def test_check_calculate_tf_idf_no_tf(self):
"""check tf_idf calculation no tf"""
clean_texts = []
tf_instance = TfIdfCalculator(clean_texts)
tf_instance.tf_values = []
tf_instance.idf_values = {
'this': math.log(3 / 2),
'is': math.log(3 / 3),
'an': math.log(3 / 1),
'example': math.log(3 / 1),
'of': math.log(3 / 1),
'test': math.log(3 / 2),
'text': math.log(3 / 2),
'contains': math.log(3 / 1),
'two': math.log(3 / 1),
'sentences': math.log(3 / 1),
'written': math.log(3 / 1),
'on': math.log(3 / 1),
'english': math.log(3 / 1),
'simple': math.log(3 / 1),
'third': math.log(3 / 1),
'one': math.log(3 / 1),
'there': math.log(3 / 1),
'no': math.log(3 / 1),
'much': math.log(3 / 1),
'sense': math.log(3 / 1),
}
expected_res = []
tf_instance.calculate()
self.assertCountEqual(tf_instance.tf_idf_values, expected_res)
def test_check_calculate_tf_idf_none_tf(self):
"""check tf_idf calculation none tf_none"""
clean_texts = []
tf_instance = TfIdfCalculator(clean_texts)
tf_instance.tf_values = None
expected_res = []
tf_instance.calculate()
self.assertCountEqual(tf_instance.tf_idf_values, expected_res)
def test_report_on_word_not_in_tfidf(self):
"""Check report_on none tf_idf"""
clean_texts = [
['this', 'is', 'an', 'example', 'of', 'test', 'text', 'it', 'contains', 'two', 'sentences'],
['das', 'ist', 'ein', 'testtext', 'es', 'ist', 'auf', 'deutsch', 'geschrieben']
]
tf_instance = TfIdfCalculator(clean_texts)
tf_instance.tf_idf_values = None
tf_instance.calculate()
res = tf_instance.report_on('wtf', 0)
exp_res = ()
self.assertEqual(res, exp_res)
def test_report_on_index_bigger(self):
"""Check report_on invalid doc index"""
clean_texts = [
['this', 'is', 'an', 'example', 'of', 'test', 'text', 'it', 'contains', 'two', 'sentences'],
['das', 'ist', 'ein', 'testtext', 'es', 'ist', 'auf', 'deutsch', 'geschrieben']
]
tf_instance = TfIdfCalculator(clean_texts)
tf_instance.tf_idf_values = [
{
'this': 10,
'that': 9,
'another': 5
}
]
tf_instance.calculate()
res = tf_instance.report_on('this', 2)
exp_res = ()
self.assertEqual(res, exp_res)
def test_check_calculate_tf_idf_no_idf(self):
"""check tf_idf calculation no idf"""
clean_texts = []
tf_instance = TfIdfCalculator(clean_texts)
tf_instance.tf_values = [{
'this': 1 / 11,
'is': 1 / 11,
'an': 1 / 11,
'example': 1 / 11,
'of': 1 / 11,
'test': 1 / 11,
'text': 2 / 11,
'contains': 1 / 11,
'two': 1 / 11,
'sentences': 1 / 11
}, {
'this': 1 / 12,
'is': 3 / 12,
'test': 1 / 12,
'text': 3 / 12,
'written': 1 / 12,
'on': 1 / 12,
'english': 1 / 12,
'simple': 1 / 12
}, {
'there': 1 / 5,
'is': 1 / 5,
'no': 1 / 5,
'much': 1 / 5,
'sense': 1 / 5
}]
tf_instance.idf_values = {}
expected_res = []
tf_instance.calculate()
self.assertCountEqual(tf_instance.tf_idf_values, expected_res)
def test_check_calculate_tf_idf_ideal(self):
"""check tf_idf calculation ideal case"""
clean_texts = []
tf_instance = TfIdfCalculator(clean_texts)
tf_instance.tf_values = [{
'this': 1 / 11,
'is': 1 / 11,
'an': 1 / 11,
'example': 1 / 11,
'of': 1 / 11,
'test': 1 / 11,
'text': 2 / 11,
'contains': 1 / 11,
'two': 1 / 11,
'sentences': 1 / 11
}, {
'this': 1 / 12,
'is': 3 / 12,
'test': 1 / 12,
'text': 3 / 12,
'written': 1 / 12,
'on': 1 / 12,
'english': 1 / 12,
'simple': 1 / 12
}, {
'there': 1 / 5,
'is': 1 / 5,
'no': 1 / 5,
'much': 1 / 5,
'sense': 1 / 5
}]
tf_instance.idf_values = {
'this': math.log(3 / 2),
'is': math.log(3 / 3),
'an': math.log(3 / 1),
'example': math.log(3 / 1),
'of': math.log(3 / 1),
'test': math.log(3 / 2),
'text': math.log(3 / 2),
'contains': math.log(3 / 1),
'two': math.log(3 / 1),
'sentences': math.log(3 / 1),
'written': math.log(3 / 1),
'on': math.log(3 / 1),
'english': math.log(3 / 1),
'simple': math.log(3 / 1),
'third': math.log(3 / 1),
'one': math.log(3 / 1),
'there': math.log(3 / 1),
'no': math.log(3 / 1),
'much': math.log(3 / 1),
'sense': math.log(3 / 1),
}
expected_res = [{
'this': (1 / 11) * math.log(3 / 2),
'is': (1 / 11) * math.log(3 / 3),
'an': (1 / 11) * math.log(3 / 1),
'example': (1 / 11) * math.log(3 / 1),
'of': (1 / 11) * math.log(3 / 1),
'test': (1 / 11) * math.log(3 / 2),
'text': (2 / 11) * math.log(3 / 2),
'contains': (1 / 11) * math.log(3 / 1),
'two': (1 / 11) * math.log(3 / 1),
'sentences': (1 / 11) * math.log(3 / 1)
}, {
'this': 1 / 12 * math.log(3 / 2),
'is': 3 / 12 * math.log(3 / 3),
'test': 1 / 12 * math.log(3 / 2),
'text': 3 / 12 * math.log(3 / 2),
'written': 1 / 12 * math.log(3 / 1),
'on': 1 / 12 * math.log(3 / 1),
'english': 1 / 12 * math.log(3 / 1),
'simple': 1 / 12 * math.log(3 / 1)
}, {
'there': 1 / 5 * math.log(3 / 1),
'is': 1 / 5 * math.log(3 / 3),
'no': 1 / 5 * math.log(3 / 1),
'much': 1 / 5 * math.log(3 / 1),
'sense': 1 / 5 * math.log(3 / 1)
}]
tf_instance.calculate()
self.assertCountEqual(tf_instance.tf_idf_values, expected_res)
from lab_4.main import TfIdfCalculator
clean_texts = [[
'this', 'is', 'an', 'example', 'of', 'test', 'text', 'it', 'contains',
'two', 'sentences'
],
[
'das', 'ist', 'ein', 'testtext', 'es', 'ist', 'auf',
'deutsch', 'geschrieben'
]]
tf_instance = TfIdfCalculator(clean_texts)
tf_instance.tf_idf_values = [{'this': 10, 'that': 9, 'another': 5}]
tf_instance.calculate()
res = tf_instance.report_on('this', 0)
print(res)