similar to: Crashing R (PR#1651)

Suppose I have a factor size with levels "small", "medium" and "large". Then, when I subset this factor: >ss<-size[size!="medium"] to get at the extremes, >levels(ss) .... Levels: large medium small The same happens with >subset( size, size!="medium") I understand that the resulting factor inherits the possible levels from its

New to R, I had the bad idea to send a bug report about '[' not knowing it had a drop= argument. Now, I wonder about the absence of this argument in subset... In both availabe methods (see below), there is a ... argument, but this argument is not used in either. Rather, subset.data.frame explitictly passes drop=F in 1 instance. Before I start patching (for my own use): what is the

Starting html help in the current version of R has a very annoying side-effect. It indiscriminantly removes $HOME/.R, and replaces it with a virgin copy. I discovered that when all of a sudden I got complaints about my startup "library" not being found. Below is a modified version of the script that doesn't do this. It is not perfect yet (it shouldn't try to recreate links

https://www.redhat.com/archives/libguestfs/2019-August/thread.html#00347 Thanks: Eric Blake and Daniel P. Berrangé --- common/utils/utils.h | 1 + server/connections.c | 4 ++-- server/crypto.c | 5 +++-- server/main.c | 23 +++++++++++++++++++++++ common/utils/utils.c | 29 +++++++++++++++++++++++++++++ 5 files changed, 58 insertions(+), 4 deletions(-) diff --git

Hi, This question is related to the bwplot issue I reported yesterday. I have a 3 factors (2x3x2) dataset that I collapsed into a 2 factors dataset (3x2 = sizexModality). For size==small, I have 2 observations per subject (Snr), for the other sizes only 1. I reckoned that aov (and underneath, lm) might handle this as it should, since the subjects are idendified, when I do > aov(

R provides a few ways of handling missing values, a.o. in the context of an anova (aov); 2 types of exclusion, and failure. In some situations, I personally like to have missing values replaced by the mean (or the median) for the given combination of factors. A routine that does that is something like the code included below. It works, but is (of course) rather slow. It would be much quicker

Hello Jean-Marc, Below are the results that show test_unit_dft passes, but test_unit_mdct fails (only for nfft=480, 960, 1920) Note: Tested on BeagleboneBlack(Cortex-A8) fixed point on branch [1] ./test_unit_dft nfft=32 inverse=0,snr = 88.394372 nfft=32 inverse=1,snr = 93.896470 nfft=128 inverse=0,snr = 89.185895 nfft=128 inverse=1,snr = 93.537021 nfft=256 inverse=0,snr = 88.353151 nfft=256

Hello Jean-Marc, Yep, that was it.. with your patch, test_unit_mdct passes for all nfft. So, what you do you suggest the next step here is? Regards, Vish On 8 May 2015 at 12:30, Jean-Marc Valin <jmvalin at jmvalin.ca> wrote: > Hi, > > Can you apply this change to the MDCT test and run it again. See if more > (all) sizes pass. Given the results, I strongly suspect an

Dear All, There is no advantage of GUI over CLI, IMO. The real issue is the answer to the questions: "What should I do next?" or "What am I allowed to do here?" A "nice" interface, not necessarily GUI, will offer friendly answers: "I was expecting you to do _this_" or "In this situation you are allowed to do _these things_" You see, it's all

Hi, Apologies if this is a known issue, but running make on revision e3187444692195957eb66989622c7b1ad8448b06 fails one of the tests when using fixed point configuration (floating point is ok) on my linux x86. Note that libopus1.1, as extracted from the tar ball, is OK. Specifically, the tests that fail are in celt/tests/test_unit_mdct: nfft=32 inverse=0,snr = 85.341197 nfft=32 inverse=1,snr =

File names on a Samba share with accented characters using the NFD form of UTF8 cannot be seen or used by Mac clients. While tying to find a solution, I came across this old thread : https://lists.samba.org/archive/samba/2014-December/187545.html ("[Samba] Mount unix samba 4 share to osx client without mangled file names") A reply in that thread suggested: > >/Do I have

I'm trying to get these cleaned up and landed, but I'm running into some trouble with this patch. Using commit a08b29d88e3c (July 21) of Ne10, I'm seeing test failures for 60-point FFTs: nfft=60 inverse=0,snr = -3.312408 ** poor snr: -3.312408 ** nfft=60 inverse=1,snr = -16.079597 ** poor snr: -16.079597 ** All other sizes tested appear to work fine (84 to 140 dB of SNR). This

Hi all, I'm new to the group. I'm looking at the speex code with an eye towards maybe helping out with either codec optimization or fixed-point implementation, The SNR calculation in testenc.c and testenc_uwb.c doesn't make sense to me. The code is { float enoise=0, esig=0, snr; for (i=0;i<FRAME_SIZE;i++) {

I found a package on www.bioconductor.com that allows me to install using this line: source("http://bioconductor.org/biocLite.R") biocLite("MassSpecWavelet") The prompt showed me the following message: Running biocinstall version 2.1.10 with R version 2.6.2 Your version of R requires version 2.1 of Bioconductor. trying URL

Hi, there ! I'm pretty sure that the following text (and attached picture) explains the reason for the gain of high frequencies. when quantizing a vector scalar by scalar by simply rounding each scalar to the nearest level, the quantization-error-vector and the original signal-vector can be assumed to be orthogonal (average case) This is a problem when we want to preserve the energy level

I've had slew of problems with my Bell Canada Single Number Reach (SNR) dropping in the past couple of months. Another outage Monday for several hours has me wondering if there's a way to 1. Make a call out of my system via a PSTN back to my SNR line, say every 30 minutes (this I'm sure is easy enough via the call file...however...) 2. Track the outgoing call and match to an

Hi, I'd like to use R to do what excel pivot tables do, and plot results. I've never used R before, and I've managed to do something, but it's quite a lot of code to do something simple. I can't help but think I'm not "Doing it the R way". I could be using R for the wrong thing, in which case, please tell me off. I was hoping something like plot(by(t,

Hi Folks, I have just started using dplyr and could use some help getting unstuck. It could well be that dplyr is not the package to be using, but let me just pose the question and seek your advice. Here is my basic data frame. head(h) subject ageGrp ear hearingGrp sex freq L2 Ldp Phidp NF SNR 1 HALAF032 A L A F 2 0 -23.54459 55.56005 -43.08282

Dear R-List, I would like to recode categorial variables into binary data, so that all values above median are coded 1 and all values below 0, separating each var into two equally large groups (e.g. good performers = 0 vs. bad performers =1). I have not succeeded so far in finding a nice solution to do that in R. I thought there might be a better way than ordering each column and recoding the

Dear R-List, I would like to recode categorial variables into binary data, so that all values above median are coded 1 and all values below 0, separating each var into two equally large groups (e.g. good performers = 0 vs. bad performers =1). I have not succeeded so far in finding a nice solution to do that in R. I thought there might be a better way than ordering each column and recoding the