jpmschweitzerandClaude Opus 4.6
d364e1907d
Ruff pre-push lint caught 17 unused imports across 7 files. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
190 lines
7.8 KiB
Python
190 lines
7.8 KiB
Python
"""
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Mars (GJ0e) terrain builder.
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Data source:
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- Elevation: MOLA MEGDR (Mars Orbiter Laser Altimeter)
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PDS format, big-endian int16, metres relative to areoid.
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Available at multiple resolutions. We use 4ppd (1440×720)
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or 16ppd (5760×2880) — both small enough to download quickly.
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Mars properties:
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- Min elevation: ~-8200 m (Hellas Basin)
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- Max elevation: ~21229 m (Olympus Mons)
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- Polar ice caps: CO2 + water ice
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- Thin atmosphere (6 mbar) — classified as "thin" in body_def
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- Almost no liquid water (hydrosphere: "ice")
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"""
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import numpy as np
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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_raw_binary, 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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# MOLA MEGDR — 4 pixels per degree (1440 × 720), big-endian int16
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# Each pixel = metres relative to Mars areoid
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# PDS binary with no header (data starts at byte 0 for .img files)
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MOLA_4PPD_URL = "https://pds-geosciences.wustl.edu/mgs/mgs-m-mola-5-megdr-l3-v1/mgsl_300x/meg004/megt90n000cb.img"
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MOLA_4PPD_FILE = "mola_megdr_4ppd.img"
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MOLA_4PPD_W = 1440
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MOLA_4PPD_H = 720
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# Alternative: 16ppd (5760 × 2880) for higher quality
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MOLA_16PPD_URL = "https://pds-geosciences.wustl.edu/mgs/mgs-m-mola-5-megdr-l3-v1/mgsl_300x/meg016/megt90n000eb.img"
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MOLA_16PPD_FILE = "mola_megdr_16ppd.img"
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MOLA_16PPD_W = 5760
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MOLA_16PPD_H = 2880
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# Mars physical constants
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MARS_MIN_ELEV_M = -8200.0 # Hellas Basin
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MARS_MAX_ELEV_M = 21229.0 # Olympus Mons summit
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# Real Mars temperatures — we don't fudge these. Mars colour comes from
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# ferric biome classes (34/35/36) applied based on iron oxide substrate.
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MARS_EQUATORIAL_TEMP_K = 215.0 # daytime average near equator
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MARS_POLAR_TEMP_K = 150.0
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MARS_OCEAN_FRACTION = 0.0 # no liquid water (ice only)
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# Ferric biome class IDs (from biomes.toml)
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FERRIC_DUST = 34
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FERRIC_HIGHLAND = 35
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FERRIC_LOWLAND = 36
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def _load_mola(use_16ppd: bool = False) -> np.ndarray:
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"""Load MOLA DEM, return elevation in metres."""
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if use_16ppd:
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url, filename, w, h = MOLA_16PPD_URL, MOLA_16PPD_FILE, MOLA_16PPD_W, MOLA_16PPD_H
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else:
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url, filename, w, h = MOLA_4PPD_URL, MOLA_4PPD_FILE, MOLA_4PPD_W, MOLA_4PPD_H
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path = ensure_cached(url, filename)
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print(f" loading MOLA: {path} ({w}x{h})")
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# MOLA MEGDR: big-endian int16, metres, no header
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arr = load_raw_binary(str(path), w, h, dtype=">i2", offset=0)
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# MOLA nodata is typically 32767 or -32768
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arr[arr > 30000] = 0.0
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arr[arr < -30000] = 0.0
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print(f" MOLA range: [{arr.min():.0f}, {arr.max():.0f}] m")
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return arr
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def build_terrain(body_def: dict) -> dict:
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"""Build Mars terrain dict from MOLA data."""
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print(" Mars: loading MOLA data...")
