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cdsc_reddit/clustering/Makefile

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Updating to support wang-style user overlaps.
2020-12-25 06:38:04 +00:00
#srun_cdsc='srun -p comdata-int -A comdata --time=300:00:00 --time-min=00:15:00 --mem=100G --ntasks=1 --cpus-per-task=28'
add 2 more umap parameters
2022-06-09 00:27:37 +00:00
srun_singularity=srun -p compute-bigmem -A comdata --time=48:00:00 --mem=362G -c 40
grid sweep selection for clustering hyperparameters
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similarity_data=/gscratch/comdata/output/reddit_similarity
clustering_data=/gscratch/comdata/output/reddit_clustering
update clustering scripts
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kmeans_selection_grid=--max_iters=[3000] --n_inits=[10] --n_clusters=[100,500,1000,1250,1500,1750,2000]
add support for umap->hdbscan clustering method
2022-06-09 00:01:27 +00:00
changes from dirty branch.
2023-05-18 17:29:08 +00:00
umap_hdbscan_selection_grid=--min_cluster_sizes=[2] --min_samples=[2,3,4,5] --cluster_selection_epsilons=[0,0.01,0.05,0.1,0.15,0.2] --cluster_selection_methods=[eom,leaf] --n_neighbors=[5,15,25,50,75,100] --learning_rate=[1] --min_dist=[0,0.1,0.25,0.5,0.75,0.9,0.99] --local_connectivity=[1] --densmap=[True,False] --n_components=[2,5,10,15,25]
add support for umap->hdbscan clustering method
2022-06-09 00:01:27 +00:00
update clustering scripts
2021-08-03 21:55:02 +00:00
hdbscan_selection_grid=--min_cluster_sizes=[2,3,4,5] --min_samples=[2,3,4,5] --cluster_selection_epsilons=[0,0.01,0.05,0.1,0.15,0.2] --cluster_selection_methods=[eom,leaf]
affinity_selection_grid=--dampings=[0.5,0.6,0.7,0.8,0.95,0.97,0.99] --preference_quantiles=[0.1,0.3,0.5,0.7,0.9] --convergence_iters=[15]
Updating to support wang-style user overlaps.
2020-12-25 06:38:04 +00:00
Refactor to make a decent api.
2021-05-10 20:46:49 +00:00
authors_10k_input=$(similarity_data)/subreddit_comment_authors_10k.feather
authors_10k_input_lsi=$(similarity_data)/subreddit_comment_authors_10k_LSI
authors_10k_output=$(clustering_data)/subreddit_comment_authors_10k
authors_10k_output_lsi=$(clustering_data)/subreddit_comment_authors_10k_LSI
Updating to support wang-style user overlaps.
2020-12-25 06:38:04 +00:00
Refactor to make a decent api.
2021-05-10 20:46:49 +00:00
authors_tf_10k_input=$(similarity_data)/subreddit_comment_authors-tf_10k.feather
authors_tf_10k_input_lsi=$(similarity_data)/subreddit_comment_authors-tf_10k_LSI
authors_tf_10k_output=$(clustering_data)/subreddit_comment_authors-tf_10k
authors_tf_10k_output_lsi=$(clustering_data)/subreddit_comment_authors-tf_10k_LSI
grid sweep selection for clustering hyperparameters
2021-04-20 18:33:54 +00:00
Refactor to make a decent api.
2021-05-10 20:46:49 +00:00
terms_10k_input=$(similarity_data)/subreddit_comment_terms_10k.feather
terms_10k_input_lsi=$(similarity_data)/subreddit_comment_terms_10k_LSI
terms_10k_output=$(clustering_data)/subreddit_comment_terms_10k
terms_10k_output_lsi=$(clustering_data)/subreddit_comment_terms_10k_LSI
Use Latent semantic indexing and hdbscan
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Refactor to make a decent api.
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all:terms_10k authors_10k authors_tf_10k terms_10k_lsi authors_10k_lsi authors_tf_10k_lsi
Use Latent semantic indexing and hdbscan
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Refactor to make a decent api.
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terms_10k:${terms_10k_output}/kmeans/selection_data.csv ${terms_10k_output}/affinity/selection_data.csv ${terms_10k_output}/hdbscan/selection_data.csv
Use Latent semantic indexing and hdbscan
2021-05-03 06:39:55 +00:00
Refactor to make a decent api.
