Refactoring for Improved Readability and Maintainability

src/main/java/fiji/plugin/trackmate/LoadTrackMatePlugIn.java

@@ -53,6 +53,7 @@
 
 public class LoadTrackMatePlugIn extends TrackMatePlugIn
 {
+	private String pluginTitle = TrackMate.PLUGIN_NAME_STR + " v" + TrackMate.PLUGIN_NAME_VERSION;
 
 	/**
 	 * Loads a TrackMate file in the GUI.
@@ -82,13 +83,13 @@ public void run( final String filePath )
 			file = new File( filePath );
 			if ( !file.exists() )
 			{
-				IJ.error( TrackMate.PLUGIN_NAME_STR + " v" + TrackMate.PLUGIN_NAME_VERSION,
+				IJ.error( pluginTitle,
 						"Could not find file with path " + filePath + "." );
 				return;
 			}
 			if ( !file.canRead() )
 			{
-				IJ.error( TrackMate.PLUGIN_NAME_STR + " v" + TrackMate.PLUGIN_NAME_VERSION,
+				IJ.error( pluginTitle,
 						"Could not read file with path " + filePath + "." );
 				return;
 			}
@@ -98,7 +99,7 @@ public void run( final String filePath )
 		final TmXmlReader reader = createReader( file );
 		if ( !reader.isReadingOk() )
 		{
-			IJ.error( TrackMate.PLUGIN_NAME_STR + " v" + TrackMate.PLUGIN_NAME_VERSION, reader.getErrorMessage() );
+			IJ.error( pluginTitle, reader.getErrorMessage() );
 			return;
 		}
 
@@ -232,7 +233,7 @@ public void run( final String filePath )
 		}
 
 		logger2.log( "File loaded on " + TMUtils.getCurrentTimeString() + '\n', Logger.BLUE_COLOR );
-		final String welcomeMessage = TrackMate.PLUGIN_NAME_STR + " v" + TrackMate.PLUGIN_NAME_VERSION + '\n';
+		final String welcomeMessage = pluginTitle + '\n';
 		// Log GUI processing start
 		logger2.log( welcomeMessage, Logger.BLUE_COLOR );
 		logger2.log( "Please note that TrackMate is available through Fiji, and is based on a publication. "

src/main/java/fiji/plugin/trackmate/SpotCollection.java

@@ -313,7 +313,7 @@ public void run()
 							final double tval = featureFilter.value;
 							final boolean isAbove = featureFilter.isAbove;
 
-							if ( null == val || isAbove && val.compareTo( tval ) < 0 || !isAbove && val.compareTo( tval ) > 0 )
+							if (isSpotVisible(val, tval, isAbove))
 							{
 								shouldNotBeVisible = true;
 								break;
@@ -340,6 +340,10 @@ public void run()
 		}
 	}
 
+	private boolean isSpotVisible(Double val, double tval, boolean isAbove){
+		return (null == val || isAbove && val.compareTo( tval ) < 0 || !isAbove && val.compareTo( tval ) > 0);
+	}
+
 	/**
 	 * Returns the closest {@link Spot} to the given location (encoded as a
 	 * Spot), contained in the frame <code>frame</code>. If the frame has no

src/main/java/fiji/plugin/trackmate/detection/MaskUtils.java

@@ -102,72 +102,56 @@ public static final < T extends RealType< T > > double otsuThreshold( final Rand
 		return val.getRealDouble();
 	}
 
-	public static final long getThreshold( final Histogram1d< ? > hist )
-	{
-		final long[] histogram = hist.toLongArray();
+	public static final long getThreshold(final Histogram1d<?> histogram) {
+		final long[] intensityHistogram = histogram.toLongArray();
 		// Otsu's threshold algorithm
 		// C++ code by Jordan Bevik <Jordan.Bevic@qtiworld.com>
 		// ported to ImageJ plugin by G.Landini
-		int k, kStar; // k = the current threshold; kStar = optimal threshold
-		final int L = histogram.length; // The total intensity of the image
-		long N1, N; // N1 = # points with intensity <=k; N = total number of
-					// points
-		long Sk; // The total intensity for all histogram points <=k
-		long S;
-		double BCV, BCVmax; // The current Between Class Variance and maximum
-							// BCV
-		double num, denom; // temporary bookkeeping
+		int currentThreshold, optimalThreshold; // currentThreshold = the current threshold; optimalThreshold = optimal threshold
+		final int totalIntensity = intensityHistogram.length; // The total intensity of the image
+		long pointsBelowThreshold, totalPoints; // pointsBelowThreshold = # points with intensity <= currentThreshold; totalPoints = total number of points
+		long totalIntensityBelowThreshold; // The total intensity for all histogram points <= currentThreshold
+		long totalIntensityOverall;
+		double betweenClassVariance, maxBetweenClassVariance; // The current Between Class Variance and maximum BCV
+		double numerator, denominator; // temporary bookkeeping
 
 		// Initialize values:
-		S = 0;
-		N = 0;
-		for ( k = 0; k < L; k++ )
-		{
-			S += k * histogram[ k ]; // Total histogram intensity
-			N += histogram[ k ]; // Total number of data points
+		totalIntensityOverall = 0;
+		totalPoints = 0;
+		for (currentThreshold = 0; currentThreshold < totalIntensity; currentThreshold++) {
+			totalIntensityOverall += currentThreshold * intensityHistogram[currentThreshold]; // Total histogram intensity
+			totalPoints += intensityHistogram[currentThreshold]; // Total number of data points
 		}
 
