Numpy.unique Generates A List Unique In What Regard?

If you input an array with general objects to numpy.unique, the result will be unique based upon what? I have tried: import numpy as np class A(object): #probably exists a nice mi

Solution 1:

Assuming the duplicate A(2) is a typo, I think you simply need to define __hash__ (see the docs):

import numpy as np
from functools import total_ordering

@total_orderingclassA(object):
    def__init__(self, a):
        self.a = a
    def__lt__(self, other):
        return self.a < other.a
    def__eq__(self, other):
        return self.a == other.a
    def__ne__(self, other):
        return self.a != other.a
    def__hash__(self):
        returnhash(self.a)
    def__repr__(self):
        return"A({})".format(self.a)
    def__str__(self):
       returnrepr(self)

produces

>>>map(A, range(3)+range(3))
[A(0), A(1), A(2), A(0), A(1), A(2)]
>>>set(map(A, range(3)+range(3)))
set([A(0), A(1), A(2)])
>>>np.unique(map(A, range(3)+range(3)))
array([A(0), A(1), A(2)], dtype=object)

where I've used total_ordering to reduce the proliferation of methods, as you guessed was possible. :^)

[Edited after posting to correct missing __ne__.]