Nov-22-2019, 06:25 AM
It depends on
vector arguments (however, it is just a for-loop).
version of your function (
some_function
. In any case, you can use numpy.vectorize
decorator. It turns your function in another which acceptvector arguments (however, it is just a for-loop).
import numpy as np @np.vectorize def some_function(k): pass A = some_function(np.arange(1, N-1)) * some_array[1:-1]Another option would be considering using of numba.jit (JIT-compiler) and implement vectorized
version of your function (
some_function
).