def test_prob_vec_parameter(self):
f, s = MutableFloatParameter(.5), MutableFloatParameter(.5)
h = ProbabilityVectorParameter([f, s])
f.value = .4
self.assertAlmostEqual(s.value, 0.6, places=5)
self.assertRaises(ValueError, f.set_value, 1.1)
self.assertRaises(ValueError, f.set_value, -.1)
def test_change_kappa(self):
mp = MutableFloatParameter(2.0)
m = Kimura2ParameterModel(mp)
nc, ti, tv = 0.951679099289, 0.0239356129609, 0.0121926438748
assert_list_of_mat_eq(self, m.prob_matrices(0.05), [[[nc, tv, ti, tv], [tv, nc, tv, ti], [ti, tv, nc, tv], [tv, ti, tv, nc]]])
mp.value = 1.0
nc, ti, tv = 0.951630238774, 0.0161232537421, 0.0161232537421
assert_list_of_mat_eq(self, m.prob_matrices(0.05), [[[nc, tv, ti, tv], [tv, nc, tv, ti], [ti, tv, nc, tv], [tv, ti, tv, nc]]])
assert_list_of_mat_eq(self, m.prob_matrices(0.05), [[[nc, tv, ti, tv], [tv, nc, tv, ti], [ti, tv, nc, tv], [tv, ti, tv, nc]]])
def test_simple(self):
fp = FloatParameter(1.0)
self.assertRaises(AttributeError, fp.set_value, 3)
mfp = MutableFloatParameter(1.0)
self.assertEqual(mfp.value, 1.0)
mfp.value = 2.5
self.assertEqual(mfp.value, 2.5)
self.assertRaises(ValueError, mfp.set_value, "bogus")
x = ProbabilityVectorParameter([0.5, 0.5])
self.assertRaises(ValueError, ProbabilityVectorParameter, [1])
self.assertRaises(ValueError, ProbabilityVectorParameter, "hi")
self.assertRaises(ValueError, ProbabilityVectorParameter, [.7, .2])
self.assertRaises(ValueError, ProbabilityVectorParameter, [MutableFloatParameter(.5), .5])
