numpy gcd功能 [英] Numpy gcd function

问题描述

numpy在其模块结构的某处是否具有gcd功能?

Does numpy have a gcd function somewhere in its structure of modules?

我知道fractions.gcd，但认为numpy等效项可能更快并且可以更好地与numpy数据类型一起使用.

I'm aware of fractions.gcd but thought a numpy equivalent maybe potentially quicker and work better with numpy datatypes.

除了这个链接似乎已过时，我不知道如何访问它暗示存在的_gcd函数.

I have been unable to uncover anything on google other than this link which seems out of date and I don't know how I would access the _gcd function it suggests exists.

天真地尝试:

np.gcd
np.euclid

不是为我工作...

推荐答案

您可以自己编写:

def numpy_gcd(a, b):
    a, b = np.broadcast_arrays(a, b)
    a = a.copy()
    b = b.copy()
    pos = np.nonzero(b)[0]
    while len(pos) > 0:
        b2 = b[pos]
        a[pos], b[pos] = b2, a[pos] % b2
        pos = pos[b[pos]!=0]
    return a

以下是测试结果和速度的代码:

Here is the code to test the result and speed:

In [181]:
n = 2000
a = np.random.randint(100, 1000, n)
b = np.random.randint(1, 100, n)
al = a.tolist()
bl = b.tolist()
cl = zip(al, bl)
from fractions import gcd
g1 = numpy_gcd(a, b)
g2 = [gcd(x, y) for x, y in cl]
print np.all(g1 == g2)

True

In [182]:
%timeit numpy_gcd(a, b)

1000 loops, best of 3: 721 us per loop

In [183]:
%timeit [gcd(x, y) for x, y in cl]

1000 loops, best of 3: 1.64 ms per loop

这篇关于numpy gcd功能的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！