I want to write a user defined function that I can replace part of R codes.
first, I ran the following code.
middle.pred.young <-PAMfunction(training=middle, met.status=middle$met,
test=young, ....)
correlation.middle <-corfunction(middle.pred.young)
(more R code with different functions to process the file
"middle.pred.young)
then, I replaced the word "middle" a few times to run the following codes;
old.pred.young <-PAMfunction(training=old, met.status=old$met, test=young,
....)
correlation.old <-corfunction(old.pred.young)
then more similar code I need to run;
all_age.pred.young <-PAMfunction(training=all_age, met.status=all_age$met,
test=young, ....)
correlation.allage <-corfunction(all_age.pred.young)
so, I only need to replace one word. I would like to copy SAS macro idea in R.
%macro predict;
&age..pred.young <-PAMfunction(training=&age, met.status=&age.$met,
test=young, ....);
correlation.&age <-corfunction(&age..pred.young);
.....;
%mend;
%predict(age="old")
%predict(age="middle")
%predict(age="all_age")
Can you do me a great favor to write R function to do the repetitive job?
Thank you,
Ding
2 answers
Hi Ding, this is the standard way of creating and then setting a function in R:
PAMfunction <- function(training, met.status=middle$met, test, ...)
{
correlation <- corfunction(get(paste(training, ".pred.", test, sep="")))
...
}
Then call the function
PAMfunction("old", old$met, "young")
In this situation, the following will be called corfunction(get("old.pred.yound")) The get() function will call a variable by its String name. If it's a file, as you seem to indicate, you will have to read it in with read.table() or read.csv()
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Welcome to biostars. Interesting guidelines for posting can be found in the following posts:
You didn't really specify whether you're interested in both results or just the last one.
The following function will return a list with both results (of PAMfunction and corfunction).
combinedFunction <- function(set_of_interest, test_set, ...){
dataset <- set_of_interest
pred_result <- PAMfunction(training = dataset,
met.status = dataset$met,
test = test_set, ....)
corr_result <- corfunction(pred_result)
return(list(pred_result, corr_result)
}
Use it so:
old <- combinedFunction(old, young)
middle <- combinedFunction(middle, young)
all <- combinedFunction(all_ages, young)
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Hi Kevin,
Thank you so much!! yes, I am a R beginner and did not know the "get()" function.