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 905476569,MDU6SXNzdWU5MDU0NzY1Njk=,5396,bug with to_netcdf when reading dataset via THREDDS,16655388,open,0,,,1,2021-05-28T14:08:12Z,2022-02-03T11:49:29Z,,NONE,,,," I am trying to extract data for a specific station from data observations accessed via THREDDS. At first I got an error but a colleague found a way to make it work. In the code below it works if `APPLY_PATCH=True` but it crashes if `APPLY_PATCH=False`. I do not know if this behaviour is expected and/or linked to the way the data is 'served' via THREDDS but I would never have found the way around it by myself. ``` import xarray as xr CLEF_STATION = ""MONTREAL"" NOM_VAR = 'prsn' APPLY_PATCH = False url_pavics = ""http://pavics.ouranos.ca:8083/twitcher/ows/proxy/thredds/dodsC"" url_donnees_homo = ""/"".join((url_pavics, ""datasets/station_obs/ECCC_AHCCD_gen2_precipitation.ncml"")) ds = xr.open_dataset(url_donnees_homo) # data for specific station(s) dsr = ds.sel(station=ds.station_name.str.contains(CLEF_STATION)) # apply patch if APPLY_PATCH: for var in dsr.variables: if dsr[var].dtype == 'O': dsr[var].encoding = {} # save to a netcdf file dsr.to_netcdf(""out.nc"", format=""NETCDF4_CLASSIC"") ``` **What happened**: When running this I get the following error ``` runfile('/Users/sbiner/cloud/OneDrive - Ouranos inc/job/stagiaires_etudiants/2021_tempete_neige/code/issue_xaray.py', wdir='/Users/sbiner/cloud/OneDrive - Ouranos inc/job/stagiaires_etudiants/2021_tempete_neige/code') Traceback (most recent call last): File ""src/netCDF4/_netCDF4.pyx"", line 4931, in netCDF4._netCDF4.Variable.__setitem__ ValueError: cannot reshape array of size 7 into shape (1,1) During handling of the above exception, another exception occurred: Traceback (most recent call last): File ""/Users/sbiner/cloud/OneDrive - Ouranos inc/job/stagiaires_etudiants/2021_tempete_neige/code/issue_xaray.py"", line 14, in dsr.to_netcdf(""out.nc"", format=""NETCDF4_CLASSIC"") File ""/Users/sbiner/anaconda3/envs/py38/lib/python3.8/site-packages/xarray/core/dataset.py"", line 1689, in to_netcdf return to_netcdf( File ""/Users/sbiner/anaconda3/envs/py38/lib/python3.8/site-packages/xarray/backends/api.py"", line 1107, in to_netcdf dump_to_store( File ""/Users/sbiner/anaconda3/envs/py38/lib/python3.8/site-packages/xarray/backends/api.py"", line 1154, in dump_to_store store.store(variables, attrs, check_encoding, writer, unlimited_dims=unlimited_dims) File ""/Users/sbiner/anaconda3/envs/py38/lib/python3.8/site-packages/xarray/backends/common.py"", line 255, in store self.set_variables( File ""/Users/sbiner/anaconda3/envs/py38/lib/python3.8/site-packages/xarray/backends/common.py"", line 297, in set_variables writer.add(source, target) File ""/Users/sbiner/anaconda3/envs/py38/lib/python3.8/site-packages/xarray/backends/common.py"", line 146, in add target[...] = source File ""/Users/sbiner/anaconda3/envs/py38/lib/python3.8/site-packages/xarray/backends/netCDF4_.py"", line 64, in __setitem__ data[key] = value File ""src/netCDF4/_netCDF4.pyx"", line 4933, in netCDF4._netCDF4.Variable.__setitem__ File ""<__array_function__ internals>"", line 5, in broadcast_to File ""/Users/sbiner/anaconda3/envs/py38/lib/python3.8/site-packages/numpy/lib/stride_tricks.py"", line 411, in broadcast_to return _broadcast_to(array, shape, subok=subok, readonly=True) File ""/Users/sbiner/anaconda3/envs/py38/lib/python3.8/site-packages/numpy/lib/stride_tricks.py"", line 348, in _broadcast_to it = np.nditer( ValueError: operands could not be broadcast together with remapped shapes [original->remapped]: (1,7) and requested shape (1,1) ``` **What you expected to happen**: I expect a netcdf file to be written **Environment**:
Output of xr.show_versions() INSTALLED VERSIONS ------------------ commit: None python: 3.8.8 (default, Apr 13 2021, 12:59:45) [Clang 10.0.0 ] python-bits: 64 OS: Darwin OS-release: 19.6.0 machine: x86_64 processor: i386 byteorder: little LC_ALL: fr_CA.UTF-8 LANG: fr_CA.UTF-8 LOCALE: fr_CA.UTF-8 libhdf5: 1.10.6 libnetcdf: 4.6.1 xarray: 0.17.0 pandas: 1.2.4 numpy: 1.20.1 scipy: 1.6.2 netCDF4: 1.5.6 pydap: None h5netcdf: None h5py: None Nio: None zarr: None cftime: 1.4.1 nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: None dask: 2021.04.0 distributed: 2021.04.0 matplotlib: 3.3.4 cartopy: 0.18.0 seaborn: 0.11.1 numbagg: None pint: None setuptools: 52.0.0.post20210125 pip: 20.3.3 conda: None pytest: None IPython: 7.22.0 sphinx: 4.0.1
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/5396/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 363299007,MDU6SXNzdWUzNjMyOTkwMDc=,2436,"save ""encoding"" when using open_mfdataset",16655388,open,0,,,15,2018-09-24T20:02:49Z,2021-07-28T10:35:42Z,,NONE,,,,"I like the automatic decoding of the time variable when reading netcdf files but I often need to keep the calendar attribute of the time variable. Could it be possible to keep those attributes in the DataSet/DataArray return by open_dataset? ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/2436/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,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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