opennlp.tools.ml.model.UniformPrior Maven / Gradle / Ivy
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package opennlp.tools.ml.model;
import java.util.Objects;
/**
* Provide a maximum entropy model with a uniform prior.
*/
public class UniformPrior implements Prior {
private int numOutcomes;
private double r;
public void logPrior(double[] dist, int[] context, float[] values) {
for (int oi = 0; oi < numOutcomes; oi++) {
dist[oi] = r;
}
}
@Override
public void logPrior(double[] dist, Context[] context, float[] values) {
logPrior(dist, (int[]) null, values);
}
public void logPrior(double[] dist, int[] context) {
logPrior(dist,context,null);
}
public void setLabels(String[] outcomeLabels, String[] contextLabels) {
this.numOutcomes = outcomeLabels.length;
r = Math.log(1.0 / numOutcomes);
}
@Override
public int hashCode() {
return Objects.hash(numOutcomes, r);
}
@Override
public boolean equals(Object obj) {
if (obj == this) {
return true;
}
if (obj instanceof UniformPrior) {
UniformPrior prior = (UniformPrior) obj;
return numOutcomes == prior.numOutcomes && r == prior.r;
}
return false;
}
}