Coordinate data is copied when initializing DataArray

[ckutlu]

What happened?

Hi there! I am designing an internal library where I want to provide some utilities with some guarantees on the amount of copies are happening.

I noticed that if I do:

darr_coord = xarray.DataArray(some_array, dims="x")
darr = xr.DataArray(another_array, coords={"x": darr_coord}, dims=("x"))

darr["x"] does not share memory with some_array, which I check with np.shares_memory(darr["x"].data, some_array). This is surprising because another_array shares data with darr.data, and I'd expect coordinate to behave the same. Moreover, if I do:

darr.coords["x"] = ("x", some_array)

They do share the underlying data.

This is not a huge blocker for us, since the workaround is fairly straightforward, but I thought it may be an unexpected behavior.

What did you expect to happen?

I expect no copy to happen both for data and coordinates when I create DataArrays.

Minimal Complete Verifiable Example

import xarray as xr
import numpy as np


def test_data_array_coord_array_not_copied_when_assigning():
    arr = np.random.random(2)
    arr_coord = np.arange(2)

    darr = xr.DataArray(arr, dims=("x"))
    assert darr.data is arr  # Variable is the same as input array.

    darr.coords["x"] = ("x", arr_coord)
    assert np.shares_memory(darr["x"].data, arr_coord)


def test_data_array_coord_array_not_copied_when_providing_at_initialization():
    arr = np.random.random(2)
    arr_coord = np.arange(2)

    darr_coord = xr.DataArray(arr_coord, dims="x")
    assert darr_coord.data is arr_coord  # Variable is the same as input array.

    darr = xr.DataArray(arr, coords={"x": darr_coord}, dims=("x"))
    assert darr.data is arr  # Variable is the same as input array.
    assert np.shares_memory(darr["x"].data, arr_coord)

test_data_array_coord_array_not_copied_when_assigning()  # <- Bueno!
test_data_array_coord_array_not_copied_when_providing_at_initialization()  # <- Sad :(

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

No response

Anything else we need to know?

No response

Environment

INSTALLED VERSIONS

commit: None
python: 3.9.19 (main, Aug 14 2024, 05:11:09)
[Clang 18.1.8 ]
python-bits: 64
OS: Linux
OS-release: 6.8.0-51-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: ('en_US', 'UTF-8')
libhdf5: None
libnetcdf: None

xarray: 2024.7.0
pandas: 2.2.3
numpy: 2.0.2
scipy: None
netCDF4: None
pydap: None
h5netcdf: None
h5py: None
zarr: None
cftime: None
nc_time_axis: None
iris: None
bottleneck: None
dask: None
distributed: None
matplotlib: None
cartopy: None
seaborn: None
numbagg: None
fsspec: None
cupy: None
pint: None
sparse: None
flox: None
numpy_groupies: None
setuptools: None
pip: None
conda: None
pytest: 8.3.4
mypy: 1.13.0
IPython: None
sphinx: None
None

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