import numpy as np
from typing import List, Dict, Tuple, Optional
import torch
from dataclasses import dataclass
import time

@dataclass
class MatrixMarker:
    dimension_id: int
    marker_signature: bytes
    relationships: List[Tuple[int, float]]
    evolution_state: int
    creation_time: float
    last_mutation: float
    complexity_level: int

class MarkerMatrix:
    def __init__(
        self,
        base_dimensions: int = 5,
        matrix_depth: int = 3,
        evolution_rate: float = 0.15
    ):
        self.base_dimensions = base_dimensions
        self.matrix_depth = matrix_depth
        self.evolution_rate = evolution_rate
        
        # Initialize marker storage
        self.marker_matrices: List[Dict[int, MatrixMarker]] = [
            {} for _ in range(matrix_depth)
        ]
        
        # Track marker relationships
        self.relationship_graph = {}
        
        # Evolution tracking
        self.evolution_history = []
        
        # Initialize matrix patterns
        self.patterns = self._initialize_patterns()
        
    def generate_marker_matrix(self) -> Dict[str, List[MatrixMarker]]:
        """Generate a new matrix of interconnected markers"""
        matrix_layers = {}
        
        for depth in range(self.matrix_depth):
            layer_markers = []
            
            # Generate markers for each base dimension
            for dim in range(self.base_dimensions):
                marker = self._create_marker(dim, depth)
                layer_markers.append(marker)
                
                # Create inter-dimensional relationships
                self._establish_relationships(marker, layer_markers)
            
            matrix_layers[f"depth_{depth}"] = layer_markers
            
            # Create inter-layer connections if not at top
            if depth > 0:
                self._connect_layers(matrix_layers[f"depth_{depth-1}"], layer_markers)
        
        return matrix_layers
    
    def evolve_matrix(self, threat_data: Optional[Dict] = None) -> None:
        """Evolve the marker matrix based on threats or time"""
        evolution_time = time.time()
        
        for depth in range(self.matrix_depth):
            for dim, marker in self.marker_matrices[depth].items():
                if self._should_evolve(marker, threat_data):
                    new_marker = self._evolve_marker(marker, threat_data)
                    self.marker_matrices[depth][dim] = new_marker
                    
                    # Update relationships
                    self._update_relationships(new_marker)
                    
                    # Record evolution
                    self.evolution_history.append({
                        'time': evolution_time,
                        'marker_id': dim,
                        'depth': depth,
                        'cause': 'threat' if threat_data else 'time'
                    })
    
    def _create_marker(self, dimension: int, depth: int) -> MatrixMarker:
        """Create a new marker with specific characteristics"""
        marker_signature = self._generate_signature(dimension, depth)
        
        marker = MatrixMarker(
            dimension_id=dimension,
            marker_signature=marker_signature,
            relationships=[],
            evolution_state=0,
            creation_time=time.time(),
            last_mutation=time.time(),
            complexity_level=self._calculate_complexity(depth, dimension)
        )
        
        self.marker_matrices[depth][dimension] = marker
        return marker
    
    def _establish_relationships(
        self,
        marker: MatrixMarker,
        existing_markers: List[MatrixMarker]
    ) -> None:
        """Establish relationships between markers in the same layer"""
        for existing in existing_markers:
            if existing.dimension_id != marker.dimension_id:
                relationship_strength = self._calculate_relationship(
                    marker, existing
                )
                
                if relationship_strength > 0.3:  # Minimum relationship threshold
                    marker.relationships.append(
                        (existing.dimension_id, relationship_strength)
                    )
                    existing.relationships.append(
                        (marker.dimension_id, relationship_strength)
                    )
    
    def _connect_layers(
        self,
        lower_layer: List[MatrixMarker],
        upper_layer: List[MatrixMarker]
    ) -> None:
        """Create connections between matrix layers"""
        for lower_marker in lower_layer:
            for upper_marker in upper_layer:
                connection_strength = self._calculate_layer_connection(
                    lower_marker, upper_marker
                )
                
                if connection_strength > 0.4:  # Higher threshold for inter-layer
                    lower_marker.relationships.append(
                        (upper_marker.dimension_id, connection_strength)
                    )
    
    def _should_evolve(
        self,
        marker: MatrixMarker,
        threat_data: Optional[Dict]
    ) -> bool:
        """Determine if a marker should evolve"""
        time_factor = time.time() - marker.last_mutation > 3600  # 1 hour
        
