I am using python 3 with numpy, it seems that numpy operations are using all my cores well, but when I use a function with np.vectorize like so for instance:
f = lambda x: (x*1000) / 20 * 15 + 3
v_func = np.vectorize(f)
v_func(arr)
It uses only one core for a long time (according to the cpu utilization chart).
How can I use it with numpy's multi core capabilities?