lars
9277d79dff
- Data pipeline: loader (parquet→numpy), transforms (log, local-frame Rodrigues rotation, Normalizer), StepsDataset with event-ID-based split - Model: SinusoidalEmbedding, ConditionEncoder, ResBlock, DenoisingMLP - Schedule: cosine DDPM and conditional flow matching loss (Lipman 2022) - Samplers: flow (Euler ODE), DDPM ancestral, DDIM deterministic - Training loop: AdamW + cosine LR, grad clipping, best-val checkpoint - Validation: per-dimension marginal summary (normalised space) - CLI: TOML config support with CLI-overrides; hyperparam-encoded output directory; config.toml with git hash saved into each run's checkpoint dir - 21 unit tests covering transforms, network, flow/DDPM losses, dataset splits Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
67 lines
2.4 KiB
Python
67 lines
2.4 KiB
Python
import numpy as np
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import pytest
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from giant.data.transforms import (
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inv_log_transform,
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local_frame_rotation,
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log_transform,
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Normalizer,
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)
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def test_log_transform_invertible():
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x = np.array([0.1, 1.0, 10.0, 1000.0], dtype=np.float32)
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np.testing.assert_allclose(inv_log_transform(log_transform(x)), x, rtol=1e-5)
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def test_local_frame_rotation_noop_when_aligned():
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N = 8
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pre_dir = np.tile([0.0, 0.0, 1.0], (N, 1)).astype(np.float32)
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rng = np.random.default_rng(0)
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post_dir = rng.standard_normal((N, 3)).astype(np.float32)
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post_dir /= np.linalg.norm(post_dir, axis=1, keepdims=True)
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result = local_frame_rotation(pre_dir, post_dir)
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np.testing.assert_allclose(result, post_dir, atol=1e-5)
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def test_local_frame_rotation_preserves_angle():
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"""Angle between pre_dir and post_dir must equal angle between ẑ and rotated."""
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rng = np.random.default_rng(1)
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N = 200
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pre_dir = rng.standard_normal((N, 3)).astype(np.float32)
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pre_dir /= np.linalg.norm(pre_dir, axis=1, keepdims=True)
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post_dir = rng.standard_normal((N, 3)).astype(np.float32)
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post_dir /= np.linalg.norm(post_dir, axis=1, keepdims=True)
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rotated = local_frame_rotation(pre_dir, post_dir)
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cos_before = (pre_dir * post_dir).sum(axis=1)
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cos_after = rotated[:, 2] # dot with ẑ = z-component (unit vectors)
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np.testing.assert_allclose(cos_after, cos_before, atol=1e-5)
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def test_local_frame_rotation_preserves_norm():
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rng = np.random.default_rng(2)
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N = 100
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pre_dir = rng.standard_normal((N, 3)).astype(np.float32)
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pre_dir /= np.linalg.norm(pre_dir, axis=1, keepdims=True)
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post_dir = rng.standard_normal((N, 3)).astype(np.float32)
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post_dir /= np.linalg.norm(post_dir, axis=1, keepdims=True)
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result = local_frame_rotation(pre_dir, post_dir)
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np.testing.assert_allclose(np.linalg.norm(result, axis=1), 1.0, atol=1e-5)
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def test_normalizer_roundtrip():
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rng = np.random.default_rng(3)
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X = rng.standard_normal((200, 9)).astype(np.float32)
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norm = Normalizer().fit(X)
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np.testing.assert_allclose(norm.inverse_transform(norm.transform(X)), X, atol=1e-5)
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def test_normalizer_serialization():
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rng = np.random.default_rng(4)
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X = rng.standard_normal((50, 6)).astype(np.float32)
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norm = Normalizer().fit(X)
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norm2 = Normalizer.from_dict(norm.to_dict())
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np.testing.assert_allclose(norm2.mean, norm.mean)
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np.testing.assert_allclose(norm2.std, norm.std)
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