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annotate env/lib/python3.9/site-packages/networkx/algorithms/approximation/tests/test_vertex_cover.py @ 0:4f3585e2f14b draft default tip
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author | shellac |
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date | Mon, 22 Mar 2021 18:12:50 +0000 |
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1 import networkx as nx |
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2 from networkx.algorithms.approximation import min_weighted_vertex_cover |
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3 |
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4 |
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5 def is_cover(G, node_cover): |
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6 return all({u, v} & node_cover for u, v in G.edges()) |
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7 |
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8 |
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9 class TestMWVC: |
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10 """Unit tests for the approximate minimum weighted vertex cover |
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11 function, |
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12 :func:`~networkx.algorithms.approximation.vertex_cover.min_weighted_vertex_cover`. |
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13 |
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14 """ |
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15 |
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16 def test_unweighted_directed(self): |
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17 # Create a star graph in which half the nodes are directed in |
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18 # and half are directed out. |
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19 G = nx.DiGraph() |
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20 G.add_edges_from((0, v) for v in range(1, 26)) |
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21 G.add_edges_from((v, 0) for v in range(26, 51)) |
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22 cover = min_weighted_vertex_cover(G) |
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23 assert 2 == len(cover) |
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24 assert is_cover(G, cover) |
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25 |
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26 def test_unweighted_undirected(self): |
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27 # create a simple star graph |
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28 size = 50 |
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29 sg = nx.star_graph(size) |
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30 cover = min_weighted_vertex_cover(sg) |
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31 assert 2 == len(cover) |
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32 assert is_cover(sg, cover) |
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33 |
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34 def test_weighted(self): |
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35 wg = nx.Graph() |
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36 wg.add_node(0, weight=10) |
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37 wg.add_node(1, weight=1) |
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38 wg.add_node(2, weight=1) |
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39 wg.add_node(3, weight=1) |
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40 wg.add_node(4, weight=1) |
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41 |
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42 wg.add_edge(0, 1) |
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43 wg.add_edge(0, 2) |
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44 wg.add_edge(0, 3) |
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45 wg.add_edge(0, 4) |
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46 |
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47 wg.add_edge(1, 2) |
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48 wg.add_edge(2, 3) |
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49 wg.add_edge(3, 4) |
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50 wg.add_edge(4, 1) |
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51 |
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52 cover = min_weighted_vertex_cover(wg, weight="weight") |
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53 csum = sum(wg.nodes[node]["weight"] for node in cover) |
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54 assert 4 == csum |
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55 assert is_cover(wg, cover) |