plot.ocp: Plot Object
In ocp: Bayesian Online Changepoint Detection

Plot ocpd object, to show the data and the R matrix probabilities.

## S3 method for class 'ocp'
plot(x, data = NULL, Rmat = NULL,
  graph_changepoints = TRUE, graph_probabilities = TRUE,
  showmaxes = TRUE, showmeans = TRUE, showcps = TRUE,
  showdata = TRUE, showRprobs = TRUE, cplistID = 3,
  main_title = "", trueCPs = NULL, showdataleg = TRUE,
  timepoints = NULL, timeunits = NULL, grey_digits = 4,
  varnames = NULL, ...)

`x`	the ocp object to plot
`data`	optional input data to plot
`Rmat`	optional input Rmat to plot
`graph_changepoints`	set to TRUE to graph the changepoints
`graph_probabilities`	set TRUE to show R matrix graphed
`showmaxes`	set TRUE to show the maxes in each columns in the R matrix plot
`showmeans`	set TRUE to show the means on the changepoints plot
`showcps`	set TRUE to show the the locations of changepoints
`showdata`	set TRUE to show the actual data points
`showRprobs`	set TRUE to show the probabilities in the R matrix
`cplistID`	method of extracting the changepoints: either "colmaxes", "threshcps", or "maxCPs" stored in the "changepoints_list" in the ocpd object
`main_title`	The main title for both plots, e.g. "Eurogames Data"
`trueCPs`	input the true known changepoints for comparison
`showdataleg`	Set true to show legend for the data points, set to false if there are too many dimensions, legend will be crowded.
`timepoints`	List of timepoints to use as x-axis labels.
`timeunits`	Units to display for the timescale on the plot.
`grey_digits`	The limit of decimal places to keep in the probability before converting to an index in the grey-scale, controls amount of detail and darkness of the shading on the plot.
`varnames`	List of variable names to display in the legend.
`...`	(optional) additional arguments, ignored.

simdatapts<- c(rnorm(n = 50), rnorm(n=50, 100))
ocpd1<- onlineCPD(simdatapts, getR=TRUE)
plot(ocpd1) # basic plot
plot(ocpd1, data= simdatapts) # plot with the original data
plot(ocpd1, trueCPs = c(1, 51)) # plot with showing the true changepoints
plot(ocpd1, main_title="Example plot", showmaxes = FALSE) # not showing max probabilities
plot(ocpd1, graph_changepoints=FALSE) # not showing the changepoints plot
plot(ocpd1, graph_probabilities=FALSE) # not showing the R matrix
plot(ocpd1, showRprobs=FALSE, showcps= FALSE)#plotting r with maxes but no probabilities,
# and not showing the locations of the found changepoints