Research-Stack/0-Core-Formalism/lean/external/OTOM/VoxelEncoding.lean

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/-
VoxelEncoding.lean - Voxel, Seed, Sieve, and Topological Encoding
Ports rows 124-133 from MATH_MODEL_MAP.tsv (Python → Lean).
-/
import Semantics.Bind
import Semantics.FixedPoint
namespace Semantics.VoxelEncoding
open Q16_16
-- Row 124: Voxel Key Encoding (30-bit packed)
-- key = ((x+512) &&& 0x3FF) <<< 20 ||| ((y+512) &&& 0x3FF) <<< 10 ||| ((z+512) &&& 0x3FF)
-- x,y,z ∈ [-512, 511]
structure VoxelKey where
val : UInt32
deriving Repr, DecidableEq, Inhabited, BEq
def encodeVoxel (x y z : Int) : VoxelKey :=
let cx := (x + 512).toNat &&& 0x3FF
let cy := (y + 512).toNat &&& 0x3FF
let cz := (z + 512).toNat &&& 0x3FF
⟨UInt32.ofNat (cx <<< 20 ||| cy <<< 10 ||| cz)⟩
def decodeVoxel (k : VoxelKey) : (Int × Int × Int) :=
let cx := (k.val.toNat >>> 20) % 0x400
let cy := (k.val.toNat >>> 10) % 0x400
let cz := k.val.toNat % 0x400
(Int.ofNat cx - 512, Int.ofNat cy - 512, Int.ofNat cz - 512)
-- Row 125: Microvoxel Seed 4-Byte Encoding
-- 32-bit: delta_p[9:0]|region[13:10]|gamma[18:14]|activation[22:19]|polarity[26:23]|confidence[30:27]|flag[31]
structure MicrovoxelSeed where
deltaP : UInt32 -- 10 bits [9:0]
region : UInt32 -- 4 bits [13:10]
gamma : UInt32 -- 5 bits [18:14]
activation : UInt32 -- 4 bits [22:19]
polarity : UInt32 -- 4 bits [26:23]
confidence : UInt32 -- 4 bits [30:27]
flag : Bool
deriving Repr, Inhabited, DecidableEq
def encodeSeed (s : MicrovoxelSeed) : UInt32 :=
(s.deltaP &&& (0x3FF : UInt32)) |||
((s.region &&& (0xF : UInt32)) <<< 10) |||
((s.gamma &&& (0x1F : UInt32)) <<< 14) |||
((s.activation &&& (0xF : UInt32)) <<< 19) |||
((s.polarity &&& (0xF : UInt32)) <<< 23) |||
((s.confidence &&& (0xF : UInt32)) <<< 27) |||
(if s.flag then (0x80000000 : UInt32) else 0)
inductive SeedClass | Exclude | Explore | Promote deriving Repr, DecidableEq, Inhabited
def classifySeedByEfficiency (eff : Q16_16) : SeedClass :=
-- eff < 0.8 → 52429; eff < 1.2 → 78643
if eff.val < 52429 then .Exclude
else if eff.val < 78643 then .Explore
else .Promote
-- Row 126: DCVN Verification Invariant Survival
-- 4 invariants: completeness(c), consistency(s), freshness(f), provenance(p)
structure DCVNState where
completeness : Q16_16
consistency : Q16_16
freshness : Q16_16
provenance : Q16_16
deriving Repr, Inhabited, DecidableEq
inductive DCVNParticipation | Full | Partial | Observer | Absent
deriving Repr, DecidableEq, Inhabited
def dcvnThreshold : Q16_16 := ⟨52429⟩ -- 0.8 * 65536
def dcvnSurvivalMask (s : DCVNState) : UInt8 :=
(if s.completeness.val >= dcvnThreshold.val then 0b1000 else 0) |||
(if s.consistency.val >= dcvnThreshold.val then 0b0100 else 0) |||
(if s.freshness.val >= dcvnThreshold.val then 0b0010 else 0) |||
(if s.provenance.val >= dcvnThreshold.val then 0b0001 else 0)
def dcvnParticipation (s : DCVNState) : DCVNParticipation :=
let bits := (dcvnSurvivalMask s).toNat
let count := (if bits &&& 8 != 0 then 1 else 0) + (if bits &&& 4 != 0 then 1 else 0) +
(if bits &&& 2 != 0 then 1 else 0) + (if bits &&& 1 != 0 then 1 else 0)
if count == 4 then .Full
else if count >= 2 then .Partial
else if count >= 1 then .Observer
else .Absent
-- Row 127: Watanabe Total Correlation + Kolmogorov complexity approximation
-- TC ≈ (0.4 · kolmogorov + 0.4 · entropy/8 + 0.2 · CV) in Q16.16
def totalCorrelationEstimate (kolmogorov entropy cv : Q16_16) : Q16_16 :=
-- 0.4 = 26214; 0.2 = 13107
let w1 : Q16_16 := ⟨26214⟩
let w2 : Q16_16 := ⟨26214⟩
let w3 : Q16_16 := ⟨13107⟩
let entropyNorm := div entropy ⟨8 * 65536⟩
add (add (mul w1 kolmogorov) (mul w2 entropyNorm)) (mul w3 cv)
-- Row 128: Relation Sieve 5-Symbol packing
-- Pack 5×2-bit symbols into 10-bit: sig = (T<<<8)|(D<<<6)|(C<<<4)|(A<<<2)|R
