擅长:python、mysql、java
<p>另一种方法:用numba生成一个通用的UFunc</p>
<pre><code>@numba.guvectorize(["void(float64[:], float64[:], float64[:])"], "(n),(n)->()", target='parallel')
def fast_cosine_gufunc(u, v, result):
m = u.shape[0]
udotv = 0
u_norm = 0
v_norm = 0
for i in range(m):
if (np.isnan(u[i])) or (np.isnan(v[i])):
continue
udotv += u[i] * v[i]
u_norm += u[i] * u[i]
v_norm += v[i] * v[i]
u_norm = np.sqrt(u_norm)
v_norm = np.sqrt(v_norm)
if (u_norm == 0) or (v_norm == 0):
ratio = 1.0
else:
ratio = udotv / (u_norm * v_norm)
result[:] = ratio
u = np.random.rand(100)
M = np.random.rand(100000, 100)
fast_cosine_gufunc(u, M[0,:])
fast_cosine_gufunc(u, M)
</code></pre>