[Numpy-discussion] Producing a Histogram When Bins Are Known
Fri Nov 27 12:15:50 CST 2009
On Fri, Nov 27, 2009 at 12:57 PM, Skipper Seabold <email@example.com> wrote:
> On Fri, Nov 27, 2009 at 12:41 PM, Christopher Barker
> <Chris.Barker@noaa.gov> wrote:
>> 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
>> 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:
>> And yes, that is the place for such questions.
> Well put, Chris. It took me a long time get my head around these
> distinctions, and then only when others pointed out my errors in
> understanding. This kind of info might be useful to other newcomers
> somewhere... <http://www.scipy.org/History_of_SciPy>? Thoughts on
> posting this on the wiki here?
I also agree. It will improve with the newly redesigned website for scipy.org
However, I cannot find the link right now for the development version of
the new website.
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