trendLevel(mydata, pollutant = "nox", x = "month", y = "hour", type = "year", rotate.axis = c(90, 0), n.levels = c(10, 10, 4), limits = c(0, 100), cols = "default", auto.text = TRUE, key.header = "use.stat.name", key.footer = pollutant, key.position = "right", key = TRUE, labels = NA, breaks = NA, statistic = c("mean", "max", "frequency"), stat.args = NULL, stat.safe.mode = TRUE, drop.unused.types = TRUE, col.na = "white", ...)trendLevel plot.mydata to sample to
produce the trendLevel plot.trendLevel x-axis. This is used with the y and
type options to bin the data before applying
statistic (see below). Other data series in mydata
can also be used. (Note: trendLevel does not allow
duplication in x, y and type options within a
call.)trendLevel y-axis and for additional conditioning,
respectively. As x above.y.trendLevel
x and y axes. The default, c(90, 0), rotates
the x axis by 90 degrees but does not rotate the y axis. (Note: If
only one value is supplied, this is applied to both axes; if more
than two values are supplied, only the first two are used.)x, y
and type data into if numeric. The default, c(10, 10,
4), cuts numeric x and y data into ten levels and
numeric type data into four levels. (Notes: This option is
ignored for date conditioning and factors. If less than three
values are supplied, three values are determined by recursion; if
more than three values are supplied, only the first three are
used.)trendLevel plot.trendLevel
surface. cols is passed to openColours for
evaluation. See ?openColours for more details.auto.text = TRUE passes common lattice
labelling terms (e.g. xlab for the x-axis, ylab for
the y-axis and main for the title) to the plot via
quickText to provide common text formatting. The
alternative auto.text = FALSE turns this option off and
passes any supplied labels to the plot without modification.key.header = "", key.footer = c("mean","nox") adds
the addition text as a scale footer. If enabled (auto.text =
TRUE), these arguments are passed to the scale key
(drawOpenKey) via quickText to handle
formatting. The term "get.stat.name", used as the default
key.header setting, is reserved and automatically adds
statistic function names or defaults to "level" when
unnamed functions are requested via statistic.drawOpenKey. See
?drawOpenKey for further details.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. labels must also be supplied.pollutant measurements with. Three options
are currently encoded: “mean” (default), “max” and
“frequency”. (Note: Functions can also be sent directly via
statistic. However, this option is still in development
and should be used with caution. See Details below.)statistic if
this is a function. The extra options should be supplied as a list of
named parameters. (see Details below.)statistic that most users can ignore. This option
returns NA instead of running statistic on binned
subsamples that are empty. Many common functions terminate with an error
message when applied to an empty dataset. So, this option provides a
mechanism to work with such functions. For a very few cases, e.g. for a
function that counted missing entries, it might need to be set to
FALSE (see Details below.)type conditioning cases.
Some conditioning options may generate empty cases for some data sets,
e.g. a hour of the day when no measurements were taken. Empty x
and y cases generate 'holes' in individual plots. However, empty
type cases would produce blank panels if plotted. Therefore, the
default, TRUE, excludes these empty panels from the plot. The
alternative FALSE plots all type panels.cutData for
type handling and levelplot in lattice for finer
control of the plot itself.trendLevel 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 <- trendLevel(mydata), 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.Summary statistics can also be extracted directly using results,
e.g. results(object) for output <- trendLevel(mydata).
trendLevel allows the use of third party summarising
functions via the statistic option. Any additional function
arguments not included within a function called using
statistic should be supplied as a list of named parameters
and sent using stat.args. For example, the encoded option
statistic = "mean" is equivalent to statistic = mean,
stat.args = list(na.rm = TRUE) or the R command mean(x,
na.rm= TRUE). Many R functions and user's own code could be
applied in a similar fashion, subject to the following
restrictions: the first argument sent to the function must be the
data series to be analysed; the name `x' cannot be used for any of
the extra options supplied in stat.args; and the function
should return the required answer as a numeric or NA. Note:
If the supplied function returns more than one answer, currently
only the first of these is retained and used by
trendLevel. All other returned information will be ignored
without warning. If the function terminates with an error when it
is sent an empty data series, the option stat.safe.mode
should not be set to FALSE or trendLevel may
fail. Note: The stat.safe.mode = TRUE option returns an NA
without warning for empty data series.
openColours and drawOpenKey for more
detailed plot control.
#basic use
#default statistic = "mean"
trendLevel(mydata, pollutant = "nox")
#applying same as 'own' statistic
my.mean <- function(x) mean(x, na.rm = TRUE)
trendLevel(mydata, pollutant = "nox", statistic = my.mean)
#alternative for 'third party' statistic
#trendLevel(mydata, pollutant = "nox", statistic = mean,
# stat.args = list(na.rm = TRUE))
## Not run:
# # example with categorical scale
# trendLevel(mydata, pollutant = "no2",
# border = "white", statistic = "max",
# breaks = c(0, 50, 100, 500),
# labels = c("low", "medium", "high"),
# cols = c("forestgreen", "yellow", "red"))
# ## End(Not run)
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