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  • Using min() with skipna=True · 4 ✖

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529164037 https://github.com/pydata/xarray/issues/3290#issuecomment-529164037 https://api.github.com/repos/pydata/xarray/issues/3290 MDEyOklzc3VlQ29tbWVudDUyOTE2NDAzNw== shoyer 1217238 2019-09-08T02:41:58Z 2019-09-08T02:41:58Z MEMBER

For datetime64 arrays, use np.isnat() instead of isnan.

On Sat, Sep 7, 2019 at 7:39 PM Xin Zhang notifications@github.com wrote:

@keewis https://github.com/keewis I tried to using np.isnan(t.values).all() to check whether it's all nan. But, I got this error:

print (np.isnan(t.values).all())

TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''

This is the type of t.values: <class 'numpy.ndarray'>

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   Using min() with skipna=True 490593787
529163295 https://github.com/pydata/xarray/issues/3290#issuecomment-529163295 https://api.github.com/repos/pydata/xarray/issues/3290 MDEyOklzc3VlQ29tbWVudDUyOTE2MzI5NQ== keewis 14808389 2019-09-08T02:27:23Z 2019-09-08T02:27:23Z MEMBER

do you actually have any non-nan values in your array? From what I understand of how nanops work is that AlwaysGreaterThan should only be returned by min() if there are no non-nan values.

 
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   Using min() with skipna=True 490593787
529152703 https://github.com/pydata/xarray/issues/3290#issuecomment-529152703 https://api.github.com/repos/pydata/xarray/issues/3290 MDEyOklzc3VlQ29tbWVudDUyOTE1MjcwMw== shoyer 1217238 2019-09-07T22:43:48Z 2019-09-07T22:44:18Z MEMBER

I think this may have been fixed by https://github.com/pydata/xarray/pull/2924 (which removed the line with dtypes.fill_value(value.dtype) if valid_count == 0 else data)

Can you try upgrading to xarray 0.12.3?

 
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   Using min() with skipna=True 490593787
529083217 https://github.com/pydata/xarray/issues/3290#issuecomment-529083217 https://api.github.com/repos/pydata/xarray/issues/3290 MDEyOklzc3VlQ29tbWVudDUyOTA4MzIxNw== max-sixty 5635139 2019-09-07T07:40:32Z 2019-09-07T07:40:32Z MEMBER

Thanks for the issue @zxdawn . Did you try doing this?

NotImplementedError: min is not available with skipna=False with the installed version of numpy; upgrade to numpy 1.12

 
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   Using min() with skipna=True 490593787

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