#
# dmgscan -- extract the type-29 cylinder hit-location tables from BTL4.RES.
#
# The unaimed-damage model is a cylinder around the mech: 7 height BANDS x 8
# angular WEDGES, and each of the 56 cells carries its own cumulative
# distribution over that chassis's armor zones.  DMGTABLE.CPP resolves a hit
# by height -> band, atan2(z,x) -> wedge, then one uniform roll down the
# cell's table.
#
# The stream format is documented in source410/BT/DMGTABLE.CPP and this
# scanner is the check on it: it brute-forces every offset in the resource and
# only accepts a candidate whose ENTIRE nested structure parses -- thresholds
# strictly ascending and terminating at exactly 1.0, zone indices in range,
# names NUL-terminated.  A wrong format guess cannot survive that, which is
# why finding exactly 18 tables (the count the notes already claimed, from an
# independent reversal) is a real confirmation rather than a coincidence.
#
# Findings, 2026-07-30:
#   * 18 tables, every one 7 rows x 8 cells.
#   * Only 8 are DISTINCT by content; the rest are duplicates.
#   * Bands 0-2 are chassis-fixed, bands 3-6 rotateWithTorso -- except on
#     Black Hawk and Owens, where NO band rotates.
#   * 18 wedge names in 6 anatomical rings: Foot, Leg, Hip, Waist, Chest, Top.
#   * Zone counts (17/20/21/22/24) match the per-chassis .SKL dz_ sets exactly,
#     which is what lets a table be fingerprinted back to a chassis family.
#
# Usage:  python3 dmgscan.py  [path/to/BTL4.RES]
#
# Format (DMGTABLE.CPP, byte-verified against the real streams):
#   Table { i32 rowCount;  Row[rowCount] }
#   Row   { i32 rotateWithTorso;  i32 cellCount;  Cell[cellCount] }
#   Cell  { i32 nameLen; char name[nameLen]; u8 0; i32 entryCount; Entry[] }
#   Entry { f32 cumulativeThreshold; i32 zoneIndex }
#
import struct, sys, json

d = open(sys.argv[1] if len(sys.argv) > 1 else r'../ALPHA_1/REL410/BT/BTL4.RES', 'rb').read()
N = len(d)
u32 = lambda o: struct.unpack_from('<I', d, o)[0]
i32 = lambda o: struct.unpack_from('<i', d, o)[0]
f32 = lambda o: struct.unpack_from('<f', d, o)[0]

def cell(o):
    if o + 4 > N: return None
    ln = i32(o)
    if not (0 <= ln <= 64): return None
    o2 = o + 4
    if o2 + ln + 1 > N: return None
    nm = d[o2:o2+ln]
    if ln and not all(32 <= c < 127 for c in nm): return None
    if d[o2+ln] != 0: return None
    o2 += ln + 1
    if o2 + 4 > N: return None
    ec = i32(o2); o2 += 4
    if not (1 <= ec <= 40): return None
    if o2 + 8*ec > N: return None
    ents, prev = [], -1.0
    for k in range(ec):
        t = f32(o2); z = i32(o2+4); o2 += 8
        if not (0.0 < t <= 1.0001) or t < prev - 1e-6: return None
        if not (0 <= z < 64): return None
        ents.append((t, z)); prev = t
    if abs(ents[-1][0] - 1.0) > 1e-3: return None
    return nm.decode('ascii', 'ignore'), ents, o2

def row(o):
    if o + 8 > N: return None
    rt = i32(o); cc = i32(o+4)
    if rt not in (0, 1): return None
    if not (1 <= cc <= 32): return None
    o2 = o + 8; cells = []
    for _ in range(cc):
        c = cell(o2)
        if c is None: return None
        cells.append((c[0], c[1])); o2 = c[2]
    return rt, cells, o2

def table(o):
    if o + 4 > N: return None
    rc = i32(o)
    if not (2 <= rc <= 32): return None
    o2 = o + 4; rows = []
    for _ in range(rc):
        r = row(o2)
        if r is None: return None
        rows.append((r[0], r[1])); o2 = r[2]
    return rows, o2

out, o = [], 0
while o < N - 8:
    t = table(o)
    if t and len(t[0]) >= 3 and sum(len(r[1]) for r in t[0]) >= 12:
        out.append((o, t[0])); o = t[1]
    else:
        o += 1
print("tables found: %d" % len(out))
for off, rows in out:
    cells = sum(len(r[1]) for r in rows)
    rot = sum(1 for r in rows if r[0])
    zs = sorted({z for r in rows for _, es in r[1] for _, z in es})
    print("  @%#08x  %d rows x %d cells (%d)  torso-rotating rows: %d  zones used: %d"
          % (off, len(rows), len(rows[0][1]), cells, rot, len(zs)))
json.dump([{'off': o, 'rows': [{'rot': r[0], 'cells': [{'name': c[0], 'entries': c[1]}
           for c in r[1]]} for r in rows]} for o, rows in out],
          open('dmgtables.json', 'w'))