y)*y)**(-k) + Piecewise(
+        (((x + y)*y)**i*((x + y)*y)**(-k)*(x + y)*((x + y)*y
+        )**l*((x + y)*y)**(-i), (i >= k) & (i <= l)), (0, True))
+
+
+def test_deltaproduct_mul_add_x_kd_add_y_kd():
+    assert dp((x + KD(i, k))*(y + KD(i, j)), (j, 1, 3)) == \
+        KD(i, 1)*(KD(i, k) + x)*((KD(i, k) + x)*y)**2 + \
+        KD(i, 2)*(KD(i, k) + x)*y*(KD(i, k) + x)**2*y + \
+        KD(i, 3)*((KD(i, k) + x)*y)**2*(KD(i, k) + x) + \
+        ((KD(i, k) + x)*y)**3
+    assert dp((x + KD(i, k))*(y + KD(i, j)), (j, 1, 1)) == \
+        (x + KD(i, k))*(y + KD(i, 1))
+    assert dp((x + KD(i, k))*(y + KD(i, j)), (j, 2, 2)) == \
+        (x + KD(i, k))*(y + KD(i, 2))
+    assert dp((x + KD(i, k))*(y + KD(i, j)), (j, 3, 3)) == \
+        (x + KD(i, k))*(y + KD(i, 3))
+    assert dp((x + KD(i, k))*(y + KD(i, j)), (j, 1, k)) == \
+        ((KD(i, k) + x)*y)**k + Piecewise(
+        (((KD(i, k) + x)*y)**(-1)*((KD(i, k) + x)*y)**i*(KD(i, k) + x
+        )*((KD(i, k) + x)*y)**k*((KD(i, k) + x)*y)**(-i), (i >= 1
+        ) & (i <= k)), (0, True))
+    assert dp((x + KD(i, k))*(y + KD(i, j)), (j, k, 3)) == (
+        (KD(i, k) + x)*y)**4*((KD(i, k) + x)*y)**(-k) + Piecewise(
+        (((KD(i, k) + x)*y)**i*((KD(i, k) + x)*y)**(-k)*(KD(i, k)
+        + x)*((KD(i, k) + x)*y)**3*((KD(i, k) + x)*y)**(-i),
+        (i >= k) & (i <= 3)), (0, True))
+    assert dp((x + KD(i, k))*(y + KD(i, j)), (j, k, l)) == (
+        KD(i, k) + x)*y*((KD(i, k) + x)*y)**l*((KD(i, k) + x)*y
+        )**(-k) + Piecewise((((KD(i, k) + x)*y)**i*((KD(i, k) + x
+        )*y)**(-k)*(KD(i, k) + x)*((KD(i, k) + x)*y)**l*((KD(i, k) + x
+        )*y)**(-i), (i >= k) & (i <= l)), (0, True))
+
+
+def test_deltasummation_trivial():
+    assert ds(x, (j, 1, 0)) == 0
+    assert ds(x, (j, 1, 3)) == 3*x
+    assert ds(x + y, (j, 1, 3)) == 3*(x + y)
+    assert ds(x*y, (j, 1, 3)) == 3*x*y
+    assert ds(KD(i, j), (k, 1, 3)) == 3*KD(i, j)
+    assert ds(x*KD(i, j), (k, 1, 3)) == 3*x*KD(i, j)
+    assert ds(x*y*KD(i, j), (k, 1, 3)) == 3*x*y*KD(i, j)
+
+
+def test_deltasummation_basic_numerical():
+    n = symbols('n', integer=True, nonzero=True)
+    assert ds(KD(n, 0), (n, 1, 3)) == 0
+
+    # return unevaluated, until it gets implemented
+    assert ds(KD(i**2, j**2), (j, -oo, oo)) == \
+        Sum(KD(i**2, j**2), (j, -oo, oo))
+
+    assert Piecewise((KD(i, k), And(1 <= i, i <= 3)), (0, True)) == \
+        ds(KD(i, j)*KD(j, k), (j, 1, 3)) == \
+        ds(KD(j, k)*KD(i, j), (j, 1, 3))
+
+    assert ds(KD(i, k), (k, -oo, oo)) == 1
+    assert ds(KD(i, k), (k, 0, oo)) == Piecewise((1, S.Zero <= i), (0, True))
+    assert ds(KD(i, k), (k, 1, 3)) == \
+        Piecewise((1, And(1 <= i, i <= 3)), (0, True))
+    assert ds(k*KD(i, j)*KD(j, k), (k, -oo, oo)) == j*KD(i, j)
+    assert ds(j*KD(i, j), (j, -oo, oo)) == i
+    assert ds(i*KD(i, j), (i, -oo, oo)) == j
+    assert ds(x, (i, 1, 3)) == 3*x
+    assert ds((i + j)*KD(i, j), (j, -oo, oo)) == 2*i
+
+
+def test_deltasummation_basic_symbolic():
+    assert ds(KD(i, j), (j, 1, 3)) == \
+        Piecewise((1, And(1 <= i, i <= 3)), (0, True))
+    assert ds(KD(i, j), (j, 1, 1)) == Piecewise((1, Eq(i, 1)), (0, True))
+    assert ds(KD(i, j), (j, 2, 2)) == Piecewise((1, Eq(i, 2)), (0, True))
+    assert ds(KD(i, j), (j, 3, 3)) == Piecewise((1, Eq(i, 3)), (0, True))
+    assert ds(KD(i, j), (j, 1, k)) == \
+        Piecewise((1, And(1 <= i, i <= k)), (0, True))
+    assert ds(KD(i, j), (j, k, 3)) == \
+        Piecewise((1, And(k <= i, i <= 3)), (0, True))
+    assert ds(KD(i, j), (j, k, l)) == \
+        Piecewise((1, And(k <= i, i <= l)), (0, True))
+
+
+def test_deltasummation_mul_x_kd():
+    assert ds(x*KD(i, j), (j, 1, 3)) == \
+        Piecewise((x, And(1 <= i, i <= 3)), (0, True))
+    assert ds(x*KD(i, j), (j, 1, 1)) == Piecewise((x, Eq(i, 1)), (0, True))
+    assert ds(x*KD(i, j), (j, 2, 2)) == Piecewise((x, Eq(i, 2)), (0, True))
+    assert ds(x*KD(i, j), (j, 3, 3)) == Piecewise((x, Eq(i, 3)), (0, True))
+    assert ds(x*KD(i, j), (j, 1, k)) == \
+        Piecewise((x, And(1 <= i, i <= k)), (0, True))
+    assert ds(x*KD(i, j), (j, k, 3)) == \
+        Piecewise((x, And(k <= i, i <= 3)), (0, True))
+    assert ds(x*KD(i, j), (j, k, l)) == \
+        Piecewise((x, And(k <= i, i <= l)), (0, True))
+
+
+def test_deltasummation_mul_add_x_y_kd():
+    assert ds((x + y)*KD(i, j), (j, 1, 3)) == \
+        Piecewise((x + y, And(1 <= i, i <= 3)), (0, True))
+    assert ds((x + y)*KD(i, j), (j, 1, 1)) == \
+        Piecewise((x + y, Eq(i, 1)), (0, True))
+    assert ds((x + y)*KD(i, j), (j, 2, 2)) == \
+        Piecewise((x + y, Eq(i, 2)), (0, True))
+    assert ds((x + y)*KD(i, j), (j, 3, 3)) == \
+        Piecewise((x + y, Eq(i, 3)), (0, True))
+    assert ds((x + y)*KD(i, j), (j, 1, k)) == \
+        Piecewise((x + y, And(1 <= i, i <= k)), (0, True))
+    assert ds((x + y)*KD(i, j), (j, k, 3)) == \
+        Piecewise((x + y, And(k <= i, i <= 3)), (0, True))
+    assert ds((x + y)*KD(i, j), (j, k, l)) == \
+        Piecewise((x + y, And(k <= i, i <= l)), (0, True))
+
+
+def test_deltasummation_add_kd_kd():
+    assert ds(KD(i, k) + KD(j, k), (k, 1, 3)) == piecewise_fold(
+        Piecewise((1, And(1 <= i, i <= 3)), (0, True)) +
+        Piecewise((1, And(1 <= j, j <= 3)), (0, True)))
+    assert ds(KD(i, k) + KD(j, k), (k, 1, 1)) == piecewise_fold(
+        Piecewise((1, Eq(i, 1)), (0, True)) +
+        Piecewise((1, Eq(j, 1)), (0, True)))
+    assert ds(KD(i, k) + KD(j, k), (k, 2, 2)) == piecewise_fold(
+        Piecewise((1, Eq(i, 2)), (0, True)) +
+        Piecewise((1, Eq(j, 2)), (0, True)))
+    assert ds(KD(i, k) + KD(j, k), (k, 3, 3)) == piecewise_fold(
+        Piecewise((1, Eq(i, 3)), (0, True)) +
+        Piecewise((1, Eq(j, 3)), (0, True)))
+    assert ds(KD(i, k) + KD(j, k), (k, 1, l)) == piecewise_fold(
+        Piecewise((1, And(1 <= i, i <= l)), (0, True)) +
+        Piecewise((1, And(1 <= j, j <= l)), (0, True)))
+    assert ds(KD(i, k) + KD(j, k), (k, l, 3)) == piecewise_fold(
+        Piecewise((1, And(l <= i, i <= 3)), (0, True)) +
+        Piecewise((1, And(l <= j, j <= 3)), (0, True)))
+    assert ds(KD(i, k) + KD(j, k), (k, l, m)) == piecewise_fold(
+        Piecewise((1, And(l <= i, i <= m)), (0, True)) +
+        Piecewise((1, And(l <= j, j <= m)), (0, True)))
+
+
+def test_deltasummation_add_mul_x_kd_kd():
+    assert ds(x*KD(i, k) + KD(j, k), (k, 1, 3)) == piecewise_fold(
+        Piecewise((x, And(1 <= i, i <= 3)), (0, True)) +
+        Piecewise((1, And(1 <= j, j <= 3)), (0, True)))
+    assert ds(x*KD(i, k) + KD(j, k), (k, 1, 1)) == piecewise_fold(
+        Piecewise((x, Eq(i, 1)), (0, True)) +
+        Piecewise((1, Eq(j, 1)), (0, True)))
+    assert ds(x*KD(i, k) + KD(j, k), (k, 2, 2)) == piecewise_fold(
+        Piecewise((x, Eq(i, 2)), (0, True)) +
+        Piecewise((1, Eq(j, 2)), (0, True)))
+    assert ds(x*KD(i, k) + KD(j, k), (k, 3, 3)) == piecewise_fold(
+        Piecewise((x, Eq(i, 3)), (0, True)) +
+        Piecewise((1, Eq(j, 3)), (0, True)))
+    assert ds(x*KD(i, k) + KD(j, k), (k, 1, l)) == piecewise_fold(
+        Piecewise((x, And(1 <= i, i <= l)), (0, True)) +
+        Piecewise((1, And(1 <= j, j <= l)), (0, True)))
+    assert ds(x*KD(i, k) + KD(j, k), (k, l, 3)) == piecewise_fold(
+        Piecewise((x, And(l <= i, i <= 3)), (0, True)) +
+        Piecewise((1, And(l <= j, j <= 3)), (0, True)))
+    assert ds(x*KD(i, k) + KD(j, k), (k, l, m)) == piecewise_fold(
+        Piecewise((x, And(l <= i, i <= m)), (0, True)) +
+        Piecewise((1, And(l <= j, j <= m)), (0, True)))
+
+
+def test_deltasummation_mul_x_add_kd_kd():
+    assert ds(x*(KD(i, k) + KD(j, k)), (k, 1, 3)) == piecewise_fold(
+        Piecewise((x, And(1 <= i, i <= 3)), (0, True)) +
+        Piecewise((x, And(1 <= j, j <= 3)), (0, True)))
+    assert ds(x*(KD(i, k) + KD(j, k)), (k, 1, 1)) == piecewise_fold(
+        Piecewise((x, Eq(i, 1)), (0, True)) +
+        Piecewise((x, Eq(j, 1)), (0, True)))
+    assert ds(x*(KD(i, k) + KD(j, k)), (k, 2, 2)) == piecewise_fold(
+        Piecewise((x, Eq(i, 2)), (0, True)) +
+        Piecewise((x, Eq(j, 2)), (0, True)))
+    assert ds(x*(KD(i, k) + KD(j, k)), (k, 3, 3)) == piecewise_fold(
+        Piecewise((x, Eq(i, 3)), (0, True)) +
+        Piecewise((x, Eq(j, 3)), (0, True)))
+    assert ds(x*(KD(i, k) + KD(j, k)), (k, 1, l)) == piecewise_fold(
+        Piecewise((x, And(1 <= i, i <= l)), (0, True)) +
+        Piecewise((x, And(1 <= j, j <= l)), (0, True)))
+    assert ds(x*(KD(i, k) + KD(j, k)), (k, l, 3)) == piecewise_fold(
+        Piecewise((x, And(l <= i, i <= 3)), (0, True)) +
+        Piecewise((x, And(l <= j, j <= 3)), (0, True)))
+    assert ds(x*(KD(i, k) + KD(j, k)), (k, l, m)) == piecewise_fold(
+        Piecewise((x, And(l <= i, i <= m)), (0, True)) +
+        Piecewise((x, And(l <= j, j <= m)), (0, True)))
+
+
+def test_deltasummation_mul_add_x_y_add_kd_kd():
+    assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, 1, 3)) == piecewise_fold(
+        Piecewise((x + y, And(1 <= i, i <= 3)), (0, True)) +
+        Piecewise((x + y, And(1 <= j, j <= 3)), (0, True)))
+    assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, 1, 1)) == piecewise_fold(
+        Piecewise((x + y, Eq(i, 1)), (0, True)) +
+        Piecewise((x + y, Eq(j, 1)), (0, True)))
+    assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, 2, 2)) == piecewise_fold(
+        Piecewise((x + y, Eq(i, 2)), (0, True)) +
+        Piecewise((x + y, Eq(j, 2)), (0, True)))
+    assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, 3, 3)) == piecewise_fold(
+        Piecewise((x + y, Eq(i, 3)), (0, True)) +
+        Piecewise((x + y, Eq(j, 3)), (0, True)))
+    assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, 1, l)) == piecewise_fold(
+        Piecewise((x + y, And(1 <= i, i <= l)), (0, True)) +
+        Piecewise((x + y, And(1 <= j, j <= l)), (0, True)))
+    assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, l, 3)) == piecewise_fold(
+        Piecewise((x + y, And(l <= i, i <= 3)), (0, True)) +
+        Piecewise((x + y, And(l <= j, j <= 3)), (0, True)))
+    assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, l, m)) == piecewise_fold(
+        Piecewise((x + y, And(l <= i, i <= m)), (0, True)) +
+        Piecewise((x + y, And(l <= j, j <= m)), (0, True)))
+
+
+def test_deltasummation_add_mul_x_y_mul_x_kd():
+    assert ds(x*y + x*KD(i, j), (j, 1, 3)) == \
+        Piecewise((3*x*y + x, And(1 <= i, i <= 3)), (3*x*y, True))
+    assert ds(x*y + x*KD(i, j), (j, 1, 1)) == \
+        Piecewise((x*y + x, Eq(i, 1)), (x*y, True))
+    assert ds(x*y + x*KD(i, j), (j, 2, 2)) == \
+        Piecewise((x*y + x, Eq(i, 2)), (x*y, True))
+    assert ds(x*y + x*KD(i, j), (j, 3, 3)) == \
+        Piecewise((x*y + x, Eq(i, 3)), (x*y, True))
+    assert ds(x*y + x*KD(i, j), (j, 1, k)) == \
+        Piecewise((k*x*y + x, And(1 <= i, i <= k)), (k*x*y, True))
+    assert ds(x*y + x*KD(i, j), (j, k, 3)) == \
+        Piecewise(((4 - k)*x*y + x, And(k <= i, i <= 3)), ((4 - k)*x*y, True))
+    assert ds(x*y + x*KD(i, j), (j, k, l)) == Piecewise(
+        ((l - k + 1)*x*y + x, And(k <= i, i <= l)), ((l - k + 1)*x*y, True))
+
+
+def test_deltasummation_mul_x_add_y_kd():
+    assert ds(x*(y + KD(i, j)), (j, 1, 3)) == \
+        Piecewise((3*x*y + x, And(1 <= i, i <= 3)), (3*x*y, True))
+    assert ds(x*(y + KD(i, j)), (j, 1, 1)) == \
+        Piecewise((x*y + x, Eq(i, 1)), (x*y, True))
+    assert ds(x*(y + KD(i, j)), (j, 2, 2)) == \
+        Piecewise((x*y + x, Eq(i, 2)), (x*y, True))
+    assert ds(x*(y + KD(i, j)), (j, 3, 3)) == \
+        Piecewise((x*y + x, Eq(i, 3)), (x*y, True))
+    assert ds(x*(y + KD(i, j)), (j, 1, k)) == \
+        Piecewise((k*x*y + x, And(1 <= i, i <= k)), (k*x*y, True))
+    assert ds(x*(y + KD(i, j)), (j, k, 3)) == \
+        Piecewise(((4 - k)*x*y + x, And(k <= i, i <= 3)), ((4 - k)*x*y, True))
+    assert ds(x*(y + KD(i, j)), (j, k, l)) == Piecewise(
+        ((l - k + 1)*x*y + x, And(k <= i, i <= l)), ((l - k + 1)*x*y, True))
+
+
+def test_deltasummation_mul_x_add_y_twokd():
+    assert ds(x*(y + 2*KD(i, j)), (j, 1, 3)) == \
+        Piecewise((3*x*y + 2*x, And(1 <= i, i <= 3)), (3*x*y, True))
+    assert ds(x*(y + 2*KD(i, j)), (j, 1, 1)) == \
+        Piecewise((x*y + 2*x, Eq(i, 1)), (x*y, True))
+    assert ds(x*(y + 2*KD(i, j)), (j, 2, 2)) == \
+        Piecewise((x*y + 2*x, Eq(i, 2)), (x*y, True))
+    assert ds(x*(y + 2*KD(i, j)), (j, 3, 3)) == \
+        Piecewise((x*y + 2*x, Eq(i, 3)), (x*y, True))
+    assert ds(x*(y + 2*KD(i, j)), (j, 1, k)) == \
+        Piecewise((k*x*y + 2*x, And(1 <= i, i <= k)), (k*x*y, True))
+    assert ds(x*(y + 2*KD(i, j)), (j, k, 3)) == Piecewise(
+        ((4 - k)*x*y + 2*x, And(k <= i, i <= 3)), ((4 - k)*x*y, True))
+    assert ds(x*(y + 2*KD(i, j)), (j, k, l)) == Piecewise(
+        ((l - k + 1)*x*y + 2*x, And(k <= i, i <= l)), ((l - k + 1)*x*y, True))
+
+
+def test_deltasummation_mul_add_x_y_add_y_kd():
+    assert ds((x + y)*(y + KD(i, j)), (j, 1, 3)) == Piecewise(
+        (3*(x + y)*y + x + y, And(1 <= i, i <= 3)), (3*(x + y)*y, True))
+    assert ds((x + y)*(y + KD(i, j)), (j, 1, 1)) == \
+        Piecewise(((x + y)*y + x + y, Eq(i, 1)), ((x + y)*y, True))
+    assert ds((x + y)*(y + KD(i, j)), (j, 2, 2)) == \
+        Piecewise(((x + y)*y + x + y, Eq(i, 2)), ((x + y)*y, True))
+    assert ds((x + y)*(y + KD(i, j)), (j, 3, 3)) == \
+        Piecewise(((x + y)*y + x + y, Eq(i, 3)), ((x + y)*y, True))
+    assert ds((x + y)*(y + KD(i, j)), (j, 1, k)) == Piecewise(
+        (k*(x + y)*y + x + y, And(1 <= i, i <= k)), (k*(x + y)*y, True))
+    assert ds((x + y)*(y + KD(i, j)), (j, k, 3)) == Piecewise(
+        ((4 - k)*(x + y)*y + x + y, And(k <= i, i <= 3)),
+        ((4 - k)*(x + y)*y, True))
+    assert ds((x + y)*(y + KD(i, j)), (j, k, l)) == Piecewise(
+        ((l - k + 1)*(x + y)*y + x + y, And(k <= i, i <= l)),
+        ((l - k + 1)*(x + y)*y, True))
+
+
+def test_deltasummation_mul_add_x_kd_add_y_kd():
+    assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 1, 3)) == piecewise_fold(
+        Piecewise((KD(i, k) + x, And(1 <= i, i <= 3)), (0, True)) +
+        3*(KD(i, k) + x)*y)
+    assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 1, 1)) == piecewise_fold(
+        Piecewise((KD(i, k) + x, Eq(i, 1)), (0, True)) +
+        (KD(i, k) + x)*y)
+    assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 2, 2)) == piecewise_fold(
+        Piecewise((KD(i, k) + x, Eq(i, 2)), (0, True)) +
+        (KD(i, k) + x)*y)
+    assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 3, 3)) == piecewise_fold(
+        Piecewise((KD(i, k) + x, Eq(i, 3)), (0, True)) +
+        (KD(i, k) + x)*y)
+    assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 1, k)) == piecewise_fold(
+        Piecewise((KD(i, k) + x, And(1 <= i, i <= k)), (0, True)) +
+        k*(KD(i, k) + x)*y)
+    assert ds((x + KD(i, k))*(y + KD(i, j)), (j, k, 3)) == piecewise_fold(
+        Piecewise((KD(i, k) + x, And(k <= i, i <= 3)), (0, True)) +
+        (4 - k)*(KD(i, k) + x)*y)
+    assert ds((x + KD(i, k))*(y + KD(i, j)), (j, k, l)) == piecewise_fold(
+        Piecewise((KD(i, k) + x, And(k <= i, i <= l)), (0, True)) +
+        (l - k + 1)*(KD(i, k) + x)*y)
+
+
+def test_extract_delta():
+    raises(ValueError, lambda: _extract_delta(KD(i, j) + KD(k, l), i))

