我有一些东西，我想这是我想做的第一步。它真的是我的要求具体。问题是，你需要了解什么是在你的matfile，在构建适当的维度。

def convert_to_nc(num:int, step:str, nn:str):

# nn correspond to a path to access the .mat file and where I want to save my new netcdf file

if nn == 'CANYONB':
    chemin = 'xx/{}.mat'.format(num)
elif nn == 'ESPER':
    chemin = 'xy/{}.mat'.format(num)
elif nn == 'CONTENT':
    chemin = 'yy/{}.mat'.format(num)
matfile = sc.io.loadmat(chemin)   

# CONDITION to choose the variables we want from the .mat file

var = [i for i in matfile[step].dtype.names if 'ci' not in i]

# var = [i for i in var if 'sigma' not in i]

# var = [i for i in var if 'raw' not in i]

# var = [i for i in var if 'cy' not in i]

print(var)

# I will open another netcdf file to look for the corresponding dimensions

ds = xr.open_dataset('my_alreadygoodnetcdf_{}.nc'.format(num))
ds_exit = xr.Dataset()
for name in range(len(var)):
    ds_exit[var[name]] = (("PRES_INTERPOLATED", "N_PROF"), matfile[step][var[name]][0][0])
ds_exit = ds_exit.assign_coords(TIME=("N_PROF", ds['TIME'].values)).assign_coords(LATITUDE=("N_PROF", ds['LATITUDE'].values)).assign_coords(LONGITUDE=("N_PROF", ds['LONGITUDE'].values)).assign_coords(N_PROF=("N_PROF", ds['N_PROF'].values)).assign_coords(PRES_INTERPOLATED=("PRES_INTERPOLATED", ds['PRES_INTERPOLATED'].values))
if nn == 'CANYONB':
    save_path = 'xx/{}.nc'.format(num)
elif nn == 'ESPER':
    save_path = 'xy/{}.nc'.format(num)
elif nn =='CONTENT':
    save_path = 'yy/{}.nc'.format(num)

ds_exit.to_netcdf(save_path)
return ds_exit

运行

convert_to_nc(1901212, 'out', 'CONTENT')