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  • dcherian · 3 ✖

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  • simple groupby_bins 10x slower than numpy · 3 ✖

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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
1176918900 https://github.com/pydata/xarray/issues/6758#issuecomment-1176918900 https://api.github.com/repos/pydata/xarray/issues/6758 IC_kwDOAMm_X85GJlt0 dcherian 2448579 2022-07-07T01:03:17Z 2022-07-07T01:03:17Z MEMBER

the IDL histogram function but in numpy.

Apparently not as awesome!

 
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   simple groupby_bins 10x slower than numpy 1295939038
1176730713 https://github.com/pydata/xarray/issues/6758#issuecomment-1176730713 https://api.github.com/repos/pydata/xarray/issues/6758 IC_kwDOAMm_X85GI3xZ dcherian 2448579 2022-07-06T20:54:23Z 2022-07-06T20:54:23Z MEMBER

Yes that's right.

For this simple problem you could combine np.digitize and np.bincount to do it much quicker.

python group_idx = np.digitize(latitude, bins) sums = np.bincount(group_idx, weights=array)

And then wrap this using apply_ufunc. See https://github.com/ml31415/numpy-groupies/blob/412be938dcdfd74c6d673dd29012d18dc25dc94f/numpy_groupies/aggregate_numpy.py#L8-L28 for inspiration.

 
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   simple groupby_bins 10x slower than numpy 1295939038
1176441916 https://github.com/pydata/xarray/issues/6758#issuecomment-1176441916 https://api.github.com/repos/pydata/xarray/issues/6758 IC_kwDOAMm_X85GHxQ8 dcherian 2448579 2022-07-06T16:40:47Z 2022-07-06T16:40:47Z MEMBER

On xarray main with flox installed:

``` python import numpy as np import xarray as xr display(xr.version)

N = 3728 ds = xr.Dataset() ds["latitude"] = ("x", 0 + 20 * np.random.standard_normal(N)) ds["data"] = ("x", 0 + 100 * np.random.standard_normal(N))

%timeit ds.groupby_bins("latitude", np.arange(-40, 40, 0.1)).sum() ``` 50.3 ms ± 203 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)

You could try it on our pre-release (https://docs.xarray.dev/en/latest/whats-new.html#v2022-06-0rc0-9-june-2022) or use xhistogram which should be faster even.

 
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   simple groupby_bins 10x slower than numpy 1295939038

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