changeset 157:d6c1556fadd0 refactors

Default is actually Manhattan, not Euclidean (it just looks like squared-Euclidean for energy vectors). Add Euclidean as another alternative.

--- a/src/DistanceMetric.cpp	Thu Jan 29 10:25:47 2015 +0000
+++ b/src/DistanceMetric.cpp	Thu Jan 29 10:55:24 2015 +0000
@@ -62,13 +62,21 @@
         if (d > 1.0) d = 1.0;
         
         return d; // normalisation param ignored
+
     }
 
-    // Euclidean
-    
-    for (int i = 0; i < featureSize; i++) {
-        d += fabs(f1[i] - f2[i]);
-        sum += fabs(f1[i]) + fabs(f2[i]);
+    if (m_params.metric == Manhattan) {
+        for (int i = 0; i < featureSize; i++) {
+            d += fabs(f1[i] - f2[i]);
+            sum += fabs(f1[i]) + fabs(f2[i]);
+        }
+    } else {
+        // Euclidean
+        for (int i = 0; i < featureSize; i++) {
+            d += (f1[i] - f2[i]) * (f1[i] - f2[i]);
+            sum += fabs(f1[i]) + fabs(f2[i]);
+        }
+        d = sqrt(d);
     }
 
     double noise = 1e-3 * featureSize;

--- a/src/DistanceMetric.h	Thu Jan 29 10:25:47 2015 +0000
+++ b/src/DistanceMetric.h	Thu Jan 29 10:55:24 2015 +0000
@@ -24,6 +24,12 @@
 public:
     enum Metric {
 
+        /** Calculate the Manhattan distance between feature
+         *  vectors. If the vectors contain energy, as the default
+         *  MATCH feature does, this could be considered as a squared
+         *  Euclidean distance metric. */
+        Manhattan,
+
         /** Calculate the Euclidean distance between feature vectors. */
         Euclidean,
 
@@ -60,7 +66,7 @@
     struct Parameters {
 
         Parameters() :
-            metric(Euclidean),
+            metric(Manhattan),
             norm(NormaliseDistanceToLogSum),
             noise(AddNoise)
         {}
@@ -72,11 +78,10 @@
     
     DistanceMetric(Parameters params);
     
-    /** Calculates the Manhattan distance between two vectors, with an
-     *  optional normalisation by the combined values in the
-     *  vectors. Since the vectors contain energy, this could be
-     *  considered as a squared Euclidean distance metric. Note that
-     *  normalisation assumes the values are all non-negative.
+    /** Calculates the distance in some metric between two vectors,
+     *  with an optional normalisation by the combined values in the
+     *  vectors. Note that normalisation assumes the values are all
+     *  non-negative.
      *
      *  @param f1 one of the vectors involved in the distance calculation
      *  @param f2 one of the vectors involved in the distance calculation

--- a/src/MatchVampPlugin.cpp	Thu Jan 29 10:25:47 2015 +0000
+++ b/src/MatchVampPlugin.cpp	Thu Jan 29 10:55:24 2015 +0000
@@ -219,11 +219,12 @@
     desc.name = "Distance metric";
     desc.description = "Metric for distance calculations.";
     desc.minValue = 0;
-    desc.maxValue = 1;
+    desc.maxValue = 2;
     desc.defaultValue = (int)m_defaultDParams.metric;
     desc.isQuantized = true;
     desc.quantizeStep = 1;
     desc.valueNames.clear();
+    desc.valueNames.push_back("Manhattan");
     desc.valueNames.push_back("Euclidean");
     desc.valueNames.push_back("Cosine");
     list.push_back(desc);