Gems.R

From Organic Design wiki
"BiplotC" <-
structure(function(xx, comps = c(1, 2), cex = c(.8, .4), pchs = 0:6, 
           colour.c = c("black"), colour.v = c("blue"), scale = 1,
           clust = 1, no.clust = 3, lab.cex = 1.2, ax.cex  = 0.9,
           xylab = "PC", expand = 1, xlim = NULL, ylim = NULL, 
           main = NULL, xlab = NULL, ylab = NULL)
{
  ## Purpose: Adds more options to BiplotB
  ## ----------------------------------------------------------------------
  ## Modified from: BiplotB
  ## ----------------------------------------------------------------------
  ## Arguments:
  ##     colour.c:  colour vector for cases
  ##     colour.v:  colour vector for variables
  ##     clust:     are we clustering cases (1) or variables (2)?
  ##                If no clustering is wanted, use BiplotB2
  ##     no.clust   number of clusters
  ##     xylab:     Prefix to x- and y-labels
  ## ----------------------------------------------------------------------
  ## Author:  Zaphod Beeblebrox, Date: 16 Aug 2006, 09:49 

  if(class(xx) == "princomp"){
    scores <- xx$scores[, paste("Comp", comps, sep = ".")]
    loadings <- xx$loadings[, paste("Comp", comps, sep = ".")]
  }
  if(class(xx) == "prcomp"){
    scores <- xx$x[, paste("PC", comps, sep = "")]
    loadings <- xx$rotation[, paste("PC", comps, sep = "")]
  }
  importance <- round(100*xx$sdev/max(cumsum(xx$sdev)), 1) # Variation attributed
  import.lab <- importance[comps]
  x <- scores
  y <- loadings
  n <- nrow(scores)
  p <- nrow(loadings)
## Copy in lam stuff from the default (omit n.obs stuff)
  lam <- xx$sdev[comps]
  lam <- lam * sqrt(n)
  if (scale < 0 || scale > 1) 
    warning("'scale' is outside [0, 1]")
  if (scale != 0) 
    lam <- lam^scale
  else lam <- 1
  x <- t(t(scores)/lam) 
  y <- t(t(loadings)*lam)
  unsigned.range <- function(x) c(-abs(min(x)), abs(max(x)))
  rangx1 <- unsigned.range(x[, 1])
  rangx2 <- unsigned.range(x[, 2])
  rangy1 <- unsigned.range(y[, 1])
  rangy2 <- unsigned.range(y[, 2])
### fix up xlim and ylim
  if (missing(xlim) && missing(ylim)) 
    xlim <- ylim <- rangx1 <- rangx2 <- range(rangx1, rangx2)
  else if (missing(xlim)) 
    xlim <- rangx1
  else if (missing(ylim)) 
    ylim <- rangx2
### Ratio of variable sclae to cases scale
  ratio <- max(rangy1/rangx1, rangy2/rangx2)/expand
  blank.plot(range(x), range(x), xlim = xlim, ylim = ylim)
  ## work out scaling factor for the loadings
  xax.tik <- pretty(range(xlim))
  xax.tik.at <- xax.tik 
  yax.tik <- pretty(range(ylim))
  yax.tik.at <- yax.tik 
  box()
  abline(v = 0, col = "grey")
  abline(h = 0, col = "grey")
### Decide on what clustering is to happen
  if(clust == 1 | clust == "case"){ # We're clustering cases
    if(length(colour.c) < no.clust)
        colour.pal.c <- brewer.pal(8, "Dark2")[1:no.clust]
    else colour.pal.c <- colour.c
    case.cluster <- pam(x, no.clust)
    colour.c <- colour.pal.c[case.cluster$clustering]
  }
  
  if(clust == 2 | clust == "variable"){ # We're clustering variables
     if(length(colour.v) < no.clust)
       colour.pal.v <- brewer.pal(8, "Dark2")[1:no.clust]
     else colour.pal.v <- colour.v
     variable.cluster <- pam(y, no.clust)
     colour.v <- colour.pal.v[variable.cluster$clustering]
   }
 
  items <- rownames(scores) # can stay non-generic for now
  ## Get same letters into groups
  ## regions <- gsub("[0-9]", "", items)
  text(x[,1], x[,2], items, cex = cex[1], col = colour.c)
  axis(2, cex.axis = ax.cex, mgp = c(1, .8, 0), at = yax.tik.at,
       labels = yax.tik)
  axis(1, cex.axis = ax.cex, mgp = c(1, .8, 0), at = xax.tik.at,
       labels = xax.tik)
  if(is.null(xlab))
    xlab <- ppaste(xylab, comps[1], " (",import.lab[1], "%)")
  if(is.null(ylab))
    ylab <- ppaste(xylab, comps[2], " (",import.lab[2], "%)")
    
  mtext(xlab, side = 1, line = 2.2, cex = lab.cex)
  mtext(ylab, side = 2, line = 2.5, cex = lab.cex)

    text(y[, 1]/ratio, y[, 2]/ratio,
         rownames(loadings), cex = cex[2], col = colour.v)
}
, comment = "18/08/2006")
"JIM" <-
structure(function()
{
  ## Purpose: Loads Jim Lindsay's libraries for gnlm
  ## ----------------------------------------------------------------------
  ## Arguments:
  ## ----------------------------------------------------------------------
  ## Author: Zaphod Beeblebrox, Date:  4 Feb 2002, 07:57

  library(rmutil, lib.loc = "/home/hrapgc/Rstuff/library/")
  library(gnlm, lib.loc = "/home/hrapgc/Rstuff/library/")

}
, comment = "01/07/2002")
"MAP" <-
structure(function()
  {
### Installs maps library
    library(maps, lib.loc = "/home/pat/Rstuff/library/")
  }
, comment = "06/06/2001")
"MASS" <-
structure(function()
  {
                                        # Installs MASS library
    library(MASS, lib.loc = "/home/hrapgc/Rstuff/library")
  }
, comment = "03/10/2001")
"PLS" <-
structure(function()
  {
### Installs Partial Least Squares library
    library(pls, lib.loc = "/home/hrapgc/patrick/library")
  }
, comment = "09/05/2001")
"Plot.rpart" <-
structure(function(x, uniform=FALSE, branch=1, compress=FALSE,
                       nspace, margin=0, minbranch=.3, col = "turquoise",...)
{
  ## Purpose: Allows different colours for lines in plot.rpart
  ## ----------------------------------------------------------------------
  ## Modified from: 
  ## ----------------------------------------------------------------------
  ## Arguments: 
  ## ----------------------------------------------------------------------
  ## Author: Patrick Connolly, Creation date: 26 Jan 2005, 09:54
    if(!inherits(x, "rpart"))
	    stop("Not an rpart object")
    if (!is.null(x$frame$splits)) x <- rpconvert(x)  #help for old objects

    if (compress & missing(nspace)) nspace <- branch
    if (!compress) nspace <- -1     #means no compression
    dev <- dev.cur()
    if (dev == 1) dev <- 2
    assign(paste(".rpart.parms", dev, sep = "."),
            list(uniform=uniform, branch=branch, nspace=nspace,
		 minbranch=minbranch), envir=.GlobalEnv)

    #define the plot region
    temp <- rpart:::rpartco(x)
    xx <- temp$x
    yy <- temp$y
    temp1 <- range(xx) + diff(range(xx))*c(-margin, margin)
    temp2 <- range(yy) + diff(range(yy))*c(-margin, margin)
    plot(temp1, temp2, type='n', axes=FALSE, xlab='', ylab='', ...)

    # Draw a series of horseshoes or V's, left son, up, down to right son
    #   NA's in the vector cause lines() to "lift the pen"
    node <- as.numeric(row.names(x$frame))
    temp <- rpart:::rpart.branch(xx, yy, node, branch)

    if (branch>0) text(xx[1], yy[1], '|')
    lines(c(temp$x), c(temp$y), col = col)
    invisible(list(x=xx, y=yy))
  }
, comment = "26/01/2005")
"SURV" <-
structure(function() library(survival5, lib.loc = "/home/hrapgc/patrick/library")
, comment = "27/04/2001")
"Text.rpart" <-
structure(function(x, splits = TRUE, label = "yval", FUN = text, all=FALSE,
             pretty = NULL, digits = getOption("digits") - 3,
             use.n=FALSE, fancy=FALSE, fwidth=.8, fheight =.8,
                       leaf.col = "darkorange",...)
{
  ## Purpose: Modifies text.rpart to position text better
  ## ----------------------------------------------------------------------
  ## Modified from: text.rpart in the basic distribution
  ## ----------------------------------------------------------------------
  ## Arguments: 
  ## ----------------------------------------------------------------------
  ## Author: Patrick Connolly, Creation date: 21 Jan 2005, 16:39
    if(!inherits(x, "rpart")) stop("Not legitimate rpart")
    if(!is.null(x$frame$splits)) x <- rpconvert(x)#Backwards compatability

    frame <- x$frame
    col <- names(frame)
    ylevels <- attr(x,'ylevels')
    if(!is.null(ylevels <- attr(x, "ylevels")))
        col <- c(col, ylevels)
    if(is.na(match(label, col)))
        stop("Label must be a column label of the frame component of the tree"
             )
    cxy <- par("cxy")                   #character width and height
    if(!is.null(srt <- list(...)$srt) && srt == 90)
        cxy <- rev(cxy)
    xy <- rpart:::rpartco(x)

    node <- as.numeric(row.names(x$frame))
    is.left <- (node%%2 ==0)            #left hand sons
    node.left <- node[is.left]
    parent <- match(node.left/2, node)

    ##Put left splits at the parent node

    if(splits) {
        left.child <- match(2 * node, node)
        right.child <- match(node * 2 + 1, node)
        rows <- labels(x, pretty = pretty)

        if(fancy) {
            ## put split labels on branches instead of nodes

            xytmp <- rpart.branch(x=xy$x,y=xy$y,node=node)
            leftptx <- (xytmp$x[2,]+xytmp$x[1,])/2
            leftpty <- (xytmp$y[2,]+xytmp$y[1,])/2
            rightptx <- (xytmp$x[3,]+xytmp$x[4,])/2
            rightpty <- (xytmp$y[3,]+xytmp$y[4,])/2

            FUN(leftptx,leftpty+.52*cxy[2],
                rows[left.child[!is.na(left.child)]],...)
            FUN(rightptx,rightpty-.52*cxy[2],
                rows[right.child[!is.na(right.child)]],...)
        }

        else FUN(xy$x, xy$y + 0.5 * cxy[2], rows[left.child], ...)
    }
    leaves <- if(all) rep(TRUE, nrow(frame)) else frame$var == "<leaf>"
    if (is.null(frame$yval2))
        stat <- x$functions$text(yval=frame$yval[leaves],
                                 dev=frame$dev[leaves],
                                 wt=frame$wt[leaves],
                                 ylevel=ylevels, digits=digits,
                                 n=frame$n[leaves], use.n=use.n)
    else
        stat <- x$functions$text(yval=frame$yval2[leaves,],
                                 dev=frame$dev[leaves],
                                 wt=frame$wt[leaves],
                                 ylevel=ylevels, digits=digits,
                                 n=frame$n[leaves], use.n=use.n)


    oval <- function(middlex,middley,a,b) {

        theta <- seq(0,2*pi,pi/30)
        newx <- middlex + a*cos(theta)
        newy <- middley + b*sin(theta)

        polygon(newx,newy,border=TRUE,col=0)
        ##	     polygon(newx,newy,border=T)
    }

    rectangle <- function(middlex, middley,a,b) {

        newx <- middlex + c(a,a,-a,-a)
        newy <- middley + c(b,-b,-b,b)

        polygon(newx,newy,border=TRUE,col=0)
        ##	  polygon(newx,newy,border=T)
    }

    if(fancy) {

        ## find maximum length of stat
        maxlen <- max(string.bounding.box(stat)$columns) + 1
        maxht <- max(string.bounding.box(stat)$rows) +1

        if(fwidth<1)  a.length <- fwidth*cxy[1]*maxlen
        else a.length <- fwidth*cxy[1]

        if(fheight<1) b.length <- fheight*cxy[2]*maxht
        else b.length <- fheight*cxy[2]

### create ovals and rectangles here
        ## sqrt(2) creates the smallest oval that fits around the
        ## best fitting rectangle
        for(i in parent) oval(xy$x[i],xy$y[i],
                              a=sqrt(2)*a.length/2, b=sqrt(2)*b.length/2)
        child <- match(node[frame$var=="<leaf>"],node)
        for(i in child) rectangle(xy$x[i],xy$y[i],
                                  a=a.length/2,b=b.length/2)
    }

    ##if FUN=text then adj=1 puts the split label to the left of the
    ##    split rather than centered
    ##Allow labels at all or just leaf nodes

    ## stick values on nodes
    if(fancy) FUN(xy$x[leaves], xy$y[leaves] + .5 * cxy[2], stat, ...)
    else FUN(xy$x[leaves], xy$y[leaves] -0.9 * cxy[2], stat, adj=.5,
             col = leaf.col, ...)

    invisible()

  }
, comment = "09/02/2005")
"Updown" <-
structure(function(cv)
{
  ## Bill Venables's function (adjusted) to make uppercase first
  ##  letters, and lower the rest.
  cv <- casefold(cv)
  first <- substring(cv, 1, 1)
  FIRST <- casefold(first, upper = T)
  paste(FIRST, substring(cv, 2), sep = "")
}
, comment = "05/04/2002")
"add.text" <-
structure(function(xp = 0.5, yp = 0.5, tex = NULL, ygap = 0.05, cex = 0.8, adj = 0,
           adj.y = 0, font = 1, col = "black", srt = 0, ...)
{
### Cut down from bar.legs: used only for text; can also be rotated
### labels is character vector of legend text
### the length of tex sets the length of other vectors
### 
### 
### Establish positions in page co-ordinates [0,1] then use regular text function
### From Splus a/c began 11/07/1997
### Added vertical adj bit 17/6/04
  uu <- par()$usr
  xd <- diff(uu[1:2])
  yd <- diff(uu[3:4])
  yp <- yp - (seq(along = tex) - 1) * ygap
  if(length(xp) == 1)
    xp <- rep(xp, length(tex))
  if(length(cex) == 1)
    cex <- rep(cex, length(xp))
  if(length(adj) == 1)
    adj <- rep(adj, length(xp))
  if(length(font) == 1)
    font <- rep(font, length(xp))
  if(length(col) == 1)
    col <- rep(col, length(xp))
  xh <- uu[1] + xd * xp
  yh <- uu[3] + yd * yp
  for(i in 1:length(tex)) {
    text(xh[i], yh[i], tex[i], adj = c(adj[i], adj.y), cex = cex[i],
         font = font[i], srt = srt, col = col[i], ...)
  }
}
, comment = "25/10/2006")
"agg" <-
structure(function(data, by, FUNS)
{
#
#   DATE WRITTEN:  14 May 1998
#   AUTHOR:  John R. Wallace (jrw@fish.washington.edu)
#
    out <- aggregate.data.frame(data, by, eval(parse(text = FUNS[1])))
    for(i in 2:length(FUNS)) {
       tmp <- aggregate.data.frame(data, by, eval(parse(text = FUNS[i])))
       tmp <- tmp[, ncol(tmp)]
       out <- cbind(out, tmp)
    }
    dimnames(out)[[2]][ - (1:length(by))] <- FUNS
    out
}
, comment = "15/09/1998")
"allfit" <-
structure(function(choice = 1, mn = NULL, xfun = function(x)
x, xfun.inv = NULL, datafun = glean.ramp, link = "cloglog", interval = T, pc = 
    c(50, 95, 99), pc.monotone = c(loess = 50, loess = 99), plot.monotone = 
    NULL, cutoff.mono = 0, span.mono = 1, pc.spline = NULL, plot.spline = F, 
    p.min = NULL, printdat = F, save.resid = F, cm.strategy = "adjust.later", 
    ext = "", cm.code = NULL, print.plot = F, full.robust = F, ...)
{
  ## Purpose: 
  ## ----------------------------------------------------------------------
  ## Modified from: 
  ## ----------------------------------------------------------------------
  ## Arguments: 
  ## ----------------------------------------------------------------------
  ## Author: John Maindonald, Creation date:  7 Sep 1994 (about)
#Changed May 1999 to make pc = 95 part of the default
    xtra <- list(...)
    new.page <- T
    if(!is.null(names(xtra))) {
       h <- xtra$h
       ri <- xtra$ri
       cj <- xtra$cj
       if(any(is.na(match(names(xtra), c("h", "ri", "cj")))))
          cat("\n*** There are one or more illegal parameters to allfit()\n", 
             "from among the names:", names(xtra), "***\n")
    }
    else {
       ri <- 3
       cj <- 4
       h <- NULL
    }
    if(is.character(choice))
       cat(choice)
    if((!is.null(plot.monotone)) | plot.spline) {
       oldpar <- par(mfrow = c(ri, cj), oma = c(0, 1, 5, 0))
       on.exit(par(oldpar))
    }
    cat("   ", date(), fill = T)
    cat("** Link =", link, "**  x-transformation =", as.character(substitute(
       xfun)), "**", fill = T)
    if(!is.null(h))
       u <- datafun(choice = choice, h = h)
    else u <- datafun(choice = choice)
    if(is.null(cm.code))
       cm.code <- u$cm.code
    if(is.null(cm.code))
       cm.code <- 0
    cm.allcodes <- u$cm.allcodes
    temp <- u$temp
    stage <- u$stage
    if(all(xfun(exp(1:5)) == (1:5)))
       takelog <- T
    else takelog <- F
    idset <- u$id
    uset <- u$trial.id.order
    if(is.null(uset))
       uset <- unique(idset)
    if(is.null(mn))
       mn <- 1:length(uset)
    if(max(mn) > length(uset)) {
       maxj <- length(uset)
       cat("You have specified a final dataset no.", max(mn), "\nwhereas", maxj,
          "datasets only are available\n")
       keep <- mn <= maxj
       if(sum(keep) > 0)
          mn <- mn[keep]
       else stop(paste("Dataset(s)", mn, "not found."))
    }
    alltimes <- u$times
    alltot <- u$total
    alldead <- u$dead
    cm <- u$cm
    cmtot <- u$cmtot
    cutx <- u$cutx
    offset <- u$offset
    xaxtitle <- u$xaxtitle
    treat <- u$treat
    maint <- u$maint
    add.main <- u$add.main
    legend <- u$legend
    leg.brief <- u$leg.brief
    xxlabels <- u$xlabels
    here <- !is.na(alltimes) & !is.na(alldead) & !is.na(alltot)
    print(maint)
    if(!is.null(pc)) {
       ltmat <- matrix(, nrow = length(mn), ncol = length(pc))
       semat <- matrix(, nrow = length(mn), ncol = length(pc))
       dimnames(ltmat) <- list(NULL, paste(pc))
    }
    else {
       ltmat <- NULL
       semat <- NULL
    }
    if(!is.null(pc.spline)) {
       ltmat.spline <- matrix(, nrow = length(mn), ncol = length(pc.spline))
       dimnames(ltmat.spline) <- list(NULL, paste(pc.spline))
    }
    else ltmat.spline <- NULL
    if(!is.null(pc.monotone)) {
       ltmat.monotone <- matrix(, nrow = length(mn), ncol = length(pc.monotone)
          )
       dimnames(ltmat.monotone) <- list(NULL, paste(pc.monotone))
    }
    else ltmat.monotone <- NULL
    dimnames(ltmat) <- list(NULL, paste(pc))
    dimnames(semat) <- list(NULL, paste(pc))
    b0 <- array(, length(mn))
    b1 <- array(, length(mn))
    cm.est <- array(, length(mn))
    dev <- array(, length(mn))
    df <- array(, length(mn))
    dev.robust <- array(, length(mn))
    df.robust <- array(, length(mn))
    times.list <- vector("list", length(mn))
    total.list <- vector("list", length(mn))
    resid.list <- vector("list", length(mn))
    resid.dev.list <- vector("list", length(mn))
    leg.allfit <- array(, length(mn))
    i <- 0
    for(j in mn) {
       i <- i + 1
       idj <- uset[j]
       here.j <- idset == idj & here
       leg <- legend[j]
       leg.allfit[i] <- leg
       dead <- alldead[here.j]
       tot <- alltot[here.j]
       mins <- alltimes[here.j]
       if(!is.null(cutx))
          cutoff <- cutx[j]
       else cutoff <- NULL
       if(!is.null(cm))
          cmj <- cm[j]
       else cmj <- NULL
       uu <- fitconf(link = link, mins, dead, tot, cutoff, offset, j, leg = leg,
          interval = interval, pc = pc, pc.spline = pc.spline, pc.monotone = 
          pc.monotone, plot.spline = plot.spline, plot.monotone = plot.monotone,
          cutoff.mono = cutoff.mono, span.mono = span.mono, xfun = xfun, cm = 
          cmj, numcm = cmtot[j], p.min = p.min, printdat = F, save.resid = 
          save.resid, cm.strategy = cm.strategy, cm.code = cm.code, cm.allcodes
           = cm.allcodes, xfun.inv = xfun.inv, full.robust = full.robust)
       if((!is.null(plot.monotone)) && prod(par()$mfg[1:2]) == 1) {
          new.page <- T
          mtext(paste(maint, add.main), 3, line = 2.75, outer = T, cex = 1)
          mtext("Curves & LT's are from smooths following monotone regression",
             3, line = -0.75, outer = T, cex = 0.80000000000000004)
       }
       if((!is.null(plot.monotone)) && prod(par()$mfg[1:2]) == prod(par()$mfg[3:
          4]) && print.plot && new.page) {
          dev.print(device = pscript, horiz = T)
          new.page <- F
       }
       if(printdat) {
          print(legend[j])
          print(cbind(mins, dead, tot))
       }
       ltmat[i,  ] <- uu$lt
       if(!is.null(ltmat.spline))
          ltmat.spline[i,  ] <- uu$lt.spline
       if(!is.null(ltmat.monotone))
          ltmat.monotone[i,  ] <- uu$lt.monotone
       semat[i,  ] <- uu$se
       b0[i] <- uu$b0
       b1[i] <- uu$b1
       dev[i] <- uu$dev
       df[i] <- uu$df
       cm.est[i] <- uu$cm
       dev.robust[i] <- uu$dev.robust
       df.robust[i] <- uu$df.robust
       resid.list[[i]] <- uu$resid
       resid.dev.list[[i]] <- uu$resid.dev
       times.list[[i]] <- uu$times
       total.list[[i]] <- uu$total
    }
    if((!is.null(plot.monotone)) && print.plot && new.page)
       dev.print(device = pscript, horiz = T)    #
    invisible(list(lt50 = NULL, lt99 = NULL, se50 = NULL, se99 = NULL, 
       intercept = b0, slope = b1, lt = ltmat, se = semat, lt.spline = 
       ltmat.spline, lt.monotone = ltmat.monotone, span.mono = span.mono, cutx
        = cutx, dev = dev, df = df, cm.strategy = cm.strategy, cm = cm.est, 
       cm.code = cm.code, dev.robust = dev.robust, df.robust = df.robust, 
       takelog = takelog, total = total.list, resid = resid.list, resid.dev = 
       resid.dev.list, times = times.list, datafun = as.character(substitute(
       datafun)), choice = choice, temp = temp, stage = stage, add.main = 
       add.main, legend = leg.allfit, leg.brief = leg.brief))

  }
, comment = "08/09/2004")
"ang" <-
structure(function(u)
{
    (180 * asin(sqrt(u)))/atan(1)/4
}
, comment = "26/09/2001")
"ang.bt" <-
structure(function(y)
{
  
    100 * (sin(pi/180 * y))^2 
}
, comment = "16/02/2005")
"append.cols" <-
structure(function(data = natural.df, repeat.cols = 1:4, collapse.cols = 5:6, resp.id = 
    "Resp.id", out.col = "Response")
{
# By default repeats the first four columns twice and 
#    makes columns 5 and 6 into one
    data <- as.data.frame(data)
    if(is.numeric(repeat.cols))
       repeat.cols <- names(data)[repeat.cols]
    if(is.numeric(collapse.cols))
       collapse.cols <- names(data)[collapse.cols]
    repeat.df <- as.data.frame(data[, repeat.cols])
    collapse.df <- data[, collapse.cols]
    ind <- 1:nrow(repeat.df)
    repeat.times <- ncol(collapse.df)
    repeated.df <- as.data.frame(repeat.df[rep(ind, repeat.times),  ])
    names(repeated.df) <- repeat.cols    # if only one column
    repeated.df[, resp.id] <- rep(collapse.cols, rep(max(ind), repeat.times))
    right <- unlist(collapse.df)
    repeated.df[[out.col]] <- right
    unfactor(repeated.df)
}
, comment = "30/04/2001")
"append.rows" <-
structure(function(x, id.cols = 1, spread.col = 3, spread.id = 2,
                        new.cols = NULL)
{
### Purpose: Unstacks dataframe -- converse of append.cols
### ----------------------------------------------------------------------
### Modified from: append.cols (a bit)
### ----------------------------------------------------------------------
### Arguments: new.cols: names of new columns
### ----------------------------------------------------------------------
### Author: Patrick Connolly, Creation date: 20 Feb 2003, 09:28

  x <- as.data.frame(x)
### more useful in character form
  if(is.numeric(spread.col))
    spread.col <- names(x)[spread.col]
  if(is.numeric(spread.id))
    spread.id <- names(x)[spread.id] # column identifier to get new names
  if(is.numeric(id.cols)) 
    id.cols <- names(x)[id.cols] # rows that identify general groups
  if(is.null(new.cols))
    new.cols <- unique(x[, spread.id])

  nrow.out <- nrow(x)/length(new.cols)
### set up dataframe and then add columns to it from rows of original
  x <- df.sort(x, spread.id) # make sure it's ordered
  out.df <- as.data.frame(x[seq(nrow.out), id.cols])
  row.names(out.df) <- seq(nrow(out.df))
  names(out.df) <- id.cols
  spread.mat <- matrix(x[, spread.col], ncol = length(new.cols))
  dimnames(spread.mat) <- list(NULL,new.cols)
  cbind(out.df, spread.mat)
}
, comment = "20/02/2003")
"average.down" <-
structure(function(x)
{
# uses fill.down() to average the missing values with ones present
    y <- fill.down(x)
    z <- rev(fill.down(rev(x)))
    xx <- (y + z)/2
}
, comment = "10/08/1999")
"axis.fudge" <-
structure(function(ax.cex = .8, las = 2, y.tix, mgp = c(2, .7, 0), fudge = 0)
{
  ## Purpose: Fudges y-axis labels (if the default is too low)
  ## ----------------------------------------------------------------------
  ## Modified from: 
  ## ----------------------------------------------------------------------
  ## Arguments: y.ax.fudge is the amount to bump up the position of
  ##            ytick labels 
  ## ----------------------------------------------------------------------
  ## Author: Patrick Connolly, Creation date: 17 Jun 2004, 13:44

  axis(2, cex.axis = ax.cex, mgp = mgp, at = y.tix, labels = FALSE)
  axis(2, cex.axis = ax.cex, las = 2, mgp = mgp,
       at = y.tix + fudge, labels = paste(y.tix), tick = FALSE)

}
, comment = "18/06/2004")
"bar.legs" <-
structure(function(xp = 0.5, yp = 0.5, ebv = NULL, labs = NULL, colour = F, pchs = 0:10, 
           ltys = 1:9, line.break = 0,
           cols = rep(1, 20), wid = 0.007, eq.tex.gap = T,
           ygap = ifelse(eq.tex.gap, 0.05, 0.02), xgap = 0.01, leg.cex = 0.6,
           point.cex = 0.8, adj = 0, hershey = F, font = 1, line.leng = ifelse(is.null(pchs),
                                                              0.03, 0.05), mixed = F, bar.lwd = par()$lwd, line.lwd = par()$lwd,
           pt.lwd = bar.lwd, pt.lty = 1)
{
### For placing legends with error bars and adjusting the spaces between lines
###
### xp and yp are x & y positions to begin
### ebv is vector of errorbars widths: or a list of two vectors (max and min)
### labels is character vector of legend text
### wid is "width" of errorbars: adjusts eps in errorbars function called from this one
### ygap space between elements of legend
### pchs is vector of plotting characters 
### mixed is T when mixed.text is to be used for mixing characters in labs
### 
###  font is becomes vfont if herschey fonts are to be used, in which case, it is a
###  vector of two elements: otherwise a numeric single value.
  uu <- par()$usr
  xd <- diff(uu[1:2])
  yd <- diff(uu[3:4])
  xh <- uu[1] + xd * xp
  yh <- uu[3] + yd * yp
  if(is.vector(labs))
    labs <- as.list(labs)
  hershey <- is.character(font)
  if(is.null(ebv)) xh <- xh - xgap * xd
  if(length(point.cex) < length(pchs))
    point.cex <- rep(point.cex, length(pchs))
  if(length(line.lwd) < length(ltys))
    line.lwd <- rep(line.lwd, length.out = length(ltys))
  if(length(cols) < length(ltys))
    cols <- rep(cols, length.out = length(ltys))

### puts lines() back to xp
  if(!is.list(ebv)) {
### If ebv is a single vector, only one lot of error bars:
    for(i in 1:length(labs)) {
### If space between errorbars is to be made equal, start top of first error bar
###  at beginning of legend. Otherwise, the legend text is at that position.
### If errorbar spaces are to be equal, half adjustment is done before drawing one, 
###  otherwise, all adjustment happens after drawing each one.
      if(!eq.tex.gap) yh <- yh - ebv[i]    ### 
      if(!is.null(ebv))
        errorbars(xh, yh, ebv[i], eps = wid * xd, lwd = bar.lwd)
      if(!is.null(pchs))
        points(xh + (line.leng/2 + xgap) * xd, yh, pch = pchs[i], cex = 
               point.cex[i], col = cols[i], lwd = pt.lwd, lty = pt.lty)
      if(!is.null(ltys))
        if(line.break > 0) {
          {
            lines(xh + (c(0, line.leng/2 - line.break) + xgap) * xd,
                  rep(yh, 2), lty = ltys[i], col = cols[i], lwd = line.lwd[i])
            lines(xh + (c(line.leng/2 + line.break, line.leng) + xgap) * 
                  xd, rep(yh, 2), lty = ltys[i], col = cols[i], lwd = 
                  line.lwd[i])
          }
        }
        else lines(xh + (c(0, line.leng) + xgap) * xd, rep(yh, 2), lty = 
                   ltys[i], col = cols[i], lwd = line.lwd[i])
      if(!is.null(labs)) {
        if(is.expression(labs[[i]]) & hershey) stop(
            "Hershey fonts cannot be used with expressions\n")    
### Use herschey fonts, font becomes vfont: adj is a bit different too
        if(hershey)
          text(xh + (line.leng + xgap * 2) * xd, yh, labels = labs[[i]], 
               adj = c(adj, 0.5), cex = leg.cex, vfont = font)
        else text(xh + (line.leng + xgap * 2) * xd, yh, labels = labs[[i]],
                  adj = c(adj, 0.5), cex = leg.cex, font = font)
      }
### Move down the appropriate amount for the next one:
      yh <- yh - ifelse(eq.tex.gap, 0, ebv[i]) - ygap * yd
    }
  }
  else {
### Two error bars, maximums and minimums are drawn 
### Move starting point to allow for extra errorbar
    xh <- xh + (xgap + wid) * xd
    ebv1 <- ebv$max
    ebv2 <- ebv$min
    for(i in 1:length(labs)) {
      if(!eq.tex.gap)
        yh <- yh - ebv1[i]
      errorbars(xh - (xgap + wid) * xd, yh, ebv1[i], eps = wid * xd, lwd = 
                bar.lwd)
      errorbars(xh, yh, ebv2[i], eps = wid * xd, lwd = bar.lwd)
      if(!is.null(pchs))
        points(xh + (line.leng/2 + xgap) * xd, yh, pch = pchs[i], cex = 
               point.cex[i], col = cols[i], lwd = pt.lwd)
      if(line.break > 0) {
        {
          lines(xh + (c(0, line.leng/2 - line.break) + xgap) * xd,
                rep(yh, 2), lty = ltys[i], col = cols[i], lwd = line.lwd[i])
          lines(xh + (c(line.leng/2 + line.break, line.leng) + xgap) * xd,
                rep(yh, 2), lty = ltys[i], col = cols[i], lwd = line.lwd[i])
        }
      }
      else lines(xh + (c(0, line.leng) + xgap) * xd, rep(yh, 2),
                 lty = ltys[i], col = cols[i], lwd = line.lwd[i])
      if(!is.null(labels)) {
        if(mixed)
          mixed.text(xh + (line.leng + xgap * 2) * xd, yh, labs[[i]], adj
                     = adj, cex = leg.cex, vfont = vfont)
        else text(xh + (line.leng + xgap * 2) * xd, yh, labs[[i]], adj = 
                  adj, cex = leg.cex, vfont = vfont)
      }
      yh <- yh - ebv1[i] - ygap * yd
    }
  }
}
, comment = "13/08/2003")
"blank.plot" <-
structure(function(x = 0, y = 0, ...)
{
# Does a blank plot.  
#
#  Useful if you want to change the axes on the current plot (in which case specify
#    par(new=F)) 
# Sometimes you might want to prevent plotting in one part of a multiplot page.
    plot(x, y, xlab = "", ylab = "", xaxt = "n", yaxt = "n", pch = " ", bty = 
       "n", ...)
}
, comment = "06/05/1997")
"boxplot.fn" <-
structure(function(x = delbbd.datf, floop = NULL, rloop = NULL, trans = function(z)
z, mod1 = 1, mod2 = 0, notch = F, subset = NULL, paste.cols = NULL)
{
# 1a) Adding Paste Columns
    if(!is.null(paste.cols) & !is.logical(paste.cols)) {
       indc <- apply(x[paste.cols], 1, paste, collapse = ":")    
    #ind <- match(indc, unique(indc))
       x <- cbind(indc, x)
       dimnames(x)[[2]][1] <- paste("treat", paste(paste.cols, collapse = ""), 
          sep = "")
       if(is.null(floop)) {
          floop <- 1
       }
       else {
          floop <- c(1, floop + 1)
       }
    }
# 1b) For loop for Responses
    for(j in rloop) {
       response.names <- dimnames(x)[[2]][j]
       response <- x[, j]
       if(!is.null(subset)) {
          response[response > subset] <- NA
       }
       yval <- trans(response/mod1 + mod2)    # 2) For loop for factors
       for(i in floop) {
          factors <- factor(x[, i])
          factor.names <- dimnames(x)[[2]][i]    # 3) Boxplot function
          plot.factor(factors, yval, xlab = factor.names, ylab = response.names,
             notch = notch, boxmeans = T, style.bxp = "old")
          if(i == floop[1] & j == rloop[1])
             mtext(paste(as.character(substitute(trans)), " ", as.character(
                substitute(x))), 3, cex = 1, line = 1.3999999999999999)
          dev.ask()
       }
    }
}
, comment = "06/12/1996")
"catalogue" <-
structure(function(x = NULL, outfile = "add.dates.sc", new = TRUE, remove = FALSE)
{
### by default, adds today's date as a comment on any object that has none.
### new: delete any previous src file?
### src.now: delete any previous src file?
### remove: delete this src file?
###
    del.comm <- paste("rm", outfile)    # deleting previous src file
    src.comm <- ppaste("source('", outfile, "')")    # to use src file
    if(new)
       try(system(del.comm))
    if(is.null(x))
       x <- ls(pos = 1)
    new.obj <- 0
    today <- system("date +%d/%m/%Y", TRUE)
    for(i in x) {
       source.line <- ppaste("comment(", i, ") <- '", today, "'")
       if(is.null(comment(get(i)))) {
          write(source.line, file = outfile, append = TRUE)
          new.obj <- new.obj + 1
       }
    }
    if(remove)
       system(del.comm)
    if(new.obj > 0)
       cat(paste("Now you can add the date comments to", new.obj, ifelse(
          new.obj > 1, "objects", "object"), "using:\n", src.comm, "\n"))
    else cat(paste("No objects need updating:\n"))
}
, comment = "02/04/2001")
"catalogue.gems" <-
structure(function(x = NULL, outfile = "gems.date.sc", new = TRUE, remove = FALSE)
{
### 
### modifies catalogue() to incorporate dates in Gems functions from Splus
### 
### x is character string of object names of interest. All if not specified
###
    month.name <- c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", 
       "Sep", "Oct", "Nov", "Dec")
    month.no <- 1:12
    names(month.no) <- month.name
    attach(gems.df)
    on.exit(detach("gems.df"))
    del.comm <- paste("rm", outfile)    # deleting previous src file
    src.comm <- ppaste("source('", outfile, "')")    # to use src file
    if(new)
       try(system(del.comm))
    if(is.null(x))
       x <- ls(pos = 1)
    today <- system("date +%d/%m/%Y", TRUE)
    new.obj <- 0
    for(i in x) {
       yr.i <- Year[Object == i]
       dy.i <- Dy[Object == i]
       mo.i <- month.no[Mo[Object == i]]
       if(length(yr.i) > 0) {
          dy.j <- substring(ppaste("0", dy.i), nchar(dy.i))
          mo.j <- substring(ppaste("0", mo.i), nchar(mo.i))
          today.i <- paste(dy.j, mo.j, yr.i, sep = "/")
          source.line <- ppaste("comment(", i, ") <- '", ifelse(today.i == "", 
             today, today.i), "'")
          if(is.null(comment(get(i)))) {
             write(source.line, file = outfile, append = TRUE)
             new.obj <- new.obj + 1
          }
       }
    }
  if(new.obj > 0)
       cat(paste("Now you can add the date comments to", new.obj, ifelse(
          new.obj > 1, "object", "objects"), "using:\n", src.comm, "\n"))
    else cat(paste("No objects need updating:\n"))
  }
, comment = "04/04/2001")
"catalogue.save.gems" <-
structure(function(x = NULL, outfile = "gems.date.save.sc", new = TRUE)
{
### 
### modifies catalogue() to incorporate dates in Gems functions from Splus
### 
### x is character string of object names of interest. All if not specified
###

  attach(gem.df)
  on.exit(detach("gem.df"))
  del.comm <- paste("rm", outfile)    # deleting previous src file
  src.comm <- ppaste("source('", outfile, "')")    # to use src file
  if(new)
    try(system(del.comm))
  if(is.null(x))
    x <- ls(pos = 1)
  
  today <- system("date +%d/%m/%Y", TRUE)
  new.obj <- 0
  for(i in x) {
    date.i <- Date[Object == i]
source.line <- ppaste("comment(", i, ") <- '", date.i, "'")
     
      if(is.null(comment(get(i)))) {
        write(source.line, file = outfile, append = TRUE)
        new.obj <- new.obj + 1
      }
  }

  if(new.obj > 0)
    cat(paste("Now you can add the date comments to", new.obj, ifelse(
                                                                      new.obj > 1, "object", "objects"), "using:\n", src.comm, "\n"))
  else cat(paste("No objects need updating:\n"))
}
, comment = "31/05/2001")
"check.fact" <-
structure(function(df)
{
#Checks if columns of dataframes are factors:
    sapply(df, is.factor)
}
, comment = "30/04/2001")
"check.na" <-
structure(function(df)
{
# Returns the number of NAs in any column of a dataframe
    sapply(df, function(x)
    sum(is.na(x)))
}
, comment = "21/09/1997")
"circ.boxplot" <-
structure(function(x, rad, fat = .1, col = "blue", rad.lim = 1,
           pch = 16, cex = .8, seg = 600, test = FALSE)
{
  ## Purpose: Curved boxplots
  ## ----------------------------------------------------------------------
  ## Modified from: 
  ## ----------------------------------------------------------------------
  ## Arguments: x- vector of values (in degrees),
  ##            rad- how far from centre to draw
  ##            fat- how thick the boxes are to be
  ##            rad.lim- max radial length on plot
  ##            test(mark individual values to test the box position)
  ## ----------------------------------------------------------------------
  ## Author: Patrick Connolly, Creation date: 29 Mar 2006, 13:20
  deg <- boxplot(x, plot = FALSE)
  box.stats <- deg$stats[,1]
  names(box.stats) <- c("beginWhisker", "beginBox", "Median", "endBox", "endWhisker")
  rad <- rad/rad.lim
  fat <- fat/rad.lim # get to unit scale if not already
### draw inner and outer sides of boxes and the whiskers
  circle(,, rad + fat/2, box.stats["beginBox"], box.stats["endBox"], col = col, seg = seg)
  circle(,, rad - fat/2, box.stats["beginBox"], box.stats["endBox"], col = col, seg = seg)
  circle(,, rad , box.stats["beginWhisker"], box.stats["beginBox"], col = col, seg = seg)
  circle(,, rad , box.stats["endBox"], box.stats["endWhisker"], col = col, seg = seg)
### co-ordinates for box edges
  x.box.i <- (rad - fat/2)* cos(box.stats * pi/180)[c("beginBox", "endBox")]
  y.box.i <- (rad - fat/2) * sin(box.stats * pi/180)[c("beginBox", "endBox")]
  x.box.o <- (rad + fat/2)* cos(box.stats * pi/180)[c("beginBox", "endBox")]
  y.box.o <- (rad + fat/2) * sin(box.stats * pi/180)[c("beginBox", "endBox")]
  ## draw two radial lines for ends of boxes
  lines(c(x.box.i["beginBox"], x.box.o["beginBox"]),
        c(y.box.i["beginBox"], y.box.o["beginBox"]), col = col)
  lines(c(x.box.i["endBox"], x.box.o["endBox"]),
        c(y.box.i["endBox"], y.box.o["endBox"]), col = col)
### co-ordinates for whisker edges
  x.whisker.i <- (rad - fat/4)*
    cos(box.stats * pi/180)[c("beginWhisker", "endWhisker")]
  y.whisker.i <- (rad - fat/4) *
    sin(box.stats * pi/180)[c("beginWhisker", "endWhisker")]
  x.whisker.o <- (rad + fat/4)*
    cos(box.stats * pi/180)[c("beginWhisker", "endWhisker")]
  y.whisker.o <- (rad + fat/4) *
    sin(box.stats * pi/180)[c("beginWhisker", "endWhisker")]
  ## draw two radial lines for ends of whiskers
  lines(c(x.whisker.i["beginWhisker"], x.whisker.o["beginWhisker"]),
        c(y.whisker.i["beginWhisker"], y.whisker.o["beginWhisker"]), col = col)
  lines(c(x.whisker.i["endWhisker"], x.whisker.o["endWhisker"]),
        c(y.whisker.i["endWhisker"], y.whisker.o["endWhisker"]), col = col)
### co-ordinates for median edges
  x.median.i <- (rad - fat/2) * cos(box.stats[c("Median")] * pi/180)
  y.median.i <- (rad - fat/2) * sin(box.stats[c("Median")] * pi/180)
  x.median.o <- (rad + fat/2) * cos(box.stats[c("Median")] * pi/180)
  y.median.o <- (rad + fat/2) * sin(box.stats[c("Median")] * pi/180)
  ## draw  radial line for median
  lines(c(x.median.i["Median"], x.median.o["Median"]),
        c(y.median.i["Median"], y.median.o["Median"]), lwd = 3, col = col)
### Mark in outliers
  x.out <- rad * cos(deg$out * pi/180)
  y.out <- rad * sin(deg$out * pi/180)
  points(x.out, y.out, pch = pch, cex = cex, col = col)
  if(test){ # if we're testing to see if the box is in the right quadrant
    points(rad * cos(x * pi/180), rad * sin(x * pi/180),
           pch = 1, col = col, cex = cex )
  }
}
, comment = "02/11/2006")
"circle" <-
structure(function(cen.x = 0, cen.y = 0, rad = 1, from = 0, to = 360, seg = 400, ...)
{
  ## Purpose: draws a circle (or part thereof) at cen.x, cen.y, with radius rad
  ## ----------------------------------------------------------------------
  ## Modified from: 
  ## ----------------------------------------------------------------------
  ## Arguments: 
  ## ----------------------------------------------------------------------
  ## Author: Patrick Connolly, Creation date:  3 Feb 2006, 16:08

  bits <- seq(from, to, length = 400)
  x.coords <- cen.x + rad * cos (bits * pi/180)
  y.coords <- cen.y + rad * sin (bits * pi/180)
  lines(x.coords, y.coords, ...)
}
, comment = "29/03/2006")
"clg" <-
structure(function()
{
# Clears graphics window
    plot(0, 0, new = T, xaxt = "n", pch = " ", yaxt = "n", bty = "n", xlab = "",
       ylab = "")
}
, comment = "09/05/1997")
"clipline" <-
structure(function(xlim, ylim, a, b, funlog = function(x)
x, unlog = function(x)
x, lty = 1, lwd = 1, loud = T, ...)
{
    x0 <- xlim[1]
    y0 <- a + b * funlog(x0)
    x1 <- xlim[2]
    y1 <- a + b * funlog(x1)
    if(y0 < ylim[1]) {
       y0 <- ylim[1]
       x0 <- unlog((ylim[1] - a)/b)
    }
    else if(y0 > ylim[2]) {
       y0 <- ylim[2]
       x0 <- unlog((ylim[2] - a)/b)
    }
    if(y1 < ylim[1]) {
       y1 <- ylim[1]
       x1 <- unlog((ylim[1] - a)/b)
    }
    else if(y1 > ylim[2]) {
       y1 <- ylim[2]
       x1 <- unlog((ylim[2] - a)/b)
    }
    if(loud)
       cat("     Join (", round(x0, 3), round(y0, 3), ") to (", round(x1, 3), 
          round(y1, 3), ")", fill = T)
    lines(c(x0, x1), c(y0, y1), lty = lty, lwd = lwd, ...)
}
, comment = "13/09/2002")
"cloglog" <-
structure(function(pr)
{
    log( - log(1 - pr))
}
, comment = "16/04/1996")
"cloglog.bt" <-
structure(function(x)
{
# To calculate the proportion that gives the known complememtary log log value
    1 - exp( - exp(x))
}
, comment = "24/11/1997")
"cols.for.genstat" <-
structure(function(x, num = F)
{
# Returns a string of the column names to use in genstat
# need only to change the opening and closing " and  to '
    y <- names(x)
    paste(y, collapse = ", ")
}
, comment = "12/04/1999")
"comb" <-
structure(function(N, x)
{
    gamma(N + 1)/gamma(x + 1)/gamma(N - x + 1)
}
, comment = "23/07/1997")
"complot" <-
structure(function(data, xtitle = "Time (Minutes)", main = "", yfun = "cloglog", logx = F,
    plimits = c(0.04, 0.9995), xtix = NULL, ytit = NULL, labp
     = NULL, lty = 1, colours = F, dot.marks = T, xlab.line = 2, x.mgp = 0.2, 
    y.mgp = ifelse(post, 0.5, 0.6), ylab.line = 1.6, pchs = c(0, 1, 2, 5, 6:16),
    id = NULL, ab.lty = 2, lab.cex = 1, ax.cex = 0.8, main.cex = 1.1, point.cex
     = 0.9, mark.control = F, ...)
{
# Modified (very) version of simplot
# 
# data is a dataframe of the sets to be plotted on one plot.
#  with names of columns: Time, Dead, Total, Id 
#
# xfun is the function to be applied to the x axis data before plotting it.
#   It ia a list which will be extended to the same length as the number of sets
#   of points to be plotted (unless already given as that length). 
#
# y.mgp is the second value in an mgp parameter
# x.mgp is the amount by which the corresponding x axis parameter is decreased
#  
#
# dot.marks: Mark 100% and 0% points with dots?
    post <- names(dev.cur()) == "postscript"
    par(...)
    if(logx)
       f <- log
    else f <- function(x)
       x
    if(logx)
       stop(
          "\ncomplot function needs fixing to do log transformation on x-axis")
    u.id <- unique(data$Id)
    g <- link.function(yfun)

# Identify Control and Treatment data:
    if(logx)
       data <- data[data$Time > 0,  ]
    data$Mort <- data$Dead/data$Total
    if(is.null(xtix))
       x.range <- range(data$Time)
    else x.range <- range(xtix)
    p.range <- range(data$Mort)    #
# Calculate adjustments for the space on the y-axis:
    ylow <- g(plimits[1])
    yhigh <- g(plimits[2])
    eps <- (yhigh - ylow) * 0.01
    ylow <- ylow - eps
    yhigh <- yhigh + eps
    if(is.null(labp))
       labp <- c(1, 5, 10, 25, 50, 75, 95, 99)
    labp <- labp[labp/100 >= plimits[1] & labp/100 <= plimits[2]]    #
# Set up blank plot: (uses blank.plot() in /home/hrapgc/Gems/.Data/ )
    blank.plot(f(x.range), c(ylow, yhigh), ...)
   usr <- par()$usr
    epsx <- 0.0125 * diff(usr[1:2])
    epsy <- 0.0125 * diff(usr[3:4])
    midhigh <- 0.5 * (yhigh + usr[4])
    midlow <- 0.5 * (ylow + usr[3])
    hundred.line <- F
    zero.line <- F
    colour <- is.character(colours)
    for(i in seq(u.id)) {
       df.i <- data[data$Id == u.id[i],  ]
       attach(df.i)    #
# Plot "normal" points:

       time <- Time[Mort > plimits[1] & Mort < plimits[2]]
       mort <- Mort[Mort > plimits[1] & Mort < plimits[2]]
       points(f(time), g(mort), pch = pchs[i], col = ifelse(colour, colours[i],
          1), cex = point.cex)    #
# Plot "high" points (i.e. ones near 100%)
       high.mort <- Mort[Mort > plimits[2]]
       high.time <- Time[Mort > plimits[2]]
       points(f(high.time), rep(midhigh, length(high.time)), pch = pchs[i], cex
           = point.cex, col = ifelse(colour, colours[i], 1))
       if(any(Mort == 1)) {
          hundred.line <- T
          full.mort <- Mort[Mort == 1]
          full.time <- Time[Mort == 1]
          if(dot.marks)
             points(f(full.time), rep(midhigh, length(full.time)), pch = ".", 
                cex = point.cex, col = ifelse(colour, colours[i], 1))
       }
# Plot "low" points (i.e. ones near 0%)
       low.mort <- Mort[Mort < plimits[1]]
       low.time <- Time[Mort < plimits[1]]
       points(f(low.time), rep(midlow, length(low.time)), pch = pchs[i], cex = 
          point.cex, col = ifelse(colour, colours[i], 1))
       if(any(Mort == 0)) {
          zero.line <- T
          zero.mort <- Mort[Mort == 0]
          zero.time <- Time[Mort == 0]
          if(logx) {
             zero.time <- zero.time[zero.time > 0]
             zero.mort <- zero.mort[zero.time > 0]
          }
          if(dot.marks)
             points(f(zero.time), rep(midlow, length(zero.time)), pch = ".", 
                cex = point.cex)
       }
       cont.mort <- Mort[Time == 0]
       if(mark.control) {
# Mark control mortalities:
         if(any(cont.mort < plimits[1])) text(0, midlow, "C")
         else text(0, g(cont.mort), "C", cex = point.cex,
                   col = ifelse(colour, colours[i], 1))
       }
       detach("df.i")
    }
# Do tricky things to y-axis:
    mgp <- c(3, y.mgp, 0)
    axis(2, at = g(labp/100), labels = paste(labp), adj = 1, mgp = mgp, cex.axis = 
       ax.cex, las = 1)
    axis(2, at = c(ylow + 2 * epsy, yhigh - 2 * epsy), labels = F, tck = 0, las = 1)
    for(k in 1:2) {
       y.end <- c(ylow, yhigh)[k]
       axis(2, at = c(y.end, usr[2 + k]), labels = F, tck = 0, las = 1)
    }
    if(zero.line)
       abline(h = ylow, lty = ab.lty)
    if(hundred.line)
       abline(h = yhigh, lty = ab.lty)
    axis(2, at = midlow, tck = 0, labels = "0", adj = 1, mgp = mgp, cex.axis = 
       ax.cex, las = 1)
    lines(usr[1] + c( - epsx, epsx), c(ylow - 1.5 * epsy, ylow + 1.5 * epsy), 
       xpd = T)
    lines(usr[1] + c( - epsx, epsx), c(ylow + 0.5 * epsy, ylow + 3.5 * epsy), 
       lty = lty, xpd = T)
    axis(2, at = midhigh, tck = 0, labels = "100", adj = 1, mgp = mgp, cex.axis = 
       ax.cex, las = 1)
    lines(usr[1] + c( - epsx, epsx), c(yhigh - 1.5 * epsy, yhigh + 1.5 * epsy),
       xpd = T)
    lines(usr[1] + c( - epsx, epsx), c(yhigh - 3.5 * epsy, yhigh - 0.5 * epsy),
       lty = lty, xpd = T)    #
# Make x-axis and labels
    if(is.null(xtix))
       xlab.pos <- pretty(range(data$Time))
    else xlab.pos <- xtix
    if(logx)
       xlab.pos <- xlab.pos[xlab.pos > 0]
    axis(1, at = f(xlab.pos), labels = paste(xlab.pos), cex.axis = ax.cex, mgp = mgp -
       c(0, x.mgp, 0))
    cat(xlab.pos, "  \n")    # xlab.pos specifies numeric labels
# Add break in x-axis if necessary: fill in left space
    
    if(logx) {
       x.cut1 <- diff(usr[1:2]) * 0.03 + usr[1]
       x.cut2 <- diff(usr[1:2]) * 0.5 + usr[1]
       axis(1, at = c(usr[1], x.cut1), labels = F, tck = 0)
       axis(1, at = c(x.cut2, usr[2]), labels = F, tck = 0)
       lines(x.cut1 + c( - epsx, epsx), usr[3] + 2 * c( - epsy, epsy), xpd = T)
       lines(x.cut2 + c( - epsx, epsx), usr[3] + 2 * c( - epsy, epsy), xpd = T)
    }
    else lines(usr[1:2], usr[c(3, 3)])
    mtext(side = 1, line = xlab.line, text = xtitle, cex = lab.cex)
    mtext(side = 2, line = ylab.line, text = ifelse(is.null(ytit), paste(
       "% Mortality,", yfun, "scale"), ytit), cex = lab.cex)
    mtext(side = 3, text = main, cex = main.cex)
    box(bty = "7")
}
, comment = "13/09/2002")
"count.nas" <-
structure(function(df)
{
# counts nas in columns of a dataframe have nas.
#
    sapply(df, function(x)
    sum(is.na(x)))
}
, comment = "01/12/1997")
"data.spot" <-
structure(function(ab, use, id = NULL, separate = T)
{
### To show table of times, dead and total to correspond to selected 
###   parts of ab type list of the form ab$use
### If id is not specified, all values will be shown
### separate will group each section and names individually, othewise
###   only one table will be made
###
### WARNING: Will crash if the legends are not unique 
  names.ab <- names(ab)
  if(length(use) > 1)
    stop("use can be of length 1 only")
  if(is.character(use))
    ab.sub <- (1:length(names.ab))[!is.na(match(names.ab, use))]
  else ab.sub <- use
  aab <- ab[[ab.sub]]
  glean <- aab$datafun
  choice <- aab$choice
  glean.fn <- get(glean)
  glean.list <- glean.fn(choice)
  df <- data.frame(id = glean.list$id, time = glean.list$times, dead = 
                   glean.list$dead, total = glean.list$total)
  df$live <- df$total - df$dead
  df <- df[, c("id", "time", "live", "dead", "total")]
  df$mort <- round(df$dead/df$total * 100)
  if(is.null(id))
    out.df <- df
  else out.df <- df[!is.na(match(df[["id"]], id)),  ]
  print(glean.list$maint)
  out.list <- list()
  browser()
  if(separate) {
    if(is.null(id))
      id <- unique(df$id)
    for(i in id)
      out.list[[glean.list$legend[i]]] <- df[df$id == i,  ]
    out.list
  }
  else {
    if(!is.null(id))
      print(glean.list$legend[id])
    out.df
  }
}
, comment = "18/04/1999")
"ddif" <-
structure(function(d1, d2)
{
### Purpose: Finds the number of days between two different dates
### ----------------------------------------------------------------------
### Modified from: 
### ----------------------------------------------------------------------
### Arguments: d1 and d2 must be POSIXct objects with tz = "GMT"
### ----------------------------------------------------------------------
### Author: Patrick Connolly, Creation date: 20 Feb 2004, 09:09
d1s <- as.numeric(d1) # number of seconds since origin
d2s <- as.numeric(d2) # 
(d1s - d2s)/24/3600

}
, comment = "20/02/2004")
"df.mat" <-
structure(function(df)
{
# Coerces a dataframe to a matrix, retaining levels instead of codes 
#  for any factors: see unfactor()
    mat <- as.matrix(unfactor(df))
    mat
}
, comment = "18/10/1996")
"df.sort" <-
structure(function(dfm, sort.by = names(dfm)[1], backwards = F)
{
### To sort the rows of a dataframe into an order set by vector "sort.by"
### If sort.by is numeric it is the column nos; if character, the column names.
  if(is.character(sort.by)) {
    sort.by.n <- match(sort.by, names(dfm))
    if(any(is.na(sort.by.n))) {
      stop(paste("\n", sort.by[is.na(sort.by.n)], 
                 "is not a recognised name"))
    }
    else sort.by <- sort.by.n
  }
  for(i in sort.by) {
    dfm.i <- dfm[order(dfm[, i]),  ]
    if(backwards)
      dfm.i <- dfm[(rev(order(dfm[, i]))),  ]
    dfm <- dfm.i
  }
  dfm
}
, comment = "13/11/2002")
"df.summary" <-
structure(function(data, y.cols = NULL, split.cols = NULL, rep.col = "Rep", decimals = 3,
           stats = "mean", help = F)
{
### cut down and modified from summarize()
### Keep Stephen's beginning:
### Requires text.bp() and df.to.file() 
###   [anything else will be in   /home/hrapgc/Gems/.Data]
  summary.names <- c("N", "Missing", "Mean", "Median", "Trimmed Mean", 
                     "Std. Dev.", "SEM", "Min", "Max", "1st Quartile", "3rd Quartile", "Sum",
                     "Boxplots")
  summary.types <- c("num", "missing", "mean", "median", "trm", "stdev", 
                     "sem", "min", "max", "q1", "q3", "sum", "boxplots")
  help.df <- (data.frame("Select one of these" = summary.types, "to get this"
                         = summary.names))
  if(help) {
    cat("\n In the argument \"stats\"\n")
    print(help.df)
    return()
  }
### A few error messages:
  if(length(stats) > 1)
    stop(
         "\n\tOnly one statistic can be calculated at a time:\n\tIf you require multiple stats with only one y.cols, \n\tyou can use summarize() with df.out set to TRUE"
         )

