I am using the "BMA" package in R 3.1.0, and get an error when running one of the functions in the package, iBMA.glm. When running the example in the package documentation:
## Not run:
############ iBMA.glm
library("MASS")
library("BMA")
data(birthwt)
y<- birthwt$lo
x<- data.frame(birthwt[,-1])
x$race<- as.factor(x$race)
x$ht<- (x$ht>=1)+0
x<- x[,-9]
x$smoke <- as.factor(x$smoke)
x$ptl<- as.factor(x$ptl)
x$ht <- as.factor(x$ht)
x$ui <- as.factor(x$ui)
### add 41 columns of noise
noise<- matrix(rnorm(41*nrow(x)), ncol=41)
colnames(noise)<- paste('noise', 1:41, sep='')
x<- cbind(x, noise)
iBMA.glm.out<- iBMA.glm( x, y, glm.family="binomial",
factor.type=FALSE, verbose = TRUE,
thresProbne0 = 5 )
summary(iBMA.glm.out)
I get the error:
Error in registerNames(names, package, ".__global__", add) :
The namespace for package "BMA" is locked; no changes in the global variables list may be made.
I get the error in RStudio running R 3.1.0 on Ubuntu.
on Windows 7, from RStudio and the R console I get a similar error:
Error in utils::globalVariables(c("nastyHack_glm.family", "nastyHack_x.df")) :
The namespace for package "BMA" is locked; no changes in the global variables list may be made.
I also get the same error when running my own data in the function. I'm not clear on what this error means and how to work around the error to be actually able to use the function. Any advice would be appreciated!
Related
I am trying to run the textEmbed function in R.
Set up needed:
require(quanteda)
require(quanteda.textstats)
require(udpipe)
require(reticulate)
#udpipe_download_model(language = "english")
ud_eng <- udpipe_load_model(here::here('english-ewt-ud-2.5-191206.udpipe'))
virtualenv_list()
reticulate::import('torch')
reticulate::import('numpy')
reticulate::import('transformers')
reticulate::import('nltk')
reticulate::import('tokenizers')
require(text)
It runs the following code
tmp1 <- textEmbed(x = 'sofa help',
model = 'roberta-base',
layers = 11)
tmp1$x
However, it does not run the following code
tmp1 <- textEmbed(x = 'sofa help',
model = 'roberta-base',
layers = 11)
tmp1$x
It gives me the following error
Error in x[[1]] : subscript out of bounds
In addition: Warning message:
Unknown or uninitialised column: `words`.
Any suggestions would be highly appreciated
I believe that this error has been fixed with a newer version of the text-package (version .9.50 and above).
(I cannot see any difference in the two code parts – but I think that this error is related to only submitting one token/word to textEmbed, which now works).
Also, see updated instructions for how to install the text-package http://r-text.org/articles/Extended_Installation_Guide.html
library(text)
library(reticulate)
# Install text required python packages in a conda environment (with defaults).
text::textrpp_install()
# Show available conda environments.
reticulate::conda_list()
# Initialize the installed conda environment.
# save_profile = TRUE saves the settings so that you don't have to run textrpp_initialize() after restarting R.
text::textrpp_initialize(save_profile = TRUE)
# Test so that the text package work.
textEmbed("hello")
I am developing an R package that calls functions from the package rstan. As a MWE, my test file is currently set up like this, using code taken verbatim from rstan's example:
library(testthat)
library(rstan)
# stan's own example
stancode <- 'data {real y_mean;} parameters {real y;} model {y ~ normal(y_mean,1);}'
mod <- stan_model(model_code = stancode, verbose = TRUE)
fit <- sampling(mod, data = list(y_mean = 0))
# I added this line, and it's the culprit
summary(fit)$summary
When I run this code in the console or via the "Run Tests" button in RStudio, no errors are thrown. However, when I run devtools::test(), I get:
Error (test_moments.R:11:1): (code run outside of `test_that()`)
Error in `summary(fit)$summary`: $ operator is invalid for atomic vectors
and this error is definitely not occurring upstream of that final line of code, because removing the final line allows devtools::test() to run without error. I am running up-to-date packages devtools and rstan.
It seems that devtools::test evaluates the test code in a setting where S4 dispatch does not work in the usual way, at least for packages that you load explicitly in the test file (in this case rstan). As a result, summary dispatches to summary.default instead of the S4 method implemented in rstan for class "stanfit".
The behaviour that you're seeing might relate to this issue on the testthat repo, which seems unresolved.
