Graph Not Changing Colors in R-CodePudding

I wrote the following procedure in R:

Start with a data frame called "giraffe" data
Sample 30% of this data and label it "sample"
Create a histogram for this data, and color the areas of this histogram that were "sampled" as one color, and the other rows another color

Repeat this process 100 times and make an animation of this process

library(ggplot2)
  library(dplyr)
  library(gganimate)

  giraffe_data <- data.frame( a = abs(rnorm(1000,17,10)), b = abs(rnorm(1000,17,10)))

  results <- list()



  for( i in 1:100) 

  {

      giraffe_data_i <- giraffe_data 
      a_i <- c("sample", "not_sampled")
      aa_i <- as.factor(sample(a_i, 1000, replace=TRUE, prob=c(0.3, 0.7)))
      giraffe_data_i $col = cut(giraffe_data_i$a, c(-Inf, 17, Inf))
      giraffe_data_i$sample <- aa_i
      giraffe_data_i$iteration <- i   1



      results[[i]] <- giraffe_data_i

  }

  results
  results_df <- do.call(rbind.data.frame, results)




  animate(
    ggplot(results_df, aes(x=a, fill = col))   
    geom_histogram(binwidth=1)    
    scale_fill_manual(breaks = levels(results_df$col), values = c('blue', 'red'))  
    transition_states(iteration, state_length = 0.2)  
    labs(title = "Group: {closest_state}"),
    fps = 25)

But for some reason, this graph does not change colors in the animation.

Can someone please show me how to fix this?

Thanks

Note: I was able to get the colors to change with the following code:

animate(
    ggplot(results_df, aes(x=a, color = sample))   
        geom_histogram(fill="white", position="dodge")   
        transition_states(iteration, state_length = 0.2)  
        labs(title = "Group: {closest_state}"),
    fps = 5)

But this shows the two colors as two separate "groups". I want there to be only one "group", but there to be different colors within this one "group". Can someone please show me how to fix this?

Thanks

CodePudding user response：

Sometimes I find it easier to do transformations of the data upstream of gganimate. So here's an approach of binning the data and counting for each iteration, and then plotting as a normal column geom.

library(tidyverse); library(gganimate)
# bins of width 2
bin_wid = 2
results_df_bins <- results_df %>%
  # "col" is set at 17 but my bins are at even #s, so to align 
  #   bins with that I offset by 1
  mutate(a_bin = floor((a   1)/ bin_wid)*bin_wid) %>%
  count(a_bin, col, sample, iteration) %>%
  mutate(sample = fct_rev(sample)) # put "sample" first

animate(
  ggplot(results_df_bins, aes(x=a_bin, y = n, fill = sample))   
    geom_col(position = position_stack(reverse = TRUE))  
    transition_states(iteration, state_length = 0.2)  
    labs(title = "Group: {closest_state}"),
  fps = 25, nframes = 500, height = 300)