#* days_plot_epoch_stats:
#*   attr:
#*     fillcolor: '2'
#*   desc: Summary visualization of pre vs post epoch lengths.
#*   ext: R
#*   inputs:
#*   - person_all_facts
#* 

library(dplyr)
library(ggplot2)
library(tidyr)

days_plot_epoch_stats <- function(person_all_facts) {
    epoch_stats_by_person <- SparkR::collect(SparkR::select(person_all_facts, c("pre_epoch_effective_days", "post_epoch_effective_days", "cohort")))
    print(str(epoch_stats_by_person))

    # p <- ggplot(epoch_stats_by_person) +
    #     stat_summary_2d(aes(x = pre_num_condition_eras, y = post_num_condition_eras, z = increase_effective_days), fun = length, bins = 60) +
    #     scale_x_continuous(trans = "log10") + 
    #     scale_y_continuous(trans = "log10") +
    #     scale_fill_continuous(trans = "log10") +
    #     annotation_logticks(sides = "bl")
    # plot(p)

    p2 <- ggplot(epoch_stats_by_person) +
        stat_summary_hex(aes(x = pre_epoch_effective_days, y = post_epoch_effective_days, z = cohort), fun = length, bins = 60) +
        scale_x_continuous(trans = "log10") + 
        scale_y_continuous(trans = "log10") +
        #scale_fill_continuous(trans = "log10") +
        annotation_logticks(sides = "bl") +
        facet_wrap(~ cohort) +
        coord_equal()
    plot(p2)

    return(NULL)
}