Solar & Wind Atlas catalog explorer (offline)¶

Inspect the bundled layer catalog without touching the network: which layers ship, which atlas each comes from, and the transport used to fetch it. This is the no-network companion to the live wind quickstart.

In [ ]:

import pandas as pd

from earthlens.solar_wind_atlas import Catalog

import pandas as pd from earthlens.solar_wind_atlas import Catalog

The shipped layers¶

Catalog() loads the bundled sharded catalog/ (solar.yaml + wind.yaml). Each row is a frozen pydantic Layer carrying its atlas, transport, URL, and units.

In [ ]:

catalog = Catalog()
rows = [
    {
        "id": lid,
        "atlas": catalog.get(lid).atlas,
        "transport": catalog.get(lid).transport,
        "units": catalog.get(lid).units,
        "long_name": catalog.get(lid).long_name,
    }
    for lid in catalog.available()
]
pd.DataFrame(rows)

catalog = Catalog() rows = [ { "id": lid, "atlas": catalog.get(lid).atlas, "transport": catalog.get(lid).transport, "units": catalog.get(lid).units, "long_name": catalog.get(lid).long_name, } for lid in catalog.available() ] pd.DataFrame(rows)

Two atlases, two transports¶

• Global Wind Atlas layers (atlas='gwa') use the vsicurl transport: a windowed read straight from the remote Cloud-Optimized GeoTIFF — only the AOI transfers.
• Global Solar Atlas layers (atlas='gsa') use download_zip: the deflate ZIP archive (no random access) is downloaded once into a cache, then cropped locally.

In [ ]:

by_transport = {}
for lid in catalog.available():
    by_transport.setdefault(catalog.get(lid).transport, []).append(lid)
by_transport

by_transport = {} for lid in catalog.available(): by_transport.setdefault(catalog.get(lid).transport, []).append(lid) by_transport

Did-you-mean on an unknown id¶

An unknown layer id raises a ValueError with the closest match.

In [ ]:

raises-exception

catalog.get("gho")  # unknown id -> ValueError with a did-you-mean hint

catalog.get("gho") # unknown id -> ValueError with a did-you-mean hint