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copied!<p>For sake of argument we'll assume that we are using the <code>data.in</code> data frame, which has two data columns and some kind of date / time information. We'll ignore the date and time information initially.</p> <h2>The ggplot function</h2> <p>I've coded the function below. I'm interested in other people's experience or suggestions on how to improve this.</p> <pre><code># 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$spd.binned = with(data, factor(spd.binned, levels = rev(levels(spd.binned)))) spd.colors = rev(spd.colors) } # create the plot ---- p.windrose <- ggplot(data = data, aes(x = dir.binned, fill = spd.binned)) + geom_bar() + scale_x_discrete(drop = FALSE, labels = waiver()) + coord_polar(start = -((dirres/2)/360) * 2*pi) + scale_fill_manual(name = "Wind Speed (m/s)", values = spd.colors, drop = FALSE) + theme(axis.title.x = element_blank()) # adjust axes if required if (!is.na(countmax)){ p.windrose <- p.windrose + ylim(c(0,countmax)) } # print the plot print(p.windrose) # return the handle to the wind rose return(p.windrose) } </code></pre> <h1>Proof of Concept and Logic</h1> <p>We'll now check that the code does what we expect. For this, we'll use the simple set of demo data.</p> <pre><code># try the default settings p0 <- plot.windrose(spd = data.in$ws.80, dir = data.in$wd.80) </code></pre> <p>This gives us this plot: <a href="https://i.stack.imgur.com/7WF1y.png" rel="noreferrer"><img src="https://i.stack.imgur.com/7WF1y.png" alt="Unit Test Results"></a> So: we've correctly binned the data by direction and wind speed, and have coded up our out-of-range data as expected. Looks good!</p> <h1>Using this function</h1> <p>Now we load the real data. We can load this from the URL:</p> <pre><code>data.in <- read.csv(file = "http://midcdmz.nrel.gov/apps/plot.pl?site=NWTC&start=20010824&edy=26&emo=3&eyr=2062&year=2013&month=1&day=1&endyear=2013&endmonth=12&endday=31&time=0&inst=21&inst=39&type=data&wrlevel=2&preset=0&first=3&math=0&second=-1&value=0.0&user=0&axis=1", col.names = c("date","hr","ws.80","wd.80")) </code></pre> <p>or from file:</p> <pre><code>data.in <- read.csv(file = "A:/blah/20130101.csv", col.names = c("date","hr","ws.80","wd.80")) </code></pre> <h2>The quick way</h2> <p>The simple way to use this with the M2 data is to just pass in separate vectors for <code>spd</code> and <code>dir</code> (speed and direction):</p> <pre><code># try the default settings p1 <- plot.windrose(spd = data.in$ws.80, dir = data.in$wd.80) </code></pre> <p>Which gives us this plot:</p> <p><a href="https://i.stack.imgur.com/1P29Y.png" rel="noreferrer"><img src="https://i.stack.imgur.com/1P29Y.png" alt="enter image description here"></a></p> <p>And if we want custom bins, we can add those as arguments:</p> <pre><code>p2 <- plot.windrose(spd = data.in$ws.80, dir = data.in$wd.80, spdseq = c(0,3,6,12,20)) </code></pre> <p><a href="https://i.stack.imgur.com/u6LzY.png" rel="noreferrer"><img src="https://i.stack.imgur.com/u6LzY.png" alt="enter image description here"></a></p> <h2>Using a data frame and the names of columns</h2> <p>To make the plots more compatible with <code>ggplot()</code>, you can also pass in a data frame and the <em>name</em> of the speed and direction variables:</p> <pre><code>p.wr2 <- plot.windrose(data = data.in, spd = "ws.80", dir = "wd.80") </code></pre> <h2>Faceting by another variable</h2> <p>We can also plot the data by month or year using ggplot's faceting capability. Let's start by getting the time stamp from the date and hour information in <code>data.in</code>, and converting to month and year:</p> <pre><code># first create a true POSIXCT timestamp from the date and hour columns data.in$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) </code></pre> <p>Then you can apply faceting to show how the wind rose varies by month:</p> <pre><code># 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()) </code></pre> <p><a href="https://i.stack.imgur.com/q0DhU.png" rel="noreferrer"><img src="https://i.stack.imgur.com/q0DhU.png" alt="enter image description here"></a></p> <h1>Comments</h1> <p>Some things to note about the function and how it can be used:</p> <ul> <li>The inputs are: <ul> <li>vectors of speed (<code>spd</code>) and direction (<code>dir</code>) <em>or</em> the name of the data frame and the names of the columns that contain the speed and direction data.</li> <li>optional values of the bin size for wind speed (<code>spdres</code>) and direction (<code>dirres</code>). </li> <li><code>palette</code> is the name of a <a href="http://colorbrewer.org" rel="noreferrer">colorbrewer</a> sequential palette, </li> <li><code>countmax</code> sets the range of the wind rose. </li> <li><code>debug</code> is a switch (0,1,2) to enable different levels of debugging.</li> </ul></li> <li>I wanted to be able to set the maximum speed (<code>spdmax</code>) and the count (<code>countmax</code>) for the plots so that I can compare windroses from different data sets</li> <li>If there are wind speeds that exceed (<code>spdmax</code>), those are added as a grey region (see the figure). I should probably code something like <code>spdmin</code> as well, and color-code regions where the wind speeds are less than that.</li> <li>Following a request, I implemented a method to use custom wind speed bins. They can be added using the <code>spdseq = c(1,3,5,12)</code> argument.</li> <li>You can remove the degree bin labels using the usual ggplot commands to clear the x axis: <code>p.wr3 + theme(axis.text.x = element_blank(),axis.title.x = element_blank())</code>.</li> <li>At some point recently ggplot2 changed the ordering of bins, so that the plots didn't work. I think this was version 2.2. But, if your plots look a bit weird, change the code so that test for "2.2" is maybe "2.1", or "2.0".</li> </ul>

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