Sure, Ondrej. I will send a PR for it.

On Wed, Jun 10, 2015 at 9:23 PM, Shivam Vats <[email protected]> wrote:

> Mario, the algorithm looks quite similar to the Newton
> method you have used for functional inverses for
> expanding tan and tanh. We could also expand `sin/cos`.
> Which one do think should be faster?
>
> Also, can the convergence of the method be proven?
> I could not find any reference to it (except the algorithm
> in Computer Arithmetic by Paul Zimmerman).
>
> Shivam Vats
>
> On Wed, Jun 10, 2015 at 9:00 PM, mario <[email protected]> wrote:
>
>>
>> There is  `series_reversion` in PR609.
>>
>> On Wednesday, June 10, 2015 at 6:39:02 AM UTC+2, Ondřej Čertík wrote:
>>>
>>> On Tue, Jun 9, 2015 at 7:33 PM, Aaron Meurer <[email protected]> wrote:
>>> > On Tue, Jun 9, 2015 at 7:09 PM, Ondřej Čertík <[email protected]>
>>> wrote:
>>> >> Hi,
>>> >>
>>> >> I would like to evaluate to higher accuracy (quadruple precision is
>>> >> enough) an inverse Fermi-Dirac integral of order 1/2. The direct
>>> >> function is the following integral (and it can also be written as a
>>> >> polylogarithm):
>>> >>
>>> >> I_{1/2}(x) = Integral(sqrt(t) / (1+exp(t-x)), (t, 0, oo))
>>> >>   = -gamma(S(3)/2) * polylog(S(3)/2, -exp(x))
>>> >>
>>> >> and I need its inverse. SymPy can evaluate either representation:
>>> >>
>>> >> In [19]: (-gamma(S(3)/2) * polylog(S(3)/2, -exp(x))).subs(x, 3).n(35,
>>> chop=True)
>>> >> Out[19]: 3.9769853540479774178558497377805661
>>> >>
>>> >> In [20]: Integral(sqrt(t) / (1+exp(t-x)), (t, 0, oo)).subs(x,
>>> 3).n(35)
>>> >> Out[20]: 3.9769853540479774178558497377805661
>>> >>
>>> >> I need to calculate an inverse, i.e. for 3.9769... it would return
>>> >> 3.00..., to arbitrary accuracy. Once I have that, I want to use
>>> >> rational function approximation to obtain very fast and accurate
>>> >> double precision implementation.
>>> >>
>>> >> What is the best way to do that?
>>> >>
>>> >> There is a recent publication [1], which does that using Mathematica,
>>> >> and then provides Fortran implementation. I tested it and it works
>>> >> great. What I actually need is to find a rational approximation to an
>>> >> expression that contains both the inverse and direct Fermi-Dirac
>>> >> integrals and I want to just have a rational approximation for the
>>> >> final expression. The inverse Fermi-Dirac is the hardest part, so
>>> >> that's why I am asking.
>>> >>
>>> >> In [1], they calculate a series expansion of the Fermi-Dirac integral
>>> >> and then they reverse (invert) the series, see eq. (9), (10), (14),
>>> >> (15) and the Mathematica code afterwards. Unfortunately, SymPy raises
>>> >> an exception for a series of the polylog function:
>>> >>
>>> >> In [23]: polylog(S(3)/2, -z).series(z, 0, 5)
>>> >>
>>> >> https://github.com/sympy/sympy/issues/9497
>>> >>
>>> >> But let's say we fix it. Here i s a slightly modified expression that
>>> works:
>>> >>
>>> >> In [6]: polylog(S(3)/2, 1+z).series(z, 0, 5)
>>> >> zeta(3/2) + z*zeta(1/2) + z**2*(zeta(-1/2)/2 - zeta(1/2)/2) +
>>> >> z**3*(zeta(1/2)/3 + zeta(-3/2)/6 - zeta(-1/2)/2) +
>>> >> z**4*(11*zeta(-1/2)/24 + zeta(-5/2)/24 - zeta(-3/2)/4 - zeta(1/2)/4)
>>> +
>>> >> O(z**5)
>>> >>
>>> >> How can we invert the series? Mathematica has a function
>>> InverseSeries:
>>> >>
>>> >> http://reference.wolfram.com/language/ref/InverseSeries.html
>>> >>
>>> >> It seems SymPy can't do it yet.
>>> >>
>>> >> Shivam, I think that would be a very useful addition to the series
>>> >> module that you are implementing. We have to figure out an algorithm
>>> >> for it.
>>> >
>>> > I think there's a closed form for the inversion of a formal power
>>> > series. See
>>> https://en.wikipedia.org/wiki/Formal_power_series#The_Lagrange_inversion_formula.
>>>
>>> >
>>> > I'm not sure what the algorithm is for series like x*sin(x), which
>>> > that Mathematica example shows is a series in sqrt(x). I suppose
>>> > that's because the linear term is 0 (the Wikipedia article claims that
>>> > the constant needs to be 0 and the linear term needs to be nonzero).
>>> > Strictly speaking x*sin(x) is not invertible near x=0 (it's an even
>>> > function). I guess this picks one branch and inverts that.
>>>
>>> I don't quite get it with the constant term, but it seems to be true,
>>> e.g. the inversion of exp(x) = 1 + x + .... doesn't exist, because
>>> that would be log(x), which doesn't have an expansion around x=0. One
>>> can only expand e.g. log(1+x), as the inverse is exp(x)-1.
>>>
>>> I found a pretty good intro here:
>>>
>>> http://mathworld.wolfram.com/SeriesReversion.html
>>>
>>> with further references to literature.
>>>
>>> >
>>> > Aaron Meurer
>>> >
>>> >>
>>> >> Ondrej
>>> >>
>>> >>
>>> >> [1] Fukushima, T. (2015). Precise and fast computation of inverse
>>> >> Fermi–Dirac integral of order 1/2 by minimax rational function
>>> >> approximation. Applied Mathematics and Computation, 259, 698–707.
>>> >> doi:10.1016/j.amc.2015.03.015
>>> >>
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