Nothing
R/plotAllABT_discrete.R
In AntibodyTiters: Antibody Titer Analysis of Vaccinated Patients
Defines functions
plotAllABT_discrete
plotAllABT_discrete <- function(objName = "inData", prefix = "",
dayStart = as.integer(NA), dayEnd = as.integer(NA), type = "M1", rainbow = FALSE, ylab = "Titer (AU)",
savePDF = FALSE, alphaFactor = 10, lwd = 2, lineAttrib = "", addPoints = FALSE,
orderOfCategories = "", lowessSmooth = FALSE, geometricMean = FALSE, lineForPre = FALSE, lineFor1st = FALSE,
logY = TRUE, PDFwidth = 8, PDFheight = 5, main = NULL, omitPreVac = FALSE, lineColDark = FALSE){
# orderOfCategories = c("young", "middle", "elderly")
if(is.null(main) == TRUE) main <- objName
if(inherits(get(objName), "ABT") != TRUE) stop("The class must be ABT\n")
if(is.na(dayStart) == FALSE & is.na(dayEnd) == FALSE & dayStart >= dayEnd){
stop("dayStart must be smaller than dayEnd")
}
if(prefix == ""){
fileName <- paste(objName, "_", type, "_All", ".pdf", sep = "")
}
if(prefix != ""){
fileName <- paste(prefix, "_", objName, "_", type, "_All",
".pdf", sep = "")
}
if(prefix == "" & lineAttrib != ""){
fileName <- paste(objName, "_", lineAttrib, "_", type, "_All", ".pdf", sep = "")
}
if(prefix != "" & lineAttrib != ""){
fileName <- paste(prefix, "_", objName, "_", lineAttrib, "_", type, "_All",
".pdf", sep = "")
}
temp <- get(objName)$DATA
pmax <- get(objName)$pmax
Attrib <- get(objName)$Attrib
if(lineAttrib != "" & orderOfCategories[1] != ""){
attributeCategories <- names(Attrib[[lineAttrib]])
if(length(attributeCategories) != length(orderOfCategories)){
stop(paste("Contents of orderOfCategories do not match those in the provided object ", objName, ".\n", sep = ""))
}
attributeCategories <- attributeCategories[order(attributeCategories)]
for(a in 1:length(attributeCategories)){
if(attributeCategories[a] != orderOfCategories[order(orderOfCategories)][a]){
stop(paste("Contents of orderOfCategories do not match those in the provided object ", objName, ".\n", sep = ""))
}
}
}
if(is.na(dayStart) == TRUE) shortestFromSecond <- get(objName)$shortestFromSecond
if(is.na(dayEnd) == TRUE) longestFromSecond <- get(objName)$longestFromSecond
if(is.na(dayStart) == FALSE) shortestFromSecond <- dayStart
if(is.na(dayEnd) == FALSE) longestFromSecond <- dayEnd
xlab <- "Months after second shot"
colNames <- character(length = 0)
x.labels <- character(length = 0)
post2ndDays <- as.integer(temp[["point3_yyyymmdd"]] - temp[["2nd_shot_yyyymmdd"]])
c <- 1
if(type == "M1"){
firstMonth <- min(ceiling(shortestFromSecond/30), ceiling(post2ndDays/30), na.rm = TRUE)
if(firstMonth == 0) firstMonth <- 1
lastMonth <- ceiling(longestFromSecond/30)
for(m in firstMonth:lastMonth){
colNames[c] <-paste("M1_", m, "_from2ndShot", sep = "")
x.labels[c] <- m
c <- c + 1
}
}
if(type == "M2"){
firstM2group <- min(ceiling(shortestFromSecond/60), ceiling(post2ndDays/60), na.rm = TRUE)
if(firstM2group == 0) firstM2group <- 1
lastM2group <- ceiling(longestFromSecond/60)
for(m in firstM2group: lastM2group){
M2start <- (m-1)*2 + 1
M2end <- (m-1)*2 + 2
colNames[c] <- paste("M2_", M2start, "-", M2end, "_from2ndShot", sep = "")
x.labels[c] <- paste(M2start, "-", M2end, sep = "")
c <- c + 1
}
}
if(type == "M3"){
firstM3group <- min(ceiling(shortestFromSecond/90), ceiling(post2ndDays/90), na.rm = TRUE)
if(firstM3group == 0) firstM3group <- 1
lastM3group <- ceiling(longestFromSecond/90)
for(m in firstM3group: lastM3group){
M3start <- (m-1)*3 + 1
M3end <- (m-1)*3 + 3
colNames[c] <- paste("M3_", M3start, "-", M3end, "_from2ndShot", sep = "")
x.labels[c] <- paste(M3start, "-", M3end, sep = "")
c <- c + 1
}
}
if(type == "M4"){
firstM4group <- min(ceiling(shortestFromSecond/120), ceiling(post2ndDays/120), na.rm = TRUE)
if(firstM4group == 0) firstM4group <- 1
lastM4group <- ceiling(longestFromSecond/120)
for(m in firstM4group: lastM4group){
M4start <- (m-1)*4 + 1
M4end <- (m-1)*4 + 4
colNames[c] <- paste("M4_", M4start, "-", M4end, "_from2ndShot", sep = "")
x.labels[c] <- paste(M4start, "-", M4end, sep = "")
c <- c + 1
}
}
if(type == "M6"){
firstM6group <- min(ceiling(shortestFromSecond/180), ceiling(post2ndDays/180), na.rm = TRUE)
if(firstM6group == 0) firstM6group <- 1
lastM6group <- ceiling(longestFromSecond/180)
for(m in firstM6group: lastM6group){
M6start <- (m-1)*6 + 1
M6end <- (m-1)*6 + 6
colNames[c] <- paste("M6_", M6start, "-", M6end, "_from2ndShot", sep = "")
x.labels[c] <- paste(M6start, "-", M6end, sep = "")
c <- c + 1
}
}
if(type != "M1" & type != "M2" & type != "M3" & type != "M4" & type != "M6") {
stop("type must be weeks, days, M1, M2, M3, M4 or M6.")
