adding updated human labels etc.
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377739
110925_unified.csv
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377739
110925_unified.csv
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146015
analysis_data/102125_constituent_dfs/110525_olmo_batched_categorized.csv
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146015
analysis_data/102125_constituent_dfs/110525_olmo_batched_categorized.csv
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@ -70,7 +70,7 @@ first_join <- main_df|>
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by = "id"
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by = "id"
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)
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)
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olmo_csv <- "~/analysis_data/102125_constituent_dfs/all_102125_olmo_batched_categorized.csv"
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olmo_csv <- "~/analysis_data/102125_constituent_dfs/110525_olmo_batched_categorized.csv"
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olmo_df <- read.csv(olmo_csv, header = TRUE)
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olmo_df <- read.csv(olmo_csv, header = TRUE)
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olmo_df <- olmo_df |>
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olmo_df <- olmo_df |>
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@ -132,6 +132,6 @@ pulling <- unified_df |>
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pulling <- unified_df |>
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pulling <- unified_df |>
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filter(id == "23366" | id == "20846" | id == "20847")
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filter(id == "23366" | id == "20846" | id == "20847")
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write.csv(unified_df, "102725_unified.csv", row.names = FALSE)
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write.csv(unified_df, "110925_unified.csv", row.names = FALSE)
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Can't render this file because it is too large.
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Can't render this file because it is too large.
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@ -1,17 +0,0 @@
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1. SSH tunnel from your workstation using the following command:
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ssh -N -L 8787:n3439:51687 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: JZoMumQwFbIc7EUcaGbK
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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 30651103
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