library(tidyverse)
library(dplyr)
entest_fp <-"/mmfs1/gscratch/comdata/users/mjilg/mw-repo-lifecycles/case1/en-testing_0312_extensions_ve_weekly_commit_count_data.csv"
entest_df <- read.csv(entest_fp, header = TRUE) |> mutate(rd_event = "en-testing")

widetest_fp <-"/mmfs1/gscratch/comdata/users/mjilg/mw-repo-lifecycles/case1/wide-testing_0312_extensions_ve_weekly_commit_count_data.csv"
widetest_df <- read.csv(widetest_fp, header = TRUE) |> mutate(rd_event = "wide-testing")

event_fp <-"/mmfs1/gscratch/comdata/users/mjilg/mw-repo-lifecycles/case1/event_0312_extensions_ve_weekly_commit_count_data.csv"
event_df <- read.csv(event_fp, header = TRUE) |> mutate(rd_event = "default")

#input_df <- bind_rows(entest_df, widetest_df, event_df)
#dropping the event (2013-07-01) from the modeling
#input_df <- bind_rows(entest_df, widetest_df)
input_df <- event_df

input_df <- input_df |>
  mutate(nonbot_commit_count = commit_count - bot_commit_count)|>
  mutate(other_commit_count = nonbot_commit_count - mediawiki_dev_commit_count - wikia_commit_count - wikimedia_commit_count) |>
  mutate(wikimedia_commit_count = wikimedia_commit_count + mediawiki_dev_commit_count + wikia_commit_count) |>
  dplyr::select(-mediawiki_dev_commit_count) |>
  dplyr::select(-wikia_commit_count)

library(MASS)

library(lme4)
library(dplyr)

#get into mlm format
long_df <- input_df |>
  tidyr::pivot_longer(cols = c(other_commit_count, wikimedia_commit_count, unaff_ft_commit_count),
               names_to = "commit_type",
               values_to = "lengthened_commit_count")

intermediate_long_df <- long_df |>
  mutate(commit_share = lengthened_commit_count / (nonbot_commit_count)) |>
  mutate(log_commits = log1p(lengthened_commit_count))|>
  mutate(scaled_long_commits = lengthened_commit_count / 10) 

library(rdd)

var(intermediate_long_df$lengthened_commit_count) 
mean(intermediate_long_df$lengthened_commit_count) 
median(intermediate_long_df$lengthened_commit_count) 

get_optimal_bandwidth <- function(df){
  bw <- tryCatch({
    IKbandwidth(df$relative_week, df$lengthened_commit_count, cutpoint = 0, verbose = FALSE, kernel = "triangular")
  }, error = function(e) {
    NA
  })
}

intermediate_long_df <- intermediate_long_df |>
  filter(commit_type != "unaff_ft_commit_count")

optimal_bandwidth <- get_optimal_bandwidth(intermediate_long_df)

library(dplyr)
window_num <- 10
final_long_df <- intermediate_long_df |>
  filter(relative_week >= (-window_num) & relative_week <= window_num) |>
  filter(commit_type != "unaff_ft_commit_count")

library(fitdistrplus)
descdist(final_long_df$lengthened_commit_count, discrete=FALSE)
#start_values <- list(shape1 = 1, shape2 = 1)
#fit <- MASS::fitdistr(as.numeric(long_df$lengthened_commit_count), "negative binomial")
#print(fit)

#NOTE should not run if you've already dropped NA
mlm <- glmer.nb(lengthened_commit_count ~ before_after*relative_week +
                  (before_after*relative_week|commit_type),
                control=glmerControl(optimizer="bobyqa",
                                     optCtrl=list(maxfun=2e5)), nAGQ=0,
                data=final_long_df)
#(before_after*relative_week|rd_event)

saveRDS(mlm, file = "0312_ve_ve_event_commits_mlm.rds")
#mlm <- readRDS("commit_analysis/case1/0312_core_ve_testing_commits_mlm.rds")
summary(mlm)
qqnorm(residuals(mlm))
res <- ranef(mlm)
print(res)


library(broom.mixed)
library(ggplot2)
condvals <- broom.mixed::tidy(mlm, effects = "ran_vals", conf.int = TRUE)
glmer_ranef_ba <- condvals
write.csv(glmer_ranef_ba, "0312_ve_ve_event_ba_ranefs.csv")




texreg(mlm)
#final_long_df <- final_long_df |>
#  drop_na()
library(performance)
library(texreg)



#descdist(final_long_df$commit_share, discrete=FALSE)

wikimedia_long_df <- final_long_df |>
  filter(commit_type == "wikimedia_commit_count")|>
  drop_na()

#wikimedia_share_lm <- lm(commit_share ~ before_after*relative_week,
#                         data=wikimedia_long_df)
#summary(wikimedia_share_lm)
#qqnorm(residuals(wikimedia_share_lm))
wikimedia_share_lmer <- lmer(commit_share ~ before_after*relative_week + 
                               (before_after*relative_week | rd_event),
                             data=wikimedia_long_df)

summary(wikimedia_share_lmer)
ranef(wikimedia_share_lmer)
texreg(wikimedia_share_lm)

other_long_df <- final_long_df |>
  filter(commit_type == "other_commit_count") |>
  drop_na()
other_share_lmer <- lmer(commit_share ~ before_after*relative_week +
                         (1| rd_event),
                           data=other_long_df)
#other_share_lm <- lm(commit_share ~ before_after*relative_week, 
#                     data=other_long_df)
summary(other_share_lmer)
qqnorm(residuals(other_share_lm))

texreg(other_share_lm)