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