}
# x <- c(1:3, 4:(3+length(colNames)))
x <- c(1:2, 3:(2+length(colNames)))
# if(omitPreVac == FALSE) x <- c(1:2, 3:(2+length(colNames)))
# if(omitPreVac == TRUE) x <- c(-1, 2, 3:(2+length(colNames)))
# ylim <- c(0, max(temp[, grep(pattern = "score", colnames(temp))], na.rm = TRUE))
temp2 <- temp
patients.pop <- nrow(temp2)
# if(1 <= patients.pop && patients.pop <= 30) alpha <- 0.5
# if(30 < patients.pop && patients.pop <= 70) alpha <- 0.3
# if(70 < patients.pop) alpha <- 0.1
alpha <- round(1/patients.pop*alphaFactor, digits = 2)
if(alpha > 1) alpha <- 1
if(alphaFactor <= 0 | alphaFactor > 100){
stop("alphaFactor should be in a range from 1 to 100")
}
if(savePDF == TRUE) pdf(file = fileName, width = PDFwidth, height = PDFheight)
if(lineAttrib != "" & inherits(temp2[[lineAttrib]], "numeric") != TRUE){
categories <- names(Attrib[[lineAttrib]])
categories <- categories[order(categories)]
if(orderOfCategories[1] != "") categories <- orderOfCategories
COLs <- hcl.colors(n = length(categories), palette = "Dynamic", rev = TRUE, alpha = 0.8)
COLsDark <- rgb(t(col2rgb(COLs)/1.2), maxColorValue=255)
pointCOLs <- hcl.colors(n = length(categories), palette = "Dynamic", rev = TRUE, alpha = 0.3)
lineCOLs <- hcl.colors(n = length(categories), palette = "Dynamic", rev = TRUE, alpha = alpha)
}
total.scores <- temp2[, grep(pattern = "_score", x = colnames(temp2))]
if(logY == FALSE){
ymin <- min(total.scores, na.rm = TRUE)
ymax <- max(total.scores, na.rm = TRUE)
ymax <- ymax * 1.1
ylim <- c(ymin, ymax)
if(omitPreVac == FALSE){
plot(x = x, y = numeric(length = length(x)), ylim = ylim, main = main,
xaxt = "n", yaxt = "n", type = "n", xlab = xlab, ylab = ylab)
}
if(omitPreVac == TRUE){
plot(x = x[2:length(x)], y = numeric(length = length(x)-1), ylim = ylim, main = main,
xaxt = "n", yaxt = "n", type = "n", xlab = xlab, ylab = ylab)
}
FROM <- floor(ymin/10000)
# BY <- floor((ymax - ymin)/5/100)*10^floor(log(ymax, base = 10))
TO <- ceiling(ymax/10^(floor(log(ymax, base = 10))))*10^(floor(log(ymax, base = 10)))
# BY <- (TO - FROM)/5
BY <- ceiling((TO - FROM)/8/(10^floor(log((TO - FROM)/8, base = 10)))) * 10^floor(log((TO - FROM)/8, base = 10))
axis(2, at = seq(from = FROM, to = TO, by = BY), lwd = lwd)
}
if(logY == TRUE){
if(length(total.scores[total.scores == 0]) > 0){
temp.ymin <- min(total.scores[total.scores != 0 & is.na(total.scores) == FALSE])
addToY <- 10^(floor(log(temp.ymin*1000, base = 10))-3)
for(n in 1:ncol(total.scores)){
total.scores[total.scores[,n] == 0 & is.na(total.scores[,n]) == FALSE, n] <-
total.scores[total.scores[,n] == 0 & is.na(total.scores[,n]) == FALSE, n] + addToY
}
cat(addToY, " was added to the time points of score=0.\n", sep = "")
}
ymin <- min(total.scores[total.scores != 0 & is.na(total.scores) == FALSE])*0.9
ymax <- max(total.scores, na.rm = TRUE)
ymax <- ymax * 11 # 5
ylim <- c(ymin, ymax)
xtemp <- numeric(length = length(x))
xtemp[1:length(x)] <- 1
if(omitPreVac == FALSE){
plot(x = x, y = xtemp, ylim = ylim, main = main,
xaxt = "n", yaxt = "n", type = "n", xlab = xlab, ylab = ylab, log = "y")
}
if(omitPreVac == TRUE){
plot(x = x[2:length(x)], y = xtemp[2:length(x)], ylim = ylim, main = main,
xaxt = "n", yaxt = "n", type = "n", xlab = xlab, ylab = ylab, log = "y")
}
FROM <- floor(log(ymin, base = 10))
TO <- floor(log(ymax, base = 10))+1
AT <- integer(length = (TO - FROM + 1) * 10 - (TO - FROM))
for(i in 1:length(FROM:TO)){
p <- seq(FROM, TO, 1)[i]
if(p == FROM){
START <- ((i-1)*10+1)
END <- ((i-1)*10+10)
AT[START:END] <- seq(from = (10^p)/10, to = (10^(p+1))/10, by = (10^p)/10)
}
if(p != FROM){
START <- END
END <- END + 9
AT[START:END] <- seq(from = (10^p)/10, to = (10^(p+1))/10, by = (10^p)/10)
}
}
axis(2, at = AT, labels = FALSE, lwd = lwd/2)
AT <- integer(length = (TO - FROM + 1))
for(i in 1:length(FROM:TO)){
p <- seq(FROM, TO, 1)[i]
AT[i] <- (10^(p+1))/10
}
axis(2, at = AT, labels = formatC(AT, format = "g"), lwd = lwd)
if(length(AT) < 5){
AT <- integer(length = (TO - FROM + 1))
for(i in 1:length(FROM:TO)){
p <- seq(FROM, TO, 1)[i]
AT[i] <- (10^(p+1))/10*5
}
axis(2, at = AT, labels = formatC(AT, format = "g"), lwd = lwd)
}
}
if(omitPreVac == FALSE){
axis(1, at = 1:2, labels = c("pre", "1st"), lwd = lwd)
axis(1, at = 3:length(x), labels = x.labels, lwd = lwd)
}
if(omitPreVac == TRUE){
axis(1, at = c(-1, 2), labels = c("pre", "1st"), lwd = lwd)
axis(1, at = 3:length(x), labels = x.labels, lwd = lwd)
}
box(lwd = lwd)
patients.max <- nrow(temp2)+1
for(p in 1:nrow(temp2)){
patientID <- temp2$ID[p]
