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SOLR-10174: reduce makeFeatureWeights code duplication in tests

This commit is contained in:
Christine Poerschke 2017-06-08 10:15:54 +01:00
parent b0020634ac
commit cf9b70b253
3 changed files with 17 additions and 27 deletions
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20
solr/contrib/ltr/src/test/org/apache/solr/ltr/TestLTRScoringQuery.java
View File

@ -89,16 +89,6 @@ public class TestLTRScoringQuery extends LuceneTestCase {
return features;
}
private static Map<String,Object> makeFeatureWeights(List<Feature> features) {
final Map<String,Object> nameParams = new HashMap<String,Object>();
final HashMap<String,Double> modelWeights = new HashMap<String,Double>();
for (final Feature feat : features) {
modelWeights.put(feat.getName(), 0.1);
}
nameParams.put("weights", modelWeights);
return nameParams;
}
private LTRScoringQuery.ModelWeight performQuery(TopDocs hits,
IndexSearcher searcher, int docid, LTRScoringQuery model) throws IOException,
ModelException {
@ -132,7 +122,7 @@ public class TestLTRScoringQuery extends LuceneTestCase {
Collections.nCopies(features.size(),IdentityNormalizer.INSTANCE));
final List<Feature> allFeatures = makeFeatures(
new int[] {0, 1, 2, 3, 4, 5, 6, 7, 8, 9});
final Map<String,Object> modelParams = makeFeatureWeights(features);
final Map<String,Object> modelParams = TestLinearModel.makeFeatureWeights(features);
final LTRScoringModel algorithm1 = TestLinearModel.createLinearModel(
"testModelName",
@ -222,7 +212,7 @@ public class TestLTRScoringQuery extends LuceneTestCase {
Collections.nCopies(features.size(),IdentityNormalizer.INSTANCE));
LTRScoringModel ltrScoringModel = TestLinearModel.createLinearModel("test",
features, norms, "test", allFeatures,
makeFeatureWeights(features));
TestLinearModel.makeFeatureWeights(features));
LTRScoringQuery.ModelWeight modelWeight = performQuery(hits, searcher,
hits.scoreDocs[0].doc, new LTRScoringQuery(ltrScoringModel));
@ -248,7 +238,7 @@ public class TestLTRScoringQuery extends LuceneTestCase {
new ArrayList<Normalizer>(
Collections.nCopies(features.size(),IdentityNormalizer.INSTANCE));
ltrScoringModel = TestLinearModel.createLinearModel("test",
features, norms, "test", allFeatures, makeFeatureWeights(features));
features, norms, "test", allFeatures, TestLinearModel.makeFeatureWeights(features));
modelWeight = performQuery(hits, searcher, hits.scoreDocs[0].doc,
new LTRScoringQuery(ltrScoringModel));
@ -268,7 +258,7 @@ public class TestLTRScoringQuery extends LuceneTestCase {
Collections.nCopies(features.size(),IdentityNormalizer.INSTANCE));
try {
ltrScoringModel = TestLinearModel.createLinearModel("test",
features, norms, "test", allFeatures, makeFeatureWeights(features));
features, norms, "test", allFeatures, TestLinearModel.makeFeatureWeights(features));
fail("unexpectedly got here instead of catching "+expectedModelException);
modelWeight = performQuery(hits, searcher, hits.scoreDocs[0].doc,
new LTRScoringQuery(ltrScoringModel));
@ -301,7 +291,7 @@ public class TestLTRScoringQuery extends LuceneTestCase {
Collections.nCopies(features.size(),norm));
final LTRScoringModel normMeta = TestLinearModel.createLinearModel("test",
features, norms, "test", allFeatures,
makeFeatureWeights(features));
TestLinearModel.makeFeatureWeights(features));
modelWeight = performQuery(hits, searcher, hits.scoreDocs[0].doc,
new LTRScoringQuery(normMeta));

14
solr/contrib/ltr/src/test/org/apache/solr/ltr/TestSelectiveWeightCreation.java
View File

@ -70,16 +70,6 @@ public class TestSelectiveWeightCreation extends TestRerankBase {
return features;
}
private static Map<String,Object> makeFeatureWeights(List<Feature> features) {
final Map<String,Object> nameParams = new HashMap<String,Object>();
final HashMap<String,Double> modelWeights = new HashMap<String,Double>();
for (final Feature feat : features) {
modelWeights.put(feat.getName(), 0.1);
}
nameParams.put("weights", modelWeights);
return nameParams;
}
private LTRScoringQuery.ModelWeight performQuery(TopDocs hits,
IndexSearcher searcher, int docid, LTRScoringQuery model) throws IOException,
ModelException {
@ -168,7 +158,7 @@ public class TestSelectiveWeightCreation extends TestRerankBase {
// when features are NOT requested in the response, only the modelFeature weights should be created
final LTRScoringModel ltrScoringModel1 = TestLinearModel.createLinearModel("test",
features, norms, "test", allFeatures,
makeFeatureWeights(features));
TestLinearModel.makeFeatureWeights(features));
LTRScoringQuery.ModelWeight modelWeight = performQuery(hits, searcher,
hits.scoreDocs[0].doc, new LTRScoringQuery(ltrScoringModel1, false)); // features not requested in response
LTRScoringQuery.FeatureInfo[] featuresInfo = modelWeight.getFeaturesInfo();
@ -185,7 +175,7 @@ public class TestSelectiveWeightCreation extends TestRerankBase {
// when features are requested in the response, weights should be created for all features
final LTRScoringModel ltrScoringModel2 = TestLinearModel.createLinearModel("test",
features, norms, "test", allFeatures,
makeFeatureWeights(features));
TestLinearModel.makeFeatureWeights(features));
modelWeight = performQuery(hits, searcher,
hits.scoreDocs[0].doc, new LTRScoringQuery(ltrScoringModel2, true)); // features requested in response
featuresInfo = modelWeight.getFeaturesInfo();

10
solr/contrib/ltr/src/test/org/apache/solr/ltr/model/TestLinearModel.java
View File

@ -45,6 +45,16 @@ public class TestLinearModel extends TestRerankBase {
return model;
}
public static Map<String,Object> makeFeatureWeights(List<Feature> features) {
final Map<String,Object> nameParams = new HashMap<String,Object>();
final HashMap<String,Double> modelWeights = new HashMap<String,Double>();
for (final Feature feat : features) {
modelWeights.put(feat.getName(), 0.1);
}
nameParams.put("weights", modelWeights);
return nameParams;
}
static ManagedModelStore store = null;
static FeatureStore fstore = null;