Nothing
## =============================================================================
## matplot methods - it is not an S3 generic...
## =============================================================================
## the following code was used to make 'matplot' a generic, but
## we disabled this because of unwanted side-effects to other packages,
## see also outcommented code at the end of this file
#matplot <- function (x, ...) UseMethod("matplot")
#matplot.default <- function (x, ...) {
#if (inherits (x, "deSolve"))
# matplot.deSolve(x,...)
#else
# graphics::matplot(x,...)
# #NextMethod()
#}
matplot.deSolve <- function(x, ..., select = NULL, which = select,
obs = NULL, obspar = list(), subset = NULL,
legend = list(x = "topright")) { # legend can be a list
t <- 1 # column with independent variable "times"
# Set the observed data
obs <- SetData(obs)
# variables to be plotted and their position in "x"
varnames <- colnames(x)
xWhich <- NULL
lW <- length(which)
WhichVar <- function(xWhich, obs, varnames) {
if (is.null(xWhich) & is.null(obs$dat)) # All variables plotted
Which <- 2 : length(varnames)
else if (is.null(xWhich)) { # All common variables in x and obs plotted
Which <- which(varnames %in% obs$name)
Which <- Which [Which > 1]
} else if (is.character(xWhich)) {
Which <- which(varnames %in% xWhich)
if (length(Which) != length(xWhich))
stop ("unknown variable", paste(xWhich, collapse = ","))
}
else
Which <- xWhich + 1
return(Which)
}
if (lW & is.list(which))
xWhich <- lapply(which, FUN = function (x) WhichVar(x, obs, varnames))
else if (lW)
xWhich <- list(WhichVar(which, obs, varnames))
else
xWhich <- list(2:length(varnames))
vn <- lapply(xWhich, FUN = function(x) paste(varnames[x], collapse = ","))
vn2 <- unlist(lapply(xWhich, FUN = function(x) paste(varnames[x])))
np <- length(xWhich) # number of y-axes
nx <- length(unlist(xWhich)) # number of y-variables
# add Position of variables to be plotted in "obs"
obs <- updateObs2 (obs, varnames, unlist(xWhich))
# The ellipsis
ldots <- list(...)
Dots <- splitdots(ldots, varnames)
if (Dots$nother > 1)
stop ("can plot only one deSolve output object at a time with matplot")
Dotmain <- setdots(Dots$main, np)
# these are different from the default
Dotmain$xlab <- expanddots(ldots$xlab, varnames[t] , np)
Dotmain$ylab <- expanddots(ldots$ylab, vn , np)
Dotmain$main <- expanddots(ldots$main, as.character(substitute(x)), np)
# ylim and xlim can be lists and are at least two values
yylim <- expanddotslist(ldots$ylim, np)
xxlim <- expanddotslist(ldots$xlim, np)
Dotpoints <- setdots(Dots$points, nx) # expand all dots to nx values
# these are different from default
Dotpoints$type <- expanddots(ldots$type, "l", nx)
Dotpoints$lty <- expanddots(ldots$lty, 1:nx, nx)
Dotpoints$pch <- expanddots(ldots$pch, 1:nx, nx)
Dotpoints$col <- expanddots(ldots$col, 1:nx, nx)
Dotpoints$bg <- expanddots(ldots$bg, 1:nx, nx)
if (! is.null(obs)) {
ii <- which(unlist(xWhich) %in% unlist(obs$Which))
ii <- ii[! is.na(ii)]
if (is.null(obs$par))
obs$par <- list()
else
obs$par <- lapply(obspar, repdots, obs$length)
if (is.null(obs$par$pch))
obs$par$pch <- Dotpoints$pch[ii]
if (is.null(obs$par$cex))
obs$par$cex <- Dotpoints$cex[ii]
if (is.null(obs$par$col))
obs$par$col <- Dotpoints$col[ii]
if (is.null(obs$par$bg))
obs$par$bg <- Dotpoints$bg[ii]
}
if (!missing(subset)){
e <- substitute(subset)
r <- eval(e, as.data.frame(x), parent.frame())
if (is.numeric(r)) {
isub <- r
} else {
if (!is.logical(r))
stop("'subset' must evaluate to logical or be a vector with integers")
