library(data.table)
library(ggplot2)
library(ggridges)
library(dplyr)
library(tidyr)
library(scales)

stackPlot <- function(dat, xlim, labx) {
   data <- data.frame(dat)
   data$X <- NULL
   nobj=dim(data)[1]
   
   # rename columns with ROI list
   rois <- dimnames(dat)[[2]]
   colnames(data) <- rois
   data_stats <- data.frame(1:length(rois))
   
   # create ROI column instead of numerics to match threat table above
   data_stats$ROI <- rois
   data_stats$mean <- colMeans(data)  # median: quantile(x, probs=.5)
   data_stats$P <- colSums(data > 0)/nobj
   data_stats$Pn <- ifelse(data_stats$P < .5, 1-data_stats$P, data_stats$P)
   # this will order the distributions correctly
   data_stats <- data_stats[order(data_stats$mean),]
   
   data_trans <- as.data.frame(t(as.matrix(data)))
   # add two more columns
   data_trans <- tibble::rownames_to_column(data_trans, "ROI")
   data_trans$X <- 1:nrow(data_trans)
   
   # merge values & stats into one table by ROI
   data_merge <- merge(data_stats, data_trans, by = "ROI")
   data_merge <- data_merge[order(data_merge$X),]
   #browser()
   # Transform data into long form: Melt dataframe by ROI
   data_long <- reshape2::melt(data_trans, id=c("ROI","X"))
   data_long <- data_long[order(data_long$X),]
   
   #clunky, but for now stats by ensuring orders are all the same and repeating each value nobj times. no success for alternatives. 
   data_long$mean <- rep(data_merge$mean, each = nobj)
   data_long$P <- rep(data_merge$P, each =nobj)
   data_long$Pn <- rep(data_merge$Pn, each =nobj)
   data_long$gray.vals <- rep(data_merge$gray.vals, each =nobj)
   
   ########################  G R A P H I N G  #########################################################
   #######################     V A R I A B L E S    ######################################################
   # set your labels here so you don't have to change within the plot below: 
   y.axis.labs <- data_stats$ROI                              # y axis labels
   sec.y.axis.labs <- round(data_stats$P,3)                   # second y axis labels (probabilities) - Rounded to 2 decimals
   
   ################# X AXIS LABELS ###########################################################
   # X AXIS LABELS NEED TO CHANGE TO CORRESPOND TO DATA SET! UNCOMMENT WHICHEVER MATCHES
   x.axis.labs <- NULL                                # x axis labels  INTERACTION, not sure what to put.
   x.labs.pos <- NULL                                 # a axis position INTERACTION, change when labels decided
   
   ######## T I T L E S #############################################################
   #data.name <- tl
   graph.title <- "Interaction (% signal change)"                                   # graph title 
   legend.title <- "P+"                              # legend title
   y.axis.title <- NULL                                       # for now ...
   x.axis.title <- NULL                                       # for now...
   
   ########################## D A T A  ##############################################################
   # GRAPH DATA 
   dataset <- data_long
   x.values <- data_long$value                               # x values
   y.values <- data_long$ROI                                 # y values
   y.values.RO <- data_long$value                            # values to reorder Y by
   distrib.fill <- data_long$P                       # fill graph with probabilities
   group <- data_long$ROI
   
   ######################### S A V E  ################################################
   # SAVE SETTINGS -- Currently low res and jpeg to make it easier to share
   # adjusting height + width will throw font sizes out of wack: need change (see other aspects below) 
   
   dpi <- 300
   units <- "in"                                           # "in", "cm", or "mm"
   height <- 5
   width <- 9
   file.type <- ".jpeg"                   # can be ".jpeg",".pdf",".png",".bmp",".tiff",etc
   
   ############################### O T H E R  #################################################
   #gradient.colors<-c("#41245C","yellow","gray","gray","blue","#C9182B") # change gradient colors  
   gradient.colors <- c("blue","cyan","gray","gray","yellow","#C9182B")  # change gradient colors here 
   ROI.label.size <- 20                 # adjust ROI and probability y-axis font size
   P.label.size <- 20
   title.size <- 20                         # adjust graph title size 
   x.axis.size <- 20                                        # adjust x-axis label sizes
   
   ##################  G R A P H  ########################################
   # change information about the graph and add other characteristics using ggplot and ggridges
   ggplot(dataset, aes(x = x.values, 
                       y = as.numeric(reorder(y.values, y.values.RO)), 
                       fill = distrib.fill, 
                       group = group))   +
     guides(fill = guide_colorbar(barwidth = 1,             #legend characteristics
                                  barheight = 20,
                                  nbin = 100, # can change # bins to play around with color gradient
                                  frame.colour = "black",
                                  frame.linewidth = 1.5,
                                  ticks.colour = "black",
                                  title.position = "top",
                                  title.hjust = 0.5)) +
     #geom_density_ridges() +                            # scale = spacing, alpha = transparency
     stat_density_ridges(quantile_lines = TRUE,         # divide into two quantiles (show mean)
                         quantiles = 2,
                         size = .6,
                         alpha = .8,
                         scale = 2,
                         color = "black") +
     geom_vline(xintercept = 0,                        #create line at X = 0
                linetype="solid",
                alpha = 1,
                size = 1,
                color = "green3") +
     scale_fill_gradientn(
                          colors = gradient.colors,                       # set gradient
                          limits = c(0,1),                                # scale size
                          name = legend.title,
                         breaks = c(0,0.05,0.1,0.9,0.95,1),
                         expand = expansion(0),
                         labels = c("0","0.05","0.1","0.9", "0.95","1")
                         ) +
     scale_y_continuous(breaks = 1:length(rois), # A VERY HACK-Y WAY TO HAVE TWO Y AXES W DISCRETE DATA
                        labels = y.axis.labs,   # Trick ggplot into thinking data is continuous...
                        sec.axis = sec_axis(~.,  # Second axis to show probabilities
                                            breaks = 1:length(rois),
                                            labels = sec.y.axis.labs)) +
     theme_ridges(font_size = ROI.label.size, grid = TRUE, center_axis_labels = TRUE) +  # theme info
     #ggtitle(graph.title)+                                                   # graph title
     annotate("text", x=0.06, y=1.5, label=labx, size=11)+
     theme(
       plot.title = element_text(vjust = -0.5, size = title.size),   # plot title size and position
       #axis.title.x=element_text(vjust=0, hjust=0.5),
       axis.text.y.left = element_text(size=ROI.label.size),        # y-axis text size
       axis.text.y.right = element_text(size = P.label.size),       # y-axis info for right axis
       axis.text.x = element_text(size = x.axis.size),   # x-axis text size/face
       #axis.text.x = element_text(size = x.axis.size, face = "bold"),   # x-axis text size/face
       axis.title=element_text(size=28), #,face="bold"),
       legend.title.align = 5,
       #legend.text = element_text(face = "bold"),
       legend.title = element_text(size = 24))+
       #legend.title = element_text(face = "bold", size = 15))+
       labs(
       #x = 'interaction (% signal change)',                 # Add or not add X and Y labels
       x = NULL,
       y = NULL) +
     scale_x_continuous(labels=waiver(), limits = xlim) +
     xlab(labx)
     #scale_x_continuous(breaks = x.labs.pos, labels = c(x.axis.labs),limits = xlim)
   # ggsave(file = paste(period, "_", data.name, file.type, sep=""), width=width, height=height, units = units, dpi = dpi)
}