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)