library(StratTourn) library(xtable) library(ggplot2) library(reshape2) library(googleVis) library(tidyr)
library(StratTourn) library(xtable) library(shiny) library(dplyr) setwd("D:/libraries/StratTourn/studies") name = "Tourn_Noisy_PD_20141020_170203" tourn = load.tournament(paste0(name,".tou")) # Data for each match md = tourn$dt md = add.other.var(md,c("strat","u")) md$delta.u = md$u - md$other.u # Names of all strategies strats = unique(md$strat) # Data for each round file = paste0(name,"_rs.csv") rd = fread(file) rd = as.tbl(as.data.frame(rd)) rd = add.other.var(rd,c("strat","u")) # Names of all strategies strats = unique(rd$strat) # Perhaps select a subset of strategies used.strats = strats ard = rd if (!identical(used.strats,strats)) { rows = rd$strat %in% used.strats & rd$other.strat %in% used.strats rd = ard[rows,] }
end.t = 150 start.t = 1
restore.point("payoffs.over.time.within.report") srd = filter(rd, strat==other.strat) td = summarise(group_by(srd,strat,t), u=mean(u), num.obs = length(t)) td = as.data.frame(td) t.seq = start.t:min(max(td$t),end.t) tsd = do(group_by(td, strat), get.smoothed.vals(.,xout=t.seq, xvar="t",yvar=c("u"), wvar="num.obs", spar=0.2)) tsd$Strat = tsd$strat tsd$t = tsd$t+1900 state = ' {"nonSelectedAlpha":0.4,"duration":{"multiplier":1,"timeUnit":"Y"},"sizeOption":"_UNISIZE","uniColorForNonSelected":false,"xZoomedDataMin":-2177452800000,"yLambda":1,"time":"1951","playDuration":15000,"colorOption":"2","showTrails":false,"yZoomedDataMin":-0.4,"xZoomedIn":false,"orderedByX":false,"orderedByY":false,"xZoomedDataMax":-599616000000,"xLambda":1,"yZoomedIn":false,"yZoomedDataMax":16,"yAxisOption":"3","iconType":"LINE","xAxisOption":"_TIME","dimensions":{"iconDimensions":["dim0"]}} ' tsd = as.data.frame(tsd) tsd$const = 1 tsd$const2 = 1 p = gvisMotionChart(tsd, idvar = "Strat", timevar = "t", xvar = "u", yvar = "u", colorvar = "strat", sizevar = "const", options = list(state=state)) #plot(p) print(p, tag="chart")
We show the payoffs of each strategy against itself. Note that we have fewer observations for later periods t (see plot below).
t.obs = tabulate(srd$t) / 2 plot(t.obs, xlab="t",ylab="matches (log scale)",main="Number of matches with a period t",log="y") grid(nx = NA, ny = NULL, col = "lightgray", lty = "dotted", lwd = par("lwd"), equilogs = TRUE)
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