I have a function in R as follows

DrawDistroGenerationClass <- function(in_hourStr, in_data){

  me <- methods::setRefClass(
    ## Define the environment where this list is defined so
    ## that I can refer to it later.
    "Draw",
    fields = list(hourStr = "character",
                  data = "numeric"),

    methods = list(
      getModel = function(){
        return("Draw Distro")
    },
      getName = function(){
        return(hourStr)
    },
      #' 
      #' @param strName the data to be drawn from
      #' @return the new hours value
      generateHoursFromStorage = function(strName){


        indSelect <- stats::runif(1, min = 1, max = length(data))

        componentLife <- data[indSelect]

        return(componentLife)
    }
    )
  )
  ## Set the name for the class
  newMe <- me$new(hourStr = in_hourStr, data = in_data)
  return(newMe)
}

The test looks like...

test_that("test Time2Repair-DrawDistroHoursGenerationClass", {

  distroHoursGenerationClass <- DrawDistroHoursGenerationClass("test", c(0.0, 1.0, 2.0, 3.0))


  testthat::expect_equal(distroHoursGenerationClass$getModel(), "Draw Distro")

  testthat::expect_equal(distroHoursGenerationClass$getName(), "test")

  testthat::expect_true(is.numeric(distroHoursGenerationClass$generateHoursFromStorage("test")))

}
)

With the purpose being I can call the function DrawDistroGenerationClass with a label and a set of values, and generate a function that will randomly draw from that set any time a call it.

The function works, but within my R project I have a unit test (testthat) for this function, and when I run R cmd I get:

1. -methods::setRefClass(...)
2. -methods::setClass(...)
3. -methods::assignClassDef(Class, classDef, where)

4. -base::assign(mname, def, where)

   "Error in assign(mname, def, where): cannot add bindings to a locked environment".

I have no idea why this problem is occurring/

I rather not make my input variables global (as they might conflict with other classes), and I'm using the setRefClass method here so I can make many independent versions of this function.