"""Terrain export for games: freeze a square of the map, exactly as the viewer shows it, into engine-neutral files. Generated terrain.""" from __future__ import annotations import json import math import multiprocessing import os import shutil import tempfile from datetime import date from pathlib import Path import numpy as np from PIL import Image from scipy.ndimage import map_coordinates import worldgen_path # noqa: F401 (mapgen on sys.path) import refine import rivers as RV import serve import tiles as T from mapgen import render as RN from mapgen.sphere import latlon_to_xyz FORMAT_VERSION = 1 WATER = ["land", "sea", "lake", "river"] def samples_for(size_km: float, res_m: float) -> int: """The smallest 2^n + 1 covering size_km at res_m (Unity, Godot Terrain3D and most tools take these sizes).""" need = size_km * 1000.0 / res_m + 1 n = 1 while 2 ** n + 1 < need: n += 1 return 2 ** n + 1 def grid_latlon(lat0, lon0, n, res_m, radius_km, rows=None): """Latitude/longitude of the n × n samples (or of rows a:b): azimuthal equidistant about (lat0, lon0), x east, y north, row 0 north.""" c = (n - 1) / 2 x = (np.arange(n) - c) * res_m r = np.arange(n) if rows is None else np.arange(*rows) y = (c - r) * res_m X, Y = np.meshgrid(x, y) d = np.hypot(X, Y) / (radius_km * 1000.0) # angular distance from the centre b = np.arctan2(X, Y) # bearing la0, lo0 = math.radians(lat0), math.radians(lon0) la = np.arcsin(np.sin(la0) * np.cos(d) + np.cos(la0) * np.sin(d) * np.cos(b)) lo = lo0 + np.arctan2(np.sin(b) * np.sin(d) * np.cos(la0), np.cos(d) - np.sin(la0) * np.sin(la)) return np.degrees(la), (np.degrees(lo) + 180.0) % 360.0 - 180.0 def to_local(lat0, lon0, lat, lon, radius_km): """Local x east, y north (m) of points (the inverse of grid_latlon).""" la0, lo0 = math.radians(lat0), math.radians(lon0) la, lo = np.radians(lat), np.radians(lon) cd = np.clip(np.sin(la0) * np.sin(la) + np.cos(la0) * np.cos(la) * np.cos(lo - lo0), -1, 1) d = np.arccos(cd) b = np.arctan2(np.sin(lo - lo0) * np.cos(la), np.cos(la0) * np.sin(la) - np.sin(la0) * np.cos(la) * np.cos(lo - lo0)) r = d * radius_km * 1000.0 return r * np.sin(b), r * np.cos(b) _SRC = None # the tile source (forked workers inherit it) def _tile(args): return tile_data(_SRC, *args) def tile_data(src, z, x, y) -> dict: """One tile's export layers (256 × 256): heights, water classes, biome, ground, landform, unshaded colours.""" f = src.fields(z, x, y, 1, ("z", "water", "cat")) c = lambda a: np.asarray(a)[1:-1, 1:-1] lake, river = c(f["lake"]).astype(bool), c(f["river"]).astype(bool) flat = np.ones(lake.shape) # unshaded colours: the export shades its own grid rgb = RN.relief_rgb(c(f["z"]), flat, c(f["holdridge"]), c(f["ground"]), c(f["ice"]), lake | c(f["river_draw"]), ~c(f["water"])) water = np.where(c(f["water"]), 1, np.where(lake, 2, np.where(river, 3, 0))).astype(np.uint8) return {"z": c(f["z"]).astype(np.float32), "water": water, "biome": c(f["holdridge"]).astype(np.uint8), "ground": c(f["ground"]).astype(np.uint8), "landform": c(f["landform"]).astype(np.uint8), "rgb": np.asarray(rgb, dtype=np.uint8)} def _rivers(src, rs, lat0, lon0, half_m, res_m): """River centrelines inside the square (local metres), world rivers where the world shows, refined ones inside.""" R = src.R centre = latlon_to_xyz(lat0, lon0).reshape(3) radius = half_m * math.sqrt(2) / 1000.0 nets = [(src.river_net, False)] + ([(rs.net, True)] if not rs.empty and rs.net is not None else []) out = [] for net, refined in nets: if net.tree is None: continue for s in