issue_comments: 375916591

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https://github.com/pydata/xarray/pull/2015#issuecomment-375916591 https://api.github.com/repos/pydata/xarray/issues/2015 375916591 MDEyOklzc3VlQ29tbWVudDM3NTkxNjU5MQ== 6815844 2018-03-24T18:58:57Z 2018-03-24T18:58:57Z MEMBER

Thanks @fmaussion .

Is there a way to make sure this line casts to a secure dtype better than my proposed solution to cast everything to a float64 first?

How about np.array([np.int32(2)]) * np.array([np.int64(2)])?

I am not sure whether numpy explains this casting behavior, but I guess this is intentional. This is consistent with python In [11]: (np.array([1.0], dtype=np.float32) * 1.0).dtype Out[11]: dtype('float32') where we expect the array dtype takes precedence.

 
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