NetworkX系列教程(5)-查看graph的信息

小書匠 Graph 圖論

有時候graph建好后,我們並不清除該graph內節點的,邊的信息,這就需要調用函數去查看了.

目錄:

• 6.查看Graph的信息
  • 6.1查看graph內節點,邊的
  • 6.2查看graph中的點,邊
  • 6.3查看某些節點的度
  • 6.4查看節點&邊信息
  • 6.5遍歷一個有權圖

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注意:如果代碼出現找不庫,請返回第一個教程,把庫文件導入.

6.查看Graph的信息

6.1查看graph內節點,邊的數量

1. #生成graph 
   

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2. G=nx.path_graph(8) 
   

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3. nx.draw(G,with_labels=True) 
   

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4. plt.axis('on') 
   

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5. plt.xticks([]) 
   

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6. plt.yticks([]) 
   

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7. plt.show() 
   

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8.  
   

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9. #查看節點和邊的情況 
   

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10. print('number of nodes',G.number_of_nodes()) 
    

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11. print('number of edges',G.number_of_edges()) 
    

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例子圖

輸出:

1. number of nodes 8 
   

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2. number of edges 7 
   

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6.2查看graph中的點,邊

1. #輸出graph所有的點和邊 
   

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2. print('all nodes of Graph',G.nodes()) 
   

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3. print('all edges of Graph',G.edges()) 
   

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輸出:

1. all nodes of Graph [0, 1, 2, 3, 4, 5, 6, 7] 
   

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2. all edges of Graph [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6), (6, 7)] 
   

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6.3查看某些節點的度

1. #查看節點2和3的度 
   

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2. print('degree of some nodes',G.degree([2, 3])) 
   

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輸出:

1. degree of some nodes [(2, 2), (3, 2)] 
   

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6.4查看節點&邊信息

1. #設置一些節點信息 
   

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2. G.nodes[1]['room'] = 714 
   

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3. G.nodes[1]['color'] = 'b' 
   

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4. #設置一些邊信息 
   

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5. G[1][2]['weight'] = 4.7 
   

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6. G[1][2]['color'] = "blue" 
   

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7.  
   

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8. print('imformation of one nodes',G.nodes[1]) 
   

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9. print('imformation of all nodes',G.nodes.data()) 
   

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10.  
    

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11. print('imformation of all nodes',G.edges.data()) #邊不支持[x]這樣的下標訪問 
    

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輸出:

1. imformation of one nodes {'room': 714, 'color': 'b'} 
   

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2. imformation of all nodes [(0, {}), (1, {'room': 714, 'color': 'b'}), (2, {}), (3, {}), (4, {}), (5, {}), (6, {}), (7, {})] 
   

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3. imformation of all nodes [(0, 1, {}), (1, 2, {'weight': 4.7, 'color': 'blue'}), (2, 3, {}), (3, 4, {}), (4, 5, {}), (5, 6, {}), (6, 
   

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7, {})]

6.5遍歷一個有權圖

1. #定義一個有權無向圖 
   

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2. FG = nx.Graph() 
   

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3. FG.add_weighted_edges_from([(1, 2, 0.125), (1, 3, 0.75), (2, 4, 1.2), (3, 4, 0.375)]) 
   

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4.  
   

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5. #遍歷鄰接矩陣 
   

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6. for n, nbrs in FG.adj.items(): 
   

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7. for nbr, eattr in nbrs.items(): 
   

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8. wt = eattr['weight'] 
   

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9. #權重小於0.5的輸出 
   

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10. if wt < 0.5:  
    

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11. print('way1-(%d, %d, %.3f)' % (n, nbr, wt)) 
    

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12.  
    

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13. #遍歷所有邊 
    

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14. for (u, v, wt) in FG.edges.data('weight'): 
    

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15. #權重小於0.5的輸出 
    

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16. if wt < 0.5:  
    

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17. print('way2-(%d, %d, %.3f)' % (u, v, wt)) 
    

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輸出:

1. way1-(1, 2, 0.125) 
   

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2. way1-(2, 1, 0.125) 
   

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3. way1-(3, 4, 0.375) 
   

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4. way1-(4, 3, 0.375) 
   

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5. way2-(1, 2, 0.125) 
   

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6. way2-(3, 4, 0.375) 
   

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