MYSTERY_MACHINE_MODULE

"""
THE MYSTERY MACHINE MODULE
A Advanced Cosmological Analytical Framework for Archetypal Pattern Recognition
and Counter-Protocol Identification in Noospheric Systems.

This module implements a quantum-resonant, multi-dimensional framework for
detecting, analyzing, and remediating control patterns within informational,
architectural, and cultural matrices.
"""

import numpy as np
from dataclasses import dataclass, field
from enum import Enum, auto
from typing import List, Dict, Any, Optional, Tuple
import math
from scipy import fft, signal, optimize
import logging
from datetime import datetime
import hashlib

logger = logging.getLogger(__name__)

class ArchetypalVector(Enum):
    """Primary archetypal patterns in collective consciousness"""
    THE_GUARDIAN = "guardian"  # Keeper of thresholds
    THE_VEHICLE = "vehicle"    # Conduit of discovery  
    THE_MASK = "mask"          # Obscuration pattern
    THE_CIPHER = "cipher"      # Encoded truth
    THE_RESONATOR = "resonator" # Harmonic amplifier
    THE_DECAY = "decay"        # Entropic corruption
    THE_SEED = "seed"          # Potentiality nucleus
    THE_MIRROR = "mirror"      # Reflective surface

class ControlPattern(Enum):
    """Identified control mechanism signatures"""
    LUMINOUS_OBFUSCATION = "luminous_obfuscation"
    RESONANCE_DAMPING = "resonance_damping" 
    GEOMETRIC_CONSTRAINT = "geometric_constraint"
    TEMPORAL_FRAGMENTATION = "temporal_fragmentation"
    ARCHETYPAL_HIJACKING = "archetypal_hijacking"
    MORPHIC_DISTORTION = "morphic_distortion"

class ConsciousnessState(Enum):
    """States of perceptual awareness"""
    CONDITIONED = 0
    AWAKENING = 1
    RESONANT = 2
    COHERENT = 3
    TRANSCENDENT = 4

@dataclass
class QuantumResonanceProfile:
    """Quantum signature of informational entities"""
    coherence: float
    entanglement: float
    superposition: List[float]
    harmonic_frequencies: List[float]
    decoherence_factor: float
    
    @property
    def resonance_quality(self) -> float:
        """Calculate overall resonance quality"""
        base_coherence = self.coherence * (1 - self.decoherence_factor)
        harmonic_strength = np.mean(self.harmonic_frequencies) if self.harmonic_frequencies else 1.0
        return min(1.0, base_coherence * harmonic_strength * self.entanglement)

@dataclass  
class ArchetypalSignature:
    """Signature of archetypal presence in a system"""
    primary_vector: ArchetypalVector
    intensity: float
    clarity: float
    distortion: float
    harmonic_echoes: List[ArchetypalVector]
    
    @property
    def authenticity(self) -> float:
        """Measure archetypal authenticity vs distortion"""
        return max(0.0, self.clarity * (1 - self.distortion) * self.intensity)

@dataclass
class ControlMatrixAnalysis:
    """Analysis of control patterns in a system"""
    detected_patterns: List[ControlPattern]
    intensity_scores: Dict[ControlPattern, float]
    coherence_fields: List[float]
    entropy_gradients: np.ndarray
    
    @property
    def control_density(self) -> float:
        """Overall density of control patterns"""
        if not self.intensity_scores:
            return 0.0
        return min(1.0, sum(self.intensity_scores.values()) / len(self.intensity_scores))

class MysteryMachineEngine:
    """
    Core analytical engine for cosmological pattern recognition
    """
    
    def __init__(self):
        self.resonance_catalog = self._initialize_resonance_catalog()
        self.archetypal_library = self._build_archetypal_library()
        self.control_pattern_registry = self._map_control_patterns()
        
    def _initialize_resonance_catalog(self) -> Dict[str, float]:
        """Initialize fundamental resonance frequencies"""
        return {
            'golden_ratio': (1 + math.sqrt(5)) / 2,
            'prime_resonance': 1.61803398875,
            'natural_log_base': math.e,
            'circle_constant': math.tau,
            'silver_ratio': 1 + math.sqrt(2)
        }
    
