In [1]:

    

from netCDF4 import Dataset


    

In [2]:

    

%cd /projects/CHARIS/snow_cover/MODSCAG_GF/v05/h24v05/
%ls -las


    

    




/projects/CHARIS/snow_cover/MODSCAG_GF/v05/h24v05
total 5322384
    45 drwxr-sr-x 2 nobody 4294967294        16 Mar 30 14:07 ./
     3 drwxr-sr-x 4 nobody 4294967294         4 Mar  8 17:07 ../
337426 -rw-r--r-- 1 nobody 4294967294 344501785 Mar 30 13:50 MODSCAG_GF_Snow.v0.5.h24v05_2001.h5
403690 -rw-r--r-- 1 nobody 4294967294 412133737 Mar 30 13:51 MODSCAG_GF_Snow.v0.5.h24v05_2002.h5
371059 -rw-r--r-- 1 nobody 4294967294 378811829 Mar 30 13:52 MODSCAG_GF_Snow.v0.5.h24v05_2003.h5
348462 -rw-r--r-- 1 nobody 4294967294 355741823 Mar 30 13:54 MODSCAG_GF_Snow.v0.5.h24v05_2004.h5
405916 -rw-r--r-- 1 nobody 4294967294 414430511 Mar 30 13:55 MODSCAG_GF_Snow.v0.5.h24v05_2005.h5
393596 -rw-r--r-- 1 nobody 4294967294 401860301 Mar 30 13:56 MODSCAG_GF_Snow.v0.5.h24v05_2006.h5
353573 -rw-r--r-- 1 nobody 4294967294 360980860 Mar 30 13:58 MODSCAG_GF_Snow.v0.5.h24v05_2007.h5
420902 -rw-r--r-- 1 nobody 4294967294 429685070 Mar 30 13:59 MODSCAG_GF_Snow.v0.5.h24v05_2008.h5
392703 -rw-r--r-- 1 nobody 4294967294 400958225 Mar 30 14:00 MODSCAG_GF_Snow.v0.5.h24v05_2009.h5
369144 -rw-r--r-- 1 nobody 4294967294 376867228 Mar 30 14:02 MODSCAG_GF_Snow.v0.5.h24v05_2010.h5
374736 -rw-r--r-- 1 nobody 4294967294 382609460 Mar 30 14:03 MODSCAG_GF_Snow.v0.5.h24v05_2011.h5
411146 -rw-r--r-- 1 nobody 4294967294 419729917 Mar 30 14:04 MODSCAG_GF_Snow.v0.5.h24v05_2012.h5
373576 -rw-r--r-- 1 nobody 4294967294 381424553 Mar 30 14:06 MODSCAG_GF_Snow.v0.5.h24v05_2013.h5
366411 -rw-r--r-- 1 nobody 4294967294 374060342 Mar 30 14:07 MODSCAG_GF_Snow.v0.5.h24v05_2014.h5

In [3]:

    

filename = "MODSCAG_GF_Snow.v0.5.h24v05_2001.h5"
f = Dataset(filename, 'r', 'NETCDF4')
f


    

    
Out[3]:





<type 'netCDF4._netCDF4.Dataset'>
root group (NETCDF4 data model, file format HDF5):
    dimensions(sizes): 
    variables(dimensions): 
    groups: 500m

In [4]:

    

d = f.groups['500m'].variables['fsca']
d


    

    
Out[4]:





<type 'netCDF4._netCDF4.Variable'>
uint8 fsca(phony_dim_0, phony_dim_1, phony_dim_1)
    packing_convention: netCDF
    packing_convention_description: unpacked = scale_factor*packed + add_offset
    scale_factor: 0.01
    add_offset: 0.0
path = /500m
unlimited dimensions: 
current shape = (365, 2400, 2400)
filling off

In [5]:

    

d.__dict__


    

    
Out[5]:





OrderedDict([(u'packing_convention', u'netCDF'),
             (u'packing_convention_description',
              u'unpacked = scale_factor*packed + add_offset'),
             (u'scale_factor', 0.0099999998),
             (u'add_offset', 0.0)])

In [6]:

    

d.add_offset


    

    
Out[6]:





0.0

In [7]:

    

d.scale_factor


    

    
Out[7]:





0.0099999998

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d.bogus


    

In [ ]:

    

f.close()


    

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