"""
Network modeling for acoustic routing.

This module contains the AcousticRoutingNetwork class for modeling
acoustic propagation through network topologies.
"""

import numpy as np
import networkx as nx
from typing import Dict, List, Tuple
from dataclasses import dataclass

@dataclass
class AcousticParameters:
    """Acoustic properties for routing edges"""
    delay_time: float  # Travel time or physical distance (ms)
    feedback: float    # Number of alternate routes/detours (0-1)
    decay: float       # Traffic dissipation/energy loss (0-1)
    reverb_density: float  # Local interconnectivity (0-1)


@dataclass
class Pulse:
    """Represents a propagating signal through the network"""
    origin: str
    current_position: str
    amplitude: float
    path_history: List[str]


class AcousticRoutingNetwork:
    """Main class for acoustic routing system.
    
    Models a network as an acoustic topology with nodes and edges
    that affect signal propagation.
    """
    
    def __init__(self):
        """Initialize a new acoustic routing network."""
        self.graph = nx.DiGraph()  # Directed graph for routing segments
        self.acoustic_params: Dict[Tuple[str, str], AcousticParameters] = {}
        self.node_positions: Dict[str, Tuple[float, float]] = {}  # For visualization

    # Add methods from the original acoustic_routing.py here
    # ... (to be implemented)
    
    # Example method - implement all methods from the original file
    def add_highway_segment(
        self,
        start: str,
        end: str,
        distance_miles: float,
        speed_limit_mph: float = 65,
        interconnectivity: float = 0.3,
        feedback_loops: float = 0.2
    ) -> None:
        """
        Add a highway segment with acoustic properties.
        
        Args:
            start: Starting city/node
            end: Ending city/node
            distance_miles: Physical distance
            speed_limit_mph: Speed limit for travel time calculation
            interconnectivity: Local density (reverb analog)
            feedback_loops: Number of detour options (echo analog)
        """

        # Calculate acoustic parameters
        travel_time_hours = distance_miles / speed_limit_mph
        delay_ms = travel_time_hours * 3600 * 1000  # Convert to milliseconds

        # Normalize feedback (0-1 scale based on typical detour count)
        feedback = min(feedback_loops / 5.0, 1.0)

        # Calculate decay based on distance (longer = more dissipation)
        decay = max(0.1, 1.0 - (distance_miles / 3000))  # Assume 3000 miles max

        params = AcousticParameters(
            delay_time=delay_ms,
            feedback=feedback,
            decay=decay,
            reverb_density=interconnectivity
        )

        # Add to graph
        self.graph.add_edge(start, end, weight=distance_miles)
        self.acoustic_params[(start, end)] = params

        # Add nodes if not exist
        if start not in self.node_positions:
            self.node_positions[start] = self._generate_position()
        if end not in self.node_positions:
            self.node_positions[end] = self._generate_position()

    def _generate_position(self) -> Tuple[float, float]:
        """Generate random position for visualization (simplified)"""
        return (np.random.uniform(-100, 100), np.random.uniform(-50, 50))
