#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Georeference HoliCity (London) LAS tiles into a real-world projected CRS.

Role in the pipeline:
    HoliCity point clouds are sampled (via CloudCompare) from FBX meshes in a
    local coordinate frame with no spatial reference. This script geo-registers
    the four 500x500 m tiles (NW/NE/SW/SE) of a HoliCity block onto the London
    map so they line up with satellite imagery before tiling.

Method:
    - The WGS84 latitude/longitude of the NW tile's top-left (north-west) corner
      is known and hard-coded below (NW_LAT/NW_LON; west longitude is negative).
    - That anchor is projected from WGS84 (EPSG:4326) into the target projected
      CRS (default EPSG:27700, OSGB36 / British National Grid).
    - The remaining tiles are placed by a fixed 500 m east/south offset.
    - For each tile, the local top-left corner (minX, maxY) is read from the LAS
      header bounding box, and a planar XY translation is computed to move that
      corner onto its target projected coordinate.

Inputs:
    The four LAS files listed in INPUT_FILES, located in the current directory.
Outputs:
    For each input, a translated copy named *_georef.las with the target EPSG
    written into its header.

External tools: laspy (LAS I/O), pyproj (CRS transform), numpy.
"""

import os
from pathlib import Path
import laspy
import numpy as np
from pyproj import Transformer

# ==== Parameters to confirm / adjust ====
# Known WGS84 lat/lon of the NW tile's top-left (north-west) corner
NW_LAT = 51.512499
NW_LON = -0.099173  # WGS84 longitude; west of Greenwich is negative

# Real-world size of a single tile (meters)
TILE_SIZE_M = 500.0

# Target projected CRS (British National Grid recommended for London)
TARGET_EPSG = 27700  # OSGB36 / British National Grid
SOURCE_CRS = "EPSG:4326"  # NW_LAT/NW_LON are given in WGS84

# The 4 files to process (filenames must distinguish the direction)
INPUT_FILES = [
    "TQ3280_NW.las",
    "TQ3280NE.las",
    "TQ3280SW.las",
    "TQ3280SE.las",
]
# Output filename suffix
OUT_SUFFIX = "_georef.las"

# =================================

def read_bbox(path: Path):
    with laspy.open(str(path)) as f:
        hdr = f.header
        mins = np.array(getattr(hdr, "mins", getattr(hdr, "min", (0,0,0))), dtype=float)
        maxs = np.array(getattr(hdr, "maxs", getattr(hdr, "max", (0,0,0))), dtype=float)
        scales = np.array(hdr.scales)
        offsets = np.array(hdr.offsets)
    return mins, maxs, scales, offsets

def apply_translation(in_path: Path, out_path: Path, tx: float, ty: float, target_epsg: int):
    las = laspy.read(str(in_path))
    # Translate (X/Y only; if a Z datum correction is needed, add a Z offset here)
    las.x = las.x + tx
    las.y = las.y + ty

    # Write the EPSG (laspy 2.x: header.epsg)
    try:
        las.header.epsg = int(target_epsg)
    except Exception:
        # Some versions may require writing via a VLR; keep the simplest setting here
        pass

    # Optional: tag generation metadata
    try:
        las.header.system_identifier = "GeorefByScript"
        las.header.generating_software = "laspy_pyproj_georef"
    except Exception:
        pass

    las.write(str(out_path))

def main():
    root = Path(".").resolve()
    # 1) Project the NW top-left corner (WGS84) into target CRS coords (easting, northing)
    transformer = Transformer.from_crs(SOURCE_CRS, f"EPSG:{TARGET_EPSG}", always_xy=True)
    # always_xy=True => input order is longitude, latitude (lon, lat)
    nw_e, nw_n = transformer.transform(NW_LON, NW_LAT)

    # 2) Build the target "top-left" coords for the four directions (top-left = north-west)
    # NE: +500m east of NW
    # SW: +500m south of NW
    # SE: +500m east and +500m south of NW
    targets = {
        "NW": (nw_e,               nw_n),
        "NE": (nw_e + TILE_SIZE_M, nw_n),
        "SW": (nw_e,               nw_n - TILE_SIZE_M),
        "SE": (nw_e + TILE_SIZE_M, nw_n - TILE_SIZE_M),
    }

    # 3) Per file: compute translation from local top-left (minX, maxY) to target top-left
    for fname in INPUT_FILES:
        in_path = root / fname
        if not in_path.exists():
            print(f"[SKIP] File not found: {in_path}")
            continue

        # Determine the direction from the filename
        up = fname.upper()
        if "NW" in up and "TQ3280NW" in up:
            key = "NW"
        elif "NE" in up:
            key = "NE"
        elif "SW" in up:
            key = "SW"
        elif "SE" in up:
            key = "SE"
        elif "NW" in up:
            # Case where the name contains _NW
            key = "NW"
        else:
            print(f"[WARN] Cannot infer direction from filename; treating as NW: {fname}")
            key = "NW"

        tgt_e, tgt_n = targets[key]

        # Read the local bbox
        mins, maxs, scales, offsets = read_bbox(in_path)
        minX, minY = float(mins[0]), float(mins[1])
        maxX, maxY = float(maxs[0]), float(maxs[1])

        # Local top-left corner (north-west) = (minX, maxY)
        local_left_top = np.array([minX, maxY], dtype=float)
        target_left_top = np.array([tgt_e, tgt_n], dtype=float)

        # Translation t = target - local
        t = target_left_top - local_left_top
        tx, ty = float(t[0]), float(t[1])

        # Print diagnostic info
        print(f"\n=== {fname} ===")
        print(f"Local bbox X:[{minX:.3f}, {maxX:.3f}]  Y:[{minY:.3f}, {maxY:.3f}]")
        print(f"Local top-left (NW local) = ({local_left_top[0]:.3f}, {local_left_top[1]:.3f})")
        print(f"Target top-left (NW target EPSG:{TARGET_EPSG}) = ({target_left_top[0]:.3f}, {target_left_top[1]:.3f})")
        print(f"Translation (tx, ty) = ({tx:.3f}, {ty:.3f})  [units: meters, projected coords]")

        out_path = in_path.with_name(in_path.stem + OUT_SUFFIX)
        apply_translation(in_path, out_path, tx, ty, TARGET_EPSG)
        print(f"Written: {out_path.name} (EPSG:{TARGET_EPSG} set)")

    print("\nDone. Load *_georef.las into QGIS and set the project CRS to EPSG:%d (or enable on-the-fly reprojection)." % TARGET_EPSG)

if __name__ == "__main__":
    main()