[R] Peak Over Threshold values
Dear List I hope you can help me: I’ve got a dataframe (df) within which I am looking for Peak Over Threshold values as well as the length of the events. An event starts when walevel equals 5.8 and it should end when walevel equals the lower threshold value (5.35). I tried “clusters (…)” from “evd package”, and varied r (see example) but it did not work for all events (again see example). walevel <- c(5.75, 5.75, 5.75, 5.76, 5.80, 5.82, 5.85, 5.86, 5.91, 5.91, 5.88, 5.92, 5.99, 6.02, 6.00, 6.08, 6.11, 6.10, 6.10, 6.11, 6.14, 6.12, 6.15, 6.17, 6.15, 6.08, 6.01, 5.95, 5.89, 5.83, 5.77, 5.72, 5.70, 5.65, 5.59, 5.51, 5.43, 5.33, 5.30, 5.25, 5.22, 5.21, 5.19, 5.19, 5.19, 5.13, 5.15, 5.07, 5.04, 5.02, 4.99, 5.05, 5.07, 5.12, 5.17, 5.22, 5.32, 5.29, 5.33, 5.33, 5.36, 5.37, 5.42, 5.43, 5.48, 5.55, 5.57, 5.66, 5.68, 5.72, 5.77, 5.79, 5.81, 5.80, 5.80, 5.77, 5.72, 5.70, 5.66, 5.62, 5.62, 5.61, 5.59, 5.57, 5.51, 5.47, 5.41, 5.39, 5.40, 5.40, 5.42, 5.45, 5.47, 5.50, 5.50, 5.49, 5.43, 5.39, 5.33, 5.26) day <- c(1:100) df <- data.frame(day,walevel) library(evd) clusters(df$walevel, u = 5.80, r = 1, ulow = 5.35, cmax = T, plot = T) clusters(df$walevel, u = 5.80, r = 50, ulow = 5.35, cmax = T, plot = T) What have I done wrong? Tonja __ 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] Peak Over Threshold values
I’m sorry, but that‘s not exactly what I was looking for. I obviously didn’t explain properly: Within my dataframe (df) I would like to find POT values that are not linked. In my definition two maximum values are linked if walevel does not fall below a certain value (the lower threshold value). walevel <- c(5.75, 5.75, 5.75, 5.76, 5.80, 5.82, 5.85, 5.86, 5.91, 5.91, 5.88, 5.92, 5.99, 6.02, 6.00, 6.08, 6.11, 6.10, 6.10, 6.11, 6.14, 6.12, 6.15, 6.17, 6.15, 6.08, 6.01, 5.95, 5.89, 5.83, 5.77, 5.72, 5.70, 5.65, 5.59, 5.51, 5.43, 5.33, 5.30, 5.25, 5.22, 5.21, 5.19, 5.19, 5.19, 5.13, 5.15, 5.07, 5.04, 5.02, 4.99, 5.05, 5.07, 5.12, 5.17, 5.22, 5.32, 5.29, 5.33, 5.33, 5.36, 5.37, 5.42, 5.43, 5.48, 5.55, 5.57, 5.66, 5.68, 5.72, 5.77, 5.79, 5.81, 5.80, 5.80, 5.77, 5.72, 5.70, 5.66, 5.62, 5.62, 5.61, 5.59, 5.57, 5.51, 5.47, 5.41, 5.39, 5.40, 5.40, 5.42, 5.45, 5.47, 5.50, 5.50, 5.49, 5.43, 5.39, 5.33, 5.26) day <- c(1:100) df <- data.frame(day,walevel) For example in my dataframe a threshold value = 5.45 and an lower threshold value = 5.3 should lead to two maximum values because between the 2^nd and 3^rd peak walevel does not fall below the lower threshold value. With “clusters (…)” from “evd package”, I could find out POT values but even though I set a lower threshold value for my example dataframe I would get three maximum values instead of two. library(evd) clusters(df$walevel,u =5.45, ulow= 5.3, r = 1, cmax=T) clusters(df$walevel,u =5.45, ulow= 5.3, r = 1, plot=T) Changing r to 30 (for example) connects the 2^nd and 3^rd maximum events and gives out the right ‘end’ for the first extreme event but not for the second event. (Also I’d rather not use a time interval to prove that the events are linked) clusters(df$walevel,u =5.45, ulow= 5.3, r = 30, cmax=T) clusters(df$walevel,u =5.45, ulow= 5.3, r = 30, plot=T) What went wrong??? Tonja -Ursprüngliche Nachricht- How about? hi.rle<-rle(walevel>5.79) lo.rle<-rle(walevel<5.36) plot(walevel) abline(h=5.8,col=2,lty=3) abline(h=5.35,col=3,lty=3) hi.lo.rle<-sort(c(cumsum(hi.rle$lengths),cumsum(lo.rle$lengths))) abline(v=hi.lo.rle) You can use the $values from the rle to sort things out. Probably want to ignore the end point at length(walevel). -- Clint Bowman INTERNET: cl...@ecy.wa.gov Air Quality Modeler INTERNET: cl...