Review and tidy solr/modules/ltr code

solr/modules/ltr/src/java/org/apache/solr/ltr/CSVFeatureLogger.java

@@ -51,7 +51,7 @@ public String printFeatureVector(LTRScoringQuery.FeatureInfo[] featuresInfo) {
       }
     }
 
-    final String features = (sb.length() > 0 ? sb.substring(0, sb.length() - 1) : "");
+    final String features = (!sb.isEmpty() ? sb.substring(0, sb.length() - 1) : "");
 
     return features;
   }

solr/modules/ltr/src/java/org/apache/solr/ltr/FeatureLogger.java

@@ -23,7 +23,7 @@ public abstract class FeatureLogger {
   public enum FeatureFormat {
     DENSE,
     SPARSE
-  };
+  }
 
   protected final FeatureFormat featureFormat;
 

solr/modules/ltr/src/java/org/apache/solr/ltr/LTRScoringQuery.java

@@ -232,7 +232,7 @@ public ModelWeight createWeight(IndexSearcher searcher, ScoreMode scoreMode, flo
         extractedFeatureWeights[i++] = fw;
       }
       for (final Feature f : modelFeatures) {
-        // we can lookup by featureid because all features will be extracted
+        // we can look up by featureid because all features will be extracted
         modelFeaturesWeights[j++] = extractedFeatureWeights[f.getIndex()];
       }
     } else {
@@ -248,10 +248,9 @@ private void createWeights(
       IndexSearcher searcher,
       boolean needsScores,
       List<Feature.FeatureWeight> featureWeights,
-      Collection<Feature> features)
-      throws IOException {
+      Collection<Feature> features) {
     final SolrQueryRequest req = getRequest();
-    // since the feature store is a linkedhashmap order is preserved
+    // since the feature store is a linked hashmap order is preserved
     for (final Feature f : features) {
       try {
         Feature.FeatureWeight fw = f.createWeight(searcher, needsScores, req, originalQuery, efi);
@@ -465,7 +464,7 @@ public ScorerSupplier scorerSupplier(LeafReaderContext context) throws IOExcepti
     public ModelScorer modelScorer(LeafReaderContext context) throws IOException {
 
       final List<Feature.FeatureWeight.FeatureScorer> featureScorers =
-          new ArrayList<Feature.FeatureWeight.FeatureScorer>(extractedFeatureWeights.length);
+          new ArrayList<>(extractedFeatureWeights.length);
       for (final Feature.FeatureWeight featureWeight : extractedFeatureWeights) {
         final Feature.FeatureWeight.FeatureScorer scorer = featureWeight.featureScorer(context);
         if (scorer != null) {

solr/modules/ltr/src/java/org/apache/solr/ltr/LTRThreadModule.java

@@ -155,7 +155,7 @@ public void acquireLTRSemaphore() throws InterruptedException {
     ltrSemaphore.acquire();
   }
 
-  public void releaseLTRSemaphore() throws InterruptedException {
+  public void releaseLTRSemaphore() {
     ltrSemaphore.release();
   }
 

solr/modules/ltr/src/java/org/apache/solr/ltr/feature/Feature.java

@@ -375,7 +375,7 @@ public DocIdSetIterator iterator() {
       }
 
       // Currently (Q1 2021) we intentionally don't delegate twoPhaseIterator()
-      // because it doesn't always work and we don't yet know why, please see
+      // because it doesn't always work, and we don't yet know why, please see
       // SOLR-15071 for more details.
 
       @Override

solr/modules/ltr/src/java/org/apache/solr/ltr/feature/FieldLengthFeature.java

@@ -82,7 +82,7 @@ protected void validate() throws FeatureException {
   }
 
   /** Decodes the norm value, assuming it is a single byte. */
-  private final float decodeNorm(long norm) {
+  private float decodeNorm(long norm) {
     return NORM_TABLE[(int) (norm & 0xFF)]; // & 0xFF maps negative bytes to
     // positive above 127
   }

solr/modules/ltr/src/java/org/apache/solr/ltr/feature/FieldValueFeature.java

@@ -127,8 +127,8 @@ public FieldValueFeatureWeight(
     }
 
     /**
-     * Override this method in sub classes that wish to use not an absolute time but an interval
-     * such as document age or remaining shelf life relative to a specific date or relative to now.
+     * Override this method in subclasses that wish to use not an absolute time but an interval such
+     * as document age or remaining shelf life relative to a specific date or relative to now.
      *
      * @param val value of the field
      * @return value after transformation
@@ -179,14 +179,12 @@ public FeatureScorer featureScorer(LeafReaderContext context) throws IOException
     /** A FeatureScorer that reads the stored value for a field */
     public class FieldValueFeatureScorer extends FeatureScorer {
 
