/// <summary>
/// Feeds the layout thread
/// </summary>
public override void StartLayout()
{
if (nodes.Count <= 1)
{
return; //nothing to do
}
//if there are cycles in the graph we have infinite loops, make sure the layout is finite
//by checking this list
for (int k = 0; k < nodes.Count; k++)
{
visited[nodes[k].UID.ToString()] = false;
positioned[nodes[k].UID.ToString()] = false;
nodes[k].Tag = k; //makes sure we can get the index in the collection
}
//the structure depends on a spanning tree (Prim's algorithm here)
if (extract == null)
{
throw new Exception("The layout algorithm doesn't have a GraphAbstract to work with.");
}
GraphAnalyzer analyzer = new GraphAnalyzer(extract, true);
IGraph g = Algorithms.PrimsAlgorithm(analyzer, 0);//TODO: allow to modify the starting vertex
//IGraph g = Algorithms.KruskalsAlgorithm(analyzer);
mSite.OutputInfo("Prim's:" + Environment.NewLine);
mSite.OutputInfo(g.ToString());
if (g == null)
{
return; //TODO: notify the failure to find a spanning tree
}
VerticalDrawTree(g, nodes[0], true, 30, 30);
//VerticalDrawTree(g,nodes[rnd.Next(0,nodes.Count-1)],true,30,30);
}
public void TestMissingProjectFile()
{
var mockLogger = new Mock <ILogger>();
var mockProjectAnalyzer = new Mock <IProjectAnalyzer>();
var mockResultsReporter = new Mock <IResultsReporter>();
var analyzer = new GraphAnalyzer(mockLogger.Object, mockProjectAnalyzer.Object, mockResultsReporter.Object, true);
string doesNotExistPath = Path.Combine(Path.GetTempPath(), $"{Guid.NewGuid()}");
analyzer.AnalyzeGraph(doesNotExistPath);
}
public void TestExistingProjectFile()
{
string testProject = TestUtilities.CreateTestProject();
var mockLogger = new Mock <ILogger>();
var mockProjectAnalyzer = new Mock <IProjectAnalyzer>();
var mockResultsReporter = new Mock <IResultsReporter>();
mockProjectAnalyzer.Setup(a => a.IsBuildUpToDate(It.IsAny <string>())).Returns((true, string.Empty));
var analyzer = new GraphAnalyzer(mockLogger.Object, mockProjectAnalyzer.Object, mockResultsReporter.Object, true);
bool isUpToDate = analyzer.AnalyzeGraph(testProject);
Assert.IsTrue(isUpToDate);
TestUtilities.CleanUpTestProject(testProject);
}
internal static void Process(Graph graph)
{
int iteration = 1;
bool foundPatterns;
PatternMap patterns = null;
if (File.Exists(PATH))
{
File.Delete(PATH);
}
do
{
Console.WriteLine("\nИтерация №" + iteration);
if (graph.VertexCount < 3)
{
Console.WriteLine("Граф имеет слишком мало вершин для поиска паттернов.");
break;
}
Console.WriteLine("Ищем паттерны...");
var analyzer = new GraphAnalyzer(graph, patterns);
foundPatterns = analyzer.FindPatterns(out patterns);
if (foundPatterns)
{
Console.WriteLine("Найдено экземпляров паттернов: " + patterns.TotalInstances);
Console.WriteLine("Делаем подстановку...");
graph.ReplacePatterns(patterns);
Export(patterns, iteration);
iteration++;
}
else
{
Console.WriteLine("Паттернов не обнаружено.");
}
} while (foundPatterns);
Console.WriteLine("Поиск завершён.");
}
public Transformation calculateTransformation(List <Contour <Point> > contours_image1, List <Contour <Point> > contours_image2)
{
List <Feature> image1_features = new List <Feature>();
List <Feature> image2_features = new List <Feature>();
//Get the points of the FIRST (=0) contour
Point[] points1 = contours_image1[0].ToArray();
//Calculate the angle at every pixel for picture 1
for (int i = 0; i < points1.Length; i++)
{
AngleCalculator angleCalculator = new AngleCalculator();
double angle = angleCalculator.calculateAngle(points1, i);
Feature f = new Feature();
f.point = points1[i];
f.angle_at_pixel = angle;
image1_features.Add(f);
}
//Get the points of the FIRST (=0) contour
Point[] points2 = contours_image2[0].ToArray();
//Calculate the angle at every pixel for picture 2
for (int i = 0; i < points2.Length; i++)
{
AngleCalculator angleCalculator = new AngleCalculator();
double angle = angleCalculator.calculateAngle(points2, i);
Feature f = new Feature();
f.point = points2[i];
f.angle_at_pixel = angle;
image2_features.Add(f);
}
GraphAnalyzer graphanalyzer = new GraphAnalyzer();
//Normalize the shorter contour to longer one
List <Feature> image1_features_normalized;
List <Feature> image2_features_normalized;
if (image1_features.Count < image2_features.Count)
{
image1_features_normalized = graphanalyzer.normalize(image2_features, image1_features);
image2_features_normalized = image2_features;
}
else
{
image2_features_normalized = graphanalyzer.normalize(image1_features, image2_features);
image1_features_normalized = image1_features;
}
//Moves the contour(graph) of image1 to best matching
image1_features_normalized = graphanalyzer.matchGraphs(image1_features_normalized, image2_features_normalized);
//Get the best Features by using extrema [0] image1 --> [1] image2, ....
