>>>>> Ista Zahn
>>>>> on Fri, 14 Dec 2018 05:58:25 -0500 writes:
> This isn't Mac specific (I can reproduce it in Linux). Switching the
> igraph from version from 1.2.2 (slow) to 0.7.1 (fast) is enough, so
> this also has nothing to do with R itself. This should be reported to
> https://igraph.org/r/, either on the mailing list, bug tracker, or
> both.
> Best,
> Ista
Indeed (on Linux, too)
A much shorter (and 5x faster running) version of the repr.ex.
R script is appended (it uses specific .libPaths() to get the
correct version if igraph).
Martin
######################
### starts here
######################
#### compiling or not compiling doesn't change the relative speeds of the two
versions
## library(compiler)
## enableJIT(3)
## MM: Need different package libraries for different R versions
myLib <- file.path("/usr/local.nfs/app/R/R_local",
if(getRversion() <= "3.1.3")
"library-3.1.3"
else "library")
library(igraph, lib.loc = myLib)
#### a function used later
PlaytheGame <- function(i11, opp1) {
P <- sum(PayoffMatrix[strategy[i11], strategy[opp1]])
return(P/length(opp1))
} # Play the Game
#### set some parameters (this is a game theory simulation, played on a network)
### payoff matrix for the game
b <- 1.5
PayoffMatrix <- matrix(c(1,0,b,0),nrow=2,ncol=2,byrow=TRUE)
## each player plays Total Rounds of the game
TotalRounds <- 100
## number of agents
num <- 100
## density of the network
dens <- 0.10
avgdeg <- dens*num/2
## how many opponents to play at each round
numoppon <- 1
### create the networks to play the game on
## notice that these are here to test the speed of the simulation
## in principle they should be inside the repetitions loop.
## I moved them here to see if igraph is causing the problem,
## igraph is only called here now instead of each time the experiment repeats.
## Below you can see these commented out. You can check the effects of igraph
by uncommenting them below.
## I concluded the problem is not igraph. Sadly.
set.seed(101)# << MM: make truly reproducible
## create the networks to play on
repeat {
g <- erdos.renyi.game(num,dens)
if(is.connected(g))
break
} # repeat
g # the graph
neigh <- neighborhood(g, order = 1)
str(neigh, list.len = 7)
strategy <- sample(c(1,2), num, replace = TRUE)
## set aggregated payoffs to zero for each player
payoff <- rep(0,num)
Sys.setlocale("LC_MESSAGES", "C")# for portability of outputs
cat("Before experimental rounds start, current proc.time():\n"); proc.time()
## ##
## start time here
## ##
for(r in 1:TotalRounds) {
PayVector <- numeric(num) # << original was numeric(), which of course
# is "bad" .. but it's not the culprit
## for each player, make him play the game
for (i in 1:num) {
## he plays against his neighbours
n1 <- neigh[[i]][-1]
nopp <- max(length(n1), numoppon)
opp <- if(length(n1) > 1) sample(n1, nopp) else n1[1]
## # get a payoff from each opponent played and add to payoffs
PayVector[i] <- PlaytheGame(i,opp) # <<< uses "globals" PayoffMatrix,
strategy
}# i loop
## ## after everyone has played, pick one guy and revise his strategy
chosen.one <- sample(1:num,1)
## for the sake of debugging just change strategy randomly
strategy[chosen.one] <- sample(c(0,1),1)
## update payoff records
payoff <- payoff+PayVector
## # a single run of the experiment ends ends here
} # r loop
cat("Done", TotalRounds, "rounds; current proc.time():\n")
proc.time()
sessionInfo() # here, just in case more packages are loaded, etc
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