updated figures, resolved some DSL issues

analysis_data/scratch.R

@@ -1,8 +1,40 @@
 library(tidyverse)
 library(dplyr)
+library(stringr)
 main_csv <-"~/analysis_data/121625_unified.csv"
 main_df <- read.csv(main_csv, header = TRUE) 
 
+#01-10-26 look for affil rosters
+affils_ <- main_df |>
+  group_by(isAuthorWMF)|>
+  summarise(
+    n_authors = n_distinct(AuthorPHID),
+    .groups = "drop"
+  )
+
+#01-09-26 looking for comments that say certain things: 
+relelvant_messages <- main_df |>
+  mutate(
+    substring_count = str_count(comment_text, "meeting")
+  ) |>
+  filter(substring_count!= 0)
+
+# 01-09-26
+split_of_comments  <- main_df |>
+  group_by(comment_type, source) |>
+  summarize(
+    count = n()
+  )
+
+authors_count <- main_df |>
+  group_by(source, isAuthorWMF)|>
+  summarise(
+    n_authors = n_distinct(AuthorPHID),
+    .groups = "drop"
+  )
+  
+
+#below 01-09-26
 bz_summary <- main_df |>
   mutate(isBz = if_else(
     AuthorPHID == "PHID-USER-idceizaw6elwiwm5xshb", TRUE, FALSE
@@ -64,7 +96,7 @@ summary_df <- tasks_flagged %>%
       TRUE ~ NA
     )
   ) |>
-  group_by(period, source, isAuthorWMF) %>%
+  group_by(period, source) %>%
   summarize(
     total_tasks = n(),
     first_time_tasks = sum(is_first_time_author),

dsl/dsl.R

@@ -82,7 +82,7 @@ dev_model <- dsl(
 )
 summary(dev_model)
 #saveRDS(dev_model, "120725_logit_dsl.RDS")
-#dev_model <- readRDS("dsl/120725_logit_dsl.RDS")
+dev_model <- readRDS("dsl/121625_logit_dsl.RDS")
 library(broom)
 library(dplyr)
 tidy.dsl <- function(x, conf.int = FALSE, conf.level = 0.95, exponentiate = FALSE, ...) {
@@ -149,9 +149,11 @@ dsl_coefs <- ggplot(coef_df, aes(x = estimate, y = term)) +
        y = "Variable") +
   theme_minimal()
 ggsave(
-  filename = "120825_dsl_coefs.png",
+  filename = "011025_dsl_coefs.png",
   plot = dsl_coefs,
   width = 8,    # inches
-  height = 6,   # inches
+  height = 4,   # inches
-  dpi = 600     # high resolution
+  dpi = 800     # high resolution
 )
+
+library(texreg)

dsl/final_bivariate.R

@@ -188,17 +188,17 @@ tasks_created <- ggplot(
              linetype = "3313", color = "black", linewidth = 0.5) +
   geom_vline(xintercept = 0, linetype = "dashed", color = "black", linewidth = 0.5) +
   geom_text(
-    data = subset(weekly_summary, source == "c1" & week_index == 6),
+    data = subset(weekly_summary, source == "c1" & week_index ==10),
     aes(x=week_index, y=120, label='Opt-out deployment'),
-    size = 2.5) + 
+    size = 3) + 
   geom_text(
-    data = subset(weekly_summary, source == "c1" & week_index == -33),
+    data = subset(weekly_summary, source == "c1" & week_index == -21),
     aes(x=week_index, y=120, label='Opt-in Testing'),
-    size = 2.5) + 
+    size = 3) + 
   geom_text(
-    data = subset(weekly_summary, source == "c2" & week_index == -12),
+    data = subset(weekly_summary, source == "c2" & week_index == -18),
     aes(x=week_index, y=20, label='Deployment Announcement'),
-    size = 2.5) + 
+    size = 3) + 
   theme_minimal() + 
   scale_fill_viridis_d(
     breaks = c("FALSE", "TRUE", "BzImport"),    
@@ -212,10 +212,10 @@ tasks_created <- ggplot(
   theme(legend.position = "top")
 tasks_created
 ggsave(
-  filename = "121625_tasks_created.png",
+  filename = "011025_tasks_created.png",
   plot = tasks_created,
-  width = 12,    # inches
+  width = 8,    # inches
-  height = 6,   # inches
+  height = 4,   # inches
   dpi = 800     # high resolution
 )
 

