On Fri, Apr 4, 2008 at 9:49 AM, Travis E. Oliphant <[EMAIL PROTECTED]> wrote: > However, if clearly better interfaces can be discovered, then we could > change it. For now, the functions are not imported into the numpy > namespace but live in > > numpy.lib.financial > > I could see a future scipy module containing much, much more. > > Comments and improvement suggestions welcome. We are a week away from > release of NumPy 1.0.5, and hopefully we can agree before then.
I'm generally in agreement with other opinions about keeping numpy lightweight even though I think these functions are useful and should be widely distributed with numpy. I've struggled with the various masked array implementations being worlds unto their own, falling down unexpectedly when mixed with other numpy functions, so keeping a narrow focus seems beneficial (as in its clear that I shouldn't expect A and B to work necessarily together). Nevertheless, I like getting a lot of utility from each package as it seems cognitive load is proportional to the number of packages required-- especially when the packages are compiled. Perhaps, as others have suggested, there should be some sort of pure-python numpy library package (a NumPyLib, if you will) that sits between numpy and scipy? I'm a numpy user but not a scipy user (I guess from an attempt to decrease the cognitive load of yet another compiled python package), so I'm speaking from that perspective. I also wouldn't be opposed to (for NumPy 4 :) breaking out the core ndarray class and basic linalg (solve, svg, eig, etc.) as NDArray and putting everything else into logically separated but independent NumKits. A blessed collection of which are together taken and distributed as "NumPy". Anything depending on one ore more NumKits would go into a SciKit, with a blessed collection distributed together as "SciPy". Has this basic distribution architecture already been proposed? I've heard hints of something along these lines. If so, then the new new financial functions should go into numpy.lib, where everything will later be broken out into a NumKit. Hmm. I've just argued myself in a circle... :O Regards, Alex _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
