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Module « numpy.matlib »

Fonction argpartition - module numpy.matlib

Signature de la fonction argpartition

def argpartition(a, kth, axis=-1, kind='introselect', order=None) 

Description

help(numpy.matlib.argpartition)

Perform an indirect partition 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 partitioned order.

Parameters
----------
a : array_like
    Array to sort.
kth : int or sequence of ints
    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 of 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.

    .. deprecated:: 1.22.0
        Passing booleans as index is deprecated.
axis : int or None, optional
    Axis along which to sort. The default is -1 (the last axis). If
    None, the flattened array is used.
kind : {'introselect'}, optional
    Selection algorithm. Default is 'introselect'
order : str 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.

Returns
-------
index_array : ndarray, int
    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=axis)``
    always yields the partitioned `a`, irrespective of dimensionality.

See Also
--------
partition : Describes partition algorithms used.
ndarray.partition : Inplace partition.
argsort : Full indirect sort.
take_along_axis : Apply ``index_array`` from argpartition
                  to an array as if by calling partition.

Notes
-----
The returned indices are not guaranteed to be sorted according to
the values. Furthermore, the default selection algorithm ``introselect``
is unstable, and hence the returned indices are not guaranteed
to be the earliest/latest occurrence of the element.

`argpartition` works for real/complex inputs with nan values,
see `partition` for notes on the enhanced sort order and
different selection algorithms.

Examples
--------
One dimensional array:

>>> import numpy as np
>>> x = np.array([3, 4, 2, 1])
>>> x[np.argpartition(x, 3)]
array([2, 1, 3, 4]) # may vary
>>> x[np.argpartition(x, (1, 3))]
array([1, 2, 3, 4]) # may vary

>>> x = [3, 4, 2, 1]
>>> np.array(x)[np.argpartition(x, 3)]
array([2, 1, 3, 4]) # may vary

Multi-dimensional array:

>>> x = np.array([[3, 4, 2], [1, 3, 1]])
>>> index_array = np.argpartition(x, kth=1, axis=-1)
>>> # below is the same as np.partition(x, kth=1)
>>> np.take_along_axis(x, index_array, axis=-1)
array([[2, 3, 4],
       [1, 1, 3]])

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