# Set up the data objects used in the examples # ------------ gait -------------------------- hip <- matrix(scan("hip.txt", 0), 20, 39) knee <- matrix(scan("knee.txt", 0), 20, 39) # set up a three-dimensional array of function values gait <- array(0, c(20, 39, 2)) dimnames(gait) <- list(NULL, NULL, c("Hip Angle", "Knee Angle")) gait[,,1] <- hip gait[,,2] <- knee save(gait, file="gait.rda", compress=TRUE) # ------------ goods index -------------------------- temp <- matrix(scan("nondurprod.txt",0), 18, 81) tempmat <- temp[2:13,] tempmat[12,81] <- 0 nondurables <- matrix(tempmat, 12*81, 1) nondurables <- nondurables[1:971] ndur <- 971 # for completeness, make dec 99 equal to dec 98, jan 00 equal to jan 99 nondurables <- c(nondurables,nondurables[961]) nondurables <- c(nondurables,nondurables[962]) ndur <- 973 save(nondurables, file="nondurables.rda", compress=TRUE) # ------------ Berkeley growth -------------------------- ncasem <- 39 ncasef <- 54 nage <- 31 hgtm <- t(matrix(scan("hgtm.txt", 0), ncasem, byrow=TRUE)) hgtf <- t(matrix(scan("hgtf.txt", 0), ncasef, byrow=TRUE)) age <- c( seq(1, 2, 0.25), seq(3, 8, 1), seq(8.5, 18, 0.5)) growth <- list(hgtm=hgtm, hgtf=hgtf, age=age) save(growth, file="growth.rda", compress=TRUE) # ------------ handwriting -------------------------- temp <- array(scan("fdareg.txt",0), c(20,2,1401)) # set up a three-dimensional array handwrit <- array(0, c(1401, 20, 2)) handwrit[,,1] <- t(temp[,1,])/1000 handwrit[,,2] <- t(temp[,2,])/1000 dimnames(handwrit) <- list(NULL, NULL, c("X", "Y") ) save(handwrit, file="handwrit.rda", compress=TRUE) # ------------ lip -------------------------- lip <- matrix(scan("lip.txt", 0), 51, 20) save(lip, file="lip.rda", compress=TRUE) # ------------ melanoma -------------------------- tempmat <- t(matrix(scan("melanoma.txt", 0), 3, 37)) colnames(tempmat) <- c("index","year","melanoma") melanoma <- as.data.frame(tempmat) save(melanoma, file="melanoma.rda", compress=TRUE) # ------------ pinch -------------------------- pinch <- matrix(scan("pinch.txt",0), 151, 20, byrow=TRUE) save(pinch, file="pinch.rda", compress=TRUE) # ------------ refinery -------------------------- refinery <- t(matrix(scan("refinery.txt", 0), 3)) #tval <- refinery[,1] # observation time #uval <- refinery[,2] # reflux flow #yval <- refinery[,3] # tray 47 level colnames(refinery) <- c("tval", "uval", "yval") refinery <- as.data.frame(refinery) # center the data on mean values prior to change refinery <- transform(refinery, yval = yval - mean(yval[1:60]), uval = uval - mean(uval[1:60]) ) save(refinery, file="refinery.rda", compress=TRUE) # ------------ daily weather -------------------------- tempav <- matrix(scan("dailtemp.txt",0), 365, 35) precav <- matrix(scan("dailprec.txt",0), 365, 35) # define 11-character names for stations place <- c( "Arvida ", "Bagottville", "Calgary ", "Charlottvl ", "Churchill ", "Dawson ", "Edmonton ", "Fredericton", "Halifax ", "Inuvik ", "Iqaluit ", "Kamloops ", "London ", "Montreal ", "Ottawa ", "Pr. Albert ", "Pr. George ", "Pr. Rupert ", "Quebec ", "Regina ", "Resolute ", "Scheffervll", "Sherbrooke ", "St. Johns ", "Sydney ", "The Pas ", "Thunderbay ", "Toronto ", "Uranium Cty", "Vancouver ", "Victoria ", "Whitehorse ", "Winnipeg ", "Yarmouth ", "Yellowknife") dimnames(tempav) <- list(NULL,place) dimnames(precav) <- list(NULL,place) # set up indices that order the stations from east to west to north geogindex <- c(24, 9, 25, 34, 4, 8, 22, 1, 2, 19, 23, 14, 15, 28, 13, 27, 33, 26, 5, 20, 16, 29, 7, 3, 12, 30, 31, 17, 18, 32, 6, 35, 11, 10, 21) # put the stations in geographical order, from east to west to north # rather in the original alphatical order. library(gdata) Place <- trim(place) CanadianWeather <- daily library(gdata) (place <- trim(daily$place)) CanadianWeather$place <- place dimnames(CanadianWeather$tempav)[[2]] <- place dimnames(CanadianWeather$precav)[[2]] <- place daysPerMonth <- rep(31, 12) names(daysPerMonth) <- c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec") daysPerMonth[c("Sep", "Apr", "Jun", "Nov")] <- 30 daysPerMonth["Feb"] <- 28 CanadianWeather$month365 <- rep(names(daysPerMonth), daysPerMonth) CanadianWeather$dayOfYear <- 1:365 Mon. <- with(CanadianWeather, tapply(dayOfYear, month365, mean)) oM <- order(Mon.) CanadianWeather$Month <- Mon.[oM] CanadianWeather$monthlyTemp <- (with(CanadianWeather, apply(tempav, 2, function(x)tapply(x, month365, mean)) )[oM,]) CanadianWeather$monthlyPrecip <- (with(CanadianWeather, apply(precav, 2, function(x)tapply(x, month365, mean)) )[oM, ]) CanadianWeather$geogindex <- geogindex save(CanadianWeather, file="CanadianWeather.rda", compress=TRUE) str(CanadianWeather) tempav <- tempav[,geogindex] precav <- precav[,geogindex] place <- place[geogindex] daily <- list(place=place, tempav=tempav, precav=precav) save(daily, file="daily.rda", compress=TRUE)