OpasnetUtils/Update
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Contents
Description
Updates the output of an ovariable based on data and function. The function assumes that object@data is always available, but object@dependencies may be empty.
Code
# SETMETHOD UPDATE ########## update updates the output of an ovariable based on data and function.
####### The function assumes that object@data is always available, but object@dependencies may be empty.
temp <- setMethod(
f = "update",
signature = "ovariable",
definition = function(object) {
dat <- data.frame(Source = "Data", interpret(object@data))
if(ncol(object@dependencies) == 0 & nrow(object@dependencies) == 0) {
object@output <- dat
} else {
form <- object@formula(object@dependencies)
if(is.vector(form)) {form <- data.frame(Result = form)}
if(class(form) == "ovariable") {form <- form@output}
form <- data.frame(Source = "Formula", form)
object@output <- orbind(dat, form)
}
colnames(object@output)[colnames(object@output) == "Source"] <- paste("Source", object@name, sep = ".")
object@marginal <- c(TRUE, object@marginal) # This alone is not enough; orbind must operate with marginals as well.
return(object)
}
)
#### This code was taken out of update. It is still needed somewhere but not here.
# dep <- object@dependencies
# for(i in 1:length(dep)) {
# if(class(dep[[i]]) == "ovariable") {
# dep[[i]] <- dep[[i]]@output
# } else {
# if(length(grep("Op_(en|fi)", dep[[i]])) > 0) {
# dep[[i]] <- op_baseGetData("opasnet_base", dep[[i]])}
# else {
# if(class(dep[[i]]) != "data.frame" & !is.numeric(dep[[i]])) {
# dep[[i]] <- get(dep[[i]])
# }
# }
# }
# }
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Alternative
--# : To be able to control, when variables are evaluated we need functions EvalOutput and CheckMargins. Which determine the values of the output and margin of an ovariable. --Teemu R 13:06, 15 June 2012 (EEST)
# EvalOutput #################### evaluates the output slot of ovariables
##### Marginals should be also checked and updated here or elsewhere
EvalOutput <- function(variable, ...) {
#if (nrow(variable@data) > 0) { # if interpret can handle zero rows, no problem
a <- interpret(variable@data, ...)
#}
b <- variable@formula(variable@dependencies)
if (b == 0 & nrow(variable@data) == 0) {
stop(paste("No proper data nor formula defined for ", variable@name, "!\n", sep = ""))
}
if (b == 0) {
a$Source <- "Data"
return(a)
}
if (nrow(variable@data) == 0) {
b$Source <- "Formula"
return(b)
}
colnames(a)[colnames(a) == "Result"] <- "Data"
colnames(b)[colnames(b) == "Result"] <- "Formula"
return(
melt(
merge(a, b, all = TRUE, ...),
measure.vars = c("Data", "Formula"),
variable.name = "Source",
value.name = "Result",
...
)
)
}
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