a99e4291db7d7f26bf3b689a37f158af80002b25,pymc3/distributions/discrete.py,ZeroInflatedBinomial,logp,#ZeroInflatedBinomial#Any#,691

Before Change

        return reshape_sampled(sampled, size, self.shape)

    def logp(self, value):
        return tt.switch(value > 0,
                         tt.log(self.psi) + self.bin.logp(value),
                         tt.log((1. - self.psi) + self.psi * tt.pow(1 - self.p, self.n)))

    def _repr_latex_(self, name=None, dist=None):
        if dist is None:
            dist = self

After Change

        return reshape_sampled(sampled, size, self.shape)

    def logp(self, value):
        psi = self.psi
        p = self.p
        n = self.n

        logp_val = tt.switch(value > 0,
                 logsumexp(tt.log(psi) + self.bin.logp(value)),
                 logsumexp(tt.log((1. - psi) + psi * tt.pow(1 - p, n))))

        return bound(logp_val.sum(),
            0 <= value, value <= n,
            0 <= psi, psi <= 1,
            0 <= p, p <= 1)

    def _repr_latex_(self, name=None, dist=None):
        if dist is None:
            dist = self
        n = dist.n

Instances