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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
29 lines
2.0 KiB
Python
29 lines
2.0 KiB
Python
#!/usr/bin/env python3
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"""GFS 1.0 deg 10 m wind U/V from NOAA's AWS Open Data bucket (noaa-gfs-bdp-pds) via .idx byte
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ranges, same approach as server/providers/wind/gfs.js; decoded with python `eccodes` (pip).
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Usage: python fetch_wind.py <gfs file base url (no .idx)> <out wind.json>"""
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import json, sys, requests, numpy as np, eccodes
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base, out = sys.argv[1], sys.argv[2]
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lines = [l.split(':') for l in requests.get(base + '.idx', timeout=60).text.strip().split('\n')]
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def field(var):
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i = next(k for k, p in enumerate(lines) if p[3] == var and p[4] == '10 m above ground')
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s, e = int(lines[i][1]), int(lines[i + 1][1]) - 1
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b = requests.get(base, headers={'Range': f'bytes={s}-{e}'}, timeout=120).content
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h = eccodes.codes_new_from_message(b)
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g = {k: eccodes.codes_get(h, k) for k in ['Ni', 'Nj', 'dataDate', 'dataTime', 'step']}
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g.update({k: eccodes.codes_get_double(h, k) for k in ['longitudeOfFirstGridPointInDegrees', 'latitudeOfFirstGridPointInDegrees', 'iDirectionIncrementInDegrees', 'jDirectionIncrementInDegrees']})
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g['values'] = eccodes.codes_get_values(h).reshape(g['Nj'], g['Ni'])
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eccodes.codes_release(h)
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return g
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U, V = field('UGRD'), field('VGRD')
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assert U['longitudeOfFirstGridPointInDegrees'] == 0 and U['latitudeOfFirstGridPointInDegrees'] == 90
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dx = U['iDirectionIncrementInDegrees']; shift = int(round(180 / dx))
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u = np.roll(U['values'], -shift, axis=1); v = np.roll(V['values'], -shift, axis=1) # lon 0..359 -> -180..179
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ny, nx = u.shape
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json.dump({'source': 'NOAA GFS 1.0deg ' + base.split('/')[-1], 'refTime': f"{U['dataDate']} {U['dataTime']:04d}Z", 'forecastHour': U['step'],
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'level': '10 m above ground', 'units': 'm/s', 'nx': nx, 'ny': ny, 'lo1': -180, 'la1': 90, 'dx': dx, 'dy': U['jDirectionIncrementInDegrees'],
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'u': [round(float(x), 2) for x in u.ravel()], 'v': [round(float(x), 2) for x in v.ravel()]},
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open(out, 'w'), separators=(',', ':'))
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sp = np.hypot(u, v)
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print(nx, ny, 'max', sp.max().round(1), 'mean', sp.mean().round(2), U['dataDate'], U['dataTime'], 'f', U['step'])
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