Matplotlib/Cartopy：pcolormesh 错误：ValueError：要解包的值太多（预期为 3）答案

【问题标题】：Matplotlib/Cartopy: pcolormesh error: ValueError: too many values to unpack (expected 3)Matplotlib/Cartopy：pcolormesh 错误：ValueError：要解包的值太多（预期为 3）
【发布时间】：2021-06-14 14:08:09
【问题描述】：

我在绘图时遇到问题，尝试使用 pcolormesh 通过 matplotlib/cartopy 绘制纬度/经度数据。

我有下面的代码块和错误。我似乎无法理解特定错误的来源：pcolormesh 函数发现太多需要解包的值。

Python3.8、Matplotlib 3.4.2、Cartopy 0.17

我仍在学习这个过程......但这看起来应该很简单，但我似乎无法解决这个错误。任何帮助将不胜感激！

import matplotlib.pyplot as plt
import xarray as xr
import numpy as np
import cartopy.crs as ccrs
import cartopy.feature as cfeat
from cartopy.feature import ShapelyFeature
import cartopy
import geopandas as gpd
import matplotlib.ticker as mticker
from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER
import cmocean as cm

##Open weather data file (grib2 format) via xarray, select data from proper level
ds = xr.open_dataset('/fewxops/Tom/learn_python/data/grib2/gfs.t00z.pgrb2.0p25.f024', engine='cfgrib', filter_by_keys={'typeOfLevel': 'isobaricInhPa'})
##Select individual level (from designated 'type of level')
ds_z500=ds.sel(isobaricInhPa=500)
##Select temperature variable from specific level
t500 = ds_z500['t']
lats = ds_z500['latitude']
lons = ds_z500['longitude']
latdata = lats.values
londata = lons.values
data = t500.values

fig = plt.figure(figsize=(10,10))
ax = fig.add_subplot(1,1,1, projection=ccrs.PlateCarree())

ax.pcolormesh(londata, latdata, data, transform=ccrs.PlateCarree(), cmap=cm.cm.thermal, vmin=250, vmax=330)
##This contourf function works fine.
##ax.contourf(ds_z500['longitude'], ds_z500['latitude'], ds_z500['t'], transform=ccrs.PlateCarree())

ax.add_feature(cfeat.COASTLINE.with_scale('50m'),edgecolor='black')
ax.add_feature(cfeat.LAKES.with_scale('50m'), edgecolor='black',facecolor='none')
ax.add_feature(cfeat.BORDERS.with_scale('50m'),edgecolor='black')

plt.savefig('test_grib_colormesh.png')

***************************************************************
/home/fewx/anaconda3/lib/python3.8/site-packages/cartopy/mpl/geoaxes.py:1491: MatplotlibDeprecationWarning: shading='flat' when X and Y have the same dimensions as C is deprecated since 3.3.  Either specify the corners of the quadrilaterals with X and Y, or pass shading='auto', 'nearest' or 'gouraud', or set rcParams['pcolor.shading'].  This will become an error two minor releases later.
  X, Y, C = self._pcolorargs('pcolormesh', *args, allmatch=allmatch)
Traceback (most recent call last):
  File "work_with_grib_data.py", line 132, in <module>
    ax.pcolormesh(londata, latdata, data, transform=ccrs.PlateCarree(), cmap=cm.cm.thermal, vmin=250, vmax=330)
  File "/home/fewx/anaconda3/lib/python3.8/site-packages/cartopy/mpl/geoaxes.py", line 1459, in pcolormesh
    result = self._pcolormesh_patched(*args, **kwargs)
  File "/home/fewx/anaconda3/lib/python3.8/site-packages/cartopy/mpl/geoaxes.py", line 1491, in _pcolormesh_patched
    X, Y, C = self._pcolorargs('pcolormesh', *args, allmatch=allmatch)
ValueError: too many values to unpack (expected 3)

【问题讨论】：

data的形状是什么？如果它不是 2-D pcolormesh 将不起作用
我曾认为这也是一个问题，这就是为什么我对从文件中提取的数据如此明确的原因。但是快速打印出 londata、latdata 和 data 的形状，可以发现它们分别是 (1440,)、(721,) 和 (1440,721)。所以看起来数据数组是二维的，我很难过！
尝试X,Y=np.meshgrid(londata, latdata) 然后ax.pcolormesh(X,Y,data, ...)。

标签： python matplotlib cartopy

【解决方案1】：

这与以下问题相同：Plotting with matplotlib/cartopy: ValueError: too many values to unpack (expected 3)

这是 cartopy 0.17 版和 matplotlib >3.3 的问题。这在 cartopy 版本 0.19 中已修复，因此只需更新即可。

【讨论】：