# temp2.scores <- as.numeric(temp2[p, grep(pattern = "score", colnames(temp2))][1:3])
temp2.scores <- as.numeric(temp2[p, grep(pattern = "score", colnames(temp2))][1:2])
for(c in 1:length(colNames)){
colName <- colNames[c]
# temp2.scores[3 + c] <- temp2[[colName]][p]
temp2.scores[2 + c] <- temp2[[colName]][p]
}
if(logY == TRUE){
if(length(temp2.scores[temp2.scores == 0 & is.na(temp2.scores) == FALSE]) > 0){
# temp.ymin <- min(temp2.scores[temp2.scores != 0 & is.na(temp2.scores) == FALSE])
# addToY <- 10^(floor(log(temp.ymin*1000, base = 10))-3)
temp2.scores[temp2.scores == 0 & is.na(temp2.scores) == FALSE] <-
temp2.scores[temp2.scores == 0 & is.na(temp2.scores) == FALSE] + addToY
# cat(addToY, " was added to the time points of score=0.\n", sep = "")
}
}
x.patient <- x[is.na(temp2.scores) == FALSE]
temp2.scores.patient <- temp2.scores[is.na(temp2.scores) == FALSE]
# if(omitPreVac == TRUE){
# x.patient <- x.patient[x.patient != 1]
# temp2.scores.patient <- temp2.scores.patient[x.patient != 1]
# }
if(rainbow == TRUE){
lines(x = x.patient,
y = temp2.scores.patient, lty = 1, lwd = lwd,
col = rainbow(1, start = p/patients.max, alpha = alpha))
}
if(rainbow == FALSE){
if(lineAttrib == "" | inherits(temp2[[lineAttrib]], "numeric") == TRUE){
lines(x = x.patient,
y = temp2.scores.patient, lty = 1, lwd = lwd, col = gray(0, alpha = alpha))
}
if(lineAttrib != "" & inherits(temp2[[lineAttrib]], "numeric") != TRUE){
c <- which(temp2[[lineAttrib]][p] == categories)
lines(x = x.patient,
y = temp2.scores.patient, lty = 1, lwd = lwd, col = lineCOLs[c])
}
}
}
if(lineAttrib != ""){
# require(DescTools)
if(length(grep(pattern = lineAttrib, x = names(Attrib))) == 0){
stop("lineAttrib must be found in the Attrib of the given ABT object")
}
if(inherits(temp2[[lineAttrib]], "numeric") == TRUE){
stop("lineAttrib cannot be applied for numeric values")
}
if(inherits(temp2[[lineAttrib]], "numeric") != TRUE){
for(c in 1:length(categories)){
temp3 <- subset(temp2, temp2[[lineAttrib]] == categories[c])
if(type == "M1") temp3.scores <- temp3[, grep(pattern = "M1_", colnames(temp3))]
if(type == "M2") temp3.scores <- temp3[, grep(pattern = "M2_", colnames(temp3))]
if(type == "M4") temp3.scores <- temp3[, grep(pattern = "M4_", colnames(temp3))]
if(type == "M3") temp3.scores <- temp3[, grep(pattern = "M3_", colnames(temp3))]
if(type == "M6") temp3.scores <- temp3[, grep(pattern = "M6_", colnames(temp3))]
RAW <- list()
if(type == "M1"){
firstMonth <- as.integer(strsplit(colNames[1], split = "_")[[1]][2])
lastMonth <- as.integer(strsplit(colNames[length(colNames)], split = "_")[[1]][2])
}
if(type != "M1"){
tempM <- strsplit(colNames[1], split = "_")[[1]][2]
firstMonth <- as.integer(strsplit(tempM, split = "-")[[1]][1])
tempM <- strsplit(colNames[length(colNames)], split = "_")[[1]][2]
lastMonth <- as.integer(strsplit(tempM, split = "-")[[1]][1])
}
RAW[["Pre"]] <- temp3$pre_vaccination_score
RAW[["Post1st"]] <- temp3$post_1st_shot_score
RAW[(firstMonth:lastMonth)+2] <- as.numeric(NA)
names(RAW)[(firstMonth:lastMonth)+2] <- firstMonth:lastMonth
for(m in 1:length(colNames)){
colName <- colNames[m]
if(type == "M1"){
Month <- as.character(strsplit(colName, split = "_")[[1]][2])
}
if(type != "M1"){
tempM <- strsplit(colName, split = "_")[[1]][2]
Month <- as.character(strsplit(tempM, split = "-")[[1]][1])
}
RAW[[Month]] <- temp3.scores[[colName]]
}
RAW <- RAW[is.na(RAW) == FALSE]
if(omitPreVac == TRUE){
RAW[["Pre"]] <- NA
}
if(addPoints == TRUE){
for(mx in 1:length(RAW)){
for(y in 1:length(RAW[[mx]])){
xShiftFactor <- 0.05 * length(x) /12
# shifted.x <- mx + 3 - ((length(categories) * xShiftFactor)/2) + (c-1) * xShiftFactor
shifted.x <- mx - ((length(categories) * xShiftFactor)/2) + (c-1) * xShiftFactor
points(x = shifted.x, y = RAW[[mx]][y], pch = 20, cex = 0.8, col = pointCOLs[c])
}
}
}
if(lowessSmooth == TRUE){
RAW2 <- data.frame(x = names(RAW))
RAW2$score <- NA
for(m in 1:length(RAW)){
rawValues <- RAW[[m]][is.na(RAW[[m]]) == FALSE & RAW[[m]] >= 0]
if(length(rawValues) > 0){
RAW2$score[m] <- mean(rawValues)
}
}
RAW3 <- subset(RAW2, is.na(RAW2$score) == FALSE)
# RAW3 <- RAW2
# RAW3$l <- lowess(RAW3)$y
if(logY == FALSE){
RAW3$l <- lowess(RAW3)$y
}
if(logY == TRUE){
RAW3$scoreLog <- log(RAW3$score, base = 10)
RAW3$lLog <- as.numeric(NA)
RAW3$lLog[-(1:2)] <- lowess(x = RAW3$x[-(1:2)], y = RAW3$scoreLog[-(1:2)])$y
RAW3$l <- 10^RAW3$lLog
}
# lowess.x <- x
lowess.x <- x[is.na(RAW2$score) == FALSE]
names(lowess.x) <- RAW3$x
if(lineForPre == FALSE){
RAW3 <- RAW3[RAW3$x != "Pre",]
