Closed
Description
What happened?
While trying to store datetimes into netcdf, ran into the problem of overflowing int32 when datetimes include nanoseconds.
What did you expect to happen?
First surprised that my data did not store successfully, but after investigating, come to understand that the netcdf3 format is quite limited. It would probably make sense to include some warning when using datetime64 when storing to netcdf3.
Minimal Complete Verifiable Example
import numpy as np
import xarray as xr
import datetime
dataset = xr.combine_by_coords(
[
xr.Dataset(
{"value": (["step"], [0.0])},
coords={
"step": np.array(
[datetime.datetime(2000, 1, 1, 0, 0)], dtype="datetime64[ns]"
),
},
),
xr.Dataset(
{"value": (["step"], [0.0])},
coords={
"step": np.array(
[datetime.datetime(2000, 1, 1, 1, 0, 0, 1)],
dtype="datetime64[ns]",
),
},
),
]
)
dataset.to_netcdf("./out.nc", engine="scipy")MVCE confirmation
- Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
- Complete example — the example is self-contained, including all data and the text of any traceback.
- Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
- New issue — a search of GitHub Issues suggests this is not a duplicate.
- Recent environment — the issue occurs with the latest version of xarray and its dependencies.
Relevant log output
File ~/.local/share/virtualenvs/ert-0_7in3Ct/lib/python3.11/site-packages/xarray/core/dataset.py:2303, in Dataset.to_netcdf(self, path
, mode, format, group, engine, encoding, unlimited_dims, compute, invalid_netcdf)
2300 encoding = {}
2301 from xarray.backends.api import to_netcdf
-> 2303 return to_netcdf( # type: ignore # mypy cannot resolve the overloads:(
2304 self,
2305 path,
2306 mode=mode,
2307 format=format,
2308 group=group,
2309 engine=engine,
2310 encoding=encoding,
2311 unlimited_dims=unlimited_dims,
2312 compute=compute,
2313 multifile=False,
2314 invalid_netcdf=invalid_netcdf,
2315 )
File ~/.local/share/virtualenvs/ert-0_7in3Ct/lib/python3.11/site-packages/xarray/backends/api.py:1315, in to_netcdf(dataset, path_or_f
ile, mode, format, group, engine, encoding, unlimited_dims, compute, multifile, invalid_netcdf)
1310 # TODO: figure out how to refactor this logic (here and in save_mfdataset)
1311 # to avoid this mess of conditionals
1312 try:
1313 # TODO: allow this work (setting up the file for writing array data)
1314 # to be parallelized with dask
-> 1315 dump_to_store(
1316 dataset, store, writer, encoding=encoding, unlimited_dims=unlimited_dims
1317 )
1318 if autoclose:
1319 store.close()
File ~/.local/share/virtualenvs/ert-0_7in3Ct/lib/python3.11/site-packages/xarray/backends/api.py:1362, in dump_to_store(dataset, store
, writer, encoder, encoding, unlimited_dims)
1359 if encoder:
1360 variables, attrs = encoder(variables, attrs)
-> 1362 store.store(variables, attrs, check_encoding, writer, unlimited_dims=unlimited_dims)
File ~/.local/share/virtualenvs/ert-0_7in3Ct/lib/python3.11/site-packages/xarray/backends/common.py:352, in AbstractWritableDataStore.
store(self, variables, attributes, check_encoding_set, writer, unlimited_dims)
349 if writer is None:
350 writer = ArrayWriter()
--> 352 variables, attributes = self.encode(variables, attributes)
354 self.set_attributes(attributes)
355 self.set_dimensions(variables, unlimited_dims=unlimited_dims)
File ~/.local/share/virtualenvs/ert-0_7in3Ct/lib/python3.11/site-packages/xarray/backends/common.py:442, in WritableCFDataStore.encode
(self, variables, attributes)
438 def encode(self, variables, attributes):
439 # All NetCDF files get CF encoded by default, without this attempting
440 # to write times, for example, would fail.
441 variables, attributes = cf_encoder(variables, attributes)
--> 442 variables = {k: self.encode_variable(v) for k, v in variables.items()}
443 attributes = {k: self.encode_attribute(v) for k, v in attributes.items()}
444 return variables, attributes
File ~/.local/share/virtualenvs/ert-0_7in3Ct/lib/python3.11/site-packages/xarray/backends/common.py:442, in <dictcomp>(.0)
438 def encode(self, variables, attributes):
439 # All NetCDF files get CF encoded by default, without this attempting
440 # to write times, for example, would fail.
441 variables, attributes = cf_encoder(variables, attributes)
--> 442 variables = {k: self.encode_variable(v) for k, v in variables.items()}
443 attributes = {k: self.encode_attribute(v) for k, v in attributes.items()}
444 return variables, attributes
File ~/.local/share/virtualenvs/ert-0_7in3Ct/lib/python3.11/site-packages/xarray/backends/scipy_.py:213, in ScipyDataStore.encode_vari
able(self, variable)
212 def encode_variable(self, variable):
--> 213 variable = encode_nc3_variable(variable)
214 return variable
File ~/.local/share/virtualenvs/ert-0_7in3Ct/lib/python3.11/site-packages/xarray/backends/netcdf3.py:114, in encode_nc3_variable(var)
112 var = coder.encode(var)
113 data = _maybe_prepare_times(var)
--> 114 data = coerce_nc3_dtype(data)
115 attrs = encode_nc3_attrs(var.attrs)
116 return Variable(var.dims, data, attrs, var.encoding)
File ~/.local/share/virtualenvs/ert-0_7in3Ct/lib/python3.11/site-packages/xarray/backends/netcdf3.py:68, in coerce_nc3_dtype(arr)
66 cast_arr = arr.astype(new_dtype)
67 if not (cast_arr == arr).all():
---> 68 raise ValueError(
69 f"could not safely cast array from dtype {dtype} to {new_dtype}"
70 )
71 arr = cast_arr
72 return arr
ValueError: could not safely cast array from dtype int64 to int32
Anything else we need to know?
No response
Environment
/home/eivind/.local/share/virtualenvs/ert-0_7in3Ct/lib/python3.11/site-packages/_distutils_hack/__init__.py:33: UserWarning: Setuptool
s is replacing distutils.
warnings.warn("Setuptools is replacing distutils.")
INSTALLED VERSIONS
commit: None
python: 3.11.4 (main, Dec 7 2023, 15:43:41) [GCC 12.3.0]
python-bits: 64
OS: Linux
OS-release: 6.2.0-39-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: ('en_US', 'UTF-8')
libhdf5: 1.12.2
libnetcdf: 4.9.3-development
xarray: 2023.10.1
pandas: 2.1.1
numpy: 1.26.1
scipy: 1.11.3
netCDF4: 1.6.5
pydap: None
h5netcdf: None
h5py: 3.10.0
Nio: None
zarr: None
cftime: 1.6.3
nc_time_axis: None
PseudoNetCDF: None
iris: None
bottleneck: None
dask: None
distributed: None
matplotlib: 3.8.0
cartopy: None
seaborn: 0.13.1
numbagg: None
fsspec: None
cupy: None
pint: None
sparse: None
flox: None
numpy_groupies: None
setuptools: 63.4.3
pip: 23.3.1
conda: None
pytest: 7.4.4
mypy: 1.6.1
IPython: 8.17.2
sphinx: 7.1.2