On 14 April 2014 18:17, Alan G Isaac wrote:
> I find it rather more convenient to use boolean arrays,
> but I wonder if arrays of indexes might have other
> advantages (which would suggest using the set operations
> instead). In particular, might a[boolean_array] be slower
> that a[indexes]? (I'
On 4/12/2014 5:20 PM, Alexander Belopolsky wrote:
> The "set routines" [1] are in this category and may help
> you deal with partitions, but I would recommend using
> boolean arrays instead. If you commonly deal with both
> a subset and a complement, set representation does not
> give you a memory
On Sat, Apr 12, 2014 at 5:03 PM, Sebastian Berg
wrote:
> > As a simple example, suppose for array `a` I want
> > np.flatnonzero(a>0) and np.flatnonzero(a<=0).
> > Can I get them both in one go?
> >
>
> Might be missing something, but I don't think there is a way to do it in
> one go. The result is
On Sa, 2014-04-12 at 16:47 -0400, Alan G Isaac wrote:
> From a 1d array, I want two arrays of indexes:
> the first for elements that satisfy a criterion,
> and the second for elements that do not. Naturally
> there are many ways to do this. Is there a preferred way?
>
> As a simple example, sup
On Sat, Apr 12, 2014 at 4:47 PM, Alan G Isaac wrote:
> As a simple example, suppose for array `a` I want
> np.flatnonzero(a>0) and np.flatnonzero(a<=0).
> Can I get them both in one go?
>
I don't think you can do better than
x = a > 0
p, q = np.flatnonzero(x), np.flatnonzero(~x)
___
From a 1d array, I want two arrays of indexes:
the first for elements that satisfy a criterion,
and the second for elements that do not. Naturally
there are many ways to do this. Is there a preferred way?
As a simple example, suppose for array `a` I want
np.flatnonzero(a>0) and np.flatnonzero(a
