Re: [Numpy-discussion] tie breaking for max, min, argmax, argmin

2015-03-12 Thread Julian Taylor 
On 03/12/2015 02:42 PM, Robert Kern wrote:
> On Thu, Mar 12, 2015 at 1:31 PM, Johannes Kulick
>  > wrote:
>>
>> Hello,
>>
>> I wonder if it would be worth to enhance max, min, argmax and argmin
> (more?)
>> with a tie breaking parameter: If multiple entries have the same value
> the first
>> value is returned by now. It would be useful to have a parameter to
> alter this
>> behavior to an arbitrary tie-breaking. I would propose, that the
> tie-breaking
>> function gets a list with all indices of the max/mins.
>>
>> Example:
>> >>> a = np.array([ 1, 2, 5, 5, 2, 1])
>> >>> np.argmax(a, tie_breaking=random.choice)
>> 3
>>
>> >>> np.argmax(a, tie_breaking=random.choice)
>> 2
>>
>> >>> np.argmax(a, tie_breaking=random.choice)
>> 2
>>
>> >>> np.argmax(a, tie_breaking=random.choice)
>> 2
>>
>> >>> np.argmax(a, tie_breaking=random.choice)
>> 3
>>
>> Especially for some randomized experiments it is necessary that not
> always the
>> first maximum is returned, but a random optimum. Thus I end up writing
> these
>> things over and over again.
>>
>> I understand, that max and min are crucial functions, which shouldn't
> be slowed
>> down by the proposed changes. Adding new functions instead of altering the
>> existing ones would be a good option.
>>
>> Are there any concerns against me implementing these things and
> sending a pull
>> request? Should such a function better be included in scipy for example?
> 
> On the whole, I think I would prefer new functions for this. I assume
> you only need variants for argmin() and argmax() and not min() and
> max(), since all of the tied values for the latter two would be
> identical, so returning the first one is just as good as any other.
> 

is this such a common usecase that its worth a numpy function to replace
one liners like this?

np.random.choice(np.where(a == a.max())[0])

its also not that inefficient if the number of equal elements is not too
large.
___
NumPy-Discussion mailing list
NumPy-Discussion@scipy.org
http://mail.scipy.org/mailman/listinfo/numpy-discussion

Re: [Numpy-discussion] tie breaking for max, min, argmax, argmin

2015-03-12 Thread Robert Kern 
On Thu, Mar 12, 2015 at 1:31 PM, Johannes Kulick <
johannes.kul...@ipvs.uni-stuttgart.de> wrote:
>
> Hello,
>
> I wonder if it would be worth to enhance max, min, argmax and argmin
(more?)
> with a tie breaking parameter: If multiple entries have the same value
the first
> value is returned by now. It would be useful to have a parameter to alter
this
> behavior to an arbitrary tie-breaking. I would propose, that the
tie-breaking
> function gets a list with all indices of the max/mins.
>
> Example:
> >>> a = np.array([ 1, 2, 5, 5, 2, 1])
> >>> np.argmax(a, tie_breaking=random.choice)
> 3
>
> >>> np.argmax(a, tie_breaking=random.choice)
> 2
>
> >>> np.argmax(a, tie_breaking=random.choice)
> 2
>
> >>> np.argmax(a, tie_breaking=random.choice)
> 2
>
> >>> np.argmax(a, tie_breaking=random.choice)
> 3
>
> Especially for some randomized experiments it is necessary that not
always the
> first maximum is returned, but a random optimum. Thus I end up writing
these
> things over and over again.
>
> I understand, that max and min are crucial functions, which shouldn't be
slowed
> down by the proposed changes. Adding new functions instead of altering the
> existing ones would be a good option.
>
> Are there any concerns against me implementing these things and sending a
pull
> request? Should such a function better be included in scipy for example?

On the whole, I think I would prefer new functions for this. I assume you
only need variants for argmin() and argmax() and not min() and max(), since
all of the tied values for the latter two would be identical, so returning
the first one is just as good as any other.

--
Robert Kern
___
NumPy-Discussion mailing list
NumPy-Discussion@scipy.org
http://mail.scipy.org/mailman/listinfo/numpy-discussion

[Numpy-discussion] tie breaking for max, min, argmax, argmin

2015-03-12 Thread Johannes Kulick 
Hello,

I wonder if it would be worth to enhance max, min, argmax and argmin (more?)
with a tie breaking parameter: If multiple entries have the same value the first
value is returned by now. It would be useful to have a parameter to alter this
behavior to an arbitrary tie-breaking. I would propose, that the tie-breaking
function gets a list with all indices of the max/mins. 

Example:
>>> a = np.array([ 1, 2, 5, 5, 2, 1])
>>> np.argmax(a, tie_breaking=random.choice)
3

>>> np.argmax(a, tie_breaking=random.choice)
2

>>> np.argmax(a, tie_breaking=random.choice)
2

>>> np.argmax(a, tie_breaking=random.choice)
2

>>> np.argmax(a, tie_breaking=random.choice)
3

Especially for some randomized experiments it is necessary that not always the
first maximum is returned, but a random optimum. Thus I end up writing these
things over and over again.

I understand, that max and min are crucial functions, which shouldn't be slowed
down by the proposed changes. Adding new functions instead of altering the
existing ones would be a good option.

Are there any concerns against me implementing these things and sending a pull
request? Should such a function better be included in scipy for example?

Best,
Johannes
___
NumPy-Discussion mailing list
NumPy-Discussion@scipy.org
http://mail.scipy.org/mailman/listinfo/numpy-discussion