valid_variables_script_local.R

rm(list=ls())

dir_name <- readline("Introduce the name of the directory please: ")
# C:\Users\guill\Documents\harmonize_scripts

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)

codebook_file <- "20220315_Data Harmonisation.xlsb.xlsx"

codebook_demo <- read.xlsx(codebook_file , sheet = 2 )
codebook_com_and_rf <- read.xlsx(codebook_file , sheet = 3 ) 

codebook_home_med <- read.xlsx(codebook_file , sheet = 4 ) 
codebook_si_sympt <- read.xlsx(codebook_file , sheet = 5 ) 

codebook_treatments <- read.xlsx(codebook_file , sheet = 6 ) 
codebook_labo <- read.xlsx(codebook_file , sheet = 7 ) 

codebook_complications <- read.xlsx(codebook_file , sheet = 8 ) 
codebook_imaging_data <- read.xlsx(codebook_file , sheet = 9 ) 

codebook_lifestyle_diet <- read.xlsx(codebook_file , sheet = 10 ) 
codebook_dates <- read.xlsx(codebook_file , sheet = 11 )

codebook <- rbind(codebook_demo , codebook_com_and_rf)
codebook <- rbind(codebook , codebook_home_med)
codebook <- rbind(codebook , codebook_si_sympt)
codebook <- rbind(codebook , codebook_treatments)
codebook <- rbind(codebook , codebook_labo)
codebook <- rbind(codebook , codebook_complications)
codebook <- rbind(codebook , codebook_imaging_data)

codebook_lifestyle_diet <- codebook_lifestyle_diet[, !names(codebook_lifestyle_diet) %in% c("X2", "X4" , "X10")] 
codebook <- rbind(codebook , codebook_lifestyle_diet)
codebook <- rbind(codebook , codebook_dates)


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]]
#   
#   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)]
#     failing_value_counts <- table(failing_values)
#     
#     str_res <- paste(colname, "has failing values:")
#     
#     for (i in seq_along(failing_value_counts)) {
#       value <- names(failing_value_counts)[i]
#       count <- failing_value_counts[i]
#       str_res <- paste(str_res, paste(value, "(", count, "times)", collapse = " "), sep = " ")
#     }
#     
#     str_res <- paste(str_res, "should be in range", range_as_str, "(continuous)", sep = " ")
#   }
#   
#   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 {
#     range_as_str <- paste(min_value, "-", max_value, " (categorical)")
#     failing_values <- failing_values[!is.na(failing_values)]
#     failing_value_counts <- table(failing_values)
#     
#     str_res <- paste(colname, "has failing values:")
#     
#     for (i in seq_along(failing_value_counts)) {
#       value <- names(failing_value_counts)[i]
#       count <- failing_value_counts[i]
#       str_res <- paste(str_res, paste(value, "(", count, "times)", collapse = " "), sep = " ")
#     }
#     
#     str_res <- paste(str_res, "should be in range", range_as_str, sep = " ")
#   }
#   
#   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 {
#     range_as_str <- "0-1 (binary)"
#     failing_values <- failing_values[!is.na(failing_values)]
#     failing_value_counts <- table(failing_values)
#     
#     str_res <- paste(colname, "has failing values:")
#     
#     for (i in seq_along(failing_value_counts)) {
#       value <- names(failing_value_counts)[i]
#       count <- failing_value_counts[i]
#       str_res <- paste(str_res, paste(value, "(", count, "times)", collapse = " "), sep = " ")
#     }
#     
#     str_res <- paste(str_res, "should be in range", range_as_str, sep = " ")
#   }
#   
#   return(str_res)
# }

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]]
  
  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 {
    range_as_str <- paste(min_value, "-", max_value, "(continuous)")
    
    str_res <- paste(colname, "has", number_of_failing_values, "failing values")
    str_res <- paste(str_res, "should be in range", range_as_str, sep = " ")
  }
  
  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 {
    range_as_str <- paste(min_value, "-", max_value, " (categorical)")
    
    str_res <- paste(colname, "has", number_of_failing_values, "failing values")
    str_res <- paste(str_res, "should be in range", range_as_str, sep = " ")
  }
  
  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 {
    range_as_str <- "0-1 (binary)"
    
    str_res <- paste(colname, "has", number_of_failing_values, "failing values")
    str_res <- paste(str_res, "should be in range", range_as_str, sep = " ")
  }
  
  return(str_res)
}



check_valid_values <- function(valid_colnames, codebook_param){
  
  res <- ""
  
  for(i in  1:(ncol(valid_colnames))){
    name <- names(valid_colnames)[i]
    
    if (grepl("DAT", name, fixed=TRUE)){
      next
    }
    
    #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]
    
    if (is.na(column_type) ) {
        variable <- paste("Variable ", name, " wrong", sep = " ")
        res <- paste(res,  variable , sep="\n")
        next
      }
    
    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"),
      {
        paste("some column " , column_type , sep = " ")
      }
    )
    
    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(columns_not_valid)
cat(result)