I am trying to construct a function with an if statement within.
IN the code below,
I basically want to use different contr_x<- makeContrast.. command for different contr_x. ex) If contr_1 is in the input, it will use the first 1f's make constrast command, if contr_2 is in the input, it will use the second if's make constrast command...
But I am running in to the error that says the object contr_1 is not found. I am confused because in my understanding. contr_1 is just an input name, not an object. (not previously defined)
I am attaching the function code and the error below; I 'll appreciate any insight!!
code
run_limma <- function (model_x, support_x, fit_x,editing_x,contr_x,tmp_x){
message("starting modeling")
model_x<-model(support_x, model_x)
message("starting fitting")
fit_x<-limma_diff(editing_x, model_x,fit_x)
message("Making contrasts")
if (contr_x == "contr_1") {contr_x<-makeContrasts (diseaseAD - diseaseControl,
levels = colnames(coef(fit_x)))
}
if (contr_x == "contr_2") {contr_x<-makeContrasts (diseaseAD_MCI - diseaseControl,
levels = colnames(coef(fit_x)))
}
if (contr_x == "contr_3") {contr_x<-makeContrasts (diseaseMCI - diseaseControl,
levels = colnames(coef(fit_x)))
}
if (contr_x == "contr_4") {contr_x<-makeContrasts (diseasePD - diseaseControl,
levels = colnames(coef(fit_x)))
}
message("making tmp file")
tmp_x<-limma_cont(contr_x, fit_x, tmp_x)
tmp_x
}
error
run_limma(model_1, support_1, fit_1,editing_1,contr_1,tmp_1)
starting modeling
starting fitting
Making contrasts
Error in run_limma(model_1, support_1, fit_1, editing_1, contr_1, tmp_1) :
object 'contr_1' not found
Related
We have a basic tryCatch that writes a dataframe to Google Sheets, and trys again if the first write fails for any reason:
result = tryCatch({
print('TRYING')
googlesheets4::sheet_write(data = our_df, ss = our_spreadsheet, sheet = 'our_sheetname')
}, error = function(e) {
print('ERROR, TRYING AGAIN')
googlesheets4::sheet_write(data = our_df, ss = our_spreadsheet, sheet = 'our_sheetname')
})
It is possible to generalize this code to retry the googlesheets4::sheet_write() function call for N number of tries? Is something built into base R for this or is there a good R library that handles unlimited retries of a function?
You can put it in a for loop like this.
First, I am going to define a function that often fails (as I don't have access to your Google sheet).
russian_roulette <- function(n = 6) {
revolver <- sample(1:n, 1)
if (revolver == 1) {
return("You lived")
} else {
stop("Better luck next time...")
}
}
Then you can try it as many times as you consider reasonable. You can replace my call to russian_roulette() with your call to googlesheets4::sheet_write().
NUM_TRIES <- 10
for (i in 1:NUM_TRIES) {
message(i)
result <- try({
russian_roulette()
})
if (class(result) != "try-error") {
print("Success!")
break
}
}
Output:
1
Error in russian_roulette() : Better luck next time...
2
Error in russian_roulette() : Better luck next time...
3
Error in russian_roulette() : Better luck next time...
4
Error in russian_roulette() : Better luck next time...
5
Error in russian_roulette() : Better luck next time...
6
[1] "Success!"
result
# [1] "You lived"
I don't know why you expect writing to a file to fail - depending on the reason you may want to add a Sys.sleep() call in there for a certain number of seconds after every failure.
I am coding in R-studio and have a function called saveResults(). It takes:
sce - a Single Cell Experiment object.
opt - a list with five things
clusterLabels - simple dataframe with two columns
The important thing is that I receive an error stating:
Error: unexpected symbol in:
"saveResults(sce = sce, opt = opt, clusteInputs()
zhengMix"
which doesn't agree at all with the parameters I pass into the function. You can see this on the last line of the code block below: I pass in proper parameters, but I receive an error that says I have passed in clusteInputs(), and zhengMix instead of clusterLabels. I don't have a function called clusteInputs(), and zhengMix was several lines above.
# Save the clustering data
InstallAndLoadPackagesForSC3Clustering()
opt <- GetOptionInputs()
zhengMix <- FetchzhengMix(opt)
sce <- CreateSingleCellExperiment(zhengMix)
clusterLabels <- getClusterLabels(sce)
opt <- createNewDirectoriesToSaveData(opt)
saveResults <- function(sce, opt, clusterLabels){
print("Beginning process of saving results...")
maxClusters = ncol(clusterLabels)/2+1
for (n in 2:maxClusters){
savePCAasPDF(sce, opt, numOfClusters = n, clusterLabels)
saveClusterLabelsAsRDS(clusterLabels, numOfClusters = n, opt)
}
saveSilhouetteScores(sce, opt)
print("Done.")
