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scat1d.s
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scat1d.s
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## Improvements due to Martin Maechler <maechler@stat.math.ethz.ch>
scat1d <- function(x, side=3, frac=.02, jitfrac=.008, tfrac,
eps=ifelse(preserve,0,.001),
lwd=0.1, col=par('col'), y=NULL, curve=NULL,
bottom.align=FALSE, preserve=FALSE, fill=1/3, limit=TRUE,
nhistSpike=2000, nint=100,
type=c('proportion','count','density'),
grid=FALSE,
...)
{
type <- match.arg(type)
if(length(x) >= nhistSpike)
return(histSpike(x, side=side, type=type,
frac=2.5 * frac, col=col, y=y, curve=curve,
bottom.align=if(type == 'density') TRUE else bottom.align,
add=TRUE, nint=nint, grid=grid, ...))
gfun <- ordGridFun(grid)
if(side == 1 || side == 3 || length(y) || length(curve)) {
l <- 1:2
ax <- 1
} else {
l <- 3:4
ax <- 2
}
pr <- parGrid(grid)
usr <- pr$usr; pin <- pr$pin; uin <- pr$uin
u <- usr[ l]
u.opp <- usr[- l]
w <- u[2] - u[1]
## Start JOA 12.8.97 : handle xy missings parallel
if (length(y) > 1) { ## length=1 special case needed for datadensity
if (length(x) != length(y))
stop("y must have same length as x (or length(y)=1)")
selector <- ! (is.na(x) | is.na(y))
x <- unclass(x[selector])
y <- unclass(y[selector])
} else x <- unclass(x[! is.na(x)])
## Stop JOA 12.8.97
if(length(curve))
y <- approx(curve, xout=x, rule=2)$y
n <- length(x)
if(missing(tfrac))
tfrac <- if(n < 125) 1 else max(.1, 125 / n)
else if (tfrac < 0 || tfrac > 1)
stop("must have 0 <= tfrac <= 1")
## Start JOA 19.8.97
if(jitfrac > 0 && anyDuplicated( if(eps > 0) round(x / w / eps) else x ))
if (preserve)
x <- jitter2(x, fill=fill, limit=limit, eps=w * eps)
else
## Stop JOA 19.8.97
x <- x + runif(n, -w * jitfrac, w * jitfrac)
h <- min(pin) * frac / uin[- ax]
h2 <- h / 2
if(grid && length(y) && inherits(y, 'unit')) {
h <- unit(frac, 'npc')
h2 <- unit(frac/2, 'npc')
}
if(length(y)) {
a <- y - h2
b <- y + h2
} else {
a <- if(side < 3) u.opp[1]
else u.opp[2] - h
b <- if(side < 3) u.opp[1] + h
else u.opp[2]
}
if(tfrac < 1) {
l <- tfrac * (b - a)
a <- a + runif(n) * (b - l - a) ##runif(n, a, b-l) if frac>0
b <- a + l
}
if(ax == 1 && bottom.align) {
a <- a + h2
b <- b + h2
}
if(ax == 1)
gfun$segments(x, a, x, b, lwd=lwd, xpd=frac < 0, col=col)
else
gfun$segments(a, x, b, x, lwd=lwd, xpd=frac < 0, col=col)
invisible()
}
jitter2 <- function(x,...) UseMethod("jitter2")
jitter2.default <- function(x, fill=1/3, limit=TRUE, eps=0,
presorted=FALSE, ...)
{
x2 <- x[!is.na(x)]
if (!presorted){
o <- order(x2)
x2 <- x2[o]
}
r <- if (eps > 0) rle(round(x2 / eps) * eps) else rle(x2)
if ( length(r$length) < 2 || max(r$length) < 2 )
return(x)
d <- abs(diff(r$values))
d <- pmin( c(d[1], d), c(d, d[length(d)]) )
who <- rep(r$lengths > 1, r$lengths)
d <- d[r$lengths > 1] * fill / 2
if (is.logical(limit) && limit) limit <- min(d)
if (limit) d <- pmin(d,limit)
r$values <- r$values[r$lengths > 1] - d
r$lengths <- r$lengths[r$lengths > 1]
d <- d * 2 / (r$lengths - 1)
k <- length(r$lengths)
n <- sum(who)
val <- rep(r$values, r$lengths)
add <- (0 : (n - 1)) - rep(c(0, cumsum(r$lengths[-k])), r$lengths)
add <- add[order(rep(1 : k, r$lengths), runif(n))]
add <- add * rep(d, r$lengths)
val <- val + add
x2[who] <- val
if (!presorted)
x2[o]<-x2
x[!is.na(x)] <- x2
x
}
jitter2.data.frame <- function(x, ...)
