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c6eaad2 e7c9bd3 c6eaad2 e7c9bd3 c6eaad2 e7c9bd3 c6eaad2 e7c9bd3 c6eaad2 e7c9bd3 c6eaad2 | 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 | """Independent counterexample and raw-audit checker for Claim 4."""
from __future__ import annotations
import json
import re
import xml.etree.ElementTree as ET
from itertools import combinations
from pathlib import Path
import numpy as np
GRAPHML_NS = "http://graphml.graphdrawing.org/xmlns"
SUBJECT_RE = re.compile(r"^sub-(OAS\d+)_ses-d(\d+)_")
def independent_ids(path: Path) -> list[int]:
root = ET.parse(path).getroot()
key_names = {
element.attrib["id"]: element.attrib.get("attr.name")
for element in root.findall(f"{{{GRAPHML_NS}}}key")
}
ids: list[int] = []
for node in root.iter(f"{{{GRAPHML_NS}}}node"):
values = [
data.text
for data in node.findall(f"{{{GRAPHML_NS}}}data")
if key_names.get(data.attrib.get("key", ""))
== "dn_multiscaleID"
]
if len(values) != 1 or values[0] is None:
raise ValueError("independent parser found an ambiguous node ID")
ids.append(int(values[0]))
return sorted(ids)
def check(runtime_dir: Path) -> dict[str, object]:
primary = json.loads((runtime_dir / "claim_4_result.json").read_text())
session_rows: list[dict[str, object]] = []
for path in sorted(runtime_dir.glob("claim_4_session_audit_*.json")):
session_rows.extend(json.loads(path.read_text()))
subject_rows = json.loads(
(runtime_dir / "claim_4_subject_audit.json").read_text()
)
files = list((runtime_dir / "work" / "extracted").rglob("*.graphml"))
counterexample_name = primary["data_provenance"]["counterexample_file"]
counterexample_paths = [
path for path in files if path.name == counterexample_name
]
if len(counterexample_paths) != 1:
raise RuntimeError("counterexample file is not uniquely materialized")
ids = independent_ids(counterexample_paths[0])
subject_counts: dict[str, int] = {}
for row in session_rows:
match = SUBJECT_RE.match(str(row["file"]))
if not match or match.group(1) != row["subject"]:
raise RuntimeError("session filename/subject mismatch")
subject_counts[str(row["subject"])] = (
subject_counts.get(str(row["subject"]), 0) + 1
)
recorded_invalid = [
row for row in session_rows if row["subject"] == "OAS30938"
]
table3 = json.loads(
(runtime_dir / "claim_4_table3_result.json").read_text()
)
pair_rows: list[dict[str, object]] = []
for path in sorted(runtime_dir.glob("claim_4_table3_pairs_*.json")):
pair_rows.extend(json.loads(path.read_text()))
expected_pairs = {
(left, right) for left, right in combinations(range(100), 2)
}
subject_order = [
str(row["subject"]) for row in table3["selected_subjects"]
]
observed_pairs = {
(
subject_order.index(str(row["left_subject"])),
subject_order.index(str(row["right_subject"])),
)
for row in pair_rows
}
independent_summary: dict[str, float] = {}
for metric in ("diffusion", "geodesic"):
for method in ("CDOT", "FGW"):
values = np.asarray(
[
float(row["accuracy"])
for row in pair_rows
if row["metric"] == metric
and row["method"] == method
]
)
independent_summary[f"{metric}_{method}"] = float(values.mean())
recorded_summary = {
key: float(value["mean_accuracy"])
for key, value in table3["rerun"].items()
}
summary_error = max(
abs(independent_summary[key] - recorded_summary[key])
for key in independent_summary
)
diffusion_margin = (
independent_summary["diffusion_CDOT"]
- independent_summary["diffusion_FGW"]
)
geodesic_margin = (
independent_summary["geodesic_FGW"]
- independent_summary["geodesic_CDOT"]
)
gates = {
"all_chunked_sessions_loaded": len(session_rows) == 975,
"all_subject_rows_loaded": len(subject_rows) == 696,
"filename_parser_independently_finds_696_subjects": len(subject_counts)
== 696,
"counterexample_has_one_session": len(recorded_invalid) == 1,
"independent_xml_parser_finds_exact_ids_1_to_168": ids
== list(range(1, 169)),
"no_counterexample_session_contains_169_or_170": 169 not in ids
and 170 not in ids,
"primary_falsification_status_rechecked": primary["status"]
== "FALSIFIED",
"table3_all_19800_method_metric_rows_loaded": len(pair_rows)
== 4_950 * 4,
"table3_exact_4950_pair_inventory": observed_pairs
== expected_pairs,
"table3_each_cell_has_4950_rows": all(
sum(
row["metric"] == metric and row["method"] == method
for row in pair_rows
)
== 4_950
for metric in ("diffusion", "geodesic")
for method in ("CDOT", "FGW")
),
"table3_summary_recomputed_from_raw_rows": summary_error < 1e-9,
"table3_diffusion_direction_rechecked": diffusion_margin > 0,
"table3_geodesic_direction_rechecked": geodesic_margin > 0,
"table3_primary_gates_rechecked": table3["all_gates_pass"],
}
result = {
"checker": (
"independent filename inventory plus direct ElementTree reparse "
"of the primary-archive counterexample"
),
"counterexample_file": counterexample_name,
"independent_node_count": len(ids),
"independent_min_id": min(ids),
"independent_max_id": max(ids),
"independent_subject_count": len(subject_counts),
"table3_raw_rows": len(pair_rows),
"table3_unique_pairs": len(observed_pairs),
"table3_independent_summary": independent_summary,
"table3_summary_max_abs_error": summary_error,
"table3_diffusion_CDOT_minus_FGW": diffusion_margin,
"table3_geodesic_FGW_minus_CDOT": geodesic_margin,
"gates": gates,
"all_gates_pass": all(gates.values()),
}
(runtime_dir / "claim_4_independent_checker.json").write_text(
json.dumps(result, indent=2) + "\n", encoding="utf-8"
)
if not result["all_gates_pass"]:
raise RuntimeError("Independent Claim 4 checker failed")
return result
|