def test_closest():
# Unfinished test
a = gm.Vector2d(1, 2)
ops = []
for i in range(100):
ops.append(gm.Vector2d(random.randint(0, 100), random.randint(0, 100)))
winner = gm.closest(a, ops)
def test_look():
a = gm.Vector2d(1, 2)
b = gm.Vector2d(2, 3)
normal = gm.look(a, b)
assert_true(-1 <= normal.x <= 1, normal.x)
assert_true(-1 <= normal.y <= 1, normal.y)
assert_equal(round(normal.length), 1, normal.length)
def test_scalar():
a = gm.Vector2d(1, 2)
c = a * 5
assert_equal(c, gm.Vector2d(5, 10))
assert_equal(c.length, a.length * 5)
a = gm.Vector2d(10, 20)
c = a / 5
assert_equal(c, gm.Vector2d(2.0, 4.0))
assert_equal(c.length, a.length / 5)
def test_lerp():
start = gm.Vector2d(0, 1.)
goal = gm.Vector2d(100, 100)
def approach(steps):
move = gm.lerp(goal, start, gm.delta_time())
while steps:
move = gm.lerp(goal, move, gm.delta_time())
steps -= 1
return move
current = approach(5)
assert_not_equal(current, start)
assert current.length_comparison > start.length_comparison
start, goal = goal, start
current = approach(5)
assert_not_equal(current, start)
assert current.length_comparison > start.length_comparison
def test_subtraction():
a = gm.Vector2d(1, 2)
b = gm.Vector2d(2, 3)
c = a - b
assert_equal(c, gm.Vector2d(-1, -1))
def test_addition():
a = gm.Vector2d(1, 2)
b = gm.Vector2d(2, 3)
c = a + b
assert_equal(c, gm.Vector2d(3, 5))