def test_rule_count_p_n5(self):
df = pd.read_csv('tests/test_files/testfile_4.csv',
encoding='utf-8',
delimiter=';')
l = Literal('Sex', 'in', 'Female')
rule = Rule()
rule.add_literal(l)
ds = BitmapDataset(1, df)
ds.delete_covered(ds.unmake_rule(rule))
p, n = ds.count_p_n_rule(ds.unmake_rule(rule))
self.assertEqual(0, p)
self.assertEqual(0, n)
def test_delete_not_covered_4(self):
df = pd.read_csv('tests/test_files/testfile_4.csv',
encoding='utf-8',
delimiter=';')
l = Literal('Sex', 'in', 'Male')
rule = Rule()
rule.add_literal(l)
ds = BitmapDataset(1, df)
len_before = ds.length()
ds.delete_covered(ds.unmake_rule(rule))
self.assertEqual(36, ds.length())
ds.delete_not_covered(ds.unmake_rule(rule))
len_after = ds.length()
self.assertEqual(len_before - 64, len_after)
def test_unmake_rule_2(self):
df = pd.read_csv('tests/test_files/mushroom.csv',
encoding='utf-8',
delimiter=';')
ds = BitmapDataset(0, df)
rule = Rule()
rule = ds.unmake_rule(rule)
self.assertEqual("[]", str(rule))
def test_rule_count_p_n4(self):
df = pd.read_csv('tests/test_files/testfile_8.csv',
encoding='utf-8',
delimiter=';')
rule = Rule()
ds = BitmapDataset(1, df)
p, n = ds.count_p_n_rule(ds.unmake_rule(rule))
self.assertEqual(16, p)
self.assertEqual(16, n)
def test_delete_not_covered_1(self):
df = pd.read_csv('tests/test_files/testfile_8.csv',
encoding='utf-8',
delimiter=';')
rule = Rule()
ds = BitmapDataset(1, df)
len_before = ds.length()
ds.delete_not_covered(ds.unmake_rule(rule))
len_after = ds.length()
self.assertEqual(0, len_after)
def test_rule_count_p_n3(self):
df = pd.read_csv('tests/test_files/testfile_8.csv',
encoding='utf-8',
delimiter=';')
l = Literal('ClassOfSeat', 'in', '1st')
rule = Rule()
rule.add_literal(l)
ds = BitmapDataset(1, df)
p, n = ds.count_p_n_rule(ds.unmake_rule(rule))
self.assertEqual(4, p)
self.assertEqual(4, n)
def test_delete_not_covered_3(self):
df = pd.read_csv('tests/test_files/testfile_8.csv',
encoding='utf-8',
delimiter=';')
l = Literal('ClassOfSeat', 'in', '1st')
rule = Rule()
rule.add_literal(l)
ds = BitmapDataset(1, df)
len_before = ds.length()
ds.delete_not_covered(ds.unmake_rule(rule))
len_after = ds.length()
self.assertEqual(len_before - 24, len_after)
def test_prune_rule_2(self):
df = pd.read_csv('tests/test_files/mushroom.csv',
encoding='utf-8',
delimiter=';')
ds = BitmapDataset(0, df)
l = Literal('a5', 'in', ['c', 'f', 'm', 'p', 's', 'y'])
rule = Rule()
rule.add_literal(l)
rule = ds.unmake_rule(rule)
rule = ds.prune_rule(rule)
rule = ds.make_rule(rule)
self.assertEqual("a5 in ['c', 'f', 'm', 'p', 's', 'y']",
rule.to_string())
def test_prune_rule_1(self):
df = pd.read_csv('tests/test_files/testfile_3.csv',
encoding='utf-8',
delimiter=';')
l = Literal('Sex', 'in', 'Female')
l2 = Literal('Sex', 'in', 'Male')
rule = Rule()
rule.add_literal(l)
rule.add_literal(l2)
ds = BitmapDataset(1, df)
rule = ds.prune_rule(ds.unmake_rule(rule))
rule = ds.make_rule(rule)
self.assertEqual("", rule.to_string())
def test_unmake_rule_1(self):
df = pd.read_csv('tests/test_files/mushroom.csv',
encoding='utf-8',
delimiter=';')
ds = BitmapDataset(0, df)
rule = Rule()
l = Literal('a1', 'in', 'x')
l2 = Literal('a3', 'in', 'g')
l3 = Literal('a6', 'in', ['a', 'f'])
rule.add_literal(l)
rule.add_literal(l2)
rule.add_literal(l3)
rule = ds.unmake_rule(rule)
self.assertEqual("[[0, 0], [2, 3], [5, 0], [5, 1]]", str(rule))