#!/bin/env Rscript

################
# Confidences
################
read_day_1_confidences <- function() {
  readr::read_csv("../../../naiss_intro_python/docs/evaluations/20260420/average_confidences.csv", show_col_types = FALSE)
}
read_day_2_confidences <- function() {
  readr::read_csv("../20260422_day_2/average_confidences.csv", show_col_types = FALSE)
}
read_day_3_confidences <- function() {
  readr::read_csv("../20260423_day_3/average_confidences.csv", show_col_types = FALSE)
}
read_day_4_confidences <- function() {
  readr::read_csv("../20260424_day_4/average_confidences.csv", show_col_types = FALSE)
}

get_day_1_condidences <- function() {
  t <- read_day_1_confidences()
  names(t) <- c("learning_outcomes", "average_confidence")
  t$day <- 1
  t
}
get_day_2_condidences <- function() {
  t <- read_day_2_confidences()
  names(t) <- c("learning_outcomes", "average_confidence")
  t$day <- 2
  t
}
get_day_3_condidences <- function() {
  t <- read_day_3_confidences()
  names(t) <- c("learning_outcomes", "average_confidence")
  t$day <- 3
  t
}
get_day_4_condidences <- function() {
  t <- read_day_4_confidences()
  names(t) <- c("learning_outcomes", "average_confidence")
  t$day <- 4
  t
}
get_condidences <- function() {
  dplyr::bind_rows(
    get_day_1_condidences(),
    get_day_2_condidences(),
    get_day_3_condidences(),
    get_day_4_condidences()
  )
}

t <- get_condidences()
t$day <- as.factor(t$day)
t <- t |> dplyr::arrange(average_confidence)
t$learning_outcomes <- as.factor(t$learning_outcomes)
t$learning_outcomes <- reorder(
  x = t$learning_outcomes,
  X = order(t$average_confidence),
  decreasing = TRUE
)
readr::write_csv(t, "confidences_course.csv")

average_average_confidence <- mean(t$average_confidence)

ggplot2::ggplot(t,
  ggplot2::aes(
    x = average_confidence,
    y = learning_outcomes,
    fill = day
  )
) +
  ggplot2::geom_col() +
  ggplot2::geom_vline(xintercept = average_average_confidence, lty = "dashed") +
  ggplot2::theme(
    strip.text.y = ggplot2::element_text(angle = 0),
    legend.position = "bottom",
    axis.text = ggplot2::element_text(size = 7)
  ) +
  ggplot2::labs(
    title = "Confidences per question",
    caption = paste0(
      " Dashed line denotes the average at ", round(average_average_confidence, digits = 2)
    )
  )

ggplot2::ggsave(filename = "confidences_per_question.png", width = 7, height = 7)

################
# Feedback
################
get_comment_files <- function() {
  comment_files <- tibble::tribble(
    ~day, ~comment_filename,
    1, "../../../naiss_intro_python/docs/evaluations/20260420/survey_end_text_question.txt",
    2, "../20260422_day_2/comments.txt",
    3, "../20260423_day_3/comments.txt",
    4, "../20260424_day_4/comments.txt"
  )
  testthat::expect_all_true(file.exists(comment_files$comment_filename))
  comment_files
}

read_comments <- function(day, comment_files = get_comment_files()) {
  filename <- comment_files[comment_files$day == day, ]$comment_filename
  testthat::expect_true(file.exists(filename))
  lines <- readr::read_lines(filename)
  lines <- lines[!is.na(lines)]
  stringr::str_subset(lines, pattern = "NA|N/a", negate = TRUE)
}

t <- dplyr::bind_rows(
  tibble::tibble(day = 1, comment = read_comments(1)),
  tibble::tibble(day = 2, comment = read_comments(2)),
  tibble::tibble(day = 3, comment = read_comments(3)),
  tibble::tibble(day = 4, comment = read_comments(4))
)
readr::write_csv(t, "comments.csv")

knitr::kable()