dynamic box height

Dockerfile

@@ -28,5 +28,7 @@ COPY --chown=shiny:shiny rhino.yml ./
 COPY --chown=shiny:shiny app app/
 
 COPY --chown=shiny:shiny docker/shiny-server.conf /etc/shiny-server/
-# RUN mkdir -p /var/run/s6 && chown -R shiny:shiny /var/run/s6
-# USER shiny
+
+# TODO HOW TO USE SHINY USER AND STILL SEE ENV VARIABLE
+# RUN mkdir -p /var/run/s6 && chown -R shiny:shiny /var/run/s6 
+# USER shiny 

app/logic/plots/trisk_lineplot.R

@@ -65,9 +65,9 @@ draw_trisk_line_plot <- function(
     # 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" = "dashed",
-      "production_target_scenario" = "solid",
-      "production_shock_scenario" = "dotted"
+      "production_baseline_scenario" = "dotted",
+      "production_target_scenario" = "dashed",
+      "production_shock_scenario" = "solid"
     )) +
     ggplot2::labs(
       x = "Year",

app/logic/renamings.R

@@ -68,7 +68,8 @@ RENAMING_ANALYSIS_COLUMNS <- c(
   "expected_loss_portfolio" = "Expected Loss",
   "expected_loss_baseline" = "Expected Loss (Baseline)",
   "expected_loss_shock" = "Expected Loss (Shock)",
-  "pd_difference" = "Difference in PD"
+  "pd_difference" = "PDs Difference (shock-baseline)",
+  "expected_loss_difference" = "Expected losses difference (shock-baseline)"
 )
 
 

app/view/crispy_loans.R

@@ -48,13 +48,11 @@ server <- function(id, perimeter, backend_trisk_run_folder, possible_trisk_combi
       "term",
       "exposure_value_usd",
       "loss_given_default",
-      "pd_baseline",
-      "expected_loss_baseline",
-      "pd_shock",
-      "expected_loss_shock"
+      "pd_difference",
+      "expected_loss_difference"
     )
     editable_columns_names_loans <- c("exposure_value_usd", "loss_given_default")
-    colored_columns_names_loans <- c("pd_baseline", "pd_shock")
+    colored_columns_names_loans <- c("pd_difference")
 
     out <- portfolio_analysis$server(
       "portfolio_analysis",
@@ -79,3 +77,4 @@ server <- function(id, perimeter, backend_trisk_run_folder, possible_trisk_combi
     )
   })
 }
+

app/view/modules/plots_loans.R

@@ -13,11 +13,13 @@ box::use(
 ui <- function(id) {
   ns <- NS(id)
   shiny::fluidRow(
-    # style = "height: 1300px;",
-    shiny::uiOutput(ns("dynamicHeightBox_pd_term_plot")), # Dynamic UI for the box
-    shiny::uiOutput(ns("dynamicHeightBox_expected_loss_plot")) # Dynamic UI for the box
+    semantic.dashboard::box(title = "PD Difference", width = 8, collapsible = FALSE,
+      plotOutput(ns("pd_term_plot_output"), height = "100%")
+    ),
+    semantic.dashboard::box(title = "Exposure Change", width = 8, collapsible = FALSE,
+      plotOutput(ns("exposure_change_plot"), height = "100%")
+      )
   )
-
 }
 
 ####### Server
@@ -27,13 +29,11 @@ ui <- function(id) {
 server <- function(id, analysis_data_r, crispy_data_agg_r, max_trisk_granularity) {
   moduleServer(id, function(input, output, session) {
 
-
-    base_height_per_facet <- 200 # height in pixels # TODO GO IN CONF
-
+    base_height_per_facet <- 150 # height in pixels # TODO GO IN CONF
 
     # PD PLOT
 
-    observeEvent(crispy_data_agg_r(), {
+    observeEvent(c(crispy_data_agg_r(), analysis_data_r()), {
       if (nrow(crispy_data_agg_r()) > 0) {
 
     granul_levels <- dplyr::intersect(colnames(crispy_data_agg_r()), names(max_trisk_granularity))
@@ -42,21 +42,13 @@ server <- function(id, analysis_data_r, crispy_data_agg_r, max_trisk_granularity
     num_facets <- length(unique(crispy_data_agg_r()[[granul_top_level]]))
 
