polarCluster
and trajCluster
that consider local and regional (back trajectory)
cluster analysis respectively. However, the function has
more general use for understanding time series data.timeProp(mydata, pollutant = "nox",
proportion = "cluster", avg.time = "day",
type = "default", statistic = "mean",
normalise = FALSE, cols = "Set1", date.breaks = 7,
date.format = NULL, box.width = 1, key.columns = 1,
key.position = "right", auto.text = TRUE, ...)
obs
and mod
representing observed and
modelled values.mydata
.proportion =
"cluster"
if the output from polarCluster
is
being analysed. If proportion
is a numeric
variable it is split into 4 quantiltype
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", "statistic
= "frequency"
will give the proportion in terms of
counts.normalise = TRUE
then each
time interval is scaled to 100. This is helpful to show
the relative (percentage) contribution of the
proportions.RColorBrewer
colours --- see the openair
openColours
timePlot
generally sets the
date format sensibly there can be some situations where
the user wishes to have more control. For format types
see strptime
. For expanel.boxplot
. A value of 1 means that there is no
gap between the boxes.columns
to be less than the number of
pollutants.TRUE
(default) or
FALSE
. If TRUE
titles and axis labels etc.
will automatically try and format pollutant names and
units properly e.g. by subscripting the `2' in NO2.timeProp
and cutData
. For example,
timeProp
passes the option hemisphere =
"southern"
on to cutData
to provide southern
(rather than defaulavg.time
.
The plot shows the value of pollutant
on the
y-axis (averaged according to avg.time
). The time
intervals are made up of bars split according to
proportion
. The bars therefore show how the total
value of pollutant
is made up for any time
interval.timePlot
for time series plotting,
polarCluster
for cluster analysis of
bivariate polar plots and trajCluster
for
cluster analysis of HYSPLIT back trajectories.## See manual for more examples e.g. related to clustering
## monthly plot of NOx showing the contribution by wind sector
timeProp(mydata, pollutant="so2", avg.time="month", proportion="wd")
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