def test_is_diagonal_matrix_false(self): matrix = zeros([5, 5], dtype='4float64') for i in range(5): matrix[i][i] = (1.0, 0.0, 1.0, 1.0) matrix[0][3] = (1.0, 0.0, 1.0, 1.0) matrix[3][0] = (1.0, 0.0, 1.0, 1.0) self.assertFalse(is_diagonal_matrix(matrix))
def subpopulation_model_test(dist_mat, category, output_dir): """ Tests the subpopulation model in the profiles distance matrix Inputs: dist_mat: profiles distance matrix category: category used for generate the distance matrix output_dir: output directory """ # Write the test result output_fp = join(output_dir, 'subpopulation_model_test.txt') outf = open(output_fp, 'w') outf.write("Subpopulation model results:\n") outf.write("\tCategory used: %s\n" % category) outf.write("\tSubpopulation model test passed: ") # The subpopulation model is followed if the similarity matrix is # a diagonal matrix if is_diagonal_matrix(dist_mat): outf.write("Yes\n") else: outf.write("No\n") outf.close()
def test_is_diagonal_matrix_true(self): matrix = zeros([5, 5], dtype='4float64') for i in range(5): matrix[i][i] = (1.0, 0.0, 0.0, 0.0) self.assertTrue(is_diagonal_matrix(matrix))