Fix review items

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: sivirep
 Title: Data Wrangling and Automated Reports from 'SIVIGILA' Source
 Type: Package
-Version: 1.0.0
+Version: 1.0.1
 Authors@R: 
   c(
     person(given = "Geraldine", family = "Gómez-Millán", email = "[email protected]", role = c("aut", "cre", "ctb"),
@@ -67,7 +67,7 @@ Config/Needs/website:
     r-lib/pkgdown,
     epiverse-trace/epiversetheme
 VignetteBuilder: knitr
-Language: es_ES
+Language: es-ES
 URL: https://epiverse-trace.github.io/sivirep/, https://github.com/epiverse-trace/sivirep
 BugReports: https://github.com/epiverse-trace/sivirep/issues
 Config/testthat/edition: 3

NEWS.md

@@ -1,3 +1,5 @@
+# sivirep 1.0.1
+
 # sivirep 0.0.1
 
 This is the initial version of the package. It contains four modules which are as follows:
@@ -78,3 +80,13 @@ The report template `Reporte Basico` now includes five new sections called:
 -   `Distribución por área geográfica`
 -   `Distribución por pertenencia étnica` 
 -   `Incidencia`
+
+# sivirep 1.0.1
+
+This patch release fixes the following items::
+
+-   `es_ES` was replaced with `es-ES` in the `DESCRIPTION` file.
+
+-   Updated function examples that require data import and 
+    use the `cache` parameter to prevent an increase in the package's size 
+    on CRAN.

R/checking_data.R

@@ -907,13 +907,15 @@ agrupar_per_etn <- function(data_event, cols_etn = "per_etn",
 #' data_limpia <- limpiar_data_sivigila(data_event = dengue2020)
 #' # Cálculo de la incidencia con proyecciones poblacionales por departamento
 #' data_agrupada_mpios <- agrupar_mpio(data_limpia, dpto = "Antioquia")
-#' calcular_incidencia(
-#'   data_agrupada = data_agrupada_mpios,
-#'   poblacion = "proyecciones",
-#'   dpto = "05",
-#'   year = 2020,
-#'   cache = TRUE
-#' )
+#' if (interactive()) {
+#'   calcular_incidencia(
+#'     data_agrupada = data_agrupada_mpios,
+#'     poblacion = "proyecciones",
+#'     dpto = "05",
+#'     year = 2020,
+#'     cache = TRUE
+#'   )
+#' }
 #' # Cálculo de la incidencia con proyecciones poblacionales por municipio
 #' calcular_incidencia(
 #'   data_agrupada = data_agrupada_mpios,
@@ -929,7 +931,7 @@ agrupar_per_etn <- function(data_event, cols_etn = "per_etn",
 #'   poblacion = "riesgo",
 #'   data_agrupada = data_agrupada_dptos,
 #'   year = 2020,
-#'   cache = TRUE
+#'   ruta_dir = tempdir()
 #' )
 #' }
 #' @export
@@ -1068,12 +1070,14 @@ calcular_incidencia <- function(data_incidencia = NULL,
 #' data_limpia <- limpiar_data_sivigila(data_event = dengue2020)
 #' data_agrupada_mpios <- agrupar_mpio(data_limpia, dpto = "Antioquia")
 #' # Cálculo de la incidencia con población a riesgo por departamento
-#' calcular_incidencia_geo(
-#'   poblacion = "riesgo",
-#'   data_agrupada = data_agrupada_mpios,
-#'   year = 2020,
-#'   cache = TRUE
-#' )
+#' if (interactive()) {
+#'   calcular_incidencia_geo(
+#'     poblacion = "riesgo",
+#'     data_agrupada = data_agrupada_mpios,
+#'     year = 2020,
+#'     cache = TRUE
+#'   )
+#' }
 #' data_agrupada_dptos <- agrupar_dpto(data_limpia)
 #' # Cálculo de la incidencia con proyecciones poblacionales para Colombia
 #' calcular_incidencia_geo(
@@ -1219,12 +1223,14 @@ calcular_incidencia_geo <- function(data_incidencia = NULL,
 #'   dpto = "05"
 #' )
 #' data_agrupada <- agrupar_sex(data_filtrada)
-#' calcular_incidencia_sex(
-#'   data_agrupada = data_agrupada,
-#'   dpto = "05",
-#'   year = 2020,
-#'   cache = TRUE
-#' )
+#' if (interactive()) {
+#'   calcular_incidencia_sex(
+#'     data_agrupada = data_agrupada,
+#'     dpto = "05",
+#'     year = 2020,
+#'     cache = TRUE
+#'   )
+#' }
 #' #' Cálculo de la incidencia con proyecciones poblacionales por sexo y
 #' # municipio
 #' data_filtrada <- geo_filtro(