isub <- r & !is.na(r)
}
} else {
isub <- TRUE
}
# LOOP for each (set of) output variables (and y-axes)
if (np > 1)
par(mar = c(5.1, 4.1, 4.1, 2.1) + c(0, (np-1)*4, 0, 0))
ii <- 1
for (ip in 1 : np) {
ix <- xWhich[[ip]] # position of y-variables in 'x'
iL <- length(ix)
iip <- ii:(ii+iL-1) # for dotpoints
ii <- ii + iL
io <- obs$Which[iip]
# plotting parameters for matplot and axes
dotmain <- extractdots(Dotmain, ip)
if (is.null(dotmain$axes)) dotmain$axes <- FALSE
if (is.null(dotmain$frame.plot)) dotmain$frame.plot <- TRUE
dotpoints <- extractdots(Dotpoints, iip) # for all variables
Xlog <- Ylog <- FALSE
if (! is.null(dotmain$log)) {
Ylog <- length(grep("y",dotmain$log))
Xlog <- length(grep("x",dotmain$log))
}
SetRangeMat <- function(lim, x, isub, ix, obs, io, Log) {
if ( is.null (lim)) {
yrange <- Range(NULL, as.vector(x[isub, ix]), Log)
if (! is.na(io[1])) yrange <- Range(yrange, as.vector(obs$dat[,io]), Log)
} else
yrange <- lim
return(yrange)
}
dotmain$ylim <- SetRangeMat(yylim[[ip]], x, isub, ix, obs, io, Ylog)
dotmain$xlim <- SetRangeMat(xxlim[[ip]], x, isub, t, obs, io, Xlog)
Ylab <- dotmain$ylab
dotmain$ylab <- ""
if (ip > 1) {
par(new = TRUE)
dotmain$xlab <- dotmain$main <- ""
}
do.call("matplot", c(alist(x[isub, t], x[isub, ix]), dotmain, dotpoints))
if (ip == 1)
axis(1, cex = dotmain$cex.axis)
cex <- ifelse (is.null(dotmain$cex.lab), 0.9, 0.9*dotmain$cex.lab)
bL <- 4*(ip-1)
axis(side = 2, line = bL, cex = dotmain$cex.axis)
mtext(side = 2, line = bL+2, Ylab, cex = cex)
if (! is.na(io[1]))
for (j in 1: length(io)) {
i <- which (obs$Which == io[j])
if (length (i.obs <- obs$pos[i, 1]:obs$pos[i, 2]) > 0)
do.call("points", c(alist(obs$dat[i.obs, 1], obs$dat[i.obs, io[j]]),
extractdots(obs$par, j) ))
}
}
if (is.null(legend))
legend <- list(x = "topright")
if (is.list(legend)){ # can also be FALSE
if (length(legend$legend))
L <- legend$legend
else
L <- vn2
legend$legend <- NULL
if (is.null(legend$x))
legend$x <- "topright"
lty <- Dotpoints$lty
pch <- Dotpoints$pch
lty[Dotpoints$type == "p"] <- NA
pch[Dotpoints$type == "l"] <- NA
do.call ("legend", c(legend, alist(lty = lty, lwd = Dotpoints$lwd,
pch =pch, col = Dotpoints$col, pt.bg =Dotpoints$bg,
legend = L)))
}
}
### ============================================================================
### plotting 1-D variables as line plot, one for each time
### ============================================================================
matplot.1D <- function (x, select= NULL, which = select, ask = NULL,
obs = NULL, obspar = list(), grid = NULL,
xyswap = FALSE, vertical = FALSE, subset = NULL, ...) {
## Check settings of x
att <- attributes(x)
nspec <- att$nspec
dimens <- att$dimens
proddim <- prod(dimens)
if (length(dimens) != 1)
stop ("matplot.1D only works for models solved with 'ode.1D'")
if ((ncol(x)- nspec*proddim) < 1)
stop("ncol of 'x' should be > 'nspec' * dimens if x is a vector")
# Set the observed data
obs <- SetData(obs)
# 1-D variable names
varnames <- if (! is.null(att$ynames))
att$ynames else 1:nspec
if (! is.null(att$lengthvar))
varnames <- c(varnames, names(att$lengthvar)[-1])
# variables to be plotted, common between obs and x
Which <- WhichVarObs(which, obs, nspec, varnames, remove1st = FALSE)
np <- length(Which)
# Position of variables to be plotted in "x"
Select <- select1dvar(Which, varnames, att) # also start and end position
xWhich <- Select$Which
# add Position of variables to be plotted in "obs"
obs <- updateObs (obs, varnames, xWhich)
obs$par <- lapply(obspar, repdots, obs$length)
# the ellipsis
ldots <- list(...)
