refactor clustring in object oriented style

[cdsc_reddit.git] / clustering / Makefile

diff --git a/clustering/Makefile b/clustering/Makefile
index 338f0a64da298294087c9f132f8e39a2b5f5e947..d09cfd9bce18059287fb991d16009f940c96ff4d 100644 (file)
--- a/clustering/Makefile
+++ b/clustering/Makefile
@@ -2,20 +2,41 @@
 srun_singularity=source /gscratch/comdata/users/nathante/cdsc_reddit/bin/activate && srun_singularity.sh
 similarity_data=/gscratch/comdata/output/reddit_similarity
 clustering_data=/gscratch/comdata/output/reddit_clustering
 srun_singularity=source /gscratch/comdata/users/nathante/cdsc_reddit/bin/activate && srun_singularity.sh
 similarity_data=/gscratch/comdata/output/reddit_similarity
 clustering_data=/gscratch/comdata/output/reddit_clustering

-selection_grid="--max_iter=3000 --convergence_iter=15,30,100 --damping=0.5,0.6,0.7,0.8,0.85,0.9,0.95,0.97,0.99, --preference_quantile=0.1,0.3,0.5,0.7,0.9"
+kmeans_selection_grid="--max_iter=3000 --n_init=[10] --n_clusters=[100,500,1000,1500,2000,2500,3000,2350,3500,3570,4000]"

 #selection_grid="--max_iter=3000 --convergence_iter=[15] --preference_quantile=[0.5] --damping=[0.99]"
 #selection_grid="--max_iter=3000 --convergence_iter=[15] --preference_quantile=[0.5] --damping=[0.99]"

-all:$(clustering_data)/subreddit_comment_authors_10k/selection_data.csv $(clustering_data)/subreddit_comment_authors-tf_10k/selection_data.csv $(clustering_data)/subreddit_comment_terms_10k/selection_data.csv
+all:$(clustering_data)/subreddit_comment_authors_10k/kmeans/selection_data.csv $(clustering_data)/subreddit_comment_authors-tf_10k/kmeans/selection_data.csv $(clustering_data)/subreddit_comment_terms_10k/kmeans/selection_data.csv $(clustering_data)/subreddit_comment_terms_10k/affinity/selection_data.csv $(clustering_data)/subreddit_comment_authors_10k/affinity/selection_data.csv $(clustering_data)/subreddit_comment_authors-tf_10k/affinity/selection_data.csv

 # $(clustering_data)/subreddit_comment_authors_30k.feather/SUCCESS $(clustering_data)/subreddit_authors-tf_similarities_30k.feather/SUCCESS
 # $(clustering_data)/subreddit_comment_terms_30k.feather/SUCCESS
 
 # $(clustering_data)/subreddit_comment_authors_30k.feather/SUCCESS $(clustering_data)/subreddit_authors-tf_similarities_30k.feather/SUCCESS
 # $(clustering_data)/subreddit_comment_terms_30k.feather/SUCCESS
 

-$(clustering_data)/subreddit_comment_authors_10k/selection_data.csv:selection.py $(similarity_data)/subreddit_comment_authors_10k.feather clustering.py
-       $(srun_singularity) python3 selection.py $(similarity_data)/subreddit_comment_authors_10k.feather $(clustering_data)/subreddit_comment_authors_10k $(clustering_data)/subreddit_comment_authors_10k/selection_data.csv $(selection_grid) -J 20
+$(clustering_data)/subreddit_comment_authors_10k/kmeans/selection_data.csv:selection.py $(similarity_data)/subreddit_comment_authors_10k.feather clustering.py
+       $(srun_singularity) python3 selection.py kmeans $(similarity_data)/subreddit_comment_authors_10k.feather $(clustering_data)/subreddit_comment_authors_10k/kmeans $(clustering_data)/subreddit_comment_authors_10k/kmeans/selection_data.csv $(kmeans_selection_grid)

 
 

