def test_quality(self):
for _ in range(100):
one_prob = np.random.uniform(0.1, 0.9)
nrows = np.random.randint(1, 30)
ncols = np.random.randint(1, 8)
arr = np.random.uniform(0, 1, size=(nrows, ncols)) < one_prob
permutation = run_randomized_greedy_algorithm(arr)
target = get_total_gaps_in_rows(arr[:, permutation])
best_permutation = find_best_columns_permutation_bruteforce(arr)
best_target = get_total_gaps_in_rows(arr[:, best_permutation])
self.assertLessEqual((target - best_target), 0.3 * best_target + 1)
def test_all_ones(self):
"""
Test that the number of runs of a matrix of ones is equal to the number of rows.
"""
arr = np.ones((7, 3), dtype=bool)
gaps_count = get_total_gaps_in_rows(arr)
self.assertEqual(gaps_count, 0)
def test_all_zeros(self):
"""
Test that number of runs of a zero matrix is zero
"""
arr = np.zeros((2, 3), dtype=bool)
gaps_count = get_total_gaps_in_rows(arr)
self.assertEqual(gaps_count, 0)
def test_one_col(self):
"""
Test that the number of runs of a matrix with one col is equal to the number of ones
"""
rows_count = 100
arr = np.random.randint(0, 2, size=(rows_count, 1))
gaps_count = get_total_gaps_in_rows(arr)
self.assertEqual(gaps_count, 0)
def test_nontrivial_two(self):
arr = np.array([[1, 0, 0, 0],
[0, 0, 0, 1],
[0, 0, 0, 1]])
gaps_count = get_total_gaps_in_rows(arr)
self.assertEqual(gaps_count, 0)
