Produce a plot in which the output of dc_win() and dc_ccp() on the same multivariate timeseries data is combined with the output of ts_level() on a state variable of the same length as the multivariate data.
plotDC_lvl(
df_win,
df_ccp = NA,
df_lvl,
win,
useVarNames = TRUE,
colOrder = TRUE,
useTimeVector = NA,
timeStamp = "31-01-1999",
doPlot = TRUE,
title = "Peaks versus Levels Plot",
subtitle = "",
xlabel = "Time",
ylabel = "",
levelName = "State variable"
)A data frame containing series of Dynamic Complexity values obtained by running function dc_win()
If an object generated by dc_ccp(), the levels shown in the plot will only be displayed if there is an cumulative complexity peak at that time point (default = NA )
A dataframe generated by ts_level() of a variable that is considered a state variable.
Size of window in which to calculate Dynamic Complexity. If win < NROW(df) the window will move along the time series with a stepsize of 1 (default = NROW(df))
Use the column names of df as variable names in the Complexity Resonance Diagram (default = TRUE)
If TRUE, the order of the columns in df determines the of variables on the y-axis. Use FALSE for alphabetic/numeric order. Use NA to sort by by mean value of Dynamic Complexity (default = TRUE)
Parameter used for plotting. A vector of length NROW(df), containing date/time information (default = NA)
If useTimeVector is not NA, a character string that can be passed to lubridate::stamp() to format the the dates/times passed in useTimeVector (default = "01-01-1999")
If TRUE shows a Complexity Resonance Diagram of the Dynamic Complexity and returns an invisible ggplot2::ggplot() object. (default = FALSE)
A title for the plot.
A subtitle for the plot.
A label for the x-axis.
A label for the y-axis.
A name for the state variable.
An invisible ggplot2 object.
Other Dynamic Complexity functions:
dc_ccp(),
dc_d(),
dc_f(),
dc_win(),
plotDC_ccp(),
plotDC_res()