LengthNorm() public abstract method

Computes the normalization value for a field given the total number of terms contained in a field. These values, together with field boosts, are stored in an index and multipled into scores for hits on each field by the search code.

Matches in longer fields are less precise, so implementations of this method usually return smaller values when numTokens is large, and larger values when numTokens is small.

Note that the return values are computed under Lucene.Net.Index.IndexWriter.AddDocument(Lucene.Net.Documents.Document) and then stored using EncodeNorm(float). Thus they have limited precision, and documents must be re-indexed if this method is altered.

public abstract LengthNorm ( System fieldName, int numTokens ) : float
fieldName System the name of the field ///
numTokens int the total number of tokens contained in fields named /// fieldName of doc. ///
return float
コード例 #1
0
        public virtual void  TestKnownSetOfDocuments()
        {
            System.String test1 = "eating chocolate in a computer lab";                                             //6 terms
            System.String test2 = "computer in a computer lab";                                                     //5 terms
            System.String test3 = "a chocolate lab grows old";                                                      //5 terms
            System.String test4 = "eating chocolate with a chocolate lab in an old chocolate colored computer lab"; //13 terms
            System.Collections.IDictionary test4Map = new System.Collections.Hashtable();
            test4Map["chocolate"] = 3;
            test4Map["lab"]       = 2;
            test4Map["eating"]    = 1;
            test4Map["computer"]  = 1;
            test4Map["with"]      = 1;
            test4Map["a"]         = 1;
            test4Map["colored"]   = 1;
            test4Map["in"]        = 1;
            test4Map["an"]        = 1;
            test4Map["computer"]  = 1;
            test4Map["old"]       = 1;

            Document testDoc1 = new Document();

            SetupDoc(testDoc1, test1);
            Document testDoc2 = new Document();

            SetupDoc(testDoc2, test2);
            Document testDoc3 = new Document();

            SetupDoc(testDoc3, test3);
            Document testDoc4 = new Document();

            SetupDoc(testDoc4, test4);

            Directory dir = new MockRAMDirectory();

            try
            {
                IndexWriter writer = new IndexWriter(dir, new SimpleAnalyzer(), true, IndexWriter.MaxFieldLength.LIMITED);
                Assert.IsTrue(writer != null);
                writer.AddDocument(testDoc1);
                writer.AddDocument(testDoc2);
                writer.AddDocument(testDoc3);
                writer.AddDocument(testDoc4);
                writer.Close();
                IndexSearcher knownSearcher = new IndexSearcher(dir);
                TermEnum      termEnum      = knownSearcher.reader_ForNUnit.Terms();
                TermDocs      termDocs      = knownSearcher.reader_ForNUnit.TermDocs();
                //System.out.println("Terms: " + termEnum.size() + " Orig Len: " + termArray.length);

                Similarity sim = knownSearcher.GetSimilarity();
                while (termEnum.Next() == true)
                {
                    Term term = termEnum.Term();
                    //System.out.println("Term: " + term);
                    termDocs.Seek(term);
                    while (termDocs.Next())
                    {
                        int docId = termDocs.Doc();
                        int freq  = termDocs.Freq();
                        //System.out.println("Doc Id: " + docId + " freq " + freq);
                        TermFreqVector vector = knownSearcher.reader_ForNUnit.GetTermFreqVector(docId, "field");
                        float          tf     = sim.Tf(freq);
                        float          idf    = sim.Idf(term, knownSearcher);
                        //float qNorm = sim.queryNorm()
                        //This is fine since we don't have stop words
                        float lNorm = sim.LengthNorm("field", vector.GetTerms().Length);
                        //float coord = sim.coord()
                        //System.out.println("TF: " + tf + " IDF: " + idf + " LenNorm: " + lNorm);
                        Assert.IsTrue(vector != null);
                        System.String[] vTerms = vector.GetTerms();
                        int[]           freqs  = vector.GetTermFrequencies();
                        for (int i = 0; i < vTerms.Length; i++)
                        {
                            if (term.Text().Equals(vTerms[i]))
                            {
                                Assert.IsTrue(freqs[i] == freq);
                            }
                        }
                    }
                    //System.out.println("--------");
                }
                Query      query = new TermQuery(new Term("field", "chocolate"));
                ScoreDoc[] hits  = knownSearcher.Search(query, null, 1000).scoreDocs;
                //doc 3 should be the first hit b/c it is the shortest match
                Assert.IsTrue(hits.Length == 3);
                float score = hits[0].score;

