private static void WriteBinaryImageSurfer6Grid(IRegularGrid2D prototypeGrid, IImage <bool> image, string uri)
{
IRegularGrid2D thresholdGrid = prototypeGrid.CloneSize(image.Width, image.Height);
for (int i = 0; i < image.Width; ++i)
{
for (int j = 0; j < image.Height; ++j)
{
thresholdGrid[i, j] = image[i, j] ? 1.0 : 0.0;
}
}
thresholdGrid.WriteSurfer6BinaryFile(uri);
}
// usage : Training: C:\Users\rjs\Documents\dev\p4workspace\sandbox\geodyssey\proto\Athena\testdata\training.irap
// Expected: C:\Users\rjs\Documents\dev\p4workspace\sandbox\geodyssey\proto\Athena\testdata\expected.grd
// Grid for analysis: F:\sapere_aude\data\IrapClassic\grid_surface\ASCII\RMS\analysis.irap
static int Main(string[] args)
{
// Get a URI from the command line argument
Uri trainingInputUri = UriFromArg(args, 0);
Uri trainingExpectedUri = UriFromArg(args, 1);
Uri analysisUri = UriFromArg(args, 2);
GeodysseyModel model = new GeodysseyModel();
LoaderController.Instance.Open(trainingInputUri, model);
IRegularGrid2D trainingInputGrid = model[0]; // The first grid
LoaderController.Instance.Open(trainingExpectedUri, model);
IRegularGrid2D trainingExpectedGrid = model[1]; // The second grid
LoaderController.Instance.Open(analysisUri, model);
IRegularGrid2D analysisGrid = model[2]; // The third grid
// Replaces blanks with 0.0
for (int j = 0; j < trainingExpectedGrid.SizeJ; ++j)
{
for (int i = 0; i < trainingExpectedGrid.SizeI; ++i)
{
if (!trainingExpectedGrid[i, j].HasValue)
{
trainingExpectedGrid[i, j] = 0.0;
}
else
{
if (trainingExpectedGrid[i, j] < 0.0)
{
trainingExpectedGrid[i, j] = 0.0;
}
else if (trainingExpectedGrid[i, j] > 1.0)
{
trainingExpectedGrid[i, j] = 1.0;
}
}
}
}
int matrixWidth = 5;
FaultInHorizonClassifer classifier = new FaultInHorizonClassifer(matrixWidth);
classifier.Learn(trainingInputGrid, trainingExpectedGrid);
IRegularGrid2D predictedGrid = classifier.CreateFaultProbability(analysisGrid);
predictedGrid.WriteSurfer6BinaryFile("predicted.grd");
return(0);
}
static void Main(string[] args)
{
Uri horizonUri = UriFromArg(args, 0);
GeodysseyModel model = new GeodysseyModel();
LoaderController.Instance.Open(horizonUri, model);
IRegularGrid2D horizon = model[0];
//string pathOriginal = horizonUri.LocalPath.Replace(".dat", ".grd");
//horizon.WriteSurfer6BinaryFile(pathOriginal);
// TODO: Make IRegularGrid IEnumerable
var extentMap = new FastImage <bool>(horizon.SizeI, horizon.SizeJ, horizon.Select(item => item.HasValue));
IImage <bool> faultMap = Morphology.Invert(extentMap);
IImage <double> distanceMap = DistanceMap.EuclideanTransform(extentMap);
// Remove anything above a threshold distance from data
const double threshold = 50;
var clippedFaultMap = extentMap.CloneTransform((i, j) => distanceMap[i, j] < threshold &&
faultMap[i, j]);
Trace.WriteLine("Pepper filter");
IImage <bool> filtered = Morphology.PepperFiltering(5, clippedFaultMap);
Trace.WriteLine("Closing gaps");
IImage <bool> closed = Morphology.Closing(filtered);
Trace.WriteLine("Thinning until convergence");
IImage <bool> thinned = Morphology.ThinUntilConvergence(closed);
Trace.WriteLine("Thinning blocks until convergence");
IImage <bool> blockthinned = Morphology.ThinBlockUntilConvergence(thinned);
Trace.WriteLine("Filling");
IImage <bool> filled = Morphology.Fill(blockthinned);
WriteBinaryImageSurfer6Grid(horizon, filled, horizonUri.LocalPath.Replace(".grd", "_filled.grd"));
//// Create a double valued 'binary' image showing the extent of the horizon data
//FastImage<double> extentMap = new FastImage<double>(horizon.SizeI, horizon.SizeJ);
//for (int i = 0; i < horizon.SizeI; ++i)
//{
// for (int j = 0; j < horizon.SizeJ; ++j)
// {
// bool hasValue = horizon[i, j].HasValue;
// extentMap[i, j] = hasValue ? 1.0 : 0.0;
// }
//}
//int extent = extentMap.Where(v => v == 1.0).Count();
//double extentProportion = (double) extent / (extentMap.Width * extentMap.Height);
//IImage<double> scaledExtentMap = Scaler.Downscale(extentMap, 5);
//IImage<double> smoothedExtentMap = scaledExtentMap.CloneSize();
//Convolver.GaussianSmooth(scaledExtentMap, smoothedExtentMap, 3.0);
//IRegularGrid2D smoothedGrid = horizon.CloneSize(smoothedExtentMap.Width, smoothedExtentMap.Height);
//for (int i = 0 ; i < smoothedGrid.SizeI; ++i)
//{
// for (int j = 0 ; j < smoothedGrid.SizeJ; ++j)
// {
// smoothedGrid[i, j] = smoothedExtentMap[i, j];
// }
//}
//PriorityQueue<double> orderedIntensities = PriorityQueue<double>.CreateHighFirstOut(smoothedExtentMap);
//int k = (int) (extentProportion * orderedIntensities.Count);
//Debug.Assert(k >= 0);
//for (int i = 0 ; i < k - 1; ++i)
//{
// orderedIntensities.Dequeue();
//}
//double threshold = orderedIntensities.Dequeue();
//string pathSmoothed = horizonUri.LocalPath.Replace(".grd", "_smoothed.grd");
//smoothedGrid.WriteSurfer6BinaryFile(pathSmoothed);
//IImage<bool> thresholdMap = BitImage.Analysis.Threshold(smoothedExtentMap, threshold * 2.0);
//int actual = thresholdMap.Where(v => v).Count();
//double actualProportion = (double) actual / (thresholdMap.Width * thresholdMap.Height);
//IRegularGrid2D thresholdGrid = horizon.CloneSize(thresholdMap.Width, thresholdMap.Height);
//for (int i = 0; i < smoothedGrid.SizeI; ++i)
//{
// for (int j = 0; j < smoothedGrid.SizeJ; ++j)
// {
// thresholdGrid[i, j] = thresholdMap[i, j] ? 1.0 : 0.0;
// }
//}
//string pathThresholded = horizonUri.LocalPath.Replace(".grd", "_thresholded.grd");
//thresholdGrid.WriteSurfer6BinaryFile(pathThresholded);
//IImage<double> distanceMap = DistanceMap.EuclideanTransform(scaledExtentMap);
// Convert the image back to a grid for convenient output
IRegularGrid2D distanceGrid = horizon.CloneSize(distanceMap.Width, distanceMap.Height);
for (int i = 0; i < distanceMap.Width; ++i)
{
for (int j = 0; j < distanceMap.Height; ++j)
{
distanceGrid[i, j] = distanceMap[i, j];
}
}
string pathDistance = horizonUri.LocalPath.Replace(".grd", "_distance.grd");
distanceGrid.WriteSurfer6BinaryFile(pathDistance);
}