}
saveResults(sce = sce, opt = opt, clusterLabels = clusterLabels)
Does anyone have an idea what is going on? I'm pretty stuck on this.
This isn't the best solution, but I fixed my own problem by removing the code out of the function and running it there caused no issues.
Background
I have a simple function called TBT. This function has a single argument called x. A user can provide any type rdistribution_name() (e.g., rnorm(), rf(), rt(), rbinom() etc.) existing in R for argument x, EXCEPT ONE: "rcauchy()".
Question
I was wondering how R could recognize that a user has provided an rcauchy() as the input for x, and when this is the case, then R issues a warning message?
Here is my R code with no success:
TBT = function(x) {
if( x == rcauchy(...) ) { warning("\n\tThis type of distribution is not supported.") }
}
TBT( x = rcauchy(1e4) )
Error in TBT(rcauchy(10000)) : '...' used in an incorrect context
If you are expeciting them do call to random function when they call your function, you could so
TBT <- function(x) {
xcall <- match.call()$x
if (class(xcall)=="call" && xcall[[1]]=="rcauchy") {
warning("\n\tThis type of distribution is not supported.")
}
}
TBT( x = rcauchy(1e4) )
But this would not catch cases like
x <- rcauchy(1e4)
TBT( x )
R can't track where the data in the x variable came from
I intend to record the errors in my R code while calling functions in a dataframe (ERR_LOG, say). I want to use 'try' to identify errors while calling a function,if any.The dataframe(ERR_LOG) will have the following columns :
Time : The time at which the function was called (Sys.time)
Loc : For which function call was this error recorded (name of the
function)
Desc : Description of the error which R throws at us (Error message
in R)
Example :
First I would like to initialize a blank dataframe 'ERR_LOG' with these columns
Then write the function
f <- function(a){
x <- a*100
return(x)
}
Now I put the output of the call to 'f' in 'chk'
chk <- try(f())
The above call gives the error 'Error in a * 100 : 'a' is missing' (description of the error)
Check
if(inherits(chk,'try-error'))
{then I want to populate ERR_LOG and stop the code execution}
How can this be done in R?
use tryCatch instead of try
Then inside tryCatch(), use the argument error=function(e){}
e will have an element named message, which is what you would like
Use the following call with browser to explore e$message:
x <- tryCatch(stop("This is your error message"), error=function(e) {browser()})
Note that your function need not be anonymous.
MyErrorParser <- function(e) {
m <- e$message
if (grepl("something", m))
do something
return (something_else)
}
## THEN
tryCatch(stop("This is a test"), error=MyErrorParser)
For a dataset of "Baltimore homicides"
It is required to create a function that takes a string for example "shooting" and return an integer represents the count of victims of "shooting".
I wrote the following function but i receive errors
Error: unexpected '}' in " }"
Error: object 'counti' not found
I also cant figure out if the ==Null is correct
count <- function(cause = NULL) {
## Check that "cause" is non-NULL; else throw error
if cause==NULL
{
stop()
print("no cause provided")
}
## Read "homicides.txt" data file
homicides <- readLines("homicides.txt")
## Extract causes of death
i <- grep(cause, homicides) ##get indices of cause
counti <- lenghth(i) ##get count of indices
## Check that specific "cause" is allowed; else throw error
if counti=0
{
stop()
print("no such cause")
}
## Return integer containing count of homicides for that cause
return(counti)
}
this is my working function after edit, thanks guys
count <- function(cause = NULL) {
if(missing(cause) | is.null(cause)) stop("no cause provided")
homicides <- readLines("homicides.txt")
i=length(grep(cause, homicides))
if(i==0) stop("no cause found")
return(i)
}
You can simplify your function to 2 lines by doing this:
count <- function(cause = NULL, data) {
if(is.null(cause)) stop("no cause provided")
length(grep(cause, data))
}
data <- c("murder", "some other cause")
count("murder", data)
[1] 1
Note the following principles:
R has many features of a functional language. This means that each function should, as far as possible, depend only on the arguments you pass it.
When you have a bug in your code, simplify it to the shortest possible version, fix the bug, then build out from there.
Also, keep stop() for really fatal errors. Not finding a search string in your data isn't an error, it simply means the cause wasn't found. You don't want your code to stop. At most, issue a message() or a warning().