private List <SpatialmHGResult> Solve2DProblem(List <Coordinate> coords, List <bool> labels, List <Coordinate3D> projectedFrom = null, PrincipalComponentAnalysis pca = null)
{
var T = new Tesselation(coords, labels, new List <string>(), Config)
{
pca = pca
};
if (projectedFrom != null)
{
T.ProjectedFrom = projectedFrom.Cast <ICoordinate>().ToList();
}
IEnumerable <Cell> topResults = null;
if ((Config.ActionList & Actions.Search_CellSkipping) != 0)
{
topResults = T.GradientSkippingSweep(numStartCoords: 20, numThreads: Environment.ProcessorCount - 1);
Tesselation.Reset();
return(topResults.Select(t => new SpatialmHGResult(t)).ToList());
}
if ((Config.ActionList & Actions.Search_Exhaustive) != 0)
{
T.GenerateFromCoordinates();
}
if ((Config.ActionList & Actions.Search_Originals) != 0)
{
//mHGOnOriginalPoints(args, coordinates, labels, numcoords);
}
if ((Config.ActionList & Actions.Search_FixedSet) != 0)
{
/*
* var avgX = coordinates.Select(c => c.GetDimension(0)).Average();
* var avgY = coordinates.Select(c => c.GetDimension(1)).Average();
* var cord = new Coordinate(avgX, avgY);
* mHGOnOriginalPoints(args, coordinates, labels, numcoords, new List<ICoordinate>() { cord });
*/
}
if ((Config.ActionList & Actions.Search_LineSweep) != 0)
{
T.LineSweep();
}
if ((Config.ActionList & Actions.Search_EmpricalSampling) != 0)
{
var problem = coords.Zip(labels, (a, b) => new Tuple <ICoordinate, bool>(a, b)).ToList();
var gr = new Gridding();
var problemSize = MathExtensions.Binomial(Line.Count, 2) + Line.Count + 1;
gr.GenerateEmpricialDensityGrid((long)Math.Min(problemSize, 100000), problem);
var results = new ConcurrentPriorityQueue <double, SpatialmHGResult>();
Parallel.ForEach(gr.GetPivots(), pivot =>
{
var binvec = problem.OrderBy(c => c.Item1.EuclideanDistance(pivot)).Select(c => c.Item2).ToArray();
var res = mHGJumper.minimumHypergeometric(binvec);
results.Enqueue(res.Item1, new SpatialmHGResult(res.Item1, res.Item2, (Coordinate)pivot));
while (results.Count > Config.GetTopKResults)
{
results.TryDequeue(out var junk);
}
});
return(results.Select(v => v.Value).ToList());
}
return(null);
}
/// <summary>
/// 3d subsample from 50 points 20. run 100 times. compare to opt.
/// </summary>
/// <param name="numcoords"></param>a
/// <param name="numiter"></param>
public static List <double> CompareExahustiveWithSubsamplingInput(int numcoords = 50, int subsampleSize = 20, int numiter = 100, string suffix = "0")
{
Config = new ConfigParams("");
#region init
StaticConfigParams.rnd = (Config.ActionList & Actions.Program_RandomConstSeed) != 0 ? new SafeRandom(1) : new SafeRandom();
Config.timer.Start();
#endregion
//Load coordinates and labels
var resultPairedDiff = new List <double>();
var extraAnalyses = new List <string>();
int victories = 0, ties = 0;
var coordinates = new List <ICoordinate>();
var labels = new List <bool>();
Program.Config = Config;
StaticConfigParams.filenamesuffix = suffix;
var res = Program.RandomizeCoordinatesAndSave(numcoords, true);
coordinates = res.Item1;
labels = res.Item2;
var zeros = labels.Count(l => l == false);
var filterCount = (int)(Config.FilterKFurthestZeros * zeros);
if (filterCount > 0)
{
Console.WriteLine("Filtering {0} far away points", filterCount);
var positives = new List <ICoordinate>();
var negatives = new List <ICoordinate>();
var negIds = new List <int>();
for (var i = 0; i < coordinates.Count; i++)
{
if (labels[i])
{
positives.Add(coordinates[i]);
}
else
{
negatives.Add(coordinates[i]);
negIds.Add(i);
}
}
var negMinDist = new HashSet <int>(negatives.Zip(negIds, (a, b) => new { PosMinDist = positives.Select(p => p.EuclideanDistance(a)).Min(), Id = b })
.OrderByDescending(n => n.PosMinDist).Select(t => t.Id).Take(filterCount));
coordinates = coordinates.Where((a, b) => !negMinDist.Contains(b)).ToList();
labels = labels.Where((a, b) => !negMinDist.Contains(b)).ToList();
numcoords -= filterCount;
}
var instanceDataCoords = coordinates.Zip(labels, (a, b) => new Tuple <ICoordinate, bool>(a, b)).ToList();
var instanceData = coordinates.Zip(labels, (a, b) => new Tuple <double, double, bool>(a.GetDimension(0), a.GetDimension(1), b)).ToList();
