Hey Travis, It sounds like the Berkeley meeting went well. I am glad that the Numeric3 project is going well and looks like it has a good chance to unify the Numeric/Numarray communities. I really appreciate you putting in so much effort intto its implementation. I also appreciate all the work by Perry, Todd, and the others at StSci have done building Numarray. We've all learned a ton from it. Most of the plans sound right to me (several questions/comments below). Much of SciPy has been structured in this way already, but we really have never worked to make the core useful as a stand alone package. Supporting lite and full versions of fft, linalg, and stats sounds potentially painful, but also worthwhile given the circumstances. Now: 1. How much of stats do we loose from removing fortran dependencies? 2. I do question whether weave really be in this core? I think it was in scipy_core before because it was needed to build some of scipy. 3. Now that I think about it, I also wonder if f2py should really be there -- especially since we are explicitly removing any fortran dependencies from the core. 4. I think keeping scipy a algorithms library and leaving plotting to other libraries is a good plan. At one point, the setup_xplt.py file was more than 1000 lines. It is much cleaner now, but dealing with X11, etc. does take maintenance work. Removing these libraries from scipy would decrease the maintenance effort and leave the plotting to matplotlib, chaco, and others. 5. I think having all the generic algorithm packages (signal, ga, stats, etc. -- basically all the packages that are there now) under the scipy namespace is a good idea. It prevents worry about colliding with other peoples packages. However, I think domain specific libraries (such as astropy) should be in their own namespace and shouldn't be in scipy. thanks, eric Travis Oliphant wrote:
I had a lengthy discussion with Eric today and clarified some things in my mind about the future directions of scipy. The following is basically what we have decided. We are still interested in input so don't think the issues are closed, but I'm just giving people an idea of my (and Eric's as far as I understand it) thinking on scipy.
1) There will be a scipy_core package which will be essentially what Numeric has always been (plus a few easy to install extras already in current scipy_core). It will likely contain the functionality of (the names and placements will be similar to current scipy_core). Numeric3 (actually called ndarray or narray or numstar or numerix or something....) fft (based on c-only code -- no fortran dependency) linalg (a lite version -- no fortran or ATLAS dependency) stats (a lite version --- no fortran dependency) special (only c-code --- no fortran dependency) weave f2py? (still need to ask Pearu about this) scipy_distutils and testing matrix and polynomial classes
...others...?
We will push to make this an easy-to-install effective replacement for Numeric and hopefully for numarray users as well. Therefore community input and assistance will be particularly important.
2) The rest of scipy will be a package (or a series of packages) of algorithms. We will not try to do plotting as part of scipy. The current plotting in scipy will be supported for a time, but users will be weaned off to other packages: matplotlib, pygist (for xplt -- and I will work to get any improvements for xplt into pygist itself), gnuplot, etc.
3) Having everything under a scipy namespace is not necessary, nor worth worrying about at this point.
My scipy-related focus over the next 5-6 months will be to get scipy_core to the point that most can agree it effectively replaces the basic tools of Numeric and numarray.
-Travis
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