Slippy Map Regionalizer Example¶

In [1]:

import geopandas as gpd
from shapely import geometry

from srai.regionalizers import SlippyMapRegionalizer
from srai.plotting.folium_wrapper import plot_regions
from srai.constants import WGS84_CRS

import geopandas as gpd from shapely import geometry from srai.regionalizers import SlippyMapRegionalizer from srai.plotting.folium_wrapper import plot_regions from srai.constants import WGS84_CRS

Define starting polygons¶

In [2]:

gdf = gpd.GeoDataFrame(
    geometry=[
        geometry.Polygon(
            shell=[
                (-1, 0),
                (0, 0.5),
                (1, 0),
                (1, 1),
                (0, 1),
            ],
            holes=[
                [
                    (0.8, 0.9),
                    (0.9, 0.55),
                    (0.8, 0.3),
                    (0.5, 0.4),
                ]
            ],
        ),
        geometry.Polygon(shell=[(-0.25, 0), (0.25, 0), (0, 0.2)]),
    ],
    crs=WGS84_CRS,
)
gdf.explore()

gdf = gpd.GeoDataFrame( geometry=[ geometry.Polygon( shell=[ (-1, 0), (0, 0.5), (1, 0), (1, 1), (0, 1), ], holes=[ [ (0.8, 0.9), (0.9, 0.55), (0.8, 0.3), (0.5, 0.4), ] ], ), geometry.Polygon(shell=[(-0.25, 0), (0.25, 0), (0, 0.2)]), ], crs=WGS84_CRS, ) gdf.explore()

Out[2]:

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Define tile resolution¶

In [3]:

zoom = 12

zoom = 12

Regionalize using SlippyMapRegionalizer¶

In [4]:

regionalizer = SlippyMapRegionalizer(zoom)
gdf_slippy = regionalizer.transform(gdf)

folium_map = gdf.explore()
plot_regions(gdf_slippy, colormap=["red"], map=folium_map)

regionalizer = SlippyMapRegionalizer(zoom) gdf_slippy = regionalizer.transform(gdf) folium_map = gdf.explore() plot_regions(gdf_slippy, colormap=["red"], map=folium_map)

Out[4]:

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