"""Backward compatibility wrapper for sdf module.

This module re-exports all functions from the sdf subpackage for backward compatibility.
New code should import directly from the sdf subpackage instead.
"""

from layout_system.sdf import optimize
from layout_system.sdf.core import (
    binary_to_sdf_norm,
    load_binary_mask_from_rgba,
)
from layout_system.sdf.visualization import (
    visualize_sdf,
    visualize_sdf_norm_and_softmask,
)

if __name__ == "__main__":
    import json
    
    # Visualize SDFs
    print("Loading images and computing SDFs...")
    mask1 = load_binary_mask_from_rgba("chart.png")
    mask2 = load_binary_mask_from_rgba("pictogram.png")
    
    sdf1_norm = binary_to_sdf_norm(mask1, pad=16)
    sdf2_norm = binary_to_sdf_norm(mask2, pad=16)
    
    print(f"SDF 1 shape: {sdf1_norm.shape}, range: [{sdf1_norm.min():.3f}, {sdf1_norm.max():.3f}]")
    print(f"SDF 2 shape: {sdf2_norm.shape}, range: [{sdf2_norm.min():.3f}, {sdf2_norm.max():.3f}]")
    
    # Use a smaller range (0.05) for finer detail around the boundary
    visualize_sdf(sdf1_norm, sdf2_norm, mask1, mask2, 
                  save_path="sdf_visualization.png", sdf_range=0.05)
    
    # Visualize SDF normalization and softmask conversion for both images
    print("\nVisualizing SDF normalization and softmask conversion...")
    
    # For mask1 (chart) - use a sample bbox covering most of the image
    H1, W1 = mask1.shape
    bbox1_sample = (W1 * 0.1, H1 * 0.1, W1 * 0.8, H1 * 0.8)
    visualize_sdf_norm_and_softmask(sdf1_norm, mask1, 
                                     bbox=bbox1_sample, 
                                     container_size=(W1, H1),
                                     save_path="sdf_norm_softmask_chart.png")
    
    # For mask2 (pictogram) - use a sample bbox covering most of the image
    H2, W2 = mask2.shape
    bbox2_sample = (W2 * 0.1, H2 * 0.1, W2 * 0.8, H2 * 0.8)
    visualize_sdf_norm_and_softmask(sdf2_norm, mask2,
                                     bbox=bbox2_sample,
                                     container_size=(W2, H2),
                                     save_path="sdf_norm_softmask_pictogram.png")
    
    # Load reference layout from JSON
    print("\n" + "="*50)
    print("Loading reference layout from simplified.json...")
    print("="*50)
    
    json_path = "simplified.json"
    
    with open(json_path, 'r') as f:
        json_data = json.load(f)
    
    # Extract reference bboxes from children
    reference_bboxes = []
    reference_parent_bbox = None
    
    if "children" in json_data and len(json_data["children"]) >= 2:
        # Extract parent container bbox
        parent_bbox = json_data.get("bbox", {})
        reference_parent_bbox = (
            parent_bbox.get("x", 0),
            parent_bbox.get("y", 0),
            parent_bbox.get("width", 1000),
            parent_bbox.get("height", 1000)
        )
        
        # Extract children bboxes (reference layout)
        for child in json_data["children"]:
            child_bbox = child.get("bbox", {})
            ref_bbox = (
                child_bbox.get("x", 0),
                child_bbox.get("y", 0),
                child_bbox.get("width", 100),
                child_bbox.get("height", 100)
            )
            reference_bboxes.append(ref_bbox)
    
    print(f"Reference parent bbox: {reference_parent_bbox}")
    print(f"Reference bboxes: {reference_bboxes}")
    
    # Run optimization
    print("\n" + "="*50)
    print("Running optimization...")
    print("="*50)
    optimize(png_list=["chart.png", "pictogram.png"], 
             reference_bboxes=reference_bboxes,
             reference_parent_bbox=reference_parent_bbox,
             w_similarity=1000.0)