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4415131 d21403c 4415131 829160b 4415131 829160b 4415131 829160b 4415131 829160b 4415131 2897ee3 829160b 2897ee3 829160b 2897ee3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 | """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
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