knn_anim.R

library(tidymodels)
library(tidyverse)
library(discrim)
library(gganimate)

# grid size
n <- 100

parabolic_grid <-
  expand.grid(X1 = seq(-5, 5, length = n),
              X2 = seq(-5, 5, length = n))

get_data <- function(neighbors){
  parabolic_grid <-
    expand.grid(X1 = seq(-5, 5, length = n),
                X2 = seq(-5, 5, length = n))
  
  fda_mod <-
    nearest_neighbor(neighbors=neighbors) %>%
    set_mode("classification") %>%
    set_engine("kknn") %>%
    fit(class ~ ., data = parabolic)
  
  parabolic_grid$fda <-
    predict(fda_mod, parabolic_grid, type = "prob")$.pred_Class1
  
  parabolic_grid <-
  parabolic_grid %>%
    mutate(neighbors = neighbors)
  
  return(parabolic_grid)
}

df <- map_df(c(1,2,3,4,5,6,7,8,9,10,15,20,30,40,50,100,200,300), ~get_data(neighbors=.x))

anim <-
ggplot(parabolic, aes(x = X1, y = X2)) +
  geom_point(aes(color = class), alpha = .5) +
  geom_contour(data = df, aes(z = fda), col = "black", breaks = .5) +
  cowplot::theme_minimal_grid(font_family = "Source Sans Pro", font_size=12) +
  theme(legend.position = "none") +
  coord_equal() +
  transition_manual(neighbors) +
  labs(title= "Neighbors: {current_frame}")

gif <- animate(anim,
               duration=12,
               height = 5,
               width = 5,
               units = "in",
               res = 300,
               renderer = gifski_renderer())

# Save to mp4
anim_save(animation = gif, filename = "knn_anim.gif")