{
as.data.frame(lapply(x,
function(z,...)
{
if (is.numeric(z))
jitter2.default(z,...)
else z
},
...))
}
datadensity <- function(object, ...)
{
if(!length(class(object)))
class(object) <- data.class(object)
UseMethod('datadensity')
}
datadensity.data.frame <-
function(object, group,
which=c('all','continuous','categorical'),
method.cat=c('bar','freq'),
col.group=1:10,
n.unique=10, show.na=TRUE, nint=1, naxes,
q, bottom.align=nint > 1,
cex.axis=sc(.5,.3), cex.var=sc(.8,.3),
lmgp=NULL, tck=sc(-.009,-.002),
ranges=NULL, labels=NULL, ...)
{
which <- match.arg(which)
method.cat <- match.arg(method.cat)
maxna <- 0
mgroup <- missing(group) # before R changes it
z <-
sapply(object,
function(x, n.unique)
{
xp <- x[!is.na(x)]
nu <- if(length(xp)) length(unique(xp))
else 0
if(nu < 2) c(0,0)
else
c(type=if(is.factor(x) || is.character(x) || nu < n.unique)
1
else 2,
na=sum(is.na(x)))
},
n.unique=n.unique)
types <- c('nil','cat','cont')[z[1,]+1]
numna <- z[2,]
fnumna <- format(numna)
maxna <- max(numna)
w <- switch(which,
all = types != 'nil',
continuous = types == 'cont',
categorical= types == 'cat')
if(missing(naxes)) naxes <- sum(w)
## Function to scale values such that when naxes<=3 get hi, >=50 get
## lo, otherwise linearly interpolate between 3 and 50
sc <- function(hi,lo,naxes)
approx(c(50,3),c(lo,hi),xout=naxes,rule=2)$y
formals(sc) <- list(hi=NA,lo=NA,naxes=naxes)
nams <- names(object)
max.length.name <- max(nchar(nams))
if(!length(lmgp))
lmgp <- sc(0,0)
oldpar <- oPar() # in Hmisc Misc.s
mgp <- c(0,lmgp,0)
mai <- oldpar$mai
plot.new();
par(new=TRUE)
## enables strwidth
mxlb <- .1 + max(strwidth(nams, units='inches', cex=cex.var))
mai[2] <- mxlb
if(!show.na) maxna <- 0
max.digits.na <- if(maxna == 0) 0
else trunc(log10(maxna)) + 1
if(maxna > 0)
mai[4] <- .1 + strwidth('Missing', units='inches', cex=cex.var)
par(mgp=mgp, mai=mai,tck=tck)
on.exit(setParNro(oldpar))
if(!mgroup)
group <- as.factor(group)
else
{
group <- factor(rep(1,length(object[[1]])))
ngroup <- 0
}
ngroup <- length(levels(group))
col.group <- rep(col.group, length.out=ngroup)
y <- 0
for(i in (1:length(nams))[w])
{
if(y < 1)
{
plot(c(0,1),c(1,naxes),xlim=c(.02,.98),ylim=c(1,naxes),
xlab='',ylab='',type='n',axes=FALSE)
usr <- par('usr')
y <- naxes + 1
if(maxna > 0)
{
outerText('Missing',
y=naxes+strheight('Missing',units='user',cex=cex.var),
cex=cex.var)
}
charheight <- strheight('X',units='user',cex=.6) ## par('cxy')[2]
}
y <- y - 1
x <- object[[i]]
if(types[i] == 'cont' )
{ ## continuous variable
x <- unclass(x) ## handles dates
isna <- is.na(x)
nna <- sum(isna)
N <- length(x) - nna
r <-
if(length(ranges) && length(ranges[[nams[i]]]))
ranges[[nams[i]]]
else
range(x, na.rm=TRUE)
p <- pretty(r,
if(nint == 1)5
else nint)
if(nint < 2)
p <- c(p[1],p[length(p)]) ##bug in pretty for nint=1
xmin <- p[1]
xmax <- p[length(p)]
cex <- par(cex=cex.axis) # Bug in R: cex= ignored in
# axis( )
axis(side=1, at=(p-xmin)/(xmax-xmin), labels=format(p),
pos=y, cex=cex.axis)
par(cex=cex)
if(mgroup)
scat1d((x-xmin)/(xmax-xmin), y=y, bottom.align=bottom.align,
minf=.075, frac=sc(.02,.005), ...)
