def setUp(self):
self.v = Variables()
self.prp = PhrasesRequirementProcessor()
class TestPhrasesRequirementProcessor(TestCase):
def setUp(self):
self.v = Variables()
self.prp = PhrasesRequirementProcessor()
def it_generates_new_corpus_from_segmented_reports(self):
self.prp.generate_corpus_from_segmented_reports \
|should| equal_to((self.v.cut_of_segmented_reports, self.v.topics))
def it_aggregates_sentences_of_topics_on_segmented_reports(self):
self.prp.aggregate_topics_of_segmented_reports(self.v.cut_of_segmented_reports, self.v.topics) \
|should| equal_to(self.v.aggregated_topics)
def it_organizes_aggregated_topics_by_dictionary(self):
self.prp.organize_aggregated_topics_by_dict(self.v.aggregated_topics, self.v.topics) \
|should| equal_to(self.v.dict_of_sentences_by_topic)
def it_tags_unigrams_by_topic(self):
self.prp.tag_unigrams_by_topic(self.v.dict_of_sentences_by_topic) \
|should| equal_to(self.v.tagged_unigrams_by_topic)
def it_generates_nouns_unigrams_by_topic(self):
self.prp.generate_nouns_unigrams_by_topic(self.v.tagged_unigrams_by_topic) \
|should| equal_to(self.v.nouns_unigrams_by_topic)
def it_generates_none_unigrams_by_topic(self):
self.prp.generate_none_unigrams_by_topic(self.v.tagged_unigrams_by_topic) \
|should| equal_to(self.v.none_unigrams_by_topic)
def it_creates_a_dictionary_model_for_test_accuracy_of_tagger_by_topic(
self):
self.prp.create_a_dict_model_for_test_accuracy(self.v.tagged_unigrams_by_topic) \
|should| equal_to((self.v.dict_model_by_topic, self.v.tagger_accuracy_by_topic))
def it_creates_most_frequent_nouns_unigrams_by_topic(self):
self.prp.create_most_frequent_nouns_unigrams_by_topic(self.v.nouns_unigrams_by_topic) \
|should| equal_to(self.v.run_time_most_frequent_nouns_unigrams_by_topic)
def it_creates_wordtypes_of_none_unigrams_by_topic(self):
self.prp.create_wordtypes_of_none_unigrams_by_topic(self.v.none_unigrams_by_topic) \
|should| equal_to(self.v.run_time_wordtypes_of_none_unigrams_by_topic)
def setUp(self):
self.v = Variables()
self.prp = PhrasesRequirementProcessor()
class TestPhrasesRequirementProcessor(TestCase):
def setUp(self):
self.v = Variables()
self.prp = PhrasesRequirementProcessor()
def it_generates_new_corpus_from_segmented_reports(self):
self.prp.generate_corpus_from_segmented_reports | should | equal_to(
(self.v.cut_of_segmented_reports, self.v.topics)
)
def it_aggregates_sentences_of_topics_on_segmented_reports(self):
self.prp.aggregate_topics_of_segmented_reports(
self.v.cut_of_segmented_reports, self.v.topics
) | should | equal_to(self.v.aggregated_topics)
def it_organizes_aggregated_topics_by_dictionary(self):
self.prp.organize_aggregated_topics_by_dict(self.v.aggregated_topics, self.v.topics) | should | equal_to(
self.v.dict_of_sentences_by_topic
)
def it_tags_unigrams_by_topic(self):
self.prp.tag_unigrams_by_topic(self.v.dict_of_sentences_by_topic) | should | equal_to(
self.v.tagged_unigrams_by_topic
)
def it_generates_nouns_unigrams_by_topic(self):
self.prp.generate_nouns_unigrams_by_topic(self.v.tagged_unigrams_by_topic) | should | equal_to(
self.v.nouns_unigrams_by_topic
)
def it_generates_none_unigrams_by_topic(self):
