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  • slevang · 1 ✖

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  • Polyfit performance on large datasets - Suboptimal dask task graph · 1 ✖

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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
885216203 https://github.com/pydata/xarray/issues/5629#issuecomment-885216203 https://api.github.com/repos/pydata/xarray/issues/5629 IC_kwDOAMm_X840w1PL slevang 39069044 2021-07-22T20:37:04Z 2021-07-22T20:37:04Z CONTRIBUTOR

Potentially a useful comparison: here is the task graph for the same problem posed to da.curvefit, which uses xr.apply_ufunc(scipy.optimize.curvefit, ..., vectorize=True). Looks a lot cleaner, and I think xr.polyfit could be re-implemented this way without much trouble. ```python import xarray as xr import dask.array as dsa

def linear(x, m, b): return m * x + b

da = xr.DataArray(dsa.random.random((4,6, 100), chunks=(1,2,100)), dims=['x','y', 'time']) fit = da.curvefit('time', linear).curvefit_coefficients ``` 

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   Polyfit performance on large datasets - Suboptimal dask task graph 950882492

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