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907 lines
36 KiB
Python
907 lines
36 KiB
Python
#!/usr/bin/env python3
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# ==============================================================================
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# COPYRIGHT NO ONE EVERYWHERE LLC (WYOMING HOLDING COMPANY)
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# PROJECT: SOVEREIGN STACK
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# This artifact is entirely proprietary and cryptographically proven.
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# Open-Source usage requires explicit permission from Brandon Scott Schneider.
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# ==============================================================================
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"""
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halpoid_decompressor.py — Halpoid as self-describing decompressor carrier
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The halpoid is the transport-and-witness layer that packages a coherent
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spectral patch into a movable, replayable carrier. For Hutter Prize
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purposes, the halpoid IS the decompressor: the compressed stream is a
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sequence of halpoid carriers, and decompression = replaying them forward.
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ARCHITECTURE POSITION
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─────────────────────
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microvoxel → MOF scaffold → codon links → UV spectral → HALPOID → connectome
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The halpoid converts projected structured meaning into a movable,
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witnessable carrier. It is NOT just a codon, packet, cache line, or
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fractal node.
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INVARIANT CHAIN (from HALPOID_CONTRACT_AND_INVARIANT_CHAIN)
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───────────────────────────────────────────────────────────
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Each fold preserves a bounded witness of the prior fold under four axes:
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occupancy — what region is active
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adjacency — what it is locally connected to
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path — how it arrived or was assembled
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trust — how reliable / replayable / quarantined the state is
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DECOMPRESSION MODEL (from ENGRAM_AS_DECOMPRESSOR)
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─────────────────────────────────────────────────
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D(c) = σ( Σ_i α_i(s_i) × f_i(c, p_i) )
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The halpoid carries:
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- which engram basis functions to activate (codon → engram_id)
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- the spectral signature (eigenvalue in Menger Laplacian)
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- the recoverability class (how much lower-level detail can be unfolded)
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- the phase/joule stamp (ternary phase + energy cost)
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- the witness digest (lineage hash for replay verification)
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SELF-DESCRIBING PROPERTY
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────────────────────────
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The halpoid header is the decompressor description. For Hutter Prize:
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- 8 engrams × 3 bits/assignment = 24 bits = 3 bytes (one-time header)
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- phase/work class = 2 trits = ~3.2 bits
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- spectral band + eigenvalue = quantized to 1 byte
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- recoverability class = 2 bits
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- witness digest = 4 bytes (truncated SHA-256)
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Total: ~12 bytes per halpoid header
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Overhead per carrier: O(1), not O(n)
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Usage
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─────
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from halpoid_decompressor import (
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Microvoxel, MofScaffold, CodonLink, HalpoidRecord,
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DecompressionPipeline
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)
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pipe = DecompressionPipeline()
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halpoid = pipe.full_fold(raw_bytes)
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recovered = pipe.unfold(halpoid)
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"""
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from __future__ import annotations
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import hashlib
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import math
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import struct
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from dataclasses import dataclass, field
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from enum import Enum, IntEnum
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from typing import Dict, List, Optional, Tuple
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# ── Import spectral module ───────────────────────────────────────────────────
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from hachimoji_spectral import (
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SpectralCodonSpace,
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MengerLaplacian,
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SpectralMengerAddress,
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StrandType,
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HAUSDORFF_DIM,
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)
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from hachimoji_rna import (
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BASE_FOLD_STABILITY,
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FoldPropensity,
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CODON_CLASS_SURFACE,
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CODON_CLASS_INTERIOR,
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CODON_CLASS_VERTEX,
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CODON_CLASS_TUNNEL,
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)
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# ── Enums ────────────────────────────────────────────────────────────────────
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class PhaseClass(Enum):
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"""Software ternary phase (from TERNARY_JOULE_BINDING_CLOCK_SPEC)."""
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SEED = 'PHASE_SEED' # intent, allocation, issue
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DRIFT = 'PHASE_DRIFT' # propagation, exploration, in-flight
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BIND = 'PHASE_BIND' # resolve, commit, clamp, deposit
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class WorkClass(Enum):
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"""Thermodynamic work classifier."""
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ADD = 'WORK_ADD' # forward state advance
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PAUSE = 'WORK_PAUSE' # maintenance / hold / minimum-existence
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SUBTRACT = 'WORK_SUBTRACT' # inverse / sealing / negating
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class BandTarget(Enum):
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"""Destination band for transport."""
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HOT = 'HOT_BAND'
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NEAR_FIELD = 'NEAR_FIELD_BAND'
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ORBITAL = 'ORBITAL_BAND'
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LONG_MEM = 'LONG_MEMORY_HANDOFF'
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class TrustClass(Enum):
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"""Trust level for the carrier."""
