'Compute the log probability for the counts in the bin, under the model.
Args:
bin_counts: array-like integer counts
Returns:
The log-probability under the Poisson models for each element of
bin_counts.'

def logp(self, bin_counts):

    k = tf.to_float(bin_counts)
    return (((k * self.logr) - tf.exp(self.logr)) - tf.lgamma((k + 1)))
