More gracefully handle missing plot configs

qhtcp-workflow/apps/r/calculate_interaction_zscores.R

@@ -7,6 +7,7 @@ suppressMessages({
   library("rlang")
   library("ggthemes")
   library("data.table")
+  library("grid")
   library("gridExtra")
   library("future")
   library("furrr")
@@ -506,31 +507,6 @@ generate_and_save_plots <- function(out_dir, filename, plot_configs, page_width
     grid_layout <- group$grid_layout
     plots <- group$plots
 
-    # Only handle grid layout if it exists
-    if (!is.null(grid_layout)) {
-      # Set grid_ncol to 1 if not specified
-      if (is.null(grid_layout$ncol)) {
-        grid_layout$ncol <- 1
-      }
-
-      # If ncol is set but nrow is not, calculate nrow dynamically based on num_plots
-      if (!is.null(grid_layout$ncol) && is.null(grid_layout$nrow)) {
-        num_plots <- length(plots)
-        nrow <- ceiling(num_plots / grid_layout$ncol)
-        # message("No nrow provided, automatically using nrow = ", nrow)
-        grid_layout$nrow <- nrow
-      }
-
-      # Fill missing spots with nullGrob() if necessary
-      total_spots <- grid_layout$nrow * grid_layout$ncol
-      num_plots <- length(plots)
-      
-      if (num_plots < total_spots) {
-        message("Filling ", total_spots - num_plots, " empty spots with nullGrob()")
-        plots <- c(plots, replicate(total_spots - num_plots, nullGrob(), simplify = FALSE))
-      }
-    }
-
     for (i in seq_along(plots)) {
       config <- plots[[i]]
       df <- config$df
@@ -548,7 +524,7 @@ generate_and_save_plots <- function(out_dir, filename, plot_configs, page_width
         if (nrow(out_of_bounds_df) > 0) {
           message("Filtered: ", config$title, " using y-limits: [", config$ylim_vals[1], ", ", config$ylim_vals[2], "]")
           message("# of filtered rows outside y-limits (for plotting): ", nrow(out_of_bounds_df))
-          # print(out_of_bounds_df)
+          print(out_of_bounds_df)
         }
 
         df <- df %>%
@@ -582,15 +558,6 @@ generate_and_save_plots <- function(out_dir, filename, plot_configs, page_width
         }
       }
 
-      # Create a null plot with a "No data" message if no rows remain
-      # if (nrow(df) == 0) {
-      #   plot <- ggplot() +
-      #     geom_text(aes(0.5, 0.5), label = "No data available", size = 5) +
-      #     theme_void() + ggtitle(config$title)
-      # } else {
-      #   plot <- ggplot(df, aes_mapping) + theme_publication(legend_position = config$legend_position)
-      # }
-
       plot <- ggplot(df, aes_mapping) + theme_publication(legend_position = config$legend_position)
 
       # Add appropriate plot layer or helper function based on plot type
@@ -718,18 +685,37 @@ generate_and_save_plots <- function(out_dir, filename, plot_configs, page_width
     }
 
     # Print the plots in the current group to the PDF
-    if (is.null(grid_layout)) {
+    if (!is.null(grid_layout)) {
-      # Print each plot individually on separate pages if no grid layout is specified
+      # Set grid_ncol to 1 if not specified
-      for (plot in static_plots) {
+      if (is.null(grid_layout$ncol)) {
-        print(plot)
+        grid_layout$ncol <- 1
+      }
+
+      # If ncol is set but nrow is not, calculate nrow dynamically based on num_plots
+      if (!is.null(grid_layout$ncol) && is.null(grid_layout$nrow)) {
+        num_plots <- length(static_plots)
+        nrow <- ceiling(num_plots / grid_layout$ncol)
+        # message("No nrow provided, automatically using nrow = ", nrow)
+        grid_layout$nrow <- nrow
+      }
+      
+      total_spots <- grid_layout$nrow * grid_layout$ncol
+      num_plots <- length(static_plots)
+
+      if (num_plots < total_spots) {
+        message("Filling ", total_spots - num_plots, " empty spots with nullGrob()")
+        static_plots <- c(static_plots, replicate(total_spots - num_plots, nullGrob(), simplify = FALSE))
       }
-    } else {
-      # Arrange plots in grid layout on a single page
       grid.arrange(
         grobs = static_plots,
         ncol = grid_layout$ncol,
         nrow = grid_layout$nrow
       )
+    } else {
+      # Print individual plots on separate pages if no grid layout
+      for (plot in static_plots) {
+        print(plot)
+      }
     }
   }
 