lowess.x <- lowess.x[names(lowess.x) != "Pre"]
}
if(lineFor1st == FALSE){
RAW3 <- RAW3[RAW3$x != "Post1st",]
lowess.x <- lowess.x[names(lowess.x) != "Post1st"]
}
lowess.index <- is.na(RAW3$l) == FALSE
if(lineColDark == FALSE){
lines(x = lowess.x[lowess.index], y = RAW3$l[lowess.index], col = COLs[c], lwd = lwd*2)
}
if(lineColDark == TRUE){
lines(x = lowess.x[lowess.index], y = RAW3$l[lowess.index], col = COLsDark[c], lwd = lwd*2)
}
} # if(lowessSmooth == TRUE)
if(geometricMean == TRUE){
months <- seq(firstMonth, lastMonth, as.integer(strsplit(type, "M")[[1]][2]))
GMDF <- data.frame(x = c("Pre", "Post1st", as.character(months)), mean = as.numeric(NA),
lwr.ci = as.numeric(NA), upr.ci = as.numeric(NA))
tooLow <- 1
for(m in 1:length(RAW)){
rawValues <- RAW[[m]][is.na(RAW[[m]]) == FALSE & RAW[[m]] > 0]
# if(length(rawValues) > 1){
if(length(rawValues) > 2){
GmeanResult <- Gmean(rawValues, conf.level = 0.95, na.rm = TRUE)
GM <- GmeanResult[1]
if(is.na(GM) == FALSE) GMDF$mean[m] <- GM
LOWCI <- GmeanResult[2]
if(is.na(LOWCI) == FALSE) GMDF$lwr.ci[m] <- LOWCI
UPRCI <- GmeanResult[3]
if(is.na(UPRCI) == FALSE) GMDF$upr.ci[m] <- UPRCI
}
if(length(rawValues) <= 2){
if(m <= 2) DataPoint <- GMDF$x[m]
if(m > 2) DataPoint <- paste("M", GMDF$x[m], sep = "")
if(tooLow > 1) cat(paste(", ", DataPoint, sep = ""))
if(tooLow == 1){
cat(paste("Number of samples is too low (<3) for geometric mean calculation",
" of the category \"", categories[c], "\"\n", sep = ""))
cat(paste(" at ", DataPoint, sep = ""))
tooLow <- tooLow + 1
}
}
}
if(tooLow > 1) cat("\n")
GMs <- numeric(length = length(x))
GMs[1:length(GMs)] <- NA
LOWCIs <- numeric(length = length(x))
LOWCIs[1:length(LOWCIs)] <- NA
UPRCIs <- numeric(length = length(x))
UPRCIs[1:length(UPRCIs)] <- NA
for(m in 1:length(months)){
GMs[m] <- GMDF$mean[m]
LOWCIs[m] <- GMDF$lwr.ci[m]
UPRCIs[m] <- GMDF$upr.ci[m]
}
GMDF$x.axis <- x
GMDF <- GMDF[is.na(GMDF$mean) == FALSE, ]
if(lineForPre == FALSE) GMDF <- GMDF[GMDF$x != "Pre",]
if(lineFor1st == FALSE) GMDF <- GMDF[GMDF$x != "Post1st",]
for(l in 1:nrow(GMDF)){
xShiftFactor <- 0.05 * length(x) /12
shifted.x <- GMDF$x.axis[l] - ((length(categories) * xShiftFactor)/2) + (c-1) * xShiftFactor
if(lineColDark == FALSE){
lines(x = c(shifted.x, shifted.x),
y = c(GMDF$lwr.ci[l], GMDF$mean[l]), col = COLs[c], lwd = lwd)
lines(x = c(shifted.x-0.1, shifted.x +0.1),
y = c(GMDF$lwr.ci[l], GMDF$lwr.ci[l]), col = COLs[c], lwd = lwd)
lines(x = c(shifted.x, shifted.x),
y = c(GMDF$upr.ci[l], GMDF$mean[l]), col = COLs[c], lwd = lwd)
lines(x = c(shifted.x-0.1, shifted.x +0.1),
y = c(GMDF$upr.ci[l], GMDF$upr.ci[l]), col = COLs[c], lwd = lwd)
}
if(lineColDark == TRUE){
lines(x = c(shifted.x, shifted.x),
y = c(GMDF$lwr.ci[l], GMDF$mean[l]), col = COLsDark[c], lwd = lwd)
lines(x = c(shifted.x-0.1, shifted.x +0.1),
y = c(GMDF$lwr.ci[l], GMDF$lwr.ci[l]), col = COLsDark[c], lwd = lwd)
lines(x = c(shifted.x, shifted.x),
y = c(GMDF$upr.ci[l], GMDF$mean[l]), col = COLsDark[c], lwd = lwd)
lines(x = c(shifted.x-0.1, shifted.x +0.1),
y = c(GMDF$upr.ci[l], GMDF$upr.ci[l]), col = COLsDark[c], lwd = lwd)
}
}
shiftedX <- GMDF$x.axis - ((length(categories) * xShiftFactor)/2) + (c-1) * xShiftFactor
if(lineColDark == FALSE){
lines(x = shiftedX, y = GMDF$mean, col = COLs[c], lwd = lwd*2)
}
if(lineColDark == TRUE){
lines(x = shiftedX, y = GMDF$mean, col = COLsDark[c], lwd = lwd*2)
}
} # if(geometricMean == TRUE)
legendX <- 3+length(colNames) - (3+length(colNames))/3
# legendY <- ylim[2] - (ylim[2] - ylim[1])/10*c
if(logY == FALSE) legendY <- ylim[2] - (ylim[2] - ylim[1])/10*c
if(logY == TRUE) legendY <- 10^(log(ylim[2], base = 10) -
((log(ylim[2], base = 10) - log(ylim[1], base = 10))/15*(c))) # c+1 or c?
if(lineColDark == FALSE){
legend(x = legendX, y = legendY, col = COLs[c], lwd = lwd*2,
legend = categories[c], bty = "n")
}
if(lineColDark == TRUE){
legend(x = legendX, y = legendY, col = COLsDark[c], lwd = lwd*2,
legend = categories[c], bty = "n")
}
if(c == 1){
legendX <- 2+length(colNames) - (2+length(colNames))/4
# legendY <- ylim[2] - (ylim[2] - ylim[1])/10*c * 1.4
if(logY == FALSE) legendY <- ylim[2] - (ylim[2] - ylim[1])/10*c * 1.4
if(logY == TRUE) legendY <- 10^(log(ylim[2], base = 10) -
((log(ylim[2], base = 10) - log(ylim[1], base = 10))/20*(c+1))) # c+1
text(x = legendX, y = legendY, pos = 3, labels = lineAttrib)
}
}
}
}
if(savePDF == TRUE) dev.off()
}
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AntibodyTiters documentation built on May 24, 2022, 5:05 p.m.