-		Sk = 0;
-		N1 = histogram[ 0 ]; // The entry for zero intensity
-		BCV = 0;
-		BCVmax = 0;
-		kStar = 0;
+		totalIntensityBelowThreshold = 0;
+		pointsBelowThreshold = intensityHistogram[0]; // The entry for zero intensity
+		betweenClassVariance = 0;
+		maxBetweenClassVariance = 0;
+		optimalThreshold = 0;
 
 		// Look at each possible threshold value,
 		// calculate the between-class variance, and decide if it's a max
-		for ( k = 1; k < L - 1; k++ )
-		{ // No need to check endpoints k = 0 or k = L-1
-			Sk += k * histogram[ k ];
-			N1 += histogram[ k ];
-
-			// The float casting here is to avoid compiler warning about loss of
-			// precision and
-			// will prevent overflow in the case of large saturated images
-			denom = ( double ) ( N1 ) * ( N - N1 ); // Maximum value of denom is
-													// (N^2)/4 =
-													// approx. 3E10
-
-			if ( denom != 0 )
-			{
-				// Float here is to avoid loss of precision when dividing
-				num = ( ( double ) N1 / N ) * S - Sk; // Maximum value of num =
-														// 255*N =
-														// approx 8E7
-				BCV = ( num * num ) / denom;
+		for (currentThreshold = 1; currentThreshold < totalIntensity - 1; currentThreshold++) {
+			totalIntensityBelowThreshold += currentThreshold * intensityHistogram[currentThreshold];
+			pointsBelowThreshold += intensityHistogram[currentThreshold];
+
+			denominator = (double) (pointsBelowThreshold) * (totalPoints - pointsBelowThreshold);
+
+			if (denominator != 0) {
+				numerator = ((double) pointsBelowThreshold / totalPoints) * totalIntensityOverall - totalIntensityBelowThreshold;
+				betweenClassVariance = (numerator * numerator) / denominator;
+			} else {
+				betweenClassVariance = 0;
 			}
-			else
-				BCV = 0;
 
-			if ( BCV >= BCVmax )
-			{ // Assign the best threshold found so far
-				BCVmax = BCV;
-				kStar = k;
+			if (betweenClassVariance >= maxBetweenClassVariance) {
+				maxBetweenClassVariance = betweenClassVariance;
+				optimalThreshold = currentThreshold;
 			}
 		}
-		// kStar += 1; // Use QTI convention that intensity -> 1 if intensity >=
-		// k
-		// (the algorithm was developed for I-> 1 if I <= k.)
-		return kStar;
+		// optimalThreshold += 1; // Use QTI convention that intensity -> 1 if intensity >= optimalThreshold
+		// (the algorithm was developed for I-> 1 if I <= optimalThreshold.)
+		return optimalThreshold;
 	}
 
 	/**

src/main/java/fiji/plugin/trackmate/features/Defaults.java

@@ -0,0 +1,28 @@
+package fiji.plugin.trackmate.features;
+
+import fiji.plugin.trackmate.Model;
+import fiji.plugin.trackmate.Settings;
+import fiji.plugin.trackmate.gui.displaysettings.DisplaySettings;
+
+import java.util.*;
+
+public class Defaults extends FeatureUtils {
+    private static final String USE_UNIFORM_COLOR_NAME = "Uniform color";
+    private static final String USE_RANDOM_COLOR_NAME = "Random color";
+
+    public Map<String, String> collectFeatureKeys(DisplaySettings.TrackMateObject target, Model model, Settings settings) {
+        final Map<String, String> inverseMap = new HashMap<>();
+        inverseMap.put(USE_UNIFORM_COLOR_NAME, USE_UNIFORM_COLOR_KEY);
+        inverseMap.put(USE_RANDOM_COLOR_NAME, USE_RANDOM_COLOR_KEY);
+
+        // Sort by feature name.
+        final List<String> featureNameList = new ArrayList<>(inverseMap.keySet());
+        featureNameList.sort(null);
+
+        final Map<String, String> featureNames = new LinkedHashMap<>(featureNameList.size());
+        for (final String featureName : featureNameList)
+            featureNames.put(inverseMap.get(featureName), featureName);
+
+        return featureNames;
+    }
+}

src/main/java/fiji/plugin/trackmate/features/Edges.java

@@ -0,0 +1,34 @@
+package fiji.plugin.trackmate.features;
+
+import fiji.plugin.trackmate.Model;
+import fiji.plugin.trackmate.Settings;
+import fiji.plugin.trackmate.features.edges.EdgeAnalyzer;
+import fiji.plugin.trackmate.gui.displaysettings.DisplaySettings;
+
+import java.util.*;
+
+public class Edges extends FeatureUtils {
+
+
+    public Map<String, String> collectFeatureKeys(DisplaySettings.TrackMateObject target, Model model, Settings settings) {
+        final Map<String, String> inverseMap = new HashMap<>();
+        if (model != null) {
+            for (final String featureKey : model.getFeatureModel().getEdgeFeatureNames().keySet())
+                inverseMap.put(model.getFeatureModel().getEdgeFeatureNames().get(featureKey), featureKey);
+        }
+        if (settings != null) {
+            for (final EdgeAnalyzer ea : settings.getEdgeAnalyzers())
+                for (final String featureKey : ea.getFeatureNames().keySet())
+                    inverseMap.put(ea.getFeatureNames().get(featureKey), featureKey);
+        }
+        // Sort by feature name.
+        final List<String> featureNameList = new ArrayList<>(inverseMap.keySet());
+        featureNameList.sort(null);
+
+        final Map<String, String> featureNames = new LinkedHashMap<>(featureNameList.size());
+        for (final String featureName : featureNameList)
+            featureNames.put(inverseMap.get(featureName), featureName);
+
+        return featureNames;
+    }
+}