R/import_data.R

@@ -320,8 +320,10 @@ import_sep_data <- function(ruta_data = NULL,
 #' @examples
 #'  \donttest{
 #' # Importación proyecciones poblaciones DANE
-#' import_pob_incidencia(poblacion = "proyecciones", year = 2020,
-#'                       cache = TRUE)
+#' if (interactive()) {
+#'   import_pob_incidencia(poblacion = "proyecciones", year = 2020,
+#'                         cache = TRUE)
+#' }
 #' # Importación población a riesgo de Dengue del año 2020
 #' import_pob_incidencia(poblacion = "riesgo", event = "dengue", year = 2020,
 #'                       ruta_dir = tempdir())
@@ -360,6 +362,9 @@ import_pob_incidencia <- function(
 #' @examples
 #' \donttest{
 #' import_pob_proyecciones(year = 2020, ruta_dir = tempdir())
+#' if (interactive()) {
+#'   import_pob_proyecciones(year = 2020, cache = TRUE)
+#'   }
 #' }
 #' @export
 import_pob_proyecciones <- function(year,
@@ -406,6 +411,9 @@ import_pob_proyecciones <- function(year,
 #' @examples
 #' \donttest{
 #' import_pob_riesgo(event = "Dengue", year = 2020, ruta_dir = tempdir())
+#' if (interactive()) {
+#'   import_pob_riesgo(event = "Dengue", year = 2020, cache = TRUE)
+#'   }
 #' }
 #' @export
 import_pob_riesgo <- function(event, year,

R/plotting.R

@@ -29,11 +29,13 @@
 #' geo_ocurrencia <- obtener_tip_ocurren_geo(nombre_event = "dengue")
 #' data_espacial <- agrupar_dpto(data_event = data_estandar,
 #'                               geo_ocurrencia[1:4])
-#' plot_map(
-#'   data_agrupada = data_espacial,
-#'   col_distribucion = "casos",
-#'   cache = TRUE
-#' )
+#' if (interactive()) {
+#'   plot_map(
+#'     data_agrupada = data_espacial,
+#'     col_distribucion = "casos",
+#'     cache = TRUE
+#'   )
+#' }
 #' # Mapa por municipios de un departamento especifico
 #' data_filtrada_dpto <- geo_filtro(
 #'   data_event = data_estandar,
@@ -53,14 +55,16 @@
 #'   mpio = "Medellin"
 #' )
 #' data_espacial_mpio <- agrupar_mpio(data_event = data_filtrada_mpio)
-#' plot_map(
-#'   data_agrupada = data_espacial_mpio,
-#'   col_codigos = "cod_mun_o",
-#'   col_distribucion = "casos",
-#'   dpto = "Antioquia",
-#'   mpio = "Medellin",
-#'   cache = TRUE
-#' )
+#' if (interactive()) {
+#'   plot_map(
+#'     data_agrupada = data_espacial_mpio,
+#'     col_codigos = "cod_mun_o",
+#'     col_distribucion = "casos",
+#'     dpto = "Antioquia",
+#'     mpio = "Medellin",
+#'     cache = TRUE
+#'   )
+#' }
 #' # Mapa con la incidencia por municipios de un departamento específico
 #' incidencia_dpto <-
 #'   calcular_incidencia_geo(data_agrupada = data_espacial_dpto,

cran-comments.md

@@ -4,39 +4,9 @@
 
 * This is a new release.
 
-* sivirep currently has its documentation, function names, and website in 
-  Spanish, as user testing in various regions of Colombia, such as the Chocó 
-  region, revealed that having these components in English posed a 
-  significant barrier. Many users in these areas are not proficient in English, 
-  which increases learning curves and limits the adoption of the tool. This 
-  package is expected to be used by Health Departments and Professionals 
-  throughout the country to facilitate the generation and access to 
-  epidemiological reports from SIVIGILA (National Public Health Surveillance 
-  System).
-
-## Resubmission
-
-This is a resubmission. In this version:
-
-* Expanded the Description field to provide a more detailed overview of the 
-  package's functionality, benefits and the methods it implements, as requested.
+* Updated `DESCRIPTION` file to use language tags compliant with RFC 5646. 
+  Specifically, `es_ES` was replaced with `es-ES` as recommended.
 
-* Added a direct link to the web services used in the package, formatted with 
-  angle brackets for auto-linking, following the recommended format.
-
-* Replaced `\dontrun{}` with `\donttest{}` in the examples of the following 
-  functions: `import_data_event()`, `list_events()` and `plot_year()`.
-
-* Added `\donttest{}` in examples of `import_geo_codes` function, since it was
-  involve data downloading and was the only function that did not have 
-  this tag.
-
-* Used `tempdir()` in examples and tests of functions that require data import
-  for execution.
-
-* In the internal function `obtener_ruta_dir()` of `R\utils.R`, the `cache` 
-  parameter was added, and the functions that use it were modified to always 
-  pass it. This parameter requests explicit confirmation from the user if they 
-  want the data to be stored in the respective user directory, which is 
-  obtained from `tools::R_user_dir()`. These files are cleaned up and actively 
-  managed in accordance with CRAN policy.
+* Implemented `tempdir()` for function examples that require data import and 
+  improved the use of `cache` parameter. These changes resolves additional 
+  `donttest` issues related to package's size on CRAN.