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.
polarFreq(
mydata,
pollutant = NULL,
statistic = "frequency",
ws.int = 1,
wd.nint = 36,
grid.line = 5,
breaks = NULL,
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,
alpha = 1,
plot = TRUE,
...
)an openair object
A data frame minimally containing ws, wd and
date.
Mandatory. A pollutant name corresponding to a variable in
a data frame should be supplied e.g. pollutant = "nox"
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”. The option “frequency” (the
default) is the simplest and plots the frequency of wind speed/direction
in different bins. The scale therefore shows the counts in each bin. The
option “mean” will plot the mean concentration of a pollutant (see
next point) in wind speed/direction bins, and so on. Finally,
“weighted.mean” will plot the concentration of a pollutant weighted
by wind speed/direction. Each segment therefore provides the percentage
overall contribution to the total concentration. More information is given
in the examples. Note that for options other than “frequency”, it
is necessary to also provide the name of a pollutant. See function
cutData for further details.
Wind speed interval assumed. In some cases e.g. a low met mast, an interval of 0.5 may be more appropriate.
Number of intervals of wind direction.
Radial spacing of grid lines.
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 10, or a more flexible sequence e.g.
breaks = c(0, 1, 5, 7, 10), which may be useful for some
situations.
Colours to be used for plotting. Options include
“default”, “increment”, “heat”, “jet” and
RColorBrewer colours --- see the openair openColours
function for more details. For user defined the user can supply a list of
colour names recognised by R (type colours() to see the full list).
An example would be cols = c("yellow", "green", "blue"). cols
can also take the values "viridis", "magma",
"inferno", or "plasma" which are the viridis colour maps
ported from Python's Matplotlib library.
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) a better representation of the
distribution. If set to FALSE a linear scale is used.
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”, “year”, “weekday” and so
on. For example, type = "season" will produce four plots --- one for
each season.
It is also possible to choose type as another variable in the data
frame. If that variable is numeric, then the data will be split into four
quantiles (if possible) and labelled accordingly. If type is an existing
character or factor variable, then those categories/levels will be used
directly. This offers great flexibility for understanding the variation of
different variables and how they depend on one another.
Type can be up length two e.g. type = c("season", "weekday") will
produce a 2x2 plot split by season and day of the week. Note, when two
types are provided the first forms the columns and the second the rows.
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 > 1 because of the risk of
removing real data points. It is recommended to consider your data with
care. Also, the polarFreq function can be of use in such
circumstances.
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 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.int is greater than the maximum wind
speed. See example below.
The colour of the boundary of each wind speed/direction bin. The default is transparent. Another useful choice sometimes is "white".
Adds additional text/labels to the scale key. For example,
passing the options key.header = "header", key.footer = "footer1"
adds addition text above and below the scale key. These arguments are
passed to drawOpenKey via quickText, applying the
auto.text argument, to handle formatting.
see key.footer.
Location where the scale key is to plotted. Allowed
arguments currently include "top", "right", "bottom"
and "left".
Fine control of the scale key via drawOpenKey. See
drawOpenKey for further details.
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.
The alpha transparency to use for the plotting surface (a value
between 0 and 1 with zero being fully transparent and 1 fully opaque).
Setting a value below 1 can be useful when plotting surfaces on a map using
the package openairmaps.
Should a plot be produced? FALSE can be useful when
analysing data to extract plot components and plotting them in other ways.
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 northern) hemisphere handling of type =
"season". Similarly, common axis and title labelling options (such as
xlab, ylab, main) are passed to xyplot via
quickText to handle routine formatting.
David Carslaw
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.
Other polar directional analysis functions:
percentileRose(),
polarAnnulus(),
polarCluster(),
polarDiff(),
polarPlot(),
pollutionRose(),
windRose()
# basic wind frequency plot
polarFreq(mydata)
# wind frequencies by year
if (FALSE) polarFreq(mydata, type = "year")
# mean SO2 by year, showing only bins with at least 2 points
if (FALSE) polarFreq(mydata, pollutant = "so2", type = "year", statistic = "mean", min.bin = 2)
# weighted mean SO2 by year, showing only bins with at least 2 points
if (FALSE) polarFreq(mydata, pollutant = "so2", type = "year", statistic = "weighted.mean",
min.bin = 2)
#windRose for just 2000 and 2003 with different colours
if (FALSE) polarFreq(subset(mydata, format(date, "%Y") %in% c(2000, 2003)),
type = "year", cols = "turbo")
# user defined breaks from 0-700 in intervals of 100 (note linear scale)
if (FALSE) polarFreq(mydata, breaks = seq(0, 700, 100))
# more complicated user-defined breaks - useful for highlighting bins
# with a certain number of data points
if (FALSE) polarFreq(mydata, breaks = c(0, 10, 50, 100, 250, 500, 700))
# source contribution plot and use of offset option
if (FALSE) polarFreq(mydata, pollutant = "pm25", statistic
="weighted.mean", offset = 50, ws.int = 25, trans = FALSE)
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