Last active
May 15, 2016 23:43
-
-
Save mbq/6a2443990c526973ad40debd001da835 to your computer and use it in GitHub Desktop.
Code to reproduce https://mbq.me/blog/nomads/
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
source('nomads.R'); | |
library(ggplot2); | |
library(brew); | |
#Run simulationA, but only once | |
if(!exists("simA")) | |
simulationA()->simA; | |
#Plot | |
ptA<-ggplot(simA,aes(y=Distance,fill=Solution,x=p))+ | |
geom_hline(yintercept=1/7)+ | |
geom_boxplot(outlier.size=NA)+ | |
theme(legend.position="bottom"); | |
print(ptA); | |
#Make SVG animations | |
brew('nom2.brew.svg','nom2.svg'); | |
brew('nom3.brew.svg','nom3.svg'); |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
#Generate votes, as complex numbers | |
generateVotes<-function(N=500,p=0.3) | |
exp(1i*ifelse(p<runif(N), | |
runif(N,0,2*pi), #Those who have no idea | |
rnorm(N,0,5/180*pi) #Those who know, with a small deviation of sd=5deg | |
)) | |
distance<-function(z) | |
abs(z-(1+0i)) | |
vote<-function(z){ | |
sum(z)->z | |
return(z/abs(z)) | |
} | |
baselineDistance<-function(trials=1000,...) | |
distance(exp(1i*runif(trials,0,2*pi))) | |
singleDistance<-function(trials=1000,p=0.3,...) | |
distance(sample(generateVotes(N=trials,p))) | |
ensembleDistance<-function(trials=1000,N=500,p=0.3,...) | |
replicate(trials,distance(vote(generateVotes(N,p)))) | |
#Make simulation | |
simulationA<-function(trials=10000,p=c(.01,.03,.05,.1,.3,.5,.7,.75,.8)){ | |
BD<-data.frame( | |
p=0, | |
Solution="Random direction", | |
Distance=baselineDistance(trials) | |
); | |
RD<-do.call(rbind,lapply(p,function(p) | |
data.frame( | |
p=p, | |
Solution="Single nomad", | |
Distance=singleDistance(trials,p) | |
) | |
)); | |
VD500<-do.call(rbind,lapply(p,function(p) | |
data.frame( | |
p=p, | |
Solution="Ensemble voting 500", | |
Distance=ensembleDistance(trials,500,p) | |
) | |
)); | |
VD5k<-do.call(rbind,lapply(p,function(p) | |
data.frame( | |
p=p, | |
Solution="Ensemble voting 5k", | |
Distance=ensembleDistance(trials,5000,p) | |
) | |
)); | |
rbind(BD,RD,VD500,VD5k)->U; | |
U$p<-factor(U$p); | |
U | |
} | |
#Generate "hedgehog" plots as SVG paths, for nom2.brew.svg | |
genPath<-function(z,r=90) | |
paste(sprintf("M0,0L%0.1f,%0.1f",r*Re(z),r*Im(z)),collapse="") | |
genPaths<-function(N=50,p=0.01){ | |
ans<-list(); | |
exp(1i*runif(floor(N*(1-p)),0,2*pi))->ans$guessing; | |
exp(1i*rnorm(ceiling(N*p),0,5/180*pi))->ans$knowing; | |
#Voting result | |
sum(c(ans$guessing,ans$knowing))->vote; | |
#Vector averages of both, normalised | |
sum(ans$guessing)/abs(vote)->ans$ave_guess; | |
sum(ans$knowing)/abs(vote)->ans$ave_know; | |
#Final, normalised direction | |
vote/abs(vote)->ans$vote; | |
lapply(ans,genPath) | |
} | |
genPathsCelebrity<-function(N=50,p=0.01){ | |
ans<-list(); | |
exp(1i*rnorm(floor(N*(1-p)),runif(1,0,2*pi),1.5))->ans$guessing; | |
exp(1i*rnorm(ceiling(N*p),0,5/180*pi))->ans$knowing; | |
#Voting result | |
sum(c(ans$guessing,ans$knowing))->vote; | |
#Vector averages of both, normalised | |
sum(ans$guessing)/abs(vote)->ans$ave_guess; | |
sum(ans$knowing)/abs(vote)->ans$ave_know; | |
#Final, normalised direction | |
vote/abs(vote)->ans$vote; | |
lapply(ans,genPath) | |
} |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment