### Copyright (C) 2001-2006 Deepayan Sarkar <Deepayan.Sarkar@R-project.org>
###
### This file is part of the lattice package for R.
### It is made available under the terms of the GNU General Public
### License, version 2, or at your option, any later version,
### incorporated herein by reference.
###
### This program is distributed in the hope that it will be
### useful, but WITHOUT ANY WARRANTY; without even the implied
### warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
### PURPOSE. See the GNU General Public License for more
### details.
###
### You should have received a copy of the GNU General Public
### License along with this program; if not, write to the Free
### Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston,
### MA 02110-1301, USA
prepanel.default.qqmath <-
function(x,
f.value = NULL,
distribution = qnorm,
qtype = 7,
groups = NULL,
subscripts, ...,
tails.n = 0)
{
if (!is.numeric(x)) x <- as.numeric(x) # FIXME: dates?
distribution <- getFunctionOrName(distribution)
nobs <- sum(!is.na(x))
## if plotting tails, do prepanel as for raw data:
if (tails.n > 0)
f.value <- NULL
getxx <- function(x, f.value = NULL,
nobs = sum(!is.na(x)))
{
if (is.null(f.value))
distribution(ppoints(nobs))
else if (is.numeric(f.value))
distribution(f.value)
else
distribution(f.value(nobs))
}
getyy <- function(x, f.value = NULL,
nobs = sum(!is.na(x)))
{
if (is.null(f.value))
sort(x)
else if (is.numeric(f.value))
quantile(x, f.value, # was fast.quantile
names = FALSE,
type = qtype,
na.rm = TRUE)
else
quantile(x, f.value(nobs), # was fast.quantile
names = FALSE,
type = qtype,
na.rm = TRUE)
}
if (!nobs)
prepanel.null()
else if (!is.null(groups))
{
sx <- split(x, groups[subscripts])
xxlist <- lapply(sx, getxx, f.value = f.value)
yylist <- lapply(sx, getyy, f.value = f.value)
list(xlim = range(unlist(xxlist), finite = TRUE),
ylim = range(unlist(yylist), finite = TRUE),
dx = unlist(lapply(xxlist, diff)),
dy = unlist(lapply(yylist, diff)))
}
else
{
xx <- getxx(x, f.value, nobs)
yy <- getyy(x, f.value, nobs)
list(xlim = scale_limits(xx), # range(xx, finite = TRUE),
ylim = scale_limits(yy), # range(yy, finite = TRUE),
dx = diff(xx),
dy = diff(yy))
}
}
panel.qqmath <-
function(x,
f.value = NULL,
distribution = qnorm,
qtype = 7,
groups = NULL, ...,
tails.n = 0,
identifier = "qqmath")
{
x <- as.numeric(x)
distribution <- getFunctionOrName(distribution)
nobs <- sum(!is.na(x))
if (!is.null(groups))
panel.superpose(x, y = NULL,
f.value = f.value,
distribution = distribution,
qtype = qtype,
groups = groups,
panel.groups = panel.qqmath,
...,
tails.n = tails.n)
else if (nobs)
{
if (is.null(f.value)) # exact data instead of quantiles
{
panel.xyplot(x = distribution(ppoints(nobs)),
y = sort(x),
...,
identifier = identifier)
}
else
{
pp <- if (is.numeric(f.value)) f.value else f.value(nobs)
if (tails.n > 0)
{
## use exact data for tails of distribution
tails.n <- min(tails.n, nobs %/% 2)
ppd <- ppoints(nobs)
## omit probabilities within the exact tails
pp <- pp[(pp > ppd[tails.n] &
pp < ppd[nobs + 1 - tails.n])]
## add on probs corresponding to exact tails
pp <- c(head(ppd, tails.n), pp, tail(ppd, tails.n))
## must use a quantile type that recovers exact values:
qtype <- 1
}
xx <- distribution(pp)
yy <- quantile(x, pp,
names = FALSE,
type = qtype,
na.rm = TRUE)
panel.xyplot(x = xx, y = yy, ...,
identifier = identifier)
}
}
}
qqmath <- function(x, data, ...) UseMethod("qqmath")
qqmath.numeric <-
function(x, data = NULL, ylab = deparse(substitute(x)), ...)