else for(g in 1:ngroup)
{
j <- group == levels(group)[g]
scat1d((x[j]-xmin)/(xmax-xmin), y=y, bottom.align=bottom.align,
col=col.group[g], tfrac=if(N<125) 1 else max(.1, 125/N),
minf=.075, frac=sc(.02,.005), ...)
}
if(!missing(q))
{
quant <- quantile(x, probs=q, na.rm=nna>0)
points((quant-xmin)/(xmax-xmin),
rep(y-.5*charheight,length(q)),
pch=17, cex=.6)
}
} else { ## character or categorical or discrete numeric
if(is.character(x)) x <- as.factor(x)
isna <- is.na(x)
nna <- sum(isna)
if(length(group) != length(x)) {
if(is.data.frame(object))
stop('length of group must equal length of variables in data frame')
group <- rep(1, length(x))
}
tab <- table(group,x)
lev <- dimnames(tab)[[2]]
nl <- length(lev)
if(is.numeric(x))
{
xx <- as.numeric(lev)
xx <- (xx - min(xx)) / (max(xx) - min(xx))
} else {
if(sum(nchar(lev)) > 200)
lev <- substring(lev, 1, max(1, round(200 / length(lev))))
xx <- (0 : (nl - 1)) / (nl - 1)
}
cex <- par(cex=cex.axis)
axis(side=1, at=xx, labels=lev, pos=y, cex=cex.axis, tick=FALSE)
par(cex=cex)
lines(c(0,1), c(y,y))
maxfreq <- max(tab)
for(g in if(ngroup == 0) 1 else 1 : ngroup)
{
tabg <- tab[g,]
if(method.cat == 'bar')
symbols(xx, y + .4 * tabg / maxfreq / 2, add=TRUE,
rectangles=cbind(.02, .4 * tabg / maxfreq),
inches=FALSE,
col=col.group[g])
else text(xx, rep(y + .1, nl), format(tabg),
cex=cex.axis * sqrt(tab / maxfreq),
adj=.5)
}
}
mtext(if(length(labels))labels[i]
else nams[i],
2, 0, at = y, srt = 0, cex = cex.var, adj = 1, las=1)
## las=1 for R (also 3 lines down)
if(show.na && nna > 0)
outerText(fnumna[i], y, cex=cex.var)
}
invisible()
}
histSpike <-
function(x, side=1, nint=100, bins=NULL, frac=.05, minf=NULL, mult.width=1,
type=c('proportion','count','density'),
xlim=range(x),
ylim=c(0, max(f)), xlab=deparse(substitute(x)),
ylab=switch(type, proportion='Proportion',
count ='Frequency',
density ='Density'),
y=NULL, curve=NULL, add=FALSE, minimal=FALSE,
bottom.align=type == 'density',
col=par('col'), lwd=par('lwd'), grid=FALSE, ...)
