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if(!require('openair')) {
install.packages('openair')
library('openair')
}# load example data from package data(mydata)
# basic plot
windRose(mydata)
# one windRose for each year
windRose(mydata,type = "year")
# windRose in 10 degree intervals with gridlines and width adjusted
windRose(mydata, angle = 10, width = 0.2, grid.line = 1)
# pollutionRose of nox
pollutionRose(mydata, pollutant = "nox")
## source apportionment plot - contribution to mean
pollutionRose(mydata, pollutant = "pm10", type = "year", statistic = "prop.mean")
## example of comparing 2 met sites
## first we will make some new ws/wd data with a postive bias
mydata$ws2 = mydata$ws + 2 * rnorm(nrow(mydata)) + 1
mydata$wd2 = mydata$wd + 30 * rnorm(nrow(mydata)) + 30
## need to correct negative wd
id <- which(mydata$wd2 < 0)
mydata$wd2[id] <- mydata$wd2[id] + 360
## results show postive bias in wd and ws
pollutionRose(mydata, ws = "ws", wd = "wd", ws2 = "ws2", wd2 = "wd2")