What happened?

Reading or writing netCDF variables containing scale_factor and/or fill_value might raise the following error: python UFuncTypeError: Cannot cast ufunc 'multiply' output from dtype('float64') to dtype('int64') with casting rule 'same_kind' This problem might be related to the following changes: #7654.

What did you expect to happen?

I'm expecting it to work like it did before xarray 2024.03.0!

Minimal Complete Verifiable Example

```Python

Example 1, decoding problem.

import netCDF4 as nc import numpy as np import xarray as xr

with nc.Dataset("test1.nc", mode="w") as ncds: ncds.createDimension(dimname="d") ncx = ncds.createVariable( varname="x", datatype=np.int64, dimensions=("d",), fill_value=-1, )

ncx.scale_factor = 1e-3
ncx.units = "seconds"

ncx[:] = np.array([0.001, 0.002, 0.003])

This will raise the error

xr.load_dataset("test1.nc")

Example 2, encoding problem.

import netCDF4 as nc import numpy as np import xarray as xr

with nc.Dataset("test2.nc", mode="w") as ncds: ncds.createDimension(dimname="d") ncx = ncds.createVariable(varname="x", datatype=np.int8, dimensions=("d",))

ncx.scale_factor = 1000

ncx[:] = np.array([1000, 2000, 3000])

Reading it does work

data = xr.load_dataset("test2.nc")

Writing read data does not work

data.to_netcdf("text2x.nc") ```

MVCE confirmation

• [X] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
• [X] Complete example — the example is self-contained, including all data and the text of any traceback.
• [X] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
• [X] New issue — a search of GitHub Issues suggests this is not a duplicate.
• [X] Recent environment — the issue occurs with the latest version of xarray and its dependencies.

Relevant log output

```Python

Example 1 error

---

UFuncTypeError Traceback (most recent call last) Cell In[38], line 1 ----> 1 xr.load_dataset("test2.nc")

File .../conda/envs/ong312_local/lib/python3.12/site-packages/xarray/backends/api.py:280, in load_dataset(filename_or_obj, kwargs) 277 raise TypeError("cache has no effect in this context") 279 with open_dataset(filename_or_obj, kwargs) as ds: --> 280 return ds.load()

File .../conda/envs/ong312_local/lib/python3.12/site-packages/xarray/core/dataset.py:855, in Dataset.load(self, **kwargs) 853 for k, v in self.variables.items(): 854 if k not in lazy_data: --> 855 v.load() 857 return self

File .../conda/envs/ong312_local/lib/python3.12/site-packages/xarray/core/variable.py:961, in Variable.load(self, kwargs) 944 def load(self, kwargs): 945 """Manually trigger loading of this variable's data from disk or a 946 remote source into memory and return this variable. 947 (...) 959 dask.array.compute 960 """ --> 961 self._data = to_duck_array(self._data, **kwargs) 962 return self

File .../conda/envs/ong312_local/lib/python3.12/site-packages/xarray/namedarray/pycompat.py:134, in to_duck_array(data, **kwargs) 131 return loaded_data 133 if isinstance(data, ExplicitlyIndexed): --> 134 return data.get_duck_array() # type: ignore[no-untyped-call, no-any-return] 135 elif is_duck_array(data): 136 return data

File .../conda/envs/ong312_local/lib/python3.12/site-packages/xarray/core/indexing.py:809, in MemoryCachedArray.get_duck_array(self) 808 def get_duck_array(self): --> 809 self._ensure_cached() 810 return self.array.get_duck_array()

File .../conda/envs/ong312_local/lib/python3.12/site-packages/xarray/core/indexing.py:803, in MemoryCachedArray._ensure_cached(self) 802 def _ensure_cached(self): --> 803 self.array = as_indexable(self.array.get_duck_array())

File .../conda/envs/ong312_local/lib/python3.12/site-packages/xarray/core/indexing.py:760, in CopyOnWriteArray.get_duck_array(self) 759 def get_duck_array(self): --> 760 return self.array.get_duck_array()

File .../conda/envs/ong312_local/lib/python3.12/site-packages/xarray/core/indexing.py:630, in LazilyIndexedArray.get_duck_array(self) 625 # self.array[self.key] is now a numpy array when 626 # self.array is a BackendArray subclass 627 # and self.key is BasicIndexer((slice(None, None, None),)) 628 # so we need the explicit check for ExplicitlyIndexed 629 if isinstance(array, ExplicitlyIndexed): --> 630 array = array.get_duck_array() 631 return _wrap_numpy_scalars(array)

File .../conda/envs/ong312_local/lib/python3.12/site-packages/xarray/coding/variables.py:81, in _ElementwiseFunctionArray.get_duck_array(self) 80 def get_duck_array(self): ---> 81 return self.func(self.array.get_duck_array())

File .../conda/envs/ong312_local/lib/python3.12/site-packages/xarray/coding/variables.py:81, in _ElementwiseFunctionArray.get_duck_array(self) 80 def get_duck_array(self): ---> 81 return self.func(self.array.get_duck_array())

File .../conda/envs/ong312_local/lib/python3.12/site-packages/xarray/coding/variables.py:399, in _scale_offset_decoding(data, scale_factor, add_offset, dtype) 397 data = data.astype(dtype=dtype, copy=True) 398 if scale_factor is not None: --> 399 data *= scale_factor 400 if add_offset is not None: 401 data += add_offset

UFuncTypeError: Cannot cast ufunc 'multiply' output from dtype('float64') to dtype('int64') with casting rule 'same_kind'

Example 2 error

---

UFuncTypeError Traceback (most recent call last) Cell In[42], line 1 ----> 1 data.to_netcdf("text1x.nc")

