def test_find_best_literal_from_variable_1(self):
df = pd.read_csv('tests/test_files/testfile_4.csv',
encoding='utf-8',
delimiter=';')
ds = BitmapDataset(0, df)
literal, foil = ds.find_best_literal_from_variable(1, 32, 32, list())
self.assertEqual("[[1, 0]]", str(literal))
def test_make_rule_2(self):
df = pd.read_csv('tests/test_files/mushroom.csv',
encoding='utf-8',
delimiter=';')
ds = BitmapDataset(0, df)
rule = list()
rule = ds.make_rule(rule)
self.assertEqual("", rule.to_string())
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_split_into_growset_pruneset_1(self):
df = pd.read_csv('tests/test_files/testfile_8.csv',
encoding='utf-8',
delimiter=';')
ds = BitmapDataset(1, df)
grow, prune = ds.split_into_growset_pruneset()
self.assertEqual(21, grow.length())
self.assertEqual(11, prune.length())
def test_find_best_literal_from_variable_3(self):
df = pd.read_csv('tests/test_files/testfile_4.csv',
encoding='utf-8',
delimiter=';')
ds = BitmapDataset(0, df)
old_rule = list()
old_rule.append([2, 4])
literal, foil = ds.find_best_literal_from_variable(1, 2, 4, old_rule)
self.assertEqual("[[1, 0]]", str(literal))
def test_grow_rule_4(self):
df = pd.read_csv('tests/test_files/mushroom.csv',
encoding='utf-8',
delimiter=';')
ds = BitmapDataset(0, df)
rule = ds.grow_rule_inductive()
rule = ds.make_rule(rule)
self.assertEqual("a5 in ['c', 'f', 'm', 'p', 's', 'y']",
rule.to_string())
def test_grow_rule_3(self):
df = pd.read_csv('tests/test_files/testfile_4.csv',
encoding='utf-8',
delimiter=';')
ds = BitmapDataset(0, df)
rule = ds.grow_rule_inductive()
rule = ds.make_rule(rule)
self.assertEqual("Sex in ['Female'] and Age in [4, 5, 6, 7, 8, 9]",
rule.to_string())
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_make_rules_from_iters_3(self):
df = pd.read_csv('tests/test_files/testfile_4.csv',
encoding='utf-8',
delimiter=';')
ds = BitmapDataset(0, df)
rule = list()
rule.append([1, 1])
ds.delete_covered(rule)
bitmap_rule = ds.make_rules_from_iters(rule)
self.assertEqual("BitMap([])", str(bitmap_rule))
def test_make_rules_from_iters_2(self):
df = pd.read_csv('tests/test_files/testfile_4.csv',
encoding='utf-8',
delimiter=';')
ds = BitmapDataset(0, df)
rule = list()
rule.append([1, 1])
bitmap_rule = ds.make_rules_from_iters(rule)
self.assertEqual(
"BitMap([8, 10, 11, 16, 17, 18, 19, 21, 24, 25, 26, 27, 28, 30, 40, 42, 43, 48, 49, 50, 51, "
"53, 56, 57, 58, 59, 60, 62])", str(bitmap_rule))
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_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_make_rule_1(self):
df = pd.read_csv('tests/test_files/mushroom.csv',
encoding='utf-8',
delimiter=';')
ds = BitmapDataset(0, df)
rule = list()
rule.append([0, 0])
rule.append([2, 3])
rule.append([5, 1])
rule.append([5, 0])
rule = ds.make_rule(rule)
self.assertEqual("a1 in ['x'] and a3 in ['g'] and a6 in ['a', 'f']",
rule.to_string())
def test_make_rules_from_iters_1(self):
df = pd.read_csv('tests/test_files/testfile_4.csv',
encoding='utf-8',
delimiter=';')
ds = BitmapDataset(0, df)
rule = list()
rule.append([0, 0])
bitmap_rule = ds.make_rules_from_iters(rule)
self.assertEqual(
"BitMap([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, "
"23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, "
"46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63])",
str(bitmap_rule))
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))
def test_create_bitmap_for_value_1(self):
df = pd.read_csv('tests/test_files/testfile_3.csv',
encoding='utf-8',
delimiter=';')
bitmap = BitmapDataset.create_bitmap_for_value('ClassOfSeat', '1st',
df)
self.assertEqual("BitMap([0, 4, 8, 12, 16, 20, 24, 28])", str(bitmap))
def test_constructor_neg_map_3(self):
df = pd.read_csv('tests/test_files/testfile_7_not_all_n.csv',
encoding='utf-8',
delimiter=';')
ds = BitmapDataset(1, df)
self.assertEqual(16, len(ds.neg_map))
self.assertEqual(
"BitMap([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15])",
str(ds.neg_map))
def test_constructor_pos_map_3(self):
df = pd.read_csv('tests/test_files/testfile_7_not_all_n.csv',
encoding='utf-8',
delimiter=';')
ds = BitmapDataset(1, df)
self.assertEqual(16, len(ds.pos_map))
self.assertEqual(
"BitMap([16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31])",
str(ds.pos_map))
def test_create_bitmap_for_value_3(self):
df = pd.read_csv('tests/test_files/testfile_4.csv',
encoding='utf-8',
delimiter=';')
bitmap = BitmapDataset.create_bitmap_for_value('ClassOfSeat', '1st',
df)
self.assertEqual(
"BitMap([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, "
"23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, "
"46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63])",
str(bitmap))
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_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_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_constructor_neg_map_2(self):
df = pd.read_csv('tests/test_files/testfile_10_all_p.csv',
encoding='utf-8',
delimiter=';')
ds = BitmapDataset(1, df)
self.assertEqual(0, len(ds.neg_map))
def test_constructor_number_of_unique_values_3(self):
df = pd.read_csv('tests/test_files/testfile_4.csv',
encoding='utf-8',
delimiter=';')
ds = BitmapDataset(1, df)
self.assertEqual(1, len(ds.col_unique_values[0]))
def test_constructor_number_of_columns_1(self):
df = pd.read_csv('tests/test_files/testfile_7_not_all_n.csv',
encoding='utf-8',
delimiter=';')
ds = BitmapDataset(1, df)
self.assertEqual(3, len(ds.col_names))
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_length_dataset_2_no_rows(self):
df = pd.read_csv('tests/test_files/testfile_11_no_rows.csv',
encoding='utf-8',
delimiter=';')
ds = BitmapDataset(1, df)
self.assertEqual(0, ds.length())
def test_length_dataset_4_all_n(self):
df = pd.read_csv('tests/test_files/testfile_6_all_n.csv',
encoding='utf-8',
delimiter=';')
ds = BitmapDataset(1, df)
self.assertEqual(32, ds.length())
def test_is_any_pos_example_true_all_p(self):
df = pd.read_csv('tests/test_files/testfile_10_all_p.csv',
encoding='utf-8',
delimiter=';')
ds = BitmapDataset(1, df)
self.assertEqual(True, ds.is_any_pos_example())