許多R函數的好處是你可以在許多情況下鍵入他們的名字來查看源代碼。所以在這裏，您可以鍵入windRose，和編輯需要的標籤如下：
windRose.2 <- function (mydata, ws = "ws", wd = "wd", ws2 = NA, wd2 = NA, ws.int = 2,
angle = 30, type = "default", cols = "default", grid.line = NULL,
width = 1, seg = NULL, auto.text = TRUE, breaks = 4, offset = 10,
paddle = TRUE, key.header = NULL, key.footer = "(m/s)", key.position = "bottom",
key = TRUE, dig.lab = 5, statistic = "prop.count", pollutant = NULL,
annotate = TRUE, border = NA, ...)
{
if (is.null(seg))
seg <- 0.9
if (length(cols) == 1 && cols == "greyscale") {
trellis.par.set(list(strip.background = list(col = "white")))
calm.col <- "black"
}
else {
calm.col <- "forestgreen"
}
current.strip <- trellis.par.get("strip.background")
on.exit(trellis.par.set("strip.background", current.strip))
if (360/angle != round(360/angle)) {
warning("In windRose(...):\n angle will produce some spoke overlap",
"\n suggest one of: 5, 6, 8, 9, 10, 12, 15, 30, 45, etc.",
call. = FALSE)
}
if (angle < 3) {
warning("In windRose(...):\n angle too small", "\n enforcing 'angle = 3'",
call. = FALSE)
angle <- 3
}
extra.args <- list(...)
extra.args$xlab <- if ("xlab" %in% names(extra.args))
quickText(extra.args$xlab, auto.text)
else quickText("", auto.text)
extra.args$ylab <- if ("ylab" %in% names(extra.args))
quickText(extra.args$ylab, auto.text)
else quickText("", auto.text)
extra.args$main <- if ("main" %in% names(extra.args))
quickText(extra.args$main, auto.text)
else quickText("", auto.text)
if (is.character(statistic)) {
ok.stat <- c("prop.count", "prop.mean", "abs.count",
"frequency")
if (!is.character(statistic) || !statistic[1] %in% ok.stat) {
warning("In windRose(...):\n statistic unrecognised",
"\n enforcing statistic = 'prop.count'", call. = FALSE)
statistic <- "prop.count"
}
if (statistic == "prop.count") {
stat.fun <- length
stat.unit <- "%"
stat.scale <- "all"
stat.lab <- ""
stat.fun2 <- function(x) signif(mean(x, na.rm = TRUE),
3)
stat.lab2 <- "mean"
stat.labcalm <- function(x) round(x, 1)
}
if (statistic == "prop.mean") {
stat.fun <- function(x) sum(x, na.rm = TRUE)
stat.unit <- "%"
stat.scale <- "panel"
stat.lab <- "Proportion contribution to the mean (%)"
stat.fun2 <- function(x) signif(mean(x, na.rm = TRUE),
3)
stat.lab2 <- "mean"
stat.labcalm <- function(x) round(x, 1)
}
if (statistic == "abs.count" | statistic == "frequency") {
stat.fun <- length
stat.unit <- ""
stat.scale <- "none"
stat.lab <- "Count by wind direction"
stat.fun2 <- function(x) round(length(x), 0)
stat.lab2 <- "count"
stat.labcalm <- function(x) round(x, 0)
}
}
if (is.list(statistic)) {
stat.fun <- statistic$fun
stat.unit <- statistic$unit
stat.scale <- statistic$scale
stat.lab <- statistic$lab
stat.fun2 <- statistic$fun2
stat.lab2 <- statistic$lab2
stat.labcalm <- statistic$labcalm
}
vars <- c(wd, ws)
diff <- FALSE
rm.neg <- TRUE
if (!is.na(ws2) & !is.na(wd2)) {
vars <- c(vars, ws2, wd2)
diff <- TRUE
rm.neg <- FALSE
mydata$ws <- mydata[, ws2] - mydata[, ws]
mydata$wd <- mydata[, wd2] - mydata[, wd]
id <- which(mydata$wd < 0)
if (length(id) > 0)
mydata$wd[id] <- mydata$wd[id] + 360
pollutant <- "ws"
key.footer <- "ws"
wd <- "wd"
ws <- "ws"
vars <- c("ws", "wd")
if (missing(angle))
angle <- 10
if (missing(offset))
offset <- 20
if (is.na(breaks[1])) {
max.br <- max(ceiling(abs(c(min(mydata$ws, na.rm = TRUE),
max(mydata$ws, na.rm = TRUE)))))
breaks <- c(-1 * max.br, 0, max.br)
}
if (missing(cols))
cols <- c("lightskyblue", "tomato")
seg <- 1
}
if (any(type %in% openair:::dateTypes))
vars <- c(vars, "date")
if (!is.null(pollutant))
vars <- c(vars, pollutant)
mydata <- openair:::checkPrep(mydata, vars, type, remove.calm = FALSE,
remove.neg = rm.neg)
mydata <- na.omit(mydata)
if (is.null(pollutant))
pollutant <- ws
mydata$x <- mydata[, pollutant]
mydata[, wd] <- angle * ceiling(mydata[, wd]/angle - 0.5)
mydata[, wd][mydata[, wd] == 0] <- 360
mydata[, wd][mydata[, ws] == 0] <- -999
if (length(breaks) == 1)
breaks <- 0:(breaks - 1) * ws.int
if (max(breaks) < max(mydata$x, na.rm = TRUE))
breaks <- c(breaks, max(mydata$x, na.rm = TRUE))
if (min(breaks) > min(mydata$x, na.rm = TRUE))
warning("Some values are below minimum break.")
