v0.14.4 - fix bug in data processing to mage sure we get the same res…

…ults in every operating mode of the dashboard.

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: lemur
 Title: Life expectancy monitor upscaled in R
-Version: 0.14.3
+Version: 0.14.4
 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")),

R/app_process_data.R

@@ -1,8 +1,10 @@
 # -------------------------------------------------------------- #
 # Author: Marius D. PASCARIU
-# Last Update: Tue Dec  5 22:08:41 2023
+# Last Update: Tue Dec 19 22:08:15 2023
 # -------------------------------------------------------------- #
 
+# somebody should merge these functions in 1?
+
 # ----------------------------------------------------------------------------
 # PROCESS DATA
 
@@ -16,6 +18,8 @@ prepare_data_mode_cod <- function(cod,
                                   sex,
                                   cod_change) {
 
+  region <- NULL
+
   # Select cod and lt for 1 region
   # If no risk change is applied the tables before and after are the same
   # not change in LE no decomposition
@@ -56,25 +60,25 @@ prepare_data_mode_cntr <- function(cod,
   region <- NULL
 
   # select cod and lt tables for 2 regions
-  c1 <- cod[cod$region == region1 & cod$sex == sex, ]
-  c2 <- cod[cod$region == region2 & cod$sex == sex, ]
-  l1 <- lt[lt$region == region1 & lt$sex == sex, ]
-  l2 <- lt[lt$region == region2 & lt$sex == sex, ]
+  c1_init <- c1 <- cod[cod$region == region1 & cod$sex == sex, ]
+  c2_init <- c2 <- cod[cod$region == region2 & cod$sex == sex, ]
+  l1_init <- l1 <- lt[lt$region == region1 & lt$sex == sex, ]
+  l2_init <- l2 <- lt[lt$region == region2 & lt$sex == sex, ]
 
   # IF we look at 2 regions and we change the risks
   # we need to adjust the cod and lt tables for both regions
   logic <- any(cod_change != 0)
   if (logic) {
-    c1 <- modify_cod_table(c1, cod_change)
-    c2 <- modify_cod_table(c2, cod_change)
-    l1 <- modify_life_table(l1, c1, cod_change)
-    l2 <- modify_life_table(l2, c2, cod_change)
+    c1 <- modify_cod_table(c1_init, cod_change)
+    c2 <- modify_cod_table(c2_init, cod_change)
+    l1 <- modify_life_table(l1_init, c1_init, cod_change)
+    l2 <- modify_life_table(l2_init, c2_init, cod_change)
   }
 
   lv <- if (region1 == region2) region1 else c(region1, region2) 
   c1 <- mutate(c1, region = factor(region, levels = lv))
   c2 <- mutate(c2, region = factor(region, levels = lv))
-
+  
   out <- list(
     cod_initial = c1,
     cod_final   = c2,
@@ -96,21 +100,22 @@ prepare_data_mode_sex <- function(cod,
                                   cod_change){
 
   region <- NULL
+  sex    <- NULL
 
   # select cod and lt tables for the 2 sexes
-  c1 <- cod[cod$region == region1 & cod$sex == "male" , ]
-  c2 <- cod[cod$region == region1 & cod$sex == "female", ]
-  l1 <- lt[lt$region == region1 & lt$sex == "male", ]
-  l2 <- lt[lt$region == region1 & lt$sex == "female", ]
+  c1_init <- c1 <- cod[cod$region == region1 & cod$sex == "male" , ]
+  c2_init <- c2 <- cod[cod$region == region1 & cod$sex == "female", ]
+  l1_init <- l1 <- lt[lt$region == region1 & lt$sex == "male", ]
+  l2_init <- l2 <- lt[lt$region == region1 & lt$sex == "female", ]
 
   # IF we look at 2 gender and we change the risks
   # we need to adjust the cod and lt tables for both populations
   logic <- any(cod_change != 0)
   if (logic) {
-    c1 <- modify_cod_table(c1, cod_change)
-    c2 <- modify_cod_table(c2, cod_change)
-    l1 <- modify_life_table(l1, c1, cod_change)
-    l2 <- modify_life_table(l2, c2, cod_change)
+    c1 <- modify_cod_table(c1_init, cod_change)
+    c2 <- modify_cod_table(c2_init, cod_change)
+    l1 <- modify_life_table(l1_init, c1_init, cod_change)
+    l2 <- modify_life_table(l2_init, c2_init, cod_change)
   }
 
   out <- list(