Harold Fellermann wrote: > 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 (Numeric, Numarray) seem to be outdated.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 -- http://mail.python.org/mailman/listinfo/python-list