-$(clustering_data)/subreddit_comment_terms_10k/selection_data.csv:selection.py $(similarity_data)/subreddit_comment_terms_10k.feather clustering.py
-       $(srun_singularity) python3 selection.py $(similarity_data)/subreddit_comment_terms_10k.feather $(clustering_data)/subreddit_comment_terms_10k  $(clustering_data)/subreddit_comment_terms_10k/selection_data.csv $(selection_grid) -J 20 
+$(clustering_data)/subreddit_comment_terms_10k/kmeans/selection_data.csv:selection.py $(similarity_data)/subreddit_comment_terms_10k.feather clustering.py
+       $(srun_singularity) python3 selection.py kmeans $(similarity_data)/subreddit_comment_terms_10k.feather $(clustering_data)/subreddit_comment_terms_10k/kmeans  $(clustering_data)/subreddit_comment_terms_10k/kmeans/selection_data.csv $(kmeans_selection_grid)

 
 

-$(clustering_data)/subreddit_comment_authors-tf_10k/selection_data.csv:clustering.py $(similarity_data)/subreddit_comment_authors-tf_10k.feather
-       $(srun_singularity) python3 selection.py $(similarity_data)/subreddit_comment_authors-tf_10k.feather $(clustering_data)/subreddit_comment_authors-tf_10k  $(clustering_data)/subreddit_comment_authors-tf_10k/selection_data.csv $(selection_grid) -J 20
+$(clustering_data)/subreddit_comment_authors-tf_10k/kmeans/selection_data.csv:clustering.py $(similarity_data)/subreddit_comment_authors-tf_10k.feather
+       $(srun_singularity) python3 selection.py kmeans $(similarity_data)/subreddit_comment_authors-tf_10k.feather $(clustering_data)/subreddit_comment_authors-tf_10k/kmeans  $(clustering_data)/subreddit_comment_authors-tf_10k/kmeans/selection_data.csv $(kmeans_selection_grid)
+
+
+affinity_selection_grid="--max_iter=3000 --convergence_iter=[15] --preference_quantile=[0.5] --damping=[0.99]"
+$(clustering_data)/subreddit_comment_authors_10k/affinity/selection_data.csv:selection.py $(similarity_data)/subreddit_comment_authors_10k.feather clustering.py
+       $(srun_singularity) python3 selection.py affinity $(similarity_data)/subreddit_comment_authors_10k.feather $(clustering_data)/subreddit_comment_authors_10k/affinity $(clustering_data)/subreddit_comment_authors_10k/affinity/selection_data.csv $(affinity_selection_grid) -J 20
+
+$(clustering_data)/subreddit_comment_terms_10k/affinity/selection_data.csv:selection.py $(similarity_data)/subreddit_comment_terms_10k.feather clustering.py
+       $(srun_singularity) python3 selection.py affinity $(similarity_data)/subreddit_comment_terms_10k.feather $(clustering_data)/subreddit_comment_terms_10k/affinity  $(clustering_data)/subreddit_comment_terms_10k/affinity/selection_data.csv $(affinity_selection_grid) -J 20 
+
+$(clustering_data)/subreddit_comment_authors-tf_10k/affinity/selection_data.csv:clustering.py $(similarity_data)/subreddit_comment_authors-tf_10k.feather
+       $(srun_singularity) python3 selection.py affinity $(similarity_data)/subreddit_comment_authors-tf_10k.feather $(clustering_data)/subreddit_comment_authors-tf_10k/affinity  $(clustering_data)/subreddit_comment_authors-tf_10k/affinity/selection_data.csv $(affinity_selection_grid) -J 20
+
+clean:
+       rm -f $(clustering_data)/subreddit_comment_authors-tf_10k/affinity/selection_data.csv
+       rm -f $(clustering_data)/subreddit_comment_authors_10k/affinity/selection_data.csv
+       rm -f $(clustering_data)/subreddit_comment_terms_10k/affinity/selection_data.csv
+       rm -f $(clustering_data)/subreddit_comment_authors-tf_10k/kmeans/selection_data.csv
+       rm -f $(clustering_data)/subreddit_comment_authors_10k/kmeans/selection_data.csv
+       rm -f $(clustering_data)/subreddit_comment_terms_10k/kmeans/selection_data.csv
+
+PHONY: clean

 
 # $(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
 
 # $(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