@math.utah.edu Department of Ecology VOICE: (360) 407-6815 PO Box 47600 FAX: (360) 407-7534 Olympia, WA 98504-7600 On Wed, 26 May 2010, Vito Muggeo (UniPa) wrote: > dear Tonja, > By plotting your data > > plot(df) > > it seems to me that you are looking for a piecewise linear relationships. If > this is the case, have a look to the package segmented. You have to specify > or not the number and the starting values for the breakpoints > > library(segmented) > olm<-lm(walevel~day) > > #specify number and starting values for the breakpoints.. > oseg<-segmented(olm, seg.Z=~day, psi=c(20,50,80)) > plot(oseg,add=TRUE,col=2) > oseg$psi > > #or you can avoid to specify starting values for psi > oseg<-segmented(olm, seg.Z=~day, > psi=NA,control=seg.control(stop.if.error=FALSE,K=30)) > > plot(oseg,add=TRUE,col=2) > oseg$psi > > > best, > vito > > > Tonja Krueger ha scritto: >> Dear List >> >> I hope you can help me: I’ve got a dataframe (df) within which I am >> looking >> for Peak Over Threshold values as well as the length of the events. An >> event >> starts when walevel equals 5.8 and it should end when walevel equals >> the >> lower threshold value (5.35). >> >> I tried “clusters (…)” from “evd package”, and varied r (see example) >> but it >> did not work for all events (again see example). >> >> walevel <- c(5.75, 5.75, 5.75, 5.76, 5.80, 5.82, 5.85, 5.86, 5.91, >> 5.91, >> 5.88, 5.92, 5.99, 6.02, 6.00, 6.08, 6.11, 6.10, 6.10, 6.11, 6.14, 6.12, >> 6.15, 6.17, 6.15, 6.08, 6.01, 5.95, 5.89, 5.83, 5.77, 5.72, 5.70, 5.65, >> 5.59, 5.51, 5.43, 5.33, 5.30, 5.25, 5.22, 5.21, 5.19, 5.19, 5.19, 5.13, >> 5.15, 5.07, 5.04, 5.02, 4.99, 5.05, 5.07, 5.12, 5.17, 5.22, 5.32, 5.29, >> 5.33, 5.33, 5.36, 5.37, 5.42, 5.43, 5.48, 5.55, 5.57, 5.66, 5.68, 5.72, >> 5.77, 5.79, 5.81, 5.80, 5.80, 5.77, 5.72, 5.70, 5.66, 5.62, 5.62, 5.61, >> 5.59, 5.57, 5.51, 5.47, 5.41, 5.39, 5.40, 5.40, 5.42, 5.45, 5.47, 5.50, >> 5.50, 5.49, 5.43, 5.39, 5.33, 5.26) >> >> day <- c(1:100) >> >> df <- data.frame(day,walevel) >> >> library(evd) >> clusters(df$walevel, u = 5.80, r = 1, ulow = 5.35, cmax = T, plot = T) >> clusters(df$walevel, u = 5.80, r = 50, ulow = 5.35, cmax = T, plot = T) >> >> What have I done wrong? >> >> Tonja >> __ >> R-help@r-project.org mailing list >> [
Re: [R] Peak Over Threshold values
dear Tonja, By plotting your data plot(df) it seems to me that you are looking for a piecewise linear relationships. If this is the case, have a look to the package segmented. You have to specify or not the number and the starting values for the breakpoints library(segmented) olm<-lm(walevel~day) #specify number and starting values for the breakpoints.. oseg<-segmented(olm, seg.Z=~day, psi=c(20,50,80)) plot(oseg,add=TRUE,col=2) oseg$psi #or you can avoid to specify starting values for psi oseg<-segmented(olm, seg.Z=~day, psi=NA,control=seg.control(stop.if.error=FALSE,K=30)) plot(oseg,add=TRUE,col=2) oseg$psi best, vito Tonja Krueger ha scritto: Dear List I hope you can help me: I’ve got a dataframe (df) within which I am looking for Peak Over Threshold values as well as the length of the events. An event starts when walevel equals 5.8 and it should end when walevel equals the lower threshold value (5.35). I tried “clusters (…)” from “evd package”, and varied r (see example) but it did not work for all events (again see example). walevel <- c(5.75, 5.75, 5.75, 5.76, 5.80, 5.82, 5.85, 5.86, 5.91, 5.91, 5.88, 5.92, 5.99, 6.02, 6.00, 6.08, 6.11, 6.10, 6.10, 6.11, 6.14, 6.12, 6.15, 6.17, 6.15, 6.08, 6.01, 5.95, 5.89, 5.83, 5.77, 5.72, 5.70, 5.65, 5.59, 5.51, 5.43, 5.33, 5.30, 5.25, 5.22, 5.21, 5.19, 5.19, 5.19, 5.13, 5.15, 5.07, 5.04, 5.02, 4.99, 5.05, 5.07, 5.12, 5.17, 5.22, 5.32, 5.29, 5.33, 5.33, 5.36, 5.37, 5.42, 5.43, 5.48, 5.55, 5.57, 5.66, 5.68, 5.72, 5.77, 5.79, 5.81, 5.80, 5.80, 5.77, 5.72, 5.70, 5.66, 5.62, 5.62, 5.61, 5.59, 5.57, 5.51, 5.47, 5.41, 5.39, 5.40, 5.40, 5.42, 5.45, 5.47, 5.50, 5.50, 5.49, 5.43, 5.39, 5.33, 5.26) day <- c(1:100) df <- data.frame(day,walevel) library(evd) clusters(df$walevel, u = 5.80, r = 1, ulow = 5.35, cmax = T, plot = T) clusters(df$walevel, u = 5.80, r = 50, ulow = 5.35, cmax = T, plot = T) What have I done wrong? Tonja __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- Vito M.R. Muggeo Dip.to Sc Statist e Matem `Vianelli' Università di Palermo viale delle Scienze, edificio 13 90128 Palermo - ITALY tel: 091 23895240 fax: 091 485726/485612 http://dssm.unipa.it/vmuggeo __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Peak Over Threshold values
