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backing up renewed PCA analysis

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This commit is contained in:
Matthew Gaughan 2025-10-08 14:55:31 -07:00
parent 840b32a2e4
commit 186a26f261
2 changed files with 42 additions and 21 deletions
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13
analysis_data/data_verification_2.R Normal file
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@ -0,0 +1,13 @@
library(tidyverse)
library(stringr)
library(tidyr)
library(dplyr)
library(purrr)
main_csv <- "~/analysis_data/100625_unified_w_affil.csv"
main_df <- read.csv(main_csv, header = TRUE)
duplicates <- main_df[duplicated(main_df[, c("comment_text", "TaskPHID", "AuthorPHID")]) |
duplicated(main_df[, c("comment_text", "TaskPHID", "AuthorPHID")], fromLast = TRUE), ]
pulling <- main_df |>
filter(id == "24695" | id == "24696")

50
p2/quest/neurobiber_PCA_analysis.R
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@ -1,11 +1,26 @@
library(tidyverse)
neurobiber_description_pca_csv <-"~/p2/quest/100125_description_PCA_df.csv"
neurobiber_description_pca_df <- read.csv(neurobiber_description_pca_csv , header = TRUE)
neurobiber_description_pca_df <- read.csv(neurobiber_description_pca_csv , header = TRUE) |> mutate(comment_text = text)
neurobiber_subcomment_pca_csv <-"~/p2/quest/100125_subcomment_PCA_df.csv"
neurobiber_subcomment_pca_df <- read.csv(neurobiber_subcomment_pca_csv , header = TRUE)
neurobiber_subcomment_pca_df <- read.csv(neurobiber_subcomment_pca_csv , header = TRUE) |> mutate(comment_text = text)
main_csv <- "~/analysis_data/100625_unified_w_affil.csv"
main_df <- read.csv(main_csv , header = TRUE)
main_df <- main_df |>
select(TaskPHID, AuthorPHID, date_created, comment_text, isAuthorWMF, isGerritBot, resolution_outcome, task_title)
# Join main_df to neurobiber_description_pca_df
description_joined <- main_df |>
right_join(neurobiber_description_pca_df, by = c("TaskPHID", "AuthorPHID", "date_created", "comment_text")) |>
filter(comment_text != "nan") #TODO: look at this more in depth
# Join main_df to neurobiber_subcomment_pca_df
subcomment_joined <- main_df |>
right_join(neurobiber_subcomment_pca_df, by = c("TaskPHID", "AuthorPHID", "date_created", "comment_text")) |>
filter(comment_text != "nan") #TODO: look at this more in depth
preprocess_comment <- function(message) {
library(stringr)
@ -38,7 +53,7 @@ neurobiber_subcomment_pca_df$comment_type <- "subcomment"
neurobiber_description_pca_df$cleaned_comment <- sapply(neurobiber_description_pca_df$text, preprocess_comment)
neurobiber_subcomment_pca_df$cleaned_comment <- sapply(neurobiber_subcomment_pca_df$text, preprocess_comment)
neurobiber_subcomment_pca_df <- neurobiber_subcomment_pca_df %>%
subcomment_joined <- subcomment_joined %>%
mutate(pair_in_description = (paste(AuthorPHID, TaskPHID) %in%
paste(neurobiber_description_pca_df$AuthorPHID,
neurobiber_description_pca_df$TaskPHID)))
@ -81,31 +96,24 @@ affiliationColors <-
setNames( c('#5da2d8', '#c7756a')
,c("False", "True"))
subcomment_joined_no_gerrit <- subcomment_joined |>
filter(isGerritBot != "TRUE")
neurobiber_subcomment_pca_df_x <- neurobiber_subcomment_pca_df %>%
left_join(
neurobiber_description_pca_df %>%
select(TaskPHID, priority),
by = "TaskPHID"
)
neurobiber_description_pca_df_x <- neurobiber_description_pca_df |>
filter(priority %in% c("Lowest","Unbreak Now!"))
#unified_df$AuthorWMFAffil <- factor(unified_df$AuthorWMFAffil, levels = c("False", "True"))
#unified_df <- unified_df[order(unified_df$AuthorWMFAffil), ]
# geom_point(shape = 21, alpha=0.4, size=2) +
# geom_bin_2d() +
ggplot(neurobiber_descriptions_pca_df, aes(x = PC4, y = PC1, fill = pair_in_description)) +
facet_grid(source ~ phase, scales="fixed") +
geom_point(shape = 21, alpha=0.1, size=2) +
geom_smooth() +
xlim(-5, 5) +
ylim(-5, 5) +
scale_fill_viridis_d() + # Or scale_fill_brewer/palette of your choice
ggplot(subcomment_joined_no_gerrit, aes(x = PC2, y = PC1, fill = isAuthorWMF)) +
facet_grid(source ~ pair_in_description, scales="fixed") +
geom_point(shape = 21, alpha=0.3, size=2) +
xlim(-15, 15) +
ylim(-15, 15) +
scale_fill_viridis_d() +
theme_minimal() +
labs(
title = "PCs for Task Comments (Faceted by Source and Phase)",
x = "PC4",
title = "PCs for Task Comments (Faceted by source and pair_in_description)",
x = "PC2",
y = "PC1",
fill = "author_same_as_task_creator?"
fill = "isAuthorWMF?"
)