Sampling with Probability

In Scallop, samplers share the same syntax as aggregators. They usually work with probabilistic provenances, but can also work without them. Here are some example samplers:

• top: get the $k$ facts with top probabilities
• categorical: treat the relation as a categorical distribution and sample from it
• uniform: treat the relation as a uniform distribution and sample from it

Let’s take top as an example. We can obtain the top ranked symbol by using the following rule:

rel symbols = {0.9::"+", 0.05::"-", 0.02::"3"}
rel top_symbol(s) = s := top<1>(s: symbols(s)) // 0.9::top_symbol("+")