{
type <- match.arg(type)
if(! minimal) {
if(! add && side != 1)
stop('side must be 1 if add=FALSE')
if(add && type == 'count')
warning('type="count" is ignored if add=TRUE')
}
if(length(y) > 1) {
if(length(y) != length(x))
stop('lengths of x and y must match')
if(length(curve))
warning('curve ignored when y specified')
i <- ! is.na(x + y)
curve <- list(x=x[i], y=y[i])
}
if(length(curve) && !missing(bottom.align) && bottom.align)
warning('bottom.align=T specified with curve or y; ignoring bottom.align')
gfun <- ordGridFun(grid)
x <- x[!is.na(x)]
x <- x[x >= xlim[1] & x <= xlim[2]]
if(type != 'density') {
if(is.character(nint) || length(x) <= 10) {
f <- table(x)
x <- as.numeric(names(f))
} else {
ncut <- nint + 1
if(! length(bins)) bins <- seq(xlim[1], xlim[2], length = ncut)
delta <- (bins[2] - bins[1]) / 2
f <- table(cut(x, c(bins[1] - delta, bins)))
x <- bins
j <- f > 0
x <- x[j]
f <- f[j]
}
if(type == 'proportion') f <- f / sum(f)
} else {
nbar <- logb(length(x), base = 2) + 1
width <- diff(range(x)) / nbar * .75 * mult.width
den <- density(x, width=width, n=200, from=xlim[1], to=xlim[2])
x <- den$x
f <- den$y
}
if(! minimal && ! add) {
if(grid)
stop('add=FALSE not implemented for lattice')
plot(0, 0, xlim=xlim, ylim=ylim, xlab=xlab, ylab=ylab, type='n')
}
if(side == 1 || side == 3) {
l <- 1:2;
ax <- 1
} else {
l <- 3:4;
ax <- 2
}
f <- f / max(f)
if(length(minf)) f <- pmax(f, minf)
if(minimal) {
plot.new() # sets (0,0) to (1,1)
del <- diff(xlim)
usr <- c(xlim[1] - 0.04 * del, xlim[2] + 0.04 * del, 0, 1)
par(mar=c(3.5, 0.5, 0.5, 0.5), mgp=c(2, 0.5, 0), usr=usr)
axis(1, line=0.25)
title(xlab=xlab)
segments(x, rep(0, length(x)), x, f, lwd=lwd, col=col)
return(invisible(xlim))
}
pr <- parGrid(grid)
usr <- pr$usr;
pin <- pr$pin;
uin <- pr$uin
u <- usr[l]
u.opp <- usr[- l]
h <- min(pin) * frac / uin[- ax] * f
h2 <- h / 2
if(length(y) && inherits(y, 'unit')) {
h <- unit(frac, 'npc')
h2 <- unit(frac / 2, 'npc')
}
if(length(curve) || length(y)) {
if(length(curve))
y <- approx(curve, xout=x, rule=2)$y
a <- y - h2; b <- y + h2
} else {
a <- if(side < 3) u.opp[1]
else u.opp[2] - h
b <- if(side < 3) u.opp[1] + h
else u.opp[2]
}
if(ax == 1 && bottom.align && type != 'density') {
a <- a + h2
b <- b + h2
}
if(type == 'density') {
lll <- gfun$lines
## Problem in S+ getting right value of lwd
if(ax == 1)
do.call('lll',list(x,
if(side == 1)b
else a,
lwd=lwd, col=col))
else
do.call('lll',list(if(side == 2)b
else a,
x, lwd=lwd, col=col))
} else {
lll <- gfun$segments
if(ax == 1)
do.call('lll',list(x, a, x, b, lwd=lwd, xpd=frac < 0, col=col))
else
do.call('lll',list(a, x, b, x, lwd=lwd, xpd=frac < 0, col=col))
}
invisible(xlim)
}
if(FALSE)
histSpikep <- function(p, x, y, z, group=NULL, color=NULL, hovertext=NULL,
colors=NULL,
bottom.align=TRUE, tracename='Proportion', ...) {
d <- data.frame(x=rep(x, each=3),
y=rep(y, each=3),
z=rep(z, each=3))
origcolor <- color
if(length(group)) d$group <- rep(group, each=3)
if(length(hovertext)) d$hovertext <- rep(hovertext, each=3)
if(length(color)) d$color <- rep(color, each=3)
n <- nrow(d)
j <- seq(1, n, by=3)
if(length(hovertext)) d$hovertext[j] <- ''
if(! bottom.align) d$y[j] <- d$y[j] - d$z[j] / 2
j <- seq(3, n, by=3)
d$x[j] <- NA
if(length(hovertext)) d$hovertext[j] <- ''
j <- seq(2, n, by=3)
d$y[j] <- d$y[j] + d$z[j] / ifelse(bottom.align, 1, 2)
plotly::plot_ly(d, x=~ x, y=~ y, mode='lines', type='scatter',
line=list(color=d$color, width=1.4), # ...
