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  • Feature request: Implement interp for interpolating between chunks of data (dask) · 6 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
644024630 https://github.com/pydata/xarray/issues/4078#issuecomment-644024630 https://api.github.com/repos/pydata/xarray/issues/4078 MDEyOklzc3VlQ29tbWVudDY0NDAyNDYzMA== pums974 1005109 2020-06-15T09:46:42Z 2020-06-15T09:46:42Z CONTRIBUTOR

I also want to alert that my version does not work with "advanced interpolation" (as shown in the xarray documentation) Also, my version cannot be used to make interpolate_na work with chunked data

 
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   Feature request: Implement interp for interpolating between chunks of data (dask) 621021621
643972816 https://github.com/pydata/xarray/issues/4078#issuecomment-643972816 https://api.github.com/repos/pydata/xarray/issues/4078 MDEyOklzc3VlQ29tbWVudDY0Mzk3MjgxNg== pums974 1005109 2020-06-15T08:07:52Z 2020-06-15T09:10:17Z CONTRIBUTOR

When using the current official interp function (xarray v0.15.1), the code: ```python datax = xr.DataArray(data=da.from_array(np.arange(0, 4), chunks=2), coords={"x": np.linspace(0, 1, 4)}, dims="x") datay = xr.DataArray(data=da.from_array(np.arange(0, 4), chunks=2), coords={"y": np.linspace(0, 1, 4)}, dims="y") data = datax * datay

# both of these interp call fails
res = datax.interp(x=np.linspace(0, 1))
print(res.load())

res = data.interp(x=np.linspace(0, 1), y=0.5)
print(res.load())

`` fails withNotImplementedError: Chunking along the dimension to be interpolated (0) is not yet supported.`

but succeed with the monkey patched version

EDIT : added the second interp in order to show more general use

 
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   Feature request: Implement interp for interpolating between chunks of data (dask) 621021621
643758667 https://github.com/pydata/xarray/issues/4078#issuecomment-643758667 https://api.github.com/repos/pydata/xarray/issues/4078 MDEyOklzc3VlQ29tbWVudDY0Mzc1ODY2Nw== pums974 1005109 2020-06-14T12:15:12Z 2020-06-15T08:32:27Z CONTRIBUTOR

Thanks, I'll try to make you tests and example quickly.

As for map_overlap, I tried, but something went wrong (I don't remember what though) . Maybe I didn't try enough.

EDIT: I cannot use map_overlap because it doesn't pass *args through to map_blocks

 
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   Feature request: Implement interp for interpolating between chunks of data (dask) 621021621
643320768 https://github.com/pydata/xarray/issues/4078#issuecomment-643320768 https://api.github.com/repos/pydata/xarray/issues/4078 MDEyOklzc3VlQ29tbWVudDY0MzMyMDc2OA== dcherian 2448579 2020-06-12T15:02:24Z 2020-06-12T15:02:24Z MEMBER

Thanks @pums974 we would gladly take a pull request. As @jkmacc-LANL suggests, some tests and comments would be nice in the PR.

It's hard to see exactly what this code is doing, but the general idea of using overlap and map_blocks is sound. Is there a reason you didn't use map_overlap?

 
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   Feature request: Implement interp for interpolating between chunks of data (dask) 621021621
643284336 https://github.com/pydata/xarray/issues/4078#issuecomment-643284336 https://api.github.com/repos/pydata/xarray/issues/4078 MDEyOklzc3VlQ29tbWVudDY0MzI4NDMzNg== jkmacc-LANL 6475152 2020-06-12T13:57:40Z 2020-06-12T13:57:40Z NONE

This looks interesting, but it’s hard to see what it does from the code block. Could you please include a minimal example that includes inputs and outputs, similar to how the xarray docs do it?

 
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   Feature request: Implement interp for interpolating between chunks of data (dask) 621021621
643249507 https://github.com/pydata/xarray/issues/4078#issuecomment-643249507 https://api.github.com/repos/pydata/xarray/issues/4078 MDEyOklzc3VlQ29tbWVudDY0MzI0OTUwNw== pums974 1005109 2020-06-12T12:41:01Z 2020-06-12T12:41:01Z CONTRIBUTOR

Any feedback ? Is my issue usefull ? Should I write a merge request ?

 
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   Feature request: Implement interp for interpolating between chunks of data (dask) 621021621

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