2021-05-10 20:46:49 +00:00
authors_10k:${authors_10k_output}/kmeans/selection_data.csv ${authors_10k_output}/hdbscan/selection_data.csv ${authors_10k_output}/affinity/selection_data.csv
Use Latent semantic indexing and hdbscan
2021-05-03 06:39:55 +00:00
Refactor to make a decent api.
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authors_tf_10k:${authors_tf_10k_output}/kmeans/selection_data.csv ${authors_tf_10k_output}/hdbscan/selection_data.csv ${authors_tf_10k_output}/affinity/selection_data.csv
Use Latent semantic indexing and hdbscan
2021-05-03 06:39:55 +00:00
Refactor to make a decent api.
2021-05-10 20:46:49 +00:00
terms_10k_lsi:${terms_10k_output_lsi}/kmeans/selection_data.csv ${terms_10k_output_lsi}/affinity/selection_data.csv ${terms_10k_output_lsi}/hdbscan/selection_data.csv
Use Latent semantic indexing and hdbscan
2021-05-03 06:39:55 +00:00
Refactor to make a decent api.
2021-05-10 20:46:49 +00:00
authors_10k_lsi:${authors_10k_output_lsi}/kmeans/selection_data.csv ${authors_10k_output_lsi}/hdbscan/selection_data.csv ${authors_10k_output_lsi}/affinity/selection_data.csv
authors_tf_10k_lsi:${authors_tf_10k_output_lsi}/kmeans/selection_data.csv ${authors_tf_10k_output_lsi}/hdbscan/selection_data.csv ${authors_tf_10k_output_lsi}/affinity/selection_data.csv
${authors_10k_output}/kmeans/selection_data.csv:selection.py ${authors_10k_input} clustering_base.py kmeans_clustering.py
$(srun_singularity) python3 kmeans_clustering.py --inpath=${authors_10k_input} --outpath=${authors_10k_output}/kmeans --savefile=${authors_10k_output}/kmeans/selection_data.csv $(kmeans_selection_grid)
${terms_10k_output}/kmeans/selection_data.csv:selection.py ${terms_10k_input} clustering_base.py kmeans_clustering.py
$(srun_singularity) python3 kmeans_clustering.py --inpath=${terms_10k_input} --outpath=${terms_10k_output}/kmeans --savefile=${terms_10k_output}/kmeans/selection_data.csv $(kmeans_selection_grid)
${authors_tf_10k_output}/kmeans/selection_data.csv:clustering.py ${authors_tf_10k_input} clustering_base.py kmeans_clustering.py
$(srun_singularity) python3 kmeans_clustering.py --inpath=${authors_tf_10k_input} --outpath=${authors_tf_10k_output}/kmeans --savefile=${authors_tf_10k_output}/kmeans/selection_data.csv $(kmeans_selection_grid)
${authors_10k_output}/affinity/selection_data.csv:selection.py ${authors_10k_input} clustering_base.py affinity_clustering.py
$(srun_singularity) python3 affinity_clustering.py --inpath=${authors_10k_input} --outpath=${authors_10k_output}/affinity --savefile=${authors_10k_output}/affinity/selection_data.csv $(affinity_selection_grid)
${terms_10k_output}/affinity/selection_data.csv:selection.py ${terms_10k_input} clustering_base.py affinity_clustering.py
$(srun_singularity) python3 affinity_clustering.py --inpath=${terms_10k_input} --outpath=${terms_10k_output}/affinity --savefile=${terms_10k_output}/affinity/selection_data.csv $(affinity_selection_grid)
${authors_tf_10k_output}/affinity/selection_data.csv:clustering.py ${authors_tf_10k_input} clustering_base.py affinity_clustering.py
$(srun_singularity) python3 affinity_clustering.py --inpath=${authors_tf_10k_input} --outpath=${authors_tf_10k_output}/affinity --savefile=${authors_tf_10k_output}/affinity/selection_data.csv $(affinity_selection_grid)
${authors_10k_output}/hdbscan/selection_data.csv:selection.py ${authors_10k_input} clustering_base.py hdbscan_clustering.py
