def test_generate_summary(self):
topics = {
'PUP1A': [
Document('TST_ENG_20190101.0001'),
Document('TST_ENG_20190101.0002'),
Document('TST20190201.0001'),
Document('TST20190201.0002')
],
'WAR2A': [
Document('TST_ENG_20190301.0001'),
Document('TST_ENG_20190301.0002'),
Document('TST20190401.0001'),
Document('TST20190401.0002')
]
}
WordMap.create_mapping()
vec = Vectors()
vec.create_freq_vectors(topics)
idf = MeadSummaryGenerator(self.doc_list, MeadContentSelector(),
self.args).get_idf_array()
for topic_id, documents in topics.items():
summarizer = MeadSummaryGenerator(documents, MeadContentSelector(),
self.args)
summary = summarizer.generate_summary(idf)
self.assertIsNot(summary, None)
def load_documents_for_topics(topic_soup):
"""
Load documents for each topic
:param topic_soup:
:return:
"""
topics = {}
for topic in topic_soup.find_all('topic'):
documents = load_documents(topic)
topics[topic['id']] = documents
# At this point, all docs have been loaded and all unique words are stored in WordMap set
# Need to trigger creation of mapping and of vectors
WordMap.create_mapping()
vec = Vectors()
vec.create_freq_vectors(topics) # do we need to have this here if we don't run mead based content selection
vec.create_term_doc_freq(topics)
return topics
def test_mead_summary_length(self):
"""
Test length of summary is less than 100 words
:return:
"""
topics = {
'PUP1A': [
Document('TST_ENG_20190101.0001'),
Document('TST_ENG_20190101.0002'),
Document('TST20190201.0001'),
Document('TST20190201.0002')
],
'WAR2A': [
Document('TST_ENG_20190301.0001'),
Document('TST_ENG_20190301.0002'),
Document('TST20190401.0001'),
Document('TST20190401.0002')
]
}
WordMap.create_mapping()
vec = Vectors()
vec.create_freq_vectors(topics)
idf = MeadSummaryGenerator(self.doc_list, MeadContentSelector(),
self.args).get_idf_array()
max_length = 100
for topic_id, documents in topics.items():
generator = MeadSummaryGenerator(documents, MeadContentSelector(),
self.args)
generator.select_content(idf)
generator.order_information()
realized_content = generator.realize_content()
realized_content = [
w for w in realized_content.split(" ") if not " "
]
content_length = len(realized_content)
self.assertLessEqual(content_length, max_length)