Python as a numerical prototyping language.

[Carl]

Johannes.Nix at web.de wrote:

> In my eyes, what Python, and Open Source in general, is still lacking
> is an very easy, fast and very high-quality library for scientific and
> financial plotting, although there are lots of good and thougthful
> beginnings like Gnuplot, OpenDX, and many more. This would be an
> essential building block to foster the use of Python in science.

I agree! I use Gnuplot, it works OK, but is not perfect. I am also not that
enthusiastic about the algebra syntax of the Numerics module. I wish it was
closer to the Matlab syntax, which is much easier to grasp. 

Python + Numeric + pygsl + FFTW + ... is, according to my view, a very good
alternative to using Matlab, Scilab, or R. What is missing is a large, rich
scientific library, and a better syntax for manipulating matrices and
vectors. On the other hand, what Python has got is an enormous amount of
modules for doing almost anything. For instance, there are Python libraries
for reading and writing to databases and building interfaces (very
important for building industry strength applications). So, if only Python
had a very large, rich, and fast library for numerical calculations and
scientific plotting I would be as happy as one can be.

I have used Matlab, Scilab, and R for quite some time. The last year,
however, I have started to use Python more and more. I wonder why? My guess
is that Python already is a viable environment for doing explorative data
analyses and testing numerical algorithms.

When it comes to speed, I feel that Python + Numeric is up to the task. For
example, I have been playing around with Monte Carlo simulation using list,
dictionaries, an numerical vectors and matrices as much as possible, and
have experienced performance very close to comparable code in C.

Carl