Source artifacts from the multi-model landing package (README + Super-Blueprint + ADR-0238/0239/0240 + goldtether/dynamic_manifold/surprise) are now the contractual surface, implemented on the live algebra/* kernel: - GoldTetherMonitor.residual/update/may_relax_hitl/force_reset/autonomy - signature_aware_pca (5×K, null-safe), conformal_procrustes, cartan_iwasawa_extract - surprise_residual (Minkowski) + dual_procrustes_surprise audit dict Package stubs (core.algebra.backend placeholders, scipy, identity-only Procrustes) are replaced with dual-corrected Cl(4,1) operators. ADRs match package decision language; docs/adr remains canonical with decisions redirects. 34/34 Third-Door tests + 7/7 ADR-0199 arena regression green.
124 lines
3.8 KiB
Python
124 lines
3.8 KiB
Python
"""ADR-0238 — GoldTether residual, floor, autonomy, may_relax_hitl, blend."""
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from __future__ import annotations
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import numpy as np
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import pytest
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from hypothesis import given, settings
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from hypothesis import strategies as st
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from algebra.rotor import make_rotor_from_angle
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from algebra.versor import versor_condition
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from core.physics.goldtether import (
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AutonomyBand,
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GoldTetherMonitor,
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OperatingMode,
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coherence_residual,
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)
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def _id() -> np.ndarray:
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v = np.zeros(32, dtype=np.float64)
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v[0] = 1.0
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return v
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def test_coherence_residual_nonnegative_and_zero_on_identity():
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assert coherence_residual(_id()) == 0.0
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r = coherence_residual(make_rotor_from_angle(0.5))
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assert r >= 0.0
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def test_residual_dual_corrected_and_replay():
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m = GoldTetherMonitor()
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F = make_rotor_from_angle(0.4)
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assert m.residual(F) == m.residual(F)
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assert m.residual(F) == coherence_residual(F)
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def test_fail_closed_on_drift():
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m = GoldTetherMonitor(epsilon_drift=1e-9)
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# Inject a non-closed multivector by raw coefficients
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dirty = np.zeros(32, dtype=np.float64)
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dirty[0] = 0.5
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dirty[1] = 0.5
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r, auto = m.update(dirty, epistemic_elevation=True)
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assert r > m.epsilon_drift
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assert auto == 0.0
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assert m.may_relax_hitl() is False
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def test_epistemic_elevation_raises_floor_and_autonomy():
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m = GoldTetherMonitor(epsilon_drift=1e-5, floor_step=0.1, autonomy_step=0.1)
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F = _id()
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for _ in range(10):
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m.update(F, epistemic_elevation=True)
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assert m.floor > 0.0
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assert m.autonomy > 0.0
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assert m.autonomy <= m.floor
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assert m.supervised_autonomy_level == m.autonomy
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def test_never_autonomy_above_floor():
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m = GoldTetherMonitor(floor_step=0.02, autonomy_step=0.5)
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for _ in range(20):
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m.update(_id(), epistemic_elevation=True)
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assert m.autonomy <= m.floor + 1e-12
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def test_may_relax_hitl_thresholds():
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m = GoldTetherMonitor(
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hitl_floor_threshold=0.3,
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hitl_autonomy_threshold=0.2,
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floor_step=0.1,
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autonomy_step=0.1,
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)
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assert m.may_relax_hitl() is False
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for _ in range(20):
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m.update(_id(), epistemic_elevation=True)
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assert m.may_relax_hitl() is True
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def test_force_reset():
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m = GoldTetherMonitor()
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m.update(_id(), epistemic_elevation=True)
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m.force_reset()
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assert m.floor == 0.0 and m.autonomy == 0.0 and m.history == []
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def test_serve_never_autonomous_band():
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m = GoldTetherMonitor(floor_step=0.2, autonomy_step=0.2, hitl_floor_threshold=0.1, hitl_autonomy_threshold=0.1)
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for _ in range(10):
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m.update(_id(), epistemic_elevation=True)
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d = m.decide(0.0, mode=OperatingMode.SERVE)
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assert d.band is not AutonomyBand.AUTONOMOUS
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def test_lifelong_curve_telemetry_replay():
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m1 = GoldTetherMonitor()
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m2 = GoldTetherMonitor()
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for i in range(5):
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F = make_rotor_from_angle(0.01 * i) if i else _id()
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# identity always closed; elevation path
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m1.update(_id(), epistemic_elevation=True)
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m2.update(_id(), epistemic_elevation=True)
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assert m1.telemetry()["history_tail"] == m2.telemetry()["history_tail"]
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assert m1.telemetry()["schema_version"] == "goldtether_coherence_v1"
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def test_supervised_blend_closure_and_endpoints():
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m = GoldTetherMonitor()
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src = _id()
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tgt = make_rotor_from_angle(0.6)
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assert np.allclose(m.supervised_blend(src, tgt, 0.0), src)
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assert np.allclose(m.supervised_blend(src, tgt, 1.0), tgt, atol=1e-6)
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mid = m.supervised_blend(src, tgt, 0.5)
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assert versor_condition(mid) < 1e-6
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@given(st.floats(min_value=0.0, max_value=1.0, allow_nan=False, allow_infinity=False))
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@settings(max_examples=30)
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def test_blend_property_closed(alpha: float):
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m = GoldTetherMonitor()
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out = m.supervised_blend(_id(), make_rotor_from_angle(0.8), float(alpha))
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assert versor_condition(out) < 1e-6
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