Arthur M. Greene wrote:
> Just to add a little info:
>
> I've been poking around various OPeNDAP servers looking for files to
> try and open (and read), and have had a little success, so the module
> does seem to work, if not all the time for my purposes. At the moment
> I'm on a 64-bit machine
Just to add a little info:
I've been poking around various OPeNDAP servers looking for files to try
and open (and read), and have had a little success, so the module does
seem to work, if not all the time for my purposes. At the moment I'm on
a 64-bit machine (Fedora 10), so this is encouraging
Arthur M. Greene wrote:
> Thanks much. I am able to replicate your results using netcdf4.
>
> FYI, I don't believe the xml file is a CDAT creation; rather, it is
> probably written using CMOR (http://www2-pcmdi.llnl.gov/cmor), which
> was used to standardize the IPCC model output files, presumabl
Thanks much. I am able to replicate your results using netcdf4.
FYI, I don't believe the xml file is a CDAT creation; rather, it is
probably written using CMOR (http://www2-pcmdi.llnl.gov/cmor), which was
used to standardize the IPCC model output files, presumably so they
could be accessed by
Arthur M. Greene wrote:
> Thanks much for the quick response. I updated both matplotlib and
> basemap (now at 0.99.5) via svn and noticed the new netcdftime.py.
> First, from within site-packages/mpl_toolkits/basemap,
>
> $ grep date2index *.py
> __init__.py::func:`date2index`: compute a time vari
Thanks much for the quick response. I updated both matplotlib and
basemap (now at 0.99.5) via svn and noticed the new netcdftime.py.
First, from within site-packages/mpl_toolkits/basemap,
$ grep date2index *.py
__init__.py::func:`date2index`: compute a time variable index
corresponding to a dat
Arthur,
I wrote the date2index function and I think what you are seeing is a bug
that I fixed a couple of months ago. By using the latest version of
netcdf4-python, not only should this bug disappear, but you'll also find
that date2index now supports different selection methods: 'exact', 'before',
Hi All,
The problem is not with fetching the data slice itself, but finding the
correct indices to specify, particularly with the time dimension. The
below examples refer to a remote dataset that I can open and slice using
indices, as in
slice = remoteobj.variables['tas'][:120,20:40,30:50].
H
