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  • applying ufunc over lon and lat · 2 ✖

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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
566454958 https://github.com/pydata/xarray/issues/3632#issuecomment-566454958 https://api.github.com/repos/pydata/xarray/issues/3632 MDEyOklzc3VlQ29tbWVudDU2NjQ1NDk1OA== mathause 10194086 2019-12-17T09:19:50Z 2019-12-17T09:19:50Z MEMBER

Maybe the code here does something similar to what you want:

https://github.com/pydata/xarray/blob/f2b2f9f62ea0f1020262a7ff563bfe74258ffaa1/xarray/core/missing.py#L17

``` python import numpy as np import xarray as xr from xarray.core import missing as xrmissing

data = [0, -2, -2, -2, 0, -2, -2, 0] da = xr.DataArray(data, coords=dict(time=np.arange(8)), dims=["time"]) dlt = da < 0 xrmissing._get_nan_block_lengths(dlt.where(~ dlt), "time", dlt.time)

```

 
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   applying ufunc over lon and lat  538809911
566368337 https://github.com/pydata/xarray/issues/3632#issuecomment-566368337 https://api.github.com/repos/pydata/xarray/issues/3632 MDEyOklzc3VlQ29tbWVudDU2NjM2ODMzNw== dcherian 2448579 2019-12-17T03:51:06Z 2019-12-17T03:51:06Z MEMBER

I would use %debug and inspect what index and result look like. It's hard to debug without a minimal example.

 
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   applying ufunc over lon and lat  538809911

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