def test_vector_suggestion_result_as_vector_destination(subject_index):
orig_vector = np.ones(len(subject_index), dtype=np.float32)
suggestions = VectorSuggestionResult(orig_vector)
destination = np.zeros(len(subject_index), dtype=np.float32)
assert not (destination == orig_vector).all() # destination is all zeros
vector = suggestions.as_vector(subject_index, destination=destination)
assert vector is destination
assert (destination == orig_vector).all() # destination now all ones
def test_vector_suggestions_enforce_score_range(subject_index):
orig_vector = np.array([-0.1, 0.0, 0.5, 1.0, 1.5], dtype=np.float32)
suggestions = VectorSuggestionResult(orig_vector)
vector = suggestions.as_vector(subject_index)
expected = np.array([0.0, 0.0, 0.5, 1.0, 1.0], dtype=np.float32)
assert (vector == expected).all()
def test_vector_suggestion_result_as_vector(subject_index):
orig_vector = np.ones(len(subject_index), dtype=np.float32)
suggestions = VectorSuggestionResult(orig_vector)
vector = suggestions.as_vector(subject_index)
assert (vector == orig_vector).all()