/// <summary>
/// Returns a computational context which is a set of nodes and a set "weights" to apply to the nodes to form a linear combination to get the mean value of the cells
/// </summary>
public async Task <LinearCombinationContext> CreateAsync(IEnumerable <ICellRequest> cells)
{
Stopwatch sw = Stopwatch.StartNew();
var tsAveragerTask = timeSeriesAveragerFactory.CreateAsync();
var liTask = linearInterpolatorFactory.CreateAsync();
var tsAverager = await tsAveragerTask;
var linearInterpolator = await liTask;
sw.Stop();
traceSource.TraceEvent(TraceEventType.Verbose, 1, "Time series averager and lenear interpolator constructed in {0}", sw.Elapsed);
sw = Stopwatch.StartNew();
var resultTasks = cells.Select <ICellRequest, Task <Tuple <ICellRequest, RealValueNodes, IEnumerable <LinearWeight> > > >(async c =>
{
var tsa = (RealValueNodes)(await tsAverager.GetAsync(c));
var w = (IEnumerable <LinearWeight>)(await linearInterpolator.GetLinearWeigthsAsync(tsa, c));
return(Tuple.Create(c, tsa, w));
}).ToArray();
var result = await Task.WhenAll(resultTasks);
sw.Stop();
traceSource.TraceEvent(TraceEventType.Verbose, 2, "Linear weights for {0} cells prepared in {1}", resultTasks.Length, sw.Elapsed);
LinearCombinationContext lcc = new LinearCombinationContext(result);
return(lcc);
}
public async Task LinearCombinationAggregatorTest()
{
LinearCombinationAggregator lca = new LinearCombinationAggregator();
var nodes = new RealValueNodes(new double[3], new double[3], new double[] { 2.0, 3.0, 5.0 });
var weights = new LinearWeight[] { new LinearWeight(1, 7.0), new LinearWeight(0, 11.0), new LinearWeight(2, 13.0) };
LinearCombinationContext lcc = new LinearCombinationContext(new Tuple <ICellRequest, RealValueNodes, IEnumerable <LinearWeight> >[] { new Tuple <ICellRequest, RealValueNodes, IEnumerable <LinearWeight> >(new RequestStubs(), nodes, (IEnumerable <LinearWeight>)weights) });
double[] result = await lca.AggregateCellsBatchAsync(lcc, new ICellRequest[] { new RequestStubs() });
Assert.AreEqual(1, result.Length);
Assert.AreEqual(108, result[0]);
}
public async Task <double[]> EvaluateCellsBatchAsync(LinearCombinationContext computationalContext, IEnumerable <ICellRequest> cells)
{
var variogramProvider = await variogramProviderFactory.ConstructAsync();
var combinationsIterator = computationalContext.Combinations.GetEnumerator();
traceSource.TraceEvent(TraceEventType.Start, 1, "Filtering out cells that are not requested");
var filtered = cells.Select(cell =>
{
Tuple <ICellRequest, RealValueNodes, IEnumerable <LinearWeight> > currentElement;
ICellRequest contextCell;
do
{
var nextExists = combinationsIterator.MoveNext();
if (!nextExists)
{
throw new InvalidOperationException("Received linear combination does not containg information about requested cell. Context is not synchronize with requested cells sequenece.");
}
currentElement = combinationsIterator.Current;
contextCell = currentElement.Item1;
} while (!contextCell.Equals(cell));
return(currentElement);
}).ToArray();
traceSource.TraceEvent(TraceEventType.Stop, 1, "Filtered out cells that are not requested");
traceSource.TraceEvent(TraceEventType.Start, 2, "Evaluating uncertatinty for sequence of cells using precomputed linear combinations");
var resultsTasks = filtered.AsParallel().AsOrdered().Select(async tuple =>
{
if (tuple.Item2.Lats.Length == 0)
{
return(Double.NaN); //there are no nodes. Out of data request? can't produce uncertainty
}
var variogram = await variogramProvider.GetSpatialVariogramAsync(tuple.Item2);
var cell = tuple.Item1;
var weights = tuple.Item3.ToArray();
var nodes = tuple.Item2;
Debug.Assert(Math.Abs(weights.Sum(w => w.Weight) - 1.0) < 1e-10);
double sill = variogram.Sill;
double cellLat = (cell.LatMax + cell.LatMin) * 0.5;
double cellLon = (cell.LonMax + cell.LonMin) * 0.5;
//var = cov(0)+ sum sum (w[i]*w[j]*cov(i,j))-2.0*sum(w[i]*cov(x,i))
double cov_at_0 = sill;
double acc = cov_at_0; //cov(0)
for (int i = 0; i < weights.Length; i++)
{
double w = weights[i].Weight;
int idx1 = weights[i].DataIndex;
double lat1 = nodes.Lats[idx1];
double lon1 = nodes.Lons[idx1];
for (int j = 0; j < i; j++)
{
int idx2 = weights[j].DataIndex;
double lat2 = nodes.Lats[idx2];
double lon2 = nodes.Lons[idx2];
double dist = SphereMath.GetDistance(lat1, lon1, lat2, lon2);
double cov = sill - variogram.GetGamma(dist);
acc += 2.0 * w * weights[j].Weight * cov;
}
acc += w * w * cov_at_0; //diagonal elements
double dist2 = SphereMath.GetDistance(lat1, lon1, cellLat, cellLon);
double cov2 = sill - variogram.GetGamma(dist2);
acc -= 2.0 * w * cov2;
}
return(acc * 0.5); //as dealing with full variogram instead of semivariogram
}).ToArray();
var results = await Task.WhenAll(resultsTasks);
traceSource.TraceEvent(TraceEventType.Stop, 2, "Evaluated uncertatinty for sequence of cells using precomputed linear combinations");
return(results);
}
