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

The above answers work if you want to create a set out of the elements contained in an ndarray, but if you want to create a set of ndarray objects – or use ndarray objects as keys in a dictionary – then you'll have to provide a hashable wrapper for them. See the code below for a simple example:

from hashlib import sha1

from numpy import all, array, uint8


class hashable(object):
    r'''Hashable wrapper for ndarray objects.

        Instances of ndarray are not hashable, meaning they cannot be added to
        sets, nor used as keys in dictionaries. This is by design - ndarray
        objects are mutable, and therefore cannot reliably implement the
        __hash__() method.

        The hashable class allows a way around this limitation. It implements
        the required methods for hashable objects in terms of an encapsulated
        ndarray object. This can be either a copied instance (which is safer)
        or the original object (which requires the user to be careful enough
        not to modify it).
    '''
    def __init__(self, wrapped, tight=False):
        r'''Creates a new hashable object encapsulating an ndarray.

            wrapped
                The wrapped ndarray.

            tight
                Optional. If True, a copy of the input ndaray is created.
                Defaults to False.
        '''
        self.__tight = tight
        self.__wrapped = array(wrapped) if tight else wrapped
        self.__hash = int(sha1(wrapped.view(uint8)).hexdigest(), 16)

    def __eq__(self, other):
        return all(self.__wrapped == other.__wrapped)

    def __hash__(self):
        return self.__hash

    def unwrap(self):
        r'''Returns the encapsulated ndarray.

            If the wrapper is "tight", a copy of the encapsulated ndarray is
            returned. Otherwise, the encapsulated ndarray itself is returned.
        '''
        if self.__tight:
            return array(self.__wrapped)

        return self.__wrapped

Using the wrapper class is simple enough:

>>> from numpy import arange

>>> a = arange(0, 1024)
>>> d = {}
>>> d[a] = 'foo'
Traceback (most recent call last):
  File "", line 1, in 
TypeError: unhashable type: 'numpy.ndarray'
>>> b = hashable(a)
>>> d[b] = 'bar'
>>> d[b]
'bar'