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R/utils_authentication.R
In verdata: Analyze Data from the Truth Commission in Colombia
Defines functions
build_path
medidas
# ============================================
# Authors: MJ
# Maintainers: MJ, MG
# Copyright: 2023, HRDAG, GPL v2 or later
# ============================================
#' Calculate measurements in order to make sure each replicate file has the correct
#' content.
#'
#' @param replicate_path A string that contains a path to the replicate to be checked.
#'
#' @return A data frame with the results.
#'
#' @noRd
medidas <- function(replicate_path) {
ext <- tools::file_ext(replicate_path)
if (ext == "parquet") {
replicate_data <- arrow::read_parquet(replicate_path)
}
else {
replicate_data <- readr::read_csv(replicate_path)
}
replicate <- unique(replicate_data$replica)
dpto <- replicate_data %>%
dplyr::group_by(dept_code_hecho) %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::filter(dept_code_hecho == 5 | dept_code_hecho == 20) %>%
dplyr::mutate(variable = dplyr::recode(dept_code_hecho,
"5" = "antioquia",
"20" = "cesar")) %>%
dplyr::select(variable,valor)
etnia <- replicate_data %>%
dplyr::group_by(etnia) %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::filter(etnia == "NARP" | etnia == "INDIGENA") %>%
dplyr::rename(variable = etnia) %>%
dplyr::select(variable,valor)
edad <- replicate_data %>%
dplyr::group_by(edad_categoria) %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::filter(edad_categoria == "50-54") %>%
dplyr::mutate(edad_categoria = as.character(edad_categoria)) %>%
dplyr::rename(variable = edad_categoria) %>%
dplyr::select(variable, valor)
year_2002_2007 <- replicate_data %>%
dplyr::filter(yy_hecho >= 2002 & yy_hecho <= 2007) %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::mutate(variable = "2002-2007") %>%
dplyr::select(variable, valor)
year_1990_1994 <- replicate_data %>%
dplyr::filter(yy_hecho >= 1990 & yy_hecho <= 1994) %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::mutate(variable = "1990-1994") %>%
dplyr::select(variable, valor)
sexo <- replicate_data %>%
dplyr::group_by(sexo) %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::rename(variable = sexo) %>%
dplyr::select(variable, valor)
perp <- replicate_data %>%
dplyr::group_by(p_str) %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::rename(variable = p_str) %>%
dplyr::select(variable, valor)
w_minor <- replicate_data %>%
dplyr::filter(sexo == "MUJER" & edad_categoria == "10-14") %>%
dplyr::group_by(sexo) %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::mutate(variable = dplyr::recode(sexo,
"MUJER" = "mujer menor de edad")) %>%
dplyr::select(variable, valor)
caq_89_93 <- replicate_data %>%
dplyr::filter(yy_hecho >= 1989 & yy_hecho <= 1993 & dept_code_hecho == 18) %>%
dplyr::group_by(dept_code_hecho) %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::mutate(variable = dplyr::recode(dept_code_hecho,
"18" = "caqueta entre 1989 y 1993")) %>%
dplyr::select(variable, valor)
may <- replicate_data %>%
dplyr::filter(yymm_hecho == 199005) %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::mutate(variable = "mayo de 1999") %>%
dplyr::select(variable, valor)
paras_bog <- replicate_data %>%
dplyr::filter(p_str == "PARA" & dept_code_hecho == 11) %>%
dplyr::group_by(dept_code_hecho) %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::mutate(variable = dplyr::recode(dept_code_hecho,
"11" = "paramilitares en bogota")) %>%
dplyr::select(variable, valor)
paras_2016 <- replicate_data %>%
dplyr::filter(p_str == "PARA" & yy_hecho == 2016) %>%
dplyr::group_by(yy_hecho) %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::mutate(variable = dplyr::recode(yy_hecho,
"2016" = "paramilitares en 2016")) %>%
dplyr::select(variable, valor)
mestizo_2000 <- replicate_data %>%
dplyr::filter(yy_hecho == 2000 & etnia == "MESTIZO") %>%
dplyr::group_by(etnia) %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::mutate(variable = dplyr::recode(etnia,
"MESTIZO" = "mestizos en el 2000")) %>%
dplyr::select(variable, valor)
farc_2007 <- replicate_data %>%
dplyr::filter(yy_hecho == 2007 & p_str == "GUE-FARC") %>%
dplyr::group_by(yy_hecho) %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::mutate(variable = dplyr::recode(yy_hecho,
"2007" = "farc en 2007")) %>%
dplyr::select(variable, valor)
N_rows <- replicate_data %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::mutate(variable = "N rows") %>%
dplyr::select(variable, valor)
N_in_24 <- replicate_data %>%
dplyr::summarise(valor = sum(in_24)) %>%
dplyr::mutate(variable = "N in_24") %>%
dplyr::select(variable, valor)
comparar <- dplyr::bind_rows(dpto, etnia, edad, year_2002_2007, year_1990_1994,
sexo, perp, w_minor, caq_89_93, may, paras_bog,
paras_2016, mestizo_2000, farc_2007, N_rows, N_in_24)
replicate <- rep(replicate, each = nrow(comparar)) %>%
as.data.frame()
names(replicate) <- "replica"
comparar <- dplyr::bind_cols(replicate, comparar)
comparar$valor <- as.numeric(comparar$valor)
return(comparar)
}
#' Calculate measurements in order to ensure that each replicate file has the
#' correct content.