text=~ hovertext,
hoverinfo=if(length(hovertext)) 'text' else 'none')
}
histboxp <- function(p=plotly::plot_ly(height=height),
x, group=NULL, xlab=NULL,
gmd=TRUE, sd=FALSE, bins=100, wmax=190, mult=7,
connect=TRUE, showlegend=TRUE) {
if (!requireNamespace("plotly"))
stop("This function requires the 'plotly' package.")
if(! length(xlab)) xlab <- label(x, html=TRUE, plot=TRUE,
default=deparse(substitute(x)))
if(! length(group)) group <- rep(1, length(x))
if(length(x) != length(group)) stop('x and group must be same length')
distinct <- unique(x)
distinct <- distinct[! is.na(distinct)]
xmin <- min(distinct)
xr <- x
## Still do slight rounding if < bins distinct values because
## values extremely close to each other won't show otherwise
if((length(distinct) > bins) ||
min(diff(sort(distinct))) < diff(range(distinct)) / (5 * bins)) {
pret <- pretty(x, if(length(distinct) > bins) bins else 5 * bins)
dist <- pret[2] - pret[1]
r <- range(pret)
xr <- r[1] + dist * round((x - r[1]) / dist)
}
mu <- markupSpecs$html
fmt <- function(x) htmlSN(x, digits=5)
y <- 0
dh <- dm <- dq1 <- dq2 <- dq3 <- dgmd <- dsd <- levs <- NULL
group <- as.factor(group)
mis <- is.na(x)
levs <- levels(group)
ng <- length(levs)
Qu <- matrix(NA, nrow=ng, ncol=5)
j <- 0
for(g in levels(group)) {
i <- group == g
j <- j + 1
miss <- sum(mis[i])
if(miss > 0) i <- i & ! mis
if(! any(i)) next
u <- x[i]
ur <- xr[i]
tab <- as.data.frame(table(ur))
z <- as.numeric(as.character(tab$ur))
prop <- tab$Freq / length(ur)
y <- y - 1
dh <- rbind(dh, data.frame(x=z, prop=prop, freq=tab$Freq,
txt=paste0(fmt(z), '<br>', round(prop, 3),
'<br>n=', tab$Freq),
y=y))
dm <- rbind(dm, data.frame(Mean=mean(u), n=length(u), miss=miss, y=y))
if(gmd) {
Gmd <- GiniMd(u)
dgmd <- rbind(dgmd, data.frame(Gmd, x=xmin,
txt=paste0('Gini mean difference:',
fmt(Gmd)),
y=y))
}
if(sd) {
Sd <- sd(u)
dsd <- rbind(dsd, data.frame(sd=Sd, x=xmin,
txt=paste0('SD:', fmt(Sd)),
y=y))
}
probs <- c(0.05, 0.25, 0.5, 0.75, 0.95)
qu <- quantile(u, probs)
Qu[j, ] <- qu
nam <- paste0('Q', mu$sub(probs))
txt <- paste0(nam, ':', fmt(qu))
dq1 <- rbind(dq1, data.frame(Median=qu[3], txt=txt[3], y=y))
dq2 <- rbind(dq2, data.frame(quartiles=qu[c(2,4)], txt=txt[c(2,4)], y=y))
dq3 <- rbind(dq3, data.frame(outer=qu[c(1,5)], txt=txt[c(1,5)], y=y))
}
height <- plotlyParm$heightDotchart(1.2 * ng) + 50 * (gmd & sd)
if(length(.Options$plotlyauto) && .Options$plotlyauto) height <- NULL
dh$prop <- 0.6 * dh$prop / max(dh$prop)
p <- plotly::add_segments(p, data=dh,
x = ~ x,
y = ~ y,
xend = ~ x,
yend = ~ y + prop,
text = ~ txt,
hoverinfo = 'text',
color = I('black'),
name = 'Histogram',
legendgroup = 'Histogram',
showlegend=showlegend)
dm$txt <- with(dm, paste0('Mean:', fmt(Mean), '<br>n=', n,
'<br>', miss, ' missing'))
a <- 0.05
b <- 0.4
k <- (a + b) / 2
w <- (b - a) / 2
p <- plotly::add_markers(p, data=dm, mode='markers', color=I('black'),
x = ~ Mean, y = ~ y - k,
