I’d like to save values of each prior in my model for each sample as a deterministic RV. At the moment, I’m doing it like this:

```
a = pm.Normal('a', mu=0., sd=1., testval=0.5.)
logp_a = pm.Deterministic('logp_a',
pm.Normal.dist(mu=0., sd=1.).logp(a))
```

Is there an easier way to do this so I don’t have type in the parameters of the distribution every time I want save the value of the log prior for a given RV?