numpy数组排序

╰半橙微兮° 2022-05-16 06:51 237阅读 0赞

## sort 函数 ##

先看这个例子：

![70][]

`sort` 返回的结果是从小到大排列的。

## argsort 函数 ##

`argsort` 返回从小到大的排列在数组中的索引位置：

![70 1][]

可以用它来进行索引:

![70 2][]

使用函数并不会改变原来数组的值：

![70 3][]

## sort 和 argsort 方法 ##

数组也支持方法操作：

![70 4][]

## 二维数组排序 ##

对于多维数组，sort方法默认沿着最后一维开始排序：

![70 5][]

对于二维数组，默认相当于对每一行进行排序.

改变轴，对每一列进行排序：

![70 6][]

## searchsorted 函数 ##

searchsorted(sorted_array, values)

`searchsorted` 接受两个参数，其中，第一个必需是已排序的数组。

![70 7][]

排序数组：

数值：

`searchsorted` 返回的值相当于保持第一个数组的排序性质不变，将第二个数组中的值插入第一个数组中的位置：

例如 `0.1` 在 \[0.0, 0.25) 之间，所以插入时应当放在第一个数组的索引 `1` 处，故第一个返回值为 `1`。

![70 8][]

利用插入位置，将数组中所有在这两个值之间的值提取出来.

注：

In [36]: np.searchsorted?
    Signature: np.searchsorted(a, v, side='left', sorter=None)
    Docstring:
    Find indices where elements should be inserted to maintain order.
    
    Find the indices into a sorted array `a` such that, if the
    corresponding elements in `v` were inserted before the indices, the
    order of `a` would be preserved.
    
    Parameters
    ----------
    a : 1-D array_like
        Input array. If `sorter` is None, then it must be sorted in
        ascending order, otherwise `sorter` must be an array of indices
        that sort it.
    v : array_like
        Values to insert into `a`.
    side : {'left', 'right'}, optional
        If 'left', the index of the first suitable location found is given.
        If 'right', return the last such index.  If there is no suitable
        index, return either 0 or N (where N is the length of `a`).
    sorter : 1-D array_like, optional
        Optional array of integer indices that sort array a into ascending
        order. They are typically the result of argsort.
    
        .. versionadded:: 1.7.0
    
    Returns
    -------
    indices : array of ints
        Array of insertion points with the same shape as `v`.
    
    See Also
    --------
    sort : Return a sorted copy of an array.
    histogram : Produce histogram from 1-D data.
    
    Notes
    -----
    Binary search is used to find the required insertion points.
    
    As of NumPy 1.4.0 `searchsorted` works with real/complex arrays containing
    `nan` values. The enhanced sort order is documented in `sort`.
    
    Examples
    --------
    >>> np.searchsorted([1,2,3,4,5], 3)
    2
    >>> np.searchsorted([1,2,3,4,5], 3, side='right')
    3
    >>> np.searchsorted([1,2,3,4,5], [-10, 10, 2, 3])
    array([0, 5, 1, 2])
    File:      c:\users\xiaoj\anaconda3\lib\site-packages\numpy\core\fromnumeric.py
    Type:      function

[70]: /images/20220516/94ef949863104116bed813da34096436.png
[70 1]: /images/20220516/eafcc2e6dbaa438a8563260fce3e6690.png
[70 2]: /images/20220516/a638e962bc874a27bb2ba9dac2d14a21.png
[70 3]: /images/20220516/7c38c718ee824d64a4450cb20c919e79.png
[70 4]: /images/20220516/4e3e8b1dac59435dadecdf94dab702a2.png
[70 5]: /images/20220516/6f6181178e9f4da696f06fdaac67c325.png
[70 6]: /images/20220516/c304e1619c8d4fa2a7e64977011635e6.png
[70 7]: /images/20220516/b3637d7a3bdd4553824edd91a1d4b2ce.png
[70 8]: /images/20220516/b022e50e46184d94a16ff732516f82d9.png