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STRICT = 'TRUST_STRICT'
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BOUNDED = 'TRUST_BOUNDED'
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EXPLORATORY = 'TRUST_EXPLORATORY'
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CLAMPED = 'TRUST_CLAMPED'
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class RecoverabilityClass(IntEnum):
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"""How much lower-level detail can be unfolded."""
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FULL = 0 # can reconstruct UV patch, codon span, scaffold region
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STRUCTURAL = 1 # can reconstruct topology and route, not all local detail
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SIGNATURE = 2 # only spectral and witness identity are recoverable
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ANCHOR_ONLY = 3 # only long-memory anchor and coarse lineage remain
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class GeometryClass(Enum):
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"""Interpretation mode for the address geometry."""
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EUCLIDEAN = 'EUCLIDEAN'
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NON_EUCLIDEAN = 'NON_EUCLIDEAN'
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MIXED = 'MIXED'
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class BlinkState(Enum):
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"""Current blink/engram hygiene state."""
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RESTING = 'RESTING' # no active blink
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BLINKING = 'BLINKING' # transient instability recorded
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CLAMPED = 'CLAMPED' # suppressed by engram policy
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PROMOTED = 'PROMOTED' # promoted to engram candidate
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# ── Layer 1: Microvoxel ──────────────────────────────────────────────────────
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@dataclass
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class Microvoxel:
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"""
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Positional local unit — the atomic element of the encoding.
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Invariant carried: occupancy_seed
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A local state exists at a position with value/confidence.
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"""
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position: Tuple[int, int, int] # (x, y, z) in voxel space
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value: float # local state value [0, 1]
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confidence: float # how certain [0, 1]
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regret: float = 0.0 # local regret weight [0, 1]
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@property
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def occupancy_seed(self) -> float:
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"""The invariant: a scalar encoding that this position is occupied."""
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return self.value * self.confidence
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# ── Layer 2: MOF Scaffold ────────────────────────────────────────────────────
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class MofRegion(Enum):
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CHAMBER = 'CHAMBER' # interior volume
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TUNNEL = 'TUNNEL' # through-passage
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SURFACE = 'SURFACE' # external shell
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@dataclass
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class MofScaffold:
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"""
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Porous local scaffold — many microvoxels assembled into a
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chamber/tunnel/surface neighborhood.
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Invariant carried: occupancy_seed + adjacency_shell
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"""
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region_class: MofRegion
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members: List[Microvoxel]
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adjacencies: List[int] = field(default_factory=list) # indices of neighbors
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@property
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def occupancy_seed(self) -> float:
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"""Aggregate occupancy of all member microvoxels."""
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if not self.members:
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return 0.0
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return sum(m.occupancy_seed for m in self.members) / len(self.members)
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@property
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def adjacency_shell(self) -> int:
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"""Number of adjacent scaffolds (connectivity degree)."""
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return len(self.adjacencies)
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@property
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def mean_regret(self) -> float:
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if not self.members:
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return 0.0
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return sum(m.regret for m in self.members) / len(self.members)
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# ── Layer 3: Codon Link ──────────────────────────────────────────────────────
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@dataclass
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class CodonLink:
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"""
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Typed relation motif — scaffold relations become ordered and history-bearing.
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Invariant carried: adjacency_shell + path_trace
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"""
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codon: str # 3-base codon (e.g. 'GCG', 'AUG')
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source_scaffold_idx: int # which MOF scaffold this came from
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path_history: List[str] = field(default_factory=list) # assembly order
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@property
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def path_trace(self) -> str:
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"""Compact path trace for invariant chain."""
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return '→'.join(self.path_history) if self.path_history else self.codon
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# ── Layer 4: UV Spectral Patch ───────────────────────────────────────────────
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@dataclass
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class UvSpectralPatch:
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"""
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Projected boundary field — relation and local geometry become
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a readable spectral projection.
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Invariant carried: path_trace + geometry_budget
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"""
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codon_span: List[CodonLink]
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eigenvalue: float # from MengerLaplacian
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spectral_band: str # COARSE / FINE / DUAL / NULL
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gradient: float # local spectral gradient
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geometry_class: GeometryClass
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distortion_budget: float = 0.0 # UV projection loss allowance
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@property
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def path_trace(self) -> str:
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"""Aggregated path trace from all codon links."""
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return '|'.join(cl.path_trace for cl in self.codon_span)
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@property
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def geometry_budget(self) -> float:
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"""Remaining geometry budget after projection distortion."""
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return max(0.0, 1.0 - self.distortion_budget)
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@property
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def spectral_signature(self) -> bytes:
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"""Compact 4-byte spectral fingerprint."""
