netCDF4-Python Plotting variables

Question

I would like to plot a selection of variables from a netCDF file using netCDF4-Python.I am using the following code:

import numpy as np
import pandas as pd
from pylab import *
from netCDF4 import Dataset
pals = Dataset('pals_amplero_2003_2006_ecmwf_v1.nc4', "a",format='NETCDF4')
print (pals.variables.keys())
print (pals.variables['Rainf'])
print (pals.variables['Evap'])
print (pals.variables['time'])
evap = pals.variables['Evap'][:,:]
rain = pals.variables['Rainf'][:,:]
subplot(2,1,1)
pcolor(evap)
subplot(2,1,2)
pcolor(rain)

Unfortunately, it outputs an error message (more detailed in the enclosed document):

ValueError: too many values to unpack (expected 2)

For info the following is the output of the print commands

odict_keys(['DelIntercept', 'DelSWE', 'DelSoilMoist', 'Evap', 'Qs', 'Qsb',      'Qsm', 'Rainf', 'Snowf', 'lat', 'lon', 'nlevs', 'time', 'timestp', 'M_fieldcap', 'M_sat', 'M_wilt', 'SoilDepth', 'CanopInt', 'Conds', 'ECanop', 'ESoil', 'RootMoist', 'SubSnow', 'TVeg', 'DelColdCont', 'DelSoilHeat', 'LWnet', 'LWup', 'Qf', 'Qg', 'Qh', 'Qle', 'SWnet', 'Fdepth', 'HFLUXRF', 'IceFrac', 'MFLUXRF', 'SAlbedo', 'SnowDepth', 'SnowFrac', 'Tdepth', 'WSN', 'AvgSurfT', 'HLICE', 'HLML', 'SWE', 'SnowT', 'SoilMoist', 'SoilTemp', 'TLBOT', 'TLICE', 'TLMNW', 'TLSF', 'TLWML', 'icetemp', 'snowdens', 'Albedo', 'BaresoilT', 'RH2m', 'RadT', 'T2m', 'VegT', 'Bgain', 'Biomstr', 'Biomstr2', 'Bloss', 'biomass', 'lai', 'Ag', 'An', 'CO2flux', 'Rd', 'Reco', 'Rsoil_str'])
<class 'netCDF4._netCDF4.Variable'>
float32 Rainf(time, y, x)
units: mm/day
long_name: Rainfall rate
associate: time y x
missing_value: 1e+20
time_representation: average over past model timestep
unlimited dimensions: time
current shape = (70084, 1, 1)
filling on, default _FillValue of 9.969209968386869e+36 used

<class 'netCDF4._netCDF4.Variable'>
float32 Evap(time, y, x)
units: mm/day
long_name: Total evapotranspiration
associate: time y x
missing_value: 1e+20
time_representation: average over past model timestep
unlimited dimensions: time
current shape = (70084, 1, 1)
filling on, default _FillValue of 9.969209968386869e+36 used

<class 'netCDF4._netCDF4.Variable'>
float64 time(time)
units: seconds since 2003-01-01 00:00:00
long_name: Time in seconds
Time_label: Start of output interval
unlimited dimensions: time
current shape = (70084,)
filling on, default _FillValue of 9.969209968386869e+36 used

You don't show where/how your read prec. Normally your code should work; e.g. evap has a three dimensional shape in the NetCDF file, but you slice ([:,:]) the first two dimensions out of it, so this should work with pcolor. Could be that prec has more than two dimensions. — Bart
– Bart, Commented Nov 17, 2017 at 5:46
Thank you for your answer! Actually, you pointed out an error in my code there is no variable "prec". There is only "evap" and "rain" and both of them have 3 dimensions that I slice using [:,:] I just don't understand the error! — steve
– steve, Commented Nov 17, 2017 at 14:25
Me neither. Can you add the full error message (at least including which line causes the error)? — Bart
– Bart, Commented Nov 18, 2017 at 7:50
Ok! I re-edit my question now with the full error message. Thank you! — steve
– steve, Commented Nov 20, 2017 at 15:11

Bart · Accepted Answer · 2017-11-20 17:03:26Z

1

Finally see the problem. Take this example (a random NetCDF file):

ncdump -h th.xz.nc

Gives (amongst other things):

float th(time, z, x, y) ;

So the variable th has 4 dimensions. If you read/plot this in a similar way as in your code:

import netCDF4 as nc4
import matplotlib.pylab as pl

nc = nc4.Dataset('th.xz.nc')
th = nc.variables['th'][:,:]

pl.figure()
pl.pcolor(th)

It gives the same error:

ValueError: too many values to unpack (expected 2)

Why? The slicing with [:,:] (or [:], or [:,:,:]) will still give you more than two dimensions:

print(th.shape)

(9, 32, 32, 1)

while pcolor expects a two-dimensional array. The solution is simple; you need to select which 2D slice you want to show, for example pcolor(evap[0,:,:]) (x-y slice) or pcolor(evap[:,0,:]) (time-x slice), or ...

answered Nov 20, 2017 at 17:03

Bart

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