See Harry Hsu. “An algorithm for finding a minimal equivalent graph of a digraph.”, Journal of the ACM, 22(1):11-16, January 1975. The simple cubic algorithm below (using an N x N path matrix) suffices for DAGs, but Hsu generalizes it to cyclic graphs. // reflexive reduction for (int i = 0; i < N; ++i) … Read more
In essence, there are some techniques to efficiently query graph data within an SQL database, that apply to highly specialized scenarios. You could opt to maintain a GRIPP index, for instance, if your interests lie in finding shortest paths. (It basically works a bit like pre-ordered tree index, applied to graphs.) To the best of … Read more
OrientDB (old link) appears to support graph storage in much the same was as Neo4j
The issue here is that the number of ticks -set automatically – isn’t the same as the number of points in your plot. To resolve this, set the number of ticks: ax1.set_xticks(np.arange(len(x))) Before the ax1.set_xticklabels(x) call.
Use depth-first search (DFS) to mark all individual connected components as visited: dfs(node u) for each node v connected to u : if v is not visited : visited[v] = true dfs(v) for each node u: if u is not visited : visited[u] = true connected_component += 1 dfs(u) The best way is to use … Read more
Each node is named uniquely and knows who it is connected to. The List of connections allows for a Node to be connected to an arbitrary number of other nodes. public class Node { public String name; public List<Edge> connections; } Each connection is directed, has a start and an end, and is weighted. public … Read more
Update: This is not the best solution I have come up with, but I’ve left it because there are so many comments relating to it. You have a set of events (birth/death), parental state (no descendants, parent, grandparent, etc) and life state (alive, dead). I would store my data in structures with the following fields: … Read more
Using Mathematica 8, I created a morphological graph from the list of white pixels in the image. It is working fine on your first image: Create the morphological graph: graph = MorphologicalGraph[binaryimage]; Then you can query the graph properties that are of interest to you. This gives the names of the vertex in the graph: … Read more
There’s more than one way do to this, depending on the relationship that you want the inset to have. If you just want to inset a graph that has no set relationship with the bigger graph, just do something like: import matplotlib.pyplot as plt fig, ax1 = plt.subplots() # These are in unitless percentages of … Read more
See my other post for how to make the sum of all bins in a histogram equal to one: https://stackoverflow.com/a/16399202/1542814 Copy & Paste: weights = np.ones_like(myarray)/float(len(myarray)) plt.hist(myarray, weights=weights) where myarray contains your data