OPeNDAP dataset¶

In [1]:

import netCDF4
import numpy as np

In [2]:

def start_stop(url,tvar):
    nc = netCDF4.Dataset(url)
    ncv = nc.variables
    time_var = ncv[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 [3]:

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 16:00

In [4]:

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

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

Calculate the average time step

In [5]:

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

1.00136131061

So we have time steps of about 1 hour

Now calculate the unique time steps

In [6]:

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