-      private final LeafReaderContext context;
       private final StoredFields storedFields;
 
       public FieldValueFeatureScorer(
           FeatureWeight weight, LeafReaderContext context, DocIdSetIterator itr)
           throws IOException {
         super(weight, itr);
-        this.context = context;
         this.storedFields = (context == null ? null : context.reader().storedFields());
       }
 
@@ -205,7 +203,7 @@ public float score() throws IOException {
           } else {
             final String string = indexableField.stringValue();
             if (string.length() == 1) {
-              // boolean values in the index are encoded with the
+              // boolean values in the index are encoded with
               // a single char contained in TRUE_TOKEN or FALSE_TOKEN
               // (see BoolField)
               if (string.charAt(0) == BoolField.TRUE_TOKEN[0]) {
@@ -217,8 +215,7 @@ public float score() throws IOException {
             }
           }
         } catch (final IOException e) {
-          throw new FeatureException(
-              e.toString() + ": " + "Unable to extract feature for " + name, e);
+          throw new FeatureException(e + ": " + "Unable to extract feature for " + name, e);
         }
         return getDefaultValue();
       }
@@ -320,7 +317,7 @@ public float score() throws IOException {
       private float readSortedDocValues(BytesRef bytesRef) {
         String string = bytesRef.utf8ToString();
         if (string.length() == 1) {
-          // boolean values in the index are encoded with the
+          // boolean values in the index are encoded with
           // a single char contained in TRUE_TOKEN or FALSE_TOKEN
           // (see BoolField)
           if (string.charAt(0) == BoolField.TRUE_TOKEN[0]) {

solr/modules/ltr/src/java/org/apache/solr/ltr/feature/ValueFeature.java

@@ -43,7 +43,7 @@
  * differently if the search came from a mobile device, or maybe you want to use your external query
  * intent system as a feature. In the rerank request you can pass in rq={... efi.userFromMobile=1},
  * and the above feature will return 1 for all the docs for that request. If required is set to
- * true, the request will return an error since you failed to pass in the efi, otherwise if will
+ * true, the request will return an error since you failed to pass in the efi, otherwise it will
  * just skip the feature and use a default value of 0 instead.
  */
 public class ValueFeature extends Feature {
@@ -64,7 +64,7 @@ public void setValue(Object value) {
     } else if (value instanceof Double) {
       configValue = ((Double) value).floatValue();
     } else if (value instanceof Float) {
-      configValue = ((Float) value).floatValue();
+      configValue = (Float) value;
     } else if (value instanceof Integer) {
       configValue = ((Integer) value).floatValue();
     } else if (value instanceof Long) {

solr/modules/ltr/src/java/org/apache/solr/ltr/interleaving/LTRInterleavingQuery.java

@@ -24,20 +24,20 @@
 import org.apache.solr.search.RankQuery;
 
 /**
- * A learning to rank Query with Interleaving, will incapsulate two models, and delegate to it the
+ * A learning to rank Query with Interleaving, will encapsulate two models, and delegate to it the
  * rescoring of the documents.
  */
 public class LTRInterleavingQuery extends LTRQuery {
   private final LTRInterleavingScoringQuery[] rerankingQueries;
-  private final Interleaving interlavingAlgorithm;
+  private final Interleaving interleavingAlgorithm;
 
   public LTRInterleavingQuery(
       Interleaving interleavingAlgorithm,
       LTRInterleavingScoringQuery[] rerankingQueries,
       int rerankDocs) {
     super(null, rerankDocs, new LTRInterleavingRescorer(interleavingAlgorithm, rerankingQueries));
     this.rerankingQueries = rerankingQueries;
-    this.interlavingAlgorithm = interleavingAlgorithm;
+    this.interleavingAlgorithm = interleavingAlgorithm;
   }
 
