#!/usr/bin/env python3
"""
Generate metadata markdown file for a completed panorama.
Can be called standalone or imported by the pipeline.
"""

import json
import math
import os
import re
import sys
from datetime import datetime


def generate_metadata(work_dir, output_name, sol, camera, rover,
                      azs, els, img_w, img_h, fov, n_cps, timings,
                      original_images, blender, output_png):
    """Generate a metadata .md file for a completed panorama."""

    md_path = os.path.join(work_dir, f"{output_name}_metadata.md")

    # Image info
    n_images = len(azs)
    az_min = min(azs)
    az_max = max(azs)
    az_range = az_max - az_min
    el_min = min(els)
    el_max = max(els)
    el_range = el_max - el_min

    # Output image info
    out_w, out_h, out_size_mb = 0, 0, 0
    if output_png and os.path.exists(output_png):
        out_size_mb = os.path.getsize(output_png) / 1024 / 1024
        try:
            from PIL import Image
            Image.MAX_IMAGE_PIXELS = None
            img = Image.open(output_png)
            out_w, out_h = img.size
        except Exception:
            pass

    # Gaps analysis
    sorted_azs = sorted(azs)
    gaps = [sorted_azs[i+1] - sorted_azs[i] for i in range(len(sorted_azs)-1)]
    avg_gap = sum(gaps) / len(gaps) if gaps else 0
    max_gap = max(gaps) if gaps else 0
    min_gap = min(gaps) if gaps else 0

    # Overlap estimate
    overlap_per_pair = fov - avg_gap if fov > avg_gap else 0

    # Coverage estimate
    total_coverage_h = az_range + fov  # first and last image extend beyond their centers
    coverage_pct = min(total_coverage_h / 360 * 100, 100)

    # Vertical coverage
    total_coverage_v = el_range + (img_h / img_w * fov)  # approximate VFOV
    vfov_per_image = img_h / img_w * fov  # approximate

    # Resolution estimate (degrees per pixel in output)
    if out_w > 0:
        deg_per_px_h = total_coverage_h / out_w
        px_per_deg_h = out_w / total_coverage_h
    else:
        deg_per_px_h = 0
        px_per_deg_h = 0

    # Equirectangular full sphere equivalent
    equiv_360_w = int(px_per_deg_h * 360) if px_per_deg_h > 0 else 0
    equiv_180_h = int(px_per_deg_h * 180) if px_per_deg_h > 0 else 0

    # Image list with details
    image_details = []
    for i, (az, el) in enumerate(zip(azs, els)):
        fname = os.path.basename(original_images[i]) if i < len(original_images) else f"image_{i}"
        image_details.append((i, fname, az, el))

    total_time = sum(timings.values()) if timings else 0

    content = f"""# Panorama Metadata — Sol {sol}

> Auto-generated by mars-panorama-pipeline on {datetime.utcnow().strftime('%Y-%m-%d %H:%M UTC')}

---

## Summary

| Property | Value |
|----------|-------|
| **Sol** | {sol} |
| **Rover** | {rover.capitalize()} |
| **Camera** | {camera} |
| **Images** | {n_images} |
| **Control Points** | {n_cps:,} |
| **Blender** | {blender} |
| **Processing Time** | {total_time:.0f}s ({total_time/60:.1f} min) |
| **Output** | {out_w} x {out_h} pixels |
| **File Size** | {out_size_mb:.1f} MB |

---

## Coverage

| Property | Value |
|----------|-------|
| **Azimuth Range** | {az_min:.1f}° to {az_max:.1f}° ({az_range:.1f}° span) |
| **Elevation Range** | {el_min:.1f}° to {el_max:.1f}° ({el_range:.1f}° span) |
| **Horizontal Coverage** | ~{total_coverage_h:.0f}° ({coverage_pct:.0f}% of 360°) |
| **Vertical Coverage** | ~{total_coverage_v:.0f}° |
| **FOV per Image** | {fov:.2f}° (horizontal) |
| **Avg Gap Between Images** | {avg_gap:.1f}° |
| **Avg Overlap** | {overlap_per_pair:.1f}° per pair |

### Equirectangular Projection Info

| Property | Value |
|----------|-------|
| **Projection** | Equirectangular (Hugin f2) |
| **Resolution** | {px_per_deg_h:.1f} px/deg |
| **Full 360° Equivalent Width** | {equiv_360_w} px |
| **Full 180° Equivalent Height** | {equiv_180_h} px |
| **Suitable for VR Skybox** | {'Yes' if coverage_pct > 80 else 'Partial — needs gap filling'} |

---

## Camera Specifications

| Property | Value |
|----------|-------|
| **Camera** | {camera} |
| **Image Size (per frame)** | {img_w} x {img_h} px |
| **HFOV** | {fov:.2f}° |
| **VFOV** | ~{vfov_per_image:.1f}° (estimated) |
"""

    if "NAVCAM" in camera:
        content += f"""| **Tile Combining** | Yes (01+04, 16px overlap) |
| **Native Sensor** | 5120 x 3840 (20 MP) |
| **Focal Length** | 19.1 mm, f/12 |
| **Empirical f (pixels)** | 1468 px |
"""
    elif "MCZ" in camera:
        content += f"""| **Tile Combining** | No (single frame) |
| **Native Sensor** | 1648 x 1200 |
| **Focal Length** | 26-110 mm (zoom) |
| **Zoom Used** | Wide (26 mm) based on FOV |
"""

    content += f"""
---

## Photogrammetry Reference

These parameters are needed for photogrammetric reconstruction of the terrain.

| Property | Value |
|----------|-------|
| **Number of Viewpoints** | {n_images} |
| **Baseline Between Views** | ~{avg_gap:.1f}° azimuth ({avg_gap * 0.017:.3f} rad) |
| **Stereo Pair Available** | {'Yes (Left+Right NavCam)' if 'NAVCAM' in camera else 'Single camera only'} |
| **Depth Estimation Potential** | {'Good — multiple overlapping views' if overlap_per_pair > 5 else 'Limited — minimal overlap'} |
| **Recommended Software** | Meshroom, COLMAP, OpenMVS |
| **Notes** | Images sorted by azimuth. Adjacent images have ~{overlap_per_pair:.0f}° overlap. |

### Rover Position (for scene reconstruction)

The rover is at the center of the panorama. All azimuth/elevation values are
relative to the rover's mast coordinate system.

- **Mast height**: ~2.2m above ground (Perseverance)
- **Azimuth 0°**: Rover forward direction
- **Elevation 0°**: Horizontal plane
- **Negative elevation**: Below horizon (ground)

---

## Timing Breakdown

| Step | Time |
|------|------|
"""
    for step, t in timings.items():
        content += f"| {step} | {t:.1f}s |\n"
    content += f"| **Total** | **{total_time:.0f}s** |\n"

    content += f"""
---

## Image List

| # | Azimuth | Elevation | Filename |
|---|---------|-----------|----------|
"""
    for i, fname, az, el in image_details:
        content += f"| {i} | {az:.1f}° | {el:.1f}° | {fname} |\n"

    content += f"""
---

## Pipeline Parameters

```
Camera FOV: {fov:.2f}°
Image size: {img_w} x {img_h}
Blender: {blender}
Projection: equirectangular (f2)
Photometric optimization: disabled (geometry only)
CLAHE: clipLimit=2.0, tileGrid=16x16
Vignette correction: 0.35 strength
```
"""

    with open(md_path, 'w') as f:
        f.write(content)

    print(f"  Metadata: {md_path}")
    return md_path