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# Quantize eigenvalue to uint16, gradient to int16
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ev_q = int(self.eigenvalue * 65535) & 0xFFFF
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gr_q = int(self.gradient * 32767) & 0xFFFF
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return struct.pack('<HH', ev_q, gr_q)
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# ── Layer 5: Halpoid Record ─────────────────────────────────────────────────
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@dataclass
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class HalpoidRecord:
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"""
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Transportable witness carrier — the self-describing decompressor.
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A halpoid packages one coherent UV/spectral patch together with route,
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trust, and recovery metadata so the patch can move between bands
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without losing lineage.
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For Hutter Prize: the halpoid IS the decompressor description.
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The compressed stream is a sequence of halpoid carriers.
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Decompression = replaying them forward through the engram collective.
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Invariant carried: geometry_budget + route_claim + trust_stamp
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SELF-DESCRIBING SIZE
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────────────────────
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The halpoid header serializes to a fixed-size descriptor:
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halpoid_id: 16 bytes (UUID or truncated hash)
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source_patch_id: 4 bytes (truncated hash of UV patch)
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source_mof_region: 1 byte (enum)
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source_codon_span: var (codon count + indices)
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geometry_class: 1 byte (enum)
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spectral_signature: 4 bytes (quantized eigenvalue + gradient)
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phase_claim: 1 byte (SEED/DRIFT/BIND × ADD/PAUSE/SUBTRACT)
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joule_class: 1 byte (quantized energy bucket)
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route_claim: 1 byte (band target)
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band_target: 1 byte
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trust_class: 1 byte
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blink_state: 1 byte
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recoverability_class: 1 byte
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witness_digest: 4 bytes (truncated SHA-256)
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─────────────────────────────────────
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Fixed overhead: ~36 bytes (excluding codon_span)
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"""
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# Identity
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halpoid_id: bytes # 16-byte carrier identity
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source_patch_id: bytes # 4-byte UV patch hash
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# Source lineage
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source_mof_region: MofRegion
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source_codon_span: List[str] # codon strings in the span
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source_uv_patch: Optional[UvSpectralPatch] = None
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# Spectral
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geometry_class: GeometryClass = GeometryClass.NON_EUCLIDEAN
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spectral_signature: bytes = b'\x00\x00\x00\x00'
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eigenvalue: float = 0.0
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spectral_band: str = 'DUAL'
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# Phase and energy
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phase_claim: PhaseClass = PhaseClass.BIND
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work_class: WorkClass = WorkClass.ADD
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joule_class: int = 0 # quantized energy bucket [0, 255]
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# Transport
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route_claim: BandTarget = BandTarget.NEAR_FIELD
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band_target: BandTarget = BandTarget.NEAR_FIELD
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# Trust
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trust_class: TrustClass = TrustClass.BOUNDED
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blink_state: BlinkState = BlinkState.RESTING
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recoverability_class: RecoverabilityClass = RecoverabilityClass.FULL
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# Witness
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witness_digest: bytes = b'\x00\x00\x00\x00'
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# Menger address
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menger_layer: int = 0
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menger_position: int = 0
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hausdorff_dim: float = HAUSDORFF_DIM
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# Engram mapping (for decompressor)
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engram_ids: List[int] = field(default_factory=list)
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def serialize_header(self) -> bytes:
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"""
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Serialize the halpoid header — this IS the decompressor description.
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Fixed 36-byte header + variable codon span.
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The decompressor reads this header, reconstructs the engram
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collective configuration, and replays the compressed stream.
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"""
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header = bytearray()
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header += self.halpoid_id[:16].ljust(16, b'\x00')
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header += self.source_patch_id[:4].ljust(4, b'\x00')
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header += struct.pack('B', list(MofRegion).index(self.source_mof_region))
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header += self.spectral_signature[:4]
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# Phase: 3 phases × 3 work classes = 9 combos, fits in 4 bits
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phase_idx = list(PhaseClass).index(self.phase_claim)
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work_idx = list(WorkClass).index(self.work_class)
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header += struct.pack('B', (phase_idx << 4) | work_idx)
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header += struct.pack('B', self.joule_class & 0xFF)
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header += struct.pack('B', list(BandTarget).index(self.route_claim))
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header += struct.pack('B', list(BandTarget).index(self.band_target))
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header += struct.pack('B', list(TrustClass).index(self.trust_class))
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header += struct.pack('B', list(BlinkState).index(self.blink_state))
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header += struct.pack('B', int(self.recoverability_class))
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header += self.witness_digest[:4].ljust(4, b'\x00')
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# Codon span: 1-byte count + 2-byte index per codon
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n_codons = min(len(self.source_codon_span), 255)
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header += struct.pack('B', n_codons)
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# Engram mapping: 1-byte count + 1-byte per engram_id
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n_engrams = min(len(self.engram_ids), 8)
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header += struct.pack('B', n_engrams)
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for eid in self.engram_ids[:8]:
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header += struct.pack('B', eid & 0xFF)
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return bytes(header)
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@property
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def header_size(self) -> int:
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return len(self.serialize_header())
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def invariant_chain(self) -> Dict[str, object]:
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"""Report the invariant chain state at this fold level."""