@@ -917,7 +903,7 @@ generate_plate_analysis_plot_configs <- function(variables, df_before = NULL, df
   return(list(plots = plot_configs))
 }
 
-generate_interaction_plot_configs <- function(df_summary, df_interaction, type) {
+generate_interaction_plot_configs <- function(df_summary, df_interactions, type) {
 
   # Define the y-limits for the plots
   limits_map <- list(
@@ -982,7 +968,6 @@ generate_interaction_plot_configs <- function(df_summary, df_interaction, type)
         }
 
         plot_config$annotations <- annotations
-        
         stats_plot_configs <- append(stats_plot_configs, list(plot_config))
 
       } else if (plot_type == "box") {
@@ -995,12 +980,6 @@ generate_interaction_plot_configs <- function(df_summary, df_interaction, type)
   }
 
   # Delta interaction plots
-  if (type == "reference") {
-    group_vars <- c("OrfRep", "Gene", "num")
-  } else if (type == "deletion") {
-    group_vars <- c("OrfRep", "Gene")
-  }
-
   delta_limits_map <- list(
     L = c(-60, 60),
     K = c(-60, 60),
@@ -1008,16 +987,23 @@ generate_interaction_plot_configs <- function(df_summary, df_interaction, type)
     AUC = c(-6000, 6000)
   )
 
-  grouped_data <- df_interaction %>%
+  # Select the data grouping by data type
+  if (type == "reference") {
+    group_vars <- c("OrfRep", "Gene", "num")
+  } else if (type == "deletion") {
+    group_vars <- c("OrfRep", "Gene")
+  }
+
+  grouped_data <- df_interactions %>%
     group_by(across(all_of(group_vars))) %>%
     group_split()
 
   for (group_data in grouped_data) {
+    # Build the plot title
     OrfRep <- first(group_data$OrfRep)
     Gene <- first(group_data$Gene)
-    num <- if ("num" %in% names(group_data)) first(group_data$num) else ""
-
     if (type == "reference") {
+      num <- if ("num" %in% names(group_data)) first(group_data$num) else ""
       OrfRepTitle <- paste(OrfRep, Gene, num, sep = "_")
     } else if (type == "deletion") {
       OrfRepTitle <- OrfRep
@@ -1049,7 +1035,7 @@ generate_interaction_plot_configs <- function(df_summary, df_interaction, type)
         x_label = paste0("[", unique(df_summary$Drug)[1], "]"),
         shape = 16,
         title = paste(OrfRepTitle, Gene, sep = "      "),
-        title_size = rel(1.3),
+        title_size = rel(1.4),
         coord_cartesian = y_limits,
         annotations = list(
           list(x = 1, y = y_limits[2] - 0.1 * y_span, label = paste("      ZShift =", round(Z_Shift_value, 2))),
@@ -1089,6 +1075,7 @@ generate_interaction_plot_configs <- function(df_summary, df_interaction, type)
   chunk_size <- 12
   delta_plot_chunks <- split(delta_plot_configs, ceiling(seq_along(delta_plot_configs) / chunk_size))
 
+  # TODO, only return first page of plots for testing, remove this later
   return(c(
     list(list(grid_layout = list(ncol = 2), plots = stats_plot_configs)),
     list(list(grid_layout = list(ncol = 2), plots = stats_boxplot_configs)),
@@ -1575,7 +1562,7 @@ main <- function() {
       df_deletion <- df_na_stats %>% # formerly X2
         filter(OrfRep != strain) %>%
         filter(!is.na(L)) %>%
-        group_by(OrfRep, Gene, conc_num) %>%
+        group_by(OrfRep, Gene, conc_num, conc_num_factor_factor) %>%
         mutate(
           max_l_theoretical = max(max_L, na.rm = TRUE),
           L = ifelse(L == 0 & !is.na(L) & conc_num > 0, max_l_theoretical, L),