[Numpy-discussion] Nice float -> integer conversion?
Derek Homeier
derek@astro.physik.uni-goettingen...
Tue Oct 11 14:06:25 CDT 2011
On 11 Oct 2011, at 20:06, Matthew Brett wrote:
> Have I missed a fast way of doing nice float to integer conversion?
>
> By nice I mean, rounding to the nearest integer, converting NaN to 0,
> inf, -inf to the max and min of the integer range? The astype method
> and cast functions don't do what I need here:
>
> In [40]: np.array([1.6, np.nan, np.inf, -np.inf]).astype(np.int16)
> Out[40]: array([1, 0, 0, 0], dtype=int16)
>
> In [41]: np.cast[np.int16](np.array([1.6, np.nan, np.inf, -np.inf]))
> Out[41]: array([1, 0, 0, 0], dtype=int16)
>
> Have I missed something obvious?
np.[a]round comes closer to what you wish (is there consensus
that NaN should map to 0?), but not quite there, and it's not really
consistent either!
In [42]: c = np.zeros(4, np.int16)
In [43]: d = np.zeros(4, np.int32)
In [44]: np.around([1.6,np.nan,np.inf,-np.inf], out=c)
Out[44]: array([2, 0, 0, 0], dtype=int16)
In [45]: np.around([1.6,np.nan,np.inf,-np.inf], out=d)
Out[45]: array([ 2, -2147483648, -2147483648, -2147483648], dtype=int32)
Perhaps a starting point to harmonise this behaviour and get it closer to
your expectations (it still would not be really nice having to define the
output array first, I guess)...
Cheers,
Derek
More information about the NumPy-Discussion
mailing list