text = ~ txt,
hoverinfo = 'text', size=I(5),
name='Mean', legendgroup='Mean',
showlegend=showlegend)
segs <- function(p, x, y, yend, text, data, color, name, width=2) {
plotly::add_segments(p, data=data,
x=x, y=y,
xend=x, yend=yend,
text=text, hoverinfo='text',
name=name, legendgroup=name,
showlegend=showlegend,
color=color, line=list(width=width))
}
p <- segs(p, x=~Median, y=~y-k-w, yend=~y-k+w, text=~txt,
data=dq1, color=I('black'), name='Median', width=3)
p <- segs(p, x=~quartiles, y=~y-k-w*.8, yend=~y-k+w*.8, text=~txt,
data=dq2, color=I('blue'), name='Quartiles')
onam <- '0.05, 0.95<br>Quantiles'
p <- segs(p, x=~outer, y=~y-k-w*.64, yend=~y-k+w*.64, text=~txt,
data=dq3, color=I('red'), name=onam)
if(connect) {
ys <- -(1 : ng) - k
qs <- function(p, x, xend, color, lg)
plotly::add_segments(p, x=x, xend=xend, y=~ys, yend=~ys,
hoverinfo='none', showlegend=FALSE,
alpha=0.3, color=color,
legendgroup=lg, name='ignored')
p <- qs(p, x= ~ Qu[,1], xend=~ Qu[,2], color=I('red'), lg=onam)
p <- qs(p, x= ~ Qu[,2], xend=~ Qu[,4], color=I('blue'), lg='Quartiles')
p <- qs(p, x= ~ Qu[,4], xend=~ Qu[,5], color=I('red'), lg=onam)
}
gnam <- paste0('Gini ', mu$overbar(paste0('|', htmlGreek('Delta'), '|')))
if(gmd)
p <- plotly::add_segments(p, data=dgmd,
x = ~ x,
y = ~ y - 0.19,
xend = ~ x + Gmd,
yend = ~ y - 0.19,
text = ~ txt,
hoverinfo = 'text',
color = I('light gray'),
name = gnam, legendgroup=gnam,
visible='legendonly',
showlegend=showlegend)
if(sd)
p <- plotly::add_segments(p, data=dsd,
x = ~ x,
y = ~ y - 0.23,
xend = ~ x + sd,
yend = ~ y - 0.23,
text = ~ txt,
hoverinfo = 'text',
color = I('light blue'),
name = 'SD', legendgroup='SD',
visible='legendonly',
showlegend=showlegend)
p <- plotly::layout(p,
margin = list(l=plotlyParm$lrmargin(levs,
wmax=wmax, mult=mult)),
xaxis = list(title=xlab, zeroline=FALSE),
yaxis = list(title='',
tickvals= - (1 : ng),
ticktext = levs))
p
}
dhistboxp <- function(x, group=NULL, strata=NULL, xlab=NULL,
gmd=FALSE, sd=FALSE, bins=100, nmin=5, ff1=1, ff2=1) {
if(! length(group)) group <- rep(1, length(x))
if(length(x) != length(group)) stop('x and group must be same length')
if(! length(strata)) strata <- rep(1, length(x))
if(length(x) != length(strata)) stop('x and strata must be same length')
distinct <- unique(x)
distinct <- distinct[! is.na(distinct)]
xmin <- min(distinct)
xr <- x
ustrata <- sort(unique(strata))
## Still do slight rounding if < bins distinct values because
## values extremely close to each other won't show otherwise
if(length(distinct) > bins ||
min(diff(sort(distinct))) < diff(range(distinct)) / (5 * bins)) {
pret <- pretty(x, if(length(distinct) > bins) bins else 5 * bins)
dist <- pret[2] - pret[1]
r <- range(pret)
xr <- r[1] + dist * round((x - r[1]) / dist)
}
mu <- markupSpecs$html
fmt <- function(x) htmlSN(x, digits=5)
quant <- function(x, probs=0.5) {
x <- x[! is.na(x)]
n <- length(x)
