738df50803
ob_by_hud.py now scans seven readings of the same bytes and keeps a separate candidate set for each, as byte offsets: u32 big and little endian, u16 both endiannesses at both alignments, and u8. The big-endian u32 reading had been refuted, so widening rather than assuming is the point. u32le is much the tightest at 154 candidates against u32be's 4452. That is a hint about the encoding rather than a result, since a rarer bit pattern narrows faster regardless of meaning. The run is inconclusive. The HUD read 4 at every sample, so there was no second value to collapse the sets against, and from t=136 the candidate counts are byte-identical across five samples in all seven encodings, which is what a frozen guest looks like -- nothing in 32 MB changed at all. The probe had no stall witness, so the run cannot prove it either way. One is added now. Worth stating plainly: this is the fourth probe written without a witness and the third whose flat output could not be distinguished from a freeze. Each time the fix gets applied to that one script. The durable fix is the shared probe harness already noted in this file, and the lesson recurring four times is itself the argument for building it. What the hunt needs is unchanged: two HUD readings at different values in non-stalled samples. The counter moves on kills, which lands back on the combat limit, though the earlier 4 to 11 observation shows it does move.
124 lines
5.0 KiB
Python
Executable File
124 lines
5.0 KiB
Python
Executable File
#!/usr/bin/env python3
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"""Locate REMAINING OB from the HUD value instead of from kill events.
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The correlation route works but needs marked-fighter kills, and the pilot gets
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about two per five minutes (remaining-ob-hunt.md). The HUD already shows the
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number, and ob_read.py already reads it, so match the displayed value against
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memory directly -- no kills required.
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Each reading intersects: keep heap words equal to the value the HUD shows at
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that moment. A second reading at a DIFFERENT value collapses the set hard; even
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repeated readings at the same value help, since unrelated words drift.
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"""
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import os, sys, time, subprocess, collections
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sys.path.insert(0, __file__.rsplit('/', 1)[0])
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import gmem, gworld
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import numpy as np
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import ob_read
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LO, HI = 0xBD000000, 0xBE000000
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SHOT = '/tmp/ob_hud.png'
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def region(fd):
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lo, hi = gmem.va_to_off(LO), gmem.va_to_off(HI)
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out, pos = bytearray(), lo
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while pos < hi:
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n = min(1 << 24, hi - pos); out += os.pread(fd, n, pos); pos += n
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return bytes(out), lo
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# The big-endian u32 reading was refuted: no word held 4 then 11. Widen rather
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# than assume -- the counter may be narrower, little-endian, or unaligned. Each
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# encoding keeps its own candidate set, expressed as BYTE OFFSETS so the answer
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# is directly usable whichever one wins.
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ENCODINGS = [
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('u32be', '>u4', 4, 0), ('u32le', '<u4', 4, 0),
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('u16be', '>u2', 2, 0), ('u16be@1', '>u2', 2, 1),
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('u16le', '<u2', 2, 0), ('u16le@1', '<u2', 2, 1),
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('u8', 'u1', 1, 0),
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]
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def matches(buf, value):
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"""byte offsets whose value equals `value`, per encoding"""
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out = {}
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for name, dt, w, skew in ENCODINGS:
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if value > (1 << (8 * w)) - 1:
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continue
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n = (len(buf) - skew) // w * w
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a = np.frombuffer(buf[skew:skew + n], dtype=dt)
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idx = np.nonzero(a == value)[0]
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out[name] = idx.astype(np.int64) * w + skew
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return out
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def hud_value():
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subprocess.run(['screenshot', SHOT], capture_output=True, timeout=60)
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try:
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txt, scores = ob_read.read(SHOT)
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except Exception as e:
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return None, str(e)
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t = (txt or '').strip()
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if not t.isdigit(): return None, 'unreadable %r' % txt
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return int(t), 'scores %s' % (scores,) # ob_read returns tuples, not floats
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def main():
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secs = int(sys.argv[1]) if len(sys.argv) > 1 else 240
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every = int(sys.argv[2]) if len(sys.argv) > 2 else 25
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w = gworld.World(); fd = w.fd
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# Witness. This is the FOURTH probe written without one, and the third to
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# produce a run whose flat output could not be distinguished from a freeze.
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# The recurring fix is a shared harness; until that exists, carry it.
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b0, _ = region(fd); time.sleep(3.0); b1, _ = region(fd)
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a0 = np.frombuffer(b0, dtype='>u4').astype(np.int64)
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a1 = np.frombuffer(b1, dtype='>u4').astype(np.int64)
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d = a1 - a0
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rates = collections.Counter((d[(d > 15) & (d < 600)] // 3).tolist())
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band = [r for r in rates if 8 <= r <= 40]
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pick = max(band, key=lambda r: rates[r]) if band else None
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ticks = np.nonzero(d // 3 == pick)[0][:32] if pick is not None else np.array([], dtype=int)
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print('tick witnesses: %d at %s/s' % (len(ticks), pick), flush=True)
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last_t = a1[ticks] if len(ticks) else None
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cand = None; base = None; seen = []
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t0 = time.time()
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while time.time() - t0 < secs:
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v, note = hud_value()
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el = round(time.time() - t0)
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if v is None:
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print(' t=%4ds HUD unreadable (%s)' % (el, note), flush=True)
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else:
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buf, base = region(fd)
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hit = matches(buf, v)
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if cand is None:
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cand = hit
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else:
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cand = {k: np.intersect1d(cand[k], hit[k], assume_unique=True)
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for k in cand if k in hit}
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seen.append(v)
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st = ''
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if len(ticks):
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now_t = np.frombuffer(buf, dtype='>u4').astype(np.int64)[ticks]
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if int((now_t > last_t).sum()) == 0: st = ' *** GUEST STALLED ***'
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last_t = now_t
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print(' t=%4ds HUD=%-4d %s%s (%s)'
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% (el, v, ' '.join('%s:%d' % (k, len(cand[k])) for k in cand), st, note),
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flush=True)
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live = {k: c for k, c in cand.items() if len(c)}
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if live and len(set(seen)) >= 2 and min(len(c) for c in live.values()) <= 40:
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break
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time.sleep(every)
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print('\nHUD values seen: %s' % sorted(set(seen)))
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if cand and base is not None:
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for k in sorted(cand, key=lambda k: len(cand[k])):
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c = cand[k]
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print(' %-8s %d candidate(s)' % (k, len(c)))
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for off in c[:8]:
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va = gmem.primary_va(base + int(off))
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print(' va %s' % (('%#010x' % va) if va else '?'))
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if all(len(c) == 0 for c in cand.values()):
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print('\nEVERY encoding eliminated -- the counter is not in this region '
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'in any of them, or a HUD reading is wrong.')
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else:
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print('no candidates (HUD never read)')
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return 0
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if __name__ == '__main__':
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sys.exit(main())
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