networkx

问题 I currently have the following code for my networkx graph: import matplotlib.pyplot as plt import networkx as nx G = nx.Graph() G.add_edge("a", "b", weight=0.6) G.add_edge("a", "c", weight=0.2) G.add_edge("c", "d", weight=0.1) G.add_edge("c", "e", weight=0.7) G.add_edge("c", "f", weight=0.9) G.add_edge("a", "d", weight=0.3) elarge = [(u, v) for (u, v, d) in G.edges(data=True) if d["weight"] > 0.5] esmall = [(u, v) for (u, v, d) in G.edges(data=True) if d["weight"] <= 0.5] pos = nx.circular

问题 I found DiGraph.reverse() to reverse the direction of all edges in the directed graph, but is there a way to change the direction of a specific edge only? 回答1: It can certainly be done manually, but there's nothing in the API for it. $ cat edges.py; echo; python edges.py import networkx as nx G=nx.DiGraph() G.add_edge(1,2,{'weight':.5}) G.add_edge(3,4,{'weight':1.0}) attrs = G[1][2] G.remove_edge(1,2) G.add_edge(2,1,attrs) print G.edges(data=True) [(2, 1, {'weight': 0.5}), (3, 4, {'weight': 1

问题 I am trying to represent relationships between numbers in column A and their corresponding values in B. A B Home [Kitchen, Home, Towel] Donald [US, 02 , Donald, Trump] Trump [Trump,Family, Cat, Dog] Dog [Dog,Cat,Paws] Numbers in column A and numbers in B are nodes in a graph. I would like to connect elements in B to A or to each other. For example: Home in A is linked with itself; if I look within B column (the value appears only in the first row), Home in B is connected to Kitchen and Towel

问题 B = nx.Graph() B.add_nodes_from(data['movie'].unique(), bipartite=0, label='movie') B.add_nodes_from(data['actor'].unique(), bipartite=1, label='actor') B.add_edges_from(edges, label='acted') A = list(nx.connected_component_subgraphs(B))[0] I am getting the below given error when am trying to use nx.connected_component_subgraphs(G). Please help with this issue. In the dataset there are two coumns(movie and actor), and it's in the form bipartite graph. I want to get connected components for

问题 B = nx.Graph() B.add_nodes_from(data['movie'].unique(), bipartite=0, label='movie') B.add_nodes_from(data['actor'].unique(), bipartite=1, label='actor') B.add_edges_from(edges, label='acted') A = list(nx.connected_component_subgraphs(B))[0] I am getting the below given error when am trying to use nx.connected_component_subgraphs(G). Please help with this issue. In the dataset there are two coumns(movie and actor), and it's in the form bipartite graph. I want to get connected components for

问题 I have a osmnx plot that has two routes, but the map is quite vast therefore I cannot see the routes properly. Is there a fast way to limit my plot, to sort of 'zoom in', using for example bbox ? I know I could search for districts instead of a whole city, I was just curious to know if there was a fastest way to 'zoom' in the plot. Here is the code: import osmnx as ox import igraph as ig import matplotlib.pyplot as plt import pandas as pd import networkx as nx import numpy as np import

问题 I'm a beginner at using NetworkX and I'm trying to find a way to detect which nodes have distance x from each other. I've started by using this algorithm to get all pairs path=nx.all_pairs_dijkstra_path(G) But I'm still unsure on how to detect the distance between nodes using a for loop. I'd appreciate any help. Thank you 回答1: NetworkX has methods for automatically calculating the shortest paths (or just the path lengths) for weighted and unweighted graphs. Make sure that you use the correct

问题 I'd like to select and perform operations on nodes within a graph with particular attributes. How would you select nodes with a given attribute value? For example: P=nx.Graph() P.add_node('node1',at=5) P.add_node('node2',at=5) P.add_node('node3',at=6) Is there a way to select only the nodes with at == 5?. I'm imagining something like (this doesn't work): for p in P.nodes(): P.node[p]['at'==5] 回答1: Python <= 2.7: According to the documentation try: nodesAt5 = filter(lambda (n, d): d['at'] == 5

问题 I'd like to select and perform operations on nodes within a graph with particular attributes. How would you select nodes with a given attribute value? For example: P=nx.Graph() P.add_node('node1',at=5) P.add_node('node2',at=5) P.add_node('node3',at=6) Is there a way to select only the nodes with at == 5?. I'm imagining something like (this doesn't work): for p in P.nodes(): P.node[p]['at'==5] 回答1: Python <= 2.7: According to the documentation try: nodesAt5 = filter(lambda (n, d): d['at'] == 5

问题 I am trying to deal with a super-massive NetworkX Graph object with hundreds of millions of nodes. I'd like to be able to write it to file as to not consume all my computer memory. However, I need to constantly be searching across existing nodes, updating edges, etc. Is there a good solution for this? I'm not sure how it would work with any of the file formats provided on http://networkx.lanl.gov/reference/readwrite.html The only solution i can think of is to store each node as a separate