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#!/usr/bin/env python3
"""Audit the frozen nonlinear CLLN hardware confirmation."""
from __future__ import annotations
import argparse
import json
from pathlib import Path
import numpy as np
METHODS = (
"clean",
"raw",
"constant",
"sdil",
"overclamp_clean",
"overclamp",
"overclamp_sdil",
)
DEVICE_SEEDS = (20260833, 20260834, 20260835)
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser()
parser.add_argument(
"--input", type=Path,
default=Path(
"results/physical_bias/p11_nonlinear_hardware_confirmation.json"),
)
parser.add_argument(
"--output", type=Path,
default=Path(
"results/physical_bias/p11_nonlinear_hardware_confirmation_gate.json"),
)
parser.add_argument("--bootstrap-replicates", type=int, default=20000)
parser.add_argument("--bootstrap-seed", type=int, default=20260829)
return parser.parse_args()
def task_means(records: list[dict], method: str) -> np.ndarray:
return np.asarray([
np.mean([
record["methods"][method]["classification_error"]
for record in records
if record["task_index"] == task
])
for task in range(40)
])
def summarize(
values: np.ndarray, rng: np.random.Generator, replicates: int
) -> dict:
samples = rng.integers(0, len(values), size=(replicates, len(values)))
means = np.mean(values[samples], axis=1)
return {
"mean_classification_error": float(np.mean(values)),
"task_bootstrap_95ci": [
float(value) for value in np.percentile(means, (2.5, 97.5))
],
}
def main() -> None:
args = parse_args()
report = json.loads(args.input.read_text())
protocol = report["protocol"]
records = report["records"]
exact_cells = {
(task, seed) for task in range(40) for seed in DEVICE_SEEDS
}
actual_cells = {
(record["task_index"], record["device_seed"]) for record in records
}
protocol_checks = {
"source_marked_confirmatory": report["confirmatory"] is True,
"exact_120_paired_cells": actual_cells == exact_cells,
"all_40_tasks": protocol["task_count"] == 40
and protocol["rotations_per_input_diameter"] == 8,
"new_component_seeds_exact": (
tuple(protocol["device_seeds"]) == DEVICE_SEEDS),
"seven_methods_exact": tuple(protocol["methods"]) == METHODS,
"calibration_observations_16": (
protocol["calibration_observations_per_trial"] == 16),
"degree_two_predictor": protocol["sdil_polynomial_degree"] == 2,
"standard_epochs_600": protocol["standard_epochs"] == 600,
"overclamp_epochs_1000": (
protocol["overclamp_epochs_maximum"] == 1000),
"autodiff_unused": report["autodiff_used"] is False,
}
finite_complete = len(records) == 120 and all(
set(record["methods"]) == set(METHODS)
and all(
np.isfinite(method["classification_error"])
and np.isfinite(method["hinge_loss_v2"])
for method in record["methods"].values()
)
for record in records
)
rng = np.random.default_rng(args.bootstrap_seed)
by_method_values = {
method: task_means(records, method) for method in METHODS
}
by_method = {
method: summarize(values, rng, args.bootstrap_replicates)
for method, values in by_method_values.items()
}
means = {
method: by_method[method]["mean_classification_error"]
for method in METHODS
}
standard_gap_closed = (
(means["raw"] - means["sdil"])
/ (means["raw"] - means["clean"])
)
overclamp_gap_closed = (
(means["overclamp"] - means["overclamp_sdil"])
/ (means["overclamp"] - means["overclamp_clean"])
)
checks = {
**protocol_checks,
"all_task_metrics_finite": finite_complete,
"sdil_improves_raw_in_every_task": bool(np.all(
by_method_values["sdil"] < by_method_values["raw"])),
"sdil_closes_at_least_95_percent_standard_gap": (
standard_gap_closed >= 0.95),
"sdil_within_one_point_of_clean": (
means["sdil"] - means["clean"] <= 0.01),
"overclamp_sdil_closes_at_least_95_percent_gap": (
overclamp_gap_closed >= 0.95),
"constant_and_overclamp_retained": (
"constant" in by_method and "overclamp" in by_method),
}
output = {
"analysis": "nonlinear_clln_hardware_confirmation_gate",
"source": str(args.input),
"bootstrap": {
"unit": "task; three device draws averaged within task",
"task_clusters": 40,
"replicates": args.bootstrap_replicates,
"seed": args.bootstrap_seed,
"interval": "percentile 95%",
},
"checks": checks,
"by_method": by_method,
"standard_raw_to_clean_gap_closed": float(standard_gap_closed),
"overclamp_raw_to_clean_gap_closed": float(overclamp_gap_closed),
"gate": "pass" if all(checks.values()) else "fail",
}
args.output.parent.mkdir(parents=True, exist_ok=True)
args.output.write_text(json.dumps(output, indent=2) + "\n")
print(json.dumps(output, indent=2))
print(f"wrote {args.output}")
if output["gate"] != "pass":
raise SystemExit(1)
if __name__ == "__main__":
main()
|
