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  • veenstrajelmer · 2 ✖

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  • Recently introduced different behaviour of da.interp() when using floats vs DataArrays with new dim · 2 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1491747796 https://github.com/pydata/xarray/issues/7701#issuecomment-1491747796 https://api.github.com/repos/pydata/xarray/issues/7701 IC_kwDOAMm_X85Y6kPU veenstrajelmer 60435591 2023-03-31T11:03:36Z 2023-04-03T07:36:33Z CONTRIBUTOR

@headtr1ck I just discovered that it is not per se a difference between floats/da, but it has to do with the creation of the new dimension (plipoints in this case), I have updated the MCVE in https://github.com/pydata/xarray/issues/7701#issue-1647883619.

 
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   Recently introduced different behaviour of da.interp() when using floats vs DataArrays with new dim 1647883619
1491634350 https://github.com/pydata/xarray/issues/7701#issuecomment-1491634350 https://api.github.com/repos/pydata/xarray/issues/7701 IC_kwDOAMm_X85Y6Iiu veenstrajelmer 60435591 2023-03-31T09:36:33Z 2023-03-31T10:06:51Z CONTRIBUTOR

Thanks for your feedback, that is interesting and helpful. I have tested the older xarray version on a laptop with an older environment. I assumed the xarray version was the difference, but I guess there is something else that is causing it if you cannot reproduce it.

Environment where it does work as expected

INSTALLED VERSIONS ------------------ commit: None python: 3.8.13 | packaged by conda-forge | (default, Mar 25 2022, 05:59:45) [MSC v.1929 64 bit (AMD64)] python-bits: 64 OS: Windows OS-release: 10 machine: AMD64 processor: Intel64 Family 6 Model 142 Stepping 9, GenuineIntel byteorder: little LC_ALL: None LANG: en LOCALE: ('Dutch_Netherlands', '1252') libhdf5: 1.12.2 libnetcdf: 4.8.1 xarray: 2022.6.0 pandas: 1.5.0 numpy: 1.23.3 scipy: 1.9.1 netCDF4: 1.6.1 pydap: None h5netcdf: None h5py: None Nio: None zarr: None cftime: 1.6.2 nc_time_axis: None PseudoNetCDF: None rasterio: 1.3.2 cfgrib: None iris: None bottleneck: 1.3.5 dask: 2022.02.1 distributed: 2022.2.1 matplotlib: 3.6.0 cartopy: 0.21.0 seaborn: None numbagg: None fsspec: 2022.8.2 cupy: None pint: None sparse: None flox: None numpy_groupies: None setuptools: 65.3.0 pip: 22.2.2 conda: None pytest: None IPython: 7.33.0 sphinx: 5.2.1

Since .interp() is where it goes wrong, my next hunch was to check the scipy versions. The working env contains scipy 1.9.1, the failing environment contains scipy 1.10.1. When I downgrade to scipy 1.9.1 (or 1.9.3), the behaviour is as expected independent of the xarray version (.interp() gives same results with floats/da as input). When I use scipy 1.10.0 the behaviour is unexpected (different .interp() results), just like scipy 1.10.1. I see there are many scipy.interpolate changes done in scipy with the scipy 1.10.0 release, so that could explain it. For completeness, the interp_with_da variable changes with this scipy version change, not the interp_with_float variable, so it is still a bit xarray related.

I see no related+recent scipy issues yet. Do you have a suggestion on how to proceed?

 
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   Recently introduced different behaviour of da.interp() when using floats vs DataArrays with new dim 1647883619

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