modeling.py 文件源码

def log_zero_inflated_poisson(x, pi, log_lambda, eps = 0.0):
    """
    Compute log pdf of a zero-inflated Poisson distribution with success probability pi and number of failures, r, until the experiment is stopped, at values x.

    A simple variation of Stirling's approximation is used: log x! = x log x - x.
    """

    pi = T.clip(pi, eps, 1.0 - eps)

    lambda_ = T.exp(log_lambda)
    lambda_ = T.clip(lambda_, eps, lambda_)

    y_0 = T.log(pi + (1 - pi) * T.exp(-lambda_))
    y_1 = T.log(1 - pi) + log_poisson(x, log_lambda, eps)

    y = T.eq(x, 0) * y_0 + T.gt(x, 0) * y_1

    return y