SimDesign (version 2.17.1)

manageWarnings: Manage specific warning messages

Description

Function provides more nuanced management of known warning messages that appear in function calls outside the front-end users control (e.g., functions written in third-party packages). Specifically, this function provides a less nuclear approach than suppressWarnings, which suppresses all warning messages rather than those which are known to be innocuous to the current application, or when globally setting options(warn=2), which has the opposite effect of treating all warnings messages as errors in the function executions. To avoid these two extreme behaviors, character vectors can instead be supplied to this function to either leave the raised warnings as-is (default behaviour), raise only specific warning messages to errors, or specify specific warning messages that can be generally be ignored (and therefore suppressed) while allowing new or yet to be discovered warnings to still be raised.

Usage

manageWarnings(expr, warning2error = FALSE, suppress = NULL, ...)

Value

returns the original result of eval(expr), with warning messages either left the same, increased to errors, or suppressed (depending on the input specifications)

Arguments

expr

expression to be evaluated (e.g., ret <- myfun(args)). Function should either be used as a wrapper, such as manageWarnings(ret <- myfun(args), ...) or ret <- manageWarnings(myfun(args), ...), or more readably as a pipe, ret <- myfun(args) |> manageWarnings(...)

warning2error

logical or character vector to control the conversion of warnings to errors. Setting this input to TRUE will treat all observed warning messages as errors (same behavior as options(warn=2), though defined on a per expression basis rather than globally), while setting to FALSE (default) will leave all warning messages as-is, retaining the default behavior

Alternatively, and more useful for specificity reasons, input can be a character vector containing known-to-be-severe warning messages that should be converted to errors. Each supplied character vector element is matched using a grepl expression, so partial matching is supported (though more specific messages are less likely to throw false positives).

suppress

a character vector indicating warning messages that are known to be innocuous a priori and can therefore be suppressed. Each supplied warning message is matched using a grepl expression, so partial matching is supported (though more specific messages are less likely to throw false positives). If NULL, no warning message will be suppressed

...

additional arguments passed to grepl

Author

Phil Chalmers

Details

In general, global/nuclear behaviour of warning messages should be avoided as they are generally bad practice. On one extreme, when suppressing all warning messages using suppressWarnings, potentially important warning messages will become muffled, which can be problematic if the code developer has not become aware of these (now muffled) warnings. Moreover, this can become a long-term sustainability issue when third-party functions that the developer's code depends upon throw new warnings in the future as the code developer will be less likely to become aware of these newly implemented warnings.

On the other extreme, where all warning messages are turned into errors using options(warn=2), innocuous warning messages can and will be (unwantingly) raised to an error. This negatively affects the logical workflow of the developer's functions, where more error messages must now be manually managed (e.g., via tryCatch), including the known to be innocuous warning messages as these will now considered as errors.

To avoid these extremes, front-end users should first make note of the warning messages that have been raised in their prior executions, and organized these messages into vectors of ignorable warnings (least severe), known/unknown warnings that should remain as warnings (even if not known by the code developer yet), and explicit warnings that ought to be considered errors for the current application (most severe). Once collected, these can be passed to the respective warning2error argument to increase the intensity of a specific warning raised, or to the suppress argument to suppress only the messages that have been deemed ignorable a priori (and therefore allowing all other warning messages to be raised).

References

Chalmers, R. P., & Adkins, M. C. (2020). Writing Effective and Reliable Monte Carlo Simulations with the SimDesign Package. The Quantitative Methods for Psychology, 16(4), 248-280. tools:::Rd_expr_doi("10.20982/tqmp.16.4.p248")

See Also

manageMessages, quiet

Examples

if (FALSE) {

fun <- function(warn1=FALSE, warn2=FALSE, warn3=FALSE,
                warn_trailing = FALSE, error=FALSE){
   if(warn1) warning('Message one')
   if(warn2) warning('Message two')
   if(warn3) warning('Message three')
   if(warn_trailing) warning(sprintf('Message with lots of random trailings: %s',
                             paste0(sample(letters, sample(1:20, 1)), collapse=',')))
   if(error) stop('terminate function call')
   return('Returned from fun()')
}

# normal run (no warnings or errors)
out <- fun()
out

# these are all the same
manageWarnings(out <- fun())
out <- manageWarnings(fun())
out <- fun() |> manageWarnings()

# errors treated normally
fun(error=TRUE)
fun(error=TRUE) |> manageWarnings()

# all warnings/returns treated normally by default
ret1 <- fun(warn1=TRUE)
ret2 <- fun(warn1=TRUE) |> manageWarnings()
identical(ret1, ret2)

