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The Three Faces of the Trignum Pyramid.
Face α (Alpha) — Logic Pole (Blue, Positive Charge)
Face β (Beta) — Illogic Pole (Red, Negative Charge / Vacuum)
Face γ (Gamma) — Context / Human Pulse Pole (Gold, Resonant Frequency)
"""
import math
import random
from dataclasses import dataclass
from typing import Any, Dict, Optional
class FaceAlpha:
"""
Face α — The Logic Pole (Blue).
Attracts coherent patterns, statistical certainties, established knowledge.
Magnetic charge: Positive.
"""
COLOR = "blue"
SYMBOL = "α"
NAME = "Logic"
def __init__(self, strength: float = 1.0):
self.strength = max(0.0, min(2.0, strength))
self._accumulated: float = 0.0
self._cycles: int = 0
def attract(self, ferro_data: Dict[str, Any]) -> float:
"""
Calculate attraction strength for the given Ferro-Data.
Logic attraction is proportional to:
- Low entropy (structured, predictable data)
- Token consistency
- Pattern regularity
"""
entropy = ferro_data.get("entropy", 0.5)
length = ferro_data.get("length", 1)
# Low entropy = high logic attraction
attraction = self.strength * (1.0 - min(entropy / 8.0, 1.0))
# Longer, structured data attracts more to Logic
length_factor = min(math.log2(length + 1) / 10.0, 1.0)
attraction *= (0.5 + 0.5 * length_factor)
self._accumulated += attraction
self._cycles += 1
return attraction
def reset(self) -> None:
self._accumulated = 0.0
self._cycles = 0
def __repr__(self) -> str:
return f"FaceAlpha(strength={self.strength:.2f}, cycles={self._cycles})"
class FaceBeta:
"""
Face β — The Illogic Pole (Red).
Attracts contradictions, anomalies, pulse-stopping impossibilities.
Magnetic charge: Negative (creates vacuum).
Does not process — it HALTS processing.
"""
COLOR = "red"
SYMBOL = "β"
NAME = "Illogic"
def __init__(self, strength: float = 1.0):
self.strength = max(0.0, min(2.0, strength))
self._accumulated: float = 0.0
self._cycles: int = 0
self._vacuum_active: bool = False
def attract(self, ferro_data: Dict[str, Any]) -> float:
"""
Calculate attraction strength for the given Ferro-Data.
Illogic attraction is proportional to:
- High entropy (chaotic, unpredictable data)
- Contradictions
- Anomalies in token patterns
"""
entropy = ferro_data.get("entropy", 0.5)
length = ferro_data.get("length", 1)
# High entropy = high illogic attraction
attraction = self.strength * min(entropy / 8.0, 1.0)
# Add stochastic noise to simulate hallucination detection
noise = random.gauss(0, 0.05)
attraction = max(0.0, attraction + noise)
self._accumulated += attraction
self._cycles += 1
return attraction
def create_vacuum(self, illogic_ratio: float) -> float:
"""
Create a Magnetic Vacuum based on accumulated Illogic.
The vacuum is the key innovation — it pulls Truth by creating
an absence of falsehood.
Returns vacuum strength (0.0 to 1.0).
"""
self._vacuum_active = True
vacuum = illogic_ratio * self.strength
return min(vacuum, 1.0)
def reset(self) -> None:
self._accumulated = 0.0
self._cycles = 0
self._vacuum_active = False
@property
def is_vacuum_active(self) -> bool:
return self._vacuum_active
def __repr__(self) -> str:
return (
f"FaceBeta(strength={self.strength:.2f}, "
f"vacuum={'ON' if self._vacuum_active else 'OFF'})"
)
class FaceGamma:
"""
Face γ — The Context / Human Pulse Pole (Gold).
Attracts the sovereign intent and emotional frequency of the human user.
Magnetic charge: Resonant frequency.
Collapses the wave-function when the Pulse is applied.
"""
COLOR = "gold"
SYMBOL = "γ"
NAME = "Context"
def __init__(self, strength: float = 1.0):
self.strength = max(0.0, min(2.0, strength))
self._accumulated: float = 0.0
self._cycles: int = 0
self._pulse_applied: bool = False
self._pulse_value: float = 0.0
def attract(self, ferro_data: Dict[str, Any]) -> float:
"""
Calculate attraction strength for the given Ferro-Data.
Context attraction is proportional to:
- Presence of human-contextual markers
- Emotional/intentional signals
- Sovereignty indicators
"""
entropy = ferro_data.get("entropy", 0.5)
tokens = ferro_data.get("tokens", [])
# Moderate entropy = highest context attraction (the sweet spot)
mid_entropy = 1.0 - abs(entropy / 4.0 - 1.0)
attraction = self.strength * max(0.0, mid_entropy)
# Human-like token patterns increase attraction
if tokens:
# More diverse tokens suggest more human context
unique_ratio = len(set(tokens)) / max(len(tokens), 1)
attraction *= (0.5 + 0.5 * unique_ratio)
self._accumulated += attraction
self._cycles += 1
return attraction
def apply_pulse(self, pulse: float) -> None:
"""
Apply the Human Pulse to the Context face.
Args:
pulse: Sovereignty signal strength (0.0 to 1.0).
1.0 = full sovereign presence
0.0 = no human engagement
"""
self._pulse_applied = True
self._pulse_value = max(0.0, min(1.0, pulse))
def reset(self) -> None:
self._accumulated = 0.0
self._cycles = 0
self._pulse_applied = False
self._pulse_value = 0.0
@property
def is_pulse_active(self) -> bool:
return self._pulse_applied
@property
def pulse_value(self) -> float:
return self._pulse_value
def __repr__(self) -> str:
return (
f"FaceGamma(strength={self.strength:.2f}, "
f"pulse={'ON' if self._pulse_applied else 'OFF'}, "
f"value={self._pulse_value:.2f})"
)
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