标签:led show put weight UNC double fir net cti
pip install python-louvain
import community
#first compute the best partition partition = community.best_partition(G)
#Drawing partition
Method 1:
#drawing size = float(len(set(partition.values()))) pos = nx.spring_layout(G) count = 0. for com in set(partition.values()) : count = count + 1. list_nodes = [nodes for nodes in partition.keys() if partition[nodes] == com] nx.draw_networkx_nodes(G, pos, list_nodes, node_size = 20, node_color = str(count / size)) nx.draw_networkx_edges(G, pos, alpha=0.5) plt.show()
Method 2:
pos = nx.spring_layout(G) values = [partition.get(node) for node in G.nodes()] nx.draw_networkx(G, pos, cmap=plt.get_cmap(‘magma‘), node_color=values, node_size=50, with_labels=False)
Supplementary knowledge:
1. what is the partition of graphs.
partition: dict; {key (nodes_id): values(community_id)}
2. function : community.best_partition(G)
Returns ------- partition : dictionnary The partition, with communities numbered from 0 to number of communities
def best_partition(graph, partition=None, weight=‘weight‘, resolution=1., randomize=None, random_state=None): """Compute the partition of the graph nodes which maximises the modularity (or try..) using the Louvain heuristices This is the partition of highest modularity, i.e. the highest partition of the dendrogram generated by the Louvain algorithm. Parameters ---------- graph : networkx.Graph the networkx graph which is decomposed partition : dict, optional the algorithm will start using this partition of the nodes. It‘s a dictionary where keys are their nodes and values the communities weight : str, optional the key in graph to use as weight. Default to ‘weight‘ resolution : double, optional Will change the size of the communities, default to 1. represents the time described in "Laplacian Dynamics and Multiscale Modular Structure in Networks", R. Lambiotte, J.-C. Delvenne, M. Barahona randomize : boolean, optional Will randomize the node evaluation order and the community evaluation order to get different partitions at each call random_state : int, RandomState instance or None, optional (default=None) If int, random_state is the seed used by the random number generator; If RandomState instance, random_state is the random number generator; If None, the random number generator is the RandomState instance used by `np.random`. Returns ------- partition : dictionnary The partition, with communities numbered from 0 to number of communities
COMMUNITY DETECTION_python-louvain
标签:led show put weight UNC double fir net cti
原文地址:https://www.cnblogs.com/dulun/p/12219254.html