valid_variables_script_local.R

rm(list=ls())

dir_name <- readline("Introduce the name of the directory please: ")

setwd(dir_name)

source("dependency_installer.R")


dep_list = c("jsonlite", "stringr","DSI","DSOpal","DSLite", "fields", "metafor", "ggplot2", "gridExtra", "data.table", "dsBaseClient", "openxlsx")
install_dependencies(dep_list)

#source("connection_parameters.R")
#source("necessary_functions_connection.R")

codebook <- read.csv("new_harmon.csv" , sep = ",")

codebook_col_names <- as.data.frame(codebook$Harmonised.variable.name)

names(codebook_col_names) <- c("col_names")

setwd(paste(dir_name ,"/harmonized_data", sep=""))

file_name <- readline("Introduce the name of the file to check the values: ")
harmonized_data <- ""

if (grepl(".csv" , file_name , fixed = TRUE)){
  harmonized_data <- read.csv(file_name)
}else if (grepl(".xlsx" , file_name , fixed = TRUE)){
  harmonized_data <- read.xlsx(file_name)
}

#----------------------------------------------------------------------------

#Test if column names are valid
check_column_names <- function(col_names){
  
  str_res <- "The column names:"
  valid_colnames <- c()
  repeated_colnames <- c()
  for(i in 1:(nrow(col_names))){
    col_name <- col_names[i,1]
    number_of_column <- check_valid_name(col_name) 
    if( number_of_column == 0){
      str_res<- paste(str_res, col_name, sep=" ")
    }else if (number_of_column == 1){
      valid_colnames = c(valid_colnames, col_name)
    }else{
      repeated_colnames = c(repeated_colnames , col_name)
    }
  }
  
  str_res<- paste(str_res,"are not registered in the harmonized data codebook \n", sep=" ")
  
  new_list <- list("not_colnames" = str_res , "colnames" = valid_colnames , "repeated_colnames" = repeated_colnames)
  return (new_list)
  
}


#Test if a single variable name is valid
check_valid_name <- function(col_name){
  
  valid <- 0
  
  if(col_name %in% codebook_col_names$col_names){
    
    valid <- length(grep(col_name, names(harmonized_data)))
    
  }
  
  return (valid)
  
}

check_valid_values_continuous <- function(colname , codebook_param , column){
  column <- column[column != "."]
  possible_values_format <- codebook_param$Possible.values.format[codebook_param$Harmonised.variable.name == colname]
  possible_values_list =  str_split(possible_values_format , "/")[[1]]
  
  # Fallará cuando el codebook no tenga min-max / .
  range_as_str <- str_trim(possible_values_list[1])
  missing_value_format <- str_trim(str_trim(possible_values_list[2]))
  
  separate_range <- str_split(range_as_str , "-")[[1]]
  min_value  <- strtoi(separate_range[1]) 
  max_value  <- strtoi(separate_range[2])
  
  failing_values <- column[column < min_value | column > max_value]
  number_of_failing_values <- length(failing_values[!is.na(failing_values)])
  
  str_res <- ""
  if (number_of_failing_values == 0)
    str_res <- "No failing values"
  else{
    failing_values <- failing_values[!is.na(failing_values)]
    str_res <- paste("The failing values of column ", colname , paste(unlist(failing_values) , collapse =" "))
  }
    
  
  return(str_res)
}

check_valid_values_binary <- function(colname , column){
  column <- column[column != "."]
  failing_values <- column[column < 0 | column > 1]
  number_of_failing_values <- length(failing_values[!is.na(failing_values)])
  
  str_res <- ""
  if (number_of_failing_values == 0)
    str_res <- "No failing values"
  else{
    failing_values <- failing_values[!is.na(failing_values)]
    str_res <- paste("The failing values of column ", colname , paste(unlist(failing_values) , collapse =" "))
  }
    
  
  return(str_res)
}

check_valid_values_categorical <- function(colname , codebook_param , column){
  column <- column[column != "."]
  possible_values_format <- codebook_param$Possible.values.format[codebook_param$Harmonised.variable.name == colname]
  possible_values_list <-  str_split(possible_values_format , "/")[[1]]
  
  possible_values_list <- lapply(possible_values_list , str_trim)
  
  str_res <- ""
  min_value <- 0
  max_value <- 0 
  if (length(possible_values_list[[1]]) == 2){
    separate_range <-  str_split(possible_values_list[[1]][1], "-")[[1]]
    min_value  <- strtoi(separate_range[1]) 
    max_value  <- strtoi(separate_range[2])
    
  }else{
    
    possible_values_list <- lapply(possible_values_list , strtoi)[[1]]
    min_value <- possible_values_list[1]
    max_value <- possible_values_list[length(possible_values_list) - 1]
  }
  
  failing_values <- column[column < min_value | column > max_value ]
  number_of_failing_values <- length(failing_values[!is.na(failing_values)])
  
  if(number_of_failing_values == 0){
    str_res <- "No failing values"
  }else{
    failing_values <- failing_values[!is.na(failing_values)]
    str_res <- paste("The failing values of column ", colname , paste(unlist(failing_values) , collapse =" "))
  }
  
}

check_valid_values <- function(valid_colnames, codebook_param){
  
  res <- ""
  
  for(i in  1:(ncol(valid_colnames))){
    name <- names(valid_colnames)[i]
    #if("DMRBORN" == name | grepl("DAT", name, fixed=TRUE) | grepl("ISO", name , fixed=TRUE) | grepl("BEF", name, fixed=TRUE)){
     # next
    #}
    
    column <- valid_colnames[,i]
    
    # Esto falla si tu codebook no es mismo que new_harmon.csv
    column_type <- codebook_param$Variable.type[codebook_param$Harmonised.variable.name == name]
    
    result = switch(  
      column_type,  
      "Continuous"= check_valid_values_continuous(name , codebook_param , column),
      "Binary"= check_valid_values_binary(name , column),  
      "Categorical"= check_valid_values_categorical(name, codebook_param , column),
      "Calendar date" = paste("No failing values"),
      "ISO country code"= paste("No failing values"),
    )
    
    if (result != "No failing values"){
      res <- paste(res , result, sep="\n")
    }
  }
  
  return(res)
  
}


data_colnames <- as.data.frame(colnames(harmonized_data))

check_valid_columns <- check_column_names(data_colnames)

columns_not_valid <- check_valid_columns$not_colnames

valid_colnames_column <- as.data.frame(check_valid_columns$colnames)
names(valid_colnames_column) = c("valid_colnames")
valid_colnames_with_data <- subset(harmonized_data , select = valid_colnames_column$valid_colnames)


result <- ""
result<-check_valid_values(valid_colnames_with_data, codebook)
print(check_valid_columns)
#datashield.logout(connections) 
cat(result)



file_name<- paste(hospital_name,"_invalid_values.txt", sep="")


dir.create("../invalid_values", showWarnings = FALSE)
setwd("../invalid_values")

cat(check_valid_columns,file=file_name,sep="\n")
cat(result,file=file_name,append=TRUE)

#datashield.logout(connections)