[R] SOLVED: Lattice: How to do error bars
Thank you Gerrit,
Your suggestion proved right after all:
This does put error bars (dy) on the points. You only need to figure out
the proper y axis scaling.
xyplot(y~x|f,data=xy,groups=dy,panel=function(x,y,groups,subscripts,...)
{panel.xyplot(x,y,...)
;panel.segments(x,y+groups[subscripts],x,y-groups[subscripts],...)})
Regards,
Alex van der Spek
Hello, Alex,
not sure in this case, but I think you have to provide and use an argument
named subscripts for the panel function. See ?xyplot.
On Tue, 11 Aug 2009, Alex van der Spek wrote:
I am trying to add 2 stdev error bars to lattice type plots:
panel.ebar-function(x,y,dy=NULL,...) {
panel.xyplot(x,y,...)
panel.segments(x,y-dy,x,y+dy,...)
}
Then:
xyplot(y~x|fc,data=dat,dy=dat$dy,panel=panel.ebar)
This adds error bars but they are not conditioned on the factor fc.
xyplot(y+I(y-dy)+I(y+dy)~x|fc,data=dat)
This produces 3 series of points in different colors, conditioned on fc
as the data is now grouped per panel.
Obviously I need a combination of the above two. I can't figure it out.
Any help? Just point to docs if avaiable. The R doc is excellent. Most
of the time I can save myself.
Thanks in advance!
Alex van der Spek
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Regards -- Gerrit
-
AOR Dr. Gerrit Eichner Mathematical Institute, Room 305 E
gerrit.eich...@math.uni-giessen.de Justus-Liebig-University Giessen
Tel: +49-(0)641-99-32104 Arndtstr. 2, 35392 Giessen, Germany
Fax: +49-(0)641-99-32109 http://www.uni-giessen.de/~gcb7
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[R] transform(_data,...) using strptime gives an error
I have timstamped data like this: sd[1:10,] Tstamp Density Mesh50 Mesh70 Mesh100 Mesh150 Mesh200 2 2009/02/27 07:0030.50.7 10.721.432.841.6 3 2009/02/27 08:0032.21.6 12.423.334.543.0 4 2009/02/27 09:0032.74.8 13.024.035.143.5 5 2009/02/27 10:0026.70.36.517.628.136.9 6 2009/02/27 11:0026.60.96.617.028.637.9 7 2009/02/27 12:0023.36.33.414.025.534.6 8 2009/02/27 13:0025.21.15.115.427.336.8 9 2009/02/27 14:0028.60.28.719.430.940.0 10 2009/02/27 15:0028.00.68.018.630.239.3 11 2009/02/27 16:0028.30.98.318.930.539.5 The timstamps are character vectors: str(sd) 'data.frame': 591 obs. of 7 variables: $ Tstamp : chr 2009/02/27 07:00 2009/02/27 08:00 2009/02/27 09:00 2009/02/27 10:00 ... $ Density: num 30.5 32.2 32.7 26.7 26.6 23.3 25.2 28.6 28 28.3 ... $ Mesh50 : num 0.7 1.6 4.8 0.3 0.9 6.3 1.1 0.2 0.6 0.9 ... $ Mesh70 : num 10.7 12.4 13 6.5 6.6 3.4 5.1 8.7 8 8.3 ... $ Mesh100: num 21.4 23.3 24 17.6 17 14 15.4 19.4 18.6 18.9 ... $ Mesh150: num 32.8 34.5 35.1 28.1 28.6 25.5 27.3 30.9 30.2 30.5 ... $ Mesh200: num 41.6 43 43.5 36.9 37.9 34.6 36.8 40 39.3 39.5 ... - attr(*, na.action)=Class 'exclude' Named int [1:58] 1 88 89 90 250 318 319 320 321 322 ... .. ..- attr(*, names)= chr [1:58] 1 88 89 90 ... Trying to transform the timestamped character vector 'in place' using transform gives this error message: sd-transform(sd,Tstamp=strptime(Tstamp,format='%Y/%m/%d %H:%M')) Error in `[-.data.frame`(`*tmp*`, inx[matched], value = list(Tstamp = list( : replacement element 1 has 9 rows, need 591 Why? It beats me... I do have a backup of course: td-strptime(sd$Tstamp,format='%Y/%m/%d %H:%M') sd-data.frame(Tstamp=td, sd[2:7]) this works fine but is one step more complicated. Something I miss about transform()? Thanks in advance, Alex van der Spek __ 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] Cluster analysis, defining center seeds or number of clusters
I use kmeans to classify spectral events in high and low 1/3 octave bands: #Do cluster analysis CyclA-data.frame(LlowA,LhghA) CntrA-matrix(c(0.9,0.8,0.8,0.75,0.65,0.65), nrow = 3, ncol=2, byrow=TRUE) ClstA-kmeans(CyclA,centers=CntrA,nstart=50,algorithm=MacQueen) This works well when the actual data shows 1,2 or 3 groups that are not too close in a cross plot. The MacQueen algorithm will give one or more empty groups which is what I want. However, there are cases when the groups are closer together, less compact or diffuse which leads to the situation where visually only 2 groups are apparent but the algorithm returns 3 splitting one group in two. I looked at the package 'cluster' specifically at clara (cannot use pam as I have 1 observations). But clara always returns as many groups as you aks for. Is there a way to help find a seed for the intial cluster centers? Equivalently, is there a way to find a priori the number of groups? I know this is not an easy problem. I have looked at principal components (princomp, prcomp) because there is a connection with cluster analysis. It is not obvious to me how to program that connection though. http://en.wikipedia.org/wiki/Principal_Component_Analysis http://ranger.uta.edu/~chqding/papers/Zha-Kmeans.pdf http://ranger.uta.edu/~chqding/papers/KmeansPCA1.pdf Thanks in advance, Alex van der Spek __ 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] Returning only a file path on Windows
