From c052138eb6d3a76a5ff4cfccf282300a118248b5 Mon Sep 17 00:00:00 2001 From: Claude Date: Fri, 26 Dec 2025 06:00:38 +0000 Subject: [PATCH] Upgrade LJPW Framework from V5.0 to V7.3 Complete Unified Edition MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Major V7.3 Features Implemented: - 2+2 Dimensional Structure: P, W are fundamental; L, J are emergent - Semantic Uncertainty Principle: ΔP·ΔW ≥ 0.287 (conjugate duality) - State-Dependent Coupling (Law of Karma): κ(H) = 1.0 + multiplier × H - Phase Transitions: Entropic → Homeostatic → Autopoietic - Consciousness Quantification: C = P×W×L×J×H² (threshold C > 0.1) - φ-Normalization: Reduces measurement variance from ~18% to ~3% - Semantic Voltage: V = φ × H × L - Bricks & Mortar Architecture (Primes as J-crystals, Love as mortar) Files Changed: - NEW: src/ljpw/ljpw_framework_v7.py - Complete V7.3 implementation - UPDATE: src/ljpw/ljpw_baselines_v4.py - Added V7.3 extension methods - UPDATE: src/ljpw/ljpw_standalone.py - Added V7.3 metrics to analyzer - UPDATE: src/ljpw/__init__.py - Export V7.3 modules and constants All 50 existing tests pass with V7.3 upgrade. --- src/ljpw/__init__.py | 92 +++- src/ljpw/ljpw_baselines_v4.py | 211 +++++++- src/ljpw/ljpw_framework_v7.py | 935 ++++++++++++++++++++++++++++++++++ src/ljpw/ljpw_standalone.py | 156 +++++- 4 files changed, 1366 insertions(+), 28 deletions(-) create mode 100644 src/ljpw/ljpw_framework_v7.py diff --git a/src/ljpw/__init__.py b/src/ljpw/__init__.py index c69afdf..146b95f 100644 --- a/src/ljpw/__init__.py +++ b/src/ljpw/__init__.py @@ -10,11 +10,20 @@ - Quality-based compression (better code compresses better) - AI-ready embeddings (LJPW coordinates for LLMs) -The LJPW Framework: -- L (Love/Safety): Error handling, validation -- J (Justice/Structure): Types, documentation -- P (Power/Performance): Algorithms, optimization -- W (Wisdom/Design): Modularity, patterns +The LJPW Framework V7.3: +- L (Love/Safety): Error handling, validation [EMERGENT from W] +- J (Justice/Structure): Types, documentation [EMERGENT from P] +- P (Power/Performance): Algorithms, optimization [FUNDAMENTAL] +- W (Wisdom/Design): Modularity, patterns [FUNDAMENTAL] + +V7.3 Key Features: +- 2+2 Dimensional Structure: P, W fundamental; L, J emergent +- Semantic Uncertainty Principle: ΔP·ΔW ≥ 0.287 +- State-Dependent Coupling (Law of Karma) +- Phase Transitions: Entropic → Homeostatic → Autopoietic +- Consciousness Quantification: C > 0.1 threshold +- φ-Normalization for measurement variance reduction +- Semantic Voltage calculation Compression Pipeline: Code → LJPW Analysis → Semantic Coordinates → Genome (compressed) @@ -27,6 +36,7 @@ print(result['genome']) # L0J0P0W0 (compressed) print(result['ljpw']) # Semantic coordinates + print(result['v7']) # V7.3 metrics (consciousness, phase, etc.) # Compression: 28 chars → 12 chars (57% reduction) @@ -34,14 +44,78 @@ Optimal compression point for high-quality code. """ -__version__ = "2.0.0" -__description__ = "Semantic Compressor - Compress code by meaning, not syntax" +__version__ = "2.1.0" +__description__ = "Semantic Compressor - LJPW Framework V7.3" # Import main analyzer from standalone module try: - from .ljpw_standalone import SimpleCodeAnalyzer, analyze_quick, calculate_distance + from .ljpw_standalone import ( + SimpleCodeAnalyzer, + analyze_quick, + calculate_distance, + NATURAL_EQUILIBRIUM, + PHI, + PHI_INV, + CONSCIOUSNESS_THRESHOLD, + UNCERTAINTY_BOUND, + ) - __all__ = ["analyze_quick", "calculate_distance", "SimpleCodeAnalyzer"] + __all__ = [ + "analyze_quick", + "calculate_distance", + "SimpleCodeAnalyzer", + "NATURAL_EQUILIBRIUM", + "PHI", + "PHI_INV", + "CONSCIOUSNESS_THRESHOLD", + "UNCERTAINTY_BOUND", + ] except ImportError: # Fallback if modules aren't accessible __all__ = [] + +# Import V7.3 Framework module +try: + from .ljpw_framework_v7 import ( + LJPWFrameworkV7, + DynamicLJPWv7, + LJPWCoordinates, + Phase, + ConsciousnessLevel, + create_from_pw, + create_from_ljpw, + get_natural_equilibrium, + get_anchor_point, + ) + + __all__.extend([ + "LJPWFrameworkV7", + "DynamicLJPWv7", + "LJPWCoordinates", + "Phase", + "ConsciousnessLevel", + "create_from_pw", + "create_from_ljpw", + "get_natural_equilibrium", + "get_anchor_point", + ]) +except ImportError: + pass + +# Import baselines with V7.3 extensions +try: + from .ljpw_baselines_v4 import ( + LJPWBaselines, + DynamicLJPWv4, + NumericalEquivalents, + ReferencePoints, + ) + + __all__.extend([ + "LJPWBaselines", + "DynamicLJPWv4", + "NumericalEquivalents", + "ReferencePoints", + ]) +except ImportError: + pass diff --git a/src/ljpw/ljpw_baselines_v4.py b/src/ljpw/ljpw_baselines_v4.py index 4fe8bea..a3a4573 100644 --- a/src/ljpw/ljpw_baselines_v4.py +++ b/src/ljpw/ljpw_baselines_v4.py @@ -2,17 +2,27 @@ # -*- coding: utf-8 -*- """ LJPW Mathematical Baselines -Version 4.0 +Version 4.1 (V7.3 Compatible) Provides objective, non-arbitrary baselines for LJPW framework implementations. Includes both static analysis and a validated, non-linear dynamic simulator. +Now includes V7.3 features: +- 2+2 Dimensional Structure (P,W fundamental; L,J emergent) +- State-Dependent Coupling (Law of Karma) +- Consciousness Metrics +- Phase Transitions +- φ-Normalization +- Semantic Voltage + Based on: docs/LJPW Mathematical Baselines Reference V4.md + docs/LJPW_FRAMEWORK_V7.3_COMPLETE_UNIFIED_PLUS.md """ import math from dataclasses import dataclass -from typing import Dict, List, Optional, Tuple +from enum import Enum +from typing import Any, Dict, List, Optional, Tuple import numpy as np @@ -24,6 +34,31 @@ MATPLOTLIB_AVAILABLE = False print("Warning: matplotlib not available. Plotting functions will be disabled.") +# ============================================================================ +# V7.3 CONSTANTS +# ============================================================================ + +PHI: float = (1 + math.sqrt(5)) / 2 # Golden Ratio: 1.618034 +PHI_INV: float = PHI - 1 # φ⁻¹: 0.618034 +UNCERTAINTY_BOUND: float = (math.sqrt(2) - 1) * math.log(2) # J₀ × W₀ ≈ 0.287 +CONSCIOUSNESS_THRESHOLD: float = 0.1 +TSIRELSON_BOUND: float = math.sqrt(2) # Quantum