fix many plot functions to stop them using the "g=ggplot()" pattern,

which annoyingly throws away lots of useful data that RShiny needs for clickable plots. Also split the "flame bar" for ligand distance out into separate functions in generate_distance_colour_map.R. This can now be easily incorporated into any "wide" graph showing all positions.
2022-08-03 18:56:14 +01:00 · 2022-08-03 18:56:14 +01:00 · bdbc97c40a
commit bdbc97c40a
parent e498d46f8b
8 changed files with 1323 additions and 725 deletions
--- a/scripts/functions/generate_distance_colour_map.R
+++ b/scripts/functions/generate_distance_colour_map.R
@ -0,0 +1,121 @@
+# takes a dataframe and returns the same dataframe with two extra columns for colours and position
+generate_distance_colour_map = function(plotdf,
+                                        xvar_colname = "position",
+                                        yvar_colname = 'duet_scaled',
+                                        lig_dist_colname = "ligand_distance",
+                                        lig_dist_colours = c("green", "yellow", "orange", "red"),
+                                        #tpos0 = 0,
+                                        #tpos1 = 0,
+                                        #tpos2 = 0,
+                                        #tpos3 = 0,
+                                        debug = FALSE
+)
+{
+  #-------------------
+  # x and y axis
+  # range, scale, etc
+  #-------------------
+  my_xlim = length(unique(plotdf[[yvar_colname]])); my_xlim
+  ymin    = min(plotdf[[yvar_colname]]); ymin
+  ymax    = max(plotdf[[yvar_colname]]); ymax
+  
+  #if (tpos0 == 0){
+  #  tpos0 = ymin-0.5
+  #}
+  #if (tpos1 == 0){
+  #  tpos1 = ymin-0.65
+  #}
+  #if (tpos2 == 0){
+  #  tpos2 = ymin-0.75
+  #}
+  #if (tpos3 == 0){
+  #  tpos3 = ymin-0.85
+  #}
+  if (debug) {
+    cat("\nAnnotating x-axis ~", lig_dist_colname, "requested...")
+  }
+  #-------------------------------------
+  # round column values: to colour by
+  #--------------------------------------
+  #plotdf = plotdf[order(plotdf[[lig_dist_colname]]),]
+  plotdf['lig_distR'] = round(plotdf[[lig_dist_colname]], digits = 0)
+  #head(plotdf['lig_distR'])
+  
+  #-------------------------------------
+  # ligand distance range, min, max, etc
+  #--------------------------------------
+  lig_min  = min(round(plotdf[[lig_dist_colname]]), na.rm = T); lig_min
+  lig_max  = max(round(plotdf[[lig_dist_colname]]), na.rm = T); lig_max 
+  lig_mean = round(mean(round(plotdf[[lig_dist_colname]]), na.rm = T)); lig_mean
+  
+  #-------------------------------------
+  # Create mapping colour key
+  #--------------------------------------
+  # sorting removes NA, so that n_colours  ==  length(ligD_valsR)
+  n_colours  = length(sort(unique(round(plotdf[[lig_dist_colname]], digits = 0)))); n_colours
+  
+  lig_cols = colorRampPalette(lig_dist_colours)(n_colours); lig_cols
+  ligD_valsR = sort(unique(round(plotdf[[lig_dist_colname]], digits = 0))); ligD_valsR
+  length(ligD_valsR)
+  
+  if (debug) {
+    if (n_colours == length(ligD_valsR)) {
+      cat("\nStarting: mapping b/w"
+          , lig_dist_colname
+          , "and colours")
+    }else{
+      cat("\nCannot start mapping b/w", lig_dist_colname, "and colours..."
+          , "\nLength mismatch:"
+          , "No. of colours: ", n_colours
+          , "\nValues to map:", length(ligD_valsR))
+    }
+  }
+  
+  ligDcolKey <- data.frame(ligD_colours = lig_cols
+                           , lig_distR = ligD_valsR); ligDcolKey
+  names(ligDcolKey)
+  if (debug) {
+    cat("\nSuccessful: Mapping b/w", lig_dist_colname, "and colours")
+  }
+  #-------------------------------------
+  # merge colour key with plotdf
+  #-------------------------------------- 
+  plotdf = merge(plotdf, ligDcolKey, by = 'lig_distR')
+  
+  plotdf_check = as.data.frame(cbind(position    = plotdf[[xvar_colname]]
+                                     , ligD      = plotdf[[lig_dist_colname]]
+                                     , ligDR     = plotdf$lig_distR
+                                     , ligD_cols = plotdf$ligD_colours))
+  return(plotdf)
+}
+
+generate_distance_legend = function(plotdf,
+                                    yvar_colname,
+                                    xvar_colname = 'position',
+                                    lig_dist_colname = "ligand_distance",
+                                    legend_title = "Ligand\nDistance"
+                                    )
+{
+  # build legend for ligand distance "heat bar"
+  lig_min  = min(round(plotdf[[lig_dist_colname]]), na.rm = T); lig_min
+  lig_max  = max(round(plotdf[[lig_dist_colname]]), na.rm = T); lig_max 
+  lig_mean = round(mean(round(plotdf[[lig_dist_colname]]), na.rm = T)); lig_mean
+  
+  labels  = seq(lig_min, lig_max, len = 5); labels
+  labelsD = round(labels, digits = 0); labelsD
+  
+  get_legend(ggplot(plotdf, aes_string(x = sprintf("factor(%s)", xvar_colname)
+                            , y = yvar_colname)) +
+    
+    geom_tile(aes(fill = .data[[lig_dist_colname]])
+              , colour = "white") +
+    scale_fill_gradient2(midpoint = lig_mean
+                         , low  = "green"
+                         , mid  = "yellow"
+                         , high = "red"
+                         , breaks = labels
+                         , limits = c(lig_min, lig_max)
+                         , labels = labelsD
+                         , name   = legend_title)
+    )
+}