read.sim.data {PHYLOGR}

Read Sim Files From PDSIMUL

Description

Reads ouput file(s) from PDSIMUL —simulation of phenotypic evolution along a phylogeny— and converts into an R data frame. Can add original data from inp or pdi file(s).

Usage

read.sim.data(sim.files, inp.files = NULL, pdi.files = NULL,
              phylip.file = NULL, variable.names = NULL,
              other.variables = NULL, max.num = 0)

Arguments

sim.files

the sim file(s), with path if needed.

inp.files

the inp file(s), with path if needed. Might have already been processed by read.inp.data. If already read, enter name unquoted.

pdi.files

the pdi file(s), with path if needed. Might have already been processed by read.pdi.data. If already read, enter name unquoted.

phylip.file

the phylip.file, with path if needed. Might have already been processed by read.phylip.data. If already read, enter name unquoted.

variable.names

a optional vector of variable names

other.variables

an optional set of other variables that you want to add to the data set. Can be a vector, a matrix, or a data frame. It must be the same length as the number of tips in you sim file(s).

max.num

if different from 0, the number of simulations to process.

Details

You will almost always want to provide inp or pdi or phylip file(s) since this is what will be used for the analyses of simulated data sets. The sim and pdi (or inp or phylip) files should match one to one; for example, you might have used f1.pdi to obtain f1.sim and f2.pdi to produce f2.sim. Then, the order of files ought to be

read.sim.data(c("f1.sim","f2.sim"),pdi.files=c("f1.pdi","f2.pdi"))

or

read.sim.data(c("f2.sim","f1.sim"),pdi.files=c("f2.pdi","f1.pdi"))

but NOT

read.sim.data(c("f1.sim","f2.sim"),pdi.files=c("f2.pdi","f1.pdi"))

and NOT

read.sim.data(c("f2.sim","f1.sim"),pdi.files=c("f1.pdi","f2.pdi"))

since the last two will yield meaningless results.

Remember that the number of sim file(s) and pdi (or inp) files must match (since that is the only way the number of columns will match).

This does not apply to PHYLIP infiles, since a PHYLIP infile can contain multiple columns.

Inp and Pdi files can not (yet) be mixed in a single call. If you need to, you should use read.inp.data and read.pdi.data, and change the class of the output data frame.

If you are entering inp files only, you don't need to provide the argument name. If you are using pdi files you need to provide the pdi.files=.

Value

A data frame (of class simul.phylog and data.frame) where the first column is called sim.counter, for simulation counter (with value 0 for the pdi, or inp, data set), second column is called tips, and the rest are data columns (including, if given, the other.variables column).

Author(s)

Ramon Diaz-Uriarte and Thodore Garland, Jr.

References

Diaz-Uriarte, R., and Garland, T., Jr., in prep. PHYLOGR: an R package for the analysis of comparative data via Monte Carlo simulations and generalized least squares approaches.

See Also

read.pdi.data, read.inp.data, read.phylip.data. There are generic functions plot and summary.

Examples

# First we need to find where the Examples directory is.
# You could enter it directly (see read.pdi.data for an example).
 path.to.example <- paste(path.package(package="PHYLOGR"),"Examples/",sep="/") 



# simple example
p49.i <- paste(path.to.example,"49lbr.pdi",sep="") 
p49.s <- paste(path.to.example,"49lbr.sim",sep="")
data.49.s <- read.sim.data(p49.s, pdi.files=p49.i)
data.49.s

# several files, added variables, change column names,
# and limit number of cases

f491s <- paste(path.to.example,"49lbr.sim",sep="")
f492s <- paste(path.to.example,"49hmt.sim",sep="")
f493s <- paste(path.to.example,"49ms.sim",sep="")

f491i <- paste(path.to.example,"49lbr.pdi",sep="")
f492i <- paste(path.to.example,"49hmt.pdi",sep="")
f493i <- paste(path.to.example,"49ms.pdi",sep="")


data.hb <-
      read.sim.data(c(f491s, f492s, f493s), pdi.files=c(f491i, f492i, f493i),
                    variable.names=c("x1","x2","x3","x4","x5","x6"),
                    other.variables=data.frame(
                                     mood=c(rep("good",15),
                                            rep("bad",15),
                                            rep("terrible",19)),
                                     color=c(rep("blue",20),
                                             rep("white",29))),
                     max.num=20)

data.hb