def test_vis_debug_matcher_dt_valid_1(self):
A = read_csv_metadata(path_a)
B = read_csv_metadata(path_b, key='ID')
C = read_csv_metadata(path_c, ltable=A, rtable=B)
labels = [0] * 7
labels.extend([1] * 8)
C['labels'] = labels
feature_table = get_features_for_matching(A, B)
feature_vectors = extract_feature_vecs(C,
feature_table=feature_table,
attrs_after='labels')
dt = DTMatcher()
train_test = mu.split_train_test(feature_vectors)
train = train_test['train']
test = train_test['test']
_vis_debug_dt(
dt,
train,
test,
exclude_attrs=['_id', 'ltable_ID', 'rtable_ID', 'labels'],
target_attr='labels',
show_window=False)
def test_vis_debug_matcher_dt_invalid_tar_attr(self):
_vis_debug_dt(
DTMatcher(),
pd.DataFrame(),
pd.DataFrame(),
exclude_attrs=['_id', 'ltable_ID', 'rtable_ID', 'labels'],
target_attr=None,
show_window=False)
def test_vis_debug_matcher_dt_tar_attr_notin_train(self):
A = read_csv_metadata(path_a)
B = read_csv_metadata(path_b, key='ID')
C = read_csv_metadata(path_c, ltable=A, rtable=B)
labels = [0] * 7
labels.extend([1] * 8)
C['labels'] = labels
feature_table = get_features_for_matching(A, B)
feature_vectors = extract_feature_vecs(C, feature_table=feature_table,
attrs_after='labels')
dt = DTMatcher()
train_test = mu.split_train_test(feature_vectors)
train = train_test['train']
test = train_test['test']
_vis_debug_dt(dt, train, test,
exclude_attrs=['_id', 'ltable_ID', 'rtable_ID', 'labels'],
target_attr='labels1', show_window=False)
def test_vis_debug_matcher_dt_invalid_tar_attr(self):
_vis_debug_dt(DTMatcher(), pd.DataFrame(), pd.DataFrame(),
exclude_attrs=['_id', 'ltable_ID', 'rtable_ID', 'labels'],
target_attr=None, show_window=False)
