You should add graph-tool to the python list. It is very complete, and it is implemented in C++, with the Boost Graph Library, making it orders of magnitude faster than python-only alternatives, such as NetworkX. Disclaimer: I’m the author of graph-tool. 🙂
digraph { A; B; C subgraph Rel1 { edge [dir=none, color=red] A -> B -> C -> A } subgraph Rel2 { edge [color=blue] B -> C C -> A } }
The answer is unfortunately: Your consideration is completely right in every point. You have to store Nodes (Vertices) in one table, and Edges referencing a FromNode and a ToNode to convert a graph data structure to a relational data structure. And you are also right, that this ends up in a large number of lookups, … Read more
If you have N nodes, there are N – 1 directed edges than can lead from it (going to every other node). Therefore, the maximum number of edges is N * (N – 1).
You should just use: A -> B [dir=both]
use labelpad parameter: pl.xlabel(“…”, labelpad=20) or set it after: ax.xaxis.labelpad = 20
To plot multiple graphs on the same figure you will have to do: from numpy import * import math import matplotlib.pyplot as plt t = linspace(0, 2*math.pi, 400) a = sin(t) b = cos(t) c = a + b plt.plot(t, a, ‘r’) # plotting t, a separately plt.plot(t, b, ‘b’) # plotting t, b separately … Read more
E is the set of all edges in the graph, as G={V,E}. So, |E| is count of all edges in the graph. This alone should be enough to convince you that the overall complexity can’t be |V| times |E|, since we are not iterating over all the edges in the graph for each vertex. In … Read more
code2flow does exactly this. Full disclosure, I started this project To run $ code2flow source1.js source2.js -o out.gv Then, open out.gv with graphviz Edit: For now, this project is unmaintained. I would suggest trying out a different solution before using code2flow.