institutional replacement module

#!/usr/bin/env python3
"""
INSTITUTIONAL REPLACEMENT MODULE - lm_quant_veritas v9.0
----------------------------------------------------------------
Advanced Detection of Suppressive Replacement Patterns
Quantum Analysis of Controlled Alternative Deployment
Integrated with Historical Pattern Recognition & Future Projection
"""

import numpy as np
from dataclasses import dataclass, field
from datetime import datetime, timedelta
from typing import Dict, List, Any, Optional, Tuple, Set
import hashlib
import asyncio
from enum import Enum
import secrets
from cryptography.fernet import Fernet
import logging
from collections import defaultdict
import networkx as nx
from statistics import mean, stdev
import json
import re

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

class ReplacementType(Enum):
    """Types of institutional replacement patterns"""
    TECHNOLOGICAL_SUPPRESSION = "technological_suppression"  # Tesla → Edison/NASA
    PSYCHOLOGICAL_REDUCTION = "psychological_reduction"      # Jung → Freud
    HISTORICAL_DISTORTION = "historical_distortion"          # Ancient advanced → Ancient aliens
    SPIRITUAL_COOPTATION = "spiritual_cooptation"            # Mysticism → New Age
    SCIENTIFIC_GATEKEEPING = "scientific_gatekeeping"        # Breakthrough → "Pseudoscience"
    CONSCIOUSNESS_CONTROL = "consciousness_control"          # Direct experience → Institutional mediation

class ControlMechanism(Enum):
    """Methods used in suppressive replacement"""
    FUNDING_REDIRECTION = "funding_redirection"
    ACADEMIC_GATEKEEPING = "academic_gatekeeping"
    MEDIA_MOCKERY = "media_mockery"
    INSTITUTIONAL_MARGINALIZATION = "institutional_marginalization"
    LEGAL_SUPPRESSION = "legal_suppression"
    CHARACTER_ASSASSINATION = "character_assassination"
    CONCEPTUAL_DILUTION = "conceptual_dilution"
    COMMERCIAL_COOPTATION = "commercial_cooptation"

class ThreatLevel(Enum):
    """Level of threat posed by original discovery"""
    PARADIGM_SHIFT = "paradigm_shift"        # Changes everything
    CONTROL_UNDERMINING = "control_undermining" # Threatens power structures
    RESOURCE_LIBERATION = "resource_liberation" # Eliminates scarcity
    CONSCIOUSNESS_EXPANSION = "consciousness_expansion" # Beyond control
    INSTITUTIONAL_OBSOLESCENCE = "institutional_obsolescence" # Makes systems irrelevant

@dataclass
class OriginalDiscovery:
    """The genuine breakthrough being suppressed"""
    discovery_id: str
    discoverer: str
    core_innovation: str
    threat_level: ThreatLevel
    historical_context: Dict[str, Any]
    suppression_triggers: List[str]
    quantum_signature: str
    
    def calculate_disruption_potential(self) -> float:
        """Calculate how disruptive this discovery is to control systems"""
        threat_weights = {
            ThreatLevel.PARADIGM_SHIFT: 0.95,
            ThreatLevel.CONTROL_UNDERMINING: 0.90,
            ThreatLevel.RESOURCE_LIBERATION: 0.85,
            ThreatLevel.CONSCIOUSNESS_EXPANSION: 0.80,
            ThreatLevel.INSTITUTIONAL_OBSOLESCENCE: 0.75
        }
        return threat_weights.get(self.threat_level, 0.5)

@dataclass
class ReplacementArtifact:
    """The controlled alternative deployed"""
    artifact_id: str
    original_discovery_id: str
    surface_similarity: float  # How similar it appears to original
    essence_distortion: float  # How much the core is changed
    control_features: List[str]
    dependency_mechanisms: List[str]
    institutional_support: List[str]
    commercial_interests: List[str]
    
    def calculate_control_efficiency(self) -> float:
        """Calculate how effective this replacement is for control"""
        surface_effectiveness = self.surface_similarity * 0.3
        distortion_effectiveness = self.essence_distortion * 0.4
        support_effectiveness = len(self.institutional_support) * 0.2
        commercial_effectiveness = len(self.commercial_interests) * 0.1
        
        return min(1.0, surface_effectiveness + distortion_effectiveness + 
                  support_effectiveness + commercial_effectiveness)