I am choosing a file like this: #Bring up file selection box fn-file.choose() fp-file.path(fn,fsep='\\') Unfortunately, the file path contains the short file name and extension as well. I had hoped to get only the path so I could make my own long filenames (for output graphs) by concatenation with this file path. Of course I can split the string and assemble the components from the returned list: fp-strsplit(fp,'\\',fixed=TRUE) But there must be a better way? Thanks in advance, Alex van der Spek __ 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] Dropping 'empty' panels from lattice
How would I paste factors c1...c10 to one grouping factor? Can you give an example? Thanks much! Alex amvds at xs4all.nl writes: I have 8 cofactors possibly affecting one and only one variable. I make conditional histograms: -pdf(file=tst3.pdf,paper=special,width=36,height=36) -histogram(~Oversized|dat$c1*dat$c2*dat$c5*dat$c6*dat$c7*dat$c8* dat$c9*dat$c10,nint=21,layout=c(32,8),data=dat,type=count) -dev.off() This works (compliments to R developers!) but it does generate a large plot with many panels being 'empty', e.g. that combination of factors c1..c10 never occurs in this data set. Is there a way to autmatically drop those empty panels? Since there is little hope that you get a useful arrangement in the 2D-paper world, and neither in 4D relativistic space, I would suggest to make a new factor by pasting all cX factors, use that as the only grouping factor. Dieter __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] Dropping 'empty' panels from lattice
I have 8 cofactors possibly affecting one and only one variable. I make conditional histograms: -pdf(file=tst3.pdf,paper=special,width=36,height=36) -histogram(~Oversized|dat$c1*dat$c2*dat$c5*dat$c6*dat$c7*dat$c8*dat$c9*dat$c10,nint=21,layout=c(32,8),data=dat,type=count) -dev.off() This works (compliments to R developers!) but it does generate a large plot with many panels being 'empty', e.g. that combination of factors c1..c10 never occurs in this data set. Is there a way to autmatically drop those empty panels? I looked at the docs: there is a drop.unused.levels parameter for trellis graphs but the docs says it is default true. I checked but could not make much sense out of the list of possibilties. Thanks! Alex van der Spek __ 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] Convert data frame containing time stamps to time series
What is zoo? I cannot find anything about zoo int he documentation. I did try as.ts() see below. Thank you, Alex van der Spek have you tried using zoo and then using the function as.ts() On Wed, Apr 8, 2009 at 11:56 AM, am...@xs4all.nl wrote: Converting dates is getting stranger still. I am coercing a data frame into a ts as follows: tst1-as.POSIXct(1/21/09 5:01,format=%m/%d/%y %H:%M) tst2-as.POSIXct(1/28/09 3:40,format=%m/%d/%y %H:%M) tsdat-as.ts(dat,start=tst1,end=tst2,frequency=1) This generates a ts object. But strangely enough the first column of that matrix starts at the numeric value of 841 counts up to 1139 and then starts at 1 again, only to count up from there. The restart at 1 occurs at the first day 1/21/09 at 10:00:00. What is so special about that time? This phenomenon happens several times in the long file. But the restart count is always a different number. This creates a ramp with some bumps. Can anybody explain this? Thanks in advance, Alex van der Spek I read records using scan: dat-data.frame(scan(file=KDA.csv,what=list(t=%m/%d/%y %H:%M,f=0,p=0,d=0,o=0,s=0,a=0,l=0,c=0),skip=2,sep=,,nmax=np,flush=TRUE,na.strings=c(I/OTimeout,ArcOff-line))) which results in: dat[1:5,]        t   f   p  d  o  s   a  l c 1 1/21/09 5:01 16151  8.2 76 30 282 1060 53 7 2 1/21/09 5:02 16256  8.3 76 23 282 1059 54 7 3 1/21/09 5:03 16150  8.4 76 26 282 1059 55 7 4 1/21/09 5:04 16150  9.0 76 25 282 1051 57 6 5 1/21/09 5:05 15543 10.4 76  7 282 1024 58 6 I have been unable to find a way to convert this into a time series. I did read the manuals and came across a way to coerce a data frame to a ts object: as.ts() Trouble is I do not know how to keep the timestamps in column t in the data frame above. The t column is not strings. If I do: plot.ts(dat) I can see how the first graphics panel is indeed numbers not text. So I think scan converted the text correctly per the format string I put in. Much