plot_region_geometry_layer

site.SiteProblem.plot_region_geometry_layer(
    interactive=False,
    plot_demand=False,
    plot_equity=False,
    cmap='Blues',
    tiles='CartoDB positron',
    plot_region_of_interest_only=False,
    edgecolor='black',
    linewidth=0.5,
    **kwargs,
)

Visualize the regional geometry layer, optionally overlaid with demand data.

This method produces either a static matplotlib plot or an interactive Folium map (via Geopandas’ .explore()). If demand plotting is enabled, it performs an internal join between geometry and demand data to create a choropleth map.

Parameters

Name Type Description Default
interactive bool If True, returns a folium.Map object using the ‘explore’ backend. If False, returns a matplotlib.axes.Axes object. False
plot_demand bool If True, merges the geometry with the demand dataset and styles the regions based on the demand column values. False
cmap Colour map to be used for plotting demand. Ignored if plot_demand=False. 'Blues'
tiles Tiles to be used for background in map. Ignored if interactive = False. 'CartoDB positron'
**kwargs dict Additional keyword arguments passed to either geopandas.GeoDataFrame.plot or geopandas.GeoDataFrame.explore. {}

Returns

Name Type Description
matplotlib.axes.Axes or folium.Map The plotting object depending on the interactive parameter.

Raises

Name Type Description
ValueError If self.region_geometry_layer has not been initialized.
ValueError If plot_demand is True but self.demand_data is None.

Notes

When plot_demand is True, the method performs a merge using: - self._region_geometry_layer_common_col (left) - self._demand_data_id_col (right)

Interactive maps default to the “CartoDB positron” tile set and the “Blues” colormap for demand visualization.

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