How about? hi.rle<-rle(walevel>5.79) lo.rle<-rle(walevel<5.36) plot(walevel) abline(h=5.8,col=2,lty=3) abline(h=5.35,col=3,lty=3) hi.lo.rle<-sort(c(cumsum(hi.rle$lengths),cumsum(lo.rle$lengths))) abline(v=hi.lo.rle) You can use the $values from the rle to sort things out. Probably want to ignore the end point at length(walevel). -- Clint BowmanINTERNET: cl...@ecy.wa.gov Air Quality Modeler INTERNET: cl...@math.utah.edu Department of Ecology VOICE: (360) 407-6815 PO Box 47600FAX:(360) 407-7534 Olympia, WA 98504-7600 On Wed, 26 May 2010, Vito Muggeo (UniPa) wrote: dear Tonja, By plotting your data plot(df) it seems to me that you are looking for a piecewise linear relationships. If this is the case, have a look to the package segmented. You have to specify or not the number and the starting values for the breakpoints library(segmented) olm<-lm(walevel~day) #specify number and starting values for the breakpoints.. oseg<-segmented(olm, seg.Z=~day, psi=c(20,50,80)) plot(oseg,add=TRUE,col=2) oseg$psi #or you can avoid to specify starting values for psi oseg<-segmented(olm, seg.Z=~day, psi=NA,control=seg.control(stop.if.error=FALSE,K=30)) plot(oseg,add=TRUE,col=2) oseg$psi best, vito Tonja Krueger ha scritto: Dear List I hope you can help me: I’ve got a dataframe (df) within which I am looking for Peak Over Threshold values as well as the length of the events. An event starts when walevel equals 5.8 and it should end when walevel equals the lower threshold value (5.35). I tried “clusters (…)” from “evd package”, and varied r (see example) but it did not work for all events (again see example). walevel <- c(5.75, 5.75, 5.75, 5.76, 5.80, 5.82, 5.85, 5.86, 5.91, 5.91, 5.88, 5.92, 5.99, 6.02, 6.00, 6.08, 6.11, 6.10, 6.10, 6.11, 6.14, 6.12, 6.15, 6.17, 6.15, 6.08, 6.01, 5.95, 5.89, 5.83, 5.77, 5.72, 5.70, 5.65, 5.59, 5.51, 5.43, 5.33, 5.30, 5.25, 5.22, 5.21, 5.19, 5.19, 5.19, 5.13, 5.15, 5.07, 5.04, 5.02, 4.99, 5.05, 5.07, 5.12, 5.17, 5.22, 5.32, 5.29, 5.33, 5.33, 5.36, 5.37, 5.42, 5.43, 5.48, 5.55, 5.57, 5.66, 5.68, 5.72, 5.77, 5.79, 5.81, 5.80, 5.80, 5.77, 5.72, 5.70, 5.66, 5.62, 5.62, 5.61, 5.59, 5.57, 5.51, 5.47, 5.41, 5.39, 5.40, 5.40, 5.42, 5.45, 5.47, 5.50, 5.50, 5.49, 5.43, 5.39, 5.33, 5.26) day <- c(1:100) df <- data.frame(day,walevel) library(evd) clusters(df$walevel, u = 5.80, r = 1, ulow = 5.35, cmax = T, plot = T) clusters(df$walevel, u = 5.80, r = 50, ulow = 5.35, cmax = T, plot = T) What have I done wrong? Tonja __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Peak Over Threshold values
Perhaps not elegant, but does the job
threshold <- 5.45
meetThreshold <- walevel >= threshold
d <- rle(meetThreshold)
startPos <- c(1, 1 + cumsum(d$lengths[-length(d$lengths)]))
abv <- which(d$values == TRUE)
p.o.t <- data.frame()
for (i in seq( along = abv ) ) {
a <- startPos[abv[i]]
b <- a + (d$lengths[abv[i]] - 1)
e <- which.max(walevel[a:b])
p.o.t <- rbind( p.o.t, data.frame(
pos = a + e - 1,
val = walevel[a:b][e]
) )
}
plot (
day,
walevel, type = 'l'
)
points(
p.o.t$pos,
p.o.t$val,
col = 'red'
)
abline(h = threshold, lty = 2, col = 'red')
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of Tonja Krueger
Sent: Thursday, May 27, 2010 1:47 AM
To: Vito Muggeo (UniPa); Clint Bowman
Cc: r-help@r-project.org
Subject: [R] Peak Over Threshold values
I'm sorry, but that's not exactly what I was looking for. I obviously
didn't explain properly:
Within my dataframe (df) I would like to find POT values that are not
linked. In my definition two maximum values are linked if walevel does not
fall below a certain value (the lower threshold value).