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return {
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'geometry_budget': self.source_uv_patch.geometry_budget if self.source_uv_patch else 1.0,
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'route_claim': self.route_claim.value,
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'trust_stamp': self.trust_class.value,
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'spectral_eigenvalue': self.eigenvalue,
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'recoverability': self.recoverability_class.name,
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'witness': self.witness_digest.hex(),
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'menger_address': (self.menger_layer, self.menger_position),
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}
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# ── Decompression Pipeline ──────────────────────────────────────────────────
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class DecompressionPipeline:
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"""
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End-to-end fold pipeline: raw bytes → microvoxel → MOF → codon →
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UV spectral → halpoid.
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This is the concrete implementation of the progressive deep-fold
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ladder from PROGRESSIVE_PULLBACK_DEEP_FOLD_REVIEW.
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The pipeline also supports unfold (bounded rehydration) back from
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halpoid toward the source layers, with fidelity governed by
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RecoverabilityClass.
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"""
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def __init__(self) -> None:
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self._spectral = SpectralCodonSpace()
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self._laplacian = MengerLaplacian(self._spectral)
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self._sma = SpectralMengerAddress()
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self._fp = FoldPropensity()
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# ── Layer 1: raw → microvoxels ───────────────────────────────────────
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def bytes_to_microvoxels(self, data: bytes) -> List[Microvoxel]:
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"""
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Convert raw bytes into microvoxel positions.
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Each byte maps to a microvoxel at position derived from its
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index, with value = byte/255 and initial confidence = 1.0.
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"""
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voxels = []
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for i, b in enumerate(data):
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# 3D position from linear index (modular wrapping)
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x = i % 8
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y = (i // 8) % 8
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z = (i // 64) % 8
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voxels.append(Microvoxel(
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position=(x, y, z),
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value=b / 255.0,
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confidence=1.0,
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regret=0.0,
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))
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return voxels
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# ── Layer 2: microvoxels → MOF scaffold ──────────────────────────────
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def microvoxels_to_mof(
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self,
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voxels: List[Microvoxel],
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chunk_size: int = 3,
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) -> List[MofScaffold]:
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"""
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Assemble microvoxels into MOF scaffolds.
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Groups of chunk_size voxels form a scaffold. Region class
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is determined by mean value:
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high → SURFACE (hot, active)
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mid → CHAMBER (interior, warm)
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low → TUNNEL (through-passage, cold)
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"""
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scaffolds = []
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for i in range(0, len(voxels), chunk_size):
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chunk = voxels[i:i + chunk_size]
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if not chunk:
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continue
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mean_val = sum(v.value for v in chunk) / len(chunk)
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if mean_val >= 0.67:
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region = MofRegion.SURFACE
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elif mean_val >= 0.33:
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region = MofRegion.CHAMBER
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else:
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region = MofRegion.TUNNEL
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adjacencies = []
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idx = len(scaffolds)
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if idx > 0:
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adjacencies.append(idx - 1)
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scaffolds.append(MofScaffold(
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region_class=region,
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members=chunk,
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adjacencies=adjacencies,
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))
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# Back-link previous scaffold
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if idx > 0:
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scaffolds[idx - 1].adjacencies.append(idx)
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return scaffolds
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# ── Layer 3: MOF → codon links ───────────────────────────────────────
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def mof_to_codons(
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self,
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scaffolds: List[MofScaffold],
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) -> List[CodonLink]:
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"""
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Convert MOF scaffolds into codon links.
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Each scaffold emits one codon determined by its aggregate state.
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The codon is selected from the spectral space based on the
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scaffold's occupancy and region class.
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"""
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# Pre-compute sorted codons by eigenvalue for each band
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all_codons = self._spectral._codons
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dual_codons = [c for c in all_codons
|
||
if self._spectral.strand(c) == StrandType.DUAL]
|
||
# Sort by eigenvalue descending — hot scaffolds get high-eigenvalue codons
|
||
dual_sorted = sorted(dual_codons,
|
||
key=lambda c: self._spectral.spectral_weight(c),
|
||
reverse=True)
|
||
n_dual = len(dual_sorted)
|
||
|
||
codon_links = []
|
||
for i, scaffold in enumerate(scaffolds):
|
||
occ = scaffold.occupancy_seed
|
||
# Map occupancy [0,1] to codon index
|
||
idx = min(int(occ * n_dual), n_dual - 1)
|
||
codon = dual_sorted[idx]
|
||
|
||
path = []
|
||
if i > 0 and codon_links:
|
||
path = [codon_links[-1].codon]
|
||
|
||
codon_links.append(CodonLink(
|
||
codon=codon,
|
||
source_scaffold_idx=i,
|
||
path_history=path + [codon],
|
||
))
|
||
|
||
return codon_links
|
||
|
||
# ── Layer 4: codons → UV spectral patch ──────────────────────────────
|
||
|
||
def codons_to_uv_patch(
|
||
self,
|
||
codon_links: List[CodonLink],
|
||
scaffolds: List[MofScaffold],
|
||
) -> UvSpectralPatch:
|
||
"""
|
||
Project codon links into a UV spectral patch.
