Scruff AI
33 lines
1.4 KiB
Plaintext
33 lines
1.4 KiB
Plaintext
Capturing 500 frames from tcp://localhost:5561 (read-only)...
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100/500 cycle=87580
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200/500 cycle=88580
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300/500 cycle=89580
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400/500 cycle=90580
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500/500 cycle=91580
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Captured 500 frames in 71.9s (7.0 fps)
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cycle step: median=10 (expect ~10), min=10, max=10
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================================================================
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PASSIVE PREDICT-TEST — live 5561 coarse field
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================================================================
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frames used: 500 (cycles 86590 -> 91580, ~4990 cycles)
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channels: ['rho', 'ux', 'uy', 'sxx', 'syy', 'sxy']
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Per-step RMSE (z-scored field, lower = better predictor):
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PERSISTENCE (next=current): 0.3738 <- baseline to beat
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LINEAR (const-velocity extrap): 0.2945
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RUNNING MEAN (dumb global): 1.0054
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PRE-COMMITTED TEST: does LINEAR reliably beat PERSISTENCE?
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improvement: +21.22% (need > +2.00%)
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bootstrap 95% CI of (persist_err - linear_err): [+0.0757, +0.0828] (need lo > 0)
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VERDICT: LINEAR BEATS PERSISTENCE — field carries short-horizon dynamics
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READ: The field's next state is better predicted by its trajectory than by
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assuming it stays still. That means the live fast field carries structured
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short-horizon motion the 9 global scalars could not show. This is the FIRST
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positive signal that the live organism has learnable dynamics. It is NOT yet
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memory (that needs the poke/history test). It IS a green light to proceed.
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Wrote predict_report.txt and predict_capture.npz
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DONE.
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