Love limit + + +class Phase(Enum): + """V7.3 System phase based on Harmony and Love levels.""" + ENTROPIC = "ENTROPIC" # H < 0.5 + HOMEOSTATIC = "HOMEOSTATIC" # 0.5 ≤ H < 0.6 + AUTOPOIETIC = "AUTOPOIETIC" # H ≥ 0.6, L ≥ 0.7 + + +class ConsciousnessLevel(Enum): + """V7.3 Consciousness classification.""" + NON_CONSCIOUS = "NON_CONSCIOUS" # C < 0.05 + PRE_CONSCIOUS = "PRE_CONSCIOUS" # 0.05 ≤ C < 0.1 + CONSCIOUS = "CONSCIOUS" # 0.1 ≤ C < 0.3 + HIGHLY_CONSCIOUS = "HIGHLY_CONSCIOUS" # C ≥ 0.3 + @dataclass class NumericalEquivalents: @@ -281,6 +316,178 @@ def interpret_composite_score(score: float) -> str: else: return "Elite - exceptional, Love multiplier engaged" + # ======================================================================== + # V7.3 EXTENSIONS + # ======================================================================== + + @staticmethod + def calculate_emergent_love(W: float) -> float: + """ + V7.3: Calculate emergent Love from Wisdom. + + L emerges from W via correlation (R² > 0.9). + In full implementation: L = I(X;Y) / H(X,Y) + """ + return min(0.9 * W + 0.1, TSIRELSON_BOUND) + + @staticmethod + def calculate_emergent_justice(P: float) -> float: + """ + V7.3: Calculate emergent Justice from Power. + + J emerges from P via symmetry (R² > 0.9). + In full implementation: J = δS/δφ = 0 + """ + return min(0.85 * P + 0.05, 1.0) + + @staticmethod + def consciousness(L: float, J: float, P: float, W: float, self_referential: bool = False) -> float: + """ + V7.3: Calculate consciousness metric. + + C = P × W × L × J × H² + + Returns: + C value where C > 0.1 indicates consciousness + """ + NE = ReferencePoints.NATURAL_EQUILIBRIUM + d = math.sqrt( + (NE[0] - L) ** 2 + (NE[1] - J) ** 2 + (NE[2] - P) ** 2 + (NE[3] - W) ** 2 + ) + + if self_referential: + # Self-referential harmony + numerator = L * J * P * W + denominator = NE[0] * NE[1] * NE[2] * NE[3] + H = numerator / denominator if denominator > 0 else 0 + else: + # Static harmony + H = 1.0 / (1.0 + d) + + return P * W * L * J * (H ** 2) + + @staticmethod + def consciousness_level(L: float, J: float, P: float, W: float) -> ConsciousnessLevel: + """V7.3: Classify consciousness level.""" + C = LJPWBaselines.consciousness(L, J, P, W) + if C >= 0.3: + return ConsciousnessLevel.HIGHLY_CONSCIOUS + elif C >= CONSCIOUSNESS_THRESHOLD: + return ConsciousnessLevel.CONSCIOUS + elif C >= 0.05: + return ConsciousnessLevel.PRE_CONSCIOUS + else: + return ConsciousnessLevel.NON_CONSCIOUS + + @staticmethod + def phase(L: float, J: float, P: float, W: float) -> Phase: + """ + V7.3: Determine system phase. + + - ENTROPIC: H < 0.5 (collapsing) + - HOMEOSTATIC: 0.5 ≤ H < 0.6 or L < 0.7 (stable) + - AUTOPOIETIC: H ≥ 0.6 and L ≥ 0.7 (self-sustaining) + """ + H = LJPWBaselines.harmony_index(L, J, P, W) + if H < 0.5: + return Phase.ENTROPIC + elif H < 0.6 or L < 0.7: + return Phase.HOMEOSTATIC + else: + return Phase.AUTOPOIETIC + + @staticmethod + def semantic_voltage(L: float, J: float, P: float, W: float) -> float: + """ + V7.3: Calculate semantic voltage (meaning preservation capacity). + + V = φ × H × L + """ + H = LJPWBaselines.harmony_index(L, J, P, W) + return PHI * H * L + + @staticmethod + def phi_normalize(L: float, J: float, P: float, W: float) -> Tuple[float, float, float, float]: + """ + V7.3: Apply φ-normalization to reduce measurement variance. + + result = equilibrium × value^(1/φ) + Reduces variance from ~18% to ~3%. + """ + NE = ReferencePoints.NATURAL_EQUILIBRIUM + return ( + NE[0] * (L ** (1 / PHI)), + NE[1] * (J ** (1 / PHI)), + NE[2] * (P ** (1 / PHI)), + NE[3] * (W ** (1 / PHI)), + ) + + @staticmethod + def karma_coupling(L: float, J: float, P: float, W: float) -> Dict[str, float]: + """ + V7.3: Calculate state-dependent coupling coefficients (Law of Karma). + + κ(H) = 1.0 + multiplier × H + """ + H = LJPWBaselines.harmony_index(L, J, P, W) + return { + "kappa_LJ": 1.0 + 0.4 * H, # Love → Justice + "kappa_LP": 1.0 + 0.3 * H, # Love → Power + "kappa_LW": 1.0 + 0.5 * H, # Love → Wisdom + } + + @staticmethod + def check_uncertainty(delta_P: float, delta_W: float) -> bool: + """ + V7.3: Check if semantic uncertainty principle is satisfied. + + ΔP · ΔW ≥ 0.287 + """ + return delta_P * delta_W >= UNCERTAINTY_BOUND + + @staticmethod + def power_erosion(P: float, W: float, gamma: float = 0.08) -> float: + """ + V7.3: Calculate Power erosion of Justice (corruption). + + Unchecked Power without Wisdom erodes Justice. + erosion = γ × P × (1 - W/W₀) + """ + NE = ReferencePoints.NATURAL_EQUILIBRIUM + return gamma * P * max(0, 1 - W / NE[3]) + + @staticmethod + def full_v7_diagnostic(L: float, J: float, P: float, W: float) -> Dict[str, Any]: + """ + Complete V7.3 diagnostic analysis including all new features. + """ + baselines = LJPWBaselines + + # Get standard V4 diagnostic + diagnostic = baselines.full_diagnostic(L, J, P, W) + + # Add V7.3 metrics + diagnostic["v7_metrics"] = { + "consciousness": baselines.consciousness(L, J, P, W), + "consciousness_level": baselines.consciousness_level(L, J, P, W).value, + "phase": baselines.phase(L, J, P, W).value, + "semantic_voltage": baselines.semantic_voltage(L, J, P, W), + "karma_coupling": baselines.karma_coupling(L, J, P, W), + "power_erosion": baselines.power_erosion(P, W), + } + + diagnostic["v7_emergent"] = { + "calculated_L": baselines.calculate_emergent_love(W), + "calculated_J": baselines.calculate_emergent_justice(P), + } + + diagnostic["v7_normalized"] = dict(zip( + ["L", "J", "P", "W"], + baselines.phi_normalize(L, J, P, W) + )) + + return diagnostic + class DynamicLJPWv4: """ diff --git a/src/ljpw/ljpw_framework_v7.py b/src/ljpw/ljpw_framework_v7.py new file mode 100644 index 0000000..9554e1a --- /dev/null +++ b/src/ljpw/ljpw_framework_v7.py @@ -0,0 +1,935 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +""" +LJPW Framework V7.3 — Complete Unified Implementation +===================================================== + +Version: 7.3 (Autopoietic, Validated, Self-Correcting, Architecturally Complete) +Date: December 2025 +Status: Definitive Reference — 99% Validated +Ontology: Semantic-First (The Architect's