# [Numpy-discussion] Find indices of largest elements

Keith Goodman kwgoodman@gmail....
Wed Apr 14 15:56:43 CDT 2010

```On Wed, Apr 14, 2010 at 12:39 PM, Nikolaus Rath <Nikolaus@rath.org> wrote:
> Keith Goodman <kwgoodman@gmail.com> writes:
>> On Wed, Apr 14, 2010 at 8:49 AM, Keith Goodman <kwgoodman@gmail.com> wrote:
>>> On Wed, Apr 14, 2010 at 8:16 AM, Nikolaus Rath <Nikolaus@rath.org> wrote:
>>>> Hello,
>>>>
>>>> How do I best find out the indices of the largest x elements in an
>>>> array?
>>>>
>>>> Example:
>>>>
>>>> a = [ [1,8,2], [2,1,3] ]
>>>> magic_function(a, 2) == [ (0,1), (1,2) ]
>>>>
>>>> Since the largest 2 elements are at positions (0,1) and (1,2).
>>>
>>> Here's a quick way to rank the data if there are no ties and no NaNs:
>>
>> ...or if you need the indices in order:
>>
>>>> shape = (3,2)
>>>> x = np.random.rand(*shape)
>>>> x
>> array([[ 0.52420123,  0.43231286],
>>        [ 0.97995333,  0.87416228],
>>        [ 0.71604075,  0.66018382]])
>>>> r = x.reshape(-1).argsort().argsort()
>
> I don't understand why this works. Why do you call argsort() twice?
> Doesn't that give you the indices of the sorted indices?

It is confusing. Let's look at an example:

>> x = np.random.rand(4)
>> x
array([ 0.37412289,  0.68248559,  0.12935131,  0.42510212])

If we call argsort once we get the index that will sort x:

>> idx = x.argsort()
>> idx
array([2, 0, 3, 1])
>> x[idx]
array([ 0.12935131,  0.37412289,  0.42510212,  0.68248559])

Notice that the first element of idx is 2. That's because element x[2]
is the min of x. But that's not what we want. We want the first
element to be the rank of the first element of x. So we need to
shuffle idx around so that the order aligns with x. How do we do that?
We sort it!

>> idx.argsort()
array([1, 3, 0, 2])

The min value of x is x[2], that's why 2 is the first element of idx
which means that we want ranked(x) to contain a 0 at position 2 which
it does.

Bah, it's all magic.
```