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I'm looking to visualize the data, hopefully make it interactive. Right now I'm using NetworkX and Matplotlib, which maxes out my 8gb when I attempt to 'draw' the graph. I don't know what options and techniques exist for handling such a large cluster** of data. If someone could point me in the right direction, that'd be great. I also have a CUDA enabled GFX card if that could be of use.
Right now I'm thinking of drawing only the most connected nodes, say top 5% of vertices with the most edges, then filling in less connected nodes as the user zooms or clicks.
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Other features not much better then in Gephi, except Graphistry has reasonable default parameters, a good color scheme, and slightly better interactivity. It provides only one force-directed layout. It also has a limit of 800K nodes or edges.
Option 1: NetworkX NetworkX has its own drawing module which provides multiple options for plotting. Below we can find the visualization for some of the draw modules in the package. Using any of them is fairly easy, as all you need to do is call the module and pass the G graph variable and the package does the rest.
A graph is a pictorial representation of a set of objects where some pairs of objects are connected by links. The interconnected objects are represented by points termed as vertices, and the links that connect the vertices are called edges.
Introduction Big data and analytics can be beautifully presented by using visualization tools in Python. The most common type of visualization is a simple bar chart. First tool is Pandas. Second tool is Seaborn. Third tool is Bokeh. Forth tool is Pygal. Fifth tool is Plotly, also named as Plot.ly because of its main platform online.
If your graph has 1000000 vertices and only 50000 edges then most of your vertices won't have any edges anyway. In fact the Gephi spec is the dual of your example: "Networks up to 50,000 nodes and 1,000,000 edges" Show activity on this post.
The nodes are sometimes also referred to as vertices and the edges are lines or arcs that connect any two nodes in the graph. In this tutorial we are going to visualize undirected Graphs in Python with the help of networkx library.
While the visualization option is built in the default python graph package and is quite easy to call, it's highly counter-intuitive and good only for small networks. Most of the time, with large networks, any of the inbuilt module calls doesn’t make a lot of sense.
I don't have any experience with it, but tulip seems to be made for that.
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