breaks <- unique(breaks)
mydata$x <- cut(mydata$x, breaks = breaks, include.lowest = FALSE,
dig.lab = dig.lab)
theLabels <- gsub("[(]|[)]|[[]|[]]", "", levels(mydata$x))
theLabels <- gsub("[,]", " to ", theLabels)
prepare.grid <- function(mydata) {
if (all(is.na(mydata$x)))
return()
levels(mydata$x) <- c(paste("x", 1:length(theLabels),
sep = ""))
all <- stat.fun(mydata[, wd])
calm <- mydata[mydata[, wd] == -999, ][, pollutant]
mydata <- mydata[mydata[, wd] != -999, ]
calm <- stat.fun(calm)
weights <- tapply(mydata[, pollutant], list(mydata[,
wd], mydata$x), stat.fun)
if (stat.scale == "all") {
calm <- calm/all
weights <- weights/all
}
if (stat.scale == "panel") {
temp <- stat.fun(stat.fun(weights)) + calm
calm <- calm/temp
weights <- weights/temp
}
weights[is.na(weights)] <- 0
weights <- t(apply(weights, 1, cumsum))
if (stat.scale == "all" | stat.scale == "panel") {
weights <- weights * 100
calm <- calm * 100
}
panel.fun <- stat.fun2(mydata[, pollutant])
u <- mean(sin(2 * pi * mydata[, wd]/360))
v <- mean(cos(2 * pi * mydata[, wd]/360))
mean.wd <- atan2(u, v) * 360/2/pi
if (all(is.na(mean.wd))) {
mean.wd <- NA
}
else {
if (mean.wd < 0)
mean.wd <- mean.wd + 360
if (mean.wd > 180)
mean.wd <- mean.wd - 360
}
weights <- cbind(data.frame(weights), wd = as.numeric(row.names(weights)),
calm = calm, panel.fun = panel.fun, mean.wd = mean.wd)
weights
}
if (paddle) {
poly <- function(wd, len1, len2, width, colour, x.off = 0,
y.off = 0) {
theta <- wd * pi/180
len1 <- len1 + off.set
len2 <- len2 + off.set
x1 <- len1 * sin(theta) - width * cos(theta) + x.off
x2 <- len1 * sin(theta) + width * cos(theta) + x.off
x3 <- len2 * sin(theta) - width * cos(theta) + x.off
x4 <- len2 * sin(theta) + width * cos(theta) + x.off
y1 <- len1 * cos(theta) + width * sin(theta) + y.off
y2 <- len1 * cos(theta) - width * sin(theta) + y.off
y3 <- len2 * cos(theta) + width * sin(theta) + y.off
y4 <- len2 * cos(theta) - width * sin(theta) + y.off
lpolygon(c(x1, x2, x4, x3), c(y1, y2, y4, y3), col = colour,
border = border)
}
}
else {
poly <- function(wd, len1, len2, width, colour, x.off = 0,
y.off = 0) {
len1 <- len1 + off.set
len2 <- len2 + off.set
theta <- seq((wd - seg * angle/2), (wd + seg * angle/2),
length.out = (angle - 2) * 10)
theta <- ifelse(theta < 1, 360 - theta, theta)
theta <- theta * pi/180
x1 <- len1 * sin(theta) + x.off
x2 <- rev(len2 * sin(theta) + x.off)
y1 <- len1 * cos(theta) + x.off
y2 <- rev(len2 * cos(theta) + x.off)
lpolygon(c(x1, x2), c(y1, y2), col = colour, border = border)
}
}
mydata <- cutData(mydata, type, ...)
