trying to look at the pca_plot 1
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@ -1,5 +1,5 @@
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starting the job at: Tue Sep 2 15:34:49 CDT 2025
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starting the job at: Tue Sep 2 15:49:08 CDT 2025
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setting up the environment
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running the neurobiber labeling script
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job finished, cleaning up
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job pau at: Tue Sep 2 15:35:35 CDT 2025
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job pau at: Tue Sep 2 15:49:52 CDT 2025
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@ -16,6 +16,7 @@ def format_df_data(df):
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if __name__ == "__main__":
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biber_vec_df = pd.read_csv("/home/nws8519/git/mw-lifecycle-analysis/p2/quest/072525_pp_biberplus_labels.csv", low_memory=False)
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biber_vec_df = biber_vec_df[biber_vec_df['comment_type'] == 'task_description']
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biber_vecs = format_df_data(biber_vec_df)
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#handoff to PCA model
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pca = PCA(2)
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@ -23,7 +24,7 @@ if __name__ == "__main__":
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#first looking at comment_type
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le = LabelEncoder()
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colors = le.fit_transform(biber_vec_df['phase'])
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colors = le.fit_transform(biber_vec_df['source'])
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plt.scatter(biber_vecs_pca[:, 0], biber_vecs_pca[:, 1],
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c=colors, edgecolor='none', alpha=0.5, cmap="viridis")
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