我想檢查scipy分布是離散的還是連續的。無論對象是來自命名分發的凍結分發對象，還是自定義rv_discrete或rv_continuous分發的實例，測試都應該有效。我的第一個想法是檢查變量的類型，但這似乎與連續與離散并不完全對應。例如，這里有四個分布：from scipy.stats import *import numpy as npdist_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 0dist_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))以下是它們的類型：type(dist_norm)Out[59]: scipy.stats._distn_infrastructure.rv_frozentype(dist_poisson)Out[60]: scipy.stats._distn_infrastructure.rv_frozentype(dist_contin)Out[61]: __main__.continuous_gentype(dist_discrete)Out[62]: scipy.stats._distn_infrastructure.rv_sample現在我已經is_discrete()通過嘗試訪問該pmf()方法（只有離散分布具有）實現了一個功能，但我不確定這是否是最干凈或最可靠的方法。有沒有更好的辦法？def is_discrete(dist): try: _ = dist.pmf(0) return True except: return False
1 回答
江戶川亂折騰
TA貢獻1851條經驗 獲得超5個贊
您可以使用isinstance內置函數來定義自定義檢查：
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)
這將導致：
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
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