斐波那契数列(Fibonacci)递归与非递归的性能对比

费波那契数列由0和1开始，之后的数就由之前的两数相加 0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584,……….

递归算法

用递归算法来求值,非常好理解.伪代码:

f(n) = 0                (n=0)
f(n) = 1                (n=1)
f(n) = f(n-1) + f(n-2)  (n>1)

实现:

def f(n):
    if n==0:
        return 0
    elif n==1:
        return 1
    elif n>1:
        return f(n-1) + f(n-2)

非递归算法

def f(n):
    if n == 0:
        return 0
    if n == 1:
        return 1
    if n>1:

        prev = 1    #第n-1项的值
        p_prev = 0  #第n-2项的值
        result = 1  #第n项的值

        for i in range(1,n):
           result = prev+p_prev 
           p_prev = prev
           prev = result
        return result

功能实现了,但是代码比较冗长,函数是要对前两项做特殊判断.现在优化一下,如何才能更通用,即使是第0个和第1个也能运用到for循环呢?假设在 0, 1, 1, 2, 3, 5, 8, 13... 之前还有两项, 是-1和1, 即: -1, 1, 0, 1, 1, 2, 3, 5, 8, 13, 21, 34,这样就通用了:

def f(n):
    prev = 1
    p_prev = -1
    result = 0
    for i in range(n+1):
        result = prev+p_prev
        p_prev = prev
        prev = result
    return result

现在评估一下他们的性能: 写一个性能装饰器.

def perfromce_profile(func):
    def wrapper(*args, **kwargs):
        start = time.time()
        rtn = func(*args, **kwargs)
        end = time.time()
        print end-start
        return rtn
    return wrapper

他不能用在递归方法中. 所以最终还是写了这么个方法:

import time

def f0(n):
    if n==0:
        return 0
    elif n==1:
        return 1
    elif n>1:
        return f(n-1) + f(n-2)

def f(n):
      prev = 1
      p_prev = -1
      result = 0
      for i in range(n+1):
          result = prev+p_prev
          p_prev = prev
          prev = result
      return result   

def perfromce_profile():
    start = time.time()
    f0(1000000)
    end = time.time()
    print end-start
    start = time.time()
    f(1000000)
    print time.time()-start



if __name__ == '__main__':
    perfromce_profile()

看出性能对比了吧:

54.2904469967
27.7642970085

所以用递归弊端还是不少