{
ocall <- sys.call(); ocall[[1]] <- quote(qqmath)
ccall <- match.call()
if (!is.null(ccall$data))
warning("explicit 'data' specification ignored")
ccall$data <- environment() # list(x = x)
ccall$ylab <- ylab
ccall$x <- ~x
ccall[[1]] <- quote(lattice::qqmath)
ans <- eval.parent(ccall)
ans$call <- ocall
ans
}
qqmath.formula <-
function(x,
data = NULL,
allow.multiple = is.null(groups) || outer,
outer = !is.null(groups),
distribution = qnorm,
f.value = NULL,
auto.key = lattice.getOption("default.args")$auto.key,
aspect = "fill",
panel = lattice.getOption("panel.qqmath"),
prepanel = NULL,
scales = list(),
strip = TRUE,
groups = NULL,
xlab,
xlim,
ylab,
ylim,
drop.unused.levels = lattice.getOption("drop.unused.levels"),
...,
lattice.options = NULL,
default.scales = list(),
default.prepanel = lattice.getOption("prepanel.default.qqmath"),
subscripts = !is.null(groups),
subset = TRUE)
{
formula <- x
dots <- list(...)
groups <- eval(substitute(groups), data, environment(formula))
subset <- eval(substitute(subset), data, environment(formula))
if (!is.null(lattice.options))
{
oopt <- lattice.options(lattice.options)
on.exit(lattice.options(oopt), add = TRUE)
}
## Step 1: Evaluate x, y, etc. and do some preprocessing
form <-
latticeParseFormula(formula, data, subset = subset,
groups = groups, multiple = allow.multiple,
outer = outer, subscripts = TRUE,
drop = drop.unused.levels)
groups <- form$groups
if (!is.function(panel)) panel <- eval(panel)
if (!is.function(strip)) strip <- eval(strip)
if ("subscripts" %in% names(formals(panel))) subscripts <- TRUE
if (subscripts) subscr <- form$subscr
cond <- form$condition
## number.of.cond <- length(cond)
x <- form$right
if (length(cond) == 0)
{
strip <- FALSE
cond <- list(gl(1, length(x)))
## number.of.cond <- 1
}
dist.name <- paste(deparse(substitute(distribution)), collapse = "")
if (missing(xlab)) xlab <- dist.name
if (missing(ylab)) ylab <- form$right.name
## create a skeleton trellis object with the
## less complicated components:
foo <-
do.call("trellis.skeleton",
c(list(formula = formula,
cond = cond,
aspect = aspect,
strip = strip,
panel = panel,
xlab = xlab,
ylab = ylab,
xlab.default = dist.name,
ylab.default = form$right.name,
lattice.options = lattice.options), dots),
quote = TRUE)
dots <- foo$dots # arguments not processed by trellis.skeleton
foo <- foo$foo
foo$call <- sys.call(); foo$call[[1]] <- quote(qqmath)
## Step 2: Compute scales.common (leaving out limits for now)
if (is.character(scales)) scales <- list(relation = scales)
scales <- updateList(default.scales, scales)
foo <- c(foo, do.call("construct.scales", scales))
## Step 3: Decide if limits were specified in call:
have.xlim <- !missing(xlim)
if (!is.null(foo$x.scales$limits))
{
have.xlim <- TRUE
xlim <- foo$x.scales$limits
}
have.ylim <- !missing(ylim)
if (!is.null(foo$y.scales$limits))
{
have.ylim <- TRUE
ylim <- foo$y.scales$limits
}
## Step 4: Decide if log scales are being used:
have.xlog <- !is.logical(foo$x.scales$log) || foo$x.scales$log
have.ylog <- !is.logical(foo$y.scales$log) || foo$y.scales$log
## This is slightly weird because 'x' is eventually plotted in the
## Y-axis
if (have.xlog)
{
warning("Can't have log X-scale")
have.xlog <- FALSE
foo$x.scales$log <- FALSE
}
if (have.ylog)
