Displaying 20 results from an estimated 4000 matches similar to: "X-Axis Label Overwritten By TickMark Values"
2009 Jun 15
1
reducing space between tickmark labels and axes labels
Hello,
Does anybody know if it is possible to reduce the spaces between axes labels and axes lables in boxplots? I am trying to fit several plots onto one page ( layout() ) and need to save as much space as possible. I have reduced margins (par(mar)),adjusted font size (cex) and tck, is there anything else I can do?
Thank you
[[alternative HTML version deleted]]
2002 Apr 12
1
persp(): z-axis annotation overwrites numbers at tickmark
Dear R-users
first, thanks to Paul Murrell for fixing my problem "What line is labeled in
persp()".
It works great now (in the development version).
One more question (I don't know if it's related to the "old" problem): the
annotation on the z-axis
overwrites the numbers at the tickmarks and sometimes, if numbers are pretty
long, the numbers themselfe overlap the
2002 Nov 15
1
lattice: formatting tickmark labels of log scaled axes
Problem:
How can I format tickmark labels of log scaled axes of lattice
graphics in the usual `xxx'-Format (and not in the scientific
format).
Example:
(according to the help-page of xyplot):
In the first plot I get the xxx-Format,
in the second plot I get the scientific format (10^xxx):
data(sunspot)
plot( 1:37, sunspot, log='y',type='l')
xyplot( sunspot ~ 1:37,
2005 Oct 10
2
R.app window size
Hi all,
This is a question for any of you who use R.app (OS X). Is there any
way to resize the quartz plot window from within R? I know that you
can resize the window by dragging the corner of the window, and fro
the preferences panel. But is there a way to specify the window size
from the console? I want to specify the size of the plot window from
inside an R function.
Also a
2008 Nov 03
1
Fourier Transform with irregularly spaced x
Dear all,
I work with (vibrational) spectra: some kind of intensity (I) over frequency
(nu), wavelength or the like.
I want to do fourier transform for interpolation, smoothing, etc.
My problem is that the spectra are often irregularly spaced in nu: the
difference between 2 neighbouring nu varies across the spectrum, and data
points may be missing.
Searching for discrete fourier transform
2011 Feb 11
4
When is *interactive* data visualization useful to use?
Hello all,
Before getting to my question, I would like to apologize for asking this
question here. My question is not directly an R question, however, I still
find the topic relevant to R community of users - especially due to only *
partial* (current) support for interactive data visualization (see here:
http://cran.r-project.org/web/views/Graphics.html were with iplots we are
waiting for
2010 Oct 28
1
clustering on scaled dataset or not?
Hi, just a general question: when we do hierarchical clustering, should we
compute the dissimilarity matrix based on scaled dataset or non-scaled dataset?
daisy() in cluster package allow standardizing the variables before calculating
dissimilarity matrix; but dist() doesn't have that option at all. Appreciate if
you can share your thoughts?
Thanks
John
[[alternative HTML
2007 Jan 18
16
5.1 surround channel coupling
It obviously would be nice to have such a mode available, for e.g. DVD audio
compression. Apparently, the list doesn''t tell me too much about it. My
questions are:
1. What is the current status of the 5.1 channel coupling in Vorbis?
2. If I''ll be interested in participation in its development, what is the
recommended reading?
-------------- next part --------------
An HTML
2007 Dec 19
4
Factor Madness
Why is class(spectrum[["Ion"]]) after this "factor"?
spectrum <- cbind(spectrum,Ion=rep("",
nrow(spectrum)),Deviation.AMU=rep(0.0, nrow(spectrum)))
slowly going crazy ...
Joh
2008 Sep 09
4
Help with 'spectrum'
For the command 'spectrum' I read:
The spectrum here is defined with scaling 1/frequency(x), following S-PLUS. This makes the spectral density a density over the range (-frequency(x)/2, +frequency(x)/2], whereas a more common scaling is 2? and range (-0.5, 0.5] (e.g., Bloomfield) or 1 and range (-?, ?].
