[Numpy-discussion] Power domain (was Re: bug in oldnumeric.ma)

[Pierre GM]

On Friday 09 May 2008 17:13:02 Eric Firing wrote:
> Anne Archibald wrote:
> > 2008/5/9 Eric Firing <efiring at hawaii.edu>:
> >>      md = make_mask((fb != fb.astype(int)) & (fa < 0), shrink=True)
> >
> > Unfortunately this isn't quite the right condition:
> >
> > In [18]: x = 2.**35; numpy.array([-1.])**x; numpy.array(x).astype(int)==x
> > Out[18]: array([ 1.])
> > Out[18]: False
> >
> > Switching to int64 seems to help:

> There may not be a perfect solution, but I suspect your suggestion to
> use int64 is more than good enough to get things going for a 1.1
> release.  The docstring could note the limitation.  If it is established
> that the calculation will fail for a power outside some domain, then
> such a domain check could be added to the mask.

Interestingly, I notice that MaskedArray misses a __pow__ method: it uses the 
ndarray.__pow__ method instead, that may outputs NaNs. In other terms, I 
gonna have to code MaskedArray.__pow__, following Eric' example, with int64 
instead of int.
But, why don't we compare:
abs(np.array(b).astype(int)-b).max()<np.finfo(float).precision
instead ? At which point will b be considered sufficiently close to an integer 
that x**b won't return NaN ?