suppressPackageStartupMessages(library("foehnix"))
The foehnix
package comes with methods to create windrose plot for
foehn classification models (see getting started,
foehnix reference
) and observation
data. Two types of windrose plots are available:
The windrose
function can be called
with a set of (observed) wind direction and wind speed values. Wind
direction has to be the meteorological wind direction in degrees
([0, 360]
, 0
and 360
corresponds to wind coming from North,
90
for wind from East, 180
for wind from South, and 270
from
West).
# Loading the demo data set for station Ellboegen data <- demodata("ellboegen") print(head(data)) # Plotting windrose windrose(data$dd, data$ff, type = "density") windrose(as.numeric(data$dd), as.numeric(data$ff), type = "histogram")
Windrose plots can also be created for foehnix
foehn classification
models if wind speed and wind direction information has been provided
to the foehnix
function when estimating
the classification model.
# Loading the demo data set for Tyrol (Ellboegen and Innsbruck) data <- demodata("tyrol") # default print(head(data)) # Estimate a foehnix classification model filter <- list(dd = c(43, 223), crest_dd = c(90, 270)) mod <- foehnix(diff_t ~ ff + rh, data = data, filter = filter, switch = TRUE, verbose = FALSE) # Plotting windroses windrose(mod)
By default, windrose
expects that the parameters are called dd
(wind direction)
and ff
(wind speed), however, custom names can also be used.
# Loading the demo data set for station Ellboegen and Sattelberg (combined) data <- demodata("tyrol") # default names(data) <- gsub("dd$", "winddir", names(data)) names(data) <- gsub("ff$", "windspd", names(data)) print(head(data)) # Estimate a foehnix classification model filter <- list(winddir = c(43, 223), crest_winddir = c(90, 270)) mod <- foehnix(diff_t ~ windspd + rh, data = data, filter = filter, switch = TRUE, verbose = FALSE) # Plotting windroses windrose(mod, ddvar = "winddir", ffvar = "windspd")
TODO: Write vignette.
# Loading the demo data set for station Ellboegen and Sattelberg (combined) data <- demodata("tyrol") filter <- list(dd = c(43, 223), crest_dd = c(90, 270)) mod <- foehnix(diff_t ~ ff + rh, data = data, filter = filter, switch = TRUE, verbose = FALSE) # Time Series Plot tsplot(mod, start = "2018-03-01", end = "2018-03-20")
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