venv/lib/python3.10/site-packages/sympy/concrete/tests/test_gosper.py

@@ -0,0 +1,204 @@
+"""Tests for Gosper's algorithm for hypergeometric summation. """
+
+from sympy.core.numbers import (Rational, pi)
+from sympy.core.singleton import S
+from sympy.core.symbol import Symbol
+from sympy.functions.combinatorial.factorials import (binomial, factorial)
+from sympy.functions.elementary.exponential import (exp, log)
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.functions.special.gamma_functions import gamma
+from sympy.polys.polytools import Poly
+from sympy.simplify.simplify import simplify
+from sympy.concrete.gosper import gosper_normal, gosper_sum, gosper_term
+from sympy.abc import a, b, j, k, m, n, r, x
+
+
+def test_gosper_normal():
+    eq = 4*n + 5, 2*(4*n + 1)*(2*n + 3), n
+    assert gosper_normal(*eq) == \
+        (Poly(Rational(1, 4), n), Poly(n + Rational(3, 2)), Poly(n + Rational(1, 4)))
+    assert gosper_normal(*eq, polys=False) == \
+        (Rational(1, 4), n + Rational(3, 2), n + Rational(1, 4))
+
+
+def test_gosper_term():
+    assert gosper_term((4*k + 1)*factorial(
+        k)/factorial(2*k + 1), k) == (-k - S.Half)/(k + Rational(1, 4))
+
+
+def test_gosper_sum():
+    assert gosper_sum(1, (k, 0, n)) == 1 + n
+    assert gosper_sum(k, (k, 0, n)) == n*(1 + n)/2
+    assert gosper_sum(k**2, (k, 0, n)) == n*(1 + n)*(1 + 2*n)/6
+    assert gosper_sum(k**3, (k, 0, n)) == n**2*(1 + n)**2/4
+
+    assert gosper_sum(2**k, (k, 0, n)) == 2*2**n - 1
+
+    assert gosper_sum(factorial(k), (k, 0, n)) is None
+    assert gosper_sum(binomial(n, k), (k, 0, n)) is None
+
+    assert gosper_sum(factorial(k)/k**2, (k, 0, n)) is None
+    assert gosper_sum((k - 3)*factorial(k), (k, 0, n)) is None
+
+    assert gosper_sum(k*factorial(k), k) == factorial(k)
+    assert gosper_sum(
+        k*factorial(k), (k, 0, n)) == n*factorial(n) + factorial(n) - 1
+
+    assert gosper_sum((-1)**k*binomial(n, k), (k, 0, n)) == 0
+    assert gosper_sum((
+        -1)**k*binomial(n, k), (k, 0, m)) == -(-1)**m*(m - n)*binomial(n, m)/n
+
+    assert gosper_sum((4*k + 1)*factorial(k)/factorial(2*k + 1), (k, 0, n)) == \
+        (2*factorial(2*n + 1) - factorial(n))/factorial(2*n + 1)
+
+    # issue 6033:
+    assert gosper_sum(
+        n*(n + a + b)*a**n*b**n/(factorial(n + a)*factorial(n + b)), \
+        (n, 0, m)).simplify() == -exp(m*log(a) + m*log(b))*gamma(a + 1) \
+        *gamma(b + 1)/(gamma(a)*gamma(b)*gamma(a + m + 1)*gamma(b + m + 1)) \
+        + 1/(gamma(a)*gamma(b))
+
+
+def test_gosper_sum_indefinite():
+    assert gosper_sum(k, k) == k*(k - 1)/2
+    assert gosper_sum(k**2, k) == k*(k - 1)*(2*k - 1)/6
+
+    assert gosper_sum(1/(k*(k + 1)), k) == -1/k
+    assert gosper_sum(-(27*k**4 + 158*k**3 + 430*k**2 + 678*k + 445)*gamma(2*k
+                      + 4)/(3*(3*k + 7)*gamma(3*k + 6)), k) == \
+        (3*k + 5)*(k**2 + 2*k + 5)*gamma(2*k + 4)/gamma(3*k + 6)
+
+
+def test_gosper_sum_parametric():
+    assert gosper_sum(binomial(S.Half, m - j + 1)*binomial(S.Half, m + j), (j, 1, n)) == \
+        n*(1 + m - n)*(-1 + 2*m + 2*n)*binomial(S.Half, 1 + m - n)* \
+        binomial(S.Half, m + n)/(m*(1 + 2*m))
+
+
+def test_gosper_sum_algebraic():
+    assert gosper_sum(
+        n**2 + sqrt(2), (n, 0, m)) == (m + 1)*(2*m**2 + m + 6*sqrt(2))/6
+
+
+def test_gosper_sum_iterated():
+    f1 = binomial(2*k, k)/4**k
+    f2 = (1 + 2*n)*binomial(2*n, n)/4**n
+    f3 = (1 + 2*n)*(3 + 2*n)*binomial(2*n, n)/(3*4**n)
+    f4 = (1 + 2*n)*(3 + 2*n)*(5 + 2*n)*binomial(2*n, n)/(15*4**n)
+    f5 = (1 + 2*n)*(3 + 2*n)*(5 + 2*n)*(7 + 2*n)*binomial(2*n, n)/(105*4**n)
+
+    assert gosper_sum(f1, (k, 0, n)) == f2
+    assert gosper_sum(f2, (n, 0, n)) == f3
+    assert gosper_sum(f3, (n, 0, n)) == f4
+    assert gosper_sum(f4, (n, 0, n)) == f5
+
+# the AeqB tests test expressions given in
+# www.math.upenn.edu/~wilf/AeqB.pdf
+
+
+def test_gosper_sum_AeqB_part1():
+    f1a = n**4
+    f1b = n**3*2**n
+    f1c = 1/(n**2 + sqrt(5)*n - 1)
+    f1d = n**4*4**n/binomial(2*n, n)
+    f1e = factorial(3*n)/(factorial(n)*factorial(n + 1)*factorial(n + 2)*27**n)
+    f1f = binomial(2*n, n)**2/((n + 1)*4**(2*n))
+    f1g = (4*n - 1)*binomial(2*n, n)**2/((2*n - 1)**2*4**(2*n))
+    f1h = n*factorial(n - S.Half)**2/factorial(n + 1)**2
+
+    g1a = m*(m + 1)*(2*m + 1)*(3*m**2 + 3*m - 1)/30
+    g1b = 26 + 2**(m + 1)*(m**3 - 3*m**2 + 9*m - 13)
+    g1c = (m + 1)*(m*(m**2 - 7*m + 3)*sqrt(5) - (
+        3*m**3 - 7*m**2 + 19*m - 6))/(2*m**3*sqrt(5) + m**4 + 5*m**2 - 1)/6
+    g1d = Rational(-2, 231) + 2*4**m*(m + 1)*(63*m**4 + 112*m**3 + 18*m**2 -
+             22*m + 3)/(693*binomial(2*m, m))
+    g1e = Rational(-9, 2) + (81*m**2 + 261*m + 200)*factorial(
+        3*m + 2)/(40*27**m*factorial(m)*factorial(m + 1)*factorial(m + 2))
+    g1f = (2*m + 1)**2*binomial(2*m, m)**2/(4**(2*m)*(m + 1))
+    g1g = -binomial(2*m, m)**2/4**(2*m)
+    g1h = 4*pi -(2*m + 1)**2*(3*m + 4)*factorial(m - S.Half)**2/factorial(m + 1)**2
+
+    g = gosper_sum(f1a, (n, 0, m))
+    assert g is not None and simplify(g - g1a) == 0
+    g = gosper_sum(f1b, (n, 0, m))
+    assert g is not None and simplify(g - g1b) == 0
+    g = gosper_sum(f1c, (n, 0, m))
+    assert g is not None and simplify(g - g1c) == 0
+    g = gosper_sum(f1d, (n, 0, m))
+    assert g is not None and simplify(g - g1d) == 0
+    g = gosper_sum(f1e, (n, 0, m))
+    assert g is not None and simplify(g - g1e) == 0
+    g = gosper_sum(f1f, (n, 0, m))
+    assert g is not None and simplify(g - g1f) == 0
+    g = gosper_sum(f1g, (n, 0, m))
+    assert g is not None and simplify(g - g1g) == 0
+    g = gosper_sum(f1h, (n, 0, m))
+    # need to call rewrite(gamma) here because we have terms involving
+    # factorial(1/2)
+    assert g is not None and simplify(g - g1h).rewrite(gamma) == 0
+
+
+def test_gosper_sum_AeqB_part2():
+    f2a = n**2*a**n
+    f2b = (n - r/2)*binomial(r, n)
+    f2c = factorial(n - 1)**2/(factorial(n - x)*factorial(n + x))
+
+    g2a = -a*(a + 1)/(a - 1)**3 + a**(
+        m + 1)*(a**2*m**2 - 2*a*m**2 + m**2 - 2*a*m + 2*m + a + 1)/(a - 1)**3
+    g2b = (m - r)*binomial(r, m)/2
+    ff = factorial(1 - x)*factorial(1 + x)
+    g2c = 1/ff*(
+        1 - 1/x**2) + factorial(m)**2/(x**2*factorial(m - x)*factorial(m + x))
+
+    g = gosper_sum(f2a, (n, 0, m))
+    assert g is not None and simplify(g - g2a) == 0
+    g = gosper_sum(f2b, (n, 0, m))
+    assert g is not None and simplify(g - g2b) == 0
+    g = gosper_sum(f2c, (n, 1, m))
+    assert g is not None and simplify(g - g2c) == 0
+
+
+def test_gosper_nan():
+    a = Symbol('a', positive=True)
+    b = Symbol('b', positive=True)
+    n = Symbol('n', integer=True)
+    m = Symbol('m', integer=True)
+    f2d = n*(n + a + b)*a**n*b**n/(factorial(n + a)*factorial(n + b))
+    g2d = 1/(factorial(a - 1)*factorial(
+        b - 1)) - a**(m + 1)*b**(m + 1)/(factorial(a + m)*factorial(b + m))
+    g = gosper_sum(f2d, (n, 0, m))
+    assert simplify(g - g2d) == 0
+
+
+def test_gosper_sum_AeqB_part3():
+    f3a = 1/n**4
+    f3b = (6*n + 3)/(4*n**4 + 8*n**3 + 8*n**2 + 4*n + 3)
+    f3c = 2**n*(n**2 - 2*n - 1)/(n**2*(n + 1)**2)
+    f3d = n**2*4**n/((n + 1)*(n + 2))
+    f3e = 2**n/(n + 1)
+    f3f = 4*(n - 1)*(n**2 - 2*n - 1)/(n**2*(n + 1)**2*(n - 2)**2*(n - 3)**2)
+    f3g = (n**4 - 14*n**2 - 24*n - 9)*2**n/(n**2*(n + 1)**2*(n + 2)**2*
+           (n + 3)**2)
+
+    # g3a -> no closed form
+    g3b = m*(m + 2)/(2*m**2 + 4*m + 3)
+    g3c = 2**m/m**2 - 2
+    g3d = Rational(2, 3) + 4**(m + 1)*(m - 1)/(m + 2)/3
+    # g3e -> no closed form
+    g3f = -(Rational(-1, 16) + 1/((m - 2)**2*(m + 1)**2))  # the AeqB key is wrong
+    g3g = Rational(-2, 9) + 2**(m + 1)/((m + 1)**2*(m + 3)**2)
+
+    g = gosper_sum(f3a, (n, 1, m))
+    assert g is None
+    g = gosper_sum(f3b, (n, 1, m))
+    assert g is not None and simplify(g - g3b) == 0
+    g = gosper_sum(f3c, (n, 1, m - 1))
+    assert g is not None and simplify(g - g3c) == 0
+    g = gosper_sum(f3d, (n, 1, m))
+    assert g is not None and simplify(g - g3d) == 0
+    g = gosper_sum(f3e, (n, 0, m - 1))
+    assert g is None
+    g = gosper_sum(f3f, (n, 4, m))
+    assert g is not None and simplify(g - g3f) == 0
+    g = gosper_sum(f3g, (n, 1, m))
+    assert g is not None and simplify(g - g3g) == 0

venv/lib/python3.10/site-packages/sympy/concrete/tests/test_guess.py

@@ -0,0 +1,82 @@
+from sympy.concrete.guess import (
+            find_simple_recurrence_vector,
+            find_simple_recurrence,
+            rationalize,
+            guess_generating_function_rational,
+            guess_generating_function,
+            guess
+        )
+from sympy.concrete.products import Product
+from sympy.core.function import Function
+from sympy.core.numbers import Rational
+from sympy.core.singleton import S
+from sympy.core.symbol import (Symbol, symbols)
+from sympy.core.sympify import sympify
+from sympy.functions.combinatorial.factorials import (RisingFactorial, factorial)
+from sympy.functions.combinatorial.numbers import fibonacci
+from sympy.functions.elementary.exponential import exp
+
+
+def test_find_simple_recurrence_vector():
+    assert find_simple_recurrence_vector(
+            [fibonacci(k) for k in range(12)]) == [1, -1, -1]
+
+
+def test_find_simple_recurrence():
+    a = Function('a')
+    n = Symbol('n')
+    assert find_simple_recurrence([fibonacci(k) for k in range(12)]) == (
+        -a(n) - a(n + 1) + a(n + 2))
+
+    f = Function('a')
+    i = Symbol('n')
+    a = [1, 1, 1]
+    for k in range(15): a.append(5*a[-1]-3*a[-2]+8*a[-3])
+    assert find_simple_recurrence(a, A=f, N=i) == (
+        -8*f(i) + 3*f(i + 1) - 5*f(i + 2) + f(i + 3))
+    assert find_simple_recurrence([0, 2, 15, 74, 12, 3, 0,
+                                    1, 2, 85, 4, 5, 63]) == 0
+
+
+def test_rationalize():
+    from mpmath import cos, pi, mpf
+    assert rationalize(cos(pi/3)) == S.Half
+    assert rationalize(mpf("0.333333333333333")) == Rational(1, 3)
+    assert rationalize(mpf("-0.333333333333333")) == Rational(-1, 3)
+    assert rationalize(pi, maxcoeff = 250) == Rational(355, 113)
+
+
+def test_guess_generating_function_rational():
+    x = Symbol('x')
+    assert guess_generating_function_rational([fibonacci(k)
+        for k in range(5, 15)]) == ((3*x + 5)/(-x**2 - x + 1))
+
+
+def test_guess_generating_function():
+    x = Symbol('x')
+    assert guess_generating_function([fibonacci(k)
+        for k in range(5, 15)])['ogf'] == ((3*x + 5)/(-x**2 - x + 1))
+    assert guess_generating_function(
+        [1, 2, 5, 14, 41, 124, 383, 1200, 3799, 12122, 38919])['ogf'] == (
+        (1/(x**4 + 2*x**2 - 4*x + 1))**S.Half)
+    assert guess_generating_function(sympify(
+       "[3/2, 11/2, 0, -121/2, -363/2, 121, 4719/2, 11495/2, -8712, -178717/2]")
+       )['ogf'] == (x + Rational(3, 2))/(11*x**2 - 3*x + 1)
+    assert guess_generating_function([factorial(k) for k in range(12)],
+       types=['egf'])['egf'] == 1/(-x + 1)
+    assert guess_generating_function([k+1 for k in range(12)],
+       types=['egf']) == {'egf': (x + 1)*exp(x), 'lgdegf': (x + 2)/(x + 1)}
+
+
+def test_guess():
+    i0, i1 = symbols('i0 i1')
+    assert guess([1, 2, 6, 24, 120], evaluate=False) == [Product(i1 + 1, (i1, 1, i0 - 1))]
+    assert guess([1, 2, 6, 24, 120]) == [RisingFactorial(2, i0 - 1)]
+    assert guess([1, 2, 7, 42, 429, 7436, 218348, 10850216], niter=4) == [
+        2**(i0 - 1)*(Rational(27, 16))**(i0**2/2 - 3*i0/2 +
+        1)*Product(RisingFactorial(Rational(5, 3), i1 - 1)*RisingFactorial(Rational(7, 3), i1
+        - 1)/(RisingFactorial(Rational(3, 2), i1 - 1)*RisingFactorial(Rational(5, 2), i1 -
+        1)), (i1, 1, i0 - 1))]
+    assert guess([1, 0, 2]) == []
+    x, y = symbols('x y')
+    assert guess([1, 2, 6, 24, 120], variables=[x, y]) == [RisingFactorial(2, x - 1)]

