windRose(polar,
ws.int = 2, angle = 30, type = "default",
cols = "default", main = "", grid.line = 5,
width = 1, auto.text = TRUE, breaks = 4, paddle = TRUE,
key.header = NULL, key.footer = "(m/s)",
key.position = "bottom", key = NULL, dig.lab = 5,
pollutant = NULL,
...)
ans <- windRose(...)
pollutionRose(polar,
pollutant = "nox",
key.footer = pollutant,
breaks = 6, paddle = FALSE,
key.position = "right",
...)
ans <- pollutionRose(...)ws and wdpollutionRose. See
breaks below.windRose or pollutant in pollutionRose. For
windRose and the ws.int default of 2 m/s, the default,
4, generates the break points 2, 4, 6, 8 width.type determines how the data are split
i.e. conditioned, and then plotted. The default is will produce a
single plot using the entire data. Type can be one of the built-in
types as detailed in cutData e.g. "season"default, increment, heat, jet, hue
and user defined. For user defined the user can supply a list of
colour names recognised by R (tyTRUE (default) or FALSE. If
TRUE plots rose using `paddle' style spokes. If FALSE
plots rose using `wedge' style spokes.paddle = TRUE, the adjustment factor for width
of wind speed intervals. For example, width = 1.5 will make the
paddle width 1.5 times wider.TRUE (default) or FALSE. If
TRUE titles and axis labels will automatically try and format
pollutant names and units properly e.g. by subscripting the `2' in
NO2.windRose(mydata, key.header = "ws") adds the addition text as
a scale header. Note: This argument is passed to
drawOpenKey<"top", "right",
"bottom" and "left".drawOpenKey. See
drawOpenKey for further details.windRose default NULL is equivalent
to pollutant = "ws".pollutionRose other parameters that are
passed on to windRose. For windRose other parameters
that are passed on to drawOpenKey and
lattice:xyplot.windRose and pollutionRose
also return an object of class ``openair''. The object includes three main
components: call, the command used to generate the plot; data,
the data frame of summarised information used to make the
plot; and plot, the plot itself. If retained, e.g. using
output <- windRose(mydata), this output can be used to recover the data, reproduce
or rework the original plot or undertake further analysis.
An openair output can be manipulated using a number of generic operations, including
print, plot and summarise. See openair.generics
for further details.
Summarised proportions can also be extracted directly using the $data operator, e.g.
object$data for output <- windRose(mydata). This returns a data frame with
three set columns: cond, conditioning based on type; wd, the wind
direction; and calm, proportion of data unattributed to any specific wind direction
because it was collected under calm conditions; and then several (one for each range binned
for the plot) columns giving proportions of measurements associated with each ws or
pollutant range plotted as a discrete panel.windRose and pollutionRose
are designed to work with UK Met Office files. Wind directions of 0
degrees are assumed to be calms. The function will assume any data
with wind speed = 0 or wind direction = 0 will be calm.windRose data are summarised by direction,
typically by 45 or 30 (or 10) degrees and by different wind speed
categories. Typically, wind speeds are represented by different
width "paddles". The plots show the proportion (here represented
as a percentage) of time that the wind is from a certain angle and
wind speed range.
By default windRose will plot a windRose in using
"paddle" style segments and placing the scale key below the plot.
The argument pollutant uses the same plotting structure but
substitutes another data series, defined by pollutant, for
wind speed.
pollutionRose is a windRose wrapper which brings
pollutant forward in the argument list, and attempts to
sensibly rescale break points based on the pollutant data
range by by-passing ws.int.
By default, pollutionRose will plot a pollution rose of
nox using "wedge" style segments and placing the scale
key to the right of the plot.
Note also that all rows that contain at least one NA are
removed to make the plot. Therefore the the frequencies will be based
on the proportions of data that have had missing data removed first.drawOpenKey for fine control of the scale key.
See polarFreq for a more flexible version that
considers other statistics and pollutant concentrations.# 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 = 0.3, grid.line = 1)
# pollutionRose of nox
pollutionRose(mydata, pollutant = "nox")Run the code above in your browser using DataLab