Add dynamic scaling for axes

qhtcp-workflow/apps/r/calculate_interaction_zscores.R

@@ -419,6 +419,20 @@ generate_and_save_plots <- function(output_dir, file_name, plot_configs, grid_la
       "bar" = plot + geom_bar()
     )
     
+    # Conditionally apply scale_x_continuous if x_breaks, x_labels, and x_label are present
+    if (!is.null(config$x_breaks) && !is.null(config$x_labels) && !is.null(config$x_label)) {
+      plot <- plot + scale_x_continuous(
+        name = config$x_label,
+        breaks = config$x_breaks,
+        labels = config$x_labels
+      )
+    }
+    
+    # Conditionally apply scale_y_continuous if ylim_vals is present
+    if (!is.null(config$ylim_vals)) {
+      plot <- plot + scale_y_continuous(limits = config$ylim_vals)
+    }
+    
     plot
   })
   
@@ -438,15 +452,30 @@ generate_interaction_plot_configs <- function(df, variables) {
   # Define common y-limits and other attributes for each variable dynamically
   limits_map <- list(L = c(-65, 65), K = c(-65, 65), r = c(-0.65, 0.65), AUC = c(-6500, 6500))
 
+  # Define annotation positions based on the variable being plotted
+  annotation_positions <- list(
+    L = list(ZShift = 45, lm_ZScore = 25, NG = -25, DB = -35, SM = -45),
+    K = list(ZShift = 45, lm_ZScore = 25, NG = -25, DB = -35, SM = -45),
+    r = list(ZShift = 0.45, lm_ZScore = 0.25, NG = -0.25, DB = -0.35, SM = -0.45),
+    AUC = list(ZShift = 4500, lm_ZScore = 2500, NG = -2500, DB = -3500, SM = -4500)
+  )
+
+  # Define which annotations to include for each plot
+  annotation_labels <- list(
+    ZShift = function(df, var) paste("ZShift =", round(df[[paste0("Z_Shift_", var)]], 2)),
+    lm_ZScore = function(df, var) paste("lm ZScore =", round(df[[paste0("Z_lm_", var)]], 2)),
+    NG = function(df, var) paste("NG =", df$NG),
+    DB = function(df, var) paste("DB =", df$DB),
+    SM = function(df, var) paste("SM =", df$SM)
+  )
+
   for (variable in variables) {
     # Dynamically generate the names of the columns
     var_info <- list(
       ylim = limits_map[[variable]],
       lm_model = df[[paste0("lm_", variable)]][[1]],    # Access the precomputed linear model
       sd_col = paste0("WT_sd_", variable),
-      delta_var = paste0("Delta_", variable),
+      delta_var = paste0("Delta_", variable)
-      z_shift = paste0("Z_Shift_", variable),
-      z_lm = paste0("Z_lm_", variable)
     )
 
     # Extract the precomputed linear model coefficients
@@ -455,15 +484,12 @@ generate_interaction_plot_configs <- function(df, variables) {
       slope = coef(var_info$lm_model)[2]
     )
 
-    # Set annotations dynamically for ZShift, Z lm Score, NG, DB, SM
+    # Dynamically create annotations based on variable
-    base_y <- if (variable == "L" || variable == "K") 45 else if (variable == "r") 0.45 else 4500
+    annotations <- lapply(names(annotation_positions[[variable]]), function(annotation_name) {
-    annotations <- list(
+      y_pos <- annotation_positions[[variable]][[annotation_name]]
-      list(x = 1, y = base_y, label = paste("ZShift =", round(df[[var_info$z_shift]], 2))),
+      label <- annotation_labels[[annotation_name]](df, variable)
-      list(x = 1, y = base_y - 20, label = paste("lm ZScore =", round(df[[var_info$z_lm]], 2))),
+      list(x = 1, y = y_pos, label = label)
-      list(x = 1, y = base_y - 70, label = paste("NG =", df$NG)),
+    })
-      list(x = 1, y = base_y - 80, label = paste("DB =", df$DB)),
-      list(x = 1, y = base_y - 90, label = paste("SM =", df$SM))
-    )
 
     # Add scatter plot configuration for this variable
     configs[[length(configs) + 1]] <- list(
@@ -506,6 +532,7 @@ generate_interaction_plot_configs <- function(df, variables) {
   return(configs)
 }
 
+
 # Adjust missing values and calculate ranks
 adjust_missing_and_rank <- function(df, variables) {