walevel <- c(5.75, 5.75, 5.75, 5.76, 5.80, 5.82, 5.85, 5.86, 5.91, 5.91,
5.88, 5.92, 5.99, 6.02, 6.00, 6.08, 6.11, 6.10, 6.10, 6.11, 6.14, 6.12,
6.15, 6.17, 6.15, 6.08, 6.01, 5.95, 5.89, 5.83, 5.77, 5.72, 5.70, 5.65,
5.59, 5.51, 5.43, 5.33, 5.30, 5.25, 5.22, 5.21, 5.19, 5.19, 5.19, 5.13,
5.15, 5.07, 5.04, 5.02, 4.99, 5.05, 5.07, 5.12, 5.17, 5.22, 5.32, 5.29,
5.33, 5.33, 5.36, 5.37, 5.42, 5.43, 5.48, 5.55, 5.57, 5.66, 5.68, 5.72,
5.77, 5.79, 5.81, 5.80, 5.80, 5.77, 5.72, 5.70, 5.66, 5.62, 5.62, 5.61,
5.59, 5.57, 5.51, 5.47, 5.41, 5.39, 5.40, 5.40, 5.42, 5.45, 5.47, 5.50,
5.50, 5.49, 5.43, 5.39, 5.33, 5.26)
day <- c(1:100)
df <- data.frame(day,walevel)
For example in my dataframe a threshold value = 5.45 and an lower threshold
value = 5.3 should lead to two maximum values because between the 2^nd and
3^rd peak walevel does not fall below the lower threshold value.
With "clusters (...)" from "evd package", I could find out POT values but
even though I set a lower threshold value for my example dataframe I would
get three maximum values instead of two.
library(evd)
clusters(df$walevel,u =5.45, ulow= 5.3, r = 1, cmax=T)
clusters(df$walevel,u =5.45, ulow= 5.3, r = 1, plot=T)
Changing r to 30 (for example) connects the 2^nd and 3^rd maximum events and
gives out the right 'end' for the first extreme event but not for the second
event. (Also I'd rather not use a time interval to prove that the events are
linked)
clusters(df$walevel,u =5.45, ulow= 5.3, r = 30, cmax=T)
clusters(df$walevel,u =5.45, ulow= 5.3, r = 30, plot=T)
What went wrong???
Tonja
-Ursprüngliche Nachricht-
How about?
hi.rle<-rle(walevel>5.79)
lo.rle<-rle(walevel<5.36)
plot(walevel)
abline(h=5.8,col=2,lty=3)
abline(h=5.35,col=3,lty=3)
hi.lo.rle<-sort(c(cumsum(hi.rle$lengths),cumsum(lo.rle$lengths)))
abline(v=hi.lo.rle)
You can use the $values from the rle to sort things out. Probably
want to ignore the end point at length(walevel).
--
Clint Bowman INTERNET: cl...@ecy.wa.gov
Air Quality Modeler INTERNET: cl...@math.utah.edu
Department of Ecology VOICE: (360) 407-6815
PO Box 47600 FAX: (360) 407-7534
Olympia, WA 98504-7600
On Wed, 26 May 2010, Vito Muggeo (UniPa) wrote:
> dear Tonja,
> By plotting your data
>
> plot(df)
>
> it seems to me that you are looking for a piecewise linear relationships.
If
> this is the case, have a look to the package segmented. You have to
specify
> or not the number and the starting values for the breakpoints
>
> library(segmented)
> olm<-lm(walevel~day)
>
> #specify number and starting values for the breakpoints..
> oseg<-segmented(olm, seg.Z=~day, psi=c(20,50,80))
> plot(oseg,add=TRUE,col=2)
> oseg$psi
>
> #or you can avoid to specify starting values for psi
> oseg<-segmented(olm, seg.Z=~day,
> psi=NA,control=seg.control(stop.if.error=FALSE,K=30))
>
> plot(oseg,add=TRUE,col=2)
> oseg$psi
>
>
> best,
> vito
>
>
> Tonja Krueger ha scritto:
>> Dear List
>>
>> I hope you can help me: I've got a dataframe (df) within which I am
>> looking
>> for Peak Over Threshold values as well as the length of the events. An
>> event
>> starts when walevel equals 5.8 and it should end when walevel equals
>> the
>> lower threshold value (5.35).