#'
#' @param replicates_dir A string that contains a path to the directory containing
#' the replicates to be checked
#' @param violation Violation to be analyzed. Options are "homicidio", "secuestro",
#' "reclutamiento", and "desaparicion".
#' @param replicate_nums A numeric vector containing the replicates to be analyzed.
#' Values in the vector should be between 1 and 100 inclusive.
#' @return A data frame with the path to the replicates, the replicate number,
#' and violation type.
#'
#' @noRd
build_path <- function(replicates_dir, violation, replicate_nums) {
if (length(replicate_nums) == 0) {
stop("replicate_nums is empty, please specifify which replicates to use")
}
if (!all(is.numeric(replicate_nums))) {
stop("replicate_nums should contain only numeric values")
}
if (any(replicate_nums < 1 | replicate_nums > 100)) {
stop("All values of replicate_nums should be between 1 and 100 inclusive")
}
valid_violations <- c("secuestro",
"reclutamiento",
"homicidio",
"desaparicion")
if (violation %in% valid_violations) {
path <- list.files(path = replicates_dir, full.names = TRUE)
if (rlang::is_empty(path)) {
stop("This directory does not contain any files")
}
parquet_check <- list.files(replicates_dir, pattern = "parquet")
csv_check <- list.files(replicates_dir, pattern = "csv")
if (rlang::is_empty(parquet_check) & rlang::is_empty(csv_check)) {
stop("No parquet or csv files were found in this directory")
}
if (!rlang::is_empty(parquet_check) & rlang::is_empty(csv_check)) {
file_extension <- "parquet"
}
if (rlang::is_empty(parquet_check) & !rlang::is_empty(csv_check)) {
file_extension <- "csv"
}
if (!rlang::is_empty(parquet_check) & !rlang::is_empty(csv_check)) {
file_extension <- "parquet"
}
if (file_extension == "parquet") {
matchpattern <- "([^-]+)\\-R([0-9]+).parquet"
matches <- stringr::str_match(path, matchpattern) %>%
tibble::as_tibble(.name_repair = ~c("full_match",
"violation",
"rep_number"))
rep_lista <- tibble::tibble(full_path = path, matches) %>%
dplyr::mutate(rep_number = as.integer(rep_number)) %>%
dplyr::filter(violation == violation & rep_number %in% replicate_nums)
} else {
matchpattern <- "([^-]+)\\-R([0-9]+).csv"
matches <- stringr::str_match(path, matchpattern) %>%
tibble::as_tibble(.name_repair = ~c("full_match",
"violation",
"rep_number"))
rep_lista <- tibble::tibble(full_path = path, matches) %>%
dplyr::mutate(rep_number = as.integer(rep_number)) %>%
dplyr::filter(violation == violation & rep_number %in% replicate_nums)
}
if (nrow(rep_lista) < length(replicate_nums)) {
missing_reps <- setdiff(replicate_nums, rep_lista$rep_number)
stop(glue::glue("replicates_dir missing replicates:\n{paste0(missing_reps, collapse = '\n')}"))
}
return(rep_lista %>% purrr::pluck("full_path"))
}
else {
stop("Violation argument incorrectly specified. Please enter one of the following valid violation types: reclutamiento, secuestro, homicidio, desaparicion")
}
}
# done.
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verdata documentation built on June 8, 2025, 11:46 a.m.
