Repository associated with the paper "Fast Estimation of Percolation Centrality".
The input file must be an edge list, one line for each edge (an edge is a tuple (u,v), where u and v are two vertices). While loading the edge list you must specify if the graph is directed or undirected. The two elements of an edge can be separated by any string, which can be specified using the load_graph function (see below). In the following, we assume that this string is just a tab.
In order to properly run the multi-threading implementations of our approaches you need to set the number of threads that you desire to use with:
julia --threads 16
where the number indicates the number of thread to use, for more information we refer to the official documentation: Starting Julia with multiple threads
To reproduce all the experiments you need to:
(i) Compute the exact percolation centrality values running the command julia --threads <nthreads> compute_exact_percolations.jl
(ii) Compute our algorithm's approximation, running julia --threads <nthreads> compute_progressive_cmcera.jl
(iii) Compute the Lima et al., progressive sampling algorithm's approximation, running julia --threads <nthreads> compute_progressive_era.jl
(iv) Compute the Lima et al., progressive sampling algorithm's approximation, running julia --threads <nthreads> compute_apx_fixed_ss.jl
where <nthreads> is the number of assigned threads.
All the results will be automatically saved in the scores and times folders.