{
ylog <- foo$y.scales$log
ybase <-
if (is.logical(ylog)) 10
else if (is.numeric(ylog)) ylog
else if (ylog == "e") exp(1)
x <- log(x, ybase)
if (have.ylim) ylim <- logLimits(ylim, ybase)
}
## Step 5: Process cond
cond.max.level <- unlist(lapply(cond, nlevels))
## Step 6: Determine packets
foo$panel.args.common <-
c(list(distribution = distribution,
f.value = f.value),
dots)
if (subscripts)
{
foo$panel.args.common$groups <- groups
}
npackets <- prod(cond.max.level)
if (npackets != prod(sapply(foo$condlevels, length)))
stop("mismatch in number of packets")
foo$panel.args <- vector(mode = "list", length = npackets)
foo$packet.sizes <- numeric(npackets)
if (npackets > 1)
{
dim(foo$packet.sizes) <- sapply(foo$condlevels, length)
dimnames(foo$packet.sizes) <- lapply(foo$condlevels, as.character)
}
cond.current.level <- rep(1, length(cond))
for (packet.number in seq_len(npackets))
{
id <- compute.packet(cond, cond.current.level)
foo$packet.sizes[packet.number] <- sum(id)
foo$panel.args[[packet.number]] <-
list(x = x[id])
if (subscripts)
foo$panel.args[[packet.number]]$subscripts <-
subscr[id]
cond.current.level <-
cupdate(cond.current.level,
cond.max.level)
}
more.comp <-
c(limits.and.aspect(default.prepanel,
prepanel = prepanel,
have.xlim = have.xlim, xlim = xlim,
have.ylim = have.ylim, ylim = ylim,
x.relation = foo$x.scales$relation,
y.relation = foo$y.scales$relation,
panel.args.common = foo$panel.args.common,
panel.args = foo$panel.args,
aspect = aspect,
npackets = npackets,
x.axs = foo$x.scales$axs,
y.axs = foo$y.scales$axs),
cond.orders(foo))
foo[names(more.comp)] <- more.comp
if (is.null(foo$legend) && needAutoKey(auto.key, groups))
{
foo$legend <-
autoKeyLegend(list(text = levels(as.factor(groups)),
points = TRUE,
rectangles = FALSE,
lines = FALSE),
auto.key)
}
class(foo) <- "trellis"
foo
}
##############################################
panel.qqmathline <-
function(x, y = x,
distribution = qnorm,
probs = c(0.25, 0.75),
qtype = 7,
groups = NULL,
...,
identifier = "qqmathline")
{
y <- as.numeric(y)
stopifnot(length(probs) == 2)
distribution <- getFunctionOrName(distribution)
nobs <- sum(!is.na(y))
if (!is.null(groups))
panel.superpose(x = y, y = NULL,
distribution = distribution,
probs = probs,
qtype = qtype,
groups = groups,
panel.groups = panel.qqmathline,
...)
else if (nobs > 0)
{
yy <-
quantile(y, probs, names = FALSE, # was fast.quantile
type = qtype, na.rm = TRUE)
xx <- distribution(probs)
r <- diff(yy)/diff(xx)
panel.abline(c( yy[1]-xx[1]*r , r), ...,
identifier = identifier)
}
}
prepanel.qqmathline <-
function(x, y = x,
distribution = qnorm,
probs = c(0.25, 0.75),
qtype = 7,
groups = NULL,
subscripts = TRUE,
...)
{
ans <-
prepanel.default.qqmath(x,
distribution = distribution,
qtype = qtype,
groups = groups,
subscripts = subscripts,
...)
y <- as.numeric(y)
stopifnot(length(probs) == 2)
distribution <- getFunctionOrName(distribution)
getdy <- function(x)
{
diff(quantile(x, probs, names = FALSE, # was fast.quantile
type = qtype,
na.rm = TRUE))
}
dy <-
if (!is.null(groups)) sapply(split(y, groups[subscripts]), getdy)
else getdy(y)
if (!all(is.na(dy)))
{
ans$dy <- dy[!is.na(dy)]
ans$dx <- rep(diff(distribution(probs)), length(ans$dy))
}
ans
}
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