 
-  # Dynamically create the box with adjusted height
-  output$dynamicHeightBox_pd_term_plot <- shiny::renderUI({
-    # Assuming plot height plus some margin
-    calculated_height <- (num_facets * base_height_per_facet) + 50
-    semantic.dashboard::box(
-      title = "PD Difference", 
-      width = 8, 
-      collapsible = FALSE,
-      style = paste0("height: ", calculated_height, "px;"), # Setting height dynamically
-      plotOutput(session$ns("pd_term_plot_output")) # this id value is used in the server, just below
-      )
-  })
+      # crispy_data_agg_user_filtered <- crispy_data_agg_r() |>
+      #   dplyr::inner_join(
+      #     analysis_data_r() |> dplyr::distinct_at(granul_top_level)
+      #   )
 
 
-      pd_term_plot <- pipeline_pd_term_plot(
+    pd_term_plot <- pipeline_pd_term_plot(
         crispy_data_agg=crispy_data_agg_r(), 
         facet_var=granul_top_level
       )
@@ -69,53 +61,29 @@ server <- function(id, analysis_data_r, crispy_data_agg_r, max_trisk_granularity
       }
     })
 
+    # EXPECTED LOSS PLOT
 
+    observeEvent(analysis_data_r(), {
+        if (nrow(analysis_data_r()) > 0) {
 
+          # Then, prepare and render the plot
+          granul_levels <- dplyr::intersect(colnames(analysis_data_r()), names(max_trisk_granularity))
+          granul_top_level <- names(max_trisk_granularity[granul_levels])[which.max(unlist(max_trisk_granularity[granul_levels]))]
 
-# EXPECTED LOSS PLOT
-
-
-   observeEvent(analysis_data_r(), {
-      if (nrow(analysis_data_r()) > 0) {
-
-        # Then, prepare and render the plot
-        granul_levels <- dplyr::intersect(colnames(analysis_data_r()), names(max_trisk_granularity))
-        granul_top_level <- names(max_trisk_granularity[granul_levels])[which.max(unlist(max_trisk_granularity[granul_levels]))]
-
-    num_facets <- length(unique(analysis_data_r()[[granul_top_level]]))
+          num_facets <- length(unique(analysis_data_r()[[granul_top_level]]))
 
-    # Dynamically create the box with adjusted height
-    output$dynamicHeightBox_expected_loss_plot <- shiny::renderUI({
-      # Assuming plot height plus some margin
-      calculated_height <- (num_facets * base_height_per_facet) + 50
-
-      # Return box with dynamic height set via inline CSS
-      semantic.dashboard::box(
-        title = "Expected Loss Baseline and Shock", 
-        width = 8, 
-        collapsible = FALSE,
-        style = paste0("height: ", calculated_height, "px;"), # Setting height dynamically
-        plotOutput(session$ns("expected_loss_plot_output")))
-
-      })
-
-
-        expected_loss_plot <- pipeline_expected_loss_plot(
-          analysis_data_r(), 
-          facet_var = granul_top_level
+          expected_loss_plot <- pipeline_expected_loss_plot(
+            analysis_data_r(), 
+            facet_var = granul_top_level
+            )
+          output$expected_loss_plot_output <- shiny::renderPlot({
+              expected_loss_plot
+            },
+          height = num_facets * base_height_per_facet
           )
-        output$expected_loss_plot_output <- shiny::renderPlot({
-            expected_loss_plot
-          },
-         height = num_facets * base_height_per_facet
-        )
-
-
-
-    }
-  }
-
-)})}
+      }
+    })
+  })}
 
 
 

app/view/modules/plots_trajectories.R

@@ -16,8 +16,7 @@ ui <- function(id) {
       title = "Production Trajectories",
       width = 16,
       collapsible = FALSE,
-      # height = "900px",
-      plotOutput(ns("trisk_line_plot_output"))
+      plotOutput(ns("trisk_line_plot_output"), height = "100%")
     )
   )
 }

app/view/portfolio/portfolio_analysis.R

@@ -206,12 +206,13 @@ generate_analysis_data <- function(portfolio_data_r, crispy_data_r, portfolio_as
           portfolio_data_r(),
           crispy_data_r(),
           by = granularity
-        ) |>
-          dplyr::mutate(
-            crispy_perc_value_change = NA,
-            crispy_value_loss = NA,
-            pd_difference = NA
-          )
+        )
+        #  |>
+        #   dplyr::mutate(
+        #     crispy_perc_value_change = NA,
+        #     crispy_value_loss = NA,
+        #     pd_difference = NA
+        #   )
       }
 
       # Aggregate Crispy data without portfolio with stress.test.plot.report fun