for line in f: if 'average' in line: line = line.split(' ') it = int(line[1].strip()) r = float(line[-1].strip()) if r < best_r: best_r = r best_it = it assert best_it >= 0 print 'using iter=', best_it, 'with r=', best_r return '%s/nrange_%d_%d_iter_%d.model' % (opt['save_dir'], min_n, max_n, best_it) if __name__ == '__main__': api = MvcLib(sys.argv) opt = {} for i in range(1, len(sys.argv), 2): opt[sys.argv[i][1:]] = sys.argv[i + 1] model_file = find_model_file(opt) assert model_file is not None print 'loading', model_file sys.stdout.flush() api.LoadModel(model_file) n_test = 1000 f = open(opt['data_test'], 'rb') frac = 0.0
with open(log_file, 'r') as f: for line in f: if 'average' in line: line = line.split(' ') it = int(line[1].strip()) r = -float(line[-1].strip()) if it > 10000 and r > best_r: best_r = r best_it = it if best_it < 0: return None print best_it, best_r return '%s/nrange_%d_%d_iter_%d.model' % (opt['save_dir'], n1, n2, best_it) if __name__ == '__main__': api = MvcLib(sys.argv) opt = {} for i in range(1, len(sys.argv), 2): opt[sys.argv[i][1:]] = sys.argv[i + 1] model_file = find_model_file(opt) if model_file is not None: print 'loading', model_file sys.stdout.flush() api.LoadModel(model_file) PrepareValidData(opt) # startup gen_new_graphs(opt)
idxes = range(nx.number_of_nodes(G)) idxes = sorted(idxes, key=lambda x: len(nx.neighbors(G, x)), reverse=True) pos = 0 while numCoveredEdges < nx.number_of_edges(G): new_action = idxes[pos] covered_set.add(new_action) for neigh in nx.neighbors(G, new_action): if neigh not in covered_set: numCoveredEdges += 1 pos += 1 print 'done' return len(covered_set) if __name__ == '__main__': api = MvcLib(sys.argv) opt = {} for i in range(1, len(sys.argv), 2): opt[sys.argv[i][1:]] = sys.argv[i + 1] g_undirected, _ = build_full_graph( '%s/InfoNet5000Q1000NEXP.txt' % opt['data_root'], 'undirected') print(nx.number_of_nodes(g_undirected)) print(nx.number_of_edges(g_undirected)) print greedy(g_undirected) api.InsertGraph(g_undirected, is_test=True) # startup gen_new_graphs(opt)
if 'average' in line: line = [w for w in line.split(' ') if w] it = int(line[1].strip()) vc = line.index('vc:') r = float(line[vc + 1].strip()) if r < best_r: best_r = r best_it = it assert best_it >= 0 print 'using iter=', best_it, 'with r=', best_r return '%s/nrange_%d_%d_iter_%d.model' % (opt['save_dir'], min_n, max_n, best_it) if __name__ == '__main__': api = MvcLib(sys.argv) opt = {} for i in range(1, len(sys.argv), 2): opt[sys.argv[i][1:]] = sys.argv[i + 1] model_file = find_model_file(opt) assert model_file is not None print 'loading', model_file sys.stdout.flush() api.LoadModel(model_file) n_test = 1000 f = open(opt['data_test'], 'rb') frac = 0.0 frac_fastwvc = 0.0