Polytope's is_valid possibly not working as intended

[CharlesArnal]

Hello,

If I am not mistaken, the following code snippet describes a valid polytope and non-valid triangulation, but raises no exception from triangulate (which in turns calls is_valid):

triangulation = np.array([[0, 8, 9, 1, 10]])
vertices = np.array([
    [0, 0, 0, 0],
    [-1, 0, -1, 0],
    [-1, 0, -1, 2],
    [-1, 0, 0, 1],
    [-1, 1, -1, 0],
    [-1, 1, -1, 1],
    [0, 0, -1, 0],
    [1, -1, 1, -1],
    [1, -1, 1, 0],
    [1, 0, 1, -1],
    [-1, 0, -1, 1]
])
p = Polytope(vertices)
t = p.triangulate(simplices=triangulation, check_input_simplices = True)
print(t)

The output is:

A non-fine, star triangulation of a 4-dimensional point configuration with 11 points in ZZ^4

I am new to the library and I might have made a dumb mistake, in which case I apologize.

Assuming that there is indeed a problem, do you know under which conditions I can trust that a triangulation that is described as fine, star and regular is actually fine, star and regular ?

[ariostas]

I think there was a related issue fixed some time ago. @natemacfadden could you check if this is still an issue?

[natemacfadden]

It is still an issue, but I believe I have fixed the bug - just running through checks now. If simps.shape[0] == 1, then Triangulation.is_valid() would return True without further checks. That is the case here, since simps = np.array([[0, 8, 9, 1, 10]]).

[natemacfadden]

This commit should fix it