net.candidates(centre, radius): p, _ = net.segment_points(s, centre, radius, res_m / 1000.0) if not len(p): continue lat = np.degrees(np.arcsin(np.clip(p[:, 2], -1, 1))) lon = np.degrees(np.arctan2(p[:, 1], p[:, 0])) x, y = to_local(lat0, lon0, lat, lon, R) keep = (np.abs(x) <= half_m) & (np.abs(y) <= half_m) if not rs.empty: w = rs.weight(p) keep &= (w >= 0.5) if refined else (w < 0.5) runs = np.split(np.arange(len(p)), np.where(~keep)[0]) q = (net.half_w[s] / 0.004) ** 2 / 31.7 # back from the hydraulic width (rivers.half_width_km) for run in runs: run = run[keep[run]] if len(run) >= 2: out.append({"points": [[round(float(a), 1), round(float(b), 1)] for a, b in zip(x[run], y[run])], "width_m": round(float(2000.0 * net.half_w[s]), 1), "discharge_km3_yr": round(float(q), 3), "refined": refined}) out.sort(key=lambda r: (r["points"][0], r["width_m"])) return out def _hillshade(h, res_m, exag): gy, gx = np.gradient(np.asarray(h, dtype=np.float32), np.float32(res_m)) dzdx, dzdn = gx * exag, -gy * exag # rows run north → south a, b = np.radians(315.0), np.radians(45.0) L = (np.sin(a) * np.cos(b), np.cos(a) * np.cos(b), np.sin(b)) return np.clip((-dzdx * L[0] - dzdn * L[1] + L[2]) / np.sqrt(dzdx ** 2 + dzdn ** 2 + 1.0), 0.0, 1.0) def _hillshade_exaggeration(h, res_m): """Vertical exaggeration for the preview: gentle land steepened until its steeper slopes read (≤ 50×).""" step = max(1, h.shape[0] // 1024) # a sample of the slopes is enough hh = np.asarray(h[::step, ::step], dtype=np.float64) gy, gx = np.gradient(hh, res_m * step) p95 = float(np.percentile(np.hypot(gx, gy), 95)) return float(np.clip(0.35 / max(p95, 1e-6), 1.0, 50.0)) MAX_TILES = 1600 # ≈ an 80 km square at 10 m near the equator (≈ 1 GB of tile data): more is refused POLE_LIMIT_DEG = 85.0 # squares reaching closer to a pole are refused (tiles narrow toward the poles) def plan(lat, lon, size_km, res_m, radius_km, pixels=None) -> dict: """Samples, tile zoom and the tile rectangle an export needs (ValueError near a pole).""" n = int(pixels) if pixels else samples_for(size_km, res_m) half = (n - 1) / 2 * res_m reach = math.degrees(half * math.sqrt(2) / (radius_km * 1000.0)) if abs(lat) + reach > POLE_LIMIT_DEG: raise ValueError(f"the square reaches within {90 - POLE_LIMIT_DEG:g}° of a pole: move it or make it smaller") # the tile zoom whose pixels are at least as fine as res_m (north-south; east-west pixels are finer still) z = int(min(T.MAX_Z, max(5, math.ceil(math.log2(math.pi * radius_km * 1000.0 / (T.TILE * res_m)))))) span = 180.0 / 2 ** z edge = np.r_[0, n - 1] # the square's extremes lie on its edges la1, lo1 = grid_latlon(lat, lon, n, res_m, radius_km, rows=(0, 1)) la2, lo2 = grid_latlon(lat, lon, n, res_m, radius_km, rows=(n - 1, n)) la3, lo3 = (np.concatenate(v) for v in zip(*(grid_latlon(lat, lon, n, res_m, radius_km, rows=(k, k + 1)) for k in range(0, n, max(1, (n - 1) // 64))))) la = np.concatenate([la1.ravel(), la2.ravel(), la3[:, edge].ravel()]) lo = np.concatenate([lo1.ravel(), lo2.ravel(), lo3[:, edge].ravel()]) lonu = lon + ((lo - lon + 180.0) % 360.0 - 180.0) fx, fy = (lonu + 180.0) / span, (90.0 - la) / span x0, x1 = int(math.floor(fx.min())) - 1, int(math.floor(fx.max())) + 1 y0, y1 = max(0, int(math.floor(fy.min())) - 1), min(2 ** z - 1, int(math.floor(fy.max())) + 1) return {"n": n, "z": z, "span": span, "x0": x0, "x1": x1, "y0": y0, "y1": y1, "tiles": (x1 - x0 + 1) * (y1 - y0 + 1)} def _parallel(jobs, fn, threads, put, stop): """fn(job) on daemon threads (never delaying the server's