>>
>> I tried "clusters (
Re: [R] Peak Over Threshold values
Here is another version, loopless, but still
a bit clumsy (can the call to which be removed?):
f <- function (x = walevel,
startThreshhold = 5.45,
stopThreshhold = 5.3,
plot = TRUE)
{
stopifnot(startThreshhold > stopThreshhold)
isFirstInRun <- function(x) c(TRUE, x[-1] != x[-length(x)])
isLastInRun <- function(x) c(x[-1] != x[-length(x)], TRUE)
isOverStart <- x >= startThreshhold
isOverStop <- x >= stopThreshhold
possibleStartPt <- which(isFirstInRun(isOverStart) & isOverStart)
possibleStopPt <- which(isLastInRun(isOverStop) & isOverStop)
pts <- c(possibleStartPt, possibleStopPt)
names(pts) <- rep(c("start", "stop"),
c(length(possibleStartPt), length(possibleStopPt)))
pts <- pts[order(pts)]
tmp <- isFirstInRun(names(pts))
start <- pts[tmp & names(pts) == "start"]
stop <- pts[tmp & names(pts) == "stop"]
if (length(stop) > length(start)) {
# i.e., when first downcrossing happens before
# first upcrossing
stop <- stop[-1]
}
if (plot) {
plot(x, cex = 0.5)
abline(h = c(startThreshhold, stopThreshhold))
abline(v = start, col = "green")
abline(v = stop, col = "red")
}
data.frame(start = start, stop = stop)
}
# define the data in the original message and call f().
The isFirstInRun and isLastInRun functions do the
first part of the calculation that rle does and
avoid the cumsum(diff()) roundtrip that
cumsum(rle()$lengths) involves and their names
make it clearer what I'm trying to do.
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
> Hutchinson,David [PYR]
> Sent: Thursday, May 27, 2010 10:41 AM
> To: Tonja Krueger
> Cc: r-help@r-project.org
> Subject: Re: [R] Peak Over Threshold values
>
> Perhaps not elegant, but does the job
>
> threshold <- 5.45
> meetThreshold <- walevel >= threshold
>
> d <- rle(meetThreshold)
> startPos <- c(1, 1 + cumsum(d$lengths[-length(d$lengths)]))
>
> abv <- which(d$values == TRUE)
> p.o.t <- data.frame()
>
> for (i in seq( along = abv ) ) {
> a <- startPos[abv[i]]
> b <- a + (d$lengths[abv[i]] - 1)
> e <- which.max(walevel[a:b])
> p.o.t <- rbind( p.o.t, data.frame(
>pos = a + e - 1,
>val = walevel[a:b][e]
>) )
> }
>
> plot (
> day,
> walevel, type = 'l'
> )
>
> points(
> p.o.t$pos,
> p.o.t$val,
> col = 'red'
> )
>
> abline(h = threshold, lty = 2, col = 'red')
>
> -Original Message-
> From: r-help-boun...@r-project.org
> [mailto:r-help-boun...@r-project.org] On Behalf Of Tonja Krueger
> Sent: Thursday, May 27, 2010 1:47 AM
> To: Vito Muggeo (UniPa); Clint Bowman
> Cc: r-help@r-project.org
> Subject: [R] Peak Over Threshold values
>
>
>I'm sorry, but that's not exactly what I was looking for.
> I obviously
>didn't explain properly:
>
>Within my dataframe (df) I would like to find POT values
> that are not
>linked. In my definition two maximum values are linked if
> walevel does not
>fall below a certain value (the lower threshold value).
>
>walevel <- c(5.75, 5.75, 5.75, 5.76, 5.80, 5.82, 5.85,
> 5.86, 5.91, 5.91,
>5.88, 5.92, 5.99, 6.02, 6.00, 6.08, 6.11, 6.10, 6.10,
> 6.11, 6.14, 6.12,
>6.15, 6.17, 6.15, 6.08, 6.01, 5.95, 5.89, 5.83, 5.77,
> 5.72, 5.70, 5.65,
>5.59, 5.51, 5.43, 5.33, 5.30, 5.25, 5.22, 5.21, 5.19,
> 5.19, 5.19, 5.13,
>5.15, 5.07, 5.04, 5.02, 4.99, 5.05, 5.07, 5.12, 5.17,
> 5.22, 5.32, 5.29,
>5.33, 5.33, 5.36, 5.37, 5.42, 5.43, 5.48, 5.55, 5.57,
> 5.66, 5.68, 5.72,
>5.77, 5.79, 5.81, 5.80, 5.80, 5.77, 5.72, 5.70, 5.66,
> 5.62, 5.62, 5.61,
>5.59, 5.57, 5.51, 5.47, 5.41, 5.39, 5.40, 5.40, 5.42,
> 5.45, 5.47, 5.50,
>5.50, 5.49, 5.43, 5.39, 5.33, 5.26)
>
>day <- c(1:100)
>
>df <- data.frame(day,walevel)
>
>For example in my dataframe a threshold value = 5.45 and
> an lower threshold
>value = 5.3 should lead to two maximum values because
> between the 2^nd and
>3^rd peak walevel does not fall below the lower threshold value.
>
>With "clusters (...)" from "evd package", I could find
> out POT values but
>even though I set a lower threshold value for my example
> dataframe I would
>get three maximum values instead of two.
