U ?h@sdZddlZddlmZddlZdddZdZej dded Z e e Z e e ee Zd d ZdZe jZeZee eeeZe eZed ed eeje ed ZddddddZeje efeeje eegdddedS)z =========== Beam Search =========== Beam search with dynamic beam width. The progressive widening beam search repeatedly executes a beam search with increasing beam width until the target node is found. Nc Csx||r |Sttt|}t|D]@}|td|}t||||D]\}} || rJ| SqJq(tddS)aProgressive widening beam search to find a node. The progressive widening beam search involves a repeated beam search, starting with a small beam width then extending to progressively larger beam widths if the target node is not found. This implementation simply returns the first node found that matches the termination condition. `G` is a NetworkX graph. `source` is a node in the graph. The search for the node of interest begins here and extends only to those nodes in the (weakly) connected component of this node. `value` is a function that returns a real number indicating how good a potential neighbor node is when deciding which neighbor nodes to enqueue in the breadth-first search. Only the best nodes within the current beam width will be enqueued at each step. `condition` is the termination condition for the search. This is a function that takes a node as input and return a Boolean indicating whether the node is the target. If no node matches the termination condition, this function raises :exc:`NodeNotFound`. `initial_width` is the starting beam width for the beam search (the default is one). If no node matching the `condition` is found with this beam width, the beam search is restarted from the `source` node with a beam width that is twice as large (so the beam width increases exponentially). The search terminates after the beam width exceeds the number of nodes in the graph. z+no node satisfied the termination conditionN) mathceillog2lenrangepownxZbfs_beam_edgesZ NodeNotFound) Gsourcevalue conditionZ initial_widthZlog_miwidthuvrv/var/www/html/venv/lib/python3.8/site-packages/../../../share/doc/networkx-3.1/examples/algorithms/plot_beam_search.pyprogressive_widening_searchs# rYdg?)seedcCs t|tkS)N) centralityavg_centrality)rrrrhas_high_centralityWsrz found node z with centrality blueZgreyg?) node_color node_sizeZ edge_colorZ linewidthsrr)Znodelistrr)r)__doc__rZmatplotlib.pyplotZpyplotZpltZnetworkxr rrZgnp_random_graphr Zeigenvector_centralityrsumvaluesrrrr getr rZ found_nodecprintZ spring_layoutposoptionsZdrawZdraw_networkx_nodesshowrrrrs2   ?