##最大マッチング問題
無向グラフ$G=(V,E)$に対し辺の本数が最大のマッチングを求めよ。
##実行方法
usage
Signature: nx.max_weight_matching(G, maxcardinality=False)
Docstring:
Compute a maximum-weighted matching of G.
A matching is a subset of edges in which no node occurs more than once.
The cardinality of a matching is the number of matched edges.
The weight of a matching is the sum of the weights of its edges.
python
# CSVデータ
import pandas as pd, networkx as nx, matplotlib.pyplot as plt
from ortoolpy import graph_from_table, networkx_draw
tbn = pd.read_csv('data/node0.csv')
tbe = pd.read_csv('data/edge0.csv')
g = graph_from_table(tbn, tbe)[0]
for i, j in g.edges():
del g.adj[i][j]['weight']
d = nx.max_weight_matching(g)
pos = networkx_draw(g)
nx.draw_networkx_edges(g, pos, width=3, edgelist=[(i, j) for i, j in d])
plt.show()
print(d)
結果
{5: 0, 0: 5, 4: 3, 3: 4, 2: 1, 1: 2}
python
# pandas.DataFrame
from ortoolpy.optimization import MaxMatching
MaxMatching('data/edge0.csv')
| node1 | node2 | capacity | weight | |
|---|---|---|---|---|
| 0 | 0 | 5 | 2 | 4 |
| 1 | 1 | 2 | 2 | 5 |
| 2 | 3 | 4 | 2 | 4 |
python
# 乱数データ
import networkx as nx, matplotlib.pyplot as plt
from ortoolpy import networkx_draw
g = nx.random_graphs.fast_gnp_random_graph(10, 0.3, 1)
d = nx.max_weight_matching(g)
pos = networkx_draw(g, nx.spring_layout(g))
nx.draw_networkx_edges(g, pos, width=3, edgelist=[(i, j) for i, j in d])
plt.show()
##データ