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[igraph] igraph all_simple_paths processing time efficiency in R


From: Daniel Filipe Da Silva Pereira
Subject: [igraph] igraph all_simple_paths processing time efficiency in R
Date: Mon, 7 May 2018 14:30:51 +0200

Good afternoon,

I'm using the function all_simple_paths from the igraph R package: (1) to generate the list of all simple paths in networks; and (2) to calculate the total number of simple paths.

I'm using the function in the form:

pathsMp <- unlist(lapply(V(graphMp), function(x)all_simple_paths(graphMp, from = x)), recursive =FALSE)

List_paths_Mp <- lapply(1:length(pathsMp), function(x)as_ids(pathsMp[[x]]))

n_paths<-length(List_paths_Mp)

The function does what I need, but with the increase in the number of variables and interactions the processing time grows too much and it takes very long to get the results. In particular, using a network with 11 variables and 60 interactions, there is a total of 146338 possible simple paths. And this already takes a long time to compute. Using a bigger network, with 13 variables and 91 interactions, causes the program to take even longer times to process (after half hour the function still didn't run its course).

Is there a way to increase the efficiency of the task (i.e. to get results in a faster way)? Has anyone ever encountered a similar problem and found a solution? And, I know, I could use a CPU with higher processing power, but the point is to have the function to run efficiently (as much as possible) in a normal personal computer.


Kind regards, 
Daniel Pereira
PhD visiting Student at GEOMAR - Helmholtz Centre for Ocean Research Kiel
D├╝sternbrooker Weg 20
24105 Kiel, Germany

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