>
>library(evd)
>
Re: [R] Peak Over Threshold values
> -Original Message-
> From: r-help-boun...@r-project.org
> [mailto:r-help-boun...@r-project.org] On Behalf Of William Dunlap
> Sent: Thursday, May 27, 2010 12:24 PM
> To: Hutchinson,David [PYR]; Tonja Krueger
> Cc: r-help@r-project.org
> Subject: Re: [R] Peak Over Threshold values
>
> Here is another version, loopless, but still
> a bit clumsy (can the call to which be removed?):
Note that avoiding loops is mostly for
the aesthetic effect. On my aging laptop
the following loopy and vector-growing version
takes 3 seconds on a million-long vector
while the non-loopy one takes 0.22 seconds
(timings done with plot=FALSE). That is
a nice ratio but not much of a difference.
f0 <- function (x = walevel,
startThreshhold = 5.45,
stopThreshhold = 5.3,
plot = TRUE)
{
stopifnot(startThreshhold > stopThreshhold)
inRun <- FALSE
start <- integer()
stop <- integer()
for (i in seq_along(x)) {
if (inRun) {
if (x[i] < stopThreshhold) {
stop[length(stop) + 1] <- i - 1
inRun <- FALSE
}
}
else {
if (x[i] > startThreshhold) {
start[length(start) + 1] <- i
inRun <- TRUE
}
}
}
if (inRun)
stop[length(stop) + 1] <- length(x)
if (length(stop) > length(start))
stop <- stop[-1]
if (plot) {
plot(x, cex = 0.5)
abline(h = c(startThreshhold, stopThreshhold))
abline(v = start, col = "green")
abline(v = stop, col = "red")
}
data.frame(start = start, stop = stop)
}
>
> f <- function (x = walevel,
>startThreshhold = 5.45,
>stopThreshhold = 5.3,
>plot = TRUE)
> {
> stopifnot(startThreshhold > stopThreshhold)
> isFirstInRun <- function(x) c(TRUE, x[-1] != x[-length(x)])
> isLastInRun <- function(x) c(x[-1] != x[-length(x)], TRUE)
> isOverStart <- x >= startThreshhold
> isOverStop <- x >= stopThreshhold
> possibleStartPt <- which(isFirstInRun(isOverStart) & isOverStart)
> possibleStopPt <- which(isLastInRun(isOverStop) & isOverStop)
> pts <- c(possibleStartPt, possibleStopPt)
> names(pts) <- rep(c("start", "stop"),
> c(length(possibleStartPt), length(possibleStopPt)))
> pts <- pts[order(pts)]
> tmp <- isFirstInRun(names(pts))
> start <- pts[tmp & names(pts) == "start"]
> stop <- pts[tmp & names(pts) == "stop"]
> if (length(stop) > length(start)) {
> # i.e., when first downcrossing happens before
> # first upcrossing
> stop <- stop[-1]
> }
> if (plot) {
> plot(x, cex = 0.5)
> abline(h = c(startThreshhold, stopThreshhold))
> abline(v = start, col = "green")
> abline(v = stop, col = "red")
> }
> data.frame(start = start, stop = stop)
> }
>
> # define the data in the original message and call f().
>
> The isFirstInRun and isLastInRun functions do the
> first part of the calculation that rle does and
> avoid the cumsum(diff()) roundtrip that
> cumsum(rle()$lengths) involves and their names
> make it clearer what I'm trying to do.
>
> Bill Dunlap
> Spotfire, TIBCO Software
> wdunlap tibco.com
>
> > -Original Message-
> > From: r-help-boun...@r-project.org
> > [mailto:r-help-boun...@r-project.org] On Behalf Of
> > Hutchinson,David [PYR]
> > Sent: Thursday, May 27, 2010 10:41 AM
> > To: Tonja Krueger
> > Cc: r-help@r-project.org
> > Subject: Re: [R] Peak Over Threshold values
> >
> > Perhaps not elegant, but does the job
> >
> > threshold <- 5.45
> > meetThreshold <- walevel >= threshold
> >
> > d <- rle(meetThreshold)
> > startPos <- c(1, 1 + cumsum(d$lengths[-length(d$lengths)]))
> >
> > abv <- which(d$values == TRUE)
> > p.o.t <- data.frame()
> >
> > for (i in seq( along = abv ) ) {
> > a <- startPos[abv[i]]
> > b <- a + (d$lengths[abv[i]] - 1)
> > e <- which.max(walevel[a:b])
> > p.o.t <- rbind( p.o.t, data.frame(
> > pos = a + e - 1,
> >val = walevel[a:b][e]
> >) )
> > }
> >
> > plot (
> > day,
> > walevel, type = 'l'
> > )
> >
> > points(
> > p.o.t$pos,
> > p.o.t$val,
> > col = 'red'
> > )
> >
> > abline(h = threshold, lty = 2, col = 'red')
> >
Re: [R] Peak Over Threshold values
Thanks a lot for your help. That’s the time period I was looking for.
I’ve got one more question: for further analyses I need the respective maximum
values
within these time periods (between the green and red lines). Preferably in
combination
with the date the maximum event happened.