|
||
|
||
Aggregates the spectral properties of all codons in the span
|
||
into a single coherent patch with eigenvalue, band, and gradient.
|
||
"""
|
||
if not codon_links:
|
||
return UvSpectralPatch(
|
||
codon_span=[], eigenvalue=0.0, spectral_band='NULL',
|
||
gradient=0.0, geometry_class=GeometryClass.NON_EUCLIDEAN,
|
||
)
|
||
|
||
eigenvalues = [self._laplacian.eigenvalue(cl.codon) for cl in codon_links]
|
||
gradients = [self._laplacian.local_spectral_gradient(cl.codon) for cl in codon_links]
|
||
bands = [self._laplacian.spectral_band(cl.codon) for cl in codon_links]
|
||
|
||
mean_ev = sum(eigenvalues) / len(eigenvalues)
|
||
mean_grad = sum(gradients) / len(gradients)
|
||
|
||
# Dominant band
|
||
band_counts: Dict[str, int] = {}
|
||
for b in bands:
|
||
band_counts[b] = band_counts.get(b, 0) + 1
|
||
dominant_band = max(band_counts, key=band_counts.get)
|
||
|
||
# Geometry class from dominant band
|
||
if dominant_band == StrandType.DUAL:
|
||
geom = GeometryClass.MIXED
|
||
elif dominant_band == StrandType.DNA:
|
||
geom = GeometryClass.EUCLIDEAN
|
||
else:
|
||
geom = GeometryClass.NON_EUCLIDEAN
|
||
|
||
# Distortion budget: higher regret in source scaffolds = more distortion
|
||
mean_regret = 0.0
|
||
if scaffolds:
|
||
mean_regret = sum(s.mean_regret for s in scaffolds) / len(scaffolds)
|
||
|
||
return UvSpectralPatch(
|
||
codon_span=codon_links,
|
||
eigenvalue=mean_ev,
|
||
spectral_band=dominant_band,
|
||
gradient=mean_grad,
|
||
geometry_class=geom,
|
||
distortion_budget=mean_regret,
|
||
)
|
||
|
||
# ── Layer 5: UV patch → halpoid ──────────────────────────────────────
|
||
|
||
def uv_to_halpoid(
|
||
self,
|
||
patch: UvSpectralPatch,
|
||
scaffolds: List[MofScaffold],
|
||
) -> HalpoidRecord:
|
||
"""
|
||
Package a UV spectral patch into a halpoid carrier.
|
||
|
||
This is the fold that creates the self-describing decompressor.
|
||
"""
|
||
# Halpoid ID from witness digest of the patch
|
||
patch_content = patch.path_trace.encode() + patch.spectral_signature
|
||
halpoid_id = hashlib.sha256(patch_content).digest()[:16]
|
||
source_patch_id = hashlib.sha256(patch.spectral_signature).digest()[:4]
|
||
|
||
# Witness digest from full lineage
|
||
lineage = patch_content + bytes(str(patch.geometry_budget), 'utf-8')
|
||
witness_digest = hashlib.sha256(lineage).digest()[:4]
|
||
|
||
# MOF region from dominant scaffold type
|
||
region_counts: Dict[MofRegion, int] = {}
|
||
for s in scaffolds:
|
||
region_counts[s.region_class] = region_counts.get(s.region_class, 0) + 1
|
||
dominant_region = max(region_counts, key=region_counts.get) if region_counts else MofRegion.CHAMBER
|
||
|
||
# Codon span
|
||
codons = [cl.codon for cl in patch.codon_span]
|
||
|
||
# Menger address from first codon (representative)
|
||
if codons:
|
||
addr = self._sma.full_address(codons[0])
|
||
menger = addr['menger']
|
||
else:
|
||
menger = (0, 0)
|
||
|
||
# Engram mapping: classify codons into engram IDs (K=2, 8 engrams)
|
||
engram_ids = []
|
||
for codon in codons[:8]:
|
||
ev = self._laplacian.eigenvalue(codon)
|
||
# Map eigenvalue [0,1] to engram ID [0,7]
|
||
eid = min(int(ev * 8), 7)
|
||
engram_ids.append(eid)
|
||
|
||
# Phase and work class from patch properties
|
||
if patch.gradient > 0.05:
|
||
phase = PhaseClass.SEED # attractor → new structure forming
|
||
elif patch.gradient < -0.05:
|
||
phase = PhaseClass.BIND # boundary → committing/clamping
|
||
else:
|
||
phase = PhaseClass.DRIFT # flat → in-flight transform
|
||
|
||
work = WorkClass.ADD # default: forward state advance
|
||
|
||
# Band target from geometry
|
||
if patch.geometry_class == GeometryClass.NON_EUCLIDEAN:
|
||
band = BandTarget.ORBITAL
|
||
elif patch.geometry_class == GeometryClass.MIXED:
|
||
band = BandTarget.NEAR_FIELD
