Merge remote-tracking branch 'upstream/main' into dev

.gitignore

@@ -1,3 +1,6 @@
+.DS_Store
+/dev/*
+
 *.env
 /deploy/*.tar
 /deploy/*.csv

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: lemur
 Title: Life expectancy monitor upscaled in R
-Version: 0.13.1
+Version: 0.14.0
 Authors@R: c(
   person("Marius D.", "Pascariu", role = c("aut", "cre", "cph"), email = "rpascariu@outlook.com", comment = c(ORCID = "0000-0002-2568-6489")),
   person("Jose Manuel", "Aburto", role = "aut", comment = c(ORCID = "0000-0002-2926-6879")),
@@ -42,9 +42,8 @@ Imports:
   RPostgres
 Encoding: UTF-8
 LazyData: true
-RoxygenNote: 7.1.2
+RoxygenNote: 7.2.3
 Suggests: 
   testthat (>= 3.0.0)
 Depends: 
   R (>= 2.10)
-

NAMESPACE

@@ -18,10 +18,12 @@ export(prepare_data_mode_cntr)
 export(prepare_data_mode_cod)
 export(prepare_data_mode_sex)
 export(run_app)
+export(setSliderColor_)
 export(tab_md)
 export(ui_dashbord)
 export(ui_datatab)
 export(ui_tabs)
+export(useShinydashboard_)
 import(data.table)
 import(ggplot2)
 import(golem)
@@ -54,6 +56,8 @@ importFrom(dplyr,summarise)
 importFrom(dplyr,ungroup)
 importFrom(glue,glue_data)
 importFrom(htmltools,HTML)
+importFrom(htmltools,attachDependencies)
+importFrom(htmltools,findDependencies)
 importFrom(htmltools,tagAppendAttributes)
 importFrom(htmltools,tagList)
 importFrom(htmltools,tags)

NEWS

@@ -1,83 +1,87 @@
-version 0.13.0
-- Include the maternal and neonatal mortality in the SDG section;
-
-version 0.12.2
-- Add the servedMode argument in the run_app() function that would allow the user
-to select the datasource at the launch of the application.
-
-version 0.10.0
-- Create datatab corresponding to dashboard figures (lifetables, cod distributions and decomposition values)
-
-version 0.9.0
-- Update database by adding macro-regions 
-
-version 0.8.2
-- remove home page tab
-
-version 0.8.1
-- bug fixes. Minor but important.
-
-version 0.8.0
-- rebrand the developing R package from MortalityCauses to lemur
-
-version 0.7.0
-- add data.table filtering - major update
-
-version 0.6.0
-- make the figures plotly.
-
-version 0.5.5
-- sdg mode working. Not with refrence to 2015 values, but working without errors.
-
-version 0.5.4
-- bug fixes;
-- sdg mode still not working.
-
-version 0.5.3
-- update datasets processing;
-- make the sdg mode functional.Now we only need to make it work correctly and 
-will all the inputs.
-
-version 0.5.2
-- include tooltips to save dashboard real-estate;
-- now shiny app is operational except the SDG mode.
-
-version 0.5.1
-- specify glue and purrr dependencies, remove some more warnings.
-
-version 0.5.0
-- Add yearly COD data and also a SDG classification. 
-- Re-run the data preprocessing scripts.
-- No tests have been performed on the shiny app, so probably contains fatal bugs. To be verified in the next version.
-
-version 0.4.5
-- Fix bug issues in map;
-
-version 0.4.5
-- Add dynamic map and start the SDG mode; 
-
-version 0.3.0
-- Start dashboard development;
-
-version 0.2.0
-- Include the function to compute life expectancy decomposition by age and cod;
-
-version 0.1.0 
-- add function to compute cause modified life tables;
-
-version 0.0.6
-- Create function for performing decomposition of age-specific mortality 
-contributions in life expectancy: decompose_ex_by_age().
-
-version 0.0.5
--  Add GBD life tables consistent with the COD data over the 204 regions. Also, include hierarchical maps of the data.
-
-version 0.0.3
-- Add GBD data;
-
-version 0.0.2
-- Add WPP data;
-
-version 0.0.1
-- Start with a {golem} skeleton;
-- Added a `NEWS` file to track changes to the package.
+version 0.14.0
+- Fix bug related to lack of maternal mortality data when male population is selected;
+- Fix bug in the under 5 mortality reduction method;
+
+version 0.13.0
+- Include the maternal and neonatal mortality in the SDG section;
+
+version 0.12.2
+- Add the servedMode argument in the run_app() function that would allow the user
+to select the datasource at the launch of the application.
+
+version 0.10.0
+- Create datatab corresponding to dashboard figures (lifetables, cod distributions and decomposition values)
+
+version 0.9.0
+- Update database by adding macro-regions 
+
+version 0.8.2
+- remove home page tab
+
+version 0.8.1
+- bug fixes. Minor but important.
+
+version 0.8.0
+- rebrand the developing R package from MortalityCauses to lemur
+
+version 0.7.0
+- add data.table filtering - major update
+
+version 0.6.0
+- make the figures plotly.
+
+version 0.5.5
+- sdg mode working. Not with refrence to 2015 values, but working without errors.
+
+version 0.5.4
+- bug fixes;
+- sdg mode still not working.
+
+version 0.5.3
+- update datasets processing;
+- make the sdg mode functional.Now we only need to make it work correctly and 
+will all the inputs.
+
+version 0.5.2
+- include tooltips to save dashboard real-estate;
+- now shiny app is operational except the SDG mode.
+
+version 0.5.1
+- specify glue and purrr dependencies, remove some more warnings.
+
+version 0.5.0
+- Add yearly COD data and also a SDG classification. 
+- Re-run the data preprocessing scripts.
+- No tests have been performed on the shiny app, so probably contains fatal bugs. To be verified in the next version.
+
+version 0.4.5
+- Fix bug issues in map;
+
+version 0.4.5
+- Add dynamic map and start the SDG mode; 
+
+version 0.3.0
+- Start dashboard development;
+
+version 0.2.0
+- Include the function to compute life expectancy decomposition by age and cod;
+
+version 0.1.0 
+- add function to compute cause modified life tables;
+
+version 0.0.6
+- Create function for performing decomposition of age-specific mortality 
+contributions in life expectancy: decompose_ex_by_age().
+
+version 0.0.5
+-  Add GBD life tables consistent with the COD data over the 204 regions. Also, include hierarchical maps of the data.
+
+version 0.0.3
+- Add GBD data;
+
+version 0.0.2
+- Add WPP data;
+
+version 0.0.1
+- Start with a {golem} skeleton;
+- Added a `NEWS` file to track changes to the package.

