numpy.argsort#

numpy.argsort(a,axis=-1,kind=None,order=None,*,stable=None)[source]#

Returns the indices that would sort an array.

Perform an indirect sort along the given axis using the algorithm specifiedby thekind keyword. It returns an array of indices of the same shape asa that index data along the given axis in sorted order.

Parameters:
aarray_like

Array to sort.

axisint or None, optional

Axis along which to sort. The default is -1 (the last axis). If None,the flattened array is used.

kind{‘quicksort’, ‘mergesort’, ‘heapsort’, ‘stable’}, optional

Sorting algorithm. The default is ‘quicksort’. Note that both ‘stable’and ‘mergesort’ use timsort under the covers and, in general, theactual implementation will vary with data type. The ‘mergesort’ optionis retained for backwards compatibility.

orderstr or list of str, optional

Whena is an array with fields defined, this argument specifieswhich fields to compare first, second, etc. A single field canbe specified as a string, and not all fields need be specified,but unspecified fields will still be used, in the order in whichthey come up in the dtype, to break ties.

stablebool, optional

Sort stability. IfTrue, the returned array will maintainthe relative order ofa values which compare as equal.IfFalse orNone, this is not guaranteed. Internally,this option selectskind='stable'. Default:None.

New in version 2.0.0.

Returns:
index_arrayndarray, int

Array of indices that sorta along the specifiedaxis.Ifa is one-dimensional,a[index_array] yields a sorteda.More generally,np.take_along_axis(a,index_array,axis=axis)always yields the sorteda, irrespective of dimensionality.

See also

sort

Describes sorting algorithms used.

lexsort

Indirect stable sort with multiple keys.

ndarray.sort

Inplace sort.

argpartition

Indirect partial sort.

take_along_axis

Applyindex_array from argsort to an array as if by calling sort.

Notes

Seesort for notes on the different sorting algorithms.

As of NumPy 1.4.0argsort works with real/complex arrays containingnan values. The enhanced sort order is documented insort.

Examples

One dimensional array:

>>>importnumpyasnp>>>x=np.array([3,1,2])>>>np.argsort(x)array([1, 2, 0])

Two-dimensional array:

>>>x=np.array([[0,3],[2,2]])>>>xarray([[0, 3],       [2, 2]])
>>>ind=np.argsort(x,axis=0)# sorts along first axis (down)>>>indarray([[0, 1],       [1, 0]])>>>np.take_along_axis(x,ind,axis=0)# same as np.sort(x, axis=0)array([[0, 2],       [2, 3]])
>>>ind=np.argsort(x,axis=1)# sorts along last axis (across)>>>indarray([[0, 1],       [0, 1]])>>>np.take_along_axis(x,ind,axis=1)# same as np.sort(x, axis=1)array([[0, 3],       [2, 2]])

Indices of the sorted elements of a N-dimensional array:

>>>ind=np.unravel_index(np.argsort(x,axis=None),x.shape)>>>ind(array([0, 1, 1, 0]), array([0, 0, 1, 1]))>>>x[ind]# same as np.sort(x, axis=None)array([0, 2, 2, 3])

Sorting with keys:

>>>x=np.array([(1,0),(0,1)],dtype=[('x','<i4'),('y','<i4')])>>>xarray([(1, 0), (0, 1)],      dtype=[('x', '<i4'), ('y', '<i4')])
>>>np.argsort(x,order=('x','y'))array([1, 0])
>>>np.argsort(x,order=('y','x'))array([0, 1])
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