示例#1
0
 def test_mk(self):
     ver = sys.version_info
     if ver[0] == 2 and ver[1] == 6:
         warnings.warn('Python 2.6 detected. Skip testing MK method')
         pass
     else:
         from run_tests import is_numpy
         if is_numpy():
             p = SeqIO.index(TEST_ALIGN_FILE7[0][0], 'fasta', alphabet=IUPAC.IUPACUnambiguousDNA())
             pro_aln = AlignIO.read(TEST_ALIGN_FILE7[0][1], 'clustal', alphabet=IUPAC.protein)
             codon_aln = CodonAlign.build(pro_aln, p)
             self.assertAlmostEquals(round(CodonAlign.mktest([codon_aln[1:12], codon_aln[12:16], codon_aln[16:]]), 4), 0.0021, places=4)
         else:
             warnings.warn('Numpy not installed. Skip MK test.')
示例#2
0
 def test_mk(self):
     ver = sys.version_info
     if ver[0] == 2 and ver[1] == 6:
         warnings.warn('Python 2.6 detected. Skip testing MK method')
         pass
     else:
         from run_tests import is_numpy
         if is_numpy():
             p = SeqIO.index(TEST_ALIGN_FILE7[0][0],
                             'fasta',
                             alphabet=IUPAC.IUPACUnambiguousDNA())
             pro_aln = AlignIO.read(TEST_ALIGN_FILE7[0][1],
                                    'clustal',
                                    alphabet=IUPAC.protein)
             codon_aln = CodonAlign.build(pro_aln, p)
             self.assertAlmostEquals(round(
                 CodonAlign.mktest(
                     [codon_aln[1:12], codon_aln[12:16], codon_aln[16:]]),
                 4),
                                     0.0021,
                                     places=4)
         else:
             warnings.warn('Numpy not installed. Skip MK test.')
示例#3
0
        try:
            # New in scipy v0.11
            from scipy.optimize import minimize
            dN, dS = cal_dn_ds(codon_seq1, codon_seq2, method='ML')
            self.assertAlmostEqual(round(dN, 4), 0.0194, places=4)
            self.assertAlmostEqual(round(dS, 4), 0.0217, places=4)
        except ImportError:
            # TODO - Show a warning?
            pass


from run_tests import is_numpy
try:
    from math import lgamma  # New in Python 2.7
except ImportError:
    lgamma = None
if is_numpy() and lgamma:
    class Test_MK(unittest.TestCase):
        def test_mk(self):
            p = SeqIO.index(TEST_ALIGN_FILE7[0][0], 'fasta', alphabet=IUPAC.IUPACUnambiguousDNA())
            pro_aln = AlignIO.read(TEST_ALIGN_FILE7[0][1], 'clustal', alphabet=IUPAC.protein)
            codon_aln = codonalign.build(pro_aln, p)
            p.close()  # Close indexed FASTA file
            self.assertAlmostEqual(round(codonalign.mktest([codon_aln[1:12], codon_aln[12:16], codon_aln[16:]]), 4), 0.0021, places=4)


if __name__ == "__main__":
    runner = unittest.TextTestRunner(verbosity=2)
    unittest.main(testRunner=runner)
示例#4
0
        try:
            # New in scipy v0.11
            from scipy.optimize import minimize
            dN, dS = cal_dn_ds(codon_seq1, codon_seq2, method='ML')
            self.assertAlmostEqual(round(dN, 4), 0.0194, places=4)
            self.assertAlmostEqual(round(dS, 4), 0.0217, places=4)
        except ImportError:
            # TODO - Show a warning?
            pass


from run_tests import is_numpy
try:
    from math import lgamma  # New in Python 2.7
except ImportError:
    lgamma = None
if is_numpy() and lgamma:
    class Test_MK(unittest.TestCase):
        def test_mk(self):
            p = SeqIO.index(TEST_ALIGN_FILE7[0][0], 'fasta', alphabet=IUPAC.IUPACUnambiguousDNA())
            pro_aln = AlignIO.read(TEST_ALIGN_FILE7[0][1], 'clustal', alphabet=IUPAC.protein)
            codon_aln = codonalign.build(pro_aln, p)
            p.close()  # Close indexed FASTA file
            self.assertAlmostEqual(round(codonalign.mktest([codon_aln[1:12], codon_aln[12:16], codon_aln[16:]]), 4), 0.0021, places=4)


if __name__ == "__main__":
    runner = unittest.TextTestRunner(verbosity=2)
    unittest.main(testRunner=runner)