scientific libraries for python

[Harold Fellermann]

Hi all,

I want to use the current need for a Levenberg-Marquardt least squares
fitting procedure
for my long term desire to dive into scientific libraries for python.
However, I am always
confused by the shear sheer variety of available packages and the fact
that some of them
(Numeric, Numarray) seem to be outdated.

http://wiki.python.org/moin/NumericAndScientific gives a nice overview
of the most
popular packages. According to this listing, ScientificPython and
PyDSTool seem most
appropriate for what I generally work on (simulations of dynamical
systems and data
analysis).

Before I start to dive into one of these packages (I would go for
ScientificPython from what
I know so far), I want to ask about your experiences. Is there a good
reason to choose
one instead of the other? Or do they even work together, in the sense
that I can use
PyDSTool to generate data to be later analyzed by ScientifPython
without much timeconsuming
conversion a.s.o. in between?

Thanks for any suggestions!

- harold -

 

[Robert Kern]

Hi all,

I want to use the current need for a Levenberg-Marquardt least squares
fitting procedure
for my long term desire to dive into scientific libraries for python.

Does it have to be Levenberg-Marquardt, or will another non-linear least squares
procedure do?

However, I am always
confused by the shear sheer variety of available packages and the fact
that some of them
(Numeric, Numarray) seem to be outdated.

Fair enough.

http://wiki.python.org/moin/NumericAndScientific gives a nice overview
of the most
popular packages. According to this listing, ScientificPython and
PyDSTool seem most
appropriate for what I generally work on (simulations of dynamical
systems and data
analysis).

I find this page to be a little bit richer:

http://www.scipy.org/Topical_Software

Before I start to dive into one of these packages (I would go for
ScientificPython from what
I know so far), I want to ask about your experiences. Is there a good
reason to choose
one instead of the other?

They are largely orthogonal to one another in capabilities. You would use the
package that solves the problem in front of you. Quite possibly, you will be
using both.

Or do they even work together, in the sense
that I can use
PyDSTool to generate data to be later analyzed by ScientifPython
without much timeconsuming
conversion a.s.o. in between?

Both of them currently use the old Numeric so there are no real issues
converting between the two of them; they both use the same arrays. Install the
latest version of old Numeric (24.2), and you can convert to numpy arrays
without wasting memory.

For nonlinear least squares, I would probably recommend using my wrappers of
ODRPACK currently residing in the scipy sandbox. It uses numpy. It is very flexible.

http://projects.scipy.org/scipy/scipy/browser/trunk/Lib/sandbox/odr

If you need help installing scipy or using odr, come over to one of the scipy
lists, and I'll help you out.

http://www.scipy.org/Mailing_Lists

--
Robert Kern

"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