$(srun_singularity) python3 hdbscan_clustering.py --inpath=${authors_10k_input} --outpath=${authors_10k_output}/hdbscan --savefile=${authors_10k_output}/hdbscan/selection_data.csv $(hdbscan_selection_grid)
${terms_10k_output}/hdbscan/selection_data.csv:selection.py ${terms_10k_input} clustering_base.py hdbscan_clustering.py
$(srun_singularity) python3 hdbscan_clustering.py --inpath=${terms_10k_input} --outpath=${terms_10k_output}/hdbscan --savefile=${terms_10k_output}/hdbscan/selection_data.csv $(hdbscan_selection_grid)
${authors_tf_10k_output}/hdbscan/selection_data.csv:clustering.py ${authors_tf_10k_input} clustering_base.py hdbscan_clustering.py
$(srun_singularity) python3 hdbscan_clustering.py --inpath=${authors_tf_10k_input} --outpath=${authors_tf_10k_output}/hdbscan --savefile=${authors_tf_10k_output}/hdbscan/selection_data.csv $(hdbscan_selection_grid)
## LSI Models
${authors_10k_output_lsi}/kmeans/selection_data.csv:selection.py ${authors_10k_input_lsi} clustering_base.py kmeans_clustering.py
$(srun_singularity) python3 kmeans_clustering_lsi.py --inpath=${authors_10k_input_lsi} --outpath=${authors_10k_output_lsi}/kmeans --savefile=${authors_10k_output_lsi}/kmeans/selection_data.csv $(kmeans_selection_grid)
${terms_10k_output_lsi}/kmeans/selection_data.csv:selection.py ${terms_10k_input_lsi} clustering_base.py kmeans_clustering.py
$(srun_singularity) python3 kmeans_clustering_lsi.py --inpath=${terms_10k_input_lsi} --outpath=${terms_10k_output_lsi}/kmeans --savefile=${terms_10k_output_lsi}/kmeans/selection_data.csv $(kmeans_selection_grid)
${authors_tf_10k_output_lsi}/kmeans/selection_data.csv:clustering.py ${authors_tf_10k_input_lsi} clustering_base.py kmeans_clustering.py
$(srun_singularity) python3 kmeans_clustering_lsi.py --inpath=${authors_tf_10k_input_lsi} --outpath=${authors_tf_10k_output_lsi}/kmeans --savefile=${authors_tf_10k_output_lsi}/kmeans/selection_data.csv $(kmeans_selection_grid)
${authors_10k_output_lsi}/affinity/selection_data.csv:selection.py ${authors_10k_input_lsi} clustering_base.py affinity_clustering.py
$(srun_singularity) python3 affinity_clustering_lsi.py --inpath=${authors_10k_input_lsi} --outpath=${authors_10k_output_lsi}/affinity --savefile=${authors_10k_output_lsi}/affinity/selection_data.csv $(affinity_selection_grid)
${terms_10k_output_lsi}/affinity/selection_data.csv:selection.py ${terms_10k_input_lsi} clustering_base.py affinity_clustering.py
$(srun_singularity) python3 affinity_clustering_lsi.py --inpath=${terms_10k_input_lsi} --outpath=${terms_10k_output_lsi}/affinity --savefile=${terms_10k_output_lsi}/affinity/selection_data.csv $(affinity_selection_grid)
${authors_tf_10k_output_lsi}/affinity/selection_data.csv:clustering.py ${authors_tf_10k_input_lsi} clustering_base.py affinity_clustering.py
$(srun_singularity) python3 affinity_clustering_lsi.py --inpath=${authors_tf_10k_input_lsi} --outpath=${authors_tf_10k_output_lsi}/affinity --savefile=${authors_tf_10k_output_lsi}/affinity/selection_data.csv $(affinity_selection_grid)
${authors_10k_output_lsi}/hdbscan/selection_data.csv:selection.py ${authors_10k_input_lsi} clustering_base.py hdbscan_clustering.py
$(srun_singularity) python3 hdbscan_clustering_lsi.py --inpath=${authors_10k_input_lsi} --outpath=${authors_10k_output_lsi}/hdbscan --savefile=${authors_10k_output_lsi}/hdbscan/selection_data.csv $(hdbscan_selection_grid)
