Use cases of `numpy.positive`

Question

There is a positive function in numpy (version 1.13+), which seemingly does nothing:

In [1]: import numpy as np                                                                               

In [2]: A = np.array([0, 1, -1, 1j, -1j, 1+1j, 1-1j, -1+1j, -1-1j, np.inf, -np.inf])                     

In [3]: A == np.positive(A)                                                                              
Out[3]: 
array([ True,  True,  True,  True,  True,  True,  True,  True,  True,
        True,  True])

The documentation says: Returned array or scalar: `y = +x`

What are the use cases of this function?

Answer 1

There are likely very few use-cases for this function. It is provided because every python operator is exposed as a ufunc in numpy:

• Unary +: np.positive
• Unary -: np.negative
• Binary +: np.add
• Binary -: np.subtract
• etc ...

As the documentation states, and noted in the other answer, np.positive makes a copy of the data, just as np.copy does, but with two caveats:

1. It can change the dtype of the input

2. It is only defined for arithmetic types. If you attempt to call it on a boolean array, for example, you will get

    UFuncTypeError: ufunc 'positive' did not contain a loop with signature matching types dtype('bool') -> dtype('bool')
   

One other thing, is that since positive is a ufunc, it can work in-place, making it an effective no-op function for arithmetic types:

np.positive(x, out=x)