generated some more descriptive stats for Results

analysis_data/scratch.R

@@ -1,4 +1,5 @@
 library(tidyverse)
+library(dplyr)
 main_csv <-"~/analysis_data/121625_unified.csv"
 main_df <- read.csv(main_csv, header = TRUE) 
 
@@ -7,7 +8,7 @@ bz_summary <- main_df |>
     AuthorPHID == "PHID-USER-idceizaw6elwiwm5xshb", TRUE, FALSE
   )) |>
   group_by(source, comment_type, isBz)|>
-  summarise(count = n(), .groups = 'drop')
+  summarize(count = n(), .groups = 'drop')
   
 
 needs_triage <- dsl_df |>
@@ -34,7 +35,7 @@ changes<- dsl_df |>
   filter(!is.na(period)) |>
   mutate(ttr_weeks = TTR/168) |>
   group_by(source, period, priority) %>%
-  summarise(
+  summarize(
     count = n(),
     mean_ttr_weeks = mean(ttr_weeks, na.rm = TRUE),
     sd_ttr_weeks = sd(ttr_weeks, na.rm = TRUE),
@@ -45,7 +46,7 @@ changes<- dsl_df |>
 first_task <- main_df |>
   filter(comment_type == "task_description") |>
   group_by(source, AuthorPHID) |>
-  summarise(
+  summarize(
     task_count = n(),
     first_task_week = min(week_index)
   ) 
@@ -56,7 +57,14 @@ tasks_flagged <- main_df %>%
   mutate(is_first_time_author = week_index == first_task_week)
 
 summary_df <- tasks_flagged %>%
-  group_by(week_index, source) %>%
+  mutate(
+    period = case_when(
+      week_index >= -4 & week_index <= 4   ~ "8 weeks after announcement",
+      week_index >= -13 & week_index <= -5 ~ "8 weeks before deployment announcement",
+      TRUE ~ NA
+    )
+  ) |>
+  group_by(period, source, isAuthorWMF) %>%
   summarize(
     total_tasks = n(),
     first_time_tasks = sum(is_first_time_author),

dsl/scratch.R

@@ -3,6 +3,43 @@ library(tidyverse)
 dsl_csv <-"~/dsl/121625_DSL_frame.csv"
 dsl_df <- read.csv(dsl_csv, header = TRUE) 
 
+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)
+  )
+
+ggplot(ttr_trajectory, aes(x = week_index)) +
+  # Line for mean TTR
+  geom_line(aes(y = mean_ttr, color = "Mean TTR"), size = 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_line(aes(y = count, 
+                color = "Count of New Tasks"), size = 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() +
+  theme(
+    strip.text = element_text(face = "bold", size = 12),
+    axis.text = element_text(size = 10),
+    axis.title = element_text(size = 12)
+  )
+
 dsl_df |>
   filter(week_index >= 4)|>
   filter(source == "c1") |>

mgaughan-rstudio-server_32164721.out

@@ -1,18 +0,0 @@
-1. SSH tunnel from your workstation using the following command:
-
-   ssh -N -L 8787:n3439:57601 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: OmvStzwArWC2NNHj/j8p
-
-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 32164721
-[2026-01-06T14:05:14.031] error: *** JOB 32164721 ON n3439 CANCELLED AT 2026-01-06T14:05:14 DUE TO TIME LIMIT ***