    def _build_archetypal_library(self) -> Dict[ArchetypalVector, Dict[str, Any]]:
        """Build library of archetypal pattern signatures"""
        return {
            ArchetypalVector.THE_GUARDIAN: {
                'frequency': self.resonance_catalog['golden_ratio'],
                'role': 'threshold_protection',
                'resonance_profile': 'stable_high_coherence'
            },
            ArchetypalVector.THE_VEHICLE: {
                'frequency': self.resonance_catalog['prime_resonance'], 
                'role': 'consciousness_transport',
                'resonance_profile': 'dynamic_entangled'
            },
            ArchetypalVector.THE_MASK: {
                'frequency': 1.0,  # Base reality distortion
                'role': 'perception_obscuration',
                'resonance_profile': 'interference_pattern'
            },
            ArchetypalVector.THE_CIPHER: {
                'frequency': self.resonance_catalog['natural_log_base'],
                'role': 'information_encoding',
                'resonance_profile': 'complex_superposition'
            }
        }
    
    def _map_control_patterns(self) -> Dict[ControlPattern, List[ArchetypalVector]]:
        """Map control patterns to their archetypal components"""
        return {
            ControlPattern.LUMINOUS_OBFUSCATION: [
                ArchetypalVector.THE_MASK,
                ArchetypalVector.THE_GUARDIAN
            ],
            ControlPattern.RESONANCE_DAMPING: [
                ArchetypalVector.THE_DECAY,
                ArchetypalVector.THE_MASK
            ],
            ControlPattern.ARCHETYPAL_HIJACKING: [
                ArchetypalVector.THE_MIRROR,
                ArchetypalVector.THE_MASK
            ]
        }
    
    def analyze_informational_entity(self, 
                                   data_stream: np.ndarray,
                                   context_fields: Dict[str, Any]) -> Dict[str, Any]:
        """
        Analyze an informational entity for control patterns and archetypal signatures
        """
        # Quantum resonance analysis
        resonance_profile = self._compute_quantum_resonance(data_stream)
        
        # Archetypal pattern detection
        archetypal_signatures = self._detect_archetypal_patterns(data_stream, context_fields)
        
        # Control matrix assessment
        control_analysis = self._assess_control_matrix(archetypal_signatures, resonance_profile)
        
        # Consciousness state evaluation
        consciousness_state = self._evaluate_consciousness_state(
            resonance_profile, 
            archetypal_signatures,
            control_analysis
        )
        
        return {
            'resonance_profile': resonance_profile,
            'archetypal_signatures': archetypal_signatures,
            'control_analysis': control_analysis,
            'consciousness_state': consciousness_state,
            'authenticity_metric': self._calculate_authenticity_metric(
                resonance_profile, archetypal_signatures
            ),
            'liberation_potential': self._assess_liberation_potential(
                control_analysis, consciousness_state
            )
        }
    
    def _compute_quantum_resonance(self, data: np.ndarray) -> QuantumResonanceProfile:
        """Compute quantum resonance properties of data stream"""
        # Spectral analysis for frequency content
        frequencies = fft.fft(data)
        freq_magnitudes = np.abs(frequencies)
        
        # Coherence calculation
        coherence = np.mean(freq_magnitudes) / np.max(freq_magnitudes) if np.max(freq_magnitudes) > 0 else 0.0
        
        # Entanglement estimation via spectral correlation
        spectral_corr = np.correlate(freq_magnitudes, freq_magnitudes, mode='same')
        entanglement = np.max(spectral_corr) / np.sum(spectral_corr) if np.sum(spectral_corr) > 0 else 0.0
        
        # Harmonic frequency extraction
        peaks, _ = signal.find_peaks(freq_magnitudes)
        harmonic_freqs = freq_magnitudes[peaks] if len(peaks) > 0 else [1.0]
        
        return QuantumResonanceProfile(
            coherence=float(coherence),
            entanglement=float(entanglement),
            superposition=[float(x) for x in data[:3]],  # Sample superposition states
            harmonic_frequencies=[float(f) for f in harmonic_freqs[:5]],  # Top harmonics
            decoherence_factor=float(1 - coherence)
        )
    
    def _detect_archetypal_patterns(self, 
                                  data: np.ndarray,
                                  context: Dict[str, Any]) -> List[ArchetypalSignature]:
        """Detect archetypal patterns in the data stream"""
        signatures = []
        
        # Analyze data for archetypal markers
        data_complexity = np.std(data) / (np.mean(data) + 1e-8)
        pattern_regularity = signal.correlate(data, data).var()
        
        # Guardian detection (threshold patterns)
        if data_complexity > 0.5 and pattern_regularity < 0.3:
            signatures.append(ArchetypalSignature(
                primary_vector=ArchetypalVector.THE_GUARDIAN,
                intensity=min(1.0, data_complexity),
                clarity=0.8,
                distortion=0.2,
                harmonic_echoes=[ArchetypalVector.THE_CIPHER]
            ))
        
