Re: [R] Reading CSV file
Dear Gafar Matanmi Oyeyemi, Re: I am trying to read a csv file using the code; contol - read.csv(RBS.csv) This is the error message I got; Error in file(file, r) : unable to open connection In addition: Warning message: In file(file, r) : cannot open file 'RBS.csv', reason 'No such file or directory' I always use file.choose() to find the exact path name, e.g. contol - read.csv(file.choose()) After having found the path name, you can put it in the R source text for future use (provided it remains the same of course). Best wishes, Franklin Bretschneider -- Dept of Biology Kruytgebouw W711 Padualaan 8 3584 CH Utrecht The Netherlands __ 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] A categorized list of R functions
Dear Rees Morrison,
Re:
(...)
What additional code would create a table output, with the function name in
the left column, sorted alphabetically within a pattern, and the pattern of
the function in the column to the right. Users could then sort by those
patterns, rename some to suit themselves, etc.
(...)
The version below creates a tab-delimited table with 3 columns: seach string,
package name and function name.
Can be imported e.g. in Excel. Maybe not elegant, but seems to work (however:
test it!).
Column order can be changed by changing the printing order of newhits[ ,1] ,2
and ,3.
In addition, Liviu Andronic's suggestion to use the package sos (strange
name, but good tip) seems also interesting.
Best wishes,
Franklin Bretschneider
--
Dept of Biology
Kruytgebouw W711
Padualaan 8
3584 CH Utrecht
The Netherlands
- - - - - - - - - - - - - - - - -
# categorize functions 2.R
# Franklin Bretschneider
# after R-help, R. Michael Weylandt
# 08-04-2013
# this version produces a tab-delimited text file with
# the columns: (search) pattern; (in which) package and function (name).
# ==
allfuncs = unlist(sapply(search(), ls))
n = length(allfuncs)
allnames = names(allfuncs)
package.names = substr(allnames, start=9, stop=nchar(allnames))
allfuncs = cbind(package.names, allfuncs)
# which patterns to search: can be customized
patterns = c(print, plot, axes, axis, color, file, read, write,
load, save,wave, image, table, data, apply, title, matrix,
names)
patterns = sort(patterns) # optional
k = length(patterns)
# open output file
options(verbose=FALSE)
zz - file(all functions.txt, open=wt)
sink(zz, type=output)
# print the output to the file
cat(\n\n )
cat(pattern\tpackage\tfunction\r)
for (i in 1:k) {
cat(\n )
hits = allfuncs[grep(patterns[i], allfuncs[,2], ignore.case=TRUE),2]
hitpkg = allfuncs[grep(patterns[i], allfuncs[,2], ignore.case=TRUE),1]
hitpkg = gsub(\\d, , hitpkg)
labels = rep(patterns[i],length(hits))
newhits = cbind(labels, hitpkg, hits)
newhits =newhits[order(newhits[,3]),] # sort data frame on
basis of one column
cat(sprintf(fmt = %s\t%s\t %s\r, newhits[,1], newhits[,2],
newhits[,3]))
}
cat(\n\n)
## back to the console
sink(type=output)
close(zz) # close the file
print(Finished)
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Re: [R] categorized complete list of R commands?
Dear Rees Morrison, Re: Franklin, I am very impressed. I ran your code and am amazed at the output. I want to use it in my efforts to figure out which are the most widely used functions, so that I can concentrate on understanding those basics reasonably well. May I ask you two few questions? What additional code would create a table output, with the function name in the left column, sorted alphabetically within a pattern, and the pattern of the function in the column to the right. Users could then sort by those patterns, rename some to suit themselves, etc. That would be handy, indeed, as well as in which package each function resides. However, my own motive was that if you know the existence and exact name of (seemingly) relevant functions, you can find the full syntax etc. throught R's built-in help system. I'm not sure whether this would be simple, because grep yields a variable number of hits, which must then be combined with a fixed string value. I'll think about it. Second, I assume this function searches base only? Could you add a parameter to the function so that it would search other, installed packages, such as Hmisc or stringr or plyr? If so, the table (or your output) would need to identify the package. search() gives a list of attached packages, so if you load all packages of your interest you 'll get all relevant functions. Third, the patterns might usefully include wd, str, and names. Certainly; for others it might be model, summary etc. Users can extend the pattern list or load them from a text file, e.g. patterns = read.csv(file.choose()) I did not want to post this on R-Help because that site is much too intimidating for a newcomer. In that regard, Hadley Wickham sent the .csv file where he compiled the base functions and stats functions. I have done one of my own, but it is not as comprehensive, but goes beyond base. In my opinion it's better to CC the r-help, because someone in the vast R community might come up with a faster, or better, solution. Much obliged. Rees -- Rees Morrison General Counsel Metrics, LLC (management consulting and data analytics) 4 Hawthorne Ave. Princeton, NJ 08540-3840 USA (973) 568-9110 Hosts www.lawdepartmentmanagementblog.com Best wishes, Franklin Bretschneider -- Dept Biologie Kruytgebouw W711 Padualaan 8 3584 CH Utrecht The Netherlands [[alternative HTML version deleted]] __ 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] categorized complete list of R commands?
