本文整理匯總了Python中dit.Distribution.from_distribution方法的典型用法代碼示例。如果您正苦於以下問題：Python Distribution.from_distribution方法的具體用法？Python Distribution.from_distribution怎麽用？Python Distribution.from_distribution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dit.Distribution的用法示例。
在下文中一共展示了Distribution.from_distribution方法的12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_LMPR_complexity3
# 需要導入模塊: from dit import Distribution [as 別名]
# 或者: from dit.Distribution import from_distribution [as 別名]
def test_LMPR_complexity3():
"""
Test that uniform Distirbutions have zero complexity.
"""
for n in range(2, 11):
d = Distribution.from_distribution(uniform(n))
yield assert_almost_equal, LMPR_complexity(d), 0示例2: test_disequilibrium4
# 需要導入模塊: from dit import Distribution [as 別名]
# 或者: from dit.Distribution import from_distribution [as 別名]
def test_disequilibrium4():
"""
Test that uniform Distributions have zero disequilibrium.
"""
for n in range(2, 11):
d = Distribution.from_distribution(uniform(n))
yield assert_almost_equal, disequilibrium(d), 0示例3: test_disequilibrium6
# 需要導入模塊: from dit import Distribution [as 別名]
# 或者: from dit.Distribution import from_distribution [as 別名]
def test_disequilibrium6(n):
"""
Test that peaked Distributions have non-zero disequilibrium.
"""
d = ScalarDistribution([1] + [0]*(n-1))
d.make_dense()
d = Distribution.from_distribution(d)
assert disequilibrium(d) >= 0示例4: test_LMPR_complexity5
# 需要導入模塊: from dit import Distribution [as 別名]
# 或者: from dit.Distribution import from_distribution [as 別名]
def test_LMPR_complexity5(n):
"""
Test that peaked Distributions have zero complexity.
"""
d = ScalarDistribution([1] + [0]*(n-1))
d.make_dense()
d = Distribution.from_distribution(d)
assert LMPR_complexity(d) == pytest.approx(0)示例5: test_disequilibrium6
# 需要導入模塊: from dit import Distribution [as 別名]
# 或者: from dit.Distribution import from_distribution [as 別名]
def test_disequilibrium6():
"""
Test that peaked Distributions have non-zero disequilibrium.
"""
for n in range(2, 11):
d = ScalarDistribution([1] + [0]*(n-1))
d.make_dense()
d = Distribution.from_distribution(d)
yield assert_greater, disequilibrium(d), 0示例6: test_LMPR_complexity4
# 需要導入模塊: from dit import Distribution [as 別名]
# 或者: from dit.Distribution import from_distribution [as 別名]
def test_LMPR_complexity4():
"""
Test that peaked Distributions have zero complexity.
"""
for n in range(2, 11):
d = ScalarDistribution([1] + [0]*(n-1))
d.make_dense()
d = Distribution.from_distribution(d)
yield assert_almost_equal, LMPR_complexity(d), 0示例7: test_H5
# 需要導入模塊: from dit import Distribution [as 別名]
# 或者: from dit.Distribution import from_distribution [as 別名]
def test_H5():
""" Test H for uniform distributions in various bases """
for i in range(2, 10):
d = D.from_distribution(uniform(i))
d.set_base(i)
yield assert_almost_equal, H(d), 1示例8: test_H4
# 需要導入模塊: from dit import Distribution [as 別名]
# 或者: from dit.Distribution import from_distribution [as 別名]
def test_H4():
""" Test H for uniform distributions """
for i in range(2, 10):
d = D.from_distribution(uniform(i))
yield assert_almost_equal, H(d), np.log2(i)示例9: test_H5
# 需要導入模塊: from dit import Distribution [as 別名]
# 或者: from dit.Distribution import from_distribution [as 別名]
def test_H5(i):
""" Test H for uniform distributions in various bases """
d = D.from_distribution(uniform(i))
d.set_base(i)
assert H(d) == pytest.approx(1)示例10: test_H4
# 需要導入模塊: from dit import Distribution [as 別名]
# 或者: from dit.Distribution import from_distribution [as 別名]
def test_H4(i):
""" Test H for uniform distributions """
d = D.from_distribution(uniform(i))
assert H(d) == pytest.approx(np.log2(i))示例11: test_LMPR_complexity3
# 需要導入模塊: from dit import Distribution [as 別名]
# 或者: from dit.Distribution import from_distribution [as 別名]
def test_LMPR_complexity3(n):
"""
Test that uniform Distirbutions have zero complexity.
"""
d = Distribution.from_distribution(uniform(n))
assert LMPR_complexity(d) == pytest.approx(0)示例12: test_disequilibrium4
# 需要導入模塊: from dit import Distribution [as 別名]
# 或者: from dit.Distribution import from_distribution [as 別名]
def test_disequilibrium4(n):
"""
Test that uniform Distributions have zero disequilibrium.
"""
d = Distribution.from_distribution(uniform(n))
assert disequilibrium(d) == pytest.approx(0)