R help - Aug 2007 - Managing global/local variables when creating R packages

I'm working on a package for R to create graphs for modeling 
interactions between latent variables in SEM.  At the moment, I have one 
function which performs the necessary steps to prepare the data for 
graphing, and then separate graphing functions depending on what graph 
type (or types) the user wants.  To get the prepped data from the setup 
function to the graphing functions, I currently put the data into a 
dataframe and declare it as a global variable (<<-).  Is there a way to 
make a data frame or a set of variables available to all the functions 
in a package but NOT to users?  As it is, if users were to use the var 
name of the data frame for something else, the data will be lost and 
they'll have to rerun setup before creating their graphs. 

Thanks,

Bethany

-- 
Bethany Kok
Graduate Student
Department of Psychology, Davie Hall, CB 3270
University of North Carolina at Chapel Hill
Chapel Hill, NC 27599

TEL:  919-667-4752

1. This probably translates best from what you have.  It places
the object in the package space itself.  The lattice package illustrates
that.  Download the lattice package code from CRAN and look at
.LatticeEnv defined in zzz.R there.  Also try this:

library(lattice)
lattice:::.LatticeEnv
ls(lattice:::.LatticeEnv)

2. Another approach is to output an object with the data from your
constructor function and pass it through the argument list to
each consumer function.  The object could be implemented as
a list, environment, S3 object, S4 object, proto package object or with the
R.oo package or implicitly as demo(scoping) shows.

On 8/2/07, Bethany Kok <bethanyk at email.unc.edu>
wrote:
> I'm working on a package for R to create graphs for modeling
> interactions between latent variables in SEM.  At the moment, I have one
> function which performs the necessary steps to prepare the data for
> graphing, and then separate graphing functions depending on what graph
> type (or types) the user wants.  To get the prepped data from the setup
> function to the graphing functions, I currently put the data into a
> dataframe and declare it as a global variable (<<-).  Is there a way
to
> make a data frame or a set of variables available to all the functions
> in a package but NOT to users?  As it is, if users were to use the var
> name of the data frame for something else, the data will be lost and
> they'll have to rerun setup before creating their graphs.
>
> Thanks,
>
> Bethany
>
> --
> Bethany Kok
> Graduate Student
> Department of Psychology, Davie Hall, CB 3270
> University of North Carolina at Chapel Hill
> Chapel Hill, NC 27599
>
> TEL:  919-667-4752
>
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

On Thu, 2 Aug 2007, Bethany Kok wrote:
> I'm working on a package for R to create graphs for modeling
> interactions between latent variables in SEM.  At the moment, I have one
> function which performs the necessary steps to prepare the data for
> graphing, and then separate graphing functions depending on what graph
> type (or types) the user wants.  To get the prepped data from the setup
> function to the graphing functions, I currently put the data into a
> dataframe and declare it as a global variable (<<-).  Is there a way
to
> make a data frame or a set of variables available to all the functions
> in a package but NOT to users?  As it is, if users were to use the var
> name of the data frame for something else, the data will be lost and
> they'll have to rerun setup before creating their graphs.
You can do this via namespaces (if an object of that name exists in the 
namespace, <<- will update the object in the namespace, and functions in 
the package will look first in the namespace).

However, this stateful behaviour goes against the philosophy of functional 
languages, and the normal way to do this is for the setup function to 
return a classed object containing the 'prepped data' which is then
passed
to the graphing functions.  Users familiar with R will find such a design 
much easier to work with.  (Those familiar with certain other statistical 
packages may not.)

-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595