${terms_10k_output_lsi}/hdbscan/selection_data.csv:selection.py ${terms_10k_input_lsi} clustering_base.py hdbscan_clustering.py
$(srun_singularity) python3 hdbscan_clustering_lsi.py --inpath=${terms_10k_input_lsi} --outpath=${terms_10k_output_lsi}/hdbscan --savefile=${terms_10k_output_lsi}/hdbscan/selection_data.csv $(hdbscan_selection_grid)
${authors_tf_10k_output_lsi}/hdbscan/selection_data.csv:clustering.py ${authors_tf_10k_input_lsi} clustering_base.py hdbscan_clustering.py
$(srun_singularity) python3 hdbscan_clustering_lsi.py --inpath=${authors_tf_10k_input_lsi} --outpath=${authors_tf_10k_output_lsi}/hdbscan --savefile=${authors_tf_10k_output_lsi}/hdbscan/selection_data.csv $(hdbscan_selection_grid)
add support for umap->hdbscan clustering method
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${authors_tf_10k_output_lsi}/umap_hdbscan/selection_data.csv:umap_hdbscan_clustering_lsi.py
$(srun_singularity) python3 umap_hdbscan_clustering_lsi.py --inpath=${authors_tf_10k_input_lsi} --outpath=${authors_tf_10k_output_lsi}/umap_hdbscan --savefile=${authors_tf_10k_output_lsi}/umap_hdbscan/selection_data.csv $(umap_hdbscan_selection_grid)
update clustering scripts
2021-08-03 21:55:02 +00:00
${terms_10k_output_lsi}/best_hdbscan.feather:${terms_10k_output_lsi}/hdbscan/selection_data.csv pick_best_clustering.py
$(srun_singularity) python3 pick_best_clustering.py $< $@ --min_clusters=50 --max_isolates=5000 --min_cluster_size=2
Refactor to make a decent api.
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update clustering scripts
2021-08-03 21:55:02 +00:00
${authors_tf_10k_output_lsi}/best_hdbscan.feather:${authors_tf_10k_output_lsi}/hdbscan/selection_data.csv pick_best_clustering.py
$(srun_singularity) python3 pick_best_clustering.py $< $@ --min_clusters=50 --max_isolates=5000 --min_cluster_size=2
Refactor to make a decent api.
2021-05-10 20:46:49 +00:00
add support for umap->hdbscan clustering method
2022-06-09 00:01:27 +00:00
${authors_tf_10k_output_lsi}/best_umap_hdbscan_2.feather:${authors_tf_10k_output_lsi}/umap_hdbscan/selection_data.csv pick_best_clustering.py
$(srun_singularity) python3 pick_best_clustering.py $< $@ --min_clusters=50 --max_isolates=5000 --min_cluster_size=2
best_umap_hdbscan.feather:${authors_tf_10k_output_lsi}/best_umap_hdbscan_2.feather
# {'lsi_dimensions': 700, 'outpath': '/gscratch/comdata/output/reddit_clustering/subreddit_comment_authors-tf_10k_LSI/umap_hdbscan', 'silhouette_score': 0.27616957, 'name': 'mcs-2_ms-5_cse-0.05_csm-leaf_nn-15_lr-1.0_md-0.1_lc-1_lsi-700', 'n_clusters': 547, 'n_isolates': 2093, 'silhouette_samples': '/gscratch/comdata/output/reddit_clustering/subreddit_comment_authors-tf_10k_LSI/umap_hdbscan/silhouette_samples-mcs-2_ms-5_cse-0.05_csm-leaf_nn-15_lr-1.0_md-0.1_lc-1_lsi-700.feather', 'min_cluster_size': 2, 'min_samples': 5, 'cluster_selection_epsilon': 0.05, 'cluster_selection_method': 'leaf', 'n_neighbors': 15, 'learning_rate': 1.0, 'min_dist': 0.1, 'local_connectivity': 1, 'n_isolates_str': '2093', 'n_isolates_0': False}
best_umap_grid=--min_cluster_sizes=[2] --min_samples=[5] --cluster_selection_epsilons=[0.05] --cluster_selection_methods=[leaf] --n_neighbors=[15] --learning_rate=[1] --min_dist=[0.1] --local_connectivity=[1] --save_step1=True
umap_hdbscan_coords:
python3 umap_hdbscan_clustering_lsi.py --inpath=${authors_tf_10k_input_lsi} --outpath=${authors_tf_10k_output_lsi}/umap_hdbscan --savefile=/dev/null ${best_umap_grid}
Refactor to make a decent api.
