networkx

Read/Write NetworkX Graph Object

由 扶醉桌前 提交于 2020-11-30 04:27:38
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

Select nodes and edges form networkx graph with attributes

由 戏子无情 提交于 2020-11-27 01:49:45
问题 I've just started doing graphs in networkx and I want to follow the evolution of a graph in time: how it changed, what nodes/edges are in the graph at a specified time t. Here is my code: import networkx as nx import matplotlib.pyplot as plt G=nx.Graph() G.add_node(1,id=1000,since='December 2008') G.add_node(2,id=2000,since='December 2008') G.add_node(3,id=3000,since='January 2010') G.add_node(4,id=2000,since='December 2016') G.add_edge(1,2,since='December 2008') G.add_edge(1,3,since=

Trying to plot two or more infrastructures in the same figure using OSMnx

由 ╄→гoц情女王★ 提交于 2020-11-24 18:05:48
问题 I'm trying to plot multiple infrastructure networks(for example streets, rails and buildings) in the same figure using OSMnx but not really having success. This is one of my attempts: import osmnx as ox dist = 2000 point = (41.877092, -87.628) north, south, east, west = ox.bbox_from_point(point, distance=dist) bbox_proj = ox.bbox_from_point(point, dist, project_utm=True) streets = ox.core.osm_net_download( north=north, south=south, east=east, west=west, infrastructure='way["highway"]' )

Trying to plot two or more infrastructures in the same figure using OSMnx

由 会有一股神秘感。 提交于 2020-11-24 18:05:31
问题 I'm trying to plot multiple infrastructure networks(for example streets, rails and buildings) in the same figure using OSMnx but not really having success. This is one of my attempts: import osmnx as ox dist = 2000 point = (41.877092, -87.628) north, south, east, west = ox.bbox_from_point(point, distance=dist) bbox_proj = ox.bbox_from_point(point, dist, project_utm=True) streets = ox.core.osm_net_download( north=north, south=south, east=east, west=west, infrastructure='way["highway"]' )

Trying to plot two or more infrastructures in the same figure using OSMnx

由 ﹥＞﹥吖頭↗ 提交于 2020-11-24 18:04:55
问题 I'm trying to plot multiple infrastructure networks(for example streets, rails and buildings) in the same figure using OSMnx but not really having success. This is one of my attempts: import osmnx as ox dist = 2000 point = (41.877092, -87.628) north, south, east, west = ox.bbox_from_point(point, distance=dist) bbox_proj = ox.bbox_from_point(point, dist, project_utm=True) streets = ox.core.osm_net_download( north=north, south=south, east=east, west=west, infrastructure='way["highway"]' )

干货 ：使用Spark进行大规模图形挖掘（附链接）

由 元气小坏坏 提交于 2020-11-18 14:46:18
翻译：陈丹 校对：王雨桐 本文 约4700字 ，建议阅读 15 分钟 本文为大家介绍了多种图挖掘工具，并运用Spark为大家展示了一个标签传播算法LPA构建图的实例。 本教程分为两部分： 第1部分：无监督学习图 （https://towardsdatascience.com/large-scale-graph-mining-with-spark-750995050656） 第2部分（就是本文！） ： 如何运用神奇的图。我们将讨论标签传播，Spark GraphFrame和结果。 下文可回顾示例图和笔记： https://github.com/wsuen/pygotham2018_graphmining 在第1部分，我们看到了如何使用图来解决无监督的机器学习问题，因为社区是集群。我们可以利用节点之间的边作为相似性或相关性的指标，特征空间中的距离可用于其他类型的聚类。 本文将深入探讨社区检测的方式。我们构建和挖掘一个大型网络图，学习如何在Spark中实现标签传播算法（LPA）的社区检测方法。 通过标签传播检测社区 尽管有许多社区检测技术，但本文仅关注一种：标签传播。有关其他方法的概述，我推荐Santo Fortunato的“图形中的社区检测”（https://arxiv.org/pdf/0906.0612.pdf）。 Raghavan，Usha Nandini
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