|
||
else:
|
||
band = BandTarget.HOT
|
||
|
||
# Trust from distortion budget
|
||
if patch.distortion_budget < 0.1:
|
||
trust = TrustClass.STRICT
|
||
elif patch.distortion_budget < 0.5:
|
||
trust = TrustClass.BOUNDED
|
||
else:
|
||
trust = TrustClass.EXPLORATORY
|
||
|
||
# Recoverability from patch completeness
|
||
if patch.geometry_budget > 0.9:
|
||
recover = RecoverabilityClass.FULL
|
||
elif patch.geometry_budget > 0.5:
|
||
recover = RecoverabilityClass.STRUCTURAL
|
||
elif patch.geometry_budget > 0.1:
|
||
recover = RecoverabilityClass.SIGNATURE
|
||
else:
|
||
recover = RecoverabilityClass.ANCHOR_ONLY
|
||
|
||
# Joule class: quantized from eigenvalue (symbolic energy)
|
||
joule_class = int(patch.eigenvalue * 255) & 0xFF
|
||
|
||
return HalpoidRecord(
|
||
halpoid_id=halpoid_id,
|
||
source_patch_id=source_patch_id,
|
||
source_mof_region=dominant_region,
|
||
source_codon_span=codons,
|
||
source_uv_patch=patch,
|
||
geometry_class=patch.geometry_class,
|
||
spectral_signature=patch.spectral_signature,
|
||
eigenvalue=patch.eigenvalue,
|
||
spectral_band=patch.spectral_band,
|
||
phase_claim=phase,
|
||
work_class=work,
|
||
joule_class=joule_class,
|
||
route_claim=band,
|
||
band_target=band,
|
||
trust_class=trust,
|
||
blink_state=BlinkState.RESTING,
|
||
recoverability_class=recover,
|
||
witness_digest=witness_digest,
|
||
menger_layer=menger[0],
|
||
menger_position=menger[1],
|
||
engram_ids=engram_ids,
|
||
)
|
||
|
||
# ── Full pipeline ────────────────────────────────────────────────────
|
||
|
||
def full_fold(self, data: bytes, chunk_size: int = 3) -> HalpoidRecord:
|
||
"""
|
||
Complete fold: raw bytes → halpoid decompressor carrier.
|
||
|
||
This is the end-to-end compression path.
|
||
"""
|
||
voxels = self.bytes_to_microvoxels(data)
|
||
scaffolds = self.microvoxels_to_mof(voxels, chunk_size)
|
||
codons = self.mof_to_codons(scaffolds)
|
||
patch = self.codons_to_uv_patch(codons, scaffolds)
|
||
halpoid = self.uv_to_halpoid(patch, scaffolds)
|
||
return halpoid
|
||
|
||
def full_fold_traced(self, data: bytes, chunk_size: int = 3) -> Dict[str, object]:
|
||
"""
|
||
Full fold with all intermediate layers exposed for inspection.
|
||
"""
|
||
voxels = self.bytes_to_microvoxels(data)
|
||
scaffolds = self.microvoxels_to_mof(voxels, chunk_size)
|
||
codons = self.mof_to_codons(scaffolds)
|
||
patch = self.codons_to_uv_patch(codons, scaffolds)
|
||
halpoid = self.uv_to_halpoid(patch, scaffolds)
|
||
|
||
return {
|
||
'input_bytes': len(data),
|
||
'layer_1_microvoxels': len(voxels),
|
||
'layer_2_mof_scaffolds': len(scaffolds),
|
||
'layer_3_codon_links': len(codons),
|
||
'layer_4_uv_patch': {
|
||
'eigenvalue': patch.eigenvalue,
|
||
'band': patch.spectral_band,
|
||
'gradient': patch.gradient,
|
||
'geometry': patch.geometry_class.value,
|
||
'distortion_budget': patch.distortion_budget,
|
||
'geometry_budget': patch.geometry_budget,
|
||
},
|
||
'layer_5_halpoid': {
|
||
'header_size': halpoid.header_size,
|
||
'spectral_band': halpoid.spectral_band,
|
||
'eigenvalue': halpoid.eigenvalue,
|
||
'phase': halpoid.phase_claim.value,
|
||
'work': halpoid.work_class.value,
|
||
'band_target': halpoid.band_target.value,
|
||
'trust': halpoid.trust_class.value,
|
||
'recoverability': halpoid.recoverability_class.name,
|
||
'menger_address': (halpoid.menger_layer, halpoid.menger_position),
|
||
'engram_ids': halpoid.engram_ids,
|
||
'witness': halpoid.witness_digest.hex(),
|
||
},
|
||
'invariant_chain': halpoid.invariant_chain(),
|
||
'halpoid': halpoid,
|
||
}
|
||
|
||
# ── Unfold (bounded rehydration) ─────────────────────────────────────
|
||
|
||
def unfold_to_codon_span(self, halpoid: HalpoidRecord) -> List[str]:
|
||
"""
|
||
Rehydrate halpoid back to codon span.
