jpmschweitzerandClaude Opus 4.6
18bdb1ed3d
Custom pipeline for GJ-0 (Sol) that imports real NASA/USGS planetary data instead of procedural generation. Produces the same output format (heightmap.png, globe.png, markers.json). Real data bodies: - Earth: ETOPO2022 elevation + WorldClim climate + 14 rivers - Mars: MOLA DEM + ferric biome classes + terraformed water - Luna: LOLA DEM + lunar biome palette Procedural fallback for Mercury, Venus, Phobos, Deimos. Synthetic elevation from albedo for Io, Europa, Ganymede, Callisto, Titan, Enceladus. Gas giants use existing renderer. New biome classes 34-36 (ferric_dust/highland/lowland) for Mars iron oxide surface. Earth features: 50 cities (smart scatter by continent), 15 named rivers, oceans, mountains. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
121 lines
4.8 KiB
Python
121 lines
4.8 KiB
Python
"""
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Mercury (GJ0b) terrain builder.
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Data source:
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- Elevation: MESSENGER DEM from USGS Astrogeology
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665m/px global DEM, GeoTIFF.
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Mercury properties:
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- Min elevation: ~-5380 m
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- Max elevation: ~4480 m
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- No atmosphere, no water
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- Extreme temperature range: ~100K (night) to ~700K (day)
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- body_type: "planet", planet_class: "barren", atmosphere: "none"
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"""
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import numpy as np
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from pathlib import Path
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from sol_data.download import ensure_cached
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from sol_data.shared import (
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GRID_W, GRID_H,
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load_tiff_as_array, load_raw_binary,
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resample_to_grid, normalize_01,
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compute_hillshade, assemble_terrain,
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temperature_grid_analytical,
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)
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# MESSENGER DEM — try PDS binary first (compact), fall back to USGS GeoTIFF
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MESSENGER_PDS_URL = "https://pds-geosciences.wustl.edu/messenger/mess-h-mdis_mla-6-dem-elevation-v1/messdmdem_1001/data/global_dem_16ppd.img"
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MESSENGER_PDS_FILE = "messenger_dem_16ppd.img"
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MESSENGER_PDS_W = 5760
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MESSENGER_PDS_H = 2880
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# USGS GeoTIFF fallback (~506 MB, but PIL-loadable)
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MESSENGER_TIFF_URL = "https://planetarymaps.usgs.gov/mosaic/Mercury_Messenger_USGS_DEM_Global_665m_v2.tif"
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MESSENGER_TIFF_FILE = "Mercury_Messenger_USGS_DEM_Global_665m_v2.tif"
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MERCURY_MIN_ELEV_M = -5380.0
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MERCURY_MAX_ELEV_M = 4480.0
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MERCURY_EQUATORIAL_TEMP_K = 440.0 # mean dayside
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MERCURY_POLAR_TEMP_K = 200.0
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def _load_messenger() -> np.ndarray:
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"""Load MESSENGER DEM, return elevation in metres."""
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# Try PDS binary first (compact ~33 MB)
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try:
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path = ensure_cached(MESSENGER_PDS_URL, MESSENGER_PDS_FILE)
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print(f" loading MESSENGER PDS: {path}")
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arr = load_raw_binary(str(path), MESSENGER_PDS_W, MESSENGER_PDS_H,
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dtype=">i2", offset=0)
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arr[arr > 20000] = 0.0
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arr[arr < -20000] = 0.0
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print(f" MESSENGER range: [{arr.min():.0f}, {arr.max():.0f}] m")
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return arr
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except Exception as e:
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print(f" PDS load failed ({e}), trying USGS GeoTIFF...")
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# Fallback: USGS GeoTIFF (~506 MB)
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try:
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path = ensure_cached(MESSENGER_TIFF_URL, MESSENGER_TIFF_FILE)
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print(f" loading MESSENGER GeoTIFF: {path}")
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arr = load_tiff_as_array(str(path))
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arr[arr < -20000] = 0.0
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print(f" MESSENGER shape: {arr.shape}, range: [{arr.min():.0f}, {arr.max():.0f}] m")
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return arr
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except Exception as e2:
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print(f" GeoTIFF also failed ({e2}), using procedural")
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return None
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def build_terrain(body_def: dict) -> dict:
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"""Build Mercury terrain dict from MESSENGER data."""
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import sys
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sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
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from planet_simulation import compute_biome
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print(" Mercury: loading MESSENGER data...")
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# ── 1. Elevation ────────────────────────────────────────────────────
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raw = _load_messenger()
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if raw is None:
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import sys
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sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
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from planet_simulation import simulate
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return simulate(body_def)
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from sol_data.shared import greenwich_to_dateline
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shifted = greenwich_to_dateline(raw)
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elevation_m = resample_to_grid(shifted, GRID_H, GRID_W, order=1)
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elevation = normalize_01(elevation_m, MERCURY_MIN_ELEV_M, MERCURY_MAX_ELEV_M)
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sea_level = 0.0
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surface_water = np.zeros((GRID_H, GRID_W), dtype=bool)
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# ── 2. Temperature ──────────────────────────────────────────────────
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temperature_K = temperature_grid_analytical(
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base_T_K=MERCURY_EQUATORIAL_TEMP_K,
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elevation=elevation,
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lapse_rate_K_per_unit=20.0,
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lat_gradient_K=240.0,
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)
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temperature_K = np.maximum(temperature_K, 100.0)
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# ── 3. Moisture ─────────────────────────────────────────────────────
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moisture = np.zeros((GRID_H, GRID_W), dtype=np.float32)
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# ── 4. Biome ────────────────────────────────────────────────────────
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biome = compute_biome(body_def, elevation, sea_level, surface_water,
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temperature_K, moisture)
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# ── 5. Hillshade ────────────────────────────────────────────────────
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hillshade = compute_hillshade(elevation)
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return assemble_terrain(
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elevation=elevation, temperature_K=temperature_K,
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moisture=moisture, biome=biome,
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surface_water=surface_water, hillshade=hillshade,
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rivers=[], sea_level=sea_level,
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)
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