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Defines functions build_path medidas
# ============================================
# Authors: MJ
# Maintainers: MJ, MG
# Copyright: 2023, HRDAG, GPL v2 or later
# ============================================
#' Calculate measurements in order to make sure each replicate file has the correct
#' content.
#'
#' @param replicate_path A string that contains a path to the replicate to be checked.
#'
#' @return A data frame with the results.
#'
#' @noRd
medidas <- function(replicate_path) {
ext <- tools::file_ext(replicate_path)
if (ext == "parquet") {
replicate_data <- arrow::read_parquet(replicate_path)
}
else {
replicate_data <- readr::read_csv(replicate_path)
}
replicate <- unique(replicate_data$replica)
dpto <- replicate_data %>%
dplyr::group_by(dept_code_hecho) %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::filter(dept_code_hecho == 5 | dept_code_hecho == 20) %>%
dplyr::mutate(variable = dplyr::recode(dept_code_hecho,
"5" = "antioquia",
"20" = "cesar")) %>%
dplyr::select(variable,valor)
etnia <- replicate_data %>%
dplyr::group_by(etnia) %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::filter(etnia == "NARP" | etnia == "INDIGENA") %>%
dplyr::rename(variable = etnia) %>%
dplyr::select(variable,valor)
edad <- replicate_data %>%
dplyr::group_by(edad_categoria) %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::filter(edad_categoria == "50-54") %>%
dplyr::mutate(edad_categoria = as.character(edad_categoria)) %>%
dplyr::rename(variable = edad_categoria) %>%
dplyr::select(variable, valor)
year_2002_2007 <- replicate_data %>%
dplyr::filter(yy_hecho >= 2002 & yy_hecho <= 2007) %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::mutate(variable = "2002-2007") %>%
dplyr::select(variable, valor)
year_1990_1994 <- replicate_data %>%
dplyr::filter(yy_hecho >= 1990 & yy_hecho <= 1994) %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::mutate(variable = "1990-1994") %>%
dplyr::select(variable, valor)
sexo <- replicate_data %>%
dplyr::group_by(sexo) %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::rename(variable = sexo) %>%
dplyr::select(variable, valor)
perp <- replicate_data %>%
dplyr::group_by(p_str) %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::rename(variable = p_str) %>%
dplyr::select(variable, valor)
w_minor <- replicate_data %>%
dplyr::filter(sexo == "MUJER" & edad_categoria == "10-14") %>%
dplyr::group_by(sexo) %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::mutate(variable = dplyr::recode(sexo,
"MUJER" = "mujer menor de edad")) %>%
dplyr::select(variable, valor)
caq_89_93 <- replicate_data %>%
dplyr::filter(yy_hecho >= 1989 & yy_hecho <= 1993 & dept_code_hecho == 18) %>%
dplyr::group_by(dept_code_hecho) %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::mutate(variable = dplyr::recode(dept_code_hecho,
"18" = "caqueta entre 1989 y 1993")) %>%
dplyr::select(variable, valor)
may <- replicate_data %>%
dplyr::filter(yymm_hecho == 199005) %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::mutate(variable = "mayo de 1999") %>%
dplyr::select(variable, valor)
paras_bog <- replicate_data %>%
dplyr::filter(p_str == "PARA" & dept_code_hecho == 11) %>%
dplyr::group_by(dept_code_hecho) %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::mutate(variable = dplyr::recode(dept_code_hecho,
"11" = "paramilitares en bogota")) %>%
dplyr::select(variable, valor)
paras_2016 <- replicate_data %>%
dplyr::filter(p_str == "PARA" & yy_hecho == 2016) %>%
dplyr::group_by(yy_hecho) %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::mutate(variable = dplyr::recode(yy_hecho,
"2016" = "paramilitares en 2016")) %>%
dplyr::select(variable, valor)
mestizo_2000 <- replicate_data %>%
dplyr::filter(yy_hecho == 2000 & etnia == "MESTIZO") %>%
dplyr::group_by(etnia) %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::mutate(variable = dplyr::recode(etnia,
"MESTIZO" = "mestizos en el 2000")) %>%
dplyr::select(variable, valor)
farc_2007 <- replicate_data %>%
dplyr::filter(yy_hecho == 2007 & p_str == "GUE-FARC") %>%
dplyr::group_by(yy_hecho) %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::mutate(variable = dplyr::recode(yy_hecho,
"2007" = "farc en 2007")) %>%
dplyr::select(variable, valor)
N_rows <- replicate_data %>%
dplyr::summarise(valor = dplyr::n()) %>%
dplyr::mutate(variable = "N rows") %>%
dplyr::select(variable, valor)
N_in_24 <- replicate_data %>%
dplyr::summarise(valor = sum(in_24)) %>%
dplyr::mutate(variable = "N in_24") %>%
dplyr::select(variable, valor)
comparar <- dplyr::bind_rows(dpto, etnia, edad, year_2002_2007, year_1990_1994,
sexo, perp, w_minor, caq_89_93, may, paras_bog,
paras_2016, mestizo_2000, farc_2007, N_rows, N_in_24)
replicate <- rep(replicate, each = nrow(comparar)) %>%
as.data.frame()
names(replicate) <- "replica"
comparar <- dplyr::bind_cols(replicate, comparar)
comparar$valor <- as.numeric(comparar$valor)
return(comparar)
}
#' Calculate measurements in order to ensure that each replicate file has the
#' correct content.
