从函数内部使用jags.parallel(R语言get(name，envir = envir)中的错误:未找到对象'y') [英] Using jags.parallel from within a function (R language Error in get(name, envir = envir) : object 'y' not found)

问题描述

从命令行或脚本中使用jags.parallel可以正常工作.我可以从 http://www.inside-r运行此修改后的示例.org/packages/cran/R2jags/docs/jags 很好

# An example model file is given in:
  model.file <- system.file(package="R2jags", "model", "schools.txt")
#=================#
# initialization  #
#=================#

  # data
  J <- 8.0
  y <- c(28.4,7.9,-2.8,6.8,-0.6,0.6,18.0,12.2)
  sd <- c(14.9,10.2,16.3,11.0,9.4,11.4,10.4,17.6)

  jags.data <- list("y","sd","J")
  jags.params <- c("mu","sigma","theta")
  jags.inits <- function(){
    list("mu"=rnorm(1),"sigma"=runif(1),"theta"=rnorm(J))
  }


#===============================#
# RUN jags and postprocessing   #
#===============================#
#  jagsfit <- jags(data=jags.data, inits=jags.inits, jags.params, 
#    n.iter=5000, model.file=model.file)

  # Run jags parallely, no progress bar. R may be frozen for a while, 
  # Be patient. Currenlty update afterward does not run parallelly

  print("Running Parallel") 
  jagsfit <- jags.parallel(data=jags.data, inits=jags.inits, jags.params, 
    n.iter=5000, model.file=model.file)

但是，如果我将其包装在函数中

testparallel <- functions(out){
# An example model file is given in:
    .
    .
    .
jagsfit <- jags.parallel(data=jags.data, inits=jags.inits, jags.params, 
  n.iter=5000, model.file=model.file)
print(out)
return(jagsfit)
}

然后我得到了错误: get(name，envir = envir)中的错误:找不到对象"y" 根据我在此处的发现，我知道这是一个问题导出到集群的环境，我已经通过更改对其进行了修复

J <- 8.0
y <- c(28.4,7.9,-2.8,6.8,-0.6,0.6,18.0,12.2)
sd <- c(14.9,10.2,16.3,11.0,9.4,11.4,10.4,17.6)

到

  assign("J",8.0,envir=globalenv()) 
  assign("y",c(28.4,7.9,-2.8,6.8,-0.6,0.6,18.0,12.2),envir=globalenv()) 
  assign("sd",c(14.9,10.2,16.3,11.0,9.4,11.4,10.4,17.6),envir=globalenv()) 

有更好的方法解决这个问题吗?

谢谢你， 格雷格

P.S.

我正在为其他人编写此代码，因此我确实不想更改R2jags软件包中的内容，尽管我打算向软件包的作者建议，但我不想让它进入要导出的环境.

解决方案

所以我联系了R2jags的作者，他在jags.parallel中添加了一个附加参数，使您可以传递envir，然后将其传递给clusterExport. /p>

这很好用，除了它允许我的数据名称与jags.parallel函数中的变量之间发生冲突.

Using jags.parallel from the command line or a script works fine. I can run this modified example from http://www.inside-r.org/packages/cran/R2jags/docs/jags just fine

# An example model file is given in:
  model.file <- system.file(package="R2jags", "model", "schools.txt")
#=================#
# initialization  #
#=================#

  # data
  J <- 8.0
  y <- c(28.4,7.9,-2.8,6.8,-0.6,0.6,18.0,12.2)
  sd <- c(14.9,10.2,16.3,11.0,9.4,11.4,10.4,17.6)

  jags.data <- list("y","sd","J")
  jags.params <- c("mu","sigma","theta")
  jags.inits <- function(){
    list("mu"=rnorm(1),"sigma"=runif(1),"theta"=rnorm(J))
  }


#===============================#
# RUN jags and postprocessing   #
#===============================#
#  jagsfit <- jags(data=jags.data, inits=jags.inits, jags.params, 
#    n.iter=5000, model.file=model.file)

  # Run jags parallely, no progress bar. R may be frozen for a while, 
  # Be patient. Currenlty update afterward does not run parallelly

  print("Running Parallel") 
  jagsfit <- jags.parallel(data=jags.data, inits=jags.inits, jags.params, 
    n.iter=5000, model.file=model.file)

However if I wrap it in a function

testparallel <- functions(out){
# An example model file is given in:
    .
    .
    .
jagsfit <- jags.parallel(data=jags.data, inits=jags.inits, jags.params, 
  n.iter=5000, model.file=model.file)
print(out)
return(jagsfit)
}

Then I get the error: Error in get(name, envir = envir) : object 'y' not found Based on what I found here I know that it is an issue with the environment exported to the cluster and I have fixed it by changing

J <- 8.0
y <- c(28.4,7.9,-2.8,6.8,-0.6,0.6,18.0,12.2)
sd <- c(14.9,10.2,16.3,11.0,9.4,11.4,10.4,17.6)

to

  assign("J",8.0,envir=globalenv()) 
  assign("y",c(28.4,7.9,-2.8,6.8,-0.6,0.6,18.0,12.2),envir=globalenv()) 
  assign("sd",c(14.9,10.2,16.3,11.0,9.4,11.4,10.4,17.6),envir=globalenv()) 

Is there a better way to get around this?

Thank you, Greg

P.S.

I am working on this code for someone else so I don't really want to changes things in the R2jags package to let me pass in the environment to export though I plan on suggesting it to the authors of the package.

解决方案

So I have contacted the author of R2jags and he has added an addition argument to jags.parallel that lets you pass envir, which is then past onto clusterExport.

This works well except it allows clashes between the name of my data and variables in the jags.parallel function.

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