I never noticed this kind of cast before (1.8.0), it's just a bit surprising.

It was convenient to write translations (for a bunch of points) such as:

Z = np.ones((n,2),dtype=np.float32) + (300,300)

but I can live with Z += 300,300


Nicolas

On 03 Mar 2014, at 23:02, Benjamin Root <ben.root@ou.edu> wrote:

> IIRC, this is dependent on whether you are using 32bit versus 64bit numpy. All regular integer numbers can fit in 32 bits (is that right?), but the 1.1 is treated as a float32 if on a 32 bit NumPy or as float64 if on a 64 bit NumPy.
>
> That's my stab at it.
>
> Ben Root
>
>
> On Mon, Mar 3, 2014 at 4:06 PM, Nicolas Rougier <Nicolas.Rougier@inria.fr> wrote:
>
> Hi all,
>
> I'm using numpy 1.8.0 (osx 10.9, python 2.7.6) and I can't understand dtype promotion in the following case:
>
> >>> Z = np.zeros((2,2),dtype=np.float32) + 1
> >>> print Z.dtype
> float32
>
> >>> Z = np.zeros((2,2),dtype=np.float32) + (1,1)
> >>> print Z.dtype
> float64
>
>
> Is this the expected behavior ?
> What it the difference between the two lines ?
>
>
>
> Nicolas
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