## -----------------------------------------------------------------------------
#| label: Setup
#| include: false

library(here)

source(here("R", ".setup.R"))


## -----------------------------------------------------------------------------
#| output: false

library(logolink)

library(dplyr)
library(ggplot2)
library(ggimage)
library(ggtext)
library(here)
library(magick)
library(magrittr)
library(ragg)
library(stringr)
library(tidyr)


## -----------------------------------------------------------------------------
model_path <-
  find_netlogo_home() |>
  file.path(
    "models",
    "IABM Textbook",
    "chapter 4",
    "Wolf Sheep Simple 5.nlogox"
  )


## -----------------------------------------------------------------------------
sheep_shape <- get_netlogo_shape("sheep")


## -----------------------------------------------------------------------------
wolf_shape <- get_netlogo_shape("wolf")


## -----------------------------------------------------------------------------
setup_file <- create_experiment(
  name = "Wolf Sheep Simple Model Analysis",
  repetitions = 1,
  sequential_run_order = TRUE,
  run_metrics_every_step = FALSE,
  setup = "setup",
  go = "go",
  time_limit = 500,
  run_metrics_condition = 'ticks mod 100 = 0',
  metrics = c(
    '[xcor] of sheep',
    '[ycor] of sheep',
    '[xcor] of wolves',
    '[ycor] of wolves',
    '[pxcor] of patches',
    '[pycor] of patches',
    '[pcolor] of patches'
  ),
  constants = list(
    "number-of-sheep" = 100,
    "number-of-wolves" = 15,
    "movement-cost" = 0.5,
    "grass-regrowth-rate" = 0.3,
    "energy-gain-from-grass" = 2,
    "energy-gain-from-sheep" = 5
  )
)


## -----------------------------------------------------------------------------
#| output: false

results <-
  model_path |>
  run_experiment(
    setup_file = setup_file,
    output = c("table", "lists")
  )
#> ✔ Running model [2.1s]
#> ✔ Gathering metadata [12ms]
#> ✔ Processing table output [33ms]
#> ✔ Processing lists output [6ms]


## -----------------------------------------------------------------------------
results |>
  extract2("lists") |>
  glimpse()
#> Rows: 7,350
#> Columns: 16
#> $ run_number             <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
#> $ number_of_sheep        <dbl> 100, 100, 100, 100, 100, 100, 100, 100, 100,…
#> $ number_of_wolves       <dbl> 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15,…
#> $ movement_cost          <dbl> 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5,…
#> $ grass_regrowth_rate    <dbl> 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3,…
#> $ energy_gain_from_grass <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
#> $ energy_gain_from_sheep <dbl> 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5,…
#> $ step                   <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
#> $ index                  <chr> "0", "1", "2", "3", "4", "5", "6", "7", "8",…
#> $ pcolor_of_patches      <dbl> 56.35257, 55.37902, 55.10799, 56.12433,…
#> $ pxcor_of_patches       <dbl> -12, 12, 7, -16, 6, -11, 11, 8, 5, -7, -13,…
#> $ pycor_of_patches       <dbl> -6, 11, 10, 15, -14, 13, 13, 6, -9, 8, -5,…
#> $ xcor_of_sheep          <dbl> -12.6365795, 16.9131184, -8.5579481,…
#> $ xcor_of_wolves         <dbl> -17.368182, -11.239707, -13.813702, …
#> $ ycor_of_sheep          <dbl> 17.44700318, 14.04946398, 12.60102781, …
#> $ ycor_of_wolves         <dbl> 16.403987, -15.657477, -1.630277,…


## -----------------------------------------------------------------------------
plot_data <-
  results |>
  extract2("lists") |>
  mutate(
    across(
      .cols = matches("^pcolor_of_patches|^color_of_"),
      .fns = parse_netlogo_color
    )
  )


## -----------------------------------------------------------------------------
plot_netlogo_world <- function(
  data,
  run_number = 1,
  step = 0,
  step_label = TRUE
) {
  data <-
    data |>
    filter(
      run_number == .env$run_number,
      step == .env$step
    )

  plot <-
    data |>
    ggplot(
      aes(
        x = pxcor_of_patches,
        y = pycor_of_patches,
        fill = pcolor_of_patches
      )
    ) +
    geom_raster() +
    coord_fixed(expand = FALSE) +
    geom_image(
      data = data |> drop_na(xcor_of_sheep),
      mapping = aes(
        x = xcor_of_sheep,
        y = ycor_of_sheep,
        image = sheep_shape
      ),
      size = 0.04
    ) +
    geom_image(
      data = data |> drop_na(xcor_of_wolves),
      mapping = aes(
        x = xcor_of_wolves,
        y = ycor_of_wolves,
        image = wolf_shape
      ),
      size = 0.055,
      color = parse_netlogo_color(31)
    ) +
    scale_fill_identity(na.value = parse_netlogo_color(7.5)) +
    theme_void() +
    theme(legend.position = "none")

  if (isTRUE(step_label)) {
    plot +
      labs(title = paste0("Step: **", step, "**")) +
      theme(
        plot.title.position = "plot",
        plot.title = element_markdown(size = 20, margin = margin(b = 10)),
        plot.background = element_rect(fill = "white", color = NA),
        plot.margin = margin(1.5, 1.5, 1.5, 1.5, "line")
      )
  } else {
    plot
  }
}


## -----------------------------------------------------------------------------
#| eval: false
#| include: false

# showtext_auto(FALSE)


## -----------------------------------------------------------------------------
plot_netlogo_world(plot_data)


## -----------------------------------------------------------------------------
#| eval: false
#| include: false

# ggsave(
#   filename = "vignette-wolf-sheep-model-plot-1.png",
#   plot = get_last_plot(),
#   device = agg_png,
#   path = here("man", "figures"),
#   width = 7,
#   height = 7.4,
#   units = "in",
#   dpi = 96
# )


## -----------------------------------------------------------------------------
steps <-
  plot_data |>
  pull(step) |>
  unique()


## -----------------------------------------------------------------------------
steps
#> [1]   0 100 200 300 400 500


## -----------------------------------------------------------------------------
files <- character()

cli_progress_bar("Generating frames", total = length(steps))

for (i in steps) {
  i_plot <- plot_netlogo_world(plot_data, step = i, step_label = TRUE)

  i_file <- tempfile(pattern = paste0("step-", i, "-"), fileext = ".png")

  ggsave(
    filename = i_file,
    plot = i_plot,
    device = agg_png,
    width = 7,
    height = 7.4,
    units = "in",
    dpi = 96
  )

  files <- append(files, i_file)
  cli_progress_update()
}

cli_progress_done()


## -----------------------------------------------------------------------------
animation <-
  files |>
  lapply(image_read) |>
  image_join() |>
  image_animate(fps = 1)


## -----------------------------------------------------------------------------
#| eval: false
#| include: false

# animation |>
#   image_write(
#     here(
#       "man",
#       "figures",
#       "vignette-wolf-sheep-model-animation-1.gif"
#     )
#   )


## -----------------------------------------------------------------------------
#| eval: false
#| output: false

# animation |> image_write("netlogo-world-animation.gif")


## -----------------------------------------------------------------------------
animation