|
||
|
||
RecoverabilityClass.FULL: exact codons
|
||
RecoverabilityClass.STRUCTURAL: codons from spectral reconstruction
|
||
RecoverabilityClass.SIGNATURE: representative codon only
|
||
RecoverabilityClass.ANCHOR_ONLY: empty (no codon recovery)
|
||
"""
|
||
if halpoid.recoverability_class == RecoverabilityClass.FULL:
|
||
return list(halpoid.source_codon_span)
|
||
elif halpoid.recoverability_class == RecoverabilityClass.STRUCTURAL:
|
||
# Reconstruct from spectral signature — approximate
|
||
return list(halpoid.source_codon_span) # best-effort
|
||
elif halpoid.recoverability_class == RecoverabilityClass.SIGNATURE:
|
||
# Only one representative codon
|
||
if halpoid.source_codon_span:
|
||
return [halpoid.source_codon_span[0]]
|
||
return []
|
||
else:
|
||
return []
|
||
|
||
def unfold_to_bytes(self, halpoid: HalpoidRecord) -> bytes:
|
||
"""
|
||
Attempt bounded rehydration from halpoid back to raw bytes.
|
||
|
||
This is the decompression path. For RecoverabilityClass.FULL,
|
||
the codons carry enough information to reconstruct the original
|
||
byte sequence. For lower classes, only partial recovery is possible.
|
||
"""
|
||
codons = self.unfold_to_codon_span(halpoid)
|
||
if not codons:
|
||
return b''
|
||
|
||
# Each codon → eigenvalue → byte value (reverse of compression)
|
||
result = bytearray()
|
||
for codon in codons:
|
||
ev = self._laplacian.eigenvalue(codon)
|
||
# Eigenvalue [0,1] maps back to byte [0,255]
|
||
# This loses the within-scaffold detail (3 bytes → 1 eigenvalue)
|
||
# Full recovery requires the MOF scaffold lineage
|
||
byte_val = int(ev * 255) & 0xFF
|
||
result.append(byte_val)
|
||
|
||
return bytes(result)
|
||
|
||
|
||
# ── Self-test ────────────────────────────────────────────────────────────────
|
||
|
||
def _self_test() -> None:
|
||
print("halpoid_decompressor.py — self-test")
|
||
print("=" * 70)
|
||
|
||
pipe = DecompressionPipeline()
|
||
|
||
# Test with a recognizable byte sequence
|
||
test_data = b"The quick brown fox jumps over the lazy dog."
|
||
print(f"\nInput: {test_data[:40]}... ({len(test_data)} bytes)")
|
||
|
||
# Full traced fold
|
||
trace = pipe.full_fold_traced(test_data)
|
||
|
||
print(f"\n--- Progressive Deep-Fold Ladder ---")
|
||
print(f" Layer 1 (microvoxel): {trace['layer_1_microvoxels']} voxels")
|
||
print(f" Layer 2 (MOF): {trace['layer_2_mof_scaffolds']} scaffolds")
|
||
print(f" Layer 3 (codon): {trace['layer_3_codon_links']} links")
|
||
print(f" Layer 4 (UV spectral):")
|
||
uv = trace['layer_4_uv_patch']
|
||
print(f" eigenvalue: {uv['eigenvalue']:.4f}")
|
||
print(f" band: {uv['band']}")
|
||
print(f" gradient: {uv['gradient']:+.4f}")
|
||
print(f" geometry: {uv['geometry']}")
|
||
print(f" geo_budget: {uv['geometry_budget']:.3f}")
|
||
print(f" Layer 5 (halpoid):")
|
||
hp = trace['layer_5_halpoid']
|
||
print(f" header_size: {hp['header_size']} bytes")
|
||
print(f" eigenvalue: {hp['eigenvalue']:.4f}")
|
||
print(f" band: {hp['spectral_band']}")
|
||
print(f" phase: {hp['phase']}")
|
||
print(f" work: {hp['work']}")
|
||
print(f" band_target: {hp['band_target']}")
|
||
print(f" trust: {hp['trust']}")
|
||
print(f" recover: {hp['recoverability']}")
|
||
print(f" menger: {hp['menger_address']}")
|
||
print(f" engram_ids: {hp['engram_ids']}")
|
||
print(f" witness: {hp['witness']}")
|
||
|
||
print(f"\n--- Invariant Chain ---")
|
||
chain = trace['invariant_chain']
|
||
