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- Support for monotonically decreasing indices in interpolate_na · 3 ✖
| id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1492399834 | https://github.com/pydata/xarray/issues/4637#issuecomment-1492399834 | https://api.github.com/repos/pydata/xarray/issues/4637 | IC_kwDOAMm_X85Y9Dba | TomNicholas 35968931 | 2023-03-31T18:10:24Z | 2023-03-31T18:10:24Z | MEMBER | @alrho007 the code for this method on which calls the implementation defined in I would start by trying to understand that code (looking at where things are imported to make it work), and then create a small test case example with a monotonically decreasing index that causes a problem. Then try to work out exactly which step in the code causes the issue, and whether it can be generalized to fix the issue. |
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Support for monotonically decreasing indices in interpolate_na 754789691 | |
| 1491793033 | https://github.com/pydata/xarray/issues/4637#issuecomment-1491793033 | https://api.github.com/repos/pydata/xarray/issues/4637 | IC_kwDOAMm_X85Y6vSJ | husainridwan 61923007 | 2023-03-31T11:36:46Z | 2023-03-31T11:37:12Z | NONE | @TomNicholas @dcherian where would I start from if I want to work on this? |
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Support for monotonically decreasing indices in interpolate_na 754789691 | |
| 789652922 | https://github.com/pydata/xarray/issues/4637#issuecomment-789652922 | https://api.github.com/repos/pydata/xarray/issues/4637 | MDEyOklzc3VlQ29tbWVudDc4OTY1MjkyMg== | cvoivret 7123715 | 2021-03-03T11:39:38Z | 2021-03-03T11:39:38Z | NONE | A simple trick could be to not use the coordinate while interpolating. An example with the same data but the second dataset has a decreasing index. ```python import numpy as np import xarray as xr da = xr.DataArray([0, 2, np.nan, 3, 3.25], dims="x", coords={"x": [0, 1, 2, 3, 4]}) da1= xr.DataArray([3.25, 3,np.nan,2,0],dims='x',coords={"x":[4,3,2,1,0]}) da_inter=da.interpolate_na(dim='x', method='cubic') da1_inter=da1.interpolate_na(dim='x',method='cubic',use_coordinate=False) ``` As far as I understand interpolation, the result is the same. |
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Support for monotonically decreasing indices in interpolate_na 754789691 |
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