# Python algorithm learning-counting sorting instance

Source: Internet
Author: User
This code introduces the counting sorting instance in python algorithm learning. for details about the code, refer to the example of using python algorithm learning for counting sorting.

The code is as follows:

#-*-Coding: UTF-8 -*-

Def _ counting_sort (A, B, k ):
"Counts are sorted. the pseudo code is as follows:
COUNTING-SORT (A, B, k)
1 for I defaults 0 to k // initialize the value of the bucket
2 do C [I] defaults 0
3 for j every 1 to length [A] // count each value
4 do C [A [j] ← C [A [j] + 1
5. Objective C [I] contains the number of elements equal to I
6 for I limit 1 to k // calculate the sum of counts and determine the number of elements <= each value
7 do C [I] ← C [I] + C [i-1]
8. Objective C [I] contains the number of elements smaller than or equal to I
9 for j segment length [A] downto 1
10 do B [C [A [j] then A [j] // place the [j] value in the corresponding position
11 C [A [j] ← C [A [j]-1 // avoid element overwriting at the same time

T (n) = θ (n)

Args:
A (Sequence): Original array
B (Sequence): result array
K (int): the maximum value. it is assumed that all elements are between [0, k].
"""
Len_c = k + 1
C = [0] * len_c
For a in:
C [a] = C [a] + 1
For I in range (1, len_c ):
C [I] = C [I] + C [i-1]
For a in A [:-1]:
B [C [a]-1] =
C [a] = C [a]-1

Def counting_sort ():
"Assuming that all elements in array A are between [0, len (A)-1]"
B = [0] * len ()
_ Counting_sort (A, B, len (A)-1)
Return B

If _ name _ = '_ main __':
Import random, timeit

Items = range (1, 10000)
Random. shuffle (items)

Def test_sorted ():
Print (items)
Sorted_items = sorted (items)
Print (sorted_items)

Def test_counting_sort ():
Print (items)
Sorted_items = counting_sort (items)
Print (sorted_items)

Test_methods = [test_sorted, test_counting_sort]
For test in test_methods:
Name = test. _ name _ # test. func_name
T = timeit. Timer (name + '()', 'from _ main _ import '+ name)
Print (name + 'takes time: % f' % t. timeit (1 ))

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