R/blifestring.R

In abremout: Output functions for the Abernethy Reliability Methods package (abrem), including plotting.

# R package 'abremout'
# output methods for the abrem object
# May 2013, Jurgen Symynck
# Copyright 2013, Jurgen Symynck
#
# For the latest version of this file, check the Subversion repository at
# http://r-forge.r-project.org/projects/abernethy/
#
# Disclaimer:
#    The author is not affiliated with Dr. Abernethy or Wes Fulton - CEO of
#    Fulton Findings(TM) and author of the software package SuperSMITH
#-------------------------------------------------------------------------------
#    This program is free software: you can redistribute it and/or modify
#    it under the terms of the GNU General Public License as published by
#    the Free Software Foundation, either version 3 of the License, or
#    (at your option) any later version.
#
#    This program is distributed in the hope that it will be useful,
#    but WITHOUT ANY WARRANTY; without even the implied warranty of
#    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
#    GNU General Public License for more details.
#
#    You should have received a copy of the GNU General Public License
#    along with this program.  If not, see <http://www.gnu.org/licenses/>.
#
#    For more info on this software and its predecesser, the "weibulltoolkit",
#    consult following documents:
#
#    - "Weibull analysis using R, in a nutshell",
#      (Jurgen Symynck, Filip De Bal, 2010)
#    - "Monte Carlo pivotal confidence bounds for Weibull analysis
#      with implementations in R",
#      (Jurgen Symynck, Filip De Bal, 2011)
#
# +-----------------------------------+
# |  execute this program with R:     |
# |  http://www.r-project.org/        |
# +-----------------------------------+
#
Blifestring <- function(B,blicon,signif,...){
    # This functions creates a string for displaying the B-lives in the plot's
    # legend. missing input data result in an "NA". For example, the output
    # string could look like:
    #   "B10 = 9.86 | 50.13 | 103.4"
    # or
    #   "B1 = 9.86 | 50.13 | NA"
    si <- function(number)
        if(!is.null(number))signif(number,signif)
        else NA
      # shorthand writing of the signif() function
    qfun <- function(B,...){
        args <- as.list(unlist(...))
            # this doesn't look very nice, does it? but it works
        ret <- NULL
        if(!is.null(args$beta) && !is.null(args$eta)){
            # the fit type was weibull
            ret <- qweibull(B,args$beta,args$eta)
        }
        if(!is.null(args$meanlog) && !is.null(args$sdlog)){
            # the fit type was lognormal
            ret <- qlnorm(B,args$meanlog,args$sdlog)
        }
        if(!is.null(args$rate)){
            # the fit type was exponential
            ret <- qexp(B,args$rate)
        }
        ret
    }
    id <- function(x,y)isTRUE(all.equal(x,y))
    c1 <- is.null(blicon$bounds) || is.null(blicon$bounds$Lower)
    lo <- si(subset(blicon$bounds,
        sapply(blicon$bounds$unrel,id,B),Lower))
    c2 <- is.null(blicon$bounds) || is.null(blicon$bounds$Upper)
    up <- si(subset(blicon$bounds,
        sapply(blicon$bounds$unrel,id,B),Upper))
    ret <- paste(sep = "","    B",signif(100*B)," = ",
        ifelse(c1,
           "NA",lo),
        " | ",si(qfun(B,...)),
        " | ",ifelse(c2,
           "NA",up))
    ret
#    NA
}