如何检查 scipy 分布是否离散？

Question

我想检查 scipy 分布是离散的还是连续的。无论对象是来自命名分布的冻结分布对象，还是自定义 rv_discrete 或 rv_continuous 分布的实例，测试都应该有效。

我的第一个想法是检查变量的类型，但这似乎并不完全对应连续与离散。例如，这里有四个分布：

from scipy.stats import *
import numpy as np

dist_norm = norm(10, 2)
dist_poisson = poisson(10)

class continuous_gen(rv_continuous):
    def _pdf(self, x, *args):
        if x >= 0 and x <= 1:
            return 1
        else:
            return 0
dist_contin = continuous_gen()

xk = np.arange(7)
pk = (0.1, 0.2, 0.3, 0.1, 0.1, 0.0, 0.2)
dist_discrete = rv_discrete(values=(xk, pk))

这是它们的类型：

type(dist_norm)
Out[59]: scipy.stats._distn_infrastructure.rv_frozen
type(dist_poisson)
Out[60]: scipy.stats._distn_infrastructure.rv_frozen
type(dist_contin)
Out[61]: __main__.continuous_gen
type(dist_discrete)
Out[62]: scipy.stats._distn_infrastructure.rv_sample

现在我已经通过尝试访问 pmf() 方法（只有离散分布有）实现了 is_discrete() 函数，但我不确定这是否是最干净或最可靠的方法.有没有更好的方法？

def is_discrete(dist):
    try:
        _ = dist.pmf(0)
        return True
    except:
        return False

Answer 1

您可以使用isinstance内置函数来定义自定义检查：

from scipy.stats import poisson, norm, rv_discrete, rv_continuous

def is_discrete(dist):

    if hasattr(dist, 'dist'):
        return isinstance(dist.dist, rv_discrete)
    else: return isinstance(dist, rv_discrete)

def is_continuous(dist):

    if hasattr(dist, 'dist'):
        return isinstance(dist.dist, rv_continuous)
    else: return isinstance(dist, rv_continuous)

这将导致：

class continuous_gen(rv_continuous):
    def _pdf(self, x, *args):
        if x >= 0 and x <= 1:
            return 1
        else:
            return 0
dist_contin = continuous_gen()
dist_poisson = poisson(10)

is_discrete(dist_contin)
#False
is_continuous(dist_contin)
#True
is_discrete(dist_poisson)
#True
is_continuous(dist_poisson)
#False

如何检查 scipy 分布是否离散？

how can I check whether a scipy distribution is discrete?

python

distribution

scipy