momepy.subgraph(graph, radius=5, distance=None, meshedness=True, cds_length=True, mode='sum', degree='degree', length='mm_len', mean_node_degree=True, proportion={0: True, 3: True, 4: True}, cyclomatic=True, edge_node_ratio=True, gamma=True, local_closeness=True, closeness_weight=None, verbose=True)[source]#

Calculates all subgraph-based characters.

Generating subgraph might be a time consuming activity. If we want to use the same subgraph for more characters, subgraph allows this by generating subgraph and then analysing it using selected options.


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

radius: int

radius defining the extent of subgraph

distancestr, 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.

meshednessbool, default True

Calculate meshedness (True/False)

cds_lengthbool, default True

Calculate cul-de-sac length (True/False)

modestr (defualt ‘sum’)

if 'sum', calculate total cds_length, if 'mean' calculate mean cds_length


name of attribute of node degree (momepy.node_degree())

lengthstr, default mm_len

name of attribute of segment length (geographical)

mean_node_degreebool, default True

Calculate mean node degree (True/False)

proportiondict, default {3: True, 4: True, 0: True}

Calculate proportion {3: True/False, 4: True/False, 0: True/False}

cyclomaticbool, default True

Calculate cyclomatic complexity (True/False)

edge_node_ratiobool, default True

Calculate edge node ratio (True/False)

gammabool, default True

Calculate gamma index (True/False)

local_closenessbool, default True

Calculate local closeness centrality (True/False)

closeness_weightstr, optional

Use the specified edge attribute as the edge distance in shortest path calculations in closeness centrality algorithm

verbosebool (default True)

if True, shows progress bars in loops and indication of steps




>>> network_graph = mm.subgraph(network_graph)