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Claude
c9421a3f33
A deterministic WebGL film of God's Eye View coming online: a seed on Null Island grows into a culture that draws the planet, indexes the surface tile by tile, ingests the live feeds and outgrows its dish, ending on the logo. Renders 16:9 and 9:16 frame by frame in headless Chromium; the procedural score is locked to the same clock. Data and imagery are fetched by the scripts in tools/ and are not committed. Co-Authored-By: Claude Opus 5.5 <[email protected]> Claude-Session: https://claude.ai/code/session_01KqP857pippaUs6konSDfe8
92 lines
3.9 KiB
Python
92 lines
3.9 KiB
Python
"""Deliverable 1: earth_day.jpg (8192x4096) + earth_day_4k.jpg (4096x2048).
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Esri World Imagery z5 (32x32 tiles, 8192x8192 Web Mercator) reprojected to
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equirectangular with bilinear sampling. Because both grids are 8192 px wide and
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linear in longitude, the horizontal axis maps 1:1 and only latitude needs
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resampling (linear interpolation between Mercator rows = bilinear).
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Polar caps beyond the Mercator limit (+-85.0511 deg) come from NASA GIBS
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BlueMarble_ShadedRelief_Bathymetry (EPSG:4326, level 4 = 10240x5120; its shaded
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bathymetry matches Esri's small-scale ocean rendering), colour-matched to Esri
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with a least-squares affine colour transform fitted on co-registered overlap pixels and cross-faded between 80 and 84.5 deg.
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"""
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import os
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import numpy as np
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from PIL import Image
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from common import OUT, esri_jobs, fetch_many, decode, gibs_mosaic
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Image.MAX_IMAGE_PIXELS = None
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W, H = 8192, 4096
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Z = 5
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N = 2 ** Z
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TS = 256
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MERC = N * TS # 8192
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MERC_LIMIT = np.degrees(np.arctan(np.sinh(np.pi))) # 85.0511
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FADE_A, FADE_B = 80.0, 84.5 # pure Esri below A, pure Blue Marble above B
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CAP_LAYER = os.environ.get("CAP_LAYER", "BlueMarble_ShadedRelief_Bathymetry")
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def esri_mercator():
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coords = [(x, y) for y in range(N) for x in range(N)]
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res = fetch_many(esri_jobs(Z, coords), desc="esri z5")
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merc = np.zeros((MERC, MERC, 3), np.uint8)
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for (x, y), b in res.items():
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if b is None:
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raise SystemExit(f"missing esri tile {x},{y}")
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merc[y * TS:(y + 1) * TS, x * TS:(x + 1) * TS] = np.asarray(decode(b))
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return merc
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def main():
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merc = esri_mercator()
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print("reprojecting")
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lat = 90.0 - (np.arange(H) + 0.5) * 180.0 / H
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latc = np.clip(lat, -MERC_LIMIT + 1e-6, MERC_LIMIT - 1e-6)
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yn = (1.0 - np.log(np.tan(np.pi / 4 + np.radians(latc) / 2)) / np.pi) / 2.0
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v = yn * MERC - 0.5
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v0 = np.clip(np.floor(v).astype(int), 0, MERC - 1)
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v1 = np.clip(v0 + 1, 0, MERC - 1)
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f = np.clip(v - np.floor(v), 0, 1).astype(np.float32)[:, None, None]
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eq = np.empty((H, W, 3), np.float32)
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for s in range(0, H, 256):
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e = s + 256
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eq[s:e] = merc[v0[s:e]].astype(np.float32) * (1 - f[s:e]) + merc[v1[s:e]].astype(np.float32) * f[s:e]
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del merc
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print("fetching polar caps:", CAP_LAYER)
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bm = gibs_mosaic(CAP_LAYER, None, "500m", 4, 10, 20, "jpg")
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bm = np.asarray(bm.resize((W, H), Image.LANCZOS)).astype(np.float32)
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# colour-match Blue Marble to Esri per hemisphere: fit an affine 3x3+offset colour
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# transform (least squares) on co-registered pixels in the 76-84.5 deg overlap band
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alat = np.abs(lat)
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band = (alat > 76) & (alat < 84.5)
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t = np.clip((alat - FADE_A) / (FADE_B - FADE_A), 0, 1)
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t = (t * t * (3 - 2 * t)).astype(np.float32)[:, None, None] # smoothstep
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out = eq.copy()
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for hemi in (lat > 0, lat < 0):
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rows = band & hemi
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a = eq[rows][:, ::4].reshape(-1, 3)
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b = bm[rows][:, ::4].reshape(-1, 3)
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X = np.hstack([b, np.ones((len(b), 1), np.float32)])
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# ridge-regularised toward identity: near-grey ice makes the plain fit ill-conditioned
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lam = len(b) * 50.0
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D = np.diag([1.0, 1.0, 1.0, 0.0])
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I0 = np.vstack([np.eye(3), np.zeros((1, 3))])
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X64, a64 = X.astype(np.float64), a.astype(np.float64)
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M = np.linalg.solve(X64.T @ X64 + lam * D, X64.T @ a64 + lam * D @ I0)
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print(" colour transform\n", M.round(3))
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h = bm[hemi]
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bm[hemi] = (h.reshape(-1, 3) @ M[:3] + M[3]).reshape(h.shape)
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out[hemi] = eq[hemi] * (1 - t[hemi]) + bm[hemi] * t[hemi]
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img = Image.fromarray(np.clip(out + 0.5, 0, 255).astype(np.uint8))
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os.makedirs(OUT, exist_ok=True)
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img.save(os.path.join(OUT, "earth_day.jpg"), quality=92, optimize=True, progressive=True)
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img.resize((4096, 2048), Image.LANCZOS).save(os.path.join(OUT, "earth_day_4k.jpg"), quality=92, optimize=True, progressive=True)
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print("done")
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if __name__ == "__main__":
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main()
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