mirror of
https://github.com/saymrwulf/autoresearch-quantum.git
synced 2026-05-14 20:37:51 +00:00
saymrwulf
e13a3268c2
- 8 Jupyter notebooks across 3 learning plans (A: bottom-up, B: spiral, C: parallel tracks)
- Teaching toolkit (src/autoresearch_quantum/teaching/) with ipywidgets-based
quiz, predict_choice, reflect, and order widgets — visually distinct from code cells
- Fix spectator_z operator: was {1:'Z',2:'Z'} (IZZI, expectation=0), now {1:'Z',3:'Z'}
(ZIZI, expectation=+1 for ideal T-state, commutes with logical operators)
- Fix u_magic seed: swap phase arguments to match h_p and ry_rz preparations
- Fix double-display bug: widgets rendered twice when function returned the box
- Fix CLI override parser for negative integers and missing '=' validation
- Fix stabilizer detection quiz: ZZZZ detects X errors, not Z errors
- Add ties parameter to order() for questions with interchangeable items
- Expand test suite from 21 to 107 tests
- Update README with notebook instructions and project tree
111 lines
3.4 KiB
Python
111 lines
3.4 KiB
Python
"""Tests for persistence.store — edge cases and round-trip serialization."""
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from __future__ import annotations
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from pathlib import Path
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from autoresearch_quantum.models import (
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EvaluationMetrics,
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ExperimentRecord,
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ExperimentSpec,
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RatchetStepRecord,
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RungLesson,
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TierResult,
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)
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from autoresearch_quantum.persistence.store import ResearchStore
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def _make_record(experiment_id: str = "r1-test-abc", score: float = 0.5) -> ExperimentRecord:
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return ExperimentRecord(
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experiment_id=experiment_id,
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rung=1,
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role="challenger",
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parent_incumbent_id=None,
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mutation_note="test",
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spec=ExperimentSpec(rung=1),
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cheap_result=TierResult(
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tier="cheap",
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score=score,
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quality_estimate=0.5,
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metrics=EvaluationMetrics(),
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),
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final_score=score,
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)
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def test_save_and_load_experiment(tmp_path: Path) -> None:
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store = ResearchStore(tmp_path)
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record = _make_record()
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store.save_experiment(record)
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loaded = store.load_experiment(1, "r1-test-abc")
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assert loaded["experiment_id"] == "r1-test-abc"
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assert loaded["final_score"] == 0.5
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def test_list_experiments_sorted(tmp_path: Path) -> None:
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store = ResearchStore(tmp_path)
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store.save_experiment(_make_record("r1-a-111", 0.3))
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store.save_experiment(_make_record("r1-b-222", 0.7))
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experiments = store.list_experiments(1)
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assert len(experiments) == 2
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def test_save_and_load_ratchet_step(tmp_path: Path) -> None:
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store = ResearchStore(tmp_path)
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step = RatchetStepRecord(
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step_index=1,
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rung=1,
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incumbent_before_id="r1-inc",
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challengers_tested=["r1-c1", "r1-c2"],
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promoted_challengers=[],
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winner_id="r1-inc",
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winning_margin=0.0,
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cheap_tier_justification="none promoted",
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expensive_tier_result="disabled",
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distilled_lesson="no change",
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)
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store.save_ratchet_step(step)
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steps = store.list_ratchet_steps(1)
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assert len(steps) == 1
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assert steps[0]["step_index"] == 1
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def test_set_and_load_incumbent(tmp_path: Path) -> None:
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store = ResearchStore(tmp_path)
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assert store.load_incumbent_id(1) is None
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store.set_incumbent(1, "r1-inc-xyz")
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assert store.load_incumbent_id(1) == "r1-inc-xyz"
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def test_save_lesson_writes_markdown(tmp_path: Path) -> None:
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store = ResearchStore(tmp_path)
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lesson = RungLesson(
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rung=1,
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name="test",
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objective="test obj",
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what_helped=["a"],
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what_hurt=["b"],
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what_seems_invariant=["c"],
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what_seems_hardware_specific=["d"],
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what_should_be_tested_next=["e"],
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what_should_be_promoted_to_next_rung=["f"],
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what_should_be_discarded=["g"],
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narrative="# Test narrative",
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)
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store.save_lesson(lesson)
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md_path = store.rung_dir(1) / "lesson.md"
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assert md_path.exists()
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assert md_path.read_text() == "# Test narrative"
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def test_load_propagated_spec_missing(tmp_path: Path) -> None:
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store = ResearchStore(tmp_path)
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assert store.load_propagated_spec(99) is None
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def test_save_and_load_propagated_spec(tmp_path: Path) -> None:
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store = ResearchStore(tmp_path)
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spec = ExperimentSpec(rung=2, seed_style="ry_rz")
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store.save_propagated_spec(2, spec)
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loaded = store.load_propagated_spec(2)
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assert loaded is not None
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assert loaded["seed_style"] == "ry_rz"
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