structure SieveSymbols where
torsion : UInt8 -- 2-bit [0..3]
drift : UInt8 -- 2-bit
coherence : UInt8 -- 2-bit
angmom : UInt8 -- 2-bit
radius : UInt8 -- 2-bit
deriving Repr, Inhabited, DecidableEq
def packSieveSymbols (s : SieveSymbols) : UInt16 :=
(s.torsion.toUInt16 <<< 8) |||
(s.drift.toUInt16 <<< 6) |||
(s.coherence.toUInt16 <<< 4) |||
(s.angmom.toUInt16 <<< 2) |||
s.radius.toUInt16
inductive SieveDecision | Pass | Hold | Reject deriving Repr, DecidableEq, Inhabited
def classifySieve (s : SieveSymbols) : SieveDecision :=
if s.torsion == 3 || s.angmom == 3 || s.coherence == 3 ||
(s.torsion >= 2 && s.coherence >= 2) ||
(s.drift == 3 && s.angmom >= 2) ||
(s.radius == 3 && s.coherence >= 2)
then .Reject
else if s.torsion == 2 || s.drift == 2 || s.coherence >= 1
then .Hold
else .Pass
-- Row 129: Proxy Extraction
def proxyExtractTorsion (torsionSamples : Array Q16_16) : UInt8 :=
let sum := Array.foldl (fun acc s => acc + s.val) 0 (torsionSamples.take 32)
let scaled := (sum / 65536) * 100
UInt8.ofNat (Nat.min 255 scaled.toNat)
def proxyExtractCoherence (torsion : UInt8) : UInt8 :=
255 - torsion
-- Row 130: SEISMIC Shell Detection bounds
-- 0.35 ≤ φ_corr < 0.47 in Q16.16: [22938, 30801]
def seismicLow : UInt32 := 22938 -- 0.35 * 65536
def seismicHigh : UInt32 := 30801 -- 0.47 * 65536
def isSeismicShell (phiCorr : Q16_16) : Bool :=
phiCorr.val >= seismicLow && phiCorr.val < seismicHigh
-- Row 131: Half Möbius Closure Integral ∮τ·ds = π
-- Accumulate until torsion integral reaches π (≈205887 in Q16.16)
def piQ : Q16_16 := ⟨205887⟩ -- π * 65536
def halfMobiusClosure (torsionSamples : Array Q16_16) (stepSize : Q16_16) : Option Nat :=
let rec go (i : Nat) (acc : Q16_16) : Option Nat :=
if i >= torsionSamples.size then none
else
let newAcc := add acc (mul torsionSamples[i]! stepSize)
if newAcc.val >= piQ.val then some i
else go (i + 1) newAcc
go 0 zero
-- Row 132: Regret Field Blink Cycle
def baselineMs : Q16_16 := ⟨500 * 65536⟩ -- 500ms
def regretMs : Q16_16 := ⟨700 * 65536⟩ -- 700ms
def decayLambda : Q16_16 := ⟨2 * 65536⟩ -- λ = 2.0
def blinkDuration (regretMagnitude : Q16_16) : Q16_16 :=
let range := sub regretMs baselineMs
let offset := mul range regretMagnitude
add baselineMs offset
def regretDecay (regret dt : Q16_16) : Q16_16 :=
let ldt := mul decayLambda dt
if ldt.val >= one.val then zero
else mul regret (sub one ldt)
-- Row 133: Hugoniot Shock — kinetic energy harvesting
-- E_kinetic = ½ · I · ω²; E_harvested = E_stored · efficiency (Q16.16)
def kineticEnergy (momentOfInertia omega : Q16_16) : Q16_16 :=
mul ⟨32768⟩ (mul momentOfInertia (mul omega omega)) -- ½ * I * ω²
def harvestedEnergy (stored efficiency : Q16_16) : Q16_16 :=
mul stored efficiency
-- Bind wrappers
def voxelInvariant (k : VoxelKey) : String := s!"voxel:{k.val}"
def voxelCost (a b : VoxelKey) (_m : Metric) : UInt32 :=
if a.val > b.val then a.val - b.val else b.val - a.val
def voxelBind (a b : VoxelKey) (m : Metric) : Bind VoxelKey VoxelKey :=
geometricBind a b m voxelCost voxelInvariant voxelInvariant
def sieveInvariant (s : SieveSymbols) : String :=
s!"sieve:{s.torsion}{s.drift}{s.coherence}{s.angmom}{s.radius}"
def sieveCostFn (a b : SieveSymbols) (_m : Metric) : UInt32 :=
(packSieveSymbols a).toUInt32 + (packSieveSymbols b).toUInt32
def sieveControlBind (a b : SieveSymbols) (m : Metric) : Bind SieveSymbols SieveSymbols :=
controlBind a b m sieveCostFn sieveInvariant sieveInvariant
-- Verify
#eval encodeVoxel 0 0 0
#eval decodeVoxel (encodeVoxel 100 (-50) 200) -- expect (100, -50, 200)
#eval classifySieve { torsion := 3, drift := 0, coherence := 0, angmom := 0, radius := 0 }
#eval isSeismicShell ⟨26214⟩ -- 0.4 * 65536 → should be true
end Semantics.VoxelEncoding