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Examples of common allocation sorting methods in Python data structures and algorithms [Bucket sorting and radix sorting]_python
Examples of common allocation sorting methods in Python data structures and algorithms [Bucket sorting and radix sorting]_python
This article mainly introduces the common allocation and sorting methods of Python data structures and algorithms. It analyzes the related principles and implementation techniques of bucket sorting and radix sorting in the form of examples. Friends who need to learn Python can refer to this article and examples of this article. Describes the common allocation and sorting methods of Python data structures and algorithms. Share it with everyone for your reference, the details are as follows:
Box sorting (bucket sorting)
Box sorting is based on the value range of the keyword 1~m, create m boxes in advance. Box sorting requires the keyword type to be a limited type. There may be infinite boxes. It has little practical value and is generally used in the intermediate process of radix sorting.
Bucket sorting is a practical variant of box sorting. It divides the range of the data set, such as [0,1), into n sub-intervals of the same size, each sub-interval is a bucket, and then n non-records are allocated to each bucket. Because the keyword sequence is evenly distributed on [0,1), there are generally not many records falling into the same bucket.
The following bucket sorting method is implemented using a dictionary, so for integer types, there is no need to create extra space
def BuckSort(A): bucks = dict() # 桶 for i in A: bucks.setdefault(i,[]) # 每个桶默认为空列表 bucks[i].append(i) # 往对应的桶中添加元素 A_sort = [] for i in range(min(A), max(A)+1): if i in bucks: # 检查是否存在对应数字的桶 A_sort.extend(bucks[i]) # 合并桶中数据 return A_sort
radixsort
# 基数排序
# 输入：待排序数组s, keysize关键字位数, 亦即装箱次数, radix基数
def RadixSort(s, keysize=4, radix=10):
# 按关键字的第k分量进行分配 k = 4,3,2,1
def distribute(s,k):
box = {r:[] for r in range(radix)} # 分配用的空箱子
for item in s: # 依次扫描s[]，将其装箱
t = item
t /= 10**(k-1)
t %= 10 # 去关键字第k位
box[t].append(item)
return box
# 按分配结果重新排列数据
def collect(s,box):
a = 0
for i in range(radix):
s[a:a + len(box[i])] = box[i][:] # 将箱子中元素的合并，覆盖到原来的数组中
a += len(box[i]) # 增加偏移值
# 核心算法
for k in range(1,keysize+1):
box = distribute(s,k) # 按基数分配
collect(s,box) # 按分配结果拼合The following is excerpted from: "Data Structures and Algorithms - Theory and Practice"
Radix sorting can be expanded to sorting by multiple keywords, such as sorting poker cards by suit and point.
Generally, assuming that the linear table has elements to be sorted, each element contains d keywords {k1, k2,...,kd}, then the linear table has an ordered reference to the keywords. For the linear table Any two elements r[i] and r[j], 1<=i<=j<=n, satisfy the following ordered relationship:
{k1i,k2i,...,kdi} < {k1j ,k2j,...,kdj}
K1 is called the most significant digit keyword, kd is called the least significant digit keyword
There are two sorting methods: MSD (most significant digit first) With least significant digit first LSD (least significant digit first)
MSD: First sort the groups by k1. If the elements of the same group are equal to the keyword k1, then sort each group by k2 and divide it into subgroups, and so on. , until the subgroups are sorted by the lowest position kd, and then the groups are linked.
LSD: Contrary to MSD, sort by kd first, then kd-1, and so on.
PS: Here is another demonstration tool about sorting recommended for your reference:
Online animation Demonstration of insertion/selection/bubble/merge/Hill/quick sort algorithm process tools:
http://tools.jb51.net/aideddesign/paixu_ys
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