### Make special functions to use in apply calls
  q1 <- function(x)
    quantile(x, na.rm = T)[2]
  q3 <- function(x)
    quantile(x, na.rm = T)[4]
  no.missing <- function(x)
    length(x[is.na(x)])
  round.mean <- function(x, y = decimals)
    round(mean(x, na.rm = T), y)
  round.sem <- function(x, y = decimals)
    round(sem(x, na.rm = T), y)
  round.sum <- function(x, y = decimals)
    round(sum(x, na.rm = T), y)
  add.boxplot <- function(x, y.range = range.j, width = bp.width)
    text.bp(x, y.range, width)    #
### Functions are now set up:
###
### Make named vector of functions to be used:
  use.functions <- c("length", "no.missing", "round.mean", "median", "trm", 
                     "stdev", "round.sem", "min", "max", "q1", "q3", "round.sum", 
                     "add.boxplot")
  names(use.functions) <- summary.types
  names(summary.names) <- summary.types    #
### Use dataframes instead of matrices:
  if(is.matrix(data))
    data <- unfactor(as.data.frame(data))
  else data <- unfactor(data)    # avoid pesky factors
  data <- df.sort(data, rev(split.cols))    #
### Make character vectors of y.cols and split.cols if necessary:
  if(is.numeric(y.cols))
    y.cols <- names(data)[y.cols]
  if(is.numeric(split.cols)) split.cols <- names(data)[split.cols]    #
### Create index and adjust for single split columns if necessary:
  indx.df <- data.frame(data[, split.cols])
  names(indx.df) <- split.cols    # Necessary for single split.cols
  attach(indx.df)
  indx <- NULL
  for(i in split.cols)
    indx <- paste(indx, get(i), sep = ":")
  detach("indx.df")
  out.df <- data.frame(indx.df[match(unique(indx), indx), split.cols])
  names(out.df) <- split.cols    # Necessary for single split.cols
  dimnames(out.df) <- list(paste(1:nrow(out.df)), names(out.df))
  for(j in y.cols)
    out.df[, j] <- s.tapply(data[, j], indx, get(use.functions[stats]))
  out.df
}
, comment = "30/04/2001")
"df.to.file" <-
structure(function(df = unfactor(junk.df), file = "", pad = "mid", append = F,
           row.nos = F, col.names = T)
{
### To print a data frame to a text file and having names line up with values
###    underneath, and no need to use tab spacing
###
###  Set up some padding functions:  Need columns with same number of characters
###    all the way down.
  pad.char.cols <- function(y)
    {
                                        # For padding character columns
      biggest <- max(nchar(y))
      col.width <- nchar(y)
      padding <- paste(rep(" ", biggest - min(col.width)), collapse = "")
      out <- substring(paste(y, padding, sep = ""), 1, biggest)
      out
    }
  pad.left <- function(z, pads)
    {
      padding <- paste(rep(" ", pads), collapse = "")
      paste(padding, z, sep = "")
    }
  pad.mid <- function(z, pads)
    {
                                        # Centres text in available space
      padding.right <- paste(rep(" ", pads %/% 2), collapse = "")
      padding.left <- paste(rep(" ", pads - pads %/% 2), collapse = "")
      paste(padding.left, z, padding.right, sep = "")
    }
  pad.right <- function(z, pads)
    {
      padding <- paste(rep(" ", pads), collapse = "")
      paste(z, padding, sep = "")
    }
### Character columns need different treatment from numeric columns
#browser()
  char.cols <- sapply(df, is.character)
  if(any(char.cols))
  df[char.cols] <- sapply(df[char.cols], pad.char.cols)
  if(any(!char.cols))
  df[!char.cols] <- sapply(df[!char.cols], format)    #
### Sometimes the names of columns are wider than the columns they name, 
###  sometimes vice versa.
  names.width <- nchar(names(df))
  row.width <- sapply(df, function(x)
                      max(nchar(x)))    #
#browser()
### (the width of the characters in the columns (and rows) as distinct
###      from their names
  name.pads <- row.width - names.width
  row.pads <- name.pads * -1
  name.pads[name.pads < 0] <- 0
  row.pads[row.pads < 0] <- 0
  pad.names <- name.pads > 0
  pad.rows <- row.pads > 0    #
### Pad out the column names if necessary:
  pad.funct <- get(paste("pad.", pad, sep = ""))
  if(any(pad.names)) {
    stretch.names <- names(df)[pad.names]
    for(i in stretch.names) {
      names(df)[names(df) == i] <- pad.funct(i, name.pads[i])
    }
  }
### likewise for the rows and columns
  if(any(pad.rows)) {
    stretch.rows <- names(df)[pad.rows]
    for(j in stretch.rows)
      df[, j] <- pad.funct(df[, j], row.pads[j])
  }
### the write() function doesn't use the names of the matrix, so put them
###   into it. 
  df2 <- df
  if(row.nos) {
    df2 <- cbind(seq(nrow(df)), df)
    no.wid <- nchar(nrow(df))
    no.col.name <- paste(rep(" ", no.wid), collapse = "")
    names(df2) <- c(no.col.name, names(df))
  }
  if(col.names)
    df2 <- rbind(names(df2), as.matrix(df2))
  else df2 <- as.matrix(df2)
  write(t(df2), file, ncol(df2), append = append)
}
, comment = "24/07/2001")
"disp" <-
structure(function(x, r = 4)
{
### Purpose: Estimates dispersion of a glm
### ----------------------------------------------------------------------
### Modified from: 
### ----------------------------------------------------------------------
### Arguments: x is a glm object (mabye can be more generic)
### ----------------------------------------------------------------------
### Author: Patrick Connolly, Creation date:  8 Aug 2003, 11:21

  dev.x <- deviance(x)
  df.x <- x$df.residual
  round(dev.x/df.x, r)
}
, comment = "08/08/2003")
"dmodes" <-
structure(function(t.ob = NULL, pos = 1, max = NULL, date.sort = TRUE)
{
### Returns a Data frame showing modes of objects in the stated directory.
### Can be sorted by Mode, Length, or Date in addition to default Object
### A variation on this one is modes(). Made for lazy typists to sort by object name 
### max is the maximum number of objects returned; useful if ls() is long and 
###  you're only interested in the first few
###browser()
  if(is.null(t.ob)) ls.o <- objects(pos = pos) else ls.o <- objects(pos = pos,
                                      pattern = t.ob)
  if(!is.null(max) && max > length(ls.o))
    print(paste("Only", length(ls.o), "match", t.ob, "in", search()[pos]))
  if(is.null(max) || (max > length(ls.o))) max <- length(ls.o)    #
### Rearrange date information
  date.chr <- NULL
  for(i in seq(ls.o)) {
    if(FALSE){
      cat(paste("Got down to", ls.o[i], ":\n")) 
      ##browser()
    }
    
    date.i <- comment(get(ls.o[i], pos = pos))
    if(is.null(date.i))
###
###date.i <- try(comment(get(ls.o[i], pos = pos)))
###if(class(date.i) == "try-error")
      date.i <- "NA/NA/NA"
    date.chr[i] <- date.i
  }
  break.at <- occurrence(date.chr, "/", 1:2)
  if(is.null(dim(break.at)))
    break.at <- matrix(break.at, nrow=1)
  first <- break.at[, 1] - 1
  second <- break.at[, 2] - 1
  day <- as.numeric(substring(date.chr, 1, first))
  month <- as.numeric(substring(date.chr, first + 2, second))
  year <- as.numeric(substring(date.chr, second + 2))
  ob.df <- unfactor(data.frame(Object = ls.o, Day = day, Mon = month, Year = 
                               year))
  ob.df <- df.sort(ob.df, "Object", backwards = TRUE)
  if(all(is.na(ob.df$Day)))
    date.sort <- FALSE ## no point trying to sort
  if(date.sort) {
    xx <- df.sort(ob.df, c("Day","Mon"))
    xx <- df.sort(xx, "Year", backwards = TRUE)[seq(max),  ]
  }
  else xx <- df.sort(ob.df, "Object")
  xx$Date <- date.chr[as.numeric(row.names(xx))]
  options(warn = -1)
  on.exit(options(warn = 0))
  out <- list()
  dummy <- matrix(nc = 3, nr = 3)    # a non-null last list element
  out$Object <- c(xx$Object, "dummy")
  objs.mat <- cbind(out$Object)
  out$Mode <- apply(objs.mat, 1, function(X)
                    mode(get(X)))    #
### Dimension information of dataframes and matrices
  dimensions <- apply(objs.mat, 1, function(X)
                      dim(get(X))[1:2])
  y <- dimensions
  if(!is.null(y)) {
    if(is.list(y)) {
      y[unlist(lapply(y, is.null))] <- list(c(NA, NA))
      z <- t(matrix(unlist(y), byrow = F, nc = length(y)))
      z[is.na(z)] <- "--"
      out$Rows <- z[, 1]
      out$Cols <- z[, 2]
    }
    else {
### otherwise it's a matrix which will work differently (not checked in R version)
      out$Rows <- y[1,  ]
      out$Cols <- y[2,  ]
    }
  }

  else out$Cols <- out$Rows <- rep("--", length(out$Object))    #  
  out$Len <- apply(objs.mat, 1, function(X)
                   length(get(X)))    #  browser()
  out$Date <- xx$Date
  dfobj <- apply(objs.mat, 1, function(X)
                 is.data.frame(get(X)))    #
  out$Mode[dfobj] <- "dataframe"
  out.df <- unfactor(as.data.frame(lapply(out, function(X)
                                          X[seq(max)])), c("Object", "Mode"))
  df.to.file(out.df, row.nos = T)
}
, comment = "25/07/2006")
"dmodes.f" <-
structure(function(t.ob = NULL, pos = 1, max = NULL, date.sort = TRUE)
{
### Purpose: lists only the functions
### ----------------------------------------------------------------------
### Modified from: dmodes
### ----------------------------------------------------------------------
### Arguments: 
### ----------------------------------------------------------------------
### Author: Patrick Connolly, Creation date: 10 Sep 2002, 09:55
### Returns a Data frame showing modes of objects in the stated directory.
### Can be sorted by Mode, Length, or Date in addition to default Object
### A variation on this one is modes(). Made for lazy typists to sort by object name 
### max is the maximum number of objects returned; useful if ls() is long and 
###  you're only interested in the first few
  if(is.null(t.ob)) ls.o <- objects(pos = pos, all.names =FALSE)
  else ls.o <- objects(pos = pos, pattern = t.ob, all.names =FALSE)
  if(!is.null(max) && max > length(ls.o))
    print(paste("Only", length(ls.o), "match", t.ob, "in", search()[pos]))
  if(is.null(max) || (max > length(ls.o))) max <- length(ls.o)    #
### Rearrange date information
  date.chr <- NULL
  for(i in seq(ls.o)) {
    date.i <- comment(get(ls.o[i], pos = pos))
    if(is.null(date.i))
      date.i <- "NA/NA/NA"
    date.chr[i] <- date.i
  }
  break.at <- occurrence(date.chr, "/", 1:2)
  if(is.null(dim(break.at)))
    break.at_matrix(break.at,nrow=1)
  first <- break.at[, 1] - 1
  second <- break.at[, 2] - 1
  day <- as.numeric(substring(date.chr, 1, first))
  month <- as.numeric(substring(date.chr, first + 2, second))
  year <- as.numeric(substring(date.chr, second + 2))
  ob.df <- unfactor(data.frame(Object = ls.o, Day = day, Mon = month, Year = 
                               year))
  ob.df <- df.sort(ob.df, "Object", backwards = TRUE)
  if(all(is.na(ob.df$Day)))
    date.sort <- FALSE ## no point trying to sort
  if(date.sort) {
    xx <- df.sort(ob.df, c("Day","Mon"))
    xx <- df.sort(xx, "Year", backwards = TRUE)[seq(max),  ]
  }
  else xx <- df.sort(ob.df, "Object")
  xx$Date <- date.chr[as.numeric(row.names(xx))]
  options(warn = -1)
  on.exit(options(warn = 0))
  out <- list()
  dummy <- matrix(nc = 3, nr = 3)    # a non-null last list element
  out$Object <- c(xx$Object, "dummy")
  objs.mat <- cbind(out$Object)
  out$Mode <- apply(objs.mat, 1, function(X)
                    mode(get(X)))    #
### Dimension information of dataframes and matrices
  dimensions <- apply(objs.mat, 1, function(X)
                      dim(get(X))[1:2])
  y <- dimensions
  if(!is.null(y)) {
    if(is.list(y)) {
      y[unlist(lapply(y, is.null))] <- list(c(NA, NA))
      z <- t(matrix(unlist(y), byrow = F, nc = length(y)))
      z[is.na(z)] <- "--"
      out$Rows <- z[, 1]
      out$Cols <- z[, 2]
    }
    else {
### otherwise it's a matrix which will work differently (not checked in R version)
      out$Rows <- y[1,  ]
      out$Cols <- y[2,  ]
    }
  }

  else out$Cols <- out$Rows <- rep("--", length(out$Object))    #  
  out$Len <- apply(objs.mat, 1, function(X)
                   length(get(X)))    #  browser()
  out$Date <- xx$Date
  dfobj <- apply(objs.mat, 1, function(X)
              is.data.frame(get(X)))    #
  out$Mode[dfobj] <- "dataframe"
  out.df <- unfactor(as.data.frame(lapply(out, function(X)
                                          X[seq(max)])), c("Object", "Mode"))
  
  out.df <- out.df[out.df$Mode == "function", ]
  df.to.file(out.df, row.nos = T)
}
, comment = "10/09/2002")
"errorbars" <-
structure(function(x, y, se, yl = y - se, yu = y + se, eps, ...)
{
    if(any(is.na(yl)) | any(is.na(yu)))
       text(x[is.na(yl) | is.na(yu)], y[is.na(yl) | is.na(yu)], "NA", adj = 1)
    segments(x, yl, x, yu, ...)
    segments(x - eps, yl, x + eps, yl, ...)
    segments(x - eps, yu, x + eps, yu, ...)
}
, comment = "31/06/1996")
"ext.range" <-
structure(function(x, a = 5, ...)
{
  ## Purpose: Extend the xlim or ylim range of a vector
  ## ----------------------------------------------------------------------
  ## Modified from: 
  ## ----------------------------------------------------------------------
  ## Arguments: a is % to extend the range of vector x
  ## ----------------------------------------------------------------------
  ## Author: Patrick Connolly, Creation date: 13 Jan 2006, 09:11
ra <- range(x, ...)
interval <- diff(ra)
adjustment <- interval * a/100
ra + adjustment * c(-1, 1)
}
, comment = "13/01/2006")
"factorize" <-
structure(function(n)
{
    p <- n/(z <- 1:ceiling(sqrt(n)))
    z <- z[trunc(p) == p]
    unique(c(z, rev(n/z)))
}
, comment = "14/12/1998")
"fieller" <-
structure(function(phat, a, b, v11, v12, v22, df.t = Inf, link = "logit")
{
                                        # fiducial interval calculation from Finney p.78
                                        #
                                        # a,b    estimated intercept and slope
                                        # v11, v12, v22  variance and covariance of estimates of a and b
                                        # t    t statistic
                                        #
  if(df.t == Inf) tt <- 1.96 else tt <- qt(0.975, df.t)
  g.link <- link.function(link)
  a <- g.link(phat) - a
  v12 <- v12* -1
  m <- a/b
  g <- (gg <- (tt/b)^2) * v22

  if(g > 0.99 || g < 0) {
    return(list(xhat = m, ci = NULL, lower = 1, upper = -1, g = g))
  }
  xhat0 <- m + g/(1 - g) * m - gg/(1 - g) * v12
  vv <- v11 - 2 * m * v12 + m^2 * v22 - g * v11 + gg * v12^2
  Ix <- tt/b/(1 - g) * sqrt(vv)
  Ix <- abs(Ix)
  list(xhat = m, var = vv, lower = xhat0 - Ix, upper = xhat0 + Ix, g = g)
}
, comment = "14/09/2004")
"fill.down" <-
structure(function(x)
{
# Replaces NAs in a numeric vector or blanks in a character one 
#   with the value preceding it.  
#    Too lazy to use fill-down in Excel
#
#  Warning: Replaces an initial NA with a zero.  Might not always be appropriate.
    if(is.na(x[1])) x[1] <- 0
    stillsome <- T
    while(stillsome) {
       nas.at <- iff(is.character(x), x == "", is.na(x))
       na.indx <- seq(along = x)[nas.at]
       x[na.indx] <- x[na.indx - 1]
       stillsome <- length(na.indx) > 0
    }
    x
}
, comment = "16/08/1999")
"find.first" <-
structure(function(x, char = " ")
{
### Finds position of first occurence of a particular character in a character string
    if(!is.character(x)) stop(
          "find.first() applicable only for character strings")
    beg <- NULL
    for(k in 1:length(x)) {
       leg.vec <- paste(substring(x[k], 1:nchar(x[k]), 1:nchar(x[k])), sep = ""
          )
       beg[k] <- match(char, leg.vec)
    }
    beg
}
, comment = "01/06/1996")
"find.pos" <-
structure(function(y, inn)
{
#
# Finds positions of "y" in a vector "inn"
    x <- match(inn, y)
    seq(along = x)[!is.na(x)]
}
, comment = "30/04/2001")
"find.pos.mat" <-
structure(function(mat = b, test = (b > 1))
{
# Finds positions in matrix of elements which meet test
    want <- mat[test]
    if(length(want) == 0)
       cat("No matches\n")
    else pass <- cbind(row(mat)[test], col(mat)[test])
    dimnames(pass) <- list(paste("Soln:", 1:dim(pass)[1], sep = ""), c("Row", 
       "Col"))
    pass
}
, comment = "13/05/1997")
"fitconf" <-
structure(function(link = "cloglog", mins, dead, tot, cutoff = NULL, offset, j, leg, 
           interval = F, pc = c(line = 50, line = 99), pc.spline = NULL, pc.monotone
           = c(line = 50, line = 99), span.mono = 1, plot.spline = F, plot.monotone
           = NULL, cutoff.mono = 0, xfun = function(x)
           x, cm = NULL, numcm = NULL, p.min = NULL, printdat = F, save.resid = F, 
           cm.strategy = "adjust.later", cm.code = 0, cm.allcodes = NULL, xfun.inv = 
           NULL, full.robust = F)
{
# link is link function for binomial model
# mins is time of sampling
# dead is number of dead
# total is total number
# cutoff - data at less than this time are not included in the fitting
# offset is the amount added to time to improve linearity
# j is the dataset index number
# log time is used in calculations
# calculations are done using mean zero data
#
# nmid is the number of points suitable for fitting
  if(is.null(xfun.inv)) xfun.inv <- function(x)
    x
  if(all(xfun(exp(1:5)) == (1:5))) {
    takelog <- T
    xfun.inv <- exp
  }
  else takelog <- F
#browser()
  if(all(xfun(1:8) == (1:8)))
    xfun.inv <- function(x)
      x
  if(all(xfun(1:8) == (1:8)^2)) xfun.inv <- sqrt    
# link choices are "identity", "log", "logsurv", "logit", "sqrt", 
#               "inverse", "probit", "cloglog", "loglog"
  inv.fun <- link.inverse(link)    # get inverse of link function
  link.fun <- link.function(link)    # get link function
  if(any(dead > tot))
    stop(paste("\none or more totals is less than no of dead\n", "Dead:", 
               paste(dead, collapse = " "), "\nTotal:", paste(tot, collapse = " ")))
  mins <- as.character(mins)
  cmrows <- mins == cm.code[1]
  if(sum(cmrows) == 0 & length(cm.code) > 1) {
    cmrows <- mins == cm.code[2]
    second.cm <- T
  }
  else second.cm <- F
  x.all <- array(, length(mins))
  x.all <- array(, length(mins))
  x.all[cmrows] <-  - Inf
  cutit <- !cmrows & tot > 0
  if(!is.null(cm.allcodes)) {
    other.rows <- as.logical(match(mins, cm.allcodes, nomatch = 0))
    if(any(other.rows))
      cutit[other.rows] <- F
    x.all[!cutit & !cmrows] <- NA
    x.cm <- mins[other.rows]
    dead.cm <- dead[other.rows]
    tot.cm <- tot[other.rows]
  }
  else x.cm <- NULL
  interp.rows <- cutit | mins == "0"
  if(is.null(cutoff.mono))
    cutoff.mono <- min(c(0, x.all[cutit]))
  mono.rows <- cutit | mins == "0"
  x.all[mono.rows] <- as.numeric(mins[mono.rows])
  if(any(is.na(x.all[cutit])))
    stop(paste("Illegal code", mins[cutit][is.na(x.all[cutit])], 
               "has appeared."))
  mono.rows[mono.rows][x.all[mono.rows] < cutoff.mono] <- F
  if(!is.null(pc.monotone) | !is.null(plot.monotone))
    monospeak <- paste("Monotone fit: Include x >= ", cutoff.mono, ":", sep
                       = "")
  else monospeak <- ""
  if(!is.null(cutoff)) {
    cutit[cutit] <- x.all[cutit] >= cutoff
    cutspeak <- paste("Line: Include x >= ", cutoff, ":", sep = "")
  }
  else cutspeak <- ""
  if(!is.null(p.min)) {
    p <- dead/tot
    omitspeak <- paste("Omit until p > ", format(round(p.min, 2)), ":", sep
                       = "")
    testseq <- seq(along = x.all)[p < p.min]
    if(length(testseq) > 0)
      omit <- 1:max(testseq)
    else omit <- 0
  }
  else {
    omit <- 0
    omitspeak <- ""
  }
  cat("\n", j, "  ", leg, fill = T)
  cutit[omit] <- F
  if(is.null(numcm)) numcm <- 0    # numcm may be reset below
  if(!is.null(cm)) {
    if(numcm == 0)
      cmspeak <- paste("   cm (taken as fixed) =")
    else cmspeak <- "  cm (supplied) ="
    cmspeak <- paste(cmspeak, format(round(cm, 3)))
  }
  else {
    if(sum(cmrows) > 0) {
      if(any(x.all[cmrows] !=  - Inf & x.all[cmrows] != 0))
        cat("\n*** Warning: Fault in specification of cm rows ***", "\n")
      dead0 <- sum(dead[cmrows])
      tot0 <- sum(tot[cmrows])
      cm <- dead0/tot0
      numcm <- tot0
      n.cm <- sum(cmrows)
      cmspeak <- paste("   cm(obs) =", format(round(cm, 3)), "(from", n.cm,
                       paste("point", switch((n.cm > 1) + 1,
                                             "",
                                             "s",
                                             ), ")", sep = ""))
      if(second.cm)
        cmspeak <- paste(cmspeak, "  cm code (2nd choice) =", cm.code[2])
    }
    else cmspeak <- "No information is available on cm"
  }
  if(!is.null(pc.spline)) {
    pfrac.interp <- pc.spline/100
    yhat.pred <- link.fun(pfrac.interp)
    dead.interp <- dead[interp.rows]
    tot.interp <- tot[interp.rows]
    p.obs <- (dead.interp/tot.interp)
    time.interp <- as.numeric(mins[interp.rows])
    time1 <- max(time.interp[p.obs == 0])
    if(is.na(time1))
      time1 <- min(time.interp)
    time2 <- min(time.interp[p.obs == 1])
    if(is.na(time2))
      time2 <- max(time.interp)
    time.here <- (time.interp >= time1) & (time.interp <= time2)
    dead.interp <- dead.interp[time.here]
    tot.interp <- tot.interp[time.here]
    p.interp <- (dead.interp + 1/6)/(tot.interp + 1/3)
    x.interp <- time.interp[time.here]
  }
  ##
  if(!is.null(pc.monotone)) {
    time.here <- as.numeric(mins[mono.rows])
    ord.x <- order(time.here)
    subs.here <- (1:length(mono.rows))[mono.rows][ord.x]
    dead.mono <- dead[subs.here]
    tot.mono <- tot[subs.here]
    p.obs <- (dead.mono/tot.mono)
    time.mono <- time.here[ord.x]
  }
  ##
  ld.dp <- 2 - floor(log(max(x.all[cutit], na.rm = T))/log(10))
  ld.dp <- max(0, ld.dp)
  if(is.na(ld.dp))
    ld.dp <- 1
  if(nchar(monospeak) > 0)
    cat(monospeak, "\n")
  if(nchar(cutspeak) + nchar(omitspeak) > 0)
    cat(cutspeak, " ", omitspeak)
  cat(sum(cutit), "points remain_")
  cat(cmspeak, "\n")
  if(takelog) {
    x.trt <- log(x.all[cutit] + offset)
  }
  else {
    x.trt <- xfun(x.all[cutit] + offset)
  }
  xbar <- mean(x.trt)
  x.explan <- x.trt - xbar
  dead2 <- dead[cutit]
  tot2 <- tot[cutit]
  nmid <- length(x.trt[dead2 < tot2])
  lt <- rep(-999, length(pc))
  b0 <- -999
  b1 <- -999
  selog50 <- -999
  selog99 <- -999
  cept <- NA
  dev <- NA
  df <- NA
  dev.robust <- NA
  df.robust <- NA
  disp <- NA
  resid <- NULL
  resid.dev <- NULL
  lt.se <- rep(NA, length(pc))
  cm.est <- cm
  cm.n <- c(cm, numcm)
  if(!is.null(pc.monotone) && (length(time.mono) >= 2)) {
    if(link == "loglog")
      link <- "cloglog"
    lt.monotone <- pool.adj(time.mono, dead.mono, tot.mono, phat = pc.monotone,
                            cm = cm, cm.strategy = cm.strategy, cm.allcodes = 
                            cm.allcodes, plotit = plot.monotone, link = link,
                            xfun = xfun, legend = leg, x.cm = x.cm,
                            dead.cm = dead.cm, tot.cm = tot.cm, span = 
                            span.mono)
    note <- c("( loess)", "( monotone line)")[names(lt.monotone)]
    cat(paste("   LT", pc.monotone, ":", format(round(lt.monotone, ld.dp)), 
              sep = ""), note, "\n")
  }
  else lt.monotone <- NULL
  if(!is.null(pc.spline)) {
    lt.spline <- interp.curve(x.interp, p = p.interp, pval = pfrac.interp, 
                              plot.interp = plot.spline, fun = link.fun)
    cat(paste("   LT", pc.spline, ":",  , sep = ""),
        format(round(lt.spline, ld.dp)), "(spline)   ", "\n")
  }
  else lt.spline <- NULL
  if(nmid == 2)
    full.robust <- F
###  browser()
  if(nmid >= 2) {
    u <- likelihood.ci(cm.n = cm.n, x.explan, xbar, dead2, tot2, link = link,
                       xfun.inv = xfun.inv, interval = interval, pc = pc,
                       save.resid = save.resid, cm.strategy = cm.strategy,
                       full.robust = full.robust)
    lt <- u$ld
    ld.dp <- 2 - floor(log(lt[length(lt)])/log(10))
    if(is.na(ld.dp))
      ld.dp <- 1
    ld.dp <- max(ld.dp, 0)
    b0 <- u$coef[1]
    b1 <- u$coef[2]
    cept <- b0 - b1 * xbar
    lt.se <- u$selog
    resid <- u$resid
    resid.dev <- u$resid.dev
    dev <- u$dev
    df <- u$df
    dev.robust <- u$dev.robust
    df.robust <- u$df.robust
    disp <- u$dispersion
    linpred <- b0 + b1 * x.explan    #  comprob <- inv.fun(linpred)
###  fitr <- (1 - comprob) * tot2
###  fitc <- comprob * tot2
    if(printdat) print(cbind(x.all[cutit], dead2, tot2))    
###   print(cbind(x.all[cutit], x.explan, fitr, dead2, tot2))
###  if(min(fitr) < 1) {
###   cat("Warning.  Some expected numbers 0f dead are < 1", 
###    fill = T)
###   cat("Exp. No. Dead:", format(round(fitr, 3)), fill = T)
###   
###  }
###  if(min(fitc) < 1) {
###   cat(
###    "Warning.  Some expected numbers of survivors are < 1", 
###    fill = T)
###   cat("Exp. Survivors   :", format(round(fitc, 3)), fill
###     = T)
###  }
  }
  else {
### Estimates of LT50 and LT90 when too few data points are available
                                        ###
    if(printdat) print(cbind(x.all, dead, tot, cutit))
    cat(nmid, " data points give mortalities < 1.0:     ")
    lt <- NA
    cat("No estimate is available", "\n")
  }
  if(!save.resid) tot2 <- NULL    
### Keep totals only if required along with residual information 
  list(lt = lt, se = lt.se, b0 = cept, b1 = b1, lt.spline = lt.spline, 
       lt.monotone = lt.monotone, cm = cm.est, dev = dev, df = df, dev.robust
       = dev.robust, df.robust = df.robust, dispersion = disp, total = tot2, 
       resid = resid, resid.dev = resid.dev, times = x.trt)
}
, comment = "14/09/2004")
"flex.contour" <-
structure(function(df = cont.test.df[1:273, (1:3)], transpose = F, label.pos = (13:18)/20,
    levs.pc = c(50, 75, 90, 95, 99), lev.cex = 0.6, lev.font = 1, mark = F, 
    alone = F, ztransform = "logit")
{
# Flexibility in positioning the contour-level labels is the name of the game.
#
# df is dataframe such as produced by gee.
# Requires also is.not.na() in Gems & make.line.loess()
# Not generic yet. Uses only logit transformed % data
    xxs <- unique(df[, 1])
    yys <- unique(df[, 2])
    zzs <- df[, 3]
    zzs.mat <- matrix(zzs, nr = length(is.not.na(xxs)))
    x.use <- iff(transpose, yys, xxs)
    y.use <- iff(transpose, xxs, yys)
    if(transpose)
       zzs.mat <- t(zzs.mat)
    ztransform.fn <- get(ztransform)
    lev.pos <- ztransform.fn(levs.pc/100)    # (levs.pc are percentages)
    lev.txt <- paste(levs.pc)
    cont.fit <- contour(x.use, y.use, zzs.mat, save = T, levels = lev.pos)
    if(alone)
       plot(range(x.use), range(y.use), type = "n")
    if(length(label.pos < length(levs.pc)))
       label.pos <- rep(label.pos, length(levs.pc))
    for(i in 1:length(cont.fit)) {
       make.line.loess(cont.fit[[i]], lab = lev.txt[i], mark = mark, label.pos
           = label.pos[i], cex = lev.cex, lev.font = lev.font)
    }
}
, comment = "03/06/1998")
"flyplot" <-
structure(function(mn = 1:12, ri = 3, cj = 4, line = T, cutoff.mono = NULL, data = NULL, 
           datafun = NULL, choice = 1, plimits = c(0.1, 0.9995), link = "cloglog", 
           range.strategy = "page", fit.trend = "line", pc = c(line = 50, line = 99), 
           span.mono = 1, n.strategy = "mn", xlabels = NULL, xfun = function(x)
           x, takelog = F, before = NA, new.page = T, mkh = 0.025, cex = NULL, maint.line
           = 1, title.line = 0.25, title.space = 0, xtitle = NULL, ytitle = NULL, ext
           = NULL, lt.ld = "LT", datestamp = T, byrow = T, mtext.line = 2)
{
### Title for data subset j is maint
### Prints graphs 4 to a page, starting with graph for data subset j=i
### dset holds all the data
### values of idset (1, 2, ...) identify subsets of dset
### range.strategy may be "individual", or "page", or "all"
### fit.trend may be line, or mono(tone), or mono.line
### mono.line gives monotone fit, then line
### Set pc to decide which LTs will appear on the margin of the plot.
  ##
  options(width = 200)
  on.exit(options(width = 80))
  trend.4 <- substring(fit.trend, 1, 4)
  do.abers <- trend.4 == "mono" | trend.4 == "loes"
  oldpar <- par()
  on.exit(par(oldpar), T)    #
### Set up different par parameters for postscript and motif devices.

