def test_order_sets_chunk_count_descending(self):
for _ in range(10):
sets = make_random_sets()
_, composition_matrix = _get_ordered_chunks_and_composition_array(sets, sets_ordering='chunk count')
chunk_counts = composition_matrix.sum(1)
chunk_counts_descending = is_ascending(chunk_counts[::-1])
self.assertTrue(chunk_counts_descending)
def test_order_chunks_occurence_descending(self):
for _ in range(10):
sets = make_random_sets()
_, composition_matrix = _get_ordered_chunks_and_composition_array(sets, chunks_ordering='occurrence')
occurences = composition_matrix.sum(0)
occurences_descending = is_ascending(occurences[::-1])
self.assertTrue(occurences_descending)
def test_order_chunks_size_ascending(self):
for _ in range(10):
sets = make_random_sets()
chunks, _ = _get_ordered_chunks_and_composition_array(sets, chunks_ordering='size',
reverse_chunks_order=False)
chunk_sizes_ascending = is_ascending([len(chunk) for chunk in chunks])
self.assertTrue(chunk_sizes_ascending)
def test_order_sets_size_descending(self):
for _ in range(1):
sets = make_random_sets()
chunks, composition_matrix = _get_ordered_chunks_and_composition_array(sets, sets_ordering='size')
chunk_sizes = np.array([len(chunk) for chunk in chunks])
set_sizes = composition_matrix.dot(chunk_sizes.reshape((-1, 1))).flatten()
set_sizes_descending = is_ascending(set_sizes[::-1])
self.assertTrue(set_sizes_descending)
def test_order_sets_random(self):
done = False
while not done:
sets = make_random_sets(min_sets_count=9)
chunks, composition_matrix = get_chunks_and_composition_array(sets)
if len(chunks) == 1:
continue
representations_set = set()
for i in range(10):
_, composition_matrix = _get_ordered_chunks_and_composition_array(sets, sets_ordering='random')
representations_set.add(str(composition_matrix))
self.assertGreater(len(representations_set), 1)
done = True