   @Override
@@ -79,7 +79,7 @@ public String toString(String field) {
 
   @Override
   protected Query rewrite(Query rewrittenMainQuery) throws IOException {
-    return new LTRInterleavingQuery(interlavingAlgorithm, rerankingQueries, reRankDocs)
+    return new LTRInterleavingQuery(interleavingAlgorithm, rerankingQueries, reRankDocs)
         .wrap(rewrittenMainQuery);
   }
 }

solr/modules/ltr/src/java/org/apache/solr/ltr/model/LTRScoringModel.java

@@ -201,7 +201,7 @@ public int hashCode() {
     return hashCode;
   }
 
-  private final int calculateHashCode() {
+  private int calculateHashCode() {
     final int prime = 31;
     int result = 1;
     result = (prime * result) + Objects.hashCode(features);

solr/modules/ltr/src/java/org/apache/solr/ltr/model/LinearModel.java

@@ -151,8 +151,7 @@ public Explanation explain(
       index++;
     }
 
-    return Explanation.match(
-        finalScore, toString() + " model applied to features, sum of:", details);
+    return Explanation.match(finalScore, this + " model applied to features, sum of:", details);
   }
 
   @Override

solr/modules/ltr/src/java/org/apache/solr/ltr/model/MultipleAdditiveTreesModel.java

@@ -116,6 +116,10 @@ public class MultipleAdditiveTreesModel extends LTRScoringModel {
 
   private boolean isNullSameAsZero = true;
 
+  public void setIsNullSameAsZero(boolean nullSameAsZero) {
+    isNullSameAsZero = nullSameAsZero;
+  }
+
   private RegressionTree createRegressionTree(Map<String, Object> map) {
     final RegressionTree rt = new RegressionTree();
     if (map != null) {
@@ -132,10 +136,6 @@ private RegressionTreeNode createRegressionTreeNode(Map<String, Object> map) {
     return rtn;
   }
 
-  public void setIsNullSameAsZero(boolean nullSameAsZero) {
-    isNullSameAsZero = nullSameAsZero;
-  }
-
   public class RegressionTreeNode {
     private static final float NODE_SPLIT_SLACK = 1E-6f;
 
@@ -197,7 +197,7 @@ public String toString() {
         sb.append(value);
       } else {
         sb.append("(feature=").append(feature);
-        sb.append(",threshold=").append(threshold.floatValue() - NODE_SPLIT_SLACK);
+        sb.append(",threshold=").append(threshold - NODE_SPLIT_SLACK);
         if (missing != null) {
           sb.append(",missing=").append(missing);
         }
@@ -231,9 +231,9 @@ public void setRoot(Object root) {
 
     public float score(float[] featureVector) {
       if (isNullSameAsZero) {
-        return weight.floatValue() * scoreNode(featureVector, root);
+        return weight * scoreNode(featureVector, root);
       } else {
-        return weight.floatValue() * scoreNodeWithNullSupport(featureVector, root);
+        return weight * scoreNodeWithNullSupport(featureVector, root);
       }
     }
 
@@ -500,8 +500,7 @@ public Explanation explain(
       index++;
     }
 
-    return Explanation.match(
-        finalScore, toString() + " model applied to features, sum of:", details);
+    return Explanation.match(finalScore, this + " model applied to features, sum of:", details);
   }
 
   @Override

solr/modules/ltr/src/java/org/apache/solr/ltr/model/NeuralNetworkModel.java

@@ -112,11 +112,11 @@ protected interface Activation {
   }
 
   public interface Layer {
-    public float[] calculateOutput(float[] inputVec);
+    float[] calculateOutput(float[] inputVec);
 
-    public int validate(int inputDim) throws ModelException;
+    int validate(int inputDim) throws ModelException;
 
