Windrose Plot for foehnix Mixture Models and Observations

Source: R/windrose.R

foehnix Mixture Model Windrose Plot

windrose(x, ...)

# S3 method for class 'foehnix'
windrose(
  x,
  type = NULL,
  which = NULL,
  ddvar = "dd",
  ffvar = "ff",
  breaks = NULL,
  ncol = NULL,
  maxpp = Inf,
  ...,
  main = NULL
)

Arguments

x

object of class foehnix if the windrose plot is applied to a model, or a vector of wind directions for windrose.default (see 'Details' section).

...

forwarded to windrose.default.

type

NULL or character, one of density or histogram. If NULL both types will be plotted.

which

NULL or character, one of unconditional, nofoehn, or foehn. If NULL all three will be plotted.

ddvar

character, name of the column in the training data set which contains the wind direction information.

ffvar

character, name of the column in the training data set which contains the wind speed (or gust speed) data.

breaks

NULL or a numeric vector to define the wind speed (ff) breaks.

ncol

integer, number of columns of subplots.

maxpp

integer (>0), maximum plots per page. Not all plots fit on one page the script loops trough.

main

NULL (default) or character. If NULL the function will add default figure titles.

Details

Windrose plot based on a foehnix mixture model object.

Allows to draw windrose plots from foehnix mixture model object or a set of observations. If input x to windrose is an object of class foehnix (as returned by foehnix) the data set which the classification is based on is used to plot the windrose. If inputs dd and ff are given (univariate zoo time series objects or numeric vectors) windrose plots can be plotted for observations without the need of a foehnix object.

Two types are available: circular density plots and circular histograms. If the input argument x is a foehnix object an additional input argument which is available to specify the subset which should be used to create the windrose plots. The following inputs are allowed:

  • which = "unconditional": unconditional windrose (all observations of the data set used to estimate the foehnix model).

  • which = "nofoehn": windrose of all observations which have not been classified as foehn (probability < 0.5).

  • which = "foehn": windrose of all observations classified as foehn events (probability >= 0.5).

  • which = NULL: all three subsets will be plotted (individual windroses).

Specific combinations can be specified by calling the windrose function with e.g., type = "histogram" and which = c("foehn", "nofoehn") (will show histograms for foehn and no foehn events), or type = NULL and which = "foehn" (will show density and histogram plot for foehn events). By default (type = NULL, which = NULL) all combinations will be plotted.

If dd and ff are set only the type argument is available (type = "histogram" or type = "density").

Author

Reto Stauffer

Examples

# Loading combined demo data set
data <- demodata("tyrol") # default

# Before estimating a model: plot a wind rose for all observations
windrose(data$dd, data$ff, type = "histogram")

windrose(data$dd, data$ff, type = "density")


# Estimate a foehnix foehn classification model
filter <- list(dd = c(43, 223), crest_dd = c(90, 270)) 
mod <- foehnix(diff_t ~ ff + rh, data = data,
               filter = filter, verbose = FALSE)

# Plotting wind roses
windrose(mod)


# Only density windrose for foehn events
windrose(mod, type = "density", which = "foehn")


# Using custom names: by default wind direction is expected
# to be called 'dd', wind speed is expected to be called 'ff'.
# However, ddvar and ffvar allow to change that (only if
# windrose is called with a foehnix object as input).
# An example:
# - make a copy of data to data2
# - rename dd to winddir, crest_dd to crest_winddir
# - estimate the same foehnix model as above using the
#   new variable names
# - plot windrose with custom names for wind direction (winddir)
#   and wind speed (windspd).

data2 <- data
names(data2)[which(names(data2) == "ff")]       <- "windspd"
names(data2)[which(names(data2) == "dd")]       <- "winddir"
names(data2)[which(names(data2) == "crest_dd")] <- "crest_winddir"
print(head(data2))
#>                     winddir windspd  rh    t crest_winddir crest_ff crest_rh
#> 2006-01-01 01:00:00     171     0.6  90 -0.4           180     10.8      100
#> 2006-01-01 02:00:00     268     0.3 100 -1.8           186     12.5      100
#> 2006-01-01 03:00:00     115     5.2  79  0.9           181     11.3      100
#> 2006-01-01 04:00:00     152     2.1  88 -0.6           178     13.3      100
#> 2006-01-01 05:00:00     319     0.7 100 -2.6           176     13.1      100
#> 2006-01-01 06:00:00      36     0.1  99 -1.7           184     10.0      100
#>                     crest_t diff_t
#> 2006-01-01 01:00:00    -7.8   2.87
#> 2006-01-01 02:00:00    -8.0   4.07
#> 2006-01-01 03:00:00    -7.4   1.97
#> 2006-01-01 04:00:00    -7.5   3.37
#> 2006-01-01 05:00:00    -7.1   5.77
#> 2006-01-01 06:00:00    -6.9   5.07

filter2 <- list(winddir = c(43, 223), crest_winddir = c(90, 270)) 
mod2 <- foehnix(diff_t ~ windspd + rh, data = data2,
                filter = filter2, verbose = FALSE)

windrose(mod2, type = "density", which = "foehn",
         ddvar = "winddir", ffvar = "windspd")