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# ── 1. Elevation ────────────────────────────────────────────────────
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mola_raw = _load_mola(use_16ppd=False)
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# MOLA is col 0 = 0° longitude — shift to col 0 = 180°W
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from sol_data.shared import greenwich_to_dateline
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mola_shifted = greenwich_to_dateline(mola_raw)
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# Resample to grid
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elevation_m = resample_to_grid(mola_shifted, GRID_H, GRID_W, order=1)
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# Normalise to [0, 1]
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elevation = normalize_01(elevation_m, MARS_MIN_ELEV_M, MARS_MAX_ELEV_M)
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print(f" elevation normalised")
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# ── 2. Temperature ──────────────────────────────────────────────────
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# Analytical: equatorial ~210K, polar ~150K, elevation lapse
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temperature_K = temperature_grid_analytical(
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base_T_K=MARS_EQUATORIAL_TEMP_K,
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elevation=elevation,
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lapse_rate_K_per_unit=30.0,
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lat_gradient_K=60.0,
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)
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# Polar ice caps: very cold at high latitudes
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v = np.linspace(0, 1, GRID_H, dtype=np.float32)
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lat_abs = np.abs(v - 0.5) * 2.0
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polar_rows = lat_abs > 0.75
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temperature_K[polar_rows, :] = np.minimum(temperature_K[polar_rows, :], 155.0)
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print(f" temperature: [{temperature_K.min():.0f}, {temperature_K.max():.0f}] K")
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# ── 3. Moisture ─────────────────────────────────────────────────────
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# Mars has almost no moisture — thin atmosphere
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moisture = np.zeros((GRID_H, GRID_W), dtype=np.float32)
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# Slight moisture near polar caps (water ice)
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moisture[polar_rows, :] = 0.1
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# ── 4. Terraformed water bodies ─────────────────────────────────────
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# Lore: 800 years of partial terraforming. Water pools in the deepest
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# basins (Hellas, Utopia, Isidis). ~2% of surface is now liquid water.
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from sol_data.shared import compute_sea_level as _compute_sl
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from scipy.ndimage import binary_dilation
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TERRAFORM_OCEAN_FRAC = 0.02 # 2% water coverage
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sea_level = _compute_sl(elevation, TERRAFORM_OCEAN_FRAC)
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surface_water = elevation < sea_level
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# Don't flood polar regions — those stay as ice caps, not lakes
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surface_water[polar_rows, :] = False
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n_water = int(surface_water.sum())
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print(f" terraformed water: {n_water} cells "
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f"(sea_level={sea_level:.4f})")
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# ── 5. Biome classification ─────────────────────────────────────────
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# Mars biome is built directly — compute_biome() would classify
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# everything as ice at these temperatures.
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biome = np.full((GRID_H, GRID_W), FERRIC_DUST, dtype=np.int8)
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# Elevation-based ferric variation
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biome[elevation > 0.55] = FERRIC_HIGHLAND # volcanic highlands
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biome[elevation < 0.25] = FERRIC_LOWLAND # basin floors
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# Polar ice caps
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biome[polar_rows, :] = 17 # ice/snow
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# Terraformed green fringe around water bodies — vegetation band
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# where the thicker local atmosphere and water access allow plants.
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# ~5 cell band around each water body.
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veg_ring = binary_dilation(surface_water, iterations=5) & ~surface_water
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# Don't put vegetation at poles
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veg_ring[polar_rows, :] = False
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biome[veg_ring] = 12 # shrubland (olive green — sparse terraformed vegetation)
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# Inner vegetation ring (closer to water = lusher)
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inner_ring = binary_dilation(surface_water, iterations=2) & ~surface_water
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inner_ring[polar_rows, :] = False
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biome[inner_ring] = 8 # temperate grassland (greener)
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# Ocean depth bands for water bodies
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if surface_water.any():
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depth = np.clip((sea_level - elevation) / (sea_level + 1e-9), 0, 1)
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biome[surface_water & (depth < 0.15)] = 2 # shallow
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biome[surface_water & (depth >= 0.15) & (depth < 0.50)] = 1 # mid
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biome[surface_water & (depth >= 0.50)] = 0 # deep
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n_ice = int((biome == 17).sum())
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n_ferric = int(((biome >= 34) & (biome <= 36)).sum())
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n_veg = int(((biome == 8) | (biome == 12)).sum())
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n_ocean = int(((biome >= 0) & (biome <= 2)).sum())
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print(f" biomes: {len(np.unique(biome))} classes "
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f"(ferric={n_ferric}, ice={n_ice}, veg={n_veg}, water={n_ocean})")
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# ── 5. Hillshade ────────────────────────────────────────────────────
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hillshade = compute_hillshade(elevation)
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# ── 6. Assemble ─────────────────────────────────────────────────────
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return assemble_terrain(
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elevation=elevation,
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temperature_K=temperature_K,
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moisture=moisture,
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biome=biome,
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surface_water=surface_water,
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hillshade=hillshade,
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rivers=[], # no rivers on Mars
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sea_level=sea_level,
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)
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