-    public String describe();
+    String describe();
   }
 
   public class DefaultLayer implements Layer {
@@ -235,19 +235,19 @@ public int validate(int inputDim) throws ModelException {
             "Dimension mismatch in model \""
                 + name
                 + "\". Layer "
-                + Integer.toString(this.layerID)
+                + this.layerID
                 + " has "
-                + Integer.toString(this.numUnits)
+                + this.numUnits
                 + " bias weights but "
-                + Integer.toString(this.matrixRows)
+                + this.matrixRows
                 + " weight matrix rows.");
       }
       if (this.activation == null) {
         throw new ModelException(
             "Invalid activation function (\""
                 + this.activationStr
                 + "\") in layer "
-                + Integer.toString(this.layerID)
+                + this.layerID
                 + " of model \""
                 + name
                 + "\".");
@@ -258,23 +258,23 @@ public int validate(int inputDim) throws ModelException {
               "Dimension mismatch in model \""
                   + name
                   + "\". The input has "
-                  + Integer.toString(inputDim)
+                  + inputDim
                   + " features, but the weight matrix for layer 0 has "
-                  + Integer.toString(this.matrixCols)
+                  + this.matrixCols
                   + " columns.");
         } else {
           throw new ModelException(
               "Dimension mismatch in model \""
                   + name
                   + "\". The weight matrix for layer "
-                  + Integer.toString(this.layerID - 1)
+                  + (this.layerID - 1)
                   + " has "
-                  + Integer.toString(inputDim)
+                  + inputDim
                   + " rows, but the "
                   + "weight matrix for layer "
-                  + Integer.toString(this.layerID)
+                  + this.layerID
                   + " has "
-                  + Integer.toString(this.matrixCols)
+                  + this.matrixCols
                   + " columns.");
         }
       }
@@ -285,9 +285,9 @@ public int validate(int inputDim) throws ModelException {
     public String describe() {
       final StringBuilder sb = new StringBuilder();
       sb.append("(matrix=")
-          .append(Integer.toString(this.matrixRows))
+          .append(this.matrixRows)
           .append('x')
-          .append(Integer.toString(this.matrixCols))
+          .append(this.matrixCols)
           .append(",activation=")
           .append(this.activationStr)
           .append(")");
@@ -338,7 +338,7 @@ protected void validate() throws ModelException {
           "The output matrix for model \""
               + name
               + "\" has "
-              + Integer.toString(inputDim)
+              + inputDim
               + " rows, but should only have one.");
     }
   }

solr/modules/ltr/src/java/org/apache/solr/ltr/model/WrapperModel.java

@@ -165,10 +165,6 @@ public Explanation getNormalizerExplanation(Explanation e, int idx) {
 
   @Override
   public String toString() {
-    final StringBuilder sb = new StringBuilder(getClass().getSimpleName());
-    sb.append("(name=").append(getName());
-    sb.append(",model=(").append(model.toString()).append(")");
-
-    return sb.toString();
+    return getClass().getSimpleName() + "(name=" + getName() + ",model=(" + model.toString() + ")";
   }
 }

solr/modules/ltr/src/java/org/apache/solr/ltr/norm/Normalizer.java

@@ -35,7 +35,7 @@ public abstract class Normalizer {
 
   public Explanation explain(Explanation explain) {
     final float normalized = normalize(explain.getValue().floatValue());
-    final String explainDesc = "normalized using " + toString();
+    final String explainDesc = "normalized using " + this;
 
     return Explanation.match(normalized, explainDesc, explain);
   }

solr/modules/ltr/src/java/org/apache/solr/ltr/response/transform/LTRFeatureLoggerTransformerFactory.java

@@ -486,7 +486,7 @@ public Explanation explain(
         float finalScore,
         List<Explanation> featureExplanations) {
       return Explanation.match(
-          finalScore, toString() + " logging model, used only for logging the features");
+          finalScore, this + " logging model, used only for logging the features");
     }
   }
 }

solr/modules/ltr/src/java/org/apache/solr/ltr/search/LTRQParserPlugin.java

@@ -99,9 +99,9 @@ public QParser createParser(
   }
 
   /**
-   * Given a set of local SolrParams, extract all of the efi.key=value params into a map
+   * Given a set of local SolrParams, extract all the efi.key=value params into a map
    *
-   * @param localParams Local request parameters that might conatin efi params
+   * @param localParams Local request parameters that might contain efi params
    * @return Map of efi params, where the key is the name of the efi param, and the value is the
    *     value of the efi param
    */

solr/modules/ltr/src/java/org/apache/solr/ltr/search/LTRQuery.java

@@ -26,7 +26,7 @@
 import org.apache.solr.search.RankQuery;
 
 /**
- * A learning to rank Query, will incapsulate a learning to rank model, and delegate to it the
+ * A learning to rank Query, will encapsulate a learning to rank model, and delegate to it the
  * rescoring of the documents.
  */
 public class LTRQuery extends AbstractReRankQuery {