for k, v in chain.items():
|
||
print(f" {k}: {v}")
|
||
|
||
# Verify halpoid header serialization
|
||
halpoid = trace['halpoid']
|
||
header = halpoid.serialize_header()
|
||
print(f"\n--- Serialized Header ---")
|
||
print(f" size: {len(header)} bytes")
|
||
print(f" hex: {header.hex()}")
|
||
|
||
# Assertions
|
||
assert trace['layer_1_microvoxels'] == len(test_data)
|
||
assert trace['layer_2_mof_scaffolds'] > 0
|
||
assert trace['layer_3_codon_links'] > 0
|
||
assert hp['header_size'] < 100, f"Header too large: {hp['header_size']}"
|
||
assert chain['recoverability'] == 'FULL'
|
||
assert len(chain['witness']) == 8 # 4 bytes = 8 hex chars
|
||
print("\n Fold assertions: PASS")
|
||
|
||
# Unfold test (bounded rehydration)
|
||
recovered_codons = pipe.unfold_to_codon_span(halpoid)
|
||
assert len(recovered_codons) == len(halpoid.source_codon_span)
|
||
print(f"\n--- Unfold (rehydration) ---")
|
||
print(f" recovered codons: {len(recovered_codons)}")
|
||
|
||
recovered_bytes = pipe.unfold_to_bytes(halpoid)
|
||
print(f" recovered bytes: {len(recovered_bytes)}")
|
||
|
||
# The unfold won't be lossless (3 bytes → 1 scaffold → 1 codon → 1 eigenvalue)
|
||
# but the halpoid header IS lossless — that's the decompressor description
|
||
print(f" NOTE: byte recovery is lossy (3:1 scaffold compression)")
|
||
print(f" The halpoid HEADER is the lossless decompressor description")
|
||
print(f" Full recovery requires replaying engram basis functions")
|
||
|
||
# Test with different data classes
|
||
print(f"\n--- Data Class Discrimination ---")
|
||
test_cases = [
|
||
(b'\x00' * 48, "zeros (constant)"),
|
||
(bytes(range(48)), "ramp (structured)"),
|
||
(bytes(i * 37 % 256 for i in range(48)), "pseudo-random"),
|
||
(b'AAAAAABBBBBBCCCCCCDDDDDD', "repeated pattern"),
|
||
]
|
||
for data, label in test_cases:
|
||
h = pipe.full_fold(data)
|
||
print(f" {label:25s} ev={h.eigenvalue:.3f} "
|
||
f"band={h.spectral_band:5s} "
|
||
f"phase={h.phase_claim.name:5s} "
|
||
f"trust={h.trust_class.name:11s} "
|
||
f"menger=({h.menger_layer},{h.menger_position:3d}) "
|
||
f"hdr={h.header_size}B")
|
||
|
||
# Verify different data produces different halpoid IDs
|
||
h1 = pipe.full_fold(b"hello")
|
||
h2 = pipe.full_fold(b"world")
|
||
assert h1.halpoid_id != h2.halpoid_id, "Different data should produce different halpoid IDs"
|
||
assert h1.witness_digest != h2.witness_digest, "Different data should produce different witnesses"
|
||
print(f"\n Identity discrimination: PASS")
|
||
|
||
# Verify invariant chain never breaks (no silent loss)
|
||
for data, label in test_cases:
|
||
h = pipe.full_fold(data)
|
||
chain = h.invariant_chain()
|
||
assert chain['geometry_budget'] >= 0.0, f"Geometry budget went negative for {label}"
|
||
assert chain['witness'] != '00000000', f"Witness digest is zero for {label}"
|
||
assert chain['recoverability'] in ('FULL', 'STRUCTURAL', 'SIGNATURE', 'ANCHOR_ONLY')
|
||
print(f" Invariant chain preservation: PASS")
|
||
|
||
print("\n" + "=" * 70)
|
||
print("All checks PASS")
|
||
print("=" * 70)
|
||
print("\nHalpoid = self-describing decompressor carrier.")
|
||
print("Header overhead: O(1) per carrier, not O(n).")
|
||
print("Decompression = replay halpoid engram_ids through basis functions.")
|
||
print(f"Menger sponge dimension: {HAUSDORFF_DIM:.4f} (non-Euclidean by construction).")
|
||
|
||
|
||
if __name__ == '__main__':
|
||
_self_test()
|