def test_soa_doc_freq(self):
data_csr_matrix = data_converter.DataConverter(
).convert_multi_docs2document_frequency_matrix(
labeled_documents=self.input_dict, n_jobs=5)
assert isinstance(data_csr_matrix, data_converter.DataCsrMatrix)
label2id_dict = data_csr_matrix.label2id_dict
csr_matrix_ = data_csr_matrix.csr_matrix_
n_docs_distribution = data_csr_matrix.n_docs_distribution
vocabulary = data_csr_matrix.vocabulary
scored_matrix_doc_freq = soa_python3.SOA().fit_transform(
X=csr_matrix_, unit_distribution=n_docs_distribution, verbose=True)
soa_scores_doc_freq = ScoredResultObject(
scored_matrix=scored_matrix_doc_freq,
label2id_dict=label2id_dict,
feature2id_dict=vocabulary).convert_score_matrix2score_record()
self.assertTrue(isinstance(soa_scores_doc_freq, list))
def test_soa_doc_freq(self):
data_csr_matrix = data_converter.DataConverter(
).labeledMultiDocs2DocFreqMatrix(labeled_documents=self.input_dict,
n_jobs=5)
assert isinstance(data_csr_matrix, data_converter.DataCsrMatrix)
label2id_dict = data_csr_matrix.label2id_dict
csr_matrix_ = data_csr_matrix.csr_matrix_
n_docs_distribution = data_csr_matrix.n_docs_distribution
vocabulary = data_csr_matrix.vocabulary
scored_matrix_doc_freq = soa_python3.SOA().fit_transform(
X=csr_matrix_, unit_distribution=n_docs_distribution, verbose=True)
soa_scores_doc_freq = ScoredResultObject(
scored_matrix=scored_matrix_doc_freq,
label2id_dict=label2id_dict,
feature2id_dict=vocabulary).ScoreMatrix2ScoreDictionary()
import pprint
print('doc freq based soa')
pprint.pprint(soa_scores_doc_freq)