similar to: Joining tables and query design advice

Hello, Here's a script i use to join multiple PCM source files and feed them to FLAC. In the future i plan to add tag support from static CDDB (files). It would be nice if this feature could be incorporated to the native encoder. Another idea is to have flac/metaflac support joining FLAC files themselves (but this is much heavier to implement) -- and may pose issues with meta info like

Dear all, I am having trouble creating summary tables using aggregate function. given the following table: Var1 Var2 Var3 dummy S1 T1 I 1 S1 T1 I 1 S1 T1 D 1 S1 T1 D 1 S1 T2 I 1 S1 T2 I 1 S1 T2 D 1 S1 T2 D 1 S2

Hello list, I am wondering if a joining "one-to-many" can be done a little bit easier. I tried merge function but I was not able to do it, so I end up using for and if. Suppose you have a table with locations, each location repeated several times, and some attributes at that location. The second table has the same locations, but only once with a different set of attributes. I would

Dear All user, Hello, I'm a student and I have some trouble with the experimental (columns-experiments) design of my project. I use a randomized block design with 4 treatments including a control. For each treatment, I use 3 replicates and 3 blocks. The treatments are: -T1 = COD (300 mg/Lit) COD=chemical oxygen demand -T2 = COD (200 mg/Lit) -T3 = COD (100 mg/Lit) -T4 = COD (0 mg/Lit) as

The code below is intended to analyse a textbook example of a balanced incomplete block design: # # Data taken from pp. 219-230 in # Cox, D.R. (1958) Planning of Experiments. John Wiley and Son, Inc. New York. 308 pp. # day <- factor(rep(1:10, each = 3)) T <-

Dear R community, I wish to combine two tables in one by adding an additional dimension: e.g.: > t1<-as.table(matrix(rnorm(40),nrow=4,ncol=10));rownames(t1)<-c("rowone","rowtwo","rowthree","rowfour") > t1 A B C D E F G H I J rowone

R Help: I have read a number of tables into R with identical headings and I would now like to make a single table that has all the data appended under this single heading line. for example: t1 <- read.csv("f1",header=TRUE) t2 <- read.csv("f2",header=TRUE) all <- c(t1,t2) #all is now twice as wide as t1 or t2 with the same number of row!!!! #I need to know how

Hello I'm trying to write a function to calculate the relative entropy between two distributions. The data I have is in table format, for example: > t1 <- prop.table(table(c(0,0,2,4,4))) > t2 <- prop.table(table(c(0,2,2,2,3))) > t1 0 2 4 0.4 0.2 0.4 > t2 0 2 3 0.2 0.6 0.2 The relative entropy is given by H[P||Q] = sum(p * log2(p/q)) with the

Database structure as follows: t1 -> t2 -> t3 -> t4 select * from t1; +----+-------+-------+ | id | t2_id | t3_id | +----+-------+-------+ | 1 | 1 | null | | 2 | null | 1 | | 3 | null | 2 | +----+-------+-------+ select * from t2; +----+-------+ | id | title | +----+-------+ | 1 | "hat" | +----+-------+ select * from t3; +----+-------+ | id | t4_id |

I have big .csv file. I would like to filter that file into a new table. For example, I have .csv file as below: f1 f2 f3 f4 f5 f6 f7 f9 f10 f11 t1 1 0 1 0 1 0 0 0 0 1 t2 1 0 0 0 0 1 1 1 1 1 t3 0 0 0 0 0 0 0 0 0 0 t4 1 0 0 0 1 0 0 0 0 0 t5 0 0 0 0 0 0 0 0 0 0 t6 0 0 0 0 0 0

Hello, Am writing to the list in the hope that someone out there might be able to help me make sure I have the right configuration here. I''m not all that au fait with routing using multiple interfaces. Some time ago I configured a web server to have two different IP addresses from two different network ranges on each of it''s two ethernet cards. I followed the excellent

I'm attempting to create a sequence for an experiment and am hoping I can use R to create it. It has several constraints: (1) It is made up of two sequences (red and green) that have 4 different repeating triplets (e.g. T1=ABC T2=DEF T3=GHI JKL) (2) Each sequence has the following constraints: (a) there cannot be repeating triplets (e.g. T1 T1), (b) there cannot be repeating triplet pairs

Hi, I have big .csv file. I would like to filter that file into a new table. For example, I have .csv file as below: f1 f2 f3 f4 f5 f6 f7 f9 f10 f11 t1 1 0 1 0 1 0 0 0 0 1 t2 1 0 0 0 0 1 1 1 1 1 t3 0 0 0 0 0 0 0 0 0 0 t4 1 0 0 0 1 0 0 0 0 0 t5 0 0 0 0 0 0 0 0 0 0 t6 0 0 0 0 0 0 0 0 0 0

this is a clearer (I hope) version of an earlier post - My problem is formulating the random = argument to give estimates of all 9 random components for this kind of setup where there are (I think) 9 variance/covariance components ... Study.1 Study.2 ... Study.5 Treatment T1: subject: 1 2 3 4 5 6 ... 13 14 15 Treatment T2: subject: 16 17

Building of llvm with gcc-4.5.2-1 gives these warnings: 1) Building FileManagerTest "llvm[4]: Compiling FileManagerTest.cpp for Debug+Asserts build C:/Programming/VersionControl/llvm/tools/clang/unittests/Basic/FileManagerTest.cpp: In member function 'virtual void<unnamed>::FileManagerTest_NoVirtualDirectoryExistsBeforeAVirtualFileIsAdded_Test::TestBody()':

Hello. I'd like to compute the associate vector of distances between leaves in a binary non-rooted tree. The definition of a distance between two leaves in a binary non-rooted tree is the number of edges in the path joining the two leaves. I've tried the ape package but I'm unable to find this vector. For example, using rtree(5,rooted=F) I've obtained the following tree: $edge

#subject: type III sum of squares - anova() Anova() AnovaM() #R-version: 2.12.2 #Hello everyone, #I am currently evaluating experimental data of a two factor experiment. to illustrate de my problem I will use following #dummy dataset: Factor "T1" has 3 levels ("A","B","C") and factor "T2" has 2 levels "E" and "F". The

Hi R user, I could not combine two tables. Would any one help me on how I can combine with following example tables? > T1 X Y Z XX A 1 5 9 13 B 2 6 10 14 C 3 7 11 15 D 4 8 12 16 > T2 X Y XX a 1 4 7 b 2 5 8 c 3 6 9 I want to get the following table cT X Y XX A 1 5 13 B 2 6 14 C 3 7 15 D 4 8 16 A1 1 4 7 B1 2 5 8 C1 3 6 9 Thanks for your help. Thanks, Kristi ===

?s 15:13 de 10/10/2024, Jeff Newmiller via R-help escreveu: > POSIXt vectors do not support different time zones element-to-element. > > If you want to keep track of timezones per element, you have to create a vector of timestamps (I would recommend POSIXct using UTC) and a parallel vector of timezone strings. How you manipulate these depends on your use cases, but from R's

I think this is a great patch but, in my view, an even better way to tackle the fundamental problem (the performance limitations) is to use a much faster checksum like xxhash, as has been suggested before: https://lists.samba.org/archive/rsync/2019-October/031975.html Cheers, Filipe On Mon, 18 May 2020 at 17:08, Jorrit Jongma via rsync <rsync at lists.samba.org> wrote: > This drop-in