Re: [Matplotlib-users] Fetching a data slab with NetCDFFile

[Arthur M. G. <am...@ir...>]

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. Some details:

I tried several of the IPCC AR4 models at PCMDI, with results similar to 
what I reported earlier. The time object appears with neither units nor 
a calendar. Looking at the metadata shows this not to be correct, for at 
least the three models I investigated (gfdl_cm2_1, mpi_echam5, 
ncar_ccsm3_0). I believe the inclusion of units and a calendar are 
standard procedure for all of these models, and would probably cause the 
dataset to be flagged if they weren't present. Many users (like 
hundreds) have downloaded and analyzed these files.

The IRI data library (http://iridl.ldeo.columbia.edu/) has a large 
collection of datasets, all available using opendap. But I had problems 
with the ones I tried because the calendars seem all to be given as 
"360", rather than "360_day". (Perhaps someone is cutting corners with 
the typing, I can't say...) I couldn't correct this by setting 
timedata.calendar='360_day' because the files are opened read-only. 
There must be files on this server with differently-defined calendars, 
since the data come from many different sources. I'll have to root 
around some more to turn some up.

Similarly, the time units in 
http://test.opendap.org/opendap/data/nc/data.nc are given simply as 
'hour', so num2date can't figure out what dates the time values refer 
to. I wouldn't have expected this at this URL, but maybe it's a test? 
Aside from the fact that "... since" was missing, netcdf4 also 
complained that 'hour' was not an acceptable unit. Only 'hours' will do. 
(No 'months' or 'years' either, it seems.)

http://test.opendap.org/opendap/data/nc/coads_climatology.nc seems to 
download OK, and there are units, but it's a 12-month climatology, so 
calendar is irrelevant. I could plot the data, although it appeared 
reversed left-to-right. (I didn't add axes, but just plotted it raw.)

The conclusion seems to be that (1) there may be a lot of non-conforming 
datasets out there (and netcdf4 may be a little fussy about what time 
units it will accept, too), but (2) since there seems to be some 
discordance w.r.t. the IPCC data (where we believe the units and 
calendar must actually be present) one cannot be absolutely sure that 
all of the problems experienced are solely due to malformed data 
descriptions. Evidently more detective work will be required to sort 
everything out...

Best, thanks again for the assistance. I've been up too late chasing 
around the web...