  if(names(dev.cur()) == "postscript") {
    omi <- c(10, 12 + title.space/3, 12 + title.space, 12 + title.space/3)/25.4
    mgp <- c(1.75, 0.7, 0)
    mai <- c(8, 10, 5, 1)/25.4
  }
  else {
    omi <- c(5, 5 + title.space/3, 7 + title.space, 10 + title.space/3)/25.4
    mgp <- c(2.25, 1, 0)
    mai <- c(15, 20, 10, 0)/25.4
  }
  
  if(new.page & byrow)
    par(mai = mai, mgp = mgp, mfrow = c(ri, cj), omi = omi)
  else if(new.page & !byrow)
    par(mai = mai, mgp = mgp, mfcol = c(ri, cj), omi = omi)
  if(is.null(cex) & (ri * cj == 6))
    cex <- 0.65
  if(!is.null(cex))
    par(cex = cex)
  final.choice <- choice[length(choice)]
  if(!is.null(data)) {
    ab <- data[[final.choice]]
    leg.ab <- ab$leg.brief
    if(is.null(leg.ab))
      leg.ab <- ab$legend
    choice.call <- ab$choice
    if(missing(takelog) & missing(xfun)) {
      takelog <- ab$takelog
      if(takelog)
        xfun <- log
    }
  }
  else {
    ab <- NULL
    leg.ab <- NULL
    choice.call <- choice
  }
  if(missing(datafun) & !is.null(ab))
    datafun <- get(ab$datafun)
  if(!is.null(ext))
    u <- datafun(choice.call, ext = ext)
  else u <- datafun(choice.call)
  if(is.null(leg.ab))
    leg.ab <- u$leg.brief
  if(!is.null(pc)) {
    lt.txts <- paste(pc)
    lt.prefix <- paste(lt.ld, pc, "=", sep = "")
    lt.strategy <- names(pc)
  }
  else {
    lt.strategy <- NULL
    lt.txts <- NULL
  }
  if(missing(ext))
    ext <- NULL
  if(!is.null(ab) & !is.null(lt.strategy)) {
    first.one <- switch(lt.strategy[1],
                        loess = ,
                        monotone = ,
                        mono = "lt.monotone",
                        line = "lt")
    ltmat.leg <- matrix(, dim(ab[[first.one]])[1], length(pc))
    for(k in seq(along = lt.strategy)) {
      which.lt <- switch(lt.strategy[k],
                         loess = ,
                         monotone = ,
                         mono = "lt.monotone",
                         line = "lt")
      ltmat.leg[, k] <- ab[[which.lt]][, lt.txts[k]]
    }
    dp <- max(c(3 - ceiling(log(quantile(ab[[first.one]], probs = 0.75, 
                                         na.rm = T))/log(10)), 0))
  }
  else ltmat.leg <- NULL
  if(!is.null(ltmat.leg)) {
    if(is.null(leg.ab))
      leg.ab <- rep("", dim(ltmat.leg)[1])
    leg.lt <- apply(ltmat.leg, 1, function(x, z, u, dp)
                    paste(z, round(x, dp), collapse = "; ", sep = ""),
                    z = lt.prefix, dp = dp)
    legend <- paste(leg.ab, " [", leg.lt, "]", sep = "")
  }
  else if(!is.null(leg.ab))
    legend <- leg.ab
  else if(length(lt.txts) > 0)
    cat(paste(paste("LT", lt.txts, sep = ""), collapse = ""), 
        "values are not available, perhaps because pc was not given correctly\n"
        )
  cutx <- u$cutx
  offset <- u$offset
  cm <- NULL
  if(!is.null(ab)) {
    cm.code <- ab$cm.code
    cm <- ab$cm
    cm.strategy <- ab$cm.strategy
    cmtot <- u$cmtot
  }
  else {
    cm.code <- u$cm.code
    cm <- u$cm
    cmtot <- u$cmtot
    cm.strategy <- u$cm.strategy
  }
  if(is.null(cm.strategy))
    cm.strategy <- "adjust.later"
  if(is.null(cm.code))
    cm.code <- 0
  cm.allcodes <- u$cm.allcodes
  if(is.null(cm.allcodes))
    cm.allcodes <- cm.code
  times.all <- as.character(u$time)
  tot.all <- u$tot
  other.rows <- as.logical(match(times.all, cm.allcodes, nomatch = 0))
  keep <- rep(T, length(other.rows))
  if(any(is.na(as.numeric(times.all[!other.rows])))) {
    cat("\n*** NA(s) appear among non-control times ***\n")
    numit <- times.all[!other.rows]
    look <- is.na(as.numeric(numit))
    print(data.frame(times = numit[look], totals = tot.all[!other.rows][look
                                            ], dead = u$dead[!other.rows][look]))
    keep[!other.rows][look] <- F
  }
  if(any(is.na(tot.all) | tot.all == 0)) {
    look <- is.na(tot.all) | tot.all == 0
    cat("\nNAs or zeros appear among totals\n")
    print(data.frame(times = times.all[look], total = tot.all[look], dead = 
                     u$dead[look]))
    keep[look] <- F
  }
  time.txt <- times.all[keep]
  times <- array( - Inf, length(time.txt))
  use.trt <- !other.rows[keep] | time.txt == "0"
  times[use.trt] <- as.numeric(time.txt[use.trt])
  xmin <- min(times[use.trt])
  idset <- u$id[keep]
  tot <- u$total[keep]
  dead <- u$dead[keep]
  if(missing(xtitle))
    xaxtitle <- u$xaxtitle
  else xaxtitle <- xtitle
  treat <- u$treat
  maint <- u$maint
  if(is.null(xlabels))
    xxlabels <- u$xlabels
  else xxlabels <- xlabels
  nu <- unique(idset)
  nn <- match(nu, idset)    # bigstage <- dset[, stagecol]
  n <- ri * cj
  if(max(mn) > length(nu)) {
    maxj <- length(nu)
    cat("You have specified plots up to plot no.", max(mn), 
        "\nwhereas data is available for", maxj, "plots only.\n")
    mn <- mn[mn <= maxj]
  }
  graphnum <- mn
  maxj <- max(mn)
  if(range.strategy != "individual")
    common.range <- switch(range.strategy,
                           page = mn,
                           all = 1:length(nu))
  todo <- length(nu) - maxj
  if(todo > 0)
    cat("Datasets", maxj + 1, "to", length(nu), "will remain after this.", 
        fill = T)
  xmin <- min(times)
  if(takelog)
    xmin <- min(times[times + offset > 0])
  xrange <- switch(cm.strategy,
                   adjust.later = range(times),
                   abbott = range(times))
  ij <- 0
  if(range.strategy != "individual") {
    xrm <- matrix(, 2, length(common.range))
    for(k in common.range) {
      ij <- ij + 1
      timtim <- times[idset == nu[k]]
      xrm[, ij] <- switch(cm.strategy,
                          adjust.later = range(timtim),
                          abbott = range(timtim))
    }
    xrange <- range(xrm)
  }
  if(!missing(before))
    xrange[2] <- before
  ij <- 0
  cmk <- NULL
  for(k in graphnum) {
    leg.k <- legend[k]
    ij <- ij + 1
    j <- nu[k]
    take <- idset == j
    timesj <- times[take]
    deadj <- dead[take]
    totj <- tot[take]
    time.txj <- time.txt[take]
    cmrows <- time.txj == cm.code[1]
    second.cm <- F
    if(sum(cmrows) == 0 & length(cm.code) > 1) {
      cmrows <- time.txj == cm.code[2]
      second.cm <- T
    }
    else second.cm <- F
    if(!is.null(cmtot))
      numcm <- cmtot[k]
    else numcm <- NULL
    if(is.null(numcm)) numcm <- 0    # numcm may be reset below
    if(is.null(cm)) {
      if(sum(cmrows) > 0) {
        if(any(timesj[cmrows] !=  - Inf & timesj[cmrows] != 0))
          cat("\n*** Warning: Fault in specification of cm rows ***", 
              "\n")
        dead0 <- sum(deadj[cmrows])
        tot0 <- sum(totj[cmrows])
        cmk <- dead0/tot0
        numcm <- tot0
        n.cm <- sum(cmrows)
        cmspeak <- paste("   cm(obs) =", format(round(cm, 3)), "(from", 
                         n.cm, paste("point", switch((n.cm > 1) + 1,
                                                     "",
                                                     "s",
                                                     ), ")", sep = ""))
        if(second.cm)
          cmspeak <- paste(cmspeak, "  cm code (2nd choice) =", cm.code[2
                                                                        ])
      }
      else cmspeak <- "No information is available on cm"
    }
    else {
                                        # !is.null(cm)
      cmk <- cm[k]
      if(cm.strategy == "abbott") {
        cat("Take cm =", format(round(cmk, 3)), "\n")
        take <- take & !other.rows
      }
    }
    if(do.abers) {
      use.mono <- use.trt[take]
      if(!is.null(cutoff.mono))
        use.mono[timesj[use.mono] < cutoff.mono] <- F
      time.here <- timesj[use.mono]
      ord.x <- order(time.here)
      subs.here <- (1:length(use.mono))[use.mono][ord.x]
      dead.mono <- deadj[subs.here]
      tot.mono <- totj[subs.here]
      p.mono <- (dead.mono/tot.mono)
      time.mono <- time.here[ord.x]
      other.take <- other.rows[take]
      x.cm <- time.txt[take][other.take]
      dead.cm <- deadj[other.take]
      tot.cm <- totj[other.take]
      if(length(time.mono) < 2)
        do.abers <- F
    }
    if(do.abers) {
      if(link == "loglog")
        link <- "cloglog"
      lt.mono <- pool.adj(time.mono, dead.mono, tot.mono, phat = NULL, cm
                          = cmk, cm.strategy = cm.strategy, cm.allcodes = cm.allcodes, 
                          plimits = plimits, xtit = xaxtitle, plotit = fit.trend, link = 
                          link, xfun = xfun, legend = leg.k, x.cm = x.cm, dead.cm = dead.cm,
                          tot.cm = tot.cm, span = span.mono)
    }
    if(range.strategy == "individual")
      xrange <- switch(cm.strategy,
                       adjust.later = ,
                       abbott = range(times[take]))
    if(diff(range(xxlabels)) > 0)
      xlabels <- xxlabels
    else xlabels <- pretty(range(times[take]))
    if(line) {
      ltab <- ab
      b <- ltab[["slope"]][k]
      a <- ltab[["intercept"]][k]
    }
    else {
      a <- -999
      b <- -999
    }
    startx <- max(xmin, cutx[k])
    jk <- switch(n.strategy,
                 id = j,
                 mn = k)
    if(!do.abers) {
                                        #

      simplot(time.txt[take], deadj, totj, link, cm = cmk, cm.strategy = 
              cm.strategy, xtit = xaxtitle, ytit = ytitle,
              main = paste(jk, ": ", "", leg.k, sep = ""), xfun = xfun,
              takelog = takelog, line = line,
              ab = c(a, b), clip = c(startx, max(timesj)), xlimits = xrange, 
              xlabels = xlabels, offset = offset, plimits = plimits, mkh = mkh, 
              title.line = title.line, id = NULL)
    }
    
###     if(names(dev.cur()) == "postscript" & nchar(maint) > 0)
###       mixed.mtext(texts = maint, side = 3, outer = T, cex = 1.25, line = 
###                   maint.line, adj = 0.5)
###     else

    mtext(maint, 3, outer = T, cex = 1.4, font = 2, line = maint.line)
  }
  if(cm.strategy == "abbott")
    mtext("Data is plotted following Abott's adjustment", 3, line = 
          maint.line - 1, outer = T, cex = 0.5)
  lt.leg <- paste(paste("lt", pc, ":", names(pc), sep = ""), collapse = "; ")
  par(cex = 0.4)
  if(datestamp) {
    r.txt <- paste(lt.leg, "   ", system("date +%d/%m/%y'  '%H:%M", TRUE))
    l.txt <- system("pwd", TRUE) ## get call to work sometime, deparse(match.call())
    mtext(r.txt, side = 1, adj = 1, outer = T, line = mtext.line, cex = .6)
    mtext(l.txt, side = 1, adj = 0, outer = T, line = mtext.line, cex = .6)
  }
}
, comment = "03/04/2006")
"formula.variables" <-
structure(function(myformula, unwanted = NULL)
{
    ops <- c("~", "+", "-", "*", "|", "I", "(", ")", "sqrt", "log", "exp", 
       "logit", "cloglog", "ang", unwanted)
    out <- unlist(myformula)
    out[!(out %in% ops)]
}
, comment = "10/10/1997")
"gem.df" <-
structure(list(Object = structure(as.integer(c(26, 65, 67, 89, 
80, 60, 25, 94, 10, 9, 99, 73, 53, 45, 39, 77, 41, 61, 19, 47, 
76, 75, 74, 31, 5, 63, 43, 21, 42, 37, 17, 64, 55, 88, 98, 28, 
97, 6, 86, 2, 4, 93, 72, 14, 59, 36, 24, 85, 70, 69, 29, 57, 
90, 83, 20, 82, 16, 38, 12, 11, 84, 18, 46, 1, 44, 23, 34, 13, 
7, 95, 91, 52, 58, 56, 87, 71, 51, 96, 8, 78, 40, 22, 54, 62, 
27, 32, 68, 15, 33, 3, 48, 35, 66, 81, 49, 92, 50, 79, 30)), .Label = c("add.text", 
"agg", "ang.bt", "append.cols", "average.down", "bar.legs", "blank.plot", 
"boxplot.fn", "catalogue", "catalogue.gems", "check.fact", "check.na", 
"clg", "clipline", "cloglog", "cloglog.bt", "cols.for.genstat", 
"comb", "complot", "count.nas", "data.spot", "df.mat", "df.sort", 
"df.summary", "df.to.file", "dmodes", "errorbars", "factorize", 
"FF", "fieller", "fill.down", "find.first", "find.pos", "find.pos.mat", 
"fitconf", "flex.contour", "flyplot", "formula.variables", "gems.df", 
"gen.write", "get.col.names", "get.formula", "get.mort.tables", 
"glean.blank", "glm", "junk.df", "levels.for.genstat", "likelihood.ci", 
"link.function", "link.inverse", "list.mat", "list.to.data.frame", 
"logit", "logit.bt", "lookup", "make.df", "make.factors", "make.id", 
"make.line.loess", "MASS", "mean.lt", "mean.lt.short", "month.length", 
"occurrence", "pid", "plot.lt", "PLS", "pool.adj", "ppaste", 
"pseudo.f", "p.sunflowers", "qik.sum", "read.table", "relevel", 
"relevel.default", "relevel.factor", "reorder", "rms", "robust.deviance", 
"save.new", "sem", "set.screens", "show.nas", "simplot", "s.tapply", 
"stdev", "strip.trail", "summarize", "SURV", "tab.file", "table.all", 
"tab.mat", "text.bp", "text.lot", "time.to.mort", "tuk.calc", 
"unfactor", "Updown", "write.function"), class = "factor"), Mode = structure(as.integer(c(2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)), .Label = c("dataframe", 
"function", "numeric"), class = "factor"), Rows = structure(as.integer(c(1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1)), .Label = c("--", 
"137", "15"), class = "factor"), Cols = structure(as.integer(c(1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1)), .Label = c("--", 
"13", "8"), class = "factor"), Len = c(1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 8, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 12, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 13, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1), Date = structure(as.integer(c(85, 
66, 18, 76, 76, 53, 48, 10, 10, 6, 81, 78, 78, 78, 75, 30, 33, 
61, 60, 50, 8, 8, 8, 41, 22, 82, 32, 47, 44, 28, 28, 71, 71, 
65, 46, 36, 64, 9, 59, 37, 74, 49, 34, 77, 7, 7, 4, 26, 43, 25, 
16, 11, 70, 5, 5, 80, 67, 23, 58, 58, 55, 63, 29, 27, 19, 45, 
31, 17, 12, 69, 52, 52, 14, 2, 62, 35, 1, 68, 13, 83, 38, 51, 
57, 54, 86, 3, 84, 40, 24, 39, 79, 79, 15, 21, 20, 73, 42, 72, 
56)), .Label = c("01/02/1997", "01/04/1997", "01/06/1996", "01/06/1998", 
"01/12/1997", "02/04/2001", "03/06/1998", "03/09/1999", "03/10/1998", 
"04/04/2001", "06/01/1998", "06/05/1997", "06/12/1996", "07/04/1997", 
"08/10/1995", "09/01/1998", "09/05/1997", "09/05/2001", "09/07/1997", 
"09/08/1995", "09/09/1995", "10/08/1999", "10/10/1997", "11/01/1996", 
"11/02/1998", "11/04/1998", "11/07/1997", "12/04/1999", "12/07/1997", 
"12/07/2000", "13/05/1997", "13/05/1999", "13/06/2000", "13/08/1998", 
"14/02/1997", "14/12/1998", "15/09/1998", "15/11/1996", "15/12/1995", 
"16/04/1996", "16/08/1999", "16/10/1994", "17/02/1998", "17/04/1999", 
"17/05/1997", "17/12/1998", "18/04/1999", "18/04/2001", "18/08/1998", 
"18/09/1999", "18/10/1996", "19/04/1997", "20/04/2001", "20/08/1996", 
"20/09/1997", "21/03/1994", "21/08/1996", "21/09/1997", "21/09/1998", 
"22/04/2000", "22/05/2000", "23/03/1997", "23/07/1997", "23/11/1998", 
"23/12/1998", "24/05/2001", "24/11/1997", "24/12/1996", "25/04/1997", 
"25/12/1997", "26/01/1999", "26/06/1994", "26/06/1995", "26/08/1998", 
"27/03/2001", "27/04/2001", "27/06/1998", "28/03/2001", "29/10/1995", 
"29/11/1997", "30/03/2001", "30/07/1999", "30/11/1996", "31/05/1996", 
"31/05/2001", "31/06/1996"), class = "factor")), .Names = c("Object", 
"Mode", "Rows", "Cols", "Len", "Date"), class = "data.frame", row.names = c("1", 
"2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", 
"14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24", 
"25", "26", "27", "28", "29", "30", "31", "32", "33", "34", "35", 
"36", "37", "38", "39", "40", "41", "42", "43", "44", "45", "46", 
"47", "48", "49", "50", "51", "52", "53", "54", "55", "56", "57", 
"58", "59", "60", "61", "62", "63", "64", "65", "66", "67", "68", 
"69", "70", "71", "72", "73", "74", "75", "76", "77", "78", "79", 
"80", "81", "82", "83", "84", "85", "86", "87", "88", "89", "90", 
"91", "92", "93", "94", "95", "96", "97", "98", "99"), comment = "31/05/2001")
"gems" <-
structure(function(ww = "plot", most = 10)
{
  ## Purpose: searches Gems for function using dmodes
  ## ----------------------------------------------------------------------
  ## Modified from: 
  ## ----------------------------------------------------------------------
  ## Arguments: 
  ## ----------------------------------------------------------------------
  ## Author: Patrick Connolly, Creation date: 17 Jun 2004, 13:56

gem.pos <- grep("Gems", search())
dmodes(ww, gem.pos, most)

}
, comment = "17/06/2004")
"gen.write" <-
structure(function(df, file)
{
#To create a file readable by genstat from a dataframe
#
  write.table(df, file, sep = "  ", na = "*", row.names = F, col.names = F, quote = F)
}
, comment = "26/03/2003")
"get.col.names" <-
structure(function(x, patt = ".D")
{
# Gets the names of x that fit a particular pattern patt
    col.names <- names(x)
    y <- col.names[grep(patt, col.names)]
}
, comment = "13/06/2000")
"get.formula" <-
structure(function(ab.list = ab.second.comb, bit = "cs", link = "cloglog", rnd = 4)
{
# Gets the formula for lines from ab list
    ab <- ab.list[[paste(bit)]]
    legends <- ab$legend
    glean <- get(ab$datafun)
    cat(glean()$maint)
    cat("\n\n")
    out.list <- list()
    for(i in 1:len(legends))
       out.list[[ab$legend[i]]] <- ppaste(link, "(p) = ", round(ab$intercept[i],
          rnd), " + ", round(ab$slope[i], rnd), " * t")
    out.list
}
, comment = "17/04/1999")
"get.mort.tables" <-
structure(function(ab.list = ab.second.comb, bit = "cs", intervals = NULL, rnd = 4, file
     = "")
{
# Does table of expected mortality for lines from ab list
    ab <- ab.list[[paste(bit)]]
    legends <- ab$legend
    glean <- get(ab$datafun)
    cat(glean(choice = bit)$maint)    # browser()
    cat("\n\n")
    if(is.null(intervals))
       intervals <- seq(0, round(max(glean(choice = bit)$time)))
    out.list <- list(times = intervals)
    for(i in 1:len(legends))
       out.list[[ab$legend[i]]] <- round(cloglog.bt(ab$intercept[i] + ab$slope[
          i] * intervals) * 100, 1)
    out.df <- as.data.frame(out.list)
    if(file != "") {
       write(glean(choice = bit)$maint, file = file)
       df.to.file(out.df, file = file, append = T)
    }
    else out.df
}
, comment = "13/05/1999")
"gimp" <-
structure(function(file = NULL)
{
  ## Purpose:
  ## ----------------------------------------------------------------------
  ## Arguments:
  ## ----------------------------------------------------------------------
  ## Author: Zaphod Beeblebrox, Date: 15 Apr 2002, 11:26
if(is.null(file))
  system("gimp &")
else system(paste("gimp",file,"&"))
}
, comment = "15/04/2002")
"glean.blank" <-
structure(function(choice = 1)
{
    blank.df <- df.sort(blank.df, rev(c("Stage", "Position", "Rep")))
    attach(blank.df)
    on.exit(detach("blank.df"))
    idset <- make.id(Time)
    cutx <- NULL
    leg.brief <- unique(paste(Stage, Position, " Rep", Rep, sep = ""))
    maint <- paste(degree(40), "heat treatment of some bug or other")
    xlabels <- c(0, 0)
    xaxtitle <- "Time (minutes)"
    list(id = idset, times = Time, total = Dead + Live, dead = Dead, cutx = 
       cutx, offset = 0, xaxtitle = xaxtitle, maint = maint, legend = leg.brief,
       xlabels = xlabels, takelog = F)
}
, comment = "09/07/1997")
"gmt" <-
structure(function(x, format = "%Y-%m-%d")
{
### Purpose: Converts a text string of yyyy-mm-dd format to POSIXct at tz = GMT
### ----------------------------------------------------------------------
### Modified from: (useful to use with ddif() to get days difference
### ----------------------------------------------------------------------
### Arguments: modify format for zillions of different date formats
### ----------------------------------------------------------------------
### Author: Patrick Connolly, Creation date: 20 Feb 2004, 09:41
  
x1 <- strptime(x, format = format)
 as.POSIXct(x1, tz = "GMT")


}
, comment = "05/03/2004")
"gnum" <-
structure(function(file = NULL)
{
  ## Purpose:
  ## ----------------------------------------------------------------------
  ## Arguments:
  ## ----------------------------------------------------------------------
  ## Author: Zaphod Beeblebrox, Date: 15 Apr 2002, 11:26
if(is.null(file))
  system("gnumeric &")
else system(paste("gnumeric",file,"&"))
}
, comment = "28/06/2002")
"gv" <-
structure(function(file = NULL)
{
  ## Purpose:  Starts Ghostview in the current directory
  ## ----------------------------------------------------------------------
  ## Arguments:
  ## ----------------------------------------------------------------------
  ## Author: Zaphod Beeblebrox, Date: 21 Mar 2002, 13:18
if(is.null(file))
  system("gv &")
else system(paste("gv",file,"&"))

}
, comment = "28/06/2002")
"iff" <-
structure(function(test, true.result, false.result)
{
    if(test)
       true.result
    else false.result
}
, comment = "15/07/1997")
"ipsofactor" <-
structure(function(x)
{
  ## Purpose:  Makes a factor with levels in the current order
  ## ----------------------------------------------------------------------
  ## Arguments:
  ##           x: character vector 
  ## ----------------------------------------------------------------------
  ## Author: Zaphod Beeblebrox, Date:  6 Mar 2002, 10:47

y <- factor(x, levels = unique(x))
y
}
, comment = "28/06/2002")
"junk.df" <-
structure(list(Fruit = c("apple", "pear", "plum", "cherry", "apricot", 
"apple", "pear", "plum", "cherry", "apricot", "apple", "pear", 
"plum", "cherry", "apricot"), January = c(4, 15, 10, 11, 14, 
5, 8, 18, 11, 15, 18, 14, 11, 5, 14), February = c(8, 13, 6, 
5, 13, 12, 14, 9, 7, 13, 11, 9, 11, 14, 5), March = c(11, 15, 
11, 13, 12, 13, 14, 15, 16, 15, 10, 16, 14, 10, 16), April = c(22, 
15, 9, 13, 16, 21, 8, 18, 14, 22, 13, 18, 23, 10, 14), May = c(25, 
11, 15, 18, 24, 15, 9, 11, 24, 17, 25, 23, 13, 20, 20), Week = c("A", 
"A", "A", "A", "A", "B", "B", "B", "B", "B", "C", "C", "C", "C", 
"C")), .Names = c("Fruit", "January", "February", "March", "April", 
"May", "Week"), row.names = c("1", "2", "3", "4", "5", "6", "7", 
"8", "9", "10", "11", "12", "13", "14", "15"), comment = "31/05/2001", class = "data.frame")
"kullas" <-
structure(function()
{
### Purpose: Basic Trellis colours for lattice plots
### ----------------------------------------------------------------------
### Modified from: col.spray in /home/hrapgc/Rstuff/garry/industry
### ----------------------------------------------------------------------
### Arguments: 
### ----------------------------------------------------------------------
### Author: Patrick Connolly, Creation date: 16 Jan 2004, 13:52
  lab.cex <- 1.2
  list(background = list(col="transparent"),
       bar.fill = list(col="#c8ffc8"),
       box.rectangle = list(col = "darkgreen"),
       box.umbrella = list(col = "darkseagreen", lty = 1),
       box.dot = list(col = "darkorchid", cex = 1),
       dot.line = list(col="#e8e8e8"),
       dot.symbol = list(col="orchid", cex = .8, pch = 1),
       plot.line = list(col="darkgreen"),
       plot.symbol = list(col="orchid", cex = .8, pch = 1),
       plot.polygon = list(alpha = 1, col="darkseagreen", border = "black",
         lty = 1, lwd = 1),       
       par.xlab.text = list(cex = lab.cex),
       par.ylab.text = list(cex = lab.cex),
       axis.components = list(
         left = list(tck = .6, pad1 = .5),
         top = list(tck = .6, pad1 = .65),
         right = list(tck = .6, pad1 = .5),
         bottom = list(tck = .6, pad1 = .65)),
       
       regions = list(col = heat.colors(100)),
       reference.line = list(col="turquoise", lty = 3),
       superpose.line = list(col = c("darkgreen", "red", "royalblue",
                               "orange", "brown", "turquoise", "orchid"),
         lty = rep(1,7), lwd = rep(1, 7)),
       superpose.symbol = list(pch = c(1:7), cex = rep(.9, 7),
         col = c("darkgreen", "red", "royalblue", "orange", "brown",
           "turquoise", "orchid"))
       )
}
, comment = "03/08/2006")
"lat.set" <-
structure(function(setting = par.xlab.text, subsetting = cex, to = 1.3)
{
  ## Purpose: Change trellis settings in one move
  ## ----------------------------------------------------------------------
  ## Arguments:
  ##  setting    -- which setting is to be changed
  ##                  (a name of a list from trellis.settings)
  ##  subsetting -- which part of that list
  ##  to         -- what are we changing it to
  ## ----------------------------------------------------------------------
  ## Author: Patrick Connolly, Date: 19 Apr 2002, 10:06

  y <- as.character(substitute(setting))
  z <- as.character(substitute(subsetting))
  x <- trellis.par.get(y)
  x[[z]] <- to
  trellis.par.set(y, x)
}
, comment = "07/06/2002")
"lattice" <-
structure(function()
  {
### Installs grid and lattice library
    library(grid, lib.loc = "/home/hrapgc/Rstuff/library/")
    library(lattice, lib.loc = "/home/hrapgc/Rstuff/library/")
  }
, comment = "02/10/2001")
"lerrorbars" <-
structure(function(x, y, se, yl = y - se, yu = y + se, eps, ...)
{
  ## Purpose: Lattice errorbars
  ## ----------------------------------------------------------------------
  ## Modified from: errorbar
  ## ----------------------------------------------------------------------
  ## Arguments: 
  ## ----------------------------------------------------------------------
  ## Author: Marcus Davy , Creation date: 31 Aug 2005, 10:58

