"""Numeric verification of the edge decode. The edge SEND payloads carry floats
~0.1262. Edges are pure screen-space (no z ambiguity), so if 0.1262 matches an
object edge's line coefficient computed from the captured screen vertices, the
edge decode is confirmed. Try normalised normal, raw dy/dx, and dx/len forms."""
import sys, time, struct, pickle, math
sys.path.insert(0, r'C:\VWE\TeslaRel410\emulator\firmware-decomp')
import emu860, dis860, emu_main
emu860.Mem.log = lambda self, *a, **k: None
S = r'C:\Users\cyd\AppData\Local\Temp\claude\c--VWE-TeslaRel410\4e848c76-6e89-4034-8047-d8d491cb32d8\scratchpad'

snap = pickle.load(open(S + r'\snapv2.pkl', 'rb'))
r = emu_main.MainRunner(r'C:\VWE\TeslaRel410\dpl3-revive\patha\cap7.raw.bin', fw='capfw7', max_cmds=6000)
cpu = r.cpu
cpu.mem.pages = {k: bytearray(v) for k, v in snap['pages'].items()}
cpu.ctrl.clear(); cpu.ctrl.update(snap['ctrl'])
cpu.r = list(snap['r']); cpu.f = list(snap['f']); cpu.cr = dict(snap['cr']); cpu.pc = snap['pc']
cpu._apipe = list(snap['apipe']); cpu._mpipe = list(snap['mpipe']); cpu._fp_pipes()
cpu._lpipe = list(snap['lpipe']); cpu._gpipe = list(snap['gpipe'])
cpu._kr, cpu._ki, cpu._t = snap['kr'], snap['ki'], snap['t']
cpu.lcc = snap['lcc']; r.qi = snap['qi']; r.heap = list(snap['heap'])
t0 = time.time(); startq = r.qi
while time.time() - t0 < 60:
    if r.qi >= startq + 2: break
    h = r.hooks.get(cpu.pc)
    if h:
        if h(cpu) == 'done': break
        continue
    if not cpu.step(): break
def rw(a): return cpu.mem.r32(a & 0xffffffff)
def asf(w): return struct.unpack('<f', struct.pack('<I', w))[0]

# edge-family payload floats (from SEND(4) + SEND(0x21) headers): the ~0.125 group
edge_floats = set()
for base, n in [(0x08015000, 4), (0x08015260, 0x21)]:
    for i in range(n):
        f = asf(rw(base + i * 4))
        if 0.05 < abs(f) < 0.5:
            edge_floats.add(round(f, 5))
print("edge-family payload floats:", sorted(edge_floats, key=abs))

# object edges (screen space) from captured verts -> candidate coefficient forms
objs = pickle.load(open(S + r'\vfull.pkl', 'rb'))['objs']
allv = [v for o in objs for v in o]
xs = sorted(set(round(v['mx'], 2) for v in allv)); zs = sorted(set(round(v['mz'], 2) for v in allv))
grid = {(round(v['mx'], 2), round(v['mz'], 2)): v for v in allv}
cands = []   # (value, form, edge desc)
for i in range(len(xs)-1):
    for j in range(len(zs)-1):
        tri = [grid[(xs[i],zs[j])], grid[(xs[i+1],zs[j])], grid[(xs[i],zs[j+1])]]
        for k in range(3):
            p, q = tri[k], tri[(k+1)%3]
            dx = q['sx']-p['sx']; dy = q['sy']-p['sy']; L = math.hypot(dx,dy) or 1
            cands.append((abs(dy/L), 'norm|A|'))     # normalised normal x-comp
            cands.append((abs(dx/L), 'norm|B|'))     # normalised normal y-comp
# match each payload edge float to nearest candidate
print("\nmatches:")
for ef in sorted(edge_floats, key=abs):
    best = min(cands, key=lambda c: abs(abs(ef)-c[0]))
    err = abs(abs(ef)-best[0]) / max(abs(ef), 1e-6) * 100
    print("  payload %.5f  ~  %.5f (%s)   err %.1f%%" % (ef, best[0], best[1], err))