本文整理匯總了Python中LOTlib.Hypotheses.LOTHypothesis.LOTHypothesis.compute_likelihood方法的典型用法代碼示例。如果您正苦於以下問題:Python LOTHypothesis.compute_likelihood方法的具體用法?Python LOTHypothesis.compute_likelihood怎麽用?Python LOTHypothesis.compute_likelihood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LOTlib.Hypotheses.LOTHypothesis.LOTHypothesis
的用法示例。
在下文中一共展示了LOTHypothesis.compute_likelihood方法的1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: to_maximize
# 需要導入模塊: from LOTlib.Hypotheses.LOTHypothesis import LOTHypothesis [as 別名]
# 或者: from LOTlib.Hypotheses.LOTHypothesis.LOTHypothesis import compute_likelihood [as 別名]
def to_maximize(fit_params):
self.parameters = fit_params.tolist() # set these
# And return the original likelihood, which by get_function_responses above uses this
constant_prior = sum(map(lambda x: normlogpdf(x,0.0,self.constant_sd), self.parameters))
return -(LOTHypothesis.compute_likelihood(self, data) + constant_prior)