similar to: Announce: R from Python

Hi All: Walter Moreira wrote a small extension module for using the R programming language from within Python. Tim Church's example at http://www.cmat.edu.uy/~walterm/rpy was so compelling, I could not resist installing it on my Linux Mandrake 8.1 box. But I ran into problems. I have installed on Mandrake 8.1 both python and R: R-base-1.4.1-1mdk.i586.rpm

Walter Moreira wrote: > I wrote a small extension module for using the R programming language from > within Python. It makes it possible to use the huge mathematical and > statistical library of R from Python, almost whitout any changes from the text > of R manuals. > > As a side effect, it is also possible to use the full graphics capabilities of > R, which are extremely

I am trying to install Rpy to test it out as an R interface for a project that I am working on. However, I get the following error. Any clues as to what might be going on? I have alo tried RSPython, but I gave up due to errors. RSPython segfaults when started from R and gives an error message I can;t remember from python. Thanks, Brett >>> import rpy Traceback (most recent call

I am a long time user of R for financial time series analysis (xts, zoo, etc) and for my next project I am thinking of adding the Python language to the mix. The reason for adding Python is primarily its non-statistical capabilities. So my questions are what have people's experiences been with using interop between R and Python. I see there are two items, rPy and RSPython. It looks like rPy

>> Can some kind soul please give me a fool proof recipe for building R >> and RSPython so that it actually works? > I don't have a recipe, but one thought to help debug the process: Try > installing RPy [1]. RPy also provides access to R via Python and uses > the libR.so library. If you can install and "import rpy" without > problem then it must be

Hi, I'm planning to write some code in Python using R functions. I'm aware of the two R<->Python packages - Rpy and RSPython. Rpy seems easier to get up and running with, but does anybody have any comments regarding which would be a better system to work with in the long run? Thanks, ------------------------------------------------------------------- Rajarshi Guha <rxg218 at

Dear users, some days ago a user of the local network told me that she was not able to change ACL's through Windows. I've done some tests and indeed, when I right click a file/folder that is on the Samba server, the "Security" tab is no longer available. It does appear when I right-click any local file. The clients are running Windows XP Professional SP2 and the Samba server

A question for a (experienced) user of the RPython package on linux. I'm trying to call R from python on a linux (Suse 7.3) box. After installing R CMD INSTALL -c RSPython_0.5-2.tar.gz I start python and do: >>> import sys >>> sys.path.append('/usr/local/lib/R/library/RSPython') >>> sys.path.append('/usr/local/lib/R/library/RSPython/Python')

Hello, My platform is SuSE 8.1. After downloading and unpacking R version 1.7 I tried building with shared libs enabled. (./configure --enabl-R-shlib). My goal is to use RSPython but I am now in my own private segmentation fault hell. The R build worked fine: make, make check, make install cool. The RSPython build worked fine. Thinking I'm good to go, I run python. But when I import RS

Dear list, Rpy is a python module that provides python interface to R. The following simple commands >>> from rpy import * >>> r.plot(0) is supposed to create a window that displays the result of plot(0). However, we observe that 1. Under *nix, rpy+R+python work as expected 2. Under windows, python + pythonWin32 (a python GUI provided by the pywin32 module), work as expected

I develop quite a bit of R code that I tend to distribute, or let other people embed in their software. One of the things I'd really like to do is find a way to load an R library I've developed, and call one function with arguments. Currently, I achieve that by building a separate R client file, which reads in the command line arguments, loads the library, and calls the main

Under RSPython and rpy, the regexec C function is returning nonsensical results leading to segmentation faults. This is happening in some situations under R 1.4.1 and (more often?) under R 1.5.0 on my Solaris 8 box. R 1.4.1 was compiled with gcc 2.95.2, and I've tried 1.5.0 with both gcc 2.95.2 and gcc 3.0.3. The error appears to be exactly the same under both python tools and both

Hello I can construct a correlation matrix from an (ordered) vector of correlation coefficients as follows: x <- c(0.1,0.2,0.3,0.4,0.5) n <- length(x) cmat <- diag(rep(0.5,n)) cmat[lower.tri(cmat,diag=0)] <- x cmat <- cmat+t(cmat) But how to do the reverse operation, i.e. produce x from cmat? Thanks for help, Serguei Kaniovski [[alternative HTML version deleted]]

printCoefmat(signif.legend =FALSE) does not work properly. The option "signif.legend = FALSE" is ignored as shown in the example below. cmat <- cbind(rnorm(3, 10), sqrt(rchisq(3, 12))) cmat <- cbind(cmat, cmat[,1]/cmat[,2]) cmat <- cbind(cmat, 2*pnorm(-cmat[,3])) colnames(cmat) <- c("Estimate", "Std.Err", "Z value", "Pr(>z)") #

Hi, In the data below, "case" represents cases, "x" binary states. Each "case" has exactly 9 "x", ie is a binary vector of length 9. There are 2^9=512 possible combinations of binary states in a given "case", ie 512 possible vectors. I generate these in the order of the decimals the vectors represent, as:

Hello, I don't know if this question ought to go here, or rather on R-devel, so please bear with me. I'm interfacing to R via RPy (rpy.sf.net) and an embedded Python interpreter. This is really quite convenient. I use this approach to calculate the correlation coefficient of 1 independent dataset (vector) with 4 dependent vectors. It'd be nice if that could be done in 4 parallel

Hello, I don't know if this question ought to go here, or rather on R-devel, so please bear with me. I'm interfacing to R via RPy (rpy.sf.net) and an embedded Python interpreter. This is really quite convenient. I use this approach to calculate the correlation coefficient of 1 independent dataset (vector) with 4 dependent vectors. It'd be nice if that could be done in 4 parallel

I try to code the ULS factor analysis descrbied in ftp://ftp.spss.com/pub/spss/statistics/spss/algorithms/ factor.pdf # see PP5-6 factanal.fit.uls <- function(cmat, factors, start=NULL, lower = 0.005, control = NULL, ...) { FAfn <- function(Psi, S, q) { Sstar <- S - diag(Psi) E <- eigen(Sstar, symmetric = TRUE, only.values = TRUE) e <- E$values[-(1:q)] e <-

My data looks like this: > data name G_hat_0_0 G_hat_1_0 G_hat_2_0 G_0 G_hat_0_1 G_hat_1_1 G_hat_2_1 G_1 1 rs0 0.488000 0.448625 0.063375 1 0.480875 0.454500 0.064625 1 2 rs1 0.002375 0.955375 0.042250 1 0.000000 0.062875 0.937125 2 3 rs2 0.050375 0.835875 0.113750 1 0.877250 0.115875 0.006875 0 4 rs3 0.000000 0.074750 0.925250 2 0.897750 0.102000

How can I parse a YAML file in R 2.6.0 in Windows? I cannot get the RYaml package to compile in Windows, I can't find a MinGW compiled .dll for an existing YAML parser like syck (which would appear to be the best hope for creating my own R wrapper functions), and I don't know how to call a Ruby or Python function from R (so that I could parse the file in Ruby or Python and pass the parsed