parser = argparse.ArgumentParser( description='Run all queries on the inverted index.') parser.add_argument( '--new', default=True, help='If True then build a new index from scratch. If False then attempt to' ' reuse existing index') parser.add_argument( '--sim', default='BM25', help='The type of similarity to use. Should be "TF" or "TFIDF" or "BM25"') args = parser.parse_args() index = InvertedIndex(Preprocessor()) index.index_directory(os.path.join('gov', 'documents'), use_stored_index=(not args.new)) sim_name_to_class = { 'TF': TF_Similarity, 'TFIDF': TFIDF_Similarity, 'BM25': BM25_Similarity } sim = sim_name_to_class[args.sim] index.set_similarity(sim) print(f'Setting similarity to {sim.__name__}') print() print('Index ready.') topics_file = os.path.join('gov', 'topics', 'gov.topics')
import argparse import os from inverted_index import InvertedIndex from preprocessor import Preprocessor from similarity_measures import TF_Similarity, TFIDF_Similarity, BM25_Similarity parser = argparse.ArgumentParser(description='Run all queries on the inverted index.') parser.add_argument('--new', default=True, help='If True then build a new index from scratch. If False then attempt to' ' reuse existing index') parser.add_argument('--sim', default='BM25', help='The type of similarity to use. Should be "TF" or "TFIDF" or "BM25') args = parser.parse_args() index = InvertedIndex(Preprocessor()) index.index_directory(os.path.join('gov', 'documents'), use_stored_index=True) sim_name_to_class = {'TF': TF_Similarity, 'TFIDF': TFIDF_Similarity, 'BM25': BM25_Similarity} sim = sim_name_to_class[args.sim] index.set_similarity(sim) print(f'Setting similarity to {sim.__name__}') print() print('Index ready.') topics_file = os.path.join('gov', 'topics', 'gov.topics') runs_file = os.path.join('runs', 'retrieved.runs')