argpartition(a, kth, axis=-1, kind='introselect', order=None)
See partition
for notes on the different selection algorithms.
Array to sort.
Element index to partition by. The k-th element will be in its final sorted position and all smaller elements will be moved before it and all larger elements behind it. The order all elements in the partitions is undefined. If provided with a sequence of k-th it will partition all of them into their sorted position at once.
Passing booleans as index is deprecated.
Axis along which to sort. The default is -1 (the last axis). If None, the flattened array is used.
Selection algorithm. Default is 'introselect'
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.
Array of indices that partition a along the specified axis. If a is one-dimensional, a[index_array]
yields a partitioned a. More generally, np.take_along_axis(a, index_array, axis=a)
always yields the partitioned a, irrespective of dimensionality.
Perform an indirect partition along the given axis using the algorithm specified by the :None:None:`kind` keyword. It returns an array of indices of the same shape as a that index data along the given axis in partitioned order.
argsort
Full indirect sort.
ndarray.partition
Inplace partition.
partition
Describes partition algorithms used.
take_along_axis
Apply index_array
from argpartition to an array as if by calling partition.
One dimensional array:
>>> x = np.array([3, 4, 2, 1])
... x[np.argpartition(x, 3)] array([2, 1, 3, 4])
>>> x[np.argpartition(x, (1, 3))] array([1, 2, 3, 4])
>>> x = [3, 4, 2, 1]
... np.array(x)[np.argpartition(x, 3)] array([2, 1, 3, 4])
Multi-dimensional array:
>>> x = np.array([[3, 4, 2], [1, 3, 1]])See :
... index_array = np.argpartition(x, kth=1, axis=-1)
... np.take_along_axis(x, index_array, axis=-1) # same as np.partition(x, kth=1) array([[2, 3, 4], [1, 1, 3]])
The following pages refer to to this document either explicitly or contain code examples using this.
numpy.take_along_axis
numpy.partition
numpy.put_along_axis
numpy.argsort
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