private void PairSkyBot(List <Tracklet> Tracklets, double ArcLengthSec, string ReportFieldName, int CCDNumber, FitsImage[] ImageSet, Step.StepPipeline Pipeline) { foreach (Image img in ImageSet) { SkyBotImageData skid = img.GetProperty <SkyBotImageData>(); //skid.RetrieveObjects(ObservatoryCode); foreach (Tracklet tk in Tracklets) { skid.TryPair(tk, ArcLengthSec); } var unp = skid.GetUnpaired(); if (unp.Count != 0) { Logger("SkyBoT: Unpaired objects left: "); foreach (var o in unp) { string SkData = "SkyBoT: " + ExtraIO.EquatorialPointStringFormatter.FormatToString(o, ExtraIO.EquatorialPointStringFormatter.Format.MPC); PixelPoint pp = img.Transform.GetPixelPoint(o); SkData += ";" + pp.ToString(); Logger(SkData); var Reasons = Pipeline.QueryWhyNot(o, 5); string LRs = "Reasons: "; foreach (string x in Reasons) { LRs += x + ";"; } if (Reasons.Count == 0) { Logger("Not found in removal log, so not detected."); } else { Logger(LRs); } } } } for (int i = 0; i < Tracklets.Count; i++) { Tracklet tk = Tracklets[i]; if (!tk.TryFetchProperty(out ObjectIdentity objid)) { objid = new ObjectIdentity(); } objid.ComputeNamescoreWithDefault(tk, null, ReportFieldName, CCDNumber, i); tk.SetResetProperty(objid); } }
public List <Tracklet> AnalyzeCCD(PipelineArguments Args) { Logger("Setting up pipeline"); /* Deal with incorrect SWARP flux scaling */ SWarpScaling.ApplyTransform = CorrectSWARP; string RunDir = Args.RunDir; if (!Directory.Exists(RunDir)) { Directory.CreateDirectory(RunDir); } /* Read input images and preprocess for poisson noise */ int ImageCount = Args.Inputs.Length; FitsImage[] FirstProcess = new FitsImage[ImageCount]; double[] PFW = PipelineHelperFunctions.LinearizedPoissonKernel(PoissonRadius); Step.StepPipeline sp = new Step.StepPipeline(StandardBITPIX, RunDir, Args.Inputs.Length, MaxDetections); sp.LogHookImage = LogImage; sp.LogHookDetection = LogDet; sp.LogMessage = LogMessage; bool HasBadpix = Args.Badpixel != null; Logger("Begining to run the pipeline"); var zpTask = System.Threading.Tasks.Task <Dictionary <IO.Image, double> > .Factory.StartNew(() => CalibrateZP(Args.Inputs)); var skTask = System.Threading.Tasks.Task <bool> .Factory.StartNew(() => PrecacheSkyBot(Args.Inputs)); BitArray[] map = PipelineHelperFunctions.ExtractBadpixel(Args.Badpixel, Logger); for (int i = 0; i < ImageCount; i++) { FitsImage Pipeline = Args.Inputs[i]; Pipeline.GetProperty <ImageSource>().AddToSet(Pipeline, "Original"); sp.SetModel(i, Pipeline, new List <IO.ImageProperties>() { Pipeline.GetProperty <ObservationTime>() }); if (!UseCoreFilter) { sp.RunPipeline(RestrictedMean.RestrictedMeanFilter, "Poisson", i, ref Pipeline, PFW, RestrictedMean.Parameters(PoissonRadius)); } else if (HasBadpix) { sp.RunPipeline(CoreFilter.Filter, "Poisson", i, ref Pipeline, new CoreFilter.CoreFilterParameters(PFW, map), CoreFilter.Parameters(PoissonRadius)); } else { throw new ArgumentException("Must specify Badpixel files if trying to run with CoreFilter"); } if (Operations.HasFlag(EnabledOperations.Normalization)) { if (!sp.EnsureImage("Normalized", i, out FitsImage Normalized)) { Point4Distance p4d = new Point4Distance(Pipeline, Normalized, NormalizationMeshSize); Logger("Generated Normalized image " + i); } else { Logger("Found Normalized image " + i); } Normalized.GetProperty <ImageSource>().AddToSet(Args.Inputs[i], "Normalized"); Pipeline = Normalized; } FirstProcess[i] = Pipeline; } /* Create the central median */ string CentralPath = Path.Combine(RunDir, "Central.fits"); if (!sp.EnsureCentralImage("Central", out FitsImage Central)) { HardMedians.MultiImageMedian.Run(null, FirstProcess, Central, HardMedians.MultiImageMedianParameters); Logger("Generated Central image"); } else { Logger("Found Central image"); } Logger("Computed the multi-image median"); /* Prepare the mask, slow object detector, trail detector, weights for second median filtering, etc. */ ImageStatistics CentralStats = new ImageStatistics(Central); if (Args.Clipped) { CentralStats = new ImageStatistics(Central, CentralStats.ZeroLevel, 2 * CentralStats.StDev); } StarData StarList = new StarData(); ComputeDetectorData(Central, CentralStats, StarList, out MaskByMedian.MaskProperties MaskProp, out DotDetector SlowDetector, out LongTrailDetector.LongTrailData LTD); if (Args.Clipped) { SlowDetector.HighThresholdMultiplier *= 2; SlowDetector.LowThresholdMultiplier *= 2; } DetectionReducer dr = new DetectionReducer() { PairingRadius = 0.7 }; if (Operations.HasFlag(EnabledOperations.SourceExtractor)) { try { dr.LoadStars(StarList.FixedStarList); } catch (Exception ex) { throw new ArgumentException("Could not read detections from SE catalog.", ex); } dr.GeneratePool(); } Logger("Set up detectors"); List <ImageDetection> FullDetectionsList = new List <ImageDetection>(); double[] FMW2 = PipelineHelperFunctions.LinearizedMedianKernel(); LTLimit ltl = new LTLimit() { MinPix = TrailMinPix }; RipFilter rf = new RipFilter() { SigmaTop = 30 }; Logger("Ready for final image processing and detection"); for (int i = 0; i < ImageCount; i++) { List <ImageDetection> LocalDetectionList = new List <ImageDetection>(); FitsImage DetectionSource = FirstProcess[i]; if (Operations.HasFlag(EnabledOperations.Masking)) { sp.RunPipeline(MaskByMedian.Masker, "Masked", i, ref DetectionSource, MaskProp, MaskByMedian.Parameters); } if (Operations.HasFlag(EnabledOperations.SecondMedian)) { sp.RunPipeline(HardMedians.WeightedMedian, "Second Median", i, ref DetectionSource, FMW2, HardMedians.WeightedMedianParameters(SecMedRadius)); } ImageStatistics SecMedStat = new ImageStatistics(DetectionSource); if (Operations.HasFlag(EnabledOperations.LongTrailDetector)) { var Dets = sp.RunDetector((FitsImage img) => { LongTrailDetector.PrepareAlgorithmForImage(img, SecMedStat, ref LTD); LongTrailDetector.Algorithm.Run(LTD, DetectionSource, LongTrailDetector.Parameters); return(LTD.Results); }, DetectionSource, "Trail", DetectionAlgorithm.Trail); LocalDetectionList.AddRange(Dets); } if (Operations.HasFlag(EnabledOperations.BlobDetector)) { var Dets = sp.RunDetector(SlowDetector.Detect, DetectionSource, "Blob", DetectionAlgorithm.Blob); LocalDetectionList.AddRange(Dets); } if (Operations.HasFlag(EnabledOperations.SourceExtractor)) { var dts = sp.RunDetector((arg) => { List <ImageDetection> Dets = ExtraIO.SourceExtractor.ParseSEFile(Args.CatalogData[i], Args.Inputs[i]); Dets = Dets.Where((x) => x.FetchProperty <ObjectPhotometry>().Flux > 300).ToList(); var ND = dr.Reduce(Dets); return(ND); }, DetectionSource, "SE", DetectionAlgorithm.SourceExtractor); LocalDetectionList.AddRange(dts); } if (Operations.HasFlag(EnabledOperations.OutputDetectionMap)) { DetectionDebugMap(RunDir, i, LocalDetectionList, DetectionSource); } rf.ImgMean = SecMedStat.ZeroLevel; rf.ImgSigma = SecMedStat.StDev; var NLDL = sp.RunFilters(LocalDetectionList, "LocalToGlobal", ltl, rf); Logger("Total " + NLDL.Count + " detections."); FullDetectionsList.AddRange(NLDL); } Logger("Filtering and pairing detections..."); LinearityThresholdFilter LTF = new LinearityThresholdFilter() { MaxLineThickness = MaxLineThickness }; List <ImageDetection> FilteredDetections = sp.RunFilters(FullDetectionsList, "MainFilter", LTF); StarList.MarkStarCrossed(FilteredDetections, StarCrossRadiusM, StarCrossMinFlux); if (Args.CCDBadzone != null) { FilteredDetections = sp.RunFilters(FilteredDetections, "Badzone", Args.CCDBadzone); } Logger("Before PrePair " + FilteredDetections.Count); PrePair.MatchDetections(FilteredDetections, MaxPairmatchDistance, MixMatch, SameArcSep); Logger("Left with " + FilteredDetections.Count + " detections"); LinePoolSimple lps = new LinePoolSimple() { MaxLinErrorArcSec = MaxResidual, SearchExtraSmall = SmallExtraSearchRadius, SearchExtraBig = BigExtraSearchRadius }; lps.LoadDetections(FilteredDetections); lps.GeneratePool(); var Pairings = lps.FindTracklets(); sp.NotePairings(FilteredDetections, Pairings); Logger("Found " + Pairings.Count + " raw tracklets"); LinearityTest lintest = new LinearityTest(); StaticFilter stf = new StaticFilter(); TotalError te = new TotalError(); var TK2List = sp.RunFilters(Pairings, "Tracklet Filtering", stf, te); Logger("After filtering: " + TK2List.Count + " candidate objects found"); sp.LogDetections(Path.Combine(RunDir, "detlog.txt")); Dictionary <IO.Image, double> ZP = zpTask.Result; skTask.Wait(); var Recovered = RecoverTracklets(TK2List, Args.Inputs, Path.Combine(RunDir, "reclog.txt"), ZP); TrackletsDeduplication.Deduplicate(Recovered, 1.0); Logger("Recovered " + Recovered.Count + " candidate objects"); PairSkyBot(Recovered, SkyBoTDistance, Args.FieldName, Args.CCDNumber, Args.Inputs, sp); return(Recovered); }