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#
# depvar_not_log.R, 13 Jul 16
#
# Data from:
# On the variation and specialisation of workload - A case study of the Gnome ecosystem community
# Bogdan Vasilescu and Alexander Serebrenik and Mathieu Goeminne and Tom Mens
#
# Example from:
# Empirical Software Engineering using R
# Derek M. Jones
source("ESEUR_config.r")
plot_layout(2, 1)
pal_col=rainbow(3)
aw_path = paste0(ESEUR_dir, "regression/AW.csv.xz")
nta_path = paste0(ESEUR_dir, "regression/NTA.csv.xz")
AW = read.csv(file=aw_path, head=TRUE, sep=";")
NTA = read.csv(file=nta_path, head=TRUE, sep=";")
mdf = merge(AW, NTA)
# Ignore 'unknown' activities
# Authors with 14 activities become authors with 13 activities
mdf1 = mdf
mdf1[which(mdf1$NTA == 14),]$NTA = 13
plot(mdf1$NTA, mdf1$AW, log="y", col=point_col,
xlab="Activity types per author", ylab="Author workload\n")
plot(0, type="n", log="y",
xlim=c(0, 12), ylim=c(1e-3, 1e4),
xlab="Activity types per author", ylab="Ratio\n")
points(mdf1$NTA, mdf1$AW/mdf1$NTA, col=pal_col[1])
points(mdf1$NTA, mdf1$AW/mdf1$NTA^2, col=pal_col[2])
points(mdf1$NTA, mdf1$AW/exp(mdf1$NTA), col=pal_col[3])
legend(x="bottomleft", legend=c("Linear", "Quadratic", "Exponential"), bty="n", fill=pal_col, cex=1.2)