Add new GIS example: Solar Adoption model

[ShreyasN707]

This PR adds a new Solar Adoption example to the gis/ directory to demonstrate how raster data and vector agents can be used together with mesa-geo.

The model simulates how households decide to adopt solar panels based on two geographic factors:

• Economic viability (raster data): Each household is linked to a solar radiation value from a RasterLayer. Locations with higher radiation make adoption more likely.

• Social influence (vector neighbors): Households are influenced by nearby households. Agents use GeoSpace.get_neighbors_within_distance() to calculate local adoption and model peer effects.

What this example demonstrates

• Using GeoSpace to manage spatial relationships between agents

• Loading environmental data with RasterLayer.from_file()

• Creating agents from GeoJSON using AgentCreator

• Visualizing the simulation with a Solara dashboard using make_geospace_component, where households change color as they adopt solar

Implementation notes

A data/generate_data.py script generates synthetic households.geojson and solar_radiation.tif files so the example can run without external datasets.

The code follows the standard Mesa example structure and uses the built-in random generator.

The example runs successfully with the existing test_gis_examples.py test suite.