main_plot_script.R

@@ -0,0 +1,215 @@
+library(tidyverse)
+library(dplyr)
+library(tidyr)
+dsl_csv <-"~/dsl/121625_DSL_frame.csv"
+dsl_df <- read.csv(dsl_csv, header = TRUE) 
+#4.1
+weekly_summary <- dsl_df |>
+  group_by(week_index, source, isAuthorWMF)|>
+  summarise(
+    tasks_made = sum(!is.na(resolution_outcome)),
+    count_resolution_outcome = sum(dsl_score),
+    author_closer_sum  = sum(author_closer == TRUE),
+    median_olmo_EP_prop_adac = median(olmo_EP_prop_adac),
+    median_olmo_TSOL_prop_adac = median(olmo_TSOL_prop_adac),
+    median_olmo_RK_prop_adac = median(olmo_RK_prop_adac),
+    median_comments_before_resolution = median(n_comments_before)
+  ) |>
+  mutate(isAuthorWMF = factor(isAuthorWMF, levels = c("FALSE", "BzImport", "TRUE")))
+
+tasks_created <- ggplot(
+  weekly_summary,
+  aes(
+    x=week_index,
+    y=tasks_made, 
+    fill=isAuthorWMF
+  )
+) + 
+  facet_grid(source ~ ., 
+             scales = "free_y",
+             labeller = labeller(source = c("c1" = "VisualEditor", 
+                                            "c2" = "HTTPS-login", 
+                                            "c3" = "HTTP-deprecation"))) +  
+  geom_col(position = position_dodge(width = 0.9), width = 0.8) +
+  geom_vline(data = weekly_summary |> filter(source == "c1"), 
+             aes(xintercept = -29), 
+             linetype = "dotted", color = "black", linewidth = 0.5) +
+  geom_vline(data = weekly_summary |> filter(source == "c1"), 
+             aes(xintercept = -9), 
+             linetype = "dotted", color = "black", linewidth = 0.5) +
+  geom_vline(data = weekly_summary |> filter(source == "c1"), 
+             aes(xintercept = -4), 
+             linetype = "3313", color = "black", linewidth = 0.5) +
+  geom_vline(data = weekly_summary |> filter(source == "c2"), 
+             aes(xintercept = -99), 
+             linetype = "dotted", color = "black", linewidth = 0.5) +
+  geom_vline(data = weekly_summary |> filter(source == "c2"), 
+             aes(xintercept = -4),   
+             linetype = "3313", color = "black", linewidth = 0.5) +
+  geom_vline(data = weekly_summary |> filter(source == "c3"), 
+             aes(xintercept = -97), 
+             linetype = "dotted", color = "black", linewidth = 0.5) +
+  geom_vline(data = weekly_summary |> filter(source == "c3"), 
+             aes(xintercept = -3), 
+             linetype = "3313", color = "black", linewidth = 0.5) +
+  geom_vline(xintercept = 0, linetype = "dashed", color = "black", linewidth = 0.5) +
+  geom_text(
+    data = subset(weekly_summary, source == "c1" & week_index ==10),
+    aes(x=week_index, y=120, label='Opt-out deployment'),
+    size = 3) + 
+  geom_text(
+    data = subset(weekly_summary, source == "c1" & week_index == -21),
+    aes(x=week_index, y=120, label='Opt-in Testing'),
+    size = 3) + 
+  geom_text(
+    data = subset(weekly_summary, source == "c2" & week_index == -18),
+    aes(x=week_index, y=20, label='Deployment Announcement'),
+    size = 3) + 
+  theme_minimal() + 
+  scale_fill_viridis_d(
+    breaks = c("FALSE", "TRUE", "BzImport"),    
+    labels = c("Nonaffiliate", "WMF-affiliate", "BzImport")  
+  ) + 
+  labs(
+    x = "Weeks from Feature Deployment", 
+    y = "Count of Tasks Created", 
+    fill = "Task Author"
+  ) + 
+  theme(legend.position = "top")
+tasks_created
+ggsave(
+  filename = "011025_tasks_created.png",
+  plot = tasks_created,
+  width = 8,    # inches
+  height = 4,   # inches
+  dpi = 800     # high resolution
+)
+
+
+#4.2 plot comparing the TTR for different things 
+ttr_trajectory <- dsl_df |>
+  mutate(ttr_weeks = TTR_hours / 168) |>
+  mutate(isTriaged = if_else(priority == 'Needs Triage',
+                             "Not Triaged",
+                             "Triaged")) |>
+  group_by(week_index, isTriaged, source) |>
+  summarise(
+    count = n(),
+    mean_ttr = mean(ttr_weeks, na.rm = TRUE),
+    sd_ttr = sd(ttr_weeks, na.rm = TRUE)
+  )
+ttr_trajectory_plot <- ttr_trajectory |>
+  filter(week_index >= -13) |>
+  filter(isTriaged == "Not Triaged") |>
+  ggplot(aes(x = week_index)) +
+  # Line for mean TTR
