On Tue, Nov 15, 2011 at 2:53 AM, Volker Blum <b...@fhi-berlin.mpg.de> wrote:
>
> On Nov 14, 2011, at 5:34 PM, Volker Blum wrote:
>
> > Thanks for the (two!) fast answers on the list. So there is hope :) I'll
> take a look at the fink internals, I guess.
> > best wishes
> > Volker
>
> having said that ... after trying the one piece of software that I need on
> another platform, here's what I get:
>
> File "[...]", line 84, in <module>
> length = norm(dot(rlatvec,end) - dot(rlatvec,start))
> File "/usr/lib64/python2.6/site-packages/matplotlib/mlab.py", line 1998,
> in norm
> raise NotImplementedError('Deprecated - see numpy.linalg.norm')
> NotImplementedError: Deprecated - see numpy.linalg.norm
>
> The script that I was trying to get to work worked fine on Ubuntu this
> summer. Where has "norm" gone? How can it have been deprecated? It looks
> like a matplotlib problem, hence I am asking here.
>
> [I am also asking out of some curiosity - I am sure the problem can be
> fixed relatively easily, but what I am wondering is, am I looking at a
> problem that came with a new version of matplotlib, am I using too old a
> version of matplotlib?]
>
> best wishes
> Volker
>
>
Others are probably more suited for explaining the hows and whys of
mlab.py, but I will give it a crack. mlab.py was originally made to help
assist users transitioning from Matlab over to matplotlib. Some functions
that were probably considered to be top-tier in Matlab had to be accessed
in sub-modules in NumPy, or were only available in the scipy packages.
mlab.py attempted to address that.
There is also the issue where we were attempting to bridge compatibility
with the old Numerix package which did not have many of these things at
all. Support for Numerix has long been deprecated and so the need for many
of the functions in mlab.py has gone away. This is why we now refer to the
equivalent numpy function in the deprecation messages.
In v1.1.0, the norm() function is completely removed and you will not even
get a deprecation message at all. The easiest solution is to adapt your
scripts to use the numpy equivalents as suggested in the messages.
Cheers!
Ben Root
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