Arthur


Jeff Whitaker wrote:
> 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, presumably so 
>> they could be accessed by a variety of applications via OpenDAP. Hmmmm...
>>
>> At any rate, I can access the remote data object with netcdf4, but no 
>> luck retrieving either data or a time index.
>>
>> In [94]: datobj = ncf(fname)
>> In [95]: timedata = datobj.variables['time']
>> In [97]: taxvals = timedata[1070:1090]
>> In [99]: print taxvals
>> [ 32559.5  32590.   32620.5  32651.   32681.5  32712.5  32743.   32773.5
>>   32804.   32834.5  32865.5  32895.   32924.5  32955.   32985.5  33016.
>>   33046.5  33077.5  33108.   33138.5]
>> In [100]: print 
>> date2index(date0,timedata.units,timedata.calendar,select='nearest')
> 
> Arthur:  That's because the timedata variable has no attributes (no 
> calendar or units), and the date2index function looks for these 
> attributes.  That's weird though, since that dataset is supposed to be 
> CF compliant.  I wonder if openDAP is not handling that xml file correctly.
> 
> -Jeff
>> --------------------------------------------------------------------------- 
>>
>> AttributeError                            Traceback (most recent call 
>> last)
>>
>> /home/amg/work/nhmm/<ipython console> in <module>()
>>
>> /home/amg/usr/local/cdat/trunk/lib/python2.5/site-packages/netCDF4.so 
>> in netCDF4.Variable.__getattr__ (netCDF4.c:13593)()
>>
>> /home/amg/usr/local/cdat/trunk/lib/python2.5/site-packages/netCDF4.so 
>> in netCDF4._get_att (netCDF4.c:1806)()
>>
>> AttributeError: NetCDF: Attribute not found
>>
>>
>> In [96]: print datobj.variables['tas'].shape
>> (1680, 90, 144)
>> In [101]: testdat = datobj.variables['tas'][0,:,:]
>> --------------------------------------------------------------------------- 
>>
>> RuntimeError                              Traceback (most recent call 
>> last)
>>
>> /home/amg/work/nhmm/<ipython console> in <module>()
>>
>> /home/amg/usr/local/cdat/trunk/lib/python2.5/site-packages/netCDF4.so 
>> in netCDF4.Variable.__getitem__ (netCDF4.c:14286)()
>>
>> /home/amg/usr/local/cdat/trunk/lib/python2.5/site-packages/netCDF4.so 
>> in netCDF4.Variable._get (netCDF4.c:18945)()
>>
>> RuntimeError: NetCDF: Variable has no data in DAP request
>>
>> --------------------------
>>
>> Well, at least the error messages are different...
>>
>> Thanks again for all the assistance. It would be useful to access the 
>> IPCC output with OpenDap at some point.
>>
>> Best,
>>
>> Arthur
>>
>>
>> Jeff Whitaker wrote:
>>> 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 variable index
>>>> corresponding to a date.
>>>> __init__.py:def date2index(dates, nctime, 
>>>> calendar='proleptic_gregorian'):
>>>> __init__.py:    return netcdftime.date2index(dates, nctime, 
>>>> calendar=None)
>>>> netcdftime.py:def date2index(dates, nctime, calendar=None, 
>>>> select='exact'):
>>>> netcdftime.py:    date2index(dates, nctime, calendar=None, 
>>>> select='exact')
>>>>
>>>> so there seems to be some disagreement between __init__.py and
>>>> netcdftime.py concerning the presence of the "select" argument. When I
>>>> call date2index with the "select" keyword arg I get
>>>>
>>>> In [24]: ix0 = 
>>>> date2index(date0,timedata,timedata.calendar,select='nearest')
>>>> --------------------------------------------------------------------------- 
>>>>
>>>> TypeError                                 Traceback (most recent 
>>>> call last)
>>>>
>>>> /home/amg/work/nhmm/<ipython console> in <module>()
>>>>
>>>> TypeError: date2index() got an unexpected keyword argument 'select'
>>>
>>> Arthur:  I forgot to update the wrapper function in __init__.py - 
>>> that's fixed now if you do an svn update.  Concerning your other 
>>> problems below, using your test case exposed a couple of other bugs, 
>>> but it still doesn't work.  The basic problem is that the date2index 
>>> function was designed to work with netCDF4 variable objects 
>>> (http://code.google.com/p/netcdf4-python), and the netcdf 
