interp() performance regression in 2025.1.0+ #10683
Description
What happened?
A performance regression has been introduced between 2024.11.0 and 2025.1.0, possibly in #9881, as was the case in #10287. This issue is still present in 2025.8.0. In the example running on my machine it is a 76x performance regression. It seems to be present when interpolating 2D arrays but the degradation is more extreme with 3D arrays.
What did you expect to happen?
No performance regression.
Minimal Complete Verifiable Example
import numpy as np
import xarray as xr
import time
n_repeats = 10
# array dims
n_t = 122
n_r = 65
n_z = 65
# generate some random data to interpolate
rng = np.random.default_rng(seed=42)
data = rng.random((n_t, n_r, n_z))
data_t = np.linspace(0.01, 0.855, n_t)
data_r = np.linspace(0.04, 4., n_r)
data_z = np.linspace(-1.2, 1.2, n_z)
da = xr.DataArray(
data=data,
dims=["t", "r", "z"],
coords=dict(
t=data_t,
r=data_r,
z=data_z,
),
)
interp_z_data = rng.random((n_t))
interp_z = xr.DataArray(
data=interp_z_data,
dims=["t"],
coords=dict(
t=data_t,
),
)
start = time.time()
for _ in range(n_repeats):
# regression is here:
da.interp(z=interp_z)
end = time.time()
t_elapsed = end - start
print(f"Time elapsed: {t_elapsed}")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
pip install "xarray==2024.11.0"
python test.py
Time elapsed: 0.22251605987548828
pip install "xarray==2025.1.0"
python test.py
Time elapsed: 16.765803813934326Anything else we need to know?
No response
Environment
xarray: 2025.1.0
pandas: 2.3.2
numpy: 2.3.2
scipy: 1.16.1
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: 24.3.1
conda: None
pytest: None
mypy: None
IPython: None
sphinx: None