NumPy: create ndarray of objects-CodePudding

I like to create a numpy array -- with a shape, say [2, 3], where each array element is a list. Yes, I know this isn't efficient, or even desirable, and all the good reasons for that -- but can it be done?

So I want a 2x3 array where each point is a length 2 vector, not a 2x3x2 array. Yes, really.

If I fudge it by making it ragged, it works:

>>> np.array([[0, 0], [0, 1], [0, 2], [1, 0], [9, 8], [2, 4, -1]], dtype=object).reshape([2, 3])
array([[list([0, 0]), list([0, 1]), list([0, 2])],
       [list([1, 0]), list([9, 8]), list([2, 4, -1])]], dtype=object)

but if numpy can make it fit cleanly, it does so, and so throws an error:

>>> np.array([[0, 0], [0, 1], [0, 2], [1, 0], [9, 8], [2, 4]], dtype=object).reshape([2, 3])
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: cannot reshape array of size 12 into shape (2,3)

So putting aside your instincts that this is a silly thing to want to do (it is, and I know this), can I make the last example work somehow to create a shape 2x3 array where each element is a Python list of length 2, without numpy forcing it into 2x3x2?

CodePudding user response：

First, you should create an object array with expected shape.

Then, use list to fill the array.

l = [[[0, 0], [0, 1], [0, 2]], [[1, 0], [9, 8], [2, 4]]]
arr = np.empty((2, 3), dtype=object)
arr[:] = l

CodePudding user response：

You can create an empty array and fill it with objects manually:

>>> a = np.empty((3,2), dtype=object)
>>> a
array([[None, None],
       [None, None],
       [None, None]], dtype=object)
>>> a[0,0] = [1,2,3]
>>> a
array([[list([1, 2, 3]), None],
       [None, None],
       [None, None]], dtype=object)