d0 <- read.csv("bart16eAllData.csv", sep = ",")
d0 <- d0[d0$SourceE == "3D",]
d0 <- droplevels(d0)
d0$ht <- as.factor(d0$ht)
d0$Cyclone <- as.factor(d0$Cyclone)
pdf("box1.pdf")
boxplot(d0$E ~d0$ht + d0$Cyclone,ylab="Collection efficiency")
dev.off()

mean(d0$E[d0$Cyclone == "L" & d0$ht == 0])
mean(d0$E[d0$Cyclone == "M" & d0$ht == 0])
mean(d0$E[d0$Cyclone == "S" & d0$ht == 0])
mean(d0$E[d0$Cyclone == "L" & d0$ht == 35])
mean(d0$E[d0$Cyclone == "M" & d0$ht == 35])
mean(d0$E[d0$Cyclone == "S" & d0$ht == 35])
mean(d0$E[d0$Cyclone == "L" & d0$ht == 44])
mean(d0$E[d0$Cyclone == "M" & d0$ht == 44])
mean(d0$E[d0$Cyclone == "S" & d0$ht == 44])

sd(d0$E[d0$Cyclone == "L" & d0$ht == 0])
sd(d0$E[d0$Cyclone == "M" & d0$ht == 0])
sd(d0$E[d0$Cyclone == "S" & d0$ht == 0])
sd(d0$E[d0$Cyclone == "L" & d0$ht == 35])
sd(d0$E[d0$Cyclone == "M" & d0$ht == 35])
sd(d0$E[d0$Cyclone == "S" & d0$ht == 35])
sd(d0$E[d0$Cyclone == "L" & d0$ht == 44])
sd(d0$E[d0$Cyclone == "M" & d0$ht == 44])
sd(d0$E[d0$Cyclone == "S" & d0$ht == 44])


# remove outliers:
d2 <- d0[d0$E < 100 & d0$E > 50,]
d2 <- droplevels(d2)
boxplot(d2$E ~d2$ht + d2$Cyclone)

mean(d2$E[d2$Cyclone == "L" & d2$ht == 0])
mean(d2$E[d2$Cyclone == "M" & d2$ht == 0])
mean(d2$E[d2$Cyclone == "S" & d2$ht == 0])
mean(d2$E[d2$Cyclone == "L" & d2$ht == 35])
mean(d2$E[d2$Cyclone == "M" & d2$ht == 35])
mean(d2$E[d2$Cyclone == "S" & d2$ht == 35])
mean(d2$E[d2$Cyclone == "L" & d2$ht == 44])
mean(d2$E[d2$Cyclone == "M" & d2$ht == 44])
mean(d2$E[d2$Cyclone == "S" & d2$ht == 44])

sd(d2$E[d2$Cyclone == "L" & d2$ht == 0])
sd(d2$E[d2$Cyclone == "M" & d2$ht == 0])
sd(d2$E[d2$Cyclone == "S" & d2$ht == 0])
sd(d2$E[d2$Cyclone == "L" & d2$ht == 35])
sd(d2$E[d2$Cyclone == "M" & d2$ht == 35])
sd(d2$E[d2$Cyclone == "S" & d2$ht == 35])
sd(d2$E[d2$Cyclone == "L" & d2$ht == 44])
sd(d2$E[d2$Cyclone == "M" & d2$ht == 44])
sd(d2$E[d2$Cyclone == "S" & d2$ht == 44])