Implemented kebab algo
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@ -1,6 +1,7 @@
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import numpy as np
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import networkx as nx
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import argparse
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import time
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parser = argparse.ArgumentParser(description='')
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parser.add_argument('-g', '--graph', dest='graph', action='store', default=None)
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@ -13,9 +14,9 @@ if not args.graph:
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def read_graph(graph_file):
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with open(graph_file) as f:
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n = int(f.readline())
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m = int(f.readline())
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A = [[0] * n for _ in range(n)]
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n = int(f.readline()) # pontok száma
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m = int(f.readline()) # élek száma
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A = [[0] * n for _ in range(n)] # táblázat, ahol az élek helyén 1 van, ammeg 0
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for _ in range(m):
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[u, v] = map(int, f.readline().split())
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A[u][v] = 1
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@ -24,21 +25,55 @@ def read_graph(graph_file):
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return G
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input_graph = read_graph(args.graph)
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def max_comp_size(G):
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return max([len(c) for c in nx.connected_components(G)])
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del_list = []
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G = read_graph(args.graph)
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n = len(G.nodes)
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while max_comp_size(G) > n / 2:
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u = np.random.choice(G.nodes)
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if u not in del_list:
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del_list.append(u)
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G.remove_node(u)
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def run_random_once() -> list:
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del_list = []
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G = input_graph.copy()
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target = len(G.nodes) / 2
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while max_comp_size(G) > target:
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u = np.random.choice(G.nodes)
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if u not in del_list:
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del_list.append(u)
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G.remove_node(u)
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# print len(del_list), del_list
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return del_list
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for u in del_list:
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print(u)
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def remove_highest_kebab() -> list:
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del_list = []
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G = input_graph.copy()
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target = len(G.nodes) / 2
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while max_comp_size(G) > target:
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highest_node = None
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highest_node_deg = 0
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for node in G.nodes:
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if G.degree[node] > highest_node_deg:
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highest_node = node
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highest_node_deg = G.degree[node]
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del_list.append(highest_node)
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G.remove_node(highest_node)
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return del_list
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print(len(remove_highest_kebab()))
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# target_runtime = 600
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# start_time = time.time()
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# results = []
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# while (time.time() - start_time) < target_runtime:
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# for _ in range(50):
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# results.append(run_random_once())
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#
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# print("Total runs: ", len(results))
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# print("Min: ", min(results))
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# print("Max: ", max(results))
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# print("Runtime: ", time.time() - start_time)
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