venv/lib/python3.10/site-packages/sympy/concrete/tests/test_products.py

@@ -0,0 +1,410 @@
+from sympy.concrete.products import (Product, product)
+from sympy.concrete.summations import Sum
+from sympy.core.function import (Derivative, Function, diff)
+from sympy.core.numbers import (Rational, oo, pi)
+from sympy.core.singleton import S
+from sympy.core.symbol import (Dummy, Symbol, symbols)
+from sympy.functions.combinatorial.factorials import (rf, factorial)
+from sympy.functions.elementary.exponential import (exp, log)
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.functions.elementary.trigonometric import (cos, sin)
+from sympy.functions.special.tensor_functions import KroneckerDelta
+from sympy.simplify.combsimp import combsimp
+from sympy.simplify.simplify import simplify
+from sympy.testing.pytest import raises
+
+a, k, n, m, x = symbols('a,k,n,m,x', integer=True)
+f = Function('f')
+
+
+def test_karr_convention():
+    # Test the Karr product convention that we want to hold.
+    # See his paper "Summation in Finite Terms" for a detailed
+    # reasoning why we really want exactly this definition.
+    # The convention is described for sums on page 309 and
+    # essentially in section 1.4, definition 3. For products
+    # we can find in analogy:
+    #
+    # \prod_{m <= i < n} f(i) 'has the obvious meaning'      for m < n
+    # \prod_{m <= i < n} f(i) = 0                            for m = n
+    # \prod_{m <= i < n} f(i) = 1 / \prod_{n <= i < m} f(i)  for m > n
+    #
+    # It is important to note that he defines all products with
+    # the upper limit being *exclusive*.
+    # In contrast, SymPy and the usual mathematical notation has:
+    #
+    # prod_{i = a}^b f(i) = f(a) * f(a+1) * ... * f(b-1) * f(b)
+    #
+    # with the upper limit *inclusive*. So translating between
+    # the two we find that:
+    #
+    # \prod_{m <= i < n} f(i) = \prod_{i = m}^{n-1} f(i)
+    #
+    # where we intentionally used two different ways to typeset the
+    # products and its limits.
+
+    i = Symbol("i", integer=True)
+    k = Symbol("k", integer=True)
+    j = Symbol("j", integer=True, positive=True)
+
+    # A simple example with a concrete factors and symbolic limits.
+
+    # The normal product: m = k and n = k + j and therefore m < n:
+    m = k
+    n = k + j
+
+    a = m
+    b = n - 1
+    S1 = Product(i**2, (i, a, b)).doit()
+
+    # The reversed product: m = k + j and n = k and therefore m > n:
+    m = k + j
+    n = k
+
+    a = m
+    b = n - 1
+    S2 = Product(i**2, (i, a, b)).doit()
+
+    assert S1 * S2 == 1
+
+    # Test the empty product: m = k and n = k and therefore m = n:
+    m = k
+    n = k
+
+    a = m
+    b = n - 1
+    Sz = Product(i**2, (i, a, b)).doit()
+
+    assert Sz == 1
+
+    # Another example this time with an unspecified factor and
+    # numeric limits. (We can not do both tests in the same example.)
+    f = Function("f")
+
+    # The normal product with m < n:
+    m = 2
+    n = 11
+
+    a = m
+    b = n - 1
+    S1 = Product(f(i), (i, a, b)).doit()
+
+    # The reversed product with m > n:
+    m = 11
+    n = 2
+
+    a = m
+    b = n - 1
+    S2 = Product(f(i), (i, a, b)).doit()
+
+    assert simplify(S1 * S2) == 1
+
+    # Test the empty product with m = n:
+    m = 5
+    n = 5
+
+    a = m
+    b = n - 1
+    Sz = Product(f(i), (i, a, b)).doit()
+
+    assert Sz == 1
+
+
+def test_karr_proposition_2a():
+    # Test Karr, page 309, proposition 2, part a
+    i, u, v = symbols('i u v', integer=True)
+
+    def test_the_product(m, n):
+        # g
+        g = i**3 + 2*i**2 - 3*i
+        # f = Delta g
+        f = simplify(g.subs(i, i+1) / g)
+        # The product
+        a = m
+        b = n - 1
+        P = Product(f, (i, a, b)).doit()
+        # Test if Product_{m <= i < n} f(i) = g(n) / g(m)
+        assert combsimp(P / (g.subs(i, n) / g.subs(i, m))) == 1
+
+    # m < n
+    test_the_product(u, u + v)
+    # m = n
+    test_the_product(u, u)
+    # m > n
+    test_the_product(u + v, u)
+
+
+def test_karr_proposition_2b():
+    # Test Karr, page 309, proposition 2, part b
+    i, u, v, w = symbols('i u v w', integer=True)
+
+    def test_the_product(l, n, m):
+        # Productmand
+        s = i**3
+        # First product
+        a = l
+        b = n - 1
+        S1 = Product(s, (i, a, b)).doit()
+        # Second product
+        a = l
+        b = m - 1
+        S2 = Product(s, (i, a, b)).doit()
+        # Third product
+        a = m
+        b = n - 1
+        S3 = Product(s, (i, a, b)).doit()
+        # Test if S1 = S2 * S3 as required
+        assert combsimp(S1 / (S2 * S3)) == 1
+
+    # l < m < n
+    test_the_product(u, u + v, u + v + w)
+    # l < m = n
+    test_the_product(u, u + v, u + v)
+    # l < m > n
+    test_the_product(u, u + v + w, v)
+    # l = m < n
+    test_the_product(u, u, u + v)
+    # l = m = n
+    test_the_product(u, u, u)
+    # l = m > n
+    test_the_product(u + v, u + v, u)
+    # l > m < n
+    test_the_product(u + v, u, u + w)
+    # l > m = n
+    test_the_product(u + v, u, u)
+    # l > m > n
+    test_the_product(u + v + w, u + v, u)
+
+
+def test_simple_products():
+    assert product(2, (k, a, n)) == 2**(n - a + 1)
+    assert product(k, (k, 1, n)) == factorial(n)
+    assert product(k**3, (k, 1, n)) == factorial(n)**3
+
+    assert product(k + 1, (k, 0, n - 1)) == factorial(n)
+    assert product(k + 1, (k, a, n - 1)) == rf(1 + a, n - a)
+
+    assert product(cos(k), (k, 0, 5)) == cos(1)*cos(2)*cos(3)*cos(4)*cos(5)
+    assert product(cos(k), (k, 3, 5)) == cos(3)*cos(4)*cos(5)
+    assert product(cos(k), (k, 1, Rational(5, 2))) != cos(1)*cos(2)
+
+    assert isinstance(product(k**k, (k, 1, n)), Product)
+
+    assert Product(x**k, (k, 1, n)).variables == [k]
+
+    raises(ValueError, lambda: Product(n))
+    raises(ValueError, lambda: Product(n, k))
+    raises(ValueError, lambda: Product(n, k, 1))
+    raises(ValueError, lambda: Product(n, k, 1, 10))
+    raises(ValueError, lambda: Product(n, (k, 1)))
+
+    assert product(1, (n, 1, oo)) == 1  # issue 8301
+    assert product(2, (n, 1, oo)) is oo
+    assert product(-1, (n, 1, oo)).func is Product
+
+
+def test_multiple_products():
+    assert product(x, (n, 1, k), (k, 1, m)) == x**(m**2/2 + m/2)
+    assert product(f(n), (
+        n, 1, m), (m, 1, k)) == Product(f(n), (n, 1, m), (m, 1, k)).doit()
+    assert Product(f(n), (m, 1, k), (n, 1, k)).doit() == \
+        Product(Product(f(n), (m, 1, k)), (n, 1, k)).doit() == \
+        product(f(n), (m, 1, k), (n, 1, k)) == \
+        product(product(f(n), (m, 1, k)), (n, 1, k)) == \
+        Product(f(n)**k, (n, 1, k))
+    assert Product(
+        x, (x, 1, k), (k, 1, n)).doit() == Product(factorial(k), (k, 1, n))
+
+    assert Product(x**k, (n, 1, k), (k, 1, m)).variables == [n, k]
+
+
+def test_rational_products():
+    assert product(1 + 1/k, (k, 1, n)) == rf(2, n)/factorial(n)
+
+
+def test_special_products():
+    # Wallis product
+    assert product((4*k)**2 / (4*k**2 - 1), (k, 1, n)) == \
+        4**n*factorial(n)**2/rf(S.Half, n)/rf(Rational(3, 2), n)
+
+    # Euler's product formula for sin
+    assert product(1 + a/k**2, (k, 1, n)) == \
+        rf(1 - sqrt(-a), n)*rf(1 + sqrt(-a), n)/factorial(n)**2
+
+
+def test__eval_product():
+    from sympy.abc import i, n
+    # issue 4809
+    a = Function('a')
+    assert product(2*a(i), (i, 1, n)) == 2**n * Product(a(i), (i, 1, n))
+    # issue 4810
+    assert product(2**i, (i, 1, n)) == 2**(n*(n + 1)/2)
+    k, m = symbols('k m', integer=True)
+    assert product(2**i, (i, k, m)) == 2**(-k**2/2 + k/2 + m**2/2 + m/2)
+    n = Symbol('n', negative=True, integer=True)
+    p = Symbol('p', positive=True, integer=True)
+    assert product(2**i, (i, n, p)) == 2**(-n**2/2 + n/2 + p**2/2 + p/2)
+    assert product(2**i, (i, p, n)) == 2**(n**2/2 + n/2 - p**2/2 + p/2)
+
+
+def test_product_pow():
+    # issue 4817
+    assert product(2**f(k), (k, 1, n)) == 2**Sum(f(k), (k, 1, n))
+    assert product(2**(2*f(k)), (k, 1, n)) == 2**Sum(2*f(k), (k, 1, n))
+
+
+def test_infinite_product():
+    # issue 5737
+    assert isinstance(Product(2**(1/factorial(n)), (n, 0, oo)), Product)
+
+
+def test_conjugate_transpose():
+    p = Product(x**k, (k, 1, 3))
+    assert p.adjoint().doit() == p.doit().adjoint()
+    assert p.conjugate().doit() == p.doit().conjugate()
+    assert p.transpose().doit() == p.doit().transpose()
+
+    A, B = symbols("A B", commutative=False)
+    p = Product(A*B**k, (k, 1, 3))
+    assert p.adjoint().doit() == p.doit().adjoint()
+    assert p.conjugate().doit() == p.doit().conjugate()
+    assert p.transpose().doit() == p.doit().transpose()
+
+    p = Product(B**k*A, (k, 1, 3))
+    assert p.adjoint().doit() == p.doit().adjoint()
+    assert p.conjugate().doit() == p.doit().conjugate()
+    assert p.transpose().doit() == p.doit().transpose()
+
+
+def test_simplify_prod():
+    y, t, b, c, v, d = symbols('y, t, b, c, v, d', integer = True)
+
+    _simplify = lambda e: simplify(e, doit=False)
+    assert _simplify(Product(x*y, (x, n, m), (y, a, k)) * \
+        Product(y, (x, n, m), (y, a, k))) == \
+            Product(x*y**2, (x, n, m), (y, a, k))
+    assert _simplify(3 * y* Product(x, (x, n, m)) * Product(x, (x, m + 1, a))) \
+        == 3 * y * Product(x, (x, n, a))
+    assert _simplify(Product(x, (x, k + 1, a)) * Product(x, (x, n, k))) == \
+        Product(x, (x, n, a))
+    assert _simplify(Product(x, (x, k + 1, a)) * Product(x + 1, (x, n, k))) == \
+        Product(x, (x, k + 1, a)) * Product(x + 1, (x, n, k))
+    assert _simplify(Product(x, (t, a, b)) * Product(y, (t, a, b)) * \
+        Product(x, (t, b+1, c))) == Product(x*y, (t, a, b)) * \
+            Product(x, (t, b+1, c))
+    assert _simplify(Product(x, (t, a, b)) * Product(x, (t, b+1, c)) * \
+        Product(y, (t, a, b))) == Product(x*y, (t, a, b)) * \
+            Product(x, (t, b+1, c))
+    assert _simplify(Product(sin(t)**2 + cos(t)**2 + 1, (t, a, b))) == \
+        Product(2, (t, a, b))
+    assert _simplify(Product(sin(t)**2 + cos(t)**2 - 1, (t, a, b))) == \
+           Product(0, (t, a, b))
+    assert _simplify(Product(v*Product(sin(t)**2 + cos(t)**2, (t, a, b)),
+                             (v, c, d))) == Product(v*Product(1, (t, a, b)), (v, c, d))
+
+
+def test_change_index():
+    b, y, c, d, z = symbols('b, y, c, d, z', integer = True)
+
+    assert Product(x, (x, a, b)).change_index(x, x + 1, y) == \
+        Product(y - 1, (y, a + 1, b + 1))
+    assert Product(x**2, (x, a, b)).change_index(x, x - 1) == \
+        Product((x + 1)**2, (x, a - 1, b - 1))
+    assert Product(x**2, (x, a, b)).change_index(x, -x, y) == \
+        Product((-y)**2, (y, -b, -a))
+    assert Product(x, (x, a, b)).change_index(x, -x - 1) == \
+        Product(-x - 1, (x, - b - 1, -a - 1))
+    assert Product(x*y, (x, a, b), (y, c, d)).change_index(x, x - 1, z) == \
+        Product((z + 1)*y, (z, a - 1, b - 1), (y, c, d))
+
+
+def test_reorder():
+    b, y, c, d, z = symbols('b, y, c, d, z', integer = True)
+
+    assert Product(x*y, (x, a, b), (y, c, d)).reorder((0, 1)) == \
+        Product(x*y, (y, c, d), (x, a, b))
+    assert Product(x, (x, a, b), (x, c, d)).reorder((0, 1)) == \
+        Product(x, (x, c, d), (x, a, b))
+    assert Product(x*y + z, (x, a, b), (z, m, n), (y, c, d)).reorder(\
+        (2, 0), (0, 1)) == Product(x*y + z, (z, m, n), (y, c, d), (x, a, b))
+    assert Product(x*y*z, (x, a, b), (y, c, d), (z, m, n)).reorder(\
+        (0, 1), (1, 2), (0, 2)) == \
+        Product(x*y*z, (x, a, b), (z, m, n), (y, c, d))
+    assert Product(x*y*z, (x, a, b), (y, c, d), (z, m, n)).reorder(\
+        (x, y), (y, z), (x, z)) == \
+        Product(x*y*z, (x, a, b), (z, m, n), (y, c, d))
+    assert Product(x*y, (x, a, b), (y, c, d)).reorder((x, 1)) == \
+        Product(x*y, (y, c, d), (x, a, b))
+    assert Product(x*y, (x, a, b), (y, c, d)).reorder((y, x)) == \
+        Product(x*y, (y, c, d), (x, a, b))
+
+
+def test_Product_is_convergent():
+    assert Product(1/n**2, (n, 1, oo)).is_convergent() is S.false
+    assert Product(exp(1/n**2), (n, 1, oo)).is_convergent() is S.true
+    assert Product(1/n, (n, 1, oo)).is_convergent() is S.false
+    assert Product(1 + 1/n, (n, 1, oo)).is_convergent() is S.false
+    assert Product(1 + 1/n**2, (n, 1, oo)).is_convergent() is S.true
+
+
+def test_reverse_order():
+    x, y, a, b, c, d= symbols('x, y, a, b, c, d', integer = True)
+
+    assert Product(x, (x, 0, 3)).reverse_order(0) == Product(1/x, (x, 4, -1))
+    assert Product(x*y, (x, 1, 5), (y, 0, 6)).reverse_order(0, 1) == \
+           Product(x*y, (x, 6, 0), (y, 7, -1))
+    assert Product(x, (x, 1, 2)).reverse_order(0) == Product(1/x, (x, 3, 0))
+    assert Product(x, (x, 1, 3)).reverse_order(0) == Product(1/x, (x, 4, 0))
+    assert Product(x, (x, 1, a)).reverse_order(0) == Product(1/x, (x, a + 1, 0))
+    assert Product(x, (x, a, 5)).reverse_order(0) == Product(1/x, (x, 6, a - 1))
+    assert Product(x, (x, a + 1, a + 5)).reverse_order(0) == \
+           Product(1/x, (x, a + 6, a))
+    assert Product(x, (x, a + 1, a + 2)).reverse_order(0) == \
+           Product(1/x, (x, a + 3, a))
+    assert Product(x, (x, a + 1, a + 1)).reverse_order(0) == \
+           Product(1/x, (x, a + 2, a))
+    assert Product(x, (x, a, b)).reverse_order(0) == Product(1/x, (x, b + 1, a - 1))
+    assert Product(x, (x, a, b)).reverse_order(x) == Product(1/x, (x, b + 1, a - 1))
+    assert Product(x*y, (x, a, b), (y, 2, 5)).reverse_order(x, 1) == \
+           Product(x*y, (x, b + 1, a - 1), (y, 6, 1))
+    assert Product(x*y, (x, a, b), (y, 2, 5)).reverse_order(y, x) == \
+           Product(x*y, (x, b + 1, a - 1), (y, 6, 1))
+
+
+def test_issue_9983():
+    n = Symbol('n', integer=True, positive=True)
+    p = Product(1 + 1/n**Rational(2, 3), (n, 1, oo))
+    assert p.is_convergent() is S.false
+    assert product(1 + 1/n**Rational(2, 3), (n, 1, oo)) == p.doit()
+
+
+def test_issue_13546():
+    n = Symbol('n')
+    k = Symbol('k')
+    p = Product(n + 1 / 2**k, (k, 0, n-1)).doit()
+    assert p.subs(n, 2).doit() == Rational(15, 2)
+
+
+def test_issue_14036():
+    a, n = symbols('a n')
+    assert product(1 - a**2 / (n*pi)**2, [n, 1, oo]) != 0
+
+
+def test_rewrite_Sum():
+    assert Product(1 - S.Half**2/k**2, (k, 1, oo)).rewrite(Sum) == \
+        exp(Sum(log(1 - 1/(4*k**2)), (k, 1, oo)))
+
+
+def test_KroneckerDelta_Product():
+    y = Symbol('y')
+    assert Product(x*KroneckerDelta(x, y), (x, 0, 1)).doit() == 0
+
+
+def test_issue_20848():
+    _i = Dummy('i')
+    t, y, z = symbols('t y z')
+    assert diff(Product(x, (y, 1, z)), x).as_dummy() == Sum(Product(x, (y, 1, _i - 1))*Product(x, (y, _i + 1, z)), (_i, 1, z)).as_dummy()
+    assert diff(Product(x, (y, 1, z)), x).doit() == x**(z - 1)*z
+    assert diff(Product(x, (y, x, z)), x) == Derivative(Product(x, (y, x, z)), x)
+    assert diff(Product(t, (x, 1, z)), x) == S(0)
+    assert Product(sin(n*x), (n, -1, 1)).diff(x).doit() == S(0)

