Wayne Watson wrote:
Yes, I'm just beginning to deal with the contents of NumPy, SciLab, and SciPy. They all have seemed part of one another, but I think I see how they've divided up the game.
For the record: I know this is a bit confusing, particularly for someone used to an integrated package like Matlab, etc, but there is a lot of power an flexibility gained by the divisions: Python: is a general-purpose, extensible programming language Numpy: is a set of package of classes, functions, etc that provide facilities for numeric computation -- primarily a n-d array class and the utilities to use it. Matplotlib (MPL): is a plotting package, built on top of numpy -- it was originally designed to somewhat mimic the plotting interface of Matlab. MPL is the most commonly used plotting package for numpy, but by no means the only one. Pylab: Is a package that integrates matplotlib and numpy and an assortment of other utilities into one namespace, making it more like Matlab -- personally, I think you should avoid using it, it makes it a bit easier to type code, but harder to know where the heck what you are doing is coming from. SciPy: Is a broad collection of assorted utilities that facilitate scientific computing, built on Numpy -- it is also sometimes used as an umbrella term for anything connected to scientific computing with Python (i.e. the SciPy conferences) These distinctions are a bit confusing (particularly MPL-numpy), because MPL includes a number of utility functions that combine computation and plotting: like "hist", which both computes a histogram, and plots it as bar chart in one call -- it's a convenient way to perform a common operation, but it does blur the lines a bit! By the way -- there is also potentially a bit of confusion as to how MPL uses/interacts with the command line and GUI toolkits. This is because MPL can be used with a number of different GUI front-ends (or none), and they tend to take over control from the command line. Which brings up to: iPython: an enhanced python interactive interpreter command line system. It adds many nice features that make using python in interactive mode nicer. IN particularly, it adds a "--pylab" mode that helps it play well with MPL. You won't regret using it!
I thought I'd look through Amazon for books on Python and scientific uses. I found almost all were written by authors outside the US, and none seemed to talk about items like matplotlib.
FWIW, a book about MPL has just been published -- I don't know any more about it, but I'm sure google will tell you.
Is there a matplotlib or Pylab mailing list?
There certainly is: https://lists.sourceforge.net/lists/listinfo/matplotlib-users And yes, that is the place for such questions. HTH, -Chris -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/OR&R (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception Chris.Barker@noaa.gov