62 lines
3.2 KiB
Python
62 lines
3.2 KiB
Python
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import pandas as pd
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import fire
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from pathlib import Path
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from similarities_helper import similarities, lsi_column_similarities
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from functools import partial
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def lsi_similarities(infile, term_colname, outfile, min_df=None, max_df=None, included_subreddits=None, topN=500, from_date=None, to_date=None, tfidf_colname='tf_idf',n_components=100,n_iter=5,random_state=1968,algorithm='arpack'):
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print(n_components,flush=True)
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simfunc = partial(lsi_column_similarities,n_components=n_components,n_iter=n_iter,random_state=random_state,algorithm=algorithm)
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return similarities(infile=infile, simfunc=simfunc, term_colname=term_colname, outfile=outfile, min_df=min_df, max_df=max_df, included_subreddits=included_subreddits, topN=topN, from_date=from_date, to_date=to_date, tfidf_colname=tfidf_colname)
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# change so that these take in an input as an optional argument (for speed, but also for idf).
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def term_lsi_similarities(outfile, min_df=None, max_df=None, included_subreddits=None, topN=500, from_date=None, to_date=None, n_components=300,n_iter=5,random_state=1968,algorithm='arpack'):
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return lsi_similarities('/gscratch/comdata/output/reddit_similarity/tfidf/comment_terms_100k.parquet',
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'term',
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outfile,
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min_df,
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max_df,
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included_subreddits,
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topN,
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from_date,
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to_date,
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n_components=n_components
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)
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def author_lsi_similarities(outfile, min_df=2, max_df=None, included_subreddits=None, topN=10000, from_date=None, to_date=None,n_components=300,n_iter=5,random_state=1968,algorithm='arpack'):
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return lsi_similarities('/gscratch/comdata/output/reddit_similarity/tfidf/comment_authors_100k.parquet',
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'author',
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outfile,
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min_df,
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max_df,
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included_subreddits,
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topN,
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from_date=from_date,
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to_date=to_date,
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n_components=n_components
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)
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def author_tf_similarities(outfile, min_df=2, max_df=None, included_subreddits=None, topN=10000, from_date=None, to_date=None,n_components=300,n_iter=5,random_state=1968,algorithm='arpack'):
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return lsi_similarities('/gscratch/comdata/output/reddit_similarity/tfidf/comment_authors_100k.parquet',
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'author',
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outfile,
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min_df,
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max_df,
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included_subreddits,
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topN,
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from_date=from_date,
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to_date=to_date,
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tfidf_colname='relative_tf',
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n_components=n_components
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)
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if __name__ == "__main__":
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fire.Fire({'term':term_lsi_similarities,
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'author':author_lsi_similarities,
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'author-tf':author_tf_similarities})
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