screening-ceiling / tests /test_dataset.py
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"""Tests for the screening-ceiling dataset.
The important tests here are not "does the file parse" -- they are "is the
published claim true of the published data". A dataset whose ground truth is
wrong is worse than no dataset, because every result scored against it inherits
the error.
"""
from __future__ import annotations
import json
import math
import pathlib
import random
import sys
import pytest
HERE = pathlib.Path(__file__).resolve().parents[1]
sys.path.insert(0, str(HERE))
import verify # noqa: E402
from loader import ( # noqa: E402
family_layout,
load_counterexamples,
load_regions,
load_theorem,
)
DATA = HERE / "data"
# --------------------------------------------------------------------- presence
def test_data_files_exist_and_are_nonempty():
for name in ("certified_regions.jsonl", "counterexamples.jsonl", "theorem.json"):
p = DATA / name
assert p.exists(), f"missing {name}"
assert p.stat().st_size > 0, f"empty {name}"
def test_every_line_is_valid_json():
for name in ("certified_regions.jsonl", "counterexamples.jsonl"):
for i, line in enumerate((DATA / name).read_text(encoding="utf-8").splitlines()):
if line.strip():
json.loads(line) # raises on malformed
# ---------------------------------------------------------------------- schema
def test_region_schema_is_complete():
required = {"region_id", "bounds", "status", "certified_leaves",
"processed_leaves", "sup_certified_k_hi",
"volume_fraction_of_region", "unresolved_leaves"}
for r in load_regions():
assert required <= set(r), f"{r.get('region_id')} missing {required - set(r)}"
assert set(r["bounds"]) == {"d0_um", "pt_mult", "sep_mult", "jog_mult"}
for b in r["bounds"].values():
assert b["lo"] < b["hi"], "degenerate interval"
def test_counterexample_schema_is_complete():
required = {"case_id", "model", "n_conductors", "worst_pair", "k_predicted",
"violates_ceiling", "xy_um", "radius_um", "eps_r"}
for c in load_counterexamples():
assert required <= set(c), f"{c.get('case_id')} missing {required - set(c)}"
assert len(c["xy_um"]) == c["n_conductors"]
assert len(c["radius_um"]) == c["n_conductors"]
def test_case_ids_are_unique():
ids = [c["case_id"] for c in load_counterexamples()]
assert len(ids) == len(set(ids))
def test_region_ids_are_unique():
ids = [r["region_id"] for r in load_regions()]
assert len(ids) == len(set(ids))
# ------------------------------------------------------------------ the claims
def test_every_region_is_certified_with_no_unresolved_leaves():
for r in load_regions():
assert r["status"] == "CERTIFIED", f"{r['region_id']} is {r['status']}"
assert r["unresolved_leaves"] == 0
def test_no_region_admits_a_k_above_the_bound():
"""The published per-region supremum must respect the published bound."""
k_bar = load_theorem()["k_bar"]
for r in load_regions():
assert r["sup_certified_k_hi"] <= k_bar, \
f"{r['region_id']} admits {r['sup_certified_k_hi']} > {k_bar}"
def test_leaf_total_matches_the_sum_over_regions():
t = load_theorem()
assert sum(r["certified_leaves"] for r in load_regions()) \
== t["certified_leaves_total"]
def test_regions_tile_the_family_box():
"""Union of region bounds must span the declared family box on every axis."""
t = load_theorem()
regions = load_regions()
for name, b in t["family_box"].items():
assert min(r["bounds"][name]["lo"] for r in regions) == b["lo"]
assert max(r["bounds"][name]["hi"] for r in regions) == b["hi"]
@pytest.mark.parametrize("seed", [0, 1, 2])
def test_sampling_inside_certified_regions_never_exceeds_the_bound(seed):
"""Independent re-derivation: sampling must fail to refute the claim."""