                /*System.out.println("Hit 0: " + hits.id(0) + " Score: " + hits.score(0) + " String: " + hits.doc(0).toString());
                 * System.out.println("Explain: " + knownSearcher.explain(query, hits.id(0)));
                 * System.out.println("Hit 1: " + hits.id(1) + " Score: " + hits.score(1) + " String: " + hits.doc(1).toString());
                 * System.out.println("Explain: " + knownSearcher.explain(query, hits.id(1)));
                 * System.out.println("Hit 2: " + hits.id(2) + " Score: " + hits.score(2) + " String: " +  hits.doc(2).toString());
                 * System.out.println("Explain: " + knownSearcher.explain(query, hits.id(2)));*/
                Assert.IsTrue(hits[0].doc == 2);
                Assert.IsTrue(hits[1].doc == 3);
                Assert.IsTrue(hits[2].doc == 0);
                TermFreqVector vector2 = knownSearcher.reader_ForNUnit.GetTermFreqVector(hits[1].doc, "field");
                Assert.IsTrue(vector2 != null);
                //System.out.println("Vector: " + vector);
                System.String[] terms  = vector2.GetTerms();
                int[]           freqs2 = vector2.GetTermFrequencies();
                Assert.IsTrue(terms != null && terms.Length == 10);
                for (int i = 0; i < terms.Length; i++)
                {
                    System.String term = terms[i];
                    //System.out.println("Term: " + term);
                    int freq = freqs2[i];
                    Assert.IsTrue(test4.IndexOf(term) != -1);
                    System.Int32 freqInt = -1;
                    try
                    {
                        freqInt = (System.Int32)test4Map[term];
                    }
                    catch (Exception)
                    {
                        Assert.IsTrue(false);
                    }
                    Assert.IsTrue(freqInt == freq);
                }
                SortedTermVectorMapper mapper = new SortedTermVectorMapper(new TermVectorEntryFreqSortedComparator());
                knownSearcher.reader_ForNUnit.GetTermFreqVector(hits[1].doc, mapper);
                System.Collections.Generic.SortedDictionary <object, object> vectorEntrySet = mapper.GetTermVectorEntrySet();
                Assert.IsTrue(vectorEntrySet.Count == 10, "mapper.getTermVectorEntrySet() Size: " + vectorEntrySet.Count + " is not: " + 10);
                TermVectorEntry last = null;
                foreach (TermVectorEntry tve in vectorEntrySet.Keys)
                {
                    if (tve != null && last != null)
                    {
                        Assert.IsTrue(last.GetFrequency() >= tve.GetFrequency(), "terms are not properly sorted");
                        System.Int32 expectedFreq = (System.Int32)test4Map[tve.GetTerm()];
                        //we expect double the expectedFreq, since there are two fields with the exact same text and we are collapsing all fields
                        Assert.IsTrue(tve.GetFrequency() == 2 * expectedFreq, "Frequency is not correct:");
                    }
                    last = tve;
                }

                FieldSortedTermVectorMapper fieldMapper = new FieldSortedTermVectorMapper(new TermVectorEntryFreqSortedComparator());
                knownSearcher.reader_ForNUnit.GetTermFreqVector(hits[1].doc, fieldMapper);
                System.Collections.IDictionary map = fieldMapper.GetFieldToTerms();
                Assert.IsTrue(map.Count == 2, "map Size: " + map.Count + " is not: " + 2);
                vectorEntrySet = (System.Collections.Generic.SortedDictionary <Object, Object>)map["field"];
                Assert.IsTrue(vectorEntrySet != null, "vectorEntrySet is null and it shouldn't be");
                Assert.IsTrue(vectorEntrySet.Count == 10, "vectorEntrySet Size: " + vectorEntrySet.Count + " is not: " + 10);
                knownSearcher.Close();
            }
            catch (System.IO.IOException e)
            {
                System.Console.Error.WriteLine(e.StackTrace);
                Assert.IsTrue(false);
            }
        }
コード例 #2
0
ファイル: TestTermVectors.cs プロジェクト: yonder/mono
        public virtual void  TestKnownSetOfDocuments()
        {
            System.String[] termArray = new System.String[] { "eating", "chocolate", "in", "a", "computer", "lab", "grows", "old", "colored", "with", "an" };
            System.String   test1     = "eating chocolate in a computer lab";                                             //6 terms
            System.String   test2     = "computer in a computer lab";                                                     //5 terms
            System.String   test3     = "a chocolate lab grows old";                                                      //5 terms
            System.String   test4     = "eating chocolate with a chocolate lab in an old chocolate colored computer lab"; //13 terms
            System.Collections.IDictionary test4Map = new System.Collections.Hashtable();
            test4Map["chocolate"] = 3;
            test4Map["lab"]       = 2;
            test4Map["eating"]    = 1;
            test4Map["computer"]  = 1;
            test4Map["with"]      = 1;
            test4Map["a"]         = 1;
            test4Map["colored"]   = 1;
            test4Map["in"]        = 1;
            test4Map["an"]        = 1;
            test4Map["computer"]  = 1;
            test4Map["old"]       = 1;

            Document testDoc1 = new Document();

            SetupDoc(testDoc1, test1);
            Document testDoc2 = new Document();

            SetupDoc(testDoc2, test2);
            Document testDoc3 = new Document();

            SetupDoc(testDoc3, test3);
            Document testDoc4 = new Document();

            SetupDoc(testDoc4, test4);

            Directory dir = new RAMDirectory();

            try
            {
                IndexWriter writer = new IndexWriter(dir, new SimpleAnalyzer(), true);
                Assert.IsTrue(writer != null);
                writer.AddDocument(testDoc1);
                writer.AddDocument(testDoc2);
                writer.AddDocument(testDoc3);
                writer.AddDocument(testDoc4);
                writer.Close();
                IndexSearcher knownSearcher = new IndexSearcher(dir);
                TermEnum      termEnum      = knownSearcher.reader.Terms();
                TermDocs      termDocs      = knownSearcher.reader.TermDocs();
                //System.out.println("Terms: " + termEnum.size() + " Orig Len: " + termArray.length);

                Similarity sim = knownSearcher.GetSimilarity();
                while (termEnum.Next() == true)
                {
                    Term term = termEnum.Term();
                    //System.out.println("Term: " + term);
                    termDocs.Seek(term);
                    while (termDocs.Next())
                    {
                        int docId = termDocs.Doc();
                        int freq  = termDocs.Freq();
                        //System.out.println("Doc Id: " + docId + " freq " + freq);
                        TermFreqVector vector = knownSearcher.reader.GetTermFreqVector(docId, "Field");
                        float          tf     = sim.Tf(freq);
                        float          idf    = sim.Idf(term, knownSearcher);
                        //float qNorm = sim.queryNorm()
                        //This is fine since we don't have stop words
                        float lNorm = sim.LengthNorm("Field", vector.GetTerms().Length);
                        //float coord = sim.coord()
                        //System.out.println("TF: " + tf + " IDF: " + idf + " LenNorm: " + lNorm);
                        Assert.IsTrue(vector != null);
                        System.String[] vTerms = vector.GetTerms();
                        int[]           freqs  = vector.GetTermFrequencies();
                        for (int i = 0; i < vTerms.Length; i++)
                        {
                            if (term.Text().Equals(vTerms[i]) == true)
                            {
                                Assert.IsTrue(freqs[i] == freq);
                            }
                        }
                    }
                    //System.out.println("--------");
                }
                Query query = new TermQuery(new Term("Field", "chocolate"));
                Hits  hits  = knownSearcher.Search(query);
                //doc 3 should be the first hit b/c it is the shortest match
                Assert.IsTrue(hits.Length() == 3);
                float score = hits.Score(0);

                /*System.out.println("Hit 0: " + hits.id(0) + " Score: " + hits.score(0) + " String: " + hits.doc(0).toString());
                 * System.out.println("Explain: " + knownSearcher.explain(query, hits.id(0)));
                 * System.out.println("Hit 1: " + hits.id(1) + " Score: " + hits.score(1) + " String: " + hits.doc(1).toString());
                 * System.out.println("Explain: " + knownSearcher.explain(query, hits.id(1)));
                 * System.out.println("Hit 2: " + hits.id(2) + " Score: " + hits.score(2) + " String: " +  hits.doc(2).toString());
                 * System.out.println("Explain: " + knownSearcher.explain(query, hits.id(2)));*/
                Assert.IsTrue(testDoc3.ToString().Equals(hits.Doc(0).ToString()));
                Assert.IsTrue(testDoc4.ToString().Equals(hits.Doc(1).ToString()));
                Assert.IsTrue(testDoc1.ToString().Equals(hits.Doc(2).ToString()));
                TermFreqVector vector2 = knownSearcher.reader.GetTermFreqVector(hits.Id(1), "Field");
                Assert.IsTrue(vector2 != null);
                //System.out.println("Vector: " + vector);
                System.String[] terms  = vector2.GetTerms();
                int[]           freqs2 = vector2.GetTermFrequencies();
                Assert.IsTrue(terms != null && terms.Length == 10);
                for (int i = 0; i < terms.Length; i++)
                {
                    System.String term = terms[i];
                    //System.out.println("Term: " + term);
                    int freq = freqs2[i];
                    Assert.IsTrue(test4.IndexOf(term) != -1);
                    System.Int32  freqInt    = (System.Int32)test4Map[term];
                    System.Object tmpFreqInt = test4Map[term];
                    Assert.IsTrue(tmpFreqInt != null);
                    Assert.IsTrue(freqInt == freq);
                }
                knownSearcher.Close();
            }
            catch (System.IO.IOException e)
            {
                System.Console.Error.WriteLine(e.StackTrace);
                Assert.IsTrue(false);
            }
        }
コード例 #3
0
 public override float LengthNorm(System.String fieldName, int numTerms)
 {
     return(delegee.LengthNorm(fieldName, numTerms));
 }