"""Fixed sealed-trace transport check; no closed-loop dynamics or gain search.""" import hashlib import numpy as np from context import AG, EXP, CFG, check, read, save, digest, budget from timing_queue import TimingQueue, audit_sequence def transport(generated, delay): if generated.ndim != 2 or generated.dtype != np.float32: raise ValueError('Expected stored float32 generated h') queue = TimingQueue(delay, generated.shape[1]) applied = np.empty_like(generated) for tick, row in enumerate(generated): applied[tick] = queue.push(row, tick) pending = queue.pending() report = audit_sequence(generated, applied, pending, delay) report.update(queue.metadata()) report['applied_bytes_sha256'] = hashlib.sha256(applied.tobytes()).hexdigest() report['pending_bytes_sha256'] = hashlib.sha256(pending.tobytes()).hexdigest() return applied, pending, report def main(): check() assert read(EXP / 'origin-audit/summary.json')['pass_all'] names = CFG['fixtures'] + [r['name'] for r in read(EXP / 'protocol/calibration-cases.json')] records = [] for name in names: path = AG / 'gpu' / (name + '-r0') / 'apl-inhibition.float32.npy' generated = np.load(path, mmap_mode='r', allow_pickle=False) assert generated.shape == (read(AG / 'cases' / name / 'spec.json')['steps'], 4064) for delay in CFG['delays_steps']: _, _, report = transport(generated, delay) records.append(dict(case=name, delay_steps=delay, input_sha256=digest(path), **report)) save(EXP / 'audit/shift-gate.json', dict(pass_all=all(r['pass_all'] for r in records), records=records, input_trace_count=len(names), no_new_brain_trajectory=True, no_future_APL_advance=True, closed_loop_equal_integral_claim=False, preservation='Every generated finite-window sample retained bitwise in applied or chronological pending slots; initial padding is +0')) budget() print('PASS: 68 fixed generated traces, 2 exact shifts; no new brain trajectories', flush=True) if __name__ == '__main__': main()