def test_transform():
trans = tf.ThesaurusFeatureTransformation(None, None, None, None)
trans.mapping_ = {
'a': coo_matrix([[1]]),
'b': coo_matrix([[2]]),
'c': coo_matrix([[3]])
}
res = trans.transform(['c', 'c', 'a'])
assert (res.toarray() == array([[3], [3], [1]])).all()
def test_empty_relation(full_graph):
trans = tf.ThesaurusFeatureTransformation(
full_graph,
set(t.extract_by_type_uri(full_graph, c.test_type_concept)),
set(),
"",
)
trans.fit([], [])
features = trans.transform(['empty'])
assert features.shape == (1, 1)
assert features.getnnz() == 0
def test_transform_unknown():
trans = tf.ThesaurusFeatureTransformation(
None,
None,
None,
None,
)
feature_dim = 12
trans.feature_dim_ = feature_dim
known = csr_matrix(([1], ([0], [4])), shape=(1, feature_dim))
trans.mapping_ = {'key': known}
random_results = trans.transform(
['some random stuff edsfysdfhjsedf', 'key'])
assert random_results.shape == (2, feature_dim)
assert random_results.getrow(0).getnnz() == 0
assert random_results.getrow(1).getnnz() == 1
def test_fit(full_graph):
concepts = set(t.extract_by_type_uri(full_graph, c.test_type_concept))
thesauri = set(t.extract_by_type_uri(full_graph, c.test_type_thesaurus))
trans = tf.ThesaurusFeatureTransformation(full_graph, concepts, thesauri,
SKOS.broader)
trans.fit()
mapping = trans.mapping_
assert len(mapping) == len(c.test_concepts)
for x in mapping.values():
assert x.shape[1] == 6
# Can not test positions because retrieval from graph is not deterministic.
# Therefore, test non zero entries only.
assert mapping[c.test_concept_uri_0_0].getnnz() == 1
assert mapping[c.test_concept_uri_01_0].getnnz() == 2
assert mapping[c.test_concept_uri_01_00].getnnz() == 2
assert mapping[c.test_concept_uri_10_0].getnnz() == 2
assert mapping[c.test_concept_uri_10_1].getnnz() == 2
assert mapping[c.test_concept_uri_100_0].getnnz() == 3
assert mapping[c.test_concept_uri_100_00].getnnz() == 3
assert mapping[c.test_concept_uri_100_01].getnnz() == 3
assert mapping[c.test_concept_uri_100_02].getnnz() == 3
def test_unfitted_raises():
feat = tf.ThesaurusFeatureTransformation(None, None, None, None)
with pytest.raises(NotFittedError):
feat.transform([])