exit), put(job, result) in turn; the first error wins.""" import threading it, lock, err = iter(jobs), threading.Lock(), [] def run(): while not err: with lock: job = next(it, None) if job is None: return try: r = fn(job) with lock: put(job, r) stop() except BaseException as e: # noqa: BLE001 — re-raised below err.append(e) ts = [threading.Thread(target=run, daemon=True) for _ in range(max(1, threads))] for t in ts: t.start() for t in ts: t.join() if err: raise err[0] def export(root: Path, res: int, lat: float, lon: float, size_km: float = 40.0, res_m: float = 10.0, out_dir: Path | None = None, name: str | None = None, pixels: int | None = None, pins_path: Path | None = None, regions_dir: Path | None = None, workers: int = 0, progress=None, src=None, max_tiles: int = MAX_TILES, era: str | None = None) -> Path: """Write the export folder and return it. progress(done, total) per tile. src: a running server's tile source (its world, regions and render workers are used; nothing is loaded again). RuntimeError if the refined regions change meanwhile (the export would mix two maps). era: a built era (default: [eras] default, else the base); a server's src already is its chosen era's.""" global _SRC from mapgen import config as C root = Path(root) cfg = C.load(root)[0] out_dir = Path(out_dir or (root / "exports")) name = name or default_name(lat, lon, size_km, res_m) dest = out_dir / name if dest.exists(): raise FileExistsError(f"export {dest} exists: pick another name or remove it") own = src is None if own: import refine built = [n for n, _ in refine.world_dirs(root, res, log=lambda m: None)] if ( root / "out" / f"r{res}" / "cells.npz").exists() else ["base"] default = (C.load(root)[1].get("eras") or {}).get("default") name_era = era or (default if default in built else built[0]) if name_era not in built: raise SystemExit(f"no built era {name_era!r} at res {res} (have: {built})") world = dict(serve.load_worlds(root, res, log=lambda m: None, only=name_era))[name_era] src = T.TileSource(world, int(cfg["build"]["seed"]), cache_dir=Path(tempfile.mkdtemp(prefix="export-tiles-")), regions_dir=regions_dir or (root / "out" / f"r{res}" / "regions")) try: return _export(src, own, root, res, lat, lon, size_km, res_m, out_dir, name, dest, pixels, pins_path, workers, progress, max_tiles, cfg) finally: if own: shutil.rmtree(src.cache_root, ignore_errors=True) def _export(src, own, root, res, lat, lon, size_km, res_m, out_dir, name, dest, pixels, pins_path, workers, progress, max_tiles, cfg): global _SRC world, R = src.w, src.R P = plan(lat, lon, size_km, res_m, R, pixels) if P["tiles"] > max_tiles: raise ValueError(f"{P['tiles']} tiles is too many (≤ {max_tiles}): a coarser resolution or a smaller square") n, z, x0, x1, y0, y1 = P["n"], P["z"], P["x0"], P["x1"], P["y0"], P["y1"] half = (n - 1) / 2 * res_m rs = src.regions # one region set for the whole export changed = lambda: src.regions is not rs W, H = (x1 - x0 + 1), (y1 - y0 + 1) jobs = [(z, xx % 2 ** (z + 1), yy) for yy in range(y0, y1 + 1) for xx in range(x0, x1 + 1)] mosaic = {"z": np.zeros((H * T.TILE, W * T.TILE), np.float32), "rgb": np.zeros((H * T.TILE, W * T.TILE, 3), np.uint8), **{k: np.zeros((H * T.TILE, W * T.TILE), np.uint8) for k in ("water", "biome", "ground", "landform")}} done = [0] def put(job, part): zz, xx, yy = job r, c = (yy - y0) * T.TILE, ((xx - x0) % 2 ** (z + 1)) * T.TILE for k, v in part.items(): mosaic[k][r:r + T.TILE, c:c + T.TILE] = v done[0] += 1 if progress: progress(done[0], len(jobs)) def check(): if