results.grid <- ddply(mydata, type, prepare.grid)
results.grid$calm <- stat.labcalm(results.grid$calm)
results.grid$mean.wd <- stat.labcalm(results.grid$mean.wd)
strip.dat <- openair:::strip.fun(results.grid, type, auto.text)
strip <- strip.dat[[1]]
strip.left <- strip.dat[[2]]
pol.name <- strip.dat[[3]]
if (length(theLabels) < length(cols)) {
col <- cols[1:length(theLabels)]
}
else {
col <- openColours(cols, length(theLabels))
}
max.freq <- max(results.grid[, (length(type) + 1):(length(theLabels) +
length(type))], na.rm = TRUE)
off.set <- max.freq * (offset/100)
box.widths <- seq(0.002^0.25, 0.016^0.25, length.out = length(theLabels))^4
box.widths <- box.widths * max.freq * angle/5
legend <- list(col = col, space = key.position, auto.text = auto.text,
labels = theLabels, footer = key.footer, header = key.header,
height = 0.6, width = 1.5, fit = "scale", plot.style = if (paddle) "paddle" else "other")
legend <- openair:::makeOpenKeyLegend(key, legend, "windRose")
temp <- paste(type, collapse = "+")
myform <- formula(paste("x1 ~ wd | ", temp, sep = ""))
mymax <- 2 * max.freq
myby <- if (is.null(grid.line))
pretty(c(0, mymax), 10)[2]
else grid.line
if (myby/mymax > 0.9)
myby <- mymax * 0.9
xyplot.args <- list(x = myform, xlim = 1.03 * c(-max.freq -
off.set, max.freq + off.set), ylim = 1.03 * c(-max.freq -
off.set, max.freq + off.set), data = results.grid, type = "n",
sub = stat.lab, strip = strip, strip.left = strip.left,
as.table = TRUE, aspect = 1, par.strip.text = list(cex = 0.8),
scales = list(draw = FALSE), panel = function(x, y, subscripts,
...) {
panel.xyplot(x, y, ...)
angles <- seq(0, 2 * pi, length = 360)
sapply(seq(off.set, mymax, by = myby), function(x) llines(x *
sin(angles), x * cos(angles), col = "grey85",
lwd = 1))
subdata <- results.grid[subscripts, ]
upper <- max.freq + off.set
larrows(-upper, 0, upper, 0, code = 3, length = 0.1)
larrows(0, -upper, 0, upper, code = 3, length = 0.1)
ltext(upper * -1 * 0.95, 0.07 * upper, "W", cex = 0.7)
ltext(0.07 * upper, upper * -1 * 0.95, "S", cex = 0.7)
ltext(0.07 * upper, upper * 0.95, "N", cex = 0.7)
ltext(upper * 0.95, 0.07 * upper, "E", cex = 0.7)
if (nrow(subdata) > 0) {
for (i in 1:nrow(subdata)) {
with(subdata, {
for (j in 1:length(theLabels)) {
if (j == 1) {
temp <- "poly(wd[i], 0, x1[i], width * box.widths[1], col[1])"
} else {
temp <- paste("poly(wd[i], x", j - 1,
"[i], x", j, "[i], width * box.widths[",
j, "], col[", j, "])", sep = "")
}
eval(parse(text = temp))
}
})
}
}
ltext(seq((myby + off.set), mymax, myby) * sin(pi/4),
seq((myby + off.set), mymax, myby) * cos(pi/4),
paste(seq(myby, mymax, by = myby), stat.unit,
sep = ""), cex = 0.7)
if (annotate) if (statistic != "prop.mean") {
if (!diff) {
ltext(max.freq + off.set, -max.freq - off.set,
label = paste(stat.lab2, " = ", subdata$panel.fun[1],
"\ncalm = ", subdata$calm[1], stat.unit,
sep = ""), adj = c(1, 0), cex = 0.7, col = calm.col)
}
if (diff) {
ltext(max.freq + off.set, -max.freq - off.set,
label = paste("mean ws = ", round(subdata$panel.fun[1],
1), "\nmean wd = ", round(subdata$mean.wd[1],
1), sep = ""), adj = c(1, 0), cex = 0.7,
col = calm.col)
}
} else {
ltext(max.freq + off.set, -max.freq - off.set,
label = paste(stat.lab2, " = ", subdata$panel.fun[1],
stat.unit, sep = ""), adj = c(1, 0), cex = 0.7,
col = calm.col)
}
}, legend = legend)
xyplot.args <- openair:::listUpdate(xyplot.args, extra.args)
plt <- do.call(xyplot, xyplot.args)
if (length(type) == 1)
plot(plt)
else plot(useOuterStrips(plt, strip = strip, strip.left = strip.left))
newdata <- results.grid
output <- list(plot = plt, data = newdata, call = match.call())
class(output) <- "openair"
invisible(output)
}
在這裏，我複製了整個源，並提出了新的功能，windRose.2與正在stat.lab <- "Frequency of counts by wind direction (%)"唯一的區別是現在stat.lab <- ""。
如果函數使用包中的非導出函數，除非您明確地使用:::符號（該函數本身使用，它不應該）使用它們，否則將會失敗。 – Spacedman
是的，應該添加它沒有經過測試，因爲缺乏可重複的示例 – blmoore
如果加載包'lattice'和'ddply'，它可以很好地工作。非常感謝！ – Jesinsky