From 6126ba35bbd5271b90e08947d06880993f0e7cf8 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?J=C3=A9r=C3=B4me=20Euzenat?= <Jerome.Euzenat@inria.fr>
Date: Mon, 30 Aug 2010 13:08:20 +0000
Subject: [PATCH] - better documented the Hungarian alorithm guard
---
.../exmo/align/impl/DistanceAlignment.java | 29 ++++++++++---------
1 file changed, 15 insertions(+), 14 deletions(-)
diff --git a/src/fr/inrialpes/exmo/align/impl/DistanceAlignment.java b/src/fr/inrialpes/exmo/align/impl/DistanceAlignment.java
index 4251e75a..99864d18 100644
--- a/src/fr/inrialpes/exmo/align/impl/DistanceAlignment.java
+++ b/src/fr/inrialpes/exmo/align/impl/DistanceAlignment.java
@@ -238,6 +238,7 @@ public abstract class DistanceAlignment extends ObjectAlignment implements Align
for ( Object ob : ontology2().getClasses() ) {
class2[j++] = ob;
}
+ // ival indicates if all cells have the same value, or different (-1)
double ival = sim.getClassSimilarity(class1[0],class2[0]);
for( i = 0; i < nbclasses1; i++ ){
for( j = 0; j < nbclasses2; j++ ){
@@ -247,22 +248,22 @@ public abstract class DistanceAlignment extends ObjectAlignment implements Align
}
}
// Pass it to the algorithm
- if ( ival == -1. ) {
- int[][] result = HungarianAlgorithm.hgAlgorithm( matrix, "max" );
- // Extract the result
- for( i=0; i < result.length ; i++ ){
- // The matrix has been destroyed
- double val;
- if ( sim.getSimilarity() ) val = sim.getClassSimilarity(class1[result[i][0]],class2[result[i][1]]);
- else val = 1 - sim.getClassSimilarity(class1[result[i][0]],class2[result[i][1]]);
- // JE: here using strict-> is a very good idea.
- // it means that alignments with 0. similarity
- // will be excluded from the best match.
- if( val > threshold ){
- addCell( new ObjectCell( (String)null, class1[result[i][0]], class2[result[i][1]], BasicRelation.createRelation("="), val ) );
+ if ( ival == -1. ) { // if values are the same, return an empty alignment
+ int[][] result = HungarianAlgorithm.hgAlgorithm( matrix, "max" );
+ // Extract the result
+ for( i=0; i < result.length ; i++ ){
+ // The matrix has been destroyed
+ double val;
+ if ( sim.getSimilarity() ) val = sim.getClassSimilarity(class1[result[i][0]],class2[result[i][1]]);
+ else val = 1 - sim.getClassSimilarity(class1[result[i][0]],class2[result[i][1]]);
+ // JE: here using strict-> is a very good idea.
+ // it means that correspondences with 0. similarity
+ // will be excluded from the best match.
+ if( val > threshold ){
+ addCell( new ObjectCell( (String)null, class1[result[i][0]], class2[result[i][1]], BasicRelation.createRelation("="), val ) );
+ }
}
}
- }
} catch (AlignmentException alex) { alex.printStackTrace(); }
catch (OntowrapException owex) { owex.printStackTrace(); }
// For properties
--
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