changed(): raise RuntimeError("the refined regions changed during the export (a region build finished): export again") src.tree() src.river_net src.raster("elevation") src.regions.warm() # region search trees too: forked workers share them if not own: # a server: several render workers at once pool = src.pool _parallel(jobs, lambda j: src.export_tile(*j), max(1, min(4, pool.alive // 2)) if pool else 1, put, check) elif workers and workers > 0: _SRC = src with multiprocessing.get_context("fork").Pool(workers) as mp: for job, part in zip(jobs, mp.imap(_tile, jobs, chunksize=1)): put(job, part) else: for job in jobs: put(job, tile_data(src, *job)) check() # sample the square in row blocks (memory: the mosaic and the outputs, not n² float64 grids) span = P["span"] h = np.empty((n, n), np.float32) cls = {k: np.empty((n, n), np.uint8) for k in ("water", "biome", "ground", "landform")} rgb = np.empty((n, n, 3), np.uint8) for r0 in range(0, n, 256): r1 = min(n, r0 + 256) la, lo = grid_latlon(lat, lon, n, res_m, R, rows=(r0, r1)) lonu = lon + ((lo - lon + 180.0) % 360.0 - 180.0) pr = ((90.0 - la) / span - y0) * T.TILE - 0.5 # mosaic pixel positions (pixel centres) pc = ((lonu + 180.0) / span - x0) * T.TILE - 0.5 h[r0:r1] = map_coordinates(mosaic["z"], [pr, pc], order=1, mode="nearest") ri = np.clip(np.rint(pr).astype(np.int32), 0, H * T.TILE - 1) ci = np.clip(np.rint(pc).astype(np.int32), 0, W * T.TILE - 1) for k in cls: cls[k][r0:r1] = mosaic[k][ri, ci] rgb[r0:r1] = mosaic["rgb"][ri, ci] del mosaic out_dir.mkdir(parents=True, exist_ok=True) tmp = Path(tempfile.mkdtemp(prefix=f".{name}-", dir=out_dir)) # same file system: the final rename is atomic try: h.astype(" str: """e.g. s13.400-w30.400-40km-10m""" return f"{'n' if lat >= 0 else 's'}{abs(lat):.3f}-{'e' if lon >= 0 else 'w'}{abs(lon):.3f}-{size_km:g}km-{res_m:g}m" README = """Terrain export "{name}" (format {version}) Square of {size_km:g} km around {center[lat]}, {center[lon]}: {samples} x {samples} samples every {res_m:g} m. Row 0 is the north edge, samples lie on the edges (vertex grid); x east, y north from the centre sample (azimuthal equidistant on a sphere of {projection[sphere_radius_km]:g} km). height.f32 float32 little-endian metres (ground, lake and river surfaces; sea floor below 0 m; sea level 0 m) height.png 16-bit grayscale, height.r16 16-bit little-endian raw: h = {lo:.2f} + v / 65535 * ({hi:.2f} - {lo:.2f}) m water.png 0 land, 1 sea, 2 lake, 3 river channel biome.png, ground.png, landform.png class indices, names in legend.json preview.png the map's relief colours with hillshade rivers.json river centrelines [{{points: [[x, y], ...] m, width_m, discharge_km3_yr, refined}}] pins.json map pins in the square (x, y in m) meta.json all of the above, sources and versions; the era, water depth, vents in the square (x, y m; types in the viewer legend) and the centre's gravity / O₂ / air pressure / fire reactivity Import hints: Unity: Terrain > Import Raw, height.r16, {samples} x {samples}, 16 bit, byte order Windows (little), terrain size {size_m:g} x {size_m:g} m, height = max - min ({hi:.2f} - {lo:.2f}), and the terrain's Y position = min ({lo:.2f}) so heights come out in metres (sea level at Y = 0). Godot (Terrain3D / HTerrain): height.png or height.f32 (heights in metres). Unreal: height.png (resample to a landscape size such as 4033 or 8129 if asked). Own engines: height.f32 is a plain row-major grid (x east, row 0 north); subtract center_height_m (meta.json) to put the centre at 0 m. Generated terrain. """