if(! n) return(rep(NA, length(probs)))
if(n < 3) return(quantile(x, probs))
hdquantile(x, probs, se=FALSE)
}
group <- as.factor(group)
mis <- is.na(x)
levs <- levels(group)
ng <- length(levs)
stdel <- diff(range(ustrata)) * 0.025 * ff1
stmin <- min(strata, na.rm=TRUE)
R <- NULL
## Compute maximum proportion in any bin in any group/stratum
prop <- numeric(0)
nn <- integer(0)
j <- 0
for(st in ustrata) {
for(g in levels(group)) {
i <- strata == st & group == g
if(any(i)) {
tab <- table(xr[i])
den <- sum(tab)
if(den > 0) {
j <- j + 1
prop <- c(prop, max(tab) / den)
nn <- c(nn, den)
}
}
}
}
maxp <- if(any(nn >= nmin)) max(prop[nn >= nmin]) else max(prop)
maxp <- min(maxp, wtd.quantile(prop, probs=0.98, weights=nn))
propfac <- stdel / maxp
j <- 0
for(st in ustrata) {
stdir <- 1
ig <- 0
for(g in levels(group)) {
ig <- ig + 1
stdir <- - stdir
stoffset <- stdir * (stdel * floor((ig + 1) / 2))
i <- strata == st & group == g
miss <- sum(mis[i])
if(miss > 0) i <- i & ! mis
if(! any(i)) next
u <- x[i]
ur <- xr[i]
nn <- length(ur)
if(nn >= nmin) {
tab <- as.data.frame(table(ur))
z <- as.numeric(as.character(tab$ur))
prop <- tab$Freq / nn
R <- rbind(R,
data.frame(x=z,
y =st + 0.5 * stdir * stdel, xhi=NA,
yhi=st + 0.5 * stdir * stdel +
stoffset * prop * propfac * ff2,
group=g, strata=st,
txt=paste0(fmt(z), '<br>', round(prop, 3),
'<br>n=', tab$Freq),
type='histogram', connect=NA))
}
med <- quant(u)
R <- rbind(R,
data.frame(x=med, y=st, xhi=NA, yhi=NA,
group=g, strata=st,
txt=paste0('Median:', fmt(med),
'<br>n=', length(u),
'<br>', miss, ' missing'),
type='median', connect=TRUE))
if(gmd) {
gnam <- paste0('Gini ', mu$overbar(paste0('|', htmlGreek('Delta'), '|')))
Gmd <- GiniMd(u)
R <- rbind(R,
data.frame(x = xmin,
xhi = xmin + Gmd,
y = st - stdel * 2,
yhi = NA,
group=g, strata=st,
txt=paste0(gnam, ': ', fmt(Gmd)),
type=gnam, connect=NA))
}
if(sd) {
Sd <- sd(u)
R <- rbind(R,
data.frame(x = xmin,
xhi = xmin + Sd,
y = st - stdel * (if(gmd) 3 else 2),
yhi = NA,
group=g, strata=st,
txt = paste0('SD:', fmt(Sd)),
type = 'SD', connect=NA))
}
if(nn >= nmin) {
probs <- c(0.5, 0.25, 0.75, 0.05, 0.95)
qu <- quant(u, probs)
nam <- paste0('Q', mu$sub(probs))
txt <- paste0(nam, ':', fmt(qu))
mult <- c(1.15, 1, 1, 0.64, 0.64)
yinc <- 0.3 * stdir * stdel * mult
ycenter <- st + stdir * stdel + stoffset * maxp * propfac
R <- rbind(R,
data.frame(x = qu,
xhi = NA,
y = ycenter - yinc,
yhi = ycenter + yinc,
group=g, strata=st,
txt = txt,
type='quantiles', connect=FALSE))
R <- rbind(R,
data.frame(x = min(qu),
xhi = max(qu),
y = ycenter,
yhi = ycenter,
group=g, strata=st,
txt = '',
type='quantiles', connect=FALSE))
}
} ## end groups
} ## end strata
R
}
histboxpM <- function(p=plotly::plot_ly(height=height, width=width),
x, group=NULL,
gmd=TRUE, sd=FALSE, width=NULL, nrows=NULL, ncols=NULL, ...) {
if (!requireNamespace("plotly"))
stop("This function requires the 'plotly' package.")
