Is it possible to numpy.vectorize an instance method?

Question

I\'ve found that the numpy.vectorize allows one to convert \'ordinary\' functions which expect a single number as input to a function which can also convert a list of inputs

Answer 1

Remembering a technique I saw in the memoized decorator, I managed to get the decorator to also work for instance methods by subclassing numpy.vectorize as follows:

import numpy as np
import functools


class vectorize(np.vectorize):
    def __get__(self, obj, objtype):
        return functools.partial(self.__call__, obj)

Now if I decorate the Dummy class' f method with vectorize instead of np.vectorize, the test passes:

class Dummy(object):
    def __init__(self, val=1):
        self.val = val

    @vectorize
    def f(self, x):
        if x == 0:
            return self.val
        else:
            return 2


def test_3():
    assert list(Dummy().f([0, 1, 2])) == [1, 2, 2]

if __name__ == "__main__":
    pytest.main([__file__])

with output

test_numpy_vectorize.py .

=========================== 1 passed in 0.01 seconds ===========================
[Finished in 0.7s]