#' create concentration rose
#'
#' @param data
#'
#' @return ggplot object
#'
#' @import ggplot2
#' @import scales
#' @import RColorBrewer
#'
#' @export mgsplot.concrose
#########################################################################
mgsplot.concrose <- function(data,
spd,
dir,
spdres = 2,
dirres = 30,
spdmin = 2,
spdmax = NULL,
spdseq = NULL,
#palette = "YlGnBu", #MGS changed this color palette
palette = "Spectral",
#countmax = NA,#MGS commented out this option
prctmax = 15, #MGS
prctseq = NULL, #MGS
debug = 0){
# Look to see what data was passed in to the function
if (is.numeric(spd) & is.numeric(dir)){
# assume that we've been given vectors of the speed and direction vectors
data <- data.frame(spd = spd,
dir = dir)
spd = "spd"
dir = "dir"
} else if (exists("data")){
# Assume that we've been given a data frame, and the name of the speed
# and direction columns. This is the format we want for later use.
}
# Tidy up input data ----
n.in <- NROW(data)
dnu <- (is.na(data[[spd]]) | is.na(data[[dir]]))
data[[spd]][dnu] <- NA
data[[dir]][dnu] <- NA
# figure out the wind speed bins ----
if(missing(spdmax) && !missing(spdseq)){
spdmax <- max(spdseq)
} else if(missing(spdmax) && missing(spdseq)){
spdmax <- max(data[[spd]],na.rm=TRUE)
}
if (missing(spdseq)){
spdseq <- seq(spdmin,spdmax,spdres)
} else {
if (debug >0){
cat("Using custom speed bins \n")
}
}
# get some information about the number of bins, etc.
n.spd.seq <- length(spdseq)
n.colors.in.range <- n.spd.seq - 1
# create the color map
spd.colors <- colorRampPalette(brewer.pal(min(max(3,
n.colors.in.range),
min(9,
n.colors.in.range)),
palette))(n.colors.in.range)
spd.colors <- rev(spd.colors) #for concentration make highs RED
#spd.colors <- colorRampPalette(c("blue","red"))(n.colors.in.range)
if (max(data[[spd]],na.rm = TRUE) > ceiling(spdmax)){
spd.breaks <- c(spdseq,
max(data[[spd]],na.rm = TRUE))
spd.labels <- c(paste(c(spdseq[1:n.spd.seq-1]),
'-',
c(spdseq[2:n.spd.seq])),
paste(spdmax,
"-",
max(data[spd],na.rm = TRUE)))
spd.colors <- c(spd.colors, "grey50")
} else{
spd.breaks <- spdseq #c(seq(spdseq))
spd.labels <- paste(c(spdseq[1:n.spd.seq-1]),
'-',
c(spdseq[2:n.spd.seq]))
}
data$spd.binned <- cut(x = data[[spd]],
breaks = spd.breaks,
labels = spd.labels,
ordered_result = TRUE)
# figure out the wind direction bins
dir.breaks <- c(-dirres/2,
seq(dirres/2, 360-dirres/2, by = dirres),
360+dirres/2)
#dir.labels <- c(paste(360-dirres/2,"-",dirres/2),
# paste(seq(dirres/2, 360-3*dirres/2, by = dirres),
# "-",
# seq(3*dirres/2, 360-dirres/2, by = dirres)),
# paste(360-dirres/2,"-",dirres/2))
dir.labels <- c("N","NNE","ENE","E","ESE","SSE","S","SSW","WSW","W","WNW","NNW","N") #MGS
# assign each wind direction to a bin
dir.binned <- cut(data[[dir]],
breaks = dir.breaks,
ordered_result = TRUE)
levels(dir.binned) <- dir.labels
data$dir.binned <- dir.binned
# Run debug if required ----
if (debug>0){
cat(dir.breaks,"\n")
cat(dir.labels,"\n")
cat(levels(dir.binned),"\n")
cat(speedcuts.colors, "\n")
}
# create the plot ----
if (missing(prctseq)){
if (!is.na(prctmax)){
ybreaks <- seq(5,prctmax,2.5)
}else{
ybreaks <- seq(5,15,2.5)
}
}else{
ybreaks <- prctseq
}
ybreaks.prct <- ybreaks/100
p.windrose <- ggplot(data = data,
aes(x = dir.binned,y = (..count..)/sum(..count..),
fill = spd.binned)) +
geom_bar()+
scale_y_continuous(breaks = ybreaks.prct,labels=percent)+
ylab("")+
scale_x_discrete(drop = FALSE,
labels = waiver()) +
coord_polar(start = -((dirres/2)/360) * 2*pi) +
scale_fill_manual(name = "Concentration",
values = spd.colors,
drop = FALSE)+
theme_bw(base_size = 12, base_family = "Helvetica")
#if(length(data)>2){
# p.windrose <- p + facet_wrap(~data[,3],ncol=2)
#}
# adjust axes if required
#if (!is.na(countmax)){
# p.windrose <- p.windrose +
# ylim(c(0,countmax))
#}
# print the plot
#print(p.windrose)
# return the handle to the wind rose
return(p.windrose)
}
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