## See stackoverflow.com/questions/26939121
## stackoverflow.com/questions/39948151
nx <- if(is.data.frame(x)) ncol(x) else 1
ng <- if(length(group)) length(unique(group)) else 1
height <- nx * (plotlyParm$heightDotchart(1.2 * ng) + 50 * (gmd & sd))
height <- min(height, 1700)
auto <- .Options$plotlyauto
if(length(auto) && auto) height <- width <- NULL
nam <- deparse(substitute(x))
if(is.data.frame(x) && ncol(x) == 1) x <- x[[1]]
if(! is.data.frame(x))
return(histboxp(p=p, x=x, group=group,
xlab=labelPlotmath(label(x, default=nam), units(x),
html=TRUE), gmd=gmd, sd=sd, ...))
P <- list()
for(i in 1 : nx) {
y <- x[[i]]
xlab <- labelPlotmath(label(y, default=names(x)[i]), units(y), html=TRUE)
P[[i]] <- histboxp(p, x=y, group=group, xlab=xlab, showlegend=i==nx,
gmd=gmd, sd=sd, ...)
}
if(length(ncols)) nrows <- ceil(ncol(x) / ncols)
else if(! length(nrows)) nrows <- ncol(x)
plotly::subplot(P, nrows=nrows, shareX=FALSE, shareY=FALSE,
titleX=TRUE, margin=c(.02, .02, .05, .04))
}
ecdfpM <- function(x, group=NULL, what=c('F','1-F','f','1-f'), q=NULL,
extra=c(0.025, 0.025), xlab=NULL, ylab=NULL,
height=NULL, width=NULL,
colors=NULL, nrows=NULL, ncols=NULL, ...) {
if (!requireNamespace("plotly"))
stop("This function requires the 'plotly' package.")
auto <- .Options$plotlyauto
if(length(auto) && auto) height <- width <- NULL
what <- match.arg(what)
nam <- deparse(substitute(x))
if(! is.data.frame(x)) x <- data.frame(x)
nx <- ncol(x)
if(! length(group)) group <- rep('', nrow(x))
group <- as.factor(group)
fmt <- function(x) htmlSN(x, digits=5)
trans <- switch(what,
'F' = function(y) y,
'1-F' = function(y) 1 - y,
'f' = function(y) n * y,
'1-f' = function(y) n * (1 - y))
P <- list()
kq <- length(q)
for(i in 1 : nx) {
y <- x[[i]]
rng <- range(y, na.rm=TRUE)
xl <- if(! length(xlab))
labelPlotmath(label(y, default=names(x)[i]), units(y), html=TRUE)
else
xlab[min(length(xlab), i)]
D <- Dq <- NULL
p <- plotly::plot_ly(height=height, width=width)
for(gv in levels(group)) {
j <- group == gv & ! is.na(y)
yg <- sort(y[j])
n <- length(yg)
vals <- unique(yg) # see stats::ecdf
a <- approx(vals, cumsum(tabulate(match(yg, vals))) / n,
method='constant', yleft=0, yright=1, f=0,
ties='ordered', xout=vals)
delta <- diff(rng)
a$x <- c(min(a$x) - extra[1] * delta, a$x, max(a$x) + extra[2] * delta)
a$y <- c(0, a$y, 1)
yg <- a$y
d <- data.frame(x = a$x, y = trans(yg), g=gv)
D <- rbind(D, d)
if(kq) for(k in 1 : kq) {
quant <- min(a$x[yg >= q[k]])
tx <- paste0(q[k], ' quantile of ', names(x)[i], ':', fmt(quant))
if(gv != '') tx <- paste0(tx, '<br>', gv)
Dq <- rbind(Dq,
data.frame(x=rng[1], xe=quant,
y=trans(q[k]), ye=trans(q[k]), g=gv, txt=''),
data.frame(x=quant, xe=quant,
y=trans(q[k]), ye=trans(0), g=gv, txt=tx))
}
}
linet <- if(what %in% c('F', 'f')) 'hv' else 'vh'
p <- plotly::add_lines(p, data=D, x= ~ x, y= ~ y,
showlegend = i == nx,
color= ~ g,
colors=colors,
line=list(shape=linet),
...)
if(kq)