comparing a string 1-d numpy array elementwise

Question

I have two 1-d arrays (a and b) containing strings, which I want to compare element wise to get output c like shown below. I tried converting it to set and comparing, however that does not give the correct solution. Also logical_xor does not work for string. I can write a loop to do this but then it defeats the purpose of using arrays, What can be the best way to do this without a loop?

  >>  a
      array(['S', 'S', 'D', 'S', 'N', 'S', 'A', 'S', 'M'], 
          dtype='|S1')
  >>  b
      array(['T', 'I', 'D', 'N', 'G', 'B', 'A', 'J', 'M'], 
          dtype='|S1')

  >> c 
     array([False, False, True, False, False, False, True, False, True], 
      dtype=bool)

Answer 1

Just use the ndarray's __eq__ method, i.e. ==

>>> a = array(['S', 'S', 'D', 'S', 'N', 'S', 'A', 'S', 'M'], dtype='|S1')
>>> b = array(['T', 'I', 'D', 'N', 'G', 'B', 'A', 'J', 'M'], dtype='|S1')
>>> a == b
array([False, False,  True, False, False, False,  True, False,  True], dtype=bool)

Answer 2

You can use numpy.equal :

import numpy as np
c = np.equal(a,b)

Or numpy.core.defchararray.equal :

c = np.core.defchararray.equal(a, b)

EDIT

np.equal has been deprecated in the last numpy's releases and now raises a FutureWarning:

>>> c = np.equal(a,b)
__main__:1: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison
>>> c
NotImplemented

The equality operator == will suffer the same fate as np.equal. So I suggest using:

c = np.array([a == b], dtype=bool)