In [1]:

    

import netCDF4
url='http://geoport.whoi.edu/thredds/dodsC/usgs/data2/emontgomery/stellwagen/Data/ARGO_MERCHANT/1211TR-A1H.cdf'
nc=netCDF4.Dataset(url)


    

In [5]:

    

print ncv.keys()
ncv=nc.variables


    

    




[u'time', u'time2', u'depth', u'lat', u'lon', u'T_20', u'rtrn_4012', u'V00_1900', u'NEP_56', u'V01_1901']

In [8]:

    

nc.summary


    

    
Out[8]:





u"1211TR-A1H     start time = 28 Dec 1976  16:29:59  cycles = 1279\n               stop  time = 19 Feb 1977  22:29:59  # days = 53\nExpt. = 'USGS'  sampling interval = 60.00 minutes\nLat =  40.901112\nLon = -69.176666  File created:  22:51 JUN 29,'83\ndepth = 69m  Mag.var = -16.000000\n#  Variable     Units        Codes Depth   Inst.   Minimum   Maximum\n-- ------------ ------------ ----- ------- ------ --------- ---------\n 1 TIME         SECONDS      T     \n 2 TEMPERATURE  DEGREES      R       69.00            3.753     7.057\n 3 TRANSON      VOLTS        R       69.00 NT-1       1.449     2.184\n 4 TRANSOFF     VOLTS        R       69.00 NT-1       0.000     0.001\n 5 NEPHON       VOLTS        R       69.00 NT-1       0.695     1.178\n 6 NEPHOFF      VOLTS        R       69.00 NT-1       1.005     1.230\n---------------------------------------------------------------------\n Comments:                                                      REDUCE\n G.B. G; ARGO MERCHANT.  TRANSMISSION ONLY.  FROM 1211TR-A.\n VARIABLES LISTED IN ORDER SHOWN ABOVE\n"

In [11]:

    

u=ncv['rtrn_4012'][:].flatten()


    

In [12]:

    

plot(u)


    

    
Out[12]:





[<matplotlib.lines.Line2D at 0x7f3709a2da10>]






    

In [15]:

    

url='http://geoport.whoi.edu/thredds/dodsC/usgs/data2/emontgomery/stellwagen/Data/ARGO_MERCHANT/1211P-A1H.cdf'
nc = netCDF4.Dataset(url)
ncv = nc.variables


    

In [16]:

    

ncv.keys()


    

    
Out[16]:





[u'time', u'time2', u'depth', u'lat', u'lon', u'P_4022', u'P_4023', u'SDP_850']

In [17]:

    

p = ncv['SDP_850'][:].flatten()


    

In [18]:

    

plot(p)


    

    
Out[18]:





[<matplotlib.lines.Line2D at 0x7f370993ee90>]






    

In [19]:

    

p = ncv['P_4022'][:].flatten()
plot(p)


    

    
Out[19]:





[<matplotlib.lines.Line2D at 0x7f37098b1050>]






    

In [ ]: