robert.kern at gmail.com
Mon Mar 12 18:27:37 CET 2007
Michele Simionato wrote:
> On Mar 12, 5:28 pm, Paul Rubin <http://phr...@NOSPAM.invalid> wrote:
>> "Michele Simionato" <michele.simion... at gmail.com> writes:
>>> Any pointer would be well received :)
>> Dunno about those libs but it helps to understand the mathematical
>> options. Numerical Recipes by Teukolsky et al has understandable,
>> cookbook-like advice about this stuff. I'm told that true numerics
>> gurus scoff at it but it's at least a start.
> No, I know about Numerical Recipes, I want an already-made solution.
> For instance I found one here
> but I wonder if I should use numpy or something else, since
> I am not following the progresses in numerical Python these days.
It sounds like you want nonlinear curve fitting rather than interpolation. I do
recommend using numpy as the underlying array package, but it does not provide
any curve fitting itself. The 2.7 branch of ScientificPython can work with numpy
instead of Numeric, if you like. See the README.
scipy also has a variety of curve fitting routines at the expense of a more
involved install. scipy.optimize.leastsq() might be sufficient for you, but the
scipy.odr package is much more flexible (but get scipy from SVN for that; the
latest release has some unfortunate bugs in that package).
"I have come to believe that the whole world is an enigma, a harmless enigma
that is made terrible by our own mad attempt to interpret it as though it had
an underlying truth."
-- Umberto Eco
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