Thank you
in advance,
Tonja
-Ursprüngliche Nachricht-
Von: William Dunlap
Gesendet: 27.05.2010 22:13:21
An: "Hutchinson,David [PYR]" ,Tonja Krueger
Betreff: RE: [R] Peak Over Threshold values
>> -Original Message-
>> From: r-help-boun...@r-project.org
>> [mailto:r-help-boun...@r-project.org] On Behalf Of William Dunlap
>> Sent: Thursday, May 27, 2010 12:24 PM
>> To: Hutchinson,David [PYR]; Tonja Krueger
>> Cc: r-help@r-project.org
>> Subject: Re: [R] Peak Over Threshold values
>>
>> Here is another version, loopless, but still
>> a bit clumsy (can the call to which be removed?):
>
>Note that avoiding loops is mostly for
>the aesthetic effect. On my aging laptop
>the following loopy and vector-growing version
>takes 3 seconds on a million-long vector
>while the non-loopy one takes 0.22 seconds
>(timings done with plot=FALSE). That is
>a nice ratio but not much of a difference.
>
>f0 <- function (x = walevel,
>startThreshhold = 5.45,
>stopThreshhold = 5.3,
>plot = TRUE)
>{
>stopifnot(startThreshhold > stopThreshhold)
>inRun <- FALSE
>start <- integer()
>stop <- integer()
>for (i in seq_along(x)) {
>if (inRun) {
>if (x[i] < stopThreshhold) {
>stop[length(stop) + 1] <- i - 1
>inRun <- FALSE
>}
>}
>else {
>if (x[i] > startThreshhold) {
>start[length(start) + 1] <- i
>inRun <- TRUE
>}
>}
>}
>if (inRun)
>stop[length(stop) + 1] <- length(x)
>if (length(stop) > length(start))
>stop <- stop[-1]
>if (plot) {
>plot(x, cex = 0.5)
>abline(h = c(startThreshhold, stopThreshhold))
>abline(v = start, col = "green")
>abline(v = stop, col = "red")
>}
>data.frame(start = start, stop = stop)
>}
>
>>
>> f <- function (x = walevel,
>>startThreshhold = 5.45,
>>stopThreshhold = 5.3,
>>plot = TRUE)
>> {
>> stopifnot(startThreshhold > stopThreshhold)
>> isFirstInRun <- function(x) c(TRUE, x[-1] != x[-length(x)])
>> isLastInRun <- function(x) c(x[-1] != x[-length(x)], TRUE)
>> isOverStart <- x >= startThreshhold
>> isOverStop <- x >= stopThreshhold
>> possibleStartPt <- which(isFirstInRun(isOverStart) & isOverStart)
>> possibleStopPt <- which(isLastInRun(isOverStop) & isOverStop)
>> pts <- c(possibleStartPt, possibleStopPt)
>> names(pts) <- rep(c("start", "stop"),
>> c(length(possibleStartPt), length(possibleStopPt)))
>> pts <- pts[order(pts)]
>> tmp <- isFirstInRun(names(pts))
>> start <- pts[tmp & names(pts) == "start"]
>> stop <- pts[tmp & names(pts) == "stop"]
>> if (length(stop) > length(start)) {
>> # i.e., when first downcrossing happens before
>> # first upcrossing
>> stop <- stop[-1]
>> }
>> if (plot) {
>> plot(x, cex = 0.5)
>> abline(h = c(startThreshhold, stopThreshhold))
>> abline(v = start, col = "green")
>> abline(v = stop, col = "red")
>> }
>> data.frame(start = start, stop = stop)
>> }
>>
>> # define the data in the original message and call f().
>>
>> The isFirstInRun and isLastInRun functions do the
>> first part of the calculation that rle does and
>> avoid the cumsum(diff()) roundtrip that
>> cumsum(rle()$lengths) involves and their names
>> make it clearer what I'm trying to do.
>>
>> 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
>> > Hutchinson,David [PYR]
>> > Sent: Thursday, May 27, 2010 10:41 AM
>> > To: Tonja Krueger
>> > Cc: r-help@r-project.org
>> > Subject: Re: [R] Peak Over Threshold values
>> >
>> > Perhaps not elegant, but does the job
&g
Re: [R] Peak Over Threshold values
> -Original Message-
> From: Tonja Krueger [mailto:tonja.krue...@web.de]
> Sent: Monday, May 31, 2010 2:03 AM
> To: William Dunlap
> Cc: r-help@r-project.org
> Subject: RE: [R] Peak Over Threshold values
>
> Thanks a lot for your help. That's the time period I was looking for.
>
> I've got one more question: for further analyses I need the
> respective maximum values
> within these time periods (between the green and red lines).
> Preferably in combination
> with the date the maximum event happened.
Looping over the intervals found by f() (or f0()) is
simple to do and probably quick enough for you. E.g.,
to get the position of the maximum of each interval use
something like
positionOfMaxInEachInterval <- function (x, intervals)
{
with(intervals, sapply(seq_along(start), function(i) start[i] +
which.max(x[start[i]:stop[i]]) - 1))
}
The maxima themselve would be gotten by
intervals <- f(x, startThreshold, stopThreshold, plot=TRUE)
imax <- postionOfMaxInEachInterval(x, intervals)
# abline(v=imax) if you had plot=TRUE above
maxs <- x[imax]
By the way, the looping form of f() can be made much faster
than the f0 I showed earlier, in the case where there are
many intervals (e.g., f(sin(1:1e6),.1,0)), by preallocating
the output. You may prefer to edit that version to get the
positions of the interval maxima as you compute the intervals.
