应该接近0.3
$ cat monte.py
import random,math
density=int(1e6)
x = [random.uniform(0,1)*7*math.pi for _ in range(density)]
y = [random.uniform(0,1) for _ in range(density)]
i = [math.sin(xx)*math.cos(xx) > yy for (xx,yy) in zip(x,y)]
print sum(i)/(float(density)*10.0)*7*math.pi
$ python monte.py
0.350184850795
我正在尝试重写下面的内容,但由于某种原因,python代码甚至没有关闭。
x = rand(1, 1000000)*7pi;
y = rand(1, 1000000);
i = sin(x).* cos(x) >y;
Area3 = (sum(i) / 10000000)*7pi;
答案 0 :(得分:2)
我在你的matlab和python版本之间得到相同的结果......你确定matlab版本给你~2,而不是~0.35?
例如:
MATLAB:
x = rand(1, 1000000)*7*pi;
y = rand(1, 1000000);
i = sin(x).* cos(x) >y;
Area3 = (sum(i) / 10000000)*7*pi
这会产生:0.3511
你的纯python版本:
import random,math
density=int(1e6)
x = [random.uniform(0,1)*7*math.pi for _ in range(density)]
y = [random.uniform(0,1) for _ in range(density)]
i = [math.sin(xx)*math.cos(xx) > yy for (xx,yy) in zip(x,y)]
print sum(i)/(float(density)*10.0)*7*math.pi
这会产生:0.347935156296
numpy的基:
import numpy as np
x = np.random.random(1e6) * 7 * np.pi
y = np.random.random(x.size)
i = np.sin(x) * np.cos(x) > y
print 7 * np.pi * i.sum() / (10 * x.size)
这会产生:0.350475133957