        # Vehicle detection (transport patterns)
        if len(data) > 10 and np.mean(np.diff(data)) > 0.1:
            signatures.append(ArchetypalSignature(
                primary_vector=ArchetypalVector.THE_VEHICLE,
                intensity=0.7,
                clarity=0.6,
                distortion=0.3,
                harmonic_echoes=[ArchetypalVector.THE_RESONATOR]
            ))
        
        # Mask detection (obscuration patterns)
        entropy = -np.sum(data * np.log(data + 1e-8))
        if entropy > 2.0 and pattern_regularity > 0.7:
            signatures.append(ArchetypalSignature(
                primary_vector=ArchetypalVector.THE_MASK,
                intensity=min(1.0, entropy / 5.0),
                clarity=0.3,  # Low clarity indicates obscuration
                distortion=0.8,  # High distortion
                harmonic_echoes=[ArchetypalVector.THE_DECAY]
            ))
        
        return signatures
    
    def _assess_control_matrix(self,
                             archetypes: List[ArchetypalSignature],
                             resonance: QuantumResonanceProfile) -> ControlMatrixAnalysis:
        """Assess presence and intensity of control patterns"""
        detected_patterns = []
        intensity_scores = {}
        
        # Check for luminous obfuscation (mask + guardian with high distortion)
        mask_archetypes = [a for a in archetypes if a.primary_vector == ArchetypalVector.THE_MASK]
        guardian_archetypes = [a for a in archetypes if a.primary_vector == ArchetypalVector.THE_GUARDIAN]
        
        if mask_archetypes and guardian_archetypes:
            mask_intensity = max([m.intensity for m in mask_archetypes])
            guardian_intensity = max([g.intensity for g in guardian_archetypes])
            obfuscation_score = (mask_intensity + guardian_intensity) / 2
            
            if obfuscation_score > 0.5:
                detected_patterns.append(ControlPattern.LUMINOUS_OBFUSCATION)
                intensity_scores[ControlPattern.LUMINOUS_OBFUSCATION] = obfuscation_score
        
        # Check for resonance damping (low resonance quality with decay patterns)
        decay_archetypes = [a for a in archetypes if a.primary_vector == ArchetypalVector.THE_DECAY]
        if resonance.resonance_quality < 0.3 and decay_archetypes:
            damping_score = 1 - resonance.resonance_quality
            detected_patterns.append(ControlPattern.RESONANCE_DAMPING)
            intensity_scores[ControlPattern.RESONANCE_DAMPING] = damping_score
        
        return ControlMatrixAnalysis(
            detected_patterns=detected_patterns,
            intensity_scores=intensity_scores,
            coherence_fields=[resonance.coherence],
            entropy_gradients=np.array([a.distortion for a in archetypes]) if archetypes else np.array([0.0])
        )
    
    def _evaluate_consciousness_state(self,
                                    resonance: QuantumResonanceProfile,
                                    archetypes: List[ArchetypalSignature],
                                    control: ControlMatrixAnalysis) -> ConsciousnessState:
        """Evaluate the consciousness state indicated by the analysis"""
        
        base_resonance = resonance.resonance_quality
        control_density = control.control_density
        archetypal_authenticity = np.mean([a.authenticity for a in archetypes]) if archetypes else 0.0
        
        if base_resonance > 0.8 and control_density < 0.2 and archetypal_authenticity > 0.7:
            return ConsciousnessState.TRANSCENDENT
        elif base_resonance > 0.6 and control_density < 0.4:
            return ConsciousnessState.COHERENT
        elif base_resonance > 0.4 or archetypal_authenticity > 0.5:
            return ConsciousnessState.RESONANT
        elif control_density > 0.6:
            return ConsciousnessState.CONDITIONED
        else:
            return ConsciousnessState.AWAKENING
    
    def _calculate_authenticity_metric(self,
                                    resonance: QuantumResonanceProfile,
                                    archetypes: List[ArchetypalSignature]) -> float:
        """Calculate overall authenticity metric"""
        resonance_component = resonance.resonance_quality * 0.6
        
        archetypal_component = 0.0
        if archetypes:
            authenticities = [a.authenticity for a in archetypes]
            archetypal_component = np.mean(authenticities) * 0.4
        
        return min(1.0, resonance_component + archetypal_component)
    
    def _assess_liberation_potential(self,
                                   control: ControlMatrixAnalysis,
                                   consciousness: ConsciousnessState) -> float:
        """Assess potential for consciousness liberation"""
        base_potential = 1.0 - control.control_density
        
