[SciPy-dev] Re: Future directions
gruben at bigpond.net.au
Wed Mar 9 06:12:39 CST 2005
> It would seem that while the scipy conference demonstrates a continuing
> and even increasing use of Python for scientific computing, not as many
> of these users are scipy devotees. Why?
> I think the answers come down to a few issues which I will attempt to
> answer with proposals.
> 1) Plotting -- scipy's plotting wasn't good enough (we knew that) and
> the promised solution (chaco) took too long to emerge as a simple
> replacement. While the elements were all there for chaco to work, very
> few people knew that and nobody stepped up to take chaco to the level
> that matplotlib, for example, has reached in terms of cross-gui
> applicability and user-interface usability.
I found plt and gplt too limiting from early on and quickly moved to
Matplotlib would be a nice choice, mainly due to its active development,
clean interface and good documentation.
I haven't been keeping up - is Chaco dead? That would be a shame. Python
is still missing a cross-platform GUI-interactive plotting package. A
long time ago, I toyed with implementing errorbars in Chaco, but found
it too unapproachable, mainly due to lack of documentation.
> 2) Installation problems -- I'm not completely clear on what the
> "installation problems" really are. I hear people talk about them, but
> Pearu has made significant strides to improve installation, so I'm not
> sure what precise issues remain. Yes, installing ATLAS can be a pain,
> but scipy doesn't require it. Yes, fortran support can be a pain, but
> if you use g77 then it isn't a big deal. The reality, though, is that
> there is this perception of installation trouble and it must be based on
> something. Let's find out what it is. Please speak up users of the
They may be thinking of what it used to be like - things have improved,
so it may be a case of re-education or patience.
> Thoughts and comments (and even half-working code) welcomed and
> -Travis O.
One thing missing from your list about lack of uptake is lack of decent
pdf-based documentation a'la Numeric or Numarray or even matplotlib
docs. I know this was discussed a little while back so it will happen,
but I personally think it is a hurdle for people wanting to know exactly
what Scipy contains and could be the main reason for lower than expected
One day I'll get my ErrorVal module cleaned up enough to re-propose it
for inclusion in Scipy :-) but I'm studying honours physics at the
moment, so I have no life or time.
More information about the Scipy-dev