'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.
Usage
``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.simplification.index,
sympy.concrete.simplification.reorder_limit,
sympy.concrete.simplification.reorder,
sympy.concrete.simplification.reverse_order'

def change_index(self, var, trafo, newvar=None):

    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:
                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)
