This function will plot data by month laid out in a conventional calendar format. The main purpose is to help rapidly visualise potentially complex data in a familiar way. Users can also choose to show daily mean wind vectors if wind speed and direction are available.
calendarPlot(
mydata,
pollutant = "nox",
year = 2003,
month = 1:12,
type = "default",
annotate = "date",
statistic = "mean",
cols = "heat",
limits = c(0, 100),
lim = NULL,
col.lim = c("grey30", "black"),
col.arrow = "black",
font.lim = c(1, 2),
cex.lim = c(0.6, 1),
digits = 0,
data.thresh = 0,
labels = NA,
breaks = NA,
w.shift = 0,
remove.empty = TRUE,
main = NULL,
key.header = "",
key.footer = "",
key.position = "right",
key = TRUE,
auto.text = TRUE,
plot = TRUE,
...
)
As well as generating the plot itself, calendarPlot
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 <- calendarPlot(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
.
A data frame minimally containing date
and at least one
other numeric variable. The date should be in either Date
format or
class POSIXct
.
Mandatory. A pollutant name corresponding to a variable in
a data frame should be supplied e.g. pollutant = "nox".
Year to plot e.g. year = 2003
. If not supplied all data
potentially spanning several years will be plotted.
If only certain month are required. By default the function
will plot an entire year even if months are missing. To only plot certain
months use the month
option where month is a numeric 1:12 e.g.
month = c(1, 12)
to only plot January and December.
Not yet implemented.
This option controls what appears on each day of the calendar. Can be: “date” --- shows day of the month; “wd” --- shows vector-averaged wind direction, or “ws” --- shows vector-averaged wind direction scaled by wind speed. Finally it can be “value” which shows the daily mean value.
Statistic passed to timeAverage
.
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")
Use this option to manually set the colour scale limits. This
is useful in the case when there is a need for two or more plots and a
consistent scale is needed on each. Set the limits to cover the maximimum
range of the data for all plots of interest. For example, if one plot had
data covering 0--60 and another 0--100, then set limits = c(0,
100)
. Note that data will be ignored if outside the limits range.
A threshold value to help differentiate values above and below
lim
. It is used when annotate = "value"
. See next few
options for control over the labels used.
For the annotation of concentration labels on each day. The
first sets the colour of the text below lim
and the second sets the
colour of the text above lim
.
The colour of the annotated wind direction / wind speed arrows.
For the annotation of concentration labels on each day. The
first sets the font of the text below lim
and the second sets the
font of the text above lim
. Note that font = 1 is normal text and
font = 2 is bold text.
For the annotation of concentration labels on each day. The
first sets the size of the text below lim
and the second sets the
size of the text above lim
.
The number of digits used to display concentration values when
annotate = "value"
.
Data capture threshold passed to timeAverage
. For
example, data.thresh = 75
means that at least 75% of the data must
be available in a day for the value to be calculate, else the data is
removed.
If a categorical scale is required then these labels will be
used. Note there is one less label than break. For example, labels =
c("good", "bad", "very bad")
. breaks
must also be supplied if
labels are given.
If a categorical scale is required then these breaks will be
used. For example, breaks = c(0, 50, 100, 1000)
. In this case
“good” corresponds to values berween 0 and 50 and so on. Users
should set the maximum value of breaks
to exceed the maximum data
value to ensure it is within the maximum final range e.g. 100--1000 in
this case.
Controls the order of the days of the week. By default the
plot shows Saturday first (w.shift = 0
). To change this so that it
starts on a Monday for example, set w.shift = 2
, and so on.
Should months with no data present be removed? Default
is TRUE
.
The plot title; default is pollutant and year.
Adds additional text/labels to the scale key. For example,
passing calendarPlot(mydata, key.header = "header", key.footer =
"footer")
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.header
.
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.
Should a plot be produced? FALSE
can be useful when
analysing data to extract calendar plot components and plotting them in
other ways.
Other graphical parameters are passed onto the lattice
function lattice:levelplot
, with common axis and title labelling
options (such as xlab
, ylab
, main
) being passed to
via quickText
to handle routine formatting.
David Carslaw
calendarPlot
will plot data in a conventional calendar format i.e. by
month and day of the week. Daily statistics are calculated using
timeAverage
, which by default will calculate the daily mean
concentration.
If wind direction is available it is then possible to plot the wind
direction vector on each day. This is very useful for getting a feel for the
meteorological conditions that affect pollutant concentrations. Note that if
hourly or higher time resolution are supplied, then calendarPlot
will
calculate daily averages using timeAverage
, which ensures that
wind directions are vector-averaged.
If wind speed is also available, then setting the option annotate =
"ws"
will plot the wind vectors whose length is scaled to the wind speed.
Thus information on the daily mean wind speed and direction are available.
It is also possible to plot categorical scales. This is useful where, for
example, an air quality index defines concentrations as bands e.g.
“good”, “poor”. In these cases users must supply labels
and corresponding breaks
.
Note that is is possible to pre-calculate concentrations in some way before
passing the data to calendarPlot
. For example
rollingMean
could be used to calculate rolling 8-hour mean
concentrations. The data can then be passed to calendarPlot
and
statistic = "max"
chosen, which will plot maximum daily 8-hour mean
concentrations.
timePlot
, timeVariation
# load example data from package
data(mydata)
# basic plot
calendarPlot(mydata, pollutant = "o3", year = 2003)
# show wind vectors
calendarPlot(mydata, pollutant = "o3", year = 2003, annotate = "wd")
if (FALSE) {
# show wind vectors scaled by wind speed and different colours
calendarPlot(mydata, pollutant = "o3", year = 2003, annotate = "ws",
cols = "heat")
# show only specific months with selectByDate
calendarPlot(selectByDate(mydata, month = c(3,6,10), year = 2003),
pollutant = "o3", year = 2003, annotate = "ws", cols = "heat")
# categorical scale example
calendarPlot(mydata, pollutant = "no2", breaks = c(0, 50, 100, 150, 1000),
labels = c("Very low", "Low", "High", "Very High"),
cols = c("lightblue", "green", "yellow", "red"), statistic = "max")
}
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