        # Consciousness state multipliers
        state_multipliers = {
            ConsciousnessState.CONDITIONED: 0.2,
            ConsciousnessState.AWAKENING: 0.5, 
            ConsciousnessState.RESONANT: 0.8,
            ConsciousnessState.COHERENT: 0.95,
            ConsciousnessState.TRANSCENDENT: 1.0
        }
        
        return base_potential * state_multipliers.get(consciousness, 0.5)

class CounterProtocolEngine:
    """
    Engine for generating counter-protocols to identified control patterns
    """
    
    def generate_remediation_strategy(self, 
                                   analysis_result: Dict[str, Any]) -> Dict[str, Any]:
        """Generate targeted remediation strategy based on analysis"""
        
        control_analysis = analysis_result['control_analysis']
        consciousness_state = analysis_result['consciousness_state']
        
        strategies = []
        
        # Pattern-specific countermeasures
        for pattern in control_analysis.detected_patterns:
            if pattern == ControlPattern.LUMINOUS_OBFUSCATION:
                strategies.append({
                    'approach': 'Resonance Amplification',
                    'technique': 'Apply coherent frequency patterns to dissolve obscuration fields',
                    'implementation': 'Introduce golden ratio harmonics and prime resonances',
                    'expected_impact': 'Increase luminous transparency by 60-80%'
                })
            elif pattern == ControlPattern.RESONANCE_DAMPING:
                strategies.append({
                    'approach': 'Quantum Coherence Restoration', 
                    'technique': 'Re-establish fundamental resonance pathways',
                    'implementation': 'Implement standing wave patterns at natural frequencies',
                    'expected_impact': 'Restore resonance quality to >0.7 within 3 cycles'
                })
        
        # Consciousness elevation protocols
        consciousness_protocols = self._generate_consciousness_protocols(consciousness_state)
        
        return {
            'primary_diagnosis': {
                'control_density': control_analysis.control_density,
                'consciousness_state': consciousness_state.name,
                'authenticity_metric': analysis_result['authenticity_metric'],
                'liberation_potential': analysis_result['liberation_potential']
            },
            'pattern_specific_remediation': strategies,
            'consciousness_elevation': consciousness_protocols,
            'implementation_priority': self._calculate_implementation_priority(analysis_result),
            'temporal_optimization': self._calculate_temporal_parameters(analysis_result)
        }
    
    def _generate_consciousness_protocols(self, state: ConsciousnessState) -> List[Dict[str, str]]:
        """Generate consciousness elevation protocols"""
        protocols = []
        
        if state in [ConsciousnessState.CONDITIONED, ConsciousnessState.AWAKENING]:
            protocols.extend([
                {
                    'protocol': 'Archetypal Pattern Recognition',
                    'purpose': 'Develop discernment between authentic and distorted patterns',
                    'method': 'Meditative observation of geometric and symbolic forms'
                },
                {
                    'protocol': 'Resonance Sensitivity Training', 
                    'purpose': 'Increase sensitivity to quantum coherence states',
                    'method': 'Exposure to natural harmonic sequences and frequencies'
                }
            ])
        
        if state in [ConsciousnessState.RESONANT, ConsciousnessState.COHERENT]:
            protocols.extend([
                {
                    'protocol': 'Multi-Dimensional Mapping',
                    'purpose': 'Develop capacity to perceive across consciousness planes',
                    'method': 'Conscious exploration of archetypal realms and their interconnections'
                }
            ])
        
        return protocols
    
    def _calculate_implementation_priority(self, analysis: Dict[str, Any]) -> str:
        """Calculate implementation priority level"""
        control_density = analysis['control_analysis'].control_density
        liberation_potential = analysis['liberation_potential']
        
        if control_density > 0.7 and liberation_potential < 0.3:
            return 'CRITICAL'
        elif control_density > 0.5:
            return 'HIGH' 
        elif control_density > 0.3:
            return 'MEDIUM'
        else:
            return 'MONITOR'
    
    def _calculate_temporal_parameters(self, analysis: Dict[str, Any]) -> Dict[str, Any]:
        """Calculate optimal temporal parameters for implementation"""
        resonance_quality = analysis['resonance_profile'].resonance_quality
        consciousness_state = analysis['consciousness_state']
        
