I would use a complex32 dtype if it existed, whether provided by numpy or another library.

My guess would be that there was not much demand for a complex32 datatype since float16s are slow and are generally used as a storage format [1] and you could easily store a complex array as two float16 arrays and get the same space savings. 

That said, I am occasionally storing complex-valued validation data in memory, and the datatype would make it more convenient. I just don't know how common my use case is. Maybe there are more compelling use cases? I know some GPUs natively support float16, I'm not sure how common complex32 support is though.

[1] https://stackoverflow.com/a/24590380/5026175

On Thu, Jul 11, 2019 at 7:47 AM Neal Becker <ndbecker2@gmail.com> wrote:
I see a float16 dtype but not complex32.  Is this an oversight?


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