I am using the function FixedPoint() from the package FixedPoint for some computations in R. Even if a fixed point of some function cannot be found, FixedPoint() still returns output (indicating the error) and, in addition, returns an error message. I want to suppress any such additional error messages from being printed. Neither try(), nor suppressWarnings(), nor suppressMessages() seem to work. Please find an example below that produces such an additional error message.
library(FixedPoint)
ell=0.95
delta=0.1
r=0.1
lambda=1
tH=1
tL=0.5
etaL=1
etaH=1
sys1=function(y){
A=y[1]
B=y[2]
TA=(etaM*(1-exp(-(lambda*A+lambda*(A+B)+2*delta)*tL))-2*lambda*A^2-lambda*A*B)/2/delta
TB=(etaM*exp(-(lambda*A+lambda*(A+B)+2*delta)*tL)*(1-exp(-(lambda*(A+B)+2*delta)*(tH-tL)))-lambda*B^2-lambda*A*B)/2/delta
return(c(TA,TB))
}
FixedPoint(sys1,c(1.90,0.04))
This seems to work:
cc <- capture.output(ff <- FixedPoint(sys1,c(1.90,0.04)),type="message")
where ff now holds the output you want. (Alternately, you could wrap capture.output(...) in invisible() rather than assigning its return value to a variable.)
The problem seems to be that the error message emanates from an un-silence-d try() clause within the package code.
Related
Using the syuzhet package in R, the following works but returns a warning message:
object <- get_text_as_string("path/name.txt")
When I put this in a function, it returns the same warning error but does NOT change the value of object:
gen <- function(file){
object <- get_text_as_string(file)
}
gen("path/name.txt")
This is the warning message, if it matters:
Warning message:
In readLines(path_to_file) :
incomplete final line found on 'path/name.txt'
...but again, I get that from get_text_as_string() when used outside of the function, but it DOES change the value of object.
Anyone have any advice? There must be something I don't understand about functions?
(I've looked for similar questions/answers, if I've missed the right one I'd be happy to just be directed there.)
I got the error message:
Error: object 'x' not found
Or a more complex version like
Error in mean(x) :
error in evaluating the argument 'x' in selecting a method for function 'mean': Error: object 'x' not found
What does this mean?
The error means that R could not find the variable mentioned in the error message.
The easiest way to reproduce the error is to type the name of a variable that doesn't exist. (If you've defined x already, use a different variable name.)
x
## Error: object 'x' not found
The more complex version of the error has the same cause: calling a function when x does not exist.
mean(x)
## Error in mean(x) :
## error in evaluating the argument 'x' in selecting a method for function 'mean': Error: object 'x' not found
Once the variable has been defined, the error will not occur.
x <- 1:5
x
## [1] 1 2 3 4 5
mean(x)
## [1] 3
You can check to see if a variable exists using ls or exists.
ls() # lists all the variables that have been defined
exists("x") # returns TRUE or FALSE, depending upon whether x has been defined.
Errors like this can occur when you are using non-standard evaluation. For example, when using subset, the error will occur if a column name is not present in the data frame to subset.
d <- data.frame(a = rnorm(5))
subset(d, b > 0)
## Error in eval(expr, envir, enclos) : object 'b' not found
The error can also occur if you use custom evaluation.
get("var", "package:stats") #returns the var function
get("var", "package:utils")
## Error in get("var", "package:utils") : object 'var' not found
In the second case, the var function cannot be found when R looks in the utils package's environment because utils is further down the search list than stats.
In more advanced use cases, you may wish to read:
The Scope section of the CRAN manual Intro to R and demo(scoping)
The Non-standard evaluation chapter of Advanced R
While executing multiple lines of code in R, you need to first select all the lines of code and then click on "Run".
This error usually comes up when we don't select our statements and click on "Run".
Let's discuss why an "object not found" error can be thrown in R in addition to explaining what it means. What it means (to many) is obvious: the variable in question, at least according to the R interpreter, has not yet been defined, but if you see your object in your code there can be multiple reasons for why this is happening:
check syntax of your declarations. If you mis-typed even one letter or used upper case instead of lower case in a later calling statement, then it won't match your original declaration and this error will occur.
