# ---------------------------------------------------------------------------- # Copyright (c) 2013--, scikit-bio development team. # # Distributed under the terms of the Modified BSD License. # # The full license is in the file LICENSE.txt, distributed with this software. # ---------------------------------------------------------------------------- import itertools import unittest import numpy as np import numpy.testing as npt from skbio import Sequence, DNA from skbio.sequence.distance import hamming, kmer_distance class TestHamming(unittest.TestCase): def test_non_sequence(self): seq1 = Sequence('abc') seq2 = 'abc' with self.assertRaisesRegex(TypeError, r'seq1.*seq2.*Sequence.*str'): hamming(seq1, seq2) with self.assertRaisesRegex(TypeError, r'seq1.*seq2.*Sequence.*str'): hamming(seq2, seq1) def test_type_mismatch(self): seq1 = Sequence('ABC') seq2 = DNA('ACG') with self.assertRaisesRegex(TypeError, r'Sequence.*does not match.*DNA'): hamming(seq1, seq2) def test_length_mismatch(self): seq1 = Sequence('ABC') seq2 = Sequence('ABCD') with self.assertRaisesRegex(ValueError, r'equal length.*3 != 4'): hamming(seq1, seq2) def test_return_type(self): seq1 = Sequence('ABC') seq2 = Sequence('ABC') distance = hamming(seq1, seq2) self.assertIsInstance(distance, float) self.assertEqual(distance, 0.0) def test_minimum_distance(self): seq1 = Sequence('ABC') seq2 = Sequence('ABC') distance = hamming(seq1, seq2) self.assertEqual(distance, 0.0) def test_mid_range_distance(self): seq1 = Sequence("abcdefgh") seq2 = Sequence("1b23ef45") distance = hamming(seq1, seq2) self.assertEqual(distance, 5.0/8.0) def test_maximum_distance(self): seq1 = Sequence('ABC') seq2 = Sequence('CAB') distance = hamming(seq1, seq2) self.assertEqual(distance, 1.0) def test_empty_sequences(self): seq1 = Sequence('') seq2 = Sequence('') distance = hamming(seq1, seq2) npt.assert_equal(distance, np.nan) def test_single_character_sequences(self): seq1 = Sequence('a') seq2 = Sequence('b') self.assertEqual(hamming(seq1, seq1), 0.0) self.assertEqual(hamming(seq1, seq2), 1.0) def test_sequence_subclass(self): seq1 = DNA('ACG-T') seq2 = DNA('ACCTT') distance = hamming(seq1, seq2) self.assertEqual(distance, 2.0/5.0) def test_sequences_with_metadata(self): # test for #1254 seqs1 = [ Sequence("ACGT"), Sequence("ACGT", metadata={'id': 'abc'}), Sequence("ACGT", positional_metadata={'qual': range(4)}) ] seqs2 = [ Sequence("AAAA"), Sequence("AAAA", metadata={'id': 'def'}), Sequence("AAAA", positional_metadata={'qual': range(4, 8)}) ] for seqs in seqs1, seqs2: for seq1, seq2 in itertools.product(seqs, repeat=2): distance = hamming(seq1, seq2) self.assertEqual(distance, 0.0) for seq1, seq2 in itertools.product(seqs1, seqs2): distance = hamming(seq1, seq2) self.assertEqual(distance, 0.75) class TestKmerDistance(unittest.TestCase): def test_default_kwargs(self): seq1 = Sequence('AACCTAGCAATGGAT') seq2 = Sequence('CAGGCAGTTCTCACC') obs = kmer_distance(seq1, seq2, 3) exp = 0.9130434782608695 self.assertAlmostEqual(obs, exp) def test_nondefault_k(self): seq1 = Sequence('GCTTATGGAGAGAGA') seq2 = Sequence('CTCGAACTCCAGCCA') obs = kmer_distance(seq1, seq2, 2) exp = 0.7333333333333333 self.assertAlmostEqual(obs, exp) seq1 = Sequence('EADDECAEECDEACD') seq2 = Sequence('DCBCBADADABCCDA') obs = kmer_distance(seq1, seq2, 1) exp = 0.4 self.assertAlmostEqual(obs, exp) def test_overlap_false(self): seq1 = Sequence('CGTTATGTCTGTGAT') seq2 = Sequence('CTGAATCGGTAGTGT') obs = kmer_distance(seq1, seq2, 3, overlap=False) exp = 0.8888888888888888 self.assertAlmostEqual(obs, exp) def test_entirely_different_sequences(self): seq1 = Sequence('CCGTGGTCGTATAAG') seq2 = Sequence('CGCCTTCCACATCAG') obs = kmer_distance(seq1, seq2, 3) exp = 1.0 self.assertEqual(obs, exp) def test_same_sequence(self): seq1 = Sequence('CTGCGACAGTTGGTA') seq2 = Sequence('CTGCGACAGTTGGTA') obs = kmer_distance(seq1, seq2, 3) exp = 0.0 self.assertEqual(obs, exp) def test_differing_length_seqs(self): seq1 = Sequence('AGAAATCTGAGCAAGGATCA') seq2 = Sequence('TTAGTGCGTAATCCG') obs = kmer_distance(seq1, seq2, 3) exp = 0.9285714285714286 self.assertAlmostEqual(obs, exp) def test_with_sequence_subclass(self): seq1 = DNA('GATGGTACTGTAGGT') seq2 = DNA('AGGGTGAAGGTATCA') obs = kmer_distance(seq1, seq2, 3) exp = 0.8421052631578947 self.assertAlmostEqual(obs, exp) def test_with_metadata_sanity(self): seq1 = Sequence('AACCTAGCAATGGAT', metadata={'Name': 'Kestrel Gorlick'}, positional_metadata={'seq': list('ACTCAAGCTACGAAG')}) seq2 = Sequence('CAGGCAGTTCTCACC') obs = kmer_distance(seq1, seq2, 3) exp = 0.9130434782608695 self.assertAlmostEqual(obs, exp) def test_return_type(self): seq1 = Sequence('ATCG') seq2 = Sequence('ATCG') obs = kmer_distance(seq1, seq2, 3) self.assertIsInstance(obs, float) self.assertEqual(obs, 0.0) def test_empty_sequences(self): seq1 = Sequence('') seq2 = Sequence('') obs = kmer_distance(seq1, seq2, 3) npt.assert_equal(obs, np.nan) def test_one_empty_sequence(self): seq1 = Sequence('') seq2 = Sequence('CGGGCAGCTCCTACCTGCTA') obs = kmer_distance(seq1, seq2, 3) exp = 1.0 self.assertAlmostEqual(obs, exp) def test_no_kmers_found(self): seq1 = Sequence('ATCG') seq2 = Sequence('ACGT') obs = kmer_distance(seq1, seq2, 5) npt.assert_equal(obs, np.nan) def test_k_less_than_one_error(self): seq1 = Sequence('ATCG') seq2 = Sequence('ACTG') with self.assertRaisesRegex(ValueError, r'k must be greater than 0.'): kmer_distance(seq1, seq2, 0) def test_type_mismatch_error(self): seq1 = Sequence('ABC') seq2 = DNA('ATC') with self.assertRaisesRegex(TypeError, r"Type 'Sequence'.*type 'DNA'"): kmer_distance(seq1, seq2, 3) def test_non_sequence_error(self): seq1 = Sequence('ATCG') seq2 = 'ATCG' with self.assertRaisesRegex(TypeError, r"not 'str'"): kmer_distance(seq1, seq2, 3) if __name__ == "__main__": unittest.main()