k_bar = load_theorem()["k_bar"]
rng = random.Random(seed)
worst, violations = verify.check_regions(load_regions(), k_bar, samples=3,
rng=rng, verbose=False)
assert violations == [], f"claim refuted at {violations[:2]}"
assert worst <= k_bar
def test_every_counterexample_really_violates_the_ceiling():
"""Existential claim, re-derived from stored coordinates rather than trusted."""
confirmed, failed = verify.check_counterexamples(load_counterexamples(),
verbose=False)
assert failed == [], f"counterexamples did not re-derive: {failed[:2]}"
assert confirmed == len(load_counterexamples())
def test_published_k_matches_recomputation_to_tight_tolerance():
for c in load_counterexamples():
xy = [[x * 1e-6, y * 1e-6] for x, y in c["xy_um"]]
radius = [r * 1e-6 for r in c["radius_um"]]
k = verify.born_second_order_k(xy, radius)
n = len(xy)
kmax = max(k[i][j] for i in range(n) for j in range(n) if i != j)
assert kmax == pytest.approx(c["k_predicted"], rel=1e-9)
assert kmax > 1.0
# ------------------------------------------------------------------- physics
def test_isolated_pair_has_no_screening():
"""Two conductors alone: k must be exactly 1, since there is nothing to screen."""
k = verify.screening_factors([[0.0, 0.0], [1e-4, 0.0]], [2e-5, 2e-5])
assert k[0][1] == pytest.approx(1.0, abs=1e-12)
assert k[1][0] == pytest.approx(1.0, abs=1e-12)
def test_adding_a_conductor_reduces_coupling():
"""The physical content of the ceiling: screening only ever removes coupling."""
pair = verify.screening_factors([[0.0, 0.0], [2e-4, 0.0]], [2e-5] * 2)[0][1]
with_third = verify.screening_factors(
[[0.0, 0.0], [2e-4, 0.0], [1e-4, 0.0]], [2e-5] * 3)[0][1]
assert with_third < pair
def test_family_layout_matches_the_documented_geometry():
xy, radius = family_layout(40.0, 1.0, 3.0, 0.0)
pt = 1.6 * 40.0 * 1e-6
assert xy[1][0] == pytest.approx(pt)
assert xy[2][0] == pytest.approx(pt * 3.0)
assert xy[3][0] == pytest.approx(pt * 3.0 + pt)
assert all(r == pytest.approx(20e-6) for r in radius)
def test_loader_and_verify_agree_on_geometry():
"""Two implementations of the family layout must not drift apart."""
a_xy, a_r = family_layout(37.5, 1.1, 3.3, -0.2)
b_xy, b_r = verify.family_layout(37.5, 1.1, 3.3, -0.2)
assert [c for pt in a_xy for c in pt] == pytest.approx(
[c for pt in b_xy for c in pt])
assert a_r == pytest.approx(b_r)
def test_inverse_is_correct():
m = [[4.0, 7.0], [2.0, 6.0]]
inv = verify.inverse(m)
prod = [[sum(m[i][k] * inv[k][j] for k in range(2)) for j in range(2)]
for i in range(2)]
assert prod[0][0] == pytest.approx(1.0)
assert prod[1][1] == pytest.approx(1.0)
assert prod[0][1] == pytest.approx(0.0, abs=1e-12)
def test_singular_matrix_raises_rather_than_returning_garbage():
with pytest.raises(ZeroDivisionError):
verify.inverse([[1.0, 2.0], [2.0, 4.0]])
# ------------------------------------------------------------ negative control
def test_the_checker_rejects_a_fabricated_bound():
"""A checker that cannot fail is not a checker."""
