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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
1470583016 I_kwDOAMm_X85Xp1Do 7340 xr.corr produces incorrect output for complex arrays mattragoza 7647340 closed 0     4 2022-12-01T03:00:09Z 2023-02-14T16:38:29Z 2023-02-14T16:38:29Z NONE      

What happened?

I create a DataArray full of complex numbers, and I compute the correlation of the DataArray with itself.

What did you expect to happen?

The absolute value of the correlation coefficient should be equal to 1, up to numerical precision. However, this is not the case. The returned correlation coefficient is around 0.26 and change depending on the number of values in the array.

Minimal Complete Verifiable Example

```Python import xarray as xr

array = xr.DataArray([ -4.21904583e-03-1.53714478e-03j, -4.24663044e-03-1.12832926e-03j, -4.26968892e-03-4.87451439e-04j, -6.99917538e-03+3.07376860e-04j, 0.00000000e+00+0.00000000e+00j, -2.42585590e-02+1.42052459e-02j, -5.53404148e-03+4.60188062e-03j, -4.68829482e-03+4.90179019e-03j, -7.02331258e-03+8.75908673e-03j, -1.31233383e-01+1.86572484e-01j, -4.05137401e-03+6.59972035e-03j, -4.20701822e-03+7.29813816e-03j, -3.56487231e-03+6.51759430e-03j, -3.68077200e-03+7.04388575e-03j, -8.16459981e-02+1.70084145e-01j, -5.11737898e-03+1.98164995e-02j, 6.72772914e-04-7.28110367e-05j, 2.13957504e-03-1.82525995e-03j, 1.60369835e-03-1.54029189e-03j, 8.77788719e-02-8.45568854e-02j, 1.04277417e-01-9.38854749e-02j, 7.58465696e-03-6.07906563e-03j, 8.00776452e-03-5.70470615e-03j, 8.36166252e-03-5.14978313e-03j, 0.00000000e+00+0.00000000e+00j, 0.00000000e+00+0.00000000e+00j, 0.00000000e+00+0.00000000e+00j, 7.26422461e-03+4.40382166e-04j, 4.01364547e-03+1.09269127e-03j, -1.99069471e-01-1.20355081e-01j, 1.56511579e-01+2.59839758e-01j, 9.14046953e-04+5.42262898e-03j, -8.37800782e-04+5.67555708e-03j, -3.36561822e-03+7.50108018e-03j, -4.22682090e-03+5.36279242e-03j, 5.95438564e-02-3.48209841e-02j, -6.77184281e-03+2.10711488e-03j, -4.84293269e-03+3.78698499e-04j, -5.13547723e-03-6.86765713e-04j, 4.48392070e-01+1.54568226e-01j, -3.17412047e-01-2.35431216e-01j, -2.95731737e-03-3.39078899e-03j, -1.95111443e-03-3.77545168e-03j, -2.82719903e-04-1.61393513e-03j, 7.20241467e-04-1.73515565e-03j, -1.96675563e-01-4.42259734e-02j, 0.00000000e+00+0.00000000e+00j, 4.84813452e-03+7.60742077e-03j, 6.31707602e-03+1.51808252e-02j, 2.99277774e-03+1.18667410e-02j, 5.64640060e-04+1.58372118e-02j, -1.74137347e-03+1.70383706e-02j, -5.91398408e-03+2.30008930e-02j, -7.12027831e-03+1.87732435e-02j, 9.30919156e-02-1.65255887e-01j, -2.09716130e-01+2.30490479e-01j, -1.80115101e-02+1.37248240e-02j, -1.85851718e-02+9.23420957e-03j, -1.88459965e-02+5.12854226e-03j, 1.09175874e+00-9.17875627e-02j, -1.63766142e-02-5.32431671e-03j, -1.24749963e-02-9.63714407e-03j, -7.58657222e-03-1.27728267e-02j, -1.99052439e-03-1.35879033e-02j, -5.70595470e-01+2.27742231e+00j, 1.24516564e-02-1.21867738e-02j, 1.82174257e-02-8.67884733e-03j, 2.27204879e-02-3.77097224e-03j, 2.66143091e-02+2.68683768e-03j, 1.06983372e+00+3.19301893e-01j, -6.86033738e-01-4.72910865e-01j, 3.00291320e-02+3.10297521e-02j, 2.22880055e-02+3.45332319e-02j, 1.61724440e-02+4.04122368e-02j, 9.78881043e-03+4.96053678e-02j, -6.51085120e-03+5.27227722e-02j, -1.76752380e-02+5.26095806e-02j, -3.81856382e-02+6.41735764e-02j, 0.00000000e+00+0.00000000e+00j, -4.32481463e-02+3.88706950e-02j ]) r = np.abs(xr.corr(array, array).item()) assert np.isclose(r, 1.0), r ```

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.

Relevant log output

```Python The exact output I get for the self-contained example below is:

AssertionError Traceback (most recent call last) Cell In [44], line 46 3 array = xr.DataArray([ 4 -4.21904583e-03-1.53714478e-03j, -4.24663044e-03-1.12832926e-03j, 5 -4.26968892e-03-4.87451439e-04j, -6.99917538e-03+3.07376860e-04j, (...) 43 0.00000000e+00+0.00000000e+00j, -4.32481463e-02+3.88706950e-02j 44 ]) 45 r = np.abs(xr.corr(array, array).item()) ---> 46 assert np.isclose(r, 1.0), r

AssertionError: 0.2664911388214005

Anything else we need to know?

Python 3.8.5 (default, Sep 4 2020, 07:30:14) [GCC 7.3.0]

Xarray version is '2022.9.0'

Environment

INSTALLED VERSIONS ------------------ commit: None python: 3.10.6 | packaged by conda-forge | (main, Aug 22 2022, 20:36:39) [GCC 10.4.0] python-bits: 64 OS: Linux OS-release: 4.18.0-193.28.1.el8_2.x86_64 machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: None LOCALE: ('en_US', 'UTF-8') libhdf5: 1.12.1 libnetcdf: 4.8.1 xarray: 2022.9.0 pandas: 1.5.0 numpy: 1.23.3 scipy: 1.9.1 netCDF4: 1.6.0 pydap: None h5netcdf: None h5py: None Nio: None zarr: None cftime: 1.6.2 nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: None dask: 2022.11.0 distributed: None matplotlib: 3.6.2 cartopy: None seaborn: 0.12.1 numbagg: None fsspec: 2022.11.0 cupy: None pint: None sparse: None flox: None numpy_groupies: None setuptools: 65.4.1 pip: 22.2.2 conda: None pytest: None IPython: 8.5.0 sphinx: None 
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   completed xarray 13221727 issue

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