#########################################################
# 1b: Define function: coloured barplot by subgroup
# LINK: https://stackoverflow.com/questions/49818271/stacked-barplot-with-colour-gradients-for-each-bar
#########################################################

ColourPalleteMulti = function(df, group, subgroup){
  
  # Find how many colour categories to create and the number of colours in each
  categories <- aggregate(as.formula(paste(subgroup, group, sep="~" ))
                          , df
                          , function(x) length(unique(x)))
  #  return(categories) }
  
  category.start <- (scales::hue_pal(l = 100)(nrow(categories))) # Set the top of the colour pallete
  
  category.end  <- (scales::hue_pal(l = 40)(nrow(categories))) # set the bottom
  
  #return(category.start); return(category.end)}
  
  # Build Colour pallette
  colours <- unlist(lapply(1:nrow(categories),
                           function(i){
                             colorRampPalette(colors = c(category.start[i]
                                                         , category.end[i]))(categories[i,2])}))
  return(colours)
}
#########################################################################

########################
# Generate bp with
# colour palette derived
# from the data using 
# above function
#########################

bp_stability_hmap <- function(plotdf = merged_df3
                              , xvar_colname = "position"
                              #, bar_col_colname = "group"
                              , stability_colname = ""
                              , stability_outcome_colname = ""
                              , p_title = ""  # "Protein stability (DUET)"
                              , my_xaxls = 12 # x-axis label size
                              , my_yaxls = 20 # y-axis label size
                              , my_xaxts = 18 # x-axis text size
                              , my_yaxts = 20 # y-axis text size
                              , my_pts  = 20  # plot-title size
                              , my_xlab = "Position"
                              , my_ylab = "No. of nsSNPs"
)
{
  
  # order the df by position and ensure it is a factor
  plotdf = plotdf[order(plotdf[[xvar_colname]]), ]
  plotdf[[xvar_colname]] = factor(plotdf[[xvar_colname]])
  
  #cat("\nSneak peak:\n")
  head(data.frame( plotdf[[xvar_colname]], plotdf[[stability_colname]] ) )
  
  # stability values isolated to help with generating column called: 'group'
  my_grp = plotdf[[stability_colname]]
  cat( "\nLength of nsSNPs:", length(my_grp)
       , "\nLength of unique values for nsSNPs:", length(unique(my_grp)) )
  
  # Add col: 'group'
  plotdf$group = paste0(plotdf[[stability_outcome_colname]], "_", my_grp, sep = "")
  
  # check unique values in normalised data
  cat("\nNo. of unique values in", stability_colname, "no rounding:"
      , length(unique(plotdf[[stability_colname]])))
  
  # Call the function to create the palette based on the group defined above
  #subcols_ps
  subcols_bp_hmap = ColourPalleteMulti(plotdf, stability_outcome_colname, stability_colname)
  
  cat("\nNo. of sub colours generated:", length(subcols_bp_hmap))
  
  #-------------------------------
  # Generate the subcols barplot
  #-------------------------------
  
  #g = ggplot(plotdf, aes(x = factor(position, ordered = T)))
  g = ggplot(plotdf, aes_string(x = xvar_colname
                                # , ordered = T)
  ))
  
  
  OutWidePlot = g + geom_bar(aes(fill = group)
                             , colour = "grey") +
    
    scale_fill_manual( values = subcols_bp_hmap
                       , guide = "none") +
    
    theme( axis.text.x = element_text(size = my_xaxls
                                      , angle = 90
                                      , hjust = 1
                                      , vjust = 0.4)
           , axis.text.y = element_text(size = my_yaxls
                                        , angle = 0
                                        , hjust = 1
                                        , vjust = 0)
           , axis.title.x = element_text(size = my_xaxts)
           , axis.title.y = element_text(size = my_yaxts ) 
           , plot.title = element_text(size = my_pts
                                       , hjust = 0.5)) +
    
    labs(title = p_title
         , x = my_xlab
         , y = my_ylab)
  
  return(OutWidePlot)
}