Time to move from Numerical Python to SciPy Core

If you are a Python user, and you do Numerical Analysis, it might be time to move from Numerical Python to SciPy Core. I complained earlier about SciPy Core, but it seems that most of the problems I pointed out (missing inline documentation and broken functions) have either been fixed, or I wrongly pointed a finger.

I still have a few issues with the new package though:

  • The naming convention for the LinearAlgebra package is awful. I don’t want to have to work with a package called “scipy.basic.linalg”: if you want to save space, don’t abbreviate LinearAlgebra to linalg and add three subpackages to it. Call the package scipy.LinearAlgebra, for example.
  • There are glitches in the documentation. Both “help(scipy.basic.linalg)” or “help(scipy.linalg)” return a page describing “scipy.basic.linalg” as the “Lite version of scipy.linalg” and a list of 3 supported functions (Heigenvectors, eigenvectors, singular_value_decomposition). There are more than only 3 functions in this package!

On the positive side of things, you can now simply do “import scipy” to get the basic functions (like the scipy.array class). So, time to switch!

Published by

Daniel Lemire

A computer science professor at the Université du Québec (TELUQ).

Leave a Reply

Your email address will not be published. Required fields are marked *

To create code blocks or other preformatted text, indent by four spaces:

    This will be displayed in a monospaced font. The first four 
    spaces will be stripped off, but all other whitespace
    will be preserved.
    
    Markdown is turned off in code blocks:
     [This is not a link](http://example.com)

To create not a block, but an inline code span, use backticks:

Here is some inline `code`.

For more help see http://daringfireball.net/projects/markdown/syntax