"""
Vectorized NumPy utilities for geographic distance calculations.
"""

import numpy as np
import logging

logger = logging.getLogger(__name__)

def calculate_haversine_matrix_vectorized(lats: np.ndarray, lons: np.ndarray) -> np.ndarray:
    """
    Calculate an N x N distance matrix using the Haversine formula.
    Fully vectorized using NumPy for O(N^2) speed improvement over Python loops.
    """
    # Earth's radius in kilometers
    R = 6371.0
    
    # Convert degrees to radians
    lats_rad = np.radians(lats)
    lons_rad = np.radians(lons)
    
    # Create meshgrids for pairwise differences
    # lats.reshape(-1, 1) creates a column vector
    # lats.reshape(1, -1) creates a row vector
    # Subtracting them creates an N x N matrix of differences
    dlat = lats_rad.reshape(-1, 1) - lats_rad.reshape(1, -1)
    dlon = lons_rad.reshape(-1, 1) - lons_rad.reshape(1, -1)
    
    # Haversine formula
    a = np.sin(dlat / 2)**2 + np.cos(lats_rad.reshape(-1, 1)) * np.cos(lats_rad.reshape(1, -1)) * np.sin(dlon / 2)**2
    c = 2 * np.arctan2(np.sqrt(a), np.sqrt(1 - a))
    
    return R * c