从集合中创建 numpy 数组

Question

I noticed the following behaviour exhibited by numpy arrays:

>>> import numpy as np
>>> s = {1,2,3}
>>> l = [1,2,3]
>>> np.array(l)
array([1, 2, 3])
>>> np.array(s)
array({1, 2, 3}, dtype=object)
>>> np.array(l, dtype='int')
array([1, 2, 3])
>>> np.array(l, dtype='int').dtype
dtype('int64')
>>> np.array(s, dtype='int')
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: int() argument must be a string, a bytes-like object or a number, not 'set'

There are 2 things to notice:

1. Creating an array from a set results in the array dtype being object
2. Trying to specify dtype results in an error which suggests that the set is being treated as a single element rather than an iterable.

What am I missing - I don't fully understand which bit of python I'm overlooking. Set is a mutable object much like a list is.

EDIT: tuples work fine:

>>> t = (1,2,3)
>>> np.array(t)
array([1, 2, 3])
>>> np.array(t).dtype
dtype('int64')

Answer 1

The array factory works best with sequence objects which a set is not. If you do not care about the order of elements and know they are all ints or convertible to int, then you can use np.fromiter

np.fromiter({1,2,3},int,3)
# array([1, 2, 3])

The second (dtype) argument is mandatory; the last (count) argument is optional, providing it can improve performance.

Answer 2

As you can see from the syntax of using curly brackets, a set are more closely related to a dict than to a list . You can solve it very simply by turning the set into a list or tuple before converting to an array:

>>> import numpy as np
>>> s = {1,2,3}
>>> np.array(s)
array({1, 2, 3}, dtype=object)
>>> np.array(list(s))
array([1, 2, 3])
>>> np.array(tuple(s))
array([1, 2, 3])

However this might be too inefficient for large sets, because the list or tuple functions have to run through the whole set before even starting the creation of the array. A better method would be to use the set as an iterator:

>>> np.fromiter(s, int)
array([1, 2, 3])

Answer 3

The np.array documentation says that the object argument must be "an array, any object exposing the array interface, an object whose __array__ method returns an array, or any (nested) sequence " (emphasis added).

A set is not a sequence . Specifically, sets are unordered and do not support the __getitem__ method. Hence you cannot create an array from a set like you trying to with the list.

Answer 4

Numpy expects the argument to be a list, it doesn't understand the set type so it creates an object array (this would be the same if you passed any other non sequence object). You can create a numpy array with a set by first converting the set to a list numpy.array(list(my_set)) . Hope this helps.