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Plot time series values in a conventional calendar format

Source: R/calendarPlot.R
calendarPlot.Rd

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.

Usage

calendarPlot(
  mydata,
  pollutant = "nox",
  year = NULL,
  month = NULL,
  annotate = "date",
  statistic = "mean",
  data.thresh = 0,
  percentile = NA,
  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),
  cex.date = 0.6,
  digits = 0,
  labels = NA,
  breaks = NA,
  w.shift = 0,
  w.abbr.len = 1,
  remove.empty = TRUE,
  show.year = TRUE,
  key.header = "",
  key.footer = "",
  key.position = "right",
  key = TRUE,
  auto.text = TRUE,
  plot = TRUE,
  ...
)

Arguments

mydata

A data frame of time series. Must include a date field and at least one variable to plot.

pollutant

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

year

Year to plot e.g. year = 2003. If not supplied all data potentially spanning several years will be plotted.

month

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.

annotate

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

  • "ws" — shows vector-averaged wind direction scaled by wind speed

  • "value" — shows the daily mean value

statistic

Statistic passed to timeAverage(). Note that if statistic %in% c("max", "min") and annotate is "ws" or "wd", the hour corresponding to the maximum/minimum concentration of polluant is used to provide the associated ws or wd and not the maximum/minimum daily ws or wd.

data.thresh

The data capture threshold to use (%). A value of zero means that all available data will be used in a particular period regardless if of the number of values available. Conversely, a value of 100 will mean that all data will need to be present for the average to be calculated, else it is recorded as NA. See also interval, start.date and end.date to see whether it is advisable to set these other options.

percentile

The percentile level in percent used when statistic = "percentile" and when aggregating the data with avg.time. More than one percentile level is allowed for type = "default" e.g. percentile = c(50, 95). Not used if avg.time = "default".

cols

Colours to be used for plotting; see openColours() for details.

limits

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 maximum 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.

lim

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.

col.lim

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.

col.arrow

The colour of the annotated wind direction / wind speed arrows.

font.lim

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.

cex.lim

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.

cex.date

The base size of the annotation text for the date.

digits

The number of digits used to display concentration values when annotate = "value".

labels

If a categorical scale is defined using breaks, then labels can be used to override the default category labels, e.g., labels = c("good", "bad", "very bad"). Note there is one less label than break.

breaks

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 between 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

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.

w.abbr.len

The default (1) abbreviates the days of the week to a single letter (e.g., in English, S/S/M/T/W/T/F). w.abbr.len defines the number of letters to abbreviate until. For example, w.abbr.len = 3 will abbreviate "Monday" to "Mon".

remove.empty

Should months with no data present be removed? Default is TRUE.

show.year

If only a single year is being plotted, should the calendar labels include the year label? TRUE creates labels like "January-2000", FALSE labels just as "January". If multiple years of data are detected, this option is forced to be TRUE.

key.header

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.

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.

plot

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 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.

Value

an openair object

Details

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.

See also

Other time series and trend functions: TheilSen(), runRegression(), smoothTrend(), timePlot(), timeProp(), timeVariation(), trendLevel()

Author

David Carslaw

Examples

# basic plot
calendarPlot(mydata, pollutant = "o3", year = 2003)


# show wind vectors
calendarPlot(mydata, pollutant = "o3", year = 2003, annotate = "wd")

if (FALSE) { # \dontrun{
# 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"
)

# UK daily air quality index
pm10.breaks <- c(0, 17, 34, 50, 59, 67, 75, 84, 92, 100, 1000)
calendarPlot(mydata, "pm10",
  year = 1999, breaks = pm10.breaks,
  labels = c(1:10), cols = "daqi", statistic = "mean", key.header = "DAQI"
)
} # }