  if(any(is.na(yl)) | any(is.na(yu)))
    ltext(x[is.na(yl) | is.na(yu)], y[is.na(yl) | is.na(yu)], "NA",
          adj = 1)
  lsegments(x, yl, x, yu, ...)
  lsegments(x - eps, yl, x + eps, yl, ...)
  lsegments(x - eps, yu, x + eps, yu, ...)
}
, comment = "31/08/2005")
"levels.for.genstat" <-
structure(function(x, no.quotes = T)
{
# Returns a string of the factor levels to use in genstat
# paste from between " marks
# change the opening and closing "   to ' if quotes are wanted
  paste(unique(x), collapse = ifelse(no.quotes, ", ", "', '"))
}
, comment = "27/03/2003")
"likelihood.ci" <-
structure(function(cm.n = c(0, 0), heatval, xbar, dead, tot, offset = 0, link = "cloglog",
    xfun.inv = exp, interval = T, pc = c(50, 99), dp = 1, save.resid = F, 
    cm.strategy = "adjust.later", full.robust = T)
{
# Uses robust glm
# heatval is the x-variable.
# xbar is a (usually centred) origin of measurement for heatval
  cm <- cm.n[1]
    numcm <- cm.n[2]
    pfrac <- pc/100
    if(cm.strategy == "adjust.later")
       pval <- cm + (1 - cm) * pfrac
    else pval <- pfrac
    n <- length(heatval)
    xvec <- heatval
    link.fun <- link.function(link)    # inv.fun <- link.inverse(link)
    resid <- NULL
    resid.dev <- NULL
    if(cm.strategy == "adjust.later") {
       p <- dead/tot    #  ymat <- cbind(dead, tot - dead)
       reflect.logsurv <- 1
       if(link == "logsurv") {
          ymat <- cbind(tot - dead, dead)
          reflect.logsurv <- -1
       }
       if(link == "log" | link == "logsurv")
          fam <- quasi(link = log, variance = "mu(1-mu)")
       else fam <- call("quasibinomial", link)
       pnx <- data.frame(p.obs = p, x = heatval)
       u.call <- call("glm", p.obs ~ x, data = pnx, family = fam, weight = tot)
       u <- eval(u.call)
       if(full.robust) {
          r1 <- residuals(u, type = "deviance")
          here.r <- abs(r1) != max(abs(r1))
          u2.call <- call("glm", p.obs ~ x, family = fam, data = pnx[here.r,  ],
             weight = tot[here.r])
          u2 <- eval(u2.call)
          assign("startr", predict(u2, newdata = pnx), frame = 1)
          u3.call <- call("glm", p.obs ~ x, family = fam, data = pnx, start = 
             startr, weight = tot)
          u <- eval(u3.call)
       }
       if(any(abs(u$weights) == Inf)) {
          u$weights[abs(u$weights) == Inf] <- 0    
    # Fudge to ensure calculations continue
       }
       uu <- summary.glm(u, correl = F)
       if(save.resid) {
          resid.dev <- residuals(u, type = "deviance") * reflect.logsurv
          resid <- residuals(u, type = "response") * reflect.logsurv
       }
       b0 <- uu$coef[1, 1] * reflect.logsurv
       b1 <- uu$coef[2, 1] * reflect.logsurv
       cm.est <- NULL    # phat <- inv.fun(b0 + b1 * xvec)
       fit.p <- fitted(u)
       if(link == "logsurv")
          fit.p <- 1 - fit.p
       rob.info <- robust.deviance(fit.p, tot, dead)
       dev.robust <- rob.info[[1]]
       df.robust <- rob.info[[2]]
       dev0 <- uu$deviance
       disp0 <- uu$dispersion
       df0 <- uu$df[2]
    }
    else if(cm.strategy == "abbott") {
       uu <- abbott(cmobs = cm, numcm = numcm, dose = heatval, dead = dead, 
          total = tot, link = link, max.iter = 12, save.resid = save.resid)
       b0 <- uu$coef[1]
       b1 <- uu$coef[2]
       cm.est <- uu$cm
       dev0 <- uu$dev
       df0 <- length(heatval) - 2
       if(df0 > 0)
          disp0 <- dev0/df0
       else disp0 <- NA
       if(save.resid) {
          resid.dev <- uu$resid.dev
          resid <- uu$resid
       }
       dev.robust <- NULL
       df.robust <- NULL
    }
    else stop(paste("Unrecognized cm strategy:", cm.strategy))
    cat("Dev. =", format(round(dev0, 2)), "(df", df0, ")", "  [Disp =", format(
       round(disp0, 3)), "]", "  [Dev =", format(round(dev.robust, 2)), "(df", 
       df.robust, ")]", fill = T)
    if(!is.na(disp0)) {
       if(disp0 < 1)
          het <- 1
       else het <- disp0
    }
    else het <- NA
    if(!is.na(disp0)) {
       if(disp0 > 1)
          df.t <- df0
       else df.t <- Inf
    }
    else df.t <- NA
    v11 <- (uu$cov.un[1, 1]) * het
    v22 <- (uu$cov.un[2, 2]) * het
    v12 <- (uu$cov.un[1, 2]) * het
    ld <- xfun.inv((link.fun(pval) - b0)/b1 + xbar) - offset
    dp <- 2 - floor(log(ld[length(ld)])/log(10))
    if(is.na(dp))
       dp <- 1
    dp <- max(dp, 0)
    selog <- array(, length(pc))
    j <- 0
    if(!is.na(v22))
       for(percent in pval) {
          j <- j + 1
         if(b1/sqrt(v22) > 0.5) {
            ci <- fieller(percent, b0, b1, v11, v12, v22, df.t = df.t, link = 
                           link)
           if(is.null(ci$var))
             ci$var <- NA
             ld[j] <- xfun.inv(ci$xhat + xbar) - offset
             selog[j] <- sqrt(ci$var)
             cat(paste("LT", pc[j], ":", sep = ""), format(round(ld[j], dp)),
                "  ", fill = F)
             if(interval)
                if(ci$upper > ci$lower) {
                   cat("95% C.I. is", format(round(xfun.inv(ci$lower + xbar) - 
                      offset, dp)), " to", format(round(xfun.inv(ci$upper + 
                      xbar) - offset, dp)), fill = T)
                }
                else cat("  * CI could not be calculated (g =", paste(round(ci$
                      g, 5), ") *", sep = ""), fill = T)
          }
          else cat(paste("LT", pc[j], ":",  sep = ""), format(round(ld[j], dp
                )), "   ", fill = T)
       }
    else {
       for(i in seq(along = pc))
          cat(paste("   LT", pc[i], ":", sep = ""), format(round(ld[i], dp)))
       cat("\n")
    }
    cept <- b0 - b1 * xbar
    se0 <- sqrt(v11)
    se1 <- sqrt(v22)
    cept <- b0 - b1 * xbar
    var.cept <- v11 + v22 * xbar^2 - 2 * xbar * v12
    rho.cept.b <- (v12 - xbar * v22)/sqrt(var.cept)/se1
    se <- c(sqrt(var.cept), se1)
    rho <- v12/(se0 * se1)
    cat("   Coeffs:", format(round(c(cept, b1), 4)), "[SE", format(round(se, 3)
       ), " r=", format(round(rho.cept.b, 5)), "]", "\n")
    list(coef = c(b0, b1), selog = selog, vcov = c(v11, v12, v22), df = df0, cm
        = cm.est, dev = dev0, dev.robust = dev.robust, df.robust = df.robust, 
       ld = ld, resid = resid, resid.dev = resid.dev)
}
, comment = "14/12/2004")
"link.function" <-
structure(function(link)
{
  link.options <- c("identity", "log", "logsurv", "logit", "sqrt", "inverse",
                    "probit", "loglog", "cloglog", "help")
  if(link == "help")
    cat("\nOptions are:", paste(link.options, sep = "  "), "\n")
  link.int <- charmatch(link, link.options)
  if(is.na(link.int))
    stop("Invalid link type")
  else if(link.int == 0)
    stop("Ambiguous link type")
  g <- switch(link,
              identity = function(p)
              p,
              log = function(p)
              log(p),
              logsurv = function(p)
              - log(1 - p),
              logit = function(p)
              {
                p <- ifelse(p > 1, NA, ifelse(p < 0, NA, p))
                p1 <- ifelse(p > 1 - 9.9999999999999998e-17, 1 - 
                             9.9999999999999998e-17, ifelse(p < 1.0000000000000001e-16, 
                                                            1.0000000000000001e-16, p))
                log(p1/(1 - p1))
              }
              ,
              sqrt = function(p)
              sqrt(p),
              inverse = function(p)
              1/p,
              probit = qnorm,
              loglog = ,
              cloglog = function(p)
              {
                p <- ifelse(p > 1, NA, ifelse(p < 0, NA, p))
                p1 <- ifelse(p > 1 - 9.9999999999999998e-8, 1 - 
                             9.9999999999999998e-8, ifelse(p < 1.0000000000000001e-8, 
                                                            1.0000000000000001e-8, p))
                log((log(1 - p1)*-1))
              }
              )
  
  g
}
, comment = "16/09/2002")
"link.inverse" <-
structure(function(link = "help")
{
    link.options <- c("identity", "log", "logsurv", "logit", "sqrt", "inverse",
       "probit", "loglog", "cloglog", "help")
    if(link == "help")
       cat("\nOptions are:", paste(link.options, sep = "  "), "\n")
    link.int <- charmatch(link, link.options)
    if(is.na(link.int))
       stop(paste("Invalid link type: \nOptions are:", paste(link.options, 
          collapse = " ")))
    else if(link.int == 0)
       stop("Ambiguous link type")
    f <- switch(link,
       identity = function(x)
       x,
       log = function(x)
       exp(x),
       logsurv = function(x)
       1 - exp( - x),
       logit = function(x)
       {
          z <- exp(ifelse(x > 80, 80, ifelse(x < -80, -80, x)))
          z/(z + 1)
       }
       ,
       sqrt = function(x)
       x^2,
       inverse = function(x)
       1/x,
       probit = pnorm,
       loglog = ,
       cloglog = function(x)
       {
          z <- exp(ifelse(x > 80, 80, ifelse(x < -80, -80, x)))
          1 - exp(.Uminus(z))
       }
       )
    f
}
, comment = "16/10/1994")
"list.mat" <-
structure(function(x)
{
# To convert a list of vectors into a matrix
#
# x must be a named list of "named vectors"
    rownames <- names(x)
    colnames <- names(x[[1]])
    mat <- matrix(nr = length(rownames), nc = length(colnames), dimnames = list(
       rownames, colnames))
    for(i in rownames)
       mat[i,  ] <- unlist(x[[i]])
    mat
}
, comment = "01/02/1997")
"list.to.data.frame" <-
structure(function(x)
{
# 1) Test list element lengths are the same
    lengths <- unlist(lapply(x, length))
    len <- mean(lengths)
    if(all(lengths == len)) {
       attr(x, "class") <- "data.frame"
       attr(x, "row.names") <- 1:len
    }
    else {
       stop("list elements are not of same length")
    }
    x
}
, comment = "19/04/1997")
"logit" <-
structure(function(p)
{
    pres <- (p > 0) & (p < 1)
    p[pres] <- log(p[pres]/(1 - p[pres]))
    n <- length(p[!pres])
    p[!pres] <- rep(NA, n)
    p
}
, comment = "28/03/2001")
"logit.bt" <-
structure(function(x)
{
  p <- exp(x)/(1 + exp(x))
p
}
, comment = "04/10/2001")
"lookup" <-
structure(function(x, y, z = NULL)
{
# Looks up a legend to find the corresponding elements of the input vector
#
# y has all possible values x could take;
# z has all corresponding unabbreviated values of interest
# This function returns those bits of z which correspond to the input values x
# 
# if z is NULL, y must be a matrix of two columns
    if(is.null(z) && dim(y)[2] != 2) stop("z must be specified OR y a matrix\n"
          )
    if(!is.null(dim(y))) {
       z <- y[, 2]
       y <- y[, 1]
    }
    names(z) <- y
    z[x]
}
, comment = "26/01/1999")
"make.df" <-
structure(function(text.file, ...)
{
# Making a dataframe from a text file and using tab separators
    read.table(text.file, T, as.is = T, sep = "\t", row.names = NULL, ...)
}
, comment = "01/04/1997")
"make.factors" <-
structure(function(df, fcols = 1, ordered = F, ...)
{
### To change specified columns into factors.  By default levels are reordered 
###    in alphabetical order.  Keeping that order makes it an ordered factor (ordered = T)
###    which does some strange things in glms and the like, but it's useful for ordering 
###    factors for trellis plotting.
###
###  Without named columns, will not work unless fcols are sequential (col nos. are used:
###    somehow that makes a difference)
###
### Vectors can also be used, in which case setting sorted to T is the same
###   as using factor()
###
    onecol <- is.null(dim(df))    #
    if(onecol) {
       vec <- unfactor(df)
       if(!ordered)
          df <- factor(vec, ...)
       else df <- ordered(vec, labels = unique(vec, ...))
    }
    else {
       if(is.character(fcols))
          fcols <- find.pos(fcols, names(df))
       for(i in fcols) {
          if(!ordered) {
             df[[i]] <- factor(df[[i]], ...)
          }
          else df[[i]] <- ordered(df[[i]], levels = unique(df[[i]]), ...)
       }
    }
    df
}
, comment = "06/01/1998")
"make.id" <-
structure(function(x)
{
# Creates one id value for each row.  Value increases by 1 for each
# element where the value of x is less than for the previous element.
    dx <- c(0, diff(x))
    u <- rep(0, length(x))
    u[dx < 0] <- 1
    cumsum(u) + 1
}
, comment = "07/04/1997")
"make.line.loess" <-
structure(function(xy, lab, label.pos = 0.9, cex = par()$cex, lev.font = 1, lty = 1, lwd
     = par()$lwd, inclusion = "ALL", mark = T, mark.extra = "")
{
    overlap <- function(x, y, xl, yl)
    {
       over <- F
       i <- 1
       while(i <= length(xl)) {
          first.pair.match <- (1:length(xl[[i]]))[(xl[[i]] == x[1]) & yl[[i]] == 
             y[1]]
          if(is.na(diff(x)))
             browser()
          if((diff(x) == 0) & (diff(y) == 0)) {
             if(length(first.pair.match) > 0)
                over <- T
          }
          else {
             second.pair.match <- (1:length(xl[[i]]))[(xl[[i]] == x[2]) & yl[[i
                ]] == y[2]]
             names(first.pair.match) <- rep("f", length(first.pair.match))
             names(second.pair.match) <- rep("s", length(second.pair.match))
             pair.match <- sort(c(first.pair.match, second.pair.match))
             adj.pairs <- (1:(length(pair.match) - 1))[diff(pair.match) == 1]
             adj.pairs <- adj.pairs[!is.na(adj.pairs)]
             if(length(adj.pairs) > 0)
                if((names(pair.match)[adj.pairs[1]] == "f") & (names(pair.match
                   )[adj.pairs[1] + 1] == "s"))
                   over <- T
          }
          i <- i + 1
       }
       over
    }
    assign("overlap", overlap, 0)
    pos <- function(posn, x, y)
    {
       if(posn == 1)
          length(x)
       else {
          dx <- c(0, diff(x))
          dy <- c(0, diff(y))
          lengths <- sqrt(dx^2 + dy^2)
          cum.lengths <- cumsum(lengths)
          full.length <- cum.lengths[length(cum.lengths)]
          main.index <- ((1:length(cum.lengths))[cum.lengths > posn * 
             full.length])[1] - 1
          left.over <- posn * full.length - cum.lengths[main.index]
          main.index + left.over/lengths[main.index + 1]
       }
    }
    assign("pos", pos, 0)
    label.line <- function(label.pos, x, y, lab, cex, i, font)
    {
       if(label.pos >= 0) {
          j <- pos(label.pos, x, y)
          index <- trunc(j)
          if(!is.na(diff(x[index + 0:1])) & !is.na(diff(y[index + 0:1])))
             if(!overlap(x[index + 0:1], y[index + 0:1], x.keep, y.keep)) {
                j <- j - index
                tx <- x[index] + j * (x[index + 1] - x[index])
                ty <- y[index] + j * (y[index + 1] - y[index])
                text(tx, ty, lab, cex = cex, font = font)
                x.keep[[i - 1]] <- x
                y.keep[[i - 1]] <- y
                assign("x.keep", x.keep, 1)
                assign("y.keep", y.keep, 1)
             }
       }
    }
    plot.line <- function(x, y, lty, lwd, inclusion)
    {
       find.point <- function(inclusion, x, y, start)
       {
          p <- pos(inclusion, x, y)
          index <- trunc(p)
          p <- p - index
          tx <- x[index] + p * (x[index + 1] - x[index])
          ty <- y[index] + p * (y[index + 1] - y[index])
          list(tx = tx, ty = ty, index = index + start)
       }
       if(is.character(inclusion)) {
          lines(x, y, lty = lty, lwd = lwd)
          T
       }
       else if(is.null(inclusion))
          F
       else if(inclusion[1] == inclusion[2])
          F
       else {
          if(inclusion[1] > inclusion[2])
             inclusion <- c(inclusion[1], 1, 0, inclusion[2])
          x.save <- x
          y.save <- y
          for(i in 1:(length(inclusion) %/% 2)) {
             x <- x.save
             y <- y.save
             start <- find.point(inclusion[1 + (i - 1) * 2], x, y, T)
             finish <- find.point(inclusion[2 + (i - 1) * 2], x, y, F)
             x <- c(start$tx, x[start$index:finish$index], finish$tx)
             y <- c(start$ty, y[start$index:finish$index], finish$ty)
             lines(x, y, lty = lty, lwd = lwd)
          }
          T
       }
    }
## Main ##
    xy$x <- c(NA, xy$x, NA)
    na <- (1:length(xy$x))[is.na(xy$x)]
    xy$x <- xy$x[ - (na[diff(na) == 1])]
    xy$y <- c(NA, xy$y, NA)
    xy$y <- xy$y[ - (na[diff(na) == 1])]
    na <- (1:length(xy$x))[is.na(xy$x)]
    x.keep <- list()
    y.keep <- list()
    assign("x.keep", x.keep, 1)
    assign("y.keep", y.keep, 1)
    if(length(label.pos) < length(na) - 1)
       label.pos <- c(label.pos, rep(label.pos[1], length(na) - length(
          label.pos)))
    cat("Lev ", lab, mark.extra, " Lines ", max(length(na) - 1, 0), "\n", sep
        = "")
    if(length(na) > 0)
       for(i in 2:length(na)) {
          x <- xy$x[(na[i - 1] + 1):(na[i] - 1)]
          y <- xy$y[(na[i - 1] + 1):(na[i] - 1)]
          old.x <- x
          old.y <- y
          x <- x[!is.na(old.x) & !is.na(old.y)]
          y <- y[!is.na(old.x) & !is.na(old.y)]
          if(length(x) > 0) {
             if(plot.line(x, y, lty, lwd, inclusion[[i - 1]]))
                label.line(label.pos[i - 1], x, y, paste(lab, ifelse(mark, 
                   paste(mark.extra, "-", i - 1, sep = ""), ""), sep = ""), cex,
                   i, font = lev.font)
          }
       }
}
, comment = "03/06/1998")
"mean.lt" <-
structure(function(start.list = ab.soluble, choose = 1, lt = 99, intv = 95, new.order = F,
           leg.beg = NULL, leg.end = 4, insect = "interesting critters", fit = NULL, 
           two.tables = F, borders = F, omit = NULL)
{
  ## Requires LT data in an ab. type list with sublist names such as "total"
  ## referring to LTs at those locations
  ##
  ## LT50s calculated by mono fit: LT99s calculated by line fit
  ## Has to group species to take mean, and then restore to the original
  ##  order of species (otherwise, it's very simple)
  ## The name "species" really refers to location and life stage in 
  ##   some cases: it is what appears on the individual mortality plots
  ##
  ## leg.end will usually be used to remove "Rep_" from hames. If there are more than 
  ##  9 reps in the legend name, it won't work.
  ##
  ## leg.beg is the number of characters to omit from the legend text in determining what
  ##    groups similar trials 
  ## leg.beg by default is the postion of the first blank in the legend name: That is 
  ##   to allow the practice of having trial numbers in that legend: if there's no space
  ##   in the legend, it won't work.
  ablist <- as.character(substitute(start.list))
  leng.name <- nchar(ablist)
  interval <- intv/100
  if(is.character(choose)) {
    choose.i <- (1:length(names(start.list)))[names(start.list) == 
                                              as.character(choose)]
  }
  else (choose.i <- choose)
  ab <- start.list[[choose.i]]
  legs <- as.character(ab$legend)    
### Seems to be necessary for correct class
  if(is.null(leg.beg)) {
### Find the first space in the legend names:
    leg.beg <- NULL
    for(k in 1:length(legs)) {
      leg.vec <- paste(substring(legs[k], 1:nchar(legs[k]), 1:nchar(legs[k]
                                                                    )), sep = "")
      leg.beg[k] <- match(" ", leg.vec)
    }
  }
  spec <- substring(legs, leg.beg + 1, nchar(legs) - leg.end)
  include <- rep(TRUE, length = (length(spec)))    #
### Are there any we wish to exclude? (22/1/2001)
  if(!is.null(omit))
    include[grep(omit, spec)] <- FALSE
  spec <- spec[include]
  uniq.spec <- unique(spec)
  sortspec <- sort(spec)
  if(is.null(fit))
    fit <- ifelse(lt == 50, "monotone", "line")
  if(fit == "line")
    lt.vector <- ab$lt[, paste(lt)]
  else lt.vector <- ab$lt.monotone[, paste(lt)]
  type <- paste(insect, "  [", choose, "] (", fit, " fit)", sep = "")
  lt.vector[lt.vector < 0 | lt.vector == Inf] <- NA    # (22/1/2001)
  lt.vector <- lt.vector[include]    # (22/1/2001)
  lts <- round(as.numeric(lt.vector), 5)
  lt.1 <- matrix(round(lts, 1), ncol = 1, dimnames = list(spec, NULL))
  lt.2 <- NULL    #
### Sort to arrange species together
  for(i in uniq.spec) {
    lt.2 <- c(lt.2, lt.1[dimnames(lt.1)[[1]] == i,  ])
  }
### Change vector into single column matrix
  lt.3 <- matrix(lt.2, nc = 1, dimnames = list(names(lt.2), NULL))    #
### Have vector of grouped lts. Continue finding means, etc.
  av.log.lt <- tapply(log(lts), spec, mean, na.rm = T)
  my.var <- function(x) var(x, na.rm = T)
  var.log.lt.i <- tapply(log(lts), spec, my.var)    #
### Replace any missing variances with zero 
  var.log.lt <- ifelse(is.na(var.log.lt.i), 0, var.log.lt.i)
  sem.log.lt <- tapply(log(lts), spec, sem, na.rm = T)
  reps <- tapply(lts, spec, function(x)
                 length(x[!is.na(x)]))
  deg.pool <- sum(reps[reps > 0] - 1)
  ind.var.free <- var.log.lt * (reps - 1)
  pool.var.free <- sum(ind.var.free)/deg.pool
  delta <- qt(1 - (1 - interval)/2, deg.pool) * sqrt(pool.var.free/reps)
  log.up <- av.log.lt + delta
  log.low <- av.log.lt - delta
  lt.mean <- round(exp(av.log.lt), 1)
  upper <- round(exp(log.up), 1)
  lower <- round(exp(log.low), 1)
  sem <- round(sem.log.lt * lt.mean, 3)    #
### Make matrix of means, etc
  y <- cbind(reps, lt.mean, lower, upper, sem)
  x <- y[uniq.spec,  ]    #
### Put individual LTs into matrix
  rn <- dimnames(lt.3)[[1]]
  urn <- unique(rn)
  cn <- max(table(rn))
  mm <- matrix(rep("---", length(urn) * cn), nc = cn, dimnames = list(urn, 
                                                        paste("Rep", 1:cn, sep = "")))
  for(i in urn) {
### Not all rows have same number of reps
    kk <- lt.2[names(lt.2) == i]
    for(k in 1:length(kk))
      mm[i, k] <- kk[k]
  }
### If original order of plots is not wanted, sort into new order
  if(new.order) {
    mm <- mm[order(dimnames(mm)[[1]]),  ]
    x <- x[order(dimnames(x)[[1]]),  ]
  }
### Output to screen
  if(two.tables) {
    cat(c(paste("Separate LT", lt, "s for ", type, ":", sep = ""), "\n\n"))
    tab.mat(mm)
    cat("\n\n")
    cat(c(paste("Mean LT", lt, "s and ", intv, "% c.i.:", sep = ""), "\n\n")
        )
    tab.mat(x)
    cat("\n\n")
  }
  else {
    one.table <- cbind(mm, x)
    cat(c(paste("Separate LT", lt, "s with mean and ", intv, "% c.i. for ", 
                type, ":", sep = ""), "\n\n"))
    tab.mat(one.table)
  }
  if(borders)
    print.char.matrix(unfactor(as.data.frame(one.table)), col.names = T)
}
, comment = "14/12/2004")
"mean.lt.short" <-
structure(function(lt.vector, lt = 99, intv = 95)
{
# Shortened version of mean.lt()
    interval <- intv/100
    lts <- round(as.numeric(lt.vector), 5)
    lts <- lts[!is.na(lts)]
    reps <- length(lts)    # Change vector into single column matrix
    lt.3 <- matrix(lts, nc = 1)    #
# Have vector of grouped lts. Continue finding means, etc.
    av.log.lt <- mean(log(lts), na.rm = T)
    var.log.lt <- my.var(log(lts))    #
# Replace any missing variances with zero 
    sem.log.lt <- sem(log(lts), na.rm = T)
    deg <- length(lts) - 1
    delta <- qt(1 - (1 - interval)/2, deg) * sqrt(var.log.lt/reps)
    log.up <- av.log.lt + delta
    log.low <- av.log.lt - delta
    lt.mean <- round(exp(av.log.lt), 1)
    upper <- round(exp(log.up), 1)
    lower <- round(exp(log.low), 1)
    sem <- round(sem.log.lt * lt.mean, 3)    #
# Make vector of means, etc
    y <- matrix(c(reps, lt.mean, lower, upper, sem), nr = 1)
    dimnames(y) <- list(NULL, c("reps", "lt.mean", "lower", "upper", " sem"))
        # Put individual LTs into vector
    mm <- matrix(round(lts, 1), nr = 1)
    dimnames(mm) <- list(NULL, paste("Rep", 1:length(mm), sep = ""))    
    # Output to screen
    cat(c(paste("Separate LT", lt, "s ", sep = ""), "\n\n"))
    tab.mat(mm)
    cat("\n\n")
    cat(c(paste("Mean LT", lt, "s and ", intv, "% c.i.:", sep = ""), "\n\n"))
        #if(dim(y)[1]==1)
#x_matrix(x,nc=5,dimnames=dimnames(y))
    tab.mat(y)
    cat("\n\n")
}
, comment = "20/08/1996")
"occurrence" <-
structure(function(x, char = " ", positions = 1)
{
### Finds positions of specified occurrences of a  character (char) in a 
###  character string (x), or vector thereof
                                        #
### Default is to find the first occurrence.  A vector of occurrences can be given
    if(!is.character(x)) x <- as.character(x)
    z <- as.list(x)
    find.gaps <- function(a, b)
    {
       size <- 1:nchar(a)
       size[substring(a, 1:nchar(a), 1:nchar(a)) == b]
    }
    y <- lapply(z, function(w)
    find.gaps(w, char))
    longest <- max(sapply(y, length))
    names(y) <- paste(1:length(y))    #
# if the number of occurrences is not the same for all elenents...
    if(any(diff((sapply(y, length)))) > 0) {
# Fix up odd ones
       short.y <- names(y[sapply(y, length) < longest])
       for(i in short.y) {
          short.y.len <- length(unlist(y[[i]]))
          y[[i]] <- c(unlist(y[[i]]), rep(NA, (longest - short.y.len)))
       }
    }
    if(max(positions) > longest) {
       positions <- positions[!(positions > longest)]
       cat(paste("No more than", longest, "of such character in any element\n")
          )
    }
    t(matrix(unlist(y), byrow = F, nc = length(y)))[, positions]
}
, comment = "26/01/1999")
"p.sunflowers" <-
structure(function(x, y, number, size = 0.125, add = FALSE, rotate = F, pch = 16, ...)
{
## Purpose: Produce a 'sunflower'-Plot
## -------------------------------------------------------------------------
## Arguments: x,y: coordinates;
##    number[i] = number of times for (x[i],y[i])  [may be 0]
##    size: in inches  add : Should add to a previous plot ?
##    rotate: randomly rotate flowers? further args: as for plot(..)
## -------------------------------------------------------------------------
## Authors: Andreas Ruckstuhl, Werner Stahel, Martin Maechler, Tim Hesterberg
## Date   : Aug 89 / Jan 93,   March 92,      Jan, Dec 93,        Jan 93
## Examples: p.sunflowers(x=sort(2*round(rnorm(100))), y=round(rnorm(100),0))
## 16:12, 16 Nov 2006 (NZDT)[[User:Sven|Sven]]  p.sunflowers(rnorm(100),rnorm(100),number=rpois(n=100,lambda=2), 
##                        rotate=T, main="Sunflower plot")
    n <- length(x)
    if(length(y) != n)
       stop("x & y must have same length !")
    if(missing(number)) {
       orderxy <- order(x, y)
       x <- x[orderxy]
       y <- y[orderxy]
       first <- c(T, (x[-1] != x[ - n]) | (y[-1] != y[ - n]))
       x <- x[first]
       y <- y[first]
       number <- diff(c((1:n)[first], n + 1))
    }
    else {
       if(length(number) != n)
          stop("number must have same length as x & y\n!")
       x <- x[number > 0]
       y <- y[number > 0]
       number <- number[number > 0]
    }
    n <- length(x)
    if(!add) {
       axislabels <- match(c("xlab", "ylab"), names(list(...)))
       if(!is.na(axislabels[1]))
          xlab <- list(...)[[axislabels[1]]]
       else xlab <- deparse(substitute(x))
       if(!is.na(axislabels[2]))
          ylab <- list(...)[[axislabels[2]]]
       else ylab <- deparse(substitute(y))
       plot(x, y, xlab = xlab, ylab = ylab, type = "n", ...)
    }
    nequ1 <- number == 1
    if(any(nequ1))
       points(x[nequ1], y[nequ1], pch = pch, csi = size * 1.25)
    if(any(!nequ1))
       points(x[!nequ1], y[!nequ1], pch = pch, csi = size * 0.80000000000000004
          )
    i.multi <- (1:n)[number > 1]
    if(length(i.multi)) {
       ppin <- par()$pin
       pusr <- par()$usr
       xr <- (size * abs(pusr[2] - pusr[1]))/ppin[1]
       yr <- (size * abs(pusr[4] - pusr[3]))/ppin[2]
       i.rep <- rep(i.multi, number[number > 1])
       z <- NULL
       for(i in i.multi)
          z <- c(z, 1:number[i] + if(rotate) runif(1) else 0)
       deg <- (2 * pi * z)/number[i.rep]
       segments(x[i.rep], y[i.rep], x[i.rep] + xr * sin(deg), y[i.rep] + yr * 
          cos(deg))
    }
}
, comment = "14/02/1997")
"pdfn" <-
structure(function(x, ps2pdf = TRUE, cex = .5, adj = 1, side = 1, line = -1, ...)
{
### Purpose: Print file name on a plot
### ----------------------------------------------------------------------
### Modified from: 
### ----------------------------------------------------------------------
### Arguments: ps2pdf -- are we making a postscript name into a PDF name?
### ----------------------------------------------------------------------
### Author: Patrick Connolly, Creation date: 24 Feb 2004, 14:55
  par(new = T)
  par(omi = rep(0,4), mai = rep(0,4), ...)
  if(ps2pdf)
    x <- ppaste(substring(x, 1,nchar(x)-1), "df")
  blank.plot()
  mtext(x, side = side, line = line, cex = cex, adj = adj)
}
, comment = "28/07/2004")
"pid" <-
structure(function()

