library(plyr)
library(tidyverse)
library(gridExtra)
library(cowplot)
library(data.table)

#install.packages("extrafont")
#library(extrafont)
# Install **TTF** Latin Modern Roman fonts from www.fontsquirrel.com/fonts/latin-modern-roman
# Import the newly installed LModern fonts, change the pattern according to the 
# filename of the lmodern ttf files in your fonts folder
#font_import(pattern = 'lmroman*') 


library(extrafont)
loadfonts(device = "win")
par(family = "LM Roman 10")

#source("CI-Functions.R")
source("CI-Functions-Bonferroni.R")

defaultpath <- dirname(rstudioapi::getActiveDocumentContext()$path)
setwd(defaultpath)

if (exists ("mydata")) { rm(mydata) }
mydata <- read.table("aggregated_data.csv", header=T, sep=",")

# collect all trials in order to calculate average error rate and time per question per participant, keep non training trials (isTraining = "False")
tmp <- mydata
tmp <- tmp [ order(tmp$user, tmp$vis), ]

# ALL TASKS
tasks <- c('A', 'B', 'C', 'D', 'E')
tasks_names <- c('Scope', 'Direction', 'Arrival', 'Hops', 'Peaks')
plots <- list()


for (i in 1:5) {
  task <- tasks[i]
  task_name <- tasks_names[i]

  # READ TIME
  filename_time <- paste0('plots/printed_time_means_task_', task, '.txt', sep='')
  printed_time <- read.table(filename_time, header = T, sep = ',')
  colnames(printed_time)[colnames(printed_time)=="upperBound_CI."] <- "upperBound_CI"
  printed_time$vis <- factor(printed_time$vis, levels=rev(levels(printed_time$vis)))
  
  filename_timediff <- paste0('plots/printed_time_diffs_task_', task, '.txt', sep='')
  printed_timediff <- read.table(filename_timediff, header = T, sep = ',')
  printed_timediff$technique <- factor(printed_timediff$technique, levels=c("Gly-Ani","Gly-SMul","Ani-SMul"))
  
  # READ ERROR
  filename_error <- paste0('plots/printed_error_means_task_', task, '.txt', sep='')
  printed_error <- read.table(filename_error, header = T, sep = ',')
  colnames(printed_error)[colnames(printed_error)=="upperBound_CI."] <- "upperBound_CI"
  printed_error$vis <- factor(printed_error$vis, levels=rev(levels(printed_error$vis)))
  
  filename_errordiff <- paste0('plots/printed_error_diffs_task_', task, '.txt', sep='')
  printed_errordiff <- read.table(filename_errordiff, header = T, sep = ',')
  printed_errordiff$technique <- factor(printed_errordiff$technique, levels=c("Gly-Ani","Gly-SMul","Ani-SMul"))
  
  # PLOT LABEL
 df_label <- data.frame(
    x = c(0),
    y = c(0),
    text = c(task_name)
  )
  plot_label <- ggplot(df_label, aes(x, y)) + geom_text(aes(label = text), size=7) + ylim(0, 0) + theme_void()

  # PLOT TIME
  analysisData <- c()
  analysisData$name <- printed_time$vis
  analysisData$pointEstimate <- printed_time$mean_time
  analysisData$ci.max <- printed_time$upperBound_CI
  analysisData$ci.min <- printed_time$lowerBound_CI
  
  plot_time <- barChart(printed_time, analysisData$name, nbTechs = 3, ymin = 0, ymax = 40, "", "", mycolor='dodgerblue2')
  
  ## TIME DIFF
  analysisData <- c()
  analysisData$name <- printed_timediff$technique
  analysisData$pointEstimate <- printed_timediff$mean_time
  analysisData$ci.max <- printed_timediff$upperBound_CI
  analysisData$ci.min <- printed_timediff$lowerBound_CI
  analysisData$level <- printed_timediff$corrected_CI
  analysisData$ci_corr.max <- printed_timediff$upperBound_CI_corr
  analysisData$ci_corr.min <- printed_timediff$lowerBound_CI_corr
  
  plot_timediff <- barChart(printed_timediff, analysisData$name, nbTechs = 3, ymin = -15, ymax = 25, "", "", mycolor='dodgerblue2')
  