On 04 Apr 2013, at 07:34 , ivo welch wrote:
every time I read the R release notes for the next release, I see many
functions that I had forgotten about and many functions that I never knew
existed to begin with. (who knew there were bibtex facilities in R?
obviously, everyone except me.)
I wonder whether there is a complete list of all R commands (incl the
standard packages) somewhere, preferably each with its one-liner AND
categorization(s). the one-liner can be generated from the documentation.
I am thinking one categorization for function area (e.g., programming
related for, say, deparse; and statistical model related for lm; and
another categorization for importance (e.g., like common for lm and
obscure for ..). Such categorizations require intelligence.
if I am going to do this for myself, I think a csv spreadsheet may be a
good idea to make it easy to resort by keys.
regards,
/iaw
Ivo Welch (ivo.we...@gmail.com)
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A categorized list of functions would indeed come in handy.
So, based on Michael Weylandt's lines, I gave it a try:
# categorize functions.R
# Franklin Bretschneider
# after R-help: R. Michael Weylandt
# 05-04-2013
# =
nprint - function(x) print(x,quote=FALSE)
allfuncs = unlist(sapply(search(), ls))
names(allfuncs) - NULL
patterns = c(print, plot, axes, axis, color, file, read,
write, load, save,wave, image, table, data, apply, title)
patterns = sort(patterns) # optional
n = length(patterns)
nprint( )
nprint( )
for (i in 1:n) {
nprint( )
nprint(paste(Functions with,patterns[i],:))
nprint(===)
nprint(allfuncs[grep(patterns[i], allfuncs, ignore.case=TRUE)])
nprint(- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
-)
}
nprint( )
nprint( )
The list of keywords can be adapted to one's own wishes.
Maybe this helps.
Best wishes,
Franklin
--
Franklin Bretschneider
Dept of Biology
Utrecht University
Kruytgebouw W711
Padualaan 8
3584 CH Utrecht
The Netherlands
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Re: [R] custom startup/welcome message
Dear lejeczek,
Re:
hi everybody
I wonder if there is a simple way, but not simple would be
ok too,
to customize info/welcome page at session start time?
what I'd like to do is to put together simple short howto /
dos don'ts page for users,
I'm thinking it would be great if it was possible
Indeed, you can put all kinds of things in the Rprofile.
I use this:
# = my own first-function
.First - function(){
cat(\n R 2.15.2 Rprofile van 13-02-2013 \n\nFunctions
added:\t sinc()\t permute()\t combine()\n dice(n)\t countif()\t pplot()\t
lplot()\n ln()\t xmatplot()\t ascii()\t chr()\n to.dec()\t
to.hex()\tincr()\tdecr()\n as.sci()\tas.eng()\tnprint()\nVectors added: eps,
ans, xpoints, xcols\nText:lorem\n\n)
cat(Default Packages:,getOption(defaultPackages))
}
# ==
This gets printed after R's built-in message.
As this text states, I also put my own functions in the Rprofile. Works fine.
