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PDL 2.4.0: Scientific Computing for the Masses
Dr. Zowie writes "Perl Data Language 2.4.0 was just released;
get it here. This release includes even more powerful array slicing, a complete GIS cartography package, API access to the Gnu Scientific Library, and a host of other goodies. Between PDL and its less-mature siblings Numeric Python and Octave, the established commercial languages'
days appear numbered."
Well, I don't know about how mature/not mature Scientific Python or Octave are with respect to PDL, but I like Python better and I was used to Matlab in the past anyway.
At present, I am using Scipy, a nice more complete version of Numerical Python. Together with IPython, I get a very nice numerical environment. Unfortunately, while Scipy is very nice, it is still a bit of a bleeding edge product. But it is **very** fast for large array computations. I also like the fact that you can link fortran routines easily (yes, people still use fortran, it's useful and easy).
I also use Octave because I miss the ease of generating plots in Matlab (yes, I could do this with scipy, but somehow, I resort to using Octave). It is a very complete program, with many toolboxes. Given that some of the Matlab toolboxes can also be incorporated, there is a vast array of functions for you to play around with.
On the other hand, I think that none of the "established languages" are a good comparison. IDL is extremely powerful for Remote Sensing/Image Processing tasks (my area of research). It is simple to use, and a bit of a standard in the field. From the PDL changelog, the cartographic features in PDL amount to no more than transformations... Mathematica is extremely powerful in symbolic Maths, which as far as I can tell, is not what pdl is about. And Matlab is turning into the VB of scientists (at least, it is multiplatform :D)
Oh well, I'll have to give it a go :-D