Here is a minimal example that tries to illuminate what is happening, showing one possible (admittedly inconvenient) work-around.
pkgname <- "foo"
usethis::create_package(pkgname, rstudio = FALSE, open = FALSE)
setwd(pkgname)
usethis::use_testthat()
path_to_test <- file.path("tests", "testthat", "test-summary.R")
text <- "test_that('summary', {
library('rstan')
stancode <- 'data {real y_mean;} parameters {real y;} model {y ~ normal(y_mean,1);}'
mod <- stan_model(model_code = stancode, verbose = TRUE)
fit <- sampling(mod, data = list(y_mean = 0))
expect_identical(class(fit), structure('stanfit', package = 'rstan'))
expect_true(existsMethod('summary', 'stanfit'))
x <- summary(fit)
expect_error(x$summary)
expect_identical(x, summary.default(fit))
print(x)
f <- selectMethod('summary', 'stanfit')
y <- f(fit)
str(y)
})
"
cat(text, file = path_to_test)
devtools::test(".") # all tests pass
If your package actually imports rstan (in the NAMESPACE sense, not in the DESCRIPTION sense), then S4 dispatch seems to work fine, presumably because devtools loads your package and its dependencies in a "proper" way before running any tests.
cat("import(rstan)\n", file = "NAMESPACE")
newtext <- "test_that('summary', {
stancode <- 'data {real y_mean;} parameters {real y;} model {y ~ normal(y_mean,1);}'
mod <- stan_model(model_code = stancode, verbose = TRUE)
fit <- sampling(mod, data = list(y_mean = 0))
x <- summary(fit)
f <- selectMethod('summary', 'stanfit')
y <- f(fit)
expect_identical(x, y)
})
"
cat(newtext, file = path_to_test)
## You must restart your R session here. The current session
## is contaminated by the previous call to 'devtools::test',
## which loads packages without cleaning up after itself...
devtools::test(".") # all tests pass
If your test is failing and your package imports rstan, then something else may be going on, but it is difficult to diagnose without a minimal version of your package.
Disclaimer: Going out of your way to import rstan to get around a relatively obscure devtools issue should be considered more of a hack than a fix, and documented accordingly...
I'm trying to use a few functions from car package, but while when starting the function (e.g. scatterplotMatrix or bcPower) I get a message "could not find function "scatterplotMatrix""
I I removed and installed package, updated R Studio and I still have the same problem.
A few lines from my code:
d <- read.csv2("World.csv")
d1 <- d[,c(1,16,25,27,47,56,57,58,59,70)]
d1 <- d1[complete.cases(d1), ]
scatterplotMatrix(d1[,2:9],smooth = FALSE)
I get:
Error in scatterplotMatrix(d1[, 2:9], smooth = FALSE) :
could not find function "scatterplotMatrix"
As recommended in other posts I wrote my own package in R to parallelize functions I wrote with Rcpp. I can load the package and everything works, but when I'm using optimParallel, I get the message:
Error in checkForRemoteErrors(val) :
3 nodes produced errors; first error: object '_EffES_profileLLcpp' not found
Here is what I'm doing:
library(optimParallel)
library(EffES) # EffES is my own package
cl <- makeCluster(detectCores()-1)
clusterEvalQ(cl, library(EffES))
clusterEvalQ(cl, library(optimParallel))
setDefaultCluster(cl = cl)
w.es <- optimParallel(par=rep(0.001,3), profileLLcpp, y=y.test, x=x.test, lower = rep(0.001,3), method = "L-BFGS-B")$par
Error in checkForRemoteErrors(val) :
3 nodes produced errors; first error: object '_EffES_profileLLcpp' not found
What am I doing wrong?
Edit: The problem is solved in optimParallel version 0.7-4
The version is available on CRAN: https://CRAN.R-project.org/package=optimParallel
For older versions:
As detailed in this post optimParallel() needs to trick a bit in order to have no restrictions on the argument names that can be passed through the ... argument. Currently, this implies that the function passed to optimParallel() has to be defined in the .GlobalEnv in order to find compiled code properly.
Hence, a workaround could be to define the function in the .GlobalEnv:
library(optimParallel)
library(EffES) # EffES is your own package
cl <- makeCluster(detectCores()-1)
clusterEvalQ(cl, library(EffES))
setDefaultCluster(cl=cl)
f <- function(par, y, x) {
profileLLcpp(par=par, x=x, y=y)
}
optimParallel(par=rep(0.001,3), f=f, y=y.test, x=x.test,
lower = rep(0.001,3), method = "L-BFGS-B")$par
Suggestions to improve the code of optimParallel() are welcome. I opened a corresponding question here.
You have to spread the object '_EffES_profileLLcpp' to each core of your cluster. You can do this using clusterExport, in your case:
clusterExport(cl,'_EffES_profileLLcpp')
Repeat this step with every object needed to be used in parallel (or just check which object shows up in the error log and spreat it using clusterExport).
Hope this helps
I'm using the R leaps package to obtain a fit to some data:
(My dataframe df contains a Y variable and 41 predictor variables)
require(leaps)
N=3
regsubsets(Y ~ ., data = df, nbest=1, nvmax=N+1,force.in="X", method = 'exhaustive')-> regfit
coef(regfit,id = N)
When I run the code more than once (the first time works fine) I get the following error when I run the coef command:
Error in .Fortran("REORDR", np = as.integer(object$np), nrbar = as.integer(object$nrbar), :
"reordr" not resolved from current namespace (leaps)
Any help with why this is happening would be much appreciated.
A.
I had to build the package from source inserting the (PACKAGE = 'leaps') argument into the REORDR function in the leaps.R file. It now works fine every time.
The solution is related to:
R: error message --- package error: "functionName" not resolved from current namespace