Check the start/stop time of a netcdf/OPeNDAP dataset



In [9]:

    
import netCDF4
import numpy as np



In [10]:

    
def start_stop(url,tvar):
    nc = netCDF4.Dataset(url)
    time_var = nc[tvar]
    first = netCDF4.num2date(time_var[0],time_var.units)
    last = netCDF4.num2date(time_var[-1],time_var.units)

    print(first.strftime('%Y-%b-%d %H:%M'))
    print(last.strftime('%Y-%b-%d %H:%M'))



In [11]:

    
url='http://hfrnet.ucsd.edu/thredds/dodsC/HFR/USWC/6km/hourly/RTV/HFRADAR,_US_West_Coast,_6km_Resolution,_Hourly_RTV_best.ncd'
tvar='time'
start_stop(url,tvar)









    



2011-Oct-01 00:00
2016-Aug-12 19:00



In [12]:

    
nc = netCDF4.Dataset(url)
t = nc[tvar][:]
print(nc[tvar].units)









    



hours since 2011-10-01T00:00:00Z

Calculate the average time step



In [13]:

    
print np.mean(np.diff(t))









    



1.00136121477

So we have time steps of about 1 hour

Now calculate the unique time steps



In [14]:

    
print(np.unique(np.diff(t)).data)









    



[  1.   2.   3.   6.   9.  10.  14.  19.]

So there are gaps of 2, 3, 6, 9, 10, 14 and 19 hours in the otherwise hourly data



In [15]:

    
nc['time'][:]









    Out[15]:





masked_array(data = [0.0 1.0 2.0 ..., 42665.0 42666.0 42667.0],
             mask = [False False False ..., False False False],
       fill_value = nan)



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