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"), font.lim = c(1, 2), cex.lim = c(0.6, 1), digits = 0, data.thresh = 0, labels = NA, breaks = NA, w.shift = 0, main = paste(pollutant, "in", year), key.header = "", key.footer = "", key.position = "right", key = TRUE, auto.text = TRUE, ...)date and at
least one other numeric variable. The date should be in either
Date format or class POSIXct.pollutant
= "nox". year = 2003.month option where month
is a numeric 1:12 e.g. month = c(1, 12) to only plot
January and December.timeAverage.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")limits = c(0, 100). Note that
data will be ignored if outside the limits range.lim. It is used when annotate = "value".
See next few options for control over the labels used.lim and
the second sets the colour of the text above lim.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.lim and
the second sets the size of the text above lim.annotate = "value".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.labels = c("good", "bad", "very bad").
breaks must also be supplied if labels are given.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.w.shift = 0). To
change this so that it starts on a Monday for example, set
w.shift = 2, and so on.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.key.header."top",
"right", "bottom" and "left".drawOpenKey.
See drawOpenKey for further details.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.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.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.
calendarPlot will plot one year of data in a conventional
calendar format i.e. by month and day of the week. The main
purpose of this function is to make it easy to visualise data in a
familiar way. 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")
## Not run:
# # 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")
#
# ## End(Not run)
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