Numpy comparing vectors of length m and n resulting in boolean matrix of size m,n

I am wondering if there is a more efficient way to run the comparison (or really many other functions) using numpy.

a = np.array([1,2,5,7])
b = np.array([0,4,6])

np.repeat(a, len(b)).reshape(-1, len(b)) > b

> array([[ True, False, False],
       [ True, False, False],
       [ True,  True, False],
       [ True,  True,  True]])

Basically each output (m, n) is the comparison if A_m > B_n

>Solution :

You can use broadcasting to make this operation more efficient. Indeed, repeat creates a new temporary array. Here is the resulting code:

a.reshape(-1, 1) > b