public void ParallelNSampler()
{
var prior = from a in Normal(0, 100)
from b in Normal(0, 100)
select new Param(a, b);
var smc = LinearRegression.CreateLinearRegression(prior, LinearRegression.BeachSandData).SmcStandard(5000);
var sTimer = new Stopwatch();
sTimer.Start();
var serial = from s1 in smc
from s2 in smc
from s3 in smc
select new Tuple <Samples <Param>, Samples <Param>, Samples <Param> >(s1, s2, s3);
var result = serial.SampleN(2).ToList();
sTimer.Stop();
var pTimer = new Stopwatch();
pTimer.Start();
var parallel = from s1 in Independent(smc)
from s2 in Independent(smc)
from s3 in Independent(smc)
from triple in RunIndependent(s1, s2, s3)
select triple;
var thing = parallel.SampleNParallel(2).ToList();
pTimer.Stop();
Trace.WriteLine($"parallel: {pTimer.ElapsedMilliseconds}ms, serial: {sTimer.ElapsedMilliseconds}ms");
Assert.IsTrue(pTimer.ElapsedMilliseconds < sTimer.ElapsedMilliseconds);
}
public void Metropolis_LinReg()
{
// Define a prior with heavy tails
var prior = from a in Normal(0, 100)
from b in Normal(0, 100)
select new Param(a, b);
var linReg = LinearRegression.CreateLinearRegression(prior, LinearRegression.BeachSandData);
var mh = MetropolisHastings.MHPrior(linReg, 1000);
var samples = mh.SampleNParallel(100);
var paramA = from outer in samples
from inner in outer
select inner.a;
var paramB = from outer in samples
from inner in outer
select inner.b;
Debug.WriteLine(Histogram.Unweighted(paramA));
Debug.WriteLine(Histogram.Unweighted(paramB));
}
public void LinReg()
{
// Define a prior with heavy tails
var prior = from a in Normal(5, 10)
from b in Normal(1, 10)
select new Param(a, b);
// Create the linear regression, but don't do any inference yet
var linReg = LinearRegression.CreateLinearRegression(prior, LinearRegression.LinearData);
// Basically do importance sampling using the prior
var samples = linReg.WeightedPrior().SampleNParallel(1000);
var posteriorA = samples.Select(sample => ItemProb(sample.Item.a, sample.Prob));
var posteriorB = samples.Select(sample => ItemProb(sample.Item.b, sample.Prob));
// Graph the results
Debug.WriteLine("Posterior distribution of a:");
Debug.WriteLine(Histogram.Weighted(posteriorA, 20, 2));
Debug.WriteLine("Posterior distribution of b:");
Debug.WriteLine(Histogram.Weighted(posteriorB, 20, 2));
}
