networkx

How to visualize (dendrogram) a dictionary of hierarchical items?

由 人盡茶涼 提交于 2020-08-22 19:17:29
问题 This is my first time of doing visualization from hierarchical data in dictionary format with Python. Last part of the data looks like this: d = {^2820: [^391, ^1024], ^2821: [^759, 'w', ^118, ^51], ^2822: [^291, 'o'], ^2823: [^25, ^64], ^2824: [^177, ^2459], ^2825: [^338, ^1946], ^2826: [^186, ^1511], ^2827: [^162, 'i']} So I have indices on lists referring back to the keys (index) of the dictionary. I suppose this could be used as a base structure for the visualization, please correct me if

How to visualize (dendrogram) a dictionary of hierarchical items?

由 我只是一个虾纸丫 提交于 2020-08-22 19:17:18
问题 This is my first time of doing visualization from hierarchical data in dictionary format with Python. Last part of the data looks like this: d = {^2820: [^391, ^1024], ^2821: [^759, 'w', ^118, ^51], ^2822: [^291, 'o'], ^2823: [^25, ^64], ^2824: [^177, ^2459], ^2825: [^338, ^1946], ^2826: [^186, ^1511], ^2827: [^162, 'i']} So I have indices on lists referring back to the keys (index) of the dictionary. I suppose this could be used as a base structure for the visualization, please correct me if

Efficient way to extract triangles in a graph [duplicate]

由 纵饮孤独 提交于 2020-08-20 11:50:33
问题 This question already has answers here : Finding cycle of 3 nodes ( or triangles) in a graph (11 answers) Closed 19 days ago . I am trying to find triangles in graph using the following code : triangles_list = [] for v1 in G.nodes(): v1_nebs = G.neighbors(v1) if len(v1_nebs)>=2: for v2 in v1_nebs: for v3 in v1_nebs: if v2==v3: continue else: if v2 in G.neighbors(v3): list_str = [] list_str.append(int(v1)) list_str.append(int(v2)) list_str.append(int(v3)) list_str.sort() triangles_list.append

Edgelist within pandas dataframe to visualise using networkx

由 ﹥＞﹥吖頭↗ 提交于 2020-08-19 05:12:09
问题 I am having difficulties in representing a dataframe as a network using networkx. The problem seems to be related to the size of dataframe, or, to better explaining, to the presence of duplicates within the dataframe. My dataset is Src Dst x.serm.cool [x.serm.cool, x.creat.cool] x.creat.cool [x.creat.cool, x.serm.cool] sms.sol.tr [sms.sol.tr] bbb.asl.gt [bbb.asl.gt,cdc.fre.gh,str.alert.jf] cdc.fre.gh [cdc.fre.gh, bbb.asl.gt,str.alert.jf] str.alert.jf [str.alert.jf, bbb.asl.gt, cdc.fre.gh] ...

浅谈通过推特获取威胁情报

由 你。 提交于 2020-08-17 02:56:24
作者：果胜 本文为作者投稿，Seebug Paper 期待你的分享，凡经采用即有礼品相送！ 投稿邮箱：paper@seebug.org 在SOC的实践中，对安全事件的跟踪以及威胁溯源是安全预警和防御的重要步骤。目前安全社区和白帽黑客建立了多种事件情报的分享渠道，其中社交媒体是非常重要的组成部分，有很多组织和个人通过各类社交APP发布恶意软件，安全事件，漏洞和利用工具的相关信息。故而目前许多安全人员都开始通过SOCMINT（社交媒体情报）来辅助威胁跟踪和预警工作。由于国内外的法律和文化不同，目前国内的微博更重于舆情、安全事件的发布，而推特更重于漏洞，恶意软件等技术信息的发布，在威胁跟踪时可以根据自身的具体需求选取，这里介绍一些twitter中进行威胁情报采集的方法。 twitter搜索语法 同google,github等平台的搜索功能类似,twitter也提供了搜索语法来进行高精度的搜索,这里是一些标准搜索语法: - 搜索包含同时多个关键字的推文 keyword1 keyword2 - 精确搜索包含某一关键字的推文 "keyword" - 并列搜索(包含一个或多个关键字) keyword1 OR keyword2 - 搜索不包含某一关键字的推文 keyword1 -keyword2 (不包含keyword2) - 搜索某一hashtag的推文 keyword -

How to get the weight of the smallest path between two nodes?