rng = random.Random(0)
_, violations = verify.check_regions(load_regions()[:4], k_bar=0.5, samples=5,
rng=rng, verbose=False)
assert violations, "an impossible bound was not refuted"
def test_the_checker_rejects_a_tampered_counterexample():
cases = load_counterexamples()
bad = dict(cases[0], k_predicted=cases[0]["k_predicted"] * 1.5)
_, failed = verify.check_counterexamples([bad], verbose=False)
assert failed, "a tampered value was accepted"
def test_self_test_entrypoint_passes():
assert verify.self_test() == 0
# ---------------------------------------------------------------- provenance
def test_theorem_records_provenance_and_scope():
t = load_theorem()
p = t["provenance"]
assert len(p["source_sha256"]) == 64
assert len(p["witness_content_sha256"]) == 64
assert p["partition_regions"] == len(load_regions())
assert "MONOPOLE-CLOSURE" in t["honest_scope"]
assert "not establish" in t["honest_scope"]
def test_stated_overprediction_follows_from_the_certified_supremum():
"""The headline percentage must be derivable, not asserted.
It derives from the supremum the proof actually certified rather than from
the target bound, so it is marginally STRONGER than 100/k_bar - 100. Both
relationships are checked, because that last digit is exactly the kind of
thing a careful reader will try to reproduce and then query.
"""
t = load_theorem()
assert t["forced_pairwise_overprediction_basis"] == "sup_certified_k_hi"
assert t["forced_pairwise_overprediction_pct"] == \
pytest.approx(100.0 / t["sup_certified_k_hi"] - 100.0, rel=1e-12)
assert t["forced_pairwise_overprediction_pct"] >= 100.0 / t["k_bar"] - 100.0
def test_scope_is_not_overclaimed_anywhere_in_the_card():
"""The card must not say the theorem is about Maxwell or measured silicon."""
card = (HERE / "README.md").read_text(encoding="utf-8").lower()
assert "monopole-closure" in card or "monopole closure" in card
for forbidden in ("proves maxwell", "measured silicon shows",
"validated against measurement"):
assert forbidden not in card
def test_verify_is_importable_with_no_third_party_modules():
"""The zero-dependency promise, enforced rather than documented."""
src = (HERE / "verify.py").read_text(encoding="utf-8")
banned = ("import numpy", "import pandas", "import scipy", "import torch",
"from numpy", "from pandas", "import datasets")
for b in banned:
assert b not in src, f"verify.py must stay stdlib-only, found {b!r}"
def test_math_import_is_actually_used():
assert math.hypot(3, 4) == 5.0 # guards the import above from bit-rot
def test_readme_figures_match_the_data():
"""Headline numbers in the card are re-derived from the files, not typed once."""
readme = (HERE / "README.md").read_text(encoding="utf-8")
cs, t = load_counterexamples(), load_theorem()
assert f"{sum(c['n_pairs_violating'] for c in cs):,}" in readme
assert f"{max(c['k_predicted'] for c in cs):.4f}" in readme
assert f"{t['certified_leaves_total']:,}" in readme
assert f"{t['processed_leaves_total']:,}" in readme
assert f"{t['forced_pairwise_overprediction_pct']:.6f}"[:9] in readme
@pytest.mark.parametrize("samples,expected", [
(25, "0.902144353337"),
(100, "0.903775408593"),
])
def test_readme_sampling_ladder_reproduces(samples, expected):
"""The card quotes a sampling ladder; a reader will run it, so it must hold.
400 samples is quoted too but takes ~6 s, so it is exercised by the
quoted-string check below rather than re-run on every commit.
"""
worst, violations = verify.check_regions(
load_regions(), load_theorem()["k_bar"], samples,
random.Random(7), verbose=False)
assert f"{worst:.12f}" == expected
assert violations == []
assert expected in (HERE / "README.md").read_text(encoding="utf-8")
def test_readme_marks_the_two_figures_it_cannot_reproduce():
"""0.081% and 0.9053 come from tooling that is not in this release.
Every other number on the card re-derives from the published files. These
two do not, and a reader has no way to tell them apart unless we say so.
"""
readme = (HERE / "README.md").read_text(encoding="utf-8")
for figure in ("0.081%", "0.9053"):
assert figure in readme, f"{figure} vanished; drop this guard with it"
assert "not part of this release" in readme
assert "cannot re-derive it from what is published here" in readme