我正在尝试计算 MetPy 中多个（连续）垂直水平的涡度。当我尝试计算单个级别时，一切正常。
这是代码；我使用了来自https://unidata.github.io/MetPy/latest/examples/cross_section.html#sphx-glr-examples-cross-section-py的横截面示例。
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import matplotlib.pyplot as plt
import numpy as np
import xarray as xr
import metpy.calc as mpcalc
from metpy.cbook import get_test_data
from metpy.interpolate import cross_section
from metpy.units import units
data = xr.open_dataset(get_test_data('narr_example.nc', False))
data = data.metpy.parse_cf().squeeze()
data_crs = data['Temperature'].metpy.cartopy_crs
lat = data['lat']
lon = data['lon']
f = mpcalc.coriolis_parameter(lat)
dx, dy = mpcalc.lat_lon_grid_deltas(lon, lat, initstring=data_crs.proj4_init)
然后进行涡度计算。
vort = mpcalc.vorticity(data['u_wind'], data['v_wind'], dx, dy)
追溯：
Traceback (most recent call last):
File "E:\Временные файлы\cross_section (1).py", line 63, in <module>
vort = mpcalc.vorticity(data['u_wind'], data['v_wind'], dx, dy)
File "C:\ProgramData\Miniconda3\lib\site-packages\metpy\xarray.py", line 436, in wrapper
return func(*args, **kwargs)
File "C:\ProgramData\Miniconda3\lib\site-packages\metpy\calc\kinematics.py", line 60, in wrapper
ret = func(*args, **kwargs)
File "C:\ProgramData\Miniconda3\lib\site-packages\metpy\calc\kinematics.py", line 121, in vorticity
dudy = first_derivative(u, delta=dy, axis=-2)
File "C:\ProgramData\Miniconda3\lib\site-packages\metpy\calc\tools.py", line 920, in wrapper
return preprocess_xarray(func)(f, **kwargs)
File "C:\ProgramData\Miniconda3\lib\site-packages\metpy\xarray.py", line 436, in wrapper
return func(*args, **kwargs)
File "C:\ProgramData\Miniconda3\lib\site-packages\metpy\calc\tools.py", line 1014, in first_derivative
combined_delta = delta[tuple(delta_slice0)] + delta[tuple(delta_slice1)]
File "C:\ProgramData\Miniconda3\lib\site-packages\pint\quantity.py", line 1400, in __getitem__
value = self._magnitude[key]
IndexError: too many indices for array
我完全被困住了。搜索“metpy 多级计算”（没有实际报价）没有相关结果。医生说：
metpy.calc.vorticity(u, v, dx, dy)[source]
Calculate the vertical vorticity of the horizontal wind.
Parameters:
u ((M, N) ndarray) – x component of the wind
v ((M, N) ndarray) – y component of the wind
dx (float or ndarray) – The grid spacing(s) in the x-direction. If an array, there should be one item less than the size of u along the applicable axis.
dy (float or ndarray) – The grid spacing(s) in the y-direction. If an array, there should be one item less than the size of u along the applicable axis.
dim_order (str or None, optional) – The ordering of dimensions in passed in arrays. Can be one of None, 'xy', or 'yx'. 'xy' indicates that the dimension corresponding to x is the leading dimension, followed by y. 'yx' indicates that x is the last dimension, preceded by y. None indicates that the default ordering should be assumed, which is ‘yx’. Can only be passed as a keyword argument, i.e. func(…, dim_order=’xy’).
Returns:
(M, N) ndarray – vertical vorticity
我得出的结论是输入可以有超过 2 维，但是 3 维输入（在我的情况下）会产生错误。可以做些什么来修复它们？
我对 Python 完全陌生，所以我可能犯了一个愚蠢的错误。