### current PID
  system("echo $PPID",intern=T)
, comment = "24/05/2001")
"plot.lt" <-
structure(function(lt = 99, datafun = get.leaf, choose = "lbam", fun = function(x)
x, poly = T, poly.limits = list(NULL), poly.keep.x = list(NULL), 
    poly.plot.limits = list(NULL), deg = 2, splin = F, wide.legend = 1, 
    high.legend = 1, expand.y = 0, print.statistics = T, x.limits = NULL, 
    y.limits = NULL, predict.x = NULL, confidence = 0.95, compare = NULL, 
    fit.robust = F, plot.ci = F, plotit = T, plot.means = T, plot.points = F, 
    plot.single.sem = F, plot.groups.sem = T, legend.sem = T, legend.linespace
     = 1.25, errors = "aov", include = NULL, parallel = NULL, mkh = 0.08, 
    datestamp = T, prefix = "", prefix.y = "", legend.header = "", legend.note
     = "Limits shown are one SE\neither side of the mean", bars.pretext = 
    "2 SE", na.means = T, wts = NULL, style = list(lwd = 1, plotch = c(0, 1, 2,
    5, 3, 4, 16, 18, 6:15), cex.labels = 1, cex.title = 1.15, mai.xtra = c(0.25,
    0.5, 0.25, 0.5)), mtext.line = -1)
{
### Means, for each temperature in each list item, are calculated and plotted
### An overall SD is calculated for each set of list items, 
### as identified in groups.
### Set na.means to F to omit plotting of means when data for a mean relies
### partly on NAs
### Examples
### plot.lt(lt=50,datafun=get.air.CA.lt,poly=F, poly.limits=list(c(32.5,40)), 
### splin=T,wide.legend=0.67)
### plot.lt(lt=50,datafun=get.co2.o2.lt,poly=c(T,F),deg=1, splin=F,wide.legend=0.67)
### plot.lt(lt=99,datafun=get.co2.o2.lt,poly=c(T,F),deg=2, splin=F,wide.legend=0.67)
### plot.lt(lt=50,datafun=get.pretreat.lt,poly=T,deg=2, splin=F,wide.legend=0.67)
#
### aov.errors = T causes the within x mean square to be used for SEs etc.
#
### lt= : gives lt % to be printed on the y-axis label
#
### datafun: This function collects up the data, labelling information etc., 
### and delivers it in a standard form to plot.lt.
#
### fun: Transformation function for the y-axis.  Usually identity or log.
#
### poly: T if a line or polynomial is required.
#
### poly.limits: used in connection with splin=T when a specific polynomial
### (usually a quadratic) is required over the part of the range specified 
### by poly.limits, with a spline for the remainder.
### 
### deg: degree for polynomial(s)
#
### Note: Parameters poly, poly.limits and deg are expanded, if necessary, 
### into a vector or (for poly.limits) a list.
### wide.legend, high.legend: point at which to start printing first legend item
### Specify as a fraction of the x- or y-distance.
### expand.y: e.g. 25% will increase the upper y-limit to give 25% extra space 
### for legend etc.
#
### print.statistics: whether to print out coeffs, ses etc of fitted polynomials
### plot.means, plot.points: means and/or points
### plot.single.sem, plot.groups.sem: strategy for calculating sem
### errors: strategy for calculation of error mean square.
###  "aov" calculates the mean square from the "within x" sum of squares.
###  Alternatives are lack.of.fit (deviations from the fitted polynomial)
###  and total (aov and lack.of.fit combined).
### include: This is a vector of booleans; T where a list element is included.
#
#
    par(new = F)
    options(width = 180)
    var.new <- function(x)
    {
       pres <- !is.na(x)
       var(x[pres])
    }
    date.txt <- unix("date '+DATE: %d/%m/%y %H:%Mh'")
    docs <- paste(unix("pwd"), as.character(as.name(match.call())), date.txt, 
       collapse = "")
    print(docs)
    if(!plotit) {
       if(missing(plot.means))
          plot.means <- F
       if(missing(plot.points))
          plot.points <- F
    }
    plotch <- style$plotch
    lwd <- style$lwd
    cex.title <- style$cex.title
    cex.labels <- style$cex.labels
    mai.xtra <- style$mai.xtra
    if(!is.null(confidence) & !is.null(compare)) {
       cat("\nValues set both for ci's & for comparisons.", 
          "\nCode for both is not implemented at this point.", 
          "\nWill do comparisons only.\n")
       confidence <- NULL
    }
    if(plot.points | plot.means | plotit)
       plot.some <- T
    else plot.some <- F
    xtra <- numeric(0)
    linetype.len <- 0
    oldpar <- par()
    on.exit(par(oldpar))
    par(mai = par()$mai + mai.xtra)
    u <- datafun(lt = lt, choice = choose)
    leg <- u$leg
    ltraw.list <- u$lt
    xval.list <- u$xval
    xlab <- u$xlab
    xaxlab <- u$xaxlab
    yaxlab <- u$yaxlab
    ylab <- u$ylab
    groups <- u$groups
    maint <- u$maint
    if(is.list(maint))
       maint <- paste(maint[["prefix"]], " LT~v~c.8~.", lt, "~h0~c1~.",  , " ",
          maint[["main"]], sep = "")
    else maint <- paste(prefix, maint)
    mean.list <- lapply(xval.list, unique)    
### Set up structure that has the right shape
    num.list <- mean.list
    uniqx.list <- mean.list
    nlist <- length(xval.list)
    if(is.numeric(include)) {
       tmp <- rep(F, nlist)
       tmp[include] <- T
       include <- tmp
    }
    else if(is.null(include))
       include <- rep(T, nlist)
    else if(length(include) < nlist)
       include <- c(include, rep(F, nlist - length(include)))
    include.parallel <- rep(F, nlist)
    if(!is.null(parallel)) {
       include.parallel[parallel] <- T
       xval.parallel <- list()
       pres.parallel <- list()
       lt.parallel <- list()
       n.parallel <- sum(include.parallel)
       num.parallel <- rep(0, n.parallel)
       wts.parallel <- rep(0, n.parallel)
       df.parallel <- rep(0, n.parallel)
       leg.parallel <- leg[include.parallel]
    }
    if(is.null(groups))
       groups <- as.list((1:nlist)[include])
    ngroups <- length(groups)
    if(nlist > 1 & length(deg) == 1)
       deg.pol <- rep(deg, nlist)
    else deg.pol <- deg
    if(nlist > 1 & length(poly) == 1)
       poly <- rep(poly, nlist)
    if(nlist > 1 & length(splin) == 1)
       splin <- rep(splin, nlist)
    if(!is.list(poly.limits))
       poly.limits <- list(poly.limits)
    if(!is.list(poly.keep.x))
       poly.keep.x <- list(poly.keep.x)
    if(nlist > 1 & length(poly.limits) == 1)
       poly.limits <- rep(poly.limits, nlist)
    if(nlist > 1 & length(poly.keep.x) == 1)
       poly.keep <- rep(poly.keep.x, nlist)
    if(!is.list(poly.plot.limits))
       poly.plot.limits <- list(poly.plot.limits)
    if(nlist > 1 & length(poly.plot.limits) == 1)
       poly.plot.limits <- rep(poly.plot.limits, nlist)
    if(!is.null(wts))
       if(nlist > 1 & length(wts) == 1)
          wts <- rep(wts, nlist)
    xlab <- u$xlab
    if(sum(include) > length(plotch))
       plotch <- c(plotch, letters)
    vm.aov <- array(, nlist)
    vm.other <- array(, nlist)
    df.other <- array(, nlist)
    numdf <- array(, nlist)
    nummin <- array(, nlist)
    nummax <- array(, nlist)
    lt.list <- ltraw.list
    for(i in 1:nlist)
       lt.list[[i]] <- fun(ltraw.list[[i]])
    mat.range <- matrix(unlist(lapply(ltraw.list, range, na.rm = T)), nrow = 2)
    unlist.raw <- unlist(ltraw.list)
    yrange <- range(mat.range[, include], na.rm = T)
    log.y <- F
    if(all(fun(exp(1:4)) == 1:4)) {
       log.y <- T
       mat.range <- matrix(unlist(lapply(ltraw.list, function(x, na.rm = T)
       range(x[x > 0]), na.rm = T)), nrow = 2)
       yrange[1] <- min(mat.range, na.rm = T)
       yrange[1] <- min(unlist.raw[unlist.raw > 0], na.rm = T)
    }
    if(is.null(y.limits)) {
       funrange <- fun(yrange)
       y.limits <- yrange
    }
    else funrange <- fun(y.limits)
    funrange[2] <- funrange[2] + diff(funrange) * expand.y    
### Often set expand.y = 0.05 or 0.1, to allow room for legend
    if(is.null(yaxlab)) {
       ylabels <- pretty(y.limits)
       if(all(fun(exp(1:4)) == 1:4)) {
          splity <- sqrt(y.limits[1] * y.limits[2])
          ylabels2 <- pretty(c(splity, max(y.limits)), 4)
          ylabels1 <- pretty(c(min(y.limits), splity), 4)
          ylabels <- sort(unique(c(ylabels1, ylabels2)))
          if(ylabels[1] == 0)
             ylabels[1] <- mean(ylabels[1:2])
       }
    }
    else ylabels <- yaxlab
    ncharwid <- max(nchar(paste(ylabels)))
    ylabadd <- (ncharwid - 1.5) * 0.25
    ytitladd <- (1.25 * ncharwid - 2) * 0.125
    if(plot.some) {
       if(is.null(x.limits))
          x.limits <- range(unlist(xval.list), na.rm = T)
       plot(x.limits, funrange, xlim = x.limits, type = "n", xlab = "", xaxt = 
          "n", ylab = "", yaxt = "n")
       if(is.null(xaxlab))
          xaxlab <- pretty(x.limits)
       axis(1, at = xaxlab)
       axis(2, at = fun(ylabels), labels = paste(ylabels), mgp = c(3 + ytitladd,
          1 + ylabadd, 0))
       chh <- par()$cxy[2]
       chw <- par()$cxy[1]
       uxy <- par()$usr
    }
    outvals <- vector("list", sum(include))
    names(outvals) <- names(lt.list)[include]
    i.plot <- 0
    j.parallel <- 0
    for(i in 1:nlist)
       if(include[i]) {
          u.x <- NULL
          bt.y <- NULL
          i.plot <- i.plot + 1
          deg.i <- deg.pol[i]
          pres <- !is.na(lt.list[[i]])
          if(all(!pres))
             next
          temps <- xval.list[[i]][pres]
          ltval <- lt.list[[i]][pres]
          if(plot.points)
             points(temps, ltval, pch = plotch[i.plot], mkh = 0.75 * mkh, lwd
                 = lwd)
          vv <- tapply(ltval, list(temps), var)
          my <- tapply(ltval, list(temps), mean)
          tab.temps <- table(temps)
          utemps <- as.numeric(names(tab.temps))
          num <- as.numeric(tab.temps)
          num.list[[i]] <- num
          uniqx.list[[i]] <- utemps
          if(!na.means) {
             my.test.na <- tapply(lt.list[[i]], list(xval.list[[i]]), function(
                x)
             any(is.na(x)))
             utemps.all <- unique(xval.list[[i]])
             utemps.na <- utemps.all[my.test.na]
             if(length(utemps.na) > 0) {
                u.match <- match(utemps.na, utemps, nomatch = 0)
                if(any(u.match > 0))
                   my[u.match] <- NA
             }
             mean.list[[i]] <- my
          }
          if(plot.means)
             points(utemps, my, pch = plotch[i.plot], mkh = mkh, lwd = 2)
          nummin[i] <- min(num[!is.na(my)])
          nummax[i] <- max(num[!is.na(my)])
          sd <- sqrt(vv)
          sem <- sd/sqrt(num)
          df.aov.rss <- sum(num - 1)
          numdf[i] <- df.aov.rss
          ms.aov <- sum(vv * (num - 1), na.rm = T)/df.aov.rss
          vm.aov[i] <- ms.aov
          sd.aov <- sqrt(ms.aov)
          cat("\n", leg[i], "  ", date(), fill = T)
          av.se <- data.frame(rbind(format(round(my, 2)), format(round(sem, 2)),
             num))
          row.names(av.se) <- c("Means are:", "sem's are:", "Nos.")
          names(av.se) <- paste(utemps)
          print(av.se)
          cat("sds are", format(round(sd, 2)))
          if(df.aov.rss > 0)
             cat("  pooled:", format(round(sd.aov, 3)), "  df =", df.aov.rss, 
                fill = T)
          if(log.y) {
             btmeans <- exp(my)
             btsem <- btmeans * sem
             bt.se <- data.frame(rbind(format(round(btmeans, 1)), format(round(
                btsem, 2))))
             row.names(bt.se) <- c("BT means:", "Appr sem:")
             names(bt.se) <- paste(utemps)
             print(bt.se)
          }
          cat("\n", fill = T)
          rtemps <- range(temps)
          utemps <- uniqx.list[[i]]
          poly.i <- poly[i]
          if(poly.i)
             linetype.len <- 3.5
          splin.i <- splin[i]
          if(poly.i & length(utemps) <= deg.i) {
             if(length(utemps) > 1)
                cat("*** Insufficient points for polynomial  of degree", deg.i,
                   fill = T)
             poly.i <- F
          }
          if(splin.i & length(utemps) < 4) {
             if(length(utemps) > 1)
                cat(
                   "*** Insufficient points for spline -- at least 4 are required",
                   fill = T)
             splin.i <- F
          }
          poly.lim <- poly.limits[[i]]
          poly.keep <- poly.keep.x[[i]]
          if(is.null(poly.lim))
             poly.lim <- rtemps
          else if(any(is.na(match(poly.lim, utemps))))
             cat(
                "One or both endpoints for the polynomial fit do not match actual data values",
                fill = T)
          if(length(poly.lim) == 1 & is.null(poly.keep)) {
             cat("Only one limit has been given; cannot fit quadratic", fill = 
                T)
             poly.lim <- rep(poly.lim, 2)
          }
          if(is.null(poly.keep)) {
             keep <- (utemps >= poly.lim[1] & utemps <= poly.lim[2])
             poly.keep <- utemps[keep]
          }
          else keep <- as.logical(match(utemps, poly.keep, nomatch = F))
          nu <- (1:length(utemps))[keep]
          y.means <- my[nu]
          x.means <- utemps[nu]
          yfit <- my
          use.quad <- as.logical(match(temps, poly.keep, nomatch = F))
          x.quad <- temps[use.quad]
          y.quad <- ltval[use.quad]
          num.quad <- num[nu]
          df.quad <- sum(num.quad - 1)
          if(df.quad == 0)
             ms.quad <- 0
          else ms.quad <- sum(vv[nu] * (num.quad - 1), na.rm = T)/df.quad
          ems <- ms.quad
          df.t <- df.quad
          if(poly.i) {
             poly.legend <- "Polynomial"
             if(fit.robust)
                poly.legend <- "Polynomial (robust fit)"
             if(!is.null(poly.keep.x[[i]]))
                cat(poly.legend, "of degree", deg.i, "through points", 
                   poly.keep, fill = T)
             else cat(poly.legend, "of degree", deg.i, "from points", poly.lim[
                   1], "to", poly.lim[2], fill = T)
             uu <- poly.fit(x.quad, y.quad, num.quad, deg.i, ms.quad, df.quad, 
                errors, print.statistics = print.statistics, predict.x = 
                predict.x, fit.robust = fit.robust, wts = wts)
             ypred.se <- uu$pred$se.fit
             df.t <- uu$df.ms
             xtra <- uu$xtra
             ems <- uu$ems
             vm.other[i] <- ems
             df.other[i] <- df.t
             df.t0 <- uu$pred$df
             ems0 <- uu$pred$ms
             if(!is.null(df.t0))
                if(df.t != df.t0)
                   cat("\n ******* df.t =", df.t, "   df.t0 =", df.t0, "\n")
             if(!is.null(ems0)) if(ems != ems0) {
                   cat("****** Warning ******\n")
                   cat("ems =", ems, "   ems0 =", ems0, "\n\n")
                }
### vanilla ms; depends on errors
             b <- uu$b
             if(include.parallel[i]) {
                j.parallel <- j.parallel + 1
                xval.parallel[[j.parallel]] <- x.quad
                lt.parallel[[j.parallel]] <- y.quad
                num.parallel[j.parallel] <- sum(num[nu])
                wts.parallel[j.parallel] <- 1/ems
                df.parallel[j.parallel] <- df.t
             }
             if(!is.null(predict.x)) {
                ypred <- uu$pred$fit
                u.x <- predict.x
                if(!is.null(confidence)) {
                   alpha <- 1 - confidence
                   c.txt <- paste(round(confidence * 100))
                   c.txt1 <- NULL
                   t.stat <- qt(1 - alpha/2, df.t)
                }
                else if(!is.null(compare)) {
                   alpha <- 1 - compare
                   t.stat <- qt(1 - alpha/2, df.t)/sqrt(2)
                   c.txt <- format(round((2 * pt(t.stat, df.t) - 1) * 100, 1))
                   c.txt1 <- paste(round((1 - compare) * 100))
                }
                ci.low <- ypred - ypred.se * t.stat
                ci.high <- ypred + ypred.se * t.stat
                if(log.y) {
                   bt.y <- exp(ypred)
                   bt.sem <- bt.y * ypred.se
                   xx <- data.frame(rbind(format(round(bt.y, 1)), format(signif(
                      exp(ci.low), 3)), format(signif(exp(ci.high), 3)), format(
                      signif(bt.sem, 2))))
                   dimnames(xx) <- list(c("BT preds:", paste(c.txt, "pc low:", 
                      sep = ""), paste(c.txt, "pc high:", sep = ""), 
                      "Approx sem:"), paste(u.x))
                   print(xx)
                   if(!is.null(c.txt1))
                      cat("\nNon-overlap of ci's is equivalent to a test for", 
                         "\nno difference at the", paste(c.txt1, "pc", sep = ""
                         ), "level.\n")
                }
                else {
                   cat("\nTemps   :", format(round(u.x, 1)), fill = T)
                   cat("Pred vals:", format(round(ypred, 1)), fill = T)
                   cat("Appr. sem:", format(round(ypred.se, 2)), fill = T)
                   bt.y <- ypred
                }
             }
             sem[nu] <- sqrt(ems/num.quad)
             if(length(nu) < length(utemps) & errors == "aov") {
                ms.other <- sum(vv[ - nu] * (num[ - nu] - 1), na.rm = T)/sum(
                   num[ - nu] - 1)
                sem[ - nu] <- sqrt(ms.other/num[ - nu])
             }
          }
          if(plot.single.sem)
             errorbars(utemps, my, sem, 0.25 * chw)
          if(poly.i) {
             if(is.null(poly.plot.limits[[i]]))
                xpoints <- pretty(utemps[nu], 50)
             else xpoints <- pretty(poly.plot.limits[[i]], 50)
             yfit[nu] <- rep(b[1], length(nu))
             yhat <- rep(b[1], length(xpoints))
          }
          if(poly.i)
             if(deg.i > 0)
                for(k in 2:(deg.i + 1)) {
                   yfit[nu] <- yfit[nu] + b[k] * utemps[nu]^(k - 1)
                   yhat <- yhat + b[k] * xpoints^(k - 1)
                }
          if(plot.some) {
             if(poly.i & !splin.i)
                lines(xpoints, yhat, lty = i.plot, lwd = lwd)
             if(plot.ci) {
                lines(spline(u.x, ci.low), lty = i.plot)
                lines(spline(u.x, ci.high), lty = i.plot)
             }
          }
          if(splin.i) {
### spline; perhaps polynomial through points between poly.limits
             if(diff(rtemps) > diff(range(utemps[nu]))) cat(
                   "Extend polynomial to the whole range of x-values as a spline curve.",
                   fill = T)
             if(length(utemps) >= 3) {
                uus <- spline(utemps, yfit)
                xpoints <- uus$x
                yhat <- uus$y
                if(length(xtra) > 3) {
                   xtrafit <- approx(uus$x, uus$y, xout = xtra)$y
                   if(log.y)
                      xtrafit <- exp(xtrafit)
                   names(xtrafit) <- paste(xtra)
                   cat("\n Predictions from spline fit:\n")
                   print(round(xtrafit, 2))
                }
                if(plot.some)
                   lines(xpoints, yhat, lty = i.plot)
             }
          }
          if(!is.null(u.x) & !is.null(bt.y))
             outvals[[i.plot]] <- cbind(u.x, bt.y)
       }
### Parallel curve analysis, if requested
### At present, lines are the only option (no plots)
    if(!is.null(parallel)) {
       cat("\nParallel line or curve analysis", fill = T)
       cat("Factors are:", leg.parallel, fill = T)
       deg.here <- max(deg.pol[include.parallel])
       x.all <- unlist(xval.parallel)
       y.all <- unlist(lt.parallel)
       wts.all <- rep(wts.parallel, num.parallel)
       id.parallel <- rep(1:n.parallel, num.parallel)
       f.parallel <- factor(id.parallel, labels = leg.parallel)
       u.parallel <- lm(lt ~ C(stage, treatment) + temp, data = list(lt = y.all,
          temp = x.all, stage = f.parallel, wts = wts.all, deg.here = deg.here),
          weights = wts)
       u.one <- lm(lt ~ temp, data = list(lt = y.all, temp = x.all, stage = 
          f.parallel, wts = wts.all, deg.here = deg.here), weights = wts)    
       print(summary(u.parallel, correl = F))
       print(anova(u.one, u.parallel), test = "F")
    }
    semin <- array(, ngroups)
    semax <- array(, ngroups)
    groupsd <- array(, nlist)
    for(k in 1:ngroups) {
       sublist <- groups[[k]]    ### N.B. May have >1 list item per group
       leg.k <- paste(leg[sublist], collapse = "; ")
       if(!any(include[sublist])) {
          cat("** List nos.", sublist, "have been specified", 
             "\nOne or more of these is not in the include list", fill = T)
          break
       }
       nmin <- min(nummin[sublist])
       nmax <- max(nummax[sublist])
       sd.aov <- sqrt(sum(vm.aov[sublist] * numdf[sublist], na.rm = T)/sum(
          numdf[sublist]))
       sd.other <- sqrt(sum(vm.other[sublist] * df.other[sublist], na.rm = T)/
          sum(df.other[sublist]))
       if(is.na(sd.other))
          next
       if(errors == "aov" & sum(numdf[sublist]) == 0 & poly.i)
          errors.here <- "lack.of.fit"
       else errors.here <- errors
       sd.points <- switch(errors.here,
          aov = sd.aov,
          lack.of.fit = ,
          total = sd.other)
       groupsd[k] <- sd.points
       if(length(sublist) > 1) {
          cat("\nGroup together lists", sublist, fill = T)
          cat("   Overall pooled sd =", format(round(sd.points, 3)), fill = T)
       }
       semax[k] <- sd.points * sqrt(1/nmin)
       semin[k] <- sd.points * sqrt(1/nmax)
       cat("\n", leg.k, ":")
       if(nmax > nmin)
          cat("sem = Max:", format(round(semax[k], 3)), "    Min:", format(
             round(semin[k], 3)), fill = T)
       else cat("sem =", format(round(semax[k], 3)), fill = T)
    }
    if(plot.some) {
       if(plot.groups.sem)
          if(ngroups > 1) {
             se.tmp <- semax
             se.tmp[is.na(se.tmp)] <- 0.55 * chh
             se.last <- se.tmp[ngroups]
             se.two <- se.tmp + c(0, se.tmp[ - ngroups]) + 0.4 * chh
             if(length(legend.linespace) == 1) legend.linespace <- se.two/chh
        
### Can get spacing from parameter legend.linespace by making this a vector
          }
       x.legend <- uxy[1] + diff(uxy[1:2]) * wide.legend + chw
       if(wide.legend == 1)
          x.legend <- uxy[2] - linetype.len * chw - max(nchar(leg)) * chw
       y.legend <- uxy[3] + diff(uxy[3:4]) * high.legend - chh
       if(high.legend == 1) {
          y.legend <- uxy[4] - 0.5 * chh
       }
       if(high.legend == 0)
          y.legend <- uxy[1] + se.last + sum(se.two)
       xpos <- rep(x.legend, length(leg))
       ypos <- y.legend - cumsum(legend.linespace) * chh
    }
    j0 <- 0
    if(plot.groups.sem)
       for(k in 1:ngroups) {
          sd.here <- groupsd[k]
          sublist <- groups[[k]]
          if(legend.sem) {
             j0 <- j0 + 1
             sem.max <- semax[k]
             sem.min <- semin[k]
             errorbars(xpos[j0] - 1.25 * chw, ypos[j0], sem.max, eps = chw/2)
             pretext.pos <- xpos[j0] - 2.5 * chw
             if(!is.na(sem.min) & sem.min < 0.75 * sem.max) {
                errorbars(xpos[j0] - 3 * chw, ypos[j0], sem.min, eps = chw/2)
                pretext.pos <- xpos[j0] - 4.25 * chw
             }
             if(j0 == 1)
                text(pretext.pos, ypos[j0], bars.pretext, adj = 1)
          }
          for(jk in sublist) {
             mv <- mean.list[[jk]]
             num <- num.list[[jk]]
             sem <- sd.here/sqrt(num)
             uniqx <- uniqx.list[[jk]]
             if(!legend.sem)
                errorbars(uniqx, mv, sem, eps = chw/2)
          }
       }
    if(!plot.some)
       return()
    note.pos <- ypos[j0] - 1 * chh
    if(plot.groups.sem)
       note.pos <- note.pos - semax[length(semax)]
    if(nchar(legend.note) > 0)
       text(xpos[1], note.pos, legend.note, adj = 0, cex = 0.75)
    oldmgp <- par(mgp = c(2.75 + ytitladd, 0.5, 0))$oldmgp
    if(names(dev.cur()) == "postscript")
       mixed.mtext(texts = paste(prefix.y, "LT~v~c.8~.", lt, "~h0~c1~. ", ylab,
          sep = ""), side = 2, line = 2.5 + ytitladd, adj = 0.5, cex = 
          cex.labels)
    else mtext(text = paste(prefix.y, "LT", lt, " ", ylab, sep = ""), side = 2,
          line = 2.5 + ytitladd, adj = 0.5, cex = cex.labels)
    par()$oldmgp
    if(length(leg) < nlist) {
       cat("Insufficient legends", fill = T)
       leg <- c(leg, rep("", nlist - length(leg)))
    }
    else if(length(leg) > nlist)
       cat("NB: There are superfluous legends", fill = T)
    if(length(leg) < nlist)
       cat("Insufficient legends", fill = T)
    j0 <- 0
    if(sum(include) > 1) {
       for(i in 1:nlist)
          if(include[i]) {
             j0 <- j0 + 1
             points(xpos[j0], ypos[j0], pch = plotch[j0], cex = 0.9, mkh = mkh)
             if(poly[i])
                lines(c(xpos[j0] + 1.5 * chw, xpos[j0] + (linetype.len + 1.5) * 
                   chw), c(ypos[j0], ypos[j0]), lty = j0)
             if(names(dev.cur()) == "postscript")
                mixed.text(xpos[j0] + (linetype.len + 2) * chw, ypos[j0], leg[i
                   ], adj = 0, cex = 0.8)
             else text(xpos[j0] + (linetype.len + 2) * chw, ypos[j0], leg[i], 
                   adj = 0)
          }
    }
    if(is.null(xlab)) {
       xlab <- ""
       cat("No setting was provided for xlab\n")
    }
    if(names(dev.cur()) == "postscript") {
       mixed.mtext(texts = paste(xlab, sep = ""), side = 1, line = 2.25, adj = 
          0.5, cex = cex.labels)
       if(maint != "")
          mixed.mtext(texts = maint, side = 3, line = 1.75, adj = 0.5, cex = 
             cex.title)
    }
    else {
       mtext(paste(xlab, sep = ""), 1, line = 2.25, cex = cex.labels)
       mtext(text = maint, side = 3, line = 1.75, adj = 0.5, cex = cex.title)
    }
    oldcex <- par(cex = 0.4)
    r.txt <- unix("date +%d/%m/%y'  '%H:%M")
    l.txt <- paste(unix("pwd"), as.character(as.name(match.call())), collapse
        = "")    
### docs <- paste(unix("pwd"), as.character(as.name(match.call())), 
### date.txt, collapse = "")
    if(datestamp) {
       mtext(r.txt, side = 1, adj = 1, outer = T, line = mtext.line)
       mtext(l.txt, side = 1, adj = 0, outer = T, line = mtext.line)
    }
    options(width = 80)    # docs
    invisible()
}
, comment = "08/10/1995")
"plot.resid" <-
structure(function(xx)
{
  ## Purpose: Plots fitted values against the residuals for aovs, lms, etc
  ## ----------------------------------------------------------------------
  ## Modified from: 
  ## ----------------------------------------------------------------------
  ## Arguments: xx is an aov, glm, lm type object 
  ## ----------------------------------------------------------------------
  ## Author: Patrick Connolly, Creation date: 26 Aug 2005, 16:14

with(xx, plot(fitted.values, residuals))

