openair (version 1.0)

polarFreq: Function to plot wind speed/direction frequencies and other statistics

Description

polarFreq primarily plots wind speed-direction frequencies in bins. Each bin is colour-coded depending on the frequency of measurements. Bins can also be used to show the concentration of pollutants using a range of commonly used statistics.

Usage

polarFreq(mydata, pollutant = "", statistic = "frequency", ws.int = 1,
  grid.line = 5, breaks = seq(0, 5000, 500), cols = "default",
  trans = TRUE, type = "default", min.bin = 1, ws.upper = NA,
  offset = 10, border.col = "transparent", key.header = statistic,
  key.footer = pollutant, key.position = "right", key = TRUE,
  auto.text = TRUE, ...)

Arguments

mydata

A data frame minimally containing ws, wd and date.

pollutant

Mandatory. A pollutant name corresponding to a variable in a data frame should be supplied e.g. pollutant = "nox"

statistic

The statistic that should be applied to each wind speed/direction bin. Can be frequency, mean, median, max (maximum), stdev (standard deviation) or weighted.mean<

ws.int

Wind speed interval assumed. In some cases e.g. a low met mast, an interval of 0.5 may be more appropriate.

grid.line

Radial spacing of grid lines.

breaks

The user can provide their own scale. breaks expects a sequence of numbers that define the range of the scale. The sequence could represent one with equal spacing e.g. breaks = seq(0, 100, 10) - a scale from 0-10 in intervals of

cols

Colours to be used for plotting. Options include default, increment, heat, jet and RColorBrewer colours --- see the openair openColours function for

trans

Should a transformation be applied? Sometimes when producing plots of this kind they can be dominated by a few high points. The default therefore is TRUE and a square-root transform is applied. This results in a non-linear scale and (usually)

type

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

min.bin

The minimum number of points allowed in a wind speed/wind direction bin. The default is 1. A value of two requires at least 2 valid records in each bin an so on; bins with less than 2 valid records are set to NA. Care should be taken when using a value >

ws.upper

A user-defined upper wind speed to use. This is useful for ensuring a consistent scale between different plots. For example, to always ensure that wind speeds are displayed between 1-10, set ws.int = 10.

offset

offset controls the size of the hole in the middle and is expressed as a percentage of the maximum wind speed. Setting a higher offset e.g. 50 is useful for statistic = "weighted.mean" when ws.

border.col

The colour of the boundary of each wind speed/direction bin. The default is transparent. Another useful choice sometimes is "white".

key.header,key.footer

Adds additional text/labels to the scale key. For example, passing options key.header = "header", key.footer = "footer" adds addition text above and below the scale key. These arguments are passed to drawOpenKey via quickTe

key.position

Location where the scale key is to plotted. Allowed arguments currently include "top", "right", "bottom" and "left".

key

Fine control of the scale key via drawOpenKey. See drawOpenKey for further details.

auto.text

Either 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.

...

Other graphical parameters passed onto lattice:xyplot and cutData. For example, polarFreq passes the option hemisphere = "southern" on to cutData to provide southern (rather than default nor

Value

• As well as generating the plot itself, polarFreq also returns 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 <- polarFreq(mydata, "nox"), 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 summary.

Details

polarFreq is its default use provides details of wind speed and direction frequencies. In this respect it is similar to windRose, but considers wind direction intervals of 10 degrees and a user-specified wind speed interval. The frequency of wind speeds/directions formed by these bins is represented on a colour scale.

The polarFreq function is more flexible than either windRose or polarPlot. It can, for example, also consider pollutant concentrations (see examples below). Instead of the number of data points in each bin, the concentration can be shown. Further, a range of statistics can be used to describe each bin - see statistic above. Plotting mean concentrations is useful for source identification and is the same as polarPlot but without smoothing, which may be preferable for some data. Plotting with statistic = "weighted.mean" is particularly useful for understanding the relative importance of different source contributions. For example, high mean concentrations may be observed for high wind speed conditions, but the weighted mean concentration may well show that the contribution to overall concentrations is very low.

polarFreq also offers great flexibility with the scale used and the user has fine control over both the range, interval and colour.

References

~put references to the literature/web site here ~

See Also

See Also as windRose, polarPlot

Examples

# basic wind frequency plot
polarFreq(mydata)

# wind frequencies by year
polarFreq(mydata, type = "year")


# mean SO2 by year, showing only bins with at least 2 points
polarFreq(mydata, pollutant = "so2", type = "year", statistic = "mean", min.bin = 2)

# weighted mean SO2 by year, showing only bins with at least 2 points
polarFreq(mydata, pollutant = "so2", type = "year", statistic = "weighted.mean",
min.bin = 2)

#windRose for just 2000 and 2003 with different colours
polarFreq(subset(mydata, format(date, "%Y") %in% c(2000, 2003)),
type = "year", cols = "jet")

# user defined breaks from 0-700 in intervals of 100 (note linear scale)
polarFreq(mydata, breaks = seq(0, 700, 100))

# more complicated user-defined breaks - useful for highlighting bins
# with a certain number of data points
polarFreq(mydata, breaks = c(0, 10, 50, 100, 250, 500, 700))

# source contribution plot and use of offset option
polarFreq(mydata, pollutant = "pm25", statistic
="weighted.mean", offset = 50, ws.int = 25, trans = FALSE)