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, ...)date, pollutant and a splitting variable
proportionmydata.proportion =
"cluster" if the output from polarCluster is
being analysed. If proportion is a numeric
variable it is split into 4 quantiles (type 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", "yearstatistic
= "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
functimePlot 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 examplpanel.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 default noavg.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")Run the code above in your browser using DataLab