>>> file/variable objects that are produced by pupynere/pydap (the pure 
>>> python netcdf /dap reader included in basemap) don't quite behave the 
>>> same way.  Using netCDF4, I can get your gfdl_test.nc case to work with
>>>
>>>  > cat testdate2index.py
>>>
>>> #from mpl_toolkits.basemap import date2index,num2date,NetCDFFile as ncf
>>> from netCDF4 import Dataset as ncf
>>> from netCDF4 import date2index, num2date
>>> from mpl_toolkits import basemap
>>> fname0 = 'http://esgcet.llnl.gov/dap/'
>>> fname1 =\
>>> 'ipcc4/20c3m/gfdl_cm2_1/pcmdi.ipcc4.gfdl_cm2_1.20c3m.run1.atm.mo.xml'
>>> fname = fname0+fname1
>>> #fname = 'gfdl_test.nc'
>>> print fname
>>> datobj = ncf(fname)
>>> print datobj.variables['tas'].shape
>>> timedata = datobj.variables['time']
>>> from datetime import datetime as dt
>>> date0 = dt(1951,1,16,12,0,0)
>>> print num2date(timedata[:],timedata.units,calendar=timedata.calendar)
>>> print date0
>>> nt0 = date2index(date0,timedata,select='nearest')
>>> print nt0
>>> print \
>>> timedata[nt0],num2date(timedata[nt0],timedata.units,calendar=timedata.calendar) 
>>>
>>>
>>>  > python testdate2index.py
>>>
>>> gfdl_test.nc
>>> (13, 31, 29)
>>> [1950-08-16 12:00:00 1950-09-16 00:00:00 1950-10-16 12:00:00
>>> 1950-11-16 00:00:00 1950-12-16 12:00:00 1951-01-16 12:00:00
>>> 1951-02-15 00:00:00 1951-03-16 12:00:00 1951-04-16 00:00:00
>>> 1951-05-16 12:00:00 1951-06-16 00:00:00 1951-07-16 12:00:00
>>> 1951-08-16 12:00:00]
>>> 1951-01-16 12:00:00
>>> 5
>>> [ 32865.5] [1951-01-16 12:00:00]
>>>
>>>
>>> Your original example doesn't work because the URL is not an opendap 
>>> server, it's some kind of CDAT xml file that presumably only CDAT 
>>> understands.
>>>
>>> We will see if we can fix the date2index function included in basemap 
>>> (if not I will remove it), but for now I recommend using 
>>> netcdf4-python.  It's really a much more robust and feature-rich 
>>> solution for netcdf reading and writing.
>>> -Jeff                                                                             
>>>
>>>
>>>
>>>
>>>>
>>>> -----------------------
>>>>
>>>> This detail aside, I am still having difficulty with date2index, but
>>>> annoyingly, I seem to get different error messages with different 
>>>> datasets. I'll illustrate two here, starting with the one I 
>>>> initially posted about. (See note below regarding this data.)
>>>>
>>>> In [3]: from mpl_toolkits.basemap import 
>>>> date2index,num2date,NetCDFFile as ncf
>>>> In [10]: from mpl_toolkits import basemap
>>>> In [11]: print basemap.__version__
>>>> 0.99.5
>>>> In [24]: fname0 = 'http://esgcet.llnl.gov/dap/'
>>>> In [25]: fname1 = 
>>>> 'ipcc4/20c3m/gfdl_cm2_1/pcmdi.ipcc4.gfdl_cm2_1.20c3m.run1.atm.mo.xml'
>>>> In [26]: fname = fname0+fname1
>>>> In [28]: datobj = ncf(fname)
>>>> In [33]: datobj.variables['tas'].shape
>>>> Out[33]: (1680, 90, 144)
>>>> In [34]: timedata = datobj.variables['time']
>>>> In [35]: from datetime import datetime as dt
>>>> In [36]: date0 = dt(1951,1,16,12,0,0)
>>>> In [37]: print date0
>>>> 1951-01-16 12:00:00
>>>> In [38]: nt0 = date2index(date0,timedata)
>>>> --------------------------------------------------------------------------- 
>>>>
>>>> ClientError                               Traceback (most recent 
>>>> call last)
>>>>
>>>> /home/amg/work/nhmm/<ipython console> in <module>()
>>>>
>>>> /home/amg/usr/local/cdat/trunk/lib/python2.5/site-packages/mpl_toolkits/basemap/__init__.pyc 
>>>> in date2index(dates, nctime, calendar)
>>>>    3931     Returns an index or a sequence of indices.
>>>>    3932     """
>>>> -> 3933     return netcdftime.date2index(dates, nctime, calendar=None)
>>>>    3934
>>>>    3935 def maskoceans(lonsin,latsin,datain,inlands=False):
>>>>
>>>> /home/amg/usr/local/cdat/trunk/lib/python2.5/site-packages/mpl_toolkits/basemap/netcdftime.pyc 
>>>> in date2index(dates, nctime, calendar, select)
>>>>    1006     # If the times do not correspond, then it means that the 
>>>> times
