momepy.node_density¶

momepy.node_density(graph, radius, length='mm_len', distance=None, verbose=True)[source]¶

Calculate the density of a nodes on the street network defined in graph.

Density is calculated for subgraph around each node if radius is set, or for whole graph, if radius=None. A subgraph is generated around each node within set radius. If distance=None, radius will define topological distance, otherwise it uses values in distance attribute.

Calculated as the number of neighbouring nodes / cumulative length of street network (or a subgraph). Returns two values - an unweighted and weighted density unweighted is calculated based on the number of neigbhouring nodes, whereas weighted density will take into account node degree as k-1.

Adapted from [Dibble et al., 2017].

Calculates connectivity gamma index

Parameters:¶

graph : networkx.Graph¶

A Graph representing a street network. Ideally generated from GeoDataFrame using momepy.gdf_to_nx().

radius : int | None, optional¶

Include all neighbors of distance <= radius from n. If None, calculate the metrics for the entire graph.

length='mm_len'¶

The name of the attribute of segment length (geographical).

distance : str, optional¶

Use specified edge data key as distance. For example, setting distance=’weight’ will use the edge weight to measure the distance from the node n during ego_graph generation.

verbose : bool (default True)¶

If True, shows progress bars in loops and indication of steps.

Returns:¶

• netx (Graph) – A networkx.Graph object if radius is set.

• (unweighted, wieghted) (tuple) – A tuple of floats if radius is None.

Examples

>>> network_graph = mm.node_density(network_graph, radius=5)