+1 on quantile()
-CHB
On Sun, Aug 13, 2017 at 6:28 AM, Charles R Harris wrote:
>
>
> On Thu, Aug 10, 2017 at 3:08 PM, Eric Wieser
> wrote:
>
>> Let’s try and keep this on topic - most replies to this message has been
>> about #9211, which is an orthogonal issue.
>>
>> There are two main quest
On Sun, Aug 13, 2017 at 9:28 AM, Charles R Harris wrote:
>
>
> On Thu, Aug 10, 2017 at 3:08 PM, Eric Wieser
> wrote:
>
>> Let’s try and keep this on topic - most replies to this message has been
>> about #9211, which is an orthogonal issue.
>>
>> There are two main questions here:
>>
>>1. Wo
On Thu, Aug 10, 2017 at 3:08 PM, Eric Wieser
wrote:
> Let’s try and keep this on topic - most replies to this message has been
> about #9211, which is an orthogonal issue.
>
> There are two main questions here:
>
>1. Would the community prefer to use np.quantile(x, 0.25) instead of
> np.perc
I concur with the consensus.
On 10 Aug 2017, 11:10 PM +0200, Eric Wieser ,
wrote:
> Let’s try and keep this on topic - most replies to this message has been
> about #9211, which is an orthogonal issue.
> There are two main questions here:
>
> 1. Would the community prefer to use np.quantile(x, 0
Let’s try and keep this on topic - most replies to this message has been
about #9211, which is an orthogonal issue.
There are two main questions here:
1. Would the community prefer to use np.quantile(x, 0.25) instead
of np.percentile(x,
25), if they had the choice
2. Is this desirable en
I will go over your PR carefully to make sure we can agree on a
matching API. After that, we can swap the backend out whenever I get
around to it.
Thanks for working on this.
-Joe
On Thu, Aug 3, 2017 at 5:36 PM, Chun-Wei Yuan wrote:
> Cool. Just as a heads up, for my algorithm to work, I a
Cool. Just as a heads up, for my algorithm to work, I actually need the
indices, which is why argsort() is so important to me. I use it to get
both ap_sorted and ws_sorted variables. If your weighted-quantile algo is
faster and doesn't require those indices, please by all means change my
impleme
Not that I know of. The algorithm is very simple, requiring a
relatively small addition to the current introselect algorithm used
for `np.partition`. My biggest hurdle is figuring out how the calling
machinery really works so that I can figure out which input type
permutations I need to generate, a
Any way I can help expedite this?
On Fri, Jul 21, 2017 at 4:42 PM, Chun-Wei Yuan
wrote:
> That would be great. I just used np.argsort because it was familiar to
> me. Didn't know about the C code.
>
> On Fri, Jul 21, 2017 at 3:43 PM, Joseph Fox-Rabinovitz <
> jfoxrabinov...@gmail.com> wrote:
>
That would be great. I just used np.argsort because it was familiar to
me. Didn't know about the C code.
On Fri, Jul 21, 2017 at 3:43 PM, Joseph Fox-Rabinovitz <
jfoxrabinov...@gmail.com> wrote:
> While #9211 is a good start, it is pretty inefficient in terms of the fact
> that it performs an O
While #9211 is a good start, it is pretty inefficient in terms of the fact
that it performs an O(nlogn) sort of the array. It is possible to reduce
the time to O(n) by using a similar partitioning algorithm to the one in
the C code of percentile. I will look into it as soon as I can.
-Joe
On
Just to provide some context, 9213 actually spawned off of this guy:
https://github.com/numpy/numpy/pull/9211
which might address the weighted inputs issue Joe brought up.
C
On Fri, Jul 21, 2017 at 2:21 PM, Joseph Fox-Rabinovitz <
jfoxrabinov...@gmail.com> wrote:
> I think that there would be
I think that there would be a very good reason to have a separate function
if we were to introduce weights to the inputs, similarly to the way that we
have mean and average. This would have some (positive) repercussions like
making weighted histograms with the Freedman-Diaconis binwidth estimator a
There's an ongoing effort to introduce quantile() into numpy. You'd use it
just like percentile(), but would input your q value in probability space
(0.5 for 50%):
https://github.com/numpy/numpy/pull/9213
Since there's a great deal of overlap between these two functions, we'd
like to solicit opi
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