Apply function over numpy arrays without looping

Question

1. So we can do this in with numpy arrays:

   IN:
    a = np.array([1,2,3])
    b = np.array([[1,2,3], [1,2,4], [1,2,5]])
    a+b
   OUT:
     array([[2, 4, 6],
            [2, 4, 7],
            [2, 4, 8]])
   

2. I have this function, where di and dj are lists or arrays of the same lenght and KL is scipy.stats.entropy

   def dis(di,dj):
       di = np.array(di)
       dj = np.array(dj)
       m =  0.5 * (di+dj)
       kl1 = KL(di,m)
       kl2 = KL(dj,m)
       return 0.5*(kl1+kl2)
   

3. I was wondering if there was a way to apply the function as with a+b:

   dis(a,b) 
   

So instead of doing:

 for x in b:
     dis(a,x)

I am getting this error when trying to run:

    dis(a,b)

UPDATE After resolving the error thanks to hpaulj suggestion I get the following result: Result 2

The problem with the result is that KL should only give positive values. So I don't get quiet well what does: dis(a,b) is actually doing.