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,
key.columns = 1, key.position = "right", key.title = proportion,
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 (by defatype 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",
"year", "weestatistic = "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 function fotimePlot 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
example, tcolumns 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 northern) avg.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 SO2 showing the contribution by wind sector
timeProp(mydata, pollutant = "so2", avg.time = "month", proportion = "wd")Run the code above in your browser using DataLab