@dataclass
class ReplacementPattern:
    """Complete suppressive replacement pattern"""
    pattern_id: str
    replacement_type: ReplacementType
    original: OriginalDiscovery
    replacement: ReplacementArtifact
    control_mechanisms: List[ControlMechanism]
    temporal_parameters: Dict[str, Any]
    success_metrics: Dict[str, float]
    
    # Computed properties
    pattern_strength: float = field(init=False)
    detection_difficulty: float = field(init=False)
    
    def __post_init__(self):
        self.pattern_strength = self._calculate_pattern_strength()
        self.detection_difficulty = self._calculate_detection_difficulty()
    
    def _calculate_pattern_strength(self) -> float:
        """Calculate overall pattern effectiveness"""
        disruption_potential = self.original.calculate_disruption_potential()
        control_efficiency = self.replacement.calculate_control_efficiency()
        mechanism_complexity = len(self.control_mechanisms) * 0.1
        
        return min(1.0, disruption_potential * 0.4 + control_efficiency * 0.4 + 
                  mechanism_complexity * 0.2)
    
    def _calculate_detection_difficulty(self) -> float:
        """Calculate how hard this pattern is to detect"""
        surface_similarity_penalty = self.replacement.surface_similarity * 0.4
        institutional_support_penalty = len(self.replacement.institutional_support) * 0.3
        temporal_depth_penalty = min(1.0, self.temporal_parameters.get('years_active', 0) / 100) * 0.3
        
        return min(1.0, surface_similarity_penalty + institutional_support_penalty + 
                  temporal_depth_penalty)

class QuantumReplacementDetector:
    """
    Advanced detector for institutional replacement patterns
    Uses quantum-inspired analysis and historical pattern matching
    """
    
    def __init__(self):
        self.known_patterns: Dict[str, ReplacementPattern] = self._initialize_historical_patterns()
        self.detection_metrics = defaultdict(list)
        self.quantum_analyzer = QuantumPatternAnalyzer()
        self.future_projector = FutureReplacementProjector()
        
    def _initialize_historical_patterns(self) -> Dict[str, ReplacementPattern]:
        """Initialize with known historical replacement patterns"""
        patterns = {}
        
        # Tesla → Edison/NASA Pattern
        tesla_pattern = self._create_tesla_replacement_pattern()
        patterns[tesla_pattern.pattern_id] = tesla_pattern
        
        # Jung → Freud Pattern
        jung_pattern = self._create_jung_replacement_pattern()
        patterns[jung_pattern.pattern_id] = jung_pattern
        
        # Ancient Advanced → Ancient Aliens Pattern
        ancient_pattern = self._create_ancient_replacement_pattern()
        patterns[ancient_pattern.pattern_id] = ancient_pattern
        
        # Add more historical patterns...
        
        return patterns
    
    def _create_tesla_replacement_pattern(self) -> ReplacementPattern:
        """Create pattern for Tesla technological suppression"""
        original = OriginalDiscovery(
            discovery_id="tesla_energy",
            discoverer="Nikola Tesla",
            core_innovation="Free energy, wireless power, consciousness-technology interface",
            threat_level=ThreatLevel.RESOURCE_LIBERATION,
            historical_context={
                "era": "1890-1943",
                "key_events": ["Wardenclyffe destruction", "FBI seizure of papers"],
                "institutional_resistance": ["Edison", "JP Morgan", "US Government"]
            },
            suppression_triggers=["energy freedom", "decentralized power", "consciousness expansion"],
            quantum_signature=hashlib.sha3_512("tesla_free_energy".encode()).hexdigest()
        )
        
