o ˷e @sJdZddlmZddlZddlZddlmZddlZ ddZ dddZ e dd Z e dd Ze dd d Ze eefD]XZed edee eedeZe eZedeeddededdedeZe eZedeeddededdq;ed e je ddedS)a ==================== Parallel Betweenness ==================== Example of parallel implementation of betweenness centrality using the multiprocessing module from Python Standard Library. The function betweenness centrality accepts a bunch of nodes and computes the contribution of those nodes to the betweenness centrality of the whole network. Here we divide the network in chunks of nodes and we compute their contribution to the betweenness centrality of the whole network. Note: The example output below shows that the non-parallel implementation is faster. This is a limitation of our CI/CD pipeline running on a single core. Depending on your setup, you will likely observe a speedup. )PoolNccs,t|} tt||}|sdS|Vq)z(Divide a list of nodes `l` in `n` chunksN)itertuple itertoolsislice)lnl_cxr /var/www/ideatree/venv/lib/python3.10/site-packages/../../../share/doc/networkx-2.8.6/examples/algorithms/plot_parallel_betweenness.pychunkssrc Cst|d}t|jd}tt|||}t|}|tj t |g||t|g|dg|dg|}|d}|ddD]}|D] } || || 7<qFqB|S)z)Parallel betweenness centrality function) processesTNrr) rlen_poollistrnodesorderstarmapnxbetweenness_centrality_subsetzip) Grp node_divisor node_chunks num_chunksbt_scbt_cbtr r r r betweenness_centrality_parallel%s(   r"ig{Gz?rg?z%Computing betweenness centrality for:z Parallel versionz Time: z.4Fz secondsz% Betweenness centrality for node 0: z.5fz Non-Parallel versiond) node_size)N)__doc__multiprocessingrtimermatplotlib.pyplotpyplotpltnetworkxrrr"barabasi_albert_graphG_bagnp_random_graphG_erconnected_watts_strogatz_graphG_wsrprintinfostartr!betweenness_centralitydrawshowr r r r s8