Repeat elements from one array based on another - numpy

Question

Given
a = np.array([1,2,3,4,5,6,7,8])
b = np.array(['a','b','c','d','e','f','g','h'])
c = np.array([1,1,1,4,4,4,8,8])
where a & b 'correspond' to each other, how can I use c to slice b to get d which 'corresponds' to c:
d = np.array(['a','a','a','d','d','d','h','h')]
I know how to do this by looping
for n in range(a.shape[0]):
d[n] = b[np.argmax(a==c[n])]
but want to know if I can do this without loops.
Thanks in advance!

Answer 1

With the a that is just position+1 you can simply use
In [33]: b[c - 1]
Out[33]: array(['a', 'a', 'a', 'd', 'd', 'd', 'h', 'h'], dtype='<U1')
I'm tempted to leave it at that, since the a example isn't enough to distinguish it from the argmax approach.
But we can test all a against all c with:
In [36]: a[:,None]==c
Out[36]:
array([[ True, True, True, False, False, False, False, False],
[False, False, False, False, False, False, False, False],
[False, False, False, False, False, False, False, False],
[False, False, False, True, True, True, False, False],
[False, False, False, False, False, False, False, False],
[False, False, False, False, False, False, False, False],
[False, False, False, False, False, False, False, False],
[False, False, False, False, False, False, True, True]])
In [37]: (a[:,None]==c).argmax(axis=0)
Out[37]: array([0, 0, 0, 3, 3, 3, 7, 7])
In [38]: b[_]
Out[38]: array(['a', 'a', 'a', 'd', 'd', 'd', 'h', 'h'], dtype='<U1')