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### Definition and construction method for class `ModelEnv'
setMethod("initialize", signature = "ModelEnv",
definition = function(.Object) {
### a new environment: all data are stored here
.Object@env <- new.env()
### extract a variable names `which' from the environment
.Object@get <-
function(which) get(which, envir = .Object@env,
inherits = FALSE)
### set a variable
.Object@set <-
function(which, data) assign(which, data, .Object@env)
return(.Object)
}
)
### some utility methods for ModelEnv onjects
setMethod("show", signature = "ModelEnv",
definition = function(object) {
cat("\n")
cat("A", class(object), "with \n\n")
n <- NULL
if (has(object, "response")) {
cat(" response variable(s): ",
colnamesnum(object@get("response")), "\n")
n <- nrow(object@get("response"))
}
else if (has(object, "responseMatrix")) {
cat(" response matrix column(s): ",
colnamesnum(object@get("responseMatrix")), "\n")
n <- nrow(object@get("responseMatrix"))
}
if (has(object, "input")) {
cat(" input variable(s): ",
colnamesnum(object@get("input")), "\n")
n <- nrow(object@get("input"))
}
else if (has(object, "designMatrix")) {
cat(" design matrix column(s): ",
colnamesnum(object@get("designMatrix")), "\n")
n <- nrow(object@get("designMatrix"))
}
if (is.null(n))
cat(" no observations\n")
else
cat(" number of observations:", n, "\n")
if(length(object@hooks)>0){
for(n in 1:length(object@hooks)){
if(n==1)
cat(" hooks : ")
else
cat(" ")
cat(paste(names(object@hooks)[n],"(",
paste(names(object@hooks[[n]]), collapse=", "),
")", sep=""), "\n")
}
}
cat("\n")
})
## Utility function: return either names or number of columns
colnamesnum <- function(x)
{
if(is.null(colnames(x)))
return(ncol(x))
else
return(colnames(x))
}
setGeneric("has", function(object, which) standardGeneric("has"))
setMethod("has", signature(object = "ModelEnv", which = "character"),
definition = function(object, which) {
exists(which, envir = object@env, inherits = FALSE)
}
)
setGeneric("dimension", function(object, which) standardGeneric("dimension"))
setMethod("dimension", signature(object = "ModelEnv", which = "character"),
definition = function(object, which) {
if (has(object, which))
eval(parse(text = paste("dim(",which,")")) , envir = object@env)
else
NULL
}
)
setGeneric("empty", function(object) standardGeneric("empty"))
setMethod("empty", signature(object = "ModelEnv"),
definition = function(object) length(ls(object@env))==0)
###**********************************************************
setGeneric("clone", function(object, ...) standardGeneric("clone"))
## the set() method of ModelEnvFormula objects uses lexical scope on
## various bits and pieces, hence cloning currently returns only a
## ModelEnv object, which only has a trivial get method and no set
## method
setMethod("clone", signature = "ModelEnv",
definition = function(object, copydata = TRUE) {
z <- new(class(object))
if (extends(class(object), "ModelEnvFormula"))
z@formula <- object@formula
### call set and get from object, however, they work in z@env
### <FIXME> what about parent.frame() ???
z@set <- function(which = NULL, data = NULL, frame = parent.frame(),
envir = z@env)
object@set(which = which, data = data, frame = frame, env = envir)
z@get <- function(which, data = NULL, frame = parent.frame(),
envir = z@env)
object@get(which = which, data = data, frame = frame, env = envir)
### </FIXME>
if (copydata) {
for (name in ls(object@env))
assign(name, object@get(name), envir = z@env)
}
return(z)
})
setGeneric("subset", function(x, ...) standardGeneric("subset"))
setMethod("subset", signature = "ModelEnv",
definition = function(x, subset, clone = TRUE, ...)
{
MYSUBSET <- function(x, subset, ...){
if (is(x, "matrix"))
x[subset,,drop=FALSE]
else
subset(x, subset, ...)
}
z <- MEapply(x, MYSUBSET, clone=clone, subset=subset, ...)
if (!clone)
invisible(z)
else
return(z)
})
### dpp, fit and predict generics for StatModel objects
setGeneric("fit", function(model, data, ...) standardGeneric("fit"))
setMethod("fit", signature = signature(model = "StatModel",
data = "ModelEnv"),
definition = function(model, data, ...)
model@fit(data, ...)
)
setGeneric("dpp", function(model, ...) standardGeneric("dpp"))
setMethod("dpp", signature = "StatModel",
definition = function(model, ...)
model@dpp(...)
)
### don't want to redefine stats:::predict, but ...
Predict <- function(object, ...) {
if ("statmodel" %in% names(object)) {
if (is(object$statmodel, "StatModel"))
return(object$statmodel@predict(object, ...))
}
return(predict(object, ...))
}
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