def test_run_fasta_checks(self): """ Properly returns dictionary of percentage for each check """ actual_fasta_report = run_fasta_checks(self.sample_fasta_fp, self.sample_mapping_fp) # All values should be zero expected_fasta_report = {'invalid_labels': '0.000', 'tree_subset': False, 'all_ids_found': False, 'same_seq_lens': False, 'barcodes_detected': '0.000', 'duplicate_labels': '0.000', 'invalid_seq_chars': '0.000', 'nosample_ids_map': '0.000', 'linkerprimers_detected': '0.000', 'tree_exact_match': False, 'barcodes_at_start': '0.000'} self.assertEqual(actual_fasta_report, expected_fasta_report)
def test_run_fasta_checks_with_invalid_data(self): """ Properly returns dictionary of percentage for each check """ actual_fasta_report = run_fasta_checks(self.sample_fasta_invalid_fp, self.sample_mapping_fp) # All values should be nonzero expected_fasta_report = {'invalid_labels': '0.500', 'tree_subset': False, 'all_ids_found': False, 'same_seq_lens': False, 'barcodes_detected': '0.250', 'duplicate_labels': '0.250', 'duplicate_ids': ['seq1'], 'invalid_seq_chars': '0.500', 'nosample_ids_map': '0.750', 'linkerprimers_detected': '0.250', 'tree_exact_match': False, 'barcodes_at_start': '0.000'} self.assertEqual(actual_fasta_report, expected_fasta_report)