+  geom_line(aes(y = mean_ttr, color = "Mean TTR"), linewidth = 1) +
+  # Ribbon for standard deviation
+  geom_ribbon(aes(ymin = mean_ttr - sd_ttr, ymax = mean_ttr + sd_ttr),
+              fill = "lightblue", alpha = 0.4) +
+  # Line for count of tasks
+  geom_point(aes(y = count, 
+                color = "Count of New Tasks"), linewidth = 1, linetype = "dashed") +
+  # Facet the plot by source and triaged status
+  facet_wrap(source ~ isTriaged, scales = "free_y") +
+  labs(
+    title = "TTR by Source and Triage Status (TODO)",
+    x = "Week Index",
+    y = "Mean TTR (in weeks)",
+    color = "Metrics"
+  ) +
+  scale_color_manual(values = c("Mean TTR" = "blue", "Count of New Tasks" = "red")) +
+  theme_minimal() 
+ttr_trajectory_plot
+
+
+ttr_boxplot <- dsl_df |>
+  filter(priority == "Needs Triage" | 
+           priority == "Unbreak Now!" |
+           priority == "High") |>
+  filter(week_index >= -13) |>
+  ggplot(
+    aes(
+      x=as.factor(week_index),
+      y= TTR_hours/168, 
+      color=priority,
+    )
+  ) + 
+  facet_grid(source ~ ., 
+             scales = "free_y",
+             labeller = labeller(source = c("c1" = "VisualEditor", 
+                                            "c2" = "HTTPS-login", 
+                                            "c3" = "HTTP-deprecation"))) + 
+  geom_boxplot(outlier.shape = NA) +
+  theme_minimal() + 
+  coord_cartesian(ylim = c(0, 112)) + 
+  geom_text(
+    data = subset(dsl_df |>
+                    filter(priority == "Needs Triage" | 
+                             priority == "Unbreak Now!" |
+                             priority == "High"), source == "c1" & week_index == 12),
+    aes(x=week_index, y=80, label='Opt-in Testing'),
+    color = "black",
+    size = 3) + 
+  geom_vline(xintercept =14, linetype = "dashed", color = "black", linewidth = 0.5) +
+  scale_color_viridis_d(option='turbo') + 
+  labs(x = "Weeks from Release", 
+       y = "Time to Resolution (weeks)", 
+       color = "Priority Tag") +
+  theme(legend.position = "top")
+ttr_boxplot
+ggsave(
+  filename = "011025_ttr_boxplot.png",
+  plot = ttr_boxplot,
+  width = 8,    # inches
+  height = 4,   # inches
+  dpi = 800     # high resolution
+)
+#4.3 plot comparing machine labels of information type 
+dsl_df <- dsl_df |>
+  filter(isAuthorWMF != "BzImport")
+
+dsl_df_long <- dsl_df %>%
+  pivot_longer(
+    cols = c(olmo_EP_prop_adac, olmo_RK_prop_adac, olmo_TSOL_prop_adac),
+    names_to = "tag",
+    values_to = "proportion"
+  ) %>%
+  mutate(tag = gsub("olmo_|_prop_adac", "", tag),
+         tag = case_when(
+           tag == "EP" ~ "Existent Problem",
+           tag == "RK" ~ "Record Keeping",
+           tag =="TSOL" ~ "Solutions"
+         )) 
+
+olmo_comparison <- ggplot(
+  dsl_df_long,
+  aes(
+    x = tag,
+    y = proportion, 
+    fill = isAuthorWMF,
+  )
+) + 
+  facet_grid(source ~ ., 
+             scales = "free_y",
+             labeller = labeller(source = c("c1" = "VisualEditor", 
+                                            "c2" = "HTTPS-login", 
+                                            "c3" = "HTTP-deprecation"))) +
+  geom_boxplot() +
+  theme_minimal() + 
+  scale_fill_viridis_d() +
+  labs(
+    x = "Issue Information Type Category", 
+    y = "% of sentences machine-labeled", 
+    color = "Is Author WMF?",
+    fill = "Is Author WMF?"
+  ) + 
+  theme(legend.position = "top")
+olmo_comparison
+ggsave(
+  filename = "011025_machine_label_comparison.png",
+  plot = olmo_comparison,
+  width = 8,    # inches
+  height = 4,   # inches
+  dpi = 800     # high resolution
+)

mgaughan-rstudio-server_32251441.out

@@ -0,0 +1,17 @@
+1. SSH tunnel from your workstation using the following command:
+
+   ssh -N -L 8787:n3443:42777 mjilg@klone.hyak.uw.edu
+
+   and point your web browser to http://localhost:8787
+
+2. log in to RStudio Server using the following credentials:
+
+   user: mjilg
+   password: u+Vtuz9i8I2EYxQXIDps
+
+When done using RStudio Server, terminate the job by:
+
+1. Exit the RStudio Session ("power" button in the top right corner of the RStudio window)
+2. Issue the following command on the login node:
+
+      scancel -f 32251441