The code doesn't quite run, since it references some other function
(ps_coefficient); here's an updated version which uses only built-in
functions:
def ps_inverse_Lagrange(f):
if f.valuation() != 1:
raise ValueError, "series must have valuation one for
reversion"
if f.prec() is infinity:
raise ValueError, "series must have finite precision for
reversion"
t = parent(f).gen()
h = t/f
k = 1
g = 0
for i in range(1, f.prec()):
k *= h
g += (1/i)*k.padded_list(i)[i - 1]*t^i
g += O(t^f.prec())
return g
On Dec 9, 3:20 pm, William Stein <wst...@gmail.com> wrote:
> On Wed, Dec 9, 2009 at 10:50 AM, Matt Bainbridge
>
> > For more options, visit this group athttp://groups.google.com/group/sage-support