def test_inverse_inverse():
link = tf.Translation((1, 0), amount=0.5)
inv_link = tf.InvertLink(link)
inverse_inverse = tf.InvertLink(inv_link)
point = (3, 5)
result = inverse_inverse.transform(point)
expected = link.transform(point)
assert np.allclose(result, expected)
def test_keep_joints():
points = np.arange(200 * 3).reshape(200, 3)
joint1 = tf.RotationalJoint((0, 1, 0))
joint2 = tf.PrismaticJoint((1, 0, 0))
links: List[tf.Link] = [
tf.Rotation((1, 0, 0), (0, 1, 0)),
tf.Translation((1, 0, 0)),
joint1,
tf.Translation((1, 1, 0)),
tf.Translation((1, 1, 1)),
tf.InvertLink(joint2),
]
simplified_links = tf.simplify_links(links, keep_joints=True)
expected = points
for link in links:
expected = link.transform(expected)
result = points
for link in simplified_links:
result = link.transform(result)
assert np.allclose(result, expected)
assert joint1 in simplified_links
assert joint2 is simplified_links[-1]._forward_link
def test_inverse_links():
points = np.arange(200 * 3).reshape(200, 3)
# --- test double_inverse ---
link = tf.InvertLink(tf.InvertLink(tf.Translation((1, 0, 0))))
simplified = tf.simplify_links([link])[0]
assert isinstance(simplified, tf.Translation)
expected = link.transform(points)
result = simplified.transform(points)
assert np.allclose(result, expected)
# --- test translation unwrapping ---
link = tf.InvertLink(tf.Translation((1, 0, 0)))
simplified = tf.simplify_links([link])[0]
assert isinstance(simplified, tf.Translation)
expected = link.transform(points)
result = simplified.transform(points)
assert np.allclose(result, expected)
# --- test rotation unwrapping ---
link = tf.InvertLink(tf.EulerRotation("X", np.pi / 2))
simplified = tf.simplify_links([link])[0]
assert isinstance(simplified, tf.Rotation)
expected = link.transform(points)
result = simplified.transform(points)
assert np.allclose(result, expected)
# --- test compound unpacking ---
link = tf.InvertLink(
tf.CompundLink([tf.Translation((1, 0, 0)),
tf.Translation((0, 1, 0))]))
simplified_links = tf.simplify_links([link])
expected = link.transform(points)
result = points
for link in simplified_links:
result = link.transform(result)
assert np.allclose(result, expected)
for link in simplified_links:
assert isinstance(link, tf.Translation)
def test_keep_link():
points = np.arange(200 * 3).reshape(200, 3)
keep_link = tf.Translation((0, 1, 0))
link = tf.CompundLink([
tf.Translation((1, 0, 0)),
tf.CompundLink([keep_link]),
tf.EulerRotation("Y", -90, degrees=True),
])
simplified_links = tf.simplify_links([link], keep_links=[keep_link])
assert keep_link in simplified_links
expected = link.transform(points)
result = points
for link in simplified_links:
result = link.transform(result)
assert np.allclose(result, expected)
keep_link = tf.Translation((0, 1, 0))
original_link = tf.CompundLink([
tf.Translation((1, 0, 0)),
tf.CompundLink([tf.InvertLink(keep_link)]),
tf.EulerRotation("Y", -90, degrees=True),
])
simplified_links = tf.simplify_links([original_link],
keep_links=[keep_link])
for link in simplified_links:
if isinstance(link, tf.InvertLink):
if link._forward_link is keep_link:
break
else:
raise AssertionError("`keep_link` no longer in link chain.")
expected = original_link.transform(points)
result = points
for link in simplified_links:
result = link.transform(result)
assert np.allclose(result, expected)
keep_link = tf.Translation((0, 1, 0))
original_link = tf.CompundLink([
tf.Translation((1, 0, 0)),
tf.Translation((1, 1, 0)),
keep_link,
tf.EulerRotation("Y", -90, degrees=True),
])
simplified_links = tf.simplify_links([original_link],
keep_links=[keep_link])
assert keep_link in simplified_links
expected = original_link.transform(points)
result = points
for link in simplified_links:
result = link.transform(result)
assert np.allclose(result, expected)
def test_inverted_custom_link():
class Custom(tf.Link):
def transform(self, x: ArrayLike) -> np.ndarray:
return x
def __inverse_transform__(self, x: ArrayLike) -> np.ndarray:
return x
points = np.arange(200 * 3).reshape(200, 3)
link = tf.InvertLink(Custom(3, 3))
simplified_links = tf.simplify_links([link])
expected = link.transform(points)
result = points
for link in simplified_links:
result = link.transform(result)
assert np.allclose(result, expected)
def test_joints_between():
joint1 = tf.RotationalJoint((0, 1, 0))
joint2 = tf.PrismaticJoint((1, 0, 0))
start = tf.Frame(3)
x = tf.Rotation((1, 0, 0), (0, 1, 0))(start)
x = tf.Translation((1, 0, 0))(x)
x = joint1(x)
x = tf.CompundLink(
[joint2,
tf.EulerRotation("xy", (90, -90), degrees=True), joint1])(x)
x = tf.Translation((1, 1, 0))(x)
x = tf.Translation((1, 1, 1))(x)
end = tf.InvertLink(joint2)(x)
joints = start.joints_between(end)
assert joints == [joint1, joint2, joint1, joint2]
# # tf.AxialHexagonTransform() # tf.AxialHexagonTransform(size=4) # a hex grid with larger hexagons # tf.AxialHexagonTransform(flat_top=False) # a hex grid that is rotated by 90 degrees # # When you use this transformation, the result will be a continous value, which # is useful because it keeps all information and can be inverted to go back to # cartesian coordinates. However, often you want to know which hexagon a # coordinate falls into, which is where :class:`tf.HexagonAxisRound # <skbot.transform.HexagonAxisRound>` comes in. As the name suggests, it will # round a vector in hexagon coordinates to the closest hexagon. # # We can use this, for example, to perform rejection sampling on the hexagon grid: to_hex = tf.AxialHexagonTransform() from_hex = tf.InvertLink(to_hex) # a 3x3 hex grid (because we can use a nice colormap in this case) grid = np.stack(np.meshgrid(np.arange(3), np.arange(3)), axis=-1) hex_centers = from_hex.transform(grid) sampling_rectangle = [-1, -1, 7, 5] x, y, w, h = [-1, -1, 7, 5] candidate_points = np.random.rand(150, 2) * (h, w) + (y, x) hex_points = to_hex.transform(candidate_points) hex_points_rounded = tf.HexagonAxisRound().transform(hex_points) is_in_hexagon = np.all(np.isin(hex_points_rounded, [0, 1, 2]), axis=1) points = candidate_points[is_in_hexagon, :] # points are rejected here # %% # We can also use :class:`tf.HexagonAxisRound
def test_inverse_attributes():
link = tf.Translation((1, 0), amount=0.5)
inv_link = tf.InvertLink(link)
hasattr(inv_link, "amount")
assert inv_link.amount == 0.5