[igraph] igraph all_simple_paths processing time efficiency in R

[Daniel Filipe Da Silva Pereira]

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
DÃŒsternbrooker Weg 20
24105 Kiel, Germany