#!/usr/bin/Rscript   
getwd()
setwd("~/git/mosaic_2020/")
getwd()
############################################################
# TASK: boxplots with stats
############################################################
doMyPlotsStats <- function(df) {
    mediators = levels(as.factor(df$mediator))
    
    plots <- list()
    
    for (i in mediators) {
      cat("Plotting:", i, "\n")
      single=df[df$mediator==i,]
      
      max_y = max(single$value, na.rm = T)
      cat("Plotting:", i, "max_y:", max_y, "\n")
    
      #----------
      # boxplot
      #----------
      p = ggplot(single)+ geom_boxplot(aes(x = timepoint
                                           , y = value
                                           , color = obesity
                                           #, palette = c("#00BFC4", "#F8766D")
                                           ))+
        scale_colour_manual(values=c("#00BFC4", "#F8766D")) + 
      theme(axis.text.x = element_text(size = 15)
            , axis.text.y = element_text(size = 15
                                         , angle = 0
                                         , hjust = 1
                                         , vjust = 0)
            , axis.title.x = element_blank()
            , axis.title.y = element_blank()
            , legend.position = "none"
            , plot.subtitle = element_text(size = 20, hjust = 0.5)
            , plot.title = element_text(size = 20, hjust = 0.5)) +
        labs(title = i)
      
      #--------
      # stats
      #---------
      stat_df <- single %>%
        group_by(timepoint, mediator) %>%
        wilcox_test(value ~ obesity, paired = F) %>%
        add_significance("p")
      stat_df$p_format = round(stat_df$p, digits = 3)
      
      stat_df <- stat_df %>%
        add_xy_position(x = "timepoint", dodge = 0.8)
      p2 = p + stat_pvalue_manual(stat_df
                                   #, y.position = max_y
                                   , label = "{p_format} {p.signif}"
                                   , hide.ns = T
                                   , tip.length = 0)+
        scale_y_continuous(expand = expansion(mult = c(0.05, 0.25)))
      plots[[i]] <- p2
      
    }
    return(plots)
  }

###############################################################