説明のために、data.in2 つのデータ列と何らかの日付/時刻情報を持つデータ フレームを使用していると仮定します。最初は日付と時刻の情報は無視します。

ggplot関数

以下の関数をコーディングしました。他の人の経験や、これを改善する方法についての提案に興味があります。

# WindRose.R
require(ggplot2)
require(RColorBrewer)

plot.windrose <- function(data,
                      spd,
                      dir,
                      spdres = 2,
                      dirres = 30,
                      spdmin = 2,
                      spdmax = 20,
                      spdseq = NULL,
                      palette = "YlGnBu",
                      countmax = NA,
                      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(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)

  if (max(data[[spd]],na.rm = TRUE) > 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
    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)
  # clean up the data
  data. <- na.omit(data)

  # 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))
  # 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")       
  }  

  # deal with change in ordering introduced somewhere around version 2.2
  if(packageVersion("ggplot2") > "2.2"){    
    cat("Hadley broke my code\n")
    data$spd.binned = with(data, factor(spd.binned, levels = rev(levels(spd.binned))))
    spd.colors = rev(spd.colors)
  }

  # create the plot ----
  p.windrose <- ggplot(data = data,
                       aes(x = dir.binned,
                           fill = spd.binned)) +
    geom_bar() + 
    scale_x_discrete(drop = FALSE,
                     labels = waiver()) +
    coord_polar(start = -((dirres/2)/360) * 2*pi) +
    scale_fill_manual(name = "Wind Speed (m/s)", 
                      values = spd.colors,
                      drop = FALSE) +
    theme(axis.title.x = element_blank())

  # 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)
}

# try the default settings
p0 <- plot.windrose(spd = data.in$ws.80,
                   dir = data.in$wd.80)

data.in <- read.csv(file = "http://midcdmz.nrel.gov/apps/plot.pl?site=NWTC&start=20010824&edy=26&emo=3&eyr=2062&year=2013&month=1&day=1&endyear=2013&endmonth=12&endday=31&time=0&inst=21&inst=39&type=data&wrlevel=2&preset=0&first=3&math=0&second=-1&value=0.0&user=0&axis=1",
                    col.names = c("date","hr","ws.80","wd.80"))

data.in <- read.csv(file = "A:/blah/20130101.csv",
                    col.names = c("date","hr","ws.80","wd.80"))

# try the default settings
p1 <- plot.windrose(spd = data.in$ws.80,
                   dir = data.in$wd.80)

p2 <- plot.windrose(spd = data.in$ws.80,
                   dir = data.in$wd.80,
                   spdseq = c(0,3,6,12,20))

p.wr2 <- plot.windrose(data = data.in,
              spd = "ws.80",
              dir = "wd.80")

# first create a true POSIXCT timestamp from the date and hour columns
data.in$timestamp <- as.POSIXct(paste0(data.in$date, " ", data.in$hr),
                                tz = "GMT",
                                format = "%m/%d/%Y %H:%M")

# Convert the time stamp to years and months 
data.in$Year <- as.numeric(format(data.in$timestamp, "%Y"))
data.in$month <- factor(format(data.in$timestamp, "%B"),
                        levels = month.name)

# recreate p.wr2, so that includes the new data
p.wr2 <- plot.windrose(data = data.in,
              spd = "ws.80",
              dir = "wd.80")
# now generate the faceting
p.wr3 <- p.wr2 + facet_wrap(~month,
                            ncol = 3)
# and remove labels for clarity
p.wr3 <- p.wr3 + theme(axis.text.x = element_blank(),
          axis.title.x = element_blank())