Should numpy.sqrt(-1) return 1j rather than nan?

[Travis Oliphant]

>
>     Personally I think that the default error mode should be tightened
>     up.
>     Then people would only see these sort of things if they really care
>     about them. Using Python 2.5 and the errstate class I posted earlier:
>
>         # This is what I like for the default error state
>         numpy.seterr (invalid='raise', divide='raise', over='raise',
>         under='ignore')
>
>
> I like these choices too. Overflow, division by zero, and sqrt(-x) are 
> usually errors, indicating bad data or programming bugs. Underflowed 
> floats, OTOH, are just really, really small numbers and can be treated 
> as zero. An exception might be if the result is used in division and 
> no error is raised, resulting in a loss of accuracy.
>

I'm fine with this.  I've hesitated because error checking is by default 
slower.  But, I can agree that it is "less surprising" to new-comers.  
People that don't mind no-checking can simply set their defaults back to 
'ignore'


-Travis


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