Hi,
Given that cdplot() is used to produce the conditional density of a
categorical y along a numerical x, it seems natural that it could be
used with a date or time x (such as 'POSIXct'). Is this desirable? If
so, I've created a patch that would allow this, by coercing the POSIXct
x variable to produce the density, but use the original POSIXct x to
draw the x axis.
Index: src/library/graphics/R/cdplot.R
===================================================================
--- src/library/graphics/R/cdplot.R (revision 51984)
+++ src/library/graphics/R/cdplot.R (working copy)
@@ -43,8 +43,8 @@
if(!is.null(ylevels))
y <- factor(y, levels = if(is.numeric(ylevels)) levels(y)[ylevels] else
ylevels)
x <- mf[,2]
- if(!is.numeric(x))
- stop("explanatory variable should be numeric")
+ if (!(is.numeric(x) || is(x, "POSIXct")))
+ stop("explanatory variable should be numeric or POSIXct")
## graphical parameters
if(is.null(xlab)) xlab <- names(mf)[2L]
@@ -66,7 +66,8 @@
yaxlabels = NULL, xlim = NULL, ylim = c(0, 1), ...)
{
## check x and y
- if(!is.numeric(x)) stop("explanatory variable should be numeric")
+ if (!(is.numeric(x) || is(x, "POSIXct")))
+ stop("explanatory variable should be numeric or POSIXct")
if(!is.factor(y)) stop("dependent variable should be a factor")
if(!is.null(ylevels))
y <- factor(y, levels = if(is.numeric(ylevels)) levels(y)[ylevels] else
ylevels)
@@ -79,10 +80,12 @@
if(is.null(yaxlabels)) yaxlabels <- levels(y)
## unconditional density of x
- dx <- if(is.null(from) & is.null(to))
- stats::density(x, bw = bw, n = n, ...)
- else
- stats::density(x, bw = bw, from = from, to = to, n = n, ...)
+ xnum <- as.numeric(x)
+ dx <- if (is.null(from) & is.null(to)) {
+ stats::density(xnum, bw = bw, n = n, ...)
+ } else {
+ stats::density(xnum, bw = bw, from = from, to = to, n = n, ...)
+ }
x1 <- dx$x
## setup conditional values
@@ -94,7 +97,7 @@
rval <- list()
for(i in seq_len(ny-1L)) {
- dxi <- stats::density(x[y %in% levels(y)[seq_len(i)]], bw = dx$bw, n =
n,
+ dxi <- stats::density(xnum[y %in% levels(y)[seq_len(i)]], bw = dx$bw,
n = n,
from = min(dx$x), to = max(dx$x), ...)
y1[i,] <- dxi$y/dx$y * yprop[i]
rval[[i]] <- stats::approxfun(x1, y1[i,], rule = 2)
@@ -103,8 +106,8 @@
## use known ranges
y1 <- rbind(0, y1, 1)
- y1 <- y1[,which(x1 >= min(x) & x1 <= max(x))]
- x1 <- x1[x1 >= min(x) & x1 <= max(x)]
+ y1 <- y1[,which(x1 >= min(xnum) & x1 <= max(xnum))]
+ x1 <- x1[x1 >= min(xnum) & x1 <= max(xnum)]
if(is.null(xlim)) xlim <- range(x1)
if(any(ylim < 0) || any(ylim > 1)) {
@@ -120,7 +123,9 @@
for(i in seq_len(NROW(y1)-1))
polygon(c(x1, rev(x1)), c(y1[i+1,], rev(y1[i,])), col = col[i],
border = border)
- axis(1)
+ if (is(x, "POSIXct")) {
+ axis.POSIXct(1, x)
+ } else axis(1)
equidist <- any(diff(y1[,1L]) < tol.ylab)
if(equidist)
--
Seb
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