On Thu, 2021-05-20 at 13:46 -0400, Robert Kern wrote:
> On Thu, May 20, 2021 at 1:40 PM CJ Carey
> wrote:
> > If NEP 21 is accepted (
> > https://numpy.org/neps/nep-0021-advanced-indexing.html) this would
> > be
> > even simpler:
> >
> > out.vindex[:, x] = 1
> >
> > Was there ever a decision
On Thu, May 20, 2021 at 1:40 PM CJ Carey wrote:
> Or as a one-liner:
>
> out[np.arange(len(x)), x] = 1
>
Ah, right. `x[arange(len(x))]` is a no-op.
> If NEP 21 is accepted (
> https://numpy.org/neps/nep-0021-advanced-indexing.html) this would be
> even simpler:
>
> out.vindex[:, x] = 1
>
> Was
Or as a one-liner:
out[np.arange(len(x)), x] = 1
If NEP 21 is accepted (
https://numpy.org/neps/nep-0021-advanced-indexing.html) this would be even
simpler:
out.vindex[:, x] = 1
Was there ever a decision about that NEP? I didn't follow the discussion
too closely at the time.
On Thu, May 20, 20
Thanks!
On Thu, May 20, 2021 at 9:53 AM Robert Kern wrote:
>
> On Thu, May 20, 2021 at 9:47 AM Neal Becker wrote:
>>
>> This seems like something that can be done with indexing, but I
>> haven't found the solution.
>>
>> out is a 2D array is initialized to zeros. x is a 1D array whose
>> values
On Thu, May 20, 2021 at 9:47 AM Neal Becker wrote:
> This seems like something that can be done with indexing, but I
> haven't found the solution.
>
> out is a 2D array is initialized to zeros. x is a 1D array whose
> values correspond to the columns of out. For each row in out, set
> out[row,x
This seems like something that can be done with indexing, but I
haven't found the solution.
out is a 2D array is initialized to zeros. x is a 1D array whose
values correspond to the columns of out. For each row in out, set
out[row,x[row]] = 1. Here is working code:
def orthogonal_mod (x, nbits)