Are you getting this error in a notebook or markdown document? You may simply need to re-run an earlier cell that has your declarations before running the current cell where you are calling the variable.
Are you trying to knit your R document and the variable works find when you run the cells but not when you knit the cells? If so - then you want to examine the snippet I am providing below for a possible side effect that triggers this error:
{r sourceDataProb1, echo=F, eval=F}
# some code here
The above snippet is from the beginning of an R markdown cell. If eval and echo are both set to False this can trigger an error when you try to knit the document. To clarify. I had a use case where I had left these flags as False because I thought i did not want my code echoed or its results to show in the markdown HTML I was generating. But since the variable was then used in later cells, this caused an error during knitting. Simple trial and error with T/F TRUE/FALSE flags can establish if this is the source of your error when it occurs in knitting an R markdown document from RStudio.
Lastly: did you remove the variable or clear it from memory after declaring it?
rm() removes the variable
hitting the broom icon in the evironment window of RStudio clearls everything in the current working environment
ls() can help you see what is active right now to look for a missing declaration.
exists("x") - as mentioned by another poster, can help you test a specific value in an environment with a very lengthy list of active variables
I had a similar problem with R-studio. When I tried to do my plots, this message was showing up.
Eventually I realised that the reason behind this was that my "window" for the plots was too small, and I had to make it bigger to "fit" all the plots inside!
Hope to help
I'm going to add this on here even though it's not a new question as it comes quite highly in the search results for the error:
As mentioned above, re checking syntax, if you're using dplyr, make sure you have all the %>% pipes at the end of the lines above the error, otherwise the contents of anything like a select statement won't pass down into the next part of the code block.
I am running a simulation study in R. Occassionally, my simulation study produces an error message. As I implemented my simulation study in a function, the simulation stops when this error message occurs. I know that it is bad practice to suppress errors, but at this moment to me there is no other option than to suppress the error and then go on with the next simulation until the total number of simulations I like to run. To do this, I have to suppress the error message R produces.
To do this, I tried different things:
library(base64)
suppressWarnings
suppressMessages
options(error = expression(NULL))
In the first two options, only warnings and message are suprressed, so that's no help. If I understand it correctly, in the last case, all error messages should be avoided. However, that does not help, the function still stops with an error message.
Has someone any idea why this does not work the way I expect it to work? I searched the internet for solutions, but could only find the above mentioned ways.
In the function I am running my simulation, a part of the code is analysed by the external program JAGS (Gibbs sampler) and the error message is produced by this analysis. Might this be where it goes wrong?
Note that I do not have to supress a certain/specific error message, as there are no other error messages produced, it is 'good enough' to have an option that supresses just all error messages.
Thanks for your time and help!
As suggested by the previous solution, you can use try or tryCatch functions, which will encapsulate the error (more info in Advanced R). However, they will not suppress the error reporting message to stderr by default.
This can be achieved by setting their parameters. For try, set silent=TRUE. For tryCatch set error=function(e){}.
Examples:
o <- try(1 + "a")
> Error in 1 + "a" : non-numeric argument to binary operator
o <- try(1 + "a", silent=TRUE) # no error printed
o <- tryCatch(1 + "a")
> Error in 1 + "a" : non-numeric argument to binary operator
o <- tryCatch(1 + "a", error=function(e){})
There is a big difference between suppressing a message and suppressing the response to an error. If a function cannot complete its task, it will of necessity return an error (although some functions have a command-line argument to take some other action in case of error). What you need, as Zoonekynd suggested, is to use try or trycatch to "encapsulate" the error so that your main program flow can continue even when the function fails.
The knitr would always evaluate the R code before formatting the output, so just wondering how can I know whether the R code evaluation has error. Thanks
Basically it boils down to three lines of code in the evaluate package. The key is withCallingHandlers(), which can be used to capture errors, messages, and warnings, etc. A minimal example:
withCallingHandlers(1 + 'a', error = function(e) {
cat('An error occurred! The error object is:\n')
str(e)
})
If you don't want the error to halt R, you can wrap the code in try().
I'm facing a strange issue in R.
