Implemented kebab algo

destroy_p3.py

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