venv/lib/python3.10/site-packages/sympy/concrete/tests/test_sums_products.py

@@ -0,0 +1,1646 @@
+from math import prod
+
+from sympy.concrete.expr_with_intlimits import ReorderError
+from sympy.concrete.products import (Product, product)
+from sympy.concrete.summations import (Sum, summation, telescopic,
+     eval_sum_residue, _dummy_with_inherited_properties_concrete)
+from sympy.core.function import (Derivative, Function)
+from sympy.core import (Catalan, EulerGamma)
+from sympy.core.facts import InconsistentAssumptions
+from sympy.core.mod import Mod
+from sympy.core.numbers import (E, I, Rational, nan, oo, pi)
+from sympy.core.relational import Eq
+from sympy.core.numbers import Float
+from sympy.core.singleton import S
+from sympy.core.symbol import (Dummy, Symbol, symbols)
+from sympy.core.sympify import sympify
+from sympy.functions.combinatorial.factorials import (rf, binomial, factorial)
+from sympy.functions.combinatorial.numbers import harmonic
+from sympy.functions.elementary.complexes import Abs
+from sympy.functions.elementary.exponential import (exp, log)
+from sympy.functions.elementary.hyperbolic import (sinh, tanh)
+from sympy.functions.elementary.integers import floor
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.functions.elementary.piecewise import Piecewise
+from sympy.functions.elementary.trigonometric import (cos, sin)
+from sympy.functions.special.gamma_functions import (gamma, lowergamma)
+from sympy.functions.special.tensor_functions import KroneckerDelta
+from sympy.functions.special.zeta_functions import zeta
+from sympy.integrals.integrals import Integral
+from sympy.logic.boolalg import And, Or
+from sympy.matrices.expressions.matexpr import MatrixSymbol
+from sympy.matrices.expressions.special import Identity
+from sympy.matrices import (Matrix, SparseMatrix,
+    ImmutableDenseMatrix, ImmutableSparseMatrix, diag)
+from sympy.sets.fancysets import Range
+from sympy.sets.sets import Interval
+from sympy.simplify.combsimp import combsimp
+from sympy.simplify.simplify import simplify
+from sympy.tensor.indexed import (Idx, Indexed, IndexedBase)
+from sympy.testing.pytest import XFAIL, raises, slow
+from sympy.abc import a, b, c, d, k, m, x, y, z
+
+n = Symbol('n', integer=True)
+f, g = symbols('f g', cls=Function)
+
+def test_karr_convention():
+    # Test the Karr summation convention that we want to hold.
+    # See his paper "Summation in Finite Terms" for a detailed
+    # reasoning why we really want exactly this definition.
+    # The convention is described on page 309 and essentially
+    # in section 1.4, definition 3:
+    #
+    # \sum_{m <= i < n} f(i) 'has the obvious meaning'   for m < n
+    # \sum_{m <= i < n} f(i) = 0                         for m = n
+    # \sum_{m <= i < n} f(i) = - \sum_{n <= i < m} f(i)  for m > n
+    #
+    # It is important to note that he defines all sums with
+    # the upper limit being *exclusive*.
+    # In contrast, SymPy and the usual mathematical notation has:
+    #
+    # sum_{i = a}^b f(i) = f(a) + f(a+1) + ... + f(b-1) + f(b)
+    #
+    # with the upper limit *inclusive*. So translating between
+    # the two we find that:
+    #
+    # \sum_{m <= i < n} f(i) = \sum_{i = m}^{n-1} f(i)
+    #
+    # where we intentionally used two different ways to typeset the
+    # sum and its limits.
+
+    i = Symbol("i", integer=True)
+    k = Symbol("k", integer=True)
+    j = Symbol("j", integer=True)
+
+    # A simple example with a concrete summand and symbolic limits.
+
+    # The normal sum: m = k and n = k + j and therefore m < n:
+    m = k
+    n = k + j
+
+    a = m
+    b = n - 1
+    S1 = Sum(i**2, (i, a, b)).doit()
+
+    # The reversed sum: m = k + j and n = k and therefore m > n:
+    m = k + j
+    n = k
+
+    a = m
+    b = n - 1
+    S2 = Sum(i**2, (i, a, b)).doit()
+
+    assert simplify(S1 + S2) == 0
+
+    # Test the empty sum: m = k and n = k and therefore m = n:
+    m = k
+    n = k
+
+    a = m
+    b = n - 1
+    Sz = Sum(i**2, (i, a, b)).doit()
+
+    assert Sz == 0
+
+    # Another example this time with an unspecified summand and
+    # numeric limits. (We can not do both tests in the same example.)
+
+    # The normal sum with m < n:
+    m = 2
+    n = 11
+
+    a = m
+    b = n - 1
+    S1 = Sum(f(i), (i, a, b)).doit()
+
+    # The reversed sum with m > n:
+    m = 11
+    n = 2
+
+    a = m
+    b = n - 1
+    S2 = Sum(f(i), (i, a, b)).doit()
+
+    assert simplify(S1 + S2) == 0
+
+    # Test the empty sum with m = n:
+    m = 5
+    n = 5
+
+    a = m
+    b = n - 1
+    Sz = Sum(f(i), (i, a, b)).doit()
+
+    assert Sz == 0
+
+    e = Piecewise((exp(-i), Mod(i, 2) > 0), (0, True))
+    s = Sum(e, (i, 0, 11))
+    assert s.n(3) == s.doit().n(3)
+
+
+def test_karr_proposition_2a():
+    # Test Karr, page 309, proposition 2, part a
+    i = Symbol("i", integer=True)
+    u = Symbol("u", integer=True)
+    v = Symbol("v", integer=True)
+
+    def test_the_sum(m, n):
+        # g
+        g = i**3 + 2*i**2 - 3*i
+        # f = Delta g
+        f = simplify(g.subs(i, i+1) - g)
+        # The sum
+        a = m
+        b = n - 1
+        S = Sum(f, (i, a, b)).doit()
+        # Test if Sum_{m <= i < n} f(i) = g(n) - g(m)
+        assert simplify(S - (g.subs(i, n) - g.subs(i, m))) == 0
+
+    # m < n
+    test_the_sum(u,   u+v)
+    # m = n
+    test_the_sum(u,   u  )
+    # m > n
+    test_the_sum(u+v, u  )
+
+
+def test_karr_proposition_2b():
+    # Test Karr, page 309, proposition 2, part b
+    i = Symbol("i", integer=True)
+    u = Symbol("u", integer=True)
+    v = Symbol("v", integer=True)
+    w = Symbol("w", integer=True)
+
+    def test_the_sum(l, n, m):
+        # Summand
+        s = i**3
+        # First sum
+        a = l
+        b = n - 1
+        S1 = Sum(s, (i, a, b)).doit()
+        # Second sum
+        a = l
+        b = m - 1
+        S2 = Sum(s, (i, a, b)).doit()
+        # Third sum
+        a = m
+        b = n - 1
+        S3 = Sum(s, (i, a, b)).doit()
+        # Test if S1 = S2 + S3 as required
+        assert S1 - (S2 + S3) == 0
+
+    # l < m < n
+    test_the_sum(u,     u+v,   u+v+w)
+    # l < m = n
+    test_the_sum(u,     u+v,   u+v  )
+    # l < m > n
+    test_the_sum(u,     u+v+w, v    )
+    # l = m < n
+    test_the_sum(u,     u,     u+v  )
+    # l = m = n
+    test_the_sum(u,     u,     u    )
+    # l = m > n
+    test_the_sum(u+v,   u+v,   u    )
+    # l > m < n
+    test_the_sum(u+v,   u,     u+w  )
+    # l > m = n
+    test_the_sum(u+v,   u,     u    )
+    # l > m > n
+    test_the_sum(u+v+w, u+v,   u    )
+
+
+def test_arithmetic_sums():
+    assert summation(1, (n, a, b)) == b - a + 1
+    assert Sum(S.NaN, (n, a, b)) is S.NaN
+    assert Sum(x, (n, a, a)).doit() == x
+    assert Sum(x, (x, a, a)).doit() == a
+    assert Sum(x, (n, 1, a)).doit() == a*x
+    assert Sum(x, (x, Range(1, 11))).doit() == 55
+    assert Sum(x, (x, Range(1, 11, 2))).doit() == 25
+    assert Sum(x, (x, Range(1, 10, 2))) == Sum(x, (x, Range(9, 0, -2)))
+    lo, hi = 1, 2
+    s1 = Sum(n, (n, lo, hi))
+    s2 = Sum(n, (n, hi, lo))
+    assert s1 != s2
+    assert s1.doit() == 3 and s2.doit() == 0
+    lo, hi = x, x + 1
+    s1 = Sum(n, (n, lo, hi))
+    s2 = Sum(n, (n, hi, lo))
+    assert s1 != s2
+    assert s1.doit() == 2*x + 1 and s2.doit() == 0
+    assert Sum(Integral(x, (x, 1, y)) + x, (x, 1, 2)).doit() == \
+        y**2 + 2
+    assert summation(1, (n, 1, 10)) == 10
+    assert summation(2*n, (n, 0, 10**10)) == 100000000010000000000
+    assert summation(4*n*m, (n, a, 1), (m, 1, d)).expand() == \
+        2*d + 2*d**2 + a*d + a*d**2 - d*a**2 - a**2*d**2
+    assert summation(cos(n), (n, -2, 1)) == cos(-2) + cos(-1) + cos(0) + cos(1)
+    assert summation(cos(n), (n, x, x + 2)) == cos(x) + cos(x + 1) + cos(x + 2)
+    assert isinstance(summation(cos(n), (n, x, x + S.Half)), Sum)
+    assert summation(k, (k, 0, oo)) is oo
+    assert summation(k, (k, Range(1, 11))) == 55
+
+
+def test_polynomial_sums():
+    assert summation(n**2, (n, 3, 8)) == 199
+    assert summation(n, (n, a, b)) == \
+        ((a + b)*(b - a + 1)/2).expand()
+    assert summation(n**2, (n, 1, b)) == \
+        ((2*b**3 + 3*b**2 + b)/6).expand()
+    assert summation(n**3, (n, 1, b)) == \
+        ((b**4 + 2*b**3 + b**2)/4).expand()
+    assert summation(n**6, (n, 1, b)) == \
+        ((6*b**7 + 21*b**6 + 21*b**5 - 7*b**3 + b)/42).expand()
+
+
+def test_geometric_sums():
+    assert summation(pi**n, (n, 0, b)) == (1 - pi**(b + 1)) / (1 - pi)
+    assert summation(2 * 3**n, (n, 0, b)) == 3**(b + 1) - 1
+    assert summation(S.Half**n, (n, 1, oo)) == 1
+    assert summation(2**n, (n, 0, b)) == 2**(b + 1) - 1
+    assert summation(2**n, (n, 1, oo)) is oo
+    assert summation(2**(-n), (n, 1, oo)) == 1
+    assert summation(3**(-n), (n, 4, oo)) == Rational(1, 54)
+    assert summation(2**(-4*n + 3), (n, 1, oo)) == Rational(8, 15)
+    assert summation(2**(n + 1), (n, 1, b)).expand() == 4*(2**b - 1)
+
+    # issue 6664:
+    assert summation(x**n, (n, 0, oo)) == \
+        Piecewise((1/(-x + 1), Abs(x) < 1), (Sum(x**n, (n, 0, oo)), True))
+
+    assert summation(-2**n, (n, 0, oo)) is -oo
+    assert summation(I**n, (n, 0, oo)) == Sum(I**n, (n, 0, oo))
+
+    # issue 6802:
+    assert summation((-1)**(2*x + 2), (x, 0, n)) == n + 1
+    assert summation((-2)**(2*x + 2), (x, 0, n)) == 4*4**(n + 1)/S(3) - Rational(4, 3)
+    assert summation((-1)**x, (x, 0, n)) == -(-1)**(n + 1)/S(2) + S.Half
+    assert summation(y**x, (x, a, b)) == \
+        Piecewise((-a + b + 1, Eq(y, 1)), ((y**a - y**(b + 1))/(-y + 1), True))
+    assert summation((-2)**(y*x + 2), (x, 0, n)) == \
+        4*Piecewise((n + 1, Eq((-2)**y, 1)),
+                    ((-(-2)**(y*(n + 1)) + 1)/(-(-2)**y + 1), True))
+
+    # issue 8251:
+    assert summation((1/(n + 1)**2)*n**2, (n, 0, oo)) is oo
+
+    #issue 9908:
+    assert Sum(1/(n**3 - 1), (n, -oo, -2)).doit() == summation(1/(n**3 - 1), (n, -oo, -2))
+
+    #issue 11642:
+    result = Sum(0.5**n, (n, 1, oo)).doit()
+    assert result == 1.0
+    assert result.is_Float
+
+    result = Sum(0.25**n, (n, 1, oo)).doit()
+    assert result == 1/3.
+    assert result.is_Float
+
+    result = Sum(0.99999**n, (n, 1, oo)).doit()
+    assert result == 99999.0
+    assert result.is_Float
+
+    result = Sum(S.Half**n, (n, 1, oo)).doit()
+    assert result == 1
+    assert not result.is_Float
+
+    result = Sum(Rational(3, 5)**n, (n, 1, oo)).doit()
+    assert result == Rational(3, 2)
+    assert not result.is_Float
+
+    assert Sum(1.0**n, (n, 1, oo)).doit() is oo
+    assert Sum(2.43**n, (n, 1, oo)).doit() is oo
+
+    # Issue 13979
+    i, k, q = symbols('i k q', integer=True)
+    result = summation(
+        exp(-2*I*pi*k*i/n) * exp(2*I*pi*q*i/n) / n, (i, 0, n - 1)
+    )
+    assert result.simplify() == Piecewise(
+            (1, Eq(exp(-2*I*pi*(k - q)/n), 1)), (0, True)
+    )
+
+    #Issue 23491
+    assert Sum(1/(n**2 + 1), (n, 1, oo)).doit() == S(-1)/2 + pi/(2*tanh(pi))
+
+def test_harmonic_sums():
+    assert summation(1/k, (k, 0, n)) == Sum(1/k, (k, 0, n))
+    assert summation(1/k, (k, 1, n)) == harmonic(n)
+    assert summation(n/k, (k, 1, n)) == n*harmonic(n)
+    assert summation(1/k, (k, 5, n)) == harmonic(n) - harmonic(4)
+
+
+def test_composite_sums():
+    f = S.Half*(7 - 6*n + Rational(1, 7)*n**3)
+    s = summation(f, (n, a, b))
+    assert not isinstance(s, Sum)
+    A = 0
+    for i in range(-3, 5):
+        A += f.subs(n, i)
+    B = s.subs(a, -3).subs(b, 4)
+    assert A == B
+
+
+def test_hypergeometric_sums():
+    assert summation(
+        binomial(2*k, k)/4**k, (k, 0, n)) == (1 + 2*n)*binomial(2*n, n)/4**n
+    assert summation(binomial(2*k, k)/5**k, (k, -oo, oo)) == sqrt(5)
+
+
+def test_other_sums():
+    f = m**2 + m*exp(m)
+    g = 3*exp(Rational(3, 2))/2 + exp(S.Half)/2 - exp(Rational(-1, 2))/2 - 3*exp(Rational(-3, 2))/2 + 5
+
+    assert summation(f, (m, Rational(-3, 2), Rational(3, 2))) == g
+    assert summation(f, (m, -1.5, 1.5)).evalf().epsilon_eq(g.evalf(), 1e-10)
+
+fac = factorial
+
+
+def NS(e, n=15, **options):
+    return str(sympify(e).evalf(n, **options))
+
+
+def test_evalf_fast_series():
+    # Euler transformed series for sqrt(1+x)
+    assert NS(Sum(
+        fac(2*n + 1)/fac(n)**2/2**(3*n + 1), (n, 0, oo)), 100) == NS(sqrt(2), 100)
+
+    # Some series for exp(1)
+    estr = NS(E, 100)
+    assert NS(Sum(1/fac(n), (n, 0, oo)), 100) == estr
+    assert NS(1/Sum((1 - 2*n)/fac(2*n), (n, 0, oo)), 100) == estr
+    assert NS(Sum((2*n + 1)/fac(2*n), (n, 0, oo)), 100) == estr
+    assert NS(Sum((4*n + 3)/2**(2*n + 1)/fac(2*n + 1), (n, 0, oo))**2, 100) == estr
+
+    pistr = NS(pi, 100)
+    # Ramanujan series for pi
+    assert NS(9801/sqrt(8)/Sum(fac(
+        4*n)*(1103 + 26390*n)/fac(n)**4/396**(4*n), (n, 0, oo)), 100) == pistr
+    assert NS(1/Sum(
+        binomial(2*n, n)**3 * (42*n + 5)/2**(12*n + 4), (n, 0, oo)), 100) == pistr
+    # Machin's formula for pi
+    assert NS(16*Sum((-1)**n/(2*n + 1)/5**(2*n + 1), (n, 0, oo)) -
+        4*Sum((-1)**n/(2*n + 1)/239**(2*n + 1), (n, 0, oo)), 100) == pistr
+
+    # Apery's constant
+    astr = NS(zeta(3), 100)
+    P = 126392*n**5 + 412708*n**4 + 531578*n**3 + 336367*n**2 + 104000* \
+        n + 12463
+    assert NS(Sum((-1)**n * P / 24 * (fac(2*n + 1)*fac(2*n)*fac(
+        n))**3 / fac(3*n + 2) / fac(4*n + 3)**3, (n, 0, oo)), 100) == astr
+    assert NS(Sum((-1)**n * (205*n**2 + 250*n + 77)/64 * fac(n)**10 /
+              fac(2*n + 1)**5, (n, 0, oo)), 100) == astr
+
+
+def test_evalf_fast_series_issue_4021():
+    # Catalan's constant
+    assert NS(Sum((-1)**(n - 1)*2**(8*n)*(40*n**2 - 24*n + 3)*fac(2*n)**3*
+        fac(n)**2/n**3/(2*n - 1)/fac(4*n)**2, (n, 1, oo))/64, 100) == \
+        NS(Catalan, 100)
+    astr = NS(zeta(3), 100)
+    assert NS(5*Sum(
+        (-1)**(n - 1)*fac(n)**2 / n**3 / fac(2*n), (n, 1, oo))/2, 100) == astr
+    assert NS(Sum((-1)**(n - 1)*(56*n**2 - 32*n + 5) / (2*n - 1)**2 * fac(n - 1)
+              **3 / fac(3*n), (n, 1, oo))/4, 100) == astr
+
+
+def test_evalf_slow_series():
+    assert NS(Sum((-1)**n / n, (n, 1, oo)), 15) == NS(-log(2), 15)
+    assert NS(Sum((-1)**n / n, (n, 1, oo)), 50) == NS(-log(2), 50)
+    assert NS(Sum(1/n**2, (n, 1, oo)), 15) == NS(pi**2/6, 15)
+    assert NS(Sum(1/n**2, (n, 1, oo)), 100) == NS(pi**2/6, 100)
+    assert NS(Sum(1/n**2, (n, 1, oo)), 500) == NS(pi**2/6, 500)
+    assert NS(Sum((-1)**n / (2*n + 1)**3, (n, 0, oo)), 15) == NS(pi**3/32, 15)
+    assert NS(Sum((-1)**n / (2*n + 1)**3, (n, 0, oo)), 50) == NS(pi**3/32, 50)
+
+
+def test_evalf_oo_to_oo():
+    # There used to be an error in certain cases
+    # Does not evaluate, but at least do not throw an error
+    # Evaluates symbolically to 0, which is not correct
+    assert Sum(1/(n**2+1), (n, -oo, oo)).evalf() == Sum(1/(n**2+1), (n, -oo, oo))
+    # This evaluates if from 1 to oo and symbolically
+    assert Sum(1/(factorial(abs(n))), (n, -oo, -1)).evalf() == Sum(1/(factorial(abs(n))), (n, -oo, -1))
+
+
+def test_euler_maclaurin():
+    # Exact polynomial sums with E-M
+    def check_exact(f, a, b, m, n):
+        A = Sum(f, (k, a, b))
+        s, e = A.euler_maclaurin(m, n)
+        assert (e == 0) and (s.expand() == A.doit())
+    check_exact(k**4, a, b, 0, 2)
+    check_exact(k**4 + 2*k, a, b, 1, 2)
+    check_exact(k**4 + k**2, a, b, 1, 5)
+    check_exact(k**5, 2, 6, 1, 2)
+    check_exact(k**5, 2, 6, 1, 3)
+    assert Sum(x-1, (x, 0, 2)).euler_maclaurin(m=30, n=30, eps=2**-15) == (0, 0)
+    # Not exact
+    assert Sum(k**6, (k, a, b)).euler_maclaurin(0, 2)[1] != 0
+    # Numerical test
+    for mi, ni in [(2, 4), (2, 20), (10, 20), (18, 20)]:
+        A = Sum(1/k**3, (k, 1, oo))
+        s, e = A.euler_maclaurin(mi, ni)
+        assert abs((s - zeta(3)).evalf()) < e.evalf()
+
+    raises(ValueError, lambda: Sum(1, (x, 0, 1), (k, 0, 1)).euler_maclaurin())
+
+
+@slow
+def test_evalf_euler_maclaurin():
+    assert NS(Sum(1/k**k, (k, 1, oo)), 15) == '1.29128599706266'
+    assert NS(Sum(1/k**k, (k, 1, oo)),
+              50) == '1.2912859970626635404072825905956005414986193682745'
+    assert NS(Sum(1/k - log(1 + 1/k), (k, 1, oo)), 15) == NS(EulerGamma, 15)
+    assert NS(Sum(1/k - log(1 + 1/k), (k, 1, oo)), 50) == NS(EulerGamma, 50)
+    assert NS(Sum(log(k)/k**2, (k, 1, oo)), 15) == '0.937548254315844'
+    assert NS(Sum(log(k)/k**2, (k, 1, oo)),
+              50) == '0.93754825431584375370257409456786497789786028861483'
+    assert NS(Sum(1/k, (k, 1000000, 2000000)), 15) == '0.693147930560008'