>>>>    1007     # are not increasing uniformly and we try the bisection 
>>>> method.
>>>> -> 1008     if not _check_index(index, dates, nctime, calendar):
>>>>    1009
>>>>    1010         # Use the bisection method. Assumes the dates are 
>>>> ordered.
>>>>
>>>> /home/amg/usr/local/cdat/trunk/lib/python2.5/site-packages/mpl_toolkits/basemap/netcdftime.pyc 
>>>> in _check_index(indices, dates, nctime, calendar)
>>>>     959         return False
>>>>     960
>>>> --> 961     t = nctime[indices]
>>>>     962     return numpy.all( num2date(t, nctime.units, calendar) == 
>>>> dates)
>>>>     963
>>>>
>>>> /home/amg/usr/local/cdat/trunk/lib/python2.5/site-packages/mpl_toolkits/basemap/netcdf.pyc 
>>>> in __getitem__(self, index)
>>>>      65
>>>>      66     def __getitem__(self, index):
>>>> ---> 67         datout = squeeze(self._var.__getitem__(index))
>>>>      68         # automatically
>>>>      69         # - remove singleton dimensions
>>>>
>>>> /home/amg/usr/local/cdat/trunk/lib/python2.5/site-packages/dap/dtypes.pyc 
>>>> in __getitem__(self, key)
>>>>     409     def __getitem__(self, key):
>>>>     410         # Return data from the array.
>>>> --> 411         return self.data[key]
>>>>     412
>>>>     413     def __setitem__(self, key, item):
>>>>
>>>> /home/amg/usr/local/cdat/trunk/lib/python2.5/site-packages/dap/proxy.pyc 
>>>> in __getitem__(self, index)
>>>>     112
>>>>     113         # Fetch data.
>>>> --> 114         resp, data = openurl(url, self.cache, self.username, 
>>>> self.password)
>>>>     115
>>>>     116         # First lines are ASCII information that end with 
>>>> 'Data:\n'.
>>>>
>>>> /home/amg/usr/local/cdat/trunk/lib/python2.5/site-packages/dap/util/http.pyc 
>>>> in openurl(url, cache, username, password)
>>>>      19         m = re.search('code = (?P<code>\d+);\s*message = 
>>>> "(?P<msg>.*)"', data, re.DOTALL | re.MULTILINE)
>>>>      20         msg =  'Server error %(code)s: "%(msg)s"' % 
>>>> m.groupdict()
>>>> ---> 21         raise ClientError(msg)
>>>>      22
>>>>      23     return resp, data
>>>>
>>>> ClientError: 'Server error 0: "invalid literal for int(): [1113"'
>>>>
>>>> -----------------------------
>>>>
>>>> Note that this is a different error than previously reported. Also, 
>>>> the correct time index is still 1080:
>>>>
>>>> In [40]: taxvals = datobj.variables['time'][:]
>>>>
>>>> In [41]: num2date(taxvals[1080],timedata.units,timedata.calendar)
>>>> Out[41]: 1951-01-16 12:00:00
>>>>
>>>> -----------------------------
>>>>
>>>> This dataset, generated by one of the IPCC models, is 
>>>> password-protected, but could be a good target for decoding, since 
>>>> it is typical of a large class of climate models, that generate a 
>>>> lot of analytical activity. To get a password (they're free) one 
>>>> must register. Info is here: 
>>>> http://www-pcmdi.llnl.gov/ipcc/info_for_analysts.php. Follow "How to 
>>>> access..." then "Register to download output." Once you get a userid 
>>>> and password they can be inserted in the NetCDFFile call, voila. 
>>>> Note that there is a new iteration of IPCC coming down the pike; new 
>>>> model files to become widely available starting in 2010.
>>>>
>>>> ------------------------------
>>>>
>>>> The underlying data is available via ftp. I fetched it and extracted 
>>>> a small slab, which is available at 
>>>> http://iri.columbia.edu/~amg/test/gfdl_test.nc. The CDAT package can 
>>>> digest this file; first time step is plotted here: 
>>>> http://iri.columbia.edu/~amg/test/gfdl_test_time0.png. The dates can 
>>>> also be read by this package, and run from Aug 1950 to Aug 1951, 
>>>> inclusive (13 mos). So the file does not seem to be garbage.
>>>>
>>>> In [16]: datobj = ncf('gfdl_test.nc')
>>>> In [17]: timedata = datobj.variables['time']
>>>> In [18]: date0 = dt(1951,1,16,12,0,0)
>>>> In [19]: nt0 = date2index(date0,timedata)
>>>> --------------------------------------------------------------------------- 
>>>>
