UFuncTypeError with comparison between numpy.arrays

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I am trying to achieve a comparison between arrays using the np.equal() -I cannot use == because I want to create some sort of a dynamic list of conditions to put as an argument in the np.select().

However, it seems that there is a problem with the types of data and the comparison does not work. Here is a piece of code:

a = np.full((2,3), 'C', dtype='<U5')
b = np.array([['C', 'B', 'A'], ['B', 'C', 'C']], dtype='<U5')
display(a.shape, b.shape)
display(a.dtype, b.dtype)
np.equal(a, b)

>>>
(2, 3)
(2, 3)
dtype('<U5')
dtype('<U5')
---------------------------------------------------------------------------
UFuncTypeError                            Traceback (most recent call last)
Input In [17], in <cell line: 5>()
      3 display(a.shape, b.shape)
      4 display(a.dtype, b.dtype)
----> 5 np.equal(a, b)

UFuncTypeError: ufunc 'equal' did not contain a loop with signature matching types (<class 'numpy.dtype[str_]'>, <class 'numpy.dtype[str_]'>) -> None

Is there a work-around to achieve what I need?

dtype numpy arrays python comparison
1 Answers

With credits to @cromod who has posted a thorough response to this question, the following seemed to work just fine:

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

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

I guess it has something to do with the fact that the elements of the arrays are not numeric values but string values.

user_107505410
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