Can't create COO object if shape parameter is ndarray

When creating a new sparse COO object there is an error if the shape is an ndarray instead of a list.

The error can be encountered as follows:

import numpy as np
import sparse

coords = [[0, 1, 2, 3, 4],

          [0, 1, 2, 3, 4]]

data = [10, 20, 30, 40, 50]

s = sparse.COO(coords, data, shape=np.array((5, 5)))

Which results in the following propt

File "<stdin>", line 1, in <module>
File "path\to\directory\.venv\lib\site-packages\sparse\_coo\core.py", line 244, in __init__
    if shape and not self.coords.size:
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

The error is produced when shape is casted into a bool, if it is a list the result will be False if it’s empty and True in any other situation. For an ndarray the casting is done element by element and thus cannot be evaluated in an if statement.

The solution is just to cast the value of shape into a list before operating with it

System

• Windows 10
• sparse version 0.13.0
• NumPy version 1.21.5
• Numba version 0.55.1

[jakevdp]

For what it’s worth, it looks like scipy.sparse handles shapes specified as arrays:

>>> sparse.coo_matrix(([0], ([0], [0])), shape=np.array([5, 5]))
<5x5 sparse matrix of type '<class 'numpy.int64'>'
	with 1 stored elements in COOrdinate format>

[hameerabbasi]

Ah, I understand. You are looking to use a 1-D array of integers as a shape.

Yes, this is easily fixed. I’m willing to accept a PR, or I can try to do it over the weekend.

Please feel free to ping me if I don’t.