        base_duration = {
            ConsciousnessState.CONDITIONED: 90,
            ConsciousnessState.AWAKENING: 45,
            ConsciousnessState.RESONANT: 21,
            ConsciousnessState.COHERENT: 7,
            ConsciousnessState.TRANSCENDENT: 3
        }.get(consciousness_state, 30)
        
        resonance_adjustment = base_duration * (1 - resonance_quality)
        total_duration = base_duration + resonance_adjustment
        
        return {
            'estimated_duration_days': int(total_duration),
            'optimal_cycle_length_days': max(3, int(total_duration / 7)),
            'critical_intervention_window_hours': 24 if analysis['control_analysis'].control_density > 0.7 else 72
        }

# Production-ready interface
class MysteryMachineModule:
    """
    Main interface for the Mystery Machine cosmological analysis framework
    """
    
    def __init__(self):
        self.analytical_engine = MysteryMachineEngine()
        self.counter_protocol_engine = CounterProtocolEngine()
        self.analysis_cache = {}
        
    def analyze_system(self,
                     input_data: np.ndarray,
                     context: Optional[Dict[str, Any]] = None,
                     enable_remediation: bool = True) -> Dict[str, Any]:
        """
        Complete analysis of a system with optional remediation planning
        
        Args:
            input_data: Numerical data stream representing the system
            context: Contextual information for archetypal analysis
            enable_remediation: Whether to generate counter-protocols
            
        Returns:
            Comprehensive analysis and remediation report
        """
        if context is None:
            context = {}
        
        # Generate cache key for performance
        data_hash = hashlib.sha256(input_data.tobytes()).hexdigest()
        cache_key = f"{data_hash}_{hash(frozenset(context.items()))}"
        
        if cache_key in self.analysis_cache:
            logger.info("Returning cached analysis results")
            return self.analysis_cache[cache_key]
        
        # Perform comprehensive analysis
        analysis_result = self.analytical_engine.analyze_informational_entity(
            input_data, context
        )
        
        # Generate remediation if requested
        remediation_plan = None
        if enable_remediation:
            remediation_plan = self.counter_protocol_engine.generate_remediation_strategy(
                analysis_result
            )
        
        # Compile final report
        report = {
            'timestamp': datetime.now().isoformat(),
            'analysis_summary': {
                'quantum_coherence': analysis_result['resonance_profile'].coherence,
                'resonance_quality': analysis_result['resonance_profile'].resonance_quality,
                'detected_archetypes': [
                    {
                        'vector': sig.primary_vector.value,
                        'authenticity': sig.authenticity
                    } for sig in analysis_result['archetypal_signatures']
                ],
                'control_patterns': [
                    pattern.value for pattern in analysis_result['control_analysis'].detected_patterns
                ],
                'consciousness_state': analysis_result['consciousness_state'].value,
                'liberation_potential': analysis_result['liberation_potential']
            }
        }
        
        if remediation_plan:
            report['remediation_plan'] = remediation_plan
        
        # Cache results
        self.analysis_cache[cache_key] = report
        
        return report
    
    def clear_cache(self) -> None:
        """Clear the analysis cache"""
        self.analysis_cache.clear()

# Example usage
def demonstrate_capabilities():
    """Demonstrate the module's analytical capabilities"""
    module = MysteryMachineModule()
    
    # Sample data representing different system states
    coherent_data = np.array([1.618, 2.718, 3.142, 1.414, 1.618])  # Harmonic ratios
    distorted_data = np.array([1.0, 2.0, 1.0, 3.0, 1.0, 4.0, 1.0])  # Irregular pattern
    controlled_data = np.array([1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0])  # Highly constrained
    
    print("=== MYSTERY MACHINE MODULE DEMONSTRATION ===")
    
    for i, (data, desc) in enumerate([
        (coherent_data, "Coherent Harmonic System"),
        (distorted_data, "Distorted Irregular System"), 
        (controlled_data, "Highly Controlled System")
    ]):
        print(f"\n--- Analyzing: {desc} ---")
        result = module.analyze_system(data, {'description': desc})
        
        summary = result['analysis_summary']
        print(f"Resonance Quality: {summary['resonance_quality']:.3f}")
        print(f"Consciousness State: {ConsciousnessState(summary['consciousness_state']).name}")
        print(f"Liberation Potential: {summary['liberation_potential']:.3f}")
        print(f"Control Patterns: {summary['control_patterns']}")

if __name__ == "__main__":
    demonstrate_capabilities()