def testMetricsEffectiveFoundersBoichardB(self):
# Example taken from Boichard et al. (1997), Figure 2.
# Used to test calculation of effective founder number.
options = {}
options['messages'] = 'quiet'
options['pedfile'] = 'tests/boichard/boichard2b.ped'
options['pedname'] = 'Boichard Pedigree (Family 2 only)'
options['pedformat'] = 'asdg'
options['pedigree_is_renumbered'] = '1'
options['filetag'] = 'example2b'
example2b = pyp_newclasses.NewPedigree(options)
example2b.load()
fe = pyp_metrics.a_effective_founders_boichard(example2b)
self.assertEqual(round(2.0, 1), round(fe, 1))
def testMetricsEffectiveFoundersLacy(self):
# Example taken from Lacy (1989), Appendix A.
# Used to test calculation of effective population size.
options = {}
options['renumber'] = 0
options['messages'] = 'quiet'
options['pedfile'] = 'tests/lacy/lacy.ped'
options['pedformat'] = 'asd'
options['sepchar'] = ' '
options['pedigree_is_renumbered'] = '1'
example = pyp_newclasses.NewPedigree(options)
example.load()
fe = pyp_metrics.effective_founders_lacy(example)
self.assertEqual(2.91, round(fe, 2))
def testMetricsEffectiveAncestorsDefiniteBoichardC(self):
# Example taken from Boichard et al. (1997), Figure 2.
# Used to test calculation of effective ancestor number.
options = {}
options['messages'] = 'quiet'
options['pedfile'] = 'tests/boichard/boichard2.ped'
options['pedname'] = 'Boichard Pedigree (Family 1 and 2)'
options['pedformat'] = 'asdg'
options['pedigree_is_renumbered'] = '1'
options['filetag'] = 'example2'
example2 = pyp_newclasses.NewPedigree(options)
example2.load()
fa = pyp_metrics.a_effective_ancestors_definite(example2)
self.assertEqual(round(2.94, 2), round(fa, 2))
def testMetricsMinMaxF(self):
# Pedigree from van Noordwijck and Scharloo (1981) as presented
# in Hartl and Clark (1989), p. 242.
options = {}
options['renumber'] = 0
options['messages'] = 'quiet'
options['pedfile'] = 'tests/hartlandclark.ped'
options['pedformat'] = 'asd'
options['sepchar'] = ' '
options['pedigree_is_renumbered'] = '1'
options['form_nrm'] = '1'
example = pyp_newclasses.NewPedigree(options)
example.load()
#example.nrm.info()
high_coi, low_coi = pyp_metrics.min_max_f(example, n=5)
print high_coi
print low_coi