>>>> TypeError                                 Traceback (most recent 
>>>> call last)
>>>>
>>>> /home/amg/work/nhmm/<ipython console> in <module>()
>>>>
>>>> /home/amg/usr/local/cdat/trunk/lib/python2.5/site-packages/mpl_toolkits/basemap/__init__.pyc 
>>>> in date2index(dates, nctime, calendar)
>>>>    3931     Returns an index or a sequence of indices.
>>>>    3932     """
>>>> -> 3933     return netcdftime.date2index(dates, nctime, calendar=None)
>>>>    3934
>>>>    3935 def maskoceans(lonsin,latsin,datain,inlands=False):
>>>>
>>>> /home/amg/usr/local/cdat/trunk/lib/python2.5/site-packages/mpl_toolkits/basemap/netcdftime.pyc 
>>>> in date2index(dates, nctime, calendar, select)
>>>>    1011         import bisect
>>>>    1012
>>>> -> 1013         index = numpy.array([bisect.bisect_left(nctime, n) 
>>>> for n in num], int)
>>>>    1014
>>>>    1015         nomatch = num2date(nctime[index], nctime.units) != 
>>>> dates
>>>>
>>>> TypeError: object of type 'netcdf_variable' has no len()
>>>>
>>>> Investigating the time axis,
>>>>
>>>> In [20]: taxvals = timedata[:]
>>>>
>>>> In [21]: taxvals
>>>> Out[21]: array([ 32712.5,  32743. ,  32773.5,  32804. ,  32834.5, 
>>>> 32865.5, 32895. ,  32924.5,  32955. ,  32985.5,  33016. ,  33046.5, 
>>>> 33077.5])
>>>>
>>>> In [22]: num2date(taxvals,timedata.units,timedata.calendar)
>>>> Out[22]: array([1950-08-16 12:00:00, 1950-09-16 00:00:00, 1950-10-16 
>>>> 12:00:00,
>>>>        1950-11-16 00:00:00, 1950-12-16 12:00:00, 1951-01-16 12:00:00,
>>>>        1951-02-15 00:00:00, 1951-03-16 12:00:00, 1951-04-16 00:00:00,
>>>>        1951-05-16 12:00:00, 1951-06-16 00:00:00, 1951-07-16 12:00:00,
>>>>        1951-08-16 12:00:00], dtype=object)
>>>>
>>>> Which agrees with what CDAT sees.
>>>>
>>>> -------------------------
>>>>
>>>> I think this is enough for now. I also had problems opening data 
>>>> files whose time units were like "months since xxxx-xx-xx," since 
>>>> the "months" unit does not seem to be supported. ("years since..." 
>>>> could also be useful in some cases.) But maybe one or two things at 
>>>> a time is enough!
>>>>
>>>> Thanks for any assistance/advice!
>>>>
>>>> Best,
>>>>
>>>> Arthur
>>>>
>>>>
>>>> Jeff Whitaker wrote:
>>>>> David Huard wrote:
>>>>>> 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', 'after', 'nearest', that should help 
>>>>>> with your use case.
>>>>>>
>>>>>> If this does not fix the problem you are seeing, I'd appreciate 
>>>>>> having a copy of the file and code to reproduce the problem and 
>>>>>> find a solution.
>>>>>>
>>>>>> HTH,
>>>>>>
>>>>>> David Huard
>>>>>
>>>>> Arthur:  I've just updated basemap svn with David's latest version 
>>>>> of date2index, so another option is to update basemap from svn.  
>>>>> Or, even simpler, just drop the attached netcdftime.py file in 
>>>>> lib/mpl_toolkits/basemap (replacing the old one) and run python 
>>>>> setup.py install.
>>>>>
>>>>> -Jeff
>>>>>>
>>>>>>
>>>>>>
>>>>>> On Mon, Sep 7, 2009 at 9:27 AM, Arthur M. Greene 
>>>>>> <am...@ir... <mailto:am...@ir...>> wrote:
>>>>>>
>>>>>>     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].
>>>>>>
>>>>>>     However, I have problems when trying to use the syntax in
>>>>>>     plotsst.py or
>>>>>>     pnganim.py (from the examples) to find time indices:
>>>>>>
>>>>>>     In [107]: from datetime import datetime as dt
>>>>>>     In [108]: date0 = dt(1951,1,1,0)
>>>>>>     In [110]: print date0
>>>>>>     1951-01-01 00:00:00
>>>>>>
>>>>>>     In [125]: timedata = remoteobj.variables['time']
>>>>>>     In [126]: nt0 = date2index(date0,timedata)
>>>>>>     
>>>>>> --------------------------------------------------------------------------- 
>>>>>>
>>>>>>     AssertionError                            Traceback (most recent
>>>>>>     call last)
>>>>>>
>>>>>>     /home/amg/work/nhmm/<ipython console> in <module>()
>>>>>>
>>>>>>     
>>>>>> /usr/local/cdat/trunk/lib/python2.5/site-packages/mpl_toolkits/basemap/__init__.pyc 
>>>>>>
>>>>>>