+    assert NS(Sum(1/k, (k, 1000000, 2000000)),
+              50) == '0.69314793056000780941723211364567656807940638436025'
+
+
+def test_evalf_symbolic():
+    # issue 6328
+    expr = Sum(f(x), (x, 1, 3)) + Sum(g(x), (x, 1, 3))
+    assert expr.evalf() == expr
+
+
+def test_evalf_issue_3273():
+    assert Sum(0, (k, 1, oo)).evalf() == 0
+
+
+def test_simple_products():
+    assert Product(S.NaN, (x, 1, 3)) is S.NaN
+    assert product(S.NaN, (x, 1, 3)) is S.NaN
+    assert Product(x, (n, a, a)).doit() == x
+    assert Product(x, (x, a, a)).doit() == a
+    assert Product(x, (y, 1, a)).doit() == x**a
+
+    lo, hi = 1, 2
+    s1 = Product(n, (n, lo, hi))
+    s2 = Product(n, (n, hi, lo))
+    assert s1 != s2
+    # This IS correct according to Karr product convention
+    assert s1.doit() == 2
+    assert s2.doit() == 1
+
+    lo, hi = x, x + 1
+    s1 = Product(n, (n, lo, hi))
+    s2 = Product(n, (n, hi, lo))
+    s3 = 1 / Product(n, (n, hi + 1, lo - 1))
+    assert s1 != s2
+    # This IS correct according to Karr product convention
+    assert s1.doit() == x*(x + 1)
+    assert s2.doit() == 1
+    assert s3.doit() == x*(x + 1)
+
+    assert Product(Integral(2*x, (x, 1, y)) + 2*x, (x, 1, 2)).doit() == \
+        (y**2 + 1)*(y**2 + 3)
+    assert product(2, (n, a, b)) == 2**(b - a + 1)
+    assert product(n, (n, 1, b)) == factorial(b)
+    assert product(n**3, (n, 1, b)) == factorial(b)**3
+    assert product(3**(2 + n), (n, a, b)) \
+        == 3**(2*(1 - a + b) + b/2 + (b**2)/2 + a/2 - (a**2)/2)
+    assert product(cos(n), (n, 3, 5)) == cos(3)*cos(4)*cos(5)
+    assert product(cos(n), (n, x, x + 2)) == cos(x)*cos(x + 1)*cos(x + 2)
+    assert isinstance(product(cos(n), (n, x, x + S.Half)), Product)
+    # If Product managed to evaluate this one, it most likely got it wrong!
+    assert isinstance(Product(n**n, (n, 1, b)), Product)
+
+
+def test_rational_products():
+    assert combsimp(product(1 + 1/n, (n, a, b))) == (1 + b)/a
+    assert combsimp(product(n + 1, (n, a, b))) == gamma(2 + b)/gamma(1 + a)
+    assert combsimp(product((n + 1)/(n - 1), (n, a, b))) == b*(1 + b)/(a*(a - 1))
+    assert combsimp(product(n/(n + 1)/(n + 2), (n, a, b))) == \
+        a*gamma(a + 2)/(b + 1)/gamma(b + 3)
+    assert combsimp(product(n*(n + 1)/(n - 1)/(n - 2), (n, a, b))) == \
+        b**2*(b - 1)*(1 + b)/(a - 1)**2/(a*(a - 2))
+
+
+def test_wallis_product():
+    # Wallis product, given in two different forms to ensure that Product
+    # can factor simple rational expressions
+    A = Product(4*n**2 / (4*n**2 - 1), (n, 1, b))
+    B = Product((2*n)*(2*n)/(2*n - 1)/(2*n + 1), (n, 1, b))
+    R = pi*gamma(b + 1)**2/(2*gamma(b + S.Half)*gamma(b + Rational(3, 2)))
+    assert simplify(A.doit()) == R
+    assert simplify(B.doit()) == R
+    # This one should eventually also be doable (Euler's product formula for sin)
+    # assert Product(1+x/n**2, (n, 1, b)) == ...
+
+
+def test_telescopic_sums():
+    #checks also input 2 of comment 1 issue 4127
+    assert Sum(1/k - 1/(k + 1), (k, 1, n)).doit() == 1 - 1/(1 + n)
+    assert Sum(
+        f(k) - f(k + 2), (k, m, n)).doit() == -f(1 + n) - f(2 + n) + f(m) + f(1 + m)
+    assert Sum(cos(k) - cos(k + 3), (k, 1, n)).doit() == -cos(1 + n) - \
+        cos(2 + n) - cos(3 + n) + cos(1) + cos(2) + cos(3)
+
+    # dummy variable shouldn't matter
+    assert telescopic(1/m, -m/(1 + m), (m, n - 1, n)) == \
+        telescopic(1/k, -k/(1 + k), (k, n - 1, n))
+
+    assert Sum(1/x/(x - 1), (x, a, b)).doit() == 1/(a - 1) - 1/b
+    eq = 1/((5*n + 2)*(5*(n + 1) + 2))
+    assert Sum(eq, (n, 0, oo)).doit() == S(1)/10
+    nz = symbols('nz', nonzero=True)
+    v = Sum(eq.subs(5, nz), (n, 0, oo)).doit()
+    assert v.subs(nz, 5).simplify() == S(1)/10
+    # check that apart is being used in non-symbolic case
+    s = Sum(eq, (n, 0, k)).doit()
+    v = Sum(eq, (n, 0, 10**100)).doit()
+    assert v == s.subs(k, 10**100)
+
+
+def test_sum_reconstruct():
+    s = Sum(n**2, (n, -1, 1))
+    assert s == Sum(*s.args)
+    raises(ValueError, lambda: Sum(x, x))
+    raises(ValueError, lambda: Sum(x, (x, 1)))
+
+
+def test_limit_subs():
+    for F in (Sum, Product, Integral):
+        assert F(a*exp(a), (a, -2, 2)) == F(a*exp(a), (a, -b, b)).subs(b, 2)
+        assert F(a, (a, F(b, (b, 1, 2)), 4)).subs(F(b, (b, 1, 2)), c) == \
+            F(a, (a, c, 4))
+        assert F(x, (x, 1, x + y)).subs(x, 1) == F(x, (x, 1, y + 1))
+
+
+def test_function_subs():
+    S = Sum(x*f(y),(x,0,oo),(y,0,oo))
+    assert S.subs(f(y),y) == Sum(x*y,(x,0,oo),(y,0,oo))
+    assert S.subs(f(x),x) == S
+    raises(ValueError, lambda: S.subs(f(y),x+y) )
+    S = Sum(x*log(y),(x,0,oo),(y,0,oo))
+    assert S.subs(log(y),y) == S
+    S = Sum(x*f(y),(x,0,oo),(y,0,oo))
+    assert S.subs(f(y),y) == Sum(x*y,(x,0,oo),(y,0,oo))
+
+
+def test_equality():
+    # if this fails remove special handling below
+    raises(ValueError, lambda: Sum(x, x))
+    r = symbols('x', real=True)
+    for F in (Sum, Product, Integral):
+        try:
+            assert F(x, x) != F(y, y)
+            assert F(x, (x, 1, 2)) != F(x, x)
+            assert F(x, (x, x)) != F(x, x)  # or else they print the same
+            assert F(1, x) != F(1, y)
+        except ValueError:
+            pass
+        assert F(a, (x, 1, 2)) != F(a, (x, 1, 3))  # diff limit
+        assert F(a, (x, 1, x)) != F(a, (y, 1, y))
+        assert F(a, (x, 1, 2)) != F(b, (x, 1, 2))  # diff expression
+        assert F(x, (x, 1, 2)) != F(r, (r, 1, 2))  # diff assumptions
+        assert F(1, (x, 1, x)) != F(1, (y, 1, x))  # only dummy is diff
+        assert F(1, (x, 1, x)).dummy_eq(F(1, (y, 1, x)))
+
+    # issue 5265
+    assert Sum(x, (x, 1, x)).subs(x, a) == Sum(x, (x, 1, a))
+
+
+def test_Sum_doit():
+    assert Sum(n*Integral(a**2), (n, 0, 2)).doit() == a**3
+    assert Sum(n*Integral(a**2), (n, 0, 2)).doit(deep=False) == \
+        3*Integral(a**2)
+    assert summation(n*Integral(a**2), (n, 0, 2)) == 3*Integral(a**2)
+
+    # test nested sum evaluation
+    s = Sum( Sum( Sum(2,(z,1,n+1)), (y,x+1,n)), (x,1,n))
+    assert 0 == (s.doit() - n*(n+1)*(n-1)).factor()
+
+    # Integer assumes finite
+    assert Sum(KroneckerDelta(x, y), (x, -oo, oo)).doit() == Piecewise((1, And(-oo < y, y < oo)), (0, True))
+    assert Sum(KroneckerDelta(m, n), (m, -oo, oo)).doit() == 1
+    assert Sum(m*KroneckerDelta(x, y), (x, -oo, oo)).doit() == Piecewise((m, And(-oo < y, y < oo)), (0, True))
+    assert Sum(x*KroneckerDelta(m, n), (m, -oo, oo)).doit() == x
+    assert Sum(Sum(KroneckerDelta(m, n), (m, 1, 3)), (n, 1, 3)).doit() == 3
+    assert Sum(Sum(KroneckerDelta(k, m), (m, 1, 3)), (n, 1, 3)).doit() == \
+           3 * Piecewise((1, And(1 <= k, k <= 3)), (0, True))
+    assert Sum(f(n) * Sum(KroneckerDelta(m, n), (m, 0, oo)), (n, 1, 3)).doit() == \
+           f(1) + f(2) + f(3)
+    assert Sum(f(n) * Sum(KroneckerDelta(m, n), (m, 0, oo)), (n, 1, oo)).doit() == \
+           Sum(f(n), (n, 1, oo))
+
+    # issue 2597
+    nmax = symbols('N', integer=True, positive=True)
+    pw = Piecewise((1, And(1 <= n, n <= nmax)), (0, True))
+    assert Sum(pw, (n, 1, nmax)).doit() == Sum(Piecewise((1, nmax >= n),
+                    (0, True)), (n, 1, nmax))
+
+    q, s = symbols('q, s')
+    assert summation(1/n**(2*s), (n, 1, oo)) == Piecewise((zeta(2*s), 2*s > 1),
+        (Sum(n**(-2*s), (n, 1, oo)), True))
+    assert summation(1/(n+1)**s, (n, 0, oo)) == Piecewise((zeta(s), s > 1),
+        (Sum((n + 1)**(-s), (n, 0, oo)), True))
+    assert summation(1/(n+q)**s, (n, 0, oo)) == Piecewise(
+        (zeta(s, q), And(q > 0, s > 1)),
+        (Sum((n + q)**(-s), (n, 0, oo)), True))
+    assert summation(1/(n+q)**s, (n, q, oo)) == Piecewise(
+        (zeta(s, 2*q), And(2*q > 0, s > 1)),
+        (Sum((n + q)**(-s), (n, q, oo)), True))
+    assert summation(1/n**2, (n, 1, oo)) == zeta(2)
+    assert summation(1/n**s, (n, 0, oo)) == Sum(n**(-s), (n, 0, oo))
+
+
+def test_Product_doit():
+    assert Product(n*Integral(a**2), (n, 1, 3)).doit() == 2 * a**9 / 9
+    assert Product(n*Integral(a**2), (n, 1, 3)).doit(deep=False) == \
+        6*Integral(a**2)**3
+    assert product(n*Integral(a**2), (n, 1, 3)) == 6*Integral(a**2)**3
+
+
+def test_Sum_interface():
+    assert isinstance(Sum(0, (n, 0, 2)), Sum)
+    assert Sum(nan, (n, 0, 2)) is nan
+    assert Sum(nan, (n, 0, oo)) is nan
+    assert Sum(0, (n, 0, 2)).doit() == 0
+    assert isinstance(Sum(0, (n, 0, oo)), Sum)
+    assert Sum(0, (n, 0, oo)).doit() == 0
+    raises(ValueError, lambda: Sum(1))
+    raises(ValueError, lambda: summation(1))
+
+
+def test_diff():
+    assert Sum(x, (x, 1, 2)).diff(x) == 0
+    assert Sum(x*y, (x, 1, 2)).diff(x) == 0
+    assert Sum(x*y, (y, 1, 2)).diff(x) == Sum(y, (y, 1, 2))
+    e = Sum(x*y, (x, 1, a))
+    assert e.diff(a) == Derivative(e, a)
+    assert Sum(x*y, (x, 1, 3), (a, 2, 5)).diff(y).doit() == \
+        Sum(x*y, (x, 1, 3), (a, 2, 5)).doit().diff(y) == 24
+    assert Sum(x, (x, 1, 2)).diff(y) == 0
+
+
+def test_hypersum():
+    assert simplify(summation(x**n/fac(n), (n, 1, oo))) == -1 + exp(x)
+    assert summation((-1)**n * x**(2*n) / fac(2*n), (n, 0, oo)) == cos(x)
+    assert simplify(summation((-1)**n*x**(2*n + 1) /
+        factorial(2*n + 1), (n, 3, oo))) == -x + sin(x) + x**3/6 - x**5/120
+
+    assert summation(1/(n + 2)**3, (n, 1, oo)) == Rational(-9, 8) + zeta(3)
+    assert summation(1/n**4, (n, 1, oo)) == pi**4/90
+
+    s = summation(x**n*n, (n, -oo, 0))
+    assert s.is_Piecewise
+    assert s.args[0].args[0] == -1/(x*(1 - 1/x)**2)
+    assert s.args[0].args[1] == (abs(1/x) < 1)
+
+    m = Symbol('n', integer=True, positive=True)
+    assert summation(binomial(m, k), (k, 0, m)) == 2**m
+
+
+def test_issue_4170():
+    assert summation(1/factorial(k), (k, 0, oo)) == E
+
+
+def test_is_commutative():
+    from sympy.physics.secondquant import NO, F, Fd
+    m = Symbol('m', commutative=False)
+    for f in (Sum, Product, Integral):
+        assert f(z, (z, 1, 1)).is_commutative is True
+        assert f(z*y, (z, 1, 6)).is_commutative is True
+        assert f(m*x, (x, 1, 2)).is_commutative is False
+
+        assert f(NO(Fd(x)*F(y))*z, (z, 1, 2)).is_commutative is False
+
+
+def test_is_zero():
+    for func in [Sum, Product]:
+        assert func(0, (x, 1, 1)).is_zero is True
+        assert func(x, (x, 1, 1)).is_zero is None
+
+    assert Sum(0, (x, 1, 0)).is_zero is True
+    assert Product(0, (x, 1, 0)).is_zero is False
+
+
+def test_is_number():
+    # is number should not rely on evaluation or assumptions,
+    # it should be equivalent to `not foo.free_symbols`
+    assert Sum(1, (x, 1, 1)).is_number is True
+    assert Sum(1, (x, 1, x)).is_number is False
+    assert Sum(0, (x, y, z)).is_number is False
+    assert Sum(x, (y, 1, 2)).is_number is False
+    assert Sum(x, (y, 1, 1)).is_number is False
+    assert Sum(x, (x, 1, 2)).is_number is True
+    assert Sum(x*y, (x, 1, 2), (y, 1, 3)).is_number is True
+
+    assert Product(2, (x, 1, 1)).is_number is True
+    assert Product(2, (x, 1, y)).is_number is False
+    assert Product(0, (x, y, z)).is_number is False
+    assert Product(1, (x, y, z)).is_number is False
+    assert Product(x, (y, 1, x)).is_number is False
+    assert Product(x, (y, 1, 2)).is_number is False
+    assert Product(x, (y, 1, 1)).is_number is False
+    assert Product(x, (x, 1, 2)).is_number is True
+
+
+def test_free_symbols():
+    for func in [Sum, Product]:
+        assert func(1, (x, 1, 2)).free_symbols == set()
+        assert func(0, (x, 1, y)).free_symbols == {y}
+        assert func(2, (x, 1, y)).free_symbols == {y}
+        assert func(x, (x, 1, 2)).free_symbols == set()
+        assert func(x, (x, 1, y)).free_symbols == {y}
+        assert func(x, (y, 1, y)).free_symbols == {x, y}
+        assert func(x, (y, 1, 2)).free_symbols == {x}
+        assert func(x, (y, 1, 1)).free_symbols == {x}
+        assert func(x, (y, 1, z)).free_symbols == {x, z}
+        assert func(x, (x, 1, y), (y, 1, 2)).free_symbols == set()
+        assert func(x, (x, 1, y), (y, 1, z)).free_symbols == {z}
+        assert func(x, (x, 1, y), (y, 1, y)).free_symbols == {y}
+        assert func(x, (y, 1, y), (y, 1, z)).free_symbols == {x, z}
+    assert Sum(1, (x, 1, y)).free_symbols == {y}
+    # free_symbols answers whether the object *as written* has free symbols,
+    # not whether the evaluated expression has free symbols
+    assert Product(1, (x, 1, y)).free_symbols == {y}
+    # don't count free symbols that are not independent of integration
+    # variable(s)
+    assert func(f(x), (f(x), 1, 2)).free_symbols == set()
+    assert func(f(x), (f(x), 1, x)).free_symbols == {x}
+    assert func(f(x), (f(x), 1, y)).free_symbols == {y}
+    assert func(f(x), (z, 1, y)).free_symbols == {x, y}
+
+
+def test_conjugate_transpose():
+    A, B = symbols("A B", commutative=False)
+    p = Sum(A*B**n, (n, 1, 3))
+    assert p.adjoint().doit() == p.doit().adjoint()
+    assert p.conjugate().doit() == p.doit().conjugate()
+    assert p.transpose().doit() == p.doit().transpose()
+
+    p = Sum(B**n*A, (n, 1, 3))
+    assert p.adjoint().doit() == p.doit().adjoint()
+    assert p.conjugate().doit() == p.doit().conjugate()
+    assert p.transpose().doit() == p.doit().transpose()
+
+
+def test_noncommutativity_honoured():
+    A, B = symbols("A B", commutative=False)
+    M = symbols('M', integer=True, positive=True)
+    p = Sum(A*B**n, (n, 1, M))
+    assert p.doit() == A*Piecewise((M, Eq(B, 1)),
+                                   ((B - B**(M + 1))*(1 - B)**(-1), True))
+
+    p = Sum(B**n*A, (n, 1, M))
+    assert p.doit() == Piecewise((M, Eq(B, 1)),
+                                 ((B - B**(M + 1))*(1 - B)**(-1), True))*A
+
+    p = Sum(B**n*A*B**n, (n, 1, M))
+    assert p.doit() == p
+
+
+def test_issue_4171():
+    assert summation(factorial(2*k + 1)/factorial(2*k), (k, 0, oo)) is oo
+    assert summation(2*k + 1, (k, 0, oo)) is oo
+
+
+def test_issue_6273():
+    assert Sum(x, (x, 1, n)).n(2, subs={n: 1}) == Float(1, 2)
+
+
+def test_issue_6274():
+    assert Sum(x, (x, 1, 0)).doit() == 0
+    assert NS(Sum(x, (x, 1, 0))) == '0'
+    assert Sum(n, (n, 10, 5)).doit() == -30
+    assert NS(Sum(n, (n, 10, 5))) == '-30.0000000000000'
+
+
+def test_simplify_sum():
+    y, t, v = symbols('y, t, v')
+
+    _simplify = lambda e: simplify(e, doit=False)
+    assert _simplify(Sum(x*y, (x, n, m), (y, a, k)) + \
+        Sum(y, (x, n, m), (y, a, k))) == Sum(y * (x + 1), (x, n, m), (y, a, k))
+    assert _simplify(Sum(x, (x, n, m)) + Sum(x, (x, m + 1, a))) == \
+        Sum(x, (x, n, a))
+    assert _simplify(Sum(x, (x, k + 1, a)) + Sum(x, (x, n, k))) == \
+        Sum(x, (x, n, a))
+    assert _simplify(Sum(x, (x, k + 1, a)) + Sum(x + 1, (x, n, k))) == \
+        Sum(x, (x, n, a)) + Sum(1, (x, n, k))
+    assert _simplify(Sum(x, (x, 0, 3)) * 3 + 3 * Sum(x, (x, 4, 6)) + \
+        4 * Sum(z, (z, 0, 1))) == 4*Sum(z, (z, 0, 1)) + 3*Sum(x, (x, 0, 6))
+    assert _simplify(3*Sum(x**2, (x, a, b)) + Sum(x, (x, a, b))) == \
+        Sum(x*(3*x + 1), (x, a, b))
+    assert _simplify(Sum(x**3, (x, n, k)) * 3 + 3 * Sum(x, (x, n, k)) + \
+        4 * y * Sum(z, (z, n, k))) + 1 == \
+            4*y*Sum(z, (z, n, k)) + 3*Sum(x**3 + x, (x, n, k)) + 1
+    assert _simplify(Sum(x, (x, a, b)) + 1 + Sum(x, (x, b + 1, c))) == \
+        1 + Sum(x, (x, a, c))
+    assert _simplify(Sum(x, (t, a, b)) + Sum(y, (t, a, b)) + \
+        Sum(x, (t, b+1, c))) == x * Sum(1, (t, a, c)) + y * Sum(1, (t, a, b))
+    assert _simplify(Sum(x, (t, a, b)) + Sum(x, (t, b+1, c)) + \
+        Sum(y, (t, a, b))) == x * Sum(1, (t, a, c)) + y * Sum(1, (t, a, b))
+    assert _simplify(Sum(x, (t, a, b)) + 2 * Sum(x, (t, b+1, c))) == \
+        _simplify(Sum(x, (t, a, b)) + Sum(x, (t, b+1, c)) + Sum(x, (t, b+1, c)))
+    assert _simplify(Sum(x, (x, a, b))*Sum(x**2, (x, a, b))) == \
+        Sum(x, (x, a, b)) * Sum(x**2, (x, a, b))
+    assert _simplify(Sum(x, (t, a, b)) + Sum(y, (t, a, b)) + Sum(z, (t, a, b))) \
+        == (x + y + z) * Sum(1, (t, a, b))          # issue 8596
+    assert _simplify(Sum(x, (t, a, b)) + Sum(y, (t, a, b)) + Sum(z, (t, a, b)) + \
+        Sum(v, (t, a, b))) == (x + y + z + v) * Sum(1, (t, a, b))  # issue 8596
+    assert _simplify(Sum(x * y, (x, a, b)) / (3 * y)) == \
+        (Sum(x, (x, a, b)) / 3)
+    assert _simplify(Sum(f(x) * y * z, (x, a, b)) / (y * z)) \
+        == Sum(f(x), (x, a, b))
+    assert _simplify(Sum(c * x, (x, a, b)) - c * Sum(x, (x, a, b))) == 0
+    assert _simplify(c * (Sum(x, (x, a, b))  + y)) == c * (y + Sum(x, (x, a, b)))