f0a <-
function (x = walevel, startThreshhold = 5.45, stopThreshhold = 5.3,
plot = TRUE)
{
stopifnot(startThreshhold > stopThreshhold)
inRun <- FALSE
start <- integer(length(x))
stop <- integer(length(x))
nStart <- 0
nStop <- 0
for (i in seq_along(x)) {
if (inRun) {
if (x[i] < stopThreshhold) {
nStop <- nStop + 1
stop[nStop] <- i - 1L
inRun <- FALSE
}
}
else {
if (x[i] > startThreshhold) {
nStart <- nStart + 1
start[nStart] <- i
inRun <- TRUE
}
}
}
if (inRun) {
nStop <- nStop + 1
stop[nStop] <- length(x)
}
if (nStop > nStart) {
stop <- stop[-1]
nStop <- nStop - 1
}
length(stop) <- nStop
length(start) <- nStart
if (plot) {
plot(x, cex = 0.5)
abline(h = c(startThreshhold, stopThreshhold))
abline(v = start, col = "green")
abline(v = stop, col = "red")
}
data.frame(start = start, stop = stop)
}
Bill Dunlap
Spotfire, TIBCO Software
wdunlap tibco.com
> Thank you
> in advance,
>
> Tonja
>
>
>
> -----Ursprüngliche Nachricht-
> Von: William Dunlap
> Gesendet: 27.05.2010 22:13:21
> An: "Hutchinson,David [PYR]"
> ,Tonja Krueger
> Betreff: RE: [R] Peak Over Threshold values
>
> >> -Original Message-
> >> From: r-help-boun...@r-project.org
> >> [mailto:r-help-boun...@r-project.org] On Behalf Of William Dunlap
> >> Sent: Thursday, May 27, 2010 12:24 PM
> >> To: Hutchinson,David [PYR]; Tonja Krueger
> >> Cc: r-help@r-project.org
> >> Subject: Re: [R] Peak Over Threshold values
> >>
> >> Here is another version, loopless, but still
> >> a bit clumsy (can the call to which be removed?):
> >
> >Note that avoiding loops is mostly for
> >the aesthetic effect. On my aging laptop
> >the following loopy and vector-growing version
> >takes 3 seconds on a million-long vector
> >while the non-loopy one takes 0.22 seconds
> >(timings done with plot=FALSE). That is
> >a nice ratio but not much of a difference.
> >
> >f0 <- function (x = walevel,
> >startThreshhold = 5.45,
> >stopThreshhold = 5.3,
> >plot = TRUE)
> >{
> >stopifnot(startThreshhold > stopThreshhold)
> >inRun <- FALSE
> >start <- integer()
> >stop <- integer()
> >for (i in seq_along(x)) {
> >if (inRun) {
> >if (x[i] < stopThreshhold) {
> >stop[length(stop) + 1] <- i - 1
> >inRun <- FALSE
> >}
> >}
> >else {
> >if (x[i] > startThreshhold) {
> >start[length(start) + 1] <- i
> >inRun <- TRUE
> >}
> >}
> >}
> >if (inRun)
> >stop[length(stop) + 1] <- length(x)
> >if (length(stop) > length(start))
> >stop <- stop[-1]
> >if (plot) {
> >plot(x, cex = 0.5)
> >abline(h =
[R] Peak Over Threshold values/ length of the events
Dear List I hope you can help me: I’ve got a dataframe (df) within which I am looking for Peak Over Threshold values as well as the length of the events. An event starts when walevel equals 5.8 and it should end when walevel equals the lower threshold value (5.35). I tried “clusters (…)” from “evd package”, and varied r (see example) but it did not work for all events (again see example). walevel <- c(5.75, 5.75, 5.75, 5.76, 5.80, 5.82, 5.85, 5.86, 5.91, 5.91, 5.88, 5.92, 5.99, 6.02, 6.00, 6.08, 6.11, 6.10, 6.10, 6.11, 6.14, 6.12, 6.15, 6.17, 6.15, 6.08, 6.01, 5.95, 5.89, 5.83, 5.77, 5.72, 5.70, 5.65, 5.59, 5.51, 5.43, 5.33, 5.30, 5.25, 5.22, 5.21, 5.19, 5.19, 5.19, 5.13, 5.15, 5.07, 5.04, 5.02, 4.99, 5.05, 5.07, 5.12, 5.17, 5.22, 5.32, 5.29, 5.33, 5.33, 5.36, 5.37, 5.42, 5.43, 5.48, 5.55, 5.57, 5.66, 5.68, 5.72, 5.77, 5.79, 5.81, 5.80, 5.80, 5.77, 5.72, 5.70, 5.66, 5.62, 5.62, 5.61, 5.59, 5.57, 5.51, 5.47, 5.41, 5.39, 5.40, 5.40, 5.42, 5.45, 5.47, 5.50, 5.50, 5.49, 5.43, 5.39, 5.33, 5.26) day <- c(1:100) df <- data.frame(day,walevel) library(evd) clusters(df$walevel, u = 5.80, r = 1, ulow = 5.35, cmax = T, plot = T) clusters(df$walevel, u = 5.80, r = 50, ulow = 5.35, cmax = T, plot = T) What have I done wrong? Tonja __ 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.
