Trajectory Test

In [13]:

    

%matplotlib inline
import matplotlib.pyplot as plt
import numpy.ma as ma
import numpy as np
import netCDF4
import gridded


    

In [14]:

    

url = 'http://geoport.whoi.edu/thredds/dodsC/examples/bora_feb.nc'


    

In [15]:

    

nc = netCDF4.Dataset(url)
lon = nc['lon_rho'][:]
lat = nc['lat_rho'][:]
temp = nc['temp'][-1,-1,:,:]


    

In [16]:

    

x = np.linspace(13., 15.)
y = np.linspace(45.3, 43.5)
len(x)


    

    
Out[16]:





50

In [22]:

    

fig = plt.figure(figsize=(6, 5), dpi=100)
plt.pcolormesh(lon,lat,ma.masked_invalid(temp),vmin=5,vmax=15,cmap='jet');
plt.plot(x,y,'-')
plt.grid()
plt.colorbar();


    

In [18]:

    

#Create temperature Variable from the file
temperature = gridded.Variable.from_netCDF(filename=url, name='Temperature', varname='temp')

#Create salinity Variable from the file, and sharing the same grid as temperature
salinity = gridded.Variable.from_netCDF(filename=url, name='Salinity', varname='salt', grid=temperature.grid)

points = np.column_stack((x,y))
t0 = temperature.time.max_time


    

In [19]:

    

salts = salinity.at(points, t0)


    

In [20]:

    

temps = temperature.at(points, t0)


    

In [9]:

    

plt.plot(temps)


    

    
Out[9]:





[<matplotlib.lines.Line2D at 0xdc1d978>]






    

In [10]:

    

times = temperature.time.data
len(times)


    

    
Out[10]:





8

In [11]:

    

over_time = [temperature.at((x[0],y[0]), t) for i,t in enumerate(times)]


    

In [12]:

    

plt.plot(over_time)


    

    
Out[12]:





[<matplotlib.lines.Line2D at 0xf0ec048>]






    

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