+    assert _simplify(c * (Sum(x, (x, a, b)) + y * Sum(x, (x, a, b)))) == \
+        c * (y + 1) * Sum(x, (x, a, b))
+    assert _simplify(Sum(Sum(c * x, (x, a, b)), (y, a, b))) == \
+                c * Sum(x, (x, a, b), (y, a, b))
+    assert _simplify(Sum((3 + y) * Sum(c * x, (x, a, b)), (y, a, b))) == \
+                c * Sum((3 + y), (y, a, b)) * Sum(x, (x, a, b))
+    assert _simplify(Sum((3 + t) * Sum(c * t, (x, a, b)), (y, a, b))) == \
+                c*t*(t + 3)*Sum(1, (x, a, b))*Sum(1, (y, a, b))
+    assert _simplify(Sum(Sum(d * t, (x, a, b - 1)) + \
+                Sum(d * t, (x, b, c)), (t, a, b))) == \
+                    d * Sum(1, (x, a, c)) * Sum(t, (t, a, b))
+    assert _simplify(Sum(sin(t)**2 + cos(t)**2 + 1, (t, a, b))) == \
+        2 * Sum(1, (t, a, b))
+
+
+def test_change_index():
+    b, v, w = symbols('b, v, w', integer = True)
+
+    assert Sum(x, (x, a, b)).change_index(x, x + 1, y) == \
+        Sum(y - 1, (y, a + 1, b + 1))
+    assert Sum(x**2, (x, a, b)).change_index( x, x - 1) == \
+        Sum((x+1)**2, (x, a - 1, b - 1))
+    assert Sum(x**2, (x, a, b)).change_index( x, -x, y) == \
+        Sum((-y)**2, (y, -b, -a))
+    assert Sum(x, (x, a, b)).change_index( x, -x - 1) == \
+        Sum(-x - 1, (x, -b - 1, -a - 1))
+    assert Sum(x*y, (x, a, b), (y, c, d)).change_index( x, x - 1, z) == \
+        Sum((z + 1)*y, (z, a - 1, b - 1), (y, c, d))
+    assert Sum(x, (x, a, b)).change_index( x, x + v) == \
+        Sum(-v + x, (x, a + v, b + v))
+    assert Sum(x, (x, a, b)).change_index( x, -x - v) == \
+        Sum(-v - x, (x, -b - v, -a - v))
+    assert Sum(x, (x, a, b)).change_index(x, w*x, v) == \
+        Sum(v/w, (v, b*w, a*w))
+    raises(ValueError, lambda: Sum(x, (x, a, b)).change_index(x, 2*x))
+
+
+def test_reorder():
+    b, y, c, d, z = symbols('b, y, c, d, z', integer = True)
+
+    assert Sum(x*y, (x, a, b), (y, c, d)).reorder((0, 1)) == \
+        Sum(x*y, (y, c, d), (x, a, b))
+    assert Sum(x, (x, a, b), (x, c, d)).reorder((0, 1)) == \
+        Sum(x, (x, c, d), (x, a, b))
+    assert Sum(x*y + z, (x, a, b), (z, m, n), (y, c, d)).reorder(\
+        (2, 0), (0, 1)) == Sum(x*y + z, (z, m, n), (y, c, d), (x, a, b))
+    assert Sum(x*y*z, (x, a, b), (y, c, d), (z, m, n)).reorder(\
+        (0, 1), (1, 2), (0, 2)) == Sum(x*y*z, (x, a, b), (z, m, n), (y, c, d))
+    assert Sum(x*y*z, (x, a, b), (y, c, d), (z, m, n)).reorder(\
+        (x, y), (y, z), (x, z)) == Sum(x*y*z, (x, a, b), (z, m, n), (y, c, d))
+    assert Sum(x*y, (x, a, b), (y, c, d)).reorder((x, 1)) == \
+        Sum(x*y, (y, c, d), (x, a, b))
+    assert Sum(x*y, (x, a, b), (y, c, d)).reorder((y, x)) == \
+        Sum(x*y, (y, c, d), (x, a, b))
+
+
+def test_reverse_order():
+    assert Sum(x, (x, 0, 3)).reverse_order(0) == Sum(-x, (x, 4, -1))
+    assert Sum(x*y, (x, 1, 5), (y, 0, 6)).reverse_order(0, 1) == \
+           Sum(x*y, (x, 6, 0), (y, 7, -1))
+    assert Sum(x, (x, 1, 2)).reverse_order(0) == Sum(-x, (x, 3, 0))
+    assert Sum(x, (x, 1, 3)).reverse_order(0) == Sum(-x, (x, 4, 0))
+    assert Sum(x, (x, 1, a)).reverse_order(0) == Sum(-x, (x, a + 1, 0))
+    assert Sum(x, (x, a, 5)).reverse_order(0) == Sum(-x, (x, 6, a - 1))
+    assert Sum(x, (x, a + 1, a + 5)).reverse_order(0) == \
+                         Sum(-x, (x, a + 6, a))
+    assert Sum(x, (x, a + 1, a + 2)).reverse_order(0) == \
+           Sum(-x, (x, a + 3, a))
+    assert Sum(x, (x, a + 1, a + 1)).reverse_order(0) == \
+           Sum(-x, (x, a + 2, a))
+    assert Sum(x, (x, a, b)).reverse_order(0) == Sum(-x, (x, b + 1, a - 1))
+    assert Sum(x, (x, a, b)).reverse_order(x) == Sum(-x, (x, b + 1, a - 1))
+    assert Sum(x*y, (x, a, b), (y, 2, 5)).reverse_order(x, 1) == \
+        Sum(x*y, (x, b + 1, a - 1), (y, 6, 1))
+    assert Sum(x*y, (x, a, b), (y, 2, 5)).reverse_order(y, x) == \
+        Sum(x*y, (x, b + 1, a - 1), (y, 6, 1))
+
+
+def test_issue_7097():
+    assert sum(x**n/n for n in range(1, 401)) == summation(x**n/n, (n, 1, 400))
+
+
+def test_factor_expand_subs():
+    # test factoring
+    assert Sum(4 * x, (x, 1, y)).factor() == 4 * Sum(x, (x, 1, y))
+    assert Sum(x * a, (x, 1, y)).factor() == a * Sum(x, (x, 1, y))
+    assert Sum(4 * x * a, (x, 1, y)).factor() == 4 * a * Sum(x, (x, 1, y))
+    assert Sum(4 * x * y, (x, 1, y)).factor() == 4 * y * Sum(x, (x, 1, y))
+
+    # test expand
+    _x = Symbol('x', zero=False)
+    assert Sum(x+1,(x,1,y)).expand() == Sum(x,(x,1,y)) + Sum(1,(x,1,y))
+    assert Sum(x+a*x**2,(x,1,y)).expand() == Sum(x,(x,1,y)) + Sum(a*x**2,(x,1,y))
+    assert Sum(_x**(n + 1)*(n + 1), (n, -1, oo)).expand() \
+        == Sum(n*_x*_x**n + _x*_x**n, (n, -1, oo))
+    assert Sum(x**(n + 1)*(n + 1), (n, -1, oo)).expand(power_exp=False) \
+        == Sum(n*x**(n + 1) + x**(n + 1), (n, -1, oo))
+    assert Sum(x**(n + 1)*(n + 1), (n, -1, oo)).expand(force=True) \
+           == Sum(x*x**n, (n, -1, oo)) + Sum(n*x*x**n, (n, -1, oo))
+    assert Sum(a*n+a*n**2,(n,0,4)).expand() \
+        == Sum(a*n,(n,0,4)) + Sum(a*n**2,(n,0,4))
+    assert Sum(_x**a*_x**n,(x,0,3)) \
+        == Sum(_x**(a+n),(x,0,3)).expand(power_exp=True)
+    _a, _n = symbols('a n', positive=True)
+    assert Sum(x**(_a+_n),(x,0,3)).expand(power_exp=True) \
+        == Sum(x**_a*x**_n, (x, 0, 3))
+    assert Sum(x**(_a-_n),(x,0,3)).expand(power_exp=True) \
+        == Sum(x**(_a-_n),(x,0,3)).expand(power_exp=False)
+
+    # test subs
+    assert Sum(1/(1+a*x**2),(x,0,3)).subs([(a,3)]) == Sum(1/(1+3*x**2),(x,0,3))
+    assert Sum(x*y,(x,0,y),(y,0,x)).subs([(x,3)]) == Sum(x*y,(x,0,y),(y,0,3))
+    assert Sum(x,(x,1,10)).subs([(x,y-2)]) == Sum(x,(x,1,10))
+    assert Sum(1/x,(x,1,10)).subs([(x,(3+n)**3)]) == Sum(1/x,(x,1,10))
+    assert Sum(1/x,(x,1,10)).subs([(x,3*x-2)]) == Sum(1/x,(x,1,10))
+
+
+def test_distribution_over_equality():
+    assert Product(Eq(x*2, f(x)), (x, 1, 3)).doit() == Eq(48, f(1)*f(2)*f(3))
+    assert Sum(Eq(f(x), x**2), (x, 0, y)) == \
+        Eq(Sum(f(x), (x, 0, y)), Sum(x**2, (x, 0, y)))
+
+
+def test_issue_2787():
+    n, k = symbols('n k', positive=True, integer=True)
+    p = symbols('p', positive=True)
+    binomial_dist = binomial(n, k)*p**k*(1 - p)**(n - k)
+    s = Sum(binomial_dist*k, (k, 0, n))
+    res = s.doit().simplify()
+    ans = Piecewise(
+        (n*p, x),
+        (Sum(k*p**k*binomial(n, k)*(1 - p)**(n - k), (k, 0, n)),
+        True)).subs(x, (Eq(n, 1) | (n > 1)) & (p/Abs(p - 1) <= 1))
+    ans2 = Piecewise(
+        (n*p, x),
+        (factorial(n)*Sum(p**k*(1 - p)**(-k + n)/
+        (factorial(-k + n)*factorial(k - 1)), (k, 0, n)),
+        True)).subs(x, (Eq(n, 1) | (n > 1)) & (p/Abs(p - 1) <= 1))
+    assert res in [ans, ans2]  # XXX system dependent
+    # Issue #17165: make sure that another simplify does not complicate
+    # the result by much. Why didn't first simplify replace
+    # Eq(n, 1) | (n > 1) with True?
+    assert res.simplify().count_ops() <= res.count_ops() + 2
+
+
+def test_issue_4668():
+    assert summation(1/n, (n, 2, oo)) is oo
+
+
+def test_matrix_sum():
+    A = Matrix([[0, 1], [n, 0]])
+
+    result = Sum(A, (n, 0, 3)).doit()
+    assert result == Matrix([[0, 4], [6, 0]])
+    assert result.__class__ == ImmutableDenseMatrix
+
+    A = SparseMatrix([[0, 1], [n, 0]])
+
+    result = Sum(A, (n, 0, 3)).doit()
+    assert result.__class__ == ImmutableSparseMatrix
+
+
+def test_failing_matrix_sum():
+    n = Symbol('n')
+    # TODO Implement matrix geometric series summation.
+    A = Matrix([[0, 1, 0], [-1, 0, 0], [0, 0, 0]])
+    assert Sum(A ** n, (n, 1, 4)).doit() == \
+        Matrix([[0, 0, 0], [0, 0, 0], [0, 0, 0]])
+    # issue sympy/sympy#16989
+    assert summation(A**n, (n, 1, 1)) == A
+
+
+def test_indexed_idx_sum():
+    i = symbols('i', cls=Idx)
+    r = Indexed('r', i)
+    assert Sum(r, (i, 0, 3)).doit() == sum([r.xreplace({i: j}) for j in range(4)])
+    assert Product(r, (i, 0, 3)).doit() == prod([r.xreplace({i: j}) for j in range(4)])
+
+    j = symbols('j', integer=True)
+    assert Sum(r, (i, j, j+2)).doit() == sum([r.xreplace({i: j+k}) for k in range(3)])
+    assert Product(r, (i, j, j+2)).doit() == prod([r.xreplace({i: j+k}) for k in range(3)])
+
+    k = Idx('k', range=(1, 3))
+    A = IndexedBase('A')
+    assert Sum(A[k], k).doit() == sum([A[Idx(j, (1, 3))] for j in range(1, 4)])
+    assert Product(A[k], k).doit() == prod([A[Idx(j, (1, 3))] for j in range(1, 4)])
+
+    raises(ValueError, lambda: Sum(A[k], (k, 1, 4)))
+    raises(ValueError, lambda: Sum(A[k], (k, 0, 3)))
+    raises(ValueError, lambda: Sum(A[k], (k, 2, oo)))
+
+    raises(ValueError, lambda: Product(A[k], (k, 1, 4)))
+    raises(ValueError, lambda: Product(A[k], (k, 0, 3)))
+    raises(ValueError, lambda: Product(A[k], (k, 2, oo)))
+
+
+@slow
+def test_is_convergent():
+    # divergence tests --
+    assert Sum(n/(2*n + 1), (n, 1, oo)).is_convergent() is S.false
+    assert Sum(factorial(n)/5**n, (n, 1, oo)).is_convergent() is S.false
+    assert Sum(3**(-2*n - 1)*n**n, (n, 1, oo)).is_convergent() is S.false
+    assert Sum((-1)**n*n, (n, 3, oo)).is_convergent() is S.false
+    assert Sum((-1)**n, (n, 1, oo)).is_convergent() is S.false
+    assert Sum(log(1/n), (n, 2, oo)).is_convergent() is S.false
+
+    # Raabe's test --
+    assert Sum(Product((3*m),(m,1,n))/Product((3*m+4),(m,1,n)),(n,1,oo)).is_convergent() is S.true
+
+    # root test --
+    assert Sum((-12)**n/n, (n, 1, oo)).is_convergent() is S.false
+
+    # integral test --
+
+    # p-series test --
+    assert Sum(1/(n**2 + 1), (n, 1, oo)).is_convergent() is S.true
+    assert Sum(1/n**Rational(6, 5), (n, 1, oo)).is_convergent() is S.true
+    assert Sum(2/(n*sqrt(n - 1)), (n, 2, oo)).is_convergent() is S.true
+    assert Sum(1/(sqrt(n)*sqrt(n)), (n, 2, oo)).is_convergent() is S.false
+    assert Sum(factorial(n) / factorial(n+2), (n, 1, oo)).is_convergent() is S.true
+    assert Sum(rf(5,n)/rf(7,n),(n,1,oo)).is_convergent() is S.true
+    assert Sum((rf(1, n)*rf(2, n))/(rf(3, n)*factorial(n)),(n,1,oo)).is_convergent() is S.false
+
+    # comparison test --
+    assert Sum(1/(n + log(n)), (n, 1, oo)).is_convergent() is S.false
+    assert Sum(1/(n**2*log(n)), (n, 2, oo)).is_convergent() is S.true
+    assert Sum(1/(n*log(n)), (n, 2, oo)).is_convergent() is S.false
+    assert Sum(2/(n*log(n)*log(log(n))**2), (n, 5, oo)).is_convergent() is S.true
+    assert Sum(2/(n*log(n)**2), (n, 2, oo)).is_convergent() is S.true
+    assert Sum((n - 1)/(n**2*log(n)**3), (n, 2, oo)).is_convergent() is S.true
+    assert Sum(1/(n*log(n)*log(log(n))), (n, 5, oo)).is_convergent() is S.false
+    assert Sum((n - 1)/(n*log(n)**3), (n, 3, oo)).is_convergent() is S.false
+    assert Sum(2/(n**2*log(n)), (n, 2, oo)).is_convergent() is S.true
+    assert Sum(1/(n*sqrt(log(n))*log(log(n))), (n, 100, oo)).is_convergent() is S.false
+    assert Sum(log(log(n))/(n*log(n)**2), (n, 100, oo)).is_convergent() is S.true
+    assert Sum(log(n)/n**2, (n, 5, oo)).is_convergent() is S.true
+
+    # alternating series tests --
+    assert Sum((-1)**(n - 1)/(n**2 - 1), (n, 3, oo)).is_convergent() is S.true
+
+    # with -negativeInfinite Limits
+    assert Sum(1/(n**2 + 1), (n, -oo, 1)).is_convergent() is S.true
+    assert Sum(1/(n - 1), (n, -oo, -1)).is_convergent() is S.false
+    assert Sum(1/(n**2 - 1), (n, -oo, -5)).is_convergent() is S.true
+    assert Sum(1/(n**2 - 1), (n, -oo, 2)).is_convergent() is S.true
+    assert Sum(1/(n**2 - 1), (n, -oo, oo)).is_convergent() is S.true
+
+    # piecewise functions
+    f = Piecewise((n**(-2), n <= 1), (n**2, n > 1))
+    assert Sum(f, (n, 1, oo)).is_convergent() is S.false
+    assert Sum(f, (n, -oo, oo)).is_convergent() is S.false
+    assert Sum(f, (n, 1, 100)).is_convergent() is S.true
+    #assert Sum(f, (n, -oo, 1)).is_convergent() is S.true
+
+    # integral test
+
+    assert Sum(log(n)/n**3, (n, 1, oo)).is_convergent() is S.true
+    assert Sum(-log(n)/n**3, (n, 1, oo)).is_convergent() is S.true
+    # the following function has maxima located at (x, y) =
+    # (1.2, 0.43), (3.0, -0.25) and (6.8, 0.050)
+    eq = (x - 2)*(x**2 - 6*x + 4)*exp(-x)
+    assert Sum(eq, (x, 1, oo)).is_convergent() is S.true
+    assert Sum(eq, (x, 1, 2)).is_convergent() is S.true
+    assert Sum(1/(x**3), (x, 1, oo)).is_convergent() is S.true
+    assert Sum(1/(x**S.Half), (x, 1, oo)).is_convergent() is S.false
+
+    # issue 19545
+    assert Sum(1/n - 3/(3*n +2), (n, 1, oo)).is_convergent() is S.true
+
+    # issue 19836
+    assert Sum(4/(n + 2) - 5/(n + 1) + 1/n,(n, 7, oo)).is_convergent() is S.true
+
+
+def test_is_absolutely_convergent():
+    assert Sum((-1)**n, (n, 1, oo)).is_absolutely_convergent() is S.false
+    assert Sum((-1)**n/n**2, (n, 1, oo)).is_absolutely_convergent() is S.true
+
+
+@XFAIL
+def test_convergent_failing():
+    # dirichlet tests
+    assert Sum(sin(n)/n, (n, 1, oo)).is_convergent() is S.true
+    assert Sum(sin(2*n)/n, (n, 1, oo)).is_convergent() is S.true
+
+
+def test_issue_6966():
+    i, k, m = symbols('i k m', integer=True)
+    z_i, q_i = symbols('z_i q_i')
+    a_k = Sum(-q_i*z_i/k,(i,1,m))
+    b_k = a_k.diff(z_i)
+    assert isinstance(b_k, Sum)
+    assert b_k == Sum(-q_i/k,(i,1,m))
+
+
+def test_issue_10156():
+    cx = Sum(2*y**2*x, (x, 1,3))
+    e = 2*y*Sum(2*cx*x**2, (x, 1, 9))
+    assert e.factor() == \
+        8*y**3*Sum(x, (x, 1, 3))*Sum(x**2, (x, 1, 9))
+
+
+def test_issue_10973():
+    assert Sum((-n + (n**3 + 1)**(S(1)/3))/log(n), (n, 1, oo)).is_convergent() is S.true
+
+
+def test_issue_14129():
+    x = Symbol('x', zero=False)
+    assert Sum( k*x**k, (k, 0, n-1)).doit() == \
+        Piecewise((n**2/2 - n/2, Eq(x, 1)), ((n*x*x**n -
+            n*x**n - x*x**n + x)/(x - 1)**2, True))
+    assert Sum( x**k, (k, 0, n-1)).doit() == \
+        Piecewise((n, Eq(x, 1)), ((-x**n + 1)/(-x + 1), True))
+    assert Sum( k*(x/y+x)**k, (k, 0, n-1)).doit() == \
+        Piecewise((n*(n - 1)/2, Eq(x, y/(y + 1))),
+        (x*(y + 1)*(n*x*y*(x + x/y)**(n - 1) +
+        n*x*(x + x/y)**(n - 1) - n*y*(x + x/y)**(n - 1) -
+        x*y*(x + x/y)**(n - 1) - x*(x + x/y)**(n - 1) + y)/
+        (x*y + x - y)**2, True))
+
+
+def test_issue_14112():
+    assert Sum((-1)**n/sqrt(n), (n, 1, oo)).is_absolutely_convergent() is S.false
+    assert Sum((-1)**(2*n)/n, (n, 1, oo)).is_convergent() is S.false
+    assert Sum((-2)**n + (-3)**n, (n, 1, oo)).is_convergent() is S.false
+
+
+def test_issue_14219():
+    A = diag(0, 2, -3)
+    res = diag(1, 15, -20)
+    assert Sum(A**n, (n, 0, 3)).doit() == res
+
+
+def test_sin_times_absolutely_convergent():
+    assert Sum(sin(n) / n**3, (n, 1, oo)).is_convergent() is S.true
+    assert Sum(sin(n) * log(n) / n**3, (n, 1, oo)).is_convergent() is S.true
+
+
+def test_issue_14111():
+    assert Sum(1/log(log(n)), (n, 22, oo)).is_convergent() is S.false
+
+
+def test_issue_14484():
+    assert Sum(sin(n)/log(log(n)), (n, 22, oo)).is_convergent() is S.false
+
+
+def test_issue_14640():
+    i, n = symbols("i n", integer=True)
+    a, b, c = symbols("a b c", zero=False)
+
+    assert Sum(a**-i/(a - b), (i, 0, n)).doit() == Sum(
+        1/(a*a**i - a**i*b), (i, 0, n)).doit() == Piecewise(
+            (n + 1, Eq(1/a, 1)),
+            ((-a**(-n - 1) + 1)/(1 - 1/a), True))/(a - b)
+
+    assert Sum((b*a**i - c*a**i)**-2, (i, 0, n)).doit() == Piecewise(
+        (n + 1, Eq(a**(-2), 1)),
+        ((-a**(-2*n - 2) + 1)/(1 - 1/a**2), True))/(b - c)**2
+
+    s = Sum(i*(a**(n - i) - b**(n - i))/(a - b), (i, 0, n)).doit()
+    assert not s.has(Sum)
+    assert s.subs({a: 2, b: 3, n: 5}) == 122
+
+
+def test_issue_15943():
+    s = Sum(binomial(n, k)*factorial(n - k), (k, 0, n)).doit().rewrite(gamma)
+    assert s == -E*(n + 1)*gamma(n + 1)*lowergamma(n + 1, 1)/gamma(n + 2
+        ) + E*gamma(n + 1)
+    assert s.simplify() == E*(factorial(n) - lowergamma(n + 1, 1))
+
+
+def test_Sum_dummy_eq():
+    assert not Sum(x, (x, a, b)).dummy_eq(1)
+    assert not Sum(x, (x, a, b)).dummy_eq(Sum(x, (x, a, b), (a, 1, 2)))
+    assert not Sum(x, (x, a, b)).dummy_eq(Sum(x, (x, a, c)))
+    assert Sum(x, (x, a, b)).dummy_eq(Sum(x, (x, a, b)))
+    d = Dummy()
+    assert Sum(x, (x, a, d)).dummy_eq(Sum(x, (x, a, c)), c)
+    assert not Sum(x, (x, a, d)).dummy_eq(Sum(x, (x, a, c)))
+    assert Sum(x, (x, a, c)).dummy_eq(Sum(y, (y, a, c)))
+    assert Sum(x, (x, a, d)).dummy_eq(Sum(y, (y, a, c)), c)
+    assert not Sum(x, (x, a, d)).dummy_eq(Sum(y, (y, a, c)))
+
+
+def test_issue_15852():
+    assert summation(x**y*y, (y, -oo, oo)).doit() == Sum(x**y*y, (y, -oo, oo))
