from __future__ import annotations

from dataclasses import dataclass
from pathlib import Path


@dataclass(frozen=True)
class GpsRecord:
    rel_path: str
    lon: float
    lat: float
    height: float


def parse_dense_gps_txt(path: Path) -> list[GpsRecord]:
    """
    DenseUAV формат строки (эмпирически):
        <rel_path> E<lon> N<lat> <height>
    пример:
        train/satellite/000001/H80.tif E120.387... N30.324... 94.761
    """
    records: list[GpsRecord] = []
    with path.open("r", encoding="utf-8", errors="replace") as f:
        for i, line in enumerate(f, start=1):
            line = line.strip()
            if not line:
                continue
            parts = line.split()
            if len(parts) != 4:
                raise ValueError(f"Bad GPS line {path}:{i}: expected 4 fields, got {len(parts)}: {line!r}")
            rel_path, e_lon, n_lat, height_s = parts
            if not e_lon.startswith("E") or not n_lat.startswith("N"):
                raise ValueError(f"Bad GPS line {path}:{i}: expected E.. N.. fields: {line!r}")
            lon = float(e_lon[1:])
            lat = float(n_lat[1:])
            height = float(height_s)
            records.append(GpsRecord(rel_path=rel_path, lon=lon, lat=lat, height=height))
    return records


def write_gps_csv(records: list[GpsRecord], out_csv: Path) -> None:
    out_csv.parent.mkdir(parents=True, exist_ok=True)
    with out_csv.open("w", encoding="utf-8") as f:
        f.write("rel_path,lon,lat,height\n")
        for r in records:
            f.write(f"{r.rel_path},{r.lon:.12f},{r.lat:.12f},{r.height:.6f}\n")