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clean_affinity:
rm -f ${authors_10k_output}/affinity/selection_data.csv
rm -f ${authors_tf_10k_output}/affinity/selection_data.csv
rm -f ${terms_10k_output}/affinity/selection_data.csv
clean_kmeans:
rm -f ${authors_10k_output}/kmeans/selection_data.csv
rm -f ${authors_tf_10k_output}/kmeans/selection_data.csv
rm -f ${terms_10k_output}/kmeans/selection_data.csv
clean_hdbscan:
rm -f ${authors_10k_output}/hdbscan/selection_data.csv
rm -f ${authors_tf_10k_output}/hdbscan/selection_data.csv
rm -f ${terms_10k_output}/hdbscan/selection_data.csv
clean_authors:
rm -f ${authors_10k_output}/affinity/selection_data.csv
rm -f ${authors_10k_output}/kmeans/selection_data.csv
rm -f ${authors_10k_output}/hdbscan/selection_data.csv
clean_authors_tf:
rm -f ${authors_tf_10k_output}/affinity/selection_data.csv
rm -f ${authors_tf_10k_output}/kmeans/selection_data.csv
rm -f ${authors_tf_10k_output}/hdbscan/selection_data.csv
clean_terms:
rm -f ${terms_10k_output}/affinity/selection_data.csv
rm -f ${terms_10k_output}/kmeans/selection_data.csv
rm -f ${terms_10k_output}/hdbscan/selection_data.csv
clean_lsi_affinity:
rm -f ${authors_10k_output_lsi}/affinity/selection_data.csv
rm -f ${authors_tf_10k_output_lsi}/affinity/selection_data.csv
rm -f ${terms_10k_output_lsi}/affinity/selection_data.csv
clean_lsi_kmeans:
rm -f ${authors_10k_output_lsi}/kmeans/selection_data.csv
rm -f ${authors_tf_10k_output_lsi}/kmeans/selection_data.csv
rm -f ${terms_10k_output_lsi}/kmeans/selection_data.csv
clean_lsi_hdbscan:
rm -f ${authors_10k_output_lsi}/hdbscan/selection_data.csv
rm -f ${authors_tf_10k_output_lsi}/hdbscan/selection_data.csv
rm -f ${terms_10k_output_lsi}/hdbscan/selection_data.csv
clean_lsi_authors:
rm -f ${authors_10k_output_lsi}/affinity/selection_data.csv
rm -f ${authors_10k_output_lsi}/kmeans/selection_data.csv
rm -f ${authors_10k_output_lsi}/hdbscan/selection_data.csv
clean_lsi_authors_tf:
rm -f ${authors_tf_10k_output_lsi}/affinity/selection_data.csv
rm -f ${authors_tf_10k_output_lsi}/kmeans/selection_data.csv
rm -f ${authors_tf_10k_output_lsi}/hdbscan/selection_data.csv
clean_lsi_terms:
rm -f ${terms_10k_output_lsi}/affinity/selection_data.csv
rm -f ${terms_10k_output_lsi}/kmeans/selection_data.csv
rm -f ${terms_10k_output_lsi}/hdbscan/selection_data.csv
clean: clean_affinity clean_kmeans clean_hdbscan
add support for umap->hdbscan clustering method
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PHONY: clean clean_affinity clean_kmeans clean_hdbscan clean_authors clean_authors_tf clean_terms terms_10k authors_10k authors_tf_10k best_umap_hdbscan.feather umap_hdbscan_coords
grid sweep selection for clustering hyperparameters
2021-04-20 18:33:54 +00:00
bugfixes in clustering selection.
2021-04-21 23:56:25 +00:00
# $(clustering_data)/subreddit_comment_authors_30k.feather/SUCCESS:selection.py $(similarity_data)/subreddit_comment_authors_30k.feather clustering.py
# $(srun_singularity) python3 selection.py $(similarity_data)/subreddit_comment_authors_30k.feather $(clustering_data)/subreddit_comment_authors_30k $(selection_grid) -J 10 && touch $(clustering_data)/subreddit_comment_authors_30k.feather/SUCCESS
grid sweep selection for clustering hyperparameters
2021-04-20 18:33:54 +00:00
bugfixes in clustering selection.
