#!/usr/bin/Rscript   
getwd()
setwd("~/git/mosaic_2020/")
getwd()
############################################################
# TASK: boxplots at T1
# FIXME: currently not rendering, problem with NAs for stats?
############################################################
#=============
# Input
#=============
#source("boxplot_linear.R")
#######################################################
med_names = c("eotaxin3", "il12p70", "itac", "il13")
lf_test = lf_fp_npa[lf_fp_npa$mediator%in%med_names,]

mediators = levels(as.factor(lf_test$mediator))

plots <- list()

for (i in mediators) {
single=lf_test[lf_test$mediator==i,]

max_y = max(single$value, na.rm = T)
cat("Plotting:", i, "max_y:", max_y, "\n")

p2 = ggplot(single)+ geom_boxplot(aes(x = timepoint
                     , y = value
                     , color = obesity
                    #, palette = 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
       #, subtitle = "test2"
       )

stat_npa2 <- single %>%
  group_by(timepoint, mediator) %>%
  wilcox_test(value ~ obesity, paired = F) %>%
  add_significance("p")
stat_npa2

stat_npa2 <- stat_npa2 %>%
  add_xy_position(x = "timepoint", dodge = 0.8)

p2 = p2 + stat_pvalue_manual(stat_npa2
                             #, y.position = max_y
                             , label = "{p} {p.signif}"
                             , hide.ns=T
                             , tip.length = 0)+
  scale_y_continuous(expand = expansion(mult = c(0.05, 0.25)))
plots[[i]] <- p2
}

cowplot::plot_grid(plotlist=plots, align = 'hv', ncol=2, nrow=2)
##################################################################
#=======
# facet
#=======
#--------
# wilcox stats
#--------
stat_npa3 <- lf_test %>%
  group_by(timepoint, mediator) %>%
  wilcox_test(value ~ obesity, paired = F) %>%
  add_significance("p")
stat_npa3 

stat_npa3 <- stat_npa3 %>%
  add_xy_position(x = "timepoint", dodge = 0.8)
head(stat_npa3)

#--------
# summary stats
#--------
my_summary = lf_test %>%
  group_by(timepoint, mediator) %>%
  get_summary_stats(value)
my_summary
my_max_df = subset(my_summary
                   , select = c("mediator", "timepoint"
                                #, "obesity"
                                , "max"))

head(my_max_df); head(stat_npa3)

#-----------------------------
# merge my_max and stat_npa3
#-----------------------------
head(my_max_df)
merging_cols = intersect(names(stat_npa3), names(my_max_df)); merging_cols

stat_npa3_v2 = merge(stat_npa3, my_max_df, by = merging_cols, all.x = T)
stat_npa3_v2$my_y_pos = (stat_npa3_v2$max)*1.2
stat_npa3_v2$my_y_pos

head(stat_npa3_v2); head(stat_npa3)

p3 = ggplot(lf_test)+ geom_boxplot(aes(x = timepoint
                                      , y = value
                                      , color = obesity))+
  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 ="NPA")+
  #facet_wrap(~mediator, scales = "free")

p3_build = ggbuild(p3)  
  
p4 = p3 + stat_pvalue_manual(stat_npa3_v2
                             , y.position = "my_y_pos"
                             #, y.position = 50
                             , label = "{p} {p.signif}"
                             , hide.ns=T
                             , tip.length = 0)+
  scale_y_continuous(expand = expansion(mult = c(0.05, 0.25)))

p4
#========================================
p3_build = ggplot_build(p3)
p3_build$layout$panel_scales_y

get_facet_ymax <- function (x){
  ret <- x$layout$panel_scales_y
  y_max =  NULL
  
  for (i in 1:length(ret)){
    print(i)
    y_max_i <- max(x$layout$panel_scales_y[[i]]$range$range)
    y_max = c(y_max, y_max_i)
  }
  
  return(y_max)
}

y_max_l = get_facet_ymax(p3_build); y_max_l