def test_find_subsets4(self):
kwc1 = KeywordCoordinate(0, 0, ['0'])
kwc2 = KeywordCoordinate(1, 1, ['1'])
kwc3 = KeywordCoordinate(2, 2, ['2'])
kwc4 = KeywordCoordinate(3, 3, ['3'])
superset = [kwc1, kwc2, kwc3, kwc4]
subsets = mt.find_subsets(superset, 4)
self.assertEqual(len(subsets), 1)
for subset in subsets:
self.assertEqual(len(subset), 4)
def get_all_subsets(self, data):
"""
Calculates all the possible subsets for the given data. Takes the set maximum length for subsets into account.
:param data: The data
:return: A list of all possible subsets
"""
start_time = time.time()
max_length = min(len(data), self.max_subset_size)
list_of_subsets = []
# nlp = en_core_web_lg.load()
j = 1
# query_docs = []
# for kw in self.query.keywords:
# doc_query = nlp(kw)
# query_docs.append(doc_query)
for index in range(max_length):
print('***** Longitud ', j)
j += 1
new_subsets = find_subsets(data, index + 1)
# temp = 1
for subset in new_subsets:
to_set = True
# simDict = {}
max = []
# Initialize max list to 0 for every query keyword
for i in range(0, len(self.query.keywords)):
# print('INDEX: ', i)
max.append(0)
for poi in subset:
# Transform POI keywords into NLP encoding
# element_string = ''
# for kw in poi.keywords:
# element_string = element_string + ' ' + kw
# doc = nlp(element_string)
# doc = self.df_poi_encoded.at[poi.name,'nlp_keywords_encoded']
sims = semantic_similarity(
self.query.keywords, poi.name,
self.df_poi_queries_similarities)
for i in range(0, len(self.query.keywords)):
# print('sims[i]=', sims[i], ' - max[i]=', max[i])
if sims[i] > max[i]:
max[i] = sims[i]
for i in range(0, len(max)):
to_set = to_set and max[i] >= self.SEMANTIC_THRESHOLD
# to_set = to_set and semantic_similarity(self.query, poi, nlp, self.SEMANTIC_THRESHOLD)
if to_set:
list_of_subsets.append(subset)
# print('subset ', subset)
# temp = temp + 1
self.number_of_subsets_after_semantic_filtering = len(
list_of_subsets)
print('# subsets: ', len(list_of_subsets))
finish_time = time.time()
self.time_4_build_subsets = finish_time - start_time
return list_of_subsets