issue_comments: 497254984
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| html_url | issue_url | id | node_id | user | created_at | updated_at | author_association | body | reactions | performed_via_github_app | issue |
|---|---|---|---|---|---|---|---|---|---|---|---|
| https://github.com/pydata/xarray/issues/2281#issuecomment-497254984 | https://api.github.com/repos/pydata/xarray/issues/2281 | 497254984 | MDEyOklzc3VlQ29tbWVudDQ5NzI1NDk4NA== | 6213168 | 2019-05-30T08:45:16Z | 2019-05-30T08:50:13Z | MEMBER | I did not test it but this looks like what you want: ``` from scipy.interpolate import bisplrep, bisplev x = cube1.x.values.ravel() y = cube1.y.values.ravel() z = cube1.values.ravel() x_new = cube2.x.values.ravel() y_new = cube2.y.values.ravel() tck = bisplrep(x, y, z) z_new = bisplev(x_new, y_new, tck) z_new = z_new.reshape(cube2.shape) cube3 = xarray.DataArray(z_new, dims=cube2.dims, coords=cube2.coords) ``` I read above that you have concerns about performance as the above does not understand the geometry of the input data - did you run performance tests on it already? [EDIT] you will probably need to break down your problem on 1-point slices along dimension t before you apply the above. |
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