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Defines functions plotAllABT_discrete
plotAllABT_discrete <- function(objName = "inData", prefix = "",
dayStart = as.integer(NA), dayEnd = as.integer(NA), type = "M1", rainbow = FALSE, ylab = "Titer (AU)",
savePDF = FALSE, alphaFactor = 10, lwd = 2, lineAttrib = "", addPoints = FALSE,
orderOfCategories = "", lowessSmooth = FALSE, geometricMean = FALSE, lineForPre = FALSE, lineFor1st = FALSE,
logY = TRUE, PDFwidth = 8, PDFheight = 5, main = NULL, omitPreVac = FALSE, lineColDark = FALSE){
# orderOfCategories = c("young", "middle", "elderly")
if(is.null(main) == TRUE) main <- objName
if(inherits(get(objName), "ABT") != TRUE) stop("The class must be ABT\n")
if(is.na(dayStart) == FALSE & is.na(dayEnd) == FALSE & dayStart >= dayEnd){
stop("dayStart must be smaller than dayEnd")
}
if(prefix == ""){
fileName <- paste(objName, "_", type, "_All", ".pdf", sep = "")
}
if(prefix != ""){
fileName <- paste(prefix, "_", objName, "_", type, "_All",
".pdf", sep = "")
}
if(prefix == "" & lineAttrib != ""){
fileName <- paste(objName, "_", lineAttrib, "_", type, "_All", ".pdf", sep = "")
}
if(prefix != "" & lineAttrib != ""){
fileName <- paste(prefix, "_", objName, "_", lineAttrib, "_", type, "_All",
".pdf", sep = "")
}
temp <- get(objName)$DATA
pmax <- get(objName)$pmax
Attrib <- get(objName)$Attrib
if(lineAttrib != "" & orderOfCategories[1] != ""){
attributeCategories <- names(Attrib[[lineAttrib]])
if(length(attributeCategories) != length(orderOfCategories)){
stop(paste("Contents of orderOfCategories do not match those in the provided object ", objName, ".\n", sep = ""))
}
attributeCategories <- attributeCategories[order(attributeCategories)]
for(a in 1:length(attributeCategories)){
if(attributeCategories[a] != orderOfCategories[order(orderOfCategories)][a]){
stop(paste("Contents of orderOfCategories do not match those in the provided object ", objName, ".\n", sep = ""))
}
}
}
if(is.na(dayStart) == TRUE) shortestFromSecond <- get(objName)$shortestFromSecond
if(is.na(dayEnd) == TRUE) longestFromSecond <- get(objName)$longestFromSecond
if(is.na(dayStart) == FALSE) shortestFromSecond <- dayStart
if(is.na(dayEnd) == FALSE) longestFromSecond <- dayEnd
xlab <- "Months after second shot"
colNames <- character(length = 0)
x.labels <- character(length = 0)
post2ndDays <- as.integer(temp[["point3_yyyymmdd"]] - temp[["2nd_shot_yyyymmdd"]])
c <- 1
if(type == "M1"){
firstMonth <- min(ceiling(shortestFromSecond/30), ceiling(post2ndDays/30), na.rm = TRUE)
if(firstMonth == 0) firstMonth <- 1
lastMonth <- ceiling(longestFromSecond/30)
for(m in firstMonth:lastMonth){
colNames[c] <-paste("M1_", m, "_from2ndShot", sep = "")
x.labels[c] <- m
c <- c + 1
}
}
if(type == "M2"){
firstM2group <- min(ceiling(shortestFromSecond/60), ceiling(post2ndDays/60), na.rm = TRUE)
if(firstM2group == 0) firstM2group <- 1
lastM2group <- ceiling(longestFromSecond/60)
for(m in firstM2group: lastM2group){
M2start <- (m-1)*2 + 1
M2end <- (m-1)*2 + 2
colNames[c] <- paste("M2_", M2start, "-", M2end, "_from2ndShot", sep = "")
x.labels[c] <- paste(M2start, "-", M2end, sep = "")
c <- c + 1
}
}
if(type == "M3"){
firstM3group <- min(ceiling(shortestFromSecond/90), ceiling(post2ndDays/90), na.rm = TRUE)
if(firstM3group == 0) firstM3group <- 1
lastM3group <- ceiling(longestFromSecond/90)
for(m in firstM3group: lastM3group){
M3start <- (m-1)*3 + 1
M3end <- (m-1)*3 + 3
colNames[c] <- paste("M3_", M3start, "-", M3end, "_from2ndShot", sep = "")
x.labels[c] <- paste(M3start, "-", M3end, sep = "")
c <- c + 1
}
}
if(type == "M4"){
firstM4group <- min(ceiling(shortestFromSecond/120), ceiling(post2ndDays/120), na.rm = TRUE)
if(firstM4group == 0) firstM4group <- 1
lastM4group <- ceiling(longestFromSecond/120)
for(m in firstM4group: lastM4group){
M4start <- (m-1)*4 + 1
M4end <- (m-1)*4 + 4
colNames[c] <- paste("M4_", M4start, "-", M4end, "_from2ndShot", sep = "")
x.labels[c] <- paste(M4start, "-", M4end, sep = "")
c <- c + 1
}
}
if(type == "M6"){
firstM6group <- min(ceiling(shortestFromSecond/180), ceiling(post2ndDays/180), na.rm = TRUE)
if(firstM6group == 0) firstM6group <- 1
lastM6group <- ceiling(longestFromSecond/180)
for(m in firstM6group: lastM6group){
M6start <- (m-1)*6 + 1
M6end <- (m-1)*6 + 6
colNames[c] <- paste("M6_", M6start, "-", M6end, "_from2ndShot", sep = "")
x.labels[c] <- paste(M6start, "-", M6end, sep = "")
c <- c + 1
}
}
if(type != "M1" & type != "M2" & type != "M3" & type != "M4" & type != "M6") {
stop("type must be weeks, days, M1, M2, M3, M4 or M6.")