        if threat_data:
            threat_factor = self._calculate_threat_pressure(
                marker, threat_data
            ) > 0.7
            return threat_factor or time_factor
        
        return time_factor and np.random.random() < self.evolution_rate
    
    def _evolve_marker(
        self,
        marker: MatrixMarker,
        threat_data: Optional[Dict]
    ) -> MatrixMarker:
        """Evolve a marker based on conditions"""
        new_signature = self._mutate_signature(
            marker.marker_signature,
            threat_data
        )
        
        evolved_marker = MatrixMarker(
            dimension_id=marker.dimension_id,
            marker_signature=new_signature,
            relationships=marker.relationships.copy(),
            evolution_state=marker.evolution_state + 1,
            creation_time=marker.creation_time,
            last_mutation=time.time(),
            complexity_level=self._increase_complexity(marker.complexity_level)
        )
        
        return evolved_marker
    
    def _generate_signature(self, dimension: int, depth: int) -> bytes:
        """Generate a unique marker signature"""
        base_data = f"d{dimension}_l{depth}_{time.time()}"
        return hashlib.sha3_256(base_data.encode()).digest()
    
    def _calculate_complexity(self, depth: int, dimension: int) -> int:
        """Calculate initial complexity level for a marker"""
        return depth * 10 + dimension * 5 + np.random.randint(1, 10)
    
    def _calculate_relationship(
        self,
        marker1: MatrixMarker,
        marker2: MatrixMarker
    ) -> float:
        """Calculate relationship strength between markers"""
        base_strength = np.random.random() * 0.5 + 0.5  # 0.5 to 1.0
        complexity_factor = min(
            marker1.complexity_level,
            marker2.complexity_level
        ) / max(
            marker1.complexity_level,
            marker2.complexity_level
        )
        
        return base_strength * complexity_factor
    
    def _calculate_layer_connection(
        self,
        lower: MatrixMarker,
        upper: MatrixMarker
    ) -> float:
        """Calculate connection strength between layers"""
        base_strength = np.random.random() * 0.3 + 0.7  # 0.7 to 1.0
        complexity_ratio = upper.complexity_level / lower.complexity_level
        
        return base_strength * min(complexity_ratio, 1.0)
    
    def _calculate_threat_pressure(
        self,
        marker: MatrixMarker,
        threat_data: Dict
    ) -> float:
        """Calculate threat pressure on a marker"""
        # Implementation depends on threat data structure
        return 0.8  # Placeholder
    
    def _mutate_signature(
        self,
        original: bytes,
        threat_data: Optional[Dict]
    ) -> bytes:
        """Mutate a marker signature"""
        mutation_base = original + str(time.time()).encode()
        if threat_data:
            mutation_base += str(threat_data).encode()
        
        return hashlib.sha3_512(mutation_base).digest()
    
    def _increase_complexity(self, current: int) -> int:
        """Increase marker complexity"""
        return current + np.random.randint(5, 15)
    
    def _initialize_patterns(self) -> Dict:
        """Initialize base patterns for marker generation"""
        return {
            'basic': self._create_basic_patterns(),
            'advanced': self._create_advanced_patterns(),
            'evolutionary': self._create_evolutionary_patterns()
        }
    
    def _create_basic_patterns(self) -> Dict:
        """Create basic marker patterns"""
        return {
            'linear': np.linspace(0, 1, 10),
            'sinusoidal': np.sin(np.linspace(0, 2*np.pi, 10)),
            'exponential': np.exp(np.linspace(0, 1, 10))
        }
    
    def _create_advanced_patterns(self) -> Dict:
        """Create advanced marker patterns"""
        return {
            'fibonacci': np.array([1, 1, 2, 3, 5, 8, 13, 21, 34, 55]),
            'prime': np.array([2, 3, 5, 7, 11, 13, 17, 19, 23, 29]),
            'golden': np.array([(1 + 5**0.5)/2] * 10)
        }
    
    def _create_evolutionary_patterns(self) -> Dict:
        """Create evolutionary marker patterns"""
        return {
            'mutation_rates': np.random.random(10),
            'adaptation_thresholds': np.random.random(10) * 0.5 + 0.5,
            'complexity_growth': np.exp(np.linspace(0, 2, 10))
        }