Constructing a Python set from a Numpy matrix

Question

I\'m trying to execute the following

>> from numpy import *
>> x = array([[3,2,3],[4,4,4]])
>> y = set(x)
TypeError: unhashable type: \'num         


        

Answer 1

I liked xperroni's idea. But I think implementation can be simplified using direct inheritance from ndarray instead of wrapping it.

from hashlib import sha1
from numpy import ndarray, uint8, array

class HashableNdarray(ndarray):
    def __hash__(self):
        if not hasattr(hasattr, '__hash'):
            self.__hash = int(sha1(self.view(uint8)).hexdigest(), 16)
        return self.__hash

    def __eq__(self, other):
        if not isinstance(other, HashableNdarray):
            return super(HashableNdarray, self).__eq__(other)
        return super(HashableNdarray, self).__eq__(super(HashableNdarray, other)).all()

NumPy ndarray can be viewed as derived class and used as hashable object. view(ndarray) can be used for back transformation, but it is not even needed in most cases.

>>> a = array([1,2,3])
>>> b = array([2,3,4])
>>> c = array([1,2,3])
>>> s = set()

>>> s.add(a.view(HashableNdarray))
>>> s.add(b.view(HashableNdarray))
>>> s.add(c.view(HashableNdarray))
>>> print(s)
{HashableNdarray([2, 3, 4]), HashableNdarray([1, 2, 3])}
>>> d = next(iter(s))
>>> print(d == a)
[False False False]
>>> import ctypes
>>> print(d.ctypes.data_as(ctypes.POINTER(ctypes.c_double)))
<__main__.LP_c_double object at 0x7f99f4dbe488>