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sort 函数
先看这个例子: 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: 可以用它来进行索引: 使用函数并不会改变原来数组的值: 数组也支持方法操作: 对于多维数组,sort方法默认沿着最后一维开始排序: 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: searchsorted 接受两个参数,其中,第一个必需是已排序的数组。
排序数组: 012340.00.250.50.751.0数值: 值0.10.80.30.120.50.25插入位置142121searchsorted 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。 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
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