}
, comment = "26/08/2005")
"pool.adj" <-
structure(function(x, r, n, phat, cm, cm.strategy = "adjust.later", cm.code = NULL, 
           cm.allcodes = NULL, plimits = c(0.0025, 0.9995), plotit = "loess",
         link = "loglog", xfun = function(x) x, legend = "", x.cm = NULL,
         dead.cm = NULL, tot.cm = NULL, xtit = "Time", ytit = NULL,
         mkh = 0.025, extrap.low = 0.25, extrap.high = 0.25, span = 1,
         deg = 1, lo.lty = 2, lwd = 1, n.lo = 50, title.line = 0.25)
{
### pool.adj is called both by fitconf and by flyplot
###
### extrap.low (extrap.high) is fraction
### of range allowed for extrapolation below (above)
### These are halved if there are just two points
  if(!is.null(plotit)) {
    plotit[plotit == "loess"] <- "mono.loess"
    plotit[plotit == "mono"] <- "mono.loess"
    show.curve <- as.logical(match(c("mono.line", "mono.loess"), plotit, 
                                   nomatch = 0))
  }
  else show.curve <- rep(F, 2)
  if(!is.null(phat)) {
    phat.strategy <- names(phat)
    new.lt <- T
    lt <- array(NA, length(phat))
    nam.lt <- names(phat)
    ab <- vector("list", length(phat))
  }
  else {
    lt <- NULL
    ab <- NULL
    new.lt <- F
    phat.strategy <- ""
  }
  plot.some <- any(show.curve)
  if(all(xfun(exp(1:8)) == 1:8)) {
    xfun.inv <- exp
    takelog <- T
  }
  else {
    xfun.inv <- function(x)
      x
    takelog <- F
  }
  if(any(diff(x)) < 0)
    stop("** Monotone fitting requires that data is ordered by x-values **")
  x0 <- x
  r0 <- r
  n0 <- n
  p0 <- r0/n0
  if(any(diff(x) == 0)) {
    r <- tapply(r, x, sum)
    n <- tapply(n, x, sum)
    x <- as.numeric(names(r))
  }
  if(takelog)
    if(any(x <= 0)) {
      x.0 <- x > 0
      x <- x[x.0]
      r <- r[x.0]
      n <- n[x.0]
    }
  g <- link.function(link)
  nn <- length(n)
  p <- r/n
  if(is.null(cm)) {
    cat("\nNo control mortality was supplied.\n")
    cat("\nFor monotone estimation set cm = 0\n")
  }
  if(cm.strategy == "adjust.later" & !is.null(phat))
    ptarg <- cm + ((1 - cm) * phat)/100
  id <- 1:nn
  repeat {
    i <- 2
    while(i <= nn && p[id[i]] >= p[id[i - 1]]) i <- i + 1
    if(i <= nn) {
      x[id[i - 1]] <- x[id[i]] <- (n[id[i - 1]] * x[id[i - 1]] + n[id[i]] * 
                                   x[id[i]])/(n[id[i - 1]] + n[id[i]])
      r[id[i - 1]] <- r[id[i]] <- r[id[i]] + r[id[i - 1]]
      n[id[i - 1]] <- n[id[i]] <- n[id[i]] + n[id[i - 1]]
      p[id[i - 1]] <- p[id[i]] <- r[id[i]]/n[id[i]]
      idi <- id[i]
      while(i <= nn && id[i] == idi) {
        id[i] <- id[i - 1]
        i <- i + 1
      }
    }
    else break
  }
  n1 <- max((1:nn)[p == 0])
  if(!is.na(n1))
    id <- id[id >= n1]
  use <- unique(id)
  ux <- x[use]
  ux.tran <- xfun(ux)
  if(!is.null(phat))
    ptarg.interp <- ptarg
  r.use <- r[use]
  n.use <- n[use]
  p.use <- r.use/n.use
  if(cm.strategy == "abbott") {
    here.use <- p.use >= cm
    use <- use[here.use]
    ux <- ux[here.use]
    ux.tran <- xfun(ux)
    p.use <- (p.use[here.use] - cm)/(1 - cm)
  }
  xx <- cbind(r[use], (n - r)[use])
  p.max <- max(p.use)
  p.min <- min(p.use)
  done.loess <- F
  show.line <- show.curve[1]
  show.loess <- show.curve[2]
  nx <- sum(p.use < 1)
  n01 <- sum(p.use > 0 & p.use < 1)
  phat.strategy[phat.strategy == "mono"] <- "loess"
  phat.strategy[phat.strategy == "mono.loess"] <- "loess"
  calc.loess <- any(as.logical(match("loess", phat.strategy, nomatch = 0)))
  if(length(ux) >= 4 & nx >= 3 & (show.loess | calc.loess) & n01 >= 2) {
    gp <- g(p.use)
    df.lo <- data.frame(y = p.use, x = ux.tran, n = n.use)
    browser()
    u <- switch(link,
                identity = gam(y ~ lo(x, span = span, degree = deg), family = 
                  binomial("identity"), data = df.lo, weight = n), logsurv = ,
                log = gam(y ~ lo(x), family = binomial("log"), data = df.lo,
                  weight = n, span = span, degree = deg),
                logit = gam(y ~ lo(x, span = span, degree = deg),
                  family = binomial("logit"), data = df.lo, weight = n),
                sqrt = gam(y ~ lo(x, span = span, degree = deg),
                  family = binomial("sqrt"), data = df.lo, weight = n),
                inverse = gam(y ~ lo(x, span = span, degree = deg),
                  family = binomial("inverse"), data = df.lo, weight = n),
                probit = gam(y ~ lo(x, span = span, degree = deg),
                  family = binomial("probit"), data = df.lo, weight = n),
                cloglog = ,
                loglog = gam(y ~ lo(x, span = span, degree = deg),
                  family = binomial("cloglog"), data = df.lo, weight = n))
    df.new <- data.frame(x = pretty(ux.tran, n.lo))
    hat.u <- predict(u)
    u.lo <- loess(y ~ x, data = list(y = hat.u, x = ux.tran), span = span, 
                  deg = deg, span = span)    # If no. of points is 4 and span<1, 
### the fitted curve has a tendency to oscillate up and down
    hat.loess <- predict(u.lo, newdata = df.new)
    range.loess <- range(hat.loess, na.rm = T)
    done.loess <- T
  }
  else done.loess <- F
  for(i in seq(along = phat)) {
    if(n01 < 2)
      break
    pc <- ptarg[i]
    yhat <- g(pc)
    get.lt <- as.logical(match(c("line", "loess"), phat.strategy[i], nomatch
                               = 0))
    lt.line <- get.lt[1]
    lt.loess <- get.lt[2]
    pc.interp <- ptarg.interp[i]
    yhat.interp <- g(pc.interp)
    alt.line <- F
    if(!done.loess || yhat.interp < range.loess[1] || yhat.interp > 
       range.loess[2])
      alt.line <- T
    mn.use <- 1:length(use)
    if(any(r.use < n.use))
      n.ones <- max(mn.use[r.use < n.use]) + 1
    else n.ones <- mn.use[1]
    take.above <- (r.use > n.use * pc) & (mn.use <= n.ones)
    take.low <- r.use <= n.use * pc
    if(lt.line | (alt.line & lt.loess))
      if(sum(take.above) >= 1) {
        mn.above <- mn.use[take.above]
        n.above <- min(c(max(mn.above), min(mn.above) + 2))
        n.low <- max(c(1, n.above - 3))
        if(n.low == 1)
          n.above <- min(c(max(mn.above), min(mn.above) + 3))
      }
      else if(sum(take.low) >= 1) {
        mn.low <- mn.use[take.low]
        n.above <- max(mn.low)
        n.low <- max(c(mn.low[1], n.above - 3))
      }
      else {
        lt.line <- F
        alt.line <- F
      }
    if(lt.line | alt.line) {
      p.here <- p.use[n.low:n.above]
      not.one <- sum(p.here < 1)
      g.here <- g(p.here)
      g.interp <- g(pc.interp)
      n.span <- n.above - n.low + 1
      eps.low <- extrap.low * diff(range(g.here))
      eps.high <- extrap.high * diff(range(g.here))
      if(n.span == 2) {
        eps.low <- eps.low/2
        eps.high <- eps.high/2
      }
      if(n.span >= 2 & not.one > 1)
        show.line <- ((max(g.here) > pc.interp - eps.high & min(g.here) < 
                       pc.interp) | (min(g.here) < pc.interp + eps.low &
                                     max(g.here) > pc.interp))
      else {
        show.line <- F
        lt.line <- F
        alt.line <- F
      }
    }
    if(lt.line | (alt.line & lt.loess)) {
      rn <- xx[n.low:n.above,  ]
      xv <- xfun(ux[n.low:n.above])
      u <- switch(link,
                  identity = glm(y ~ x, family = binomial("identity"),
                    data = list(y = rn, x = xv)), logsurv = ,
                  log = glm(y ~ x, family = binomial("log"),
                    data = list(y = rn, x = xv)),
                  logit = glm(y ~ x, family = binomial("logit"),
                    data = list(y = rn, x = xv)),
                  sqrt = glm(y ~ x, family = binomial("sqrt"),
                    data = list(y = rn, x = xv)),
                  inverse = glm(y ~ x, family = binomial("inverse"),
                    data = list(y = rn, x = xv)),
                  probit = glm(y ~ x, family = binomial("probit"),
                    data = list(y = rn, x = xv)),
                  cloglog = ,
                  loglog = glm(y ~ x, family = binomial("cloglog"),
                    data = list(y = rn, x = xv)))
      if(!is.na(u$coef[2]) & (lt.line | (alt.line & lt.loess)) & u$coef[2] >
         0) {
        lt[i] <- xfun.inv((yhat - u$coef[1])/u$coef[2])
        ab[[i]] <- u$coef[1:2]
        nam.lt[i] <- "line"
      }
      else {
        lt[i] <- NA
        ab <- NULL
      }
    }
    if(done.loess && lt.loess && min(hat.loess, na.rm = T) <= yhat && max(
                                      hat.loess, na.rm = T) >= yhat) {
      here.hat <- !is.na(hat.loess)
      lt[i] <- xfun.inv(approx(x = hat.loess[here.hat],
                               y = df.new$x[ here.hat], xout = yhat.interp)$y)
      nam.lt[i] <- "mono"
    }
  }
  if(new.lt & !is.null(phat)) {
    p.txt <- paste("LT", phat, "=", format(round(lt, 1)), sep = "")
    leg <- paste(legend, " [", paste(p.txt, collapse = "; "), "]", sep = "")
    names(lt) <- nam.lt
  }
  else leg <- legend
  if(plot.some) {
    if(!is.null(x.cm)) {
      x0 <- c(paste(x0), x.cm)
      r0 <- c(r0, dead.cm)
      n0 <- c(n0, tot.cm)
    }
### NB x0, r0, n0 do not appear below
    simplot(x = x0, resp = r0, tot = n0, fun = link, cm.strategy = 
            cm.strategy, cm = cm, cm.code = cm.code,
            cm.allcodes = cm.allcodes, xtit = xtit, ytit = ytit, mkh = mkh,
            xfun = xfun, main = leg, title.line = title.line,
            plimits = plimits, points.lwd = lwd)
    yp <- g(plimits)
    for(j in seq(along = ab))
      abline(ab[[j]], lty = i)
    if(done.loess) {
      here <- hat.loess >= yp[1] & hat.loess <= yp[2]
      lines(df.new$x[here], hat.loess[here], lty = lo.lty, lwd = lwd)
    }
  }
  lt
}
, comment = "01/10/2004")
"ppaste" <-
structure(function(...)
{
    paste(..., sep = "")
}
, comment = "11/02/1998")
"print.char.matrix" <-
structure(function (x, file = "", col.name.align = "cen", col.txt.align = "right", 
            cell.align = "cen", hsep = "|", vsep = "-", csep = "+", row.names = TRUE, 
            col.names = FALSE, append = FALSE, top.border = TRUE, left.border = TRUE) 
{
### To print a data frame or matrix to a text file or screen
###   and having names line up with stacked cells
###
### First, add row names as first column (might be removed later)
  rownames <- dimnames(x)[[1]]
  x <- cbind(rownames, x)
  dimnames(x)[[1]] <- seq(nrow(x))
###  Set up some padding functions:
###
  pad.left <- function(z, pads) {
### Pads spaces to left of text
    padding <- paste(rep(" ", pads), collapse = "")
    paste(padding, z, sep = "")
  }
  pad.mid <- function(z, pads) {
### Centres text in available space
    padding.right <- paste(rep(" ", pads%/%2), collapse = "")
    padding.left <- paste(rep(" ", pads - pads%/%2), collapse = "")
    paste(padding.left, z, padding.right, sep = "")
  }
  pad.right <- function(z, pads) {
### Pads spaces to right of text
    padding <- paste(rep(" ", pads), collapse = "")
    paste(z, padding, sep = "")
  }
###  (Padding happens on the opposite side to alignment)
  pad.types <- c("left", "mid", "right")
  names(pad.types) <- c("right", "cen", "left")
  pad.name <- pad.types[col.name.align]
  pad.txt <- pad.types[col.txt.align]
  pad.cell <- pad.types[cell.align]
### Padding character columns
###    Need columns with uniform number of characters
  pad.char.col.right <- function(y) {
### For aligning text to LHS of column
    col.width <- nchar(y)
    biggest <- max(col.width)
    smallest <- min(col.width)
    padding <- biggest - col.width
    out <- NULL
    for (i in seq(y)) out[i] <- pad.right(y[i], pads = padding[i])
    out
  }
  pad.char.col.left <- function(y) {
### For aligning text to RHS of column
    col.width <- nchar(y)
    biggest <- max(col.width)
    smallest <- min(col.width)
    padding <- biggest - col.width
    out <- NULL
    for (i in seq(y)) out[i] <- pad.left(y[i], pads = padding[i])
    out
  }
  pad.char.col.mid <- function(y) {
### For aligning text to centre of column
    col.width <- nchar(y)
    biggest <- max(col.width)
    smallest <- min(col.width)
    padding <- biggest - col.width
    out <- NULL
    for (i in seq(y)) out[i] <- pad.mid(y[i], pads = padding[i])
    out
  }
### which functions to use this time.
  pad.name.fn <- get(paste("pad.", pad.name, sep = ""))
  pad.txt.fn <- get(paste("pad.char.col.", pad.txt, sep = ""))
  pad.cell.fn <- get(paste("pad.", pad.cell, sep = ""))
###
### Remove troublesome factors
  x <- as.data.frame(x)
  fac.col <- names(x)[sapply(x, is.factor)]
  for (i in fac.col) x[, i] <- I(as.character(x[, i]))
### ARE ANY LINE BREAKS IN ANY COLUMNS?
  break.list <- list()
  for (i in seq(nrow(x))) {
    x.i <- unlist(x[i, ])
    rows.i <- sapply(strsplit(unlist(x[i, ]), "\n"), length)
    rows.i[rows.i < 1] <- 1
    break.list[[i]] <- rows.i
  }
  break.row <- sapply(break.list, function(x) any(x > 1))
  names(break.row) <- seq(nrow(x))
  xx <- x
  if (any(break.row)) {
### add in extra row/s
    xx <- NULL
    reprow <- lapply(break.list, unique)
    for (k in seq(nrow(x))) {
      x.k <- unlist(x[k, ])
      x.k[x.k == ""] <- " "
      if (break.row[k]) {
        l.k <- strsplit(x.k, "\n")
        add.blanks <- max(break.list[[k]]) - break.list[[k]]
        names(l.k) <- names(add.blanks) <- seq(length(l.k))
        if (any(add.blanks > 0)) {
          for (kk in names(add.blanks[add.blanks > 0]))
            l.k[[kk]] <- c(l.k[[kk]], rep(" ", add.blanks[kk]))
        }
        l.k.df <- as.data.frame(l.k)
        names(l.k.df) <- names(x)
        xx <- rbind(xx, as.matrix(l.k.df))
      }
      else xx <- rbind(xx, x.k)
    }
    row.names(xx) <- paste(rep(row.names(x), sapply(reprow, 
                                                    max)), unlist(reprow), sep = ".")
### Make an index for the rows to be printed
    rn <- row.names(xx)
    rnb <- strsplit(rn, "\\.")
    rpref <- codes(factor(sapply(rnb, function(z) z[1])))
  }
  else rpref <- seq(nrow(x))
  x <- as.data.frame(xx)
### Character columns need different treatment from numeric columns
  char.cols <- sapply(x, is.character)
  if (any(char.cols)) 
    x[char.cols] <- sapply(x[char.cols], pad.txt.fn)
### Change numeric columns into character
  if (any(!char.cols)) 
    x[!char.cols] <- sapply(x[!char.cols], format)
### now all character columns each of which is uniform element width
###
### Lining up names with their columns
### Sometimes the names of columns are wider than the columns they name, 
###  sometimes vice versa.
###
  names.width <- nchar(names(x))
  if (!col.names) 
    names.width <- rep(0, length(names.width))
  cell.width <- sapply(x, function(y) max(nchar(as.character(y))))
### (the width of the characters in the cells as distinct
###      from their names)  
  name.pads <- cell.width - names.width
  cell.pads <- -name.pads
  name.pads[name.pads < 0] <- 0
  cell.pads[cell.pads < 0] <- 0
  pad.names <- name.pads > 0
  pad.cells <- cell.pads > 0
### Pad out the column names if necessary:
  if (any(pad.names)) {
    stretch.names <- names(x)[pad.names]
    for (i in stretch.names) {
      names(x)[names(x) == i] <- pad.name.fn(i, name.pads[i])
    }
  }
### likewise for the cells and columns
  if (any(pad.cells)) {
    stretch.cells <- names(x)[pad.cells]
    for (j in stretch.cells) x[, j] <- pad.cell.fn(x[, j], 
                                                   cell.pads[j])
  }
### Remove row names if not required
  if (!row.names) 
    x <- x[-1]
### Put the column names on top of matrix
  if (col.names)  {
    mat2 <- rbind(names(x), as.matrix(x))
    if(row.names) # Don't remove first column name if there are no rownames
      mat2[1, 1] <- paste(rep(" ", cell.width[1]), collapse = "") # get rid of "rownames" from first column
  }
  else mat2 <- as.matrix(x)
  mat.names.width <- nchar(mat2[1, ])
### character string to separate rows
  space.h <- ""
  for (k in seq(mat.names.width)) {
    space.h <- c(space.h, rep(vsep, mat.names.width[k]), 
                 csep)
  }
  line.sep <- paste(c(ifelse(left.border, csep, ""), space.h), 
                    collapse = "")
  if (col.names) 
    rpref <- c(0, rpref, 0)
  else rpref <- c(rpref, 0)
### print to screen or file

  if (top.border) {
    write(line.sep, file = file, append = append)
    append <- TRUE
  }
  for (i in 1:nrow(mat2)) {
    if (left.border) 
      write(paste(paste(c("", mat2[i, ]), collapse = hsep), 
                  hsep, sep = ""), file = file, append = append)
    else write(paste(paste(mat2[i, ], collapse = hsep), hsep, 
                     sep = ""), file = file, append = append)
    append <- TRUE
### print separator if row prefix is not same as next one
    if (rpref[i] != rpref[i + 1]) 
      write(line.sep, file = file, append = TRUE)
  }
}
, comment = "19/10/2006")
"pseudo.f" <-
structure(function(y, show.aov = F)
{
# Calculates pseudo F-statistics from an anova of a glm object y
    x <- summary(y)
    bits <- unlist(dimnames(x)[[1]])
    resid.df <- x[rev(bits)[1], "Resid. Df"]
    out.df <- NULL
    for(i in bits[-1]) {
       f.stat <- (x[i, "Deviance"]/x[i, "Df"])/(x[rev(bits)[1], "Resid. Dev"]/
          resid.df)
       prf <- 1 - round(pf(f.stat, x[i, "Df"], resid.df), 3)
       out.df <- rbind(out.df, data.frame(Factor = i, "F value" = round(f.stat,
          4), Df1 = x[i, "Df"], Df2 = resid.df, Prob = prf))
    }
    if(show.aov) {
       print(x)
       cat("\n")
    }
    out.df
}
, comment = "30/04/2001")
"qik.sum" <-
structure(function(df, cols = 1:4, ordered = F)
{
### Does a quick summary, first coercing specified cols to factors and making a matrix
###  into a dataframe.
#
### Requires make.factors() also
    df <- as.data.frame(df)
    summary(make.factors(df, cols, ordered = ordered))
}
, comment = "13/08/1998")
"relevel.default" <-
structure(function(x, ref, ...)
stop("relevel only for factors")
, comment = "03/09/1999")
"relevel.factor" <-
structure(function(x, ref, ...)
{
    lev <- levels(x)
    nlev <- length(lev)
    if(is.character(ref))
       ref <- match(ref, lev)
    if(is.na(ref))
       stop("ref must be an existing level")
    if(ref < 1 || ref > nlev)
       stop(paste("ref =", ref, "must be in 1 :", nlev))
    factor(x, levels = lev[c(ref, seq(along = lev)[ - ref])], labels = lev[c(
       ref, seq(along = lev)[ - ref])])
}
, comment = "03/09/1999")
"remove.shading" <-
structure(function()
{
# To get rid of shading on shingles above plots
    strip.background <- trellis.par.get("strip.background")
    strip.background$col <- 0
    trellis.par.set("strip.background", strip.background)
    strip.shingle <- trellis.par.get("strip.shingle")
    strip.shingle$col <- 0
    trellis.par.set("strip.shingle", strip.shingle)
}
, comment = "09/07/2001")
"rms" <-
structure(function(x, na.rm = T, zero.rm = F)
{
    if(na.rm)
       x <- x[!is.na(x)]
    if(zero.rm)
       x <- x[abs(x) > 0]
    sqrt(mean(x^2))
}
, comment = "30/11/1996")
"robust.deviance" <-
structure(function(phat, n, r, min.expected = 1)
{
### phat : vector of fitted probabilities
### n : binomial totals
### r : binomial successes
### min.expected : groups combined so that minimum number expected 
    eps <- 1.0000000000000001e-15
    if(any(n < 0))
       stop("can't have 0 or negative binomial sample size")
    rhat <- phat * n
    ord <- order(phat)
    ind <- match(1:length(n), ord)
    cum.rhat <- cumsum(rhat[ord])
    g1 <- cum.rhat < min.expected
    g1 <- c(T, g1)[1:length(n)]
    revcum.rhat <- rev(cumsum(rev((n - rhat)[ord])))
    g3 <- revcum.rhat < min.expected
    g3 <- c(g3, T)[-1]
    g2 <- !(g1 | g3)
    df <- sum(g2)    ### Really, sum(g2)+2-2; the endpoints are always F
    grp1 <- rep(NA, length(n))
    grp1[g1] <- 1
    grp1[g2] <- 2:(sum(g2) + 1)
    grp1[g3] <- sum(g2) + 2
    grp <- grp1[ind]
    grp
    r.grp <- tapply(r, grp, sum)
    n.grp <- tapply(n, grp, sum)
    phat.grp <- tapply(phat * n, grp, sum)/tapply(n, grp, sum)
    qhat.grp <- 1 - phat.grp
    pobs <- r.grp/n.grp
    qobs <- 1 - pobs
    D1 <- ifelse(pobs < eps, log((pobs/phat.grp)^r.grp), r.grp * log(pobs/
       phat.grp))
    D2 <- ifelse(qobs < eps, log((qobs/qhat.grp)^(n.grp - r.grp)), (n.grp - 
       r.grp) * log(qobs/qhat.grp))
    dev <- 2 * sum(D1 + D2)
    list(dev = dev, df = df)
}
, comment = "26/06/1994")
"s.tapply" <-
structure(function(x, y, z, ...)
{
# Counteracts tapply's propensity to return in sorted index order
#  instead of the order in which they were
    tapply(x, y, z, ...)[(unique(y))]
}
, comment = "30/04/2001")
"save.new" <-
structure(function(neuobj, gem.pos = NULL)
{
                                        # For saving a new function to the Gems database
  if(is.null(gem.pos)) gem.pos <- grep("Gems", search())
  fun.name <- deparse(substitute(neuobj))
  assign(fun.name, neuobj, pos = gem.pos)
  save(list = ls(all = TRUE, pos = gem.pos), file = substring(search()[
                                               gem.pos], 6))
}
, comment = "27/04/2001")
"sem" <-
structure(function(x, na.rm = F)
{
    if(na.rm)
       x <- x[!is.na(x)]
    if(length(x) == 0)
       NA
    else sqrt(var(x)/length(x))
}
, comment = "09/09/1995")
"set.screens" <-
structure(function(across = 2, down = 3, left.margin = 10, top.margin = 20, height = 80, 
    width = 90, ygap = -10, xgap = -1, overwrite = T, centre.x = T, centre.y = 
    T, byrow = T)
{
# Uses split.screen for setting up screens: alternative to par(mfrow/mfcol)
    uu <- ps.region/72 * 25.4    # Change points to mm
    x.all <- uu[3] - uu[1]
    y.all <- uu[4] - uu[2]    #
# Check if there is room for what has been set
    spare.x <- x.all - across * width - xgap * (across - 1)
    if(spare.x < 0)
       stop("\nInsufficient space:\nCheck left.margin, width and xgap")
    spare.y <- y.all - down * height - ygap * (down - 1)
    if(spare.y < 0) stop(
          "\nInsufficient space:\nCheck top.margin, height and ygap")    #
# Set up coordinates for the screens
    top <- top.margin + ifelse(centre.y, spare.y/(down + 1), 0)
    left <- left.margin + ifelse(centre.x, spare.x/(across + 1), 0)
    N <- across * down
    first.x.corners <- c(left - uu[1], left - uu[1] + width)/x.all
    first.y.corners <- c(uu[4] - top - height, uu[4] - top)/y.all    #browser()
    if(N == 1)
       pos.mat <- matrix(c(first.x.corner, first.y.corner), nr = 1)
    else {
       pos.mat <- NULL
       if(byrow) {
          for(j in 1:down) {
             y.corners.j <- first.y.corners - (ygap + height)/y.all * (j - 1)
             for(i in 1:across) {
                x.corners.i <- first.x.corners + ((width + xgap) * (i - 1))/
                   x.all
                pos.mat <- rbind(pos.mat, c(x.corners.i, y.corners.j))
             }
          }
       }
       else {
          for(i in 1:across) {
             x.corners.i <- first.x.corners + ((width + xgap) * (i - 1))/x.all
             for(j in 1:down) {
                y.corners.j <- first.y.corners - (ygap + height)/y.all * (j - 1
                   )
                pos.mat <- rbind(pos.mat, c(x.corners.i, y.corners.j))
             }
          }
       }
       split.screen(pos.mat, erase = !overwrite)
    }
}
, comment = "29/11/1997")
"show.nas" <-
structure(function(df)
{
### identifies which columns of a dataframe have nas.
#
    sapply(df, function(x)
    any(is.na(x)))
}
, comment = "01/12/1997")
"simplot" <-
structure(function(x, resp, tot, fun, cm.strategy = "adjust.later", cm = 0, cm.code = 
           NULL, cm.allcodes = NULL, xtit = "Time in Min", main = "", mkh = 0.025, 
           xfun = function(x) x, takelog = F, line = F, ab = c(NA, NA),
           clip = NULL, xlimits = c(0, 0), 
           xlabels = c(0, 0), offset = 0, title.line = 1, plimits = c(0.0025, 0.9995),
           ytit = NULL, new = F, lty = 1, plot.char = c(0, 1, 2, 5, 6:16),
           id = NULL, points.lwd = 1)
{
  if(missing(mkh))
    mkh <- par()$cin[2]/3
  if(new)
    par(new = T)
  g <- link.function(fun)
  m <- length(x)
  if(is.null(id))
    id <- 1
  if(length(id) == 1)
    id <- rep(id, length(x))
  if(takelog)
    xfun <- log
  if(all(xfun(exp(1:8)) == (1:8))) takelog <- T    
### *****************************************************************
  if(is.null(cm.code))
    cm.code <- 0
  if(is.null(cm.allcodes))
    cm.allcodes <- cm.code
  other.rows <- match(x, cm.allcodes, nomatch = 0)
  cm.here.codes <- unique(cm.allcodes[other.rows])
  cmrows <- as.logical(other.rows)
  if(cm.strategy == "adjust.later" & !takelog)
    here.trt <- !cmrows | x == "0"
  else here.trt <- !cmrows
  x.trt <- as.numeric(x[here.trt])
  resp.trt <- resp[here.trt]
  tot.trt <- tot[here.trt]
  id.trt <- id[here.trt]
  if(missing(xlimits))
    xlimits <- range(x.trt)
  if(takelog) {
    if(any(x.trt + offset < 0)) {
      cat(
          "*** Warning: The following x-values have been omitted because\n x"
          )
      if(offset != 0)
        cat("+", offset)
      cat(" < 0:", fill = T)
      cat(format(x.trt[x.trt + offset < 0]), fill = T)
    }
    if(any(x.trt + offset <= 0)) {
      x.logable <- x.trt + offset > 0
      resp.trt <- resp.trt[x.logable]
      tot.trt <- tot.trt[x.logable]
      x.trt <- x.trt[x.logable]
      id.trt <- id.trt[x.logable]
    }
    if(xlimits[1] + offset <= 0)
      xlimits[1] <- min(x.trt[x.trt + offset > 0], na.rm = T)
  }
  if(diff(range(xlabels)) == 0)
    xlabels <- pretty(xlimits)
  if(takelog)
    xlabels <- xlabels[xlabels > 0]
  cat(xlabels, "  ")    # xlabels specifies numeric labels
  p <- resp.trt/tot.trt
  prange <- range(p)
  if(prange[1] < 0 | prange[2] > 1) {
    cat("Error: Smallest p is", prange[1], fill = T)
    cat("     Largest p is", prange[2], fill = T)
    break
  }
  cm0 <- switch(cm.strategy,
                adjust.later = 0,
                abbott = cm)
  here <- p > cm0 & p < 1
  p.adj <- (p - cm0)/(1 - cm0)
  ylow <- g(plimits[1])
  yhigh <- g(plimits[2])
  eps <- (yhigh - ylow) * 0.01
  ylow <- ylow - eps
  yhigh <- yhigh + eps
  labp <- c(1, 5, 25, 50, 75, 95, 99, 99.9)
  labp <- labp[labp/100 > plimits[1] & labp/100 < plimits[2]]
  aty <- g(labp/100)
  dist <- yhigh - ylow
  if(is.null(ytit)) {
    fun.text <- fun
    ytit <- paste("% Mortality,", fun.text, "scale")
  }
  par(mkh = mkh)
  u.id <- unique(id.trt)
  xlim.here <- xfun(xlimits + offset)
  if(takelog)
    xlim.here <- xlim.here - c(0.115 * diff(xlim.here), 0)
  x.cpos <- xlim.here[1]
  if(sum(here) > 0) {
    plot(xfun(x.trt + offset)[here], g(p.adj[here]), xlim = xlim.here, ylim
         = c(ylow, yhigh), xlab = "", ylab = ytit, axes = F, type = "n")
  }
  else plot(xfun(xlimits + offset), c(ylow, yhigh), xlim = xlim.here, xlab = 
            "", ylab = ytit, axes = F, type = "n")
  midhigh <- 0.5 * (yhigh + par()$usr[4])
  midlow <- 0.5 * (ylow + par()$usr[3])
  chw <- par()$cxy[1]
  chh <- par()$cxy[2]
  j <- 0
  for(i in u.id) {
    j <- j + 1
    here.i <- here & i == id.trt
    g.i <- g(p.adj[here.i])
    if(any(here.i) & any(g.i < ylow | g.i > yhigh)) {
      cat("\n*** One or more points is outside limits set by plimits.***\n"
          )
      cat("\n*** plimits =", format(round(plimits, 4)), "***", "\n")
      cat("\n*** Points are:\n")
      if(any(g.i < ylow)) {
        cat(format(round(p.adj[g.i < ylow], 4)), "\n")
        g.i[g.i < ylow] <- ylow
      }
      if(any(g.i > yhigh)) {
        cat(format(round(p.adj[g.i > yhigh], 4)), "\n")
        g.i[g.i > yhigh] <- yhigh
      }
    }
    if(any(here.i))
      points(xfun(x.trt + offset)[here.i], g(p.adj[here.i]), pch = 
             plot.char[j], mkh = mkh)
    x100 <- x.trt[p == 1 & i == id.trt]
    x0 <- x.trt[p == 0 & i == id.trt]
    x0.100 <- c(x0, x100)
    y0.100 <- c(rep(midlow, length(x0)), rep(midhigh, length(x100)))
    if(length(x0.100) > 0) {
      points(xfun(x0.100 + offset), y0.100, pch = ".", mkh = mkh)
      points(xfun(x0.100 + offset), y0.100, pch = plot.char[j], mkh = mkh)
    }
  }
  if((length(cm.here.codes) > 0) & cm.strategy == "adjust.later") {
    u.cm <- unique(cm.here.codes)
    for(cm.i in u.cm) {
###       here.cm <- x == cm.i ## Try character 8/9/04
       here.cm <- as.character(cm.i)  == x
     p.cm <- resp[here.cm]/tot[here.cm]
      here.cm <- here.cm[p.cm > 0]
      p.cm <- p.cm[p.cm >= 0]## add in equality
#browser()
      if(sum(here) > 0)
        text(rep(x.cpos, length(p.cm)), g(p.cm), rep(cm.i, length(p.cm)))
    }
  }
  if(line) {
    b <- ab[2]
    a <- ab[1]
    if(is.na(b))
      b <- -999
    if(is.null(clip))
      clip <- xlimits
    if(b > 0)
      clipline(xfun(clip + offset), c(ylow, yhigh - chh/3), a, b)
  }
  xmax <- max(x.trt)
  epsx <- 0.0125 * diff(par()$usr[1:2])
  epsy <- 0.0125 * diff(par()$usr[3:4])
  if(takelog) {
    x.cut1 <- x.cpos + epsx
    x.cut2 <- x.cpos + 2.5 * epsx
    here.pos <- xfun(xlabels + offset) > x.cut2 & xlabels <= xmax
  }
  else here.pos <- xlabels <= xmax
  xpos <- xlabels[here.pos]
  if(length(xpos) <= 2)
    xpos <- xlabels[xlabels <= xmax]
###   if(FALSE) {
###       if(names(dev.cur()) == "postscript" & nchar(main) > 0)
###         mixed.mtext(side = 3, line = title.line, texts = main, cex = par()$cex * 
###                     1.2, adj = 0.5)
###       else
###       }

