def test_isValid(self):
"""Probs isValid should return True if it's a prob matrix"""
a = self.ab_pairs
m = Probs([0.5,0.5,1,0], a)
self.assertEqual(m.isValid(), True)
#fails if don't sum to 1
m = Probs([0.5, 0, 1, 0], a)
self.assertEqual(m.isValid(), False)
#fails if negative elements
m = Probs([1, -1, 0, 1], a)
self.assertEqual(m.isValid(), False)
def test_isValid(self):
"""Probs isValid should return True if it's a prob matrix"""
a = self.ab_pairs
m = Probs([0.5, 0.5, 1, 0], a)
self.assertEqual(m.isValid(), True)
#fails if don't sum to 1
m = Probs([0.5, 0, 1, 0], a)
self.assertEqual(m.isValid(), False)
#fails if negative elements
m = Probs([1, -1, 0, 1], a)
self.assertEqual(m.isValid(), False)
def test_toRates(self):
"""Probs toRates should return log of probs, optionally normalized"""
a = Alphabet('abc')**2
p = Probs([0.9,0.05,0.05,0.1,0.85,0.05,0.02,0.02,0.96], a)
assert p.isValid()
r = p.toRates()
assert isinstance(r, Rates)
assert r.isValid()
assert not r.isComplex()
self.assertEqual(r._data, logm(p._data))
r_norm = p.toRates(normalize=True)
self.assertFloatEqual(trace(r_norm._data), -1.0)
def test_toRates(self):
"""Probs toRates should return log of probs, optionally normalized"""
a = Alphabet('abc')**2
p = Probs([0.9, 0.05, 0.05, 0.1, 0.85, 0.05, 0.02, 0.02, 0.96], a)
assert p.isValid()
r = p.toRates()
assert isinstance(r, Rates)
assert r.isValid()
assert not r.isComplex()
self.assertEqual(r._data, logm(p._data))
r_norm = p.toRates(normalize=True)
self.assertFloatEqual(trace(r_norm._data), -1.0)
