[Matrix-SIG] Re: a full-blown interactive data analysis environment

[Johann Hibschman]

>>>>> "david" == david buscher <david.buscher@durham.ac.uk> writes:

    david> [1] A python-specific IDL-alike, well documented and
    david> integrated, having the major advantages that have been
    david> described (basically all the specific advantages of python
    david> and general interpreted language and open source
    david> advantages).

    david> [2] A non-language specific system which can be rapidly
    david> ported to the next flavour-of-the-month language (not that
    david> I think python is flavour-of-the-month!).

    david> My feeling is that the [2] is a much harder project, and we
    david> might only have a feeling of how to do it by the end of
    david> doing [1]. Obviously it would be a great help if while
    david> doing [1] we had [2] in mind. What do others think?

I agree that [2] is much harder.  I think that if we are to get
anything done, we should just do [1] with [2] in mind, otherwise we'll
have a spurt of theory posts which eventually die down without having
accomplished anything.

[2] seems hard.  For a lot of interesting things (numeric integration,
ODEs, PDEs), we'd need a decent (and fast) way to pass functions
around, whether those functions are native-code, python, or
interpolations on discrete data points.  I've yet to see one which
works well.

FFTPACK and friends certainly exist, but using those on many machines
requries running them through f2c, and that adds complexity (and extra
required libraries).  Ideally, in today's world (assuming we're
targetting typical workstation users, we'd just use straight C.
(C++ still seems dangerous, but that may just be the result of some
bad experiences on my part...)

Well, I'm rambling.  I'd like to see this work, even if all it does is
assemble a recommended set of netlib routines with extra
documentation.  As a numeric novice, I'm often swamped by the sheer
volume of choice and lack of information on how to choose when looking
at netlib.

-- 
Johann Hibschman                           johann@physics.berkeley.edu