List <Feature> bestFeatures = graphanalyzer.findBestFeaturesWithExtrema(image1_features_normalized, image2_features_normalized);
bestFeatureStorage1.Add(bestFeatures[0]);
bestFeatureStorage1.Add(bestFeatures[2]);
bestFeatureStorage2.Add(bestFeatures[1]);
bestFeatureStorage2.Add(bestFeatures[3]);
//Calculating the transformation for the best features
Transformation transformation = calculateTransformationValues(bestFeatures);
//Exporting the graph
Exporter exporter = new Exporter();
exporter.exportFeatures(image1_features_normalized, image2_features_normalized);
return(transformation);
}
public Transformation calculateTransformation(List<Contour<Point>> contours_image1, List<Contour<Point>> contours_image2)
{
List<Feature> image1_features = new List<Feature>();
List<Feature> image2_features = new List<Feature>();
//Get the points of the FIRST (=0) contour
Point[] points1 = contours_image1[0].ToArray();
//Calculate the angle at every pixel for picture 1
for (int i = 0; i < points1.Length; i++)
{
AngleCalculator angleCalculator = new AngleCalculator();
double angle = angleCalculator.calculateAngle (points1, i);
Feature f = new Feature();
f.point = points1[i];
f.angle_at_pixel = angle;
image1_features.Add(f);
}
//Get the points of the FIRST (=0) contour
Point[] points2 = contours_image2[0].ToArray();
//Calculate the angle at every pixel for picture 2
for (int i = 0; i < points2.Length; i++)
{
AngleCalculator angleCalculator = new AngleCalculator();
double angle = angleCalculator.calculateAngle(points2, i);
Feature f = new Feature();
f.point = points2[i];
f.angle_at_pixel = angle;
image2_features.Add(f);
}
GraphAnalyzer graphanalyzer = new GraphAnalyzer();
//Normalize the shorter contour to longer one
List<Feature> image1_features_normalized;
List<Feature> image2_features_normalized;
if (image1_features.Count < image2_features.Count)
{
image1_features_normalized = graphanalyzer.normalize(image2_features, image1_features);
image2_features_normalized = image2_features;
}
else
{
image2_features_normalized = graphanalyzer.normalize(image1_features, image2_features);
image1_features_normalized = image1_features;
}
//Moves the contour(graph) of image1 to best matching
image1_features_normalized = graphanalyzer.matchGraphs(image1_features_normalized, image2_features_normalized);
//Get the best Features by using extrema [0] image1 --> [1] image2, ....
List<Feature> bestFeatures = graphanalyzer.findBestFeaturesWithExtrema(image1_features_normalized, image2_features_normalized);
bestFeatureStorage1.Add(bestFeatures[0]);
bestFeatureStorage1.Add(bestFeatures[2]);
bestFeatureStorage2.Add(bestFeatures[1]);
bestFeatureStorage2.Add(bestFeatures[3]);
//Calculating the transformation for the best features
Transformation transformation = calculateTransformationValues(bestFeatures);
//Exporting the graph
Exporter exporter = new Exporter();
exporter.exportFeatures(image1_features_normalized, image2_features_normalized);
return transformation;
}