+
+
+def test_exceptions():
+    S = Sum(x, (x, a, b))
+    raises(ValueError, lambda: S.change_index(x, x**2, y))
+    S = Sum(x, (x, a, b), (x, 1, 4))
+    raises(ValueError, lambda: S.index(x))
+    S = Sum(x, (x, a, b), (y, 1, 4))
+    raises(ValueError, lambda: S.reorder([x]))
+    S = Sum(x, (x, y, b), (y, 1, 4))
+    raises(ReorderError, lambda: S.reorder_limit(0, 1))
+    S = Sum(x*y, (x, a, b), (y, 1, 4))
+    raises(NotImplementedError, lambda: S.is_convergent())
+
+
+def test_sumproducts_assumptions():
+    M = Symbol('M', integer=True, positive=True)
+
+    m = Symbol('m', integer=True)
+    for func in [Sum, Product]:
+        assert func(m, (m, -M, M)).is_positive is None
+        assert func(m, (m, -M, M)).is_nonpositive is None
+        assert func(m, (m, -M, M)).is_negative is None
+        assert func(m, (m, -M, M)).is_nonnegative is None
+        assert func(m, (m, -M, M)).is_finite is True
+
+    m = Symbol('m', integer=True, nonnegative=True)
+    for func in [Sum, Product]:
+        assert func(m, (m, 0, M)).is_positive is None
+        assert func(m, (m, 0, M)).is_nonpositive is None
+        assert func(m, (m, 0, M)).is_negative is False
+        assert func(m, (m, 0, M)).is_nonnegative is True
+        assert func(m, (m, 0, M)).is_finite is True
+
+    m = Symbol('m', integer=True, positive=True)
+    for func in [Sum, Product]:
+        assert func(m, (m, 1, M)).is_positive is True
+        assert func(m, (m, 1, M)).is_nonpositive is False
+        assert func(m, (m, 1, M)).is_negative is False
+        assert func(m, (m, 1, M)).is_nonnegative is True
+        assert func(m, (m, 1, M)).is_finite is True
+
+    m = Symbol('m', integer=True, negative=True)
+    assert Sum(m, (m, -M, -1)).is_positive is False
+    assert Sum(m, (m, -M, -1)).is_nonpositive is True
+    assert Sum(m, (m, -M, -1)).is_negative is True
+    assert Sum(m, (m, -M, -1)).is_nonnegative is False
+    assert Sum(m, (m, -M, -1)).is_finite is True
+    assert Product(m, (m, -M, -1)).is_positive is None
+    assert Product(m, (m, -M, -1)).is_nonpositive is None
+    assert Product(m, (m, -M, -1)).is_negative is None
+    assert Product(m, (m, -M, -1)).is_nonnegative is None
+    assert Product(m, (m, -M, -1)).is_finite is True
+
+    m = Symbol('m', integer=True, nonpositive=True)
+    assert Sum(m, (m, -M, 0)).is_positive is False
+    assert Sum(m, (m, -M, 0)).is_nonpositive is True
+    assert Sum(m, (m, -M, 0)).is_negative is None
+    assert Sum(m, (m, -M, 0)).is_nonnegative is None
+    assert Sum(m, (m, -M, 0)).is_finite is True
+    assert Product(m, (m, -M, 0)).is_positive is None
+    assert Product(m, (m, -M, 0)).is_nonpositive is None
+    assert Product(m, (m, -M, 0)).is_negative is None
+    assert Product(m, (m, -M, 0)).is_nonnegative is None
+    assert Product(m, (m, -M, 0)).is_finite is True
+
+    m = Symbol('m', integer=True)
+    assert Sum(2, (m, 0, oo)).is_positive is None
+    assert Sum(2, (m, 0, oo)).is_nonpositive is None
+    assert Sum(2, (m, 0, oo)).is_negative is None
+    assert Sum(2, (m, 0, oo)).is_nonnegative is None
+    assert Sum(2, (m, 0, oo)).is_finite is None
+
+    assert Product(2, (m, 0, oo)).is_positive is None
+    assert Product(2, (m, 0, oo)).is_nonpositive is None
+    assert Product(2, (m, 0, oo)).is_negative is False
+    assert Product(2, (m, 0, oo)).is_nonnegative is None
+    assert Product(2, (m, 0, oo)).is_finite is None
+
+    assert Product(0, (x, M, M-1)).is_positive is True
+    assert Product(0, (x, M, M-1)).is_finite is True
+
+
+def test_expand_with_assumptions():
+    M = Symbol('M', integer=True, positive=True)
+    x = Symbol('x', positive=True)
+    m = Symbol('m', nonnegative=True)
+    assert log(Product(x**m, (m, 0, M))).expand() == Sum(m*log(x), (m, 0, M))
+    assert log(Product(exp(x**m), (m, 0, M))).expand() == Sum(x**m, (m, 0, M))
+    assert log(Product(x**m, (m, 0, M))).rewrite(Sum).expand() == Sum(m*log(x), (m, 0, M))
+    assert log(Product(exp(x**m), (m, 0, M))).rewrite(Sum).expand() == Sum(x**m, (m, 0, M))
+
+    n = Symbol('n', nonnegative=True)
+    i, j = symbols('i,j', positive=True, integer=True)
+    x, y = symbols('x,y', positive=True)
+    assert log(Product(x**i*y**j, (i, 1, n), (j, 1, m))).expand() \
+        == Sum(i*log(x) + j*log(y), (i, 1, n), (j, 1, m))
+
+    m = Symbol('m', nonnegative=True, integer=True)
+    s = Sum(x**m, (m, 0, M))
+    s_as_product = s.rewrite(Product)
+    assert s_as_product.has(Product)
+    assert s_as_product == log(Product(exp(x**m), (m, 0, M)))
+    assert s_as_product.expand() == s
+    s5 = s.subs(M, 5)
+    s5_as_product = s5.rewrite(Product)
+    assert s5_as_product.has(Product)
+    assert s5_as_product.doit().expand() == s5.doit()
+
+
+def test_has_finite_limits():
+    x = Symbol('x')
+    assert Sum(1, (x, 1, 9)).has_finite_limits is True
+    assert Sum(1, (x, 1, oo)).has_finite_limits is False
+    M = Symbol('M')
+    assert Sum(1, (x, 1, M)).has_finite_limits is None
+    M = Symbol('M', positive=True)
+    assert Sum(1, (x, 1, M)).has_finite_limits is True
+    x = Symbol('x', positive=True)
+    M = Symbol('M')
+    assert Sum(1, (x, 1, M)).has_finite_limits is True
+
+    assert Sum(1, (x, 1, M), (y, -oo, oo)).has_finite_limits is False
+
+def test_has_reversed_limits():
+    assert Sum(1, (x, 1, 1)).has_reversed_limits is False
+    assert Sum(1, (x, 1, 9)).has_reversed_limits is False
+    assert Sum(1, (x, 1, -9)).has_reversed_limits is True
+    assert Sum(1, (x, 1, 0)).has_reversed_limits is True
+    assert Sum(1, (x, 1, oo)).has_reversed_limits is False
+    M = Symbol('M')
+    assert Sum(1, (x, 1, M)).has_reversed_limits is None
+    M = Symbol('M', positive=True, integer=True)
+    assert Sum(1, (x, 1, M)).has_reversed_limits is False
+    assert Sum(1, (x, 1, M), (y, -oo, oo)).has_reversed_limits is False
+    M = Symbol('M', negative=True)
+    assert Sum(1, (x, 1, M)).has_reversed_limits is True
+
+    assert Sum(1, (x, 1, M), (y, -oo, oo)).has_reversed_limits is True
+    assert Sum(1, (x, oo, oo)).has_reversed_limits is None
+
+
+def test_has_empty_sequence():
+    assert Sum(1, (x, 1, 1)).has_empty_sequence is False
+    assert Sum(1, (x, 1, 9)).has_empty_sequence is False
+    assert Sum(1, (x, 1, -9)).has_empty_sequence is False
+    assert Sum(1, (x, 1, 0)).has_empty_sequence is True
+    assert Sum(1, (x, y, y - 1)).has_empty_sequence is True
+    assert Sum(1, (x, 3, 2), (y, -oo, oo)).has_empty_sequence is True
+    assert Sum(1, (y, -oo, oo), (x, 3, 2)).has_empty_sequence is True
+    assert Sum(1, (x, oo, oo)).has_empty_sequence is False
+
+
+def test_empty_sequence():
+    assert Product(x*y, (x, -oo, oo), (y, 1, 0)).doit() == 1
+    assert Product(x*y, (y, 1, 0), (x, -oo, oo)).doit() == 1
+    assert Sum(x, (x, -oo, oo), (y, 1, 0)).doit() == 0
+    assert Sum(x, (y, 1, 0), (x, -oo, oo)).doit() == 0
+
+
+def test_issue_8016():
+    k = Symbol('k', integer=True)
+    n, m = symbols('n, m', integer=True, positive=True)
+    s = Sum(binomial(m, k)*binomial(m, n - k)*(-1)**k, (k, 0, n))
+    assert s.doit().simplify() == \
+        cos(pi*n/2)*gamma(m + 1)/gamma(n/2 + 1)/gamma(m - n/2 + 1)
+
+
+def test_issue_14313():
+    assert Sum(S.Half**floor(n/2), (n, 1, oo)).is_convergent()
+
+
+def test_issue_14563():
+    # The assertion was failing due to no assumptions methods in Sums and Product
+    assert 1 % Sum(1, (x, 0, 1)) == 1
+
+
+def test_issue_16735():
+    assert Sum(5**n/gamma(n+1), (n, 1, oo)).is_convergent() is S.true
+
+
+def test_issue_14871():
+    assert Sum((Rational(1, 10))**n*rf(0, n)/factorial(n), (n, 0, oo)).rewrite(factorial).doit() == 1
+
+
+def test_issue_17165():
+    n = symbols("n", integer=True)
+    x = symbols('x')
+    s = (x*Sum(x**n, (n, -1, oo)))
+    ssimp = s.doit().simplify()
+
+    assert ssimp == Piecewise((-1/(x - 1), (x > -1) & (x < 1)),
+                              (x*Sum(x**n, (n, -1, oo)), True)), ssimp
+    assert ssimp.simplify() == ssimp
+
+
+def test_issue_19379():
+    assert Sum(factorial(n)/factorial(n + 2), (n, 1, oo)).is_convergent() is S.true
+
+
+def test_issue_20777():
+    assert Sum(exp(x*sin(n/m)), (n, 1, m)).doit() == Sum(exp(x*sin(n/m)), (n, 1, m))
+
+
+def test__dummy_with_inherited_properties_concrete():
+    x = Symbol('x')
+
+    from sympy.core.containers import Tuple
+    d = _dummy_with_inherited_properties_concrete(Tuple(x, 0, 5))
+    assert d.is_real
+    assert d.is_integer
+    assert d.is_nonnegative
+    assert d.is_extended_nonnegative
+
+    d = _dummy_with_inherited_properties_concrete(Tuple(x, 1, 9))
+    assert d.is_real
+    assert d.is_integer
+    assert d.is_positive
+    assert d.is_odd is None
+
+    d = _dummy_with_inherited_properties_concrete(Tuple(x, -5, 5))
+    assert d.is_real
+    assert d.is_integer
+    assert d.is_positive is None
+    assert d.is_extended_nonnegative is None
+    assert d.is_odd is None
+
+    d = _dummy_with_inherited_properties_concrete(Tuple(x, -1.5, 1.5))
+    assert d.is_real
+    assert d.is_integer is None
+    assert d.is_positive is None
+    assert d.is_extended_nonnegative is None
+
+    N = Symbol('N', integer=True, positive=True)
+    d = _dummy_with_inherited_properties_concrete(Tuple(x, 2, N))
+    assert d.is_real
+    assert d.is_positive
+    assert d.is_integer
+
+    # Return None if no assumptions are added
+    N = Symbol('N', integer=True, positive=True)
+    d = _dummy_with_inherited_properties_concrete(Tuple(N, 2, 4))
+    assert d is None
+
+    x = Symbol('x', negative=True)
+    raises(InconsistentAssumptions,
+           lambda: _dummy_with_inherited_properties_concrete(Tuple(x, 1, 5)))
+
+
+def test_matrixsymbol_summation_numerical_limits():
+    A = MatrixSymbol('A', 3, 3)
+    n = Symbol('n', integer=True)
+
+    assert Sum(A**n, (n, 0, 2)).doit() == Identity(3) + A + A**2
+    assert Sum(A, (n, 0, 2)).doit() == 3*A
+    assert Sum(n*A, (n, 0, 2)).doit() == 3*A
+
+    B = Matrix([[0, n, 0], [-1, 0, 0], [0, 0, 2]])
+    ans = Matrix([[0, 6, 0], [-4, 0, 0], [0, 0, 8]]) + 4*A
+    assert Sum(A+B, (n, 0, 3)).doit() == ans
+    ans = A*Matrix([[0, 6, 0], [-4, 0, 0], [0, 0, 8]])
+    assert Sum(A*B, (n, 0, 3)).doit() == ans
+
+    ans = (A**2*Matrix([[-2, 0, 0], [0,-2, 0], [0, 0, 4]]) +
+           A**3*Matrix([[0, -9, 0], [3, 0, 0], [0, 0, 8]]) +
+           A*Matrix([[0, 1, 0], [-1, 0, 0], [0, 0, 2]]))
+    assert Sum(A**n*B**n, (n, 1, 3)).doit() == ans
+
+
+def test_issue_21651():
+    i = Symbol('i')
+    a = Sum(floor(2*2**(-i)), (i, S.One, 2))
+    assert a.doit() == S.One
+
+
+@XFAIL
+def test_matrixsymbol_summation_symbolic_limits():
+    N = Symbol('N', integer=True, positive=True)
+
+    A = MatrixSymbol('A', 3, 3)
+    n = Symbol('n', integer=True)
+    assert Sum(A, (n, 0, N)).doit() == (N+1)*A
+    assert Sum(n*A, (n, 0, N)).doit() == (N**2/2+N/2)*A
+
+
+def test_summation_by_residues():
+    x = Symbol('x')
+
+    # Examples from Nakhle H. Asmar, Loukas Grafakos,
+    # Complex Analysis with Applications
+    assert eval_sum_residue(1 / (x**2 + 1), (x, -oo, oo)) == pi/tanh(pi)
+    assert eval_sum_residue(1 / x**6, (x, S(1), oo)) == pi**6/945
+    assert eval_sum_residue(1 / (x**2 + 9), (x, -oo, oo)) == pi/(3*tanh(3*pi))
+    assert eval_sum_residue(1 / (x**2 + 1)**2, (x, -oo, oo)).cancel() == \
+        (-pi**2*tanh(pi)**2 + pi*tanh(pi) + pi**2)/(2*tanh(pi)**2)
+    assert eval_sum_residue(x**2 / (x**2 + 1)**2, (x, -oo, oo)).cancel() == \
+        (-pi**2 + pi*tanh(pi) + pi**2*tanh(pi)**2)/(2*tanh(pi)**2)
+    assert eval_sum_residue(1 / (4*x**2 - 1), (x, -oo, oo)) == 0
+    assert eval_sum_residue(x**2 / (x**2 - S(1)/4)**2, (x, -oo, oo)) == pi**2/2
+    assert eval_sum_residue(1 / (4*x**2 - 1)**2, (x, -oo, oo)) == pi**2/8
+    assert eval_sum_residue(1 / ((x - S(1)/2)**2 + 1), (x, -oo, oo)) == pi*tanh(pi)
+    assert eval_sum_residue(1 / x**2, (x, S(1), oo)) == pi**2/6
+    assert eval_sum_residue(1 / x**4, (x, S(1), oo)) == pi**4/90
+    assert eval_sum_residue(1 / x**2 / (x**2 + 4), (x, S(1), oo)) == \
+        -pi*(-pi/12 - 1/(16*pi) + 1/(8*tanh(2*pi)))/2
+
+    # Some examples made from 1 / (x**2 + 1)
+    assert eval_sum_residue(1 / (x**2 + 1), (x, S(0), oo)) == \
+        S(1)/2 + pi/(2*tanh(pi))
+    assert eval_sum_residue(1 / (x**2 + 1), (x, S(1), oo)) == \
+        -S(1)/2 + pi/(2*tanh(pi))
+    assert eval_sum_residue(1 / (x**2 + 1), (x, S(-1), oo)) == \
+        1 + pi/(2*tanh(pi))
+    assert eval_sum_residue((-1)**x / (x**2 + 1), (x, -oo, oo)) == \
+        pi/sinh(pi)
+    assert eval_sum_residue((-1)**x / (x**2 + 1), (x, S(0), oo)) == \
+        pi/(2*sinh(pi)) + S(1)/2
+    assert eval_sum_residue((-1)**x / (x**2 + 1), (x, S(1), oo)) == \
+        -S(1)/2 + pi/(2*sinh(pi))
+    assert eval_sum_residue((-1)**x / (x**2 + 1), (x, S(-1), oo)) == \
+        pi/(2*sinh(pi))
+
+    # Some examples made from shifting of 1 / (x**2 + 1)
+    assert eval_sum_residue(1 / (x**2 + 2*x + 2), (x, S(-1), oo)) == S(1)/2 + pi/(2*tanh(pi))
+    assert eval_sum_residue(1 / (x**2 + 4*x + 5), (x, S(-2), oo)) == S(1)/2 + pi/(2*tanh(pi))
+    assert eval_sum_residue(1 / (x**2 - 2*x + 2), (x, S(1), oo)) == S(1)/2 + pi/(2*tanh(pi))
+    assert eval_sum_residue(1 / (x**2 - 4*x + 5), (x, S(2), oo)) == S(1)/2 + pi/(2*tanh(pi))
+    assert eval_sum_residue((-1)**x * -1 / (x**2 + 2*x + 2), (x, S(-1), oo)) ==  S(1)/2 + pi/(2*sinh(pi))
+    assert eval_sum_residue((-1)**x * -1 / (x**2 -2*x + 2), (x, S(1), oo)) == S(1)/2 + pi/(2*sinh(pi))
+
+    # Some examples made from 1 / x**2
+    assert eval_sum_residue(1 / x**2, (x, S(2), oo)) == -1 + pi**2/6
+    assert eval_sum_residue(1 / x**2, (x, S(3), oo)) == -S(5)/4 + pi**2/6
+    assert eval_sum_residue((-1)**x / x**2, (x, S(1), oo)) == -pi**2/12
+    assert eval_sum_residue((-1)**x / x**2, (x, S(2), oo)) == 1 - pi**2/12
+
+
+@slow
+def test_summation_by_residues_failing():
+    x = Symbol('x')
+
+    # Failing because of the bug in residue computation
+    assert eval_sum_residue(x**2 / (x**4 + 1), (x, S(1), oo))
+    assert eval_sum_residue(1 / ((x - 1)*(x - 2) + 1), (x, -oo, oo)) != 0
+
+
+def test_process_limits():
+    from sympy.concrete.expr_with_limits import _process_limits
+
+    # these should be (x, Range(3)) not Range(3)
+    raises(ValueError, lambda: _process_limits(
+        Range(3), discrete=True))
+    raises(ValueError, lambda: _process_limits(
+        Range(3), discrete=False))
+    # these should be (x, union) not union
+    # (but then we would get a TypeError because we don't
+    # handle non-contiguous sets: see below use of `union`)
+    union = Or(x < 1, x > 3).as_set()
+    raises(ValueError, lambda: _process_limits(
+        union, discrete=True))
+    raises(ValueError, lambda: _process_limits(
+        union, discrete=False))
+
+    # error not triggered if not needed
+    assert _process_limits((x, 1, 2)) == ([(x, 1, 2)], 1)
+
+    # this equivalence is used to detect Reals in _process_limits
+    assert isinstance(S.Reals, Interval)
+
+    C = Integral  # continuous limits
+    assert C(x, x >= 5) == C(x, (x, 5, oo))
+    assert C(x, x < 3) == C(x, (x, -oo, 3))
+    ans = C(x, (x, 0, 3))
+    assert C(x, And(x >= 0, x < 3)) == ans
+    assert C(x, (x, Interval.Ropen(0, 3))) == ans
+    raises(TypeError, lambda: C(x, (x, Range(3))))
+
+    # discrete limits
+    for D in (Sum, Product):
+        r, ans = Range(3, 10, 2), D(2*x + 3, (x, 0, 3))
+        assert D(x, (x, r)) == ans
+        assert D(x, (x, r.reversed)) == ans
+        r, ans = Range(3, oo, 2), D(2*x + 3, (x, 0, oo))
+        assert D(x, (x, r)) == ans
+        assert D(x, (x, r.reversed)) == ans
+        r, ans = Range(-oo, 5, 2), D(3 - 2*x, (x, 0, oo))
+        assert D(x, (x, r)) == ans
+        assert D(x, (x, r.reversed)) == ans
+        raises(TypeError, lambda: D(x, x > 0))
+        raises(ValueError, lambda: D(x, Interval(1, 3)))
+        raises(NotImplementedError, lambda: D(x, (x, union)))
+
+
+def test_pr_22677():
+    b = Symbol('b', integer=True, positive=True)
+    assert Sum(1/x**2,(x, 0, b)).doit() == Sum(x**(-2), (x, 0, b))
+    assert Sum(1/(x - b)**2,(x, 0, b-1)).doit() == Sum(
+        (-b + x)**(-2), (x, 0, b - 1))
+
+
+def test_issue_23952():
+    p, q = symbols("p q", real=True, nonnegative=True)
+    k1, k2 = symbols("k1 k2", integer=True, nonnegative=True)
+    n = Symbol("n", integer=True, positive=True)
+    expr = Sum(abs(k1 - k2)*p**k1 *(1 - q)**(n - k2),
+        (k1, 0, n), (k2, 0, n))
+    assert expr.subs(p,0).subs(q,1).subs(n, 3).doit() == 3

