On Wed, Apr 14, 2010 at 8:49 AM, Keith Goodman <kwgood...@gmail.com> wrote:
> On Wed, Apr 14, 2010 at 8:16 AM, Nikolaus Rath <nikol...@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:
>
>>> shape = (3,2)
>>> x = np.random.rand(*shape)
>>> x
> array([[ 0.83424288, 0.17821326],
> [ 0.62718311, 0.63514286],
> [ 0.18373934, 0.90634162]])
>>> r = x.reshape(-1).argsort().argsort().reshape(shape)
>>> r
> array([[4, 0],
> [2, 3],
> [1, 5]])
>
> To find the indices you can use where:
>
>>> r < 2
> array([[False, True],
> [False, False],
> [ True, False]], dtype=bool)
>>> np.where(r < 2)
> (array([0, 2]), array([1, 0]))
>
> ...but the indices will not be in order.
...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()
>> np.unravel_index(r[0], shape)
(0, 1)
>> np.unravel_index(r[1], shape)
(0, 0)
>> np.unravel_index(r[2], shape)
(2, 1)
>> np.unravel_index(r[-1], shape)
(1, 0)
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