I am trying to do the following:
import numpy as np
A = np.array([1,5,2,7,1])
B = np.sort(A)
print B
>>> [1,1,2,5,7]
I want to find the location of all elements in B as in original array A. i.e. I want to create an array C such that
print C
>>[0,4,2,1,3]
which refers to 1 in B being present in A at 0 and 4th location, 5 in B was present in A at 1st location, etc.
I tried using np.where( B == A) but it produces gibberish
import numpy as np
A = np.array([1,5,2,7,1])
print np.argsort(A) #prints [0 4 2 1 3]
If you don't want to imporr numpy for any reason you can also use this code:
a = [1,5,2,7,1]
b = zip(a, range(len(a)))
tmp = sorted(b, key=lambda x: x[0])
c = map( lambda x: x[1], tmp)
print c
[0, 4, 2, 1, 3]
A = [1,5,2,7,1]
for i,e in sorted(enumerate(A), key=lambda x: x[1]):
print(i, e)
B = [x for x,_ in sorted(enumerate(A), key=lambda x: x[1])]
A = sorted(A)
print(A)
print(B)