2021-04-21 23:56:25 +00:00
# $(clustering_data)/subreddit_comment_terms_30k.feather/SUCCESS:selection.py $(similarity_data)/subreddit_comment_terms_30k.feather clustering.py
# $(srun_singularity) python3 selection.py $(similarity_data)/subreddit_comment_terms_30k.feather $(clustering_data)/subreddit_comment_terms_30k $(selection_grid) -J 10 && touch $(clustering_data)/subreddit_comment_terms_30k.feather/SUCCESS
grid sweep selection for clustering hyperparameters
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bugfixes in clustering selection.
2021-04-21 23:56:25 +00:00
# $(clustering_data)/subreddit_authors-tf_similarities_30k.feather/SUCCESS:clustering.py $(similarity_data)/subreddit_comment_authors-tf_30k.feather
# $(srun_singularity) python3 selection.py $(similarity_data)/subreddit_comment_authors-tf_30k.feather $(clustering_data)/subreddit_comment_authors-tf_30k $(selection_grid) -J 8 && touch $(clustering_data)/subreddit_authors-tf_similarities_30k.feather/SUCCESS
grid sweep selection for clustering hyperparameters
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# $(clustering_data)/subreddit_comment_authors_100k.feather:clustering.py $(similarity_data)/subreddit_comment_authors_100k.feather
# $(srun_singularity) python3 clustering.py $(similarity_data)/subreddit_comment_authors_100k.feather $(clustering_data)/subreddit_comment_authors_100k.feather ---max_iter=400 --convergence_iter=15 --preference_quantile=0.85 --damping=0.85
# $(clustering_data)/comment_terms_100k.feather:clustering.py $(similarity_data)/subreddit_comment_terms_100k.feather
# $(srun_singularity) python3 clustering.py $(similarity_data)/comment_terms_10000.feather $(clustering_data)/comment_terms_10000.feather ---max_iter=1000 --convergence_iter=15 --preference_quantile=0.9 --damping=0.5
# $(clustering_data)/subreddit_comment_author-tf_100k.feather:clustering.py $(similarity_data)/subreddit_comment_author-tf_100k.feather
# $(srun_singularity) python3 clustering.py $(similarity_data)/subreddit_comment_author-tf_100k.parquet $(clustering_data)/subreddit_comment_author-tf_100k.feather ---max_iter=400 --convergence_iter=15 --preference_quantile=0.5 --damping=0.85
Changes from hyak.
2021-02-23 00:03:48 +00:00
# it's pretty difficult to get a result that isn't one huge megacluster. A sign that it's bullcrap
# /gscratch/comdata/output/reddit_clustering/wang_similarity_10000.feather:clustering.py /gscratch/comdata/output/reddit_similarity/wang_similarity_10000.feather
# ./clustering.py /gscratch/comdata/output/reddit_similarity/wang_similarity_10000.feather /gscratch/comdata/output/reddit_clustering/wang_similarity_10000.feather ---max_iter=400 --convergence_iter=15 --preference_quantile=0.9 --damping=0.85
grid sweep selection for clustering hyperparameters
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# /gscratch/comdata/output/reddit_tsne/subreddit_author_tf_similarities_10000.feather:fit_tsne.py /gscratch/comdata/output/reddit_similarity/subreddit_author_tf_similarities_10000.parquet
Changes from hyak.
2021-02-23 00:03:48 +00:00
grid sweep selection for clustering hyperparameters
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# start_spark_and_run.sh 1 fit_tsne.py --similarities=/gscratch/comdata/output/reddit_similarity/subreddit_author_tf_similarities_10000.parquet --output=/gscratch/comdata/output/reddit_tsne/subreddit_author_tf_similarities_10000.feather
Changes from hyak.
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# /gscratch/comdata/output/reddit_tsne/wang_similarity_10000.feather:fit_tsne.py /gscratch/comdata/output/reddit_similarity/wang_similarity_10000.feather
# python3 fit_tsne.py --similarities=/gscratch/comdata/output/reddit_similarity/wang_similarity_10000.feather --output=/gscratch/comdata/output/reddit_tsne/wang_similarity_10000.feather
grid sweep selection for clustering hyperparameters
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# /gscratch/comdata/output/reddit_tsne/comment_authors_10000.feather:clustering.py /gscratch/comdata/output/reddit_similarity/comment_authors_10000.feather
# # $srun_cdsc python3
# start_spark_and_run.sh 1 fit_tsne.py --similarities=/gscratch/comdata/output/reddit_similarity/comment_authors_10000.feather --output=/gscratch/comdata/output/reddit_tsne/comment_authors_10000.feather
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