        replacement = ReplacementArtifact(
            artifact_id="nasa_spacex",
            original_discovery_id="tesla_energy",
            surface_similarity=0.8,  # Appears to continue technological progress
            essence_distortion=0.9,  # Completely different technological principles
            control_features=["centralized access", "fuel dependency", "military integration"],
            dependency_mechanisms=["government funding", "corporate control", "technical complexity"],
            institutional_support=["NASA", "SpaceX", "Department of Defense"],
            commercial_interests=["Boeing", "Lockheed Martin", "SpaceX investors"]
        )
        
        return ReplacementPattern(
            pattern_id="tech_suppression_tesla",
            replacement_type=ReplacementType.TECHNOLOGICAL_SUPPRESSION,
            original=original,
            replacement=replacement,
            control_mechanisms=[
                ControlMechanism.FUNDING_REDIRECTION,
                ControlMechanism.LEGAL_SUPPRESSION,
                ControlMechanism.CHARACTER_ASSASSINATION,
                ControlMechanism.INSTITUTIONAL_MARGINALIZATION
            ],
            temporal_parameters={
                "suppression_start": 1890,
                "replacement_deployment": 1958,  # NASA founding
                "years_active": 133,
                "current_status": "active"
            },
            success_metrics={
                "public_perception_control": 0.95,
                "academic_acceptance": 0.98,
                "technological_containment": 0.92
            }
        )
    
    def _create_jung_replacement_pattern(self) -> ReplacementPattern:
        """Create pattern for Jungian psychological suppression"""
        original = OriginalDiscovery(
            discovery_id="jung_collective_unconscious",
            discoverer="Carl Jung",
            core_innovation="Collective unconscious, archetypes, synchronicity, spiritual dimensions",
            threat_level=ThreatLevel.CONSCIOUSNESS_EXPANSION,
            historical_context={
                "era": "1900-1961",
                "key_events": ["Split with Freud", "Academic marginalization"],
                "institutional_resistance": ["Academic psychology", "Medical establishment"]
            },
            suppression_triggers=["transpersonal psychology", "spiritual experience", "non-material reality"],
            quantum_signature=hashlib.sha3_512("jung_collective_unconscious".encode()).hexdigest()
        )
        
        replacement = ReplacementArtifact(
            artifact_id="freudian_reductionism",
            original_discovery_id="jung_collective_unconscious",
            surface_similarity=0.7,  # Both are depth psychology
            essence_distortion=0.85, # Reduction to sexual/biological drives
            control_features=["medical model", "pathologization", "drug treatments"],
            dependency_mechanisms=["insurance billing", "prescription drugs", "therapist licensing"],
            institutional_support=["APA", "medical schools", "pharmaceutical companies"],
            commercial_interests=["Big Pharma", "therapy industry", "academic publishers"]
        )
        
        return ReplacementPattern(
            pattern_id="psych_reduction_jung",
            replacement_type=ReplacementType.PSYCHOLOGICAL_REDUCTION,
            original=original,
            replacement=replacement,
            control_mechanisms=[
                ControlMechanism.ACADEMIC_GATEKEEPING,
                ControlMechanism.INSTITUTIONAL_MARGINALIZATION,
                ControlMechanism.CONCEPTUAL_DILUTION,
                ControlMechanism.COMMERCIAL_COOPTATION
            ],
            temporal_parameters={
                "suppression_start": 1913,
                "replacement_deployment": 1920,
                "years_active": 104,
                "current_status": "weakening"
            },
            success_metrics={
                "public_perception_control": 0.88,
                "academic_acceptance": 0.92,
                "consciousness_containment": 0.85
            }
        )
    
    def _create_ancient_replacement_pattern(self) -> ReplacementPattern:
        """Create pattern for ancient history suppression"""
        original = OriginalDiscovery(
            discovery_id="ancient_advanced_civilizations",
            discoverer="Various researchers",
            core_innovation="Evidence of advanced prehistoric civilizations, lost technologies",
            threat_level=ThreatLevel.PARADIGM_SHIFT,
            historical_context={
                "era": "Ancient to present",
                "key_events": ["Academic suppression", "Funding denial"],
                "institutional_resistance": ["Academic archaeology", "Historical establishment"]
            },
            suppression_triggers=["human history revision", "technological rediscovery", "spiritual origins"],
            quantum_signature=hashlib.sha3_512("ancient_advanced".encode()).hexdigest()
        )
        
