private IEnumerable <Weighted <T1> > GetEnumerator <T1>(Uncertain <T1> fromsource)
{
while (true)
{
this.generation++;
fromsource.Accept(this);
yield return((Weighted <T1>) this.sample);
}
}
private IEnumerable <Weighted <T1> > GetEnumerator <T1>(Uncertain <T1> uncertain)
{
/// TODO: I am still building a caching mechanism!
var regenFrom = 0;
RandomPrimitive sampled = null;
var initstack = this.stack;
var sampler = new SingleSampler();
do
{
this.stack = initstack;
// Run the program.
uncertain.Accept(this);
//var samples = (from e in this.trace select e.Sample).ToArray();
//int count;
//if (!this.cache.TryGetValue(samples, out count))
//{
// count = 0;
//}
//else
//{
// count = count;
//}
//this.cache[samples] = count + 1;
// TODO: should we return 0 mass samples?
// 0 IS a reasonable weight if all
// one wants to do is know about a
// posterior - need to compute the score
// from the Weighted<T1> object rather
// than the trace.
var returnval = (Weighted <T1>) this.sample;
//if (returnval.Probability > 0)
// yield return returnval;
yield return(returnval);
var roll = Extensions.NextRandom();
var acceptance = Accept(trace, oldTrace, regenFrom);
if (this.generation > 1 && !(Math.Log(roll) < acceptance))
{
// rollback proposal
trace.Clear();
trace.AddRange(oldTrace);
}
Swap(ref trace, ref oldTrace);
if (oldTrace.Count > 0)
{
// A programmer induced dependence implies the trace can have
// more than one copy of any given Random Primitive
// only sample from the set of distinct RandomPrimitives
// to avoid oversampling any particular RandomPrimitive.
//var dict = new Dictionary<RandomPrimitive, IList<int>>();
//var pos = 0;
//foreach(var e in oldTrace)
//{
// IList<int> lst;
// if (! dict.TryGetValue(e.Erp, out lst))
// {
// lst = new List<int>();
// dict[e.Erp] = lst;
// }
// lst.Add(pos++);
//}
//regenFrom = (int)Math.Floor(Extensions.NextRandom() * dict.Keys.Count);
//sampled = dict.Keys.ElementAt(regenFrom);
var distinct = oldTrace.Select(e => e.Erp).Distinct().ToList();
regenFrom = (int)Math.Floor(Extensions.NextRandom() * distinct.Count);
sampled = distinct[regenFrom];
// force regeneration of this random primitive
// note we reset this to false in the
// Visit(RandomPrimitive) method
sampled.ForceRegen = true;
sampled.Accept(sampler);
//var key = (from e in this.trace select e.Sample).ToArray();
}
trace.Clear();
this.generation++;
} while (true);
}