Description
Here is code used to read/write a masked_array with the netCDF4 and xarray modules.
As seen if you run the code, for 3 cases the masked_value is read as a np.nan. However, for the netcdf file written by netCDF4 and read by xarray, the masked_value is the default _FillValue of 9.96920997e+36.
I wonder if this is expected or if I am doing something wrong.
import xarray as xr
import netCDF4 as nc
import numpy as np
import os
data = np.ma.array([1.,2.], mask = [True, False])
# create file with netcdf$
nc_file = 'ncfile.nc'
if os.path.exists(nc_file): os.remove(nc_file)
ds = nc.Dataset(nc_file, 'w')
ds.createDimension('dim1', 2)
var = ds.createVariable('data', 'f8', dimensions = ('dim1'))
var[:] = data
ds.close()
# create file with xarray
da = xr.DataArray(data, name = 'data', dims = {'dim1':2})
nc_file = 'xrfile.nc'
if os.path.exists(nc_file): os.remove(nc_file)
da.to_netcdf(nc_file, 'w')
da.close()
print('original data: {}'.format(data))
da = xr.open_dataset('ncfile.nc').data
print('data from nc read by xr: {}'.format(da.values))
da = xr.open_dataset('xrfile.nc').data
print('data from xr read by xr: {}'.format(da.values))
data = nc.Dataset('ncfile.nc').variables['data'][:]
print('data from nc read by nc: {}'.format(da.values))
data = nc.Dataset('xrfile.nc').variables['data'][:]
print('data from xr read by nc: {}'.format(da.values))
print('done')Here is the output I get:
original data: [-- 2.0]
data from nc read by xr: [9.96920997e+36 2.00000000e+00]
data from xr read by xr: [nan 2.]
data from nc read by nc: [nan 2.]
data from xr read by nc: [nan 2.]
done
Output of xr.show_versions()
INSTALLED VERSIONS
commit: None
python: 3.6.6.final.0
python-bits: 64
OS: Darwin
OS-release: 17.7.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: fr_CA.UTF-8
LOCALE: fr_CA.UTF-8
xarray: 0.10.8
pandas: 0.23.4
numpy: 1.15.1
scipy: 1.1.0
netCDF4: 1.4.1
h5netcdf: None
h5py: None
Nio: None
zarr: None
bottleneck: 1.2.1
cyordereddict: None
dask: 0.19.2
distributed: None
matplotlib: None
cartopy: None
seaborn: None
setuptools: 40.2.0
pip: 18.0
conda: None
pytest: 3.8.0
IPython: 7.0.1
sphinx: None