xarray自动将_FillValue应用于netCDF输出的坐标

Question

我正在尝试创建一个兼容cf的netcdf文件.我可以得到大约98%cf与xarray兼容但是我遇到了一个问题.当我在我正在创建的文件上执行ncdump时,我看到以下内容:

float lon(lon) ;
    lon:_FillValue = NaNf ;
    lon:long_name = "Longitude" ;
    lon:standard_name = "longitude" ;
    lon:short_name = "lon" ;
    lon:units = "degrees_east" ;
    lon:axis = "X" ;
    lon:valid_min = -180.f ;
    lon:valid_max = 180.f ;
float lat(lat) ;
    lat:_FillValue = NaNf ;
    lat:long_name = "Latitude" ;
    lat:standard_name = "latitude" ;
    lat:short_name = "lat" ;
    lat:units = "degrees_north" ;
    lat:axis = "Y" ;
    lat:valid_min = -90.f ;
    lat:valid_max = 90.f ;
double time(time) ;
    time:_FillValue = NaN ;
    time:standard_name = "time" ;
    time:units = "days since 2006-01-01" ;
    time:calendar = "gregorian" ;

我的数据集的坐标是lat,lon和time.当我通过ds.to_netcdf()转换为netcdf时,所有坐标变量都会自动应用填充值,因为它们是浮点数.使用具有填充值的坐标变量违反了cf标准(http://cfconventions.org/cf-conventions/v1.6.0/cf-conventions.html#attribute-appendix).

我试图更改编码,以便不压缩这些特定变量:

import numpy as np
import xarray as xr
import pandas as pd
import datetime as dt

lons = np.arange(-75, -70, .5).astype(np.float32)
lats = np.arange(40,42, .25).astype(np.float32)
[x, y] = np.meshgrid(lons, lats)
u = np.random.randn(1, 8, 10).astype(np.float32)
v = np.random.randn(1, 8, 10).astype(np.float32)
time_index = pd.date_range(dt.datetime.now(), periods=1)

ds = xr.Dataset()
coords = ('time', 'lat', 'lon')
ds['u'] = (coords, np.float32(u))
ds['v'] = (coords, np.float32(v))
ds.coords['lon'] = lons
ds.coords['lat'] = lats
ds.coords['time'] = time_index

encoding = {'lat': {'zlib': False},
            'lon': {'zlib': False},
            'u': {'_FillValue': -999.0,
                  'chunksizes': (1, 8, 10),
                  'complevel': 1,
                  'zlib': True}
            }
ds.to_netcdf('test.nc', encoding=encoding)

或通过改变dtypes,但我没有运气.我不想使用netCDF4重新加载文件来删除_FillValues.是否存在内置于xarray中的方法？

Answer 1

添加_FillValue: False到lat/lon编码似乎有效:

encoding = {'lat': {'zlib': False, '_FillValue': False},
            'lon': {'zlib': False, '_FillValue': False},
            'u': {'_FillValue': -999.0,
                  'chunksizes': (1, 8, 10),
                  'complevel': 1,
                  'zlib': True}
            }

ncdump -h 生成的文件:

netcdf test {
dimensions:
    time = 1 ;
    lat = 8 ;
    lon = 10 ;
variables:
    float u(time, lat, lon) ;
        u:_FillValue = -999.f ;
    float v(time, lat, lon) ;
        v:_FillValue = NaNf ;
    float lon(lon) ;
    float lat(lat) ;
    int64 time(time) ;
        string time:units = "days since 2017-08-15 17:41:19.460662" ;
        string time:calendar = "proleptic_gregorian" ;
}