private TestEval eval(List <int> estimates, int vocabSize, string descr)
{
TestEval res = new TestEval {
Descr = descr, VocabSize = vocabSize, RunCount = estimates.Count
};
int sum = 0;
int diffSum = 0;
foreach (int est in estimates)
{
sum += est;
int diff = Math.Abs(vocabSize - est);
diffSum += diff;
if (diff <= 500)
{
++res.Range0500;
}
else if (diff < 1000)
{
++res.Range1000;
}
else if (diff < 1500)
{
++res.Range1500;
}
else if (diff < 2000)
{
++res.Range2000;
}
else if (diff < 2500)
{
++res.Range2500;
}
else if (diff < 3000)
{
++res.Range3000;
}
else if (diff < 3500)
{
++res.Range3500;
}
else if (diff < 4000)
{
++res.Range4000;
}
else if (diff < 4500)
{
++res.Range4500;
}
else
{
++res.RangeGreater;
}
}
res.AvgEstimate = sum / estimates.Count;
res.AvgDiff = diffSum / estimates.Count;
return(res);
}
public override void Process()
{
// Split rank-based sim with points denser in first part
simSplitRank();
// Split prop sim with points denser in first part
simSplitProp();
// Old.
List <int> estimates = new List <int>();
genPointsLinear(0, dictSize, points);
// Muchos FlatA trials: proportional estimate with linear points
estimates.Clear();
for (int i = 0; i != 1000; ++i)
{
genSubject(propsFlatA);
estimates.Add(simProp(points, dictSize, 0));
}
TestEval evalFlatAProp = eval(estimates, vocabSize, "FlatA, proportion, linear");
// Muchos SkewA trials: proportional estimate with linear points
estimates.Clear();
for (int i = 0; i != 1000; ++i)
{
genSubject(propsSkewA);
estimates.Add(simProp(points, dictSize, 0));
}
TestEval eee = eval(estimates, vocabSize, "SkewA, proportion, linear");
// Muchos SkewA trials: proportional estimate with linear points
estimates.Clear();
for (int i = 0; i != 1000; ++i)
{
genSubject(propsSkewB);
estimates.Add(simProp(points, dictSize, 0));
}
TestEval evalSkewAProp = eval(estimates, vocabSize, "SkewA, proportion, linear");
// Muchos SkewB trials: proportional estimate with linear points
estimates.Clear();
for (int i = 0; i != 1000; ++i)
{
genSubject(propsSkewC);
estimates.Add(simProp(points, dictSize, 0));
}
TestEval evalSkewBProp = eval(estimates, vocabSize, "SkewB, proportion, linear");
}
private void simSplitProp()
{
genPointsLinHalf(0, 16500, pointsX);
genPointsLinHalf(0, 33500, pointsY);
List <int> estimates = new List <int>();
for (int i = 0; i != 1000; ++i)
{
genSubject(propsFlatA);
int estX = simProp(pointsX, 16500, 0);
int estY = simProp(pointsY, 33500, 16500);
estimates.Add(estX + estY);
}
TestEval srFlatA = eval(estimates, vocabSize, "");
estimates.Clear();
for (int i = 0; i != 1000; ++i)
{
genSubject(propsSkewA);
int estX = simProp(pointsX, 16500, 0);
int estY = simProp(pointsY, 33500, 16500);
estimates.Add(estX + estY);
}
TestEval srSkewA = eval(estimates, vocabSize, "");
estimates.Clear();
for (int i = 0; i != 1000; ++i)
{
genSubject(propsSkewB);
int estX = simProp(pointsX, 16500, 0);
int estY = simProp(pointsY, 33500, 16500);
estimates.Add(estX + estY);
}
TestEval srSkewB = eval(estimates, vocabSize, "");
estimates.Clear();
for (int i = 0; i != 1000; ++i)
{
genSubject(propsSkewC);
int estX = simProp(pointsX, 16500, 0);
int estY = simProp(pointsY, 33500, 16500);
estimates.Add(estX + estY);
}
TestEval srSkewC = eval(estimates, vocabSize, "");
}
