similar to: deafening silence

I'm actually not using 0.9 yet. I have my CD collection archived in 0.8 format, and I want to keep my ID3 tags. If someone can whip up a script that lets me extract my ID3 tags to a file for each file, decompress into WAV, then recompress into 0.9 format, then re-integrate the ID3 data, that'd be good. Otherwise. I'll be stuck in 0.8 forever. Which I don't want.... -- Asheesh.

I haven't seen too much feedback since the 0.9 release, which probably means one of three things: 1. it works perfectly and nobody has any complaints! 2. nobody is using 0.9. 3. the list is having problems. I mention #3 because at least one person has been blocked by sourceforge's new filter. Anyone...anyone? __________________________________________________ Do You Yahoo!? Get email

This will post-pend id3v1 tags. I thought they were found at the beginning of files. If not, then it looks fine to me. I may add some parentheses, though, like (tail -c 128 ${f} > tag) && (flac-0.8 -d $f ${f%flac}wav), etc. That decoding line should be "${f%.flac}", no "*", right? For simplicity's sake, I'm not going to take off the "." at the

This will post-pend id3v1 tags. I thought they were found at the beginning of files. If not, then it looks fine to me. I may add some parentheses, though, like (tail -c 128 ${f} > tag) && (flac-0.8 -d $f ${f%flac}wav), etc. That decoding line should be "${f%.flac}", no "*", right? Same with the encoding command: flac-0.9 -V ${f%flac}wav $f Seem better? (-8

if your talking id3v1, something along the lines of (in bash): for f in *.flac ; do tail -c 128 $f > tag && flac-0.8 -d $f ${f%*.flac}.wav && flac-0.9 -V ${f%*.flac}.wav $f && cat tag >> $f ; done should work. of course, test it before you set it loose on your whole collection. if you're on windows, my condolences... no wait, just get cygwin :) Josh ---

hi, I was wondering how perfect silence frames (no audio at all) in a PCM stream are encoded by the flac encoder. Suppose I have a PCM audio file with some perfect silence frames in the beginning and at the end of the audio recording and suppose I have the same audio file but without the silence frames in the beginning and at the end (so the second file is identical except for the silence frames

I was doing a daily make update for asterisk. On the 19th the new version compiled fine. I installed it. All of my ata 186's can call out to pstn etc. All inbound calls, the phones ring but when you pickup, just silence both local and remote with no complaints in the cli. I backed down to the r 1.0 1.0.3 on the 20th CVS-v1-0-12/20/04-18:24:52 it worked ok. Yesterday I did a cvs update on the

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Hello list, I'm trying to figure out how exactly the specification of nested random effects works in the lmer function of lme4. To give a concrete example, consider the rat-liver dataset from the R book (rats.txt from: http://www.bio.ic.ac.uk/research/mjcraw/therbook/data/ ). Crawley suggests to analyze this data in the following way: library(lme4) attach(rats) Treatment <-

Ronaldo, Further to my previous posting on your Glycogen nested aov model. Having read Douglas Bates' response and Reflected on his lmer analysis output of your aov nested model example as given.The Glycogen treatment has to be a Fixed Effect.If a 'treatment' isn't a Fixed Effect what is ? If Douglas Bates' lmer model is modified to treat Glycogen Treatment as a purely

Dear all, During my pre-R era I tried (yes, tried) to understand mixed models by working through the 'rat example' in Sokal and Rohlfs Biometry (2000) 3ed p 288-292. The same example was later used by Crawley (2002) in his Statistical Computing p 363-373 and I have seen the same data being used elsewhere in the litterature. Because this example is so thoroughly described, I thought

Hi, I''m trying to understand the lme output and procedure. I''m using the Crawley''s book. I''m try to analyse the rats example take from Sokal and Rohlf (1995). I make a nested analysis using aov following the book. > summary(rats) Glycogen Treatment Rat Liver Min. :125.0 Min. :1 Min. :1.0 Min. :1 1st Qu.:135.8

Your response nicely clarifies a question that I've had for a long time, but which I've dealt with by giving each subject a unique label. Unless I'm missing something, both techniques should work as the toy example below gives exactly the same output in all 3 cases below (forgetting about the convergence problem). Would there be a reason to prefer labeling the levels one way or

Fellow R users, I'm using the BCE {BCE} function to run a Bayesian sediment mixing model. The aim is to find the optimum % contribution from each of the 4 source areas that can yield the target geochemistry. I have geochemistry for 4 source areas called Rat: Rat<-read.table(text="CaO MgO Na2O Al2O3 Topsoils 2.511250 0.7445500 0.7085500 14.10375 ChannelBanks

Steffen, When the new biomaRt tries to load it errors out because I do not have RMySQL installed. There is not a Windows binary for RMySQL and it does contain C code that I do not know how to build. I do not use the MySQL option in biomaRt. Does RMySQL need to be a required dependency? Below is my screen output and sessionINfo. require(biomaRt) Loading required package: biomaRt Loading required

Hi All, I would like to ask a question on fixed and random effecti in lme. I am fiddlying around Mick Crawley dataset "rats" : http://www.bio.ic.ac.uk/research/mjcraw/statcomp/data/ The advantage is that most work is already done in Crawley's book (page 361 onwards) so I can check what I am doing. I am tryg to reproduce the nested analysis on page 368:

In a system connected to a verizon T1, Digium TE411P (quad T1 echo cancellation), client is complaining it is "too quiet". The complaint regards calls over the T1, not in house SIP only calls. Their description indicates they want some earpiece feedback of themselves speaking. Also, they complain that it takes several seconds (3-4) for the other party to respond. That is kind of

Hi! All, I am working on a dataset 'rat' with dimension 20500x363. I have calculated pca of samples (columns). Now I am trying to plot first two principle components with specified columns in different color. I have done following so far: > dim(rat) [1] 20500 363 >#specifying columns to be colored in red >

Dear R-people, recently at s-news we had a discussion about factor(). I thought you might be interested in some of my thoughts about factors. Any comments welcome Best regards Jens Oehlschlaegel-Akiyoshi ------------------------------------------------------------------- I think the problem is deeper than that factors would just be handled inapprobriately by some S+ functions, the

Hi, I have taken one microarray experiment and trying to implement same statistical measures what they have done.I have taken datasets from GEO platform with accession number GSE1557. In the experiment,about half of double transgenic rats (dTGR) over-expressing the human renin and angiotensinogen genes die by age 7 weeks of terminal heart failure (THF); the other (preterminal) half develops