more difficult still. The datafiles I have contain invalid data, missing values and other none relevant information. I filter this out using subset which works brilliantly. However, how can I filter using subset and convert to a time series afterwards. Since after subsetting there will be 'holes' i.e. missing records. Can a ts object deal with missing records? If so, how? Just point me to a document. I can and will put in the work to figure it out myself. Thank you! Alex van der Spek __ 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. -- Stephen Sefick Let's not spend our time and resources thinking about things that are so little or so large that all they really do for us is puff us up and make us feel like gods. We are mammals, and have not exhausted the annoying little problems of being mammals. -K. Mullis __ 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] Convert data frame containing time stamps to time series
I read records using scan: dat-data.frame(scan(file=KDA.csv,what=list(t=%m/%d/%y %H:%M,f=0,p=0,d=0,o=0,s=0,a=0,l=0,c=0),skip=2,sep=,,nmax=np,flush=TRUE,na.strings=c(I/OTimeout,ArcOff-line))) which results in: dat[1:5,] t fp d o sa l c 1 1/21/09 5:01 16151 8.2 76 30 282 1060 53 7 2 1/21/09 5:02 16256 8.3 76 23 282 1059 54 7 3 1/21/09 5:03 16150 8.4 76 26 282 1059 55 7 4 1/21/09 5:04 16150 9.0 76 25 282 1051 57 6 5 1/21/09 5:05 15543 10.4 76 7 282 1024 58 6 I have been unable to find a way to convert this into a time series. I did read the manuals and came across a way to coerce a data frame to a ts object: as.ts() Trouble is I do not know how to keep the timestamps in column t in the data frame above. The t column is not strings. If I do: plot.ts(dat) I can see how the first graphics panel is indeed numbers not text. So I think scan converted the text correctly per the format string I put in. Much more difficult still. The datafiles I have contain invalid data, missing values and other none relevant information. I filter this out using subset which works brilliantly. However, how can I filter using subset and convert to a time series afterwards. Since after subsetting there will be 'holes' i.e. missing records. Can a ts object deal with missing records? If so, how? Just point me to a document. I can and will put in the work to figure it out myself. Thank you! Alex van der Spek __ 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] Convert data frame containing time stamps to time series
Converting dates is getting stranger still. I am coercing a data frame into a ts as follows: tst1-as.POSIXct(1/21/09 5:01,format=%m/%d/%y %H:%M) tst2-as.POSIXct(1/28/09 3:40,format=%m/%d/%y %H:%M) tsdat-as.ts(dat,start=tst1,end=tst2,frequency=1) This generates a ts object. But strangely enough the first column of that matrix starts at the numeric value of 841 counts up to 1139 and then starts at 1 again, only to count up from there. The restart at 1 occurs at the first day 1/21/09 at 10:00:00. What is so special about that time? This phenomenon happens several times in the long file. But the restart count is always a different number. This creates a ramp with some bumps. Can anybody explain this? Thanks in advance, Alex van der Spek I read records using scan: dat-data.frame(scan(file=KDA.csv,what=list(t=%m/%d/%y %H:%M,f=0,p=0,d=0,o=0,s=0,a=0,l=0,c=0),skip=2,sep=,,nmax=np,flush=TRUE,na.strings=c(I/OTimeout,ArcOff-line))) which results in: dat[1:5,] t fp d o sa l c 1 1/21/09 5:01 16151 8.2 76 30 282 1060 53 7 2 1/21/09 5:02 16256 8.3 76 23 282 1059 54 7 3 1/21/09 5:03 16150 8.4 76 26 282 1059 55 7 4 1/21/09 5:04 16150 9.0 76 25 282 1051 57 6 5 1/21/09 5:05 15543 10.4 76 7 282 1024 58 6 I have been unable to find a way to convert this into a time series. I did read the manuals and came across a way to coerce a data frame to a ts object: as.ts() Trouble is I do not know how to keep the timestamps in column t in the data frame above. The t column is not strings. If I do: plot.ts(dat) I can see how the first graphics panel is indeed numbers not text. So I think scan converted the text correctly per the format string I put in. Much more difficult still. The datafiles I have contain invalid data, missing values and other none relevant information. I filter this out using subset which works brilliantly. However, how can I filter using subset and convert to a time series afterwards. Since after subsetting there will be 'holes' i.e. missing records. Can a ts object deal with missing records? If so, how? Just point me to a document. I can and will put in the work to figure it out myself. Thank you! Alex van der Spek __ 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.
