Modify the colors to match the risk categories (#31)

* changed color scaled to corresponds to the risk categories values

* used fill_scale_color function

* used swith mode function for consistency

* changed plot sankey

R/plot_sankey.R

@@ -36,36 +36,31 @@ plot_sankey <- function(data, with_company = TRUE, mode = c("equal_weight", "wor
     "worst_case_finance",
     "best_case_finance"
   )
-  data |> check_crucial_names(c(names(select(data, matches(crucial)))))
-  risk_category_var <- names(select(data, matches("_risk_category")))
+  data |> check_crucial_names(names_matching(data, crucial))
+  risk_var <- names_matching(data, "_risk_category")
 
-  limits <- c("Bank", if (with_company) "Company", NULL, "Tilt Sector", risk_category_var)
+  limits <- c("Bank", if (with_company) "Company", NULL, "Tilt Sector", risk_var)
 
-  # TODO : color code per low, medium and high
   p <- ggplot(
     data = data,
     aes(
+      y = .data[[switch_mode(mode)]],
       axis1 = .data$kg_id,
       axis3 = .data$tilt_sector,
-      axis4 = factor(.data[[risk_category_var]], levels = c("low", "medium", "high"))
+      axis4 = as_risk_category(.data[[risk_var]]),
+      fill = as_risk_category(.data[[risk_var]])
     )
   ) +
     scale_x_discrete(
       limits = limits,
       expand = c(.2, .05)
     ) +
-    geom_alluvium(aes(
-      fill = case_when(
-        mode == "equal_weight" ~ .data$equal_weight_finance,
-        mode == "worst_case" ~ .data$worst_case_finance,
-        mode == "best_case" ~ .data$best_case_finance,
-        mode == "main_activity" ~ .data$main_activity
-      )
-    )) +
+    geom_alluvium() +
     geom_stratum() +
     geom_text(stat = StatStratum, aes(label = after_stat(.data$stratum))) +
+    fill_score_colors() +
     theme_minimal() +
-    labs(fill = "amount") +
+    labs(fill = "Risk Categories") +
     ggtitle(
       "Sankey Plot",
       paste("Stratified by the amount of loan by the bank and", mode, "mode")