CatPlex <-
function (myData, foldLen=24, Debug=F) {
# filter, Ycolumn, time column, alpha in window formula
#library("signal", lib.loc="/Library/Frameworks/R.framework/Versions/2.15/Resources/library")
data<-vector(length=length(myData),mode="numeric")
#data$time.n=as.numeric(myData[]) # this is done only to prime the vector for later use ( so it doesn't give an error)
dataN<-length(myData)
str(myData)
#write.matrix(dfData, file = "~/R_WD/testDataFile.txt", sep = ",")
avgIndexes <-factor(rep(1:foldLen, length = dataN))
Plex <- by(myData, avgIndexes, mean)
#--opar = par()
opar = par()
layout(matrix(c(1,2), 2, 1, byrow = TRUE),
widths=c(1), heights=c(1,1))
par(mar=c(2,4,1,1), oma=c(1,0,0,0))
plot(myData,ylab="data", type="l",bty='n')
pplex<-t(Plex[]) #Plex is a list: Plex[[1]] gives first col; t rotates it so a col is all means.
plot(c(1:foldLen)*6,pplex[1:foldLen], ylab=paste("folded over",foldLen), type="l",bty='n')
data$Observation<-myData[]
data$ObservationHr<-avgIndexes
aov.ex1 = aov(Observation~ObservationHr,data=data) #do the analysis of variance
print("SUMMARY")
print(summary(aov.ex1)) #display Type I ANOVA table
print(coefficients(aov.ex1))
print(model.tables(aov.ex1,"means",se=TRUE),digits=6) #report the means and the number of subjects/cell
print("TUKEY")
# Tukey Honestly Significant Differences
TukeyHSD(aov.ex1)
print("DROP1")
drop1(aov.ex1,~.,test="F") # type III SS and F Tests
boxplot(Observation~ObservationHr,data=data) #graphical summary
layout(matrix(c(1,2,3,4),2,2)) # optional layout
plot(aov.ex1) # diagnostic plots
browser()
#remove read only list components
opar$cin<-NULL
opar$cra<-NULL
opar$csi<-NULL
opar$cxy<-NULL
opar$din<-NULL
opar$page<-NULL
par(opar)
return(list(data=pplex))
end
}
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