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Last data update: 2014.03.03

R: Plots the realization of a process evolving on a phylogenetic...

drawPhylProcess

R Documentation

Plots the realization of a process evolving on a phylogenetic tree

Description

The function takes the output of the simulation functions and based on it plots the realization of the process on the tree. Can handle multiple traits, in this case each trait is plotted separately. The function does draw anything else (like axes) but the realization of the process. Any additions are up to the user.

Usage

drawPhylProcess(PhylTraitProcess, phyltree = NULL, vColours = "black", 
plotlayout = c(1, 1), additionalfigs = FALSE, modelParams = NULL, 
EvolModel = NULL, xlimits = NULL, ylimits = NULL)

Arguments

`PhylTraitProcess`	The simulated realization of the process, the direct output of one of the package's simulation function or a matrix (if `fullTrajectory` is `TRUE`). In the second case the matrix consists of k+1 columns, where k is the number of traits. The first column are the time instances, the next k the values of the traits at that instance. Since evolution takes place on a phylogenetic tree - there should be multiple copies of the same time moment, i.e. one for each branch of the tree.
`phyltree`	The phylogenetic tree, currently not used in the function but parameter is for future development
`vColours`	A vector of colours to be used for each trait. If length is less than the number of traits then colours are recycled
`plotlayout`	How many plots per page if more than one trait, i.e. `par(mfrow=plotlayout))`.
`additionalfigs`	Should additional items be plotted on each figure, the ancestral state and deterministic, Ψ when appropriate. If there are many regime levels then only the first column of Ψ is used.
`modelParams`	List of model parameters.
`EvolModel`	The evolutionary model.
`xlimits`	The x limits of the plot. Can be useful to fix if one wants to have a number of graphs on the same scale. This can be either a vector of length 2 (minimum and maximum value of the x-axis), or a list of length equalling the number of traits with each entry being a vector of length 2 or a matrix with two columns and rows equalling the number of traits. If not provided then the value is just the minimum and maximum from the data.
`ylimits`	The y limits of the plot. Can be useful to fix if one wants to have a number of graphs on the same scale. This can be either a vector of length 2 (minimum and maximum value of the x-axis), or a list of length equalling the number of traits with each entry being a vector of length 2 or a matrix with two columns and rows equalling the number of traits. If not provided then the value is just the minimum and maximum from the data.

Value

Returns a meaningless NA value.

Author(s)

Krzysztof Bartoszek

References

Bartoszek, K. and Pienaar, J. and Mostad. P. and Andersson, S. and Hansen, T. F. (2012) A phylogenetic comparative method for studying multivariate adaptation. Journal of Theoretical Biology 314:204-215.

Examples

## Not run:  ##It takes too long to run this
### We will first simulate a small phylogenetic tree using functions from ape and ouch.
### For simulating the tree one could also use alternative functions, eg. sim.bd.taxa 
### from the TreeSim package
phyltree<-ape2ouch(rtree(5))

### Correct the names of the internal node labels.
phyltree@nodelabels[1:(phyltree@nnodes-phyltree@nterm)]<-as.character(
1:(phyltree@nnodes-phyltree@nterm))

### Define a vector of regimes.
regimes<-c("small","small","small","large","small","small","large","large","large")

### Define SDE parameters to be able to simulate data under the OUOU model.
OUOUparameters<-list(vY0=matrix(c(1,-1,0.5),nrow=3,ncol=1),
A=rbind(c(9,0,0),c(0,5,0),c(0,0,1)),mPsi=cbind("small"=c(1,-1,0.5),
"large"=c(-1,1,0.5)),Syy=rbind(c(1,0.25,0.3),c(0,1,0.2),c(0,0,1)))

### Now simulate the data and remove the values corresponding to the internal nodes.
OUOUdata<-simulOUCHProcPhylTree(phyltree,OUOUparameters,regimes,NULL,fullTrajectory=TRUE)
drawPhylProcess(PhylTraitProcess=OUOUdata)

## End(Not run)