removed asset_type column

R/crispy_trisk_lineplot.R

@@ -13,20 +13,22 @@ pipeline_crispy_trisk_line_plot <- function(
     trajectories_data,
     x_var = "year",
     facet_var = "ald_business_unit",
-    linecolor = "ald_sector") {
+    linecolor = "ald_sector",
+    y_in_percent=TRUE) {
   linecolor <- dplyr::intersect(colnames(trajectories_data), linecolor)
 
   data_trisk_line_plot <- prepare_for_trisk_line_plot(
     trajectories_data = trajectories_data,
     facet_var = facet_var,
     linecolor = linecolor
-  )
+    )
 
   trisk_line_plot <- draw_trisk_line_plot(
     data_trisk_line_plot,
     x_var = x_var,
     facet_var = facet_var,
-    linecolor = linecolor
+    linecolor = linecolor,
+    y_in_percent=y_in_percent
   )
 
   return(trisk_line_plot)
@@ -75,28 +77,51 @@ draw_trisk_line_plot <- function(
     data_trisk_line_plot,
     x_var,
     facet_var,
-    linecolor) {
+    linecolor,
+    y_in_percent) {
+
+  if (y_in_percent){
+    trisk_line_plot <- ggplot2::ggplot(
+      data_trisk_line_plot,
+      ggplot2::aes(
+        x = !!rlang::sym(x_var),
+        y = production_pct,
+        color = !!rlang::sym(linecolor),
+        linetype = scenario
+      )
+    ) +
+    ggplot2::scale_y_continuous(labels = scales::percent_format(scale = 1)) +
+      ggplot2::labs(
+        y = "Production as a percentage of the maximum"
+      )
+  } else {
+    trisk_line_plot <- ggplot2::ggplot(
+      data_trisk_line_plot,
+      ggplot2::aes(
+        x = !!rlang::sym(x_var),
+        y = production,
+        color = !!rlang::sym(linecolor),
+        linetype = scenario
+      )
+    ) +
+    ggplot2::scale_y_continuous(labels = function(x) scales::scientific(x)) +
+    ggplot2::labs(
+      y = "Production in raw unit"
+      )
+  }
+
+
   facets_colors <- r2dii.colours::palette_2dii_plot[seq_along(unique(data_trisk_line_plot[[linecolor]])), ]$hex
-  trisk_line_plot <- ggplot2::ggplot(
-    data_trisk_line_plot,
-    ggplot2::aes(
-      x = !!rlang::sym(x_var),
-      y = production_pct,
-      color = !!rlang::sym(linecolor),
-      linetype = scenario
-    )
-  ) +
+  trisk_line_plot <- trisk_line_plot +
     ggplot2::geom_line() +
     # ggplot2::geom_point(size = 0.1) +
-    ggplot2::scale_y_continuous(labels = scales::percent_format(scale = 1)) +
     ggplot2::scale_linetype_manual(values = c(
       "production_baseline_scenario" = "dotted",
       "production_target_scenario" = "dashed",
       "production_shock_scenario" = "solid"
     )) +
     ggplot2::labs(
       x = "Year",
-      y = "Production as a percentage of the maximum",
       linetype = "Scenario"
     ) +
     ggplot2::scale_color_manual(values = facets_colors) +

R/data_load_main.R

@@ -130,7 +130,7 @@ main_load_analysis_data <-
 main_load_portfolio_data <-
   function(portfolio_data,
            granularity,
-           param_cols = c("portfolio_id", "term", "asset_type"),
+           param_cols = c("portfolio_id", "term"),
            trisk_start_year) {
     group_cols <- unique(c(granularity, param_cols))
 

R/data_load_portfolio.R

@@ -10,7 +10,6 @@ load_portfolio_data <- function(portfolio_data_path) {
         portfolio_id = "c",
         company_id = "c",
         company_name = "c",
-        asset_type = "c",
         ald_sector = "c",
         ald_business_unit = "c",
         ald_location = "c",
@@ -23,7 +22,6 @@ load_portfolio_data <- function(portfolio_data_path) {
   } else {
     portfolio_data <- tibble::tibble(
       portfolio_id = character(),
-      asset_type = character(),
       company_id = character(),
       company_name = character(),
       ald_sector = character(),
@@ -64,9 +62,11 @@ map_portfolio_maturity_to_term <-
         dplyr::mutate(term = 1)
     }
 
-    # replace term by 1 if asset_type is equity
+    # replace term by 1 if asset type is equity
     portfolio_data <- portfolio_data |>
-      dplyr::mutate(term = dplyr::if_else(asset_type == "equity", 1, .data$term))
+      dplyr::mutate(
+        term = dplyr::if_else(is.na(.data$term), 1, .data$term)
+        portfolio_id=dplyr::if_else(is.na(.data$portfolio_id), 1, .data$portfolio_id))
     return(portfolio_data)
   }
 

R/prepare_for_cdi_plots.R

@@ -28,7 +28,7 @@ prepare_for_cdi_npv_plots <-
 
 
 #' Title
-#'
+#'  TODO IS THIS FUNCTION USED ANYWHERE ?
 #' @param analysis_data analysis_data
 #' @param group_variables_vec group_variables_vec
 #' @param weight_variable_char weight_variable_char

data-raw/scripts/generate_synthetic_data/generate_synthetic_portfolio_data.R

@@ -17,7 +17,6 @@ portfolio_values <- abcd_stress_test_input |>
 companies_fixed_income <-
   portfolio_values |>
   sample_n(200) |>
-  mutate(asset_type = "fixed_income") |>
   left_join(eikon_data |> select(company_id, isin) |> sample_frac(0.3),
     by = "company_id",
     relationship = "many-to-many"
@@ -27,7 +26,6 @@ companies_equities <-
   portfolio_values |>
   sample_n(200) |>
   mutate(
-    asset_type = "equity",
     expiration_date = NA
   )
 
@@ -72,7 +70,6 @@ portfolio_data <- portfolio_data |> select(
   portfolio_id,
   company_name,
   company_id,
-  asset_type,
   ald_sector,
   ald_business_unit,
   ald_location,