Best wishes,
Franklin
--
Franklin Bretschneider
--
Dept Biologie
Kruytgebouw W711
Padualaan 8
3584 CH Utrecht
The Netherlands
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Re: [R] Plotting with basic plot
Dear Neuwirth Erich, Re: On 16 Mar 2013, at 19:18 , Neuwirth Erich wrote: When I run this code fragment x - (0:100)/100 y - x^2 plot(x,y,type=l,xlab=expression(x),ylab=expression(f(x)==x^2), main=Quadratfunktion) the exponent on the y-axis label is mutilated. How can the be changed with minimal effort? ggplot2 does not have this problem: library(ggplot2) x - (0:100)/100 y - x^2 qplot(x,y,geom=line,xlab=expression(x),ylab=expression(f(x)==x^2), main=Quadratfunktion) __ 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. # The left margin can be chosen wider, e.g.bij putting: par(mar=c(4,5,4,4)) # before the plotting statement. Beste wishes, Franklin Bretschneider -- Dept Biologie Kruytgebouw W711 Padualaan 8 3584 CH Utrecht The Netherlands __ 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] low pass filter analysis in R
Dear Janesh, Re: Dear Franklin Bretschneider, Thank you so much for your reply and explanation about the filter using the stats and signal package. I decided to opt the filter method in signal package. I have a simple question about the cut off frequency here. I have 30 minute collected tidal data and I want to use the 48 hour low pass filter to my data to remove the fluctuations and then get only the residuals. What should be the cutoff frequency in my case ? I have tried to figure out cut off frequency with the following rationale : . The parameters for butter filter are n, Wn and type. In the help, Wis defined as critical frequencies of the filter. W must be a scalar for low-pass and high-pass filters, and W must be a two-element vector c(low, high) specifying the lower and upper bands. For digital filters, W must be between 0 and 1 where 1 is the Nyquist frequency. A value of 1 corresponds to half the sampling frequency. In my case the sampling frequency is 2 hr^-1. Hence a value of 0.01 corresponds to a frequency cutoff of .01*1 = .01 hr^-1 or 100 hrs time. Using unitary method, if 100 hours cut off frequency is 0.01 then 48 hours cut off frequency is 0.01/100*48 = 0.0048 hr^-1 . Is that correct ? Thank you so much Janesh With digital filters (called z-plane in the signal package), the cut-off frequency must indeed be given as a fraction of the Nyquist freqency. With your tidal data, taken at 2 samples per hour, the nyquist is 1 per hour. So, a cutoff interval of 48 h means a cutoff frequncy of 1/48 f(nyq) , or 0.020833. This must be fed into the butterworth function. Note btw that at the cut-off frequency, the amplitude is still rather high (about 0.707), so the tidal signal (period about 12.5 h) will not be attenuated much. I hope this helps. It's always best to check with a simple example, such as an f= 1/48 sine, which after your filter should be reduced to an amplitude of 0.707). Then check with a simulated tidal signal (say, a sine of about 12:25 h period). With such simple tests, I often find my own programming errors. Best wishes, Franklin -- Franklin Bretschneider -- Dept Biology Kruyt Building W711 Padualaan 8 3584 CH Utrecht The Netherlands [[alternative HTML version deleted]] __ 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] Add text A, B, C and D on multiple ordered plot
Dear Fabrice Tourre, Re: John Kane, Thanks. It makes some of sense. But it seems not exactly what I want. I just remember it need using mtext and adjust margin. I saw such of example long time ago, but I have forgotten it. (etc...) Maybe this is what you're after? Fiddled a bit with the margins: a- rnorm(1000,0,1) b-rnorm(1000,0,2) c-rnorm(1000,0,3) d-rnorm(1000,0,4) quartz(w=6,h=8) par(mfrow=c(2,2)) #par(mai=c(1,0,1,1)) par(mar=c(3,2,4,1)) #par(plt=c(1.1,1.1,1.1,1.1)) tlin=2 hist(a) mtext(A,3, line=tlin, adj=0, cex=2) hist(b) mtext(B,3, line=tlin, adj=1, cex=2) hist(c) mtext(C,3, line=tlin, adj=0, cex=2) hist(d) mtext(D,3, line=tlin, adj=1, cex=2) Hope this helps, Best regards, Franklin Bretschneider -- Dept Biologie Kruytgebouw W711 Padualaan 8 3584 CH Utrecht The Netherlands __ 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] low pass filter analysis in R
