[R] Function with large nested list

[@vi@e@gross m@iii@g oii gm@ii@com]

Emily,

I too copied/pasted your code in and it worked fine. I then asked for the
function definition and got it.

Did you put the entire text in? I mean nothing extra above or below except
maybe whitespace or comments?

What sometimes happens to make the code incomplete is to leave out a
matching parentheses of brace or bracket or sometimes quotes or using the
wrong kind of quote as in copying from a program like Microsoft Word.


-----Original Message-----
From: R-help <r-help-bounces using r-project.org> On Behalf Of Emily Bakker
Sent: Monday, December 18, 2023 4:56 AM
To: r-help using r-project.org
Subject: [R] Function with large nested list

Hello list,

I want to make a large rulebased algorithm, to provide decision support for
drug prescriptions. I have defined the algorithm in a function, with a for
loop and many if statements. The structure should be as follows:
1. Iterate over a list of drug names. For each drug:
2. Get some drug related data (external dataset). Row of a dataframe.
3.  Check if adaptions should be made to standard dosage and safety
information in case of contraindications. If patient has an indication,
update current dosage and safety information with the value from the
dataframe row. 
4. Save dosage and safety information in some lists and continue to the next
drug. 
5. When the iteration over all drugs is done, return the lists.

ISSUE:
So it is a very large function with many nested if statements. I have
checked the code structure multiple times, but i run into some issues. When
i try to run the function definiton, the command never "completes" in de
console. Instead of ">", the console shows "+". No errors are raised.

As I said, i have checked the structure multiple times, but cant find an
error. I have tried rebuilding it and testing each time i add a part. Each
part functions isolated, but not together in the same function. I can't find
any infinite loops either. 
I suspect the function may be too large, and i have to define functions for
each part separately. That isn't an issue necessarily, but i would still
like to know why my code won't run. And whether there are any downsides or
considerations for using many small functions.

Below is my code. I have left part of it out. There are six more parts like
the diabetes part that are similar.
I also use a lot of data/variabeles not included here, to try and keep
things compact. But I can provide additional information if helpful.
Thanks it advance for thinking along!!
Kind regards,
Emily

The code:

decision_algorithm <- function(AB_list, dataset_ab = data.frame(), diagnose
= 'cystitis', diabetes_status = "nee", katheter_status = "nee", 
                               lang_QT_status = "nee", obesitas_status =
"nee", zwangerschap_status = "nee", 
                               medicatie_actief =
data.frame(dict[["med_AB"]]), geslacht = "man", gfr=90){
  
  
  
  # vars
  list_AB_status <- setNames(as.list(rep("green", length(AB_list))),
names(AB_list)) #make a dict of all AB's and assign status green as deafault
for status
  list_AB_remarks <- setNames(as.list(rep("Geen opmerkingen",
length(AB_list))), names(AB_list)) #make a dict of all AB's and assign
"Geen" as default for remarks #Try empty list
  list_AB_dosering <- setNames(as.list(rep("Geen informatie",
length(AB_list))), names(AB_list)) # make named list of all AB's and assign
"Geen informatie", will be replaced with actual information in algorithm
  list_AB_duur <- setNames(as.list(rep("Geen informatie", length(AB_list))),
names(AB_list)) # make named list of all AB's and assign "Geen informatie",
will be replaced with actual information in algorithm
  
  ##### CULTURES #####
  for (i in names(AB_list)) {
    
    ab_data <- dataset_ab[dataset_ab$middel == i,] #get info for this AB
from dataset_ab
    
    # Extract and split the diagnoses, dosering, and duur info for the
current antibiotic
    ab_diagnoses <- str_split(ab_data$diagnoses, pattern = " \\| ")[[1]]
    ab_diagnose_dosering <- str_split(ab_data$`diagnose dosering`, pattern =
" \\| ")[[1]]
    ab_diagnose_duur <- str_split(ab_data$`diagnose duur`, pattern = " \\|
")[[1]]
    
    # Find the index of the current diagnose in the ab_diagnoses list
    diagnose_index <- match(diagnose, ab_diagnoses)
    
    # Determine dosering and duur based on the diagnose_index
    if (!is.na(diagnose_index)) {
      dosering <- ifelse(ab_diagnose_dosering[diagnose_index] ==
"standaard", ab_data$dosering, ab_diagnose_dosering[diagnose_index])
      duur <- ifelse(ab_diagnose_duur[diagnose_index] == "standaard",
ab_data$duur, ab_diagnose_duur[diagnose_index])
    } else {
      # Use general dosering and duur as fallback if diagnose is not found
      dosering <- ab_data$dosering
      duur <- ab_data$duur
    }
    
    list_AB_dosering[[i]] <- dosering
    list_AB_duur[[i]] <- duur
    
    if ((!is.null(AB_list[[i]]) && AB_list[[i]] == "I")) {
      list_AB_status[[i]] <- "yellow"
        list_AB_remarks[[i]] <- "Kweek verminderd gevoelig"
    } else if ((!is.null(AB_list[[i]]) && AB_list[[i]] == "R")) {
      list_AB_status[[i]] <- "red"
        list_AB_remarks[[i]] <- "Kweek resistent"
    }else if ((!is.null(AB_list[[i]]) && AB_list[[i]] == "S")) {
      next
    } else {
      list_AB_status[[i]] <- "yellow"
        list_AB_remarks[[i]] <- "Geen kweekgegevens"
    }
  
    
    # counters, for check if dosering / duur are updated more than once
    dosering_update_count <- 0
    duur_update_count <- 0
    
    ##### DIABETES #####
    if (diabetes_status == "ja") {
      if (ab_data$'diabetes veiligheid' == "ja") {
        list_AB_status[[i]] <- "red"
          list_AB_remarks[[i]] <- paste(list_AB_remarks[[i]], "Niet veilig
met diabetes")
      }

      if (ab_data$'diabetes effectiviteit' == "aanpassing") {
        dosering <- ifelse(ab_data$'diabetes dosering' != "standaard",
ab_data$'diabetes dosering', dosering) # if dosering does not equal
standaard, apply dosering in column, otherwise keep initial dosering
        duur <- ifelse(ab_data$'diabetes duur' != "standaard",
ab_data$'diabetes duur', duur) # if dosering does not equal standaard, apply
dosering in column, otherwise keep initial dosering
        dosering_update_count <- dosering_update_count + 1
        duur_update_count <- duur_update_count + 1
        list_AB_remarks[[i]] <- paste(list_AB_remarks[[i]],
ab_data$'diabetes opmerkingen')
      }

    } else if (diabetes_status == "?") {
      if (ab_data$'diabetes veiligheid' == "ja") {
        list_AB_remarks[[i]] <- paste(list_AB_remarks[[i]], "Waarschuwing:
Dit middel kan veiligheidsimplicaties hebben bij diabetes.")
      }
      if (ab_data$'diabetes effectiviteit' == "aanpassing") {
        list_AB_remarks[[i]] <- paste(list_AB_remarks[[i]], "Waarschuwing:
Dit middel kan dosisaanpassingen vereisen bij diabetes.")
      }
    }

    list_AB_dosering[[i]] <- dosering
    list_AB_duur[[i]] <- duur
    
    # within for loop
    
  }
  # within function
  return(list(status = list_AB_status, remarks = list_AB_remarks, duur =
list_AB_duur, dosering = list_AB_dosering))
}
    




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