In [3]:

    

import numpy as np
import os
import matplotlib.pylab as plt


    

In [4]:

    

%matplotlib


    

    




Using matplotlib backend: MacOSX

In [5]:

    

path = '/Volumes/wjlee_apl_3/ooi_eao_buoy/'
file = 'eao_buoy_solar_radiation_20170831download.txt'


    

In [136]:

    

f = open(os.path.join(path,file), 'rU')


    

In [137]:

    

header1 = f.readline().split()
header2 = f.readline().split()
data_block = f.readlines()


    

In [138]:

    

header1


    

    
Out[138]:





['#YY', 'MM', 'DD', 'hh', 'mm', 'SRAD1', 'SWRAD', 'LWRAD']

In [139]:

    

header2


    

    
Out[139]:





['#yr', 'mo', 'dy', 'hr', 'mn', 'w/m2', 'w/m2', 'w/m2']

In [140]:

    

data = {}
for col_name in header1:
    data[col_name] = np.ma.zeros(len(data_block), 'f', fill_value = -999.999)


    

In [141]:

    

data


    

    
Out[141]:





{'#YY': masked_array(data = [ 0.  0.  0. ...,  0.  0.  0.],
              mask = False,
        fill_value = -999.999),
 'DD': masked_array(data = [ 0.  0.  0. ...,  0.  0.  0.],
              mask = False,
        fill_value = -999.999),
 'LWRAD': masked_array(data = [ 0.  0.  0. ...,  0.  0.  0.],
              mask = False,
        fill_value = -999.999),
 'MM': masked_array(data = [ 0.  0.  0. ...,  0.  0.  0.],
              mask = False,
        fill_value = -999.999),
 'SRAD1': masked_array(data = [ 0.  0.  0. ...,  0.  0.  0.],
              mask = False,
        fill_value = -999.999),
 'SWRAD': masked_array(data = [ 0.  0.  0. ...,  0.  0.  0.],
              mask = False,
        fill_value = -999.999),
 'hh': masked_array(data = [ 0.  0.  0. ...,  0.  0.  0.],
              mask = False,
        fill_value = -999.999),
 'mm': masked_array(data = [ 0.  0.  0. ...,  0.  0.  0.],
              mask = False,
        fill_value = -999.999)}

In [172]:

    

for (line_count, line) in enumerate(data_block):
    items = line.split()
    
    for (col_count, col_name) in enumerate(col_names1):
        if col_count!=6:
            value = items[col_count]
            if value == "MM":
                 value = np.ma.masked
            else:
                 value = float(value)
            data[col_name][line_count] = value


    

In [174]:

    

plt.plot(data['SRAD1'])


    

    
Out[174]:





[<matplotlib.lines.Line2D at 0x1139f6550>]

In [135]:

    

f.close()


    

In [ ]:

    




    

In [6]:

    

import read_srad


    

In [7]:

    

data_unpack = read_srad.read_srad_file(os.path.join(path,file))


    

In [8]:

    

plt.plot(data_unpack['SRAD1'])


    

    
Out[8]:





[<matplotlib.lines.Line2D at 0x1127e4e10>]

In [ ]: