netCDF4-Python 绘制变量

Question

我想使用 netCDF4 绘制 netCDF 文件中的变量选择-Python.I 我正在使用以下代码：

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)

不幸的是，它输出了一条错误消息（更多详细信息在随附的文档中）：

ValueError: too many values to unpack (expected 2)

有关信息，以下是打印命令的输出

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

Answer 1

终于看到问题了。以这个例子（一个随机的 NetCDF 文件）为例：

ncdump -h th.xz.nc

给予（除其他外）：

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

所以变量 th 有 4 个维度。如果您 read/plot 使用与您的代码类似的方式：

import netCDF4 as nc4
import matplotlib.pylab as pl

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

pl.figure()
pl.pcolor(th)

它给出了同样的错误：

ValueError: too many values to unpack (expected 2)

为什么？使用[:,:]（或[:]，或[:,:,:]）的切片仍然会给你两个以上的维度：

print(th.shape)

(9, 32, 32, 1)

而 pcolor 需要一个二维数组。解决方法很简单；您需要 select 您想要显示的 2D 切片，例如 pcolor(evap[0,:,:])（x-y 切片）或 pcolor(evap[:,0,:])（time-x 切片），或 ...

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