  # PLOT ERROR
  analysisData <- c()
  analysisData$name <- printed_error$vis
  analysisData$pointEstimate <- printed_error$mean_time
  analysisData$ci.max <- printed_error$upperBound_CI
  analysisData$ci.min <- printed_error$lowerBound_CI
  
  plot_error <- barChart(printed_error, analysisData$name, nbTechs = 3, ymin = 0, ymax = 15, "", "", mycolor='darkorange3')
  
  ## ERROR DIFF
  analysisData <- c()
  analysisData$name <- printed_errordiff$technique
  analysisData$pointEstimate <- printed_errordiff$mean_time
  analysisData$ci.max <- printed_errordiff$upperBound_CI
  analysisData$ci.min <- printed_errordiff$lowerBound_CI
  analysisData$level <- printed_errordiff$corrected_CI
  analysisData$ci_corr.max <- printed_errordiff$upperBound_CI_corr
  analysisData$ci_corr.min <- printed_errordiff$lowerBound_CI_corr
  
  plot_errordiff <- barChart(printed_errordiff, analysisData$name, nbTechs = 3, ymin = -15, ymax = 15, "", "", mycolor='darkorange3')
  
  #### CONFIDENCE
  # TODO: MAKE IT PRETTY
  tmp <- mydata [ which (mydata$question_code == task),]
  
  tmp <- tmp [ order(tmp$user, tmp$vis), ]
  #
  myvars <- c("user", "vis", "question_code","question_internal_id","mean_confidence")
  tmp <- tmp [myvars]
  
  tmp2 <- reshape(tmp, timevar="vis", idvar=c("user","question_code","question_internal_id"), direction="wide")
  colnames(tmp2) <- gsub("mean_confidence.", "", colnames(tmp2))
  
  tmp2 <- na.omit(tmp2)
  
  setnames(tmp2, old=c("SmallMultiples","Animation", "OneMap"), new=c("SMul","Ani", "Gly"))
  
  likert_table <- tmp2
  myvars <- c("SMul", "Ani","Gly") # Symbol name has been changed in paper to Glyph
  likert_table <- likert_table[myvars]
  
  
  likert_table$SMul = factor (likert_table$SMul,
                              levels = c("1","2","3"),
                              ordered = TRUE)
  likert_table$Ani = factor (likert_table$Ani,
                             levels = c("1","2","3"),
                             ordered = TRUE)
  likert_table$Gly = factor (likert_table$Gly,
                             levels = c("1","2","3"),
                             ordered = TRUE)
  
  library(psych)
  headTail(likert_table)
  str(likert_table)
  
  library(likert)
  Result <- likert(likert_table)
  summary(Result)
  confidence_plot <- plot(Result, type="bar",  group.order=c("SMul", "Ani", "Gly")) +
                    theme(legend.position = 'none', 
                          axis.title.x = element_blank(), 
                          plot.background = element_blank(), 
                          panel.background = element_blank(), 
                          text = element_text(size = 20, color = 'black')) +
                    ggtitle('')
  # make grids
  
  this_grid <- plot_grid(
    # label
    plot_grid(plot_label, ncol = 1), # + theme(plot.background = element_rect(color = "black")),
    # time
    plot_grid(plot_time, plot_timediff, ncol = 2, rel_widths =c(2, 3)) +
      theme(plot.background = element_rect(color = "#999999")),
    # error
    plot_grid(plot_error, plot_errordiff, ncol = 2, rel_widths =c(2, 3)) +
      theme(plot.background = element_rect(color = "#999999")), 
    # confidence
    plot_grid(confidence_plot, ncol = 1) +
      theme(plot.background = element_rect(color = "#999999")),
    # config
    #nrow = 3,
    #rel_heights =c(1, 5, 5) 
    ncol = 4,
    rel_widths =c(1, 5, 5, 3) 
  )

  plots[[i]] <- this_grid
}

margin = theme(plot.margin = unit(c(2,2,2,2), "cm"))
#p <- do.call("grid.arrange", c(plots, ncol=3))
p <- do.call("plot_grid", c(plots, nrow=5))
#p <- do.call("ggarrange", c(plots, ncol=6))
#ggarrange(plot_time, plot_timediff, plot_error, plot_errordiff, ncol = 2, nrow = 2)
filename <- "plots/table_all.pdf"
ggsave(filename = filename, p, device = "pdf", width=25, height=12)


#grid.arrange(grobs = lapply(pl, "+", margin))