> that's exactly what I was looking for!
That code has some problems if your time series do not cross at the time
points. E.g., Duncan's code with some diagnostic plotting is:
f0 <- function (site1, site2, x = time(site1), check = FALSE)
{
stopifnot(length(x) == length(site1), length(x) == length(site2),
all(diff(x) > 0))
if (check) {
oldMfrow <- par(mfrow = c(2, 1))
on.exit(par(oldMfrow))
matplot(x, cbind(site1, site2), type = "b")
}
smaller <- pmin(site1, site2)
plot(x, site1, ylim = range(c(site1, site2)), type = "n")
polygon(c(x, rev(x)), c(smaller, rev(site1)), col = "red")
polygon(c(x, rev(x)), c(smaller, rev(site2)), col = "blue")
}
# See how it messes the crossings in
f0(c(0, 1, -1, 0), c(1, 0, -2, 1), check=TRUE)
The following is a quick and dirty way of adding all the crossing
points to the original data sets so the plot is right.
addCrossingPoints <- function (y1, y2, x)
{
stopifnot(length(y1)==length(x), length(y2)==length(x), all(diff(x)>0))
# isCrossingSegment[i]==TRUE means that y1 and y2 cross between
# x[i] and x[i+1] (strictly, not at x[i] or x[i+1]).
i <- seq_len(length(y1) - 1)
isCrossingSegment <- ((y1[i] < y2[i]) & (y1[i+1] > y2[i+1])) |
((y1[i] > y2[i]) & (y1[i+1] < y2[i+1]))
if (any(isCrossingSegment)) {
i <- which(isCrossingSegment)
dx <- x[i+1] - x[i]
m1 <- (y1[i+1] - y1[i]) / dx
m2 <- (y2[i+1] - y2[i]) / dx
newDX <- (y1[i] - y2[i]) / (m2 - m1)
newY <- y1[i] + newDX * m1
o <- order( x <- c(x, x[i] + newDX))
x <- x[o]
y1 <- c(y1, newY)[o]
y2 <- c(y2, newY)[o]
}
list(y1=y1, y2=y2, x=x)
}
# Combine it with Duncan's code to get a better looking plot
f1 <- function(site1, site2, x=time(site1), check = FALSE) {
tmp <- addCrossingPoints(site1, site2, x)
f0(tmp$y1, tmp$y2, tmp$x, check=check)
}
f1(c(0, 1, -1, 0), c(1, 0, -2, 1), check=TRUE)
Bill Dunlap
Spotfire, TIBCO Software
wdunlap tibco.com
> -----Original Message-----
> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
> Behalf
> Of Roland Pape
> Sent: Friday, June 07, 2013 2:51 AM
> To: Duncan Murdoch
> Cc: r-help@r-project.org
> Subject: Re: [R] Conditional coloring of area between curves
>
> Hi Duncan,
>
> that's exactly what I was looking for! The series have common times, so
> that's no
> problem. Thanks a lot!
>
> Roland
> ________________________________________
> Von: Duncan Murdoch [murdoch.dun...@gmail.com]
> Gesendet: Donnerstag, 6. Juni 2013 18:45
> An: Roland Pape
> Cc: r-help@r-project.org
> Betreff: Re: [R] Conditional coloring of area between curves
>
> On 06/06/2013 10:41 AM, Roland Pape wrote:
> > Dear list,
> >
> > I have two time series of temperatures from different sites plotted in the
> > same diagram
> and would like to color the area between the curves differently, dependent on
> whether
> site 1 is cooler than site 2 (colored let's say in blue) or warmer (red).
> While polygone()
> works fine to color the enclosed area in general, I'm struggling with this
> conditional
> coloring. Any help is greatly appreciated!
>
> Suppose the series are named "site1" and "site2", and they have common
> times in a variable "times". Then the following should do what you want:
>
> smaller <- pmin(site1, site2)
> plot(x, site1, ylim = range(c(site1, site2)), type="n")
> polygon(c(x, rev(x)), c(smaller, rev(site1)), col="red")
> polygon(c(x, rev(x)), c(smaller, rev(site2)), col="blue")
>
> If the times for the two series are different it's a little harder;
> first you need to give them common times, and that will depend on how
> you decide to evaluate the values between observations. Probably linear
> interpolation (using approx()) is fine, but it's up to you.
>
> Duncan Murdoch
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