  mtext(side = 3, line = title.line, text = main, cex = par()$cex * 1.2)
  title(xlab = xtit)
  axis(1, at = xfun(xpos + offset), labels = F)
  xusr1 <- par()$usr[1]
  axis(1, at = xfun(xpos + offset), labels = paste(xpos), mgp = c(2, 0.5, 0))
  if(takelog) {
    axis(1, at = c(par()$usr[1], x.cut1), labels = F, tck = 0, mgp = c(2, 
                                                                 0.5, 0))
    axis(1, at = c(x.cut2, par()$usr[2]), labels = F, tck = 0, mgp = c(2, 
                                                                 0.5, 0))
    lines(x.cut1 + c( - epsx, epsx), par()$usr[3] + 2 * c( - epsy, epsy), 
          xpd = T)
    lines(x.cut2 + c( - epsx, epsx), par()$usr[3] + 2 * c( - epsy, epsy), 
          xpd = T)
  }
  else axis(1, at = par()$usr[1:2], labels = F, tck = 0, mgp = c(2, 0.5, 0))
  pr <- c(1, 5, 20, 50, 80, 99)
  extreme.pr <- c(0, 100)
  npr <- length(pr)
  if(all(g(pr/100) == pr/100))
    identity <- T
  else identity <- F
  if(identity)
    pr <- c(0, 25, 50, 75, 100)
  else pr <- pr[g(pr/100) > ylow & g(pr/100) < yhigh]
  axis(2, at = g(pr/100), labels = paste(pr))
  if(identity) {
    midhigh <- g(1)
    axis(2, at = (0:20)/20, labels = F)
  }
  if(!identity) {
    axis(2, at = c(ylow + 2 * epsy, yhigh - 2 * epsy), labels = F, tck = 0)
    for(k in 1:2) {
      y.end <- c(ylow, yhigh)[k]
      axis(2, at = c(y.end, par()$usr[2 + k]), labels = F, tck = 0)
    }
    kk <- (1:2)[c(length(x0) > 0, length(x100) > 0)]
    for(k in kk) {
      y.mid <- c(midlow, midhigh)[k]
      axis(2, at = y.mid, tck = 0, labels = paste(extreme.pr[k]))
      y.end <- c(ylow, yhigh)[k]
      k <- k + 1
      abline(h = y.end, lty = 3)
      lines(xusr1 + c( - epsx, epsx), c(y.end - 1.5 * epsy, y.end + 1.5 * 
                                        epsy), xpd = T)
    ## 1/5/06 fixed up long running error with this: ifelse(k == 2, 4, 0) * epsy +
      lines(xusr1 + c( - epsx, epsx), ifelse(k == 2, 4, 0) * epsy +
            c(y.end - 3.5 * epsy, y.end - 0.5 * epsy), lty = lty, xpd = T)
      
    }
  }
  else axis(2, at = par()$usr[3:4], labels = F, tck = 0)
  box(bty = "7")
}
, comment = "01/05/2006")
"stdev" <-
structure(function(x, na.rm = F)
{
    if(na.rm)
       x <- x[!is.na(x)]
    if(length(x) == 0)
       NA
    else sqrt(var(x))
}
, comment = "21/09/1998")
"strip.trail" <-
structure(function(x, trail = " ")
{
### This function strips away trailing characters of specified value
### from character vectors: everything from the first occurrence of the trail
###  character is removed
    begin.spaces <- find.first(x, trail)
    need.strip <- !is.na(begin.spaces)
    x[need.strip] <- substring(x[need.strip], 1, begin.spaces[need.strip] - 1)
    x
}
, comment = "23/03/1997")
"subsets" <-
structure(function(n, r, v = 1:n) # works in S or R
{
  ## Purpose: Gets permutations of vectors
  ## ----------------------------------------------------------------------
  ## Modified from: Rnews (Vol 2 I think)
  ## ----------------------------------------------------------------------
  ## Arguments:
  ## ----------------------------------------------------------------------
  ## Author: Bill Venables , Creation date:  6 Jun 2000
  if(r <= 0) vector(mode(v), 0) else
  if(r >= n) v[1:n] else {
    rbind(cbind(v[1], Recall(n-1, r-1, v[-1])),
          Recall(n-1, r, v[-1]))
  }
}
, comment = "06/06/2000")
"summarize" <-
structure(function(data, y.cols = NULL, split.cols = NULL, rep.col = "Rep", file = "", 
           append = FALSE, help = FALSE, bp.width = 30, between = FALSE, dec = 3,
           select = c("num", "mean", "sem", "min", "max", "boxplots"), 
           df.out = FALSE, pad = "mid", show.type = FALSE)
{
### Keep Stephen's beginning:
### Requires text.bp(), df.summary(), and df.to.file()
  summary.names <- c("N", "Missing", "Mean", "Median", "Trimmed Mean", 
                     "Std. Dev.", "SEM", "Min", "Max", "1st Quartile",
                     "3rd Quartile", "Sum", "Boxplots")
  summary.types <- c("num", "missing", "mean", "median", "trm", "stdev", 
                     "sem", "min", "max", "q1", "q3", "sum", "boxplots")
  help.df <- (data.frame(Select.this = summary.types, to.get.this = 
                         summary.names))
  if(help) {
    cat("\n In the argument \"select\"\n")
    print(help.df)
    return()
  }

### Make character vectors of y.cols and split.cols if necessary:
  if(is.numeric(y.cols))
    y.cols <- names(data)[y.cols]
  if(is.numeric(split.cols)) split.cols <- names(data)[split.cols]    #
### If between reps are needed, first find means for each rep
  if(between & show.type) {
    if(file == "")
      cat("\n\t16:12, 16 Nov 2006 (NZDT)16:12, 16 Nov 2006 (NZDT)~ BETWEEN REPLICATES 16:12, 16 Nov 2006 (NZDT)16:12, 16 Nov 2006 (NZDT)~\n\n")
    else write("\n\t16:12, 16 Nov 2006 (NZDT)16:12, 16 Nov 2006 (NZDT)~ BETWEEN REPLICATES 16:12, 16 Nov 2006 (NZDT)16:12, 16 Nov 2006 (NZDT)~\n\n", file = 
               file, append = append)
    append <- TRUE
    data <- df.summary(data = data, y.cols = y.cols,
                       split.cols = c(split.cols, rep.col), decimals = 6)
  }
  else {
    if(show.type){
      if(file == "")
        cat("\n\t********* WITHIN REPLICATES *********\n\n")
      else write("\n\t********* WITHIN REPLICATES *********\n\n", file = file,
                 append = append)
      append <- TRUE
    }
  }
  s.tapply <- function(x, y, z, ...)
    tapply(x, y, z, ...)[(unique(y))]
  q1 <- function(x)
    quantile(x, na.rm = TRUE)[2]
  q3 <- function(x)
    quantile(x, na.rm = TRUE)[4]
  no.missing <- function(x)
    length(x[is.na(x)])
  len.rm <- function(x)
    length(x[!is.na(x)])
  round.stdev <- function(x, y = dec)
    round(stdev(x, na.rm = TRUE), y)
  round.mean <- function(x, y = dec)
    round(mean(x, na.rm = TRUE), y)
  round.sem <- function(x, y = dec)
    round(sem(x, na.rm = TRUE), y)
  round.max <- function(x, y = dec)
    round(max(x, na.rm = TRUE), y)
  round.min <- function(x, y = dec)
    round(min(x, na.rm = TRUE), y)
  round.median <- function(x, y = dec)
    round(median(x, na.rm = TRUE), y)
  add.boxplot <- function(x, y.range = range.j, width = bp.width)
    text.bp(x, y.range, width)    #
### Functions are now set up:
                                        #
### Make named vector of functions to be used:
  use.functions <- c("len.rm", "no.missing", "round.mean", "round.median", 
                     "trm", "round.stdev", "round.sem", "round.min", "round.max",
                     "q1", "q3", "sum", "add.boxplot")
  names(use.functions) <- summary.types
  names(summary.names) <- summary.types    #
### Use dataframes instead of matrices:
  if(is.matrix(data))
    data <- unfactor(as.data.frame(data))
  else data <- unfactor(data)    ### avoid pesky factors
  data <- df.sort(data, rev(split.cols))    #
### Create index and adjust for single split columns if necessary:
  indx.df <- data.frame(data[, split.cols])
  names(indx.df) <- split.cols    ### Necessary for single split.cols
  attach(indx.df)
  indx <- NULL
  for(i in split.cols)
    indx <- paste(indx, get(i), sep = ":")
  detach("indx.df")
  out.df <- data.frame(indx.df[match(unique(indx), indx), split.cols])
  names(out.df) <- split.cols    ### Necessary for single split.cols
  dimnames(out.df) <- list(paste(1:nrow(out.df)), names(out.df))
  for(j in y.cols) {
    range.j <- range(data[, j], na.rm = TRUE)
    for(k in select)
      out.df[[summary.names[k]]] <- as.vector(s.tapply(data[, j], indx,
                                                       get(use.functions[k])))
    if(df.out) {
      names(out.df) <- c(split.cols, paste(j, select, sep = "."))
      return(out.df)
    }
    else {
### Get rid of weird row number names:
      dimnames(out.df)[[1]] <- seq(nrow(out.df))
      out.df <- unfactor(out.df)
      numeric.cols <- !sapply(out.df, function(x)
                              any(is.na(as.numeric(x))))
      ## add in as.vector to cope with R-1.8.1 26/11/03 (and above)
      out.df[numeric.cols] <- as.vector(lapply(out.df[numeric.cols], as.numeric))
      underlines <- paste(rep("=", nchar(j)), collapse = "")
      if(file == "") {
        cat(paste("\n ", j, "\n", sep = ""))
        cat(paste(" ", underlines, "\n", sep = ""))
        print(out.df)
      }
      else {
        write(paste("\n", j), file = file, append = append)
        append <- TRUE    # hereafter appending will always be wanted
        write(paste(" ", underlines, sep = ""), file = file, append = TRUE)
        df.to.file(out.df, file = file, append = append, pad = pad)
      }
    }
  }
  invisible()
}
, comment = "17/02/2004")
"tab.file" <-
structure(function(x, file, rounding = 3, ...)
{
### To write a dataframe or matrix to a tab delimited file
    if(!is.null(rounding)) {
       if(is.data.frame(x))
          x <- as.matrix(x)
       x <- round(x, rounding)
    }
    write.table(x, file, sep = "\t", ...)
}
, comment = "25/12/1997")
"tab.mat" <-
structure(function(mat)
{
  rownames <- dimnames(mat)[[1]]
  colnames <- dimnames(mat)[[2]]
  cat(c("\t", paste(colnames, collapse = "\t")), "\n")
  for(i in 1:dim(mat)[1]) {
    cat(paste(c(rownames[i], mat[i,  ]), collapse = "\t"), "\n")
  }
}
, comment = "26/06/1995")
"table.all" <-
structure(function(x, own.seq = seq(0, 3, by = 0.5), minx = 0, maxx = NULL)
{
### returns a table that indicates a zero if the value is absent
### 1a) if else when specifying own sequence
    if(!is.null(own.seq)) {
       same.intervals <- mean(diff(own.seq))
       if(all(diff(own.seq) == same.intervals)) {
          table(c(x, own.seq)) - 1
       }
       else {
          stop("Sequence steps not all the same")
       }
    }
    else {
### 1b) when own sequence is NULL
### 2) if else when specifying a maximum for x
       if(!is.null(maxx)) {
          table(c(x, minx:maxx)) - 1
       }
       else {
          table(c(x, minx:max(x, na.rm = T))) - 1
       }
    }
}
, comment = "19/04/1997")
"ternary" <-
structure(function(X, pch = par("pch"), lcex = 1, add = FALSE,
                    ord = 1:3, space = 1, ...)
{
### Purpose: Draws ternary plots
### ----------------------------------------------------------------------
### Modified from: MASS Skye dataset
### ----------------------------------------------------------------------
### Arguments: space: how much space needed to allow for long apex names?
### ----------------------------------------------------------------------
### Author: Patrick Connolly, Creation date:  7 Apr 2004, 10:01
  X <- as.matrix(X)
  if(any(X) < 0) stop("X must be non-negative")
  s <- drop(X %*% rep(1, ncol(X)))
  if(any(s <= 0)) stop("each row of X must have a positive sum")
  if(max(abs(s - 1)) > 1e-6) {
    warning("row(s) of X will be rescaled")
    X <- X / s
  }
  X <- X[, ord]
  s3 <- sqrt(1/3)
  if(!add)
    {
      oldpty <- par("pty")
      on.exit(par(pty = oldpty))
      par(pty = "s")
      plot(c(-s3, s3) * space, c(0.5 - s3, 0.5 + s3) * space, type = "n",
           axes = FALSE, xlab = "", ylab = "")
      polygon(c(0, -s3, s3), c(1, 0, 0), density = 0)
      lab <- NULL
      if(!is.null(dn <- dimnames(X))) lab <- dn[[2]]
      if(length(lab) < 3) lab <- as.character(1:3)
      eps <- 0.05 * lcex
      text(c(0, s3 + eps * 0.7, -s3 - eps * 0.7),
           c(1 + eps, -0.1 * eps, - 0.1 * eps), lab, cex = lcex)
    }
  points((X[, 2] - X[, 3]) * s3, X[, 1], pch = pch, ...)
}
, comment = "15/04/2004")
"text.bp" <-
structure(function(x, y.range, width = 45, no.data.string = "NA")
{
### Does a "text boxplot" to use in summarize()

 x <- x[!is.na(x)]
  if(length(x) < 1)
    return(no.data.string)
  x.quan <- (boxplot(x, plot = F)$stats[, 1])
  x.outliers <- boxplot(x, plot = F)$out
#browser()
 if(length(x.outliers)>0)
    out.pos <- round(approx(seq(y.range[1], y.range[2], length = width), 1:
                            width, xout = x.outliers)$y)
  qps <- round(approx(seq(y.range[1], y.range[2], length = width), 1:width, 
                      xout = x.quan)$y)    #
### Have quantile positions...
### Make allowances for overlapping positions of quantiles
                                        #
  qps.start <- qps
  if(prod(diff(qps[-3])) == 0) {
    if(qps[2] - qps[1] < 1)
      qps[2] <- qps[1] + 1
    if(qps[5] - qps[4] < 1)
      qps[4] <- qps[4] - 1
    if(qps[4] - qps[2] < 1) {
      if(qps[5] < width)
        qps[4:5] <- qps[4:5] + 1
      else qps[1:2] <- qps[1:2] - 1
    }
  }
 bar.vec <- rep(" ", width)
 bar.vec[qps[1]] <- "("
 bar.vec[qps[2]] <- "["
 bar.vec[qps[4]] <- "]"
 bar.vec[qps[5]] <- ")"
 if(qps[2] - qps[1] > 1)
    bar.vec[(qps[1] + 1):(qps[2] - 1)] <- "."
 if(qps[4] - qps[2] > 1)
    bar.vec[(qps[2] + 1):(qps[4] - 1)] <- "-"
 if(qps[5] - qps[4] > 1) bar.vec[(qps[4] + 1):(qps[5] - 1)] <- "."    #
### Add in outliers if present
 if(length(x.outliers)>0)
   bar.vec[out.pos] <- "*"
 bar.tex <- paste(bar.vec, collapse = "")
 full.bar.tex <- paste(":", bar.tex, ":", sep = "")
 full.bar.tex
}
, comment = "18/06/2001")
"text.lot" <-
structure(function(outfile = "write.fn.src")
{
                                        # creates source file to list all functions
  src.comm <- ppaste("source('", outfile, "')")    # to use src file
  oblist <- ls(pos = 1)
  new.function <- 0    # no of functions to write
  app <- FALSE
  today <- system("date +%d/%m/%Y", TRUE)
  for(i in oblist) {
    date.fn <- comment(get(i))
    if(is.function(get(i)) & (date.fn == today | date.fn == "") ) {
      source.line <- ppaste("write.function(", i, ")")
      write(source.line, file = outfile, append = app)
      new.function <- new.function + 1
      app <- TRUE
    }
  }
  cat(ppaste("Now you can write ", new.function, " function",
             ifelse(new.function > 1, "s", "")," using:\n", src.comm,
             "\n"))
}
, comment = "04/02/2003")
"tidy" <-
structure(function()
{
### Purpose: Source file that adds dates to undated functions and keeps code.
### ----------------------------------------------------------------------
### Modified from: incorporates catalogue and few others
### ----------------------------------------------------------------------
### Arguments: 
### ----------------------------------------------------------------------
### Author: Patrick Connolly, Creation date: 17 Oct 2002, 11:06

source("/home/hrapgc/Rstuff/Gems/tidyup")
}
, comment = "17/10/2002")
"time.to.mort" <-
structure(function(ab, link = "cloglog", pc = 0.99996830000000003)
{
### For calculating time to (by default) Probit9 mortality, or any other %
#
### Note: if the x-axis has used a transformation before fitting the line, 
###  the reverse transformation must be made to this output.
#
    f <- link.function(link)
    targ <- f(ab$cm + (1 - ab$cm) * pc)
    lt <- (targ - ab$intercept)/ab$slope
    lt
}
, comment = "25/04/1997")
"tuk.calc" <-
structure(function(comp = 3, error.df = 50, se = 0.2029, interval = 0.94999999999999996, 
    sed.logical = T)
{
    if(sed.logical) {
       qtukey(interval, comp, error.df) * (se/sqrt(2))
    }
    else {
       qtukey(interval, comp, error.df) * se
    }
}
, comment = "24/12/1996")
"tuk.groups" <-
structure(function(xx, y, sing.top.ok = TRUE, print.mat = FALSE, conf = 0.95,
           full.names = FALSE, print.grid = FALSE, print.sim.df = FALSE)
{
### Purpose: Get Tukey HSD groupings from an aov
### ----------------------------------------------------------------------
### Modified from: Various -- terminology is from palatability of plants
### ----------------------------------------------------------------------
### Arguments: sing.top.ok Sometimes need to fudge last value (Why??)
###            not entirely trustable -- use with caution
###            can't handle factor levels containing a '-' character
###            xx: an anova object
###            y: which factor are we interested in?
###            sing.top.ok: Is it OK to have a singular top value? (fudge?)
###            full.names: long names will maker colnames too long
###            print.mat:  Do we want to see the matrix with astrixes?
###            print.grid: Do we want the table printed with grids?
###            print.sim.df: Print the dataframe with levels that
###                          do not have an HSD with some other?
### ----------------------------------------------------------------------
### Author: Patrick Connolly, Creation date: 20 Aug 2003, 14:07

  xx.tuk <- TukeyHSD(xx, ordered = T, conf.level = conf)
  tuk.df <- as.data.frame(xx.tuk[[y]])
  tuk.df$HSD[tuk.df$lwr < 0 ] <- "*"
  ## Get order of most palatable host
  palatable <- names(sort(model.tables(xx, type = "means")$tables[[y]]))
  plants <- rownames(tuk.df)
  plants.list <- strsplit(plants, "-")
  tuk.df$Plant1 <- unlist(lapply(plants.list, "[", 2))
  tuk.df$Plant2 <- unlist(lapply(plants.list, "[", 1))
  same.groups <- list()
  tuk.same <- tuk.df[tuk.df$lwr < 0 , ]
  tuk.diff <- tuk.df[tuk.df$lwr >= 0 , ]
  if(print.sim.df)
    print(tuk.same)
  if(print.mat){ ## Print similarity matrix
    diff.mat <- matrix("", nrow = length(palatable), ncol = length(palatable))
    dimnames(diff.mat) <- list(palatable, palatable)
    for(i in palatable){
      for(j in palatable){
        if(i != j ){
          first <- match(i, tuk.df$Plant1)
          second <- match(j, tuk.df$Plant2)
          whichrow <- paste(j, i, sep = "-")
          diff.mat[i, j] <- tuk.df[whichrow, ]$HSD
        }    
      }
    }
    diag(diff.mat) <- "∑"
    diff.mat[is.na(diff.mat)] <- ""
    diff.df <- as.data.frame(t(diff.mat))
    if(!full.names)
      names(diff.df) <- LETTERS[seq(palatable)]
    if(print.grid)
      print.char.matrix(as.data.frame(diff.df), col.names = T)
    else print(as.data.frame(diff.df))
    cat("\n")
  }
  for(i in palatable){
    same.i1 <- tuk.same[tuk.same$Plant1 == i, "Plant2"]
    same.i2 <- tuk.same[tuk.same$Plant2 == i, "Plant1"]
    same.groups[[i]]$max <- same.groups[[i]]$min <- match(i, palatable)
    if(length(same.i1) > 0)
      same.groups[[i]]$max <- match(rev(same.i1)[1], palatable)
    if(length(same.i2) > 0)
      same.groups[[i]]$min <- match(same.i2, palatable)
  }
### Find corners in similarity matrix
  mins <- sapply(same.groups, function(x) x$min[1])
  maxs <- sapply(same.groups, function(x) x$max[1]) 
  low <- rep(seq(unique(mins)), table(mins))
                                        #
  if(!sing.top.ok){# might be inaccurate to stop singular top value
    if(rev(low)[1] != rev(low)[2]) 
      low[length(low)] <- low[length(low) - 1]
  }
  high <- rep(seq(unique(maxs)), table(maxs)) # same length as palatable
  if(length(low) != length(high))
    return()
  group <- list()
  for(i in seq(palatable))
    group[[palatable[i]]] <- paste(sort(unique(letters[seq(low[i], high[i])])),
                                   collapse = "")
### return a named vector
  groups <- sapply(group, function(x) x)
  groups
}
, comment = "18/03/2005")
"unfactor" <-
structure(function(x, cols = "every.factor.column", notify = F)
{
#Converts factors back to numerics or character vectors
#
# A dataframe (or vector) of the same dimensions and names is returned
# Default is to change all factor columns 
# Alternatively, specific columns can be specified
#
# notify:  Notify that no factors need changing? 
# Vectors have to be handled differently:
    onecol <- is.null(dim(x))
    if(is.null(dim(x))) {
       x <- as.data.frame(x)
       cols <- 1
    }
# Handling data frames:
    if(is.numeric(cols))
       change.cols <- cols
    else {
       if(cols == "every.factor.column") {
          fact.cols <- check.fact(x)
          change.cols <- find.pos(T, fact.cols)    #
# (a numerical vector of column numbers that are to be changed)
       }
       else change.cols <- find.pos(cols, names(x))
    }
    if(length(change.cols) == 0 & notify)
       cat(paste("No factors to change in", as.character(substitute(x)), "\n"))
    else {
       options(warn = -1)
       on.exit(options(warn = 0))
       for(i in change.cols) {
          levels.i <- levels(x[[i]])
          level.nos <- as.numeric(levels.i)
          numbers <- ifelse(any(is.na(level.nos)), F, T)
          if(numbers)
             x[, i] <- as.numeric(I(as.character(x[, i])))
          else x[, i] <- I(as.character(x[, i]))
       }
    }
    if(onecol)
       x <- as.vector(unlist(x))
    x
}
, comment = "30/04/2001")
"wipe" <-
structure(function (x) 
{
  ## Purpose:  Removes the file in /tmp/ and sets source attribe to NULL
  ## ----------------------------------------------------------------------
  ## Arguments:
  ## ----------------------------------------------------------------------
  ## Author: Zaphod Beeblebrox, Date:  2 Mar 2002, 17:09
  ob.name <- deparse(substitute(x))
  attr.com <- ppaste("attr(", ob.name, ", \"source\") <- NULL\n")
  tmp.com <- ppaste("rm /tmp/hrapgc.", ob.name, ".R\n")
  try(system(tmp.com))
  write.com <- ppaste("write.function(", ob.name, ")")
  cat("  If you want to keep the code, now run these commands:\n")
  cat(paste(write.com, attr.com, sep = " ;"))
}
, comment = "28/06/2002")
"write.function" <-
structure(function(x)
{
### writes a function to file in the ./scr/ directory
  fun.name <- as.character(substitute(x))
  filedate <- comment(get(fun.name))
  location <- system("pwd", TRUE)
    file.name <- ppaste(location,"/.src/R.", fun.name)
  write(paste("  Listing of:", fun.name), ncolumns = 1, file = file.name)
  write(paste("  Located in:", location), file = file.name, ncolumns = 1, append = TRUE)
  write(paste("Last updated:", filedate, 
              "\n**************************************\n"),
        file = file.name, append = TRUE)
  dump(fun.name, file = file.name, append = TRUE)
}
, comment = "22/08/2002")