gganimate gif for visual-world eye-tracking data from de Carvalho et al. (2017)

eyetracking_gganimate

read_csv("https://yjunechoe.netlify.app/data/CarvalhoEtAl_2017.csv", col_types = cols(reveal_time = col_integer())) %>%
ggplot(aes(Time, Proportion)) +
  geom_ribbon(
    aes(ymin = YMin, ymax = YMax, group = Condition),
    color = "grey70",
    fill = "grey80",
    alpha = .3
  ) +
  geom_point(
    aes(color = Condition, group = Condition)
  ) +
  geom_line(
    aes(color = Condition, group = Condition), 
    size = 1
  ) +
  geom_segment(
    aes(xend = 6500, yend = Proportion, group = Condition), 
    linetype = 2, 
    color = 'grey'
  ) +
  geom_text(
    aes(x = 6750, label = paste(Condition, "Accent"), color = Condition, group = Condition), 
    hjust = 0, size = 4, family = "Montserrat")
+
  geom_text(
    aes(x = 4100, y = 0.85, label = "Disambiguating Word Presented"), 
    data = tibble(reveal_time = 280L), 
    family = "Adelle", size = 3
  ) +
  geom_segment(
    aes(x = 4100, xend = 4100, y = 0, yend = 0.8), 
    linetype = 2, size = .6, color = "red", 
    data = tibble(reveal_time = 280L)
  ) +
  scale_y_continuous(limits = c(0, 1)) +
  scale_x_continuous(labels = function(x) {paste0(x, "ms")}) +
  coord_cartesian(clip = 'off', expand = FALSE, xlim = c(-1550, 6500)) + 
  palettetown::scale_color_poke(pokemon = "Squirtle", spread = 2) +
  ggthemes::theme_clean(base_family = "Roboto") +
  labs(
    y = NULL, 
    title = "Proportion of looks towards NOUN picture", 
    x = "Time from onset of ambiguous word", 
    caption = "Source: de Carvalho et al. (2017)"
  ) +
  theme(
    plot.margin = margin(.5, 4, .4, 1, "cm"), 
    legend.position = 0, 
    plot.background = element_rect(color = "#f9f9f9"),
    plot.title = element_text(family = "Roboto Slab", margin = margin(b = .5, unit = "cm")),
    axis.title.x = element_text(margin = margin(t = .2, unit = "cm")), 
    plot.caption = element_text(family = "IBM Plex Mono", size = 7, margin = margin(t = .3, unit = "cm")),
    plot.caption.position = "plot"
  ) +
  transition_reveal(reveal_time)