Config.SKIP_SLACK = -1000;
var ew = new EnrichmentWrapper(Config);
var resultsExhaustive = ew.SpatialmHGWrapper(instanceData).Select(v => (SpatialmHGResult)v).First();
//Actual work starts here
var ones = labels.Count(l => l);
var linecount = ones * (numcoords - ones);
Config.Cellcount = ((long)linecount * (linecount - 1)) / 2.0 + linecount + 1;
mHGJumper.Initialize(ones, numcoords - ones);
mHGJumper.optHGT = Config.SIGNIFICANCE_THRESHOLD; // / Cellcount; //for bonferonni
//alpha is the Bonferonni (union-bound) corrected significance level
using (var fileout = new StreamWriter($"sample_vs_exhaustive_{suffix}.csv"))
for (var instanceIter = 1; instanceIter < numiter; instanceIter++)
{
StaticConfigParams.filenamesuffix = instanceIter.ToString();
Console.WriteLine("File {0}", instanceIter);
var sampleCoords = coordinates
.Zip(labels, (a, b) => new { Coords = a, Labels = b, Rand = StaticConfigParams.rnd.Next() })
.OrderBy(v => v.Rand).Take(subsampleSize).ToList();
while (sampleCoords.All(v => v.Labels) || !sampleCoords.Any(v => v.Labels))
{
sampleCoords = coordinates
.Zip(labels, (a, b) => new { Coords = a, Labels = b, Rand = StaticConfigParams.rnd.Next() })
.OrderBy(v => v.Rand).Take(subsampleSize).ToList();
}
if (StaticConfigParams.WriteToCSV)
{
Generics.SaveToCSV(sampleCoords.Select(t => t.Coords.ToString() + "," + Convert.ToDouble(t.Labels)),
$@"coords_{StaticConfigParams.filenamesuffix}.csv");
}
ones = sampleCoords.Count(l => l.Labels);
linecount = ones * (subsampleSize - ones);
Config.Cellcount = ((long)linecount * (linecount - 1)) / 2.0 + linecount + 1;
Console.WriteLine(@"Starting work on {0} coordinates with {1} 1's (|cells|={2:n0}, alpha={3}).", numcoords, ones, Config.Cellcount, mHGJumper.optHGT);
mHGJumper.optHGT = Config.SIGNIFICANCE_THRESHOLD;
Tesselation T = new Tesselation(sampleCoords.Select(v => (Coordinate)v.Coords).ToList(), sampleCoords.Select(v => v.Labels).ToList(), null, Config)
{
ProjectedFrom = coordinates,
SourceLabels = labels.ToArray()
};
var topResults = T.GradientSkippingSweep(numStartCoords: 20, numThreads: Environment.ProcessorCount - 1).First();
Line.Reset();
if (resultsExhaustive.pvalue < topResults.mHG.Item1)
{
victories++;
}
else if (resultsExhaustive.pvalue == topResults.mHG.Item1)
{
ties++;
}
else
{
Console.WriteLine($"Debug me");
}
var pdiff = Math.Log10(topResults.mHG.Item1) - Math.Log10(resultsExhaustive.pvalue);
resultPairedDiff.Add(pdiff);
mHGJumper.optHGT = Config.SIGNIFICANCE_THRESHOLD;
Console.Write($"Uniform grid strategy @{Config.Cellcount} pivots... ");
var uniformGridFactory = new Gridding();
uniformGridFactory.GeneratePivotGrid(Convert.ToInt64(Config.Cellcount));
var uniformGridPivotlst = uniformGridFactory.GetPivots().ToList();
var uniformGridPivot = uniformGridPivotlst.AsParallel().Max(p => - Math.Log10(EnrichmentAtPivot(instanceDataCoords, p)));
Console.WriteLine($"p={uniformGridPivot:e}");
Console.Write($"Empirical grid strategy @{Config.Cellcount} pivots... ");
mHGJumper.optHGT = Config.SIGNIFICANCE_THRESHOLD;
var empiricalGridFactory = new Gridding();
empiricalGridFactory.GenerateEmpricialDensityGrid(Convert.ToInt64(Config.Cellcount), instanceDataCoords);
var empiricalGridPivotlst = empiricalGridFactory.GetPivots().ToList();
var empiricalGridPivot = empiricalGridPivotlst.AsParallel().Max(p => - Math.Log10(EnrichmentAtPivot(instanceDataCoords, p)));
Console.WriteLine($"p={empiricalGridPivot:e}");
//extraAnalyses.Add($"{-Math.Log10(resultsExhaustive.pvalue)}, {-Math.Log10(topResults.mHG.Item1)}, {uniformGridPivot}, {empiricalGridPivot}");
fileout.WriteLine($"{-Math.Log10(resultsExhaustive.pvalue)}, {-Math.Log10(topResults.mHG.Item1)}, {uniformGridPivot}, {empiricalGridPivot}");
}
Console.WriteLine($"Out of {numiter} iterations, spatial enrichment won in {victories} and tied in {ties}.");
Console.WriteLine("Total elapsed time: {0:g}.\nPress any key to continue.", Config.timer.Elapsed);
//File.WriteAllLines($"experiment_pvaldiffs_{suffix}.txt", resultPairedDiff.Select(v => v.ToString()).ToArray());
//File.WriteAllLines($"experimentsAll_{suffix}.txt", extraAnalyses);
return(resultPairedDiff);
}