DataArray.idxmax converts coordinates into float64 by default
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Description
What happened?
Same example as in DataArray.idxmax but instead we look at the "y" dimension.
The starting "y" coordinates are of type int: [-1,0,1]
The return values of argmax are of type int64: good.
The return values of idxmax are of type float64: bad.
What did you expect to happen?
If no fillna operation must occur, then the return values of idxmax should be the same type as from the input.
Else, the return type might change to a new type depending on the type of the filled value.
Minimal Complete Verifiable Example
array = xr.DataArray(
[
[2.0, 1.0, 2.0, 0.0, -2.0],
[-4.0, np.NaN, 2.0, np.NaN, -2.0],
[np.NaN, np.NaN, 1.0, np.NaN, np.NaN],
],
dims=["y", "x"],
coords={"y": [-1, 0, 1], "x": np.arange(5.0) ** 2},
)
print(array.argmax(dim="y").dtype)
print(array.idxmax(dim="y").dtype)
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.
Relevant log output
In [41]: print(array.argmax(dim="y").dtype)
int64
In [42]: print(array.idxmax(dim="y").dtype)
float64
Anything else we need to know?
Suggestions:
- change these two lines:
if skipna or (skipna is None and array.dtype.kind in na_dtypes):
# Put the NaN values back in after removing them
into
if (skipna or (skipna is None and array.dtype.kind in na_dtypes)) and allna.any():
# Put the NaN values back in after removing them, if any
- or maybe instead, it is a bug from
DataArray.where: thisres = res.where(~allna, fill_value)should not change the array type ifnot allna.any()? Actually, it is a known limitation ofwhere: #3570
Environment
INSTALLED VERSIONS
commit: None
python: 3.9.13 (main, Aug 25 2022, 23:51:50) [MSC v.1916 64 bit (AMD64)]
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 158 Stepping 13, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: ('English_United States', '1252')
libhdf5: 1.10.6
libnetcdf: None
xarray: 0.20.1
pandas: 1.4.4
numpy: 1.24.2
scipy: 1.9.1
netCDF4: None
pydap: None
h5netcdf: None
h5py: 3.7.0
Nio: None
zarr: 2.13.3
cftime: None
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: 1.3.5
dask: 2022.7.0
distributed: 2022.7.0
matplotlib: 3.5.2
cartopy: None
seaborn: 0.11.2
numbagg: None
fsspec: 2022.7.1
cupy: None
pint: None
sparse: None
setuptools: 63.4.1
pip: 23.0
conda: 22.9.0
pytest: 7.1.2
IPython: 7.31.1
sphinx: 5.0.2
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The idxmax handling is in xarray/core/computation.py around lines 2086-2088; begin by running the provided DataArray example and inspecting the allna/where path. Add regression coverage for integer y coordinates, then verify idxmax preserves the input coordinate dtype when no fill value is needed.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- numpy, python
- Domain
- data
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 52/100