#'
#' @param replicates_dir A string that contains a path to the directory containing
#' the replicates to be checked
#' @param violation Violation to be analyzed. Options are "homicidio", "secuestro",
#' "reclutamiento", and "desaparicion".
#' @param replicate_nums A numeric vector containing the replicates to be analyzed.
#' Values in the vector should be between 1 and 100 inclusive.
#' @return A data frame with the path to the replicates, the replicate number,
#' and violation type.
#'
#' @noRd
build_path <- function(replicates_dir, violation, replicate_nums) {
if (length(replicate_nums) == 0) {
stop("replicate_nums is empty, please specifify which replicates to use")
}
if (!all(is.numeric(replicate_nums))) {
stop("replicate_nums should contain only numeric values")
}
if (any(replicate_nums < 1 | replicate_nums > 100)) {
stop("All values of replicate_nums should be between 1 and 100 inclusive")
}
valid_violations <- c("secuestro",
"reclutamiento",
"homicidio",
"desaparicion")
if (violation %in% valid_violations) {
path <- list.files(path = replicates_dir, full.names = TRUE)
if (rlang::is_empty(path)) {
stop("This directory does not contain any files")
}
parquet_check <- list.files(replicates_dir, pattern = "parquet")
csv_check <- list.files(replicates_dir, pattern = "csv")
if (rlang::is_empty(parquet_check) & rlang::is_empty(csv_check)) {
stop("No parquet or csv files were found in this directory")
}
if (!rlang::is_empty(parquet_check) & rlang::is_empty(csv_check)) {
file_extension <- "parquet"
}
if (rlang::is_empty(parquet_check) & !rlang::is_empty(csv_check)) {
file_extension <- "csv"
}
if (!rlang::is_empty(parquet_check) & !rlang::is_empty(csv_check)) {
file_extension <- "parquet"
}
if (file_extension == "parquet") {
matchpattern <- "([^-]+)\\-R([0-9]+).parquet"
matches <- stringr::str_match(path, matchpattern) %>%
tibble::as_tibble(.name_repair = ~c("full_match",
"violation",
"rep_number"))
rep_lista <- tibble::tibble(full_path = path, matches) %>%
dplyr::mutate(rep_number = as.integer(rep_number)) %>%
dplyr::filter(violation == violation & rep_number %in% replicate_nums)
} else {
matchpattern <- "([^-]+)\\-R([0-9]+).csv"
matches <- stringr::str_match(path, matchpattern) %>%
tibble::as_tibble(.name_repair = ~c("full_match",
"violation",
"rep_number"))
rep_lista <- tibble::tibble(full_path = path, matches) %>%
dplyr::mutate(rep_number = as.integer(rep_number)) %>%
dplyr::filter(violation == violation & rep_number %in% replicate_nums)
}
if (nrow(rep_lista) < length(replicate_nums)) {
missing_reps <- setdiff(replicate_nums, rep_lista$rep_number)
stop(glue::glue("replicates_dir missing replicates:\n{paste0(missing_reps, collapse = '\n')}"))
}
return(rep_lista %>% purrr::pluck("full_path"))
}
else {
stop("Violation argument incorrectly specified. Please enter one of the following valid violation types: reclutamiento, secuestro, homicidio, desaparicion")
}
}
# done.
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