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- API for multi-dimensional resampling/regridding · 1 ✖
| id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 291953242 | https://github.com/pydata/xarray/issues/486#issuecomment-291953242 | https://api.github.com/repos/pydata/xarray/issues/486 | MDEyOklzc3VlQ29tbWVudDI5MTk1MzI0Mg== | duncanwp 3169620 | 2017-04-05T18:29:33Z | 2017-04-05T18:29:53Z | CONTRIBUTOR | @jhamman @godfrey4000 - I'm not sure of the status of this, but I'm the lead developer on a package called CIS which might be useful/relevant. It was designed as a command line tool to allow easy collocation (resampling) between different model and observation datasets, but is now also a Python library. We spent a fair amount of time thinking about the various permutations and you can see some of the details in our paper here. Internally we currently use Iris Cube-like objects but it would be pretty easy to operate on xarray Datasets since they share a similar design. The basic syntax is: ``` from CIS import read_data X = read_data('some_obs_data.nc') Y = read_data('some_other_data.nc') X.sampled_from(Y) or...Y.collocated_onto(X)
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API for multi-dimensional resampling/regridding 96211612 |
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