venv/lib/python3.10/site-packages/sympy/matrices/benchmarks/bench_matrix.py

@@ -0,0 +1,21 @@
+from sympy.core.numbers import Integer
+from sympy.matrices.dense import (eye, zeros)
+
+i3 = Integer(3)
+M = eye(100)
+
+
+def timeit_Matrix__getitem_ii():
+    M[3, 3]
+
+
+def timeit_Matrix__getitem_II():
+    M[i3, i3]
+
+
+def timeit_Matrix__getslice():
+    M[:, :]
+
+
+def timeit_Matrix_zeronm():
+    zeros(100, 100)

venv/lib/python3.10/site-packages/sympy/matrices/tests/test_graph.py

@@ -0,0 +1,108 @@
+from sympy.combinatorics import Permutation
+from sympy.core.symbol import symbols
+from sympy.matrices import Matrix
+from sympy.matrices.expressions import (
+    PermutationMatrix, BlockDiagMatrix, BlockMatrix)
+
+
+def test_connected_components():
+    a, b, c, d, e, f, g, h, i, j, k, l, m = symbols('a:m')
+
+    M = Matrix([
+        [a, 0, 0, 0, b, 0, 0, 0, 0, 0, c, 0, 0],
+        [0, d, 0, 0, 0, e, 0, 0, 0, 0, 0, f, 0],
+        [0, 0, g, 0, 0, 0, h, 0, 0, 0, 0, 0, i],
+        [0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+        [m, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0],
+        [0, m, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0],
+        [0, 0, m, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0],
+        [j, 0, 0, 0, k, 0, 0, 1, 0, 0, l, 0, 0],
+        [0, j, 0, 0, 0, k, 0, 0, 1, 0, 0, l, 0],
+        [0, 0, j, 0, 0, 0, k, 0, 0, 1, 0, 0, l],
+        [0, 0, 0, 0, d, 0, 0, 0, 0, 0, 1, 0, 0],
+        [0, 0, 0, 0, 0, d, 0, 0, 0, 0, 0, 1, 0],
+        [0, 0, 0, 0, 0, 0, d, 0, 0, 0, 0, 0, 1]])
+    cc = M.connected_components()
+    assert cc == [[0, 4, 7, 10], [1, 5, 8, 11], [2, 6, 9, 12], [3]]
+
+    P, B = M.connected_components_decomposition()
+    p = Permutation([0, 4, 7, 10, 1, 5, 8, 11, 2, 6, 9, 12, 3])
+    assert P == PermutationMatrix(p)
+
+    B0 = Matrix([
+        [a, b, 0, c],
+        [m, 1, 0, 0],
+        [j, k, 1, l],
+        [0, d, 0, 1]])
+    B1 = Matrix([
+        [d, e, 0, f],
+        [m, 1, 0, 0],
+        [j, k, 1, l],
+        [0, d, 0, 1]])
+    B2 = Matrix([
+        [g, h, 0, i],
+        [m, 1, 0, 0],
+        [j, k, 1, l],
+        [0, d, 0, 1]])
+    B3 = Matrix([[1]])
+    assert B == BlockDiagMatrix(B0, B1, B2, B3)
+
+
+def test_strongly_connected_components():
+    M = Matrix([
+        [11, 14, 10, 0, 15, 0],
+        [0, 44, 0, 0, 45, 0],
+        [1, 4, 0, 0, 5, 0],
+        [0, 0, 0, 22, 0, 23],
+        [0, 54, 0, 0, 55, 0],
+        [0, 0, 0, 32, 0, 33]])
+    scc = M.strongly_connected_components()
+    assert scc == [[1, 4], [0, 2], [3, 5]]
+
+    P, B = M.strongly_connected_components_decomposition()
+    p = Permutation([1, 4, 0, 2, 3, 5])
+    assert P == PermutationMatrix(p)
+    assert B == BlockMatrix([
+        [
+            Matrix([[44, 45], [54, 55]]),
+            Matrix.zeros(2, 2),
+            Matrix.zeros(2, 2)
+        ],
+        [
+            Matrix([[14, 15], [4, 5]]),
+            Matrix([[11, 10], [1, 0]]),
+            Matrix.zeros(2, 2)
+        ],
+        [
+            Matrix.zeros(2, 2),
+            Matrix.zeros(2, 2),
+            Matrix([[22, 23], [32, 33]])
+        ]
+    ])
+    P = P.as_explicit()
+    B = B.as_explicit()
+    assert P.T * B * P == M
+
+    P, B = M.strongly_connected_components_decomposition(lower=False)
+    p = Permutation([3, 5, 0, 2, 1, 4])
+    assert P == PermutationMatrix(p)
+    assert B == BlockMatrix([
+        [
+            Matrix([[22, 23], [32, 33]]),
+            Matrix.zeros(2, 2),
+            Matrix.zeros(2, 2)
+        ],
+        [
+            Matrix.zeros(2, 2),
+            Matrix([[11, 10], [1, 0]]),
+            Matrix([[14, 15], [4, 5]])
+        ],
+        [
+            Matrix.zeros(2, 2),
+            Matrix.zeros(2, 2),
+            Matrix([[44, 45], [54, 55]])
+        ]
+    ])
+    P = P.as_explicit()
+    B = B.as_explicit()
+    assert P.T * B * P == M

venv/lib/python3.10/site-packages/sympy/matrices/tests/test_sparsetools.py

@@ -0,0 +1,132 @@
+from sympy.matrices.sparsetools import _doktocsr, _csrtodok, banded
+from sympy.matrices.dense import (Matrix, eye, ones, zeros)
+from sympy.matrices import SparseMatrix
+from sympy.testing.pytest import raises
+
+
+def test_doktocsr():
+    a = SparseMatrix([[1, 2, 0, 0], [0, 3, 9, 0], [0, 1, 4, 0]])
+    b = SparseMatrix(4, 6, [10, 20, 0, 0, 0, 0, 0, 30, 0, 40, 0, 0, 0, 0, 50,
+        60, 70, 0, 0, 0, 0, 0, 0, 80])
+    c = SparseMatrix(4, 4, [0, 0, 0, 0, 0, 12, 0, 2, 15, 0, 12, 0, 0, 0, 0, 4])
+    d = SparseMatrix(10, 10, {(1, 1): 12, (3, 5): 7, (7, 8): 12})
+    e = SparseMatrix([[0, 0, 0], [1, 0, 2], [3, 0, 0]])
+    f = SparseMatrix(7, 8, {(2, 3): 5, (4, 5):12})
+    assert _doktocsr(a) == [[1, 2, 3, 9, 1, 4], [0, 1, 1, 2, 1, 2],
+        [0, 2, 4, 6], [3, 4]]
+    assert _doktocsr(b) == [[10, 20, 30, 40, 50, 60, 70, 80],
+        [0, 1, 1, 3, 2, 3, 4, 5], [0, 2, 4, 7, 8], [4, 6]]
+    assert _doktocsr(c) == [[12, 2, 15, 12, 4], [1, 3, 0, 2, 3],
+        [0, 0, 2, 4, 5], [4, 4]]
+    assert _doktocsr(d) == [[12, 7, 12], [1, 5, 8],
+        [0, 0, 1, 1, 2, 2, 2, 2, 3, 3, 3], [10, 10]]
+    assert _doktocsr(e) == [[1, 2, 3], [0, 2, 0], [0, 0, 2, 3], [3, 3]]
+    assert _doktocsr(f) == [[5, 12], [3, 5], [0, 0, 0, 1, 1, 2, 2, 2], [7, 8]]
+
+
+def test_csrtodok():
+    h = [[5, 7, 5], [2, 1, 3], [0, 1, 1, 3], [3, 4]]
+    g = [[12, 5, 4], [2, 4, 2], [0, 1, 2, 3], [3, 7]]
+    i = [[1, 3, 12], [0, 2, 4], [0, 2, 3], [2, 5]]
+    j = [[11, 15, 12, 15], [2, 4, 1, 2], [0, 1, 1, 2, 3, 4], [5, 8]]
+    k = [[1, 3], [2, 1], [0, 1, 1, 2], [3, 3]]
+    m = _csrtodok(h)
+    assert isinstance(m, SparseMatrix)
+    assert m == SparseMatrix(3, 4,
+        {(0, 2): 5, (2, 1): 7, (2, 3): 5})
+    assert _csrtodok(g) == SparseMatrix(3, 7,
+        {(0, 2): 12, (1, 4): 5, (2, 2): 4})
+    assert _csrtodok(i) == SparseMatrix([[1, 0, 3, 0, 0], [0, 0, 0, 0, 12]])
+    assert _csrtodok(j) == SparseMatrix(5, 8,
+        {(0, 2): 11, (2, 4): 15, (3, 1): 12, (4, 2): 15})
+    assert _csrtodok(k) == SparseMatrix(3, 3, {(0, 2): 1, (2, 1): 3})
+
+
+def test_banded():
+    raises(TypeError, lambda: banded())
+    raises(TypeError, lambda: banded(1))
+    raises(TypeError, lambda: banded(1, 2))
+    raises(TypeError, lambda: banded(1, 2, 3))
+    raises(TypeError, lambda: banded(1, 2, 3, 4))
+    raises(ValueError, lambda: banded({0: (1, 2)}, rows=1))
+    raises(ValueError, lambda: banded({0: (1, 2)}, cols=1))
+    raises(ValueError, lambda: banded(1, {0: (1, 2)}))
+    raises(ValueError, lambda: banded(2, 1, {0: (1, 2)}))
+    raises(ValueError, lambda: banded(1, 2, {0: (1, 2)}))
+
+    assert isinstance(banded(2, 4, {}), SparseMatrix)
+    assert banded(2, 4, {}) == zeros(2, 4)
+    assert banded({0: 0, 1: 0}) == zeros(0)
+    assert banded({0: Matrix([1, 2])}) == Matrix([1, 2])
+    assert banded({1: [1, 2, 3, 0], -1: [4, 5, 6]}) == \
+        banded({1: (1, 2, 3), -1: (4, 5, 6)}) == \
+        Matrix([
+        [0, 1, 0, 0],
+        [4, 0, 2, 0],
+        [0, 5, 0, 3],
+        [0, 0, 6, 0]])
+    assert banded(3, 4, {-1: 1, 0: 2, 1: 3}) == \
+        Matrix([
+        [2, 3, 0, 0],
+        [1, 2, 3, 0],
+        [0, 1, 2, 3]])
+    s = lambda d: (1 + d)**2
+    assert banded(5, {0: s, 2: s}) == \
+        Matrix([
+        [1, 0, 1,  0,  0],
+        [0, 4, 0,  4,  0],
+        [0, 0, 9,  0,  9],
+        [0, 0, 0, 16,  0],
+        [0, 0, 0,  0, 25]])
+    assert banded(2, {0: 1}) == \
+        Matrix([
+        [1, 0],
+        [0, 1]])
+    assert banded(2, 3, {0: 1}) == \
+        Matrix([
+        [1, 0, 0],
+        [0, 1, 0]])
+    vert = Matrix([1, 2, 3])
+    assert banded({0: vert}, cols=3) == \
+        Matrix([
+        [1, 0, 0],
+        [2, 1, 0],
+        [3, 2, 1],
+        [0, 3, 2],
+        [0, 0, 3]])
+    assert banded(4, {0: ones(2)}) == \
+        Matrix([
+        [1, 1, 0, 0],
+        [1, 1, 0, 0],
+        [0, 0, 1, 1],
+        [0, 0, 1, 1]])
+    raises(ValueError, lambda: banded({0: 2, 1: ones(2)}, rows=5))
+    assert banded({0: 2, 2: (ones(2),)*3}) == \
+        Matrix([
+        [2, 0, 1, 1, 0, 0, 0, 0],
+        [0, 2, 1, 1, 0, 0, 0, 0],
+        [0, 0, 2, 0, 1, 1, 0, 0],
+        [0, 0, 0, 2, 1, 1, 0, 0],
+        [0, 0, 0, 0, 2, 0, 1, 1],
+        [0, 0, 0, 0, 0, 2, 1, 1]])
+    raises(ValueError, lambda: banded({0: (2,)*5, 1: (ones(2),)*3}))
+    u2 = Matrix([[1, 1], [0, 1]])
+    assert banded({0: (2,)*5, 1: (u2,)*3}) == \
+        Matrix([
+        [2, 1, 1, 0, 0, 0, 0],
+        [0, 2, 1, 0, 0, 0, 0],
+        [0, 0, 2, 1, 1, 0, 0],
+        [0, 0, 0, 2, 1, 0, 0],
+        [0, 0, 0, 0, 2, 1, 1],
+        [0, 0, 0, 0, 0, 0, 1]])
+    assert banded({0:(0, ones(2)), 2: 2}) == \
+        Matrix([
+        [0, 0, 2],
+        [0, 1, 1],
+        [0, 1, 1]])
+    raises(ValueError, lambda: banded({0: (0, ones(2)), 1: 2}))
+    assert banded({0: 1}, cols=3) == banded({0: 1}, rows=3) == eye(3)
+    assert banded({1: 1}, rows=3) == Matrix([
+        [0, 1, 0],
+        [0, 0, 1],
+        [0, 0, 0]])

venv/lib/python3.10/site-packages/sympy/multipledispatch/__init__.py

@@ -0,0 +1,11 @@
+from .core import dispatch
+from .dispatcher import (Dispatcher, halt_ordering, restart_ordering,
+    MDNotImplementedError)
+
+__version__ = '0.4.9'
+
+__all__ = [
+    'dispatch',
+
+    'Dispatcher', 'halt_ordering', 'restart_ordering', 'MDNotImplementedError',
+]