def main(): G = gg.Graph() set1 = G.create_nodes(200, {"clustId": 1}, 0) set2 = G.create_nodes(400, {"clustId": 2}, 0) set3 = G.create_nodes(50, {"clustId": 3}, 0) set4 = G.create_nodes(50, {"clustId": 3}, 0) for i in range(10): G.create_random_edges(2500, [set1, set2, set3, set4], [[0.29, 0.01, 0, 0], [0, 0.5, 0, 0], [0, 0, 0.10, 0], [0, 0, 0, 0.10]], [ gg.UniformDistrib(), gg.UniformDistrib(), gg.UniformDistrib(), gg.UniformDistrib() ], i) for i in range(10, 15): G.create_random_edges( 500, [set1, set2, set3, set4], [[0.1, 0, 0.4, 0], [0, 0.1, 0, 0.4], [0, 0, 0, 0], [0, 0, 0, 0]], [ gg.UniformDistrib(), gg.UniformDistrib(), gg.UniformDistrib(), gg.UniformDistrib() ], i) for i in range(15, 25): G.create_random_edges( 500, [set1, set2, set3, set4], [[0.2, 0, 0, 0], [0, 0.2, 0, 0], [0, 0, 0, 0.6], [0, 0, 0, 0]], [ gg.UniformDistrib(), gg.UniformDistrib(), gg.UniformDistrib(), gg.UniformDistrib() ], i) # set5 = G.create_nodes(50, {"clustId":5}, 2) # G.create_random_edges( 200, # [set5], # [[1]], # [gg.UniformDistrib()], # 2) # G.create_random_edges( 200, # [set5], # [[1]], # [gg.UniformDistrib()], # 3) # G.create_random_edges( 100, # [set5], # [[1]], # [gg.UniformDistrib()], # 4) # learn_parameters(G) # cdr = cd.CommunityDetector(G, sorted_results[-1][1]["tr"], sorted_results[-1][1]["h"], sorted_results[-1][1]["d"], sorted_results[-1][1]["p"]) cdr = cd.CommunityDetector(G, 10, 100, 5, 10000) cdr.run(False, False) # G.create_random_edges(200, [set1, set2], [[0,1],[0,0]], [gg.UniformDistrib(), gg.UniformDistrib()],4) # G.create_random_edges(200, [set1, set2, set3, set4], [[0,0,0,0.5],[0,0,0.5,0],[0,0,0,0],[0,0,0,0]], [gg.UniformDistrib(), gg.UniformDistrib(), gg.UniformDistrib(), gg.UniformDistrib()],5) # G.create_random_edges(400, [set1, set2], [[0.49,0.02],[0.,0.49]], [gg.UniformDistrib(), gg.UniformDistrib()],10) # G.plot_sequence() # G = gg.Graph(True) # set1 = G.create_nodes(100) # set2 = G.create_nodes(80) # G.create_random_edges(500, [set1, set2], [[0.49,0.01],[0.01,0.49]], [gg.UniformDistrib(), gg.UniformDistrib()]) # G.plot_sequence() # tree = st.SegmentTree() # elements = [(0,5),(0,5),(0,10),(0,7),(5,10),(15,20),(12,st.SegmentTree.infinite)] # for i in range(len(elements)): # tree.insert(i, elements[i]) # # query = [0,3,5,7,11,12,20,98] # # for q in query: # # print "query=",q," - result=",tree.query(q) # # pdb.set_trace() # to_delete = range(len(elements)) # random.shuffle(to_delete) # print to_delete # for d in to_delete: # tree.delete(d, elements[d]) # print "query=",elements[d][1]," - result=",tree.query(elements[d][1]) # pdb.set_trace()
def main(factor): G = gg.Graph() set1 = G.create_nodes(200, {"clustId": 1}, 0) set2 = G.create_nodes(200, {"clustId": 2}, 0) set3 = G.create_nodes(200, {"clustId": 2}, 0) set4 = G.create_nodes(50, {"clustId": 4}, 0) set5 = G.create_nodes(50, {"clustId": 5}, 0) for i in range(4): G.create_random_edges( 500 * factor, [set1, set2, set3, set4, set5], [[0.303, 0.005, 0.005, 0.001, 0.001], [0, 0.17, 0.24, 0.001, 0.001], [0, 0, 0.17, 0.001, 0.001], [0, 0, 0, 0.05, 0.001], [0, 0, 0, 0, 0.05]], [ gg.UniformDistrib(), gg.UniformDistrib(), gg.UniformDistrib(), gg.UniformDistrib(), gg.UniformDistrib() ], i) for i in range(4, 7): G.create_random_edges( 40 * factor, [set1, set2, set3, set4, set5], [[0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 0, 1], [0, 0, 0, 0, 0]], [ gg.UniformDistrib(), gg.UniformDistrib(), gg.UniformDistrib(), gg.UniformDistrib(), gg.UniformDistrib() ], i) for i in range(7, 9): G.delete_random_edges( 200 * factor, [set1, set2, set3, set4, set5], [[0, 0, 0, 0, 0], [0, 0, 1, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 0, 0]], [ gg.UniformDistrib(), gg.UniformDistrib(), gg.UniformDistrib(), gg.UniformDistrib(), gg.UniformDistrib() ], i) G.delete_random_edges(0, [set1, set2, set3, set4, set5], [[0, 0, 0, 0, 0], [0, 0, 1, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 0, 0]], [ gg.UniformDistrib(), gg.UniformDistrib(), gg.UniformDistrib(), gg.UniformDistrib(), gg.UniformDistrib() ], 9) # for i in range(9,14): # G.delete_random_edges( 40*factor, # [set1, set2, set3, set4, set5], # [[0 ,0 ,0 ,0 ,0 ], # [0 ,0 ,1 ,0 ,0 ], # [0 ,0 ,0 ,0 ,0 ], # [0 ,0 ,0 ,0 ,0 ], # [0 ,0 ,0 ,0 ,0 ]], # [gg.UniformDistrib(), gg.UniformDistrib(), gg.UniformDistrib(), gg.UniformDistrib(), gg.UniformDistrib()], # i) cdr = cd.CommunityDetector(G, 10, 100, 5, 10000) cdr.run(True, True, False, 0, 4) G.update_nodes(set5, {"clustId": 4}) cdr.run(True, True, False, 4, 7) G.update_nodes(set3, {"clustId": 3}) cdr.run(True, True, False, 7, 12)