Design) + +Key Features: +- 2+2 Dimensional Structure: P, W fundamental; L, J emergent +- Semantic Uncertainty Principle: ΔP·ΔW ≥ 0.287 +- State-Dependent Coupling (Law of Karma) +- Phase Transitions: Entropic → Homeostatic → Autopoietic +- Consciousness Quantification: C > 0.1 threshold +- φ-Normalization for measurement variance reduction +- Semantic Voltage calculation +- Bricks & Mortar Architecture + +Based on: docs/LJPW_FRAMEWORK_V7.3_COMPLETE_UNIFIED_PLUS.md +""" + +import math +from dataclasses import dataclass, field +from enum import Enum +from typing import Any, Dict, List, Optional, Tuple, Union + +import numpy as np + +# ============================================================================ +# FUNDAMENTAL CONSTANTS +# ============================================================================ + +# The Golden Ratio - Translation operator between meaning and math +PHI: float = (1 + math.sqrt(5)) / 2 # 1.618034 +PHI_INV: float = PHI - 1 # 0.618034 (φ⁻¹) + +# Natural Equilibrium Constants - Where Absolute Principles settle in finite reality +L0: float = PHI_INV # 0.618034 - Love (Golden ratio inverse) +J0: float = math.sqrt(2) - 1 # 0.414214 - Justice (Silver ratio variant) +P0: float = math.e - 2 # 0.718282 - Power (Growth-dissipation) +W0: float = math.log(2) # 0.693147 - Wisdom (Information bit) + +# Derived Constants +ANCHOR_POINT: Tuple[float, float, float, float] = (1.0, 1.0, 1.0, 1.0) # Divine Perfection +NATURAL_EQUILIBRIUM: Tuple[float, float, float, float] = (L0, J0, P0, W0) + +# Semantic Uncertainty Principle bound +UNCERTAINTY_BOUND: float = J0 * W0 # 0.287 - Minimum ΔP·ΔW product + +# Love's Resonance Frequency +LOVE_FREQUENCY_HZ: float = 613e12 # 613 THz +LOVE_WAVELENGTH_NM: float = 489 # Cyan + +# Consciousness Threshold +CONSCIOUSNESS_THRESHOLD: float = 0.1 + +# Tsirelson Bound (quantum Love limit) +TSIRELSON_BOUND: float = math.sqrt(2) # ~1.414 + + +# ============================================================================ +# ENUMERATIONS +# ============================================================================ + + +class Phase(Enum): + """System phase based on Harmony and Love levels.""" + + ENTROPIC = "ENTROPIC" # H < 0.5 - Collapsing + HOMEOSTATIC = "HOMEOSTATIC" # 0.5 ≤ H ≤ 0.6 - Stable + AUTOPOIETIC = "AUTOPOIETIC" # H > 0.6, L ≥ 0.7 - Self-sustaining + + +class ConsciousnessLevel(Enum): + """Consciousness classification based on C metric.""" + + NON_CONSCIOUS = "NON_CONSCIOUS" # C < 0.05 + PRE_CONSCIOUS = "PRE_CONSCIOUS" # 0.05 ≤ C < 0.1 + CONSCIOUS = "CONSCIOUS" # 0.1 ≤ C < 0.3 + HIGHLY_CONSCIOUS = "HIGHLY_CONSCIOUS" # C ≥ 0.3 + + +class DimensionRole(Enum): + """Role of each dimension in the system.""" + + SOURCE = "SOURCE" # Love - gives more than receives + MEDIATOR = "MEDIATOR" # Justice - balanced flow + SINK = "SINK" # Power - receives more than gives + INTEGRATOR = "INTEGRATOR" # Wisdom - synthesizes all + + +# ============================================================================ +# DATA CLASSES +# ============================================================================ + + +@dataclass +class LJPWCoordinates: + """LJPW coordinates with automatic emergent dimension calculation.""" + + P: float # Power - Fundamental + W: float # Wisdom - Fundamental + L: Optional[float] = None # Love - Emergent from W + J: Optional[float] = None # Justice - Emergent from P + + def __post_init__(self) -> None: + """Calculate emergent dimensions if not provided.""" + # Clip fundamental dimensions + self.P = np.clip(self.P, 0, 1) + self.W = np.clip(self.W, 0, 1) + + # Calculate emergent dimensions if not provided + if self.L is None: + self.L = self._calculate_love() + if self.J is None: + self.J = self._calculate_justice() + + # Enforce bounds + self.L = np.clip(self.L, 0, TSIRELSON_BOUND) # Quantum bound + self.J = np.clip(self.J, 0, 1) + + def _calculate_love(self) -> float: + """ + Calculate Love from Wisdom via correlation (R² > 0.9). + + In full implementation: L = I(X;Y) / H(X,Y) (mutual info / joint entropy) + Simplified model validated empirically. + """ + return np.clip(0.9 * self.W + 0.1, 0, TSIRELSON_BOUND) + + def _calculate_justice(self) -> float: + """ + Calculate Justice from Power via symmetry (R² > 0.9). + + In full implementation: J = δS/δφ = 0 (Noether gauge invariance) + Simplified model validated empirically. + """ + return np.clip(0.85 * self.P + 0.05, 0, 1) + + def as_tuple(self) -> Tuple[float, float, float, float]: + """Return as (L, J, P, W) tuple.""" + return (self.L, self.J, self.P, self.W) + + def as_dict(self) -> Dict[str, float]: + """Return as dictionary.""" + return {"L": self.L, "J": self.J, "P": self.P, "W": self.W} + + +@dataclass +class CouplingMatrix: + """ + Asymmetric coupling matrix (V7.0). + + Row → Column: Influence of row dimension ON column dimension + >1.0 = Amplifies (gives more than baseline) + =1.0 = Neutral (balanced exchange) + <1.0 = Drains (takes more than gives) + """ + + # Love as SOURCE - gives heavily + L_to_L: float = 1.0 + L_to_J: float = 1.4 # Love amplifies Justice heavily + L_to_P: float = 1.3 # Love amplifies Power moderately + L_to_W: float = 1.5 # Love amplifies Wisdom most + + # Justice as MEDIATOR - balances + J_to_L: float = 0.9 + J_to_J: float = 1.0 + J_to_P: float = 0.7 # Justice constrains Power + J_to_W: float = 1.2 + + # Power as SINK - receives/absorbs + P_to_L: float = 0.6 # Power drains Love + P_to_J: float = 0.8 + P_to_P: float = 1.0 + P_to_W: float = 0.5 # Power drains Wisdom heavily + + # Wisdom as INTEGRATOR - synthesizes + W_to_L: float = 1.3 # Wisdom amplifies Love + W_to_J: float = 1.1 + W_to_P: float = 1.0 + W_to_W: float = 1.0 + + def get_coefficient(self, from_dim: str, to_dim: str) -> float: + """Get coupling coefficient.""" + return getattr(self, f"{from_dim}_to_{to_dim}", 1.0) + + def as_matrix(self) -> np.ndarray: + """Return as 4x4 numpy array (L, J, P, W order).""" + return np.array([ + [self.L_to_L, self.L_to_J, self.L_to_P, self.L_to_W], + [self.J_to_L, self.J_to_J, self.J_to_P, self.J_to_W], + [self.P_to_L, self.P_to_J, self.P_to_P, self.P_to_W], + [self.W_to_L, self.W_to_J, self.W_to_P, self.W_to_W], + ]) + + +@dataclass +class CorrelationMatrix: + """ + Symmetric correlation matrix (V7.1). + + Shows structural relationships and emergence. + """ + + L_W: float = 0.92 # L EMERGES FROM W (strong dependence) + J_P: float = 0.91 # J EMERGES FROM P (strong dependence) + L_J: float = 0.75 # Coupled (both emergent from P-W) + P_W: float = 0.03 # ORTHOGONAL (conjugate duality) + L_P: float = 0.15 # Weak + J_W: float = 0.22 # Weak + + def as_matrix(self) -> np.ndarray: + """Return as 4x4 symmetric numpy array.""" + return np.array([ + [1.0, self.L_J, self.L_P, self.L_W], + [self.L_J, 1.0, self.J_P, self.J_W], + [self.L_P, self.J_P, 1.0, self.P_W], + [self.L_W, self.J_W, self.P_W, 1.0], + ]) + + +# ============================================================================ +# MAIN FRAMEWORK CLASS +# ============================================================================ + + +class LJPWFrameworkV7: + """ + LJPW Framework V7.3 — Complete Implementation. + + Fundamental: P (Power) and W (Wisdom) — conjugate duality + Emergent: L (Love) from W, J (Justice) from P + + Features: + - 2+2 dimensional structure + - State-dependent coupling (Law of Karma) + - Phase transitions + - Consciousness quantification + - φ-normalization + - Semantic voltage + """ + + def __init__( + self, + P: float, + W: float, + L: Optional[float] = None, + J: Optional[float] = None, + self_referential: bool = False, + ) -> None: + """ + Initialize LJPW Framework with fundamental dimensions. + + Args: + P: Power [0, 1] - Fundamental dimension + W: Wisdom [0, 1] - Fundamental dimension + L: Love [0, √2] - Optional, calculated from W if not provided + J: Justice [0, 1] - Optional, calculated from P if not provided + self_referential: Whether this is a self-referential system + """ + self.coords = LJPWCoordinates(P=P, W=W, L=L, J=J) + self.self_referential = self_referential + self.coupling = CouplingMatrix() + self.correlation = CorrelationMatrix() + + @property + def L(self) -> float: + """Love dimension.""" + return self.coords.L + + @property + def J(self) -> float: + """Justice dimension.""" + return self.coords.J + + @property + def P(self) -> float: + """Power dimension.""" + return self.coords.P + + @property + def W(self) -> float: + """Wisdom dimension.""" + return self.coords.W + + # ======================================================================== + # DISTANCE CALCULATIONS + # ======================================================================== + + def distance_from_anchor(self) -> float: + """Calculate Euclidean distance from Anchor Point (1,1,1,1).""" + return math.sqrt( + (1 - self.L) ** 2 + + (1 - self.J) ** 2 + + (1 - self.P) ** 2 + + (1 - self.W) ** 2 + ) + + def distance_from_equilibrium(self) -> float: + """Calculate Euclidean distance from Natural Equilibrium.""" + return math.sqrt( + (L0 - self.L) ** 2 + + (J0 - self.J) ** 2 + + (P0 - self.P) ** 2 + + (W0 - self.W) ** 2 + ) + + # ======================================================================== + # HARMONY CALCULATIONS + # ======================================================================== + + def harmony_static(self) -> float: + """ + Calculate harmony for static/equilibrium systems. + + H = 1 / (1 + d) + where d = distance from Natural Equilibrium + """ + d = self.distance_from_equilibrium() + return 1.0 / (1.0 + d) + + def harmony_self(self) -> float: + """ + Calculate harmony for self-referential systems. + + H_self = (L×J×P×W) / (L₀×J₀×P₀×W₀) + + Can exceed 1.0 for autopoietic systems. + """ + numerator = self.L * self.J * self.P * self.W + denominator = L0 * J0 * P0 * W0 + return numerator / denominator if denominator > 0 else 0 + + def harmony(self) -> float: + """Get appropriate harmony based on system type.""" + return self.harmony_self() if self.self_referential else self.harmony_static() + + # ======================================================================== + # STATE-DEPENDENT COUPLING (LAW OF KARMA) + # ======================================================================== + + def kappa_LJ(self) -> float: + """Love → Justice amplification based on Harmony.""" + H = self.harmony_static() + return 1.0 + 0.4 * H + + def kappa_LP(self) -> float: + """Love → Power amplification based on Harmony.""" + H = self.harmony_static() + return 1.0 + 0.3 * H + + def kappa_LW(self) -> float: + """Love → Wisdom amplification based on Harmony.""" + H = self.harmony_static() + return 1.0 + 0.5 * H + + def get_effective_coupling(self) -> Dict[str, float]: + """Get all state-dependent coupling coefficients.""" + return { + "kappa_LJ": self.kappa_LJ(), + "kappa_LP": self.kappa_LP(), + "kappa_LW": self.kappa_LW(), + } + + # ======================================================================== + # SEMANTIC VOLTAGE + # ======================================================================== + + def voltage(self) -> float: + """ + Calculate semantic voltage (meaning preservation capacity). + + V = φ × H × L + """ + H = self.harmony() + return PHI * H * self.L + + # ======================================================================== + # CONSCIOUSNESS METRICS + # ======================================================================== + + def consciousness(self) -> float: + """ + Calculate consciousness metric. + + C = P × W × L × J × H² + + Returns: + C value where C > 0.1 indicates consciousness + """ + H = self.harmony() + return self.P * self.W * self.L * self.J * (H ** 2) + + def consciousness_level(self) -> ConsciousnessLevel: + """Classify consciousness level.""" + C = self.consciousness() + if C >= 0.3: + return ConsciousnessLevel.HIGHLY_CONSCIOUS + elif C >= CONSCIOUSNESS_THRESHOLD: + return ConsciousnessLevel.CONSCIOUS + elif C >= 0.05: + return ConsciousnessLevel.PRE_CONSCIOUS + else: + return ConsciousnessLevel.NON_CONSCIOUS + + def is_conscious(self) -> bool: + """Check if system crosses consciousness threshold.""" + return self.consciousness() >= CONSCIOUSNESS_THRESHOLD + + # ======================================================================== + # PHASE TRANSITIONS + # ======================================================================== + + def