package LBJ2.classify;
import LBJ2.learn.Lexicon;
import LBJ2.util.ByteString;
import LBJ2.util.ExceptionlessInputStream;
import LBJ2.util.ExceptionlessOutputStream;
/**
* A primitive discrete feature is a discrete feature with a string value.
*
* @author Nick Rizzolo
**/
public class DiscretePrimitiveFeature extends DiscreteFeature
{
/**
* The <code>identifier</code> string distinguishes this
* <code>Feature</code> from other <code>Feature</code>s.
**/
protected ByteString identifier;
/** The discrete value is represented as a string. */
protected ByteString value;
/**
* For internal use only.
*
* @see Feature#readFeature(ExceptionlessInputStream)
**/
protected DiscretePrimitiveFeature() { }
/**
* Sets both the identifier and the value. The value index and total
* allowable values, having not been specified, default to -1 and 0
* respectively.
*
* @param p The new discrete feature's package.
* @param c The name of the classifier that produced this feature.
* @param i The new discrete feature's identifier.
* @param v The new discrete feature's value.
**/
public DiscretePrimitiveFeature(String p, String c, ByteString i,
ByteString v) {
this(p, c, i, v, (short) -1, (short) 0);
}
/**
* Sets the identifier, value, value index, and total allowable values.
*
* @param p The new discrete feature's package.
* @param c The name of the classifier that produced this feature.
* @param i The new discrete feature's identifier.
* @param v The new discrete feature's value.
* @param vi The index corresponding to the value.
* @param t The total allowable values for this feature.
**/
public DiscretePrimitiveFeature(String p, String c, ByteString i,
ByteString v, short vi, short t) {
super(p, c, vi, t);
identifier = i;
value = v;
}
/**
* Determines if this feature contains a byte string identifier field.
*
* @return <code>true</code> iff this feature contains a byte string
* identifier field.
**/
public boolean hasByteStringIdentifier() { return true; }
/**
* Determines if this feature is primitive.
*
* @return <code>true</code> iff this is primitive.
**/
public boolean isPrimitive() { return true; }
/**
* Retrieves this feature's identifier as a string.
*
* @return This feature's identifier as a string.
**/
public String getStringIdentifier() { return identifier.toString(); }
/**
* Retrieves this feature's identifier as a byte string.
*
* @return This feature's identifier as a byte string.
**/
public ByteString getByteStringIdentifier() {
return (ByteString) identifier.clone();
}
/**
* Gives a string representation of the value of this feature.
*
* @return The string decoding of {@link #value}.
**/
public String getStringValue() { return value.toString(); }
/**
* Gives a string representation of the value of this feature.
*
* @return A clone of {@link #value}.
**/
public ByteString getByteStringValue() {
return (ByteString) value.clone();
}
/**
* Determines whether or not the parameter is equivalent to the string
* representation of the value of this feature.
*
* @param v The string to compare against.
* @return <code>true</code> iff the parameter is equivalent to the string
* representation of the value of this feature.
**/
public boolean valueEquals(String v) { return value.equals(v); }
/**
* Return the feature that should be used to index this feature into a
* lexicon. If it is a binary feature, we return the feature with an empty
* value so that the feature will be mapped to the same weight whether it
* is active or not. If the feature can take multiple values, then simply
* return the feature object as-is.
*
* @param lexicon The lexicon into which this feature will be indexed.
* @param training Whether or not the learner is currently training.
* @param label The label of the example containing this feature, or -1
* if we aren't doing per class feature counting.
* @return A feature object appropriate for use as the key of a map.
**/
public Feature getFeatureKey(Lexicon lexicon, boolean training, int label) {
if (totalValues() == 2)
return
new DiscretePrimitiveFeature(
containingPackage, generatingClassifier, identifier,
ByteString.emptyString, (short) -1, (short) 2);
return this;
}
/**
* Returns a {@link RealPrimitiveFeature} whose
* {@link RealPrimitiveFeature#value value} field is set to the strength of
* the current feature, and whose {@link #identifier} field contains all
* the information necessary to distinguish this feature from other
* features.
**/
public RealFeature makeReal() {
if (totalValues == 2)
return
new RealPrimitiveFeature(containingPackage, generatingClassifier,
identifier, valueIndex);
else {
ByteString id = (ByteString) identifier.clone();
ByteString[] toAppend =
{ new ByteString("_", id.getEncoding()), value };
id.append(toAppend);
return
new RealPrimitiveFeature(containingPackage, generatingClassifier, id,
1);
}
}
/**
* Returns a new feature object that's identical to this feature except its
* strength is given by <code>s</code>.
*
* @param s The strength of the new feature.
* @return A new feature object as above, or <code>null</code> if this
* feature cannot take the specified strength.
**/
public Feature withStrength(double s) {
if (totalValues != 2 || !(s == 0 || s == 1)) return null;
return
new DiscretePrimitiveFeature(
containingPackage, generatingClassifier, identifier,
ByteString.emptyString, (short) Math.round(s), (short) 2);
}
/**
* Returns a feature object in which any strings that are being used to
* represent an identifier or value have been encoded in byte strings.
*
* @param e The encoding to use.
* @return A feature object as above; possible this object.
**/
public Feature encode(String e) { return this; }
/**
* The hash code of a <code>DiscretePrimitiveFeature</code> is the sum of
* the hash codes of its containing package, identifier, and value.
*
* @return The hash code of this feature.
**/
public int hashCode() {
return 31 * super.hashCode() + 17 * identifier.hashCode()
+ value.hashCode();
}
/**
* Two <code>DiscretePrimitive(String)Feature</code>s are equivalent when
* their containing packages, identifiers, and values are equivalent.
*
* @param o The object with which to compare this feature.
* @return <code>true</code> iff the parameter is an equivalent feature.
**/
public boolean equals(Object o) {
if (!super.equals(o)) return false;
if (o instanceof DiscretePrimitiveFeature) {
DiscretePrimitiveFeature f = (DiscretePrimitiveFeature) o;
return identifier.equals(f.identifier)
&& valueIndex > -1 ? valueIndex == f.valueIndex
: value.equals(f.value);
}
DiscretePrimitiveStringFeature f = (DiscretePrimitiveStringFeature) o;
return identifier.equals(f.identifier)
&& valueIndex > -1 ? valueIndex == f.valueIndex
: value.equals(f.value);
}
/**
* Some features are functionally equivalent, differing only in the
* encoding of their values; this method will return <code>true</code> iff
* the class of this feature and <code>f</code> are different, but they
* differ only because they encode their values differently. This method
* does not compare the values themselves, however.
*
* @param f Another feature.
* @return See above.
**/
public boolean classEquivalent(Feature f) {
return f instanceof DiscretePrimitiveStringFeature;
}
/**
* Used to sort features into an order that is convenient both to page
* through and for the lexicon to read off disk.
*
* @param o An object to compare with.
* @return Integers appropriate for sorting features first by package, then
* by identifier, then by value.
**/
public int compareTo(Object o) {
int d = compareNameStrings(o);
if (d != 0) return d;
DiscretePrimitiveFeature f = (DiscretePrimitiveFeature) o;
d = identifier.compareTo(f.identifier);
if (d != 0) return d;
return value.compareTo(f.value);
}
/**
* Writes a string representation of this <code>Feature</code> to the
* specified buffer.
*
* @param buffer The buffer to write to.
**/
public void write(StringBuffer buffer) {
writeNameString(buffer);
buffer.append("(");
buffer.append(value.toString());
buffer.append(")");
}
/**
* Writes a string representation of this <code>Feature</code>'s package,
* generating classifier, and identifier information to the specified
* buffer.
*
* @param buffer The buffer to write to.
**/
public void writeNameString(StringBuffer buffer) {
super.writeNameString(buffer);
buffer.append(":");
buffer.append(identifier.toString());
}
/**
* Writes a complete binary representation of the feature.
*
* @param out The output stream.
**/
public void write(ExceptionlessOutputStream out) {
super.write(out);
identifier.write(out);
value.write(out);
}
/**
* Reads the representation of a feaeture with this object's run-time type
* from the given stream, overwriting the data in this object.
*
* @param in The input stream.
**/
public void read(ExceptionlessInputStream in) {
super.read(in);
identifier = ByteString.readByteString(in);
value = ByteString.readByteString(in);
}
/**
* Writes a binary representation of the feature intended for use by a
* lexicon, omitting redundant information when possible.
*
* @param out The output stream.
* @param lex The lexicon out of which this feature is being written.
* @param c The fully qualified name of the assumed class. The runtime
* class of this feature won't be written if it's equivalent to
* <code>c</code>.
* @param p The assumed package string. This feature's package string
* won't be written if it's equivalent to <code>p</code>.
* @param g The assumed classifier name string. This feature's
* classifier name string won't be written if it's equivalent
* to <code>g</code>.
* @param si The assumed identifier as a string. If this feature has a
* string identifier, it won't be written if it's equivalent to
* <code>si</code>.
* @param bi The assumed identifier as a byte string. If this feature
* has a byte string identifier, it won't be written if it's
* equivalent to <code>bi</code>.
* @return The name of the runtime type of this feature.
**/
public String lexWrite(ExceptionlessOutputStream out, Lexicon lex, String c,
String p, String g, String si, ByteString bi) {
String result = super.lexWrite(out, lex, c, p, g, si, bi);
identifier.lexWrite(out, bi);
// This method does not have an "assumed value" parameter because we don't
// expect the value of the current feature to be the same as the value of
// the previous feature very often. However, it should always be the case
// that the identifier and value of this feature have the same encoding.
// So, the line below uses the identifier as the "assumed value".
value.lexWrite(out, identifier);
return result;
}
/**
* Reads the representation of a feature with this object's run-time type
* as stored by a lexicon, overwriting the data in this object.
*
* <p> This method is appropriate for reading features as written by
* {@link #lexWrite(ExceptionlessOutputStream,Lexicon,String,String,String,String,ByteString)}.
*
* @param in The input stream.
* @param lex The lexicon we are reading in to.
* @param p The assumed package string. If no package name is given in
* the input stream, the instantiated feature is given this
* package.
* @param g The assumed classifier name string. If no classifier name
* is given in the input stream, the instantiated feature is
* given this classifier name.
* @param si The assumed identifier as a string. If the feature being
* read has a string identifier field and no identifier is
* given in the input stream, the feature is given this
* identifier.
* @param bi The assumed identifier as a byte string. If the feature
* being read has a byte string identifier field and no
* identifier is given in the input stream, the feature is
* given this identifier.
**/
public void lexRead(ExceptionlessInputStream in, Lexicon lex, String p,
String g, String si, ByteString bi) {
super.lexRead(in, lex, p, g, si, bi);
identifier = ByteString.lexReadByteString(in, bi);
value = ByteString.lexReadByteString(in, identifier);
}
}