本文整理匯總了Python中cogent.core.profile.Profile.toOddsMatrix方法的典型用法代碼示例。如果您正苦於以下問題：Python Profile.toOddsMatrix方法的具體用法？Python Profile.toOddsMatrix怎麽用？Python Profile.toOddsMatrix使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類cogent.core.profile.Profile的用法示例。
在下文中一共展示了Profile.toOddsMatrix方法的2個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: test_toOddsMatrix
# 需要導入模塊: from cogent.core.profile import Profile [as 別名]
# 或者: from cogent.core.profile.Profile import toOddsMatrix [as 別名]
def test_toOddsMatrix(self):
"""toOddsMatrix: should work on valid data or raise an error
"""
p = Profile(
array(
[
[0.1, 0.3, 0.5, 0.1],
[0.25, 0.25, 0.25, 0.25],
[0.05, 0.8, 0.05, 0.1],
[0.7, 0.1, 0.1, 0.1],
[0.6, 0.15, 0.05, 0.2],
]
),
Alphabet="ACTG",
)
p_exp = Profile(
array([[0.4, 1.2, 2, 0.4], [1, 1, 1, 1], [0.2, 3.2, 0.2, 0.4], [2.8, 0.4, 0.4, 0.4], [2.4, 0.6, 0.2, 0.8]]),
Alphabet="ACTG",
)
self.assertEqual(p.toOddsMatrix().Data, p_exp.Data)
assert p.Alphabet is p.toOddsMatrix().Alphabet
self.assertEqual(p.toOddsMatrix([0.25, 0.25, 0.25, 0.25]).Data, p_exp.Data)
# fails if symbol_freqs has wrong size
self.assertRaises(ProfileError, p.toOddsMatrix, [0.25, 0.25, 0.25, 0.25, 0.25, 0.25])
self.assertRaises(ProfileError, self.zero_entry.toOddsMatrix, [0.1, 0.2, 0.3])
# works on empty profile
self.assertEqual(self.empty.toOddsMatrix().Data.tolist(), [[]])
# works with different input
self.assertEqual(self.zero_entry.toOddsMatrix().Data, array([[1.2, 0.8, 0, 2], [0, 0, 3.2, 0.8]]))
self.assertFloatEqual(
self.zero_entry.toOddsMatrix([0.1, 0.2, 0.3, 0.4]).Data, array([[3, 1, 0, 1.25], [0, 0, 2.667, 0.5]]), 1e-3
)
# fails when one of the background frequencies is 0
self.assertRaises(ProfileError, self.zero_entry.toOddsMatrix, [0.1, 0.2, 0.3, 0])示例2: ProfileTests
# 需要導入模塊: from cogent.core.profile import Profile [as 別名]
# 或者: from cogent.core.profile.Profile import toOddsMatrix [as 別名]
#.........這裏部分代碼省略.........
def test__div_(self):
"""__div__ and __truediv__: always true division b/c __future__.division
"""
p1 = Profile(array([[2, 3], [4, 5]]), "AB")
p2 = Profile(array([[1, 0], [4, 5]]), "AB") # Int 0
p3 = Profile(array([[1, 0.0], [4, 5]]), "AB") # Float 0.0
p4 = Profile(array([[1, 2], [8.0, 5]]), "AB") # Float 0.0
self.assertRaises(ProfileError, p1.__truediv__, p2)
# infinity in result data
self.assertRaises(ProfileError, p1.__div__, p3)
self.assertFloatEqual((p1.__div__(p4)).Data, array([[2, 1.5], [0.5, 1]]))
def test_distance(self):
"""distance: should return correct distance between the profiles
"""
p1 = Profile(array([[2, 4], [3, 1]]), "AB")
p2 = Profile(array([[4, 6], [5, 3]]), "AB")
p3 = Profile(array([[4, 6], [5, 3], [1, 1]]), "AB")
p4 = Profile(array([2, 2]), "AB")
p5 = Profile(array([2, 2, 2]), "AB")
p6 = Profile(array([[]]), "AB")
self.assertEqual(p1.distance(p2), 4)
self.assertEqual(p2.distance(p1), 4)
self.assertEqual(p1.distance(p4), sqrt(6))
self.assertEqual(p6.distance(p6), 0)
# Raises error when frames are not aligned
self.assertRaises(ProfileError, p1.distance, p3)
self.assertRaises(ProfileError, p1.distance, p5)
def test_toOddsMatrix(self):
"""toOddsMatrix: should work on valid data or raise an error
"""
p = Profile(
array(
[
[0.1, 0.3, 0.5, 0.1],
[0.25, 0.25, 0.25, 0.25],
[0.05, 0.8, 0.05, 0.1],
[0.7, 0.1, 0.1, 0.1],
[0.6, 0.15, 0.05, 0.2],
]
),
Alphabet="ACTG",
)
p_exp = Profile(
array([[0.4, 1.2, 2, 0.4], [1, 1, 1, 1], [0.2, 3.2, 0.2, 0.4], [2.8, 0.4, 0.4, 0.4], [2.4, 0.6, 0.2, 0.8]]),
Alphabet="ACTG",
)
self.assertEqual(p.toOddsMatrix().Data, p_exp.Data)
assert p.Alphabet is p.toOddsMatrix().Alphabet
self.assertEqual(p.toOddsMatrix([0.25, 0.25, 0.25, 0.25]).Data, p_exp.Data)
# fails if symbol_freqs has wrong size
self.assertRaises(ProfileError, p.toOddsMatrix, [0.25, 0.25, 0.25, 0.25, 0.25, 0.25])
self.assertRaises(ProfileError, self.zero_entry.toOddsMatrix, [0.1, 0.2, 0.3])
# works on empty profile
self.assertEqual(self.empty.toOddsMatrix().Data.tolist(), [[]])
# works with different input
self.assertEqual(self.zero_entry.toOddsMatrix().Data, array([[1.2, 0.8, 0, 2], [0, 0, 3.2, 0.8]]))
self.assertFloatEqual(
self.zero_entry.toOddsMatrix([0.1, 0.2, 0.3, 0.4]).Data, array([[3, 1, 0, 1.25], [0, 0, 2.667, 0.5]]), 1e-3
)