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 specified by the kind keyword. It returns an array of indices of the same shape as a 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, the actual implementation will vary with data type. The ‘mergesort’ option is retained for backwards compatibility.
Changed in version 1.15.0.: The ‘stable’ option was added.
- orderstr or list of str, optional
When a is an array with fields defined, this argument specifies which fields to compare first, second, etc. A single field can be specified as a string, and not all fields need be specified, but unspecified fields will still be used, in the order in which they come up in the dtype, to break ties.
- stablebool, optional
Sort stability. If
True
, the returned array will maintain the 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 sort a along the specified axis. If a is one-dimensional,
a[index_array]
yields a sorted a. More generally,np.take_along_axis(a, index_array, axis=axis)
always yields the sorted a, 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
Apply
index_array
from argsort to an array as if by calling sort.
Notes
See
sort
for notes on the different sorting algorithms.As of NumPy 1.4.0
argsort
works with real/complex arrays containing nan values. The enhanced sort order is documented insort
.Examples
One dimensional array:
>>> x = np.array([3, 1, 2]) >>> np.argsort(x) array([1, 2, 0])
Two-dimensional array:
>>> x = np.array([[0, 3], [2, 2]]) >>> x array([[0, 3], [2, 2]])
>>> ind = np.argsort(x, axis=0) # sorts along first axis (down) >>> ind array([[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) >>> ind array([[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')]) >>> x array([(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])