self.prp.generate_none_unigrams_by_topic(self.v.tagged_unigrams_by_topic) | should | equal_to(
self.v.none_unigrams_by_topic
)
def it_creates_a_dictionary_model_for_test_accuracy_of_tagger_by_topic(self):
self.prp.create_a_dict_model_for_test_accuracy(self.v.tagged_unigrams_by_topic) | should | equal_to(
(self.v.dict_model_by_topic, self.v.tagger_accuracy_by_topic)
)
def it_creates_most_frequent_nouns_unigrams_by_topic(self):
self.prp.create_most_frequent_nouns_unigrams_by_topic(self.v.nouns_unigrams_by_topic) | should | equal_to(
self.v.run_time_most_frequent_nouns_unigrams_by_topic
)
def it_creates_wordtypes_of_none_unigrams_by_topic(self):
self.prp.create_wordtypes_of_none_unigrams_by_topic(self.v.none_unigrams_by_topic) | should | equal_to(
self.v.run_time_wordtypes_of_none_unigrams_by_topic
)
def detect_unigrams(self):
prp = PhrasesRequirementProcessor()
cut_of_segmented_reports, \
topics = prp.generate_corpus_from_segmented_reports
aggregated_topics = \
prp.aggregate_topics_of_segmented_reports(cut_of_segmented_reports,
topics)
dict_of_sentences_by_topic = \
prp.organize_aggregated_topics_by_dict(aggregated_topics,
topics)
tagged_unigrams_by_topic = prp.tag_unigrams_by_topic(dict_of_sentences_by_topic)
nouns_unigrams_by_topic = \
prp.generate_nouns_unigrams_by_topic(tagged_unigrams_by_topic)
none_unigrams_by_topic = \
prp.generate_none_unigrams_by_topic(tagged_unigrams_by_topic)
dict_model_by_topic, \
tagger_accuracy_by_topic = \
prp.create_a_dict_model_for_test_accuracy(tagged_unigrams_by_topic)
run_time_most_frequent_nouns_unigrams_by_topic = \
prp.create_most_frequent_nouns_unigrams_by_topic(nouns_unigrams_by_topic)
run_time_wordtypes_of_none_unigrams_by_topic = prp.create_wordtypes_of_none_unigrams_by_topic(none_unigrams_by_topic)
prp.create_unigram_set_of_nouns_and_nones(run_time_most_frequent_nouns_unigrams_by_topic, run_time_wordtypes_of_none_unigrams_by_topic)
prp.show_accuracy_by_topic(tagger_accuracy_by_topic)
prp.remove_pyc_and_zombie_files
def detect_unigrams(self):
prp = PhrasesRequirementProcessor()
cut_of_segmented_reports, \
topics = prp.generate_corpus_from_segmented_reports
aggregated_topics = \
prp.aggregate_topics_of_segmented_reports(cut_of_segmented_reports,
topics)
dict_of_sentences_by_topic = \
prp.organize_aggregated_topics_by_dict(aggregated_topics,
topics)
tagged_unigrams_by_topic = prp.tag_unigrams_by_topic(
dict_of_sentences_by_topic)
nouns_unigrams_by_topic = \
prp.generate_nouns_unigrams_by_topic(tagged_unigrams_by_topic)
none_unigrams_by_topic = \
prp.generate_none_unigrams_by_topic(tagged_unigrams_by_topic)
dict_model_by_topic, \
tagger_accuracy_by_topic = \
prp.create_a_dict_model_for_test_accuracy(tagged_unigrams_by_topic)
run_time_most_frequent_nouns_unigrams_by_topic = \
prp.create_most_frequent_nouns_unigrams_by_topic(nouns_unigrams_by_topic)
run_time_wordtypes_of_none_unigrams_by_topic = prp.create_wordtypes_of_none_unigrams_by_topic(
none_unigrams_by_topic)
prp.create_unigram_set_of_nouns_and_nones(
run_time_most_frequent_nouns_unigrams_by_topic,
run_time_wordtypes_of_none_unigrams_by_topic)
prp.show_accuracy_by_topic(tagger_accuracy_by_topic)
prp.remove_pyc_and_zombie_files