}
# x <- c(1:3, 4:(3+length(colNames)))
x <- c(1:2, 3:(2+length(colNames)))
# if(omitPreVac == FALSE) x <- c(1:2, 3:(2+length(colNames)))
# if(omitPreVac == TRUE) x <- c(-1, 2, 3:(2+length(colNames)))
# ylim <- c(0, max(temp[, grep(pattern = "score", colnames(temp))], na.rm = TRUE))
temp2 <- temp
patients.pop <- nrow(temp2)
# if(1 <= patients.pop && patients.pop <= 30) alpha <- 0.5
# if(30 < patients.pop && patients.pop <= 70) alpha <- 0.3
# if(70 < patients.pop) alpha <- 0.1
alpha <- round(1/patients.pop*alphaFactor, digits = 2)
if(alpha > 1) alpha <- 1
if(alphaFactor <= 0 | alphaFactor > 100){
stop("alphaFactor should be in a range from 1 to 100")
}
if(savePDF == TRUE) pdf(file = fileName, width = PDFwidth, height = PDFheight)
if(lineAttrib != "" & inherits(temp2[[lineAttrib]], "numeric") != TRUE){
categories <- names(Attrib[[lineAttrib]])
categories <- categories[order(categories)]
if(orderOfCategories[1] != "") categories <- orderOfCategories
COLs <- hcl.colors(n = length(categories), palette = "Dynamic", rev = TRUE, alpha = 0.8)
COLsDark <- rgb(t(col2rgb(COLs)/1.2), maxColorValue=255)
pointCOLs <- hcl.colors(n = length(categories), palette = "Dynamic", rev = TRUE, alpha = 0.3)
lineCOLs <- hcl.colors(n = length(categories), palette = "Dynamic", rev = TRUE, alpha = alpha)
}
total.scores <- temp2[, grep(pattern = "_score", x = colnames(temp2))]
if(logY == FALSE){
ymin <- min(total.scores, na.rm = TRUE)
ymax <- max(total.scores, na.rm = TRUE)
ymax <- ymax * 1.1
ylim <- c(ymin, ymax)
if(omitPreVac == FALSE){
plot(x = x, y = numeric(length = length(x)), ylim = ylim, main = main,
xaxt = "n", yaxt = "n", type = "n", xlab = xlab, ylab = ylab)
}
if(omitPreVac == TRUE){
plot(x = x[2:length(x)], y = numeric(length = length(x)-1), ylim = ylim, main = main,
xaxt = "n", yaxt = "n", type = "n", xlab = xlab, ylab = ylab)
}
FROM <- floor(ymin/10000)
# BY <- floor((ymax - ymin)/5/100)*10^floor(log(ymax, base = 10))
TO <- ceiling(ymax/10^(floor(log(ymax, base = 10))))*10^(floor(log(ymax, base = 10)))
# BY <- (TO - FROM)/5
BY <- ceiling((TO - FROM)/8/(10^floor(log((TO - FROM)/8, base = 10)))) * 10^floor(log((TO - FROM)/8, base = 10))
axis(2, at = seq(from = FROM, to = TO, by = BY), lwd = lwd)
}
if(logY == TRUE){
if(length(total.scores[total.scores == 0]) > 0){
temp.ymin <- min(total.scores[total.scores != 0 & is.na(total.scores) == FALSE])
addToY <- 10^(floor(log(temp.ymin*1000, base = 10))-3)
for(n in 1:ncol(total.scores)){
total.scores[total.scores[,n] == 0 & is.na(total.scores[,n]) == FALSE, n] <-
total.scores[total.scores[,n] == 0 & is.na(total.scores[,n]) == FALSE, n] + addToY
}
cat(addToY, " was added to the time points of score=0.\n", sep = "")
}
ymin <- min(total.scores[total.scores != 0 & is.na(total.scores) == FALSE])*0.9
ymax <- max(total.scores, na.rm = TRUE)
ymax <- ymax * 11 # 5
ylim <- c(ymin, ymax)
xtemp <- numeric(length = length(x))
xtemp[1:length(x)] <- 1
if(omitPreVac == FALSE){
plot(x = x, y = xtemp, ylim = ylim, main = main,
xaxt = "n", yaxt = "n", type = "n", xlab = xlab, ylab = ylab, log = "y")
}
if(omitPreVac == TRUE){
plot(x = x[2:length(x)], y = xtemp[2:length(x)], ylim = ylim, main = main,
xaxt = "n", yaxt = "n", type = "n", xlab = xlab, ylab = ylab, log = "y")
}
FROM <- floor(log(ymin, base = 10))
TO <- floor(log(ymax, base = 10))+1
AT <- integer(length = (TO - FROM + 1) * 10 - (TO - FROM))
for(i in 1:length(FROM:TO)){
p <- seq(FROM, TO, 1)[i]
if(p == FROM){
START <- ((i-1)*10+1)
END <- ((i-1)*10+10)
AT[START:END] <- seq(from = (10^p)/10, to = (10^(p+1))/10, by = (10^p)/10)
}
if(p != FROM){
START <- END
END <- END + 9
AT[START:END] <- seq(from = (10^p)/10, to = (10^(p+1))/10, by = (10^p)/10)
}
}
axis(2, at = AT, labels = FALSE, lwd = lwd/2)
AT <- integer(length = (TO - FROM + 1))
for(i in 1:length(FROM:TO)){
p <- seq(FROM, TO, 1)[i]
AT[i] <- (10^(p+1))/10
}
axis(2, at = AT, labels = formatC(AT, format = "g"), lwd = lwd)
if(length(AT) < 5){
AT <- integer(length = (TO - FROM + 1))
for(i in 1:length(FROM:TO)){
p <- seq(FROM, TO, 1)[i]
AT[i] <- (10^(p+1))/10*5
}
axis(2, at = AT, labels = formatC(AT, format = "g"), lwd = lwd)
}
}
if(omitPreVac == FALSE){
axis(1, at = 1:2, labels = c("pre", "1st"), lwd = lwd)
axis(1, at = 3:length(x), labels = x.labels, lwd = lwd)
}
if(omitPreVac == TRUE){
axis(1, at = c(-1, 2), labels = c("pre", "1st"), lwd = lwd)
axis(1, at = 3:length(x), labels = x.labels, lwd = lwd)
}
box(lwd = lwd)
patients.max <- nrow(temp2)+1
for(p in 1:nrow(temp2)){