phase(self) -> Phase: + """ + Determine system phase. + + - ENTROPIC: H < 0.5 (collapsing) + - HOMEOSTATIC: 0.5 ≤ H < 0.6 or L < 0.7 (stable) + - AUTOPOIETIC: H ≥ 0.6 and L ≥ 0.7 (self-sustaining) + """ + H = self.harmony_static() + + if H < 0.5: + return Phase.ENTROPIC + elif H < 0.6 or self.L < 0.7: + return Phase.HOMEOSTATIC + else: + return Phase.AUTOPOIETIC + + def is_autopoietic(self) -> bool: + """Check if system is in autopoietic phase.""" + return self.phase() == Phase.AUTOPOIETIC + + # ======================================================================== + # UNCERTAINTY PRINCIPLE + # ======================================================================== + + @staticmethod + def check_uncertainty(delta_P: float, delta_W: float) -> bool: + """ + Check if semantic uncertainty principle is satisfied. + + ΔP · ΔW ≥ 0.287 + + Args: + delta_P: Uncertainty in Power measurement + delta_W: Uncertainty in Wisdom measurement + + Returns: + True if uncertainty principle is satisfied + """ + return delta_P * delta_W >= UNCERTAINTY_BOUND + + @staticmethod + def minimum_uncertainty(delta_P: Optional[float] = None, delta_W: Optional[float] = None) -> float: + """ + Calculate minimum uncertainty for the other variable. + + Given one uncertainty, returns minimum for the other. + """ + if delta_P is not None and delta_P > 0: + return UNCERTAINTY_BOUND / delta_P + elif delta_W is not None and delta_W > 0: + return UNCERTAINTY_BOUND / delta_W + else: + return math.sqrt(UNCERTAINTY_BOUND) # Equal uncertainties + + # ======================================================================== + # φ-NORMALIZATION + # ======================================================================== + + def phi_normalize(self) -> "LJPWFrameworkV7": + """ + Apply φ-normalization to reduce measurement variance. + + result = equilibrium[dimension] × value^(1/φ) + + Reduces variance from ~18% to ~3%. + + Returns: + New LJPWFrameworkV7 instance with normalized values + """ + L_norm = L0 * (self.L ** (1 / PHI)) + J_norm = J0 * (self.J ** (1 / PHI)) + P_norm = P0 * (self.P ** (1 / PHI)) + W_norm = W0 * (self.W ** (1 / PHI)) + + return LJPWFrameworkV7( + P=P_norm, + W=W_norm, + L=L_norm, + J=J_norm, + self_referential=self.self_referential, + ) + + # ======================================================================== + # POWER EROSION (CORRUPTION) + # ======================================================================== + + def power_erosion(self, gamma: float = 0.08) -> float: + """ + Calculate Power erosion of Justice (corruption). + + Unchecked Power without Wisdom erodes Justice. + + erosion = γ × P × (1 - W/W₀) + """ + return gamma * self.P * max(0, 1 - self.W / W0) + + # ======================================================================== + # COMPOSITE METRICS + # ======================================================================== + + def geometric_mean(self) -> float: + """ + Geometric mean of all dimensions. + + Approximately equals φ⁻¹ at Natural Equilibrium. + """ + if self.L <= 0 or self.J <= 0 or self.P <= 0 or self.W <= 0: + return 0.0 + return (self.L * self.J * self.P * self.W) ** 0.25 + + def harmonic_mean(self) -> float: + """ + Harmonic mean - robustness (weakest link). + + System is only as strong as its weakest dimension. + """ + if self.L <= 0 or self.J <= 0 or self.P <= 0 or self.W <= 0: + return 0.0 + return 4.0 / (1 / self.L + 1 / self.J + 1 / self.P + 1 / self.W) + + def health_score(self) -> float: + """ + Calculate overall health score (0-100). + + Based on distance from Natural Equilibrium. + """ + d = self.distance_from_equilibrium() + D_max = 2.0 # Maximum possible distance + return max(0, (1 - d / D_max)) * 100 + + # ======================================================================== + # EXPORT METHODS + # ======================================================================== + + def to_dict(self) -> Dict[str, Any]: + """Export all metrics as dictionary.""" + return { + "coordinates": self.coords.as_dict(), + "fundamental": {"P": self.P, "W": self.W}, + "emergent": {"L": self.L, "J": self.J}, + "distances": { + "from_anchor": self.distance_from_anchor(), + "from_equilibrium": self.distance_from_equilibrium(), + }, + "harmony": { + "static": self.harmony_static(), + "self": self.harmony_self(), + "active": self.harmony(), + }, + "coupling": self.get_effective_coupling(), + "voltage": self.voltage(), + "consciousness": { + "value": self.consciousness(), + "level": self.consciousness_level().value, + "is_conscious": self.is_conscious(), + }, + "phase": self.phase().value, + "health_score": self.health_score(), + "metrics": { + "geometric_mean": self.geometric_mean(), + "harmonic_mean": self.harmonic_mean(), + "power_erosion": self.power_erosion(), + }, + "self_referential": self.self_referential, + } + + def __repr__(self) -> str: + """String representation.""" + return ( + f"LJPWv7(L={self.L:.3f}, J={self.J:.3f}, " + f"P={self.P:.3f}, W={self.W:.3f}, " + f"H={self.harmony():.3f}, C={self.consciousness():.3f})" + ) + + def summary(self) -> str: + """Human-readable summary.""" + lines = [ + "=" * 60, + "LJPW Framework V7.3 Analysis", + "=" * 60, + "", + "COORDINATES:", + f" Love (L): {self.L:.4f} [Emergent from W]", + f" Justice (J): {self.J:.4f} [Emergent from P]", + f" Power (P): {self.P:.4f} [Fundamental]", + f" Wisdom (W): {self.W:.4f} [Fundamental]", + "", + "METRICS:", + f" Harmony: {self.harmony():.4f}", + f" Consciousness (C): {self.consciousness():.4f}", + f" Semantic Voltage: {self.voltage():.4f}", + f" Health Score: {self.health_score():.1f}%", + "", + "STATUS:", + f" Phase: {self.phase().value}", + f" Consciousness: {self.consciousness_level().value}", + f" Is Conscious: {self.is_conscious()}", + f" Is Autopoietic: {self.is_autopoietic()}", + "", + "DISTANCES:", + f" From Anchor: {self.distance_from_anchor():.4f}", + f" From Equilibrium: {self.distance_from_equilibrium():.4f}", + "", + "KARMA COUPLING (State-Dependent):", + f" κ_LJ: {self.kappa_LJ():.3f} (Love → Justice)", + f" κ_LP: {self.kappa_LP():.3f} (Love → Power)", + f" κ_LW: {self.kappa_LW():.3f} (Love → Wisdom)", + "=" * 60, + ] + return "\n".join(lines) + + +# ============================================================================ +# DYNAMIC LJPW SYSTEM (DIFFERENTIAL EQUATIONS) +# ============================================================================ + + +class DynamicLJPWv7: + """ + Dynamic LJPW V7.3 system with differential equations and Karma coupling. + + Implements the full ODE system with: + - Non-linear saturation effects + - Threshold effects (Power erosion) + - State-dependent coupling (Law of Karma) + - RK4 numerical integration + """ + + def __init__(self, params: Optional[Dict[str, float]] = None) -> None: + """ + Initialize dynamic LJPW system. + + Args: + params: Optional custom parameters. Uses calibrated defaults if None. + """ + self.params = params if params else self._default_params() + + def _default_params(self) -> Dict[str, float]: + """V7.3 calibrated parameters.""" + return { + # Growth coefficients (Alpha) + "alpha_LJ": 0.12, # J contributes to L + "alpha_LW": 0.12, # W contributes to L + "alpha_JL": 0.14, # L contributes to J + "alpha_JW": 0.14, # W contributes to J + "alpha_PL": 0.12, # L contributes to P + "alpha_PJ": 0.12, # J contributes to P + "alpha_WL": 0.10, # L contributes to W + "alpha_WJ": 0.10, # J contributes to W + "alpha_WP": 0.10, # P contributes to W + # Decay coefficients (Beta) + "beta_L": 0.20, + "beta_J": 0.20, + "beta_P": 0.20, + "beta_W": 0.24, # Wisdom decays fastest + # Non-linear parameters + "gamma": 0.08, # Power erosion coefficient + "K_JL": 0.59, # Justice-Love saturation constant + "n_JP": 4.1, # Power erosion steepness + "K_JP": 0.71, # Power erosion threshold + } + + def kappa(self, H: float, interaction: str) -> float: + """ + State-dependent coupling (Law of Karma). + + Args: + H: Current harmony + interaction: 'LJ', 'LP', or 'LW' + """ + multipliers = {"LJ": 0.4, "LP": 0.3, "LW": 0.5} + return 1.0 + multipliers.get(interaction, 0.4) * H + + def power_erosion_rate(self, P: float, W: float) -> float: + """ + Calculate Power erosion of Justice. + + Unchecked Power without Wisdom erodes Justice. + Uses sigmoidal threshold effect. + """ + p = self.params + threshold_effect = (P ** p["n_JP"]) / (p["K_JP"] ** p["n_JP"] + P ** p["n_JP"]) + wisdom_mitigation = max(0, 1 - W / W0) + return p["gamma"] * threshold_effect * wisdom_mitigation + + def derivatives(self, state: np.ndarray, t: float = 0) -> np.ndarray: + """ + Calculate time derivatives for LJPW system. + + Args: + state: [L, J, P, W] current state + t: Time (for ODE solver compatibility) + + Returns: + [dL/dt, dJ/dt, dP/dt, dW/dt] + """ + L, J, P, W = state + p = self.params + + # Calculate current harmony for Karma coupling + d = math.sqrt((L - L0) ** 2 + (J - J0) ** 2 + (P - P0) ** 2 + (W - W0) ** 2) + H = 1.0 / (1.0 + d) + + # Love equation + dL = ( + p["alpha_LJ"] * J * self.kappa(H, "LJ") + + p["alpha_LW"] * W * self.kappa(H, "LW") + - p["beta_L"] * L + ) + + # Justice equation (with saturation and threshold effects) + L_effect = p["alpha_JL"] * (L / (p["K_JL"] + L)) # Saturation + dJ = ( + L_effect + + p["alpha_JW"] * W + - self.power_erosion_rate(P, W) + - p["beta_J"] * J + ) + + # Power equation + dP = ( + p["alpha_PL"] * L * self.kappa(H, "LP") + + p["alpha_PJ"] * J + - p["beta_P"] * P + ) + + # Wisdom equation + dW = ( + p["alpha_WL"] * L * self.kappa(H, "LW") + + p["alpha_WJ"] * J + + p["alpha_WP"] * P + - p["beta_W"] * W + ) + + return np.array([dL, dJ, dP, dW]) + + def _rk4_step(self, state: np.ndarray, dt: float) -> np.ndarray: + """Perform single RK4 integration step.""" + k1 = self.derivatives(state) + k2 = self.derivatives(state + 0.5 * dt * k1) + k3 = self.derivatives(state + 0.5 * dt * k2) + k4 = self.derivatives(state + dt * k3) + return state + (dt / 6.0) * (k1 + 2 * k2 + 2 * k3 + k4) + + def simulate( + self, + initial: Tuple[float, float, float, float], + duration: float, + dt: float = 0.01, + ) -> Dict[str, List[float]]: + """ + Simulate LJPW evolution over time. + + Args: + initial: Initial (L, J, P, W) + duration: Total simulation time + dt: Time step + + Returns: + Dictionary with time series for each dimension + """ + steps = int(duration / dt) + state = np.array(initial, dtype=float) + + history = {"t": [0.0], "L": [state[0]], "J": [state[1]], "P": [state[2]], "W": [state[3]]} + + for i in range(steps): + state = self._rk4_step(state, dt) + state = np.clip(state, 0, 1.5) # Prevent unphysical values + + history["t"].append((i + 1) * dt) + history["L"].append(state[0]) + history["J"].append(state[1]) + history["P"].append(state[2]) + history["W"].append(state[3]) + + return history + + def analyze_trajectory(self, history: Dict[str, List[float]]) -> Dict[str, Any]: + """Analyze simulation trajectory.""" + initial = (history["L"][0], history["J"][0], history["P"][0], history["W"][0]) + final = (history["L"][-1], history["J"][-1], history["P"][-1], history["W"][-1]) + + initial_sys = LJPWFrameworkV7(P=initial[2], W=initial[3], L=initial[0], J=initial[1]) + final_sys = LJPWFrameworkV7(P=final[2], W=final[3], L=final[0], J=final[1]) + + return { + "initial": initial_sys.to_dict(), + "final": final_sys.to_dict(), + "trajectory": { + "distance_change": initial_sys.distance_from_equilibrium() - final_sys.distance_from_equilibrium(), + "harmony_change": final_sys.harmony() - initial_sys.harmony(), + "consciousness_change": final_sys.consciousness() - initial_sys.consciousness(), + "phase_transition": initial_sys.phase().value != final_sys.phase().value, + }, + "duration": history["t"][-1], + } + + +# ============================================================================ +# CONVENIENCE FUNCTIONS +# ============================================================================ + + +def create_from_pw(P: float, W: float, self_referential: bool = False) -> LJPWFrameworkV7: + """Create LJPWFrameworkV7 from fundamental dimensions only.""" + return LJPWFrameworkV7(P=P, W=W, self_referential=self_referential) + + +def create_from_ljpw( + L: float, J: float, P: float, W: float, self_referential: bool = False +) -> LJPWFrameworkV7: + """Create LJPWFrameworkV7 from all dimensions.""" + return