def test_convex_hull_invalid_min_separation():
x = [0.0, 10.0, 10.0, 5.0, 0.0, 0.0]
y = [0.0, 0.0, 10.0, 11.0, 10.0, 0.0]
with pytest.raises(ValueError) as e:
convex_hull(x, y, min_separation=-1)
assert (
e.value.args[0] == "'min_separation' must be non-negative or None.")
def test_convex_hull_adjacent():
x = [0.0, 10.0, 10.0, 5.001, 5.0, 0.0, 0.0]
y = [0.0, 0.0, 10.0, 11.000001, 11.0, 10.0, 0.0]
xc, yc = convex_hull(x, y, min_separation=None)
assert np.allclose([x, y], [xc, yc], rtol=0, atol=1e-14)
xc, yc = convex_hull(x, y, min_separation=1e-2)
x.pop(3)
y.pop(3)
assert np.allclose([x, y], [xc, yc], rtol=0, atol=1e-14)
def test_wcsrefcat_convex_hull(mock_fits_wcs):
ref = RefCatalog(None)
ref._calc_cat_convex_hull() # catalog is None
assert convex_hull([], []) == ([], [])
assert all(
isinstance(x, np.ndarray) and x.size == 0
for x in convex_hull(np.array([]), np.array([])))
assert convex_hull([123], [456]) == ([123], [456])
x = [0, 0, 10, 10]
y = [0, 10, 10, 0]
xc, yc = convex_hull(x + [10, 3, 6, 7], y + [0, 5, 1, 8])
assert set(xc) == set(x) and set(yc) == set(y)
xc, yc = convex_hull(np.array(x + [3, 6, 7]), np.array(y + [5, 1, 8]))
assert set(xc) == set(x) and set(yc) == set(y)
xc, yc = convex_hull(x + [3, 6, 7], y + [5, 1, 8], lambda x, y: (x, y))
assert set(xc) == set(x) and set(yc) == set(y)
xc, yc = convex_hull(np.array(x + [3, 6, 7]), np.array(y + [5, 1, 8]),
lambda x, y: (x, y))
assert set(xc) == set(x) and set(yc) == set(y)