public IEnumerable <KeyValuePair <DateTime, Tuple <double, double>[]> > BatchRun1D(IEnumerable <KeyValuePair <DateTime, Point> > meas)
{
ParticleFilterSharp1D FilterSharp = new ParticleFilterSharp1D();
FilterSharp.Particles = ParticleFactory.BuildSwarm(N, new int[] { min, max }).ToList();
DateTime dt = meas.First().Key;
foreach (var m in meas)
{
TimeSpan ticks = (m.Key - dt);
// move based on last measurement
FilterSharp.Predict(EffectiveCountMinRatio, ticks);
var prd = new KeyValuePair <DateTime, Tuple <double, double>[]>(
m.Key, FilterSharp.Particles.Select(__ => Tuple.Create(__.Y, __.Weight)).ToArray());
// incorporate measurement
if (m.Value != default(Point))
{
FilterSharp.Update(m.Value);
}
dt = m.Key;
yield return(prd);
}
;
}
public IEnumerable <KeyValuePair <DateTime, Tuple <double, double>[]> > BatchRun(IEnumerable <KeyValuePair <DateTime, double> > meas)
{
ParticleFilterSharp1D FilterSharp = new ParticleFilterSharp1D();
FilterSharp.Particles = ParticleFactory.BuildSwarm(N, new int[] { min, max }).ToList();
DateTime dt = meas.First().Key;
return(meas.Select(_ =>
{
TimeSpan ticks = (_.Key - dt);
// move based on last measurement
FilterSharp.Predict(EffectiveCountMinRatio, ticks);
var prd = new KeyValuePair <DateTime, Tuple <double, double>[]>(
dt, FilterSharp.Particles.Select(__ => Tuple.Create(__.Y, __.Weight)).ToArray());
// incorporate measurement
FilterSharp.Update(new Point(0, _.Value));
dt = _.Key;
return prd;
}));
}
public IObservable <KeyValuePair <DateTime, Tuple <double, double>[]> > Run(IObservable <KeyValuePair <DateTime, double?> > meas)
{
ParticleFilterSharp1D FilterSharp = new ParticleFilterSharp1D();
FilterSharp.Particles = ParticleFactory.BuildSwarm(N, new int[] { min, max }).ToList();
return(meas.IncrementalTimeOffsets().Select(_ =>
{
// move based on last measurement
FilterSharp.Predict(EffectiveCountMinRatio, _.Key.Item2);
var prd = new KeyValuePair <DateTime, Tuple <double, double>[]>(
_.Key.Item1, FilterSharp.Particles.Select(__ => Tuple.Create(__.Y, __.Weight)).ToArray());
// incorporate measurement
if (_.Value != null)
{
FilterSharp.Update(new Point(0, (double)_.Value));
}
return prd;
}));
}
public IEnumerable <KeyValuePair <DateTime, Tuple <Normal, Normal> > > BatchRun(List <Tuple <DateTime, Point> > meas, Point initialPoint)
{
ParticleFilterSharp2D FilterSharp = new ParticleFilterSharp2D();
IContinuousDistribution xDistribution = null;
IContinuousDistribution yDistribution = null;
IContinuousDistribution oDistribution = null;
IContinuousDistribution vDistribution = null;
if (initialPoint == null)
{
xDistribution = new ContinuousUniform(-10, 10);
yDistribution = new ContinuousUniform(-10, 10);
oDistribution = new ContinuousUniform(0, 2 * Math.PI);
vDistribution = new ContinuousUniform(0.000001, 0.000001);
}
FilterSharp.Particles = ParticleFactory.BuildSwarm(N, xDistribution, yDistribution, vDistribution, oDistribution).ToList();
DateTime dt = meas[0].Item1.AddTicks(-(long)meas.Select(_ => (double)_.Item1.Ticks).ToArray().SelectDifferences().Average());
for (int i = 0; i < meas.Count(); i++)
{
long ticks = (meas[i].Item1 - dt).Ticks;
// move based on last measurement
FilterSharp.Predict(EffectiveCountMinRatio);
var est = ParticleHelper.Estimate(FilterSharp.Particles);
yield return(new KeyValuePair <DateTime, Tuple <Normal, Normal> >(dt, est));
// predictions.Add(new KeyValuePair<DateTime, List<Point>>(dt, particles.Select(_=>(Point)(_)).ToList()));
// incorporate measurements
FilterSharp.Update(meas[i].Item2);
dt = meas[i].Item1;
}
}
