本文整理汇总了Python中dit.ScalarDistribution.make_dense方法的典型用法代码示例。如果您正苦于以下问题：Python ScalarDistribution.make_dense方法的具体用法？Python ScalarDistribution.make_dense怎么用？Python ScalarDistribution.make_dense使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类dit.ScalarDistribution的用法示例。
在下文中一共展示了ScalarDistribution.make_dense方法的6个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_disequilibrium6
# 需要导入模块: from dit import ScalarDistribution [as 别名]
# 或者: from dit.ScalarDistribution import make_dense [as 别名]
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2: test_LMPR_complexity5
# 需要导入模块: from dit import ScalarDistribution [as 别名]
# 或者: from dit.ScalarDistribution import make_dense [as 别名]
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3: test_disequilibrium6
# 需要导入模块: from dit import ScalarDistribution [as 别名]
# 或者: from dit.ScalarDistribution import make_dense [as 别名]
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4: test_LMPR_complexity4
# 需要导入模块: from dit import ScalarDistribution [as 别名]
# 或者: from dit.ScalarDistribution import make_dense [as 别名]
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5: test_is_approx_equal2
# 需要导入模块: from dit import ScalarDistribution [as 别名]
# 或者: from dit.ScalarDistribution import make_dense [as 别名]
def test_is_approx_equal2():
d1 = ScalarDistribution([1 / 2, 1 / 2, 0])
d1.make_dense()
d2 = ScalarDistribution([1 / 2, 0, 1 / 2])
d2.make_dense()
assert_false(d1.is_approx_equal(d2))示例6: test_del2
# 需要导入模块: from dit import ScalarDistribution [as 别名]
# 或者: from dit.ScalarDistribution import make_dense [as 别名]
def test_del2():
d = ScalarDistribution([1 / 2, 1 / 2])
d.make_dense()
del d[1]
d.normalize()
assert_almost_equal(d[0], 1)