Let's see if we can read a generic h5 file using netCDF4

In [1]:

    

%matplotlib inline
import matplotlib.pyplot as plt
import netCDF4


    

In [2]:

    

url='/usgs/data2/rsignell/temp_delta_newer.h5'


    

In [3]:

    

nc = netCDF4.Dataset(url)


    

In [4]:

    

nc.variables.keys()


    

    
Out[4]:





[u'lat', u'lon']

In [5]:

    

lat = nc.variables['lat'][:]
lon = nc.variables['lon'][:]


    

In [6]:

    

g = nc.groups


    

In [7]:

    

g


    

    
Out[7]:





OrderedDict([(u'2020', <type 'netCDF4._netCDF4.Group'>
              group /2020:
                  created: 2015-11-05 11:56:11
                  dimensions(sizes): 
                  variables(dimensions): 
                  groups: 45, 85), (u'2050', <type 'netCDF4._netCDF4.Group'>
              group /2050:
                  created: 2015-11-05 11:56:50
                  dimensions(sizes): 
                  variables(dimensions): 
                  groups: 45, 85), (u'2080', <type 'netCDF4._netCDF4.Group'>
              group /2080:
                  created: 2015-11-05 11:57:32
                  dimensions(sizes): 
                  variables(dimensions): 
                  groups: 45, 85)])

In [8]:

    

g['2020']['45'].variables.keys()


    

    
Out[8]:





[u'10', u'25', u'75', u'90', u'mean']

In [9]:

    

t = g['2020']['45'].variables['10'][:,:]


    

In [10]:

    

print lat.shape,lon.shape,t.shape


    

    




(61, 161) (61, 161) (61, 161)

In [14]:

    

plt.pcolormesh(lon,lat,t)
plt.colorbar();


    

In [ ]: