Similarity
or DefaultSimilarity
instead.@Deprecated public class SimilarityDelegator extends Similarity
Query.getSimilarity(Searcher)
implementations, to override only certain
methods of a Searcher's Similarity implementation..NO_DOC_ID_PROVIDED
Constructor and Description 

SimilarityDelegator(Similarity delegee)
Deprecated.
Construct a
Similarity that delegates all methods to another. 
Modifier and Type  Method and Description 

float 
computeNorm(String fieldName,
FieldInvertState state)
Deprecated.
Computes the normalization value for a field, given the accumulated
state of term processing for this field (see
FieldInvertState ). 
float 
coord(int overlap,
int maxOverlap)
Deprecated.
Computes a score factor based on the fraction of all query terms that a
document contains.

float 
idf(int docFreq,
int numDocs)
Deprecated.
Computes a score factor based on a term's document frequency (the number
of documents which contain the term).

float 
queryNorm(float sumOfSquaredWeights)
Deprecated.
Computes the normalization value for a query given the sum of the squared
weights of each of the query terms.

float 
scorePayload(int docId,
String fieldName,
int start,
int end,
byte[] payload,
int offset,
int length)
Deprecated.
Calculate a scoring factor based on the data in the payload.

float 
sloppyFreq(int distance)
Deprecated.
Computes the amount of a sloppy phrase match, based on an edit distance.

float 
tf(float freq)
Deprecated.
Computes a score factor based on a term or phrase's frequency in a
document.

decodeNorm, decodeNormValue, encodeNorm, encodeNormValue, getDefault, getNormDecoder, idfExplain, idfExplain, idfExplain, lengthNorm, setDefault, tf
public SimilarityDelegator(Similarity delegee)
Similarity
that delegates all methods to another.delegee
 the Similarity implementation to delegate topublic float computeNorm(String fieldName, FieldInvertState state)
Similarity
FieldInvertState
).
Implementations should calculate a float value based on the field state and then return that value.
Matches in longer fields are less precise, so implementations of this
method usually return smaller values when state.getLength()
is large,
and larger values when state.getLength()
is small.
Note that the return values are computed under
IndexWriter.addDocument(org.apache.lucene.document.Document)
and then stored using
Similarity.encodeNormValue(float)
.
Thus they have limited precision, and documents
must be reindexed if this method is altered.
For backward compatibility this method by default calls
Similarity.lengthNorm(String, int)
passing
FieldInvertState.getLength()
as the second argument, and
then multiplies this value by FieldInvertState.getBoost()
.
computeNorm
in class Similarity
fieldName
 field namestate
 current processing state for this fieldpublic float queryNorm(float sumOfSquaredWeights)
Similarity
This does not affect ranking, but the default implementation does make scores from different queries more comparable than they would be by eliminating the magnitude of the Query vector as a factor in the score.
queryNorm
in class Similarity
sumOfSquaredWeights
 the sum of the squares of query term weightspublic float tf(float freq)
Similarity
Similarity.idf(int, int)
factor for each term in the query and these products are then summed to
form the initial score for a document.
Terms and phrases repeated in a document indicate the topic of the
document, so implementations of this method usually return larger values
when freq
is large, and smaller values when freq
is small.
tf
in class Similarity
freq
 the frequency of a term within a documentpublic float sloppyFreq(int distance)
Similarity
Similarity.tf(float)
.
A phrase match with a small edit distance to a document passage more closely matches the document, so implementations of this method usually return larger values when the edit distance is small and smaller values when it is large.
sloppyFreq
in class Similarity
distance
 the edit distance of this sloppy phrase matchPhraseQuery.setSlop(int)
public float idf(int docFreq, int numDocs)
Similarity
Similarity.tf(int)
factor for each term in the query and these products are
then summed to form the initial score for a document.
Terms that occur in fewer documents are better indicators of topic, so implementations of this method usually return larger values for rare terms, and smaller values for common terms.
idf
in class Similarity
docFreq
 the number of documents which contain the termnumDocs
 the total number of documents in the collectionpublic float coord(int overlap, int maxOverlap)
Similarity
The presence of a large portion of the query terms indicates a better match with the query, so implementations of this method usually return larger values when the ratio between these parameters is large and smaller values when the ratio between them is small.
coord
in class Similarity
overlap
 the number of query terms matched in the documentmaxOverlap
 the total number of terms in the querypublic float scorePayload(int docId, String fieldName, int start, int end, byte[] payload, int offset, int length)
Similarity
The default implementation returns 1.
scorePayload
in class Similarity
docId
 The docId currently being scored. If this value is Similarity.NO_DOC_ID_PROVIDED
, then it should be assumed that the PayloadQuery implementation does not provide document informationfieldName
 The fieldName of the term this payload belongs tostart
 The start position of the payloadend
 The end position of the payloadpayload
 The payload byte array to be scoredoffset
 The offset into the payload arraylength
 The length in the array