Dear Janesh Devkota, Re: Hello R users, I am trying to use R to do the low pass filter analysis for the tidal data. I am a novice in R and so far been doing only simple stuffs on R. I found a package called signal but couldn't find the proper tutorial for the low pass filter. Could anyone point me to the proper tutorial or starting point on how to do low pass filter analysis in R ? Thank you so much. Janesh Indeed, filters are in both the stats and the signal packages. The simplest is to define a running average smoothing, e.g. if your data is called y: yfiltered = stats:::filter(y, c(1,1,1,1,1,1,1)/7) So, smooth the data by the filter c(1,1,1,1,1,1,1)/7 Note that the first 3 and last 3 data points are lost. The longer the filter, the more data at the start and the end of your data will be lost. The signal package allows more sphisticated forms of filter. In addition, it contains functions to compute filter types well-known in signal analysis, such as butterworth and chebysheff filters. A second-order butterworth filter with a cutoff at 0.1 x the sampling frequency: myfilter = butter(2, 0.1, type = 'low', plane='z') Apply this: yfiltered = signal:::filter(y, x) # apply filter Note that loading the signal package may mask the filter from stats. Hence the call with the ::: in it. Succes. Best wishes, Franklin Bretschneider -- Dept Biologie Kruytgebouw W711 Padualaan 8 3584 CH Utrecht The Netherlands __ 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] low pass filter analysis in R
Dear Janesh Devkota, Sorry, I forgot an edit. The last command should read: yfiltered = signal:::filter(myfilter, y) # apply filter Best wishes, Franklin Bretschneider -- Dept Biologie Kruytgebouw W711 Padualaan 8 3584 CH Utrecht The Netherlands __ 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] Starting with R
On 30 Dec 2012, at 12:22 , Siddhant Gupta wrote: I have installed R on my machine. Can anyone now suggest to me the best book/e-book from where I can learn the R language most efficiently? Thanks in advance -- Siddhant Gupta III Year Department of Biotechnology IIT Roorkee India [[alternative HTML version deleted]] __ 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. Yes, quite a lot! At: http://ftp.iitm.ac.in/cran/ Succes, and Best wishes, Franklin Bretschneider -- Dept Biologie Kruytgebouw W711 Padualaan 8 3584 CH Utrecht The Netherlands __ 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] what is the function naming convention?
Dear R people, In typing names of functions (built in or from a package) I often guess wrong, and have to look the name up. In other words, I don't understand the logic in naming functions (if there is any): - most names are plain, lower case: cos, plot, sapply, t, toupper, unserialize, (etc) - some are capitalized: Filter, Machine, Map, NCOL, RNGversion, T (etc) - many are dotted: as.complex, as.data.frame.array, merge.data.frame, write.dcf (etc) The manual Creating R Packages states that it depends on the classes and instances. I couldn't find more hints. And there's more: - using underscore characters: check_tzones, Cstack_info, R_system_version (etc) - using interCapping: closeAllConnections, rawToChar, rowSums, toString, tryCatch, writeLines (etc) - using dots and intercapping: as.Date, julian.Date, toString.default (etc) So, an entire zoo of function names. Did I miss a system, or is it arbitrary (within the set of accepted characters) ? What is the best way to name one's own functions? Thanks in advance, Franklin Bretschneider Utrecht University Dept Biology Kruytgebouw W711 Padualaan 8 3584 CH Utrecht The Netherlands __ 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] Reading multiple files
On 26 Sep 2012, at 16:11 , Silvano Cesar da Costa wrote:
Hi,
I have 35 data files for reading. I would like get a program for
performing reading of 35 files at once.
All are of the type: Dados1.raw, Dados2.raw and so on.
If the files have the same number of columns, I can read with the
following commands:
rm(list=ls())
filenames = list.files(path=~/Silvano/Arq, pattern=Dados+.*raw)
names = substr(filenames, 1, 7)
for(i in names){
filepath = file.path(~/Silvano/Dados, paste(i, .raw, sep=))
assign(i, read.delim(filepath,
colClasses=c(rep(character, 5), rep(numeric, 5)),
sep = ))
}
It happens that the files have different number of columns. And I can't
solve the problem.
Any suggestions?
Dear Silvano Cesar da Costa,
You can read an entire folder by analysing the path.
I wrote this program to convert wave files, but it can be applied to any file
type.