patientID <- temp2$ID[p]
# temp2.scores <- as.numeric(temp2[p, grep(pattern = "score", colnames(temp2))][1:3])
temp2.scores <- as.numeric(temp2[p, grep(pattern = "score", colnames(temp2))][1:2])
for(c in 1:length(colNames)){
colName <- colNames[c]
# temp2.scores[3 + c] <- temp2[[colName]][p]
temp2.scores[2 + c] <- temp2[[colName]][p]
}
if(logY == TRUE){
if(length(temp2.scores[temp2.scores == 0 & is.na(temp2.scores) == FALSE]) > 0){
# temp.ymin <- min(temp2.scores[temp2.scores != 0 & is.na(temp2.scores) == FALSE])
# addToY <- 10^(floor(log(temp.ymin*1000, base = 10))-3)
temp2.scores[temp2.scores == 0 & is.na(temp2.scores) == FALSE] <-
temp2.scores[temp2.scores == 0 & is.na(temp2.scores) == FALSE] + addToY
# cat(addToY, " was added to the time points of score=0.\n", sep = "")
}
}
x.patient <- x[is.na(temp2.scores) == FALSE]
temp2.scores.patient <- temp2.scores[is.na(temp2.scores) == FALSE]
# if(omitPreVac == TRUE){
# x.patient <- x.patient[x.patient != 1]
# temp2.scores.patient <- temp2.scores.patient[x.patient != 1]
# }
if(rainbow == TRUE){
lines(x = x.patient,
y = temp2.scores.patient, lty = 1, lwd = lwd,
col = rainbow(1, start = p/patients.max, alpha = alpha))
}
if(rainbow == FALSE){
if(lineAttrib == "" | inherits(temp2[[lineAttrib]], "numeric") == TRUE){
lines(x = x.patient,
y = temp2.scores.patient, lty = 1, lwd = lwd, col = gray(0, alpha = alpha))
}
if(lineAttrib != "" & inherits(temp2[[lineAttrib]], "numeric") != TRUE){
c <- which(temp2[[lineAttrib]][p] == categories)
lines(x = x.patient,
y = temp2.scores.patient, lty = 1, lwd = lwd, col = lineCOLs[c])
}
}
}
if(lineAttrib != ""){
# require(DescTools)
if(length(grep(pattern = lineAttrib, x = names(Attrib))) == 0){
stop("lineAttrib must be found in the Attrib of the given ABT object")
}
if(inherits(temp2[[lineAttrib]], "numeric") == TRUE){
stop("lineAttrib cannot be applied for numeric values")
}
if(inherits(temp2[[lineAttrib]], "numeric") != TRUE){
for(c in 1:length(categories)){
temp3 <- subset(temp2, temp2[[lineAttrib]] == categories[c])
if(type == "M1") temp3.scores <- temp3[, grep(pattern = "M1_", colnames(temp3))]
if(type == "M2") temp3.scores <- temp3[, grep(pattern = "M2_", colnames(temp3))]
if(type == "M4") temp3.scores <- temp3[, grep(pattern = "M4_", colnames(temp3))]
if(type == "M3") temp3.scores <- temp3[, grep(pattern = "M3_", colnames(temp3))]
if(type == "M6") temp3.scores <- temp3[, grep(pattern = "M6_", colnames(temp3))]
RAW <- list()
if(type == "M1"){
firstMonth <- as.integer(strsplit(colNames[1], split = "_")[[1]][2])
lastMonth <- as.integer(strsplit(colNames[length(colNames)], split = "_")[[1]][2])
}
if(type != "M1"){
tempM <- strsplit(colNames[1], split = "_")[[1]][2]
firstMonth <- as.integer(strsplit(tempM, split = "-")[[1]][1])
tempM <- strsplit(colNames[length(colNames)], split = "_")[[1]][2]
lastMonth <- as.integer(strsplit(tempM, split = "-")[[1]][1])
}
RAW[["Pre"]] <- temp3$pre_vaccination_score
RAW[["Post1st"]] <- temp3$post_1st_shot_score
RAW[(firstMonth:lastMonth)+2] <- as.numeric(NA)
names(RAW)[(firstMonth:lastMonth)+2] <- firstMonth:lastMonth
for(m in 1:length(colNames)){
colName <- colNames[m]
if(type == "M1"){
Month <- as.character(strsplit(colName, split = "_")[[1]][2])
}
if(type != "M1"){
tempM <- strsplit(colName, split = "_")[[1]][2]
Month <- as.character(strsplit(tempM, split = "-")[[1]][1])
}
RAW[[Month]] <- temp3.scores[[colName]]
}
RAW <- RAW[is.na(RAW) == FALSE]
if(omitPreVac == TRUE){
RAW[["Pre"]] <- NA
}
if(addPoints == TRUE){
for(mx in 1:length(RAW)){
for(y in 1:length(RAW[[mx]])){
xShiftFactor <- 0.05 * length(x) /12
# shifted.x <- mx + 3 - ((length(categories) * xShiftFactor)/2) + (c-1) * xShiftFactor
shifted.x <- mx - ((length(categories) * xShiftFactor)/2) + (c-1) * xShiftFactor
points(x = shifted.x, y = RAW[[mx]][y], pch = 20, cex = 0.8, col = pointCOLs[c])
}
}
}
if(lowessSmooth == TRUE){
RAW2 <- data.frame(x = names(RAW))
RAW2$score <- NA
for(m in 1:length(RAW)){
rawValues <- RAW[[m]][is.na(RAW[[m]]) == FALSE & RAW[[m]] >= 0]
if(length(rawValues) > 0){
RAW2$score[m] <- mean(rawValues)
}
}
RAW3 <- subset(RAW2, is.na(RAW2$score) == FALSE)
# RAW3 <- RAW2
# RAW3$l <- lowess(RAW3)$y
if(logY == FALSE){
RAW3$l <- lowess(RAW3)$y
}
if(logY == TRUE){
RAW3$scoreLog <- log(RAW3$score, base = 10)
RAW3$lLog <- as.numeric(NA)
RAW3$lLog[-(1:2)] <- lowess(x = RAW3$x[-(1:2)], y = RAW3$scoreLog[-(1:2)])$y
RAW3$l <- 10^RAW3$lLog
}
# lowess.x <- x
lowess.x <- x[is.na(RAW2$score) == FALSE]
names(lowess.x) <- RAW3$x