由 女生的网名这么多〃 提交于 2020-08-08 05:20:27
问题 I have a networkx graph in Python, with weighted edges. I want to get the weight of the smallest path between two nodes. Currently, I am getting the nodes in the shortest path from the nx.shortest_path implementation, and then iterating through each pair and summing over the weights between each pair of node. shortest_path = nx.shortest_path(G, source, destination, 'distance') #function to iterate over each pair import itertools def pairwise(iterable): a, b = itertools.tee(iterable) next(b,

How to place nodes in a specific position - networkx

由 ☆樱花仙子☆ 提交于 2020-08-02 04:59:50
问题 I am doing a Ford-Fulkerson method which draws the graph at every stage. I want to place the source and the sink on specific positions (I want the source to be on the far left of the graph and the sink on the far right). I've already tried the pos argument inside the spring_layout function, but that doesn't seem to work. This is my graph: graph.add_edges_from([ ('A', 'B', {'capacity': 4, 'flow': 0}), ('A', 'C', {'capacity': 5, 'flow': 0}), ('A', 'D', {'capacity': 7, 'flow': 0}), ('B', 'E', {

How to place nodes in a specific position - networkx

由 大兔子大兔子 提交于 2020-08-02 04:59:43
问题 I am doing a Ford-Fulkerson method which draws the graph at every stage. I want to place the source and the sink on specific positions (I want the source to be on the far left of the graph and the sink on the far right). I've already tried the pos argument inside the spring_layout function, but that doesn't seem to work. This is my graph: graph.add_edges_from([ ('A', 'B', {'capacity': 4, 'flow': 0}), ('A', 'C', {'capacity': 5, 'flow': 0}), ('A', 'D', {'capacity': 7, 'flow': 0}), ('B', 'E', {

networkx+python构建图结构数据并可视化

由 荒凉一梦 提交于 2020-07-27 05:52:39
目前处理非欧数据最常见的方法还是构建 图 ，而networkx一个专门的构建图数据的工具。方便又好用。 先给链接： https://networkx.github.io/ 官方文档 ： https://networkx.github.io/documentation/latest/ networkx的安装方法上面的官方文档已经很详细记录，阿盏就不赘述了。 官方文档里给了几个demo，虽然便利，但泛化性不强。我这边给一个泛化性强一些的demo： import networkx as nx import matplotlib.pyplot as plt g = nx.Graph() g.add_edge('1', '2') g.add_edge('2', '3') g.add_edge('1', '4') g.add_edge('2', '4') fig, ax = plt.subplots() nx.draw(g, ax=ax) plt.show() 咱们构建的图数据就是g，看得出来一共有['1', '2', '3', 4'']四个节点。可视化结果为： 就一张光秃秃的点棍图，可以把节点label加上，只需设置with_labels=True: import networkx as nx import matplotlib.pyplot as plt g = nx.Graph() g

Clipping a networkx graph according to georeferenced polygon

由 非 Y 不嫁゛ 提交于 2020-07-23 06:52:05
问题 I am running a loop that computes a networkx.classes.multidigraph.MultiDiGraph for each row (neighbourhood) of a list of GeoDataFrames (cities). It then computes some statistics for each row and writes the file out to disk. The problem is that the loop is extremely long to compute because the graph is computed for each row. The way I want to quicken the loop is by computing the graph for the whole GeoDataFrame and then clipping the graph into each row (each row has a polygon). You can do this
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