import netCDF4

nc = netCDF4.Dataset('../data/pottmp.2014.1time.nc')

nc.variables.keys()

pottmp = nc.variables['pottmp']

pottmp.units

pottmp.long_name

pottmp.shape

pottmp.dimensions

data = pottmp[0,0]
data.shape

import matplotlib.pyplot as plt

# These two lines are needed to make matplotlib plot figures inline and at a decent size.
# They are not needed in scripts.
%matplotlib inline
plt.rcParams['figure.figsize'] = (12.0, 8.0)

# These lines do the actual plotting
plt.contourf(data, 20)
plt.show()

lon = nc.variables['lon']
lat = nc.variables['lat']

lonvals = lon[:]
latvals = lat[:]

plt.title (pottmp.long_name + ' (' + pottmp.units + ')')
plt.xlabel(lon.long_name    + ' (' + lon.units    + ')')
plt.ylabel(lat.long_name    + ' (' + lat.units    + ')')
plt.contourf(lonvals, latvals, data, 20, cmap=plt.get_cmap('YlGnBu_r'))
plt.colorbar()
plt.show()

profile = pottmp[0,:,214,180]

depthvar = nc.variables['level']
depthvals = depthvar[:]

plt.plot(depthvals, profile)
plt.xlabel(depthvar.long_name + ' (' + depthvar.units + ')')
plt.ylabel(pottmp.long_name   + ' (' + pottmp.units   + ')')
plt.title('Vertical profile: first attempt')
plt.show()

plt.plot(profile, depthvals)
plt.xlabel(pottmp.long_name   + ' (' + pottmp.units   + ')')
plt.ylabel(depthvar.long_name + ' (' + depthvar.units + ')')

plt.gca().invert_yaxis() # Gets the axes of the plot and reverses the y axis

plt.title('Vertical profile: this is better')
plt.show()