Just change the few lines (if ywave... etc) into your own operations:
# select FOLDER with WAV-files
fnam = dirname(file.choose())
print(); print(FILES)
print(list.files(fnam))
print(); print(DIRS)
print(list.dirs(fnam, full.names=FALSE))
print(); print(RECURSIVE FILE LIST)
filist = list.files(fnam, recursive=TRUE, pattern=wav)
print(filist)
filist1 = paste(fnam,/,filist, sep=)
nfiles = length(filist1)
#
# filenames loop ===
for(i in 1:nfiles) {
inname=filist1[i]
ywave=readWave(inname)
ster=ywave@stereo
if (ster==stereo) {} # wat dan??
srate=yw...@samp.rate
ywave2=ywave
if (ywave2@bit==8) {
ywave2@left=(ywave2@left-128)*255
ywave2@bit - 16
}
if (ywa...@samp.rate10) {
ywa...@samp.rate - ywa...@samp.rate * 10
}
if (ywa...@samp.rate != 312500) {
ywave2 - resamp(ywave2,f=ywa...@samp.rate,g=312500,
output=Wave)
}
outname=paste(dirname(inname), /*,basename(inname), sep=)
writeWave(ywave2,outname)
}
Best wishes,
Franklin Bretschneider
Dept of Biology
Kruytgebouw W711
Padualaan 8
3584 CH Utrecht
The Netherlands
f.bretschnei...@uu.nl
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Re: [R] how to get list of files within a particular local file folder
Dear Ajay Ohri,
Re:
Dear List,
Say I can use getwd() and setwd() to change my working directory. How can I
read in all the files within that directory using command line (like a ls()
but for the path specified)
I use this function,
# functions
getFolder - function(pat)
{
txt=file.choose()
#cat(txt,'\n')
pos=0
fname=basename(txt)
#cat(paste(\nFilename found is: ,fname,'\n'))
foln = dirname(txt)
cat(paste(\nFolder name found is: ,foln,'\n'))
drtext=dir(foln, pattern=pat, full.names = TRUE)
#cat('\n\n\n\n')
return(drtext)
}
Best,
Franklin
Dr F. Bretschneider
Dept of Biology
Kruytgebouw W711
Padualaan 8
3584 CH Utrecht
The Netherlands
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Re: [R] how to plot a nice legend
Dear Jonas Stein, You may add a line defining a large margin to harbour the legend, such as: par(mai=c(0.5, 0.5, 0.5, 1.8)) # enlarged right margin plot(1:10) legend(right, legend=c(one, two), inset=-0.2, xpd=NA) Kind regards, Franklin Bretschneider -- Dept Biologie Kruytgebouw W711 Padualaan 8 3584 CH Utrecht The Netherlands __ 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] How to loop on file names
Dear Hélène Genet,
Re:
Dear all,
I need to do the same procedure on several files. But I don't know how to
refer to the file name.
Here is an example of what I am trying to do.
List of files: file1(A,B,C, D1...Dn), file2(A,B,C,E1,...,En),
file3(A,B,C,F1,...,Fn)
Procedure I want to apply on each file:
dft - melt(df,id=c('A','B','C'))
dft$X - substr(dft$variable,1,3)
dft$Y - substr(dft$variable,4,8)
dft1 - cast(dft, A+B+C+X ~ Y,value=response)
As you see all the files contains the same 3 variables A,B,C that I use in
the procedure.
So I want to apply the procedure on all the file in a loop.
Something like :
filelist - c('file1' , 'file2' , 'file3')
for (i in 1:3) {
filename - filelist[i]
...
}
Any suggestion to refer to these files in this loop?
Thanks you in advance,
Helene
--
Hélène Genet, PhD
Institute of Arctic Biology
University of Alaska Fairbanks
Irving I Blg, Room 402
Fairbanks AK 99775
Phone: 907-474-5472
Cell: 907-699-4340
Email: hge...@alaska.edu
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and provide commented, minimal, self-contained, reproducible code.
I use this procedure to point to a folder (of WAV files in this example) and
process all those files in a loop:
# select FOLDER w. WAV-files
fnam = dirname(file.choose())# choose any one file from the folder (=
directory)
filist = list.files(fnam, recursive=TRUE, pattern=wav)
filist1 = paste(fnam,/,filist, sep=)
nfiles = length(filist1)
#
# filenames loop ===
for(i in 1:nfiles) {
inname=filist1[i]
ywave=readWave(inname) # read the i'th file (wav as an example, can
be any filetype you need)
ywave2=ywave # output is the same as input (yet)
###
### DO ANY PROCESSING YOU WANT HERE to change ywave into ywave2
###
outname=paste(dirname(inname), /*,basename(inname), sep=)
writeWave(ywave2,outname)
}
I took these few lines out of a larger program with wave file processing not
relevant here.
Hope I didn't forget something, and that this works for your case,
Beste wishes,
Franklin Bretschneider
Utrecht University
--
Dept Biologie
Kruytgebouw W711
Padualaan 8
3584 CH Utrecht
The Netherlands
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