[SciPy-user] Would anyone connect fortran constrained linear least squares solver to Python?

[dmitrey]

hi Dominique,
I think the example is rather precise and convenient.
However, I get error while building NLPy:

make
[[ ! -d /home/dmitrey/install/NLPy/nlpy/.objects ]] && mkdir
/bin/sh: [[: not found
make: *** [/home/dmitrey/install/NLPy/nlpy/.objects] Error 127

same error from restore-links I have avoided via restoring it in command 
prompt (I guess it would be better to write several files 
restoreLinksLinux, restoreLinksWindows etc).

So, what should I do to avoid the error?
Regards, D.

Dominique Orban wrote:
> In a sense, my situation is not unlike yours since I am not often able
> to spend much time writing documentation. However, a text document is
> not the only medium to communicate documentation. NLPy has demo code
> for almost all features in the Examples subfolder. Moreover, many
> modules can be executed (to run a basic test). Regarding LSQR, the
> default demo is
>
> http://nlpy.svn.sourceforge.net/viewvc/nlpy/trunk/nlpy/Examples/demo_lsqr.py?revision=68&view=markup
>
> and shows how to use the code. The function aprod() could be any
> function that computes a matrix-vector product. The module lsqr.py
> itself has a docstring explaining what problem it is trying to solve
> and how. It also gives references to papers, for those who are that
> motivated.
>
> Cheers,
> Dominique
>