Numpy gcd function

Question

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

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

I have been unable to uncover anything on google other than this link which seems out of date and I don't know how I would access the _gcd function it suggests exists.

Naively trying:

np.gcd
np.euclid

hasn't worked for me...

Answer 1

You can write it yourself:

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

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