argmax, argmin argsort and quick sort | 快速排序

This Saturday class we went over indexing and ordering a group of items by their sorted indices. For those who are more advanced, please go over the section on quick sort.

For example,

>> import numpy as np
>>> packpack =np.array([‘snack’,’book’,’pen’,’eraser’,’apple’])
# Position of the biggest word (alphabetically)
>>> np.argmax(packpack)

[out]: 0
# Position of the smallest word (alphabetically)
>>> np.argmin(packpack)

[out]: 4

# Position of the words if we are to sort them alphabetically
>>> np.argsort(packpack)

[out]: array([4, 1, 3, 2, 0], dtype=int64)

Now let us sort them:
>>> packpack[np.argsort(packpack)]

[out]: array([‘apple’, ‘book’, ‘eraser’, ‘pen’, ‘snack’], dtype='<U6′)

Then we tried sorting numbers:

numbers = np.array([2,3,5,7,1,4,6,15,5,2,7,9,10,15,9,17,12])
>>> numbers[np.argsort(numbers)]

[out]: array([ 1, 2, 2, 3, 4, 5, 5, 6, 7, 7, 9, 9, 10, 12, 15, 15, 17])


Finally we dig deeper: how do you really sort things fast systematically? Using quick sort!

def quick_sort(data):
    """快速排序"""
    if len(data) >= 2:  # 递归入口及出口
        mid = data[len(data)//2]  # 选取基准值,也可以选取第一个或最后一个元素
        left, right = [], []  # 定义基准值左右两侧的列表
        data.remove(mid)  # 从原始数组中移除基准值
        for num in data:
            if num >= mid:
                right.append(num)
            else:
                left.append(num)
        return quick_sort(left) + [mid] + quick_sort(right)
    else:
        return data
numbers= [2,3,5,7,1,4,6,15,5,2,7,9,10,15,9,17,12]
Backpack = ['snack','book','pen','eraser','apple']
print(quick_sort(Backpack))
print(quick_sort(numbers))

 

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