#!/usr/bin/env python3 """Guided virtual-connectome reconfiguration runner. This is the non-autonomous middle stage: it takes a guarded retune candidate, recomputes the projection/residual geometry in a sandboxed receipt, and decides whether the change is ready for a route trial, should stay diagnostic, or must fail closed. It deliberately does not rewrite the canonical Standard Model projection. """ from __future__ import annotations import argparse import hashlib import json from datetime import datetime, timezone from fractions import Fraction from pathlib import Path from typing import Any REPO = Path(__file__).resolve().parents[2] REDUCTION_RECEIPT = ( REPO / "4-Infrastructure" / "hardware" / "standard_model_12_to_4_reduction_receipt.json" ) BOAT_RECEIPT = ( REPO / "4-Infrastructure" / "hardware" / "standard_model_genus3_residual_boat_receipt.json" ) W_GUARD_RECEIPT = ( REPO / "4-Infrastructure" / "hardware" / "standard_model_w_conservation_guard_receipt.json" ) OUT = ( REPO / "4-Infrastructure" / "hardware" / "standard_model_connectome_reconfiguration_receipt.json" ) PRIMITIVES = ("field", "shear", "packet", "spectral") def stable_json(obj: Any) -> str: return json.dumps(obj, sort_keys=True, separators=(",", ":"), ensure_ascii=True) def sha256_bytes(data: bytes) -> str: return hashlib.sha256(data).hexdigest() def fraction_str(value: Fraction) -> str: return str(value.numerator) if value.denominator == 1 else f"{value.numerator}/{value.denominator}" def fraction_json(value: Fraction) -> dict[str, Any]: return { "fraction": fraction_str(value), "numerator": value.numerator, "denominator": value.denominator, "decimal": float(value), } def parse_fraction_json(item: dict[str, Any]) -> Fraction: return Fraction(int(item["numerator"]), int(item["denominator"])) def load_json(path: Path) -> dict[str, Any]: return json.loads(path.read_text(encoding="utf-8")) def vector_from_json(items: dict[str, dict[str, Any]]) -> dict[str, Fraction]: return {key: parse_fraction_json(value) for key, value in items.items()} def vector_json(vector: dict[str, Fraction]) -> dict[str, dict[str, Any]]: return {key: fraction_json(value) for key, value in sorted(vector.items())} def projection_from_json(items: dict[str, dict[str, dict[str, Any]]]) -> dict[str, dict[str, Fraction]]: return { axis: { primitive: parse_fraction_json(weight) for primitive, weight in row.items() } for axis, row in items.items() } def projection_json(projection: dict[str, dict[str, Fraction]]) -> dict[str, dict[str, dict[str, Any]]]: return { axis: { primitive: fraction_json(weight) for primitive, weight in sorted(row.items()) if weight } for axis, row in sorted(projection.items()) } def signed_l1(vector: dict[str, Fraction]) -> Fraction: return sum((abs(value) for value in vector.values()), Fraction(0)) def project_12_to_4( centroid: dict[str, Fraction], projection: dict[str, dict[str, Fraction]], ) -> dict[str, Fraction]: reduced = {primitive: Fraction(0) for primitive in PRIMITIVES} for axis, mass in centroid.items(): for primitive, weight in projection[axis].items(): reduced[primitive] += mass * weight return reduced def lift_4_to_12( reduced: dict[str, Fraction], projection: dict[str, dict[str, Fraction]], ) -> dict[str, Fraction]: support_weight_sum = {primitive: Fraction(0) for primitive in PRIMITIVES} for row in projection.values(): for primitive, weight in row.items(): support_weight_sum[primitive] += weight lifted = {axis: Fraction(0) for axis in projection} for axis, row in projection.items(): for primitive, weight in row.items(): if support_weight_sum[primitive]: lifted[axis] += reduced[primitive] * weight / support_weight_sum[primitive] return lifted def evaluate_projection( centroid: dict[str, Fraction], projection: dict[str, dict[str, Fraction]], ) -> dict[str, Any]: reduced = project_12_to_4(centroid, projection) lifted = lift_4_to_12(reduced, projection) residual = { axis: centroid[axis] - lifted[axis] for axis in centroid } rehydrated_delta = { axis: lifted[axis] + residual[axis] - centroid[axis] for axis in centroid } return { "reduced_4d": reduced, "lifted_12d": lifted, "residual_12d": residual, "residual_l1": signed_l1(residual), "rehydrated_delta": rehydrated_delta, "rehydrated_delta_l1": signed_l1(rehydrated_delta), "exact_rehydration": signed_l1(rehydrated_delta) == 0, } def row_from_guard_json(row: dict[str, dict[str, Any]]) -> dict[str, Fraction]: return { primitive: parse_fraction_json(value) for primitive, value in row.items() } def row_support(row: dict[str, Fraction]) -> tuple[str, ...]: return tuple(sorted(row)) def row_cost(row: dict[str, Fraction]) -> int: """Tiny metadata proxy: primitive count plus denominator complexity.""" return len(row) + sum(value.denominator for value in row.values()) def residual_pressure_by_handle( residual: dict[str, Fraction], boat: dict[str, Any], ) -> dict[str, Fraction]: pressure = {handle: Fraction(0) for handle in boat["handle_vectors"]} for handle, vector in boat["handle_vectors"].items(): for axis in vector: pressure[handle] += abs(residual[axis]) return pressure def ranked_fraction_map(values: dict[str, Fraction]) -> list[dict[str, Any]]: return [ {"axis": key, "value": fraction_json(value)} for key, value in sorted(values.items(), key=lambda item: abs(item[1]), reverse=True) ] def ranked_abs_vector(vector: dict[str, Fraction], limit: int = 8) -> list[dict[str, Any]]: return [ { "axis": key, "value": fraction_json(value), "absolute": fraction_json(abs(value)), } for key, value in sorted(vector.items(), key=lambda item: abs(item[1]), reverse=True)[:limit] ] def decide( guard_passes: bool, exact_rehydration: bool, residual_improvement: Fraction, support_preserved: bool, metadata_cost_proxy: int, ) -> tuple[str, list[str]]: reasons: list[str] = [] if not exact_rehydration: return "nan0_fail_closed", ["exact rehydration failed"] if residual_improvement <= 0: return "diagnostic_only", ["candidate does not improve residual_l1"] if not guard_passes: return "diagnostic_only", ["guard did not pass"] if not support_preserved: return "diagnostic_only", ["candidate changes primitive support"] reasons.append("guard passed") reasons.append("exact rehydration remained closed") reasons.append("residual_l1 improved") reasons.append("primitive support preserved") reasons.append(f"metadata_cost_proxy={metadata_cost_proxy} is recorded but not byte-priced") return "hold_for_route_trial", reasons def build_receipt() -> dict[str, Any]: reduction = load_json(REDUCTION_RECEIPT) boat = load_json(BOAT_RECEIPT) guard = load_json(W_GUARD_RECEIPT) centroid = vector_from_json(reduction["visible_centroid_12d"]) baseline_projection = projection_from_json(reduction["projection_matrix_12_to_4"]) guarded = guard["candidate_classification"]["best_support_preserving_candidate"] axis = guarded["axis"] candidate_row = row_from_guard_json(guarded["candidate_row"]) baseline_row = baseline_projection[axis] trial_projection = { key: dict(value) for key, value in baseline_projection.items() } trial_projection[axis] = candidate_row baseline_eval = evaluate_projection(centroid, baseline_projection) trial_eval = evaluate_projection(centroid, trial_projection) residual_improvement = baseline_eval["residual_l1"] - trial_eval["residual_l1"] support_preserved = row_support(baseline_row) == row_support(candidate_row) metadata_cost_proxy = row_cost(candidate_row) - row_cost(baseline_row) decision, reasons = decide( guard_passes=bool(guarded["passes_guard"]), exact_rehydration=bool(trial_eval["exact_rehydration"]), residual_improvement=residual_improvement, support_preserved=support_preserved, metadata_cost_proxy=metadata_cost_proxy, ) residual_delta = { key: trial_eval["residual_12d"][key] - baseline_eval["residual_12d"][key] for key in centroid } baseline_handle_pressure = residual_pressure_by_handle(baseline_eval["residual_12d"], boat) trial_handle_pressure = residual_pressure_by_handle(trial_eval["residual_12d"], boat) handle_pressure_delta = { handle: trial_handle_pressure[handle] - baseline_handle_pressure[handle] for handle in baseline_handle_pressure } receipt = { "schema": "standard_model_connectome_reconfiguration_receipt_v1", "generated_utc": datetime.now(timezone.utc).isoformat(), "surface_id": "standard_model_connectome_reconfiguration", "source": { "reduction_receipt": str(REDUCTION_RECEIPT.relative_to(REPO)), "reduction_stable_hash_sha256": reduction.get("stable_reduction_hash_sha256"), "boat_receipt": str(BOAT_RECEIPT.relative_to(REPO)), "boat_stable_hash_sha256": boat.get("stable_boat_hash_sha256"), "w_guard_receipt": str(W_GUARD_RECEIPT.relative_to(REPO)), "w_guard_stable_hash_sha256": guard.get("stable_w_conservation_guard_hash_sha256"), }, "reconfiguration_scope": { "mode": "guided_local_retune", "autonomy_level": "human_gated_candidate_generation", "canonical_projection_rewritten": False, "axis": axis, }, "candidate": { "axis": axis, "baseline_row": { primitive: fraction_json(value) for primitive, value in sorted(baseline_row.items()) }, "candidate_row": { primitive: fraction_json(value) for primitive, value in sorted(candidate_row.items()) }, "guard_status": guarded["status"], "guard_reasons": guarded["reasons"], "support_preserved": support_preserved, "metadata_cost_proxy_delta": metadata_cost_proxy, }, "baseline": { "residual_l1": fraction_json(baseline_eval["residual_l1"]), "reduced_4d": vector_json(baseline_eval["reduced_4d"]), "top_residual_axes": ranked_abs_vector(baseline_eval["residual_12d"]), "handle_pressure": ranked_fraction_map(baseline_handle_pressure), }, "trial": { "residual_l1": fraction_json(trial_eval["residual_l1"]), "residual_l1_improvement": fraction_json(residual_improvement), "residual_l1_improvement_ratio": fraction_json( residual_improvement / baseline_eval["residual_l1"] if baseline_eval["residual_l1"] else Fraction(0) ), "reduced_4d": vector_json(trial_eval["reduced_4d"]), "top_residual_axes": ranked_abs_vector(trial_eval["residual_12d"]), "residual_delta_top_axes": ranked_abs_vector(residual_delta), "handle_pressure": ranked_fraction_map(trial_handle_pressure), "handle_pressure_delta": ranked_fraction_map(handle_pressure_delta), "exact_rehydration": trial_eval["exact_rehydration"], "rehydrated_delta_l1": fraction_json(trial_eval["rehydrated_delta_l1"]), }, "decision": { "status": decision, "reasons": reasons, "next_required_actions": [ "do not rewrite canonical projection yet", "run downstream residual-accounting and force-regime probes against the trial projection", "price projection-row metadata before compression promotion", "promote only if exact receipt boundary and objective both improve", ], }, "claim_boundary": ( "This is a guided virtual-connectome reconfiguration receipt. It " "tests a local symbolic projection retune without claiming autonomous " "metatyping, physical Standard Model correction, or compression proof." ), "lawful": True, } stable_preimage = stable_json({ "schema": receipt["schema"], "surface_id": receipt["surface_id"], "source": receipt["source"], "reconfiguration_scope": receipt["reconfiguration_scope"], "candidate": receipt["candidate"], "baseline": receipt["baseline"], "trial": receipt["trial"], "decision": receipt["decision"], "claim_boundary": receipt["claim_boundary"], "lawful": receipt["lawful"], }).encode("utf-8") receipt["stable_connectome_reconfiguration_hash_sha256"] = sha256_bytes(stable_preimage) receipt["receipt_hash_preimage_sha256"] = sha256_bytes(stable_json(receipt).encode("utf-8")) return receipt def main() -> int: parser = argparse.ArgumentParser(description=__doc__) parser.add_argument("--out", type=Path, default=OUT) args = parser.parse_args() receipt = build_receipt() args.out.parent.mkdir(parents=True, exist_ok=True) args.out.write_text(json.dumps(receipt, indent=2, sort_keys=True), encoding="utf-8") print(json.dumps({ "lawful": receipt["lawful"], "stable_connectome_reconfiguration_hash_sha256": receipt["stable_connectome_reconfiguration_hash_sha256"], "receipt_hash_preimage_sha256": receipt["receipt_hash_preimage_sha256"], "axis": receipt["candidate"]["axis"], "decision": receipt["decision"], "baseline_residual_l1": receipt["baseline"]["residual_l1"], "trial_residual_l1": receipt["trial"]["residual_l1"], "residual_l1_improvement": receipt["trial"]["residual_l1_improvement"], "residual_l1_improvement_ratio": receipt["trial"]["residual_l1_improvement_ratio"], "exact_rehydration": receipt["trial"]["exact_rehydration"], }, indent=2, sort_keys=True)) return 0 if __name__ == "__main__": raise SystemExit(main())