Add post_pos as a model target via travel_dir decomposition

step_length already encodes |post_pos - pre_pos| by definition, so a raw
post_pos target would duplicate that magnitude and could drift inconsistent
with step_length during sampling. Instead add travel_dir, a unit vector
(local frame) giving only the direction of pre_pos->post_pos; post_pos is
reconstructed at inference as pre_pos + step_length * travel_dir, keeping
the two self-consistent. Target grows from 6D to 9D.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
2026-06-18 10:36:55 +02:00
parent c3b7b2744c
commit 72bd65ff9f
11 changed files with 121 additions and 17 deletions
+54
View File
@@ -5,6 +5,8 @@ from giant.data.transforms import (
local_frame_rotation,
log_transform,
Normalizer,
reconstruct_post_pos,
travel_direction,
)
@@ -50,6 +52,58 @@ def test_local_frame_rotation_preserves_norm():
np.testing.assert_allclose(np.linalg.norm(result, axis=1), 1.0, atol=1e-5)
def test_travel_direction_is_unit_norm():
rng = np.random.default_rng(5)
N = 50
pre_pos = rng.standard_normal((N, 3)).astype(np.float32)
post_pos = pre_pos + rng.standard_normal((N, 3)).astype(np.float32)
result = travel_direction(pre_pos, post_pos)
np.testing.assert_allclose(np.linalg.norm(result, axis=1), 1.0, atol=1e-5)
def test_travel_direction_matches_normalized_displacement():
rng = np.random.default_rng(6)
N = 50
pre_pos = rng.standard_normal((N, 3)).astype(np.float32)
disp = rng.standard_normal((N, 3)).astype(np.float32)
post_pos = pre_pos + disp
expected = disp / np.linalg.norm(disp, axis=1, keepdims=True)
np.testing.assert_allclose(travel_direction(pre_pos, post_pos), expected, atol=1e-5)
def test_reconstruct_post_pos_straight_line():
"""When post_pos = pre_pos + L * pre_dir, travel_dir equals pre_dir, so its
local-frame encoding is ẑ — reconstruction must recover post_pos exactly."""
rng = np.random.default_rng(7)
N = 20
pre_pos = rng.standard_normal((N, 3)).astype(np.float32)
pre_dir = rng.standard_normal((N, 3)).astype(np.float32)
pre_dir /= np.linalg.norm(pre_dir, axis=1, keepdims=True)
step_length = rng.uniform(0.1, 5.0, size=N).astype(np.float32)
post_pos = pre_pos + step_length[:, None] * pre_dir
travel_dir_local = local_frame_rotation(pre_dir, travel_direction(pre_pos, post_pos))
np.testing.assert_allclose(travel_dir_local, np.tile([0, 0, 1], (N, 1)), atol=1e-4)
reconstructed = reconstruct_post_pos(pre_pos, pre_dir, step_length, travel_dir_local)
np.testing.assert_allclose(reconstructed, post_pos, atol=1e-4)
def test_reconstruct_post_pos_general_roundtrip():
"""Full encode (build_features-style) -> decode (cli.py predict-style) path."""
rng = np.random.default_rng(8)
N = 100
pre_pos = rng.standard_normal((N, 3)).astype(np.float32)
pre_dir = rng.standard_normal((N, 3)).astype(np.float32)
pre_dir /= np.linalg.norm(pre_dir, axis=1, keepdims=True)
post_pos = pre_pos + rng.standard_normal((N, 3)).astype(np.float32)
step_length = np.linalg.norm(post_pos - pre_pos, axis=1).astype(np.float32)
travel_dir_local = local_frame_rotation(pre_dir, travel_direction(pre_pos, post_pos))
reconstructed = reconstruct_post_pos(pre_pos, pre_dir, step_length, travel_dir_local)
np.testing.assert_allclose(reconstructed, post_pos, atol=1e-4)
def test_normalizer_roundtrip():
rng = np.random.default_rng(3)
X = rng.standard_normal((200, 9)).astype(np.float32)