# all warnings converted to errors (similar to options(warn=2), but local)
fun(warn1=TRUE) |> manageWarnings(warning2error=TRUE)
fun(warn2=TRUE) |> manageWarnings(warning2error=TRUE)

# Specific warnings treated as errors (others stay as warnings)
# Here, treat first warning message as error but not the second or third
ret <- fun(warn1=TRUE) # warning
ret <- fun(warn1=TRUE) |> manageWarnings("Message one")  # now error
ret <- fun(warn2=TRUE) |> manageWarnings("Message one")  # still a warning

# multiple warnings raised but not converted as they do not match criteria
fun(warn2=TRUE, warn3=TRUE)
fun(warn2=TRUE, warn3=TRUE) |> manageWarnings("Message one")

# Explicitly convert multiple warning messages, allowing others through.
#   This is generally the best use of the function's specificity
fun(warn1=TRUE, warn2=TRUE)
fun(warn1=TRUE) |>   # error given either message
        manageWarnings(c("Message one", "Message two"))
fun(warn2=TRUE) |>
       manageWarnings(c("Message one", "Message two"))

# last warning gets through (left as valid warning)
ret <- fun(warn3=TRUE) |>
            manageWarnings(c("Message one", "Message two"))
ret

# suppress warnings that have only partial matching
fun(warn_trailing=TRUE)
fun(warn_trailing=TRUE)
fun(warn_trailing=TRUE)

# partial match, therefore suppressed
fun(warn_trailing=TRUE) |>
  manageWarnings(suppress="Message with lots of random trailings: ")

# multiple suppress strings
fun(warn_trailing=TRUE) |>
  manageWarnings(suppress=c("Message with lots of random trailings: ",
                           "Suppress this too"))

# could also use .* to catch all remaining characters (finer regex control)
fun(warn_trailing=TRUE) |>
  manageWarnings(suppress="Message with lots of random trailings: .*")


###########
# Combine with quiet() and suppress argument to suppress innocuous messages

fun <- function(warn1=FALSE, warn2=FALSE, warn3=FALSE, error=FALSE){
   message('This function is rather chatty')
   cat("It even prints in different output forms!\n")
   if(warn1) warning('Message one')
   if(warn2) warning('Message two')
   if(warn3) warning('Message three')
   if(error) stop('terminate function call')
   return('Returned from fun()')
}

# normal run (no warnings or errors, but messages)
out <- fun()
out <- quiet(fun()) # using "indoor voice"

# suppress all print messages and warnings (not recommended)
fun(warn2=TRUE) |> quiet()
fun(warn2=TRUE) |> quiet() |> suppressWarnings()

# convert all warning to errors, and keep suppressing messages via quiet()
fun(warn2=TRUE) |> quiet() |> manageWarnings(warning2error=TRUE)

# define tolerable warning messages (only warn1 deemed ignorable)
ret <- fun(warn1=TRUE) |> quiet() |>
  manageWarnings(suppress = 'Message one')

# all other warnings raised to an error except ignorable ones
fun(warn1=TRUE, warn2=TRUE) |> quiet() |>
  manageWarnings(warning2error=TRUE, suppress = 'Message one')

# only warn2 raised to an error explicitly (warn3 remains as warning)
ret <- fun(warn1=TRUE, warn3=TRUE) |> quiet() |>
  manageWarnings(warning2error = 'Message two',
                 suppress = 'Message one')

fun(warn1=TRUE, warn2 = TRUE, warn3=TRUE) |> quiet() |>
  manageWarnings(warning2error = 'Message two',
                 suppress = 'Message one')


###########################
# Practical example, converting warning into error for model that
# failed to converged normally

 library(lavaan)

## The industrialization and Political Democracy Example
## Bollen (1989), page 332
model <- '
  # latent variable definitions
     ind60 =~ x1 + x2 + x3
     dem60 =~ y1 + a*y2 + b*y3 + c*y4
     dem65 =~ y5 + a*y6 + b*y7 + c*y8

  # regressions
    dem60 ~ ind60
    dem65 ~ ind60 + dem60

  # residual correlations
    y1 ~~ y5
    y2 ~~ y4 + y6
    y3 ~~ y7
    y4 ~~ y8
    y6 ~~ y8
'

# throws a warning
fit <- sem(model, data = PoliticalDemocracy, control=list(iter.max=60))

# for a simulation study, often better to treat this as an error
fit <- sem(model, data = PoliticalDemocracy, control=list(iter.max=60)) |>
   manageWarnings(warning2error = "the optimizer warns that a solution has NOT been found!")

}