Seal Phase 4AJ fixed APL timing hypothesis audit

models/male-cns-lif/apl-timing-lab-v1/shift_audit.py

@@ -0,0 +1,44 @@
+"""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()