File .../conda/envs/ong312_local/lib/python3.12/site-packages/xarray/core/dataset.py:2298, in Dataset.to_netcdf(self, path, mode, format, group, engine, encoding, unlimited_dims, compute, invalid_netcdf) 2295 encoding = {} 2296 from xarray.backends.api import to_netcdf -> 2298 return to_netcdf( # type: ignore # mypy cannot resolve the overloads:( 2299 self, 2300 path, 2301 mode=mode, 2302 format=format, 2303 group=group, 2304 engine=engine, 2305 encoding=encoding, 2306 unlimited_dims=unlimited_dims, 2307 compute=compute, 2308 multifile=False, 2309 invalid_netcdf=invalid_netcdf, 2310 )

File .../conda/envs/ong312_local/lib/python3.12/site-packages/xarray/backends/api.py:1339, in to_netcdf(dataset, path_or_file, mode, format, group, engine, encoding, unlimited_dims, compute, multifile, invalid_netcdf) 1334 # TODO: figure out how to refactor this logic (here and in save_mfdataset) 1335 # to avoid this mess of conditionals 1336 try: 1337 # TODO: allow this work (setting up the file for writing array data) 1338 # to be parallelized with dask -> 1339 dump_to_store( 1340 dataset, store, writer, encoding=encoding, unlimited_dims=unlimited_dims 1341 ) 1342 if autoclose: 1343 store.close()

File .../conda/envs/ong312_local/lib/python3.12/site-packages/xarray/backends/api.py:1386, in dump_to_store(dataset, store, writer, encoder, encoding, unlimited_dims) 1383 if encoder: 1384 variables, attrs = encoder(variables, attrs) -> 1386 store.store(variables, attrs, check_encoding, writer, unlimited_dims=unlimited_dims)

File .../conda/envs/ong312_local/lib/python3.12/site-packages/xarray/backends/common.py:393, in AbstractWritableDataStore.store(self, variables, attributes, check_encoding_set, writer, unlimited_dims) 390 if writer is None: 391 writer = ArrayWriter() --> 393 variables, attributes = self.encode(variables, attributes) 395 self.set_attributes(attributes) 396 self.set_dimensions(variables, unlimited_dims=unlimited_dims)

File .../conda/envs/ong312_local/lib/python3.12/site-packages/xarray/backends/common.py:482, in WritableCFDataStore.encode(self, variables, attributes) 479 def encode(self, variables, attributes): 480 # All NetCDF files get CF encoded by default, without this attempting 481 # to write times, for example, would fail. --> 482 variables, attributes = cf_encoder(variables, attributes) 483 variables = {k: self.encode_variable(v) for k, v in variables.items()} 484 attributes = {k: self.encode_attribute(v) for k, v in attributes.items()}

File .../conda/envs/ong312_local/lib/python3.12/site-packages/xarray/conventions.py:795, in cf_encoder(variables, attributes) 792 # add encoding for time bounds variables if present. 793 _update_bounds_encoding(variables) --> 795 new_vars = {k: encode_cf_variable(v, name=k) for k, v in variables.items()} 797 # Remove attrs from bounds variables (issue #2921) 798 for var in new_vars.values():

File .../conda/envs/ong312_local/lib/python3.12/site-packages/xarray/conventions.py:196, in encode_cf_variable(var, needs_copy, name) 183 ensure_not_multiindex(var, name=name) 185 for coder in [ 186 times.CFDatetimeCoder(), 187 times.CFTimedeltaCoder(), (...) 194 variables.BooleanCoder(), 195 ]: --> 196 var = coder.encode(var, name=name) 198 # TODO(kmuehlbauer): check if ensure_dtype_not_object can be moved to backends: 199 var = ensure_dtype_not_object(var, name=name)

File .../conda/envs/ong312_local/lib/python3.12/site-packages/xarray/coding/variables.py:476, in CFScaleOffsetCoder.encode(self, variable, name) 474 data -= pop_to(encoding, attrs, "add_offset", name=name) 475 if "scale_factor" in encoding: --> 476 data /= pop_to(encoding, attrs, "scale_factor", name=name) 478 return Variable(dims, data, attrs, encoding, fastpath=True)

UFuncTypeError: Cannot cast ufunc 'divide' output from dtype('float64') to dtype('int64') with casting rule 'same_kind' ```

Anything else we need to know?

No response

Environment

INSTALLED VERSIONS ------------------ commit: None python: 3.12.3 | packaged by conda-forge | (main, Apr 15 2024, 18:38:13) [GCC 12.3.0] python-bits: 64 OS: Linux OS-release: 5.15.0-92-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: fr_FR.UTF-8 LOCALE: ('fr_FR', 'UTF-8') libhdf5: 1.14.3 libnetcdf: 4.9.2 xarray: 2024.3.0 pandas: 2.2.2 numpy: 1.26.4 scipy: 1.13.0 netCDF4: 1.6.5 pydap: None h5netcdf: 1.3.0 h5py: 3.11.0 Nio: None zarr: 2.17.2 cftime: 1.6.3 nc_time_axis: None iris: None bottleneck: None dask: 2024.4.1 distributed: 2024.4.1 matplotlib: 3.8.4 cartopy: 0.23.0 seaborn: None numbagg: None fsspec: 2024.3.1 cupy: None pint: 0.23 sparse: None flox: None numpy_groupies: None setuptools: 69.5.1 pip: 24.0 conda: 24.3.0 pytest: 8.1.1 mypy: 1.9.0 IPython: 8.22.2 sphinx: 7.3.5