R/app_server.R

@@ -1,7 +1,7 @@
-# --------------------------------------------------- #
+# -------------------------------------------------------------- #
 # Author: Marius D. PASCARIU
-# Last update: Thu Jun 02 15:45:46 2022
-# --------------------------------------------------- #
+# Last Update: Tue Oct 17 22:30:57 2023
+# -------------------------------------------------------------- #
 
 #' The application server-side
 #'
@@ -48,7 +48,7 @@ app_server <- function(input, output, session) {
 
       dataSource <- if (serverMode()) "sdg" else lemur::data_gbd2019_sdg
 
-      eval(
+      dt <- eval(
         call(
           name    = queryFunction(), 
           data    = dataSource,
@@ -58,11 +58,12 @@ app_server <- function(input, output, session) {
           gender  = input$sex,
           year    = input$time_slider
         )
-      ) %>%
+      ) %>% 
         mutate(
           cause_name = factor(cause_name, levels = lemur::data_app_input$cause_name_sdg))
 
     }
+    dt
   })
 
   # 3) life tables data
@@ -96,8 +97,9 @@ app_server <- function(input, output, session) {
 
   # Reduction matrix -----------------------------
   data_cod_change <- reactive({
-
+    
     if (input$mode == "mode_sdg") {
+
       M <- build_reduction_matrix(
         data       = data_sdg(),
         select_cod = as.character(unique(data_sdg()$cause_name)),
@@ -120,28 +122,30 @@ app_server <- function(input, output, session) {
       S6 = "Transport Injuries"
       S7 = "Exposure to Forces of Nature"
 
-      M[  , S2a] <- input$sdg_2a
+      if (input$sex != 'male') {
+        # For now males are not exposed to maternal disorders :)
+        M[  , S2a] <- input$sdg_2a
+      }
       M[  , S2b] <- input$sdg_2b
       M[  , S3] <- input$sdg_3
       M[  , S4] <- input$sdg_4
       M[  , S5] <- input$sdg_5
       M[  , S6] <- input$sdg_6
       M[  , S7] <- input$sdg_7
-      
+
       # when under 5 mortality is reduced across all COD we have to deal with 
       # interactions, or successive reduction inputs. E.g. One may reduce 
       # neonatal mortality (50%) and under-five mortality (10%) resulting a 55%
-      # total reduction. This is what we try to in the next 5 lines.
-       
+      # total reduction. This is what we try to do in the next 5 lines.
+
       if (input$sdg_1 != 0) {
         if (sum(M[S1, ]) != 0) {
-          M[S1,   ] <- input$sdg_1 + M[S1, ] * abs(input$sdg_1)/100
+          M[S1,   ] <- ((1 + input$sdg_1/100) * ((M[S1, ] + 100)/100) - 1) * 100
         } else  {
           M[S1,   ] <- input$sdg_1 
         }
       }
 
-
     } else {
       M <- build_reduction_matrix(
         data = data_cod(),
@@ -194,6 +198,7 @@ app_server <- function(input, output, session) {
 
   # Decompose the difference in life expectancy at birth
   data_decomp <- reactive({
+    # print(data_fig())
     decompose_by_cod(
       data_fig()$lt_initial,
       data_fig()$lt_final,
@@ -528,7 +533,7 @@ dt_filter_local <- function(data, mode, region1, region2, gender, year) {
   dt <- as.data.table(data)
   dt <- dt[period == year]
   dt <- dt[region %in% c(region1, region2)]
-
+  
   if (mode != "mode_sex") {
     dt <- dt[sex == gender]
   }