if(lineForPre == FALSE){
RAW3 <- RAW3[RAW3$x != "Pre",]
lowess.x <- lowess.x[names(lowess.x) != "Pre"]
}
if(lineFor1st == FALSE){
RAW3 <- RAW3[RAW3$x != "Post1st",]
lowess.x <- lowess.x[names(lowess.x) != "Post1st"]
}
lowess.index <- is.na(RAW3$l) == FALSE
if(lineColDark == FALSE){
lines(x = lowess.x[lowess.index], y = RAW3$l[lowess.index], col = COLs[c], lwd = lwd*2)
}
if(lineColDark == TRUE){
lines(x = lowess.x[lowess.index], y = RAW3$l[lowess.index], col = COLsDark[c], lwd = lwd*2)
}
} # if(lowessSmooth == TRUE)
if(geometricMean == TRUE){
months <- seq(firstMonth, lastMonth, as.integer(strsplit(type, "M")[[1]][2]))
GMDF <- data.frame(x = c("Pre", "Post1st", as.character(months)), mean = as.numeric(NA),
lwr.ci = as.numeric(NA), upr.ci = as.numeric(NA))
tooLow <- 1
for(m in 1:length(RAW)){
rawValues <- RAW[[m]][is.na(RAW[[m]]) == FALSE & RAW[[m]] > 0]
# if(length(rawValues) > 1){
if(length(rawValues) > 2){
GmeanResult <- Gmean(rawValues, conf.level = 0.95, na.rm = TRUE)
GM <- GmeanResult[1]
if(is.na(GM) == FALSE) GMDF$mean[m] <- GM
LOWCI <- GmeanResult[2]
if(is.na(LOWCI) == FALSE) GMDF$lwr.ci[m] <- LOWCI
UPRCI <- GmeanResult[3]
if(is.na(UPRCI) == FALSE) GMDF$upr.ci[m] <- UPRCI
}
if(length(rawValues) <= 2){
if(m <= 2) DataPoint <- GMDF$x[m]
if(m > 2) DataPoint <- paste("M", GMDF$x[m], sep = "")
if(tooLow > 1) cat(paste(", ", DataPoint, sep = ""))
if(tooLow == 1){
cat(paste("Number of samples is too low (<3) for geometric mean calculation",
" of the category \"", categories[c], "\"\n", sep = ""))
cat(paste(" at ", DataPoint, sep = ""))
tooLow <- tooLow + 1
}
}
}
if(tooLow > 1) cat("\n")
GMs <- numeric(length = length(x))
GMs[1:length(GMs)] <- NA
LOWCIs <- numeric(length = length(x))
LOWCIs[1:length(LOWCIs)] <- NA
UPRCIs <- numeric(length = length(x))
UPRCIs[1:length(UPRCIs)] <- NA
for(m in 1:length(months)){
GMs[m] <- GMDF$mean[m]
LOWCIs[m] <- GMDF$lwr.ci[m]
UPRCIs[m] <- GMDF$upr.ci[m]
}
GMDF$x.axis <- x
GMDF <- GMDF[is.na(GMDF$mean) == FALSE, ]
if(lineForPre == FALSE) GMDF <- GMDF[GMDF$x != "Pre",]
if(lineFor1st == FALSE) GMDF <- GMDF[GMDF$x != "Post1st",]
for(l in 1:nrow(GMDF)){
xShiftFactor <- 0.05 * length(x) /12
shifted.x <- GMDF$x.axis[l] - ((length(categories) * xShiftFactor)/2) + (c-1) * xShiftFactor
if(lineColDark == FALSE){
lines(x = c(shifted.x, shifted.x),
y = c(GMDF$lwr.ci[l], GMDF$mean[l]), col = COLs[c], lwd = lwd)
lines(x = c(shifted.x-0.1, shifted.x +0.1),
y = c(GMDF$lwr.ci[l], GMDF$lwr.ci[l]), col = COLs[c], lwd = lwd)
lines(x = c(shifted.x, shifted.x),
y = c(GMDF$upr.ci[l], GMDF$mean[l]), col = COLs[c], lwd = lwd)
lines(x = c(shifted.x-0.1, shifted.x +0.1),
y = c(GMDF$upr.ci[l], GMDF$upr.ci[l]), col = COLs[c], lwd = lwd)
}
if(lineColDark == TRUE){
lines(x = c(shifted.x, shifted.x),
y = c(GMDF$lwr.ci[l], GMDF$mean[l]), col = COLsDark[c], lwd = lwd)
lines(x = c(shifted.x-0.1, shifted.x +0.1),
y = c(GMDF$lwr.ci[l], GMDF$lwr.ci[l]), col = COLsDark[c], lwd = lwd)
lines(x = c(shifted.x, shifted.x),
y = c(GMDF$upr.ci[l], GMDF$mean[l]), col = COLsDark[c], lwd = lwd)
lines(x = c(shifted.x-0.1, shifted.x +0.1),
y = c(GMDF$upr.ci[l], GMDF$upr.ci[l]), col = COLsDark[c], lwd = lwd)
}
}
shiftedX <- GMDF$x.axis - ((length(categories) * xShiftFactor)/2) + (c-1) * xShiftFactor
if(lineColDark == FALSE){
lines(x = shiftedX, y = GMDF$mean, col = COLs[c], lwd = lwd*2)
}
if(lineColDark == TRUE){
lines(x = shiftedX, y = GMDF$mean, col = COLsDark[c], lwd = lwd*2)
}
} # if(geometricMean == TRUE)
legendX <- 3+length(colNames) - (3+length(colNames))/3
# legendY <- ylim[2] - (ylim[2] - ylim[1])/10*c
if(logY == FALSE) legendY <- ylim[2] - (ylim[2] - ylim[1])/10*c
if(logY == TRUE) legendY <- 10^(log(ylim[2], base = 10) -
((log(ylim[2], base = 10) - log(ylim[1], base = 10))/15*(c))) # c+1 or c?
if(lineColDark == FALSE){
legend(x = legendX, y = legendY, col = COLs[c], lwd = lwd*2,
legend = categories[c], bty = "n")
}
if(lineColDark == TRUE){
legend(x = legendX, y = legendY, col = COLsDark[c], lwd = lwd*2,
legend = categories[c], bty = "n")
}
if(c == 1){
legendX <- 2+length(colNames) - (2+length(colNames))/4
# legendY <- ylim[2] - (ylim[2] - ylim[1])/10*c * 1.4
if(logY == FALSE) legendY <- ylim[2] - (ylim[2] - ylim[1])/10*c * 1.4
if(logY == TRUE) legendY <- 10^(log(ylim[2], base = 10) -
((log(ylim[2], base = 10) - log(ylim[1], base = 10))/20*(c+1))) # c+1
text(x = legendX, y = legendY, pos = 3, labels = lineAttrib)
}
}
}
}
if(savePDF == TRUE) dev.off()
}
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