随机行走者Python代码

Question

随机行走者Python代码

3

如何加快以下代码的速度，以便能够处理超过100个人？

""" Random Walker """
import numpy as np
import scipy as sp
import random as rd
import time

def procedure():
    time.sleep(2.5)
    t0C = time.clock()
    t0 = time.time()

    """Definitions"""

    def ifilterfalse(predicate, iterable):
        # ifilterfalse(lambda x: x%2, range(10)) --> 0 2 4 6 8
        if predicate is None:
            predicate = bool
        for x in iterable:
            if not predicate(x):
                yield x

    def unique_everseen(iterable, key=None):
        "List unique elements, preserving order. Remember all elements ever seen."
        # unique_everseen('AAAABBBCCDAABBB') --> A B C D
        # unique_everseen('ABBCcAD', str.lower) --> A B C D
        seen = set()
        seen_add = seen.add
        if key is None:
            for element in ifilterfalse(seen.__contains__, iterable):
                seen_add(element)
                yield element
        else:
            for element in iterable:
                k = key(element)
                if k not in seen:
                    seen_add(k)
                    yield element

    """Creating the Random Walk"""

    n=int(input('Number of Individuals at Table: '))
    iters=10000
    final=np.zeros(n)
    total=0
    for j in xrange(iters):
        d=np.array([0])
        i=0
        while i<1:
            new=d[len(d)-1]+rd.choice([-1,1])
            if new<0:
                new+=n
            elif new>=n:
                new-=n
            d=np.append(d,new)
            dshort=list(unique_everseen(d))
            if len(dshort)>=n:
                i=1
            last=dshort[len(dshort)-1]
            length=len(d)
        final[last]+=1
        total+=length

    final=np.round(final/iters,4)
    total=round(total/iters,3)

    """Writing To A File"""

    print (40 * '-')
    print (" ")
    print ("   Percentages: ")
    print (" ")
    print ("   S#:"+"      S#:".join(map(str,range(n))))
    print ("   "+"%   ".join(map(str,final))+"%")
    print (" ")
    print ("   Average Number of Passes of Plate: {}".format(total))
    print (" ")
    print (40 * '-')

    # measure process time
    print time.clock() - t0C, "seconds process time"

     # measure wall time
    print time.time() - t0, "seconds wall time"


if __name__ == "__main__":
    procedure()

目前对于10个人的情况，时间为：

5.877529秒的处理时间

12.9134569168秒的墙壁时间

问题在于当人数增加到100或1000时，代码运行速度太慢，有什么建议吗？

- user3671704

如果您调整一下缩进，回答问题会更容易。 - Jivan

抱歉，缩进已经修复。 - user3671704

1个回答

网页内容由stack overflow 提供, 点击上面的

可以查看英文原文，
原文链接

- malbarbo · Accepted Answer

问题在于unique_everseen在连续执行时实际上完成了相同的工作，耗费了太多时间。这是一个简化版本，删除了unique_everseen函数和d列表，并直接在主循环中使用seen集合和last变量来保留最后一个项：

""" Random Walker """
import random as rd
import time

def procedure():
    n = int(input('Number of Individuals at Table: '))

    t0C = time.clock()
    t0 = time.time()

    iters = 10000
    final = [0] * n
    total = 0
    for j in xrange(iters):
        last = 0
        count = 1
        seen = set([0])
        while len(seen) < n:
            count += 1;
            new = last + rd.choice([-1, 1])
            if new < 0:
                new += n
            elif new >= n:
                new -= n
            seen.add(new)
            last = new
        final[last] += 1
        total += count

    final = [round(float(f) / iters, 4) for f in final]
    total = round(float(total) / iters, 3)

    """Writing To A File"""

    print(40 * '-')
    print(" ")
    print("   Percentages: ")
    print(" ")
    print("   S#:" + "      S#:".join(map(str, range(n))))
    print("   " + "%   ".join(map(str, final)) + "%")
    print(" ")
    print("   Average Number of Passes of Plate: {}".format(total))
    print(" ")
    print(40 * '-')

    # measure process time
    print time.clock() - t0C, "seconds process time"

    # measure wall time
    print time.time() - t0, "seconds wall time"


if __name__ == "__main__":
    procedure()

请注意，去除 numpy 依赖可以使脚本在 pypy 上运行。 一些结果（以秒为单位）

对于10个个体
- python: 0.472
- pypy: 0.084
对于100个个体
- python: 49.352
- pypy: 3.256
对于500个个体
- pypy: 80.460
对于1000个个体
- pypy: 318.392