wind-power/wind-rose.r at main · hydro-lab/wind-power · GitHub

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## Wind data from Pittsburgh International Airport.
## Example of rose plot of wind direction

library(tidyverse) # includes ggplot and readr commands
library(RColorBrewer) # used for wind rose with color code by speed
library(lubridate) # used for dates, specifically month separation

## Pittsburgh International Airport (PIT)
pit <- read_csv("https://duq.box.com/shared/static/i9qlh63qdzf5hqvf40dphkbwkh93o2h0.csv")
pit$month <- pit$Month
pit$dir <- pit$`Wind Dir` # degrees
pit$spd <- 0.51444444444 * pit$`Wind Speed` # converted to m/s from knots, per http://www.climate.psu.edu/data/current/help.php

## Heinz Field (HFP)
hfp <- read_csv("https://duq.box.com/shared/static/2cs6xi81xtcmq4mmi46t0v0ev4f2mehs.csv")
hfp$date <- as_date(hfp$Timestamp)
hfp$month <- month(hfp$date)
hfp$dir <- hfp$`Wind Vane` # degrees
hfp$spd <- 0.44704 * hfp$Anemometer # converted to m/s from mph, per https://allegheny.weatherstem.com/pitt

## OLD METHOD - no speed binning
# br <- 10*(c(0:36)) # This array constructs the bins in degrees
# h <- hist(hfp.dir, breaks = br)
## Make rose plot, based on:
## https://stackoverflow.com/questions/39024758/how-to-use-r-package-circular-to-make-rose-plot-of-histogram-data-on-360/39025913
## https://stackoverflow.com/questions/50163352/plot-wind-rose-in-r
# angle <- h$mids
# count <- h$counts
# y <- data.frame(angle, count)
# ggplot(y, aes(x = angle, y = count)) +
#       labs(caption = "Heinz Field") +
#       geom_col(fill = "steelblue", color = "steelblue") +
#       coord_polar(theta = "x", start = 0) +
#       scale_x_continuous(breaks = seq(0, 360, 45)) +
#       theme_linedraw() +
#       theme(axis.title = element_blank(), panel.ontop = TRUE, panel.background = element_blank())

# ## NEW METHOD - with speed binning
# ## sort data:
# d <- x$dir
# s <- x$spd
# speed.bins <- 7 # this used for monthly data at HFP
# # speed.bins <- ceiling(max(s)) # HFP will work with this binning.
# # speed.bins <- 6 # PIT needs this binning
# wind <- array(0, dim = c(36,speed.bins))
# for (i in 1:(length(s))) {
#       speed.index <- ceiling(s[i]) # HFP will work with this binning.
#       ## for use when speed categories exceed colormap (>9)
#       # if (s[i] <= 2) {
#       #       speed.index <- 1
#       # } else if (s[i] <= 4) {
#       #       speed.index <- 2
#       # } else if (s[i] <= 6) {
#       #       speed.index <- 3
#       # } else if (s[i] <= 8) {
#       #       speed.index <- 4
#       # } else if (s[i] <= 10) {
#       #       speed.index <- 5
#       # } else {
#       #       speed.index <- 6
#       # }
#       wind[ceiling(d[i]/10),speed.index] <- wind[ceiling(d[i]/10),speed.index] + 1
# }
# ## Now, form long array rather than wide:
# wind.long <- array(NA, dim = 36*speed.bins)
# for (i in 1:speed.bins) {
#       for (j in 1:36) {
#             wind.long[(36*(i-1))+j] <- wind[j,i]
#       }
# }
# # speeds <- c(rep("0-2",36), rep("2-4",36), rep("4-6",36), rep("6-8",36), rep("8-10",36), rep("above 10",36)) # be sure to fill in as many as the wind bins in "wind" allocation
# speeds <- c(rep("0-1",36), rep("1-2",36), rep("2-3",36), rep("3-4",36), rep("4-5",36), rep("5-6",36), rep("6-7",36)) # for HFP
# directions <- rep(5+10*(c(0:35)), speed.bins)
# rose <- data.frame(directions, speeds, wind.long)
#
# windHFP <- ggplot(rose, aes(fill = fct_rev(speeds), x = directions, y = wind.long)) +
#       labs(caption = paste("Pittsburgh International Airport")) +
#       geom_bar(position="stack", stat="identity") +
#       scale_fill_brewer("Speed (m/s)", palette = "Blues") +
#       coord_polar(theta = "x", start = 0) +
#       scale_x_continuous(breaks = seq(0, 360, 45)) +
#       theme_linedraw() +
#       theme(axis.title = element_blank(), panel.ontop = TRUE, panel.background = element_blank()) # NOTE: ylim used in export
#
# # caption = "Pittsburgh International Airport" +
# # caption = "Heinz Field" +


## NEWer METHOD - with speed binning - even newer, with month separation
## sort data:
for (k in 1:12) {
      x <- pit %>%
            filter(month == k)
      d <- x$dir
      s <- x$spd
      #speed.bins <- 7 # this used for monthly data at HFP
      # speed.bins <- ceiling(max(s)) # HFP will work with this binning.
      speed.bins <- 6 # PIT needs this binning
      wind <- array(0, dim = c(36,speed.bins))
      for (i in 1:(length(s))) {
            #speed.index <- ceiling(s[i]) # HFP will work with this binning.
            ## for use when speed categories exceed colormap (>9)
            if (s[i] <= 2) {
                  speed.index <- 1
            } else if (s[i] <= 4) {
                  speed.index <- 2
            } else if (s[i] <= 6) {
                  speed.index <- 3
            } else if (s[i] <= 8) {
                  speed.index <- 4
            } else if (s[i] <= 10) {
                  speed.index <- 5
            } else {
                  speed.index <- 6
            }
            wind[ceiling(d[i]/10),speed.index] <- wind[ceiling(d[i]/10),speed.index] + 1
      }
      ## Now, form long array rather than wide:
      wind.long <- array(NA, dim = 36*speed.bins)
      for (i in 1:speed.bins) {
            for (j in 1:36) {
                  wind.long[(36*(i-1))+j] <- wind[j,i]
            }
      }
      speeds <- c(rep("0-2",36), rep("2-4",36), rep("4-6",36), rep("6-8",36), rep("8-10",36), rep("above 10",36)) # be sure to fill in as many as the wind bins in "wind" allocation
      #speeds <- c(rep("0-1",36), rep("1-2",36), rep("2-3",36), rep("3-4",36), rep("4-5",36), rep("5-6",36), rep("6-7",36)) # for HFP
      directions <- rep(5+10*(c(0:35)), speed.bins)
      rose <- data.frame(directions, speeds, wind.long)

      windHFP <- ggplot(rose, aes(fill = fct_rev(speeds), x = directions, y = wind.long)) +
            labs(caption = paste("month = ", k, sep = "")) +
            geom_bar(position="stack", stat="identity") +
            scale_fill_brewer("Speed (m/s)", palette = "Blues") +
            coord_polar(theta = "x", start = 0) +
            scale_x_continuous(breaks = seq(0, 360, 45)) +
            ylim(0,15) +
            theme_linedraw() +
            theme(axis.title = element_blank(), panel.ontop = TRUE, panel.background = element_blank()) # NOTE: ylim used in export

      # caption = "Pittsburgh International Airport" +
      # caption = "Heinz Field" +

      ## to save immediately:
      ggsave(paste("windPIT", k, ".png", sep = ""), plot = windHFP, device = "png")

}