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hello-algo/codes/python/chapter_computational_compl.../time_complexity.py

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3.8 KiB

"""
File: time_complexity.py
Created Time: 2022-11-25
Author: krahets (krahets@163.com)
"""
def constant(n: int) -> int:
"""常数阶"""
count = 0
size = 100000
for _ in range(size):
count += 1
return count
def linear(n: int) -> int:
"""线性阶"""
count = 0
for _ in range(n):
count += 1
return count
def array_traversal(nums: list[int]) -> int:
"""线性阶(遍历数组)"""
count = 0
# 循环次数与数组长度成正比
for num in nums:
count += 1
return count
def quadratic(n: int) -> int:
"""平方阶"""
count = 0
# 循环次数与数据大小 n 成平方关系
for i in range(n):
for j in range(n):
count += 1
return count
def bubble_sort(nums: list[int]) -> int:
"""平方阶(冒泡排序)"""
count = 0 # 计数器
# 外循环:未排序区间为 [0, i]
for i in range(len(nums) - 1, 0, -1):
# 内循环:将未排序区间 [0, i] 中的最大元素交换至该区间的最右端
for j in range(i):
if nums[j] > nums[j + 1]:
# 交换 nums[j] 与 nums[j + 1]
tmp: int = nums[j]
nums[j] = nums[j + 1]
nums[j + 1] = tmp
count += 3 # 元素交换包含 3 个单元操作
return count
def exponential(n: int) -> int:
"""指数阶(循环实现)"""
count = 0
base = 1
# 细胞每轮一分为二,形成数列 1, 2, 4, 8, ..., 2^(n-1)
for _ in range(n):
for _ in range(base):
count += 1
base *= 2
# count = 1 + 2 + 4 + 8 + .. + 2^(n-1) = 2^n - 1
return count
def exp_recur(n: int) -> int:
"""指数阶(递归实现)"""
if n == 1:
return 1
return exp_recur(n - 1) + exp_recur(n - 1) + 1
def logarithmic(n: int) -> int:
"""对数阶(循环实现)"""
count = 0
while n > 1:
n = n / 2
count += 1
return count
def log_recur(n: int) -> int:
"""对数阶(递归实现)"""
if n <= 1:
return 0
return log_recur(n / 2) + 1
def linear_log_recur(n: int) -> int:
"""线性对数阶"""
if n <= 1:
return 1
# 一分为二,子问题的规模减小一半
count = linear_log_recur(n // 2) + linear_log_recur(n // 2)
# 当前子问题包含 n 个操作
for _ in range(n):
count += 1
return count
def factorial_recur(n: int) -> int:
"""阶乘阶(递归实现)"""
if n == 0:
return 1
count = 0
# 从 1 个分裂出 n 个
for _ in range(n):
count += factorial_recur(n - 1)
return count
"""Driver Code"""
if __name__ == "__main__":
# 可以修改 n 运行,体会一下各种复杂度的操作数量变化趋势
n = 8
print("输入数据大小 n =", n)
count = constant(n)
print("常数阶的操作数量 =", count)
count = linear(n)
print("线性阶的操作数量 =", count)
count = array_traversal([0] * n)
print("线性阶(遍历数组)的操作数量 =", count)
count = quadratic(n)
print("平方阶的操作数量 =", count)
nums = [i for i in range(n, 0, -1)] # [n, n-1, ..., 2, 1]
count = bubble_sort(nums)
print("平方阶(冒泡排序)的操作数量 =", count)
count = exponential(n)
print("指数阶(循环实现)的操作数量 =", count)
count = exp_recur(n)
print("指数阶(递归实现)的操作数量 =", count)
count = logarithmic(n)
print("对数阶(循环实现)的操作数量 =", count)
count = log_recur(n)
print("对数阶(递归实现)的操作数量 =", count)
count = linear_log_recur(n)
print("线性对数阶(递归实现)的操作数量 =", count)
count = factorial_recur(n)
print("阶乘阶(递归实现)的操作数量 =", count)