Scruff AI
46 lines
1.6 KiB
Python
46 lines
1.6 KiB
Python
"""Sample post-reset baselines for all telemetry fields.
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Captures 60 frames (~60 s) from a quiescent lattice and reports mean/std
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per field. Output matches the BASELINE_MEAN / BASELINE_STD dict structure
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in fractonaut.py so we can paste it straight in.
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"""
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import zmq, json, time, statistics
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FIELDS = ["asymmetry","coherence","vel_mean","vel_max","vel_var",
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"vorticity_mean","stress_xx","stress_yy","stress_xy"]
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ctx = zmq.Context()
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tel = ctx.socket(zmq.SUB); tel.connect("tcp://127.0.0.1:5556")
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tel.setsockopt_string(zmq.SUBSCRIBE, "")
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time.sleep(0.5)
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frames = []
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print("Capturing 60 frames...", flush=True)
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for i in range(60):
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raw = tel.recv_string()
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f = json.loads(raw)
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if i == 0:
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print(f" cycle_start={f['cycle']} khra={f['khra_amp']} gixx={f['gixx_amp']} omega={f['omega']}", flush=True)
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frames.append(f)
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print(f" cycle_end={frames[-1]['cycle']} ({frames[-1]['cycle']-frames[0]['cycle']} cycles spanned)")
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products = []
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print("\nBASELINE_MEAN = {")
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for f in FIELDS:
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vals = [fr[f] for fr in frames]
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m = statistics.mean(vals)
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print(f' "{f}":{" "*(16-len(f))} {m:.6f},')
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print("}")
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print("\nBASELINE_STD = {")
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for f in FIELDS:
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vals = [fr[f] for fr in frames]
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s = statistics.stdev(vals) if len(vals) > 1 else 0.0
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print(f' "{f}":{" "*(16-len(f))} {max(s, 1e-9):.6f},')
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print("}")
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# regime product
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for fr in frames:
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products.append(fr["asymmetry"] * fr["coherence"])
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print(f"\nregime_product: mean={statistics.mean(products):.4f} std={statistics.stdev(products):.4f} min={min(products):.4f} max={max(products):.4f}")
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