Forgive my ignorance but I am having a hard time interpreting this. Does this mean
2012 Feb 07
2
Help need
I have mad a for loop to try and output values which i have named spectrum. However, I cannot seem to get the answers to come out as a vector which is what i need. They come out as separate values which I am then unable to join together. Thank you
for(f in seq(0,0.5,0.1)) {
sigmasqaured <- 1
i = complex(real = 0, imaginary = 1)
spectrum <-
2009 Jun 11
2
Problem with new version of GlusterFS-2.0.1 while copying.
Hi,
I am having some problem with new version of
GlusterFS-2.0.1 while copying using "apache" user.
sudo -u apache cp -pvf zip/* test/
getting the message
cp: getting attribute
`trusted.glusterfs.afr.data-pending' of
`zip/speccok1ma131231824637.zip': Operation not permitted
`zip/speccok1ma131231824776.zip' -> `test/speccok1ma131231824776.zip'
No problem while
2008 Apr 30
3
Cross Spectrum Analysis
I am reading some documentation about Cross Spectrum Analysis as a technique
to compare spectra.
My understanding is that it estimates the correlation strength between
quasi-periodic structures embedded in two signals. I believe it may be
useful for my signals analysis.
I was referred to the R functions that implement this type of analysis. I
tried all the examples which generated a series of
2011 Sep 23
1
Cross Spectrum : Conversion of 2-D spectrum into a single complex array
Hi, I'm wondering why the spectrum() phase of quadrature
couple isn't purely +/-pi.
But mostly, I'm looking for a recommended way to take a 2-D
spectrum and convert it into a single complex array.
Kindly consider:
# 10 Hz sine wave 10 seconds long sampled at 50 Hz
deltaT = 1/50
t = seq(0, 10, deltaT)
w = 2 * pi * 10
x = ts( sin( w * t ), deltat = deltaT )
y = ts( sin(
2005 Dec 01
1
squared coherency and cross-spectrum
Hi All,
I have two time series, each has length 354. I tried to calculate the
coherency^2 between them, but the value I got is always 1. On a website,
it says: " Note that if the ensemble averaging were to be omitted, the
coherency (squared) would be 1, independent of the data". Does any of
you know how to specify properly in R in order to get more useful
coherency? The examples in
2007 Jan 08
2
Simple spectral analysis
Hello world,
I am actually trying to transfer a lecture from Statistica to
R and I ran into problems with spectral analysis, I think I
just don't get it 8-(
(The posting from "FFT, frequs, magnitudes, phases" from 2005
did not enlighten me)
As a starter for the students I have a 10year data set of air
temperature with daily values and I try to
get a periodogram where the annual
2011 Jul 11
1
Spectral Coherence
Greetings,
I would like to estimate a spectral coherence between
two timeseries. The stats : spectrum() returns a coh matrix
which estimates coherence (squared).
A basic test which from which i expect near-zero coherence:
x = rnorm(500)
y = rnorm(500)
xts = ts(x, frequency = 10)
yts = ts(y, frequency = 10)
gxy = spectrum( cbind( xts, yts ) )
plot( gxy $ freq, gxy $
2001 Jul 19
1
Strange behaviour of spectrum()?
Dear r-help list:
In the following R session, I seem to be somehow breaking the spectrum()
function, but I'm not sure how. Could somebody please point out my
mistake? My apologies if it's something that should be obvious.
The mysterious bit is how spectrum(my.ts) at first works, but then later
fails with an error message that I find difficult to interpret.
I'm running R 1.3.0
2008 Nov 06
1
nls: Fitting two models at once?
Hello,
I'm still a newbie user and struggling to automate some analyses from
SigmaPlot using R. R is a great help for me so far!
But the following problem makes me go nuts.
I have two spectra, both have to be fitted to reference data. Problem: the
both spectra are connected in some way: the stoichiometry of coefficients
"cytf.v"/"cytb.v" is 1/2.
{{In the SigmaPlot
2008 Jun 04
2
estimate phase shift between two signals
Hi,
Are there any functions in R that could be used to estimate the phase-shift
between two semi-sinusoidal vectors? Here is what I have tried so far, using
the spectrum() function -- possibly incorrectly:
# generate some fake data, normalized to unit circle
x <- jitter(seq(-2*pi, 2*pi, by=0.1), amount=pi/8)
# functions defining two out-of-phase phenomena
f1 <- function(x)