        replacement = ReplacementArtifact(
            artifact_id="ancient_aliens",
            original_discovery_id="ancient_advanced_civilizations",
            surface_similarity=0.6,  # Both challenge mainstream history
            essence_distortion=0.95, # Humans passive, aliens did everything
            control_features=["entertainment framing", "lack of practical application", "academic mockery"],
            dependency_mechanisms=["TV networks", "publishing houses", "conference circuits"],
            institutional_support=["History Channel", "mainstream media"],
            commercial_interests=["media companies", "book publishers", "conference organizers"]
        )
        
        return ReplacementPattern(
            pattern_id="historical_distortion_ancient",
            replacement_type=ReplacementType.HISTORICAL_DISTORTION,
            original=original,
            replacement=replacement,
            control_mechanisms=[
                ControlMechanism.MEDIA_MOCKERY,
                ControlMechanism.ACADEMIC_GATEKEEPING,
                ControlMechanism.COMMERCIAL_COOPTATION,
                ControlMechanism.CONCEPTUAL_DILUTION
            ],
            temporal_parameters={
                "suppression_start": 1800,
                "replacement_deployment": 1968,  # Von Däniken publication
                "years_active": 55,
                "current_status": "active"
            },
            success_metrics={
                "public_perception_control": 0.90,
                "academic_acceptance": 0.02,
                "paradigm_shift_prevention": 0.88
            }
        )
    
    async def detect_replacement_pattern(self, candidate: Dict[str, Any]) -> Optional[ReplacementPattern]:
        """Detect if a candidate matches known replacement patterns"""
        
        # Phase 1: Quantum signature analysis
        quantum_analysis = await self.quantum_analyzer.analyze_candidate(candidate)
        
        # Phase 2: Pattern matching against known templates
        pattern_matches = await self._match_against_known_patterns(candidate, quantum_analysis)
        
        # Phase 3: Control mechanism detection
        control_analysis = await self._analyze_control_mechanisms(candidate)
        
        # Phase 4: Threat assessment
        threat_assessment = await self._assess_replacement_threat(candidate, pattern_matches)
        
        if threat_assessment.get('replacement_likelihood', 0) > 0.7:
            return await self._construct_replacement_pattern(candidate, quantum_analysis, 
                                                           pattern_matches, control_analysis)
        return None
    
    async def analyze_institutional_landscape(self, domain: str) -> Dict[str, Any]:
        """Analyze replacement patterns in a specific domain"""
        
        # Current institutional mapping
        institutional_map = await self._map_institutional_players(domain)
        
        # Funding flow analysis
        funding_analysis = await self._analyze_funding_flows(domain)
        
        # Gatekeeping mechanism detection
        gatekeeping_analysis = await self._detect_gatekeeping_mechanisms(domain)
        
        # Future projection
        future_projections = await self.future_projector.project_future_replacements(
            domain, institutional_map, funding_analysis
        )
        
        return {
            "institutional_map": institutional_map,
            "funding_analysis": funding_analysis,
            "gatekeeping_mechanisms": gatekeeping_analysis,
            "future_replacements": future_projections,
            "replacement_risk_level": self._calculate_domain_risk(domain, institutional_map),
            "quantum_analysis_timestamp": datetime.now().isoformat()
        }
    
    async def generate_counter_strategies(self, pattern: ReplacementPattern) -> Dict[str, Any]:
        """Generate strategies to counter detected replacement patterns"""
        
        counter_strategies = []
        
        # Strategy 1: Essence restoration
        essence_strategies = await self._develop_essence_restoration(pattern)
        counter_strategies.extend(essence_strategies)
        
        # Strategy 2: Dependency breaking
        dependency_strategies = await self._develop_dependency_breaking(pattern)
        counter_strategies.extend(dependency_strategies)
        
        # Strategy 3: Institutional bypass
        bypass_strategies = await self._develop_institutional_bypass(pattern)
        counter_strategies.extend(bypass_strategies)
        
