Re: [Numpy-discussion] Unwanted upcast from uint64 to float64

[Torgil S. <tor...@gm...>]

> Yes, because you are adding a signed scalar to an unsigned scalar and a
> float64 is the only thing that can handle it
>
> t+numpy.uint64(1)

Thanks, this make sense. This is a good thing to have back in the head.

//Torgil


On 8/31/06, Travis Oliphant <oli...@ie...> wrote:
> Torgil Svensson wrote:
> > I'm using windows datetimes (100nano-seconds since 0001,1,1) as time
> > in a numpy array and was hit by this behaviour.
> >
> >
> >>>> numpy.__version__
> >>>>
> > '1.0b4'
> >
> >>>> a=numpy.array([632925394330000000L],numpy.uint64)
> >>>> t=a[0]
> >>>> t
> >>>>
> > 632925394330000000L
> >
> >>>> type(t)
> >>>>
> > <type 'numpy.uint64'>
> >
> >>>> t+1
> >>>>
> > 6.3292539433e+017
> >
> >>>> type(t+1)
> >>>>
> > <type 'numpy.float64'>
> >
> >>>> t==(t+1)
> >>>>
> > True
> >
> > I was trying to set t larger than any time in an array. Is there any
> > reason for the scalar to upcast in this case?
> >
> Yes, because you are adding a signed scalar to an unsigned scalar and a
> float64 is the only thing that can handle it (well actually it should be
> the long double scalar but we've made a special case here because long
> doubles are not that common).   Add an unsigned scalar
>
> t+numpy.uint64(1)
>
> to get what you want.
>
> -Travis
>
>
> > //Torgil
> >
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