compactness

compactness(domain, network_name, edge_weight_name=None, population=None, include_boundaries=None, exclude_boundaries=None, boundary_exclude_distance=0)

Provides an index [0,1] of how compact the network is in terms of its area and length of edges.

The compactness of a spatial network measures how efficiently locations (nodes) within the network are connected in space. A spatial network with high compactness has short, direct connections between nodes, allowing for efficient movement or communication. This concept is commonly used in fields like transportation, urban planning, and ecology to assess how well a system facilitates interactions across its spatial structure.

Parameters:

domainobject

The domain containing the network and objects.

network_namestr

The name of the network to evaluate.

edge_weight_namestr, optional

The name of the edge weight to use, by default None.

populationarray-like or query, optional

A query or array of object indices to filter the labels. Default is None.

include_boundariesarray-like, query-like, or None, optional

Boundaries to include in the analysis. Defaults to None.

exclude_boundariesarray-like, query-like, or None, optional

Boundaries to exclude from the analysis. Defaults to None.

boundary_exclude_distancefloat, optional

Buffer to exclude objects located within boundary_exclude_distance from the boundaries. Defaults to 0.

Returns:

float

An index [0,1] indicating the compactness of the network.

Raises:

RuntimeError

If the network name is not in the list of generated networks or if there is no edge weight named edge_weight_name within the network.

Notes

See reference: Barthelemy, Marc. Spatial Networks: A Complete Introduction: From Graph Theory and Statistical Physics to Real-World Applications. Springer Nature, 2022.