id,node_id,number,title,user,state,locked,assignee,milestone,comments,created_at,updated_at,closed_at,author_association,active_lock_reason,draft,pull_request,body,reactions,performed_via_github_app,state_reason,repo,type
368833116,MDU6SXNzdWUzNjg4MzMxMTY=,2478,masked_array write/read differences between xarray and netCDF4,16655388,closed,0,,,3,2018-10-10T20:12:19Z,2023-09-13T12:41:03Z,2023-09-13T12:41:02Z,NONE,,,,"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.
```python
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()``
# Paste the output here xr.show_versions() here
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
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/2478/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
363326726,MDU6SXNzdWUzNjMzMjY3MjY=,2437,xarray potential inconstistencies with cftime,16655388,closed,0,,,16,2018-09-24T21:25:46Z,2021-06-22T17:01:35Z,2019-02-08T15:05:38Z,NONE,,,,"I am trying to use xarray with different types of calendars. I made a few tests and wonder if somebody can help me make sense of the results. In my test, I generate a DataArray `da` time series with a 365_day calendar using cftime. I then write that DataArray in a netCDF file and read it in another DataArray `da2`
#### Code Sample, a copy-pastable example if possible
```python
import xarray as xr
import cftime
import numpy as np
# generate data for 365_days calendar
#
units = 'days since 2000-01-01 00:00'
time_365 = cftime.num2date(np.arange(0, 10 * 365), units, '365_day')
da = xr.DataArray(np.arange(time_365.size), coords = [time_365], dims = 'time', name = 'data')
# write dataArray in netcdf and read it in new DataArray
da.to_netcdf('data_365.nc', 'w')
da2 = xr.open_dataset('data_365.nc').data
# try resample da
try:
mean = da.resample(time='Y').mean()
print(mean.values)
except TypeError:
print('got TypeError for da')
# try resample da2
mean = da2.resample(time = 'Y').mean()
print (mean.values)
```
### Problem description
As seen in the code the resampledoes not work for `da` while it does for `da2`. The problem is related to the the type of `da.time` which is `cftime.DatetimeNoLeap` while `da2.time` is a `datetime64`. I thought that xarray is using cftime to make the conversion from time numerical values to dates but it looks to me as if it is not the case.
I wonder if this makes sense or if it is something that should eventually be corrected.
INSTALLED VERSIONS
In [6]: print (cftime.__version__)
1.0.1
------------------
commit: None
python: 3.6.5.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: 0.23.0
numpy: 1.14.3
scipy: 1.1.0
netCDF4: 1.4.1
h5netcdf: None
h5py: 2.7.1
Nio: None
zarr: None
bottleneck: 1.2.1
cyordereddict: None
dask: 0.17.5
distributed: 1.21.8
matplotlib: 2.2.2
cartopy: None
seaborn: 0.8.1
setuptools: 39.1.0
pip: 10.0.1
conda: 4.5.11
pytest: 3.5.1
IPython: 6.4.0
sphinx: 1.7.4
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/2437/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
326553877,MDU6SXNzdWUzMjY1NTM4Nzc=,2187,open_dataset crash with long filenames,16655388,closed,0,,,2,2018-05-25T14:47:31Z,2018-05-29T14:43:50Z,2018-05-29T14:42:35Z,NONE,,,,"#### Code Sample
```python
import xarray as xr
import shutil
import numpy as np
# create netcdf file
data = np.random.rand(4, 3)
foo = xr.DataArray(data)
foo.to_netcdf('test.nc')
f_nc = 'a.nc'
shutil.copy('test.nc', f_nc)
while 1:
print '{:05n} characteres'.format(len(f_nc))
ds1 = xr.open_dataset(f_nc)
ds1.close()
nf_nc = 'a' + f_nc
shutil.move(f_nc, nf_nc)
f_nc = nf_nc
if len(f_nc) == 100:
break
```
#### Problem description
On my linux machine (CentOS) this code crashes (memory corrruption) when the filename length hits 32 characters.
On my OSX machine it is fine until 255 character and stops with an IOError
#### Output of ``xr.show_versions()``
# Paste the output here xr.show_versions() here
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.11.final.0
python-bits: 64
OS: Linux
OS-release: 3.10.0-514.2.2.el7.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_CA.UTF-8
LOCALE: None.None
xarray: 0.10.4
pandas: 0.22.0
numpy: 1.14.2
scipy: 0.16.1
netCDF4: 1.2.2
h5netcdf: None
h5py: 2.5.0
Nio: None
zarr: None
bottleneck: None
cyordereddict: None
dask: 0.17.2
distributed: None
matplotlib: 1.5.0
cartopy: 0.13.1
seaborn: 0.8.1
setuptools: 19.2
pip: 10.0.1
conda: None
pytest: None
IPython: 4.0.1
sphinx: 1.7.2
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