2025-02-04 04:50:34 +00:00
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library(dplyr)
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2025-02-02 20:16:42 +00:00
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contributing_df_filepath <- "/mmfs1/gscratch/comdata/users/mjilg/govdoc-cr-data/final_data/CONTRIBUTING_weekly_count_data.csv"
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contributing_df = read.csv(contributing_df_filepath, header = TRUE)
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readme_df_filepath <- "/mmfs1/gscratch/comdata/users/mjilg/govdoc-cr-data/final_data/README_weekly_count_data.csv"
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readme_df = read.csv(readme_df_filepath, header = TRUE)
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window_num <- 5
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contributing_df <- contributing_df |>
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filter(week_index >= (- window_num) & week_index <= (window_num)) |>
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mutate(doc_type = "CONTRIBUTING")
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readme_df <- readme_df |>
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filter(week_index >= (- window_num) & week_index <= (window_num)) |>
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mutate(doc_type = "README")
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main_df <- rbind(contributing_df, readme_df)
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main_df$log1p_count <- log1p(main_df$commit_count)
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library(scales)
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library(ggplot2)
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expm1_trans <- trans_new(
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name = 'expm1',
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transform = function(x) expm1(x),
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inverse = function(x) log1p(x)
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)
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doctypeColors <-
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setNames( c('#5da2d8', '#c7756a')
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, c("CONTRIBUTING", "README"))
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time_plot <- main_df |>
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ggplot(aes(x=week_index, y=commit_count, color=factor(doc_type))) +
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scale_y_continuous(trans = 'log1p', labels = scales::comma) +
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labs(x="Weekly Offset", y="Commit Count", color="Document Type: ") +
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scale_color_manual(values = doctypeColors) +
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geom_smooth() +
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geom_vline(xintercept = 0)+
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theme_bw() +
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theme(legend.position = "top")
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time_plot
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2025-02-04 04:50:34 +00:00
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ggsave(filename = "plots/cr-020325-gam-introduction.png", plot = time_plot, width = 9, height = 9, dpi = 800)
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