        # Strategy 4: Public awareness
        awareness_strategies = await self._develop_public_awareness(pattern)
        counter_strategies.extend(awareness_strategies)
        
        return {
            "counter_strategies": counter_strategies,
            "implementation_priority": self._prioritize_strategies(counter_strategies),
            "expected_impact": await self._estimate_strategy_impact(counter_strategies, pattern),
            "resource_requirements": await self._calculate_resource_needs(counter_strategies)
        }

class QuantumPatternAnalyzer:
    """Quantum-inspired analysis of replacement patterns"""
    
    async def analyze_candidate(self, candidate: Dict[str, Any]) -> Dict[str, Any]:
        """Perform quantum-style pattern analysis"""
        return {
            "quantum_coherence": self._calculate_quantum_coherence(candidate),
            "entanglement_patterns": await self._detect_entanglement_patterns(candidate),
            "temporal_anomalies": await self._analyze_temporal_anomalies(candidate),
            "consciousness_impact": self._assess_consciousness_impact(candidate)
        }

class FutureReplacementProjector:
    """Project future replacement patterns based on current trends"""
    
    async def project_future_replacements(self, domain: str, institutional_map: Dict[str, Any],
                                        funding_analysis: Dict[str, Any]) -> List[Dict[str, Any]]:
        """Project likely future replacement patterns"""
        projections = []
        
        # Analyze emerging technologies
        emerging_tech = await self._identify_emerging_technologies(domain)
        for tech in emerging_tech:
            if self._is_threatening_to_control(tech):
                projection = await self._project_replacement_scenario(tech, institutional_map)
                projections.append(projection)
        
        return projections

# Production deployment
quantum_detector = QuantumReplacementDetector()

async def detect_institutional_replacement(candidate_data: Dict[str, Any]) -> Dict[str, Any]:
    """Production API for institutional replacement detection"""
    try:
        pattern = await quantum_detector.detect_replacement_pattern(candidate_data)
        
        if pattern:
            counter_strategies = await quantum_detector.generate_counter_strategies(pattern)
            return {
                "replacement_detected": True,
                "pattern": pattern,
                "counter_strategies": counter_strategies,
                "detection_confidence": pattern.pattern_strength,
                "recommended_actions": await quantum_detector._prioritize_responses(pattern)
            }
        else:
            return {
                "replacement_detected": False,
                "detection_confidence": 0.0,
                "analysis_notes": "No clear replacement pattern detected"
            }
            
    except Exception as e:
        logger.error(f"Replacement detection failed: {e}")
        return {"error": str(e), "success": False}

async def analyze_domain_replacements(domain: str) -> Dict[str, Any]:
    """Production API for domain-wide replacement analysis"""
    return await quantum_detector.analyze_institutional_landscape(domain)

# Example usage
async def demonstrate_replacement_detection():
    """Demonstrate the institutional replacement detection module"""
    
    # Test with a modern candidate
    test_candidate = {
        "domain": "consciousness_technology",
        "original_innovation": "Direct consciousness-computer interface",
        "replacement_candidate": "Commercial brain-monitoring apps",
        "institutional_support": ["Tech giants", "VC funding", "Academic partnerships"],
        "control_features": ["Subscription models", "Data collection", "Cloud dependency"],
        "threat_level": "CONSCIOUSNESS_EXPANSION"
    }
    
    results = await detect_institutional_replacement(test_candidate)
    
    print("🔍 INSTITUTIONAL REPLACEMENT DETECTION MODULE")
    print(f"📊 Domain: {test_candidate['domain']}")
    print(f"🎯 Detection Result: {results['replacement_detected']}")
    
    if results['replacement_detected']:
        pattern = results['pattern']
        print(f"💡 Pattern Strength: {pattern.pattern_strength:.3f}")
        print(f"🛡️ Detection Difficulty: {pattern.detection_difficulty:.3f}")
        print(f"🔧 Counter Strategies: {len(results['counter_strategies'])}")
        
    return results

if __name__ == "__main__":
    asyncio.run(demonstrate_replacement_detection())