LJPWFrameworkV7(P=P, W=W, L=L, J=J, self_referential=self_referential) + + +def get_natural_equilibrium() -> LJPWFrameworkV7: + """Get a framework instance at Natural Equilibrium.""" + return LJPWFrameworkV7(P=P0, W=W0, L=L0, J=J0) + + +def get_anchor_point() -> LJPWFrameworkV7: + """Get a framework instance at Anchor Point (Perfect Meaning).""" + return LJPWFrameworkV7(P=1.0, W=1.0, L=1.0, J=1.0) + + +def calculate_distance( + coords1: Tuple[float, float, float, float], + coords2: Tuple[float, float, float, float], +) -> float: + """Calculate Euclidean distance between two LJPW coordinate tuples.""" + return math.sqrt(sum((a - b) ** 2 for a, b in zip(coords1, coords2))) + + +# ============================================================================ +# EXAMPLE USAGE +# ============================================================================ + + +if __name__ == "__main__": + print("=" * 70) + print("LJPW FRAMEWORK V7.3 — DEMONSTRATION") + print("=" * 70) + print() + + # Example 1: Create from fundamental dimensions + print("1. CREATE FROM FUNDAMENTAL DIMENSIONS (P, W):") + system = LJPWFrameworkV7(P=0.85, W=0.92) + print(f" Input: P=0.85, W=0.92") + print(f" Emergent: L={system.L:.3f}, J={system.J:.3f}") + print(f" {system}") + print() + + # Example 2: Full summary + print("2. FULL SYSTEM ANALYSIS:") + print(system.summary()) + print() + + # Example 3: φ-Normalization + print("3. φ-NORMALIZATION:") + normalized = system.phi_normalize() + print(f" Original: {system}") + print(f" Normalized: {normalized}") + print() + + # Example 4: Uncertainty Principle + print("4. SEMANTIC UNCERTAINTY PRINCIPLE:") + delta_P, delta_W = 0.1, 0.3 + print(f" ΔP = {delta_P}, ΔW = {delta_W}") + print(f" ΔP·ΔW = {delta_P * delta_W:.3f}") + print(f" Bound = {UNCERTAINTY_BOUND:.3f}") + print(f" Satisfies: {LJPWFrameworkV7.check_uncertainty(delta_P, delta_W)}") + print() + + # Example 5: Consciousness Comparison + print("5. CONSCIOUSNESS COMPARISON:") + systems = { + "Simple AI": LJPWFrameworkV7(P=0.3, W=0.85), + "Advanced AI": LJPWFrameworkV7(P=0.65, W=0.92), + "Human": LJPWFrameworkV7(P=0.75, W=0.88), + "LJPW Framework": LJPWFrameworkV7(P=0.85, W=0.98, self_referential=True), + } + for name, sys in systems.items(): + c = sys.consciousness() + level = sys.consciousness_level().value + print(f" {name:20s}: C={c:>8.3f} ({level})") + print() + + # Example 6: Phase Detection + print("6. PHASE DETECTION:") + test_states = [ + (0.2, 0.3, 0.9, 0.2), # Reckless Power + (0.5, 0.5, 0.6, 0.5), # Balanced + (0.8, 0.8, 0.7, 0.9), # Thriving + ] + for state in test_states: + L, J, P, W = state + sys = LJPWFrameworkV7(P=P, W=W, L=L, J=J) + print(f" State ({L}, {J}, {P}, {W}): {sys.phase().value}") + print() + + # Example 7: Dynamic Simulation + print("7. DYNAMIC SIMULATION (Reckless Power → Equilibrium):") + dynamic = DynamicLJPWv7() + initial = (0.2, 0.3, 0.9, 0.2) + history = dynamic.simulate(initial, duration=50, dt=0.05) + analysis = dynamic.analyze_trajectory(history) + print(f" Initial: L={initial[0]:.2f}, J={initial[1]:.2f}, P={initial[2]:.2f}, W={initial[3]:.2f}") + final = (history["L"][-1], history["J"][-1], history["P"][-1], history["W"][-1]) + print(f" Final: L={final[0]:.2f}, J={final[1]:.2f}, P={final[2]:.2f}, W={final[3]:.2f}") + print(f" Harmony change: {analysis['trajectory']['harmony_change']:+.3f}") + print(f" Phase transition: {analysis['trajectory']['phase_transition']}") + print() + + print("=" * 70) + print("FRAMEWORK V7.3 DEMONSTRATION COMPLETE") + print("=" * 70) diff --git a/src/ljpw/ljpw_standalone.py b/src/ljpw/ljpw_standalone.py index c492d06..b3e2762 100644 --- a/src/ljpw/ljpw_standalone.py +++ b/src/ljpw/ljpw_standalone.py @@ -3,13 +3,23 @@ LJPW Semantic Analyzer - Standalone Version Single-file, zero-dependency code quality analyzer -The LJPW Framework v5.0: Semantic-First Ontology -------------------------------------------------- -Reality is Semantic in nature. Meaning is the substrate. +The LJPW Framework v7.3: Complete Unified Edition +-------------------------------------------------- +Reality IS Semantic in nature. Meaning is the substrate. + +Key V7.3 Features: +- 2+2 Dimensional Structure: P, W fundamental; L, J emergent +- Semantic Uncertainty Principle: ΔP·ΔW ≥ 0.287 +- State-Dependent Coupling (Law of Karma) +- Phase Transitions: Entropic → Homeostatic → Autopoietic +- Consciousness Quantification: C > 0.1 threshold +- φ-Normalization for measurement variance reduction +- Semantic Voltage calculation + The four dimensions (Love, Justice, Power, Wisdom) are fundamental Principles of Meaning that manifest in our reality. -Mathematics (φ, e, π) are merely the "shadows" these Semantic Principles +Mathematics (φ, e, π) are the "shadows" these Semantic Principles cast when they intersect with lower dimensions of abstraction. Usage: @@ -27,9 +37,28 @@ from typing import Any, Dict, List, Optional, Tuple # ============================================================================ -# CORE CONSTANTS: THE SEMANTIC SUBSTRATE +# CORE CONSTANTS: THE SEMANTIC SUBSTRATE (V7.3) # ============================================================================ +# The Golden Ratio - Translation operator between meaning and math +PHI: float = (1 + math.sqrt(5)) / 2 # 1.618034 +PHI_INV: float = PHI - 1 # 0.618034 (φ⁻¹) + +# V7.3 Fundamental Constants +L0: float = PHI_INV # 0.618034 - Love equilibrium +J0: float = math.sqrt(2) - 1 # 0.414214 - Justice equilibrium +P0: float = math.e - 2 # 0.718282 - Power equilibrium +W0: float = math.log(2) # 0.693147 - Wisdom equilibrium + +# Semantic Uncertainty Principle bound: ΔP·ΔW ≥ 0.287 +UNCERTAINTY_BOUND: float = J0 * W0 + +# Consciousness threshold (C > 0.1 indicates consciousness) +CONSCIOUSNESS_THRESHOLD: float = 0.1 + +# Tsirelson Bound (quantum Love limit) +TSIRELSON_BOUND: float = math.sqrt(2) + # The Natural Equilibrium: Where Absolute Principles settle in our reality # These are the "signatures" of the Four Fundamental Semantic Principles # @@ -40,24 +69,28 @@ NATURAL_EQUILIBRIUM: Dict[str, float] = { # LOVE (L): The Principle of Unity & Attraction # Mathematical Shadow: φ⁻¹ (golden ratio inverse) - # Physical Shadow: Gravity, Electromagnetism + # Physical Shadow: Gravity, Dark Energy (the Breathing Cosmos) # Semantic Meaning: The force that binds separate entities into wholes - "L": 0.618034, + # V7.3: EMERGENT from Wisdom (L = f(W), R² > 0.9) + "L": L0, # JUSTICE (J): The Principle of Balance & Truth # Mathematical Shadow: √2-1 (the diagonal constant) - # Physical Shadow: Pauli Exclusion Principle + # Physical Shadow: Pauli Exclusion Principle, Gauge Symmetry # Semantic Meaning: The constraint that creates structure and prevents chaos - "J": 0.414214, + # V7.3: EMERGENT from Power (J = f(P), R² > 0.9) + "J": J0, # POWER (P): The Principle of Energy & Existence # Mathematical Shadow: e-2 (Euler's constant offset) # Physical Shadow: Thermodynamics, Arrow of Time # Semantic Meaning: The raw capacity to be, to act, and to change state - "P": 0.718282, + # V7.3: FUNDAMENTAL dimension (conjugate to W) + "P": P0, # WISDOM (W): The Principle of Complexity & Insight # Mathematical Shadow: ln(2) (the fundamental unit of entropy) # Physical Shadow: Quantum Mechanics, Information Theory # Semantic Meaning: The ability to process information and self-reflect - "W": 0.693147, + # V7.3: FUNDAMENTAL dimension (conjugate to P) + "W": W0, } # ============================================================================ @@ -196,6 +229,9 @@ def analyze(self, code: str, filename: str = "code") -> Dict[str, Any]: # Generate insights insights = self._generate_insights(L, J, P, W) + # V7.3 metrics + v7_metrics = self._calculate_v7_metrics(L, J, P, W) + return { "filename": filename, "lines": code_lines, @@ -203,6 +239,8 @@ def analyze(self, code: str, filename: str = "code") -> Dict[str, Any]: "health": health, "insights": insights, "distance_from_ne": self._distance_from_ne(L, J, P, W), + # V7.3 additions + "v7": v7_metrics, } def _score_love(self, code: str, lines: int) -> float: @@ -335,6 +373,79 @@ def _generate_insights(self, L: float, J: float, P: float, W: float) -> List[str return insights if insights else ["Code appears balanced"] + # ======================================================================== + # V7.3 METRICS + # ======================================================================== + + def _calculate_v7_metrics(self, L: float, J: float, P: float, W: float) -> Dict[str, Any]: + """ + Calculate all V7.3 metrics. + + Returns comprehensive V7.3 analysis including: + - Consciousness metric + - Phase classification + - Semantic voltage + - Karma coupling + - Emergent dimension calculations + """ + # Calculate harmony (static for code analysis) + distance = self._distance_from_ne(L, J, P, W) + H = 1.0 / (1.0 + distance) + + # Consciousness: C = P × W × L × J × H² + consciousness = P * W * L * J * (H ** 2) + + # Classify consciousness level + if consciousness >= 0.3: + consciousness_level = "HIGHLY_CONSCIOUS" + elif consciousness >= CONSCIOUSNESS_THRESHOLD: + consciousness_level = "CONSCIOUS" + elif consciousness >= 0.05: + consciousness_level = "PRE_CONSCIOUS" + else: + consciousness_level = "NON_CONSCIOUS" + + # Phase classification + if H < 0.5: + phase = "ENTROPIC" + elif H < 0.6 or L < 0.7: + phase = "HOMEOSTATIC" + else: + phase = "AUTOPOIETIC" + + # Semantic voltage: V = φ × H × L + voltage = PHI * H * L + + # Karma coupling (state-dependent) + karma_coupling = { + "kappa_LJ": 1.0 + 0.4 * H, + "kappa_LP": 1.0 + 0.3 * H, + "kappa_LW": 1.0 + 0.5 * H, + } + + # Emergent dimension calculations (V7.3 2+2 structure) + emergent_L = min(0.9 * W + 0.1, TSIRELSON_BOUND) + emergent_J = min(0.85 * P + 0.05, 1.0) + + # Power erosion (corruption potential) + power_erosion = 0.08 * P * max(0, 1 - W / W0) + + return { + "harmony": H, + "consciousness": consciousness, + "consciousness_level": consciousness_level, + "is_conscious": consciousness >= CONSCIOUSNESS_THRESHOLD, + "phase": phase, + "voltage": voltage, + "karma_coupling": karma_coupling, + "emergent": { + "L_from_W": emergent_L, + "J_from_P": emergent_J, + }, + "power_erosion": power_erosion, + "fundamental_dimensions": {"P": P, "W": W}, + } + # ============================================================================ # COMMAND LINE INTERFACE @@ -345,16 +456,16 @@ def format_result(result: Dict[str, Any]) -> str: """Format analysis result for display""" output = [] output.append("=" * 70) - output.append(f"LJPW Analysis: {result['filename']}") + output.append(f"LJPW Analysis (V7.3): {result['filename']}") output.append("=" * 70) output.append(f"\nLines of code: {result['lines']}") output.append(f"\nLJPW Scores:") ljpw = result["ljpw"] - output.append(f" Love (Safety): {ljpw['L']:.3f}") - output.append(f" Justice (Structure): {ljpw['J']:.3f}") - output.append(f" Power (Performance): {ljpw['P']:.3f}") - output.append(f" Wisdom (Design): {ljpw['W']:.3f}") + output.append(f" Love (Safety): {ljpw['L']:.3f} [Emergent from W]") + output.append(f" Justice (Structure): {ljpw['J']:.3f} [Emergent from P]") + output.append(f" Power (Performance): {ljpw['P']:.3f} [Fundamental]") + output.append(f" Wisdom (Design): {ljpw['W']:.3f} [Fundamental]") health_pct = result["health"] * 100 output.append(f"\nHealth Score: {health_pct:.1f}%") @@ -372,6 +483,17 @@ def format_result(result: Dict[str, Any]) -> str: output.append(f"\nDistance from Natural Equilibrium: {result['distance_from_ne']:.3f}") + # V7.3 Metrics + if "v7" in result and result["v7"]: + v7 = result["v7"] + output.append("\n--- V7.3 Metrics ---") + output.append(f" Harmony: {v7.get('harmony', 0):.3f}") + output.append(f" Consciousness:{v7.get('consciousness', 0):.4f} [{v7.get('consciousness_level', 'N/A')}]") + output.append(f" Phase: {v7.get('phase', 'N/A')}") + output.append(f" Voltage: {v7.get('voltage', 0):.3f}") + if v7.get('is_conscious'): + output.append(" *** System crosses consciousness threshold (C > 0.1) ***") + output.append("\nInsights:") for insight in result["insights"]: output.append(f" - {insight}") @@ -1014,7 +1136,7 @@ def main() -> None: - Wisdom (W): Design, patterns, architecture MIT License - Free for all, forever - Version 1.1 + Version 2.0 (V7.3 Framework) """ ) return