Consider the following code (a really simplified version of the real code but still having the problem) :
library(timeSeries)
tryCatch(
{
specificWeekDay <- 2
currTs <- timeSeries(c(1,2),c('2012-01-01','2012-01-02'),
format='%Y-%m-%d',units='A')
# just 2 dates out of range
start <- time(currTs)[2]+100*24*3600
end <- time(currTs)[2]+110*24*3600
# this line returns an empty timeSeries
currTs <- window(currTs,start=start,end=end)
message("Up to now, everything is OK")
# this is the line with the uncatchable error
currTs[!(as.POSIXlt(time(currTs))$wday %in% specificWeekDay),] <- NA
message("I'm after the bugged line !")
},error=function(e){message(e)})
message("End")
When I run that code in RGui, I correctly get the following output:
Up to now, everything is OK
error in evaluating the argument 'i' in
selecting a method for function '[<-': Error in
as.POSIXlt.numeric(time(currTs)) : 'origin' must be supplied
End
Instead, when I run it through RScript (in windows) using the following line:
RScript.exe --vanilla "myscript.R"
I get this output:
Up to now, everything is OK
Execution interrupted
It seems like RScript crashes...
Any idea about the reason?
Is this a timeSeries package bug, or I'm doing something wrong ?
If the latter, what's the right way to be sure to catch all the errors ?
Thanks in advance.
EDIT :
Here's a smaller example reproducing the issue that doesn't use timeSeries package. To test it, just run it as described above:
library(methods)
# define a generic function
setGeneric("foo",
function(x, ...){standardGeneric("foo")})
# set a method for the generic function
setMethod("foo", signature("character"),
function(x) {x})
tryCatch(
{
foo("abc")
foo(notExisting)
},error=function(e)print(e))
It seems something related to generic method dispatching; when an argument of a method causes an error, the dispatcher cannot find the signature of the method and conseguently raises an exception that tryCatch function seems unable to handle when run through RScript.
Strangely, it doesn't happen for example with print(notExisting); in that case the exception is correctly handled.
Any idea about the reason and how to catch this kind of errors ?
Note:
I'm using R-2.14.2 on Windows 7
The issue is in the way the internal C code implementing S4 method dispatch tries to catch and handle some errors and how the non-interactive case is treated in this approach. A work-around should be in place in R-devel and R-patched soon.
Work-around now committed to R-devel and R-patched.
Information about tryCatch() [that the OP already knew and used but I didn't notice]
I think you are missing that your tryCatch() is not doing anything special with the error, hence you are raising an error in the normal fashion. In interactive use the error is thrown and handled in the usual fashion, but an error inside a script run in a non-interactive session (a la Rscript) will abort the running script.
tryCatch() is a complex function that allows the potential to trap and handle all sorts of events in R, not just errors. However by default it is set up to mimic the standard R error handling procedure; basically allow the error to be thrown and reported by R. If you want R to do anything other than the basic behaviour then you need to add a specific handler for the error:
> e <- simpleError("test error")
> tryCatch(foo, error = function(e) e,
+ finally = writeLines("There was a problem!"))
There was a problem!
<simpleError in doTryCatch(return(expr), name, parentenv, handler): object 'foo'
not found>
I suggest you read ?tryCatch in more detail to understand better what it does.
An alternative is to use try(). To modify your script I would just do:
# this is the line with the uncatchable error
tried <- try(currTs[!(as.POSIXlt(time(currTs))$wday %in% specificWeekDay),] <- NA,
silent = TRUE)
if(inherits(tried, "try-error")) {
writeLines("There was an error!")
} else {
writeLines("Everything worked fine!")
}
The key bit is to save the object returned from try() so you can test the class, and to have try() operate silently. Consider the difference:
> bar <- try(foo)
Error in try(foo) : object 'foo' not found
> bar <- try(foo, silent = TRUE)
> class(bar)
[1] "try-error"
Note that in the first call above, the error is caught and reported as a message. In the second, it is not reported. In both cases an object of class "try-error" is returned.
Internally, try() is written as a single call to tryCatch() which sets up a custom function for the error handler which reports the error as a message and sets up the returned object. You might wish to study the R code for try() as another example of using tryCatch().