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firestar5683
84 lines
4.1 KiB
Python
84 lines
4.1 KiB
Python
from dataclasses import replace
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from openpilot.starpilot.flm.adaptive_profile import ReplayValidation
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from openpilot.starpilot.flm.canonical_surface_adapter import NAMES
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from openpilot.starpilot.flm.event_objective import EffectObjective
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from openpilot.starpilot.flm.full_surface_store import remember_full, load_prior
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from openpilot.starpilot.flm.selected_effects import EffectRestoreTrial, EffectOwner, RESTORE_POLICY
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from openpilot.starpilot.flm.tests.test_history_restore import history, restore_profile
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from openpilot.starpilot.flm.tests.test_full_surface_profile import base, profile
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from openpilot.starpilot.flm.torque_adapter import Admission
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def full_restore():
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raw, last = history()
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prior = load_prior(raw, binding=last.source_binding())
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# Another genuinely persisted group, beyond the marker group's dimensions.
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updated = base(('ff_gain_right',), prior.envelope).with_proposal({'ff_gain_right': 0.005})
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raw = remember_full(raw, profile(updated), validation_sha256='4' * 64)
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current = replace(base(), source_epoch='8' * 64, context_key='8' * 64).validate()
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history_prior = load_prior(raw, binding=current.source_binding())
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envelope = current.restore_from_history(history_prior)
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p = restore_profile(envelope)
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objective = EffectObjective('ff.left', envelope.trial_names, envelope.trial_anchor, envelope.context_key)
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return envelope, p, objective
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def test_explicit_restore_source_runs_full_map_not_only_marker_parameters():
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env, p, objective = full_restore()
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assert len(p.parameters) == 1 and env.trial_names == ('ff_gain_left',)
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trial = EffectRestoreTrial(objective, p.coefficients, env.selected_baseline_revision, env.replay_anchor(), env)
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source = trial.source()
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assert source.values['ff_gain_left'] == 0.020
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assert source.values['ff_gain_right'] == 0.005
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assert tuple((n, source.values[n]) for n in NAMES) == env.coordinates
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def test_restore_owner_slews_all_groups_and_exact_renewal_keeps_continuity():
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env, p, objective = full_restore()
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owner = EffectOwner(
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p.identity,
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objective,
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selected_baseline_revision=env.selected_baseline_revision,
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physical_model_revision='physical',
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original_anchor=env.replay_anchor(),
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restore_envelope=env,
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)
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context = {
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'cp_sha256': env.cp_sha256,
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'controller_revision': env.controller_revision,
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'source_epoch': env.source_epoch,
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'reset_generation': env.reset_generation,
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'selected_baseline_revision': env.selected_baseline_revision,
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'context_key': env.context_key,
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'persistent_source_epoch': env.persistent_source_epoch,
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'current_full_profile_sha256': env.prior_full_profile_sha256,
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}
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v = ReplayValidation(p, env.selected_baseline_revision, 'physical', True, True, 0.1)
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owner.prepare(Admission(p, 10, True, False, True, v), active=True, current_context=context)
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assert owner.profile_policy == RESTORE_POLICY and owner.source is not None
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assert owner.applied_full['ff_gain_left'] == owner.applied_full['ff_gain_right'] == 0.005 * 0.01
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first = dict(owner.applied_full)
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owner.prepare(Admission(p, 10_000_010, True, False, True, v), active=True, current_context=context)
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assert all(abs(owner.applied_full[n] - first[n]) <= 0.005 * 0.01 + 1e-12 for n in NAMES)
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assert owner.applied_full['ff_gain_right'] > first['ff_gain_right']
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owner.prepare(Admission(p, 20_000_010, True, True, True, v), active=True, current_context=context)
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assert owner.source is None and not any(owner.applied_full.values())
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def test_child_group_off_analysis_preserves_historical_envelope_and_cannot_admit():
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import pytest
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from openpilot.starpilot.flm.canonical_surface_adapter import GROUPS
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from openpilot.starpilot.flm.selected_effects import EffectRestoreAblationTrial, EffectReplayTransition
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env, p, objective = full_restore()
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before = env.coordinates
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analysis = EffectRestoreAblationTrial(objective, p.coefficients, env.selected_baseline_revision, env.replay_anchor(), env, GROUPS['ff.right'])
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source = analysis.source()
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assert source.values['ff_gain_left'] == 0.020
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assert source.values['ff_gain_right'] == 0
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assert env.coordinates == before
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assert dict(env.coordinates)['ff_gain_right'] == 0.005
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with pytest.raises(ValueError):
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EffectReplayTransition(analysis)
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