\HeaderA{plot-methods}{Method for visualizing mutagenetic trees mixture models}{plot.Rdash.methods}
\aliasA{plot}{plot-methods}{plot}
\aliasA{plot,RtreemixModel,missing-method}{plot-methods}{plot,RtreemixModel,missing.Rdash.method}
\keyword{methods}{plot-methods}
\begin{Description}\relax
Function for visualizing the tree components comprising a mutagenetic trees mixture model.  
The user can also specify the \code{fontSize} used for the text labels of the nodes and the edges of the plotted trees. 
Additionally, one can use the parameter \code{k} to plot a certain tree component from the 
mixture model.
\end{Description}
\begin{Usage}
\begin{verbatim}
## S4 method for signature 'RtreemixModel, missing':
plot(x, y, ...)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{x}] An \code{RtreemixModel} object giving the mixture model that should be visualized.
\item[\code{y}] Not specified.
\item[\code{...}] \code{fontSize} is the size of the text labels of the nodes and the edges of the tree components. The default value is 8.
\code{k} is a \code{numeric} giving the specific tree component from the given mixture model that should be plotted. Its value 
can be from one to the number of tree components in the given model.

\end{ldescription}
\end{Arguments}
\begin{Details}\relax
The value of \code{k} (that gives the tree component to be plotted) can take \code{"integer"} values from one to the number of tree components.
\end{Details}
\begin{Value}
The method returns a plot of the mixture model model.
\end{Value}
\begin{Author}\relax
Jasmina Bogojeska
\end{Author}
\begin{References}\relax
Learning multiple evolutionary pathways from cross-sectional
data, N. Beerenwinkel et al.
\end{References}
\begin{SeeAlso}\relax
\code{\LinkA{RtreemixData-class}{RtreemixData.Rdash.class}}, \code{\LinkA{RtreemixModel-class}{RtreemixModel.Rdash.class}},
\code{\LinkA{generate-methods}{generate.Rdash.methods}}
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
## Generate a random RtreemixModel object.
rand.mod <- generate(K = 2, no.events = 7, noise.tree = TRUE, prob = c(0.2, 0.8))

## Visualize it.
plot(rand.mod)

## Increase the font size of the text labels in the plot.
plot(rand.mod, fontSize = 10)

## Plot the second component of the mixture model rand.mod
plot(rand.mod, k = 2)

\end{ExampleCode}
\end{Examples}

