R/AllClasses.R

In usl: Analyze System Scalability with the Universal Scalability Law

# Copyright (c) 2013-2020 Stefan Moeding
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##############################################################################
#' Class "\code{USL}" for Universal Scalability Law models
#'
#' This class encapsulates the Universal Scalability Law. Use the function
#' \code{\link{usl}} to create new objects from this class.
#'
#' @slot frame The model frame.
#' @slot call The call used to create the model.
#' @slot regr The name of the regressor variable.
#' @slot resp The name of the response variable.
#' @slot coefficients The coefficients alpha, beta and gamma of the model.
#' @slot coef.std.err The standard errors for the coefficients alpha and beta.
#' @slot coef.names A vector with the names of the coefficients.
#' @slot fitted The fitted values of the model. This is a vector.
#' @slot residuals The residuals of the model. This is a vector.
#' @slot df.residual The degrees of freedom of the model.
#' @slot sigma The residual standard deviation of the model.
#' @slot limit The scalability limit as per Amdahl.
#' @slot peak A vector with the predictor and response values of the peak.
#' @slot optimal A vector with the optimal predictor and response values.
#' @slot efficiency The efficiency, e.g. speedup per processor.
#' @slot na.action The \code{na.action} used by the model.
#'
#' @seealso \code{\link{usl}}
#'
#' @name USL-class
#' @exportClass USL
setClass("USL",
         representation(frame         = "data.frame",
                        call          = "call",
                        regr          = "character",
                        resp          = "character",
                        coefficients  = "vector",
                        coef.std.err  = "vector",
                        coef.names    = "vector",
                        fitted        = "vector",
                        residuals     = "vector",
                        df.residual   = "integer",
                        sigma         = "numeric",
                        limit         = "numeric",
                        peak          = "vector",
                        optimal       = "vector",
                        efficiency    = "vector",
                        na.action     = "character"),
         prototype(coef.names    = c("alpha", "beta", "gamma"),
                   df.residual   = 0L,
                   na.action     = "na.omit"),
         validity = function(object) {
           err <- character()

           if (length(object@regr) == 0) {
             msg <- "name of regressor variable cannot be empty"
             err <- c(err, msg)
           }

           if (length(object@resp) == 0) {
             msg <- "name of regsponse variable cannot be empty"
             err <- c(err, msg)
           }

           if (length(err) == 0) return(TRUE) else return(err)
         })