caught duplicates in documents, re-running README topic model
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020325_readme_model.rda
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020325_readme_model.rda
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0203_readme_dweek_ranefs.csv
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0203_readme_dweek_ranefs.csv
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mg-govdoc-cr_24004290.out
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mg-govdoc-cr_24004290.out
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@ -0,0 +1,17 @@
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1. SSH tunnel from your workstation using the following command:
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ssh -N -L 8787:n3434:42289 mjilg@klone.hyak.uw.edu
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and point your web browser to http://localhost:8787
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2. log in to RStudio Server using the following credentials:
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user: mjilg
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password: K/bHQjx0xRAp26CGpsXM
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When done using RStudio Server, terminate the job by:
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1. Exit the RStudio Session ("power" button in the top right corner of the RStudio window)
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2. Issue the following command on the login node:
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scancel -f 24004290
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@ -22,7 +22,7 @@ all_gmodel <- glmer.nb(log1p_count ~ before_after * week_index + scaled_age + (b
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data=readme_df)
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summary(all_gmodel)
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#saveRDS(all_gmodel, "020125_readme_model.rda")
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#saveRDS(all_gmodel, "020325_readme_model.rda")
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model_residuals <- residuals(all_gmodel)
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acf(model_residuals)
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@ -35,7 +35,7 @@ variance_components <- as.data.frame(VarCorr(all_gmodel))
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library(broom.mixed)
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library(ggplot2)
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condvals <- broom.mixed::tidy(all_gmodel, effects = "ran_vals", conf.int = TRUE)
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glmer_ranef_Dweek <- test_condvals [which(test_condvals $term == "before_after:week_index"),]
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glmer_ranef_Dweek <- condvals [which(condvals $term == "before_after:week_index"),]
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has_zero <- function(estimate, low, high){
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return(ifelse((low < 0),ifelse((high > 0), 1, 0), 2))
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}
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@ -48,4 +48,4 @@ g <- glmer_ranef_Dweek |>
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theme_bw()
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g
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write.csv(glmer_ranef_Dweek, "0201_readme_dweek_ranefs.csv")
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write.csv(glmer_ranef_Dweek, "0203_readme_dweek_ranefs.csv")
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@ -26,5 +26,14 @@ readme_topics_df <- readme_topics_df |>
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mutate(project_id = ifelse(filename=="jaraco_keyrings.alt_hullabaloo_README.rst", "jaraco_keyrings.alt", project_id)) |>
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mutate(project_id = ifelse(filename=="_vcr_vcr_README.md", "vcr_vcr", project_id))
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filtered_topics <- readme_topics_df |>
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filter(project_id %in% summed_data$project_id)
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merged_df <- inner_join(summed_data, readme_topics_df, by="project_id")
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multiple_mappings <- merged_df %>%
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group_by(project_id) %>%
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filter(n() > 1) %>%
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ungroup()
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merged_df$logged_commits <- log1p(merged_df$summed_count)
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