# number of figures in a row and interactively wait if remaining figures
ask <- setplotpar(ldots, np, ask)
if (ask) {
oask <- devAskNewPage(TRUE)
on.exit(devAskNewPage(oask))
}
Dots <- splitdots(ldots, varnames)
nother <- Dots$nother
Dotpoints <- Dots$points
Dotmain <- setdots(Dots$main, np) # expand all dots to np values (no defaults)
# These are different from defaults
Dotmain$xlab <- expanddots(ldots$xlab, "x", np)
Dotmain$ylab <- expanddots(ldots$ylab, "", np)
Dotmain$main <- expanddots(ldots$main, varnames[xWhich], np)
# xlim and ylim are special:
xxlim <- expanddotslist(ldots$xlim, np)
yylim <- expanddotslist(ldots$ylim, np)
xyswap <- rep(xyswap, length = np)
vertical <- rep(vertical, length = np)
if (!missing(subset)){
e <- substitute(subset)
r <- eval(e, as.data.frame(x), parent.frame())
if (is.numeric(r)) {
isub <- r
} else {
if (!is.logical(r))
stop("'subset' must evaluate to logical or be a vector with integers")
isub <- r & !is.na(r)
}
} else isub <- 1:nrow(x)
grid <- expanddotslist(grid, np)
for (ip in 1:np) {
istart <- Select$istart[ip]
istop <- Select$istop[ip]
io <- obs$Which[ip]
out <- t(x[ isub, istart:istop])
if (length (isub) > 1 & sum (isub) == 1)
out <- matrix (out)
Grid <- grid[[ip]]
if (is.null(Grid))
Grid <- 1:nrow(out)
dotmain <- extractdots(Dotmain, ip)
Xlog <- Ylog <- FALSE
if (! is.null(dotmain$log)) {
Ylog <- length(grep("y", dotmain$log))
Xlog <- length(grep("x", dotmain$log))
}
if (vertical[ip]) { # overrules other settings; vertical profiles
xyswap[ip] <- TRUE
dotmain$axes <- FALSE
dotmain$xlab <- ""
dotmain$xaxs <- "i"
dotmain$yaxs <- "i"
}
if (! xyswap[ip]) {
if (! is.null(xxlim[[ip]]))
dotmain$xlim <- xxlim[[ip]]
dotmain$ylim <- SetRange(yylim[[ip]], x, NULL, isub, istart:istop, obs, io, Ylog)
} else {
if (! is.null(yylim[[ip]]))
dotmain$ylim <- yylim[[ip]]
dotmain$xlim <- SetRange(xxlim[[ip]], x, NULL, isub, istart:istop, obs, io, Xlog)
if (is.null(yylim[[ip]]) & xyswap[ip])
dotmain$ylim <- rev(range(Grid)) # y-axis
}
if (! xyswap[ip]) {
do.call("matplot", c(alist(Grid, out), dotmain, Dotpoints))
if (! is.na(io))
plotObs(obs, io)
} else {
if (is.null(dotmain$xlab[ip]) | is.null(dotmain$ylab[ip])) {
dotmain$ylab <- dotmain$xlab[ip]
dotmain$xlab <- dotmain$ylab[ip]
}
do.call("matplot", c(alist(out, Grid), dotmain, Dotpoints))
if (vertical[ip])
DrawVerticalAxis(dotmain, min(out))
if (! is.na(io))
plotObs(obs, io, xyswap = TRUE)
}
}
}
## =============================================================================
## S3/S4 compatibility
## =============================================================================
## make matplot an S4 method and then extend generic for class deSolve
## but note that matplot.1D is not (yet) a generic, because .1D is just an
## alternative way of plotting and not a well defined class
setGeneric("matplot", function(x, ...) graphics::matplot(x, ...))
setOldClass("deSolve")
setMethod("matplot", list(x = "deSolve"), matplot.deSolve)
## thpe: 2016-06-20, deSolve 1.14
## exporting matplot leads to annoying messages during package startup
## experimental approach:
## - do not anymore export matplot
## - instead, use exported 'matplot.deSolve' or alias 'matplot.0D'
matplot.0D <- matplot.deSolve
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