>>>>>>     in date2index(dates, nctime, calendar)
>>>>>>        3924     Returns an index or a sequence of indices.
>>>>>>        3925     """
>>>>>>     -> 3926     return netcdftime.date2index(dates, nctime, 
>>>>>> calendar=None)
>>>>>>        3927
>>>>>>        3928 def maskoceans(lonsin,latsin,datain,inlands=False):
>>>>>>
>>>>>>     
>>>>>> /usr/local/cdat/trunk/lib/python2.5/site-packages/mpl_toolkits/basemap/netcdftime.pyc 
>>>>>>
>>>>>>
>>>>>>     in date2index(dates, nctime, calendar)
>>>>>>         986
>>>>>>         987         # Perform check again.
>>>>>>     --> 988         _check_index(index, dates, nctime, calendar)
>>>>>>         989
>>>>>>         990     # convert numpy scalars or single element arrays 
>>>>>> to python
>>>>>>     ints.
>>>>>>
>>>>>>     
>>>>>> /usr/local/cdat/trunk/lib/python2.5/site-packages/mpl_toolkits/basemap/netcdftime.pyc 
>>>>>>
>>>>>>
>>>>>>     in _check_index(indices, dates, nctime, calendar)
>>>>>>         941     for n,i in enumerate(indices):
>>>>>>         942         t[n] = nctime[i]
>>>>>>     --> 943     assert numpy.all( num2date(t, nctime.units, calendar)
>>>>>>     == dates)
>>>>>>         944
>>>>>>         945
>>>>>>
>>>>>>     AssertionError:
>>>>>>
>>>>>>     ---------------------------------------------------------
>>>>>>
>>>>>>     It turns out that date0 corresponds best to index 1080:
>>>>>>
>>>>>>     In [139]: remoteobj.variables['time'][1080]
>>>>>>     Out[139]: 32865.5
>>>>>>
>>>>>>     In [141]: num2date(32865.5,timedata.units,timedata.calendar)
>>>>>>     Out[141]: 1951-01-16 12:00:00
>>>>>>
>>>>>>     This isn't the _exact_ date and time I had specified, but
>>>>>>
>>>>>>     In [142]: date0 = dt(1951,01,16,12,00,00)
>>>>>>     In [143]: print date0
>>>>>>     1951-01-16 12:00:00
>>>>>>
>>>>>>     In [144]: date2index(date0,timedata,timedata.calendar)
>>>>>>
>>>>>>     produces the same AssertionError. Where is the problem?
>>>>>>
>>>>>>     What I would _like_ to do is to issue a simple call using 
>>>>>> coordinates
>>>>>>     rather than the indices, of the form:
>>>>>>
>>>>>>     slice = variable[date0:date1,[plev],lat0:lat1,lon0:lon1],
>>>>>>
>>>>>>     or similar, preferably without writing a whole module just to 
>>>>>> find the
>>>>>>     correct indices. I need to fetch similar slices from a group of
>>>>>>     models,
>>>>>>     having time axes that may each be defined slightly differently --
>>>>>>     different calendars, time point set at a different day of the 
>>>>>> month,
>>>>>>     etc. (It's monthly data and I'm specifying only monthly 
>>>>>> bounds, even
>>>>>>     though the calendar may be defined as "days since 1860...") I 
>>>>>> need to
>>>>>>     automate the process so I get back the correct slab regardless.
>>>>>>
>>>>>>     Suggestions appreciated!
>>>>>>
>>>>>>     Thx,
>>>>>>
>>>>>>     Arthur
>>>>>>
>>>>>>
>>>>>>     *^*~*^*~*^*~*^*~*^*~*^*~*^*~*^*~*^*~*^*~*^*~*^*~*^*~*^*~*^*~*
>>>>>>     Arthur M. Greene, Ph.D.
>>>>>>     The International Research Institute for Climate and Society 
>>>>>> (IRI)
>>>>>>     The Earth Institute, Columbia University, Lamont Campus
>>>>>>
>>>>>>     amg at iri dot columbia dot edu | http://iri.columbia.edu
>>>>>>     *^*~*^*~*^*~*^*~*^*~*^*~*^*~*^*~*^*~*^*~*^*~*^*~*^*~*^*~*^*~*
>>>>>>
>>>>>>
>>>>>>     
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>>>>>>
>>>>>>
>>>>>> _______________________________________________
>>>>>> Matplotlib-users mailing list
>>>>>> Mat...@li...
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>>>>>>   
>>>>
>>>
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>>
> 
> 

-- 
*^*~*^*~*^*~*^*~*^*~*^*~*^*~*^*~*^*~*^*~*^*~*^*~*^*~*^*~*^*~*
Arthur M. Greene, Ph.D.
The International Research Institute for Climate and Society (IRI)
The Earth Institute, Columbia University, Lamont Campus
Monell Building, 61 Route 9W, Palisades, NY  10964-8000 USA
amg at iri dot columbia dot edu   | http://iri.columbia.edu
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