Constructing a python set from a numpy matrix

I'm trying to execute the following

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

How can I easily and efficiently create a set from a numpy array?

From stackoverflow

• The immutable counterpart to an array is the tuple, hence, try convert the array of arrays into an array of tuples:

  >> from numpy import *
  >> x = array([[3,2,3],[4,4,4]])
  
  >> x_hashable = map(tuple, x)
  
  >> y = set(x_hashable)
  set([(3, 2, 3), (4, 4, 4)])
  

• If you want a set of the elements:

  >> y = set(e for r in x
               for e in r)
  set([2, 3, 4])
  

  For a set of the rows:

  >> y = set(tuple(r) for r in x)
  set([(3, 2, 3), (4, 4, 4)])
  

• If you want a set of the elements, here is another, probably faster way:

  y = set(x.flatten())
  

  PS: after performing comparisons between x.flat, x.flatten(), and x.ravel() on a 10x100 array, I found out that they all perform at the same speed. For a 3x3 array, the fastest version is the iterator version:

  y = set(x.flat)
  

  which I would recommend because it is the less memory expensive version (it scales up well with the size of the array).

  : Good suggestion! You could also use set(x.ravel()), which does the same thing but creates a copy only if needed. Or, better, use set(x.flat). x.flat is an iterator over the elements of the flattened array, but does not waste time actually flattening the array

  EOL : @musicinmybrain: very good points! Thank you!