mfreidank / arspy Goto Github PK
View Code? Open in Web Editor NEWAdaptive Rejection Sampling for Python
License: MIT License
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With the code:
import numpy as np
from numpy.random import RandomState
from arspy.ars import adaptive_rejection_sampling
logpdf = lambda x: -x**2/2
rs = RandomState()
x = np.array([adaptive_rejection_sampling(logpdf,-1,1,(-np.inf,np.inf),1,rs) for i in range(1000)])I get:
... \arspy\hull.py:204: RuntimeWarning: divide by zero encountered in log
return -log(abs(m)) + log(abs(exp(m * r + b - M) - exp(m * l + b - M))) + M
If I kill the warning, like:
with np.errstate(divide='ignore'):
return -log(abs(m)) + log(abs(exp(m * r + b - M) - exp(m * l + b - M))) + MThen things seem to work, but I'm not sure if the sampler remains statistically correct in such cases.
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