If such issue is at numpy level,
eg xor, which tests for number truth value is equal to n:
xor([1, 1, 0], 2) == True
xor([1, 0, 0], 2) == False
I try to use builtin iterator functions for efficiency, such as combination of
filter + next.
If, however, the problem is at numpy level, I find `numba
It's typically called short-circuiting or quick exit when the target
condition is met.
if you have an array a = np.array([-1, 2, 3, 4, , 1]) and you are
looking for a true/false result whether anything is negative or not (a <
0).any() will generate a bool array equal to and then check all
Could you please give a concise example? I know you have provided one, but it
is engrained deep in verbose text and has some typos in it, which makes hard to
understand exactly what inputs should result in what output.
Regards,
DG
> On 25 Oct 2023, at 22:59, rosko37 wrote:
>
> I know this que
I know this question has been asked before, both on this list as well as
several threads on Stack Overflow, etc. It's a common issue. I'm NOT asking
for how to do this using existing Numpy functions (as that information can
be found in any of those sources)--what I'm asking is whether Numpy would
a
